Springer Protocols Methods and Protocols

Springer Protocols

Biological Microarrays Methods and Protocols

Edited by

Ali Khademhosseini Kahp-Yang Suh Mohammed Zourob

Methods

in

Molecular Biology™

Series Editor John M. Walker School of Life Sciences University of Hertfordshire Hatfield, Hertfordshire, AL10 9AB, UK

For other titles published in this series, go to www.springer.com/series/7651

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Biological Microarrays Methods and Protocols

Edited by

Ali Khademhosseini Department of Medicine, MIT Division of Health Sciences and Tech, Harvard Medical School, Cambridge, MA, USA

Kahp-Yang Suh Department of Mechanical and Aerospace E, Seoul National University, Kwanak-gu, Shinlim-dong 56-1-1, 151-742, Seoul, Korea, Republic of (South Korea) Gwanak-ro 599, Gwanak-gu, Seoul 151-742, Republic of Korea

Mohammed Zourob Biophage Pharma, Montreal, QC, Canada

Editors Prof. Dr. Ali Khademhosseini Department of Medicine MIT Division of Health Sciences and Tech Harvard Medical School Cambridge, MA USA [email protected]

Dr. Mohammed Zourob Biophage Pharma Montreal, QC Canada [email protected]

Kahp-Yang Suh Department of Mechanical and Aerospace E Seoul National University Kwanak-gu, Shinlim-dong 56-1-1, 151-742 Seoul, Korea, Republic of (South Korea) Gwanak-ro 599, Gwanak-gu, Seoul 151-742, Republic of Korea [email protected]

ISSN 1064-3745 e-ISSN 1940-6029 ISBN 978-1-934115-95-4 e-ISBN 978-1-59745-551-0 DOI 10.1007/978-1-59745-551-0 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2010938723 © Springer Science+Business Media, LLC 2011 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Humana Press, c/o Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of going to press, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Humana Press is part of Springer Science+Business Media (www.springer.com)

Preface Microarrays are spatially ordered arrays with ligands chemically immobilized in discrete spots on a solid matrix, usually a microscope slide. Microarrays are a high-throughput large-scale screening system enabling simultaneous identification of a large number of target molecules (up to several hundred thousand) that bind specifically to the immobilized ligands of the array. Microarrays represent a promising tool for clinical, environmental, and industrial microbiology since the technology allows relatively rapid screening and identification of large number of specific analytes or genetic determinants simultaneously. The successful use of microarrays requires attention to unique issues of experimental design and execution. This book provides an overview of the methodology and applications of biological microarrays in various areas of biological and biomedical research. This book presents a significant and up-to-date review of the various biological microarrays, recognition elements, their immobilization, characterization techniques by a panel of distinguished scientists. This work is a comprehensive approach to the biological microarrays area presenting a thorough knowledge of the subject and an effective integration of these biological entities on microarray surfaces in order to appropriately convey the state-of-the-art fundamentals and applications of the most innovative approaches. This book comprises of 18 chapters written by 50 researchers actively working in USA, Canada, Germany, Spain, Korea, China, and the UK. The authors were requested to adopt a pedagogical tone in order to accommodate the needs of novice researchers such as graduate students and post-doctoral scholars as well as of established researchers seeking new avenues. This has resulted in duplication of some material, which we have chosen to retain, because we know that many readers will pick only a specific chapter to read at a certain time. We have divided this book into two major sections. The first part (Chaps. 1–9) comprises nine chapters, which are devoted to the application of biological microarrays including DNA/RNA, apatmer, proteins, tissues, oligonucleotides, carbohydrates, biomaterials, cells, bacteria, and virus microarrays. The second part (Chaps. 10–18) describes in detail the different techniques used for generating the microarray platforms. The second part divided into four subsections including photolithography (microfluidic-based approaches and cells and proteins patterns using photolithography), bioprinting (microspotters, microprinting), soft lithography (microcontact, micromolding, microstructure surface based on chemical vapor deposition, permeability of microvascular tubes), and microarray bioinformatics. It covers the theory behind each technique and delivers a detailed state-ofthe-art review for all the new technologies used. This book is intended to be a primary source both on fundamental and practical information of where the biological microarray area is now and where it is headed in the future. We anticipate that the book will be helpful to academics, practitioners and professionals working in various fields to name a few biologist, biotechnologists, biochemists, analytical chemists, biomedical, physical, microsystems engineering, nanotechnology, medicine, food, bioterrorism and security as well as allied health, health care, and surveillance. Since

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Preface

the fundamentals were also reviewed, we believe that the book will appeal to advanced undergraduate and graduate students who study in areas related to biological microarrays and biosensors. We gratefully acknowledge all authors for their participation and contributions, which made this book a reality. We give many thanks to Prof. John M. Walker for his guidance and patience. Last, but not least, we thank our families for their patience and enthusiastic support of this project.

Cambridge, MA Seoul, Korea Montreal, QC

Ali Khademhosseini Kahp-Yang Suh Mohammed Zourob

Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

v ix

Part I Application of Biological Microarray 1 RNA and DNA Microarrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stuart C. Sealfon and Tearina T. Chu 2 Aptamer Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Eva Baldrich 3 Oligonucleotide Microarrays for Identification of Microbial Pathogens and Detection of Their Virulence-Associated or Drug-Resistance Determinants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dmitriy V. Volokhov, Hyesuk Kong, Keith Herold, Vladimir E. Chizhikov, and Avraham Rasooly 4 Protein Microarrays Printed from DNA Microarrays . . . . . . . . . . . . . . . . . . . . . . Oda Stoevesandt, Mingyue He, and Michael J. Taussig 5 Lithographically Defined Two- and Three-Dimensional Tissue Microarrays . . . . . Esther W. Gomez and Celeste M. Nelson 6 Ratiometric Lectin Microarray Analysis of the Mammalian Cell Surface Glycome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ku-Lung Hsu, Kanoelani Pilobello, Lakshmipriya Krishnamoorthy, and Lara K. Mahal 7 Cell Microarrays Based on Hydrogel Microstructures for the Application to Cell-Based Biosensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Won-Gun Koh 8 Fabrication of Bacteria and Virus Microarrays Based on Polymeric Capillary Force Lithography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pil J. Yoo 9 3D Polymer Scaffold Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Carl G. Simon Jr., Yanyin Yang, Shauna M. Dorsey, Murugan Ramalingam, and Kaushik Chatterjee

3 35

55

95 107

117

133

147 161

Part II Methods for Microarray Generation 10 PDMS Microfluidic Capillary Systems for Patterning Proteins on Surfaces and Performing Miniaturized Immunoassays . . . . . . . . . . . . . . . . . . . 177 Mateu Pla-Roca and David Juncker 11 Merging Photolithography and Robotic Protein Printing to Create Cellular Microarrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 Ji Youn Lee and Alexander Revzin

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12 Generation of Protein and Cell Microarrays on Functionalized Surfaces . . . . . . . . Yoo Seong Choi and Chang-Soo Lee 13 Microprinting of Liver Micro-organ for Drug Metabolism Study . . . . . . . . . . . . . Robert C. Chang, Kamal Emami, Antony Jeevarajan, Honglu Wu, and Wei Sun 14 Microcontact Printing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yunyan Xie and Xingyu Jiang 15 Micromolding for the Fabrication of Biological Microarrays . . . . . . . . . . . . . . . . . Ashley L. Galloway, Andrew Murphy, Jason P. Rolland, Kevin P. Herlihy, Robby A. Petros, Mary E. Napier, and Joseph M. DeSimone 16 Progress Report on Microstructured Surfaces Based on Chemical Vapor Deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yaseen Elkasabi and Joerg Lahann 17 Methods for Forming Human Microvascular Tubes In Vitro and Measuring Their Macromolecular Permeability . . . . . . . . . . . . . . . . . . . . . . . Gavrielle M. Price and Joe Tien 18 Microarray Bioinformatics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Robert P. Loewe and Peter J. Nelson

207 219

239 249

261

281 295

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321

Contributors Eva Baldrich • Instituto de Microelectrónica de Barcelona (IMB-CNM), Barcelona, Spain Robert C. Chang • Department of Mechanical Engineering and Mechanics, Drexel University, Philadelphia, PA, USA Kaushik Chatterjee • Polymers Division, National Institute of Standards and Technology, Gaithersburg, MD, USA Vladimir E. Chizhikov • Center for Biologics Evaluation and Research, Food and Drug Administration, Kensington, MD, USA Yoo Seong Choi • Department of Chemical Engineering, Pohang University of Science and Technology, Pohang, Korea Tearina T. Chu • Departments of Pharmacology and Systems Therapeutics, Mount Sinai School of Medicine, New York, NY, USA Joseph M. DeSimone • North Carolina State University, Raleigh, NC, USA Shauna M. Dorsey • Polymers Division, National Institute of Standard sand Technology, Gaithersburg, MD, USA Yaseen Elkasabi • Material Science and Engineering, University of Michigan, Ann Arbor, MI, USA Kamal Emami • Radiation Physics Laboratory, NASA Johnson Space Center, Houston, TX, USA Ashley L. Galloway • Liquidia Technologies Research, Triangle Park, NC, USA Esther W. Gomez • Departments of Chemical Engineering and Molecular Biology, Princeton University, Princeton, NJ, USA Mingyue He • The Babraham Institute, Cambridge, UK Kevin P. Herlihy • Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Keith Herold • Department of Bioengineering, University of Maryland, College Park, MD, USA Ku-Lung Hsu • Department of Chemistry and Biochemistry, University of Texas at Austin, Austin, TX, USA Antony Jeevarajan • Radiation Physics Laboratory, NASA Johnson Space Center, Houston, TX, USA Xingyu Jiang • National Center for NanoScience & Technology, Beijing, China David Junker • Bio-Medical Engineering Department, McGill University, Montreal, QC, Canada Won-Gun Koh • Department of Chemical and Biological Engineering, Yonsei University, Seoul, Korea Hyesuk Kong • Center for Biologics Evaluation and Research, Food and Drug Administration, Kensington, MD, USA

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Contributors

Lakshmipriya Krishnamoorthy • Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX, USA Joerg Lahann • University of Michigan, Ann Arbor, MI, USA Chang-Soo Lee • Department of Chemical and Biological Engineering, Chungnam National University, Daejeon, Korea Ji Youn Lee • Department of Biomedical Engineering, University of California, Davis, CA, USA Robert P. Loewe • Medical Policlinic, Ludwig Maximillians, University of Munich, Munich, Germany Lara K. Mahal • Chemistry and Biochemistry Department, The University of Texas at Austin, Austin, TX, USA Andrew Murphy • Liquidia Technologies Research, Triangle Park, NC, USA Mary E. Napier • Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill NC, USA Celeste M. Nelson • Department of Chemical Engineering, Princeton University, Princeton, NJ, USA Peter J. Nelson • Medical Policlinic, Ludwig Maximillians, University of Munich, Munich, Germany Robby A. Petros • Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Kanoelani Pilobello • Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX, USA Gavrielle M. Price • Department of Biomedical Engineering, Boston University, Boston, MA, USA Murugan Ramalingam • Polymers Division, National Institute of Standards and Technology, Gaithersburg, MD, USA Avraham Rasooly • National Institutes of Health, National Cancer Institute, FDA, Bethesda, MD, USA Alexander Revzın • Department of Biomedical Engineering, University of California, Davis, CA, USA Jason P. Rolland • Liquidia Technologies Research, Triangle Park, NC, USA Stuart C. Sealfon • Neurology, Mount Sinai School of Medicine, New York, NY, USA Oda Stoevesandt • Babraham Bioscience Technologies, Cambridge, UK Wei Sun • Department of Mechanical Engineering and Mechanics, Drexel University, Philadelphia, PA, USA Joe Tien • Department of Biomedical Engineering, Boston University, Boston, MA, USA Dmitriy V. Volokhov • Center for Biologics Evaluation and Research, Food and Drug Administration, Kensington, MD, USA Honglu Wu • Radiation Physics Laboratory, NASA Johnson Space Center, Houston, TX, USA Yunyan Xie • National Center for NanoScience & Technology, Beijing, China Yanyin Yang • Polymers Division, National Institute of Standards and Technology, Gaithersburg, MD, USA

Contributors

xi

Pil J. Yoo • Chemical Engineering, Sungkyunkwan University, Seoul, Korea Michael J. Taussig • Babraham Bioscience Technologies, Cambridge,UK Carl G.Simon Jr • Polymers Division,National Institute of Standards and Technology, Gaithersburg, MD, USA Mateu Pla-Roca • Bio-Medical Engineering Department, McGill University, Montreal, QC, Canada

Part I Application of Biological Microarray

Chapter 1 RNA and DNA Microarrays Stuart C. Sealfon and Tearina T. Chu Abstract The development of microarray technology has revolutionized RNA and deoxyribonucleic acid (DNA) research. In contrast with traditional biological assays, microarrays allow the simultaneous measurement of tens of thousands of messenger RNA (mRNA) transcripts for gene expression or of genomic DNA fragments for copy number variation analysis. Over the past decade, genome-wide RNA or DNA microarray analysis has become an essential component of biology and biomedical research. The successful use of microarrays requires attention to unique issues of experimental design and execution. This chapter provides an overview of the methodology and applications of RNA and DNA microarrays in various areas of biological research. Key words: RNA, DNA, Expression, Comparative genomic hybridization, cDNA, BAC, Microarray, Copy number variation, Transcripts

1. Introduction Deoxyribonucleic acid (DNA) carries the hereditary information content of the genome, which is organized into discrete functional genes that regulate and encode individual RNAs. Genome size varies in organisms ranging from bacteria containing 1–5 million bases and 1,000–3,000 genes (1) to humans containing three billion bases and 20,000–25,000 protein-coding genes. Genes encoding protein are dynamically regulated and produce messenger RNA (mRNA) that are translated into protein. The human genome also contains thousands of nonprotein encoding RNA genes and large areas of regulatory and noncoding sequence (2). Measuring mRNAs indicate the level of gene activity and provide a snapshot of the biosynthetic state of the cell or tissue. The expression level of each gene can be influenced by a combination of genetic or environmental factors. The genetic factors include Ali Khademhosseini et al. (eds.), Biological Microarrays: Methods and Protocols, Methods in Molecular Biology, vol. 671, DOI 10.1007/978-1-59745-551-0_1, © Springer Science+Business Media, LLC 2011

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DNA polymorphisms in the regulatory regions of genes (such as the promoter/enhancer regions), and variations in the number of copies of the gene [copy number variation (CNV)]. Environment factors such as temperature, stress, nutrition, or exercise can lead to changes in extracellular hormones or intracellular signaling molecules that influence the expression level of genes. The expression levels of the genes of a cell determine the cell type, developmental stage, cell functions, and/or pathological state. However, it must be noted that the measurement of mRNA levels provides an imperfect reflection of protein levels and activity. The concentration of a particular protein is controlled not only by the level of its mRNA, but also by the rate of mRNA translation into protein and of protein degradation. Other modifications of protein, such as phosphorylation, are also important determinants of activity. With these limitations in mind, measurement of global mRNA expression provides insight into the overall level of gene activity and protein expression. Many human diseases involve altered gene expression (3). Small genomic deletions and duplications (1 kb to 10 Mb) constitute up to 15% of all mutations underlying human monogenic diseases (4). Thus, the study of small regions of chromosomal variation provides insight into the pathogenesis of many diseases. Changes in gene expression can arise from polymorphisms, deletions, or insertions in protein coding or regulatory sequences of DNA. Changes in gene expression can also arise from altered regulation of mRNA production in response to various signaling mechanisms or stimuli. In contrast with classical Mendelian genetics involving hereditable defects of a single gene locus, many diseases are polygenetic and have clusters of genes that may contribute to the pathological state (5–11). Microarray techniques that allow detection of small regions of DNA deletions or duplications play an important role in mapping diseases with a complex hereditary etiology. Microarray technology was first introduced in 1995 by Patrick Brown and colleagues (12). The first microarray was generated using complementary DNAs (cDNA) derived from polymerase chain reaction (PCR) products. The array was printed using a home-made robot and was used to measure the gene expression patterns in parallel of 48 Arabidopsis thaliana genes. Advances in microarray technology and the decoding of the human genome (13–15) as well as the genome of many other species (16–20), now make it feasible to assay simultaneously the expression level of tens of thousands of mRNA transcripts. We use the term RNA microarrays to refer to arrays used to measure RNA levels, whereas DNA microarrays measure DNA sequence or levels. RNA microarrays have been widely used to identify regulated genes, pathways, or gene networks in a variety of cells and tissues when two or more related biological conditions are compared.

RNA and DNA Microarrays

5

These approaches provide insight into biological mechanisms or cellular programs such as cell cycle progression (21–23), embryonic development (24–26), cell fate determination (27, 28), hormone responsive gene regulation programs (29–31), and drug or disease model -mediated gene expression changes (32–35). Microarrays have also been widely to define disease-associated gene regulation, gene expression patterns in disease subtypes, and gene biomarkers of various disease states such as cancers (36–40), infectious diseases (41–43), inflammatory disease (44, 45), neurological diseases (46–48), and psychiatric disorders (32, 49–51). In addition, microarray approach has been used in pharmacogenomic/ toxicogenomic studies for drug discovery, and for determining the mechanisms of therapeutic or side effects of specific drugs (35, 52–55). In the development of many human diseases, for example tumors, chromosomal damage leads to gain or loss of genomic material (4, 56–58). Comparative genomic hybridization (CGH) allows the study of the entire genome for variations in DNA copy number. Originally, metaphase chromosomes were used to represent the genome (59). This approach has limited resolution (~5–10 Mb for single copy gains and losses) and is technically difficult in requiring optimal chromosome metaphase spreads. Array-CGH (aCGH) circumvents some of these technical difficulties, and offers higher resolution (~1–100 kb intermarker spacing). This technique is useful for the detection of deletions or duplications of chromosomal regions or gene CNV in a comparison between individuals with altered disease states (60–62). Microarrays are important in cancer biology in identifying new tumor subtypes and prognostic groups. For example, breast cancer is a heterogeneous disease comprising many biological subtypes. After diagnosis, 30–40% of patients will develop metastases and die of the disease within 15 years. The selection of adjuvant chemotherapy is currently based on prognostic and predictive factors including age, tumor size, histological grade, hormone receptor status, Her2/neu status, menopausal status, and lymph node status (63, 64). Although these “classical” factors are effective based on general population statistics, they poorly predict the outcome for the individual patient because of the heterogeneity of this disease. Using RNA microarrays, Perou et al. was the first to divide breast carcinomas into distinct subtypes, based on the unique gene expression patterns of a subgroup of genes, called the “gene set” or “gene signature” (37). In a follow-up study, this gene set was used to predict the prognosis of 78 breast carcinoma patients (40). Using similar approaches, other workers have developed gene sets to predict the development of metastases and the prognosis of different groups (65–68). Microarrays have also been used to predict response to therapy (69–71). Using a DNA CGH microarray, Gonzalez-Neira et al. identified a genetic

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classifier based on specific somatic genetic aberration of regions on chromosome 3p, 3q, and 5q to differentiate BRCA1 (breast cancer risk gene) mutation carriers from nonBRCA1 carriers of breast cancer patients (72). In a similar manner, array-CGH technology has been used in the characterization of different features of breast cancer including tumor stage classification and diagnostic/ prognostic subgroups of patients (for review see ref. 73). These studies raise the possibility that prediction of prognosis may be improved and that treatment for many diseases may be individualized based on gene analysis or gene signature patterns. The first diagnostic microarray to influence drug selection and dosage, the Roche AmpliChip Cytochrome P450 test, was approved by the FDA in 2004. Large-scale DNA or RNA analysis can be performed using microarrays generated by cloned libraries or synthetic oligonucleotides. The latter, nucleotide microarrays, will be discussed in a different section of this volume. In this chapter, we provide an introduction to the use, sample quality control, and sample preparation for cDNA-based RNA microarrays and BAC-based CGH DNA microarrays. The selection of reagents that are used in the materials and methods is based on authors’ preferences and experience. 1.1. RNA Microarray

Printing cDNA microarrays on glass slides was the first microarray technique developed and is still commonly used. cDNAs are amplified from individual clones in a library. Each cDNA fragment representing an individual gene of interest is immobilized on a glass slide that has been coated with DNA-binding chemicals such as amino silane or poly-l-lysine. These slide arrays can be printed as whole genome microarrays or with a focused selection of genes of interest. The two-color cDNA microarray assay is illustrated in Fig. 1. In a typical slide microarray experiment, the mRNAs from experimental samples to be compared (such as test vs. control) are reverse transcribed and are then labeled with two different detectable fluorescent markers (typically Cy3 vs. Cy5 or compatible Alexa dyes). When the amount of RNA in each sample is limited, such as assays from few or single cells, the RNAs may be subjected to an amplification procedure prior to fluorescent labeling. The two labeled samples are mixed and then hybridized to a microarray. After the excess of labeled probes is removed by washing, the intensity of each fluorophore at each array location is read using a laser scanner. Hybridization intensity is represented by the amount of fluorescent emission, which provides an estimate of the relative amount of each transcript present in the different samples. These arrays are printed using a library containing the sequences of interest. In a library, each bacteria clone carries a plasmid containing a unique sequence derived from the mRNA of a gene.

RNA and DNA Microarrays Test

RNA QC

Labeling QC

7

Control

or Total RNA RT & label or Amplify &

or cRNA

Fig. 1. Two-color RNA microarray assay. Test and control samples are reverse transcribed and labeled with different fluorophores. The labeled samples are competitively hybridized to the microarray that has been printed at each location with a different DNA sequence for a gene of interest. Determination of the relative fluorescence obtained at each array location, after normalization, reflects the relative levels of expression of each specific mRNA in the original samples. RT reverse transcription, QC quality control.

The library cDNAs, ranging from 500 bp to 2 kb, are amplified by PCR using the specific flanking primers of the gene, according to each clone library. The amplified cDNA fragments are purified, and the concentration determined. The end product of each clone is quality controlled by gel electrophoresis and printed using a specialized printing robot. 1.1.1. RNA QC

A slide RNA microarray offers a high level of flexibility in terms of labeling choices. The starting amount of RNA plays a significant role in influencing the choice of method used for target production, since it determines the level of amplification required. Three examples of labeling protocols are included in this section. Regardless of which method is chosen, the test and control samples must be properly matched to minimize the background variation.

1.2. DNA Microarray

CGH allows partial or entire genome analysis for variations in DNA copy number. In a CGH DNA microarray, artificial chromosomes from bacteria (BAC) containing known genomic

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fragments are immobilized on a glass surface and hybridized with a mixture of different fluorescence-labeled test and control DNAs. The ratio of the fluorescent intensities of the fluorophores is measured for each feature on the array. This ratio provides a relative measure of the difference in gene copy number between the samples. This technique is useful for a comparison between individuals with altered disease states in order to detect tissue-specific deletions or duplications of chromosomal regions. BAC genomic libraries can be purchased or custom made by an industrial provider or academic core facility, e.g., National Human Genome Research Institute, Wellcome Trust Sanger institute, Children’s Hospital Oakland Research Institute, Roswell Park Cancer Center, Clemson University Genomics Institute, Arizona Genomics Institute, Arabidopsis Biological Resource Center (ABRC) at Ohio State University, etc. The detailed protocol for preparation of the BAC DNAs is usually provided with the source library obtained, and the fabrication of a microarray slide is performed in an array printing service center. Briefly, BAC clones are streaked on LB-agar plates containing the appropriate antibiotic and grown overnight at 37°C. A single colony is inoculated in TB media containing the appropriate antibiotic and placed in a shaking incubator at 37°C for 16 h. From this culture, DNA is isolated and amplified through ligation-mediated PCR where a genomic DNA clone is digested with a restriction enzyme and a universal primer adaptor is ligated to serve as a priming site for PCR amplification. The amplified genomic DNA fragments are purified, the concentrations are determined and normalized, and then they are used for the fabrication of array slides for CGH. 1.2.1. DNA QC

Good quality of genomic DNA generally increases the sensitivity and accuracy of the array CGH assay. The DNA must be pure and free of contaminants, especially other sources of genomic DNA. Genomic DNA can be extracted from various sources, e.g., blood, buccal cells, cultured cells, tissue, and paraffin-embedded tissue. Many commercial kits targeting a particular sample source produce high-quality genomic DNA. Methods that include boiling or strong denaturants that may generate single-stranded DNA are not suitable to use. The purity of the DNA can be determined by the 260/280 spectrophotometer absorbance ratio. Ratio of 1.8 in a 10-mM Tris-HCl buffer typically represents pure DNA, whereas lower value for protein contamination and higher value for RNA contamination or degraded samples. The approximate average size of genomic DNA can be viewed on a 1% agarose gel. High-quality genomic DNA will run as a major peak at approximately 10–20 kb on the gel. Whole genome amplification (WGA) was developed in 1992 (74, 75) as a way to increase the amount of DNA from limited samples such as forensics and genetic disease research.


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Various WGA techniques have been developed. One approach, multiple displacement amplification (MDA) provides unbiased and accurate amplification of whole genomes (76, 77). This method utilizes Phi29 DNA polymerase, producing micrograms of high-molecular weight DNA fragments from as little as 10 ng of starting DNA. The end products are suitable for array CGH assay.

2. Materials 2.1. RNA QC 2.1.1. Direct Labeling

See Note 1 for preparing the mixture. 1. Oligo-dT18. 2. Superscript II. 3. 100 mM dNTP set. 4. Cy3- or Cy5- dUTP. 5. RNAsin. 6. RNAse H. 7. RNAseOne. 8. Minelute Cleanup Kit.

2.1.1.1. Stock Solutions and Master Mixtures

10× low dTTP dNTPs stock solution: Reagents

Amount

dGTP (100 mM)

25 ml

dATP (100 mM)

25 ml

dCTP (100 mM)

25 ml

dTTP (100 mM)

10 ml

DEPC-water

415 ml

Total

500 ml

Master Mix for making fluorescent cDNA target: Reagents

Amount

5× First strand buffer

6 ml

0.1 M DTT

3 ml

10× Low dTTP dNTP mix

0.8 ml

Cy-3 or Cy-5 dUTP (1 mM)

2 ml

RNAsin

1 ml

Total

12.8 ml

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2.1.2. Indirect Labeling

1. Oligo-dT18. 2. Superscript II. 3. 100 mM dNTP set. 4. aa-dUTP. 5. Sodium bicarbonate. 6. CyDye PostLabeling Reactive Dye Pack. 7. K2HPO4. 8. KH2PO4. 9. 0.5 M EDTA. 10. NaOH. 11. HCl. 12. MinElute cleanup kit. 13. NaAcetate. 14. DMSO.


Phosphate buffers (1 M Potassium phosphate, pH 8.5): Check pH with pH paper. Reagents

Amount

1 M K2HPO4

9.5 ml

1 M KH2PO4

0.5 ml

Total

10 ml

Phosphate wash buffer (5 mM KPO4, pH 8.5, 80% EtOH): Reagents

Amount

1 M Phosphate buffer, pH 8.5

0.5 ml

Water

15.25 ml

95% EtOH (alcohol)

84.25 ml

Total

100 ml

Phosphate elution buffer: Reagents 1 M Phosphate buffer, pH 8.5

Amount 4 ml

Water

996 ml

Total

1,000 ml


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100 mM Amino-allyl dUTP: Store in −20°C Reagents

Amount

aa-dUTP

1 mg

Water

19.1 ml

50× Labeling Mix (2:3 aa-dUTP:dTTP): Store in −20°C Reagents

Amount

dGTP (100 mM)

5 ml

dATP (100 mM)

5 ml

dCTP (100 mM)

5 ml

dTTP (100 mM)

3 ml

aa-dUTP (100 mM)

2 ml

Total

20 ml

0.3 M Sodium bicarbonate, pH 9.0: Check pH with pH paper. Use for 1 day only. Reagents

Amount

Sodium bicarbonate

1 g

dH2O

40 ml

NaOH (10 N)

180 ml

aa-dUTP-labeled cDNA target:

2.1.3. Small Sample Labeling

Reagents

Amount


6 ml

0.1 M DTT

3 ml

50× Aminoallyl-dNTP mix

0.6 ml

Total

9.6 ml

1. Low input RNA amplification kit, see Note 2. 2. RNeasy MinElute Cleanup kit. 3. 50 mM aa-UTP. 4. 100 mM NTP set. 5. Sodium bicarbonate. 6. CyDye PostLabeling Reactive Dye Pack. 7. Hydroxylamine. 8. Fragmentation buffer.

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Low UTP NTP mixture: Aliquot 100 ml per tube and store at −80°C. Reagents

Amount

100 mM ATP

100 ml

100 mM GTP

100 ml

100 mM CTP

100 ml

100 mM UTP

75 ml

DEPC-water

25 ml

Total

400 ml

25 mM aa-UTP mixture: Aliquot 50 ml per tube and store at −80°C. Reagents

Amount

50 mM aa-UTP

100 ml

DEPC-water

100 ml

Total

200 ml

0.3 M Sodium bicarbonate at pH 9.0: Check pH with pH paper. Use for 1 day only. Reagents

Amount

Sodium bicarbonate

1 g

dH2O

40 ml

NaOH (10 N)

180 ml

cDNA Master Mix: Reagents

Amount


4 ml

0.1 M DTT

2 ml

10 mM dNTP

1 ml

MMLV RT

1 ml

RNase OUT

0.5 ml

Total

8.5 ml


In vitro transcription Master Mix:

2.1.4. Hybridization and Scanning (see Note 4)

Reagents

Amount

Water

5.7 ml

4× Transcription buffer

20 ml

0.1 M DTT

6 ml

Low UTP NTP Mix

16 ml

50% PEG

6.4 ml

RNAse OUT

0.5 ml

Inorganic pyrophosphatase

0.6 ml

aa-UTP (25 mM)

4 ml

T7 RNA polymerase

0.8 ml

Total

60 ml

1. Human or mouse Cot-1 DNA. 2. Poly(dA). 3. Transfer RNA (tRNA). 4. Formamide. 5. Succinic anhydride. 6. n-Methyl-pyrrilidinone. 7. NaBorate. 8. 50× Denhardt’s solution. 9. 20× SSPE. 10. 20× SSC. 11. SDS. 12. SS salmon sperm DNA. 13. Raised-edge coverslip. 14. Microarray hybridization cassette.

2.1.4.1. Stock Solutions

20× Blocking mixture: Reagents

Amount

Poly(dA)

40 mg

tRNA

80 mg

Human or mouse Cot-1 DNA 2,000 mg

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Add 1/10 volume of 3 M NaAcetate, pH 5.2, then precipitate the content with 2.5 × volume of 100% ethanol. Wash the pellet 1× with 70% ethanol and air-dry. Resuspend in 20-ml filtered Mili-Q water. Hybridization solution: Reagents

Amount

Formamide

35 ml

20× SSPE

20 ml

20% SDS

2.5 ml

50× Denhardt’s solution

5 ml

Water

37.5 ml

Total

100 ml

Prehybridization solution: Reagents

Amount

Formamide

35 ml

20× SSPE

20 ml

10% SDS

5 ml

50× Denhardt’s solution

5 ml

SS salmon sperm DNA (10 mg/ml)

2 ml

Water

33 ml

Total

100 ml

2.2. DNA QC

1. REPLIg Mini Kit.

2.2.1. Materials for Genomic DNA Amplification

2. Mini Quick Spin Column.

2.2.1.1. Stock Solutions and Master Mixtures (see Note 5)

Buffer D1 (sufficient for 15 reactions): Reagents

Amount

Reconstituted DLB buffer

5 ml

Nuclease-free water

35 ml

Total

40 ml

Buffer N1 (sufficient for 15 reactions): Reagents

Amount

Stop solution

8 ml

Nuclease-free water

72 ml

Total

80 ml


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Master Mix for amplification: Add the master mix components in the order listed in the table below. After addition of water and reaction buffer, briefly vortex and centrifuge the mixture before the addition of the DNA polymerase. The master mix should be kept on ice and used immediately upon the addition of the DNA polymerase.

2.2.2. Direct Labeling

Reagents

Amount

Nuclease-free water

10 ml

Reaction buffer

29 ml

DNA polymerase

1 ml

Total

40 ml

1. BioPrime Array CGH Genomic DNA Labeling module. 2. 100 mM dNTP set. 3. 1 M Tris–HCl, pH 8.0. 4. 0.5 M EDTA, pH 8.0. 5. 1 mM Cy3 or Cy5-labeled dCTP. 6. Microcon YM 30.


10× dNTP Mix (0.5 mM dCTP, 2 mM dATP, 2 mM dGTP, 2 mM dTTP in TE buffer): Reagents

Amount

dGTP (100 mM)

4 ml

dATP (100 mM)

4 ml

dTTP (100 mM)

4 ml

dCTP (100 mM)

1 ml

1 M Tris–HCl, pH 8.0

2 ml

0.5 M EDTA, pH 8.0

0.4 ml

DEPC-water

184.6 ml

Total

200 ml

Master Mix for DNA labeling: Add the component in order listed. Reagents

Amount

10× dNTP

10 ml

Cy3 or Cy5-labeled dCTP

4 ml

Klenow

2 ml

Total

16 ml

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Sealfon and Chu

2.2.3. Hybridization and Scanning

1. 3 M NaAcetate, pH 5.2. 2. Ethanol, 100%, 80%. 3. Yeast RNA. 4. Herring sperm DNA. 5. Cot-1 DNA. 6. TE buffer, pH 8.0. 7. Formamide. 8. Dextran sulphate. 9. 10% Tween-20. 10. SSC. 11. 1 M Tris buffer pH 7.4. 12. Raised-edge coverslip. 13. Microarray hybridization cassette.


Reagents

Amount

Formamide

500 ml

Dextran sulphate

100 mg

Tween-20

1 ml

20× SSC

100 ml

1 M Tris buffer, pH 7.4

10 ml

Nuclease-free water

~389 ml

Total

1 ml

Pre-/hybridization buffer (50% formamide, 10% dextran sulphate, 0.1% Tween-20, 2× SSC, 10 mM Tris–HCl, pH 7.4).

3. Methods 3.1. RNA QC

Accurate measurement of transcripts requires RNA samples that are free of degradation, which can differentially affect individual sequences. The quality of the total RNA should be verified by two methods – spectrophotometer-based assay and visualization of the ribosomal RNA (rRNA). The 260/280 spectrophotometer absorbance ratio is the simplest test to assess RNA quality. Ratios between 1.9 and 2.1 in a 10-mM Tris-based buffer typically represent high quality, pure RNA. Values considerably below this range suggest DNA, protein, or chemical contamination. Values greater than this range suggest the presence of degraded RNAs. A more sensitive method to assess the integrity of RNA is to


a

17

c RIN=9.6 18S rRNA

RIN=5.5

28S rRNA

Leading marker

b

d RIN=8.3

RIN=2.8

Fig. 2. Representative Bioanalyzer electropherogram showing RNA samples of varying quality. RIN: RNA integrity number, ranging from 10 to 0 for the best to worst RNA integrity. RNAs in panels (c) or (d) are not suitable for RNA microarray assay.

visualize the rRNA component of total RNA. This can be achieved by performing an RNA gel electrophoresis; however, the process is tedious and requires micrograms levels of RNA. The Bioanalyzer (Agilent Technologies, Inc., Palo Alto, CA), a microfluidics-based platform, is a satisfactory way to assess RNA quality using small quantities of RNA. Representative Bioanalyzer readouts are depicted in Fig. 2. In addition to providing a “gel-like” image of the sample, this system derives an RNA integrity number or RIN that is useful in estimating the overall quality of total RNA samples. 3.1.1. Direct Labeling Methods

Reagents’ list and amounts are given in Subheading 2.1.1 to prepare Stock Solutions or Master Mixtures. 1. Resuspend 20–50 mg of total RNA or 1–2 mg of mRNA in DEPC-H2O to make the final volume of 13.2 ml. 2. Add 2 ml of oligo-dT18 (2 mg/ml). 3. Final volume: 15.2 ml. 4. Incubate at 65°C for 10 min. 5. Place on ice for at least 2 min.

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3.1.1.1. To Make Fluorescent cDNA Target

1. Add the mixed content, given in Subheading 2.1.1, to the annealed RNA mix. 2. Add 2 ml of superscript II into the mixture. 3. Final volume: 30 ml. 4. Incubate at 42°C for 1 h. 5. Add another 1 ml of superscript II. 6. Incubate for another 1 h. 7. Heat at 94°C for 2 min.

3.1.1.2. To Degrade RNA

1. Add 48 ml dH2O to each tube. 2. Add 9 ml 10× RNAse One buffer. 3. Add 2 ml RNAse One. 4. Incubate at 37°C for 10 min. 5. Heat 94°C for 1 min.

3.1.1.3. To Cleanup cDNA Targets by MinElute Column

1. Keep Cy5 and Cy3 separate for MinElute cleanup to measure CyDye incorporation, if desired. 2. Add 9 ml 3 M NaAcetate, pH 5.2 to the sample tube. 3. Add 495 ml binding buffer to each sample. 4. Assemble the MinElute column on the provided 2-ml collection tubes. 5. Load the entire mixture to a MinElute column. 6. Centrifuge for 1 min at 10,000 RCF. Discard the flowthrough and reuse the 2-ml tube. 7. Add 750 ml PE wash buffer to the column. 8. Centrifuge at 10,000 RCF for 1 min. Discard the flowthrough and reuse the 2-ml tube. 9. Repeat steps 7 and 8. 10. Centrifuge again at maximum speed for 1 min to remove residual EtOH. 11. Place column in a fresh 1.5-ml tube. Add 10 ml of water (pH 7.5) to elute. 12. Allow elution water to stand for at least 2 min before spinning. 13. Centrifuge at maximum speed for 1 min. Add 10 ml of water (pH 7.5) to elute. 14. Allow elution water to stand for at least 2 min before spinning. 15. Centrifuge at maximum speed for 1 min. 16. Proceed to “Analysis of Target Labeling Reaction by NanoDrop Spectrophotometer” in Subheading 3.1.3.7.


19

17. Combine equal amount of the exp- and control-labeled cDNA targets. Bring the final volume to 18.5 ml. Reduce volume by speedvac if necessary. 3.1.2. Indirect Labeling Methods

Reagents’ list and amounts are given in Subheading 2.1.2 to prepare Stock Solutions or Master Mixtures.

3.1.2.1. To Anneal RNA

1. Resuspend 20–50 mg of total RNA or 1–2 mg of mRNA in DEPC-H2O to make the final volume to 16.4 ml. 2. Add 2 ml of oligo-dT18 (2 mg/ml). 3. Final volume: 18.4 ml. 4. Incubate at 65°C for 10 min. 5. Quick spin and place on ice for at least 2 min.

3.1.2.2. To Make aa-dUTP-Labeled cDNA Target

1. Add the mixed content given in Subheading 2.1.2 to the annealed RNA mix. 2. Add 2 ml superscript II into the mixture. 3. Final volume: 30 ml. 4. Incubate at 42°C for 2 h. 5. Add another 1 ml superscript II. 6. Incubate for another 1 h. 7. Add 1 ml 0.5 M EDTA, see Note 6.

3.1.2.3. RNA Hydrolysis

1. Heat mixture at 95°C for 3 min. 2. Quick spin and immediately place on ice for at least 2 min. 3. Add 15 ml 1 M NaOH. 4. Mix and incubate at 65°C for 15 min. 5. Quick spin and put the tube on ice. 6. Add 15 ml 1 M HCl. 7. Total volume: 62 ml.

3.1.2.4. Targets Purification (see Note 7)

1. Add 6 ml 3 M NaAcetate, pH 5.2 to each sample tube. 2. Add 340 ml binding buffer to each sample. 3. Assemble the MinElute column on the 2-ml collection tubes provided. 4. Load the entire mixture to a MinElute column. 5. Centrifuge for 1 min @ 10,000 RCF. Discard the flowthrough and reuse the 2-ml tube. 6. Add 750 ml phosphate wash buffer to the column. 7. Centrifuge at 10,000 RCF for 1 min. Discard the flow-through and reuse the 2-ml tube. 8. Repeat steps 6 and 7.

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Sealfon and Chu

9. Centrifuge again at maximum speed for 1 min to remove residual EtOH. 10. Place column in a fresh 1.5-ml tube. Add 10 ml of phosphate elution buffer to elute. 11. Allow elution buffer to stand for at least 2 min before spinning. 12. Centrifuge at maximum speed for 1 min. Add 10 ml phosphate elution buffer to elute. 13. Allow elution buffer to stand for at least 2 min before spinning. 14. Centrifuge at maximum speed for 1 min. 15. Dry sample completely in a speedvac. 3.1.2.5. Coupling aa-cDNA to Cy Dye Ester

1. Resuspend sample in 6 ml water. 2. Add 3 ml 0.3 M Na2CO3 buffer, pH 9.0. 3. Total volume: 9 ml. 4. Add 11 ml high-quality DMSO to one tube of Cy3 or Cy5 dye. 5. Vortex to mix thoroughly. Keep dye in the dark until ready to use (do not prepare dye >1 h before using). Make sure that no water gets into the dye/DMSO mix at any point. 6. Transfer the dye mix to sample tube. 7. Total volume: 20 ml. 8. Incubate at RT in the dark for 1 h.

3.1.2.6. Target Purification

1. To the tube, add 70 ml H2O and 10 ml 3 M NaOAc, pH 5.2. 2. Add 500 ml binding buffer. 3. Assemble the MinElute column on the provided 2-ml collection tubes. 4. Load the entire mixture to a MinElute column. 5. Centrifuge for 1 min at 10,000 RCF. Discard the flowthrough and reuse the 2-ml tube. 6. Add 750 ml PE buffer to the column. 7. Centrifuge at 10,000 RCF for 1 min. Discard the flowthrough and reuse the 2-ml tube. 8. Repeat steps 6 and 7. 9. Centrifuge again at maximum speed for 1 min to remove residual EtOH. 10. Place column in a fresh 1.5-ml tube. Add 10 ml of water (pH 7.5) to elute. 11. Allow elution buffer to stand for at least 2 min before spinning. 12. Centrifuge at maximum speed for 1 min. Add 10 ml of water (pH 7.5) to elute.


21

13. Allow elution water to stand for at least 2 min before spinning. 14. Centrifuge at maximum speed for 1 min. 15. Put sample on ice and in the dark. 16. Proceed to “Analysis of Target Labeling Reaction by NanoDrop Spectrophotometer” in Subheading 3.1.3.7, if desired. 17. Combine the test- and control-labeled cDNA targets. Bring the final volume to 18.5 ml. Reduce volume by speedvac if necessary. 3.1.3. Small Sample Labeling Methods

3.1.3.1. RNA Annealing

Reagents’ list and amounts are given in Subheading 2.1.3 to prepare Stock Solutions or Master Mixtures. Preset a PCR program with lid heat off as follows: ●●

65°C 10 min

●●

4°C 5 min

●●

4°C pause

●●

40°C 2 h

●●

65°C 15 min

●●

4°C 5 min

●●

4°C hold

1. Use 50 ng to 5 mg of total RNA per reaction. If possible, start with 2 mg of total RNA and make the final volume to 6.5 ml. 2. Add 5 ml T7 promoter primer. 3. Place the tube in a preprogrammed PCR machine. 4. Incubate at 65°C for 10 min, 4°C for 5 min and pause.

3.1.3.2. cDNA Synthesis

1. Prewarm 5× first strand buffer at 80°C for 3–4 min. Quick spin the tube and keep at RT until use. 2. To each sample tube, add 8.5 ml of cDNA Master Mix. 3. Incubate samples at 40°C for 2 h, 65°C for 15 min, 4°C for 5 min, then 4°C hold (see Note 8).

3.1.3.3. In Vitro Transcription

1. Prewarm the 50% PEG solution at 40°C for 1 min. 2. In a separate tube, prepare a master mix, given in Subheading 2.1.3 at RT immediately prior to use. 3. Add 60 ml of transcription master mix to each sample tube. 4. Total volume: 80 ml. 5. Place tubes on PCR machine. Run program 6. 40°C 2 h 7. 4°C hold 8. Add 20 ml RNase-free water to each sample tube to make a total volume of 100 ml.

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3.1.3.4. cRNA Purification with RNeasy MinElute Column

See Note 9 for cRNA purification. 1. Prewarm RNase-free water at 50°C for at least 10 min. 2. Add 350 ml Buffer RLT, and mix thoroughly. 3. Add 250 ml ethanol (96–100%) to the mixture, and mix thoroughly by pipetting. Do not centrifuge. Continue immediately with step 4. 4. Apply the sample (700 ml) to an RNeasy MinElute column placed in a 2-ml collection tube (supplied). Close the tube gently, and centrifuge for 30 s at ³10,000 × g. 5. Discard the flow-through and collection tube. 6. Transfer the RNeasy column into a new 2-ml collection tube (supplied). Pipet 500 ml Buffer RPE onto the RNeasy column. Close the tube gently, and centrifuge for 1 min at ³10,000 × g to wash the column. Discard the flow-through. Reuse the collection tube in step 6. 7. Add 500 ml 80% ethanol to the RNeasy column. Close the tube gently, and centrifuge for 1 min at ³10,000 × g. Discard the flow-through. Reuse the collection tube and centrifuge for additional 2 min. 8. To elute, transfer the RNeasy column to a new 1.5-ml collection tube. Pipet preheated 10 ml RNase-free water directly onto the RNeasy silica-gel membrane. Close the tube gently, let sit at room temperature for 1 min, and centrifuge for 1 min at ³10,000 × g to elute. 9. Repeat step 8 once. 10. Quantitate cRNA yield by spectrophotometer.

3.1.3.5. Cy Dye Coupling Reaction

1. Add 11 ml of high-quality DMSO to each dye tube. Mix thoroughly and keep in dark. 2. Use 5 mg of aa-modified cRNA and vacuum dry (not to complete dryness). 3. Adjust volume to 6 ml. 4. Add 3 ml 0.3 M sodium bicarbonate buffer, pH 9.0 to sample tube. 5. Transfer the Cy-DMSO dye solution to sample tube and mix well. 6. Total volume: 20 ml. 7. Incubate in the dark at RT for 1 h. 8. Add 4.5 ml 4 M hydroxylamine solution to the mixture and incubate for 15 min in the dark at RT. 9. Add 5.5 ml DEPC-water to the labeled cRNA. 10. Total volume: 30 ml.

RNA and DNA Microarrays 3.1.3.6. Labeled cRNA Purification with RNeasy MinElute Column (see Note 8)

23

1. Prewarm RNase-free water at 50°C for at least 10 min. 2. Add 105 ml Buffer RLT, and mix thoroughly. 3. Add 75 ml ethanol (96–100%) to the mixture, and mix thoroughly by pipetting. Do not centrifuge. Continue immediately with step 4. 4. Apply the sample mixture (210 ml) to an RNeasy MinElute column placed in a 2-ml collection tube (supplied). Close the tube gently, and centrifuge for 30 s at ³10,000 × g. 5. Discard the flow through and collection tube. 6. Transfer the RNeasy column into a new 2-ml collection tube (supplied). Pipet 500 ml Buffer RPE onto the RNeasy column. Close the tube gently, and centrifuge for 1 min at ³10,000 × g to wash the column. Discard the flow-through. Reuse the collection tube in step 6. 7. Add 500 ml 80% ethanol to the RNeasy column. Close the tube gently, and centrifuge for 1 min at ³10,000 × g. Discard the flow-through. Reuse the collection tube and centrifuge for additional 1 min. 8. To elute, transfer the RNeasy column to a new 1.5-ml collection tube. Pipet preheated 10 ml RNase-free water directly onto the RNeasy silica-gel membrane. Close the tube gently; let it sit at room temperature for 1 min, and centrifuge for 1 min at ³10,000 × g to elute. 9. Repeat step 8 once. 10. Proceed to “Analysis of Target Labeling Reaction by NanoDrop Spectrophotometer” in Subheading 3.1.3.7 if desired. 11. Combine equal amount of the labeled cRNAs, approximately 100 pmol of Cy3 and 50 pmol Cy5 for each hybridization reaction. 12. Bring the volume to 20 ml with Nuclease-free water (or reduce volume in a speedvac if necessary). Do not dry completely. 13. Proceed to hybridization.

3.1.3.7. Analysis of Target Labeling Reaction by NanoDrop Spectrophotometer

1. Start the NanoDrop software. 2. Click the MicroArray tab. 3. Before initializing the instrument as requested by the software, clean the sample loading area with nuclease-free water. 4. Load 1.0 ml of nuclease-free water to initialize. Then, click OK. 5. Once the instrument has initialized, select RNA-40 (for cRNA), ssDNA-33 (for cDNA), or DNA-50 (for genomic DNA) as the Sample type (use the drop down menu) or according to your sample.

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6. Make sure the Recording button is selected. If not, click Recording so that the readings can be recorded, saved, and printed. 7. Blank the instrument by pipetting 1.0 ml of nuclease-free water or elution buffer (whatever the samples are in) and click Blank. 8. Clean the sample loading area with a laboratory wipe. Pipette 1.0 ml of the sample onto the instrument sample loading area. Type the sample name in the space provided and click Measure (see Note 10). 9. Similarly, measure the RNA, ssDNA, or DNA absorbance by clicking the NucleicAcid tab in the main menu. 10. Print the results. If printing the results is not possible, record the following values: ●●

Cyanine 3 or cyanine 5 dye concentration (pmol/ml)

●●

RNA, ssDNA, or DNA absorbance ratio (260/280 nm)

●●

cRNA, ssDNA, or DNA concentration (ng/ml)

11. Determine the yield and specific activity of each reaction as follows: ●●

●●

●●

Use the concentration of RNA or DNA (ng/ml) to determine the mg RNA or DNA yield as follows: (Concentration of RNA or DNA) × (elution volume)/1,000 = mg of RNA or DNA. Use the concentrations of RNA or DNA (ng/ml) and cyanine 3 or cyanine 5 (pmol/ml) to determine the specific activity as follows: (Concentration of Cy3 or Cy5)/ (Concentration of RNA or DNA) × 1,000 = pmol Cy3/mg RNA or DNA. Use the A260 and A550 (for Cy3) or A650 (for Cy5) to determine the base-to-dye ratio as follows: Base/dye for Cy3™ = [A260 × 150,000 (cm–1 M–1)]/(A550 × 6,600). Base/dye for Cy5™ = [A260 × 250,000 (cm–1 M–1)]/ (A650 × 6,600). The base-to-dye ratio should be 40–80 for both Cy3 and Cy5.

12. Examine the yield and specific activity results. 13. If the yield is Science>Biology> Bioinformatics>Software. 2008; Available from: http://www.google.com. 36. Herold, K.E. and A. Rasooly, Oligo Design: a computer program for development of probes for oligonucleotide microarrays. Biotechniques, 2003. 35(6): pp. 1216–21. 37. Smith, T.F. and M.S. Waterman, Identification of common molecular subsequences. J Mol Biol, 1981. 147(1): pp. 195–197. 38. Lyon, Alignment software. 2008; Available from: http://pbil.univ-lyon1.fr/alignment. html. 39. Huang, X.Q. and W. Miller, A time-efficient, linear-space local similarity algorithm. Adv Appl Math, 1991. 12(3): pp. 337–357. 40. Pearson, W., LAlign program, part of the FASTA program set. 2008; Available from: http://fasta. bioch.virginia.edu/fasta_www2/fasta_ www.cgi?rm=lalign, http://www.ch.embnet.org/ software/LALIGN_form.html. 41. Pearson, W.R. and D.J. Lipman, Improved tools for biological sequence comparison. Proc Natl Acad Sci USA, 1988. 85(8): pp. 2444–8. 42. Altschul, S.F., et al., Issues in searching molecular sequence databases. Nat Genet, 1994. 6(2): pp. 119–29. 43. Altschul, S.F., et al., Basic local alignment search tool. J Mol Biol, 1990. 215(3): pp. 403–10. 44. Larkin, M.A., et al., Clustal W and Clustal X version 2.0. Bioinformatics, 2007. 23(21): pp. 2947–8. 45. Clustal, Clustal download site. 2008; Available from: http://www.clustal.org/. 46. Google, Science>Biology>Biochemistry and Molecular Biology>Methods and Techniques> PCR>Software. 2008; Available from: http:// www.google.com. 47. Bodrossy, L. and A. Sessitsch, Oligonucleotide microarrays in microbial diagnostics. Curr Opin Microbiol, 2004. 7(3): pp. 245–54. 48. Schena, M., et al., Quantitative monitoring of gene expression patterns with a complementary

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50.

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53. 54.

Volokhov et al. DNA microarray. Science, 1995. 270(5235): pp. 467–70. Badiee, A., et al., Evaluation of five different cDNA labeling methods for microarrays using spike controls. BMC Biotechnol, 2003. 3(1): p. 23. Lyon, L.A., M.D. Musick, and M.J. Natan, Colloidal Au-enhanced surface plasmon resonance immunosensing. Anal Chem, 1998. 70(24): pp. 5177–83. Lian, W., et al., Ultrasensitive detection of biomolecules with fluorescent dye-doped nanoparticles. Anal Biochem, 2004. 334(1): pp. 135–44. Raychaudhuri, S., et al., Basic microarray analysis: grouping and feature reduction. Trends Biotechnol, 2001. 19(5): pp. 189–93. Jarvinen, A.K., et al., Are data from different gene expression microarray platforms comparable? Genomics, 2004. 83(6): pp. 1164–8. Yauk, C.L., et al., Comprehensive comparison of six microarray technologies. Nucleic Acids Res, 2004. 32(15): p. e124.

55. Aguilar, Z.P., W.R. Vandaveer, and I. Fritsch, Self-contained microelectrochemical immunoassay for small volumes using mouse IgG as a model system. Anal Chem, 2002. 74(14): pp. 3321–9. 56. Sergeev, N., et al., Microarray analysis of Bacillus cereus group virulence factors. J Microbiol Methods, 2005. 57. Sergeev, N., et al., Microarray analysis of Bacillus cereus group virulence factors. J Microbiol Methods, 2006. 65(3): pp. 488–502. 58. AOAC International, Bacteriological analytical manual (BAM). 8th ed. (revision A). 1998, Gaithersburg, MD: AOAC International. 59. Sambrook, J. and D.W. Russell, Molecular cloning: a laboratory manual. 3rd ed. 2001, Cold Spring Harbor, NY: Cold Spring Harbor Laboratory. 60. Chachaty, E. and P. Saulnier, Isolation chromosomal DNA from bacteria, in The nucleic acid protocols: handbook, R. Rapley, Editor. 2000, Totowa, NJ: Humana Press Inc. pp. 29–32.

Chapter 4 Protein Microarrays Printed from DNA Microarrays Oda Stoevesandt, Mingyue He, and Michael J. Taussig Abstract Protein arrays are miniaturised and highly parallelised formats of interaction-based functional protein assays. Major bottlenecks in protein microarraying are the limited availability and high cost of purified, functional proteins for immobilisation and the limited stability of immobilised proteins in their functional state. In contrast, protein-coding DNA is readily available by PCR, and DNA arrays can be stored over prolonged times without deterioration. This chapter presents a method for the rapid and economical “printing” of replicate protein microarrays directly from a single DNA array template using cell-free protein synthesis, termed “DNA array to protein array,” DAPA. The procedure is a truly enabling technology, making customised protein microarrays affordable for laboratories with no access to routine microarray spotting. The experimental effort involved for the printing of a protein array from the template DNA array is comparable to the assembly of a Western blot. Key words: Protein array, Protein microarray, Cell-free protein synthesis, Protein immobilisation

1. Introduction Proteomics and systems biology require technologies for highthroughput, multiplexed analysis of protein expression levels and protein function. Protein arrays are miniaturised and highly parallelised formats of interaction-based assays using a minimum amount of samples and reagents. Among the interactions that can be assayed are protein–protein, protein–antibody, protein–nucleic acid, and protein–small molecule (1). Therefore, protein arrays are increasingly applied for profiling protein expression, identification of biomarkers for diagnostics, studying protein interactions, and discovery of protein signalling pathways (2). One of the impediments limiting the more widespread use of protein arrays is the preparative effort involved in expressing and purifying large numbers of functional proteins for immobilisation.

Ali Khademhosseini et al. (eds.), Biological Microarrays: Methods and Protocols, Methods in Molecular Biology, vol. 671, DOI 10.1007/978-1-59745-551-0_4, © Springer Science+Business Media, LLC 2011

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Commercially available protein arrays are therefore very costly. Another major problem is the limited stability of functional proteins in immobilised state on an array, especially when the array is stored over time periods of days to weeks before usage. Cell-free protein synthesis systems have been used to overcome these problems (3–8). These systems direct the synthesis of proteins directly from added DNA templates, providing a rapid means for conversion of genetic information into functional proteins. As cell-free protein synthesis systems are open for addition of further components, they allow the creation of optimised environments, for example correct protein folding or post-translational modifications (9). By coupling cell-free synthesis and simultaneous in situ protein immobilisation on the array surface, we have developed two cell-free methods, termed PISA (3, 6) and DAPA (7), for making protein arrays on demand directly from PCR DNA molecules. Here, we describe the details of the recent DAPA procedure (Fig. 1). In DAPA, a slide with a DNA microarray encoding a set of tagged proteins is assembled face-to-face with a second slide, functionalised with the tag-capturing reagent. A membrane soaked

Fig. 1. Principle (a) and sample results (b) of DAPA.

Protein Microarrays Printed from DNA Microarrays

97

with an in vitro transcription and translation system is positioned between the two slide surfaces. Tagged proteins synthesised from the immobilised DNA diffuse towards the capture slide surface where they adhere, creating the protein array corresponding to the DNA array template, with well-defined protein spot morphologies described by Gaussian intensity profiles. The DNA template slide can be re-used in further cycles of DAPA. We have demonstrated that at least 20 cycles of protein array printing are feasible using a single DNA template array (7). In this protocol, we describe 1. The PCR-based generation of constructs for cell-free expression in DAPA, encoding proteins with a C-terminal double (His)6 tag (10) for immobilisation. 2. The immobilisation of the PCR constructs on epoxy-activated slides for generation of template DNA microarrays. 3. The DAPA procedure itself for printing a protein microarray from the template DNA array, using an Escherichia coli (E. coli) lysate-based system for cell-free protein synthesis.

2. Materials 2.1. DNA Encoding Proteins of Interest

The protocol below assumes the availability of DNA (cDNA or cloned) encoding the proteins of interest for arraying by DAPA.

2.2. Primers for Construction of DNA Templates for DAPA

The primers described here are suitable for generation of constructs for cell-free expression in E. coli S30 extracts. The numbering follows the primer designations in the overview schematic drawing of the construction process (Fig. 2). 1. T7-for: 5′-GATCTCGATCCCGCG-3′: Forward primer for generating the fragment with T7 sequence (see Subheading 2.3.1) in combination with T7-rev (primer 2). 2. T7-rev: 5′-CATGGTATATCTCCTTCTTAAAG-3′: Reverse primer for generating the fragment with T7 sequence in combination with T7-for (primer 1). 3. GENE-for: 5′-CTTTAAGAAGGAGATATACCATG(N)15–25-3′: Forward primer for PCR amplification of a target gene in combination with GENE-rev (primer 4). It contains a sequence (underlined) overlapping with the T7 fragment and 15–25 nucleotides from the 5′-sequence of the target gene. 4. GENE-rev: 5′-CACCGCCTCTAGAGCG(N)15–25-3′: Reverse primer for PCR amplification of a target gene in combination with GENE-for (primer 3). It contains a sequence (underlined)

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Fig. 2. PCR strategy to generate constructs for cell-free expression on DAPA arrays. The primers used are as follows: (1) T7-for, (2) T7-rev, (3) GENE-for, (4) GENE-rev, (5) LTT-for, (6) LTT-rev, (7) Cy5-T7-for (fluorophore-coupled derivative of 1), (8) NH2-LTT-rev (NH2-functionalised derivative of 6).

overlapping with the linker sequence and 15–25 nucleotides complementary to the 3′-sequence of the target gene. 5. LTT-for: 5′-GCTCTAGAGGCGGTGGC-3′: Forward primer for PCR generation of a fragment encoding linker, protein tag, and termination region (see Subheading 2.3.2) in combination with LTT-rev (primer 6). 6. LTT-rev: 5′-TCCGGATATAGTTCCTCC-3′: Reverse primer for PCR generation of a fragment encoding linker, protein tag, and termination region in combination with the LTT-for (primer 5).


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7. Cy5-T7-for: 5′-Cy5-GATCTCGATCCCGCG-3′: Fluorophorecoupled T7-for (primer 1). Forward primer for PCR amplification of a full length DAPA construct in combination with NH2-LTT-rev (primer 8). The Cy5-label allows detection of the immobilised PCR product on DNA microarrays. 8. NH2-LTT-rev: 5′-NH2-TCCGGATATAGTTCCTCC-3′: NH2functionalised LTT-rev (primer 6). Reverse primer for PCR amplification of a full length DAPA construct in combination with Cy5-T7-for (primer 7). The NH2-group allows immobilisation of the PCR product on epoxy-activated slides. 2.3. Plasmids Encoding Generic Elements for Cell-Free Protein Expression 2.3.1. Plasmid Including the T7 Domain

2.3.2. Plasmid Encoding Linker, Double (His)6-tag and Termination Sequence

2.4. Further Reagents and Kits for Molecular Biology and Cell-Free Protein Expression

The control plasmid included in the RTS100 E. coli HY kit (Roche) is used. It contains the T7 promoter (underlined), the ribosome-binding site (underlined italics), and the start codon ATG (bold) within the following sequence: 5 ′ G AT C T C G AT C C C G C G A A AT TA ATA C G A C T C A C TATA G G G A G A C C A C A A C G G T T T C C C T C TA G A AATAATTTTGTTTAACTTTAAGAAGGAGATA TACCATG-3′. Using standard molecular biology techniques a plasmid is created, containing a DNA insert encoding a flexible 19 amino acid linker (lowercase), a double (His)6-tag (underlined), two consecutive stop codons (bold), a poly(A) tail, and a transcription termination region (italics) (3). The double-(His)6 tag used here has shown improved affinity for arraying proteins on Ni-NTA modified surfaces compared to a conventional single-(His)6 tag (3, 10, 11). The detailed sequence of the insert is as follows: 5′-GCTCTAGAggcggtggctctggtggcggttc tggcggtggcaccggtggcggttctggcggtggcAAAC G G G C T G AT G C T G C A C AT C A C C AT C A C C AT C A CTCTAGAGCTTGGCGTCACCCGCAGTTCGGTGGTCA CCACCACCACCACCACTAATAA(A)28CCGCTGAGCAAT A A C TA G C ATA A C C C C T T G G G G C C T C TA A A C G G G TCTTGAGGGGTTTTTTGCTGAAAGGAGGAAC TATATCCGGA-3′. 1. Desoxy nucleotides (Sigma, UK). 2. Taq DNA polymerase and buffers (Qiagen, UK). 3. GenElute™ Gel Extraction kit (Sigma, UK). 4. GenElute™ PCR Clean-Up kit (Sigma, UK). 5. RTS100 E. coli HY (5 prime, UK) cell-free protein expression system for production of up to 20 mg of protein in a 50 ml reaction.

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6. Durapore 0.22 mm membrane filters (Millipore, UK). 7. Ni-NTA-coated microscope slide (Xenopore, USA). 8. Nexterion™ slide E (epoxysilane coated) (Schott Nexterion, UK). 2.5. Buffers for DNA Microarray Spotting

1. PBS-Tween: PBS pH 7.4, 0.05% Tween20. 2. 6× Spotting buffer: 300 mM sodium phosphate, pH 8.5. 3. Quenching buffer: 0.1 M Tris–HCl, pH 9.0. Add ethanolamine (Sigma, UK) to a final concentration of 50 mM immediately before use. 4. 0.1% (v/v) Tween-20. 5. 1 mM HCl. 6. 100 mM KCl. 7. Saturated NaCl solution for humidified chamber: 30% NaCl in H2O, boil to dissolve, cool down.

3. Methods 3.1. Generation of PCR Constructs for Cell-Free Expression in DAPA

3.1.1. Generation of PCR Fragments for Assembly

The PCR constructs contain the essential elements for cell-free transcription and translation, including a T7 promoter, a ribosome-binding site, start and stop codons, a poly(A) tail, and a transcription termination region. For immobilisation of proteins on a Ni-NTA modified surface in DAPA, a sequence encoding a linker and a double (His)6-tag is included downstream of the target gene (see Note 1). To simplify the PCR construction, these common upstream and downstream elements are assembled in plasmids which are used as templates for PCR. Figure 2 shows the PCR construction process in overview. 1. Set up standard 50 ml PCR reactions (see Note 2): (a) 5 ml 10× PCR buffer (b) 10 ml 5× Q solution (c) 4 ml dNTP (2.5 mM each) (d) 1.5 ml Forward primer (16 mM) (e) 1.5 ml Reverse primer (16 mM) (f) 1–10 ng Template (g) 1.25 U Taq (h) H2O to 50 ml


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With the following combinations of primers and templates: Forward primer

Reverse primer

T7-for

Template

PCR product (Fig. 2)

T7-rev

Plasmid encoding T7

Upstream T7 fragment (101 bp)

GENEfor

GENE-rev

Gene of interest

Target gene fragment (encoding protein of interest with deleted stop codon and short flanking 5′ and 3′ sequences)

LTT-for

LTT-rev

Plasmid encoding linker, tag, termination sequences

Downstream fragment (encoding linker, double (His)6 tag and termination sequences; 249 bp)

PCR programme: 30 Cycles: 94°C, 30 s → 54°C, 30 s → 72°C, 80 s 1 Cycle: 72°C, 480 s End: hold 10°C 2. Analyse the PCR products by electrophoresis on a 1% agarose gel. 3. Isolate the expected fragments by extracting them from the gel (use kit as specified by manufacturer). 4. Determine the concentration and purity of the cleaned PCR product by absorption at 260 and 280 nm or by gel electrophoresis and comparison with DNA marker bands. 3.1.2. Assembly of PCR Fragments to Complete Construct for Cell-Free Expression

1. Set up a 25 ml assembly PCR reaction as follows: (a) 2.5 ml 10× PCR buffer (b) 5 ml 5× Q solution (c) 1 ml dNTP (2.5 mM each) (d) Mix of upstream T7 fragment, target gene fragment, and downstream fragment in equimolar ratio (total DNA 50–100 ng) (e) 0.67 U Taq (f) H2O to 25 ml PCR programme for fragment assembly: 8 Cycles: 94°C, 30 s → 54°C, 60 s → 72°C, 60 s End: hold 10°C

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2. Amplify the assembled product by a second 50 ml PCR: (a) 5 ml 10× PCR buffer (b) 10 ml 5× Q solution (c) 4 ml dNTP (2.5 mM each) (d) 1.5 ml Primer T7-for (16 mM) (e) 1.5 ml Primer LTT-rev (16 mM) (f) 2 ml Product of assembly PCR product (step 1 above) (g) 1.25 U Taq (h) H2O to 50 ml PCR programme: 30 Cycles: 94°C, 30 s → 54°C, 60 s → 72°C, 80 s 1 Cycle: 72°C, 480 s End: hold 10°C 3. Analyse the PCR product by electrophoresis on a 1% agarose gel and purify the DNA if required (see Note 3). Construct identity can be further confirmed by PCR mapping using primers annealing at various positions along the desired sequence (see Note 4). The resulting PCR construct may be stored at −20°C for at least 6 months. 3.1.3. Re-amplification of Construct with Labelled Primers for Immobilisation on Arrays

1. Set up standard 50 ml PCR as in step 2 Subheading 3.1.2, but with labelled primers: (a) Cy5-T7-for (instead T7-for) (b) NH2-LTT-rev (instead LTT-rev) 2. Analyse the PCR product for correct size by agarose gel electrophoresis, purify on a spin column (use kit as specified by manufacturer), and elute in H2O. 3. Determine the concentration and purity of the cleaned PCR product by absorption at 260 and 280 nm or by gel electrophoresis and comparison with DNA marker bands. A DNA concentration of 100–200 ng/ml is recommended for DAPA template array spotting (see Subheading 3.2) (see Note 5).

3.2. Generation of DNA Arrays as Templates for DAPA

1. Add one volume of 6× spotting buffer to five volumes of the labelled PCR product (see Subheading 3.1.3). 2. Spot DNA samples on epoxysilane slides (see Note 6) with spot-to-spot distances of 1 mm and volumes per spot of 5–10 nl. 3. Incubate spotted slides in a humidified chamber (see Note 7) at RT for 1 h. 4. Incubate slides at 60°C for 30 min.


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5. Wash the slides at RT as follows: (a) 1× with 0.1% Tween-20 for 5 min (b) 2× with 1 mM HCl for 2 min (c) 1× with 100 mM KCl for 10 min (d) 1× with ddH2O for 1 min 6. Quench remaining epoxy groups by incubating slides in 0.1 M Tris–HCl pH 9.0, 50 mM ethanolamine at 50°C for 15 min. 7. Wash slides with ddH2O for 1 min and dry by pressurised air. 8. Scan slides in microarray scanner to confirm immobilisation of Cy5-labelled DNA. The slides are ready for use and can be stored in the dark at 4°C. 3.3. DAPA: Printing Protein Arrays from the Template DNA Array

Use a glass slide holder similar to a prototype designed by us. Figure 3 shows a schematic cross-section of the holder and the DAPA assembly process. 1. Cut a Durapore membrane filter large enough to cover the area of the DNA template array. 2. Prepare 10 ml E. coli cell-free lysate (according to the instructions of the manufacturer) for every 1 cm² of the membrane. 3. Assemble the DAPA sandwich in the slide holder in the following order (numbering refers to Fig. 3): (a) Bottom plate (1) (b) Rubber spacer (2) (c) Layer of parafilm (3) (d) Ni-NTA-coated slide (4), with the protein-capturing surface facing up (see Note 6)

Fig. 3. Schematic cross-section of DAPA assembly. (1) Bottom plate, (2) rubber spacer, (3) parafilm, (4) Ni-NTA-coated slide, protein-capturing surface facing up, (5) membrane filter soaked with cell-free lysate, (6) DNA array template slide, DNA surface facing down, (7) parafilm, (8) rubber spacer, (9) top plate.

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(e) Cell-free lysate, distributed on the surface of the Ni-NTA slide (f) Membrane filter (5), allowing it to soak up the lysate (see Note 8) (g) DNA array template slide (6), with DNA surface facing down (h) Layer of parafilm (7) (see Note 9) (i) Rubber spacer (8) (j) Top plate (9) Ensure even pressure on the slide sandwich. 4. Incubate the assembled slide holder at 30°C for 2–4 h (see Note 10). 5. Disassemble the slide sandwich and (a) Wash the Ni-NTA slide with the DAPA protein array on it with PBS-Tween. Do not dry the DAPA array before application in order to avoid denaturation of the immobilised proteins. (b) Wash the DNA template slide with ddH2O, dry by pressurised air, and store at 4°C for use in further DAPA cycles. 3.4. Downstream Usage of DAPA Arrays

The DAPA protein array is now ready for immediate use in an assay of choice. Downstream handling protocols and detection protocols will be dependent on the individual application. To control for expression of proteins and their immobilisation on the array, it is advisable to perform immunofluorescence staining with appropriate reagents against the arrayed proteins (Fig. 1b) (7).

4. Notes 1. The location of a tag should be tested at both the N- and C-terminus of the protein to make sure it is accessible and does not affect protein activity. C-terminal immobilisation tags are preferable, as their presence guarantees that the entire protein is synthesised. 2. The T7 fragment and the downstream fragment are usually produced in a larger quantity and stored at −20°C for use as required. 3. In case multiple PCR bands are generated, the PCR fragment with the expected size is isolated by gel extraction and used as the template for PCR re-amplification (see Subheading 3.1.3). In general, PCR fragments without purification can be directly used for protein synthesis in cell-free systems.


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4. A construct can be confirmed by PCR mapping, which is performed by using a combination of various primers annealing at different positions in the construct. If all PCR products have the expected size, it suggests the correct construction. 5. If the eluted PCR product is below this range, it can be concentrated in a vacuum centrifuge. The Cy5-label of the purified PCR product is usually not detectable by absorption (as there is only one Cy5 fluorophore per DNA double strand). 6. Mark glass slides and their orientation with a diamond-tipped pen. Any possible glass splinters or dust from the slide surfaces can be removed by using pressurised air. 7. This can be prepared using a box containing saturated NaCl solution and a raised platform for incubation of slides. 8. The soaking process takes a few seconds. It is crucial to avoid drying of the cell-free lysate within the membrane filter. 9. The parafilm must form an airtight seal around the slide sandwich (Fig. 3) in order to prevent evaporation of cell-free lysate soaked in the membrane filter between the two slides. 10. The incubation time may be varied depending on the downstream applications.

Acknowledgements Research at the Babraham Institute is supported by Biotechnology and Biological Sciences Research Council (BBSRC), UK. The Protein Technology Group at Babraham Bioscience Technologies is a partner in the EC FP6 CA 026008 ProteomeBinders, and in. References 1. Hall D A, Ptacek J, Snyder M. Protein microarray technology. Mech Ageing Dev 2007;128:161–167. 2. Bertone P, Snyder M. Advances in functional protein microarray technology. FEBS J 2005; 272:5400–5411. 3. He M, Taussig M J. Single step generation of protein arrays from DNA by cell-free expression and in situ immobilization (PISA method). Nucleic Acid Res 2001;29:e73. 4. Ramachandran N, Hainsworth E, Bhullar B, Eisenstein S, Rosen B, Lau A Y, Walter J C, LaBaer J. Self-assembling protein mircoarrays. Science 2004;305:86–90.

5. Angenendt P, Kreutzberger J, Glokler J, Hoheisel J D. Generation of high density protein microarrays by cell-free in situ expression of unpurified PCR products. Mol Cell Proteomics 2006;5: 1658–1666. 6. He M, Taussig M J. DiscernArray™ technology: a cell-free method for the generation of protein arrays from PCR DNA. J Immunol Methods 2003;274:265–270. 7. He M, Stoevesandt O, Palmer E A, Khan F, Ericsson O, Taussig M J. Printing protein arrays from DNA arrays. Nat Methods 2008;5: 175–177.

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8. He M, Stoevesandt O, Taussig M J. In situ synthesis of protein arrays. Curr Opin Biotechnol 2008;19:4–9. 9. He M. Cell-free protein synthesis: applications in proteomics and biotech-nology. N Biotechnol 2008;Aug2025:126–132. 10. Khan F, He M, Taussig M J. A double-His tag with high affinity binding for protein immo-

bilisation, purification, and detection on Ni-NTA surfaces. Anal Chem 2006;78:3072–3079. 11. Steinhauer C, Wingren C, Khan F, He M, Taussig M J, Borrebaeck C A. Improved affinity coupling for antibody microarrays: engineering of double-(His)6-tagged single framework recombinant antibody fragments. Proteomics 2006;6:4227–4234.

Chapter 5 Lithographically Defined Two- and Three-Dimensional Tissue Microarrays Esther W. Gomez and Celeste M. Nelson Abstract Traditional methods to study normal and pathological development of tissues have been limited by difficulties in controlling experimental conditions and quantifying biological processes of interest. Here we describe methods to create microarrays of engineered tissues that enable controlled and quantitative investigations. Using soft lithography-based techniques, extracellular matrix proteins can be microcontact printed or micromolded to make two- and three-dimensional micropatterned scaffolds. The ultimate form and resulting properties of the tissue construct are dictated by the geometry of the patterned extracellular matrix components. This chapter describes elastomeric stamp fabrication, microcontact printing and micromolding of extracellular matrix proteins, cell culture in micropatterned substrata, and quantitative immunofluorescence analysis of micropatterned tissues. Key words: Tissue engineering, Microfabrication, Organotypic culture, Epithelial

1. Introduction Understanding the processes involved in both normal and pathological tissue development is crucial to the engineering of tissue constructs for therapeutic and diagnostic purposes (1). Studies in vivo are difficult to control, observe, and quantify. As a result, much effort has been directed toward culturing organs ex vivo. Despite progress made in this field, organ cultures tend to be difficult to maintain as they require fresh tissues and are often uncontrollable. Engineered tissues offer unique benefits over organ culture approaches by allowing for the investigation of developmental processes and cellular behaviors within tissues in a controlled and quantitative manner. By defining the properties of the extracellular matrix (ECM) environment and the specific


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biochemical factors that are presented, one can precisely control the spatial organization and behaviors of the cells that make up the engineered tissue. One can then study how properties of the tissue, such as geometry and form, contribute to the control of biological events including proliferation, apoptosis, gene expression, and differentiation. Geometry can be chosen to best recapitulate the system of interest with, for example, two-dimensional (2D) engineered tissues approximating epithelial sheets and three-dimensional (3D) engineered tissues approximating epithelial tubes. Additionally, engineered tissues are advantageous due to the fact that they can be multiplexed into microarray formats thereby enabling quantitative analysis and high-throughput assays. Several techniques have been developed to pattern microarrays of ECM proteins in 2D onto rigid substrate. Early experiments used photolithographic methods to deposit adhesive islands of defined size onto nonadhesive substrate in order to study the effects of anchorage on cellular behavior (2). In recent years, soft lithographic techniques, which use elastomeric stamps to either print proteins using contact or adsorb proteins using microfluidics, have become popular (3–5). Soft lithography approaches have enabled the formation of complex patterns and gradients of ECM proteins on 2D substrate (6, 7). Similarly, elastomeric membranes containing holes can be used to mask regions of substrate thus enabling stenciling of proteins onto surfaces (8). More recently, microarrays of ECM proteins have been printed using both a standard DNA spotter and the atomic force microscopy technique of dip-pen nanolithography (9, 10). Sacrificial layers, such as aluminum thin films, have been used to pattern combinations of proteins and bioactive molecules onto silica (11). Of the techniques outlined, soft lithography offers the benefits of low cost and ease of use. Recently, much effort has been directed toward tailoring the biochemical and mechanical properties of 3D ECMs to more closely mimic the natural cellular microenvironment. Photopo lymerization has been used to form hydrogels through the activation of light-sensitive photoinitiator molecules to encapsulate cells and to create scaffolding materials (12). Through the use of multilayer photopatterning platforms, increased complexity can be built into engineered materials (13). Applications of 2D soft lithography have been extended to 3D by using elastomeric stamps as molds for macromolecular gels and hydrogel systems (14–19). Additionally, soft lithographic techniques have been used for layer-by-layer deposition of biopolymers, which exploits the use of alternating layers of cell-adhesive and cell-repellant polysaccharides and proteins, to pattern cellular co-cultures (20). Another strategy for patterning 3D ECMs relies on the use of a combination of microfluidics and sacrificial materials, such as

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paraffin, matrigel, and gelatin, to create internal cavities, channels, and networks with gels (21, 22). Although progress has been made in patterning 3D ECMs, much work is still required in order to replicate the complex properties and architectures of ECMs found in vivo. Here we describe soft lithography-based techniques to pattern 2D and 3D epithelial tissue microarrays using microcontact printing and micromolding approaches, respectively. In both the 2D and 3D patterning methods the geometry of the ECM is controlled, thus dictating the geometry and form of the tissue and the individual and collective behaviors of the cells that make up the tissue. Micropatterned tissues can be treated with biological molecules of interest, and the behaviors of the cells within the tissues tracked statistically by analyzing the spatial distributions of specific cellular markers within the tissue constructs. Here, we outline the procedures for (1) casting elastomeric stamps from patterned templates; (2) microcontact printing islands of ECM proteins onto slides to create 2D tissue microarrays; (3) micromolding collagen gels to create 3D tissue microarrays; and (4) immunofluorescence analysis of micropatterned tissues.

2. Materials 2.1. Stamp Preparation

1. Patterned silicon wafer.

2.2. Two-Dimensional Tissue Microarrays

1. Patterned PDMS stamp.

2. Poly(dimethyl siloxane) (PDMS; Sylgard 184, Dow Corning).

2. 22-mm glass coverslips (Fisher Scientific). 3. Spin-coater. 4. Extracellular matrix protein (fibronectin, BD Biosciences). 5. Phosphate-buffered saline (PBS). 6. Pluronic F108 Pastille, 1% (w/v) solution in PBS (BASF Corporation).

2.3. ThreeDimensional Tissue Microarrays

1. Patterned PDMS stamp. 2. 35-mm tissue culture dish. 3. Ethanol. 4. Bovine serum albumin (BSA, Calbiochem), 1% (w/v) solution in PBS. 5. 10× Dulbecco’s Modified Eagle’s Medium (DMEM/F12, Sigma).

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6. 1:1 Dulbecco’s Modified Eagle’s Medium:Ham’s F12 Nutrient Mixture (DMEM/F12 (1:1), Hyclone), supplemented with 2% fetal bovine serum (Atlanta Biologicals), 50 mg/mL gentamicin (Invitrogen), and 5 mg/mL insulin (Sigma). 7. 0.1 N NaOH. 8. Collagen (bovine dermal or rat tail, BD Biosciences). 9. Glass coverslips, 15-mm diameter. 10. Ice. 2.4. Immunoflu orescence Staining and Image Analysis

1. PBS. 2. Paraformaldehyde, 4% (w/v) solution in PBS (Electron Microscopy Sciences). 3. IgePal CA 630, 0.5% (v/v) solution in PBS (Sigma). 4. Block buffer and antibody dilution buffer: 10% (v/v) goat serum/0.1% (v/v) Triton X-100/PBS. 5. Primary antibody: Phospho-p44/42 MAP Kinase (Thr202/ Tyr204) Antibody (Cell Signaling Technology). 6. Secondary antibody: Alexa 594 goat anti-rabbit (Invitrogen). 7. Nuclear stain: Hoechst 33258 (Invitrogen). 8. Glass coverslips (Fisher). 9. Mounting medium: Fluormount G (Southern Biotech). 10. Photoshop, ImageJ, or another image analysis program.

3. Methods Here, we describe soft lithography-based methods for creating 2D and 3D tissue microarrays (Fig. 1). First, PDMS stamps with defined patterns are prepared from a silicon wafer master. The patterned PDMS stamp is then used for microcontact printing or micromolding of ECM proteins for 2D and 3D ECM microarrays, respectively. Cells are then seeded on the ECM microarrays to form engineered tissues. The tissues can then be fixed, stained, and analyzed for spatial distributions of specific cellular markers. The methods described outline the following: 1. Preparation of the stamp. 2. Fabrication of 2D tissue microarrays. 3. Fabrication of 3D tissue microarrays. 4. Staining and imaging the tissues. 5. Analysis of the spatial distribution of cellular behaviors.

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Fig. 1. Schematic of patterning two- and three-dimensional tissues.

3.1. Stamp Preparation

1. Prepare 60 g of 10:1 (w/w) PDMS polymer:curing agent solution. Mix thoroughly and place the mixture in a vacuum dessicator to remove air bubbles. 2. Pour degassed PDMS mixture onto patterned silicon wafer master (see Note 1). 3. Bake at 60°C for 2 h to cure the PDMS. 4. Carefully peel the PDMS from the surface of the master. 5. Cut PDMS patterned by master into stamps of the desired size.

3.2. Two-Dimensional Tissue Microarrays

1. Spin coat a thin layer of PDMS onto the surfaces of glass coverslips. 2. Bake at 60°C for 2 h to cure PDMS. 3. Treat PDMS-coated coverslips for 7 min in UV/ozone cleaner before use in 2D microarray patterning. This oxidizing treatment increases the wettability of the PDMS substration thus allowing for both microcontact printing of protein and adsorption of Pluronics F108 (see steps below) (23). 4. Sterilize PDMS stamps with ethanol. Dry the stamps thoroughly with a vacuum aspirator.

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5. Coat the PDMS stamps with a solution of 25 mg/mL of fibronectin in PBS. Incubate for 2 h at room temperature. 6. Rinse once with PBS. 7. Dry the stamps with a steady stream of compressed nitrogen. 8. Stamp fibronectin onto the surface of a UV/ozone-treated PDMS-coated glass coverslip. Press lightly and then lift directly upward to remove stamp. 9. Flood the dish with a solution of 1% (w/v) Pluronics F108 in PBS. Incubate for 15 min. 10. Rinse twice with PBS. Leave patterned coverslips in PBS until ready to plate cells. 11. Plate cells on fibronectin patterned coverslips in cell culture media. Place in incubator and allow cells to adhere to fibronectin islands. Rinse to remove excess cells that have not adhered (see Note 2). 3.3. ThreeDimensional Tissue Microarrays

1. Cut PDMS into stamps that are ~5 mm cubes. Cut two small rectangles per sample from a thin sheet of polymerized PDMS to use as supports. Place stamps into Petri dish feature-side up. 2. Sterilize the PDMS stamps, PDMS supports, and 15-mm diameter coverslips with ethanol. Dry thoroughly with a vacuum aspirator. 3. Coat the feature side of the PDMS stamps with a solution of 1% BSA in PBS. Using a pipette tip, gently scrape the surface of the PDMS to remove air bubbles from the PDMS surface. Incubate for at least 30 min at room temperature (see Note 3). 4. Prepare a neutralized solution of collagen by mixing stock collagen with 0.1 N NaOH and 10× DMEM on ice. Mix thoroughly without introducing air bubbles (see Note 4). Adjust to the desired collagen concentration by adding 1× DMEM/F12. 5. Aspirate the BSA from PDMS stamps with a vacuum pipette. Rinse the BSA-coated surface twice with neutralized collagen (~30 mL). 6. Pipette a drop of neutralized collagen to the top of the PDMS stamp (~30 mL). 7. Flip over the collagen-coated stamp and place on top of two supports. 8. Pipette ~30 mL of collagen to the center of 15-mm round coverslips to make lids. 9. Place the dishes and lids in a 37°C incubator for 30 min. 10. Prepare a concentrated suspension of cells and keep them on ice. 11. Remove PDMS stamp from collagen gels by lifting directly upward with sterilized tweezers.

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12. Add ~30 mL of resuspended cells to the collagen gel. Monitor the sample with a phase-contrast microscope. When cells have settled into the wells, wash the sample by holding the dish at a 45° angle and gently pipetting 400 mL of cold media across the surface to remove excess cells. Repeat up to three times. Place the sample in a 37°C incubator for 5 min to allow the cells to adhere to the collagen. 13. Remove samples from the incubator and gently place a collagen lid on each sample. Add 2.5 mL of culture media to each sample and return the sample to the incubator. Observe the sample after ~24 h for tubule formation. 3.4. Immunoflu orescence Staining and Analysis

After seeding cells onto the 2D and 3D micropatterned ECM arrays, cellular and tissue properties, such as projected cell area and tissue form, can be observed by phase-contrast microscopy (see Fig. 2a, d). Likewise, samples can be fixed and stained for markers of interest. Here, as an example we describe the spatial distribution of phosphorylated extracellular signal-regulated kinase (ERK1 and ERK2) in 2D and 3D epithelial tissues. After treatment with epidermal growth factor (EGF), ERK1 and ERK2 are phosphorylated and are then translocated to the nucleus where they promote transcription of target genes of the mitogen-activated protein kinase (MAPK) signaling pathway.

Fig. 2. Two- and three-dimensional mammary epithelial tissue microarrays. (a) Phase-contrast image of 2D mammary epithelial tissue microarray. (b) Gray-scale fluorescence microscopy image of 2D tissue stained for phosphorylated ERK1/2. (c) Color-coded frequency map of nuclear localized phosphorylated ERK1/2 in 2D tissue. (d) Phase-contrast image of 3D mammary epithelial tissue microarray. (e) Gray-scale fluorescence microscopy image of 3D mammary tissue stained for phosphorylated ERK1/2. (f) Frequency map of total phosphorylated ERK1/2 in 3D mammary epithelial tubule. Scalebars: (a, d) 100 mm; (b, c, e, f ) 25 mm.

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1. Treat sample with 25 ng/mL EGF and place in an incubator for 15 min. 2. Remove sample from the incubator and aspirate media. Rinse the sample once with PBS. Aspirate the PBS and replace with fixative solution (4% paraformaldehyde in PBS). Incubate at room temperature for 15 min. Wash fixed samples three times with PBS. 3. Incubate in 0.5% IgePal CA 630 in PBS twice for 10 min each time. 4. Incubate in 0.1% TritonX-100 in PBS for 15 min at room temperature. 5. Block sample with blocking buffer for 2 h at room temperature. Rinse sample once with PBS. 6. Apply diluted primary antibody (1:500) and incubate overnight at 4°C. For 2D samples, rinse sample with PBS three times for 5 min. For 3D, rinse with PBS for 5 h at room temperature. 7. Apply diluted secondary antibody (1:1,000). Incubate for 1–2 h at room temperature in the dark or overnight at 4°C for 2D and 3D tissues, respectively. For 2D samples, rinse sample with PBS three times for 5 min. For 3D, rinse with PBS for 5 h at room temperature. 8. Apply diluted nuclear stain (1:10,000) and incubate for 20 min at room temperature. Rinse sample with PBS. Mount samples on cover slides. 9. Observe and image using a fluorescence microscope. Take 50 images of tissues that have been aligned using the eyepiece or a stage micrometer on a fluorescence microscope. 10. Using an image analysis software convert gray-scale images into black-and-white images using binarize function. 11. Add the black-and-white images together. 12. Convert the gray-scale image into a color-coded frequency map using the Indexed Color mode in Photoshop (see Fig. 2c, f).

4. Notes 1. Silicon masters can be silanized to aid in removal of the PDMS. Place the master in a vacuum dessicator with a glass slide containing a drop of (tridecafluoro-1,1,2,2,tetrahydrooctyl)-1-tricholorosilane (Sigma-Aldrich). Evacuate the chamber. After 1–2 min isolate the chamber and allow for vapor silanization reaction to proceed for 2 h. Alternatively, a PDMS master can be made from the silicon master. First create a PDMS master with posts from the silicon wafer.

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Silanize the PDMS master as described above. Use PDMS master with posts to make a PDMS master with holes. 2. Observe samples every half hour to determine when cells begin to adhere to ECM islands. The concentration of plated cells and the plating time can be modified to best achieve desired number of cells per island. 3. Stamps can be incubated overnight with BSA at 4°C. 4. The neutralized collagen solution can be quickly spun down in a centrifuge to remove air bubbles, if needed.

Acknowledgments This work was supported by grants from the NIH (CA128660 and GM083997), Susan G. Komen for the Cure (FAS0703855); and the David & Lucile Packard Foundation. C.M.N. holds a Career Award at the Scientific Interface from the Burroughs Wellcome Fund. E.W.G. was supported by post doctoral fellowships from the New Jersey Commission on Cancer Research and Susan G. Komen for the cure. References 1. Langer, R., and Vacanti, J. P. (1993) Tissue engineering. Science 260, 920–926. 2. O’Neill, C., Jordan, P., and Ireland, G. (1986) Evidence for two distinct mechanisms of anchorage stimulation in freshly explanted and 3t3 swiss mouse fibroblasts. Cell 44, 489–496. 3. Chen, C. S., Mrksich, M., Huang, S., Whitesides, G. M., and Ingber, D. E. (1997) Geometric control of cell life and death. Science 276, 1425–1428. 4. Whitesides, G. M., Ostuni, E., Takayama, S., Jiang, X., and Ingber, D. E. (2001) Soft lithography in biology and biochemistry. Annu. Rev. Biomed. Eng. 3, 335–373. 5. Nelson, C. M., Jean, R. P., Tan, J. L., Liu, W. F., Sniadecki, N. J., Spector, A. A., and Chen, C. S. (2005) Emergent patterns of growth controlled by multicellular form and mechanics. Proc. Natl. Acad. Sci. USA 102, 11594–11599. 6. Tien, J., Nelson, C. M., and Chen, C. S. (2002) Fabrication of aligned microstructures with a single elastomeric stamp. Proc. Natl. Acad. Sci. USA 99, 1758–1762. 7. Jeon, N. L., Dertinger, S. K. W., Chiu, D. T., Choi, I. S., Stroock, A. D., and Whitesides, G. M.

8.

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11. 12.

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(2000) Generation of solution and surface gradients using microfluidic systems. Langmuir 16, 8311–8316. Ostuni, E., Kane, R., Chen, C. S., Ingber, D. E., and Whitesides, G. M. (2000) Patterning mammalian cells using elastomeric membranes. Langmuir 16, 7811–7819. Flaim, C. J., Chien, S., and Bhatia, S. N. (2005) An extracellular matrix microarray for probing cellular differentiation. Nat. Methods 2, 119–125. Wilson, D. L., Martin, R., Hong, S., CroninGolomb, M., Mirkin, C. A., and Kaplan, D. L. (2001) Surface organization and nanopatterning of collagen by dip-pen nanolithography. Proc. Natl. Acad. Sci. USA 98, 13660–13664. Jackson, B. L., and Groves, J. T. (2007) Hybrid protein-lipid patterns from aluminum templates. Langmuir 23, 2052–2057. Nguyen, K. T., and West, J. L. (2002) Photopolymerizable hydrogels for tissue engineering applications. Biomaterials 23, 4307–4314. Tsang, V. L., Chen, A. A., Cho, L. M., Jadin, K. D., Sah, R. L., DeLong, S., West, J. L., and

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Gomez and Nelson Bhatia, S. N. (2007) Fabrication of 3d hepatic tissues by additive photopatterning of cellular hydrogels. Faseb J. 21, 790–801. Tang, M. D., Golden, A. P., and Tien, J. (2003) Molding of three-dimensional microstructures of gels. J. Am. Chem. Soc. 125, 12988–12989. Tang, M. D., Golden, A. P., and Tien, J. (2004) Fabrication of collagen gels that contain patterned, micrometer-scale cavities. Adv. Mater. 16, 1345–1348. Nelson, C. M., Vanduijn, M. M., Inman, J. L., Fletcher, D. A., and Bissell, M. J. (2006) Tissue geometry determines sites of mammary branching morphogenesis in organotypic cultures. Science 314, 298–300. Fukuda, J., Khademhosseini, A., Yeo, Y., Yang, X. Y., Yeh, J., Eng, G., Blumling, J., Wang, C. F., Kohane, D. S., and Langer, R. (2006) Micromolding of photocrosslinkable chitosan hydrogel for spheroid microarray and cocultures. Biomaterials 27, 5259–5267. Nelson, C. M., Inman, J. L., and Bissell, M. J. (2008) Three-dimensional lithographically defined organotypic tissue arrays for quantitative analysis of morphogenesis and neoplastic progression. Nat. Protoc. 3, 674–678.

19. Jongpaiboonkit, L., King, W. J., Lyons, G. E., Paguirigan, A. L., Warrick, J. W., Beebe, D. J., and Murphy, W. L. (2008) An adaptable hydrogel array format for 3-dimensional cell culture and analysis. Biomaterials 29, 3346–3356. 20. Fukuda, J., Khademhosseini, A., Yeh, J., Eng, G., Cheng, J. J., Farokhzad, O. C., and Langer, R. (2006) Micropatterned cell co-cultures using layer-by-layer deposition of extracellular matrix components. Biomaterials 27, 1479–1486. 21. Bettinger, C. J., Weinberg, E. J., Kulig, K. M., Vacanti, J. P., Wang, Y. D., Borenstein, J. T., and Langer, R. (2006) Three-dimensional microfluidic tissue-engineering scaffolds using a flexible biodegradable polymer. Adv. Mater. 18, 165–169. 22. Golden, A. P., and Tien, J. (2007) Fabrication of microfluidic hydrogels using molded gelatin as a sacrificial element. Lab Chip 7, 720–725. 23. Tan, J. L., Liu, W., Nelson, C. M., Raghavan, S., and Chen, C. S. (2004) Simple approach to micropattern cells on common culture substrates by tuning substrate wettability. Tissue Eng. 10, 865–872.

Chapter 6 Ratiometric Lectin Microarray Analysis of the Mammalian Cell Surface Glycome Ku-Lung Hsu, Kanoelani Pilobello, Lakshmipriya Krishnamoorthy, and Lara K. Mahal Abstract The mammalian cell surface is rich with carbohydrate polymers involved in a diversity of biological recognition events. Dynamic alterations of surface glycans mediate cell–cell communication in the immune system and host specificity of bacterial and viral pathogens. In addition, altered surface glycosylation has been implicated in disease progression of many cancers and may serve as important new targets for therapeutics. Despite the importance of glycosylation, the systematic analysis of sugars, i.e., glycomics, has lagged behind the well-studied disciplines of genomics and proteomics. This deficiency is due in part to the unique analytical challenges presented by glycans and the overwhelming diversity of sugars in nature. New microarray technologies have provided a high-throughput methods with which to probe the glycome. Our laboratory has pioneered a shown ratiometric two-color lectin microarray method that rapidly evaluates differences in the glycosylation of mammalian cells. Herein, we present a detailed protocol of our lectin microarray methodology for the differential analysis of mammalian glycomes. Key words: Lectin, Microarray, Glycomics, Carbohydrate, Glycan, Glycosylation, Cancer, Pathogen, Differentiation

1. Introduction The cell surface is a densely packed assortment of glycosylated proteins and lipids that function in a myriad of biological processes. The carbohydrate motifs embedded within these complex polymers encode information that mediate many biological events including cell–cell interactions, differentiation, and the host tropism of pathogens (1). Unlike proteins and nucleic acids, carbohydrates exist as both linear and branched polymers that can differ in the linkages between monomers and in the anomeric stereochemistry, in addition to varying in monomer Ali Khademhosseini et al. (eds.), Biological Microarrays: Methods and Protocols, Methods in Molecular Biology, vol. 671, DOI 10.1007/978-1-59745-551-0_6, © Springer Science+Business Media, LLC 2011

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composition, resulting in enormous structural diversity. These issues pose a challenge to the high-throughput profiling of glycosylation, a critical element in the systems-level study of glycosylation, i.e., glycomics (2, 3). In response, we have developed lectin microarray technology that utilizes the innate ability of natural carbohydrate-binding proteins to recognize complex glycan motifs, as a rapid method for glycan analysis and applied it to the glycomic characterization of glycoproteins, bacteria, and mammalian cells (4–8). Lectin microarrays consist of a series of carbohydrate-binding proteins (lectins) immobilized onto a glass slide as high density spots in a defined layout. Hybridization of fluorescently labeled samples to the microarray gives a visual binding pattern that provides structural information about the glycosylation status of samples. We have recently extended this technology to the characterization of mammalian cell surface glycans using a sensitive ratiometric method (Fig. 1) (8). Hybridization of fluorescently labeled cell membrane-derived micellae against an orthogonally labeled biological reference sample allows the comparison of samples across multiple slides and examination of subtle differences in glycosylation between samples. This ratiometric lectin microarray approach has the advantage of increased resolution and improved quality control for the differential analysis of mammalian glycomes (8).

4 3 WGA

2 Log2 (PC / L8 Ratio)

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1 ConA

HPA

–1 –2 –3 –4

Fig. 1. Schematic of a ratiometric lectin microarray experiment (from (8)). Orthogonally labeled cellular samples are hybridized to a subarray on a slide. The comparative lectin binding pattern of the sample allows us to elucidate the relative level of glycan epitopes present in the cellular membrane.

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2. Materials 2.1. Manufacture of Lectin Microarray

1. Commercially available lectins (E.Y. Labs, San Mateo, CA and Vector Labs, Burlingame, CA). 2. Nexterion Slide H (Schott, North America, Elmsford, NY). Slides should be stored at −20°C in a dessicator. 3. Spotbot Arrayit Microarrayer with SMP3 pins (Telechem International, Sunnyvale, CA). 4. 384-well plates. 5. Standard centrifuge with adapters to spin 384-well plates (same outer dimensions as a standard 96-well plate).

2.2. Sample Preparation

1. 0.5 M Ethylenediaminetetraacetic acid (EDTA, in ddI H2O, pH 8). 2. PBS (0.1 M NaH2PO4, 0.15 M NaCl, pH 7.2–7.4). 3. Cell sonicator with 1/8″ microtip horn (Branson Inc, Danbury, CT). 4. Ultracentrifuge (either tabletop or floor model). 5. Cy dye buffer (0.1 M NaCO3 in H2O, pH = 9.3). A stock buffer may be made but the pH will change over time and will need adjustment. 6. 25-Gauge needle, 1-mL plastic syringe. 7. DC protein assay (Bio-Rad, Hercules, CA).

2.3. Dye Conjugation

1. NHS-Cy3 or -Cy5 dye (GE Healthcare Life Sciences, Piscataway, NJ). This reagent is light sensitive and should be stored at 4°C. 2. Slide-A-Lyzer cassette (Pierce, Rockford, IL).

2.4. Hybridization and Scanning

1. Blocking reagent (50 mM ethanolamine in 50 mM sodium borate, pH 8.0). 2. PBST (PBS, 0.005% Tween-20). 3. Ovalbumin, porcine mucin (Sigma, St. Louis, MO). These should be stored at 4°C. 4. Coplin jars. 5. Hybridization cassettes (1 × 24 configuration, Telechem International). 6. Slide spinner (Labnet International, Edison, NJ) or a standard floor centrifuge with slide rack adaptors may be used. 7. GenePix 4000B scanner (Molecular Devices, Sunnyvale, CA).

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3. Methods Our current lectin microarray consists of commercially available lectins that are mainly plant derived. We have also now included some recombinant lectins of bacterial origin (4). All lectins are printed at concentrations optimized to give a minimum signal of 1,000 arbitrary fluorescence units (A.U.) under fixed scanning conditions with glycoprotein standards. Each slide provides 24 total subarrays of which at least two need to be used for quality control hybridizations with glycoprotein standards. This adds an important level of quality control that can help identify inactive and misprinted lectins. In addition, all lectins are printed in multiple replicates ensuring more precise measurement of lectin activity. 3.1. Lectin Microarray Print Procedure

1. Remove Nexterion H slides from −20°C freezer, and let thaw to room temperature before use. 2. Dilute lectins to the recommended concentration in the appropriate print buffer (see Table 1 and Note 1). Load 10 ml of each lectin mixture into a 384-well plate in the desired order and centrifuge the plate at 50 × g for 5 min prior to use. 3. To ensure consistent print quality, the SMP3 pins should be cleaned before each use. Place pins in a floatable pin rack, and sonicate for 5 min in an ultrasonic water bath filled with 5% Micro Cleaning Solution (Telechem International, Inc.). Sonicate the pins for an additional 5 min in distilled water. Remove and dry pins (see Note 2). 4. The printhead on the Spotbot Microarrayer should also be cleaned before each use. Prepare 50 mL of hot (65°C) printhead cleaning solution (Telechem International, Inc.). Scrub extensively the outer surface and pin-holes of the printhead using a brush. Rinse the printhead extensively with distilled water and dry with forced air (see Note 3). 5. Insert the pin carefully into the printhead, and test the movement of the pin in the printhead by pushing the pin up and down several (5–10) times (see Note 4). 6. Turn on the Spotbot and all accessory devices. Open the Multiple Microarray Format SpoCLe Generator and select the desired print configuration (see Note 5). 7. Insert the preprint slide(s), the Nexterion H slide(s), and the 384-well plate loaded with lectin mix (see Note 6). 8. Check the humidity of the print chamber. Ideally, the humidity should be kept around 50–60% during the entire print process.

500 1,000 1,000 500 500 500

500 500 500 500 1,000 500 500 500 500

ABA AAL AAA PNA AIA BPA Blackbean BDA Con A CCA CAA CPA CA CSA CVN DSA

Agaricus bisporus

Aleuria aurantia

Anguilla anguilla

Arachis hyogaea

Artocarpus intergrifolia (Jacalin)

Bauhinia purpurea

Black bean crude

Bryonia dioica

Canavalia ensiformis

Cancer antennarius

Caragana arborescens

Cicer arietinum

Colchicum autumnale

Cystisus scoparius

Cyanovirin

Datura stramonium

1,000

500

APA

Abrus precatorius

[Print] mg/mL

Abbreviation

Lectin

Table 1 Panel of lectins in microarray

Lactose

Mannose

Galactose

Galactose

Lactose

Galactose

Lactose

Mannose

Galactose

Lactose

Galactose

Galactose

Galactose

Fucose

Fucose

Galactose

Galactose

Carbohydrates

(continued)

GlcNAcb-1,4GlcNAc oligomers and LacNAc

a-1,2 Mannose

b-GalNAc, terminal

Terminal Gal b-OR

Complex

GalNAc/Gal (monosaccharides best)

9-O-Acetyl Sia and 4-O-Acetyl Sia

Branched and terminal mannose, terminal GlcNAc

GalNAc

GalNAc

Primarily Gal b-1,3 or 1,4 but will also bind b-GalNAc more weakly

a-GalNAc

Terminal Gal b-OR

a-Fuc

Fuc

Gal b-1-3GalNAc

Gal b-1,3GalNAc (TF antigen) > Gal

Rough specificity a

Ratiometric Lectin Microarray Analysis of the Mammalian Cell Surface Glycome 121

500 1,000 1,000 500 2,500 500 1,000 500 500 500 1,000 500 500 500 1,000 500 500 500 1,000 1,000

DBA ECA EEA GNA Gal-1 SBA GRFT GS-I GS-II HPA HHL HMA IAA LAA LcH LFA LPA LTL LEA MAA-I

Dolichos biflorus

Erythrina cristagalli

Euonymus eurpaeus

Galanthus nivalis

Galectin-1

Glycine max

Griffithsin

Griffonia simplicifolia I

Griffonia simplicifolia II

Helix pomatia

Hippeastrum hybrid

Homaris americanus

Iberis amara

Laburnum alpinum

Lens culinaris

Limax flavus

Limulus polphemus

Lotus tetragonolobus

Lypersicon esculentum

Maackia amurensis

[Print] mg/mL

Abbreviation

Lectin

Table 1 (continued)

Lactose

GlcNAc

Fucose

Lactose

Lactose

Mannose

GlcNAc

Lactose

Lactose

Mannose

Galactose

GlcNAc

Galactose

GlcNAc

Galactose

Lactose

Mannose

Lactose

Galactose

Galactose

Carbohydrates

LacNAc

b-1,4GlcNAc oligomers

Terminal a-Fuc, Lex

a-Sia

a-Sia

Complex (man/GlcNAc core with a-1,6 Fuc)

GlcNAc oligomers

GalNAc

Sialic acid

a-1,3 Mannose and a-1,6 mannose

a-GalNAc terminal

Terminal GlcNAc

a-Galactose

Mannose, GlcNAc

Terminal GalNAc

LacNAc

Terminal a-1,3 mannose

Blood Groups B and H

LacNAc and GalNAc

GalNAca-OR

Rough specificity a

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1,000 500 1,000 500 1,000 500 500

500 500 1,000 1,000 1,000 1,000 500 500 500 1,000 500 500

MAA-II MAA NPA PAA LBA PHA-E PHA-L PEA, PSA PSL PTA galactose PTL-I PTL-II RCA RPA SNA SVN STA SJA TKA RTA

Maackia amurensis

Maackia amurensis

Narcissus pseudonarcissus

Persea americana

Phaseolus lunatus

Phaseolus vulgaris-L

Phaseolus vulgaris-L

Pisum sativum

Polyporus squamosus

Psophocarpus tetragonolobus



Ricin B chain

Robinia pseudoacacia

Sambucus nigra

Scytovirin

Solanus tuberosum

Sophora japonica

Trichosanthes kirilowii

Trifolium repens

1,000

[Print] mg/mL

Abbreviation

Lectin

GlcNAc

Galactose

Galactose

GlcNAc

Mannose

Lactose

Lactose

Lactose

Galactose

Galactose

Galactose

Lactose

Mannose

Galactose

Lactose

Galactose

GlcNAc

Mannose

Lactose

Lactose

Carbohydrates

2-Deoxy-Glu (continued)

b-Gal, LacNAc but Sia-a-2,3 or 2,6 inhibits best

GalNAc

GlcNAc oligomers, LacNAc

a-1,2 Mannose

a-2,6 Sialic acid on LacNAc

Complex

b-Gal/GalNAc

a-1,2 Fucosylated LacNAc

a-GalNAc

Gal

a-2,6 Sialic acid

Man

b-1,6 Branched trimannosyl core N-linked glycans

Complex

GalNAca-1,3[Fuca-1,2]Gal

Unknown

Terminal and internal Man

a-2,3 Sialic acid

a-2,3 Sialic acid

Rough specificity a

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1,000 1,000 500 500 500 500 500 500 500 500

WGA TL UEA UEA-II UDA VFA VGA VVA VVA (man) WFA

Tritiicum vulgare

Tulipa sp.

Ulex europaaeus I

Ulex europaaeus II

Uritica dioica

Vicia fava

Vicia graminea

Vicia villosa

Vicia villosa

Wisteria floribunda

Galactose

Galactose

Galactose

Galactose

Galactose

GlcNAc

GlcNAc

Fucose

GlcNAc

GlcNAc

Carbohydrates

GalNAc

Man

GalNAc

O-linked Gal b-1,3GalNAc clusters

Man > Glc > GlcNAc

GlcNAc b-1,4GlcNAc oligomers and high mannose epitopes

GlcNAc oligomers

a-Fucose

GlcNAc

b-GlcNAc, sialic acid, GalNAc

Rough specificity a

a Specificity shown is very rough and was obtained from a variety of sources including the Consortium for Functional Glycomics Carbohydrate Array Analysis and the Handbook of Plant Lectins (1998, Wiley and Sons)

[Print] mg/mL

Abbreviation

Lectin

Table 1 (continued)

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A humidity control device may be used to maintain the appropriate relative humidity (see Note 7). 9. Turn on the cooling plate and set the temperature to ~8°C. This is important to help maintain lectin activity during extended and overnight prints. 10. Once the temperature and humidity have reached the desired parameters, start the printing process. Periodically monitor the printing process to make sure that everything is functioning properly. 11. After the printing process has finished, turn off the cooling plate and allow the slides to remain in the chamber for 1 h at ~50% relative humidity. This helps to ensure maximum coupling efficiency. 12. Once printed, slides can be stored at −20°C in moisture barrier bags. In our hands, these arrays are stable for up to 2 weeks, without any noticeable decreases in lectin activity. 3.2. Preparation of Micellae

The isolation of membrane glycoproteins and glycolipids for ratiometric lectin microarray analysis requires harvesting of cells without the use of proteases or detergents. Trypsin, a common protease used in cell cultures, has been shown to preferentially bind N-linked glycoproteins, potentially biasing the glycan pools. Detergents solubilize glycolipids leading to samples that do not accurately represent the glycome. Thus, our protocol avoids the use of both reagents, forming micellae from the physical disruption of membranes. Previous work has shown no significant differences in the lectin binding patterns from cells labeled prior to or after lysis, validating that our micellae accurately represent cellsurface glycans (8). In addition, the presence of glycolipids in our micellae samples was verified by TLC, followed by resorcinol staining for sialic acids that are a major component of gangliosides. 1. Adherent cells should be harvested without trypsin, which cleaves cell surface glycans in a biased manner. Cells are incubated with 0.5 M EDTA for 15 min at room temperature and harvested with a cell scraper. 2. Suspension or adherent cells are centrifuged at 200 × g for 10 min at 4°C. A pellet should form at the bottom. The samples should be kept at 4°C (i.e., on ice) from this point onward. 3. Cells are resuspended in cold PBS at a concentration of 3–10 million cells per 3 mL of PBS. 4. Using a cell sonicator with a 1/8 in. microtip, sonicate the cells in 5 s pulses with 10 s intervals at 70% power. Sonication homogenizes the cell membranes creating micellae. While this may include organellar membranes, we have validated that the glycomic composition of these samples match that of the surface via lectin histology (Fig. 2, see Note 8).

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Fig. 2. Comparison of Yang Correlation data from cellular micellae to fluorescence microscopy. (a) Comparative Yang Correlation data derived from a dye-swapped pair of lectin microarrays are shown for ConA, HPA, and WGA binding to the Chinese Hamster Ovary cells Pro-CHO 5 (Pro-5) and Lec8 (adapted from (8)). Green indicates stronger binding to Pro-5, while red indicates stronger binding to Lec8. (b) Fluorescence microscopy confirms that data obtained by microarray methods are accurate to the cell surface (8).

5. Micellae are pelleted at 100,000 × g for 60 min in an ultracentrifuge. The supernatant should be removed immediately after centrifugation to maintain the integrity of the pellet. 6. The pellet is resuspended in 250–500 mL of Cy dye buffer and homogenized by passing it through a 25-gauge needle as many times as necessary, typically 10× (see Note 9). 7. After homogenization, the protein concentration of the samples is determined using the DC protein assay.


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1. It is important to make sure that sample labeling is consistent. For every milligram of protein, we use 60 mg of the appropriate NHS-Cy dye. 2. Incubate the samples with Cy dye for 45 min at room temperature in the dark (i.e., covered in foil). 3. After 45 min, the dyed samples are dialyzed. The most effective dialysis method is to use the Slide-A-Lyzer cassettes. However, for multiple samples, this can be highly time consuming. An alternative is to use the Pierce mini-dialysis units. These are more effective for sample volumes under 100 ml (see Note 10). 4. Float the dialysis units in 2 L of PBS at 4°C and stir on low in the dark to prevent loss of fluorescence. 5. The dialysis buffer should be changed once after 30 min, and the samples should then dialyze overnight at 4°C in the dark. 6. After dialysis, sample concentrations can be redetermined by the DC assay to check for protein loss. Labeled samples should be immediately aliquotted and snap frozen in liquid nitrogen for storage in the dark at −20°C.

3.4. Hybridization of Samples and Scanning

1. The printed slide is allowed to come to room temperature for approximately 10–15 min. 2. The slide is gently immersed in blocking solution for 1 min, with the printed side facing down. 3. The slide is then slowly immersed in a coplin jar filled with blocking solution. The ethanolamine reacts with the free, unreacted sites on the slides, preventing them from binding nonspecifically to proteins. 4. The slide is blocked for 1 h at room temperature on the benchtop. 5. After 1 h, the blocking solution in the coplin jar is discarded and replaced with a solution of PBST. The slide is rinsed gently with PBST by carefully swirling the coplin jar. The slides are gently rinsed 3× with PBST, followed by a final rinse with PBS. 6. The slide is then dried using a slide spinner for 30 s. It is important to ensure that the slide is dry prior to use. 7. The slide is fitted tightly within the hybridization cassette. 8. The samples are diluted in PBST to obtain the desired sample concentrations (see Note 11) and are carefully added to each subarray at one corner in such a way that liquids are not pipetted directly over the printed array (see Note 12). For single-color experiments, a unique Cy3- or Cy5- labeled sample is added to each subarray. For ratiometric dual-color

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experiments, two differentially labeled samples are added to a single subarray in equal amounts. For example, equal amounts of Cy3- labeled sample A and Cy5- labeled sample B are added to the same subarray (Fig. 1). 9. For dye-swap experiments, two subarrays are used for the analysis of orthogonally labeled pair of analytes. For example, equal amounts of Cy3- labeled sample A and Cy5- labeled sample B are added to one subarray, while equal amounts of Cy3- labeled sample B and Cy5- labeled sample A are added to another subarray. 10. For every array, two subarrays are used to ensure quality control of the lectin microarray. Typically, 10 mg of Cy3- or Cy5labeled glycoproteins with known glycosylation patterns, such as ovalbumin or porcine mucin, are used for this purpose. 11. The samples are hybridized to the array for 2 h with gentle rocking on a shaker. The array is covered with aluminum foil to protect the samples from light (see Note 13). 12. After 2 h, the samples are carefully removed from the array using a pipette (a multichannel pipetter works well for this). 13. The arrays are rinsed by addition of 200 mL of PBST to each array and gently rocking on a shaker for 5 × 3 min. 14. Any residual liquid is removed after the last wash, the slide is carefully removed from the cassette and immersed in a coplin jar with PBS. The slide is rinsed in PBS for 5 min on a shaker. 15. The slide is then dried using a slide spinner and scanned using a GenePix 4000B scanner (see Note 14). 3.5. Single Color and Ratiometric Analysis

Data from the microarray are extracted using a standard fluorescent slide scanner and image analysis software. For single color analysis, signals are considered positive if the signal to noise ratio is greater than 5. For ratiometric analysis, single color analysis of the two samples is used to determine positive signals. Outlier points are determined using the Grubbs outlier test at the 95% confidence interval to account for experimental variations (www.graphpad.com). For ratiometric two-color analysis, Yang’s correlations are calculated to compensate for dye bias, and hierarchical clustering allows comparison between sample sets. The carbohydrate composition of samples is inferred using the carbohydrate specificity profiles of lectins obtained from the Consortium for Functional Glycomics (www.functionalglycomics.org) and literature. 1. The spots on the scanned slide image are aligned and segmented in GenePix Pro 5.1 (or above) with circular alignment and local background subtraction.


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2. The data are exported to a .txt file and imported into Microsoft Excel as a tab delimited file. 3. We currently use the single color signal to noise (S/N) data as a reference for positive signals. Signal to noise is calculated from the median signal (S, not background subtracted) and the median local background (N). We consider signals with S/N > 5 to be positive (see Note 16). 4. Yang’s correlations are calculated for ratiometric data using two dye-swapped arrays. The median background subtracted fluorescence values are used (e.g., “F635-B median” column in GenePix for Cy5). The background subtracted fluorescence data are tested for outliers using the Grubbs outlier test (www.graphpad.com). The remaining values are transformed to Log base 2 values and averaged. We then perform the following operation: [(Log2 (Cy5 Cell B signal) − Log2 (Cy3 Cell A signal)) − (Log2 (Cy3 Cell B signal) − Log2 (Cy5 Cell A signal))]/2, which is the equivalent of taking the average of the log2 ratios for the dye swapped pair (the Yang’s correlation, 9, see Note 17). 5. We compare samples by hierarchically clustering the results in Cluster (10) using centered Pearson correlation as a distance metric and average linkage analysis. The significance of a node value can be determined by comparing the correlation coefficients to the p-values.

4. Notes 1. Lectins are resuspended in PBS or the supplier’s recommended buffer at concentrations of 1 mg/mL. Some lectins may need to be rocked gently overnight to completely resuspend. Lectins are aliquoted (10–20 ml), snap frozen in a liquid nitrogen bath, and stored for up to 1 year at −80°C. 2. When cleaning the SMP3 pins, do not use forced air on the pin tip as it may result in damage. It is okay to dry the base of the pin using forced air. Also, be careful not to drop the pin as it will need to be replaced. 3. When cleaning the printhead, be sure that it is completely dry before inserting the pin. Any leftover moisture can cause the pin to get stuck during the printing process resulting in misprints. 4. When testing the movement of the pin in the printhead, cover the pin with the supplied sheath to prevent damage to the pin tip. Never move the pin by pushing on the pin tip.

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5. When using the Multiple Microarray Format SpoCLe Generator program, be sure to adjust the offsets so that there is space between lectins and the subarray edges. If the lectins are printed too close to the edges, the SuperMask frame (Telechem International, Inc.) may contact the lectins. 6. Preprint slides can be plain glass slides or old slides that have been cleaned. 7. When using a humidity controller, be sure to allow the sensor to adjust to the humidity in the chamber for ~45 min before beginning to print. 8. During sample sonication, it is important that the samples are either on ice during or immediately following sonication because the samples can overheat. 9. After pelleting the cellular micellae, the homogenization of the sample is much easier to do immediately after centrifugation. We have not seen differences in lectin microarray signals with samples stored over night at 4°C. However, the homogenization is more difficult. 10. During sample dialysis, we have found that making sure the mini-dialysis units are flush with the floater and not pressed too deeply or unevenly results in homogenously dialyzed samples. While this method is easier to work with for large sets, it is less reliable. 11. For cellular micellar samples, we typically use 10 mg of each labeled sample per subarray in 100 mL total volume (diluted with PBS), though lesser amounts (~1–3 mg) have been used successfully in our lab. 12. Care should be taken during the addition of samples or during rinses to avoid pipetting liquids directly on the printed part of the array. Usually, an empty corner of the subarray is used for this purpose. 13. The fluorescent samples should be protected from light during the entire procedure using aluminum foil. 14. It is important to ensure that the slide is dry in all the steps that utilize the slide spinner. 15. For analyzing the specificity of our lectin microarray, inhibition experiments are performed with a small panel of carbohydrates including mannose, galactose, N-acetyl glucosamine, fucose, and lactose. The array is preincubated with the inhibitory sugars for 30 min, followed by the addition of the sample. 16. In data analysis using signal to noise ratios, occasionally, a trend in background affects the S/N. For example, the background may increase as with the rows in each subarray. Care should be taken in the washes by aspirating wash buffer from


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each side of the well, if possible. Background trends and anomalies in general should be considered when comparing data and trying to validate dual color data. 17. The single color S/N values should be used to help exclude ratiometric data on nonpositive lectins. Because the ratiometric data are a ratio, spurious values are obtained when the lectins are not positive.

References 1. Gabius, H. J., Siebert, H. C., Andre, S., Jimenez-Barbero, J., and Rudiger, H. (2004) Chembiochem 5, 740–64. 2. Mahal, L. K. (2008) Anticancer Agents Med Chem 8, 37–51. 3. Raman, R., Raguram, S., Venkataraman, G., Paulson, J. C., and Sasisekharan, R. (2005) Nat Methods 2, 817–24. 4. Hsu, K. L., Gildersleeve, J. C., and Mahal, L. K. (2008) Mol Biosyst 4, 654–62. 5. Hsu, K. L., and Mahal, L. K. (2006) Nat Protoc 1, 543–9.

6. Hsu, K. L., Pilobello, K. T., and Mahal, L. K. (2006) Nat Chem Biol 2, 153–7. 7. Pilobello, K. T., Krishnamoorthy, L., Slawek, D., and Mahal, L. K. (2005) Chembiochem 6, 985–9. 8. Pilobello, K. T., Slawek, D. E., and Mahal, L. K. (2007) Proc Natl Acad Sci USA 104, 11534–9. 9. Yang, Y. H., Dudoit, S., Luu, P., Lin, D. M., Peng, V., Ngai, J., and Speed, T. P. (2002) Nucleic Acids Res 30, e15. 10. Eisen, M. B., Spellman, P. T., Brown, P. O., and Botstein, D. (1998) Proc Natl Acad Sci USA 95, 14863–8.

Chapter 7 Cell Microarrays Based on Hydrogel Microstructures for the Application to Cell-Based Biosensor Won-Gun Koh Abstract Cell-based biosensors constitute a promising field that has numerous applications ranging from pharmaceutical screening to detection of pathogen and toxicant. The trends toward miniaturization of cell-based biosensor continue to spur development of cell microarray integrated into microfluidic devices. For cellbased biosensors to be useful for larger applications, several technical goals must be realized. First, the cell-patterning method used to generate multi-phenotypic array can accommodate multiple cell lines without major losses of cell viability, maintain total isolation of each cell phenotype, provide for the adequate mass transfer of dissolved gases and nutrients, and easy enough to allow for mass production. Second, cells on microarray must be cultured in three-dimensional environment as they do in real tissue to obtain accurate response of cells against target analyte. Third, physiological status of micropatterned cells must be monitored non-invasively. As one solution to satisfy these requirements, we prepare cell microarrays using microfabricated poly(ethylene glycol)(PEG) hydrogel. Arrays of hydrogel microstructures encapsulating one or more different cell phenotypes can be fabricated using photolithography or photoreaction injection molding, and can be incorporated within microfluidic network. Finally, we demonstrate the potential application of cell-containing hydrogel microarrays for toxin detection by monitoring toxin-induced change of cell viability and intercellular enzymatic reaction. Key words: Cell-based biosensor, Cell microarray, Hydrogel microstructures, Microfluidic devices, Cell encapsulation, Microfabrication

1. Introduction Cell-based biosensors are devices that use living cells as the biorecognition elements to detect a broad range of agents and have been receiving attention recently because of potential applications of high content drug screening and detection of biological warfare agents and pathogens (1). Of particular importance is the application of cell-based biosensor to drug screening, Ali Khademhosseini et al. (eds.), Biological Microarrays: Methods and Protocols, Methods in Molecular Biology, vol. 671, DOI 10.1007/978-1-59745-551-0_7, © Springer Science+Business Media, LLC 2011

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because cells represent the ultimate target for pharmaceuticals (2). In these cell-based biosensors, analytes (i.e., drug candidates) act on immobilized cells, and physiological changes such as cell metabolism and viability are detected by electrochemical or optical methods. Although cell-based systems often exhibit a long response time and poor selectivity, they have several advantages over other biosensor based on enzymes or antibodies, including extremely good sensitivity, the ability to detect large number of analytes and the easiness of growing and isolating sensing components (i.e., the cells). The most distinct advantage of cell-based systems over conventional biosensor system is that they can offer functional information, i.e., information about the effects of stimulus on a living system, which includes the effects of stimuli on cell death (toxicity) as well as cell function. Currently, most of the cell-based assays are still being performed out in 96-well plates; however, the move toward higher density plate format and system miniaturization is essential to improve the performance or functionality of cell-based biosensor systems (3). To move toward assay miniaturization, significant efforts have focused on the fabrication of cell microarray using a variety of cell-patterning techniques such as photolithography or soft lithography (4–17). Cell microarray are being coupled with fluorescent or electrochemical technologies and incorporated into microfluidic devices to detect the physiological changes of cells by external environment (1). In most of these applications, anchorage-dependent cells are immobilized on a two-dimensional substrate. However, in a two-dimensional system, non-adherent cells are difficult to immobilize and adherent cells such as fibroblasts and hepatocytes are in an unnatural environment; i.e., in tissue they exist in a three-dimensional hydrogel matrix consisting of proteins and polysaccharides (i.e., the extracellular matrix). As a result, the response of these cells to target molecules may be very different than that of the same cells in their native tissue. One strategy to overcome the problems associated with a two-dimensional culture system is to encapsulate cells inside a three-dimensional hydrogel matrix. Originally, cell encapsulation technologies using hydrogels were developed for tissue engineering or therapeutic cell transplantation to prevent the rejection of transplanted cells by the host’s immune system. Hydrogels have been widely used because of their high water content, softness, pliability, biocompatibility, and easily controlled mass transfer properties, essential for allowing transport of nutrients to and waste products from cells (18–22). Recently, micropatterned hydrogels were prepared using microfabrication technique for the development of electrochemical and optical sensors (23, 24). Hydrogel micropattern could be also fabricated inside microfluidic devices for use as “smart” flow controllers or various sensor applications (25).

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In this chapter, we first describe the fabrication of cell microarray using poly(ethylene glycol)(PEG)-based hydrogel. Arrays of hydrogel microstructures encapsulating one or more different cell phenotypes can be fabricated using photolithography or photoreaction injection molding using microfluidic networks made from poly(dimethylsiloxane) (PDMS) (26–28). Next, we describe the incorporation and culture of hydrogel-encapsulated mammalian cells within microfluidic devices (29). Finally, investigation of viability and intracellular enzyme reactions of encapsulated cells is described as examples of cell-based assay systems that can potentially be used in biosensing application (29, 30).

2. Materials 2.1. Substrate Preparation

1. 3-(Trichlorosilyl)propyl methacrylate (TPM) (Fluka Chem.)

2.2. Microchannels for Injection Molding and Microfluidic Device

1. Silicon master, which has negative patterns of desired microchannels defined with SU-8 photoresist (Microlithography Chemical Corp.).

2.3. PEG Hydrogel Microarray

1. Poly(ethyelene glycol) diacrylate (PEG-DA) (MW 4,000) (Polysciences).

2. Hydrogel peroxide (30 wt% in water), sulfuric acid (30 wt% in water), carbon tetrachloride, and n-heptane.

2. PDMS (Sylgard 184, Dow Corning), which is composed of prepolymer and curing agent.

2. Acryloyl-PEG-n-hydroxysuccinimide ester (acryloyl-PEGNHS, MW 3,400) (Nektar). 3. Gly–Arg–Gly–Asp–Ser (GRGDS) peptide (CalBioChem). 4. 2-Hydroxy-1[4-(hydroxyethoxy)phenyl]-2-methyl-1-propanone (Ciba) as a photoinitiator. 5. Photomask (advanced reproductions). 2.4. Cell Culture

1. Murine 3T3 fibroblast, SV-40 transformed murine hepatocyte, and SV-40 transformed murine peritoneal macrophage cell (American Type Culture Collection). 2. Dulbecco’s modified Eagle’s medium (DMEM), RPMI 1640 medium, fetal bovine serum (FBS), antibiotic/antimycotic solution, dexamethasone, trypsin, ethylenediaminetetraacetate (EDTA), sodium chloride, sodium phosphate, and potassium phosphate monobasic (Sigma).

2.5. Fluorescence Detection

1. Calcein-AM (molecular probes). 2. Live/dead viability/cytotoxicity assay kit (molecular probes).

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2.6. E quipment

1. Oxygen plasma (Harrick Scientific Co.). 2. Syringe pumps (Harvard Inst.). 3. UV spot lamp (EXFO Corp.). 4. A Zeiss Axiovert 200 microscope equipped with an integrated color CCD camera (Carl Zeiss Inc.). 5. Image analysis software (KS 300, Carl Zeiss Inc.).

3. Methods In this section, we describe experimental protocol to create single or multi-phenotype cell microarrays by combining cell encapsulation and micropatterning process. First, cell-containing PEG hydrogel microarrays are fabricated on the TPM-modified glass substrates using photolithography or photoreaction injection. Mammalian cells encapsulated in PEG hydrogel microarray can be also prepared and grown under static culture conditions in microfluidic devices. Finally, encapsulated cells are examined for their response to the addition of model chemotoxins to demonstrate possible application of cell microarray to biosensor. The methods described outline the following: 1. Surface modification of glass substrate 2. Preparation of PDMS microchannel molds 3. Fabrication of cell-containing hydrogel microarray 4. Incorporation of cell microarray into microfluidic device 5. Toxin detection using cell microarray 3.1. Surface Modification of Glass Substrate

When PEG hydrogel microarrays are generated on glass substrate without surface modification, array elements are easily delaminated upon hydration due to swelling of the cross-linked PEG hydrogel. To prevent delamination, a self-assembled monolayer of TPM on glass is used to create a reactive surface onto which the gel is covalently affixed during photopolymerization (see Note 1). 1. Glass substrates are immersed in piranha solution, consisting of a 3:1 ratio of 30% sulfuric acid and 30% hydrogen peroxide (caution: this mixture reacts violently with organic materials and must be handled with extreme care), for 30 min at 80°C, washed with deionized water thoroughly and dried under nitrogen. 2. Substrates were then treated for 5 min, at room temperature, in a 1 mM solution of TPM in a 4:1 ratio of heptane–carbon tetrachloride in an N2 atmosphere, followed by washing with hexane and water.


3.2. Preparation of PDMS Microchannel Molds 3.2.1. Fabrication of Master Using SU-8 Photoresist on Silicon Wafer 3.2.2. Preparation of PDMS Mold

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1. SU-8 50 photoresist is spin-coated for 20 s at 2,000 rpm and baked for 20 min at 95°C on a horizontal hot plate. 2. Photoresist-coated wafers are then exposed to 365 nm UV light through the photomasks, which have designed microchannels, followed by post-bake at 95°C for 15 min. 3. Finally, dissolving away the unpolymerzied photoresist using developer leaves a positive relief that serves as a master. 1. PDMS precursor is prepared by mixing a PDMS prepolymer with curing agent in a 10:1 ratio by weight. 2. This mixture is poured onto the silicon master and then placed in vacuum desiccators to evacuate the bubbles created during mixing. 3. The PDMS is cured in an oven at 60°C for at least 2 h and the replica is peeled from the master. 4. Several holes are punched through PDMS replica using 16-gauge needle to access the microchannels. 5. PDMS replicas are treated with oxygen plasma for 1 min to change its hydrophobic surface to hydrophilic. 6. Oxidized PDMS microchannels are placed by hand on the TPM-modified glass to form an enclosed channel. Here, reversible, conformal sealing with TPM-modified glass surfaces was used. (These PDMS microchannel systems are used as mold inserts for photoreaction injection molding.)

3.3. Cell Culture

1. Murine fibroblasts are cultured in DMEM with 4.5 g/L glucose and 10% FBS. SV-40 transformed murine hepatocytes are cultured in DMEM containing 1.0 g/L glucose, 200 nM dexamethasone, and 4% FBS. Both phenotypes are grown to confluence in 75 cm2 polystyrene tissue culture flasks, and confluent cells are subcultured every 2–3 days by trypsinization with 0.25% (w/v) trypsin and 0.13% (w/v) EDTA. 2. SV-40-transformed murine macrophages are cultured in RPMI 1640 medium with 2 mM l-glutamine containing 1.5 g/L sodium bicarbonate, 4.5 g/L glucose, 10 mM HEPES, 1.0 mM sodium pyruvate, and 10% FBS. Confluent cells are subcultured every 2–3 days by cell scraping. 3. All cell lines are incubated at 37°C in 5% CO2 and 95% air.

3.4. Fabrication of Cell-Containing Hydrogel Microarray

Cell microarray is prepared by encapsulating mammalian cells inside hydrogel microarray to mimic in vivo environment where cells exist in a three-dimensional hydrogel matrix consisting of proteins and polysaccharides so that more accurate response of cells against analytes can be obtained. PEG hydrogel is modified

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with Arg–Gly–Asp (RGD) peptide sequence to promote adhesion and spreading of encapsulated cells. Two different methods are used to create hydrogel microarray. First method is using spincoating and photolithography, while second method is using photoreaction injection molding with microfluidic networks. 3.4.1. Preparation of Hydrogel Precursor Solution

1. Incorporation of the GRGDS peptide: the peptide is conjugated to PEG by reacting the peptide with acryloyl-PEGNHS. The peptide is dissolved to a final concentration of 1 mg/mL in culture media and then 10% w/v of acryloylPEG-NHS is dissolved in peptide solution and reacted at room temperature for at least 2 h (see Note 4). 2. Final precursor solution is prepared by adding 10% w/v of PEG-DA and 0.1% v/v 2-hydroxy-1-[4-(hydroxyethoxy) phenyl]-2-methyl-1-propanone in ethanol as photoinitiator to solution containing acrylated peptide (see Notes 2 and 3). 3. The solution is sterilized by filtration and added to cell suspension (see Note 7).

3.4.2. Cell Microarray Using Photolithography (Fig. 1 Part A)

1. The cell-containing polymer suspension is spin-coated onto functionalized glass substrates to form uniform fluid layer. 2. This layer is covered with a photomask and exposed to 365 nm UV light for 30 s through the photomask. (Proximity

Fig. 1. Part A. (a) Schematic of photoencapsulation of mammalian cells inside hydrogel microarray. (b) SEM and fluorescence images of resultant hydrogel microarray encapsulating fibroblasts (from ref. 26).


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Fig. 1. (continued) Part B. (a) Schematic diagram of the photoreaction injection molding process for creating hydrogel microstructures (from refs. 27). (b) Fabrication of 6 × 6 array of hydrogel microstructure encapsulating three phenotypes of cells using photoreaction injection molding: fibroblasts (upper row), macrophage (middle row), hepatocytes (bottom row) (from refs. 28).

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photolithography is used to avoid contact between photomask and precursor solution) (see Note 6). 3. Upon exposure to UV light, only exposed regions undergo free-radical-induced gelation and become insoluble in common PEG solvents such as water. As a result, desired microstructures are obtained by washing away unreacted precursor solution with PBS or cell culture medium so that only the hydrogel microstructures remain on the substrate surface. 4. During the UV-light-induced gelation process, cells suspended in the precursor solution are encapsulated in the resultant hydrogel microstructures. 5. Glass substrates with cell-containing microstructures are immersed in cell culture media and incubated in a 5% CO2. 3.4.3. Cell Microarray Using Photoreaction Injection Molding (Fig. 1 Part B)

PDMS microchannel systems are used as mold inserts for photoreaction injection molding. Photoreaction injection molding offers several advantages over previously described methods of encapsulating mammalian cells in hydrogel microstructures. For example, a small volume of cell-containing precursor solution is sufficient to fill and be photopolymerized inside microchannel, whereas cell-patterning techniques based on spin-coating requires a much larger volume of precursor solution because of solution loss during the spin-coating procedure. Another important advantage of photoreaction injection molding is the possibility to encapsulate different phenotypes on the same array. 1. Each independent microchannel is filled with cell-containing precursor solution. (For the preparation of multi-phenotype cell microarray, precursor solutions containing different cells are introduced to different microchannels) (see Note 5). 2. To make various patterns of hydrogel microstructures, a photomask is aligned over the microchannels. 3. UV exposure for 30 s. 4. PDMS microfluidic networks are quickly removed from the glass substrate. 5. Final hydrogel microstructures are obtained after washing processes.

3.5. Incorporation of Cell Microarray into Microfluidic Device (Fig. 2)

Microfluidic systems offer several advantages, including decreased sample volume, fewer cells, shorter reaction time, and the ability to perform many experiments in parallel. Microfluidic devices are well suited for biological experiments at cellular level since microchannels within these devices can mimic the physical size found in vivo. Because of small size of microchannels, microfluidic devices also allow adequate oxygenation and fast nutrition diffusion. Such an environment helps cells to easily maintain local


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Fig. 2. (a) Fabrication of cell-containing hydrogel microstructure within a microchannel (First image: A cell-containing hydrogel precursor solution in a microchannel. Second image: Gelation of the hydrogel inside the microchannel after exposure to UV light through a photomask. Third image : A cell-containing hydrogel microstructure inside a microchannel after the removal of unreacted precursor solution.) (b) Hydrogel microarray encapsulating macrophages within microfluidic devices (cell-containing hydrogel microarrays are prepared inside 200 mm-wide microchannels or a 2 mm × 2 mm chamber connected to 100 mm-wide microchannels.) (from refs. 27 and 29).

microenvironment than in macro-scale cell culture flasks and exist in less stressful, more in vivo like surroundings, which can lead to more accurate observation on cellular behavior in response to external stimuli. 1. To create microfluidic system, PDMS replica of desired design and cover glass are placed in low-energy plasma cleaner and oxidized at medium power for 1 min. 2. After removal from the plasma cleaner, two substrates are brought into conformal contact and irreversible sealing forms spontaneously. 3. Enclosed microchannels are treated with dilute TPM solution in perfluorooctane for 10 min immediately after sealing to enhance the adhesion of hydrogel microstructure inside the microchannels. 4. Cell-containing hydrogel precursor solution is introduced to the microfluidic network and exposed to UV light through the photomask (see Note 8).

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5. After photopolymerization, cell culture media is introduced into channels at 10–100 mL/min with a syringe pump not only to remove unreacted precursor solution from microchannels but also to culture encapsulated cells inside microfluidic devices. 6. Cell culture media inside microchannels was replaced with fresh media every day. 7. These microfluidic devices containing encapsulated mammalian cells are placed onto Petri dish filled with deionized water or culture media to prevent evaporation of cell culture media from microchannels and incubated at 37°C in 5% CO2 and 95% air. 3.6. Toxin Detection Using Cell Microarray

Cell microarray can be used to detect toxic compounds. Here, we describe experimental protocol for the optical detection of sodium azide, a model toxin, using cell-containing hydrogel microarrays. After incubation with sodium azide, response of encapsulated cells against sodium azide is monitored by observing intercellular reaction or cell viability.

3.6.1. Cell Viability Assays

1. A live/dead viability/cytotoxicity fluorescence assay is used to investigate the viability of encapsulated cells. This assay uses SYTO 10 and Dead Red as fluorophores to distinguish living cells and dead cells. SYTO 10 stains live cells green and Dead Red stains dead cells red. 2. For this assay, 2 mL of two fluorophores are added to 1 mL of cell culture media to make the staining solution. 3. The staining solution is introduced to the encapsulated cells and incubated for 20 min in the dark, at room temperature. 4. Viability of cells encapsulated in hydrogel microarrays is imaged and analyzed using A Zeiss Axiovert 200 microscope equipped with fluorescent optical package. 5. A difference in viability is observed between the cells exposed to sodium azide and unexposed cells. Most of the encapsulated cells are alive before the dose of sodium azide; however, when the cells are exposed to sodium azide, the azide anion kills the cells in the hydrogel microstructures as anticipated, and this results in cells that stained red in the assay (Fig. 3a).

3.6.2. Intercellular Reactions

1. Calcein-AM is used to investigate the intercellular reaction of encapsulated cells after exposure to sodium azide. Calcein-AM is colorless and nonfluorescent which can permeate cell membrane. Once inside cells, ester group of calcein-AM are hydrolyzed by esterase enzymes contained within cells to yield calcein, which is fluorescent-emitting green light. If cells are


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Fig. 3. (a) Results of live/dead fluorescence viability assay for encapsulated cells before and after the exposure to sodium azide. (b) Left : Fluorescence images of encapsulated macrophages incubated with calcein-AM, which show an initial (A and C) and 2-h time lapse (B and D) images of a single array element upon exposure to 0 mM (A and B) and 100 mM (C and D) sodium azide. Right: Change of fluorescent intensity by exposure to different concentrations of sodium azide (from refs. 29 and 30).

damaged, they will lose the ability to convert calcein-AM into calcein, which results in decrease of fluorescence intensity. 2. 10 mM Calcein-AM solution is prepared by diluting calceinAM stock solution dissolved in anhydrous dimethylsulfoxide (DMSO) with cell culture media. 3. Encapsulated cells are incubated with this solution for 30 min inside microchannels and then observed with fluorescence microscope. 4. In general, azide damages cellular mitochondria, effectively blocking the flow of electrons to oxygen and halting the production of ATP in cells. Without ATP production, cell viability is gradually diminished, decreasing the fluorescence intensity of cells reacting with calcein-AM (Fig. 3b).

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4. Notes 1. Surface modification of glass surface with TPM should be carried out under nitrogen environment because TPM can react with water in the air. When TPM solution contact with air, transparent solution become opaque. 2. Various molecular weights of PEG can be used. However, for the long-term cultures, higher molecular weight of PEG is more desirable due to the enhanced mass transfer for the supply of nutrient and removal of metabolic wastes. 3. PEG-DA with higher molecular weight of PEG (>4,000 Da) can be prepared by reaction PEG with acyloyl chloride. In brief, PEG (20 g) is dissolved in 200 mL of dry benzene under nitrogen and heated at 40°C until fully dissolved. The solution is cooled in an ice bath, followed by the addition of 0.7 mL of triethylamine and 1.13 mL of acryloyl chloride. The mixture is then heated to reflux for 2 h, followed by stirring overnight at room temperature under nitrogen. The solution is filtered to remove the amine salts formed during the reaction, and then the polymer is precipitated in n-heptane. The final product is isolated as a powder by subsequent drying at room temperature in a vacuum oven. Fourier transform infrared (FTIR) spectroscopy can confirm that hydroxyl groups on the PEG polymer are acrylated to near completion. 4. Incorporation of RGD into hydrogels is achieved by functionalizing the amide terminus of the peptide with an acrylate moiety, enabling the adhesion peptide to copolymerize rapidly with PEG-DA during photopolymerization. Without RGD peptide incorporation, encapsulated cells appear rounded after 24 h and slowly spread over the course of several days due to the non-adhesive nature of PEG hydrogels toward proteins and, hence, toward cells. 5. For the photoreaction injection molding of PEG hydrogels, the gel precursor solution must completely fill the microchannels. Since reversible sealing cannot withstand high pressure in the microchannels, the precursor solution should fill the channel by capillary action. For the precursor solutions described here, however, both PDMS and TPM-modified glass surfaces are hydrophobic; therefore, the solution cannot flow through the channel by capillary action. To solve this problem, PDMS microchannels are treated with oxygen plasma to make them hydrophilic. Oxygen plasma treatment lowered the contact angle of channel surfaces with water to almost zero, allowing channels to be easily filled with the gel precursor solution via capillary action.


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6. For the photopolymerization, the spot UV lamp should be placed at a height such that the cell-containing precursor solutions received a light intensity of approximately 10 mW/cm2. 7. The number of cells in one hydrogel microstructure can be controlled by adjusting the cell density in the hydrogel precursor solution or size of hydrogel microstructures. 8. When hydrogel microarrays are fabricated within microfluidic devices, the introduced precursor solution should be allowed to reach a stationary state and then exposed to UV light to avoid deformed structures. References 1. Pancrazio, J. J., Whelan, J. P., Borkholder, D. A., Ma, W., and Stenger, D. A., Annals of Biomedical Engineering, 73: 697–711 (1999). 2. Castel, D., Pitaval, A., Debily, M., and Gidrol, X., Drug Discovery Today, 11: 616–622 (2006). 3. Sundberg, C. J., Current Opinion in Biotechnology, 11: 47–53 (2000). 4. Bhatia, S. N., Yarmush, M. L., and Toner, M., Journal of Biomedical Materials Research, 34: 189–199 (1997). 5. Kleinfeld, D., Journal of Neuroscience, 8: 4098–4120 (1988). 6. Matsuda, T., Inoue, K., and Sugawara, T., ASAIO Journal, 36: M559–M562 (1990). 7. Matsuda, T., and Inoue, K., ASAIO Journal, 36: M161–M164 (1990). 8. Matsuda, T., and Sugawara, T., Journal of Biomedical Materials Research, 29: 749–756 (1995). 9. Chen, C. S., Biotechnology Progress, 14: 356– 363 (1998). 10. Singhvi, R., Kumer, A., Lopez, G. P., Stephanopoulos, G. N., Daniel, I. C., Wang, D., Whitesides, G. M., and Ingber, D. E., Science, 264: 696–698 (1994). 11. McDonald, J. C., Duffy, D. C., Anderson, J. R., Chiu, D. T., Wu, H., Schueller, O. J. A., and Whitesides, G. M., Electrophoresis, 21: 27–40 (2000). 12. Delamarche, E., Bernard, A., Schmid, H., Bietsch, A., Michel, B., and Biebuyck, H., Journal of American Chemical Society, 120: 500–508 (1998). 13. Ito, Y., Biomaterials, 20: 2333–2342 (1999). 14. Kane, R. S., Takayama, S., Ostuni, E., Ingber, D. E., and Whitesides, G. M., Biomaterials, 20: 2363–2376 (1999). 15. Jung, D. R., Kapur, R., Adams, T., Giuliano, K. A., Mrksich, M., Craighead, H. G., and Taylor, D. L., Critical Reviews in Biotechnology, 21: 111–154 (2001).

16. Park, T. H., and Schuler, M. L., Biotechnology Progress, 3: 335–373 (2003). 17. Whitesides, G. M., Ostuni, E., Takayama, S., Jiang, X., and Ingber, D. E., Annual Review of Biomedical Engineering, 3: 335–373 (2001). 18. Quinn, C. P., Pathak, C. P., Heller, A., and Hubbell, J. A., Biomaterials, 16: 389–396 (1995). 19. Csoregi, E., Quinn, C. P., Schmidtke, D. W., Lindquist, S. E., Pishko, M. V., Ye, L., Katakis, I., and Heller, A., Analytical Biochemistry, 66: 3131–3138 (1994). 20. Pathak, C. P., Sawhney, A. S., and Hubbell, J. A., Journal of the American Chemical Society, 114: 8311–8312 (1992). 21. Mann, B. K., Gobin, A. S., Tsai, A. T., Schmedlen, R. H., and West, J. L., Biomaterials, 22: 3045–3051 (2001). 22. Mellott, M. B., Searcy, K., and Pishko, M. V., Biomaterials, 22: 929–941 (2001). 23. Sirkar, K., and Pishko, M. V., Analytical Chemistry, 70: 2888–2894 (1998). 24. Revzin, A. R., Yadavalli, V., Koh, W., Deister, C., Hile, D., Mellott, M., and Pishko, M. V., Langmuir, 17: 5440–5447 (2001). 25. Beebe, D. J., Moore, J. S., Bauer, J. M., Yu, Q., Liu, R. H., Devadoss, C., and Jo, B., Nature 404: 588–590 (2000). 26. Koh, W. G., Revzin, A., and Pishko, M. V., Langmuir, 18: 2459–2462 (2002). 27. Koh, W. G., and Pishko, M. V., Langmuir, 19: 10310–10316 (2003). 28. Koh, W., Itle, L. J., and Pishko, M. V., Analytical Chemistry, 75: 5783–5789 (2003). 29. Koh, W. G., and Pishko, M. V., Analytical and Bioanalytical Chemistry, 385: 1389–1397 (2006). 30. Itle, L. J., and Pishko, M. V., Analytical Chemistry, 77: 7887–7893 (2005).

Chapter 8 Fabrication of Bacteria and Virus Microarrays Based on Polymeric Capillary Force Lithography Pil J. Yoo Abstract There is a growing interest on the fabrication of bacteria and virus microarray owing to their great potential in many biological applications ranging from diagnostic devices to advanced platforms for fundamental studies on molecular biology. Over the past decade, a number of studies with regard to the biomolecular patterning have been presented. Capillary force lithography (CFL) for polymeric thin films can provide well-ordered microarray structures over a large area in a facile and cost-efficient way while maintaining its biocompatibility during a process. Patterned polymeric structures can be utilized either to physical barriers for the confinement of bacteria or to physicochemical template for the subsequent binding of viruses. In this chapter, we have shown that the patterned structures of poly(ethylene glycol) (PEG) containing polymer enables a selective binding of Escherichia coli, leading to a physically guided microarray of bacteria. Additionally, we demonstrate the fabrication of virus microarray of M13 viruses via electrostatic interactions with a prepatterned microstructure of polyelectrolyte multilayers. Key words: Bacteria microarray, Virus microarray, E. coli, M13 bacteriophages, Patterning, Capillary force lithography, Polydimethylsiloxane, Layer-by-layer assembly, Polyelectrolyte multilayers

1. Introduction The ability to spatially locate and anchor bacteria or viruses at the microscale in a precise manner affords useful platforms for biosensors, disease markers, and drug-screening applications (1–4). Particularly, bacteria are strong candidates for sensing applications since analytical specificity can be readily manipulated via genetic engineering and their micro-organisms are relatively robust as compared to mammalian cells (5). Additionally, with a growing threat of vial outbreaks and the reemergence of previously eradicated viruses, more efficient and reliable methods to identify viruses and to discover the relevant drugs must be investigated (6). Ali Khademhosseini et al. (eds.), Biological Microarrays: Methods and Protocols, Methods in Molecular Biology, vol. 671, DOI 10.1007/978-1-59745-551-0_8, © Springer Science+Business Media, LLC 2011

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Biopatterning technology has advanced at a rapid pace in the last decade with a variety of patterning methodologies for immobilizing and functionalizing these biomaterials onto a designed matrix. Among the diverse approaches, capillary force lithography for polymeric matrix layer has received much attention due to its attractiveness in economical feasibility, straightforward process, accessible scalability, and biocompatibility (7). Here, we focus on two representative methods for the presentation of bacteria and viruses into ordered micropatterns. First method for bacteria microarray fabrication utilizes the strategy of physical confinement of biomolecular species within a polymeric pattern engraved surface (8, 9). In order to prevent a nonspecific binding of bacteria over surface, a bio-repellent barrier layer that is including poly(ethylene glycol) polymer is synthesized (10). Then, the coated polymeric layer is patterned with the capillary force lithographic method, which renders a substrateexposed polymeric microarray structure. After a selective decoration with antibodies onto the substrate-exposed regions, bacteria are subsequently deposited through host–parasite interactions. As a result, the micropatterned array where bacteria are confined by the physical walls of polymeric structure can be obtained. Second method for virus microarray is employing electrostatic interactions between viruses and functionalized polymeric patterns. Layer-by-layer assembly of polyelectrolyte multilayers is adopted to prepare the polymeric base layer (11). Then, the solvent-assisted capillary molding, a modification of conventional capillary force lithographic method, is performed under ambient environment to pattern the polyelectrolyte multilayers that are prone to be thermally cross-linked (12, 13). The next deposition of charged viruses atop the prepatterned polymeric structure gives rise to the electrostatic binding between viruses and charged polyelectrolyte multilayers and thus leaves a micropatterned array where the viruses are placed onto the underlying polymeric patterns.

2. Materials 2.1. Escherichia coli Growth and Virus Amplification

1. TBS buffer: 50 mM Tris–HCl and 150 mM NaCl, pH 7.5. Store at room temperature. 2. Luria-Bertani (LB) medium: Dissolve 10 g/L tryptone (BD), 5 g/L yeast extract (BD), and 10 g/L NaCl in deionized water. Autoclave and store at room temperature. 3. LB agar: Dissolve 10 g/L tryptone, 5 g/L yeast extract, 10 g/L NaCl, and 15 g/L agar in deionized water. Autoclave and store at room temperature.

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4. LB plate: LB medium with agar of 15 g/L is sterilized by autoclaving. 5. LB-Tet plate: Autoclave LB medium with agar of 15 g/L. Add 1 mL of tetracycline hydrochloride stock (20 mg/mL in ethanol, Aldrich). Pour the stock onto plate (Petri dish) and store them at 4°C in dark. Final concentration of tetracycline hydrochloride is 20 mg/mL. 6. YT medium containing 5 mM MgCl2 (×2): Add 16 g of tryptone, 10 g of yeast extract, and 5 g of NaCl to 900 mL of deionized water. Dissolve all the components and adjust the solution pH to 7.0 with 5 N of NaOH. Finally, adjust volume to 1 L and autoclave. 7. M13 virus (bacteriophage): 50 mL of ER2738 [Wild-type M13 virus, Escherichia coli (E. coli) strain ER2738, New England Biolabs] is overnight cultured in LB medium from a colony (see Note 1). 8. PEG/NaCl: Prepare solution of 20 wt% PEG (crystalline powder, average Mn ~ 8,000, Aldrich) with 2.5 M of NaCl. Autoclave and store at room temperature. 2.2. Fabrication of Bacteria Microarrays 2.2.1. Synthesis of Nonbiofouling Copolymer of Poly (TMSMA-r-PEGMA)

1. Monomer 1: 2.5 g of 3-(trimethoxysilyl) propyl metharylate (TMSMA) (10 mmol, Aldrich) is used as received. This reagent is moisture-sensitive; therefore, it should be transferred with a double-ended needle under nitrogen purging. 2. Monomer 2: 4.75 g of poly(ethylene glycol) methyl ether methacrylate (PEGMA) (10 mmol, Aldrich, average Mn ~ 475) is used as received. 3. Initiator: 16.5 mg of 2,2′-azobisisobutyronitrile (AIBN) (0.1 mmol, Aldrich, 98%) is used as received. AIBN is a free radical initiator and very reactive and explosive. So, special caution is required. 4. Inhibitor remover: Prepacked column for removing hydroquinone and monomethyl ether hydroquinone (Aldrich), used as received. 5. Reaction solvent: 10 mL of tetrahydrofuran (Aldrich, anhydrous, inhibitor free, 99.9%) is used as received.

2.2.2. Patterning of Nonbiofouling Copolymer Film and Fabrication of Bacteria Array

1. Substrates: Diced silicon substrates (25 × 25 mm) from 8-in. silicon wafer (orientation ~100, test grade, Silicon Quest). 2. Silicon master pattern: Prepare the master using a silicon wafer that had been thermally oxidized to a thickness of 1 mm. Emboss micrometer scaled line-and-space patterns or dot array patterns onto the wafer surface by photolithography. 3. Trichloroethylene: Purchased from Aldrich, used as cleaning solvent for the substrates.

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4. Methyl alcohol: Purchased from Aldrich, used as cleaning solvent for the substrates. 5. Polydimethylsiloxane (PDMS) mold: Prepare the replicated PDMS molds using thermally casting prepolymer (Sylgard 184, Dow Corning) onto the complimentary relief structures of a silicon master. To thermally cure the PDMS molds, mix the curing agent and the prepolymer with a ratio of 1:10 (wt%), and incubate at 70°C for 6 h. Then, peel off from the master and cut into desired sizes (see Note 2). 6. Antibody: Anti-M13 P3 monoclonal antibody (New England Biolabs), store at −20°C. 2.3. Fabrication of Virus Microarrays 2.3.1. Layer-by-Layer Assembly of Polyelectrolyte Multilayers

1. Cationic polyelectrolyte: Dissolve linear polyethylenimine (LPEI, 25,000 MW, Polysciences) in deionized water to 30 mM based on the repeat-unit molecular weight, e.g., 1.50 g LPEI in 1 L of water (see Note 3). Then, filter out the impurities and nonsoluble residues through filtered bottle (pore size ~0.2 mm). Store the filtered solution at room temperature at least for 2 weeks before use. 2. Anionic polyelectrolyte: Dissolve poly(acrylic acid) (PAA, 90,000 MW, 25% aqueous solution, Polysciences) in water at 20 mM based on the repeat-unit molecular weight, e.g., 5.77 g PAA (25% aqueous solution) in 1 L of water. Store the filtered solution at room temperature at least for 2 weeks before use. 3. Substrates: Glass substrate (VWR international, 75 × 25 mm) or diced silicon substrates (60 × 25 mm) from 8-in. silicon wafer (orientation ~100, test grade, Silicon Quest).

2.3.2. Preparation of Polymeric Microarray Using Solvent-Assisted Capillary Molding

1. Silicon master pattern: Prepare the master using a silicon wafer that had been thermally oxidized to a thickness of 1 mm. Emboss micrometer scaled line-and-space patterns or dot array patterns onto the wafer surface by photolithography. 2. PDMS mold: Prepare the replicated PDMS molds using thermally casting prepolymer (Sylgard 184, Dow Corning) onto the complimentary relief structures of a silicon master. To thermally cure the PDMS molds, mix the curing agent and the prepolymer with a ratio of 1:10 (wt%), and incubate at 70°C for 6 h. Then, peel off from the master and cut into desired sizes.

2.3.3. Proteins Binding onto Virus Array

1. PBS buffer: Dilute phosphate buffer solution (pH 7.2, Aldrich) to 1/10 of the original concentration in deionized water and sterilize by filtering.


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2. Blocking agent: Prepare Tween 20 (Aldrich) stock solution to 0.2% (v/v) solution by serial dilution of original solution in PBS (see Note 4). 3. Virus-binding protein: Biotin-conjugated anti-fd bacteriophage (Sigma), which is developed in rabbits using repeated injections of M13 bacteriophage as the immunogen, is diluted to 3 mg/mL in the prepared phosphate buffer solution. 4. Fluorescence-labeled Streptavidin: Streptavidin conjugated Alexa Fluors 430 and 568 (molecular probes, green and red fluorophore, respectively) is diluted to 5 mg/mL in the prepared phosphate buffer solution.

3. Methods In this method section, the protocols for E. coli growth and M13 bacteriophage amplification are firstly presented as preparatory materials for the fabrication of bacteria and virus microarray. Bacteria microarray can be obtained using a scheme of the physical confinement of bacteria within patterned polymeric microstructures. In the course of bacteria ordering, alleviating nonspecific adsorption of bacteria onto polymeric micropatterns is very important to obtain the pattern selectivity of the microarray. The synthesized PEG containing nonbiofouling polymer is thus introduced as a nonbiofouling material. For the fabrication of virus microarray, instead of using the strategy of the physical confinement, the ability of physicochemical templating of the patterned polymeric structures can be exploited. To provide these properties, layer-by-layer assembled polyelectrolyte multilayers are employed as a patternable polymeric layer. It is worthwhile noting that the viruses are electrostatically bound onto the protruded surface of polymeric patterns of the polyelectrolyte multilayers (templated assembly), which is contrasted to the case of bacteria microarray, where bacteria are placed only in the recessed regions surrounded by topographically patterned polymeric barriers (confinement-induced assembly). 3.1. E. coli Growth in LB Media 3.1.1. Day 1: Media Preparation

This protocol gives the steps to grow E. coli in LB media from a stab culture. The culture volume is 250 mL. 1. Prepare 250 mL of liquid LB media and aliquot 50 mL each into 250 mL flasks. If necessary, adjust pH to 7.0 with 5 M NaOH. 2. Prepare 100 mL of LB agar.

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3. Prepare 80% (v/v) glycerol solution to make glycerol stocks of cell strains. 4. Autoclave the LB media and LB agar prepared in steps 1–3. Both of LB media and LB agar would become clear light yellow solutions after autoclaving. LB agar can be stored in 60°C oven before use. 5. Prepare stock antibiotic solutions (50 mg/mL ampicillin stock) by filter sterilizing. Distribute 1 mL aliquots into sterilized Eppendorf tubes, and store them at −20°C in a dark condition. 3.1.2. Day 2: Inoculation by Streaking

1. Cool down the autoclaved LB agar to below 50°C (could be touched by hands), then add 100 mL ampicillin stock solution into 100 mL LB agar. Pour the LB agar into five petri dishes and let them solidify. 2. Inoculate the agar plates from stab culture by streaking. Flame a wire loop and cool on a spare sterile agar plate. Dip the wire loop into the stab culture, and streak an inoculum of E. coli across one corner of a fresh agar plate. Flame and cool the wire loop again. Pass it through the first streak and then streak again across a fresh corner of the plate. 3. Incubate the plate upside down in 37°C incubator for 12–24 h until colonies develop.

3.1.3. Day 3: Grow E. coli in LB Media

1. Remove plates from incubator. Seal the plates with parafilm and keep them at 4°C if not use immediately. 2. Before transfering colonies from LB agar plates into LB liquid media, add 50 mL ampicillin stock solution into each flask, which contains 50 mL liquid media. 3. Take agar plates from refrigerator. Pick one colony with blunt toothpicks to inoculate one 250 mL shake flask. 4. Incubate all flasks overnight at 37°C with 250 rpm.

3.1.4. Day 4: Make Master Bank and Working Bank of Cell Strains

1. Harvest the cell culture. 2. Get two cryogenic vials (1.8 mL) for each cell strain. Add 200 mL sterilized 80% glycerol into each vial first. Then, add 800 mL overnight cell culture into each vial (the final concentration of glycerol is 16%). Mix them well. 3. Label the vials and keep them at −80°C as glycerol stocks. One vial of each cell strain works as the master bank, and the other works as the working bank.

3.2. Virus Amplification and Extraction

1. Set up an overnight culture of ER2738 in LB-Tet from a colony. Dilute overnight culture 1:100 in 2× YT medium containing 5 mM MgCl2.


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2. Add the neutralized phage elute (~1 mL) to the diluted 20 mL ER2738 culture and incubate at 37°C with vigorous shaking for 4–5 h. 3. Transfer the culture to a centrifuge tube and spin 10 min at 10,000 rpm at 4°C. 4. Transfer the supernatant to a fresh tube and re-spin. 5. Pipet the upper 80% of the supernatant to a fresh tube. The volume of PEG/NaCl added to the supernatant is 1/5 of the supernatant volume. Allow phage to precipitate at 4°C for 1 h (see Note 5). 6. Spin PEG precipitation 15 min at 10,000 rpm, at 4°C. Decant supernatant, re-spin briefly, and remove residual supernatant with a pipette. 7. Suspend the pellet in 1 mL TBS. 8. Transfer the suspension to a microcentrifuge tube and spin for 5 min at 4°C to pellet residual cells. 9. Transfer the supernatant to a fresh microcentrifuge tube and re-precipitate with 1/6 volume of PEG/NaCl. Incubate on ice 15–60 min. 10. Microcentrifuge for 10 min at 4°C. Discard supernatant, respin briefly, and remove residual supernatant with a micropipette. 11. Suspend the pellet in 200 mL TBS (0.02% NaN3). 12. Microcentrifuge for 1 min to pellet any remaining insoluble matter. 13. Transfer the supernatant to a fresh tube. This is the amplified elute. Take 10 mL to titer. The rest are stored at 4°C. For a long-term storage of amplified phage, dilute 1:1 with sterile glycerol (20%) and store at −20°C. 3.3. Fabrication of Bacteria Microarrays 3.3.1. Synthesis of Nonbiofouling Copolymer of Poly(TMSMA-r-PEGMA) (see Note 6)

1. Prior to polymerization, flow the neat PEGMA through the inhibitor removal column. 2. Place 10 mmol PEGMA, 10 mmol TMSMA, and 0.01 mmol AIBN in a vial and dissolve in 10 mL of anhydrous tetrahydrofuran. 3. Degas the mixture for 20 min using an Ar gas stream and seal the vial with a Teflon-lined screw cap. 4. To carry out the polymerization, place the mixture at 70°C for 24 h with a slight stirring, then evaporate the solvent under vacuum condition. As a result, a viscous polymeric liquid of poly(TMSMA-r-PEGMA) is obtained (see Note 7).

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Fig. 1. (a) Experimental procedure of fabricating bacteria arrays using capillary force lithography and host–parasite/virus–antibody interactions. (b) Scanning electron microscope (SEM) image of a single Escherichia coli (E. coli ) on a silicon substrate. Bar scale is 1 mm. (c) Fluorescent micrograph for FITC-labeled P3 antibody of 50 mm circle pattern. (d) Optical micrograph for subsequently adsorbed E. coli onto the same pattern. (e) SEM micrograph for single arrays of E. coli along the channel direction. Pattern spacing is 1 mm. 3.3.2. Patterning of Nonbiofouling Copolymer Film and Fabrication of Bacteria Array

1. Clean silicon wafer or glass substrate by ultrasonification in trichloroethylene and methanol for 5 min each, then dry in nitrogen. The native oxide is not removed from the surface and would exist. 2. Place a few drops of a 1–10 wt% solution of poly(TMSMA-rPEGMA) on a silicon wafer and spin-coat at 1,000 rpm for 10 s. 3. Place patterned PDMS mold carefully onto the polymer surface with ensuring a conformal contact (capillary force lithography). 4. Store the samples overnight at room temperature to allow for complete evaporation of the solvent. Ellipsometric measure-


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ment reveals that the patterned film thickness ranges from 32 to 370 nm depending on the solution concentration of poly(TMSMA-r-PEGMA) (see Note 8). 5. To selectively attach the antibodies inside the polymeric patterns, prepare the diluted solution of P3 antibodies at 1:100 in PBS (see Note 9). 6. Spread a few drops of the antibody solution evenly on the surface for an hour. Then, rinse the surface with diluted PBS buffer for 1 min. 7. Place the samples in a solution of E. coli (cultured with M13 viruses) for 4 h to attach bacteria onto the patterned antibodies with an aid of the virus–antibody (host–parasite) interactions. Finally, rinse the surface with diluted PBS buffer for 1 min. 3.3.3. Characterization and Imaging of Virus Array

1. The patterned bacteria array is characterized with atomic force microscope (AFM, Veeco, Dimension 3100 with Nanoscope IIIa controller) in dry condition. In order to minimize any possible misreading during data acquisition on topologically patterned surface, use in a slow scanning tapping mode (0.5– 1.0 Hz of scan speed). 2. Scanning electron microscope can be used to capture the images of bacteria array as well. Prior to imaging, deposit 5 nm thicknesses of the Au layer on the patterned surface to prevent charging.

3.4. Fabrication of Virus Microarrays 3.4.1. Layer-by-Layer Assembly of Polyelectrolyte Multilayers

1. Clean a silicon wafer or a glass substrate by ultrasonification in trichloroethylene and methanol for 5 min each, then dry in nitrogen. 2. Plasma-treat the cleaned substrate with a conventional plasma cleaner for 30 s (PDC-001, Harrick Scientific Corp.) to prepare an initial negatively charged surface. 3. Adjust pH of LPEI and PAA solutions to 4.7 carefully with diluted solutions of hydrochloric acid and sodium hydroxide. 4. Prepare the polyelectrolyte multilayers of LPEI and PAA using a programmable slide stainer (HMS-70, Microm) with a deposition condition of 15 min adsorption of polyelectrolyte and followed by three sequential washing steps in the bath of deionized water (2 min for each washing step). To compensate the negative surface charge of the substrate, deposit positively charged LPEI firstly onto the substrate. For the deposition of 200 nm thick film of LPEI/PAA, prepare 11.5 bilayers of LPEI/PAA, (LPEI/PAA 4.7/4.7)11.5 (see Note 9). 5. Remove the loaded samples from the slide stainer and store at ambient temperature in dry condition.

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Fig. 2. (a) Experimental procedure of fabricating virus arrays using solvent-assisted capillary molding and electrostatic interactions between viruses and polyelectrolyte multilayers. (b) Three-dimensional atomic force microscope (AFM) image for assembled viruses atop patterned template of polyelectrolyte multilayers (1.5 mm circle pattern). (c) Twodimensional AFM image for assembled viruses (phase mode, Z-range = 30°). (d) Phase mode AFM images for assembled viruses from “before biotinylation” (left ) to “after biotinylation” (right ). (e) Green fluorescence image of Alexa Fluor 430 streptavidin bound viral dot array. (Reproduced from [13] with permission from American Chemical Society).

3.4.2. Preparation of Polymeric Microarray Using Solvent-Assisted Capillary Molding (see Note 10)

1. Place the prepared samples of the LPEI/PAA film in a mildly heated humid chamber (normally at 80°C, 100% relative humidity) for 30 min to soften the film prior to contact with PDMS mold. 2. Place the PDMS mold onto a vapor-exposed polymeric film with a slight pressure of a few bars to promote the capillary


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molding. After 3–4 h of heating in a vapor-saturated environment, detach the PDMS mold from the sample surface and the replicated patterns of the polyelectrolyte multilayers remained on the surface. 3. To remove the very thin residual layers of polymer from the mold contact regions, treat the patterned surface with 1 min of plasma cleaning, during which an air plasma is irradiated onto the sample with an etching rate of about 20–30 nm/ min for the polymeric layer. As a result, one can assure the clean removal of residual polymeric layer from the interstitial regions between patterns. 3.4.3. Electrostatic Self-Assembly of M13 Viruses on Polymeric Micro Array

1. Dilute the stock solution of wild-type M13 virus in deionized water to the final concentration of 109–1010 molecules/mL. 2. Adjust the solution pH of virus to 4.8 by adding 0.01 M HCl or 0.01 M NaOH, near the isoelectric point of M13 viruses (see Note 11). 3. Drop-dispense the pH-adjusted virus solution (~200 mL/ cm2) on prepared polymer surface for 20–30 min at ambient temperature. During an adsorption process, negatively charged M13 viruses were electrostatically bound on the positively charged top surface of LPEI/PAA multilayer, finally leading to an ordered monolayer structure of M13 viruses on the surface. 4. Rinse the virus assembled surfaces with deionized water several times to remove loosely bound viruses and dried by blowing with nitrogen.

3.4.4. Proteins Binding onto Virus Array

1. To attach biotin groups onto assembled M13 viruses, dropdispense a diluted solution of the biotin-conjugated anti-fd bacteriophage (~200 mL/cm2) onto the patterned virus surface for 5 min. Then, rinse the surface with diluted PBS buffer for 1 min. 2. For the biotin–streptavidin coupling reaction, similar procedures can be applied by using fluorophore-tagged streptavidin. Drop-dispense a diluted solution of the streptavidin conjugated Alexa Fluors 430 or 568 (~200 mL/cm2) onto the patterned biotins atop viruses for 20 min. Then, rinse the surface with diluted PBS buffer several times and dry with nitrogen.

3.4.5. Characterization and Imaging of Virus Array

1. The patterned assembly of viruses is mainly characterized with AFM (Veeco, Dimension 3100 with Nanoscope IIIa controller) in dry condition. In order to minimize any possible misreading during data acquisition on topologically patterned surface and to enhance the image resolution, operate

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in a slow scanning tapping mode (0.5–1.0 Hz of scan speed) with super sharp silicon probes (Pacific Nanotechnology, SSSNCH, typical tip radius of curvature ~2 nm). 2. Fluorescence microscopic images of the labeled virus array are obtained with microscope (Zeiss Axioplan 2, Carl Zeiss).

4. Notes 1. The M13 bacteriophage, a virus that only infects bacteria, is composed of ~2,700 major coat proteins helically stacked around its single-stranded DNA, rendering a monodispersed and semi-flexible filamentous structure (880 nm in length and 6.6 nm in width). 2. In spite of being cured and solidified, cured PDMS contains considerable amounts of unthethered siloxane chains that can provide lubrication property to the surface. This lubrication effect lowers the surface energy of the PDMS mold, which is required surface property as a mold material. Therefore, freshly made PDMS molds are to be used for a molding process. 3. Due to its linear and regular structure, LPEI forms a crystalline solid when unprotonated and is thus insoluble in water above its pKa (~4.5). To dissolve LPEI into water, therefore, a small amount of HCl solution was added to a mixture of LPEI and deionized water until all the LPEI was dissolved. 4. Tween 20 detergent is employed to minimize any nonspecific (e.g., electrostatic or van der Waals interactions) binding of the antibodies or proteins onto the prepared patterns of polyelectrolyte multilayers and the substrate. 5. PEG is a long-chain polymeric compound which, in the presence of salt, absorbs water, thereby causing macromolecular assemblies such as phage particles to precipitate. 6. Random copolymer of poly(TMSMA-r-PEGMA) is comprised of “anchor part” of trialkoxysilane and a “function part” of PEG. Incorporation of the surface-reactive trimethoxysilyl group in the monomer can allow the copolymer to form multiple covalent bonds onto the oxide surface to provide multiple PEG immobilizations. Consequently, nonspecific protein adsorption and biomolecules adhesion can be significantly reduced. 7. The molecular weight of poly(TMSMA-r-PEGMA) was Mn = 26,000 with Mw/Mn = 1.88 as measured by gel permeation chromatography (GPC) relative to monodisperse polystyrene standards.


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8. Capillary force lithography of polymeric molding is a powerful method to construct microscale polymeric patterns on the surface. One potential concern with this technique is whether the substrate surface can be completely exposed, which is a prerequisite to enable the successful attachment of biological species. The PEG moieties in poly(TMSMA-r-PEGMA) allows a full exposure of the substrate surface during a molding process. 9. The nomenclature (A/B m/n)X is used to denote a multilayer film of X layer pairs of cationic A and anionic B deposited at pH m and n, respectively. When X includes 0.5, cationic A is the final adsorbed layer and thus the outermost surface of the multilayer. 10. Generally, polymeric molding process is an efficient way of generating physically patterned polymeric structures. Among several approaches, capillary force lithography is a promising candidate that utilizes the fluidic mobility of polymers at high temperature conditions (above the Tg of the polymer) to induce a fluidic mobility for a molding. Using thermal mobility, however, is not applicable to most layer-by-layer assembled polyelectrolyte multilayers film systems because in the dry state, the ionic complexes might be considered as networks based on multivalent ionic crosslinks that impede flow, and furthermore, the heating of polyacid/polyamine multilayers to high temperatures usually brings about thermal crosslinking between cationic and anionic species. To overcome this challenge, instead of utilizing thermally induced mobility, one should turn to another means of achieving polymeric mobility via softening of the multilayer film with suitable solvents (solvent-assisted capillary molding). For polyelectrolyte multilayers, water vapor can be a relevant solvent. Notably, cured PDMS does not significantly take up water (20 mW/cm2) while remaining under a nitrogen gas purge for two additional minutes. 3. The cured resin can be easily peeled off of the silicon master, yielding a mold with a perfect imprint of the patterned surface (Fig. 1).

3.1.2. Fabrication of Particles in an Array from a Fluorocur Mold (11, 13, 20)

1. A mixture containing 67% trimethyloylpropane ethoxylate triacrylate (MW = 428 g/mol), 20 wt% poly(ethylene glycol) monomethylether monomethacrylate (MW = 1,000 g/mol), 10 wt% 2-aminoethylmethacrylate hydrochloride (AEM⋅HCl), 2 wt% fluorescein-o-acrylate, and 1 wt% 2,2-diethoxyacetophenone was diluted to 10 wt/vol% solution in 2-propanol. 2. This solution is then deposited onto a mold containing 200 × 200 nm cylindrical cavities, laminated with a polymer sheet, and the polymer sheet is removed to yield filled mold cavities. 3. The filled Fluorocur mold is purged with nitrogen for 2 min followed by exposure to 365 nm UV irradiation at >20 mW/ cm2 for an additional 2 min. 4. After curing, the particles are removed from the mold using a medical adhesive such as poly(cyanoacrylate). Images of nanoparticle arrays (9) of various sizes composed of polyethylene glycol based materials are shown in Fig. 3.

3.2. Methods for Fabrication of Protein Arrays and Particles (4)

1. A 25 wt% of albumin was prepared by dissolving 25 mg lyophilized powder with 75 mL H2O. 2. This solution was spotted directly onto a Fluorocur mold (patterned with 200 × 200 nm cylinders) at the contact point of the patterned molded and an unpatterned polyethyleneterephthalate film affixed at the nip point on a laminator. 3. The solution was laminated between the mold and the PET sheet at a speed 0.25 ft/min and a pressure of 50 psi. The PET and mold were separated at the far side of the nip. 4. The solvent was allowed to evaporate from the filled mold by maintaining the arrays exposure to the atmosphere. 5. To harvest discrete particles from the protein array in the Fluorocur mold, 2 mL of a non-solvent (in this case chloroform) was placed on the mold surface and the particles were removed by slowly scraping the surface with a glass slide.

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Fig. 3. PEG-based particles in various sizes and shapes (9). (a) 200 × 200 nm trapezoidal particles. (b) 200 × 800 nm rod-like particles. (c) Conical particles with a 500 nm base and a 50 nm tip. (d) 3-mm-sized arrows.

6. To harvest the discrete protein particles in an array on a glass substrate, a small quantity of cyanoacrylate was laminated between the surface of the filled mold and a glass slide. 7. After the polymerization of cyanoacrylate was completed, the mold was slowly peeled from the surface of the glass yield a patterned array of discrete protein particles. 8. The particles can then be released from the array by dissolving the adhesive (see Fig. 4). 3.3. Fabrication of Organic Nanoparticle Arrays with Encapsulated Protein

Encapsulation of biomolecular cargo such as proteins (9, 14, 17) is straightforward using the PRINT process. In one example, avidin is blended with PEG diacrylate and solidified to yield a protein embedded in a biocompatible polymer matrix. To make this nanoarray (9) follow the steps outlined below: 1. Dissolve 1 mg of Cy-3-labeled avidin (68 kDa) in 1 mL of water. 2. 50 mL of this solution is then mixed with 20 mL of PEG400 diacarylate monomer containing 1% photoinitiator. 3. This mixture is concentrated to remove the water completely. 4. Since the concentration in step 3 produces a cloudy suspension, 20 mL of water, the minimum amount of water necessary to obtain a clear solution, is added back. 5. The PEG solution containing avidin is then thinly spread across a mold containing cones with a 500 nm base and a 50 nm tip.

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Fig. 4. Albumin particles harvested on a cyanoacrylate layer.

Fig. 5. Images of conical poly(ethylene glycol) particles with a 500 nm base and a 50 nm tip. (a) Fluorescence image of Cy-3-labeled avidin encapsulated within the PEG matrix. (b) Fluorescence image of FITC-labeled Biotin associated with the array. (c) Overlap of the two images in (a) and (b) showing that the avidin and biotin are co-localized.

6. The mold is sandwiched against a fluorinated surface and pressure (100 N/cm2) is applied to squeeze out any excess protein/PEG glycol solution. 7. While remaining under pressure, the sample is purged with nitrogen and exposed to UV light at 365 nm for 10 min. 8. Removal of the mold left the avidin-containing nanoarray on the fluorinated substrate (Fig. 5a). 3.3.1. Activity Retained of Avidin Encapsulated in Nanoparticle Arrays (9, 14)

In an effort to demonstrate that the avidin protein maintained its integrity, an array containing Cy-3-labeled avidin-containing poly(ethylene glycol) particles were fabricated from a mixture of PEG acrylates) (3). 1. 70% PEG400 diacrylate and 30% PEG1000 monomethacrylate were mixed with Cy3-labeled avidin and molded as described above (Fig. 5a).


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2. Fluorescein-isothiocyanate-labeled biotin was exposed to the nanoarray of avidin-containing poly(ethylene glycol) particles for 30 min and then washed well with water to remove any unbound biotin. 3. As evident in Fig. 5b, c, the biotin binds with the avidin in the nanoarray and is only localized on the nanoparticles not in the area in between particles. 3.4. Conjugation of Avidin to Nanomolded Poly(Ethylene Glycol) Particles (17, 18)

In addition to fabricating nanoarrays out of pure protein or mixtures of protein and polymers, it is also possible to attach proteins to the surface of biocompatible nanoarrays. In order to fabricate these nanoarrays, a suitable biocompatible material should be chosen that contains a reactive end group that can serve as a point of attachment after array fabrication. In this example, arrays of triacrylate-based particles containing a reactive carbonyl imidazole group are fabricated as described below. 1. Poly(ethylene glycol) monomethacrylate (MW = 485 g/mol) is treated with 1,1¢ carbonyl diimidazole to produce the reactive monomer, PEG485 carbonyl imidazole monomethacrylate (18) as shown in Fig. 6. 2. A solution of 59 wt% poly(ethylene) glycol428 triacrylate is mixed with 40 wt% PEG485 carbonyl imidazole monomethacrylate and 1% 2, 2¢-diethoxyacetophenone photoinitiator. 3. This mixture is then spotted onto a Fluorocur mold with 200 × 200 nm cavities and covered with a plastic sheet. 4. The plastic sheet is then removed leaving a mold with filled cavities. 5. Next, the filled mold is subjected to a nitrogen purge for 2 min followed by UV exposure (l = 365 nm, 20 mW/cm2) for an additional 2 min. 6. The discrete particles in the mold can be removed onto a cyanoacrylate harvesting layer by first placing a drop of cyanoacrylate onto a glass slide followed by lamination of the slide to the mold surface. 7. After allowing the cyanoacrylate to polymerize (5 min), the mold is removed leaving an array of nanoparticles on the glass slide.

Fig. 6. Reaction of poly(ethylene glycol) monomethacrylate (MW = 485 g/mol) with carbonyl diimidazole to produce the reactive monomer, PEG485 carbonyl imidazole monomethacrylate.

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8. If desired, the particles can remain in the array for surface functionalization or be released into solution by exposure to acetone. 9. The resulting 200 × 200 nm particles dispersed in DMSO are then exposed to a 0.7 mg/mL solution of Alexa-Fluor 488-labeled streptavidin in PBS (18). 10. After stirring for 14 h at room temperature, the particle solution was treated with ethanolamine to quench any remaining reactive end groups. 11. The particle solution was diluted 3× in deionized water, filtered through a 25 mm pore, and collected on a 100 nm pore size filter membrane. 12. After concentration via centrifugal filtration, the particles are resuspended in fresh water and imaged by fluorescence microscopy to see if the avidin conjugation was successful. 13. Alternatively, the nanoarray could be treated directly with the protein solution for a period of time, and then wash with water to obtain conjugation of the protein to the nanoparticle surface while remaining in the array. 14. If labeling of one side only is desired, it is possible to treat the single exposed side of the nanoarray while the individual particles remain in the Fluorocur mold. Treat the exposed side of the array with the protein solution for a period of time and wash with water to obtain an array of particles with one labeled side. It is of course possible to collect these particles in solution as mentioned earlier in this section. 3.5. Encapsulation of Oligonucleotides in Organic Nanoparticle Arrays

1. A solution of UV-curable monomers and a fluorescently labeled DNA oligonucleotide (18 mer, sequence GCT ATT ACC TTA ACC CAG containing a 3¢ fluorescein label) was prepared by adding 2 mg of DNA in 2 mL of H2O to a mixture of 13.65 mg of bis(ethyl methacrylate)disulfide, 1.53 mg of acryloxyethyltrimethylammonium chloride, 0.075 mg of Polyfluor 570, 0.15 mg 2,2¢-diethoxyacetophenone, 2.34 mg of acetonitrile, 2.34 mg of methanol, 9.5 mg of N,Ndimethylformamide, and 0.4 mg of H2O. 2. The mixture was spotted directly onto a 2 × 2 × 1 mm patterned Fluorocur mold and then covered with a plastic film. 3. The film was removed from the mold to leave filled mold cavities. 4. The filled mold was then subjected to UV light (l = 365 nm) for 2 min under a nitrogen purge that was passed through a gas scrubber filled with N,N-dimethylformamide prior to entering the curing chamber.


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Fig. 7. Percent release of oligonucleotide from degradable disulfide PRINT™ particles.

5. The isolated polymeric particles containing DNA can be removed from the array in the mold by placing ~0.4 mL of filtered acetone (0.22-mm PTFE filter) and scrapping the surface of the mold gently with a glass slide. 6. The particle suspension was transferred to a centrifuge tube, the particles were pelleted, the supernatant removed, and the particles were dried under vacuum. 7. The particles (1.44 mg) were then suspended in 1 mL of H2O, vortex rigorously, and pelleted out to purify. 8. The DNA can be released from the particles by treatment with 0.1 M dithiothreitol in PBS with 1–2 h. The rate of release in the absence of reductant is minimal (see Fig. 7).

Acknowledgments The authors would like to acknowledge outstanding scientific collaborations between the Carolina Center of Cancer Nanotechnology Excellence, Liquidia Technologies, and the Chemistry Department at the University of North Carolina, Chapel Hill. Much of this work was carried out by a team of exceptional postdoctoral fellows and graduate students. This work was supported by NIH U54-CA-119343 (the Carolina Center of Cancer Nanotechnology Excellence), NIH F32-CA-123650 (Ruth L. Kirschstein National Research Service Award), PPG P01-GM059299-07 (Pharma codynamics of Genes and Oligonucleotides), STC Program of the NSF (CHE-9876674), the William R. Kenan Professorship at the University of North Carolina at Chapel Hill, and through a supported research agreement with Liquidia Technologies.

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References 1. Voldman, J.; Gray, M. L.; Schmidt, M. A. Microfabrication in Biology and medicine. Annu. Rev. Biomed. Eng. 1999, 1, 401–425. 2. Truskett, V. N.; Watts, M. P. C. Trends in imprint lithography for biological applications. Trends Biotechnol. 2006, 24(7), 312–317. 3. Kane, R. S.; Takayama, S.; Ostuni, E.; Ingber, D. E.; Whitesides, G. M. Patterning proteins and cells using soft lithography. Biomaterials 1999, 20, 2363–2376. 4. Kelly, J. Y.; DeSimone, J. M. Shape-specific, monodisperse nano-molding of protein particles. J. Am. Chem. Soc. 2008, 130(16), 5438–5439. 5. Torres, C. M. S.; Zankovych, S.; Seekamp, J.; Kam, A. P.; Cedeno, C. C.; Hoffman, T.; Ahopelto, J.; Reuther, F.; Pfeiffer, K.; Bleidiessel, G.; Gruetzner, G.; Maximov, M. V.; Heidari, B. Nanoimprint lithography: an alternative nanofabrication approach. Mater. Sci. Eng. C. 2003, 23, 23–31. 6. Glangchai, L. C.; Caldorera-Moore, M.; Shi, L.; Roy, K. Nanoimprint lithography based fabrication of shape-specific enzymaticallytriggered smart nanoparticles. J. Control Release 2008, 125, 263–272. 7. Rolland, J. P.; Hagberg, E. C.; Denison, G. M.; Carter, K. R.; DeSimone, J. M. High resolution soft lithography: Enabling materials for nanotechnologies. Angew Chem. Int. Ed. Engl. 2004, 43(43), 5796–5799. 8. Rolland, J. P.; Van Dam, R. M.; Schorzman, D. A.; Quake, S. R.; DeSimone, J. M. Solventresistant photocurable “liquid teflon” for microfluidic device fabrication. J. Am. Chem. Soc. 2004, 126, 2322–2323. 9. Rolland, J. P.; Maynor, B. W.; Euliss, L. E.; Exner, A. E.; Denison, G. M.; DeSimone, J. M. Direct fabrication and harvesting of monodisperse, shape-specific nanobiomaterials. J. Am. Chem. Soc. 2005, 127(28), 10096–10100. 10. Maynor, B. W.; Larue, I.; Hu, Z.; Rolland, J. P.; Pandya, A.; Fu, Q; Liu, J.; Spontak, R. J.; Sheiko, S. S.; Samulski, R. J.; Samulski, E. T.; DeSimone, J. M. Supramolecular nanomimetics: Replication of micelles, viruses, and other

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Chapter 16 Progress Report on Microstructured Surfaces Based on Chemical Vapor Deposition Yaseen Elkasabi and Joerg Lahann Abstract This book chapter discusses recent advances in the fabrication of microscale surface patterns using chemical vapor deposition polymerization. Reactive poly(p-xylylene) (PPX) coatings are useful for their ability to immobilize specific biomolecules, as determined by the PPX functional group. PPXs can either be modified postdeposition, or they can be patterned onto a substrate in situ. Specific methods discussed in this progress report include microcontact printing, vapor-assisted micropatterning in replica structures, projection lithography-based patterning, and selective polymer deposition. Key words: Bioarrays, Chemical vapor deposition, Immobilization, Micropatterns, Surface engineering

1. Introduction Controlled surface engineering has been a long-standing challenge in the development of bioarrays. Moreover, miniaturized diagnostic systems, such as micro-total analysis systems (mTAS) (1), cell-based assays (2), microseparators for proteins (3, 4), DNA (5), and polysaccharides (6), often require universally applicable surface engineering protocols. Some general surface modification techniques have proven to be versatile in alleviating adverse biological effects. One technique that is widely used to tailor the interfacial properties of metals, metal oxides, and semiconductor surfaces is the use of self-assembled monolayers (SAMs) (7). Based on the terminal functional groups exposed on the surface of a SAM, the reactivity of the surface can be varied. SAMs have been used for the direct immobilization of DNA, polypeptides, and proteins (8). However, the use of SAMs is limited due to the relative chemical instability of the monolayer and the specificity of


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the substrates. In contrast, the above-mentioned applications require robust surface chemistry. Extensive efforts have been made to create topological surface patterns using printing methods, such as dip/pen lithography (9), patterning via scanning probes (10), imprinting lithographies (11, 12), or soft lithography (13, 14). Included within soft lithography are micromoulding in capillaries (15), microcontact printing (16), replica molding (17), microtransfer molding (18), solventassisted micromoulding (19), and capillary force lithography (20). Soft lithographical methods rely on the use of elastomeric stamps or replica structures to transfer material from a solution onto a surface. Patterned substrates created using shadow masks included a range of different materials, such as semiconductors (21–23), organic metals (24), polymers (25), biomaterials (26), or cells (27–29). Surface patterns have also been fabricated using lithographical techniques, on the basis of light (30), X-rays (31), electrons (32), ion beams (33), or atoms (34). Furthermore, patterned substrates can be incorporated into microfluidic systems and subsequently used for high-throughput proteomics applications, pharmaceutical screening of cellular assays, or cell-based biosensors. Methods for creating patterns in microfluidic channels previously depended on patterning of a flat substrate, which is then sealed to the microchannel. Some specific processes utilize microfluidic patterning (35), laminar flow patterning (36–38), robotic spotting (39–41), and jet printing (42, 43), and selective plasma etching (44). These patterning methods have been used to pattern hydrogels (45–47), cells (48, 49), and proteins (36) within microfluidic systems. However, they often have several shortcomings. For example, patterns generated by laminar flow patterning and microfluidic patterning are limited to a relatively narrow range of continuous patterns, which are mainly determined by the flow geometry.

2. Chemical Vapor Deposition In addition to solvent-based methods that are being utilized for biomedical surface modification, solventless surface modification methods, such as chemical vapor deposition (CVD) polymerization, are currently being explored for biomedical devices. Many of the advantages of CVD polymerization are unique when compared to solvent-based coating processes. First, impurities associated with the use of solvents, initiators, or plasticizers are essentially nonexistent. Second, CVD coatings are conformal, allowing for simple and uniform modification of three-dimensional substrate geometries (50). Third, although the initiation step requires high temperatures, initiation takes place away from the substrate,

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and the substrates can be controlled and maintained at room temperature. The control over substrate temperature allows for the deposition of polymers onto delicate substrates, as well as onto mechanically strong materials made of inorganic substances. Several examples of CVD-based polymer coatings have been reported: Frank and coworkers (51, 52) have grafted polypeptide chains onto a surface using CVD. Gleason and coworkers (53, 54) have shown that polymerization initiators can be introduced together with the monomer through basic process modification, thus facilitating the polymerization of monomers which do not contain an initiator. Hot filaments within the deposition chamber can be used for initiation of radical polymerizations, which often yields conformal coatings. A major focus of CVD polymerization has been the polymerization of substituted (2.2]paracyclophanes (PCP) to yield functionalized poly(p-xylylenes) (PPX). This CVD polymerization is adapted from a process first developed by Gorham for parylene coatings (55). In this procedure (Fig. 1), a cyclic dimer is sublimated under vacuum (0.2–0.3 Torr), and transported by a carrier gas through an external heat source (T = 600–800°C). If the temperature is sufficiently high, a homolytic cleavage occurs across both bridge bonds, resulting in two quinodimethane diradicals, serving as an initiation step. The radicals then deposit and polymerize onto a sample that is fixed at a particular temperature (between −40 and 60°C). We have successfully modified PCPs with a wide variety of functional groups (56–60), which can then serve as reactive sites for immobilization of biomolecules. Vaporbased polymerization of PCPs produces a conformal PPX coating with mechanical integrity and low dielectric constants. Such properties are useful attributes for various applications including MEMS devices (61–64). In this chapter, we discuss recently developed methods of fabricating micropatterns onto substrates via CVD of reactive poly(p-xylylenes). For this purpose, the CVD technology can be utilized in one of two general ways (Fig. 2): (1) Deposition of a homogenous polymer coating that is reactive, then chemically pattern the coating after CVD treatment, and (2) fabrication of patterns of CVD polymer during the deposition process in situ. 2.1. Microcontact Printing onto Reactive CVD Coatings

Microcontact printing technology can be used to fabricate micropatterns of immobilized biomolecules onto reactive CVD coatings post-deposition. In this method, a PDMS stamp is cast from a photolithographically produced master made of silicon. Once the PDMS is cured, the biomolecule of interest is dissolved in a buffer, and the resulting solution is inked onto the PDMS pattern. The patterned PDMS substrate is then laid onto the surface, and the biomolecules are allowed to react (Fig. 3a). The PDMS stamp can be removed and reused multiple times.

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Fig. 1. Functionalized [2.2] paracyclophanes (PCPs) can be polymerized into functionalized poly(p-xylylenes) (PPXs) with tailored reactivity. (a) Reaction Scheme yielding functionalized poly-p-xylylenes; (b) Block diagram describing the chemical vapor deposition polymerization process; (c) Examples of functionalized [2.2] paracyclophanes that have been used for CVD polymerization. Taken from (60).

One recent example (65) exploits the specificity of hydrazides toward aldehydes and ketones (66). Carbonyl-containing surfaces can be modified using dihydrazide homobifunctional linkers to form hydrazone bonds on one side, yielding alkyl hydrazide spacers on the other side, which can react further with formyl-containing groups in saccharides (66). Adipic acid dihydrazide was chosen as the linker due to its intermediate-length spacer arm, which leads to accessible reactive sites for further reaction. A substrate coated with poly(4-formyl-p-xylylene-co-p-xylylene) (formylPPX) was patterned with adipic acid dihydrazide, hence creating hydrazide-activated surfaces suitable for targeting saccharides.


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Fig. 2. Two general protocols for fabrication of micropatterned surfaces are described. (1) CVD process, followed by subsequent patterning of the reactive coating. (2) Patterned deposition of the CVD polymer.

Fig. 3. Microcontact printing process for (a) the immobilization of sugars onto aldehyde-functionalized PPX and (b) click chemistry. Taken from (65) and (69).

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The hydrazide-modified polymer surface was then reacted with 2-mannobiose, a disaccharide. One mannose group reacted with the hydrazide while leaving the other saccharide group free. Rhodamine-labeled concanavalin A, a mannose-specific lectin that recognizes the free mannose unit (67), was used to investigate saccharide binding. Patterned substrates were visualized using fluorescence microscopy (Fig. 3a, inset). The rhodamine-labeled lectin bound specifically to the disaccharide-presenting surface, which was then immobilized onto a substrate coated with formylPPX and patterned with lines of adipic acid dihydrazide. Immobilization of microscale patterns on formyl-PPX can also be extended towards DNA immobilization (68). Supermolecular nanostamping (SuNS) was used to fabricate DNA nanopatterns immobilized onto formyl-PPX. The patterns can be lines or spots, an important feature for the operation of DNA microarrays. Another example (69) involved the use of poly(4-ethynyl-pxylylene-co-p-xylylene) (ethynyl-PPX), a polymer specifically tailored for use in click chemistry. Its reactivity against azides was studied in order to assess whether the coating can be used for heterogeneous click reactions. Huisgen 1,3-dipolar cycloaddition between ethynylPPX and an azide-containing biotin-based ligands in the presence of copper(II) sulfate and sodium ascorbate was examined (Fig. 3b). This coupling reaction yields triazoles, as described for solventbased systems (70). Sodium ascorbate acts as a reductant, generating CuI ions in situ, which then function as the catalyst (70). Biotin azide was chosen as the representative ligand in this study, because biotin forms a strong noncovalent interaction with streptavidin (which has been widely used for binding biotinylated biomolecules) (56). A thin layer of biotin azide and sodium ascorbate was spread onto a film of ethynyl-PPX and dried using N2. In comparison to the concurrent microcontact printing of catalyst and azide, a twostep approach was found to be superior. A patterned PDMS stamp was inked with a CuSO4 solution and kept in contact with the substrate for 12–18 h. The patterned substrate was then rinsed and incubated with an aqueous solution of rhodamine-labeled streptavidin. The immobilization of biotin azide onto ethynylPPX was assed using fluorescence microscopy. The fluorescence micrograph and ellipsometric thickness map shown in Fig. 3b confirm selective protein coupling in the regions where the CuSO4 solution was microcontact printed, thus demonstrating the spatially directed binding of biotin azide to ethynyl-PPX. Thus, the alkyne groups on the polymer surface are reactive and can be effectively used as anchoring sites for various biomolecules. 2.2. CVD Patterning Within Confined Microgeometries

Even though miniaturized bioanalytical devices contain dimensions of high aspect ratios, the homogeneous modification of their surfaces can be challenging. In an attempt to expand CVD polymerization to the coating of complex microgeometries with


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high aspect ratios, a recent study (71) examined the deposition behavior of functionalized poly(p-xylylenes) within preassembled microfluidic devices. It was demonstrated that CVD polymerization can be used to deposit a range of functionalized poly(p-xylylenes) within confined microgeometries. Seven different poly(p-xylylenes) were deposited via CVD polymerization within both removable and sealed PDMS microchannels (72). A subgroup of five poly(p-xylylenes) had reactive side groups (so-called reactive coatings), while two commercially available poly(p-xylylenes) were included as nonfunctionalized references (ParyleneTM N and C). The PDMS microchannels used in this study were open at both ends and were 75 mm high and 100 mm wide. Both straight (1,600 microns long) and meandering channel (2,800 microns long) layouts with high aspect ratios were studied (Fig. 4). For both straight and meandering microchannels the degree of deposition was constant and did not change with increasing

Fig. 4. Conformal deposition of CVD polymers occurs even within microscale geometries. Facile modification and biofunctionalization of microfluidic channels can be attained. Adapted from (71).

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film thickness. Homogenous surface coverage of different microgeometries has been demonstrated for these reactive coatings. Deposition within aspect ratios of up to 37 was accomplished, based on optical microscopy and imaging XPS results. In addition to the deposition studies, immobilization studies were conducted using permanently sealed PDMS devices (72) after CVD polymerization. The microchannels were coated with either poly(4-amino-p-xylylene-co-p-xylylene) (amino-PPX) or poly(4-trifluoroacetyl-p-xylylene-co-p-xylylene) (PPX-COCF3) prior to immobilization. While amino-PPX provides primary amino groups for coupling with activated carboxyl groups (amide formation), PPX-COCF3 has keto groups that can react with hydrazines or hydrazides. To assess the chemical activity of both reactive coatings, a PFP-derived biotin ligand and a biotin hydrazide ligand were used to evaluate chemical reactivity of amino-PPX and PPX-COCF3, respectively. These ligands undergo nearly quantitative conversion with amines or ketones; also, the interactions between biotin and streptavidin result in confinement of streptavidin on the biotin-modified surface. For all ligand immobilization reactions, aqueous solutions of the corresponding biotin derivative were filled into the sealed microchannels of either meandering or straight geometry. After thorough rinsing with buffer, microchannels were incubated with rhodamine-labeled streptavidin, then the surfaces were rinsed and visualized by fluorescence microscopy. Figure 4 shows microchannels that were coated with polymer and then subjected to the biotin/strepdavidin protocol. Homogeneous distribution throughout the entire microchannel was observed, indicating that functional groups were available throughout the entire coating area, for both aminoPPX and PPX-COCF3. The deposition of reactive CVD coatings within confined microgeometries bridges a critical technological gap toward surface-modified microfluidic devices for use in “BioMEMS” applications. 2.3. Vapor-Assisted Micropatterning in Replica Structures

A related patterning approach utilizes vapor-assisted micropatterning in replica structures (VAMPIR). In this method, chemical and topological surface microstructures can be obtained by masking certain areas of the substrate during CVD polymerization and then depositing the reactive coatings only within the exposed areas. Although conceptually simple, such an approach toward microstructured surfaces came with some challenges. For instance, in CVD polymerization, polymer deposition is transport-limited, and the feasibility of deposition within replica structures with micronscale capillaries was unclear. However, the properties of polymers deposited are of a greater variety. While stencils and shadow masks have been applied for area-selective deposition using both rigid and elastomeric materials (24, 73, 74), many of those pattern processes are limited to hydrophilic polymers that are soluble in


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polar solvents. However, the solvent-free process described here can be used for both hydrophilic and hydrophobic coatings. In a recent study (75), polydimethylsiloxane (PDMS)based replica structures (or stencils) designed to generate a desired surface pattern were reversibly sealed onto a silicon substrate (Fig. 5). The masked substrate was then placed onto a temperature-controlled stage (15°C) inside of the CVD polymerization chamber. 4-pentafluoropropionyl[2.2]paracyclophane underwent pyrolysis and polymerized into poly(4- pentafluoropropionyl-p-xylylene-co-p-xylylene). After completion

Fig. 5. (a) Process of vapor-assisted microstructuring using replica structures (left column) as well as shadow masks (right column) during CVD polymerization. Fluorescently tagged molecules are immobilized onto (b) poly(4-pentafluoropropionyl-p-xylylene-co-p-xylylene) and (c) poly(p-xylylene-4-methyl-2-bromoisobutyrate-co-p-xylylene). The latter was used to grow poly(OEGMA) within the squares, which inhibited the adsorption of fibrinogen (i ) and attachment of NIH 3T3 fibroblasts (ii ). Adapted from (75) and (76).

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of the CVD polymerization, the PDMS molds were removed, and hence a chemically and topologically structured surface was created. Surface features are defined by the deposited polymer footprints. In one instance, a substrate was masked with a PDMS membrane, which contained footprints shaped into the letters “UM” (Fig. 5b). Subsequent CVD polymerization resulted in ultra-thin polymer films outside of the masked areas. Imaging X-ray photoelectron spectroscopy confirmed the presence of characteristic elements within their localized regions – i.e., fluorine was found only outside the “UM” footprint boundaries, whereas silicon was found within the footprint. PPX-COC2F5 has keto groups that can react with hydrazines or hydrazides in high yields (66). Biotin hydrazide, a model ligand, was used again for immobilization onto the functionalized polymer. In a subsequent step, the well-known interactions between biotin and streptavidin were used for visualization of surface-immobilized biotin. To examine the immobilization of biotin ligands within the patterns, streptavidin conjugated with CdSe quantum dots (Qdot® 525) were allowed to bind to the biotin-modified surfaces. Binding was homogenous throughout the surface-modified areas. As anticipated, after biotin immobilization, the subsequently self-assembled quantum dots were resolved into a range of different predesigned patterns. In another instance (76), poly(p-xylylene-4-methyl-2bromoisobutyrate-co-p-xylylene) was patterned in the same manner as described for PPX-COC2F5. A PDMS structure with square holes was used during the deposition process. After patterned deposition of poly(p-xylylene-4-methyl-2-bromoisobutyrateco-p-xylylene) onto PMMA surfaces (Fig. 5c), the initiator contained within the functionalized coating was used to perform ATRP of poly(OEGMA). Fluorescently labeled fibrinogen was found to adsorb selectively onto the bare PMMA substrate, whereas the poly(OEGMA)-modified squares inhibited protein adsorption (Fig. 5c.i). The attachment and growth of NIH3T3 fibroblasts followed a similar trend (Fig. 5c.ii). The lower limit of VAMPIR feature sizes was also evaluated. A PDMS replica structure was prepared with varying distances between posts (150, 100, 50, and 25 mm). Thicknesses of the deposited polymer coatings were measured in the center of each region. The thickness decreased from 49.6 nm measured for the area with 150 mm feature sizes, over 42 nm (100 mm) and 28.7 nm (50 mm), to 7.3 nm measured for the areas with 25 mm wide features. A relative coordinate system is used to express the coating thickness distribution for different feature sizes (Fig. 6) (77, 78). Rearrangement of the thickness data in terms of dimensionless thicknesses d(x)/d0 and width (x/b) reveals a surprisingly uniform behavior. d(x)/d0 denotes the ratio of the absolute film thickness at the given point x to that at the open surface, and x/b is the ratio of depth over width of the feature. As indicated in Fig. 6, the


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Fig. 6. Plot of dimensionless thicknesses d(x)/d0 vs. dimensionless width (x/b), where d0 is film thickness (nm) on an open area for an according dimension recorded by using imaging ellipsometry; b is the width (mm) of the dimension. Taken from (75).

dimensionless thicknesses measured for feature sizes ranging from 25 to 200 mm fall onto a single trend line. Process parameters dominate over feature size, as predicted by Tolstopyatov et al. In this study, universal thickness distributions for the deposition of unfunctionalized poly-p-xylylene in microchannels were found (77, 78). Given the theoretical and experimental findings done on vapor deposition, vapor-assisted microstructuring in replica structures (VAMPIR) establishes a simple technique to create both chemical and topological surface patterns. 2.4. Projection Lithography-Based Patterning Using on Photoreactive CVD Polymers

Another method of post-CVD micropatterning involves the projection of ultraviolet light onto photoreactive PPX coatings. Recently, a photodefinable polymer, poly(4-benzoyl-p-xylylene-co-p-xylylene) (benzoyl-PPX), was prepared by CVD polymerization and was used for fabrication of discontinuous surface patterns onto threedimensional microscale objects (79, 80). Due to its structural analogy to benzophenone, the reactive coating provides light-reactive carbonyl groups that are readily activated at wavelengths of ~340 nm. The temporarily generated free radicals spontaneously react with adjunct molecules, mainly via C–H abstraction (81). Suh et al. (82) have demonstrated the ability of benzoyl-PPX to immobilize hydrogel elements, an important requirement in microfabrication processes. Capillary force lithography was combined with photoreactive patterning in order to fabricate an array of immobilized PEG hydrogels. As shown in Fig. 7, microstructured stents and microchannels were recently fabricated by a two-step procedure: (1) coating of the objects with a photodefinable polymer, poly[4-benzoylp-xylylene-co-p-xylylene], via CVD polymerization (82, 83)

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Fig. 7. Schematic description of the 3D projection lithography technique. The method comprises two process steps: deposition of the photodefinable CVD coating (step 1) and subsequent projection lithographic rendering of the polymercoated colloids (step 2). Inset shows an endovascular stent and a microfluidic pathway that are patterned using projection lithography. Adapted from (79) and (80).

and (2) spatially controlled surface reaction of the photoreactive coatings using a highly parallel projection lithographic patterning step. Once the deposition of the photoreactive coatings on endovascular stents was demonstrated, spatially directed microstructuring became achievable. To obtain spatially controlled surface patches on stents, we selectively illuminated certain areas of previously coated stents with UV radiation at 365–400 nm by using a high-throughput projection technique that has been previously used for in situ synthesis of peptides and DNA on microarrays (84–86). After surface modification via CVD polymerization, coated stents were immersed in an aqueous solution of a four-arm star polyethylene glycol (star-PEO, 10,000 g/mol, 1 weight-%). For patterning, a digital micromirror device (DMD, Texas Instruments) was used as a dynamic mask (87). UV radiation of about 365– 400 nm wavelength was modulated by the dynamic mask. The corresponding patterns were then transferred onto the stents (Fig. 5a). DI-water was used to separate excess PEO. The stents were incubated with protein (Alexa Fluor 546-conjugated fibrinogen, Molecular Probes Inc.) solutions for 5 min. After incubation, phosphate-buffered saline (PBS) and DI-water were used to


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rinse off excess adsorbed proteins. After CVD coating, PDMS microchannels were immersed in an aque-ous solution of biotinPEO-LC-amine (10 mM, Pierce) in PBS (pH 7.4). The corresponding patterns were then transferred onto the microchannels. After rinsing, samples were incubated with rhodamine (TRITC)conjugated streptavidin (50 mg/mL, Pierce) in PBS containing 0.1% (w/v) bovine albumin and Tween 20 (0.02% (v/v)) for 60 min. The surface was rinsed several times with PBS containing 0.1% (w/v) bovine albumin and Tween 20 (0.02% (v/v)). Programmable patterns were created by using a 1,024 × 768-pixel digital micromirror device (DMD) (Fig. 7). While the entire surface of the substrates was coated with the photoreactive coating during CVD polymerization, only the areas illuminated with the DMD underwent photochemical conversion of the carbon–oxygen double bond from the singlet ground state into the corresponding triplet state (88). As seen in Fig. 7, an endovascular stent and a microchannel were coated with the photoreactive benzoyl-PPX polymer and subsequently exposed to the DMD grid UV patterning. The PEO-free areas facilitated adsorption of fibrinogen, while the areas of PEO immobilization did not (inside squares). An identical pattern of immobilized streptavidin (inside the squares) was observed within microchannels. Despite the irregular shape and small dimensions of the objects, homogenous chemical micropatterns were obtained on the stent surface, making possible the progression of advanced surface architectures for medical devices. 2.5. Selective Deposition of Reactive CVD Polymers

While the methods mentioned thus far rely on physical means to obtain spatially controlled surface modification, an even simpler approach would be to selectively inhibit CVD polymerization and deposition based on differences in the substrate chemistry. Jensen and coworkers first reported the selective inhibition of parylene™ N, parylene™ C, as well as poly(p-phenylene vinylene) (PPV) by iron and iron salts (89) and used selective CVD polymerization to create a wide range of patterns (89). It was also shown that, in a similar fashion, several transitional metals, metal salts, and organometallic complexes inhibit the growth of parylene™ N and C (90). Suh et al. have used selective CVD polymerization within submicron scale PDMS channels to yield high aspect ratio structures. Surface-coated PDMS channels of as little as 180 nm in width were obtained by depositing iron on the bottom of microchannels and then selectively depositing polymer only on the channel sidewalls (91). Recently, the first selective CVD polymerization of a functionalized poly-p-xylylene was reported (92). The result is a simple patterning process that relies on selective inhibition of polymer films that can act as chemical anchors for further surface modification via covalent immobilization. The study investigated selective inhibition of CVD polymerization by series of metals. Based on IRRAS spectra, Ti appeared

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to be the only metal that effectively inhibited the growth of poly(4-vinyl-p-xylylene-co-p-xylylene) (vinyl-PPX) during the CVD polymerization process. Ti also inhibited CVD polymerization of poly(4-chloro-p-xylylene). Next, a Ti-coated silicon wafer was prepared, and circles of Au were deposited onto the Ti-coated silicon using a shadow mask. Following the protocol outlined in Fig. 8a, this bi-metal surface was CVD coated with vinyl-PPX and subsequently subjected to olefin cross-metathesis reaction with fluorescein O-methacrylate. Only the Au islands showed significant fluorescence signals (Fig. 8b). In addition, a strong contrast

Fig. 8. (a) Schematic illustration of the selective deposition of poly(4-vinyl-p-xylylene-co-p-xylylene) on patterned Ti/Au substrates. Au was deposited through a shadow mask onto a Ti-coated silicon wafer followed by polymer deposition via CVD polymerization. Olefin cross-metathesis reaction of fluorescein O-methacrylate was used to probe the selective deposited polymer on Au surface. (b) Fluorescence micrograph reveals that only the Au islands showed appreciable signals of fluorescence. Taken from (92).


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was observed between Au and the Ti surfaces providing further clarification on the selective inhibition of CVD of vinyl-PPX. Moreover, Ti or Au samples were coated with vinyl-PPX, and cross-metathesis reaction of poly(ethylene glycol) methyl ether methacrylate (PEGMA) was conducted on both samples. For each modification step, IRRAS spectra were recorded. Absorption bands at 2,866, 2,924, and 3,013 cm–1 due to C–H symmetric and asymmetric stretching bands can be clearly detected on the Au surface after deposition of vinyl-PPX. In addition, a strong, sharp band at 1,717 cm–1 indicative of the C=O bond of the ester group, and a strong band at 1,110 cm–1, which is due to C–O–C stretches of the ester group appeared after olefin cross-metathesis reaction of OEGMA. At each modification step, no significant signal was detected on the Ti surface, providing strong evidence that vinyl-PPX was not deposited on Ti, which consequently prevented cross-metathesis reaction of OEGMA. The fact that the selectively deposited reactive coatings are equipped with functional groups for further surface modification provides a simple access route toward micro- and nanostructured surfaces.

3. Conclusions The merger of materials science and biotechnology has fueled the demand for novel types of bioarrays with highly engineered surfaces. Toward this goal, a range of methods for the facile fabrication of surface micropatterns has been developed based on vapor-based reactive coatings. In this chapter, we have discussed the current use of CVD polymerization toward surface engineering of bioarrays and biodiagnostic devices. Specifically, we have outlined the adaptability of the CVD process toward microfabrication of polymer thin films. Two general fabrication methods were discussed. First, one may fabricate a biomolecular micropattern after the reactive poly(p-xylylene) has been coated. Micro contact printing and projection lithography are two approaches used for post-CVD surface modification. In microcontact printing, a patterned PDMS stamp is inked with the molecule of interest, then subsequently laid upon the CVD film. Projection lithography employs micromirrors in order to project UV light onto a photoreactive CVD polymer coatings. Secondly, one may pattern a CVD polymer onto the substrate directly during the deposition process. Patterned replica structures mounted onto a substrate will mask deposition over specified areas. In addition, certain polymers have been known to deposit selectively on different transition metals. Thus, a patterned metal substrate would lead to patterned polymer deposition. Microstructuring of reactive CVD polymer coatings produces robust coatings with excellent

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Progress Report on Microstructured Surfaces Based on Chemical Vapor Deposition 79. H. Y. Chen, J. M. Rouillard, E. Gulari, J. Lahann, “Colloids with high-definition surface structures” Proc. Nat. Acad. Sci. 2007, 104, 11173. 80. H. Y. Chen, J. M. Rouillard, E. Gulari, J. Lahann, “High-precision surface modification of three-dimensional geometries using photodefinable ultra-thin polymer coatings” PMSE Preprints 2006, 95, 125. 81. W. W. Shen, S.G. Boxer, W. Knoll, C.W. Frank, “Polymer-supported lipid bilayers on benzophenone-modified substrates” Biomac romolecules 2001, 2, 70–79. 82. K. Y. Suh, R. Langer, J. Lahann, “A novel photodefinable reactive polymer coating and its use for microfabrication of hydrogel elements” Adv. Mater. 2004, 16, 1401. 83. H. Y. Chen, J. Lahann, “Fabrication of discontinuous surface patterns within microfluidic channels using photodefinable vapor-based polymer coatings” Anal. Chem. 2005, 77, 6909. 84. J. Tian, H Gong, N. Sheng, X. Zhou, E. Gulari, X. Gao, G. Church, “Accurate multiplex gene synthesis from programmable DNA microchips” Nature 2004, 432, 1050. 85. J. P. Pellois, X. Zhou, O. Srivannavit, T. Zhou, E. Gulari, X. Gao, “Individually addressable parallel peptide synthesis on microchips” Nat. Biotech. 2002, 20, 922.

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86. X. L. Gao, X. C. Zhou, E. Gulari, “Light directed massively parallel on-chip synthesis of peptide arrays with t-Boc chemistry” Proteomics 2003, 3, 2135. 87. X. Gao, E. LeProust, H. Zhang, O. Srivannavit, E. Gulari, P. Yu, C. Nishiguchi, Q. Xiang, X. Zhou, “A flexible light-directed DNA chip synthesis gated by deprotection using solution photogenerated acids” Nucl. Acids Res. 2001, 29, 4744–4750. 88. K. S. Taton, P. E. Guire, “Photoreactive selfassembling polyethers for biomedical coatings” Colloids Surf. B 2002, 24, 123–132. 89. K. M. Vaeth, K. F. Jensen, “Selective growth of Poly(p-phenylene vinylene) prepared by chemical vapor deposition” Adv. Mater. 1999, 11, 814. 90. K. M. Vaeth, K. F. Jensen, “Transition metals for selective chemical vapor deposition of parylene-based polymers” Chem. Mater. 2000, 12, 1305. 91. K. Y. Suh, R. Langer, J. Lahann, “Fabrication of elastomeric stamps with polymer-reinforced sidewalls via chemically selective vapor deposition polymerization of poly(p-xylylene)” App. Phys. Lett. 2003, 83, 4250. 92. H. Y. Chen, J. H. Lai, X. Jiang, J. Lahann, “Substrate-selective chemical vapor deposition of reactive polymer coatings” Adv. Mater. 2008, 20, 3474.

Chapter 17 Methods for Forming Human Microvascular Tubes In Vitro and Measuring Their Macromolecular Permeability Gavrielle M. Price and Joe Tien Abstract This chapter describes a protocol for forming open endothelial tubes in vitro and quantifying their permeability to macromolecules. These tubes consist of confluent monolayers of human microvascular endothelial cells in perfused microfluidic collagen gels. The cylindrical geometry of the tubes mimics the shape of microvessels in vivo; it allows simultaneous and/or repeated measurements of permeability coefficients and detection of focal leaks. We have used these in vitro models to test the effects of agonists on microvascular permeability and are developing arrays of microvascular tubes to enable large-scale testing. Key words: Microvascular tissue engineering, Endothelial cells, Collagen, Permeability, Focal leaks

1. Introduction This chapter describes methods recently developed by our group to quantify the barrier function of engineered human microvascular tubes in vitro (1, 2). It provides step-by-step instructions for forming endothelial tubes within channel-containing collagen gels, measuring their permeabilities to macromolecules, and determining their number of focal leaks. We assume that the reader is familiar with standard cell culture techniques and with our complementary review on methods to form cylindrical channels within collagen (3). Our methods are adapted from those originally designed for use in intact or explanted microvessels from mice, rats, and frogs (4–8). In vivo, macromolecular permeability can be quantified with two metrics: (1) an effective permeability coefficient Pd, which describes the ability of a solute to escape uniformly from the vascular lumen and (2) the density of focal leaks, which are localized regions of high permeability (9). The reflection coefficient s,


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which describes the oncotic contribution of a solute, provides a third measure of barrier function (10, 11); we do not describe how to measure this quantity in our system. Traditionally, the permeability of human endothelium has been examined in planar cell cultures in vitro (12). These cultures lack physiologically relevant shear stress, and the permeability coefficients are averaged over large areas and long times. In contrast, the open cylindrical architecture of our vessels allows constant perfusion, which enables real-time measurement of permeabilities and focal leaks, just as in cannulated microvessels. The small footprint of these tubes may eventually enable the development of microvascular arrays for high-throughput assays of human microvascular barrier function.

2. Materials 2.1. Endothelial Cell Culture

1. Human dermal blood microvascular endothelial cells (BECs; Lonza) or human dermal lymphatic microvascular endothelial cells (LECs; Lonza). 2. Sterile phosphate-buffered saline (PBS; Invitrogen). 3. 60-mm-diameter tissue culture polystyrene dishes (Corning). 4. 0.1% gelatin from pig skin (Sigma) in PBS, filter-sterilized, autoclaved, filter-sterilized again, and stored at 4°C. 5. MCDB 131 medium (Invitrogen), supplemented with 10% fetal bovine serum (FBS; Invitrogen), 1% penicillin–streptomycinglutamine (Invitrogen), 1 mg/mL hydrocortisone (Sigma), 80 mM dibutyryl cyclic AMP (db-cAMP; Sigma), 25 mg/mL endothelial cell growth supplement (ECGS; Biomedical Technologies), 2 U/mL heparin (Sigma), and 0.2 mM L-ascorbic acid 2-phosphate (Sigma). 6. Complete medium (see Subheading 2.1, item 5) supplemented with 3% 70 kD dextran (dex; Sigma) and filter-sterilized (“3% dex media”). 7. Trypsin/EDTA (Invitrogen). 8. Dispase (Invitrogen), optional.

2.2. Formation of Microvascular Tubes

1. Culture media (see Subheading 2.1, item 5). 2. Trypsin/EDTA. 3. 1.7-mL microcentrifuge tubes (Costar). 4. 3% dex media (see Subheading 2.1, item 6). 5. Collagen gels with channels, assembled between silicone housings and glass coverslips (as described in 11.3.1–11.3.4 of (3)). 6. Silicone lids with attached tubing (as described in 11.3.5.2 of (3)).

Permeability of Microvascular Tubes

2.3. Measurement of Permeability

283

1. Alexa Fluor 594-conjugated bovine serum albumin (BSA594; Invitrogen). 2. Alexa Fluor 488-conjugated 10 kD dextran (dex-488; Invitrogen). 3. 3% dex media (see Subheading 2.1, item 6) supplemented with 50 mg/mL BSA-594 and 20 mg/mL dex-488. 4. A microscope environmental chamber (Zeiss) that maintains temperature at 37°C. 5. Image-processing software, such as ImageJ (NIH freeware). 6. Silicone blocks with channels (as described in 11.3.3.1 of (3)), with the same dimensions as the channel-containing gels in Subheading 2.2, item 5. 7. Silicone lids with tubing (see Subheading 2.2, item 6).

3. Methods As shown in Fig. 1, we form human endothelial tubes by seeding BECs or LECs into collagen gels that contain open channels and allowing the seeded cells to form confluent linings on the channels

Fig. 1. Schematic diagram of the formation of a perfused microvascular tube from a channel-containing collagen gel. Left panel, a channel within a collagen gel. The collagen is surrounded by a silicone housing and a glass substrate (3 ). The parameters “d ” and “ℓ ” refer to the diameter and length of the channel, respectively. Middle panel, a channel seeded with endothelial cells (ECs). Right panel, a seeded tube coupled to a lid that establishes high-flow perfusion. The tubing of the lid aligns with the centers of the inlet and outlet wells adjacent to the tube.

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under constant perfusion. Once the cells reach confluence, the lumen widens with the inlet and outlet diameters increasing by ~40 and ~10%, respectively (1, 2). Figure 2 illustrates a typical time-course of this expansion. Tubular widening takes place over 2 days, and we usually perform permeability assays on the third day after seeding. The operating principle behind our permeability assay is to measure the rate at which a fluorescently labeled macromolecule (bovine serum albumin or dextran) escapes from the endothelial lumen. This idea has been implemented previously for intact or explanted microvessels (5). Application of this assay to engineered endothelial tubes requires two modifications: First, because our tubes consist solely of an endothelial monolayer, they are not

Fig. 2. Maturation of tubes over a span of 3 days. The top row shows phase-contrast images of a middle segment of an unseeded channel. The second row displays spreading endothelial cells in a channel a few hours after seeding (day 0). The subsequent rows show changes in tubular morphology as the cells grow to confluence: By day 1, endothelial cells have formed a confluent monolayer. By day 2, the tube has widened. By day 3, morphological changes have stabilized.


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mechanically strong enough to withstand direct cannulation. The introduction of fluorescent molecules thus has a lag time on the order of several minutes, as a dead volume is flushed out of the inlet well and tubing. Second, the perfusing medium contains bleachable solutes (possibly, flavins) that can interfere with imaging, which limits the frequency of measurement. With these caveats in mind, we can obtain Pd for each macromolecule. Manual counts of focal leaks provide complementary data on the nonuniformity of leakage. Calibration of the permeability assay is absolutely essential to obtain meaningful values of Pd. The methods described below confirm that the fluorescence signal is proportional to the concentration of solute, and that light collection efficiency does not depend on the location of fluorophore (e.g., above or below the mid-plane of the tube). We use a standard inverted epifluorescence microscope (Zeiss), with a Plan-Neo 10×/0.30 NA objective, 1,388 × 1,040 resolution AxioCam HRm camera, and flat-field correction software. The fluorescent solutes we use are conjugated to Alexa Fluor dyes, which do not photobleach appreciably with our exposure doses. Our calculation of Pd assumes that the tube is cylindrical in geometry; this assumption is valid within each ~1-mm-wide measuring window. The assay also takes the perfusion rate into account to ensure that the lumenal concentration of fluorescent solute is constant during imaging. Imaging systems that do not satisfy the above requirements (e.g., by using highly bleachable dyes such as fluorescein) require extensive mathematical compensation to obtain accurate values of Pd (6, 13). The equation we use for Pd calculates the effective permeability coefficient, which includes diffusional and convective contributions (10, 14). Since the tubes are enclosed in an impermeable housing (silicone and glass), we assume that transendothelial water flux – and, therefore, convective transport – is negligible. The convective contribution to permeability cannot be ignored if a large water flux exists across the endothelium (e.g., due to a large transendothelial pressure), and a more complex analysis must be used (5, 14, 15). 3.1. Formation of Endothelial Tubes 3.1.1. Endothelial Cell Culture

3.1.2. Seeding Channels in Collagen Gels

1. Coat polystyrene dishes with gelatin for 40 min at room temperature. Wash with sterile water and dry. 2. Plate human BECs or LECs in the gelatin-coated dishes. Routinely passage confluent cultures at a 1:4 dilution using trypsin/EDTA or dispase. A confluent 60-mm-diameter dish typically provides enough cells to seed 3–4 channels. 1. Form collagen gels that contain single open channels, following the directions described in our recent work (1, 3). Condition the gels with 3% dex media for at least 1 h at 37°C

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by adding media to the inlet well and removing it from the outlet well. Do not allow any media to overflow on top of the silicone housing as this media will interfere with perfusion under high pressures. 2. Treat a culture of BECs or LECs with trypsin/EDTA, collect the cells in ~1 mL dextran-free media, and pellet them at 200 × g for 2 min (see Note 1). 3. Aspirate the media from the vial of pelleted cells and gently resuspend the cells in 20 mL of 3% dex media. 4. Aspirate media from the inlet and outlet wells of a conditioned collagen gel. 5. Add 1–2 mL of cell suspension to each of the inlet and outlet wells. A steady, dense stream of cells should begin flowing through the collagen channel. 6. Modulate the flow velocity by tilting the dish that contains the collagen gel until the cells are nearly stationary within the channel. Hold the dish steady for 30–40 s to allow cells to settle and adhere to the collagen channel. We typically perform this step while constantly viewing the channel with a 10× objective on an inverted microscope. 7. If the seeding is sparse, level the dish to add more cell suspension to the channel as needed. Seeding should require ≤5 min for a single channel (see Note 2). 8. Gently wash the inlet and outlet wells twice with 3% dex media. Avoid disturbing the collagen, else the gel may detach from the surrounding silicone or glass. 9. Add a large drop of 3% dex media to the inlet well and add a small drop to the outlet. Place the seeded tube in a 5% CO2 incubator at 37°C. The cells should visibly spread within the channel after 15 min (see Note 3). Wait at least 1 h before establishing perfusion under high pressure (see below). 3.1.3. Perfusing Seeded Tubes

1. Assemble perfusion lids and associated tubing and dishes by following step 13.3.5.2 described in our recent review (3). 2. Fill reservoir dishes with 30 mL of warm 3% dex media and aspirate media through the tubing. 3. Place a lid on a seeded channel to establish fluidic contact between the tubing and the inlet and outlet wells (see Note 4). 4. Set the height difference of the reservoirs to ~6 cm. A pressure difference of 6 cm H2O should yield a flow rate of 0.5-1 mL/h for subconfluent tubes and ~1 mL/h for confluent, widened ones. 5. Regenerate the pressure difference by pipetting media from the outlet reservoir to the inlet reservoir every ~12 h (see Note 5). The same media may be reused to perfuse a microvascular tube


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for 3 days (by which we usually perform the permeability assay), after which the media should be replaced (see Notes 6–11). 3.2. Control Experiments and Calibration of Permeability Assay

All control experiments and calibrations should be performed under conditions as close as possible to those used in the actual permeability assay (e.g., with environmental chamber warmed to 37°C, in the dark, etc.).

3.2.1. Signal Detection

1. Place a drop of BSA-594 or dex-488 between two #1½ glass coverslips. Capture fluorescence images using flat-field correction, and measure the average light intensity (e.g., with ImageJ). Focus at various planes to ensure that the intensity of the collected light does not change with focus; the range of focus should span ~1 mm. 2. Repeat the above step with different solute concentrations to create a standard curve of fluorescence intensity vs. concentration. The solute concentrations used in all subsequent sections should be within the linear range of this curve. We typically find a linear range of 0.2–50 mg/mL for BSA-594 and dex-488.

3.2.2. Determination of Assay Sensitivity

1. Form channels in silicone by following step 11.3.3.1 of our review on microfluidic gels (2). 2. Establish perfusion exactly as described for endothelialized tubes (see Subheading 3.1.3) with fluorescent 3% dex media. 3. Capture several fluorescence images in succession. Since silicone is impermeable to proteins, the intensity of the images should theoretically not vary over time. The range of values indicates the inherent noise of the imaging system (e.g., due to lamp flicker) and sets a bound on the precision of our permeability measurements (see Note 12).

3.2.3. Determination of Lag Time

1. Establish perfusion in a silicone channel as in Subheading 3.2.2, but with nonfluorescent 3% dex media. 2. Supplement the media in the inlet reservoir with 50 mg/mL BSA-594 and 20 mg/mL dex-488. 3. Capture fluorescence images every minute as the fluorescent solute flows through the tubing into the inlet well and through the silicone channel. The lag time is the time at which the intensity of fluorescent solute reaches a maximum (within the sensitivity determined in Subheading 3.2.2). Increasing the length of tubing, increasing the size of the inlet well, or decreasing the perfusion rate will increase the lag time. With our standard setup and perfusion conditions, we observe a lag time of 1 so that their sum is 1. For m equal to 2, this is equivalent to normalizing the coefficient linearly to make their sum 1. When m is close to 1, then the cluster center closest to the point is given much more weight than the others, and the algorithm is similar to k-means. The fuzzy c-means algorithm is very similar to the k-means algorithm where one can: ●●

●●

●●

Choose a number of clusters. Assign randomly to each point coefficients for being in the clusters. Repeat until the algorithm has converged (that is, the coefficients’ change between two iterations is no more than e, the given sensitivity threshold): –– Compute the centroid for each cluster. –– For each point, compute its coefficients of being in the clusters.

The algorithm minimizes intracluster variance as well, but has the same problems as k-means, the minimum is a local minimum, and the results depend on the initial choice of weights. According to Kim et al. (43), FCM clustering can be represented as follows: n

c

minimize J fcm (W , V ) = ∑∑ (wik ) xi − vk , i =1 k =1

m

2

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where Jm(W,V) represents the objective function defining the quality of the result obtained for prototypes V and membership W, and m is the degree of fuzzification in the clustering. The membership degrees, wik, are defined such that: c 0 ≤ wik ≤ 1, under the constraint of ∑ k =1 wik = 1, for i = 1, …, n. 2

V = (vk) is the cluster center or prototype and xi − vk is the Euclidean distance between gene i and the prototype of cluster k. FCM can be used especially when clusters are alike and sample subgroups differ only to a lesser degree. Cluster analysis is generally visualized using a graphic plot. The compound regulation (up- and downregulation) in each group is displayed in pseudo-colors (green as downregulation and red as upregulation). This display is often referred to as a heatmap and is frequently used in literature for visualization. 2.4.5. Principal Component Analysis

PCA can be used for dimensionality reduction in a data set by retaining those characteristics of the data set that contribute most to its variance, and by keeping lower-order principal components and ignoring higher-order ones (33, 44–46). Such low-order components often contain the “most important” aspects of the data. However, depending on the application, this may not always be the case. PCA is mathematically defined as an orthogonal linear transformation that transforms the data to a new coordinate system such that the greatest variance by any projection of the data comes to lie on the first coordinate (called the first principal component), the second greatest variance on the second coordinate, and so on. PCA is theoretically the optimum transform for a given data in least square terms. PCA has the distinction of being the optimal linear transformation for keeping the subspace that has largest variance. Each microarray gives one value for each principle component or in general dimension. Values and microarrays are termed eigenvalue and eigenarray after transformation (44). As PCA is a dimension reduction technique, the following applies to the data set (46). From the original set of variables Xj, PCA constructs a new set of uncorrelated and orthogonal variables Pj . They are linear combinations of mean-centered variables X j = X j − X j and are often called the loadings or the principal components. It is assumed that these loadings correspond with the eigenvectors of the sample covariance matrix S=

n 1 ′ xi − x )(xi − x ) ( ∑ (n − 1) i =1

of the data. For each loading vector Pj the corresponding eigenvalue lj of S tells us how much of the variability of the data is explained by Pj through the relation lj = var (Pj ) . Usually, these

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loading vectors are sorted in descending order of the eigenvalues. Hence, the first k principle components explain most of the variability of the data. After selecting k, we can project the p-dimensional data points onto the subspace spanned by k loading vectors and compute their coordinates with respect to Pj . This yields the scores ti = P (xi − x )

for each i = 1, …, n which have trivially zero mean, as all points taken together cancel each other out in their variation. With respect to the original coordinate system, the projected data point is computed as the fitted value  . xˆ i = x + Pt i

PCA can be employed for example to visualize differences of cell types, diseases and tissues. As microarrays are transformed into one point (eigenarray), it is made simple to display vast sample numbers and group them together. 2.4.6. Other Methods

More recently, pathway analysis (e.g., (47)) and gene set enrichment analysis (GSEA) (48) have been applied for the grouping and characterization of array data output. In this analysis, terms with functional meaning that have previously been attributed to the biological compounds accessed by the microarray are grouped by function. For example, the output of DNA arrays can be grouped or filtered by gene ontology (GO) (http://www.geneontology.org) or by association with KEGG pathways (http://www.genome.jp/ kegg/) (49). GSEA pioneered a variety of methods to search for groups of functionally related compounds with a coordinate overor underexpression across a list of genes ranked by differential expression coming from microarray experiments. For a current status of available methods for this analysis see ref. 50.

2.5. Example

As an example of microarray output data, results of a low-density microarray were generated. The array design included 30 biological compounds tested for regulation, and one calibrator, defined as equal in all samples. Two groups (Healthy vs. Ill) with each three individual samples (biological replicates) were calculated. Values are shown in Table 1. With the use of the Calibrator, the microarrays were normalized (described above). Briefly, the mean was calculated for all Calibrator values. Mean(Calibrator) =

∑ all _ calibrators

Number _ of _ samples

.

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Table 1 Raw data for example microarray Raw data

Healthy 1

Healthy 2

Healthy 3

Compound 1

6,490

5,480

5,435

196

288

207

Compound 2

7,970

6,630

6,794

201

294

212

Compound 3

7,173

6,011

6,062

72

106

77

Compound 4

10,247

8,397

8,884

705

1,032

743

Compound 5

12,524

10,165

10,974

1,053

1,541

1,110

Compound 6

7,742

6,453

6,585

73

108

78

Compound 7

9,222

7,602

7,943

104

153

110

Compound 8

7,628

6,364

6,480

180

264

190

Compound 9

7,742

6,453

6,585

97

143

103

Compound 10

10,133

8,309

8,780

7,752

10,666

9,892

Compound 11

7,970

6,630

6,794

6,116

8,487

7,804

Compound 12

7,742

6,453

6,585

5,944

8,258

7,584

Compound 13

10,247

8,397

8,884

7,839

10,781

10,002

Compound 14

9,108

7,513

7,839

6,977

9,634

8,903

Compound 15

7,628

6,364

6,480

5,857

8,143

7,474

Compound 16

9,905

8,132

8,571

7,580

10,437

9,672

Compound 17

10,589

8,663

9,198

8,097

11,125

10,332

Compound 18

9,564

7,867

8,257

7,322

10,093

9,343

Compound 19

8,995

7,425

7,734

6,891

9,519

8,793

Compound 20

11,955

9,723

10,452

9,131

12,501

11,651

Compound 21

342

292

282

517

757

546

Compound 22

455

389

376

11,026

16,149

11,631

Compound 23

512

438

423

1,938

2,839

2,048

Compound 24

285

243

235

11,413

16,716

12,035

Compound 25

319

272

263

7,718

11,304

8,133

Compound 26

342

292

282

7,752

11,355

8,173

Compound 27

512

438

423

9,691

14,193

10,215

Compound 28

239

204

198

11,396

16,691

12,018

Compound 29

342

292

282

6,719

9,841

7,086

Compound 30

911

778

753

6,202

9,084

6,540

10,970

14,130

11,950

14,500

10,890

12,500

Calibrator

Ill 1

Ill 2

Ill 3

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The factor that let each calibrator result in equaling the mean was applied to all compound values of the corresponding group. e.g., Calibrator (Healthy 1) × X = mean(Calibrator), where X is the normalizing factor. The arising arbitrary numbers are given in Table 2. These data represent the starting point for further analysis as well as visualization of the results. The biological compound expression values are visualized in a heatmap (darker grey upregulation, lighter grey downregulation (in general color coded green); both against the mean of all expression values) as depicted in Fig. 1. For this illustration and for all subsequent output files Genesis by the TU Graz (Austria) was used (http://www.genome. tugraz.at/). In this example, it is apparent that Compounds 1–9 are more represented in samples Healthy 1–Healthy 3, whereas Compounds 22–30 are more frequently represented in Ill 1–Ill 3. Compounds 10–20 appear to be similar regarding the measured values. Compound 21 is increased in the “Ill”-group, but the fold change (twofold) is not high enough to induce a color switch. To find significantly differences in the generated data, hierarchical clustering, k-means clustering and one-way ANOVA analysis was employed. As previously described, the length of the branches of the dendrogram (resulting from hierarchical clustering) shows the distance of similarity. In essence, shorter branches show more similar samples or compounds, whereas longer branches symbolize more differences. The resulting dendrogram and hierarchical expression cluster is provided in Fig. 2. Hierarchical clustering shows us that there are three distinct groups present in the analyzed compounds and two in the samples. Distance to the next branch in the dendrogram gives an idea of the degree of similarity. This type of clustering is unsupervised and divides the data set in vast number of groups. If however the group number is predictable, k-means clustering can be used with k as the number of clusters as in Fig. 3. By having three groups of compounds → k = 3 k-means clustering will give the groups in different clusters. Group 1 (left, upregulated in “Healthy”), Group 2 (middle, upregulated in “Ill”), and Group 3 (right, no difference in regulation) are depictured separately. Although illustration gives us an idea of sample and compound regulation, significance testing is necessary to see the true difference. For this example, one-way ANOVA was used due to low complexity of the data. The arising p values and significant statistics are provided in Table 3. One-way ANOVA shows the significance in a p value. In some cases, the program also answers the significance question directly. For Compounds 1–9 and 20–30, a significant difference between the groups was found.


313

Table 2 Normalized data of example microarray Normalized

Healthy 1

Healthy 2

Healthy 3

Compound 1

5,700

6,200

5,200

228

251

207

25

Compound 2

7,000

7,500

6,500

233

256

212

30

Compound 3

6,300

6,800

5,800

84

92

77

75

Compound 4

9,000

9,500

8,500

818

900

744

11

Compound 5

11,000

11,500

10,500

1,222

1,344

1,111

9

Compound 6

6,800

7,300

6,300

85

94

78

79

Compound 7

8,100

8,600

7,600

121

133

110

67

Compound 8

6,700

7,200

6,200

209

230

190

32

Compound 9

6,800

7,300

6,300

113

125

103

60

Compound 10

8,900

9,400

8,400

9,000

9,300

9,900

1

Compound 11

7,000

7,500

6,500

7,100

7,400

7,810

1

Compound 12

6,800

7,300

6,300

6,900

7,200

7,590

1

Compound 13

9,000

9,500

8,500

9,100

9,400

10,010

1

Compound 14

8,000

8,500

7,500

8,100

8,400

8,910

1

Compound 15

6,700

7,200

6,200

6,800

7,100

7,480

1

Compound 16

8,700

9,200

8,200

8,800

9,100

9,680

1

Compound 17

9,300

9,800

8,800

9,400

9,700

10,340

1

Compound 18

8,400

8,900

7,900

8,500

8,800

9,350

1

Compound 19

7,900

8,400

7,400

8,000

8,300

8,800

1

Compound 20

10,500

11,000

10,000

10,600

10,900

11,660

1

Compound 21

300

330

270

600

660

546

−2

Compound 22

400

440

360

12,800

14,080

11,640

−32

Compound 23

450

495

405

2,250

2,475

2,050

−5

Compound 24

250

275

225

13,250

14,575

12,045

−53

Compound 25

280

308

252

8,960

9,856

8,140

−32

Compound 26

300

330

270

9,000

9,900

8,180

−30

Compound 27

450

495

405

11,250

12,375

10,223

−25

Compound 28

210

231

189

13,230

14,553

12,028

−63

Compound 29

300

330

270

7,800

8,580

7,092

−26

Compound 30

800

880

720

7,200

7,920

6,545

−9

12,490

12,490

12,490

12,490

12,490

12,490

1

Calibrator

Ill 1

Ill 2

Ill 3

FC

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Fig. 1. Expression visualization of example microarray.

Multiple examples of bioinformatics are detailed in the literature. A number of web pages are available that focus on providing researchers with the possibly to download expression data (e.g., GEO) (http://www.ncbi.nlm.nih.gov/geo/), programs for bioinformatics (e.g., EBI) (http://www.ebi.ac.uk/) or examples for used algorithms. 2.6. Program Packages

Many software packages are readily available for the researcher who wishes to conduct microarray experimental interpretation. The software generally employs the various bioinformatics algorithms that have been outlined in this chapter. RMA-based characterization can be applied using freely available RMAexpress software (http:// www.rmaexpress.bmbolstad.com). SAM-based analysis software is also available online (http://www.stat.stanford.edu/~tibs/SAM/).


Fig. 2. Hierarchical clustering of example microarray.

Fig. 3. k-Means clustering of an example microarray.

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Table 3 Significance calculation for one-way ANOVA Unique ID

p Value

Significant

Compound 1

1.90E−03

True

Compound 2

1.67E−04

True

Compound 3

5.87E−04

True

Compound 4

1.01E−02

True

Compound 5

4.45E−01

True

Compound 6

1.74E−03

True

Compound 7

5.26E−06

True

Compound 8

4.82E−04

True

Compound 9

3.41E−05

True

Compound 10

0.020681819

False

Compound 11

0.1011849

False

Compound 12

0.12724395

False

Compound 13

0.01946915

False

Compound 14

0.038977187

False

Compound 15

0.14337784

False

Compound 16

0.023464832

False

Compound 17

0.016402658

False

Compound 18

0.028777085

False

Compound 19

0.04231185

False

Compound 20

0.009301341

True

Compound 21

6.86E−02

True

Compound 22

9.30E−02

True

Compound 23

1.46E+00

True

Compound 24

5.53E−02

True

Compound 25

6.33E−02

True

Compound 26

6.77E−02

True

Compound 27

1.12E+00

True

Compound 28

4.65E−01

True

Compound 29

6.70E−02

True

Compound 30

3.33E+00

True


317

Other software tools such as Genesis enable the user to conduct multiple algorithms (http://www.genome.tugraz.at/), allowing not only clustering (e.g., hierarchical and k-means) and significance analysis (e.g., one-way ANOVA), but also PCA and other algorithms. Some programs are applets and add-ons for R (http:// www.r-project.org/), a programming language with focus on statistical analysis. They include BioConductor (51) – a bioinformatics open software with multiple possible application (52) – and RefPlus – a RMA expanding package (30). GenMAPP (http:// www.genmapp.org/) is an example for pathway analysis. Addi tional available tools with similar purpose are reviewed in ref. 35. JMP genomics by SAS (http://www.jmp.com/software/genomics/) is a widely available commercial software, which employs all basic algorithms and is easy-to-use especially for first time bioinformatics users. Graphic displaying and significance testing can be conducted for multiple types of microarrays. ChipInspector available from Genomatix provides a complete platform for DNA analysis. ChipInspector extracts information from the expression level of single probes from microarrays as opposed to probesets. The input files for ChipInspector supports Affymetrix CEL (cell intensity) files (other platforms are possible). ChipInspector assigns probes directly to transcripts and genes and is able to account for alternative transcripts. The software makes use of up to date genomic knowledge and databases of alternative transcripts and promoters to achieve superior signal– noise ratios in microarray analysis. Importantly, the results from this analysis are directly usable as input to the BiblioSphere Pathway software for pathway and association data. This single probe-based analysis of oligonucleotide-based arrays has demonstrated clear advantages over the common probe set-based approach, most notably in improved sensitivity and specificity of the biological findings (DAVID analysis). This was highlighted by the unique detection of a number of categories directly linked to clinical observations (12). While this analysis technique was found to increase the number of significant features, it also simultaneously reduced false-positive rates by an order of magnitude (12). ChipInspector can be summarized in the following steps: 1. Single probe-transcript annotation (resulting reduced list of probes that have a specificity of 100%) 2. Total intensity normalization (modified for usage on single probe level) 3. SAM (adapted to single-probe application) 4. Output generation of significantly expressed transcripts Multiple other software solutions are available. Some are summarized by Werner (50).

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3. Notes 1. Quality of the input material is giving rise to differences of microarray level (53). Quality control is essential to achieve comparability between samples. 2. If differences between groups are more drastic than mere up- or downregulation, a discrepancy between present or absent should be used to analyze data. This is done by binarization, whereas 0 expression of the compound stands for absent and 1 stands for present. This approach is more likely to succeed if the sample groups are immensely different (e.g., comparison of brain and spleen tissue samples). 3. Conservative appointing of k can lead to incoherent results if the possibility of subgroups is given. If diseases are analyzed this is often the case (e.g., subgroups of cancer).

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8. Voduc D, Kenney C, Nielsen TO. Tissue microarrays in clinical oncology. Semin Radiat Oncol 2008;18(2):89–97. 9. Wu P, Castner DG, Grainger DW. Diagnostic devices as biomaterials: a review of nucleic acid and protein microarray surface performance issues. J Biomater Sci Polym Ed 2008;19(6):725–53. 10. Simon R. Microarray-based expression profiling and informatics. Curr Opin Biotechnol 2008;19(1):26–9. 11. Knudsen S. Image analysis. In: Guide to analysis of DNA microarray data; 2004. 12. Cohen CD, Lindenmeyer MT, Eichinger F, et al. Improved elucidation of biological processes linked to diabetic nephropathy by single probe-based microarray data analysis. PLoS One 2008;3(8):e2937. 13. Henger A, Schmid H, Kretzler M. Gene expression analysis of human renal biopsies: recent developments towards molecular diagnosis of kidney disease. Curr Opin Nephrol Hypertens 2004;13(3):313–8. 14. Scherer A, Krause A, Walker JR, et al. Opti mized protocol for linear RNA amplification


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28. Hochreiter S, Clevert DA, Obermayer K. A new summarization method for Affymetrix probe level data. Bioinformatics 2006;22(8):943–9. 29. Irizarry RA, Hobbs B, Collin F, et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 2003;4(2):249–64. 30. Harbron C, Chang KM, South MC. RefPlus: an R package extending the RMA algorithm. Bioinformatics 2007;23(18):2493–4. 31. Holder D, Raubertas RF, Pikounis VB, Svetnik V, Soper K. Statistical analysis of high density oligonucleotide arrays: A SAFER approach. In: ASA annual meeting. Atlanta, GA; 2001. 32. Kerr MK, Martin M, Churchill GA. Analysis of variance for gene expression microarray data. J Comput Biol 2000;7(6):819–37. 33. de Haan JR, Wehrens R, Bauerschmidt S, Piek E, van Schaik RC, Buydens LM. Interpretation of ANOVA models for microarray data using PCA. Bioinformatics 2007;23(2):184–90. 34. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A 2001;98(9):5116–21. 35. Kadota K, Nakai Y, Shimizu K. A weighted average difference method for detecting differentially expressed genes from microarray data. Algorithms Mol Biol 2008;3:8. 36. Zhao H, Chan KL, Cheng LM, Yan H. Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments. BMC Bioinformatics 2008;9(Suppl 1):S9. 37. Schreiber F. Visualization. Methods Mol Biol 2008;453:441–50. 38. MacQueen J. Some methods for classification and analysis of multivariate observations. In: Fifth Berkeley symposium on mathematical statistics and probability. University of California Press, Berkeley, CA; 1967. p. 281–97. 39. Goldstein DR, Ghosh D, Conlon EM. Statistical issues in the clustering of gene expression data. Stat Sin 2002;12:219–40. 40. Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genomewide expression patterns. Proc Natl Acad Sci U S A 1998;95(25):14863–8. 41. McLachlan GJ, Bean RW, Ng SK. Clustering. Methods Mol Biol 2008;453:423–39. 42. Chen G, Jaradat SA, Banerjee N, Tanaka TS, Ko MSH, Zhang MQ. Evaluation and comparison of clustering algorithms in analyzing ES cell gene expression data. Stat Sin 2002;12:241–62.

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43. Kim SY, Lee JW, Bae JS. Effect of data normalization on fuzzy clustering of DNA microarray data. BMC Bioinformatics 2006;7:134. 44. Alter O, Brown PO, Botstein D. Singular value decomposition for genome-wide expression data processing and modeling. Proc Natl Acad Sci U S A 2000;97(18): 10101–6. 45. Daffertshofer A, Lamoth CJ, Meijer OG, Beek PJ. PCA in studying coordination and variability: a tutorial. Clin Biomech 2004;19(4):415–28. 46. Hubert M, Engelen S. Robust PCA and classification in biosciences. Bioinformatics 2004;20(11):1728–36. 47. D’Souza M, Zhu X, Frisina RD. Novel approach to select genes from RMA normalized microarray data using functional hearing tests in aging mice. J Neurosci Methods 2008;171(2):279–87.

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Index A aa-dUTP-labeled cDNA target.................................. 11, 19 a-Amperometric approach................................................ 43 Analysis of target labeling reaction............18, 21, 23–24, 28 Applications of microarray technology gene expression..................................................... 56–57 genomic analysis and genotyping......................... 57–59 target sequence for microbial arrays antibiotic resistance genes............................... 59–60 bacterial virulence factors................................ 59–60 ribosomal DNA polymorphisms.......................... 59 Aptamer array fluorescein-labeled RNA/DNA aptamers.................. 37 Photoaptamers............................................................ 37 Aptamer immobilization amine-silane-based..................................................... 39 biotinylated aptamer on streptavidin-coated glass slides....................................................... 44 covalent conjugation of NH-aptamer to amino-silanized surfaces....................... 44–45 covalent conjugation of SH-aptamer to thiol-or maleimide-silanized surfaces.......................... 45 Aptamer modification incorporation of commercial amine-reactive compounds to amine-modified aptamer..................................................... 45–46 incorporation of COOH-bearing electroactive labels to amine-modified aptamer............ 46–47 Aptamers conjugation................................................................. 39 labeling....................................................................... 39 novel aptamers............................................................ 38 precipitation................................................................ 39 production and manipulation............................... 38–39 reconstitute lyophilized aptamers............................... 38 RNA aptamers.................................................39, 47, 52 Aptasensor.................................................................. 49, 51 Arabidopsis thaliana genes................................................... 4 Array printing....................................................8, 63, 70, 97 Array regeneration and reutilization................................. 49

B BAC-based CGH DNA microarray................................... 6 BAC clones......................................................................... 8

BAC DNA......................................................................... 8 Bacteria (BAC) genomic libraries....................................... 8 Bacteria microarray, fabrication...............148–150, 153–155 Bioarrays................................................................. 261, 275 Biological microarray.............................................. 249–259 Biomaterials............................. 148, 161–163, 196, 229, 262 Biosensor................................................................133–145 BLAST............................................................61, 71, 85, 86 BRCA1............................................................................... 6

C Cancer.............................................. 5, 6, 121, 222, 252, 318 Capillary force lithography......................147–159, 262, 271 Capillary pump.................177, 178, 181–184, 189, 190, 191 Carbohydrate..............64, 117, 118, 121–124, 128, 130, 251 cDNA..............................................4, 6, 7, 9, 11, 12, 18–21, 23, 29, 31, 56, 57, 62, 64–66, 97, 297, 299 synthesis............................................................. 21, 296 Cell adhesion..................................................162, 170, 178, 180, 188, 202, 205, 251 Cell-alginate solution..................................................... 234 Cell-based biosensor................................133–145, 195, 262 Cell encapsulation.......................................................... 134 Cell free expression......................................97, 98, 100–102 Cell free protein synthesis.......................................... 96, 97 Cell microarray........................................133–145, 207–216 Cell proliferation............................. 162, 170, 231, 232, 236 Cellular micropatterning.................................195, 196, 198 Cell viability assays..................................142, 170, 233–234 CGH DNA microarray.................................................. 5–7 Chemical vapor deposition (CVD).................209, 261–276 Clustal....................................................................... 62, 71, 86 Clustering.........................................................69, 128, 129, 304–310, 312, 315, 317 Collagen............109, 110, 112, 113, 115, 162, 197, 198, 200, 202, 203, 205, 206, 281–283, 285, 286, 289–291 Combinatorial methods.................................................. 161 Comparative genomic hybridization (CGH)........... 5–9, 15 Contact printing................................................64, 204, 275 Copy number variation (CNV)................................ 4, 5, 30 CS chip........................................................................... 183 Cy dye coupling reaction.................................................. 22 Cy-labeled QC oligonucleotides...................................... 88 Cy3-or Cy5-dUTP............................................................ 9

Ali Khademhosseini et al. (eds.), Biological Microarrays: Methods and Protocols, Methods in Molecular Biology, vol. 671, DOI 10.1007/978-1-59745-551-0, © Springer Science+Business Media, LLC 2011

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D Data analysis.......................... 56–59, 63, 64, 68–70, 92, 130 Deletion.................................................................4, 5, 8, 59 Denhardt’s solution...............................................13, 14, 75 Detection strategy electrochemical aptamer microarrays.......................... 51 fluorescence aptamer microarrays............................... 50 surface plasmon resonance imaging (SPRi)................ 50 Differentiation........................................ 108, 117, 161, 162, 197, 220, 222, 223, 232 Dimethylsulfoxide (DMSO)..........................10, 20, 22, 39, 40, 45–47, 143, 236, 252, 258 Direct cell writing.................... 223–227, 229–232, 234–235 Direct fluorescence detection of fluorescent reporters................................... 35 DNA array to protein array (DAPA)........................ 96–104 DNA microarray........................................ 3–31, 40, 55, 56, 63–71, 85–88, 95–105, 215, 266, 295, 296 DNA QC.................................................. 8–9, 14–16, 27–30 Drop immunoassay................................................. 180, 190

E Electrochemical detection.......................................... 42, 43 Electrodes macroelectrode............................................................ 44 Endothelial cells.............................. 245, 282–285, 290, 291 Endothelial tubes.............................................281, 283–286 Enhancer....................................................................... 4, 76 Escherichia coli (E.coli)....................... 60, 72, 76, 97, 99, 103, 148–149, 151–152, 154, 155

F Fluorescence anisotropy.........................................37, 42, 50 Fluorocur mold................................ 251, 253, 254, 257, 258 Focal leaks....................................... 281, 282, 285, 288–291 Food safety....................................................................... 56 Fragmentation buffer........................................................ 11 FRET................................................................................ 35 Functionalized surface............................................ 207–216

G Gene delivery................................................................. 251 Gene set...................................................................... 5, 310 Gene signature............................................................... 5, 6 Glycan.............................................................. 118, 123, 125 Glycomics........................................................118, 125, 128 Glycosylation.......................................................... 118, 128 Gold coated slides...................................................... 38, 43

H Hereditary etiology............................................................. 4 Hot spots..........................................................................161 Human monogenic disease................................................. 4

Human/mouse Cot-1 DNA............................................. 13 Hybridization........................5, 6, 13–14, 16, 23–30, 55, 56, 58, 62–65, 67–68, 70, 71, 73–78, 83–85, 90–91, 118, 119, 120, 127–128, 180, 296–300, 302 Hydrogel microstructures....................................... 133–145 Hydrogel precursor solution............................138, 141, 145 Hydroxylamine................................................11, 22, 40, 47

I Immobilization............................. 36, 38–41, 43–45, 49, 51, 52, 55, 74, 158, 207, 215, 261, 263, 265, 266, 268, 270, 273 Immunofluorescence staining..................104, 110, 113–114 Insertion...........................................................................4, 59 Intercellular reactions............................................. 142–143

L Labeled cRNA purification with RNeasy MinElute column..................................... 22, 23 LAlign.............................................................. 61, 71, 85, 86 Layer-by-layer assembly.................. 148, 150, 151, 155, 159 Lectin................................................................ 117–131, 266 Lectin microarray manufacture.............................................................. 119 print procedure................................................. 120–125 Lift-off process........................................208, 209, 211–212 Liver....................................................................... 219–237 Loading pads........................... 177, 178, 181–184, 188, 190

M Magnetic bead based strand separation................ 73, 82–83 MDA. See Multiple displacement amplification Micellae.................................................... 118, 125–126, 130 Microarray.........................................3–31, 40, 50, 51, 55–92, 95–105, 107–115, 117–131, 133–145, 147–159, 180, 195–216, 249–259, 266, 272, 295–318 bioinformatics........................................60–63, 295–318 oligoprobe binding...................................................... 64 probe design....................................................61, 63, 88 Microbial pathogens................................................... 55–92 Microchannels................................. 135–137, 140–144, 177, 178, 180–184, 188, 190–193, 221, 225, 226, 262, 267, 268, 271, 273 Microfabrication..................................... 134, 184, 198, 209, 211–213, 220, 222, 225, 226, 271, 275 Microfluidic devices........................ 134, 135, 136, 140–142, 145, 220, 221, 225, 226, 232, 234–235, 267, 268 Microfluidics.....................17, 108, 134–136, 138, 140–142, 145, 177–193, 220, 221, 224–227, 231, 232, 234–235, 262, 267, 268, 272, 287 Micromolding in capillaries.....................208–210, 213–215 Micromosaic immunoassays....................178–181, 183, 191 Micropatterns.......... 109, 113, 134, 136, 148, 151, 195–203, 205, 208, 212, 239, 263, 265, 268–271, 273, 275


Microprinting......................................................... 219–237 Microscale.................................147, 159, 220, 221, 223, 224, 226, 227, 229, 266, 267, 271 Microspotting...................................... 74, 90, 208–211, 216 Microstructure........................ 133–145, 151, 168–170, 183, 188, 190, 201, 202, 210, 214, 216, 261–276 Microvascular tissue engineering...................................... 81 Microvascular tubes................................................ 281–292 Miniaturizated immunoassays................................ 177–193 M13 macrophages........................... 149, 151, 155, 157, 158 Molding...................135, 137–140, 144, 148, 150, 156–159, 181, 184–186, 239, 240, 242, 243, 250, 262 mRNA translation.............................................................. 4 Multiple displacement amplification (MDA)..................... 9

N Nanoarray fabrication..............................250, 251, 253, 257 NanoDrop Spectrophotometer Analysis of Target Labeling Reaction.................. 18, 21, 23–24, 28 Nanoparticles...................................... 51, 67, 250, 253–259 Nonspecific binding..................................67, 148, 208, 215 Nucleotide microarray............................................ 6, 55–92

O Oligo Design.............................................56, 60–62, 71, 85 Oligo-dT18........................................................9, 10, 17, 19 Oligonucleotides................6, 38, 55–92, 250, 251, 258–259 Organotypic culture................................................ 107, 221

P Particle generation.................................................. 249–251 Pathogen...................................... 55–92, 117, 133, 222, 251 Pathological state................................................................ 4 Patterning........................................ 108, 109, 111, 134, 140, 148–150, 154–155, 177–193, 196, 198, 202, 205, 207–215, 222, 242, 244, 262, 265–268, 271–273 PBPK. See Physiologically-based pharmacokinetic model PCL:PDLLA. See Poly(e-caprolactone):poly(D,L-lactic acid) PCR. See Polymerase chain reaction PCR amplification asymmetric..........................................65, 66, 77, 79–80 multiplex....................................................65, 71, 77–79 multiplex-assymetric....................................... 77–78, 80 standard................................................................ 77, 78 universal primers........................ 8, 62, 65, 71, 78, 80–81 PDMS. See Polydimethylsiloxane PDMS-CSs. See Polydimethylsiloxane-capillary systems Perfluoropolyethers (PFPE)........................................... 250 Perfused tubes................................................................. 288 Permeability..................................... 159, 226, 250, 281–292 Permeability assay....................................284, 285, 287–291

PFPE. See Perfluoropolyethers Phosphate buffers phosphate elution buffers................................10, 20, 31 phosphate wash buffers....................................10, 19, 31 Photolithography PEG hydrogel lithography................197, 198, 201, 202 photoresist lithography......................196–198, 200, 203 Photoreactive CVD polymers.........................271–273, 275 Photoresist.............................. 135, 137, 184, 195–203, 208, 212, 213, 241–243 Physiologically-based pharmacokinetic model (PBPK).............................................. 221 Polydimethylsiloxane (PDMS)...............109–112, 114–115, 135–137, 140, 141, 144, 150, 154, 156–159, 177–193, 210, 214–216, 225–227, 233–235, 239–247, 250, 263, 266–270, 273, 275 Polydimethylsiloxane-capillary systems (PDMS-CSs)................................178, 180–190 Polyelectrolyte (PEL) multilayers...................148, 150, 151, 155–159 Poly(ethylene glycol) hydrogel........................135–137, 144, 196, 198, 201, 202, 204, 205, 271 Polymerase chain reaction (PCR)................... 4, 7, 8, 21, 56, 58, 60–62, 64–66, 70–74, 77–85, 87, 88, 90, 96–102, 104–105 primer design........................... 60–62, 65, 78, 85, 87, 88 Polymer scaffold..................................................... 161–172 Polymorphism.............................................................. 4, 59 Poly(e-caprolactone):poly(D,L-lactic acid) (PCL:PDLLA)............................................. 161 Poly-(TMSMA-r-PEGMA).......... 149, 153–155, 158, 159 Precipitation labeled-DNA.............................................................. 29 labeled targets............................................................. 29 microarray slide..................................................... 27, 29 Predictive factor.................................................................. 5 Prehybridization solution......................................14, 26, 29 Primer extension (PE) reaction.................65, 72–74, 83–84 Primers Cy5-T7-for....................................................98, 99, 102 GENE-for............................................................ 97, 98 GENE-rev.....................................................97, 98, 101 LTT-for.............................................................. 98, 101 LTT-rev.................................................98, 99, 101, 102 NH2-LTT-rev................................................98, 99, 102 T7 domain.................................................................. 99 T7-for.............................................97, 98, 99, 101, 102 T7-rev............................................................. 97, 98, 101 PRINT process........................................250, 251, 253–255 Prognostic factor............................................................. 5, 6 Promoter............................ 4, 21, 52, 66, 73, 78, 83, 99, 100, 182, 185, 317 Protein array................ 95–97, 103–104, 202, 254–255, 299 Protein immobilization............................................. 96, 208 Protein microarray......95–105, 196, 199, 201–203, 208, 216


Protein micropatterning..................197–198, 200–202, 208 Protein patterning...........................................209, 211–213 Proteins........................ 3, 4, 8, 16, 35, 37, 41, 47, 52, 53, 64, 71, 77, 95–105, 108–111, 113, 117–119, 126–128, 134, 137, 144, 150–151, 157, 158, 162, 177–193, 195–216, 240–242, 244–247, 249–251, 254–258, 261, 262, 266, 270, 272, 273, 287, 295, 297, 299

R Reactive CVD polymers......................................... 273–275 Reagentless detection................................................. 37, 42 Regulatory regions of genes................................................ 4 RNA annealing................................................................. 21 RNA hydrolysis................................................................ 19 RNA QC.......................................................7, 9–14, 16–27 RNAse H............................................................................ 9 RNAseOne................................................................... 9, 18 RNAsin..................................................................................9 RNeasy MinElute column.......................................... 22, 23

S Salt leaching....................................................165, 167–171 Sandwich assay formats.........................................36, 41, 50 Scaffold arrays........................................................ 161–172 Scaffold porosity..................................................... 168–170 Scanning...................... 13, 16, 24, 27, 28, 30, 31, 56, 57, 58, 59, 68–70, 92, 119, 120, 127–128, 154, 155, 158, 201, 262, 296, 297 Sequence alignment multiple sequence alignment................................ 61, 85 pairwise local alignment............................................. 85 Silanization........................................................43, 114, 200 Single-stranded DNA (ssDNA)................. 8, 23, 24, 64, 65, 71–74, 77, 78, 81–85, 90, 91, 158, 251 Single-stranded RNA (ssRNA)........... 72–74, 78, 81–84, 90 ssDNA. See Single-stranded DNA

ssRNA. See Single-stranded RNA Suboptimal fluorophore-labeled target............................. 41 Superscript II.....................................................9, 10, 18, 19 Supervised analysis methods.................................... 69, 305 Surface engineering.........................................197, 261, 275 Surface plasmon resonance (SPR) imaging..........37, 38, 42, 50–51

T Target amplification........................................56, 70, 78–84 Target labeling, with an amine-reactive fluorophore.. 47–48 Target purification...................................................... 20–21 Three-dimensional tissue microarrays.................... 107–115 Tissue engineering........................... 134, 195, 220, 222, 249 Tissue printing...........64, 220–224, 226, 229, 231, 232, 235 Toxicity............................................................. 134, 221, 250 Two-color cDNA microarray............................................. 6 Two-dimensional tissue microarrays................109, 111–112

U Universal buffer................................................................ 37 Unsupervised analysis methods........................................ 69

V VAMPIR. See Vapor assisted micropatterning in replica structures Vapor assisted micropatterning in replica structures (VAMPIR)........................................... 268–272 Virulence factors........................................59–60, 71, 79, 80 Virus microarray, fabrication...................148–151, 153–158 Voltametric approach.................................................. 43, 51

W WGA. See Whole genome amplification Whole genome amplification (WGA)....................................8–9, 27, 124, 126