MCP Papers in Press. Published on May 12, 2017 as Manuscript M117.068080
Translating Divergent Environmental Stresses into a Common Proteome Response through Hik33 in a Model Cyanobacterium Haitao Ge1, Longfa Fang2,3, Xiahe Huang2, Jinlong Wang2,3, Weiyang Chen2,3, Ye Liu2,3, Yuanya Zhang2, Xiaorong Wang2,3, Wu Xu4, Qingfang He1, 5*, and Yingchun Wang2,3* Running title: Hik33-regulated Stress Responsive Proteome 1
State Key Laboratory of Microbial Technology, College of Life Science, Shandong University, Jinan 250100, China. 2
State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, No.1 West Beichen Rd., Beijing 100101, China. 3 University
of Chinese Academy of Sciences
4 Department
of Chemistry, University of Louisiana at Lafayette, Lafayette, LA 70504,
USA. 5 Department
of Applied Science, University of Arkansas at Little Rock, Little Rock, AR,
USA. *Corresponding author Yingchun Wang, Ph.D. Email:
[email protected] Phone: (010)6480-6149 Fax: (010)6480-6252 Qingfang He, Ph.D. Email:
[email protected] Phone: (501) 569-8033 Fax: (501) 569-8020
1
Copyright 2017 by The American Society for Biochemistry and Molecular Biology, Inc.
ABBREVIATIONS: WT: Wild type WCL: Whole cell lysate HL: High light NL: Normal light Chl: Chlorophyll PS I: Photosystem I PS II: Photosystem II PBS: Phycobilisome PET: Photosynthetic electron transport Synechocystis: Synechocystis sp. PCC 6803 MS: Mass spectrometry TMT: Tandem mass tag CSR: common stress responsive PSR: pseudo-stress response RP-HPLC: reversed phase - high performance liquid chromatography OPP: oxidative pentose phosphorylation ACN: acetonitrile FDR: False discovery rate ROS: reactive oxygen species FASP: filter-aided sample preparation
2
SUMMARY The histidine kinase Hik33 plays important roles in mediating cyanobacterial response to divergent types of abiotic stresses including cold, salt, high light (HL), and osmotic stresses. However, how these functions are regulated by Hik33 remains to be addressed. Using a hik33-deficient strain (Δhik33) of Synechocystis sp. PCC 6803 (Synechocystis) and quantitative proteomics, we found that Hik33 depletion induces differential protein expression highly similar to that induced by divergent types of stresses. This typically includes downregulation of proteins in photosynthesis and carbon assimilation that are necessary for cell propagation, and upregulation of heat shock proteins, chaperons, and proteases that are important for cell survival. This observation indicates that depletion of Hik33 alone mimics divergent types of abiotic stresses, and that Hik33 could be important for preventing abnormal stress response in the normal condition. Moreover, we found the majority of proteins of plasmid origin were significantly upregulated in Δhik33, though their biological significance remains to be addressed. Together, the systematically characterized Hik33-regulated cyanobacterial proteome, which is largely involved in stress responses, builds the molecular basis for Hik33 as a general regulator of stress responses. Key words: Hik33, Stress response, Photosynthesis, Carbon metabolism, Proteomics
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INTRODUCTION Cyanobacteria are a group of photosynthetic gram-negative bacteria that play an important role in shaping the current living condition of the biosphere by contributing a significant fraction of oxygen in the atmosphere (1-3). Cyanobacteria are widely distributed in almost every terrestrial and aquatic habitat, and thus have developed an efficient system to cope with versatile and ever-changing adverse environmental conditions during the long evolutional process. Understanding the mechanism how cyanobacteria adapt to such divergent environmental stresses is important for better utilizing these organisms with great potential in producing clean and renewable biofuels (4-7). The most frequently occurring environment stresses cyanobacteria have to cope with in their natural habitats include HL irradiation, high or low temperature, high salt, acid, and drought. In the past two decades, application of genomics and proteomics approaches have accelerated the investigations of the cyanobacterial stress responses at a system level. One of the most prominent findings of such investigations is that different types of stresses can induce a common response in terms of gene expression (8-11), though some stress-type specific responses were also observed. For example, expression of heat shock proteins, chaperons, and some proteases is usually dramatically upregulated in response to HL, salt, or cold stresses, whereas the expression of proteins in photosystem I (PS I) and phycobilisome (PBS) are usually significantly repressed in the same conditions. Though it is believed that such responses are important for 4
protecting cyanobacteria from the stresses-induced damages, unfortunately, how different stresses induce the same response in protein expression is far from addressed. Like the other prokaryotes, cyanobacteria perceive and transduce environmental signals through the two-component systems, which are usually composed of a histidine kinase (Hik) acting as the sensor and a cognate response regulator (Rre). Upon perceiving the environment signals, the Hik is activated through autophosphorylation of one of its histidine residues, and then transfer the phosphor-group to an aspartate residue of its cognate Rre. The phosphorylated Rre in turn regulates expression of genes, by acting as a transcription factor or some undefined mechanism, that are necessary for adapting to the environmental changes (12). Cyanobacterial genomes usually encode large families of Hiks and Rres to cope with versatile environmental stresses in their divergent natural habitats (12). Multiple Hik-Rre systems may be required to cope with a particular type of stress, but the degree of their involvement could be different. On the other hand, a single Hik may be involved in sensing and transducing multiple types of environmental stresses, such as Hik33. Hik33 is highly conserved in cyanobacteria but not in other prokaryotes, suggesting that the functions of Hik33 are specialized to coordinate photosynthesis and stress response. Hik33 was originally named as the drug sensory protein A (DspA) because a knockout mutant of hik33 is more resistant to herbicides (13). Screening of cyanobacterial mutants defective in cold response revealed that hik33 mutation repressed the coldinduced upregulation of a number of cold-responsive genes (14), and for the first time, 5
implicated Hik33 in stress response. Later on, Hik33 was implicated in additional types of stress responses, such as HL irradiation, hyperosmotic stress, salt, and acid (15-18). Thus, it is conceivable to presume that Hik33 plays a general but critical role in regulating differential gene expression in response to divergent types of stresses. Unfortunately, despite the tremendous amount of attempts in elucidating the working mechanism of Hik33, how Hik33 perceives the divergent environmental signals and regulates the corresponding
cellular
response
in
cyanobacteria
remain
largely
unknown.
Characterization of Hik33-dependent differential gene expression can provide important information for the understanding how Hik33 operates in stress response. Nevertheless, such information is only available at transcription level and limited to only a single stress condition in each study (19). Because transcription levels are usually not well correlated with the protein levels (20), and because Hik33 operates in multiple types of stress responses, such transcription information without enough generality is still not sufficient for elucidating the working mechanism of Hik33 in regulating stress responses Herein, we tried to investigate the causal relationship of Hik33 and the common stress response in proteome expression using the unicellular model organism Synechocystis by taking its unique advantages. First, Synechocystis is the first cyanobacterium with the completely sequenced and best annotated genome (21), which contains 3,672 proteincoding open reading frames (ORFs). The relatively small size of the genome can significantly reduce the complexity of large scale genomic or proteomic analyses. Second, Synechocystis is naturally transformable which allows utilization of reverse genetics 6
approaches to study the functional significance of stress-related proteins. Finally, Synechocystis highly resembles the chloroplast in higher plants, as such the protective mechanism for photosynthetic machineries in environment stress uncovered for Synechocystis could also be applied for higher plants. Using a previously established hik33 mutant strain of Synechocystis and a quantitative proteomics approach (15), we compared the Hik33-regulated proteome with the previously described stress-responsive genes and/or proteins, and demonstrated that Hik33 plays a central role in regulating the expression of proteins that are common in divergent types of stress-responses.
EXPERIMENTAL PROCEDURES Antibodies and cell culture All primary antibodies were purchased from Agrisera (Vännäs, Sweden). The wild type (WT) strain of Synechocystis and the Δhik33 were cultured in liquid BG-11 medium in moderate light (50 μmol/m2s photons) in a shaker or bubbled with air as necessary. The cells were collected by centrifugation (4,000 x g for 10 min) for biochemical and proteomic analyses when the culture reaches the optical density at 730 nm of about 1.0. The optical density measures the turbidity of the cell culture (22), which positively correlates with cell density and can be used to compare the concentrations of cells in different cultures if the average sizes of the cells being compared are equal. The harvested cells were stored at -80°C until they were used for protein preparation.
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Pigment analysis The Chl and total carotenoids in cells were extracted with N, N-dimethylformamide (DMF, Sigma-Aldrich, Saint Louis, MO), and the concentrations were determined using a previously described approach(23). The equations used for the calculation of pigment concentration are: Chl a (μg/ml) = 12.1 x OD664 – 0.17 x OD625. Total Carotenoids (μg/ml) = (OD461 – 0.046 x OD664) x 4.
Preparation of PS I Trimers Thylakoid membranes were prepared through differential centrifugation as previously described (24,25). The PS I trimers were prepared by sucrose-gradient centrifugation using a well-established protocol (26,27). Briefly, the thylakoid membranes containing 2 mg/ml protein were added with n-dodecyl β-D-maltoside (DM, Sigma-Aldrich, Saint Louis, MO) to a final concentration 1.5%, and then allowed to solubilize at 4°C for 30 min. The solubilized membranes were loaded on the top of a 10% to 30% (w/w) step sucrose gradient and centrifuged with 160,000 g for 16 h at 4°C. The fractions containing PS I trimers were collected and stored at -80°C until use.
Protein preparation Cell pellets were lysed in a buffer containing 0.4 M sucrose, 50 mM 3-(N-morpholino) propanesulfonic acid, pH 7.0, 10 mM NaCl, 5 mM EDTA, and 0.5 mM 8
phenylmethanesulfonyl fluoride (PMSF, Sigma-Aldrich, Saint Louis, MO) with a bead beater. The WCLs were centrifuged for 30 min at 5000 x g at 4°C to remove insoluble debris. After precipitation with ice-cold 10% trichloroacetic acid in acetone at -20°C, total proteins were washed with acetone and resolubilized with 4% sodium dodecyl sulfate (SDS) in 0.1 M Tris-HCl, pH 7.6. A BCA protein assay kit (Thermo Scientific, Rockford, IL) was used to determine the protein concentration.
Protein digestion and Tandem Mass Tag (TMT) labeling Proteins were digested using the filter-aided sample preparation (FASP) method according to a previously described method with slight modifications (28). Briefly, the lysates (100 μg protein for each sample) were reduced with 10 mM DTT at 37°C for 1 h and alkylated with 55 mM iodoacetamide (IAA, Sigma-Aldrich, Saint Louis, MO) at room temperature for 1 h in the dark. The alkylated lysates were transferred into the Microcon YM-30 centrifugal filter units (EMD Millipore Corporation, Billerica, MA), where the denaturing buffer was replaced by the 0.1 M triethylammonium bicarbonate (TEAB, Sigma-Aldrich, Saint Louis, MO), and then digested with sequencing grade trypsin (Promega, Madison, WI) at 37°C overnight. The resulting tryptic peptides from three biological replicates of the WT and Δhik33 were collected and labeled with 6-plex TMT reagents (Thermo Scientific, Rockford, IL) by incubating peptides with ethanol-dissolved TMT reagents for 2 h at room temperature in dark. The labeling reaction was inactivated by addition of 5% hydroxylamine, and the labeled samples were mixed together with equal ratios before fractionated with reversed phase (RP)-high performance liquid chromatography (HPLC). 9
RP-HPLC Offline basic RP-HPLC was performed using a Waters e2695 separations HPLC system coupled with a phenomenex gemini-NX 5u C18 column (250 x 3.0 mm, 110 Å) (Torrance, CA, USA). The sample was separated with a 97 min basic RP-LC gradient as previously described (29). A flow rate of 0.4 mL/min was used for the entire LC separation. The separated samples were collected into 15 fractions, and completely dried with a SpeedVac concentrator and stored at -20°C for further analysis.
Mass spectrometry For MS analysis, the peptides were resuspended in 0.1% formic acid (FA) and analyzed by a LTQ Orbitrap Elite mass spectrometer (Thermo Scientific, Rockford, IL Waltham, MA) coupled online to an Easy-nLC 1000 in the data-dependent mode. Briefly, 2 μL of peptide sample (1 μg/μL) was injected into a 15-cm-long, 75-μm inner diameter capillary analytic column packed with C18 particles of 5-μm diameter. The mobile phases for the LC include buffer A (2 % acetonitrile, 0.1 % FA) and buffer B (98 % acetonitrile, 0.1 % FA). The peptides were separated using a 90-min non-linear gradient consisting of 3%–8% B for 10 min, 8%–20% B for 60 min, 20%–30% B for 8 min, 30%–100% B for 2 min, and 100% B for 10 min at a flow rate of 300 nl/min. The source voltage and current were set at 2.5 KV and 100 μA, respectively. All MS measurements were performed in the positive ion mode and acquired across the mass range of 300-1800 m/z. The fifteen most intense ions from each MS scan were isolated and fragmented by high-energy collisional dissociation. 10
Data analysis Raw mass spectrometric files were analyzed using the software MaxQuant (version 1.5.3.28) (30). The database search was performed using the integrated searching engine Andromeda, and the proteome sequence database used was downloaded from CyanoBase that contains 3,672 protein entries concatenated with 248 common contaminations
(ftp://ftp.kazusa.or.jp/pub/CyanoBase/Synechocystis,
released
on
5/11/2009). The type of search was set to report ion MS2 and the 6-plex TMT was chosen for isobaric labels, and the minimum reporter parent ion interference (PIF) was set to 0.75. Trypsin was chosen as the protease for protein digestion, and the maximum of 2 was set as the allowable miscleavages. N-terminal acetylation and methionine oxidation were included as the variable modification. Cysteine carbamidomethylation was included as the fix modification. The mass tolerances were set to 4.5 ppm for the main search and 20 ppm for precursor and fragment ions. The minimum score for unmodified peptides and modified peptides were set to 15 and 40, respectively. Other parameters were set up using the default values. The false discovery rate (FDR) was set to 0.01 for both peptide and protein identifications.
Experimental design and statistical rationale For the quantitative proteomic analysis, tryptic peptides from three biological replicates of the WT (control) and Δhik33 were labeled with 6-plex TMT reagents in an alternating order as shown in Fig.1C to reduce quantitative bias resulting from the TMT reagents. The labeled peptides were mixed together with an equal molar ratio and separated into 11
15 fractions by RP-HPLC before LC-MS/MS analysis. Bioinformatic and statistical analyses were mainly performed using the software Perseus (version 1.5.5.3) (31). Student’s t-test was used to determine the significance of differential expression of proteins between the WT and Δhik33, and Fisher’s-exact test was used for the functional enrichment analysis. A p-value0.49, p
