Blackwell Science, LtdOxford, UKEMIEnvironmental Microbiology 1462-2912Society for Applied Microbiology and Blackwell Publishing Ltd, 200581165177Original ArticlePseudomonas putida transcriptional apparatusL. Yuste et al.
Environmental Microbiology (2006) 8(1), 165–177
doi:10.1111/j.1462-2920.2005.00890.x
Growth phase-dependent expression of the Pseudomonas putida KT2440 transcriptional machinery analysed with a genome-wide DNA microarray Luis Yuste,1 Ana B. Hervás,2 Inés Canosa,2 Raquel Tobes,3 José Ignacio Jiménez,4 Juan Nogales,4 Manuel M. Pérez-Pérez,5 Eduardo Santero,2 Eduardo Díaz,4 Juan-Luis Ramos,3 Víctor de Lorenzo1 and Fernando Rojo1* 1 Departamento de Biotecnología Microbiana, Centro Nacional de Biotecnología, CSIC, Campus de la Universidad Autónoma de Madrid, Cantoblanco, 28049 – Madrid, Spain. 2 Centro Andaluz de Biología del Desarrollo, Facultad de Ciencias Experimentales, Universidad Pablo de Olavide. Ctra. Utrera, Km. 1. 41013 – Sevilla, Spain. 3 Estación Experimental del Zaidín, CSIC, Profesor Albareda 1, 18008 – Granada, Spain. 4 Centro de Investigaciones Biológicas, CSIC, Ramiro de Maeztu 9, 28040 – Madrid, Spain. 5 Servicio de Genómica, Centro Nacional de Biotecnología, CSIC, Campus de la Universidad Autónoma de Madrid, Cantoblanco, 28049 – Madrid, Spain. Summary Bacterial transcriptional networks are built on a hierarchy of regulators, on top of which lie the components of the RNA polymerase (in particular the sigma factors) and the global control elements, which play a pivotal role. We have designed a genome-wide oligonucleotide-based DNA microarray for Pseudomonas putida KT2440. In combination with real-time reverse transcription polymerase chain reaction (RTPCR), we have used it to analyse the expression pattern of the genes encoding the RNA polymerase subunits (the core enzyme and the 24 sigma factors), and various proteins involved in global regulation (Crc, Lrp, Fur, Anr, Fis, CsrA, IHF, HupA, HupB, HupN, BipA and several MvaT-like proteins), during the shift from exponential growth in rich medium into starvation and stress brought about by the entry into stationary phase. Expression of the genes encoding the RNA
Received 28 March, 2005; accepted 23 June, 2005. *For correspondence. E-mail
[email protected]; Tel. (+34) 91 585 45 39; Fax (+34) 91 585 45 06.
© 2005 Society for Applied Microbiology and Blackwell Publishing Ltd
polymerase core and the vegetative sigma factor decreased in stationary phase, while that of sS increased. Data obtained for sN, sH, FliA and for the 19 extracytoplasmic function (ECF)-like sigma factors suggested that their mRNA levels change little upon entry into stationary phase. Expression of Crc, BipA, Fis, HupB, HupN and the MvaT-like protein PP3693 decreased in stationary phase, while that of HupA and the MvaT-like protein PP3765 increased significantly. Expression of IHF was indicative of posttranscriptional control. These results provide the first global study of the expression of the transcriptional machinery through the exponential stationary-phase shift in P. putida. Introduction Pseudomonas putida is a ubiquitous Gram-negative bacterium, metabolically very versatile and adapted to thrive in very diverse habitats. It can be found in soils, aquatic systems or associated to plants (Timmis, 2002). Pseudomonas putida KT2440 is non-pathogenic and has been certified as a safety strain by the Recombinant DNA Advisory Committee. It is widely used as experimental model, as host for gene cloning and expression of heterologous genes, and for biotechnological applications such as bioremediation or biotransformations (Wackett, 2003; Jiménez et al., 2004; Pieper et al., 2004). This strain has been extensively characterized at the physiological, biochemical and genetic levels. KT2440 is a plasmid-free derivative of P. putida mt-2, which contains the TOL plasmid pWW0 (Franklin et al., 1981; Nakazawa, 2002; Regenhardt et al., 2002). This plasmid harbours a catabolic pathway for toluene and xylenes that has been extensively studied from the biochemical and molecular points of view (Ramos et al., 1997). The sequence of P. putida KT2440 genome has been determined and annotated (Nelson et al., 2002). The genome (6.2 Mb) contains 105 distinguishable genomic islands that provide increased metabolic proficiency as well as defence against several kinds of biotic and abiotic stresses (Weinel et al., 2002). Its metabolic versatility, as well as the need to adapt to changing environmental conditions, suggests that P. putida should be endowed with sophisticated
166 L. Yuste et al. mechanisms to regulate gene expression. Several observations support this idea. The number of transcriptional regulators is very large in relation to the genome size. Twenty-four sigma factors have been identified or predicted, 19 of which correspond to the subfamily of extracytoplasmic function (ECF) sigma factors (MartínezBueno et al., 2002). Known ECF sigma factors coordinate transcription in response to extracytoplasmic stimuli (Raivio and Silhavy, 2001). Genes corresponding to several global regulators are also present. Genomic DNA microarrays are now available for several bacterial species (Khodursky et al., 2000; Denef et al., 2004; Goodman and Lory, 2004; Pappas et al., 2004; Zhou et al., 2004; Kang et al., 2005), and are helping to better understand bacterial physiology and lifestyle from a genome-wide perspective. A DNA array for P. putida has been described based on ~2 kb DNA fragments (Stjepandic et al., 2002). However, each spot on this array does not correspond to a defined gene, but to a pair of genome coordinates, which limits its usefulness for gene expression analyses. We have constructed a P. putida genomewide oligonucleotide-based DNA microarray that contains spots corresponding to all the P. putida KT2440 open reading frames (ORFs) annotated at the NCBI Microbial Genome database, and those of the pWW0 TOL plasmid. In combination with real-time reverse transcription polymerase chain reaction (RT-PCR) analyses, this microarray was used to visualize the expression profiles of the principal components of the basic transcriptional machinery when cells leave exponential growth in a complete medium and enter stationary phase. This transition is environmentally relevant, as cells pass from an unrestricted growth to a situation of nutrient limitation and diverse stresses. In particular, we focused on the genes encoding the different subunits of RNA polymerase (RNAP), including the 24 sigma factors described in this strain, and on genes encoding several global regulators known or presumed to be important for the expression of metabolic pathways. The results provide a global picture of the changes that occur in the expression of the main components of the transcriptional regulatory network when this bacterial strain enters the stationary phase of growth.
Results Expression of genes coding for components of the RNAP upon entry into stationary phase The P. putida oligonucleotide-based genomic microarray developed is described in detail in Experimental procedures. We used the microarray for analysing the entry into stationary phase of cells growing in batch cultures containing a complete LB medium. These growth conditions
were chosen because they are the most frequently used in previous reports on the expression of the P. putida transcriptional machinery. All microarray analyses were performed with RNA samples obtained from three independent cultures grown under identical conditions. The cDNA obtained from each RNA preparation was hybridized to a minimum of two microarray slides. Therefore, each data set corresponds to the average of the data obtained in a minimum of six hybridizations. In addition, the expression profile of many of the genes was analysed as well by real-time RT-PCR on RNA samples obtained from at least two additional different cultures. Total RNAs were prepared from culture samples taken at mid-exponential phase (A600 of 0.5), late exponential phase (A600 of 1.2), early stationary phase (A600 of 2.2) and late stationary phase (A600 of 4). The transcriptome profiles of cells collected at turbidity values of 1.2, 2.2 and 4 were compared with that of cells collected at midexponential phase (A600 of 0.5). The microarray data were normalized and statistically analysed with the software package ‘LIMMA’ (Smyth, 2004), as detailed in Experimental procedures. In brief, LIMMA deduces the differential expression values of the genes in the microarray using linear models and moderated t-statistics using the empirical Bayes approach. The probability values obtained (Pvalues) were adjusted for multiple testing to control the false discovery rate (Benjamini and Hochberg, 1995). In this work we have concentrated in a detailed analysis of the changes detected for the genes corresponding to the RNAP and its sigma factors, as well as for several known or predicted global regulators or chromatin-associated proteins that affect gene expression. The results obtained are summarized in Table 1. The mRNA levels corresponding to genes of the RNAP core (a, b, b¢ and w) and to all the sigma factors were very similar in cells collected at the mid-exponential (A600 of 0.5) and at the late-exponential (A600 of 1.2) phases of growth, showing small fold changes and, in many cases, relatively high P-values. However, the mRNA levels for many of the RNAP genes clearly changed upon entry into stationary phase (A600 of 2.2) and in late stationary phase (A600 of 4), with P-values that were very low in most cases (Table 1 and Fig. 1). These low P-values are indicative of a high probability of these genes being differentially expressed in the two conditions considered. In the case of the genes corresponding to the RNAP core (rpoA, rpoB, rpoC and rpoZ, encoding the a-, b-, b¢- and wsubunits respectively), the microarray showed a modest decrease (about 1.5-fold) in their mRNA levels upon entry into early stationary phase. The levels of rpoA and rpoB diminished close to fourfold in late stationary phase, although for rpoC and rpoZ the decrease was lower. Expression of rpoA and rpoB was further analysed by quantitative real-time RT-PCR. The results confirmed that
© 2005 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 8, 165–177
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RNAP a-subunit, RpoA, PP0479 RNAP b-subunit, RpoB, PP0447 RNAP b¢-subunit, RpoC, PP0448 RNAP w-subunit, RpoZ, PP5301 Sigma factor RpoD, PP0387 Sigma factor RpoS, PP1623 Sigma factor RpoN, PP0952 Sigma factor RpoH, PP5108 Sigma factor FliA, PP4341 Sigma factor Pp-ECF-1, PP2088 Sigma factor Pp-ECF-2, PP4611 Sigma factor Pp-ECF-3, PP1427 Sigma factor Pp-ECF-4, PP4244 Sigma factor Pp-ECF-5, PP4608 Sigma factor Pp-ECF-6, PP4208 Sigma factor Pp-ECF-7, PP0352 Sigma factor Pp-ECF-8, PP0162 Sigma factor Pp-ECF-9, PP3086 Sigma factor Pp-ECF-10, PP4553 Sigma factor Pp-ECF-11, PP2888 Sigma factor Pp-ECF-12, PP3006 Sigma factor Pp-ECF-13, PP0994 Sigma factor Pp-ECF-14, PP1008 Sigma factor Pp-ECF-15, PP0667 Sigma factor Pp-ECF-16, PP0704 Sigma factor Pp-ECF-17, PP3577 Sigma factor Pp-ECF-18, PP0865 Sigma factor Pp-ECF-19, PP2192 Crc, PP5292 Lrp, PP5271 Fur, PP4730 Anr, PP4265 CsrA, PP4472 BipA, PP5044 Fis, PP4821 IHF-a, PP2471 IHF-b, PP1773 HupA, PP5313 HupB, PP2303 HupN, PP0975 TurA, PP1366 (MvaT-like regulator) PP0017 (MvaT-like regulator) PP2947 (MvaT-like regulator) PP3765 (MvaT-like regulator) PP3693 (MvaT-like regulator) 0.8 0.7 0.8 0.7 0.6 1.1 0.7 0.9 0.7 0.8 1.0 1.1 0.9 1.1 0.8 1.2 1.3 1.0 1.1 1.0 1.1 0.9 1.1 1.1 0.9 1.1 0.9 1.0 0.6 0.9 0.9 0.7 0.8 0.6 0.8 0.7 0.8 1.1 0.8 0.9 0.7 0.9 0.9 1.4 0.6
Fold changeb -0.40 -0.53 -0.33 -0.57 -0.76 0.12 -0.42 -0.21 -0.47 -0.35 -0.06 0.09 -0.13 0.12 -0.32 0.25 0.34 0.05 0.08 0.03 0.13 -0.15 0.16 0.18 -0.10 0.12 -0.11 -0.06 -0.71 -0.20 -0.14 -0.55 -0.33 -0.62 -0.35 -0.51 -0.26 0.10 -0.32 -0.21 -0.54 -0.12 -0.08 0.44 -0.82
Log2 fold change 0.254 0.151 0.345 0.055 0.024 0.798 0.087 0.390 0.065 0.367 0.797 0.824 0.623 0.611 0.279 0.220 0.119 0.892 0.788 0.933 0.513 0.470 0.406 0.370 0.802 0.636 0.682 0.854 0.134 0.370 0.729 0.107 0.256 0.279 0.246 0.185 0.472 0.775 0.221 0.364 0.290 0.654 0.761 0.057 0.047
Adjusted P-valuec 0.8 0.7 0.9 0.8 0.3 4.4 0.8 0.9 1.0 0.6 1.0 0.9 0.9 1.0 1.1 0.9 1.1 0.9 1.2 1.1 1.0 0.9 1.0 1.1 0.9 1.0 0.9 0.8 0.5 0.6 1.1 1.5 0.8 0.3 1.1 1.1 1.2 3.2 1.0 0.4 1.0 0.6 0.7 5.8 0.4
Fold changeb -0.37 -0.48 -0.15 -0.40 -1.53 2.15 -0.31 -0.21 0.02 -0.83 0.01 -0.18 -0.12 0.05 0.19 -0.17 0.15 -0.16 0.29 0.11 0.05 -0.12 -0.03 0.12 -0.14 -0.04 -0.21 -0.27 -1.10 -0.69 0.09 0.58 -0.41 -1.80 0.11 0.10 0.26 1.66 -0.01 -1.29 0.04 -0.77 -0.59 2.54 -1.50
Log2 fold change
2.2 versus 0.5
0.00569 0.00032 0.09480 0.00247 0.00047 0.00079 0.09601 0.01049 0.85945 0.00018 0.84371 0.35474 0.09598 0.49336 0.28256 0.19086 0.13362 0.21851 0.01223 0.29022 0.44337 0.07881 0.58906 0.21032 0.04641 0.57383 0.00791 0.00214 0.00013 0.00003 0.26589 0.00475 0.01815 0.00003 0.38281 0.50280 0.04600 0.00016 0.83595 0.00204 0.74062 0.00004 0.01050 0.00015 0.00116
Adjusted P-valuec 0.3 0.2 0.6 0.7 0.4 3.3 0.8 1.1 0.6 0.7 1.1 1.3 1.2 1.1 0.7 1.2 1.3 0.8 1.1 1.3 1.1 1.1 1.2 1.4 1.0 1.3 1.1 0.9 0.6 0.6 1.4 0.7 0.7 0.4 0.6 1.2 0.9 2.6 0.3 0.6 0.4 1.0 0.7 1.4 0.3
Fold changeb -1.99 -2.01 -0.74 -0.48 -1.51 1.70 -0.39 0.19 -0.74 -0.47 0.10 0.35 0.24 0.12 -0.59 0.23 0.39 -0.32 0.19 0.41 0.09 0.13 0.23 0.48 0.06 0.39 0.10 -0.17 -0.85 -0.67 0.50 -0.44 -0.51 -1.42 -0.67 0.29 -0.19 1.39 -1.97 -0.63 -1.44 0.02 -0.60 0.51 -1.63
Log2 fold change
4 versus 0.5
0.016 0.010 0.028 0.058 0.003 0.125 0.080 0.420 0.081 0.058 0.743 0.454 0.442 0.713 0.085 0.501 0.089 0.361 0.363 0.112 0.676 0.452 0.393 0.058 0.814 0.145 0.632 0.441 0.240 0.118 0.186 0.256 0.070 0.040 0.223 0.720 0.605 0.159 0.025 0.041 0.174 0.958 0.064 0.039 0.006
Adjusted P-valuec
a. Gene signal observed for each gene in the assay comparing transcriptomes at turbidities 1.2 versus 0.5 (the gene signal was calculated as the geometric mean of the fluorescence signals obtained for each gene in the two conditions compared). b. The fold change is the ratio of the signal observed at the analysed turbidity (1.2, 2.2 or 4) relative to that observed at a turbidity of 0.5. c. The P-values were adjusted for multiple testing to control the false discovery rate (see Experimental procedures).
Gene signala
Protein/TIGR ID
1.2 versus 0.5
Turbidity (A600)
Table 1. Changes in mRNA levels of genes coding for RNAP subunits or global regulators, determined by microarray analyses.
Pseudomonas putida transcriptional apparatus 167
168 L. Yuste et al. at detecting differentially expressed genes, it tends to underestimate the fold change values, a general trend in microarrays. The levels of rpoS mRNA were about fourfold higher in stationary phase than in exponential phase, while those of rpoD decreased threefold (Fig. 1 and Table 2). RT-PCR analyses confirmed these results. The mRNA levels of rpoN, rpoH and fliA sigma factors tended to remain unchanged throughout growth phase (Fig. 1 and Table 1). Pseudomonas putida contains 19 sigma factors showing similarity to members of the ECF subfamily. As shown in Table 1, the gene signal obtained for seven of them (ECF-4, ECF-7, ECF-8, ECF-12, ECF-13, ECF-14 and ECF-17) in exponentially growing cells was rather low (< 300 fluorescence units). The 203 control spots containing only spotting buffer present in the microarray rendered an average gene signal of 215 ± 17 fluorescence units (out of a range of 0–65 536). Therefore, data for genes rendering a gene signal
