SWARMING MOTILITY IN PSEUDOMONAS AERUGINOSA: A COMPLEX ADAPTATION WITH IMPLICATIONS FOR ANTIBIOTIC RESISTANCE AND VIRULENCE by Shannon Coleman B.Sc., The University of British Columbia, 2014 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (MICROBIOLOGY AND IMMUNOLOGY) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April 2020 © Shannon Coleman, 2020 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Swarming motility in Pseudomonas aeruginosa: a complex adaptation with implications for antibiotic resistance and virulence submitted by Shannon Coleman in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Microbiology and Immunology Examining Committee: Robert E.W. Hancock, Microbiology and Immunology Supervisor Charles Thompson, Microbiology and Immunology Supervisory Committee Member Rachel Fernandez, Microbiology and Immunology University Examiner Natalie Strynadka, Biochemistry and Molecular Biology University Examiner Additional Supervisory Committee Members: J. Thomas Beatty, Microbiology and Immunology Supervisory Committee Member Michael Murphy, Microbiology and Immunology Supervisory Committee Member iii Abstract Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen that possesses intrinsic antibiotic resistance. Highly adaptable, P. aeruginosa is capable of different forms of motility, including swarming, swimming, twitching and surfing. Swarming motility is a multicellular movement of cells across semisolid surfaces that is associated with complex adaptations including adaptive antibiotic resistance. Here a disc diffusion assay showed that swarming bacteria were resistant to multiple antibiotics, including aminoglycosides, β-lactams, chloramphenicol, ciprofloxacin, macrolides, tetracycline, and trimethoprim. RNA-Seq of swarming cells showed the dysregulation of 1,581 genes, including 104 regulatory factors, upregulated virulence and iron acquisition factors, and downregulated ribosomal genes. Forty-one mutants resistant to tobramycin under swarming conditions were found, including prtN, a regulator of pyocin, and wbpW, involved in LPS biosynthesis. RNA-Seq of swarming cells treated with tobramycin revealed the upregulation of the multidrug efflux pump mexXY. To investigate the role of swarming in vivo, a screen for swarming-specific mutants was performed, revealing ptsP, a regulator of carbon and nitrogen metabolism. The ∆ptsP mutant was deficient specifically in swarming but not swimming or twitching motility. Interestingly, ∆ptsP also had greatly reduced organ invasion in a mouse infection model, suggesting a likely role for swarming in vivo. Besides ptsP, small RNAs also regulated swarming motility, typically via post-transcriptional means. A screen of sRNA overexpressing strains revealed an sRNA, PA0805.1 that influenced diverse bacterial behaviours including swarming, swimming, twitching, cytotoxicity, adherence and tobramycin resistance. RNA-Seq and proteomics uncovered a broad regulatory profile with 1,121 differentially expressed genes and 925 proteins, including 118 regulatory factors, downregulated pilus genes, upregulated adherence and virulence factors, and upregulated multidrug efflux systems including mexXY and mexGHI-opmD. Another sRNA, PA2952.1, when overexpressed influenced swarming, swimming, and tobramycin, gentamicin and trimethoprim resistance. Transcriptomics and proteomics showed differential abundance of 784 genes and 445 proteins, encompassing 82 regulatory factors, downregulated pili, dysregulated flagellar genes, upregulated mexGHI-opmD and the upregulated arn operon involved in LPS modification. Overall this thesis has shown that swarming motility is a complex adaptation conferring multiple antibiotic resistance, that is regulated by sRNAs and coupled to virulence adaptations in vivo. iv Lay Summary Antibiotic resistance is a rising global health threat with several contributing causes. One of these is adaptive resistance that is triggered by and dependent on specific growth conditions, such as during multicellular movement over a surface, termed swarming motility. In Pseudomonas aeruginosa, I showed that swarming bacteria were resistant to multiple antibiotics. More than a thousand genes were dysregulated under swarming conditions. The resistance of swarming cells to tobramycin was dependent on 41 of these genes. By generating a specific swarming-defective mutant in a regulator of carbon and nitrogen metabolism, I demonstrated reduced virulence in an infection model, indicating that swarming was important for infections. I also showed that swarming was regulated by a novel element, small RNAs that typically affect the production of proteins in cells. I showed specific elements had massive and diverse impacts on cellular behaviour, gene expression and protein abundance. v Preface This thesis is an original intellectual product of the author, Shannon Coleman, with the guidance and mentorship of Dr. Robert (Bob) Hancock. Dr. Hancock was responsible for the original conceptualization, while I designed experiments using his advice. I performed the majority of all experiments in this thesis, with exceptions noted below. I analyzed all the data, with the exception of initial differential analyses of RNA-Seq and proteomics data, which were analyzed by the bioinformaticists and proteomics collaborators named below. I drafted all of the manuscripts, with help from collaborators for their specific sections in the Materials & Methods. Dr. Hancock and I both edited the manuscripts extensively. The American Society of Microbiology (ASM) states: “Authors in ASM journals retain the right to republish discrete portions of his/her article in any other publication (including print, CD-ROM, and other electronic formats) of which he or she is author or editor, provided that proper credit is given to the original ASM publication. ASM authors also retain the right to reuse the full article in his/her dissertation or thesis.” Chapter 2: Sections of Chapter 2 were derived from the three manuscripts listed for Chapters 3, 4, and 5. Chapter 3: A version of Chapter 3 has been published. Coleman SR, Blimkie T, Falsafi R, Hancock REW. Multidrug adaptive resistance of Pseudomonas aeruginosa swarming cells. Antimicrob. Agents Chemother. 2020, 64:e01999-19. Reza Falsafi depleted ribosomal RNA and prepared RNA-Seq libraries for all experiments in this thesis. Travis Blimkie analyzed the RNA-Seq data in Chapter 3, uploaded it to GEO, and wrote methods for the RNA-Seq analysis. Chapter 4: A version of Chapter 4 is currently in revision. Coleman SR, Smith ML, Spicer V, Lao Y, Mookherjee N, Hancock REW. Overexpression of the small RNA PA0805.1 in Pseudomonas aeruginosa modulates the expression of a large set of genes and proteins, resulting in altered motility, cytotoxicity and tobramycin resistance. Dr. Maren Smith analyzed the RNA-Seq data in Chapter 4 and helped me to upload it to GEO. Dr. Neeloffer Mookherjee assisted with experimental design for the proteomics experiments in Chapter 4 and also edited the manuscripts based on these studies. Ying Lao lysed bacterial pellets, prepared samples for proteomics, acquired mass spectrometry data, and wrote methods for the vi proteomics. Victor Spicer performed the differential analysis of proteins for Chapter 4, uploaded data to MassIVE, and wrote methods for the proteomics analysis. Chapter 5: A version of Chapter 5 is currently being prepared for publication. Coleman SR, Smith ML, Spicer V, Lao Y, Taylor P, Mookherjee N, Hancock REW. The small RNAs PA2952.1 and prrH as regulators of virulence, motility and iron metabolism in Pseudomonas aeruginosa. Dr. Maren Smith analyzed the RNA-Seq data in Chapter 5 and helped me to upload it to GEO. Dr. Neeloffer Mookherjee assisted with experimental design for the proteomics experiments in Chapter 5. Ying Lao lysed bacterial pellets, prepared samples for proteomics, acquired mass spectrometry data, and wrote methods for the proteomics. Victor Spicer performed the differential analysis of proteins for Chapter 5, and wrote methods for the proteomics analysis. Dr. Patrick Taylor was involved in experimental design and initial investigations of small RNAs. Chapter 6: Dr. Daniel Pletzer performed the in vivo work in Chapter 6, wrote methods for the in vivo work, and also assisted with troubleshooting and experimental design. Other publications arising from work presented in this thesis: 1. Pletzer D, Coleman SR, Hancock REW. Anti-biofilm peptides as a new weapon in antimicrobial warfare. Curr. Opin. Microbiol. 2016, 33:35–40. This review was written by Dr. Daniel Pletzer and I and edited by Dr. Hancock. Ethics statements Animal experiments were performed in accordance with The Canadian Council on Animal Care (CCAC) guidelines and were approved by the University of British Columbia Animal Care Committee (certificate number A14-0363). Mice used in this study were female outbred CD-1. All animals were purchased from Charles River Laboratories (Wilmington, MA), were 7 weeks of age, and weighed about 25 ± 3 g at the time of the experiments. Isoflurane (1 to 3%) was used to anesthetize the mice. Mice were euthanized with carbon dioxide. The use of all bacterial strains presented in this thesis was approved by UBC Risk Management Services under the UBC Biosafety Permit Number B14-0207 and B14-0208. vii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ............................................................................................................................... iv Preface .............................................................................................................................................v Table of Contents ........................................................................................................................ vii List of Tables ..................................................................................................................................x List of Figures .............................................................................................................................. xii List of Abbreviations ................................................................................................................. xiv Acknowledgements .................................................................................................................... xvi Chapter 1: Introduction ............................................................................................................... 1 1.1 Pseudomonas aeruginosa ........................................................................................... 1 1.1.1 A diverse opportunistic pathogen ....................................................................... 1 1.1.2 An arsenal of virulence factors ........................................................................... 1 1.1.3 Progression of chronic CF lung infections.......................................................... 3 1.2 Bacterial motility ........................................................................................................ 4 1.2.1 Swarming motility .............................................................................................. 4 1.2.2 Other forms of motility ....................................................................................... 6 1.3 Antibiotic resistance.................................................................................................... 7 1.3.1 Mechanism of resistance to specific antibiotics .................................................. 7 1.3.2 Acquired resistance ............................................................................................. 9 1.3.3 Adaptive resistance ............................................................................................. 9 1.3.4 Antibiotics used to treat P. aeruginosa infections .............................................. 9 1.4 Small RNAs ................................................................................................................ 9 1.4.1 Mechanisms of regulation by sRNAs ............................................................... 10 1.4.2 Known sRNAs in P. aeruginosa ....................................................................... 10 1.4.3 Uncharacterized sRNAs in P. aeruginosa ........................................................ 12 1.5 Hypothesis and Objectives ........................................................................................ 13 1.5.1 Objectives ......................................................................................................... 13 Chapter 2: Materials and Methods ........................................................................................... 15 2.1 Bacterial strains and growth conditions .................................................................... 15 2.1.1 Growth curves ................................................................................................... 15 2.2 Motility assays .......................................................................................................... 15 2.2.1 Swarming .......................................................................................................... 16 2.2.2 Swimming ......................................................................................................... 16 2.2.3 Twitching .......................................................................................................... 16 2.2.4 Disc diffusion assay .......................................................................................... 16 2.2.5 Agar dilution assay ........................................................................................... 17 2.2.6 Six well plate assays ......................................................................................... 17 2.3 Other phenotypic assays ........................................................................................... 17 2.3.1 Biofilm formation ............................................................................................. 17 2.3.2 Adherence ......................................................................................................... 17 2.3.3 Cytotoxicity....................................................................................................... 18 2.3.4 Outer membrane permeabilization assay .......................................................... 19 2.3.5 Pyoverdine assay ............................................................................................... 19 2.4 Antibiotic susceptibility assays ................................................................................. 19 2.4.1 Minimal inhibitory concentration (MIC) .......................................................... 19 2.4.2 Kill curves ......................................................................................................... 19 2.5 RNA-Seq ................................................................................................................... 19 viii 2.5.1 Conditions used ................................................................................................. 19 2.5.2 RNA isolation ................................................................................................... 20 2.5.3 RNA-Seq and identification of differentially expressed (DE) genes ................ 20 2.6 Proteomics................................................................................................................. 21 2.6.1 Protein digestion and quantification ................................................................. 21 2.6.2 Tandem mass tag (TMT) labeling..................................................................... 22 2.6.3 Mass spectrometry data acquisition .................................................................. 22 2.6.4 Identification and differential analysis of proteins ........................................... 23 2.7 Murine infection abscess model................................................................................ 23 2.8 qRT-PCR................................................................................................................... 24 2.9 DNA manipulation .................................................................................................... 26 2.9.1 Deletion mutants ............................................................................................... 26 2.9.2 Complementation and overexpression strains .................................................. 27 2.9.3 Transformation of P. aeruginosa ...................................................................... 28 126.96.36.199 Electroporation .............................................................................................. 29 188.8.131.52 Conjugation ................................................................................................... 29 2.10 In silico sRNA target prediction ............................................................................... 29 2.11 Statistical analysis ..................................................................................................... 29 2.12 Data availability ........................................................................................................ 30 Chapter 3: Swarming motility and antibiotic resistance ........................................................ 31 3.1 Introduction ............................................................................................................... 31 3.2 Swarming cells were resistant to multiple antibiotic classes .................................... 31 3.3 Swarming motility is a complex adaptation accompanied by many changes in the expression of resistome genes ............................................................................................... 32 3.4 Multiple factors contributed to swarming-mediated antibiotic resistance ................ 38 3.5 A mutant in wbpW was resistant to tobramycin and had decreased membrane permeability .......................................................................................................................... 41 3.6 Mutation of prtN induced resistance to tobramycin and trimethoprim..................... 42 3.7 Antibiotic susceptibility was affected by growth conditions .................................... 43 3.8 Subinhibitory tobramycin treatment under swarming conditions ............................. 44 3.9 Comparison of RNA-Seq experiments ..................................................................... 45 3.10 Discussion ................................................................................................................. 46 Chapter 4: Influence of the sRNA PA0805.1 on motility and virulence ................................ 49 4.1 Introduction ............................................................................................................... 49 4.2 Overexpression of PA0805.1 resulted in decreased motility .................................... 49 4.3 Overexpression of PA0805.1 resulted in increased cytotoxicity against HBE cells and increased tobramycin resistance ........................................................................................... 50 4.4 Overexpression of PA0805.1 resulted in broad protein and transcriptional changes including 118 regulatory factors ........................................................................................... 51 4.5 The multidrug efflux genes mexXY and mexGHI-opmD were upregulated in the PA0805.1 overexpression strain ........................................................................................... 59 4.6 Adherence factors were dysregulated in the PA0805.1 overexpression strain ......... 61 4.7 Additional virulence factors were upregulated in the PA0805.1 overexpression strain ....................................................................................................................................61 4.8 Comparison of RNA-Seq and proteomics ................................................................ 62 4.9 In silico sRNA target prediction ............................................................................... 62 4.10 In its native state, PA0805.1 contributed to tobramycin susceptibility under swarming conditions .............................................................................................................................. 63 ix 4.11 Discussion ................................................................................................................. 63 Chapter 5: The sRNAs PA2952.1 and prrH as regulators of virulence, motility and iron metabolism ................................................................................................................................... 66 5.1 Introduction ............................................................................................................... 66 5.2 Phenotypic screens of sRNA overexpression strains ................................................ 66 5.3 sRNA prrH played a role in cytotoxicity and pyoverdine production...................... 67 5.4 Overexpression of sRNAs altered antibiotic susceptibility under swarming conditions ....................................................................................................................................70 5.5 Overexpression of PA2952.1 resulted in broad transcriptional changes including altered expression of 82 regulatory factors ........................................................................... 70 5.6 Pili and flagellar genes were dysregulated in the PA2952.1 overexpression strain . 77 5.7 Upregulation of mexGHI-opmD and the arn operon might lead to aminoglycoside resistance in the PA2952.1 overexpression strain................................................................. 78 5.8 DNA biosynthetic pathways were dysregulated ....................................................... 79 5.9 Virulence, cell division, and metal uptake pathways were dysregulated ................. 79 5.10 In silico sRNA target prediction ............................................................................... 79 5.11 Comparison of PA2952.1 omics data with previous datasets ................................... 80 5.11.1 Comparison with swarm vs. swim RNA-Seq ................................................... 80 5.11.2 Comparison of RNA-Seq and proteomics data for the PA0805.1 and PA2952.1 overexpressing strains ....................................................................................................... 80 5.12 Discussion ................................................................................................................. 81 Chapter 6: The role of swarming in vivo .................................................................................. 83 6.1 Introduction ............................................................................................................... 83 6.2 The host defense peptide 1018 specifically inhibited swarming motility ................. 83 6.3 Screen of swarming-deficient mutants...................................................................... 84 6.4 A mutant in ptsP was specifically inhibited for swarming motility ......................... 85 6.5 The swarming-deficient mutant ∆ptsP had reduced virulence in vivo ..................... 86 6.6 Discussion ................................................................................................................. 87 Chapter 7: Conclusion ................................................................................................................ 89 7.1 Summary of thesis work ........................................................................................... 89 7.2 Applications .............................................................................................................. 91 7.3 Future directions ....................................................................................................... 91 References .....................................................................................................................................93 Appendix A Supplementary Figures.......................................................................................108 Appendix B Supplementary Tables.........................................................................................113 B.1 PA14 RNA-Seq data.....................................................................................................113 B.2 PAO1 RNA-Seq and proteomic data............................................................................163 B.3 Other Supplementary Tables.........................................................................................254 x List of Tables Table 2-1. Amount of antibiotic used in the disc diffusion assay. ................................................ 16 Table 2-2. Parameters for cocultures optimized for the PA14 and PAO1 strains. ....................... 18 Table 2-3. Number of biological replicates per RNA-Seq experiment. ....................................... 20 Table 2-4. Comparisons and media used for qRT-PCR experiments. .......................................... 24 Table 2-5. Primers used for qRT-PCR. ......................................................................................... 24 Table 2-6. Primers used for cloning. ............................................................................................. 26 Table 2-7. Cloning strategies and restriction enzymes used. ........................................................ 28 Table 2-8. Methods of transformation used in this thesis, including vectors and antibiotic concentrations. ........................................................................................................................ 29 Table 3-1. Selected results from swarm vs. swim RNA-Seq comparisons. These revealed 104 dysregulated transcriptional regulators, and dysregulated efflux and β-lactamase genes. Cutoffs used were FC ≥ 1.5 and padj ≤ 0.05. ......................................................................... 34 Table 3-2. Genes dysregulated under swarming conditions that matched with the known resistome revealed 26 tobramycin resistance mutants. PA14 transposon mutants in selected genes were tested for altered tobramycin susceptibility under swarming conditions using the agar dilution method (inhibitory concentrations shown in μg/ml of tobramycin, along with images of swarming colonies at 1 μg/ml). Evidence of dysregulation came from swarm vs. swim RNA-Seq (superscript 1) or tobramycin RNA-Seq (superscript 2). Selected genes were also confirmed by qRT-PCR from (Overhage et al. 2008) (superscript 3), Additional mutants in genes showing no evidence of dysregulation (gmd and rmd) but belonging to operons containing dysregulated genes were also tested. 17 additional mutants are described in Table A3. .......................................................................................................................................... 38 Table 3-3. Selected genes that were differentially expressed upon tobramycin treatment under swarming conditions. ............................................................................................................. 44 Table 4-1. Selected genes of interest with differential expression in the PA0805.1 overexpression strain as compared to EV by RNA-Seq and/or proteomics. Categories of interest include regulators, multidrug efflux, motility, LPS biosynthesis, type VI secretion and other virulence factors. Cutoffs used were p/padj ≤ 0.05 and for RNA-Seq, FC ≥ 1.5. ................................. 52 Table 4-2. The MexGHI-OpmD operon was upregulated in the PA0805.1 overexpression strain when compared to EV strain by qRT-PCR. Bacteria were harvested from BM2 glycerol swarm plates with 1% arabinose and 0.1% CAA. n = 3. ................................................................... 60 Table 4-3. sRNA targets predicted in silico that were confirmed for PA0805.1 by RNA-Seq or proteomics as well as their FC, p-values (padj/p) and predictive methods. ........................... 62 Table 5-1. Selected differential expressed genes/proteins in the PA2952.1 overexpression strain as compared to WT EV by RNA-Seq and/or proteomics. Loci shown in bold showed differences uniquely in the proteome. Cutoffs used were p/padj ≤ 0.05 and for RNA-Seq, FC ≥ 1.5. .... 72 Table 5-2. The mexGHI-opmD operon was modestly upregulated in the PA2952.1 overexpression strain when compared to WT EV by qRT-PCR. Bacteria were harvested from BM2 glycerol swarm plates with 1% arabinose and 0.1% CAA. n = 3. ....................................................... 78 Table 5-3. sRNA targets predicted in silico that were confirmed for PA2952.1 by RNA-Seq or proteomics as well as their FC, p-values (padj/p) and predictive methods. ........................... 80 Table 6-1. Candidate swarming-deficient mutants. Numbers shown are percent of WT. Numbers shown in bold are less than 70% of WT or significantly greater than 100% of WT. The allele numbers 1553 and 1946 designate the position (bp) of the transposon insertion for the two ptsP mutants. n ≥ 3. ................................................................................................................ 84 Table 6-2. Virulence factors were not dysregulated in the ∆ptsP mutant. n = 3. ......................... 86 Table A1. Compilation of all PA14 RNA-Seq data reported in this thesis. ............................... 113 xi Table A2. Compilation of all PAO1 RNA-Seq and proteomic data reported in this thesis. ...... 163 Table A3. 17 additional resistome genes with corresponding mutants showing tobramycin resistance under swarming conditions. Evidence of dysregulation comes from swarm vs swim RNA-Seq. PA14 transposon mutants in selected genes were tested for altered tobramycin susceptibility under swarming conditions using the agar dilution method (inhibitory concentrations shown in μg/ml of tobramycin, along with images of swarming colonies at 1 μg/ml). .................................................................................................................................. 254 Table A4. Swarming inhibitory concentrations (µg/ml) of PA14 mutants on BM2 swarm plates at 0.5% agar. n ≥ 3.................................................................................................................... 254 Table A5. Standard MIC (µg/ml) of PA14 mutants in liquid media. n = 3. ............................... 255 Table A6. Tobramycin MIC (μg/ml) in LB for additional selected PA14 mutants. n = 3. ........ 255 Table A7. Tobramycin MIC (μg/ml) in BM2 glucose with 0.1% CAA and no (NH4)2SO4. n = 3. .............................................................................................................................................. 255 Table A8. sRNA targets predicted in silico for PA0805.1. ........................................................ 255 Table A9. MIC (μg/ml) assessed by the standard broth microdilution assay in BM2 glycerol 0.1% CAA with no (NH4)2SO4. n ≥ 3..............................................................................................256 Table A10. sRNA targets predicted in silico for PA2952.1.........................................................256 xii List of Figures Figure 3-1. Swarming bacteria exhibited heightened resistance to most antibiotic classes. Top panels: Zone of inhibition assay using 0.3% agar for swimming, 0.4% for swarming and 1.5% for spread plate with different antibiotics. Statistically significant differences were determined by ANOVA. Lower panels: Zone of inhibition assay for PA14 WT using tobramycin discs. Arrows indicate position of inoculation. n ≥ 3. ...................................................................... 33 Figure 3-2. Tobramycin kill curve showing that swarming cells survived better than swimming cells in the presence of tobramycin. n = 3. ............................................................................. 34 Figure 3-3. Antibiotic susceptibility of PA14 mutants under swarming conditions using the disc diffusion method at 0.5% agar. Statistically significant differences were determined by paired t test. n ≥ 4. ............................................................................................................................. 41 Figure 3-4. Agar dilution method for determining the swarming inhibitory concentration (IC) of PA14 mutants at 0.5% agar. A) tobramycin swarming IC = 1 μg/ml B) trimethoprim IC = 10 μg/ml C) tobramycin. n ≥ 3. ................................................................................................... 41 Figure 3-5. Complementation of swarming antibiotic susceptibility phenotypes for A) prtN B) wbpW. All strains were transformed with either the respective empty vector (WT and mutants) or a vector with insert (complemented (+) strains). n ≥ 3. ..................................................... 42 Figure 3-6. A wbpW mutant had reduced membrane permeabilization. Swarm cells were harvested and treated where indicated with a) NPN and b) tobramycin. n = 3. ..................................... 43 Figure 4-1. Motility assays revealed that overexpression of PA0805.1 was generally anti-motility. 1% arabinose was used to induce expression and statistically significant differences were determined using paired Student’s t test. n ≥ 3. ..................................................................... 50 Figure 4-2. Cytotoxicity assay of the PA0805.1 overexpression strain revealed that induction of PA0805.1 led to increased cytotoxicity against HBE cells. Statistically significant differences were determined using paired Student’s t test. n ≥ 3.............................................................. 51 Figure 4-3. PA0805.1 overexpression led to swarming-dependent tobramycin resistance as assessed in BM2 glucose swarm plates with no arabinose and supplemented where indicated with tobramycin at 1 μg/ml. n = 3. ......................................................................................... 51 Figure 4-4. Proposed model for how the overexpression of PA0805.1 dysregulated many genes, resulting in altered phenotypes. Connecting arrows represent direct or indirect regulation. . 60 Figure 4-5. The PA0805.1 overexpression strain demonstrated increased adherence to polystyrene plates in 90% LB with 5% arabinose. Statistically significant differences were determined using Student’s paired t test. n ≥ 3. ........................................................................................ 61 Figure 4-6. A deletion mutant of PA0805.1 was supersusceptible to tobramycin as assessed in BM2 glucose swarming agar with no arabinose. The deletion mutant was complemented with a chromosomal insertion of the sRNA PA0805.1. Tobramycin was incorporated into the agar where indicated at 1 μg/ml. n = 3. .......................................................................................... 63 Figure 5-1. Motility screen of sRNA overexpression strains revealed that overexpression of certain sRNAs altered motility. 1% Arabinose was used to induce expression and statistically significant differences from WT EV were determined using one-way ANOVA. n ≥ 3. ....... 68 Figure 5-2. Overexpression of certain sRNAs led to partial reductions in swarming (top row) and swimming (bottom row) motilities. n ≥ 3. ............................................................................. 69 Figure 5-3. Cytotoxicity phenotypes of sRNA overexpression strains in the absence of arabinose. A) overexpression of PA2952.1 compared to WT EV. B) deletion and overexpression of prrH. Statistically significant differences were determined by unpaired t test (A) or one-way ANOVA (B). n ≥ 3. ................................................................................................................ 69 Figure 5-4. A deletion mutant ∆prrH had increased production of pyoverdine. n = 3. ................ 70 Figure 5-5. Antibiotic susceptibility phenotypes were affected by sRNAs under swarming xiii conditions. A. The strain overexpressing PA2952.1 showed resistance to tobramycin and gentamicin in BM2 glucose swarm plates with no arabinose, supplemented where indicated with 1 μg/ml antibiotic. n = 3. B. Overexpression of PA2952.1 induced susceptibility to trimethoprim in BM2 glycerol swarm plates. Trimethoprim is included where indicated at 10 μg/ml. n ≥ 3. C. The PA14sr120 overexpression strain was resistant to tobramycin in BM2 glucose swarm plates with no arabinose. Tobramycin is included where indicated at 1 μg/ml. n ≥ 3. D. Overexpression of PA1091.1b increased susceptibility to trimethoprim in BM2 glycerol swarm plates. Trimethoprim is included where indicated at 10 μg/ml. n ≥ 3. ......... 71 Figure 5-6. Proposed model for how the overexpression of PA2952.1 dysregulates many genes, resulting in altered phenotypes. Connecting arrows represent direct or indirect regulation. . 82 Figure 6-1. Peptide 1018 specifically inhibited swarming motility. n ≥ 3. .................................. 84 Figure 6-2. The ∆ptsP mutant had deficient swarming ability but relatively normal swimming and twitching motility. n ≥ 3. ........................................................................................................ 85 Figure 6-3. Growth curves for the ∆ptsP mutant in four different media. n = 3. ......................... 86 Figure 6-4. The ∆ptsP mutant had reduced organ invasion in vivo. CD-1 mice were injected with 2.5 x 107 CFU to form a cutaneous abscess. After 16-18 hours, organs were harvested, homogenized and plated for CFU counting. .......................................................................... 88 Figure A1. Disc diffusion assay for PA14 WT performed at a higher agar concentration. Agar concentrations were: 0.5% (swarming), cf. 0.3% (swimming), and 1.5% (spread plate).....108 Figure A2. Venn diagrams showing common and unique genes for omic comparisons. n ≥ 3......109 Figure A3. Scatterplots showing correlations of common genes for omic comparisons. Numbers in the four corners of each graph show the number of genes/proteins found in each quadrant. .............................................................................................................................................. 110 Figure A4. Growth curves of sRNA overexpression strains in BM2 glycerol with 1% arabinose showed little difference compared to EV. n ≥ 3......................................................................111 Figure A5. Adherence of sRNA overexpression strains to polystyrene plates. Statistically significant differences were determined using one-way ANOVA. n ≥ 3................................111 Figure A6. Cytotoxicity phenotypes of sRNA overexpression strains with 1% arabinose. a) overexpression of PA2952.1 compared to WT EV. b) deletion and overexpression of prrH. Statistically significant differences were determined by unpaired t test (a) or one-way ANOVA (b). n ≥ 3.................................................................................................................................111 Figure A7. Subinhibitory trimethoprim inhibited the growth of the PA2952.1 overexpression strain in standard MICs in BM2 glycerol with 1% arabinose. n = 3.................................................112 Figure A8. Cytotoxicity phenotype of the ∆ptsP mutant. Statistically significant differences were determined by ANOVA. n ≥ 3.....................................................................................................112 xiv List of Abbreviations ΔΔCT – comparative cycle threshold method 1D – one-dimensional 2YT – yeast extract and tryptone media 3-O-C12 – N-(3-oxododecanoyl)-L-homoserine lactone AGC – automatic gain control ANOVA – analysis of variance ASM – American Society of Microbiology BM2 – basal medium 2 bp – basepair C4-HSL – N-butanoyl-L-homoserine lactone CAA – Casamino acids CCAC – Canadian Council on Animal Care cf. – Latin: confer/conferatur (compare) CF – cystic fibrosis CFU – colony forming units CGS – Canada Graduate Scholarship CIHR – Canadian Institutes for Health Research CPA – common polysaccharide antigen CRISPR – clusters of regularly interspaced short palindromic repeats CRP – catabolite repressor protein DE – differentially expressed DMEM - Dulbecco's Modified Eagle Medium DNA – deoxyribonucleic acid EDTA - ethylenediaminetetraacetic acid e.g. – Latin exempli gratia (for example) EPS – extracellular polymeric substance EV – empty vector FBS – fetal bovine serum FC – fold change GAF – domain found in cGMP-PDEs, adenylyl cyclases, and E. coli fh1A gDNA – genomic DNA GEO – Gene Expression Omnibus h – hour HBE – human bronchial epithelial cells HEPES – 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid HHQ – 4-hydroxy-2-heptylquinoline IC – inhibitory concentration i.e. – Latin: id est (in other words) LB – Luria-Bertani broth LC-MS – liquid chromatography-mass spectrometry LC/MS/MS – liquid chromatography with tandem mass spectrometry LDH – lactate dehydrogenase LPS – lipopolysaccharide Mbp – mega basepairs MDR – multidrug resistant MEM – Minimum Essential Medium MGF – mascot generic format xv MIC – minimal inhibitory concentration min – minute mRNA – messenger RNA ms – millisecond m/z – mass per charge number NPN – N-phenyl-1-naphthylamine OSA – O-specific antigen p – probability value padj – adjusted p value PBS – phosphate buffered saline PCR – polymerase chain reaction PG – peptidoglycan PPM – parts per million PQS – 2-heptyl-3,4-dihydroxyquinoline PTM – post-translational modification qRT-PCR – quantitative reverse transcriptase PCR QS – quorum sensing RF – radio frequency RNA – ribonucleic acid RND – Resistance-Nodulation-Cell Division RPMI – Roswell Park Memorial Institute rRNA – ribosomal RNA s – second SCFM – synthetic cystic fibrosis sputum media SD – standard deviation SDS – sodium dodecyl sulfate SP3 – single-pot solid-phase-enhanced sample preparation sRNA – small RNA T1SS – type I secretion system T2SS – type II secretion system T3SS – type III secretion system T5SS – type V secretion system T6SS – type VI secretion system TE – Tris-EDTA TMT – tandem mass tag Tn – transposon TOB – tobramycin Tris – tris (hydroxymethyl) aminomethane tRNA – transfer RNA UNTR – untreated vs. – versus WT – wild type WT EV – wild type empty vector xvi Acknowledgements I thank my supervisor Dr. Robert Hancock for his advice, patience and support throughout my degree. My thesis committee was also supportive and encouraging and included Drs. J. Thomas Beatty, Michael Murphy, and Charles Thompson. Research reported in this thesis was supported by a grant from the Canadian Institutes for Health Research FDN-154287 and the Cystic Fibrosis (CF) Canada Award Number 3177. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Canadian Institutes for Health Research. I was the recipient of CIHR Frederick Banting and Charles Best Canada Graduate Scholarship Master’s (CGS-M, 141534) and Doctoral Awards (CGS-D, 146221), and a Four Year Fellowship for PhD students from UBC. My supervisor Dr. Robert Hancock holds a Canada Research Chair in Health and Genomics and a UBC Killam Professorship. I also thank all lab members for their help throughout the years, particularly Dr. Susan Farmer, Manjeet Bains and Reza Falsafi for lab management, Drs. Mike Trimble, Daniel Pletzer, Evan Haney and Amy Lee for scholarly discussions, and other residents of room 235 for assistance with daily tasks and troubleshooting, including Dr. Evelyn Sun, Lauren Wilkinson, Corrie Belanger, Melanie Dostert, Noushin Akhoundsadegh and Morgan Alford. Dr. Amy Lee and Reza Falsafi were also very helpful in coordinating and executing RNA-Seq projects in the lab. Special thanks to Dr. Daniel Pletzer for performing in vivo work in Chapter 6 and for advice about the project. In addition I also thank collaborators for assistance with proteomics: Dr. Neeloffer Mookherjee, Ying Lao and Victor Spicer. I also enjoyed collaborating with Martha Liu from the Gaynor lab on the Bacillus project. Special thanks are owed to my parents, Chris and Judy Coleman, who have provided moral and nutritional support throughout my years of education, and my brothers Jonathan and Daniel.1 Chapter 1: Introduction 1.1 Pseudomonas aeruginosa Pseudomonas aeruginosa is a Gram-negative rod-shaped -proteobacterium. As a facultative anaerobe with a large (5-7 Mbp) genome, P. aeruginosa thrives in a variety of environments, including soil, freshwater ecosystems, and is an opportunistic pathogen of plants and animals (Chatterjee et al., 2017; Curran et al., 2018; Moradali et al., 2017). 1.1.1 A diverse opportunistic pathogen P. aeruginosa infects a wide range of living organisms, including plants such as lettuce, Arabidopsis and sweet basil (Starkey & Rahme, 2019; Walker et al., 2004). In animals, P. aeruginosa is a pathogen of invertebrates, including Drosophila (D’Argenio et al., 2001) and Caenorhabditis elegans (An et al., 1999), as well as vertebrates such as dogs, cats, cattle (Haenni et al., 2017), fish (Clatworthy et al., 2009) and mice (Pletzer et al., 2018). Importantly, P. aeruginosa is also an opportunistic pathogen of humans, and able to colonize numerous niches within the host, contributing to a variety of diseases including cystic fibrosis (CF), pneumonia, burn wound infections, bloodstream infections, keratitis, nosocomial infections, urinary tract infections, ear infections and more (Davies, 2002; Mittal et al., 2009; Moore & Flaws, 2011). Patients at increased risk of infection with P. aeruginosa include those who have CF, burn wounds, or use mechanical ventilators (Moore & Flaws, 2011). P. aeruginosa is particularly problematic in the human lung, where it causes major complications in diseases such as CF and pneumonia. P. aeruginosa is one of the most common CF pathogens, and up to 60% of patients are colonized by Pseudomonas by age 30 (Surette, 2014; Davies, 2002; Murray et al., 2007; Marshall et al., 2016). Despite the aggressive use of antibiotics, P. aeruginosa infections in CF are difficult to clear and almost always become chronic (Davies, 2002; Murray et al., 2007). 1.1.2 An arsenal of virulence factors P. aeruginosa possesses numerous virulence factors that enable the bacterium to colonize and invade its host. Alkaline protease and heme acquisition factor are secreted by type I secretion systems (T1SS); the two type II secretion systems (T2SS) (Xcp and Hxc) secrete a variety of toxins, and hydrolytic enzymes including proteases, lipases, phospholipases, and alkaline phosphatases, etc.; the T3SS injects the four strain-dependent toxins ExoS, ExoT, ExoU and ExoY directly into the eukaryotic cell; the type V secretion system (T5SS) secretes a few lipases and proteases that each have an autotransporter domain for their own individual secretion; and the type VI secretion systems (T6SS) are thought to be more involved in interspecies competition (Filloux, 2 2011), although they can also function to inhibit eukaryotic cell function (Berni et al., 2019). In addition to secretion systems, P. aeruginosa also employs extracellular appendages for both motility and attachment, allowing for dissemination and virulence in the host. These include a single polar flagellum per cell (a long, flexible filament that rotates to propel the bacterium), multiple pili (contractile rods that are major adherence factors and drag the cell over surfaces in a process termed twitching) and several other adherence factors that aid in colonization and biofilm formation. Biofilms are surface-associated aggregates of bacteria held together by an extracellular matrix comprised of polysaccharides, proteins and DNA. They represent a complex adaptive growth state, are associated with major transcriptional reprogramming, and are adaptively resistant (10- to 1000-fold) to multiple antibiotics (Jefferson, 2004). Biofilms are the major cause of infections (65%) and are associated with chronic infections throughout the body and on implanted medical devices and prosthetics. QS systems also play a role in bacterial virulence. P. aeruginosa synthesizes the auto-inducer molecules N-butanoyl-L-homoserine lactone (C4-HSL) and N-(3-oxododecanoyl)-L-homoserine lactone (3-O-C12), and the quinolones 4-hydroxy-2-alkylquinoline (HAQ), 4-hydroxy-2-heptylquinoline (HHQ) and 2-heptyl-3,4-dihydroxyquinoline (PQS) (Kim et al., 2010). As bacterial density increases, the levels of these auto-inducers build, so that they can be used to sense the surrounding population. Each auto-inducer binds to a global transcriptional regulator (RhlR, LasR or PqsR/MvfR), so that specific programs can be initiated once sufficient density (and concentration of autoinducer) is reached. The QS systems are interconnected with LasR at the top of the hierarchy (Lee & Zhang, 2014). In order to survive in vivo, bacteria must also be able to extract iron, which is tightly sequestered by the host. P. aeruginosa produces several siderophores for this purpose, including pyoverdine and pyochelin. Its genome also encodes receptors to reuptake the siderophores once they have bound iron. The siderophore pyoverdine and the phenazine pyocyanin give Pseudomonas cultures their distinctive blue-green colour. In addition, pyocyanin and pyochelin also have redox activity and can modulate host functions including cilia movement (Britigan et al., 1992; Kanthakumar et al., 1993). Once bacteria establish an infection, they are able to form a biofilm to enable them to persist in the host and resist antimicrobial treatment. Adherence factors such as the type IV pili and flagella are involved in surface sensing and initial attachment. P. aeruginosa produces three exopolysaccharides that aid in biofilm formation and protection from the host, pel, psl and alginate, 3 and the latter two are the major components of biofilm matrix in this organism. Additionally, P. aeruginosa also synthesizes lipopolysaccharide (LPS), which forms the outer monolayer of the outer membrane, is a major antigen, and through the membrane-proximal lipid A portion can elicit a strong inflammatory response in the host by interacting with Toll-like receptor 4. 1.1.3 Progression of chronic CF lung infections CF is an autosomal recessive genetic disease resulting from mutations in the CF transmembrane conductance regulator (CFTR) gene (Bhagirath et al., 2016). CFTR is an important protein involved in both ion transport and signaling, and mutations in CFTR cause the accumulation of thick mucus in the lung, and also affect other organs such as the pancreas (Bhagirath et al., 2016). The CF lung is susceptible to polymicrobial infection and patients continually struggle in this regard. CF epithelial cells have decreased phagocytosis of P. aeruginosa, and the thick mucus impairs ciliary beating (Bhagirath et al., 2016). Infections with P. aeruginosa are especially concerning since progression of P. aeruginosa infections is associated with poor patient outcomes and disease severity (Lee et al., 2003; Sanders, 2014). The presence of P. aeruginosa is associated with increased morbidity: the risk of death was 2.6 times higher in those infected with P. aeruginosa than those without (Bhagirath et al., 2016). Research has shown that as P. aeruginosa lung infections progress over time, clinical isolates in chronic, cf. acute, infections tend to lose motility and lipopolysaccharide O-antigen as well as certain virulence factors such as type III secretion system (T3SS) and quorum sensing (QS), while overproducing the polysaccharide alginate and undergoing hypermutation (Figure 1-1) (Hancock et al., 1983; Winstanley et al., 2016). Overall, in chronic infections bacteria become more senescent, evade the immune system and resist antibiotic treatment (Bhagirath et al., 2016); whereas motility is thought to be more important for initial colonization in acute infections and is associated with the production of virulence factors (Overhage et al., 2008). Eventually, the P. aeruginosa bacterial burden increases to a point of no return and biofilm formation genes are expressed while the host produces antibodies against P. aeruginosa and more polymorphonuclear leukocytes are recruited (Bhagirath et al., 2016). Chronic inflammation eventually leads to irreversible loss of lung function (Bhagirath et al., 2016). Current therapies for CF largely rely on antibiotic treatment, which is ineffective in the long term due to mechanisms of antibiotic resistance. Other therapies also include oxygen therapy, bronchodilation, airway clearance, anti-inflammatory medication and CFTR modulation (Bhagirath et al., 2016). Gene therapies are being developed but thus far showed little efficacy in 4 clinical trials (Yan et al., 2019). Life expectancy of CF patients has increased over the years and is about 40-50 years, depending on factors such as location, sex and CFTR genotype (Keogh et al., 2018; Stephenson et al., 2018). Figure 1-1. Characteristic features of the progression from acute (left) to chronic (right) lung infections. EPS, extracellular polymeric substance. 1.2 Bacterial motility Motility is a critical behaviour for many bacteria, such as P. aeruginosa, as a means to seek out and rapidly colonize new niches, both in the environment and in vivo. Motility takes on many different forms, and can be observed at both macroscopic (Figure 1-2) and microscopic levels. 1.2.1 Swarming motility Swarming motility is a complex and multicellular adaptation used for surface translocation. Many rod-shaped bacteria such as Bacillus, Escherichia coli, Salmonella, Serratia, Proteus mirabilis, Vibrio and Pseudomonas can swarm, as can the spiral-shaped Rhodospirillum (Kearns, 2010). General features of swarming motility include a requirement for flagella, production of a surfactant and elongation of the cells undergoing swarming. These features vary from species to species, since some species are peritrichously flagellated; whereas P. aeruginosa can aquire an extra polar flagellum (Kearns, 2010). The degree of cellular elongation also varies, as well as the specific surfactant produced. Soft agar, representing decreased medium viscosity (compared to 5 standard solid plates with 1.5 or 2% agar), is usually required for swarming, although some species, such as P. mirabilis and Vibrio parahaemolyticus, can swarm even on hard agar (Verstraeten et al., 2008). Lastly, the macroscopic pattern produced by swarming colonies varies considerably depending on the strain and ranges from dendritic to terraced to circular or vortex-shaped (Kearns, 2010). Figure 1-2. Different forms of motility in P. aeruginosa. In P. aeruginosa, swarming occurs on lower-viscosity surfaces (0.4-0.7% agar) with amino acids as the nitrogen source. Interestingly, ammonium as a nitrogen source inhibits swarming in P. aeruginosa. It is a collective (so-called social) behaviour and cells inoculated onto a swarming plate can take at least several hours to build up sufficient density to initiate swarming, depending on the medium and inoculum. Prior to tendril formation, a clear layer can be seen expanding from the colony, representing the surfactant rhamnolipid (product of rhlABC), which is used to help the bacteria spread. Once swarming initiates, bacteria raft together and move rapidly, propelling the swarm front forward. On a macroscopic level, tendrils bud from the central colony, branching occasionally, and can fill a 10 cm dish overnight. Tendrils commonly avoid touching one another, a phenomenon known as contact inhibition that is mediated in part by rhamnolipids (Caiazza et al., 2016). Pattern formation is strain-dependent, with PA14 typically forming large, well-separated tendrils, and PAO1 forming solar flare patterns, or thinner, closely-spaced tendrils, depending on the medium. In P. aeruginosa, swarming is unusual in that it relies on both flagella and type IV pili (Köhler et al., 2000). Mutants in pili and related genes have deficiencies in swarming motility (Köhler et al., 2000; Yeung et al., 2009), although the basis for this is unclear. It is possible that the pilus is involved in surface sensing (Köhler et al., 2000), or possibly in intercellular rafting 6 and/or branching (Anyan et al., 2014). Swarming in P. aeruginosa is dependent on QS, with mutants in rhlIR being completely deficient for swarming, and mutants in lasIR showing partial reductions in swarming (Köhler et al., 2000). RhlR and LasR are global transcriptional regulators, and in addition to rhlABC and lasAB regulate many other virulence factors and biofilm formation (Medina et al., 2003; Mukherjee et al., 2017; Ueda et al., 2009). A screen of the strain PA14 transposon insertion mutant library (Liberati et al., 2006) revealed 233 mutants with altered swarming, including 35 mutants in transcriptional regulators (Yeung et al., 2009). Of the 233 mutants, only 4 were hyperswarmers; the rest had either complete or partial defects in swarming motility (Yeung et al., 2009). 1.2.2 Other forms of motility Unlike most other forms of motility, swimming is not associated with surfaces but rather occurs in liquid or low viscosity (e.g. 0.25-0.3% agar) environments. Bacteria use the flagellum and chemotactic machinery to move toward attractants or away from repellants. A widespread paradigm in E. coli is that rotation of the flagellum is occasionally reversed, causing the bacterium to tumble and allowing for reorientation (run-and-tumble). However, given that P. aeruginosa usually only has a single polar flagellum, cells reorient during a “pause” phase, or a “run-reverse-turn” paradigm by Brownian motion, and the polar flagellum spends equal time in the clockwise and counterclockwise phases (Qian et al., 2013). The pause phase allows time for the cells to turn, and pause duration is positively correlated with angle size (Qian et al., 2013). Free-swimming cells can exhibit different trajectories, including helical behaviour, which is rare in bacteria (Vater et al., 2014). Twitching motility occurs on surfaces or at interfaces such as between a layer of agar and a Petri dish. Extension and retraction of the type IV pilus allows the cell to slowly drag itself forward. Interestingly, like swarming, twitching cells also form rafts that migrate en masse and form concentric rings (Semmler et al., 1999), suggesting that these two forms of motility may share some commonalities. Bacteria are normally oriented horizontal to the surface, but interestingly the type IV pilus can also mediate “walking motility,” where the cells can be seen moving in an upright vertical position (Conrad et al., 2011). Surfing motility is another complex adaptive surface motility unique in its dependence on the presence of surface-wetting agents such as mucin (Yeung et al., 2012). It is also dependent on the presence of flagella, QS systems, and confers adaptive resistance to multiple antibiotics (Yeung et al., 2012; Sun et al., 2018a). Multiple studies have shown it to be largely distinct from swarming 7 both in transcriptional changes and genes required for surfing (Sun et al., 2018a; Sun et al., 2019; Yeung et al., 2012). Surfing motility was demonstrated in species other than P. aeruginosa although the dependence on QS varied in different species (Sun et al., 2018b). Sliding motility is a passive surface motility that relies on colony expansion and surfactant production to propagate cells across a surface (Murray & Kazmierczak, 2008). Neither flagella nor type IV pili are required for this motility, in fact the presence of pili inhibits sliding motility, suggesting that cellular appendages can, under certain circumstances, create drag and slow down motility (Murray & Kazmierczak, 2008). 1.3 Antibiotic resistance Antibiotic resistance is a growing global threat to public health. Bacterial populations are highly capable of acquiring drug resistance over time due to a number of different factors. First, their short generation time enables resistant subpopulations to rapidly dominate in the face of selective pressure (such as treatment of patients with antibiotics). Second, bacteria possess multiple systems for the uptake and exchange of foreign DNA, such as conjugation and transduction. Third, free-living bacteria are extremely versatile and can respond to different environmental stresses with massive changes in gene expression leading to adaptive resistance. All of these factors combined with the overuse of antibiotics, particularly as a growth-promoting agent in livestock, and the lack of development of new drug classes, has led to a crisis whereby simple infections are now once again life-threatening in the case of multidrug-resistant (MDR) bacteria. The Centre for Disease Control and Prevention declared in 2013 that we are now in a “post-antibiotic era” (Ventola, 2015). P. aeruginosa, specifically, is on the World Health Organization’s list for critical development of new antibiotics (WHO, 2017), and 13% of P. aeruginosa infections in 2014 were MDR (Ventola, 2015). It is therefore critical to learn more about antibiotic resistance as well as develop new antimicrobial drugs. 1.3.1 Mechanism of resistance to specific antibiotics Two mechanisms that confer resistance to multiple antibiotic classes are multidrug efflux and decreased membrane permeability. P. aeruginosa possesses a suite of multidrug efflux pumps that export from the cell many small molecules (often with diverse chemical natures and including multiple antibiotic classes and other toxic chemicals). P. aeruginosa is also known for its low outer membrane permeability, which is 12-100 times less than that of E. coli (Breidenstein et al., 2011; Fernández & Hancock, 2012). Many antibiotics target the bacterial ribosome, including aminoglycosides, tetracycline, 8 macrolides and chloramphenicol. Chloramphenicol inhibits peptidyl transferase activity; macrolides bind to 23S RNA; tetracyclines inhibit binding of aminoacyl-transfer (t)RNA to the bacterial ribosomal A-site; and aminoglycosides bind to the 30S subunit causing mismatches (Lambert, 2012). Specific mechanisms of resistance to ribosome-targeting antibiotics include plasmid-borne or chromosomal enzymes that modify aminoglycosides by adenylation, phosphorylation or acetylation (Walsh & Wencewicz, 2016). The bacterial ribosome may also be modified either by mutation or methylation of rRNA to reduce affinity to antibiotics (Walsh & Wencewicz, 2016). β-lactams target the cell wall, specifically peptidoglycan (PG) synthesis. β-lactams possess a reactive four-member ring that inhibits transpeptidation. A common mechanism of resistance to β-lactams is the production of β-lactamases, enzymes that inactivate the antibiotic. Penicillin binding proteins including transpeptidases can also be mutated or replaced by drug-insensitive forms (Walsh & Wencewicz, 2016). Fluoroquinolones, such as ciprofloxacin or norfloxacin, target DNA gyrase and topoisomerase IV, enzymes that regulate the supercoiled state of DNA (Redgrave et al., 2014). Besides efflux, bacteria commonly become resistant to fluoroquinolones as a result of point mutations in topoisomerases that decrease the fluoroquinolone-binding affinity of the target protein (Redgrave et al., 2014). Trimethoprim inhibits dihydrofolate reductase, depleting the cell of tetrahydrofolate, a one-carbon donor for a number of important metabolites in the cell including the nucleotide thymidylate (Sangurdekar et al., 2011). Structural gene mutations (i.e. in dihydrofolate reductase) are a common mechanism of trimethoprim resistance (Walsh & Wencewicz, 2016). Polymyxin B is a nonribosomal lipopeptide with positive charge. It binds to the negatively charged LPS and disrupts the bacterial outer membrane although its specific mechanism against cells has not been clearly demonstrated (Breidenstein et al., 2011). Mechanisms of resistance include modification of LPS to a less negative form by addition of 4-amino-4-deoxyarabinose or phosphatidylethanolamine (Walsh & Wencewicz, 2016). In P. aeruginosa, the arnBCADTEF operon is involved in aminoarabinosylation of LPS and is regulated by several different two-component systems, including PhoPQ, PmrAB, ParRS and CprRS (Barrow & Kwon, 2009; Fernández et al., 2010, 2012). The arnBCADTEF operon also confers resistance to cationic peptides and aminoglycosides (Breidenstein et al., 2011). 9 1.3.2 Acquired resistance Antibiotic resistance can be acquired either horizontally or vertically. Resistance genes acquired vertically (mutationally) may emerge slowly, but the existence of hypermutator strains can speed the process (Breidenstein et al., 2011). In contrast, horizontal acquisition is rapid and can occur by diverse means, including conjugation, transduction, or transformation. Mobile DNA elements include plasmids, transposons, integrons, prophages and resistance islands (Breidenstein et al., 2011). 1.3.3 Adaptive resistance Environmental conditions, specific growth states and/or antibiotics or other stresses can reversibly induce the differential expression of many genes, leading to adaptive antibiotic resistance. Conditions known to induce adaptive resistance include anaerobiosis, altered pH or temperature, low concentrations of divalent cations, and subinhibitory concentrations of antibiotics or other toxic compounds (Breidenstein et al., 2011; Fernández et al., 2010). Additionally, adaptive resistance also results from defined growth states such as biofilm formation and swarming and surfing motility. When the conditions that trigger adaptive resistance no longer exist, bacteria revert to a susceptible state. 1.3.4 Antibiotics used to treat P. aeruginosa infections Clinically relevant antibiotic classes for P. aeruginosa infections include amnioglycosides, β-lactams, fluoroquinolones and lipopeptides (Tümmler, 2019). Some of the more toxic drugs such as polymyxin B and colistin are reserved for last resort (Tümmler, 2019). Two antibiotics from different classes are often prescribed for severe cases, such as piperacillin or ceftazidime and an aminoglycoside (Tümmler, 2019). To overcome β-lactam resistance, cephalosporin-β-lactamase inhibitor combinations are sometimes used, such as ceftazidime-avibactam and ceftolozane-tazobactam (Tümmler, 2019). For CF infections, aerosolized antibiotics may be used, such as tobramycin, colistin, liposomal amikacin, or liposomal ciprofloxacin (Tümmler, 2019). Drugs such as ciprofloxacin, meropenem, tobramycin, gentamicin and amikacin can be encapsulated into liposomes or loaded into nanoparticles in order to improve penetration of antimicrobials in burn wounds or chronic lung infections (Tümmler, 2019). The macrolide azithromycin has also proved useful in treating chronic lung infections, and even helps to reduce neutrophilic inflammation and improve lung function (Bhagirath et al., 2016; Tümmler, 2019). 1.4 Small RNAs In bacteria, small inhibitory RNAs (sRNA) are short (40-500 bp) untranslated sequences 10 that are distinct from other forms of RNA such as mRNA, tRNA and rRNA. The purpose of sRNAs is to provide post-transcriptional regulation in order to alter protein abundance as needed. sRNAs may be intergenic or overlapping with other genes. In addition, sRNAs are also characterized as cis or trans. Cis-encoded sRNAs overlap with their target mRNA and have high sequence similarity; whereas trans-encoded sRNAs are encoded distant from their targets and utilize imperfect base-pairing (Li et al., 2012). 1.4.1 Mechanisms of regulation by sRNAs There are several different ways that sRNAs can regulate a target. First, sRNAs can bind to mRNAs and block the ribosome binding site, leading to inhibition of translation (Waters & Storz, 2009). Second, sRNAs can bind to a different region of the mRNA, causing unmasking of the ribosome binding site, leading to increased translation (Li et al., 2012; Storz et al., 2004). Third, sRNAs can interact directly with proteins in order to sequester or alter their activity (Gottesman & Storz, 2011; Li et al., 2012; Pita et al., 2018). Last, sRNA binding to an mRNA can also initiate degradation of the mRNA, or alternatively stabilize mRNA (Pita et al., 2018; Prévost et al., 2011). sRNA-mRNA interactions often require the chaperone Hfq for stabilization (Gottesman & Storz, 2011). Additionally, Pseudomonas possesses other more selective RNA-binding proteins such as RsmA and Crc. 1.4.2 Known sRNAs in P. aeruginosa The global transcriptional regulator GacA, part of the two-component system GacAS, induces the expression of two sRNAs, rsmY and rsmZ (Figure 1-3) (Pita et al., 2018). rsmY and rsmZ, in turn, sequester the post-transcriptional regulator RsmA from its target mRNA (Janssen et al., 2018; Pita et al., 2018). RsmA has diverse downstream effects, since it directly inhibits the translation of regulons involved in chronic infection, including T6SS, QS, biofilm formation and iron homeostasis; whereas it indirectly and positively regulates genes involved in acute lifestyles, such as T3SS, type IV pili, and virulence programs regulated by Vfr (Pita et al., 2018). Interestingly, rsmY and rsmZ can be indirectly regulated by alternative regulators such as HptB, AlgR and BfiSR; whereas the polynucleotide phosphorylase PNPase directly regulates rsmY and rsmZ by increasing their stability (Pita et al., 2018). The two tandem and highly homologous prrF sRNAs, prrF1 and prrF2, are involved in iron homeostasis and virulence in vivo, and use the RNA-binding protein Hfq (Djapgne et al., 2018; Pita et al., 2018; Wilderman et al., 2004). The entire region can also be transcribed as a whole, referred to as prrH (Djapgne et al., 2018; Pita et al., 2018). In iron-replete conditions, the 11 repressor Fur binds iron and represses prrH; whereas prrH represses or spares the use of iron under iron-limiting conditions (Pita et al., 2018). Interestingly, prrH also represses the expression of AntR, a positive regulator of genes that convert anthranilate into catechol (Djapgne et al., 2018; Pita et al., 2018). When AntR is repressed, then anthranilate is instead channeled into the PQS system, resulting in the increased expression of virulence factors (Pita et al., 2018). The sRNA crcZ competes with prrH for binding to Hfq, and can act as a sponge to sequester Hfq, since crcZ has a higher affinity for Hfq than does prrH (Pita et al., 2018; Sonnleitner et al., 2017). Figure 1-3. Known sRNAs and their involvement in the regulation of virulence factors. Reproduced from reference (Pita et al., 2018), this figure is licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). The crcZ sRNA is expressed under the control of the global two-component regulatory CbrAB system (Sonnleitner et al., 2009), involved in carbon and nitrogen metabolism, antibiotic resistance and virulence (Yeung et al., 2011). Initially, crcZ was thought to bind to Crc to influence carbon catabolite repression (Sonnleitner et al., 2009), but a subsequent study showed that Crc had no RNA binding activity, whereas crcZ bound to Hfq with high affinity (Sonnleitner & Bläsi, 2014). Instead, Crc acts in concert with Hfq by stabilizing Hfq-RNA interactions by a mechanism that is not currently fully understood (Kavita et al., 2018). The sRNA phrS activates PqsR and downstream QS pathways by an unusual mechanism (Sonnleitner et al., 2011). The pqsR mRNA has secondary structure that restricts translation to a moderate level under aerobic conditions (Sonnleitner et al., 2011). Under anaerobic conditions, an 12 oxygen-responsive regulator Anr is activated and increases levels of phrS. Then phrS binds to pqsR mRNA, and its secondary structure is rearranged, enhancing transcription from an upstream open reading frame which contributes to increased translation of pqsR (Sonnleitner et al., 2011). In turn, this leads to increased levels of PQS and pyocyanin (Sonnleitner et al., 2011). Interestingly, phrS was recently identified as a regulator of the CRISPR-Cas system (Lin et al., 2019). The ersA sRNA is Hfq-dependent and involved in envelope stress response, repressing translation of the bifunctional enzyme AlgC (Pita et al., 2018). AlgC is involved in the synthesis of polysaccharides including alginate, psl, pel, LPS and rhamnolipids (Pita et al., 2018). The porin OprD, involved in the uptake of peptides and carbapenems, is also repressed by ersA, leading to an additional role in antibiotic resistance (Pita et al., 2018). The sRNA nrsZ is induced upon nitrogen-limitation by the two-component system NtrBC in concert with RpoN (Wenner et al., 2014). Subsequently nrsZ post-transcriptionally activates RhlA, which is required for rhamnolipid production (Wenner et al., 2014). A mutant in nrsZ was unable to produce rhamnolipids or swarm (Wenner et al., 2014). This is interesting since nitrogen limitation is a feature known to enhance swarming motility in P. aeruginosa (Köhler et al., 2000). In contrast, a deletion mutant in the sRNA rgsA led to an increase in swarming motility (Lu et al., 2016). It was found that rgsA directly regulates the global transcriptional regulator Fis and the acyl carrier protein AcpP (Lu et al., 2016). This sRNA is under direct control of RpoS, and indirect control of GacAS (Lu et al., 2016); however, rgsA also negatively regulates RpoS in an intricate regulatory loop (Lu et al., 2018). Other recently characterized sRNAs include srbA, reaL, pesA and phrD. sRNA srbA is involved in biofilm formation and pathogenicity in a C. elegans infection model (Taylor et al., 2017). sRNA reaL is involved in pathogenicity in a Galleria mellonella infection model and links the Las and PQS QS systems (Pita et al., 2018). Interestingly, reaL also negatively regulates swarming motility and influences biofilm formation and pyocyanin production (Carloni et al., 2017). sRNA pesA is encoded on a pathogenicity island and present in strain PA14 but not PAO1 (Pita et al., 2018), and involved in pathogenicity against CF bronchial cells and also in regulating the expression of S-type pyocins (Pita et al., 2018). sRNA phrD was shown to positively influence the QS regulator RhlR (Malgaonkar & Nair, 2019). Overexpression of phrD results in increased production of rhamnolipids and pyocyanin (Malgaonkar & Nair, 2019). 1.4.3 Uncharacterized sRNAs in P. aeruginosa Several studies have investigated the transcription of sRNAs on a genome-wide scale in P. 13 aeruginosa. A study in 2012 on strain PAO1 identified more than 500 novel intergenic sRNAs (Gómez-Lozano et al., 2012). Strain PA14 was also studied, revealing 165 intergenic sRNAs as well as 380 cis-antisense RNAs (Wurtzel et al., 2012). In another study, the expression of 31 intergenic sRNAs was confirmed by qRT-PCR and expression was shown to be differential during swarming and/or biofilm formation (Gill et al., 2018). Another 2012 study looked for sRNAs in strains PA14 and PAO1, identifying 150 novel sRNA candidates, and validating expression of 52 sRNAs by Northern blot (Ferrara et al., 2012). Of these, 13 sRNAs showed strain specificity, with 11 unique to PA14 and 2 unique to PAO1 (Ferrara et al., 2012). This supports the idea that sRNAs are rapidly evolving (Gómez-Lozano et al., 2015). Lastly, a study in 2014 identified 232 antisense RNAs, and comparison of their results with two other studies revealed little overlap, suggesting that expression of some sRNAs may be strongly dependent on specific conditions (Gómez-Lozano et al., 2014). Hundreds of sRNAs have therefore been identified and await further characterization. This represents a large field awaiting further exploration. 1.5 Hypothesis and Objectives I hypothesize that swarming motility is a complex adaptation regulated by sRNAs that is coupled to antibiotic resistance and virulence in acute in vivo infections. 1.5.1 Objectives 1. Investigate the antibiotic resistance of swarming cells by determining wild type (WT) susceptibility to different antibiotics under swarming conditions, as well as screening selected mutants to uncover mechanistic detail. a. Approach: The antibiotic susceptibility of PA14 WT was compared between three growth conditions: swimming, swarming and spread plates using the disc diffusion assay with various antibiotics. Next, resistome mutants in genes dysregulated under swarming conditions (from RNA-Seq and qRT-PCR data) were screened for differential susceptibility vs. WT under swarming conditions. I expected that PA14 would be more resistant under swarming conditions to at least some antibiotics, and that specific mutants would reveal the underlying mechanism(s) behind this phenomenon. 2. Examine the role of sRNA species in the regulation of swarming motility by creating overexpression strains and screening for relevant phenotypes. a. Approach: Fifteen sRNA species dysregulated under swarming conditions (Gill et al., 2018) were cloned and overexpressed in PAO1 WT and screened in relevant assays such 14 as motility, adherence and cytotoxicity. Two sRNAs with interesting phenotypes in the overexpression strains were selected to identify targets by RNA-Seq and proteomics, make deletion mutants and study in further detail. 3. Study the interconnection of swarming motility with other behaviours such as biofilm formation, other forms of motility, and cytotoxicity to discover a swarming-specific mutant to enable investigation of the role of swarming in vivo. a. Approach: Previously identified swarming-deficient mutants (Yeung et al., 2009) were screened for swimming, twitching, biofilm formation, cytotoxicity and growth. The mutant with minimal effects on phenotypes other than swarming was selected to test in an acute in vivo mouse model and was expected to show reduced virulence. 15 Chapter 2: Materials and Methods 2.1 Bacterial strains and growth conditions P. aeruginosa strains UCBPP-PA14 and PAO1 H103 and transposon mutants from the PA14 Harvard library (Liberati et al., 2006) were routinely grown in Luria-Bertani broth (LB) and BM2 minimal medium (62 mM potassium phosphate buffer, pH 7, 0.5 mM MgSO4, 10 μM FeSO4, carbon and nitrogen sources as indicated). The deletion mutant ∆prrH (∆prrF1-2) was obtained from reference (Wilderman et al., 2004). Gentamicin at 30 μg/ml was included in streak plates for PA14 transposon mutants. LB overnight cultures were diluted 1/50 and grown to mid-log phase (OD600nm of 0.3 to 0.6) to initiate motility studies. 2.1.1 Growth curves Overnight cultures were diluted to a final OD600nm of 0.05 in the indicated medium and seeded in 96 well round-bottom plates at 100 μl/well. They were incubated at 37°C with shaking at frequency 567 cpm (3 mm) in the synergy H1 microplate reader and the OD600nm was read every 30 min. Media recipes used were: 1. Synthetic cystic fibrosis sputum media (SCFM) without NH4Cl modified from (Palmer et al., 2007) as follows: 1.3 mM NaH2PO4, 1.25 mM Na2HPO4, 0.348 mM KNO3, 1.114 g/L KCl, 3.03 g/L NaCl, 10 mM MOPS, 0.827 mM L-aspartate, 1.072 mM L-threonine, 1.446 mM L-serine, 1.549 mM L-glutamate HCl, 1.661 mM L-proline, 1.203 mM L-glycine, 1.78 mM L-alanine, 0.16 mM L-cysteine HCl, 1.117 mM L-valine, 0.633 mM L-methionine, 1.12 mM L-isoleucine, 1.609 mM L-leucine, 0.802 mM L-tyrosine, 0.53 mM L-phenylalanine, 0.676 mM L-ornithine HCl, 2.128 mM L-lysine, 0.519 mM L-histidine, 0.013 mM L-tryptophan, 0.306 mM L-arginine, 1.754 mM CaCl2, 0.606 mM MgCl2, 3.6 μM FeSO4, 3 mM D-glucose, 9.3 mM L-lactate (sodium lactate). 2. RPMI supplemented with 5% Mueller-Hinton Broth. 3. BM2 glycerol (no (NH4)2SO4, 0.4% glycerol (wt/vol), 0.1% Casamino acids (CAA) (wt/vol), and 1% arabinose (wt/vol)). 4. BM2 glucose (no (NH4)2SO4, 0.4% glucose (wt/vol), 0.1% CAA (wt/vol)). 5. LB. 2.2 Motility assays For direct comparisons between swarming, swimming and spread plate conditions, all plates were composed of the same medium, excepting agar concentration. All plates were stab 16 (swim and twitch) or spot (swarm) inoculated with 1.5 μl of mid-log phase bacteria, except for spread plates, which were spread with 106 cfu per plate (final OD600nm 1.3 x 10-3). Bacteria were always inoculated at the same distance from the disc or another spot inoculum by using a stencil pattern drawn on the bottom of all plates. After inoculation, plates were incubated 15-20 h at 37°C and imaged on the ChemiDoc™ Touch Imaging System (Biorad). 2.2.1 Swarming Swarming was generally assayed on BM2 with 0.4% glucose, 0.1% CAA and 0.5% agar (wt/vol), unless otherwise indicated. For strains overexpressing sRNAs on the plasmid pHERD20T, 0.4% glycerol was often substituted as the carbon source (unless otherwise indicated), since glucose represses expression from the PBAD promoter (Qiu et al., 2008). Plates were poured to contain 25 ml medium each, and solidified and dried for 1 h prior to use. 2.2.2 Swimming Swimming was generally assayed in BM2 glucose with 0.25 or 0.3% agar (wt/vol), using 0.4% glucose and 0.1% CAA as the nitrogen source for direct comparisons with swarming (as indicated). For strains overexpressing sRNAs on the plasmid pHERD20T, 20 mM potassium succinate pH 7.0 was substituted as the carbon source and 7 mM (NH4)2SO4 as the nitrogen source (unless otherwise indicated). Plates were poured to contain 25 ml medium each, and solidified for 1 h prior to use. 2.2.3 Twitching Twitching plates were composed of 10 ml of LB with 1% agar and dried overnight. Bacteria were stab inoculated to the bottom of the plate, incubated overnight at 37°C, and one extra day at room temperature before visualization on the ChemiDoc™ Touch Imaging System (Biorad). 2.2.4 Disc diffusion assay Discs were impregnated with the amount of antibiotic indicated in Table 2-1 and allowed to dry briefly before being placed in the centre of a BM2 glucose agar plate with 0.3, 0.4, 0.5 or 1.5% agar. For swarming and swimming, bacteria were spot inoculated at a distance of 19 mm from the edge of the disc; for the 1.5% agar plates, bacteria (106 cfu) were spread onto the surface of the plate prior to adding the disc. After overnight incubation, the zone of inhibition, representing the closest distance between the edge of the disc and visible bacterial growth, was measured using a ruler. Statistically significant differences were determined by ANOVA using GraphPad Prism. Table 2-1. Amount of antibiotic used in the disc diffusion assay. Antibiotic Amount (μg) Amikacin 125 17 Antibiotic Amount (μg) Azithromycin 300 Chloramphenicol 300 Ciprofloxacin 1 Erythromycin 4000 Gentamicin 80 Meropenem 0.7 Piperacillin 32 Polymyxin B 400 Tetracycline 80 Tobramycin 80 Trimethoprim 250 2.2.5 Agar dilution assay Antibiotics were incorporated into BM2 swarming agar (0.5% agar) at varying concentrations. After overnight incubation, the minimal concentration that completely inhibited swarming tendril formation was reported as the swarming inhibitory concentration (IC). 2.2.6 Six well plate assays Motility assays performed using 10 cm dishes were modified to a six well format for Figure 6-1 with the following specifications: swarming (BM2 glucose, 0.1% CAA, 0.5% agar at 4 ml/well), swimming (BM2 glucose, 7 mM (NH4)2SO4, 0.25% agar at 4 ml/well) and twitching (LB, 1% agar at 1.5 ml/well). 2.3 Other phenotypic assays 2.3.1 Biofilm formation Overnight cultures were diluted 1/100 in ¼ LB (5 g/L) and seeded at 100 μl/well in 96 well polystyrene round-bottom plates. After incubating for 24 h at 37°C, the media was discarded and plates were rinsed three times with dH2O. Crystal violet (105 μl of 0.1%) was added and incubated with shaking for 20 min at room temperature, then the plates were rinsed three times with dH2O and the crystal violet was solubilized by adding 110 μl 70% (vol/vol) ethanol and shaking for 20 min at room temperature. Then the absorbance at 595 nm was read in an Epoch plate reader (BioTek). 2.3.2 Adherence Overnight cultures were diluted to a final OD600nm of 0.03 in 90% LB supplemented with 5% arabinose (wt/vol) and seeded at 100 μl/well in 96 well flat-bottom polystyrene plates. After incubating for 4 h at 37°C, unattached cells were removed by discarding the media and rinsing three times with dH2O. Crystal violet (105 μl of 0.1%) was added and incubated with shaking for 18 20 min at room temperature, then the plates were rinsed three times with dH2O and the crystal violet was solubilized by adding 110 μl 70% (vol/vol) ethanol and shaking for 20 min at room temperature. Then the absorbance at 595 nm was read in an Epoch plate reader (BioTek). 2.3.3 Cytotoxicity Human bronchial epithelial 16HBE14o- cells (HBE) between passage 14 and 40 were grown in Minimum Essential Medium with Earle’s Salts (1X) (MEM) (Gibco) supplemented with 10% fetal bovine serum (FBS) (Gibco), 2 mM L-glutamine (Gibco) and 1% penicillin-streptomycin (Gibco). After cells reached 80-100% confluency, they were washed once with phosphate buffered saline pH 7.4 (1X) (PBS) (Gibco), trypsinized with 0.25% Trypsin-EDTA (Gibco) and diluted in medium before counting. HBE were seeded at 2 x 104 cells/well at 200 μl/well in a 96 well plate and grown again to confluency (2-3 days). Then the medium was changed to MEM or DMEM (Gibco), as indicated in Table 2-2, 1-2 h prior to infection. Next, bacterial cultures were prepared by pelleting overnight cultures, washing once with PBS and resuspending in the medium indicated in Table 2-2. Bacteria were diluted in the same medium. Next, the medium of the HBEs was removed and replaced with a suspension containing the bacterial inoculum described in Table 2-2. The coculture was incubated at 37°C with 5% CO2 for the amount of time indicated in Table 2-2, followed by monitoring the release of lactate dehydrogenase (LDH) as an indicator of cytotoxicity as described below. Cells treated with 2% Triton®-X-100 (vol/vol) (Fisher Scientific) in the respective media were used as a positive control for the LDH assay. Table 2-2. Parameters for cocultures optimized for the PA14 and PAO1 strains. Strain Medium Inoculum (cfu/ml) MOI Time (h) PA14 MEM, 1% FBS, 2 mM L-glutamine 7.5 x 105 7.5 4 PAO1 DMEM, no glucose, 1% FBS, 1% sodium pyruvate, ± 1% arabinose 3 x 105 3 16 Plates were centrifuged for 5 min at 1000 rpm in the Eppendorf centrifuge 5810 R (15 amp version) and 50 μl supernatant were removed and mixed with 50 μl solution as indicated in the Cytotoxicity Detection Kit (Roche) assessing release of LDH (1/100 catalyst/reaction mixture), and incubated for 10 min at room temperature in the dark. Then the absorbance at 492 and 900 nm was read in the Epoch plate reader (BioTek). Next, the absorbance at 900 nm was subtracted from the absorbance at 492 nm. % cytotoxicity was calculated by subtracting bacteria and HBE alone controls from coculture values, and then normalizing to the Triton-X control. 19 2.3.4 Outer membrane permeabilization assay Outer membrane permeability was assessed using the fluorescent dye N-phenyl-1-naphthylamine (NPN) as described previously (Schurek et al., 2008) with minor modifications. Briefly, cells were harvested from antibiotic-free BM2 glucose swarm plates (0.5% agar) and resuspended in 5 mM HEPES pH 7.0 supplemented with 5 μM carbonyl cyanide m-chlorophenyl hydrazone, then diluted to an OD600nm of 0.5. Fluorescence was monitored in the PerkinElmer Fluorescence Spectrometer LS 55 at an excitation wavelength of 350 nm and emission wavelength of 420 nm. NPN was added at a final concentration of 10 μM, then tobramycin was added at a final concentration of 40 μg/ml. 2.3.5 Pyoverdine assay Bacteria were grown overnight in Casamino acid medium (0.5% CAA, 0.1 mM MgSO4, 7 mM potassium phosphate buffer, pH 7.0). Turbid cultures were pelleted and the supernatant collected in a fresh tube. Next, 5 μl of supernatant was mixed with 995 μl 10 mM Tris pH 6.8. Then the fluorescence was monitored on the PerkinElmer Fluorescence Spectrometer 168 LS 55 with excitation wavelength 405 nm and scanning the emission spectrum from 400-700 nm. The fluorescence emission was corrected by subtracting the values for a blank buffer control. 2.4 Antibiotic susceptibility assays 2.4.1 Minimal inhibitory concentration (MIC) Bacteria were seeded at 5 x 105 cfu/ml (final OD600nm 6.7 x 10-5) in a twofold concentration gradient of antibiotic in either LB or BM2 0.1% CAA, no (NH4)2SO4, with glucose or glycerol as indicated, at 100 μl/well in 96 well polystyrene round-bottom plates. After incubating for 24 h at 37°C, the minimal concentration to inhibit visible bacterial growth was reported as the MIC. 2.4.2 Kill curves Bacteria were harvested from antibiotic-free swim (0.3% agar) and swarm (0.5% agar) BM2 glucose plates and resuspended in 62 mM potassium phosphate buffer, pH 7.0 and diluted to a final OD600nm of 0.025 in 10 ml 62 mM potassium phosphate buffer. Cells were then treated with 20 μg/ml tobramycin with aeration at room temperature, and aliquots were periodically taken for serial dilution in PBS pH 7.4 for colony enumeration on LB plates. 2.5 RNA-Seq 2.5.1 Conditions used Bacteria were harvested from the edge (2-3 mm) of swarm fronts or from colonies swimming within agar using the conditions as follows. Swarm (0.5% agar) vs. swim (0.25% agar) 20 RNA-Seq was performed using PA14 WT in BM2 glucose 0.1% CAA supplemented with 1.4 mM (NH4)2SO4 to inhibit swarming in swim plates. Tobramycin vs. untreated RNA-Seq was done using PA14 WT swarming in BM2 glucose 0.5% agar ± 0.5 μg/ml tobramycin. Both PA0805.1 and PA2952.1 RNA-Seq and proteomics were performed at the same time under swarming conditions using overexpression strains compared to EV in BM2 glycerol 0.5% agar and 1% arabinose to induce expression. 2.5.2 RNA isolation Harvested bacteria were transferred to RNAprotect Bacteria Reagent (Qiagen), pelleted and stored at -80°C. For the swim samples, most of the agar was removed from the pellets by pipetting. Swim pellets were lysed by resuspension in 6 mg/ml lysozyme dissolved in Tris-EDTA (TE) buffer pH 8.0 (Thermo Fisher), supplemented with 5 U β-agarase I (NEB) to digest remaining agar in the swim pellets. Swarm pellets were resuspended in lysozyme-TE without agarase. RNA isolation then proceeded according to the manufacturer’s instructions using the RNeasy Mini Kit (Qiagen). Eluted RNA was further purified with the TURBO DNA-free kit (Thermo Fisher). The quality and quantity of RNA was confirmed using the Bioanalyzer instrument. The number of biological replicates for each experiment are indicated in Table 2-1. Table 2-3. Number of biological replicates per RNA-Seq experiment. Experiment No. replicates No. independent RNA-Seq runs Test condition Control condition Swarm vs. swim 5 6 2 TOB vs. UNTR 3 3 1 PA0805.1 vs. EV 5 5 2 PA2952.1 vs. EV 5 5 2 2.5.3 RNA-Seq and identification of differentially expressed (DE) genes RNA samples were depleted of rRNA using the RiboZero Bacteria Kit (Illumina), and libraries were prepared using the KAPA Stranded Total RNA Kit (KAPA Biosystems). Sequencing was done on an Illumina HiSeq2500 by the University of British Columbia Sequencing and Bioinformatics Consortium. Sequence quality was determined using FastQC v0.11.8 and MultiQC v1.7. Reads were mapped to the P. aeruginosa UCBPP-PA14 or PAO1 reference genome obtained from the Pseudomonas Genome Database (www.pseudomonas.com) using the alignment program STAR v2.6.1a. Counts were generated using v0.11.2 of the HTSeq count function. For the experiment involving a subinhibitory concentration of tobramycin, in addition to the 3 untreated swarming controls specifically obtained for this experiment, the swarming samples 21 from the “swarm vs. swim” experiment described herein were also included when performing all downstream analyses for the subinhibitory-tobramycin experiment, bringing the total number of samples for this experiment to 11, 8 untreated swarming controls and 3 tobramycin-treated swarming samples. Experiment date was included in the design formula to control for any potential batch effects. DE genes were determined using the package DESeq2 v1.20.0, in R v3.5.3, with thresholds of adjusted p-value ≤ 0.05 and absolute fold change ≥ 1.5. All lists of DE genes are available in Tables A1 and A2. 2.6 Proteomics 2.6.1 Protein digestion and quantification Bacteria harvested in Section 2.5.1 were washed three times with PBS pH 7.4 and stored as a pellet at -80°C. Bacterial cell pellets were resuspended in lysis buffer (100 mM HEPES (pH 8.5), 4% SDS, 1X Halt protease inhibitor cocktail (Thermo Fisher Scientific). The cells were sonicated three times for 15 s per cycle with 1 min cooling on ice between each cycle. The insoluble cellular debris was removed by centrifugation at 17,000 g for 10 min. Protein concentration was determined using the Pierce detergent compatible Bradford assay kit (Thermo Fisher Scientific). All protein samples were processed and handled using single-pot solid-phase-enhanced sample preparation (SP3) protocol described below. Prior to SP3 treatment, two types of carboxylate-modified SeraMag Speed beads (GE Life Sciences) were combined in a ratio of 1:1 (vol/vol), rinsed, and reconstituted in water at a concentration of 20 μg solids per μl. Initially, 200 μg of lysate was reduced with 10 mM (final concentration) dithiothreitol for 30 min at 60°C followed by alkylation using 50 mM (final concentration) iodoacetamide for 45 min in the dark at room temperature. After that, 20 μl of the prepared bead mix was added to the lysate and samples were adjusted to pH 7 using HEPES buffer. To promote protein binding to the beads, acetonitrile was added to a final concentration of 70% (vol/vol) and samples were incubated at room temperature on a tube rotator for 18 min. Subsequently, beads were immobilized on a magnetic rack for 1 min. The supernatant was discarded and the pellet was rinsed twice with 200 μl of 70% ethanol and once with 200 μl of 100% acetonitrile while on the magnetic rack. Rinsed beads were resuspended in 65 μl of 50 mM HEPES buffer (pH 8) supplemented with trypsin/Lys-C mix (Promega) at an enzyme-to-protein ratio of 1:25 (wt/wt) and incubated for 16 h at 37°C. After overnight digestion, supernatant containing peptides was transferred into a fresh tube and subsequently measured for peptide yield using Pierce Quantitative Fluorometric Peptide Assay (Thermo Fisher Scientific). 22 2.6.2 Tandem mass tag (TMT) labeling Representative samples containing 85 μg of peptides were adjusted to the same concentration using 50 mM HEPES (pH 8) and labeled with 10-plex TMT reagents (Thermo Fisher Scientific). The TMT10 reporter channels were sequentially assigned in increasing reporter mass as TMT0-TMT9. Four TMT10 channels (TMT0-TMT3) were assigned to samples from the EV strain, three channels (TMT4-TMT6) to the PA2952.1 strain, and three channels (TMT7-TMT9) to the PA0805.1 strain. In short, 0.8 mg of each TMT channel was first dissolved in 41 μl of DMSO before adding to the corresponding peptide digests. The labeling reaction was incubated at room temperature for 60 min. Following incubation, samples were quenched for 15 min with the addition of 8 μl of 5% hydroxylamine. Finally, labeled samples were mixed at equal volume and desalted using SOLA HRP SPE cartridge (Thermo Fisher Scientific) prior to LC/MS/MS. 2.6.3 Mass spectrometry data acquisition Analysis of TMT labeled peptide digests was carried out on an Orbitrap Q Exactive HF-X instrument (Thermo Fisher Scientific, Bremen, Germany). The peptide mixture was resuspended in 0.1% formic acid prior to injection. The sample was introduced using an Easy-nLC 1000 system (Thermo Fisher Scientific) at 2 μg per injection. Mobile phase A was 0.1% (vol/vol) formic acid and mobile phase B was 0.1% (vol/vol) formic acid in 80% acetonitrile (LC-MS grade). Gradient separation of peptides was performed on a C18 (Luna C18(2), 3 μm particle size (Phenomenex, Torrance, CA)) column packed in-house in Pico-Frit (100 μm X 30 cm) capillaries (New Objective, Woburn, MA). Peptide separation used the following gradient: 3 – 5 % increase of phase B over 4 min, 5 – 7 % over 3 min, 7 – 25 % over 197 min, 25 – 60 % over 25 min, 60 – 90% over 1 min, with final elution of 90% B for 10 min at a flow rate of 300 nL/min. Data acquisition on the Orbitrap Q Exactive HF-X instrument was configured for data-dependent method using the full MS/DD−MS/MS setup in a positive mode. Spray voltage was set to 1.85 kV, funnel RF level at 40, and heated capillary at 275°C. Survey scans covering the mass range of 350–1500 m/z were acquired at a resolution of 120,000 (at m/z 200), with a maximum ion injection time of 60 ms, and an automatic gain control (AGC) target value of 3e6. For MS2 scan triggering, up to 20 most abundant ions were selected for fragmentation at 32% normalized collision energy, with intensity threshold kept at 5.7e4. AGC target value for fragment spectra was set at 1E5, which were acquired at a resolution of 45,000, with a maximum ion injection time of 88 ms and an isolation width set at 0.7 m/z. Dynamic exclusion of previously selected masses was enabled for 30 s, charge state filtering was limited to 2–6, peptide match was set to preferred, and 23 isotope exclusion was on. 2.6.4 Identification and differential analysis of proteins A January 2019 reference database of P. aeruginosa PAO1 (taxon 208964) was downloaded from uniprot (www.uniprot.org). The 1D LC-MS run was converted into an MGF file using the Proteome Discoverer bundled tool, and was searched against the PAO1 database using X!tandem (cyclone 2012.10.01.1). Peptide identification settings were standard for the instrument: single missed cleavage tryptic peptides were permitted, with a parent and fragment mass tolerance of 10 PPM. A fixed post-translational modification of C+57.021 was applied, and variable PTMs including N-terminal acetylation, deamidation, phosphorylation and oxidation were permitted. Peptide assignment into source proteins was managed by X!tandem. Peptide level TMT10 reporter tags intensities were integrated across window of ±3 mDa each, and corrected for isotopic overlap between channels using the supplied batch-specific correction matrix. Protein level quantitation required at least two unique peptides of expectation values log(e)≤-1.5 each, yielding highly confident protein assignments of at least log(e)≤-3. The sum of peptide level TMT10 reporter tag intensities for each protein was converted into a log2 scale for simplified differential analysis. Protein expression values across each TMT10 reporter channel were normalized into a common scale (mean=0, SD=1). Differential analyses between normalized sample populations (PA0805.1 vs. EV and PA2952.1 vs. EV) were conducted using the Welch T-test function in Excel between population averages. The p-scores were not subjected to multiple-testing corrections, and any differences with p<0.05 were considered candidates for biological exploration. Differences between normalized population means were scaled back into a log2 scale by multiplying them by an average system-wide SD of 2.26. 2.7 Murine infection abscess model Bacterial strains were tested in vivo by injecting bacteria subdermally to form a cutaneous abscess (Pletzer et al., 2017). P. aeruginosa PA14 was grown to an OD600nm of 1.0 in 2YT broth, subsequently washed twice with sterile PBS, and further adjusted to 5 108 CFU/ml. A 50 l bacterial suspension was injected subdermally into the right side of the dorsum. One hour post infection, mice were either treated with 14 mg/kg 1018 (dissolved in 5% dextrose), or dextrose alone. After 16-18 h, mice were euthanized, organs harvested, and homogenized in 1 ml sterile PBS using a Mini-Beadbeater-96 (Biospec products) for 5 min. Bacterial counts were determined by serial dilution and experiments were performed at least 3 times independently with 3 to 5 24 animals per group. These studies were performed in collaboration with Dr. Daniel Pletzer at UBC. 2.8 qRT-PCR Cells were harvested from a variety of conditions as described in Table 2-4. For cultures grown in BM2, (NH4)2SO4 was omitted and 0.1% CAA was used as the nitrogen source. RNA was isolated and DNase digested as described in the RNA-Seq section, but omitting the use of agarase, and quantified on a NanoDrop® Spectrophotometer ND-1000. RNA was then diluted to 1 ng/μl and 5 μl were used in a total reaction volume of 25 μl. The qScript One-Step SYBR Green RT-qPCR (Quantabio) was used and samples were run on the LightCycler® 96 (Roche). Cq values were normalized to the housekeeping gene rpoD using the ΔΔCT method. rpoD routinely served as an appropriate housekeeping gene, except in the swarm vs. swim experiment (Section 4.10), where 16S was used instead. Primers used for qRT-PCR are described in Table 2-5. Table 2-4. Comparisons and media used for qRT-PCR experiments. Comparison Medium Section Swarm vs. planktonic (Overhage et al., 2008) BM2 glucose, ± 0.5% agar Chapter 3 Swarm vs. swim BM2 glucose, 0.5 vs. 0.3% agar 4.10 PA0805.1 vs. EV BM2 glycerol, 1% arabinose, 0.5% agar 4.5 PA0805.1 induced vs. uninduced BM2 glycerol, 0.5% agar ± 0.5% arabinose 4.2 PA2952.1 vs. EV BM2 glycerol, 1% arabinose, 0.5% agar Chapter 5 ∆ptsP EV vs. WT EV ∆ptsP+ vs. WT EV LB planktonic Chapter 6 Table 2-5. Primers used for qRT-PCR. Name Sequence (5’ -> 3’) 16S F GGCAGGCCTAACACATGCAA 16S R TTATCCCCCACTACCAGGCA aprA F TCCAAGCTGGTGTTCTCGGT aprA R AGCGCCTTCTCGTTGAGGTT gmd F GAGATGTTCGGCCTGATCCA gmd R ACGGTGATCCAGTGGCCATA lasA F GACGAACTGTTCCTCTACGGTC lasA R CCAGGTATTCGCTCTTGTCG mexG F ACTCGCTCGAAAGCAACTGG mexG R AGGCTGGCCTGATAGTCGAA mexH F ATCCGTCTCAAGGCGCAGTT mexH R TTGTCCAGCTGTTCCTGCGA mexI F ATCACCGTCACCACCGAGTA mexI R AAAGGTAGTCGATGCCCTCC 25 Name Sequence (5’ -> 3’) opmD F TACAGCCGCAGCATCGAACA opmD R CCGAACAGGTCGATTTCCCA PA0805.1 qF TGGTATTGCGGGACGCC PA0805.1 qR ACTCTTCTGAAGCAATCCCCTG PA3670 F AGGATTCGCCTGCAGGTGAT PA3670 R CTGCTGCAGGGGAATTCCTT PA3836 F GGCTACGAAGACGGCAAGAA PA3836 R CTTGTCGCCGATGAACTTGC PA5542 F GCCGCCGATCTCTATGAACT PA5542 R TGGTCCCCTTGTGGATAACC pchF F GATGACTGCGTACTGCACTGCT pchF R CCATTGCGGATCGAGATAGC pcrG F AATACACCGAAGACACCCTGCG pcrG R TTGCCACATTTCCGCCAGCA prtN F CGTGGAATTGGTCTACCGCA prtN R CCAGGGCCTTGCTGAAGTTT ptsP qF CTCAACACGCTGCGCAAGAT ptsP qR TGGGTACCCATGGCTTCCTT rhlR F CGCGTCGAACTTCTTCTGGAT rhlR R GCAAGAGTTCCGGGGAAATC rmd F CTCTCCGGTTTCGTAGGCAA rmd R CAGCAGATCGTAACGATGCG rpoD F TCACGCACGCAGAGTTGCAT rpoD R AAGCTGGTGCCCAAGCAGTT vfr F TAGACAAGCTGCTCGCACAC vfr R GAAATCACCGCTGTTGAGGT wbpW F CGAGAAACCCGATGAGGAAACC wbpW R GTCGAGGCCGTGAAACAGAA wbpX F GACCAACTGGTCTTGCTGGA wbpX R TAGATCACCGAGACGATGCC wbpZ F CGGTTTTTCCCTGAGCGTGT wbpZ R GGAAATGCACCAGGTCCATG wzm F GGCTATCGTGGCTTCGTTCT wzm R ATCGACAGCGGATTGAGCAC wzt F GAGGAAATCCAGGCGCTGAT wzt R ATCTGCATGCCGCTGGAGTA 26 2.9 DNA manipulation 2.9.1 Deletion mutants Deletion mutants of PA0805.l and ptsP were constructed using previously described methods with minor modifications (Pletzer et al., 2014). Briefly, PAO1 WT genomic DNA was PCR-amplified using the primers PA0805.1 A1 and A2, and PA0805.1 B1 and B2 described in Table 2-6. PA14 WT gDNA was amplified with primers ptsP A1 and A2, and ptsP B1 and B2 (Table 2-6). After gel extraction of the fragments, a fusion PCR was performed using primers PA0805.1 A1 and B2, and ptsP A1 and B2. The PCR products were then TOPO cloned as described in Section 2.9.2, digested with BamHI and XbaI, cloned into the vector pEX18Gm, transformed into the E. coli donor strain ST18 (an auxotroph for 5-aminolevulinic acid) and conjugated into PAO1 or PA14 WT using LB agar plates with 50 μg/ml 5-aminolevulinic acid. After, P. aeruginosa conjugants were selected on gentamicin 30 μg/ml and then counterselected at least three times with LB 5% sucrose. The deletion mutants were confirmed by lack of growth on gentamicin and PCR of the deleted region. Table 2-6. Primers used for cloning. Name Sequence (5' -> 3') PA0730.1 F GACTCTAGACGATGGGAACGCGGCGA PA0730.1 R CTCGGTACCGTCCCTTTCCTTCCCGGCAT PA0805.1 A1 CTCGGATCCTCTGAGTGGAGTACGGGAGA PA0805.1 A2 CGAAAGATATACAATCCGGGAAAGCGTGAAAGTAAAGGAACAT PA0805.1 B1 ATGTTCCTTTACTTTCACGCTTTCCCGGATTGTATATCTTTCG PA0805.1 B2 GACTCTAGAGAAGGATGGGAACAGGTCG PA0805.1 F GACTCTAGAATGGAGCAGCGTATATTGC PA0805.1 R CTCGGTACCCTGCGTACCAAACTGAAAGTC PA0958.1 F GACTCTAGACTTGGCGATAGTTGAGGTTCC PA0958.1 R CTCGGTACCGTTTGCTTTCAAACAGAATAGCCT PA1091.1 F CTCGGTACCAACTTCCACCCTCTGCCG PA1091.1 R GACTCTAGAGGTGATTTCCTCCAAAGGACC PA14sr120 F CTCGGTACCATGGAGCAGCGTATATTGC PA14sr120 R GACTCTAGATAGTACCTGAACTGCCAGC PA2461.1 F GACTCTAGATCTTCAGCTCAGACACAGGTT PA2461.1 R CTCGGTACCCTTAGAGGAAGGTCCATTCAAACA PA2461.3 F GACTCTAGACTGTACCGCGAGCCCC PA2461.3 R CTCGGTACCCAACGCTGGAGTATCATCCACT PA2952.1 F CTCGGTACCGCCCGTATCTTGACCGGAT PA2952.1 R GACTCTAGATAGCTGCATGGGCAGGTC PA2952.1W F CTCGGTACCATAAGGATGTCGCCAGACAGG 27 Name Sequence (5' -> 3') PA2952.1W R GACTCTAGAGAGCGGGCGCATTAT PA3159.1 F CTCGGTACCCACCCCGCGATTGCC PA3159.1 R GACTCTAGATAGTTATTGAAGTGGTGATGCGT PA4539.1 F GACTCTAGAGCCGCCAGACCGAACG PA4539.1 R CTCGGTACCGCGGAAAAGCTGGATGCATGG PA4656.1 F CTCGGTACCATTCCGGCGTTATCCTGTGA PA4656.1 R GACTCTAGACCTCTCTGGTTGTGTAGCGT PA5078.1 F GACTCTAGACGTCCGTGAACATGAATTACT PA5078.1 R CTCGGTACCCTGTACAGGACAGGCCG PA5304.1 F GACTCTAGACAGTATAGGAAGAGGCAGGCA PA5304.1 R CTCGGTACCAGGCTCCGCGAGCGCTCTGG prrH F GGATCCAACTGGTCGCGAGAT prrH R TCTAGAAGGAAGGGCGCGAGG prtN F GGATCCATGCAGCCAACCATCGCC prtN R TCTAGATCAGGATGCGATGCTGTCC, ptsP A1 CTCGGATCCCGATGGTTTTCGCCCGAATG ptsP A2 TCCGGCGCGCGGGAAAGCTCGGGGCCTTGTCTCCGTGTT ptsP B1 AACACGGAGACAAGGCCCCGAGCTTTCCCGCGCGCCGGA ptsP B2 GACTCTAGACCTCGCAGTATTCCGGGCTT ptsP F GGATCCATGCTCAACACGCTGCGCAAGA ptsP R TCTAGATCAGGGCTGGACGGTAGC rsmY F CTCGGTACCGTCAGGACATTGCGCAGGAA rsmY R GACTCTAGAAAAACCCCGCCTTTTGGGC srbA F CTCGGTACCATCAGGGGCTCTGAAACGAC srbA R GACTCTAGATCAAGAAATGTATTGGTTGAGCACC wbpW F GGATCCATGCTGATTCCCGTGGTGC wbpW R TCTAGATCAGACCACCCTGCCGTA. 2.9.2 Complementation and overexpression strains PA14 and PAO1 WT gDNA was isolated as specified in the Qiagen DNeasy Blood and Tissue kit protocol. 80-300 ng was PCR amplified using the primers described in Table 2-6. PCR products were then cloned using one of two cloning strategies as described in Table 2-7. PCR products cloned via the TOPO strategy were gel-extracted with the GeneJet Gel Extraction Kit (Thermo Fisher) and TOPO cloned (Invitrogen). TOPO reactions were transformed into TOP10 E. coli and selected with 50 μg/ml kanamycin (TOPO). Plasmid was subsequently isolated according to the Thermo Fisher kit and digested with the restriction endonucleases indicated in Table 2-7. This allowed the sRNAs to be cloned in two different orientations, termed a and b, and 28 other constructs to be cloned in one specific orientation. After the fragments were gel-extracted, they were ligated into similarly digested vectors with T4 DNA ligase (Thermo Scientific), transformed into TOP10 E. coli, and selected with antibiotic as indicated. PCR products cloned via the direct strategy were PCR purified using the PCR purification kit (Thermo), then digested with the restriction enzymes indicated in Table 2-7. Next, digested fragments were gel extracted and ligated as described above, then transformed into TOP10 E. coli and selected with antibiotic as indicated in Table 2-7. Plasmid sequences were confirmed by Sanger sequencing at the Sequencing and Bioinformatics Consortium at UBC. Table 2-7. Cloning strategies and restriction enzymes used. PCR product Cloning strategy Enzymes used Final product Vector Antibiotic (μg/ml) PA0730.1 Direct KpnI XbaI PA0730.1 pHERD20T Ampicillin 100 PA0805.1 TOPO KpnI XbaI PA0805.1a pHERD20T Ampicillin 100 EcoRI KpnI PA0805.1 pHERD20T Ampicillin 100 pUC18miniTn7Tp Trimethoprim 50 ∆PA0805.1 TOPO BamHI XbaI ∆PA0805.1 pEX18Gm Gentamicin 15 PA0958.1 Direct KpnI XbaI PA0958.1 pHERD20T Ampicillin 100 PA1091.1 TOPO KpnI XbaI PA1091.1a pHERD20T Ampicillin 100 HindIII XbaI PA1091.1b pHERD20T Ampicillin 100 PA2461.1 Direct KpnI XbaI PA2461.1 pHERD20T Ampicillin 100 PA2461.3 Direct KpnI XbaI PA2461.3 pHERD20T Ampicillin 100 PA2952.1 Direct KpnI XbaI PA2952.1 pHERD20T Ampicillin 100 PA2952.1W Direct KpnI XbaI PA2952.1W pHERD20T Ampicillin 100 PA3159.1 TOPO KpnI XbaI PA3159.1a pHERD20T Ampicillin 100 EcoRI KpnI PA3159.1b pHERD20T Ampicillin 100 PA4539.1 Direct KpnI XbaI PA4539.1 pHERD20T Ampicillin 100 PA4656.1 TOPO KpnI XbaI PA4656.1a pHERD20T Ampicillin 100 EcoRI KpnI PA4656.1b pHERD20T Ampicillin 100 PA5078.1 Direct KpnI XbaI PA5078.1 pHERD20T Ampicillin 100 PA5304.1 Direct KpnI XbaI PA5304.1 pHERD20T Ampicillin 100 PA14sr120 Direct KpnI XbaI PA14sr120 pHERD20T Ampicillin 100 prrH TOPO EcoRI XbaI prrH pHERD20T Ampicillin 100 prtN TOPO SacI XbaI prtN pHERD20T Ampicillin 100 ptsP TOPO BamHI XbaI ptsP pBBR1mcs5 Gentamicin 10 ∆ptsP TOPO BamHI XbaI ∆ptsP pEX18Gm Gentamicin 15 rsmY Direct KpnI XbaI rsmY pHERD20T Ampicillin 100 srbA Direct KpnI XbaI srbA pHERD20T Ampicillin 100 wbpW TOPO BamHI XbaI wbpW pBBR1mcs2 Kanamycin 50 2.9.3 Transformation of P. aeruginosa P. aeruginosa strains were transformed either by electroporation or conjugation as described in Table 2-8. This was due to the observation that certain vectors transformed more 29 efficiently via conjugation. Note that for comparisons between WT, mutants, complementation and overexpression strains, the same method of transformation was always used, and WT and mutants were also always transformed with EV to rule out any effect of the vector. 184.108.40.206 Electroporation Electrocompetent P. aeruginosa were transformed with both EV and vector with insert according to Choi et al. (Choi et al., 2006). Transformants were selected with antibiotic as indicated in Table 2-8 and confirmed to carry the correct plasmid. 220.127.116.11 Conjugation Strains were transformed by conjugation using previously described methods with minor modifications (Pletzer et al., 2014). The plasmid of interest was transformed into the E. coli donor strain ST18 (an auxotroph for 5-aminolevulinic acid) and conjugated into the P. aeruginosa strain of interest using LB agar plates with 50 μg/ml 5-aminolevulinic acid. After, conjugants were selected with antibiotic as indicated in Table 2-8 and confirmed to carry the correct plasmid. Table 2-8. Methods of transformation used in this thesis, including vectors and antibiotic concentrations. Strain Mutant Method Vector Antibiotic (μg/ml) PA14 WT Electroporation pBBR1mcs2 Kanamycin 250 PA14 WT Electroporation pHERD20T Carbenicillin 300 PA14 WT Conjugation pBBR1mcs5 Gentamicin 30 PA14 prtN Electroporation pHERD20T Carbenicillin 300 PA14 wbpW Electroporation pBBR1mcs2 Kanamycin 250 PA14 ∆ptsP Conjugation pBBR1mcs5 Gentamicin 30 PAO1 WT Electroporation pHERD20T Carbenicillin 300 PAO1 ∆PA0805.1 Conjugation pUC18miniTn7Tp pTNS3 Trimethoprim 250 PAO1 ∆prrH Electroporation pHERD20T Carbenicillin 300 2.10 In silico sRNA target prediction sRNA targets were predicted using three tools: IntaRNA2 (Busch et al., 2008), RNAPredator (Eggenhofer et al., 2011), and TargetRNA2 (Tjaden et al., 2006). For IntaRNA2 and TargetRNA2, input parameters were adjusted to 75 nucleotides up and downstream, and a minimum of 7 basepairs in the seed sequence was used. Cutoffs used were top 100 and p ≤ 0.05 for IntaRNA2, p ≤ 0.05 for TargetRNA2, and top 100 for RNAPredator. Only targets predicted by more than one tool were considered. 2.11 Statistical analysis All experiments were repeated independently with at least three biological replicates. 30 Experiments performed in 96 well plates additionally used at least two technical replicates per biological replicate. Unless otherwise specified, mean ± standard error was reported or depicted in graphs. Statistical tests (Student’s t-test or ANOVA) were performed in GraphPad Prism, with a p value of 0.05 being considered significant and the p values are indicated by * (0.01 < p ≤ 0.05), ** (0.001 < p ≤ 0.01), *** (0.0001 < p ≤ 0.001), and **** (p ≤ 0.0001). 2.12 Data availability RNA-Seq data was deposited in Gene Expression Omnibus (GEO) under accession numbers GSE121504 (swarm vs. swim), GSE137676 (tobramycin vs. untreated), GSE137738 (PA0805.1 vs. EV), and GSE146765 (PA2952.1 vs. EV). Proteomics data was deposited in MassIVE under the index number MSV000084373 (PA0805.1 vs. EV). 31 Chapter 3: Swarming motility and antibiotic resistance 3.1 Introduction When P. aeruginosa undergoes swarming motility, adaptive antibiotic resistance is triggered (Lai et al. 2009; Overhage et al. 2008). To date this has only been investigated in a limited fashion; research presented in this chapter provides an in-depth investigation of this phenomenon. Swarming motility in P. aeruginosa is a rapid, coordinated, surface-associated movement that occurs under semi-viscous, nitrogen-limiting conditions (Overhage et al., 2008). Importantly, these conditions have some similarities with the mucosal surfaces of the human lung (Yeung et al., 2009); therefore, understanding how swarming in P. aeruginosa leads to multiple-antibiotic adaptive resistance is relevant to our understanding of lung infections and the limitations of antibiotic therapy in this situation. Features of the lung environment that are likely to support swarming include increased glucose levels in the diseased lung (Baker et al., 2007; Gill et al., 2016), amino acids as the main nitrogen source, sufficient levels of magnesium (Palmer et al., 2007), and a humid and viscous environment. Swarming is thought to have clinical relevance particularly in the acute or initial infection of lungs, since strains isolated from chronic infections tend to lose motility over time (Winstanley et al., 2016). Thus swarming can allow for rapid colonization in the lung and the establishment of infection, and is also important in the initial formation of biofilms (O’May & Tufenkji, 2011), which are a common problem in infections due to their ability to persist and resist antimicrobial treatment. In the swarm state, P. aeruginosa conditionally increases its resistance to several antibiotics (Lai et al., 2009; Overhage et al., 2008). This resistance is not dependent on prior antibiotic exposure and also occurs in other swarming species such as Salmonella sp. (Butler et al., 2010), E. coli and Bacillus subtilis (Lai et al., 2009). Little is known about the genetic mechanisms that result in adaptive antibiotic resistance in P. aeruginosa swarming motility. Therefore, after confirming and extending the observation that P. aeruginosa exhibits resistance in the swarm state, RNA-Seq and qRT-PCR were performed on swarming cells and swarming cells treated with tobramycin, and mutants in genes dysregulated under swarming conditions were selected and tested for altered antibiotic susceptibility under swarming conditions. 3.2 Swarming cells were resistant to multiple antibiotic classes To confirm and extend the observation that P. aeruginosa exhibits resistance in the swarming state (Lai et al., 2009; Overhage et al., 2008), BM2 glucose agar plates solidified with 32 varying concentrations of agar (allowing for different modes of growth) were inoculated with mid-log phase P. aeruginosa PA14 (Figure 3-1, Figure A1). After overnight incubation, the zone of inhibition around antibiotic discs (i.e. the closest approach of motile cells to the antibiotic disc) was measured as an indicator of resistance. PA14 swarming cells on 0.4% agar were significantly more resistant to aminoglycosides (amikacin, gentamicin, kanamycin, and tobramycin) and β-lactams (ceftazidime, meropenem, and piperacillin) when compared to the control swim and spread plates (Figure 3-1, top panels). Swarming cells were also significantly more resistant to chloramphenicol, ciprofloxacin, tetracycline and trimethoprim. For the macrolides, erythromycin and azithromycin, swarming cells were significantly more resistant than swimming cells but not bacteria on 1.5% agar spread plates. Swarming cells were not resistant to polymyxin B (Figure 3-1, top panels). Resistance of swarming cells was more readily observable at 0.4% agar since this condition permitted better swarming (Figure 3-1). However, similar trends were observed for swarming at 0.5% agar (Figure A1). To confirm these results by a different method, cells were harvested from antibiotic-free swimming and swarming plates and subjected to tobramycin treatment. Swarming cells were killed more slowly, showing approximately 100-fold better survival than swimming cells after 300 min (Figure 3-2). 3.3 Swarming motility is a complex adaptation accompanied by many changes in the expression of resistome genes Due to the complexity of these resistance data and to enable an understanding of the global changes accompanying swarming motility, I first characterized the global gene expression changes accompanying swarming motility. Previous studies analyzing global gene expression changes were performed using microarrays with planktonic (broth culture grown cells) as a control; this had identified the dysregulation of 417 genes including 18 regulators (Overhage et al., 2008). Here I improved this analysis by comparing swarming to swimming cells taken from plate cultures (varying only in the agar concentration), and utilizing the more accurate method of RNA-Seq. The comparison of swarming vs. swimming by RNA-Seq resulted in the differential expression of 1,581 genes (753 downregulated and 828 upregulated) (Table A1). This was a substantial portion, 28%, of the P. aeruginosa genome, showing that swarming is a distinct and complex adaptation. The dysregulated genes included 104 transcriptional regulators, two-component systems and sigma factors (Table 3-1). There were several regulators of nitrogen metabolism such as nirQ, 33 Figure 3-1. Swarming bacteria exhibited heightened resistance to most antibiotic classes. Top panels: Zone of inhibition assay using 0.3% agar for swimming, 0.4% for swarming and 1.5% for spread plate with different antibiotics. Statistically significant differences were determined by ANOVA. Lower panels: Zone of inhibition assay for PA14 WT using tobramycin discs. Arrows indicate position of inoculation. p values (*) are described in Section 2.11. n ≥ 3. nirG, nosR, and hutR. Other interesting regulators included BfiS, a two-component sensor involved in biofilm formation (Petrova & Sauer, 2010), PchR, a regulator of ferripyochelin receptor gene (Heinrichs & Poole, 1996), VqsR, a global regulator of QS and virulence (Liang et al., 2012a), and AlgR, which is involved in coordinating alginate and rhamnolipid production, and 34 Figure 3-2. Tobramycin kill curve showing that swarming cells survived better than swimming cells in the presence of tobramycin. n = 3. swarming and twitching motilities (Okkotsu et al., 2013). The dysregulated sigma factors included hasI, femI, fiuI, foxI, fpvI, pvdS, rpoS, vreI, PA1351, PA2050, PA2093, and PA4896. Table 3-1. Selected results from swarm vs. swim RNA-Seq comparisons. These revealed 104 dysregulated transcriptional regulators, and dysregulated efflux and β-lactamase genes. Cutoffs used were fold change (FC) ≥ 1.5 and adjusted p value (padj) ≤ 0.05. Locus Tag PAO1 Name Product Name padj FC Transcriptional regulators, two-component systems and sigma factors PA14_00600 PA0048 transcriptional regulator 9.1E-06 1.7 PA14_00680 PA0056 LysR family transcriptional regulator 2.0E-03 1.5 PA14_02250 PA0178 two-component sensor 5.2E-09 1.6 PA14_02260 PA0179 two-component response regulator 4.4E-07 1.5 PA14_02390 PA0191 transcriptional regulator 3.4E-08 -2.0 PA14_02870 PA0233 transcriptional regulator 1.9E-08 1.5 PA14_03070 PA0248 transcriptional regulator 9.0E-06 1.6 PA14_03580 PA0275 transcriptional regulator 9.8E-07 1.5 PA14_04820 PA0367 laoR TetR family transcriptional regulator 4.4E-14 1.6 PA14_06170 PA0471 fiuR transmembrane sensor 1.0E-04 1.7 PA14_06180 PA0472 fiuI RNA polymerase sigma factor 3.0E-05 1.5 PA14_06690 PA0513 nirG transcriptional regulator 1.8E-13 -3.2 PA14_06710 PA0515 transcriptional regulator 5.4E-13 -3.4 PA14_06770 PA0520 nirQ regulatory protein 4.6E-21 -2.9 PA14_06970 PA0535 Cro/CI family transcriptional regulator 2.5E-09 -1.6 PA14_07110 PA0547 ArsR family transcriptional regulator 8.7E-27 1.7 PA14_09260 PA4227 pchR transcriptional regulator 5.6E-28 3.8 PA14_09680 PA4197 bfiS two-component sensor 5.4E-09 -1.7 PA14_09790 PA4182 transcriptional regulator 1.3E-13 -1.5 PA14_10530 PA4132 GntR family transcriptional regulator 2.0E-28 -1.5 PA14_10660 PA4120 transcriptional regulator 7.9E-05 1.9 PA14_10940 PA4094 AraC family transcriptional regulator 2.0E-06 1.6 0 200 400 600 800103104105106107108Tobramycin kill curveTime (minutes)Survival (cfu/ml)SwarmingSwimming35 Locus Tag PAO1 Name Product Name padj FC PA14_11120 PA4080 response regulator 6.9E-08 1.5 PA14_12140 PA3995 transcriptional regulator 1.3E-09 1.7 PA14_13000 PA3932 transcriptional regulator 1.2E-14 -2.7 PA14_13150 PA3921 transcriptional regulator 1.6E-14 1.5 PA14_15240 PA3776 LysR family transcriptional regulator 1.3E-03 -1.6 PA14_15290 PA3771 transcriptional regulator 7.9E-06 1.9 PA14_15830 PA3757 nagR GntR family transcriptional regulator 2.9E-05 -1.5 PA14_16790 PA3678 mexL TetR family transcriptional regulator 6.8E-15 1.5 PA14_17380 PA3630 gfnR glutathione-dependent formaldehyde neutralization regulator 7.1E-11 1.8 PA14_17480 PA3622 rpoS RNA polymerase sigma factor 1.9E-11 1.6 PA14_17540 PA3616 recombination regulator RecX 6.3E-10 -1.6 PA14_19380 PA3458 transcriptional regulator 3.8E-08 1.8 PA14_19990 PA3410 hasI RNA polymerase ECF-subfamily sigma-70 factor 3.6E-06 -2.0 PA14_20230 PA3391 nosR regulatory protein 2.1E-37 -17.2 PA14_20780 PA3346 hsbR two-component response regulator 2.6E-20 1.6 PA14_23190 PA3174 hutR transcriptional regulator 1.1E-12 -2.2 PA14_23590 PA3133 sawR transcriptional regulator 5.2E-11 -2.1 PA14_24710 PA3045 rocA2 two-component response regulator 9.1E-11 -2.5 PA14_24720 PA3044 rocsS2 two-component sensor 5.2E-14 -2.1 PA14_25800 PA2957 TetR family transcriptional regulator 3.5E-13 -1.5 PA14_26330 PA2917 AraC family transcriptional regulator 4.4E-18 -2.3 PA14_26860 PA2879 LysR family transcriptional regulator 3.2E-19 2.0 PA14_30580 PA2591 vqsR LuxR family transcriptional regulator 2.5E-21 1.6 PA14_30840 PA2571 signal transduction histidine kinase 7.2E-09 1.5 PA14_32060 PA2519 xylS transcriptional regulator 3.6E-08 1.8 PA14_32460 PA2488 transcriptional regulator 7.7E-04 1.5 PA14_32710 PA2468 foxI ECF subfamily RNA polymerase sigma-70 factor 5.8E-05 1.8 PA14_32720 PA2467 foxR transmembrane sensor 1.7E-04 1.5 PA14_33260 PA2426 pvdS extracytoplasmic-function sigma-70 factor 9.7E-07 2.0 PA14_33440 PA2417 LysR family transcriptional regulator 3.5E-09 1.6 PA14_33800 PA2387 fpvI RNA polymerase sigma factor 1.8E-33 2.2 PA14_33840 PA2383 transcriptional regulator 4.3E-17 2.9 PA14_34440 PA2337 mtlR transcriptional regulator 1.7E-04 1.5 PA14_34660 PA2320 gntR transcriptional regulator 1.3E-19 1.6 PA14_34730 PA2312 XRE family transcriptional regulator 3.5E-15 -3.0 PA14_34820 PA2304 ambC regulatory protein 2.7E-20 3.5 PA14_34830 PA2303 ambD regulatory protein 1.2E-30 3.6 PA14_34880 PA2299 GntR family transcriptional regulator 7.2E-14 2.0 PA14_35250 PA2267 LysR family transcriptional regulator 1.5E-06 1.6 PA14_35370 PA2259 ptxS transcriptional regulator 1.3E-08 -2.1 36 Locus Tag PAO1 Name Product Name padj FC PA14_35380 PA2258 ptxR transcriptional regulator 1.7E-13 2.4 PA14_36300 PA2196 TetR family transcriptional regulator 5.0E-10 1.6 PA14_36420 PA2177 sensor/response regulator hybrid 3.7E-18 2.3 PA14_36990 PA2133 cyclic-guanylate-specific phosphodiesterase 4.8E-03 -1.9 PA14_37140 PA2121 LysR family transcriptional regulator 4.0E-03 1.6 PA14_37420 PA2094 transmembrane sensor protein 7.9E-13 3.7 PA14_37430 PA2093 RNA polymerase sigma factor 2.4E-07 2.5 PA14_37580 PA2082 kynR leucine-responsive regulatory protein 1.6E-04 1.5 PA14_37980 PA2051 Fe2+-dicitrate sensor, membrane protein 5.8E-08 -3.3 PA14_37990 PA2050 RNA polymerase sigma factor 1.5E-13 -4.5 PA14_38250 PA2032 transcriptional regulator 8.7E-18 1.6 PA14_39800 PA1912 femI ECF subfamily RNA polymerase sigma-70 factor 2.6E-03 -1.6 PA14_39980 PA1898 qscR transcriptional regulator 2.7E-07 1.7 PA14_42390 PA1713 exsA transcriptional regulator 1.3E-24 2.7 PA14_45250 PA1484 transcriptional regulator 5.6E-05 1.5 PA14_45950 PA1431 rsaL regulatory protein 2.1E-74 3.0 PA14_46290 PA1403 TetR family transcriptional regulator 4.2E-07 2.0 PA14_46810 PA1351 RNA polymerase ECF-subfamily sigma-70 factor 1.7E-10 1.9 PA14_47390 PA1301 transmembrane sensor 2.4E-03 1.6 PA14_48160 PA1243 sensor/response regulator hybrid 1.4E-40 3.2 PA14_48830 PA1196 ddaR transcriptional regulator 2.7E-07 1.6 PA14_49170 PA1180 phoQ two-component sensor 4.7E-16 -2.0 PA14_49180 PA1179 phoP two-component response regulator 5.5E-14 -1.8 PA14_49790 PA1128 transcriptional regulator 1.9E-05 1.7 PA14_53410 PA0839 transcriptional regulator 2.7E-04 -1.5 PA14_53720 PA0816 transcriptional regulator 2.1E-10 1.8 PA14_55160 PA0707 toxR transcriptional regulator 2.4E-17 5.5 PA14_55550 PA0675 vreI ECF subfamily RNA polymerase sigma-70 factor 8.4E-10 -2.6 PA14_55780 PA4293 pprA two-component sensor 8.6E-18 2.5 PA14_57140 PA4396 two-component response regulator 1.5E-17 1.6 PA14_58380 PA4499 psdR transcriptional regulator 7.2E-10 -1.6 PA14_58510 PA4508 AsnC family transcriptional regulator 7.7E-06 -1.6 PA14_61620 PA4659 MerR family transcriptional regulator 2.0E-11 -1.9 PA14_63280 PA4787 transcriptional regulator 1.6E-13 1.6 PA14_64050 PA4843 gcbA two-component response regulator 2.1E-48 -1.9 PA14_64500 PA4878 brlR transcriptional regulator 1.6E-13 -1.8 PA14_64690 PA4895 transmembrane sensor 3.3E-06 -1.8 PA14_64700 PA4896 RNA polymerase sigma factor 1.3E-05 -1.9 PA14_66850 PA5059 TetR family transcriptional regulator 1.1E-09 1.7 PA14_69470 PA5261 algR alginate biosynthesis regulatory protein 2.3E-12 1.6 37 Locus Tag PAO1 Name Product Name padj FC PA14_71170 PA5389 cdhR AraC family transcriptional regulator 1.1E-03 1.6 PA14_71750 PA5437 LysR family transcriptional regulator 2.5E-79 -3.3 PA14_72380 PA5483 algB two-component response regulator 2.3E-11 1.9 PA14_72390 PA5484 kinB two-component sensor 1.4E-16 1.9 Multidrug efflux and β-lactamases PA14_01940 PA0156 triA Resistance-Nodulation-Cell Division (RND) efflux membrane fusion protein 6.6E-12 1.6 PA14_09500 PA4208 opmD outer membrane protein 1.3E-22 1.8 PA14_09520 PA4207 mexI RND efflux transporter 2.0E-23 1.6 PA14_18760 PA3523 mexP RND efflux membrane fusion protein 3.1E-10 -4.0 PA14_18780 PA3522 mexQ RND efflux transporter 1.5E-31 -3.4 PA14_18790 PA3521 opmE outer membrane efflux protein 1.2E-12 -3.3 PA14_32390 PA2494 mexF RND multidrug efflux transporter 3.6E-14 -2.0 PA14_32400 PA2493 mexE RND multidrug efflux membrane fusion protein 4.2E-11 -1.9 PA14_38395 PA2019 mexX periplasmic multidrug efflux lipoprotein 3.4E-07 -1.8 PA14_38410 PA2018 mexY multidrug efflux protein 2.1E-06 -1.6 PA14_41280 PA1797 beta-lactamase 2.8E-11 2.0 PA14_44520 PA1541 drug efflux transporter 1.5E-10 -5.6 PA14_44530 PA1540 multidrug efflux system protein MdtI 6.7E-05 -2.4 PA14_45910 PA1435 RND efflux membrane fusion protein 1.1E-02 -1.6 PA14_48240 PA1238 outer membrane component of multidrug efflux pump 4.3E-02 1.7 PA14_54700 PA0740 sdsA1 beta-lactamase 1.5E-03 -1.5 RNA-Seq of swarm vs. swim cells also revealed the downregulation of 55 ribosomal genes and other related translation factors (Table A1). This was of interest since the ribosome is the target of tobramycin. Interestingly, these genes included fusA1 and rplU, which are involved in tobramycin resistance of CF clinical isolates (López-Causapé et al., 2018). The ribosome modulation factor rmf, which induces the dimerization of 70S subunits into an inactive form (Izutsu et al., 2001), was upregulated 1.8-fold. A search was made for multidrug efflux transporters and β-lactamases, and 16 genes were found, both up and downregulated (Table 3-1). Since the upregulated genes were not strongly induced, it seems unlikely that efflux or β-lactamase production is a major mechanism of the resistance intrinsic to swarm cells, although I show below that multidrug efflux could be induced upon tobramycin treatment. RNA-Seq also revealed the upregulation of several pilus-related genes and rhamnosyltransferase 2 rhlC (Table A1). This is consistent with the requirement of pili and rhamnolipids for swarming motility in P. aeruginosa, and the observation that a mutant in rcpA 38 was unable to swarm (Yeung et al., 2009). Swarm cells also upregulated numerous genes in the type I, II and III secretion systems (Table A1) including genes encoding virulence factors such as exotoxin A, exoenzyme S and Y, phospholipase PlcB and elastases LasA and LasB. Many T6SS genes were also upregulated although certain T6SS genes were downregulated (hcpC and vgrG4a,b) (Table A1). Lastly, many pyoverdine, pyochelin and phenazine genes were also upregulated under swarming conditions (Table A1). This confirms previous studies indicating that swarming cells exhibit broad enhancement of virulence potential (Overhage et al., 2008). 3.4 Multiple factors contributed to swarming-mediated antibiotic resistance Having confirmed that swarming cells were resistant to multiple antibiotics, I sought to elucidate the mechanism(s) of swarming-mediated antibiotic resistance by testing mutants for swarming in the presence of antibiotic. Tobramycin was selected as the antibiotic of interest since swarming cells were strongly resistant (Figure 3-1). RNA-Seq data were analyzed to identify genes corresponding to the resistome (i.e. those genes that affect antibiotic resistance under standard growth conditions) (Alvarez-Ortega et al., 2010; Brazas et al., 2007; Breidenstein et al., 2008; Dötsch et al., 2009; Fajardo et al., 2008; Schurek et al., 2008) that were dysregulated under swarming conditions. Mutants in these genes, as well as some in operons of interest that did not initially appear in the list of dysregulated genes, were screened for altered tobramycin susceptibility under swarming conditions using the agar dilution method. A gene was considered to potentially contribute to swarming-mediated antibiotic resistance if it was downregulated and the corresponding mutant was resistant under swarming conditions (i.e. decreased expression of the gene in question led to resistance). Conversely if the gene was upregulated, and the corresponding mutant was supersusceptible under swarming conditions this might also indicate a role in adaptive resistance, but this did not occur here (Table 3-2, Table A3). Mutants showing Table 3-2. Genes dysregulated under swarming conditions that matched with the known resistome revealed 26 tobramycin resistance mutants. PA14 transposon mutants in selected genes were tested for altered tobramycin susceptibility under swarming conditions using the agar dilution method (inhibitory concentrations shown in μg/ml of tobramycin, along with images of swarming colonies at 1 μg/ml). Evidence of dysregulation came from swarm vs. swim RNA-Seq (superscript 1) or tobramycin RNA-Seq (superscript 2). Selected genes were also confirmed by qRT-PCR from (Overhage et al., 2008) (superscript 3), Additional mutants in genes showing no evidence of dysregulation (gmd and rmd) but belonging to operons containing dysregulated genes were also tested. 17 additional mutants are described in Table A3. 39 a Two mutants showed minimal swarming at tobramycin 1 μg/ml but grew better than WT at 2 μg/ml. 40 deficiencies in swarming motility in the absence of antibiotic were excluded from testing as they would appear supersusceptible due to their lack of swarming ability, rather than true susceptibility. A comprehensive description of the resistome under planktonic conditions has been published, with mutations in 135 genes leading to adaptive resistance to tobramycin (Schurek et al., 2008). Interestingly, there were a moderate number of overlaps with the genes identified here as being likely involved in adaptive resistance, prominently including genes involved in membrane energization (ccoO, cytochrome c oxidase), LPS biosynthesis genes (wbpW and its operon wbpZ-rmd), nitrous oxide metabolism where the nosZDF genes were 16.0 to 18.6 fold downregulated, and a major facilitator superfamily transporter, PA5530, that mediates α-ketoglutarate transport (Lundgren et al., 2014). In addition to these there were some novel resistome genes previously described as being involved in susceptibility/resistance to other antibiotics including a large phage/pyocin operon (PA0613-PA0641), which has been implicated in susceptibility to ciprofloxacin (Brazas & Hancock, 2005). Similarly a cup fimbriae biosynthesis operon (cupA1-3) was identified that includes a cyclic-GMP phosphodiesterase previously implicated in regulation of flagella, chemotaxis, type III secretion, and a TolC-like efflux protein (PA2133/fcsR; (Rossello et al., 2017)). CupA1 (implicated in ceftazidime susceptibility) was identified from the resistome study (Alvarez-Ortega et al., 2010); whereas CupA3 (β-lactam and ciprofloxacin resistance) was identified in other studies (Dötsch et al., 2009). Other genes included PA3670, a component of an ABC transport system, that was implicated in susceptibility to β-lactams, levofloxacin and trimethoprim-sulfamethoxazole (identified from (Dötsch et al., 2009)). PA3836, another ABC transport protein involved in ciprofloxacin resistance was identified in (Breidenstein et al., 2008). Lastly, a carbapenemase-expressing gene (PA5542 (Fajardo et al., 2014)), the mutant in which was supersusceptible to β-lactams, was identified from (Fajardo et al., 2008). Thus resistance under swarming conditions involved both canonical/known tobramycin resistance genes, as well as novel genes. Two mutants prtN and wbpW were selected for study in greater detail, since they represented larger gene groups (the pyocins and LPS biosynthetic operon) with a uniform direction of regulation and phenotype. PrtN was of particular interest since it is a regulator and could potentially affect the expression of many genes. The antibiotic susceptibility phenotypes of prtN and wbpW were confirmed using both the disc diffusion and agar dilution methods (Figure 3-3, Figure 3-4) and their appropriate dysregulation of gene expression under swarming conditions was confirmed using qRT-PCR (i.e. prtN and wbpW were downregulated by 2.6±0.8 and 7.4±2.8 fold). 41 Figure 3-3. Antibiotic susceptibility of PA14 mutants under swarming conditions using the disc diffusion method at 0.5% agar. Statistically significant differences were determined by paired t test. n ≥ 4. Figure 3-4. Agar dilution method for determining the swarming inhibitory concentration (IC) of PA14 mutants at 0.5% agar. A) tobramycin swarming IC = 1 μg/ml B) trimethoprim IC = 10 μg/ml C) tobramycin. n ≥ 3. 3.5 A mutant in wbpW was resistant to tobramycin and had decreased membrane permeability Under swarming conditions, a mutant in wbpW, GDP-mannose pyrophosphorylase, an enzyme involved in common polysaccharide antigen (CPA) synthesis, was twofold more resistant to tobramycin (Figure 3-3, Figure 3-4, Table 3-2, Table A4). There are two forms of O antigen in P. aeruginosa LPS termed CPA and O-specific antigen (OSA). The mutant in wbpW was complemented to normal susceptibility by reintroducing wbpW in a low copy plasmid (Figure 3-5B). We have previously shown in P. aeruginosa that polycationic aminoglycosides, such as 42 tobramycin, are taken up across the outer membrane via the self-promoted uptake system (Hancock et al., 1981). The concept of self-promoted uptake is that polycationic antibiotics interact with divalent cation binding sites on outer membrane surface LPS, causing disruption of these sites (since they are more bulky than the native divalent cations Mg2+ and Ca2+) and thus promote the uptake of the polycationic antibiotic. This membrane disruption can be probed using the fluorophor 1-N-phenyl-napthylamine (NPN). NPN is a dye that is normally excluded by wild type P. aeruginosa and is weakly fluorescent in aqueous media but fluoresces strongly when it enters the hydrophobic interior of the outer membrane (Schurek et al., 2008); thus its uptake into bacterial membranes is an indicator of membrane permeabilization by tobramycin. In the NPN assay, after addition of tobramycin, the wbpW mutant had decreased membrane permeabilization, consistent with its reduced susceptibility, and this was complemented in the wbpW+ strain (Figure 3-6) and is thus the likely cause of tobramycin resistance. Figure 3-5. Complementation of swarming antibiotic susceptibility phenotypes for A) prtN B) wbpW. All strains were transformed with either the respective empty vector (WT and mutants) or a vector with insert (complemented (+) strains). n ≥ 3. 3.6 Mutation of prtN induced resistance to tobramycin and trimethoprim The mutant in the gene prtN, the positive regulator of pyocin, showed partial resistance to both tobramycin and trimethoprim under swarming conditions (Figure 3-3, Figure 3-4, Table 3-2, Table A4). Antibiotic susceptibility was restored by reintroducing prtN in an arabinose-inducible construct (pHERD20T) (Figure 3-5A). Success with other vectors was limited due to lack of plasmid stability when prtN was constitutively expressed (data not shown). These results indicated that swarming cells might increase antibiotic resistance by downregulating a process regulated by 43 PrtN, such as the biologically costly production of pyocins, also termed genotoxic stress (Penterman et al., 2014). Consistent with the latter explanation, mutants in several genes downstream of, and regulated by PrtN, namely PA0613-PA0641, were also tested for antibiotic susceptibility under swarming conditions and found to be resistant to tobramycin, although unlike prtN no significant differences were observed in trimethoprim susceptibility (Table 3-2, Table A3 and data not shown). Figure 3-6. A wbpW mutant had reduced membrane permeabilization. Swarm cells were harvested and treated where indicated with a) NPN and b) tobramycin. n = 3. 3.7 Antibiotic susceptibility was affected by growth conditions The mutants were also assayed under standard broth dilution MIC conditions in the rich medium LB and the minimal medium BM2 glucose (Table A5). In contrast to their effect on susceptibility under swarming conditions, the mutants showed little difference in MIC compared to wild type, with the exception of prtN that was two-fold more resistant to trimethoprim in LB. This indicated that growth conditions had an important effect on antibiotic resistance and suggests that standard screening methods might miss such phenotypes. The tobramycin resistance phenotype was much more pronounced under swarming conditions (Table 3-2, Figure 3-3, Figure 3-4) compared to standard MICs (Table A5). When tested in a standard MIC, the prtN and wbpW mutants showed no increase in MIC (Table A5). Other representative mutants were also tested but showed no difference under standard MIC conditions (Table A6). Nevertheless, some of the genes in Table 3-2 likely do play a role beyond the swarming condition, since they were previously shown to be part of the tobramycin resistome (including ccoO, wbpW and its operon wbpZ-rmd, nosZDF and PA5530) (Schurek et al., 2008). It seems 44 possible that some genes may confer resistance specifically under swarming conditions, whereas others may confer resistance under multiple conditions. 3.8 Subinhibitory tobramycin treatment under swarming conditions Swarming bacteria treated with the subinhibitory tobramycin dose of 0.5 μg/ml were compared to untreated swarm cells by RNA-Seq, since this was relevant to the increased resistance of cells swarming in the presence of tobramycin. Differential expression analysis revealed 224 genes, 186 of which were downregulated (Table A1). The downregulated genes included many virulence factors, particularly in T3SS and pyoverdine genes (Table A1), indicating a secondary benefit of tobramycin treatment, even in the absence of killing. Amongst the upregulated genes was the efflux pump mexXY, a known mechanism of aminoglycoside resistance (Table 3-3) (Aires et al., 1999). Eight ribosomal proteins and translation factors were also downregulated (efp, infA, infC, rplU, rpmB, rpsG, rpsS, and PA5492), as well as four genes in an LPS biosynthetic operon (wzz, wbpA, wbpI, and wbpL) (Table 3-3). Since pyocins were already implicated in swarming-mediated antibiotic resistance, it was interesting that the genes tolAR, which are involved in the uptake of pyocin AR41, were downregulated (Table 3-3) (Dennis et al., 1996). Table 3-3. Selected genes that were differentially expressed upon tobramycin treatment under swarming conditions. LocusTag PAO1 Name Product Name padj FC PA14_08810 PA4267 rpsG 30S ribosomal protein S7 2.1E-02 -1.7 PA14_08890 PA4259 rpsS 30S ribosomal protein S19 2.8E-02 -1.8 PA14_23360 PA3160 wzz O-antigen chain length regulator 6.9E-03 -1.8 PA14_23370 PA3148 wbpI putative UDP-N-acetylglucosamine 2-epimerase 2.6E-02 -1.7 PA14_23380 PA3159 wbpA UDP-N-acetyl-D-mannosaminuronate dehydrogenase 1.8E-02 -2.1 PA14_23460 PA3145 wbpL putative group 4 glycosyl transferase 2.7E-02 -1.8 PA14_27210 PA2851 efp elongation factor P 2.0E-02 -1.6 PA14_28660 PA2743 infC translation initiation factor IF-3 1.3E-02 -1.9 PA14_30240 PA2619 infA translation initiation factor IF-1 3.5E-03 -1.5 PA14_38380 PA2020 mexZ putative transcriptional regulator 2.8E-02 1.6 PA14_38395 PA2019 mexX periplasmic multidrug efflux lipoprotein precursor 3.5E-22 8.5 PA14_38410 PA2018 mexY multidrug efflux protein 1.3E-36 8.0 PA14_38430 PA2016 liuR regulatory gene of gnyRDBHAL cluster, GnyR 7.8E-03 -2.3 PA14_41575 PA1776 sigX RNA polyermase sigma factor 1.4E-02 -1.6 PA14_42390 PA1713 exsA transcriptional regulator 1.5E-07 -2.4 PA14_42460 PA1707 pcrH regulatory protein 2.7E-02 -1.8 PA14_45950 PA1431 rsaL regulatory protein 1.7E-02 -1.8 PA14_51730 PA0971 tolA membrane transport protein 2.4E-03 -1.6 PA14_51740 PA0970 tolR membrane transport protein 1.8E-02 -1.5 45 LocusTag PAO1 Name Product Name padj FC PA14_52570 PA0905 rsmA carbon storage regulator 8.8E-03 -1.9 PA14_55160 PA0707 toxR transcriptional regulator 5.8E-05 -4.4 PA14_56070 PA4315 mvaT transcriptional regulator, P16 subunit 2.6E-02 -1.5 PA14_60460 PA4568 rplU 50S ribosomal protein L21 4.0E-02 -1.6 PA14_70190 PA5316 rpmB 50S ribosomal protein L28 1.6E-02 -1.6 PA14_72210 PA5471 armZ hypothetical protein 2.3E-19 3.4 PA14_72480 PA5492 ribosome biogenesis GTP-binding protein YsxC 3.9E-02 -1.6 Dysregulated transcriptional regulators included two regulators of virulence factor production (exsA and toxR), mexZ, the repressor of mexXY (Matsuo et al., 2004), liuR, a regulator of the leucine/isovalerate utilization pathway (Díaz-Pérez et al., 2018), sigX, an extracytoplasmic function sigma factor involved in the regulation of the major porin OprF, antibiotic resistance, T3SS, swarming motility, biofilm formation and carbon catabolite repression (Blanka et al., 2014; Fléchard et al., 2018; Gicquel et al., 2013), rsaL, a repressor of virulence gene expression and QS (De Kievit et al., 1999; Rampioni et al., 2006), mvaT, a global regulator of QS, virulence and swarming motility (Diggle et al., 2002), and rsmA, a post-transcriptional regulator of multidrug efflux, motility, QS, T6SS and virulence (Allsopp et al., 2017; Burrowes et al., 2006; Mulcahy et al., 2008) (Table 3-3). Interestingly, the mexXY operon has been shown to be upregulated in a SigX mutant, along with the repressor mexZ, providing more evidence that upregulation of mexXY can be independent of mexZ (Blanka et al., 2014). Resistome mutants were also tested from the tobramycin vs. untreated RNA-Seq. Although some mutants could not be tested due to deficiencies in swarming motility, it was shown that mutants in tagR1 (a type VI secretion protein (HSI-I) with a sulfatase-modifying domain associated with the outer membrane (Casabona et al., 2013; Winsor et al., 2011)), pvdJ (peptide synthetase of pyoverdine) and hisE (involved in histidine biosynthesis (Winsor et al., 2011)) were resistant to tobramycin under swarming conditions and downregulated upon tobramycin treatment (Table 3-2). Interestingly, PvdQ, an acylase of the QS molecule 3-oxo-C12-HSL, also involved in pyoverdine synthesis, has already been shown to play a role in the antibiotic resistance of swarming cells (Wang et al., 2013). The mechanism of PvdQ-mediated resistance is via decreased membrane permeability (Wang et al., 2013). 3.9 Comparison of RNA-Seq experiments The two RNA-Seq experiments were also compared to determine what degree of overlap existed. Nintey genes were found in common between the two experiments (Figure A2). While this represented a substantial portion of the total genes dysregulated upon tobramycin treatment, 46 the majority of the 90 genes were oppositely regulated (Figure A3), with 51 genes that were downregulated upon tobramycin treatment but upregulated in swarm vs. swim. These 51 genes included iron acquisition factors (pyoverdine and phenazine) as well as T3SS genes. This indicates that the response to subinhibitory tobramycin was distinct from the swarm vs. swim comparison. 3.10 Discussion In this study, 41 mutants were characterized as tobramycin resistant under swarming conditions. This lends support to a previous study that showed that the tobramycin resistome is quite large (135 genes) with many mutants (including 57 in energy metabolism) showing low level resistance (Schurek et al., 2008). Not all genes overlapped between this prior study and the current investigation, indicating that there may be distinct mechanisms of resistance in swarm cells as compared to broth-grown cells. One mutant demonstrating complementable tobramycin and trimethoprim resistance and equivalent downregulation in the wild type under swarming conditions was in the prtN gene, that encodes a positive regulator of pyocin production under control of the prtR repressor. Under UV stress, RecA causes the autocleavage of PrtR, leading to the expression of prtN and production of pyocins (Matsui et al., 1993). A lysis cassette is also induced, including holin-like and lysozyme-like genes that cause cell lysis and the release of pyocin (Penterman et al., 2014). Interestingly, a mutation inactivating the catalytic activity of PrtR resulted in increased resistance to aminoglycosides, ciprofloxacin, and UV stress (Penterman et al., 2014), which was attributed to effects on genotoxic stress, while mutants in the phage tail-like bacteriocins regulated by prtRN were resistant to ciprofloxacin (Brazas & Hancock, 2005; Breidenstein et al., 2008). In other studies, a mutant in prtN was found to be resistant to piperacillin, cefotaxime and trimethoprim-sulfamethoxazole (Dötsch et al., 2009). Overall, the downregulation of the phage-tail like bacteriocins in the cluster of genes from PA0613-PA0641 was a striking feature observed in the transcriptome of swarming cells ((Overhage et al., 2008) and the RNA-Seq study reported here). Mutating the positive regulator for these genes, prtN, resulted in resistance to both tobramycin and trimethoprim under swarming conditions, an effect consistent with the multiple resistance of the catalytically inactive (autocleavage-resistant) repressor prtR mutant (Penterman et al., 2014). Though pyocins play a role in intra- and interspecies competition, activation of these genes clearly incurs negative consequences for the cell. Furthermore, self-killing activity in a portion of the community with damaged DNA may be beneficial to the population as a whole (Chang et al., 2005). 47 Trimethoprim inhibits dihydrofolate reductase, depleting the cell of tetrahydrofolate, a one-carbon donor for a number of important metabolites in the cell including the nucleotide thymidylate (Sangurdekar et al., 2011). Therefore, as a consequence of trimethoprim treatment, DNA synthesis is inhibited and the DNA damage response is induced (Sangurdekar et al., 2011). Since the DNA damage response also leads to the activation of PrtN and induction of pyocin genes (Matsui et al., 1993; Penterman et al., 2014), it would seem reasonable that a mutant in prtN is resistant to trimethoprim. An association between aminoglycoside resistance and the regulation of pyocins has previously been shown (Penterman et al., 2014), although the mechanism for this is less clear. It is also possible that other genes regulated by prtN might be responsible. Another interesting mutant was in the gene encoding WbpW, which catalyzes the conversion of mannose-1-phosphate to GDP-D-mannose (Byrd et al., 2015). Interestingly, GDP-D-mannose can be used in the synthesis of alginate, but is also utilized by Rmd for the synthesis of CPA LPS (Byrd et al., 2015). Mutants in genes involved in the synthesis of LPS have previously been shown to lead to tobramycin resistance, due to the reduced ability of tobramycin to cross the outer membrane via self-promoted uptake (Schurek et al., 2008). The resistance of the wbpW mutant was complemented by reintroducing wbpW in a low copy number plasmid (Figure 3-5B), and furthermore the wbpW mutant had reduced membrane permeability (Figure 3-6). While wbpW was downregulated, low levels of expression could allow for a reduced amount of CPA LPS, rather than a complete deficiency. Mutants in wbpW also have reduced but not completely absent CPA LPS due to the presence of two wbpW homologs that are bifunctional enzymes (algA and pslB) (King et al., 2009). Over time, strains unable to produce O antigen come to predominate in the lungs of cystic fibrosis patients (Hancock et al., 1983), suggesting that LPS alterations might be one mechanism by which P. aeruginosa evades host recognition and adaptive immune responses. In addition, it has been shown that lipid A modifications are common and constitute a mechanism of immune evasion (Cigana et al., 2009). In another study, the loss of OSA was associated with increased T3SS activity (facilitating acute infections), while loss of any O antigen resulted in increased lung damage in vivo (Augustin et al., 2007). Together these studies suggest that a reduction in CPA LPS might be beneficial to P. aeruginosa persistence in vivo. The two RNA-Seq experiments (swarm vs. swim and tobramycin vs. untreated) also showed that there is an important distinction between the inherent resistance of swarm cells and the inducible response of swarm cells to the antibiotic tobramycin. In the absence of antibiotic, more than 1,500 genes were dysregulated, and antibiotic resistance is likely a cumulative effect of 48 many different genes, although multidrug efflux did not appear to play a major role, as found in another study (Lai et al., 2009). In contrast, in the presence of tobramycin, fewer genes were dysregulated but an obvious mechanism of tobramycin resistance emerged in the overexpression of mexXY. Thus it appears there are genetic factors that enable swarming cells to resist antibiotics in the native swarming state, but also specific and distinct mechanisms of resistance that are induced upon antibiotic exposure. Perhaps a key role of swarming-mediated resistance genes is to allow sufficient time for more established mechanisms, such as multidrug efflux, to take effect. Upon tobramycin treatment, downregulation of the genes wzz, wbpA, wbpI, and wbpL (Table 3-3) could also contribute to tobramycin resistance, although these genes were not identified in resistome studies (Schurek et al., 2008). As these genes, like wbpW, are involved in LPS biosynthesis, the resulting alterations in LPS could potentially result in tobramycin resistance. However, the mutant in wzz was not resistant to tobramycin, and mutants in wbpAIL were either not available or deficient for swarming motility (data not shown), therefore firm conclusions could not be drawn. In both the absence and presence of tobramycin, ribosomal proteins and translation factors were downregulated under swarming conditions (Table 3-3, Table A1). Since aminoglycosides, as well as many other antibiotic classes including macrolides, chloramphenicol and tetracycline, target the bacterial ribosome, a decrease in translational activity could confer some level of resistance. However, since ribosomes are encoded by essential genes, this hypothesis is difficult to test. During swarming motility, many genes are dysregulated, resulting in a hardy, multiple antibiotic-resistant phenotype associated with increased virulence factor production and iron scavenging. Downregulation of pyocin genes could allow swarming cells to circumvent harmful agents, leading to greater resilience in the face of antibiotic treatment. Downregulation of wbpW could result in reduced uptake of tobramycin. Upon treatment with tobramycin, the multidrug efflux pump MexXY was strongly upregulated. The combination of these factors, plus other as-yet-undetermined resistance factors, results in a state of (reversible) multiple antibiotic resistance during swarming motility in P. aeruginosa. 49 Chapter 4: Influence of the sRNA PA0805.1 on motility and virulence 4.1 Introduction Swarming motility is a highly regulated process and previous studies have shown that 18 regulators are dysregulated under swarming conditions (Overhage et al., 2008), while mutants in 35 regulators have alterations in swarming motility (Yeung et al., 2009). However, alternative means of regulation have not been well investigated, including post-transcriptional and translational regulation, and the modification or degradation of proteins. sRNAs are non-coding RNA species involved in post-transcriptional regulation, and are rapidly evolving (Gómez-Lozano et al., 2015). sRNAs can be classified in two categories: cis and trans-encoded. In many bacterial species, the RNA chaperone Hfq is required to stabilize sRNA-mRNA interactions (Gottesman & Storz, 2011), although Pseudomonas exhibits other more selective RNA-binding proteins such as Crc and RsmA. Interestingly, prior to 2012 only 44 sRNAs had been identified in P. aeruginosa (Gómez-Lozano et al., 2015), but subsequent RNA-Seq studies have identified hundreds of potential intergenic sRNAs (Gómez-Lozano et al., 2012; Wurtzel et al., 2012). Nevertheless, few of these novel sRNAs have been characterized, leaving a large field to be explored. Prior research in our lab identified 20 sRNA species that were dysregulated under swarming conditions (Gill et al., 2018). One of these, sRNA PA0805.1, overlapping previously-identified sRNAs pant89 (Gómez-Lozano et al., 2012) and PA14sr119/120 (Wurtzel et al., 2012), was studied here in detail by genetic manipulation, phenotypic screens and omic comparisons. 4.2 Overexpression of PA0805.1 resulted in decreased motility Specific qRT-PCR analysis demonstrated that the transcript for PA0805.1 was upregulated in swarming motility clones, cf. swimming cells by 5.0 ± 1.7 fold. In contrast, it was downregulated in biofilm cells by -4.8 ± -3.8 fold (Gill et al., 2018). Since biofilms are considered a sedentary lifestyle typical of chronic infections while swarming is considered more typical of acute infections, this ~25-fold difference in expression levels indicated that sRNA PA0805.1 had the potential to discriminate or even act as a switch between chronic and acute modes of infection. To investigate this further I overexpressed sRNA PA0805.1, since sRNAs often act in a suppressive manner. The PA0805.1 gene was cloned and inserted after the araC promoter in the arabinose-inducible pHERD20T vector, and transformed into PAO1 H103 WT. PA0805.1 was overexpressed after induction with arabinose by 28.1 ± 1.9 fold under swarming conditions (BM2 glycerol). 50 At the time of the assay, arabinose was added to induce expression. Motility assays showed that PA0805.1 overexpression had anti-motility effects resulting in partial reductions in each of swarming (reduced to 59±6% of EV), swimming (51±10%) and twitching (61±3%) motility (Figure 4-1). Figure 4-1. Motility assays revealed that overexpression of PA0805.1 was generally anti-motility. 1% arabinose was used to induce expression and statistically significant differences were determined using paired Student’s t test. n ≥ 3. 4.3 Overexpression of PA0805.1 resulted in increased cytotoxicity against HBE cells and increased tobramycin resistance The PA0805.1 overexpression strain was also tested for cytotoxicity against HBE cells 51 (Figure 4-2). Similar to the motility assays, overexpression of PA0805.1 resulted in a consistent and statistically significant phenotype, with an increase of 15% in cytotoxicity as compared to the EV strain. Growth curves performed in BM2 glycerol with 1% arabinose showed little difference between strains (Figure A4). Interestingly the PA0805.1 overexpression strain was resistant to tobramycin even in the absence of arabinose under swarming conditions (Figure 4-3). In the presence of arabinose, the anti-motility effect of PA0805.1 made it difficult to assess any antibiotic phenotypes under swarming conditions. MIC assays performed in the equivalent medium in microtitre trays showed little difference (Table A7). Figure 4-2. Cytotoxicity assay of the PA0805.1 overexpression strain revealed that induction of PA0805.1 led to increased cytotoxicity against HBE cells. Statistically significant differences were determined using paired Student’s t test. n ≥ 3. Figure 4-3. PA0805.1 overexpression led to swarming-dependent tobramycin resistance as assessed in BM2 glucose swarm plates with no arabinose and supplemented where indicated with tobramycin at 1 μg/ml. n = 3. 4.4 Overexpression of PA0805.1 resulted in broad protein and transcriptional changes including 118 regulatory factors To investigate these phenotypes further, I performed proteomics and RNA-Seq under 52 swarming conditions in the presence of arabinose compared to the EV control. Proteomics identified 925 proteins with significantly different abundance in the PA0805.1 overexpression strain vs. EV, including 435 with increased abundance, and 490 with decreased abundance (Table A2). In addition, there were 1121 DE genes revealed by RNA-Seq, with 401 downregulated and 720 upregulated. Amongst the DE genes and proteins with differential abundance, 118 transcriptional regulators, two-component systems, sigma and anti-sigma factors were found (Table 4-1). Of these, 42 were found uniquely in the proteome and the equivalent genes did not demonstrate a change in transcription (shown with bold locus tag in Table 4-1). These changes thus might explain in part the rather substantial transcriptional dysregulation observed. These regulators were of particular interest since the mechanism of sRNA regulation is post-transcriptional, and therefore they would provide candidates for direct sRNA regulation. Many important regulators involved in diverse processes such as virulence, antimicrobial resistance, QS, and carbon metabolism were represented on the list of regulators dysregulated at the level of protein expression, including CbrB, LasR, MvaT, ParS, PsrA, RpoN, and Vfr. Other regulators with altered protein expression that were upstream of the widespread changes in motility, adherence and virulence factors described below, included FleQ, PilS, AlgU, and AlgB (Figure 4-4). Interestingly there were also three amino acid biosynthetic regulators, ArgR, BkdR and CysB. Table 4-1. Selected genes of interest with differential expression in the PA0805.1 overexpression strain as compared to EV by RNA-Seq and/or proteomics. Categories of interest include regulators, multidrug efflux, motility, LPS biosynthesis, type VI secretion and other virulence factors. Cutoffs used were p/padj ≤ 0.05 and for RNA-Seq, FC ≥ 1.5. Locus Tag Name Product Name RNA-Seq Proteomics FC padj FC p Transcriptional regulators, two-component systems, sigma and anti-sigma factors PA0150 anti-sigma factor -1.71 2.9E-02 PA0178 probable two-component sensor 1.83 8.5E-06 PA0179 probable two-component response regulator 2.02 2.0E-06 PA0268 probable transcriptional regulator 1.52 3.0E-03 PA0416 chpD probable transcriptional regulator -1.96 9.0E-07 PA0471 fiuR regulatory protein -1.80 4.6E-04 PA0472 fiuI regulatory protein -2.03 4.2E-04 PA0479 probable transcriptional regulator 1.57 2.5E-04 PA0535 probable transcriptional regulator -1.69 1.2E-03 PA0612 ptrB repressor 2.52 6.3E-04 PA0652 vfr transcriptional regulator -1.17 3.9E-04 PA0757 probable two-component sensor -1.53 9.9E-04 PA0762 algU sigma factor 1.23 9.5E-03 PA0763 mucA anti-sigma factor 1.68 5.7E-05 53 Locus Tag Name Product Name RNA-Seq Proteomics FC padj FC p PA0893 argR transcriptional regulator 1.17 3.8E-03 PA0929 two-component response regulator -1.68 1.9E-03 PA0930 two-component sensor -1.61 1.5E-02 PA0942 probable transcriptional regulator 1.54 1.2E-03 PA0964 pmpR pqsR-mediated PQS regulator -1.64 8.6E-08 -1.18 3.2E-04 PA1097 fleQ transcriptional regulator 1.18 5.0E-03 PA1099 fleR two-component response regulator 1.52 3.9E-08 PA1136 probable transcriptional regulator 1.75 1.4E-04 PA1157 probable two-component response regulator 1.17 5.5E-04 PA1315 probable transcriptional regulator 1.08 2.5E-02 PA1363 ECF sigma factor -1.69 2.4E-03 PA1397 probable two-component response regulator -1.68 5.3E-05 PA1430 lasR transcriptional regulator -1.28 4.9E-02 PA1431 rsaL regulatory protein 1.70 6.8E-04 1.25 8.3E-03 PA1490 probable transcriptional regulator 1.16 2.3E-02 PA1504 probable transcriptional regulator -1.15 1.7E-03 PA1619 probable transcriptional regulator -1.50 1.8E-03 PA1705 pcrG regulator in type III secretion -9.28 5.4E-12 PA1707 pcrH regulatory protein -8.60 4.9E-26 PA1713 exsA transcriptional regulator -4.77 6.3E-62 PA1754 cysB transcriptional regulator 1.21 3.2E-02 PA1785 nasT regulatory protein 1.76 3.3E-02 -1.26 1.3E-04 PA1798 parS two-component sensor 1.17 2.3E-02 PA1859 probable transcriptional regulator 1.55 5.8E-04 PA1945 probable transcriptional regulator 1.53 3.6E-03 PA2082 kynR regulatory protein 1.18 5.2E-03 PA2126 cgrC CupA gene regulator C 2.18 1.2E-05 PA2126.1 cgrB CupA gene regulator B 1.78 7.6E-03 PA2127 cgrA CupA gene regulator A 1.80 4.3E-06 PA2177 probable sensor/response regulator hybrid 1.77 2.5E-04 PA2227 vqsM AraC-type transcriptional regulator 1.77 3.3E-06 PA2246 bkdR transcriptional regulator 1.06 2.1E-02 PA2258 ptxR transcriptional regulator 2.15 1.2E-05 PA2259 ptxS transcriptional regulator 1.82 1.6E-04 PA2273 soxR regulatory protein 2.38 1.5E-09 PA2276 probable transcriptional regulator 3.41 2.8E-38 1.27 9.3E-04 PA2277 arsR regulatory protein 2.28 1.9E-06 PA2376 probable transcriptional regulator 1.56 1.4E-03 PA2388 fpvR regulatory protein -1.30 1.2E-02 PA2467 foxR anti-sigma factor -1.62 1.3E-02 PA2523 czcR regulatory protein 2.32 4.9E-08 PA2524 czcS regulatory protein 2.24 1.2E-04 PA2571 probable two-component sensor 2.02 3.1E-06 PA2572 probable two-component response regulator 1.86 8.1E-06 1.29 1.4E-02 PA2577 probable transcriptional regulator 1.70 3.4E-05 54 Locus Tag Name Product Name RNA-Seq Proteomics FC padj FC p PA2696 probable transcriptional regulator 1.53 4.5E-03 PA2846 probable transcriptional regulator 1.64 7.3E-03 PA2849 ohrR regulatory protein 1.63 2.2E-05 1.11 2.8E-02 PA2889 atvR atypical virulence-related response regulator 1.55 7.7E-04 PA3006 psrA transcriptional regulator 1.09 3.4E-02 PA3007 lexA repressor protein 1.84 5.6E-23 1.10 6.1E-03 PA3034 probable transcriptional regulator -1.10 1.8E-02 PA3122 probable transcriptional regulator 1.17 3.0E-03 PA3174 hutR regulatory protein -1.66 1.8E-02 PA3225 transcriptional regulator 1.14 1.6E-02 PA3271 probable two-component sensor 1.09 1.9E-02 PA3341 probable transcriptional regulator 1.23 4.2E-03 PA3346 hsbR HptB-dependent secretion and biofilm regulator 1.78 3.6E-09 1.22 1.2E-02 PA3347 hsbA HptB-dependent secretion and biofilm anti anti-sigma factor 1.66 4.9E-05 PA3477 rhlR transcriptional regulator 1.77 1.9E-05 1.17 1.9E-02 PA3622 rpoS sigma factor 1.75 1.4E-09 1.17 5.1E-03 PA3689 probable transcriptional regulator 1.06 2.4E-02 PA3702 wspR regulatory protein -1.08 1.4E-02 PA3899 fecI regulatory protein -1.73 1.3E-02 PA3946 rocS1 two-component sensor 1.74 4.3E-07 PA3947 rocR regulatory protein 1.57 7.5E-06 PA4070 probable transcriptional regulator 1.52 3.3E-02 PA4074 probable transcriptional regulator 2.20 2.7E-03 PA4080 probable response regulator 1.54 5.3E-04 PA4101 bfmR regulatory protein -1.16 5.8E-03 PA4157 probable transcriptional regulator 1.06 4.5E-02 PA4203 nmoR regulatory protein 1.50 4.6E-02 PA4288 probable transcriptional regulator 2.20 1.9E-07 PA4293 pprA two-component sensor 2.22 5.0E-16 1.31 3.8E-03 PA4296 pprB two-component response regulator 1.82 6.4E-07 1.12 1.1E-03 PA4315 mvaT transcriptional regulator MvaT, P16 subunit 1.26 2.6E-02 PA4367 bifA regulatory protein -1.10 2.6E-02 PA4396 two-component response regulator -2.15 4.8E-11 PA4462 rpoN RNA polymerase sigma-54 factor 1.16 3.2E-02 PA4464 ptsN nitrogen regulatory IIA protein 1.74 1.6E-10 PA4493 roxR regulatory protein 1.26 2.5E-02 PA4546 pilS two-component sensor 1.28 3.1E-03 PA4600 nfxB transcriptional regulator 1.25 4.7E-02 PA4601 morA motility regulator -1.54 1.2E-12 PA4659 probable transcriptional regulator 1.13 1.8E-02 PA4726 cbrB two-component response regulator -1.24 2.5E-04 PA4769 probable transcriptional regulator 1.35 2.8E-02 PA4778 cueR regulatory protein -1.17 6.5E-03 55 Locus Tag Name Product Name RNA-Seq Proteomics FC padj FC p PA4787 probable transcriptional regulator -1.11 8.5E-03 PA4843 gcbA regulatory protein -1.97 4.4E-18 PA4886 probable two-component sensor -1.65 2.3E-02 PA4916 nrtR Nudix-related transcriptional regulator 1.60 1.8E-08 1.18 4.6E-03 PA5117 typA regulatory protein -1.56 2.3E-05 PA5199 amgS regulatory protein -1.08 9.3E-03 PA5200 amgR regulatory protein -1.22 1.8E-02 PA5261 algR alginate biosynthesis regulatory protein 1.57 1.4E-05 PA5274 rnk nucleoside diphosphate kinase regulator -1.53 1.5E-05 -1.26 3.5E-02 PA5293 probable transcriptional regulator 1.05 3.7E-02 PA5301 pauR regulatory protein -1.22 1.7E-02 PA5344 oxyR regulatory protein -1.04 4.5E-02 PA5356 glcC transcriptional regulator 1.74 7.2E-07 PA5380 gbdR regulatory protein 1.58 2.5E-02 PA5483 algB two-component response regulator 1.17 1.4E-02 PA5484 kinB regulatory protein 1.23 2.6E-03 Multidrug efflux systems PA0426 mexB RND multidrug efflux transporter 1.15 1.4E-02 PA2018 mexY RND multidrug efflux transporter 1.79 6.5E-04 PA2019 mexX RND multidrug efflux membrane fusion protein 1.91 4.9E-07 1.53 5.4E-04 PA2020 mexZ negative transcriptional regulator 1.13 4.3E-02 PA2491 mexS probable transcriptional regulator -1.25 2.0E-03 PA2493 mexE RND multidrug efflux membrane fusion protein precursor 1.11 1.2E-02 PA3677 mexJ efflux transporter 1.15 3.7E-02 PA4205 mexG hypothetical protein 1.76 2.0E-14 1.59 9.1E-05 PA4206 mexH probable RND efflux membrane fusion protein 1.71 7.2E-13 1.11 2.8E-02 PA4207 mexI probable RND efflux transporter 1.16 1.3E-03 PA4208 opmD probable outer membrane protein precursor 1.14 4.4E-02 PA4374 mexV RND multidrug efflux membrane fusion protein 1.16 1.1E-02 Motility and related genes PA0020 tsaP T4P secretin-associated protein -1.97 6.8E-11 -1.35 1.0E-03 PA0395 pilT twitching motility protein -1.13 1.4E-03 PA0396 pilU twitching motility protein -1.15 3.9E-04 PA0408 pilG twitching motility protein -2.09 2.8E-17 -1.52 2.5E-03 PA0409 pilH twitching motility protein -2.42 2.2E-29 -1.64 1.2E-02 PA0410 pilI twitching motility protein -2.37 1.1E-16 -1.48 6.8E-04 PA0411 pilJ twitching motility protein -2.76 4.3E-24 -1.49 4.8E-05 PA0412 pilK methyltransferase -2.40 2.3E-19 PA0413 chpA pilus related chemotactic signal transduction system component -2.44 1.9E-33 -1.24 3.8E-06 PA0414 chpB probable methylesterase -2.31 3.1E-24 56 Locus Tag Name Product Name RNA-Seq Proteomics FC padj FC p PA0415 chpC probable chemotaxis protein -2.18 2.0E-13 PA0417 chpE probable chemotaxis protein -2.77 7.8E-04 PA0499 probable pili assembly chaperone 1.87 3.1E-03 PA1077 flgB flagellar basal-body rod protein 1.66 5.3E-11 PA1078 flgC flagellar basal-body rod protein 1.70 5.1E-10 PA1079 flgD flagellar basal-body rod modification protein 1.56 8.1E-09 PA1080 flgE flagellar hook protein 1.58 9.5E-11 PA1081 flgF flagellar basal-body rod protein 1.65 5.1E-11 PA1082 flgG flagellar basal-body rod protein 1.57 4.5E-07 PA1083 flgH flagellar L-ring protein precursor 1.15 2.5E-02 PA1084 flgI flagellar P-ring protein precursor 1.53 1.6E-08 PA1085 flgJ flagellar protein 1.54 2.4E-06 PA1092 fliC flagellin type B 1.55 4.7E-06 PA1094 fliD flagellar capping protein 1.53 4.9E-06 PA1100 fliE flagellar hook-basal body complex protein 1.76 6.3E-08 PA1101 fliF flagella M-ring outer membrane protein precursor 1.52 3.5E-11 PA1103 probable flagellar assembly protein 1.22 2.8E-02 PA1130 rhlC rhamnosyltransferase 2 1.56 5.8E-04 PA1452 flhA flagellar biosynthesis protein 1.28 1.3E-02 PA1461 motD flagellar motor protein 1.12 6.9E-03 PA1822 fimL hypothetical protein -1.13 1.1E-02 PA3350 hypothetical protein 1.62 3.1E-15 1.17 4.2E-03 PA3351 flgM flagellar anti-sigma factor 1.52 1.2E-07 PA3478 rhlB rhamnosyltransferase chain B 2.39 3.0E-04 PA3479 rhlA rhamnosyltransferase chain A 2.55 1.1E-04 PA3526 motY flagellar motor protein 1.60 2.3E-07 PA4085 cupB2 chaperone 1.52 3.7E-02 PA4294 hypothetical protein 2.32 1.4E-20 PA4295 fppA Flp prepilin peptidase A 1.68 9.8E-05 PA4297 tadG putative Tad-like Flp pilus-assembly 1.53 1.1E-02 PA4298 hypothetical protein 2.25 1.9E-07 PA4299 tadD Flp pilus assembly lipoprotein 1.89 1.4E-06 1.23 3.0E-03 PA4300 tadC Flp pilus assembly protein TadC 1.78 1.2E-05 1.29 8.1E-03 PA4301 tadB Flp pilus assembly protein 1.95 1.5E-06 PA4302 tadA ATPase 1.93 2.8E-08 1.20 5.0E-02 PA4303 tadZ pilus assembly protein 2.09 5.3E-11 1.22 1.4E-02 PA4304 rcpA secretin 1.97 1.3E-10 PA4305 rcpC Flp pilus assembly protein 2.12 8.4E-10 PA4306 flp type IVb pilin 1.84 1.4E-03 PA4525 pilA type 4 fimbrial precursor -1.64 2.0E-04 -1.30 3.4E-03 PA4527 pilC type 4 fimbrial biogenesis protein (put. pseudogene) -1.21 7.2E-04 PA4528 pilD type 4 prepilin peptidase -1.84 1.1E-08 PA4550 fimU type 4 fimbrial biogenesis protein -1.74 2.0E-06 -1.11 4.9E-02 57 Locus Tag Name Product Name RNA-Seq Proteomics FC padj FC p PA4551 pilV type 4 fimbrial biogenesis protein -1.99 9.3E-07 -1.10 1.7E-02 PA4552 pilW type 4 fimbrial biogenesis protein -1.72 9.2E-08 -1.22 2.4E-03 PA4553 pilX type 4 fimbrial biogenesis protein -1.63 1.4E-04 PA4554 pilY1 type 4 fimbrial biogenesis protein -1.59 9.6E-08 PA4555 pilY2 type 4 fimbrial biogenesis protein -1.51 6.9E-05 -1.34 7.3E-03 PA4556 pilE type 4 fimbrial biogenesis protein -1.64 9.4E-03 PA4648 cupE1 pilin subunit 2.56 2.7E-16 PA4649 cupE2 pilin subunit 2.06 1.8E-12 PA4650 cupE3 pilin subunit 1.91 1.9E-06 PA4651 cupE4 pilin assembly chaperone 2.00 5.2E-20 1.28 1.3E-03 PA4652 cupE5 fimbrial usher protein 1.66 1.7E-07 PA4653 cupE6 adhesin-like protein 1.69 1.1E-06 PA4953 motB chemotaxis protein -1.20 3.2E-03 PA4959 fimX diguanylate cyclase/phosphodiesterase -1.54 2.7E-07 PA5040 pilQ type 4 fimbrial biogenesis outer membrane protein -1.63 8.0E-11 -1.38 4.7E-03 PA5041 pilP type 4 fimbrial biogenesis protein -1.70 1.2E-08 PA5042 pilO type 4 fimbrial biogenesis protein -1.67 2.6E-12 -1.26 9.0E-04 PA5043 pilN type 4 fimbrial biogenesis protein -1.70 2.1E-10 1.77 6.6E-04 PA5044 pilM type 4 fimbrial biogenesis protein -1.53 1.5E-10 -1.27 5.6E-03 LPS biosynthesis PA3141 wbpM nucleotide sugar epimerase/dehydratase 1.25 8.3E-03 PA3145 wbpL glycosyltransferase 1.17 5.7E-03 PA3147 wbpJ probable glycosyl transferase 1.14 1.8E-03 PA3148 wbpI UDP-N-acetylglucosamine 2-epimerase 1.23 7.0E-04 PA3150 wbpG LPS biosynthesis protein 1.13 2.0E-02 PA3151 hisF2 imidazoleglycerol-phosphate synthase, cyclase subunit 1.13 1.1E-02 PA3152 hisH2 glutamine amidotransferase 1.08 1.8E-02 PA3155 wbpE UDP-2-acetamido-2-dideoxy-d-ribo-hex-3-uluronic acid transaminase 1.53 4.8E-11 PA3156 wbpD UDP-2-acetamido-3-amino-2,3-dideoxy-d-glucuronic acid N-acetyltransferase 1.18 4.3E-04 PA3158 wbpB UDP-2-acetamido-2-deoxy-d-glucuronic acid 3-dehydrogenase 1.14 5.7E-04 PA3159 wbpA UDP-N-acetyl-d-glucosamine 6-Dehydrogenase 1.21 6.2E-05 PA3160 wzz O-antigen chain length regulator 1.27 2.3E-02 PA4378 warB lipopolysaccharide kinase 1.94 5.4E-04 PA5448 wbpY glycosyltransferase -1.56 1.2E-03 PA5449 wbpX glycosyltransferase -1.62 3.8E-09 PA5452 wbpW phosphomannose isomerase/GDP-mannose -1.13 3.0E-02 PA5453 gmd GDP-mannose 4,6-dehydratase -1.12 3.1E-02 PA5454 rmd oxidoreductase -1.25 4.1E-03 Type VI secretion system 58 Locus Tag Name Product Name RNA-Seq Proteomics FC padj FC p PA0070 tagQ1 type VI secretion-associated lipoprotein 1.22 2.2E-02 PA0071 tagR1 FGE-sulfatase domain-containing protein 1.37 1.8E-03 PA0075 pppA serine/threonine protein phosphatase 1.45 1.1E-02 PA0076 tagF1 type VI secretion-associated protein 1.56 1.5E-02 PA0077 icmF1 type VI secretion protein 1.37 4.7E-04 PA0078 tssL1 type VI secretion system protein 1.59 1.3E-03 1.31 5.6E-03 PA0079 tssK1 type VI secretion protein 1.58 1.4E-04 1.40 3.1E-03 PA0080 tssJ1 type VI secretion protein 1.51 1.7E-07 PA0082 tssA1 type VI secretion protein 1.52 4.1E-05 1.48 2.7E-03 PA0083 tssB1 type VI secretion protein 1.72 2.8E-06 PA0084 tssC1 type VI secretion protein 1.58 5.7E-04 1.52 4.7E-03 PA0085 hcp1 type VI secretion system effector 1.74 3.9E-05 2.14 4.5E-04 PA0086 tagJ1 type VI secretion system 1.74 1.6E-04 PA0087 tssE1 type VI secretion system lysozyme-like protein 1.92 1.7E-04 PA0088 tssF1 type VI secretion protein 1.58 3.7E-03 PA0090 clpV1 chaperone 1.59 1.5E-03 1.54 3.4E-03 PA0091 vgrG1 type VI secretion system tip protein 1.52 6.0E-03 1.23 2.4E-04 PA0094 eagT6 chaperone 1.38 4.7E-04 PA0095 type VI secretion protein 1.57 4.4E-09 PA0096 hypothetical protein 2.11 1.4E-06 PA0097 hypothetical protein 1.63 2.0E-07 PA0098 hypothetical protein 1.67 6.2E-04 PA0099 type VI effector protein 1.57 6.4E-06 PA0100 hypothetical protein 1.52 2.0E-06 1.29 4.4E-04 PA1659 hsiF2 type VI secretion system lysozyme-like protein 1.61 1.3E-04 PA1661 hsiH2 type VI secretion protein 1.53 8.1E-03 PA1666 lip2 type VI secretion system lipoprotein 1.33 1.8E-04 PA2361 icmF3 type VI secretion protein 1.52 1.6E-05 PA2362 dotU3 type VI secretion protein 1.89 1.1E-05 PA2363 hsiJ3 type VI secretion protein 1.71 1.8E-09 PA2364 lip3 type VI secretion protein 1.55 7.4E-05 PA2365 hsiB3 type VI secretion protein 1.86 7.4E-09 PA2366 hsiC3 type VI secretion protein 1.88 1.8E-07 PA2367 hcp3 type VI secretion system effector 1.76 2.2E-06 PA2368 hsiF3 type VI secretion protein 1.68 3.1E-03 PA2369 hsiG3 type VI secretion protein 1.92 3.2E-11 PA2370 hsiH3 type VI secretion protein 2.20 1.9E-06 PA2371 clpV3 type VI secretion system ATPase 1.65 9.5E-07 PA2372 hypothetical protein 1.69 1.4E-05 PA2373 vgrG3 type VI secretion protein 1.68 4.7E-07 PA3486 vgrG4b type VI secretion protein 1.69 6.9E-04 PA5266 vgrG6 type VI secretion protein 1.89 7.3E-04 59 Locus Tag Name Product Name RNA-Seq Proteomics FC padj FC p Other virulence factors PA0051 phzH potential phenazine-modifying enzyme 2.53 9.4E-13 PA0122 rahU hemolysin 2.30 3.0E-07 2.04 1.4E-02 PA1871 lasA LasA protease precursor 1.68 2.0E-04 PA1899 phzA2 probable phenazine biosynthesis protein 1.70 2.6E-08 PA1900 phzB2 probable phenazine biosynthesis protein 1.95 3.0E-10 1.25 4.3E-02 PA1901 phzC2 phenazine biosynthesis protein 1.85 2.2E-06 1.44 4.5E-03 PA1903 phzE2 phenazine biosynthesis protein 1.24 7.2E-04 PA1905 phzG2 probable pyridoxamine 5’-phosphate oxidase 1.53 2.7E-05 1.16 9.7E-03 PA2231 pslA undecaprenyl-phosphate glucose phosphotransferase 1.85 1.3E-09 1.29 2.2E-03 PA2232 pslB mannose-1-phosphate guanylyltransferase/mannose-6-phosphate isomerase 1.80 8.7E-12 1.34 6.5E-03 PA2233 pslC putative glycosyl transferase 1.58 5.4E-09 1.14 4.5E-02 PA2234 pslD polysaccharide export protein 1.71 4.9E-18 1.29 5.6E-03 PA2235 pslE psl exopolysaccharide biosynthesis 1.68 2.6E-09 1.19 4.8E-03 PA2236 pslF glycosyl transferase 1.62 1.4E-07 PA2237 pslG beta-xylosidase 1.52 1.4E-14 1.19 4.1E-03 PA2238 pslH glycosyl transferase 1.71 1.1E-06 1.28 1.8E-03 PA2239 pslI psl exopolysaccharide biosynthesis 1.55 7.4E-05 1.13 4.6E-02 PA2243 pslM hypothetical protein 1.73 5.1E-03 PA2244 pslN hypothetical protein 1.88 8.2E-03 PA2570 lecA galactose-binding lectin 7.32 2.4E-08 2.41 3.4E-03 PA3361 lecB fucose-binding lectin PA-IIL 2.86 1,2E-07 PA3540 algD GDP-mannose 6-dehydrogenase 7.13 2.9E-09 PA3541 alg8 alginate biosynthesis protein 2.79 4.7E-05 PA3542 alg44 alginate biosynthesis protein 2.11 2.7E-02 PA3544 algE alginate production outer membrane protein 2.73 1.8E-04 PA3545 algG alginate-c5-mannuronan-epimerase 2.41 9.7E-05 PA3547 algL poly(beta-d-mannuronate) lyase precursor 2.03 3.5E-02 PA3548 algI alginate o-acetyltransferase 1.80 3.9E-02 PA3550 algF alginate o-acetyltransferase 1.74 4.7E-02 PA3551 algA phosphomannose isomerase / GDP-D-mannose pyrophosphorylase 1.82 1.3E-03 PA3724 lasB elastase 1.64 1.7E-07 PA4175 piv protease IV 1.86 1.7E-05 PA4212 phzC1 phenazine biosynthesis protein 1.44 4.5E-03 PA4213 phzD1 phenazine biosynthesis protein 1.20 1.4E-03 PA4214 phzE1 phenazine biosynthesis protein 1.24 7.2E-04 4.5 The multidrug efflux genes mexXY and mexGHI-opmD were upregulated in the PA0805.1 overexpression strain Related to the tobramycin phenotype, the multidrug efflux pump mexXY, a known efflux 60 pump mediating resistance to aminoglycosides (Aires et al., 1999), was upregulated (Table 4-1). Interestingly, the repressor of mexXY, mexZ (Matsuo et al., 2004), was also upregulated in the proteomics dataset, yet clearly this was not sufficient to repress production of mexXY (Table 4-1). In addition, the multidrug efflux genes mexGH were upregulated by 1.7-1.8 fold in the RNA-Seq data, which could contribute to tobramycin resistance, since aminoglycosides are a substrate of the MexGHI-OpmD pump (Table 4-1) (Aendekerk et al., 2005). Proteomics and qRT-PCR indeed showed that the whole mexGHI-opmD operon was upregulated (Table 4-1, Table 4-2). Additionally, there were several other upregulated efflux genes, including mexB, mexE, mexJ and mexV (Table 4-1). MexS, a negative regulator of mexEF-oprN (Uwate et al., 2013), was downregulated in the proteomics (Table 4-1). Furthermore, czcR, a response regulator involved in heavy metal resistance, was also upregulated by 2.3 fold (Table 4-1). Moreover, genes in the wbp (PA5448-PA5454) LPS biosynthetic operon were downregulated, and in other studies we showed these can also lead to tobramycin resistance (Table 4-1) (Schurek et al., 2008). In contrast, genes in a different LPS biosynthetic operon (PA3141-PA3160) were upregulated (Table 4-1). Figure 4-4. Proposed model for how the overexpression of PA0805.1 dysregulated many genes, resulting in altered phenotypes. Connecting arrows represent direct or indirect regulation. Table 4-2. The MexGHI-OpmD operon was upregulated in the PA0805.1 overexpression strain when compared to EV strain by qRT-PCR. Bacteria were harvested from BM2 glycerol swarm plates with 1% arabinose and 0.1% CAA. n = 3. Gene Fold change mexG 2.1 ± 0.1 mexH 2.0 ± 0.2 61 Gene Fold change mexI 1.9 ± 0.1 opmD 2.1 ± 0.4 4.6 Adherence factors were dysregulated in the PA0805.1 overexpression strain Amongst the DE genes were a number of genes that could explain the anti-motility effect. Downregulation of the diguanylate cyclase FimX and PilGH could cause the downregulation of twitching motility proteins PilIJKTU and the type 4 fimbrial biogenesis proteins PilACD, PilMNOPQ, PilEVWX, and PilY1-2 (Table 4-1) (Jain et al., 2017). Downregulation of these genes could lead to reductions in twitching and/or swarming motility (Figure 4-1, Table 4-1) (Yeung et al., 2009). Aside from pilus-related genes, all other adherence factors were upregulated, including the cupA gene regulators cgrABC, but not the cupA operon (Table 4-1). Regulators rocS1 and rocR were also upregulated (Table 4-1), which can lead to the production of CupB and CupC fimbriae (Kulasekara et al., 2005). The upregulated genes also included cupE1-6, cupB2, tadABCDGZ, and flp (Table 4-1). Lastly, the transcriptional regulator FleQ was also upregulated, along with downstream genes flgBCDEFGHIJ, fliCDEF and flhA. Consistent with this, an adherence assay was performed showing that the overexpression strain PA0805.1 had increased adherence (Figure 4-5). Collectively the overexpression of these adherence factors and their regulators could influence the reduced motility seen for this strain. Figure 4-5. The PA0805.1 overexpression strain demonstrated increased adherence to polystyrene plates in 90% LB with 5% arabinose. Statistically significant differences were determined using Student’s paired t test. n ≥ 3. 4.7 Additional virulence factors were upregulated in the PA0805.1 overexpression strain PA0805.1 also had an increased cytotoxicity against HBE cells (Figure 4-2). Amongst the upregulated DE genes were lasAB and piv which are cytotoxic proteases. Other upregulated virulence factors were T6SS genes, rahU, alginate and phenazine biosynthetic genes, pslABCDEFGHIMN, and rhlABC (Table 4-1, Table A2). In contrast, certain pyochelin, T1SS and EV PA0805.10.000.050.18.104.22.168AdherenceAbsorbance at 595 nm***62 T3SS genes were downregulated (Table A2). Several global regulators implicated in virulence could account for these changes, such as CbrB, LasR, MvaT, and Vfr, but specifically the sigma factor AlgU, the two-component response regulator AlgB, and the transcriptional regulators PcrGH and ExsA are likely to be involved in regulating alginate and T3SS genes. 4.8 Comparison of RNA-Seq and proteomics Comparison of the transcriptional and proteomic response revealed considerable overlap, with 243 genes and the encoded proteins identified to be differentially expressed by both methods (Figure A2). Of the 243 common gene and protein candidates, there was a good correlation in the direction of fold change (Figure A3, R2 = 0.73), with 233 genes similarly down- (quadrant III, 90 genes), or up- (quadrant I, 143 genes) regulated, while 10 were regulated in opposite fashions (quadrants II and IV). This might relate in part to the differing abilities of the two methods since RNA-Seq was more sensitive and identified transcription from 5194 genes while proteomics identified only 2366 proteins. It is worth noting that transcripts for extracellular proteins were more likely detected in the RNA-Seq data since wash steps were employed prior to proteomics. Conversely, since sRNAs act by post-transcriptional regulation, it was expected that there would be changes in protein abundance with no corresponding difference in RNA transcript levels, while a single translationally dysregulated regulatory protein might control the expression of hundreds of genes. 4.9 In silico sRNA target prediction Three in silico sRNA target prediction tools, IntaRNA2, RNAPredator and TargetRNA2 were used to predict sRNA targets for PA0805.1 (Table A8). Of the fourteen predicted targets, four were validated in vitro, in showing changes in either RNA or protein abundance (Table 4-3). These genes included aprF, the first gene in the operon encoding the T1SS for alkaline protease; mep72, a metzincin protease; PA3840, a putative rRNA methyl transferase; and PA5187, a probable acyl-CoA dehydrogenase (Table 4-3). Table 4-3. sRNA targets predicted in silico that were confirmed for PA0805.1 by RNA-Seq or proteomics as well as their FC, p-values (padj/p) and predictive methods. Locus Tag Name Product Name RNA-Seq Proteomics Predicted by FC padj FC p PA1248 aprF alkaline protease secretion outer membrane protein AprF precursor -1.18 4.6E-03 RNAPredator, IntaRNA2 PA2783 mep72 Mep72 -2.45 9.2E-05 RNAPredator, IntaRNA2 PA3840 conserved hypothetical protein -1.87 2.6E-07 RNAPredator, IntaRNA2 63 Locus Tag Name Product Name RNA-Seq Proteomics Predicted by FC padj FC p PA5187 probable acyl-CoA dehydrogenase 1.11 3.5E-03 TargetRNA2, IntaRNA2 4.10 In its native state, PA0805.1 contributed to tobramycin susceptibility under swarming conditions As mentioned above, PA0805.1 was upregulated by 5.0 ± 1.7 fold under swarming vs. swimming conditions (BM2 glucose). A deletion mutant of PA0805.1 was constructed, and showed no dramatic motility phenotype, but was supersusceptible to tobramycin under swarming conditions, and when complemented substantially restored tobramycin resistance (Figure 4-6). These data were consistent with the positive regulation of tobramycin resistance but negative regulation of motility. Figure 4-6. A deletion mutant of PA0805.1 was supersusceptible to tobramycin as assessed in BM2 glucose swarming agar with no arabinose. The deletion mutant was complemented with a chromosomal insertion of the sRNA PA0805.1. Tobramycin was incorporated into the agar where indicated at 1 μg/ml. n = 3. 4.11 Discussion Here I demonstrated that the overexpression of sRNA PA0805.1 led to a wide range of phenotypic changes including reduced swarming, swimming and twitching motility, as well as 64 increased adherence, cytotoxicity, and tobramycin resistance. In contrast to this situation, few phenotypes were observed for the deletion mutant ∆PA0805.1. This was likely due to the fact that sRNAs usually act by inhibiting translation of target mRNA; hence overexpression is more likely to have an effect than deletion. As expected, the tobramycin phenotype of the deletion mutant (TOB supersusceptible, Figure 4-6) was the opposite of that of the overexpression strain (TOB resistant) under conditions of low expression (using glucose to inhibit expression from the PBAD promoter of pHERD20T) (Figure 4-3). The tobramycin phenotype was difficult to observe in the overexpression strain at higher levels of expression (i.e. with arabinose) due to the inhibition of swarming motility. The differential expression of many global transcriptional regulators in the proteomics data was intriguing and suggests a prospective key global regulatory role for the sRNA PA0805.1 in influencing other regulators (Figure 4-4). For example, regulators with altered expression when this sRNA was overexpressed included LasR, a global regulator in P. aeruginosa that controls QS, virulence factor production, and motility (Kiratisin et al., 2002; Köhler et al., 2000), RpoN, an alternative sigma factor σ54 that regulates virulence factors and pathogenicity in plants and animals as well as nitrogen metabolism (Hendrickson et al., 2001), MvaT, another global regulator of virulence that influences swarming motility and QS (Diggle et al., 2002), Vfr, a homolog of the E. coli catabolite repressor protein (CRP) that regulates virulence factor production (Fuchs et al., 2010; Rojo, 2010; Suh et al., 2015), and CbrB, a global response regulator, part of the two-component system CbrAB that regulates carbon and nitrogen metabolism, as well as antibiotic resistance, virulence, biofilm formation and swarming motility (Abdou et al., 2011; Yeung et al., 2011). Here it was shown that overexpressing the sRNA PA0805.1 resulted in broad transcriptional and proteomic changes, most likely through a hierarchical regulatory cascade (Figure 4-4). Forty-two transcriptional regulators, two-component systems, sigma and anti-sigma factors were dysregulated at the proteomic level and 118 overall, likely explaining the extensive downstream effects. For example, type IV pili and its equivalent chemosensory system (ChpA-E) were downregulated, which would lead to decreased swarming and twitching motility, although certain other adherence factors were upregulated. Conversely, many flagellar genes were mildly upregulated but the decreased expression of particular regulators such as lasR and cbrB might explain decreased swimming and swarming. Furthermore, there is a connection between swimming and twitching, since the two-component PilRS system controls flagellar genes and 65 swimming motility (Kilmury & Burrows, 2018). Since PilS had altered protein abundance (Table 4-1), PilS may have affected swimming motility. In addition, many virulence factors, including the genes encoding the cytotoxic proteases lasAB and piv were upregulated, likely resulting in the observed increased cytotoxicity. Lastly, several multidrug efflux systems were upregulated, importantly including mexXY and mexGHI-opmD, which might contribute to tobramycin resistance. The sRNA PA0805.1 thus modulates important adaptations in P. aeruginosa, including motility, virulence and antibiotic resistance. 66 Chapter 5: The sRNAs PA2952.1 and prrH as regulators of virulence, motility and iron metabolism 5.1 Introduction Coupling a large genome with a high percentage of transcriptional regulators (roughly 10%), P. aeruginosa has considerable potential to adapt to different conditions such as surface motility and antibiotic treatment. In addition, hundreds of regulatory sRNAs have been predicted, interspersed throughout the genome (Gómez-Lozano et al., 2012; Wurtzel et al., 2012). These non-coding regulatory elements allow for rapid regulation typically through post-transcriptional modification (Kavita et al., 2018). An exception to this is the ability of some sRNAs to influence degradation or increase stability of mRNAs (Pita et al., 2018; Prévost et al., 2011). A 2018 study examined the expression of intergenic sRNAs and found 31 species to be differentially expressed under swarming and/or biofilm conditions (Gill et al., 2018). Most of the 20 sRNAs dysregulated under swarming conditions were previously uncharacterized, except for prrH, rsmY and srbA. A previous study showed that deleting srbA had an effect on biofilm formation and virulence in a C. elegans infection model (Taylor et al., 2017). The sRNAs rsmY and rsmZ are induced by GacA, a global transcriptional regulator part of the two-component system GacAS, and partially redundant (Kay et al., 2006; Pita et al., 2018). After induction, rsmY and rsmZ sequester the post-transcriptional regulator RsmA from its target mRNA, causing diverse downstream effects on chronic and acute lifestyles (Janssen et al., 2018; Pita et al., 2018). Both rsmY and rsmZ can also be (in)directly regulated by AlgR, BfiSR, HptB, and PNPase. sRNA prrH has also been shown to be dysregulated under swarming conditions (Gill et al., 2018). As mentioned in the Introduction, prrH is regulated by Fur and controls iron metabolism and virulence traits. It also competes with crcZ for binding to Hfq, since crcZ has higher affinity for Hfq than does prrH (Pita et al., 2018; Sonnleitner et al., 2017). Here we probed the role of sRNAs in adaptive behaviours in P. aeruginosa, by cloning and overexpressing sRNAs dysregulated under swarming conditions. The overexpressing strains were examined in phenotypic assays for differences in motility, cytotoxicity and adherence. Next, RNA-Seq and proteomics were performed to investigate the effects mediated by the sRNA PA2952.1. 5.2 Phenotypic screens of sRNA overexpression strains sRNA species previously show to be dysregulated under swarming conditions (Gill et al., 2018) were cloned to enable overexpression since sRNAs often have inhibitory functions. To 67 determine which region or orientation might result in a phenotype, some of these sRNAs were cloned in two orientations (PA0805.1 and PA0805.1a; PA1091.1a and b; PA3159.1a and b; and PA4656.1a and b), or different regions were cloned (PA2952.1W, overlapping version of PA2952.1; and PA14sr120, shorter version of PA0805.1) (Gill et al., 2018; Gómez-Lozano et al., 2012; Wurtzel et al., 2012). PA14sr120 was predicted from the PA14 genome (Wurtzel et al., 2012) in the same relative orientation as the construct for PA0805.1, but shorter than predicted in PAO1. A total of 21 constructs were made in the arabinose-inducible pHERD20T vector and transformed into PAO1 H103 WT by electroporation. One of these, PA0805.1, was described previously in Chapter 4. At the time of the assay, arabinose was added to induce sRNA expression. Overexpression strains were confirmed to have no growth defects (Figure A4 and data not shown). Next, overexpression strains were screened for swarming, swimming, and twitching (Figure 5-1). Strains were also screened for adherence to polystyrene, but showed little difference in this assay (Figure A5). Swarming and swimming motilities correlated well for some strains in these experiments (Figure 5-1). The overexpression strain PA14sr120 showed swarming and swimming motility that was reduced to 81±6% and 65±2% of the wild type (WT) containing the empty cloning vector (EV). The PA2952.1 overexpressing strain had motility reduced to 69±3 and 43±4% for swarming and swimming respectively. The PA1091.1b overexpressing strain showed a reduction to 80±2% in swarming motility. Interestingly, overexpression of prrH resulted in substantially reduced swimming (to 28±3% of the WT EV control) but no change in swarming motility (Figure 5-1). Overexpression strains were also screened for twitching motility but showed no significant differences (Figure 5-1). Sample colonies showing partial reductions in motility are shown in Figure 5-2. The sRNA overexpression strains were also screened for cytotoxicity against human bronchial epithelial cells (HBE), with and without arabinose. Few significant differences were found amongst the strains (data not shown), except for PA2952.1 and prrH. In the absence of arabinose, PA2952.1 had cytotoxicity reduced by 36.4% of WT levels; however the PA2952.1 overexpressing strain when compared to WT EV with 1% arabinose was not significantly different (Figure 5-3A, Figure A6a). 5.3 sRNA prrH played a role in cytotoxicity and pyoverdine production The sRNA prrH, encompassing the two adjacent and highly homologous sRNAs prrF1 68 Figure 5-1. Motility screen of sRNA overexpression strains revealed that overexpression of certain sRNAs altered motility. 1% Arabinose was used to induce expression and statistically significant differences from WT EV were determined using one-way ANOVA. n ≥ 3. and prrF2 (Wilderman et al., 2004), also played a role in cytotoxicity (Figure 5-3B). When prrH was overexpressed at low levels (0% arabinose), the cytotoxicity of WT +prrH was reduced by 40.2% of WT levels. In the absence of arabinose, a deletion mutant ∆prrH had even lower levels 69 of cytotoxicity (reduced by 68.9%), which was partially complemented (to 53.7% of WT levels) when the sRNA was reintroduced on the uninduced pHERD20T plasmid (Figure 5-3B). Interestingly, in the presence of arabinose, these phenotypes were minimized. With arabinose, only the change in cytotoxicity due to deletion in ∆prrH was significantly different and could not be complemented by overexpression of prrH (Figure A6b). Figure 5-2. Overexpression of certain sRNAs led to partial reductions in swarming (top row) and swimming (bottom row) motilities. n ≥ 3. Figure 5-3. Cytotoxicity phenotypes of sRNA overexpression strains in the absence of arabinose. A) overexpression of PA2952.1 compared to WT EV. B) deletion and overexpression of prrH. Statistically significant differences were determined by unpaired t test (A) or one-way ANOVA (B). n ≥ 3. The deletion mutant ∆prrH also produced >2-fold increased levels of pyoverdine (Figure 70 5-4). This phenotype was restored to WT levels by complementation. The strain overexpressing prrH however showed no difference from the WT EV isolate (Figure 5-4). Figure 5-4. A deletion mutant ∆prrH had increased production of pyoverdine. n = 3. 5.4 Overexpression of sRNAs altered antibiotic susceptibility under swarming conditions The sRNA PA2952.1, which inhibited swarming and swimming (Figure 5-2), also showed altered antibiotic susceptibility under swarming conditions. PA2952.1 overexpression at low levels led to resistance to both tobramycin and gentamicin (Figure 5-5A). This modest resistance phenotype could not be observed at higher levels of expression, in part due to the inhibitory effect of PA2952.1 on swarming motility. In contrast, at higher levels of expression, increased susceptibility to trimethoprim was observed under swarming conditions (Figure 5-5B). No major differences in MIC to either antibiotic were observed in standard microdilution assays (Table A9), however, subinhibitory concentrations of trimethoprim specifically inhibited the growth of the PA2952.1 overexpression strain in the presence of 1% arabinose (Figure A7). Overexpression of the sRNA PA14sr120 at low levels resulted in resistance to tobramycin under swarming conditions (Figure 5-5C). Similar to the observations made for PA2952.1, overexpression of PA1091.1b at high levels resulted in increased trimethoprim susceptibility under swarming conditions (Figure 5-5D). 5.5 Overexpression of PA2952.1 resulted in broad transcriptional changes including altered expression of 82 regulatory factors The sRNA PA2952.1 was selected for study in greater detail due to its broad phenotypic effects and lack of prior studies. To determine which genes or proteins caused the above-described phenotypic changes, RNA-Seq and proteomics were performed on the WT strain overexpressing PA2952.1 compared to that with the WT EV control, by harvesting bacteria from the edges of swarming colonies grown with 1% arabinose. Substantial transcriptional and proteomic changes 500 600 700010203040PyoverdineEmission wavelength (nm)Relative fluorescence emissionWT EVWT +prrHprrH EVprrH+71 Figure 5-5. Antibiotic susceptibility phenotypes were affected by sRNAs under swarming conditions. A. The strain overexpressing PA2952.1 showed resistance to tobramycin and gentamicin in BM2 glucose swarm plates with no arabinose, supplemented where indicated with 1 μg/ml antibiotic. n = 3. B. Overexpression of PA2952.1 induced susceptibility to trimethoprim in BM2 glycerol swarm plates. Trimethoprim is included where indicated at 10 μg/ml. n ≥ 3. C. The PA14sr120 overexpression strain was resistant to tobramycin in BM2 glucose swarm plates with no arabinose. Tobramycin is included where indicated at 1 μg/ml. n ≥ 3. D. Overexpression of PA1091.1b increased susceptibility to trimethoprim in BM2 glycerol swarm plates. Trimethoprim is included where indicated at 10 μg/ml. n ≥ 3. were observed, encompassing 446 proteins with differential abundance and 784 DE genes in the RNA-Seq (Table A2). Of these, 339 genes were downregulated and 445 were upregulated; while 72 221 proteins had decreased abundance and 225 were increased (Table A2). There was a large number (82 genes/proteins) of regulatory factors (transcriptional regulators, two-component systems, sigma and anti-sigma factors) found amongst these genes, which might have accounted for the large transcriptional changes observed (Table 5-1). Amongst the 82 regulatory factors, 27 factors showed changes only in the proteomics dataset (shown with bold locus tag in Table 5-1) and thus might represent potential post-transcriptional sRNA targets. Table 5-1. Selected differential expressed genes/proteins in the PA2952.1 overexpression strain as compared to WT EV by RNA-Seq and/or proteomics. Loci shown in bold showed differences uniquely in the proteome. Cutoffs used were p/padj ≤ 0.05 and for RNA-Seq, FC ≥ 1.5. Locus Tag Name Product Name RNA Seq Proteomics FC padj FC p Transcriptional regulators, two-component systems and sigma factors PA0048 probable transcriptional regulator -1.56 2.0E-02 PA0155 pcaR transcriptional regulator 1.84 5.5E-14 PA0217 probable transcriptional regulator 1.57 1.8E-03 PA0243 probable transcriptional regulator 1.10 1.1E-02 PA0403 pyrR transcriptional regulator 1.59 1.8E-04 PA0463 creB two-component response regulator 1.81 2.4E-13 PA0472 fiuI probable sigma-70 factor, ECF subfamily 1.94 5.0E-05 PA0528 probable transcriptional regulator 1.78 1.9E-08 PA0652 vfr transcriptional regulator -1.11 2.2E-03 PA0828 probable transcriptional regulator -2.01 2.0E-02 PA0877 probable transcriptional regulator -1.51 2.6E-02 PA0964 pmpR pqsR-mediated PQS regulator -1.08 2.7E-02 PA1157 probable two-component response regulator 1.10 6.5E-03 PA1179 phoP two-component response regulator -1.51 6.1E-21 PA1223 probable transcriptional regulator -1.56 3.7E-03 PA1261 lhpR transcriptional regulator 1.96 2.3E-03 PA1285 probable transcriptional regulator 1.66 5.1E-07 PA1290 probable transcriptional regulator 1.30 1.1E-02 PA1315 probable transcriptional regulator 1.09 3.3E-02 PA1328 probable transcriptional regulator 1.65 5.1E-06 PA1399 probable transcriptional regulator 1.62 7.5E-03 PA1431 rsaL regulatory protein 1.98 8.0E-08 PA1627 probable transcriptional regulator 2.21 1.4E-08 PA1707 pcrH regulatory protein -1.88 1.7E-04 PA1714 exsD probable transcriptional regulator -1.29 3.2E-02 PA1785 nasT regulatory protein -1.11 7.0E-03 PA1836 probable transcriptional regulator -1.51 2.5E-03 PA1911 femR sigma factor regulator 1.93 1.5E-02 PA1912 femI ECF sigma factor 1.88 1.5E-03 73 Locus Tag Name Product Name RNA Seq Proteomics FC padj FC p PA1949 rbsR ribose operon repressor 1.07 1.6E-02 PA1980 eraR response regulator -1.81 1.1E-02 PA2082 kynR probable transcriptional regulator 1.12 8.0E-03 PA2126 cgrC cupA gene regulator C 1.74 8.5E-05 PA2126.1 cgrB cupA gene regulator B 2.33 2.4E-07 PA2276 probable transcriptional regulator 1.13 4.3E-03 PA2337 mtlR transcriptional regulator 1.60 9.3E-04 PA2426 pvdS sigma factor 2.07 2.0E-02 PA2467 foxR anti-sigma factor 2.11 6.2E-07 PA2486 ptrC Pseudomonas type III repressor gene C 2.89 2.6E-13 PA2491 mexS Transcriptional regulator -1.18 5.9E-03 PA2511 antR Transcriptional regulator 1.67 2.7E-03 PA2663 ppyR psl and pyoverdine operon regulator 2.14 1.5E-04 PA2665 fhpR transcriptional activator of P. aeruginosa flavohemoglobin 1.07 1.7E-02 PA2848 probable transcriptional regulator 1.56 1.3E-02 PA2882 probable two-component sensor 2.31 5.0E-03 PA2895 sbrR anti-sigma factor 1.52 2.2E-05 PA2896 sbrI probable sigma-70 factor, ECF subfamily 1.50 1.6E-06 PA2917 probable transcriptional regulator 1.65 1.0E-06 PA2931 cifR putative transcriptional regulator -1.59 1.9E-03 PA3006 psrA transcriptional regulator 1.14 1.6E-02 PA3122 probable transcriptional regulator 1.11 7.9E-03 PA3220 probable transcriptional regulator 1.54 2.2E-04 PA3341 probable transcriptional regulator 1.13 2.0E-03 PA3458 probable transcriptional regulator -1.50 6.2E-03 PA3583 glpR glycerol-3-phosphate regulon repressor 1.06 1.3E-03 PA3622 rpoS sigma factor 1.13 1.1E-02 PA3689 probable transcriptional regulator 1.10 3.0E-04 PA3757 nagR transcriptional regulator of N-acetylglucosamine catabolism operon 1.52 2.6E-03 PA3878 narX two-component sensor 1.57 1.1E-07 PA3899 fecI probable sigma-70 factor, ECF subfamily 1.62 7.4E-03 PA4057 nrdR transcriptional repressor -1.54 2.6E-06 PA4070 probable transcriptional regulator 1.98 1.1E-05 PA4293 pprA two-component sensor 1.18 2.5E-02 PA4296 pprB two-component response regulator 1.08 2.0E-02 PA4493 roxR response regulator 1.17 2.8E-02 PA4546 pilS two-component sensor 1.09 3.5E-02 PA4726 cbrB two-component response regulator 1.51 4.4E-25 -1.13 8.9E-04 PA4764 fur ferric uptake regulation protein 1.08 3.1E-02 74 Locus Tag Name Product Name RNA Seq Proteomics FC padj FC p PA4777 pmrB two-component regulator system signal sensor kinase 1.54 5.4E-03 PA4778 cueR probable transcriptional regulator -1.14 3.1E-02 PA4784 probable transcriptional regulator 1.53 2.0E-05 PA4914 amaR transcriptional regulator 1.62 1.5E-05 PA5029 probable transcriptional regulator 1.54 2.5E-05 PA5124 ntrB two-component sensor 1.72 6.6E-06 PA5189 probable transcriptional regulator 1.59 3.6E-05 PA5261 algR alginate biosynthesis regulatory protein 1.58 5.2E-08 PA5288 glnK nitrogen regulatory protein P-II 2 1.58 4.5E-04 PA5293 probable transcriptional regulator 1.07 4.5E-02 PA5356 glcC transcriptional regulator 2.19 1.1E-18 PA5403 probable transcriptional regulator 1.70 1.1E-03 PA5484 kinB two-component sensor 1.10 6.5E-03 PA5499 zur zinc uptake regulator 2.27 6.3E-06 Motility and related genes PA0396 pilU twitching motility protein -1.12 3.6E-03 PA0408 pilG twitching motility protein -1.33 4.9E-02 PA0411 pilJ twitching motility protein -1.32 1.6E-04 PA0413 chpA component of chemotactic signal transduction system -1.17 2.3E-05 PA0415 chpC probable chemotaxis protein -1.56 3.3E-06 PA1083 flgH flagellar L-ring protein precursor 1.12 4.9E-02 PA1088 hypothetical protein 1.09 1.9E-02 PA1100 fliE flagellar hook-basal body complex protein -1.55 1.6E-06 PA1442 conserved hypothetical protein -1.52 1.0E-09 PA1445 fliO flagellar protein -1.05 3.6E-02 PA1461 motD flagellar motor protein 1.11 1.3E-02 PA4525 pilA type 4 fimbrial precursor -2.86 7.2E-24 PA4527 pilC still frameshift type 4 fimbrial biogenesis protein (putative pseudogene) -1.09 6.1E-03 PA4552 pilW type 4 fimbrial biogenesis protein -1.09 4.8E-02 PA4554 pilY1 type 4 fimbrial biogenesis protein -1.15 4.9E-02 PA5043 pilN type 4 fimbrial biogenesis protein 1.38 9.1E-03 Multidrug efflux and LPS modification PA2494 mexF RND multidrug efflux transporter 1.66 2.7E-02 PA2525 opmB outer membrane efflux protein 1.67 3.0E-02 PA2528 muxA probable RND efflux membrane fusion protein -1.10 6.5E-03 PA3522 mexQ efflux pump membrane transporter -1.63 1.8E-02 PA3676 mexK probable RND efflux transporter 1.12 4.6E-02 PA4205 mexG hypothetical protein 1.24 1.2E-03 PA4206 mexH probable RND efflux membrane fusion protein 1.07 3.4E-02 75 Locus Tag Name Product Name RNA Seq Proteomics FC padj FC p precursor PA4374 mexV RND multidrug efflux membrane fusion protein 2.89 2.2E-18 1.11 2.8E-02 PA3552 arnB UDP-4-amino-4-deoxy-L-arabinose--oxoglutarate aminotransferase 2.06 1.8E-04 PA3553 arnC undecaprenyl-phosphate 4-deoxy-4-formamido-L-arabinose transferase 2.48 3.1E-08 PA3554 arnA bifunctional polymyxin resistance protein 1.61 9.4E-03 PA3556 arnT inner membrane L-Ara4N transferase 1.71 1.5E-03 PA3558 arnF probable 4-amino-4-deoxy-L-arabinose-phosphoundecaprenol flippase subunit 2.45 1.0E-05 PA3559 probable nucleotide sugar dehydrogenase 1.97 3.8E-04 DNA synthesis PA0143 nuh purine nucleosidase -1.09 5.9E-03 PA0196 pntB pyridine nucleotide transhydrogenase, beta subunit 1.10 4.8E-02 PA0342 thyA thymidylate synthase -1.05 3.5E-02 PA0357 mutM formamidopyrimidine-DNA glycosylase -1.11 1.5E-02 PA0441 dht dihydropyrimidinase 2.10 1.9E-02 PA0582 folB dihydroneopterin aldolase -2.32 5.3E-13 PA3438 folE1 GTP cyclohydrolase I precursor -1.20 4.3E-03 PA3640 dnaE DNA polymerase III, alpha chain -1.08 3.0E-02 PA4645 probable purine/pyrimidine phosphoribosyl transferase -1.11 6.1E-04 PA4946 mutL DNA mismatch repair protein -1.07 2.9E-02 PA4964 parC topoisomerase IV subunit A -1.12 2.8E-03 PA4967 parE topoisomerase IV subunit B -1.10 7.9E-04 PA5345 recG ATP-dependent DNA helicase -1.14 2.4E-03 PA5443 uvrD DNA helicase II -1.11 2.3E-02 PA5493 polA DNA polymerase I -1.08 1.5E-03 PA5541 pyrQ dihydroorotase 6.74 7.7E-04 Virulence factors PA0071 tagR1 FGE-sulfatase domain-containing protein 1.13 4.6E-02 PA0075 pppA serine/threonine protein phosphatase 1.17 1.8E-02 PA0077 icmF1 type VI secretion protein 1.15 2.2E-02 PA0078 tssL1 type VI secretion system protein 1.19 1.6E-02 PA0079 tssK1 type VI secretion protein 1.18 2.4E-02 PA0081 fha1 type VI secretion protein 1.51 9.1E-11 PA0082 tssA1 type VI secretion protein 1.39 6.8E-03 PA1694 pscQ translocation protein in type III secretion -2.28 1.2E-03 PA1700 pcr2 type III secretion chaperone -3.32 9.0E-03 PA1703 pcrD type III secretory apparatus protein -1.59 2.0E-06 PA1706 pcrV type III secretion protein -1.61 9.4E-04 76 Locus Tag Name Product Name RNA Seq Proteomics FC padj FC p PA1708 popB translocator protein -2.16 8.9E-11 PA1709 popD translocator outer membrane protein precursor -1.79 1.5E-06 PA1710 exsC exoenzyme S synthesis protein C precursor. -1.73 2.4E-08 PA1712 exsB exoenzyme S synthesis protein B -1.76 3.1E-10 PA1715 pscB type III export apparatus protein -2.41 3.2E-04 PA1717 pscD type III export protein -2.22 9.0E-05 PA1719 pscF type III export protein -1.59 3.0E-03 PA1720 pscG type III export protein -1.71 6.4E-03 PA1722 pscI type III export protein -2.15 3.5E-04 PA1723 pscJ type III export protein -1.74 4.1E-06 PA2191 exoY adenylate cyclase -2.04 6.6E-07 PA2231 pslA undecaprenyl-phosphate glucose phosphotransferase 1.21 3.2E-02 PA2232 pslB mannose-1-phosphate guanylyltransferase/mannose-6-phosphate isomerase 1.19 3.2E-02 PA2238 pslH glycosyl transferase 1.12 4.0E-02 PA2244 pslN hypothetical protein 1.68 8.8E-03 PA3841 exoS exoenzyme S -1.53 5.3E-06 Cell division PA0373 ftsY signal recognition particle receptor -1.07 2.0E-02 PA1528 zipA cell division protein 1.07 3.3E-02 PA3243 minC cell division inhibitor -1.05 1.9E-02 PA3245 minE cell division topological specificity factor -1.73 3.9E-20 PA4003 pbpA penicillin-binding protein 2 -1.04 5.0E-02 PA4020 mpl UDP-N-acetylmuramate:L-alanyl-gamma-D-glutamyl-meso-diaminopimelate ligase -1.11 3.2E-03 PA4407 ftsZ cell division protein 1.14 2.0E-02 PA4408 ftsA cell division protein 1.10 7.4E-03 PA4411 murC UDP-N-acetylmuramate--alanine ligase 1.12 9.2E-04 PA4414 murD UDP-N-acetylmuramoylalanine--D-glutamate ligase 1.08 1.4E-02 PA4416 murF UDP-N-acetylmuramoylalanyl-D-glutamyl-2, 6-diaminopimelate--D-alanyl-D-alanyl ligase 1.11 2.8E-02 PA4417 murE UDP-N-acetylmuramoylalanyl-D-glutamate-2, 6-diaminopimelate ligase 1.09 1.1E-02 PA4418 ftsI penicillin-binding protein 3 1.12 4.3E-02 PA5538 amiA N-acetylmuramoyl-L-alanine amidase 4.63 4.7E-04 PA5562 spoOJ chromosome partitioning protein 1.08 6.2E-03 PA5563 soj chromosome partitioning protein 1.08 3.9E-02 Iron and zinc uptake PA0470 fiuA ferrichrome receptor 4.33 2.3E-23 77 Locus Tag Name Product Name RNA Seq Proteomics FC padj FC p PA3621 fdxA ferredoxin I -2.13 3.1E-09 PA3812 iscA probable iron-binding protein -1.56 1.0E-08 PA4235 ftnA bacterial ferritin 1.11 7.1E-03 PA4358 feoB ferrous iron transport protein B 1.59 1.8E-02 PA4655 hemH ferrochelatase 1.57 8.1E-12 PA4688 hitB iron (III)-transport system permease -1.07 2.7E-02 PA4880 probable bacterioferritin 2.72 1.1E-10 PA5500 znuC zinc transport protein 2.34 9.5E-08 These 27 regulatory factors that were altered only at the proteomic level included several global regulators including Fur, that regulates iron acquisition, metabolism, virulence and the response to toxic oxygen radicals (Hassett et al., 1996; Pasqua et al., 2017), RpoS, a stationary sigma factor involved in the stress response and antibiotic tolerance (Murakami et al., 2005; Suh et al., 1999), the two-component system PprAB, that regulates biofilm formation, drug susceptibility and virulence (de Bentzmann et al., 2012), PmpR, a regulator of the PQS QS system, T3SS, swarming and biofilm formation (Liang et al., 2008; Liang et al., 2012b), PsrA, a regulator of PQS, T3SS, antimicrobial peptide resistance, swarming and biofilm formation (Gooderham et al., 2008; Kojic et al., 2005; Shen et al., 2006; Wells et al., 2017), Vfr, a regulator of virulence factors and homolog of the E. coli catabolite repressor protein (Fuchs et al., 2010; Rojo, 2010; Suh et al., 2015), PilS, a two-component sensor that regulates both twitching and swimming motilities (Kilmury & Burrows, 2018), and KinB, a two-component sensor that regulates alginate production, virulence, and motility (Chand et al., 2012; Damron et al., 2012; Damron et al., 2009). Other regulators not unique to the proteome included algR, cbrB, glnK, ntrB, phoP, pmrB, pvdS, rsaL and sbrIR (Table 5-1). Comparison of the RNA-Seq and proteomics data revealed an overlap of 50 genes/proteins (Figure A2), indicative of significant post-transcriptional modulation. Nevertheless, genes within the same operon were often regulated in the same direction in both RNA-Seq and proteomics (Table 5-1), suggesting there may be more similarities between the two data sets than immediately evident. 5.6 Pili and flagellar genes were dysregulated in the PA2952.1 overexpression strain Overexpression of PA2952.1 led to partial reductions in both swarming and swimming motilities (Figure 5-2). Motility genes dysregulated in the RNA-Seq and proteomics could explain this effect (Table 5-1). Pili genes were generally downregulated, including pilAC, pilW, pilY1, 78 pilUGJ and the accompanying chemotactic genes chpAC (Table 5-1). The type IV pilus plays a role in swarming motility in P. aeruginosa (Köhler et al., 2000), and mutants in pilC, pilJ, pilW and pilY1 all have deficient swarming ability (Yeung et al., 2009). Flagellar genes were also dysregulated, and the downregulated fliE, fliO and PA1442 could contribute to decreases in both swarming and swimming motilities (Table 5-1). Other genes required for swarming that were downregulated in the PA2952.1 overexpression strain, were PA0591, PA0837 (slyD), PA0894, PA1827, PA2023 (galU), PA2445, PA2630, PA3091, PA3386, PA4005, PA4505, PA4616, PA4775 (greA), PA4778 (cueR), PA4851, PA5078 (opgG), PA5134 (ctpA), PA5232, PA5315 (rpmG), and PA5345 (recG); collectively these could have exerted a multigenic influence to decrease swarming. 5.7 Upregulation of mexGHI-opmD and the arn operon might lead to aminoglycoside resistance in the PA2952.1 overexpression strain Related to the aminoglycoside resistance phenotype (Figure 5-5A), efflux proteins MexGH demonstrated increased abundance in the proteome (Table 5-1), while qRT-PCR revealed a modest upregulation of the entire operon (Table 5-2). The mexGHI-opmD efflux pump was previously shown to be involved in aminoglycoside efflux (Aendekerk et al., 2005). Similarly, MexS, a negative regulator of efflux (Uwate et al., 2013), had decreased abundance in the proteome (Table 5-2). Table 5-2. The mexGHI-opmD operon was modestly upregulated in the PA2952.1 overexpression strain when compared to WT EV by qRT-PCR. Bacteria were harvested from BM2 glycerol swarm plates with 1% arabinose and 0.1% CAA. n = 3. Gene Fold change mexG 1.7 ± 0.2 mexH 1.7 ± 0.2 mexI 1.8 ± 0.3 opmD 1.8 ± 0.5 A dysregulation of LPS biosynthetic genes was also observed (Table A2), and this might be important due to the role of LPS in self-promoted uptake of aminoglycosides and swarming-dependent adaptive resistance to tobramycin (Chapter 3). In addition, arnBCATF were upregulated (Table 5-1). These genes are involved in the aminoarabinosylation of LPS to a more positively charged form, resulting in resistance to both aminoglycosides and cationic antimicrobial peptides (Breidenstein et al., 2011). The arn operon is regulated by several different two-component systems; in this case the PmrAB system may be implicated (Barrow & Kwon, 2009), since pmrB 79 was also upregulated (Table 5-1). Furthermore, 40 ribosomal and related genes were modestly downregulated (Table A2), which may also be a contributing factor, since the ribosome is the target of aminoglycosides. 5.8 DNA biosynthetic pathways were dysregulated Genes involved in DNA synthesis, including those involved in pyrimidine metabolism, were dysregulated (Table 5-1). These genes were generally mildly downregulated, with the exception of pntB, dht, and pyrQ that were upregulated (Table 5-1). This could contribute to the increased susceptibility to trimethoprim observed in the PA2952.1 overexpression strain (Figure 5-5B), since trimethoprim inhibits the enzyme dihydrofolate reductase, causing a decrease in the levels of tetrahydrofolate (Sangurdekar et al., 2011). Tetrahydrofolate plays a role as a carbon donor in nucleic acid and amino acid biosynthesis, importantly also enabling production of the nucleotide thymidylate (Sangurdekar et al., 2011). Therefore if DNA synthesis was already partly inhibited (Table 5-1), adding trimethoprim could further sensitize the cells. 5.9 Virulence, cell division, and metal uptake pathways were dysregulated Although significant differences were only observed in cytotoxicity of the overexpression strain in the absence of arabinose (Figure 5-3A), numerous virulence factors were dysregulated. Genes in T6SS and T1SS were dysregulated, while the T3SS, including its regulators, exsD and pcrH, and effectors, exoY and exoS, were all downregulated (Table 5-1 and Table A2). Similarly a repressor of T3SS, ptrC, was upregulated (Table 5-1) (Jin et al., 2011). Additionally, phenazine, psl and pyoverdine genes were generally upregulated, except for phzG1, and three alginate biosynthetic genes were dysregulated (Table 5-1 and Table A2). Interestingly, algR, pvdS and ppyR, regulators of alginate, pyoverdine and psl, were also upregulated (Attila et al., 2008; Hunt et al., 2002; Okkotsu et al., 2013). Genes involved in cell division also showed a mild dysregulation, particularly at the protein level (Table 5-1). Interestingly, genes involved in iron, zinc and copper acquisition were also dysregulated, including the regulators fur, zur and cueR (Table 5-1). 5.10 In silico sRNA target prediction The three tools IntaRNA2, RNAPredator and TargetRNA2 were used to predict sRNA targets (Table A10). Of the fourteen predicted targets, four were validated in vitro, showing changes in either transcript or protein abundance (Table 5-3). This included the methionine aminopeptidase map, the tRNA methyltransferase trmU, the probable TetR type transcriptional regulator PA0828 and PA2459 (Table 5-3). 80 Table 5-3. sRNA targets predicted in silico that were confirmed for PA2952.1 by RNA-Seq or proteomics as well as their FC, p-values (padj/p) and predictive methods. Locus Tag Name Product Name RNA-Seq Proteomics Predicted by FC padj FC p PA0828 probable transcriptional regulator -2.01 2.0E-02 RNAPredator, TargetRNA2 PA2459 hypothetical protein -1.87 6.2E-04 RNAPredator, TargetRNA2 PA2626 trmU tRNA methyltransferase -1.05 2.4E-02 IntaRNA2, RNAPredator PA3657 map methionine aminopeptidase 1.12 3.6E-03 IntaRNA2, RNAPredator 5.11 Comparison of PA2952.1 omics data with previous datasets To look for consistent themes, the differentially expressed RNA-Seq and proteomics datasets from the PA2952.1 overexpressing strain compared to those for the empty vector were compared with the above-described datasets. 5.11.1 Comparison with swarm vs. swim RNA-Seq Comparison of RNA-Seq from swarm vs. swim with differentially expressed genes from the PA2952.1 overexpressing strain, showed an overlap of 288 genes (Figure A2). There were some similarities in the datasets, since 220 genes were regulated in the same direction in both datasets; whereas only 68 genes were oppositely regulated (Figure A3). Similarly-regulated genes included those encoding ribosomal proteins, pyoverdine biosynthesis enzymes, and regulators such as AlgR, FoxR, PhoP, PtrC, PpyR, PvdS, and SbrR. 5.11.2 Comparison of RNA-Seq and proteomics data for the PA0805.1 and PA2952.1 overexpressing strains Although dozens to hundreds of unique genes and proteins were identified, comparison of the PA0805.1 and PA2952.1 overexpression strains omics datasets revealed striking commonalities (Figure A2, Figure A3). The PA0805.1-overexpression vs. PA2952.1-overexpression proteomics comparison was the most similar, with all of the common 363 commonly dysregulated proteins showing the same direction of regulation. Comparison of the two RNA-Seq experiments for the PA0805.1 and PA2952.1 overexpression strains also revealed considerable similarities, with 220 of the 258 commonly dysregulated genes showing the same direction of regulation. This indicates that while there were many unique genes and proteins, there were also prominent commonalities between PA0805.1 and PA2952.1, suggesting there was a relationship between the effects mediated by the two sRNAs. 81 5.12 Discussion Here I probed the role of sRNAs in motility and other adaptive processes. A total of 21 constructs were made featuring sRNAs dysregulated during swarming or biofilm formation and functions were identified for five of these (including PA0805.1) when cloned to enable overexpression, since this enhances the known inhibitory functions of sRNAs. In contrast, in this study, no phenotypes were observed for the overexpression of rsmY. This may be due to redundancy with rsmZ; for instance, when rsmY was overexpressed, rsmZ could have been downregulated to cancel out any effects (Kay et al., 2006). I also did not observe a phenotype for srbA, but this may be because the sRNA was overexpressed rather than deleted. Two of these sRNAs, prrH and PA2952.1, are related by an interconnection with Fur, the ferric uptake regulator, a transcriptional repressor that can also function as an activator (Wilderman et al., 2004). Under iron-depleted conditions, the expression of prrH is highly induced (Wilderman et al., 2004), while it is 163-fold upregulated under swarming conditions (Gill et al., 2018). Results presented here indicated that prrH was involved in both cytotoxicity (Figure 5-3B) and the production of pyoverdine (Figure 5-4), and that overexpression of prrH led to a reduction in swimming motility (Figure 5-2). Similarly, in the PA2952.1 overexpression strain, Fur had increased abundance in the proteome, iron acquisition and virulence factors were dysregulated, and swimming motility was decreased to a similar extent (Table 5-1, Figure 5-2). Other interesting regulators with altered abundance in the PA2952.1 overexpression strain included AlgR, a regulator of alginate, swarming, twitching and rhamnolipid production (Okkotsu et al., 2013), GlnK and NtrB, two regulators of nitrogen metabolism, PhoP, a two-component sensor involved in antimicrobial resistance and virulence (Gellatly et al., 2012; Macfarlene et al., 2000), PvdS, a sigma factor controlled by Fur that regulates pyoverdine and exotoxin A (Hunt et al., 2002), RsaL, a regulator of QS and virulence (De Kievit et al., 1999; Lee & Zhang, 2014), and SbrIR, a sigma-anti-sigma factor pair that controls swarming motility and biofilm formation (McGuffie et al., 2016) (Table 5-1). Upon overexpression of the sRNA PA2952.1, hundreds of genes and proteins showed significant changes in abundance (Table A2), accompanied by several phenotypic differences (Figure 5-2, Figure 5-5A and B) indicating that this has the hallmarks of a global regulatory system. A model was proposed to account for this surprisingly large amount of dysregulation (Figure 5-6). In a hierarchical fashion, overexpression of PA2952.1 directly or indirectly led to alterations in 82 regulatory factors, which then in turn influenced the expression of downstream genes (Figure 5-6). 82 For example, AlgR that was affected by PA2952.1 could in turn influence alginate, ExsD, PcrH and PtrC influence T3SS, Fur influence iron uptake, PilS influence type IV pili and flagella, PmrB influence the arn operon, and PvdS and PpyR influence pyoverdine and psl biosynthesis (Figure 5-6). This might also influence additional downstream genes without an obvious regulator, or genes with multiple potential regulators, and further experimentation would be required to determine the exact pathway. Downregulation of pili and certain flagellar genes, as well as genes required for swarming, would then lead to decreases in swarming and swimming motilities, upregulation of mexGHI-opmD and the arn operon to mediate aminoglycoside resistance, and downregulation of certain genes involved in DNA synthesis to influence trimethoprim susceptibility. Overall, this highlights a potential key role for the sRNA PA2952.1 in modulating gene expression and controlling bacterial lifestyles, and demonstrates that predictive programs that usually indicate a very modest number of target genes have the potential to dramatically underestimate actual targets. Figure 5-6. Proposed model for how the overexpression of PA2952.1 dysregulates many genes, resulting in altered phenotypes. Connecting arrows represent direct or indirect regulation. 83 Chapter 6: The role of swarming in vivo 6.1 Introduction Standard drug testing and development is typically performed using planktonic bacterial cultures. While convenient and standardized, the planktonic, rapidly-dividing bacterium is not necessarily reflective of the growth state in vivo. Biofilms, for example, are associated with two-thirds of all infections (Boisvert et al., 2016). Bacteria may also exist as motile surface-associated communities within the host; therefore drug development and treatment strategies may be better informed by considering alternative growth states. Indeed, some recent research has focused on the use of peptides to specifically target biofilms (Pletzer et al., 2016), and these compounds show efficacy in treating recalcitrant abscess infections in vivo (Pletzer et al., 2018). It is interesting to consider whether compounds that specifically target swarming motility (or target both swarming and biofilms) may also exist, and whether the use of such compounds could help to prevent the dissemination of bacteria in vivo. Peptide 1037, a derivative of the human cathelicidin LL-37, was already shown to inhibit swarming motility, as well as biofilm formation (de la Fuente-Núñez et al., 2012). Peptide 1018, a cationic peptide derived from bactenecin (de la Fuente-Núñez et al., 2016), was previously shown to act against biofilms at low concentrations (de la Fuente-Núñez et al., 2014), as well as having beneficial immunomodulatory effects (Achtman et al., 2012; Rivas-Santiago et al., 2013; Wieczorek et al., 2010). Therefore, the effect of 1018 on swarming motility was investigated in greater detail. Swarming tends to correlate with other bacterial behaviours such as biofilm formation (Caiazza et al., 2007). In addition, the flagella also powers swimming motility, whereas the type IV pilus is also used for twitching; thus, there are also overlaps between these three forms of motility. It was therefore necessary to find a mutant specific for swarming motility so that the effects of other behaviours could be ruled out in an in vivo model. 6.2 The host defense peptide 1018 specifically inhibited swarming motility In contrast to the resistance of swarming cells to most tested antibiotic classes (Chapter 3), swarming motility was inhibited at low concentrations of the host defense peptide 1018 (Figure 6-1). This effect appeared to be specific to swarming motility, since swimming and twitching were unaffected at the same concentrations of 1018 (up to 20 μg/ml). 84 Figure 6-1. Peptide 1018 specifically inhibited swarming motility. n ≥ 3. 6.3 Screen of swarming-deficient mutants Next, I sought to find a mutant that would reflect the specificity of 1018 treatment (inhibited swarming but not swimming or twitching). The 233 previously-identified PA14 transposon insertion mutants (Yeung et al., 2009) were initially screened for swarming and swimming motility in BM2 glucose (swarming: 0.5% agar and 0.1% CAA; swimming: 0.25% agar and 7 mM (NH4)2SO4). A list of initial candidates was then generated using cutoffs of less than 50% WT swarming and greater than 70% WT swimming. These mutants were then screened for other relevant phenotypes including twitching, biofilm formation, and cytotoxicity (Table 6-1). Amongst these mutants, twitching motility generally did not vary from WT, but biofilm formation was often either decreased or increased. Cytotoxicity tended to be modestly decreased in these mutants, which may correlate with the observation that swarm cells overexpress virulence factors (Chapter 3). Moving forward, the mutant in ptsP was selected as the best candidate. Table 6-1. Candidate swarming-deficient mutants. Numbers shown are percent of WT. Numbers shown in bold are less than 70% of WT or significantly greater than 100% of WT. The allele numbers 1553 and 1946 designate the position (bp) of the transposon insertion for the two ptsP mutants. n ≥ 3. Tn mutant Function Swarm Swim Twitch Biofilm Cytotox-icity dsbM protein-disulfide isomerase 2.2±0.4 78.6±5.7 83.0±11.8 285.4±19 103.3±6.5 ybeB conserved hypothetical protein 2.9±1.0 82.1±8.2 34.2±2.9 22.7±3.5 49.8±5.3 epd D-erythrose 4-phosphate dehydrogenase 3.1±1.7 101.3±3.3 101.0±2.0 212.5±20 78.5±11.1 ampG permease for AmpC beta-lactamase expression 7.7±0.9 99.6±2.9 104.7±7.8 29.0±3.8 3.0±1.0 0.25 0.5 1 2 4 8 16 32050100150PA14 WT 1018 treatment1018 (g/ml)% untreated colony diameterSwarmingSwimmingTwitching85 Tn mutant Function Swarm Swim Twitch Biofilm Cytotox-icity ptsP (1553) phosphoenolpyruvate-protein phosphotransferase 10.4±1.1 86.0±4.6 107.3±13.9 82.2±3.8 57.9±4.2 PA14_59060 hypothetical protein 11.1±4.0 95.7±6.2 77.6±7.1 99.1±10.3 13.1±5.3 ptsP (1946) phosphoenolpyruvate-protein phosphotransferase 11.9±1.2 76.6±3.8 108.3±5.9 75.1±4.4 59.4±5.8 PA14_17160 intergenic PA14_17150-17170 18.0±2.0 97.2±2.9 79.6±1.6 30.9±8.6 63.2±4.7 miaA tRNA delta(2)-isopentenylpyrophosphate transferase 28.7±1.8 92.6±2.5 53.7±6.5 73.4±6.7 13.1±5.9 surE stationary phase survival protein 34.6±3.1 89.4±6.5 89.0±6.7 86.1±6.4 58.4±8.8 6.4 A mutant in ptsP was specifically inhibited for swarming motility A deletion mutant ∆ptsP was generated and complemented. Motility assays confirmed that the mutant had greatly reduced swarming motility, but relatively normal levels of swimming and twitching (Figure 6-2). The complemented strain ∆ptsP+ had substantially restored swarming motility and normal levels of swimming and twitching. Figure 6-2. The ∆ptsP mutant had deficient swarming ability but relatively normal swimming and twitching motility. n ≥ 3. To confirm that the ∆ptsP mutant had no growth deficiencies, growth curves were performed in four different media: liquid swarming media (BM2 glucose), LB, and two host-like media, SCFM and RPMI. In these four media, the ∆ptsP mutant grew no differently from WT (Figure 6-3). 86 Figure 6-3. Growth curves for the ∆ptsP mutant in four different media. n = 3. To confirm that ptsP had no effect on the production of virulence factors, qRT-PCR was performed on the ∆ptsP mutant. No significant dysregulation was observed for aprA (the T1SS alkaline metalloproteinase), lasA (T2SS cytotoxic protease), pchF (pyochelin synthetase), pcrG (a regulator in T3SS), rhlR (QS regulator) or vfr (regulator of virulence factors) (Table 6-2). As expected, ptsP was strongly downregulated in the ∆ptsP mutant, and somewhat overexpressed in the complemented ∆ptsP+ strain. Cytotoxicity was also investigated, and although the cytotoxicity of ∆ptsP was significantly decreased compared to WT, this amounted to a minor difference (~0.15 absorbance values) that was partially restored by complementation (Figure A8). In any case, the swarming phenotype (Figure 6-2) was much more dramatic than the cytotoxicity phenotype. Table 6-2. Virulence factors were not dysregulated in the ∆ptsP mutant. n = 3. Gene ∆ptsP EV vs. WT EV ∆ptsP+ vs. WT EV aprA -1.6 ± 0.2 1.0 ± 0.3 lasA 1.6 ± 1.0 3.8 ± 1.5 pchF 1.1 ± 0.2 1.4 ± 0.4 ptsP -413.7 ± 124.0 23.6 ± 11.9 pcrG 1.1 ± 0.3 -1.5 ± 0.3 rhlR -1.5 ± 0.1 -1.1 ± 0.1 vfr -1.3 ± 0.0 -1.4 ± 0.2 6.5 The swarming-deficient mutant ∆ptsP had reduced virulence in vivo Having confirmed that the mutant ∆ptsP was specifically deficient for swarming motility, we sought to test the mutant in vivo in the cutaneous abscess model, to determine whether the lack 87 of swarming had an effect on virulence. Mutant and complemented strains (2.5 x 107 CFU) were injected subdermally into the back of mice, and after incubation overnight, mice were sacrificed and internal organs were harvested and plated for CFUs. The wild type was widely disseminated amongst the organs (heart, kidney, liver, lung, and spleen) (Figure 6-4). In contrast, far fewer CFU/organ were recovered for the ∆ptsP mutant, which could be due to its deficiency in swarming motility. On average, more CFU/organ were recovered for the complemented strain ∆ptsP+ than the mutant ∆ptsP, although the difference did not always reach statistical significance. Mice treated with 1018 had an intermediate level of CFU/organ recovered, showing that 1018 was able to reduce dissemination in the host. 6.6 Discussion In this study, the ∆ptsP mutant was shown to have greatly reduced swarming ability, and organ invasion in vivo, while maintaining normal levels of swimming and twitching. PtsP is a phosphoenolpyruvate-protein phosphotransferase involved in the regulation of carbon and nitrogen metabolism. The equivalent of enzyme I Ntr (EINtr), PtsP is a cytoplasmic enzyme involved in a phosphorelay that regulates carbon and nitrogen source utilization (Higa & Edelstein, 2001; Reizer et al., 1999; Velázquez et al., 2007). PtsP has an N-terminal GAF sensor domain and is thought to function primarily as a regulator rather than directly participating in the phosphorylation (or translocation) of carbohydrates (Mavrodi et al., 2006; Reizer et al., 1999). The ptsP mutant has been identified in several screens for virulence factors in plants (Mavrodi et al., 2006; Rahme et al., 2016, 2019), C. elegans (Feinbaum et al., 2012; Tan et al., 1999) and mammals (Higa & Edelstein, 2001), although little is known about why ptsP is a virulence factor. I suggest here it may be due to the swarming deficiency of the ∆ptsP mutant. The ∆ptsP mutant was substantially but incompletely complemented by reintroducing ptsP on a plasmid. There might be valid reasons for the lack of full complementation; in this case it is possible that ptsP was expressed too highly in the ∆ptsP+ strain (Table 6-2), and that overexpression of this gene actually inhibits swarming. Furthermore, ptsP is part of a three-gene operon between rppH and PA0388, and the lack of the other two genes on the complementation plasmid may reflect a requirement for the complete operon for full restoration of wild type phenotype. A question for future exploration is why ptsP is required for swarming. Since it is possible the ∆ptsP mutant may have deficient levels of certain metabolites, attempts were made to restore swarming of the ∆ptsP mutant by adding carbon sources such as pyruvate or citrate. Addition of 88 Figure 6-4. The ∆ptsP mutant had reduced organ invasion in vivo. CD-1 mice were injected with 2.5 x 107 CFU to form a cutaneous abscess. After 16-18 h, organs were harvested, homogenized and plated for CFU counting. pyruvate enhanced swarming of both wild type and the mutant; whereas citrate inhibited wild type swarming at concentrations greater than 25 mM (data not shown); therefore firm conclusions could not be drawn. It may be that the strong dependency of swarming on medium components such as carbon and nitrogen sources affected the ability of the ∆ptsP mutant to swarm since its lack would impact on the sugars that can be readily metabolized by Pseudomonas. There may be other more subtle consequences, since e.g. ptsP in P. putida affects production of polyhydroxyalkanoates (Velázquez et al., 2007) that are precursors of rhamnolipid (Déziel et al., 2003). In conclusion, peptide 1018 inhibited swarming motility at low concentrations that had no effect on swimming or twitching. A corresponding mutant ∆ptsP was found by phenotypic screening that was also specifically inhibited for swarming, but not swimming or twitching. Testing of ∆ptsP in vivo revealed a greatly reduced organ invasion by this mutant. This indicates that swarming may play a role in bacterial dissemination in vivo. 89 Chapter 7: Conclusion 7.1 Summary of thesis work Here I have shown that swarming motility in the opportunistic pathogen P. aeruginosa is a distinct and complex adaptation. RNA-Seq comparing the transcriptome of swarming vs. swimming cells revealed that swarming cells overexpress numerous virulence and iron acquisition factors, while modestly downregulating ribosomal proteins (total 1,581 DE genes) (Chapter 3). Antibiotic susceptibility testing showed that swarming bacteria were also adaptively resistant to many antibiotic classes, including aminoglycosides, β-lactams, macrolides, chloramphenicol, ciprofloxacin, tetracycline and trimethoprim. An exception to this was the lipopeptide polymyxin B, to which swarming cells were not resistant. I focused on the aminoglycoside tobramycin and performed mutant screens, discovering that mutants in the LPS biosynthetic gene wbpW and phage-related pyocins and their regulator prtN were resistant to tobramycin under swarming conditions. Membrane permeability assays confirmed that the mutant in wbpW had reduced membrane permeabilization to tobramycin. In total, I found 41 mutants that were resistant to tobramycin under swarming conditions, indicating that swarming-mediated antibiotic resistance is a multigenic phenomenon. I also treated swarming cells with subinhibitory tobramycin and used RNA-Seq to discover that the multidrug efflux pump MexXY was upregulated. To date, this is the first time that efflux has been demonstrated as a mechanism of resistance for swarming cells, since previous mutant studies failed to find an association, possibly due to the presence of redundant efflux systems (Lai et al., 2009). This study also advances the field by employing RNA-Seq to more accurately describe the transcriptome of swarming cells, including 104 dysregulated regulatory factors and the genes corresponding to the 41 mutants that were resistant to tobramycin under swarming conditions, whereas relatively little was previously known concerning specific mechanisms of antibiotic resistance in swarming cells. Similar to polymyxin B, I found that swarm cells displayed susceptibility to the cationic peptide 1018 (Chapter 6). Tendril formation was completely inhibited at concentrations greater than 2 μg/ml, while swimming and twitching proceeded normally up to 20 μg/ml. This suggests that 1018 may have specific anti-swarming properties and could be used to target swarming cells in cases where antibiotics may be less effective. To investigate this further, I identified a swarming-specific mutant in ptsP. In vivo testing in an acute murine infection model revealed that 1018 treatment reduced bacterial dissemination in internal organs, and the ∆ptsP mutant was recovered at even lower rates from organs. This is an interesting finding in the field of swarming motility, 90 since to date little has been done to directly investigate the role of swarming in vivo. To learn more about the regulation of swarming motility, in addition to transcriptional regulators, I studied sRNAs dysregulated under swarming conditions by overexpressing them and screening for phenotypes (Chapters 4 and 5). The screens revealed a strain overexpressing the sRNA, PA0805.1, that possessed numerous phenotypes, including reduced motility (swarming, swimming and twitching), and increased adherence, cytotoxicity and tobramycin resistance (Chapter 4). RNA-Seq and proteomics revealed broad transcriptomic and proteomic changes, including 118 regulatory factors, downregulated pilus genes, upregulated adherence and virulence factors, and upregulated multidrug efflux systems (total 1,121 DE genes and 925 DE proteins), suggestive of a hierarchical network. A deletion mutant ∆PA0805.1 was also constructed and was supersusceptible to tobramycin under swarming conditions. Another sRNA overexpressing strain, PA2952.1, was studied and showed to have reductions in swarming and swimming but not twitching (Chapter 5). Overexpression of this sRNA also led to resistance to tobramycin and gentamicin, and supersusceptibility to trimethoprim. Transcriptomic and proteomic approaches uncovered 784 DE genes and 445 proteins with differential abundance. This included downregulated pili genes, dysregulated flagellar genes, upregulated multidrug efflux genes mexGH, upregulated LPS modification operon arnBCATF, and dysregulated DNA synthesis genes. The large transcriptomes of the sRNAs PA0805.1 and PA2952.1 are relatively unprecedented for sRNAs (Chapters 4 and 5). The transcriptomes of mutants in the RNA-binding proteins Hfq and Rsm also indicate hundreds of differentially expressed genes (Romero et al., 2018; Sonnleitner et al., 2018), consistent with the conclusion that PA0805.1 and PA2952.1 might serve key regulatory functions in P. aeruginosa. The sRNA prrH was also studied and shown to be involved in the production of the siderophore pyoverdine and cytotoxicity against HBE cells, a new addition to its previously described phenotypes (Chapter 5). In addition, overexpression of prrH led to reduced swimming motility. Two other sRNAs, PA14sr120 (a short version of PA0805.1) and PA1091.1b, were also shown to be involved in tobramycin resistance and trimethoprim susceptibility, respectively. These studies contribute to the field by providing phenotypic characterization of more than a dozen sRNAs, most of which were previously completely uncharacterized. Therefore, swarming motility is a behaviour conferring antibiotic resistance (but inhibited by 1018) that is regulated by sRNAs and likely plays a role in invasiveness in vivo. 91 7.2 Applications These studies provide insights into the reasons behind observations that standard antimicrobial susceptibility testing does not always accurately predict in vivo efficacy (Ersoy et al., 2017). It shows that bacteria may enter a state of reduced drug susceptibility due to their growth as multicellular communities, such as swarming colonies or as shown by others, biofilms. Research in this thesis shows that lipopeptides or cationic peptides may be more effective against swarming bacteria than other antimicrobial agents; in particular, peptide 1018 already shows promise as an anti-swarming agent. Efflux pump inhibitors in combination with other antimicrobial drugs (Wang et al., 2016) may be another potential venue for investigation, based on RNA-Seq results of subinhibitory tobramycin treatment, which showed that MexXY was upregulated. If swarm cells have decreased outer membrane permeability, then agents that increase membrane permeability may be useful as well (Vaara, 1992). sRNAs also have potential applications as therapeutics, since they are relatively easy to synthesize and customize, and could be used to reverse specific drug resistance mechanisms (Chan et al., 2017; Di Noto et al., 2019). Potential delivery systems include nanoparticles, phages, extracellular vesicles, liposomes and the CRISPR-Cas system (Di Noto et al., 2019). sRNAs themselves, or a complementary RNA to silence the sRNA, may have use in modifying bacterial behaviour. Swarming and motility-inhibitory sRNAs could have benefits in acute infections, and PA2952.1 could be used in conjunction with trimethoprim, to which cells are sensitized. Conversely, an anti-sense version of PA0805.1 could be used to sequester PA0805.1, decrease expression of virulence factors, efflux pumps, and bacterial adhesion, leading to improved patient outcomes. Inhibiting prrH is another intriguing possibility, since bacteria may have difficulty surviving in the iron-depleted host environment without appropriate regulation of iron acquisition and utilization. In fact, mutants in Fur are conditionally essential (Pasqua et al., 2017), and decreased virulence could be another added benefit. 7.3 Future directions In this study, resistome genes were mined from the literature and used in combination with RNA-Seq and qRT-PCR data to identify initial candidates. Future work could include a comprehensive mutant library screen, or a Tn-Seq (transposon sequencing) library screen, in order to determine if any other candidates may be present at a genome-wide scale. Tn-Seq would provide additional information about mutants that survived or were eliminated, and also the relative abundance or fitness of different mutants. Tn-Seq data could be compared back to data generated 92 in this thesis to provide additional support. This could be done on swarming colonies in the presence and absence of tobramycin. Luminescent reporter strains could also be constructed for key swarming regulators in order to assess expression in vivo. Antimicrobial agents could be developed to specifically inhibit swarming motility by screening drugs in the swarming agar dilution assay, or this assay could be added as an additional step during drug screening and development to better inform on the response of bacteria grown under different conditions. The swarming assay can be modified to allow more high throughput methods, such as the 6 well format (Section 2.2.6), or a 96 well stamp on large square plates (Yeung et al., 2009). Such anti-swarming agents could then be tested alone or in combination with conventional antibiotics, to investigate potential synergistic effects. The mechanism by which 1018 inhibits swarming motility is another question for further research. Some research has already been done to address this question, including a mutant library screen and RNA-Seq of 1018-treated swarming colonies (Wilkinson, 2018), but further in-depth characterization of mutants or Tn-Seq could provide more mechanistic detail. Likewise, the mechanism causing inhibition of swarming in the ∆ptsP mutant is unclear and could be addressed by further characterization of the mutant, possibly by RNA-Seq. Further screening of sRNAs could be performed to find an ideal sRNA that would modify bacterial behaviour as desired. Computer modeling approaches could come into play, and predictions could be easily tested since nucleic acids are inexpensive to synthesize and easy to manipulate. In addition, combinations of sRNAs could be used to achieve a desired effect. It would be interesting to transform multiple sRNAs into one strain and overexpress them simultaneously to observe cumulative effects. Further characterization of the sRNAs PA0805.1 and PA2952.1 could also clarify specific sRNA targets by experimental approaches such as (G)RIL-Seq (Han et al., 2016; Melamed et al., 2018), where sRNAs are ligated to target mRNAs and then sequenced. It seems likely that PA0805.1 and PA2952.1 would have many targets, given the extensive downstream effects, and it would clarify the mechanism to validate targets experimentally. 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Agar concentrations were: 0.5% (swarming), cf. 0.3% (swimming), and 1.5% (spread plate). n ≥ 3. 109 Figure A2. Venn diagrams showing common and unique genes for omic comparisons. 110 Figure A3. Scatterplots showing correlations of common genes for omic comparisons. Numbers in the four corners of each graph show the number of genes/proteins found in each quadrant. 111 Figure A4. Growth curves of sRNA overexpression strains in BM2 glycerol with 1% arabinose showed little difference compared to EV. n ≥ 3. Figure A5. Adherence of sRNA overexpression strains to polystyrene plates. Statistically significant differences were determined using one-way ANOVA. n ≥ 3. Figure A6. Cytotoxicity phenotypes of sRNA overexpression strains with 1% arabinose. a) overexpression of PA2952.1 compared to WT EV. b) deletion and overexpression of prrH. Statistically significant differences were determined by unpaired t test (a) or one-way ANOVA (b). n ≥ 3. 0 250 500 7500.06250.1250.250.51Growth curve (BM2 glycerol)Time (minutes)OD600nmWT EVPA0730.1PA5304.1PA2461.1PA2952.1PA2461.3PA0958.1PA0805.1PA4539.1WT +srbAPA4656.1bPA1091.1bWT +rsmYPA2952.1WPA14sr120PA0805.1a PA3159.1bPA4656.1aPA5078.1PA1091.1aPA3159.1aWT EVPA0730.1PA0805.1aPA14sr120PA0958.1PA1091.1aPA1091.1bPA2461.1PA2461.3PA2952.1PA2952.1WPA3159.1aPA3159.1bPA4539.1PA4656.1aPA4656.1bPA5078.1PA5304.1rsmYsrbA0.000.050.100.150.200.25Adherence to polystyreneA595nm112 Figure A7. Subinhibitory trimethoprim inhibited the growth of the PA2952.1 overexpression strain in standard MICs in BM2 glycerol with 1% arabinose. n = 3. Figure A8. Cytotoxicity phenotype of the ∆ptsP mutant. Statistically significant differences were determined by ANOVA. n ≥ 3. WT EV ptsP EV ptsP+WT +ptsP0.00.20.40.60.8Cytotoxicity vs. HBEA492-A900nmns*****113 Appendix B Supplementary Tables B.1 PA14 RNA-Seq data Table A1. Compilation of all PA14 RNA-Seq data reported in this thesis. PAO1 PA14 Name Product Name Swarm vs. swim TOB vs. UNTR FC padj FC padj PA0007 PA14_00080 hypothetical protein 1.93 1.9E-22 PA0013 PA14_00140 conserved hypothetical protein -1.92 2.9E-22 PA0026 PA14_00300 plcB phospholipase C, PlcB 1.87 8.9E-19 PA0027 PA14_00310 hypothetical protein 2.81 1.0E-28 PA0028 PA14_00320 hypothetical protein 3.45 3.2E-38 PA0038 PA14_00470 hypothetical protein 1.77 4.3E-13 PA0039 PA14_00480 hypothetical protein 2.28 9.1E-38 PA14_00520 hypothetical protein -2.11 8.5E-03 PA0044 PA14_00560 exoT exoenzyme T -1.93 4.3E-03 PA0045 PA14_00570 hypothetical protein -2.21 5.1E-41 -1.85 1.5E-02 PA0046 PA14_00580 hypothetical protein -2.07 7.4E-38 PA0047 PA14_00590 hypothetical protein -2.32 3.5E-39 PA0048 PA14_00600 probable transcriptional regulator 1.66 9.1E-06 PA0050 PA14_00630 hypothetical protein -1.97 5.0E-13 PA0051 PA14_00640 phzH potential phenazine-modifying enzyme -1.85 4.7E-05 PA0052 PA14_00650 hypothetical protein 2.25 9.3E-16 PA0056 PA14_00680 probable transcriptional regulator 1.53 2.0E-03 PA0057 PA14_00690 hypothetical protein -1.80 1.2E-09 PA0059 PA14_00710 osmC osmotically inducible protein OsmC 2.84 6.4E-22 PA0060 PA14_00720 conserved hypothetical protein 2.41 6.7E-29 PA0062 PA14_00740 hypothetical protein 1.52 4.1E-05 PA0071 PA14_00830 tagR1 TagR1 -1.83 8.1E-03 PA0073 PA14_00860 tagT1 TagT1 1.81 4.2E-06 PA0074 PA14_00875 ppkA serine/threonine protein kinase PpkA 1.62 2.7E-10 PA0075 PA14_00890 pppA PppA 1.50 1.2E-05 PA0076 PA14_00900 tagF1 TagF1 1.50 5.4E-08 PA0078 PA14_00925 tssL1 TssL1 1.56 1.0E-09 1.77 4.1E-02 PA0098 PA14_01190 hypothetical protein 1.51 2.8E-04 PA0099 PA14_01200 type VI effector protein 1.62 3.3E-08 PA0100 PA14_01220 hypothetical protein 1.58 7.2E-09 PA0101 PA14_01230 hypothetical protein 1.56 9.9E-06 PA0105 PA14_01290 coxB cytochrome c oxidase, subunit II 3.16 1.6E-33 114 PA0106 PA14_01300 coxA cytochrome c oxidase, subunit I 6.55 1.2E-33 PA0107 PA14_01310 conserved hypothetical protein 8.87 1.1E-26 PA0108 PA14_01320 coIII cytochrome c oxidase, subunit III 7.91 1.7E-29 1.58 1.8E-02 PA0109 PA14_01330 hypothetical protein 1.76 5.8E-07 PA0110 PA14_01340 hypothetical protein 6.13 2.3E-29 PA0111 PA14_01350 hypothetical protein 6.28 2.3E-17 PA0112 PA14_01360 hypothetical protein 7.42 2.1E-27 PA0113 PA14_01380 probable cytochrome c oxidase assembly factor 7.52 1.2E-19 PA0114 PA14_01390 senC SenC -1.68 2.1E-14 PA0122 PA14_01490 rahU rahU 1.71 4.4E-18 -1.82 7.8E-03 PA0128 PA14_01560 conserved hypothetical protein -1.67 1.2E-12 PA0132 PA14_01620 bauA Beta-alanine:pyruvate transaminase -2.26 1.1E-15 PA0141 PA14_01730 conserved hypothetical protein 2.46 1.4E-15 PA0142 PA14_01750 hypothetical protein -1.87 5.6E-12 PA0144 PA14_01780 hypothetical protein 1.65 1.8E-04 PA0151 PA14_01870 probable TonB-dependent receptor -1.58 9.0E-05 PA0153 PA14_01900 pcaH protocatechuate 3,4-dioxygenase, beta subunit 3.01 1.1E-12 PA0154 PA14_01910 pcaG protocatechuate 3,4-dioxygenase, alpha subunit 3.56 2.9E-12 PA0156 PA14_01940 triA Resistance-Nodulation-Cell Division (RND) triclosan efflux membrane fusion protein, TriA 1.64 6.6E-12 PA0164 PA14_02050 probable gamma-glutamyltranspeptidase -1.60 1.9E-08 PA0165 PA14_02060 hypothetical protein -2.20 1.9E-22 PA0166 PA14_02070 probable transporter -1.84 2.9E-02 PA0169 PA14_02110 siaD SiaD -2.53 6.3E-20 PA0170 PA14_02130 hypothetical protein -3.14 6.7E-20 PA0171 PA14_02140 hypothetical protein -2.98 1.7E-14 PA0172 PA14_02150 siaA SiaA -2.74 4.9E-48 PA0173 PA14_02180 probable methylesterase 2.80 1.7E-15 PA0174 PA14_02190 conserved hypothetical protein 2.52 3.5E-13 PA0175 PA14_02200 probable chemotaxis protein methyltransferase 1.92 3.8E-11 PA0176 PA14_02220 aer2 aerotaxis transducer Aer2 1.74 1.8E-13 PA0177 PA14_02230 probable purine-binding chemotaxis protein 1.73 7.0E-09 PA0178 PA14_02250 probable two-component sensor 1.60 5.2E-09 PA0179 PA14_02260 probable two-component response regulator 1.51 4.4E-07 115 PA0185 PA14_02340 probable permease of ABC transporter -1.56 5.0E-02 PA0187 PA14_02360 hypothetical protein -1.62 2.0E-04 PA0191 PA14_02390 probable transcriptional regulator -1.96 3.4E-08 PA0193 PA14_02410 hypothetical protein -3.63 8.6E-07 PA0195 PA14_02450 pntAA putative NAD(P) transhydrogenase, subunit alpha part 1 -1.98 5.1E-04 PA0195.1 PA14_02470 pntAB putative NAD(P) transhydrogenase, subunit alpha part 2 -1.65 2.5E-02 PA0197 PA14_02490 tonB2 hypothetical protein -2.98 3.7E-07 PA0198 PA14_02500 exbB1 transport protein ExbB -1.54 1.1E-02 PA0200 PA14_02520 hypothetical protein 1.56 5.7E-03 -2.06 4.1E-02 PA0201 PA14_02530 hypothetical protein -2.96 6.1E-27 PA0209 PA14_02560 conserved hypothetical protein 2.01 1.2E-03 PA0210 PA14_02570 mdcC malonate decarboxylase subunit delta 2.46 4.5E-03 PA0211 PA14_02580 mdcD malonate decarboxylase beta subunit 2.07 2.9E-05 PA0212 PA14_02590 mdcE malonate decarboxylase gamma subunit 2.48 5.7E-07 PA0213 PA14_02610 hypothetical protein 2.40 7.9E-05 PA0214 PA14_02620 probable acyl transferase 2.81 1.4E-09 PA0216 PA14_02640 malonate transporter MadM 1.90 1.4E-05 PA0221 PA14_02700 probable aminotransferase 1.62 1.8E-02 PA0222 PA14_02720 hypothetical protein 1.72 3.5E-02 PA0223 PA14_02730 probable dihydrodipicolinate synthetase 1.61 1.2E-03 PA0226 PA14_02760 probable CoA transferase, subunit A 1.74 2.8E-11 PA0227 PA14_02770 probable CoA transferase, subunit B 2.27 1.1E-16 PA0228 PA14_02790 pcaF beta-ketoadipyl CoA thiolase PcaF 2.45 5.3E-15 PA0229 PA14_02810 pcaT dicarboxylic acid transporter PcaT 2.71 1.1E-15 PA0230 PA14_02830 pcaB 3-carboxy-cis,cis-muconate cycloisomerase 2.26 2.3E-19 PA0231 PA14_02840 pcaD beta-ketoadipate enol-lactone hydrolase 2.14 3.4E-16 PA0232 PA14_02850 pcaC gamma-carboxymuconolactone decarboxylase 2.44 1.1E-19 PA0233 PA14_02870 probable transcriptional regulator 1.51 1.9E-08 PA0234 PA14_02890 hypothetical protein -1.91 7.1E-05 PA0235 PA14_02900 pcaK 4-hydroxybenzoate transporter PcaK 1.51 2.9E-03 PA0240 PA14_02980 probable porin 2.19 1.1E-08 PA0241 PA14_02990 probable major facilitator superfamily (MFS) transporter 2.19 1.3E-09 PA0242 PA14_03000 hypothetical protein 4.08 2.6E-29 116 PA0248 PA14_03070 probable transcriptional regulator 1.65 9.0E-06 PA0263 PA14_03240 hcpC secreted protein Hcp -2.17 4.2E-04 PA1512 PA14_03240 hcpA secreted protein Hcp -2.17 4.2E-04 PA5267 PA14_03240 hcpB secreted protein Hcp -2.17 4.2E-04 PA0979 PA14_03290 conserved hypothetical protein -1.56 2.9E-02 PA14_03390 hypothetical protein -2.02 6.6E-08 PA14_03400 hypothetical protein -4.31 1.7E-13 PA0269 PA14_03490 conserved hypothetical protein 1.64 2.1E-05 PA0270 PA14_03510 hypothetical protein 2.22 1.1E-18 PA0271 PA14_03520 hypothetical protein 2.04 3.0E-13 PA0275 PA14_03580 probable transcriptional regulator 1.52 9.8E-07 PA0277 PA14_03610 conserved hypothetical protein -2.66 1.1E-38 PA0278 PA14_03620 hypothetical protein -2.40 4.4E-08 PA0280 PA14_03650 cysA sulfate transport protein CysA -2.23 7.2E-15 PA0281 PA14_03670 cysW sulfate transport protein CysW -2.85 5.2E-22 -1.67 2.6E-02 PA0282 PA14_03680 cysT sulfate transport protein CysT -2.97 1.7E-21 PA0283 PA14_03700 sbp sulfate-binding protein precursor -3.23 2.8E-23 -1.86 5.3E-03 PA0284 PA14_03710 hypothetical protein -2.86 1.0E-15 PA0286 PA14_03730 desA delta-9 fatty acid desaturase, DesA -1.68 5.8E-14 PA0287 PA14_03760 gpuP sodium:solute symporter -3.14 3.4E-16 PA0288 PA14_03770 gpuA 3-guanidinopropionase -2.49 1.2E-11 PA0291 PA14_03800 oprE Anaerobically-induced outer membrane porin OprE precursor -2.74 3.4E-69 PA0297 PA14_03870 spuA probable glutamine amidotransferase -1.72 9.3E-10 PA0320 PA14_04180 carO calcium-regulated OB-fold protein CarO -1.86 3.0E-11 PA0324 PA14_04230 probable permease of ABC transporter -1.96 4.1E-02 PA0328 PA14_04290 aaaA arginine-specific autotransporter of Pseudomonas aeruginosa, AaaA -1.56 2.8E-12 PA0340 PA14_04440 conserved hypothetical protein -1.76 1.6E-14 PA0341 PA14_04460 lgt prolipoprotein diacylglyceryl transferase -1.65 2.9E-21 PA0344 PA14_04510 hypothetical protein 2.10 5.4E-18 PA0345 PA14_04520 hypothetical protein 1.84 1.8E-16 PA0346 PA14_04530 hypothetical protein 1.95 5.9E-09 PA0352 PA14_04610 probable transporter -1.67 5.6E-17 PA0355 PA14_04650 pfpI protease PfpI 3.49 1.3E-23 PA14_04710 hypothetical protein -2.72 7.2E-38 PA0364 PA14_04780 laoA LaoA 2.06 5.7E-12 PA0365 PA14_04790 laoB LaoB 1.86 1.3E-14 117 PA0366 PA14_04810 laoC LaoC 1.99 1.9E-16 PA0367 PA14_04820 laoR LaoR 1.62 4.4E-14 PA0383 PA14_05010 conserved hypothetical protein -1.85 7.9E-13 PA0385 PA14_05030 hypothetical protein -1.55 6.0E-07 PA0386 PA14_05040 probable oxidase -1.53 3.0E-06 PA0389 PA14_05070 hypothetical protein -1.50 1.6E-14 PA0390 PA14_05080 metX homoserine O-acetyltransferase -1.61 1.3E-21 PA0409 PA14_05330 pilH twitching motility protein PilH -1.51 2.7E-02 PA0413 PA14_05390 chpA component of chemotactic signal transduction system 1.67 3.3E-41 PA0414 PA14_05400 chpB probable methylesterase 1.71 1.1E-21 PA0422 PA14_05500 conserved hypothetical protein -2.73 3.3E-51 PA0433 PA14_05630 hypothetical protein 2.72 6.0E-10 PA0434 PA14_05640 hypothetical protein 3.27 8.2E-05 PA0435 PA14_05650 hypothetical protein 2.46 5.5E-05 PA0443 PA14_05790 probable transporter -1.90 1.0E-02 PA0450 PA14_05870 probable phosphate transporter -1.52 2.9E-03 PA0451 PA14_05880 conserved hypothetical protein 1.64 2.5E-06 1.90 1.4E-02 PA0459 PA14_06000 probable ClpA/B protease ATP binding subunit 1.86 2.0E-10 PA0471 PA14_06170 fiuR FiuR 1.68 1.0E-04 PA0472 PA14_06180 fiuI FiuI 1.54 3.0E-05 PA0480 PA14_06270 hydrolase 2.49 7.5E-08 PA0484 PA14_06310 conserved hypothetical protein 1.74 5.5E-11 PA0485 PA14_06320 conserved hypothetical protein -1.57 2.7E-07 PA0490 PA14_06390 hypothetical protein 1.62 1.0E-07 PA0506 PA14_06600 probable acyl-CoA dehydrogenase -1.67 4.0E-20 PA0509 PA14_06650 nirN NirN -3.32 1.2E-19 PA0510 PA14_06660 nirE NirE -2.91 2.1E-11 PA0511 PA14_06670 nirJ heme d1 biosynthesis protein NirJ -3.19 4.9E-18 PA0512 PA14_06680 nirH hypothetical protein -2.69 1.2E-11 PA0513 PA14_06690 nirG transcriptional regulator -3.19 1.8E-13 PA0514 PA14_06700 nirL heme d1 biosynthesis protein NirL -2.92 9.1E-12 PA0515 PA14_06710 transcriptional regulator -3.38 5.4E-13 PA0516 PA14_06720 nirF heme d1 biosynthesis protein NirF -3.37 2.7E-16 PA0517 PA14_06730 nirC c-type cytochrome -3.30 5.1E-23 PA0518 PA14_06740 nirM cytochrome c-551 precursor -4.27 1.4E-35 PA0519 PA14_06750 nirS nitrite reductase precursor -4.52 7.5E-27 PA0520 PA14_06770 nirQ regulatory protein NirQ -2.93 4.6E-21 PA0521 PA14_06790 cytochrome c oxidase subunit -5.78 1.2E-23 118 PA0522 PA14_06800 hypothetical protein -10.38 3.8E-26 PA0523 PA14_06810 norC nitric-oxide reductase subunit C -13.47 8.4E-28 PA0524 PA14_06830 norB nitric-oxide reductase subunit B -13.04 2.0E-32 PA0525 PA14_06840 probable dinitrification protein NorD -13.77 2.6E-31 PA0526 PA14_06860 hypothetical protein -1.52 4.1E-05 PA0534 PA14_06960 pauB1 FAD-dependent oxidoreductase -4.68 3.4E-94 PA0535 PA14_06970 probable transcriptional regulator -1.64 2.5E-09 PA0543 PA14_07050 hypothetical protein 1.76 2.0E-06 PA0546 PA14_07090 metK methionine adenosyltransferase 1.78 2.3E-38 PA0547 PA14_07110 probable transcriptional regulator 1.74 8.7E-27 PA0553 PA14_07200 hypothetical protein 1.51 2.1E-16 PA0561 PA14_07300 hypothetical protein -1.58 1.6E-13 PA0567 PA14_07370 conserved hypothetical protein 2.28 7.7E-12 2.03 4.4E-02 PA0572 PA14_07430 hypothetical protein 2.46 4.5E-23 PA14_07460 hypothetical protein -2.03 1.2E-16 -1.50 2.5E-02 PA14_07480 reverse transcriptase -1.52 2.0E-02 PA0602 PA14_07850 probable binding protein component of ABC transporter 1.84 5.2E-19 PA0607 PA14_07910 rpe ribulose-phosphate 3-epimerase -1.65 4.9E-13 PA0608 PA14_07930 probable phosphoglycolate phosphatase -1.51 5.7E-08 -1.72 4.1E-02 PA0612 PA14_07970 ptrB repressor, PtrB -4.54 6.4E-41 PA0613 PA14_07980 hypothetical protein -4.34 2.1E-63 PA0614 PA14_07990 hypothetical protein -4.50 4.8E-47 PA0615 PA14_08000 hypothetical protein -2.61 9.5E-48 PA0616 PA14_08010 hypothetical protein -3.61 1.6E-81 PA0617 PA14_08020 probable bacteriophage protein -4.82 1.8E-63 PA0618 PA14_08030 probable bacteriophage protein -5.28 1.8E-106 PA0619 PA14_08040 probable bacteriophage protein -5.82 3.8E-79 PA0620 PA14_08050 probable bacteriophage protein -4.09 1.5E-136 PA0621 PA14_08060 conserved hypothetical protein -3.92 1.0E-24 PA0622 PA14_08070 probable bacteriophage protein -8.13 1.2E-290 PA0623 PA14_08090 probable bacteriophage protein -7.41 6.1E-221 PA0624 PA14_08100 hypothetical protein -6.43 1.1E-110 PA14_08110 hypothetical protein -6.95 1.8E-56 PA0625 PA14_08120 hypothetical protein -5.42 1.1E-133 119 PA0626 PA14_08130 hypothetical protein -4.62 2.9E-108 PA0627 PA14_08140 conserved hypothetical protein -4.31 6.1E-27 PA0628 PA14_08150 conserved hypothetical protein -5.15 4.8E-133 PA0629 PA14_08160 conserved hypothetical protein -6.46 7.3E-69 PA0630 PA14_08180 hypothetical protein -6.29 1.1E-42 PA0631 PA14_08190 hypothetical protein -8.11 5.8E-29 PA0632 PA14_08200 hypothetical protein -8.56 1.0E-41 PA0633 PA14_08210 hypothetical protein -6.66 2.8E-231 PA0634 PA14_08220 hypothetical protein -6.08 1.7E-136 PA0635 PA14_08230 hypothetical protein -6.78 9.9E-127 PA0636 PA14_08240 hypothetical protein -5.63 2.9E-172 PA0637 PA14_08250 conserved hypothetical protein -5.24 6.9E-46 PA0638 PA14_08260 probable bacteriophage protein -5.43 6.9E-104 PA0639 PA14_08270 conserved hypothetical protein -6.13 5.2E-122 PA0640 PA14_08280 probable bacteriophage protein -5.06 9.1E-84 PA0641 PA14_08300 probable bacteriophage protein -5.05 2.1E-284 PA0646 PA14_08310 hypothetical protein -1.68 2.1E-15 PA0650 PA14_08350 trpD anthranilate phosphoribosyltransferase -1.51 4.1E-02 PA0654 PA14_08390 speD S-adenosylmethionine decarboxylase proenzyme -2.78 2.2E-86 PA4280 PA14_08620 birA BirA bifunctional protein -1.70 2.7E-25 PA4279 PA14_08630 pantothenate kinase -1.68 8.7E-15 PA4278 PA14_08640 hypothetical protein -1.67 5.2E-11 PA4266 PA14_08820 fusA1 elongation factor G -1.62 1.0E-15 PA4277 PA14_08680 tufB elongation factor Tu -1.60 1.6E-26 PA4270 PA14_08760 rpoB DNA-directed RNA polymerase beta chain -1.62 7.5E-17 PA4268 PA14_08790 rpsL 30S ribosomal protein S12 -1.53 3.0E-10 PA4267 PA14_08810 rpsG 30S ribosomal protein S7 -1.58 8.0E-13 -1.67 2.1E-02 PA4265 PA14_08830 tufA elongation factor Tu -1.51 7.4E-16 PA4264 PA14_08840 rpsJ 30S ribosomal protein S10 -1.64 2.6E-15 PA4263 PA14_08850 rplC 50S ribosomal protein L3 -1.79 6.9E-20 120 PA4262 PA14_08860 rplD 50S ribosomal protein L4 -1.91 5.0E-29 PA4261 PA14_08870 rplW 50S ribosomal protein L23 -1.93 1.1E-23 PA4260 PA14_08880 rplB 50S ribosomal protein L2 -1.96 2.0E-25 PA4259 PA14_08890 rpsS 30S ribosomal protein S19 -1.95 5.2E-26 -1.78 2.8E-02 PA4258 PA14_08900 rplV 50S ribosomal protein L22 -1.88 5.2E-19 PA4257 PA14_08910 rpsC 30S ribosomal protein S3 -1.88 8.1E-24 PA4256 PA14_08920 rplP 50S ribosomal protein L16 -1.88 6.8E-23 PA4255 PA14_08930 rpmC 50S ribosomal protein L29 -1.76 5.3E-18 PA4254 PA14_08940 rpsQ 30S ribosomal protein S17 -1.88 3.6E-26 PA4253 PA14_08950 rplN 50S ribosomal protein L14 -1.78 4.2E-27 PA4252 PA14_08960 rplX 50S ribosomal protein L24 -1.72 8.5E-27 PA4251 PA14_08970 rplE 50S ribosomal protein L5 -1.60 1.8E-28 PA4250 PA14_08980 rpsN 30S ribosomal protein S14 -1.58 2.6E-30 PA4249 PA14_08990 rpsH 30S ribosomal protein S8 -1.66 5.4E-12 PA4248 PA14_09000 rplF 50S ribosomal protein L6 -1.73 3.4E-14 PA4247 PA14_09010 rplR 50S ribosomal protein L18 -1.71 5.8E-12 PA4246 PA14_09020 rpsE 30S ribosomal protein S5 -1.78 1.5E-15 PA4245 PA14_09030 rpmD 50S ribosomal protein L30 -1.80 3.5E-13 PA4244 PA14_09040 rplO 50S ribosomal protein L15 -1.70 1.2E-15 PA4243 PA14_09050 secY secretion protein SecY -1.54 1.1E-08 PA4241 PA14_09080 rpsM 30S ribosomal protein S13 -1.61 3.0E-12 PA4240 PA14_09090 rpsK 30S ribosomal protein S11 -1.75 2.8E-26 PA4239 PA14_09100 rpsD 30S ribosomal protein S4 -1.66 6.1E-17 PA4238 PA14_09115 rpoA DNA-directed RNA polymerase alpha chain -1.56 1.8E-16 PA4232 PA14_09200 ssb single-stranded DNA-binding protein -1.59 1.3E-30 PA4231 PA14_09210 pchA salicylate biosynthesis isochorismate synthase 8.11 8.0E-51 PA4230 PA14_09220 pchB salicylate biosynthesis protein PchB 7.32 8.6E-36 -1.65 2.3E-02 PA4229 PA14_09230 pchC pyochelin biosynthetic protein PchC 5.03 5.8E-26 PA4228 PA14_09240 pchD pyochelin biosynthesis protein PchD 5.12 1.2E-29 PA4227 PA14_09260 pchR transcriptional regulator PchR 3.79 5.6E-28 PA4226 PA14_09270 pchE dihydroaeruginoic acid synthetase 5.77 2.5E-41 PA4225 PA14_09280 pchF pyochelin synthetase 6.85 1.9E-56 PA4224 PA14_09290 pchG pyochelin biosynthetic protein PchG 7.94 8.9E-55 PA4223 PA14_09300 probable ATP-binding component of ABC transporter 7.87 3.8E-63 PA4222 PA14_09320 probable ATP-binding component of ABC transporter 9.07 3.9E-78 PA4221 PA14_09340 fptA Fe(III)-pyochelin outer membrane receptor precursor 3.88 1.8E-25 -1.73 7.9E-03 121 PA4220 PA14_09350 hypothetical protein 3.90 1.7E-46 PA4219 PA14_09370 ampO AmpO 3.67 5.2E-26 PA4218 PA14_09380 ampP AmpP 4.41 2.8E-30 PA4217 PA14_09400 phzS flavin-containing monooxygenase 2.28 3.1E-16 PA1905 PA14_09410 phzG2 probable pyridoxamine 5'-phosphate oxidase 2.41 9.7E-13 PA4216 PA14_09410 phzG1 probable pyridoxamine 5'-phosphate oxidase 2.41 9.7E-13 PA1903 PA14_09440 phzE2 phenazine biosynthesis protein PhzE 2.53 3.4E-21 PA4214 PA14_09440 phzE1 phenazine biosynthesis protein PhzE 2.53 3.4E-21 PA1902 PA14_09450 phzD2 phenazine biosynthesis protein PhzD 2.37 3.9E-13 PA4213 PA14_09450 phzD1 phenazine biosynthesis protein PhzD 2.37 3.9E-13 PA14_09460 phzC1 phenazine biosynthesis protein PhzC 2.23 3.2E-10 PA4211 PA14_09470 phzB1 probable phenazine biosynthesis protein 2.15 3.4E-08 PA4209 PA14_09490 phzM probable phenazine-specific methyltransferase 1.82 1.1E-08 -1.52 2.8E-02 PA4208 PA14_09500 opmD probable outer membrane protein precursor 1.77 1.3E-22 PA4207 PA14_09520 mexI probable Resistance-Nodulation-Cell Division (RND) efflux transporter 1.59 2.0E-23 PA4204 PA14_09550 ppgL periplasmic gluconolactonase, PpgL 1.90 3.0E-12 PA4198 PA14_09660 probable AMP-binding enzyme -1.91 7.1E-08 PA4197 PA14_09680 bfiS BfiS -1.71 5.4E-09 PA4189 PA14_09710 probable aldehyde dehydrogenase 1.74 1.4E-03 PA4187 PA14_09740 probable major facilitator superfamily (MFS) transporter 1.83 1.2E-02 PA4182 PA14_09790 hypothetical protein -1.54 1.3E-13 PA4181 PA14_09810 hypothetical protein -2.04 9.5E-19 PA4179 PA14_09850 probable porin -2.13 4.4E-04 PA4178 PA14_09870 eftM SAM-dependent methyltransferase , EftM -3.07 3.0E-25 PA4177 PA14_09880 hypothetical protein 2.37 4.6E-08 PA4175 PA14_09900 piv protease IV 2.36 1.5E-13 PA4172 PA14_09930 probable nuclease 3.09 5.6E-27 PA4171 PA14_09940 probable protease 2.92 4.8E-25 PA4168 PA14_09970 fpvB second ferric pyoverdine receptor FpvB -2.35 1.4E-02 PA4167 PA14_09980 probable oxidoreductase -2.45 1.1E-03 PA4166 PA14_09990 probable acetyltransferase -2.48 5.5E-11 PA14_10090 LysR family transcriptional regulator 1.57 3.4E-06 PA4152 PA14_10240 probable hydrolase 2.12 3.3E-03 122 PA4144 PA14_10330 probable outer membrane protein precursor 2.04 4.0E-07 PA4143 PA14_10340 probable toxin transporter 2.10 4.0E-08 PA4142 PA14_10350 probable secretion protein 2.68 7.3E-14 PA4141 PA14_10360 hypothetical protein 2.33 3.8E-13 -2.38 5.0E-07 PA4140 PA14_10370 hypothetical protein -3.81 1.7E-26 PA4139 PA14_10380 hypothetical protein -2.86 1.9E-39 PA4138 PA14_10420 tyrS tyrosyl-tRNA synthetase -2.05 3.6E-14 PA4137 PA14_10440 probable porin -2.20 1.6E-08 PA4134 PA14_10490 hypothetical protein -1.89 8.3E-49 PA4133 PA14_10500 cytochrome c oxidase subunit (cbb3-type) -1.97 1.2E-75 -1.68 2.0E-12 PA4132 PA14_10530 conserved hypothetical protein -1.50 2.0E-28 PA4131 PA14_10540 probable iron-sulfur protein -1.89 7.4E-56 PA4120 PA14_10660 probable transcriptional regulator 1.87 7.9E-05 PA4119 PA14_10670 aph aminoglycoside 3'-phosphotransferase type IIb -1.52 2.6E-09 PA4116 PA14_10710 bphO heme oxygenase, BphO -1.72 1.1E-21 PA4113 PA14_10750 probable major facilitator superfamily (MFS) transporter -1.88 5.8E-14 PA14_10830 LysR family transcriptional regulator 1.77 1.3E-09 PA4094 PA14_10940 probable transcriptional regulator 1.63 2.0E-06 PA4086 PA14_11060 cupB1 probable fimbrial subunit CupB1 1.96 1.5E-06 PA4080 PA14_11120 probable response regulator 1.55 6.9E-08 PA4078 PA14_11140 probable nonribosomal peptide synthetase 1.79 2.0E-10 PA4070 PA14_11240 probable transcriptional regulator 1.58 1.5E-02 PA4063 PA14_11320 hypothetical protein 1.62 4.9E-04 PA4061 PA14_11340 probable thioredoxin -1.73 4.0E-34 PA4052 PA14_11450 nusB NusB protein -1.52 8.0E-10 PA4031 PA14_11690 ppa inorganic pyrophosphatase -1.81 9.4E-52 PA4029 PA14_11720 conserved hypothetical protein -1.55 2.4E-08 PA4017 PA14_11890 conserved hypothetical protein 1.51 3.1E-09 PA4009 PA14_11980 hypothetical protein 1.69 1.7E-04 PA3995 PA14_12140 probable transcriptional regulator 1.66 1.3E-09 PA3990 PA14_12180 conserved hypothetical protein -1.79 8.0E-12 PA3986 PA14_12260 hypothetical protein 1.69 2.0E-10 PA3979 PA14_12360 hypothetical protein -1.74 2.2E-10 PA3960 PA14_12640 hypothetical protein -1.81 6.5E-05 PA3959 PA14_12650 hypothetical protein -1.64 7.1E-07 PA3957 PA14_12680 probable short-chain dehydrogenase 1.68 1.7E-09 123 PA3952 PA14_12740 hypothetical protein 2.06 1.9E-02 PA3938 PA14_12920 probable periplasmic taurine-binding protein precursor -3.89 3.6E-31 -2.40 9.4E-05 PA3937 PA14_12940 probable ATP-binding component of ABC taurine transporter -2.34 7.0E-11 PA3936 PA14_12960 probable permease of ABC taurine transporter -2.48 2.6E-11 PA3935 PA14_12970 tauD taurine dioxygenase -2.03 5.6E-08 PA3932 PA14_13000 probable transcriptional regulator -2.66 1.2E-14 PA3931 PA14_13010 conserved hypothetical protein -4.30 9.8E-34 PA3923 PA14_13130 hypothetical protein 2.00 3.3E-11 PA3922 PA14_13140 conserved hypothetical protein 2.25 4.5E-18 PA3921 PA14_13150 probable transcriptional regulator 1.52 1.6E-14 PA3920 PA14_13170 probable metal transporting P-type ATPase -3.87 6.3E-30 PA3915 PA14_13260 moaB1 molybdopterin biosynthetic protein B1 -2.36 1.4E-14 PA3914 PA14_13280 moeA1 molybdenum cofactor biosynthetic protein A1 -4.00 1.0E-17 PA3913 PA14_13290 probable protease -1.77 2.8E-10 PA3911 PA14_13320 conserved hypothetical protein -1.55 3.4E-04 PA3901 PA14_13430 fecA Fe(III) dicitrate transport protein FecA -1.55 6.0E-04 PA3891 PA14_13580 opuCA OpuC ABC transporter, ATP-binding protein, OpuCA 2.27 2.7E-16 PA3890 PA14_13590 opuCB OpuC ABC transporter, permease protein, OpuCB 2.40 1.1E-13 PA3889 PA14_13600 opuCC OpuC ABC transporter, periplasmic substrate-binding protein, OpuCC 2.55 1.8E-19 PA3888 PA14_13610 opuCD OpuC ABC transporter, permease protein, OpuCD 2.68 1.6E-15 PA14_13630 hypothetical protein 2.41 6.5E-14 PA3886 PA14_13650 hypothetical protein 1.66 2.8E-02 PA3877 PA14_13750 narK1 nitrite extrusion protein 1 -5.91 7.1E-31 PA3876 PA14_13770 narK2 nitrite extrusion protein 2 -5.68 3.0E-17 PA3875 PA14_13780 narG respiratory nitrate reductase alpha chain -6.18 1.5E-68 PA3874 PA14_13800 narH respiratory nitrate reductase beta chain -3.53 2.0E-24 PA3873 PA14_13810 narJ respiratory nitrate reductase delta chain -5.30 2.7E-18 PA3872 PA14_13830 narI respiratory nitrate reductase gamma chain -3.25 1.7E-12 124 PA3871 PA14_13840 probable peptidyl-prolyl cis-trans isomerase, PpiC-type -3.06 4.3E-17 PA3870 PA14_13850 moaA1 molybdopterin biosynthetic protein A1 -1.78 7.8E-05 PA14_13920 hypothetical protein 2.11 4.9E-04 PA3866 PA14_13940 Pyocin S4 -3.09 2.6E-05 PA3865.1 PA14_13950 hypothetical protein -1.92 7.8E-03 PA3865 PA14_13990 probable amino acid binding protein -1.85 7.5E-20 PA3863 PA14_14010 dauA FAD-dependent catabolic D-arginine dehydrogenase, DauA -1.68 5.1E-10 PA3862 PA14_14020 dauB NAD(P)H-dependent anabolic L-arginine dehydrogenase, DauB -1.99 1.3E-14 PA3842 PA14_14330 spcS specific Pseudomonas chaperone for ExoS, SpcS 1.61 8.0E-04 PA3840 PA14_14340 conserved hypothetical protein -1.74 5.7E-09 PA14_14540 hypothetical protein -2.41 4.1E-10 PA14_14550 hypothetical protein -3.78 8.8E-81 PA14_14560 hypothetical protein -2.58 3.8E-16 PA3818 PA14_14680 extragenic suppressor protein SuhB -1.75 1.4E-19 PA3815 PA14_14710 iscR IscR -1.81 1.6E-20 PA3814 PA14_14730 iscS L-cysteine desulfurase (pyridoxal phosphate-dependent) -1.89 2.6E-24 PA3813 PA14_14740 iscU probable iron-binding protein IscU -1.73 6.6E-26 PA3812 PA14_14750 iscA probable iron-binding protein IscA -1.63 1.1E-15 PA3811 PA14_14770 hscB heat shock protein HscB -1.77 2.7E-15 PA3810 PA14_14780 hscA heat shock protein HscA -1.77 7.5E-17 PA3809 PA14_14800 fdx2 ferredoxin [2Fe-2S] -1.57 3.4E-11 PA3808 PA14_14810 conserved hypothetical protein -1.58 1.5E-11 PA3795 PA14_14990 probable oxidoreductase 1.98 2.5E-18 PA3791 PA14_15050 hypothetical protein 1.53 5.3E-04 PA3790 PA14_15070 oprC Putative copper transport outer membrane porin OprC precursor 4.24 4.1E-12 PA3789 PA14_15080 hypothetical protein 2.56 3.8E-13 PA3788 PA14_15090 hypothetical protein 1.68 2.1E-08 PA3783 PA14_15140 hypothetical protein 1.71 6.7E-03 PA3776 PA14_15240 probable transcriptional regulator -1.63 1.3E-03 PA3775 PA14_15250 hypothetical protein 1.91 2.7E-02 PA3771 PA14_15290 probable transcriptional regulator 1.93 7.9E-06 PA14_15510 traJ conjugal transfer relaxosome component TraJ -1.90 3.4E-02 PA14_15520 trbJ conjugal transfer protein TrbJ -1.77 2.1E-11 125 PA14_15530 entry/exclusion protein TrbK -2.20 3.2E-04 PA14_15560 hypothetical protein -1.82 2.9E-02 PA14_15570 hypothetical protein -1.93 1.6E-02 PA14_15580 Type II restriction enzyme, methylase subunit -1.52 1.3E-02 PA3766 PA14_15700 probable aromatic amino acid transporter -1.73 1.4E-08 PA3762 PA14_15770 hypothetical protein 2.24 1.9E-16 PA3757 PA14_15830 nagR Transcriptional regulator of N-Acetylglucosamine catabolism operon -1.50 2.9E-05 PA3745 PA14_15970 rpsP 30S ribosomal protein S16 -1.51 6.3E-08 PA3743 PA14_15990 trmD tRNA (guanine-N1)-methyltransferase -1.54 6.9E-09 PA3742 PA14_16000 rplS 50S ribosomal protein L19 -1.55 4.8E-12 PA3741 PA14_16010 hypothetical protein -1.66 2.2E-08 PA3734 PA14_16100 hypothetical protein 2.05 5.3E-09 PA14_16110 hypothetical protein 1.95 3.5E-20 PA3726 PA14_16210 conserved hypothetical protein -1.58 4.0E-12 PA3725 PA14_16220 recJ single-stranded-DNA-specific exonuclease RecJ -1.57 1.7E-12 PA3724 PA14_16250 lasB elastase LasB 2.32 1.2E-29 PA3723 PA14_16260 probable FMN oxidoreductase 1.62 1.1E-11 PA3722 PA14_16270 hypothetical protein -2.16 8.0E-31 PA3719 PA14_16300 armR antirepressor for MexR, ArmR 1.61 2.3E-03 PA3716 PA14_16330 hypothetical protein -1.78 7.4E-64 PA3713 PA14_16360 spdH spermidine dehydrogenase, SpdH -1.96 7.1E-25 PA3703 PA14_16480 wspF probable methylesterase 1.54 3.8E-20 PA3692 PA14_16630 lptF Lipotoxon F, LptF 2.30 5.4E-23 PA3691 PA14_16640 hypothetical protein 2.54 9.9E-31 PA3687 PA14_16690 ppc phosphoenolpyruvate carboxylase 1.58 1.7E-12 PA3678 PA14_16790 mexL MexL 1.52 6.8E-15 PA3671 PA14_16880 probable permease of ABC transporter 1.56 7.4E-03 PA3670 PA14_16890 hypothetical protein 1.78 7.6E-06 PA3669 PA14_16910 hypothetical protein 1.97 4.8E-12 PA3662 PA14_16990 hypothetical protein -2.90 8.4E-28 PA3656 PA14_17060 rpsB 30S ribosomal protein S2 -1.52 5.0E-16 PA3655 PA14_17070 tsf elongation factor Ts -1.59 1.1E-16 PA3654 PA14_17080 pyrH uridylate kinase -1.77 1.1E-17 PA3653 PA14_17100 frr ribosome recycling factor -1.55 4.3E-22 126 PA3641 PA14_17250 probable amino acid permease -2.01 4.1E-32 PA3630 PA14_17380 gfnR glutathione-dependent formaldehyde neutralization regulator GfnR 1.82 7.1E-11 PA3622 PA14_17480 rpoS sigma factor RpoS 1.58 1.9E-11 PA3617 PA14_17530 recA RecA protein -1.76 2.5E-41 PA3616 PA14_17540 conserved hypothetical protein -1.62 6.3E-10 PA3615 PA14_17550 hypothetical protein 1.69 7.4E-16 PA3614 PA14_17570 hypothetical protein 1.63 1.8E-08 PA3613 PA14_17580 hypothetical protein 1.81 7.1E-09 PA3612 PA14_17590 conserved hypothetical protein -2.14 2.3E-02 PA3610 PA14_17610 potD polyamine transport protein PotD -3.65 3.1E-63 PA3609 PA14_17620 potC polyamine transport protein PotC -3.06 6.7E-17 PA3608 PA14_17630 potB polyamine transport protein PotB -2.40 8.0E-14 PA3607 PA14_17640 potA polyamine transport protein PotA -3.21 3.5E-45 PA3588 PA14_17730 probable porin 1.50 4.6E-02 PA3598 PA14_17730 conserved hypothetical protein 2.31 1.2E-19 PA3586 PA14_17910 probable hydrolase 1.71 1.1E-02 PA3580 PA14_17990 conserved hypothetical protein -1.73 2.8E-02 PA14_18070 periplasmic metal-binding protein -3.68 1.1E-19 PA3567 PA14_18160 probable oxidoreductase -1.55 3.1E-06 PA3566 PA14_18180 conserved hypothetical protein -2.00 4.8E-08 PA3562 PA14_18250 fruI phosphotransferase system transporter enzyme I, FruI -1.51 2.0E-03 PA3558 PA14_18310 arnF ArnF -1.51 7.3E-04 PA3556 PA14_18330 arnT inner membrane L-Ara4N transferase ArnT -1.64 5.4E-11 PA3543 PA14_18520 algK alginate biosynthetic protein AlgK precursor -3.18 4.2E-02 PA3532 PA14_18660 hypothetical protein -1.83 8.0E-15 PA3531 PA14_18670 bfrB bacterioferritin -2.02 1.5E-15 -1.62 3.9E-03 PA3530 PA14_18680 bfd bacterioferritin-associated ferredoxin Bfd 1.97 3.9E-12 -1.83 1.5E-02 PA3526 PA14_18720 motY MotY -1.67 6.1E-22 PA3523 PA14_18760 mexP RND efflux membrane fusion protein -4.03 3.1E-10 PA3522 PA14_18780 mexQ MexQ -3.38 1.5E-31 PA3521 PA14_18790 opmE outer membrane efflux protein -3.31 1.2E-12 PA3520 PA14_18800 hypothetical protein -2.56 6.8E-12 PA3519 PA14_18810 hypothetical protein -4.75 1.6E-21 PA3518 PA14_18820 hypothetical protein -10.19 1.1E-45 PA3517 PA14_18830 probable lyase -4.79 1.8E-32 127 PA3516 PA14_18850 probable lyase -5.62 8.6E-29 PA3515 PA14_18860 hypothetical protein -2.00 8.1E-08 PA3488 PA14_18960 tli5 Tli5 -1.62 9.2E-05 PA3487 PA14_18970 tle5 Tle5 -1.68 2.9E-13 PA3486 PA14_18985 vgrG4b VgrG4b -1.71 2.2E-09 PA3474 PA14_19150 conserved hypothetical protein -1.77 2.5E-09 PA3473 PA14_19160 hypothetical protein -1.62 2.9E-08 PA3466 PA14_19290 probable ATP-dependent RNA helicase -1.63 3.9E-19 -1.60 3.0E-02 PA3465 PA14_19310 conserved hypothetical protein 1.97 2.9E-12 PA3461 PA14_19350 conserved hypothetical protein 2.85 2.2E-26 PA3460 PA14_19360 probable acetyltransferase 2.68 4.6E-24 PA3459 PA14_19370 probable glutamine amidotransferase 2.85 1.2E-35 PA3458 PA14_19380 probable transcriptional regulator 1.83 3.8E-08 PA3453 PA14_19450 conserved hypothetical protein -1.63 1.3E-20 PA3450 PA14_19490 lsfA 1-Cys peroxiredoxin LsfA -2.37 9.7E-15 -2.75 7.8E-06 PA3449 PA14_19500 conserved hypothetical protein -6.73 2.1E-32 PA3448 PA14_19510 probable permease of ABC transporter -3.84 3.5E-14 PA3447 PA14_19520 probable ATP-binding component of ABC transporter -3.70 8.0E-10 PA3446 PA14_19530 conserved hypothetical protein -4.76 1.4E-31 PA3445 PA14_19540 hypothetical protein -4.06 2.9E-32 PA3444 PA14_19560 alkanesulfonate monooxygenase -3.02 3.3E-14 PA3443 PA14_19570 probable permease of ABC transporter -2.48 3.0E-09 PA3442 PA14_19580 aliphatic sulfonates transport ATP-binding subunit -2.12 1.1E-09 PA3436 PA14_19650 hypothetical protein 2.06 1.8E-05 PA3432 PA14_19680 hypothetical protein 1.82 9.2E-06 PA3431 PA14_19690 conserved hypothetical protein 2.22 1.2E-11 PA3419 PA14_19860 hypothetical protein 1.64 4.6E-09 1.63 1.0E-02 PA3415 PA14_19920 probable dihydrolipoamide acetyltransferase -1.53 3.1E-02 PA14_19930 hypothetical protein -1.70 5.7E-03 PA3414 PA14_19940 hypothetical protein -1.94 3.2E-21 PA3413 PA14_19950 conserved hypothetical protein -1.59 2.0E-12 PA3412 PA14_19960 hypothetical protein 2.39 1.6E-04 PA3411 PA14_19970 hypothetical protein -1.71 4.4E-03 PA3410 PA14_19990 hasI HasI -2.00 3.6E-06 128 PA3407 PA14_20020 hasAp heme acquisition protein HasAp 7.33 4.6E-11 PA3406 PA14_20030 hasD transport protein HasD 1.74 1.8E-03 PA3405 PA14_20040 hasE metalloprotease secretion protein 1.76 6.0E-03 PA3404 PA14_20050 outer membrane protein 1.63 2.0E-02 PA14_20060 hypothetical protein 1.71 4.7E-07 PA3396 PA14_20150 nosL NosL protein -12.77 1.3E-29 PA3395 PA14_20170 nosY NosY protein -15.62 1.1E-48 PA3394 PA14_20180 nosF NosF protein -18.65 5.8E-59 PA3393 PA14_20190 nosD copper ABC transporter periplasmic substrate-binding protein -16.02 3.4E-36 PA3392 PA14_20200 nosZ nitrous-oxide reductase precursor -16.52 8.6E-33 PA3391 PA14_20230 nosR regulatory protein NosR -17.19 2.1E-37 PA3389 PA14_20240 probable ring-cleaving dioxygenase -2.05 1.9E-04 PA3388 PA14_20260 conserved hypothetical protein -1.74 2.7E-08 PA3387 PA14_20270 rhlG beta-ketoacyl reductase -1.79 3.2E-05 PA3384 PA14_20300 phnC ATP-binding component of ABC phosphonate transporter 1.96 8.8E-05 PA3378 PA14_20380 hypothetical protein 1.57 4.2E-02 PA3376 PA14_20400 phosphonate C-P lyase system protein PhnK 1.99 7.9E-03 PA3371 PA14_20460 hypothetical protein 3.75 4.3E-20 PA3370 PA14_20470 hypothetical protein 3.85 2.5E-21 PA3369 PA14_20480 hypothetical protein 3.46 1.1E-16 PA2457 PA14_20510 hypothetical protein -1.88 1.2E-02 PA2458 PA14_20520 hypothetical protein -2.26 2.9E-03 PA14_20530 hypothetical protein 1.71 6.1E-18 -1.86 1.2E-02 PA3354 PA14_20690 hypothetical protein 1.54 3.7E-06 PA3346 PA14_20780 hsbR HptB-dependent secretion and biofilm regulator HsbR 1.60 2.6E-20 PA3337 PA14_20890 rfaD ADP-L-glycero-D-mannoheptose 6-epimerase 1.64 2.9E-06 PA3336 PA14_20900 probable major facilitator superfamily (MFS) transporter 2.02 2.2E-07 PA3335 PA14_20920 hypothetical protein 2.01 4.6E-09 PA3334 PA14_20940 acp3 Acp3 2.04 9.0E-09 PA3333 PA14_20950 fabH2 3-oxoacyl-[acyl-carrier-protein] synthase III 1.68 4.6E-05 PA3332 PA14_20960 conserved hypothetical protein 1.58 4.6E-04 PA3331 PA14_20970 cytochrome P450 1.76 2.7E-07 PA3330 PA14_20980 probable short chain dehydrogenase 1.72 1.5E-08 PA3329 PA14_21000 hypothetical protein 1.68 6.2E-06 129 PA3328 PA14_21010 probable FAD-dependent monooxygenase 1.74 2.2E-06 PA3309 PA14_21220 conserved hypothetical protein 1.63 1.6E-05 PA14_21260 hypothetical protein -2.30 7.8E-03 PA3298 PA14_21380 hypothetical protein -2.19 9.5E-06 PA3295 PA14_21440 probable HIT family protein -1.53 5.0E-23 PA3294 PA14_21450 vgrG4a VgrG4a -1.63 5.2E-13 PA3293 PA14_21460 hypothetical protein -1.81 2.4E-08 PA3292 PA14_21470 hypothetical protein -1.75 3.1E-06 PA3291 PA14_21480 tli1 Tli1 -1.65 1.7E-04 PA3290 PA14_21490 tle1 Tle1 -1.64 2.5E-02 PA3284 PA14_21570 hypothetical protein -6.08 7.9E-75 PA3283 PA14_21580 conserved hypothetical protein -7.25 8.8E-180 PA3282 PA14_21590 hypothetical protein -7.40 5.9E-80 PA3281 PA14_21600 hypothetical protein -7.11 5.1E-57 PA3280 PA14_21610 oprO Pyrophosphate-specific outer membrane porin OprO precursor -5.72 2.1E-47 PA3276 PA14_21650 hypothetical protein -1.58 4.3E-06 PA3275 PA14_21660 conserved hypothetical protein -1.55 9.9E-05 PA3274 PA14_21670 hypothetical protein 3.69 1.2E-18 PA3268 PA14_21730 probable TonB-dependent receptor -1.50 7.1E-03 PA3266 PA14_21760 capB cold acclimation protein B -2.09 1.0E-06 PA14_21830 hypothetical protein 2.38 3.2E-48 PA3248 PA14_21980 Uncharacterized protein 1.53 8.4E-06 PA3246 PA14_22000 rluA pseudouridine synthase RluA -1.54 1.8E-12 PA14_22090 hypothetical protein -2.30 1.9E-02 PA14_22160 hypothetical protein -2.23 3.5E-04 PA14_22190 hypothetical protein -1.62 1.6E-02 PA14_22250 hypothetical protein -1.72 9.3E-03 PA14_22260 hypothetical protein -2.01 2.5E-02 PA14_22280 pirin-related protein -1.98 4.6E-02 PA3235 PA14_22340 conserved hypothetical protein 2.50 1.0E-05 PA3234 PA14_22350 probable sodium:solute symporter 2.62 3.7E-04 PA3233 PA14_22370 hypothetical protein 2.12 2.3E-10 PA3232 PA14_22380 probable nuclease 2.13 1.3E-08 PA3231 PA14_22400 hypothetical protein 3.46 1.9E-27 PA3228 PA14_22440 probable ATP-binding/permease fusion ABC transporter 1.50 1.6E-10 PA3222 PA14_22560 hypothetical protein 1.96 2.6E-02 130 PA3221 PA14_22570 csaA CsaA protein -1.69 9.9E-12 PA3214 PA14_22650 hypothetical protein 1.50 3.9E-14 PA3205 PA14_22740 hypothetical protein -1.50 1.9E-06 PA3195 PA14_22890 gapA glyceraldehyde 3-phosphate dehydrogenase 1.83 5.8E-28 PA3188 PA14_23000 probable permease of ABC sugar transporter 1.53 1.6E-07 PA3187 PA14_23010 probable ATP-binding component of ABC transporter 1.67 1.8E-11 PA3186 PA14_23030 oprB Glucose/carbohydrate outer membrane porin OprB precursor 2.04 6.3E-21 PA3182 PA14_23080 pgl 6-phosphogluconolactonase 1.62 7.8E-04 PA3179 PA14_23110 conserved hypothetical protein -2.53 1.2E-56 PA3175 PA14_23170 hutE HutE -2.14 2.4E-08 PA3174 PA14_23190 hutR HutR -2.16 1.1E-12 PA3160 PA14_23360 wzz O-antigen chain length regulator -1.84 6.9E-03 PA3148 PA14_23370 wbpI UDP-N-acetylglucosamine 2-epimerase WbpI -1.68 2.6E-02 PA3159 PA14_23380 wbpA UDP-N-acetyl-d-glucosamine 6-Dehydrogenase -2.08 1.8E-02 PA14_23390 orfE polysaccharide biosynthesis protein -2.88 1.6E-02 PA14_23400 hypothetical protein -1.78 1.2E-02 PA14_23410 orfJ glycosyl transferase family protein -3.45 2.0E-02 PA14_23430 hepP HepP -1.54 2.8E-02 PA3145 PA14_23460 wbpL glycosyltransferase WbpL -1.77 2.7E-02 PA3133 PA14_23590 sawR SawR -2.06 5.2E-11 PA3132 PA14_23610 probable hydrolase -1.58 2.9E-06 PA3128 PA14_23650 probable short-chain dehydrogenase 1.54 7.5E-06 PA3126 PA14_23680 ibpA heat-shock protein IbpA -5.30 1.9E-50 PA3121 PA14_23750 leuC 3-isopropylmalate dehydratase large subunit 1.67 7.9E-09 PA3120 PA14_23760 leuD 3-isopropylmalate dehydratase small subunit 1.75 2.6E-12 PA3119 PA14_23770 conserved hypothetical protein 1.54 1.1E-07 PA3104 PA14_23980 xcpP secretion protein XcpP -1.82 7.8E-03 PA3096 PA14_24080 xcpY general secretion pathway protein L 1.51 1.0E-13 PA3095 PA14_24100 xcpZ general secretion pathway protein M 1.67 2.6E-26 PA3091 PA14_24180 hypothetical protein 1.90 5.5E-27 PA3071 PA14_24420 hypothetical protein 1.58 2.2E-02 PA3062 PA14_24500 pelC lipoprotein -1.66 1.6E-02 PA3060 PA14_24530 pelE hypothetical protein -1.70 1.6E-04 131 PA3057 PA14_24570 hypothetical protein 2.16 2.8E-04 PA3049 PA14_24650 rmf ribosome modulation factor 1.82 8.6E-13 PA3046 PA14_24700 conserved hypothetical protein -1.91 1.0E-30 PA3045 PA14_24710 rocA2 Two-component response regulator, RocA2 -2.45 9.1E-11 PA3044 PA14_24720 rocsS2 Two-component sensor RocS2 -2.09 5.2E-14 PA3042 PA14_24740 hypothetical protein 1.98 2.6E-14 PA3041 PA14_24760 hypothetical protein 1.93 2.5E-12 PA3040 PA14_24770 conserved hypothetical protein 1.89 1.3E-16 PA3038 PA14_24790 opdQ OpdQ 1.68 1.6E-02 PA3037 PA14_24810 hypothetical protein -2.07 1.6E-02 PA3036 PA14_24820 hypothetical protein -1.89 2.2E-03 PA3035 PA14_24830 probable glutathione S-transferase -1.51 3.0E-02 PA3032 PA14_24860 snr1 cytochrome c Snr1 1.74 2.5E-06 PA3024 PA14_24960 probable carbohydrate kinase 1.61 1.3E-12 PA3023 PA14_24970 conserved hypothetical protein 2.20 1.9E-20 PA3017 PA14_25040 conserved hypothetical protein 1.61 5.9E-03 PA3014 PA14_25080 faoA fatty-acid oxidation complex alpha-subunit -1.85 1.5E-77 PA3013 PA14_25090 faoB fatty-acid oxidation complex beta-subunit -1.65 3.0E-47 PA3008 PA14_25150 hypothetical protein -1.94 6.1E-27 PA3007 PA14_25160 lexA repressor protein LexA -1.81 6.9E-39 PA3001 PA14_25250 probable glyceraldehyde-3-phosphate dehydrogenase -1.50 1.6E-12 PA2957 PA14_25800 probable transcriptional regulator -1.52 3.5E-13 PA2953 PA14_25840 electron transfer flavoprotein-ubiquinone oxidoreductase -1.61 2.6E-45 PA2948 PA14_25920 cobM precorrin-3 methylase 1.75 1.3E-19 PA2944 PA14_25970 cobN cobalamin biosynthetic protein CobN 1.52 1.3E-24 PA2943 PA14_25980 phospho-2-dehydro-3-deoxyheptonate aldolase -1.60 2.0E-08 PA2939 PA14_26020 probable aminopeptidase 1.68 5.9E-05 PA2936 PA14_26070 hypothetical protein -3.86 1.9E-12 PA2934 PA14_26090 cif CFTR inhibitory factor, Cif -10.75 1.6E-38 PA2933 PA14_26110 MFS transporter -9.30 2.1E-27 PA2932 PA14_26130 morB morphinone reductase -6.49 2.3E-19 PA2929 PA14_26160 hypothetical protein -1.69 1.0E-02 PA2927 PA14_26190 hypothetical protein 1.54 3.1E-10 PA2917 PA14_26330 probable transcriptional regulator -2.27 4.4E-18 PA2916 PA14_26340 hypothetical protein -4.59 6.5E-15 132 PA2915 PA14_26350 hypothetical protein 1.56 8.3E-09 PA2914 PA14_26360 probable permease of ABC transporter 2.28 1.1E-13 PA2913 PA14_26390 hypothetical protein 2.20 3.3E-14 PA2912 PA14_26400 probable ATP-binding component of ABC transporter 2.05 1.5E-11 PA2911 PA14_26420 probable TonB-dependent receptor 1.76 1.3E-15 PA2906 PA14_26485 probable oxidoreductase 1.64 1.1E-21 PA2905 PA14_26500 cobH precorrin isomerase CobH 1.67 1.6E-13 PA2904 PA14_26510 cobI precorrin-2 methyltransferase CobI 1.63 3.2E-20 PA2903 PA14_26530 cobJ precorrin-3 methylase CobJ 1.72 2.4E-41 PA2895 PA14_26610 sbrR SbrR 1.54 7.2E-12 PA2892 PA14_26650 atuG GCase, alpha-subunit (biotin-containing) 1.88 3.8E-04 PA2891 PA14_26670 atuF geranyl-CoA carboxylase, alpha-subunit (biotin-containing) 1.74 5.4E-08 PA2889 PA14_26700 atvR atypical virulence-related response regulator AtvR 1.61 2.1E-04 PA2888 PA14_26720 atuC geranyl-CoA carboxylase, beta-subunit 1.72 6.5E-08 PA2887 PA14_26730 atuB putative dehydrogenase involved in catabolism of citronellol 1.52 3.6E-03 PA2884 PA14_26770 hypothetical protein 1.50 7.8E-11 PA2883 PA14_26780 hypothetical protein 2.55 9.5E-28 PA2879 PA14_26860 probable transcriptional regulator 1.99 3.2E-19 PA2874 PA14_26920 hypothetical protein 1.90 7.1E-14 PA2873 PA14_26930 tgpA transglutaminase protein A, TgpA 1.74 3.3E-16 PA2869 PA14_26980 hypothetical protein -1.70 1.6E-06 PA2863 PA14_27090 lipH lipase modulator protein 2.59 2.9E-07 PA2862 PA14_27100 lipA lactonizing lipase precursor 2.18 2.0E-06 PA2855 PA14_27170 hypothetical protein -1.53 2.3E-07 PA2851 PA14_27210 efp translation elongation factor P -1.59 2.0E-02 PA2850 PA14_27220 ohr organic hydroperoxide resistance protein -2.23 2.7E-14 PA2840 PA14_27370 probable ATP-dependent RNA helicase -2.75 1.7E-13 PA2839 PA14_27390 conserved hypothetical protein -1.67 5.1E-05 PA2831 PA14_27470 conserved hypothetical protein -1.92 4.3E-51 PA2830 PA14_27480 htpX heat shock protein HtpX -1.95 2.1E-27 PA2829 PA14_27490 hypothetical protein -1.60 8.5E-09 PA2826 PA14_27520 probable glutathione peroxidase -1.53 7.8E-07 PA14_27650 hypothetical protein 1.85 7.2E-03 133 PA14_27700 transcriptional regulator -2.19 1.4E-05 PA2817 PA14_27710 hypothetical protein -1.65 9.8E-10 PA2815 PA14_27730 probable acyl-CoA dehydrogenase 2.23 1.5E-24 PA2794 PA14_27990 pseudaminidase -2.07 2.0E-02 PA2790 PA14_28030 hypothetical protein -1.58 1.5E-08 PA2786 PA14_28070 hypothetical protein -1.82 3.5E-04 PA2779 PA14_28140 hypothetical protein 1.72 5.3E-05 PA2778 PA14_28150 hypothetical protein 1.73 3.1E-05 PA2777 PA14_28170 conserved hypothetical protein 3.50 1.8E-29 PA2776 PA14_28180 pauB3 FAD-dependent oxidoreductase -1.52 9.5E-08 PA2770 PA14_28280 hypothetical protein -1.57 1.6E-17 PA2769 PA14_28290 hypothetical protein -1.57 3.6E-10 PA14_28330 hypothetical protein 2.06 6.8E-03 PA2762 PA14_28380 hypothetical protein -1.67 3.0E-07 PA2761 PA14_28390 hypothetical protein -1.58 4.9E-02 PA2754 PA14_28490 conserved hypothetical protein 2.31 5.8E-17 PA14_28520 hypothetical protein 2.08 2.2E-13 PA2751 PA14_28530 conserved hypothetical protein 2.48 4.0E-14 PA2747 PA14_28600 hypothetical protein 2.59 2.3E-15 PA2746 PA14_28620 hypothetical protein 1.52 1.3E-04 PA2745 PA14_28630 probable hydrolase 1.58 3.1E-08 PA2743 PA14_28660 infC translation initiation factor IF-3 -1.91 1.3E-02 PA2740 PA14_28690 pheS phenylalanyl-tRNA synthetase, alpha-subunit -1.77 1.2E-17 PA2739 PA14_28710 pheT phenylalanyl-tRNA synthetase, beta subunit -1.70 7.2E-23 PA14_28760 hypothetical protein 1.87 1.4E-08 PA14_28840 helicase 1.59 4.4E-15 -1.52 3.0E-02 PA14_28850 hypothetical protein 1.77 8.0E-15 PA14_28870 hypothetical protein 1.69 3.0E-12 PA2721 PA14_28960 hypothetical protein 1.56 7.8E-05 PA14_28980 Fe2+-dicitrate sensor -1.94 8.7E-04 PA2717 PA14_29020 cpo chloroperoxidase precursor 1.67 3.7E-08 PA2712 PA14_29070 hypothetical protein -1.78 2.1E-07 PA2708 PA14_29120 hypothetical protein 2.43 4.2E-31 PA2701 PA14_29210 probable major facilitator superfamily (MFS) transporter 2.08 1.7E-03 PA2700 PA14_29220 opdB proline porin OpdB 1.76 1.3E-02 PA2688 PA14_29350 pfeA Ferric enterobactin receptor, outer membrane protein PfeA precursor -2.81 3.7E-13 PA2677 PA14_29490 probable type II secretion protein 1.52 1.1E-03 134 PA2672 PA14_29540 type II secretion system protein 2.06 1.3E-02 PA2670 PA14_29560 hypothetical protein 1.69 1.1E-03 PA2666 PA14_29600 probable 6-pyruvoyl tetrahydrobiopterin synthase -1.79 5.2E-10 -1.70 1.9E-02 PA2663 PA14_29650 ppyR psl and pyoverdine operon regulator, PpyR 1.61 4.5E-02 PA2653 PA14_29770 probable transporter -2.70 3.6E-45 PA2652 PA14_29800 methyl-accepting chemotaxis protein -2.24 1.1E-48 PA2650 PA14_29830 conserved hypothetical protein -1.59 2.2E-08 PA2630 PA14_30100 conserved hypothetical protein -1.86 1.2E-21 PA2629 PA14_30110 purB adenylosuccinate lyase -1.85 9.3E-17 PA2625 PA14_30160 conserved hypothetical protein -1.76 7.6E-09 PA2624 PA14_30180 idh isocitrate dehydrogenase -1.70 7.2E-13 PA2622 PA14_30200 cspD cold-shock protein CspD 1.55 1.5E-08 PA2621 PA14_30210 clpS ClpS -1.56 2.9E-02 PA2619 PA14_30240 infA initiation factor -1.54 3.5E-03 PA2600 PA14_30460 hypothetical protein -1.57 8.9E-06 PA2598 PA14_30490 hypothetical protein -1.53 5.4E-04 PA2594 PA14_30550 conserved hypothetical protein -2.82 5.7E-17 PA2591 PA14_30580 vqsR VqsR 1.58 2.5E-21 PA2587 PA14_30630 pqsH probable FAD-dependent monooxygenase 1.72 2.9E-32 PA2582 PA14_30710 hypothetical protein -1.51 1.8E-02 PA2579 PA14_30750 kynA L-Tryptophan:oxygen 2,3-oxidoreductase (decyclizing) KynA -1.56 2.0E-12 PA2575 PA14_30800 hypothetical protein -2.06 6.4E-22 PA2573 PA14_30820 probable chemotaxis transducer 1.94 3.4E-17 PA2571 PA14_30840 probable two-component sensor 1.53 7.2E-09 PA14_30850 TrbI-like protein 1.67 1.2E-02 PA14_30860 TrbG-like protein 2.14 3.5E-02 PA14_30880 conjugal transfer protein TrbL 2.61 1.5E-02 PA14_30970 transcriptional regulator 1.63 7.0E-16 PA14_31270 hypothetical protein 2.05 2.1E-07 PA2570 PA14_31290 lecA LecA 1.69 1.2E-05 PA2569 PA14_31300 hypothetical protein 2.07 1.5E-16 PA14_31340 hypothetical protein -2.02 4.5E-02 PA2566 PA14_31350 conserved hypothetical protein 2.41 8.1E-45 PA2565 PA14_31360 hypothetical protein 1.89 2.3E-17 PA2564 PA14_31370 hypothetical protein 1.55 4.4E-11 PA2563 PA14_31380 probable sulfate transporter -2.17 2.1E-10 PA2562 PA14_31390 hypothetical protein 1.86 1.5E-09 135 PA2561 PA14_31400 ctpH CtpH -1.77 8.0E-13 PA14_31430 hypothetical protein 1.70 1.8E-08 PA2550 PA14_31580 probable acyl-CoA dehydrogenase -1.66 1.4E-03 PA2531 PA14_31820 probable aminotransferase 2.58 1.9E-10 PA2519 PA14_32060 xylS transcriptional regulator XylS 1.84 3.6E-08 PA2515 PA14_32130 xylL 1,6-dihydroxycyclohexa-2,4-diene-1-carboxylate dehydrogenase 1.94 1.5E-02 PA2504 PA14_32280 hypothetical protein 1.71 2.0E-15 PA2502 PA14_32300 hypothetical protein -1.80 4.5E-20 PA2500 PA14_32330 probable major facilitator superfamily (MFS) transporter 1.81 8.3E-08 PA2499 PA14_32340 probable deaminase 2.01 1.1E-02 PA2494 PA14_32390 mexF Resistance-Nodulation-Cell Division (RND) multidrug efflux transporter MexF -2.00 3.6E-14 PA2493 PA14_32400 mexE Resistance-Nodulation-Cell Division (RND) multidrug efflux membrane fusion protein MexE precursor -1.87 4.2E-11 PA2488 PA14_32460 probable transcriptional regulator 1.52 7.7E-04 PA2486 PA14_32480 ptrC Pseudomonas type III repressor gene C, PtrC 2.02 6.3E-10 PA2485 PA14_32490 hypothetical protein 1.99 3.7E-07 PA2483 PA14_32520 conserved hypothetical protein -1.60 1.1E-09 PA2468 PA14_32710 foxI ECF sigma factor FoxI 1.77 5.8E-05 PA2467 PA14_32720 foxR Anti-sigma factor FoxR 1.51 1.7E-04 PA2465 PA14_32750 hypothetical protein -2.52 4.5E-08 PA2463 PA14_32780 hypothetical protein -1.70 7.8E-06 PA14_32820 hypothetical protein -2.29 4.1E-02 PA2458 PA14_32830 hypothetical protein -2.08 2.0E-02 PA2453 PA14_32890 hypothetical protein -1.82 2.0E-11 PA2452 PA14_32905 hypothetical protein 8.95 1.9E-16 -5.32 1.2E-06 PA2451 PA14_32905 hypothetical protein 8.95 1.9E-16 PA2448 PA14_32950 hypothetical protein 1.78 8.3E-12 PA2441 PA14_33050 hypothetical protein -2.27 4.3E-09 PA2440 PA14_33060 hypothetical protein -2.35 1.0E-11 PA2438 PA14_33080 hypothetical protein 1.53 4.8E-06 PA2435 PA14_33130 probable cation-transporting P-type ATPase 1.56 2.7E-14 PA2434 PA14_33150 hypothetical protein 1.79 9.2E-13 PA2433 PA14_33160 hypothetical protein 3.98 7.6E-49 PA2430 PA14_33220 conserved hypothetical protein 1.56 1.7E-04 136 PA2428 PA14_33240 hypothetical protein 1.55 4.1E-02 PA2427 PA14_33250 hypothetical protein 17.56 3.4E-57 PA2426 PA14_33260 pvdS sigma factor PvdS 2.03 9.7E-07 PA2425 PA14_33270 pvdG protein PvdG 10.22 6.2E-18 -9.38 2.7E-02 PA2424 PA14_33280 pvdL PvdL 14.65 5.9E-25 -8.59 4.1E-02 PA14_33330 hypothetical protein -1.93 1.4E-02 PA14_33360 hypothetical protein 1.74 2.5E-02 PA2422 PA14_33370 hypothetical protein 1.83 4.1E-02 PA2419 PA14_33420 probable hydrolase 1.64 7.8E-03 PA2417 PA14_33440 probable transcriptional regulator 1.63 3.5E-09 PA2415 PA14_33460 hypothetical protein 3.43 8.0E-21 PA2414 PA14_33480 L-sorbosone dehydrogenase 3.26 4.4E-57 PA2413 PA14_33500 pvdH L-2,4-diaminobutyrate:2-ketoglutarate 4-aminotransferase, PvdH 13.14 6.1E-19 -6.51 2.9E-02 PA2412 PA14_33510 conserved hypothetical protein 10.03 1.9E-16 -13.92 1.0E-02 PA2411 PA14_33520 probable thioesterase 10.76 7.8E-19 PA2410 PA14_33530 fpvF FpvF 4.23 1.9E-18 -6.66 7.3E-04 PA2409 PA14_33540 fpvE ABC transporter permease 4.29 8.7E-18 -6.20 1.8E-02 PA2408 PA14_33550 fpvD ABC transporter ATP-binding protein 5.11 8.0E-31 PA2407 PA14_33560 fpvC FpvC 4.85 1.1E-19 -6.32 2.0E-02 PA2406 PA14_33570 fpvK hypothetical protein 6.00 8.9E-28 PA2405 PA14_33580 fpvJ hypothetical protein 5.33 3.6E-15 PA2404 PA14_33590 fpvH hypothetical protein 6.68 4.1E-30 PA2403 PA14_33600 fpvG FpvG 4.72 2.4E-23 -5.89 9.6E-03 PA2402 PA14_33610 probable non-ribosomal peptide synthetase 13.25 6.1E-32 -8.95 2.0E-02 PA2400 PA14_33630 pvdJ PvdJ 17.29 4.0E-50 -8.89 9.6E-03 PA2399 PA14_33650 pvdD pyoverdine synthetase D 16.10 2.1E-35 -7.77 8.5E-03 PA2398 PA14_33680 fpvA ferripyoverdine receptor 6.55 7.7E-15 -7.29 1.9E-03 PA2397 PA14_33690 pvdE pyoverdine biosynthesis protein PvdE 10.94 3.2E-19 -9.69 8.5E-03 PA2396 PA14_33700 pvdF pyoverdine synthetase F 9.65 1.4E-24 -5.65 3.0E-02 PA2395 PA14_33710 pvdO protein PvdO 12.72 4.6E-11 -10.49 2.5E-02 PA2394 PA14_33720 pvdN protein PvdN 12.07 3.5E-13 -9.75 1.9E-02 PA2393 PA14_33730 putative dipeptidase 12.25 1.3E-12 -8.28 3.5E-02 PA2392 PA14_33740 pvdP PvdP 10.99 8.5E-21 -10.46 2.1E-02 PA2391 PA14_33750 opmQ probable outer membrane protein precursor 3.59 1.7E-22 -3.18 2.5E-02 PA2390 PA14_33760 pvdT PvdT 3.28 2.4E-21 137 PA2389 PA14_33770 pvdR PvdR 3.49 7.8E-20 PA2387 PA14_33800 fpvI FpvI 2.16 1.8E-33 PA2386 PA14_33810 pvdA L-ornithine N5-oxygenase 11.76 1.3E-19 -8.77 1.0E-02 PA2385 PA14_33820 pvdQ 3-oxo-C12-homoserine lactone acylase PvdQ 10.86 2.7E-18 -8.43 3.6E-02 PA2384 PA14_33830 hypothetical protein 15.30 1.5E-20 -9.14 1.3E-02 PA2383 PA14_33840 probable transcriptional regulator 2.86 4.3E-17 PA2381 PA14_33870 hypothetical protein -2.29 1.5E-11 PA2380 PA14_33880 hypothetical protein -1.67 7.9E-03 PA2378 PA14_33900 probable aldehyde dehydrogenase 1.51 4.8E-03 PA2377 PA14_33910 hypothetical protein 7.94 1.3E-10 PA2374 PA14_33940 tseF TseF 2.45 7.4E-10 PA2373 PA14_33960 vgrG3 VgrG3 2.87 1.6E-08 PA14_33970 hypothetical protein 2.18 1.1E-12 -2.02 9.6E-03 PA14_33980 hypothetical protein 4.74 1.2E-20 PA2371 PA14_33990 clpV3 ClpV3 5.36 7.2E-47 PA2370 PA14_34000 hsiH3 HsiH3 4.38 6.6E-16 PA2369 PA14_34010 hsiG3 HsiG3 3.95 3.5E-22 PA2368 PA14_34020 hsiF3 HsiF3 4.63 1.1E-08 PA2367 PA14_34030 hcp3 Hcp3 3.05 1.2E-12 PA2366 PA14_34050 hsiC3 HsiC3 3.09 1.9E-21 PA2365 PA14_34070 hsiB3 HsiB3 2.26 5.1E-14 PA2364 PA14_34080 lip3 Lip3 2.32 1.0E-11 PA2363 PA14_34100 hsiJ3 HsiJ3 2.30 2.5E-18 PA2362 PA14_34110 dotU3 DotU3 1.93 9.0E-07 PA2361 PA14_34130 icmF3 IcmF3 2.27 1.1E-19 PA2360 PA14_34140 hsiA3 hypothetical protein 2.79 4.1E-19 PA2359 PA14_34150 sfa3 probable transcriptional regulator -1.97 1.5E-07 PA2356 PA14_34190 msuD methanesulfonate sulfonatase MsuD -1.58 2.2E-02 PA2348 PA14_34290 DszA family monooxygenase -2.21 8.3E-03 PA2346 PA14_34320 DszC family monooxygenase -1.66 3.4E-02 PA2342 PA14_34360 mtlD mannitol dehydrogenase 1.74 2.1E-02 PA2338 PA14_34420 probable binding protein component of ABC maltose/mannitol transporter 1.51 4.6E-03 PA2337 PA14_34440 mtlR transcriptional regulator MtlR 1.53 1.7E-04 PA2331 PA14_34460 hypothetical protein -1.89 2.9E-11 -2.21 1.3E-02 PA2330 PA14_34490 hypothetical protein -1.72 3.2E-08 PA2329 PA14_34500 probable ATP-binding component of ABC transporter -1.70 6.4E-06 -3.14 2.7E-03 PA2328 PA14_34510 hypothetical protein -1.74 2.9E-12 PA2324 PA14_34580 hypothetical protein -1.61 6.0E-06 138 PA2320 PA14_34660 gntR transcriptional regulator GntR 1.59 1.3E-19 PA2313 PA14_34720 hypothetical protein -2.52 4.5E-08 PA2312 PA14_34730 XRE family transcriptional regulator -3.04 3.5E-15 PA2311 PA14_34740 hypothetical protein -3.01 2.5E-09 PA2310 PA14_34750 taurine catabolism dioxygenase -2.95 9.0E-16 PA2309 PA14_34770 ABC transporter substrate-binding protein -1.89 3.0E-04 PA2305 PA14_34810 ambB AmbB 2.66 3.6E-41 PA2304 PA14_34820 ambC AmbC 3.48 2.7E-20 PA2303 PA14_34830 ambD AmbD 3.59 1.2E-30 PA2302 PA14_34840 ambE AmbE 4.17 1.5E-86 PA2301 PA14_34850 hypothetical protein 2.44 1.9E-37 PA2300 PA14_34870 chiC chitinase 1.96 2.1E-16 PA2299 PA14_34880 probable transcriptional regulator 1.99 7.2E-14 PA2298 PA14_34900 probable oxidoreductase 1.61 3.6E-11 PA2288 PA14_35000 hypothetical protein -1.58 5.5E-07 PA2283 PA14_35050 hypothetical protein -1.94 4.1E-03 PA2275 PA14_35150 probable alcohol dehydrogenase (Zn-dependent) -2.01 4.7E-06 PA2272 PA14_35190 pbpC penicillin-binding protein 3A 1.90 2.8E-20 PA2268 PA14_35240 hypothetical protein -8.85 9.2E-43 PA2267 PA14_35250 probable transcriptional regulator 1.63 1.5E-06 PA2266 PA14_35270 probable cytochrome c precursor -2.40 1.2E-12 1.52 2.3E-02 PA2265 PA14_35290 gluconate dehydrogenase -2.74 1.4E-16 PA2264 PA14_35300 conserved hypothetical protein -2.66 1.3E-13 PA2263 PA14_35320 probable 2-hydroxyacid dehydrogenase -2.64 5.4E-11 PA2262 PA14_35330 probable 2-ketogluconate transporter -3.07 7.9E-15 PA2261 PA14_35340 probable 2-ketogluconate kinase -3.29 3.5E-15 PA2260 PA14_35360 hypothetical protein -3.50 2.8E-13 1.68 1.8E-02 PA2259 PA14_35370 ptxS transcriptional regulator PtxS -2.14 1.3E-08 PA2258 PA14_35380 ptxR transcriptional regulator PtxR 2.38 1.7E-13 PA2245 PA14_35550 pslO hypothetical protein 4.24 5.3E-07 PA2244 PA14_35570 pslN hypothetical protein 3.85 2.5E-26 PA2235 PA14_35690 pslE PslE -1.53 3.1E-04 PA14_35740 transposase 1.72 2.9E-20 PA14_35750 tpnA repressor protein 2.16 2.8E-09 PA14_35760 hypothetical protein 1.78 4.5E-17 -2.45 3.7E-03 PA14_35780 hypothetical protein -1.62 1.2E-02 PA14_35800 hypothetical protein 1.60 2.7E-15 PA14_35830 tnpT cointegrate resolution protein -1.84 1.7E-02 139 T PA14_35940 acyl-CoA synthetase 1.64 2.5E-02 PA14_35950 dehydrogenase 1.76 3.3E-02 PA14_36010 hypothetical protein 1.64 3.9E-06 PA2204 PA14_36200 probable binding protein component of ABC transporter -2.10 4.2E-11 -1.57 3.2E-02 PA2203 PA14_36220 probable amino acid permease -2.95 5.3E-18 PA2202 PA14_36230 amino acid ABC transporter permease -2.66 1.2E-16 PA2196 PA14_36300 TetR family transcriptional regulator 1.56 5.0E-10 PA2195 PA14_36310 hcnC hydrogen cyanide synthase HcnC 2.10 2.8E-16 PA2194 PA14_36320 hcnB hydrogen cyanide synthase HcnB 1.87 2.1E-13 PA2193 PA14_36330 hcnA hydrogen cyanide synthase HcnA 1.72 1.5E-08 PA2191 PA14_36345 exoY adenylate cyclase ExoY 1.70 2.2E-06 -1.73 2.7E-02 PA2189 PA14_36350 hypothetical protein 2.88 8.4E-07 PA2187 PA14_36360 hypothetical protein 3.74 1.9E-07 PA2181 PA14_36370 hypothetical protein 4.84 2.1E-15 PA2180 PA14_36375 hypothetical protein 4.06 1.9E-39 PA2179 PA14_36390 hypothetical protein 4.27 6.5E-23 PA14_36400 hypothetical protein 1.79 1.9E-02 PA2178 PA14_36410 hypothetical protein 3.68 5.5E-09 PA2177 PA14_36420 probable sensor/response regulator hybrid 2.34 3.7E-18 PA2176 PA14_36450 hypothetical protein 3.87 1.0E-27 PA2175 PA14_36460 hypothetical protein 4.34 1.0E-28 PA2174 PA14_36470 hypothetical protein 1.85 2.9E-06 PA14_36480 hypothetical protein 3.73 8.5E-17 PA2173 PA14_36490 hypothetical protein 4.27 6.6E-21 PA2172 PA14_36500 hypothetical protein 3.50 1.2E-33 PA2171 PA14_36520 hypothetical protein 2.74 4.4E-21 PA2169 PA14_36530 hypothetical protein 2.34 2.0E-09 PA2168 PA14_36540 hypothetical protein 4.63 3.4E-19 PA2167 PA14_36550 hypothetical protein 4.03 1.3E-35 PA2166 PA14_36560 hypothetical protein 5.06 7.3E-36 PA2165 PA14_36570 probable glycogen synthase 4.33 1.0E-55 PA2164 PA14_36580 probable glycosyl hydrolase 4.00 5.2E-53 PA2163 PA14_36590 hypothetical protein 4.06 2.0E-43 PA2162 PA14_36605 probable glycosyl hydrolase 3.17 1.7E-22 PA2161 PA14_36620 hypothetical protein 2.44 4.0E-07 PA2160 PA14_36630 probable glycosyl hydrolase 1.96 1.2E-04 PA2159 PA14_36650 conserved hypothetical protein 2.53 1.4E-13 140 PA2158 PA14_36660 probable alcohol dehydrogenase (Zn-dependent) 2.75 2.1E-14 PA2157 PA14_36670 hypothetical protein 2.94 5.3E-11 PA2156 PA14_36680 conserved hypothetical protein 2.50 1.1E-05 PA2155 PA14_36690 probable phospholipase 2.51 2.0E-08 PA2154 PA14_36700 conserved hypothetical protein 1.97 1.0E-02 PA2153 PA14_36710 glgB 1,4-alpha-glucan branching enzyme 2.98 7.6E-20 PA2152 PA14_36730 probable trehalose synthase 3.75 3.9E-72 PA2151 PA14_36740 conserved hypothetical protein 4.52 3.1E-50 PA2150 PA14_36760 conserved hypothetical protein 3.94 1.1E-26 PA2149 PA14_36770 hypothetical protein 4.84 6.1E-10 PA2148 PA14_36780 conserved hypothetical protein 3.83 3.1E-16 PA14_36790 hypothetical protein 3.50 7.4E-08 PA2147 PA14_36810 katE catalase HPII 2.91 4.0E-24 PA2146 PA14_36820 conserved hypothetical protein 2.61 1.3E-12 -1.80 1.9E-02 PA2145 PA14_36830 hypothetical protein 2.26 8.5E-07 PA2144 PA14_36840 glgP glycogen phosphorylase 3.89 3.7E-51 PA2143 PA14_36850 hypothetical protein 3.58 3.4E-32 PA2142 PA14_36870 probable short-chain dehydrogenase 3.86 6.3E-18 PA2141 PA14_36880 hypothetical protein 4.95 2.1E-07 PA2140 PA14_36890 probable metallothionein 8.66 3.5E-04 PA2170 PA14_36900 hypothetical protein 5.62 2.7E-06 PA2138 PA14_36910 ligD Multifunctional non-homologous end joining protein LigD 3.43 7.4E-17 PA2137 PA14_36920 hypothetical protein 3.25 5.6E-18 PA2136 PA14_36930 hypothetical protein 3.91 6.5E-05 PA2135 PA14_36960 probable transporter 2.75 1.3E-14 PA2134 PA14_36980 hypothetical protein 2.66 5.0E-17 PA2133 PA14_36990 Cyclic-guanylate-specific phosphodiesterase -1.95 4.7E-03 PA2132 PA14_37000 cupA5 chaperone CupA5 -4.71 1.4E-05 PA2131 PA14_37010 cupA4 fimbrial subunit CupA4 -5.04 9.0E-10 PA2130 PA14_37030 cupA3 usher -3.54 3.7E-17 PA2129 PA14_37040 cupA2 chaperone CupA2 -4.66 2.1E-23 PA2128 PA14_37060 cupA1 fimbrial subunit CupA1 -4.55 7.1E-80 PA2121 PA14_37140 probable transcriptional regulator 1.60 4.0E-03 PA2118 PA14_37190 ada O6-methylguanine-DNA methyltransferase 1.72 4.9E-10 PA2108 PA14_37340 probable decarboxylase 2.97 1.2E-16 PA2107 PA14_37350 hypothetical protein 5.03 1.6E-14 PA2099 PA14_37360 probable short-chain dehydrogenase 1.57 3.8E-02 141 PA2094 PA14_37420 transmembrane sensor protein 3.73 7.9E-13 PA2093 PA14_37430 probable sigma-70 factor, ECF subfamily 2.53 2.4E-07 PA2092 PA14_37440 MFS transporter 3.49 6.1E-13 PA2091 PA14_37460 permease 2.94 3.3E-09 PA2090 PA14_37470 flavin-dependent oxidoreductase 3.33 3.0E-12 PA2089 PA14_37490 hypothetical protein 2.59 1.4E-18 PA2088 PA14_37510 hypothetical protein 3.55 1.9E-13 PA2087 PA14_37520 hypothetical protein 3.24 4.1E-07 PA2086 PA14_37530 hydrolase 3.08 1.4E-08 PA2085 PA14_37550 ring-hydroxylating dioxygenase small subunit 2.74 9.5E-05 PA2084 PA14_37560 probable asparagine synthetase 2.32 2.2E-07 PA2082 PA14_37580 kynR KynR 1.52 1.6E-04 PA2081 PA14_37590 kynB kynurenine formamidase, KynB 1.51 4.1E-06 PA2080 PA14_37610 kynU kynureninase KynU 1.53 5.9E-06 PA2079 PA14_37630 probable amino acid permease 1.81 1.1E-07 PA14_37670 hypothetical protein 1.86 2.4E-04 PA2072 PA14_37690 conserved hypothetical protein 1.68 8.2E-17 PA2071 PA14_37710 fusA2 elongation factor G 1.78 4.4E-26 PA2067 PA14_37770 probable hydrolase 1.57 2.8E-18 PA2063 PA14_37820 hypothetical protein -1.54 9.2E-12 PA2061 PA14_37840 sppD ABC transporter ATP-binding protein, SppD 1.59 4.2E-03 PA2051 PA14_37980 Fe2+-dicitrate sensor, membrane protein -3.32 5.8E-08 PA2050 PA14_37990 RNA polymerase sigma factor -4.51 1.5E-13 PA2046 PA14_38050 hypothetical protein 3.02 9.0E-14 PA2042 PA14_38110 probable transporter (membrane subunit) -1.78 9.3E-27 PA2041 PA14_38130 Amino acid permease -2.04 1.0E-12 PA2040 PA14_38140 pauA4 Glutamylpolyamine synthetase -1.53 8.6E-08 PA2039 PA14_38160 hypothetical protein -2.18 6.0E-17 PA2038 PA14_38170 hypothetical protein -2.06 8.4E-11 PA2034 PA14_38210 hypothetical protein 1.59 1.4E-02 PA2033 PA14_38220 hypothetical protein 1.70 6.5E-04 PA2032 PA14_38250 probable transcriptional regulator 1.60 8.7E-18 PA2031 PA14_38260 hypothetical protein 1.77 2.3E-08 PA2030 PA14_38270 hypothetical protein 1.66 7.1E-09 PA2027 PA14_38310 hypothetical protein 1.88 4.3E-03 PA2021 PA14_38370 hypothetical protein 3.71 1.9E-13 142 PA2020 PA14_38380 mexZ MexZ 1.63 2.8E-02 PA2019 PA14_38395 mexX Resistance-Nodulation-Cell Division (RND) multidrug efflux membrane fusion protein MexX precursor -1.78 3.4E-07 8.54 3.5E-22 PA2018 PA14_38410 mexY Resistance-Nodulation-Cell Division (RND) multidrug efflux transporter MexY -1.59 2.1E-06 8.04 1.3E-36 PA2016 PA14_38430 liuR regulator of liu genes -2.29 7.8E-03 PA1990 PA14_38770 pqqH PqqH 2.17 4.3E-17 PA1989 PA14_38780 pqqE pyrroloquinoline quinone biosynthesis protein E 1.56 3.3E-07 PA1988 PA14_38790 pqqD pyrroloquinoline quinone biosynthesis protein D 1.95 1.2E-06 PA1987 PA14_38800 pqqC pyrroloquinoline quinone biosynthesis protein C 1.79 2.2E-09 PA1986 PA14_38820 pqqB pyrroloquinoline quinone biosynthesis protein B 1.74 7.9E-09 PA1982 PA14_38860 exaA quinoprotein ethanol dehydrogenase 1.71 1.6E-02 PA1973 PA14_39010 pqqF pyrroloquinoline quinone biosynthesis protein F 1.56 1.7E-05 PA1964 PA14_39130 probable ATP-binding component of ABC transporter -1.71 6.2E-10 PA1960 PA14_39180 hypothetical protein -1.63 1.3E-09 PA1959 PA14_39190 bacA bacitracin resistance protein -2.03 3.3E-41 PA1951 PA14_39270 fapF FapF 1.98 1.8E-16 PA1942 PA14_39420 hypothetical protein -1.52 3.2E-02 PA14_39470 hypothetical protein -1.63 1.9E-02 PA1934 PA14_39500 hypothetical protein 4.65 5.6E-18 PA1933 PA14_39520 probable hydroxylase large subunit 3.24 2.0E-45 PA1932 PA14_39530 probable hydroxylase molybdopterin-containing subunit 3.38 6.6E-31 PA1931 PA14_39540 probable ferredoxin 3.15 1.3E-24 PA1930 PA14_39560 probable chemotaxis transducer 1.52 2.8E-05 PA1927 PA14_39590 metE 5-methyltetrahydropteroyltriglutamate-homocysteine S-methyltransferase -1.73 2.8E-12 PA1921 PA14_39660 hypothetical protein 2.23 1.0E-08 PA1920 PA14_39690 nrdD class III (anaerobic) ribonucleoside-triphosphate reductase subunit, NrdD 2.75 3.2E-23 PA14_39700 hypothetical protein 3.17 3.7E-10 PA1919 PA14_39710 nrdG class III (anaerobic) ribonucleoside-triphosphate reductase activating protein, 'activase', NrdG 4.24 8.1E-07 143 PA1918 PA14_39720 amino acid oxidase 1.99 4.3E-03 PA1914 PA14_39780 conserved hypothetical protein 2.83 1.4E-12 PA1913 PA14_39790 hypothetical protein -3.09 4.5E-25 PA1912 PA14_39800 femI ECF sigma factor, FemI -1.59 2.6E-03 PA1910 PA14_39820 femA ferric-mycobactin receptor, FemA -1.53 2.7E-03 PA1907 PA14_39860 hypothetical protein 1.77 7.2E-06 PA14_39880 phzG2 pyridoxamine 5'-phosphate oxidase 3.26 7.2E-24 PA1901 PA14_39945 phzC2 phenazine biosynthesis protein PhzC 2.38 2.0E-17 PA4212 PA14_39945 phzC1 phenazine biosynthesis protein PhzC 2.38 2.0E-17 PA1900 PA14_39960 phzB2 probable phenazine biosynthesis protein 2.43 4.0E-16 PA1899 PA14_39970 phzA2 probable phenazine biosynthesis protein 2.62 9.3E-20 -1.67 9.8E-06 PA1898 PA14_39980 qscR quorum-sensing control repressor 1.73 2.7E-07 PA1897 PA14_39990 hypothetical protein 1.50 3.3E-04 PA1896 PA14_40010 hypothetical protein 1.79 2.4E-07 PA1895 PA14_40020 hypothetical protein 1.79 4.0E-08 -2.12 2.0E-02 PA1894 PA14_40030 hypothetical protein 1.89 1.7E-12 -1.54 2.1E-02 PA1893 PA14_40040 hypothetical protein 1.88 1.2E-10 PA1892 PA14_40050 hypothetical protein 1.68 7.5E-08 PA1891 PA14_40060 hypothetical protein 1.94 1.9E-08 PA1889 PA14_40080 hypothetical protein 1.52 9.5E-08 PA1882 PA14_40170 probable transporter -1.99 5.9E-06 PA1879 PA14_40210 hypothetical protein -1.51 1.6E-03 PA1878 PA14_40220 hypothetical protein -2.25 3.1E-19 PA1877 PA14_40230 probable secretion protein 2.10 2.2E-14 PA1876 PA14_40240 probable ATP-binding/permease fusion ABC transporter 2.03 2.8E-16 PA1875 PA14_40250 probable outer membrane protein precursor 2.29 5.4E-24 PA1874 PA14_40260 hypothetical protein 2.17 5.0E-18 PA1871 PA14_40290 lasA LasA protease precursor 5.84 1.2E-82 PA1860 PA14_40430 hypothetical protein 1.54 4.0E-07 PA1852 PA14_40560 hypothetical protein 1.75 4.7E-13 PA1847 PA14_40630 nfuA NfuA -1.70 1.3E-33 PA1845 PA14_40650 tsi1 Tsi1 -1.51 3.5E-05 PA14_40750 pvdD pyoverdine synthetase D 2.02 5.5E-15 PA1838 PA14_40770 cysI sulfite reductase -1.93 9.3E-22 PA1837 PA14_40780 hypothetical protein -1.75 2.8E-13 PA1824 PA14_40940 conserved hypothetical protein -2.07 2.9E-15 PA1805 PA14_41190 ppiD peptidyl-prolyl cis-trans isomerase D -1.69 4.6E-24 144 PA1803 PA14_41220 lon Lon protease -1.63 1.1E-25 PA1801 PA14_41240 clpP ClpP -1.51 3.7E-18 PA1797 PA14_41280 hypothetical protein 1.98 2.8E-11 PA14_41290 hypothetical protein 2.31 2.5E-03 PA14_41300 hypothetical protein -1.69 3.7E-09 PA1786 PA14_41480 nasS NasS -1.75 7.6E-10 1.78 2.8E-04 PA1776 PA14_41575 sigX ECF sigma factor SigX -1.59 1.4E-02 PA1768 PA14_41690 hypothetical protein -1.85 1.6E-02 PA1757 PA14_41830 thrH homoserine kinase -1.67 1.0E-17 PA1755 PA14_41860 hypothetical protein -1.60 1.7E-06 PA1751 PA14_41910 hypothetical protein 1.52 3.6E-07 PA1748 PA14_41950 probable enoyl-CoA hydratase/isomerase -1.84 3.2E-27 PA1747 PA14_41960 hypothetical protein -2.33 5.4E-05 PA1745 PA14_41980 hypothetical protein 1.92 1.2E-11 PA1733 PA14_42130 conserved hypothetical protein 1.87 1.8E-14 PA1732 PA14_42140 conserved hypothetical protein 1.72 7.1E-09 1.52 2.4E-02 PA1731 PA14_42150 conserved hypothetical protein 1.92 2.1E-15 PA1730 PA14_42160 conserved hypothetical protein 1.98 1.5E-28 PA1725 PA14_42250 pscL type III export protein PscL 2.14 1.4E-14 -1.93 2.5E-02 PA1724 PA14_42260 pscK type III export protein PscK 1.74 9.9E-06 PA1723 PA14_42270 pscJ type III export protein PscJ 1.62 8.1E-08 PA1722 PA14_42280 pscI type III export protein PscI 1.60 1.3E-05 PA1721 PA14_42290 pscH type III export protein PscH 1.61 2.3E-05 PA1720 PA14_42300 pscG type III export protein PscG 1.62 2.3E-08 PA1719 PA14_42310 pscF type III export protein PscF 1.54 1.0E-05 PA1717 PA14_42340 pscD type III export protein PscD 1.78 2.6E-07 PA1716 PA14_42350 pscC Type III secretion outer membrane protein PscC precursor 1.70 2.0E-07 -1.62 2.6E-02 PA1715 PA14_42360 pscB type III export apparatus protein 1.76 9.4E-07 PA1714 PA14_42380 exsD ExsD 2.01 1.3E-15 -1.61 1.3E-02 PA1713 PA14_42390 exsA transcriptional regulator ExsA 2.73 1.3E-24 -2.43 1.5E-07 PA1712 PA14_42400 exsB exoenzyme S synthesis protein B 1.88 8.8E-10 PA1711 PA14_42410 exsE ExsE 1.84 1.1E-13 PA1710 PA14_42430 exsC ExsC, exoenzyme S synthesis protein C precursor. 1.84 3.1E-12 PA1709 PA14_42440 popD Translocator outer membrane protein PopD precursor -1.72 1.0E-02 PA1708 PA14_42450 popB translocator protein PopB -2.32 8.7E-06 PA1707 PA14_42460 pcrH regulatory protein PcrH -1.84 2.7E-02 PA1706 PA14_42470 pcrV type III secretion protein PcrV -2.27 2.7E-04 145 PA1703 PA14_42500 pcrD type III secretory apparatus protein PcrD -2.24 2.7E-04 PA1698 PA14_42550 popN Type III secretion outer membrane protein PopN precursor -2.24 5.6E-03 PA1696 PA14_42580 pscO translocation protein in type III secretion 1.58 3.5E-03 PA1690 PA14_42660 pscU translocation protein in type III secretion 1.53 5.6E-04 PA1673 PA14_42860 hypothetical protein 1.84 6.9E-08 PA1672 PA14_42870 hypothetical protein 1.51 1.3E-10 PA5266 PA14_43080 vgrG14 VgrG14 -1.61 1.0E-02 PA14_43090 tap Tap -1.62 2.3E-03 PA1649 PA14_43180 probable short-chain dehydrogenase -1.99 1.2E-04 PA1624 PA14_43520 hypothetical protein 1.88 1.8E-02 PA1608 PA14_43710 probable chemotaxis transducer -1.93 1.6E-18 PA1606 PA14_43730 hypothetical protein 2.98 1.4E-12 PA1605 PA14_43740 hypothetical protein 2.47 4.1E-12 PA1598 PA14_43830 conserved hypothetical protein -1.55 1.1E-03 PA1596 PA14_43850 htpG heat shock protein HtpG -2.67 2.6E-10 PA1580 PA14_44070 gltA citrate synthase -1.63 3.7E-02 PA14_44090 Fe-S-cluster oxidoreductase -1.51 4.7E-05 PA1577 PA14_44110 hypothetical protein -1.96 8.4E-08 PA1574 PA14_44140 conserved hypothetical protein -1.65 2.6E-15 PA1571 PA14_44170 hypothetical protein 1.87 7.2E-15 1.53 3.4E-02 PA14_44230 hypothetical protein -1.80 3.3E-02 PA1566 PA14_44240 pauA3 Glutamylpolyamine synthetase -1.82 5.3E-03 PA1565 PA14_44260 pauB2 FAD-dependent oxidoreductase -1.55 1.9E-03 PA1562 PA14_44290 acnA aconitate hydratase 1 1.72 3.4E-11 PA1556 PA14_44350 ccoO2 Cytochrome c oxidase, cbb3-type, CcoO subunit 1.72 1.1E-05 PA1555 PA14_44360 ccoP2 Cytochrome c oxidase, cbb3-type, CcoP subunit 1.73 1.8E-06 PA1554 PA14_44370 ccoN1 Cytochrome c oxidase, cbb3-type, CcoN subunit -1.85 3.8E-26 PA1553 PA14_44380 ccoO1 Cytochrome c oxidase, cbb3-type, CcoO subunit -1.75 4.7E-25 PA1552.1 PA14_44390 ccoQ1 Cytochrome c oxidase, cbb3-type, CcoQ subunit -1.64 1.3E-16 PA1552 PA14_44400 ccoP1 Cytochrome c oxidase, cbb3-type, CcoP subunit -1.65 4.1E-21 PA1551 PA14_44420 probable ferredoxin -1.58 1.7E-11 146 PA1549 PA14_44440 probable cation-transporting P-type ATPase -1.54 6.9E-12 PA1547 PA14_44460 hypothetical protein -1.53 9.2E-06 PA1545 PA14_44480 hypothetical protein -1.78 3.0E-02 PA1543 PA14_44500 apt adenine phosphoribosyltransferase -1.52 2.1E-17 PA1542 PA14_44510 hypothetical protein -2.57 2.9E-19 PA1541 PA14_44520 drug efflux transporter -5.57 1.5E-10 PA1540 PA14_44530 multidrug efflux system protein MdtI -2.40 6.7E-05 PA1538 PA14_44560 probable flavin-containing monooxygenase -1.91 7.7E-07 PA1537 PA14_44570 probable short-chain dehydrogenase -1.74 6.7E-04 PA1525 PA14_44700 alkB2 alkane-1-monooxygenase 2 1.83 1.7E-04 PA1524 PA14_44710 xdhA xanthine dehydrogenase 1.82 8.4E-05 PA1523 PA14_44740 xdhB xanthine dehydrogenase 1.83 9.0E-07 PA1515 PA14_44850 alc allantoicase 1.54 7.9E-06 PA0263 PA14_44890 hcpC secreted protein Hcp -1.65 1.6E-02 PA1512 PA14_44890 hcpA secreted protein Hcp -1.65 1.6E-02 PA1511 PA14_44900 vgrG2a VgrG2a -1.74 1.4E-02 PA1510 PA14_44910 tplE type 6 PGAP1-like effector, TplE -1.58 3.7E-02 PA1502 PA14_45000 gcl glyoxylate carboligase -1.79 3.9E-03 PA1494 PA14_45100 muiA mucoidy inhibitor gene A -1.76 3.1E-12 PA1493 PA14_45110 cysP sulfate-binding protein of ABC transporter -1.68 9.4E-26 -1.55 1.3E-02 PA1484 PA14_45250 probable transcriptional regulator 1.54 5.6E-05 PA1439 PA14_45850 conserved hypothetical protein -1.69 2.5E-15 PA1435 PA14_45910 probable Resistance-Nodulation-Cell Division (RND) efflux membrane fusion protein precursor -1.57 1.1E-02 PA1431 PA14_45950 rsaL regulatory protein RsaL 3.01 2.1E-74 -1.77 1.7E-02 PA1429 PA14_45970 probable cation-transporting P-type ATPase 1.82 7.6E-16 PA1428 PA14_45980 conserved hypothetical protein -2.40 1.5E-12 PA1425 PA14_46010 probable ATP-binding component of ABC transporter -1.71 8.2E-10 PA1423 PA14_46030 bdlA BdlA -1.62 8.6E-06 PA1408 PA14_46240 hypothetical protein 2.28 4.3E-16 1.57 2.8E-02 PA1404 PA14_46280 hypothetical protein 3.39 4.7E-27 PA1403 PA14_46290 probable transcriptional regulator 2.02 4.2E-07 PA14_46460 hypothetical protein -1.79 9.5E-03 PA14_46510 hypothetical protein 1.83 2.2E-19 147 PA14_46520 hypothetical protein 1.79 4.0E-08 PA14_46530 hypothetical protein 1.85 1.2E-12 PA14_46540 hypothetical protein 2.21 1.8E-28 PA14_46550 ribonuclease 1.82 3.5E-18 PA1356 PA14_46750 hypothetical protein 2.68 2.5E-19 PA1355 PA14_46760 hypothetical protein 1.97 5.1E-04 PA1351 PA14_46810 probable sigma-70 factor, ECF subfamily 1.90 1.7E-10 PA1350 PA14_46820 hypothetical protein 1.86 8.1E-11 PA1349 PA14_46830 conserved hypothetical protein 1.63 3.2E-05 PA1348 PA14_46840 hypothetical protein 2.40 6.4E-16 PA1346 PA14_46860 hypothetical protein 1.85 2.7E-04 PA1343 PA14_46900 hypothetical protein -1.64 2.7E-06 PA1330 PA14_47060 probable short-chain dehydrogenase 1.75 3.0E-04 PA1324 PA14_47120 hypothetical protein 2.26 1.1E-19 PA1323 PA14_47130 hypothetical protein 2.35 3.2E-20 PA1321 PA14_47150 cyoE cytochrome o ubiquinol oxidase protein CyoE 1.88 6.0E-09 PA1320 PA14_47160 cyoD cytochrome o ubiquinol oxidase subunit IV 1.88 4.4E-05 PA1317 PA14_47210 cyoA cytochrome o ubiquinol oxidase subunit II -1.69 6.0E-04 PA1316 PA14_47230 probable major facilitator superfamily (MFS) transporter -1.56 5.9E-03 PA1314 PA14_47250 hypothetical protein 1.55 1.9E-02 PA1311 PA14_47280 phnX 2-phosphonoacetaldehyde hydrolase 1.61 8.8E-04 PA1302 PA14_47380 probable heme utilization protein precursor -1.54 1.7E-04 PA1301 PA14_47390 probable transmembrane sensor 1.55 2.4E-03 PA1299 PA14_47410 conserved hypothetical protein -1.74 5.1E-13 PA1296 PA14_47440 probable 2-hydroxyacid dehydrogenase -1.51 2.8E-03 PA1291 PA14_47510 hypothetical protein 2.20 1.1E-08 PA1288 PA14_47540 probable outer membrane protein precursor -1.68 2.7E-38 PA1286 PA14_47560 probable major facilitator superfamily (MFS) transporter -1.79 7.3E-05 PA1281 PA14_47650 cobV cobalamin (5'-phosphate) synthase 1.53 1.2E-10 PA1262 PA14_47900 MFS transporter -2.14 2.5E-04 PA1260 PA14_47920 lhpP ABC transporter periplasmic-binding protein, LhpP -3.12 2.1E-05 PA1256 PA14_47960 lhpO ABC transporter ATP-binding -2.09 7.5E-03 148 protein, LhpO PA1255 PA14_47970 lhpK D-hydroxyproline epimerase, LhpK -2.11 2.9E-04 PA1254 PA14_48000 lhpC delta1-pyrroline-4-hydroxy-2-carboxylate deaminase, LphC -6.19 1.7E-13 PA1253 PA14_48010 lhpG semialdehyde dehydrogenase -2.04 4.5E-04 PA1252 PA14_48020 dpkA DpkA 1.91 1.5E-10 PA1250 PA14_48040 aprI alkaline proteinase inhibitor AprI 2.39 9.1E-55 PA1249 PA14_48060 aprA alkaline metalloproteinase precursor 8.45 1.9E-102 -1.54 1.8E-05 PA1248 PA14_48090 aprF Alkaline protease secretion outer membrane protein AprF precursor 3.70 1.1E-64 PA1247 PA14_48100 aprE alkaline protease secretion protein AprE 3.60 2.4E-88 PA1246 PA14_48115 aprD alkaline protease secretion protein AprD 3.12 8.0E-65 PA1245 PA14_48140 aprX AprX 3.39 6.1E-98 PA1243 PA14_48160 probable sensor/response regulator hybrid 3.15 1.4E-40 PA1242 PA14_48170 sprP SprP 2.30 3.9E-26 PA1240 PA14_48200 probable enoyl-CoA hydratase/isomerase 3.08 2.1E-13 PA1239 PA14_48210 hypothetical protein 1.91 1.3E-03 PA1238 PA14_48240 outer membrane component of multidrug efflux pump 1.69 4.3E-02 PA1221 PA14_48530 hypothetical protein 2.24 3.0E-14 PA1220 PA14_48540 hypothetical protein 2.72 1.1E-18 PA1219 PA14_48550 hypothetical protein 2.28 2.1E-08 PA1218 PA14_48560 hypothetical protein 2.90 5.3E-17 PA1217 PA14_48570 probable 2-isopropylmalate synthase 2.91 1.0E-11 PA1216 PA14_48590 hypothetical protein 3.29 6.3E-22 PA1215 PA14_48600 hypothetical protein 2.75 1.1E-19 PA1214 PA14_48610 hypothetical protein 3.55 3.5E-26 PA1213 PA14_48620 hypothetical protein 3.36 2.1E-22 PA1212 PA14_48630 probable major facilitator superfamily (MFS) transporter 3.14 8.2E-15 PA1211 PA14_48640 hypothetical protein 3.41 1.9E-19 PA1200 PA14_48780 conserved hypothetical protein 1.82 1.8E-25 1.58 3.0E-02 PA1198 PA14_48800 conserved hypothetical protein -1.63 1.3E-02 PA1196 PA14_48830 ddaR transcriptional regulator DdaR 1.59 2.7E-07 PA0727 PA14_48890 hypothetical protein from bacteriophage Pf1 1.61 4.5E-03 PA14_49020 pf5r Pf5 repressor C -1.70 1.3E-02 149 PA14_49030 hypothetical protein -1.50 1.9E-02 PA1190 PA14_49050 conserved hypothetical protein 2.07 1.2E-07 1.70 4.3E-03 PA1183 PA14_49130 dctA C4-dicarboxylate transport protein -4.42 1.1E-05 PA1180 PA14_49170 phoQ two-component sensor PhoQ -2.02 4.7E-16 PA1179 PA14_49180 phoP two-component response regulator PhoP -1.80 5.5E-14 PA1178 PA14_49200 oprH PhoP/Q and low Mg2+ inducible outer membrane protein H1 precursor -1.84 5.8E-30 PA1177 PA14_49210 napE periplasmic nitrate reductase protein NapE 1.74 6.5E-06 PA1176 PA14_49220 napF ferredoxin protein NapF 1.70 1.1E-09 PA1175 PA14_49230 napD NapD protein of periplasmic nitrate reductase 1.66 2.4E-06 PA1174 PA14_49250 napA periplasmic nitrate reductase protein NapA 1.67 1.6E-10 PA1173 PA14_49260 napB cytochrome c-type protein NapB precursor 1.52 5.0E-03 PA1172 PA14_49270 napC cytochrome c-type protein NapC 1.75 1.1E-06 PA1169 PA14_49300 probable lipoxygenase -1.56 3.8E-05 PA1168 PA14_49310 hypothetical protein -1.93 5.2E-09 -1.77 9.6E-03 PA1164 PA14_49350 conserved hypothetical protein -1.52 2.4E-02 PA1159 PA14_49410 probable cold-shock protein 2.14 5.5E-44 PA14_49480 hypothetical protein -2.26 4.3E-03 PA14_49510 pyoS3I immunity protein S3I structural gene -1.82 1.9E-04 PA14_49520 pyoS3A pyocin killing protein 1.66 2.0E-07 -3.07 2.6E-11 PA1148 PA14_49560 toxA exotoxin A precursor 2.71 7.5E-03 PA1137 PA14_49690 probable oxidoreductase -11.61 2.0E-105 PA1134 PA14_49720 hypothetical protein 4.00 1.3E-17 PA1132 PA14_49740 hypothetical protein -1.56 6.7E-18 PA1130 PA14_49760 rhlC rhamnosyltransferase 2 1.85 2.6E-16 PA1129 PA14_49780 fosA fosfomycin resistance protein, FosA 1.87 9.8E-04 PA1128 PA14_49790 probable transcriptional regulator 1.66 1.9E-05 PA1127 PA14_49800 probable oxidoreductase 1.80 4.2E-21 PA1123 PA14_49850 hypothetical protein -1.55 1.5E-05 PA1116 PA14_49930 hypothetical protein -2.09 1.1E-20 PA1114 PA14_49960 hypothetical protein 1.55 6.0E-05 PA14_50000 hypothetical protein -1.61 2.1E-04 PA1112 PA14_50010 conserved hypothetical protein 1.59 2.5E-09 PA1111 PA14_50020 hypothetical protein 2.85 5.1E-18 150 PA1096 PA14_50240 hypothetical protein -1.55 1.8E-12 PA1095 PA14_50250 hypothetical protein -1.52 8.9E-19 PA1094 PA14_50270 fliD flagellar capping protein FliD -1.65 2.7E-25 PA1093 PA14_50280 hypothetical protein -2.32 2.7E-26 PA1092 PA14_50290 fliC flagellin type B -2.22 3.5E-30 PA1066 PA14_50610 probable short-chain dehydrogenase 1.79 9.1E-05 PA1055 PA14_50720 shaB ShaB -1.64 8.3E-09 PA1041 PA14_50880 probable outer membrane protein precursor 1.73 2.6E-07 PA1034 PA14_50950 hypothetical protein -1.53 2.1E-02 PA1028 PA14_51040 amaA L-Pipecolate oxidase 1.87 1.7E-06 PA1027 PA14_51050 amaB delta1-Piperideine-6-carboxylate dehydrogenase 1.72 3.3E-07 PA1024 PA14_51080 NADH:quinone reductase 1.61 5.1E-04 PA1020 PA14_51120 probable acyl-CoA dehydrogenase 1.72 1.7E-04 PA0990 PA14_51490 conserved hypothetical protein 2.68 9.5E-14 PA14_51520 spcU SpcU 2.03 2.0E-18 PA14_51530 exoU ExoU 1.91 4.8E-15 PA14_51590 hypothetical protein 1.57 3.1E-04 PA0978 PA14_51630 conserved hypothetical protein 1.78 4.9E-02 PA0976 PA14_51670 conserved hypothetical protein -2.36 9.8E-25 PA0975 PA14_51680 probable radical activating enzyme -2.19 2.5E-27 PA0971 PA14_51730 tolA TolA protein -1.62 2.4E-03 PA0970 PA14_51740 tolR TolR protein -1.53 1.8E-02 PA0968 PA14_51770 conserved hypothetical protein -1.70 1.1E-02 PA0945 PA14_52040 purM phosphoribosylaminoimidazole synthetase -1.57 4.3E-24 PA0937 PA14_52140 conserved hypothetical protein -1.93 1.7E-02 PA0922 PA14_52330 hypothetical protein -1.93 3.8E-20 PA0921 PA14_52340 hypothetical protein -1.67 2.0E-07 PA0916 PA14_52420 conserved hypothetical protein -1.83 2.7E-14 PA0915 PA14_52430 conserved hypothetical protein -2.18 2.2E-20 PA0914 PA14_52440 hypothetical protein -2.45 1.9E-18 PA0913 PA14_52460 mgtE MgtE -1.86 1.1E-57 PA0911 PA14_52480 alpE AlpE -4.05 3.1E-34 PA0910 PA14_52490 alpD AlpD -4.47 2.0E-37 PA0909 PA14_52500 alpC AlpC -4.18 2.7E-12 PA0908 PA14_52510 alpB AlpB -2.72 5.0E-06 PA0907 PA14_52520 alpA lysis phenotype activator, AlpA -1.74 5.1E-06 PA0905 PA14_52570 rsmA RsmA -1.88 8.8E-03 PA0887 PA14_52800 acsA acetyl-coenzyme A synthetase 2.29 3.9E-04 151 PA0884 PA14_52840 probable C4-dicarboxylate-binding periplasmic protein 1.89 6.6E-03 PA0866 PA14_53050 aroP2 aromatic amino acid transport protein AroP2 -1.79 1.3E-27 PA0861 PA14_53140 rbdA RbDA 1.61 5.3E-18 PA0853 PA14_53230 probable oxidoreductase 1.61 3.2E-10 PA0852 PA14_53250 cbpD chitin-binding protein CbpD precursor 1.53 5.0E-11 PA0843 PA14_53370 plcR phospholipase accessory protein PlcR precursor 1.71 8.8E-05 PA0840 PA14_53400 probable oxidoreductase -2.10 3.2E-05 PA0839 PA14_53410 probable transcriptional regulator -1.53 2.7E-04 PA0837 PA14_53430 slyD peptidyl-prolyl cis-trans isomerase SlyD -1.77 5.8E-19 PA14_53590 -2.18 7.2E-03 PA14_53600 -1.91 1.8E-02 PA0826 PA14_53620 hypothetical protein -1.62 2.9E-02 PA0820 PA14_53670 hypothetical protein -1.97 1.5E-02 PA14_53680 -1.95 1.8E-02 PA0816 PA14_53720 probable transcriptional regulator 1.82 2.1E-10 PA0814 PA14_53740 conserved hypothetical protein 1.67 7.2E-03 PA0807 PA14_53820 ampDh3 AmpDh3 -2.02 5.0E-48 PA0802 PA14_53870 hypothetical protein 1.92 8.8E-08 PA0801 PA14_53880 hypothetical protein 1.52 6.6E-06 PA0800 PA14_53890 hypothetical protein 1.55 9.5E-03 PA0798 PA14_53910 pmtA phospholipid methyltransferase 1.81 3.0E-12 PA0792 PA14_54000 prpD propionate catabolic protein PrpD 2.01 1.4E-17 PA0781 PA14_54180 hypothetical protein 1.63 1.6E-02 PA0779 PA14_54210 asrA AsrA -4.20 8.4E-36 PA0778 PA14_54220 icp inhibitor of cysteine peptidase -2.36 4.1E-25 PA0777 PA14_54230 hypothetical protein -1.60 3.7E-07 PA0755 PA14_54520 opdH cis-aconitate porin OpdH 3.23 1.2E-25 PA0754 PA14_54540 hypothetical protein 3.09 4.4E-23 PA0753 PA14_54550 hypothetical protein 4.58 7.9E-11 PA0752 PA14_54570 conserved hypothetical protein 3.09 4.3E-19 PA0751 PA14_54580 conserved hypothetical protein 2.77 1.4E-12 PA0747 PA14_54620 probable aldehyde dehydrogenase 1.61 2.2E-06 PA0746 PA14_54630 probable acyl-CoA dehydrogenase 1.58 2.5E-05 PA0745 PA14_54640 dspI DspI 1.75 2.7E-08 PA0744 PA14_54660 probable enoyl-CoA 1.87 2.8E-10 152 hydratase/isomerase PA0743 PA14_54670 probable 3-hydroxyisobutyrate dehydrogenase 1.99 1.2E-17 PA0740 PA14_54700 sdsA1 SDS hydrolase SdsA1 -1.54 1.5E-03 PA14_54750 hypothetical protein 1.79 1.5E-05 PA0732 PA14_54810 hypothetical protein 1.84 2.9E-12 PA14_54850 hypothetical protein -1.53 2.2E-03 PA14_55000 ABC transporter periplasmic protein -1.52 1.1E-02 PA14_55040 ferric enterobactin transporter ATP-binding protein -1.55 3.2E-02 PA14_55060 hypothetical protein -1.79 3.2E-02 PA0709 PA14_55140 hypothetical protein 1.88 2.5E-02 PA0707 PA14_55160 toxR transcriptional regulator ToxR 5.47 2.4E-17 -4.44 5.8E-05 PA0699 PA14_55280 peptidyl-prolyl cis-trans isomerase, PpiC-type 1.56 2.6E-02 PA0698 PA14_55290 hypothetical protein 2.10 1.6E-02 PA0675 PA14_55550 vreI ECF subfamily RNA polymerase sigma-70 factor -2.57 8.4E-10 PA0674 PA14_55560 vreA VreA -1.74 2.0E-06 PA0672 PA14_55580 hemO heme oxygenase -2.82 9.8E-05 PA0671 PA14_55590 hypothetical protein -2.74 8.4E-06 PA0670 PA14_55600 hypothetical protein -1.78 2.3E-05 PA4290 PA14_55710 probable chemotaxis transducer 1.98 1.0E-04 PA4292 PA14_55760 probable phosphate transporter -1.57 2.6E-07 PA4293 PA14_55770 pprA two-component sensor PprA 2.54 8.6E-18 PA4294 PA14_55780 hypothetical protein 2.21 2.5E-17 PA4299 PA14_55820 tadD TadD 2.58 1.3E-19 PA4298 PA14_55840 hypothetical protein 2.43 2.9E-06 PA4300 PA14_55850 tadC TadC 2.67 2.7E-11 1.77 2.1E-02 PA4301 PA14_55860 tadB TadB 2.41 5.1E-17 PA4302 PA14_55880 tadA TadA ATPase 2.27 5.3E-14 PA4303 PA14_55890 tadZ TadZ 2.23 3.3E-13 PA4304 PA14_55900 rcpA RcpA 2.20 2.3E-13 PA4305 PA14_55920 rcpC RcpC 2.16 1.7E-14 PA4306 PA14_55930 flp Type IVb pilin, Flp 1.84 4.1E-25 PA4309 PA14_55980 pctA chemotactic transducer PctA -1.50 3.7E-16 PA4310 PA14_56000 pctB chemotactic transducer PctB -1.86 5.1E-25 PA4311 PA14_56010 conserved hypothetical protein 2.17 2.1E-21 PA4312 PA14_56030 conserved hypothetical protein 1.71 6.0E-22 PA4313 PA14_56040 hypothetical protein 1.70 3.1E-16 PA4316 PA14_56070 sbcB exodeoxyribonuclease I -1.51 2.6E-02 153 PA4328 PA14_56210 hypothetical protein 1.61 2.9E-06 PA4333 PA14_56280 probable fumarase -1.63 1.5E-25 PA4335 PA14_56340 hypothetical protein 2.18 1.3E-20 PA4336 PA14_56360 conserved hypothetical protein 1.93 3.5E-12 PA4338 PA14_56370 hypothetical protein 2.22 7.3E-20 PA4337 PA14_56380 hypothetical protein 2.04 2.4E-11 PA4344 PA14_56420 probable hydrolase 2.98 7.4E-41 PA4345 PA14_56480 hypothetical protein 3.30 3.0E-30 PA4346 PA14_56520 hypothetical protein 2.68 1.7E-12 PA4349 PA14_56540 hypothetical protein 1.89 3.1E-18 PA4352 PA14_56550 conserved hypothetical protein 2.05 6.1E-11 PA4355 PA14_56640 pyeM PyeM -1.55 1.6E-04 PA4357 PA14_56660 conserved hypothetical protein 1.68 1.1E-08 PA4360 PA14_56690 hypothetical protein -2.76 6.0E-04 PA4362 PA14_56720 hypothetical protein 1.50 3.0E-07 PA4366 PA14_56730 sodB superoxide dismutase 1.62 3.5E-02 PA4364 PA14_56750 hypothetical protein -4.36 1.1E-35 PA4365 PA14_56770 lysE Lysine efflux permease -4.66 1.9E-35 PA4370 PA14_56810 icmP Insulin-cleaving metalloproteinase outer membrane protein precursor 1.74 1.9E-10 PA4371 PA14_56830 hypothetical protein -1.75 1.2E-02 PA4385 PA14_56990 groEL GroEL protein -1.76 7.6E-04 PA4386 PA14_57010 groES GroES protein -2.19 2.5E-04 PA4388 PA14_57020 hypothetical protein 1.52 3.0E-02 PA4387 PA14_57030 conserved hypothetical protein -3.22 1.8E-51 PA4390 PA14_57050 hypothetical protein 1.86 1.3E-17 PA4396 PA14_57130 two-component response regulator 1.60 1.5E-17 PA4397 PA14_57140 panE ketopantoate reductase -1.52 9.8E-15 PA4398 PA14_57160 two-component sensor -1.78 1.2E-28 PA4409 PA14_57290 ftsQ cell division protein FtsQ -1.96 7.8E-03 PA4417 PA14_57390 murE UDP-N-acetylmuramoylalanyl-D-glutamate-2, 6-diaminopimelate ligase -1.54 4.5E-02 PA4430 PA14_57540 probable cytochrome b -1.55 1.3E-22 PA4431 PA14_57560 probable iron-sulfur protein -1.52 8.8E-23 PA4433 PA14_57580 rplM 50S ribosomal protein L13 -1.55 2.7E-18 PA4434 PA14_57590 probable oxidoreductase 1.61 2.2E-20 PA4442 PA14_57690 cysN ATP sulfurylase GTP-binding subunit/APS kinase -1.95 1.1E-16 PA4443 PA14_57710 cysD ATP sulfurylase small subunit -2.04 4.2E-23 PA4448 PA14_57770 hisD histidinol dehydrogenase -1.51 9.6E-13 154 PA4452 PA14_57820 conserved hypothetical protein -1.55 1.3E-02 PA4467 PA14_57980 hypothetical protein 1.72 1.6E-03 PA4468 PA14_57990 sodM superoxide dismutase 1.78 1.6E-02 -2.12 3.4E-02 PA4470 PA14_58000 fumC1 fumarate hydratase 1.66 1.8E-02 -2.48 3.4E-02 PA4469 PA14_58010 hypothetical protein 1.54 1.8E-02 PA4475 PA14_58070 conserved hypothetical protein -1.60 1.4E-18 PA4498 PA14_58360 mdpA metallo-dipeptidase aeruginosa, MdpA -1.92 9.8E-17 PA4499 PA14_58375 psdR Pseudomonas dipeptide regulator, PdsR -1.60 7.2E-10 PA4500 PA14_58380 dppA3 probable binding protein component of ABC transporter -1.50 1.7E-17 PA4501 PA14_58390 opdD Glycine-glutamate dipeptide porin OpdP -1.79 4.5E-25 PA4502 PA14_58410 dppA4 probable binding protein component of ABC transporter -1.73 9.6E-25 PA4503 PA14_58420 dppB dipeptide ABC transporter permease DppB -1.59 1.4E-23 PA4504 PA14_58440 dppC dipeptide ABC transporter permease DppC -1.67 2.1E-17 PA4505 PA14_58450 dppD dipeptide ABC transporter ATP-binding protein DppD -1.67 3.7E-12 PA4507 PA14_58490 hypothetical protein -2.07 3.2E-21 PA4511 PA14_58500 conserved hypothetical protein 2.11 1.4E-03 PA4508 PA14_58510 probable transcriptional regulator -1.57 7.7E-06 PA4519 PA14_58610 speC ornithine decarboxylase -2.16 3.2E-84 PA4518 PA14_58620 hypothetical protein -2.03 1.0E-19 PA4523 PA14_58670 hypothetical protein 1.56 2.2E-42 PA4542 PA14_58900 clpB ClpB protein -2.80 1.1E-22 PA14_59120 hypothetical protein 1.78 1.4E-03 PA14_59160 crpP CrpP 1.56 2.0E-02 PA14_59190 hypothetical protein 1.68 2.4E-09 PA0985 PA14_59220 pyoS5 pyocin S5 -2.88 2.6E-09 PA0984 PA14_59230 colicin immunity protein 2.48 2.7E-16 PA14_59240 pilL2 type IV B pilus protein -2.15 1.3E-05 PA14_59380 hypothetical protein -1.61 2.7E-02 PA14_59410 hypothetical protein 2.08 1.4E-03 PA14_59440 hypothetical protein -1.57 3.9E-02 PA14_59480 hypothetical protein -1.67 6.9E-04 PA14_59490 hypothetical protein -2.03 7.3E-03 PA14_59510 hypothetical protein -2.09 2.4E-02 PA14_59520 hypothetical protein -3.12 4.4E-04 155 PA14_59550 hypothetical protein -1.73 7.5E-09 -1.65 2.6E-02 PA14_59560 transposase -2.40 1.2E-09 PA14_59570 transposase -5.75 4.5E-12 PA14_59770 rcsB two component response regulator 1.67 7.1E-09 PA14_59840 hypothetical protein -2.50 4.1E-02 PA14_59845 hypothetical protein -3.33 4.7E-02 PA14_60040 hypothetical protein -1.75 3.9E-02 PA1935 PA14_60080 hypothetical protein 1.52 2.1E-18 PA14_60090 hypothetical protein -1.52 2.1E-02 PA14_60140 xerD-like integrase -1.60 5.5E-07 PA4552 PA14_60280 pilW type 4 fimbrial biogenesis protein PilW 1.59 8.9E-17 PA4556 PA14_60310 pilE type 4 fimbrial biogenesis protein PilE -1.89 1.7E-02 PA4557 PA14_60320 lytB LytB protein -1.98 1.4E-02 PA4563 PA14_60390 rpsT 30S ribosomal protein S20 -1.65 9.8E-17 PA4566 PA14_60420 obg GTP-binding protein Obg -1.69 5.1E-11 PA4569 PA14_60460 ispB octaprenyl-diphosphate synthase -1.56 4.0E-02 PA4572 PA14_60490 fklB peptidyl-prolyl cis-trans isomerase FklB -2.33 1.1E-47 PA4577 PA14_60560 hypothetical protein 1.58 4.0E-04 PA4582 PA14_60630 conserved hypothetical protein -1.79 1.2E-07 PA4602 PA14_60870 glyA3 serine hydroxymethyltransferase -2.04 3.1E-33 PA4607 PA14_60950 hypothetical protein 1.90 3.4E-06 PA4610 PA14_61000 hypothetical protein -1.59 2.9E-03 PA4612 PA14_61020 conserved hypothetical protein -3.58 1.4E-14 PA4613 PA14_61040 katB catalase -6.37 2.2E-29 PA4624 PA14_61150 cdrB cyclic diguanylate-regulated TPS partner B, CdrB -1.98 1.9E-24 PA4623 PA14_61180 -1.71 3.8E-03 PA4625 PA14_61190 cdrA cyclic diguanylate-regulated TPS partner A, CdrA -2.22 4.9E-24 PA4628 PA14_61220 lysP lysine-specific permease -1.71 1.5E-16 PA4629 PA14_61250 hypothetical protein -1.79 3.3E-09 PA4630 PA14_61270 hypothetical protein -1.72 3.5E-06 PA4633 PA14_61290 probable chemotaxis transducer -1.65 1.3E-22 PA4635 PA14_61330 conserved hypothetical protein -4.66 1.6E-22 PA14_61340 hypothetical protein 1.63 1.2E-04 PA14_61380 hypothetical protein -1.97 1.3E-02 PA4644 PA14_61440 hypothetical protein -1.86 1.1E-16 PA4645 PA14_61450 probable purine/pyrimidine -1.77 1.8E-25 156 phosphoribosyl transferase PA4646 PA14_61460 upp uracil phosphoribosyltransferase -1.52 2.4E-12 PA4654 PA14_61560 probable major facilitator superfamily (MFS) transporter -2.11 4.0E-10 PA4658 PA14_61600 hypothetical protein -1.69 2.4E-08 PA4660 PA14_61610 phr deoxyribodipyrimidine photolyase -2.00 1.0E-11 PA4659 PA14_61620 probable transcriptional regulator -1.91 2.0E-11 PA4661 PA14_61640 pagL Lipid A 3-O-deacylase 2.26 3.7E-22 PA4670 PA14_61750 prs ribose-phosphate pyrophosphokinase -1.72 2.1E-05 PA4671 PA14_61770 probable ribosomal protein L25 -1.64 3.0E-31 PA4672 PA14_61780 peptidyl-tRNA hydrolase -1.51 3.3E-10 PA4673 PA14_61790 conserved hypothetical protein -1.52 3.4E-16 PA14_61845 higB HigB -2.32 1.5E-02 PA4680 PA14_61910 hypothetical protein 1.65 1.7E-02 PA4688 PA14_62000 hitB iron (III)-transport system permease HitB 1.56 4.0E-12 PA4689 PA14_62010 hypothetical protein -1.51 4.7E-17 PA4692 PA14_62020 conserved hypothetical protein -1.93 4.8E-18 PA14_62030 paraquat-inducible protein A-like protein -1.52 3.5E-12 PA4691 PA14_62100 hypothetical protein -1.86 1.1E-10 PA4714 PA14_62350 conserved hypothetical protein -2.08 6.3E-30 PA4719 PA14_62420 probable transporter -1.67 3.2E-16 PA4720 PA14_62440 trmA tRNA (uracil-5-)-methyltransferase -1.54 8.0E-11 PA4731 PA14_62590 panD aspartate 1-decarboxylase precursor -2.08 2.3E-46 PA4738 PA14_62670 conserved hypothetical protein 2.46 1.4E-16 PA4739 PA14_62680 conserved hypothetical protein 2.34 1.0E-12 PA4740 PA14_62690 pnp polyribonucleotide nucleotidyltransferase -1.91 2.0E-17 PA4743 PA14_62730 rbfA ribosome-binding factor A -1.93 3.2E-17 PA4744 PA14_62740 infB translation initiation factor IF-2 -1.79 1.1E-18 PA4745 PA14_62760 nusA N utilization substance protein A -1.85 5.2E-18 PA4746 PA14_62770 conserved hypothetical protein -1.61 1.0E-08 PA4752 PA14_62860 ftsJ cell division protein FtsJ -1.56 7.4E-12 PA4753 PA14_62870 conserved hypothetical protein -1.56 1.1E-10 PA4757 PA14_62910 conserved hypothetical protein -1.55 1.3E-08
UBC Theses and Dissertations
Swarming motility in Pseudomonas aeruginosa : a complex adaptation with implications for antibiotic resistance… Coleman, Shannon 2020
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