1887

Microbial Genomics logo

Volume 10, Issue 2

Comparative genomics reveals distinct diversification patterns among LysR-type transcriptional regulators in the ESKAPE pathogen Open Access

Abstract

, a harmful nosocomial pathogen associated with cystic fibrosis and burn wounds, encodes for a large number of LysR-type transcriptional regulator proteins. To understand how and why LTTR proteins evolved with such frequency and to establish whether any relationships exist within the distribution we set out to identify the patterns underpinning LTTR distribution in and to uncover cluster-based relationships within the pangenome. Comparative genomic studies revealed that in the JGI IMG database alone ~86 000 LTTRs are present across the sequenced genomes (=699). They are widely distributed across the species, with core LTTRs present in >93 % of the genomes and accessory LTTRs present in <7 %. Analysis showed that subsets of core LTTRs can be classified as either variable (typically specific to ) or conserved (and found to be distributed in other species). Extending the analysis to the more extensive Pseudomonas database, PA14 rooted analysis confirmed the diversification patterns and revealed PqsR, the receptor for the Pseudomonas quinolone signal (PQS) and 2-heptyl-4-quinolone (HHQ) quorum-sensing signals, to be amongst the most variable in the dataset. Successful complementation of the PAO1 mutant using representative variant sequences suggests a degree of structural promiscuity within the most variable of LTTRs, several of which play a prominent role in signalling and communication. These findings provide a new insight into the diversification of LTTR proteins within the species and suggests a functional significance to the cluster, conservation and distribution patterns identified.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): antimicrobial resistance , evolution , LysR-type transcriptional regulator (LTTR) , oxidative stress , PqsR (MvfR) and Pseudomonas aeruginosa
Funding
This study was supported by the:
  • Health Research Board (Award MRCG-2018-16)
    • Principle Award Recipient: F.Jerry Reen
  • Health Research Board (Award HRB-ILP-POR-2019-004)
    • Principle Award Recipient: F.Jerry Reen
  • Science Foundation Ireland (Award 12/RC/2275_2)
    • Principle Award Recipient: F.Jerry Reen
  • Irish Research Council for Science, Engineering and Technology (Award GOIPG/2021/692)
    • Principle Award Recipient: MuireannCarmody
© 2024 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.001205
2024-02-29
2024-04-28
Loading full text...

Full text loading...

/deliver/fulltext/mgen/10/2/mgen001205.html?itemId=/content/journal/mgen/10.1099/mgen.0.001205&mimeType=html&fmt=ahah

References

  1. Bervoets I, Charlier D. Diversity, versatility and complexity of bacterial gene regulation mechanisms: opportunities and drawbacks for applications in synthetic biology. FEMS Microbiol Rev 2019; 43:304–339 [View Article] [PubMed]
     [Google Scholar]
  2. Maddocks SE, Oyston PCF. Structure and function of the LysR-type transcriptional regulator (LTTR) family proteins. Microbiology 2008; 154:3609–3623 [View Article]
     [Google Scholar]
  3. Perez-Rueda E, Hernandez-Guerrero R, Martinez-Nuñez MA, Armenta-Medina D, Sanchez I et al. Abundance, diversity and domain architecture variability in prokaryotic DNA-binding transcription factors. PLoS One 2018; 13:e0195332 [View Article] [PubMed]
     [Google Scholar]
  4. Henikoff S, Haughn GW, Calvo JM, Wallace JC. A large family of bacterial activator proteins. Proc Natl Acad Sci U S A 1988; 85:6602–6606 [View Article] [PubMed]
     [Google Scholar]
  5. Reen FJ, Barret M, Fargier E, O’Muinneacháin M, O’Gara F. Molecular evolution of LysR-type transcriptional regulation in Pseudomonas aeruginosa. Mol Phylogenet Evol 2013; 66:1041–1049 [View Article] [PubMed]
     [Google Scholar]
  6. Wang T, Sun W, Fan L, Hua C, Wu N et al. An atlas of the binding specificities of transcription factors in Pseudomonas aeruginosa directs prediction of novel regulators in virulence. Elife 2021; 10:e61885 [View Article] [PubMed]
     [Google Scholar]
  7. Balasubramanian D, Kumari H, Mathee K. Pseudomonas aeruginosa AmpR: an acute-chronic switch regulator. Pathog Dis 2015; 73:1–14 [View Article] [PubMed]
     [Google Scholar]
  8. Brouwer S, Pustelny C, Ritter C, Klinkert B, Narberhaus F et al. The PqsR and RhlR transcriptional regulators determine the level of Pseudomonas quinolone signal synthesis in Pseudomonas aeruginosa by producing two different pqsABCDE mRNA isoforms. J Bacteriol 2014; 196:4163–4171 [View Article] [PubMed]
     [Google Scholar]
  9. Jin Y, Yang H, Qiao M, Jin S. MexT regulates the type III secretion system through MexS and PtrC in Pseudomonas aeruginosa. J Bacteriol 2011; 193:399–410 [View Article] [PubMed]
     [Google Scholar]
  10. McCarthy RR, Mooij MJ, Reen FJ, Lesouhaitier O, O’Gara F. A new regulator of pathogenicity (bvlR) is required for full virulence and tight microcolony formation in Pseudomonas aeruginosa. Microbiology 2014; 160:1488–1500 [View Article] [PubMed]
     [Google Scholar]
  11. Wei Q, Minh PNL, Dötsch A, Hildebrand F, Panmanee W et al. Global regulation of gene expression by OxyR in an important human opportunistic pathogen. Nucleic Acids Res 2012; 40:4320–4333 [View Article] [PubMed]
     [Google Scholar]
  12. Klockgether J, Cramer N, Fischer S, Wiehlmann L, Tümmler B. Long-term microevolution of Pseudomonas aeruginosa differs between mildly and severely affected cystic fibrosis lungs. Am J Respir Cell Mol Biol 2018; 59:246–256 [View Article] [PubMed]
     [Google Scholar]
  13. Marvig RL, Sommer LM, Molin S, Johansen HK. Convergent evolution and adaptation of Pseudomonas aeruginosa within patients with cystic fibrosis. Nat Genet 2015; 47:57–64 [View Article] [PubMed]
     [Google Scholar]
  14. Andersson DI, Hughes D. Gene amplification and adaptive evolution in bacteria. Annu Rev Genet 2009; 43:167–195 [View Article] [PubMed]
     [Google Scholar]
  15. Madan Babu M, Teichmann SA, Aravind L. Evolutionary dynamics of prokaryotic transcriptional regulatory networks. J Mol Biol 2006; 358:614–633 [View Article] [PubMed]
     [Google Scholar]
  16. Déziel E, Gopalan S, Tampakaki AP, Lépine F, Padfield KE et al. The contribution of MvfR to Pseudomonas aeruginosa pathogenesis and quorum sensing circuitry regulation: multiple quorum sensing-regulated genes are modulated without affecting lasRI, rhlRI or the production of N-acyl-L-homoserine lactones. Mol Microbiol 2005; 55:998–1014 [View Article] [PubMed]
     [Google Scholar]
  17. Gallagher LA, McKnight SL, Kuznetsova MS, Pesci EC, Manoil C. Functions required for extracellular quinolone signaling by Pseudomonas aeruginosa. J Bacteriol 2002; 184:6472–6480 [View Article] [PubMed]
     [Google Scholar]
  18. Ó Muimhneacháin E, Reen FJ, O’Gara F, McGlacken GP. Analogues of Pseudomonas aeruginosa signalling molecules to tackle infections. Org Biomol Chem 2018; 16:169–179 [View Article] [PubMed]
     [Google Scholar]
  19. Viale AM, Kobayashi H, Akazawa T, Henikoff S. rbcR [correction of rcbR], a gene coding for a member of the LysR family of transcriptional regulators, is located upstream of the expressed set of ribulose 1,5-bisphosphate carboxylase/oxygenase genes in the photosynthetic bacterium Chromatium vinosum. J Bacteriol 1991; 173:5224–5229 [View Article] [PubMed]
     [Google Scholar]
  20. Chen I-MA, Chu K, Palaniappan K, Pillay M, Ratner A et al. IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes. Nucleic Acids Res 2019; 47:D666–D677 [View Article] [PubMed]
     [Google Scholar]
  21. Field D, Tiwari B, Booth T, Houten S, Swan D et al. Open software for biologists: from famine to feast. Nat Biotechnol 2006; 24:801–803 [View Article] [PubMed]
     [Google Scholar]
  22. Fu L, Niu B, Zhu Z, Wu S, Li W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 2012; 28:3150–3152 [View Article] [PubMed]
     [Google Scholar]
  23. Li W, Godzik A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 2006; 22:1658–1659 [View Article] [PubMed]
     [Google Scholar]
  24. Zaslavsky L, Ciufo S, Fedorov B, Tatusova T. Clustering analysis of proteins from microbial genomes at multiple levels of resolution. BMC Bioinformatics 2016; 17 Suppl 8:276 [View Article] [PubMed]
     [Google Scholar]
  25. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 2004; 32:1792–1797 [View Article] [PubMed]
     [Google Scholar]
  26. Kishino H, Miyata T, Hasegawa M. Maximum likelihood inference of protein phylogeny and the origin of chloroplasts. J Mol Evol 1990; 31:151–160 [View Article]
     [Google Scholar]
  27. Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 2010; 59:307–321 [View Article] [PubMed]
     [Google Scholar]
  28. Whelan S, Goldman N. A general empirical model of protein evolution derived from multiple protein families using a maximum-likelihood approach. Mol Biol Evol 2001; 18:691–699 [View Article] [PubMed]
     [Google Scholar]
  29. Anisimova M, Gascuel O. Approximate likelihood-ratio test for branches: a fast, accurate, and powerful alternative. Syst Biol 2006; 55:539–552 [View Article] [PubMed]
     [Google Scholar]
  30. Letunic I, Bork P. Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res 2019; 47:W256–W259 [View Article] [PubMed]
     [Google Scholar]
  31. R-Core-Team R: A Language and Environment for Statistical Computing Vienna, Austria: R Foundation for Statistical Computing; 2019
     [Google Scholar]
  32. R-Studio-Team RStudio: Integrated Development Environment for R 2016
     [Google Scholar]
  33. Wickham H, Francois R, Henry L, Muller K. dplyr: a grammar of data manipulation; 2019
  34. Wickham H. ggplot2: Elegant Graphics for Data Analysis Cham: Springer-Verlag New York; 2016 [View Article]
     [Google Scholar]
  35. Wickham H. tidyverse: easily install and load the “Tidyverse”; 2017
  36. Egea R, Casillas S, Barbadilla A. Standard and generalized McDonald-Kreitman test: a website to detect selection by comparing different classes of DNA sites. Nucleic Acids Res 2008; 36:W157–62 [View Article] [PubMed]
     [Google Scholar]
  37. Lu S, Tian Q, Zhao W, Hu B. Evaluation of the potential of five housekeeping genes for identification of quarantine Pseudomonas syringae. J Phytopathol 2017; 165:73–81 [View Article]
     [Google Scholar]
  38. Winsor GL, Griffiths EJ, Lo R, Dhillon BK, Shay JA et al. Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database. Nucleic Acids Res 2016; 44:D646–53 [View Article] [PubMed]
     [Google Scholar]
  39. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990; 215:403–410 [View Article] [PubMed]
     [Google Scholar]
  40. Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods 2015; 12:59–60 [View Article] [PubMed]
     [Google Scholar]
  41. Gallagher LA, Manoil C. Pseudomonas aeruginosa PAO1 kills Caenorhabditis elegans by cyanide poisoning. J Bacteriol 2001; 183:6207–6214 [View Article] [PubMed]
     [Google Scholar]
  42. Fletcher MP, Diggle SP, Crusz SA, Chhabra SR, Cámara M et al. A dual biosensor for 2-alkyl-4-quinolone quorum-sensing signal molecules. Environ Microbiol 2007; 9:2683–2693 [View Article] [PubMed]
     [Google Scholar]
  43. Essar DW, Eberly L, Hadero A, Crawford IP. Identification and characterization of genes for a second anthranilate synthase in Pseudomonas aeruginosa: interchangeability of the two anthranilate synthases and evolutionary implications. J Bacteriol 1990; 172:884–900 [View Article] [PubMed]
     [Google Scholar]
  44. Tian Z-X, Fargier E, Mac Aogáin M, Adams C, Wang Y-P et al. Transcriptome profiling defines a novel regulon modulated by the LysR-type transcriptional regulator MexT in Pseudomonas aeruginosa. Nucleic Acids Res 2009; 37:7546–7559 [View Article] [PubMed]
     [Google Scholar]
  45. He W, Li G, Yang CK, Lu CD. Functional characterization of the dguRABC locus for D-Glu and D-Gln utilization in Pseudomonas aeruginosa PAO1. Microbiology 2014; 160:2331–2340 [View Article] [PubMed]
     [Google Scholar]
  46. Fujii T, Aritoku Y, Agematu H, Tsunekawa H. Increase in the rate of L-pipecolic acid production using lat-expressing Escherichia coli by lysP and yeiE amplification. Biosci Biotechnol Biochem 2002; 66:1981–1984 [View Article] [PubMed]
     [Google Scholar]
  47. Parke D. Characterization of PcaQ, a LysR-type transcriptional activator required for catabolism of phenolic compounds, from Agrobacterium tumefaciens. J Bacteriol 1996; 178:266–272 [View Article] [PubMed]
     [Google Scholar]
  48. Reen FJ, Haynes JM, Mooij MJ, O’Gara F. A non-classical LysR-type transcriptional regulator PA2206 is required for an effective oxidative stress response in Pseudomonas aeruginosa. PLoS One 2013; 8:e54479 [View Article] [PubMed]
     [Google Scholar]
  49. Modrzejewska M, Kawalek A, Bartosik AA. The LysR-type transcriptional regulator BsrA (PA2121) controls vital metabolic pathways in Pseudomonas aeruginosa. mSystems 2021; 6:e0001521 [View Article] [PubMed]
     [Google Scholar]
  50. Yang X, Zhang Z, Huang Z, Zhang X, Li D et al. A putative LysR-type transcriptional regulator inhibits biofilm synthesis in Pseudomonas aeruginosa. Biofouling 2019; 35:541–550 [View Article] [PubMed]
     [Google Scholar]
  51. Kukavica-Ibrulj I, Sanschagrin F, Peterson A, Whiteley M, Boyle B et al. Functional genomics of PycR, a LysR family transcriptional regulator essential for maintenance of Pseudomonas aeruginosa in the rat lung. Microbiology 2008; 154:2106–2118 [View Article] [PubMed]
     [Google Scholar]
  52. Yeung ATY, Torfs ECW, Jamshidi F, Bains M, Wiegand I et al. Swarming of Pseudomonas aeruginosa is controlled by a broad spectrum of transcriptional regulators, including MetR. J Bacteriol 2009; 191:5592–5602 [View Article] [PubMed]
     [Google Scholar]
  53. Maxon ME, Redfield B, Cai XY, Shoeman R, Fujita K et al. Regulation of methionine synthesis in Escherichia coli: effect of the MetR protein on the expression of the metE and metR genes. Proc Natl Acad Sci U S A 1989; 86:85–89 [View Article] [PubMed]
     [Google Scholar]
  54. Yao X, He W, Lu CD. Functional characterization of seven γ-Glutamylpolyamine synthetase genes and the bauRABCD locus for polyamine and β-Alanine utilization in Pseudomonas aeruginosa PAO1. J Bacteriol 2011; 193:3923–3930 [View Article] [PubMed]
     [Google Scholar]
  55. Delic-Attree I, Toussaint B, Garin J, Vignais PM. Cloning, sequence and mutagenesis of the structural gene of Pseudomonas aeruginosa CysB, which can activate algD transcription. Mol Microbiol 1997; 24:1275–1284 [View Article] [PubMed]
     [Google Scholar]
  56. Sung YC, Fuchs JA. The Escherichia coli K-12 cyn operon is positively regulated by a member of the lysR family. J Bacteriol 1992; 174:3645–3650 [View Article] [PubMed]
     [Google Scholar]
  57. Rothmel RK, Aldrich TL, Houghton JE, Coco WM, Ornston LN et al. Nucleotide sequencing and characterization of Pseudomonas putida catR: a positive regulator of the catBC operon is a member of the LysR family. J Bacteriol 1990; 172:922–931 [View Article] [PubMed]
     [Google Scholar]
  58. Frädrich C, March A, Fiege K, Hartmann A, Jahn D et al. The transcription factor AlsR binds and regulates the promoter of the alsSD operon responsible for acetoin formation in Bacillus subtilis. J Bacteriol 2012; 194:1100–1112 [View Article] [PubMed]
     [Google Scholar]
  59. Wargo MJ, Hogan DA. Identification of genes required for Pseudomonas aeruginosa carnitine catabolism. Microbiology 2009; 155:2411–2419 [View Article]
     [Google Scholar]
  60. Nakada Y, Itoh Y. Characterization and regulation of the gbuA gene, encoding guanidinobutyrase in the arginine dehydrogenase pathway of Pseudomonas aeruginosa PAO1. J Bacteriol 2002; 184:3377–3384 [View Article] [PubMed]
     [Google Scholar]
  61. Vercammen K, Wei Q, Charlier D, Dötsch A, Haüssler S et al. Pseudomonas aeruginosa LysR PA4203 regulator NmoR acts as a repressor of the PA4202 nmoA gene, encoding a nitronate monooxygenase. J Bacteriol 2015; 197:1026–1039 [View Article] [PubMed]
     [Google Scholar]
  62. Hall CW, Zhang L, Mah TF. PA3225 is a transcriptional repressor of antibiotic resistance mechanisms in Pseudomonas aeruginosa. Antimicrob Agents Chemother 2017; 61:e02114-16 [View Article] [PubMed]
     [Google Scholar]
  63. Heacock-Kang Y, Zarzycki-Siek J, Sun Z, Poonsuk K, Bluhm AP et al. Novel dual regulators of Pseudomonas aeruginosa essential for productive biofilms and virulence. Mol Microbiol 2018; 109:401–414 [View Article] [PubMed]
     [Google Scholar]
  64. Cao P, Fleming D, Moustafa DA, Dolan SK, Szymanik KH et al. A Pseudomonas aeruginosa small RNA regulates chronic and acute infection. Nature 2023; 618:358–364 [View Article] [PubMed]
     [Google Scholar]
  65. Hoenke S, Schmid M, Dimroth P. Sequence of a gene cluster from Klebsiella pneumoniae encoding malonate decarboxylase and expression of the enzyme in Escherichia coli. Eur J Biochem 1997; 246:530–538 [View Article] [PubMed]
     [Google Scholar]
  66. Martínez E, Cosnahan RK, Wu M, Gadila SK, Quick EB et al. Oxylipins mediate cell-to-cell communication in Pseudomonas aeruginosa. Commun Biol 2019; 2:66 [View Article] [PubMed]
     [Google Scholar]
  67. Caille O, Zincke D, Merighi M, Balasubramanian D, Kumari H et al. Structural and functional characterization of Pseudomonas aeruginosa global regulator AmpR. J Bacteriol 2014; 196:3890–3902 [View Article] [PubMed]
     [Google Scholar]
  68. Chang M, Hadero A, Crawford IP. Sequence of the Pseudomonas aeruginosa trpI activator gene and relatedness of trpI to other procaryotic regulatory genes. J Bacteriol 1989; 171:172–183 [View Article] [PubMed]
     [Google Scholar]
  69. Marbaniang CN, Gowrishankar J. Role of ArgP (IciA) in lysine-mediated repression in Escherichia coli. J Bacteriol 2011; 193:5985–5996 [View Article] [PubMed]
     [Google Scholar]
  70. Thöny B, Hwang DS, Fradkin L, Kornberg A. iciA, an Escherichia coli gene encoding a specific inhibitor of chromosomal initiation of replication in vitro. Proc Natl Acad Sci U S A 1991; 88:4066–4070 [View Article] [PubMed]
     [Google Scholar]
  71. Turner KH, Vallet-Gely I, Dove SL. Epigenetic control of virulence gene expression in Pseudomonas aeruginosa by a LysR-type transcription regulator. PLoS Genet 2009; 5:e1000779 [View Article] [PubMed]
     [Google Scholar]
  72. Willsey GG, Wargo MJ. Sarcosine catabolism in Pseudomonas aeruginosa is transcriptionally regulated by SouR. J Bacteriol 2016; 198:301–310 [View Article] [PubMed]
     [Google Scholar]
  73. Hamood AN, Colmer JA, Ochsner UA, Vasil ML. Isolation and characterization of a Pseudomonas aeruginosa gene, ptxR, which positively regulates exotoxin A production. Mol Microbiol 1996; 21:97–110 [View Article] [PubMed]
     [Google Scholar]
  74. Haegeman B, Weitz JS. A neutral theory of genome evolution and the frequency distribution of genes. BMC Genomics 2012; 13:196 [View Article] [PubMed]
     [Google Scholar]
  75. Mathee K, Narasimhan G, Valdes C, Qiu X, Matewish JM et al. Dynamics of Pseudomonas aeruginosa genome evolution. Proc Natl Acad Sci U S A 2008; 105:3100–3105 [View Article] [PubMed]
     [Google Scholar]
  76. Subedi D, Vijay AK, Kohli GS, Rice SA, Willcox M. Comparative genomics of clinical strains of Pseudomonas aeruginosa strains isolated from different geographic sites. Sci Rep 2018; 8:15668 [View Article] [PubMed]
     [Google Scholar]
  77. Stover CK, Pham XQ, Erwin AL, Mizoguchi SD, Warrener P et al. Complete genome sequence of Pseudomonas aeruginosa PAO1, an opportunistic pathogen. Nature 2000; 406:959–964 [View Article] [PubMed]
     [Google Scholar]
  78. Scanlan PD, Hall AR, Blackshields G, Friman V-P, Davis MR Jr et al. Coevolution with bacteriophages drives genome-wide host evolution and constrains the acquisition of abiotic-beneficial mutations. Mol Biol Evol 2015; 32:1425–1435 [View Article] [PubMed]
     [Google Scholar]
  79. Valverde C, Heeb S, Keel C, Haas D. RsmY, a small regulatory RNA, is required in concert with RsmZ for GacA-dependent expression of biocontrol traits in Pseudomonas fluorescens CHA0. Mol Microbiol 2003; 50:1361–1379 [View Article] [PubMed]
     [Google Scholar]
  80. Qin S, Xiao W, Zhou C, Pu Q, Deng X et al. Pseudomonas aeruginosa: pathogenesis, virulence factors, antibiotic resistance, interaction with host, technology advances and emerging therapeutics. Signal Transduct Target Ther 2022; 7:199 [View Article] [PubMed]
     [Google Scholar]
  81. Liberati NT, Urbach JM, Miyata S, Lee DG, Drenkard E et al. An ordered, nonredundant library of Pseudomonas aeruginosa strain PA14 transposon insertion mutants. Proc Natl Acad Sci U S A 2006; 103:2833–2838 [View Article] [PubMed]
     [Google Scholar]
  82. Schütz C, Empting M. Targeting the Pseudomonas quinolone signal quorum sensing system for the discovery of novel anti-infective pathoblockers. Beilstein J Org Chem 2018; 14:2627–2645 [View Article] [PubMed]
     [Google Scholar]
  83. Lee DG, Urbach JM, Wu G, Liberati NT, Feinbaum RL et al. Genomic analysis reveals that Pseudomonas aeruginosa virulence is combinatorial. Genome Biol 2006; 7:10 [View Article] [PubMed]
     [Google Scholar]
  84. Mikkelsen H, McMullan R, Filloux A. The Pseudomonas aeruginosa reference strain PA14 displays increased virulence due to a mutation in ladS. PLoS One 2011; 6:e29113 [View Article] [PubMed]
     [Google Scholar]
  85. WHO Carbapenem-resistant Pseudomonas aeruginosa Infection - Mexico 2019
     [Google Scholar]
  86. WHO publishes list of bacteria for which new antibiotics are urgently needed. https://www.who.int/news/item/27-02-2017-who-publishes-list-of-bacteria-for-which-new-antibiotics-are-urgently-needed
  87. Rivas-Marín E, Floriano B, Santero E. Genetic dissection of independent and cooperative transcriptional activation by the LysR-type activator ThnR at close divergent promoters. Sci Rep 2016; 6:24538 [View Article] [PubMed]
     [Google Scholar]
  88. Smith P, Schuster M. Antiactivators prevent self-sensing in Pseudomonas aeruginosa quorum sensing. Proc Natl Acad Sci U S A 2022; 119:e2201242119 [View Article] [PubMed]
     [Google Scholar]
  89. Venturi V, Ahmer BMM. Editorial: LuxR solos are becoming major players in cell-cell communication in bacteria. Front Cell Infect Microbiol 2015; 5:89 [View Article] [PubMed]
     [Google Scholar]
  90. Knapp GS, Hu JC. Specificity of the E. coli LysR-type transcriptional regulators. PLoS One 2010; 5:e15189 [View Article] [PubMed]
     [Google Scholar]
  91. Gómez-Martínez J, Rocha-Gracia RDC, Bello-López E, Cevallos MA, Castañeda-Lucio M et al. Comparative genomics of Pseudomonas aeruginosa strains isolated from different ecological niches. Antibiotics 2023; 12:866 [View Article] [PubMed]
     [Google Scholar]
  92. Koehorst JJ, van Dam JCJ, van Heck RGA, Saccenti E, Dos Santos VAPM et al. Comparison of 432 Pseudomonas strains through integration of genomic, functional, metabolic and expression data. Sci Rep 2016; 6:38699 [View Article] [PubMed]
     [Google Scholar]
  93. Bohlin J, Eldholm V, Pettersson JHO, Brynildsrud O, Snipen L. The nucleotide composition of microbial genomes indicates differential patterns of selection on core and accessory genomes. BMC Genomics 2017; 18:151 [View Article] [PubMed]
     [Google Scholar]
  94. Booker TR, Jackson BC, Keightley PD. Detecting positive selection in the genome. BMC Biol 2017; 15:98 [View Article] [PubMed]
     [Google Scholar]
  95. Charlesworth J, Eyre-Walker A. The McDonald-Kreitman test and slightly deleterious mutations. Mol Biol Evol 2008; 25:1007–1015 [View Article] [PubMed]
     [Google Scholar]
  96. Messer PW, Petrov DA. Frequent adaptation and the McDonald-Kreitman test. Proc Natl Acad Sci U S A 2013; 110:8615–8620 [View Article] [PubMed]
     [Google Scholar]
  97. Tsoy OV, Pyatnitskiy MA, Kazanov MD, Gelfand MS. Evolution of transcriptional regulation in closely related bacteria. BMC Evol Biol 2012; 12:200 [View Article] [PubMed]
     [Google Scholar]
  98. Liu H, Zhang J. Testing the adaptive hypothesis of lagging-strand encoding in bacterial genomes. Nat Commun 2022; 13:2628 [View Article]
     [Google Scholar]
  99. Merrikh H, Merrikh C. Reply to: testing the adaptive hypothesis of lagging-strand encoding in bacterial genomes. Nat Commun 2022; 13:2627 [View Article] [PubMed]
     [Google Scholar]
  100. Egan F, Reen FJ, O’Gara F. Tle distribution and diversity in metagenomic datasets reveal niche specialization. Environ Microbiol Rep 2015; 7:194–203 [View Article] [PubMed]
     [Google Scholar]
  101. Fondi M, Karkman A, Tamminen MV, Bosi E, Virta M et al. “Every gene is everywhere but the environment selects”: global geolocalization of gene sharing in environmental samples through network analysis. Genome Biol Evol 2016; 8:1388–1400 [View Article] [PubMed]
     [Google Scholar]
  102. Beavan AJS, Domingo-Sananes MR, McInerney JO. Contingency, repeatability, and predictability in the evolution of a prokaryotic pangenome. Proc Natl Acad Sci U S A 2024; 121:e2304934120 [View Article] [PubMed]
     [Google Scholar]
  103. McInerney JO. Prokaryotic pangenomes act as evolving ecosystems. Mol Biol Evol 2023; 40:msac232 [View Article] [PubMed]
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.001205
Loading
Comparative genomics reveals distinct diversification patterns among LysR-type transcriptional regulators in the ESKAPE pathogen Pseudomonas aeruginosa
M Gen 10, 001205 (2024); https://doi.org/10.1099/mgen.0.001205
/content/journal/mgen/10.1099/mgen.0.001205
/content/journal/mgen/10.1099/mgen.0.001205
Loading

Data & Media loading...

Supplements

Supplementary material 1

EXCEL

Supplementary material 2

PDF

Most cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error