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Volume 69, Issue 2

There is no hiding if you Seq: recent breakthroughs in research revealed by genomic and transcriptomic next-generation sequencing Free

Abstract

The advent of next-generation sequencing technology has revolutionized the field of prokaryotic genetics and genomics by allowing interrogation of entire genomes, transcriptomes and global transcription factor binding profiles. As more studies employing these techniques have been performed, the state of the art regarding prokaryotic gene regulation has developed from the level of individual genes to genetic regulatory networks and systems biology. When applied to bacterial pathogens, particularly valuable insights have been gained into the regulation of virulence-associated genes, their relative importance to bacterial survival in planktonic, biofilm or host infection scenarios, antimicrobial resistance and the molecular details of host–pathogen interactions. This review outlines some of the latest developments and applications of next-generation sequencing techniques that have used primarily as a model system. We focus particularly on insights into virulence and infection that have been gained from these approaches and the future directions in which this field could develop.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): ChIP-Seq , host–pathogen interaction , next-generation sequencing , Pseudomonas , RNA-Seq and transposon insertion sequencing
Funding
This study was supported by the:
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Award PMPDP3_158295)
    • Principle Award Recipient: Clare Louise Kirkpatrick
© 2020 The Authors
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2020-01-14
2024-04-26
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References

  1. Richmond CS, Glasner JD, Mau R, Jin H, Blattner FR. Genome-Wide expression profiling in Escherichia coli K-12. Nucleic Acids Res 1999; 27:3821–3835 [View Article]
     [Google Scholar]
  2. Tao H, Bausch C, Richmond C, Blattner FR, Conway T. Functional genomics: expression analysis of Escherichia coli growing on minimal and rich media. J Bacteriol 1999; 181:6425–6440
     [Google Scholar]
  3. Loman NJ, Pallen MJ. Twenty years of bacterial genome sequencing. Nat Rev Microbiol 2015; 13:787794 [View Article]
     [Google Scholar]
  4. Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 2009; 10:57–63 [View Article]
     [Google Scholar]
  5. Park PJ. Chip-Seq: advantages and challenges of a maturing technology. Nat Rev Genet 2009; 10:669680 [View Article]
     [Google Scholar]
  6. Myers KS, Park DM, Beauchene NA, Kiley PJ. Defining bacterial regulons using ChIP-Seq. Methods 2015; 86:80–88 [View Article]
     [Google Scholar]
  7. van Opijnen T, Camilli A. Transposon insertion sequencing: a new tool for systems-level analysis of microorganisms. Nat Rev Microbiol 2013; 11:435442 [View Article]
     [Google Scholar]
  8. Pfeilmeier S, Caly DL, Malone JG. Bacterial pathogenesis of plants: future challenges from a microbial perspective. Mol Plant Pathol 2016; 17:1298–1313 [View Article]
     [Google Scholar]
  9. Rybtke M, Hultqvist LD, Givskov M, Tolker-Nielsen T. Pseudomonas aeruginosa biofilm infections: community structure, antimicrobial tolerance and immune response. J Mol Biol 2015; 427:3628–3645 [View Article]
     [Google Scholar]
  10. Dötsch A, Eckweiler D, Schniederjans M, Zimmermann A, Jensen V et al. The Pseudomonas aeruginosa transcriptome in planktonic cultures and static biofilms using RNA sequencing. PLoS One 2012; 7:e31092 [View Article]
     [Google Scholar]
  11. Wurtzel O, Yoder-Himes DR, Han K, Dandekar AA, Edelheit S et al. The single-nucleotide resolution transcriptome of Pseudomonas aeruginosa grown in body temperature. PLoS Pathog 2012; 8:e1002945 [View Article]
     [Google Scholar]
  12. Cattoir V, Narasimhan G, Skurnik D, Aschard H, Roux D et al. Transcriptional response of mucoid Pseudomonas aeruginosa to human respiratory mucus. mBio 2012; 3:e00410–00412 [View Article]
     [Google Scholar]
  13. Dötsch A, Schniederjans M, Khaledi A, Hornischer K, Schulz S et al. The Pseudomonas aeruginosa transcriptional landscape is shaped by environmental heterogeneity and genetic variation. mBio 2015; 6:e00749–15 [View Article]
     [Google Scholar]
  14. Balasubramanian D, Kumari H, Jaric M, Fernandez M, Turner KH et al. Deep sequencing analyses expands the Pseudomonas aeruginosa AmpR regulon to include small RNA-mediated regulation of iron acquisition, heat shock and oxidative stress response. Nucleic Acids Res 2014; 42:979–998 [View Article]
     [Google Scholar]
  15. Jones CJ, Newsom D, Kelly B, Irie Y, Jennings LK et al. Chip-Seq and RNA-seq reveal an AmrZ-mediated mechanism for cyclic di-GMP synthesis and biofilm development by Pseudomonas aeruginosa . PLoS Pathog 2014; 10:e1003984 [View Article]
     [Google Scholar]
  16. Huang H, Shao X, Xie Y, Wang T, Zhang Y et al. An integrated genomic regulatory network of virulence-related transcriptional factors in Pseudomonas aeruginosa . Nat Commun 2019; 10:2931 [View Article]
     [Google Scholar]
  17. Schulz S, Eckweiler D, Bielecka A, Nicolai T, Franke R et al. Elucidation of sigma factor-associated networks in Pseudomonas aeruginosa reveals a modular architecture with limited and function-specific crosstalk. PLoS Pathog 2015; 11:e1004744 [View Article]
     [Google Scholar]
  18. Kordes A, Preusse M, Willger SD, Braubach P, Jonigk D et al. Genetically diverse Pseudomonas aeruginosa populations display similar transcriptomic profiles in a cystic fibrosis explanted lung. Nat Commun 2019; 10:3397 [View Article]
     [Google Scholar]
  19. Rossi E, Falcone M, Molin S, Johansen HK. High-Resolution in situ transcriptomics of Pseudomonas aeruginosa unveils genotype independent patho-phenotypes in cystic fibrosis lungs. Nat Commun 2018; 9:3459 [View Article]
     [Google Scholar]
  20. Cornforth DM, Dees JL, Ibberson CB, Huse HK, Mathiesen IH et al. Pseudomonas aeruginosa transcriptome during human infection. Proc Natl Acad Sci USA 2018; 115:E5125E5134 [View Article]
     [Google Scholar]
  21. Westermann AJ, Barquist L, Vogel J. Resolving host-pathogen interactions by dual RNA-seq. PLoS Pathog 2017; 13:e1006033 [View Article]
     [Google Scholar]
  22. Damron FH, Oglesby-Sherrouse AG, Wilks A, Barbier M. Dual-seq transcriptomics reveals the battle for iron during Pseudomonas aeruginosa acute murine pneumonia. Sci Rep 2016; 6:39172 [View Article]
     [Google Scholar]
  23. Kumar SS, Tandberg JI, Penesyan A, Elbourne LDH, Suarez-Bosche N et al. Dual transcriptomics of host-pathogen interaction of cystic fibrosis isolate Pseudomonas aeruginosa PASS1 with zebrafish. Front Cell Infect Microbiol 2018; 8:406 [View Article]
     [Google Scholar]
  24. Hoe C-H, Raabe CA, Rozhdestvensky TS, Tang T-H. Bacterial sRNAs: regulation in stress. Int J Med Microbiol 2013; 303:217–229 [View Article]
     [Google Scholar]
  25. Papenfort K, Vanderpool CK. Target activation by regulatory RNAs in bacteria. FEMS Microbiol Rev 2015; 39:362–378 [View Article]
     [Google Scholar]
  26. Kavita K, de Mets F, Gottesman S. New aspects of RNA-based regulation by Hfq and its partner sRNAs. Curr Opin Microbiol 2018; 42:53–61 [View Article]
     [Google Scholar]
  27. Saliba A-E, C Santos S, Vogel J. New RNA-seq approaches for the study of bacterial pathogens. Curr Opin Microbiol 2017; 35:78–87 [View Article]
     [Google Scholar]
  28. Gill EE, Chan LS, Winsor GL, Dobson N, Lo R et al. High-Throughput detection of RNA processing in bacteria. BMC Genomics 2018; 19:223 [View Article]
     [Google Scholar]
  29. Sonnleitner E, Hagens S, Rosenau F, Wilhelm S, Habel A et al. Reduced virulence of a Hfq mutant of Pseudomonas aeruginosa O1. Microb Pathog 2003; 35:217–228 [View Article]
     [Google Scholar]
  30. Kambara TK, Ramsey KM, Dove SL. Pervasive targeting of nascent transcripts by Hfq. Cell Rep 2018; 23:1543–1552 [View Article]
     [Google Scholar]
  31. Sonnleitner E, Wulf A, Campagne S, Pei X-Y, Wolfinger MT et al. Interplay between the catabolite repression control protein CRC, Hfq and RNA in Hfq-dependent translational regulation in Pseudomonas aeruginosa . Nucleic Acids Res 2018; 46:1470–1485 [View Article]
     [Google Scholar]
  32. Han K, Tjaden B, Lory S. GRIL-seq provides a method for identifying direct targets of bacterial small regulatory RNA by in vivo proximity ligation. Nature Microbiology 2016; 2:16239 [View Article]
     [Google Scholar]
  33. Zhang Y-F, Han K, Chandler CE, Tjaden B, Ernst RK et al. Probing the sRNA regulatory landscape of P. aeruginosa: post-transcriptional control of determinants of pathogenicity and antibiotic susceptibility. Mol Microbiol 2017; 106:919–937 [View Article]
     [Google Scholar]
  34. Blanco-Romero E, Redondo-Nieto M, Martínez-Granero F, Garrido-Sanz D, Ramos-González MI et al. Genome-Wide analysis of the FleQ direct regulon in Pseudomonas fluorescens F113 and Pseudomonas putida KT2440. Sci Rep 2018; 8:13145 [View Article]
     [Google Scholar]
  35. Heacock-Kang Y, Sun Z, Zarzycki-Siek J, Poonsuk K, McMillan IA et al. Two regulators, PA3898 and PA2100, modulate the Pseudomonas aeruginosa multidrug resistance MexAB-OprM and EmrAB efflux pumps and biofilm formation. Antimicrob Agents Chemother 2018; 62:e01459–18 [View Article]
     [Google Scholar]
  36. Shao X, Zhang X, Zhang Y, Zhu M, Yang P et al. RpoN-dependent direct regulation of quorum sensing and the Type VI secretion system in Pseudomonas aeruginosa PAO1. J Bacteriol 2018; 200:e00205–00218 [View Article]
     [Google Scholar]
  37. Viducic D, Murakami K, Amoh T, Ono T, Miyake Y. RpoN promotes Pseudomonas aeruginosa survival in the presence of tobramycin. Front Microbiol 2017; 8:839 [View Article]
     [Google Scholar]
  38. Kay E, Humair B, Dénervaud V, Riedel K, Spahr S et al. Two GacA-dependent small RNAs modulate the quorum-sensing response in Pseudomonas aeruginosa . J Bacteriol 2006; 188:60266033 [View Article]
     [Google Scholar]
  39. Ding F, Oinuma K-I, Smalley NE, Schaefer AL, Hamwy O et al. The Pseudomonas aeruginosa orphan quorum sensing signal receptor qscr regulates global quorum sensing gene expression by activating a single linked operon. mBio 2018; 9:e01274–18 [View Article]
     [Google Scholar]
  40. Kawalek A, Bartosik AA, Glabski K, Jagura-Burdzy G. Pseudomonas aeruginosa partitioning protein ParB acts as a nucleoid-associated protein binding to multiple copies of a parS-related motif. Nucleic Acids Res 2018; 46:4592–4606 [View Article]
     [Google Scholar]
  41. Liang H, Deng X, Li X, Ye Y, Wu M. Molecular mechanisms of master regulator VqsM mediating quorum-sensing and antibiotic resistance in Pseudomonas aeruginosa . Nucleic Acids Res 2014; 42:10307–10320 [View Article]
     [Google Scholar]
  42. Chao MC, Abel S, Davis BM, Waldor MK. The design and analysis of transposon insertion sequencing experiments. Nat Rev Microbiol 2016; 14:119128 [View Article]
     [Google Scholar]
  43. Lee SA, Gallagher LA, Thongdee M, Staudinger BJ, Lippman S et al. General and condition-specific essential functions of Pseudomonas aeruginosa . Proc Natl Acad Sci U S A 2015; 112:51895194 [View Article]
     [Google Scholar]
  44. Poulsen BE, Yang R, Clatworthy AE, White T, Osmulski SJ et al. Defining the core essential genome of Pseudomonas aeruginosa . Proc Natl Acad Sci U S A 2019; 18:10072 [View Article]
     [Google Scholar]
  45. Skurnik D, Roux D, Aschard H, Cattoir V, Yoder-Himes D et al. A comprehensive analysis of in vitro and in vivo genetic fitness of Pseudomonas aeruginosa using high-throughput sequencing of transposon libraries. PLoS Pathog 2013; 9:e1003582 [View Article]
     [Google Scholar]
  46. Skurnik D, Roux D, Cattoir V, Danilchanka O, Lu X et al. Enhanced in vivo fitness of carbapenem-resistant oprD mutants of Pseudomonas aeruginosa revealed through high-throughput sequencing. Proc Natl Acad Sci U S A 2013; 110:20747–20752 [View Article]
     [Google Scholar]
  47. Turner KH, Everett J, Trivedi U, Rumbaugh KP, Whiteley M. Requirements for Pseudomonas aeruginosa acute burn and chronic surgical wound infection. PLoS Genet 2014; 10:e1004518 [View Article]
     [Google Scholar]
  48. Pasqua M, Visaggio D, Lo Sciuto A, Genah S, Banin E et al. Ferric uptake regulator fur is conditionally essential in Pseudomonas aeruginosa . J Bacteriol 2017; 199:e00472–17 [View Article]
     [Google Scholar]
  49. Nolan LM, Whitchurch CB, Barquist L, Katrib M, Boinett CJ et al. A global genomic approach uncovers novel components for twitching motility-mediated biofilm expansion in Pseudomonas aeruginosa . Microbial Genomics 2018; 4: [View Article]
     [Google Scholar]
  50. Wetmore KM, Price MN, Waters RJ, Lamson JS, He J et al. Rapid quantification of mutant fitness in diverse bacteria by sequencing randomly Bar-Coded transposons. mBio 2015; 6:e00306–00315 [View Article]
     [Google Scholar]
  51. Cole BJ, Feltcher ME, Waters RJ, Wetmore KM, Mucyn TS et al. Genome-Wide identification of bacterial plant colonization genes. PLoS Biol 2017; 15:e2002860 [View Article]
     [Google Scholar]
  52. Brauer AL, White AN, Learman BS, Johnson AO, Armbruster CE. D-Serine degradation by Proteus mirabilis contributes to fitness during single-species and polymicrobial catheter-associated urinary tract infection. mSphere 2019; 4:e00020–19 [View Article]
     [Google Scholar]
  53. Ibberson CB, Stacy A, Fleming D, Dees JL, Rumbaugh K et al. Co-infecting microorganisms dramatically alter pathogen gene essentiality during polymicrobial infection. Nat Microbiol 2017; 2:17079 [View Article]
     [Google Scholar]
  54. Tatusov RL, Galperin MY, Natale DA, Koonin EV. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res 2000; 28:33–36 [View Article]
     [Google Scholar]
  55. Huse HK, Kwon T, Zlosnik JEA, Speert DP, Marcotte EM et al. Parallel evolution in Pseudomonas aeruginosa over 39,000 generations in vivo. mBio 2010; 1:e00199-10 [View Article]
     [Google Scholar]
  56. Jensen PA, Zhu Z, van Opijnen T. Antibiotics disrupt coordination between transcriptional and phenotypic stress responses in pathogenic bacteria. Cell Rep 2017; 20:1705–1716 [View Article]
     [Google Scholar]
  57. 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]
     [Google Scholar]
  58. Winsor GL et al. Pseudomonas aeruginosa genome database and PseudoCAP: facilitating community-based, continually updated, genome annotation. Nucleic Acids Res 2004; 33:D338–D343 [View Article]
     [Google Scholar]
  59. 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–D653 [View Article]
     [Google Scholar]
  60. Hornischer K, Khaledi A, Pohl S, Schniederjans M, Pezoldt L et al. BACTOME—a reference database to explore the sequence- and gene expression-variation landscape of Pseudomonas aeruginosa clinical isolates. Nucleic Acids Res 2019; 47:D716–D720 [View Article]
     [Google Scholar]
  61. Jacobs MA, Alwood A, Thaipisuttikul I, Spencer D, Haugen E et al. Comprehensive transposon mutant library of Pseudomonas aeruginosa . Proc Natl Acad Sci USA 2003; 100:14339–14344 [View Article]
     [Google Scholar]
  62. Lee S, Hinz A, Bauerle E, Angermeyer A, Juhaszova K et al. Targeting a bacterial stress response to enhance antibiotic action. Proc Natl Acad Sci U S A 2009; 106:1457014575 [View Article]
     [Google Scholar]
  63. Gallagher LA, Shendure J, Manoil C. Genome-scale identification of resistance functions in Pseudomonas aeruginosa using Tn-seq. mBio 2011; 2:e00315–10 [View Article]
     [Google Scholar]
  64. Murray JL, Kwon T, Marcotte EM, Whiteley M. Intrinsic antimicrobial resistance determinants in the superbug Pseudomonas aeruginosa . mBio 2015; 6:e01603–01615 [View Article]
     [Google Scholar]
  65. Khaledi A, Schniederjans M, Pohl S, Rainer R, Bodenhofer U et al. Transcriptome profiling of antimicrobial resistance in Pseudomonas aeruginosa . Antimicrob Agents Chemother 2016; 60:47224733 [View Article]
     [Google Scholar]
  66. Tan J, Hammond JH, Hogan DA, Greene CS. ADAGE-based integration of publicly available Pseudomonas aeruginosa gene expression data with denoising autoencoders illuminates microbe-host interactions. mSystems 2016; 1:e00025–15 [View Article]
     [Google Scholar]
  67. Tan J, Doing G, Lewis KA, Price CE, Chen KM et al. Unsupervised extraction of stable expression signatures from public compendia with an ensemble of neural networks. Cell Syst 2017; 5:63–71 [View Article]
     [Google Scholar]
  68. Kang Y, McMillan I, Norris MH, Hoang TT. Single prokaryotic cell isolation and total transcript amplification protocol for transcriptomic analysis. Nat Protoc 2015; 10:974984 [View Article]
     [Google Scholar]
  69. Kang Y, Norris MH, Zarzycki-Siek J, Nierman WC, Donachie SP et al. Transcript amplification from single bacterium for transcriptome analysis. Genome Res 2011; 21:925–935 [View Article]
     [Google Scholar]
  70. Fisher RA, Gollan B, Helaine S. Persistent bacterial infections and persister cells. Nat Rev Microbiol 2017; 15:453464 [View Article]
     [Google Scholar]
  71. Wessel AK, Arshad TA, Fitzpatrick M, Connell JL, Bonnecaze RT et al. Oxygen limitation within a bacterial aggregate. mBio 2014; 5:e00992–14 [View Article]
     [Google Scholar]
  72. Babin BM, Atangcho L, van Eldijk MB, Sweredoski MJ, Moradian A et al. Selective proteomic analysis of antibiotic-tolerant cellular subpopulations in Pseudomonas aeruginosa biofilms. mBio 2017; 8:e01593–17 [View Article]
     [Google Scholar]
  73. Charretier Y, Schrenzel J. Mass spectrometry methods for predicting antibiotic resistance. Proteomics Clin Appl 2016; 10:964–981 [View Article]
     [Google Scholar]
  74. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990; 215:403–410 [View Article]
     [Google Scholar]
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There is no hiding if you Seq: recent breakthroughs in Pseudomonas aeruginosa research revealed by genomic and transcriptomic next-generation sequencing
J. Med. Microbiol. 69, 162 (2020); https://doi.org/10.1099/jmm.0.001135
/content/journal/jmm/10.1099/jmm.0.001135
/content/journal/jmm/10.1099/jmm.0.001135
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