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Volume 169, Issue 8

Transcription factor expression levels and environmental signals constrain transcription factor innovation Open Access

This article is part of the Microbial Evolution collection.

Abstract

Evolutionary innovation of transcription factors frequently drives phenotypic diversification and adaptation to environmental change. Transcription factors can gain or lose connections to target genes, resulting in novel regulatory responses and phenotypes. However the frequency of functional adaptation varies between different regulators, even when they are closely related. To identify factors influencing propensity for innovation, we utilise a SBW25 strain rendered incapable of flagellar mediated motility in soft-agar plates via deletion of the flagellar master regulator (). This bacterium can evolve to rescue flagellar motility via gene regulatory network rewiring of an alternative transcription factor to rescue activity of FleQ. Previously, we have identified two members (out of 22) of the RpoN-dependent enhancer binding protein (RpoN-EBP) family of transcription factors (NtrC and PFLU1132) that are capable of innovating in this way. These two transcription factors rescue motility repeatably and reliably in a strict hierarchy – with NtrC the only route in a ∆ background, and PFLU1132 the only route in a ∆∆ background. However, why other members in the same transcription factor family have not been observed to rescue flagellar activity is unclear. Previous work shows that protein homology cannot explain this pattern within the protein family (RpoN-EBPs), and mutations in strains that rescued motility suggested high levels of transcription factor expression and activation drive innovation. We predict that mutations that increase expression of the transcription factor are vital to unlock evolutionary potential for innovation. Here, we construct titratable expression mutant lines for 11 of the RpoN-EBPs in . We show that in five additional RpoN-EBPs (FleR, HbcR, GcsR, DctD, AauR and PFLU2209), high expression levels result in different mutations conferring motility rescue, suggesting alternative rewiring pathways. Our results indicate that expression levels (and not protein homology) of RpoN-EBPs are a key constraining factor in determining evolutionary potential for innovation. This suggests that transcription factors that can achieve high expression through few mutational changes, or transcription factors that are active in the selective environment, are more likely to innovate and contribute to adaptive gene regulatory network evolution.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): experimental evolution , gene regulatory networks , Pseudomonas fluorescens , rhamnose inducible expression and transcription factor
Funding
This study was supported by the:
  • Royal Society (Award RGF\EA\201057)
    • Principle Award Recipient: TiffanyTaylor
  • Royal Society (Award DH150169)
    • Principle Award Recipient: TiffanyTaylor
  • Royal Society (Award RF\ERE\210249)
    • Principle Award Recipient: TiffanyTaylor
  • Windsor Fellowship
    • Principle Award Recipient: MitchellReynolds
  • Royal Society (Award RG160491)
    • Principle Award Recipient: TiffanyTaylor
© 2023 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.
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2023-08-16
2024-05-18
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References

  1. Payne JL, Wagner A. The causes of evolvability and their evolution. Nat Rev Genet 2019; 20:24–38 [View Article] [PubMed]
     [Google Scholar]
  2. Shepherd MJ, Pierce AP, Taylor TB. Evolutionary innovation through transcription factor promiscuity in microbes is constrained by pre-existing gene regulatory network architecture. BioRxiv 2023 [View Article]
     [Google Scholar]
  3. Taylor TB, Shepherd MJ, Jackson RW, Silby MW. Natural selection on crosstalk between gene regulatory networks facilitates bacterial adaptation to novel environments. Curr Opin Microbiol 2022; 67:102140 [View Article] [PubMed]
     [Google Scholar]
  4. Adhikari S, Erill I, Curtis PD. Transcriptional rewiring of the GcrA/CcrM bacterial epigenetic regulatory system in closely related bacteria. PLoS Genet 2021; 17:1–30 [View Article] [PubMed]
     [Google Scholar]
  5. Baumstark R, Hänzelmann S, Tsuru S, Schaerli Y, Francesconi M et al. The propagation of perturbations in rewired bacterial gene networks. Nat Commun 2015; 6:1–5 [View Article] [PubMed]
     [Google Scholar]
  6. Isalan M, Lemerle C, Michalodimitrakis K, Horn C, Beltrao P et al. Evolvability and hierarchy in rewired bacterial gene networks. Nature 2008; 452:840–845 [View Article] [PubMed]
     [Google Scholar]
  7. Martchenko M, Levitin A, Hogues H, Nantel A, Whiteway M. Transcriptional rewiring of fungal galactose-metabolism circuitry. Curr Biol 2007; 17:1007–1013 [View Article] [PubMed]
     [Google Scholar]
  8. Patel V, Matange N. Adaptation and compensation in a bacterial gene regulatory network evolving under antibiotic selection. Elife 2021; 10:1–27 [View Article] [PubMed]
     [Google Scholar]
  9. Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. Evolutionary potential of transcription factors for gene regulatory rewiring. Nat Ecol Evol 2018; 2:1633–1643 [View Article] [PubMed]
     [Google Scholar]
  10. Payne JL, Wagner A. The robustness and evolvability of transcription factor binding sites. Science 2014; 343:875–877 [View Article] [PubMed]
     [Google Scholar]
  11. Tirosh I, Barkai N, Verstrepen KJ. Promoter architecture and the evolvability of gene expression. J Biol 2009; 8:95 [View Article] [PubMed]
     [Google Scholar]
  12. Alhindi T, Zhang Z, Ruelens P, Coenen H, Degroote H et al. Protein interaction evolution from promiscuity to specificity with reduced flexibility in an increasingly complex network. Sci Rep 2017; 7:1–15 [View Article] [PubMed]
     [Google Scholar]
  13. Copley SD. An evolutionary biochemist’s perspective on promiscuity. Trends Biochem Sci 2015; 40:72–78 [View Article] [PubMed]
     [Google Scholar]
  14. Copley SD. The physical basis and practical consequences of biological promiscuity. Phys Biol 2020; 17: [View Article] [PubMed]
     [Google Scholar]
  15. Pougach K, Voet A, Kondrashov FA, Voordeckers K, Christiaens JF et al. Duplication of a promiscuous transcription factor drives the emergence of a new regulatory network. Nat Commun 2014; 5:1–11 [View Article] [PubMed]
     [Google Scholar]
  16. Taylor TB, Mulley G, Dills AH, Alsohim AS, McGuffin LJ et al. Evolutionary resurrection of flagellar motility via rewiring of the nitrogen regulation system. Science 2015; 347:1014–1017 [View Article] [PubMed]
     [Google Scholar]
  17. Studholme DJ, Dixon R. Domain architectures of sigma54-dependent transcriptional activators. J Bacteriol 2003; 185:1757–1767 [View Article] [PubMed]
     [Google Scholar]
  18. Fang X, Sastry A, Mih N, Kim D, Tan J et al. Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities. Proc Natl Acad Sci 2017; 114:10286–10291 [View Article] [PubMed]
     [Google Scholar]
  19. Martínez-Antonio A, Collado-Vides J. Identifying global regulators in transcriptional regulatory networks in bacteria. Curr Opin Microbiol 2003; 6:482–489 [View Article] [PubMed]
     [Google Scholar]
  20. Lamrabet O, Plumbridge J, Martin M, Lenski RE, Schneider D et al. Plasticity of promoter-core sequences allows bacteria to compensate for the loss of a key global regulatory gene. Mol Biol Evol 2019; 36:1121–1133 [View Article] [PubMed]
     [Google Scholar]
  21. Bandyopadhyay A, Banik SK. Positive feedback and temperature mediated molecular switch controls differential gene regulation in Bordetella pertussis. Biosystems 2012; 110:107–118 [View Article] [PubMed]
     [Google Scholar]
  22. Goulian M. Two-component signaling circuit structure and properties. Curr Opin Microbiol 2010; 13:184–189 [View Article] [PubMed]
     [Google Scholar]
  23. Groisman EA. Feedback control of two-component regulatory systems. Annu Rev Microbiol 2016; 70:103–124 [View Article] [PubMed]
     [Google Scholar]
  24. diCenzo GC, Sharthiya H, Nanda A, Zamani M, Finan TM. PhoU allows rapid adaptation to high phosphate concentrations by modulating PstSCAB transport rate in Sinorhizobium meliloti. J Bacteriol 2017; 199:1–20 [View Article] [PubMed]
     [Google Scholar]
  25. Rao SD, Igoshin OA. Overlaid positive and negative feedback loops shape dynamical properties of PhoPQ two-component system. PLoS Comput Biol 2021; 17:1–18 [View Article] [PubMed]
     [Google Scholar]
  26. Weyder M, Prudhomme M, Bergé M, Polard P, Fichant G. Dynamic modeling of Streptococcus pneumoniae competence provides regulatory mechanistic insights into its tight temporal regulation. Front Microbiol 2018; 9:1–25 [View Article] [PubMed]
     [Google Scholar]
  27. Seshasayee ASN, Bertone P, Fraser GM, Luscombe NM. Transcriptional regulatory networks in bacteria: from input signals to output responses. Curr Opin Microbiol 2006; 9:511–519 [View Article] [PubMed]
     [Google Scholar]
  28. Galperin MY. Structural classification of bacterial response regulators: diversity of output domains and domain combinations. J Bacteriol 2006; 188:4169–4182 [View Article] [PubMed]
     [Google Scholar]
  29. Browning DF, Butala M, Busby SJW. Bacterial transcription factors: regulation by pick “N” mix. J Mol Biol 2019; 431:4067–4077 [View Article] [PubMed]
     [Google Scholar]
  30. Mainiero M, Goerke C, Geiger T, Gonser C, Herbert S et al. Differential target gene activation by the Staphylococcus aureus two-component system saeRS. J Bacteriol 2010; 192:613–623 [View Article] [PubMed]
     [Google Scholar]
  31. Moskowitz SM, Brannon MK, Dasgupta N, Pier M, Sgambati N et al. PmrB mutations promote polymyxin resistance of Pseudomonas aeruginosa isolated from colistin-treated cystic fibrosis patients. Antimicrob Agents Chemother 2012; 56:1019–1030 [View Article] [PubMed]
     [Google Scholar]
  32. Olaitan AO, Morand S, Rolain J-M. Mechanisms of polymyxin resistance: acquired and intrinsic resistance in bacteria. Front Microbiol 2014; 5:643 [View Article] [PubMed]
     [Google Scholar]
  33. Taylor TB, Mulley G, McGuffin LJ, Johnson LJ, Brockhurst MA et al. Evolutionary rewiring of bacterial regulatory networks. Microb Cell 2015; 2:256–258 [View Article] [PubMed]
     [Google Scholar]
  34. Horton JS, Flanagan LM, Jackson RW, Priest NK, Taylor TB. A mutational hotspot that determines highly repeatable evolution can be built and broken by silent genetic changes. Nat Commun 2021; 12:6092 [View Article] [PubMed]
     [Google Scholar]
  35. Shepherd MJ, Horton JS, Taylor TB. A near-deterministic mutational hotspot in Pseudomonas fluorescens is constructed by multiple interacting genomic features. Mol Biol Evol 2022; 39:1–7 [View Article] [PubMed]
     [Google Scholar]
  36. Meisner J, Goldberg JB. The Escherichia coli rhaSR-PrhaBAD inducible promoter system allows tightly controlled gene expression over a wide range in Pseudomonas aeruginosa. Appl Environ Microbiol 2016; 82:6715–6727 [View Article] [PubMed]
     [Google Scholar]
  37. Choi K-H, Schweizer HP. mini-Tn7 insertion in bacteria with single attTn7 sites: example Pseudomonas aeruginosa. Nat Protoc 2006; 1:153–161 [View Article] [PubMed]
     [Google Scholar]
  38. Alsohim AS, Taylor TB, Barrett GA, Gallie J, Zhang X-X et al. The biosurfactant viscosin produced by Pseudomonas fluorescens SBW25 aids spreading motility and plant growth promotion. Environ Microbiol 2014; 16:2267–2281 [View Article] [PubMed]
     [Google Scholar]
  39. Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 2018; 34:i884–i890 [View Article] [PubMed]
     [Google Scholar]
  40. Silby MW, Cerdeño-Tárraga AM, Vernikos GS, Giddens SR, Jackson RW et al. Genomic and genetic analyses of diversity and plant interactions of Pseudomonas fluorescens. Genome Biol 2009; 10:1–16 [View Article] [PubMed]
     [Google Scholar]
  41. Deatherage DE, Barrick JE. Identification of mutations in laboratory-evolved microbes from next-generation sequencing data using breseq. In Sun L, Shou W. eds Engineering and Analyzing Multicellular Systems: Methods and Protocols New York, NY: Springer; 2014 pp 165–188 [View Article]
     [Google Scholar]
  42. Katoh K, Rozewicki J, Yamada KD. MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization. Brief Bioinform 2019; 20:1160–1166 [View Article] [PubMed]
     [Google Scholar]
  43. Mistry J, Chuguransky S, Williams L, Qureshi M, Salazar GA et al. Pfam: The protein families database in 2021. Nucleic Acids Res 2021; 49:D412–D419 [View Article] [PubMed]
     [Google Scholar]
  44. Jones P, Binns D, Chang H-Y, Fraser M, Li W et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 2014; 30:1236–1240 [View Article] [PubMed]
     [Google Scholar]
  45. O’Leary NA, Wright MW, Brister JR, Ciufo S, Haddad D et al. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res 2016; 44:D733–D745 [View Article] [PubMed]
     [Google Scholar]
  46. Manni M, Berkeley MR, Seppey M, Simão FA, Zdobnov EM. BUSCO update: novel and streamlined workflows along with broader and deeper phylogenetic coverage for scoring of eukaryotic, prokaryotic, and viral genomes. Mol Biol Evol 2021; 38:4647–4654 [View Article] [PubMed]
     [Google Scholar]
  47. Rodríguez-Beltrán J, Sørum V, Toll-Riera M, de la Vega C, Peña-Miller R et al. Genetic dominance governs the evolution and spread of mobile genetic elements in bacteria. Proc Natl Acad Sci U S A 2020; 117:15755–15762 [View Article] [PubMed]
     [Google Scholar]
  48. Bouteiller M, Dupont C, Bourigault Y, Latour X, Barbey C et al. Pseudomonas Flagella: generalities and specificities. Int J Mol Sci 2021; 22:3337 [View Article] [PubMed]
     [Google Scholar]
  49. Dasgupta N, Wolfgang MC, Goodman AL, Arora SK, Jyot J et al. A four-tiered transcriptional regulatory circuit controls flagellar biogenesis in Pseudomonas aeruginosa. Mol Microbiol 2003; 50:809–824 [View Article] [PubMed]
     [Google Scholar]
  50. Zhou T, Huang J, Liu Z, Xu Z, Zhang L-H. Molecular mechanisms underlying the regulation of biofilm formation and swimming motility by FleS/FleR in Pseudomonas aeruginosa. Front Microbiol 2021; 12:707711 [View Article] [PubMed]
     [Google Scholar]
  51. Okamura-Ikeda K, Ohmura Y, Fujiwara K, Motokawa Y. Cloning and nucleotide sequence of the gcv operon encoding the Escherichia coli glycine-cleavage system. Eur J Biochem 1993; 216:539–548 [View Article] [PubMed]
     [Google Scholar]
  52. Sarwar Z, Lundgren BR, Grassa MT, Wang MX, Gribble M et al. Gcsr, a Tyrr-like enhancer-binding protein. Regulates Expression of the Glycine Cleavage System in Pseudomonas aeruginosa PAO1 2016e00020–16 [View Article] [PubMed]
     [Google Scholar]
  53. Ernst DC, Downs DM. 2-aminoacrylate stress induces a context-dependent glycine requirement in ridA strains of Salmonella enterica. J Bacteriol 2016; 198:536–543 [View Article] [PubMed]
     [Google Scholar]
  54. Schultheisz HL, Szymczyna BR, Scott LG, Williamson JR. Enzymatic de novo pyrimidine nucleotide synthesis. J Am Chem Soc 2011; 133:297–304 [View Article] [PubMed]
     [Google Scholar]
  55. West TP. Effect of carbon source on pyrimidine biosynthesis in Pseudomonas oryzihabitans: effect of carbon source on pyrimidine biosynthesis in Pseudomonas Oryzihabitans. J Basic Microbiol 2010; 50:397–400 [View Article]
     [Google Scholar]
  56. Yan Q, Rogan CJ, Pang Y-Y, Davis EW, Anderson JC. Ancient co-option of an amino acid ABC transporter locus in Pseudomonas syringae for host signal-dependent virulence gene regulation. PLoS Pathog 2020; 16:e1008680 [View Article] [PubMed]
     [Google Scholar]
  57. Joly N, Engl C, Jovanovic G, Huvet M, Toni T et al. Managing membrane stress: the phage shock protein (Psp) response, from molecular mechanisms to physiology. FEMS Microbiol Rev 2010; 34:797–827 [View Article] [PubMed]
     [Google Scholar]
  58. Lundgren BR, Harris JR, Sarwar Z, Scheel RA, Nomura CT. The metabolism of (R)-3-hydroxybutyrate is regulated by the enhancer-binding protein PA2005 and the alternative sigma factor RpoN in Pseudomonas aeruginosa PAO1. Microbiology 2015; 161:2232–2242 [View Article] [PubMed]
     [Google Scholar]
  59. Doucleff M, Pelton JG, Lee PS, Nixon BT, Wemmer DE. Structural basis of DNA recognition by the alternative sigma-factor, sigma54. J Mol Biol 2007; 369:1070–1078 [View Article] [PubMed]
     [Google Scholar]
  60. Bush M, Dixon R. The role of bacterial enhancer binding proteins as specialized activators of σ54-dependent transcription. Microbiol Mol Biol Rev 2012; 76:497–529 [View Article] [PubMed]
     [Google Scholar]
  61. Studholme DJ, Buck M. The biology of enhancer-dependent transcriptional regulation in bacteria: insights from genome sequences. FEMS Microbiol Lett 2000; 186:1–9 [View Article] [PubMed]
     [Google Scholar]
  62. Nie X, Dong W, Yang C. Genomic reconstruction of σ54 regulons in Clostridiales. BMC Genomics 2019; 20:565 [View Article]
     [Google Scholar]
  63. Schmutzer M, Wagner A. Gene expression noise can promote the fixation of beneficial mutations in fluctuating environments. PLoS Comput Biol 2020; 16:e1007727 [View Article] [PubMed]
     [Google Scholar]
  64. Tsuda ME, Kawata M. Evolution of gene regulatory networks by fluctuating selection and intrinsic constraints. PLoS Comput Biol 2010; 6:e1000873 [View Article] [PubMed]
     [Google Scholar]
  65. Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. Intrinsic limits to gene regulation by global crosstalk. Nat Commun 2016; 7:12307 [View Article] [PubMed]
     [Google Scholar]
  66. Jothi R, Balaji S, Wuster A, Grochow JA, Gsponer J et al. Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture. Mol Syst Biol 2009; 5:294 [View Article] [PubMed]
     [Google Scholar]
  67. Hervás AB, Canosa I, Little R, Dixon R, Santero E. NtrC-dependent regulatory network for nitrogen assimilation in Pseudomonas putida. J Bacteriol 2009; 191:6123–6135 [View Article] [PubMed]
     [Google Scholar]
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Transcription factor expression levels and environmental signals constrain transcription factor innovation
Microbiology 169, 001378 (2023); https://doi.org/10.1099/mic.0.001378
/content/journal/micro/10.1099/mic.0.001378
/content/journal/micro/10.1099/mic.0.001378
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