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Volume 171, Issue 6

History shapes regulatory and evolutionary responses to tigecycline in two reference strains of Open Access

Abstract

Evolutionary history encompasses both genetic and phenotypic bacterial differences; however, the extent to which this history influences drug response and antimicrobial resistance (AMR) adaptation remains unclear. Historical contingencies arise when elements from an organism’s past leave lasting effects on the genome, altering the paths available for adaptation. Here, we compare two diverging reference strains of , representative of archaic and contemporary infections, to study the impact of deep historical differences shaped by decades of adaptation in varying antibiotic and host pressures. We evaluated these effects by comparing immediate and adaptive responses to the last-resort antibiotic, tigecycline (TGC). The strains demonstrated divergent transcriptional responses, suggesting that baseline transcript levels may dictate global responses to antibiotics. Experimental evolution in TGC revealed clear differences in population dynamics, with hard sweeps in populations founded by one strain and no mutations reaching fixation in the other strain. AMR was acquired through predictable mechanisms of increased efflux and drug target modification; however, efflux targets were dictated by strain background. Genetic adaptation may outweigh historic differences in transcriptional networks, as evolved populations no longer show transcriptomic signatures of drug response. Importantly, fitness–resistance trade-offs were only observed in lineages evolved from the archaic strain, while the contemporary reference isolate suffered no fitness defects. This suggests that decades of adaptation to antibiotics resulted in pre-existing compensatory mechanisms in the more contemporary isolate, an important example of a beneficial effect of historical contingencies.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): antimicrobial resistance , evolutionary history , experimental evolution , transcriptomics and Acinetobacter baumannii
Funding
This study was supported by the:
  • Ministerio de Ciencia, Innovación y Universidades (Award RYC2022-037765-I)
    • Principle Award Recipient: AlfonsoSantos Lopez
  • Pennsylvania Department of Health (Award CURES 4100085725)
    • Principle Award Recipient: VaughnCooper
  • National Institute of Allergy and Infectious Diseases (Award F31AI172279)
    • Principle Award Recipient: AleciaB Rokes
  • National Institute of Allergy and Infectious Diseases (Award U19AI158076)
    • Principle Award Recipient: VaughnCooper
© 2025 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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References

  1. Aslam B, Wang W, Arshad MI, Khurshid M, Muzammil S et al. Antibiotic resistance: a rundown of a global crisis. Infect Drug Resist 2018; 11:1645–1658 [View Article] [PubMed]
     [Google Scholar]
  2. Lässig M, Mustonen V, Walczak AM. Predicting evolution. Nat Ecol Evol 2017; 1:77 [View Article] [PubMed]
     [Google Scholar]
  3. Gabaldón T. Nothing makes sense in drug resistance except in the light of evolution. Curr Opin Microbiol 2023; 75:102350 [View Article] [PubMed]
     [Google Scholar]
  4. Palmer AC, Kishony R. Understanding, predicting and manipulating the genotypic evolution of antibiotic resistance. Nat Rev Genet 2013; 14:243–248 [View Article] [PubMed]
     [Google Scholar]
  5. Travisano M, Mongold JA, Bennett AF, Lenski RE. Experimental tests of the roles of adaptation, chance, and history in evolution. Science 1995; 267:87–90 [View Article] [PubMed]
     [Google Scholar]
  6. Plucain J, Suau A, Cruveiller S, Médigue C, Schneider D et al. Contrasting effects of historical contingency on phenotypic and genomic trajectories during a two-step evolution experiment with bacteria. BMC Evol Biol 2016; 16:86 [View Article]
     [Google Scholar]
  7. MacLean RC, San Millan A. The evolution of antibiotic resistance. Science 2019; 365:1082–1083 [View Article]
     [Google Scholar]
  8. Blount ZD, Lenski RE, Losos JB. Contingency and determinism in evolution: replaying life’s tape. Science 2018; 362: [View Article]
     [Google Scholar]
  9. Santos-Lopez A, Marshall CW, Haas AL, Turner C, Rasero J et al. The roles of history, chance, and natural selection in the evolution of antibiotic resistance. Elife 2021; 10:e70676 [View Article] [PubMed]
     [Google Scholar]
  10. Garoff L, Pietsch F, Huseby DL, Lilja T, Brandis G et al. Population bottlenecks strongly influence the evolutionary trajectory to fluoroquinolone resistance in Escherichia coli. Mol Biol Evol 2020; 37:1637–1646 [View Article] [PubMed]
     [Google Scholar]
  11. Wong A. Epistasis and the evolution of antimicrobial resistance. Front Microbiol 2017; 8:246 [View Article] [PubMed]
     [Google Scholar]
  12. MacLean RC. Predicting epistasis: an experimental test of metabolic control theory with bacterial transcription and translation. J Evol Biol 2010; 23:488–493 [View Article] [PubMed]
     [Google Scholar]
  13. Blount ZD. A case study in evolutionary contingency. Stud Hist Philos Biol Biomed Sci 2016; 58:82–92 [View Article] [PubMed]
     [Google Scholar]
  14. Vermeij GJ. Historical contingency and the purported uniqueness of evolutionary innovations. Proc Natl Acad Sci U S A 2006; 103:1804–1809 [View Article] [PubMed]
     [Google Scholar]
  15. Wang Y, Diaz Arenas C, Stoebel DM, Flynn K, Knapp E et al. Benefit of transferred mutations is better predicted by the fitness of recipients than by their ecological or genetic relatedness. Proc Natl Acad Sci USA 2016; 113:5047–5052 [View Article]
     [Google Scholar]
  16. Dionisi S, Huisman JS. Digest: the importance of genetic background in bacterial evolution. Evolution 2024; 78:593–594 [View Article]
     [Google Scholar]
  17. Filipow N, Mallon S, Shewaramani S, Kassen R, Wong A. The impact of genetic background during laboratory evolution of Pseudomonas aeruginosa in a cystic fibrosis-like environment. Evolution 2024; 78:566–578 [View Article] [PubMed]
     [Google Scholar]
  18. Cisneros-Mayoral S, Graña-Miraglia L, Pérez-Morales D, Peña-Miller R, Fuentes-Hernández A. Evolutionary history and strength of selection determine the rate of antibiotic resistance adaptation. Mol Biol Evol 2022; 39: [View Article]
     [Google Scholar]
  19. Card KJ, LaBar T, Gomez JB, Lenski RE. Historical contingency in the evolution of antibiotic resistance after decades of relaxed selection. PLoS Biol 2019; 17:e3000397 [View Article] [PubMed]
     [Google Scholar]
  20. Batarseh TN, Batarseh SN, Rodríguez-Verdugo A, Gaut BS. Phenotypic and genotypic adaptation of Escherichia coli to thermal stress is contingent on genetic background. Mol Biol Evol 2023; 40:msad108 [View Article] [PubMed]
     [Google Scholar]
  21. Flynn KM, Cooper TF, Moore F-G, Cooper VS. The environment affects epistatic interactions to alter the topology of an empirical fitness landscape. PLoS Genet 2013; 9:e1003426 [View Article] [PubMed]
     [Google Scholar]
  22. Baquero F, Martínez JL, F. Lanza V, Rodríguez-Beltrán J, Galán JC et al. Evolutionary pathways and trajectories in antibiotic resistance. Clin Microbiol Rev 2021; 34:e0005019 [View Article]
     [Google Scholar]
  23. Lee C-R, Lee JH, Park M, Park KS, Bae IK et al. Biology of Acinetobacter baumannii: pathogenesis, antibiotic resistance mechanisms, and prospective treatment options. Front Cell Infect Microbiol 2017; 7:55 [View Article] [PubMed]
     [Google Scholar]
  24. Touchon M, Cury J, Yoon E-J, Krizova L, Cerqueira GC et al. The genomic diversification of the whole Acinetobacter genus: origins, mechanisms, and consequences. Genome Biol Evol 2014; 6:2866–2882 [View Article] [PubMed]
     [Google Scholar]
  25. Iovleva A, Mustapha MM, Griffith MP, Komarow L, Luterbach C et al. Carbapenem-resistant Acinetobacter baumannii in U.S. hospitals: diversification of circulating lineages and antimicrobial resistance. mBio 2022; 13:e0275921 [View Article] [PubMed]
     [Google Scholar]
  26. Dorman MJ, Thomson NR. “Community evolution” - laboratory strains and pedigrees in the age of genomics. Microbiology 2020; 166:233–238 [View Article] [PubMed]
     [Google Scholar]
  27. Del Mar Cendra M, Torrents E. Differential adaptability between reference strains and clinical isolates of Pseudomonas aeruginosa into the lung epithelium intracellular lifestyle. Virulence 2020; 11:862–876 [View Article] [PubMed]
     [Google Scholar]
  28. Makke G, Bitar I, Salloum T, Panossian B, Alousi S et al. Whole-genome-sequence-based characterization of extensively drug-resistant Acinetobacter baumannii hospital outbreak. mSphere 2020; 5:e00934-19 [View Article] [PubMed]
     [Google Scholar]
  29. Camargo CH, Yamada AY, Nagamori FO, de Souza AR, Tiba-Casas MR et al. Clonal spread of ArmA- and OXA-23-coproducing Acinetobacter baumannii international clone 2 in Brazil during the first wave of the COVID-19 pandemic. J Med Microbiol 2022; 71: [View Article] [PubMed]
     [Google Scholar]
  30. Marazzato M, Scribano D, Sarshar M, Brunetti F, Fillo S et al. Genetic diversity of antimicrobial resistance and key virulence features in two extensively drug-resistant Acinetobacter baumannii isolates. Int J Environ Res Public Health 2022; 19:2870 [View Article] [PubMed]
     [Google Scholar]
  31. Galac MR, Snesrud E, Lebreton F, Stam J, Julius M et al. A diverse panel of clinical Acinetobacter baumannii for research and development. Antimicrob Agents Chemother 2020; 64:e00840-20 [View Article] [PubMed]
     [Google Scholar]
  32. van Opijnen T, Dedrick S, Bento J. Strain dependent genetic networks for antibiotic-sensitivity in a bacterial pathogen with a large pan-genome. PLoS Pathog 2016; 12:e1005869 [View Article] [PubMed]
     [Google Scholar]
  33. Rizzetto L, Giovannini G, Bromley M, Bowyer P, Romani L et al. Strain dependent variation of immune responses to A. fumigatus: definition of pathogenic species. PLoS One 2013; 8:e56651 [View Article] [PubMed]
     [Google Scholar]
  34. Davies J, Davies D. Origins and evolution of antibiotic resistance. Microbiol Mol Biol Rev 2010; 74:417–433 [View Article] [PubMed]
     [Google Scholar]
  35. Kaul A, Souque C, Holland M, Baym M. Genomic resistance in historical clinical isolates increased in frequency and mobility after the age of antibiotics. bioRxiv 20252025.01.16.633422 [View Article] [PubMed]
     [Google Scholar]
  36. Hendry AP. Prediction in ecology and evolution. Bioscience 2023; 73:785–799 [View Article]
     [Google Scholar]
  37. Erickson KE, Otoupal PB, Chatterjee A. Transcriptome-level signatures in gene expression and gene expression variability during bacterial adaptive evolution. mSphere 2017; 2: [View Article]
     [Google Scholar]
  38. Wijers CDM, Pham L, Menon S, Boyd KL, Noel HR et al. Identification of two variants of Acinetobacter baumannii strain ATCC 17978 with distinct genotypes and phenotypes. Infect Immun 2021; 89:e0045421 [View Article] [PubMed]
     [Google Scholar]
  39. Baumann P, Doudoroff M, Stanier RY. A study of the Moraxella group. II. Oxidative-negative species (genus Acinetobacter). J Bacteriol 1968; 95:1520–1541 [View Article] [PubMed]
     [Google Scholar]
  40. Jacobs AC, Thompson MG, Black CC, Kessler JL, Clark LP et al. AB5075, a highly virulent isolate of Acinetobacter baumannii, as a model strain for the evaluation of pathogenesis and antimicrobial treatments. mBio 2014; 5:e01076-14 [View Article] [PubMed]
     [Google Scholar]
  41. Gallagher LA, Ramage E, Weiss EJ, Radey M, Hayden HS et al. Resources for genetic and genomic analysis of emerging pathogen Acinetobacter baumannii. J Bacteriol 2015; 197:2027–2035 [View Article] [PubMed]
     [Google Scholar]
  42. Santos-Lopez A, Marshall CW, Scribner MR, Snyder DJ, Cooper VS. Evolutionary pathways to antibiotic resistance are dependent upon environmental structure and bacterial lifestyle. Elife 2019; 8:e47612 [View Article] [PubMed]
     [Google Scholar]
  43. Schwengers O, Jelonek L, Dieckmann MA, Beyvers S, Blom J et al. Bakta: rapid and standardized annotation of bacterial genomes via alignment-free sequence identification. Microb Genom 2021; 7:000685 [View Article] [PubMed]
     [Google Scholar]
  44. Tonkin-Hill G, MacAlasdair N, Ruis C, Weimann A, Horesh G et al. Producing polished prokaryotic pangenomes with the Panaroo pipeline. Genome Biol 2020; 21:180 [View Article] [PubMed]
     [Google Scholar]
  45. Pritchard L, Glover RH, Humphris S, Elphinstone JG, Toth IK. Genomics and taxonomy in diagnostics for food security: soft-rotting enterobacterial plant pathogens. Anal Methods 2016; 8:12–24 [View Article]
     [Google Scholar]
  46. Jolley KA, Maiden MCJ. BIGSdb: scalable analysis of bacterial genome variation at the population level. BMC Bioinformatics 2010; 11:595 [View Article] [PubMed]
     [Google Scholar]
  47. Feldgarden M, Brover V, Gonzalez-Escalona N, Frye JG, Haendiges J et al. AMRFinderPlus and the reference gene catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence. Sci Rep 2021; 11:12728 [View Article] [PubMed]
     [Google Scholar]
  48. CLSI C. M100 Performance Standards for Antimicrobial Susceptibility Testing, 32nd Ed Clinical and Laboratory Standards Institute; 2022
     [Google Scholar]
  49. Bray NL, Pimentel H, Melsted P, Pachter L. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol 2016; 34:525–527 [View Article] [PubMed]
     [Google Scholar]
  50. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014; 15:550 [View Article] [PubMed]
     [Google Scholar]
  51. Scribner MR, Santos-Lopez A, Marshall CW, Deitrick C, Cooper VS. Parallel evolution of tobramycin resistance across species and environments. mBio 2020; 11: [View Article]
     [Google Scholar]
  52. Santos-Lopez A, Fritz MJ, Lombardo JB, Burr AHP, Heinrich VA et al. Evolved resistance to a novel cationic peptide antibiotic requires high mutation supply. Evol Med Public Health 2022; 10:266–276 [View Article]
     [Google Scholar]
  53. Huo W, Busch LM, Hernandez-Bird J, Hamami E, Marshall CW et al. Immunosuppression broadens evolutionary pathways to drug resistance and treatment failure during Acinetobacter baumannii pneumonia in mice. Nat Microbiol 2022; 7:796–809 [View Article]
     [Google Scholar]
  54. Turner CB, Marshall CW, Cooper VS. Parallel genetic adaptation across environments differing in mode of growth or resource availability. Evol Lett 2018; 2:355–367 [View Article] [PubMed]
     [Google Scholar]
  55. Deatherage DE, Barrick JE. Identification of mutations in laboratory-evolved microbes from next-generation sequencing data using breseq. Methods Mol Biol 2014; 1151:165–188
     [Google Scholar]
  56. Alonso-Del Valle A, León-Sampedro R, Rodríguez-Beltrán J, DelaFuente J, Hernández-García M et al. Variability of plasmid fitness effects contributes to plasmid persistence in bacterial communities. Nat Commun 2021; 12:2653 [View Article] [PubMed]
     [Google Scholar]
  57. Muraski MJ, Nilsson EM, Fritz MJ, Richardson AR, Alexander RW et al. Adaptation to overflow metabolism by mutations that impair tRNA modification in experimentally evolved bacteria. mBio 2023; 14:e0028723 [View Article]
     [Google Scholar]
  58. Coyne S, Courvalin P, Périchon B. Efflux-mediated antibiotic resistance in Acinetobacter spp. Antimicrob Agents Chemother 2011; 55:947–953 [View Article] [PubMed]
     [Google Scholar]
  59. Lin F, Xu Y, Chang Y, Liu C, Jia X et al. Molecular characterization of reduced susceptibility to biocides in clinical isolates of Acinetobacter baumannii. Front Microbiol 2017; 8:1836 [View Article]
     [Google Scholar]
  60. Philippe C, Valcek A, Whiteway C, Robino E, Nesporova K et al. What are the reference strains of Acinetobacter baumannii referring to?. Microbiology 2022 [View Article]
     [Google Scholar]
  61. Elhosseiny NM, Elhezawy NB, Attia AS. Comparative proteomics analyses of Acinetobacter baumannii strains ATCC 17978 and AB5075 reveal the differential role of type II secretion system secretomes in lung colonization and ciprofloxacin resistance. Microb Pathog 2019; 128:20–27 [View Article] [PubMed]
     [Google Scholar]
  62. Greer ND. Tigecycline (Tygacil): the first in the glycylcycline class of antibiotics. Proc Bayl Univ Med Cent 2006; 19:155–161 [View Article] [PubMed]
     [Google Scholar]
  63. Hua X, He J, Wang J, Zhang L, Zhang L et al. Novel tigecycline resistance mechanisms in Acinetobacter baumannii mediated by mutations in adeS, rpoB, and rrf. Emerg Microbes Infect 2021; 10:1404–1417
     [Google Scholar]
  64. Lucaßen K, Müller C, Wille J, Xanthopoulou K, Hackel M et al. Prevalence of RND efflux pump regulator variants associated with tigecycline resistance in carbapenem-resistant Acinetobacter baumannii from a worldwide survey. J Antimicrob Chemother 2021; 76:1724–1730 [View Article] [PubMed]
     [Google Scholar]
  65. Hua X, Chen Q, Li X, Yu Y. Global transcriptional response of Acinetobacter baumannii to a subinhibitory concentration of tigecycline. Int J Antimicrob Agents 2014; 44:337–344 [View Article] [PubMed]
     [Google Scholar]
  66. Gao L, Ma X. Transcriptome analysis of Acinetobacter baumannii in rapid response to subinhibitory concentration of minocycline. Int J Environ Res Public Health 2022; 19:16095 [View Article] [PubMed]
     [Google Scholar]
  67. Dao TH, Echlin H, McKnight A, Marr ES, Junker J et al. Streptococcus pneumoniae favors tolerance via metabolic adaptation over resistance to circumvent fluoroquinolones. mBio 2024; 15:e0282823 [View Article] [PubMed]
     [Google Scholar]
  68. Kashyap S, Sharma P, Capalash N. Tobramycin stress induced differential gene expression in Acinetobacter baumannii. Curr Microbiol 2022; 79:88 [View Article] [PubMed]
     [Google Scholar]
  69. Vogwill T, Kojadinovic M, MacLean RC. Epistasis between antibiotic resistance mutations and genetic background shape the fitness effect of resistance across species of Pseudomonas. Proc Biol Sci 2016; 283:20160151 [View Article] [PubMed]
     [Google Scholar]
  70. Vogwill T, MacLean RC. The genetic basis of the fitness costs of antimicrobial resistance: a meta-analysis approach. Evol Appl 2015; 8:284–295 [View Article] [PubMed]
     [Google Scholar]
  71. Card KJ, Jordan JA, Lenski RE. Idiosyncratic variation in the fitness costs of tetracycline-resistance mutations in Escherichia coli. Evolution 2021; 75:1230–1238 [View Article] [PubMed]
     [Google Scholar]
  72. Harris KB, Flynn KM, Cooper VS. Polygenic adaptation and clonal interference enable sustained diversity in experimental Pseudomonas aeruginosa populations. Mol Biol Evol 2021; 38:5359–5375 [View Article] [PubMed]
     [Google Scholar]
  73. Chen Q, Li X, Zhou H, Jiang Y, Chen Y et al. Decreased susceptibility to tigecycline in Acinetobacter baumannii mediated by a mutation in trm encoding SAM-dependent methyltransferase. J Antimicrob Chemother 2014; 69:72–76 [View Article] [PubMed]
     [Google Scholar]
  74. Sharma S, Kaushik V, Kulshrestha M, Tiwari V. Different efflux pump systems in Acinetobacter baumannii and their role in multidrug resistance. Adv Exp Med Biol 2023; 1370:155–168 [View Article] [PubMed]
     [Google Scholar]
  75. Leus IV, Weeks JW, Bonifay V, Smith L, Richardson S et al. Substrate specificities and efflux efficiencies of RND efflux pumps of Acinetobacter baumannii. J Bacteriol 2018; 200:e00049-18 [View Article] [PubMed]
     [Google Scholar]
  76. Raza S, Gautam H, Mohapatra S, Sood S, Dhawan B et al. Molecular characterization of resistance-nodulation-cell division efflux pump genes in multidrug-resistant Acinetobacter baumannii. J Glob Infect Dis 2021; 13:177–179 [View Article] [PubMed]
     [Google Scholar]
  77. Huo W, Busch LM, Hamami E, Hernandez-Bird J, Marshall CW et al. Immunosuppression broadens evolutionary pathways to treatment failure during Acinetobacter baumannii pneumonia. BioRxiv 2021
     [Google Scholar]
  78. Harmand N, Gallet R, Martin G, Lenormand T. Evolution of bacteria specialization along an antibiotic dose gradient. Evol Lett 2018; 2:221–232 [View Article] [PubMed]
     [Google Scholar]
  79. Praski Alzrigat L, Huseby DL, Brandis G, Hughes D. Resistance/fitness trade-off is a barrier to the evolution of MarR inactivation mutants in Escherichia coli. J Antimicrob Chemother 2021; 76:77–83 [View Article] [PubMed]
     [Google Scholar]
  80. Levin BR, Perrot V, Walker N. Compensatory mutations, antibiotic resistance and the population genetics of adaptive evolution in bacteria. Genetics 2000; 154:985–997 [View Article] [PubMed]
     [Google Scholar]
  81. Angst DC, Hall AR. The cost of antibiotic resistance depends on evolutionary history in Escherichia coli. BMC Evol Biol 2013; 13:163 [View Article] [PubMed]
     [Google Scholar]
  82. Trindade S, Sousa A, Xavier KB, Dionisio F, Ferreira MG et al. Positive epistasis drives the acquisition of multidrug resistance. PLoS Genet 2009; 5:e1000578 [View Article] [PubMed]
     [Google Scholar]
  83. Ward H, Perron GG, Maclean RC. The cost of multiple drug resistance in Pseudomonas aeruginosa. J Evol Biol 2009; 22:997–1003 [View Article] [PubMed]
     [Google Scholar]
  84. Darby EM, Bavro VN, Dunn S, McNally A, Blair JMA. RND pumps across the genus Acinetobacter: AdeIJK is the universal efflux pump. Microb Genom 2023; 9:mgen000964 [View Article] [PubMed]
     [Google Scholar]
  85. Gaiarsa S, Bitar I, Comandatore F, Corbella M, Piazza A et al. Can insertion sequences proliferation influence genomic plasticity? Comparative analysis of Acinetobacter baumannii sequence type 78, a persistent clone in Italian hospitals. Front Microbiol 2019; 10:2080 [View Article] [PubMed]
     [Google Scholar]
  86. Wright MS, Mountain S, Beeri K, Adams MD. Assessment of insertion sequence mobilization as an adaptive response to oxidative stress in Acinetobacter baumannii using IS-seq. J Bacteriol 2017; 199:e00833-16 [View Article] [PubMed]
     [Google Scholar]
  87. Good BH, Rouzine IM, Balick DJ, Hallatschek O, Desai MM. Distribution of fixed beneficial mutations and the rate of adaptation in asexual populations. Proc Natl Acad Sci USA 2012; 109:4950–4955 [View Article] [PubMed]
     [Google Scholar]
  88. Desai MM, Fisher DS. Beneficial mutation selection balance and the effect of linkage on positive selection. Genetics 2007; 176:1759–1798 [View Article] [PubMed]
     [Google Scholar]
  89. Barnett M, Meister L, Rainey PB. Experimental evolution of evolvability. Science 2025; 387:eadr2756 [View Article] [PubMed]
     [Google Scholar]
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History shapes regulatory and evolutionary responses to tigecycline in two reference strains of Acinetobacter baumannii
Microbiology 171, 001570 (2025); https://doi.org/10.1099/mic.0.001570
/content/journal/micro/10.1099/mic.0.001570
/content/journal/micro/10.1099/mic.0.001570
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