Rapid evolution and host immunity drive the rise and fall of carbapenem resistance during an acute Pseudomonas aeruginosa infection.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
28 04 2021
Historique:
received: 22 09 2020
accepted: 31 03 2021
entrez: 29 4 2021
pubmed: 30 4 2021
medline: 13 5 2021
Statut: epublish

Résumé

It is well established that antibiotic treatment selects for resistance, but the dynamics of this process during infections are poorly understood. Here we map the responses of Pseudomonas aeruginosa to treatment in high definition during a lung infection of a single ICU patient. Host immunity and antibiotic therapy with meropenem suppressed P. aeruginosa, but a second wave of infection emerged due to the growth of oprD and wbpM meropenem resistant mutants that evolved in situ. Selection then led to a loss of resistance by decreasing the prevalence of low fitness oprD mutants, increasing the frequency of high fitness mutants lacking the MexAB-OprM efflux pump, and decreasing the copy number of a multidrug resistance plasmid. Ultimately, host immunity suppressed wbpM mutants with high meropenem resistance and fitness. Our study highlights how natural selection and host immunity interact to drive both the rapid rise, and fall, of resistance during infection.

Identifiants

pubmed: 33911082
doi: 10.1038/s41467-021-22814-9
pii: 10.1038/s41467-021-22814-9
pmc: PMC8080559
doi:

Substances chimiques

Anti-Bacterial Agents 0
Bacterial Outer Membrane Proteins 0
Bacterial Proteins 0
Membrane Transport Proteins 0
MexA protein, Pseudomonas aeruginosa 0
MexB protein, Pseudomonas aeruginosa 0
OprM protein, Pseudomonas aeruginosa 0
Porins 0
OprD protein, Pseudomonas aeruginosa 148412-32-2
Hydro-Lyases EC 4.2.1.-
wbpM protein, Pseudomonas aeruginosa EC 4.2.1.-
Meropenem FV9J3JU8B1

Banques de données

figshare
['10.6084/m9.figshare.14219129.v1']

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2460

Subventions

Organisme : Wellcome Trust
ID : 106918/Z/15/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 203141/Z/16/Z
Pays : United Kingdom

Références

Friedman, N. D., Temkin, E. & Carmeli, Y. The negative impact of antibiotic resistance. Clin. Microbiol. Infect. 22, 416–422 (2016).
pubmed: 26706614 doi: 10.1016/j.cmi.2015.12.002
Bell, B. G., Schellevis, F., Stobberingh, E., Goossens, H. & Pringle, M. A systematic review and meta-analysis of the effects of antibiotic consumption on antibiotic resistance. BMC Infect. Dis. 14, 13 (2014).
pubmed: 24405683 pmcid: 3897982 doi: 10.1186/1471-2334-14-13
Fish, D. N., Piscitelli, S. C. & Danziger, L. H. Development of resistance during antimicrobial therapy: a review of antibiotic classes and patient characteristics in 173 studies. Pharmacotherapy: J. Hum. Pharmacol. Drug Ther. 15, 279–291 (1995).
Shorr, A. F., Combes, A., Kollef, M. H. & Chastre, J. Methicillin-resistant Staphylococcus aureus prolongs intensive care unit stay in ventilator-associated pneumonia, despite initially appropriate antibiotic therapy. Crit. Care Med. 34, 700–706 (2006).
pubmed: 16505656 doi: 10.1097/01.CCM.0000201885.57697.21
Costelloe, C., Metcalfe, C., Lovering, A., Mant, D. & Hay, A. D. Effect of antibiotic prescribing in primary care on antimicrobial resistance in individual patients: systematic review and meta-analysis. BMJ 340, c2096 (2010).
pubmed: 20483949 doi: 10.1136/bmj.c2096
Malhotra-Kumar, S., Lammens, C., Coenen, S., Van Herck, K. & Goossens, H. Effect of azithromycin and clarithromycin therapy on pharyngeal carriage of macrolide-resistant streptococci in healthy volunteers: a randomised, double-blind, placebo-controlled study. Lancet 369, 482–490 (2007).
pubmed: 17292768 doi: 10.1016/S0140-6736(07)60235-9
Woolhouse, M. E., Webster, J. P., Domingo, E., Charlesworth, B. & Levin, B. R. Biological and biomedical implications of the co-evolution of pathogens and their hosts. Nat. Genet. 32, 569–577 (2002).
pubmed: 12457190 doi: 10.1038/ng1202-569
Levin, B. R., Perrot, V. & Walker, N. Compensatory mutations, antibiotic resistance and the population genetics of adaptive evolution in bacteria. Genetics 154, 985–997 (2000).
pubmed: 10757748 pmcid: 1460977 doi: 10.1093/genetics/154.3.985
Ankomah, P. & Levin, B. R. Exploring the collaboration between antibiotics and the immune response in the treatment of acute, self-limiting infections. Proc. Natl Acad. Sci. USA 111, 8331–8338 (2014).
pubmed: 24843148 doi: 10.1073/pnas.1400352111 pmcid: 4060691
Diaz Caballero, J. et al. Selective sweeps and parallel pathoadaptation drive Pseudomonas aeruginosa evolution in the cystic fibrosis lung. MBio 6, e00981–00915 (2015).
pubmed: 26330513 pmcid: 4556809 doi: 10.1128/mBio.00981-15
Diaz Caballero, J. et al. A genome-wide association analysis reveals a potential role for recombination in the evolution of antimicrobial resistance in Burkholderia multivorans. PLoS Pathog. 14, e1007453–e1007453 (2018).
pubmed: 30532201 pmcid: 6300292 doi: 10.1371/journal.ppat.1007453
Marvig, R. L., Sommer, L. M., Molin, S. & Johansen, H. K. Convergent evolution and adaptation of Pseudomonas aeruginosa within patients with cystic fibrosis. Nat. Genet. 47, 57 (2015).
pubmed: 25401299 doi: 10.1038/ng.3148
Smith, E. E. et al. Genetic adaptation by Pseudomonas aeruginosa to the airways of cystic fibrosis patients. Proc. Natl Acad. Sci. USA 103, 8487–8492 (2006).
pubmed: 16687478 doi: 10.1073/pnas.0602138103 pmcid: 1482519
Lieberman, T. D. et al. Genetic variation of a bacterial pathogen within individuals with cystic fibrosis provides a record of selective pressures. Nat. Genet. 46, 82 (2014).
pubmed: 24316980 doi: 10.1038/ng.2848
Xu, Y. et al. In vivo evolution of drug-resistant Mycobacterium tuberculosis in patients during long-term treatment. BMC Genomics 19, 640 (2018).
pubmed: 30157763 pmcid: 6116439 doi: 10.1186/s12864-018-5010-5
Liu, Q. et al. Within patient microevolution of Mycobacterium tuberculosis correlates with heterogeneous responses to treatment. Sci. Rep. 5, 17507 (2015).
pubmed: 26620446 pmcid: 4664930 doi: 10.1038/srep17507
Haque, M., Sartelli, M., McKimm, J. & Bakar, M. A. Health care-associated infections–an overview. Infect. Drug Resist. 11, 2321 (2018).
pubmed: 30532565 pmcid: 6245375 doi: 10.2147/IDR.S177247
Pena, C. et al. Carbapenem-resistant Pseudomonas aeruginosa: factors influencing multidrug-resistant acquisition in non-critically ill patients. Eur. J. Clin. Microbiol. Infect. Dis. 28, 519–522 (2009).
pubmed: 18949495 doi: 10.1007/s10096-008-0645-9
Juan, C., Peña, C. & Oliver, A. Host and pathogen biomarkers for severe Pseudomonas aeruginosa infections. J. Infect. Dis. 215, S44–S51 (2017).
pubmed: 28375513 doi: 10.1093/infdis/jiw299
Kang, C.-I. et al. Pseudomonas aeruginosa bacteremia: risk factors for mortality and influence of delayed receipt of effective antimicrobial therapy on clinical outcome. Clin. Infect. Dis. 37, 745–751 (2003).
pubmed: 12955633 doi: 10.1086/377200
Aloush, V., Navon-Venezia, S., Seigman-Igra, Y., Cabili, S. & Carmeli, Y. Multidrug-resistant Pseudomonas aeruginosa: risk factors and clinical impact. Antimicrobial Agents Chemother. 50, 43–48 (2006).
doi: 10.1128/AAC.50.1.43-48.2006
Botelho, J., Grosso, F. & Peixe, L. Antibiotic resistance in Pseudomonas aeruginosa–Mechanisms, epidemiology and evolution. Drug Resist. Updates 44, 100640 (2019).
doi: 10.1016/j.drup.2019.07.002
Breidenstein, E. B., de la Fuente-Núñez, C. & Hancock, R. E. Pseudomonas aeruginosa: all roads lead to resistance. Trends Microbiol. 19, 419–426 (2011).
pubmed: 21664819 doi: 10.1016/j.tim.2011.04.005
Gellatly, S. L. & Hancock, R. E. Pseudomonas aeruginosa: new insights into pathogenesis and host defenses. Pathog. Dis. 67, 159–173 (2013).
pubmed: 23620179 doi: 10.1111/2049-632X.12033
Morita, Y., Tomida, J. & Kawamura, Y. Responses of Pseudomonas aeruginosa to antimicrobials. Front. Microbiol. 4, 422 (2014).
pubmed: 24409175 pmcid: 3884212 doi: 10.3389/fmicb.2013.00422
Gad, G. F., El-Domany, R. A. & Ashour, H. M. Antimicrobial susceptibility profile of Pseudomonas aeruginosa isolates in Egypt. J. Urol. 180, 176–181 (2008).
pubmed: 18499192 doi: 10.1016/j.juro.2008.03.081
Paling, F. P. et al. Rationale and design of ASPIRE-ICU: a prospective cohort study on the incidence and predictors of Staphylococcus aureus and Pseudomonas aeruginosa pneumonia in the ICU. BMC Infect. Dis. 17, 643 (2017).
pubmed: 28946849 pmcid: 5613521 doi: 10.1186/s12879-017-2739-4
Michalopoulos, A. S. & Falagas, M. E. Colistin: recent data on pharmacodynamics properties and clinical efficacy in critically ill patients. Ann. Intensive Care 1, 1–6 (2011).
doi: 10.1186/2110-5820-1-30
McPhee, J. B., Lewenza, S. & Hancock, R. E. Cationic antimicrobial peptides activate a two‐component regulatory system, PmrA‐PmrB, that regulates resistance to polymyxin B and cationic antimicrobial peptides in Pseudomonas aeruginosa. Mol. Microbiol. 50, 205–217 (2003).
pubmed: 14507375 doi: 10.1046/j.1365-2958.2003.03673.x
Montero, M. M. et al. Colistin plus meropenem combination is synergistic in vitro against extensively drug-resistant Pseudomonas aeruginosa, including high-risk clones. J. Glob. Antimicrob. Resist. 18, 37–44 (2019).
pubmed: 31154007 doi: 10.1016/j.jgar.2019.04.012
Nicolau, D. P. Pharmacokinetic and pharmacodynamic properties of meropenem. Clin. Infect. Dis. 47, S32–S40 (2008).
pubmed: 18713048 doi: 10.1086/590064
Lopatkin, A. J. et al. Bacterial metabolic state more accurately predicts antibiotic lethality than growth rate. Nat. Microbiol. 4, 2109–2117 (2019).
pubmed: 31451773 pmcid: 6879803 doi: 10.1038/s41564-019-0536-0
Satlin, M. J. et al. Clinical and Laboratory Standards Institute (CLSI) and European Committee on Antimicrobial Susceptibility Testing (EUCAST) position statements on polymyxin B and colistin clinical breakpoints. Clin. Infect. Dis. 71, e523–e529 (2020).
Poole, K. Multidrug efflux pumps and antimicrobial resistance in Pseudomonas aeruginosa and related organisms. J. Mol. Microbiol. Biotechnol. 3, 255–264 (2001).
pubmed: 11321581
Fernández-Cuenca, F. et al. Nosocomial outbreak linked to a flexible gastrointestinal endoscope contaminated with an amikacin-resistant ST17 clone of Pseudomonas aeruginosa. Eur. J. Clin. Microbiol. Infect. Dis. 39, 1837–1844 (2020).
Skurnik, D. et al. Enhanced in vivo fitness of carbapenem-resistant oprD mutants of Pseudomonas aeruginosa revealed through high-throughput sequencing. Proc. Natl Acad. Sci. USA 110, 20747–20752 (2013).
pubmed: 24248354 doi: 10.1073/pnas.1221552110 pmcid: 3870709
King, J. D., Kocíncová, D., Westman, E. L. & Lam, J. S. Lipopolysaccharide biosynthesis in Pseudomonas aeruginosa. Innate Immun. 15, 261–312 (2009).
pubmed: 19710102 doi: 10.1177/1753425909106436
Tognon, M. et al. Co-evolution with Staphylococcus aureus leads to lipopolysaccharide alterations in Pseudomonas aeruginosa. ISME J. 11, 2233–2243 (2017).
pubmed: 28548661 pmcid: 5607365 doi: 10.1038/ismej.2017.83
Mah, T.-F. C. & O’Toole, G. A. Mechanisms of biofilm resistance to antimicrobial agents. Trends Microbiol. 9, 34–39 (2001).
pubmed: 11166241 doi: 10.1016/S0966-842X(00)01913-2
Brauner, A., Fridman, O., Gefen, O. & Balaban, N. Q. Distinguishing between resistance, tolerance and persistence to antibiotic treatment. Nat. Rev. Microbiol. 14, 320–330 (2016).
pubmed: 27080241 doi: 10.1038/nrmicro.2016.34
Andersson, D. I. & Hughes, D. Antibiotic resistance and its cost: is it possible to reverse resistance? Nat. Rev. Microbiol. 8, 260–271 (2010).
pubmed: 20208551 doi: 10.1038/nrmicro2319
Vogwill, T. & MacLean, R. C. The genetic basis of the fitness costs of antimicrobial resistance: a meta‐analysis approach. Evolut. Appl. 8, 284–295 (2015).
doi: 10.1111/eva.12202
Roux, D. et al. Fitness cost of antibiotic susceptibility during bacterial infection. Sci. Transl. Med. 7, 297ra114–297ra114 (2015).
pubmed: 26203082 doi: 10.1126/scitranslmed.aab1621
Winstanley, C., O’Brien, S. & Brockhurst, M. A. Pseudomonas aeruginosa evolutionary adaptation and diversification in cystic fibrosis chronic lung infections. Trends Microbiol. 24, 327–337 (2016).
pubmed: 26946977 pmcid: 4854172 doi: 10.1016/j.tim.2016.01.008
Evans, B. A. & Amyes, S. G. OXA β-lactamases. Clin. Microbiol. Rev. 27, 241–263 (2014).
pubmed: 24696435 pmcid: 3993105 doi: 10.1128/CMR.00117-13
Antunes, N. T. et al. Class D β-lactamases: are they all carbapenemases? Antimicrobial Agents Chemother. 58, 2119–2125 (2014).
doi: 10.1128/AAC.02522-13
Ma, P., Laibinis, H. H., Ernst, C. M. & Hung, D. T. Carbapenem resistance caused by high-level expression of OXA-663 β-lactamase in an OmpK36-deficient Klebsiella pneumoniae clinical isolate. Antimicrob. Agents Chemother. 62, e01281-18 (2018).
San Millan, A. et al. Integrative analysis of fitness and metabolic effects of plasmids in Pseudomonas aeruginosa PAO1. ISME J. 12, 3014–3024 (2018).
pubmed: 30097663 pmcid: 6246594 doi: 10.1038/s41396-018-0224-8
Silva, R. F. et al. Pervasive sign epistasis between conjugative plasmids and drug-resistance chromosomal mutations. PLoS Genet. 7, e1002181 (2011).
pubmed: 21829372 pmcid: 3145620 doi: 10.1371/journal.pgen.1002181
Sadikot, R. T., Blackwell, T. S., Christman, J. W. & Prince, A. S. Pathogen-host interactions in Pseudomonas aeruginosa pneumonia. Am. J. Respiratory Crit. Care Med. 171, 1209–1223 (2005).
doi: 10.1164/rccm.200408-1044SO
Mizgerd, J. P. Molecular mechanisms of neutrophil recruitment elicited by bacteria in the lungs. Semin. Immunol. 14, 123–132 (2002).
pubmed: 11978084 doi: 10.1006/smim.2001.0349
Ishimoto, H. et al. Identification of hBD-3 in respiratory tract and serum: the increase in pneumonia. Eur. Respiratory J. 27, 253–260 (2006).
doi: 10.1183/09031936.06.00105904
Artemova, T., Gerardin, Y., Dudley, C., Vega, N. M. & Gore, J. Isolated cell behavior drives the evolution of antibiotic resistance. Mol. Syst. Biol. 11, 822 (2015).
pubmed: 26227664 pmcid: 4547850 doi: 10.15252/msb.20145888
Papp-Wallace, K. M., Endimiani, A., Taracila, M. A. & Bonomo, R. A. Carbapenems: past, present, and future. Antimicrob. Agents Chemother. 55, 4943–4960 (2011).
pubmed: 21859938 pmcid: 3195018 doi: 10.1128/AAC.00296-11
Yayan, J., Ghebremedhin, B. & Rasche, K. Antibiotic resistance of Pseudomonas aeruginosa in pneumonia at a single university hospital center in Germany over a 10-year period. PLoS ONE 10, e0139836 (2015).
Sabuda, D. M. et al. Utilization of colistin for treatment of multidrug-resistant Pseudomonas aeruginosa. Can. J. Infect. Dis. Med. Microbiol. 19, 413–418 (2008).
pubmed: 19436571 pmcid: 2663472 doi: 10.1155/2008/743197
Karslake, J., Maltas, J., Brumm, P. & Wood, K. B. Population density modulates drug inhibition and gives rise to potential bistability of treatment outcomes for bacterial infections. PLoS Computational Biol. 12, e1005098 (2016).
doi: 10.1371/journal.pcbi.1005098
Alexander, H. K. & MacLean, R. C. Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells. Proc. Natl Acad. Sci. USA 117, 19455–19464 (2020).
pubmed: 32703812 doi: 10.1073/pnas.1919672117 pmcid: 7431077
Zur Wiesch, P. A., Kouyos, R., Engelstädter, J., Regoes, R. R. & Bonhoeffer, S. Population biological principles of drug-resistance evolution in infectious diseases. Lancet Infect. Dis. 11, 236–247 (2011).
pubmed: 21371657 doi: 10.1016/S1473-3099(10)70264-4
van Dorp, L. et al. Rapid phenotypic evolution in multidrug-resistant Klebsiella pneumoniae hospital outbreak strains. Microb. Genom. 5, e000263 (2019).
Rodríguez-Beltrán, J., DelaFuente, J., León-Sampedro, R., MacLean, R. C. & San Millán, Á. Beyond horizontal gene transfer: the role of plasmids in bacterial evolution. Nat. Rev. Microbiol. 1, 1–13 (2021).
San Millan, A., Escudero, J. A., Gifford, D. R., Mazel, D. & MacLean, R. C. Multicopy plasmids potentiate the evolution of antibiotic resistance in bacteria. Nat. Ecol. Evolution 1, 1–8 (2016).
doi: 10.1038/s41559-016-0010
Matzneller, P. et al. Colistin reduces LPS-triggered inflammation in a human sepsis model in vivo: a randomized controlled trial. Clin. Pharmacol. Therapeutics 101, 773–781 (2017).
doi: 10.1002/cpt.582
Lázár, V. et al. Antibiotic-resistant bacteria show widespread collateral sensitivity to antimicrobial peptides. Nat. Microbiol. 3, 718–731 (2018).
pubmed: 29795541 pmcid: 6544545 doi: 10.1038/s41564-018-0164-0
Foster, K. R. & Bell, T. Competition, not cooperation, dominates interactions among culturable microbial species. Curr. Biol. 22, 1845–1850 (2012).
pubmed: 22959348 doi: 10.1016/j.cub.2012.08.005
Schmidtchen, A., Frick, I. M., Andersson, E., Tapper, H. & Bjorck, L. Proteinases of common pathogenic bacteria degrade and inactivate the antibacterial peptide LL-37. Mol. Microbiol. 46, 157–168 (2002).
pubmed: 12366839 doi: 10.1046/j.1365-2958.2002.03146.x
Didelot, X., Walker, A. S., Peto, T. E., Crook, D. W. & Wilson, D. J. Within-host evolution of bacterial pathogens. Nat. Rev. Microbiol. 14, 150 (2016).
pubmed: 26806595 pmcid: 5053366 doi: 10.1038/nrmicro.2015.13
Costello, E. K., Stagaman, K., Dethlefsen, L., Bohannan, B. J. & Relman, D. A. The application of ecological theory toward an understanding of the human microbiome. Science 336, 1255–1262 (2012).
pubmed: 22674335 pmcid: 4208626 doi: 10.1126/science.1224203
Jernberg, C., Löfmark, S., Edlund, C. & Jansson, J. K. Long-term impacts of antibiotic exposure on the human intestinal microbiota. Microbiology 156, 3216–3223 (2010).
pubmed: 20705661 doi: 10.1099/mic.0.040618-0
Raza, A. et al. Oral meropenem for superbugs: challenges and opportunities. Drug Discov.Today 26, 551–560 (2020).
Jorth, P. et al. Regional isolation drives bacterial diversification within cystic fibrosis lungs. Cell Host Microbe 18, 307–319 (2015).
pubmed: 26299432 pmcid: 4589543 doi: 10.1016/j.chom.2015.07.006
Chung, H. et al. Global and local selection acting on the pathogen Stenotrophomonas maltophilia in the human lung. Nat. Commun. 8, 1–7 (2017).
doi: 10.1038/ncomms14078
The European Committee on Antimicrobial Susceptibility Testing. EUCAST Reading Guide for Broth Microdilution. http://www.eucast.org (2019).
The European Committee on Antimicrobial Susceptibility Testing. Breakpoint Tables for interpretation of MICs and Zone Diameters, Version 9.0 http://www.eucast.org (2019).
Stover, C. K. et al. Complete genome sequence of Pseudomonas aeruginosa PAO1, an opportunistic pathogen. Nature 406, 959 (2000).
pubmed: 10984043 doi: 10.1038/35023079
Team, R. C. R. A Language and Environment for Statistical Computing. (Team, R. C. R, 2013).
Liberati, N. T. et al. An ordered, nonredundant library of Pseudomonas aeruginosa strain PA14 transposon insertion mutants. Proc. Natl Acad. Sci. USA 103, 2833–2838 (2006).
pubmed: 16477005 doi: 10.1073/pnas.0511100103 pmcid: 1413827
Juan, C., Moyá, B., Pérez, J. L. & Oliver, A. Stepwise upregulation of the Pseudomonas aeruginosa chromosomal cephalosporinase conferring high-level β-lactam resistance involves three AmpD homologues. Antimicrob. Agents Chemother. 50, 1780–1787 (2006).
pubmed: 16641450 pmcid: 1472203 doi: 10.1128/AAC.50.5.1780-1787.2006
Oh, H., Stenhoff, J., Jalal, S. & Wretlind, B. Role of efflux pumps and mutations in genes for topoisomerases II and IV in fluoroquinolone-resistant Pseudomonas aeruginosa strains. Microb. Drug Resist. 9, 323–328 (2003).
pubmed: 15000738 doi: 10.1089/107662903322762743
Cabot, G. et al. Overexpression of AmpC and efflux pumps in Pseudomonas aeruginosa isolates from bloodstream infections: prevalence and impact on resistance in a Spanish multicenter study. Antimicrob. Agents Chemother. 55, 1906–1911 (2011).
pubmed: 21357294 pmcid: 3088238 doi: 10.1128/AAC.01645-10
Koren, S. et al. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res. 27, 722–736 (2017).
pubmed: 28298431 pmcid: 5411767 doi: 10.1101/gr.215087.116
Hunt, M. et al. Circlator: automated circularization of genome assemblies using long sequencing reads. Genome Biol. 16, 294 (2015).
pubmed: 26714481 pmcid: 4699355 doi: 10.1186/s13059-015-0849-0
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
pubmed: 24695404 pmcid: 4103590 doi: 10.1093/bioinformatics/btu170
Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Computational Biol. 19, 455–477 (2012).
doi: 10.1089/cmb.2012.0021
Arnold, M. F. et al. Genome-wide sensitivity analysis of the microsymbiont Sinorhizobium meliloti to symbiotically important, defensin-like host peptides. MBio 8, e01060–01017 (2017).
pubmed: 28765224 pmcid: 5539429 doi: 10.1128/mBio.01060-17
Lee, D. G. et al. Genomic analysis reveals that Pseudomonas aeruginosa virulence is combinatorial. Genome Biol. 7, R90 (2006).
pubmed: 17038190 pmcid: 1794565 doi: 10.1186/gb-2006-7-10-r90
Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069 (2014).
pubmed: 24642063 doi: 10.1093/bioinformatics/btu153
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357 (2012).
pubmed: 22388286 pmcid: 3322381 doi: 10.1038/nmeth.1923
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
pubmed: 19505943 pmcid: 2723002 doi: 10.1093/bioinformatics/btp352
Broad Institute. Picard Toolkit (Broad Institute, GitHub repository, 2019).
DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491 (2011).
pubmed: 21478889 pmcid: 3083463 doi: 10.1038/ng.806
del Barrio-Tofiño, E. et al. Spanish nationwide survey on Pseudomonas aeruginosa antimicrobial resistance mechanisms and epidemiology. J. Antimicrob. Chemother. 74, 1825–1835 (2019).
pubmed: 30989186 doi: 10.1093/jac/dkz147
López-Causapé, C. et al. Evolution of the Pseudomonas aeruginosa mutational resistome in an international cystic fibrosis clone. Sci. Rep. 7, 1–15 (2017).
doi: 10.1038/s41598-017-05621-5
Cabot, G. et al. Deciphering the resistome of the widespread Pseudomonas aeruginosa sequence type 175 international high-risk clone through whole-genome sequencing. Antimicrob. Agents Chemother. 60, 7415–7423 (2016).
pubmed: 27736752 pmcid: 5119024 doi: 10.1128/AAC.01720-16
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
pubmed: 19451168 pmcid: 2705234 doi: 10.1093/bioinformatics/btp324
McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
pubmed: 20644199 pmcid: 2928508 doi: 10.1101/gr.107524.110
Deatherage, D. E. & Barrick, J. E. in Engineering and Analyzing Multicellular Systems (eds Lianhong, S. & Wenying, S.) 165–188 (Springer, 2014).
Gabrielaite, M. & Marvig, R. L. GenAPI: a tool for gene absence-presence identification in fragmented bacterial genome sequences. BMC Bioinformatics 21, 320 (2019).
Krzywinski, M. et al. Circos: an information aesthetic for comparative genomics. Genome Res. 19, 1639–1645 (2009).
pubmed: 19541911 pmcid: 2752132 doi: 10.1101/gr.092759.109

Auteurs

Rachel Wheatley (R)

University of Oxford, Department of Zoology, Oxford, UK.

Julio Diaz Caballero (J)

University of Oxford, Department of Zoology, Oxford, UK.

Natalia Kapel (N)

University of Oxford, Department of Zoology, Oxford, UK.

Fien H R de Winter (FHR)

Laboratory of Medical Microbiology, Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium.

Pramod Jangir (P)

University of Oxford, Department of Zoology, Oxford, UK.

Angus Quinn (A)

University of Oxford, Department of Zoology, Oxford, UK.

Ester Del Barrio-Tofiño (E)

Hospital Universitario Son Espases, Palma de Mallorca, Spain.

Carla López-Causapé (C)

Hospital Universitario Son Espases, Palma de Mallorca, Spain.

Jessica Hedge (J)

University of Oxford, Department of Zoology, Oxford, UK.

Gabriel Torrens (G)

Hospital Universitario Son Espases, Palma de Mallorca, Spain.

Thomas Van der Schalk (T)

Laboratory of Medical Microbiology, Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium.

Basil Britto Xavier (BB)

Laboratory of Medical Microbiology, Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium.

Felipe Fernández-Cuenca (F)

Departamento de Medicina, Universidad de Sevilla, Seville, Spain.

Angel Arenzana (A)

Departamento de Medicina, Universidad de Sevilla, Seville, Spain.

Claudia Recanatini (C)

Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.

Leen Timbermont (L)

Laboratory of Medical Microbiology, Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium.

Frangiscos Sifakis (F)

Boehringer Ingelheim Pharmaceuticals, Inc, Ridgefield, CT, USA.

Alexey Ruzin (A)

Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA.

Omar Ali (O)

Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA.
Viela Bio, Gaithersburg, MD, USA.

Christine Lammens (C)

Laboratory of Medical Microbiology, Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium.

Herman Goossens (H)

Laboratory of Medical Microbiology, Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium.

Jan Kluytmans (J)

Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Microvida Laboratory for Medical Microbiology and Department of Infection Control, Amphia Hospital, Breda, The Netherlands.

Samir Kumar-Singh (S)

Laboratory of Medical Microbiology, Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium.
Molecular Pathology Group, Faculty of Medicine-Laboratory of Cell Biology and Histology, University of Antwerp, Wilrijk, Belgium.

Antonio Oliver (A)

Hospital Universitario Son Espases, Palma de Mallorca, Spain.

Surbhi Malhotra-Kumar (S)

Laboratory of Medical Microbiology, Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium.

Craig MacLean (C)

University of Oxford, Department of Zoology, Oxford, UK. craig.maclean@zoo.ox.ac.uk.

Articles similaires

Genome, Chloroplast Phylogeny Genetic Markers Base Composition High-Throughput Nucleotide Sequencing

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C

Classifications MeSH