Major role of iron uptake systems in the intrinsic extra-intestinal virulence of the genus Escherichia revealed by a genome-wide association study
Autoři:
Marco Galardini aff001; Olivier Clermont aff002; Alexandra Baron aff002; Bede Busby aff003; Sara Dion aff002; Sören Schubert aff004; Pedro Beltrao aff001; Erick Denamur aff002
Působiště autorů:
EMBL-EBI, Wellcome Genome Campus, Cambridge, United Kingdom
aff001; Université de Paris, IAME, UMR1137, INSERM, Paris, France
aff002; Genome Biology Unit, EMBL, Heidelberg, Germany
aff003; Max von Pettenkofer Institute of Hygiene and Medical Microbiology, Faculty of Medicine, LMU Munich, Germany
aff004; AP-HP, Laboratoire de Génétique Moléculaire, Hôpital Bichat, Paris, France
aff005
Vyšlo v časopise:
Major role of iron uptake systems in the intrinsic extra-intestinal virulence of the genus Escherichia revealed by a genome-wide association study. PLoS Genet 16(10): e32767. doi:10.1371/journal.pgen.1009065
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1009065
Souhrn
The genus Escherichia is composed of several species and cryptic clades, including E. coli, which behaves as a vertebrate gut commensal, but also as an opportunistic pathogen involved in both diarrheic and extra-intestinal diseases. To characterize the genetic determinants of extra-intestinal virulence within the genus, we carried out an unbiased genome-wide association study (GWAS) on 370 commensal, pathogenic and environmental strains representative of the Escherichia genus phylogenetic diversity and including E. albertii (n = 7), E. fergusonii (n = 5), Escherichia clades (n = 32) and E. coli (n = 326), tested in a mouse model of sepsis. We found that the presence of the high-pathogenicity island (HPI), a ~35 kbp gene island encoding the yersiniabactin siderophore, is highly associated with death in mice, surpassing other associated genetic factors also related to iron uptake, such as the aerobactin and the sitABCD operons. We confirmed the association in vivo by deleting key genes of the HPI in E. coli strains in two phylogenetic backgrounds. We then searched for correlations between virulence, iron capture systems and in vitro growth in a subset of E. coli strains (N = 186) previously phenotyped across growth conditions, including antibiotics and other chemical and physical stressors. We found that virulence and iron capture systems are positively correlated with growth in the presence of numerous antibiotics, probably due to co-selection of virulence and resistance. We also found negative correlations between virulence, iron uptake systems and growth in the presence of specific antibiotics (i.e. cefsulodin and tobramycin), which hints at potential “collateral sensitivities” associated with intrinsic virulence. This study points to the major role of iron capture systems in the extra-intestinal virulence of the genus Escherichia.
Klíčová slova:
Antibiotic resistance – Antibiotics – Escherichia – Genome-wide association studies – Mammalian genomics – Mouse models – Operons – Virulence factors
Zdroje
1. Tenaillon O, Skurnik D, Picard B, Denamur E. The population genetics of commensal Escherichia coli. Nat. Rev. Microbiol. 2010;8:207–217. doi: 10.1038/nrmicro2298 20157339
2. Croxen MA, Brett Finlay B. Molecular mechanisms of Escherichia coli pathogenicity. Nature Reviews Microbiology. 2010;8:26–38. doi: 10.1038/nrmicro2265 19966814
3. Oaks JL, Besser TE, Walk ST, Gordon DM, Beckmen KB, Burek KA, et al. Escherichia albertii in wild and domestic birds. Emerg. Infect. Dis. 2010;16:638–46. doi: 10.3201/eid1604.090695 20350378
4. Clermont O, Gordon DM, Brisse S, Walk ST, Denamur E. Characterization of the cryptic Escherichia lineages: rapid identification and prevalence. Environ. Microbiol. 2011;13:2468–2477. doi: 10.1111/j.1462-2920.2011.02519.x 21651689
5. Blyton MDJ, Pi H, Vangchhia B, Abraham S, Trott DJ, Johnson JR, et al. Genetic Structure and Antimicrobial Resistance of Escherichia coli and Cryptic Clades in Birds with Diverse Human Associations. Appl. Environ. Microbiol. 2015;81:5123–5133. doi: 10.1128/AEM.00861-15 26002899
6. Russo TA, Johnson JR. Medical and economic impact of extraintestinal infections due to Escherichia coli: focus on an increasingly important endemic problem. Microbes Infect. 2003;5:449–456. doi: 10.1016/s1286-4579(03)00049-2 12738001
7. Lefort A, Panhard X, Clermont O, Woerther P-L, Branger C, Mentré F, et al. Host Factors and Portal of Entry Outweigh Bacterial Determinants to Predict the Severity of Escherichia coli Bacteremia. Journal of Clinical Microbiology. 2011;49:777–783. doi: 10.1128/JCM.01902-10 21177892
8. Burdet C, Clermont O, Bonacorsi S, Laouénan C, Bingen E, Aujard Y, et al. Escherichia coli bacteremia in children: age and portal of entry are the main predictors of severity. Pediatr. Infect. Dis. J. 2014;33:872–879. doi: 10.1097/INF.0000000000000309 25222308
9. Abernethy JK, Johnson AP, Guy R, Hinton N, Sheridan EA, Hope RJ.Thirty day all-cause mortality in patients with Escherichia coli bacteraemia in England. Clin. Microbiol. Infect. 2015;21:251.e1–8. doi: 10.1016/j.cmi.2015.01.001 25698659
10. de Lastours V, Laouénan C, Royer G, Carbonnelle E, Lepeule R, Esposito-Farèse M, et al. Mortality in Escherichia coli bloodstream infections: antibiotic resistance still does not make it. J. Antimicrob. Chemother. 2020;75:2334–2343. doi: 10.1093/jac/dkaa161 32417924
11. Vihta K-D, Stoesser N, Llewelyn MJ, Phuong Quan T, Davies T, Fawcett NJ, et al. Trends over time in Escherichia coli bloodstream infections, urinary tract infections, and antibiotic susceptibilities in Oxfordshire, UK, 1998–2016: a study of electronic health records. The Lancet Infectious Diseases. 2018;18:1138–1149. doi: 10.1016/S1473-3099(18)30353-0 30126643
12. Cassini A, Högberg LD, Plachouras D, Quattrocchi A, Hoxha A, Simonsen GS, et al. Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis. Lancet Infect. Dis. 2019;19:56–66. doi: 10.1016/S1473-3099(18)30605-4 30409683
13. Baudron CR, Panhard X, Clermont O, Mentré F, Fantin B, Denamur E, et al. Escherichia coli bacteraemia in adults: age-related differences in clinical and bacteriological characteristics, and outcome. Epidemiology & Infection. 2014;142:2672–2683.
14. Picard B, Garcia JS, Gouriou S, Duriez P, Brahimi N, Bingen E, et al. The link between phylogeny and virulence in Escherichia coli extraintestinal infection. Infect. Immun. 1999;67:546–553. doi: 10.1128/IAI.67.2.546-553.1999 9916057
15. Johnson JR, Kuskowski M. Clonal origin, virulence factors, and virulence. Infection and immunity. 2000;68:424–425. 10636718
16. Tourret J, Diard M, Garry L, Matic I, Denamur E. Effects of single and multiple pathogenicity island deletions on uropathogenic Escherichia coli strain 536 intrinsic extra-intestinal virulence. Int. J. Med. Microbiol. 2010;300:435–439. doi: 10.1016/j.ijmm.2010.04.013 20510652
17. Ingle DJ, Clermont O, Skurnik D, Denamur E, Walk ST, Gordon DM, et al. Biofilm formation by and thermal niche and virulence characteristics of Escherichia spp. Appl. Environ. Microbiol. 2011;77:2695–2700. doi: 10.1128/AEM.02401-10 21335385
18. Smati M, Magistro G, Adiba S, Wieser A, Picard B, Schubert S, et al. Strain-specific impact of the high-pathogenicity island on virulence in extra-intestinal pathogenic Escherichia coli. Int. J. Med. Microbiol. 2017;307:44–56. doi: 10.1016/j.ijmm.2016.11.004 27923724
19. Johnson JR, Russo TA. Molecular Epidemiology of Extraintestinal Pathogenic Escherichia coli. EcoSal Plus. 2018:8.
20. Schubert S, Cuenca S, Fischer D, Heesemann J. High-pathogenicity island of Yersinia pestis in enterobacteriaceae isolated from blood cultures and urine samples: prevalence and functional expression. J. Infect. Dis. 2000;182:1268–1271.
21. Paauw A, Leverstein-van Hall MA, van Kessel KPM., Verhoef J, Fluit AC. Yersiniabactin reduces the respiratory oxidative stress response of innate immune cells. PLoS One. 2009;4:e8240. doi: 10.1371/journal.pone.0008240 20041108
22. Schubert S, Picard B, Gouriou S, Heesemann J, Denamur E. Yersinia high-pathogenicity island contributes to virulence in Escherichia coli causing extraintestinal infections. Infect. Immun. 2002;70:5335–5337. doi: 10.1128/iai.70.9.5335-5337.2002 12183596
23. Earle SG, Wu C-H, Charlesworth J, Stoesser N, Gordon NC, Walker TM, et al. Identifying lineage effects when controlling for population structure improves power in bacterial association studies. Nature Microbiology. 2016;1;1–8.
24. Lees JA, Vehkala M, Välimäki N, Harris SR, Chewapreecha C, Croucher NJ, et al. Sequence element enrichment analysis to determine the genetic basis of bacterial phenotypes. Nat. Commun. 2016;7:12797. doi: 10.1038/ncomms12797 27633831
25. Lees J, Galardini M, Bentley SD, Weiser JN. pyseer: a comprehensive tool for microbial pangenome-wide association studies. bioRxiv. 2018.
26. Jaillard M, Lima L, Tournoud M, Mahé P, van Belkum A, Lacroix V, Jacob L, et al. A fast and agnostic method for bacterial genome-wide association studies: Bridging the gap between k-mers and genetic events. PLoS Genet. 2018;14:e1007758. doi: 10.1371/journal.pgen.1007758 30419019
27. Johnson JR, Clermont O, Menard M, Kuskowski MA, Picard B, Denamur E, et al. Experimental mouse lethality of Escherichia coli isolates, in relation to accessory traits, phylogenetic group, and ecological source. J. Infect. Dis. 2006;194:1141–1150. doi: 10.1086/507305 16991090
28. Galardini M, Koumoutsi A, Herrera-Dominguez L, Cordero Varela JA, Telzerow A, Wagih O, et al. Phenotype inference in an Escherichia coli strain panel. Elife. 2017;6:1–19.
29. Power RA, Parkhill J, de Oliveira, T. Microbial genome-wide association studies: lessons from human GWAS. Nat. Rev. Genet. 2016;18:41–50. doi: 10.1038/nrg.2016.132 27840430
30. Clermont O, Christenson JK, Denamur E, Gordon DM. The Clermont Escherichia coli phylo-typing method revisited: improvement of specificity and detection of new phylo-groups. Environ. Microbiol. Rep. 2013;5:58–65. doi: 10.1111/1758-2229.12019 23757131
31. Ochman H, Selander RK. Standard reference strains of Escherichia coli from natural populations. J. Bacteriol. 1984;157:690–693. doi: 10.1128/JB.157.2.690-693.1984 6363394
32. Lescat M, Clermont O, Woerther PL, Glodt J, Dion S, Skurnik D, et al. Commensal Escherichia coli strains in Guiana reveal a high genetic diversity with host-dependant population structure. Environ. Microbiol. Rep. 2013;5:49–57. doi: 10.1111/j.1758-2229.2012.00374.x 23757130
33. Bleibtreu A, Clermont O, Darlu P, Glodt J, Branger C, Picard B, et al. The rpoS gene is predominantly inactivated during laboratory storage and undergoes source-sink evolution in Escherichia coli species. J. Bacteriol. 2014;196:4276–4284. doi: 10.1128/JB.01972-14 25266386
34. Skurnik D, Clermont O, Guillard T, Launay A, Danilchanka O, Pons S, et al. Emergence of Antimicrobial-Resistant Escherichia coli of Animal Origin Spreading in Humans. Mol. Biol. Evol. 2016;33:898–914. doi: 10.1093/molbev/msv280 26613786
35. Massot M, Daubié A-S, Clermont O, Jauréguy F, Couffignal C, Dahbi G, et al. Phylogenetic, virulence and antibiotic resistance characteristics of commensal strain populations of Escherichia coli from community subjects in the Paris area in 2010 and evolution over 30 years. Microbiology. 2016;162:642–650. doi: 10.1099/mic.0.000242 26822436
36. Nowrouzian FL, Clermont O, Edin M, Östblom A, Denamur E, Wold AE, et al. Escherichia coli B2 Phylogenetic Subgroups in the Infant Gut Microbiota: Predominance of Uropathogenic Lineages in Swedish Infants and Enteropathogenic Lineages in Pakistani Infants. Appl. Environ. Microbiol. 2019;85.
37. Bourrel AS, Poirel L, Royer G, Darty M, Vuillemin X, Kieffer N, et al. Colistin resistance in Parisian inpatient faecal Escherichia coli as the result of two distinct evolutionary pathways. J. Antimicrob. Chemother. 2019;74:1521–1530. doi: 10.1093/jac/dkz090 30863849
38. Moissenet D, Salauze B, Clermont O, Bingen E, Arlet G, Denamur E, et al. Meningitis caused by Escherichia coli producing TEM-52 extended-spectrum beta-lactamase within an extensive outbreak in a neonatal ward: epidemiological investigation and characterization of the strain. J. Clin. Microbiol. 2010;48:2459–2463. doi: 10.1128/JCM.00529-10 20519482
39. Clermont O, Dixit OVA, Vangchhia B, Condamine B, Dion S, Bridier‐Nahmias A, et al. Characterization and rapid identification of phylogroup G in Escherichia coli, a lineage with high virulence and antibiotic resistance potential. Environ. Microbiol. 2019;21:3107–3117. doi: 10.1111/1462-2920.14713 31188527
40. Hacker J, Carniel E. Ecological fitness, genomic islands and bacterial pathogenicity. A Darwinian view of the evolution of microbes. EMBO Rep. 2001;2:376–381. doi: 10.1093/embo-reports/kve097 11375927
41. Touchon M, Perrin A, Moura de Sousa JA, Vangchhia B, Burn S, O’Brien CL, et al. Phylogenetic background and habitat drive the genetic diversification of Escherichia coli. PLoS Genet. 2020;16:e1008866. doi: 10.1371/journal.pgen.1008866 32530914
42. Warner PJ, Williams PH, Bindereif A, Neilands JB. ColV plasmid-specific aerobactin synthesis by invasive strains of Escherichia coli. Infect. Immun. 1981;33:540–545. doi: 10.1128/IAI.33.2.540-545.1981 6456229
43. Bearden SW, Staggs TM, Perry RD. An ABC transporter system of Yersinia pestis allows utilization of chelated iron by Escherichia coli SAB11. J. Bacteriol. 1998;180:1135–1147. doi: 10.1128/JB.180.5.1135-1147.1998 9495751
44. Mühldorfer I, Hacker J. Genetic aspects of Escherichia coli virulence. Microb. Pathog. 1994;16:171–181. doi: 10.1006/mpat.1994.1018 7522300
45. Graham AI, Hunt S, Stokes SL, Bramall N, Bunch J, Cox AG, et al. Severe zinc depletion of Escherichia coli: roles for high affinity zinc binding by ZinT, zinc transport and zinc-independent proteins. J. Biol. Chem. 2009;284:18377–18389. doi: 10.1074/jbc.M109.001503 19377097
46. Becker A-K, Zeppenfeld T, Staab A, Seitz S, Boos W, Morita T, et al. YeeI, a novel protein involved in modulation of the activity of the glucose-phosphotransferase system in Escherichia coli K-12. J. Bacteriol. 2006;188:5439–5449. doi: 10.1128/JB.00219-06 16855233
47. Whipp MJ, Camakaris H, Pittard AJ. Cloning and analysis of the shiA gene, which encodes the shikimate transport system of escherichia coli K-12. Gene.1998;209:185–192. doi: 10.1016/s0378-1119(98)00043-2 9524262
48. Prévost K, Salvail H, Desnoyers G, Jacques J-F, Phaneuf E, Massé E, et al. The small RNA RyhB activates the translation of shiA mRNA encoding a permease of shikimate, a compound involved in siderophore synthesis. Mol. Microbiol. 2007;64:1260–1273. doi: 10.1111/j.1365-2958.2007.05733.x 17542919
49. Urano H, Yoshida M, Ogawa A, Yamamoto K, Ishihama A, Ogasawara H, et al. Cross-regulation between two common ancestral response regulators, HprR and CusR, in Escherichia coli. Microbiology.2017;163:243–252. doi: 10.1099/mic.0.000410 27983483
50. Gennaris A, Ezraty B, Henry C, Agrebi R, Vergnes A, Oheix E, et al. Repairing oxidized proteins in the bacterial envelope using respiratory chain electrons. Nature. 2015;528;409–412. doi: 10.1038/nature15764 26641313
51. Ilbert M, Méjean V, Giudici-Orticoni M-T, Samama J-P, Iobbi-Nivol C. Involvement of a mate chaperone (TorD) in the maturation pathway of molybdoenzyme TorA. J. Biol. Chem. 2003;278:28787–28792. doi: 10.1074/jbc.M302730200 12766163
52. Méjean V, Lobbi‐Nivol C, Lepelletier M, Giordano G, Chippaux M, Pascal M-C. TMAO anaerobic respiration in Escherichia coli: involvement of the tor operon. Mol. Microbiol. 1994;11:1169–1179. doi: 10.1111/j.1365-2958.1994.tb00393.x 8022286
53. Diard M, Garry L, Selva M, Mosser T, Denamur R, Matic I, et al. Pathogenicity-associated islands in extraintestinal pathogenic Escherichia coli are fitness elements involved in intestinal colonization. J. Bacteriol. 2010;192:4885–4893. doi: 10.1128/JB.00804-10 20656906
54. Johnson JR, Magistro G, Clabots C, Porter S, Manges A, Thuras P, et al. Contribution of yersiniabactin to the virulence of an Escherichia coli sequence type 69 (‘clonal group A’) cystitis isolate in murine models of urinary tract infection and sepsis. Microb. Pathog. 2018;120:128–131. doi: 10.1016/j.micpath.2018.04.048 29702209
55. Kallonen T, Brodrick HJ, Harris SR, Corander J, Brown NM, Martin V, et al. Systematic longitudinal survey of invasive Escherichia coli in England demonstrates a stable population structure only transiently disturbed by the emergence of ST131. Genome Res. (2017) doi: 10.1101/gr.216606.116 28720578
56. Pippard MJ, Jackson MJ, Hoffman K, Petrou M, Modell, C. B. Iron chelation using subcutaneous infusions of diethylene triamine penta-acetic acid (DTPA). Scand. J. Haematol. 1986;36:466–472.
57. Cornelis P, Dingemans J. Pseudomonas aeruginosa adapts its iron uptake strategies in function of the type of infections. Front. Cell. Infect. Microbiol. 2013;3:75. doi: 10.3389/fcimb.2013.00075 24294593
58. Mazel D, Dychinco B, Webb VA, Davies J. Antibiotic resistance in the ECOR collection: integrons and identification of a novel aad gene. Antimicrob. Agents Chemother. 2000;44:1568–1574. doi: 10.1128/aac.44.6.1568-1574.2000 10817710
59. Muheim C, Götzke H, Eriksson AU, Lindberg S, Lauritsen I, Nørholm MHH, et al. Increasing the permeability of Escherichia coli using MAC13243. Scientific Reports. 2017;7.http://paperpile.com/b/XWFpcJ/eEaYFhttp://paperpile.com/b/XWFpcJ/eEaYFhttp://paperpile.com/b/XWFpcJ/eEaYFhttp://paperpile.com/b/XWFpcJ/eEaYFhttp://paperpile.com/b/XWFpcJ/eEaYF doi: 10.1038/s41598-017-00035-9 28127057
60. Skaar EP. The battle for iron between bacterial pathogens and their vertebrate hosts. PLoS Pathog. 2010;6:e1000949. doi: 10.1371/journal.ppat.1000949 20711357
61. Johnson JR. Johnston BD, Porter S, Thuras P, Aziz M, Price LB. Accessory Traits and Phylogenetic Background Predict Escherichia coli Extraintestinal Virulence Better Than Does Ecological Source. J. Infect. Dis. 2019;219:121–132. doi: 10.1093/infdis/jiy459 30085181
62. Schubert S, Darlu P, Clermont O, Wieser A, Magistro G, Hoffmann C, et al. Role of Intraspecies Recombination in the Spread of Pathogenicity Islands within the Escherichia coli Species. PLoS Pathog. 2009;5:e1000257. doi: 10.1371/journal.ppat.1000257 19132082
63. Huisman GW, Kolter R. Sensing starvation: a homoserine lactone—dependent signaling pathway in Escherichia coli. Science. 1994;265:537–539. doi: 10.1126/science.7545940 7545940
64. Fricke WF, Rasko DA. Bacterial genome sequencing in the clinic: bioinformatic challenges and solutions. Nat. Rev. Genet. 2014;15:49–55. doi: 10.1038/nrg3624 24281148
65. Quainoo S, Coolen JPM, van Hijum SAFT, Huynen MA, Melchers WJG, van Schaik W, et al. Whole-Genome Sequencing of Bacterial Pathogens: The Future of Nosocomial Outbreak Analysis. Clin. Microbiol. Rev. 2017;30:1015–1063. doi: 10.1128/CMR.00016-17 28855266
66. Tagini F, Greub G. Bacterial genome sequencing in clinical microbiology: a pathogen-oriented review. Eur. J. Clin. Microbiol. Infect. Dis. 2017;36:2007–2020. doi: 10.1007/s10096-017-3024-6 28639162
67. Mathieu A, Fleurier S, Frénoy A, Dairou J, Bredeche M-F, Sanchez-Vizuete P, et al. Discovery and Function of a General Core Hormetic Stress Response in E. coli Induced by Sublethal Concentrations of Antibiotics. Cell Rep. 2016;17:46–57. doi: 10.1016/j.celrep.2016.09.001 27681420
68. Kuczyńska-Wiśnik D, Matuszewska E, Furmanek-Blaszk B, Leszczyńska D, Grudowska A, Szczepaniak P, et al. Antibiotics promoting oxidative stress inhibit formation of Escherichia coli biofilm via indole signalling. Res. Microbiol. 2010;161:847–853. doi: 10.1016/j.resmic.2010.09.012 20868745
69. Li G, Young KD. Indole production by the tryptophanase TnaA in Escherichia coli is determined by the amount of exogenous tryptophan. Microbiology. 2013;159:402–410. doi: 10.1099/mic.0.064139-0 23397453
70. Garbe TR, Kobayashi M, Yukawa H. Indole-inducible proteins in bacteria suggest membrane and oxidant toxicity. Arch. Microbiol. 2000;173:78–82. doi: 10.1007/s002030050012 10648109
71. Chimerel C, Field CM, Piñero-Fernandez S, Keyser UF, Summers DK. Indole prevents Escherichia coli cell division by modulating membrane potential. Biochim. Biophys. Acta. 2012;1818:1590–1594. doi: 10.1016/j.bbamem.2012.02.022 22387460
72. Giroux X, Su W-L, Bredeche M-F, Matic I. Maladaptive DNA repair is the ultimate contributor to the death of trimethoprim-treated cells under aerobic and anaerobic conditions. Proc. Natl. Acad. Sci. U. S. A. 2017;114:11512–11517. doi: 10.1073/pnas.1706236114 29073080
73. Baharoglu Z, Krin E, Mazel D. RpoS plays a central role in the SOS induction by sub-lethal aminoglycoside concentrations in Vibrio cholerae. PLoS Genet. 2013;9:e1003421. doi: 10.1371/journal.pgen.1003421 23613664
74. Pál C, Papp B, Lázár V. Collateral sensitivity of antibiotic-resistant microbes. Trends Microbiol. 2015;23:401–407. doi: 10.1016/j.tim.2015.02.009 25818802
75. Ezraty B, Barras F. The ‘liaisons dangereuses’ between iron and antibiotics. FEMS Microbiol. Rev. 2016;40:418–435. doi: 10.1093/femsre/fuw004 26945776
76. Galardini M. Escherichia coli pathogenicity GWAS: input genome sequences (updated). (2020) doi: 10.6084/m9.figshare.11879340.v1
77. Datsenko KA, Wanner BL. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc. Natl. Acad. Sci. U. S. A. 2000;97:6640–6645. doi: 10.1073/pnas.120163297 10829079
78. Chaveroche MK, Ghigo JM, d’Enfert C. A rapid method for efficient gene replacement in the filamentous fungus Aspergillus nidulans. Nucleic Acids Res. 2000;28:E97. doi: 10.1093/nar/28.22.e97 11071951
79. Martin P, Marcq I, Magistro G, Penary M, Garcie C, Payros D, et al. Interplay between Siderophores and Colibactin Genotoxin Biosynthetic Pathways in Escherichia coli. PLoS Pathogens. 2013;9:e1003437. doi: 10.1371/journal.ppat.1003437 23853582
80. Davidson-Pilon C, Kalderstam J, Zivich P, Kuhn B, Fiore-Gartland A, Moneda L, et al. CamDavidsonPilon/lifelines: v0.21.0. 2019. doi: 10.5281/zenodo.2638135
81. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068–2069. doi: 10.1093/bioinformatics/btu153 24642063
82. Treangen TJ, Ondov BD, Koren S, Phillippy AM. The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biol. 2014;15:524. doi: 10.1186/s13059-014-0524-x 25410596
83. Croucher NJ, Page AJ, Connor TR, Delaney AJ, Keane JA, et al. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Res. 2015;43:e15. doi: 10.1093/nar/gku1196 25414349
84. Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S, Holden MTG, et al. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics. 2015;31:3691–3693. doi: 10.1093/bioinformatics/btv421 26198102
85. Lippert C, Listgarten J, Liu Y, Kadie CM, Davidson RI, Heckerman D, et al. FaST linear mixed models for genome-wide association studies. Nature Methods. 2011;8:833–835. doi: 10.1038/nmeth.1681 21892150
86. Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. 2013. arXiv [q-bio.GN].
87. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26:841–842. doi: 10.1093/bioinformatics/btq033 20110278
88. Touchon M, Hoede C, Tenaillon O, Barbe V, Baeriswyl S, Bidet P, et al. Organised genome dynamics in the Escherichia coli species results in highly diverse adaptive paths. PLoS Genet. 2009;5:e1000344. doi: 10.1371/journal.pgen.1000344 19165319
89. Consortium UniProt. UniProt: a hub for protein information. Nucleic Acids Res. 2015;43:D204–12. doi: 10.1093/nar/gku989 25348405
90. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. Journal of Molecular Biology. 1990;215:403–410. doi: 10.1016/S0022-2836(05)80360-2 2231712
91. Klopfenstein DV, Zhang L, Pedersen BS, Ramírez F, Warwick Vesztrocy A, Naldi A, et al. GOATOOLS: A Python library for Gene Ontology analyses. Sci. Rep. 2018;8:10872. doi: 10.1038/s41598-018-28948-z 30022098
92. Collins SR, Schuldiner M, Krogan NJ, Weissman JS. A strategy for extracting and analyzing large-scale quantitative epistatic interaction data. Genome Biol. 2006;7:R63. doi: 10.1186/gb-2006-7-7-r63 16859555
93. Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S, Lund O, et al. Identification of acquired antimicrobial resistance genes. J. Antimicrob. Chemother. 2012;67:2640–2644. doi: 10.1093/jac/dks261 22782487
94. Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, et al. Scikit-learn: Machine Learning in Python. J. Mach. Learn. Res. 2011;12:2825–2830.
95. Van Der Walt S, Colbert SC, Varoquaux G. The NumPy array: a structure for efficient numerical computation. Comput. Sci. Eng. 2011;13:22–30.
96. Jones E, Oliphant T, Peterson P. SciPy: Open source scientific tools for Python. 2001.http://www.scipy.org/.
97. Cock PJA, Antao T, Chang JT, Chapman BA, Cox CJ, Dalke A, et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics. 2009;25:1422–1423. doi: 10.1093/bioinformatics/btp163 19304878
98. Talevich E, Invergo BM, Cock PJ, Chapman B. a. Bio.Phylo: A unified toolkit for processing, analyzing and visualizing phylogenetic trees in Biopython. BMC Bioinformatics. 2012;13:209. doi: 10.1186/1471-2105-13-209 22909249
99. McKinney W, Others. Data structures for statistical computing in Python. in Proceedings of the 9th Python in Science Conference vol. 2010;445:51–56.
100. Dale RK, Pedersen BS, Quinlan AR. Pybedtools: a flexible Python library for manipulating genomic datasets and annotations. Bioinformatics. 2011;27:3423–3424. doi: 10.1093/bioinformatics/btr539 21949271
101. Sukumaran J, Holder MT. DendroPy: a Python library for phylogenetic computing. Bioinformatics. 2010;26:1569–1571. doi: 10.1093/bioinformatics/btq228 20421198
102. Huerta-Cepas J, Serra F, Bork P. ETE 3: Reconstruction, Analysis, and Visualization of Phylogenomic Data. Mol. Biol. Evol. 2016;33:1635–1638. doi: 10.1093/molbev/msw046 26921390
103. Seabold S, Perktold J. Statsmodels: Econometric and statistical modeling with python. in Proceedings of the 9th Python in Science Conference vol. 57 61; SciPy society Austin, 2010.
104. Hunter JD. Matplotlib: A 2D Graphics Environment. Computing in Science Engineering. 2007;9:90–95.
105. Waskom M, Botvinnik O, O'Kane D, Hobson P, Ostblom J, Lukauskas S, et al. mwaskom/seaborn: v0.9.0 (July 2018). 2018. doi: 10.5281/zenodo.1313201
106. Kluyver T, Ragan-Kelley B, Pérez F, Granger B, Bussonnier M, Frederic J, et al. Jupyter Notebooks-a publishing format for reproducible computational workflows. in ELPUB 87–90. 2016.
107. Köster J, Rahmann S. Snakemake-a scalable bioinformatics workflow engine. Bioinformatics. 2018;34:3600. doi: 10.1093/bioinformatics/bty350 29788404
Článek vyšel v časopise
PLOS Genetics
2020 Číslo 10
- S diagnostikou Parkinsonovy nemoci může nově pomoci AI nástroj pro hodnocení mrkacího reflexu
- Proč při poslechu některé muziky prostě musíme tančit?
- Chůze do schodů pomáhá prodloužit život a vyhnout se srdečním chorobám
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- „Jednohubky“ z klinického výzkumu – 2024/44
Nejčtenější v tomto čísle
- Evaluation of both exonic and intronic variants for effects on RNA splicing allows for accurate assessment of the effectiveness of precision therapies
- RNA-directed DNA Methylation
- The DNA methylome of human sperm is distinct from blood with little evidence for tissue-consistent obesity associations
- Correction: Molecular predictors of brain metastasis-related microRNAs in lung adenocarcinoma
