Global responses to oxytetracycline treatment in tetracycline-resistant Escherichia coli.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
21 05 2020
21 05 2020
Historique:
received:
17
09
2019
accepted:
22
04
2020
entrez:
23
5
2020
pubmed:
23
5
2020
medline:
2
12
2020
Statut:
epublish
Résumé
We characterized the global transcriptome of Escherichia coli MG1655:: tetA grown in the presence of ½ MIC (14 mg/L) of OTC, and for comparison WT MG1655 strain grown with 1//2 MIC of OTC (0.25 mg/L OTC). 1646 genes changed expression significantly (FDR > 0.05) in the resistant strain, the majority of which (1246) were also regulated in WT strain. Genes involved in purine synthesis and ribosome structure and function were top-enriched among up-regulated genes, and anaerobic respiration, nitrate metabolism and aromatic amino acid biosynthesis genes among down-regulated genes. Blocking of the purine-synthesis- did not affect resistance phenotypes (MIC and growth rate with OTC), while blocking of protein synthesis using low concentrations of chloramphenicol or gentamicin, lowered MIC towards OTC. Metabolic-modeling, using a novel model for MG1655 and continuous weighing factor that reflected the degree of up or down regulation of genes encoding a reaction, identified 102 metabolic reactions with significant change in flux in MG1655:: tetA when grown in the presence of OTC compared to growth without OTC. These pathways could not have been predicted by simply analyzing functions of the up and down regulated genes, and thus this work has provided a novel method for identification of reactions which are essential in the adaptation to growth in the presence of antimicrobials.
Identifiants
pubmed: 32439837
doi: 10.1038/s41598-020-64995-1
pii: 10.1038/s41598-020-64995-1
pmc: PMC7242477
doi:
Substances chimiques
Anti-Bacterial Agents
0
Escherichia coli Proteins
0
Oxytetracycline
X20I9EN955
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
8438Références
Roberts, M. C. Tetracycline resistance determinants: mechanisms of action, regulation of expression, genetic mobility, and distribution. FEMS Microbiol. Rev. 19, 1–24 (1996).
pubmed: 8916553
doi: 10.1111/j.1574-6976.1996.tb00251.x
Coenen, S. et al. European surveillance of antimicrobial consumption (ESAC): outpatient use of tetracyclines, sulphonamides and trimethoprim, and other antibacterials in Europe (1997–2009). JAC 66, vi57–vi70 (2011).
pubmed: 22096067
Chopra, I. & Roberts, M. Tetracycline antibiotics: mode of action, applications, molecular biology, and epidemiology of bacterial resistance. Microbiol. Mol. Biol. Rev. 65, 232–260 (2001).
pubmed: 11381101
pmcid: 99026
doi: 10.1128/MMBR.65.2.232-260.2001
Sengelov, G., Halling-Sorensen, B. & Aarestrup, F. M. Susceptibility of Escherichia coli and Enterococcus faecium isolated from pigs and broiler chickens to tetracycline degradation products and distribution of tetracycline resistance determinants in E. coli from food animals. Vet. Microbiol. 95, 91–101 (2003).
pubmed: 12860079
doi: 10.1016/S0378-1135(03)00123-8
Tadesse, D. A. et al. Antimicrobial drug resistance in Escherichia coli from humans and food animals, United States, 1950–2002. Emerg. Infec. Dis. 18, 741–749 (2012).
doi: 10.3201/eid1805.111153
Pagel, S. & Gautier, P. Use of antimicrobial agents in livestock. Rev. Sci. Tech. (OIE) 31, 145–188 (2012).
doi: 10.20506/rst.31.1.2106
Roberts, M. C. Update on acquired tetracycline resistance genes. FEMS Microbiol. Lett. 245, 195–203 (2005).
pubmed: 15837373
doi: 10.1016/j.femsle.2005.02.034
Li, X. Z. & Nikaido, H. Efflux-mediated drug resistance in bacteria. Drugs 64, 159–204 (2004).
pubmed: 14717618
doi: 10.2165/00003495-200464020-00004
Bryan, A., Shapir, N. & Sadowsky, M. J. Frequency and distribution of tetracycline resistance genes in genetically diverse, nonselected, and nonclinical Escherichia coli strains isolated from diverse human and animal sources. Appl. Environ. Microbiol. 70, 2503–2507 (2004).
pubmed: 15066850
pmcid: 383146
doi: 10.1128/AEM.70.4.2503-2507.2004
Moller, T. S. B. et al. Relation between tetR and tetA expression is tetracycline resiatnt Escherichia coli. BMC Microbiol. 16, 39 (2016).
pubmed: 26969122
pmcid: 4788846
doi: 10.1186/s12866-016-0649-z
Moller, T. S. et al. Adaptive responses to cefotaxime treatment in ESBL-producing Escherichia coli and the possible use of significantly regulated pathways as novel secondary targets. JAC 71, 2449–2459 (2016).
pubmed: 27272725
Brochmann, P. R., Hesketh, A., Jana, B., Brodersen, G. H. & Guardabassi, L. Transcriptome analysis of extended-spectrum beta-lactamase-producing Escherichia coli and methicillin-resistant Staphylococcus aureus exposed to cefotaxime. Sci. Rep. 8, 16076 (2018).
pubmed: 30375423
pmcid: 6207760
doi: 10.1038/s41598-018-34191-3
Jana, B. et al. The secondary resistome of multidrug-resistant Klebsiella pneumoniae. Sci. Rep. 7, 42483 (2017).
pubmed: 5309761
pmcid: 5309761
doi: 10.1038/srep42483
Jensen, P. A., Zhu, Z. & van Opijnen, T. Antibiotics disrupt coordination between transcriptional and phenotypic stress responses in pathogenic bacteria. Cell Rep. 20, 1705–1716 (2017).
pubmed: 28813680
pmcid: 5584877
doi: 10.1016/j.celrep.2017.07.062
Rosenkrantz, J. T. et al. Non-essential genes form the hubs of genome scale protein function and environmental gene expression networks in Salmonella enterica serovar Typhimurium. BMC Microbiol. 13, 294 (2013).
pubmed: 24345035
pmcid: 3878590
doi: 10.1186/1471-2180-13-294
Thiele, I. & Palsson, B. Ø. A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat. Protocols 5, 93–121 (2010).
pubmed: 20057383
doi: 10.1038/nprot.2009.203
Heinrich, R. et al. Fundamentals of biochemical modeling In The regulation of cellular systems (Heinrich, R. & Schuster, S. (eds), p. 1–51 (Chapman and Hall; 1996).
Poolman, M. G., Kundu, S., Shaw, R. & Fell, D. A. Responses to light intensity in a genome-scale model of rice metabolism. Plant Physiol. 162, 1060–1072 (2013).
pubmed: 23640755
pmcid: 3668040
doi: 10.1104/pp.113.216762
Åkesson, M., Förster, J. & Nielsen, J. Integration of gene expression data into genome-scale metabolic models. Metabol. Eng. 6, 285–293 (2004).
doi: 10.1016/j.ymben.2003.12.002
Yang, L., Ebrahim, A., Lloyd, C. J., Saunders, M. A. & Palsson, B. O. DynamicME: dynamic simulation and refinement of integrated models of metabolism and protein expression. BMC Syst. Biol. 13, 2 (2019).
pubmed: 30626386
pmcid: 6327497
doi: 10.1186/s12918-018-0675-6
Agwuh, K. N. & MacGowan, A. Pharmacokinetics and pharmacodynamics of the tetracyclines including glycylcyclines. JAC 58, 256–265 (2006).
pubmed: 16816396
Lessard, I. A. et al. Homologs of the vancomycin resistance D-Ala-D-Ala dipeptidase VanX in Streptomyces toyocaensis, Escherichia coli and Synechocystis: attributes of catalytic efficiency, stereoselectivity and regulation with implications for function. Chem. Biol. 5, 489–504 (1998).
pubmed: 9751644
doi: 10.1016/S1074-5521(98)90005-9
Weber, H., Polen, T., Heuveling, J., Wendisch, V. F. & Hengge, R. Genome-wide analysis of the general stress response network in Escherichia coli: sigmaS-dependent genes, promoters, and sigma factor selectivity. J. Bacteriol. 187, 1591–1603 (2005).
pubmed: 15716429
pmcid: 1063999
doi: 10.1128/JB.187.5.1591-1603.2005
Raivio, T. L., Leblanc, S. K. D. & Price, N. L. The Escherichia coli Cpx envelope stress response regulates genes of diverse function that impact antibiotic resistance and membrane integrity. J. Bac. 195, 2755–2767 (2013).
doi: 10.1128/JB.00105-13
Dartigalongue, C., Missiakas, D. & Raina, S. Characterization of the Escherichia coli sigma(E) regulon. J. Biol. Chem. 276, 20866–20875 (2001).
pubmed: 11274153
doi: 10.1074/jbc.M100464200
Kobayashi, R., Suzuki, T. & Yoshida, M. Escherichia coli phage-shock protein A (PspA) binds to membrane phospholipids and repairs proton leakage of the damaged membranes. Mol. Microbiol. 66, 100–109 (2007).
pubmed: 17725563
doi: 10.1111/j.1365-2958.2007.05893.x
Wallrodt, I. et al. The putative thiosulfate sulfurtransferases PspE and GlpE contribute to virulence of Salmonella Typhimurium in the mouse model of systemic disease. PloS One 8, e70829 (2013).
pubmed: 23940650
pmcid: 3733917
doi: 10.1371/journal.pone.0070829
Nygaard, P. & Smith, J. M. Evidence for a novel glycinamide ribonucleotide transformylase in Escherichia coli. J. Bacteriol. 175, 3591–3597 (1993).
pubmed: 8501063
pmcid: 204760
doi: 10.1128/JB.175.11.3591-3597.1993
Bernard, M. A., Ray, N. B., Olcott, M. C., Hendricks, S. P. & Mathews, C. K. Metabolic functions of microbial nucleoside diphosphate kinases. J Bioenerg. Biomembr. 32, 259–267 (2000).
pubmed: 11768309
doi: 10.1023/A:1005537013120
Piendl, W. & Böck, A. Ribosomal resistance in the gentamicin producer organism Micromonospora purpurea. Antimicrob. Agent Chemother. 22, 231–236 (1982).
doi: 10.1128/AAC.22.2.231
Poehlsgaard, J. & Douthwaite, S. The bacterial ribosome as a target for antibiotics. Nat. Rev. Microbiol. 3, 870–881 (2005).
pubmed: 16261170
doi: 10.1038/nrmicro1265
Odds, F. C. Synergy, antagonism, and what the chequerboard puts between them. JAC 52, 1 (2003).
pubmed: 12805255
Gao, Y. et al. Development of genetically stable Escherichia coli strains for poly(3-hydroxypropionate) production. PloS One 9, e97845 (2014).
pubmed: 24837211
pmcid: 4023983
doi: 10.1371/journal.pone.0097845
Feist, A. M. et al. A genome‐scale metabolic reconstruction for Escherichia coli K‐12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Mol. Syst. Biol. 3 (2007).
Schuster, S., Fell, D. A. & Dandekar, T. A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks. Nat. Biotechnol. 18, 326–332 (2000).
pubmed: 10700151
doi: 10.1038/73786
Li, L., Kromann, S., Olsen, J. E., Svenningsen, S. W. & Olsen, R. H. Insight into synergetic mechanisms of tetracycline and the selective serotonin reuptake inhibitor, sertraline, in a tetracycline-resistant strain of Escherichia coli. J. Antibio. 70, 944–953 (2017).
doi: 10.1038/ja.2017.78
Xi, H., Schneider, B. L. & Reitzer, L. Purine catabolism in Escherichia coli and function of xanthine dehydrogenase in purine salvage. J Bacteriol. 182, 5332–5341 (2000).
pubmed: 10986234
pmcid: 110974
doi: 10.1128/JB.182.19.5332-5341.2000
Blakley, R. L. & Vitols, E. The control of nucleotide biosynthesis. Ann. Rev. Biochem. 37, 201–224 (1968).
pubmed: 4875716
doi: 10.1146/annurev.bi.37.070168.001221
EUCAST. Clinical breakpoints - breakpoints and guidance, http://www.eucast.org/clinical_breakpoints/ (2015).
Ciak, J. & Hahn, F. E. Mechanisms of action of antibiotics I: Additive action of chloramphenicol and tetracyclines on the growth of Escherichia coli. J. Bacteriol. 75, 125 (1958).
pubmed: 13513572
pmcid: 290047
doi: 10.1128/JB.75.2.125-129.1958
Garrett, E. R. & Brown, M. The action of tetracycline and chloramphenicol alone and in admixture on the growth of Escherichia coli. J. Pharm. Pharmacol. 15, 185T–191T (1963).
doi: 10.1111/j.2042-7158.1963.tb11210.x
Garrod, L. & Waterworth, P. M. Methods of testing combined antibiotic bactericidal action and the significance of the results. J. Clin. Pathol. 15, 328 (1962).
pubmed: 13897086
pmcid: 480408
doi: 10.1136/jcp.15.4.328
Yoshizawa, S., Fourmy, D. & Puglisi, J. D. Structural origins of gentamicin antibiotic action. EMBO J. 17, 6437–6448 (1998).
pubmed: 9822590
pmcid: 1170992
doi: 10.1093/emboj/17.22.6437
Solera, J. et al. Treatment of human brucellosis with doxycycline and gentamicin. Antimicrob. Agents Chemother. 41, 80–84 (1997).
pubmed: 8980759
pmcid: 163664
doi: 10.1128/AAC.41.1.80
Rodriguez, A. et al. Engineering Escherichia coli to overproduce aromatic amino acids and derived compounds. Microb. Cell Factor. 13, 126 (2014).
Rotenberg, S. & Sprinson, D. B. Isotope effects in 3-dehydroquinate synthase and dehydratase. Mechanistic implications. J. Biolog. Chem. 253, 2210–2215 (1978).
Lu, W. et al. Genome-wide transcriptional responses of Escherichia coli to glyphosate, a potent inhibitor of the shikimate pathway enzyme 5-enolpyruvylshikimate-3-phosphate synthase. Mol. Biosyst. 9, 522–530 (2013).
pubmed: 23247721
doi: 10.1039/C2MB25374G
Bulloch, E. M. et al. Identification of 4-Amino-4-deoxychorismate synthase as the molecular target for the antimicrobial action of (6 S)-6-fluoroshikimate. J. Amer. Chem.l Soc. 126, 9912–9913 (2004).
doi: 10.1021/ja048312f
Malik, J., Barry, G. & Kishore, G. The herbicide glyphosate. BioFact. 2, 17–25 (1989).
Weaver, D. S., Keseler, I. M., Mackie, A., Paulsen, I. T. & Karp, P. D. A genome-scale metabolic flux model of Escherichia coli K-12 derived from the EcoCyc database. BMC Syst. Biol. 8, 79 (2014).
pubmed: 24974895
pmcid: 4086706
doi: 10.1186/1752-0509-8-79
Yang, C., Hua, Q. & Shimizu, K. Integration of the information from gene expression and metabolic fluxes for the analysis of the regulatory mechanisms in Synechocystis. Appl. Microbiol. Biotechnol. 58, 813–822 (2002).
pubmed: 12021803
doi: 10.1007/s00253-002-0949-0
Covert, M. W., Schilling, C. H. & Palsson, B. Regulation of gene expression in flux balance models of metabolism. J. Theor. Biol. 213, 73–88 (2001).
pubmed: 11708855
doi: 10.1006/jtbi.2001.2405
Becker, S. A. & Palsson, B. O. Context-specific metabolic networks are consistent with experiments. PLoS Comput. Biol. 4, e1000082 (2008).
pubmed: 18483554
pmcid: 2366062
doi: 10.1371/journal.pcbi.1000082
Zur, H., Ruppin, E. & Shlomi, T. iMAT: an integrative metabolic analysis tool. Bioinform. 26, 3140–3142 (2010).
doi: 10.1093/bioinformatics/btq602
Shlomi, T., Cabili, M. N., Herrgård, M. J., Palsson, B. Ø. & Ruppin, E. Network-based prediction of human tissue-specific metabolism. Nat. Biotechnol. 26, 1003–1010 (2008).
pubmed: 18711341
doi: 10.1038/nbt.1487
Schurmann, M. & Sprenger, G. A. Fructose-6-phosphate aldolase is a novel class I aldolase from Escherichia coli and is related to a novel group of bacterial transaldolases. J. Biol. Chem. 276, 11055–11061 (2001).
pubmed: 11120740
doi: 10.1074/jbc.M008061200
Jin, R. Z. & Lin, E. C. An inducible phosphoenolpyruvate: dihydroxyacetone phosphotransferase system in Escherichia coli. J. Gen. Microbiol. 130, 83–88 (1984).
pubmed: 6368745
Moller, T. S. et al. Relation between tetR and tetA expression in tetracycline resistant Escherichia coli. BMC Microbiol. 16, 39 (2016).
pubmed: 26969122
pmcid: 4788846
doi: 10.1186/s12866-016-0649-z
Datsenko, K. A. & Wanner, B. L. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc. Nat. Acad. Sci. USA 97, 6640–6645 (2000).
pubmed: 10829079
doi: 10.1073/pnas.120163297
Orhan, G., Bayram, A., Zer, Y. & Balci, I. Synergy tests by E test and checkerboard methods of antimicrobial combinations against Brucella melitensis. J. Clin. Microbiol. 43, 140–143 (2005).
pubmed: 15634962
pmcid: 540140
doi: 10.1128/JCM.43.1.140-143.2005
Blattner, F. R. et al. The complete genome sequence of Escherichia coli K-12. Sci. 277, 1453–1462 (1997).
doi: 10.1126/science.277.5331.1453
Pfaffl, M. W. A new mathematical model for relative quantification in real-time RT-PCR. Nucl. Acids Res. 29, e45 (2001).
pubmed: 11328886
doi: 10.1093/nar/29.9.e45
Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinform. 26, 139–140 (2010).
doi: 10.1093/bioinformatics/btp616
Benjamini, Y., Drai, D., Elmer, G., Kafkafi, N. & Golani, I. Controlling the false discovery rate in behavior genetics research. Behav. Brain Research 125, 279–284 (2001).
doi: 10.1016/S0166-4328(01)00297-2
Maere, S., Heymans, K. & Kuiper, M. BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinform. 21, 3448–3449 (2005).
doi: 10.1093/bioinformatics/bti551
Keseler, I. M. et al. EcoCyc: a comprehensive database of Escherichia coli biology. Nucleic acids research 39, D583–D590 (2011).
pubmed: 21097882
doi: 10.1093/nar/gkq1143
Hartman, H. B. et al. Identification of potential drug targets in Salmonella enterica sv. Typhimurium using metabolic modelling and experimental validation. Microbiol. 160, 1252–1266 (2014).
doi: 10.1099/mic.0.076091-0
Poolman, M. G., Sebu, C., Pidcock, M. K. & Fell, D. A. Modular decomposition of metabolic systems via null-space analysis. J. Theor. Biol. 249, 691–705 (2007).
pubmed: 17949756
doi: 10.1016/j.jtbi.2007.08.005
Poolman, M. G., Miguet, L., Sweetlove, L. J. & Fell, D. A. A genome-scale metabolic model of Arabidopsis and some of its properties. Plant Physiol. 151, 1570–1581 (2009).
pubmed: 19755544
pmcid: 2773075
doi: 10.1104/pp.109.141267
Wang, J., Su, Y., Jia, F. & Jin, H. Characterization of casein hydrolysates derived from enzymatic hydrolysis. Chem. Cent. J. 7, 62 (2013).
pubmed: 23556455
pmcid: 3626679
doi: 10.1186/1752-153X-7-62