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Experimental Epidemiology of Antibiotic Resistance: Looking for an Appropriate Animal Model System

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  • Authors: Pablo Llop1, Amparo Latorre*2, Andrés Moya*5
  • Editors: Fernando Baquero8, Emilio Bouza9, J.A. Gutiérrez-Fuentes10, Teresa M. Coque11
  • VIEW AFFILIATIONS HIDE AFFILIATIONS
    Affiliations: 1: Foundation for the Promotion of Sanitary and Biomedical Research in the Valencian Region (FISABIO), València, Spain; 2: Foundation for the Promotion of Sanitary and Biomedical Research in the Valencian Region (FISABIO), València, Spain; 3: Integrative Systems Biology Institute, Universitat de València, València, Spain; 4: Network Research Center for Epidemiology and Public Health (CIBERESP), Madrid, Spain; 5: Foundation for the Promotion of Sanitary and Biomedical Research in the Valencian Region (FISABIO), València, Spain; 6: Integrative Systems Biology Institute, Universitat de València, València, Spain; 7: Network Research Center for Epidemiology and Public Health (CIBERESP), Madrid, Spain; 8: Hospital Ramón y Cajal (IRYCIS), Madrid, Spain; 9: Hospital Ramón y Cajal (IRYCIS), Madrid, Spain; 10: Complutensis University, Madrid, Spain; 11: Hospital Ramón y Cajal (IRYCIS), Madrid, Spain
  • Source: microbiolspec January 2018 vol. 6 no. 1 doi:10.1128/microbiolspec.MTBP-0007-2016
  • Received 22 February 2017 Accepted 13 March 2017 Published 04 January 2018
  • Andrés Moya, [email protected]
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  • Abstract:

    Antibiotic resistance is recognized as one of the major challenges in public health. The global spread of antibiotic resistance is the consequence of a constant flow of information across multi-hierarchical interactions, involving cellular (clones), subcellular (resistance genes located in plasmids, transposons, and integrons), and supracellular (clonal complexes, genetic exchange communities, and microbiotic ensembles) levels. In order to study such multilevel complexity, we propose to establish an experimental epidemiology model for the transmission of antibiotic resistance with the cockroach . This paper reports the results of five types of preliminary experiments with populations that allow us to conclude that this animal is an appropriate model for experimental epidemiology: (i) the composition, transmission, and acquisition of gut microbiota and endosymbionts; (ii) the effect of different diets on gut microbiota; (iii) the effect of antibiotics on host fitness; (iv) the evaluation of the presence of antibiotic resistance genes in natural- and lab-reared populations; and (v) the preparation of plasmids harboring specific antibiotic resistance genes. The basic idea is to have populations with higher and lower antibiotic exposure, simulating the hospital and the community, respectively, and with a certain migration rate of insects between populations. In parallel, we present a computational model based on P-membrane computing that will mimic the experimental system of antibiotic resistance transmission. The proposal serves as a proof of concept for the development of more-complex population dynamics of antibiotic resistance transmission that are of interest in public health, which can help us evaluate procedures and design appropriate interventions in epidemiology.

  • Keywords: Blatella germanica; experimental epidemiology; membrane computing; antibiotic resistance

  • Citation: Llop P, Latorre* A, Moya* A. 2018. Experimental Epidemiology of Antibiotic Resistance: Looking for an Appropriate Animal Model System. Microbiol Spectrum 6(1):MTBP-0007-2016. doi:10.1128/microbiolspec.MTBP-0007-2016.

References

1. Centers for Disease Control and Prevention. 2017. Antibiotic resistance threats in the United States. 2013. http://www.cdc.gov/drugresistance/threat-report-2013/. Accessed February 20th, 2017.
2. Foreign and Commonwealth Office. 2013. G8 Science Ministers Statement. https://www.gov.uk/government/news/g8-science-ministers-statement. Accessed February 20th, 2017.
3. World Health Organization. 2016. Antimicrobial resistance. Fact sheet No. 194. http://www.who.int/mediacentre/factsheets/fs194/en/. Accessed February 20th, 2017.
4. Carlet J, Jarlier V, Harbarth S, Voss A, Goossens H, Pittet D, Participants of the 3rd World Healthcare-Associated Infections Forum. 2012. Ready for a world without antibiotics? The Pensières Antibiotic Resistance Call to Action. Antimicrob Resist Infect Control 1:11. http://dx.doi.org/10.1186/2047-2994-1-11. [PubMed]
5. Laxminarayan R, Duse A, Wattal C, Zaidi AKM, Wertheim HFL, Sumpradit N, Vlieghe E, Hara GL, Gould IM, Goossens H, Greko C, So AD, Bigdeli M, Tomson G, Woodhouse W, Ombaka E, Peralta AQ, Qamar FN, Mir F, Kariuki S, Bhutta ZA, Coates A, Bergstrom R, Wright GD, Brown ED, Cars O. 2013. Antibiotic resistance—the need for global solutions. Lancet Infect Dis 13:1057–1098. http://dx.doi.org/10.1016/S1473-3099(13)70318-9.
6. Jarlier V, Carlet J, McGowan J, Goossens H, Voss A, Harbarth S, Pittet D, Participants of the 3rd World Healthcare-Associated Infections Forum. 2012. Priority actions to fight antibiotic resistance: results of an international meeting. Antimicrob Resist Infect Control 1:17. http://dx.doi.org/10.1186/2047-2994-1-17. [PubMed]
7. Rolain JM, Parola P, Cornaglia G. 2010. New Delhi metallo-beta-lactamase (NDM-1): towards a new pandemia? Clin Microbiol Infect 16:1699–1701. http://dx.doi.org/10.1111/j.1469-0691.2010.03385.x. [PubMed]
8. Baquero F. 2004. From pieces to patterns: evolutionary engineering in bacterial pathogens. Nat Rev Microbiol 2:510–518. http://dx.doi.org/10.1038/nrmicro909. [PubMed]
9. Baquero F, Coque TM, de la Cruz F. 2011. Ecology and evolution as targets: the need for novel eco-evo drugs and strategies to fight antibiotic resistance. Antimicrob Agents Chemother 55:3649–3660. http://dx.doi.org/10.1128/AAC.00013-11. [PubMed]
10. Baquero F, Tedim AP, Coque TM. 2013. Antibiotic resistance shaping multi-level population biology of bacteria. Front Microbiol 4:15. http://dx.doi.org/10.3389/fmicb.2013.00015. [PubMed]
11. Sekirov I, Russell SL, Antunes LC, Finlay BB. 2010. Gut microbiota in health and disease. Physiol Rev 90:859–904. http://dx.doi.org/10.1152/physrev.00045.2009. [PubMed]
12. Dethlefsen L, McFall-Ngai M, Relman DA. 2007. An ecological and evolutionary perspective on human-microbe mutualism and disease. Nature 449:811–818. http://dx.doi.org/10.1038/nature06245. [PubMed]
13. Arumugam M, Raes J, Pelletier E, Le Paslier D, Yamada T, Mende DR, Fernandes GR, Tap J, Bruls T, Batto JM, Bertalan M, Borruel N, Casellas F, Fernandez L, Gautier L, Hansen T, Hattori M, Hayashi T, Kleerebezem M, Kurokawa K, Leclerc M, Levenez F, Manichanh C, Nielsen HB, Nielsen T, Pons N, Poulain J, Qin J, Sicheritz-Ponten T, Tims S, Torrents D, Ugarte E, Zoetendal EG, Wang J, Guarner F, Pedersen O, de Vos WM, Brunak S, Doré J; MetaHIT Consortium, Antolín M, Artiguenave F, Blottiere HM, Almeida M, Brechot C, Cara C, Chervaux C, Cultrone A, Delorme C, Denariaz G, Dervyn R, Foerstner KU, Friss C, van de Guchte M, Guedon E, Haimet F, Huber W, van Hylckama-Vlieg J, Jamet A, Juste C, Kaci G, Knol J, Lakhdari O, Layec S, Le Roux K, Maguin E, Mérieux A, Melo Minardi R, M’rini C, Muller J, Oozeer R, Parkhill J, Renault P, Rescigno M, Sanchez N, Sunagawa S, Torrejon A, Turner K, Vandemeulebrouck G, Varela E, Winogradsky Y, Zeller G, Weissenbach J, Ehrlich SD, Bork P. 2011. Enterotypes of the human gut microbiome. Nature 473:174–180. http://dx.doi.org/10.1038/nature09944. [PubMed]
14. Salyers AA, Gupta A, Wang Y. 2004. Human intestinal bacteria as reservoirs for antibiotic resistance genes. Trends Microbiol 12:412–416. http://dx.doi.org/10.1016/j.tim.2004.07.004. [PubMed]
15. Francino MP. 2014. Early development of the gut microbiota and immune health. Pathogens 3:769–790. http://dx.doi.org/10.3390/pathogens3030769. [PubMed]
16. Francino MP. 2016. Antibiotics and the human gut microbiome: dysbioses and accumulation of resistances. Front Microbiol 6:1543. http://dx.doi.org/10.3389/fmicb.2015.01543. [PubMed]
17. Moore AM, Ahmadi S, Patel S, Gibson MK, Wang B, Ndao MI, Deych E, Shannon W, Tarr PI, Warner BB, Dantas G. 2015. Gut resistome development in healthy twin pairs in the first year of life. Microbiome 3:27. http://dx.doi.org/10.1186/s40168-015-0090-9. [PubMed]
18. Lu N, Hu Y, Zhu L, Yang X, Yin Y, Lei F, Zhu Y, Du Q, Wang X, Meng Z, Zhu B. 2014. DNA microarray analysis reveals that antibiotic resistance-gene diversity in human gut microbiota is age related. Sci Rep 4:4302. http://dx.doi.org/10.1038/srep04302. [PubMed]
19. von Wintersdorff CJ, Penders J, Stobberingh EE, Oude Lashof AM, Hoebe CJ, Savelkoul PH, Wolffs PF. 2014. High rates of antimicrobial drug resistance gene acquisition after international travel, The Netherlands. Emerg Infect Dis 20:649–657. http://dx.doi.org/10.3201/eid2004.131718. [PubMed]
20. Hu Y, Yang X, Lu N, Zhu B. 2014. The abundance of antibiotic resistance genes in human guts has correlation to the consumption of antibiotics in animal. Gut Microbes 5:245–249. http://dx.doi.org/10.4161/gmic.27916. [PubMed]
21. Ebert D, Lipsitch M, Mangin KL. 2000. The effect of parasites on host population density and extinction: experimental epidemiology with Daphnia and six microparasites. Am Nat 156:459–477. http://dx.doi.org/10.1086/303404.
22. Flexner S. 1922. Experimental epidemiology. J Exp Med 36:9–14. http://dx.doi.org/10.1084/jem.36.1.9. [PubMed]
23. Greenwood M, Hill AB, Topley WWC, Wilson J. 1936. Experimental Epidemiology. Medical Research Council Special Report No. 209. Medical Research Council, London, United Kingdom.
24. May RM, Anderson RM. 1979. Population biology of infectious diseases: part II. Nature 280:455–461. http://dx.doi.org/10.1038/280455a0. [PubMed]
25. Webster LT. 1932. Experimental epidemiology. Medicine 11:321–344. http://dx.doi.org/10.1097/00005792-193209000-00002.
26. Kostic AD, Howitt MR, Garrett WS. 2013. Exploring host-microbiota interactions in animal models and humans. Genes Dev 27:701–718. http://dx.doi.org/10.1101/gad.212522.112. [PubMed]
27. Sharon G, Segal D, Ringo JM, Hefetz A, Zilber-Rosenberg I, Rosenberg E. 2010. Commensal bacteria play a role in mating preference of Drosophila melanogaster. Proc Natl Acad Sci U S A 107:20051–20056. http://dx.doi.org/10.1073/pnas.1009906107. [PubMed]
28. Cho I, Yamanishi S, Cox L, Methé BA, Zavadil J, Li K, Gao Z, Mahana D, Raju K, Teitler I, Li H, Alekseyenko AV, Blaser MJ. 2012. Antibiotics in early life alter the murine colonic microbiome and adiposity. Nature 488:621–626. http://dx.doi.org/10.1038/nature11400. [PubMed]
29. Semova I, Carten JD, Stombaugh J, Mackey LC, Knight R, Farber SA, Rawls JF. 2012. Microbiota regulate intestinal absorption and metabolism of fatty acids in the zebrafish. Cell Host Microbe 12:277–288. http://dx.doi.org/10.1016/j.chom.2012.08.003. [PubMed]
30. Baquero F. 2015. Causes and interventions: need of a multiparametric analysis of microbial ecobiology. Environ Microbiol Rep 7:13–14. http://dx.doi.org/10.1111/1758-2229.12242. [PubMed]
31. Campos M, Llorens C, Sempere JM, Futami R, Rodriguez I, Carrasco P, Capilla R, Latorre A, Coque TM, Moya A, Baquero F. 2015. A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES). Biol Direct 10:41. http://dx.doi.org/10.1186/s13062-015-0070-9. [PubMed]
32. Akinjogunla OJ, Odeyemi AT, Udoinyang EP. 2012. Cockroaches (Periplaneta americana and Blattella germanica): reservoirs of multi drug resistant (MDR) bacteria in Uyo, Akwa Ibom State. Sci J Biol Sci 1:19–30.
33. Schauer C, Thompson CL, Brune A. 2012. The bacterial community in the gut of the Cockroach Shelfordella lateralis reflects the close evolutionary relatedness of cockroaches and termites. Appl Environ Microbiol 78:2758–2767. http://dx.doi.org/10.1128/AEM.07788-11. [PubMed]
34. Engel P, Moran NA. 2013. The gut microbiota of insects—diversity in structure and function. FEMS Microbiol Rev 37:699–735. http://dx.doi.org/10.1111/1574-6976.12025. [PubMed]
35. Siegfried BD, Scott SC. 1996. Insecticide resistance mechanisms in the German cockroach, Blatella germanica. Am Chem Soc 96:218–229.
36. Dubus JC, Guerra MT, Bodiou AC. 2001. Cockroach allergy and asthma. Allergy 56:351–352. http://dx.doi.org/10.1034/j.1398-9995.2001.00109.x. [PubMed]
37. Menasria T, Moussa F, El-Hamza S, Tine S, Megri R, Chenchouni H. 2014. Bacterial load of German cockroach (Blattella germanica) found in hospital environment. Pathog Glob Health 108:141–147. http://dx.doi.org/10.1179/2047773214Y.0000000136. [PubMed]
38. Pai HH, Chen WC, Peng CF. 2005. Isolation of bacteria with antibiotic resistance from household cockroaches (Periplaneta americana and Blattella germanica). Acta Trop 93:259–265. http://dx.doi.org/10.1016/j.actatropica.2004.11.006. [PubMed]
39. Carrasco P, Pérez-Cobas AE, van de Pol C, Baixeras J, Moya A, Latorre A. 2014. Succession of the gut microbiota in the cockroach Blattella germanica. Int Microbiol 17:99–109. http://dx.doi.org/10.2436/20.1501.01.212. [PubMed]
40. López-Sánchez MJ, Neef A, Peretó J, Patiño-Navarrete R, Pignatelli M, Latorre A, Moya A. 2009. Evolutionary convergence and nitrogen metabolism in Blattabacterium strain Bge, primary endosymbiont of the cockroach Blattella germanica. PLoS Genet 5:e1000721. http://dx.doi.org/10.1371/journal.pgen.1000721. [PubMed]
41. Pérez-Cobas AE, Maiques E, Angelova A, Carrasco P, Moya A, Latorre A. 2015. Diet shapes the gut microbiota of the omnivorous cockroach Blattella germanica. FEMS Microbiol Ecol 91:fiv022. http://dx.doi.org/10.1093/femsec/fiv022. [PubMed]
42. Patiño-Navarrete R, Moya A, Latorre A, Peretó J. 2013. Comparative genomics of Blattabacterium cuenoti: the frozen legacy of an ancient endosymbiont genome. Genome Biol Evol 5:351–361. http://dx.doi.org/10.1093/gbe/evt011. [PubMed]
43. Sabree ZL, Kambhampati S, Moran NA. 2009. Nitrogen recycling and nutritional provisioning by Blattabacterium, the cockroach endosymbiont. Proc Natl Acad Sci U S A 106:19521–19526. http://dx.doi.org/10.1073/pnas.0907504106. [PubMed]
44. Blekhman R, Goodrich JK, Huang K, Sun Q, Bukowski R, Bell JT, Spector TD, Keinan A, Ley RE, Gevers D, Clark AG. 2015. Host genetic variation impacts microbiome composition across human body sites. Genome Biol 16:191. http://dx.doi.org/10.1186/s13059-015-0759-1. [PubMed]
45. Thompson CL, Wang B, Holmes AJ. 2008. The immediate environment during postnatal development has long-term impact on gut community structure in pigs. ISME J 2:739–748. http://dx.doi.org/10.1038/ismej.2008.29. [PubMed]
46. Hoy YE, Bik EM, Lawley TD, Holmes SP, Monack DM, Theriot JA, Relman DA. 2015. Variation in taxonomic composition of the fecal microbiota in an inbred mouse strain across individuals and time. PLoS One 10:e0142825. http://dx.doi.org/10.1371/journal.pone.0142825. [PubMed]
47. Ley RE, Hamady M, Lozupone C, Turnbaugh PJ, Ramey RR, Bircher JS, Schlegel ML, Tucker TA, Schrenzel MD, Knight R, Gordon JI. 2008. Evolution of mammals and their gut microbes. Science 320:1647–1651. http://dx.doi.org/10.1126/science.1155725. [PubMed]
48. Pluznick JL. 2014. Gut microbes and host physiology: what happens when you host billions of guests? Front Endocrinol (Lausanne) 5:91. http://dx.doi.org/10.3389/fendo.2014.00091. [PubMed]
49. Krishnan S, Alden N, Lee K. 2015. Pathways and functions of gut microbiota metabolism impacting host physiology. Curr Opin Biotechnol 36:137–145. http://dx.doi.org/10.1016/j.copbio.2015.08.015. [PubMed]
50. Yano JM, Yu K, Donaldson GP, Shastri GG, Ann P, Ma L, Nagler CR, Ismagilov RF, Mazmanian SK, Hsiao EY. 2015. Indigenous bacteria from the gut microbiota regulate host serotonin biosynthesis. Cell 161:264–276. http://dx.doi.org/10.1016/j.cell.2015.02.047. [PubMed]
51. Gross EM, Brune A, Walenciak O. 2008. Gut pH, redox conditions and oxygen levels in an aquatic caterpillar: potential effects on the fate of ingested tannins. J Insect Physiol 54:462–471. http://dx.doi.org/10.1016/j.jinsphys.2007.11.005. [PubMed]
52. Ryu JH, Kim SH, Lee HY, Bai JY, Nam YD, Bae JW, Lee DG, Shin SC, Ha EM, Lee WJ. 2008. Innate immune homeostasis by the homeobox gene caudal and commensal-gut mutualism in Drosophila. Science 319:777–782. http://dx.doi.org/10.1126/science.1149357. [PubMed]
53. Ke J, Sun JZ, Nguyen HD, Singh D, Lee KC, Beyenal H, Chen SL. 2010. In-situ oxygen profiling and lignin modification in guts of wood-feeding termites. Insect Sci 17:277–290. http://dx.doi.org/10.1111/j.1744-7917.2010.01336.x.
54. Brooks MA, Richards AG. 1955. Intracellular symbiosis in cockroaches. I. Production of aposymbiotic cockroaches. Biol Bull 109:22–39. http://dx.doi.org/10.2307/1538656.
55. Sacchi L, Nalepa CA, Bigliardi E, Lenz M, Bandi C, Corona S, Grigolo A, Lambiase S, Laudani U. 1998. Some aspects of intracellular symbiosis during embryo development of Mastotermes darwiniensis (Isoptera: Mastotermitidae). Parassitologia 40:309–316. [PubMed]
56. Sacchi L, Grigolo A. 1989. Endocytobiosis in Blattella germanica L. (BLATTODEA): recent acquisitions. Endocytobiosis Cell Res 6:121–147.
57. Sacchi L, Corona S, Grigolo A, Laudani U, Selmi MG, Bigliardi E. 1996. The fate of the endocytobionts of Blattella germanica (Blattaria: Blattellidae) and Periplaneta americana (Blattaria: Blattidae) during embryo development. Ital J Zool (Modena) 63:1–11. http://dx.doi.org/10.1080/11250009609356100.
58. Aguilera L, Marquetti MC, Fuentes O, Navarro A. 1998. Efecto de 2 dietas sobre aspectos biológicos de Blattella germanica (Dictyoptera: Blattellidae) en condiciones de laboratorio. Rev Cubana Med Trop 50:143–149. [PubMed]
59. Colman DR, Toolson EC, Takacs-Vesbach CD. 2012. Do diet and taxonomy influence insect gut bacterial communities? Mol Ecol 21:5124–5137. http://dx.doi.org/10.1111/j.1365-294X.2012.05752.x. [PubMed]
60. Yun JH, Roh SW, Whon TW, Jung MJ, Kim MS, Park DS, Yoon C, Nam YD, Kim YJ, Choi JH, Kim JY, Shin NR, Kim SH, Lee WJ, Bae JW. 2014. Insect gut bacterial diversity determined by environmental habitat, diet, developmental stage, and phylogeny of host. Appl Environ Microbiol 80:5254–5264. http://dx.doi.org/10.1128/AEM.01226-14. [PubMed]
61. Levin BR, McCall IC, Perrot V, Weiss H, Ovesepian A, Baquero F. 2017. A numbers game: ribosome densities, bacterial growth, and antibiotic-mediated stasis and death. mBio 8:e02253-16. https://doi.org/10.1128/mBio.02253-16. [PubMed]
62. Fadrosh DW, Ma B, Gajer P, Sengamalay N, Ott S, Brotman RM, Ravel J. 2014. An improved dual-indexing approach for multiplexed 16S rRNA gene sequencing on the Illumina MiSeq platform. Microbiome 2:6. http://dx.doi.org/10.1186/2049-2618-2-6. [PubMed]
63. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Peña AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R. 2010. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336. http://dx.doi.org/10.1038/nmeth.f.303. [PubMed]
64. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL. 2006. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72:5069–5072. http://dx.doi.org/10.1128/AEM.03006-05. [PubMed]
65. Hammad KM, Mahdy HM. 2012. Antibiotic resistant-bacteria associated with the cockroach, Periplaneta americana collected from different habitat in Egypt. N Y Sci J 5:198–206.
66. Haghi FM, Nikookar H, Hajati H, Harati MR, Shafaroudi MM, Yazdani-Charati J, Ahanjan M. 2014. Evaluation of bacterial infection and antibiotic susceptibility of the bacteria isolated from cockroaches in educational hospitals of Mazandaran University of medical sciences. Bull Environ Pharmacol Life Sci 3:25–28.
67. Wannigama DL, Dwivedi R, Zahraei-Ramazani A. 2013. Prevalence and antibiotic resistance of gram-negative pathogenic bacteria species isolated from Periplaneta americana and Blattella germanica in Varanasi, India. J Arthropod Borne Dis 8:10–20. [PubMed]
68. Atlas RM. 2010. Handbook of Microbiological Media, 4th ed. ASM Press, Washington, DC, and CRC Press, Boca Raton, FL.
69. Wu SW, Dornbusch K, Kronvall G, Norgren M. 1999. Characterization and nucleotide sequence of a Klebsiella oxytoca cryptic plasmid encoding a CMY-type β-lactamase: confirmation that the plasmid-mediated cephamycinase originated from the Citrobacter freundii AmpC β-lactamase. Antimicrob Agents Chemother 43:1350–1357. [PubMed]
70. Huang TW, Wang JT, Lauderdale TL, Liao TL, Lai JF, Tan MC, Lin AC, Chen YT, Tsai SF, Chang SC. 2013. Complete sequences of two plasmids in a blaNDM-1-positive Klebsiella oxytoca isolate from Taiwan. Antimicrob Agents Chemother 57:4072–4076. http://dx.doi.org/10.1128/AAC.02266-12. [PubMed]
71. Akingbade A, Balogun SA, Ojo DA, Afolabi RO, Motayo BO, Okerentugba PO, Okonko IO. 2012. Plasmid profile analysis of multidrug resistant Pseudomonas aeruginosa isolated from wound infections in South West, Nigeria. World Appl Sci J 20:766–775.
72. Schwarz FV, Perreten V, Teuber M. 2001. Sequence of the 50-kb conjugative multiresistance plasmid pRE25 from Enterococcus faecalis RE25. Plasmid 46:170–187 http://dx.doi.org/10.1006/plas.2001.1544. [PubMed]
73. Thompson JK, Collins MA. 2003. Completed sequence of plasmid pIP501 and origin of spontaneous deletion derivatives. Plasmid 50:28–35. http://dx.doi.org/10.1016/S0147-619X(03)00042-8. [PubMed]
74. Perreten V, Teuber M. 1995. Antibiotic resistant bacteria in fermented dairy products. A new challenge for raw milk cheeses? In Proceedings of the Symposium on Residues of Antimicrobial Drugs and other Inhibitors in Milk, 28-31 August 1995, Kiel, Germany. International Dairy Federation, Brussels, Belgium.
75. Tauch A, Krieft S, Kalinowski J, Pühler A. 2000. The 51,409-bp R-plasmid pTP10 from the multiresistant clinical isolate Corynebacterium striatum M82B is composed of DNA segments initially identified in soil bacteria and in plant, animal, and human pathogens. Mol Gen Genet 263:1–11. http://dx.doi.org/10.1007/PL00008668. [PubMed]
76. Horodniceanu T, Bouanchaud DH, Bieth G, Chabbert YA. 1976. R plasmids in Streptococcus agalactiae (group B). Antimicrob Agents Chemother 10:795–801. http://dx.doi.org/10.1128/AAC.10.5.795. [PubMed]
77. Silva-Rocha R, Martínez-García E, Calles B, Chavarría M, Arce-Rodríguez A, de Las Heras A, Páez-Espino AD, Durante-Rodríguez G, Kim J, Nikel PI, Platero R, de Lorenzo V. 2013. The Standard European Vector Architecture (SEVA): a coherent platform for the analysis and deployment of complex prokaryotic phenotypes. Nucleic Acids Res 41(D1):D666–D675. http://dx.doi.org/10.1093/nar/gks1119. [PubMed]
78. Vilanova C, Tanner K, Dorado-Morales P, Villaescusa P, Chugani D, Frías A, Segredo E, Molero X, Fritschi M, Morales L, Ramón D, Peña C, Peretó J, Porcar M. 2015. Standards not that standard. J Biol Eng 9:17. http://dx.doi.org/10.1186/s13036-015-0017-9. [PubMed]
79. Marshall BM, Levy SB. 2011. Food animals and antimicrobials: impacts on human health. Clin Microbiol Rev 24:718–733. http://dx.doi.org/10.1128/CMR.00002-11. [PubMed]
80. Martínez JL, Baquero F, Andersson DI. 2007. Predicting antibiotic resistance. Nat Rev Microbiol 5:958–965. http://dx.doi.org/10.1038/nrmicro1796. [PubMed]
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2018-01-04
2018-09-26

Abstract:

Antibiotic resistance is recognized as one of the major challenges in public health. The global spread of antibiotic resistance is the consequence of a constant flow of information across multi-hierarchical interactions, involving cellular (clones), subcellular (resistance genes located in plasmids, transposons, and integrons), and supracellular (clonal complexes, genetic exchange communities, and microbiotic ensembles) levels. In order to study such multilevel complexity, we propose to establish an experimental epidemiology model for the transmission of antibiotic resistance with the cockroach . This paper reports the results of five types of preliminary experiments with populations that allow us to conclude that this animal is an appropriate model for experimental epidemiology: (i) the composition, transmission, and acquisition of gut microbiota and endosymbionts; (ii) the effect of different diets on gut microbiota; (iii) the effect of antibiotics on host fitness; (iv) the evaluation of the presence of antibiotic resistance genes in natural- and lab-reared populations; and (v) the preparation of plasmids harboring specific antibiotic resistance genes. The basic idea is to have populations with higher and lower antibiotic exposure, simulating the hospital and the community, respectively, and with a certain migration rate of insects between populations. In parallel, we present a computational model based on P-membrane computing that will mimic the experimental system of antibiotic resistance transmission. The proposal serves as a proof of concept for the development of more-complex population dynamics of antibiotic resistance transmission that are of interest in public health, which can help us evaluate procedures and design appropriate interventions in epidemiology.

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Figures

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FIGURE 1

Loss of weight and size in due to antibiotic treatment after 25 days. (A) Insect treated with chlortetracycline 1 mg/ml. (B) Insect not treated with antibiotics.

Source: microbiolspec January 2018 vol. 6 no. 1 doi:10.1128/microbiolspec.MTBP-0007-2016
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FIGURE 2

Copy number of gene of genome in treated with chlortetracycline 10 mg/ml (A) and rifampicin 2 mg/ml (B). There is a strong reduction in the number of endosymbionts with chlortetracycline, whereas with rifampin at low dose no effect is observed. (C) Copy number of gene of genome in F1 progeny of treated with chlortetracycline 1 mg/ml.

Source: microbiolspec January 2018 vol. 6 no. 1 doi:10.1128/microbiolspec.MTBP-0007-2016
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FIGURE 3

Percentage of genus abundance (>1.5%) from three wild females.

Source: microbiolspec January 2018 vol. 6 no. 1 doi:10.1128/microbiolspec.MTBP-0007-2016
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FIGURE 4

Plasmid profiles of some of the isolates from the hindgut. V517 and PJB415, marker plasmids; Mλ, marker λ HindIII; V517, strain with plasmids used as markers; WB4, ; WB9, ; PJB415, plasmid marker 90 kb.

Source: microbiolspec January 2018 vol. 6 no. 1 doi:10.1128/microbiolspec.MTBP-0007-2016
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FIGURE 5

Experimental model of transmission of information about antibiotic resistance using an experimental model system with the aim of simulating the evolution of antibiotic (AB) resistance genes in human communities mimicking hospital and urban environments.

Source: microbiolspec January 2018 vol. 6 no. 1 doi:10.1128/microbiolspec.MTBP-0007-2016
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Tables

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TABLE 1

Antibiotic resistance genes found in the metagenomic analyses performed on three wild females

Source: microbiolspec January 2018 vol. 6 no. 1 doi:10.1128/microbiolspec.MTBP-0007-2016
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TABLE 2

Species identified and the antibiotics to which they show resistance after isolation of colonies belonging to the gut microbiota of 12 wild and 5 lab-reared individuals

Source: microbiolspec January 2018 vol. 6 no. 1 doi:10.1128/microbiolspec.MTBP-0007-2016

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