Experimental epidemiology of antibiotic resistance: looking for an appropriate animal model system
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Cita bibliográficaLlop, P., Latorre, A. & Moya, A. (2018). Experimental Epidemiology of Antibiotic Resistance: Looking for an Appropriate Animal Model System. Microbiology Spectrum, 6(1).
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 Blatella germanica. This paper reports the results of five types of preliminary experiments with B. germanica 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.