Adaptive resistance to antibiotics in bacteria: a systems biology perspective.
Despite all the major breakthroughs in antibiotic development and treatment procedures, there is still no long-term solution to the bacterial antibiotic resistance problem. Among all the known types of resistance, adaptive resistance (AdR) is particularly inconvenient. This phenotype is known to emerge as a consequence of concentration gradients, as well as contact with subinhibitory concentrations of antibiotics, both known to occur in human patients and livestock. Moreover, AdR has been repeatedly correlated with the appearance of multidrug resistance, although the biological processes behind its emergence and evolution are not well understood. Epigenetic inheritance, population structure and heterogeneity, high mutation rates, gene amplification, efflux pumps, and biofilm formation have all been reported as possible explanations for its development. Nonetheless, these concepts taken independently have not been sufficient to prevent AdR's fast emergence or to predict its low stability. New strains of resistant pathogens continue to appear, and none of the new approaches used to kill them (mixed antibiotics, sequential treatments, and efflux inhibitors) are completely efficient. With the advent of systems biology and its toolsets, integrative models that combine experimentally known features with computational simulations have significantly improved our understanding of the emergence and evolution of the adaptive-resistant phenotype. Apart from outlining these findings, we propose that one of the main cornerstones of AdR in bacteria, is the conjunction of two types of mechanisms: one rapidly responding to transient environmental challenges but not very efficient, and another much more effective and specific, but developing on longer time scales. WIREs Syst Biol Med 2016, 8:253-267. doi: 10.1002/wsbm.1335 For further resources related to this article, please visit the WIREs website.
Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico.
Santiago
S
Sandoval-Motta
Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico.|Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, Mexico.
Maximino
M
Aldana
D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D001419:Bacteria / Q000187:drug effects* / Q000235:genetics / Q000378:metabolism; D004249:DNA Damage / Q000187:drug effects; D019175:DNA Methylation; D004260:DNA Repair / Q000187:drug effects; D024881:Drug Resistance, Bacterial / Q000187:drug effects; D026901:Membrane Transport Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D049490:Systems Biology / Q000379:methods*
D000900:Anti-Bacterial Agents; D026901:Membrane Transport Proteins