Metagenomics and antibiotics

Abstract

Most of the bacterial species that form part of the biosphere have never been cultivated. In this situation, a comprehensive study of bacterial communities requires the utilization of non-culture-based methods, which have been named metagenomics. In this paper we review the use of different metagenomic techniques for understanding the effect of antibiotics on microbial communities, to synthesize new antimicrobial compounds and to analyse the distribution of antibiotic resistance genes in different ecosystems. These techniques include functional metagenomics, which serves to find new antibiotics or new antibiotic resistance genes, and descriptive metagenomics, which serves to analyse changes in the composition of the microbiota and to track the presence and abundance of already known antibiotic resistance genes in different ecosystems.

Genetic elements associated with antimicrobial resistance among avian pathogenic Escherichia coli

“…The following antimicrobial discs (Oxoid, Basingstoke, UK) were used: gentamicin (GN, 10 μg), kanamycin (KAN, 30 μg), ampicillin (AMP, 10 μg), cefotaxime (CTX, 30 μg), nalidixic acid (NA, 30 μg), ciprofloxacin (CIP, 5 μg), tetracycline (TET, 30 μg), sulfamethoxazole-trimethoprim (STX, 25 μg), chloramphenicol (C, 30 μg), and streptomycin (S, 10 μg). The isolates were defined as multidrug-resistant APEC if they exhibited resistance to at least one agent in three or more antimicrobial categories [8]. Escherichia coli strain ATCC 25922 was used as a reference strain for susceptibility test.…”

Ecotoxicological assessment of antibiotics: A call for improved consideration of microorganisms

“…These approaches have been proposed as 'leading the revolution in ecotoxicology' (GarciaReyero and Perkins, 2011) and allow for deeper interrogation of microbial communities than previously possible (Armengaud, 2013;Fierer et al, 2013;Garmendia et al, 2012;Hazen et al, 2013;Jones et al, 2014;Simon and Daniel, 2011). Hence, there is little doubt that these techniques will transform our understanding of how environmental stressors affect microorganisms (Lankadurai et al, 2013;Nesatyy and Suter, 2007;Pillai et al, 2014;Schirmer et al, 2010).…”

Stochasticity, Bistability and the Wisdom of Crowds: A Model for Associative Learning in Genetic Regulatory Networks

“…For example, many bacteria produce antibiotics that are harmful to other strains [59]. Other bacteria are sensitive to these damaging antibiotics and respond to their presence by activating a pre-wired stress response, such as the multiple antibiotics response (MAR) [60].…”