期刊
FRONTIERS IN MICROBIOLOGY
卷 4, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fmicb.2013.00145
关键词
functional metagenomics; antibiotic resistance; bifunctional resistance gene; environmental resistance; resistance reservoir; transferable resistance
类别
资金
- Children's Discovery Institute of Washington University and St. Louis Children's Hospital [MD-II-2011-117]
- March of Dimes Foundation [6-FY12-394]
- Kenneth Rainin Foundation [12H1]
- National Institutes of Health [DP2-DK098089, R01-GM099538]
- Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program
- National Science Foundation [DGE-1143954]
Rates of infection with antibiotic-resistant bacteria have increased precipitously over the past several decades, with far-reaching healthcare and societal costs. Recent evidence has established a link between antibiotic resistance genes in human pathogens and those found in non-pathogenic, commensal, and environmental organisms, prompting deeper investigation of natural and human-associated reservoirs of antibiotic resistance. Functional metagenomic selections, in which shotgun-cloned DNA fragments are selected for their ability to confer survival to an indicator host, have been increasingly applied to the characterization of many antibiotic resistance reservoirs. These experiments have demonstrated that antibiotic resistance genes are highly diverse and widely distributed, many times bearing little to no similarity to known sequences. Through unbiased selections for survival to antibiotic exposure, functional metagenomics can improve annotations by reducing the discovery of false positive resistance and by allowing for the identification of previously unrecognizable resistance genes. In this review, we summarize the novel resistance functions uncovered using functional metagenomic investigations of natural and human-impacted resistance reservoirs. Examples of novel antibiotic resistance genes include those highly divergent from known sequences, those for which sequence is entirely unable to predict resistance function, bifunctional resistance genes, and those with unconventional, atypical resistance mechanisms. Overcoming antibiotic resistance in the clinic will require a better understanding of existing resistance reservoirs and the dissemination networks that govern horizontal gene exchange, informing best practices to limit the spread of resistance conferring genes to human pathogens.
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