Insights into Antibiotic Resistance Through Metagenomic Approaches

Robert Schmieder; Robert Edwards


Future Microbiol. 2012;7(1):73-89. 

In This Article


We are dependent on antibiotics for the treatment of infectious diseases and they are critical for the success of advanced surgical procedures, such as organ and prosthetic transplants. Antibiotic-resistance mechanisms create an enormous clinical and financial burden on healthcare systems worldwide. Despite the problem of antibiotic resistance in infectious bacteria, little is known about the diversity, distribution and origins of resistance genes, especially for the unculturable majority of environmental bacteria.

There exists high-level resistance both to antibiotics that have for decades served as gold standard treatments and to those only recently approved for human use. The study of the environmental resistance reservoir using metagenomic approaches will provide an early warning system for future clinically relevant antibiotic-resistance mechanisms. Knowledge of such natural variations will complement studies on clinical isolates to guide the rational development of next-generation antibiotics that will be active against resistant strains.

Functional and sequence-based metagenomics have been used for the discovery of novel resistance determinants and the improved understanding of antibiotic resistance mechanisms. Metagenomic sequence data can be used to generate sample-specific and temporal antibiotic resistance profiles to facilitate an understanding of the ecology of the microbial communities in an environment as well as the epidemiology of antibiotic resistance gene transport between and among environments.

Traditional approaches to antibiotic resistance typically concentrate on human pathogens. There is a clear need to expand the focus to include nonpathogenic bacteria in antibiotic research. This may allow researchers to predict resistance before it emerges clinically; to develop diagnostic techniques, and to build new therapeutic strategies to counteract resistance before it emerges in human pathogens. With respect to functional metagenomics, we need to develop and apply new approaches to cultivate the previously uncultivated and rare members of the microbial communities to assign functions to the vast number of unknown or hypothetical genes, and to develop novel genetic systems that allow screening of the vast array of microbes on earth to identify antibiotic-resistance genes.

Sequence-based metagenomics allows the comparison of microbial communities from different hosts to investigate differences in the response to antibiotics and to select the most favorable antibiotic to reduce side effects for certain hosts.

The transition of next-generation sequencing into clinical diagnostics is in the early stages of development in large reference laboratories and is being leveraged for applications that require large amounts of sequence information. Sequence-based metagenomic data has the ability to combine antibiotic-resistance gene abundance data with community composition and metabolic pathway information to provide a more complete profile of specific samples. This information is of great importance for the implementation of rational administration guidelines for antibiotic therapies. We may also use these techniques to learn how human-associated microbes can be manipulated by antibiotics or probiotics to reduce our dependency on antibiotics, provide alternatives to existing antibiotics, and extend the lifetime of current and new antibiotics.

Many questions remain: the roles of the environmental reservoirs in clinical resistance development are still hypothetical; we have little or no evidence that any of the putative resistance genes identified in the environmental studies have been mobilized into pathogenic bacteria and expressed as resistance phenotypes; we do not know how to rapidly identify new resistance genes; and functional approaches are still relatively low throughput.