Insights into Antibiotic Resistance Through Metagenomic Approaches

Robert Schmieder; Robert Edwards


Future Microbiol. 2012;7(1):73-89. 

In This Article

Future Perspective

The application of metagenomics will not only facilitate future identification of novel resistance genes, but will be used for the prediction of future evolution of antibiotic resistance and will enable further studies on genetic elements participating in resistance gene transfer.

Within the next few years, we will see the application of metagenomics or sequence-based technologies in almost every part of life and biomedical sciences, in particular in clinical diagnostic settings. To date, most sequence-based metagenomic studies are performed in research laboratories using the Roche/454 and Illumina systems (Figure 5). With the promises of third-generation sequencing technologies, such as higher throughput (amounts of DNA that can be processed per unit time) with increased accuracy, longer read lengths, lower cost, smaller amounts of starting material and shorter turnaround times (time to result), these technologies are anticipated to transition into clinical-diagnostics use over the next several years. In June 2011, the US FDA held a public meeting to discuss the use of ultra high-throughput sequencing for clinical diagnostic applications. In addition to sequencing technologies, the bioinformatics analysis of the sequence data was a major focus of the meeting. The large amounts of sequence data generated with next-generation sequencing technologies pose a bioinformatics challenge for the clinical laboratory to provide data processing and interpretation to the clinicians. New algorithms, visualization tools, and data abstractions will be needed to cope with the challenges presented by this data.

High-throughput sequencing allows for global analysis of commensal populations and potential identification of distinct signatures in the human microbiome. As sequencing becomes less expensive, repeated sampling of the metagenome of a microbial community can be used to evaluate changes in the community over time, and whole-body metagenome approaches can be applied in large-scale research and clinical studies. For example, urine and feces provide two windows that reflect the health status of the human body, and sequencing the microbiomes associated with these samples will provide a snapshot of overall health. We will also move towards personalized prescriptions, a subset of the genome-inspired personalized medicine. Antibiotic treatment of high-risk patients will not stop, but metagenomics will help us understand the effects of different classes of antibiotics on the composition and function of commensal and pathogenic microbial populations. These insights will allow the switch from broad- to narrow-spectrum antibiotics, antibiotics that target very specific pathogens, and very specific courses of treatment instead of the standard 7–10 days. In addition, a new category of therapeutics will be developed that target the microbiota and modulate microbe–microbe and microbe–human interactions. These therapeutics will allow us to alter the composition of the microbial community, endowing it with new functions, and use the sequences of the microbiota to diagnose disease. In the future, this might be integrated into daily life; for example, DNA sequencers in toilet bowls that automatically follow changes of the human microbiome and suggest appropriate antibiotic treatment.