In an elegantly presented review, Fouhy and coauthors (2015) discuss the case for combining proteomics into the metagenomics workflow currently in operation for examining factors of microbial resistance that threaten to scupper modern medicine.1
Antibiotic resistance has been around since…well, since before the advent of antibiotic use in medicine. However, the recent development of microbial resistance threatens to outpace novel antibiotic discovery in clinical practice. This worrying forecast could render a lot of modern clinical practice obsolete with a rise in sepsis and death from the complications brought about by infection.
Fouhy et al., noting that more than 80% of our modern antibiotics are sourced from soilborne microorganisms, acknowledge that the soil resistome is a good source for information regarding resistance mechanisms. Citing a plethora of existing studies that document novel resistance genes, pathways and products in soil-based bacteria, the reviewers advise implementation of proteomics-based study alongside the current metagenomics workflows used to characterize major elements in the resistome.
Providing a brief and concise recap of existing methodologies, Fouhy et al. describe the workflows required to extract resistome data from the soil and other reservoirs such as the gut. One approach is to focus on the culturable resistome of this medium. By culturing diverse microbiomes, researchers have been able to screen the products using selective media and demonstrate the presence of antibiotic resistance. With selective culture of these colonies, scientists can focus on microbes bearing this trait.
From this first step, molecular techniques such as polymerase chain reaction (PCR) are implemented to detect resistance genes. However, one drawback of the molecular approach is that it requires prior knowledge of resistance gene structures to create the necessary primers for the reaction. Another drawback is that there are no defined criteria to classify a mechanism or organism as resistant, or indeed to quantify the degree of resistance. Finally, many soilborne organisms are not easy to culture.
As a method for analyzing entire resistomes rather than single species, metagenomics has the potential to expand the resistome database. Fouhy et al. introduce this sequence-based technique for broad analysis of the total DNA obtained from a microbiome, and with application of functional metagenomics, it can identify resistance genes without the need to culture organisms in vitro. This approach requires cloning genetic material into plasmids, for example, followed by screening for a conferred resistance phenotype.
Proteomics, the final step suggested by the authors for examining antibiotic resistance, could provide functional classification for transcriptomic data gathered. Characterizing the proteome of bacteria showing antibiotic resistance and comparing it to species without the resistance phenotype is possible with proteomic tools such as mass spectrometry, fluorescent labeling and other quantitative strategies. As the authors describe, this approach can give more information than simply looking at gene expression and RNA transcription. They suggest that coupling proteomics to functional metagenomics could expand the study of antibiotic resistance, and give examples of published work where this has indeed been accomplished. In coupling the two approaches, researchers gain valuable information on how microbes develop antibiotic resistance; this knowledge could in turn help develop strategies for avoiding this resistance in the future, thus maintaining the success of antibiotic treatment in clinical practice.
1. Fouhy, F., et al. (2015) “Proteomics as the final step in the functional metagenomics study of antimicrobial resistance,” Frontiers in Microbiology 6(172), doi:10.3389/fmicb.2015.00172 .