The new method takes current testing one step further.
Gang Fang, PhD
Scientists have developed a new method to identify microbial species and strains in an environment, according to a new report.
A joint team of researchers from Mount Sinai, Sema4 (a health information company based in Stamford, Conn.), and other institutions built upon existing characterization tools that sorted microbial communities in the human microbiome into “bins.” The bins are advanced, but the research team took it a step further.
The team combined the use of Single Molecule, Real Time Sequencing technology and new computer tools to sort microbes after analyzing their genetic code and methylation patterns. These methods are more advanced than the standard protocols, they added, and have the ability to correct errors and incomplete results than other methods may use in identifying microbes.
The researchers believe this method should be able to find an association between genetic elements and their bacterial hosts. Today, most techniques that identify microbial members from microbiome samples aren’t clear enough; for example, a species might only be identified as part of a broader genetic family, instead of identifying it further and more uniquely. Additionally, these methods are not effective in how they characterize the genetic elements.
They hope that scientists can predict variables such as the virulence, antibiotic resistance, and other biologically and clinically critical traits of individual bacterial species and strains, according to a press release.
“The most striking observation of this study is that we found that DNA methylation events, prevalent in microbial genomes, have rich diversity and patterns can be exploited as highly informative natural barcodes to help discriminate microbial species from each other, help associate mobile genetic elements to their host-genomes and achieve more precise microbiome analysis,” senior study author Dr. Gang Fang, PhD, Mount Sinai, explained to MD Magazine.
In the pilot project using this method, which was tested on synthetic and actual microbiome samples, the researchers were able to differentiate between related strains and individual bacterial species. The methylation patterns that linked DNA sequence data showed additional information about these individual organisms, the study authors determined. They tested the tool in low- to medium-complexity microbial communities and are currently working toward developing the method for testing in high complexity communities — such as environmental microbiomes.
Dr. Fang added that the newly developed method could also be used to assemble pathogenic genomes directly from microbiome samples. That would underscore better efficiency (without the need for a culture), higher resolution (to differentiate between closely related species versus similar strains), and better completeness (linking plasmids to chromosomes). All of these, he said, are important in the clinical setting, because the plasmids often encode antibiotic resistance genes and virulence genes. Therefore, it’s vital to understand the full genetic potential of a pathogen for precision antibiotics prescriptions.
“The new method can also be used for monitoring the transmission of plasmids and bacteriophages between bacterial hosts across multiple time points or conditions, such as antibiotic treatment,” Dr. Fang concluded.
The paper, titled “Metagenomic binning and association of plasmids with bacterial host genomes using DNA methylation,” was published in the journal Nature Biotechnoloy.
The press release is here.