NEW YORK (GenomeWeb) – According to a new study published today in Nature Microbiology, techniques for analyzing metagenomic sequence data can uncover detailed information about specific microbial strains.
A team led by researchers from the Fondazione Edmund Mach and the University of Trento in Italy, demonstrated that different strains of a highly recombinant microbe present in oral microbiomes clustered in different regions of the mouth and that the strains have acquired mutations allowing them to adapt to their specific microenvironments.
In the study detailing its methods, the team wrote that the metagenomic approach could be applied to other microbes and could eventually enable researchers to "investigate microbiome strains with a resolution comparable to what is routinely achieved with single-isolate sequencing."
Metagenomic sequencing provides a good way to assess the microbial makeup of a mixed sample, including bacterial strains that cannot be cultured. However, the technique often does not allow for detailed analysis of the individual strains, particularly when analyzing differences between strains of the same genus.
In their study, the researchers used a variety of analysis tools to assess bacteria from the genus Neisseria, a highly recombinant bacteria that is present in oral microbiomes and that includes both benign and pathogenic strains.
"Characterizing the virulence potential of individual strains and their population genomics from sequence information is currently a challenge, in particular when using culture-free metagenomic sequencing," the authors wrote.
To get around this problem, they developed computational tools that allowed them to first identify the core conserved genomic regions in Neisseria, in order to build a map of genetic variability. (Such a technique has previously been used in cultured bacteria, but not with metagenomic samples.) Next, they aligned metagenomic sequence reads to the core conserved regions, which enabled them to identify genetic patterns that were characteristic of the different strains in the sample. They then combined that approach with multi-locus sequence typing and used genetic signatures to further pick apart the individual strains.
They tested the tools on 520 oral microbiome samples previously sequenced as part of the Human Microbiome Project. First they defined the core genome by aligning sequences to a reference N. meningitidis genome. They then used the SNPs found in metagenomic sequence data to identify the various Neisseria strains in each sample.
The researchers found two distinct groups of species — those from the tongue dorsum and those from gingival plaque. They also noted the presence of a third group consisting of two distinct species present in the throat, "highlighting how strains from different species are closely associated with samples from specific body sites."
Next, the authors looked at short 12-base-pair genetic features known as DUSs that are unique to the individual species as a means to identify specific species within a mixed sample. This confirmed their previous finding of a dominant species for each specific microenvironment in the oral microbiome. They then used multi-locus sequence typing (MLST) — a widely used tool for characterizing bacterial strains — to identify strain-specific alleles from the metagenomic data, and identified 362 sequence types, 26 of which were in more than one sample. Of those 26, 21 were previously unknown.
"These results suggest that the diversification of this group of species has been driven by clonal expansion accompanied by accumulation of adaptive mutations and genomic modifications specific to the microenvironments in the oral cavity," the authors wrote.
The researchers were able to use the genomic markers that they identified, as well as multiple samples taken at different time points from the same individual, to analyze how the composition of species changed within the same individual over time. Although the numbers were too small to draw firm conclusions, they found that for samples from the tongue, the species were consistent over time.
Culture-free methods to track bacterial strains is a "first step toward mapping their role and interactions in the microbiome," the authors wrote. For example, they added, being able to track Neisseria could "shed more light on the development of natural immunity and the impact of containment strategies based on vaccination. It could also help identify factors that might predispose to disease and provide a means for early detection of the clonal waves that often precede disease outbreaks."