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Study Points to Limitations of Genomic Microbiome Analyses

Using computer-generated bacterial populations, scientists from the Centro de Investigaciones Biologicas Margarita Salas have found that current genomic approaches for microbiome identification can lead to false results. Determining the composition of microbial populations is typically done by comparing DNA sequences from the populations with sequences in databases. Hypothesizing that these kinds of analyses are constrained by the amount of information in such databases, the researchers generated and analyzed virtual bacterial populations with the same ecological structures of real-world microbiomes, then compared the results against the original composition. As reported in PLOS One this week, they show that the microbes identified via DNA analyses can be very different from the actual microbial composition of the community analyzed, with some species detected not actually being present. "If microbiome data are to be useful in an effective and reproducible manner," the study's authors write, "the effort in the field must be channeled toward significantly increasing the amount of available genomic information and finding efficient ways to use this information."

The Scan

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