Research out of the University of Minnesota Genomics Center highlights an improved method for profiling the microbiome, providing more accurate data in a rapidly expanding research area.
What is the microbiome? Microbiomes are the communities of microorganisms residing on or inside humans and animals, or in the environment. Understanding the microbiome is important as it can play a key role in the healthy function of the body or of an ecosystem.
What they found: “There are a dozens of methods currently being used to classify microbes based on their ribosomal RNA gene sequences,” said Kenneth Beckman, Ph.D., director of the UMN Genomics Center and senior author. “Results are highly dependent on your experimental setup, and the large number of variables that affect accuracy and methods in the field have made it so data is difficult or impossible to compare across studies.”
The research, which identified a number of factors that contribute to errors and biases potentially leading to irreproducible results or erroneous conclusions, is published online in the journal Nature Biotechnology. Understanding how biases arise in the data allowed the researchers to design a method that minimizes amplification bias and improves accuracy. The method is available at Protocol Exchange.
This study improves one important step in the process, but making measurements of the microbiome is a multi-step process involving sample collection, storage, DNA extraction, DNA amplification, and sequencing. Because each step has an opportunity to introduce bias, researchers are now exploring ways to eliminate bias in other portions of the protocol.
Microbiomes are trending: Focus on this line of research has grown dramatically in recent years, and the White House has recently announced a Microbiome Initiative charged with utilizing interdisciplinary research to create new technologies.
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