A Museum-led study published today in the journal Scientific Reports finds that some next-generation DNA sequencing techniques—which let scientists analyze billions of fragments of genetic material at once—may not be as accurate as previously thought when it comes to measuring microbial biodiversity.
Researchers compared two techniques that are commonly used to sequence microbial DNA—amplicon sequencing, which looks at the same gene in every sample, and the so-called shotgun technique, which sequences random fragments of DNA. To make their comparison, the authors analyzed the contents of water samples from rivers throughout Brazil using both methods.
The differences were stark: shotgun sequencing recognized less than half of the phyla, or broad groups of organisms, that were found using amplicon sequencing.
“You can think about the phyla Cnidaria, which contains all of the world’s anemones, corals, and jellyfish—one method would find a representative from this group, and the other would not,” says senior author Mercer R. Brugler, a research associate in the Museum’s Division of Invertebrate Zoology and an assistant professor at NYC College of Technology, CUNY. "Phyla are huge groups that are completely missing from the shotgun sequencing data.”
The findings could have serious implications for research into microbial diversity. Although amplicon sequencing has been the workhorse for studies on microbial life, the spike in human microbiome research inspired many scientists to switch to shotgun, which is cheaper and faster.
Previous human microbiome studies comparing the two techniques have also shown that shotgun produces equivalent or better results, so researchers involved in this study were surprised when they found something very different.
“After our earlier publication on these samples, we switched from amplicon to shotgun, with the intention of simply getting larger sample sizes,” says lead author Michael Tessler, who just completed his Ph.D. at the Museum’s Richard Gilder Graduate School. “We thought the shotgun data were at least going to be equal, if not rock the socks off of the amplicon data.”
The explanation behind these disparate results may lie in the databases that genetic analyses reference. Since shotgun sequencing analyzes random fragments of DNA, it requires researchers to have a strong database they can use to match the sequences to an organism. If the data for that organism do not exist, you only get the closest match, or no match at all. For this study, which looks at understudied freshwater bacteria, the database is extremely weak, suggesting that shotgun analysis may not be the best way to survey for new forms of microscopic life.
“Studies to date that have used shotgun alone to infer microbial diversity estimates should be viewed cautiously, as they are likely underestimating true diversity,” says Brugler.