By Rob Knight, PhD, member of the scientific advisory board for the AGA Center for Gut Microbiome Research and Education, and his colleagues Daniel McDonald and Embriette R. Hyde, PhD
With microbiome associations being identified in dozens of diseases, including many GI disorders such as the IBD and IBS, there is much enthusiasm to fully characterize specific microbiome-disease associations. Two common strategies — both yielding different perspectives — for assaying the microbiome via DNA sequencing are target gene analysis and shotgun metagenomics. The former provides a coarse assessment of composition (i.e., who is there); the latter provides deeper taxonomic specificity and assessment of functional potential. Target gene analyses have been substantially cheaper to perform and therefore are the dominant type of analysis found in the literature.
Many target gene analyses use the Earth Microbiome Project 16S protocol, which targets a small region of the 16S ribosomal gene thought to exist in all bacteria and archaea. This “universal” protocol does a reasonable job of amplifying most of the organisms in these domains, although differentiating individual species is not usually possible. Target gene sequences can be fed into open source analytic platforms such as QIIME, which infer which organisms appear in which samples and the relative abundances of those organisms. Comparative analyses can then be performed, such as asking whether the composition of samples in a treatment group significantly differs from a control group, or whether specific taxonomic groups associated with different disease states.
Advancements in molecular techniques combined with cost decreases in DNA sequencing have made shotgun metagenomics a viable target for large studies. The general protocol relies on randomly shearing all of the DNA present in a sample, and sequencing a portion of it. Typically, the resulting data are fed into a package like HUMAnN2, which produces tables that describe the observed species, genes, and pathways. This type of analysis can attain higher taxonomic specificity as multiple genes can be used to assess what organism might be present. Critically, these analyses are very sensitive to the quality of the reference database used.
Using mass spectrometry to identify the presence of small molecules-host, environment or microbially-derived can also add critical information regarding microbiome function and interaction with the host or the environment. This information may prove critical in certain clinical contexts; for example, one can identify drug-microbe interactions specific to unique body sites. Tools such as GNPS can help facilitate small molecule analyses and network creation, and some of the resulting outputs are compatible with QIIME for further comparative analyses.
Both target gene analysis and shotgun metagenomics were performed on stool samples donated by AGA members for this year’s Microbiome Active Learning Session 200: The Nonbacterial Gut Microbiome in Health and Disease. Join us at this session during Digestive Disease Week® 2017 to learn more about these approaches and how they are used to understand the gut microbiota ecosystem — including and beyond bacteria.
- Pollan M. Some of my best friends are germs. The New York Times. 2013 May 15. Retrieved from http://www.nytimes.com/2013/05/19/magazine/say-hello-to-the-100-trillion-bacteria-that-make-up-your-microbiome.html
- Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature. 2012 Jun 13;486(7402):207-214. https://doi.org/10.1038/nature11234
- Gilbert JA, Quinn RA, Debelius J, Xu ZZ, Morton J, Garg N, Jansson JK, Dorrestein PC, Knight R. Microbiome-wide association studies link dynamic microbial consortia to disease. Nature. 2016 Jul 7;535(7610):94-103. https://doi.org/10.1038/nature18850
This article is part of the AGA Microbiome Update. AGA members — check your email on Friday, April 28, for more gut microbiome updates and news.