Automated in vitro microbiome screening (AiMS)

Nature Portfolio Journal

Several bioactive components of the human diet have major effects on composition and function of the gut microbiome, but no systematic framework exists for understanding variation in microbiome-active components amid the vast amount of genotypic and phenotypic variation within a given species of food crop. Here we present a powerful new approach for complex trait analysis of Microbiome-Active Traits (MATs) in food crops. Capitalizing on a novel automated in vitro microbiome screening (AiMS) methodology to quantify human gut microbiome phenotypes after fermentation of grain from genetically diverse lines, we show how microbiome phenotypes can be used as quantitative traits for genetic analysis. Quantitative Trait Locus (QTL) analysis of AiMS-based phenotypes across grain samples from 294 sorghum (Sorghum bicolor) recombinant inbred lines identified significant QTLs at 10 different genomic regions that collectively control MATs affecting 16 different microbial taxa. Segregation analysis and validation in Near-Isogenic Lines (NILs) confirmed that overlapping QTL peaks for microbiome phenotypes, seed color, and tannin concentration are driven by variation in the Tan2 (chromosome 2) and Tan1 (chromosome 4) regulators of the tannin biosynthetic pathway. Candidate genes at other QTLs suggest that variation in a diverse array of plant molecules can drive MATs.

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Complex Trait Analysis of Human Gut Microbiome-Active Traits in Sorghum bicolor: a new category of human health traits in food crops

Qinnan Yang 1,2, Mallory Van Haute 1,2, Nate Korth 2,3, Scott E. Sattler 4,5, John Toy 4,5, Devin Rose 1,2,5, James C. Schnable 2,5,6, and Andrew K. Benson 1,2