Back

A high-throughput microbial glycomics platform for prebiotic development

Modesto, J. L.; Kabonick, S. G.; Lausch, J. E.; Verma, K.; Winokur, K. M.; Gaydos, J. E.; Poudel, A.; Yochum, G. S.; Townsend, G. E.

2025-08-02 molecular biology
10.1101/2025.07.13.664583 bioRxiv
Show abstract

The mammalian intestine contains diverse carbohydrate pools that govern the gut microbiome composition. Structurally distinct polysaccharides, also called glycans, are differentially consumed by gut microbial subsets and direct their abundance by controlling gene expression and metabolite production. Therefore, identifying gut microbial accessible carbohydrates (MACs) is necessary to develop new prebiotics that beneficially manipulate the gut microbiome. However, no methods exist to efficiently examine MACs in biologically-derived mixtures. Here, we present a high-throughput platform to detect MACs from various plant, animal, and microbial sources using a genome-wide library of engineered Bacteroides thetaiotaomicron (Bt) strains that harness their endogenous glycan detection machinery. We demonstrate that this platform exhibits specific and sensitive responses to glycan mixtures and use bacterially-encoded proteins to characterize a previously unknown MAC from yeast. Expanding this technology across gut Bacteroides species will generate a broadly applicable approach to characterize heterogeneous glycan mixtures and identify prebiotic substrates.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.