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Researchers design AI method to predict metabolomic profiles of microbial communities

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Human bodies contain trillions of microbes, so much that the number of microbes rival the number of human cells in a body. These microbes help shape many of our biological functions. For example, microbes in the gut break down food into small molecules called metabolites, many of which are important for human health. Measuring species composition of the microbial community using metagenomics has become a quick and automated process, while measuring the concentrations of metabolites produced by those microbes, a process called metabolomics, is much more difficult and expensive.

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Predicting microbial interactions in the human gut

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The human gut consists of a complex community of microbes that consume and secrete hundreds of small molecules—a phenomenon called cross-feeding. However, it is challenging to study these processes experimentally. A new study, published in Nature Communications, uses models to predict cross-feeding interactions between microbial species in the gut. Predictions from such computational methods could eventually help doctors get a more complete understanding of gut health.

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CRISPR-induced immune diversification in host-virus populations

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Just like humans, microbes have equipped themselves with tools to recognize and defend themselves against viral invaders. In a continual evolutionary battle between virus and host, CRISPR-Cas acts as a major driving force of strain diversity in host-virus systems.

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Mathematical models provide snapshot of human gut microbial community

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Microbial communities can be found everywhere – from lakes to the soil on the ground, they are omnipresent yet invisible to the naked eye. Within those environments there exist dynamic communities which fluctuate in response to environmental changes. One such example is the human gut microbiome, which is comprised of microbes that influence the overall landscape of the gut.

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