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Discovery of a hydrolysis operon in Lachnospiraceae provides a genetic basis to understanding castalagin metabolism by the human microbiome in a clinical study.

Gut microbes metabolize the ellagitannin castalagin to ellagic acid and urolithins, a process associated with health effects for the host. Despite the use of the castalagin-rich camu camu extracts in clinical trials, the genes and taxa responsible for castalagin hydrolysis remain elusive. We used multi-omics to discover a castalagin associated hydrolase (cah) operon sparsely distributed in…

Researchers have uncovered the genetic basis of how gut microbes break down the compound castalagin, leading to the production of beneficial metabolites in the human microbiome. Castalagin, found in ellagitannin-rich compounds like camu camu, is metabolized into ellagic acid and urolithins, which are associated with positive health effects.

Despite clinical trials using camu camu extracts, the specific genes and microbial species responsible for castalagin hydrolysis remained unknown. To solve this mystery, scientists used multi-omics techniques to identify a castalagin-associated hydrolase (cah) operon within the Lachnospiraceae family of bacteria. By analyzing fecal samples from participants in a camu camu supplementation trial, researchers found that the prevalence of the cah operon and other genes involved in ellagic acid metabolism correlated with the presence of these metabolites.

Using genome mining strategies, they discovered and validated the presence of ellagitannin metabolism genes in previously uncharacterized and uncultured species. Additionally, they identified flavogallonic acid as another significant metabolite produced from castalagin in human feces. This groundbreaking work establishes a genetic foundation for understanding how the human microbiome processes castalagin, urolithins, and flavogallonic acid, paving the way for further exploration of the role these metabolites play in clinical trials.

Written by urgent.news from bioRxiv's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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