ArticlebioRxiv : the preprint server for biology2026
Discovery of a Human Metabolite that Mimics the Bacterial Quorum-Sensing Autoinducer AI-2.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Bacteria use small molecules to orchestrate collective behaviors in a process called quorum sensing (QS), which relies on the production, release, and group-wide detection of extracellular signal molecules referred to as autoinducers. One QS autoinducer, termed AI-2, is broadly used for inter-species bacterial communication, including in the mammalian gut. AI-2 consists of a family of interconverting compounds and adducts originating from 4,5-hydroxy-2,3-pentanedione. This complex speciation, coupled with the inherent instability of AI-2 congeners, have complicated isolation efforts. It has been known that mammalian epithelial cells produce an AI-2 mimic to which bacteria respond. However, the identity of the AI-2 mimic has remained elusive, presumably due to its instability, similar to that of known AI-2 compounds. Here, we developed a reactivity-based metabolomics approach to capture and identify a mammalian AI-2 mimic. Using a chemical strategy targeted at the α-diketone moiety of known AI-2s, we identify the unusual sugar L-xylosone, as well as the related metabolite L-xylulose, as AI-2 mimics. While L-xylulose is a common and naturally occurring sugar known in human metabolism, L-xylosone is a rare and highly reactive oxidation product. We established a facile synthetic route to access pure enantiomers of xylosone and confirmed that, like AI-2, the L-configuration is required for recognition by the bacterial AI-2 receptor, LuxP, whereas D-xylosone is inactive. L-xylosone is new to the human metabolome, suggesting that other chemically reactive small molecules that mediate host-microbe interactions await discovery. The identification of L-xylosone expands the AI-2 family of molecules and adds a new word to the lexicon of host-bacterial interactions.
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