Back

Restoring the Multiple Sclerosis Associated Imbalance of Gut Indole Metabolites Promotes Remyelination and Suppresses Neuroinflammation

Jank, L.; Singh, S. S.; Lee, J.; Dhukhwa, A.; Siavoshi, F.; Joshi, D.; Minney, V.; Gupta, K.; Ghimire, S.; Deme, P.; Schoeps, V. A.; Soman, K.; Ladakis, D.; Smith, M.; Borkowski, K.; Newman, J.; Baranzini, S. E.; Waubant, E. L.; Fitzgerald, K. C.; Mangalam, A. K.; Haughey, N.; Kornberg, M. D.; Chamling, X.; Calabresi, P. A.; Bhargava, P.

2024-10-28 neuroscience
10.1101/2024.10.27.620437 bioRxiv
Show abstract

In multiple sclerosis (MS) the circulating metabolome is dysregulated, with indole lactate (ILA) being one of the most significantly reduced metabolites. We demonstrate that oral supplementation of ILA impacts key MS disease processes in two preclinical models. ILA reduces neuroinflammation by dampening immune cell activation as well as infiltration; and promotes remyelination and in vitro oligodendrocyte differentiation through the aryl hydrocarbon receptor (AhR). Supplementation of ILA, a reductive indole metabolite, restores the gut microbiomes oxidative/reductive metabolic balance by lowering circulating indole acetate (IAA), an oxidative indole metabolite, that blocks remyelination and oligodendrocyte maturation. The ILA-induced reduction in circulating IAA is linked to changes in IAA-producing gut microbiota taxa and pathways that are also dysregulated in MS. Notably, a lower ILA:IAA ratio correlates with worse MS outcomes. Overall, these findings identify ILA as a potential anti-inflammatory remyelinating agent and provide insights into the role of gut dysbiosis-related metabolic alterations in MS progression. One Sentence SummaryIndole lactate, a postbiotic metabolite reduced in MS, corrects gut microbiome metabolic imbalances associated with remyelination and neuroinflammation.

Matching journals

The top 9 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.