ABSTRACT
The sequential activity of gut microbial and host processes can exert a powerful modulatory influence on dietary components, as exemplified by the metabolism of the amino acids tyrosine and phenylalanine to p-cresol by gut microbes, and then to p-cresol glucuronide (pCG) by host enzymes. Although such glucuronide conjugates are classically thought to be biologically inert, there is accumulating evidence that this may not always be the case. We investigated the activity of pCG, studying its interactions with the cerebral vasculature and the brain in vitro and in vivo. Male C57Bl/6 J mice were used to assess blood–brain barrier (BBB) permeability and whole-brain transcriptomic changes in response to pCG treatment. Effects were then further explored using the human cerebromicrovascular endothelial cell line hCMEC/D3, assessing paracellular permeability, transendothelial electrical resistance and barrier protein expression. Mice exposed to pCG showed reduced BBB permeability and significant changes in whole-brain transcriptome expression. Surprisingly, treatment of hCMEC/D3 cells with pCG had no notable effects until co-administered with bacterial lipopolysaccharide, at which point it was able to prevent the permeabilizing effects of endotoxin. Further analysis suggested that pCG acts as an antagonist at the principal lipopolysaccharide receptor TLR4. The amino acid phase II metabolic product pCG is biologically active at the BBB, antagonizing the effects of constitutively circulating lipopolysaccharide. These data add to the growing literature showing glucuronide conjugates to be more than merely metabolic waste products and highlight the complexity of gut microbe to host communication pathways underlying the gut–brain axis.
Acknowledgments
This work was funded by Alzheimer’s Research UK Pilot Grant No. ARUK-PPG2016B-6. PREDEASY™ efflux transporter analysis kits were generously provided through the SOLVO Biotechnology Research and Academic Collaborative Transporter Studies (ReACTS) Program. This work used the computing resources of the UK MEDical BIOinformatics partnership—aggregation, integration, visualization and analysis of large, complex data (UK MED-BIO), which was supported by the Medical Research Council (grant number MR/L01632X/1). This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 874583. This publication reflects only the authors’ view and the European Commission is not responsible for any use that may be made of the information it contains.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/21688370.2022.2073175