New Thermophilic α/β Class Epoxide Hydrolases Found in Metagenomes From Hot Environments

This is the final version. Available from Frontiers Media via the DOI in this record.Two novel epoxide hydrolases (EHs), Sibe-EH and CH65-EH, were identified in the metagenomes of samples collected in hot springs in Russia and China, respectively. The two α/β hydrolase superfamily fold enzymes were cloned, over-expressed in Escherichia coli, purified and characterized. The new EHs were active toward a broad range of substrates, and in particular, Sibe-EH was excellent in the desymmetrization of cis-2,3-epoxybutane producing the (2R,3R)-diol product with ee exceeding 99%. Interestingly these enzymes also hydrolyse (4R)-limonene-1,2-epoxide with Sibe-EH being specific for the trans isomer. The Sibe-EH is a monomer in solution whereas the CH65-EH is a dimer. Both enzymes showed high melting temperatures with the CH65-EH being the highest at 85°C retaining 80% of its initial activity after 3 h thermal treatment at 70°C making it the most thermal tolerant wild type epoxide hydrolase described. The Sibe-EH and CH65-EH have been crystallized and their structures determined to high resolution, 1.6 and 1.4 Å, respectively. The CH65-EH enzyme forms a dimer via its cap domains with different relative orientation of the monomers compared to previously described EHs. The entrance to the active site cavity is located in a different position in CH65-EH and Sibe-EH in relation to other known bacterial and mammalian EHs

Systematic assessment of secondary bile acid metabolism in gut microbes reveals distinct metabolic capabilities in inflammatory bowel disease

Background The human gut microbiome performs important functions in human health and disease. A classic example for host-gut microbial co-metabolism is host biosynthesis of primary bile acids and their subsequent deconjugation and transformation by the gut microbiome. To understand these system-level host-microbe interactions, a mechanistic, multi-scale computational systems biology approach that integrates the different types of omic data is needed. Here, we use a systematic workflow to computationally model bile acid metabolism in gut microbes and microbial communities. Results Therefore, we first performed a comparative genomic analysis of bile acid deconjugation and biotransformation pathways in 693 human gut microbial genomes and expanded 232 curated genome-scale microbial metabolic reconstructions with the corresponding reactions (available at https://vmh.life). We then predicted the bile acid biotransformation potential of each microbe and in combination with other microbes. We found that each microbe could produce maximally six of the 13 secondary bile acids in silico, while microbial pairs could produce up to 12 bile acids, suggesting bile acid biotransformation being a microbial community task. To investigate the metabolic potential of a given microbiome, publicly available metagenomics data from healthy Western individuals, as well as inflammatory bowel disease patients and healthy controls, were mapped onto the genomes of the reconstructed strains. We constructed for each individual a large-scale personalized microbial community model that takes into account strain-level abundances. Using flux balance analysis, we found considerable variation in the potential to deconjugate and transform primary bile acids between the gut microbiomes of healthy individuals. Moreover, the microbiomes of pediatric inflammatory bowel disease patients were significantly depleted in their bile acid production potential compared with that of controls. The contributions of each strain to overall bile acid production potential across individuals were found to be distinct between inflammatory bowel disease patients and controls. Finally, bottlenecks limiting secondary bile acid production potential were identified in each microbiome model. Conclusions This large-scale modeling approach provides a novel way of analyzing metagenomics data to accelerate our understanding of the metabolic interactions between the host and gut microbiomes in health and diseases states. Our models and tools are freely available to the scientific community