Biology subjects

Kerby, R. L.

Publications and source records attributed to Kerby, R. L..

5 recordsLinked to original sources

bioRxiv2025

Investigation of Bile Salt Hydrolase Activity in Human Gut Bacteria Reveals Production of Conjugated Secondary Bile Acids

Through biochemical transformation of host-derived bile acids (BAs), gut bacteria mediate host-microbe crosstalk and sit at the interface of nutrition, the microbiome, and disease. BAs play a crucial role in human health by facilitating the absorption of dietary lipophilic nutrients, interacting with hormone receptors to regulate host physiology, and shaping gut microbiota composition through antimicrobial activity. Bile acid deconjugation by bacterial bile salt hydrolase (BSH) has long been recognized as the first necessary BA modification required before further transformations can occur. Here, we show that BSH activity is common among human gut bacterial isolates spanning seven major phyla. We observed variation in both the extent and the specificity of deconjugation of BAs among the tested taxa. Unexpectedly, we discovered that certain strains were capable of directly dehydrogenating conjugated BAs via hydroxysteroid dehydrogenases (HSD) to produce conjugated secondary BAs. These results challenge the prevailing notion that deconjugation is a prerequisite for further BA modifications and lay a foundation for new hypotheses regarding how bacteria act individually or in concert to diversify the BA pool and influence host physiology.

microbiology↗

bioRxiv2022

Gut bacteria impact host uric acid burden and its association with atherosclerosis

Humans with metabolic and inflammatory diseases, including atherosclerosis harbor dysbiotic gut communities. However, the microbes and microbial pathways that influence disease progression remain largely undefined. Here, we show that variation in atherosclerosis burden is in part driven by the gut microbiota and it is associated with circulating levels of the proinflammatory molecule uric acid both in mice and humans. We identify bacterial taxa present in the gut spanning multiple phyla, including Bacillota (Firmicutes), Fusobacteriota and Pseudomonadota (Proteobacteria), that use uric acid and adenine- a key precursor of nucleic acids in intestinal cells, as carbon and energy sources anaerobically, and uncover a gene cluster encoding key steps of purine degradation that is widely distributed among gut dwelling bacteria. Furthermore, we demonstrate that colonization of germ-free mice with purine-degrading bacteria modulates levels of uric acid and other purines in the gut and systemically. Altogether this work demonstrates that gut microbes are important drivers of host global purine homeostasis and uric acid levels, and suggests that gut bacterial catabolism of purines may represent a novel mechanism by which the gut microbiome influences host health.

microbiology↗

bioRxiv2022

Gut microbiota bacterial strain richness is species specific and limits therapeutic engraftment

Despite the fundamental role of strain variation in gut microbiota function, the number of unique strains of a species that can stably colonize the human gut is still unknown. In this work, we determine the strain richness of common gut species using thousands of sequenced bacterial isolates and metagenomes. We find that strain richness varies across species, is transferable by fecal microbiota transplantation, and is low in the gut compared to other environments. Therapeutic administration of supraphysiologic numbers of strains per species only temporarily increases recipient strain richness, which subsequently converges back to the population average. These results suggest that properties of the gut ecosystem govern the number of strains of each species colonizing the gut and provide a theoretical framework for strain engraftment and replacement in fecal microbiota transplantation and defined live biotherapeutic products.

microbiology↗

bioRxiv2021

Systems genetics uncovers microbe-lipid-host connections in the murine gut

The molecular bases of how host genetic variation impact gut microbiome remain largely unknown. Here, we used a genetically diverse mouse population and systems genetics strategies to identify interactions between molecular phenotypes, including microbial functions, intestinal transcripts and cecal lipids that influence microbe-host dynamics. Quantitative trait loci (QTL) analysis identified genomic regions associated with variations in bacterial taxa, bacterial functions, including motility, sporulation and lipopolysaccharide production, and levels of bacterial- and host-derived lipids. We found overlapping QTL for the abundance of Akkermansia muciniphila and cecal levels of ornithine lipids (OL). Follow-up studies revealed that A. muciniphila is a major source of these lipids in the gut, provided evidence that OL have immunomodulatory effects and identified intestinal transcripts co-regulated with these traits. Collectively, these results suggest that OL are key players in A. muciniphila-host interactions and support the role of host genetics as a determinant of responses to gut microbes.

genetics↗

bioRxiv2018

Autometa: Automated extraction of microbial genomes from individual shotgun metagenomes

MotivationShotgun metagenomics is a powerful, high-resolution technique enabling the study of microbial communities in situ. However, species-level resolution is only achieved after a process of \"binning\" where contigs predicted to originate from the same genome are clustered. Such culture-independent sequencing frequently unearths novel microbes, and so various methods have been devised for reference-free binning. Existing methods, however, suffer from: (1) reliance on human pattern recognition, which is inherently unscalable; (2) requirement for multiple co-assembled metagenomes, which degrades assembly quality due to strain variance; and (3) assumption of prior host genome removal not feasible for non-model hosts. We therefore devised a fully-automated pipeline, termed \"Autometa,\" to address these issues. Results: Autometa implements a method for taxonomic partitioning of contigs based on predicted protein homology, and this was shown to vastly improve binning in host-associated and complex metagenomes. Autometas method of automated clustering, based on Barnes-Hut Stochastic Neighbor Embedding (BH-tSNE) and DBSCAN, was shown to be highly scalable, outperforming other binning pipelines in complex simulated datasets.\n\nAvailability and implementationAutometa is freely available at https://bitbucket.org/jasonckwan/autometa and as a docker image at https://hub.docker.com/r/jasonkwan/autometa under the GNU Affero General Public License 3 (AGPL 3).\n\nContactjason.kwan@wisc.edu\n\nSupplementary informationSupplementary data are available attached to this article at https://biorxiv.org

bioinformatics↗