PubMed HealthSearch

Biomedical subjects

Allison S Walker

Publications and source records attributed to Allison S Walker.

2 recordsLinked to original sources

Human Milk Oligosaccharides Modulate Nitrogen Utilization in Lactobacillus crispatus in a Glucose-Dependent Manner.

The vaginal microbiome's transition to a dysbiotic state increases susceptibility to pathogens like group B Streptococcus. While human milk oligosaccharides are established prebiotics in the neonatal gut, their impact on the vaginal niche remains largely unexplored. This study investigated the effects of pooled human milk oligosaccharides on the growth and physiology of vaginal (Lactobacillus crispatus, Lactobacillus gasseri, Lactobacillus iners) and gut-derived (Lactobacillus reuteri, Lactobacillus rhamnosus) commensals. Growth analyses revealed that human milk oligosaccharides significantly and selectively stimulated growth across all vaginal strains tested, whereas gut commensals exhibited variable or inhibited growth. Carbohydrate utilization assays and comparative genomics against Bifidobacterium infantis showed that Lactobacillus crispatus and Lactobacillus reuteri lack the canonical metabolic machinery to catabolize human milk oligosaccharides. Instead, nitrogen utilization assays identified a glucose-dependent pathway where human milk oligosaccharides are associated with the depletion of primary amines and amino acids in Lactobacillus crispatus supernatants. These results suggest that human milk oligosaccharides act as noncatabolic modulators of vaginal lactobacilli. Collectively, these in vitro findings may warrant investigation of human milk oligosaccharides as modulators of vaginal commensal physiology in more complex experimental systems.

Humans

Benchmarking methods for measuring biosynthetic gene cluster similarity and determination of gene cluster families.

MOTIVATION: Natural products are often produced by a set of biosynthetic enzymes that are encoded by genes clustered together in the producer's genome, referred to as a biosynthetic gene cluster (BGC). The ability to compare and cluster BGCs is essential for several applications, including predicting which bacteria will make a known product and assessing the potential diversity of natural products produced by a set of bacteria. There are multiple methods for comparing and clustering BGCs based on their similarity, but there has been a lack of investigation into how strongly BGC similarity relates to product structural similarity and how these methods perform relative to each other. RESULTS: Using publicly available databases, we developed a benchmark dataset to assess how well different BGC similarity metrics correlate with the structural similarity of their products and how well these methods cluster BGCs. We found that all methods showed moderate correlation between BGC and structural similarity, with correlations improving for more similar BGCs and varying significantly by BGC biosynthetic class. Analysis of outliers revealed some outliers were due to mistakes or omissions in public datasets, while others represented deviation between BGC similarity and product structural similarity. All methods generally performed better on clustering metrics, with BiG-SCAPE performing the best after errors in the public datasets had been corrected. AVAILABILITY AND IMPLEMENTATION: Scripts and data required to reproduce the results are available at https://github.com/aswalker-lab/BGC-clustering-benchmark and processed similarity, clusters, and scaffolds are also available at https://huggingface.co/datasets/allie-walker/BGC-clustering-benchmark. Code is also available at Zenodo: 10.5281/zenodo.17373546.

Multigene Family