Biology subjects

Skippington, E.

Publications and source records attributed to Skippington, E..

3 recordsLinked to original sources

bioRxiv2025

Dictionary of human intestinal organoid responses to secreted niche factors at single cell resolution

The intestinal epithelium is often a site of pathology, such as in inflammatory bowel disease (IBD), and its maintenance is highly modulated by interactions with the microenvironment. However, a systematic understanding of how the myriad of niche cues impact distinct epithelial cell types in a diseased context is still lacking. To address this gap, we first benchmarked diverse human colonic organoid injury models against IBD tissue, and established a disease-relevant model of epithelial inflammation using TNF, IFN{gamma}, and IL1{beta}. Using this system, we built a dictionary of epithelial responses to 81 secreted niche factors at single cell resolution via donor-pooled, multiplexed single cell RNA-sequencing (scRNA-seq). The comprehensive nature of our atlas allowed us to map relationships between perturbations, infer the function of less well-characterized ligands, and identify cell type-specific perturbed pathways. Finally, we established the relevance of organoid-derived gene programs by mapping them to single cell and spatial atlases of human IBD tissue. Our resource offers a global view of epithelial responses to microenvironmental cues in a physiologically relevant disease context and generates new hypotheses for signaling factors that may be involved in epithelial homeostasis and repair.

bioengineering↗

bioRxiv2024

A high-throughput phenotypic screen combined with an ultra-large-scale deep learning-based virtual screening reveals novel scaffolds of antibacterial compounds

The proliferation of multi-drug-resistant bacteria underscores an urgent need for novel antibiotics. Traditional discovery methods face challenges due to limited chemical diversity, high costs, and difficulties in identifying structurally novel compounds. Here, we explore the integration of small molecule high-throughput screening with a deep learning-based virtual screening approach to uncover new antibacterial compounds. Leveraging a diverse library of nearly 2 million small molecules, we conducted comprehensive phenotypic screening against a sensitized Escherichia coli strain that, at a low hit rate, yielded thousands of hits. We trained a deep learning model, GNEprop, to predict antibacterial activity, ensuring robustness through out-of-distribution generalization techniques. Virtual screening of over 1.4 billion compounds identified potential candidates, of which 82 exhibited antibacterial activity, illustrating a 90X improved hit rate over the high-throughput screening experiment GNEprop was trained on. Importantly, a significant portion of these newly identified compounds exhibited high dissimilarity to known antibiotics, indicating promising avenues for further exploration in antibiotic discovery.

bioinformatics↗

bioRxiv2024

Dysbiosis-associated gut bacterium Ruminococcus gnavus varies at the strain level in ability to utilize key mucin component sialic acid

Ruminococcus gnavus is a prevalent human gut commensal bacterium with known roles in intestinal mucus degradation, including by catabolism of the terminal mucin sugar sialic acid. While R. gnavus is not considered a pathogen, overabundance of this species is correlated with Inflammatory Bowel Disease (IBD), and its sialic acid metabolism may play a role in the dysbiotic state. Interestingly, liberation of mucin-bound sialic acid by R. gnavus yields the distinct product of 2,7-anhydro-N-acetylneuraminic acid (2,7-anhydro-Neu5Ac), in contrast to other known mucin-degrading bacteria, which generate Neu5Ac. This prompted us to look for 2,7-anhydro-Neu5Ac metabolism proteins in the genomes of 77 R. gnavus clinical isolates. We found that 2,7-anhydro-Neu5Ac metabolism is sporadically distributed in this species with respect to phylogeny and strain origin. We measured sialic acid-dependent growth of 12 sequenced isolates, finding that the presence of 2,7-anhydro-Neu5Ac catabolism proteins was predictive of growth on this substrate. Our analysis also uncovered "partial" 2,7-anhydro-Neu5Ac catabolism pathways in two R. gnavus strains, which we determined constitute the canonical Neu5Ac catabolism pathway, previously unreported in this species. These results reveal a notable diversity of sialic acid catabolism across the R. gnavus species, an essential consideration for further investigations into the importance of this metabolism in mucin degradation and in roles of R. gnavus in IBD and other gut dysbioses.

microbiology↗