Aw, A. | bioRxiv Science

bioRxiv2023

A human urothelial microtissue model reveals shared colonization and survival strategies between uropathogens and asymptomatic bacteria

Urinary tract infection is among the most common infections worldwide, and is typically studied in animals and cell lines with limited uropathogenic strains. Here, we assessed diverse bacterial pathogens and asymptomatic bacteria (ASB) in a human urothelial microtissue model including full stratification/differentiation and urine tolerance. Several uropathogens and ASB-like E. coli invaded intracellularly, suggesting invasion is a shared survival strategy, instead of a virulence hallmark. The E. coli adhesin FimH was required for intracellular community formation, but not for invasion. Other shared lifestyles included filamentation (Gram-negatives), chaining (Gram-positives) and hijacking of exfoliating cells, while biofilm-like aggregates formed mainly with Pseudomonas and Proteus. Urothelial cells expelled invasive bacteria in Rab-/LC3-decorated structures, while highly cytotoxic/invasive uropathogens, but not ASB, disrupted host barrier function and strongly induced exfoliation and cytokine production. Overall, this work highlights diverse species-/strain-specific infection strategies and corresponding host responses in a human urothelial microenvironment, providing insights at the tissue, cell and molecular level. One-Sentence SummaryA human urothelial model revealed shared colonization strategies between uropathogens and asymptomatic bacteria, and pathogen-specific innate immune responses

microbiology↗

bioRxiv2023

The Impact of Stability Considerations on Genetic Fine-Mapping

Fine-mapping methods, which aim to identify genetic variants responsible for complex traits following genetic association studies, typically assume that sufficient adjustments for confounding within the association study cohort have been made, e.g., through regressing out the top principal components (i.e., residualization). Despite its widespread use, however, residualization may not completely remove all sources of confounding. Here, we propose a complementary stability-guided approach that does not rely on residualization, which identifies consistently fine-mapped variants across different genetic backgrounds or environments. Simulations show that stability guidance neither outperforms nor underperforms residualization, but each approach picks up different variants considerably often. Critically, prioritizing variants that match between the residualization and stability-guided approaches enhances recovery of causal variants. We further demonstrate the utility of the stability approach by applying it to fine-map eQTLs in the GEUVADIS data. Using 378 different functional annotations of the human genome, including recent deep learning-based annotations (e.g., Enformer), we compare enrichments of these annotations among variants for which the stability and traditional residualization-based fine-mapping approaches agree against those for which they disagree, and find that the stability approach enhances the power of traditional fine-mapping methods in identifying variants with functional impact. Finally, in cases where the two approaches report distinct variants, our approach identifies variants comparably enriched for functional annotations. Our findings suggest that the stability principle, as a conceptually simple device, complements existing approaches to fine-mapping, reinforcing recent advocacy of evaluating cross-population and cross-environment portability of biological findings. To support visualization and interpretation of our results, we provide a Shiny app, available at: https://alan-aw.shinyapps.io/stability_v0/.

genetics↗