Tavares, N. | Search bioRxiv

bioRxiv2026

Genomic variation and ancestry of Helicobacter pylori in the admixed population of Cabo Verde reveal host adaptation, limited host-pathogen ancestry concordance, and signatures of trans-Atlantic slave trade migrations

The genomic structure of the stomach-colonising, gastric cancer-associated bacterium Helicobacter pylori mirrors human evolutionary history, making it difficult to disentangle shared ancestry from true host-pathogen interactions driving disease risk. Recently admixed populations offer opportunities for new coevolutionary trajectories between H. pylori and its host that may disrupt parallel evolution. Here, we analyse host H. pylori IgG, blood serum biomarkers, and paired host-bacterial genomic data from the general population (independent of dyspepsia symptoms) of Cabo Verde. Seropositivity is high (82.8%), as in neighbouring African populations. Serum biomarkers indicate that this unique cohort mainly comprises hosts with limited gastric inflammation. Genomic analyses show that Cabo Verdean H. pylori derive European (hspSWeurope) and West African (hspAfrica1WAfrica) ancestry. The delineation of a reference dataset that includes new strains from Ghana and Portugal, uncovered a distinct West-Central African cluster (hspAfrica1WCAfrica). This dataset allowed inference of within-Africa and within-Europe ancestries in Cabo Verdean and American strains that reflect historical migrations linked to European colonisation and the trans-Atlantic Slave Trade. European strains in Cabo Verde show additional population structure, including two low-diversity clusters. Approximate Bayesian Computation (ABC) inference indicates that the most common cluster represents a clonal expansion, likely driven by host adaptation leading to increased transmission within Cabo Verde. Notably, these strains lack known virulence genes and show significant divergence from gastric cancer strains. Finally, host and bacterial ancestry are uncoupled, indicating disruption of ancestral parallel evolution. Cabo Verde, therefore, provides a unique natural model for studying host-pathogen interactions underlying susceptibility to H. pylori.

evolutionary biology↗

bioRxiv2023

CZ CELLxGENE Discover: A single-cell data platform for scalable exploration, analysis and modeling of aggregated data

Hundreds of millions of single cells have been analyzed to date using high throughput transcriptomic methods, thanks to technological advances driving the increasingly rapid generation of single-cell data. This provides an exciting opportunity for unlocking new insights into health and disease, made possible by meta-analysis that span diverse datasets building on recent advances in large language models and other machine learning approaches. Despite the promise of these and emerging analytical tools for analyzing large amounts of data, a major challenge remains the sheer number of datasets and inconsistent format, data models and accessibility. Many datasets are available via unique portals platforms that often lack interoperability. Here, we present CZ CellxGene Discover (cellxgene.cziscience.com), a data platform that provides curated and interoperable data. This single-cell data resource, available via a free-to-use online data portal, hosts a growing corpus of community contributed data that spans more than 50 million unique cells. Curated, standardized, and associated with consistent cell-level metadata, this collection of interoperable single-cell transcriptomic data is the largest of its kind. A suite of tools and features enables accessibility and reusability of the data via both computational and visual interfaces to allow researchers to rapidly explore individual datasets and perform cross-corpus analysis. This functionality is enabling meta-analyses of tens of millions of cells across studies and tissues and providing global views of human cells at the resolution of single cells.

cell biology↗