bioRxiv Science⌕ Search

Biology subjects

Wells, H.

Publications and source records attributed to Wells, H..

5 recordsLinked to original sources

Genome-scale metabolic model atlas of the zoonotic pathogen Streptococcus suis

Streptococcus suis is a Gram-positive bacterium with a dual role as a commensal member of the porcine nasal microbiota and a pathogen causing systemic disease in pigs and humans. Mounting evidence suggests that metabolism is a key driver of S. suis pathogenicity. Given the species high genetic variability, we hypothesize that differences in metabolic networks could explain the diverse pathogenic phenotypes observed across different strains. To test this, we generated an atlas of over 3000 strain-specific and automatically curated genome-scale metabolic models that cover the breadth of pathogenic and commensal S. suis lineages. Using this model atlas, we performed the first species-level examination of metabolic traits in S. suis. Our simulations, supported by experimental validation, revealed three key insights. First, while metabolic traits are broadly conserved in S. suis, there are nevertheless lineage-dependent differences in amino acid auxotrophies and carbon utilization patterns that point towards distinct in vivo niches. Second, most strains are predicted to grow in different plausible in vivo environments regardless of their virulence phenotype, suggesting that metabolism is a weak barrier to systemic infection. Third, by systematically predicting reaction essentiality in more than 15 million reaction-strain-condition combinations, we identify a subset of 17 reactions, largely in nucleotide metabolism, that are conditionally essential in vivo and may serve as new targets for the development of new antimicrobials or vaccines. Overall, this study provides a valuable new resource for broadly examining S. suis metabolism and its role in pathogenicity.

Systems Biology↗

BIOTIA-DX RESISTANCE Achieved the Best Antimicrobial Resistance Phenotype Prediction Accuracy at CAMDA 2026

We present BIOTIA-DX RESISTANCE (BDXR), our submission to the CAMDA 2026 AMR Challenge. This work extends our CAMDA 2025 submission [1] to a new set of six species-drug pairs and adds k-mer-based feature engineering (both targeted and whole-genome) for pairs where the 2025 gene-presence base model underperforms. BDXR achieved a mean accuracy of 86.1% across the six pairs on the CAMDA 2026 test set, ranking first on four pairs, tied for first on Streptococcus pneumoniae (penicillin), and second on Campylobacter jejuni (nalidixic acid); per-pair test accuracy ranged from 69.9% (C. jejuni, nalidixic acid) to 98.8% (S. pneumoniae, penicillin). We refer the reader to our 2025 preprint [1] for the underlying workflow, dataset curation, and clinical motivation; this preprint focuses on the results and methodological changes that are new in 2026.

microbiology↗

BIOTIA-DX RESISTANCE Achieved the Best Antimicrobial Resistance Phenotype Prediction Accuracy at CAMDA 2025

We have developed BIOTIA-DX RESISTANCE (BDXR), a bioinformatic tool for predicting antimicrobial resistance (AMR) from whole genome sequencing of microbial isolates. BDXR achieved the best accuracy of any submission to the CAMDA 2025 AMR Challenge. This years challenge focused on predicting AMR phenotype which is a more complex problem than the detection of AMR marker genes, the focus of some prior years. BDXR achieved an overall F1 score of 89% on the training set and 84.1% on the challenge test set. Accuracy varied across the 9 species and drug pairs in the competition from an F1 score of 98.4% (Campylobacter jejuni, tetracycline) to 78.5% (Pseudomonas aeruginosa, cefatzidime). BDXR is based on curation of global datasets, machine learning-based predictions from input data, and highly stringent prepreprocessing of input data and databases.

microbiology↗

Forecasting Dengue Fever in Brazil Using Multimodal Data, Including Climate Data

Dengue fever is a major tropical disease transmitted by Aedes mosquitoes. Dengue affects more than 120 countries with highly variable year to year infection rates. Despite high variability, dengue has a clear relationship to climate factors and human demography. Global trends to higher temperatures and greater disorderly urban development are increasing the scale and scope of dengue risk. Dengue has complex human immunity with 4 known serotypes that make multiple infections possible. Accurate forecasting of dengue fever would allow for appropriate interventions and improved public health outcomes. We demonstrate, GeoSeeq Dengue, a forecasting model for dengue fever in Brazil. GeoSeeq Dengue predicts dengue outbreaks monthly in 5,570 Brazilian municipalities at 1, 3, and 6 months ahead of the outbreak. Model accuracy compares favorably to a historical baseline model, making it a promising model for informing public health response. We evaluate how different types of input variables effect model accuracy and explore how this model could be adapted to other countries. This model could inform public health responses to dengue including targeting vector control programs, public health education messaging, and the newly launched dengue vaccine rollout.

bioinformatics↗

Zoonotic potential of a novel bat morbillivirus

Morbilliviruses are amongst the most contagious viral pathogens that infect mammals. Metagenomic surveys have identified numerous morbillivirus sequences in bats, but no full-length authentic morbillivirus has been isolated or characterized from bats. Here we detail the discovery of full-length Myotis Bat Morbillivirus (MBaMV) from a bat surveillance program in Brazil. After determining that MBaMV utilizes bat CD150 but not human CD150 as an entry receptor, we generated an infectious clone of MBaMV using reverse genetics. MBaMV exhibited features consistent with other morbilliviruses, including pleomorphic virions, P-editing and the rule-of-six. MBaMV replicated well in human epithelial cell lines in a nectin-4 dependent manner. Surprisingly, MBaMV was able to infect human macrophages in a CD150-independent manner. However, MBaMV was restricted by cross-neutralizing human sera and did not evade the human innate immune system, indicating that while zoonotic spillover into humans may be possible, MBaMV replication in humans would likely be restricted.

microbiology↗