Biology subjects

de Oliveira Martins, L.

Publications and source records attributed to de Oliveira Martins, L..

3 recordsLinked to original sources

bioRxiv2025

Staphylococcus haemolyticus Population Genomics Provides Insights into Pathogenicity and Commensalism

Staphylococcus haemolyticus is a common commensal bacterium but also an opportunistic pathogen, frequently implicated in bacteraemia and sepsis in preterm neonates and immunocompromised patients. Despite its clinical relevance, relatively little is known about the population structure of S. haemolyticus and how this relates to its ability to colonise humans or cause disease. In this study, we analysed commensal and clinical strains isolated from neonates and adults from 20 countries between 1957 - 2022. Whole genome sequencing of these isolates, combined with publicly available data, generated a comprehensive dataset of 986 genomes. This enabled us to characterise the species population structure and track the distribution of antimicrobial resistance (AMR) and virulence determinants. Our analysis revealed a highly diverse genome structure, with multiple phylogenetic groups showing distinct associations with commensalism or pathogenicity. We observed extensive variation in mobile genetic elements, prophages, and AMR genes, alongside increased carriage of plasmids and AMR genes over time. Furthermore, genes lined to metal homeostasis, detoxification, and oxidative stress tolerance were differently abundant between commensal and clinical isolates. This work provides the most detailed view to date of S. haemolyticus diversity, its evolutionary dynamics, and the genetic factors that may underpin the transition from commensal to pathogen.

genetics↗

bioRxiv2023

Scalable neighbour search and alignment with uvaia

Despite millions of SARS-CoV-2 genomes being sequenced and shared globally, manipulating such data sets is still challenging, especially selecting sequences for focused phylogenetic analysis. We present a novel method, uvaia, which is based on partial and exact sequence similarity for quickly extracting database sequences similar to query sequences of interest. Many SARS-CoV-2 phylogenetic analyses rely on very low numbers of ambiguous sites as a measure of quality since ambiguous sites do not contribute to single nucleotide polymorphism (SNP) differences, which uvaia alleviates by using measures of sequence similarity that consider partially ambiguous sites. Such fine-grained definition of similarity allows not only for better phylogenetic analyses, but also for improved classification and biogeographical inferences. Uvaia works natively with compressed files, can use multiple cores and efficiently utilises memory, being able to analyse large data sets on a standard desktop.

bioinformatics↗

bioRxiv2021

Tatajuba - Exploring the distribution of homopolymer tracts

Length variation of homopolymeric tracts, which induces phase variation, is known to regulate gene expression leading to phenotypic variation in a wide range of bacterial species. There is no specialised bioinformatics software which can, at scale, exhaustively explore and describe these features from sequencing data. Identifying these is non-trivial as sequencing and bioinformatics methods are prone to introducing artefacts when presented with homopolymeric tracts due to the decreased base diversity. We present tatajuba, which can automatically identify potential homopolymeric tracts and their putative phenotypic impact, allowing for rapid investigation. We use it to detect all tracts in two separate datasets, one of Campylobacter jejuni and one of three Bordetella species, and to highlight those tracts that are polymorphic across samples. With this we confirm homopolymer tract variation with phenotypic impact found in previous studies and additionally find many more with potential variability. The software is written in C and is available under the open source license GNU GPL version 3 from https://github.com/quadram-institute-bioscience/tatajuba.

bioinformatics↗