Biology subjects

Rowe, W.

Publications and source records attributed to Rowe, W..

5 recordsLinked to original sources

bioRxiv2025

Human whole epigenome modelling for clinical applications with Pleiades

Gene regulation in humans extends beyond the four-letter genetic code. DNA methylation, in particular, functions as a critical epigenetic regulator, dynamically programming cellular identity, adapting gene expression in response to environmental cues, and underpinning the onset and progression of numerous diseases. Here we present Pleiades, a series of whole-genome epigenetic foundation models spanning three sizes: 90M, 600M, and 7B parameters. Pleiades is trained upon an extensive proprietary corpus of human methylation and genomic data, totalling 1.9T tokens. We introduce alignment embeddings and stacked hierarchical attention techniques to provide precise epigenetic modelling without the need for extended context lengths. Collectively, these advances enable Pleiades to perform a diverse range of down-stream biological and clinical tasks, including genomic regulatory prediction, realistic generation of cell-free DNA fragments and fragment-level cell-type-of-origin classification, within a unified and scalable computational framework. We specifically apply Pleiades to the early detection of clinical Alzheimers disease and Parkinsons disease from plasma cell-free DNA, achieving high-accuracy detection (AUROC 0.89 for AD and 0.84 for PD) using a minimally invasive blood test. Combined with plasma pTau-217, Pleiades reaches an AUROC of 0.97 for AD, underscoring the promise of multimodal epigenomic and proteomic approaches. Using mechanistic interpretability, we ground Pleiades latent features in interpretable biological signals, relating its Alzheimers predictions to fragmentomic and epigenomic properties of cfDNA. These findings demonstrate the potential of genome-wide epigenomic modelling as a clinically translatable paradigm for diagnostics and precision medicine, though prospective validation in larger, more diverse cohorts will be required to confirm clinical utility.

genomics↗

bioRxiv2025

Staphylococcus haemolyticus is a reservoir of antibiotic resistance genes in the preterm infant gut

Among coagulase-negative staphylococci, Staphylococcus haemolyticus is a primary cause of bloodstream infections in preterm infants, with gut colonisation being recognised as a risk factor for subsequent infection. Through a re-analysis of a 16S rRNA gene sequencing dataset (n=497 preterm infants), we found that S. haemolyticus was abundant and prevalent in the gut in the first month of life. To better understand the diversity of S. haemolyticus among preterm infants, we generated genome sequences of S. haemolyticus strains (n=140), which were isolated from 44 stool samples of 22 preterm infants from four different hospitals in the United Kingdom. Core genome phylogenetic analyses, incorporating 126 publicly available S. haemolyticus genome sequences, showed that 85/140 (60.1%) of the isolates, from three different hospitals, formed a clonal group with 79/85 (92.9%) strains being assigned to Multi-Locus Sequence Type (ST) 49. Antibiotic resistance genes were highly prevalent in the genome sequences. Using logistic regression, we found a strong association between the presence of the gene mecA and phenotypic resistance to oxacillin (odds ratio [OR]: 158.00, p<0.0001), and the aacA-aphD gene and phenotypic resistance to gentamicin aacA-aphD (OR: 162.00, p<0.001). None of the strains from the preterm infant cohort had a complete Staphylococcal Cassette Chromosome mec (SCCmec) element. The aacA-aphD gene was associated with the transposon Tn4001. Using hybrid genome assemblies, we found it to be present on the chromosome (54.5% of strains) or on diverse plasmids (27.3%). Four strains (18.2%) had Tn4001 copies on both plasmid and chromosome. Our data suggest the existence of a distinct sub-population of S. haemolyticus that has adapted to colonise the gut of preterm infants. Prevalent resistance to antibiotics is of clinical concern and the diversity of genetic contexts of mecA and Tn4001 suggests widespread horizontal gene transfer and recombination in this species.

microbiology↗

bioRxiv2020

An accessible, efficient and global approach for the large-scale sequencing of bacterial genomes

We have developed an efficient and inexpensive pipeline for streamlining large-scale collection and genome sequencing of bacterial isolates. Evaluation of this method involved a worldwide research collaboration focused on the model organism Salmonella enterica, the 10KSG consortium. By optimising a logistics pipeline that collected isolates as thermolysates, permitting shipment in ambient conditions, the project assembled a diverse collection of 10,419 clinical and environmental isolates from low- and middle-income countries in less than one year. The bacteria were obtained from 51 countries/territories dating from 1949 to 2017, with a focus on Africa and Latin-America. All isolates were collected in barcoded tubes and genome sequenced using an optimised DNA extraction method and the LITE pipeline for library construction. After Illumina sequencing, the total reagent cost was less than USD$10 per genome. Our method can be applied to genome-sequence other large bacterial collections at a relatively low cost, within a limited timeframe, to support global collaborations.

microbiology↗

bioRxiv2020

Explainable AI reveals key changes in skin microbiome associated with menopause, smoking, aging and skin hydration

Alterations in the human microbiome have been observed in a variety of conditions such has asthma, gingivitis, dermatitis and cancer, and much remains to be learned about the links between the microbiome and human health. The fusion of artificial intelligence with rich microbiome datasets can offer an improved understanding of the microbiomes role in our health. To gain actionable insights it is essential to consider both the predictive power and the transparency of the models by providing explanations for the predictions. We combine the effort of collecting a corpus of leg skin microbiome samples of two healthy cohorts of women with the development of an explainable artificial intelligence (EAI) approach that provides accurate predictions of phenotypes and explanations. The explanations are expressed in terms of variations in the abundance of key microbes that drive the predictions. We predict skin hydration, subjects age, pre/post-menopausal status and smoking status from the leg skin microbiome. The key changes in microbial composition linked to skin hydration can accelerate the development of personalised treatments for healthy skin, while those associated with age may offer insights into the skin aging process. The leg microbiome signatures associated with smoking and menopausal status are consistent with previous findings from oral/respiratory tract microbiomes and vaginal microbiomes respectively. This suggests that easily accessible microbiome samples could be used to investigate health-related phenotypes, offering potential for non-invasive diagnosis and condition monitoring. Our EAI approach sets the stage for new work focused on understanding the complex relationships between microbial communities and phenotypes. Our approach can be applied to predict any conditions from microbiome samples and has the potential to accelerate the development of microbiome-based personalised therapeutics and non-invasive diagnostics.

bioinformatics↗

bioRxiv2019

The diversity, evolution and ecology of Salmonella in venomous snakes

BackgroundReptile-associated Salmonella are a major, but often neglected cause of both gastrointestinal and bloodstream infection globally. The diversity of Salmonella enterica has not yet been determined in venomous snakes, however other cold-blooded animals have been reported to carry a broad range of Salmonella bacteria. We investigated the prevalence and assortment of Salmonella in a collection of venomous snakes in comparison with non-venomous reptiles.\n\nMethodology/Principle FindingsWe used a combination of selective enrichment techniques and whole-genome sequencing. We established a unique dataset of reptilian isolates to study Salmonella enterica species-level evolution and ecology and investigated differences between phylogenetic groups. We observed that 91% of venomous snakes carried Salmonella, and found substantial diversity between the serovars (n=58) carried by reptiles. The Salmonella serovars belonged to four of the six Salmonella enterica subspecies: diarizonae, enterica, houtanae and salamae. Subspecies enterica isolates were distributed among two distinct phylogenetic clusters, previously described as clade A (52%) and clade B (48%). We identified metabolic differences between S. diarizonae, S. enterica clade A and clade B involving growth on lactose, tartaric acid, dulcitol, myo-inositol and allantoin.\n\nSignificanceWe present the first whole genome-based comparative study of the Salmonella bacteria that colonise venomous and non-venomous reptiles and shed new light on Salmonella evolution. The findings raise the possibility that venomous snakes are a reservoir for human Salmonellosis in Africa. The proximity of venomous snakes to human dwellings in rural Africa may result in contaminated faecal matter being shed on surfaces and in water sources used for human homes and to irrigate salad crops. Because most of the venomous snakes had been captured in Africa, we conclude that the high level of Salmonella diversity reflects the African environmental niches where the snakes have inhabited.\n\nAuthor SummarySalmonella enterica is a remarkable bacterial species that causes Neglected Tropical Diseases globally. The burden of disease is greatest in some of the most poverty-afflicted regions of Africa, where salmonellosis frequently causes bloodstream infection with fatal consequences. The bacteria have the ability to colonise the gastrointestinal tract of a wide range of animals including reptiles. Direct or indirect contact between reptiles and humans can cause Salmonellosis. In this study, we determined the prevalence and diversity of Salmonella in a collection of African venomous snakes for the first time. Using the power of genomics, we showed that the majority of venomous snakes (91%) carry Salmonella, two thirds of which belonged to a subspecies of S. enterica called enterica, which is associated with most cases of human salmonellosis. Within the S. enterica subspecies we identified two evolutionary groups which display distinct growth patterns on infection relevant carbon sources. Our findings could have particular significance in Africa where venomous snakes wander freely around human dwellings and potentially shed contaminated faecal matter in water sources and on surfaces in rural homes.

microbiology↗