Biology subjects

To, J.

Publications and source records attributed to To, J..

9 recordsLinked to original sources

bioRxiv2026

From Field Photosynthesis to Genetic Architecture: Insights from the First Dedicated Photosynthesis Hackathon

Photosynthesis is among the most consequential yet genetically complex traits in crop plants, and translating its natural variation into actionable genomic targets remains a central challenge for breeding climate-resilient varieties. To start addressing this, researchers are generating increasingly large, multi-environment field photosynthesis datasets. Yet, these data have been structurally under-analysed since their inception. Here we report the outcomes of the first dedicated hackathon focused on computational mining of such field data held in Accra, Ghana, in March 2026. Bringing together data scientists, plant physiologists, geneticists, and breeders from Europe and Africa, these interdisciplinary teams used photosynthetic data collected with hand-held fluorometers to genome-wide marker data across four crop species: cowpea (Vigna unguiculata), barley (Hordeum vulgare), common bean (Phaseolus vulgaris), and potato (Solanum tuberosum). Despite using different species and methods, independent teams identified the same three key findings. First, mechanism-informed feature engineering and dynamic modelling recover genetic signals that are not detected or discarded in standard analysis pipelines, resulting in traits with improved heritability and meaningful associations with yield. Secondly, machine learning methods proved effective at uncovering genetic associations, with temporally resolved features substantially outperforming single time-point measurements. Third, raw chlorophyll fluorescence and absorbance traces consistently contained more information and predictive power than the extracted parameters currently used. A defining feature of this event was having experimentalists and data scientists working together, enabling AI approaches to be grounded in domain knowledge and biological mechanisms rather than relying on data alone.

plant biology↗

bioRxiv2026

Co-dissemination of anti-phage defence systems and multidrug resistance is associated with the seventh-pandemic Vibrio cholerae defensome

Anti-phage defence systems in Vibrio cholerae are increasingly recognised as cargo on mobile genetic elements (MGE) that also carry antimicrobial resistance (AMR) and virulence genes, but a population-scale view of how the V. cholerae defensome partitions between the pandemic O1 clade and the environmental non-O1 reservoir has been missing. We analysed 1,740 RefSeq V. cholerae genomes (773 O1, 967 non-O1) sampled from 1934 to 2022 across 60 countries. The non-O1 reservoir harboured 283 defence subtypes and 55 families absent from any O1 genome. O1 was dominated by abortive infection systems (33.5% vs 14.0% in non-O1; P < 0.001). Defence and prophage burden were inversely related within O1 (R = -0.15) but weakly positive in non-O1, and an 80-year reconstruction revealed mirror trajectories of rising defence diversity and declining prophage burden in O1, coincident with the emergence of SXT/R391 ICE-borne AMR. A bipartite network identified strong defence-AMR associations (Phi up to 0.80), nominating AbiE, AbiJ, dCTPdeaminase, Menshen, Retron-I_A and Lamassu-Fam as candidate co-acquired cargo. UMAP clustering resolved seven distinct defensome lineages, and a Random Forest classifier trained on the defence profile alone predicted-MDR (genotypic MDR) status with pooled cross-validated AUC of 0.96, AUC of 0.92 within O1 only and 0.93 within non-O1 only and generalised across decades (AUC = 0.88) and regions (AUC = 0.92); a five-system signature (AbiE, BREX-I, CBASS-II, dCTPdeaminase, AbiJ) achieved AUC = 0.91. These data implicate the AMR-bearing mobilome rather than phage predation as the principal driver of anti-phage defence evolution in pandemic V. cholerae, and support further evaluation of the defensome as a genomic correlate of multidrug resistance for surveillance use, pending validation in prospectively phenotyped cohorts. Impact statementThe seventh cholera pandemic, ongoing for more than six decades, is driven by a single Vibrio cholerae lineage whose success has been linked to a small set of horizontally acquired mobile genetic elements. Recent work has shown that these elements also carry anti-phage defence systems, but the population-scale picture has been bounded by small genome sets and short clinical sampling windows. We provide a pan-genomic map spanning 1934 to 2022, based on annotation of 1,740 publicly available V. cholerae genomes (with quantitative reconstruction limited to 1970 onwards, where per-window sample sizes support it). We identify the non-O1 environmental reservoir as a substantially larger source of bacterial immune diversity than previously appreciated, document a qualitatively different defence-mechanism balance between pandemic and environmental compartments, and nominate specific candidate defence systems for future mechanistic and long-read characterisation as co-occurring cargo on the SXT/R391 family of integrative conjugative elements. The resource and findings provide an evidence base for V. cholerae genomic surveillance and inform the design of phage-therapy efforts directed at circulating pandemic lineages.

microbiology↗

bioRxiv2026

Mixed-species interactions constrain diversification and shape biofilm evolution

Long-term experimental evolution (LTEE) provides a powerful framework for dissecting how ecological interactions shape adaptive trajectories. Here, we evolved Klebsiella pneumoniae, Pseudomonas protegens and Pseudomonas aeruginosa in single- and mixed-species biofilm communities for 24 weeks and tracked changes in population dynamics, phenotypes, and genomes. In mono-species evolution, all three species exhibited similar dynamics of adaptation, with steadily increasing biofilm-associated populations. In contrast, mixed-species communities displayed striking compositional shifts, with P. protegens emerging as the dominant biofilm former and K. pneumoniae dominating the supernatant. Phenotypic assays revealed that all three species showed enhanced biofilm formation, but this increase was consistently greater in isolates from mono-species than mixed species communities, with P. protegens showing the largest gains. Beyond biofilm production, biofilm-associated isolates exhibited greater phenotypic diversification than planktonic isolates, whereas mixed-species interactions constrained diversification. Whole-genome sequencing identified species-specific putative adaptations such as csrD in K. pneumoniae, yfiBNR in P. protegens, and cheA in P. aeruginosa that arose early, persisted, and were enriched in mixed-species isolates. Functional assays confirmed that these mutations were indeed adaptive by enhancing biofilm formation, with yfiBNR mutations in P. protegens increasing cyclic-di-GMP production and producing a competitive advantage that recapitulated its dominance in LTEE biofilms. Our findings show that biofilm evolution fosters phenotypic diversification, whereas interspecific interactions shape adaptive trajectories, with specific mutations acting as keystone drivers of long-term ecological dynamics in multi-species communities.

microbiology↗

bioRxiv2025

Co-isolation of genetically distinct Burkholderia pseudomallei strains from a single patient in North Queensland

While investigating colony morphology variation (CMV) within clinical isolates of Burkholderia pseudomallei (Bp) isolated from a single infection, we identified two distinct strains (based on their multi-locus sequence type) from Bp TSV292. Simultaneous co-infection is rare, previously reported in only 2 of 133 cases. Here, we present the first comprehensive multi-omics characterization of co-infecting Bp strains isolated from a single infection at a hospital in Townsville, Australia in 2018. This finding impacts the design of future diagnosis and treatment of Bp. ImportanceMelioidosis, a severe disease caused by the bacterium Burkholderia pseudomallei, is rarely caused by more than one strain at the same time. In this study, we examined two bacterial strains isolated at once from a patient treated for melioidosis at a hospital in northern Queensland (Australia). By comparing their genomes, proteins, and physical traits, we found important strain differences that may affect how they adapt and survive during infection. Considering strain diversity when studying how this pathogen causes disease is essential, as it directly impacts future diagnosis and treatment.

microbiology↗

bioRxiv2025

Profiling of Burkholderia pseudomallei variants derived from Queensland clinical isolates

Burkholderia pseudomallei (Bp), an environmental bacterium and opportunistic pathogen endemic to tropical regions, is highly adaptive and thrives in diverse environments, from soil to human hosts. Bacterial adaptation is critical for survival, virulence modulation, and persistence during infection and can manifest as colony morphotype variation (CMV). While Bp adaptation has been well studied, CMV remains poorly understood. Here, we characterized five clinical Bp isolates exhibiting heterogeneous populations with rough and smooth colony morphologies. We used phenotypic assays, whole-genome sequencing, and proteomics to investigate the molecular pathways impacted by CMV - by comparing smooth and rough morphotypes. While phenotypic differences in protease activity, haemolysis, mucoid, iron uptake and antibiotic sensitivity --including to antimicrobial agents commonly used to treat infections--were rare, these traits alone could not distinguish morphotypes or group of isolates. Genomic comparisons revealed either no differences or limited isolate-specific mutations, which does not explain the overall difference in phenotypes. In contrast, proteomic analysis uncovered consistent shifts in protein abundance related to virulence, including quorum sensing, DNA methylation, and secretion systems. Rough variants showed higher expression of EPS-associated proteins, the BpsI3/R3 quorum sensing system, and the global regulator ScmR, whereas smooth variants upregulated type III/VI secretion and siderophore biosynthesis pathways. These findings suggest that CMV is driven by phase variation and regulatory mechanisms rather than punctual genomic modifications. Our study underscores the limitations of phenotype or genome-based classification alone in the context of CMV and highlights the value of integrated multi-omics approaches to uncover CMV-associated biomarkers, with potential applications in diagnostics and the development of targeted therapies against persistent and drug-resistant Bp infections.

microbiology↗

bioRxiv2024

Combinations of genomic alterations and immune microenvironmental features associate with patient survival in multiple cancer types

Oncogenesis and tumor progression are shaped by somatic alterations in the cancer genome and features of the tumor immune microenvironment (TME). How interactions of these two systems influence tumor development and clinical outcomes remains incompletely understood. To address this challenge, we developed the multi-omics analysis framework PACIFIC to systematically integrate genetic cancer drivers and infiltration profiles of immune cells with clinical information. In an analysis of 8500 cancer samples, we report 34 immunogenomic interactions (IGXs) in 13 cancer types in which context-specific combinations of genomic alterations and immune cell activities associate with disease outcomes. Risk associations of IGXs are potentially explained by tumor-intrinsic and microenvironmental metrics of immunogenicity and differential expression of therapeutic targets. In luminal-A breast cancer, MEN1 deletion combined with reduced neutrophils is associated with poor prognosis and deregulation of immune signalling pathways. These findings help elucidate how cancer drivers interact with TME to contribute to tumorigenesis.

cancer biology↗

bioRxiv2024

A model, mixed-species urinary catheter biofilm derived from spinal cord injury patients

Complex multispecies biofilms consistently colonise the interior of indwelling urinary catheters, causing persistent asymptomatic bacteriuria and frequent symptomatic episodes in long-term catheterized individuals. Simple single-species models often fail to capture the complexities of mixed-species interactions, leading to limited conclusions about microbial behaviour and treatment efficacy. Additionally, using lab-based organisms can obscure the genomic diversity found in real-world infections. The primary objective of this study was to establish a stable and reproducible in vitro biofilm model derived from the multi-species clinical flora associated with catheter-related infections, reflecting the dynamics of in vivo infections. Biofilm samples from clinical catheters of spinal cord injury (SCI) participants were used to establish polymicrobial macro-fluidic models within catheters. Metagenomic techniques using short-read Illumina and long-read Oxford Nanopore sequencing was used to assess the community composition, produce metagenome-assembled genomes (MAGs), analyse strain-level phylogeny diversity and single nucleotide polymorphisms (SNP) of isolates. Antibiotic resistance tests using our models highlighted the drastic differences between planktonic bacteria, single-species, and multispecies biofilms. In silico analysis of antibiotic resistance further revealed a high number of varied resistance genes present in these communities. The models developed and characterised in this study are expected to facilitate more effective strategies to prevent and treat catheter-associated infections.

microbiology↗

bioRxiv2024

Prediction of symptomatic and asymptomatic bacteriuria in spinal cord injury patients using machine learning

BackgroundIndividuals with spinal cord injuries (SCI) frequently rely on urinary catheters to drain urine from the bladder, making them susceptible to asymptomatic and symptomatic catheter-associated bacteriuria and urinary tract infections (UTI). Proper identification of these conditions lacks precision, leading to inappropriate antibiotic use which promotes selection for drug-resistant bacteria. Since infection often leads to dysbiosis in the microbiome and correlates with health status, this study aimed to develop a machine learning-based diagnostic framework to predict potential UTI by monitoring urine and/or catheter microbiome data, thereby minimising unnecessary antibiotic use and improving patient health. ResultsMicrobial communities in 609 samples (309 catheter and 300 urine) with asymptomatic and symptomatic bacteriuria status were analysed using 16S rRNA gene sequencing from 27 participants over 18 months. Microbial community compositions were significantly different between asymptomatic and symptomatic bacteriuria, suggesting microbial community signatures have potential application as a diagnostic tool. A significant decrease in local (alpha) diversity was noted in symptomatic bacteriuria compared to the asymptomatic bacteriuria (P < 0.01). Beta diversity measured in weighted unifrac also showed a significant difference (P < 0.05) between groups. Supervised machine learning models trained on amplicon sequence variant (ASVs) counts and bacterial taxonomic abundances (Taxa) to classify symptomatic and asymptomatic bacteriuria with a 10-fold cross-validation approach. Combining urine and catheter microbiome data improved the model performance during cross-validation, yielding a mean area under the receiver operating characteristic curve (AUROC) of 0.91-0.98 (Interquartile range, IQR 0.93-0.96) and 0.78-0.91 (IQR 0.86-0.88) for ASVs and taxonomic features, respectively. ASVs and taxa features achieve a mean AUROC of 0.85-1 (IQR 0.93-0.98) and 0.69-0.99 (IQR 0.78-0.88) in the independent held-out test set, respectively, signifying their potential in differentiating symptomatic and asymptomatic bacteriuria states. ConclusionsOur findings demonstrate that signatures within catheter and urine microbiota could serve as tools to monitor the health status of SCI patients. Establishing an early warning system based on these microbial signatures could equip physicians with alternative management strategies, potentially reducing UTI episodes and associated hospital costs, thus significantly improving patient quality of life while mitigating the impact of drug-resistant UTI.

microbiology↗

bioRxiv2019

Hackflex: low cost Illumina sequencing library construction for high sample counts

We developed a low-cost method for the production of Illumina-compatible sequencing libraries that allows up to 14 times more libraries for high-throughput Illumina sequencing to be generated for the same cost. We call this new method Hackflex. Quality of library preparation was tested by constructing libraries from E. coli MG1655 genomic DNA using either Hackflex, standard Nextera Flex or a variation of standard Nextera Flex in which the bead-linked transposase is diluted prior to use. In order to test the library quality for genomes with a higher and a lower GC content, library construction methods were also tested on P. aeruginosa PAO1 and S. aureus ATCC25923, respectively. We demonstrated that Hackflex can produce high quality libraries and yields a highly uniform coverage, equivalent to the standard Nextera Flex kit. We show that strongly size selected libraries produce sufficient yield and complexity to support de novo microbial genome assembly, and that assemblies of the large insert libraries can be much more contiguous than standard libraries without strong size selection. We introduce a new set of sample barcodes that are distinct from standard Illumina barcodes, enabling Hackflex samples to be multiplexed with samples barcoded using standard Illumina kits. Using Hackflex, we were able to achieve a per sample reagent cost for library prep of A$7.22 (USD$5.60), which is 9.87 times lower than the Standard Nextera Flex protocol at advertised retail price. An additional simple modification and further simplification of the protocol by omitting the wash step enables a further price reduction to reach an overall 14-fold cost saving. This method will allow researchers to construct more libraries within a given budget, thereby yielding more data and facilitating research programs where sequencing large numbers of libraries is beneficial.

genomics↗