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Leo, D.

Publications and source records attributed to Leo, D..

4 recordsLinked to original sources

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↗

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↗

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↗

Disrupted PDZ-domain binding motif of the dopamine transporter uniquely alters nanoscale distribution, dopamine homeostasis and reward motivation

The dopamine transporter (DAT) is part of a presynaptic multi-protein network involving interactions with scaffold proteins via its C-terminal PDZ-domain binding sequence. In a mouse model expressing DAT with mutated PDZ binding sequence (DAT-AAA), we previously demonstrated the importance of this binding sequence for striatal expression of DAT. Here we show by application of direct Stochastic Reconstruction Microscopy (dSTORM) not only that the striatal level of transporter is reduced in DAT-AAA mice, but also that the nanoscale distribution of the transporter is altered with a higher propensity of DAT-AAA to localize to irregular nanodomains in dopaminergic terminals. In parallel, we observe mesostriatal dopamine (DA) adaptations and changes in DA-related behaviors different from those seen in other genetic DAT mouse models. DA levels in striatum are reduced to [~]45% of wild type (WT), accompanied by elevated DA turnover. Nonetheless, Fast-Scan Cyclic Voltammetry recordings on striatal slices reveal a larger amplitude and prolonged clearance rate of evoked DA release in DAT-AAA mice compared to WT mice. Autoradiography and radioligand binding show reduced DA D2 receptor levels while immunohistochemistry and autoradiography show unchanged DA D1 receptor levels. In behavioral experiments, we observe enhanced self-administration of liquid food under both a fixed-ratio (FR1) and progressive-ratio (PR) schedule of reinforcement, but a reduction compared to WT when using cocaine as reinforcer. Summarized, our data demonstrate how disruption of PDZ-domain interactions causes changes in DAT expression and its nanoscopic distribution that in turn alter DA clearance dynamics.

neuroscience↗