Biology subjects

Floto, R. A.

Publications and source records attributed to Floto, R. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Hantavirus mutagenesis is impacted by mutagens and host antiviral proteins

Hantaviruses are emerging zoonotic viruses that infect humans with high fatality rates. We currently have a poor understanding of the processes that contribute to hantavirus mutagenesis and therefore the potential for viral adaptation. To understand the drivers of mutations in hantaviruses, we calculated and compared mutational spectra across 14 divergent hantavirus species. We found that mutagens that are conserved across host species have a major impact on hantaviruses mutagenesis, contributing to at least six of the 12 possible mutation types. We found differences in mutational signatures across hantaviruses, some of which may be due to variation in host mutagen levels that are known to influence somatic mutations. However, we could find no evidence for differential mutational signatures between viruses associated with distinct diseases in humans and no evidence of tissue tropism differences between reservoir hosts. Using a novel method to quantify the impact of ZAP-mediated selection, we found that ZAP greatly influences mutational patterns in transition mutation types across hantaviruses. We also find evidence that APOBEC family proteins drive mutagenesis in all hantaviruses, with the likely exception of Nova virus. Our results therefore provide strong support that mutagens and host antiviral proteins are major contributors to hantavirus mutagenesis, thereby generating the genetic diversity necessary for viral adaptation.

microbiology↗

bioRxiv2026

HANSEN: An Integrated Structural and Functional Proteome Resource for Structure-Guided Drug Discovery in Mycobacterium leprae

Leprosy remains a leading infectious cause of preventable disability, yet its causative agent, Mycobacterium leprae (M. leprae), is structurally under-characterised. Only ten Protein Data Bank (PDB) entries represent seven of its 1,603 protein-coding genes. We present HANSEN, a proteome-wide structural and functional resource for M. leprae. Monomeric and oligomeric models were generated with AlphaFold 3, Boltz-1, Boltz-2 and Chai-1, and annotated with per-residue confidence, predicted aligned error and, for assemblies, interface confidence. Ligand-binding pockets were predicted with AF2BIND, P2Rank and fpocket, template-derived ligands were modelled within oligomeric complexes, residue-level B-cell epitope propensity was estimated with DiscoTope-3.0, and gene essentiality was transferred from Mycobacterium tuberculosis transposon-sequencing labels. These features are integrated in a relational database with interactive visualisation and combined into a calibrated Target Priority Score that ranks all 1,603 proteins into four tiers and recovers established antimycobacterial targets. HANSEN (https://hansen-leprosy.medschl.cam.ac.uk/home) provides a practical basis for target prioritisation and structure-guided drug discovery in leprosy.

bioinformatics↗

bioRxiv2026

Structural basis of biofilm formation mediated by the Pseudomonas aeruginosa fibrillar adhesin CdrA

Many bacteria, including the important human pathogen Pseudomonas aeruginosa, are naturally found in antibiotic-tolerant, multicellular biofilms. Cell-cell interactions within P. aeruginosa biofilms are mediated by a large fibrillar adhesin called CdrA in an extracellular polysaccharide-dependent manner. Here, we report an electron cryomicroscopy structure of the 60 kDa CdrA adhesive N-terminus, which combined with electron cryotomography of focused-ion beam milled specimens, allows us to derive a complete in situ model of the native adhesin. Our structure reveals a small adhesive domain (called ADEPT) at the distal tip of CdrA that is nearly perfectly conserved across the P. aeruginosa pangenome, with structural similarity to previously reported sugar-binding domains in multiple bacterial species. Inhibitory nanobodies targeting CdrA that reduce biofilm formation bind to epitopes in, or close to, the ADEPT on bacterial cells. Furthermore, structure-guided mutagenesis of residues within the ADEPT abolishes bacterial aggregation, and genomic deletion of the whole ADEPT leads to strong attenuation of biofilm formation. Our data forms a rational basis for future targeted inhibition of pathogenic P. aeruginosa biofilms and elucidates the mechanism of biofilm formation mediated by fibrillar adhesins that are widespread in bacteria.

microbiology↗

bioRxiv2026

Spatial lung niches shape Pseudomonas aeruginosa persistence

Chronic Pseudomonas aeruginosa lung infection is a major cause of morbidity and mortality in people with pre-existing lung disease. Once established, infection is rarely eradicated and often persists despite prolonged antimicrobial therapy, but the underlying mechanisms remain poorly understood. To define how P. aeruginosa occupies and adapts to diseased lung tissue, we applied host-pathogen spatial transcriptomics to profile over 23 million lung cells from explanted and resected lungs from people with Cystic Fibrosis (CF) and chronic obstructive pulmonary disease (COPD), mapping bacterial niches and transcriptional states in situ. We found that P. aeruginosa adopted distinct niche-linked states across chronically infected human lung tissue. Bacterial burden was highest in airway lumens, but bacteria also occupied submucosal glands, parenchyma and, unexpectedly, blood vessel lumens in CF tissue. Within airway lumens, two coupled host-pathogen states emerged: an alginate-rich biofilm-like state linked to PI3-positive neutrophil inflammation and host chemical-sensing programmes; and a motile, quorum-sensing state with activated type 6 secretion linked to human ciliary stress, epithelial remodelling and proteolytic injury. Intravascular bacteria co-localised with neutrophils, fibrin and vascular-remodelling signatures, suggesting local breach of barrier integrity and subsequent immune containment. P. aeruginosa also displayed disease-specific cellular associations, with neutrophil-dominated interactions in CF and greater association with macrophages and dendritic cells in COPD. Together, these data reveal chronic P. aeruginosa infection as a spatially partitioned ecosystem in which anatomical microenvironments impose distinct bacterial lifestyles and host inflammatory states. This niche-resolved framework helps explain how persistent infection can diversify within a single lung and suggests that eradication therapies may need to target multiple anatomical and cellular niches to be effective.

immunology↗

bioRxiv2026

Spatially patterned, spectral single-molecule microscopy

Multicolour and spectrally resolved single-molecule microscopy can reveal molecular interactions, nanoscale environments and dynamics, but usually depends on experimentally complex detection architectures based on beam splitting, spectral dispersion or engineered point spread functions. Here we show that spatially patterned detectors offer a conceptually simpler route to spectral single-molecule imaging. By replacing a conventional monochrome camera with a commercially available colour CMOS detector and fitting the raw detector response directly, we recover both molecular position and spectral fingerprint from a single image without optical splitting, channel registration or demosaicing. We term this approach spatial spectral single-molecule microscopy, or S3M. We show that S3M retains single-molecule sensitivity across the visible spectrum, enables robust spectral multiplexing, and supports applications spanning multicolour single-molecule tracking, single-molecule F&oumlrster resonance energy transfer, multicolour localisation microscopy and spectral PAINT. Although spatial patterning necessarily trades photon efficiency for spectral information, current low noise detectors already provide sufficient performance for a broad range of experiments. Spatially patterned detection therefore establishes a widely accessible strategy for simplified spectral microscopy and single-molecule spectroscopy, and points towards a new class of detector informed photonic measurement schemes for nanoscale imaging.

biophysics↗

bioRxiv2026

Pseudomonas aeruginosa balances cytotoxicity and motility to counter phagocytosis by macrophages

During chronic lung infections, Pseudomonas aeruginosa diversifies under selection from antibiotics, metabolic constraints, and host defenses. Macrophages are key sentinels of the innate immune system and play a central role in clearing airway pathogens. Yet, how they process heterogeneous bacterial populations remains poorly understood. Here, we investigate how P. aeruginosa evades phagocytosis under conditions that mimic chronic infection. We use an attenuated mutant lacking a functional type III secretion system (T3SS), which reduces macrophage killing, allowing us to isolate determinants of bacterial susceptibility to phagocytosis. Using transposon insertion sequencing (Tn-seq), we identify bacterial fitness factors under phagocytic selection. Our screen reveals that disruption of genes involved in swimming and twitching motility reduces uptake by macrophages. We find that motility defects interfere with the physical interactions between bacteria and macrophages. Live-cell imaging shows that motility-deficient bacteria exhibit reduced surface exploration and unstable attachment to macrophages, limiting their internalization. Clinical isolates with reduced swimming or twitching motility display similarly impaired uptake. Restoring T3SS activity in these motility mutants rescues cytotoxicity toward macrophages, with one notable exception: flagellum-less, hyper-piliated P. aeruginosa remains avirulent and resistant to phagocytosis due to their lack of engagement with macrophages. Together, these results support two distinct immune evasion strategies: during chronic infection, reduced motility promotes a "freeze"-like state that limits detection and engulfment, whereas during acute infection, P. aeruginosa adopts a "fight"-like strategy by activating its T3SS to eliminate macrophages. SummaryHow immune cells recognize and eliminate bacteria is typically explained by molecular signaling, yet the role of physical interactions remains unclear. We show that bacterial motility is a key determinant of phagocytosis by macrophages. Using functional genomics and live imaging, we find that swimming and twitching motility promote bacterial uptake by enabling effective surface exploration and stable physical engagement with macrophages. Loss of motility commonly observed in chronic P. aeruginosa infections reduces these interactions and allows bacteria to evade engulfment. In contrast, during acute infection, bacteria rely on T3SS-mediated killing of macrophages, independently of motility. These findings reveal that phagocytosis is governed not only by immune recognition but also by bacterial mechanical behavior, and identify a shift in host-pathogen interactions associated with chronic versus acute infection. More broadly, this work establishes mechanics as an important dimension of immune evasion.

microbiology↗

bioRxiv2025

Mutational spectra reveal influenza virus transmission routes and adaptation

Influenza A virus remains a major cause of morbidity and mortality in humans and animals with pandemic potential. While control of outbreaks and spillover events remains a key health priority, the transmission routes and adaptations causing these episodes remain unclear. To understand these processes, we compared mutational spectra across the complete diversity of influenza A virus. We find that niche-specific mutagens cause large convergent shifts in mutational spectrum between gastrointestinal and respiratory lineages, allowing inference of transmission route and site of infection, while additional mutational patterns are host-specific, permitting detection of species responsible for outbreaks. By identifying points of spectrum change in phylogenetic trees, we discover novel adaptive mutations enabling sustained respiratory transmission. We conclude that mutational spectra can enable early detection of lineages with increased potential for spillover and onward transmission, and should be considered as a component of genomic surveillance strategies.

microbiology↗

bioRxiv2025

Verapamil limits inflammation by restoring VGCC-driven epithelial Ca2+ in models of cystic fibrosis

RationaleIn cystic fibrosis (CF), caused by mutations in the CFTR gene, excessive neutrophilic inflammation drives lung damage and premature mortality. Current anti-inflammatory therapies have limited efficacy, partly due to an incomplete understanding of the mechanisms underlying CF-associated inflammation. Increased epithelial Ca{superscript 2} signaling has been implicated, but how CFTR dysfunction perturbs the CFTR/Ca{superscript 2} axis to promote inflammation remains unclear. ObjectivesUsing Cftr-depleted zebrafish and human approaches, we sought to i) define how CFTR dysfunction alters epithelial Ca{superscript 2} signaling and promotes inflammation, and ii) assess whether Ca{superscript 2} channel antagonists can attenuate inflammatory damage in CF. Methods and ResultsWe generated a transgenic zebrafish line expressing the Ca{superscript 2} reporter GCaMP6 under an epithelial promoter to dynamically map epithelial Ca{superscript 2} activity in vivo. Cftr-depleted zebrafish exhibited exaggerated epithelial Ca{superscript 2} elevations following injury compared with wild-type animals. Genetic or pharmacological inhibition of L-type voltage-gated Ca{superscript 2} channels (VGCCs) normalized epithelial Ca{superscript 2} responses and reduced both oxidative stress and neutrophil recruitment. Among FDA-approved VGCCs antagonists tested, only verapamil promoted resolution of neutrophilic inflammation and improved tissue repair in CF zebrafish. Mechanistically, verapamil reduced aberrant epithelial Ca{superscript 2} fluxes, ROS generation and NF-{kappa}B activation. These effects were confirmed in the human CF epithelial cell CFBE41o-, where verapamil reduced Ca2+ and oxidative stress. ConclusionsThese findings establish dysregulated Ca{superscript 2} signaling via L-type VGCCs as a pathogenic driver of inflammation in CF and identify verapamil as a promising therapeutic candidate. By restoring Ca{superscript 2} and oxidative homeostasis, verapamil alleviates inflammatory damage, supporting its repurposing as a candidate anti-inflammatory therapy in CF.

immunology↗

bioRxiv2025

A contextualised protein language model reveals the functional syntax of bacterial evolution

Bacteria have evolved a vast diversity of functions and behaviours that are currently incompletely understood and poorly predicted from DNA sequence alone. To understand the syntax of bacterial evolution and discover genome-to-phenotype relationships, we curated over 1.3 million genomes spanning bacterial phylogenetic space, represented each as an ordered sequence of proteins, and used these sequences to train a transformer-based, contextualised protein language model, Bacformer. By pretraining on genome-wide evolutionary patterns, Bacformer captures the compositional and positional relationships of proteins and thereby provides a whole-genome framework for linking genomic organisation and content to measurable bacterial traits. We demonstrate the ability of Bacformer to accurately predict protein-protein interactions; uncover operon structure, which we validated experimentally; infer important phenotypic traits, including antimicrobial resistance, while revealing likely causal genes; and design template synthetic proteomes with desirable properties. Thus, Bacformer establishes a genomic foundation model that reveals the evolutionary rules governing bacterial gene organisation, function, and phenotype, opening a route to systematic whole-genome engineering.

microbiology↗

bioRxiv2025

Defence systems drive accessory genome interactions in Pseudomonas aeruginosa.

Bacterial genomes represent dynamic ecological systems in which mutational selection and dynamic accessory genome element complements drive evolution. Emerging evidence suggests that bacterial defence systems, which protect against phages and other mobile genetic elements, interact through cooperative, competitive, and antagonistic relationships. These interactions can influence horizontal gene transfer, shape phage susceptibility, and the diversification of genome composition across environments. Recent ecological studies describe non-random co-occurrence and avoidance of defence systems, suggesting that they may emerge from ecological and evolutionary interactions, rather than by chance. This necessitates exploring whether these patterns reflect functional compatibility, shared selection pressures imposed by ecological niche, or if they merely arise from co-localisations of convenience. Understanding these patterns is key to elucidating how the accessory genome evolves and how defence systems constrain or facilitate genome plasticity. To investigate these patterns, in their genomic context, and provide a resource for future investigations, we analysed the distributions of defence systems and other accessory genome elements in a recently curated global dataset of 2,940 Pseudomonas aeruginosa genomes. Genomic defence system content varied by ecological niche, with higher numbers per genome in non-cystic fibrosis derived isolates (average n=7.9) compared to cystic fibrosis-derived isolates (average n=6.5). We identified multiple associations (n=426) and dissociations (n=50) among defence systems, and among other accessory genome elements, many of which had a plausible biological explanation. We also quantitated the relative interactions among accessory genome elements which revealed that defence systems and anti-defence systems engage in the most accessory genome interactions, compared with e.g. antimicrobial resistance genes, plasmids, phages, suggesting that systems are a major driving force in the ecological dynamics of the bacterial accessory genome. Together, these patterns provide new insights into the evolutionary forces shaping bacterial genomes, provide a valuable resource of quantitated interactions in a highly curated Pseudomonas aeruginosa dataset, and establish a framework for future mechanistic and ecological investigations of defence system interactions.

microbiology↗

bioRxiv2024

Antibiotic lethality dictates mycobacterial infection outcomes

Antibiotic development and treatment focus on bacterial growth inhibition, often with limited success. Here, we introduce Antimicrobial Single-Cell Testing (ASCT), an advanced imaging strategy to assess bacterial killing in real-time. By tracking 140 million bacteria and generating over 20,000 in vitro time-kill curves, we can predict Mycobacterium tuberculosis treatment outcomes in mice and humans and link strain-specific survival (drug tolerance) in Mycobacterium abscessus to clinical responses. Using ASCT, we reveal drug tolerance as a distinct genetically encoded bacterial trait conserved across drugs with similar targets and, via genome-wide associations, uncover molecular mechanisms that govern bacterial killing. This study establishes the technical framework and in vivo validation for large-scale bacterial killing assessments to advance our understanding of bacterial survival, antibiotic development and clinical decision-making.

microbiology↗

bioRxiv2024

Sequence-based modelling of bacterial genomes enables accurate antibiotic resistance prediction

AbstractRapid detection of antibiotic-resistant bacteria and understanding the mecha- nisms underlying antimicrobial resistance (AMR) are major unsolved problems that pose significant threats to global public health. However, existing methods for predicting antibiotic resistance from genomic sequence data have had lim- ited success due to their inability to model epistatic effects and generalize to novel variants. Here, we present GeneBac, a deep learning method for predicting antibiotic resistance from DNA sequence through the integration of interactions between genes. We apply GeneBac to two distinct bacterial species and show that it can successfully predict the minimum inhibitory concentration (MIC) of multiple antibiotics. We use the WHO Mycobacterium tuberculosis mutation cat- alogue to demonstrate that GeneBac accurately predicts the effects of different variants, including novel variants that have not been observed during training. GeneBac is a modular framework which can be applied to a number of tasks including gene expression prediction, resistant gene identification and strain clus- tering. We leverage this modularity to transfer learn from the transcriptomic data to improve performance on the MIC prediction task.

microbiology↗

bioRxiv2023

Calculating and applying pathogen mutational spectra using MutTui

Mutational spectra describe the pattern of mutations acquired during evolution and are driven by factors including mutagens, repair processes and selection. Calculating mutational spectra of pathogen genomic datasets may enable analysis of factors that influence these mutational processes, including replication niches, transmission routes and pathogen biology. Here, we introduce MutTui, which can leverage multiple types of sequence data to calculate and compare mutational spectra of DNA and RNA pathogens. MutTui is available at https://github.com/chrisruis/MutTui.

genomics↗

bioRxiv2022

Epigenetic and transcriptional plasticity of myeloid cells in Cystic Fibrosis

The relative contributions of acute and chronic inflammatory mechanisms in diseases characterised by persistent bacterial infection are unclear, despite important consequences for the development of novel anti-inflammatory therapies. Here, we examined longitudinal transcriptional and epigenetic changes in patients with Cystic Fibrosis (CF), a genetic condition characterised by persistent bacterial lung infections that drive progressive inflammatory lung damage. We find that sudden clinical deteriorations in lung health, termed Acute Pulmonary Exacerbations (APEs), are linked to innate immune signalling driven by bacterial components, and accompanied by changes in macrophage function. Treatment of patients with intravenous antibiotics results in rapid modification of myeloid cell gene expression and epigenetic state, towards that of healthy volunteers, suggesting that repeated acute inflammatory episodes play an important role in CF inflammatory lung damage.

immunology↗

bioRxiv2022

Mutational spectra distinguish SARS-CoV-2 replication niches

Exposure to different mutagens leaves distinct mutational patterns that can allow prediction of pathogen replication niches (Ruis 2022). We therefore hypothesised that analysis of SARS-CoV-2 mutational spectra might show lineage-specific differences, dependant on the dominant site(s) of replication and onwards transmission, and could therefore rapidly infer virulence of emergent variants of concern (VOC; Konings 2021). Through mutational spectrum analysis, we found a significant reduction in G>T mutations in Omicron, which replicates in the upper respiratory tract (URT), compared to other lineages, which replicate in both upper and lower respiratory tracts (LRT). Mutational analysis of other viruses and bacteria indicates a robust, generalisable association of high G>T mutations with replication within the LRT. Monitoring G>T mutation rates over time, we found early separation of Omicron from Beta, Gamma and Delta, while the mutational burden in Alpha varied consistent with changes in transmission source as social restrictions were lifted. This supports the use of mutational spectra to infer niches of established and emergent pathogens.

microbiology↗

bioRxiv2022

Mutational spectra analysis reveals bacterial niche and transmission routes

As observed in cancers, individual mutagens and defects in DNA repair create distinctive mutational signatures that combine to form context-specific spectra within cells. We reasoned that similar processes must occur in bacterial lineages, potentially allowing decomposition analysis to identify disrupted DNA repair processes and niche-specific mutagen exposure. Here we reconstructed mutational spectra for 84 clades from 31 diverse bacterial species, assigned signatures to specific DNA repair pathways using hypermutator lineages, and, by comparing mutational spectra of clades from different environmental and biological locations, extracted reproducible niche-associated mutational signatures. We show that mutational spectra can predict general and specific bacterial niches and therefore reveal the site of infection and types of transmission routes for established and emergent human bacterial pathogens. One sentence summaryVariable mutagen exposure and DNA repair drive differential mutational spectra between bacteria and enable niche inference

microbiology↗

bioRxiv2022

Ionic control of porin permeability in bacteria.

Bacterial porins permit permeation of hydrophilic nutrients and antibiotics across the outer membrane but also contribute to proton leak from the periplasmic space, suggesting that their activity might be dynamically regulated. Here we show, in Escherichia coli, that porin permeability is controlled by changes in periplasmic ions, inhibited by periplasmic acidification, thereby limiting proton loss during electron transport chain activity, and enhanced during starvation, promoting nutrient uptake. Growth in glucose increases periplasmic potassium through activating the voltage-gated channel Kch, triggering enhanced porin permeation and membrane action potentials. This metabolic control of porin permeability explains the recognized decrease in antibiotic susceptibility when bacteria are grown in lipid media and the impact of mutations in central metabolism genes on drug resistance, identifying Kch as a therapeutic target to improve bacterial killing by antibiotics. One sentence summaryThe permeability of bacterial porin is dynamically regulated by periplasmic pH and potassium levels, altering antibiotic resistance.

microbiology↗

bioRxiv2022

Phagosomal RNA sensing through TLR8 controls susceptibility to tuberculosis

Genetic determinants of susceptibility to Mycobacterium tuberculosis (Mtb) are poorly understood but could provide insights into critical pathways involved in infection, informing host-directed therapies and enabling risk stratification at individual and population levels. Through a genome-wide forward genetic screen, we identify the Toll-like Receptor 8 (TLR8), as a key regulator of intracellular killing of Mtb. Pharmacological TLR8 activation enhances killing of phylogenetically diverse clinical isolates of drug-susceptible and multidrug-resistant Mtb by macrophages and during in vivo infection in mice. TLR8 is activated by phagosomal mycobacterial RNA released by extracellular membrane vesicles, and enhances xenophagy-dependent Mtb killing. We find that the TLR8 variant, M1V, common in far eastern populations, enhances intracellular killing of Mtb through preferential signal-dependent trafficking to phagosomes. TLR8 signalling may therefore both regulate susceptibility to tuberculosis and provide novel drug targets. Single sentence summaryRNA released from Mycobacterium tuberculosis in the macrophage phagosome is sensed by the pattern recognition receptor TLR8 controlling host susceptibility to tuberculosis and revealing a druggable pathway for host-directed therapy.

immunology↗