Biology subjects

Turner, D.

Publications and source records attributed to Turner, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Ultra processed microbiome: Effects of dietary Stable Carbonyl adducts (SCars) on developing microbiota of mice

Consumption of ultra-processed food (UPF) is increasing and is causally linked with noncommunicable disease onset, however specific compounds within UPFs that influence disease risk remain poorly defined. The acronym 'SCars', for Stable Carbonyl Adducts, is introduced herein as an umbrella term encompassing advanced glycation end-products (AGEs), advanced lipoxidation end-products (ALEs), and other carbonyl-derived modifications. These molecules arise as products of spontaneous carbonyl chemistry, a reaction accelerated by industrial food processing. Dietary SCars have been associated with metabolic dysfunction; however, their impact on microbiome composition during windows of developmental vulnerability has not been well studied. Puberty in mice represents a period of developmental plasticity during which the gut microbiome is susceptible to dietary exposures. We tested whether transient exposure to high levels of dietary SCars during puberty remodels the developing gut microbiome. Using metagenomic sequencing of fecal samples from mice exposed to high-SCars or control diets, we found that high-SCars exposure profoundly impacted microbial community structure and metabolic potential. Dietary SCars reduced microbial diversity and depleted short-chain fattyacid producing taxa while enriching pathways related to membrane remodeling, branched-chain amino acid biosynthesis, and nucleotide anabolism. These data identify SCars as features of UPFs capable of reprogramming the developing gut microbiota.

microbiology↗

bioRxiv2026

PIANO: Probabilistic Inference Autoencoder Networks for multi-Omics enables robust generative modeling of gene expression and scales single-cell integration to 100 million cells

Single-cell RNA technologies enable the routine acquisition of transcriptomic atlases. However, these molecular profiles are influenced by overlapping sources of variation. Since these covariates confound comparisons, data integration is the first step in most analyses. Three challenges remain: correcting strong batch effects, scaling to millions of cells, and modeling how covariates influence gene expression. To address these challenges, we developed PIANO: Probabilistic Inference Autoencoder Networks for multi-Omics, a deep learning framework whose central feature is a generative model of gene expression data. Additionally, PIANO achieves robust integrations and trains 10x faster than previous methods. PIANO accurately integrates single-cell data across species and across single-cell and spatial transcriptomics modalities. As practical applications, PIANO models spatially-resolved gene expression during Alzheimer's disease progression in human brains and integrates over 100 million cancer cells to model drug perturbations. In summary, PIANO's integration and generative modeling capabilities will empower novel insights for countless future studies.

bioinformatics↗

bioRxiv2026

Development of low cost, robust and reproducible biofilm static and pharmacodynamic assays

SynopsisO_ST_ABSBackgroundC_ST_ABSThe complexity of diagnosing and treating biofilm-associated infections necessitates a comprehensive strategy to mitigate the rising rates of antimicrobial resistance (AMR). Microtiter plate methods are used globally for determination of biofilm eradication concentrations (MBEC) but few have been adapted to observe pharmacodynamic observations. Here, we describe a method which allows for both static and pharmacodynamic assays of biofilm evaluation. MethodsA total of 150 clinical isolates from Southmead Hospital were assessed, representing five bacterial species (N=30 per bacterial species): Pseudomonas aeruginosa, Escherichia coli, Streptococcus pneumoniae, Staphylococcus aureus and Klebsiella pneumoniae. MBECs were determined using a developed method using 96 well plates and glass beads. MBECs of seven different antibiotics were compared to those determined using the established Calgary biofilm device (CBD). Dynamic pharmacodynamic evaluations to produce Biofilm Time Kill curve (BTKC) based on published planktonic time kill curve (TKC) data and ISO recommendations were carried out using the glass bead model for K. pneumoniae and ciprofloxacin, S. aureus and levofloxacin and S. pneumoniae and vancomycin. Quantification of biofilm biomass was assessed at 0, 2, 4, 8 and 24 hours and compared to planktonic culture survival under comparable challenge conditions. ResultsComparing MBEC results for all bacterial strains and antibiotic challenges showed no statistical difference between the glass bead and CBD methods (P <0.05). Biofilm BTKC AUBKC were inferior to planktonic equivalents but demonstrated specific pharmacodynamic patterns of biofilm reduction efficacy. MBEC correlated with biofilm BTKC penetration in line with clinical observations for S. aureus vs vancomycin and S. pneumoniae vs levofloxacin. ConclusionsThe glass bead biofilm models provide robust, reproducible alternatives to the traditional methods of determining MBEC and bridge the gap with biofilm pharmacodynamic evaluations. These methods also provide a low-cost option to current methods as only standard laboratory equipment is required, allowing for the generation of comprehensive data sets. This ensures greater translatability to complex in vitro models and clinical scenarios.

microbiology↗

bioRxiv2026

Tracing PFAS Transfer from Mother to the Fetoplacental Unit: Insights from Trimester-Specific Maternal Serum Profiles

Per- and polyfluoroalkyl substances (PFAS) are ubiquitous endocrine-disrupting pollutants that cross the placenta and affect offspring health, but the extent and timing of their transfer to placental and fetal compartments remain poorly understood. We characterized the relationship between trimester-specific prenatal maternal serum PFAS levels and paired placental and cord plasma levels at term. Data came from the Central Arkansas Glowing prospective cohort (n=151, 2010-2014). Four well-detected PFAS were measured using liquid chromatography-tandem mass spectrometry. Regression, elastic net, and parametric g-formula models tested the association between maternal levels in each trimester and placental or cord PFAS levels. In g-formula models, trimester one (T1) or trimester two (T2) measures consistently had the largest effect sizes associated with placental levels (p<0.001-0.05). Similarly, T1 (PFHxS, PFNA, PFOS, PFOA), T2 (PFNA, PFOS, PFOA), and placental PFOA were associated with cord plasma levels (p<0.05-p<0.001). Results were robust to time-varying adjustment for estimated glomerular filtration rate, serum albumin, or maternal weight. Predictive models improved with additional timepoint measures. Our findings suggest PFOA may transfer more efficiently from the placenta to cord plasma and early-to-mid gestation maternal serum PFAS measures may serve as the most robust sentinels of fetoplacental exposure burden, suggesting early exposure prevention should be prioritized.

pharmacology and toxicology↗

bioRxiv2025

Evaluating drone-mounted thermal infrared sensors for macropod monitoring in Tasmania

Thermal drones offer significant advantages for monitoring wildlife in low-light conditions; however, detection performance is influenced by technical settings and environmental factors. This study evaluates the use of nocturnal drone surveys to detect macropods in Tasmania, with the aim of determining optimal flight parameters for balancing detection accuracy and survey efficiency. Field surveys were conducted in Narawntapu National Park using varying flight altitudes and image overlap settings, and detection rates were compared across thermal datasets. Manual annotations and basic thresholding method were used to quantify detection success. Results showed that detection rates were highest when surveys were conducted under cooler ambient temperatures and at moderate altitudes (e.g. 60 metres AGL) with 50% image overlap. These findings provide practical guidance for designing nocturnal drone surveys and offers baseline recommendations for using drone-mounted thermal sensors to monitor large-bodied, crepuscular mammals, with broader implications for scalable wildlife monitoring programs.

ecology↗

bioRxiv2025

Automated detection of macropods in Tasmania using drone surveys and convolutional neural networks (CNNs)

Manual annotation of drone imagery is labour-intensive and prone to observer bias, particularly when applied to large datasets across varied environments. To address this, a deep-learning pipeline was developed and evaluated for identifying macropods in visual (RGB) drone imagery, using a convolutional neural network (CNN) adapted from the DeepForest framework. The model was trained on annotated images of Forester kangaroos (Macropus giganteus tasmaniensis) and Bennetts wallabies (Notamacropus rufogriseus) collected across two Tasmanian study sites. Performance was assessed using independent test sets from each site, representing open and forest-edge habitats, as well as a combined multi-site test set. Detection accuracy was quantified using precision, recall, and F1 scores, with further analyses evaluating the effect of solar altitude angle on model performance. The model achieved high recall across sites, indicating strong potential for minimising missed detections under diverse conditions. These results demonstrate the feasibility of applying transfer learning to drone-based wildlife surveys and highlight the promise of deep learning models for reducing manual effort in macropod monitoring, with applications for broader conservation and management workflows.

ecology↗

bioRxiv2025

Four Decades of Genomic Stability and Adaptive Divergence in Xanthomonas arboricola pv. pruni-Infecting Phages: Defining Duraznoxanthovirus arenicola and Its Evolutionary Framework

Bacteriophages (phages) are abundant and ecologically significant, yet their diversity and roles in plant-associated ecosystems remain poorly understood, limiting their application in sustainable disease management. To address this gap, we characterized 15 phages infecting Xanthomonas arboricola pv. pruni, the causal agent of bacterial spot on peach, has been isolated for over four decades from North Carolina orchards. Comparative genomic and phylogenetic analyses revealed two temporally distinct clades with >95% nucleotide identity and 63 conserved core genes, forming a new genus and species, Duraznoxanthovirus arenicola. These findings challenge assumptions of pervasive genomic mosaicism, highlighting remarkable genomic stability alongside localized variability in accessory loci. Beyond genus-level characterization, our analyses support a broader taxonomic restructuring within the family Anamaviridae, introducing a new subfamily (Terravirinae) and two new genera (Duraznoxanthovirus and Ralstopathovirus). This work provides the first family-level framework for phages exclusively infecting plant-associated bacteria, offering evolutionary insights and a foundation for ecological studies and management strategies.

microbiology↗

bioRxiv2025

Fast Optimization of Robust Transcriptomics Embeddings using Probabilistic Inference Autoencoder Networks for multi-Omics

Advances in single-cell genomics technologies enable the routine acquisition of atlases with millions of cells. These datasets often include multiple covariates, such as donors, sequencing platforms, developmental timepoints, and species, which provide new opportunities for discovery and new challenges. To mitigate unwanted sources of variation, dataset integration is the starting point for most analyses. However, existing methods struggle with integrating large complex datasets. To address these limitations, we developed PIANO, a variational autoencoder framework that uses a negative binomial generalized linear model for stronger batch correction, and code compilation for ten times faster training than existing tools. We first demonstrate performant integration compared to commonly used methods on single-species datasets. We then show PIANO enables superior analyses of multiple atlases, solving challenging integration tasks across sequencing platforms, development, and species, while simultaneously preserving desired biological signals. Our contributions include a novel, high-performance integration method and recommendations for integration applications.

neuroscience↗

bioRxiv2025

Scalable and systematic hierarchical virus taxonomy with vConTACT3

Viruses are key players in diverse ecosystems, but studying their impacts is technically and taxonomically challenging. Taxonomic complexities derive from undersampling, diverse DNA and RNA genomes with multiple evolutionary origins, and lack of a universal barcode gene. While virus ecogenomics has expanded access to and understanding of the virosphere, available classification tools poorly scale to modern discovery-based datasets, lack taxonomic resolution, and/or are unable to classify novel sequence space. Here we develop, benchmark, and release vConTACT3, a machine learning-based tool that improves scalability and accuracy, adds extensive user-requested features, expands classification to both eukaryote and prokaryote viruses for 4/6 officially recognized realms, and establishes accurate hierarchical taxonomy from genus to order. Application to 48,069 public virus genomes provided new taxonomy assignments for thousands of taxa, revealed support for fewer taxonomic ranks than currently available, and systematically identified taxonomically problematic areas across the virosphere.

bioinformatics↗

bioRxiv2025

Application of spatial transcriptomics across organoids: a high-resolution spatial whole-transcriptome benchmarking dataset

Stem cell-derived organoids hold promise to model tissue-specific disease. To enable this, it is crucial to assess how transcriptional signatures, cellular organisation and composition of organoids compare to in vivo counterparts. However, technologies which elucidate regional molecular identity, like spatial transcriptomics, have been challenging to apply to organoids. This study presents the first systematic profiling of multiple stem cell derived organoid models (brain, heart muscle, heart valve, kidney, lung, cartilage, and haematopoietic) with Stereo-seq, a full transcriptome, spatial transcriptomics assay using on-chip in situ RNA capture at subcellular resolution. It describes optimisation of this assay to characterise organoids, use of multiple organoid samples on a single chip, assess differences in RNA capture efficiency compared to reference tissues and its limitations. This study introduces a bespoke analysis method that partitions samples into regions and further characterises them. These findings inform future works to characterise organoids using spatial transcriptomics, providing insights in optimising RNA capture of multiple organoids across a chip and novel methods for regional analysis.

bioinformatics↗

bioRxiv2024

Harnessing Global HLA Data for Enhanced Patient Matching in iPSC Haplobanks

Several countries have either developed or are developing national induced pluripotent stem cell (iPSC) banks of cell lines derived from donors with HLA homozygous genotypes (two identical haplotypes) prevalent in their local populations to provide immune matched tissues and cells to support regenerative medicine therapies. This haplobank approach relies on knowledge of the HLA genotypes of the population to identify the most beneficial haplotypes for patient coverage, and ultimately identify donors or cord blood units carrying two copies of the target haplotype. A potentially more efficient alternative to a national bank approach is to assess the haplotypes required to provide global patient coverage and to produce a single, global haplobank. Toward that end, we have developed an algorithm to prioritize HLA haplotypes that optimize coverage across the global population. We analyzed data from eighteen countries participating in the Global Alliance for iPS Therapy (GAiT). A representative pool of HLA genotypes, reflecting the HLA of patients, was derived by sampling from each countrys WMDA hematopoietic stem cell donor registry, or surrogate population. An algorithm was created based on HLA-A, -B and -DRB1 haplotype homozygous types with population HLA matching coverage defined by the absence of Host versus Graft (HvG) mismatches at these loci. HLA matching coverage was determined by iteratively selecting HLA haplotypes that provide the largest coverage against patient HLA genotypes sampled from the same population, excluding genotypes compatible with previous iterations. The top 10 haplotypes for each of the 18 countries were identified with patient coverage ranging from 19.5% in Brazil to 63.8% in Japan, with a mean coverage of 33.3%. In a global model, utilizing the 180 most frequent haplotypes across all 18 populations (equivalent to 10 lines pe country), the patient coverage ranged from 54.6% in India to 81.7% in Sweden, with a mean of 68.4%. Our findings demonstrate that global collaboration could more than double the potential for patient HLA matching coverage. Interrogation of unrelated hematopoietic stem cell donor registry and cord blood bank HLA data demonstrated that HLA-A, -B, and -DRB1 homozygous donors for the top 180 global haplotypes are widely available. These results show that a globally coordinated strategy for haplobanking would reduce redundancy and allow more patients to be treated with the same investment. Visual Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=170 SRC="FIGDIR/small/618361v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@117075eorg.highwire.dtl.DTLVardef@e4dc11org.highwire.dtl.DTLVardef@12be9c7org.highwire.dtl.DTLVardef@140d6_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIiPSC banks are being developed targeting HLA coverage to meet national needs C_LIO_LIGlobal collaboration has the potential to substantially increase the efficiency of this effort C_LI

genetics↗

bioRxiv2024

taxmyPHAGE: Automated taxonomy of dsDNA phage genomes at the genus and species

BackgroundBacteriophages are now classified into genera and species based on genomic similarity. To identify new species and genera requires comparison against all phage genomes currently defined by the International Committee on the Taxonomy of Viruses. With increasing amounts of phage genomic data there is a clear need to fully automate the classification of phages into existing and new genera and species. Materials and MethodsWe created a MASH database for rapid searching of closely related phages, to then be compared with BLASTn to compute intergenomic similarity between bacteriophages (https://github.com/amillard/tax_myPHAGE/tree/main). ResultsTaxmyphage is provided as a conda repository and via a user-friendly website, that allows rapid classification of phages into existing taxa at the genus and species level. ConclusionsTaxmyphage allows the rapid and accurate classification of phage genomes into existing genera and species, at a scale that is compatible with existing sequencing output.

microbiology↗

bioRxiv2024

GRAViTy-V2: a grounded viral taxonomy application

Taxonomic classification of viruses is essential for understanding their evolution and therefore their distribution, host interactions and pathogenic mechanisms. Classification methodologies usually rely on comparison of aligned sequence motifs in conserved genes, by genome organisation and gene complements, and at lower taxonomic ranks such as genus and species, through genome sequence identities. Building on our previous classification framework based on a novel whole-genome analysis method, we here describe Genome Relationships Applied to Viral Taxonomy Version 2 (GRAViTy-V2), which encompasses a greatly expanded range of features and numerous optimisations, packaged as an application that may be used as an alignment-free general-purpose virus classification tool. Using 28 datasets derived from the International Society on Taxonomy of Viruses 2022 taxonomy proposals, GRAViTy-V2 output was compared against human expert-curated classifications used for assignments in the 2023 round of ICTV taxonomy changes. GRAViTy-V2 produced taxonomies equivalent to manually-curated versions down to the family level and in almost all cases, to genus and species levels. However, discrepancies with our results primarily arose through various human and automated sequence annotation errors and erroneous annotations of coding sequences used in their original classification. Analysis times ranged from 1-506 min (median 3.59) on datasets with 17-1004 genomes and mean genome length of 3,000-1,000,000 bases, on a standard consumer-grade laptop. We discuss how the output from GRAViTY-V2 outputs allows for a full analysis of why taxonomic classifications were proposed, the value of the program for quality control of genetic comparisons, and how to optimise the speed of classification through proper use of GRAViTy-V2s workflow management system.

bioinformatics↗

bioRxiv2024

Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language

Recent research has used large language models (LLMs) to study the neural basis of naturalistic language processing in the human brain. LLMs have rapidly grown in complexity, leading to improved language processing capabilities. However, neuroscience researchers havent kept up with the quick progress in LLM development. Here, we utilized several families of transformer-based LLMs to investigate the relationship between model size and their ability to capture linguistic information in the human brain. Crucially, a subset of LLMs were trained on a fixed training set, enabling us to dissociate model size from architecture and training set size. We used electrocorticography (ECoG) to measure neural activity in epilepsy patients while they listened to a 30-minute naturalistic audio story. We fit electrode-wise encoding models using contextual embeddings extracted from each hidden layer of the LLMs to predict word-level neural signals. In line with prior work, we found that larger LLMs better capture the structure of natural language and better predict neural activity. We also found a logarithmic relationship where the encoding performance peaks in relatively earlier layers as model size increases. We also observed variations in the best-performing layer across different brain regions, corresponding to an organized language processing hierarchy.

neuroscience↗

bioRxiv2024

Systemic and targeted activation of Nrf2 reverses doxorubicin-induced cognitive impairments and sensorimotor deficits in mice

While cancer survivorship has increased due to advances in treatments, chemotherapy often carries long-lived neurotoxic side effects which reduce quality of life. Commonly affected domains include memory, executive function, attention, processing speed and sensorimotor function, colloquially known as chemotherapy-induced cognitive impairment (CICI) or "chemobrain". Oxidative stress and neuroimmune signaling in the brain have been mechanistically linked to the deleterious effects of chemotherapy on cognition and sensorimotor function. With this in mind, we tested if activation of the master regulator of antioxidant response nuclear factor E2-related factor 2 (Nrf2) alleviates cognitive and sensorimotor impairments induced by doxorubicin. The FDA-approved systemic Nrf2 activator, diroximel fumarate (DRF) was used, along with our recently developed prodrug 1c which has the advantage of specifically releasing monomethyl fumarate at sites of oxidative stress. DRF and 1c both reversed doxorubicin-induced deficits in executive function, spatial and working memory, as well as decrements in fine motor coordination and grip strength, across both male and female mice. Both treatments reversed doxorubicin-induced loss of synaptic proteins and microglia phenotypic transition in the hippocampus. Doxorubicin-induced myelin damage in the corpus callosum was reversed by both Nrf2 activators. These results demonstrate the therapeutic potential of Nrf2 activators to reverse doxorubicin-induced cognitive impairments, motor incoordination, and associated structural and phenotypic changes in the brain. The localized release of monomethyl fumarate by 1c has the potential to diminish unwanted effects of fumarates while retaining efficacy.

neuroscience↗

bioRxiv2024

Caveolar Compartmentalization is Required for Stable Rhythmicity of Sinus Nodal Cells and is Disrupted in Heart Failure

BackgroundHeart rhythm relies on complex interactions between electrogenic membrane proteins and intracellular Ca2+ signaling in sinoatrial node (SAN) myocytes; however, mechanisms underlying the functional organization of proteins involved in SAN pacemaking and its structural foundation remain elusive. Caveolae are nanoscale, plasma membrane pits that compartmentalize various ion channels and transporters, including those involved in SAN pacemaking, via binding with the caveolin-3 scaffolding protein, but the precise role of caveolae in cardiac pacemaker function is unknown. Our objective was to determine the role of caveolae in SAN pacemaking and dysfunction (SND). MethodsBiochemical co-purification, in vivo electrocardiogram monitoring, ex vivo optical mapping, in vitro confocal Ca2+ imaging, and immunofluorescent and electron microscopy analyses were performed in wild type, cardiac-specific caveolin-3 knockout, and 8-weeks post-myocardial infarction heart failure (HF) mice. SAN tissue samples from donor human hearts were used for biochemical studies. We utilized a novel 3-dimensional single SAN cell mathematical model to determine the functional outcomes of protein nanodomain-specific localization and redistribution in SAN pacemaking. ResultsIn both mouse and human SANs, caveolae compartmentalized HCN4, Cav1.2, Cav1.3, Cav3.1 and NCX1 proteins within discrete pacemaker signalosomes via direct association with caveolin-3. This compartmentalization positioned electrogenic sarcolemmal proteins near the subsarcolemmal sarcoplasmic reticulum (SR) membrane and ensured fast and robust activation of NCX1 by subsarcolemmal local SR Ca2+ release events (LCRs), which diffuse across [~]15-nm subsarcolemmal cleft. Disruption of caveolae led to the development of SND via suppression of pacemaker automaticity through a 50% decrease of the L-type Ca2+ current, a negative shift of the HCN current (If) activation curve, and a 40% reduction of Na+/Ca2+-exchanger function, along with [~]2.3-times widening of the sarcolemma-SR distance. These changes significantly decreased the SAN depolarizing force, both during diastolic depolarization and upstroke phase, leading to bradycardia, sinus pauses, recurrent development of SAN quiescence, and significant increase in heart rate lability. Computational modeling, supported by biochemical studies, identified NCX1 redistribution to extra-caveolar membrane as the primary mechanism of SAN pauses and quiescence due to the impaired ability of NCX1 to be effectively activated by LCRs and trigger action potentials. HF remodeling mirrored caveolae disruption leading to NCX1-LCR uncoupling and SND. ConclusionsSAN pacemaking is driven by complex protein interactions within a nanoscale caveolar pacemaker signalosome. Disruption of caveolae leads to SND, potentially demonstrating a new dimension of SAN remodeling and providing a newly recognized target for therapy.

physiology↗

bioRxiv2024

NONEXPRESSOR OF PATHOGENESIS-RELATED GENES control Huanglongbing tolerance by regulating immune balance in citrus plants

Huanglongbing (HLB) is a devastating citrus disease caused by the phloem-resident bacterial pathogen Candidatus liberibacter asiaticus (CLas). CLas infection of susceptible varieties triggers unbalanced immune responses, leading to overaccumulation of callose and reactive oxygen species (ROS), which in turn causes phloem plugging and HLB symptom development. Interestingly, some citrus relatives exhibit little or no symptoms in the presence of CLas, a phenomenon termed HLB tolerance. Moreover, overexpression of the Arabidopsis thaliana NPR1 (AtNPR1) gene in susceptible varieties has been shown to confer robust HLB tolerance. However, the mechanisms underlying HLB tolerance remain enigmatic. Here, we show that overexpression of AtNPR1 suppresses CLas- and Pseudomonas syringae pv. maculicola ES4326 (Psm)-induced overaccumulation of callose and ROS in citrus and Arabidopsis, respectively. Importantly, we found that knocking out of the Arabidopsis negative immune regulators, AtNPR3 and AtNPR4, and silencing of their Citrus sinensis ortholog CsNPR3, similarly suppress Psm- and CLas-induced callose and ROS overaccumulation, respectively, and that silencing of CsNPR3 also enhances HLB tolerance. These results reveal a conserved role of the NPR1/NPR3/NPR4-mediated signaling pathway in regulating plant immune balances and provide mechanistic support for overexpression of AtNPR1 or silencing of AtNPR3/AtNPR4 orthologs in citrus as a long-term solution to the HLB disease.

plant biology↗

bioRxiv2022

In vitro and in vivo evaluation of the biofilm-degrading Pseudomonas phage Motto, as a candidate for phage therapy

Infections caused by Pseudomonas aeruginosa are becoming increasingly difficult to treat due to the emergence of strains that have acquired multidrug resistance. Therefore, phage therapy has gained attention as an alternative to the treatment of pseudomonal infections. Phages are not only bactericidal but occasionally show activity against biofilm as well. Here, we describe the Pseudomonas phage Motto which has the ability to clear P. aeruginosa infections in an animal model and also exhibited biofilm-degrading properties. The phage has substantial antibiofilm activity against strong biofilm-producing isolates (n = 10), with at least a 2-fold reduction within 24 hours. To demonstrate the safety of using phage Motto, we performed cytotoxicity studies with human cell lines (HEK 293 and RAW 264.7 macrophages). Using a previously established in vivo model, we demonstrated the efficacy of Motto in C. elegans, with a 90% survival rate when treated with the phage at an MOI of 10. ImportancePhages are often evaluated mainly on their ability to kill bacterial hosts. One important aspect, however, is often neglected: Their ability to degrade biofilms. Not all phages are able to disintegrate biofilms. While phages can kill planktonic cells, it also has often been observed that phages are not able to infect those that are embedded in biofilms. Phage Motto appears to have highly efficient enzymes that degrade biofilms, and might therefore be a highly valuable therapeutic candidate.

microbiology↗