Biology subjects

Johnson, B.

Publications and source records attributed to Johnson, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Heterochromatin protein 1α acts as an essential stabilizer of chromatin packing domains

Background: The spatial organization of the human genome emerges from an enzyme-guided self-assembly process in which chromatin has a bidirectional relationship with transcription. Central to this architecture are chromatin packing domains, 50-200 nm structures exhibiting mass-scaling behavior. Nascent domains arise through transcription and cohesin/CTCF-mediated loop extrusion, while their maturation depends on conditions that permit differential access of epigenetic enzymes to their dense cores and continuously lower density periphery, resulting in the accumulation of heterochromatic marks in domain cores and euchromatic marks outside of the domain cores. In turn, packing domains support transcription by creating an "ideal zone" peripherally to their cores due to a nonmonotonic dependence of transcription rate on local chromatin density. Results: We investigated the role of heterochromatin protein 1 alpha (HP1), a key chromatin crosslinking factor with affinity to H3K9me3 marks, in maintaining packing domain organization. Paradoxically, short-term HP1 degradation resulted in overall downregulation of genes, contrasting with the canonical view that repression of heterochromatin allows chromatin to become more accessible for transcription. While some packing domains persisted, heterochromatic cores of dense packing domains were disrupted. When exposed to hypoxia, HP1-depleted cells exhibited a dampened transcriptional response, showcasing that when domain maturation is disrupted, stress response pathways are not effectively activated. Conclusions: This work highlights HP1 crosslinking as an essential component of domain maturation, as HP1 loss disrupts domain geometry and inhibits efficient transcriptional reprogramming. Our findings suggest an intriguing perspective on the potential relationship between chromatin architecture and gene regulation that could inform chromatin engineering-based treatments.

genomics↗

bioRxiv2026

VEGFR-2 Phosphorylation at Y1054 or Y1214 is Necessary for Mechanically-Induced Angiogenesis

Anti-angiogenic cancer therapies attempt to withhold necessary nutrients and oxygen from growing tumors by targeting the major promoters of endothelial cell (EC) angiogenesis: vascular endothelial growth factor (VEGF) and VEGF receptor 2 (VEGFR-2). Unfortunately, these treatments are often insufficient, even when coupled with chemotherapies, and fail to significantly increase survival rates. The tumor microenvironment (TME) is mechanically distinct compared to normal tissue, including increased matrix deformations or strains caused by cancer-associated fibroblasts (CAFs). In this report, we detail the specific and independent roles of two tyrosine residues, Y1054 and Y1214, on mechanical activation of VEGFR-2. Furthermore, we characterize CAF biochemical and mechanical signaling and demonstrate how ECs exhibit decreased vessel growth when co-cultured with CAFs and treated with a contractility inhibitor. Using non-phosphorylatable VEGFR-2 mutants, we reveal Y1054 and Y1214 are each necessary for EC angiogenesis, particularly in response to strain. Overall, this research highlights the need to study how mechanics in the TME promote vessel growth and thus tumor progression, which is important to consider when developing future anti-angiogenic therapies.

bioengineering↗

bioRxiv2026

Genome-wide association study in Heterogeneous Stock rats identifies genetic loci associated with aversion-based learning and cocaine aversion

Addiction is a complex and heritable trait which progresses through several developmental stages, each of which is presumably influenced by multiple partially overlapping genetic factors. Cocaine initially produces rewarding effects, followed by aversive effects including anxiety, craving, anhedonia, and withdrawal. These aversive effects have been suggested to contribute to the etiology of cocaine use disorders (CUD), as repeated exposure is thought to desensitize the rewarding effects and sensitize the aversive effects through a process involving both aberrant reward-based learning and aberrant avoidance-based learning. We examined the genetic basis of aversion learning using both food-based and cocaine-based behavioral assays in outbred Heterogenous Stock (HS) rats. A total of 1,074 HS rats (35.3% male) underwent runway operant cocaine-seeking, food-based progressive ratio and punishment testing, and locomotion testing. These phenotypes were significantly heritable (with h2 estimates as high as 0.307) and identified significant (p < 0.05) genetic loci related to avoidance-based learning including from the punishment task on Chromosomes 2, 3, 5, and 6, and the cocaine-operant runway latency task on Chromosome X. 172 positional candidate genes were identified from significant and suggestive loci, including Cdh10, Cdh12, Cdh18 which have previously been associated with smoking initiation from human GWAS, Adcy3, Cfap206, and Drc1 which are associated with primary neuronal cilia, as well as SNPs associated with novelty-related and social interaction phenotypes in independent samples of HS rats. Our results suggest that these aversion learning phenotypes are themselves complex heritable traits influenced by multiple genetic loci, which may pleiotropically affect other aspects of addiction biology.

genetics↗

bioRxiv2026

The Effects of Mean Temperature and Diurnal Temperature Range on West Nile Virus Transmission

Temperature is a major driver of arbovirus transmission, and a changing climate is expected to affect this process significantly. Most experimental studies rely on constant temperatures and overlook realistic daily temperature fluctuations that impact vector-pathogen interactions. The nonlinear relationship between temperature and vector traits responsible for pathogen transmission suggests that daily fluctuating temperatures produce phenotypes important for transmission distinct from those at constant temperatures. Here, we tested whether realistic variations in mean temperature and diurnal temperature range (DTR) influence West Nile virus (WNV) transmission. We experimentally infected colonized Culex tarsalis with WNV-infectious blood meals and maintained them under constant and fluctuating temperature regimes. We quantified how temperature, DTR, and incubation time shaped several outcomes (infection, dissemination, infectiousness, WNV loads in mosquito saliva and mosquito survival). We also integrated survival and infectiousness probabilities to infer implications for transmission. We observed strong effects of temperature on the WNV infection dynamics, viral loads and mosquito survival. Although the probability of initial infection was similar among all temperature regimes, dissemination and infectiousness were constrained by temperature. Dissemination and infectiousness were highest at 26{degrees}C and reduced at cooler (22{degrees}C) and warmer (30{degrees}C) temperatures. Fluctuating temperatures significantly decreased infection and dissemination probabilities, while the probability of becoming infectious was driven primarily by mean temperature rather than DTR. Mosquito survival probability was temperature dependent, and fluctuating regimes increased mortality risk by 1.95-fold. Integrating mosquito survival and infectiousness dynamics demonstrated that, although at higher temperatures the extrinsic incubation period is shorter, reduced mosquito lifespan can limit viral transmission. Together, these results indicate that overall WNV transmission is affected by temperature-dependent viral dynamics and host physiological constraints. Fluctuating temperature regimes significantly delay viral dissemination within the host, especially at the optimal temperature (26{degrees}C). Measurement of infection outcomes under constant temperatures treatments may lead to over/under estimation of transmission parameters in epidemiological models, therefore integrating fluctuating temperature treatments into mechanistic models of transmission can improve estimates of when and where WNV transmission is most likely to occur.

ecology↗

bioRxiv2026

Rett syndrome lifespan extension in mice via AI-guided ADAR editing

Rett syndrome is a severe neurodevelopmental disorder primarily caused by mutations in the MECP2 gene. A significant subset of severe cases are driven by nonsense mutations that generate premature stop codons, leading to loss of functional MeCP2 protein. Here, we describe a novel therapeutic strategy that uses endogenous adenosine deaminase acting on RNA (ADAR) enzymes to correct the R168X mutation at the RNA level. Using generative artificial intelligence trained on large empirical datasets, we engineered guide RNAs (gRNAs) that recruit endogenous ADAR to convert the mutant stop codon (UGA) into a tryptophan (UGG) to restore full-length MeCP2. Once incorporated into an optimized expression system based on endogenous small nuclear RNA regulatory elements and packaged into adeno-associated virus, these gRNAs enabled precise RNA editing at the target site with minimal off-target activity across the transcriptome while restoring full-length MeCP2 protein expression in patient-derived induced pluripotent stem cell neurons. Delivered intravenously to an R168X mouse model, the gRNAs achieved ~70% targeted RNA editing and substantially restored MeCP2 throughout the brain resulting in markedly improved Rett-like phenotypes and significantly extended lifespan. These findings demonstrate that AI-guided ADAR-mediated RNA editing is a precise and efficient technology for correcting nonsense mutations, with therapeutic potential for Rett syndrome and other genetic diseases.

neuroscience↗

bioRxiv2026

Vertical Sleeve Gastrectomy inhibits 11βHSD1 and subsequently reduces IL6 secretion in Mice and Humans: A Shared Anti-Inflammatory Mechanism

BackgroundVertical sleeve gastrectomy (VSG) improves glycaemic control in type 2 diabetes (T2D) through mechanisms that extend beyond weight loss. The interaction between glucocorticoid metabolism and inflammation in this context remains unclear. MethodsWe investigated the role of 11{beta}-hydroxysteroid dehydrogenase type 1 (11{beta}HSD1) in mediating the metabolic effects of VSG in humans and mice. Subcutaneous adipose tissue biopsies were collected before and 6 months after VSG. Parallel studies were conducted in lean and high-fat diet-fed mice undergoing VSG or sham surgery, alongside 11{beta}HSD1 knockout models. Glucose tolerance and expression of 11{beta}HSD1 and interleukin-6 (IL6) were assessed. Mechanistic interactions were examined in IL6-treated human hepatocytes. ResultsVSG reduced 11{beta}HSD1 and IL6 expression in human adipose tissue and improved insulin resistance. In lean mice, VSG improved glucose tolerance and downregulated both markers independently of weight loss. 11{beta}HSD1 knockout mice exhibited improved glucose tolerance despite increased adiposity, partially recapitulating the VSG phenotype. Both interventions reduced circulating and tissue IL6 levels. IL6 stimulation increased HSD11B1 expression in hepatocytes. Conclusions11{beta}HSD1 links glucocorticoid metabolism, inflammation, and glucose homeostasis following VSG. Targeting this pathway may offer a strategy to replicate key metabolic benefits of metabolic bariatric surgery.

physiology↗

bioRxiv2026

Accurate single-bead force calibration in high-throughput magnetic tweezers reveals the mechanism of directional transcription termination by MTERF1

High-throughput force spectroscopy assays, such as with magnetic tweezers, enable reconstruction of biomolecular reaction energy landscapes and provide access to rare events with deep statistics. Precise force calibration is essential for accurately describing complex reactions, which can be hindered by sample heterogeneity, such as bead-to-bead difference in magnetic content. Here, we describe an in-situ force calibration methodology for high-throughput magnetic tweezers that enables the calibration for each individual bead with an accuracy of up to 3%, limited only by the statistical resolution. We apply this approach to characterize the directional transcription termination molecular mechanism by the polar roadblock mitochondrial transcription termination factor 1 (MTERF1). Establishing a SpyTag-SpyCatcher surface-attachment strategy, we performed force-jump experiments on the same tethers for up to 11 hours. We showed that directional DNA unwinding is sufficient to explain the polar roadblock activity of MTERF1. Accurate force spectroscopy further reveals that the unlocking transition is rate-limited by a single kinetic barrier, with a transition-state distance consistent with structural interpretations. Together, these results provide a mechanistic and broadly applicable model for the asymmetric stability of MTERF1 and other nucleic acid polar roadblocks and establish a robust force spectroscopy framework for high-throughput magnetic tweezers experiments.

biophysics↗

bioRxiv2026

Humidity shapes the thermal niche of Anopheles stephensi,an invasive malaria vector

Vector-borne pathogens cause 17% of all human infectious diseases, and rising global temperatures are shifting the distribution and abundance of mosquito vectors. Because mosquitoes are ectotherms, temperature strongly governs biological rates and physiology; however, mosquitoes also experience other environmental factors that may interact with temperature to shape the thermal performance of traits driving population dynamics. Here, we use a factorial life-table experiment spanning five relative humidities (30-90%) and seven temperatures (16-38{whitebullet}C) to show that humidity modifies the thermal performance of key fitness traits in adult Anopheles stephensi, an invasive urban malaria vector. When integrated into a demographic model, humidity markedly reshapes projections of population fitness relative to temperatureonly models, suppressing growth and contracting year-round suitability in hot, arid regions while enhancing fitness in more humid or high-elevation climates characteristic of South Asia and Africa. Together, these results highlight the need to integrate multiple environmental drivers into projections of climatic suitability, as temperature-only approaches may mischaracterize both the magnitude and spatial structure of mosquito population fitness. More broadly, our findings demonstrate how moisture availability reshapes thermal niches, population fitness, and climate-driven projections of vector distributions.

ecology↗

bioRxiv2026

Evaluating satellite and modeled lake surface water temperature across the contiguous United States.

We developed a model to predict surface water temperature across U.S. lakes using satellite remote sensing and in situ observations to enhance cyanobacterial harmful algal bloom (cyanoHAB) forecasting. The study focused on Sentinel-3 Ocean and Land Colour Instrument (OLCI) sensor resolved lakes. We developed random forest models using both Landsat-derived and in-situ-measured surface water temperature. Landsat models offered broad spatial and temporal coverage of all OLCI resolved lakes, but they were sensitive to cloud cover and required filtering to minimize error. In contrast, the in situ model represented fewer OLCI resolved lakes, but yielded lower mean absolute error and bias. The models predicted lake surface temperature across the entire calendar year, with best performance (RMSEapplied=1.11; biasapplied=0.01; MAEapplied=0.77) from the in situ model. This approach allowed for the continuous prediction of lake surface temperatures from 1.1 to 31.6 {degrees}C for unfrozen, open-water conditions critical for improving the accuracy of cyanoHAB forecasting. A key strength of this study was the use of an extensive dataset and model validation against in situ observations, which improved predictive accuracy throughout the year across all seasons. The predictive model offers a water resource tool for management, ecosystem protection, and public health.

ecology↗

bioRxiv2026

A Robust Chemical-free Platform for Age-Synchronized Caenorhabditis elegans Populations Maintenance for High-Throughput Screening in Aging Studies

Caenorhabditis elegans (C. elegans) is a well-established model for investigating the mechanisms of aging and age-related disorders like neurodegeneration. However, maintaining age-synchronized populations of C. elegans for aging studies without genetic or pharmacological interventions presents significant challenges, given their high reproductive rate: each nematode produces over 300 progeny. The traditional method for maintaining an age-synchronized population for multi-day studies without interventions is labor-intensive and low-throughput, hindering research on aging mechanisms and the identification of novel interventions for aging. To address these limitations, a novel, robust method was developed to sustain age-synchronized populations in a 96-well plate liquid culture format for up to 12 days without custom-made apparatuses. The robustness of this method was substantially improved by optimizing the surface composition of the multi-well plate and disposables, refining culture parameters, including life stage, medium composition, and bacterial food concentration. To facilitate unbiased phenotype assessment throughout the lifespan, we used a Wmicrotracker ONE reader to monitor worm movement and viability in a multi-well plate. The overall fitness decline with aging using our method is comparable to that of worms maintained on solid agar. Lastly, using transgenic C. elegans carrying tauopathy, we demonstrated the ability of applying our optimized platform for high-throughput screening with a Z-factor of 0.7. Our novel method simplifies age-synchronized population maintenance, enhances progeny separation, and reduces costs, enabling high-throughput screening of compounds and RNAi libraries. These advancements greatly enhance the versatility of C. elegans as a model organism, offering a scalable platform for genetic and compound screening and for comprehensive investigations into drug discovery and disease mechanisms.

pharmacology and toxicology↗

bioRxiv2026

A Manifold-Based Measure of Transcriptional Entropy for Quantifying Aging in Single Cells

Aging reshapes tissues through changes in cellular composition, coordinated transcriptional reprogramming, and loss of transcriptional coordination. Whereas the first two have been characterized across aging tissues, the third remains difficult to quantify. We introduce an unsupervised, first-principles framework for measuring transcriptional dyscoordination in single cells as deviation from a learned, predictable structure accounting for technical noise. Orthogonal validation links transcriptional dyscoordination to classical intrinsic noise and distinguishes it from coordinated change. In controlled perturbations, dyscoordination rises after genotoxic injury and senescence induction, then falls following senolytic depletion. Across mouse, rat, and human tissues, dyscoordination increases with chronological age, especially in regenerative compartments. In human T cells, dyscoordination increases with clonal expansion and effector function yet declines within persisting clones after checkpoint blockade. Cross-modal analyses further link dyscoordination to chromatin-based mitotic age and genome instability. These results identify loss of transcriptional coordination as a distinct and dynamic feature of cellular aging.

genomics↗

bioRxiv2026

Species Identification and Antimicrobial Susceptibility of Mycobacterial Isolates from Dogs and Cats

Nontuberculous Mycobacterium (NTM) species are increasingly recognized as opportunistic pathogens in companion animals, yet data on species distribution and antimicrobial resistance remain limited. The goal of this study was to evaluate species identification methods and determine antimicrobial susceptibility profiles of NTM isolates from cats and dogs submitted to the University of Tennessee veterinary diagnostic laboratory. Twenty-nine NTM isolates (25 feline, 4 canine) collected between 2016 and 2022 were cultured and identified using MALDI-TOF MS and 16S rRNA sequencing. Antimicrobial susceptibility testing (AST) was performed by broth microdilution. Most isolates (27/29) were rapidly growing mycobacteria from skin or wound samples. Combined MALDI-TOF and sequencing identified 11 isolates within the Mycobacterium fortuitum complex, 10 as M. smegmatis, 4 within the M. abscessus group, and one each as M. mucogenicum and M. farcinogenes. MALDI-TOF failed to identify four isolates, including two slow-growing strains. AST revealed consistent susceptibility to amikacin and moxifloxacin, while resistance was highest to doxycycline (44%), clarithromycin (37%), and tobramycin (33%). Rapidly growing NTM predominates in feline cutaneous infections, with species-specific resistance patterns underscoring the need for accurate identification and AST to guide therapy. Importance StatementNontuberculous mycobacteria (NTM) are emerging causes of skin infections in cats and dogs, yet little is known about which species are involved or how they respond to treatment. Knowing the specific species and their resistance patterns is critical for choosing effective treatments and improving outcomes for affected animals. This study provides critical baseline data by identifying NTM species and their antimicrobial resistance patterns in companion animals. These findings highlight the need for accurate diagnostic methods and targeted therapy to improve clinical outcomes. Understanding these trends is essential for guiding veterinary care and informing future research on antimicrobial resistance in animal health.

microbiology↗

bioRxiv2025

Cysteine protease cathepsin B promotes high population density-induced mutagenesis, driving genome evolution and competitive growth in response to the crowding stress

In a wide variety of species from invertebrates to mammals, overpopulation has been shown to induce low fertility and high mortality. Although density-dependent population regulation is widespread in the animal kingdom, the underlying molecular mechanisms remain poorly understood. We show here that C. elegans animals respond to the crowding stress by secreting CPR-4, a homologue of human cathepsin B cysteine protease, to promote chromosomal DNA damage in germ cells, leading to high density-induced deficiencies that include increased embryonic lethality and larval arrest and decreased brood size. CPR-4 mediates these crowding responses through the insulin-like growth factor receptor DAF-2, multiple components in the insulin signaling pathway, and the SKN-1/Nrf transcription factor. Whole genome sequencing analyses of animals from 10 generations of continual growth in the crowded condition reveal that CPR-4-induced DNA damage produces an average of 2.9 more de novo genome mutations per animal per generation and a 75% increase in mutation rate compared with animals grown in the uncrowded condition. CPR-4-induced mutagenesis also facilitates evolution of the genomes through multi-generational crowding selection, leading to biased mutation distributions towards the intergenic regions over the gene bodies and crowd-inducible growth advantage. Our findings suggest that CPR-4 acts as a crucial crowd-responding factor to induce chromosomal DNA damage, leading to density-dependent deficiencies, increased genome mutation rates, and genome evolution and competitive growth of animals in response to the crowding stress.

developmental biology↗

bioRxiv2025

MCA: A Multicellular analysis Calcium Imaging toolbox for ImageJ

Functional imaging using genetically encoded indicators, such as GCaMP, has become a foundational tool for in vivo experiments and allows for the analysis of cellular dynamics, sensory processing, and cellular communication. However, large scale or complex functional imaging experiments pose analytical challenges. Many programs have worked to create pipelines to address these challenges, however, most platforms require proprietary software, impose operational restrictions, offer limited outputs, or require significant knowledge of various programming languages, which collectively can limit utility. To address this, we designed MCA (a Multicellular Analysis toolkit) to work with ImageJ, a widely used open-source software which has been the standard image analysis platform for the last 30 years. We developed MCA to be visually intuitive, utilizing ImageJs platform to generate new images based on completed tasks so users can visually see each step in the analysis pipeline. In addition, MCA implements a user-friendly GUI providing a simple interface which resembles other native ImageJ plugins. We incorporated functionality for rigid registration to correct motion artifacts, algorithms for cell body prediction, and methods for annotating cells and exporting data. For cell prediction, we trained a custom model in Cellpose 2.0 for segmentation of nuclei expressing pan-neuronal nuclear localized GCaMP in zebrafish. We validated the accuracy of MCA output to previously published zebrafish calcium imaging data which elicited visually evoked neuronal responses. To show the versatility of MCA, we also show that our software can be utilized for multiple sensory modalities, brain regions, and multiple model organisms including Drosophila and mouse. Together these data show that MCA is viable for extracting calcium dynamics in a user-friendly environment for multiple forms of functional imaging. MotivationCalcium imaging has become one of the most common methods for investigating neural activity, however analytical methods are limited to a few software platforms or are custom made. This limits replicability and imposes restrictions on incorporating additional tools to support analysis. To address these challenges, we developed a modular, graphical based, open-source toolbox, based in the ImageJ application, for performing functional imaging analysis in diverse models and datasets. HighlightsO_LIDeveloped MCA, an ImageJ based plugin for analyzing functional imaging datasets. C_LIO_LIValidated accuracy of MCA functions C_LIO_LIUtilized MCA across multiple sensory modalities and model organisms C_LI

neuroscience↗

bioRxiv2025

Comparison of a computer vision model to a human observer in detecting African mammals in camera trap images within a safari park

Remote monitoring technologies are increasingly utilized in animal research for their capacity to enhance data collection efficiency. However, they present challenges, and as such researchers have resorted to utilizing deep learning to automatically classify acquired data therefore expediting the review process. While this practice is common in field studies it has been less adopted in zoo monitoring. In this paper we deploy the YOLOv10x model to monitor four species at Knowsley Safari in the UK: African lions (Panthera leo), Southern white rhino (Ceratotherium simum simum), Grevys zebra (Equus grevyi) and Olive baboons (Papio anubis). Camera trap images were processed and classified using the Conservation AI desktop application. The raw images were saved to facilitate the comparative analysis of the models predictions against the findings of human observed images. Processing time for both methods was compared using a subset of 3015 images with Conservation AI, reducing the time required to classify the images by 82% compared to a human analyst. Confusion matrix results showed high accuracy rates for all four species (>0.90). Analysis of count data showed significant differences in three species, where the human observer recorded more observations of each than Conservation AI (lion, rhino, baboon p<0.005). However, no significant difference was seen in zebra (p>0.05). A strong positive correlation in count data between both methodologies was seen in all species; baboon (rho=0.955, p<0.005), lion (rho = 0.969, p<0.005), rhino (rho=0.887, p<0.005) and zebra (rho=0.843, p<0.005). This study highlights the potential for these technologies as a monitoring system in zoos.

animal behavior and cognition↗

bioRxiv2025

Beyond temperature: Relative humidity systematically shifts the temperature dependence of population growth in a malariavector

Understanding ectotherm responses to environmental change is central to coping with many of humanitys current and future challenges in public health, biodiversity conservation, and food security. Complex relationships between abiotic and biotic factors can influence ectotherm abundance and distribution patterns by introducing stage-specific variation in fitness trait responses. Variation in temperature, rainfall, competition, and habitat have all been considered in previous attempts to understand how environmental factors can interact and vary in their relative influence on species maximal population growth rates, rm. However, the combined effects of temperature and humidity on this fundamental metric are poorly understood. We show that variation in relative humidity can influence juvenile trait responses and rms temperature dependence in Anopheles stephensi, an important malaria vector. Our climate suitability maps show that the interactive effects of temperature x humidity on juvenile traits have important implications for predicting how environmental change will influence arthropod-mediated systems.

ecology↗

bioRxiv2025

Rapid population flux in bacterial spot xanthomonads during a transition in dominance between two genotypes in consecutive tomato production seasons and identification of a new species Xanthomonas oklahomensis sp. nov.

In the bacterial spot of tomato disease complex, Xanthomonas euvesicatoria pv. perforans (Xep) is known to outcompete X. euvesicatoria pv. euvesicatoria (Xee). The result, over time in tomato production systems where both pathogens are present, is the anticipated displacement of Xee by Xep. In this study, we characterized the population of recovered strains from grower fields in response to a bacterial spot of tomato outbreak in east and central Oklahoma in 2018 and 2019. Tomato and pepper strains sampled in earlier years were included to provide additional context. Phenotypic and genome-based analyses showed marked differences in race and species composition in recovered strains. All pre-2018 (2001-2014) tomato bacterial spot strains were Xep race T3, except one T4 strain. Tomato bacterial spot strains in 2018 consisted of Xee race T1 and Xep T3, while strains recovered in 2019 from the same locations were exclusively Xep T4 strains. The 2019 Xep T4 strains form the same cluster with the 2014 Xep T4 strain on the phylogenetic tree, suggesting the same population. Only the Xep race T4 strains showed an expanded host range to pepper. The recovered strains were also variable in copper sensitivity and effector content. We additionally recovered non-bacterial spot xanthomonads, one of which belongs to the new species, Xanthomonas oklahomensis sp. nov. These results contributes to novel insights in understanding genomic heterogeneity and seasonal population flux between competing bacterial genotypes during disease outbreaks and can be considered when developing disease management strategies.

plant biology↗

bioRxiv2025

α-Melanocyte Stimulating Hormone Reduces Blood Glucose Across Species

Peripheral administration of -melanocyte stimulating hormone (-MSH) promotes glucose uptake in skeletal muscle via a melanocortin 5 receptor (MC5R)-dependent mechanism in rodents. Here we demonstrate that this pathway is functional in humans. During an oral glucose tolerance test (GTT) in healthy human volunteers, peripheral administration of -MSH was well tolerated, and reduced glucose and insulin incremental area under the curve by 39% and 35%, respectively. During a GTT in non-human primates, both -MSH and a selective MC5R agonist, PG-901, increased glucose tolerance. In vitro, both -MSH and PG-901 induced glucose uptake in primary human and non-human primate myotubes and immortalised human myotubes. Subcutaneous injection of PG-901 reduced blood glucose concentrations during a GTT in WT mice but had no effect in MC5R deficient mice. Thus, the novel MC5R-skeletal muscle pathway found in animals is functional in humans and represents a novel target for glycaemic control in people with diabetes.

physiology↗