Biology subjects

Bishop, A.

Publications and source records attributed to Bishop, A..

7 recordsLinked to original sources

bioRxiv2026

Mapping tsetse fly connectivity in Uganda with machine learning landscape genetics

Introduction - Tsetse flies (genus Glossina) are biting insects that transmit human and animal trypanosomiases across sub-Saharan Africa, and sustainable vector control depends on understanding dispersal barriers and reinvasion routes. Despite major progress toward elimination, Uganda remains at risk for both human forms of the disease (Trypanosoma brucei gambiense and T. b. rhodesiense) and planners still lack reliable maps of tsetse movement and reinvasion risk. Methods and Results - We address this gap with machine-learning landscape genetics and species distribution models, integrating estimates of population genetic distance and geospatial environmental data to predict and map Glossina fuscipes fuscipes connectivity across Uganda and western Kenya. Inputs included microsatellite genotypes from 11 loci genotyped in 2,736 flies sampled from 87 localities and remotely sensed environmental predictors summarized along least-cost paths. Random forest models predicted patterns of genetic differentiation better than distance-only models, supporting the use of a machine-learning framework for connectivity inference across complex heterogeneous landscapes, and identified variables related to temperature and water availability as the strongest predictors of genetic connectivity. Conclusions - Combining landscape genetics predictions of connectivity with a species distribution model revealed regions with high habitat suitability but low connectivity that represent priority zones for area-wide integrated pest management strategies, including established riverine control tools such as tiny targets and other targeted interventions aimed at reducing reinvasion risk. These results provide biologically interpretable maps and quantitative uncertainty metrics that can guide targeted tsetse control, while providing a transferable analytical pipeline for modeling and mapping genetic connectivity across other species and landscapes.

evolutionary biology↗

bioRxiv2026

The UPR drives gametogenesis via an unexpected response, coordinating translation and ER structure

Stress responses, including the unfolded protein response (UPR), are commonly studied via induction with harsh exogenous stressors, leaving endogenous functions of these pathways less well understood. We found that the endogenous UPR that precedes meiosis in budding yeast is required for gamete production but diverges dramatically from previously defined UPR outputs, with only a few characterized UPR targets induced, and mildly. The role of this UPR can be replaced by increasing ER chaperones, reducing bulk translation, or impairing the machinery for protein translocation into the ER. ER integrity appears compromised in pre-meiotic cells lacking the UPR, as foci of reticulon proteins are seen and correlate strongly with an inability of cells to enter meiosis. These findings indicate that physiological UPR activation supports proteostasis and normal ER structure, preparing cells for meiotic entry by reducing the load of proteins that enter the ER. Overall, our study reveals surprising features of a physiological UPR induction that enables a cell fate decision.

cell biology↗

bioRxiv2025

Optimizing the Characterization and Quantification of Retinal Ganglion Cell Somas in Healthy and Injured Retinas Using Cellpose

Quantification of retinal ganglion cell (RGC) soma number and characterization of somal features are commonly used output metrics for investigation of optic neuropathies. Many investigators still perform these quantifications by hand, which is time consuming and prone to bias. Cellpose is an open-source Python package that can perform cellular segmentation and holds promise for automating somal analyses. Here, we designed a custom script incorporating the Cellpose package and custom-trained Cellpose models that are capable of automatic characterization and quantification of RGC somas. Our script, using our models, is capable of automatically counting RGC somas, along with characterizing RGC somal size. Further, we show that Cellpose can quantify RGCs using multiple cell-type specific markers and has the potential to quantify RGCs across the entire retina. Together, our custom Cellpose models and script which generates and analyzes Cellpose outputs provides a powerful tool for all-in-one RGC somal analysis.

neuroscience↗

bioRxiv2025

Song familiarity relies on evidence accumulation

Familiarity judgements are thought to involve evidence accumulation, a decision-making process in which information is gathered over time until a threshold is reached. Previous work has identified a scalp-recorded signature of evidence accumulation called the central-parietal positivity (CPP). We built on this previous work and recorded electroencephalography (EEG) while participants listened to several melodies, instructing participants to respond as soon as the song felt familiar. A prominent CPP was noted, time-locked to decisions. We then used linear regression to unmix overlapping neural responses and observed a stimulus-locked indicator of evidence accumulation that increased in amplitude just prior to a familiarity decision. This result suggests that song familiarity relies on evidence accumulation, with individual notes in a familiar song acting as "evidence".

neuroscience↗

bioRxiv2024

Efficient High-Throughput DNA Breathing Features Generation Using Jax-EPBD

DNA breathing dynamics--transient base-pair opening and closing due to thermal fluctuations--are vital for processes like transcription, replication, and repair. Traditional models, such as the Extended Peyrard-Bishop-Dauxois (EPBD), provide insights into these dynamics but are computationally limited for long sequences. We present JAX-EPBD, a high-throughput Langevin molecular dynamics framework leveraging JAX for GPU-accelerated simulations, achieving up to 30x speedup and superior scalability compared to the original C-based EPBD implementation. JAX-EPBD efficiently captures time-dependent behaviors, including bubble lifetimes and base flipping kinetics, enabling genome-scale analyses. Applying it to transcription factor (TF) binding affinity prediction using SELEX datasets, we observed consistent improvements in R2 values when incorporating breathing features with sequence data. Validating on the 77-bp AAV P5 promoter, JAX-EPBD revealed sequence-specific differences in bubble dynamics correlating with transcriptional activity. These findings establish JAX-EPBD as a powerful and scalable tool for understanding DNA breathing dynamics and their role in gene regulation and transcription factor binding.

bioinformatics↗

bioRxiv2024

Scalable DNA Feature Generation and Transcription Factor Binding Prediction via Deep Surrogate Models

Simulating DNA breathing dynamics, for instance Extended Peyrard-Bishop-Dauxois (EPBD) model, across the entire human genome using traditional biophysical methods like pyDNA-EPBD is computationally prohibitive due to intensive techniques such as Markov Chain Monte Carlo (MCMC) and Langevin dynamics. To overcome this limitation, we propose a deep surrogate generative model utilizing a conditional Denoising Diffusion Probabilistic Model (DDPM) trained on DNA sequence-EPBD feature pairs. This surrogate model efficiently generates high-fidelity DNA breathing features conditioned on DNA sequences, reducing computational time from months to hours-a speedup of over 1000 times. By integrating these features into the EPBDxDNABERT-2 model, we enhance the accuracy of transcription factor (TF) binding site predictions. Experiments demonstrate that the surrogate-generated features perform comparably to those obtained from the original EPBD framework, validating the models efficacy and fidelity. This advancement enables real-time, genome-wide analyses, significantly accelerating genomic research and offering powerful tools for disease understanding and therapeutic development.

genomics↗

bioRxiv2021

Fenbendazole resistance in Heterakis gallinarum, the vector of Histomonas meleagridis, the causative agent of Blackhead Disease in poultry.

Due to their ubiquity, management of parasites is a common and important factor for profitable production of poultry. Heterakis gallinarum, the cecal nematode, is the most common nematode parasite of poultry. While typically causing no pathology on its own, H. gallinarum is the vector of Histomonas meleagridis, a protozoan parasite that causes blackhead disease. Histomonas meleagridis is highly pathogenic in turkeys, potentially causing high mortality. In contrast, disease caused by H. meleagridis is much less severe in chickens, where it primarily reduces productivity without manifestations of clinical disease. There are no approved treatments for H. meleagridis, making control reliant on control of the helminth vector through the use of fenbendazole (FBZ) the only drug labeled for treatment of H. gallinarum in the United States We were contacted by an industry veterinarian regarding health-related concerns in a broiler-breeder house due to histomoniasis, despite frequent anthelmintic treatments. Since we had recently diagnosed resistance to FBZ in Ascaridia dissimilis, a closely related nematode of turkeys, we were interested to determine if H. gallinarum had also evolved resistance to FBZ. Heterakis gallinarum eggs were isolated from litter collected from the house and used to infect 108 chickens. Treatment groups included a non-treated control, a label-dose and a 2X-label dose of FBZ, with 36 birds per group divided into two replicate pens of 18 birds each. Birds were placed at 1-day post hatch, and at 3 weeks of age were infected with 150 embryonated eggs via oral gavage. Two weeks post infection, treated birds were administered a minimum of either a label- or 2X label-dose of FBZ in water for 5 days (SafeGuard(R) Aquasol, 1mg/kg BW). To ensure that all birds consumed the full intended dose at a minimum, the dosage was calculated using 1.25 times the average body weight. One-week post treatment, birds were euthanized, ceca removed, and parasites enumerated. Efficacy was calculated by comparing the total numbers of worms recovered from each treatment group to the numbers recovered in the non-treated control group. There were no significant differences in worm numbers recovered from any of the three groups (p-value=0.81). There also was no efficacy benefit to treatment with a 2X dose; H. gallinarum worm counts were reduced by 42.7% and 41.4%, for the label and 2X dosages, respectively. These data provide strong evidence that H. gallinarum has developed resistance to FBZ. Consequently, in houses infected with FBZ-resistant H. gallinarum, H. meleagridis will be able to cycle through the birds in an unrestricted manner. Further investigation is needed to determine the prevalence of resistance in H. gallinarum on chicken farms, but it is clear this has the potential to have a large-scale economic impact on the poultry industry. These data when viewed together with our recent findings of FBZ resistance in A. dissimilis, suggest that drug resistance in ascarid nematodes may be an important emerging problem on poultry operations.

zoology↗