Biology subjects

Barrett-Jolley, R.

Publications and source records attributed to Barrett-Jolley, R..

11 recordsLinked to original sources

bioRxiv2026

DiffuChannel: A Conditional Denoising Diffusion Model that Synthesises Single-Molecule Patch-Clamp Data with Exactly Known Idealisation (Ground Truth)

Development of computational models for single-channel patch-clamp analysis is hampered by limited availability of labelled (idealised) data. Since experiment alone cannot provide a genuine ground truth, two simulation methods are commonly employed; Stochastic sampling from a specified Markov model, augmented with synthetic noise allows creation of unlimited, flawlessly idealised/annotated datasets, yet its authenticity hinges entirely on the premises underlying data and noise generation. A more recent method uses GAN-based generation, this also replicates real-world noise and artefacts, but does not include a ground truth idealisation or annotation and training is notoriously unstable. Here, we introduce DiffuChannel, a conditional noise-removal diffusion model that addresses these drawbacks. Channel dynamics come directly from a user-defined discrete-time Markov chain (or a model fitted to biological seed data), thus, the state assignment for each synthetic trace is precisely determined by design. The diffusion model is then trained exclusively to capture the noise distribution of raw current conditioned on a given idealisation, thereby replicating genuine noise, filtering, and artefact patterns observed in real data without needing to hand craft noise models. We use a two-step coarse-to-fine workflow that starts with a defined slow-envelope component conditioned on longer-term dwell-time features extracted from the input idealisation. This allows a degree of baseline drift and time-dependent relaxations to be captured over timescales far longer than the network's field of view. At generation time, we use a context-preserving inpainting method that enables creation of relatively seamless traces of any desired duration. We demonstrate that with only a limited set of labelled seed traces, synthetic records yield realistic all-points amplitude distribution, noise power spectrum, autocorrelation pattern, and slow envelope comparable to the source data. The model achieves a maximum mean discrepancy (MMD) between windowed real and generated data of 0.005 (median across the five phenotypes). This compares to a within real-split-half MMD value of 0.002 and an amplitude-matched white noise MMD value of 0.108. In this paper, we benchmark this against DeepGANnel. Since the underlying Markov model is defined rather than estimated, DiffuChannel generates infinite, perfectly labelled, phenotype-consistent training data ideal for developing and testing idealisation algorithms. We find that, in practice, this new method is far more stable than previous GAN models and runs start to end without human intervention. We provide the model open-source along with an interactive web-based training and synthesis interface/app.

biophysics↗

bioRxiv2026

Proteomic Signatures of Mitochondrial Dysfunction Associated with Atrial Fibrillation in Goats

Atrial fibrillation (AF) increases energy demand in atrial myocytes, yet the mitochondrial mechanisms underlying this stress remain poorly defined. Using previously published proteomic data from left atrial tissue of AF and sham-operated goats, we performed organelle-specific bioinformatic analyses of the mitochondrial fraction. Over-representation and consensus pathway analyses consistently highlighted enrichment of oxidative phosphorylation (OXPHOS) subunits. Gene set enrichment and network analyses implicated Heat Shock Protein Family A Member 9 (HSPA9) as a potentially central regulatory hub coordinating the dysregulation of Complex I and III subunits, with 69% of regulatory relationships showing pathway concordance. These results indicate a coordinated, system-wide mitochondrial adaptation in AF, integrating energy production, proteostasis, and respiratory chain regulation.

molecular biology↗

bioRxiv2022

Variables associated with owner perceptions of the health of their dog: further analysis of data from a large international survey

In a recent study (doi: 10.1371/journal.pone.0265662), associations were identified between owner-reported dog health status and diet, whereby those fed a vegan diet were perceived to be healthier. However, the study was limited because it did not consider possible confounding from variables not included in the analysis. The aim of the current study was to extend these earlier findings, using different modelling techniques and including multiple variables, to identify the most important predictors of owner perceptions of dog health. From the original dataset, two binary outcome variables were created: the any health problem distinguished dogs that owners perceived to be healthy ("no") from those perceived to have illness of any severity; the significant illness variable distinguished dogs that owners perceived to be either healthy or having mild illness ("no") from those perceived to have significant or serious illness ("yes"). Associations between these health outcomes and both owner-animal metadata and healthcare variables were assessed using logistic regression and machine learning predictive modelling using XGBoost. For the any health problem outcome, best-fit models for both logistic regression (area under curve [AUC] 0.842) and XGBoost (AUC 0.836) contained the variables dog age, veterinary visits and received medication, whilst owner age and breed size category also featured. For the significant illness outcome, received medication, veterinary visits, dog age and were again the most important predictors for both logistic regression (AUC 0.903) and XGBoost (AUC 0.887), whilst breed size category, education and owner age also featured in the latter. Any contribution from the dog vegan diet variable was negligible. The results of the current study extend the previous research using the same dataset and suggest that diet has limited impact on owner-perceived dog health status; instead, dog age, frequency of veterinary visits and receiving medication are most important.

zoology↗

bioRxiv2022

The temporal transcriptomic signature of cartilage formation

Chondrogenesis is a multistep process, in which cartilage progenitor cells generate a tissue with distinct structural and functional properties. Although several approaches to cartilage regeneration rely on the differentiation of implanted progenitor cells, the temporal transcriptomic landscape of in vitro chondrogenesis in different models has not been reported. Using RNA sequencing, we examined differences in gene expression patterns during cartilage formation in micromass cultures of embryonic limb bud-derived progenitors. Principal component and trajectory analyses revealed a progressively different and distinct transcriptome during chondrogenesis. Differentially expressed genes (DEGs), based on pairwise comparisons of samples from consecutive days were classified into clusters and analysed. We confirmed the involvement of the top DEGs in chondrogenic differentiation using pathway analysis and identified several chondrogenesis-associated transcription factors and collagen subtypes that were not previously linked to cartilage formation. Transient gene silencing of ATOH8 or EBF1 on day 0 attenuated chondrogenesis by deregulating the expression of key osteochondrogenic marker genes in micromass cultures. These results provide detailed insight into the molecular mechanism of chondrogenesis in primary micromass cultures and present a comprehensive dataset of the temporal transcriptomic landscape of chondrogenesis, which may serve as a platform for new molecular approaches in cartilage tissue engineering. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=181 SRC="FIGDIR/small/486765v2_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1b599d5org.highwire.dtl.DTLVardef@18670daorg.highwire.dtl.DTLVardef@15afc12org.highwire.dtl.DTLVardef@5b0791_HPS_FORMAT_FIGEXP M_FIG This study provides insights into the mechanisms of cartilage formation. Gene expression patterns during cartilage formation in micromass cultures were analysed using RNA sequencing. Silencing ATOH8 or EBF1 attenuates chondrogenesis. C_FIG Key points* We examined the global gene expression patterns during in vitro chondrogenesis. * Using WGCNA, we created a module of genes with patterns similar to those of SOX9, ACAN, and COL2A1. * We identified ATOH8 and EBF1 transcription factors with a yet unexplored role in chondrogenesis.

molecular biology↗

bioRxiv2022

Temperature modulates PVN pre-sympathetic neurones via transient receptor potential ion channels.

Background and purposeThe paraventricular nucleus (PVN) of the hypothalamus plays a vital role in maintaining homeostasis and controls cardiovascular function via autonomic pre-sympathetic neurones. We have previously shown that coupling between transient receptor potential cation channel subfamily V member 4 (Trpv4) and small-conductance calcium-activated potassium channels (SK) in the PVN facilitate osmosensing. TRP channels are also thermosensitive and therefore, in this report we investigated the temperature sensitivity of PVN neurones. Experimental approachWe identified TRP channel mRNA in mouse PVN using quantitative reverse transcription-PCR (RT-PCR). Using cell-attached patch-clamp electrophysiology, we characterised the thermosensitivity of Trpv4-like ion channels on mouse PVN neurones. Following recovery of temperature sensitive single channel kinetic schema, we constructed a novel and predictive stochastic mathematical model of these neurones. We then validated this model with electrophysiological recordings of action current frequency from mouse PVN neurones. ResultsWe identified 7 TRP channel genes in the PVN with known thermosensitive capabilities. Trpv4 was the most abundant of these and was easily identified at the single channel level using cell-attached patch-clamp electrophysiology on PVN neurones. We investigated the thermosensitivity of these Trpv4-like channels; open probability (Po) markedly decreased when temperature was decreased, mediated by a decrease in mean open dwell times. Our neuronal model predicted that PVN spontaneous action current frequency (ACf) would increase as temperature is decreased and in our electrophysiological experiments, we found that ACf from PVN neurones was significantly higher at lower temperatures. The broad-spectrum channel blocker, gadolinium (100 M), was used to block the warm-activated Ca2+-permeable Trpv4 and Trpv3 channels. In the presence of gadolinium (100 M), the temperature effect was largely retained. Using econazole (10 M), a blocker of Trpm2, we found there were significant increases in overall ACf and the temperature effect was inhibited. ConclusionOur work identified Trpv4 mRNA as an abundantly expressed thermosensitive TRP channel gene in the PVN and this ion channel contributes to the intrinsic thermosensitive properties of PVN neurones. At physiological temperatures (37{degrees}C), we observed relatively low ACf primarily due to the activity of Trpm2 channels, whereas at room temperature, where most of the previous characterisation of PVN neuronal activity has been performed, ACf is much higher, and appears to be predominately due to reduced Trpv4 activity. This work gives insight into the fundamental mechanisms by which the body decodes temperature signals and maintains homeostasis.

physiology↗

bioRxiv2021

A robust method for performing 1H-NMR lipidomics in embryonic zebrafish

The embryonic zebrafish is an ideal system for lipid analyses with relevance to many areas of bioscience research, including biomarkers and therapeutics. Research in this area has been hampered by difficulties in extracting, identifying and quantifying lipids. We employed 1H-NMR at 700MHz to profile lipids in developing zebrafish embryos. The optimal method for lipidomics in embryonic zebrafish incorporated rapid lipid extraction using chloroform and an environment without oxygen depletion. Pools of 10 embryos gave the most acceptable signal-to-noise ratio, and the inclusion of chorions in the sample had no significant effect on lipid abundances. Embryos, bisected into cranial (head and yolk sac) and caudal (tail) regions, were compared by principal component analysis and analysis of variance. The lipid spectra (including lipid annotation) are available in the public repository MetaboLights (MTBLS2396).

biochemistry↗

bioRxiv2021

Systemic application of the TRPV4 antagonist GSK2193874 induces tail vasodilation in a mouse model of thermoregulation

In humans the skin is a primary thermoregulatory organ, with vasodilation leading to rapid body cooling, whereas in Rodentia the tail performs an analogous function. Many thermodetection mechanisms are likely to be involved including transient receptor potential vanilloid-type 4 (TRPV4), a widely distributed ion channel with both mechanical and thermosensitive properties. Previous studies have shown that TRPV4 can act as a vasodilator by local action in blood vessels, and in this study, we investigated whether TRPV4 activity effects mus muscularis tail vascular tone and thermoregulation. We measured tail blood flow by pressure plethysmography in lightly sedated mus muscularis (CD1 strain) at a range of ambient temperatures, with and without intraperitoneal administration of the blood brain barrier crossing TRPV4 antagonist GSK2193874. We also measured heart rate and blood pressure with and without GSK2193874. As expected for a thermoregulatory organ, we found that tail blood flow increased with temperature. However, unexpectedly we found that the TRPV4 antagonist GSK2193874 increased tail blood flow at all temperatures, and we observed changes in heart rate variability. Since TRPV4 activation stimulates the relaxation of peripheral resistance arteries (vasodilation) that would increase tail blood flow, these data suggest that increases in tail blood flow resulting from the TRPV4 antagonist may arise from a site other than the blood vessels themselves, perhaps in central cardiovascular control centres such as the hypothalamus.

physiology↗

bioRxiv2020

DeepGANnel: Synthesis of fully annotated single molecule patch-clamp data using generative adversarial networks

Development of automated analysis tools for "single ion channel" recording is hampered by the lack of available training data. For machine learning based tools, very large training sets are necessary with sample-by-sample point labelled data (e.g., 1 sample point every 100microsecond). In an experimental context, such data are labelled with human supervision, and whilst this is feasible for simple experimental analysis, it is infeasible to generate the enormous datasets that would be necessary for a big data approach using hand crafting. In this work we aimed to develop methods to generate simulated ion channel data that is free from assumptions and prior knowledge of noise and underlying hidden Markov models. We successfully leverage generative adversarial networks (GANs) to build an end-to-end pipeline for generating an unlimited amount of labelled training data from a small annotated ion channel "seed" record, and this needs no prior knowledge of theoretical dynamical ion channel properties. Our method utilises 2D CNNs to maintain the synchronised temporal relationship between the raw and idealised record. We demonstrate the applicability of the method with 5 different data sources and show authenticity with t-SNE and UMAP projection comparisons between real and synthetic data. The model would be easily extendable to other time series data requiring parallel labelling, such as labelled ECG signals or raw nanopore sequencing data.

physiology↗

bioRxiv2020

Pro-inflammatory cytokines drive deregulation of potassium channel expression in primary synovial fibroblasts

The synovium secretes synovial fluid, but is also richly innervated with nociceptors and acts as a gateway between avascular joint tissues and the circulatory system. Resident fibroblast-like synoviocytes (FLS) calcium-activated potassium channels (KCa) change in activity in arthritis models and this correlates with FLS activation. ObjectiveTo investigate this activation in an in vitro model of inflammatory arthritis; 72hr treatment with cytokines TNF and IL1{beta}. MethodsFLS cells were isolated from rat synovial membranes. We analysed global changes in FLS mRNA by RNA-sequencing and then focused on FLS ion channels genes and corresponding FLS electrophysiological phenotype, finally modelling data with Ingenuity Pathway Analysis (IPA) and MATLAB. ResultsIPA showed significant activation of inflammatory, osteoarthritic and calcium signalling canonical pathways by cytokines, and we identified ~200 channel gene transcripts. The large KCa (BK) channel consists of the pore forming Kcnma1 together with {beta}-subunits. Following cytokine treatment, a significant increase in Kcnma1 RNA abundance was detected by qPCR and changes in several ion channels were detected by RNA-sequencing, including a loss of BK channel {beta}-subunit expression Kcnmb1/2 and increase in Kcnmb3. In electrophysiological experiments, there was a decrease in overall current density at 20mV without change in chord conductance at this potential. ConclusionTNF and IL1{beta} treatment of FLS in vitro recapitulated several common features of inflammatory arthritis at the transcriptomic level, including increase in Kcnma1 and Kcnmb3 gene expression.

bioinformatics↗

bioRxiv2020

Discriminant Analysis of Principle Component analyses of Physiological Data.

There are many situations in physiological and pharmacological analyses where multivariate data is collected. Frequently these are analysed with t-tests and multiple (Bonferroni) comparisons or ANOVA with post-hoc test. Increasingly, even with more powerful computers many variables and it seems that feature reduction would be a useful approach. The most commonly used method is principle component analyses, but in this report we compare this to a technique developed for genetic analyses, discriminant analysis of principle component (DAPC) analyses. A simple to use and well-maintained library exists for DAPC analyses, Adegenet2, and using this we find that DAPC detects differences between synthetic physiological datasets with significantly greater accuracy than traditional PCA.

physiology↗

bioRxiv2019

Deep-Channel: A Deep Convolution and Recurrent Neural Network for Detection of Single Molecule Events

Single-molecule research such as patch-clamp recording delivers unique biological insight by capturing the movement of individual proteins in real time, unobscured by whole-cell ensemble averaging. The critical first step in analysis is event detection, so called "idealisation", where noisy raw data are turned into discrete records of protein movement. To date there have been practical limitations in patch-clamp data idealisation; high quality idealisation is typically laborious and becomes infeasible and subjective with complex biological data containing many distinct native single ion channel proteins gating simultaneously. Here we show a deep learning model based on convolutional neural networks and long short-term memory architecture can automatically idealise complex single molecule activity more accurately and faster than traditional methods. There are no parameters to set; baseline, channel amplitude or numbers of channels for example. We believe this approach could revolutionise the unsupervised automatic detection of single-molecule transition events in the future.

physiology↗