Biology subjects

Barton, K.

Publications and source records attributed to Barton, K..

14 recordsLinked to original sources

bioRxiv2026

Transcriptionally Active HIV Reservoirs Enriched for Interferon-Inducible APOBEC3-Related Mutational Signatures Associate with Reduced Neuroaxonal Integrity

Despite sustained viral suppression with effective antiretroviral therapy (ART), impaired neuroaxonal integrity persist in a subset of people with HIV-1 (PWH). We investigated whether interferon (IFN)-inducible APOBEC3-associated mutational signatures, reflected by premature stop codons (PSCs), and reservoir-associated drug resistance mutations (RS-DRMs) within transcriptionally active HIV-1 reservoirs influence neuroaxonal integrity in fully virally suppressed individuals. Peripheral CD4 T cells from individuals with undetectable plasma HIV-1 RNA (n = 27) were analyzed for long HIV-1 gag/pol transcripts (>4.2 kb), and frontal white matter (FWM) neuroaxonal integrity was assessed using proton magnetic resonance spectroscopy ({superscript 1}H-MRS) measurement of N-acetylaspartate (NAA). Short HIV-1 RNA transcripts, reflecting promoter-associated transcriptional activity, were detected in all participants and were associated with reduced NAA levels in FWM, consistent with a relationship between ongoing reservoir activity and impaired neuroaxonal integrity despite virological suppression. Long gag/pol transcripts (>4.2 kb) were detected in 78% of participants and exhibited marked heterogeneity in APOBEC3-associated PSC burden. PSC-containing long transcripts were associated with higher NAA, whereas long transcripts lacking such inactivating mutations were associated with reduced NAA, suggesting that APOBEC3-associated restriction of viral translational competence may contribute to differences in the downstream neurobiological effects of transcriptionally active reservoir states. RA-DRMs were detected in 43% of participants, including triple-class resistance consistent with archived treatment exposure over more than a decade. Matching gag/pol sequences from reactivated virions confirmed latent reservoir origin; however, RS-DRMs showed no independent association with neuroaxonal outcomes. Across systemic inflammatory markers, vascular risk factors, cerebrospinal fluid immune activation measures, and clinical neurocognitive outcomes (including HAND status), no consistent associations with NAA were observed. Overall, reduced neuroaxonal integrity in the FWM was associated with the interplay between short HIV-1 RNA transcriptional activity and APOBEC3-edited translational states of long HIV-1 RNA transcripts within peripheral reservoirs, suggesting that interferon-inducible APOBEC3-associated mutational signatures may reflect biologically distinct reservoir states that correspond to neurobiological effects during suppressive antiretroviral therapy. Graphical AbstractInterferon-Inducible APOBEC3-Associated Premature Stop Codon Signatures in HIV-1 Reservoirs and Preservation of Neuroaxonal Integrity O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/729658v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@19c98d8org.highwire.dtl.DTLVardef@1f6c627org.highwire.dtl.DTLVardef@4b33a7org.highwire.dtl.DTLVardef@12c4a54_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIShort HIV-1 RNA transcription within peripheral CD4 T-cell reservoirs was associated with reduced frontal white matter N-acetylaspartate during suppressive ART. C_LIO_LILong HIV-1 gag/pol RNA transcripts exhibited marked heterogeneity in interferon-inducible APOBEC3-associated G-to-A hypermutation, including premature stop codon signatures. C_LIO_LIArchived reservoir-associated drug resistance mutations were identified within transcriptionally active long HIV-1 reservoir-derived RNA during suppressive ART. C_LIO_LIReduced neuroaxonal integrity was associated with the interplay between short HIV-1 transcriptional activity and interferon-inducible APOBEC3-associated editing of long HIV-1 transcripts with reduced predicted translational competence. C_LI

molecular biology↗

bioRxiv2025

Tissue resident memory T cells populate the human uveal tract

The current concept is that the eye is an immune privileged site endowed with innate immune regulatory networks to maintain organ function. We now have evidence that resident T cells occupy intraocular tissues. In immune-mediated inflammatory diseases, such as psoriasis and rheumatoid arthritis, tissue resident T cells trigger disease flares in the skin and joints. This suggests resident T cells in the uvea may have similar functions in non-infectious immune-mediated uveitis, a collective term for autoinflammatory and autoimmune diseases of the uveal tract causing intraocular inflammation. Here, we demonstrate by spectral cytometry and immunofluorescence imaging that non-inflamed uveal tissue contains multiple T cell subtypes including CD8+ CD103+ tissue resident memory T (TRM) cells. Using single cell RNA & T cell receptor (TCR) sequencing to profile aqueous humour cells from donors with acute, active uveitis, we identify clonally expanded T cells which are enriched for TRM -associated genes. We further show that in donors with active uveitis, CD8+ CD103+ T cells persist within tissue in the uveal tract. Using bulk RNA sequencing and weighted gene co-expression network analysis (WGCNA) we show that quiescent iris tissue from donors with a history of uveitis are enriched for genes associated with T cell activation and antigen presentation. Finally, we demonstrate that TRM cells persist in the anterior uvea in mice following resolution of experimental autoimmune uveoretinitis (EAU). Our results show that the human eye contains T cells both in health and during active inflammation. Our findings challenge the dogma that the eye is devoid of lymphocytes and supports the concept of resident T cell involvement in the pathogenesis of non-infectious immune-mediated uveitis and as promising targets for therapy. One Sentence SummaryT cells infiltrate aqueous humour during intraocular inflammation and have capacity to migrate into uveal tissue where they remain long-lived.

immunology↗

bioRxiv2025

The non-steroidal mineralocorticoid receptor (MR) antagonist (FINERENONE) reverses Western diet-induced kidney disease by enhancing mitochondrial metabolism and decreasing lipid accumulation and inflammation

Mineralocorticoid receptor (MR) overactivation plays a crucial role in the pathogenesis of chronic kidney disease, as well as several cardiovascular and arterial diseases. Current studies determined the mechanisms of the beneficial kidney effects of the non-steroidal MR antagonist Finerenone (FN) in a mouse model of western diet-induced obesity and insulin resistance. 10-week-old male C57BL/6J mice were fed a low fat (LF) or a western diet (WD) for 12 weeks followed by treatment with either vehicle or finerenone (FN) for another 14 weeks (intervention studies) until they were 36 weeks old. Finerenone treatment prevented a) the increased albuminuria and kidney injury molecule 1 (KIM1), b) the expanded extracellular mesangial matrix, and podocyte injury, c) fibronectin, collagen IV, CD45 and CD68 immunostaining, d) glomerular basement membrane disruption, podocyte foot process loss, and mitochondrial structural abnormalities, e) the pro-inflammatory cytokines (MCP1), innate immunity pathways (TLR2, STING, STAT3), and fibrosis markers fibronectin, TGF{beta} and Pai1, and f) the increased kidney cholesterol levels. There was also reduced expression of nuclear receptor ERR{gamma} without changes in ERR in WD-fed mice whereas both ERR and ERR{gamma} expression levels increased after Finerenone treatment. NADH lifetime analysis showed decreased bound NADH, compatible with decreased mitochondrial OXPHOS in the kidneys of WD-fed mice compared to controls, which was prevented by finerenone treatment. In conclusion, Finerenone treatment exhibits a renal protective role and prevents the progression of kidney disease by regulating mitochondrial function, most likely via ERR{gamma}, and reducing lipid accumulation and inflammation.

pharmacology and toxicology↗

bioRxiv2024

Repeat-rich regions cause false positive detection of NUMTs - a case study in amphibians using an improved cane toad reference genome

Mitochondrial DNA (mtDNA) has been widely used in genetics research for decades. Contamination from nuclear DNA of mitochondrial origin (NUMT) can confound studies of phylogenetic relationships and mtDNA heteroplasmy. Homology searches with mtDNA are widely used to detect NUMTs in the nuclear genome. Nevertheless, false positive detection of NUMTs is common when handling repeat-rich sequences, whilst fragmented genomes might result in missing true NUMTs. In this study, we investigated different NUMT detection methods and how the quality of the genome assembly affects them. We presented an improved nuclear genome assembly (aRhiMar1.3) of the invasive cane toad (Rhinella marina) with additional long-read Nanopore and 10x linked-read sequencing. The final assembly was 3.47 Gb in length with 91.3% of tetrapod universal single-copy orthologs (n=5,310), indicating the gene-containing regions were well assembled. We used three complementary methods (NUMTFinder, dinumt and PALMER) to study the NUMT landscape of the cane toad genome. All three methods yielded consistent results, showing very few NUMTs in the cane toad genome. Furthermore, we expanded NUMT detection analyses to other amphibians and confirmed a weak relationship between genome size and the number of NUMTs present in the nuclear genome. Amphibians are repeat-rich, and we show that the number of NUMTs found in highly repetitive genomes is prone to inflation when using homology-based detection without filters. Together, this study provides an exemplar of how to robustly identify NUMTs in complex genomes when confounding effects on mtDNA analyses are a concern. SignificanceThis study uses an updated cane toad nuclear genome assembly and multiple NUMT detection methods to confirm a lack of NUMTs that might confound the use of mtDNA as a population genetic marker in the cane toad. We provide an exemplar study for NUMT detection accounting for genome assembly quality and composition, and highlight the risks of using BLASTN-based approaches in highly repetitive nuclear genomes.

genomics↗

bioRxiv2023

Understanding the Influence of Context on Real-World Walking Energetics

Speeds that minimize energetic cost during steady-state walking have been observed during lab-based investigations of walking biomechanics and energetics. However, in real-world scenarios, humans walk in various contexts that elicit different walking strategies, which may not always prioritize minimizing energetic cost. To investigate whether individuals tend to select energetically optimal speeds in real-world situations and how contextual factors influence gait, we conducted a study combining data from lab and real-world experiments. Walking kinematics and context were measured during daily life over a week (N = 17) using wearable sensors and a mobile phone. To determine context, we utilized self-reported activity logs, GPS data, and follow-up exit interviews. Additionally, we estimated energetic cost using respirometry over a range of gait speeds in the lab. Cost of transport during these trials was used to identify an energetically optimal walking speed range for each participant. The proportion of real world steady-state stride speeds within this range was identified for all data and for each context. We found that participants walked significantly faster than what was energetically optimal, and the proportion of steady-state strides within the energetically optimal speed range was dependent on the context. On average, 45.6% of all steady-state stride speeds were energetically optimal across all contexts for all participants. These results suggest that while energetic cost is a factor considered by humans when selecting gait speed in daily life, it is not the sole determining factor. Context contributes to the observed variability in movement parameters both within and between individuals.

animal behavior and cognition↗

bioRxiv2022

Dynamics and Energetics of Bottlenose Dolphins (Tursiops truncatus) Fluke-and-Glide Gait

Intermittent locomotion composed of periods of active flapping/stroking followed by inactive gliding has been observed with species that inhabit both aerial and marine environments. However, studies on the energetic benefits of a fluke-and-glide (FG) gait during horizontal locomotion are limited for dolphins. This work presents a physics-based model of FG gait and analysis of the associated costs of transport of bottlenose dolphins (Tursiops truncatus). New estimates of gliding drag coefficients for the model were estimated experimentally from free-swimming bottlenose dolphins. The data-driven approach used kinematic measurement from 84 hours of biologging tag data collected from 3 animals to estimate the coefficients. A set of 532 qualified gliding events were automatically extracted for gliding drag coefficient estimation, and an additional 783 FG bouts were parameterized and used to inform the model-based dynamic analysis. Experimental results indicate that FG gait was preferred at speeds around 2.2 - 2.7 m/s. Observed FG bouts had an average duty factor of 0.45 and gliding duration of 5 sec. The average associated metabolic cost of transport (COT) and mechanical cost of transport (MECOT) of FG gait are 2.53 and 0.35 J {middle dot} m-1 {middle dot} kg-1 at the preferred speeds. This corresponded to an 18.9% and 27.1% reduction in cost when compared to modeled continuous fluking gait at the same reference speed. Average thrust was positively correlated with fluking frequency and amplitude as animals accelerated during the FG bouts. While fluking frequency and amplitude were negatively correlated for a given thrust range. These results support the supposition that FG gait enhances the horizontal swimming efficiency of bottlenose dolphins and provides new dynamical insights into the gait of these animals.

animal behavior and cognition↗

bioRxiv2021

Pose-gait analysis for cetaceans with biologging tags

Biologging tags are a key enabling tool for investigating cetacean behavior and locomotion in their natural habitat. Identifying and then parameterizing gait from movement sensor data is critical for these investigations. But how best to characterize gait from tag data remains an open question. Further, the location and orientation of the tag on an animal in the field are variable and can change multiple times during deployment. As a result, the relative orientation of the tag with respect to (wrt) the animal must be determined before a wide variety of further analyses. Currently, custom scripts that involve specific manual heuristics methods tend to be used in the literature. These methods require a level of knowledge and experience that can affect the reliability and repeatability of the analysis. The authors of this work argue that an animals gait is composed of a sequence of body poses observed by the tag, demonstrating a specific spatial pattern in the data that can be utilized for different purposes. This work presents an automated data processing pipeline (and software) that takes advantage of the common characteristics of pose and gait of the animal to 1) Identify time instances associated with occurrences of relative motion between the tag and animal; 2) Identify the relative orientation of tag wrt the animals body for a given data segment; and 3) Extract gait parameters that are invariant to pose and tag orientation. The authors included biologging tag data from bottlenose dolphins, humpback whales, and beluga whales in this work to validate and demonstrate the approach. Results show that the average relative orientation error of the tag wrt the dolphins body after processing was within 11 degrees in roll, pitch, and yaw directions. The average precision and recall for identifying relative tag motion were 0.87 and 0.89, respectively. Examples of the resulting pose and gait analysis demonstrate the potential of this approach to enhance studies that use tag data to investigate movement and behavior. MATLAB source code and data presented in the paper were made available to the public (https://github.com/ding-z/cetacean-pose-gait-analysis.git), with suggestions related to tag data processing practices provided in this paper. The proposed analysis approach will facilitate the use of biologging tags to study cetacean locomotion and behavior.

animal behavior and cognition↗

bioRxiv2021

3-dimensional arenas for the assessment of C. elegans behavior

C. elegans nematodes are a well-established model organism in numerous fields of experimental biology. In nature, C. elegans live in a rich 3-dimensional environment. However, their behavior has been assessed almost exclusively on the open, flat surface of NGM (Nematode Growth Medium) plates, the golden standard for C. elegans culture in the lab. We present two methods to build 3-dimensional behavioral arenas for C. elegans, by casting, and by directly 3D printing NGM hydrogel. The latter is achieved by using a highly customized fused deposition modeling (FDM) 3D-printer, modified to employ NGM hydrogel as ink. The result is the advancement of 3-dimensional complexity of behavioral assays. To demonstrate the potential of our method, we use the 3D-printed arenas to assess C. elegans physical barriers crossing. C. elegans decision to cross physical obstacles is affected by aging, physiological status (i.e., starvation), and prior experience. The 3D-printed structures can be used to spatially confine C. elegans behaviors, i.e., egg laying. We consider these findings a decisive step toward characterizing C. elegans 3-dimensional behavior, an area long overlooked due to technical constrains. We envision our method of 3D-printing NGM arenas as a powerful tool in behavioral neurogenetics, neuroethology, and invertebrate model organisms neurobiology.

bioengineering↗

bioRxiv2021

Vision-based monitoring and measurement of bottlenose dolphins' daily habitat use and kinematics

This research presents a framework to enable computer-automated observation and monitoring of bottlenose dolphins (Tursiops truncatus) in a professionally managed environment. Results from this work provide insight into the dolphins movement patterns, kinematic diversity, and how changes in the environment affect their dynamics. Fixed overhead cameras were used to collect [~]100 hours of observations, recorded over multiple days including time both during and outside of formal training sessions. Animal locations were estimated using convolutional neural network (CNN) object detectors and Kalman filter post-processing. The resulting animal tracks were used to quantify habitat use and animal dynamics. Additionally, Kolmogorov-Smirnov analyses of the swimming kinematics were used for high-level behavioral mode classification. The detectors achieved a minimum Average Precision of 0.76. Performing detections and post-processing yielded 1.24x107 estimated dolphin locations. Animal kinematic diversity was found to be lowest in the morning and peaked immediately before noon. Regions of the habitat displaying the highest activity levels correlated to locations associated with animal care specialists, conspecifics, or enrichment. The work presented here demonstrates that CNN object detection is not only viable for large-scale marine mammal tracking, it also enables automated analyses of dynamics that provide new insight into animal movement and behavior.

animal behavior and cognition↗

bioRxiv2020

DNA methylation is required to maintain DNA replication timing precision and 3D genome integrity

DNA replication timing and three-dimensional (3D) genome organisation occur across large domains associated with distinct epigenome patterns to functionally compartmentalise genome regulation. However, it is still unclear if alternations in the epigenome, in particular cancer-related DNA hypomethylation, can directly result in alterations to cancer higher order genome architecture. Here, we use Hi-C and single cell Repli-Seq, in the colorectal cancer DNMT1 and DNMT3B DNA methyltransferases double knockout model, to determine the impact of DNA hypomethylation on replication timing and 3D genome organisation. First, we find that the hypomethylated cells show a striking loss of replication timing precision with gain of cell-to-cell replication timing heterogeneity and loss of 3D genome compartmentalisation. Second, hypomethylated regions that undergo a large change in replication timing also show loss of allelic replication timing, including at cancer-related genes. Finally, we observe the formation of broad ectopic H3K4me3-H3K9me3 domains across hypomethylated regions where late replication is maintained, that potentially prevent aberrant transcription and loss of genome organisation after DNA demethylation. Together, our results highlight a previously underappreciated role for DNA methylation in maintenance of 3D genome architecture.

molecular biology↗

bioRxiv2020

sangeranalyseR: simple and interactive analysis of Sanger sequencing data in R

SummarysangeranalyseR is an interactive R/Bioconductor package and two associated Shiny applications designed for analysing Sanger sequencing from data from the ABIF file format in R. It allows users to go from loading reads to saving aligned contigs in a few lines of R code. sangeranalyseR provides a wide range of options for a number of commonly-performed actions including read trimming, detecting secondary peaks, viewing chromatograms, and detecting indels using a reference sequence. All parameters can be adjusted interactively either in R or in the associated Shiny applications. sangeranalyseR comes with extensive online documentation, and outputs detailed interactive HTML reports. Availability and implementationsangeranalyseR is implemented in R and released under an MIT license. It is available for all platforms on Bioconductor (https://bioconductor.org/packages/sangeranalyseR) and on Github (https://github.com/roblanf/sangeranalyseR). Contactkuanhao.chao@gmail.com Supplementary informationDocumentation at https://sangeranalyser.readthedocs.io/.

bioinformatics↗

bioRxiv2019

Barcoding and demultiplexing Oxford Nanopore native RNA sequencing reads with deep residual learning

Nanopore sequencing has enabled sequencing of native RNA molecules without conversion to cDNA, thus opening the gates to a new era for the unbiased study of RNA biology. However, a formal barcoding protocol for direct sequencing of native RNA molecules is currently lacking, limiting the efficient processing of multiple samples in the same flowcell. A major limitation for the development of barcoding protocols for direct RNA sequencing is the error rate introduced during the base-calling process, especially towards the 5 and 3 ends of reads, which complicates sequence-based barcode demultiplexing. Here, we propose a novel strategy to barcode and demultiplex direct RNA sequencing nanopore data, which does not rely on base-calling or additional library preparation steps. Specifically, custom DNA oligonucleotides are ligated to RNA transcripts during library preparation. Then, raw current signal corresponding to the DNA barcode is extracted and transformed into an array of pixels, which is used to determine the underlying barcode using a deep convolutional neural network classifier. Our method, DeePlexiCon, implements a 20-layer residual neural network model that can demultiplex 93% of the reads with 95.1% specificity, or 60% of reads with 99.9% specificity. The availability of an efficient and simple barcoding strategy for native RNA sequencing will enhance the use of direct RNA sequencing by making it more cost-effective to the entire community. Moreover, it will facilitate the applicability of direct RNA sequencing to samples where the RNA amounts are limited, such as patient-derived samples.

genomics↗

bioRxiv2019

Targeted, High-Resolution RNA Sequencing Of Non-Coding Genomic Regions Associated With Neuropsychiatric Functions

The human brain is one of the last frontiers of biomedical research. Genome-wide association studies (GWAS) have succeeded in identifying thousands of haplotype blocks associated with a range of neuropsychiatric traits, including disorders such as schizophrenia, Alzheimers and Parkinsons disease. However, the majority of single nucleotide polymorphisms (SNPs) that mark these haplotype blocks fall within non-coding regions of the genome, hindering their functional validation. While some of these GWAS loci may contain cis-acting regulatory DNA elements such as enhancers, we hypothesized that many are also transcribed into non-coding RNAs that are missing from publicly available transcriptome annotations. Here, we use targeted RNA capture ( RNA CaptureSeq) in combination with nanopore long-read cDNA sequencing to transcriptionally profile 1,023 haplotype blocks across the genome containing non-coding GWAS SNPs associated with neuropsychiatric traits, using post-mortem human brain tissue from three neurologically healthy donors. We find that the majority (62%) of targeted haplotype blocks, including 13% of intergenic blocks, are transcribed into novel, multi-exonic RNAs, most of which are not yet recorded in GENCODE annotations. We validated our findings with short-read RNA-seq, providing orthogonal confirmation of novel splice junctions and enabling a quantitative assessment of the long-read assemblies. Many novel transcripts are supported by independent evidence of transcription including cap analysis of gene expression (CAGE) data and epigenetic marks, and some show signs of potential functional roles. We present these transcriptomes as a preliminary atlas of non-coding transcription in human brain that can be used to connect neurological phenotypes with gene expression.

genomics↗

bioRxiv2018

High-throughput targeted long-read single cell sequencing reveals the clonal and transcriptional landscape of lymphocytes

High-throughput single-cell RNA-Sequencing is a powerful technique for gene expression profiling of complex and heterogeneous cellular populations such as the immune system. However, these methods only provide short-read sequence from one end of a cDNA template, making them poorly suited to the investigation of gene-regulatory events such as mRNA splicing, adaptive immune responses or somatic genome evolution. To address this challenge, we have developed a method that combines targeted long-read sequencing with short-read based transcriptome profiling of barcoded single cell libraries generated by droplet-based partitioning. We use Repertoire And Gene Expression sequencing (RAGE-seq) to accurately characterize full-length T cell (TCR) and B cell (BCR) receptor sequences and transcriptional profiles of more than 7,138 lymphocytes sampled from the primary tumour and draining lymph node of a breast cancer patient. With this method we show that somatic mutation, alternate splicing and clonal evolution of T and B lymphocytes can be tracked across these tissue compartments. Our results demonstrate that RAGE-Seq is an accessible and cost-effective method for high-throughput deep single cell profiling, applicable to a wide range of biological challenges.

genomics↗