Biology subjects

Byrne, A.

Publications and source records attributed to Byrne, A..

At least 19 recordsLinked to original sources

bioRxiv2026

A network-based framework for detecting communities of similar neural spike trains

Recent advances in large-scale electrophysiological recording technologies now allow simultaneous measurement of spike trains from ensembles of neurons. A central challenge in mathematical neuroscience is therefore to identify functional assemblies and their collective organisation directly from this data. The goal of this work is to devise a method to infer the collective organisation of the neurons from their spiking activity. We construct weighted functional networks from neural spike trains using the van Rossum distance to quantify pairwise similarity. The functional network captures similarities in neuron firing patterns and provides a representation of their collective organisation. We hypothesise that similar neuronal assemblies will appear as clustered communities in the network, and employ the Louvain algorithm to detect such assemblies. We validate our approach using synthetic spike train data and simulated data from a stochastic block model of Leaky Integrate and Fire neurons subjected to external Poisson drives, where the ground truth is known. Finally, we apply our approach to large-scale recordings from the Allen Institute Visual Coding: Neuropixels dataset. We find that our methodology works well as long as a sufficient amount of data is available and the temporal structure is strong relative to the noise.

neuroscience↗

bioRxiv2026

A Stochastic Neural Mass Model for Cortical Beta Bursts in Parkinsons Disease

Beta-band (13-30 Hz) oscillations are increasingly understood to occur as transient "bursts" rather than sustained rhythms, with altered burst dynamics, specifically increased duration and power alongside reduced burst rates, in patients with Parkinsons disease (PD). In this study, we utilise resting state magnetoencephalography (MEG) data from healthy adults to quantify the temporal fluctuations in the beta-band, and examine the distributions of burst statistics. We then fit a stochastic next-generation neural mass model to these empirical statistics using a Genetic Algorithm. Systematic parameter sweeps reveal that reducing background drive to excitatory and inhibitory neuronal populations reproduces the altered burst statistics observed in PD. Crucially, we show that strengthening synaptic coupling can counteract these deficits and restore healthy bursting dynamics. Together, this work establishes a computational framework linking cellular-level mechanisms to macroscale burst statistics, and highlights potential targets for therapeutic neuromodulation in movement disorders. Author summaryBrain activity is comprised of rhythmic electrical patterns called "brain waves." Traditionally, these waves were viewed as smooth and continuous, but recent evidence reveals that they actually occur in brief, intense bursts. In conditions such as Parkinsons disease, these bursts become altered--lasting longer, growing stronger, and occurring less frequently. In this study, we developed a mathematical model of brain tissue to understand what drives these burst patterns. Using real brain scans from healthy human volunteers, we tuned our model with an optimisation algorithm until its simulated bursts closely matched real human brain activity. We then systematically varied the models settings to investigate how abnormal bursting arises in disease. We discovered that reducing the background signals to the brain cells reproduces the burst alterations seen in Parkinsons disease. Importantly, our simulations showed that strengthening the connections between brain cells can counteract this deficit, restoring healthy burst patterns. By connecting microscopic cell properties to whole-brain rhythms, our work offers new insights into how movement disorders disrupt brain networks and highlights potential cellular targets to guide future brain stimulation therapies or medications.

biophysics↗

bioRxiv2026

Direct RNA Sequencing reveals epitranscriptomic regulation of brain cells and Alzheimer's Disease pathology

Alternative mRNA splicing and post-transcriptional RNA modification are key mechanisms that regulate transcript function; however, their role in neuronal activity and neurodegenerative disease remains poorly defined. In this study, we evaluated two nanopore-based long-read sequencing (LR-seq) formats: cDNA-PCR sequencing (CPS) and direct RNA sequencing (DRS). We then applied DRS to profile both full-length isoforms and RNA modifications in major brain cell types derived from induced pluripotent stem cells (iPSCs) and post-mortem Alzheimers disease (AD) brains. Relative to CPS, DRS achieved higher accuracy and sensitivity for transcript quantification, de novo transcript model construction, and open reading frame (ORF) annotation across neuropathological gene sets. Focusing on iPSC-derived neurons, we built a multi-omic atlas to connect transcriptional output with translational engagement and protein abundance, by integrating DRS-based mRNA abundance, N6-methyladenosine (m6A) status and poly(A) tail length with ribosome profiling (Ribo-seq) and mass spectrometry (MS). The combination of DRS and Ribo-seq data demonstrated synergism in predicting protein abundance. This analysis also uncovered a significant inverse relationship between m6A modification and mRNA abundance, which was dependent on the engagement of the ribosomal A-site. Lastly, we applied DRS to the epitranscriptomic analysis of AD brain samples, demonstrating that m6A profiles can be used to distinguish early-versus late-stage disease.

neuroscience↗

bioRxiv2026

Emergence and antigenic characterisation of influenza A(H3N2) viruses with hemagglutinin substitutions N158K and K189R during the 2024/25 influenza season

BackgroundSeasonal human influenza viruses can escape from antibody-mediated neutralization when amino acid changes occur in the hemagglutinin protein. Routine surveillance identified circulation of an A(H3N2) virus variant in the Netherlands with amino acid substitutions at hemagglutinin positions 158 and 189. These amino acid positions were previously responsible for antigenic change of influenza A(H3N2) viruses and potentially lead to escape of this variant from vaccine-mediated immunity. AimTo characterize the emergence and antigenic properties of N158K and K189R double substitution virus variants. MethodsWe analyzed the geographical and temporal dynamics of the double-substitution variant using a phylogeographic approach and used hemagglutination inhibition assays and antigenic cartography methods to map its antigenic properties. ResultsA(H3N2) viruses carrying K189R were first detected in Guatemala in June 2024, before subsequently gaining the N158K substitution, which was intially detected in Colombia in November 2024, followed by detection in the Netherlands in December 2024. However, detections within Europe remained almost entirely confined to the Netherlands. The proportion of viruses carrying the N158K and K189R substitutions increased to 16% - 24% per collection week of sequenced Dutch viruses during the peak of the epidemic of the 2024-2025 respiratory season. Antigenic characterization of viruses with N158K and K189R substitutions indicated that these are antigenically distinct from the A(H3N2) components of 2025-2026 Northern Hemisphere vaccines, showing 8-192-fold reduction in hemagglutination inhibition titers with antisera against the vaccine strain compared to antisera against the homologous virus. ConclusionsInfluenza A(H3N2) viruses with N158K and K189R escaped recognition by antibodies raised against the 2024-2025 and 2025/2026 Northern Hemipshere vaccine strains in hemagglutination inhibition assays. These variants circulated widely in the Netherlands during the 2024-2025 influenza season, raising concerns about reduced vaccine-mediated protection if such variants would spread more broadly during 2025-2026 Northern Hemipshere season.

microbiology↗

bioRxiv2025

Maternal IL-17A administration fails to disrupt fetal cortical lamination in the absence of maternal microbes

Maternal inflammation during pregnancy can disrupt fetal neurodevelopment and contribute to the pathogenesis of neurodevelopmental disorders. Interleukin-17A (IL-17A) has emerged as a potential mediator linking maternal immune activation (MIA) to neurodevelopmental abnormalities in offspring. Production of this cytokine is in-part regulated by the maternal gastrointestinal microbiome. However, it remains unclear whether IL-17A alone is sufficient to induce offspring brain abnormalities independent of maternal microbial signals. This study tests the potential for IL-17A to mediate fetal brain cortical architecture through administration of recombinant (r)IL-17A to pregnant germ-free (GF) dams. Pregnant GF mice received daily intraperitoneal injections of rIL-17A for six days, covering the mid- to latter half of the gestational period. Placental tissue was processed for histopathological evaluation, and cortical lamination was examined in the fetal brain using gold-standard immunohistochemical approaches. Spatial Light Interference Microscopy (SLIM), a novel label-free imaging technique, was employed to further quantify cortical architecture. This is the first report of SLIM imaging performed in the mouse embryonic brain. Overall, administration of rIL-17A to pregnant GF dams during mid-to-late gestation resulted in normal placental morphology and fetal cortical lamination patterns, suggesting that IL-17A alone is insufficient for altering cortical neurodevelopment, at least at this gestational timepoint. These findings highlight the importance of accounting for the maternal microbiome when interpreting the impacts of prenatal inflammation on brain development in utero.

neuroscience↗

bioRxiv2025

Unraveling the Dual Immunomodulatory and Immunogenic Roles of the Central Conserved Cysteine-Rich Region in Respiratory Syncytial Virus G Protein

Respiratory syncytial virus (RSV) causes severe respiratory disease in infants and high-risk adults, in part by subverting host immunity. The RSV G glycoproteins central conserved cysteine-rich domain (CCD) contains a CX3C motif implicated in immune modulation, but the relationship between CCD redox state, structure and function is unresolved. We recombinantly expressed a CCD peptide (Gpep, residues 149-196) and combined structural and biophysical characterizations with cellular immunology and human serology to define how redox-dependent conformations govern immunogenicity and immunomodulation. Reduced Gpep is compact and rapidly folds via a dominant intermediate into an oxidized, extended monomer; at higher concentrations intermolecular disulfide isomerization produces covalent oligomers. Functionally, monomeric Gpep potently suppresses innate and adaptive activation inhibiting LPS- or UV-inactivated RSV-induced maturation of mouse bone marrow-derived dendritic cells, reducing antigen-specific CD4+ T cell proliferation and IFN-{gamma} production, and attenuating multiple human neutrophil responses (chemotaxis, CD11b upregulation, ROS, MPO release and NET formation), without cytotoxicity. Oligomerized Gpep lacks these suppressive activities. To link molecular mechanism and human exposure, analysis of sera from an ambulatory pediatric cohort (0-72 months) showed a progressive transient increase in the anti-F/anti-G IgG ratio with repeated early RSV exposures, maturating into a functional 2 to 3 ratio. This serologic shift is consistent with previously reported enrichment of F-directed neutralizing immunity. We propose a redox-dependent immune-evasion model in which soluble, monomeric G mediates transient immunosuppression that is removed by disulfide-driven oligomerization, which may occur in membrane-bound G. This may impact therapeutic strategies that commonly favor F-focused responses. ImportanceRespiratory syncytial virus (RSV) remains a leading cause of severe respiratory disease in young children and high-risk adults. This study identifies a chemical switch in a small conserved region of the RSV attachment protein that changes its shape and immune activity: when the region is present as a soluble, single chain, it transiently suppresses key innate and adaptive immune cells, but this activity is lost upon disulfide-mediated oligomerization. We also show that repetitive RSV exposures in early life bias the antibody response, initially boosting antibody responses toward the Fusion protein, rather than this conserved central region. Together, these results may uncover a mechanism by which RSV shapes the host immune response explaining the features of antibody development in children. Understanding this redox-dependent balance between immune evasion and antigenicity will inform safer vaccine and antibody strategies against RSV.

immunology↗

bioRxiv2025

Inhibiting Clarinet/CLA-1 restores function to injured motor neurons

To regain function, injured axons need to both regenerate and reform synapses with appropriate postsynaptic cells. We found that inhibiting the scaffolding protein Clarinet/CLA-1, a C. elegans ortholog of Piccolo and Fife, robustly improves axon regeneration. Despite the importance of CLA-1 during synapse development, disrupting the medium isoform of CLA-1 increases the number of axons that regenerate to the neuromuscular junction without significantly influencing synapse reformation. Consequently, the axons that do regenerate are capable of regaining function. Mechanistically, the enhanced axon regeneration observed in cla-1(-) mutants depends on the function of PTRN-1, a microtubule minus-end binding protein. Our data supports a model where loss of CLA-1 promotes PTRN-1 function, which speeds trafficking of injury-related cargo to and from the lesion, thus improving repair. Together, our results reveal a highly conserved synaptic active zone protein that can be manipulated to enhance axon regeneration without sacrificing the function of the repaired axons. HighlightsO_LIClarinet/CLA-1 is a robust inhibitor of C. elegans GABAergic axon regeneration C_LIO_LILoss of CLA-1 function improves both axon regeneration and functional repair C_LIO_LICLA-1 isoforms differentially regulate axon regeneration and synaptic transmission C_LIO_LICLA-1 regulates axon regeneration via microtubule minus-end protein PTRN-1/Patronin C_LIO_LICLA-1 knockdown improves cargo trafficking during the early injury response C_LI

neuroscience↗

bioRxiv2024

Inflammation-associated monocytes express ACOD1 to curtail inflammatory behaviour in IBD and experimental colitis

Monocytes are essential for replenishing homeostatic macrophages in the intestine. However, they also accumulate in significant numbers when intestinal homeostasis is disrupted in diseases, such as inflammatory bowel disease (IBD). The molecular pathways governing monocyte behaviour across these different contexts remain poorly understood. Here, we profile the monocyte / macrophage compartment in human IBD using single-cell RNA sequencing and identify a discrete population of monocytes that accumulate in IBD, which we term inflammation associated monocytes (IAMs). These can be identified by the expression of CD319, CD274 and CCRL2, and demonstrate increased expression of IBD susceptibility genes. By performing cross-species analysis, we show an analogous population of IAMs accumulate during chemically induced colitis in mice. Using transgenic fate mapping approaches, we show these cells likely derive from a discrete precursor in the bone marrow (BM) and are locally imprinted to produce heightened IL-1{beta} and TNF in mouse and humans. Importantly, we show that co-incident with a hyper-inflammatory phenotype, these same cells uniquely and specifically express aconitate decarboxylase (ACOD1) in response to local Toll-like receptor (TLR) and interferon (IFN) receptor signalling, to limit unrestricted cytokine production. Thus, the intestinal environment after injury instructs both inflammation and recovery specifically within a transitioning population of monocytes that are absent in health.

immunology↗

bioRxiv2024

Fibroblastic FLT3L supports lymph node dendritic cells in the interfollicular niche

Dendritic cell (DC) homeostasis is maintained in secondary lymphoid organs (SLOs) by Fms-like tyrosine kinase 3 ligand (FLT3L). The specific niche providing this DC growth factor within human and mouse SLOs is unclear. Here, we show that Gremlin1 (Grem1)-expressing lymph node fibroblastic reticular cells (FRCs) support DC homeostasis via provision of FLT3L. Grem1 FRCs co-localize with DCs and express FLT3L in human and mouse lymph nodes. Using a new genetic model, we provide evidence that FLT3L produced by GREM1 FRCs maintains lymph node preDCs, cDCs, and plasmacytoid DCs (pDCs). Spatial transcriptomics and cytofluorometry reveal that Grem1 FRC-derived FLT3L supports not only proliferation, but also survival of lymph node cDCs within the interfollicular zone (IFZ). Functionally, loss of Grem1 FRC-derived FLT3L impairs cDC priming of antigen-specific T cell responses. These findings provide key mechanistic insights underlying stromal cell support of DC homeostasis and function.

immunology↗

bioRxiv2023

Accurate long-read transcript discovery and quantification at single-cell resolution with Isosceles

Accurate detection and quantification of mRNA isoforms from nanopore long-read sequencing remains challenged by technical noise, particularly in single cells. To address this, we introduce Isosceles, a computational toolkit that outperforms other methods in isoform detection sensitivity and quantification accuracy across single-cell, pseudo-bulk and bulk resolution levels, as demonstrated using synthetic and biologically-derived datasets. Isosceles improves the fidelity of single-cell transcriptome quantification at the isoform-level, and enables flexible downstream analysis. As a case study, we apply Isosceles, uncovering coordinated splicing within and between neuronal differentiation lineages. Isosceles is suitable to be applied in diverse biological systems, facilitating studies of cellular heterogeneity across biomedical research applications.

bioinformatics↗

bioRxiv2023

Single-cell long-read targeted sequencing reveals transcriptional variation in ovarian cancer

Single-cell RNA sequencing predominantly employs short-read sequencing to characterize cell types, states and dynamics; however, it is inadequate for comprehensive characterization of RNA isoforms. Long-read sequencing technologies enable single-cell RNA isoform detection but are hampered by lower throughput and unintended sequencing of artifacts. Here we developed Single-cell Targeted Isoform Long-Read Sequencing (scTaILoR-seq), a hybridization capture method which targets over a thousand genes of interest, improving the median number of unique transcripts per cell by 29-fold. We used scTaILoR-seq to identify and quantify RNA isoforms from ovarian cancer cell lines and primary tumors, yielding 10,796 single-cell transcriptomes. Using long-read variant calling we revealed associations of expressed single nucleotide variants (SNVs) with alternative transcript structures. In addition, phasing of SNVs across transcripts facilitated measurement of allelic imbalance within distinct cell populations. Overall, scTaILoR-seq is a long-read targeted RNA sequencing method and analytical framework for exploring transcriptional variation at single-cell resolution.

genomics↗

bioRxiv2023

Coordinated wound responses in a regenerative animal-algal photosymbiotic metaorganism

Animal regeneration requires coordinated responses of many cell types throughout the animal body. In animals carrying endosymbionts, cells from the other species may also participate in regeneration, but how cellular responses are integrated across species is yet to be unraveled. Here, we study the acoel Convolutriloba longifissura, which hosts symbiotic Tetraselmis green algae and can regenerate entire bodies from small tissue fragments. We show that animal injury leads to a decline in the photosynthetic efficiency of the symbiotic algae and concurrently induces upregulation of a cohort of photosynthesis-related genes. A deeply conserved animal transcription factor, runt, is induced after injury and required for the acoel regeneration. Knockdown of runt also dampens algal transcriptional responses to the host injury, particularly in photosynthesis related pathways, and results in further reduction of photosynthetic efficiency post-injury. Our results suggest that the runt-dependent animal regeneration program coordinates wound responses across the symbiotic partners and regulates photosynthetic carbon assimilation in this metaorganism.

developmental biology↗

bioRxiv2022

Mean-field approximations with adaptive coupling for networks with spike-timing-dependent plasticity

Understanding the effect of spike-timing-dependent plasticity (STDP) is key to elucidate how neural networks change over long timescales and to design interventions aimed at modulating such networks in neurological disorders. However, progress is restricted by the significant computational cost associated with simulating neural network models with STDP, and by the lack of low-dimensional description that could provide analytical insights. Phase-difference-dependent plasticity (PDDP) rules approximate STDP in phase oscillator networks, which prescribe synaptic changes based on phase differences of neuron pairs rather than differences in spike timing. Here we construct mean-field approximations for phase oscillator networks with STDP to describe part of the phase space for this very high dimensional system. We first show that single-harmonic PDDP rules can approximate a simple form of symmetric STDP, while multi-harmonic rules are required to accurately approximate causal STDP. We then derive exact expressions for the evolution of the average PDDP coupling weight in terms of network synchrony. For adaptive networks of Kuramoto oscillators that form clusters, we formulate a family of low-dimensional descriptions based on the mean field dynamics of each cluster and average coupling weights between and within clusters. Finally, we show that such a two-cluster mean-field model can be fitted to synthetic data to provide a low-dimensional approximation of a full adaptive network with symmetric STDP. Our framework represents a step towards a low-dimensional description of adaptive networks with STDP, and could for example inform the development of new therapies aimed at maximizing the long-lasting effects of brain stimulation.

neuroscience↗

bioRxiv2022

Identifying and quantifying isoforms from accurate full-length transcriptome sequencing reads with Mandalorion

The Mandalorion tool, which we have continuously developed over the last 5 years, identifies and quantifies high-confidence isoforms from accurate full-length transcriptome sequencing reads produced by methods like PacBio Iso-Seq and ONT-based R2C2. In this manuscript, we introduce and benchmark Mandalorion v4 which further improves upon the already strong performance of Mandalorion v3.6 used in the LRGASP consortium challenge. By processing real and simulated accurate full-length transcriptome sequencing data sets, we show three main features of Mandalorion: First, Mandalorion-based isoform identification has very high Precision and maintains high Recall even when used in the absence of any genome annotation. Second, isoform read counts as quantified by Mandalorion show high correlation with simulated read counts. Third, isoforms identified by Mandalorion closely reflect the full-length transcriptome sequencing data sets they are based on.

bioinformatics↗

bioRxiv2022

Comparative analysis of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing

Spatial transcriptomics extends single cell RNA sequencing (scRNA-seq) by providing spatial context for cell type identification and analysis. Imaging-based spatial technologies such as Multiplexed Error-Robust Fluorescence In Situ Hybridization (MERFISH) can achieve single-cell resolution, directly mapping single cell identities to spatial positions. MERFISH produces an intrinsically different data type than scRNA-seq and a technical comparison between the two modalities is necessary to ascertain how to best integrate them. We performed MERFISH on mouse liver and kidney and compared the resulting bulk and single-cell RNA statistics with those from the Tabula Muris Senis cell atlas as well as from two Visium datasets. MERFISH quantitatively reproduced the bulk RNA-seq and scRNA-seq results with improvements in overall dropout rates and sensitivity. Finally, we found that MERFISH independently resolved distinct cell types and spatial structure in both liver and kidney. Computational integration with the Tabula Muris Senis atlas did not enhance these results. We conclude that compared to scRNA-seq, MERFISH provides a quantitatively comparable method for measuring single-cell gene expression and can robustly identify cell types without the need for computational integration with scRNA-seq reference atlases.

bioinformatics↗

bioRxiv2021

Longitudinal single-cell epitope and RNA-sequencing reveals the immunological impact of type 1 interferon autoantibodies in critical COVID-19

Type I interferon (IFN-I) neutralizing autoantibodies have been found in some critical COVID-19 patients; however, their prevalence and longitudinal dynamics across the disease severity scale, and functional effects on circulating leukocytes remain unknown. Here, in 284 COVID-19 patients, we found IFN-I autoantibodies in 19% of critical, 6% of severe and none of the moderate cases. Longitudinal profiling of over 600,000 peripheral blood mononuclear cells using multiplexed single-cell epitope and transcriptome sequencing from 54 COVID-19 patients, 15 non-COVID-19 patients and 11 non-hospitalized healthy controls, revealed a lack of IFN-I stimulated gene (ISG-I) response in myeloid cells from critical cases, including those producing anti-IFN-I autoantibodies. Moreover, surface protein analysis showed an inverse correlation of the inhibitory receptor LAIR-1 with ISG-I expression response early in the disease course. This aberrant ISG-I response in critical patients with and without IFN-I autoantibodies, supports a unifying model for disease pathogenesis involving ISG-I suppression via convergent mechanisms.

immunology↗

bioRxiv2020

Mean-field models for EEG/MEG: from oscillations to waves

Neural mass models have been actively used since the 1970s to model the coarse-grained activity of large populations of neurons. They have proven especially fruitful for understanding brain rhythms. However, although motivated by neurobiological considerations they are phenomeno-logical in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. Here we consider a simple spiking neuron network model that has recently been shown to admit to an exact mean-field description for both synaptic and gap-junction interactions. The mean-field model takes a similar form to a standard neural mass model, with an additional dynamical equation to describe the evolution of population synchrony. As well as reviewing the origins of this next generation mass model we discuss its extension to describe an idealised spatially extended planar cortex. To emphasise the usefulness of this model for EEG/MEG modelling we show how it can be used to uncover the role of local gap-junction coupling in shaping large scale synaptic waves.

neuroscience↗

bioRxiv2020

Network Analysis and Human Single Cell Brain Transcriptomics Reveal Novel Aspects of Alpha-Synuclein (SNCA) Biology

Alpha-synuclein (SNCA) aggregates are pathological hallmarks of synucleinopathies, neurodegenerative disorders including Parkinsons Disease (PD) and Lewy Body Dementia (LBD). Functional networks are not yet well-characterized for SNCA by CNS cell type. We investigated cell-specific differences in SNCA expression using Allen Brain Database single-nucleus RNA-seq data from human Middle Temporal Gyrus (MTG, 15,928 nuclei) and Anterior Cingulate Cortex (ACC, 7,258 nuclei). Weighted gene co-expression analysis (WGCNA) and hierarchical clustering identified a conserved SNCA co-expression module. Module genes were highly conserved (p < 10-10) and most highly expressed in excitatory neurons versus inhibitory neurons and other glial cells. SNCA co-expression module genes from ACC and MTG regions were then used to construct a protein-protein interaction (PPI) network, with SNCA empirically top hub. Genes in the SNCA PPI network were compared with genes nearest single nucleotide polymorphisms linked with PD risk in genome-wide association studies. 16 genes in our PPI network are nearest genes to PD risk loci (p < 0.0006) and 55 genes map within 100kb. Selected SNCA PPI network genes nearest PD risk loci were disrupted by CRISPR knock out gene editing for validation of network functional significance; disruption of STK39, GBA, and MBNL2 resulted in significantly elevated intracellular SNCA expression.

neuroscience↗