Biology subjects

Bailey, M.

Publications and source records attributed to Bailey, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Optimising MALDI on PEN substrates for small molecule analysis in the context of same-section multimodal workflows

Multimodal imaging workflows increasingly require multiple analytical techniques to be applied to the same tissue section to improve spatial co-registration and molecular interpretation. Polyethylene naphthalate (PEN) membrane substrates are attractive for this purpose because of their low thickness and compatibility with downstream modalities, but their use for matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI MSI) remains challenging due to low conductivity, reduced ion yield and susceptibility to laser-induced damage. In this study, MALDI MSI conditions for small-molecule analysis on PEN substrates were systematically optimised using bovine brain homogenate and mouse brain tissue using a TimsTOF flex MALDI-2 platform. Matrix selection, laser energy, pixel size (5 and 20 m), ionisation mode and PEN type were evaluated to identify acquisition conditions that balanced signal intensity with spectral quality and preservation of sample and membrane integrity. Among the matrices tested, 1,5-diaminonaphthalene (DAN) resulted in the best overall performance, providing higher ion intensities, less damage to the PEN substrates and a broader usable laser energy range than the other matrices tested. Different PEN substrate formats were also compared, showing distinct trade-offs between analytical performance and practical suitability for multimodal analysis. Under the tested conditions, glass-supported PEN (gPEN) provided the most practical overall compromise, while frame-supported PEN was not suitable for routine analysis on the instrument configuration used. Application of the optimised method to mouse brain tissue confirmed that spatially resolved metabolite imaging on PEN substrates is feasible and can support same-section multimodal workflows.

biochemistry↗

bioRxiv2026

Complementary Single-Cell Microflow HILIC and Ion Pair LC-MS Reveal Bystander Metabolic Effects in a Macrophage Model of Tuberculosis

Single-cell metabolomics remains analytically challenging due to the low abundance and chemical diversity of metabolites in individual cells. We have developed complementary microflow HILIC and ion pair LC-MS methods to expand metabolite coverage in single macrophages. Ion pair LC-MS was applied to single cells for the first time, enabling retention of highly polar and ionic metabolites that elute early under conventional reversed-phase conditions. Across Mycobacterium bovis BCG infected, uninfected bystander, and control unexposed THP-1 macrophages, both microflow methods detected significantly more features than a previously reported analytical-flow HILIC method. The two microflow methods provided complementary chemical space, together yielding 633 unique named metabolites with MS2 spectra. This depth enabled pathway-level interpretation at single-cell resolution, revealing infection-associated changes in purine-, arginine-, glutathione-, and one-carbon folate-associated metabolism. Metabolite-level interrogation indicated shared purine and amino acid changes in both infected and neighbouring macrophages, while revealing a distinct bystander phenotype characterised by elevated glycine and heterogeneous ATP levels. Finally, we demonstrate sequential IP and HILIC analysis of the same single cell, establishing a route toward maximal coverage from individual cells. These results position microflow HILIC and IP LC-MS as powerful, orthogonal strategies for advancing single-cell metabolomics and unveiling heterogeneity within complex biological microenvironments. Table of Contents O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/733771v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@103ecfforg.highwire.dtl.DTLVardef@bc6734org.highwire.dtl.DTLVardef@11b96aforg.highwire.dtl.DTLVardef@41edfe_HPS_FORMAT_FIGEXP M_FIG Figure made in BioRender. C_FIG

microbiology↗

bioRxiv2026

Nanoflow ion-pairing LC-MS for ultra-low-input polar metabolomics and isotope tracing

Low-input and single-cell metabolomics remain constrained by the poor retention of polar metabolites in conventional reversed-phase nanoflow LC-MS workflows. Here, we establish nanoflow tributylamine (TBA) ion-pairing LC-MS as a platform for ultra-low-input polar metabolomics and stable isotope tracing. By adapting an analytical-flow TBA ion-pairing method to the nanoflow scale, this workflow extends the sensitivity and inline concentration advantages of nanoflow chromatography to charged metabolites involved in central carbon metabolism. Using mouse liver metabolite extracts, we show that the nanoflow method preserves chromatographic retention and separation of chemically diverse metabolite classes, including adenine nucleotides, nucleotide cofactors, TCA cycle intermediates, acyl-CoAs, and bile acid isomers. Despite loading 20-fold less tissue-equivalent material on column, nanoflow LC-MS produced higher signal intensity than the analytical-flow method for many metabolites. Across representative compounds, the nanoflow workflow reduced the biomass required for detection by approximately 20- to >600-fold, with pronounced gains for low-abundance metabolites such as NADPH and acetyl-CoA. TBA ion-pairing also enabled trap-and-elute nanoflow analysis of retained polar metabolites from single-cell-equivalent inputs. ATP was detected from one cell equivalent using both full-scan and targeted parallel reaction monitoring acquisition, with targeted acquisition further increasing signal over blank. Finally, we applied the workflow to stable isotope tracing in uniformly labeled 13C-glucose-treated cells. 13C-labeled ATP isotopologues were detectable from single-cell-equivalent input, and targeted acquisition improved isotopologue measurement near the detection limit. Together, these results demonstrate that nanoflow TBA ion-pairing LC-MS enables retained, high-sensitivity analysis of polar metabolites from ultra-low inputs and provides a foundation for extending central carbon metabolite analysis and isotope tracing toward single-cell-scale applications.

biochemistry↗

bioRxiv2026

Capillary-based Subcellular Sampling Uncovers the Stress Granule Proteome in Single Cells

Many diseases arise from dysfunction within specific organelles or biomolecular condensates, highlighting the value of analysing proteins at subcellular resolution to uncover new biological mechanisms. We report a novel capillary-based subcellular sampling workflow coupled with liquid chromatography-mass spectrometry (LC-MS) for proteomic analysis of defined subcellular regions of individual cells. We applied this methodology to stress granules (SGs), membrane-less biomolecular condensates that form in response to cellular stress (including viral infection), and are implicated in infection, neuropathology and cancer. Comprehensive characterisation of SG protein composition remains limited by technical challenges associated with bulk purification, including loss of spatial context, dynamic behaviour and contamination from cytosolic material. Using our novel method, we identified a high-confidence set of 405 SG-associated proteins, including 46 established SG residents alongside numerous previously unreported candidates. Functional enrichment analysis revealed pathways consistent with known SG biology, while comparison with an independent cytosolic proteome dataset demonstrated minimal overlap, supporting the specificity of the sampling strategy. Selected novel SG protein candidates (AHNAK2, DDX39B, NUDT1 and FKBP2) were validated using immunofluorescence microscopy. These findings establish capillary-based subcellular sampling as a viable approach for proteomic analysis of SGs with preserved spatial context and provide a framework for analysing other subcellular compartments. Table of contentsWe report an LC-MS-based capillary sampling workflow for proteomic analysis of subcellular structures within single cells. This methodology identified 405 high-confidence stress granule-associated proteins, including 46 previously established and numerous novel candidates. The approach demonstrated high specificity and preserved spatial context, expanding the capabilities of subcellular proteomics. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=55 SRC="FIGDIR/small/724230v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1fa0bb0org.highwire.dtl.DTLVardef@1158524org.highwire.dtl.DTLVardef@1d82812org.highwire.dtl.DTLVardef@2ee4d9_HPS_FORMAT_FIGEXP M_FIG C_FIG Figure made in Biorender.com.

cell biology↗

bioRxiv2026

Dynamic modelling of human neural crest development using a bioengineered stem cell organoid system

The neural crest (NC) is a transient stem cell population which migrates throughout the developing embryo to contribute to diverse tissues dependent on axial origin. For example, cranial NC can give rise to bone and cartilage, while more posterior NC populations give rise to peripheral nervous system and neuroendocrine tissues. Perturbations in neural crest development can lead to severe congenital anomalies and cancers, with over 700 neurocristopathies reported. In humans, early NC development remains poorly understood due to the inaccessibility of tissue samples, thus necessitating the development of in vitro models. Currently, a limited number of NC organoid protocols are available, but these mainly focus on cranial NC and lack relevant tissue architecture. Here, we describe a novel bioengineered pipeline to derive human pluripotent stem cell (hPSC)-derived neuroepithelial organoids, "neurocrestoids" featuring physiologically-relevant tissue architecture. We show that neurocrestoids recapitulate the dynamics of induction, delamination, and migration of human neural crest cells (NCCs), and can be directly compared to murine NC explants for cross-species validation. Organoids express an array of HOX genes indicating the successful generation of cranial, vagal and trunk NCCs. Moreover, we have integrated our neurocrestoids with a customised micropatterned substrate suitable for live visualisation and guided separation of SOX10-positive migratory human NCCs. Our "NCC migration on-chip" are reproducible across multiple hPSC lines and should be scalable for future diagnostic and therapeutic applications, significantly improving our ability to study human NC pathologies.

developmental biology↗

bioRxiv2026

mRNA-GPT: A Generative Model for Full-Length mRNA Design and Optimization

We introduce mRNA-GPT, a generative model for end-to-end full-length mRNA sequence design and optimization. Unlike existing approaches that optimize isolated regions, mRNA-GPT jointly optimizes across all three regions (5' UTR, CDS, and 3' UTR) to capture long-range sequence dependencies and cross-region regulatory interactions critical for therapeutic efficacy. The model is pre-trained on 30 million full-length natural mRNA sequences across diverse species and organisms, establishing a robust foundation for sequence generation. We employ Reinforcement Learning (RL), specifically Proximal Policy Optimization (PPO) with oracle-based reward signals, to directly and iteratively optimize target properties, such as half-life and translation efficiency. mRNA-GPT supports flexible generation modes: single regions (UTR or CDS alone), full-length sequences, or generation of any region conditioned on any other region. Through multi-objective optimization, mRNA-GPT achieves Pareto-optimal designs, i.e., solutions for which no single objective can be improved without degrading another, that balance competing properties without sacrificing performance on either objective. mRNA-GPT demonstrates superior design capabilities compared to state-of-the-art methods, achieving enhanced performance in 3' UTR stability optimization, CDS translation rate enhancement, and comprehensive full-length sequence design.

bioinformatics↗

bioRxiv2026

Short-chain PFAS exposure alters embryonic development and behavior in zebrafish

Per- and polyfluoroalkyl substances (PFAS) are manmade chemicals that are persistent in the environment and have been linked to various physiological and neurobehavioral outcomes, including anxiety disorders. Trifluoroacetic acid (TFA), a short chain PFAS and the most common PFAS degradation product, is increasingly detected in water, soil, and human blood, raising significant concerns about its developmental toxicity. However, the impact of early-life TFA exposure on neurodevelopment and behavior remain insufficiently characterized. In this study, we employed Zebrafish (Danio rerio) embryos as a New Approach Methodology (NAM), to evaluate the development, behavior, and protein expression changes in response to early-life TFA exposure. Embryos were exposed to environmentally relevant low and high concentrations of TFA beginning at one-cell stage. Early developmental physiology was assessed by measuring viability, tail twitch response, hatching rates, and chorion diameters during embryogenesis. Anxiety-like behaviors were evaluated at 5- and 6-days post-fertilization using validated behavioral assays such as the Light-Dark Test and Startle Response. Each test evaluates distinct anxiety-related behaviors by measuring locomotor activity, thigmotaxis (wall preference), and stimulus reactivity, with anxious zebrafish larvae showing increased movement in light and greater wall preference. Then to identify molecular pathways underlying observed developmental phenotypes with TFA exposure, proteomic analyses were performed on embryos at 24- and 48-hours post-fertilization. Our results indicate that TFA exposure altered developmental physiology, evidenced by reduced chorion diameters, and lead to increased anxiety-like behaviors with larvae exhibiting thigmotaxis. These phenotypic changes were accompanied by detectable alterations in the embryonic proteome. Collectively, our findings provide insight into how short-chain PFAS exposure during critical windows of development may contribute to neurobehavioral dysfunction, highlighting potential risks relevant to inform public health policies and environmental regulations.

developmental biology↗

bioRxiv2025

Mechanism of Lutein to meso-Zeaxanthin Isomerization by RPE65 Catalysis

The macular pigments lutein (L), zeaxanthin (Z), and meso-zeaxanthin (MZ) protect the human retina from light and oxidative stress. While L and Z are abundant in the human diet, MZ is nearly absent. We previously demonstrated MZ is derived from L in chicken embryos precisely timed with expression of RPE65. Herein, we show that RPE65 from mouse, an animal that does not concentrate MZ in the eye, catalyzes L to MZ isomerization similarly as found for RPE65 from chicken and human, when expressed in cultured cells. Co-expression with xanthophyll-binding proteins had no impact on MZ yield. L and MZ both fit deep into the tunnel accessing the non-heme iron center, with strain evident for the 3R,6R {varepsilon} ring of L. Interestingly, a negatively charged Glu148, found along substrate tunnel, highly conserved among carotenoid cleavage dioxygenases, and which is critical for eye health, could be replaced by a neutral, isosteric residue (Gln) without impacting MZ yield. We propose that L to MZ isomerization proceeds by a neutral, radical transition state that differs from the carbocation encountered during retinoid isomerization. These findings extend our mechanistic understanding for macular carotenoid metabolism and should be considered when developing therapeutic interventions that act via RPE65.

biochemistry↗

bioRxiv2025

CenSegNet: a generalist high-throughput deep learning framework for centrosome phenotyping at spatial and single-cell resolution in heterogeneous tissues

Centrosome abnormalities (CA) are a hallmark of epithelial cancers, yet their spatial complexity and phenotypic heterogeneity remain poorly resolved due to limitations in conventional image analysis. We present CenSegNet (Centrosome Segmentation Network), a modular deep learning framework for high-resolution, context-aware segmentation of centrosomes and epithelial architecture across diverse tissue types. Integrating a dual-branch architecture with uncertainty-guided refinement, CenSegNet achieves state-of-the-art performance and generalisability across both immunofluorescence and immunohistochemistry modalities, outperforming existing models in accuracy and morphological fidelity. Applied to tissue microarrays (TMAs) containing 911 breast cancer sample cores from 127 patients, CenSegNet enables the first large-scale, spatially resolved quantification of numerical and structural CA at single-cell resolution. These CA subtypes are mechanistically uncoupled, exhibiting distinct spatial distributions, age-dependent dynamics, and associations with histological tumour grade, hormone receptor status, genomic alterations, and nodal involvement. Structural CA levels are additionally associated with overall survival, supporting the clinical relevance of spatially resolved CA patterns. Discordant CA profiles at tumour margins are linked to local aggressiveness and stromal remodelling. To support broad adoption and reproducibility, CenSegNet is released as an open-source Python library. Together, our findings establish CenSegNet as a scalable, generalisable platform for spatially resolved centrosome phenotyping in intact tissues, enabling systematic dissection of the biology of this organelle and its dysregulation in cancer and other epithelial diseases.

cell biology↗

bioRxiv2025

Social stress worsens colitis through beta-adrenergic-driven oxidative stress in intestinal mucosal compartments

AbstractPsychological stress is a known risk factor for inflammatory bowel disease (IBD), but the mechanisms linking stress to worsened disease remain unclear. Because distinct stress paradigms activate different neuroimmune circuits, it is critical to investigate model-specific effects. We examined how social stress primes the gut for heightened inflammation and whether this is mediated by specific neuroendocrine pathways, including 2-/{beta}-adrenergic (sympathetic) or glucocorticoid/ corticotropin-releasing hormone receptor (CRHR1) (HPA axis) signaling. Mice were exposed to social disruption (SDR) stress and pre- treated with pharmacological antagonists targeting 2-adrenergic receptors (idazoxan), {beta}-adrenergic receptor ({beta}-AR) (propranolol), glucocorticoid receptor (mifepristone), or CRHR1 (antalarmin). Intestinal epithelial cell (IEC) gene expression and microbiota composition were assessed following SDR. To determine disease impact, SDR was combined with either Citrobacter rodentium infection or dextran sulfate sodium (DSS)-induced colitis, with interventions including the {beta}-AR inhibitor propranolol and the NADPH oxidase inhibitor apocynin. SDR significantly upregulated expression of Dual oxidase 2 (Duox2), Dual oxidase maturation factor 2 (Duoxa2), and inducible nitric oxide synthase 2 (Nos2) in IECs (2- to 8- fold, p < 0.0001), effects reversed by {beta}-AR blockade but not 2-adrenergic, CRH, or glucocorticoid inhibition. SDR also induced microbial dysbiosis, characterized by reduced alpha-diversity and compositional shifts, which was rescued by propranolol. Stress exacerbated disease severity in both infectious (C. rodentium) and chemically induced (DSS) colitis, amplifying colonic expression of Duox2, Nos2, and Ccl2, especially. Apocynin mitigated stress-induced ROS/RNS production and body weight loss even prior to colitis onset, reduced colonic gene expression of key oxidative enzymes, and alleviated both chemically and infectious colitis severity. These findings provide strong evidence that social stress sensitizes the gut to inflammation through {beta}-adrenergic and NADPH oxidase-driven oxidative stress, highlighting potential therapeutic targets for mitigating stress-exacerbated IBD. HighlightsSocial disruption (SDR) and restraint stress (RST) activate distinct neuroendocrine pathways, with SDR driving epithelial ROS/RNS pathways via {beta}-adrenergic signaling. {beta}-adrenergic blockade prevents SDR-induced epithelial priming, microbial dysbiosis, and colitis exacerbation. NADPH oxidase inhibition with apocynin mitigates stress-induced oxidative stress and disease severity across different colitis models. Findings identify {beta}-adrenergic and redox pathways as therapeutic targets for stress-exacerbated IBD.

immunology↗

bioRxiv2025

PROFET Predicts Continuous Gene Expression Dynamics from scRNA-seq Data to Elucidate Heterogeneity of Cancer Treatment Responses

Single-cell RNA sequencing profiles cellular heterogeneity but captures only static snapshots, limiting inference of gene expression dynamics. We developed PROFET (Particle-based Reconstruction Of generative Force-matched Expression Trajectories), a framework that reconstructs continuous, nonlinear single-cell trajectories from sparsely sampled scRNA-seq time series. PROFET combines a particle-based gradient-flow algorithm with simulation-free force matching to accurately infer cellular dynamics. Across mouse and human in vitro datasets and an in vivo axolotl regeneration dataset, PROFET achieved 2.6-12.5X lower prediction error than ten state-of-the-art trajectory inference methods. Applying PROFET to newly generated scRNA-seq data from a palbociclib-treated MCF7 cell line and three published breast cancer patient datasets, we reconstructed treatment-response trajectories and identified a resistant cell subpopulation exhibiting large phenotypic shifts and enrichment of the surface markers UNC5B, TLR3, PCDH19, PROCR, SLITRK6, and SEMA6B. PROFET provides a biologically grounded framework for reconstructing cell-state dynamics from static single-cell data across development, regeneration, and therapeutic response.

bioinformatics↗

bioRxiv2025

Superior intracellular detection of cytokines, transcription factors, and phosphoproteins by CyTOF compared with fluorescent cytometry

Unraveling biological complexity, whether it be immune subset distribution in infectious disease(s), autoimmunity or tumor heterogeneity, requires technologies capable of single-cell proteomic analysis, such as flow cytometry. Surface immunophenotyping alone is often insufficient, as interrogating functional capacity is required to determine cellular mechanisms and effectively inform diagnostic biomarker discovery, therapeutics and vaccine development. However, large panels with intracellular markers are subject to numerous challenges, including spectral overlap and background cellular autofluorescence, reducing resolving power for rare subsets or populations defined by low-abundance expression. We posited that mass cytometry may overcome such limitations; to address this, three small (11-12-plex) clone-matched antibody panels were evaluated by spectral flow and mass cytometry. Panels were comprised of surface and intracellular targets (phospho-epitopes, transcription factors or cytokines) and designed to minimize fluorescence spectral overlap. CyTOF technology offered superior signal resolution across the range of intracellular targets. Improved signal-to-noise provided better resolution of phospho-events and transcription factor expression, in particular TOX and T-bet. Most strikingly, stimulation-specific IL-10+ and IL-13+ cells were only detected by CyTOF. Superior resolution of these cytokines enabled accurate population clustering, permitting more unique immune cell signatures to be found, including Tr1 and Tc2 populations, thus providing a more comprehensive picture of the immuno-diversity present. Our findings indicate that CyTOF technology could catalyze seminal discoveries in functional immune profiling, driving therapeutic design and diagnostics.

immunology↗

bioRxiv2025

Active Learning for Protein Structure Prediction

Accurate protein structure prediction is challenging especially for families and types that are not well-represented in current training data. Active learning selects candidates for labeling with the aim of most rapidly improving model performance. In a general, many labeling strategies have been proposed. However, with protein structure prediction, most of these strategies dont apply or are difficult due to the high-dimensional, variable-dimensional regression target and the inherent complexity of the models involved. We applied a novel active learning strategy, DEW-DROP, to protein structure prediction on two different protein datasets: VHH-only antibodies (Nanobodies), and Mycobacterial proteins. We introduce a domain-specific fine-tuned Equifold model for VHH structures and apply DEWDROP to generate ensembles of predictions using Monte Carlo dropout. Using the statistics of these we select batches with high information content for labeling. We show that DEWDROP (1) improves model training efficiency through batch optimization outper-forming baselines, and (2) selects data with relevant high information content.

molecular biology↗

bioRxiv2025

Light induces Phytochrome B SUMOylation to recruit the immune regulator NPR1 in nuclear condensates to control immunity in plants

It has long been observed that light perception by phytochromes control plant immunity, however, the underpinning molecular mechanism is less well understood. We demonstrate that light mediated SUMO conjugation to Phytochrome B (PhyB) is critical for increasing cellular salicylic-acid (SA) levels to orchestrate systemic acquired resistance (SAR) upon avirulent bacterial infection. SUMOylation is critical for PhyB nuclear condensate formation during light activated immunity. Light induced PhyB SUMOylation recruits NPR1, through its SUMO interacting motif to nuclear condensates to elevate SA levels for immune responses. In the dark during SAR, elevated SA levels substitute for light to maintain PhyB SUMOylation and immune-related photobody formation by stimulating the degradation of PhyB targeting deSUMOylase, OTS1. SUMOylated PhyB-NPR1 immune photobodies associate with TGA transcription factor associated chromatin to trigger immune gene expression. We unravel a mechanism where SUMOylation can enable light to recruit NPR1 to PhyB nuclear condensates to form immune photobodies to regulate plant immunity. HighlightsO_LILight-dependent immunity in plants relies on the SUMO mediated interaction between the photoreceptor PhyB and the Salicylic Acid (SA) receptor NPR1. C_LIO_LILight induced PhyB SUMOylation recruits NPR1 to nuclear condensates which we identify as immune photobodies that elevate SA levels for immune responses. C_LIO_LIIn darkness, SA can replace light in enabling PhyB-NPR1 immune photobody formation by regulating SUMOylation revealing a SA mediated mechanism for controlling PhyB liquid-liquid phase separation. C_LIO_LISUMO-modified PhyB-NPR1 immune photobodies regulate transcriptional activity of immune associated chromatin to shape defence responses in plants. C_LI

plant biology↗

bioRxiv2025

Revisiting the Central Dogma: the distinct roles of genome, methylation, transcription, and translation on protein expression in Arabidopsis thaliana

BackgroundWe investigated the flow of information from genome sequence to protein expression implied by the Central Dogma, to determine the impact of intermediate genomic levels in plants. ResultsWe performed genomic profiling of rosettes in two Arabidopsis accessions, Col-0 and Can-0, and assembled their genomes using long reads and chromatin interaction data. We measured gene and protein expression in biological replicates grown in a controlled environment, also measuring CpG methylation, ribosome-associated transcript levels and tRNA abundance. Each omic level is highly reproducible between biological replicates and between accessions despite their 0.5% sequence divergence; the single best predictor of any level in one accession is the corresponding level in the other. Within each accession, gene codon frequencies accurately model both mRNA and protein expression. The effects of a codon on mRNA and protein expression are highly correlated but are unrelated to genome-wide codon frequencies or to tRNA levels which instead match genome-wide amino acid frequencies. Ribosome-associated transcripts closely track mRNA levels. ConclusionsIn the absence of environmental perturbation, neither methylation, tRNA nor ribosome-associated transcript levels add appreciable information about constitutive protein abundance beyond that in DNA codon frequencies and mRNA expression levels. The impact of constitutive gbM is mostly explained by gene codon composition. tRNA abundance tracks overall amino acid demand. However, genetic differences between accessions associate with differential gbM by inflating differential expression variation. Our data show that the Central Dogma holds only if both sequence and abundance information in mRNA are considered.

plant biology↗

bioRxiv2024

Aberrant iron deposition in the multiple sclerosis spinal cord relates to neurodegeneration

BackgroundIron accumulates in microglia-macrophages at the edge of multiple sclerosis (MS) lesions in the brain. Iron-rimmed brain lesions strongly predict disability accumulation, supporting iron metabolism is crucial in MS pathology. Little is known about iron distribution in the spinal cord. MethodsAutopsy cervical, thoracic and lumbar spinal cord samples from 9 controls and 46 MS donors of whom a subset (n=36) had mesiofrontal motor cortical tissue available for study, were labelled and systematically assessed for iron (DAB-enhanced Turnbull), myelin (PLP), axons (Palmgren silver), microglia-macrophages (TMEM119, Iba1, CD68), astroglia (GFAP), oligodendroglia (OLIG2), acute axonal injury (B-APP, SMI-32, NPY-1R) and oxidative stress (E06). MS lesional and non-lesional areas were considered. Total non-haem iron was quantified by inductively coupled plasma optical emission spectroscopy (ICP-OES). ResultsIn controls, iron predominantly localised to oligodendrocytes with total non-haem iron relating to total myelin fraction, which markedly differed in MS where iron accumulated in microglia-macrophages, subpial astrocytes, and axons in non-lesional areas. Iron laden microglia-macrophages were over-represented relative to total microglial-macrophages and displayed dysmorphic features. Iron-positive axons showed a disto-proximal gradient (highest at lumbar level) with a predilection for the corticospinal tracts. The extent of iron axon positivity related to smaller spinal cord area, lower total axonal counts, and greater oxidative stress. Iron positivity in each cellular compartment (i.e. subpial astrocytes, microglia-macrophage and axons) related to one-another and total non-haem iron correlated with axonal counts in MS. No iron-rimmed lesions were detected in the spinal cord unlike in cortical grey and subcortical white matter of the same cases where 22% and 80% of iron-rimmed lesions, respectively, were seen. ConclusionsDespite the conspicuous absence of iron-rimmed lesions in the MS spinal cord, we demonstrate widespread aberrant iron distribution in the MS spinal cord that relates to oxidative stress and neurodegeneration independent of demyelination. The distal cord predominant and corticospinal tract specific accumulation of iron in axons mirrors the pattern of length-dependent motoric disability commonly encountered in progressive MS. These findings implicate aberrant iron accumulation as a novel, clinically relevant, feature of MS spinal cord pathology.

neuroscience↗

bioRxiv2024

SCRATCH: A programmable, open-hardware, benchtop robot that automatically scratches cultured tissues to investigate cell migration, healing, and tissue sculpting.

Despite the widespread popularity of the scratch assay, where a pipette is dragged through cultured tissue to create an injury gap to study cell migration and healing, the manual nature of the assay carries significant drawbacks. So much of the process depends on individual manual technique, which can complicate quantification, reduce throughput, and limit the versatility and reproducibility of the approach. Here, we present a truly open-source, low-cost, accessible, and robotic scratching platform that addresses all of the core issues. Compatible with nearly all standard cell culture dishes and usable directly in a sterile culture hood, our robot makes highly reproducible scratches in a variety of complex cultured tissues with high throughput. Moreover, we demonstrate how scratching can be programmed to precisely remove areas of tissue to sculpt arbitrary tissue and wound shapes, as well as enable truly complex co-culture experiments. This system significantly improves the usefulness of the conventional scratch assay, and opens up new possibilities in complex tissue engineering and cell biological assays for realistic wound healing and migration research.

bioengineering↗

bioRxiv2023

SARS-CoV-2 infection is associated with intestinal permeability, systemic inflammation, and microbial dysbiosis in hospitalized COVID-19 patients

Coronavirus disease 2019 (COVID-19) and associated severity has been linked to uncontrolled inflammation and may be associated with changes in the microbiome of mucosal sites including the gastrointestinal tract and oral cavity. These sites play an important role in host-microbe homeostasis and disruption of epithelial barrier integrity during COVID-19 may potentially lead to exacerbated inflammation and immune dysfunction. Outcomes in COVID-19 are highly disparate, ranging from asymptomatic to fatal, and the impact of microbial dysbiosis on disease severity is unclear. Here, we obtained plasma, rectal swabs, oropharyngeal swabs, and nasal swabs from 86 patients hospitalized with COVID-19 and 12 healthy volunteers. We performed 16S rRNA sequencing to characterize the microbial communities in the mucosal swabs and measured circulating cytokines, markers of gut barrier integrity, and fatty acids in the plasma samples. We compared these plasma concentrations and microbiomes between healthy volunteers and the COVID-19 patients who had survived or unfortunately died by the end of study enrollment, and between severe disease and healthy controls, as well as performed a correlation analysis between plasma variables and bacterial abundances. The rectal swabs of COVID-19 patients had reduced abundances of several commensal bacteria including Faecalibacterium prausnitsii, and an increased abundance of the opportunistic pathogens Eggerthella lenta and Hungatella hathewayi. Furthermore, the oral pathogen Scardovia wiggsiae was more abundant in the oropharyngeal swabs of COVID-19 patients who died. The abundance of both H. hathewayi and S. wiggsiae correlated with circulating inflammatory markers including IL-6, highlighting the possible role of the microbiome in COVID-19 severity, and providing potential therapeutic targets for managing COVID-19.

microbiology↗