Biology subjects

Jackson, H.

Publications and source records attributed to Jackson, H..

9 recordsLinked to original sources

bioRxiv2025

Neuronal extracellular vesicles regulate axon development in primary cortical neurons via local miR-99a targeting of HS3ST2

Fully functional neural competence and integrity requires a complex array of communication means among neurons, with extracellular vesicles (EVs) emerging as a relevant mechanism for cell-cell interaction in the CNS. Despite the growing number of studies demonstrating the presence of microRNAs (miRNAs) in axon and EVs, the molecular mechanisms of those miRNAs present in EVs and their functional role in nervous system development has not been fully explored. In this study, we investigated whether neuronal EVs can have a role in neuron-to-neuron communication during the development of neuron connectivity in mouse primary cortical neuron cultures. Our results demonstrate how miR-99a can regulate axonal growth via its EV-mediated delivery and through the targeting of HS3ST2, a heparan sulphate glucosamine 3-O-sulphotransferase, which is predominantly expressed in the brain and generates rare 3-O-sulphated domains in heparan sulphate proteoglycans, with growing importance in development and neurodegenerative mechanisms. Importantly, we show how in compartmentalised microfluidic cultures, where axons are isolated from neuronal somas, the growth-promoting effects of neuron-derived EVs are local to the axon. These findings establish that neuronal EVs can deliver miRNAs to discrete subcellular domains to acutely modulate local gene expression, thereby driving axonal growth and shaping neurodevelopment.

neuroscience↗

bioRxiv2025

Multi-view deep learning of highly multiplexed imaging data improves association of cell states with clinical outcomes

Highly multiplexed imaging technologies can quantify the expression of 10s-100s of proteins and their modifications at sub-cellular resolution. Applications to tissue specimens across a broad array of pathologies have enabled patient subtyping in terms of novel cell states and spatial cell communities and linked their prevalence and overall architecture to patient outcomes. While highly multiplexed imaging analysis workflows typically summarize each cell in terms of its post-segmentation mean expression, additional cellular information can be quantified including cell morphology, sub-cellular expression patterns, and spatial cellular context, ultimately giving a multi-modal view of each cell. While deep latent variable models such as variational autoencoders (VAEs) are well established for other multi-modal single-cell assays, their ability to integrate these multiple views of a cell from highly multiplexed imaging data remains largely unknown. Here, we explore the abilities of multi-modal VAEs to learn unified latent cellular representations from multiple views of each single-cell quantified from highly multiplexed imaging, including mean expression, morphology, sub-cellular protein co-localization, and spatial cellular context, while conditioning on technical and batch specific effects. We first discuss strategies for training and hyperparameter optimization of such models across a set of highly multiplexed imaging datasets of breast and melanoma cancers. We next quantify the relevance of the integrated multi-modal latent space in predicting patient-specific clinical outcomes and demonstrate competitive performance across a range of outcomes compared to existing baselines. Then, we explore the ability of the cellular representations to learn cellular phenotypes that align with known cell types and find that the expression-specific latent representation can identify clusters more closely aligned with known lymphocyte and epithelial subpopulations compared to established workflows. Finally, we test the ability of each representation to perform consistent batch integration across different cohorts and discuss the considerations on taking known background variables into account.

bioinformatics↗

bioRxiv2025

Psychedelic-mediated Reversal of General Anesthesia and Restoration of Brain Dynamics in Rat

Serotonergic psychedelics enhance neurophysiological complexity and the repertoire of brain states, whereas general anesthetics produce opposite effects. Serotonergic psychedelics are also known to increase wakefulness and reduce sleep time in rodents. Therefore, we hypothesized that 2,5-dimethoxy-4-iodopamphetamine (DOI), a serotonergic psychedelic, will reverse general anesthesia and restore neurophysiological conditions associated with normal wakefulness. We demonstrate that intravenous administration of DOI in rats under general anesthesia induced wakefulness despite ongoing delivery of the anesthetics, propofol or isoflurane. Behavioral arousal was accompanied by recovery of directional and non-directional high gamma (125-165Hz) functional connectivity and restoration of functional brain network structure. These behavioral and neurophysiological effects were blocked by a 5-HT2A antagonist, volinanserin. Intravenous administration of a non-psychedelic 5-HT2A agonist, lisuride, failed to restore wakefulness or brain dynamics in anesthetized rats. To our knowledge, these results provide the first evidence of psychedelic-mediated reversal of general anesthesia and concurrent restoration of brain dynamics associated with normal wakefulness.

neuroscience↗

bioRxiv2021

Kawasaki Disease patient stratification and pathway analysis based on host transcriptomic and proteomic profiles

The aetiology of Kawasaki Disease (KD), an acute inflammatory disorder of childhood, remains unknown despite various triggers of KD having been proposed. Host omic profiles offer insights into the host response to infection and inflammation, with the interrogation of multiple omic levels in parallel providing a more comprehensive picture. We used differential abundance analysis, pathway analysis, clustering and classification techniques to explore whether the host response in KD is more similar to the response to bacterial or viral infection at the transcriptomic and proteomic levels through comparison of omic profiles from children with KD to those with bacterial and viral infections. Pathways activated in patients with KD included those involved in anti-viral and anti-bacterial responses. Unsupervised clustering showed that the majority of KD patients clustered with bacterial patients on both omic levels, whilst application of diagnostic signatures specific for bacterial and viral infections revealed that many transcriptomic KD samples had low probabilities of having bacterial or viral infections, suggesting that KD may be triggered by a different process not typical of either common bacterial or viral infections. Clustering based on the transcriptomic and proteomic responses during KD revealed three clusters of KD patients on both omic levels, suggesting heterogeneity within the inflammatory response during KD. The observed heterogeneity may reflect differences in the host response to a common trigger, or variation dependent on different triggers of the condition.

bioinformatics↗

bioRxiv2021

Single-Cell Proteomics Defines the Cellular Heterogeneity of Localized Prostate Cancer

Localized prostate cancer exhibits multiple genomic alterations and heterogeneity at the proteomic level. Single-cell technologies capture important cell-to-cell variability responsible for heterogeneity in biomarker expression that may be overlooked when molecular alterations are based on bulk tissue samples. The aim of this study was to identify novel prognostic biomarkers and describe the heterogeneity of prostate cancer and the associated immune cell infiltrates by simultaneously quantifying 36 proteins using single-cell mass cytometry analysis of over 1,6 million cells from 58 men with localized prostate cancer. To perform this task, we proposed a novel computational pipeline, Franken, which showed unprecedented combination of performance, sensitivity and scalability for high dimensional clustering compared to state of the art methods. We were able to describe subpopulations of immune, stromal, and prostate cells, including unique changes occurring in tumor tissues and high grade disease providing insights into the coordinated progression of prostate cancer. Our results further indicated that men with localized disease already harbor rare subpopulations that typically occur in castration-resistant and metastatic disease, which were confirmed through imaging. Our methodology could be used to discover novel prognostic biomarkers to personalize treatment and improve outcomes.

cancer biology↗

bioRxiv2019

A novel mouse model expressing human forms for complement receptors CR1 and CR2

The complement cascade is increasingly implicated in development of a variety of diseases with strong immune contributions such as Alzheimers disease and Systemic Lupus Erythematosus. Mouse models have been used to determine function of central components of the complement cascade such as C1q and C3. However, species differences in their gene structures mean that mice do not adequately replicate human complement regulators, including CR1 and CR2. Genetic variation in CR1 and CR2 have been implicated in modifying disease states but the mechanisms are not known. To decipher the roles of human CR1 and CR2 in health and disease, we engineered C57BL/6J (B6) mice to replace endogenous murine Cr2 with human complement receptors, CR1 and CR2 (B6.CR2CR1). CR1 has an array of allotypes in human populations and using traditional recombination methods (Flp-frt and Cre-loxP) two of the most common alleles (referred to as CR1long and CR1short) are replicated within this mouse model, along with a CR1 knockout allele (CR1KO). Transcriptional profiling of spleens and brains identifies genes and pathways differentially expressed between mice homozygous for either CR1long, CR1short or CR1KO. Gene set enrichment analysis predicts hematopoietic cell number and cell infiltration are modulated by CR1long, but not CR1short or CR1KO. Therefore, this mouse model provides a novel tool for determining the relationship between human-relevant CR1 alleles and disease. Summary StatementWe present the creation and validation of a novel mouse model that expresses human forms of complement cascade regulators CR1 and CR2.

genetics↗

bioRxiv2019

Staging Alzheimer’s disease in the brain and retina of B6.APP/PS1 mice by transcriptional profiling

Alzheimers disease (AD) is a common form of dementia characterized by amyloid plaque deposition, TAU pathology, neuroinflammation and neurodegeneration. Mouse models recapitulate some key features of AD. For instance, the B6.APP/PS1 model (carrying human transgenes for mutant forms of APP and PSEN1) shows plaque deposition and associated neuroinflammatory responses involving both astrocytes and microglia beginning around 6 months of age. However, in our colony, TAU pathology, significant neurodegeneration and cognitive decline are not apparent in this model even at older ages. Therefore, this model is ideal for studying neuroinflammatory responses to amyloid deposition. Here, RNA sequencing of brain and retinal tissue, generalized linear modeling (GLM), functional annotation followed by validation by immunofluorescence (IF) was performed in B6.APP/PS1 mice to determine the earliest molecular changes prior to and around the onset of plaque deposition (2-6 months of age). Multiple pathways were shown to be activated in response to amyloid deposition including the JAK/STAT and NALFD pathways. Putative, cell-specific targets of STAT3, a central component of the JAK/STAT pathway, were identified that we propose provide more precise options for assessing the potential for targeting activation of the JAK/STAT pathway as a treatment for human AD. In the retina, GLM predicted activation of vascular-related pathways. However, many of the gene expression changes comparing B6 with B6.APP/PS1 retina samples occurred prior to plaque onset (2 months of age). This suggests retinal changes in B6.APP/PS1 mice may be an artefact of overexpression of mutant forms of APP and PSEN1 providing limited translatability to human AD. Therefore, caution should be taken when using this mouse model to assess the potential of using the eye as a window to the brain for AD.

neuroscience↗

bioRxiv2019

Regulation of neuron-specific gene transcription by stress hormone signalling requires synaptic activity in zebrafish

The Glucocorticoid Receptor (GR) co-ordinates metabolic and behavioural responses to stressors. We hypothesised that GR influences behaviour by modulating specific epigenetic and transcriptional processes in the brain. Using the zebrafish as a model organism, the brain methylomes of wild-type and grs357 mutant adults were analysed and GR-sensitive, differentially methylated regions (GR-DMRs) were identified. Two genes with GR-DMRs exhibited distinct methylation and transcriptional sensitivities to GR: the widely expressed direct GR target fkbp5 and neuron-specific aplp1. In larvae, neural activity is required for GR-mediated transcription of aplp1, but not for that of fkbp5. GR regulates metabotropic glutamate receptor gene expression, the activities of which also modulated aplp1 expression, implicating synaptic neurotransmission as an effector of GR function upstream of aplp1. Our results identify two distinct routes of GR-regulated transcription in the brain, including a pathway through which GR couples endocrine signalling to synaptic activity-regulated transcription by modulating metabotropic glutamate receptor expression.

developmental biology↗

bioRxiv2019

Viral and bacterial infection elicit distinct changes in plasma lipids in febrile children

Fever is the most common reason that children present to Emergency Departments in the UK. Clinical signs and symptoms suggestive of bacterial infection are often non-specific, and there is no definitive test for the accurate diagnosis of infection. As a result, many children are prescribed antibiotics often unnecessarily, while others with life-threatening bacterial infections can remain untreated. The omics approaches to identifying biomarkers from the host-response to bacterial infection are promising. In this study, lipidomic analysis was carried out with plasma samples obtained from febrile children with confirmed bacterial infection (n=20) and confirmed viral infection (n=20). We show for the first time that bacterial and viral infection elicit distinct changes in the host lipidome. Glycerophosphoinositol, sphingomyelin, lysophosphotidylcholine and cholesterol sulfate were increased in the confirmed virus infected group, while fatty acids, glycerophosphocholine, glycerophosphoserine, lactosylceramide and bilirubin were increased in cases with confirmed bacterial infection. A combination of three lipids achieved the area under the receiver operating characteristic (ROC) curve of 0.918 (95% CI 0.835 to 1). This pilot study demonstrates the potential of metabolic biomarkers to assist clinicians in distinguishing bacterial from viral infection in febrile children, to facilitate effective clinical management and to the limit inappropriate use of antibiotics.

systems biology↗