Biology subjects

Cooper, G.

Publications and source records attributed to Cooper, G..

16 recordsLinked to original sources

bioRxiv2026

Atypical T cell receptor signalling permits distinct gut gd T cell responses to healthy versus dysregulated tissues

Intraepithelial lymphocytes (IEL) are conserved across vertebrates and commonly enriched in {gamma}{delta} T cells. Several such {gamma}{delta} IELs depend upon homeostatic interactions of their T cell receptors (TCRs) with butyrophilin-like (BTNL) proteins expressed by healthy enterocytes and colonocytes. What limits such interactions from inducing full-blown T cell activation which would disrupt barrier integrity is unknown. Here, using primary IEL, we describe an atypical TCR signalling pathway (Signal 1) downstream of BTNL engagement, that fails to activate either global protein synthesis or cell proliferation. This attenuation could be overcome by provision of a co-stimulator (Signal 2) or inflammatory cytokines (Signal 3). It could also be relieved cell-intrinsically by blocking a lipid phosphatase. These findings can, at least in part, explain how extrinsic and intrinsic regulators permit IEL to be constitutively active in healthy tissues and additionally make full-blown responses to adaptive TCR ligands during tissue perturbation.

immunology↗

bioRxiv2026

Language-associated brain representations covary with disruption of selfhood under psilocybin

Language helps organise experience into an idiosyncratic, temporally extended sense of self. We therefore used fMRI to investigate whether greater similarity between participants in the activity of language-associated brain regions accompanied psilocybin-induced loss of selfhood. Participants heard music and viewed moving clouds at baseline and after 19 mg psilocybin. At each brain location and time point, we tested whether similarity increased with each pair's summed rank on the Ego Dissolution Inventory (EDI; N=43). We grouped independent components of these associations by time course and decoded each group's map with Neurosynth. Elementary visual imagery (SI; N=49) and baseline activity served as comparators. Under psilocybin, one group formed a distributed, left-lateralised frontotemporal network matching the Neurosynth language map (r=.382, spatial-null p<.001, q=.003), nearly twice the largest comparator estimate (SI: r=.208, p=.004, q=.028; baseline: r<.12). In exploratory analyses, resting-state connectivity of this network decreased with posterior visual cortex and increased with thalamic and frontal regions. Participants with higher EDI scores showed larger changes (Spearman's rho=.455, Bonferroni-adjusted p=.048; SI: rho=.008), most strongly for items describing loss of ego or identity (rho=.43 to .51). We propose that language-associated systems incorporate each person's semantic and autobiographical context into experience, and that disrupting them contributes to loss of ego and identity.

neuroscience↗

bioRxiv2026

What is it like to be a blob? A distributed, decentred and context-sensitive neurobiology of consciousness

Consciousness is often studied by asking whether particular brain regions or systems are privileged. We tested a distributed, decentred and context-sensitive alternative using 579 consciousness-focused neuroimaging studies. Semantic clustering of titles and abstracts identified seven domains whose corrected meta-analytic maps showed limited overlap and no invariant cross-domain core. These maps occupied 18.0% of grey matter while extending across 91.0% of brain regions. After controlling for reporting topography, distributed cognitive, sensorimotor and organismic-affective maps reconstructed the residual consciousness landscape better than spatial surrogates. Organismic-affective maps contributed most, but functional contributions varied contextually across domains. Theory-associated regional loci added no additional meaningful prediction. Information carried by the functional families was both redundant and synergistic. Coactivation-network and hypergraph analyses revealed a shared network repertoire but context-dependent higher-order coalitions. These results argue against an invariant core, supporting a distributed neurobiology of consciousness in which specialised systems are weighted and combined differently across contexts.

neuroscience↗

bioRxiv2026

Proof-of-concept of targeted degradation of p38α/β MAPK host-kinase as a potent inhibitor of coronaviruses.

Host-targeting antivirals offer a promising strategy for combating emerging viral threats by targeting cellular pathways required for infection. The p38 mitogen-activated protein kinase (MAPK) pathway has been implicated as a host dependency factor exploited by multiple viruses, including coronaviruses, making it an attractive antiviral target. Here, we show for the first time that targeted degradation of p38 using the proteolysis-targeting chimera (PROTAC) NR-7h potently inhibits coronavirus infection. NR-7h induced substantial degradation of p38 in multiple cell lines and inhibited infection of two seasonal coronaviruses OC43 and 229E, providing broad pan-coronavirus activity. Infectious viral titres and viral RNA levels were significantly reduced without any detectable cytotoxicity. NR-7h exhibited greater antiviral potency than conventional p38 small-molecule inhibitors, with an IC50 of 1.0 nM compared with 648.4 nM for LY2228820, while the parent kinase inhibitor PH-797804 did not achieve 50% inhibition at the highest concentration tested. Pseudovirus and time-of-addition studies indicated that antiviral activity occurred at a post-entry stage of infection. Importantly, antiviral activity was eliminated by inhibition of proteasome function or E3 ligase activity, demonstrating dependence on PROTAC-mediated degradation. Our findings provide a proof-of-concept that targeted degradation of host kinase p38 can function as an antiviral modality and suggest PROTAC-based host-directed therapeutics may offer advantages over conventional kinase inhibition for broad-spectrum antiviral development.

microbiology↗

bioRxiv2026

Sympathetic innervation regulates metabolic flexibility of skeletal muscle

The sympathetic nervous system (SNS) is recognized for its role in the physiological regulation of organs, such as heart, vasculature and lungs, and has emerged as a potential player in skeletal muscle metabolic and neuromuscular junction (NMJ) health. However, the mechanism through which SNS signaling influences skeletal muscle function and adaptation to exercise remains unclear. Using molecular, electrophysiological, immunohistochemical, and high-resolution respirometry techniques, we tested the role of sympathetic innervation to skeletal muscle in response to exercise. Our findings reveal that sympathetic denervation disrupts the NMJ, reducing motor and sympathetic receptor expression, with concomitant deficits in skeletal muscle function. Mechanistically, these deficits are linked to diminished CPT1 enzyme activity, which impairs long-chain fatty acid-mediated oxidation in skeletal muscle mitochondria. These findings reveal a key role for sympathetic innervation in maintaining mitochondrial metabolic function and by extension, skeletal muscle performance, offering novel insight into the interplay between the SNS, exercise, and muscle mitochondria.

cell biology↗

bioRxiv2025

Identification and characterization of host-modulating effectors encoded by the Cluster F1 mycobacteriophage NormanBulbieJr

NormanBulbieJr (NBJ) is a temperate siphovirus isolated on the host Mycobacterium smegmatis mc2155 that encodes 102 gene products, 60 of which have no known function (NKF). Based on gene content, NBJ is classified as a Cluster F, Subcluster F1 phage and shares 70% of its encoded gene phamilies with Girr, another F1 mycobacteriophage that was recently analyzed in a genome-wide overexpression screen and found to encode 29 diverse gene products capable of inhibiting growth of M. smegmatis. Similar functional screens in other mycobacteriophages have uncovered a growing repertoire of diverse, phage-encoded bacterial growth inhibitors, providing prime candidates for dissecting novel bacterial-phage interactions. An arrayed overexpression library encoding all 102 genes was constructed and systematically screened using a plate-based cytotoxicity assay, identifying 29 genes that inhibit mycobacterial growth. Because mycobacteriophage genomes are also known to encode systems involved in phage-phage competition, we conducted additional phage defense assays for a subset of NBJ genes in our library. This analysis confirmed homotypic immunity by the predicted immunity repressor and identified gp45 as a second defense factor that protects against Cluster F phages and promotes NBJ lysogen stability. Additional mechanistic analyses indicate that gp45 functions in a secretion-dependent manner, acting after phage adsorption to reduce productive infection and early phage transcript accumulation. Escape mutant and bacterial two-hybrid analyses implicate Cluster F tape measure proteins as the likely target of gp45, consistent with disruption of an early step in phage genome delivery. Finally, we extended our analysis to explore the essentiality of all identified host-modulating genes in the NBJ life cycle, using CRISPR-enhanced recombineering to generate phage deletion mutants, revealing two host modulators that are critical for lytic growth. Conducted as part of the SEA-GENES undergraduate research consortium, this study adds to a growing functional genomics resource and provides new insights into the complex interactions between phage gene products and the mycobacterial host cell.

microbiology↗

bioRxiv2025

Elevated urea levels in human frontotemporal dementia and amyotrophic lateral sclerosis post-mortem brain tissue: Evidence of a multi-dementia pathogenic mechanism

1Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) represent two neurodegenerative diseases on opposite sides of a movement disorder continuum. However, like many other neurodegenerative diseases, the molecular pathogenesis of FTD and ALS is not fully understood. Our group has previously reported evidence for a pervasive elevation of brain urea levels in five other dementia-causing diseases. However, brain urea levels have yet to be measured in ALS and FTD. Here, we employed ultra-high-performance liquid chromatography-tandem mass spectrometry to characterise brain urea differences between control (n=14/12) and ALS/FTD (FTD: n=8/9; ALS: n=13/14) cases in post-mortem tissue from two brain regions with different levels of neuropathological burden (high vs. low). Elevated urea levels were observed in both the frontal cortex (high neuropathological burden) and primary visual cortex (low neuropathological burden) in cases with FTD. Contrastingly, in cases with ALS, elevated urea was observed in the primary motor cortex (high neuropathological burden), but not the dentate nucleus (low neuropathological burden). These results not only suggest that elevated urea levels are also present in ALS and FTD but imply that elevated brain urea is linked to a multi-dementia pathogenic mechanism. In contrast to ALS, the observation of elevated urea in regions of both high and low neuropathological burden in FTD implies that this phenotype is likely widespread and, therefore, may play a larger role in the pathogenesis of disease. Such a mechanism could offer new directions for developing treatments targeting this underlying pathology.

neuroscience↗

bioRxiv2025

Causal Modeling Reveals Cell-Cell Communication Dynamics in the Tumor Microenvironment During Anti-PD-1 Therapy in Breast Cancer Patients

BackgroundImmune checkpoint blockade (ICB) targeting PD-1/PD-L1 plays a crucial role in breast cancer treatment. Despite clinical success, how ICB reshapes the tumor microenvironment (TME) to enhance anti-tumor activity remains unclear. Anti-PD-1 therapy alters TME cells beyond PD-1+ T cells, with extensive cell-cell communication (CCC) playing a key role. Understanding the dynamic CCC changes upon anti-PD-1 treatment can illuminate ICB mechanisms of action and TME dynamics. MethodsWe analyzed single-cell RNA-seq data from 31 breast cancer patients before and after anti-PD-1 (pembrolizumab) treatment (Bassez et al., 2021). We identified differentially expressed genes (DEGs) induced by treatment in major cell types. We then applied an instrumental variable approach to uncover causal relationships between T-cell and non-T-cell DEGs. We further mapped ligand-receptor interactions mediating signal transduction between cells and constructed a CCC network from T to non-T cells. ResultsAnti-PD-1 therapy induced widespread transcriptional changes across multiple cell populations. Key pathways modulated in T cells included NF-{kappa}B, interferon-{gamma}, and interleukin signaling. CD4+ and CD8+ exhausted T cells engaged in distinct ligand-receptor interactions with tumor-associated macrophages (TAMs) and other types of cells, reshaping the TME. Our results indicated CD4+ exhausted T cells activated M1-like TAMs via TNF-TNFRSF1A and TNFSF14-LTBR, while CD8+ exhausted T cells engaged M1-like TAMs through ICAM1-ITGAL/ITGB2 and CCL8-CCR2, promoting anti-tumor immunity. Conversely, immunosuppressive interactions were also observed, such as TNF-TNFRSF1B (TNFR2) and TNFSF14-TNFRSF14 (HVEM) from CD4 T cells, as well as CSF1-CSF1R and RPS19-C5AR1 from CD8 T cells, which likely promote M2-like tumor-associated macrophage (TAM) polarization and contribute to pro-tumor immune regulation and resistance to therapy. Notably, key receptors in the causal CCC networks, such as C5AR1, TNFR2, and CSF1R, emerged as potential targets to enhance anti-PD-1 efficacy. ConclusionsThese findings elucidate TME remodeling during anti-PD-1 therapy and underscore the pivotal role of CCC in treatment response. Our study identifies critical communication networks that may be biomarkers for immunotherapy responsiveness and highlights novel therapeutic targets, including C5AR1 and HVEM. Furthermore, our application of causal inference methodologies provides a robust framework for dissecting CCC mechanisms in immunotherapy.

bioinformatics↗

bioRxiv2025

Inferring Personalized Cell-Cell Communication Networks in Colorectal Cancer with Individualized Causal Discovery

Understanding tumor heterogeneity at the resolution of individualized cell-cell communication networks (CCCNs) remains a major computational challenge in precision oncology. Existing inference methods largely rely on population-level correlation and thus fail to capture patient-specific signaling patterns across diverse cell types. To address this limitation, we developed an integrative computational framework combining the nested hierarchical Dirichlet process (nHDP) model for identifying hierarchically structured gene expression modules, with instance-specific Greedy Fast Causal Inference (iGFCI) for inferring individualized CCCNs (iCCCNs) in colorectal cancer (CRC). Applied to large-scale single-cell RNA-seq data from over 625,000 cells, our model successfully decomposed complex gene expression modules GEMs, potentially representing the cell lineage and cellular signaling states, and uncovered iCCCNs across detailed cell subtypes. We further used TCGA bulk RNA-seq data with survival data to validate the clinical relevance of these individualized gene expression module causal interactions, demonstrating their potential as robust prognostic signatures in CRC. Finally, we used principled causal inference methods to search for ligand-receptor pairs that mediate cell-cell communication. This framework enables mechanistic insights into immune evasion. Our computational method represents a significant advance toward realizing personalized oncology, enabling precise patient stratification and identification of actionable biomarkers for improved therapeutic targeting in cancers.

bioinformatics↗

bioRxiv2025

Proteasome mutations associated with CANDLE syndrome cause altered neuronal development by dysregulating polyamine synthesis

Genetic mutations affecting proteasome function can result in multi-organ diseases, such as Chronic atypical neutrophilic dermatosis with lipodystrophy and elevated temperature (CANDLE) syndrome. Neurological symptoms associated with CANDLE suggest that proteasomal mutations may impact neuronal development and/or function. We generated cerebral organoids (COs) from CANDLE patient induced pluripotent stem cells (iPSCs), which exhibited impaired neuronal development when compared to COs from healthy control iPSCs. Impaired neuronal maturation in CANDLE COs was correlated with increased polyamines, which were also elevated in CANDLE patient CSF. The proteasome-regulated Ornithine decarboxylase (ODC), a rate limiting enzyme for polyamines, was elevated in CANDLE neurons. Inhibition of ODC reversed polyamine overproduction and repaired neuronal maturation in CANDLE COs, suggesting a potential therapeutic avenue for intervention. These findings demonstrate that dysfunction of the proteasome affects neuronal development through overproduction of polyamines via dysregulation of ODC and offer insight into potential therapeutic strategies for CNS-related proteasomal dysfunction.

neuroscience↗

bioRxiv2025

Vascular endothelial growth factor receptors 1 and 3 mediate placental trophoblast leptin production in preeclampsia, inducing vascular dysfunction

Heightened soluble FMS-like tyrosine kinase-1 (sFlt-1) levels is a hallmark of preeclampsia patients and induces a state of angiogenic imbalance by sequestering free vascular endothelial growth factor (VEGF) and placental growth factor (PlGF). The receptors for VEGF and PlGF, membrane-bound VEGFR, are expressed in placental trophoblast cells, but their functions are largely unknown. Placenta production of leptin significantly increases in preeclampsia, and we recently showed leptin induces placental and vascular endothelial dysfunction in pregnancy. We hypothesized that there is a mechanistic link in which inappropriately high sFlt-1 in preeclampsia leads to an increase in trophoblast leptin production. We treated human placental explants and trophoblast cells with sFlt-1 and show an increase in leptin peptide production, which is ablated by coadministration with either VEGF or placental growth factor (PLGF). We further demonstrate that VEGFR1 and 3, not R2, expressions are predominant in human trophoblasts and that reducing activation of these receptors mediates trophoblast leptin production. In pregnant mice, we show that sFlt-1 infusion induces vascular endothelial dysfunction in association with significantly elevated plasma leptin levels. In pregnant sFlt-1-infused mice treatment with leptin receptor antagonist significantly ablated vascular endothelial dysfunction. Collectively, these data indicate that angiogenic imbalance in preeclampsia impacts placental trophoblast endocrine function by suppressing VEGFR1 and 3 activation, resulting in leptin overproduction. Furthermore, sFlt-1 induces vascular endothelial dysfunction in mice dependent on leptin receptor activation.

physiology↗

bioRxiv2024

Metabolic Profiles of Encapsulated Chondrocytes Exposed to Short-Term Simulated Microgravity

The mechanism by which chondrocytes respond to reduced mechanical loading environments and the subsequent risk of developing osteoarthritis remains unclear. This is of particular concern for astronauts. In space the reduced joint loading forces during prolonged microgravity (10-6 g) exposure could lead to osteoarthritis (OA), compromising quality of life post-spaceflight. In this study, we encapsulated human chondrocytes in an agarose gel of similar stiffness to the pericellular matrix to mimic the cartilage microenvironment. We then exposed agarose-chondrocyte constructs to simulated microgravity (SM) using a rotating wall vessel (RWV) bioreactor to better assess the cartilage health risks associated with spaceflight. Global metabolomic profiling detected a total of 1205 metabolite features across all samples, with 497 significant metabolite features identified by ANOVA (FDR-corrected p-value < 0.05). Specific metabolic shifts detected in response to SM exposure resulted in clusters of co-regulated metabolites, as well as key metabolites identified by variable importance in projection scores. Microgravity-induced metabolic shifts in gel constructs and media were indicative of protein synthesis, energy metabolism, nucleotide metabolism, and oxidative catabolism. The microgravity associated-metabolic shifts were consistent with early osteoarthritic metabolomic profiles in human synovial fluid, which suggests that even short-term exposure to microgravity (or other reduced mechanical loading environments) may lead to the development of OA.

bioengineering↗

bioRxiv2024

Morphometrical asymmetries and tractography of speech-relevant cortex in relation to language lateralisation and rapid temporal processing

Differences in the functional roles of the left and right cortices for speech-related processes have been known since the findings of Broca [1] and Wernicke [2]. Nearly 100 years later anatomical asymmetries of speech-related cortex was emphasised as a potential substrate to such functional lateralisations [3]. Exploration of associations of anatomical asymmetries and functional lateralisations in speech has since continued, with developing technologies and theoretical insights mutually affording increasingly refined understandings. The present study is another such continuance; we outline and report associations of neuroanatomical (morphometrical) and connective (diffusion tractography) measures of speech-related cortex with differences of participant speech lateralisation and rapid temporal acuity (a hypothesised general auditory ability that contributes to superior speech processing). Review and support of developments in methodological approaches to morphometry and tractography to are also provided. Overall, our study affirms complex and selectively overlapping relationships of anatomy and connectivity (especially in the planum temporale) with behavioural language lateralisation and the processing of rapid temporal acoustics. Implications, limitations, and recommendations are discussed.

neuroscience↗

bioRxiv2021

Does the evolution of division of labour require accelerating returns from individual specialisation?

Recent theory has overturned the assumption that accelerating returns from individual specialisation are required to favour the evolution of division of labour. Yanni et al. (2020) showed that topologically constrained groups, where cells cooperate with only direct neighbours such as for filaments or branching growths, can evolve a reproductive division of labour even with diminishing returns from individual specialisation. We developed a conceptual framework and specific models to investigate the factors that can favour the initial evolution of reproductive division of labour. We found that selection for division of labour in topologically constrained groups: (1) is not a single mechanism to favour division of labour - depending upon details of the group structure, division of labour can be favoured for different reasons; (2) always involves an efficiency benefit at the level of group fitness; and (3) requires a mechanism of coordination to determine which individuals perform which tasks. Given that such coordination is unlikely to evolve before division of labour, this limits the extent to which topological constraints could have favoured the initial evolution of division of labour. We conclude by suggesting experimental designs that could determine why division of labour is favoured in the natural world.

evolutionary biology↗

bioRxiv2018

Systematic Discovery of the Functional Impact of Somatic Genome Alterations in Individual Tumors through Tumor-specific Causal Inference

We report a tumor-specific causal inference (TCI) framework, which discovers causative somatic genome alterations (SGAs) through inferring causal relationships between SGAs and molecular phenotypes (e.g., transcriptomic, proteomic, or metabolomic changes) within an individual tumor. We applied the TCI algorithm to tumors from The Cancer Genome Atlas (TCGA) and identified those SGAs that causally regulate the differentially expressed genes (DEGs) within each tumor. Overall, TCI identified 634 SGAs that cause cancer-related DEGs in a significant number of tumors, including most of the previously known drivers and many novel candidate cancer drivers. The inferred causal relationships are statistically robust and biologically sensible, and multiple lines of experimental evidence support the predicted functional impact of both well-known and novel candidate drivers. By identifying major candidate drivers and revealing their functional impact in a tumor, TCI shed light on disease mechanisms of each tumor, providing useful information for advancing cancer biology and precision oncology.\n\nSignificance statementsCancer is mainly caused by SGAs. Precision oncology involves identifying and targeting tumor-specific aberrations resulting from causative SGAs. TCI is a novel computational framework for discovering the causative SGAs and their impact on oncogenic processes, thus revealing tumor-specific disease mechanisms. This information can be used to guide precision oncology.

cancer biology↗

bioRxiv2017

Tumor-specific Causal Inference (TCI): A Bayesian Method for Identifying Causative Genome Alterations within Individual Tumors

Precision medicine for cancer involves identifying and targeting the somatic genome alterations (SGAs) that drive the development of an individual tumor. Much of current efforts at finding driver SGAs have involved identifying the genes that are mutated more frequently than expected among a collection of tumors. When these population-derived driver genes are altered (perhaps in particular ways) in a given tumor, they are posited as driver genes for that tumor. In this technical report, we introduce an alternative approach for identifying causative SGAs, also known as \"drivers\", by inferring causal relationships between SGAs and molecular phenotypes at the individual tumor level. Our tumor-specific causal inference (TCI) algorithm uses a Bayesian method to identify the SGAs in a given tumor that have a high probability of regulating transcriptomic changes observed in that specific tumor. Thus, the method is focused on identifying the tumor specific SGAs that are causing expression changes that are specific to the tumor. Those SGAs that have a high probability of regulating transcriptomic changes related to oncogenic processes are then designated to be the putative drivers of the tumor. In this paper, we describe in detail the TCI algorithm and its implementation.

bioinformatics↗