Biology subjects

Ferguson, A.

Publications and source records attributed to Ferguson, A..

15 recordsLinked to original sources

bioRxiv2026

Microdomes: Micro-engineered Microdome arrays enable standardised and shear-free 3D biology with full-spectrum optical imaging compatibility

Three-dimensional cellular models such as organoids and spheroids hold major promise for developmental biology, disease modelling and precision medicine, yet their large-scale production and analysis remain constrained by handling-induced shear stress, sample fragility, positional instability and limited compatibility with advanced imaging workflows. Here, we introduce Microdomes, dense arrays of open-top, dome-shaped microcavities. Each cavity holds a single specimen in its own miniature aquarium, accessed through a narrow apical opening that admits cells, medium, matrix and staining reagents while shielding it from the shear generated during routine pipetting. Each Microdomes chip accommodates more than 100 spheroids or organoids, supporting diverse cell types, co-culture formats and both matrix-free and matrix-embedded culture. All specimens are retained through prolonged culture, repeated medium exchange, fixation and immunostaining. Because every specimen occupies a fixed, addressable position against a thin transparent film, the same spheroid can be relocated and re-imaged over weeks of culture and across microscopes, from array-wide overviews to subcellular details, without transfer, embedding or other perturbation. Microdomes also support AI-based automated segmentation, from whole-spheroid outlines to individual nuclei in 3D, using common image analysis software. Microdomes thereby turn each array into a self-contained quality control unit, providing specimen-level traceability that organoid production pipelines currently lack.

cell biology↗

bioRxiv2026

An open multimodal spatial resource integrating same-tissue transcriptomics, proteomics, and histology

Spatial transcriptomic and proteomic technologies provide complementary insights into tissue organisation, cellular phenotype and function, yet integrating these modalities on the same tissue section remains technically challenging. Sequential workflows must preserve RNA integrity, antigenicity and tissue morphology while maintaining accurate spatial registration. At present, publicly available multimodal datasets suitable for computational method development remain limited. Here, we present a workflow for sequential 10x Genomics Xenium spatial transcriptomics, COMET cyclic immunofluorescence, and haematoxylin and eosin (H&E) histological staining on the same formalin-fixed paraffin-embedded tissue section. We demonstrate this approach across multiple biologically distinct human tissues, including tonsil, hepatocellular adenoma, and matched tumour and non-tumour hepatocellular carcinoma, illustrating the widespread applicability of the workflow beyond a single tissue type. Following image registration, Xenium-derived cell segmentations were applied to protein images to generate integrated single-cell transcriptomic and proteomic measurements for downstream analyses. To facilitate community reuse, we publicly release four representative aligned tissue cores together with transcript coordinates, multiplex protein images, H&E images, cell segmentations, and integrated single-cell datasets. We additionally introduce UnumLocalia, an open-source visualisation and data extraction tool that enables interactive exploration of aligned multimodal images, supports user-defined cell segmentation, and allows export of integrated single-cell data for downstream analyses. Together, this technical protocol, workflow, software, and openly available dataset provide a reusable resource for multimodal spatial biology, supporting advances in biological discovery, computational method development, multimodal data integration, and validation of emerging analytical approaches across complementary spatial technologies.

immunology↗

bioRxiv2026

Historic and contemporary museum specimens implicate Northern Red-backed Vole (Clethrionomys rutilus) as borealpox host as early as 1990s

Borealpox virus (BRPV; formerly Alaskapox) is an orthopoxvirus that has caused seven reported human infections in Alaska since 2015, including a fatal case in 2023. The natural reservoir of BRPV is unknown, although previous investigations have raised the possibility of wild small mammals transmitting the virus to humans, either through direct contact or via domestic cats and dogs. To understand which species may be involved in the maintenance and/or spillover of BRPV in Alaska, we trapped and sampled wild small mammals (including voles, shrews, and squirrels) in 2021 and 2024 near reported human case locations in Fairbanks and the Kenai Peninsula, respectively. We found evidence of previous exposure to orthopoxviruses in five species (including the House Mouse, Mus musculus) and detected BRPV DNA as well as viable virus in Northern Red-backed Voles (Clethrionomys rutilus). Further, screening of tissues from historical museum specimens revealed BRPV DNA in C. rutilus specimens collected in Denali National Park and Preserve in 1998 and 1999, 17 years before the first reported human case of BRPV. Phylogenomic analysis of all human and animal BRPV isolates strongly supports the hypothesis of local human infections through multiple spillover events. These findings suggest C. rutilus as a possible reservoir species for BRPV and indicate that BRPV has been present in Alaskan wild small-mammal populations for at least 25 years. Our study highlights the potential of museum collections to elucidate the temporal, spatial, and host ranges of emerging pathogens. Further museum- and field-based sampling will clarify the true geographic range of BRPV, which is closely related to Old World orthopoxviruses and may be circulating beyond North America.

ecology↗

bioRxiv2023

ProtWave-VAE: Integrating autoregressive sampling with latent-based inference for data-driven protein design

Deep generative models (DGMs) have shown great success in the understanding of data-driven design of proteins. Variational autoencoders (VAEs) are a popular DGM approach that can learn the correlated patterns of amino acid mutations within a multiple sequence alignment (MSA) of protein sequences and distill this information into a low-dimensional latent space to expose phylogenetic and functional relationships and guide generative protein design. Autoregressive (AR) models are another popular DGM approach that typically lack a low-dimensional latent embedding but do not require training sequences to be aligned into an MSA and enable the design of variable length proteins. In this work, we propose ProtWave-VAE as a novel and lightweight DGM employing an information maximizing VAE with a dilated convolution encoder and autoregressive WaveNet decoder. This architecture blends the strengths of the VAE and AR paradigms in enabling training over unaligned sequence data and the conditional generative design of variable length sequences from an interpretable low-dimensional learned latent space. We evaluate the models ability to infer patterns and design rules within alignment-free homologous protein family sequences and to design novel synthetic proteins in four diverse protein families. We show that our model can infer meaningful functional and phylogenetic embeddings within latent spaces and make highly accurate predictions within semi-supervised downstream fitness prediction tasks. In an application to the C-terminal SH3 domain in the Sho1 transmembrane osmosensing receptor in bakers yeast, we subject ProtWave-VAE designed sequences to experimental gene synthesis and select-seq assays for osmosensing function to show that the model enables de novo generative design, conditional C-terminus diversification, and engineering of osmosensing function into SH3 paralogs.

synthetic biology↗

bioRxiv2022

Didemnin B and ternatin-4 inhibit conformational changes in eEF1A required for aminoacyl-tRNA accommodation into mammalian ribosomes

Rapid and accurate mRNA translation requires efficient codon-dependent delivery of the correct aminoacyl-tRNA (aa-tRNA) to the ribosomal A site. In mammals, this fidelity-determining reaction is facilitated by the GTPase elongation factor-1 alpha (eEF1A), which escorts aa-tRNA as an eEF1A(GTP)-aa-tRNA ternary complex into the ribosome. Two structurally unrelated cyclic peptides didemnin B and ternatin-4 bind to the eEF1A(GTP)-aa-tRNA ternary complex and inhibit translation. Here, we employ single-molecule fluorescence imaging and cryogenic electron microscopy to determine how these natural products inhibit translational elongation on mammalian ribosomes. By binding to a common allosteric site on eEF1A, didemnin B and ternatin-4 trap eEF1A in its GTPase-activated conformation, preventing aa-tRNA accommodation on the ribosome. We also show that didemnin B and ternatin-4 exhibit distinct effects on aa-tRNA selection that inform on observed disparities in their inhibition efficacies and physiological impacts. These integrated findings highlight the potential of single-molecule methods to reveal how distinct natural products differentially impact the human translation mechanism.

biochemistry↗

bioRxiv2020

A single dose, BCG-adjuvanted SARS-CoV-2 vaccine induces Th1-polarized immunity and high-titre neutralizing antibodies in mice

Global control of COVID-19 requires broadly accessible vaccines that are effective against SARS-CoV-2 variants. In this report, we exploit the immunostimulatory properties of bacille Calmette-Guerin (BCG), the existing tuberculosis vaccine, to deliver a vaccination regimen with potent SARS-CoV-2-specific protective immunity. Combination of BCG with a stabilized, trimeric form of SARS-CoV-2 spike antigen promoted rapid development of virus-specific IgG antibodies in the blood of vaccinated mice, that was further augmented by the addition of alum. This vaccine formulation, BCG:CoVac, induced high-titre SARS-CoV-2 neutralizing antibodies (NAbs) and Th1-biased cytokine release by vaccine-specific T cells, which correlated with the early emergence of T follicular helper cells in local lymph nodes and heightened levels of antigen-specific plasma B cells after vaccination. Vaccination of K18-hACE2 mice with a single dose of BCG:CoVac almost completely abrogated disease after SARS-CoV-2 challenge, with minimal inflammation and no detectable virus in the lungs of infected animals. Boosting BCG:CoVac-primed mice with a heterologous vaccine further increased SARS-CoV-2-specific antibody responses, which effectively neutralized B.1.1.7 and B.1.351 SARS-CoV-2 variants of concern. These findings demonstrate the potential for BCG-based vaccination to protect against major SARS-CoV-2 variants circulating globally.

microbiology↗

bioRxiv2020

The Genomic Landscape of Prostate Cancer Brain Metastases

Lethal prostate cancer commonly metastasizes to bone, lymph nodes, and visceral organs but with more effective therapies, there is an increased frequency of metastases to the brain. Little is known about the genomic drivers of prostate cancer brain metastases (PCBM). To address this, we conducted a comprehensive multi-regional, genomic, and targeted transcriptomic analysis of PCBM from 28 patients. We compared whole-exome and targeted RNA sequencing with matched primary tumors when available (n = 10) and with publicly available genomic data from non-brain prostate cancer metastases (n = 416). In addition to common alterations in TP53, AR, RB1, and PTEN, we identified highly significant enrichment of mutations in NF1 (25% cases (6/28), q = 0.049, 95% CI = 2.38 - 26.52, OR = 8.37) and RICTOR (17.9% cases (5/28), q = 0.01, 95% CI = 6.74 - 480.15, OR = 43.7) in PCBM compared to non-brain prostate cancer metastases, suggesting possible activation of the druggable pathways RAS/RAF/MEK/ERK and PI3K/AKT/mTOR, respectively. Compared to non-brain prostate cancer metastases, PCBM were almost three times as likely to harbor DNA homologous repair (HR) alterations (42.9% cases (12/28), p =0.016, 95% CI = 1.17 - 6.64, OR = 2.8). When considering the combination of somatic mutations, copy number alteration, and Large-scale State Transitions, 64.3% of patients (18/28) were affected. HR alterations may be critical drivers of brain metastasis that potentially provide cancer cells a survival advantage during re-establishment in a special microenvironment. We demonstrate that PCBM have genomic dependencies that may be exploitable through clinical interventions including PARP inhibition.

cancer biology↗

bioRxiv2020

Development of a Novel Class of Self-Assembling dsRNA Cancer Therapeutics: a Proof of Concept Investigation

Cancer has proven to be an extremely difficult challenge to treat. Several fundamental issues currently underlie cancer treatment including differentiating self from non-self, functional coupling of the recognition and therapeutic components of various therapies, and the propensity of cancerous cells to develop resistance to common treatment modalities via evolutionary pressure. Given these limitations, there is an increasing need to develop an all-encompassing therapeutic that can uniquely target malignant cells, decouple recognition from treatment, and overcome evolutionarily driven cancer resistance. We describe herein, a new class of programmable self-assembling dsRNA-based cancer therapeutics, that uniquely targets aberrant genetic sequences, and in a functionally decoupled manner, undergoes oncogenic RNA activated displacement (ORAD), initiating a therapeutic cascade that induces apoptosis and immune activation. As a proof-of-concept, we show that RNA strands targeting the EWS/Fli1 fusion gene in Ewing Sarcoma cells that are end-blocked with phosphorothioate bonds and additionally sealed with a 2-U modified DNA protector can be used to induce specific and potent killing of cells containing the target oncogenic sequence, but not wildtype.

bioengineering↗

bioRxiv2019

Carotid intima-media thickness in UK Biobank: Identification of novel genome-wide loci, sex-specific effects and genetic correlations with obesity and glucometabolic traits.

ObjectivesAtherosclerosis is the underlying cause of most cardiovascular disease, but mechanisms underlying atherosclerosis are incompletely understood. Ultra-sound measurement of the carotid artery intima-media thickness (cIMT) can be used to measure vascular remodelling, which is indicative of atherosclerosis. Genome-wide association studies have identified a number of genetic loci associated with cIMT, but heterogeneity of measurements collected by many small cohorts have been a major limitation in these efforts. Here we conducted genome-wide association analyses in UK Biobank (N=22,179), the largest single study with consistent cIMT measurements.\n\nApproach and resultsWe used BOLT-LMM to run linear regression of cIMT in UK Biobank, adjusted for age, sex, genotyping platform and population structure. In white British participants, we identified 4 novel loci associated with cIMT and replicated most previously reported loci. In the first sex-specific analyses of cIMT, we identified a female-specific locus on Chromosome 5, associated with cIMT in women only and highlight VCAN as a good candidate gene at this locus. Genetic correlations with body-mass index and glucometabolic traits were also observed.\n\nConclusionThese findings replicate previously reported associations, highlight novel biology and provide new directions for investigating the sex differences observed in cardiovascular disease presentation and progression.

genetics↗

bioRxiv2019

The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function.

Genome-wide association studies (GWAS) of psychiatric phenotypes have tended to focus on categorical diagnoses, but to understand the biology of mental illness it may be more useful to study traits which cut across traditional boundaries. Here we report the results of a GWAS of mood instability (MI) as a trait in a large population cohort (UK Biobank, n=363,705). We also assess the clinical and biological relevance of the findings, including whether genetic associations show enrichment for nervous system pathways. Forty six unique loci associated with MI were identified with a heritability estimate of 9%. Linkage Disequilibrium Score Regression (LDSR) analyses identified genetic correlations with Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizophrenia (SZ), anxiety and Post Traumatic Stress Disorder (PTSD). Gene-level and gene set analyses identified total 244 significant genes and 6 enriched gene sets. Tissue expression analysis from the SNP level data found enrichment in multiple brain regions, and eQTL analyses highlighted an inversion on chromosome 17 plus two brain-specific eQTLs. Additionally, we used a Phenotype Linkage Network (PLN) analysis and community analysis to assess for enrichment of nervous system gene sets using mouse orthologue databases. The PLN analysis found enrichment in nervous system PLNs for a community containing serotonin and melatonin receptors. In summary, this work has identified novel loci, tissues, and gene sets contributing to MI as a normal trait and will inform future work on the biology of mood and psychotic disorders, and to point the way towards potential for new stratified medicine approaches and the identification of novel trans-diagnostic drug targets.

genetics↗

bioRxiv2018

Genome-wide Association Study of Multisite Chronic Pain in UK Biobank

Chronic pain is highly prevalent worldwide, contributing a significant socioeconomic and public health burden. Several aspects of chronic pain, for example back pain and a severity-related phenotype, chronic pain grade, have been shown to be complex, heritable traits with a polygenic component. Additional pain-related phenotypes capturing aspects of an individuals overall sensitivity to experiencing and reporting chronic pain have also been suggested. We have here made use of a measure of the number of sites of chronic pain in individuals within the general UK population. This measure, termed Multisite Chronic Pain (MCP), is also a complex trait, but its genetic architecture has not previously been investigated. To address this, a large-scale genome-wide association study (GWAS) of MCP was carried out in ~380,000 UK Biobank participants to identify associated genetic variants. Findings were consistent with MCP having a significant polygenic component with a SNP heritability of 10.2%, and 76 independent lead single nucleotide polymorphisms (SNPs) at 39 risk loci were identified. Additional gene-level association analyses identified neurogenesis, synaptic plasticity, nervous system development, cell-cycle progression and apoptosis genes as being enriched for genetic association with MCP. Genetic correlations were observed between MCP and a range of psychiatric, autoimmune and anthropometric traits including major depressive disorder (MDD), asthma and BMI. Furthermore, in Mendelian randomisation (MR) analyses a bi-directional causal relationship was observed between MCP and MDD. A polygenic risk score (PRS) for MCP was found to significantly predict chronic widespread pain (pain all over the body), indicating the existence of genetic variants contributing to both of these pain phenotypes. These findings support the proposition that chronic pain involves a strong nervous system component and have implications for our understanding of the physiology of chronic pain and for the development of novel treatment strategies.

genetics↗

bioRxiv2018

Novel genome-wide associations for suicidality in UK Biobank, genetic correlation with psychiatric disorders and polygenic association with completed suicide.

AbstractBackground: Suicide is a major issue for global public health. Suicidality describes a broad clinical spectrum of thoughts and behaviours, some of which are common in the general population.\n\nMethods: UK Biobank recruited [~]0{middle dot}5 million middle age individuals from the UK, of whom 157,000 completed an assessment of suicidality. Mutually exclusive groups were assessed in an ordinal genome-wide association study of suicidality: no suicidality controls (N=83,557); thoughts that life was not worth living (N=21,063); ever contemplated self-harm (N=13,038); an act of deliberate self-harm in the past (N=2,498); and a previous suicide attempt (N=2,666). Linkage of UK Biobank to death certification records identified a small sub-group of completed suicide (N=137).\n\nOutcomes: We identified three novel genome-wide significant loci for suicidality (on Chromosomes 9, 11 and 13) and moderate-to-strong genetic correlations between suicidality and a range of psychiatric disorders, most notably depression (rg 0{middle dot}81). Higher polygenic risk scores for suicidality were associated with increased risk of completed suicide relative to controls in an independent sub-group (N=137 vs N=5,330, OR 1{middle dot}23, 95%CI 1{middle dot}06 to 1{middle dot}41, p=0.03). Rs598046-G (chromosome 11) demonstrated a similar effect size and direction (p=0{middle dot}05) within a Danish suicidality study.\n\nInterpretation: These findings have significant implications for our understanding of genetic vulnerability to suicidal thoughts and behaviours. Future work should assess the extent to which polygenic risk scores for suicidality, in combination with non-genetic risk factors, may be useful for stratified approaches to suicide prevention at a population level.\n\nFunding: UKRI Innovation-HDR-UK Fellowship (MR/S003061/1). MRC Mental Health Data Pathfinder Award (MC_PC_17217).

genetics↗

bioRxiv2018

Genome-wide association study of circadian rhythmicity in 71 500 UK Biobank participants and polygenic association with mood instability

BackgroundCircadian rhythms are fundamental to health and are particularly important for mental wellbeing. Disrupted rhythms of rest and activity are recognised as risk factors for major depressive disorder and bipolar disorder.\n\nMethodsWe conducted a genome-wide association study (GWAS) of low relative amplitude (RA), an objective measure of circadian rhythmicity derived from the accelerometer data of 71 500 UK Biobank participants. Polygenic risk scores (PRS) for low RA were used to investigate potential associations with psychiatric phenotypes.\n\nOutcomesTwo independent genetic loci were associated with low RA, within genomic regions for Neurofascin (NFASC) and Solute Carrier Family 25 Member 17 (SLC25A17). A secondary GWAS of RA as a continuous measure identified a locus within Meis Homeobox 1 (MEIS1). There were no significant genetic correlations between low RA and any of the psychiatric phenotypes assessed. However, PRS for low RA was significantly associated with mood instability across multiple PRS thresholds (at PRS threshold 0{middle dot}05: OR=1{middle dot}02, 95% CI=1{middle dot}01-1{middle dot}02, p=9{middle dot}6x10-5), and with major depressive disorder (at PRS threshold 0{middle dot}1: OR=1{middle dot}03, 95% CI=1{middle dot}01-1{middle dot}05, p=0{middle dot}025) and neuroticism (at PRS threshold 0{middle dot}5: Beta=0{middle dot}02, 95% CI=0{middle dot}007-0{middle dot}04, p=0{middle dot}021).\n\nInterpretationOverall, our findings contribute new knowledge on the complex genetic architecture of circadian rhythmicity and suggest a putative biological link between disrupted circadian function and mood disorder phenotypes, particularly mood instability, but also major depressive disorder and neuroticism.

genomics↗

bioRxiv2018

Polygenic risk scores for major depressive disorder and neuroticism as predictors of antidepressant response: meta-analysis of three treatment cohorts.

There are currently no reliable approaches for correctly identifying which patients with major depressive disorder (MDD) will respond well to antidepressant therapy. However, recent genetic advances suggest that Polygenic Risk Scores (PRS) could allow MDD patients to be stratified for antidepressant response. We used PRS for MDD and PRS for neuroticism as putative predictors of antidepressant response within three treatment cohorts: The Genome-based Therapeutic Drugs for Depression (GENDEP) cohort, and 2 sub-cohorts from the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomics Study PRGN-AMPS (total patient number = 783). Results across cohorts were combined via meta-analysis within a random effects model. Overall, PRS for MDD and neuroticism did not significantly predict antidepressant response but there was a consistent direction of effect, whereby greater genetic loading for both MDD (best MDD result, p < 5*10-5 MDD-PRS at 4 weeks, {beta} = -0.019, S.E = 0.008, p = 0.01) and neuroticism (best neuroticism result, p < 0.1 neuroticism-PRS at 8 weeks, {beta} = -0.017, S.E = 0.008, p = 0.03) were associated with less favourable response. We conclude that the PRS approach may offer some promise for treatment stratification in MDD and should now be assessed within larger clinical cohorts.

genetics↗

bioRxiv2017

Genome-wide analysis of risk-taking behaviour and cross-disorder genetic correlations in 116,255 individuals from the UK Biobank cohort

Risk-taking behaviour is a key component of several psychiatric disorders and could influence lifestyle choices such as smoking, alcohol use and diet. As a phenotype, risk-taking behaviour therefore fits within a Research Domain Criteria (RDoC) approach, whereby identifying genetic determinants of this trait has the potential to improve our understanding across different psychiatric disorders. Here we report a genome wide association study in 116 255 UK Biobank participants who responded yes/no to the question \"Would you consider yourself a risk-taker?\" Risk-takers (compared to controls) were more likely to be men, smokers and have a history of psychiatric disorder. Genetic loci associated with risk-taking behaviour were identified on chromosomes 3 (rs13084531) and 6 (rs9379971). The effects of both lead SNPs were comparable between men and women. The chromosome 3 locus highlights CADM2, previously implicated in cognitive and executive functions, but the chromosome 6 locus is challenging to interpret due to the complexity of the HLA region. Risk-taking behaviour shared significant genetic risk with schizophrenia, bipolar disorder, attention deficit hyperactivity disorder and post-traumatic stress disorder, as well as with smoking and total obesity. Despite being based on only a single question, this study furthers our understanding of the biology of risk-taking behaviour, a trait which has a major impact on a range of common physical and mental health disorders.

genetics↗