Biology subjects

Cole, B.

Publications and source records attributed to Cole, B..

15 recordsLinked to original sources

bioRxiv2026

Longitudinal tumor ecosystem mapping defines glioblastoma treatment trajectories

Glioblastoma remains an invariably recurring and lethal brain tumor shaped by complex interactions between malignant and microenvironmental cells. How these interactions evolve under first-line standard-of-care (SOC) therapy remains unclear. We performed spatial single-cell profiling of 671 paired newly diagnosed and recurrent glioblastoma samples from 96 patients to map tumor-ecosystem evolution and its clinical relevance. We delineated five distinct patient subgroups, each characterized by unique ecosystem trajectories that correlated with clinical outcome. Patients whose tumors transitioned into oligodendrocyte-progenitor-like niches with enhanced vascular integrity, oxygenation and an IL10/CCL/MHCII immunomodulatory environment experienced improved clinical prognosis. In contrast, progression towards hypoxic mesenchymal/astrocyte-like niches dominated by strong LGALS1/SPP1/TGF{beta} immunosuppression predicted poor outcome. Furthermore, a subgroup of early-relapsing patients on SOC therapy that was characterized by a depletion of an antigen-presenting myeloid-cell-rich niche, exhibited diminished responsiveness to second-line lomustine therapy. Overall, mapping evolutions in glioblastoma ecosystems offers a novel framework for prognostic stratification and therapeutic guidance.

cancer biology↗

bioRxiv2025

Atorvastatin suppresses cardiac fibrosis and dysfunction induced by HIV and certain antiretroviral drugs in mice by blocking platelet TGFβ1

Cardiovascular disease (CVD) both atherosclerosis-related and heart failure with preserved ejection fraction (HFpEF) and linked to cardiac fibrosis, contributes to morbidity and mortality in people with HIV (PWH) receiving antiretroviral therapy (ART). In the REPRIEVE trial, pitavastatin reduced atherosclerotic CVD risk to a magnitude inconsistent with pitavastatins impact solely on LDL-cholesterol and inflammation. We hypothesized that HFpEF in PWH relates to HIV-induced fibrosis mediated by platelet TGF{beta}1, that it is accelerated by certain contemporary ART, and may also be inhibited by statins. ART drugs used in REPRIEVE, including a nucleoside/nucleotide, integrase inhibitor-based regimen (tenofovir (TDF), emtricitabine (FTC), and dolutegravir (DTG)), and the protease inhibitors ritonavir (RTV) and darunavir (DRV), and the impact of atorvastatin, were examined in two HIV mouse models: transgenic Tg26 mice and HIV-PDX mice engrafted with HIV-infected T cells. Tg26 and HIV-PDX mice had higher cardiac fibrosis than littermate controls without HIV (p<0.05). Administration of TDF-FTC-DTG or RTV, but not DRV, resulted in a further [~]2-fold increase in fibrosis (p<0.01). Higher cardiac fibrosis with intracardiac fat accumulation correlated with reduced diastolic function. Mice depleted of platelet TGF{beta}1 (TGF{beta}1Platelet-{Delta}Tg26), or treated with atorvastatin, were partially protected from HIV- and ART-induced cardiac fibrosis, steatosis, and diastolic dysfunction. Atorvastatin effects occurred independently of changes in inflammatory cytokines and total cholesterol. They correlated with reduced platelet activation and TGF{beta}1 signaling in cardiac endothelial cells, fibroblasts, and macrophages undergoing mesenchymal transition. These results indicate that certain ART regimens accelerate HIV-associated CVD characterized by HFpEF via platelet TGF{beta}1-dependent processes and mitigated by atorvastatin. They enhance understanding of the pleiotropic effects of statins in HIV/ART CVD and suggest a mechanism that might be targeted by antiplatelet agents or inhibition of TGF{beta} signaling. Key PointsO_LIContemporary ART regimens induce release of platelet TGF{beta}1 and are associated with cardiac fibrosis and diastolic dysfunction with ectopic fat deposition in HIV-infected mice. C_LIO_LIDepleting platelet TGF{beta}1 and/or treating with atorvastatin therapy suppresses HIV-ART-induced cardiac fibrosis, suggesting use of anti-platelet strategies to prevent heart failure among PWH. C_LI

biochemistry↗

bioRxiv2025

Multi-season analysis reveals hundreds of drought-responsive genes in sorghum

Persistent drought affects global crop production and is becoming more severe in many parts of the world in recent decades. Deciphering how plants respond to drought will facilitate the development of flexible mitigation strategies. Sorghum bicolor L. Moench (sorghum), a major cereal crop and an emerging bioenergy crop, exhibits remarkable resilience to drought. To better understand the molecular traits that underlie sorghums remarkable drought tolerance, we undertook a large-scale sorghum gene expression profiling effort, totaling nearly 1,500 transcriptome profiles, across a 3-year field study with replicated plots in Californias Central Valley. This study included time-resolved gene expression data from roots and leaves of two sorghum genotypes, BTx642 and RTx430, with different pre-flowering and post-flowering drought-tolerance adaptations under control and drought conditions. Quantification of genotype-specific drought tolerance effects was enabled by de novo sequencing, assembly, and annotation of both BTx642 and RTx430 genomes. These reference-quality genomes were used to construct a pan-gene set for characterizing conserved and genotype-specific expression. By integrating time-resolved transcriptomic responses to drought in the field across three consecutive years, we identified a set of drought-responsive genes that responded similarly in all three years of our field study. This expansive dataset represents a unique resource for sorghum and drought research communities and provides a methodological framework for the integration of multi-faceted time-resolved transcriptomic datasets.

genomics↗

bioRxiv2023

Spatial Co-transcriptomics Reveals Discrete Stages of the Arbuscular Mycorrhizal Symbiosis

The symbiotic interaction of plants with arbuscular mycorrhizal fungi (AM fungi) is ancient and widespread. Plants provide AM fungi with carbon in exchange for nutrients and water, making this interaction a prime target for crop improvement. However, plant-fungal interactions are restricted to a small subset of root cells, precluding the application of most conventional functional genomic techniques to study the molecular bases of these interactions. Here we used single-nucleus and spatial RNA sequencing to explore both M. truncatula and R. irregularis transcriptomes in AM symbiosis at cellular and spatial resolution. Integrated spatially-registered single-cell maps of interacting cells revealed major infected and uninfected plant root cell types. We observed that cortex cells exhibit distinct transcriptome profiles during different stages of colonization by AM fungi, indicating dynamic interplay between both organisms during establishment of the cellular interface enabling successful symbiosis. Our study provides insight into a symbiotic relationship of major agricultural and environmental importance and demonstrates a paradigm combining single-cell and spatial transcriptomics for the analysis of complex organismal interactions.

plant biology↗

bioRxiv2023

Single-cell profiling and zebrafish avatars reveal LGALS1 as immunomodulating target in glioblastoma

Glioblastoma (GBM) remains the most malignant primary brain tumor, with a median survival rarely exceeding 2 years. Tumor heterogeneity and an immunosuppressive microenvironment are key factors contributing to the poor response rates of current therapeutic approaches. GBM-associated macrophages (GAMs) often exhibit immunosuppressive features that promote tumor progression. However, their dynamic interactions with GBM tumor cells remain poorly understood. Here, we used patient-derived GBM stem cell cultures and combined single-cell RNA sequencing of GAM-GBM co-cultures and real-time in vivo monitoring of GAM-GBM interactions in orthotopic zebrafish xenograft models to provide insight into the cellular, molecular, and spatial heterogeneity. Our analyses revealed substantial heterogeneity across GBM patients in GBM-induced GAM polarization and the ability to attract and activate GAMs - features that correlated with patient survival. Differential gene expression analysis, immunohistochemistry on original tumor samples, and knock-out experiments in zebrafish subsequently identified LGALS1 as a primary regulator of immunosuppression. Overall, our work highlights that GAM-GBM interactions can be studied in a clinically relevant way using co-cultures and avatar models, while offering new opportunities to identify promising immune-modulating targets.

cancer biology↗

bioRxiv2023

Epidermal GIGANTEA adjusts the response to shade at dusk by directly impinging on PHYTOCHROMEINTERACTING FACTOR 7 function

For plants adapted to bright light, a decrease in the amount of light received can be detrimental to their growth and survival. Consequently, in response to shade from surrounding vegetation, they initiate a suite of molecular and morphological changes known as the shade avoidance response (SAR) through which stems and petioles elongate in search for light. Under sunlight-night cycles, the plants responsiveness to shade varies across the day, being maximal at dusk time. While a role for the circadian clock in this regulation has long been proposed, mechanistic understanding of how it is achieved is incomplete. Here we show that the clock component GIGANTEA (GI) directly interacts with the transcriptional regulator PHYTOCHROME INTERACTING FACTOR 7 (PIF7), a key player in the response to shade. GI represses PIF7 transcriptional activity and the expression of its target genes in response to shade, thereby fine-tuning the magnitude of the response to limiting light conditions. We find that, under light/dark cycles, this function of GI is required to adequately modulate the gating of the response to shade at dusk. Importantly, we also show that GI expression in epidermal cells is sufficient for proper SAR regulation. SIGNIFICANCEPlants have a remarkable capacity to adapt to and cope with changes in environmental conditions. Because of the importance of light to their survival, plants have evolved sophisticated mechanisms to optimize responses to light. An outstanding adaptive response in terms of plant plasticity in dynamic light environments is the shade avoidance response which sun-loving plants deploy to escape canopy and grow towards the light. This response is the result of a complex signaling network in which cues from different pathways are integrated, including light, hormone, and circadian signaling. Within this framework, our study provides a mechanistic model of how the circadian clock contributes to this complex response by temporalizing the sensitivity to shade signals towards the end of the light period. In light of evolution and local adaptation, this work gives insights into a mechanism through which plants may have optimized resource allocation in fluctuating environments.

plant biology↗

bioRxiv2023

HIV-PULSE: A long-read sequencing assay for high-throughput near full-length HIV-1 proviral genome characterization

A deep understanding of the composition of the HIV-1 reservoir is necessary for the development of targeted therapies and the evaluation of curative efforts. However, current near full-length (NFL) HIV-1 proviral genome sequencing assays are based on labor-intensive and costly principles of repeated PCRs at limiting dilution, restricting their scalability. To address this, we developed a high-throughput, long-read sequencing assay called HIV-PULSE (HIV Proviral UMI-mediated Long-read Sequencing). This assay uses unique molecular identifiers (UMIs) to tag individual HIV-1 genomes, allowing for the omission of the limiting dilution step and enabling long-range PCR amplification of many NFL genomes in a single PCR reaction, while simultaneously overcoming poor single-read accuracy. We optimized the assay using HIV-infected cell lines and then applied it to blood samples from 18 individuals living with HIV on antiretroviral therapy, yielding a total of 1,308 distinct HIV-1 genomes. Benchmarking against the widely applied Full-Length Individual Proviral Sequencing assay revealed similar sensitivity (11% vs 18%) and overall good concordance, though at a significantly higher throughput. In conclusion, HIV-PULSE is a cost-efficient and scalable assay that allows for the characterization of the HIV-1 proviral landscape, making it an attractive method to study the HIV-1 reservoir composition and dynamics.

molecular biology↗

bioRxiv2022

Single-cell molecular profiling using ex vivo functional readouts fuels precision oncology in glioblastoma

BackgroundFunctional profiling of freshly isolated glioblastoma cells is being evaluated as a next-generation method for precision oncology. While promising, its success largely depends on the method to evaluate treatment activity which requires sufficient resolution and specificity. MethodsHere, we describe the precision oncology by single-cell profiling using ex vivo readouts of functionality (PROSPERO) assay to evaluate the intrinsic susceptibility of high- grade brain tumor cells to respond to therapy. Different from other assays, PROSPERO extends beyond life/death screening by rapidly evaluating acute molecular drug responses at single-cell resolution. ResultsThe PROSPERO assay was developed by correlating short-term single-cell molecular signatures using CyTOF to long-term cytotoxicity readouts in representative patient- derived glioblastoma cell cultures (n=14) that were exposed to radiotherapy and the small- molecule p53/MDM2 inhibitor AMG232. The predictive model was subsequently projected to evaluate drug activity in freshly resected GBM samples from patients (n=34). Here, PROSPERO revealed an overall limited capacity of tumor cells to respond to therapy, as reflected by the inability to induce key molecular markers upon ex vivo treatment exposure, while retaining proliferative capacity, insights that were validated in PDX models. This approach also allowed the investigation of cellular plasticity, which in PDCLs highlighted therapy-induced proneural-to-mesenchymal transitions, while in patients samples this was more heterogeneous. ConclusionPROSPERO provides a precise way to evaluate therapy efficacy by measuring molecular drug responses using specific biomarker changes in freshly resected brain tumor samples, in addition to providing key functional insights in cellular behavior, which may ultimately complement standard, clinical biomarker evaluations.

cancer biology↗

bioRxiv2022

Single-cell profiling of complex plant responses to Pseudomonas syringae infection

Plant response to pathogen infection varies within a leaf, yet this heterogeneity is not well resolved. We exposed Arabidopsis to Pseudomonas syringae or mock treatment and profiled >11,000 individual cells using single-cell RNA sequencing. Integrative analysis of cell populations from both treatments identified distinct pathogen responsive cell clusters exhibiting transcriptional responses ranging from immunity to susceptibility. Pseudotime analyses through pathogen infection revealed a continuum of disease progression from an immune to susceptible state. Confocal imaging of promoter reporter lines for transcripts enriched in immune cell clusters expressed surrounding substomatal cavities colonized or in close proximity to bacterial colonies, suggesting cells within immune clusters represent sites of early pathogen invasion. Susceptibility clusters exhibited more general localization and were highly induced at later stages of infection. Overall, our work uncovers cellular heterogeneity within an infected leaf and provides unique insight into plant differential response to infection at a single-cell level.

plant biology↗

bioRxiv2021

ECLIPSER: identifying causal cell types and genes for complex traits through single cell enrichment of e/sQTL-mapped genes in GWAS loci

SummaryECLIPSER was developed to identify pathogenic cell types and cell type-specific genes that may affect complex disease susceptibility and trait variation by integrating single cell data with known GWAS loci. ECLIPSER maps genes to GWAS loci for a given complex trait based on expression and splicing quantitative trait loci (e/sQTLs) and other functional data, and tests whether the mapped genes are enriched for cell type-specific expression in particular cell types using single-cell/nucleus RNA-seq data from one or more tissues of interest. A Bayesian Fishers exact test is used to compute fold-enrichment significance. We demonstrate the application of ECLIPSER on various skin diseases and traits using snRNA-seq of healthy human skin samples. Availability and ImplementationThe source code and documentation for ECLIPSER and a Jupyter notebook for generating output tables and figures are available at https://github.com/segrelabgenomics/ECLIPSER. The source code for GWASvar2gene that maps genes to GWAS loci based on e/sQTLs is available at https://github.com/segrelabgenomics/GWASvar2gene. The analysis presented here used data from GTEx (https://gtexportal.org/home/datasets) and Open Targets Genetics (https://genetics-docs.opentargets.org/data-access/graphql-api), but can also be applied to other GWAS variant lists and QTL studies. Data used to reproduce the results of the paper are available in Supplementary data.

bioinformatics↗

bioRxiv2021

LoFTK: a framework for fully automated calculation of predicted Loss-of-Function variants

MotivationLoss-of-Function (LoF) variants in human genes are important due to their impact on clinical phenotypes and frequent occurrence in the genomes of healthy individuals. Current approaches predict high-confidence LoF variants without identifying the specific genes or the number of copies they affect. Moreover, there is a lack of methods for detecting knockout genes caused by compound heterozygous (CH) LoF variants. ResultsWe have developed the Loss-of-Function ToolKit (LoFTK), which allows efficient and automated prediction of LoF variants from both genotyped and sequenced genomes. LoFTK enables the identification of genes that are inactive in one or two copies and provides summary statistics for downstream analyses. LoFTK can identify CH LoF variants, which result in LoF genes with two copies lost. Using data from parents and offspring we show that 96% of CH LoF genes predicted by LoFTK in the offspring have the respective alleles donated by each parent. Availability and implementationLoFTK is an open source software and is freely available to non-commercial users at https://github.com/CirculatoryHealth/LoFTK Contactj.vansetten@umcutrecht.nl Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2021

Plant Metabolic Network: A multi-species resource of plant metabolic information

Plant metabolism is a pillar of our ecosystem, food security, and economy. To understand and engineer plant metabolism, we first need a comprehensive and accurate annotation of all metabolic information across plant species. As a step towards this goal, we previously created the Plant Metabolic Network (PMN), an online resource of curated and computationally predicted information about the enzymes, compounds, reactions, and pathways that make up plant metabolism. Here we report PMN 15, which contains genome-scale metabolic pathway databases of 126 algal and plant genomes, ranging from model organisms to crops to medicinal plants, and new tools for analyzing and viewing metabolism information across species and integrating omics data in a metabolic context. We systematically evaluated the quality of the databases, which revealed that our semi-automated validation pipeline dramatically improves the quality. We then compared the metabolic content across the 126 organisms using multiple correspondence analysis and found that Brassicaceae, Poaceae, and Chlorophyta appeared as metabolically distinct groups. To demonstrate the utility of this resource, we used recently published sorghum transcriptomics data to discover previously unreported trends of metabolism underlying drought tolerance. We also used single-cell transcriptomics data from the Arabidopsis root to infer cell-type specific metabolic pathways. This work shows the continued growth and refinement of the PMN resource and demonstrates its wide-ranging utility in integrating metabolism with other areas of plant biology. One-sentence SummaryThe Plant Metabolic Network is a collection of databases containing experimentally-supported and predicted information about plant metabolism spanning many species.

plant biology↗

bioRxiv2021

In-depth single-cell analysis of translation-competent HIV-1 reservoirs identifies cellular sources of plasma viremia

Clonal expansion of HIV-infected cells contributes to the long-term persistence of the HIV reservoir in ART-suppressed individuals. However, the contribution to plasma viremia from cell clones that harbor inducible proviruses is poorly understood. Here, we describe a single-cell approach to simultaneously sequence the TCR, integration sites and proviral genomes from translation-competent reservoir cells, called STIP-Seq. By applying this approach to blood samples from eight participants, we showed that the translation-competent reservoir mainly consists of proviruses with short deletions at the 5-end of the genome, often involving the major splice donor site. TCR and integration site sequencing revealed that antigen-responsive cells can harbor inducible proviruses integrated into cancer-related genes. Furthermore, we found several matches between proviruses retrieved with STIP-Seq and plasma viruses obtained during ART and upon treatment interruption, showing that STIP-Seq can capture clones that are responsible for low-level viremia or viral rebound.

microbiology↗

bioRxiv2021

In-depth characterization of HIV-1 reservoirs reveals links to viral rebound during treatment interruption

The HIV-1 reservoir is composed of cells harboring latent proviruses that are capable of contributing to viremia upon antiretroviral treatment (ART) interruption. Although this reservoir is known to be maintained by clonal expansion, the contribution of large, infected cell clones to residual viremia and viral rebound remains underexplored. Here, we conducted an extensive analysis on four ART-treated individuals who underwent an analytical treatment interruption (ATI). We performed subgenomic (V1-V3 env), near full-length proviral and integration site sequencing, and used multiple displacement amplification to sequence both the integration site and provirus from single HIV-infected cells. We found eight proviruses that could phylogenetically be linked to plasma virus obtained before or during the ATI. This study highlights a role for HIV-infected cell clones in the maintenance of the replication-competent reservoir and suggests that infected cell clones can directly contribute to rebound viremia upon ATI.

microbiology↗

bioRxiv2021

Integration of Protein Interactome Networks with Congenital Heart Disease Variants Reveals Candidate Disease Genes

Congenital heart disease (CHD) is present in 1% of live births, yet identification of causal mutations remains a challenge despite large-scale genomic sequencing efforts. We hypothesized that genetic determinants for CHDs may lie in protein interactomes of GATA4 and TBX5, two transcription factors that cause CHDs. Defining their interactomes in human cardiac progenitors via affinity purification-mass spectrometry and integrating results with genetic data from the Pediatric Cardiac Genomic Consortium revealed an enrichment of de novo variants among proteins that interact with GATA4 or TBX5. A consolidative score that prioritized interactome members based on variant, gene, and proband features identified likely CHD-causing genes, including the epigenetic reader GLYR1. GLYR1 and GATA4 widely co-occupied cardiac developmental genes, resulting in co-activation, and the GLYR1 missense variant associated with CHD disrupted interaction with GATA4. This integrative proteomic and genetic approach provides a framework for prioritizing and interrogating the contribution of genetic variants in disease.

genetics↗