Biology subjects

Hindmarch, C. C. T.

Publications and source records attributed to Hindmarch, C. C. T..

4 recordsLinked to original sources

bioRxiv2026

A National Survey of 205 Canadian Biomedical Research Core Facilities Reveals Structural Challenges and Opportunities for Strengthening Canada's Research Ecosystem

BackgroundCanadian biomedical core facilities (BCFs) provide researchers with access to advanced tools and unique technical expertise, essential for research. However, their role, sustainability, and impact remain poorly understood. We report on the evolution of model and existing state of Canadas 205 BCFs, examining challenges and benefits. MethodsCross referencing of national databases by the Canadian Innovation Fund (CFI), and from data collected by the Canadian Network of Scientific Platforms (CNSP) allowed he identification of BCFs. Hand curation of these lists validated that cores are operational. To ensure cores not listed by CFI/CNSP were captured, research intensive institutions in Canada were independently searched to identify active cores. ResultsThere are currently 205 active and operational BCFs located across 9 provinces, which can be further stratified into 9 technical domains that describe the nature of services they provide. Quebec (80 cores) and Ontario (75 cores) have the highest confluence of BCFs, with Quebec having a higher ratio of cores per capita. ConclusionsWhile our data establishes the ubiquity of Canadian BCFs, we highlight substantial challenges including sustainability, governance, evaluation and the recognition of support for core scientists. Here, we establish a framework to address these challenges and to inform best practice, to optimize creation of impactful, accessible and functional biomedical core facilities.

scientific communication and education↗

bioRxiv2026

Pulmonary Hypertension Engine for Linked Experiments (PHELEX): a platform for the re-analysis of public transcriptomic data related to pulmonary hypertension in both animal models, and humans.

Pulmonary hypertension (PH) is a vasculopathy that results in elevated mean pulmonary arterial pressures over 20mmHg. Despite significant advances in research, PH still has a high mortality rate, and there is currently no cure for the disease. As with all biomedical fields, PH researchers have embraced the power of next generation technologies such as microarrays and RNA sequencing. Most of these data can be found on public repositories, which is usually a requirement for publication. While these repositories are rich sources of data, they require intermediate to advanced bioinformatics skills to access, download, and make these data useful. Here we present Pulmonary Hypertension Engine for Linked Experiments (PHELEX), which represents a comprehensive catalogue of all RNA sequencing data related to PH that is currently available on the Gene Expression Omnibus (GEO), hosted by the US National Centre for Biotechnology Information (NCBI). We identified 2,278 bulk RNA sequencing samples from human, mouse and rat, and built a searchable tool based on the metadata that is associated with each sample. PHELEX is a functional tool that allows selected studies to be highlighted, and parsed through Confidence, an analysis tool we have created, which will model the data based on user-defined classifiers, perform differential gene expression and pathway analysis, and present these data using standard graphics, and text-file results. PHELEX also allows PH researchers to cross-cut between discrete studies, facilitating de novo understanding of these data. As a robust searchable repository of genomic data, we hope that PHELEX will accelerate PH innovation and discovery, by allowing researchers to mine existing genomic data and thus better understand the molecular signatures that underpin PH.

genomics↗

bioRxiv2025

Confidence: A Web App for Cross-Platform Differential Gene Expression Analysis, Gene Scoring, and Enrichment Analysis

RNA sequencing (RNA-seq) is used to quantify transcript levels through measurement of nucleotide sequences. To evaluate statistically significant changes in gene expression, transcript counts between samples are compared using differential expression analysis methods. However, three of the most pressing challenges in transcriptomics analyses are: 1) analytical packages produce a distinct number of differentially expressed genes with varied P-value and fold-change values; 2) the effective use of these analytical packages requires substantial knowledge of programming and bioinformatics; and 3) there are a lack of intuitive methods to select target genes for further investigation in an unbiased manner. To address these challenges, we developed Confidence, a web-based application to perform simultaneous statistical analysis of RNA-seq count data. Confidence incorporates the Confidence Score (CS), ranging from 1 to 4 to aid in gene prioritization, where 1 represents low confidence and 4 represents high confidence. The Confidence web-based application was designed for rapid and intuitive analysis of standard experimental metadata and gene count inputs. Confidence provided a web-based, wide-net approach to differential gene expression analysis. Gene scoring allows for unbiased gene selection and identification of novel genes strongly associated with disease and treatment models across multiple species. Additionally, pathway analysis tools have been integrated so that highly confident genes can be placed into biological context in terms of functions and pathways. Confidence provides a new strategy for target prioritization in RNA-seq analysis and the generation of publication-quality figures.

bioinformatics↗

bioRxiv2024

Multi-Tissue Metabolomics Reveal mtDNA- and Diet-Specific Metabolite Profiles in a Mouse Model of Cardiometabolic Disease

RationaleExcess consumption of sugar- and fat-rich foods has heightened the prevalence of cardiometabolic disease, which remains a driver of cardiovascular disease- and type II diabetes-related mortality globally. Skeletal muscle insulin resistance is an early feature of cardiometabolic disease and is a precursor to diabetes. Insulin resistance risk varies with self-reported race, whereby, African-Americans have a greater risk of diabetes development relative to their White counterparts. Self-reported race is strongly associated with mitochondrial DNA (mtDNA) haplogroups, and previous reports have noted marked differences in bioenergetic and metabolic parameters in cells belonging to distinct mtDNA haplogroups, but the mechanism of these associations remains unknown. Additionally, distinguishing nuclear DNA (nDNA) and mtDNA contributions to cardiometabolic disease remains challenging in humans. The Mitochondrial-Nuclear eXchange (MNX) mouse model enables in vivo preclinical investigation of the role of mtDNA in cardiometabolic disease development, and has been implemented in studies of insulin resistance, fatty liver disease, and obesity in previous reports. MethodsSix-week-old male C57nDNA:C57mtDNA and C3HnDNA:C3HmtDNA wild-type mice, and C57nDNA:C3HmtDNA and C3HnDNA:C57mtDNA MNX mice, were fed sucrose-matched high-fat (45% kcal fat) or control diet (10% kcal fat) until 12 weeks of age (n = 5/group). Mice were weighed weekly and total body fat was collected at euthanasia. Gastrocnemius skeletal muscle and plasma metabolomes were characterized using untargeted dual-chromatography mass spectrometry; both hydrophilic interaction liquid chromatography (HILIC) and C18 columns were used, in positive- and negative-ion modes, respectively. ResultsComparative analyses between nDNA-matched wild-type and MNX strains demonstrated significantly increased body fat percentage in mice possessing C57mtDNA regardless of nDNA background. High-fat diet in mice possessing C57mtDNA was associated with differential abundance of phosphatidylcholines, lysophosphatidylcholines, phosphatidylethanolamines, and glucose. Conversely, high-fat diet in mice possessing C3HmtDNA was associated with differential abundance of phosphatidylcholines, cardiolipins, and alanine. Glycerophospholipid metabolism and beta-alanine signaling pathways were enriched in skeletal muscle and plasma, indicating mtDNA-directed priming of mitochondria towards oxidative stress and increased fatty acid oxidation in C57nDNA:C57mtDNA wild-type and C3HnDNA:C57mtDNA MNX mice, relative to their nDNA-matched counterparts. In mtDNA-matched mice, C57mtDNA was associated with metabolite co-expression related to the pentose phosphate pathway and sugar-related metabolism; C3HmtDNA was associated with branched chain amino acid metabolite co-expression. ConclusionsThese results reveal novel nDNA-mtDNA interactions that drive significant changes in metabolite levels. Alterations to key metabolites involved in mitochondrial bioenergetic dysfunction and electron transport chain activity are implicated in elevated beta-oxidation during high-fat diet feeding; abnormally elevated rates of beta-oxidation may be a key driver of insulin resistance. The results reported here support the hypothesis that mtDNA influences cardiometabolic disease-susceptibility by modulating mitochondrial function and metabolic pathways.

molecular biology↗