Biology subjects

Forrest, A.

Publications and source records attributed to Forrest, A..

12 recordsLinked to original sources

bioRxiv2025

Inhibition Of One-Carbon Metabolism In Ewing Sarcoma Results In Profound And Prolonged Growth Suppression Associated With Purine Depletion

Ewing sarcoma (EWS) is the second most common primary bone malignancy in adolescents and young adults. Patients who present with localized disease have experienced a steadily improving survival rate over the years, whereas those who present with metastatic disease have the same dismal prognosis as 30 years ago, with long term survival rates less than 20%, despite maximal intensification of chemotherapy. Thus, novel treatment approaches are a significant unmet clinical need. Targeting metabolic differences between EWS and normal cells offers a promising approach to improve outcomes for these patients. One-carbon metabolism utilizes serine and folate to generate glycine and tetrahydrofolate (THF)-bound one-carbon units required for de novo nucleotide biosynthesis. Elevated expression of several one-carbon metabolism genes is significantly associated with reduced survival in EWS patients. We show that both genetic and pharmacological inhibition of a key enzyme of the mitochondrial arm of the one-carbon metabolic pathway, serine hydroxymethyltransferase 2 (SHMT2), leads to substantial inhibition of EWS cell proliferation and colony-forming ability, and that this effect is primarily caused by depletion of glycine and one-carbon units required for synthesis of purine nucleotides. Inhibition of one-carbon metabolism at a different node, using the clinically relevant dihydrofolate reductase inhibitor Pralatrexate, similarly yields a profound growth inhibition, with depletion of thymidylate and purine nucleotides. Genetic depletion of SHMT2 dramatically impairs tumor growth in a xenograft model of EWS. Together, these data establish the upregulation of the one-carbon metabolism as a novel and targetable vulnerability of EWS cells, which can be exploited for therapy. Statement of SignificanceUsing both genetic and pharmacologic approaches, this study identifies Ewing sarcomas dependence on the mitochondrial arm, but not the cytoplasmic arm, of one-carbon metabolism as a targetable vulnerability that can be effectively harnessed for therapy.

cancer biology↗

bioRxiv2023

Neuronal functional connectivity is impaired in a layer dependent manner near the chronically implanted microelectrodes

ObjectiveThis study aims to reveal longitudinal changes in functional network connectivity within and across different brain structures near the chronically implanted microelectrode. While it is well established that the foreign-body response (FBR) contributes to the gradual decline of the signals recorded from brain implants over time, how does the FBR impact affect the functional stability of neural circuits near implanted Brain-Computer Interfaces (BCIs) remains unknown. This research aims to illuminate how the chronic FBR can alter local neural circuit function and the implications for BCI decoders. ApproachThis study utilized multisite Michigan-style microelectrodes that span all cortical layers and the hippocampal CA1 region to collect spontaneous and visually-evoked electrophysiological activity. Alterations in neuronal activity near the microelectrode were tested assessing cross-frequency synchronization of LFP and spike entrainment to LFP oscillatory activity throughout 16 weeks after microelectrode implantation. Main ResultsThe study found that cortical layer 4, the input-receiving layer, maintained activity over the implantation time. However, layers 2/3 rapidly experienced severe impairment, leading to a loss of proper intralaminar connectivity in the downstream output layers 5/6. Furthermore, the impairment of interlaminar connectivity near the microelectrode was unidirectional, showing decreased connectivity from Layers 2/3 to Layers 5/6 but not the reverse direction. In the hippocampus, CA1 neurons gradually became unable to properly entrain to the surrounding LFP oscillations. SignificanceThis study provides a detailed characterization of network connectivity dysfunction over long-term microelectrode implantation periods. This new knowledge could contribute to the development of targeted therapeutic strategies aimed at improving the health of the tissue surrounding brain implants and potentially inform engineering of adaptive decoders as the FBR progresses. Our studys understanding of the dynamic changes in the functional network over time opens the door to developing interventions for improving the long-term stability and performance of intracortical microelectrodes.

bioengineering↗

bioRxiv2023

Hierarchy in influence but not firing patterns among forelimb motor cortices

Though hierarchy is commonly invoked in descriptions of motor cortical function, its presence and manifestation in firing patterns remain poorly resolved. Here we use optogenetic inactivation to demonstrate that short-latency influence between forelimb premotor and primary motor cortices is asymmetric during reaching in mice, demonstrating a partial hierarchy between the endogenous activity in each region. Multi-region recordings revealed that some activity is captured by similar but delayed patterns where either regions activity leads, with premotor activity leading more. Yet firing in each region is dominated by patterns shared between regions and is equally predictive of firing in the other region at the single-neuron level. In dual-region network models fit to data, regions differed in their dependence on across-region input, rather than the amount of such input they received. Our results indicate that motor cortical hierarchy, while present, may not be exposed when inferring interactions between populations from firing patterns alone.

neuroscience↗

bioRxiv2022

Global Phylogeny of the Brassicaceae Provides Important Insights into Gene Discordance

The mustard family (Brassicaceae) is a scientifically and economically important family, containing the model plant Arabidopsis thaliana and numerous crop species that feed billions worldwide. Despite its relevance, most published family phylogenies are incompletely sampled, generally contain massive polytomies, and/or show incongruent topologies between datasets. Here, we present the most complete Brassicaceae genus-level family phylogenies to date (Brassicaceae Tree of Life, or BrassiToL) based on nuclear (>1,000 genes, almost all 349 genera and 53 tribes) and plastome (60 genes, 79% of the genera, all tribes) data. We found cytonuclear discordance between nuclear and plastome-derived phylogenies, which is likely a result of rampant hybridisation among closely and more distantly related species, and highlight rogue taxa. To evaluate the impact of this rampant hybridisation on the nuclear phylogeny reconstruction, we performed four different sampling routines that increasingly removed variable data and likely paralogs. Our resulting cleaned subset of 297 nuclear genes revealed high support for the tribes, while support for the main lineages remained relatively low. Calibration based on the 20 most clock-like nuclear genes suggests a late Eocene to late Oligocene icehouse origin of the family. Finally, we propose five new or re-established tribes, including the recognition of Arabidopsideae, a monotypic tribe to accommodate Arabidopsis. With a worldwide community of thousands of researchers working on this family, our new, densely sampled family phylogeny will be an indispensable tool to further highlight Brassicaceae as an excellent model family for studies on biodiversity and plant biology.

evolutionary biology↗

bioRxiv2021

Biallelic loss-of-function OBSCN variants predispose individuals to severe, recurrent rhabdomyolysis

Rhabdomyolysis is the acute breakdown of skeletal myofibres in response to an initiating factor, most commonly toxins and over exertion. A variety of genetic disorders predispose to rhabdomyolysis through different pathogenic mechanisms, particularly in patients with recurrent episodes. However, the majority of cases remain without a genetic diagnosis. Here we present six patients who presented with severe and recurrent rhabdomyolysis, usually with onset in the teenage years; other features included a history of myalgia and muscle cramps. We identified ten bi-allelic loss-of-function variants in the gene encoding obscurin (OBSCN) co-segregating with disease. We show reduced expression of OBSCN and loss of obscurin protein in patient muscle. Obscurin is proposed to be involved in SR function and Ca2+ handling. Patient cultured myoblasts appear more susceptible to starvation as evidenced by a greater decreased in SR Ca2+ content compared to control myoblasts. This likely reflects a lower efficiency when pumping Ca2+ back into the SR and/or a decrease in Ca2+ SR storage ability when metabolism is diminished. OSBCN variants have previously been associated with cardiomyopathies. None of the patients presented with a cardiomyopathy and cardiac examinations were normal in all cases in which cardiac function was assessed. There was also no history of cardiomyopathy in first degree relatives, in particular in any of the carrier parents. This cohort is relatively young, thus follow-up studies and the identification of additional cases with bi-allelic null OBSCN variants will further delineate OBSCN-related disease and the clinical course of disease.

genetics↗

bioRxiv2020

Single-cell analysis reveals diverse stromal subsets associated with immune evasion in triple-negative breast cancer

The tumour stroma regulates nearly all stages of carcinogenesis. Stromal heterogeneity in human triple-negative breast cancers (TNBCs) remains poorly understood, limiting the development of stromal-targeted therapies. Single cell RNA-sequencing of five TNBCs revealed two cancer-associated fibroblast (CAF) and two perivascular-like (PVL) subpopulations. CAFs clustered into two states, the first with features of myofibroblasts and the second characterised by high expression of growth factors and immunomodulatory molecules. PVL cells clustered into two states consistent with a differentiated and immature phenotype. We showed that these stromal states have distinct morphologies, spatial relationships and functional properties in regulating the extracellular matrix. Using cell-signalling predictions, we provide evidence that stromal-immune crosstalk acts via a diverse array of immunoregulatory molecules. Importantly, the investigation of gene signatures from inflammatory-CAFs and differentiated-PVL cells in independent TNBC patient cohorts revealed strong associations with cytotoxic T-cell dysfunction and exclusion, respectively. Such insights present promising candidates to further investigate for new therapeutic strategies in the treatment of TNBCs.

cancer biology↗

bioRxiv2020

Evidence for enhancer noncoding RNAs (enhancer-ncRNAs) with gene regulatory functions relevant to neurodevelopmental disorders

Noncoding RNAs (ncRNAs) comprise a significant proportion of the mammalian genome, but their biological significance in neurodevelopment disorders is poorly understood. In this study, we identified 908 brain-enriched noncoding RNAs comprising at least one nervous system-related eQTL polymorphism that is associated with protein coding genes and also overlap with chromatin states characterised as enhancers. We referred to such noncoding RNAs with putative enhancer activity as brain enhancer-ncRNAs. By integrating GWAS SNPs and Copy Number Variation (CNV) data from neurodevelopment disorders, we found that 265 enhancer-ncRNAs were either mutated (CNV deletion or duplication) or contain at least one GWAS SNPs in the context of such conditions. Of these, the eQTL-associated gene for 82 enhancer-ncRNAs did not overlap with either GWAS SNPs or CNVs suggesting in such contexts that mutations to neurodevelopment gene enhancers disrupt ncRNA interaction. Taken together, we identified 49 novel NDD-associated ncRNAs that influence genomic enhancers during neurodevelopment, suggesting enhancer mutations may be relevant to the functions for such ncRNAs in neurodevelopmental disorders.

neuroscience↗

bioRxiv2020

MaxHiC: robust estimation of chromatin interaction frequency in Hi-C and capture Hi-C experiments

Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions, and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than random (background) interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly identifies statistically significant interactions in both Hi-C and capture Hi-C experiments. MaxHiC uses a negative binomial distribution model and a maximum likelihood technique to correct biases in both Hi-C and capture Hi-C libraries. We systematically benchmark MaxHiC against major Hi-C background correction tools and demonstrate using published Hi-C and capture Hi-C datasets that 1) Interacting regions identified by MaxHiC have significantly greater levels of overlap with known regulatory features (e.g. active chromatin histone marks, CTCF binding sites, DNase sensitivity) and also disease-associated genome-wide association SNPs than those identified by currently existing models, and 2) the pairs of interacting regions are more likely to be linked by eQTL pairs and more likely to link known regulatory features than any of the existing methods. We also demonstrate that interactions between different genomic region types have distinct distance distribution only revealed by MaxHiC. MaxHiC is publicly available as a python package for the analysis of Hi-C and capture Hi-C data. Author summaryMaxHiC is a robust machine learning based tool for identifying significant interacting regions from both Hi-C and capture Hi-C data. All the current existing models are designed for either Hi-C or capture Hi-C data, however we developed MaxHiC to be applicable for both Hi-C and capture Hi-C libraries (two different models have been used for Hi-C and capture Hi-C data). MaxHiC is also able to analyse very deep Hi-C libraries (e.g., MicroC) without any computational issues. MaxHiC significantly outperforms current existing tools in terms of enrichment of interactions between known regulatory regions as well as biologically relevant interactions.

bioinformatics↗

bioRxiv2019

Comprehensive characterisation of molecular host-pathogen interactions in influenza A virus-infected human macrophages

Macrophages in the lung detect and respond to influenza A virus (IAV), determining the nature of the immune response. Using terminal depth 5-RNA sequencing (CAGE) we quantify transcriptional activity of both host and pathogen over a 24-hour timecourse of IAV infection in primary human monocyte-derived macrophages (MDM). We use a systems approach to describe the transcriptional landscape of the host response to IAV contrasted with bacterial lipopolysaccharide treated MDMs, observing a failure of IAV-treated MDMs to induce feedback inhibitors of inflammation. Systematic comparison of host RNA sequences incorporated into viral mRNA (\"snatched\") against a complete survey of background RNA in the host cell enables an unbiased quantification of over-represented features of snatched host RNAs. We detect preferential snatching of RNAs associated with snRNA transcription and demonstrate that cap-snatching avoids transcripts encoding host ribosomal proteins, which are required by IAV for replication.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=177 SRC=\"FIGDIR/small/670919v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (34K):\norg.highwire.dtl.DTLVardef@b05478org.highwire.dtl.DTLVardef@79a519org.highwire.dtl.DTLVardef@462739org.highwire.dtl.DTLVardef@1b91eb6_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical Abstract(A) Overview of bioinformatics pipeline. (B) Host gene expression reveals that human macrophages exposed to IAV exhibit sustained production of key inflammatory mediators and failure to induce expression of feedback inhibitors of inflammation. (C) Unbiased comparison with total background RNA expression demonstrates that IAV cap-snatching has a strong preference for, and aversion to, different groups of host transcripts.

immunology↗

bioRxiv2019

Brain-enriched coding and long non-coding RNA genes are overrepresented in recurrent autism spectrum disorder CNVs

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with substantial phenotypic and etiological heterogeneity. It is estimated that 10-20% of cases are due to copy number variations (CNVs). Here we apply a newly developed CNV association tool (SNATCNV) to reanalyse CNV data from 19,663 autistic and 6,479 control subjects from the AutDB database. We demonstrate that SNATCNV outperforms existing CNV association methods by finding smaller genomic regions that better discriminate cases and controls. By integrating data from the FANTOM5 expression atlas we show that both known ASD causal genes identified by the SFARI and MSSNG consortia and genes within the CNVs identified by SNATCNV have brain enriched expression patterns; both brain-enriched coding and long-non-coding RNA genes are over-represented. We provide full lists of these brain enriched coding and lncRNA genes as a resource to the research community. We also go on to show that each CNV region is associated with a distinct set of phenotypes, that some are sex biased and highlight one deleted region where a brain-enriched lncRNA is the only gene present. Our analyses identify 47 high confidence ASD associated CNV regions and identifies brain-enriched genes which underlie this neurodevelopmental disorder.

neuroscience↗

bioRxiv2018

CANCERSIGN: a user-friendly and robust tool for identification and classification of mutational signatures and patterns in cancer genomes

Analyses of large somatic mutation datasets, using advanced computational algorithms, have revealed at least 30 independent mutational signatures in tumor samples. These studies have been instrumental in identification and quantification of responsible endogenous and exogenous molecular processes against cancer. The quantitative approach used to deconvolute mutational signatures is becoming an integral part of cancer research. Therefore, development of a stand-alone tool with a user-friendly graphical interface for analysis of cancer mutational signatures is necessary. In this manuscript, we introduce CANCERSIGN as an open access1 bioinformatics tool that uses raw mutation data (BED files) as input, and generates 3-mer and 5-mer mutational signatures. Additionally, this tool enables users to perform clustering on tumor samples based on the raw mutation counts as well as using the proportion of mutational signatures in each sample. Using this tool, we analysed all the whole genome somatic mutation datasets of International Cancer Genome Consortium (ICGC) samples and identified a number of novel signatures.

bioinformatics↗

bioRxiv2017

Linking FANTOM5 CAGE Peaks To Annotations With CAGEscan

The FANTOM5 expression atlas is a quantitative measurement of the activity of nearly 200,000 promoter regions across nearly 2,000 different human primary cells, tissue types and cell lines. Generation of this atlas was made possible by the use of CAGE, an experimental approach to localise transcription start sites at single-nucleotide resolution by sequencing the 5' ends of capped RNAs after their conversion to cDNAs. While 50% of CAGE-defined promoter regions could be confidently associated to adjacent transcriptional units, nearly 100,000 promoter regions remained gene-orphan. To address this, we used the CAGEscan method, in which random-primed 5'-cDNAs are paired-end sequenced. Pairs starting in the same region are assembled in transcript models called CAGEscan clusters. Here, we present the production and quality control of CAGEscan libraries from 56 FANTOM5 RNA sources, which enhances the FANTOM5 expression atlas by providing experimental evidence associating core promoter regions with their cognate transcripts.

genomics↗