Biology subjects

Vincent, E. E.

Publications and source records attributed to Vincent, E. E..

9 recordsLinked to original sources

bioRxiv2025

ABHD11 inhibition drives sterol metabolism to modulate T cell effector function and alleviate autoimmunity

Chronic inflammation in autoimmunity is driven by T cell hyperactivation. This unregulated response to self is fuelled by heightened metabolic programmes, which offers a promising new direction to uncover novel treatment strategies. /{beta}-hydrolase domain-containing protein 11 (ABHD11) is a mitochondrial hydrolase that maintains the catalytic function of -ketoglutarate dehydrogenase (-KGDH), and its expression in CD4+ T cells has been linked to remission status in rheumatoid arthritis (RA). However, the importance of ABHD11 in regulating T cell metabolism and function - and thus, the downstream implication for autoimmunity - is yet to be explored. Here, we show that pharmacological inhibition of ABHD11 dampens cytokine production by human and mouse T cells. Mechanistically, the anti-inflammatory effects of ABHD11 inhibition are attributed to increased 24,25-epoxycholesterol (24,25-EC) biosynthesis and subsequent liver X receptor (LXR) activation, which arise from a compromised TCA cycle. The impaired cytokine profile established by ABHD11 inhibition is extended to two patient cohorts of autoimmunity. Importantly, using a murine model of accelerated type 1 diabetes (T1D), we show that targeting ABHD11 suppresses cytokine production in antigen-specific T cells and delays the onset of diabetes in vivo. Collectively, our work provides pre-clinical evidence that ABHD11 is an encouraging drug target in T cell-mediated autoimmunity. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/643996v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@bb3fcborg.highwire.dtl.DTLVardef@1594fc8org.highwire.dtl.DTLVardef@84e078org.highwire.dtl.DTLVardef@1ad023e_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2024

PRMT5 inhibition preferentially targets MYCN-amplified neuroblastoma via altered transcriptional and splicing programmes regulating key cancer cell fitness pathways.

About 50% of poor prognosis neuroblastoma arises due to MYCN over-expression. We previously demonstrated that MYCN and PRMT5 proteins interact and PRMT5 knockdown led to apoptosis of MYCN amplified (MNA) neuroblastoma. Here we evaluate PRMT5 inhibitors GSK3203591/GSK3326593 as targeted therapeutics for MNA neuroblastoma and show MYCN-dependent growth inhibition and apoptosis. RNAseq revealed dysregulated MYCN transcriptional programmes and altered mRNA splicing, converging on key regulatory pathways such as DNA damage response, epitranscriptomics and cellular metabolism. Metabolic tracing showed glutamine metabolism was impeded following GSK3203591 treatment, which disrupted the MLX/Mondo nutrient sensors via intron retention of MLX mRNA. Glutaminase (GLS) protein was decreased by GSK3203591 despite unchanged transcript levels, suggesting post-transcriptional regulation. We demonstrate the RNA methyltransferase METTL3 and cognate reader YTHDF3 proteins are lowered following splicing alterations; accordingly, we observed hypomethylation of GLS mRNA and decreased GLS following YTHDF3 knockdown. In vivo efficacy of GSK3326593 was confirmed by increased survival of Th-MYCN mice together with splicing events and protein decreases consistent with in vitro data. Our study supports the spliceosome as a key vulnerability of MNA neuroblastoma and rationalises PRMT5 inhibition as a targeted therapy. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/582087v2_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@1ac6b5org.highwire.dtl.DTLVardef@1eb9520org.highwire.dtl.DTLVardef@18b980corg.highwire.dtl.DTLVardef@1ab46e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

Aspirin reprogrammes colorectal cancer cell metabolism and sensitises to glutaminase inhibition

To support proliferation and survival within a challenging microenvironment, cancer cells must reprogramme their metabolism. As such, targeting cancer cell metabolism is a promising therapeutic avenue. However, identifying tractable nodes of metabolic vulnerability in cancer cells is challenging due to their metabolic plasticity. Identification of effective treatment combinations to counter this is an active area of research. Aspirin has a well-established role in cancer prevention, particularly in colorectal cancer (CRC), although the mechanisms are not fully understood. Here, we comprehensively characterise the metabolic impact of long-term aspirin exposure (2-4mM for 52 weeks) on CRC cells. We show that aspirin regulates several enzymes and transporters of central carbon metabolism and results in a reduction in glutaminolysis and a concomitant increase in glucose metabolism, demonstrating reprogramming of nutrient utilisation. We show that aspirin causes likely compensatory changes that renders the cells sensitive to the glutaminase 1 (GLS1) inhibitor - CB-839. Of note given the clinical interest, treatment with CB-839 alone had little effect on CRC cell growth or survival. However, in combination with aspirin, CB-839 inhibited CRC cell proliferation and induced apoptosis in vitro, and importantly, reduced crypt proliferation in Apcfl/fl mice in vivo. Together, these results show that aspirin leads to significant metabolic reprogramming in colorectal cancer cells and raises the possibility that aspirin could significantly increase the efficacy of metabolic cancer therapies in CRC.

cancer biology↗

bioRxiv2022

Identifying targetable metabolic dependencies across colorectal cancer progression

Colorectal cancer (CRC) is a multi-stage process initiated through the formation of a benign adenoma, progressing to an invasive carcinoma and finally metastatic spread. Tumour cells must adapt their metabolism to support the energetic and biosynthetic demands associated with disease progression. As such, targeting cancer cell metabolism is a promising therapeutic avenue in CRC. However, to identify tractable nodes of metabolic vulnerability specific to CRC stage, we must understand how metabolism changes during CRC development. Here, we use a unique model system - comprising human early adenoma to late adenocarcinoma. We show that adenoma cells transition to elevated glycolysis at the early stages of tumour progression but maintain oxidative metabolism. Progressed adenocarcinoma cells rely more on glutamine-derived carbon to fuel the TCA cycle, whereas glycolysis and TCA cycle activity remain tightly coupled in early adenoma cells. Adenocarcinoma cells are more flexible with respect to fuel source, enabling them to proliferate in nutrient-poor environments. Despite this plasticity, we identify asparagine (ASN) synthesis as a node of metabolic vulnerability in late-stage adenocarcinoma cells. We show that loss of asparagine synthetase (ASNS) blocks their proliferation, whereas early adenoma cells are largely resistant to ASN deprivation. Mechanistically, we show that late-stage adenocarcinoma cells are dependent on ASNS to support mTORC1 signalling and maximal glycolytic and oxidative capacity. Resistance to ASNS loss in early adenoma cells is likely due to a feedback loop, absent in late-stage cells, allowing them to sense and regulate ASN levels and supplement ASN by autophagy. Together, our study defines metabolic changes during CRC development and highlights ASN synthesis as a targetable metabolic vulnerability in later stage disease.

cancer biology↗

bioRxiv2021

A framework for research into continental ancestry groups of the UK Biobank

BackgroundThe UK Biobank is a large prospective cohort, based in the United Kingdom, that has deep phenotypic and genomic data on roughly a half a million individuals. Included in this resource are data on approximately 78,000 individuals with "non-white British ancestry". Whilst most epidemiology studies have focused predominantly on populations of European ancestry, there is an opportunity to contribute to the study of health and disease for a broader segment of the population by making use of the UK Biobanks "non-white British ancestry" samples. Here we present an empirical description of the continental ancestry and population structure among the individuals in this UK Biobank subset. ResultsReference populations from the 1000 Genomes Project for Africa, Europe, East Asia, and South Asia were used to estimate ancestry for each individual. Those with at least 80% ancestry in one of these four continental ancestry groups were taken forward (N=62,484). Principal component and K-means clustering analyses were used to identify and characterize population structure within each ancestry group. Of the approximately 78,000 individuals in the UK Biobank that are of "non-white British" ancestry, 50,685, 6,653, 2,782, and 2,364 individuals were associated to the European, African, South Asian, and East Asian continental ancestry groups, respectively. Each continental ancestry group exhibits prominent population structure that is consistent with self-reported country of birth data and geography. ConclusionsMethods outlined here provide an avenue to leverage UK Biobanks deeply phenotyped data allowing researchers to maximise its potential in the study of health and disease in individuals of non-white British ancestry.

genomics↗

bioRxiv2021

A non-canonical role for glutamate decarboxylase 1 in cancer cell amino acid homeostasis, independent of the GABA shunt.

Glutamate decarboxylase 1 (GAD1) is best known for its role in producing the neurotransmitter {gamma}-amino butyric acid (GABA) as part of the "GABA shunt" metabolic pathway, an alternative mechanism of glutamine anaplerosis for TCA cycle metabolism (Yogeeswari et al., 2005). However, understanding of the metabolic function of GAD1 in non-neuronal tissues has remained limited. Here, we show that GAD1 supports cancer cell proliferation independent of the GABA shunt. Despite its elevated expression in lung cancer tissue, GAD1 is not engaged in the GABA shunt in proliferating non-small cell lung cancer (NSCLC) cells, but rather is required for regulating amino acid homeostasis. Silencing GAD1 promotes a broad deficiency in amino acid uptake, leading to reduced glutamine-dependent TCA cycle metabolism and defects in serum- and amino acid-stimulated mTORC1 activation. Mechanistically, GAD1 regulates amino acid uptake through ATF4-dependent amino acid transporter expression including SLC7A5 (LAT1), an amino acid transporter required for branched chain amino acid (BCAA) uptake. Overexpression of LAT1 rescues the proliferative and mTORC1 signalling defects of GAD1-deficient tumor cells. Our results, therefore, define a non-canonical role for GAD1, independent of its characterised role in GABA metabolism, whereby GAD1 regulates amino acid homeostasis to maintain tumor cell proliferation.

cancer biology↗

bioRxiv2021

Interleukin-33 regulates metabolic reprogramming of the retinal pigment epithelium in response to immune stressors.

It remains unresolved how retinal pigment epithelial (RPE) cell metabolism is regulated following immune activation to maintain retinal homeostasis and retinal function. We exposed RPE to several stress signals, particularly toll-like receptor stimulation, and uncovered an ability of RPE to adapt their metabolic preference on aerobic glycolysis or oxidative glucose metabolism in response to different immune stimuli. We have identified interleukin-33 (IL-33) as a key metabolic checkpoint that antagonises the Warburg effect to ensure the functional stability of the RPE. The identification of IL-33 as a key regulator of mitochondrial metabolism suggests roles for the cytokine that go beyond its extracellular "alarmin" activities. IL-33 exerts control over mitochondrial respiration in RPE by facilitating oxidative pyruvate catabolism. We have also revealed that in the absence of IL-33, mitochondrial function declines and resultant bioenergetic switching is aligned with altered mitochondrial morphology. Our data not only sheds new light in the molecular pathway of activation of mitochondrial respiration in RPE in response to immune stressors, but also uncovers a novel role of nuclear intrinsic IL-33 as a metabolic checkpoint regulator.

immunology↗

bioRxiv2019

Early metabolic features of genetic liability to type 2 diabetes: cohort study with repeated metabolomics across early life

BackgroundType 2 diabetes develops for many years before diagnosis. We aimed to reveal early metabolic features characterising liability to adult disease by examining genetic liability to adult type 2 diabetes in relation to detailed metabolic traits across early life.\n\nMethods and FindingsData were from up to 4,761 offspring from the Avon Longitudinal Study of Parents and Children cohort. Linear models were used to examine effects of a genetic risk score (GRS, including 162 variants) for adult type 2 diabetes on 4 repeated measures of 229 traits from targeted nuclear magnetic resonance (NMR) metabolomics. These traits included lipoprotein subclass-specific cholesterol and triglyceride content, amino and fatty acids, inflammatory glycoprotein acetyls, and others, and were measured in childhood (age 8y), adolescence (age 16y), young-adulthood (age 18y), and adulthood (age 25y). For replication, two-sample Mendelian randomization (MR) was conducted using summary data from genome-wide association studies of metabolic traits from NMR in an independent sample of adults (N range 13,476 to 24,925; mean (SD) age range 23.9y (2.1y) to 61.3y (2.9y)). Among ALSPAC participants (49.7% male), the prevalence of type 2 diabetes was very low across time points (< 5 cases when first assessed at age 16y; 7 cases (0.4%) when assessed at age 25y). At age 8y, type 2 diabetes liability (per SD-higher GRS) was associated with lower lipids in high-density lipoprotein (HDL) particle subtypes - e.g. -0.03 SD (95% CI = -0.06, -0.003; P = 0.03) for total lipids in very-large HDL. At age 16y, associations remained strongest with lower lipids in HDL and became stronger with pre-glycemic traits including citrate (-0.06 SD, 95% CI = -0.09, -0.02; P = 1.41x10-03) and with glycoprotein acetyls (0.05 SD, 95% CI = 0.01, 0.08; P = 0.01). At age 18y, associations were stronger with branched chain amino acids including valine (0.06 SD; 95% CI = 0.02, 0.09; P = 1.24x10-03), while at age 25y, associations had strengthened with VLDL lipids and remained consistent with previously altered traits including HDL lipids. Results of two-sample MR in an independent sample of adults indicated persistent patterns of effect of type 2 diabetes liability, with higher type 2 diabetes liability positively associated with VLDL lipids and branched chain amino acid levels, and inversely associated with HDL lipids - again for large and very large HDL particularly (-0.004 SD (95% CI = -0.007, -0.002; P = 8.45x10-04) per 1 log odds of type 2 diabetes for total lipids in large HDL). Study limitations include modest sample sizes for ALSPAC analyses and limited coverage of protein and hormonal traits; insulin was absent as it is not quantified by NMR and not consistently available at each time point. Analyses were restricted to white-Europeans which reduced confounding by population structure but limited inference to other ethnic groups.\n\nConclusionsOur results support perturbed HDL lipid metabolism as one of the earliest features of type 2 diabetes liability which precedes higher branched chain amino acid and inflammatory glycoprotein acetyl levels. This feature is apparent in childhood as early as age 8y, decades before the clinical onset of disease.\n\nAuthor summaryO_ST_ABSWhy was this study done?C_ST_ABSO_LIType 2 diabetes develops for many years before diagnosis. Clinical disease is characterised by numerous metabolic perturbations that are detectable in circulation, but which of these reflect the developmental stages of type 2 diabetes - as opposed to independent causes of type 2 diabetes or markers of other disease processes - is unknown. Revealing traits specific to type 2 diabetes development could inform the targeting of key pathways to prevent the clinical onset of disease and its complications.\nC_LIO_LIGenetic liability to type 2 diabetes is less prone to confounding than measured type 2 diabetes or blood glucose and may help reveal early perturbations in the blood that arise in response to type 2 diabetes liability itself.\nC_LI\n\nWhat did the researchers do and find?O_LIWe examined effects of genetic liability to adult type 2 diabetes, based on a genetic risk score including 162 variants, on detailed metabolic traits measured on the same individuals across four stages of early life - childhood (age 8y), adolescence (age 16y), young-adulthood (age 18y), and adulthood (age 25y).\nC_LIO_LIWe found that higher type 2 diabetes liability was associated most consistently across ages with lower lipid content in certain subtypes of HDL particles. Effects were more gradual on higher lipid content in VLDL particles and on higher branched chain amino acid and inflammatory glycoprotein acetyl levels.\nC_LI\n\nWhat do these findings mean?O_LISigns of type 2 diabetes liability are detectable in the blood in childhood, decades before the disease becomes noticeable. These signs, taken to reflect the early features of, or coincident with, disease, likely involve lower lipid content in HDL particles, followed by higher levels of branched chain amino acids and inflammation.\nC_LIO_LIGenetic risk scores for adult diseases can be integrated with metabolic measurements taken earlier in life to help to reveal the timing at which signs of disease liability become visible and the traits most central to its development.\nC_LI

genetics↗

bioRxiv2017

MELODI - Mining Enriched Literature Objects to Derive Intermediates

MotivationThe scientific literature contains a wealth of information from different fields on potential disease mechanisms. However, prioritising mechanisms for further analytical evaluation presents enormous challenges in terms of the quantity and diversity of published research. The application of data mining approaches to the literature offers the potential to identify and prioritise mechanisms for more focused and detailed analysis.\n\nResultsHere we present MELODI, a literature mining platform that can identify mechanistic pathways between any two biomedical concepts. Two case studies demonstrate the potential uses of MELODI and how it can generate hypotheses for further investigation. Firstly, an analysis of ERG and prostate cancer derives the intermediate transcription factor SP1, recently confirmed to be physically interacting with ERG. Secondly, examining the relationship between a new potential risk factor for pancreatic cancer identifies possible mechanistic insights which can be studied in vitro.\n\nAvailabilityMELODI has been implemented as a Python/Django web application, and is freely available to use at www.melodi.biocompute.org.uk\n\nContactmelodi@biocompute.org.uk

bioinformatics↗