Biology subjects

Chambers, E.

Publications and source records attributed to Chambers, E..

6 recordsLinked to original sources

bioRxiv2025

TWIST1 drives endothelial-to-mesenchymal-transition to stabilize atherosclerotic plaques

Atherosclerosis progresses from fatty streaks to complex plaques, with rupture leading to life-threatening complications. Endothelial-to-mesenchymal transition (EndMT) is associated with advanced atherosclerotic plaques, but its role in plaque progression remains unclear. To investigate this, we analyzed the role of TWIST1, a key EndMT-driving transcription factor, in plaque development. Using single-cell RNA sequencing of atherosclerotic plaques from hypercholesterolemic mice with inducible deletion of Twist1 from endothelial cells (Twist1ECKO ApoE-/-) we demonstrate that Twist1 regulates endothelial cell heterogeneity by promoting cell states expressing EndMT markers. Cell tracking confirmed that Twist1 induces EndMT in advanced plaques. Mechanistically, we found that TWIST1 contributes to EndMT by promoting endothelial migration and proliferation through the transcriptional coactivator PELP1. Additionally, TWIST1 induces AEBP1 transcription, which upregulates COL4A1 to drive endothelial proliferation. Analyses of murine brachiocephalic plaques show that endothelial Twist1 promotes plaque growth, collagen deposition, and ACTA2-positive cell accumulation, hallmarks of plaque stability, while reducing necrosis and macrophage infiltration, features of plaque instability. Moreover, TWIST1 expression was associated with asymptomatic human carotid atherosclerosis and predicts favourable clinical outcomes. These findings challenge the prevailing view that EndMT destabilizes plaques, by suggesting that TWIST1-driven EndMT can promote plaque stability, offering new insights into atherosclerosis pathophysiology and therapeutic potential.

pathology↗

bioRxiv2023

EPAS1 Attenuates Atherosclerosis Initiation at Disturbed Flow Sites through Endothelial Fatty Acid Uptake

BackgroundAtherosclerotic plaques form unevenly due to disturbed blood flow, causing localized endothelial cell (EC) dysfunction. Obesity exacerbates this process, but the underlying molecular mechanisms are unclear. The transcription factor EPAS1 (HIF2A) has regulatory roles in endothelium, but its involvement in atherosclerosis remains unexplored. This study investigates the potential interplay between EPAS1, obesity, and atherosclerosis. MethodsResponses to shear stress were analysed using cultured porcine aortic EC exposed to flow in vitro coupled with metabolic and molecular analyses, and by en face immunostaining of murine aortic EC exposed to disturbed flow in vivo. Obesity and dyslipidemia were induced in mice via exposure to high-fat diet or through Leptin gene deletion. The role of Epas1 in atherosclerosis was evaluated by inducible endothelial Epas1 deletion, followed by hypercholesterolemia induction (AAV-PCSK9; high-fat diet). ResultsEn face staining revealed EPAS1 enrichment at sites of disturbed blood flow that are prone to atherosclerosis initiation. Obese mice exhibited substantial reduction in endothelial EPAS1 expression, correlating with hyperlipidaemia. Sulforaphane, a compound with known atheroprotective effects, restored EPAS1 expression and concurrently reduced plasma triglyceride levels in obese mice. Consistently, triglyceride derivatives (free fatty acids) suppressed EPAS1 in cultured EC by upregulating the negative regulator PHD3. Clinical observations revealed that reduced plasma EPAS1 correlated with increased endothelial PHD3 in obese individuals. Functionally, endothelial EPAS1 deletion increased lesion formation in hypercholesterolemic mice, indicating an atheroprotective function. Mechanistic insights revealed that EPAS1 protects arteries by maintaining endothelial proliferation by positively regulating CD36 and LIPG expression to increase fatty acid beta-oxidation. ConclusionsEndothelial EPAS1 attenuates atherosclerosis at sites of disturbed flow by maintaining EC proliferative via fatty acid uptake and metabolism. This endothelial repair pathway is inhibited in obesity, suggesting a novel triglyceride-PHD3 modulation pathway suppressing EPAS1 expression. These findings have implications for therapeutic strategies addressing vascular dysfunction in obesity.

physiology↗

bioRxiv2021

TopoRoot: A method for computing hierarchy and fine-grained traits of maize roots from X-ray CT images

Background3D imaging, such as X-ray CT and MRI, has been widely deployed to study plant root structures. Many computational tools exist to extract coarse-grained features from 3D root images, such as total volume, root number and total root length. However, methods that can accurately and efficiently compute fine-grained root traits, such as root number and geometry at each hierarchy level, are still lacking. These traits would allow biologists to gain deeper insights into the root system architecture (RSA). ResultsWe present TopoRoot, a high-throughput computational method that computes fine-grained architectural traits from 3D X-ray CT images of field-excavated maize root crowns. These traits include the number, length, thickness, angle, tortuosity, and number of children for the roots at each level of the hierarchy. TopoRoot combines state-of-the-art algorithms in computer graphics, such as topological simplification and geometric skeletonization, with customized heuristics for robustly obtaining the branching structure and hierarchical information. TopoRoot is validated on both real and simulated root images, and in both cases it was shown to improve the accuracy of traits over existing methods. We also demonstrate TopoRoot in differentiating a maize root mutant from its wild type segregant using fine-grained traits. TopoRoot runs within a few minutes on a desktop workstation for volumes at the resolution range of 400^3, without need for human intervention. ConclusionsTopoRoot improves the state-of-the-art methods in obtaining more accurate and comprehensive fine-grained traits of maize roots from 3D CT images. The automation and efficiency makes TopoRoot suitable for batch processing on a large number of root images. Our method is thus useful for phenomic studies aimed at finding the genetic basis behind root system architecture and the subsequent development of more productive crops.

plant biology↗

bioRxiv2021

Integrative annotation of genomic features reveal functional elements and epigenetic landscapes in the developing zebrafish

Zebrafish, a popular model for embryonic development and for modelling human diseases, has so far lacked a systematic functional annotation programme akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created the first central repository to store and process zebrafish developmental functional genomic data. Our Data Coordination Center (https://danio-code.zfin.org) combines a total of 1,802 sets of unpublished and reanalysed published genomics data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements in development, including novel classes with distinct features dependent on their activity in time and space. We delineated the distinction between regulatory elements active during zygotic genome activation and those active during organogenesis, identifying new aspects of how they relate to each other. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predict functional relationships between them beyond sequence similarity, extending the utility of zebrafish developmental genomics to mammals.

developmental biology↗

bioRxiv2020

JAG1-NOTCH4 MECHANOSENSING DRIVES ATHEROSCLEROSIS

Endothelial cell (EC) sensing of fluid shear stress regulates atherosclerosis, a disease of arteries that causes heart attack and stroke. Atherosclerosis preferentially develops at regions of arteries exposed to low oscillatory shear stress (LOSS), whereas high shear regions are protected. We show using inducible EC-specific genetic deletion in hyperlipidaemic mice that the Notch ligands JAG1 and DLL4 have opposing roles in atherosclerosis. While endothelial Jag1 promoted atherosclerosis at sites of LOSS, endothelial Dll4 was atheroprotective. Analysis of porcine and murine arteries and cultured human coronary artery EC exposed to experimental flow revealed that JAG1 and its receptor NOTCH4 are strongly upregulated by LOSS. Functional studies in cultured cells and in mice with EC-specific deletion of Jag1 show that JAG1-NOTCH4 signalling drives vascular dysfunction by repressing endothelial repair. These data demonstrate a fundamental role for JAG1-NOTCH4 in sensing LOSS during disease, and suggest therapeutic targeting of this pathway to treat atherosclerosis.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pathology↗

bioRxiv2019

Multiplexed single-cell profiling of post-perturbation transcriptional responses to define cancer vulnerabilities and therapeutic mechanism of action

Assays to study cancer cell responses to pharmacologic or genetic perturbations are typically restricted to using simple phenotypic readouts such as proliferation rate or the expression of a marker gene. Information-rich assays, such as gene-expression profiling, are generally not amenable to efficient profiling of a given perturbation across multiple cellular contexts. Here, we developed MIX-Seq, a method for multiplexed transcriptional profiling of post-perturbation responses across a mixture of samples with single-cell resolution, using SNP-based computational demultiplexing of single-cell RNA-sequencing data. We show that MIX-Seq can be used to profile responses to chemical or genetic perturbations across pools of 100 or more cancer cell lines, and combine it with Cell Hashing to further multiplex additional experimental conditions, such as multiple post-treatment time points or drug doses. Analyzing the high-content readout of scRNA-seq reveals both shared and context-specific transcriptional response components that can identify drug mechanism of action and can be used to predict long-term cell viability from short-term transcriptional responses to treatment.

cancer biology↗