Biology subjects

Owen, D.

Publications and source records attributed to Owen, D..

24 records · Page 2Linked to original sources

bioRxiv2019

Multi-colour DNA-qPAINT reveals how Csk nano-clusters regulate T-cell receptor signalling

Phosphorylation of the negative regulatory element of the tyrosine kinase Lck by Csk down-modulates T-cell receptor induced signalling. Being constitutively active, Csk spatial organization is responsible for regulating this signalling interaction. Here, we used stoichiometrically accurate, multiplexed, single-molecule super-resolution microscopy (DNA-qPAINT) to image the nanoscale spatial architecture of Csk and two binding partners implicated in its membrane association - PAG and TRAF3. Combined with a newly developed co-clustering analysis framework, we provide a powerful resource for dissecting signalling pathways regulated by spatio-temporal organisation. We found that Csk forms nanoscale clusters proximal to the plasma membrane that are lost post-stimulation and re-recruited at later time points. Unexpectedly, these clusters do not directly co-localise with PAG at the membrane, but instead provide a ready pool of monomers to down-regulate signalling. By generating CRISPR/Cas9 knock-out T-cells, our data also identify that protein tyrosine phosphatase non-receptor type 22 (PTPN22) is essential for Csk nanocluster re-recruitment and for maintenance of the synaptic PAG population.

immunology↗

bioRxiv2019

Assembly of novel, nuclear dimers of the PI3-Kinase regulatory subunits underpins the pro-proliferative activity of the Cdc42-activated tyrosine kinase, ACK

The tyrosine kinase ACK is an oncogene associated with poor prognosis in human cancers. ACK promotes proliferation, in part, by contributing to the activation of Akt, the major PI3-Kinase effector. We show that ACK also regulates PI3-Kinase directly, via interactions with the PI3-Kinase regulatory subunits. ACK interacts with all five regulatory subunit isoforms and directly phosphorylates p85, p85{beta}, p55 and p50 on Tyr607 (or equivalent). Phosphorylation of p85{beta} at this residue promotes cell proliferation but, counterintuitively, ACK does not stimulate PI3-Kinase catalytic activity. We show that ACK stabilizes p85 levels by promoting an interaction between the p85 nSH2 domain and pTyr607, protecting p85 from ubiquitination. We demonstrate that ACK interacts with p85 exclusively in nuclear-enriched cell fractions where the increased levels of the regulatory subunits, together with the nSH2-pTyr607 interaction, promote formation of dimeric p85. We postulate that these novel dimers undertake nuclear functions that contribute to Cdc42-ACK driven oncogenesis. We propose that ACK shapes PI3-Kinase signalling by dampening the PIP3 response, whilst continuing to drive cell proliferation through Akt activation and hereto unexplored but crucial functions of nuclear dimeric p85. These new regulatory subunit dimers represent a previously undescribed mode of regulation for PI3-Kinase and potentially reveal additional avenues for therapeutic intervention.

molecular biology↗

bioRxiv2019

An agent-based model of molecular aggregation at the cell membrane

Molecular clustering at the plasma membrane has long been identified as a key process and is associated with regulating signalling pathways across cell types. Recent advances in microscopy, in particular the rise of super-resolution, have allowed the experimental observation of nanoscale molecular clusters in the plasma membrane. However, modelling approaches capable of recapitulating these observations are in their infancy, partly because of the extremely complex array of biophysical factors which influence molecular distributions and dynamics in the plasma membrane. We propose here a highly abstracted approach: an agent-based model dedicated to the study of molecular aggregation at the plasma membrane. We show that when molecules are modelled as though they can act (diffuse) in a manner which is influenced by their molecular neighbourhood, many of the distributions observed in cells can be recapitulated, even though such sensing and response is not possible for real membrane molecules. As such, agent-based offers a unique platform which may lead to a new understanding of how molecular clustering in extremely complex molecular environments can be abstracted, simulated and interpreted using simple rules.\n\nAuthor summaryMolecular aggregation in cell membranes is a key component of cellular machinery, involved across cell types in inter-cellular communication and signalling pathway initiation. As such, understanding the underlying mechanisms and molecule cluster characteristics at a more theoretical level is a pre-requisite. Complete descriptive molecular models have proven impossible to realise due to the overall complexity of the processes involved, highlighting the need for novel approaches. While conceptual models have been shown to be powerful tools and are routinely used in other fields with high level of complexity such as social sciences or economics, they are overall lacking from the literature when it comes to cell studies. We suggest in this work that the same principle applies to cell biology and in particular, the study of molecular clustering. We propose here a general model, independent of cell types or signalling pathways: an agent-based model dedicated to molecular clustering in the plasma membrane. We show we are able to recapitulate molecular aggregation similar to observations in cells while new properties are highlighted by our model, for instance, clustering is a digitised process.

bioinformatics↗

bioRxiv2019

Activation of the liver X receptors alters CD4+ T cell membrane lipids and signalling through direct regulation of glycosphingolipid synthesis

The liver X receptor (LXR) is a key transcriptional regulator of cholesterol, fatty acid, and phospholipid metabolism. Dynamic remodeling of immunometabolic pathways, including lipid metabolism, is a crucial step in T cell activation. Here we explored the role of LXR-regulated metabolic processes in primary human CD4+ T cells, and their role in controlling plasma membrane lipids (glycosphingolipids and cholesterol) which strongly influence T cell immune signaling and function. Crucially, we identified the glycosphingolipid biosynthesis enzyme glucosylceramide synthase (UGCG) as a direct transcriptional LXR target. LXR activation by agonist GW3965 or endogenous oxysterol ligands significantly altered the glycosphingolipid:cholesterol balance in the plasma membrane by increasing glycosphingolipid levels and reducing cholesterol. Consequently, LXR activation lowered plasma membrane lipid order (stability), and an LXR antagonist could block this effect. LXR stimulation also reduced lipid order at the immune synapse and accelerated activation of proximal T cell signaling molecules. Ultimately, LXR activation dampened pro-inflammatory T cell function. Finally, compared to responder T cells, regulatory T cells had a distinct pattern of LXR-target gene expression corresponding to reduced lipid order. This suggests LXR-driven lipid metabolism could contribute to functional specialization of these T cell subsets. Overall, we report a novel mode of action for LXR in T cells involving the regulation of glycosphingolipid and cholesterol metabolism, and demonstrate its relevance in modulating T cell function.

immunology↗

bioRxiv2019

Differential nanoscale organisation of LFA-1 modulates T cell migration

Effector T-cells rely on integrins to drive adhesion and migration to facilitate their immune function. Heterodimeric transmembrane integrin LFA-1 (L{beta}2) regulates adhesion and migration through linkage of the extracellular matrix with the intracellular actin treadmill machinery. We quantitated the velocity and direction of F-actin flow in migrating T-cells alongside single molecule localisation of transmembrane and intracellular LFA-1. Our results show that retrograde actin flow positively correlated and immobile actin negatively correlated with T-cell velocity. Plasma membrane localised LFA-1 forms unique nano-clustering patterns in the leading edge, compared to the mid-focal zone, in migrating T-cells. Deleting the cytosolic phosphatase PTPN22, a negative regulator of integrin signaling, increased T-cell velocity, and leading-edge cluster co-localisation of pY397 FAK, pY416 Src family kinases and LFA-1. These data suggest that differential nanoclustering patterns of LFA-1 in migrating T-cells can instruct intracellular signalling linked with the actin treadmill. Our data presents a paradigm where T cells modulate the nanoscale organisation of adhesion and signalling molecules to fine tune their migration speed. This has implications for the regulation of immune and inflammatory responses.

immunology↗

bioRxiv2018

Effects of pathogenic CNVs on physical traits in participants of the UK Biobank

BackgroundCopy number variants (CNVs) have been shown to increase risk for physical anomalies, developmental, psychiatric and medical disorders. Some of them have been associated with changes in weight, height, and other physical traits. As most studies have been performed on children and young people, these effects of CNVs in adulthood are not well established.\n\nMethodsThe UK Biobank recruited half a million adults who provided a variety of physical measurements. We called all CNVs from the Affymetrix microarrays and selected a set of 54 CNVs implicated as pathogenic (including their reciprocal deletions/duplications) and that were present in five or more persons. Linear regression analysis was used to establish their association with 16 physical traits, relevant to human health.\n\nResults396,725 participants of white British or Irish descent (excluding first-degree relatives) passed our quality control filters. There were 214 CNV/trait associations significant at a false discovery rate of 0.1, most of them novel. These traits are associated with adverse health outcomes: e.g. increased weight, waist-to-hip ratio, pulse rate and body fat composition. Deletions at 16p11.2, 16p12.1, NRXN1 and duplications at 16p13.11 and 22q11.2 produced the highest numbers of significant associations. CNVs at 1q21.1, 2q13, 16p11.2, 16p11.2 distal, 16p12.1, 17p12 and 17q12 demonstrated one or more mirror image effects of deletions versus duplications.\n\nConclusionsCarriers of many CNVs should be monitored for physical traits that increase morbidity and mortality. Genes within these CNVs can give insights into biological processes and therapeutic interventions.

genetics↗