Biology subjects

Read, E.

Publications and source records attributed to Read, E..

8 recordsLinked to original sources

bioRxiv2026

Virtual reality exposes fine-scale alterations in behaviour following loss of the ADHD-linked gene adgrl3.1 in zebrafish

Zebrafish have been used a prominent model for high-throughput phenotypic screens of candidate risk gene mutations for several disorders. This also includes models for attention deficit/hyperactivity disorder (ADHD). Traditional behavioural tests, such as the forced light/dark assay, concentrate on basic locomotion measures. However, recently developed visually-driven locomotion assays, for example closed-loop systems using virtual reality, have allowed extraction of richer data on animal locomotion and decision-making under different sensory stimuli. Here, we have used such a system to assess the behaviour in adgrl3.1 mutant fish, an established model for ADHD. Our results show that mutants exhibit a higher baseline excitability and a lower threshold for initiating motor events, demonstrating that collecting behavioural responses in an interactive environment enables a more precise characterisation of ADHD-relevant phenotypes associated with adgrl3.1 disruption. More generally, we establish a scalable translational platform to screen gene-function relationships and possible therapeutic interventions, not only for ADHD but multiple neurodevelopmental disorders.

neuroscience↗

bioRxiv2024

Noxious stimulation induces self-protective behaviour in bumblebees

Self-grooming directed towards a noxiously-stimulated body part is one indicator that an animal may feel pain. In insects, the lack of evidence for such behaviour has been widely argued to reflect the absence of pain experiences. Here, we tested whether bumblebees (Bombus terrestris) selectively groom one of their antennae that was touched with a noxiously-heated (65 {square}C) probe. In the first two minutes after being touched with the noxiously-heated probe, bees groomed their touched antenna a) more than their untouched antenna, b) more than bees that were touched on the antenna with an unheated probe, and c) more than control (untouched) bees groomed either of their antennae. Our results clearly show that bumblebees can direct grooming towards a site of noxious stimulation. Our findings thus refute arguments that claim that insects do not feel pain because of their lack of displaying this behaviour.

animal behavior and cognition↗

bioRxiv2023

A locomotion-based assay to measure prepulse inhibition in zebrafish larvae

Sensory gating, assessed using a prepulse inhibition assay (PPI), is a promising endophenotype of neuropsychiatric disorders that can be measured in larval zebrafish models. However, current PPI assays require high-speed cameras to capture rapid c-bend startle behaviours. In this study, we designed and employed a PPI paradigm that uses locomotion as read-out of startle responses. PPI percentage was measured at a maximum of 86% and this was reduced to 42% upon administration of an NMDA receptor antagonist, MK-801. This work provides the foundation for simpler and more accessible PPI assays using larval zebrafish to model key endophenotypes of neurodevelopmental disorders.

animal behavior and cognition↗

bioRxiv2021

Simulation of receptor triggering by kinetic segregation shows role of oligomers and close-contacts

The activation of T cells, key players of the immune system, involves local evacuation of phosphatase CD45 from a region of the T cells surface, segregating it from the T cell receptor. What drives this evacuation? In the presence of antigen, what ensures evacuation happens in the sub-second timescales necessary to initiate signaling? In the absence of antigen, what mechanisms ensure evacuation does not happen spontaneously, which could cause signaling errors? Phenomena known to influence spatial organization of CD45 or similar surface molecules include diffusive motion in the lipid bilayer, oligomerization reactions, and mechanical compression against a nearby surface, such as that of the cell presenting antigen. Computer simulations can investigate hypothesized spatiotemporal mechanisms of T cell signaling. The challenge to computational studies of evacuation is that the base process, spontaneous evacuation by simple diffusion, is in the extreme rare event limit, meaning direct stochastic simulation is unfeasible. Here we combine particle-based spatial stochastic simulation with the Weighted Ensemble method for rare events to compute the mean first-passage time for cell surface availability by surface reorganization of CD45. We confirm mathematical estimates that, at physiological concentrations, spontaneous evacuation is extremely rare, roughly 300 years. We find that dimerization decreases the time required for evacuation. A weak bi-molecular interaction (dissociation constant estimate 460 microMolar) is sufficient for an order of magnitude reduction of spontaneous evacuation times, and oligomerization to hexamers reduces times to below 1 second. This introduces a mechanism whereby CD45 oligomerization could be accessible to an engineered therapeutic. For large regions of close-contact, such as those induced by large microvilli, molecular size and compressibility imply a nonzero re-entry probability 60%, decreasing evacuation times. Simulations show that these reduced evacuation times are still unrealistically long, suggesting that a yet-to-be-described mechanism, besides compressional exclusion at a close contact, drives evacuation. Statement of SignificanceIn the immune system, T cells sensing pathogens depends on a process called T cell receptor triggering. In this process, proteins on the cell surface undergo reorganization, including local depletion of large membrane proteins from the area surrounding the T cell receptor. Computer simulations of protein dynamics provide a means to investigate phenomena in greater detail than that afforded by experiments. However, even simulations present challenges, because tracking the motion and interactions of individual molecules is computationally expensive. Combining a rare event algorithm with spatial simulations, we show that biochemical and mechanical properties drastically affect depletion timescales, and thus receptor triggering. Quantitative understanding of these timescales will constrain hypothesized mechanistic models and could suggest new strategies for T cell engineering.

biophysics↗

bioRxiv2021

Locally-correlated kinetics of post-replication DNA methylation reveals processivity and region-specificity in DNA methylation maintenance

DNA methylation occurs predominantly on cytosine-phosphate-guanine (CpG) dinucleotides in the mammalian genome, and the methylation landscape is maintained over mitotic cell division. It has been posited that coupling of maintenance methylation activity among neighboring CpGs is critical to collective stability over cellular generations, however the mechanism of this coupling is unclear. We used mathematical models and stochastic simulation to analyze data from experiments that probe genome-wide methylation of nascent DNA postreplication in cells. We find that DNA methylation maintenance rates on individual CpGs are locally correlated, and the degree of this correlation varies by genomic regional context. Applying theory of one-dimensional diffusion of proteins along DNA, we show that exponential decay of methylation rate correlation with genomic distance is consistent with enzyme processivity. Our results provide quantitative evidence of genome-wide methyltransferase processivity in vivo. From the experiment-derived correlations, we estimate that an individual methyl-transferase methylates neighbor CpGs in sequence if they are 36 basepairs apart, on average. But other mechanisms of coupling dominate for inter-CpG distances past ~ 100 basepairs. Our study demonstrates that quantitative insights into enzymatic mechanisms can be obtained from replication-associated, cell-based genome-wide measurements, by combining data-driven statistical analyses with hypothesis-driven mathematical modeling.

biophysics↗

bioRxiv2020

ILC1-derived TGFβ1 drives intestinal remodelling

Organoids can shed light on the dynamic interplay between complex tissues and rare cell types within a controlled microenvironment. Here, we developed gut organoid co-cultures with type-1 innate lymphoid cells (ILC1) to dissect the impact of their accumulation in inflamed intestines. We demonstrate for the first time that murine and human ILC1 secrete TGF{beta}1, driving expansion of CD44v6+ epithelial crypts. ILC1 additionally express MMP9 and drive gene signatures indicative of extracellular matrix remodelling. We therefore encapsulated human epithelial-mesenchymal intestinal organoids in MMP-sensitive, synthetic hydrogels designed to form efficient networks at low polymer concentrations. Harnessing this defined system, we demonstrate that ILC1 drive matrix softening and stiffening, which we suggest occurs through balanced matrix degradation and deposition. Our platform enabled us to elucidate previously undescribed interactions between ILC1 and their microenvironment, which suggest that they may exacerbate fibrosis and tumour growth when enriched in inflamed patient tissues.

immunology↗

bioRxiv2019

Analysis of single-cell gene pair coexpression landscapes by stochastic kinetic modeling reveals gene-pair interactions in development

Single-cell transcriptomics is advancing discovery of the molecular determinants of cell identity, while spurring development of novel data analysis methods. Stochastic mathematical models of gene regulatory networks help unravel the dynamic, molecular mechanisms underlying cell-to-cell heterogeneity, and can thus aid interpretation of heterogeneous cell-states revealed by single-cell measurements. However, integrating stochastic gene network models with single cell data is challenging. Here, we present a method for analyzing single-cell gene-pair coexpression patterns, based on biophysical models of stochastic gene expression and interaction dynamics. We first developed a high-computational-throughput approach to stochastic modeling of gene-pair coexpression landscapes, based on numerical solution of gene network Master Equations. We then comprehensively catalogued coexpression patterns arising from tens of thousands of gene-gene interaction models with different biochemical kinetic parameters and regulatory interactions. From the computed landscapes, we obtain a low-dimensional "shape-space" describing distinct types of coexpression patterns. We applied the theoretical results to analysis of published single cell RNA sequencing data and uncovered complex dynamics of coexpression among gene pairs during embryonic development. Our approach provides a generalizable framework for inferring evolution of gene-gene interactions during critical cell-state transitions.

systems biology↗

bioRxiv2018

Hydrodynamics of transient cell-cell contact: The role of membrane permeability and active protrusion length

In many biological settings, two or more cells come into physical contact to form a cell-cell interface. In some cases, the cell-cell contact must be transient, forming on timescales of seconds. One example is offered by the T cell, an immune cell which must attach to the surface of other cells in order to decipher information about disease. The aspect ratio of these interfaces (tens of nanometers thick and tens of micrometers in diameter) puts them into the thin-layer limit, or \"lubrication limit\", of fluid dynamics. A key question is how the receptors and ligands on opposing cells come into contact. What are the relative roles of thermal undulations of the plasma membrane and deterministic forces from active filopodia? We use a computational fluid dynamics algorithm capable of simulating 10-nanometer-scale fluid-structure interactions with thermal fluctuations up to seconds-and microns-scales. We use this to simulate two opposing membranes, variously including thermal fluctuations, active forces, and membrane permeability. In some regimes dominated by thermal fluctuations, proximity is a rare event, which we capture by computing mean first-passage times using a Weighted Ensemble rare-event computational method. Our results demonstrate that the time-to-contact increases for smaller cell-cell distances (where the thin-layer effect is strongest), leading to an optimal initial cell-cell separation for fastest receptor-ligand binding. We reproduce a previous experimental observation that fluctuation spatial scales are largely unaffected, but timescales are dramatically slowed, by the thin-layer effect. We also find that membrane permeability would need to be above physiological levels to abrogate the thin-layer effect.\n\nAuthor summaryThe elastohydrodynamics of water in and around cells is playing an increasingly recognized role in biology. In this work, we investigate the flow of extracellular fluid in between cells during the formation of a cell-cell contact, to determine whether its necessary evacuation as the cells approach is a rate-limiting step before molecules on either cell can interact. To overcome the computational challenges associated with simulating fluid in this mechanically soft, stochastic and high-aspect-ratio environment, we extend a computational framework where the cell plasma membranes are treated as immersed boundaries in the fluid, and combine this with computational methods for simulating stochastic rare events in which an ensemble of simulations are given weights according to their probability. We find that the internal dynamics of the membranes has speeds in approximately microseconds, but that as the cells approach, a new slow timescale of approximately milliseconds is introduced. Thermal undulations nor typical amounts of membrane permeability can overcome the timescale, but active forces, e.g., from the cytoskeleton, can. Our results suggest an explanation for differences in molecular interactions in live cells compared to in vitro reconstitution experiments.

biophysics↗