Biology subjects

Boocock, D.

Publications and source records attributed to Boocock, D..

4 recordsLinked to original sources

bioRxiv2023

Interplay between mechanochemical patterning and glassy dynamics in cellular monolayers

Living tissues are characterized by an intrinsically mechano-chemical interplay of active physical forces and complex biochemical signalling pathways. Either feature alone can give rise to complex emergent phenomena, for example mechanically driven glassy dynamics and rigidity transitions, or chemically driven reaction-diffusion instabilities. An important question is how to quantitatively assess the contribution of these different cues to the large-scale dynamics of biological materials. We address this in MDCK monolayers, considering both mechanochemical feedbacks between ERK signalling activity and cellular density as well as a mechanically active tissue rheology via a self-propelled vertex model. We show that the relative strength of active migration forces to mechanochemical couplings controls a transition from uniform active glass to periodic spatiotemporal waves. We parameterize the model from published experimental datasets on MDCK monolayers, and use it to make new predictions on the correlation functions of cellular dynamics and the dynamics of topological defects associated with the oscillatory phase of cells. Interestingly, MDCK monolayers are best described by an intermediary parameter region in which both mechanochemical couplings and noisy active propulsion have a strong influence on the dynamics. Finally, we study how tissue rheology and ERK waves feedback on one another, and uncover a mechanism via which tissue fluidity can be controlled by mechano-chemical waves both at the local and global levels.

biophysics↗

bioRxiv2020

Theory of mechano-chemical patterning and optimal migration in cell monolayers

Collective cell migration offers a rich field of study for non-equilibrium physics and cellular biology, revealing phenomena such as glassy dynamics [1], pattern formation [2] and active turbulence [3]. However, how mechanical and chemical signaling are integrated at the cellular level to give rise to such collective behaviors remains unclear. We address this by focusing on the highly conserved phenomenon of spatio-temporal waves of density [2, 4-8] and ERK/MAPK activation [9-11], which appear both in vitro and in vivo during collective cell migration and wound healing. First, we propose a biophysical theory, backed by mechanical and optogenetic perturbation experiments, showing that patterns can be quantitatively explained by a mechano-chemical coupling between three-dimensional active cellular tensions and the mechano-sensitive ERK/MAPK pathway. Next, we demonstrate how this biophysical mechanism can robustly induce migration in a desired orientation, and we determine a theoretically optimal pattern for inducing efficient collective migration fitting well with experimentally observed dynamics. We thereby provide a bridge between the biophysical origin of spatio-temporal instabilities and the design principles of robust and efficient long-ranged migration.

biophysics↗

bioRxiv2019

Standard housing temperature but not β3-adrenoreceptor agonism drives weight-gain and adipose tissue deposition in rats following diet induced obesity at thermoneutrality

Therapeutic activation of thermogenic brown adipose tissue (BAT) may be feasible to prevent, or treat, cardiometabolic disease. However, rodents are commonly housed below thermoneutrality ([~]20{degrees}C) which can modulate their metabolism and physiology including the hyperactivation of brown (BAT) and beige white adipose tissue. We housed animals at thermoneutrality from weaning to chronically supress BAT, mimic human physiology and explore the efficacy of chronic, mild cold-exposure and {beta}3-adrenoreceptor agonism under these conditions. Using metabolic phenotyping and exploratory proteomics we show that transfer from 28{degrees}C to 20{degrees}C drives weight gain and a 125% increase in subcutaneous fat mass, an effect not seen with YM-178 administration thus suggesting a direct effect of a cool ambient temperature in promoting weight gain and further adiposity in obese rats. Following chronic suppression of BAT, uncoupling protein 1 mRNA was undetectable in IWAT in all groups. Using exploratory adipose tissue proteomics, we reveal novel gene ontology terms associated with cold-induced weight gain in BAT and IWAT whilst Reactome pathway analysis highlights the regulation of mitotic (i.e. G2/M transition) and metabolism of amino acids and derivatives pathways. Conversely, YM-178 had minimal metabolic-related effects but modified pathways involved in proteolysis (i.e. eukaryotic translation initiation) and RNA surveillance across both tissues. Taken together these findings are indicative of a novel mechanism whereby animals increase body weight and fat mass following chronic suppression of adaptive thermogenesis from weaning. In addition, treatment with a B3-adrenoreceptor agonist did not improve metabolic health in obese animals raised at thermoneutrality.

physiology↗

bioRxiv2017

Modelling Competition for Nutrients between MicrobialPopulations Growing on a Solid Agar Surface

MotivationGrowth rate is a major component of the evolutionary fitness of microbial organisms and an excellent surrogate for cell health. In the high-throughput procedures QFA and SGA, microbial cultures are inoculated in an array on solid agar, and growth is measured to obtain quantitative fitness estimates. Neighbouring cultures, which are often different genetic strains, consume nutrients at different rates, creating gradients in nutrient density. We believe that diffusion of nutrients between cultures is affecting growth in these experiments. Current analysis does not account for this; instead, it is assumed that cultures grow independently. I use a network model of nutrient diffusion and nutrient-dependent growth, to correct for competition, to try to improve the accuracy and precision of fitness estimates. I test the model against QFA data from studies on telomere function in Saccharomyces cerevisiae. Ultimately, the model might be used to improve the reliability of screens for genetic interaction and drug sensitivity.\n\nResultsI fit the competition model to a QFA plate from Addinall et al. (2011). Using far fewer parameters (387 vs 1152), the new model fits timecourses with similar closeness to the previous model. Fitness estimates are less precise for the fastest growing strains, but more precise for the majority of strains (36 out of 50). Fitness rankings agree in the positions of the fastest and slowest growing strains, but disagree in the middle positions. In a cross-plate validation experiment, the competition model overestimates timecourses to a similar degree that the previous model underestimates. A different method of fitting is required to find globally optimal solutions which might improve reliability.\n\nAvailability and ImplementationCANS, a Python package developed for the analysis in this paper, is freely available at https://github.com/lwlss/CANS.

microbiology↗