arXiv subjects

Ushasi Roy

Publications and source records attributed to Ushasi Roy.

8 recordsLinked to original sources

arXiv2024

Resource competition in Three-gene-motif & Emergence of Feed-forward response: A Spatiotemporal Study

Feed-forward dynamics, which is well-known to have several important implications in nonlinear dynamical systems, frequently occurs in gene expression motifs, and has been well explored experimentally and mathematically. However, dependency of the components of a genetic circuit upon its host, due to the requirement for resources like ribosome, ATP, transcription factors, tRNA, etc., and related effects are of utmost importance, which is commonly ignored in mathematical models. In a resource-limited environment, two apparently unconnected genes can compete for resources for their respective expression and may exhibit indirect regulatory connection; an emergent response thus arises in the system completely because of resource competition. In this work, we have shown how the responses of the feed-forward loop (FFL), a well-studied regulatory genetic motif, can be recreated considering the resource competition in a three-gene pathway. Exploring the genetic system with temporal as well as spatiotemporal stability analysis, interesting transient and steady-state responses have been observed. The genetic motifs explored in this paper show many of the characteristic features of the conventional FFL structure, like response delay and pulse generation. Most interestingly, in a two-dimensional cellular arrangement, characteristic pattern formation under a concentration gradient of input signals have also been observed. This study pinpoints a larger area of research and exploration in synthetic and cellular systems, which will reveal novel controlling ideas and unique behavioral changes in the system for its context dependencies.

q-bio.MN↗

arXiv2022

Spatio-temporal Pattern Formation due to Host-Circuit Interplay in Gene Expression Dynamics

Biological systems are majorly dependent on their property of bistability in order to exhibit nongenetic heterogeneity in terms of cellular morphology and physiology. Spatial patterns of phenotypically heterogeneous cells, arising due to underlying bistability, may play significant role in phenomena like biofilm development, adaptation, cell motility etc. While nonlinear positive feedback regulation, like cooperative heterodimer formation are the usual reason behind bistability, similar dynamics can also occur as a consequence of host-circuit interaction. In this paper, we have investigated the pattern formation by a motif with non-cooperative positive feedback, that imposes a metabolic burden on its host due to its expression. In a cellular array set inside diffusible environment, we investigate spatio-temporal diffusion in one dimension as well as in two dimension in the context of various initial conditions respectively. Moreover, the number of cells exhibiting the same steady state, as well as their spatial distribution has been quantified in terms of connected component analysis. The effect of diffusion coefficient variation has been studied in terms of stability of related states and time evolution of patterns.

q-bio.QM↗

arXiv2022

Biophysical and Biochemical mechanisms underlying Collective Cell Migration in Cancer Metastasis

Multicellular collective migration is a ubiquitous strategy of cells to translocate spatially in diverse tissue environments to accomplish a wide variety of biological phenomena, viz. embryonic development, wound healing, and tumor progression. Diverse cellular functions and behaviors, for instance, cell protrusions, active contractions, cell-cell adhesion, biochemical signaling, remodeling of tissue micro-environment, etc., play their own role concomitantly to have a single concerted consequence of multicellular migration. Thus unveiling the driving principles, both biochemical and biophysical, of the inherently complex process of collective cell migration is an insurmountable task. Mathematical and computational models, in tandem with experimental data, help in shedding some light on it. Here we review different factors influencing Collective Cell Migration and then focus on different mathematical and computational models - discrete, hybrid, and continuum - which helps in revealing different aspects of multicellular migration. Finally, we discuss the applications of these modeling frameworks specific to cancer

q-bio.CB↗

arXiv2021

Precision of protein thermometry

Temperature sensing is a ubiquitous cell behavior, but the fundamental limits to the precision of temperature sensing are poorly understood. Unlike in chemical concentration sensing, the precision of temperature sensing is not limited by extrinsic fluctuations in the temperature field itself. Instead, we find that precision is limited by the intrinsic copy number, turnover, and binding kinetics of temperature-sensitive proteins. Developing a model based on the canonical TlpA protein, we find that a cell can estimate temperature to within 2%. We compare this prediction with in vivo data on temperature sensing in bacteria.

physics.bio-ph↗

arXiv2020

Effects of cell-cell adhesion on migration of multicellular clusters

Collections of cells exhibit coherent migration during morphogenesis, cancer metastasis, and wound healing. In many cases, bigger clusters split, smaller sub-clusters collide and reassemble, and gaps continually emerge. The connections between cell-level adhesion and cluster-level dynamics, as well as the resulting consequences for cluster properties such as migration velocity, remain poorly understood. Here we investigate collective migration of one- and two-dimensional cell clusters that collectively track chemical gradients using a mechanism based on contact inhibition of locomotion. We develop both a minimal description based on the lattice gas model of statistical physics, and a more realistic framework based on the cellular Potts model which captures cell shape changes and cluster rearrangement. In both cases, we find that cells have an optimal adhesion strength that maximizes cluster migration speed. The optimum negotiates a tradeoff between maintaining cell-cell contact and maintaining cluster fluidity, and we identify maximal variability in the cluster aspect ratio as a revealing signature. Our results suggest a collective benefit for intermediate cell-cell adhesion.

physics.bio-ph↗

arXiv2018

A path-integral formulation of the run and tumble motion and chemotaxis in Escherichia coli

Bacteria such as Escherichia coli move about in a series of runs and tumbles: while a run state (straight motion) entails all the flagellar motors spinning in counterclockwise mode, a tumble is caused by a shift in the state of one or more motors to clockwise spinning mode. In the presence of an attractant gradient in the environment, runs in the favourable direction are extended, and this results in a net drift of the organism in the direction of the gradient. The underlying signal transduction mechanism produces directed motion through a bi-lobed response function which relates the clockwise bias of the flagellar motor to temporal changes in the attractant concentration. The two lobes (positive and negative) of the response function are separated by a time interval of $\sim 1$s, such that the bacterium effectively compares the concentration at two different positions in space and responds accordingly. We present here a novel path-integral method which allows us to address this problem in the most general way possible, including multi-step CW-CCW transitions, directional persistence and power-law waiting time distributions. The method allows us to calculate quantities such as the effective diffusion coefficient and drift velocity, in a power series expansion in the attractant gradient. Explicit results in the lowest order in the expansion are presented for specific models, which, wherever applicable, agree with the known results. New results for gamma-distributed run interval distributions are also presented.

q-bio.QM↗

arXiv2017

Ultrasensitivity and Fluctuations in the Barkai-Leibler Model of Chemotaxis Receptors in {\it Escherichia coli}

A stochastic version of the Barkai-Leibler model of chemotaxis receptors in {\it E. coli} is studied here to elucidate the effects of intrinsic network noise in their conformational dynamics. It was originally proposed to explain the robust and near-perfect adaptation of {\it E. coli} observed across a wide range of spatially uniform attractant/repellent (ligand) concentrations. A receptor is either active or inactive and can stochastically switch between the two states. Enzyme CheR methylates inactive receptors while CheB demethylates active ones and the probability for it to be active depends on its level of methylation and ligandation. A simple version of the model with two methylation sites per receptor (M=2) shows zero-order ultrasensitivity (ZOU) akin to the classical 2-state model of covalent modification studied by Goldbeter and Koshland (GK). For extremely small and large ligand concentrations, the system reduces to two 2-state GK modules. A quantitative measure of the spontaneous fluctuations in activity (variance) estimated mathematically under linear noise approximation (LNA) is found to peak near the ZOU transition. The variance is a weak, non-monotonic and decreasing functions of ligand and receptor concentrations. Gillespie simulations for M=2 show excellent agreement with analytical results obtained under LNA. Numerical results for M=2, 3 and 4 show ZOU in mean activity; the variance is found to be smaller for larger M. The magnitude of receptor noise deduced from available experimental data is consistent with our predictions. A simple analysis of the downstream signaling pathway shows that this noise is large enough to have a beneficial effect on the motility of the organism. The response of mean receptor activity to small time-dependent changes in the external ligand concentration, computed within linear response theory, is found to have a bilobe form.

physics.bio-ph↗

arXiv2013

Zero-order ultrasensitivity: A study of criticality and fluctuations under the total quasi-steady state approximation in the linear noise regime

Zero-order ultrasensitivity (ZOU) is a long known and interesting phenomenon in enzyme networks. Here, a substrate is reversibly modified by two antagonistic enzymes (a "push-pull" system) and the fraction in modified state undergoes a sharp switching from near-zero to near-unity at a critical value of the ratio of the enzyme concentrations, under saturation conditions. ZOU and its extensions have been studied for several decades now, ever since the seminal paper of Goldbeter and Koshland (1981); however, a complete probabilistic treatment, important for the study of fluctuations in finite populations, is still lacking. In this paper, we study ZOU using a modular approach, akin to the total quasi-steady state approximation (tQSSA). This approach leads to a set of Fokker-Planck (drift-diffusion) equations for the probability distributions of the intermediate enzyme-bound complexes, as well as the modified/unmodified fractions of substrate molecules. We obtain explicit expressions for various average fractions and their fluctuations in the linear noise approximation (LNA). The emergence of a "critical point" for the switching transition is rigorously established. New analytical results are derived for the average and variance of the fractional substrate concentration in various chemical states in the near-critical regime. For the total fraction in the modified state, the variance is shown to be a maximum near the critical point and decays algebraically away from it, similar to a second-order phase transition. The new analytical results are compared with existing ones as well as detailed numerical simulations using a Gillespie algorithm.

q-bio.MN↗