Search bioRxiv⌕ Search

Biology subjects

Bansod, T.

Publications and source records attributed to Bansod, T..

2 recordsLinked to original sources

A Unified Control of Cellular Differentiation: From Temporal Multistability to Spatial Pattern Formation in Gene Regulatory Networks

How genetically identical cells spontaneously break symmetry to assume divergent fates is a fundamental problem in developmental biology. While modern genomics has mapped the vast molecular repertoire involved in gene regulation, understanding the mechanism of cell state transitions that drive differentiation remains a formidable challenge. To address this, we use a reaction-kinetic framework to analyze recurring motifs of two and three competing master regulators. While typically such circuits are studied numerically, we show that assuming symmetry in nodes and interactions provides exact analytical description of the bifurcations governing cell fate transitions. We find that the possible cell fates across all considered topologies are dictated by a single dimensionless quantity, {beta}--the ratio of protein degradation to production rates. In the binary Toggle Switch (TS), decreasing {beta} destabilizes the symmetric (stem cell) state, giving rise to two asymmetric (differentiated) fates via a supercritical pitchfork bifurcation. In the three-component Toggle Triad (TT), low values of {beta} yield three asymmetric fates through subcritical pitchfork bifurcation, creating an intermediate range of {beta} where both symmetric and asymmetric fates are simultaneously stable. For the Self-Activating Toggle Switch (SATS), we identify a new parameter for the self-activation threshold ({theta}) and show that decreasing{theta} progressively stabilizes the uncommitted state, leading to a regime of tristability. Building on these temporal bifurcations, we next address the feasibility of spatial structure formation: can these multistable fates stably coexist within a spatial domain? Through a minimal model of cell-cell communication via free diffusion, we extend these motifs into reaction-diffusion systems, which reveals a direct role of network topology on spatial organization. We prove that any heterogeneous pattern in two-node circuits is inherently transient and unstable. In contrast, the three-node repressive network supports the stable spatial coexistence of differentiated phenotypes through pure diffusion, a phenomenon we analyze by studying heteroclinic interface solutions as building blocks. By reducing complex regulatory dynamics to tractable models with physically meaningful parameters, we establish a minimal framework which relates topology to cell fate. Finally, the effects of temporal multistability on pattern formation provide an excellent studying ground for morphogenesis, synthetic biology, and the overarching problem of spatiotemporal self-organization.

systems biology↗

Spiral Waves and Turbulence in Mathematical Models of Oncolytic Virotherapy

Oncolytic virotherapy is a promising targeted cancer treatment that employs viruses, which selectively infect tumor cells. Although its clinical efficiency has remained limited and it is often used in conjunction with other therapies, advances in genetic engineering have produced stronger and more selective viral strains, prompting continued interest in their dynamics. In particular, previous studies have noted that viruses with sufficiently high replication rates can induce oscillations reminiscent of predator-prey systems. Here, we extend this analysis to the spatial domain by starting from an established tumor-virus reaction-diffusion model, performing a center-manifold reduction that incorporates nonlinear terms to derive a complex Ginzburg-Landau amplitude equation, and estimating its parameters directly from the original kinetics. This reduced normal form equation explains the emergence of experimentally observed patterns -- such as hollow rings and target waves -- and shows that, at longer timescales, these patterns naturally evolve toward spiral waves and a turbulent regime. Our work provides a mechanistic link between the kinetic Hopf bifurcation and the rich spatiotemporal structures observed in oncolytic virotherapy models, suggesting that these patterns are not numerical artifacts but an intrinsic feature of the system.

cancer biology↗