Amit Jangid, PhD

How structure shapes the allele diversity in self-incompatible plants
We study the impact of the structure of the self-incompatibility system on the allele diversity in self-incompatible plants. [ongoing]

Plant mating modes: self-compatibility, self-incompatibility, and mixed mode
Addressing the elusive nature of mixed-mating, this study models how molecular promiscuity and inbreeding depression drive the evolution of plant self-incompatibility. This study uncover a phase diagram with three regimes: complete self-incompatibility, self-compatibility, and a newly described mixed mode. This mixed mode is distinct, characterized by vigorous, non-decaying fluctuations in the proportion of mating types rather than a static balance. Furthermore, we find that evolutionary transitions between these modes are often reversible, offering a dynamic new framework for understanding the stability of diverse plant reproductive strategies. [Jangid A. et al. bioRxiv (2025)]

Reconciling conflicting selection pressures in self-incompatibility systems
This study investigates how plant self-incompatibility systems evolve under conflicting pressures to specifically identify partners while avoiding self-compatibility. This work uncovered that selection exerts an asymmetric effect, significantly impacting female protein amino acid composition while leaving male proteins largely unchanged. In a very good agreement with genomic data, this work offers a generalizable model for analyzing multiple selection pressures in biological systems. [Jangid A. et al. Phys. Rev. Res. 7(3) (2025)]

Evolution of small protein-protein interaction networks in collaborative non-self recognition (CNSR) system in plants
To understand how biological networks expand, we modeled the plant collaborative-non-self recognition self-incompatibility system. Unlike previous approaches, our framework incorporates interaction promiscuity and multiple protein partners. We show that these factors drive the population to spontaneously self-organize into distinct compatibility 'classes,' maintaining a dynamic balance between their emergence and decay. This underscores the importance of molecular promiscuity in network evolvability and offers a broader framework for similar biological systems. [Erez K., Jangid A. et al. Nat. Commun. 15(1) (2024)]

Modeling IFN-$\gamma$ and IL-4 mediated networks in Atopic Dermatitis
Atopic Dermatitis (AD), an auto-immune skin disease, is mainly characterized by an imbalance in Th1 and Th2 populations due to environmental interactions. Many cells and cytokines are involved in the pathogenesis of AD. We have modeled the networks of Th1, Th2, dendritic, and keratinocyte cells mediated by individual two key cytokines (IFN-$\gamma$ and IL-4). In the model, we have assumed that cytokines dynamics approach its equilibrium faster than cell dynamics. From sensitivity analysis, we observed that transitions between acute and chronic states may be through two different paths, namely, smooth and abrupt. Depending on the nature of the cytokines, there is a possibility to drive the system from a bistable phase to the acute state by giving external stimulus. [Pandey R. et al. Theor. Biol. 556 (2023)]

Stress driven minimal p53 regulatory pathway
We have constructed a stress-driven minimal model of the p53 regulatory network. This regulatory network mainly consists of active and mutant forms of tumor suppressor gene p53, MDM2, ARF, oncogene, and three different forms of stress. The model mainly represents the competition between an active and mutant form of tumor-suppressor gene p53. Depending on the nature of the external stress, four distinct dynamical states of p53 are observed. These dynamical states correspond to active, apoptosis, pre-malignant, and cancer states depending on the level of active and mutant p53. Transitions from cancer to any other state are found to be irreversible if stress is either oscillatory or constant. In case of decaying stress, the apoptotic state vanishes and for low stress, the pre-malignant state is bounded by two critical points, allowing the system to transition reversibly from the active to the pre-malignant state. For large stress, the two critical points expand, and the system moves to an irreversible cancerous state. [Jangid A. et al. Sci. Rep. 11(1) (2021), Zubair M. et al. Brief. Bioinform. 26(1) (2025)]

Nucleus and noise regulating cell fate decision
We have built a population-based stochastic cellular model starting from a single stem cell which divides stochastically to give rise to either stem or differentiated cells. The model consists of three main components: nucleus position (with and without noise), gene-regulatory network (GRN, mutual inhibition, and self-activation,) and stochastic segregation of transcription factors into daughter cells. The model shows short and non-terminating (long) genealogies similar to those observed in experimental studies of neuroblast and B cells. Non-terminating genealogies have non-zero stem cells whereas in every short-terminated genealogy, the number of stem cells goes to zero (all leaf nodes are differentiated cells). We have compared the model with the coarse-grained Markov model, both leading to bimodal probability distributions showing good agreement. The model shows that the nucleus's position towards the basal leads to more asymmetric division and apical nuclei enhance symmetric division leading to more stem cells. Introducing noise in the nucleus position, more differentiated cells are observed through symmetric differentiation. [Jangid A. et al. iScience 24(10) (2021)]

Collective dynamics of coupled NF-$\kappa$B ensembles
We studied the collective dynamics of coupled NF-$\kappa$B ensemble in a diffusive environment driven by TNF-$\alpha$ molecule. The NF-$\kappa$B gene is known to control various essential genes for smooth functioning of cells. In the model, each NF-$\kappa$B module is coupled via TNF-$\alpha$ diffusive molecule with some coupling strength. Through a suitable order parameter, we observed that for some range of coupling strength all coupled NF-$\kappa$B modules are desynchronized, and for some range there is cluster formation and chimera states -- few modules will have the same dynamics and few will have their own dynamics. We also observed complete synchronization of all modules for some range of coupling strength. We also studied another case in which there is heterogeneity in the translation of NF-$\kappa$B and observed similar behavior.