Biology subjects

Chauhan, L.

Publications and source records attributed to Chauhan, L..

4 recordsLinked to original sources

bioRxiv2024

Evolution of plasticity and character displacement in a fluctuating environment

Species that compete for the same resource may undergo ecological character displacement (CD), where the phenotype of each species evolves to deviate from its optimum in the absence of competition. As natural habitats are rarely static, interspecific competition is likely to occur in environments that fluctuate over time. Such environmental fluctuations can in turn cause the evolution of phenotypic plasticity for traits mediating the competition. However, the interplay of environmental fluctuations, evolution of plasticity, and character displacement, has been little investigated. We use a quantitative genetic model to study theoretically how a randomly fluctuating environment and evolution of plasticity influence the outcome of ecological CD between two competing species. We show that environmental fluctuations make the conditions for CD more stringent, requiring stronger competitive selection relative to stabilizing selection. This occurs because environmental fluctuations reduces the average population size, and thereby competition intensity. Evolving plasticity can restore CD by buffering the impact of environmental fluctuations through phenotypic tracking, to a degree that depends on environmental predictability. Somewhat paradoxically, competition that favors phenotypic divergence among species can cause convergence in plasticity, when this reduces the load caused by fluctuations in phenotypic divergence. Our results shed light on how competition and plasticity influences evolution of the fundamental niche in a fluctuating environment.

evolutionary biology↗

bioRxiv2024

Microenvironment Shapes Cell State, Plasticity, and Heterogeneity of Small Cell Lung Cancer

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intra-tumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the tumor microenvironment (TME) exhibits substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAF) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Together, our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLCs adaptable nature, opening possibilities for re-programming the intercellular communications that shape SCLC tumor states.

cancer biology↗

bioRxiv2023

Synthetic gene circuits combining CRISPR interference and CRISPR activation in E. coli: importance of equal guide RNA binding affinities to avoid context-dependent effects

Gene expression control based on CRISPR has emerged as a powerful approach for constructing synthetic gene circuits. While the use of CRISPR interference (CRISPRi) is already well-established in prokaryotic circuits, CRISPR activation (CRISPRa) is less mature and combination of the two in the same circuits is only just emerging. Here, we report that combining CRISPRi with SoxS-based CRISPRa in Escherichia coli can lead to context-dependent effects due to different affinities in the formation of CRISPRa and CRISPRi complexes, resulting in loss of predictable behaviour. We show that this effect can be avoided by using the same scaffold guide RNA structure for both complexes.

synthetic biology↗

bioRxiv2020

Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer

Phenotypic (non-genetic) heterogeneity has significant implications for development and evolution of organs, organisms, and populations. Recent observations in multiple cancers have unravelled the role of phenotypic heterogeneity in driving metastasis and therapy recalcitrance. However, the origins of such phenotypic heterogeneity are poorly understood in most cancers. Here, we investigate a regulatory network underlying phenotypic heterogeneity in small cell lung cancer, a devastating disease with no molecular targeted therapy. Discrete and continuous dynamical simulations of this network reveal its multistable behavior that can explain co-existence of four experimentally observed phenotypes. Analysis of the network topology uncovers that multistability emerges from two teams of players that mutually inhibit each other but members of a team activate one another, forming a toggle switch between the two teams. Deciphering these topological signatures in cancer-related regulatory networks can unravel their latent design principles and offer a rational approach to characterize phenotypic heterogeneity in a tumor.

systems biology↗