Biology subjects

Anand, V.

Publications and source records attributed to Anand, V..

7 recordsLinked to original sources

bioRxiv2026

The Warburg effect as a metabolic niche construction strategy in the tumor microenvironment

The advantage conferred by the Warburg effect to cancer cells remains unresolved. While extensive research has examined aerobic glycolysis at the intracellular level, emphasizing its possible biosynthetic or ATP-production rate benefits, the fate of the energy-rich lactate exported into the tumor microenvironment (TME) has received comparatively little attention. Yet lactate is far from metabolically inert: it actively shapes the TME, functioning as a toxin to adaptive immune cells and simultaneously promoting growth of several non-cancerous cells in the tumor microenvironment which in turn promote tumor growth. Here, we develop a minimal consumer-resource model incorporating tumor, anti-tumor immune, and pro-tumor stromal populations interacting through shared nutrients, lactate, and metabolic byproducts. We find that lactate secretion imposes a growth-exclusion tradeoff: higher glycolytic allocation suppresses anti-tumor immune cells but simultaneously reduces tumor abundance due to less efficient metabolism. This tradeoff is resolved in the presence of pro-tumor stromal populations capable of metabolic cross-feeding, namely stromal cells that convert lactate into metabolites which feed back to support tumor growth, thereby offsetting the glycolytic cost. The cross-feeding benefit is second-order in population size, requiring a critical tumor mass to operate. Taken together, these results suggest that there may be an ecological advantage of the Warburg effect, contingent on microenvironmental context. Specifically, lactate secretion is beneficial primarily when appropriate stromal partners are present, functioning as a niche-construction strategy that reorganizes the tumor ecosystem in favor of tumor expansion.

ecology↗

bioRxiv2026

Ecological Dynamics of Pro-tumor and Anti-tumor Teams in the Tumor Microenvironment

Tumor growth occurs within a complex tumor microenvironment (TME) composed of many interacting cell types. The immune cell types in TME tend to organize into two functional communities: a pro-tumor team and an anti-tumor team, each internally cooperative but mutually antagonistic forming a two-team ecosystem. Quantitatively predicting the ecological outcomes of such interactions remains challenging due to cellular diversity and interaction variability, and the exact dynamical regimes accessible to such a two-team ecosystem remain unknown. Here, we model tumor-immune interactions as a structured ecosystem with two competing teams using a generalized Lotka-Volterra framework and analyze it using the cavity method. We derive phase diagrams that delineate when these two communities coexist, when one dominates, and how these outcomes depend on intra-team cooperation, cross-team inhibition, and ecological heterogeneity. Our work provides a foundation for understanding tumor-immune dynamics from a community ecology perspective.

ecology↗

bioRxiv2025

Multi-team conflict resolution is ineffective for stable decision making

Competition between distinct groups is fundamental to complex systems, from political coalitions and economic markets to gene regulatory networks (GRNs) controlling cell fate. Strikingly, cell-fate decision systems predominantly employ binary competition between two mutually inhibitory teams of genes, despite multi-team competition being common in social and ecological contexts. This raises a fundamental question: does binary decision-making offer functional advantages over multi-team systems? We systematically analyzed multi-team competitive networks using Boolean dynamics on signed directed graphs, extending well-characterized two-team GRN architectures to systems with three or more mutually inhibitory teams. Three-team networks produced significantly less stable outcomes than two-team systems, with steady states showing higher structural frustration and increased sensitivity to perturbations. Multi-team systems exhibited unpredictable transitions even under controlled perturbations, especially at lower densities typical of real networks. Networks with four or more teams failed to maintain distinct stable states entirely. Using spectral analysis, we show that team structure can be predicted from network eigenproperties, extending structural balance theory to directed signed networks. Our findings explain why binary decisions dominate biology and provide insights into coalition instability in social systems, market dynamics, and organizational structures. This work establishes fundamental stability principles for competitive networks across disciplines.

systems biology↗

bioRxiv2024

A multi-level formalism to capture the characteristics of hybrid phenotypes in Epithelial-Mesenchymal Plasticity

Epithelial-mesenchymal plasticity (EMP) is a cell-fate switching program that enables cells to adopt a spectrum of phenotypes ranging from epithelial (E) to mesenchymal (M), including intermediate hybrid E/M states. Hybrid E/M phenotypes are conducive to cancer metastasis, as they are associated with metastatic initiation, cancer stemness, drug resistance, and collective migration. Boolean models of the gene regulatory networks (GRNs) underlying EMP have yielded valuable insights into the dynamics of E and M phenotypes. However, these models are limited in their ability to capture hybrid phenotypes effectively, as they restrict gene expression to binary states. In contrast, hybrid E/M cells often exhibit partial expression of epithelial and mesenchymal markers. To overcome this limitation, we modified a threshold-based Boolean formalism to incorporate intermediate gene expression levels. The resulting multilevel model reveals novel hybrid steady-states characterized by partial expression of both E and M genes, thereby expanding the phenotypic landscape beyond that represented by traditional Boolean approaches. Notably, these hybrid states exhibit lower frustration compared to their counterparts in classical Boolean models. Furthermore, by resolving dynamical degeneracy, we demonstrate that the hybrid states identified by the multilevel model are more stable. These findings suggest that introducing minimal additional complexity into Boolean models can uncover previously hidden qualitative features of phenotypic landscapes governed by GRNs. Significance StatementHybrid epithelial-mesenchymal phenotypes drive metastasis through collective migration, stemness, and drug resistance. However, traditional Boolean models of epithelial-mesenchymal plasticity (EMP) networks cannot capture the partial gene expression characteristic of these biologically crucial hybrid states. We developed a multilevel Boolean formalism that extends classical binary models to include intermediate expression levels. This approach successfully captures hybrid states with partial expression of both epithelial and mesenchymal genes, exhibiting lower frustration and greater stability than traditional Boolean hybrid phenotypes. While conventional Boolean hybrid states depend on modeling artifacts, multilevel hybrid states emerge independently of such uncertainties. Critically, plasticity experiments revealed that multilevel hybrid states show significantly higher transition probabilities to other hybrid states compared to traditional models, creating a stable "hybrid cloud" that maintains metastatic properties while allowing adaptive responses to environmental stress. This multilevel framework provides a biologically meaningful characterization of hybrid phenotypes essential for understanding metastasis.

systems biology↗

bioRxiv2023

Length-dependent RNA foci formation and RAN translation are associated with SCA12 disorder

Spinocerebellar ataxia type-12 (SCA-12) is a neurodegenerative disease caused by tandem CAG repeat expansion in the 5-UTR/non-coding region of PPP2R2B. Molecular pathology of SCA12 has not been studied in the context of CAG repeats and no appropriate models exist. We found in human SCA12-iPSC derived neuronal lineage that expanded CAG in PPP2R2B transcript forms nuclear RNA foci and were found to sequester variety of proteins. Further, the ectopic expression of transcript containing varying length of CAG repeats exhibits non-canonical Repeat Associated Non-AUG (RAN) translation in multiple frames in HEK293T cells, which was further validated in patient-derived neural stem cells using specific antibodies. mRNA sequencing of the SCA12 and control neurons have shown a network of crucial transcription factors affecting neural fate, in addition to alteration of various signaling pathways involved in neurodevelopment. Altogether, this study identifies the molecular signatures of spinocerebellar ataxia type-12 disorder using patient-derived neuronal cell lines.

neuroscience↗

bioRxiv2021

Anti-SARS-CoV-2 potential of Cissampelos pareira L. identified by Connectivity map-based analysis and in vitro studies

BackgroundViral infections have a history of abrupt and severe eruptions through the years in the form of pandemics. And yet, definitive therapies or preventive measures are not present. PurposeHerbal medicines have been a source of various antiviral compounds. An accelerated repurposing potential of antiviral herbs can provide usable drugs and identify druggable targets. In this study, we dissect the anti-coronavirus activity of Cissampelos pareira L (Cipa). using an integrative approach. MethodsWe analysed the signature similarities between predicted antiviral agents and Cipa using the connectivity map (https://clue.io/). Next, we tested the anti-SARS-COV-2 activity of Cipa in vitro. A three-way comparative analysis of Cipa transcriptome, COVID-19 BALF transcriptome and CMAP signatures of small compounds was also performed. ResultsSeveral predicted antivirals showed a high positive connectivity score with Cipa such as apcidin, emetine, homoharringtonine etc. We also observed 98% inhibition of SARS-COV-2 replication in infected Vero cell cultures with the whole extract. Some of its prominent pure constituents e.g pareirarine, cissamine, magnoflorine exhibited 40-80% inhibition. Comparison of genes between BALF and Cipa showed an enrichment of biological processes like transcription regulation and response to lipids, to be downregulated in Cipa while being upregulated in COVID-19. CMAP also showed that Triciribine, torin-1 and VU-0365114-2 had positive connectivity with BALF 1 and 2, and negative connectivity with Cipa.

systems biology↗

bioRxiv2021

Traditional use of Cissampelos pareira L. for hormone disorder and fever provides molecular links of ESR1 modulation to viral inhibition

Bioactive fractions or compounds obtained from medicinal plants have been used for the treatment of multiple diseases. This effect could be due to common pathways underlying these conditions that are targeted by such medicines. In this study, we explored the molecular basis of action of one such herbal formulation Cissampelos pareira, used for the treatment of female hormone disorders and fever. Genome-wide expression studies on MCF7 cell lines treated with Cipa extract were carried out using Affymetrix arrays. Transcriptome analysis revealed a downregulation of signatures of estrogen response governed by estrogen receptor (ER). Molecular docking analysis identified 38 constituent molecules in Cipa that potentially bind ({Delta}G< -7.5) with ER at the same site as estrogen. Cipa transcriptome signatures show high positive connectivity (https://clue.io/) scores with protein translation inhibitors such as emetine (score: 99.61) and knockdown signatures of genes linked to the antiviral response such as ribosomal protein RPL7 (score: 99.92), which is also an ER coactivator. Cipa exhibits antiviral activity in dengue infected MCF7 cells that is decreased upon ESR1 (estrogen receptor 1) gene knockdown. This approach reveals a novel pathway involving ESR1-RPL7 axis that could be a potential target in dengue viral infection.

genomics↗