Venkatraghavan, S. | bioRxiv Science

bioRxiv2023

Characterizing heterogeneity along EMT and metabolic axes in colorectal cancer reveals underlying consensus molecular subtype-specific trends

Colorectal cancer (CRC) is highly heterogenous with variable survival outcomes and therapeutic vulnerabilities. A commonly used classification system in CRC is the Consensus Molecular Subtypes (CMS) based on gene expression patterns. However, how these CMS categories connect to axes of phenotypic plasticity and heterogeneity remains unclear. Here, we analyze 101 bulk transcriptomic datasets, along with patient tumor samples from TCGA and single-cell RNA sequencing data, to evaluate the extent of variation among CMS subtypes across metabolic plasticity and EMT axes. Our results show that CMS2 and CMS3 samples were relatively more epithelial as compared to CMS1 and CMS4. Single-cell RNA-seq analysis of CMS1 revealed two subpopulations: one close to CMS4 (more mesenchymal) and the other closer to CMS2 or CMS3 (more epithelial), indicating a partial EMT-like behavior. Further, in our meta-analysis and in TCGA data, epithelial phenotype score was positively correlated with scores of glycolysis, OXPHOS and FAO pathways, while mesenchymal scores showed CMS subtype-specific associations with metabolic axes. PD-L1 activity scores, however, consistently correlated positively with mesenchymal signature ones and negatively with epithelial signature ones, across the four CMS categories. Together, our results quantify the patterns of two interconnected axes of phenotypic heterogeneity - EMT and metabolic reprogramming - at a CMS subtype level in CRC.

cancer biology↗

bioRxiv2021

picCASO: A Cellular Automaton for Spatial Organisation

Microbial consortia exhibit spatial patterning across diverse environments. Since probing the self-organization of natural microbial communities is limited by their inherent complexity, synthetic models have emerged as attractive alternatives. In this study, we develop novel frameworks of bacterial communication and explore the emergent spatiotemporal organization of microbes. Specifically, we build quorum sensing-mediated models of microbial growth that are utilized to characterize the dynamics of communities from arbitrary initial configurations and establish the effectiveness of our communication strategies in coupling the growth rates of microbes. Our simulations indicate that the behavior of quorum sensing-coupled consortia can be most effectively modulated by the rates of secretion of AHLs. Such a mechanism of control enables the construction of desired relative populations of constituent species in spatially organized populations. Our models accurately recapitulate previous experiments that have investigated pattern formation in synthetic multi-cellular systems. Additionally, our software tool enables the easy implementation and analysis of our frameworks for a variety of initial configurations and simplifies the development of sophisticated gene circuits facilitating distributed computing. Overall, we demonstrate the potential of spatial organization as a tunable parameter in synthetic biology by introducing a communication paradigm based on the location and strength of coupling of microbial strains. Author SummaryInteracting microorganisms that coexist in a given environment tend to have well-defined spatial arrangements. While the emergence of such organization is seen across different microbiomes in nature, it is hitherto not well understood. Decoding the inherent spatial patterning of microbes is constrained by the complexity of their natural habitats. Here, we take advantage of synthetic models of microbial communities to study the dynamics of emergent spatial organization. Our framework of bacterial communication utilizes modular synthetic devices to couple growth rates. In addition to uncovering potential principles of spatial organization, this work enables the construction of complex genetic circuits distributed across communicating strains. Additionally, we have developed a software tool, picCASO, that streamlines the investigation of microbial systems communicating through such frameworks.

systems biology↗