Biology subjects

Dubuis, S.

Publications and source records attributed to Dubuis, S..

4 recordsLinked to original sources

bioRxiv2025

The glutamine-aspartate metabolic tradeoff between fast growth and metabolic flexibility.

Cancer cells develop unique addictions to nutrients, offering attractive opportunities for clinical intervention. However, how cancer cells orchestrate and benefit from metabolic rewiring remain fundamental open questions. Here, we developed a systematic framework to investigate nutrient dependencies and applied it to study glutamine addiction. By measuring metabolite exchange rates across 54 cancer cell lines with different levels of dependency on extracellular glutamine and in human stem cells, we discovered that a dualistic regulation of glutamate biosynthesis from glutamine or aspartate, driven by the tissue of origin, generates a tradeoff between fast growth and metabolic flexibility. Monitoring dynamic metabolic adaptation to glutamine deprivation showed that the role of glutamine as limiting substrate in purine biosynthesis is not responsible for glutamine dependency. Rather, growth arrest is mediated by glutamine as a signaling molecule. Our approach opens new opportunities to map, mechanistically investigate and pharmacologically interfere with metabolic dependencies, beyond glutamine addiction.

cancer biology↗

bioRxiv2021

Epithelial-mesenchymal transition is the main driver of intrinsic metabolism in cancer cell lines

A fundamental feature of cancer cells is genomic heterogeneity. It is a main driver of phenotypic differences, including the response to drugs, and therefore a key factor in therapy selection. Motivated by the increasing role attributed to metabolic reprogramming in tumor development, we wondered how genomic heterogeneity affects metabolic phenotype. To this end, we profiled the intracellular metabolome of 180 cancer cell lines grown in similar conditions to exclude environmental factors. For each cell line, we estimate activity for 49 pathways across the whole metabolic network. Upon clustering of activity data, we found a convergence into only two major metabolic types. These were further characterized by 13C-flux analysis, lipidomics, and analysis of sensitivity to perturbations. These experiments revealed differences in lipid, mitochondrial, and carbohydrate metabolism between the two major types. Finally, a thorough integration of our metabolic data with multiple omics data revealed a strong association with markers of epithelial-mesenchymal transition (EMT). Our analysis indicates that in absence of variations imposed by the microenvironment, the metabolism of cancer cell lines falls into only two major classes despite genetic heterogeneity.

systems biology↗

bioRxiv2018

A framework for large-scale dynamic metabolome drug profiling in mammalian cells: a case study analysis of the anti-cancer drug dichloroacetate

Metabolic profiling of cell line collections have become an invaluable tool to study disease etiology, drug modes of action and personalized medicine. However, large-scale in vitro dynamic metabolic profiling is limited by time-consuming sampling and complex measurement procedures. By adapting an MS-based metabolomics workflow for high-throughput profiling of diverse adherent mammalian cells, we establish a technique for the rapid measurement and analysis of drug-induced dynamic changes in intracellular metabolites. This methodology is scalable to large compound libraries and is here applied to study the mechanism underlying the toxic effect of dichloroacetate in ovarian cancer cell lines. System-level analysis of the metabolic responses revealed a key and unexpected role of CoA imbalance in dichloroacetate toxicity. The herein proposed strategy for large-scale drug metabolic profiling is complementary to other molecular profiling techniques, opening new scientific and drug-discovery opportunities.

systems biology↗

bioRxiv2018

Charting the cross-functional map between transcription factors and cancer metabolism

Transcriptional reprogramming of cellular metabolism is a hallmark feature of cancer. However, a systematic approach to study the role of transcription factors (TFs) in mediating cancer metabolic rewiring is missing. Here, we chart a genome-scale map of TF-metabolite associations in human using a new combined computational-experimental framework for large-scale metabolic profiling of adherent cell lines, and the integration of newly generated intracellular metabolic profiles of 54 cancer cell lines with transcriptomic and proteomic data. We unravel a large space of dependencies between TFs and central metabolic pathways, suggesting that the regulation of carbon metabolism in tumors may be more diverse and flexible than previously appreciated. This map provides an unprecedented resource to predict TFs responsible for metabolic transformation in patient-derived tumor samples, opening new opportunities in designing modulators of oncogenic TFs and in understanding disease etiology.

systems biology↗