Simulating cellular biology

Understanding how cells function at the single-cell level is key to diagnosing and comprehending the aetiology of many diseases. Using a systems biology approach, European scientists have devised a new way of predicting and personalising disease treatment.

Health

Accumulating evidence suggests that apart from the molecules, the majority of signalling pathways and interconnections are conserved in organisms ranging from yeast to humans. Unveiling the cellular regulatory network and reconstructing the complex signalling pathways governing essential cellular functions such as metabolism and cell cycle represents a significant scientific challenge. The key objective of the EU-funded UNICELLSYS project was to computationally reconstruct and model the different levels of biological organisation of eukaryotes. Baker's yeast was used as a model organism. These in silico tools could predict a cell's response to stimuli such as hormones as well as the outcome of various genetic or pharmacological perturbations. To develop these models, UNICELLSYS partners generated a large set of proteomics and metabolomics data of yeast grown under different conditions. Yeast was analysed at the single-cell level to account for cell-to-cell variation. The focus was on various signalling pathways (protein kinase A, MAPK, mTOR, Hog-mediated osmotic stress pathway). Particular emphasis was also placed on how proteins within these pathways interact using the yeast two-hybrid system and bioinformatics analysis. Significant effort went into integrating the different signalling pathways into a large-scale molecular dynamic model that could predict cellular behaviour given specific stimuli or growth perturbations. Cellular biochemistry was modelled through the development of an open-source software package called ManyCell. Besides delineating mechanisms implicated in signal transduction, metabolism and growth, this dynamic modelling generated invaluable insight into the ability of unicellular organisms to adapt to altered environmental conditions. Overall, the ability to predict the response of biological extrinsic or intrinsic perturbations is emerging as the new way of understanding how different cellular processes are interconnected. Importantly, in the long run, UNICELLSYS models could impact human health by predicting the outcome of therapeutic interventions with individual patients.