Multi-scale stochastic modelling for single-cell characterizations of pluripotency

• Antragsteller: Professor Dr. Fabian Theis
• Fachliche Zuordnung: Bioinformatik und Theoretische Biologie
• Förderung: Förderung von 2011 bis 2015
• Projektkennung: Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 195121912

We propose to use stochastic multi-scale modeling techniques to further our understanding of stem cell maintenance and exit of pluripotency. Our key goals are (a) the integration of diverse information into a single model of pluripotency, (b) the prediction of novel molecular interactions and (c) quantitative predictions on systems perturbations e.g. for reprogramming. These aspects are commonly realized on different scales, from large-scale information integration systems to small-scale dynamical quantitative models. Here we propose to bridge the gap of the more commonly available large-scale high-throughput observations to single-cell small-scale data by first inferring a meso-scale qualitative model from literature information and high-throughput data, and then decomposing the model into small-scale network motifs, whose dynamics can be studied in full quantification and can be compared with time-resolved single-cell data. Since on both scales, effects of population heterogeneities and stochastic gene expression can be expected, we decided to use stochastic models, which generalize existing deterministic models. The methodological novelty is to infer stochastic models using Bayesian learning methods after moment truncation. We expect relevant biological outcomes from both models and their combination: From the qualitative model we want to infer possible novel interactions necessary to reproduce observed expression patterns. On the small-scale dynamic level we want to predict distributions of cell numbers and resting times in the pluripotent state, to infer model parameters from single-cell data, and to quantitatively delineate plausible model perturbations. Ultimately we may thus be able to derive regulatory mechanisms during cellular reprogramming.

• DFG-Verfahren: Schwerpunktprogramme
• Teilprojekt zu: SPP 1356: Pluripotency and Cellular Reprogramming