Using the yeast Saccharomyces cerevisiae as a model organism, we are interested in understanding and controlling aging and replicative lifespan at the single-cell level.
Which genes and gene networks are responsible from controlling the aging process? Which decision-making sequences can be executed to maximize the lifespan of a living system? Despite the fundamental nature of these questions, we have very limited understanding on the cellular mechanisms governing aging. Our laboratory applies quantitative Systems Biology approaches, single-cell time-dynamic imaging techniques, and novel microfluidic platforms to the study of this complex phenotype, with the goal of gaining novel insights into the regulation of cellular aging.
We are also interested in understanding how gene networks are rewired during evolution. Our work combines experimental, theoretical, and computational approaches to investigate general design principles that help gene networks robustly function in different genetic backgrounds and environmental conditions.
Projects in our lab make extensive use of single-cell level experimental methods such as fluorescence microscopy, microfluidic platforms, and flow cytometry. For a mechanistic understanding of experimental results, we also build and apply deterministic and stochastic models to describe and predict gene expression levels in single cells.