It is now well appreciated that in many evolutionarily significant cases, phenotypes evolve not due to the emergence of a new protein or modified protein functionality, but rather due to novelty in gene regulation. However, how organisms accommodate the challenges arising from modifications in gene regulations is not known. In an effort to understand cell adaptation to regulatory challenges, we have confronted yeast cells carrying a rewired regulatory circuit with a severe and unforeseen challenge. The essential HIS3 gene from the histidine biosynthesis pathway was placed under the exclusive regulation of the galactose utilization system (GAL). Glucose-containing medium strongly represses the GAL genes including HIS3, and in medium lacking histidine, these rewired cells are required to operate this essential gene.

We showed that a large fraction of cells could adapt within physiological time scales to grow in this medium and that this adapted state was inherited. The adaptation was due to a response of many individual cells to the change in environment and not due to selection of rare advantageous phenotypes. Such a mode of adaptation extends the common evolutionary framework and attests to the adaptive potential of regulatory circuits.

Next, we studied the gene expression response underlying the adaptation process. We showed that two yeast populations derived from a single steady-state mother population that exhibit a similar growth phenotype in response to an environmental challenge displayed diverse expression patterns of essential genes. Remarkably, within a population, sets of expressed genes exhibited coherent dynamics over many generations. Thus, the emerging gene-expression patterns resulted from collective population dynamics. This suggests that gene expression reflects a self-organization process coupled to population-environment dynamics.

Although protein content is an important determinant of the cell’s state it usually exhibits large cell-to-cell variation even for genetically identical cells. We measured the HIS3 protein levels in single cells at high temporal resolution by a home-made flow cytometer, monitoring the adapting populations in real-time. We found that the HIS3 distributions exhibit a universal shape: over long durations the protein-level distributions could be scaled by the first two moments and collapse into a single non-Gaussian curve. This emerging universality, which is not unique to adapting rewired cells, implies that protein fluctuations do not reflect any specific molecular or cellular mechanisms and the details are masked by a yet unknown buffering mechanism.