Proteome partitioning constraints in long-term laboratory evolution.

Adaptive laboratory evolution experiments provide a controlled context in which the dynamics of selection and adaptation can be followed in real-time at the single-nucleotide level. And yet this precision introduces hundreds of degrees-of-freedom as genetic changes accrue in parallel lineages over generations. On short timescales, physiological constraints have been leveraged to provide a coarse-grained view of bacterial gene expression characterized by a small set of phenomenological parameters.

On the design principles of metabolic flux sensing.

Metabolism is precisely coordinated, with the goal of balancing fluxes to maintain robust growth. However, coordinating fluxes requires information about rates, which can only be inferred through concentrations. While flux-sensitive metabolites have been reported, the design principles underlying such sensing have not been clearly elucidated.

Prediction of Stable Globular Proteins Using Negative Design with Non-native Backbone Ensembles.

Accurate predictions of protein stability have great potential to accelerate progress in computational protein design, yet the correlation of predicted and experimentally determined stabilities remains a significant challenge. To address this problem, we have developed a computational framework based on negative multistate design in which sequence energy is evaluated in the context of both native and non-native backbone ensembles. This framework was validated experimentally with the design of ten variants of streptococcal protein G domain β1 that retained the wild-type fold, and showed a very strong correlation between predicted and experimental stabilities (R(2) = 0.