Predictive shifts in free energy couple mutations to their phenotypic consequences

Abstract

Mutation is a critical mechanism by which evolution explores the functional landscape of proteins. Despite our ability to experimentally inflict mutations at will, it remains difficult to link sequence-level perturbations to systems-level responses. Here, we present a framework centered on measuring changes in the free energy of the system to link individual mutations in an allosteric transcriptional repressor to the parameters which govern its response. We find that the energetic effects of the mutations can be categorized into several classes which have characteristic curves as a function of the inducer concentration. We experimentally test these diagnostic predictions using the well-characterized LacI repressor ofEscherichia coli, probing several mutations in the DNA binding and inducer binding domains. We find that the change in gene expression due to a point mutation can be captured by modifying only the model parameters that describe the respective domain of the wild-type protein. These parameters appear to be insulated, with mutations in the DNA binding domain altering only the DNA affinity and those in the inducer binding domain altering only the allosteric parameters. Changing these subsets of parameters tunes the free energy of the system in a way that is concordant with theoretical expectations. Finally, we show that the induction profiles and resulting free energies associated with pairwise double mutants can be predicted with quantitative accuracy given knowledge of the single mutants, providing an avenue for identifying and quantifying epistatic interactions.

Physiological Adaptability and Parametric Versatility in a Simple Genetic Circuit

“…Despite the decrease in growth rate, both the fold-change in gene expression and the repressor copy number remains largely unaffected. We confirm this is the case by examining how the effective free energy of the system changes between carbon sources, a method we have used previously to elucidate parametric changes due to mutations within a transcription factor (15). This illustrates that the energetic parameters defining the fraction of active repressors and their affinity for the DNA are ignorant of the carbon-dependent physiological states of the cell.…”

“…Despite our knowledge of these modes of regulation, there remains a large disconnect between concrete, physical models of their behavior and experimental validation. The simple repression motif is perhaps the most thoroughly explored theoretically and experimentally (9) where equilibrium thermodynamic (10)(11)(12)(13)(14)(15) and kinetic (16)(17)(18)(19) models have been shown to accurately predict the level of gene expression in a variety of contexts. While these experiments involved variations of repressor copy number, operator sequence, concentration of an external inducer, and amino acid substitutions, none have explored how the physiological state of the cell as governed by external factors influences gene expression.…”

Systemic mutational rescue inEscherichia colielicited by a valency dependent, high affinity protein DNA interaction

“…The successful delivery of programmable synthetic organisms and novel synthetic macromolecules draws heavily on the original model of bacterial gene regulation proposed by Jacob and Monod (1961), and the subsequent validation work on the lac operon and the gene regulatory networks in bacteriophage Lambda. In a more recent study, Chure et al (2019) present a systems-based mathematical model based on the relationship between the specificity and interaction affinities of a series of Lac repressor mutants. These kinds of experiments will undoubtedly provide the basis of a more robust framework for designing controllable microbial systems.…”

“…Just as the lac operon has proven to be an enduring work-horse for both molecular biology (Jacob and Monod, 1961) and more recently systems biology (Chure et al, 2019), the cytosinespecific C-5 DNA methyltransferases (C5-DNMTs) represent a well-studied class of DNA modifying enzymes, most commonly associated with restriction and modification in prokaryotes, but also as facilitators of a range of epigenetic phenomena (Edwards et al, 2017).…”

Deciphering the regulatory genome ofEscherichia coli, one hundred promoters at a time

“…In particular, high-resolution studies like those described here yield quantitative predictions about promoter organization and protein-DNA interactions as described by energy matrices [6]. This allows us to employ the tools of statistical physics to describe the input-output properties of each of these promoters which can be explored much further with in-depth experimental dissection like those done by [16] and [17] and summarized in [18]. In this sense, the Sort-Seq approach can provide a quantitative framework to not only discover and quantitatively dissect regulatory interactions at the promoter level, but also provides an interpretable scheme to design genetic circuits with a desired expression output [19].…”