In exponentially growing bacteria, expression of heterologous protein impedes cellular growth rates. Quantitative understanding of the relationship between expression and growth rate will advance our ability to forward engineer bacteria, important for metabolic engineering and synthetic biology applications. Recently, a work described a scaling model based on optimal allocation of ribosomes for protein translation. This model quantitatively predicts a linear relationship between microbial growth rate and heterologous protein expression with no free parameters. With the aim of validating this model, we have rigorously quantified the fitness cost of gene expression by using a library of synthetic constitutive promoters to drive expression of two separate proteins (eGFP and amiE) in E. coli in different strains and growth media. In all cases, we demonstrate that the fitness cost is consistent with the previous findings. We expand upon the previous theory by introducing a simple promoter activity model to quantitatively predict how basal promoter strength relates to growth rate and protein expression. We then estimate the amount of protein expression needed to support high flux through a heterologous metabolic pathway and predict the sizable fitness cost associated with enzyme production. This work has broad implications across applied biological sciences because it allows for prediction of the interplay between promoter strength, protein expression, and the resulting cost to microbial growth rates.

The protein kinase and phosphatase enzymes within a cell catalyze the addition or removal of a phosphate group onto a protein respectively, and previous research has shown their involvement in nearly all cell‐signaling pathways. A consequence of this is that the disruption of the function of a particular kinase or phosphatase may lead to the development of diseases such as cancer. A major goal of chemical biology is to develop methods that allow for a detailed understanding of cell‐signaling pathways. However, current methods for studying the roles of these enzymes in signaling such as CRISPR‐Cas9 and siRNA for gene knockout suffer from potential compensatory mechanisms in the cell. Our research has led to the development of a potentially general approach for controlling enzyme activity via insertion of small peptide chains (BH3 helices) which bind selectively to a protein partner (Bcl‐xL) (Figure 1) for allosteric inhibition of kinase activity. Kinase activity can then be modulated by the addition of a specific small molecule that disrupts BH3/Bcl‐xL interactions thus providing specific control over turning on a single type of protein kinase within a cell. This approach is distinct compared to an approach by Professor Shokat that allows turning off activity of individual protein kinases in cells. We have shown success with this model in live cells when applied to the tyrosine‐protein kinase c‐Src, and our current project focuses on applying the model to other homologous tyrosine‐protein kinases. If successful, this research will provide greater insight into the role of specific kinases in cell‐signaling pathways, and thus allow for the development of genetic and small molecule therapeutics targeted towards dysfunctional kinases.Support or Funding InformationThis work was supported by the National Institutes of Health [1R01GM115595‐01] and the National Science Foundation [CHE‐1506091].This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.