Systems biology can offer a great deal of insight into evolution by quantitatively linking complex properties such as protein structure, folding, and function to the fitness of an organism. Although the link between diseases such as Alzheimer's and misfolding is well appreciated, directly showing the importance of protein folding to success in evolution has been more difficult. We show here that predicting success during adaptation can depend critically on enzyme kinetic and folding models. We used a 'weak link' method to favor mutations to an essential, but maladapted, adenylate kinase gene within a microbial population that resulted in the identification of five mutants that arose nearly simultaneously and competed for success. Physicochemical characterization of these mutants showed that, although steady-state enzyme activity is important, success within the population is critically dependent on resistance to denaturation and aggregation. A fitness function based on in vitro measurements of enzyme activity, reversible and irreversible unfolding, and the physiological context reproduces in vivo evolutionary fates in the population linking organismal adaptation to its physical basis.
Protein function is a balance between activity and stability. However, the relevance of stability-activity trade-offs for protein evolution and their impact on organismal fitness have been difficult to determine. Previously, we have linked organismal survival at increasing temperatures to adaptive changes to a single protein sequence through allelic replacement of an essential gene, adenylate kinase (adk), in a thermophile. In vivo continuous evolution of the temperature-sensitive thermophile has shown that the first step toward increased organismal fitness is mutation of glutamine-199 to arginine in the mesophilic enzyme (AKsub Q199R). Here, we show that although substitution of Arg-199 did confer a modest increase in stability (0.6 kcal mol(-1)at 20 degrees C; DeltaT(m) = 3.0 degrees C), it is a large change in the activity profile of the enzyme that is responsible for its exceptional robustness during the earlier experimental evolution study. Kinetic studies of AKsub Q199R show that it has a strong loss of enzymatic activity (>50%) at lower temperatures (20-45 degrees C) and a subsequent increase at elevated temperatures. The stability-activity trade-off observed for AKsub Q199R was linked to the rigidification of the overall structure through stabilization of a polypeptide loop containing Arg-199 that is part of the ATP-binding site of the enzyme. Structural analysis revealed the formation of new ionic interactions facilitated by Arg-199. Our results suggest that stability-activity trade-offs are employed readily as an evolutionary strategy during natural selection to increase organismal fitness.
Clostridium acetobutylicum is a natural producer of butanol, butyrate, acetone and ethanol. The pattern of metabolites reflects the partitioning of redox equivalents between hydrogen and carbon metabolites. Here the exogenous genes of ferredoxin-NAD(P) oxidoreductase (FdNR) and trans-enoyl-coenzyme reductase (TER) are introduced to three different Clostridium acetobutylicum strains to investigate the distribution of redox equivalents and butanol productivity. The FdNR improves NAD(P)H availability by capturing reducing power from ferredoxin. A butanol production of 9.01 g/L (36.9% higher than the control), and the highest ratios of butanol/acetate (7.02) and C/C (3.17) derived metabolites were obtained in the C acetobutylicum buk strain expressing FdNR. While the TER functions as an NAD(P)H oxidase, butanol production was decreased in the C. acetobutylicum strains containing TER. The results illustrate that metabolic flux can be significantly changed and directed into butanol or butyrate due to enhancement of NAD(P)H availability by controlling electron flow through the ferredoxin node.
Recent developments in metabolic engineering have led to the successful biosynthesis of valuable products, such as the precursor of the antimalarial compound, artemisinin, and opioid precursor, thebaine. Synthesizing these traditionally plant-derived compounds in genetically modified yeast cells introduces the possibility of significantly reducing the total time and resources required for their production, and in turn, allows these valuable compounds to become cheaper and more readily available. Most biosynthesis pathways used in metabolic engineering applications have been discovered manually, requiring a tedious search of existing literature and metabolic databases. However, the recent rapid development of available metabolic information has enabled the development of automated approaches for identifying novel pathways. Computer-assisted pathfinding has the potential to save biochemists time in the initial discovery steps of metabolic engineering. In this paper, we review the parameters and heuristics used to guide the search in recent pathfinding algorithms. These parameters and heuristics capture information on the metabolic network structure, compound structures, reaction features, and organism-specificity of pathways. No one metabolic pathfinding algorithm or search parameter stands out as the best to use broadly for solving the pathfinding problem, as each method and parameter has its own strengths and shortcomings. As assisted pathfinding approaches continue to become more sophisticated, the development of better methods for visualizing pathway results and integrating these results into existing metabolic engineering practices is also important for encouraging wider use of these pathfinding methods.
G protein–coupled receptor signaling is negatively regulated by both receptor internalization and regulator of G protein signaling (RGS) protein–stimulated inactivation of the G protein. The RGS protein can also positively regulate receptor signaling by binding to the receptor, thereby reducing receptor internalization.
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