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Adkar, B. V.

Publications and source records attributed to Adkar, B. V..

4 recordsLinked to original sources

Allosteric communication between ligand binding domains modulates substrate inhibition in adenylate kinase

Enzymes play a vital role in life processes; they control chemical reactions and allow functional cycles to be synchronized. Many enzymes harness large-scale motions of their domains to achieve tremendous catalytic prowess and high selectivity for specific substrates. One outstanding example is provided by the three-domain enzyme adenylate kinase (AK), which catalyzes phosphotransfer between ATP to AMP. Here we study the phenomenon of substrate inhibition by AMP and its correlation with domain motions. Using single-molecule FRET spectroscopy, we show that AMP does not block access to the ATP binding site, neither by competitive binding to the ATP cognate site nor by directly closing the LID domain. Instead, inhibitory concentrations of AMP lead to a faster and more cooperative domain closure by ATP, leading in turn to an increased population of the closed state. The effect of AMP binding can be modulated through mutations throughout the structure of the enzyme, as shown by the screening of an extensive AK mutant library. Mutation of multiple conserved residues leads to increased substrate inhibition, suggesting a positive selection during evolution. Combining these insights, we developed a model that explains the complex activity of AK, particularly substrate inhibition, based on the experimentally observed opening and closing rates. Notably, the model indicates that the catalytic power is affected by the microsecond balance between the open and closed states of the enzyme. Our findings highlight the crucial role of protein motions in enzymatic activity. Significance StatementHow conformational dynamics affect the catalytic activity of enzymes remains a topic of active debate. We focus here on the domain closure dynamics of adenylate kinase (AK) and how they are affected by substrate inhibition. By screening an extensive mutant library, we show that this feature of the enzyme is well conserved in evolution. Importantly, domain closure is required in order to bring AKs substrates close together for their chemical reaction; single-molecule FRET studies directly measure the populations of the open and closed states. We find that overpopulation of the closed state can be detrimental to activity. The results allow us to develop a kinetic model that properly accounts for AK kinetics by combining conformational dynamics and biochemical steps.

biophysics↗

Substrate inhibition imposes fitness penalty at high protein stability

Proteins are only moderately stable. It has long been debated whether this narrow range of stabilities is solely a result of neutral drift towards lower stability or purifying selection against excess stability is also at work -- for which no experimental evidence was found so far. Here we show that mutations outside the active site in the essential E. coli enzyme adenylate kinase result in stability-dependent increase in substrate inhibition by AMP, thereby impairing overall enzyme activity at high stability. Such inhibition caused substantial fitness defects not only in the presence of excess substrate but also under physiological conditions. In the latter case, substrate inhibition caused differential accumulation of AMP in the stationary phase for the inhibition prone mutants. Further, we show that changes in flux through Adk could accurately describe the variation in fitness effects. Taken together, these data suggest that selection against substrate inhibition and hence excess stability may have resulted in a narrow range of optimal stability observed for modern proteins.

biophysics↗

Tradeoffs between microbial growth phases lead to frequency-dependent and non-transitive selection

Mutations in a microbial population can increase the frequency of a genotype not only by increasing its exponential growth rate, but also by decreasing its lag time or adjusting the yield (resource efficiency). The contribution of multiple life-history traits to selection is a critical question for evolutionary biology as we seek to predict the evolutionary fates of mutations. Here we use a model of microbial growth to show there are two distinct components of selection corresponding to the growth and lag phases, while the yield modulates their relative importance. The model predicts rich population dynamics when there are tradeo[ff]s between phases: multiple strains can coexist or exhibit bistability due to frequency-dependent selection, and strains can engage in rock-paper-scissors interactions due to non-transitive selection. We characterize the environmental conditions and patterns of traits necessary to realize these phenomena, which we show to be readily accessible to experiments. Our results provide a theoretical framework for analyzing high-throughput measurements of microbial growth traits, especially interpreting the pleiotropy and correlations between traits across mutants. This work also highlights the need for more comprehensive measurements of selection in simple microbial systems, where the concept of an ordinary fitness landscape breaks down.

evolutionary biology↗

Optimization of lag phase shapes the evolution of a bacterial enzyme

Mutations provide the variation that drives evolution, yet their effects on fitness remain poorly understood. Here we explore how mutations in the essential enzyme Adenylate Kinase (Adk) of E. coli affect multiple phases of population growth. We introduce a biophysical fitness landscape for these phases, showing how they depend on molecular and cellular properties of Adk. We find that Adk catalytic capacity in the cell (product of activity and abundance) is the major determinant of mutational fitness effects. We show that bacterial lag times are at a well-defined optimum with respect to Adks catalytic capacity, while exponential growth rates are only weakly affected by variation in Adk. Direct pairwise competitions between strains show how environmental conditions modulate the outcome of a competition where growth rates and lag times have a tradeoff, altogether shedding light on the multidimensional nature of fitness and its importance in the evolutionary optimization of enzymes.

evolutionary biology↗