Biology subjects

Reynolds, K. A.

Publications and source records attributed to Reynolds, K. A..

10 recordsLinked to original sources

bioRxiv2026

Protein Surface Site Determines the Evolutionary Accessibility of Allosteric Regulation

Domain recombination is a major source of new allosteric regulation in both evolved and engineered proteins. However, the sequence and structural features that govern where new allostery may emerge remain poorly understood. Here, we test the hypothesis that the evolutionary accessibility of allosteric regulation following domain insertion is constrained by local surface context, specifically association with pre-existing cooperative networks known as protein sectors. We began with two synthetic domain fusions wherein the Avena sativa light-oxygen-voltage (LOV2) domain was inserted into Escherichia coli dihydrofolate reductase (DHFR) at either a sector connected or non-sector connected surface. The insertion sites are only separated by five residues and both DHFR enzymes retain similar catalytic activity, yet the sector connected version exhibits a light-dependent allosteric phenotype, while the non-sector connected version does not. Using deep mutational scanning, we measured the effect of nearly all single point mutations on allostery in each chimera. The sector-connected DL121 was significantly more evolvable, possessing numerous allostery-tuning single mutants. In contrast, DL116 lacked statistically significant mutants that introduce allosteric regulation, suggesting the protein surface used by DL116 may be an evolutionary "dead end" for a regulatory phenotype. Surprisingly, DL116 did not show cooperative unfolding at temperatures up to 80 {degrees}C, suggesting that enhanced protein stability does not promote the evolvability of allosteric regulation as it does with other phenotypes. Together, our findings show that protein surface context influences the mutational pathways available for allosteric regulation, consistent with the view that sector-connected surface sites harbor a latent capacity for allostery while other locations are more evolutionarily inert.

biophysics↗

bioRxiv2026

Systematic CRISPRi screening reveals genetic modulators of E. coli isoprenoid production

Isoprenoid biosynthesis in E. coli is a promising source of high-value natural products. However, isoprenoid production imposes a substantial metabolic burden on cellular carbon and cofactor metabolism. Optimizing yields thus requires rebalancing gene expression throughout metabolism. To systematically identify the genes in E. coli central metabolism shaping isoprenoid yield, we established a high-throughput CRISPR interference (CRISPRi) assay to examine the impact of gene repression on production of the bright red carotenoid, lycopene. Our approach enables repression of both essential and non-essential genes and links gene expression perturbations to pathway yield and biomass. We screened a CRISPRi library targeting 180 E. coli genes and found 31 genes for which repression significantly modified lycopene yield. Genes whose repression increased lycopene yield were found across fatty acid, amino acid, central carbon, and isoprenoid metabolism as well as stress response pathways. This set included four genes in amino acid biosynthesis, one in phospholipid biosynthesis, and one in the stringent response that, to our knowledge, have not previously been implicated in lycopene production. In contrast, genes for which repression decreased yield were limited to isoprenoid biosynthesis, central carbon metabolism, and stress response pathways. Together, our work reveals genetic targets for increasing lycopene yield throughout metabolism, and defines a tractable, generalizable approach to mapping genetic factors that modulate biosynthetic pathway yield.

synthetic biology↗

bioRxiv2024

Local disorder is associated with enhanced catalysis in an engineered photoswitch

Domain insertion is a common strategy for introducing allosteric regulation in both engineered and evolved systems. In this approach, an "input" domain is covalently fused to an "output" domain with the goal of conferring new regulation. In prior work, we found that insertion of the LOV2 domain at evolutionarily conserved allosteric "hot spots" on the metabolic enzyme Dihydrofolate Reductase (DHFR) could confer modest light regulation of enzymatic activity. However, it was not clear if the newly established regulation was achieved by interdomain allosteric conformational coupling, or if it represented a "simpler" mechanism like coupling of LOV2 light activation to global folding stability of DHFR or light-dependent steric occlusion of the DHFR active site. To better understand how these newly formed domain fusions harness light-inducible disorder in LOV2 for allosteric activation, we biochemically characterized a representative synthetic fusion. We observed that LOV2 photoactivation simultaneously: (1) thermally destabilized the fusion and (2) lowered the DHFR catalytic transition free energy of the lit state relative to the dark state. Light-induced NMR chemical shift changes indicated that photochemically-initiated conformational changes propagated from LOV2 to the active site of DHFR. Moreover, ligand binding at DHFR modified LOV2 chemical shifts, demonstrating bidirectional coupling between domains. Examination of select allostery-tuning mutations found a modest negative correlation between the light-induced change in thermal stability and catalytic activity, suggesting an activity-stability tradeoff. Together our data indicate that a domain fusion event can realize localized conformational coupling between active sites even in the absence of extensive evolutionary optimization.

biochemistry↗

bioRxiv2023

The Genetic Landscape of a Metabolic Interaction

Enzyme abundance, catalytic activity, and ultimately sequence are all shaped by the need of growing cells to maintain metabolic flux while minimizing accumulation of deleterious intermediates. While much prior work has explored the constraints on protein sequence and evolution induced by physical protein-protein interactions, the sequence-level constraints emerging from non-binding functional interactions in metabolism remain unclear. To quantify how variation in the activity of one enzyme constrains the biochemical parameters and sequence of another, we focused on dihydrofolate reductase (DHFR) and thymidylate synthase (TYMS), a pair of enzymes catalyzing consecutive reactions in folate metabolism. We used deep mutational scanning to quantify the growth rate effect of 2,696 DHFR single mutations in 3 TYMS backgrounds under conditions selected to emphasize biochemical epistasis. Our data are well-described by a relatively simple enzyme velocity to growth rate model that quantifies how metabolic context tunes enzyme mutational tolerance. Together our results reveal the structural distribution of epistasis in a metabolic enzyme and establish a foundation for the design of multi-enzyme systems.

biochemistry↗

bioRxiv2022

A continuous epistasis model for predicting growth rate given combinatorial variation in gene expression and environment

The ability to predict changes in cellular growth rate given variation in gene expression is critical to engineer biosynthetic pathways and understand evolutionary constraints on mRNA abundance. However, the relationship between gene expression and growth rate is nonlinear and shaped by environmental and genetic context. To address these challenges, we examined the relationship between enzyme expression and E. coli growth rate for 36 metabolic gene pairs by measuring growth following 4,404 pairwise, titrated changes in enzyme abundance under varied environmental contexts. Using 20% of these data, we trained an interpretable epistatic model to predict growth rate following simultaneous expression and environmental perturbations. The models predictions were robust to significant genetic and environmental epistasis and at times approached the accuracy of biological replicates. Based on these results, we propose a strategy using sparsely sampled, low-order measurements to quantify genetic interaction landscapes on the pathway-wide or genomic scale in a single assay.

systems biology↗

bioRxiv2022

Resonant fluctuations of selection pressure exponentially accelerate fitness valley crossing

Two functional protein sequences can sometimes be separated by a fitness valley - a series of low or non-functional intermediate mutations that must be traversed to reach a more optimal or refined function. Time-varying selection pressure modulates evolutionary sampling of such valleys. Yet, how the amplitude and frequency of fluctuating selection influence the rate of protein evolution is poorly understood. Here, we derive a simple equation for the time-dependent probability of crossing a fitness valley as a function of evolutionary parameters: valley width, protein size, mutation rate, and selection pressure. The equation predicts that, under low selection pressure, the valley crossing rate is magnified by a factor that depends exponentially on valley width. However, after a characteristic time set by the evolutionary parameters, the rate rapidly decays. Thus, there is an optimal frequency of selection-pressure fluctuations that maximizes the rate of protein optimization. This result is reminiscent of the resonance frequency in mechanical systems. The equation unites empirical and theoretical results that were previously disconnected, and is consistent with time-dependent in vitro and clinical data. More generally, these results suggest that seasonal and climate oscillations could synchronously drive protein evolution at the resonant frequency across a range of organism hosts and timescales. This theory could also be applied to optimize de novo protein evolution in laboratory directed evolution using time-varying protocols.

evolutionary biology↗

bioRxiv2021

Structurally Distributed Surface Sites Tune Allosteric Regulation

Our ability to rationally optimize allosteric regulation is limited by incomplete knowledge of the mutations that tune allostery. Are these mutations few or abundant, structurally localized or distributed? To examine this, we conducted saturation mutagenesis of a synthetic allosteric switch in which Dihydrofolate reductase (DHFR) is regulated by a blue-light sensitive LOV2 domain. Using a high-throughput assay wherein DHFR catalytic activity is coupled to E. coli growth, we assessed the impact of 1548 viable DHFR single mutations on allostery. Despite most mutations being deleterious to activity, fewer than 5% of mutations had a statistically significant influence on allostery. Most allostery disrupting mutations were proximal to the LOV2 insertion site. In contrast, allostery enhancing mutations were structurally distributed and enriched on the protein surface. Combining several allostery enhancing mutations yielded near-additive improvements to dynamic range. Our results indicate a path towards optimizing allosteric function through variation at surface sites.

biophysics↗

bioRxiv2019

Modulating the cellular context broadly reshapes the mutational landscape of a model enzyme

Protein mutational landscapes are shaped by the cellular environment, but key factors and their quantitative effects are often unknown. Here we show that Lon, a quality control protease naturally absent in common E. coli expression strains, drastically reshapes the mutational landscape of the metabolic enzyme dihydrofolate reductase (DHFR). Selection under conditions that resolve highly active mutants reveals that 23.3% of all single point mutations in DHFR are advantageous in the absence of Lon, but advantageous mutations are largely suppressed when Lon is reintroduced. Protein stability measurements demonstrate extensive activity-stability tradeoffs for the advantageous mutants and provide a mechanistic explanation for Lons widespread impact. Our findings suggest possibilities for tuning mutational landscapes by modulating the cellular environment, with implications for protein design and combatting antibiotic resistance.

biophysics↗

bioRxiv2017

Evolution and Engineering of Allosteric Regulation in Protein Kinases

Allosteric regulation - the control of protein function by sites far from the active site - is a common feature of proteins that enables dynamic cellular responses. Reversible modifications such as phosphorylation are well suited to mediate such regulatory dynamics, yet the evolution of new allosteric regulation demands explanation. To understand this, we mutationally scanned the surface of a prototypical kinase to identify readily evolvable phosphorylation sites. The data reveal a set of spatially distributed \"hotspots\" that coevolve with the active site and preferentially modulate kinase activity. By engineering simple consensus phosphorylation sites at these hotspots we successfully rewired in vivo cell signaling. Beyond synthetic biology, the hotspots are frequently used by the diversity of natural allosteric regulatory mechanisms in the kinase family and exploited in human disease.\n\nONE SENTENCE SUMMARYCell signaling is easily rewired by introducing new phosphoregulation at latent allosteric surface sites.

systems biology↗

bioRxiv2017

An evolutionary module in central metabolism

Metabolic enzyme function and evolution is influenced by the larger context of a biochemical pathway - deleterious mutations or perturbations in one enzyme can often be compensated by mutations to others. To explore strategies for mapping adaptive dependencies between enzymes, we used a combination of comparative genomics and experiments to examine interactions with the model metabolic enzyme Dihydrofolate Reductase (DHFR). Biochemically, DHFR shares a metabolic intermediate with numerous folate metabolic enzymes. In contrast, comparative genomics analyses of synteny and gene co-occurrence indicate a sparse pattern of evolutionary couplings in which DHFR is coupled to the enzyme thymidylate synthase (TYMS), but is relatively independent from the rest of folate metabolism. To test this apparent modularity, we used quantitative growth rate measurements and forward evolution in E. coli to demonstrate that the two enzymes are coupled to one another, and can adapt independently from the remainder of the genome. Mechanistically, the coupling between DHFR and TYMS is driven by a constraint wherein TYMS activity must not greatly exceed that of DHFR - both to avoid depletion of reduced folates and prevent accumulation of the metabolic intermediate dihydrofolate. Extending our comparative genomics analyses genome-wide reveals over 200 gene pairs with statistical signatures similar to DHFR/TYMS, suggesting the possibility that cellular pathways might be decomposed into small adaptive units.

systems biology↗