Consequences of Genetic Recombination on Protein Folding Stability

Ancestral recombination graphs (ARGs) are an attractive means for quantitative genetic analysis of complex traits because they encode the realized genetic relatedness between a sample of individuals in the presence of genetic drift, recombination, and mutation. Data structures for efficiently storing ARGs can also be used to rapidly process millions of genomes, and are thus promising for fitting linear mixed models to large phenotype and genome datasets. Here, we study the problems of variance component estimation and prediction of genetic values with ARGs, by describing a generative model of complex traits with additive effects on an ARG, and then developing algorithms that use the ARG to solve these problems efficiently on biobank-scale datasets. We observe nearly linear scaling of runtime with sample size, which is achieved by using the succinct tree sequence representation of the ARG for implicit matrix-vector products, along with modern randomized linear algebra algorithms. We estimate variance components using restricted maximum likelihood, which we find performs substantially better than the Haseman-Elston method. In simulation tests, both variance component estimation and prediction of genetic values (using the best linear unbiased predictor) perform nearly as well with inferred ARGs as with true ARGs. We also discuss interpretations of the variance component estimates as mutational variance and additive genetic variance. We provide an implementation of the algorithms as a Python package tslmm, which leverages the tree sequence library tskit.

Factor XIII deficiency.

Secondary structure and folding stability of proteins adsorbed on silica particles – Pressure versus temperature denaturation

The evolution of structural proteins is generally constrained by the folding stability. However, little is known about the particular capacity of viral proteins to accommodate mutations that can potentially affect the protein stability and, in general, the evolution of the protein stability over time. As an illustrative model case, here, we investigated the evolution of the stability of the human immunodeficiency virus (HIV-1) protease (PR), which is a common HIV-1 drug target, under diverse evolutionary scenarios that include (1) intra-host virus evolution in a cohort of seventy-five patients sampled over time, (2) intra-host virus evolution sampled before and after specific PR-based treatments, and (3) inter-host evolution considering extant and ancestral (reconstructed) PR sequences from diverse HIV-1 subtypes. We also investigated the specific influence of currently known HIV-1 PR resistance mutations on the PR folding stability. We found that the HIV-1 PR stability fluctuated over time within a constant and wide range in any studied evolutionary scenario, accommodating multiple mutations that partially affected the stability while maintaining activity. We did not identify relationships between change of PR stability and diverse clinical parameters such as viral load, CD4+ T-cell counts, and a surrogate of time from infection. Counterintuitively, we predicted that nearly half of the studied HIV-1 PR resistance mutations do not significantly decrease stability, which, together with compensatory mutations, would allow the protein to adapt without requiring dramatic stability changes. We conclude that the HIV-1 PR presents a wide structural plasticity to acquire molecular adaptations without affecting the overall evolution of stability.

Protein folding stabilities are a major determinant of oxidation rates for buried methionine residues

Copper(II)-Induced Secondary Structure Changes and Reduced Folding Stability of the Prion Protein

Folding of protein in vivo typically occurs in a solution highly crowded by macromolecules and in a confined space. It has been found that the effects of macromolecular crowding and confinement are similar in terms of the enhancement of protein stability. However, these effects are often considered separately in theoretical and simulation studies. In this study, by using coarse-grained models and Langevin dynamics, we show that the two effects are additive to each other when they are both present. Both crowding and confinement give rise to the folding temperature and the folding stability of protein. It is shown that the folding free energy change due to crowding in the confined condition can be fitted to Minton scaled particle theory by assuming a linear dependence of the effective radius of the protein unfolded state on the volume fraction of crowders.

Over the last few decades, the analytical method of differential scanning calorimetry (DSC) has been established to investigate the stability, folding, and binding of proteins. The technique typically measures the differential heat between the test and reference samples. The deconvoluted thermogram can provide crucial information on process development and whether there are any stable transition states. Information about all the significant thermodynamical parameters can be extracted from the denaturation curve of a protein. DSC offers several advantages over other spectral methods like fluorescence and circular dichroism (CD) spectroscopy. For instance, CD and fluorescence spectra can only provide information on the secondary structural content of a protein, whereas DSC can be used to study protein stability and different transition states in folding. This chapter summarises the utility of DSC in studying protein stability and folding.

A mutation partially suppressing the UV sensitivity caused by recF143 in a uvrA6 background was located at codon 37 of recA where GTG (valine) became ATG (methionine). This mutation, originally named srf-803, was renamed recA803. Little if any suppression of the recF143 defect in UV induction of a lexA regulon promoter was detected. This led to the hypothesis that a defect in recombination repair of UV damage was suppressed by recA803. The mutant RecA protein (RecA803) was purified and compared with wild-type protein (RecA+) as a catalyst of formation of joint molecules. Under suboptimal conditions, RecA803 produces both a higher rate of formation and a higher yield of joint molecules. The suboptimal conditions tested included addition of single-stranded DNA binding protein to single-stranded DNA prior to addition of RecA. We hypothesize that the ability of RecA803 to overcome interference by single-stranded DNA binding protein is the property that allows recA803 to suppress partially the deficiency in repair caused by recF mutations in the uvrA6 background. Implications of this hypothesis for the function of RecF protein in recombination are discussed.

Proteins evolve at different rates. What drives the speed of protein sequence changes? Two main factors are a protein's folding stability and aggregation propensity. By combining the hydrophobic-polar (HP) model with the Zwanzig-Szabo-Bagchi rate theory, we find that: (i) Adaptation is strongly accelerated by selection pressure, explaining the broad variation from days to thousands of years over which organisms adapt to new environments. (ii) The proteins that adapt fastest are those that are not very stably folded, because their fitness landscapes are steepest. And because heating destabilizes folded proteins, we predict that cells should adapt faster when put into warmer rather than cooler environments. (iii) Increasing protein abundance slows down evolution (the substitution rate of the sequence) because a typical protein is not perfectly fit, so increasing its number of copies reduces the cell's fitness. (iv) However, chaperones can mitigate this abundance effect and accelerate evolution (also called evolutionary capacitance) by effectively enhancing protein stability. This model explains key observations about protein evolution rates.

Phylogenetic methods are widely used to reconstruct the evolutionary relationships among species and individuals. However, recombination can obscure ancestral relationships as individuals may inherit different regions of their genome from different ancestors. It is, therefore, often necessary to detect recombination events, locate recombination breakpoints, and select recombination-free alignments prior to reconstructing phylogenetic trees. While many earlier studies have examined the power of different methods to detect recombination, very few have examined the ability of these methods to accurately locate recombination breakpoints. In this study, we simulated genome sequences based on ancestral recombination graphs and explored the accuracy of three popular recombination detection methods: MaxChi, 3SEQ, and Genetic Algorithm Recombination Detection. The accuracy of inferred breakpoint locations was evaluated along with the key factors contributing to variation in accuracy across datasets. While many different genomic features contribute to the variation in performance across methods, the number of informative sites consistent with the pattern of inheritance between parent and recombinant child sequences always has the greatest contribution to accuracy. While partitioning sequence alignments based on identified recombination breakpoints can greatly decrease phylogenetic error, the quality of phylogenetic reconstructions depends very little on how breakpoints are chosen to partition the alignment. Our work sheds light on how different features of recombinant genomes affect the performance of recombination detection methods and suggests best practices for reconstructing phylogenies based on recombination-free alignments.

The Saccharomyces cerevisiae RDH54-encoded product, a member of the Swi2/Snf2 protein family, is needed for mitotic and meiotic interhomologue recombination and DNA repair. Previous biochemical studies employing Rdh54 purified from yeast cells have shown DNA-dependent ATP hydrolysis and DNA supercoiling by this protein, indicative of a DNA translocase function. Importantly, Rdh54 physically interacts with the Rad51 recombinase and promotes D-loop formation by the latter. Unfortunately, the low yield of Rdh54 from the yeast expression system has greatly hampered the progress on defining the functional interactions of this Swi2/Snf2-like factor with Rad51. Here we describe an E. coli expression system and purification scheme that together provide milligram quantities of nearly homogeneous Rdh54. Using this material, we demonstrate that Rdh54-mediated DNA supercoiling leads to transient DNA strand opening. Furthermore, at the expense of ATP hydrolysis, Rdh54 removes Rad51 from DNA. We furnish evidence that the Rad51 binding domain resides within the N terminus of Rdh54. Accordingly, N-terminal truncation mutants of Rdh54 that fail to bind Rad51 are also impaired for functional interactions with the latter. Interestingly, the rdh54 K352R mutation that ablates ATPase activity engenders a DNA repair defect even more severe than that seen in the rdh54Delta mutant. These results provide molecular information concerning the role of Rdh54 in homologous recombination and DNA repair, and they also demonstrate the functional significance of Rdh54.Rad51 complex formation. The Rdh54 expression and purification procedures described here should facilitate the functional dissection of this DNA recombination/repair factor.

Macromolecular crowding plays a pivotal role in shaping protein stability and bridges insights from in vitro studies to the cellular environment. We investigated the stability of CRABP I through urea melt studies in the presence of PEG 2000 and PEG 4000, monitoring fluorescence wavelength shifts as sensitive indicators of structural transitions. In the absence of crowding agents, CRABP I unfolded with Cm at 4.39 M urea, whereas both PEG variants shifted the unfolding transition to higher concentrations, indicating an enhanced stability. This stabilization reflects crowding-induced reshaping of the free energy landscape, where excluded-volume effects entropically favor the native compact state. PEG 4000, with its larger size, imposed stronger steric constraints and augmented preferential hydration, thereby reinforcing intramolecular interactions and restricting the access of urea to the hydrophobic core. Complementary molecular dynamics simulations corroborated these mechanisms, highlighting how macromolecular crowding governs protein folding pathways and stability under physiologically relevant conditions.

Amide-amide hydrogen bonds have been implicated in directing protein folding and enhancing protein stability. Inversion transfer (13)C NMR spectroscopy and IR spectroscopy were used to compare the ability of various amide solvents and of water to alter the rate of the cis-trans isomerization of the prolyl peptide bond of Ac-Gly-[β,δ-(13)C]Pro-OMe and the amide I vibrational mode of [(13)C=O]Ac-Pro-OMe. The results indicate that secondary amides are significantly weaker hydrogen bond donors than is formamide or water. These results are most consistent with models for protein folding in which the formation of secondary structure is a cooperative process that follows hydrophobic collapse. These results also suggest that a hydrogen bond between a main-chain oxygen and an asparagine or glutamine sidechain may contribute more to protein stability than does a main-chain-main-chain hydrogen bond.

Understanding the relative contributions of various evolutionary processes—purifying selection, neutral drift, and adaptation—is fundamental to evolutionary biology. A common metric to distinguish these processes is the ratio of nonsynonymous to synonymous substitutions (i.e., dN/dS) interpreted from the neutral theory as a null model. However, from biophysical considerations, mutations have non-negligible effects on the biophysical properties of proteins such as folding stability. In this work, we investigated how stability affects the rate of protein evolution in phylogenetic trees by using simulations that combine explicit protein sequences with associated stability changes. We first simulated myoglobin evolution in phylogenetic trees with a biophysically realistic approach that accounts for 3D structural information and estimates of changes in stability upon mutation. We then compared evolutionary rates inferred directly from simulation to those estimated using maximum-likelihood (ML) methods. We found that the dN/dS estimated by ML methods (ωML) is highly predictive of the per gene dN/dS inferred from the simulated phylogenetic trees. This agreement is strong in the regime of high stability where protein evolution is neutral. At low folding stabilities and under mutation-selection balance, we observe deviations from neutrality (per gene dN/dS > 1 and dN/dS < 1). We showed that although per gene dN/dS is robust to these deviations, ML tests for positive selection detect statistically significant per site dN/dS > 1. Altogether, we show how protein biophysics affects the dN/dS estimations and its subsequent interpretation. These results are important for improving the current approaches for detecting positive selection.