Coevolutionary Patterns in Cytochrome c Oxidase Subunit I Depend on Structural and Functional Context

Episodic evolution of coadapted sets of amino acid sites in mitochondrial proteins

The rate of evolution differs between protein sites and changes with time. However, the link between these two phenomena remains poorly understood. Here, we design a phylogenetic approach for distinguishing pairs of amino acid sites that evolve concordantly, i.e., such that substitutions at one site trigger subsequent substitutions at the other; and also pairs of sites that evolve discordantly, so that substitutions at one site impede subsequent substitutions at the other. We distinguish groups of amino acid sites that undergo coordinated evolution and evolve discordantly from other such groups. In mitochondrion-encoded proteins of metazoans and fungi, we show that concordantly evolving sites are clustered in protein structures. By analysing the phylogenetic patterns of substitutions at concordantly and discordantly evolving site pairs, we find that concordant evolution has two distinct causes: epistatic interactions between amino acid substitutions and episodes of selection independently affecting substitutions at different sites. The rate of substitutions at concordantly evolving groups of protein sites changes in the course of evolution, indicating episodes of selection limited to some of the lineages. The phylogenetic positions of these changes are consistent between proteins, suggesting common selective forces underlying them.

The mode and rate of evolution of a protein site depends on the effect of its mutations on protein fitness. The fitness effect of a mutation itself can change in the course of evolution for at least two reasons. First, it can be modulated by substitutions occurring at other sites, a phenomenon called epistasis. Second, changes in selection can be non-epistatic, affecting sites independently of one another. Here, we analyse substitutions accumulated by the evolving lineages of the five proteins encoded by the mitochondrial genomes of thousands of species of metazoans and fungi. We show that substitutions at different amino acid sites occur in a coordinated fashion, and this coordination is caused both by epistasis and by episodes of selection affecting groups of sites. We partition each protein into several groups of concordantly evolving sites such that evolution of sites from different groups is discordant, and show that the proteins encoded by the mitochondrial genome consist of coevolving structural blocks. Some of these blocks have a clear functional specialization, e.g. are associated with interfaces between proteins composing respiratory complexes. Together, our results reveal a previously unrecognized complexity in the causes of variation in evolutionary rates between protein sites.

Genetic hitchhiking, mitonuclear coadaptation, and the origins of mt DNA barcode gaps

DNA barcoding based on mitochondrial (mt) nucleotide sequences is an enigma. Neutral models of mt evolution predict DNA barcoding cannot work for recently diverged taxa, and yet, mt DNA barcoding accurately delimits species for many bilaterian animals. Meanwhile, mt DNA barcoding often fails for plants and fungi. I propose that because mt gene products must cofunction with nuclear gene products, the evolution of mt genomes is best understood with full consideration of the two environments that impose selective pressure on mt genes: the external environment and the internal genomic environment. Moreover, it is critical to fully consider the potential for adaptive evolution of not just protein products of mt genes but also of mt transfer RNAs and mt ribosomal RNAs. The tight linkage of genes on mt genomes that do not engage in recombination could facilitate selective sweeps whenever there is positive selection on any element in the mt genome, leading to the purging of mt genetic diversity within a population and to the rapid fixation of novel mt DNA sequences. Accordingly, the most important factor determining whether or not mt DNA sequences diagnose species boundaries may be the extent to which the mt chromosomes engage in recombination.

Molecular Characterization of Nippostrongylus brasiliensis (Nematoda: Heligmosomatidae) from Mus musculus in India

Mus musculus (Rodentia: Muridae) has generally been infected with a rodent hookworm Nippostrongylus brasiliensis. In this report, we present morphological and molecular identification of N. brasiliensis by light and scanning electron microscopy and PCR amplification of mitochondrial cytochrome c oxidase subunit 1 (cox1) gene and the protein sequences encoded by cox1 gene, respectively. Despite the use of N. brasiliensis in many biochemistry studies from India, their taxonomic identification was not fully understood, especially at the species level, and no molecular data is available in GenBank from India. Sequence analysis of cox1 gene in this study revealed that the present specimen showed close identity with the same species available in GenBank, confirming that the species is N. brasiliensis. This study represents the first record of molecular identification of N. brasiliensis from India and the protein structure to better understand the comparative phylogenetic characteristics.

Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.

Contingency and entrenchment in protein evolution under purifying selection

The phenotypic effect of an allele at one genetic site may depend on alleles at other sites, a phenomenon known as epistasis. Epistasis can profoundly influence the process of evolution in populations and shape the patterns of protein divergence across species. Whereas epistasis between adaptive substitutions has been studied extensively, relatively little is known about epistasis under purifying selection. Here we use computational models of thermodynamic stability in a ligand-binding protein to explore the structure of epistasis in simulations of protein sequence evolution. Even though the predicted effects on stability of random mutations are almost completely additive, the mutations that fix under purifying selection are enriched for epistasis. In particular, the mutations that fix are contingent on previous substitutions: Although nearly neutral at their time of fixation, these mutations would be deleterious in the absence of preceding substitutions. Conversely, substitutions under purifying selection are subsequently entrenched by epistasis with later substitutions: They become increasingly deleterious to revert over time. Our results imply that, even under purifying selection, protein sequence evolution is often contingent on history and so it cannot be predicted by the phenotypic effects of mutations assayed in the ancestral background.

H2rs: deducing evolutionary and functionally important residue positions by means of an entropy and similarity based analysis of multiple sequence alignments

BACKGROUND

The identification of functionally important residue positions is an important task of computational biology. Methods of correlation analysis allow for the identification of pairs of residue positions, whose occupancy is mutually dependent due to constraints imposed by protein structure or function. A common measure assessing these dependencies is the mutual information, which is based on Shannon's information theory that utilizes probabilities only. Consequently, such approaches do not consider the similarity of residue pairs, which may degrade the algorithm's performance. One typical algorithm is H2r, which characterizes each individual residue position k by the conn(k)-value, which is the number of significantly correlated pairs it belongs to.

RESULTS

To improve specificity of H2r, we developed a revised algorithm, named H2rs, which is based on the von Neumann entropy (vNE). To compute the corresponding mutual information, a matrix A is required, which assesses the similarity of residue pairs. We determined A by deducing substitution frequencies from contacting residue pairs observed in the homologs of 35 809 proteins, whose structure is known. In analogy to H2r, the enhanced algorithm computes a normalized conn(k)-value. Within the framework of H2rs, only statistically significant vNE values were considered. To decide on significance, the algorithm calculates a p-value by performing a randomization test for each individual pair of residue positions. The analysis of a large in silico testbed demonstrated that specificity and precision were higher for H2rs than for H2r and two other methods of correlation analysis. The gain in prediction quality is further confirmed by a detailed assessment of five well-studied enzymes. The outcome of H2rs and of a method that predicts contacting residue positions (PSICOV) overlapped only marginally. H2rs can be downloaded from http://www-bioinf.uni-regensburg.de.

CONCLUSIONS

Considering substitution frequencies for residue pairs by means of the von Neumann entropy and a p-value improved the success rate in identifying important residue positions. The integration of proven statistical concepts and normalization allows for an easier comparison of results obtained with different proteins. Comparing the outcome of the local method H2rs and of the global method PSICOV indicates that such methods supplement each other and have different scopes of application.

Computational enzyme design approaches with significant biological outcomes: progress and challenges

Enzymes are powerful biocatalysts, however, so far there is still a large gap between the number of enzyme-based practical applications and that of naturally occurring enzymes. Multiple experimental approaches have been applied to generate nearly all possible mutations of target enzymes, allowing the identification of desirable variants with improved properties to meet the practical needs. Meanwhile, an increasing number of computational methods have been developed to assist in the modification of enzymes during the past few decades. With the development of bioinformatic algorithms, computational approaches are now able to provide more precise guidance for enzyme engineering and make it more efficient and less laborious. In this review, we summarize the recent advances of method development with significant biological outcomes to provide important insights into successful computational protein designs. We also discuss the limitations and challenges of existing methods and the future directions that should improve them.

A novel empirical mutual information approach to identify co-evolving amino acid positions of influenza A viruses

Mutual information (MI) is an approach commonly used to estimate the evolutionary correlation of 2 amino acid sites. Although several MI methods exist, prior to our contribution no systematic method had been developed to assess their performance, or to establish numerical thresholds to detect co-evolving amino acid sites. The current study performed a Markov chain Monte Carlo (MCMC) algorithm on influenza viral sequences to capture their evolutionary characteristics. A consensus maximum clade credibility (MCC) tree was estimated from the samples, together with their amino acid substitution statistics, from which we generated synthetic sequences of known dependent and independent paired amino acid sites. A pair-to-pair and influenza-specific amino acid substitution matrix (P2PFLU) incorporated into Bayesian Evolutionary Analysis Sampling Trees (BEAST) enumerated these synthetic sequences. The sequences inherited evolutionary features and co-varying characteristics from the real viral sequences, rendering these synthetic data ideal for exploring their co-evolving features. For the MI measure, we proposed a novel metric called the empirical MI (MI(Em)), which outperformed other MI measures in analysis of receiver operating characteristics (ROC). We implemented our approach on 1086 all-time PB2 sequences of influenza A H5N1 viruses, in which we found 97 sites exhibiting co-evolutionary substitution of one or more amino acid sites. In particular, PB2 451, along with eight other PB2 sites of various MI(Em) scores, was found to co-evolve with PB2 627, a known species-associated amino acid residue which plays a critical role in influenza virus replication.

Amino acid coevolution induces an evolutionary Stokes shift

The process of amino acid replacement in proteins is context-dependent, with substitution rates influenced by local structure, functional role, and amino acids at other locations. Predicting how these differences affect replacement processes is difficult. To make such inference easier, it is often assumed that the acceptabilities of different amino acids at a position are constant. However, evolutionary interactions among residue positions will tend to invalidate this assumption. Here, we use simulations of purple acid phosphatase evolution to show that amino acid propensities at a position undergo predictable change after an amino acid replacement at that position. After a replacement, the new amino acid and similar amino acids tend to become gradually more acceptable over time at that position. In other words, proteins tend to equilibrate to the presence of an amino acid at a position through replacements at other positions. Such a shift is reminiscent of the spectroscopy effect known as the Stokes shift, where molecules receiving a quantum of energy and moving to a higher electronic state will adjust to the new state and emit a smaller quantum of energy whenever they shift back down to the original ground state. Predictions of changes in stability in real proteins show that mutation reversals become less favorable over time, and thus, broadly support our results. The observation of an evolutionary Stokes shift has profound implications for the study of protein evolution and the modeling of evolutionary processes.

Coevolution of amino acid residues in the key photosynthetic enzyme Rubisco

BACKGROUND

One of the key forces shaping proteins is coevolution of amino acid residues. Knowing which residues coevolve in a particular protein may facilitate our understanding of protein evolution, structure and function, and help to identify substitutions that may lead to desired changes in enzyme kinetics. Rubisco, the most abundant enzyme in biosphere, plays an essential role in the process of carbon fixation through photosynthesis, thus facilitating life on Earth. This makes Rubisco an important model system for studying the dynamics of protein fitness optimization on the evolutionary landscape. In this study we investigated the selective and coevolutionary forces acting on large subunit of land plants Rubisco using Markov models of codon substitution and clustering approaches applied to amino acid substitution histories.

RESULTS

We found that both selection and coevolution shape Rubisco, and that positively selected and coevolving residues have their specifically favored amino acid composition and pairing preference. The mapping of these residues on the known Rubisco tertiary structures showed that the coevolving residues tend to be in closer proximity with each other compared to the background, while positively selected residues tend to be further away from each other. This study also reveals that the residues under positive selection or coevolutionary force are located within functionally important regions and that some residues are targets of both positive selection and coevolution at the same time.

CONCLUSION

Our results demonstrate that coevolution of residues is common in Rubisco of land plants and that there is an overlap between coevolving and positively selected residues. Knowledge of which Rubisco residues are coevolving and positively selected could be used for further work on structural modeling and identification of substitutions that may be changed in order to improve efficiency of this important enzyme in crops.

Mitochondrial-nuclear interactions and accelerated compensatory evolution: evidence from the primate cytochrome C oxidase complex

Accelerated rates of mitochondrial protein evolution have been proposed to reflect Darwinian coadaptation for efficient energy production for mammalian flight and brain activity. However, several features of mammalian mtDNA (absence of recombination, small effective population size, and high mutation rate) promote genome degradation through the accumulation of weakly deleterious mutations. Here, we present evidence for "compensatory" adaptive substitutions in nuclear DNA- (nDNA) encoded mitochondrial proteins to prevent fitness decline in primate mitochondrial protein complexes. We show that high mutation rate and small effective population size, key features of primate mitochondrial genomes, can accelerate compensatory adaptive evolution in nDNA-encoded genes. We combine phylogenetic information and the 3D structure of the cytochrome c oxidase (COX) complex to test for accelerated compensatory changes among interacting sites. Physical interactions among mtDNA- and nDNA-encoded components are critical in COX evolution; amino acids in close physical proximity in the 3D structure show a strong tendency for correlated evolution among lineages. Only nuclear-encoded components of COX show evidence for positive selection and adaptive nDNA-encoded changes tend to follow mtDNA-encoded amino acid changes at nearby sites in the 3D structure. This bias in the temporal order of substitutions supports compensatory weak selection as a major factor in accelerated primate COX evolution.

Searching for evidence of selection in avian DNA barcodes

The barcode of life project has assembled a tremendous number of mitochondrial cytochrome c oxidase I (COI) sequences. Although these sequences were gathered to develop a DNA-based system for species identification, it has been suggested that further biological inferences may also be derived from this wealth of data. Recurrent selective sweeps have been invoked as an evolutionary mechanism to explain limited intraspecific COI diversity, particularly in birds, but this hypothesis has not been formally tested. In this study, I collated COI sequences from previous barcoding studies on birds and tested them for evidence of selection. Using this expanded data set, I re-examined the relationships between intraspecific diversity and interspecific divergence and sampling effort, respectively. I employed the McDonald-Kreitman test to test for neutrality in sequence evolution between closely related pairs of species. Because amino acid sequences were generally constrained between closely related pairs, I also included broader intra-order comparisons to quantify patterns of protein variation in avian COI sequences. Lastly, using 22 published whole mitochondrial genomes, I compared the evolutionary rate of COI against the other 12 protein-coding mitochondrial genes to assess intragenomic variability. I found no conclusive evidence of selective sweeps. Most evidence pointed to an overall trend of strong purifying selection and functional constraint. The COI protein did vary across the class Aves, but to a very limited extent. COI was the least variable gene in the mitochondrial genome, suggesting that other genes might be more informative for probing factors constraining mitochondrial variation within species.

Correlated mutations: a hallmark of phenotypic amino acid substitutions

Point mutations resulting in the substitution of a single amino acid can cause severe functional consequences, but can also be completely harmless. Understanding what determines the phenotypical impact is important both for planning targeted mutation experiments in the laboratory and for analyzing naturally occurring mutations found in patients. Common wisdom suggests using the extent of evolutionary conservation of a residue or a sequence motif as an indicator of its functional importance and thus vulnerability in case of mutation. In this work, we put forward the hypothesis that in addition to conservation, co-evolution of residues in a protein influences the likelihood of a residue to be functionally important and thus associated with disease. While the basic idea of a relation between co-evolution and functional sites has been explored before, we have conducted the first systematic and comprehensive analysis of point mutations causing disease in humans with respect to correlated mutations. We included 14,211 distinct positions with known disease-causing point mutations in 1,153 human proteins in our analysis. Our data show that (1) correlated positions are significantly more likely to be disease-associated than expected by chance, and that (2) this signal cannot be explained by conservation patterns of individual sequence positions. Although correlated residues have primarily been used to predict contact sites, our data are in agreement with previous observations that (3) many such correlations do not relate to physical contacts between amino acid residues. Access to our analysis results are provided at http://webclu.bio.wzw.tum.de/~pagel/supplements/correlated-positions/.

Point mutations (i.e., changes of a single sequence element) can have a severe impact on protein function. Many diseases are caused by such minute defects. On the other hand, the majority of such mutations does not lead to noticeable effects. Although previous research has revealed important aspects that influence or predict the chance of a mutation to cause disease, much remains to be learned before we fully understand this complex problem. In our work, we use the observation that sometimes certain positions in a protein mutate in an apparently correlated fashion and analyze this correlation with respect to mutation vulnerability. Our results show that positions exhibiting evolutionary correlation are significantly more likely to be vulnerable to mutation than average positions. On one hand, our data further support the concept of correlated positions to not only be associated with protein contacts but also functional sites and/or disease positions (as introduced by others). On the other hand, this could be useful to further improve the understanding and prediction of the consequences of mutations. Our work is the first to attempt a large-scale quantitation of this relationship.

An integrated view of molecular coevolution in protein-protein interactions

Protein-protein interactions effectively mediate molecular function. They are the result of specific interactions between protein interfaces and are maintained by the action of evolutionary pressure on the regions of the interacting proteins that contribute to binding. For the most part, selection restricts amino acid replacements, accounting for the conservation of binding interfaces. However, in some cases, change in one protein will be mitigated by compensatory change in its binding partner, maintaining function in the face of evolutionary change. There have been several attempts to use correlations in sequence evolution to predict interactions of proteins. Most commonly, these approaches use the entire sequence to identify correlations and so infer probable binding. However, other factors such as shared evolutionary history and similarities in the rates of evolution confound these whole-sequence-based approaches. Here, we discuss recent work on this topic and argue that both site-specific coevolutionary change and whole-sequence evolution contribute to evolutionary signals in sets of interacting proteins. We discuss the relative effects of both types of selection and how they might be identified. This permits an integrated view of protein-protein interactions, their evolution, and coevolution.

Evolution in protein interaction networks: co-evolution, rewiring and the role of duplication

Molecular function is the result of proteins working together, mediated by highly specific interactions. Maintenance and change of protein interactions can thus be considered one of the main links between molecular function and mutation. As a consequence, protein interaction datasets can be used to study functional evolution directly. In terms of constraining change, the co-evolution of interacting molecules is a very subtle process. This has implications for the signal being used to predict protein–protein interactions. In terms of functional change, the ‘rewiring’ of interaction networks, gene duplication is critically important. Interestingly, once duplication has occurred, the genes involved have different probabilities of being retained related to how they were generated. In the present paper, we discuss some of our recent work in this area.

Identification of coevolving residues and coevolution potentials emphasizing structure, bond formation and catalytic coordination in protein evolution

The structure and function of a protein is dependent on coordinated interactions between its residues. The selective pressures associated with a mutation at one site should therefore depend on the amino acid identity of interacting sites. Mutual information has previously been applied to multiple sequence alignments as a means of detecting coevolutionary interactions. Here, we introduce a refinement of the mutual information method that: 1) removes a significant, non-coevolutionary bias and 2) accounts for heteroscedasticity. Using a large, non-overlapping database of protein alignments, we demonstrate that predicted coevolving residue-pairs tend to lie in close physical proximity. We introduce coevolution potentials as a novel measure of the propensity for the 20 amino acids to pair amongst predicted coevolutionary interactions. Ionic, hydrogen, and disulfide bond-forming pairs exhibited the highest potentials. Finally, we demonstrate that pairs of catalytic residues have a significantly increased likelihood to be identified as coevolving. These correlations to distinct protein features verify the accuracy of our algorithm and are consistent with a model of coevolution in which selective pressures towards preserving residue interactions act to shape the mutational landscape of a protein by restricting the set of admissible neutral mutations.

The effect of sequence evolution on protein structural divergence

The complex constraints imposed by protein structure and function result in varied rates of sequence and structural divergence in proteins. Analysis of sequence differences between homologous proteins can advance our understanding of structural divergence and some of the constraints that govern the evolution of these molecules. Here, we assess the relationship between amino acid sequence and structural divergence. Firstly, we demonstrate that the relationship between protein sequence and structural divergence is governed by a variety of evolutionary constraints, including solvent exposure and secondary structure. Secondly, although compensatory substitutions are widespread, we find many radical size-changing mutations that are not compensated by neighboring complementary changes. Instead, these noncompensated substitutions are mitigated by alteration of protein structure. These results suggest a combined mechanism of accommodating substitutions in proteins, involving both coevolution and structural accommodation. Such a mechanism can explain previously observed correlated substitutions of residues that are distant both in sequence and structure, allowing an integrated view of sequence and structural divergence of proteins.

Detecting coevolution without phylogenetic trees? Tree-ignorant metrics of coevolution perform as well as tree-aware metrics

BACKGROUND

Identifying coevolving positions in protein sequences has myriad applications, ranging from understanding and predicting the structure of single molecules to generating proteome-wide predictions of interactions. Algorithms for detecting coevolving positions can be classified into two categories: tree-aware, which incorporate knowledge of phylogeny, and tree-ignorant, which do not. Tree-ignorant methods are frequently orders of magnitude faster, but are widely held to be insufficiently accurate because of a confounding of shared ancestry with coevolution. We conjectured that by using a null distribution that appropriately controls for the shared-ancestry signal, tree-ignorant methods would exhibit equivalent statistical power to tree-aware methods. Using a novel t-test transformation of coevolution metrics, we systematically compared four tree-aware and five tree-ignorant coevolution algorithms, applying them to myoglobin and myosin. We further considered the influence of sequence recoding using reduced-state amino acid alphabets, a common tactic employed in coevolutionary analyses to improve both statistical and computational performance.

RESULTS

Consistent with our conjecture, the transformed tree-ignorant metrics (particularly Mutual Information) often outperformed the tree-aware metrics. Our examination of the effect of recoding suggested that charge-based alphabets were generally superior for identifying the stabilizing interactions in alpha helices. Performance was not always improved by recoding however, indicating that the choice of alphabet is critical.

CONCLUSION

The results suggest that t-test transformation of tree-ignorant metrics can be sufficient to control for patterns arising from shared ancestry.