Amino acid contacts in proteins adapted to different temperatures: hydrophobic interactions and surface charges play a key role

Thermophiles, mesophiles, and psychrophiles have different amino acid frequencies in their proteins, probably because of the way the species adapt to very different temperatures in their environment. In this paper, we analyse how contacts between sidechains vary between homologous proteins from species that are adapted to different temperatures, but displaying relatively high sequence similarity. We investigate whether specific contacts between amino acids sidechains is a key factor in thermostabilisation in proteins. The dataset was divided into two subsets with optimal growth temperatures from 0–40 and 35–102°C. Comparison of homologues was made between low-temperature species and high-temperature species within each subset. We found that unspecific interactions like hydrophobic interactions in the core and solvent interactions and entropic effects at the surface, appear to be more important factors than specific contact types like salt bridges and aromatic clusters. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Analysis of Protein Three-Dimension Structure Using Amino Acids Depths

The issue of amino acid depth in proteins gives important insights to our understanding of protein’s three-dimensional structure. There has already been much research done in mathematical and statistical sciences regarding the general definitions, properties and algorithms describing the particle depth of spatially extended systems. We constructed a method of calculating the amino acids depths and applied it to a set of 527 protein structures. We propose the introduction of amino acid depth tendency factors for three-dimensional structures of proteins. The depth tendency factors relate not only to the hydrophobicity indices but also to the electrostatic charge. We found a relationship between the protein size and the number of residues using the distance between the deepest residue and surface residues. We made a prediction regarding the number of residues on the surface of a protein, the deepest amino acid, and the average depth, all of which are fitted well to a linear functional relationship with the length of the protein. Finally, we have predicted the depths of multiple peptides in protein’s three-dimension structure. Electronic supplementary material The online version of this article () contains supplementary material, which is available to authorized users.     

Chemical differences between seeds and elaiosomes indicate an adaptation to nutritional needs of ants

Ant-dispersed plants usually produce seeds with appendages (elaiosomes) as reward for ants. Plants that produce high-quality elaiosomes benefit because ants preferentially disperse their diaspores. We therefore hypothesized that seeds and elaiosomes differ in chemical composition in ways that make elaiosomes of high nutritional quality for ants, capable of providing essential dietary components that explain the increased fitness and higher gyne production documented for colonies with elaiosome consumption. To test the hypothesis we analysed the content and composition of lipids, amino acids, soluble carbohydrates, proteins and starch in seeds and elaiosomes of 15 central European ant-dispersed plants. After separating the different fractions, total lipids were determined gravimetrically, fatty acids and soluble carbohydrates were detected by gas chromatography (GC) and GC–mass spectrometry, free amino acids by an amino acid analyser while starch and protein were analysed photometrically. Seeds accumulated high molecular weight compounds such as proteins and starch, whereas elaiosomes accumulated more easily digestible low molecular weight compounds such as amino acids and monosaccharides. Analysis of similarities and similarity percentages analysis demonstrated that the composition of fatty acids, free amino acids and carbohydrates differed markedly between elaiosomes and seeds. The most important difference was in total amino acid content, which was on average 7.5 times higher in elaiosomes than in seeds. The difference was especially marked for the nitrogen-rich amino acid histidine. The availability of essential nutrients and, in some species, the higher nitrogen content in elaiosomes suggest that their nutritional value for larvae plays a key role in this interaction. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Low Contents of Carbon and Nitrogen in Highly Abundant Proteins: Evidence of Selection for the Economy of Atomic Composition

Proteins that assimilate particular elements were found to avoid using amino acids containing the element, which indicates that the metabolic constraints of amino acids may influence the evolution of proteins. We suspected that low contents of carbon, nitrogen, and sulfur may also be selected for economy in highly abundant proteins that consume large amounts of the resources of cells. By analyzing recently available proteomic data in Escherichia coli, Saccharomyces cerevisiae, and Schizosaccharomyces pombe, we found that at least the carbon and nitrogen contents in amino acid side chains are negatively correlated with protein abundance. An amino acid with a high number of carbon atoms in its side chain generally requires relatively more energy for its synthesis. Thus, it may be selected against in highly abundant proteins either because of economy in building blocks or because of economy in energy. Previous studies showed that highly abundant proteins preferentially use cheap (in terms of energy) amino acids. We found that the carbon content is still negatively correlated with protein abundance after controlling for the energetic cost of the amino acids. However, the negative correlation between protein abundance and energetic cost disappeared after controlling for carbon content. Building blocks seem to be more restricted than energy. It seems that the amino acid sequences of highly abundant proteins have to compromise between optimization for their biological functions and reducing the consumption of limiting resources. By contrast, the amino acid sequences of weakly expressed proteins are more likely to be optimized for their biological functions. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Amino Acid Metabolic Origin as an Evolutionary Influence on Protein Sequence in Yeast

The metabolic cycle of Saccharomyces cerevisiae consists of alternating oxidative (respiration) and reductive (glycolysis) energy-yielding reactions. The intracellular concentrations of amino acid precursors generated by these reactions oscillate accordingly, attaining maximal concentration during the middle of their respective yeast metabolic cycle phases. Typically, the amino acids themselves are most abundant at the end of their precursor’s phase. We show that this metabolic cycling has likely biased the amino acid composition of proteins across the S. cerevisiae genome. In particular, we observed that the metabolic source of amino acids is the single most important source of variation in the amino acid compositions of functionally related proteins and that this signal appears only in (facultative) organisms using both oxidative and reductive metabolism. Periodically expressed proteins are enriched for amino acids generated in the preceding phase of the metabolic cycle. Proteins expressed during the oxidative phase contain more glycolysis-derived amino acids, whereas proteins expressed during the reductive phase contain more respiration-derived amino acids. Rare amino acids (e.g., tryptophan) are greatly overrepresented or underrepresented, relative to the proteomic average, in periodically expressed proteins, whereas common amino acids vary by a few percent. Genome-wide, we infer that 20,000 to 60,000 residues have been modified by this previously unappreciated pressure. This trend is strongest in ancient proteins, suggesting that oscillating endogenous amino acid availability exerted genome-wide selective pressure on protein sequences across evolutionary time. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. Benjamin L. de Bivort and Ethan O. Perlstein have contributed equally to this work.     

Selection on Synthesis Cost Affects Interprotein Amino Acid Usage in All Three Domains of Life

Most investigations of the forces shaping protein evolution have focussed on protein function. However, cells are typically 50%–75% protein by dry weight, with protein expression levels distributed over five orders of magnitude. Cells may, therefore, be under considerable selection pressure to incorporate amino acids that are cheap to synthesize into proteins that are highly expressed. Such selection pressure has been demonstrated to alter amino acid usage in a few organisms, but whether “cost selection” is a general phenomenon remains unknown. One reason for this is that reliable protein expression level data is not available for most organisms. Accordingly, I have developed a new method for detecting cost selection. This method depends solely on interprotein gradients in amino acid usage. Applying it to an analysis of 43 whole genomes from all three domains of life, I show that selection on the synthesis cost of amino acids is a pervasive force in shaping the composition of proteins. Moreover, some amino acids have different price tags for different organisms—the cost of amino acids is changed for organisms living in hydrothermal vents compared with those living at the sea surface or for organisms that have difficulty acquiring elements such as nitrogen compared with those that do not—so I also investigated whether differences between organisms in amino acid usage might reflect differences in synthesis or acquisition costs. The results suggest that organisms evolve to alter amino acid usage in response to environmental conditions. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. [Reviewing Editor: Hector Musto]     

The Universal Trend of Amino Acid Gain–Loss is Caused by CpG Hypermutability

Understanding the cause of the changes in the amino acid composition of proteins is essential for understanding the evolution of protein functions. Since the early 1970s, it has been known that the frequency of some amino acids in protein sequences is increasing and that of others is decreasing. Recently, it was found that the trends of amino acid changes were similar in 15 taxa representing Bacteria, Archaea, and Eukaryota. However, the cause of this similarity in the trend of the gains and losses of amino acids continued to be debated. Here, we show that this trend of the gain and loss of amino acids can be simply explained by CpG hypermutability. We found that the frequency of amino acids coded by codons with TpG dinucleotides and those with CpA dinucleotides is increasing, while that of amino acids coded by codons with CpG dinucleotides is decreasing. We also found that organisms that lack DNA methyltransferase show different trends of the gain and loss of amino acids. DNA methyltransferase methylates CpG dinucleotides and induces CpG hypermutability. The incorporation of CpG hypermutability into models of protein evolution will improve studies on protein evolution in different organisms. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Using Genome-Wide Protein Sequence Data to Predict Amino Acid Conservation

For most proteins, multiple sequence alignments are a viable method to identify functionally and structurally important amino acids, but for most organisms, there is a subset of proteins that are unique or found in a few closely related organisms. For these proteins, it is not possible to produce sequence alignments that are useful in identifying functionally or structurally important amino acids. We have investigated the relationship between amino acid conservation and five factors (the amino acid’s identity, N-terminal neighbor, C-terminal neighbor, the local hydropathy of surrounding amino acids, and the local expected net charge of the surrounding amino acids based on the primary sequence) in Escherichia coli proteins. For four of the factors examined (all but the amino acid’s identity), there is a significant relationship with conservation for some of the standard 20 amino acids. Using the combination of all five factors, we show that it is possible to calculate a score based on the primary sequences of a subset of E. coli proteins that has statistically significant predictive value with respect to predicting conserved amino acids in other E. coli proteins and Saccharomyces cerevisiae proteins. As these five variables show significant relationships with conservation, we have termed them conservation factors. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A Reexamination of Correlations of Amino Acids with Particular Secondary Structures

Using the data from Protein Data Bank the correlations of primary and secondary structures of proteins were analyzed. The correlation values of the amino acids and the eight secondary structure types were calculated, where the position of the amino acid and the position in sequence with the particular secondary structure differ at most 25. The diagrams describing these results indicate that correlations are significant at distances between −9 and 10. The results show that the substituents on Cβ or Cγ atoms of amino acid play major role in their preference for particular secondary structure at the same position in the sequence, while the polarity of amino acid has significant influence on α-helices and strands at some distance in the sequence. The diagrams corresponding to polar amino acids are noticeably asymmetric. The diagrams point out the exchangeability of residues in the proteins; the amino acids with similar diagrams have similar local folding requirements. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Molecular characterization of cold adaptation based on ortholog protein sequences from <Emphasis Type="Italic">Vibrionaceae</Emphasis> species

A set of 298 protein families from psychrophilic Vibrio salmonicida was compiled to identify genotypic characteristics that discern it from orthologous sequences from the mesophilic Vibrio/Photobacterium branch of the gamma-Proteobacteria (Vibrionaceae family). In our comparative exploration we employed alignment based bioinformatical and statistical methods. Interesting information was found in the substitution matrices, and the pattern of asymmetries in the amino acid substitution process. Together with the compositional difference, they identified the amino acids Ile, Asn, Ala and Gln as those having the most psycrophilic involvement. Ile and Asn are enhanced whereas Gln and Ala are suppressed. The inflexible Pro residue is also suppressed in loop regions, as expected in a flexible structure. The dataset were also classified and analysed according to the predicted subcellular location, and we made an additional study of 183 intracellular and 65 membrane proteins. Our results revealed that the psychrophilic proteins have similar hydrophobic and charge contributions in the core of the protein as mesophilic proteins, while the solvent-exposed surface area is significantly more hydrophobic. In addition, the psychrophilic intracellular (but not the membrane) proteins are significantly more negatively charged at the surface. Our analysis supports the hypothesis of preference for more flexible amino acids at the molecular surface. Life in cold climate seems to be obtained through many minor structural modifications rather than certain amino acids substitutions.     

Asymmetric amino acid compositions of transmembrane beta-strands

In contrast to water-soluble proteins, membrane proteins reside in a heterogeneous environment, and their surfaces must interact with both polar and apolar membrane regions. As a consequence, the composition of membrane proteins' residues varies substantially between the membrane core and the interfacial regions. The amino acid compositions of helical membrane proteins are also known to be different on the cytoplasmic and extracellular sides of the membrane. Here we report that in the 16 transmembrane beta-barrel structures, the amino acid compositions of lipid-facing residues are different near the N and C termini of the individual strands. Polar amino acids are more prevalent near the C termini than near the N termini, and hydrophobic amino acids show the opposite trend. We suggest that this difference arises because it is easier for polar atoms to escape from the apolar regions of the bilayer at the C terminus of a beta-strand. This new characteristic of beta-barrel membrane proteins enhances our understanding of how a sequence encodes a membrane protein structure and should prove useful in identifying and predicting the structures of trans-membrane beta-barrels.     

Nonatomic solvent-driven Voronoi tessellation of proteins: an open tool to analyze protein folds

A three-dimensional Voronoi tessellation of folded proteins is used to analyze geometrical and topological properties of a set of proteins. To each amino acid is associated a central point surrounded by a Voronoi cell. Voronoi cells describe the packing of the amino acids. Special attention is given to reproduction of the protein surface. Once the Voronoi cells are built, a lot of tools from geometrical analysis can be applied to investigate the protein structure; volume of cells, number of faces per cell, and number of sides per face are the usual signatures of the protein structure. A distinct difference between faces related to primary, secondary, and tertiary structures has been observed. Faces threaded by the main-chain have on average more than six edges, whereas those related to helical packing of the amino acid chain have less than five edges. The faces on the protein surface have on average five edges within 1% error. The average number of faces on the protein surface for a given type of amino acid brings a new point of view in the characterization of the exposition to the solvent and the classification of amino acid as hydrophilic or hydrophobic. It may be a convenient tool for model validation.     

Statistical approach for lysosomal membrane proteins (LMPs) identification

Discrimination of Lysosomal membrane proteins (LMP’s) from folding types of globular (GPs) and other membrane proteins (OtMPs) is an important task both for identifying LMPs from genomic sequences and for the successful prediction of their secondary and tertiary structures. We have systematically analyzed the amino acid frequencies as well as dipeptide count of GPs, LMPs and OtMPs. Based on the above calculated single amino acid frequency combined with dipeptide count information, we statistically discriminated LMPs from GPs and OtMPs. This approach correctly classified the LMPs with an accuracy of 95 %. On the other hand, the amino acid frequency alone can discriminate LMPs with an accuracy of only 79 %. Similarly dipeptide count alone has an accuracy of 87 % for the discrimination of LMPs. Thus the combined information of both amino acid frequencies and dipeptide composition gives us significant high accurate results.

Electronic supplementary material

The online version of this article (doi:10.1007/s11693-014-9153-7) contains supplementary material, which is available to authorized users.     

Protein surface amino acid compositions distinctively differ between thermophilic and mesophilic bacteria

One of the well-known observations of proteins from thermophilic bacteria is the bias of the amino acid composition in which charged residues are present in large numbers, and polar residues are scarce. On the other hand, it has been reported that the molecular surfaces of proteins are adapted to their subcellular locations, in terms of the amino acid composition. Thus, it would be reasonable to expect that the differences in the amino acid compositions between proteins of thermophilic and mesophilic bacteria would be much greater on the protein surface than in the interior. We performed systematic comparisons between proteins from thermophilic bacteria and mesophilic bacteria, in terms of the amino acid composition of the protein surface and the interior, as well as the entire amino acid chains, by using sequence information from the genome projects. The biased amino acid composition of thermophilic proteins was confirmed, and the differences from those of mesophilic proteins were most obvious in the compositions of the protein surface. In contrast to the surface composition, the interior composition was not distinctive between the thermophilic and mesophilic proteins. The frequency of the amino acid pairs that are closely located in the space was also analyzed to show the same trend of the single amino acid compositions. Interestingly, extracellular proteins from mesophilic bacteria showed an inverse trend against thermophilic proteins (i.e. a reduced number of charged residues and rich in polar residues). Nuclear proteins from eukaryotes, which are known to be abundant in positive charges, showed different compositions as a whole from the thermophiles. These results suggest that the bias of the amino acid composition of thermophilic proteins is due to the residues on the protein surfaces, which may be constrained by the extreme environment.     

Positive Darwinian Selection at Single Amino Acid Sites Conferring Plant Virus Resistance

Explicit evaluation of the accuracy and power of maximum likelihood and Bayesian methods for detecting site-specific positive Darwinian selection presents a challenge because selective consequences of single amino acid changes are generally unknown. We exploited extensive molecular and functional characterization of amino acid substitutions in the plant gene eIF4E to evaluate the performance of these methods in detecting site-specific positive selection. We documented for the first time a molecular signature of positive selection within a recessive resistance gene in plants. We then used two statistical platforms, Phylogenetic Analysis Using Maximum Likelihood and Hypothesis Testing Using Phylogenies (HyPhy), to look for site-specific positive selection. Their relative power and accuracy are assessed by comparing the sites they identify as being positively selected with those of resistance-determining amino acids. Our results indicate that although both methods are surprisingly accurate in their identification of resistance sites, HyPhy appears to more accurately identify biologically significant amino acids using our data set. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. J. R. Cavatorta and A. E. Savage have contributed equally to this work.     

Frequent and widespread parallel evolution of protein sequences

Understanding the patterns and causes of protein sequence evolution is a major challenge in evolutionary biology. One of the critical unresolved issues is the relative contribution of selection and genetic drift to the fixation of amino acid sequence differences between species. Molecular homoplasy, the independent evolution of the same amino acids at orthologous sites in different taxa, is one potential signature of selection; however, relatively little is known about its prevalence in eukaryotic proteomes. To quantify the extent and type of homoplasy among evolving proteins, we used phylogenetic methodology to analyze 8 genome-scale data matrices from clades of different evolutionary depths that span the eukaryotic tree of life. We found that the frequency of homoplastic amino acid substitutions in eukaryotic proteins was more than 2-fold higher than expected under neutral models of protein evolution. The overwhelming majority of homoplastic substitutions were parallelisms that involved the most frequently exchanged amino acids with similar physicochemical properties and that could be reached by a single-mutational step. We conclude that the role of homoplasy in shaping the protein record is much larger than generally assumed, and we suggest that its high frequency can be explained by both weak positive selection for certain substitutions and purifying selection that constrains substitutions to a small number of functionally equivalent amino acids.     

Universal biases in protein composition of model prokaryotes

The levels of cellular organization in living organisms are the results of a variety of selection pressures. We have investigated here the final outcome of this integrated selective process in proteins of the best known microbial models Escherichia coli, Bacillus subtilis, and Methanococcus jannaschii, supposed to have undergone separate evolution for more than 1 billion years. Using multivariate analysis methods, including correspondence analysis, we studied the overall amino acid composition of all proteins making a proteome. Starting from and further developing previous results that had pointed out some general forces driving the amino acid composition of the proteomes of these model bacteria, we explored the correlations existing between the structure and functions of the proteins forming a proteome and their amino acid composition. The electric charge of amino acids measured against hydrophobicity creates a highly homogeneous cluster, made exclusively of proteins that are core components of the cytoplasmic membrane of the cell (integral inner membrane proteins). A second bias is imposed by the G+C content of the genome, indicating that protein functions are so robust with respect to amino acid changes that they can accommodate a large shift in the nucleotide content of the genome. A remarkable role of aromatic amino acids was uncovered. Expressed orphan proteins are enriched in these residues, suggesting that they might participate in a process of gain of function during evolution.     

Selective constraints, amino acid composition, and the rate of protein evolution

What are the major forces governing protein evolution? A common view is that proteins with strong structural and functional requirements evolve more slowly than proteins with weak constraints, because a stringent negative selection pressure limits the number of substitutions. In contrast, Graur claimed that the substitution rate of a protein is mainly determined by its amino acid composition and the changeabilities of amino acids. In this paper, however, we found that the relative changeabilities of amino acids in mammalian proteins are different for transmembranal and nontransmembranal segments, which have very distinct structural requirements. This indicates that the changeability of a given residue is influenced by the structural and functional context. We also reexamined the relationship between substitution rate and amino acid composition. Indeed, the two kinds of segments exhibit contrasting amino acid compositions: transmembranal regions are made up mainly of hydrophobic residues (a total frequency of approximately 60%) and are very poor in polar amino acids (<5%), whereas nontransmembranal segments have frequencies of 30% and 22%, respectively. Interestingly, we found that within a given integral membrane protein, nontransmembranal segments accumulate, on average, twice as many substitutions as transmembranal regions. However, regression analyses showed that the variability in amino acid frequencies among proteins cannot explain more than 30% of the variability in substitution rate for the transmembranal and nontransmembranal data sets. Furthermore, transmembranal and nontransmembranal segments evolving at the same rate in different proteins have different compositions, and the compositions of slowly evolving and rapidly evolving segments of the same type are similar. From these observations, we conclude that the rate of protein evolution is only weakly affected by amino acid composition but is mostly determined by the strength of functional requirements or selective constraints.