Function-structure analysis of proteins using covarion-based evolutionary approaches: Elongation factors

Microbial Communities and Interactions of Nitrogen Oxides With Methanogenesis in Diverse Peatlands of the Amazon Basin

Tropical peatlands are hotspots of methane (CH₄) production but present high variation and emission uncertainties in the Amazon region. This is because the controlling factors of methane production in tropical peats are not yet well documented. Although inhibitory effects of nitrogen oxides (NO_x) on methanogenic activity are known from pure culture studies, the role of NO_x in the methane cycling of peatlands remains unexplored. Here, we investigated the CH₄ content, soil geochemistry and microbial communities along 1-m-soil profiles and assessed the effects of soil NO_x and nitrous oxide (N₂O) on methanogenic abundance and activity in three peatlands of the Pastaza-Marañón foreland basin. The peatlands were distinct in pH, DOC, nitrate pore water concentrations, C/N ratios of shallow soils, redox potential, and ¹³C enrichment in dissolved inorganic carbon and CH₄ pools, which are primarily contingent on H₂-dependent methanogenesis. Molecular 16S rRNA and mcrA gene data revealed diverse and novel methanogens varying across sites. Importantly, we also observed a strong stratification in relative abundances of microbial groups involved in NO_x cycling, along with a concordant stratification of methanogens. The higher relative abundance of ammonia-oxidizing archaea (Thaumarchaeota) in acidic oligotrophic peat than ammonia-oxidizing bacteria (Nitrospira) is noteworthy as putative sources of NO_x. Experiments testing the interaction of NO_x species and methanogenesis found that the latter showed differential sensitivity to nitrite (up to 85% reduction) and N₂O (complete inhibition), which would act as an unaccounted CH₄ control in these ecosystems. Overall, we present evidence of diverse peatlands likely differently affected by inhibitory effects of nitrogen species on methanogens as another contributor to variable CH₄ fluxes.

Effects of Sub-Lethal High Pressure Homogenization Treatment on the Adhesion Mechanisms and Stress Response Genes in Lactobacillus acidophilus 08

Cell surface hydrophobicity (CSH) and adhesion are very important phenotypical traits for probiotics that confer them a competitive advantage for the resilience in the human gastrointestinal tract. This study was aimed to understand the effects over time of a 50 MPa hyperbaric treatment on the surface properties of Lactobacillus acidophilus 08 including CSH, autoaggregation, and in vitro adhesion (mucin layer and Caco-2 cells). Moreover, a link between the hurdle applied and the expression of genes involved in the general stress response (groEL and clpP) and adhesion processes (efTu and slpA) was evaluated. High pressure homogenization (HPH) at 50 MPa significantly increased the CSH percentage (H%), autoaggregation and in vitro adhesion on mucin of L. acidophilus 08 cells compared with the untreated cells. Moreover, the hyperbaric hurdle induced an upregulation of the stress response genes groEL and ef-TU together with a down regulation of the clpP and S-layer slpA genes. Looking at the protein profile, HPH-treatment showed an increase in the number or intensity of protein bands at high and low molecular weights.

A Phylogenetic Rate Parameter Indicates Different Sequence Divergence Patterns in Orthologs and Paralogs

Heterotachy-the change in sequence evolutionary rate over time-is a common feature of protein molecular evolution. Decades of studies have shed light on the conditions under which heterotachy occurs, and there is evidence that site-specific evolutionary rate shifts are correlated with changes in protein function. Here, we present a large-scale, computational analysis using thousands of protein sequence alignments from animal and plant proteomes, representing genes related either by orthology (speciation events) or paralogy (gene duplication), to compare sequence divergence patterns in orthologous vs. paralogous sequence alignments. We use sequence-based phylogenetic analyses to infer overall sequence divergence (tree length/number of sequences) and to fit site-specific rates to a discrete gamma distribution with a shape parameter α. This inference method is applied to real protein sequence alignments, as well as alignments simulated under various models of protein sequence evolution. Our simulations indicate that sequence divergence and the α parameter are positively correlated when sequences evolve with heterotachy, meaning that inferred site rate distributions appear more uniform as sequences diverge. Divergence and α are also positively correlated in both orthologous and paralogous genes, but the average increase in α (as a function of divergence) is significantly higher in paralogous protein alignments than in orthologous alignments. This result is consistent with the widely held view that recently duplicated proteins initially evolve under relaxed selective pressure, promoting functional divergence by accumulation of amino acid replacements, and hence experience more evolutionary rate fluctuations than orthologous proteins. We discuss these findings in the context of the ortholog conjecture, a long-standing assumption in molecular evolution, which posits that protein sequences related by orthology tend to be more functionally conserved than paralogous proteins.

A common root for coevolution and substitution rate variability in protein sequence evolution

We introduce a simple model that describes the average occurrence of point variations in a generic protein sequence. This model is based on the idea that mutations are more likely to be fixed at sites in contact with others that have mutated in the recent past. Therefore, we extend the usual assumptions made in protein coevolution by introducing a time dumping on the effect of a substitution on its surrounding and makes correlated substitutions happen in avalanches localized in space and time. The model correctly predicts the average correlation of substitutions as a function of their distance along the sequence. At the same time, it predicts an among-site distribution of the number of substitutions per site highly compatible with a negative binomial, consistently with experimental data. The promising outcomes achieved with this model encourage the application of the same ideas in the field of pairwise and multiple sequence alignment.

Artificially Expanded Genetic Information Systems for New Aptamer Technologies

Directed evolution was first applied to diverse libraries of DNA and RNA molecules a quarter century ago in the hope of gaining technology that would allow the creation of receptors, ligands, and catalysts on demand. Despite isolated successes, the outputs of this technology have been somewhat disappointing, perhaps because the four building blocks of standard DNA and RNA have too little functionality to have versatile binding properties, and offer too little information density to fold unambiguously. This review covers the recent literature that seeks to create an improved platform to support laboratory Darwinism, one based on an artificially expanded genetic information system (AEGIS) that adds independently replicating nucleotide “letters” to the evolving “alphabet”.

Predicting Amino Acid Substitution Probabilities Using Single Nucleotide Polymorphisms

Fast genome sequencing offers invaluable opportunities for building updated and improved models of protein sequence evolution. We here show that Single Nucleotide Polymorphisms (SNPs) can be used to build a model capable of predicting the probability of substitution between amino acids in variants of the same protein in different species. The model is based on a substitution matrix inferred from the frequency of codon interchanges observed in a suitably selected subset of human SNPs, and predicts the substitution probabilities observed in alignments between Homo sapiens and related species at 85-100% of sequence identity better than any other approach we are aware of. The model gradually loses its predictive power at lower sequence identity. Our results suggest that SNPs can be employed, together with multiple sequence alignment data, to model protein sequence evolution. The SNP-based substitution matrix developed in this work can be exploited to better align protein sequences of related organisms, to refine the estimate of the evolutionary distance between protein variants from related species in phylogenetic trees and, in perspective, might become a useful tool for population analysis.

Evolution of the 3R-MYB Gene Family in Plants

Plant 3R-MYB transcription factors are an important subgroup of the MYB super family in plants; however, their evolutionary history and functions remain poorly understood. We identified 225 3R-MYB proteins from 65 plant species, including algae and all major lineages of land plants. Two segmental duplication events preceding the common ancestor of angiosperms have given rise to three subgroups of the 3R-MYB proteins. Five conserved introns in the domain region of the 3R-MYB genes were identified, which arose through a step-wise pattern of intron gain during plant evolution. Alternative splicing (AS) analysis of selected species revealed that transcripts from more than 60% of 3R-MYB genes undergo AS. AS could regulate transcriptional activity for some of the plant 3R-MYBs by generating different regulatory motifs. The 3R-MYB genes of all subgroups appear to be enriched for Mitosis-Specific Activator element core sequences within their upstream promoter region, which suggests a functional involvement in cell cycle. Notably, expression of 3R-MYB genes from different species exhibits differential regulation under various abiotic stresses. These data suggest that the plant 3R-MYBs function in both cell cycle regulation and abiotic stress response, which may contribute to the adaptation of plants to a sessile lifestyle.

Coevolution of URAT1 and Uricase during Primate Evolution: Implications for Serum Urate Homeostasis and Gout

Uric acid is the highly insoluble end-product of purine metabolism in humans. Serum levels exceeding the solubility threshold can trigger formation of urate crystals resulting in gouty arthritis. Uric acid is primarily excreted through the kidneys with 90% reabsorbed back into the bloodstream through the uric acid transporter URAT1. This reabsorption process is essential for the high serum uric acid levels found in humans. We discovered that URAT1 proteins from humans and baboons have higher affinity for uric acid compared with transporters from rats and mice. This difference in transport kinetics of URAT1 orthologs, along with inability of modern apes to oxidize uric acid due to loss of the uricase enzyme, prompted us to ask whether these events occurred concomitantly during primate evolution. Ancestral URAT1 sequences were computationally inferred and ancient transporters were resurrected and assayed, revealing that affinity for uric acid was increased during the evolution of primates. This molecular fine-tuning occurred between the origins of simians and their diversification into New- and Old-World monkey and ape lineages. Remarkably, it was driven in large-part by only a few amino acid replacements within the transporter. This alteration in primate URAT1 coincided with changes in uricase that greatly diminished the enzymatic activity and took place 27–77 Ma. These results suggest that the modifications to URAT1 transporters were potentially adaptive and that maintaining more constant, high levels of serum uric acid may have provided an advantage to our primate ancestors.

Thermal-stable proteins of fruit of long-living Sacred Lotus Nelumbo nucifera Gaertn var. China Antique

Single-seeded fruit of the sacred lotus Nelumbo nucifera Gaertn var. China Antique from NE China have viability as long as ~1300 years determined by direct radiocarbon-dating, having a germination rate of 84%. The pericarp, a fruit tissue that encloses the single seeds of Nelumbo, is considered one of the major factors that contribute to fruit longevity. Proteins that are heat stable and have protective function may be equally important to seed viability. We show proteins of Nelumbo fruit that are able to withstand heating, 31% of which remained soluble in the 110°C-treated embryo-axis of a 549-yr-old fruit and 76% retained fluidity in its cotyledons. Genome of Nelumbo is published. The amino-acid sequences of 11 "thermal proteins" (soluble at 100°C) of modern Nelumbo embryo-axes and cotyledons, identified by mass spectrometry, Western blot and bioassay, are assembled and aligned with those of an archaeal-hyperthermophile Methancaldococcus jannaschii (Mj; an anaerobic methanogen having a growth optimum of 85°C) and with five mesophile angiosperms. These thermal proteins have roles in protection and repair under stress. More than half of the Nelumbo thermal proteins (55%) are present in the archaean Mj, indicating their long-term durability and history. One Nelumbo protein-repair enzyme exhibits activity at 100°C, having a higher heat-tolerance than that of Arabidopsis. A list of 30 sequenced but unassembled thermal proteins of Nelumbo is supplemented.

Interchanging functionality among homologous elongation factors using signatures of heterotachy

Numerous models of molecular evolution have been formulated to describe the forces that shape sequence divergence among homologous proteins. These models have greatly enhanced our understanding of evolutionary processes. Rarely are such models empirically tested in the laboratory, and even more rare, are such models exploited to generate novel molecules useful for synthetic biology. Here, we experimentally demonstrate that the heterotachy model of evolution captures signatures of functional divergence among homologous elongation factors (EFs) between bacterial EF-Tu and eukaryotic eEF1A. These EFs are GTPases that participate in protein translation by presenting aminoacylated-tRNAs to the ribosome. Upon release from the ribosome, the EFs are recharged by nucleotide exchange factors EF-Ts in bacteria or eEF1B in eukaryotes. The two nucleotide exchange factors perform analogous functions despite not being homologous proteins. The heterotachy model was used to identify a set of sites in eEF1A/EF-Tu associated with eEF1B binding in eukaryotes and another reciprocal set associated with EF-Ts binding in bacteria. Introduction of bacterial EF-Tu residues at these sites into eEF1A protein efficiently disrupted binding of cognate eEF1B as well as endowed eEF1A with the novel ability to bind bacterial EF-Ts. We further demonstrate that eEF1A variants, unlike yeast wild-type, can function in a reconstituted in vitro bacterial translation system.

Speeding with control: codon usage, tRNAs, and ribosomes

Codon usage and tRNA abundance are critical parameters for gene synthesis. However, the forces determining codon usage bias within genomes and between organisms, as well as the functional roles of biased codon compositions, remain poorly understood. Similarly, the composition and dynamics of mature tRNA populations in cells in terms of isoacceptor abundances, and the prevalence and function of base modifications are not well understood. As we begin to decipher some of the rules that govern codon usage and tRNA abundances, it is becoming clear that these parameters are a way to not only increase gene expression, but also regulate the speed of ribosomal translation, the efficiency of protein folding, and the coordinated expression of functionally related gene families. Here, we discuss the importance of codon-anticodon interactions in translation regulation and highlight the contribution of non-random codon distributions and post-transcriptional base modifications to this regulation.

Roles of Protein Synthesis Elongation Factor EF-Tu in Heat Tolerance in Plants

EF-Tu proteins of plastids, mitochondria, and the cytosolic counterpart EF-1α in plants, as well as EF-Tu proteins of bacteria, are highly conserved and multifunctional. The functions of EF-Tu include transporting the aminoacyl-tRNA complex to the A site of the ribosome during protein biosynthesis; chaperone activity in protecting other proteins from aggregation caused by environmental stresses, facilitating renaturation of proteins when conditions return to normal; displaying a protein disulfide isomerase activity; participating in the degradation of N-terminally blocked proteins by the proteasome; eliciting innate immunity and triggering resistance to pathogenic bacteria in plants; participating in transcription when an E. coli host is infected with phages. EF-Tu genes are upregulated by abiotic stresses in plants, and EF-Tu plays important role in stress responses. Expression of a plant EF-Tu gene confers heat tolerance in E. coli, maize knock-out EF-Tu null mutants are heat susceptible, and over-expression of an EF-Tu gene improves heat tolerance in crop plants. This review paper summarizes the current knowledge of EF-Tu proteins in stress responses in plants and progress on application of EF-Tu for developing crop varieties tolerant to abiotic stresses, such as high temperatures.

Synonymous codon ordering: a subtle but prevalent strategy of bacteria to improve translational efficiency

BACKGROUND

In yeast coding sequences, once a particular codon has been used, subsequent occurrence of the same amino acid tends to use codons sharing the same tRNA. Such a phenomenon of co-tRNA codons pairing bias (CTCPB) is also found in some other eukaryotes but it is not known whether it occurs in prokaryotes.

METHODOLOGY/PRINCIPAL FINDINGS

In this study, we focused on a total of 773 bacterial genomes to investigate their synonymous codon pairing preferences. After calculating the actual frequencies of synonymous codon pairs and comparing them with their expected values, we detected an obvious pairing bias towards identical codon pairs. This seems consistent with the previously reported CTCPB phenomenon, since identical codons are certainly read by the same tRNA. However, among co-tRNA but non-identical codon pairs, only 22 were often found overrepresented, suggesting that many co-tRNA codons actually do not preferentially pair together in prokaryotes. Therefore, the previously reported co-tRNA codons pairing rule needs to be more rigorously defined. The affinity differences between a tRNA anticodon and its readable codons should be taken into account. Moreover, both within-gene-shuffling tests and phylogenetic analyses support the idea that translational selection played an important role in shaping the observed synonymous codon pairing pattern in prokaryotes.

CONCLUSIONS

Overall, a high level of synonymous codon pairing bias was detected in 73% investigated bacterial species, suggesting the synonymous codon ordering strategy has been prevalently adopted by prokaryotes to improve their translational efficiencies. The findings in this study also provide important clues to better understand the complex dynamics of translational process.

A combined molecular dynamics and rapid kinetics approach to identify conserved three-dimensional communication networks in elongation factor Tu

Elongation factor (EF) Tu delivers aminoacyl-tRNAs to the actively translating bacterial ribosome in a GTP-hydrolysis-dependent process. Rapid recycling of EF-Tu, catalyzed by EF-Ts, is required for efficient protein synthesis in vivo. Here we report a combined theoretical and experimental approach aimed at identifying three-dimensional communication networks in EF-Tu. As an example, we focus on the mechanistic role of second-shell residue Asp(109). We constructed full-length structural models of EF-Tu from Escherichia coli in the GDP-/GTP-bound state and performed several 10-ns-long molecular-dynamics simulations. During these simulations, the side chain of Asp(109) formed a previously undetected transient hydrogen bond to His(22), an invariant residue in the phosphate-binding loop (P-loop). To experimentally validate our molecular-dynamics results and further analyze the role of this hydrogen bond, we determined all rate constants for the multistep reaction between EF-Tu (wild-type and two mutants), EF-Ts, GDP, and GTP using the stopped-flow technique. This mutational analysis revealed that the side chain of Asp(109) is important for acceleration of GDP, but not for GTP dissociation by EF-Ts. The possibility that the Asp(109) side chain has a role in transition-state stabilization and coupling of P-loop movements with rearrangements at the base side of the nucleotide is discussed.

Fast statistical tests for detecting heterotachy in protein evolution

The w statistic introduced by Lockhart et al. (1998. A covariotide model explains apparent phylogenetic structure of oxygenic photosynthetic lineages. Mol Biol Evol. 15:1183-1188) is a simple and easily calculated statistic intended to detect heterotachy by comparing amino acid substitution patterns between two monophyletic groups of protein sequences. It is defined as the difference between the fraction of varied sites in both groups and the fraction of varied sites in each group. The w test has been used to distinguish a covarion process from equal rates and rates variation across sites processes. Using simulation we show that the w test is effective for small data sets and for data sets that have low substitution rates in the groups but can have difficulties when these conditions are not met. Using site entropy as a measure of variability of a sequence site, we modify the w statistic to a w' statistic by assigning as varied in one group those sites that are actually varied in both groups but have a large entropy difference. We show that the w' test has more power to detect two kinds of heterotachy processes (covarion and bivariate rate shifts) in large and variable data. We also show that a test of Pearson's correlation of the site entropies between two monophyletic groups can be used to detect heterotachy and has more power than the w' test. Furthermore, we demonstrate that there are settings where the correlation test as well as w and w' tests do not detect heterotachy signals in data simulated under a branch length mixture model. In such cases, it is sometimes possible to detect heterotachy through subselection of appropriate taxa. Finally, we discuss the abilities of the three statistical tests to detect a fourth mode of heterotachy: lineage-specific changes in proportion of variable sites.

Exploiting models of molecular evolution to efficiently direct protein engineering

Directed evolution and protein engineering approaches used to generate novel or enhanced biomolecular function often use the evolutionary sequence diversity of protein homologs to rationally guide library design. To fully capture this sequence diversity, however, libraries containing millions of variants are often necessary. Screening libraries of this size is often undesirable due to inaccuracies of high-throughput assays, costs, and time constraints. The ability to effectively cull sequence diversity while still generating the functional diversity within a library thus holds considerable value. This is particularly relevant when high-throughput assays are not amenable to select/screen for certain biomolecular properties. Here, we summarize our recent attempts to develop an evolution-guided approach, Reconstructing Evolutionary Adaptive Paths (REAP), for directed evolution and protein engineering that exploits phylogenetic and sequence analyses to identify amino acid substitutions that are likely to alter or enhance function of a protein. To demonstrate the utility of this technique, we highlight our previous work with DNA polymerases in which a REAP-designed small library was used to identify a DNA polymerase capable of accepting non-standard nucleosides. We anticipate that the REAP approach will be used in the future to facilitate the engineering of biopolymers with expanded functions and will thus have a significant impact on the developing field of 'evolutionary synthetic biology'.

Deep phylogeny--how a tree can help characterize early life on Earth

The Darwinian concept of biological evolution assumes that life on Earth shares a common ancestor. The diversification of this common ancestor through speciation events and vertical transmission of genetic material implies that the classification of life can be illustrated in a tree-like manner, commonly referred to as the Tree of Life. This article describes features of the Tree of Life, such as how the tree has been both pruned and become bushier throughout the past century as our knowledge of biology has expanded. We present current views that the classification of life may be best illustrated as a ring or even a coral with tree-like characteristics. This article also discusses how the organization of the Tree of Life offers clues about ancient life on Earth. In particular, we focus on the environmental conditions and temperature history of Precambrian life and show how chemical, biological, and geological data can converge to better understand this history."You know, a tree is a tree. How many more do you need to look at?"--Ronald Reagan (Governor of California), quoted in the Sacramento Bee, opposing expansion of Redwood National Park, March 3, 1966.

Phylogenetic substitution models for detecting heterotachy during plastid evolution

There is widespread evidence of lineage-specific rate variation, known as heterotachy, during protein evolution. Changes in the structural and functional constraints acting on a protein can lead to heterotachy, and it is plausible that such changes, known as covarion shifts, may affect many amino acids at once. Several previous attempts to model heterotachy have used covarion models, where the sequence undergoes covarion drift, whereby each site may switch independently among a set of discrete classes having different substitution rates. However, such independent switching may not capture biologically important events where the selective forces acting on a protein affect many sites at once. We describe a new class of models that allow the rates of substitution and switching to vary among branches of a phylogenetic tree. Such models are better able to handle covarion shifts. We apply these models to a set of genes occurring in nonphotosynthetic bacteria, cyanobacteria, and the plastids of green and red algae. We find that 4/5 genes show evidence of some form of rate switching and that 3/5 genes show evidence that the relative switching rate differs among taxonomic groups. We conclude that covarion shifts may be frequent during the deep evolution of plastid genes and that our methodology may provide a powerful new tool for investigating such shifts in other systems.

In silico identification of functional protein interfaces

Proteins perform many of their biological roles through protein–protein, protein–DNA or protein–ligand interfaces. The identification of the amino acids comprising these interfaces often enhances our understanding of the biological function of the proteins. Many methods for the detection of functional interfaces have been developed, and large-scale analyses have provided assessments of their accuracy. Among them are those that consider the size of the protein interface, its amino acid composition and its physicochemical and geometrical properties. Other methods to this effect use statistical potential functions of pairwise interactions, and evolutionary information. The rationale of the evolutionary approach is that functional and structural constraints impose selective pressure; hence, biologically important interfaces often evolve at a slower pace than do other external regions of the protein. Recently, an algorithm, Rate4Site, and a web-server, ConSurf (http://consurf.tau.ac.il/), for the identification of functional interfaces based on the evolutionary relations among homologous proteins as reflected in phylogenetic trees, were developed in our laboratory. The explicit use of the tree topology and branch lengths makes the method remarkably accurate and sensitive. Here we demonstrate its potency in the identification of the functional interfaces of a hypothetical protein, the structure of which was determined as part of the international structural genomics effort. Finally, we propose to combine complementary procedures, in order to enhance the overall performance of methods for the identification of functional interfaces in proteins.

Large-scale analysis of orthologs and paralogs under covarion-like and constant-but-different models of amino acid evolution

Functional divergence between homologous proteins is expected to affect amino acid sequences in two main ways, which can be considered as proxies of biochemical divergence: a “covarion-like” pattern of correlated changes in evolutionary rates, and switches in conserved residues (“conserved but different”). Although these patterns have been used in case studies, a large-scale analysis is needed to estimate their frequency and distribution. We use a phylogenomic framework of animal genes to answer three questions: 1) What is the prevalence of such patterns? 2) Can we link such patterns at the amino acid level with selection inferred at the codon level? 3) Are patterns different between paralogs and orthologs? We find that covarion-like patterns are more frequently detected than “constant but different,” but that only the latter are correlated with signal for positive selection. Finally, there is no obvious difference in patterns between orthologs and paralogs.

A role for codon order in translation dynamics

The genetic code is degenerate. Each amino acid is encoded by up to six synonymous codons; the choice between these codons influences gene expression. Here, we show that in coding sequences, once a particular codon has been used, subsequent occurrences of the same amino acid do not use codons randomly, but favor codons that use the same tRNA. The effect is pronounced in rapidly induced genes, involves both frequent and rare codons and diminishes only slowly as a function of the distance between subsequent synonymous codons. Furthermore, we found that in S. cerevisiae codon correlation accelerates translation relative to the translation of synonymous yet anticorrelated sequences. The data suggest that tRNA diffusion away from the ribosome is slower than translation, and that some tRNA channeling takes place at the ribosome. They also establish that the dynamics of translation leave a significant signature at the level of the genome.

PROCOV: maximum likelihood estimation of protein phylogeny under covarion models and site-specific covarion pattern analysis

Background

The covarion hypothesis of molecular evolution holds that selective pressures on a given amino acid or nucleotide site are dependent on the identity of other sites in the molecule that change throughout time, resulting in changes of evolutionary rates of sites along the branches of a phylogenetic tree. At the sequence level, covarion-like evolution at a site manifests as conservation of nucleotide or amino acid states among some homologs where the states are not conserved in other homologs (or groups of homologs). Covarion-like evolution has been shown to relate to changes in functions at sites in different clades, and, if ignored, can adversely affect the accuracy of phylogenetic inference.

Results

PROCOV (protein covarion analysis) is a software tool that implements a number of previously proposed covarion models of protein evolution for phylogenetic inference in a maximum likelihood framework. Several algorithmic and implementation improvements in this tool over previous versions make computationally expensive tree searches with covarion models more efficient and analyses of large phylogenomic data sets tractable. PROCOV can be used to identify covarion sites by comparing the site likelihoods under the covarion process to the corresponding site likelihoods under a rates-across-sites (RAS) process. Those sites with the greatest log-likelihood difference between a 'covarion' and an RAS process were found to be of functional or structural significance in a dataset of bacterial and eukaryotic elongation factors.

Conclusion

Covarion models implemented in PROCOV may be especially useful for phylogenetic estimation when ancient divergences between sequences have occurred and rates of evolution at sites are likely to have changed over the tree. It can also be used to study lineage-specific functional shifts in protein families that result in changes in the patterns of site variability among subtrees.

Expression of the Mucus Adhesion Gene Mub, Surface Layer Protein Slp and Adhesion-Like Factor EF-TU of Lactobacillus acidophilus ATCC 4356 Under Digestive Stress Conditions, as Monitored with Real-Time PCR

Expression of the mucus adhesion gene Mub, surface layer protein Slp and adhesion-like factor EF-Tu by Lactobacillus acidophilus ATCC 4356 grown in the presence of mucin, bile and pancreatin and at low pH was studied using real-time PCR. None of the genes were up-regulated under increasing concentrations of mucin, while Slp and EF-Tu were up-regulated in the presence of bile and pancreatin at normal concentrations (0.3%, w/v) and under stress conditions (1.0%, w/v).

Evolutionary modeling of rate shifts reveals specificity determinants in HIV-1 subtypes

A hallmark of the human immunodeficiency virus 1 (HIV-1) is its rapid rate of evolution within and among its various subtypes. Two complementary hypotheses are suggested to explain the sequence variability among HIV-1 subtypes. The first suggests that the functional constraints at each site remain the same across all subtypes, and the differences among subtypes are a direct reflection of random substitutions, which have occurred during the time elapsed since their divergence. The alternative hypothesis suggests that the functional constraints themselves have evolved, and thus sequence differences among subtypes in some sites reflect shifts in function. To determine the contribution of each of these two alternatives to HIV-1 subtype evolution, we have developed a novel Bayesian method for testing and detecting site-specific rate shifts. The RAte Shift EstimatoR (RASER) method determines whether or not site-specific functional shifts characterize the evolution of a protein and, if so, points to the specific sites and lineages in which these shifts have most likely occurred. Applying RASER to a dataset composed of large samples of HIV-1 sequences from different group M subtypes, we reveal rampant evolutionary shifts throughout the HIV-1 proteome. Most of these rate shifts have occurred during the divergence of the major subtypes, establishing that subtype divergence occurred together with functional diversification. We report further evidence for the emergence of a new sub-subtype, characterized by abundant rate-shifting sites. When focusing on the rate-shifting sites detected, we find that many are associated with known function relating to viral life cycle and drug resistance. Finally, we discuss mechanisms of covariation of rate-shifting sites.

The AIDS epidemic, inflicted by the human immunodeficiency virus (HIV), has already claimed 25 million lives, thus posing a global threat. Since its discovery, several HIV subtypes have emerged, characterized by distinct genomic sequences and variable geographic locations. Here, we investigate the nature of the genetic differences among the subtypes. The neutral theory of evolution suggests that most genetic differences marginally affect the function of the encoded proteins (hence neutral) and thus occur randomly. Alternatively, changes in protein function are reflected by a pattern of nonrandom genetic differences. To address this issue, we developed a computational method, which studies the differences between sequences of different HIV subtypes, and estimates which of the explanations is more likely. Using a large sample of HIV protein sequences, we discovered that part of the variability among the subtypes is not random and possibly reflects different functional constraints imposed on the subtypes during the course of their evolution. An in-depth inspection of these nonrandom changes revealed a correlation with biological traits, such as drug resistance and mechanisms facilitating viral entry into the host cell. Interestingly, nonrandom changes are also characteristic of a viral strain that recently emerged in the former Soviet Union.

Surface-bound proteins of Lactobacillus plantarum 423 that contribute to adhesion of Caco-2 cells and their role in competitive exclusion and displacement of Clostridium sporogenes and Enterococcus faecalis

Elongation factor Tu (EF-Tu), glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and triosephosphate isomerase (TPI) are surface-bound proteins with a role in adhesion of Lactobacillus plantarum 423 to Caco-2 cells. Removal of surface-bound proteins from L. plantarum 423 (treated with 4M guanidine-HCl) reduced adhesion to Caco-2 cells by 40%. In a competitive exclusion experiment where all three strains were given an equal chance to adhere to Caco-2 cells, L. plantarum 423 prevented 71% of cells of Clostridium sporogenes LMG 13570 and 89% of cells of Enterococcus faecalis LMG 13566 from adhering. Cells of L. plantarum 423, from which surface-bound proteins were removed, prevented 49% of cells of C. sporogenes LMG 13570 and 70% of cells of E. faecalis LMG 13566 from adhering to Caco-2 cells, suggesting that factors other than surface-bound proteins are involved in adhesion. Colonization of L. plantarum 423 to Caco-2 cells prevented adhesion of 74% of cells of C. sporogenes LMG 13570 and 62% of cells of E. faecalis LMG 13566. Furthermore, L. plantarum 423 displaced 81% of cells of C. sporogenes LMG 13570 and 91% of cells of E. faecalis LMG 13566 from Caco-2 cells. L. plantarum 423 is a potential probiotic strain.

A mixed branch length model of heterotachy improves phylogenetic accuracy

Evolutionary relationships are typically inferred from molecular sequence data using a statistical model of the evolutionary process. When the model accurately reflects the underlying process, probabilistic phylogenetic methods recover the correct relationships with high accuracy. There is ample evidence, however, that models commonly used today do not adequately reflect real-world evolutionary dynamics. Virtually all contemporary models assume that relatively fast-evolving sites are fast across the entire tree, whereas slower sites always evolve at relatively slower rates. Many molecular sequences, however, exhibit site-specific changes in evolutionary rates, called "heterotachy." Here we examine the accuracy of 2 phylogenetic methods for incorporating heterotachy, the mixed branch length model--which incorporates site-specific rate changes by summing likelihoods over multiple sets of branch lengths on the same tree--and the covarion model, which uses a hidden Markov process to allow sites to switch between variable and invariable as they evolve. Under a variety of simple heterogeneous simulation conditions, the mixed model was dramatically more accurate than homotachous models, which were subject to topological biases as well as biases in branch length estimates. When data were simulated with strong versions of the types of heterotachy observed in real molecular sequences, the mixed branch length model was more accurate than homotachous techniques. Analyses of empirical data sets confirmed that the mixed branch length model can improve phylogenetic accuracy under conditions that cause homotachous models to fail. In contrast, the covarion model did not improve phylogenetic accuracy compared with homotachous models and was sometimes substantially less accurate. We conclude that a mixed branch length approach, although not the solution to all phylogenetic errors, is a valuable strategy for improving the accuracy of inferred trees.

Topological estimation biases with covarion evolution

Covarion processes allow changes in evolutionary rates at sites along the branches of a phylogenetic tree. Covarion-like evolution is increasingly recognized as an important mode of protein evolution. Several recent reports suggest that maximum likelihood estimation employing covarion models may support different optimal topologies than estimation using standard rates-across-sites (RAS) models. However, it remains to be demonstrated that ignoring covarion evolution will generally result in topological misestimation. In this study we performed analytical and theoretical studies of limiting distances under the covarion model and four-taxon tree simulations to investigate the extent to which the covarion process impacts on phylogenetic estimation. In particular, we assessed the limits of an RAS model-based maximum likelihood method to recover the phylogenies when the sequence data were simulated under the covarion processes. We find that, when ignored, covarion processes can induce systematic errors in phylogeny reconstruction. Surprisingly, when sequences are evolved under a covarion process but an RAS model is used for estimation, we find that a long branch repel bias occurs.

Evolutionary Analysis for Functional Divergence of the Toll-Like Receptor Gene Family and Altered Functional Constraints

The Toll-like receptor (TLR) gene family consists of type 1 transmembrane receptors, which play essential roles in both innate immunity and adaptive immune response by ligand recognition and signal transduction. Using all available vertebrate TLR protein sequences, we inferred the phylogenetic tree and then characterized critical amino acid residues for functional divergence by detecting altered functional constraints after gene duplications. We found that the extracellular domain of TLR genes showed higher functional divergence than that of the cytoplasmic domain, particularly in the region between leucine-rich repeat (LRR) 10 and LRR 15 of TLR 4. Our finding supports the concept that sequence evolution in the extracellular domain may be responsible for the broad diversity of TLR ligand-binding affinity, providing a testable hypothesis for potential targets that could be verified by further experimentation.

An empirical test of the concomitantly variable codon hypothesis

A central assumption of models of molecular evolution, that each site in a sequence evolves independently of all other sites, lacks empirical support. We investigated the extent to which sites evolve codependently in triosephosphate isomerase (TIM), a ubiquitous glycolytic enzyme conserved in both structure and function. Codependencies among sites, or concomitantly variable codons (covarions), are evident from the reduced function and misfolding of hybrid TIM proteins. Although they exist, we find covarions are relatively rare, and closely related proteins are unlikely to have developed them. However, the potential for covarions increases with genetic distance so that highly divergent proteins may have evolved codependencies between many sites. The evolution of covarions undermines a key assumption in phylogenetics and calls into question our ability to disentangle ancient relationships among major taxonomic groups.

Molecular paleoscience: systems biology from the past

Experimental paleomolecular biology, paleobiochemistry, and paleogenetics are closely related emerging fields that infer the sequences of ancient genes and proteins from now-extinct organisms, and then resurrect them for study in the laboratory. The goal of paleogenetics is to use information from natural history to solve the conundrum of modern genomics: How can we understand deeply the function of biomolecular structures uncovered and described by modern chemical biology? Reviewed here are the first 20 cases where biomolecular resurrections have been achieved. These show how paleogenetics can lead to an understanding of the function of biomolecules, analyze changing function, and put meaning to genomic sequences, all in ways that are not possible with traditional molecular biological studies.

Expression of the mucus adhesion genes Mub and MapA, adhesion-like factor EF-Tu and bacteriocin gene plaA of Lactobacillus plantarum 423, monitored with real-time PCR

Expression of the mucus adhesion genes Mub and MapA, adhesion-like factor EF-Tu and bacteriocin gene plaA by Lactobacillus plantarum 423, grown in the presence of bile, pancreatin and at low pH, was studied by real-time PCR. Mub, MapA and EF-Tu were up-regulated in the presence of mucus, proportional to increasing concentrations. Expression of MapA was up-regulated in the presence of 3.0 g/l bile and 3.0 g/l pancreatin at pH 6.5. Similar results were recorded in the presence of 10.0 g/l bile and 10.0 g/l pancreatin at pH 6.5. Expression of Mub was down-regulated in the presence of bile and pancreatin, whilst the expression of EF-Tu and plaA remained unchanged. Expression of Mub and MapA remained unchanged at pH 4.0, whilst expression of EF-Tu and plaA were up-regulated. Expression of MapA was down-regulated in the presence of 1.0 g/l l-cysteine HCl, suggesting that the gene is regulated by transcription attenuation that involves cysteine.

Identifying dramatic selection shifts in phylogenetic trees

Background

The rate of evolution varies spatially along genomes and temporally in time. The presence of evolutionary rate variation is an informative signal that often marks functional regions of genomes and historical selection events. There exist many tests for temporal rate variation, or heterotachy, that start by partitioning sampled sequences into two or more groups and testing rate homogeneity among the groups. I develop a Bayesian method to infer phylogenetic trees with a divergence point, or dramatic temporal shifts in selection pressure that affect many nucleotide sites simultaneously, located at an unknown position in the tree.

Results

Simulation demonstrates that the method is most able to detect divergence points when rate variation and the number of affected sites is high, but not beyond biologically relevant values. The method is applied to two viral data sets. A divergence point is identified separating the B and C subtypes, two genetically distinct variants of HIV that have spread into different human populations with the AIDS epidemic. In contrast, no strong signal of temporal rate variation is found in a sample of F and H genotypes, two genetic variants of HBV that have likely evolved with humans during their immigration and expansion into the Americas.

Conclusion

Temporal shifts in evolutionary rate of sufficient magnitude are detectable in the history of sampled sequences. The ability to detect such divergence points without the need to specify a prior hypothesis about the location or timing of the divergence point should help scientists identify historically important selection events and decipher mechanisms of evolution.

Structural divergence and adaptive evolution in mammalian cytochromes P450 2C

Cytochromes P450 (CYPs) comprise a superfamily of enzymes involved in various physiological functions, including the metabolism of drugs and carcinogenic compounds present in food, making them of great importance for human health. The possibility that CYPs could be broadening or changing substrate specificity in accordance to the high diversity of xenobiotics compounds environmentally available suggests that their metabolic function could be under adaptive evolution. We evaluated the existence of functional divergence and signatures of selection on mammalian genes from the drug-metabolizing CYP2 family. Thirteen of the sites found to be functionally divergent and the eight found to be under strong positive selection occurred in important functional domains, namely on the substrate entrance channel and within the active site. Our results provide insight into CYPs evolution and the role of molecular adaptation in enzyme substrate-specificity diversification.

Tracking the connection between evolutionary and functional shifts using the fungal lipase/feruloyl esterase A family

Background

There have been many claims of adaptive molecular evolution, but what role does positive selection play in functional divergence? The aim of this study was to test the relationship between evolutionary and functional shifts with special emphasis on the role of the environment. For this purpose, we studied the fungal lipase/feruloyl esterase A family, whose functional diversification makes it a very promising candidate.

Results

The results suggested functional shift following a duplication event where neofunctionalisation of feruloyl esterase A had occurred with conservation of the ancestral lipase function. Evolutionary shift was detected using the branch-site model for testing positive selection on individual codons along specific lineages. Positively selected amino acids were detected. Furthermore, biological data obtained from site-directed mutagenesis experiments clearly demonstrated that certain amino acids under positive selection were involved in the functional shift. We reassessed evolutionary history in terms of environmental response, and hypothesized that environmental changes such as colonisation by terrestrial plants might have driven adaptation by functional diversification in Euascomycetes (Aspergilli), thus conferring a selective advantage on this group.

Conclusion

The results reported here illustrate a rare example of connection between fundamental events in molecular evolution. We demonstrated an unequivocal connection between evolutionary and functional shifts, which led us to conclude that these events were probably linked to environmental change.

Testing for covarion-like evolution in protein sequences

The covarion hypothesis of molecular evolution proposes that selective pressures on an amino acid or nucleotide site change through time, thus causing changes of evolutionary rate along the edges of a phylogenetic tree. Several kinds of Markov models for the covarion process have been proposed. One model, proposed by Huelsenbeck (2002), has 2 substitution rate classes: the substitution process at a site can switch between a single variable rate, drawn from a discrete gamma distribution, and a zero invariable rate. A second model, suggested by Galtier (2001), assumes rate switches among an arbitrary number of rate classes but switching to and from the invariable rate class is not allowed. The latter model allows for some sites that do not participate in the rate-switching process. Here we propose a general covarion model that combines features of both models, allowing evolutionary rates not only to switch between variable and invariable classes but also to switch among different rates when they are in a variable state. We have implemented all 3 covarion models in a maximum likelihood framework for amino acid sequences and tested them on 23 protein data sets. We found significant likelihood increases for all data sets for the 3 models, compared with a model that does not allow site-specific rate switches along the tree. Furthermore, we found that the general model fit the data better than the simpler covarion models in the majority of the cases, highlighting the complexity in modeling the covarion process. The general covarion model can be used for comparing tree topologies, molecular dating studies, and the investigation of protein adaptation.

EFL GTPase in cryptomonads and the distribution of EFL and EF-1alpha in chromalveolates

EFL (EF-like protein) is a member of the GTPase superfamily that includes several translation factors. Because it has only been found in a few eukaryotic lineages and its presence correlates with the absence of the related core translation factor EF-1alpha, its distribution is hypothesized to be the result of lateral gene transfer and replacement of EF-1alpha. In one supergroup of eukaryotes, the chromalveolates, two major lineages were found to contain EFL (dinoflagellates and haptophytes), while the others encode EF-1alpha (apicomplexans, ciliates, heterokonts and cryptomonads). For each of these groups, this distribution was deduced from whole genome sequence or expressed sequence tag (EST) data from several species, with the exception of cryptomonads from which only a single EF-1alpha PCR product from one species was known. By sequencing ESTs from two cryptomonads, Guillardia theta and Rhodomonas salina, and searching for all GTPase translation factors, we revealed that EFL is present in both species, but, contrary to expectations, we found EF-1alpha in neither. On balance, we suggest the previously reported EF-1alpha from Rhodomonas salina is likely an artefact of contamination. We also identified EFL in EST data from two members of the dinoflagellate lineage, Karlodinium micrum and Oxyrrhis marina, and from an ongoing genomic sequence project from a third, Perkinsus marinus. Karlodinium micrum is a symbiotic pairing of two lineages that would have both had EFL (a dinoflagellate and a haptophyte), but only the dinoflagellate gene remains. Oxyrrhis marina and Perkinsus marinus are early diverging sister-groups to dinoflagellates, and together show that EFL originated early in this lineage. Phylogenetic analysis confirmed that these genes are all EFL homologues, and showed that cryptomonad genes are not detectably related to EFL from other chromalveolates, which collectively form several distinct groups. The known distribution of EFL now includes a third group of chromalveolates, cryptomonads. Of the six major subgroups of chromalveolates, EFL is found in half and EF-1alpha in the other half, and none as yet unambiguously possess both genes. Phylogenetic analysis indicates EFL likely arose early within each subgroup where it is found, but suggests it may have originated multiple times within chromalveolates as a whole.

Prediction of function divergence in protein families using the substitution rate variation parameter alpha

Protein families typically embody a range of related functions and may thus be decomposed into subfamilies with, for example, distinct substrate specificities. Detection of functionally divergent subfamilies is possible by methods for recognizing branches of adaptive evolution in a gene tree. As the number of genome sequences is growing rapidly, it is highly desirable to automatically detect subfamily function divergence. To this end, we here introduce a method for large-scale prediction of function divergence within protein families. It is called the alpha shift measure (ASM) as it is based on detecting a shift in the shape parameter (alpha [alpha]) of the substitution rate gamma distribution. Four different methods for estimating alpha were investigated. We benchmarked the accuracy of ASM using function annotation from Enzyme Commission numbers within Pfam protein families divided into subfamilies by the automatic tree-based method BETE. In a test using 563 subfamily pairs in 162 families, ASM outperformed functional site-based methods using rate or conservation shifting (rate shift measure [RSM] and conservation shift measure [CSM]). The best results were obtained using the "GZ-Gamma" method for estimating alpha. By combining ASM with RSM and CSM using linear discriminant analysis, the prediction accuracy was further improved.

Large-scale prediction of function shift in protein families with a focus on enzymatic function

Protein function shift can be predicted from sequence comparisons, either using positive selection signals or evolutionary rate estimation. None of the methods have been validated on large datasets, however. Here we investigate existing and novel methods for protein function shift prediction, and benchmark the accuracy against a large dataset of proteins with known enzymatic functions. Function change was predicted between subfamilies by identifying two kinds of sites in a multiple sequence alignment: Conservation-Shifting Sites (CSS), which are conserved in two subfamilies using two different amino acid types, and Rate-Shifting Sites (RSS), which have different evolutionary rates in two subfamilies. CSS were predicted by a new entropy-based method, and RSS using the Rate-Shift program. In principle, the more CSS and RSS between two subfamilies, the more likely a function shift between them. A test dataset was built by extracting subfamilies from Pfam with different EC numbers that belong to the same domain family. Subfamilies were generated automatically using a phylogenetic tree-based program, BETE. The dataset comprised 997 subfamily pairs with four or more members per subfamily. We observed a significant increase in CSS and RSS for subfamily comparisons with different EC numbers compared to cases with same EC numbers. The discrimination was better using RSS than CSS, and was more pronounced for larger families. Combining RSS and CSS by discriminant analysis improved classification accuracy to 71%. The method was applied to the Pfam database and the results are available at http://FunShift.cgb.ki.se. A closer examination of some superfamily comparisons showed that single EC numbers sometimes embody distinct functional classes. Hence, the measured accuracy of function shift is underestimated.

Networks of coevolving sites in structural and functional domains of serpin proteins

Amino acids do not occur randomly in proteins; rather, their occurrence at any given site is strongly influenced by the amino acid composition at other sites, the structural and functional aspects of the region of the protein in which they occur, and the evolutionary history of the protein. The goal of our research study is to identify networks of coevolving sites within the serpin proteins (serine protease inhibitors) and classify them as being caused by structural-functional constraints or by evolutionary history. To address this, a matrix of pairwise normalized mutual information (NMI) values was computed among amino acid sites for the serpin proteins. The NMI matrix was partitioned into orthogonal patterns of amino acid variability by factor analysis. Each common factor pattern was interpreted as having phylogenetic and/or structural-functional explanations. In addition, we used a bootstrap factor analysis technique to limit the effects of phylogenetic history on our factor patterns. Our results show an extensive network of correlations among amino acid sites in key functional regions (reactive center loop, shutter, and breach). Additionally, we have discovered long-range coevolution for packed amino acids within the serpin protein core. Lastly, we have discovered a group of serpin sites which coevolve in the hydrophobic core region (s5B and s4B) and appear to represent sites important for formation of the "native" instead of the "latent" serpin structure. This research provides a better understanding on how protein structure evolves; in particular, it elucidates the selective forces creating coevolution among protein sites.

FunShift: a database of function shift analysis on protein subfamilies

Members of a protein family normally have a general biochemical function in common, but frequently one or more subgroups have evolved a slightly different function, such as different substrate specificity. It is important to detect such function shifts for a more accurate functional annotation. The FunShift database described here is a compilation of function shift analysis performed between subfamilies in protein families. It consists of two main components: (i) subfamilies derived from protein domain families and (ii) pairwise subfamily comparisons analyzed for function shift. The present release, FunShift 12, was derived from Pfam 12 and consists of 151 934 subfamilies derived from 7300 families. We carried out function shift analysis by two complementary methods on families with up to 500 members. From a total of 179 210 subfamily pairs, 62 384 were predicted to be functionally shifted in 2881 families. Each subfamily pair is provided with a markup of probable functional specificity-determining sites. Tools for searching and exploring the data are provided to make this database a valuable resource for protein function annotation. Knowledge of these functionally important sites will be useful for experimental biologists performing functional mutation studies. FunShift is available at http://FunShift.cgb.ki.se.

Analytical Methods for Studying the Evolution of Paralogs Using Duplicate Gene Datasets

Gene duplication is widely viewed as an important source of raw material for functional innovation in proteins because at least some duplicate copies will evolve new or slightly modified functions. The study of the molecular processes by which functional innovation occurs interests both evolutionary biologists and protein chemists, and the development of methods to investigate these processes has led to a productive meeting of disciplines and an availability of complementary approaches for exploring datasets. This has resulted in insights into past events, prediction of current function, and prediction of future change. The methods fall broadly into two categories: those that rely on detection of shifts in selective constraints and those that rely on detection of correlations between molecular changes and functional shifts. Strengths and limitations of the methods are evaluated here in the context of the question being addressed, the input required, and the specific metric that is evaluated in each test.