Coevolutionary Analysis Research Articles

Tanglegrams: A Reduction Tool for Mathematical Phylogenetics.

Many discrete mathematics problems in phylogenetics are defined in terms of the relative labeling of pairs of leaf-labeled trees. These relative labelings are naturally formalized as tanglegrams, which have previously been an object of study in coevolutionary analysis. Although there has been considerable work on planar drawings of tanglegrams, they have not been fully explored as combinatorial objects until recently. In this paper, we describe how many discrete mathematical questions on trees "factor" through a problem on tanglegrams, and how understanding that factoring can simplify analysis. Depending on the problem, it may be useful to consider a unordered version of tanglegrams, and/or their unrooted counterparts. For all of these definitions, we show how the isomorphism types of tanglegrams can be understood in terms of double cosets of the symmetric group, and we investigate their automorphisms. Understanding tanglegrams better will isolate the distinct problems on leaf-labeled pairs of trees and reveal natural symmetries of spaces associated with such problems.

Phylogenetic Evidence for Ancient and Persistent Environmental Symbiont Reacquisition in Largidae (Hemiptera: Heteroptera).

Obligate symbioses with bacteria are common in insects, particularly Hemiptera, in which various forms of symbiosis occur. However, knowledge regarding symbionts remains incomplete for major hemipteran lineages. Thus, an accurate understanding of how these partnerships evolved and changed over millions of years is not yet achievable. We contribute to our understanding of the evolution of symbiotic complexes in Hemiptera by characterizing bacterial associates of Pyrrhocoroidea, focusing on the family Largidae. Members of Largidae are associated with specific symbiotic Burkholderia strains from a different clade than Burkholderia symbionts in other Burkholderia-associated Hemiptera. Evidence suggests that species of Largidae reacquire specific symbiotic bacteria from the environment every generation, which is a rare strategy for insects, with potentially volatile evolutionary ramifications, but one that must have persisted in Largidae and related lineages since their origin in the Cretaceous Period.

Origin of the plant Tm-1-like gene via two independent horizontal transfer events and one gene fusion event.

The Tomato mosaic virus (ToMV) resistance gene Tm-1 encodes a direct inhibitor of ToMV RNA replication to protect tomato from infection. The plant Tm-1-like (Tm-1L) protein is predicted to contain an uncharacterized N-terminal UPF0261 domain and a C-terminal TIM-barrel signal transduction (TBST) domain. Homologous searches revealed that proteins containing both of these two domains are mainly present in charophyte green algae and land plants but absent from glaucophytes, red algae and chlorophyte green algae. Although Tm-1 homologs are widely present in bacteria, archaea and fungi, UPF0261- and TBST-domain-containing proteins are generally encoded by different genes in these linages. A co-evolution analysis also suggested a putative interaction between UPF0261- and TBST-domain-containing proteins. Phylogenetic analyses based on homologs of these two domains revealed that plants have acquired UPF0261- and TBST-domain-encoding genes through two independent horizontal gene transfer (HGT) events before the origin of land plants from charophytes. Subsequently, gene fusion occurred between these two horizontally acquired genes and resulted in the origin of the Tm-1L gene in streptophytes. Our results demonstrate a novel evolutionary mechanism through which the recipient organism may acquire genes with functional interaction through two different HGT events and further fuse them into one functional gene.

Gammaproteobacteria as essential primary symbionts in the striped shield bug, Graphosoma Lineatum (Hemiptera: Pentatomidae).

Many members of suborder Heteroptra harbor heritable symbiotic bacteria. Here we characterize the gut symbiotic bacterium in Graphosoma lineatum (Hemiptera: Pentatomidae) by using molecular phylogeny, real-time PCR analysis as well as light and electron microscopy observations. The microscopy observations revealed the presence of a large number of rod-shaped bacterial cells in the crypts. A very high prevalence (98 to 100%) of the symbiont infection was found in the insect populations that strongly supports an intimate association between these two organisms. Real-time PCR analysis also showed that the Gammaproteobacteria dominated the crypts. The sequences of 16sr RNA and groEL genes of symbiont showed high levels of similarity (93 to 95%) to Pantoea agglomeranse and Erwinia herbicola Gammaproteobacteria. Phylogenetic analyses placed G. lineatum symbiont in a well-defined branch, divergent from other stink bug bacterial symbionts. Co-evolutionary analysis showed lack of host-symbiont phylogenetic congruence. Surface sterilization of eggs resulted in increased pre-adult stage in the offspring (aposymbionts) in comparison to the normal. Also, fecundity, longevity, and adult stage were significantly decreased in the aposymbionts. Therefore, it seems that the symbiont might play a vital function in the host biology, in which host optimal development depends on the symbiont.

Distinct Structural Elements Govern the Folding, Stability, and Catalysis in the Outer Membrane Enzyme PagP

The outer membrane enzyme PagP is indispensable for lipid A palmitoylation in Gram-negative bacteria and has been implicated in resistance to host immune defenses. PagP possesses an unusual structure for an integral membrane protein, with a highly dynamic barrel domain that is tilted with respect to the membrane normal. In addition, it contains an N-terminal amphipathic helix. Recent functional and structural studies have shown that these molecular factors are critical for PagP to carry out its function in the challenging environment of the bacterial outer membrane. However, the precise contributions of the N-helix to folding and stability and residues that can influence catalytic rates remain to be addressed. Here, we identify a sequence-dependent stabilizing role for the N-terminal helix of PagP in the measured thermodynamic stability of the barrel. Using chimeric barrel sequences, we show that the Escherichia coli PagP N-terminal helix confers 2-fold greater stability to the Salmonella typhimurium barrel. Further, we find that the W78F substitution in S. typhimurium causes a nearly 20-fold increase in the specific activity in vitro for the phospholipase reaction, compared to that of E. coli PagP. Here, phenylalanine serves as a key regulator of catalysis, possibly by increasing the reaction rate. Through coevolution analysis, we detect an interaction network between seemingly unrelated segments of this membrane protein. Exchanging the structural and functional features between homologous PagP enzymes from E. coli and S. typhimurium has provided us with an understanding of the molecular factors governing PagP stability and function.

Antiparallel protocadherin homodimers use distinct affinity- and specificity-mediating regions in cadherin repeats 1-4.

Protocadherins (Pcdhs) are cell adhesion and signaling proteins used by neurons to develop and maintain neuronal networks, relying on trans homophilic interactions between their extracellular cadherin (EC) repeat domains. We present the structure of the antiparallel EC1-4 homodimer of human PcdhγB3, a member of the γ subfamily of clustered Pcdhs. Structure and sequence comparisons of α, β, and γ clustered Pcdh isoforms illustrate that subfamilies encode specificity in distinct ways through diversification of loop region structure and composition in EC2 and EC3, which contains isoform-specific conservation of primarily polar residues. In contrast, the EC1/EC4 interface comprises hydrophobic interactions that provide non-selective dimerization affinity. Using sequence coevolution analysis, we found evidence for a similar antiparallel EC1-4 interaction in non-clustered Pcdh families. We thus deduce that the EC1-4 antiparallel homodimer is a general interaction strategy that evolved before the divergence of these distinct protocadherin families.

A Combined Computational and Genetic Approach Uncovers Network Interactions of the Cyanobacterial Circadian Clock.

Two-component systems (TCS) that employ histidine kinases (HK) and response regulators (RR) are critical mediators of cellular signaling in bacteria. In the model cyanobacterium Synechococcus elongatus PCC 7942, TCSs control global rhythms of transcription that reflect an integration of time information from the circadian clock with a variety of cellular and environmental inputs. The HK CikA and the SasA/RpaA TCS transduce time information from the circadian oscillator to modulate downstream cellular processes. Despite immense progress in understanding of the circadian clock itself, many of the connections between the clock and other cellular signaling systems have remained enigmatic. To narrow the search for additional TCS components that connect to the clock, we utilized direct-coupling analysis (DCA), a statistical analysis of covariant residues among related amino acid sequences, to infer coevolution of new and known clock TCS components. DCA revealed a high degree of interaction specificity between SasA and CikA with RpaA, as expected, but also with the phosphate-responsive response regulator SphR. Coevolutionary analysis also predicted strong specificity between RpaA and a previously undescribed kinase, HK0480 (herein CikB). A knockout of the gene for CikB (cikB) in a sasA cikA null background eliminated the RpaA phosphorylation and RpaA-controlled transcription that is otherwise present in that background and suppressed cell elongation, supporting the notion that CikB is an interactor with RpaA and the clock network. This study demonstrates the power of DCA to identify subnetworks and key interactions in signaling pathways and of combinatorial mutagenesis to explore the phenotypic consequences. Such a combined strategy is broadly applicable to other prokaryotic systems. Signaling networks are complex and extensive, comprising multiple integrated pathways that respond to cellular and environmental cues. A TCS interaction model, based on DCA, independently confirmed known interactions and revealed a core set of subnetworks within the larger HK-RR set. We validated high-scoring candidate proteins via combinatorial genetics, demonstrating that DCA can be utilized to reduce the search space of complex protein networks and to infer undiscovered specific interactions for signaling proteins in vivo Significantly, new interactions that link circadian response to cell division and fitness in a light/dark cycle were uncovered. The combined analysis also uncovered a more basic core clock, illustrating the synergy and applicability of a combined computational and genetic approach for investigating prokaryotic signaling networks.

Analysis of coevolution in nonstructural proteins of chikungunya virus.

BackgroundRNA viruses are characterized by high rate of mutations mainly due to the lack of proofreading repair activities associated with its RNA-dependent RNA-polymerase (RdRp). In case of arboviruses, this phenomenon has lead to the existence of mixed population of genomic variants within the host called quasi-species. The stability of strains within the quasi-species lies on mutations that are positively selected which in turn depend on whether these mutations are beneficial in either or both hosts. Coevolution of amino acids (aa) is one phenomenon that leads to establishment of favorable traits in viruses and leading to their fitness.ResultsFourteen CHIKV clinical samples collected over three years were subjected to RT-PCR, the four non-structural genes amplified and subjected to various genetic analyses. Coevolution analysis showed 30 aa pairs coevolving in nsP1, 23 aa pairs coevolving in nsP2, 239 in nsP3 and 46 aa coevolving pairs in nsP4 when each non-structural protein was considered independently. Further analysis showed that 705 amino acids pairs of the non-structural polyproteins coevolved together with a correlation coefficient of ≥0.5. Functional relevance of these coevolving amino acids in all the nonstructural proteins of CHIKV were predicted using Eukaryotic Linear Motifs (ELMs) of human.ConclusionsThe present study was undertaken to study co-evolving amino acids in the non-structural proteins of chikungunya virus (CHIKV), an important arbovirus. It was observed that several amino acids residues were coevolving and shared common functions.

Towards sub-quadratic time and space complexity solutions for the dated tree reconciliation problem.

BackgroundRecent coevolutionary analysis has considered tree topology as a means to reduce the asymptotic complexity associated with inferring the complex coevolutionary interrelationships that arise between phylogenetic trees. Targeted algorithmic design for specific tree topologies has to date been highly successful, with one recent formulation providing a logarithmic space complexity reduction for the dated tree reconciliation problem.MethodsIn this work we build on this prior analysis providing a further asymptotic space reduction, by providing a new formulation for the dynamic programming table used by a number of popular coevolutionary analysis techniques. This model gives rise to a sub quadratic running time solution for the dated tree reconciliation problem for selected tree topologies, and is shown to be, in practice, the fastest method for solving the dated tree reconciliation problem for expected evolutionary trees. This result is achieved through the analysis of not only the topology of the trees considered for coevolutionary analysis, but also the underlying structure of the dynamic programming algorithms that are traditionally applied to such analysis.ConclusionThe newly inferred theoretical complexity bounds introduced herein are then validated using a combination of synthetic and biological data sets, where the proposed model is shown to provide an O(sqrt{n}) space saving, while it is observed to run in half the time compared to the fastest known algorithm for solving the dated tree reconciliation problem. What is even more significant is that the algorithm derived herein is able to guarantee the optimality of its inferred solution, something that algorithms of comparable speed have to date been unable to achieve.

Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins.

A novel computational approach of coevolution analysis allowed us to reconstruct the protein-protein interaction network of the Hepatitis C Virus (HCV) at the residue resolution. For the first time, coevolution analysis of an entire viral genome was realized, based on a limited set of protein sequences with high sequence identity within genotypes. The identified coevolving residues constitute highly relevant predictions of protein-protein interactions for further experimental identification of HCV protein complexes. The method can be used to analyse other viral genomes and to predict the associated protein interaction networks.

Dimerization and Transactivation Domains as Candidates for Functional Modulation and Diversity of Sox9.

Sox9 plays an important role in a large variety of developmental pathways in vertebrates. It is composed of three domains: high-mobility group box (HMG box), dimerization (DIM) and transactivation (TAD). One of the main processes for regulation and variability of the pathways involving Sox9 is the self-gene expression regulation of Sox9. However, the subsequent roles of the Sox9 domains can also generate regulatory modulations. Studies have shown that TADs can bind to different types of proteins and its function seems to be influenced by DIM. Therefore, we hypothesized that both domains are directly associated and can be responsible for the functional variability of Sox9. We applied a method based on a broad phylogenetic context, using sequences of the HMG box domain, to ensure the homology of all the Sox9 copies used herein. The data obtained included 4,921 sequences relative to 657 metazoan species. Based on coevolutionary and selective pressure analyses of the Sox9 sequences, we observed coevolutions involving DIM and TADs. These data, along with the experimental data from literature, indicate a functional relationship between these domains. Moreover, DIM and TADs may be responsible for the functional plasticity of Sox9 because they are more tolerant for molecular changes (higher Ka/Ks ratio than the HMG box domain). This tolerance could allow a differential regulation of target genes or promote novel targets during transcriptional activation. In conclusion, we suggest that DIM and TADs functional association may regulate differentially the target genes or even promote novel targets during transcription activation mediated by Sox9 paralogs, contributing to the subfunctionalization of Sox9a and Sox9b in teleosts.

Improving the catalytic activity of isopentenyl phosphate kinase through protein coevolution analysis.

Protein rational design has become more and more popular for protein engineering with the advantage of biological big-data. In this study, we described a method of rational design that is able to identify desired mutants by analyzing the coevolution of protein sequence. We employed this approach to evolve an archaeal isopentenyl phosphate kinase that can convert dimethylallyl alcohol (DMA) into precursor of isoprenoids. By designing 9 point mutations, we improved the catalytic activities of IPK about 8-fold in vitro. After introducing the optimal mutant of IPK into engineered E. coli strain for β-carotenoids production, we found that β-carotenoids production exhibited 97% increase over the starting strain. The process of enzyme optimization presented here could be used to improve the catalytic activities of other enzymes.

CoeViz: a web-based tool for coevolution analysis of protein residues.

BackgroundProteins generally perform their function in a folded state. Residues forming an active site, whether it is a catalytic center or interaction interface, are frequently distant in a protein sequence. Hence, traditional sequence-based prediction methods focusing on a single residue (or a short window of residues) at a time may have difficulties in identifying and clustering the residues constituting a functional site, especially when a protein has multiple functions. Evolutionary information encoded in multiple sequence alignments is known to greatly improve sequence-based predictions. Identification of coevolving residues further advances the protein structure and function annotation by revealing cooperative pairs and higher order groupings of residues.ResultsWe present a new web-based tool (CoeViz) that provides a versatile analysis and visualization of pairwise coevolution of amino acid residues. The tool computes three covariance metrics: mutual information, chi-square statistic, Pearson correlation, and one conservation metric: joint Shannon entropy. Implemented adjustments of covariance scores include phylogeny correction, corrections for sequence dissimilarity and alignment gaps, and the average product correction. Visualization of residue relationships is enhanced by hierarchical cluster trees, heat maps, circular diagrams, and the residue highlighting in protein sequence and 3D structure. Unlike other existing tools, CoeViz is not limited to analyzing conserved domains or protein families and can process long, unstructured and multi-domain proteins thousands of residues long. Two examples are provided to illustrate the use of the tool for identification of residues (1) involved in enzymatic function, (2) forming short linear functional motifs, and (3) constituting a structural domain.ConclusionsCoeViz represents a practical resource for a quick sequence-based protein annotation for molecular biologists, e.g., for identifying putative functional clusters of residues and structural domains. CoeViz also can serve computational biologists as a resource of coevolution matrices, e.g., for developing machine learning-based prediction models. The presented tool is integrated in the POLYVIEW-2D server (http://polyview.cchmc.org/) and available from resulting pages of POLYVIEW-2D.

Structure-based Markov random field model for representing evolutionary constraints on functional sites.

BackgroundElucidating the cooperative mechanism of interconnected residues is an important component toward understanding the biological function of a protein. Coevolution analysis has been developed to model the coevolutionary information reflecting structural and functional constraints. Recently, several methods have been developed based on a probabilistic graphical model called the Markov random field (MRF), which have led to significant improvements for coevolution analysis; however, thus far, the performance of these models has mainly been assessed by focusing on the aspect of protein structure.ResultsIn this study, we built an MRF model whose graphical topology is determined by the residue proximity in the protein structure, and derived a novel positional coevolution estimate utilizing the node weight of the MRF model. This structure-based MRF method was evaluated for three data sets, each of which annotates catalytic site, allosteric site, and comprehensively determined functional site information. We demonstrate that the structure-based MRF architecture can encode the evolutionary information associated with biological function. Furthermore, we show that the node weight can more accurately represent positional coevolution information compared to the edge weight. Lastly, we demonstrate that the structure-based MRF model can be reliably built with only a few aligned sequences in linear time.ConclusionsThe results show that adoption of a structure-based architecture could be an acceptable approximation for coevolution modeling with efficient computation complexity.

Epigenomic Co-localization and Co-evolution Reveal a Key Role for 5hmC as a Communication Hub in the Chromatin Network of ESCs.

Epigenetic communication through histone and cytosine modifications is essential for gene regulation and cell identity. Here, we propose a framework that is based on a chromatin communication model to get insight on the function of epigenetic modifications in ESCs. The epigenetic communication network was inferred from genome-wide location data plus extensive manual annotation. Notably, we found that 5-hydroxymethylcytosine (5hmC) is the most-influential hub of this network, connecting DNA demethylation to nucleosome remodeling complexes and to key transcription factors of pluripotency. Moreover, an evolutionary analysis revealed a central role of 5hmC in the co-evolution of chromatin-related proteins. Further analysis of regions where 5hmC co-localizes with specific interactors shows that each interaction points to chromatin remodeling, stemness, differentiation, or metabolism. Our results highlight the importance of cytosine modifications in the epigenetic communication of ESCs.

Coupling high-throughput genetics with phylogenetic information reveals an epistatic interaction on the influenza A virus M segment.

BackgroundEpistasis is one of the central themes in viral evolution due to its importance in drug resistance, immune escape, and interspecies transmission. However, there is a lack of experimental approach to systematically probe for epistatic residues.ResultsBy utilizing the information from natural occurring sequences and high-throughput genetics, this study established a novel strategy to identify epistatic residues. The rationale is that a substitution that is deleterious in one strain may be prevalent in nature due to the presence of a naturally occurring compensatory substitution. Here, high-throughput genetics was applied to influenza A virus M segment to systematically identify deleterious substitutions. Comparison with natural sequence variation showed that a deleterious substitution M1 Q214H was prevalent in circulating strains. A coevolution analysis was then performed and indicated that M1 residues 121, 207, 209, and 214 naturally coevolved as a group. Subsequently, we experimentally validated that M1 A209T was a compensatory substitution for M1 Q214H.ConclusionsThis work provided a proof-of-concept to identify epistatic residues by coupling high-throughput genetics with phylogenetic information. In particular, we were able to identify an epistatic interaction between M1 substitutions A209T and Q214H. This analytic strategy can potentially be adapted to study any protein of interest, provided that the information on natural sequence variants is available.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2358-7) contains supplementary material, which is available to authorized users.

Coevolutionary Analysis Identifies Protein-Protein Interaction Sites between HIV-1 Reverse Transcriptase and Integrase.

The replication of human immunodeficiency virus-1 (HIV-1) requires reverse transcription of the viral RNA genome and integration of newly synthesized pro-viral DNA into the host genome. This is mediated by the viral proteins reverse transcriptase (RT) and integrase (IN). The formation and stabilization of the pre-integration complex (PIC), which is an essential step for reverse transcription, nuclear import, chromatin targeting, and subsequent integration, involves direct and indirect modes of interaction between RT and IN proteins. While epitope-based treatments targeting IN–viral DNA and IN–RT complexes appear to be a promising combination for an anti-HIV treatment, the mechanisms of IN-RT interactions within the PIC are not well understood due to the transient nature of the protein complex and the intrinsic flexibility of its components. Here, we identify potentially interacting regions between the IN and RT proteins within the PIC through the coevolutionary analysis of amino acid sequences of the two proteins. Our results show that specific regions in the two proteins have strong coevolutionary signatures, suggesting that these regions either experience direct and prolonged interactions between them that require high affinity and/or specificity or that the regions are involved in interactions mediated by dynamic conformational changes and, hence, may involve both direct and indirect interactions. Other regions were found to exhibit weak, but positive correlations, implying interactions that are likely transient and/or have low affinity. We identified a series of specific regions of potential interactions between the IN and RT proteins (e.g., specific peptide regions within the C-terminal domain of IN were identified as potentially interacting with the Connection domain of RT). Coevolutionary analysis can serve as an important step in predicting potential interactions, thus informing experimental studies. These studies can be integrated with structural data to gain a better understanding of the mechanisms of HIV protein interactions.

Characterizing the Diverse Mutational Pathways Associated with R5-Tropic Maraviroc Resistance: HIV-1 That Uses the Drug-Bound CCR5 Coreceptor.

ABSTRACTEntry inhibitors represent a potent class of antiretroviral drugs that target a host cell protein, CCR5, an HIV-1 entry coreceptor, and not viral protein. Lack of sensitivity can occur due to preexisting virus that uses the CXCR4 coreceptor, while true resistance occurs through viral adaptation to use a drug-bound CCR5 coreceptor. To understand this R5 resistance pathway, we analyzed >500 envelope protein sequences and phenotypes from viruses of 20 patients from the clinical trials MOTIVATE 1 and 2, in which treatment-experienced patients received maraviroc plus optimized background therapy. The resistant viral population was phylogenetically distinct and associated with a genetic bottleneck in each patient, consistent with de novo emergence of resistance. Recombination analysis showed that the C2-V3-C3 region tends to genotypically correspond to the recombinant's phenotype, indicating its primary importance in conferring resistance. Between patients, there was a notable lack of commonality in the specific sites conferring resistance, confirming the unusual nature of R5-tropic resistance. We used coevolutionary and positive-selection analyses to characterize the genotypic determinants of resistance and found that (i) there are complicated covariation networks, indicating frequent coevolutionary/compensatory changes in the context of protein structure; (ii) covarying sites under positive selection are enriched in resistant viruses; (iii) CD4 binding sites form part of a unique covariation network independent of the V3 loop; and (iv) the covariation network formed between the V3 loop and other regions of gp120 and gp41 intersects sites involved in glycosylation and protein secretion. These results demonstrate that while envelope sequence mutations are the key to conferring maraviroc resistance, the specific changes involved are context dependent and thus inherently unpredictable.IMPORTANCE The entry inhibitor drug maraviroc makes the cell coreceptor CCR5 unavailable for use by HIV-1 and is now used in combination antiretroviral therapy. Treatment failure with drug-resistant virus is particularly interesting because it tends to be rare, with lack of sensitivity usually associated with the presence of CXCR4-using virus (CXCR4 is the main alternative coreceptor HIV-1 uses, in addition to CD4). We analyzed envelope sequences from HIV-1, obtained from 20 patients who enrolled in maraviroc clinical trials and experienced treatment failure, without detection of CXCR4-using virus. Evolutionary analysis was employed to identify molecular changes that confer maraviroc resistance. We found that in these individuals, resistant viruses form a distinct population that evolved once and was successful as a result of drug pressure. Further evolutionary analysis placed the complex network of interdependent mutational changes into functional groups that help explain the impediments to the emergence of maraviroc-associated R5 drug resistance.

Coevolutionary analyses require phylogenetically deep alignments and better null models to accurately detect inter-protein contacts within and between species.

BackgroundWhen biomolecules physically interact, natural selection operates on them jointly. Contacting positions in protein and RNA structures exhibit correlated patterns of sequence evolution due to constraints imposed by the interaction, and molecular arms races can develop between interacting proteins in pathogens and their hosts. To evaluate how well methods developed to detect coevolving residues within proteins can be adapted for cross-species, inter-protein analysis, we used statistical criteria to quantify the performance of these methods in detecting inter-protein residues within 8 angstroms of each other in the co-crystal structures of 33 bacterial protein interactions. We also evaluated their performance for detecting known residues at the interface of a host-virus protein complex with a partially solved structure.ResultsOur quantitative benchmarking showed that all coevolutionary methods clearly benefit from alignments with many sequences. Methods that aim to detect direct correlations generally outperform other approaches. However, faster mutual information based methods are occasionally competitive in small alignments and with relaxed false positive rates. Two commonly used null distributions are anti-conservative and have high false positive rates in some scenarios, although the empirical distribution of scores performs reasonably well with deep alignments.ConclusionsWe conclude that coevolutionary analysis of cross-species protein interactions holds great promise but requires sequencing many more species pairs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0677-y) contains supplementary material, which is available to authorized users.

Identification of residues in ABCG2 affecting protein trafficking and drug transport, using co-evolutionary analysis of ABCG sequences.

ABCG2 is an ABC (ATP-binding cassette) transporter with a physiological role in urate transport in the kidney and is also implicated in multi-drug efflux from a number of organs in the body. The trafficking of the protein and the mechanism by which it recognizes and transports diverse drugs are important areas of research. In the current study, we have made a series of single amino acid mutations in ABCG2 on the basis of sequence analysis. Mutant isoforms were characterized for cell surface expression and function. One mutant (I573A) showed disrupted glycosylation and reduced trafficking kinetics. In contrast with many ABC transporter folding mutations which appear to be 'rescued' by chemical chaperones or low temperature incubation, the I573A mutation was not enriched at the cell surface by either treatment, with the majority of the protein being retained in the endoplasmic reticulum (ER). Two other mutations (P485A and M549A) showed distinct effects on transport of ABCG2 substrates reinforcing the role of TM helix 3in drug recognition and transport and indicating the presence of intracellular coupling regions in ABCG2.