Separately, we searched for the metazoan integrin type β-propeller domains among all available sequences from bacteria and unicellular eukaryotic organisms, which must incorporate seven repeats, corresponding to the seven blades of the β-propeller domain, and so that the newly found structure-derived motif would exist in every repeat. As the result, among 47 available genomes of unicellular eukaryotes we could not find a single instance of seven repeats with the motif. Several sequences contained three repeats, a predicted transmembrane segment, and a short cytoplasmic motif associated with some integrins, but otherwise differ from the metazoan integrin α subunits. Among the available bacterial sequences, we found five examples containing seven sequential metazoan integrin-specific motifs within the seven repeats. The motifs differ in having one Ca2+-binding site per repeat, whereas metazoan integrins have three or four sites. The bacterial sequences are more conserved in terms of motif conservation and loop length, suggesting that the structure is more regular and compact than those example structures from human integrins. Although the bacterial examples are not full-length integrins, the full-length metazoan-type 7-bladed β-propeller domains are present, and sometimes two tandem copies are found.Integrins are heterodimeric cell-surface receptors with key functions in cell-cell and cell-matrix adhesion. Integrin α and β subunits are present throughout the metazoans, but it is unclear whether the subunits predate the origin of multicellular organisms. Several component domains have been detected in bacteria, one of which, a specific 7-bladed β-propeller domain, is a unique feature of the integrin α subunits. Here, we describe a structure-derived motif, which incorporates key features of each blade from the X-ray structures of human αIIbβ3 and αVβ3, includes elements of the FG-GAP/Cage and Ca Integrins are large, heterodimeric cell-surface receptors that detect and transmit changes in mechanical forces resulting from interactions between a cell and the extracellular matrix Vertebrates express at least 18 different integrin α subunits and eight β subunits, forming 24 α/β heterodimeric receptors in human not contain the αI domain. The Arg-Gly-Asp (RGD) sequence, present in the integrin ligands fibronectin and laminin, is one of the very first motifs that was found to be recognized by integrins 2+ coordinated by MIDAS of the I-like βA domain present in the β subunit, while the arginine side chain directly binds to the N-terminal β-propeller domain of the α subunit The remaining nine α subunits, α3, α4, α5, α6, α7, α8, α9, αV, and αIIb, do C. elegans to H. sapiens and including sequences from the tunicate C. intestinalis and the pufferfish T. rubripes, has shown that orthologues of the human α subunits and β subunits of the integrins are highly conserved in bony vertebrates Geodia cydonium.A study of 90 integrin α subunits and 57 β subunits from 26 different metazoan species, ranging from Neoparamoeba aestuarinaCapsaspora owczarzaki (a unicellular organism diverging just prior to metazoans) Thecamonas trahens (formerly Amastigomonas sp.) contain domain sequences that appear to have the hallmarks of α and β subunits of integrins A cell adhesion system involving proteins with the RGD sequence may have already existed in protozoa since a GRGDSPK peptide but not the GRGESPK peptide caused substratum-detachment of cells of the marine amoeba Synechocystis sp. PCC6803 Planctomycetale bacteria Gemmata obscuriglobus and integrin αV, including the putative Ca2+-binding region common to integrins The first report of similarities between bacterial sequences and integrin sequences was made over ten years ago, when May and Ponting reported that an automated run of PSI-BLAST Trichodesmium erythraeum is homologous with more than 450 residues of integrin β-subunit which includes the amino-terminal βA-domain but other domains such as the EGF repeats and transmembrane segment were not present in the sequence In the course of our own search of the available sequence data for sequences matching human integrin α and β subunits, we identified several matching sequences in bacteria that aligned surprisingly well with portions of the integrin subunits As defined in the SCOP database, the N-terminal β-propeller domain of integrin α subunits has the 7-bladed β-propeller fold Structures of three different integrins containing the β-propeller domain, all from human, have now been solved: αVβ3 Previously, it was already shown, that at least four non-integrin type of 7-bladed β-propeller domains as well as several 8-, 6- and 4-bladed β-propeller domains were found in bacteria There are two reported descriptions of a repeating consensus sequence for human integrin β-propeller domains, but both define the same basic consensus sequence: (1) the “FG-GAP repeat” sequence motif plus a Gly-Ala-Pro (GAP) tripeptide in the second strand 13–20PX2–15GX5–8  consensus sequence reported with the X-ray structure of the human αVβ3 ectodomain The FG-GAP repeat motif was defined based on sequence similarities, and a structural model of the integrin β-propeller domain proposed a repeating structure, where each “blade” contains a 4-stranded β-sheet with a Phe-Gly (FG) pair in the first strand When, in an earlier sequence-based search In addition to sequence data on all of the human integrin α and β subunits, we have considered the high-resolution X-ray structures for the human integrin ectodomains: αVβ3 In this study, we considered only the sequences and structures of the β-propeller domain and excluded other regions including the I domain sequence that buds out of the β-propeller in 9 of the 18 human integrin α subunits. In order to more fully-characterize the repeating unit, we have made detailed comparisons of the sequences and structures in order to define a structural motif.Any structural motif has two major features: (1) it includes segments of the polypeptide chain with identical secondary structure, which (2) interact in an identical way to fulfill their function. Thus, based on the definition of the motif we should be able to identify key essential features that define each blade of the integrin domain, differences with the other reported family members, and see if the sequence patterns in the bacterial sequences or other non-integrin sequences support the same structural requirements as the integrin β-propeller domains.Each blade from the integrin-type β-propeller domains consists of four antiparallel β-strands and four loop regions; in These positions within the three segments, tabulated for all 7 blades from the β-propeller domains of the 18 human integrin α subunits , are higA type II β-turn is a four-residue turn characterized by the following three criteria , with torsion angles near ϕψB3 = 0° . The conψB3 = 0° . Of the I β-turn .2+ at the opposite end of the blade to segments A–C.As a consequence of the structural requirements of the type II and type I turns, two conserved residues common to the Cage and FG-GAP motifs, glycine and proline, are respectively found with high frequency at positions A3 and B2. It is due to the structural requirements that both residues are conserved in the sequence motif descriptions. In addition to the hydrogen bond stabilizing each turn type, there are 5 additional hydrogen bonds between main-chain amino and carbonyl groups that link segments A, B and C to form a rigid unit . These sGlycine in the type II turn and proline in the type I turn are conserved but not invariant . Our ana2+ . Moreover the conservation of the key glycine and proline residues was not observed in the 13 superfamilies.Characteristic 1, the presence of the Cage motif: The Cage motif Characteristic 2, the presence of type II and type I turns: Only in integrin α subunits, and not in the other 7-bladed β-propeller fold proteins, we observe the presence of two β-turns, one type II and one type I turn, within each blade. In the 32 representative structures from the other 13 superfamilies, 12 structures do not contain even one pair of β-turns within two adjacent segments A and B as seen in the integrins see  and 2. TCharacteristic 3, a hydrogen bonding network linking segments A, B and C: Only in the integrins, in each of the seven blades, the two β-turns residing in the segments A and B are closely aligned and interact with each other via a network of hydrogen bonds, as shown in 2+-binding motif: The Ca2+-binding motif formed from two adjacent loops only found in the integrin-type β-propeller domain.Characteristic 4, the presence of a CaCharacteristic 5 (non-specific), a non-sequential 4th strand in blade 7 arising from the sequence N-terminal to blade 1 of the domain. This is seen in the structures of the β-propeller domain from the human αV and αIIb subunits but it is not a feature unique to the β-propeller domain from the human α subunits.2+-binding motif, as well as the four antiparallel strands and the extensive hydrogen bonding network.The presence of four characteristics specific for the integrin-type β-propellers and one characteristic specific to the β-propeller fold in general, appears to uniquely define the blades of the integrin-type β-propeller domain. Furthermore, these features demonstrate that the repeating unit is an extensively stabilized structural motif, defined by sequence and structural features, which include the FG-GAP/Cage sequence motif forming two interlocked β-turns, the Ca2+-binding site and the consensus repeat that includes the FG-GAP/Cage sequence. As the result, 1093 sequences were identified, of which 473 are eukaryotic sequences and 620 are bacterial sequences. Among the 1093 sequences, 9 eukaryotic and 58 bacterial ones were redundant or annotated as “obsolete” by the UniProtKB protein database (http://www.uniprot.org). The remaining 464 eukaryotic sequences and 562 bacterial sequences are given in the supplementary material section as two separate fasta files, eukaryote_464_init_record.fas and bacterial_562_init_record.fas, for eukaryotic and bacterial sequences respectively. The taxonomic groups and the numbers of identified sequences are shown in Rhodobacteriales HTCC 2654 where there are 4 sequence entries, each with 14 repeats. Nitrococcus oceani ATCC 19707 has two sequence entries with seven repeats; one representative sequence, Q3JAB2_NITOC, is present in the alignment of Rhodobacteriales HTCC 2654 entries and the sequence from Synechococcus elongatus PCC 7942 (Q31NK2_SYNP7), is presented in the Supplementary Material.For the purposes of this study, we established extremely restrictive criteria in order to identify bacterial sequences that are most similar to the human integrin β-propeller domain. First, we extracted all sequences matching at least one copy of the signatures for the human integrin-type β-propeller domain using Pfam (consensus sequence pfam01839) For the 5 sequence entries (seven sets of seven repeats), the individual secondary structure predictions and the consensus predicted secondary structure made using three different methods, PHD 2+-binding site exists and it is conserved in each of the bacterial sequences but, in contrast to the human integrin β-propeller domains, the signature is present in all 7 blades. This strongly suggests that the bacterial sequences form β-propeller domains, quite similar to the β-propeller domains of the human integrin α subunits, and that the Ca2+-binding motif is exploited even more frequently than in the integrins to form one of the two anchors that stabilizes each blade of the β-propeller. This in itself suggests that the bacterial sequences might form a more regular, disk-like three-dimensional than those of the human integrins. It also would be consistent with the idea of seven tandem repeats arising first in bacteria and then later being adapted for use in the integrins with a loss of some Ca2+ binding sites.Conserved residues in the bacterial sequences, labeled “Bact_Consensus” and computed for each individual blade, are shown in other 13 families of β-propeller fold proteins, but clearly display the sequence and implied structural features of the 7-bladed β-propeller domains of the integrins. The similarities are striking and suggest a common origin of sequences derived from an approximately 60-residue repeat unit. In comparison to human integrins, these bacterial sequences have retained more common features within each repeat, i.e. a complete set of seven Ca2+-binding sequences and more consistent lengths of the loop regions, which is consistent with the notion of the bacterial sequences still retaining features of an ancestral form of the β-propeller domain that was later exploited in the integrin α subunits apparently arising early in or prior to the origins of multicellular organisms.The analysis reported here demonstrates that the bacterial sequences do not share the features of the One can not help but ask what possible functions the integrin-like β-propeller domains have in bacteria. In the integrins the β-propeller domains interact with the βA-like domain of the integrin β-subunit. Ligands bind either to this complex  2+ may play a stabilizing structural role and Ca2+ levels are high outside of cells, thus the sites should always be occupied. Within cells, Ca2+ is generally at very low concentrations, thus giving it a unique role as a secondary messenger in signaling. In bacteria, calcium plays an increasingly recognized role in signaling 2+-binding motifs, sometimes duplicated in the same sequence, and it likely these sites are functional, but what role they might play in bacteria is unclear at this time. The high similarity between the bacterial domains and metazoan integrins and presence of the key features required for the structure, strongly suggest that the presence of this domain in modern bacteria belies the origin of β-propellers in the integrins. A key question concerns the basis for the apparently different functions in bacteria to those arising in the integrins in multicellular organisms.For the bacterial proteins any functional role would be limited to the cytoplasm. In integrin β-propeller domains Cahttp://www.ncbi.nlm.nih.gov/sites/genome), and nine others that include C. owczarzaki and T. trahens  Integrins are present in species that represent the earliest metazoans. We have made a comprehensive search for integrin-type β-propeller domains from sequences of unicellular eukaryotes, including those submitted to sequence and protein databases as well as those that are located with current genome-sequencing projects. There are 47 on-going genome projects of eukaryotic unicellular organisms with identified genomic sequences at different stages, from which there are 38 projects where protein sequences have been deposited  has three FG-GAP repeatsand the sequence record we obtained from the Broad Institute “Origin of Multicellularity” project did not have the transmembrane sequence. However, the sequences from Capsaspora have three repeats, a predicted transmembrane segment, and an adjacent KXGFFXR integrin motif. In contrast, sequence matches between true integrin β-propeller domains and domains observed in bacteria match all seven blades and the alignment is excellent throughout, albeit the latter examples additionally contain Ca2+-binding motifs in all seven blades. Aside from the sequences reported by Sebé-Pedrós et al. no clear sequentially-repeated FG-GAP motifs were detected within the 47 genomes The integrin α subunit-like sequence from Ectocarpus siliculosus is a multicellular brown algae and phylogenetic studies place this species among the heterokonts (stramenophiles), which are eukaryotes that also include a large number of unicellular diatoms, and whose origin of multicellularity occurred independently from the metazoans Ectocarpus has identified several “integrin-like” sequences 2+-binding motifs within Ectocarpus align to the 4 motifs found in the human αV subunit. Differences, however, appear towards the C-terminus: there is a glycine and alanine-rich low complexity region in the Ectocarpus protein, followed by an alanine and proline-rich region “matched” to the transmembrane segment of the αV subunit; the adjacent cytoplasmic KXGFFXR motif found in αV is not present in Ectocarpus, but this motif is also absent in some integrin α subunits, too.2+-binding sites in the corresponding blades, and there are strong hints of both α-like and β-like integrin subunits in the heterokont Ectocarpus. The current scope of genomic sequence data is obviously sparse and incomplete. Nevertheless, these observations do raise some fundamental questions with regard to the origin and evolution of integrins and their role in the origin of multicellularity, suggesting that a common ancestor of both multicellular lines contained some if not all of the features of the integrin α and β subunits, including integrin-like β-propeller domains and βA domains. The observation of complete and highly-conserved integrin-type β-propeller domains in bacteria, described here, suggest that the origin of domains in integrins are indeed prokaryotic, giving rise to the components of the present-day integrin subunits. However the link between having individual domains in prokaryotes and their functions, and their integration into integrin subunits in multicellular organisms remains obscure. In metazoan integrins, the β-propeller domain of the α subunit is directly or indirectly (via the inserted A domain) involved in binding external ligands, but it is always involved in binding the βI-like domain of the β subunit. The α subunit protrudes from the exterior membrane surface where Ca2+ levels are typically much higher than in the cytoplasm; the highly-conserved calcium-binding sites of the β-propeller and their key structural role near the ligand and subunit-subunit binding sites explain why the formation of the integrin αβ heterodimer capable of binding a specific ligand is calcium-dependent. Although the function and cellular location of the β-propeller domains in bacteria is currently unknown, if these domains are confined to the cytoplasm, then perhaps they have a role related to calcium signaling or storage. Clearly, further genome sequencing combined with experimental studies aimed at establishing a functional role for these integrin-type domains in non-integrin sequences is needed in order to elucidate the linkage the establishment of the present-day integrin subunits from the putative origin in single-cell organisms.Thus, in two independent lines of multicellular organisms, metazoans and heterokonts, the β-propeller is conserved to the point of having Cahttp://www.uniprot.org/) and the NCBI sequence database (http://www.ncbi.nlm.nih.gov/) were used as the initial sources of protein sequence and functional information. These two databases, particularly the UniProt database, are also widely used as sources of sequence data by structural databases and motif and pattern analysis computer programs, such as the Pfam (http://pfam.janelia.org/) http://www.rcsb.org) http://scop.mrc-lmb.cam.ac.uk/scop/) http://weblogo.berkeley.edu/) The UniProt database . Next, among the 562 bacterial sequences, we have selected 229 sequences that contain seven or more consensus repeat signature sequences . Then, from the 229 identified sequences we identified 35 sequences from 21 different bacteria that contained seven full-length segments able to incorporate the structure-based motif for blades of the human integrin-type β-propeller domain (see Section: Search for the consensus repeat motif in bacteria). The 35 sequences were then scrutinized in order to identify and confirm the presence of the consensus FG-GAP/Cage motif in each of the seven repeat signatures . This led to nine sequences from five different bacterial species, which have seven consensus repeat motifs, similar to the β-propeller domains in human integrin α subunits . These fFigure S1Alignment of nine sequences from five different bacterial species, which have seven full-length consensus repeat motifs, similar to those found in the β-propeller domains from the human integrin α subunits. For the nine sequences, the predicted secondary structure by three different methods, PHD, PSIPRED and PROF, coincided with the secondary structure of known human integrins.(TIF)Click here for additional data file.Table S12+-binding motif within each of the seven blades of β-propeller domains of the human integrin α subunits.Localization of the FG-GAP/Cage motif and the Ca(DOC)Click here for additional data file.


Gene duplicates have been shown to evolve at different rates. Here we further investigate the mechanism and functional underpinning of this phenomenon by assessing asymmetric evolution specifically within functional domains of gene duplicates.Based on duplicate genes in five teleost fishes resulting from a whole genome duplication event, we first show that a Fisher Exact test based approach to detect asymmetry is more sensitive than the previously used Likelihood Ratio test. Using our Fisher Exact test, we found that the evolutionary rate asymmetry in the overall protein is largely explained by the asymmetric evolution within specific protein domains. Moreover, among cases of asymmetrically evolving domains, for the gene copy containing a fast evolving domain, the non-synonymous substitutions often cluster within the fast evolving domain. We found that rare substitutions were preferred within asymmetrically evolving domains suggestive of functional divergence. While overall ~32 % of the domains tested were found to be evolving asymmetrically, certain protein domains such as the Tyrosine and Ser/Thr Kinase domains had a much greater prevalence of asymmetric evolution. Finally, based on the spatial expression of Zebra fish duplicate proteins during development, we found that protein pairs containing asymmetrically evolving domains had a greater divergence in gene expression as compared to the duplicate proteins that did not exhibit asymmetric evolution.Taken together, our results suggest that the previously observed asymmetry in the overall duplicate protein evolution is largely due to divergence of specific domains of the protein, and coincides with divergence in spatial expression domains. In the case of SF asymmetric evolution may not be apparent at the whole-protein level because the two copies would include a different fast evolving functional domain. However, an increased evolutionary rate may be due to a relaxed purifying selection or a positive selection on a few residues; these two possibilities cannot always be distinguished based on evolutionary rate alone.Gene duplication plays a critical role in driving evolutionary diversity by supplying large, functional, and redundant DNA sequences as the raw material for evolution. In proposing a model to describe the possible fates of duplicated genes, Ohno postulated that the redundancy created by duplication results in a reduced selective constraint that allows a redundant locus to accumulate mutations, which may either result in its tion (NF). A thirdfunction . A duplidomains which contribute to various catalytic and interaction functions. The domains are intervened by variable non-domain regions which largely contribute to the structure of the protein [SF, they may remain undetected at the overall protein level as the opposing signals of asymmetry within these domains would cancel out. Third, a domain-centric analysis of asymmetry uniquely enables biological interpretation via functional investigation of the asymmetrically evolving domains.Asymmetric sequence evolution of gene duplicates has been observed in several prior studies. Conant and Wagner found 20-30 % of duplicated gene pairs to be evolving asymmetrically in yeast, fly and nematode . Another protein . BecauseNF as the prevalent mechanism underlying diversification of the gene duplicates, also suggested by some of the previous studies [Danio rerio spatio-temporal gene expression [Here we report a large scale analysis of asymmetric evolution of gene duplicates in five teleost fish genomes . These d studies -5. Lastlpression , we founω on the two fish lineages explains the data significantly better than the constrained model where both fish lineages have an identical ω. Using a FDR threshold of 10 %, LRT supported asymmetry in <10 % of the duplicate pairs for each fish species  (see Methods), whether unconstrained To specifically evaluate the difference between the two branches leading to the two fish duplicates, we devised the FET approach (see Methods) that directly assesses the difference in non-synonymous changes in the two branches using synonymous changes as the comparison group. FET has been previously used to test for neutral evolution along a branch by comparing the ratio of non-synonymous to synonymous substitutions along the specific branch to the ratio of overall non-synonymous to overall synonymous sites in the sequence . Interesevolver program of the PAML package [First, we assessed the false positive rate of the FET approach via simulation using the  package  for the Secondly, since PAML does not report error estimates for the predicted dS and dN values and both FET and LRT analyses treat these estimates as is, which may adversely affect the robustness of the inference of asymmetry. Therefore we assessed the robustness of the FET approach using bootstrapping. For all asymmetrically evolving protein duplicates, we sampled codons randomly with replacement from the aligned proteins to form randomized sequences of the same original length, and repeated the FET analysis on 100 such randomized set. All asymmetrically evolving proteins manifested significant asymmetry in 80 % of the randomized cases on average (FDR = 10 %). At the much higher stringent FDR of 0.01 %, the bootstrapping support increased to ~90 %. Thus, the FET analysis for detection of asymmetry is relatively sensitive and robust. As a compromise between maintaining a low false positive rate while still detecting enough cases of asymmetry for meaningful analysis, we chose to use FDR of 10 % for all further analysis.In addition, we found that the non-synonymous substitutions in each of the two fish gene copies relative to the mouse ortholog occur in different, non-interleaved, regions of the protein. In other words, the positions of the ancestral protein that is uniquely mutated in exactly one of the gene copies, tend to form contiguous runs and do not interleave with each other . This is contrasted with analysis above, based on the whole proteins sequences, referred to as Whole Protein Analysis (WPA). To elucidate our findings, here we only discuss the results for multi-domain proteins. As shown in Table Next, we analyzed whether the widespread asymmetry detected above predominantly arises from the functional domain of the proteins, and whether more instances of asymmetric evolution may be detected by focusing exclusively on sequence variation in domains as opposed to the entire protein sequence. To do so, we excluded the regions of each protein that was not annotated as a Pfam domain (see Methods). This procedure resulted in 57 % reduction in sequence length on average. We repeated FET based analysis of asymmetry on the reduced sequences, which is a concatenation of all annotated domains. We refer to this analysis as the As shown in Figure Taken together, our results suggest that for vast majority of the proteins evolving asymmetrically the overall signal of asymmetry is detectable when considering only the functional domains of the protein.Domain Specific Analysis (DSA). As shown in Table OL PRKAG2  gene duplicate pair (ENSORLG00000003934 and ENSORLG00000016783) that comprises of three CBS domains (named after cystathionine β-synthase). The CBS domains regulate the activity of associated enzymatic and transporter domains in response to binding molecules with adenosyl groups such as AMP and ATP, or s-adenosylmethionine [CBS domain is evolving asymmetrically faster in ENSORLG00000003934  while another of the CBS domains was evolving faster in ENSORLG00000016783 . Hence, the asymmetric signals in these two domains, when combined, oppose one another and remain undetected by CDA. As an example of reduced signal-to-noise in CDA, for the OL YES1  gene duplicate pair (ENSORLG00000017875 and ENSORLG00000011192) which comprises of three domains: SH3_1SH2 (Src Homology 2) and Pkinase_Tyr (Tyrosine kinase), DSA found the Pkinase_Tyr domain in ENSORLG00000011192 to be evolving faster . Tyrosine kinases are a subgroup of the larger class of protein kinases and they phosphorylate proteins and serve to carry out the crucial function of signal transduction and regulation of cellular activity [SH3_1 and SH2 function as helper domains that aids in the protein’s interaction with other proteins [Protein domains provide functional modularity, and it is possible that functional divergence between duplicate genes exploits this modularity. For instance, it was previously observed that the functional divergence of transcription factor gene duplicates in terms of their DNA binding motifs (which is directly encoded by the DNA binding domain) inversely relates to their expression divergence , underscthionine . By perfactivity . While SNext we tested whether asymmetrically evolving domains assort among different multi-domain proteins, or alternatively, concentrated within a few multi-domain proteins. We found that on average the number of multi-domain proteins with exactly one asymmetrically evolving domain is two-fold greater than expected by random assortment. In other words, in the asymmetrically evolving proteins, there is often one specific domain contributing to the asymmetry. This suggests that the asymmetry in the rate of evolution of gene duplicates can be largely attributed to the asymmetric evolution of a specific protein domain. However, there are a few cases  where multiple domains evolve asymmetrically.NF model, one of the gene copies evolves an entirely new function while the other copy retains the ancestral original function. According to SF model, both copies diversify, via complementary degenerative mutations, to retain disjoint subsets of the original functions [SF-NF models have been proposed. Although, evolutionary rate alone is not sufficient to make inferences of NF and SF, our finding is more consistent with NF of one of the duplicates, in line with previous studies [An asymmetrically evolving domain is evolving faster in one of the gene copies; we call this copy the faster evolving copy of the domain. In a gene pair with multiple asymmetrically evolving domains, we investigated the assortment of faster evolving domain copies among the two gene copies. In other words, we assessed whether the faster evolving copies of different domains largely belong to the same gene copy or are assorted evenly between the two gene copies. Based on the few cases, we found that in most instances  all the faster evolving domains belonged to the same copy . We found that most often the non-synonymous changes are clustered within a few of the domains of a protein Table . MoreoveIn our DSA, 353 of the total 1113 protein domain pairs (~32 %) were found to evolve asymmetrically . However, there is large variability among different types of domains in their tendency to evolve asymmetrically. We computed for each domain, among all instances of the domain for all five fish species, the fraction of cases it was deemed to evolve asymmetrically by the DSA  with DSA, 14 had expression localization data for at least one developmental stage in ZFIN for both copies. For the remaining 57 pairs that did not show asymmetry in any of their domains, 11 had expression localization data for at least one developmental stage in ZFIN for both copies. We computed for each such pair, the overlap (see Methods) between the expression domains. We found the asymmetrically evolving duplicates to have significantly less overlap   whereas atf7a is restricted to the notochord during segmentation [Having identified the duplicated genes that show significant asymmetry in their evolutionary rates and having found that the asymmetric pairs carry substitutions likely to have a greater functional impact, we next sought to determine whether this is accompanied by differences in spatio-temporal expression of the two copies. ZFIN database  provides) Figure . A notabentation , consistDR duplicate gene pairs with available spatio-temporal expression data, we observed a significantly greater expression divergence for the asymmetrically evolving gene pairs as compared to the non-asymmetrically evolving gene pairs which suggests a possible functional manifestation of the rate variation either due to NF or SF, as has been shown previously [Thus, for the eviously -27.NF as the prevalent mechanism underlying diversification of the gene duplicates, also suggested by some of the previous studies [In this study we have carried out a large scale analysis of asymmetric evolution of gene duplicates in five teleost fish genomes . These g studies -5. LastlDanio rerio (DR) (615), Oryzias latipes (OL) (672), Gasterosteus aculeatus (GA) (775), Tetraodon nigroviridis (TN) (650) and Takifugu rubripes (TR) (702). The counts within the parenthesis are the number of gene duplicate pairs for each species. For each fish gene duplicates, we downloaded the corresponding Mouse orthologs from Ensembl v56. The gene orthology prediction in Ensembl has been generated by a pipeline that uses maximum likelihood phylogenetic gene trees that are reconciled with their species tree and annotated to distinguish duplication or speciation events [DR (407), OL (603), GA (692), TN (406) and TR (540).The paralogs in five teleost fish genomes that showed phylogenetic and syntenic support for origin by WGD were reported in . We downn events . We onlyWe identified the protein domain architecture using Pfam 24.0 . We onlybranch model[codeml program of PAML package [model = 1 which fits the free-ratios model to compute the rate of non-synonymous substitutions (dN), rate of synonymous substitutions (dS) and the ω ratio (dN/dS) separately for each branch of the tree. We only considered the duplicate pairs for which dS along each of the branches leading to the fish duplicate gene from their last common ancestor was reasonably large  and at the same time not saturated   Table  , (b) by constraining the two branches leading to the fish gene duplicates from the last common ancestor to have the same ω value (ω1 = ω2), while allowing other branches to vary freely (model = 2). The LRT statistic is calculated as: 2* |ln L1 – ln L2|, where L1 is the likelihood of the first model and L2 is the likelihood of the second model. We estimated the significance of improvement of fit by the first model over the second model using the chi-square test with one degree of freedom. We refer to this test as the LRT.We used two approaches to assess asymmetry in evolutionary rates of the gene duplicates. The first approach uses the Likelihood-ratio test (LRT) to compare the fit of two likelihood models: (a) by allowing the ω to vary among the two branches leading to the observed duplicated fish gene sequences from the last common ancestor (ω1 and ω2), as well as among other branches  and non-synonymous (N) substitutions along the branches leading to the fish gene duplicates from their last common ancestor. By taking the synonymous substitutions as the background, we then compared the non-synonymous substitution between the two branches using Fisher Exact test. We refer to this test as FET. Given a 2x2 contingency table, FET essentially compute the fraction of all configurations of the contingency table that have a more extreme difference in the ratio of non-synonymous changes and the ratio of synonymous changes in the two branches.The second approach to test asymmetry was based on Fisher Exact test. As described above using the Domain Specific Analysis and Combined Domain Analysis (see Results), we carried out the FET as described above except that we used the non-synonymous substitutions in the domain of interest as the foreground and the synonymous substitutions of the whole protein as the background.For testing asymmetry using the DR, GA, OL, TN and TR were estimated by running DNAMLK program of the PHYLIP package (http://www.phylip.com/) on the concatenated nucleotide sequences corresponding to all the orthologous Mouse proteins and two concatenated sequences corresponding to the two copies of the duplicated genes of the fish species. Based on synteny and/or phylogenetic information the fish duplicates were designated as copy-A and copy-B in [We estimated the branch lengths of the prototypical tree in Figure opy-B in  to indicopy-B in  to simulfree-ratios model of codeml as described above. We then used FET to compare N for a given domain with the sum of N for all the other domains of the protein, while using S in the domain and sum of S in other domains as the background, with the null hypothesis that every domain in the protein is an unbiased target of non-synonymous changes.For each duplicated protein with multiple domains, we computed N and S for every domain using DR genes from the ZFIN database [DR gene, we compiled all the stages of development for which expression data were available, along with the anatomical regions where expression was observed at any particular developmental stage. We excluded any stage which showed ubiquitous expression of the gene in the whole organism. We refer to these anatomical regions as expression domains. For all DR gene duplicate pairs that were detected as evolving asymmetrically by our Domain Specific Analysis (see Results), separately at each developmental stage, we computed the ratio of intersection and union of expression domains for the two paralogs. We repeated this analysis for all the non-asymmetrically evolving gene duplicates.We obtained all available spatio-temporal expression data for database . For eacWGD, Whole genome duplication; NF, Neofunctionalization; SF, Subfunctionalization; FET, Fisher’s exact test; LRT, Likelihood-ratio test.SH conceived the study. SH and MK designed the experiments. MK carried out the experiments and analyzed the data. MK and SH wrote the paper. Both authors read and approved the final manuscript.Table S1. Number and percentage of paralogs deemed to be asymmetrically evolving (FDR = 5 %) based on the whole protein and using Fisher Exact test (FET). Table S2. Number and percentage of paralogs deemed to be asymmetrically evolving (FDR = 0.01 %) based on the whole protein and using Fisher Exact test (FET). Table S3. Fisher exact test based analysis of asymmetrically evolving duplicate gene pairs using sampled codons to create artificial domains. Table S4. Number and percentage of paralogs deemed to be asymmetrically evolving (FDR = 10 %) based on the non-domain linker regions using Fisher Exact test (FET). Table S5. Duplicate gene pairs that contained multiple asymmetrically evolving domains categorized based on whether all the faster domains were in the same copy (Category 1) or distributed between the two copies (Category 2). Table S6. Frequency of occurrence of each of the protein domains and the fraction of times they were detected to be evolving asymmetrically . Supplementary Results. Differing regions of the gene duplicates are targeted for non-synonymous substitutions. Click here for file


Cells are usually surrounded by the extracellular matrix (ECM), and adhesion of the cells to the ECM is a key step in their migration through tissues. Integrins are important receptors for the ECM and form structures called focal adhesions (FAs). Formation and disassembly of FAs are regulated dynamically during cell migration. Adhesion to the ECM has been studied mainly using cells cultured on an ECM-coated substratum, where the rate of cell migration is determined by the turnover of FAs. However, the molecular events underlying the disassembly of FAs are less well understood. We have recently identified both a new regulator of this disassembly process and its interaction partners. Here, we summarize our understanding of FA disassembly by focusing on the proteins implicated in this process. Both subunits are type I transmembrane proteins containing both a large extracellular domain responsible for binding to ECM ligands and a cytoplasmic portion (CP) that recruits multiple intracellular proteins. Eighteen different α- and 8 β-subunits have been characterized in mammals, and 24 distinct integrin heterodimers have so far been identified .–13.11–13 the ECM –18. This the ECM –23. In p the ECM , 24, 25. the ECM . Thus, b the ECM , 32.The process of cell adhesion to the ECM has been studied by seeding cells onto an ECM-coated substratum in culture , 34. Theβ-subunit of integrin, whereas the rod domain contains multiple binding sites for adhesome proteins, including one for the CP of β-integrin, two sites for actin, and multiple sites for vinculin. In addition, talin forms a dimer through its carboxy-terminal helix and thus serves as a core platform to expand intracellular structural frameworks mediated by protein-protein interactions. The binding of talin to integrin stabilizes the ligand-induced clustering of the latter at an initial step of FA formation by mediating crosslinking of integrins with filamentous actin (F-actin) and F-actin-binding proteins such as vinculin and α-actinin . PIN1 stimulates the binding of FAK to PTP-PEST, in a fashion dependent upon the isomerase activity of PIN1, although the exact role of the isomerase activity is not clear. PTP-PEST then dephosphorylates pTyr397 [397 by Phe promotes metastasis of v-H-Ras-transformed rat fibroblasts.PTP-PEST is known to regulate cell adhesion and migration  76]. As. As76]. d signal , 78. Ras pTyr397 . Intrigu397 [SHP-2 can also dephosphorylate FAK at Tyr397 . SHP-2 c397 . This in397 . Deficie397 . These fα-actinin [397 [α-actinin plays a key role in the dual functions of PTP-1B [α-Actinin phosphorylated at Tyr12 promotes dissociation of Src bound to FAK at pTyr397. This allows PTP-1B to dephosphorylate the exposed pTyr397. On the other hand, PTP-1B can dephosphorylate α-actinin pTyr12 so as to increase the α-actinin-free Src pool that is then available to phosphorylate FAK. At the same time, PTP-1B can activate Src by dephosphorylating Src pTyr527, which mediates intramolecular inhibition of Src activity. Overall, dephosphorylation of FAK by PTP-1B enhances subsequent phosphorylation of FAK by Src. These functions of PTP-1B may play roles in the dynamic turnover of FAs during dynamic cell attachment rather than simply by promoting detachment. There are several substrates for PTP-1B in FAs, including FAK, Src, and -actinin , 84. PTPnin [397 . As Zhanm-Calpain, also known as Calpain-2, is a member of the calpain family of intracellular calcium-dependent proteases . It comp m-Calpain has been shown to regulate the turnover of FAs by cleaving multiple FA-related proteins such as talin, FAK, and paxillin , 86–88. β-tubulin, m-Calpain, and SHP-2 [β-tubulin. Almost the entire ZF21 polypeptide chain is required for binding m-Calpain and SHP-2. Substitution of the FYVE domain of ZF21 with a corresponding domain derived from EEA1, another member of the FYVE domain-containing proteins, abolishes its ability to bind FAK and abrogates its ability to mediate MT-induced FA disassembly [ZF21 contains a FYVE domain, which binds to phosphatidylinositol-3-phosphate that is enriched in the lipid layers of plasma membranes. Although there are 38 FYVE domain-containing proteins in mammals, they do not necessarily have common domain structures or functions . ZF21 innd SHP-2 , 91, 94.397 and internalization of integrins [β-tubulin, may help stabilize the interaction of ZF21 with MTs and then ride on vesicles. The ability of ZF21 to bind SHP-2 and m-Calpain may facilitate the transport of the latter to FAs via vesicles loaded onto MTs  or are embedded within a 3-dimensional ECM (3D) , 96. Adv


A multi-interface domain is a domain that can shape multiple and distinctive binding sites to contact with many other domains, forming a hub in domain-domain interaction networks. The functions played by the multiple interfaces are usually different, but there is no strict bijection between the functions and interfaces as some subsets of the interfaces play the same function. This work applies graph theory and algorithms to discover fingerprints for the multiple interfaces of a domain and to establish associations between the interfaces and functions, based on a huge set of multi-interface proteins from PDB. We found that about 40% of proteins have the multi-interface property, however the involved multi-interface domains account for only a tiny fraction (1.8%) of the total number of domains. The interfaces of these domains are distinguishable in terms of their fingerprints, indicating the functional specificity of the multiple interfaces in a domain. Furthermore, we observed that both cooperative and distinctive structural patterns, which will be useful for protein engineering, exist in the multiple interfaces of a domain. A protein domain is usually a contiguous segment in a protein's primary sequence that can be independently folded to form a stable tertiary structure. Domains vary in length from about 25 amino acids to about 500 amino acids. The number of domains is huge—for example, there are 110,800 domains currently stored in the Structural Classification of Proteins (SCOP) database et al.Multi-interface domains can be found in the following situations: (i) One domain of a protein interacts with multiple other proteins at the same time. For example, as mentioned above, the catalytic domain of plasminogen can interact with three other plasmins simultaneously to shape three non-overlapping interfaces. (ii) The same domain of a protein interacts with other different proteins at different time or environments. For instance, an antigen peptide can interact with a major histocompatibility complex (MHC) molecule, while it can be also recognized by a T lymphocyte after being presented to the cell surface by an MHC molecule. This phenomenon is previously highlighted by Narayan e.g., protein-protein interaction, protein complex identification) e.g., domain-domain interaction, domain transitivity analysis) e.g., interface residue identification, hot spots prediction) The multiple interfaces in a domain can be grouped into subsets such that each of them share a unique biological function. These functions are usually distinguishable and non exchangeable. As an example shown in In this study, we address the following questions: (i) What kind of domains prefer the multi-interface property? That is, we want to know the distribution of domains that have multiple interfaces. (ii) What are the fingerprints of an interface, or a subset of interfaces, in a domain? That is, we want to discover unique structures in a domain that distinguish the multiple interfaces from each other. (iii) What are the relationships between the multiple interfaces in a domain? That is, we want to see whether the multiple interfaces in a domain have any cooperative or competitive relations. (iv) What are the associations between multiple interfaces and their molecular functions?Our study thus aims to unveil some facets of protein interaction mechanisms by looking at the multiple interfaces of a domain. This is new because past interface analysis http://sunim1.sce.ntu.edu.sg/~s080011/metp/index.html.To this end, we have compiled a representative data set of multi-interface domains from PDB Our data and method are outlined in We compile multi-interface proteins in the following four steps:Retrieve PPI (Protein-Protein Interaction) complexes from PDB;Preprocess PPI complexes by eliminating transformed chains and short chains;Cluster protein chains by sequence similarity;Identify representative multi-interface proteins from each protein cluster.We retrieve those PDB complexes produced by X-Ray crystallography that satisfy the following criteria: (i) Their macromolecule type is protein but not DNA or RNA. We exclude DNA/RNA because the difference between protein-protein binding and protein-DNA/RNA binding may cause confusion in defining multi-interface proteins. (ii) The number of protein chains within each biological unit in one complex is bigger than 1. (iii) The chain length is larger than or equal to 30. (iv) Their X-ray resolution is better than 3.0 Å. Using these selection criteria, 35,760 PDB entries containing 109,672 protein chains are obtained.A few chains in the PDB complexes have transformed coordinates . Hence the structural relation within these chains or between these chains and the other chains in the same complex may not be correctly represented by their original coordinates. We thus remove those protein chains with a non-identity transformation matrix to clean the noise in the final data set. For example, there are two chains (A and B) with transformed atom coordinates in biomolecule 2 of PDB entry 3HZN, which contains a total of four chains ; thus the interaction between chain A and chain D is incorrect without coordinates transformation. Besides excluding transformed chains, those protein chains with less than 30 amino acids are also removed from each PDB complex. With the removal of transformed chains and short chains, some chains do not have interaction partner anymore. These chains or complexes are further eliminated from the data set. Finally, a total of 24,664 PDB entries with 87,395 protein chains are used for analysis.i.e., each connected component forms a cluster. Sequence similarity The same protein chain interacting with different protein chains can be included in different PDB entries. Therefore, different instances of each chain have to be clustered together to identify multiple interfaces. We cluster similar protein chains by the following steps: (i) For each chain in the compiled data set containing 87,395 protein chains, we search the other 87,394 chains using BLAST i.e., all the chains in a cluster share a similar interface.For the 11,681 clusters, we first identify the interface residues for each chain of every cluster. Interface residues in the surface of a chain are determined by using a Euclidian distance of 5 Åwhich is commonly used to determine inter-chain contacts To explore which domains have multiple interfaces as well as their distributions in PDB, we aggregate all these 5,222 multi-interface proteins according to their structural annotations.Protein structural annotations are obtained through following steps. First we directly retrieve each multi-interface protein's structural annotations from SCOP i.e., class, fold, superfamily, family, and domain, according to their annotations.Based on structural annotations, multi-interface proteins are further aggregated into several groups in accordance with SCOP classification, as per the following steps: (i) Align each multi-interface protein sequence to its target domain sequence. (ii) Categorize each interface to a domain by the interface residues' position and domain range. If the entire set of interface residues fall into one domain for a given interface then it is annotated by that domain identifier; otherwise, multiple domain identifiers are tagged to that interface. (iii) Aggregate multi-interface proteins into clusters at different SCOP classification levels, Interface analysis is carried out on their fingerprints, where each fingerprint is represented by closed frequent interface residue contacting graph. Each interface in the 5,222 multi-interface proteins is represented as a graph Since every interface is represented by a graph, all interfaces in a domain form a graph database. We are interested in closed frequent subgraphs, paired cooperative subgraph sets and distinctive subgraph sets between interfaces to uncover fingerprints for interfaces and to identify relations between multiple interfaces of one domain.We introduce some additional notations. A graph Closed frequent subgraphs of one interface cluster, which are deemed as fingerprints of one interface, are mined from an interface graph data base, where the graph database is a set of interface residue contacting graphs in one domain. Closed frequent subgraphs instead of frequent subgraphs are mined since we aim to figure out the largest structures that can be used to identify a specific interface for a given domain. To explore fingerprints of each interface, we first align all protein's structures together by the CE algorithm Interface relation in one domain is described by paired cooperative graph sets and distinctive graph sets. Paired cooperative graph sets between two different interfaces in a domain are identified using the following steps: (i) Build graph database for each set of interfaces. (ii) Mine closed frequent subgraphs by ParMol In this section, we present results to show the distributions of multi-interface proteins and multi-interface domains, fingerprints of interfaces, cooperative and distinctive relations between multiple interfaces, associations between interfaces and molecular functions, and some properties of cross-domain interfaces.i.e., 3 interfaces each on average. We note that the number of multi-interface proteins differs with regard to the change of interface similarity threshold due to promiscuity of interface The 87,395 protein chains are grouped into 13,295 clusters according to their sequence similarities generated by BLAST p-value of this number of isomorphic fingerprints against randomly generated graph pairs is 6.7e-4. This shows that sharing of interface patterns between homo-oligomers and hetero-complexes is significantly more frequent than expected by chance. Due to a lack of homo-complex and hetero-oligomer interactions in multi-interface proteins, we cannot get reasonable results from these two types of interactions.Interfaces between proteins can be categorized into homo-oligomer, homo-complex, hetero-oligomer and hetero-complex in terms of sequence similarity and interaction lifetime The top ten multi-interface domains with the largest numbers of proteins are shown in Since there are as many as 1,730 multi-interface domains—see Given a set of multiple interfaces in a domain, we fish out interface-specific fingerprints by the mining of closed frequent subgraphs (substructures) from the corresponding interface graph database. These frequent substructures capture the natural organizations of interface residues. In the past, frequent sub-structures have been successfully applied to study protein structure and function Our experiments on identifying interface fingerprints are carried out on Ig VH domain and proteasome beta subunit domain separately. Generally, we obtained a great number of non-trivial closed frequent substructures for each interface of the two domains. Full results are provided in Supplement Closed frequent substructures characterize the common organization of interfaces in a domain. However, they cannot reveal the relations between multiple interfaces in that domain. In addition, one domain is a perfectly assembled structure constituted by all kinds of residues. It is believed that protein structures are not randomly assembled together and they should incorporate some cooperative or competitive relations Co-existing paired fingerprints somehow could reveal reenforcement of interface residues from a physicochemical perspective which could help wet-lab experiments. Our experimental results reveal that a large number of co-existing fingerprints of different interfaces exist both in Ig VH domain and proeasome beta subunit domain. The complete co-existing paired fingerprints of this two domains are presented in supplement Unique fingerprints of each interface are the signatures that distinguish one interface from the other interfaces in the same domain. Observations show that, besides cooperative fingerprints, a large number of fingerprints are interface-specific as shown in p-values before and after the removal of overlapping residues implies a little influence of the overlapping residues, but the very slight change indicates that cooperative fingerprints are not caused by overlapping, as shown in Overlapping residues between interfaces distort the study of co-existing paired fingerprints and common fingerprints between interfaces. Thus we further investigated the influence of overlapping, measured by Jaccard index, between multiple interfaces. Our experimental result on Ig VH domain shows that overlapping between antigen binding interface and protein binding interface is 0.04Co-existing paired fingerprints and distinctive fingerprints shown in our data do reveal that interface is distinguishable and cooperates with each other to some extent in the same domain.The organization of interface residues determines its capable binding partners, which further specifies its associated molecular function. Here, we conduct case studies to examine the existence of association between multiple interfaces and their biological functions. We take the following two domains as examples: Ig VH domain and the proteasome beta subunit domain.Ig VH domain has, as annotated by GO Based on the above observations, we can see that large numbers of unique fingerprints exist in the specific interfaces of Ig VH domain and those of the proteasome beta subunit domain. It suggests that the unique fingerprints of the interfaces in these two domains can be used to determine their biological functions. This observation is interesting, however, it is concluded just based on the two case studies. It does not cover some other situations, including different domains with the same function and the same domain with more than one functions. Thoroughly exploring the association between interfaces and their functions under various situations is difficult and time costly. One important reason is that the correlation between the interfaces and functions is not a bijection. For example, an antigen can have multiple epitopes binding to different antibodies although the same function is annotated. Therefore, more efforts and data are needed to annotate a function to an interface. Another important reason is as follows. For each domain of a protein, those proteins containing the same domain are obtained by searching the whole PDB, and then the interfaces of this domain are determined based on the structural information. This is followed by identifying different interfaces and retrieving function annotations for this domain. Subsequently, functions are mapped to interfaces by using physicochemical information. Since the number of domains is huge  and multiple binding partners are possible, the process of mapping functions to interfaces is very time costly and laborious. Because of these limitations and difficulties, statistically reliable association between interfaces and specific functions of a multi-interface domain will be one of our future works to extend the current study.p-value of graph label-assortativity (residue type) and graph degree-assortativity of the fingerprints from the Ig VL-kappa domain and Ig VH domain. The We have identified interface fingerprints and analyzed their similarities between interfaces within a domain. But it is still unknown whether these fingerprints are domain-specific or not for multi-interface domains. To address this issue, we take a small trick of comparing the similarity of fingerprints of two very similar domains in the same protein family. The assumption is that if the similarity is low for the two very close domains, then the similarity should be much lower for two randomly selected domains. Based on this assumption, we analyzed the fingerprints similarity between the Ig VH domain and Ig VL kappa domain which have similar number of multi-interface proteins, and both belong to the V-set domain family. We employ graph assortativity to measure the similarity between different sets of fingerprints. Assortativity is a preferred metric to quantify the equivalence of a network's nodes and connections in graph theories. Assortativity between fingerprints of this two domains is calculated using NetworkX However, difference between the fingerprints of two domains could be induced by the fingerprint topology or the number of fingerprints with their combinations. Therefore, we conducted additional experiments to understand the influence of fingerprint topology and fingerprint volume on analyzing fingerprints' domain-specificity by exploring the difference within randomly generated fingerprints and by examining disparity between subsets of fingerprints of the two domains. To explore the effect of fingerprint topology on this domain-specificity, we randomly generated two sets of fingerprints with one having an equal number of fingerprints to that of Ig VL-kappa domain and the other having the same number as that of Ig VH domain. The In protein-protein interacting complexes, most of their interfaces are located within one single domain. But there are still a few interfaces that spread over other domains; these are named cross-domain interfaces in this study. Our results show that among the 2,517 multi-interface proteins with SCOP annotations, 301 proteins contain cross-domain interfaces. The detailed result is shown in supplement lass see  with a vlass see , but theMulti-interface domains have been demonstrated to have multiple non-exchangeable interfaces in every domain. In particular, this work has conducted comprehensive analysis on the following aspects of multi-interface domains: (i) which domains have multiple interfaces; (ii) what the fingerprints of the multiple interfaces are; (iii) the relations of the multi-interfaces in a domain; (iv) the associations between multi-interface and their molecular functions, and (v) profiles of cross-domain multi-interfaces. Our data is a set of 5,222 multi-interface proteins obtained from 35,760 PDB entries. Interface geometric information, graph theories, closed frequent item set mining, and association mining techniques are utilized together to reveal interface signatures, associations between multiple interfaces in a domain, and relation between interface and its molecular function. Based on our systematic analysis, we found that around 40 percent of proteins have multiple interfaces which are distributed to a very small set of domains over all available domains, and that the multiple interfaces in one domain can have the same or different function types. We observed that the multiple interfaces of these domains were distinguishable in terms of their fingerprints, which further indicated the function-specific property of these interfaces in a domain. Moreover, we observed both unique and co-existing structural patterns existing between multiple interfaces of one domain, highlighting the distinctive and cooperative relations between multiple interfaces. The number of multi-interface domain is still very large although it accounts for a very small portion in the entire number of domains. Therefore, analysis is undertaken on other selected domains. Future works include building interface-function association database to facilitate a lower level analysis and to relate specific multi-interface domains to real-life applications, for example, multiple interface predictions in antigen-antibody interactions.Data S1Fingerprints of interfaces of Ig VH domain and proteasome beta subunit domain.(ZIP)Click here for additional data file.Data S2Co-existing paired fingerprints between interfaces of Ig VH domain, and cooperative fingerprints between interfaces of proteasome beta subunit domain.(TXT)Click here for additional data file.Data S3Function-type specific interfaces for Ig VH domain and proteasome beta subunit domain.(ZIP)Click here for additional data file.Data S4Cross-domain multi-interfaces in our data.(TXT)Click here for additional data file.


WASP family proteins stimulate the actin-nucleating activity of the ARP2/3 complex. They include members of the well-known WASP and WAVE/Scar proteins, and the recently identified WASH and WHAMM proteins. WASP family proteins contain family specific N-terminal domains followed by proline-rich regions and C-terminal VCA domains that harbour the ARP2/3-activating regions.To reveal the evolution of ARP2/3 activation by WASP family proteins we performed a "holistic" analysis by manually assembling and annotating all homologs in most of the eukaryotic genomes available. We have identified two new families: the WAML proteins (WASP and MIM like), which combine the membrane-deforming and actin bundling functions of the IMD domains with the ARP2/3-activating VCA regions, and the WAWH protein (WASP without WH1 domain) that have been identified in amoebae, Apusozoa, and the anole lizard. Surprisingly, with one exception we did not identify any alternative splice forms for WASP family proteins, which is in strong contrast to other actin-binding proteins like Ena/VASP, MIM, or NHS proteins that share domains with WASP proteins.http://www.cymobase.org.Our analysis showed that the last common ancestor of the eukaryotes must have contained a homolog of WASP, WAVE, and WASH. Specific families have subsequently been lost in many taxa like the WASPs in plants, algae, Stramenopiles, and Euglenozoa, and the WASH proteins in fungi. The WHAMM proteins are metazoa specific and have most probably been invented by the Eumetazoa. The diversity of WASP family proteins has strongly been increased by many species- and taxon-specific gene duplications and multimerisations. All data is freely accessible via  WASP homology 2 domain, also known as verprolin homology domain), a central domain , and an acidic (A) C-terminal domain. While the WH2 domains bind G-actin the CA domains bind to and activate the ARP2/3 complex.Eukaryotes mediate many cellular processes, including phagocytosis, intracellular trafficking, cell division, and cell locomotion, by remodelling of the actin cytoskeleton -4. In maDictyostelium discoideum [Dictyostelium and the plant homologs, while WAVE has been used for all metazoan family members.The founding member of the WASP family was the WASP protein, which is deficient in Wiskott-Aldrich syndrome. The Wiskott-Aldrich syndrome is an X-linked human genetic disorder that leads to a variety of defects in the immune system, including thrombocytopenia, compromised immune function, and susceptibility to leukemias and lymphomas -11. In ascoideum . At the scoideum . The namWASP proteins are multi-domain proteins consisting of an N-terminal WH1 domain, a basic domain containing many lysine and arginine residues, a GTPase binding domain (GBD) consisting of a CRIB motif (for Cdc42/Rac interactive binding) followed by an autoinhibitory domain, a poly-proline region, and the VCA domain. The WASP protein by itself is inactive through intramolecular binding of the C domain to the autoinhibitory domain . BindingIn the last years, several further proteins have been identified that also activate the ARP2/3 complex like WASH (Wiskott-Aldrich syndrome protein and Scar homolog) , WHAMM , the WH1 domain, that is shared by the Ena/VASP protein family, the WH2 domain, that is contained for example in Spire, Cobl, missing-in-metastasis (MIM), and WIP, and the CA domains, that are shared for example by certain coronins and class-1 myosins. Given such short sequence motifs a few missing residues could prevent their identification and lead to a wrong classification or even removal from the dataset. Vice versa, the identification of just one or two of the domains contained in one of the WASP family proteins and subsequent thorough analysis of the genomic region could lead to the identification of so far unrecognized or very divergent members of the WASP family. While this subfamily categorization is mainly based on domain organisation patterns, the classification of the duplicated WASP family genes into subgroups is based on the phylogenetic analysis of the corresponding protein sequences. Thus, it is of major importance to obtain the best sequence data possible and to create the most accurate sequence alignment. We had to manually assemble and annotate all WASP protein family sequences used in this study mainly for two reasons. A) Automatic gene predictions are error-prone and even those gene predictions are only available for a small subset of all sequenced eukaryotic genomes . B) BecaThe WASP dataset contains 1021 sequences from 408 organisms (Table WASP autoinhibitory domain), a unique region consisting of many proline residues  and a VCA domain , a CRIB motif, a domain that we suggest to name WAID domain  and multiplications  but also two clade-specific duplications, one of which happened in the ancestor of the Mucoromycotina, and one at the onset of the vertebrates resulting in WASP and N-WASP. The duplication and subsequent subfunctionalization of the WASP homologs at the origin of the vertebrates is most probably the result of the two whole genome duplications (2R) that happened shortly after the emergence of the vertebrates [Orn S-WASP). Therefore, we suggest naming these WASP homologs S-WASP (short WASP). Similarly, some of the sequenced Basidiomycotes encode one or two further WASP homologs that do not encode a poly-proline rich region and a VCA domain. Although these short WASPs in fish and Basidiomycotes do not encode CA and VCA domains, respectively, that are the basis of ARP2/3-complex activation and therefore a requirement of WASP protein family membership, we would suggest to also group these proteins to the WASP family because of the strong sequence homology to the WH1 and CRIB/WAID domains of the long WASPs. Thus, they were most likely derived from WASP duplications followed by domain loss events. Trichomonas vaginalis encodes two special WASP homologs that have two (TvWASP_B) and three (TvWASP_A) tandem repeats of the poly-proline rich region and the VC domain but that miss the C-terminal acidic A domain . The tree shows that there have been many species-specific WASP duplications (e.g. in tebrates . WASP (btebrates . Some ofEctocarpus siliculosus encodes two WH2 (V) domains  The plant WAVE homologs do not contain poly-proline regions. Here, we could identify for the first time some plant-specific sequence motifs in the region between the basic and the VCA domain that we suggest to name WAM 1-4  A fifth mammalian specific class that contains mainly pseudogenes but some potentially coding transcripts . Most of the members are potential pseudogenes because they are encoded by single exons, contain in-frame stop codons and frame-shifts, and sometimes miss stop-codons and starting methionines. Thus, there are more genetic disablements than can be attributed to sequencing and assembly errors. The class-5 WAVE homologs of Rattus norvegicus, Oryctolagus cuniculus, Otolemur garnetii, and Dasypus novemcinctus do not contain reading-frame interrupting mutations and might therefore present potentially expressed transcripts although they are all encoded by a single exon. The rat WAVE5A is the only class-5 WAVE supported by cDNA data. The mouse paralog WAVE5A, however, contains an in-frame stop codon.Because many species encode more than one WAVE homolog we sub-grouped the WAVE proteins based on a phylogenetic tree calculated from concatenated multiple sequence alignments of the WHD and VCA domains Figure . The plas Figure . Most maDictyostelium fasciculatum and Acytostelium subglobosum, and the Rhizaria Bigelowiella natans that encode two WASH homologs as result of species-specific gene duplications. In addition, several mammals, and especially primates, contain one or many WASH pseudogenes that are characterised by consisting of non-functional single exons because of frame-shifts, in-frame stop-codons, missing terminal stop-codons, and missing conserved sequence [Trypanosoma species WASH proteins, which miss the WH2 domain, and the Stramenopiles WASH proteins that encode two VCA domains arranged in tandem  domain.Vertebrates and almost all other species analysed contain just one single functional WASH homolog as compared to the multiple homologs of WASP and WAVE proteins. The only exceptions so far are the amoebae sequence . These psequence ) in analm Figure . Through studies . Thus, wThe first member of this protein family, which has been shown to function as an actin nucleation promoting factor, has been named WHAMM . SubsequWHAMM membrane interaction domain, Figure Previously, the N-terminal domain of WHAMM has been defined differently, sometimes marking the first 50 residues at the N-terminus , sometimClytia hemisphaerica, which is outside Bilaterians and thus extends a previously proposed origin of WHAMM homologs [Strongylocentrotus purpuratus has been proposed to contain a tandem N-terminal WMD and coiled-coil region [Strongylocentrotus genome is one of the worst assemblies available because of the high polymorphism between the two alleles. Therefore, not even the well-conserved myosin family proteins could unambiguously be annotated [We have also found a WHAMM homolog in the Hydrozoa species homologs . The WHAl region , but thinnotated .It has been reported initially  and subsDictyostelium discoideum, for which only homology to the GBD and VCA domains was indicated, we were long searching for potential WH1 domains upstream of the GBD domains, expecting even very low sequence similarity. However, we were not able to identify any WH1 domain, and when we analysed further amoebozoan genomes it became clear that we have identified a new type of the WASP protein family, that we suggest to call WAWH (WASP without WH1 domain). The WAWH proteins have a similar domain organisation as the WASP proteins, except that they miss the N-terminal WH1 domain  and also present in many other proteins we did not analyse these hits further in the first instance. As soon as further amoebozoan genomes became available we always searched the Entamoeba genomes again for WASP homologs. As we started to inspect the short hits for the WH2 domains further, the corresponding assembled genes revealed a similar domain organisation as WASP proteins starting with the WAID domain  at the N-terminus and lack the CRIB motif. IMD domains are found in proteins of the IRSp53 (insulin receptor tyrosine kinase substrate p53) and proteins of the MIM (missing-in-metastasis) family, for example. The MIM family proteins additionally contain proline-rich regions and a C-terminal WH2 domain . We therefore suggest calling these new types of WASP family proteins WAML (WASP and MIM like). One subclass of the WAML proteins comprises a short version that misses the PPR and VCA region.Because all amoeba genomes contain at least one WASP gene we were searching for WASP homologs in n Figure . SurprisThe WH2 domain is a short sequence motif of 17-27 residues and binds to actin at the barbed-end -33. The In contrast to the WH2 domains, the C domains of the VCA region have WASP sub-family specific patterns Figure . The genLeishmania WASH proteins), and many WASP and WAVE homologs that contain both a tryptophan and a phenylalanine/tyrosine, both separated by variable numbers of acidic residues. Thus, it remains an open question whether a tryptophan or just an aromatic residue is needed for proper function, and whether there is a difference in encoding only a tryptophan or an additional phenylalanine/tyrosine.The acidic C-termini of the WASP family proteins are thought to mediate ARP2/3 binding. Most acidic domains contain a tryptophan residue as last coding residues or close to the terminus. While phenylalanines instead of the tryptophans have been reported to be unique to invertebrate WHAMM homologs  we have Surprisingly, alternative splice forms of WASP family proteins have not been reported yet except for a neural-specific splicing of WASP through that a truncated WASP protein is generated lacking exon-2 . Exon-2 Aplysia californica WASP gene  for mutually exclusive spliced exons but could not identify any.We have searched all available databases for cDNA/EST clones representing different splice forms of the WASP family proteins. We were not able to identify any alternatively spliced exons except for a mutually exclusive spliced exon of the This situation is in sharp contrast to other proteins sharing WASP domains like the NHS proteins or the homer proteins. The Nance-Horan syndrome protein has an N-terminal WHD domain like the WAVE proteins, is alternatively spliced, and encodes at least five isoforms . The thrInitially, the WASP family of proteins consisted of the WASP proteins and the WAVE proteins ,38. BothEntamoeba histolytica and Entamoeba dispar both contain one WASH protein, and three WAWH and five WAML homologs, while the close relative Entamoeba invadens has lost WASH but instead encodes three WAWH and seven WAML homologs. Another example represents the green algae species sequenced by today. For the Ostreococcus species a WASH homolog could be identified, while WASP family homologs could not be identified in Volvox carteri and Chlamydomonas reinhardtii although both have ARP2/3, and the Micromonas and Chlorella species do not have the ARP2/3 complex anymore and thus do not encode any WASP family protein. Therefore, it is not sufficient to only analyse a few sample genomes of each of the main eukaryotic kingdoms as it has been done in previous analyses [The analysis of most eukaryotic sequenced genomes available allowed us to reconstruct the evolution of the WASP family members in the different branches of the eukaryotic tree and to identify and characterise new subfamilies. It is very important to analyse as many genomes as possible because even closely related species might contain different sets of the WASP subfamilies and subfamily members. For example, the Entamoeba species analyses ,39. Of cFor species for which we were not able to identify any WASP family protein homolog we searched for all actin and actin-related protein genes. If these species also did not contain members of the ARP2 and ARP3 subfamilies the absence of ARP2/3-complex activating proteins was confirmed. However, we identified ARP2 and ARP3 in some species for which we were not able to find WASP family protein members yet. Based on the comparison of about 2,200 homologs of actin-related proteins the identification of ARP2 and ARP3 homologs is straightforward (data not shown). This is in contrast to the search for homologs of the other four members of the pentameric WAVE complex. Each of the other proteins of the WAVE complex is part of a protein family whose members are also incorporated into the WASH complex . In addiHaving identified all WASP family homologs in all sequenced organisms, the presence or absence of the various homologs in the respective species can now be plotted on the tree of the eukaryotes Figure . As basiTrichomonas vaginalis encoding eleven WAVE homologs. In contrast, the Euglenozoa contain only a WASH homolog, while the Stramenopiles encode either a single WASH or a single WAVE protein, and the Haptophyceae Emiliania huxleyi contains only a WASP homolog. The ARP2/3 complex, and thus WASP family proteins, is absent in Diplomonoda, Rhodophyta, Bacillariophyta, and Apicomplexa. The Stramenopiles Blastocystis hominis contains the ARP2/3 complex, but WASP family proteins could not be found in its genome. Here, proteins from class II NPFs might regulate the ARP2/3 complex.Our analysis shows that the most ancient eukaryote must have contained a WASP, a WAVE, and a WASH homolog, because homologs of these subfamilies have been found in all major eukaryotic branches Figure . Some spOstreococcus species and some land plants that separated very early in the evolution of the viridiplantae, like the moss Physcomitrella patens and the fern Selaginella moellendorfii. Based on these WASH proteins we searched in all other available plant genomes for homologs. A full-length WASH homolog has only been identified in cDNA data of Picea glauca and fragments of very similar sequences to the Picea WASH in cDNA data of another Coniferophyta, Pinus taeda, and the Cycadophyta Cycas rumphii. N-terminal fragments of WASH have been identified in the genomes of the Liliopsida Sorghum bicolour, Oryza species, Phoenix dactylifera, and Setaria italica. These fragments comprise the N-terminal about 200 residues, and no further WASH sequence could be identified in spite of extensive manual inspection of the genomic DNA sequences. Because the C-termini of these fragments are not conserved and because homologous sequence to these fragments could not be identified in other Liliopsida genomes it is most probable that these fragments are pseudogenes in the process of being disbanded. The analysis also shows that WASH has been lost in the last common ancestor of the eudicotyledons branch. Although several good assemblies of genomes of green algae are available, WASH homologs (and the ARP2/3 complex) could only be identified in the Ostreococcus species  and Selaginella consistently group together in the phylogenetic tree of the WAVE proteins, the WAVE homologs of the Magnoliophyta clearly group into two major classes. Variants of these classes, like those in Arabidopsis and Populus, have been derived by species-specific duplications.WASP proteins have never been identified in plant genomes ,55, and s Figure . The ChlAcanthamoeba castellanii contain WASP, WAVE, and WASH homologs, and also homologs of the newly identified WAWH proteins. In addition, most amoebae species sequenced so far contain several species-specific gene duplications. In contrast, the Entamoeba species have lost WASP and WAVE, but instead encode five or more WAML homologs. WAML proteins contain an N-terminal IMD (IRSp53-MIM homology domain) domain, a WAID domain, a proline-rich region, and a C-terminal VCA domain. The VCA domain of WAML might activate the ARP2/3 complex in a similar way as the VCA domains of WASP and WAVE protein. Because the Rho-GTPase binding domain is missing in WAML there must be a different way to release the VCA domain from the intramolecular binding to the WAID domain. What might be the function of the IMD domain in WAML proteins? N-WASP is known to be essential for the formation of distinct cellular architectures such as endocytic vesicles, filopodia and podosomes/invadopodia [The amoebae have a rich repertoire of WASP family proteins Figure . The Dicadopodia . These sadopodia ,57. Thesadopodia . The SH3adopodia ,59,60. TAll fungi that have been sequenced so far have lost the WASH homolog Figure . In addiClytia hemisphaerica. However, most of the invertebrate species sequenced so far have subsequently lost the WHAMM homolog. In addition, the Trematoda Schistosoma mansoni and all sequenced Cestoda have lost the WASH homolog. At the origin of the vertebrates two whole-genome duplication events happened [Anolis carolinensis also encodes a WAWH homolog based on its domain composition.Most of the invertebrate species analyzed here contain one of each of the WASP, WAVE, and WASH homologs Figure . In a fehappened  followedhappened ,65. ThesAplysia californica. This is in strong contrast to other actin-binding proteins that have the same N-terminal domains like Ena/VASP , NHS , and MIM . Single transcripts are most probably a characteristic of the WASP family proteins because extensive cDNA data is already available. Given the recent identification of two new WASP protein subfamilies, WASH and WHAMM, and of the two new subfamilies described here, WAML and WAWH, and in the prospect of many upcoming genome sequences the WASP protein family is expected to grow further.We could show that most eukaryotes encode a rich repertoire of WASP family proteins to regulate the ARP2/3 dependent remodelling of the actin cytoskeleton. Surprisingly, alternative splice variants could be identified for only a single WASP homolog from the sea hare http://www.cymobase.org, [WASP family genes have been identified in TBLASTN searches of the completed or almost completed genomes of 529 organisms starting with the protein sequences of the human homologs. Species outside the metazoans that were expected to encode very divergent homologs were searched with many different homologs and every single hit showing homology to either the C-terminal domains , the GBD domain, or the N-terminal domains was analysed in detail. During this search, the new WASP subfamilies WAWH and WAML were identified based on the homology of their GBD domains to those from WASP proteins. All hits were manually analysed at the genomic DNA level. The correct coding sequences were identified with the help of the multiple sequence alignment of the respective protein family. As the amount of sequences increased , many of the initially predicted sequences were reanalysed to correctly identify all exon borders. Where possible, EST data has been analysed to help in the annotation process. In addition to the analysis of these large-scale sequencing projects, all WASP family genes in the "nr" database at NCBI have been collected and reanalysed. All sequence related data  and references to genome sequencing centers are available through the CyMoBase .The multiple sequence alignments of the WASP family proteins have been built and extended during the process of annotating and assembling new sequences. The initial alignments have been generated from the first 10 non-validated sequences obtained from NCBI using the ClustalW software with standard settings . During http://tree.bio.ed.ac.uk/software/figtree).The phylogenetic trees were built based on the manually constructed and maintained multiple sequence alignments of the concatenated WASP protein family characteristic N-terminal and VCA (without linker) domains using two different methods: 1. Maximum likelihood (ML) using the PROTMIXBLOSUM62 amino acid model and bootstrapping  using RAxML . 2. PostThe data sets supporting the results of this article are included within the article .CRIB: Cdc42/Rac interactive binding; GDB: GTPase binding domain; JMY: Junction-; ediating and regulatory protein; NHS: Nance-Horan syndrome; VASP: Vasodilator-stimulated phosphoprotein; WAHD: WASH homology domain; WAID: WASP autoinhibitory domain; WAML: WASP and MIM like; WASH: Wiskott-Aldrich syndrome protein and Scar homolog; WASP: Wiskott-Aldrich syndrome protein; WAVE: WASP-family verprolin-homologous protein; WAWH: WASP without WH1 domain; WH1: WASP homology domain 1; WH2: WASP homology domain 2; WHAMM: WASP homolog associated with actin, membranes, and microtubules; WHD: WAVE homology domain, WIP: WASP-interacting protein; WMD: WHAMM membrane interaction domain.The authors declare that they have no competing interests.MK assembled and annotated sequences, did all data analysis and wrote the manuscript. DL assembled part of the WASP sequences. SE assembled part of the WAVE sequences. All authors read and approved the final version of the manuscript.Zip archive of the phylogenetic trees and sequence alignments. The file includes all phylogenetic trees of the WASP family proteins. The sequence alignments of the proteins are included in fasta format.Click here for file