Comparison Of Domain Architectures Research Articles

Identification, characterization and spatiotemporal expression analysis of the FKBP family genes in Locusta migratoria

FK506 binding proteins (FKBPs) are a highly-conserved group of proteins known to bind to FK506, an immunosuppressive drug. They play different physiological roles, including transcription regulation, protein folding, signal transduction and immunosuppression. A number of FKBP genes have been identified in eukaryotes; however, very little information about these genes has been reported in Locusta migratoria. Here, we identified and characterized 10 FKBP genes from L. migratoria. Phylogenetic analysis and comparison of domain architectures indicated that the LmFKBP family can be divided into two subfamilies and five subclasses. Developmental and tissue expression pattern analysis revealed that all LmFKBPs transcripts, including LmFKBP46, LmFKBP12, LmFKBP47, LmFKBP79, LmFKBP16, LmFKBP24, LmFKBP44b, LmFKBP53, were periodically expressed during different developmental stages and mainly expressed in the fat body, hemolymph, testis, and ovary. In brief, our work depicts a outline but panoramic picture of LmFKBP family in L. migratoria, and provides a solid foundation to further investigate the molecular functions of LmFKBPs.

Identification of Rab family genes and functional analyses of LmRab5 and LmRab11A in the development and RNA interference of Locusta migratoria.

Rab proteins constitute the largest family of small GTPases, which play pivotal roles in intracellular membrane trafficking in all eukaryotes. A number of Rab genes have been identified in eukaryotes; however, very little information about these genes has been reported in insects. In the current study, for the first time we identified and characterized 27 Rab family genes from Locusta migratoria. Phylogenetic analysis and comparison of domain architecture indicated that Rab family genes are highly conserved among insect species. Tissue-dependent expression profiles indicated that expression of Rab genes was highest in the ovary, except for LmRab3, which was most highly expressed in hemolymph. The biological function of each Rab gene was investigated using RNA interference (RNAi). Double-stranded RNA targeting each Rab gene was injected into the hemocoel of nymphs and revealed that suppression of two Rab genes (LmRab5 and LmRab11A) caused 100% mortality. In addition, nymphs injected with dsLmRab5 exhibited severe phenotypic defects in the gastric caeca and midgut, while dsLmRab11A arrested the molting process. We then applied the RNAi of RNAi technique to test if silencing either of these two genes would affect the suppression of the lethal giant larvae (LmLgl) reporter gene and found that suppression of LmRab5 diminished the RNAi efficiency of LmLgl, whereas suppression of LmRab11A enhanced RNAi efficiency of LmLgl. These results indicate that Rab genes contribute differently to RNAi efficiency in different tissues. Our study provides a foundation for further functional investigations of Rab genes and their contributions to RNAi efficiency in L. migratoria.

Characterization, expression patterns, and transcriptional responses of three core RNA interference pathway genes from Ostrinia nubilalis

RNA interference (RNAi) is commonly used in the laboratory to analyze gene function, and RNAi-based pest management strategies are now being employed. Unfortunately, RNAi is hindered by inefficient and highly-variable results when different insects are targeted, especially lepidopterans, such as the European corn borer (ECB), Ostrinia nubilalis (Lepidoptera: Crambidae). Previous efforts to achieve RNAi-mediated gene suppression in ECB revealed low RNAi efficiency with both double-stranded RNA (dsRNA) injection and ingestion. One mechanism that can affect RNAi efficiency in insects is the expression and function of core RNAi pathway genes, such as those encoding Argonaut 2 (Ago2), Dicer 2 (Dcr2), and a dsRNA binding protein (R2D2). To determine if deficiencies in these core RNAi pathway genes contribute to low RNAi efficiency in ECB, full-length complementary DNAs encoding OnAgo2, OnDcr2, and OnR2D2 were cloned, sequenced, and characterized. A comparison of domain architecture suggested that all three predicted proteins contained the necessary domains to function. However, a comparison of evolutionary distances revealed potentially important variations in the first RNase III domain of OnDcr2, the double-stranded RNA binding domains of OnR2D2, and both the PAZ and PIWI domains of OnAgo2, which may indicate functional differences in enzymatic activity between species. Expression analysis indicated that transcripts for all three genes were expressed in all developmental stages and tissues investigated. Interestingly, the introduction of non-target dsRNA into ECB second-instar larvae via microinjection did not affect OnAgo2, OnDcr2, or OnR2D2 expression. In contrast, ingestion of the same dsRNAs resulted in upregulation of OnDcr2 but downregulation of OnR2D2. The unexpected transcriptional responses of the core machinery and the divergence in amino-acid sequence between specific domains in each core RNAi protein may possibly contribute to low RNAi efficiency in ECB. Understanding the contributions of different RNAi pathway components is critical to adapting this technology for use in controlling lepidopteran pests that exhibit low RNAi efficiency.

The metagenome-derived enzyme RhaB opens a new subclass of bacterial B type α-l-rhamnosidases

A combined sequence- and function-based analysis of a metagenomic library DNA derived from elephant feces led to the identification of a novel bacterial α-l-rhamnosidase belonging to glycoside hydrolase family 78 (GH78). The gene was designated rhaB (4095bp) and encoded for a putative protein of 1364 amino acids. The C-terminal part of the enzyme revealed an amino acid (AA) sequence identity of 58% to a predicted bacterial α-l-rhamnosidase from Bacteroides nordii. Interestingly, the N-terminal region of the deduced enzyme RhaB contained a GDSL-like lipase motif and an acetyl-xylan esterase (DAP2) motif. While heterologous expression of the complete rhaB failed, subcloning of the gene identified the most active open reading frame (ORF) to be of 3081bp, which we designated rhaB1. The enzyme RhaB1 was overexpressed in Escherichia coli BL21 (DE3) and was purified to an amount of 75mg/L of culture medium. In accordance to the intestinal origin, RhaB1 showed a preference for mesophilic conditions with an optimum activity at a temperature TOpt of 40°C and a pHOpt of 6.5, respectively. The recombinant protein had a Km value of 0.79mM and a specific activity vmax of 18.4U for pNP-α-l-rhamnose, a calculated Km of 6.36mM and vmax of 2.9×10−3U for naringin, and a Km of 6.75mM and specific activity vmax of 8.63×10−2U for rutin, respectively. Phylogenetic analysis and amino acid domain architecture comparison revealed that RhaB1 belongs to a new subclass of bacterial B type α-l-rhamnosidases of GH 78. To our knowledge RhaB1 is the first biochemically-characterized enzyme of this subclass.

An alignment-free domain architecture similarity search (ADASS) algorithm for inferring homology between multi-domain proteins

Annotations of the genes and their products are largely guided by inferring homology. Sequence similarity is the primary measure used for annotation purpose however, the domain content and order were given less importance albeit the fact that domain insertion, deletion, positional changes can bring in functional varieties. Of late, several methods developed quantify domain architecture similarity depending on alignments of their sequences and are focused on only homologous proteins. We present an alignment-free domain architecture-similarity search (ADASS) algorithm that identifies proteins that share very poor sequence similarity yet having similar domain architectures. We introduce a “singlet matching-triplet comparison” method in ADASS, wherein triplet of domains is compared with other triplets in a pair-wise comparison of two domain architectures. Different events in the triplet comparison are scored as per a scoring scheme and an average pairwise distance score (Domain Architecture Distance score - DAD Score) is calculated between protein domains architectures. We use domain architectures of a selected domain termed as centric domain and cluster them based on DAD score. The algorithm has high Positive Prediction Value (PPV) with respect to the clustering of the sequences of selected domain architectures. A comparison of domain architecture based dendrograms using ADASS method and an existing method revealed that ADASS can classify proteins depending on the extent of domain architecture level similarity. ADASS is more relevant in cases of proteins with tiny domains having little contribution to the overall sequence similarity but contributing significantly to the overall function.

Reassessing Domain Architecture Evolution of Metazoan Proteins: Major Impact of Gene Prediction Errors

In view of the fact that appearance of novel protein domain architectures (DA) is closely associated with biological innovations, there is a growing interest in the genome-scale reconstruction of the evolutionary history of the domain architectures of multidomain proteins. In such analyses, however, it is usually ignored that a significant proportion of Metazoan sequences analyzed is mispredicted and that this may seriously affect the validity of the conclusions. To estimate the contribution of errors in gene prediction to differences in DA of predicted proteins, we have used the high quality manually curated UniProtKB/Swiss-Prot database as a reference. For genome-scale analysis of domain architectures of predicted proteins we focused on RefSeq, EnsEMBL and NCBI's GNOMON predicted sequences of Metazoan species with completely sequenced genomes. Comparison of the DA of UniProtKB/Swiss-Prot sequences of worm, fly, zebrafish, frog, chick, mouse, rat and orangutan with those of human Swiss-Prot entries have identified relatively few cases where orthologs had different DA, although the percentage with different DA increased with evolutionary distance. In contrast with this, comparison of the DA of human, orangutan, rat, mouse, chicken, frog, zebrafish, worm and fly RefSeq, EnsEMBL and NCBI's GNOMON predicted protein sequences with those of the corresponding/orthologous human Swiss-Prot entries identified a significantly higher proportion of domain architecture differences than in the case of the comparison of Swiss-Prot entries. Analysis of RefSeq, EnsEMBL and NCBI's GNOMON predicted protein sequences with DAs different from those of their Swiss-Prot orthologs confirmed that the higher rate of domain architecture differences is due to errors in gene prediction, the majority of which could be corrected with our FixPred protocol. We have also demonstrated that contamination of databases with incomplete, abnormal or mispredicted sequences introduces a bias in DA differences in as much as it increases the proportion of terminal over internal DA differences. Here we have shown that in the case of RefSeq, EnsEMBL and NCBI's GNOMON predicted protein sequences of Metazoan species, the contribution of gene prediction errors to domain architecture differences of orthologs is comparable to or greater than those due to true gene rearrangements. We have also demonstrated that domain architecture comparison may serve as a useful tool for the quality control of gene predictions and may thus guide the correction of sequence errors. Our findings caution that earlier genome-scale studies based on comparison of predicted (frequently mispredicted) protein sequences may have led to some erroneous conclusions about the evolution of novel domain architectures of multidomain proteins. A reassessment of the DA evolution of orthologous and paralogous proteins is presented in an accompanying paper [1].

Identity and divergence of protein domain architectures after the yeast whole-genome duplication event

Gene duplication is a key mechanism in evolution for generating new functionality, and it is known to have produced a large proportion of genes. Duplication mechanisms include small-scale, or "local", events such as unequal crossing over and retroposition, together with global events, such as chromosomal or whole genome duplication (WGD). In particular, different studies confirmed that the yeast S. cerevisiae arose from a 100-150 million-year old whole-genome duplication. Detection and study of duplications are usually based on sequence alignment, synteny and phylogenetic techniques, but protein domains are also useful in assessing protein homology. We develop a simple and computationally efficient protein domain architecture comparison method based on the domain assignments available from public databases. We test the accuracy and the reliability of this method in detecting instances of gene duplication in the yeast S. cerevisiae. In particular, we analyze the evolution of WGD and non-WGD paralogs from the domain viewpoint, in comparison with a more standard functional analysis of the genes. A large number of domains is shared by genes that underwent local and global duplications, indicating the existence of a common set of "duplicable" domains. On the other hand, WGD and non-WGD paralogs tend to have different functions. We find evidence that this comes from functional migration within similar domain superfamilies, but also from the existence of small sets of WGD and non-WGD specific domain superfamilies with largely different functions. This observation gives a novel perspective on the finding that WGD paralogs tend to be functionally different from small-scale paralogs. WGD and non-WGD superfamilies carry distinct functions. Finally, the Gene Ontology similarity of paralogs tends to decrease with duplication age, while this tendency is weaker or not observable by the comparison of the domain architectures of paralogs. This suggests that the set of domains composing a protein tends to be maintained, while its function, cellular process or localization diversifies. Overall, the gathered evidence gives a different viewpoint on the biological specificity of the WGD and at the same time points out the validity of domain architecture comparison as a tool for detecting homology.

Protein comparison at the domain architecture level

BackgroundThe general method used to determine the function of newly discovered proteins is to transfer annotations from well-characterized homologous proteins. The process of selecting homologous proteins can largely be classified into sequence-based and domain-based approaches. Domain-based methods have several advantages for identifying distant homology and homology among proteins with multiple domains, as compared to sequence-based methods. However, these methods are challenged by large families defined by 'promiscuous' (or 'mobile') domains.ResultsHere we present a measure, called Weighed Domain Architecture Comparison (WDAC), of domain architecture similarity, which can be used to identify homolog of multidomain proteins. To distinguish these promiscuous domains from conventional protein domains, we assigned a weight score to Pfam domain extracted from RefSeq proteins, based on its abundance and versatility. To measure the similarity of two domain architectures, cosine similarity (a similarity measure used in information retrieval) is used. We combined sequence similarity with domain architecture comparisons to identify proteins belonging to the same domain architecture. Using human and nematode proteomes, we compared WDAC with an unweighted domain architecture method (DAC) to evaluate the effectiveness of domain weight scores. We found that WDAC is better at identifying homology among multidomain proteins.ConclusionOur analysis indicates that considering domain weight scores in domain architecture comparisons improves protein homology identification. We developed a web-based server to allow users to compare their proteins with protein domain architectures.

DAhunter: a web-based server that identifies homologous proteins by comparing domain architecture

We present DAhunter, a web-based server that identifies homologous proteins by comparing domain architectures, the organization of protein domains. A major obstacle in comparison of domain architecture is the existence of ‘promiscuous’ domains, which carry out auxiliary functions and appear in many unrelated proteins. To distinguish these promiscuous domains from protein domains, we assigned a weight score to each domain extracted from RefSeq proteins, based on its abundance and versatility. A domain's score represents its importance in the ‘protein world’ and is used in the comparison of domain architectures. In scoring domains, DAhunter also considers domain combinations as well as single domains. To measure the similarity of two domain architectures, we developed several methods that are based on algorithms used in information retrieval (the cosine similarity, the Goodman–Kruskal γ function, and domain duplication index) and then combined these into a similarity score. Compared with other domain architecture algorithms, DAhunter is better at identifying homology. The server is available at http://www.dahunter.kr and http://localodom.kobic.re.kr/dahunter/index.htm

Sequence Similarity Network Reveals Common Ancestry of Multidomain Proteins

We address the problem of homology identification in complex multidomain families with varied domain architectures. The challenge is to distinguish sequence pairs that share common ancestry from pairs that share an inserted domain but are otherwise unrelated. This distinction is essential for accuracy in gene annotation, function prediction, and comparative genomics. There are two major obstacles to multidomain homology identification: lack of a formal definition and lack of curated benchmarks for evaluating the performance of new methods. We offer preliminary solutions to both problems: 1) an extension of the traditional model of homology to include domain insertions; and 2) a manually curated benchmark of well-studied families in mouse and human. We further present Neighborhood Correlation, a novel method that exploits the local structure of the sequence similarity network to identify homologs with great accuracy based on the observation that gene duplication and domain shuffling leave distinct patterns in the sequence similarity network. In a rigorous, empirical comparison using our curated data, Neighborhood Correlation outperforms sequence similarity, alignment length, and domain architecture comparison. Neighborhood Correlation is well suited for automated, genome-scale analyses. It is easy to compute, does not require explicit knowledge of domain architecture, and classifies both single and multidomain homologs with high accuracy. Homolog predictions obtained with our method, as well as our manually curated benchmark and a web-based visualization tool for exploratory analysis of the network neighborhood structure, are available at http://www.neighborhoodcorrelation.org. Our work represents a departure from the prevailing view that the concept of homology cannot be applied to genes that have undergone domain shuffling. In contrast to current approaches that either focus on the homology of individual domains or consider only families with identical domain architectures, we show that homology can be rationally defined for multidomain families with diverse architectures by considering the genomic context of the genes that encode them. Our study demonstrates the utility of mining network structure for evolutionary information, suggesting this is a fertile approach for investigating evolutionary processes in the post-genomic era.

Comparative integromics on FAT1, FAT2, FAT3 and FAT4

WNT5A, WNT5B, WNT11, FZD3, FZD6, VANGL1, VANGL2, DVL1, DVL2, DVL3, PRICKLE1, PRICKLE2, ANKRD6, NKD1, NKD2, DAAM1, DAAM2, CELSR1, CELSR2, CELSR3, ROR1 and ROR2 are planar cell polarity (PCP) signaling molecules implicated in the regulation of cellular polarity, convergent extension, and invasion. FAT1, FAT2, FAT3 and FAT4 are Cadherin superfamily members homologous to Drosophila Fat, functioning as a positive regulator of PCP in the Drosophila wing. Complete coding sequence (CDS) for human FAT1 (NM_005245.3) and FAT2 (NM_001447.1) are available, while artificial CDS for human FAT3 (XM_926199 and XM_936538) and partial CDS for FAT4 (NM_024582.2). Here, complete CDS of human FAT3 and FAT4 were determined by using bioinformatics and human intelligence (Humint). FAT3 gene, consisting of 26 exons, encoded a 4557-aa protein with extracellular 33 Cadherin repeats, one Laminin G (LamG) domain and two EGF domains. FAT4 gene encoded a 4924-aa protein with extracellular 34 Cadherin repeats, two LamG domains and three EGF domains. Cytoplasmic VCSVxPxLP and SDYxS motifs were identified as novel motifs conserved among FAT1, FAT2 and FAT3 orthologs. Domain architecture comparison and phylogenetic analysis revealed that FAT1, FAT2 and FAR3 were divergent from FAT4. FAT1-MTNR1A locus at 4q35.2 and FAT3-MTNR1B locus at 11q14.3-q21 were paralogous regions within the human genome. FAT1 mRNA was expressed in embryonic stem (ES) cells, neural tissues, gastric cancer, pancreatic cancer, colorectal cancer, breast cancer, lung cancer and brain tumors. FAT2 mRNA was expressed in infant brain, cerebellum, gastric cancer, pancreatic cancer, ovarian cancer, esophageal cancer, skin squamous cell carcinoma, head and neck cancer. FAT3 mRNA was expressed in ES cells, primitive neuroectoderm, fetal brain, infant brain, adult neural tissues and prostate. FAT4 mRNA was expressed in fetal brain, infant brain, brain tumor and colorectal cancer. FAT family members were revealed to be targets of systems medicine in the fields of oncology and neurology.

Dichotomy of major bacterial phyla inferred from gene arrangement comparisons

A computer search for gene arrangements that are present in Gram-positive bacteria but are absent from Proteobacteria and vice versa was carried out. Four such arrangements were detected, based on which major bacterial phyla were divided into two groups; Thermotoga, Deinococcus-Thermus, Chloroflexi (green non-sulfur bacteria), and Fusobacteria, represent Gram-positive bacterial gene arrangements, while Aquifex, Spirochetes, Planctomycetes, Chlorobi (green sulfur bacteria), Bacteroides show Proteobacterial arrangements. The division is almost consistent with another partition of the major phyla based on the comparison of domain architectures of RNA polymerase subunits and sigma factor, suggesting a fundamental split of the major bacterial phyla at an early stage of bacterial evolution.

Evolution of Aminoacyl-tRNA Synthetases—Analysis of Unique Domain Architectures and Phylogenetic Trees Reveals a Complex History of Horizontal Gene Transfer Events

Phylogenetic analysis of aminoacyl-tRNA synthetases (aaRSs) of all 20 specificities from completely sequenced bacterial, archaeal, and eukaryotic genomes reveals a complex evolutionary picture. Detailed examination of the domain architecture of aaRSs using sequence profile searches delineated a network of partially conserved domains that is even more elaborate than previously suspected. Several unexpected evolutionary connections were identified, including the apparent origin of the beta-subunit of bacterial GlyRS from the HD superfamily of hydrolases, a domain shared by bacterial AspRS and the B subunit of archaeal glutamyl-tRNA amidotransferases, and another previously undetected domain that is conserved in a subset of ThrRS, guanosine polyphosphate hydrolases and synthetases, and a family of GTPases. Comparison of domain architectures and multiple alignments resulted in the delineation of synapomorphies-shared derived characters, such as extra domains or inserts-for most of the aaRSs specificities. These synapomorphies partition sets of aaRSs with the same specificity into two or more distinct and apparently monophyletic groups. In conjunction with cluster analysis and a modification of the midpoint-rooting procedure, this partitioning was used to infer the likely root position in phylogenetic trees. The topologies of the resulting rooted trees for most of the aaRSs specificities are compatible with the evolutionary "standard model" whereby the earliest radiation event separated bacteria from the common ancestor of archaea and eukaryotes as opposed to the two other possible evolutionary scenarios for the three major divisions of life. For almost all aaRSs specificities, however, this simple scheme is confounded by displacement of some of the bacterial aaRSs by their eukaryotic or, less frequently, archaeal counterparts. Displacement of ancestral eukaryotic aaRS genes by bacterial ones, presumably of mitochondrial origin, was observed for three aaRSs. In contrast, there was no convincing evidence of displacement of archaeal aaRSs by bacterial ones. Displacement of aaRS genes by eukaryotic counterparts is most common among parasitic and symbiotic bacteria, particularly the spirochaetes, in which 10 of the 19 aaRSs seem to have been displaced by the respective eukaryotic genes and two by the archaeal counterpart. Unlike the primary radiation events between the three main divisions of life, that were readily traceable through the phylogenetic analysis of aaRSs, no consistent large-scale bacterial phylogeny could be established. In part, this may be due to additional gene displacement events among bacterial lineages. Argument is presented that, although lineage-specific gene loss might have contributed to the evolution of some of the aaRSs, this is not a viable alternative to horizontal gene transfer as the principal evolutionary phenomenon in this gene class.