Loop-length-dependent SVM prediction of domain linkers for high-throughput structural proteomics

Unique Fn3-like biosensor in σI/anti-σI factors for regulatory expression of major cellulosomal scaffoldins in Pseudobacteroides cellulosolvens

Lignocellulolytic clostridia employ multiple pairs of alternative σ/anti-σ (SigI/RsgI) factors to regulate cellulosomal components for substrate-specific degradation of cellulosic biomass. The current model has proposed that RsgIs use a sensor domain to bind specific extracellular lignocellulosic components and activate cognate SigIs to initiate expression of corresponding cellulosomal enzyme genes, while expression of scaffoldins can be initiated by several different SigIs. Pseudobacteroides cellulosolvens contains the most complex known cellulosome system and the highest number of SigI-RsgI regulons yet discovered. However, the function of many RsgI sensor domains and their relationship with the various enzyme types are not fully understood. Here, we report that RsgI4 from P. cellulosolvens employs a C-terminal module that bears distant similarity to the fibronectin type III (Fn3) domain and serves as the sensor domain. Substrate-binding analysis revealed that the Fn3-like domain of RsgI4 represents a novel carbohydrate-binding module (CBM) that binds to a wide range of polysaccharide types. Structure determination further revealed that the Fn3-like domain belongs to the type B group of CBMs with a predicted concave face for substrate binding. Promoter sequence analysis of cellulosomal genes revealed that SigI4 is responsible for cellulosomal regulation of major scaffoldins rather than enzymes, consistent with the broad substrate specificity of the RsgI4 sensor domain. Notably, scaffoldins are invariably required as cellulosome components regardless of the substrate type. These findings suggest that the intricate cellulosome system of P. cellulosolvens comprises a more elaborate regulation mechanism than other bacteria and thus expands the paradigm of cellulosome regulation.

Role of mucin 2 gene for growth in Anas platyrhynchos: a novel report

Introduction

The mucin gene is expressed in the mucous membrane of the inner layer of the internal organs. Intestinalmucin 2 (MUC2), amajor gel-formingmucin, represents a primary barrier component of mucus layers.

Materials and methods

This is the first report on the role of mucin genes in growth traits in animals. In this study, we randomly studied Bengal ducks (Anas platyrhynchos) reared from day old to 10 weeks of age under an organized farm and studied the growth parameters as well as body weight and average daily body weight gain.

Result and discussion

We characterized the mucin gene for Bengal ducks and observed glycosylation and EGF1 (EGF-like domain signature) as important domains for growth traits in ducks. We observed a better expression profile for the mucin gene in high-growing ducks in comparison to that of low-growing ducks with real-time PCR. Hence, the mucin gene may be employed as a marker for growth traits.

RIGI, TLR7, and TLR3 Genes Were Predicted to Have Immune Response Against Avian Influenza in Indigenous Ducks

Avian influenza is a disease with every possibility to evolve as a human-to-human pandemic arising out of frequent mutations and genetic reassortment or recombination of avian influenza (AI) virus. The greatest concern is that till date, no satisfactory medicine or vaccines are available, leading to massive culling of poultry birds, causing huge economic loss and ban on export of chicken products, which emphasizes the need to develop an alternative strategy for control of AI. In the current study, we attempt to explore the molecular mechanism of innate immune potential of ducks against avian influenza. In the present study, we have characterized immune response molecules such as duck TLR3, TLR7, and RIGI that are predicted to have potent antiviral activities against the identified strain of avian influenza through in silico studies (molecular docking) followed by experimental validation with differential mRNA expression analysis. Future exploitation may include immunomodulation with the recombinant protein, and transgenic or gene-edited chicken resistant to bird flu.

Ovine CD14- an Immune Response Gene Has a Role Against Gastrointestinal Nematode Haemonchus contortus-A Novel Report

CD14 (also known as the monocyte differentiation antigen) is an important immune response gene known to be primarily responsible for innate immunity against bacterial pathogens, and as a pattern recognition receptor (PRR), binds with LPS (endotoxin), lipoproteins, and lipotechoic acid of bacteria. So far very limited work has been conducted in parasitic immunology. In the current study, we reported the role of CD14 in parasitic immunology in livestock species (sheep) for the first time. Ovine CD14 is characterized as a horse-shoe shaped bent solenoid with a hydrophobic amino-terminal pocket for CD14 along with domains. High mutation frequency was observed, out of total 41 mutations identified, 23 mutations were observed to be thermodynamically unstable and 11 mutations were deleterious in nature, causing major functional alteration of important domains of CD14, an indication of variations in individual susceptibility for sheep against Haemonchus contortus infestations. In silico studies with molecular docking reveal a role of immune response against Haemonchus contortus in sheep, which is later confirmed with experimental evidence through differential mRNA expression analysis for sheep, which revealed better expression of CD14 in Haemonchus contortus infected sheep compared to that of non-infected sheep. We confirmed the above findings with supportive evidence through haematological and biochemical analyses. Phylogenetic analysis was conducted to assess the evolutionary relationship with respect to humans and it was observed that sheep may well be used as model organisms due to better genetic closeness compared to that of mice.

Ancestry of the AUTS2 family-A novel group of polycomb-complex proteins involved in human neurological disease

Autism susceptibility candidate 2 (AUTS2) is a neurodevelopmental regulator associated with an autosomal dominant intellectual disability syndrome, AUTS2 syndrome, and is implicated as an important gene in human-specific evolution. AUTS2 exists as part of a tripartite gene family, the AUTS2 family, which includes two relatively undefined proteins, Fibrosin (FBRS) and Fibrosin-like protein 1 (FBRSL1). Evolutionary ancestors of AUTS2 have not been formally identified outside of the Animalia clade. A Drosophila melanogaster protein, Tay bridge, with a role in neurodevelopment, has been shown to display limited similarity to the C-terminal of AUTS2, suggesting that evolutionary ancestors of the AUTS2 family may exist within other Protostome lineages. Here we present an evolutionary analysis of the AUTS2 family, which highlights ancestral homologs of AUTS2 in multiple Protostome species, implicates AUTS2 as the closest human relative to the progenitor of the AUTS2 family, and demonstrates that Tay bridge is a divergent ortholog of the ancestral AUTS2 progenitor gene. We also define regions of high relative sequence identity, with potential functional significance, shared by the extended AUTS2 protein family. Using structural predictions coupled with sequence conservation and human variant data from 15,708 individuals, a putative domain structure for AUTS2 was produced that can be used to aid interpretation of the consequences of nucleotide variation on protein structure and function in human disease. To assess the role of AUTS2 in human-specific evolution, we recalculated allele frequencies at previously identified human derived sites using large population genome data, and show a high prevalence of ancestral alleles, suggesting that AUTS2 may not be a rapidly evolving gene, as previously thought.

DNN-Dom: predicting protein domain boundary from sequence alone by deep neural network

MOTIVATION

Accurate delineation of protein domain boundary plays an important role for protein engineering and structure prediction. Although machine-learning methods are widely used to predict domain boundary, these approaches often ignore long-range interactions among residues, which have been proven to improve the prediction performance. However, how to simultaneously model the local and global interactions to further improve domain boundary prediction is still a challenging problem.

RESULTS

This article employs a hybrid deep learning method that combines convolutional neural network and gate recurrent units' models for domain boundary prediction. It not only captures the local and non-local interactions, but also fuses these features for prediction. Additionally, we adopt balanced Random Forest for classification to deal with high imbalance of samples and high dimensions of deep features. Experimental results show that our proposed approach (DNN-Dom) outperforms existing machine-learning-based methods for boundary prediction. We expect that DNN-Dom can be useful for assisting protein structure and function prediction.

AVAILABILITY AND IMPLEMENTATION

The method is available as DNN-Dom Server at http://isyslab.info/DNN-Dom/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Molecular characterization of Bu-1 and TLR2 gene in Haringhata Black chicken

Haringhata Black is the only registered indigenous poultry genetic resource of West Bengal till date. Molecular characterization of HB revealed that Bu-1 to be highly glycoylated transmembrane protein unlike mammalian Bu-1, whereas TLR2 of HB chicken was observed to be rich in Leucine rich repeat. HB chicken was observed to be genetically close to chicken of Japan, while distant to chicken breed of UK and Chicago. Avian species wise evolution study indicates genetic closeness of HB chicken with turkey. Differential mRNA expression profile for the immune response genes (TLR2, TLR4 and Bu1 gene) were studied for HB chicken with respect to other chicken breed and poultry birds, which reveals that HB chicken were better in terms of B cell mediated immunity and hence better response to vaccination. Hence HB chicken is one of the best poultry genetic resources to be reared under backyard system where biosecurity measures are almost lacking.

Bacteriophage φEf11 ORF28 Endolysin, a Multifunctional Lytic Enzyme with Properties Distinct from All Other Identified Enterococcus faecalis Phage Endolysins

ϕEf11 is a temperate Siphoviridae bacteriophage that infects strains of Enterococcus faecalis The ϕEf11 genome, encompassing 65 open reading frames (ORFs), is contained within 42,822 bp of DNA. Within this genome, a module of six lysis-related genes was identified. Based upon sequence homology, one of these six genes, ORF28, was predicted to code for an N-acetylmuramoyl-l-alanine amidase endolysin of 46.133 kDa, composed of 421 amino acids. The PCR-amplified ORF28 was cloned and expressed, and the resulting gene product was affinity purified to homogeneity. The purified protein was obtained from a fusion protein that exhibited a molecular mass of 72.5 kDa, consistent with a 46.1-kDa protein combined with a fused 26.5-kDa glutathione S-transferase tag. It produced rapid, profound lysis in E. faecalis populations and was active against 73 of 103 (71%) E. faecalis strains tested. In addition, it caused substantial destruction of E. faecalis biofilms. The lysin was quite stable, retaining its activity for three years in refrigerated storage, was stable over a wide range of pHs, and was unaffected by the presence of a reducing agent; however, it was inhibited by increasing concentrations of Ca²⁺ Liquid chromatography-mass spectrometry analysis of E. faecalis cell wall digestion products produced by the ORF28 endolysin indicated that the lysin acted as an N-acetylmuramidase, an endo-β-N-acetylglucosaminidase, and an endopeptidase, rather than an N-acetylmuramoyl-l-alanine amidase. The ϕEf11 ORF28 lysin shared 10% to 37% amino acid identity with the lytic enzymes of all other characterized E. faecalis bacteriophages.IMPORTANCE The emergence of multidrug-resistant pathogenic microorganisms has brought increasing attention to the urgent need for the development of alternative antimicrobial strategies. One such alternative to conventional antibiotics employs lytic enzymes (endolysins) that are produced by bacteriophages in the course of lytic infection. During lytic infection by a bacteriophage, these enzymes hydrolyze the cell wall peptidoglycan, resulting in the lysis of the host cell. However, external endolysin application can result in lysis from without. In this study, we have cloned, expressed, purified, and characterized an endolysin produced by a bacteriophage infecting strains of Enterococcus faecalis The lysin is broadly active against most of the tested E. faecalis strains and exhibits multifunctional enzymatic specificities that differ from all other characterized endolysins produced by E. faecalis bacteriophages.

ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly

We develop a hierarchical pipeline, ThreaDomEx, for both continuous domain (CD) and discontinuous domain (DCD) structure predictions. Starting from a query sequence, ThreaDomEx first threads it through the PDB to identify multiple structure templates, where a profile of domain conservation score (DC-score) is derived for domain-segment assignment. To further detect DCDs that consist of separated segments along the sequence, a boundary-clustering algorithm is used to refine the DCD-linker locations. In case that the templates do not contain DCDs, a domain-segment assembly process, guided by symmetry comparison, is applied for further DCD detections. ThreaDomEx was tested a set of 1111 proteins and achieved a normalized domain overlap score of 89.3% compared to experimental data, which is significantly higher than other state-of-the-art methods. It also recalls 26.7% of DCDs with 72.7% precision on the proteins for which threading failed to detect any DCDs. The server provides facilities for users to interactively refine the domain models by adjusting DC-score threshold, deleting and adding domain linkers, and assembling domain segments, which are particularly helpful for the hard targets for which current methods have a low accuracy while human-expert knowledge and experimental insights can be used for refining models. ThreaDomEX server is available at http://zhanglab.ccmb.med.umich.edu/ThreaDomEx.

Pirin: A novel redox-sensitive modulator of primary and secondary metabolism in Streptomyces

Pirins are evolutionarily conserved iron-containing proteins that are found in all kingdoms of life, and have been implicated in diverse molecular processes, mostly associated with cellular stress. In the present study, we started from the evidence that the insertional inactivation of pirin-like gene SAM23877_RS18305 (pirA) by ΦC31 Att/Int system-based vectors in spiramycin-producing strain Streptomyces ambofaciens ATCC 23877 resulted in marked effects on central carbon and energy metabolism gene expression, high sensitivity to oxidative injury and repression of polyketide antibiotic production. By using integrated transcriptomic, proteomic and metabolite profiling, together with genetic complementation, we here show that most of these effects could be traced to the inability of the pirA-defective strain to modulate beta-oxidation pathway, leading to an unbalanced supply of precursor monomers for polyketide biosynthesis. Indeed, in silico protein-protein interaction modeling and in vitro experimental validation allowed us to demonstrate that PirA is a novel redox-sensitive negative modulator of very long-chain acyl-CoA dehydrogenase, which catalyzes the first committed step of the beta-oxidation pathway.

Structural studies and molecular dynamics simulations suggest a processive mechanism of exolytic lytic transglycosylase from Campylobacter jejuni

The bacterial soluble lytic transglycosylase (LT) breaks down the peptidoglycan (PG) layer during processes such as cell division. We present here crystal structures of the soluble LT Cj0843 from Campylobacter jejuni with and without bulgecin A inhibitor in the active site. Cj0843 has a doughnut shape similar but not identical to that of E. coli SLT70. The C-terminal catalytic domain is preceded by an L-domain, a large helical U-domain, a flexible linker, and a small N-terminal NU-domain. The flexible linker allows the NU-domain to reach over and complete the circular shape, using residues conserved in the Epsilonproteobacteria LT family. The inner surface of the Cj0843 doughnut is mostly positively charged including a pocket that has 8 Arg/Lys residues. Molecular dynamics simulations with PG strands revealed a potential functional role for this pocket in anchoring the negatively charged terminal tetrapeptide of the PG during several steps in the reaction including homing and aligning the PG strand for exolytic cleavage, and subsequent ratcheting of the PG strand to enhance processivity in degrading PG strands.

Fast H-DROP: A thirty times accelerated version of H-DROP for interactive SVM-based prediction of helical domain linkers

Efficient and rapid prediction of domain regions from amino acid sequence information alone is often required for swift structural and functional characterization of large multi-domain proteins. Here we introduce Fast H-DROP, a thirty times accelerated version of our previously reported H-DROP (Helical Domain linker pRediction using OPtimal features), which is unique in specifically predicting helical domain linkers (boundaries). Fast H-DROP, analogously to H-DROP, uses optimum features selected from a set of 3000 ones by combining a random forest and a stepwise feature selection protocol. We reduced the computational time from 8.5 min per sequence in H-DROP to 14 s per sequence in Fast H-DROP on an 8 Xeon processor Linux server by using SWISS-PROT instead of Genbank non-redundant (nr) database for generating the PSSMs. The sensitivity and precision of Fast H-DROP assessed by cross-validation were 33.7 and 36.2%, which were merely ~2% lower than that of H-DROP. The reduced computational time of Fast H-DROP, without affecting prediction performances, makes it more interactive and user-friendly. Fast H-DROP and H-DROP are freely available from http://domserv.lab.tuat.ac.jp/ .

Functional Screening of Hydrolytic Activities Reveals an Extremely Thermostable Cellulase from a Deep-Sea Archaeon

Extreme habitats serve as a source of enzymes that are active under extreme conditions and are candidates for industrial applications. In this work, six large-insert mixed genomic libraries were screened for hydrolase activities in a broad temperature range (8-70°C). Among a variety of hydrolytic activities, one fosmid clone, derived from a library of pooled isolates of hyperthermophilic archaea from deep sea vents, displayed hydrolytic activity on carboxymethyl cellulose substrate plates at 70°C but not at lower temperatures. Sequence analysis of the fosmid insert revealed a gene encoding a novel glycoside hydrolase family 12 (GHF12) endo-1,4-β-glucanase, termed Cel12E. The enzyme shares 45% sequence identity with a protein from the archaeon Thermococcus sp. AM4 and displays a unique multidomain architecture. Biochemical characterization of Cel12E revealed a remarkably thermostable protein, which appears to be of archaeal origin. The enzyme displayed maximum activity at 92°C and was active on a variety of linear 1,4-β-glucans like carboxymethyl cellulose, β-glucan, lichenan, and phosphoric acid swollen cellulose. The protein is able to bind to various insoluble β-glucans. Product pattern analysis indicated that Cel12E is an endo-cleaving β-glucanase. Cel12E expands the toolbox of hyperthermostable archaeal cellulases with biotechnological potential.

Bacterial expression and re-engineering of Gaussia princeps luciferase and its use as a reporter protein

Bioluminescence, the generation of visible light in a living organism, is widely observed in nature, and a large variety of bioluminescent proteins have been discovered and characterized. Luciferase is a generic term for bioluminescent enzymes that catalyze the emission of light through the oxidization of a luciferin (also a generic term). Luciferase are not necessarily evolutionary related and do not share sequence or structural similarities. Some luciferases, such as those from fireflies and Renilla, have been thoroughly characterized and are being used in a wide range of applications in bio-imaging. Gaussia luciferase (GLuc) from the marine copepod Gaussia princeps is the smallest known luciferase, and it is attracting much attention as a potential reporter protein. GLuc identification is relatively recent, and its structure and its biophysical properties remain to be fully characterized. Here, we review the bacterial production of natively folded GLuc with special emphasis on its disulfide bond formation and the re-engineering of its bioluminescence properties. We also compare the bioluminescent properties under a strictly controlled in vitro condition of selected GLuc's variants using extensively purified proteins with native disulfide bonds. Furthermore, we discuss and predict the domain structure and location of the catalytic core based on literature and on bioinformatics analysis. Finally, we review some examples of GLuc's emerging use in biomolecular imaging and biochemical assay systems.

Factor VIII Interacts with the Endocytic Receptor Low-density Lipoprotein Receptor-related Protein 1 via an Extended Surface Comprising "Hot-Spot" Lysine Residues

Lysine residues are implicated in driving the ligand binding to the LDL receptor family. However, it has remained unclear how specificity is regulated. Using coagulation factor VIII as a model ligand, we now study the contribution of individual lysine residues in the interaction with the largest member of the LDL receptor family, low-density lipoprotein receptor-related protein (LRP1). Using hydrogen-deuterium exchange mass spectrometry (HDX-MS) and SPR interaction analysis on a library of lysine replacement variants as two independent approaches, we demonstrate that the interaction between factor VIII (FVIII) and LRP1 occurs over an extended surface containing multiple lysine residues. None of the individual lysine residues account completely for LRP1 binding, suggesting an additive binding model. Together with structural docking studies, our data suggest that FVIII interacts with LRP1 via an extended surface of multiple lysine residues that starts at the bottom of the C1 domain and winds around the FVIII molecule.

Protein inter-domain linker prediction using Random Forest and amino acid physiochemical properties

BACKGROUND

Protein chains are generally long and consist of multiple domains. Domains are distinct structural units of a protein that can evolve and function independently. The accurate prediction of protein domain linkers and boundaries is often regarded as the initial step of protein tertiary structure and function predictions. Such information not only enhances protein-targeted drug development but also reduces the experimental cost of protein analysis by allowing researchers to work on a set of smaller and independent units. In this study, we propose a novel and accurate domain-linker prediction approach based on protein primary structure information only. We utilize a nature-inspired machine-learning model called Random Forest along with a novel domain-linker profile that contains physiochemical and domain-linker information of amino acid sequences.

RESULTS

The proposed approach was tested on two well-known benchmark protein datasets and achieved 68% sensitivity and 99% precision, which is better than any existing protein domain-linker predictor. Without applying any data balancing technique such as class weighting and data re-sampling, the proposed approach is able to accurately classify inter-domain linkers from highly imbalanced datasets.

CONCLUSION

Our experimental results prove that the proposed approach is useful for domain-linker identification in highly imbalanced single- and multi-domain proteins.

H-DROP: an SVM based helical domain linker predictor trained with features optimized by combining random forest and stepwise selection

Domain linker prediction is attracting much interest as it can help identifying novel domains suitable for high throughput proteomics analysis. Here, we report H-DROP, an SVM-based Helical Domain linker pRediction using OPtimal features. H-DROP is, to the best of our knowledge, the first predictor for specifically and effectively identifying helical linkers. This was made possible first because a large training dataset became available from IS-Dom, and second because we selected a small number of optimal features from a huge number of potential ones. The training helical linker dataset, which included 261 helical linkers, was constructed by detecting helical residues at the boundary regions of two independent structural domains listed in our previously reported IS-Dom dataset. 45 optimal feature candidates were selected from 3,000 features by random forest, which were further reduced to 26 optimal features by stepwise selection. The prediction sensitivity and precision of H-DROP were 35.2 and 38.8%, respectively. These values were over 10.7% higher than those of control methods including our previously developed DROP, which is a coil linker predictor, and PPRODO, which is trained with un-differentiated domain boundary sequences. Overall, these results indicated that helical linkers can be predicted from sequence information alone by using a strictly curated training data set for helical linkers and carefully selected set of optimal features. H-DROP is available at http://domserv.lab.tuat.ac.jp.

IS-Dom: a dataset of independent structural domains automatically delineated from protein structures

Protein domains that can fold in isolation are significant targets in diverse area of proteomics research as they are often readily analyzed by high-throughput methods. Here, we report IS-Dom, a dataset of Independent Structural Domains (ISDs) that are most likely to fold in isolation. IS-Dom was constructed by filtering domains from SCOP, CATH, and DomainParser using quantitative structural measures, which were calculated by estimating inter-domain hydrophobic clusters and hydrogen bonds from the full length protein's atomic coordinates. The ISD detection protocol is fully automated, and all of the computed interactions are stored in the server which enables rapid update of IS-Dom. We also prepared a standard IS-Dom using parameters optimized by maximizing the Youden's index. The standard IS-Dom, contained 54,860 ISDs, of which 25.5 % had high sequence identity and termini overlap with a Protein Data Bank (PDB) cataloged sequence and are thus experimentally shown to fold in isolation [coined autonomously folded domain (AFDs)]. Furthermore, our ISD detection protocol missed less than 10 % of the AFDs, which corroborated our protocol's ability to define structural domains that are able to fold independently. IS-Dom is available through the web server ( http://domserv.lab.tuat.ac.jp/IS-Dom.html ), and users can either, download the standard IS-Dom dataset, construct their own IS-Dom by interactively varying the parameters, or assess the structural independence of newly defined putative domains.

Structure of LdtMt2, an L,D-transpeptidase from Mycobacterium tuberculosis

The transpeptidase LtdMt2 catalyzes the formation of the (3-3) cross-links characteristic of the peptidoglycan layer in the Mycobacterium tuberculosis cell wall. Bioinformatics analysis suggests that the extramembrane part of the enzyme consists of three domains: two smaller domains (denoted as A and B domains) and a transpeptidase domain (the C domain) at the C-terminus. The crystal structures of two fragments comprising the AB domains and the BC domains have been determined. The structure of the BC module, which was determined to 1.86 Å resolution using Se-SAD phasing, consists of the B domain with an immunoglobulin-related fold and the catalytic domain belonging to the ErfK/YbiS/YbnG fold family. The structure of the AB-domain fragment, which was solved by molecular replacement to 1.45 Å resolution, reveals that despite a lack of overall sequence identity the A domain is structurally very similar to the B domain. Combining the structures of the two fragments provides a view of the complete three-domain extramembrane part of LdtMt2 and shows that the protein extends at least 80-100 Å from the plasma membrane into the peptidoglycan layer and thus defines the maximal distance at which cross-links are formed by this enzyme. The LdtMt-related transpeptidases contain one or two immunoglobulin domains, which suggests that these might serve as extender units to position the catalytic domain at an appropriate distance from the membrane in the peptidoglycan layer.

Crystallization and preliminary diffraction analysis of the catalytic domain of major extracellular endoglucanase from Xanthomonas campestris pv. campestris

Cellulases, such as endoglucanases, exoglucanases and β-glucosidases, are important enzymes used in the process of enzymatic hydrolysis of plant biomass. The bacteria Xanthomonas campestris pv. campestris expresses a large number of hydrolases and the major endoglucanase (XccEG), a member of glycoside hydrolase family 5 (GH5), is the most strongly secreted extracellularly. In this work, the native XccEG was purified from the extracellular extract and crystallization assays were performed on its catalytic domain. A complete data set was collected on an in-house X-ray source. The crystal diffracted to 2.7 Å resolution and belonged to space group C2, with unit-cell parameters a = 174.66, b = 141.53, c = 108.00 Å, β = 110.49°. The Matthews coefficient suggests a solvent content of 70.1% and the presence of four protein subunits in the asymmetric unit.

Prediction of protein domain boundaries from inverse covariances

It has been known even since relatively few structures had been solved that longer protein chains often contain multiple domains, which may fold separately and play the role of reusable functional modules found in many contexts. In many structural biology tasks, in particular structure prediction, it is of great use to be able to identify domains within the structure and analyze these regions separately. However, when using sequence data alone this task has proven exceptionally difficult, with relatively little improvement over the naive method of choosing boundaries based on size distributions of observed domains. The recent significant improvement in contact prediction provides a new source of information for domain prediction. We test several methods for using this information including a kernel smoothing-based approach and methods based on building alpha-carbon models and compare performance with a length-based predictor, a homology search method and four published sequence-based predictors: DOMCUT, DomPRO, DLP-SVM, and SCOOBY-DOmain. We show that the kernel-smoothing method is significantly better than the other ab initio predictors when both single-domain and multidomain targets are considered and is not significantly different to the homology-based method. Considering only multidomain targets the kernel-smoothing method outperforms all of the published methods except DLP-SVM. The kernel smoothing method therefore represents a potentially useful improvement to ab initio domain prediction.

Molecular Characterization and SNP Detection of CD14 Gene of Crossbred Cattle

CD14 is an important molecule for innate immunity that can act against a wide range of pathogens. The present paper has characterized CD14 gene of crossbred (CB) cattle (Bos indicus×Bos taurus). Cloning and sequence analysis of CD14 cDNA revealed 1119 nucleotide long open reading frame encoding 373 amino acids protein and 20 amino acids signal peptide. CB cattle CD14 gene exhibited a high percentage of nucleotide identity (59.3–98.1%) with the corresponding mammalian homologs. Cattle and buffalo appear to have diverged from a common ancestor in phylogenetic analysis. 25 SNPs with 17 amino acid changes were newly reported and the site for mutational hot-spot was detected in CB cattle CD14 gene. Non-synonymous substitutions exceeding synonymous substitutions indicate the evolution of this protein through positive selection among domestic animals. Predicted protein structures obtained from deduced amino acid sequence indicated CB cattle CD14 molecule to be a receptor with horse shoe-shaped structure. The sites for LPS binding, LPS signalling, leucine-rich repeats, putative N-linked glycosylation, O-linked glycosylation, glycosyl phosphatidyl inositol anchor, disulphide bridges, alpha helix, beta strand, leucine rich nuclear export signal, leucine zipper and domain linker were predicted. Most of leucine and cysteine residues remain conserved across the species.

SH3YL1 regulates dorsal ruffle formation by a novel phosphoinositide-binding domain

Reversible interactions between cytosolic proteins and membrane lipids such as phosphoinositides play important roles in membrane morphogenesis driven by actin polymerization. In this paper, we identify a novel lipid-binding module, which we call the SYLF domain (after the SH3YL1, Ysc84p/Lsb4p, Lsb3p, and plant FYVE proteins that contain it), that is highly conserved from bacteria to mammals. SH3YL1 (SH3 domain containing Ysc84-like 1) strongly bound to phosphatidylinositol 3,4,5-triphosphate (PI(3,4,5)P(3)) and several D5-phosphorylated phosphoinositides through its SYLF domain and was localized to circular dorsal ruffles induced by platelet-derived growth factor stimulation. Interestingly, SHIP2 (the PI(3,4,5)P(3) 5-phosphatase, src-homology 2-containing inositol-5-phosphatase 2) was identified as a binding partner of SH3YL1, and knockdown of these proteins significantly suppressed dorsal ruffle formation. Phosphatidylinositol 3,4-bisphosphate (PI(3,4)P(2)), which is mainly synthesized from PI(3,4,5)P(3) by the action of SHIP2, was enriched in dorsal ruffles, and PI(3,4)P(2) synthesis strongly correlated with formation of the circular membrane structure. These results provide new insight into the molecular mechanism of dorsal ruffle formation and its regulation by phosphoinositide metabolism.

Functional specialization in nucleotide sugar transporters occurred through differentiation of the gene cluster EamA (DUF6) before the radiation of Viridiplantae

Background

The drug/metabolite transporter superfamily comprises a diversity of protein domain families with multiple functions including transport of nucleotide sugars. Drug/metabolite transporter domains are contained in both solute carrier families 30, 35 and 39 proteins as well as in acyl-malonyl condensing enzyme proteins. In this paper, we present an evolutionary analysis of nucleotide sugar transporters in relation to the entire superfamily of drug/metabolite transporters that considers crucial intra-protein duplication events that have shaped the transporters. We use a method that combines the strengths of hidden Markov models and maximum likelihood to find relationships between drug/metabolite transporter families, and branches within families.

Results

We present evidence that the triose-phosphate transporters, domain unknown function 914, uracil-diphosphate glucose-N-acetylglucosamine, and nucleotide sugar transporter families have evolved from a domain duplication event before the radiation of Viridiplantae in the EamA family (previously called domain unknown function 6). We identify previously unknown branches in the solute carrier 30, 35 and 39 protein families that emerged simultaneously as key physiological developments after the radiation of Viridiplantae, including the "35C/E" branch of EamA, which formed in the lineage of T. adhaerens (Animalia). We identify a second cluster of DMTs, called the domain unknown function 1632 cluster, which has non-cytosolic N- and C-termini, and thus appears to have been formed from a different domain duplication event. We identify a previously uncharacterized motif, G-X(6)-G, which is overrepresented in the fifth transmembrane helix of C-terminal domains. We present evidence that the family called fatty acid elongases are homologous to transporters, not enzymes as had previously been thought.

Conclusions

The nucleotide sugar transporters families were formed through differentiation of the gene cluster EamA (domain unknown function 6) before Viridiplantae, showing for the first time the significance of EamA.

DROP: an SVM domain linker predictor trained with optimal features selected by random forest

MOTIVATION

Biologically important proteins are often large, multidomain proteins, which are difficult to characterize by high-throughput experimental methods. Efficient domain/boundary predictions are thus increasingly required in diverse area of proteomics research for computationally dissecting proteins into readily analyzable domains.

RESULTS

We constructed a support vector machine (SVM)-based domain linker predictor, DROP (Domain linker pRediction using OPtimal features), which was trained with 25 optimal features. The optimal combination of features was identified from a set of 3000 features using a random forest algorithm complemented with a stepwise feature selection. DROP demonstrated a prediction sensitivity and precision of 41.3 and 49.4%, respectively. These values were over 19.9% higher than those of control SVM predictors trained with non-optimized features, strongly suggesting the efficiency of our feature selection method. In addition, the mean NDO-Score of DROP for predicting novel domains in seven CASP8 FM multidomain proteins was 0.760, which was higher than any of the 12 published CASP8 DP servers. Overall, these results indicate that the SVM prediction of domain linkers can be improved by identifying optimal features that best distinguish linker from non-linker regions.

SAHG, a comprehensive database of predicted structures of all human proteins

Most proteins from higher organisms are known to be multi-domain proteins and contain substantial numbers of intrinsically disordered (ID) regions. To analyse such protein sequences, those from human for instance, we developed a special protein-structure-prediction pipeline and accumulated the products in the Structure Atlas of Human Genome (SAHG) database at http://bird.cbrc.jp/sahg. With the pipeline, human proteins were examined by local alignment methods (BLAST, PSI-BLAST and Smith–Waterman profile–profile alignment), global–local alignment methods (FORTE) and prediction tools for ID regions (POODLE-S) and homology modeling (MODELLER). Conformational changes of protein models upon ligand-binding were predicted by simultaneous modeling using templates of apo and holo forms. When there were no suitable templates for holo forms and the apo models were accurate, we prepared holo models using prediction methods for ligand-binding (eF-seek) and conformational change (the elastic network model and the linear response theory). Models are displayed as animated images. As of July 2010, SAHG contains 42 581 protein-domain models in approximately 24 900 unique human protein sequences from the RefSeq database. Annotation of models with functional information and links to other databases such as EzCatDB, InterPro or HPRD are also provided to facilitate understanding the protein structure-function relationships.