Annotating activation/inhibition relationships to protein-protein interactions using gene ontology relations

Background

Signaling pathways can be reconstructed by identifying ‘effect types’ (i.e. activation/inhibition) of protein-protein interactions (PPIs). Effect types are composed of ‘directions’ (i.e. upstream/downstream) and ‘signs’ (i.e. positive/negative), thereby requiring directions as well as signs of PPIs to predict signaling events from PPI networks. Here, we propose a computational method for systemically annotating effect types to PPIs using relations between functional information of proteins.

Results

We used regulates, positively regulates, and negatively regulates relations in Gene Ontology (GO) to predict directions and signs of PPIs. These relations indicate both directions and signs between GO terms so that we can project directions and signs between relevant GO terms to PPIs. Independent test results showed that our method is effective for predicting both directions and signs of PPIs. Moreover, our method outperformed a previous GO-based method that did not consider the relations between GO terms. We annotated effect types to human PPIs and validated several highly confident effect types against literature. The annotated human PPIs are available in Additional file 2 to aid signaling pathway reconstruction and network biology research.

Conclusions

We annotated effect types to PPIs by using regulates, positively regulates, and negatively regulates relations in GO. We demonstrated that those relations are effective for predicting not only signs, but also directions of PPIs. The usefulness of those relations suggests their potential applications to other types of interactions such as protein-DNA interactions.

     

New resources for functional analysis of omics data for the genus <Emphasis Type="Italic">Aspergillus</Emphasis>

Background

Detailed and comprehensive genome annotation can be considered a prerequisite for effective analysis and interpretation of omics data. As such, Gene Ontology (GO) annotation has become a well accepted framework for functional annotation. The genus Aspergillus comprises fungal species that are important model organisms, plant and human pathogens as well as industrial workhorses. However, GO annotation based on both computational predictions and extended manual curation has so far only been available for one of its species, namely A. nidulans.

Results

Based on protein homology, we mapped 97% of the 3,498 GO annotated A. nidulans genes to at least one of seven other Aspergillus species: A. niger, A. fumigatus, A. flavus, A. clavatus, A. terreus, A. oryzae and Neosartorya fischeri. GO annotation files compatible with diverse publicly available tools have been generated and deposited online. To further improve their accessibility, we developed a web application for GO enrichment analysis named FetGOat and integrated GO annotations for all Aspergillus species with public genome sequences. Both the annotation files and the web application FetGOat are accessible via the Broad Institute's website (http://www.broadinstitute.org/fetgoat/index.html). To demonstrate the value of those new resources for functional analysis of omics data for the genus Aspergillus, we performed two case studies analyzing microarray data recently published for A. nidulans, A. niger and A. oryzae.

Conclusions

We mapped A. nidulans GO annotation to seven other Aspergilli. By depositing the newly mapped GO annotation online as well as integrating it into the web tool FetGOat, we provide new, valuable and easily accessible resources for omics data analysis and interpretation for the genus Aspergillus. Furthermore, we have given a general example of how a well annotated genome can help improving GO annotation of related species to subsequently facilitate the interpretation of omics data.

     

FGsub: <Emphasis Type="Italic">Fusarium graminearum</Emphasis> protein subcellular localizations predicted from primary structures

Background

The fungal pathogen Fusarium graminearum (telomorph Gibberella zeae) is the causal agent of several destructive crop diseases, where a set of genes usually work in concert to cause diseases to crops. To function appropriately, the F. graminearum proteins inside one cell should be assigned to different compartments, i.e. subcellular localizations. Therefore, the subcellular localizations of F. graminearum proteins can provide insights into protein functions and pathogenic mechanisms of this destructive pathogen fungus. Unfortunately, there are no subcellular localization information for F. graminearum proteins available now. Computational approaches provide an alternative way to predicting F. graminearum protein subcellular localizations due to the expensive and time-consuming biological experiments in lab.

Results

In this paper, we developed a novel predictor, namely FGsub, to predict F. graminearum protein subcellular localizations from the primary structures. First, a non-redundant fungi data set with subcellular localization annotation is collected from UniProtKB database and used as training set, where the subcellular locations are classified into 10 groups. Subsequently, Support Vector Machine (SVM) is trained on the training set and used to predict F. graminearum protein subcellular localizations for those proteins that do not have significant sequence similarity to those in training set. The performance of SVMs on training set with 10-fold cross-validation demonstrates the efficiency and effectiveness of the proposed method. In addition, for F. graminearum proteins that have significant sequence similarity to those in training set, BLAST is utilized to transfer annotations of homologous proteins to uncharacterized F. graminearum proteins so that the F. graminearum proteins are annotated more comprehensively.

Conclusions

In this work, we present FGsub to predict F. graminearum protein subcellular localizations in a comprehensive manner. We make four fold contributions to this filed. First, we present a new algorithm to cope with imbalance problem that arises in protein subcellular localization prediction, which can solve imbalance problem and avoid false positive results. Second, we design an ensemble classifier which employs feature selection to further improve prediction accuracy. Third, we use BLAST to complement machine learning based methods, which enlarges our prediction coverage. Last and most important, we predict the subcellular localizations of 12786 F. graminearum proteins, which provide insights into protein functions and pathogenic mechanisms of this destructive pathogen fungus.

     

A combined approach for genome wide protein function annotation/prediction

Background

Today large scale genome sequencing technologies are uncovering an increasing amount of new genes and proteins, which remain uncharacterized. Experimental procedures for protein function prediction are low throughput by nature and thus can't be used to keep up with the rate at which new proteins are discovered. On the other hand, proteins are the prominent stakeholders in almost all biological processes, and therefore the need to precisely know their functions for a better understanding of the underlying biological mechanism is inevitable. The challenge of annotating uncharacterized proteins in functional genomics and biology in general motivates the use of computational techniques well orchestrated to accurately predict their functions.

Methods

We propose a computational flow for the functional annotation of a protein able to assign the most probable functions to a protein by aggregating heterogeneous information. Considered information include: protein motifs, protein sequence similarity, and protein homology data gathered from interacting proteins, combined with data from highly similar non-interacting proteins (hereinafter called Similactors). Moreover, to increase the predictive power of our model we also compute and integrate term specific relationships among functional terms based on Gene Ontology (GO).

Results

We tested our method on Saccharomyces Cerevisiae and Homo sapiens species proteins. The aggregation of different structural and functional evidence with GO relationships outperforms, in terms of precision and accuracy of prediction than the other methods reported in literature. The predicted precision and accuracy is 100% for more than half of the input set for both species; overall, we obtained 85.38% precision and 81.95% accuracy for Homo sapiens and 79.73% precision and 80.06% accuracy for Saccharomyces Cerevisiae species proteins.

     

A constitutive expression system for <Emphasis Type="Italic">Pichia pastoris</Emphasis> based on the <Emphasis Type="Italic">PGK1</Emphasis> promoter

Objectives

To develop a new vector for constitutive expression in Pichia pastoris based on the endogenous glycolytic PGK1 promoter.

Results

P. pastoris plasmids bearing at least 415 bp of PGK1 promoter sequences can be used to drive plasmid integration by addition at this locus without affecting cell growth. Based on this result, a new P. pastoris integrative vector, pPICK2, was constructed bearing some features that facilitate protein production in this yeast: a ~620 bp PGK1 promoter fragment with three options of restriction sites for plasmid linearization prior to yeast transformation: a codon-optimized α-factor secretion signal, a new polylinker, and the kan marker for vector propagation in bacteria and selection of yeast transformants.

Conclusions

A new constitutive vector for P. pastoris represents an alternative platform for recombinant protein production and metabolic engineering purposes.

     

A versatile <Emphasis Type="Italic">Trichoderma reesei</Emphasis> expression system for the production of heterologous proteins

Objectives

To develop a versatile Trichoderma reesei (teleomorph Hypocrea jecorina) expression system for the high-purity production of heterologous proteins.

Results

The versatile T. reesei expression system is based on xyn1 and xyn2 promoters, A824V transition in XYRI, and a bicomponent carbon source strategy. Red fluorescent protein gene rfp and alkaline endoglucanase EGV gene egv3 from Humicola insolens were used as reporter genes to test our versatile expression system

Conclusions

The versatile T. reesei expression system can be applied to produce heterologous proteins with high purity and high yield.

     

A novel Ffu fusion system for secretory expression of heterologous proteins in <Emphasis Type="Italic">Escherichia coli</Emphasis>

Background

The high level of excretion and rapid folding ability of β-fructofuranosidase (β-FFase) in Escherichia coli has suggested that β-FFase from Arthrobacter arilaitensis NJEM01 can be developed as a fusion partner.

Methods

Based on the modified Wilkinson and Harrison algorithm and the preliminary verification of the solubility-enhancing ability of β-FFase truncations, three β-FFase truncations (i.e., Ffu209, Ffu217, and Ffu312) with a native signal peptide were selected as novel Ffu fusion tags. Four difficult-to-express protein models; i.e., CARDS TX, VEGFR-2, RVs and Omp85 were used in the assessment of Ffu fusion tags.

Results

The expression levels and solubility of each protein were markedly enhanced by the Ffu fusion system. Each protein had a favorable Ffu tag. The Ffu fusion tags performed preferably when compared with the well-known fusion tags MBP and NusA. Strikingly, it was confirmed that Ffu fusion proteins were secreted into the periplasm by the periplasmic analysis and N-amino acid sequence analysis. Further, efficient excretion of HV3 with defined anti-thrombin activity was obtained when it was fused with the Ffu312 tag. Moreover, HV3 remained soluble and demonstrated notable anti-thrombin activity after the removal of the Ffu312 tag by enterokinase.

Conclusions

Observations from this work not only complements fusion technologies, but also develops a novel and effective secretory system to solve key issues that include inclusion bodies and degradation when expressing heterologous proteins in E. coli, especially for proteins that require disulfide bond formation, eukaryotic-secreted proteins, and membrane-associated proteins.

     

The predictive performance of short-linear motif features in the prediction of calmodulin-binding proteins

Background

The prediction of calmodulin-binding (CaM-binding) proteins plays a very important role in the fields of biology and biochemistry, because the calmodulin protein binds and regulates a multitude of protein targets affecting different cellular processes. Computational methods that can accurately identify CaM-binding proteins and CaM-binding domains would accelerate research in calcium signaling and calmodulin function. Short-linear motifs (SLiMs), on the other hand, have been effectively used as features for analyzing protein-protein interactions, though their properties have not been utilized in the prediction of CaM-binding proteins.

Results

We propose a new method for the prediction of CaM-binding proteins based on both the total and average scores of known and new SLiMs in protein sequences using a new scoring method called sliding window scoring (SWS) as features for the prediction module. A dataset of 194 manually curated human CaM-binding proteins and 193 mitochondrial proteins have been obtained and used for testing the proposed model. The motif generation tool, Multiple EM for Motif Elucidation (MEME), has been used to obtain new motifs from each of the positive and negative datasets individually (the SM approach) and from the combined negative and positive datasets (the CM approach). Moreover, the wrapper criterion with random forest for feature selection (FS) has been applied followed by classification using different algorithms such as k-nearest neighbors (k-NN), support vector machines (SVM), naive Bayes (NB) and random forest (RF).

Conclusions

Our proposed method shows very good prediction results and demonstrates how information contained in SLiMs is highly relevant in predicting CaM-binding proteins. Further, three new CaM-binding motifs have been computationally selected and biologically validated in this study, and which can be used for predicting CaM-binding proteins.

     

Heterologous protein display on the cell surface of lactic acid bacteria mediated by the s-layer protein

Background

Previous studies have revealed that the C-terminal region of the S-layer protein from Lactobacillus is responsible for the cell wall anchoring, which provide an approach for targeting heterologous proteins to the cell wall of lactic acid bacteria (LAB). In this study, we developed a new surface display system in lactic acid bacteria with the C-terminal region of S-layer protein SlpB of Lactobacillus crispatus K2-4-3 isolated from chicken intestine.

Results

Multiple sequence alignment revealed that the C-terminal region (LcsB) of Lb. crispatus K2-4-3 SlpB had a high similarity with the cell wall binding domains S_A and CbsA of Lactobacillus acidophilus and Lb. crispatus. To evaluate the potential application as an anchoring protein, the green fluorescent protein (GFP) or beta-galactosidase (Gal) was fused to the N-terminus of the LcsB region, and the fused proteins were successfully produced in Escherichia coli, respectively. After mixing them with the non-genetically modified lactic acid bacteria cells, the fused GFP-LcsB and Gal-LcsB were functionally associated with the cell surface of various lactic acid bacteria tested. In addition, the binding capacity could be improved by SDS pretreatment. Moreover, both of the fused proteins could simultaneously bind to the surface of a single cell. Furthermore, when the fused DNA fragment of gfp:lcsB was inserted into the Lactococcus lactis expression vector pSec:Leiss:Nuc, the GFP could not be secreted into the medium under the control of the nisA promoter. Western blot, in-gel fluorescence assay, immunofluorescence microscopy and SDS sensitivity analysis confirmed that the GFP was successfully expressed onto the cell surface of L. lactis with the aid of the LcsB anchor.

Conclusion

The LcsB region can be used as a functional scaffold to target the heterologous proteins to the cell surfaces of lactic acid bacteria in vitro and in vivo, and has also the potential for biotechnological application.

     

Expression of a high sweetness and heat-resistant mutant of sweet-tasting protein,monellin, in <Emphasis Type="Italic">Pichia pastoris</Emphasis> with a constitutive GAPDH promoter and modified <Emphasis Type="Italic">N</Emphasis>-terminus

Objectives

To improve the stability and sweetness of the sweet-tasting protein, monellin, by using site-directed mutagenesis and a Pichia pastoris expression system with a GAPDH constitutive promoter.

Results

Both wild-type and E2 N mutant of single-chain monellin gene were cloned into the PGAPZαA vector and expressed in Pichia pastoris. The majority of the secreted recombinant protein, at 0.15 g/l supernatant, was monellin. This was purified by Sephadex G50 chromatography. The sweetness threshold of wild-type and E2 N were 30 μg/ml and 20 μg/ml, respectively. Compared with the proteins expressed in Escherichia coli, the thermostability of both proteins was improved. The N-terminal sequence is determinative for the sweetness of the proteins expressed in yeast strains.

Conclusions

Site-directed mutagenesis, modification of the N-terminus of monellin, and without the need of methanol induction in P. pastoris expression system, indicate the possibility for large-scale production of this sweet-tasting protein.

     

Three-dimensional models of <Emphasis Type="Italic">Mycobacterium tuberculosis</Emphasis> proteins Rv1555, Rv1554 and their docking analyses with sildenafil,tadalafil, vardenafil drugs,suggest interference with quinol binding likely to affect protein’s function

Background

Earlier based on bioinformatics analyses, we had predicted the Mycobacterium tuberculosis (M.tb) proteins; Rv1555 and Rv1554, among the potential new tuberculosis drug targets. According to the ‘TB-drugome’ the Rv1555 protein is ‘druggable’ with sildenafil (Viagra), tadalafil (Cialis) and vardenafil (Levitra) drugs. In the present work, we intended to understand via computer modeling studies, how the above drugs are likely to inhibit the M.tb protein’s function.

Results

The three-dimensional computer models for M.tb proteins; Rv1555 and Rv1554 constructed on the template of equivalent membrane anchor subunits of the homologous E.coli quinol fumarate reductase respiratory protein complex, followed by drug docking analyses, suggested that the binding of above drugs interferes with quinol binding sites. Also, we experimentally observed the in-vitro growth inhibition of E.coli bacteria containing the homologous M.tb protein sequences with sildenafil and tadalafil drugs.

Conclusions

The predicted binding sites of the drugs is likely to affect the above M.tb proteins function as quinol binding is known to be essential for electron transfer function during anaerobic respiration in the homologous E.coli protein complex. Therefore, sildenafil and related drugs currently used in the treatment of male erectile dysfunction targeting the human phosphodiesterase 5 enzyme may be evaluated for their plausible role as repurposed drugs to treat human tuberculosis.

     

A <Emphasis Type="Italic">plant natriuretic peptide-like</Emphasis> gene in the bacterial pathogen <Emphasis Type="Italic">Xanthomonas axonopodis</Emphasis> may induce hyper-hydration in the plant host: a hypothesis of molecular mimicry

Background

Plant natriuretic peptides (PNPs) are systemically mobile molecules that regulate homeostasis at nanomolar concentrations. PNPs are up-regulated under conditions of osmotic stress and PNP-dependent processes include changes in ion transport and increases of H₂O uptake into protoplasts and whole tissue.

Presentation of the hypothesis

The bacterial citrus pathogen Xanthomonas axonopodis pv. Citri str. 306 contains a gene encoding a PNP-like protein. We hypothesise that this bacterial protein can alter plant cell homeostasis and thus is likely to represent an example of molecular mimicry that enables the pathogen to manipulate plant responses in order to bring about conditions favourable to the pathogen such as the induced plant tissue hyper-hydration seen in the wet edged lesions associated with Xanthomonas axonopodis infection.

Testing the hypothesis

We found a Xanthomonas axonopodis PNP-like protein that shares significant sequence similarity and identical domain organisation with PNPs. We also observed a significant excess of conserved residues between the two proteins within the domain previously identified as being sufficient to induce biological activity. Structural modelling predicts identical six stranded double-psi β barrel folds for both proteins thus supporting the hypothesis of similar modes of action. No significant similarity between the Xanthomonas axonopodis protein and other bacterial proteins from GenBank was found. Sequence similarity of the Xanthomonas axonopodis PNP-like protein with the Arabidopsis thaliana PNP (AtPNP-A), shared domain organisation and incongruent phylogeny suggest that the PNP-gene may have been acquired by the bacteria in an ancient lateral gene transfer event. Finally, activity of a recombinant Xanthomonas axonopodis protein in plant tissue and changes in symptoms induced by a Xanthomonas axonopodis mutant with a knocked-out PNP-like gene will be experimental proof of molecular mimicry.

Implication of the hypothesis

If the hypothesis is true, it could at least in part explain why the citrus pathogen Xanthomonas campestris that does not contain a PNP-like gene produces dry corky lesions while the closely related Xanthomonas axonopodis forms lesions with wet edges. It also suggests that genes typically found in the host, horizontally transferred or heterologous, can help to explain aspects of the physiology of the host-pathogen interactions.

     

<Emphasis Type="Italic">In silico</Emphasis> characterization and Molecular modeling of double-strand break repair protein <Emphasis Type="Italic">MRE11</Emphasis> from <Emphasis Type="Italic">Phoenix dactylifera</Emphasis> v deglet nour

Background

DNA double-strand breaks (DSBs) are highly cytotoxic and mutagenic. MRE11 plays an essential role in repairing DNA by cleaving broken ends through its 3′ to 5′ exonuclease and single-stranded DNA endonuclease activities.

Methods

The present study aimed to in silico characterization and molecular modeling of MRE11 from Phoenix dactylifera L cv deglet nour (DnMRE11) by various bioinformatic approaches. To identify DnMRE11 cDNA, assembled contigs from our cDNA libraries were analysed using the Blast2GO2.8 program.

Results

The DnMRE11 protein length was 726 amino acids. The results of HUMMER show that DnMRE11 is formed by three domains: the N-terminal core domain containing the nuclease and capping domains, the C-terminal half containing the DNA binding and coiled coil region. The structure of DnMRE11 is predicted using the Swiss-Model server, which contains the nuclease and capping domains. The obtained model was verified with the structure validation programs such as ProSA and QMEAN servers for reliability. Ligand binding studies using COACH indicated the interaction of DnMRE11 protein with two Mn²⁺ ions and dAMP. The ConSurf server predicted that residues of the active site and Nbs binding site have high conservation scores between plant species.

Conclusions

A model structure of DnMRE11 was constructed and validated with various bioinformatics programs which suggested the predicted model to be satisfactory. Further validation studies were conducted by COACH analysis for active site ligand prediction, and revealed the presence of six ligands binding sites and two ligands (2 Mn²⁺ and dAMP).

     

More than royal food - <Emphasis Type="Italic">Major royal jelly protein</Emphasis> genes in sexuals and workers of the honeybee <Emphasis Type="Italic">Apis mellifera</Emphasis>

Background

In the honeybee Apis mellifera, female larvae destined to become a queen are fed with royal jelly, a secretion of the hypopharyngeal glands of young nurse bees that rear the brood. The protein moiety of royal jelly comprises mostly major royal jelly proteins (MRJPs) of which the coding genes (mrjp1-9) have been identified on chromosome 11 in the honeybee’s genome.

Results

We determined the expression of mrjp1-9 among the honeybee worker caste (nurses, foragers) and the sexuals (queens (unmated, mated) and drones) in various body parts (head, thorax, abdomen). Specific mrjp expression was not only found in brood rearing nurse bees, but also in foragers and the sexuals.

Conclusions

The expression of mrjp1 to 7 is characteristic for the heads of worker bees, with an elevated expression of mrjp1-4 and 7 in nurse bees compared to foragers. Mrjp5 and 6 were higher in foragers compared to nurses suggesting functions in addition to those of brood food proteins. Furthermore, the expression of mrjp9 was high in the heads, thoraces and abdomen of almost all female bees, suggesting a function irrespective of body section. This completely different expression profile suggests mrjp9 to code for the most ancestral major royal jelly protein of the honeybee.

     

The promoter of filamentation (POF1) protein from <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis> is an ATPase involved in the protein quality control process

Background

The gene YCL047C, which has been renamed promoter of filamentation gene (POF1), has recently been described as a cell component involved in yeast filamentous growth. The objective of this work is to understand the molecular and biological function of this gene.

Results

Here, we report that the protein encoded by the POF1 gene, Pof1p, is an ATPase that may be part of the Saccharomyces cerevisiae protein quality control pathway. According to the results, Δpof1 cells showed increased sensitivity to hydrogen peroxide, tert-butyl hydroperoxide, heat shock and protein unfolding agents, such as dithiothreitol and tunicamycin. Besides, the overexpression of POF1 suppressed the sensitivity of Δpct1, a strain that lacks a gene that encodes a phosphocholine cytidylyltransferase, to heat shock. In vitro analysis showed, however, that the purified Pof1p enzyme had no cytidylyltransferase activity but does have ATPase activity, with catalytic efficiency comparable to other ATPases involved in endoplasmic reticulum-associated degradation of proteins (ERAD). Supporting these findings, co-immunoprecipitation experiments showed a physical interaction between Pof1p and Ubc7p (an ubiquitin conjugating enzyme) in vivo.

Conclusions

Taken together, the results strongly suggest that the biological function of Pof1p is related to the regulation of protein degradation.

     

PEGylation of cytochrome <Emphasis Type="Italic">c</Emphasis> at the level of lysine residues mediated by a microbial <Emphasis Type="Italic">trans</Emphasis>glutaminase

Objectives

To establish a method for microbial transglutaminase (mTG)-mediated PEGylation of proteins at the level of lysine (Lys) residues.

Results

Carboxybenzyl-glutaminyl–glycinyl-methoxypolyethylene glycol (CBZ-QG-mPEG) was prepared by introducing carboxybenzyl-glutaminyl-glycine (CBZ-QG) to mPEG amine. The analysis by Fourier transform infrared spectroscopy and SDS-PAGE showed that CBZ-QG-mPEG was successfully synthesized and can be recognized by mTG as an acyl donor to modify therapeutic protein, cytochrome c (cyt c). Finally, under an optimized condition (cyt c 0.5 mg/ml, CBZ-QG-mPEG 11.25 mg/ml, mTG 0.5 mg/ml, 37 °C, 2 h), the PEGylation yield reached 76.5 %.

Conclusions

This is the first study regarding the PEGylation of protein at the level of Lys residues catalyzed by mTG. The novel method could be employed to immobilize active proteins and modify therapeutic proteins.

     

Functional insights from proteome-wide structural modeling of <Emphasis Type="Italic">Treponema pallidum</Emphasis> subspecies <Emphasis Type="Italic">pallidum</Emphasis>, the causative agent of syphilis

Background

Syphilis continues to be a major global health threat with 11 million new infections each year, and a global burden of 36 million cases. The causative agent of syphilis, Treponema pallidum subspecies pallidum, is a highly virulent bacterium, however the molecular mechanisms underlying T. pallidum pathogenesis remain to be definitively identified. This is due to the fact that T. pallidum is currently uncultivatable, inherently fragile and thus difficult to work with, and phylogenetically distinct with no conventional virulence factor homologs found in other pathogens. In fact, approximately 30% of its predicted protein-coding genes have no known orthologs or assigned functions. Here we employed a structural bioinformatics approach using Phyre2-based tertiary structure modeling to improve our understanding of T. pallidum protein function on a proteome-wide scale.

Results

Phyre2-based tertiary structure modeling generated high-confidence predictions for 80% of the T. pallidum proteome (780/978 predicted proteins). Tertiary structure modeling also inferred the same function as primary structure-based annotations from genome sequencing pipelines for 525/605 proteins (87%), which represents 54% (525/978) of all T. pallidum proteins. Of the 175 T. pallidum proteins modeled with high confidence that were not assigned functions in the previously annotated published proteome, 167 (95%) were able to be assigned predicted functions. Twenty-one of the 175 hypothetical proteins modeled with high confidence were also predicted to exhibit significant structural similarity with proteins experimentally confirmed to be required for virulence in other pathogens.

Conclusions

Phyre2-based structural modeling is a powerful bioinformatics tool that has provided insight into the potential structure and function of the majority of T. pallidum proteins and helped validate the primary structure-based annotation of more than 50% of all T. pallidum proteins with high confidence. This work represents the first T. pallidum proteome-wide structural modeling study and is one of few studies to apply this approach for the functional annotation of a whole proteome.

     

Gene Ontology annotation of the rice blast fungus, <Emphasis Type="Italic">Magnaporthe oryzae</Emphasis>

Background

Magnaporthe oryzae, the causal agent of blast disease of rice, is the most destructive disease of rice worldwide. The genome of this fungal pathogen has been sequenced and an automated annotation has recently been updated to Version 6 http://www.broad.mit.edu/annotation/genome/magnaporthe_grisea/MultiDownloads.html. However, a comprehensive manual curation remains to be performed. Gene Ontology (GO) annotation is a valuable means of assigning functional information using standardized vocabulary. We report an overview of the GO annotation for Version 5 of M. oryzae genome assembly.

Methods

A similarity-based (i.e., computational) GO annotation with manual review was conducted, which was then integrated with a literature-based GO annotation with computational assistance. For similarity-based GO annotation a stringent reciprocal best hits method was used to identify similarity between predicted proteins of M. oryzae and GO proteins from multiple organisms with published associations to GO terms. Significant alignment pairs were manually reviewed. Functional assignments were further cross-validated with manually reviewed data, conserved domains, or data determined by wet lab experiments. Additionally, biological appropriateness of the functional assignments was manually checked.

Results

In total, 6,286 proteins received GO term assignment via the homology-based annotation, including 2,870 hypothetical proteins. Literature-based experimental evidence, such as microarray, MPSS, T-DNA insertion mutation, or gene knockout mutation, resulted in 2,810 proteins being annotated with GO terms. Of these, 1,673 proteins were annotated with new terms developed for Plant-Associated Microbe Gene Ontology (PAMGO). In addition, 67 experiment-determined secreted proteins were annotated with PAMGO terms. Integration of the two data sets resulted in 7,412 proteins (57%) being annotated with 1,957 distinct and specific GO terms. Unannotated proteins were assigned to the 3 root terms. The Version 5 GO annotation is publically queryable via the GO site http://amigo.geneontology.org/cgi-bin/amigo/go.cgi. Additionally, the genome of M. oryzae is constantly being refined and updated as new information is incorporated. For the latest GO annotation of Version 6 genome, please visit our website http://scotland.fgl.ncsu.edu/smeng/GoAnnotationMagnaporthegrisea.html. The preliminary GO annotation of Version 6 genome is placed at a local MySql database that is publically queryable via a user-friendly interface Adhoc Query System.

Conclusion

Our analysis provides comprehensive and robust GO annotations of the M. oryzae genome assemblies that will be solid foundations for further functional interrogation of M. oryzae.

     

Genetic diagnosis of neurofibromatosis type 1: targeted next- generation sequencing with Multiple Ligation-Dependent Probe Amplification analysis

Background

Neurofibromatosis type 1 (NF1) is a dominantly inherited tumor predisposition syndrome that targets the peripheral nervous system. It is caused by mutations of the NF1 gene which serve as a negative regulator of the cellular Ras/MAPK (mitogen-activated protein kinases) signaling pathway. Owing to the complexity in some parts of clinical diagnoses and the need for better understanding of its molecular relationships, a genetic characterization of this disorder will be helpful in the clinical setting.

Methods

In this study, we present a customized targeted gene panel of NF1/KRAS/BRAF/p53 and SPRED1 genes combined with Multiple Ligation-Dependent Probe Amplification analysis for the NF1 mutation screening in a cohort of patients clinically suspected as NF1.

Results

In this study, we identified 73 NF1 mutations and two BRAF novel variants from 100 NF1 patients who were suspected as having NF1. These genetic alterations are heterogeneous and distribute in a complicated way without clustering in either cysteine–serine-rich domain or within the GAP-related domain. We also detected fifteen multi-exon deletions within the NF1 gene by MLPA Analysis.

Conclusions

Our results suggested that a genetic screening using a NGS panel with high coverage of Ras–signaling components combined with Multiple Ligation-Dependent Probe Amplification analysis will enable differential diagnosis of patients with overlapping clinical features.