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Abstract Background Lysosomal β-D-mannosidase is a glycosyl hydrolase that breaks down the glycosidic bonds at the non-reducing end of N-linked glycoproteins. Hence, it is a crucial enzyme in polysaccharide degradation pathway. Mutations in the MANBA gene that codes for lysosomal β-mannosidase, result in improper coding and malfunctioning of protein, leading to β-mannosidosis. Studying the location of mutations on the enzyme structure is a rational approach in order to understand the functional consequences of these mutations. Accordingly, the pathology and clinical manifestations of the disease could be correlated to the genotypic modifications. Results The wild-type and inherited mutations of β-mannosidase were studied across four different species, human, cow, goat and mouse employing a previously demonstrated comprehensive homology modeling and mutational mapping technique, which reveals a correlation between the variation of genotype and the severity of phenotype in β-mannosidosis. X-ray crystallographic structure of β-mannosidase from Bacteroides thetaiotaomicron was used as template for 3D structural modeling of the wild-type enzymes containing all the associated ligands. These wild-type models subsequently served as templates for building mutational structures. Truncations account for approximately 70% of the mutational cases. In general, the proximity of mutations to the active site determines the severity of phenotypic expressions. Mapping mutations to the MANBA gene sequence has identified five mutational hot-spots. Conclusion Although restrained by a limited dataset, our comprehensive study suggests a genotype-phenotype correlation in β-mannosidosis. A predictive approach for detecting likely β-mannosidosis is also demonstrated where we have extrapolated observed mutations from one species to homologous positions in other organisms based on the proximity of the mutations to the enzyme active site and their co-location from different organisms. Apart from aiding the detection of mutational hotspots in the gene, where novel mutations could be disease-implicated, this approach also provides a way to predict new disease mutations. Higher expression of the exoglycosidase chitobiase is said to play a vital role in determining disease phenotypes in human and mouse. A bigger dataset of inherited mutations as well as a parallel study of β-mannosidase and chitobiase activities in prospective patients would be interesting to better understand the underlying reasons for β-mannosidosis.

Abstract Background Excretory/secretory proteins (ESPs) play a major role in parasitic infection as they are present at the host-parasite interface and regulate host immune system. In case of parasitic helminths, transcriptomics has been used extensively to understand the molecular basis of parasitism and for developing novel therapeutic strategies against parasitic infections. However, none of transcriptomic studies have extensively covered ES protein prediction for identifying novel therapeutic targets, especially as parasites adopt non-classical secretion pathways. Results We developed a semi-automated computational approach for prediction and annotation of ES proteins using transcriptomic data from next generation sequencing platforms. For the prediction of non-classically secreted proteins, we have used an improved computational strategy, together with homology matching to a dataset of experimentally determined parasitic helminth ES proteins. We applied this protocol to analyse 454 short reads of parasitic nematode, Strongyloides ratti. From 296231 reads, we derived 28901 contigs, which were translated into 20877 proteins. Based on our improved ES protein prediction pipeline, we identified 2572 ES proteins, of which 407 (1.9%) proteins have classical N-terminal signal peptides, 923 (4.4%) were computationally identified as non-classically secreted while 1516 (7.26%) were identified by homology to experimentally identified parasitic helminth ES proteins. Out of 2572 ES proteins, 2310 (89.8%) ES proteins had homologues in the free-living nematode Caenorhabditis elegans and 2220 (86.3%) in parasitic nematodes. We could functionally annotate 1591 (61.8%) ES proteins with protein families and domains and establish pathway associations for 691 (26.8%) proteins. In addition, we have identified 19 representative ES proteins, which have no homologues in the host organism but homologous to lethal RNAi phenotypes in C. elegans, as potential therapeutic targets. Conclusion We report a comprehensive approach using freely available computational tools for the secretome analysis of NGS data. This approach has been applied to S. ratti 454 transcriptomic data for in silico excretory/secretory proteins prediction and analysis, providing a foundation for developing new therapeutic solutions for parasitic infections.

Abstract The 2010 International Conference on Bioinformatics, InCoB2010, which is the annual conference of the Asia-Pacific Bioinformatics Network (APBioNet) has agreed to publish conference papers in compliance with the proposed Minimum Information about a Bioinformatics investigation (MIABi), proposed in June 2009. Authors of the conference supplements in BMC Bioinformatics, BMC Genomics and Immunome Research have consented to cooperate in this process, which will include the procedures described herein, where appropriate, to ensure data and software persistence and perpetuity, database and resource re-instantiability and reproducibility of results, author and contributor identity disambiguation and MIABi-compliance. Wherever possible, datasets and databases will be submitted to depositories with standardized terminologies. As standards are evolving, this process is intended as a prelude to the 100 BioDatabases (BioDB100) initiative whereby APBioNet collaborators will contribute exemplar databases to demonstrate the feasibility of standards-compliance and participate in refining the process for peer-review of such publications and validation of scientific claims and standards compliance. This testbed represents another step in advancing standards-based processes in the bioinformatics community which is essential to the growing interoperability of biological data, information, knowledge and computational resources.

Abstract Background The development of high throughput experimental technologies have given rise to the "-omics" era where terabyte-scale datasets for systems-level measurements of various cellular and molecular phenomena pose considerable challenges in data processing and extraction of biological meaning. Moreover, it has created an unmet need for the effective integration of these datasets to achieve insights into biological systems. While it has increased the demand for bioinformatics experts who can interface with biologists, it has also raised the requirement for biologists to possess a basic capability in bioinformatics and to communicate seamlessly with these experts. This may be achieved by embedding in their undergraduate and graduate life science education, basic training in bioinformatics geared towards acquiring a minimum skill set in computation and informatics. Results Based on previous attempts to define curricula suitable for addressing the bioinformatics capability gap, an initiative was taken during the Workshops on Education in Bioinformatics and Computational Biology (WEBCB) in 2008 and 2009 to identify a minimum skill set for the training of future bioinformaticians and molecular biologists with informatics capabilities. The minimum skill set proposed is cross-disciplinary in nature, involving a combination of knowledge and proficiency from the fields of biology, computer science, mathematics and statistics, and can be tailored to the needs of the "-omics". Conclusion The proposed bioinformatics minimum skill set serves as a guideline for biology curriculum design and development in universities at both the undergraduate and graduate levels.

Abstract Background Lysosomal α-mannosidase is an enzyme that acts to degrade N-linked oligosaccharides and hence plays an important role in mannose metabolism in humans and other mammalian species, especially livestock. Mutations in the gene (MAN2B1) encoding lysosomal α-D-mannosidase cause improper coding, resulting in dysfunctional or non-functional protein, causing the disease α-mannosidosis. Mapping disease mutations to the structure of the protein can help in understanding the functional consequences of these mutations and thus indirectly, the finer aspects of the pathology and clinical manifestations of the disease, including phenotypic severity as a function of the genotype. Results A comprehensive homology modeling study of all the wild-type and inherited mutations of lysosomal α-mannosidase in four different species, human, cow, cat and guinea pig, reveals a significant correlation between the severity of the genotype and the phenotype in α-mannosidosis. We used the X-ray crystallographic structure of bovine lysosomal α-mannosidase as template, containing only two disulphide bonds and some ligands, to build structural models of wild-type structures with four disulfide linkages and all bound ligands. These wild-type models were then used as templates for disease mutations. All the truncations and substitutions involving the residues in and around the active site and those that destabilize the fold led to severe genotypes resulting in lethal phenotypes, whereas the mutations lying away from the active site were milder in both their genotypic and phenotypic expression. Conclusion Based on the co-location of mutations from different organisms and their proximity to the enzyme active site, we have extrapolated observed mutations from one species to homologous positions in other organisms, as a predictive approach for detecting likely α-mannosidosis. Besides predicting new disease mutations, this approach also provides a way for detecting mutation hotspots in the gene, where novel mutations could be implicated in disease. The current study has identified five mutational hot-spot regions along the MAN2B1 gene. Structural mapping can thus provide a rational approach for predicting the phenotype of a disease, based on observed genotypic variations.

Abstract Background Caspases belong to a class of cysteine proteases which function as critical effectors in cellular processes such as apoptosis and inflammation by cleaving substrates immediately after unique tetrapeptide sites. With hundreds of reported substrates and many more expected to be discovered, the elucidation of the caspase degradome will be an important milestone in the study of these proteases in human health and disease. Several computational methods for predicting caspase cleavage sites have been developed recently for identifying potential substrates. However, as most of these methods are based primarily on the detection of the tetrapeptide cleavage sites - a factor necessary but not sufficient for predicting in vivo substrate cleavage - prediction outcomes will inevitably include many false positives. Results In this paper, we show that structural factors such as the presence of disorder and solvent exposure in the vicinity of the cleavage site are important and can be used to enhance results from cleavage site prediction. We constructed a two-step model incorporating cleavage site prediction and these factors to predict caspase substrates. Sequences are first predicted for cleavage sites using CASVM or GraBCas. Predicted cleavage sites are then scored, ranked and filtered against a cut-off based on their propensities for locating in disordered and solvent exposed regions. Using an independent dataset of caspase substrates, the model was shown to achieve greater positive predictive values compared to CASVM or GraBCas alone, and was able to reduce the false positives pool by up to 13% and 53% respectively while retaining all true positives. We applied our prediction model on the family of receptor tyrosine kinases (RTKs) and highlighted several members as potential caspase targets. The results suggest that RTKs may be generally regulated by caspase cleavage and in some cases, promote the induction of apoptotic cell death - a function distinct from their role as transducers of survival and growth signals. Conclusion As a step towards the prediction of in vivo caspase substrates, we have developed an accurate method incorporating cleavage site prediction and structural factors. The multi-factor model augments existing methods and complements experimental efforts to define the caspase degradome on the systems-wide basis.

Abstract Background Alternative transcript diversity manifests itself as a prime cause of complexity in higher eukaryotes. Recently, transcript diversity studies have suggested that 60–80% of human genes are alternatively spliced. We have used a splicing pattern approach for the bioinformatics analysis of Alternative Splicing (AS) in chicken, human and mouse. Exons involved in splicing are subdivided into distinct and variant exons, based on the prevalence of the exons across the transcripts. Four possible permutations of these two different groups of exons were categorised as class I (distinct-variant), class II (distinct-variant), class III (variant-distinct) and class IV (variant-variant). This classification quantifies the variation in transcript diversity in the three species. Results In all, 3901 chicken AS genes have been compared with 16,715 human and 16,491 mouse AS genes, with 23% of chicken genes being alternatively spliced, compared to 68% in humans and 57% in mice. To minimize any gene structure bias in the input data, comparative genome analysis has been carried out on the orthologous subset of AS genes for the three species. Gene-level analysis suggested that chicken genes show fewer AS events compared to human and mouse. An event-level analysis showed that the percentage of AS events in chicken is similar to that of human, which implies that a smaller number of chicken genes show greater transcript diversity. Overall, chicken genes were found to have fewer transcripts per gene and shorter introns than human and mouse genes. Conclusion In chicken, the majority of genes generate only two or three isoforms, compared to almost eight in human and six in mouse. We observed that intron definition is expressed strongly when compared to exon definition for chicken genome, based on 3% intron retention in chicken, compared to 2% in human and mouse. Splicing patterns with variant exons account for 33% of AS chicken orthologous genes compared to 24% in human and 27% in mouse, providing a novel measure to describe the species-wise complexity due to alternative transcript diversity.

Abstract Background Lungworms of the genus Dictyocaulus (family Dictyocaulidae) are parasitic nematodes of major economic importance. They cause pathological effects and clinical disease in various ruminant hosts, particularly in young animals. Dictyocaulus viviparus, called the bovine lungworm, is a major pathogen of cattle, with severe infections being fatal. In this study, we provide first insights into the transcriptome of the adult stage of D. viviparus through the analysis of expressed sequence tags (ESTs). Results Using our EST analysis pipeline, we estimate that the present dataset of 4436 ESTs is derived from 2258 genes based on cluster and comparative genomic analyses of the ESTs. Of the 2258 representative ESTs, 1159 (51.3%) had homologues in the free-living nematode C. elegans, 1174 (51.9%) in parasitic nematodes, 827 (36.6%) in organisms other than nematodes, and 863 (38%) had no significant match to any sequence in the current databases. Of the C. elegans homologues, 569 had observed 'non-wildtype' RNAi phenotypes, including embryonic lethality, maternal sterility, sterility in progeny, larval arrest and slow growth. We could functionally classify 776 (35%) sequences using the Gene Ontologies (GO) and established pathway associations to 696 (31%) sequences in Kyoto Encyclopedia of Genes and Genomes (KEGG). In addition, we predicted 85 secreted proteins which could represent potential candidates for developing novel anthelmintics or vaccines. Conclusion The bioinformatic analyses of ESTs data for D. viviparus has elucidated sets of relatively conserved and potentially novel genes. The genes discovered in this study should assist research toward a better understanding of the basic molecular biology of D. viviparus, which could lead, in the longer term, to novel intervention strategies. The characterization of the D. viviparus transcriptome also provides a foundation for whole genome sequence analysis and future comparative transcriptomic analyses.

Background: Influenza viruses are undergoing continuous and rapid evolution. The fatal influenza A/H7N9 has drawn attention since the first wave of infections in March 2013, and raised more grave concerns with its increased potential to spread among humans. Experimental studies have revealed several host and virulence markers, indicating differential host binding preferences which can help estimate the potential of causing a pandemic. Here we systematically investigate the sequence pattern and structural characteristics of novel influenza A/H7N9 using computational approaches. Results: The sequence analysis highlighted mutations in protein functional domains of influenza viruses. Molecular docking and molecular dynamics simulation revealed that the hemagglutinin (HA) of A/Taiwan/1/2017(H7N9) strain enhanced the binding with both avian and human receptor analogs, compared with the previous A/Shanghai/02/2013(H7N9) strain. The Molecular Mechanics - Poisson Boltzmann Surface Area (MM-PBSA) calculation revealed the change of residue-ligand interaction energy and detected the residues with conspicuous binding preference. Conclusion: The results are novel and specific to the emerging influenza A/Taiwan/1/2017(H7N9) strain compared with A/Shanghai/02/2013(H7N9). Its enhanced ability to bind human receptor analogs, which are abundant in the human upper respiratory tract, may be responsible for the recent outbreak. Residues showing binding preference were detected, which could facilitate monitoring the circulating influenza viruses. [ABSTRACT FROM AUTHOR]

Background: Small bioinformatics databases, unlike institutionally funded large databases, are vulnerable to discontinuation and many reported in publications are no longer accessible. This leads to irreproducible scientific work and redundant effort, impeding the pace of scientific progress. Results: We describe a Web-accessible system, available online at http://biodb100.apbionet.org, for archival and future on demand re-instantiation of small databases within minutes. Depositors can rebuild their databases by downloading a Linux live operating system (http://www.bioslax.com), preinstalled with bioinformatics and UNIX tools. The database and its dependencies can be compressed into an “.lzm” file for deposition. End-users can search for archived databases and activate them on dynamically re-instantiated BioSlax instances, run as virtual machines over the two popular full virtualization standard cloud-computing platforms, Xen Hypervisor or vSphere. The system is adaptable to increasing demand for disk storage or computational load and allows database developers to use the re-instantiated databases for integration and development of new databases. Conclusions: Herein, we demonstrate that a relatively inexpensive solution can be implemented for archival of bioinformatics databases and their rapid re-instantiation should the live databases disappear. [ABSTRACT FROM AUTHOR]

Background: Lysosomal β-D-mannosidase is a glycosyl hydrolase that breaks down the glycosidic bonds at the non-reducing end of N-linked glycoproteins. Hence, it is a crucial enzyme in polysaccharide degradation pathway. Mutations in the MANBA gene that codes for lysosomal β-mannosidase, result in improper coding and malfunctioning of protein, leading to β-mannosidosis. Studying the location of mutations on the enzyme structure is a rational approach in order to understand the functional consequences of these mutations. Accordingly, the pathology and clinical manifestations of the disease could be correlated to the genotypic modifications. Results: The wild-type and inherited mutations of β-mannosidase were studied across four different species, human, cow, goat and mouse employing a previously demonstrated comprehensive homology modeling and mutational mapping technique, which reveals a correlation between the variation of genotype and the severity of phenotype in β-mannosidosis. X-ray crystallographic structure of β-mannosidase from Bacteroides thetaiotaomicron was used as template for 3D structural modeling of the wild-type enzymes containing all the associated ligands. These wild-type models subsequently served as templates for building mutational structures. Truncations account for approximately 70% of the mutational cases. In general, the proximity of mutations to the active site determines the severity of phenotypic expressions. Mapping mutations to the MANBA gene sequence has identified five mutational hot-spots. Conclusion: Although restrained by a limited dataset, our comprehensive study suggests a genotype-phenotype correlation in β-mannosidosis. A predictive approach for detecting likely β-mannosidosis is also demonstrated where we have extrapolated observed mutations from one species to homologous positions in other organisms based on the proximity of the mutations to the enzyme active site and their co-location from different organisms. Apart from aiding the detection of mutational hotspots in the gene, where novel mutations could be diseaseimplicated, this approach also provides a way to predict new disease mutations. Higher expression of the exoglycosidase chitobiase is said to play a vital role in determining disease phenotypes in human and mouse. A bigger dataset of inherited mutations as well as a parallel study of β-mannosidase and chitobiase activities in prospective patients would be interesting to better understand the underlying reasons for β-mannosidosis. [ABSTRACT FROM AUTHOR]

The 2010 International Conference on Bioinformatics, InCoB2010, which is the annual conference of the Asia-Pacific Bioinformatics Network (APBioNet) has agreed to publish conference papers in compliance with the proposed Minimum Information about a Bioinformatics investigation (MIABi), proposed in June 2009. Authors of the conference supplements in BMC Bioinformatics, BMC Genomics and Immunome Research have consented to cooperate in this process, which will include the procedures described herein, where appropriate, to ensure data and software persistence and perpetuity, database and resource re-instantiability and reproducibility of results, author and contributor identity disambiguation and MIABi-compliance. Wherever possible, datasets and databases will be submitted to depositories with standardized terminologies. As standards are evolving, this process is intended as a prelude to the 100 BioDatabases (BioDB100) initiative whereby APBioNet collaborators will contribute exemplar databases to demonstrate the feasibility of standards-compliance and participate in refining the process for peer-review of such publications and validation of scientific claims and standards compliance. This testbed represents another step in advancing standards-based processes in the bioinformatics community which is essential to the growing interoperability of biological data, information, knowledge and computational resources. [ABSTRACT FROM AUTHOR]

Background: Lysosomal alpha-mannosidase is an enzyme that acts to degrade N-linked oligosaccharides and hence plays an important role in mannose metabolism in humans and other mammalian species, especially livestock. Mutations in the gene (MAN2B1) encoding lysosomal alpha-D-mannosidase cause improper coding, resulting in dysfunctional or non-functional protein, causing the disease alpha-mannosidosis. Mapping disease mutations to the structure of the protein can help in understanding the functional consequences of these mutations and thus indirectly, the finer aspects of the pathology and clinical manifestations of the disease, including phenotypic severity as a function of the genotype., Results: A comprehensive homology modeling study of all the wild-type and inherited mutations of lysosomal alpha-mannosidase in four different species, human, cow, cat and guinea pig, reveals a significant correlation between the severity of the genotype and the phenotype in alpha-mannosidosis. We used the X-ray crystallographic structure of bovine lysosomal alpha-mannosidase as template, containing only two disulphide bonds and some ligands, to build structural models of wild-type structures with four disulfide linkages and all bound ligands. These wild-type models were then used as templates for disease mutations. All the truncations and substitutions involving the residues in and around the active site and those that destabilize the fold led to severe genotypes resulting in lethal phenotypes, whereas the mutations lying away from the active site were milder in both their genotypic and phenotypic expression., Conclusion: Based on the co-location of mutations from different organisms and their proximity to the enzyme active site, we have extrapolated observed mutations from one species to homologous positions in other organisms, as a predictive approach for detecting likely alpha-mannosidosis. Besides predicting new disease mutations, this approach also provides a way for detecting mutation hotspots in the gene, where novel mutations could be implicated in disease. The current study has identified five mutational hot-spot regions along the MAN2B1 gene. Structural mapping can thus provide a rational approach for predicting the phenotype of a disease, based on observed genotypic variations.