Recruitment of rare <Emphasis Type="Italic">3</Emphasis>-grams at functional sites: Is this a mechanism for increasing enzyme specificity?

Background  

A wealth of unannotated and functionally unknown protein sequences has accumulated in recent years with rapid progresses in sequence genomics, giving rise to ever increasing demands for developing methods to efficiently assess functional sites. Sequence and structure conservations have traditionally been the major criteria adopted in various algorithms to identify functional sites. Here, we focus on the distributions of the 20³ different types of 3-grams (or triplets of sequentially contiguous amino acid) in the entire space of sequences accumulated to date in the UniProt database, and focus in particular on the rare 3-grams distinguished by their high entropy-based information content.     

Identification and characterization of parvalbumin-like protein in Trichophyton violaceum

Parvalbumins play crucial physiological roles in neuromuscular systems of vertebrates, such as cell-cycle, development of neurons, contraction of muscles, and regulation of intracellular calcium. To perform these neuromuscular functions, parvalbumin may be in associated with other proteins including calbindin, carbonic anhydrase, and cytochrome oxidase. Humans may show an IgE-specific hypersensitivity to parvalbumins after consumption of some distinct fish species. While this protein is abundant in fish muscles, literature review of publications related to fish parvalbumins, do not point to the presence of parvalbumins in eukaryotic microbes. In this study, we propose that distantly related parvalbumins may be found in some non-fish species. Bioinformatics studies such as multiple sequence alignment (MSA), phylogenetic analysis as well as molecular-based experiments indicate that, at least two parvalbumins sequences (UniProt IDs: A0A178F775 and A0A178F7E4) with EF-hand domains and Ca²⁺-binding sites could be identified in Trichophyton violaceum, a pathogenic fungal species.It was determined that both genes consisted of a single exon and encoded for parvalbumin proteins possessing conserved amino acid motifs. Antigenicity prediction revealed antigenic sites located in both sides of the Ca²⁺-binding site of the first EF-hand domain. Our phylogenetic analysis revealed that one of parvalbumins (UniProt ID: 0A178F775) can be evolved to other parvalbumins in T. violaceum (UniProt ID: A0A178F7E4) and fish species through evolutionary phenomenon. To confirm our in-silico findings, we designed three primer pairs to detect one of the T. violaceum parvalbumins (UniProt ID: A0A178F7E4) by polymerase chain reaction (PCR); one primer pair showed a strong and specific band in agarose gel electrophoresis. To evaluate the specificity of the method, the primers were tested on extracted DNA from Trichophyton rubrum and T. mentagrophytes. The results demonstrated that the evaluated parvalbumin gene (UniProt ID: A0A178F7E4) was T. violaceum-specific and this pathogenic fungus can be differentiated from T. rubrum and T. mentagrophytes through identification of parvalbumin genes. Further studies are necessary to unravel the biochemical and physiological functions of parvalbumins in T. violaceum.     

Seahawk: moving beyond HTML in Web-based bioinformatics analysis

Background  

Traditional HTML interfaces for input to and output from Bioinformatics analysis on the Web are highly variable in style, content and data formats. Combining multiple analyses can therfore be an onerous task for biologists. Semantic Web Services allow automated discovery of conceptual links between remote data analysis servers. A shared data ontology and service discovery/execution framework is particularly attractive in Bioinformatics, where data and services are often both disparate and distributed. Instead of biologists copying, pasting and reformatting data between various Web sites, Semantic Web Service protocols such as MOBY-S hold out the promise of seamlessly integrating multi-step analysis.     

Automated production of recombinant human proteins as resource for proteome research

Background  

An arbitrary set of 96 human proteins was selected and tested to set-up a fully automated protein production strategy, covering all steps from DNA preparation to protein purification and analysis. The target proteins are encoded by functionally uncharacterized open reading frames (ORF) identified by the German cDNA consortium. Fusion proteins were produced in E. coli with four different fusion tags and tested in five different purification strategies depending on the respective fusion tag. The automated strategy relies on standard liquid handling and clone picking equipment.     

Social Presence and Use of Internet-Delivered Interventions: A Multi-Method Approach

Objective

Internet-delivered interventions can effectively change health risk behaviors and their determinants, but adherence to intervention websites once they are accessed is very low. This study tests whether and how social presence elements can increase website use.

Methods

A website about Hepatitis A, B, and C virus infections was used in a preparatory lab-based eye-tracking study assessing whether social presence elements attract participants'' attention, because this is a prerequisite for affecting website use. In the following field study, 482 participants representative of the Dutch population were randomized to either a website with or a website without social presence elements. Participants completed a questionnaire of validated measures regarding user perceptions immediately after exposure to the website. Server registrations were used to assess website use.

Results

Participants in the experimental condition focused on the social presence elements, both in terms of frequency (F(1, 98) = 40.34, p<.001) and duration (F(1, 88) = 39.99, p<.001), but did not differ in website use in comparison with the control condition; neither in terms of the number of pages visited (t(456) = 1.44, p = .15), nor in terms of time on the website (t(456) = 0.01, p = .99).

Conclusions

Adding social presence elements did not affect actual use of an intervention website within a public health context. Possible reasons are limited attention for these elements in comparison with the main text and the utilitarian value of intervention websites.     

A combined approach to data mining of textual and structured data to identify cancer-related targets

Background  

We present an effective, rapid, systematic data mining approach for identifying genes or proteins related to a particular interest. A selected combination of programs exploring PubMed abstracts, universal gene/protein databases (UniProt, InterPro, NCBI Entrez), and state-of-the-art pathway knowledge bases (LSGraph and Ingenuity Pathway Analysis) was assembled to distinguish enzymes with hydrolytic activities that are expressed in the extracellular space of cancer cells. Proteins were identified with respect to six types of cancer occurring in the prostate, breast, lung, colon, ovary, and pancreas.     

DIALIGN P: Fast pair-wise and multiple sequence alignment using parallel processors

Background  

Parallel computing is frequently used to speed up computationally expensive tasks in Bioinformatics.     

Annotation and query of tissue microarray data using the NCI Thesaurus

Background  

The Stanford Tissue Microarray Database (TMAD) is a repository of data serving a consortium of pathologists and biomedical researchers. The tissue samples in TMAD are annotated with multiple free-text fields, specifying the pathological diagnoses for each sample. These text annotations are not structured according to any ontology, making future integration of this resource with other biological and clinical data difficult.     

GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies

Background  

Microarray and other high-throughput technologies are producing large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in the gene sets.     

Stability of multiple alignments and phylogenetic trees: an analysis of ABC-transporter proteins family

Background  

Sequence-based phylogeny reconstruction is a fundamental task in Bioinformatics. Practically all methods for phylogeny reconstruction are based on multiple alignments. The quality and stability of the underlying alignments is therefore crucial for phylogenetic analysis.     

Shortest triplet clustering: reconstructing large phylogenies using representative sets

Background  

Understanding the evolutionary relationships among species based on their genetic information is one of the primary objectives in phylogenetic analysis. Reconstructing phylogenies for large data sets is still a challenging task in Bioinformatics.     

GLOSSary: the GLobal Ocean 16S subunit web accessible resource

Background

Environmental metagenomics is a challenging approach that is exponentially spreading in the scientific community to investigate taxonomic diversity and possible functions of the biological components. The massive amount of sequence data produced, often endowed with rich environmental metadata, needs suitable computational tools to fully explore the embedded information. Bioinformatics plays a key role in providing methodologies to manage, process and mine molecular data, integrated with environmental metagenomics collections. One such relevant example is represented by the Tara Ocean Project.

Results

We considered the Tara 16S miTAGs released by the consortium, representing raw sequences from a shotgun metagenomics approach with similarities to 16S rRNA genes. We generated assembled 16S rDNA sequences, which were classified according to their lengths, the possible presence of chimeric reads, the putative taxonomic affiliation. The dataset was included in GLOSSary (the GLobal Ocean 16S Subunit web accessible resource), a bioinformatics platform to organize environmental metagenomics data. The aims of this work were: i) to present alternative computational approaches to manage challenging metagenomics data; ii) to set up user friendly web-based platforms to allow the integration of environmental metagenomics sequences and of the associated metadata; iii) to implement an appropriate bioinformatics platform supporting the analysis of 16S rDNA sequences exploiting reference datasets, such as the SILVA database. We organized the data in a next-generation NoSQL “schema-less” database, allowing flexible organization of large amounts of data and supporting native geospatial queries. A web interface was developed to permit an interactive exploration and a visual geographical localization of the data, either raw miTAG reads or 16S contigs, from our processing pipeline. Information on unassembled sequences is also available. The taxonomic affiliations of contigs and miTAGs, and the spatial distribution of the sampling sites and their associated sequence libraries, as they are contained in the Tara metadata, can be explored by a query interface, which allows both textual and visual investigations. In addition, all the sequence data were made available for a dedicated BLAST-based web application alongside the SILVA collection.

Conclusions

GLOSSary provides an expandable bioinformatics environment, able to support the scientific community in current and forthcoming environmental metagenomics analyses.

     

A factorization method for the classification of infrared spectra

Background  

Bioinformatics data analysis often deals with additive mixtures of signals for which only class labels are known. Then, the overall goal is to estimate class related signals for data mining purposes. A convenient application is metabolic monitoring of patients using infrared spectroscopy. Within an infrared spectrum each single compound contributes quantitatively to the measurement.     

Detailed estimation of bioinformatics prediction reliability through the Fragmented Prediction Performance Plots

Background  

An important and yet rather neglected question related to bioinformatics predictions is the estimation of the amount of data that is needed to allow reliable predictions. Bioinformatics predictions are usually validated through a series of figures of merit, like for example sensitivity and precision, and little attention is paid to the fact that their performance may depend on the amount of data used to make the predictions themselves.     

Alzheimer-specific variants in the 3'UTR of Amyloid precursor protein affect microRNA function

Background

APP expression misregulation can cause genetic Alzheimer's disease (AD). Recent evidences support the hypothesis that polymorphisms located in microRNA (miRNA) target sites could influence the risk of developing neurodegenerative disorders such as Parkinson's disease (PD) and frontotemporal dementia. Recently, a number of single nucleotide polymorphisms (SNPs) located in the 3'UTR of APP have been found in AD patients with family history of dementia. Because miRNAs have previously been implicated in APP expression regulation, we set out to determine whether these polymorphisms could affect miRNA function and therefore APP levels.

Results

Bioinformatics analysis identified twelve putative miRNA bindings sites located in or near the APP 3'UTR variants T117C, A454G and A833C. Among those candidates, seven miRNAs, including miR-20a, miR-17, miR-147, miR-655, miR-323-3p, miR-644, and miR-153 could regulate APP expression in vitro and under physiological conditions in cells. Using luciferase-based assays, we could show that the T117C variant inhibited miR-147 binding, whereas the A454G variant increased miR-20a binding, consequently having opposite effects on APP expression.

Conclusions

Taken together, our results provide proof-of-principle that APP 3'UTR polymorphisms could affect AD risk through modulation of APP expression regulation, and set the stage for further association studies in genetic and sporadic AD.     

Initial steps towards a production platform for DNA sequence analysis on the grid

Background  

Bioinformatics is confronted with a new data explosion due to the availability of high throughput DNA sequencers. Data storage and analysis becomes a problem on local servers, and therefore it is needed to switch to other IT infrastructures. Grid and workflow technology can help to handle the data more efficiently, as well as facilitate collaborations. However, interfaces to grids are often unfriendly to novice users.     

Association algorithm to mine the rules that govern enzyme definition and to classify protein sequences

Background  

The number of sequences compiled in many genome projects is growing exponentially, but most of them have not been characterized experimentally. An automatic annotation scheme must be in an urgent need to reduce the gap between the amount of new sequences produced and reliable functional annotation. This work proposes rules for automatically classifying the fungus genes. The approach involves elucidating the enzyme classifying rule that is hidden in UniProt protein knowledgebase and then applying it for classification. The association algorithm, Apriori, is utilized to mine the relationship between the enzyme class and significant InterPro entries. The candidate rules are evaluated for their classificatory capacity.     

ASH structure alignment package: Sensitivity and selectivity in domain classification

Background  

Structure alignment methods offer the possibility of measuring distant evolutionary relationships between proteins that are not visible by sequence-based analysis. However, the question of how structural differences and similarities ought to be quantified in this regard remains open. In this study we construct a training set of sequence-unique CATH and SCOP domains, from which we develop a scoring function that can reliably identify domains with the same CATH topology and SCOP fold classification. The score is implemented in the ASH structure alignment package, for which the source code and a web service are freely available from the PDBj website .