J. Miguel Ortega

Analysis of the gene expression profile of Schistosoma mansoni cercariae using the expressed sequence tag approach

ESTs constitute rapid and informative tools with which to study gene-expression profiles of the diverse stages of the schistosome life cycle. Following a comprehensive EST study of adult worms, analysis has now targeted the cercaria, the parasite larval form responsible for infection of the vertebrate host. Two Schistosoma mansoni cercarial cDNA libraries were examined and partial sequence obtained from 957 randomly selected clones. On the basis of database searches, 551 (57.6%) ESTs generated had no homologs in the public databases whilst 308 (32.2%) were putatively identified, totaling 859 informative ESTs. The remaining 98 (10.2%) were uninformative ESTs (ribosomal RNA and non-coding mitochondrial sequences). By clustering analysis we have identified 453 different genes. The most common sequences in both libraries represented Sm8 calcium binding protein (8% of ESTs), fructose-1,6-bisphosphate aldolase, glyceraldehyde-3-phosphate dehydrogenase, cytochrome oxidase subunit 1, ATP guanidine kinase and triose phosphate isomerase. One hundred and nineteen identified genes were sorted into 11 functional categories, with genes associated with energy metabolism being the most abundant (13%) and diverse. The diversity and abundance of genes associated with the transcription/translation machinery and with regulatory/signaling functions were also marked. A paramyosin transcript was identified, indicating that this gene is not exclusively expressed in adult worms and sporocysts (as had been suggested previously). The possible physiological relevance to cercariae of the presence of transcripts with homology to calcium binding proteins of the EF-hand superfamily, Gq-coupled rhodopsin photoreceptor, rod phosphodiesterase 8 subunit and peripheral-type benzodiazepine receptor is discussed.

PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries

BackgroundBiological function is greatly dependent on the interactions of proteins with other proteins and genes. Abstracts from the biomedical literature stored in the NCBIs PubMed database can be used for the derivation of interactions between genes and proteins by identifying the co-occurrences of their terms. Often, the amount of interactions obtained through such an approach is large and may mix processes occurring in different contexts. Current tools do not allow studying these data with a focus on concepts of relevance to a user, for example, interactions related to a disease or to a biological mechanism such as protein aggregation.ResultsTo help the concept-oriented exploration of such data we developed PESCADOR, a web tool that extracts a network of interactions from a set of PubMed abstracts given by a user, and allows filtering the interaction network according to user-defined concepts. We illustrate its use in exploring protein aggregation in neurodegenerative disease and in the expansion of pathways associated to colon cancer.ConclusionsPESCADOR is a platform independent web resource available at: http://cbdm.mdc-berlin.de/tools/pescador/

LAITOR--Literature Assistant for Identification of Terms co-Occurrences and Relationships.

BackgroundBiological knowledge is represented in scientific literature that often describes the function of genes/proteins (bioentities) in terms of their interactions (biointeractions). Such bioentities are often related to biological concepts of interest that are specific of a determined research field. Therefore, the study of the current literature about a selected topic deposited in public databases, facilitates the generation of novel hypotheses associating a set of bioentities to a common context.ResultsWe created a text mining system (LAITOR: LiteratureAssistant forIdentification ofTerms co-Occurrences andRelationships) that analyses co-occurrences of bioentities, biointeractions, and other biological terms in MEDLINE abstracts. The method accounts for the position of the co-occurring terms within sentences or abstracts. The system detected abstracts mentioning protein-protein interactions in a standard test (BioCreative II IAS test data) with a precision of 0.82-0.89 and a recall of 0.48-0.70. We illustrate the application of LAITOR to the detection of plant response genes in a dataset of 1000 abstracts relevant to the topic.ConclusionsText mining tools combining the extraction of interacting bioentities and biological concepts with network displays can be helpful in developing reasonable hypotheses in different scientific backgrounds.

Preimplantation development regulatory pathway construction through a text-mining approach

BackgroundThe integration of sequencing and gene interaction data and subsequent generation of pathways and networks contained in databases such as KEGG Pathway is essential for the comprehension of complex biological processes. We noticed the absence of a chart or pathway describing the well-studied preimplantation development stages; furthermore, not all genes involved in the process have entries in KEGG Orthology, important information for knowledge application with relation to other organisms.ResultsIn this work we sought to develop the regulatory pathway for the preimplantation development stage using text-mining tools such as Medline Ranker and PESCADOR to reveal biointeractions among the genes involved in this process. The genes present in the resulting pathway were also used as seeds for software developed by our group called SeedServer to create clusters of homologous genes. These homologues allowed the determination of the last common ancestor for each gene and revealed that the preimplantation development pathway consists of a conserved ancient core of genes with the addition of modern elements.ConclusionsThe generation of regulatory pathways through text-mining tools allows the integration of data generated by several studies for a more complete visualization of complex biological processes. Using the genes in this pathway as “seeds” for the generation of clusters of homologues, the pathway can be visualized for other organisms. The clustering of homologous genes together with determination of the ancestry leads to a better understanding of the evolution of such process.

Clustering of cognate proteins among distinct proteomes derived from multiple links to a single seed sequence

BackgroundModern proteomes evolved by modification of pre-existing ones. It is extremely important to comparative biology that related proteins be identified as members of the same cognate group, since a characterized putative homolog could be used to find clues about the function of uncharacterized proteins from the same group. Typically, databases of related proteins focus on those from completely-sequenced genomes. Unfortunately, relatively few organisms have had their genomes fully sequenced; accordingly, many proteins are ignored by the currently available databases of cognate proteins, despite the high amount of important genes that are functionally described only for these incomplete proteomes.ResultsWe have developed a method to cluster cognate proteins from multiple organisms beginning with only one sequence, through connectivity saturation with that Seed sequence. We show that the generated clusters are in agreement with some other approaches based on full genome comparison.ConclusionThe method produced results that are as reliable as those produced by conventional clustering approaches. Generating clusters based only on individual proteins of interest is less time consuming than generating clusters for whole proteomes.

A guide for building biological pathways along with two case studies: hair and breast development.

Genomic information is being underlined in the format of biological pathways. Building these biological pathways is an ongoing demand and benefits from methods for extracting information from biomedical literature with the aid of text-mining tools. Here we hopefully guide you in the attempt of building a customized pathway or chart representation of a system. Our manual is based on a group of software designed to look at biointeractions in a set of abstracts retrieved from PubMed. However, they aim to support the work of someone with biological background, who does not need to be an expert on the subject and will play the role of manual curator while designing the representation of the system, the pathway. We therefore illustrate with two challenging case studies: hair and breast development. They were chosen for focusing on recent acquisitions of human evolution. We produced sub-pathways for each study, representing different phases of development. Differently from most charts present in current databases, we present detailed descriptions, which will additionally guide PESCADOR users along the process. The implementation as a web interface makes PESCADOR a unique tool for guiding the user along the biointeractions, which will constitute a novel pathway.

Diet as a pressure on the amino acid content of proteomes

Whether diet has been influencing the genomic and proteomic constitution of the organisms along the evolution is an interesting and not answered question. Here, we investigate the hypothesis that essential amino acids – the ones that are not produced by the organisms – have being replaced in proteins by non-essential ones. We compare the amino acid composition of the proteome from human, worm and fly, that cannot synthesize all amino acids, with the ones from plant, baker yeast and budding yeast, capable to synthesize all of them. The analysis was made with 190,074 proteins composed of 87,175,891 amino acids. Our data seems to evidence a little bias on the usage of non-essential amino acids by the metazoan organisms, except for the worm. Thus, the preliminary results shown here support the thesis that non-essential ones have replaced essential amino acids.

BOWS (bioinformatics open web services) to centralize bioinformatics tools in web services

BackgroundBioinformaticians face a range of difficulties to get locally-installed tools running and producing results; they would greatly benefit from a system that could centralize most of the tools, using an easy interface for input and output. Web services, due to their universal nature and widely known interface, constitute a very good option to achieve this goal.ResultsBioinformatics open web services (BOWS) is a system based on generic web services produced to allow programmatic access to applications running on high-performance computing (HPC) clusters. BOWS intermediates the access to registered tools by providing front-end and back-end web services. Programmers can install applications in HPC clusters in any programming language and use the back-end service to check for new jobs and their parameters, and then to send the results to BOWS. Programs running in simple computers consume the BOWS front-end service to submit new processes and read results. BOWS compiles Java clients, which encapsulate the front-end web service requisitions, and automatically creates a web page that disposes the registered applications and clients.ConclusionsBioinformatics open web services registered applications can be accessed from virtually any programming language through web services, or using standard java clients. The back-end can run in HPC clusters, allowing bioinformaticians to remotely run high-processing demand applications directly from their machines.

High efficiency on prediction of translation initiation site (TIS) of RefSeq sequences

An important task in the area of gene discovery is the correct prediction of the translation initiation site (TIS). The TIS can correspond to the first AUG, but this is not always the case. This task can be modeled as a classification problem between positive (TIS) and negative patterns. Here we have used Support Vector Machine working with data processed by the class balancing method called Smote (Synthetic Minority Over-sampling Technique). Smote was used because the average imbalance has a positive/negative pattern ratio of around 1:28 for the databases used in this work. As a result we have attained accuracy, precision, sensitivity and specificity values of 99% on average.

Whole-Genome Sequence of Leptospira interrogans Serovar Hardjo Subtype Hardjoprajitno Strain Norma, Isolated from Cattle in a Leptospirosis Outbreak in Brazil

ABSTRACT Leptospirosis is caused by pathogenic bacteria of the genus Leptospira spp. This neglected re-emergent disease has global distribution and relevance in veterinary production. Here, we report the whole-genome sequence and annotation of Leptospira interrogans serovar Hardjo subtype Hardjoprajitno strain Norma, isolated from cattle in a livestock leptospirosis outbreak in Brazil.