Genetic basis underlying the serological affinity of leptospiral serovars from serogroups Sejroe, Mini and Hebdomadis.

Leptospirosis is a widely distributed zoonosis caused by pathogenic strains of bacteria of the genus Leptospira (Phylum Spirochaetes). Its agents are commonly classified based on their antigenic characteristics into serogroups and serovars, which are relevant for epidemiologic studies and vaccine development. Serological tests are considered laborious and require a specialized infrastructure. Some molecular methods have been proposed to accelerate these procedures, but they still can not replace the immunological tests, thus requiring a further understanding of the genetic basis underlying the serological classification. In this work, we focused on elucidating the genetic factors determinant for the serogroup Sejroe, which is one of the most prevalent serogroups in livestock. For this, we conducted a comparative analysis using >700 leptospiral genomic samples available in the public database. The analysis showed that the genes comprising the rfb locus are the main genetic factors associated with the serological classification. Samples from the serogroup Sejroe have an rfb locus with a conserved gene composition that differs from most other serogroups. Hebdomadis and Mini were the only serogroups whose samples have an rfb locus with similar gene composition to those from serogroup Sejroe, corroborating with the serological affinity shared by them. Finally, we could determine a small region in the rfb locus in which each of those three serogroups can be distinguished by its gene composition. This is the first work that uses an extensive repertoire of genomic data of leptospiral samples to elucidate the molecular basis of the serological classification and open the road to more reliable strategies based on molecular methods for serodiagnosis.

Taxallnomy: an extension of NCBI Taxonomy that produces a hierarchically complete taxonomic tree.

BACKGROUND: NCBI Taxonomy is the main taxonomic source for several bioinformatics tools and databases since all organisms with sequence accessions deposited on INSDC are organized in its hierarchical structure. Despite the extensive use and application of this data source, an alternative representation of data as a table would facilitate the use of information for processing bioinformatics data. To do so, since some taxonomic-ranks are missing in some lineages, an algorithm might propose provisional names for all taxonomic-ranks. RESULTS: To address this issue, we developed an algorithm that takes the tree structure from NCBI Taxonomy and generates a hierarchically complete taxonomic table, maintaining its compatibility with the original tree. The procedures performed by the algorithm consist of attempting to assign a taxonomic-rank to an existing clade or "no rank" node when possible, using its name as part of the created taxonomic-rank name (e.g. Ord_Ornithischia) or interpolating parent nodes when needed (e.g. Cla_of_Ornithischia), both examples given for the dinosaur Brachylophosaurus lineage. The new hierarchical structure was named Taxallnomy because it contains names for all taxonomic-ranks, and it contains 41 hierarchical levels corresponding to the 41 taxonomic-ranks currently found in the NCBI Taxonomy database. From Taxallnomy, users can obtain the complete taxonomic lineage with 41 nodes of all taxa available in the NCBI Taxonomy database, without any hazard to the original tree information. In this work, we demonstrate its applicability by embedding taxonomic information of a specified rank into a phylogenetic tree and by producing metagenomics profiles. CONCLUSION: Taxallnomy applies to any bioinformatics analyses that depend on the information from NCBI Taxonomy. Taxallnomy is updated periodically but with a distributed PERL script users can generate it locally using NCBI Taxonomy as input. All Taxallnomy resources are available at http://bioinfo.icb.ufmg.br/taxallnomy .

CORAZON: a web server for data normalization and unsupervised clustering based on expression profiles.

OBJECTIVE: Data normalization and clustering are mandatory steps in gene expression and downstream analyses, respectively. However, user-friendly implementations of these methodologies are available exclusively under expensive licensing agreements, or in stand-alone scripts developed, reflecting on a great obstacle for users with less computational skills. RESULTS: We developed an online tool called CORAZON (Correlations Analyses Zipper Online), which implements three unsupervised learning methods to cluster gene expression datasets in a friendly environment. It allows the usage of eight gene expression normalization/transformation methodologies and the attribute's influence. The normalizations requiring the gene length only could be performed to RNA-seq, meanwhile the others can be used with microarray and/or NanoString data. Clustering methodologies performances were evaluated through five models with accuracies between 92 and 100%. We applied our tool to obtain functional insights of non-coding RNAs (ncRNAs) based on Gene Ontology enrichment of clusters in a dataset generated by the ENCODE project. The clusters where the majority of transcripts are coding genes were enriched in Cellular, Metabolic, Transports, and Systems Development categories. Meanwhile, the ncRNAs were enriched in the Detection of Stimulus, Sensory Perception, Immunological System, and Digestion categories. CORAZON source-code is freely available at https://gitlab.com/integrativebioinformatics/corazon and the web-server can be accessed at http://corazon.integrativebioinformatics.me .

SWeeP: representing large biological sequences datasets in compact vectors.

Vectoral and alignment-free approaches to biological sequence representation have been explored in bioinformatics to efficiently handle big data. Even so, most current methods involve sequence comparisons via alignment-based heuristics and fail when applied to the analysis of large data sets. Here, we present "Spaced Words Projection (SWeeP)", a method for representing biological sequences using relatively small vectors while preserving intersequence comparability. SWeeP uses spaced-words by scanning the sequences and generating indices to create a higher-dimensional vector that is later projected onto a smaller randomly oriented orthonormal base. We constructed phylogenetic trees for all organisms with mitochondrial and bacterial protein data in the NCBI database. SWeeP quickly built complete and accurate trees for these organisms with low computational cost. We compared SWeeP to other alignment-free methods and Sweep was 10 to 100 times quicker than the other techniques. A tool to build SWeeP vectors is available at https://sourceforge.net/projects/spacedwordsprojection/.

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

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.

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

BACKGROUND: Bioinformaticians 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. RESULTS: Bioinformatics 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. CONCLUSIONS: Bioinformatics 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.

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.

Yeast two-hybrid liquid screening.

Yeast two-hybrid (YTH) method consists of a genetic trap that selects for "prey" cDNA products within a library that interact with a "bait" protein of interest. Here, we provide a protocol for YTH screening using a liquid medium screening method, which improves the sensitivity of this technique and streamlines the laborious classic screening in solid medium plates. The method uses a simple series of dilutions with established yeast strains transformed with diverse baits and complex cDNA libraries. This allows for prompt detection of positive clones revealed by liquid growth, due to activation of HIS3 reporter gene. Activation of a second reporter gene and reconstruction of the YTH interaction is highly reproducible using this system. This approach can either be performed using culture flasks or deep-well 96-well plates and the number of interactions obtained is similar, when compared to the classic method. In addition, the liquid screening method is faster and more economical for YTH screening and has the added benefit of automation if 96-well plates are used.

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

BACKGROUND: Biological function is greatly dependent on the interactions of proteins with other proteins and genes. Abstracts from the biomedical literature stored in the NCBI's 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. RESULTS: To 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. CONCLUSIONS: PESCADOR is a platform independent web resource available at: http://cbdm.mdc-berlin.de/tools/pescador/

Preimplantation development regulatory pathway construction through a text-mining approach.

BACKGROUND: The 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. RESULTS: In 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. CONCLUSIONS: The 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.

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

BACKGROUND: Biological 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. RESULTS: We created a text mining system (LAITOR: Literature Assistant for Identification of Terms co-Occurrences and Relationships) 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. CONCLUSIONS: Text 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.

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

BACKGROUND: Modern 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. RESULTS: We 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. CONCLUSION: The 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 set of amino acids found to occur more frequently in human and fly than in plant and yeast proteomes consists of non-essential amino acids.

We investigated the hypothesis that essential amino acids are being replaced in proteins by non-essential amino acids. We compared the amino acid composition in human, worm and fly proteomes, organisms that cannot synthesize all amino acids, with the amino acids of the proteomes of plant, bakers yeast and budding yeast, which are capable of synthesizing them. The analysis covered 460,737 proteins (212,197,907 amino acids). The data suggest a bias towards the usage of non-essential amino acids (mostly the set GAPQC) by metazoan organisms, except for the worm, a Pseudocoelomata. Our results support the hypothesis that non-essential amino acids have been substituting essential ones in the Coelomata.

Production of full-length cDNA sequences by sequencing and analysis of expressed sequence tags from Schistosoma mansoni

The number of sequences generated by genome projects has increased exponentially, but gene characterization has not followed at the same rate. Sequencing and analysis of full-length cDNAs is an important step in gene characterization that has been used nowadays by several research groups. In this work, we have selected Schistosoma mansoni clones for full-length sequencing, using an algorithm that investigates the presence of the initial methionine in the parasite sequence based on the positions of alignment start between two sequences. BLAST searches to produce such alignments have been performed using parasite expressed sequence tags produced by Minas Gerais Genome Network against sequences from the database Eukaryotic Cluster of Orthologous Groups (KOG). This procedure has allowed the selection of clones representing 398 proteins which have not been deposited as S. mansoni complete CDS in any public database. Dedicated sequencing of 96 of such clones with reads from both 5' and 3' ends has been performed. These reads have been assembled using PHRAP, resulting in the production of 33 full-length sequences that represent novel S. mansoni proteins. These results shall contribute to construct a more complete view of the biology of this important parasite.

Efficient secondary database driven annotation using model organism sequences.

The use of sequences from specific organisms for annotation requires that it does not represent great loss of information and that the sequences available suffice for annotation. In order to investigate whether or not sequences from model organisms may suffice for annotation of sequences from the trematode Schistosoma mansoni, we performed local BLAST searches of S. mansoni sequences against other organisms sequences present in the NCBI database nr. Results have been inserted into a relational database and hits to sequences from three model organisms, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens have been computed and compared to hits to sequences from other organisms present in nr; score values of each alignment have also been registered. Our observations have shown that a large fraction of orthologous proteins exists in the set of sequences from the three model organisms selected, and therefore a similar fraction of transcripts can be annotated when using either nr or model organism datasets. Moreover, hits to model organisms' sequences are largely as informative as nr. Results suggest that model organisms provide a reliable set of sequences to use as a reference database for S. mansoni sequence annotation, showing the clear possibility of using a restricted dataset of expected better quality for functional annotation and therefore supporting secondary database driven annotation approaches.

Production of full-length cDNA sequences by sequencing and analysis of expressed sequence tags from Schistosoma mansoni.

The number of sequences generated by genome projects has increased exponentially, but gene characterization has not followed at the same rate. Sequencing and analysis of full-length cDNAs is an important step in gene characterization that has been used nowadays by several research groups. In this work, we have selected Schistosoma mansoni clones for full-length sequencing, using an algorithm that investigates the presence of the initial methionine in the parasite sequence based on the positions of alignment start between two sequences. BLAST searches to produce such alignments have been performed using parasite expressed sequence tags produced by Minas Gerais Genome Network against sequences from the database Eukaryotic Cluster of Orthologous Groups (KOG). This procedure has allowed the selection of clones representing 398 proteins which have not been deposited as S. mansoni complete CDS in any public database. Dedicated sequencing of 96 of such clones with reads from both 5' and 3' ends has been performed. These reads have been assembled using PHRAP, resulting in the production of 33 full-length sequences that represent novel S. mansoni proteins. These results shall contribute to construct a more complete view of the biology of this important parasite.

Accessing optimal primer distance from insert.

When building either DNA or cDNA libraries, a researcher looks at the vector multiple cloning site and chooses which restriction enzyme(s) will be used to clone the inserts. Although this procedure does not seem to be important, the accurate choosing of primer to insert distance can save time and money from genome and transcriptome projects. Here, 846 single-pool pUC18 sequences were produced and compared with the pUC18 consensus using local alignment tools. Data show that reads often contain 0-20 miscalled bases at the beginning of read and noise to signal transition is frequently found at 46-54 bases from the first 3' base downstream the sequencing primer. For SWAT-based approaches, 60 bases was the distance where over 90% of the sequences provided reliable information, presenting 13 vector bases on average. Looking at the data, it is possible to choose the most appropriate primer to insert distance for many applications.

Evaluation of alternative reporter genes for the yeast two-hybrid system.

The yeast two-hybrid system is a powerful tool for screening protein-protein interactions and has also been used for large-scale studies. We evaluated two protein-coding sequences as reporter genes for the yeast two-hybrid system, to determine if it was suitable as an alternative screening strategy. Aspergillus awamori glucoamylase activity results in clear haloes around colonies producing this enzyme after growth on starch plates and staining with iodine vapors. However, transcription activation by Gal4 on Gal-regulated promoters was insufficient for this type of phenotypic visualization. A modified gene of Aequoria victoria enhanced green fluorescent protein (EGFP) was tested to determine its suitability for interaction screenings with flow cytometry. When the EGFP reporter gene system was incorporated into the cells, Gal4 transcriptional activation produced sufficient fluorescence for detection with the flow cytometer, especially when there were strong interactions.

Molecular basis for pacemaker cells in epithelia.

Intercellular signaling is highly coordinated in excitable tissues such as heart, but the organization of intercellular signaling in epithelia is less clear. We examined Ca(2+) signaling in hepatoma cells expressing the hepatocyte gap junction protein connexin32 (cx32) or the cardiac gap junction protein cx43, plus a fluorescently tagged V(1a) vasopressin receptor (V(1a)R). Release of inositol 1,4,5-trisphosphate (InsP(3)) in wild type cells increased Ca(2+) in the injected cell but not in neighboring cells, while the Ca(2+) signal spread to neighbors when gap junctions were expressed. Photorelease of caged Ca(2+) rather than InsP(3) resulted in a small increase in Ca(2+) that did not spread to neighbors with or without gap junctions. However, photorelease of Ca(2+) in cells stimulated with low concentrations of vasopressin resulted in a much larger increase in Ca(2+), which spread to neighbors via gap junctions. Cells expressing tagged V(1a)R similarly had increased sensitivity to vasopressin, and could signal to neighbors via gap junctions. Higher concentrations of vasopressin elicited Ca(2+) signals in all cells. In cx32 or cx43 but not in wild type cells, this signaling was synchronized and began in cells expressing the tagged V(1a)R. Thus, intercellular Ca(2+) signals in epithelia are organized by three factors: 1) InsP(3) must be generated in each cell to support a Ca(2+) signal in that cell; 2) gap junctions are necessary to synchronize Ca(2+) signals among cells; and 3) cells with relatively increased expression of hormone receptor will initiate Ca(2+) signals and thus serve as pacemakers for their neighbors. Together, these factors may allow epithelia to act in an integrated, organ-level fashion rather than as a collection of isolated cells.