68 research outputs found
Squid – a simple bioinformatics grid
BACKGROUND: BLAST is a widely used genetic research tool for analysis of similarity between nucleotide and protein sequences. This paper presents a software application entitled "Squid" that makes use of grid technology. The current version, as an example, is configured for BLAST applications, but adaptation for other computing intensive repetitive tasks can be easily accomplished in the open source version. This enables the allocation of remote resources to perform distributed computing, making large BLAST queries viable without the need of high-end computers. RESULTS: Most distributed computing / grid solutions have complex installation procedures requiring a computer specialist, or have limitations regarding operating systems. Squid is a multi-platform, open-source program designed to "keep things simple" while offering high-end computing power for large scale applications. Squid also has an efficient fault tolerance and crash recovery system against data loss, being able to re-route jobs upon node failure and recover even if the master machine fails. Our results show that a Squid application, working with N nodes and proper network resources, can process BLAST queries almost N times faster than if working with only one computer. CONCLUSION: Squid offers high-end computing, even for the non-specialist, and is freely available at the project web site. Its open-source and binary Windows distributions contain detailed instructions and a "plug-n-play" instalation containing a pre-configured example
AnEnPi: Identification and annotation of analogous enzymes
Enzymes are responsible for the catalysis of the biochemical reactions in metabolic pathways. Analogous enzymes are able to catalyze the same reactions, but they present no significant sequence similarity at the primary level, and possibly different tertiary structures as well. They are thought to have arisen as the result of independent evolutionary events. A detailed study of analogous enzymes may reveal new catalytic mechanisms, add information about the origin and evolution of biochemical pathways and disclose potential targets for drug development.
Results: In this work, we have constructed and implemented a new approach, AnEnPi (the Analogous Enzyme Pipeline), using a combination of bioinformatics tools like BLAST, HMMer, and in-house scripts, to assist in the identification, annotation, comparison and study of analogous and homologous enzymes. The algorithm for the detection of analogy is based i) on the construction of groups of homologous enzymes and ii) on the identification of cases where a given enzymatic activity is performed by two or more proteins without significant similarity between their primary structures. We applied this approach to a dataset obtained from KEGG Comprising all annotated enzymes, which resulted in the identification of 986 EC classes where putative analogy was detected (40.5% of all EC classes). AnEnPi is of considerable value in the construction of initial datasets that can be further curated, particularly in gene and genome annotation, in studies involving molecular evolution and metabolism and in the identification of new potential drug targets.
Conclusion: AnEnPi is an efficient tool for detection and annotation of analogous enzymes and other enzymes in whole genomes
Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment
<p>Abstract</p> <p>Background</p> <p><it>Trypanosoma cruzi </it>is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of <it>Trypanosoma cruzi </it>versus <it>Homo sapiens</it>.</p> <p>Results</p> <p>We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of <it>T</it>. <it>cruzi</it>. In combination with comparative genome analysis to <it>Homo sapiens</it>, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite.</p> <p>Conclusions</p> <p>In this work, we present a set of 397 enzyme models of <it>T</it>. <it>cruzi </it>that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to <it>H. sapiens </it>enzymes, were identified as new potential molecular targets.</p
Proteomic profile of culture filtrate from the Brazilian vaccine strain Mycobacterium bovis BCG Moreau compared to M. bovis BCG Pasteur
<p>Abstract</p> <p>Background</p> <p>Bacille Calmette-Guerin (BCG) is currently the only available vaccine against tuberculosis (TB) and comprises a heterogeneous family of sub-strains with genotypic and phenotypic differences. The World Health Organization (WHO) affirms that the characterization of BCG sub-strains, both on genomic and proteomic levels, is crucial for a better comprehension of the vaccine. In addition, these studies can contribute in the development of a more efficient vaccine against TB. Here, we combine two-dimensional electrophoresis (2DE) and mass spectrometry to analyse the proteomic profile of culture filtrate proteins (CFPs) from <it>M. bovis </it>BCG Moreau, the Brazilian vaccine strain, comparing it to that of BCG Pasteur. CFPs are considered of great importance given their dominant immunogenicity and role in pathogenesis, being available for interaction with host cells since early infection.</p> <p>Results</p> <p>The 2DE proteomic map of <it>M. bovis </it>BCG Moreau CFPs in the pH range 3 - 8 allowed the identification of 158 spots corresponding to 101 different proteins, identified by MS/MS. Comparison to BCG Pasteur highlights the great similarity between these BCG strains. However, quantitative analysis shows a higher expression of immunogenic proteins such as Rv1860 (BCG1896, Apa), Rv1926c (BCG1965c, Mpb63) and Rv1886c (BCG1923c, Ag85B) in BCG Moreau when compared to BCG Pasteur, while some heat shock proteins, such as Rv0440 (BCG0479, GroEL2) and Rv0350 (BCG0389, DnaK), show the opposite pattern.</p> <p>Conclusions</p> <p>Here we report the detailed 2DE profile of CFPs from <it>M. bovis </it>BCG Moreau and its comparison to BCG Pasteur, identifying differences that may provide relevant information on vaccine efficacy. These findings contribute to the detailed characterization of the Brazilian vaccine strain against TB, revealing aspects that may lead to a better understanding of the factors leading to BCG's variable protective efficacy against TB.</p
Biodegradação de matéria orgânica em lama sedimentada - definição de parâmetros na lagoa de piratininga, RJ: Biodegradation of organic matter in the sedimented mud - parameters definition at the piratininga lagoon, RJ
Entre março e julho/22, duas tecnologias complementares, EM® e Pulmão™, foram testadas para estudar a biorremediação na camada de lama da Lagoa de Piratininga, Niterói, RJ. Dados ortométricos, matéria orgânica, carbono orgânico, nitrogênio Kjeldahl total, fósforo e biopolímeros foram quantificados na superfície do sedimento. As concentrações crescentes de nitrogênio Kjeldahl indicaram aportes de esgoto doméstico ao sistema. O fósforo orgânico predominou sobre o total, pois foi consumido no processo de biorremediação. Ocorreram mudanças quali- quantitativas na composição da matéria orgânica lábil, com consumo de lipídio, molécula recalcitrante, e produção de proteínas e carboidratos. Os dados altimétricos indicaram maior tendência de consumo da lama na área que reuniu as tecnologias EM1®+Pulmão™, onde o aporte sedimentar foi praticamente anulado. Houve uma diminuição da espessura da lama, refletindo no aumento sutil de profundidade superficial da camada sedimentar. Estas modificações nas áreas experimentais indicam que o processo de restauração ambiental está ocorrendo
An oligonucleotide probe derived from kDNA minirepeats is specific for Leishmania (Viannia)
ReRep: Computational detection of repetitive sequences in genome survey sequences (GSS)
<p>Abstract</p> <p>Background</p> <p>Genome survey sequences (GSS) offer a preliminary global view of a genome since, unlike ESTs, they cover coding as well as non-coding DNA and include repetitive regions of the genome. A more precise estimation of the nature, quantity and variability of repetitive sequences very early in a genome sequencing project is of considerable importance, as such data strongly influence the estimation of genome coverage, library quality and progress in scaffold construction. Also, the elimination of repetitive sequences from the initial assembly process is important to avoid errors and unnecessary complexity. Repetitive sequences are also of interest in a variety of other studies, for instance as molecular markers.</p> <p>Results</p> <p>We designed and implemented a straightforward pipeline called ReRep, which combines bioinformatics tools for identifying repetitive structures in a GSS dataset. In a case study, we first applied the pipeline to a set of 970 GSSs, sequenced in our laboratory from the human pathogen <it>Leishmania braziliensis</it>, the causative agent of leishmaniosis, an important public health problem in Brazil. We also verified the applicability of ReRep to new sequencing technologies using a set of 454-reads of an <it>Escheria coli</it>. The behaviour of several parameters in the algorithm is evaluated and suggestions are made for tuning of the analysis.</p> <p>Conclusion</p> <p>The ReRep approach for identification of repetitive elements in GSS datasets proved to be straightforward and efficient. Several potential repetitive sequences were found in a <it>L. braziliensis </it>GSS dataset generated in our laboratory, and further validated by the analysis of a more complete genomic dataset from the EMBL and Sanger Centre databases. ReRep also identified most of the <it>E. coli </it>K12 repeats prior to assembly in an example dataset obtained by automated sequencing using 454 technology. The parameters controlling the algorithm behaved consistently and may be tuned to the properties of the dataset, in particular to the length of sequencing reads and the genome coverage. ReRep is freely available for academic use at <url>http://bioinfo.pdtis.fiocruz.br/ReRep/</url>.</p
The Next Generation Scientist program: capacity-building for future scientific leaders in low- and middle-income countries
Background
Scientific and professional development opportunities for early career scientists in low- and middle- income countries (LMICs) are limited and not consistent. There is a disproportionately low number of biomedical and clinical researchers in LMIC’s relative to their high burden of disease, a disparity that is aggravated by emigration of up to 70% of scientists from their countries of birth for education and employment elsewhere. To help address this need, a novel University-accredited, immersive fellowship program was established by a large public-academic-private network. We sought to describe the program and summarize progress and lessons learned over its first 7-years.
Methods
Hallmarks of the program are a structured learning curriculum and bespoke research activities tailored to the needs of each fellow. Research projects expose the scientists to state-of-the-art methodologies and leading experts in their fields while also ensuring that learnings are implementable within their home infrastructure. Fellows run seminars on drug discovery and development that reinforce themes of scientific leadership and teamwork together with practical modules on addressing healthcare challenges within their local systems. Industry mentors achieve mutual learning to better understand healthcare needs in traditionally underserved settings. We evaluated the impact of the program through an online survey of participants and by assessing research output.
Results
More than 140 scientists and clinicians from 25 countries participated over the 7-year period. Evaluation revealed strong evidence of knowledge and skills transfer, and beneficial self-reported impact on fellow’s research output and career trajectories. Examples of program impact included completion of post-graduate qualifications; establishment and implementation of good laboratory- and clinical- practice mechanisms; and becoming lead investigators in local programs. There was a high retention of fellows in their home countries (> 75%) and an enduring professional network among the fellows and their mentors.
Conclusions
Our experience demonstrates an example for how multi-sectoral partners can contribute to scientific and professional development of researchers in LMICs and supports the idea that capacity-building efforts should be tailored to the specific needs of beneficiaries to be maximally effective. Lessons learned may be applied to the design and conduct of other programs to strengthen science ecosystems in LMICs
Oral Administration of GW788388, an Inhibitor of Transforming Growth Factor Beta Signaling, Prevents Heart Fibrosis in Chagas Disease
Cardiac damage and dysfunction are prominent features in patients with chronic Chagas disease, which is caused by infection with the protozoan parasite Trypanosoma cruzi (T. cruzi) and affects 10–12 million individuals in South and Central America. Our group previously reported that transforming growth factor beta (TGFß) is implicated in several regulatory aspects of T. cruzi invasion and growth and in host tissue fibrosis. In the present work, we evaluated the therapeutic action of an oral inhibitor of TGFß signaling (GW788388) administered during the acute phase of experimental Chagas disease. GW788388 treatment significantly reduced mortality and decreased parasitemia. Electrocardiography showed that GW788388 treatment was effective in protecting the cardiac conduction system, preserving gap junction plaque distribution and avoiding the development of cardiac fibrosis. Inhibition of TGFß signaling in vivo appears to potently decrease T. cruzi infection and to prevent heart damage in a preclinical mouse model. This suggests that this class of molecules may represent a new therapeutic tool for acute and chronic Chagas disease that warrants further pre-clinical exploration. Administration of TGFß inhibitors during chronic infection in mouse models should be further evaluated, and future clinical trials should be envisaged
GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data
<p>Abstract</p> <p>Background</p> <p>Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge.</p> <p>Results</p> <p>Here we present a new algorithm, termed GO Explorer (GOEx), that leverages the gene ontology (GO) to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172). We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few.</p> <p>Conclusion</p> <p>GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at <url>http://pcarvalho.com/patternlab</url>.</p
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