Inferring modules of functionally interacting proteins using the Bond Energy Algorithm

<p>Abstract</p> <p>Background</p> <p>Non-homology based methods such as phylogenetic profiles are effective for predicting functional relationships between proteins with no considerable sequence or structure similarity. Those methods rely heavily on traditional similarity metrics defined on pairs of phylogenetic patterns. Proteins do not exclusively interact in pairs as the final biological function of a protein in the cellular context is often hold by a group of proteins. In order to accurately infer modules of functionally interacting proteins, the consideration of not only direct but also indirect relationships is required.</p> <p>In this paper, we used the Bond Energy Algorithm (<it>BEA</it>) to predict functionally related groups of proteins. With <it>BEA </it>we create clusters of phylogenetic profiles based on the associations of the surrounding elements of the analyzed data using a metric that considers linked relationships among elements in the data set.</p> <p>Results</p> <p>Using phylogenetic profiles obtained from the Cluster of Orthologous Groups of Proteins (<it>COG</it>) database, we conducted a series of clustering experiments using <it>BEA </it>to predict (upper level) relationships between profiles. We evaluated our results by comparing with <it>COG's </it>functional categories, And even more, with the experimentally determined functional relationships between proteins provided by the <it>DIP </it>and <it>ECOCYC </it>databases. Our results demonstrate that <it>BEA </it>is capable of predicting meaningful modules of functionally related proteins. <it>BEA </it>outperforms traditionally used clustering methods, such as <it>k</it>-means and hierarchical clustering by predicting functional relationships between proteins with higher accuracy.</p> <p>Conclusion</p> <p>This study shows that the linked relationships of phylogenetic profiles obtained by <it>BEA </it>is useful for detecting functional associations between profiles and extending functional modules not found by traditional methods. <it>BEA </it>is capable of detecting relationship among phylogenetic patterns by linking them through a common element shared in a group. Additionally, we discuss how the proposed method may become more powerful if other criteria to classify different levels of protein functional interactions, as gene neighborhood or protein fusion information, is provided.</p

Molecular chaperone-mediated rescue of mitophagy by a Parkin RING1 domain mutant

Mitochondrial dysfunction is characteristic of many neurodegenerative diseases. The Parkinson's disease-associated ubiquitin–protein ligase, Parkin, is important in the elimination of damaged mitochondria by autophagy (mitophagy) in a multistep process. Here, we show that a Parkin RING domain mutant (C289G) fails to redistribute to damaged mitochondria and cannot induce mitophagy after treatment with the mitochondrial uncoupler carbonyl cyanide m-methylhydrazone, because of protein misfolding and aggregation. Parkin(C289G) aggregation and inclusion formation were suppressed by the neuronal DnaJ/Hsp40 chaperone HSJ1a(DNAJB2a). Importantly, HSJ1a and DNAJB6 also restored mitophagy by promoting the relocation of Parkin(C289G) and the autophagy marker LC3 to depolarized mitochondria. The rescue of Parkin activity and suppression of aggregation were J domain dependent for HSJ1a, suggesting the involvement of Hsp70 in these processes, but were not dependent on the HSJ1a ubiquitin interaction motif. HSJ1a expression did not enhance mitophagy mediated by wild-type Parkin. These data show the potential of molecular chaperones to mediate the functional recovery of Parkin misfolding mutants and to combat deficits associated with Parkin aggregation in Parkinson's disease

Inference of Functional Relations in Predicted Protein Networks with a Machine Learning Approach

Background: Molecular biology is currently facing the challenging task of functionally characterizing the proteome. The large number of possible protein-protein interactions and complexes, the variety of environmental conditions and cellular states in which these interactions can be reorganized, and the multiple ways in which a protein can influence the function of others, requires the development of experimental and computational approaches to analyze and predict functional associations between proteins as part of their activity in the interactome. Methodology/Principal Findings: We have studied the possibility of constructing a classifier in order to combine the output of the several protein interaction prediction methods. The AODE (Averaged One-Dependence Estimators) machine learning algorithm is a suitable choice in this case and it provides better results than the individual prediction methods, and it has better performances than other tested alternative methods in this experimental set up. To illustrate the potential use of this new AODE-based Predictor of Protein InterActions (APPIA), when analyzing high-throughput experimental data, we show how it helps to filter the results of published High-Throughput proteomic studies, ranking in a significant way functionally related pairs. Availability: All the predictions of the individual methods and of the combined APPIA predictor, together with the used datasets of functional associations are available at http://ecid.bioinfo.cnio.es/. Conclusions: We propose a strategy that integrates the main current computational techniques used to predict functional associations into a unified classifier system, specifically focusing on the evaluation of poorly characterized protein pairs. We selected the AODE classifier as the appropriate tool to perform this task. AODE is particularly useful to extract valuable information from large unbalanced and heterogeneous data sets. The combination of the information provided by five prediction interaction prediction methods with some simple sequence features in APPIA is useful in establishing reliability values and helpful to prioritize functional interactions that can be further experimentally characterized.This work was funded by the BioSapiens (grant number LSHG-CT-2003-503265) and the Experimental Network for Functional Integration (ENFIN) Networks of Excellence (contract number LSHG-CT-2005-518254), by Consolider BSC (grant number CSD2007-00050) and by the project “Functions for gene sets” from the Spanish Ministry of Education and Science (BIO2007-66855). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Trasformaciones eclesiales. Propuestas del papa Francisco para una iglesia en pastoral

Jorge Mario Bergoglio llegó al Vaticano con un sentido de autocrítica y con el propósito de hacer cambios sustanciales. Lo que propone el papa es que la Iglesia católica deje de ser autorreferencial, salga de sí misma y vaya hacia las periferias, no solo geográficas sino también las existenciales. Sin embargo, todo cambio enfrenta inercias, más cuando se busca una trasformación desde dentro de una institución milenaria. En este libro, académicos de cinco universidades mexicanas analizan la figura, el discurso y las acciones de Francisco en sus primeros años en la sede papal, así como las críticas internas y externas a su labor, lo que permite dimensionar el alcance de la tarea que se ha impuesto el sumo pontífice

Significance of the parkin and PINK1 gene in Jordanian families with incidences of young-onset and juvenile parkinsonism

<p>Abstract</p> <p>Background</p> <p>Parkinson's disease is a progressive neurodegenerative disorder, where most cases are sporadic with a late onset. In rare incidences familial forms of early-onset parkinsonism occur, and when recessively inherited, cases are often explained by mutations in either the <it>parkin </it>(PARK2) or <it>PINK1 </it>(PARK6) gene or on exceptional occasions the <it>DJ-1 </it>(PARK7) or <it>ATP13A2 </it>(PARK9) gene. Recessively inherited deletions/duplications and point mutations in the <it>parkin </it>gene are the most common cause of early-onset parkinsonism known so far, but in an increasing number of studies, genetic variations in the serine/threonine kinase domain of the <it>PINK1 </it>gene are found to explain early-onset parkinsonism.</p> <p>Methods</p> <p>In this study all families were from a population with a high incidence of consanguinity. We investigated 11 consanguineous families comprising 17 affected with recessively inherited young-onset parkinsonism for mutations both in the <it>parkin </it>and <it>PINK1 </it>gene. Exons and flanking regions were sequenced, and segregation patterns of genetic variation were assessed in members of the respective families. An exon dosage analysis was performed for all exons in both genes.</p> <p>Results</p> <p>In the <it>parkin </it>gene, a three generation family was identified with an exon 4 deletion segregating with disease. Both affected were homozygous for the deletion that segregated on a haplotype that spanned the gene in a haplotype segregation analysis that was performed using additional markers. Exon dosage analysis confirmed the recessive pattern of inheritance with heterozygous deletions segregating in healthy family members. In the <it>PINK1 </it>gene we identified two novel putative pathogenic substitutions, P416R and S419P, located in a conserved motif of the serine/threonine kinase domain. Both substitutions segregated with disease in agreement with a recessive pattern of inheritance within respective families and both were present as homozygous in two affected each. We also discuss common polymorphisms in the two genes found to be co-segregating within families.</p> <p>Conclusion</p> <p>Our results further extend on the involvement of <it>PINK1 </it>mutations in recessive early-onset parkinsonism with clinical features similar to carriers of <it>parkin </it>mutations.</p

Regulation of the co-evolved HrpR and HrpS AAA+ proteins required for Pseudomonas syringae pathogenicity.

Published versio

Ética, hermenéutica y política. Filosofía en el fondo

Esta obra colectiva de ensayos académicos dictaminados, inspirados en el ciclo de conferencias Filosofía en el Fondo, ofrece una rica y entretejida lectura que, en cuatro secciones (La ética ante el problema del mal, Diferencia y alteridad, Hermenéutica de la modernidad, e Intersticios políticos), profundiza los problemas humanos que resisten el paso del tiempo desde enfoques hermenéuticos, genealógicos y críticos.ITESO, A.C