Predicting protein functions with message passing algorithms

Motivation: In the last few years a growing interest in biology has been shifting towards the problem of optimal information extraction from the huge amount of data generated via large scale and high-throughput techniques. One of the most relevant issues has recently become that of correctly and reliably predicting the functions of observed but still functionally undetermined proteins starting from information coming from the network of co-observed proteins of known functions. Method: The method proposed in this article is based on a message passing algorithm known as Belief Propagation, which takes as input the network of proteins physical interactions and a catalog of known proteins functions, and returns the probabilities for each unclassified protein of having one chosen function. The implementation of the algorithm allows for fast on-line analysis, and can be easily generalized to more complex graph topologies taking into account hyper-graphs, {\em i.e.} complexes of more than two interacting proteins.Comment: 12 pages, 9 eps figures, 1 additional html tabl

Alien Registration- Marcotte, Marie M. (Lewiston, Androscoggin County)

https://digitalmaine.com/alien_docs/28989/thumbnail.jp

Consumer behavior relationship between mothers and their adult daughters

The purpose of this exploratory study was to examine the consumer behavior relationship between mothers and their adult daughters. Intergenerational influences (IGI), communication patterns, and the length of time adult daughters lived with their mothers are variables explored in this study. The results of this study suggested that, although the adult daughter seems to have a meaningful relationship with her mother, the only significant correlation was between mother-daughter communication patterns and the mother\u27s role in her adult daughter\u27s consumer behavior

Consumer behavior relationship between mothers and their adult daughters

The purpose of this exploratory study was to examine the consumer behavior relationship between mothers and their adult daughters. Intergenerational influences (IGI), communication patterns, and the length of time adult daughters lived with their mothers are variables explored in this study. The results of this study suggested that, although the adult daughter seems to have a meaningful relationship with her mother, the only significant correlation was between mother-daughter communication patterns and the mother\u27s role in her adult daughter\u27s consumer behavior

Group II Intron Protein Localization and Insertion Sites Are Affected by Polyphosphate

Mobile group II introns consist of a catalytic intron RNA and an intron-encoded protein with reverse transcriptase activity, which act together in a ribonucleoprotein particle to promote DNA integration during intron mobility. Previously, we found that the Lactococcus lactis Ll.LtrB intron-encoded protein (LtrA) expressed alone or with the intron RNA to form ribonucleoprotein particles localizes to bacterial cellular poles, potentially accounting for the intron's preferential insertion in the oriC and ter regions of the Escherichia coli chromosome. Here, by using cell microarrays and automated fluorescence microscopy to screen a transposon-insertion library, we identified five E. coli genes (gppA, uhpT, wcaK, ynbC, and zntR) whose disruption results in both an increased proportion of cells with more diffuse LtrA localization and a more uniform genomic distribution of Ll.LtrB-insertion sites. Surprisingly, we find that a common factor affecting LtrA localization in these and other disruptants is the accumulation of intracellular polyphosphate, which appears to bind LtrA and other basic proteins and delocalize them away from the poles. Our findings show that the intracellular localization of a group II intron-encoded protein is a major determinant of insertion-site preference. More generally, our results suggest that polyphosphate accumulation may provide a means of localizing proteins to different sites of action during cellular stress or entry into stationary phase, with potentially wide physiological consequences.This work was supported by National Institutes of Health R01 grants GM037949 to AML and GM076536 to EMM, Welch Foundation grants F-1607 to AML and F-1515 to EMM, and a Packard Foundation fellowship to EMM.Cellular and Molecular Biolog

Prediction of gene–phenotype associations in humans, mice, and plants using phenologs

All authors are with the Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, TX 78712, USA. -- Ulf Martin Singh-Blom is with the Program in Computational and Applied Mathematics, The University of Texas at Austin, Austin, TX 78712, USA, and th Unit of Computational Medicine, Department of Medicine, Karolinska Institutet, Stockholm 171 76, Sweden. -- Kriston L. McGary is with the Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA.Background: Phenotypes and diseases may be related to seemingly dissimilar phenotypes in other species by means of the orthology of underlying genes. Such “orthologous phenotypes,” or “phenologs,” are examples of deep homology, and may be used to predict additional candidate disease genes. Results: In this work, we develop an unsupervised algorithm for ranking phenolog-based candidate disease genes through the integration of predictions from the k nearest neighbor phenologs, comparing classifiers and weighting functions by cross-validation. We also improve upon the original method by extending the theory to paralogous phenotypes. Our algorithm makes use of additional phenotype data — from chicken, zebrafish, and E. coli, as well as new datasets for C. elegans — establishing that several types of annotations may be treated as phenotypes. We demonstrate the use of our algorithm to predict novel candidate genes for human atrial fibrillation (such as HRH2, ATP4A, ATP4B, and HOPX) and epilepsy (e.g., PAX6 and NKX2-1). We suggest gene candidates for pharmacologically-induced seizures in mouse, solely based on orthologous phenotypes from E. coli. We also explore the prediction of plant gene–phenotype associations, as for the Arabidopsis response to vernalization phenotype. Conclusions: We are able to rank gene predictions for a significant portion of the diseases in the Online Mendelian Inheritance in Man database. Additionally, our method suggests candidate genes for mammalian seizures based only on bacterial phenotypes and gene orthology. We demonstrate that phenotype information may come from diverse sources, including drug sensitivities, gene ontology biological processes, and in situ hybridization annotations. Finally, we offer testable candidates for a variety of human diseases, plant traits, and other classes of phenotypes across a wide array of species.Center for Systems and Synthetic BiologyInstitute for Cellular and Molecular [email protected]

Transiently Transfected Purine Biosynthetic Enzymes Form Stress Bodies

It has been hypothesized that components of enzymatic pathways might organize into intracellular assemblies to improve their catalytic efficiency or lead to coordinate regulation. Accordingly, de novo purine biosynthesis enzymes may form a purinosome in the absence of purines, and a punctate intracellular body has been identified as the purinosome. We investigated the mechanism by which human de novo purine biosynthetic enzymes might be organized into purinosomes, especially under differing cellular conditions. Irregardless of the activity of bodies formed by endogenous enzymes, we demonstrate that intracellular bodies formed by transiently transfected, fluorescently tagged human purine biosynthesis proteins are best explained as protein aggregation.This work was supported by grants from the United States National Institutes of Health, National Science Foundation, and Welch (F1515) and Packard Foundations to EMM. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Cellular and Molecular Biolog

Age-Dependent Evolution of the Yeast Protein Interaction Network Suggests a Limited Role of Gene Duplication and Divergence

Proteins interact in complex protein–protein interaction (PPI) networks whose topological properties—such as scale-free topology, hierarchical modularity, and dissortativity—have suggested models of network evolution. Currently preferred models invoke preferential attachment or gene duplication and divergence to produce networks whose topology matches that observed for real PPIs, thus supporting these as likely models for network evolution. Here, we show that the interaction density and homodimeric frequency are highly protein age–dependent in real PPI networks in a manner which does not agree with these canonical models. In light of these results, we propose an alternative stochastic model, which adds each protein sequentially to a growing network in a manner analogous to protein crystal growth (CG) in solution. The key ideas are (1) interaction probability increases with availability of unoccupied interaction surface, thus following an anti-preferential attachment rule, (2) as a network grows, highly connected sub-networks emerge into protein modules or complexes, and (3) once a new protein is committed to a module, further connections tend to be localized within that module. The CG model produces PPI networks consistent in both topology and age distributions with real PPI networks and is well supported by the spatial arrangement of protein complexes of known 3-D structure, suggesting a plausible physical mechanism for network evolution

Normal Ribosomal Biogenesis but Shortened Protein Synthetic Response to Acute Eccentric Resistance Exercise in Old Skeletal Muscle.

Anabolic resistance to feeding in aged muscle is well-characterized; however, whether old skeletal muscle is intrinsically resistant to acute mechanical loading is less clear. The aim of this study was to determine the impact of aging on muscle protein synthesis (MPS), ribosome biogenesis, and protein breakdown in skeletal muscle following a single bout of resistance exercise. Adult male F344/BN rats aged 10 (Adult) and 30 (Old) months underwent unilateral maximal eccentric contractions of the hindlimb. Precursor rRNA increased early post-exercise (6-18 h), preceding elevations in ribosomal mass at 48 h in Adult and Old; there were no age-related differences in these responses. MPS increased early post-exercise in both Adult and Old; however, at 48 h of recovery, MPS returned to baseline in Old but not Adult. This abbreviated protein synthesis response in Old was associated with decreased levels of IRS1 protein and increased BiP, CHOP and eIF2α levels. Other than these responses, anabolic signaling was similar in Adult and Old muscle in the acute recovery phase. Basal proteasome activity was lower in Old, and resistance exercise did not increase the activity of either the ATP-dependent or independent proteasome, or autophagy (Cathepsin L activity) in either Adult or Old muscle. We conclude that MPS and ribosome biogenesis in response to maximal resistance exercise in old skeletal muscle are initially intact; however, the MPS response is abbreviated in Old, which may be the result of ER stress and/or blunted exercise-induced potentiation of the MPS response to feeding