Resistance Training Modulates Reticulum Endoplasmic Stress, Independent of Oxidative and Inflammatory Responses, in Elderly People

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Abstract

Aging is related to changes in the redox status, low-grade inflammation, and decreased endoplasmic reticulum unfolded protein response (UPR). Exercise has been shown to regulate the inflammatory response, balance redox homeostasis, and ameliorate the UPR. This work aimed to investigate the effects of resistance training on changes in the UPR, oxidative status, and inflammatory responses in peripheral blood mononuclear cells of elderly subjects. Thirty elderly subjects volunteered to participate in an 8-week resistance training program, and 11 youth subjects were included for basal assessments. Klotho, heat shock protein 60 (HSP60), oxidative marker expression (catalase, glutathione, lipid peroxidation, nuclear factor erythroid 2-related factor 2, protein carbonyls, reactive oxygen species, and superoxide dismutase 1 and 2), the IRE1 arm of UPR, and TLR4/TRAF6/pIRAK1 pathway activation were evaluated before and following training. No changes in the HSP60 and Klotho protein content, oxidative status markers, and TLR4/TRAF6/pIRAK1 pathway activation were found with exercise. However, an attenuation of the reduced pIRE1/IRE1 ratio was observed following training. Systems biology analysis showed that a low number of proteins (RPS27A, SYVN1, HSPA5, and XBP1) are associated with IRE1, where XBP1 and RPS27A are essential nodes according to the centrality analysis. Additionally, a gene ontology analysis confirms that endoplasmic reticulum stress is a key mechanism modulated by IRE1. These findings might partially support the modulatory effect of resistance training on the endoplasmic reticulum in the elderly.

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Paul Shannon, Andrew Markiel, Owen Ozier … (2003)

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

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Arthur Liberzon, Chet Birger, Helga Thorvaldsdóttir … (2015)

The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.

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The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets

Damian Szklarczyk, Annika Gable, Katerina C. Nastou … (2020)

Abstract Cellular life depends on a complex web of functional associations between biomolecules. Among these associations, protein–protein interactions are particularly important due to their versatility, specificity and adaptability. The STRING database aims to integrate all known and predicted associations between proteins, including both physical interactions as well as functional associations. To achieve this, STRING collects and scores evidence from a number of sources: (i) automated text mining of the scientific literature, (ii) databases of interaction experiments and annotated complexes/pathways, (iii) computational interaction predictions from co-expression and from conserved genomic context and (iv) systematic transfers of interaction evidence from one organism to another. STRING aims for wide coverage; the upcoming version 11.5 of the resource will contain more than 14 000 organisms. In this update paper, we describe changes to the text-mining system, a new scoring-mode for physical interactions, as well as extensive user interface features for customizing, extending and sharing protein networks. In addition, we describe how to query STRING with genome-wide, experimental data, including the automated detection of enriched functionalities and potential biases in the user's query data. The STRING resource is available online, at https://string-db.org/.