For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
1
views
83
references
 Top references
cited by
1
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      256
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Modeling exercise using optogenetically contractible Drosophila larvae

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The pathophysiological effects of a number of metabolic and age-related disorders can be prevented to some extent by exercise and increased physical activity. However, the molecular mechanisms that contribute to the beneficial effects of muscle activity remain poorly explored. Availability of a fast, inexpensive, and genetically tractable model system for muscle activity and exercise will allow the rapid identification and characterization of molecular mechanisms that mediate the beneficial effects of exercise. Here, we report the development and characterization of an optogenetically-inducible muscle contraction (OMC) model in Drosophila larvae that we used to study acute exercise-like physiological responses. To characterize muscle-specific transcriptional responses to acute exercise, we performed bulk mRNA-sequencing, revealing striking similarities between acute exercise-induced genes in flies and those previously identified in humans. Our larval muscle contraction model opens a path for rapid identification and characterization of exercise-induced factors.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12864-022-08845-6.

          Related collections

          Most cited references83

          • Record: found
          • Abstract: found
          • Article: not found

          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          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.
          Article 0 comments Cited 11214 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Guangchuang Yu, Li-Gen Wang, Yanyan Han … (2012)
            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
            Article 0 comments Cited 11197 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A PGC1α-dependent myokine that drives browning of white fat and thermogenesis

              Pontus Boström, Yao-jun Wu, Mark P. Jedrychowski … (2012)
              Exercise benefits a variety of organ systems in mammals, and some of the best-recognized effects of exercise on muscle are mediated by the transcriptional coactivator PGC1α Here we show that PGC1α expression in muscle stimulates an increase in expression of Fndc5, a membrane protein that is cleaved and secreted as a new hormone, irisin. Irisin acts on white adipose cells in culture and in vivo to stimulate UCP1 expression and a broad program of brown fat-like development. Irisin is induced with exercise in mice and humans, and mildly increased irisin levels in blood cause an increase in energy expenditure in mice with no changes in movement or food intake. This results in improvements in obesity and glucose homeostasis. Irisin could be a protein therapeutic for human metabolic disease and other disorders that are improved with exercise.
              Article 0 comments Cited 816 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Contributors
                Arpan C. Ghosh: ghosh.arpan@gmail.com
                Norbert Perrimon: perrimon@genetics.med.harvard.edu
                Journal
                Journal ID (nlm-ta): BMC Genomics
                Journal ID (iso-abbrev): BMC Genomics
                Title: BMC Genomics
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1471-2164
                Publication date (Electronic): 30 August 2022
                Publication date PMC-release: 30 August 2022
                Publication date Collection: 2022
                Volume: 23
                Electronic Location Identifier: 623
                Affiliations
                [1 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Genetics, Blavatnik Institute, Harvard Medical School, ; Boston, MA USA
                [2 ]GRID grid.413575.1, ISNI 0000 0001 2167 1581, Howard Hughes Medical Institute, ; Boston, MA USA
                Article
                Publisher ID: 8845
                DOI: 10.1186/s12864-022-08845-6
                PMC ID: 9425970
                PubMed ID: 36042416
                SO-VID: 483dcc13-3dd7-4087-9121-c1edfd7b71f5
                Copyright © © The Author(s) 2022
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                Date received : 17 February 2022
                Date accepted : 16 August 2022
                Categories
                Subject: Research
                Custom metadata
                issue-copyright-statement © The Author(s) 2022

                ScienceOpen disciplines: Genetics
                Keywords: drosophila,exercise,optogenetics,muscle,rna-seq,myokines
                Data availability:
                ScienceOpen disciplines: Genetics
                Keywords: drosophila, exercise, optogenetics, muscle, rna-seq, myokines

                Comments

                Comment on this article

                scite_

                Similar content256

                See all similar

                Cited by1

                See all cited by

                Most referenced authors1,074

                See all reference authors