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      Metabolic decline in an insect ear: correlative or causative for age-related auditory decline?

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          Abstract

          One leading hypothesis for why we lose our hearing as we age is a decrease in ear metabolism. However, direct measurements of metabolism across a lifespan in any auditory system are lacking. Even if metabolism does decrease with age, a question remains: is a metabolic decrease a cause of age-related auditory decline or simply correlative? We use an insect, the desert locust Schistocerca gregaria, as a physiologically versatile model to understand how cellular metabolism correlates with age and impacts on age-related auditory decline. We found that auditory organ metabolism decreases with age as measured fluorometrically. Next, we measured the individual auditory organ’s metabolic rate and its sound-evoked nerve activity and found no correlation. We found no age-related change in auditory nerve activity, using hook electrode recordings, and in the electrophysiological properties of auditory neurons, using patch-clamp electrophysiology, but transduction channel activity decreased. To further test for a causative role of the metabolic rate in auditory decline, we manipulated metabolism of the auditory organ through diet and cold-rearing but found no difference in sound-evoked nerve activity. We found that although metabolism correlates with age-related auditory decline, it is not causative. Finally, we performed RNA-Seq on the auditory organs of young and old locusts, and whilst we found enrichment for Gene Ontology terms associated with metabolism, we also found enrichment for a number of additional aging GO terms. We hypothesize that age-related hearing loss is dominated by accumulative damage in multiple cell types and multiple processes which outweighs its metabolic decline.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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              HTSeq—a Python framework to work with high-throughput sequencing data

              Motivation: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. Results: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. Availability and implementation: HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq. Contact: sanders@fs.tum.de
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                Author and article information

                Contributors
                Journal
                Front Cell Dev Biol
                Front Cell Dev Biol
                Front. Cell Dev. Biol.
                Frontiers in Cell and Developmental Biology
                Frontiers Media S.A.
                2296-634X
                18 May 2023
                2023
                : 11
                : 1138392
                Affiliations
                Neurogenetics, College of Life Sciences , University of Leicester , Leicester, United kingdom
                Author notes

                Edited by: Steven J. Fliesler, University at Buffalo, United States

                Reviewed by: Kevin Ohlemiller, Washington University in St. Louis, United States

                Joerg T. Albert, University College London, United Kingdom

                Bohua Hu, University at Buffalo, United States

                *Correspondence: Ben Warren, bw120@ 123456le.ac.uk ,
                [ † ]

                ORCID: Ben Warren, https://orcid.org/0000-0002-0758-7612

                Article
                1138392
                10.3389/fcell.2023.1138392
                10233746
                70e2e2a0-6fe3-436f-a3d8-ecca932fee47
                Copyright © 2023 Austin, Thomas, Lewis, Blockley and Warren.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 05 January 2023
                : 25 April 2023
                Categories
                Cell and Developmental Biology
                Original Research
                Custom metadata
                Molecular and Cellular Pathology

                audition (physiology),sensory decline,metabolism,aging,insect hearing

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