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      Catecholamine treatment induces reversible heart injury and cardiomyocyte gene expression

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          Abstract

          Background

          Catecholamines are commonly used as therapeutic drugs in intensive care medicine to maintain sufficient organ perfusion during shock. However, excessive or sustained adrenergic activation drives detrimental cardiac remodeling and may lead to heart failure. Whether catecholamine treatment in absence of heart failure causes persistent cardiac injury, is uncertain. In this experimental study, we assessed the course of cardiac remodeling and recovery during and after prolonged catecholamine treatment and investigated the molecular mechanisms involved.

          Results

          C57BL/6N wild-type mice were assigned to 14 days catecholamine treatment with isoprenaline and phenylephrine (IsoPE), treatment with IsoPE and subsequent recovery, or healthy control groups. IsoPE improved left ventricular contractility but caused substantial cardiac fibrosis and hypertrophy. However, after discontinuation of catecholamine treatment, these alterations were largely reversible. To uncover the molecular mechanisms involved, we performed RNA sequencing from isolated cardiomyocyte nuclei. IsoPE treatment resulted in a transient upregulation of genes related to extracellular matrix formation and transforming growth factor signaling. While components of adrenergic receptor signaling were downregulated during catecholamine treatment, we observed an upregulation of endothelin-1 and its receptors in cardiomyocytes, indicating crosstalk between both signaling pathways. To follow this finding, we treated mice with endothelin-1. Compared to IsoPE, treatment with endothelin-1 induced minor but longer lasting changes in cardiomyocyte gene expression. DNA methylation-guided analysis of enhancer regions identified immediate early transcription factors such as AP-1 family members Jun and Fos as key drivers of pathological gene expression following catecholamine treatment.

          Conclusions

          The results from this study show that prolonged catecholamine exposure induces adverse cardiac remodeling and gene expression before the onset of left ventricular dysfunction which has implications for clinical practice. The observed changes depend on the type of stimulus and are largely reversible after discontinuation of catecholamine treatment. Crosstalk with endothelin signaling and the downstream transcription factors identified in this study provide new opportunities for more targeted therapeutic approaches that may help to separate desired from undesired effects of catecholamine treatment.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40635-024-00632-9.

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          Most cited references55

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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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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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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
                achim.lother@uniklinik-freiburg.de
                Journal
                Intensive Care Med Exp
                Intensive Care Med Exp
                Intensive Care Medicine Experimental
                Springer International Publishing (Cham )
                2197-425X
                11 May 2024
                11 May 2024
                December 2024
                : 12
                : 48
                Affiliations
                [1 ]Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, ( https://ror.org/0245cg223) Freiburg, Germany
                [2 ]BIOSS Centre for Biological Signaling Studies, University of Freiburg, ( https://ror.org/0245cg223) Freiburg, Germany
                [3 ]Interdisciplinary Medical Intensive Care, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, ( https://ror.org/0245cg223) Freiburg, Germany
                Author information
                http://orcid.org/0000-0001-9107-5558
                Article
                632
                10.1186/s40635-024-00632-9
                11088585
                38733526
                766776ef-e32b-47d0-85ff-6afc8abaf6c8
                © The Author(s) 2024

                Open Access This 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/.

                History
                : 25 March 2024
                : 7 May 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: 192904750
                Award ID: 422681845
                Award Recipient :
                Funded by: Universitätsklinikum Freiburg (8975)
                Categories
                Research Articles
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                © European Society of Intensive Care Medicine and Springer Nature Switzerland AG 2024

                adrenergic receptors,endothelin,cardiomyocyte,gene expression,intensive care medicine

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