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  Antidepressant treatment effects on hippocampal protein turnover: Molecular and spatial insights from mass spectrometry

Turck, C. W., Webhofer, C., Reckow, S., Moy, J., Wang, M., Guillermier, C., et al. (2022). Antidepressant treatment effects on hippocampal protein turnover: Molecular and spatial insights from mass spectrometry. PROTEOMICS, e2100244. doi:10.1002/pmic.202100244.

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 Creators:
Turck, Christoph W.1, Author           
Webhofer, Christian1, Author           
Reckow, Stefan1, Author           
Moy, Jeffrey, Author
Wang, Mei, Author
Guillermier, Christelle, Author
Poczatek, J. Collin, Author
Filiou, Michaela D.1, Author           
Affiliations:
1RG Proteomics and Biomarkers, Max Planck Institute of Psychiatry, Max Planck Society, ou_2040287              

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 Abstract: A major challenge in managing depression is that antidepressant drugs take a long time to exert their therapeutic effects. For the development of faster-acting treatments, it is crucial to get an improved understanding of the molecular mechanisms underlying antidepressant mode of action. Here, we used a novel mass spectrometry-based workflow to investigate how antidepressant treatment affects brain protein turnover at single-cell and subcellular resolution. We combined stable isotope metabolic labeling, quantitative Tandem Mass Spectrometry (qTMS) and Multi-isotope Imaging Mass Spectrometry (MIMS) to simultaneously quantify and image protein synthesis and turnover in hippocampi of mice treated with the antidepressant paroxetine. We identified changes in turnover of individual hippocampal proteins that reveal altered metabolism-mitochondrial processes and report on subregion-specific turnover patterns upon paroxetine treatment. This workflow can be used to investigate brain protein turnover changes in vivo upon pharmacological interventions at a resolution and precision that has not been possible with other methods to date. Our results reveal acute paroxetine effects on brain protein turnover and shed light on antidepressant mode of action.

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 Dates: 2022-03
 Publication Status: Published online
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 Identifiers: ISI: 000787170900001
DOI: 10.1002/pmic.202100244
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Title: PROTEOMICS
Source Genre: Journal
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Pages: - Volume / Issue: - Sequence Number: e2100244 Start / End Page: - Identifier: ISSN: 1615-9853