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Licensed Unlicensed Requires Authentication Published by De Gruyter October 4, 2021

Characterization of hepatic zonation in mice by mass-spectrometric and antibody-based proteomics approaches

Simon Kling, Benedikt Lang, Helen S. Hammer, Wael Naboulsi, Heike Sprenger, Falko Frenzel, Oliver Pötz, Michael Schwarz, Albert Braeuning and Markus F. Templin
From the journal Biological Chemistry

Abstract

Periportal and perivenous hepatocytes show zonal heterogeneity in metabolism and signaling. Here, hepatic zonation in mouse liver was analyzed by non-targeted mass spectrometry (MS) and by the antibody-based DigiWest technique, yielding a comprehensive overview of protein expression in periportal and perivenous hepatocytes. Targeted immunoaffinity-based proteomics were used to substantiate findings related to drug metabolism. 165 (MS) and 82 (DigiWest) zonated proteins were identified based on the selected criteria for statistical significance, including 7 (MS) and 43 (DigiWest) proteins not identified as zonated before. New zonated proteins especially comprised kinases and phosphatases related to growth factor-dependent signaling, with mainly periportal localization. Moreover, the mainly perivenous zonation of a large panel of cytochrome P450 enzymes was characterized. DigiWest data were shown to complement the MS results, substantially improving possibilities to bioinformatically identify zonated biological processes. Data mining revealed key regulators and pathways preferentially active in either periportal or perivenous hepatocytes, with β-catenin signaling and nuclear xeno-sensing receptors as the most prominent perivenous regulators, and several kinase- and G-protein-dependent signaling cascades active mainly in periportal hepatocytes. In summary, the present data substantially broaden our knowledge of hepatic zonation in mouse liver at the protein level.


Corresponding author: Albert Braeuning, Department of Food Safety, German Federal Institute for Risk Assessment, Max-Dohrn-Str. 8-10, D-10589 Berlin, Germany, E-mail:

Acknowledgments

The authors acknowledge expert technical assistance by Silvia Vetter.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

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Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/hsz-2021-0314).


Received: 2021-07-09
Accepted: 2021-09-19
Published Online: 2021-10-04
Published in Print: 2022-02-23

© 2021 Walter de Gruyter GmbH, Berlin/Boston

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