Region and cell-type resolved quantitative proteomic map of the human heart

Sophia Doll, Martina Dreßen, Philipp E. Geyer, Daniel N. Itzhak, Christian Braun, Stefanie A. Doppler, Florian Meier, Marcus-Andre Deutsch, Harald Lahm, Rüdiger Lange, Markus Krane () and Matthias Mann ()
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Sophia Doll: Max Planck Institute of Biochemistry
Martina Dreßen: German Heart Center Munich at the Technische Universität München
Philipp E. Geyer: Max Planck Institute of Biochemistry
Daniel N. Itzhak: Max Planck Institute of Biochemistry
Christian Braun: Ludwig-Maximilians-University
Stefanie A. Doppler: German Heart Center Munich at the Technische Universität München
Florian Meier: Max Planck Institute of Biochemistry
Marcus-Andre Deutsch: German Heart Center Munich at the Technische Universität München
Harald Lahm: German Heart Center Munich at the Technische Universität München
Rüdiger Lange: German Heart Center Munich at the Technische Universität München
Markus Krane: German Heart Center Munich at the Technische Universität München
Matthias Mann: Max Planck Institute of Biochemistry

Nature Communications, 2017, vol. 8, issue 1, 1-13

Abstract: Abstract The heart is a central human organ and its diseases are the leading cause of death worldwide, but an in-depth knowledge of the identity and quantity of its constituent proteins is still lacking. Here, we determine the healthy human heart proteome by measuring 16 anatomical regions and three major cardiac cell types by high-resolution mass spectrometry-based proteomics. From low microgram sample amounts, we quantify over 10,700 proteins in this high dynamic range tissue. We combine copy numbers per cell with protein organellar assignments to build a model of the heart proteome at the subcellular level. Analysis of cardiac fibroblasts identifies cellular receptors as potential cell surface markers. Application of our heart map to atrial fibrillation reveals individually distinct mitochondrial dysfunctions. The heart map is available at maxqb.biochem.mpg.de as a resource for future analyses of normal heart function and disease.

Date: 2017
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DOI: 10.1038/s41467-017-01747-2

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