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An image-based map of the human mitochondrial proteome and its heterogeneity
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).ORCID iD: 0000-0003-0750-1070
KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0002-6368-6690
KTH, Centres, Science for Life Laboratory, SciLifeLab.
KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0002-7692-1100
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Mitochondria is involved in a numerous variety of cellular functions beyond its role in energy metabolism. Defining the human mitochondrial proteome is crucial to understand the mitochondria’s diverse functions and role in disease. Here, we present an image-based map of the human mitochondrial proteome containing 1,098 proteins. The single cell resolution revealed extensive heterogeneity for as much as 20% (n=226) of the mitochondrial proteome.  These variations are independent of cell cycle position and likely represent metabolic fluctuations in the cell. Our analysis shows that 48% (n=524) of the proteins localize to additional cellular compartments, further contributing to the diverse cellular functions of mitochondria. This map of the mitochondrial proteome, part of the Cell Atlas of the Human Protein Atlas database (www.proteinatlas.org), provides a valuable knowledge resource for studies of mitochondria function, dysfunction and disease.

Keywords [en]
Mitochondria, Human Protein Atlas, Human Proteome, Immunofluorescence, Multilocalizing protein
National Category
Natural Sciences Cell and Molecular Biology
Identifiers
URN: urn:nbn:se:kth:diva-261236OAI: oai:DiVA.org:kth-261236DiVA, id: diva2:1357400
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20191007

Available from: 2019-10-03 Created: 2019-10-03 Last updated: 2020-01-10Bibliographically approved
In thesis
1. Spatiotemporal characterization of the human proteome
Open this publication in new window or tab >>Spatiotemporal characterization of the human proteome
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Characterizing the molecular components of the basic unit of life; the cell, is crucial for a complete understanding of human biology. The cell is divided into compartments to create a suitable environment for the resident proteins to fulfill their functions. Therefore, spatial mapping of the human proteome is essential to understand protein function in health and disease.

 

Spatial proteomics is most commonly investigated using mass spectrometry or imaging, combined with machine learning for the data analysis. Until now, studies have been limited to high abundant proteins and relied on the purification of organelle fractions from a bulk of cells. Within the scope of this thesis, we were able to systematically localize proteins in their native cellular environment using antibody-based imaging techniques, and to investigate protein subcellular localization and dynamics on a single cell level, introducing a major advance within the field of spatial proteomics.

 

Paper I of this thesis presents a subcellular map of the human proteome, where the spatial distribution of 12,003 human proteins was mapped into 30 subcellular structures, half of which were not previously localized. Besides providing a valuable dataset for cell biology, this study is the first to reveal the spatial complexity of human cells with proteins localizing to multiple compartments and pronounced single cell variations. Paper II reports on the systematic temporal dissection of these single cell variations and the identification of cell cycle correlated variations. We identified 258 novel cell cycle regulated proteins and showed that several of these proteins may be connected to proliferative diseases. A key finding of Paper II is that proteins showing non-cell cycle dependent variations are significantly enriched in mitochondria, whereas cell cycle dependent proteins are enriched in nucleoli. In Paper III and IV, we spatiotemporally characterized the proteomes of these two organelles, mitochondria and nucleoli, in greater detail.

In Paper III, we expanded the mitochondrial proteome with 560 novel proteins. As many as 20% of the mitochondrial proteome showed variations in their expression pattern at the single cell level, most often independent of the cell cycle. Paper IV provides a complete characterization of the nucleolar proteome. Nucleoli are not only important for ribosome synthesis and assembly, but are also crucial for cell cycle regulation through the recruitment of its proteins to the chromosomal periphery during cell division. Here, we presented the first proteome-wide spatiotemporal analysis of the nucleolus with its sub-compartments, and identified 69 nucleolar proteins that relocated to the chromosomes periphery during mitosis.

 

In conclusion, this thesis unravels the spatiotemporal proteome organization of the human cell over the course of a cell cycle and offers a valuable starting point for a better understanding of human cell biology in health and disease.

Place, publisher, year, edition, pages
Stockholm, Sweden: KTH Royal Institute of Technology, 2019. p. 65
Series
TRITA-CBH-FOU ; 2019:48
Keywords
Spatial proteomics, Spatiotemporal proteomics, Immunofluorescence, Human Protein Atlas, Cell compartments, Single cell proteomics, Cell cycle, Cancer
National Category
Cell and Molecular Biology Biological Sciences
Identifiers
urn:nbn:se:kth:diva-261245 (URN)978-91-7873-302-6 (ISBN)
Public defence
2019-10-25, Atrium, Nobels väg 12B, Wargentinhuset, solna, 09:00 (English)
Opponent
Supervisors
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 2019-10-04

Available from: 2019-10-04 Created: 2019-10-03 Last updated: 2019-10-04Bibliographically approved

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Wiking, MikaelaBäckström, AnnaDanielsson, FridaFall, JennyStadler, CharlotteThul, PeterÅkesson, LovisaUhlén, MathiasLundberg, Emma

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Mahdessian, DianaWiking, MikaelaBäckström, AnnaDanielsson, FridaFall, JennyStadler, CharlotteThul, PeterÅkesson, LovisaUhlén, MathiasLundberg, Emma
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