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Defining the transcriptome and proteome in three functionally different human cell lines
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).ORCID iD: 0000-0001-7034-0850
KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).ORCID iD: 0000-0003-0198-7137
KTH, School of Biotechnology (BIO), Gene Technology.
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2010 (English)In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 6, 450- p.Article in journal (Refereed) Published
Abstract [en]

An essential question in human biology is how cells and tissues differ in gene and protein expression and how these differences delineate specific biological function. Here, we have performed a global analysis of both mRNA and protein levels based on sequence-based transcriptome analysis (RNA-seq), SILAC-based mass spectrometry analysis and antibody-based confocal microscopy. The study was performed in three functionally different human cell lines and based on the global analysis, we estimated the fractions of mRNA and protein that are cell specific or expressed at similar/different levels in the cell lines. A highly ubiquitous RNA expression was found with > 60% of the gene products detected in all cells. The changes of mRNA and protein levels in the cell lines using SILAC and RNA ratios show high correlations, even though the genome-wide dynamic range is substantially higher for the proteins as compared with the transcripts. Large general differences in abundance for proteins from various functional classes are observed and, in general, the cell-type specific proteins are low abundant and highly enriched for cell-surface proteins. Thus, this study shows a path to characterize the transcriptome and proteome in human cells from different origins.

Place, publisher, year, edition, pages
2010. Vol. 6, 450- p.
Keyword [en]
cell lines, expression, human, proteome, transcriptome
National Category
Biochemistry and Molecular Biology
Identifiers
URN: urn:nbn:se:kth:diva-29529DOI: 10.1038/msb.2010.106ISI: 000285930400006PubMedID: 21179022Scopus ID: 2-s2.0-78650642557OAI: oai:DiVA.org:kth-29529DiVA: diva2:395675
Funder
Knut and Alice Wallenberg Foundation
Note
QC 20110207Available from: 2011-02-07 Created: 2011-02-07 Last updated: 2017-12-11Bibliographically approved
In thesis
1. Mapping the human proteome using bioinformatic methods
Open this publication in new window or tab >>Mapping the human proteome using bioinformatic methods
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The fundamental goal of proteomics is to gain an understanding of the expression and function of the proteome on the level of individual proteins, on the level of defined cell types and on the level of the entire organism. In this thesis, the human proteome is explored using membrane protein topology prediction methods to define the human membrane proteome and by global protein expression profiling, which relies on a complex study of the location and expression levels of proteins in tissues and cells.

A whole-proteome analysis was performed based on the predicted protein-coding genes of humans using a selection of membrane protein topology prediction methods. The study used a majority decision-based method, which estimated that approximately 26% of the human genes encode for a membrane protein. The prediction results are displayed in a visualization tool to facilitate the selection of antigens to be used for antibody generation.

Global protein expression profiles in a large number of cells and tissues in the human body were analyzed for more than 4000 protein targets, based on data from the antibody-based immunohistochemistry and immunofluorescence methods within the framework of the Human Protein Atlas project. The results revealed few cell-type specific proteins and a high fraction of human proteins expressed in most cells, suggesting that cell and tissue specificity is attained by a fine-tuned regulation of protein levels. The expression profiles were also used to analyze the relationship between 45 cell lines by hierarchical clustering and principal component analysis. The global protein expression patterns overall reflected the tumor origin of the cells, and also allowed for identification of proteins of importance for distinguishing different categories of cell lines, as defined by phenotype of progenitor cell. In addition, the protein distribution in 16 subcellular compartments in three of the human cell lines was mapped. A large fraction of proteins were localized in two or more compartments and, in line with previous results, a majority of proteins were detected in all three cell lines.

Finally, mass spectrometry-based protein expression levels were compared to RNA-seq-based transcript expression levels in three cell lines. Highly ubiquitous mRNA expression was found and the changes of expression levels between the cell lines showed high correlations between proteins and transcripts. Large general differences in abundance of proteins from various functional classes were observed. A comparison between categories based on expression levels revealed that, in general, genes with varying expression levels between the cell lines or only expressed in one cell line were highly enriched for cell-surface proteins.

These studies show a path for a systematic analysis to characterize the proteome in human cells, tissues and organs.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology., 2011. 66 p.
Series
Trita-BIO-Report, ISSN 1654-2312 ; 2011:4
Keyword
proteome, transcriptome, bioinformatics, membrane protein prediction, subcellular localization, protein expression level, cell line, immunohistochemistry, immunofluorescence
National Category
Bioinformatics and Systems Biology
Research subject
SRA - Molecular Bioscience
Identifiers
urn:nbn:se:kth:diva-31477 (URN)978-91-7415-886-1 (ISBN)
Public defence
2011-04-08, F3, Lindstedtsvägen 26, KTH, Stockholm, 14:41 (English)
Opponent
Supervisors
Projects
The Human Protein Atlas project
Funder
Knut and Alice Wallenberg Foundation
Note
QC 20110317Available from: 2011-03-17 Created: 2011-03-16 Last updated: 2011-03-17Bibliographically approved

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Lundberg, EmmaFagerberg, LinnUhlén, Mathias

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