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The correlation between cellular size and protein expression levels: Normalization for global protein profiling
KTH, School of Biotechnology (BIO), Proteomics.ORCID iD: 0000-0001-7034-0850
KTH, School of Biotechnology (BIO), Proteomics.
KTH, School of Biotechnology (BIO), Proteomics.ORCID iD: 0000-0003-3014-5502
Beecher Instruments, Sun Prairie, WI USA.
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2008 (English)In: Journal of Proteomics, ISSN 1874-3919, Vol. 71, no 4, 448-460 p.Article in journal (Refereed) Published
Abstract [en]

An automated image analysis system was used for protein quantification of 1862 human proteins in 47 cancer cell lines and 12 clinical cell samples using cell microarrays and immunohistochemistry. The analysis suggests that most proteins are expressed in a cell size dependent manner, and that normalization is required for comparative protein quantification in order to correct for the inherent bias of cell size and systematic ambiguities associated with immunohistochemistry. Two reference standards were evaluated, and normalized protein expression values were found to allow for protein profiling across a panel of morphologically diverse cells, revealing putative patterns of over- and underexpression. Using this approach, proteins with stable expression as well as cell-line specific expression were identified. The results demonstrate the value of large-scale, automated proteome analysis using immunohistochemistry in revealing functional correlations and establishing methods to interpret and mine proteomic data.

Place, publisher, year, edition, pages
2008. Vol. 71, no 4, 448-460 p.
Keyword [en]
Immunohistochemistry; Protein quantification; Normalization; Expression profiling
National Category
Industrial Biotechnology
Identifiers
URN: urn:nbn:se:kth:diva-4883DOI: 10.1016/j.jprot.2008.06.014ISI: 000260816700005Scopus ID: 2-s2.0-51749118509OAI: oai:DiVA.org:kth-4883DiVA: diva2:1755
Note
QC 20100728. Uppdaterad från in press till published (20100728).Available from: 2008-09-16 Created: 2008-09-16 Last updated: 2010-07-28Bibliographically approved
In thesis
1. Bioimaging for analysis of protein expression in cells and tissues using affinity reagents
Open this publication in new window or tab >>Bioimaging for analysis of protein expression in cells and tissues using affinity reagents
2008 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

The detection and analysis of biomolecules, such as proteins, are of great interest since these molecules are fundamental for life and our health. Due to the complexity of biological processes, there is a great advantage of studying proteins in their natural context, for example by using bioimaging. The objective of this doctoral thesis has been to develop, implement and evaluate techniques for the use of proteinspecific affinity reagents in diverse bioimaging platforms for analysis of protein expression in situ in cells and tissues.

To be able to visualize a desired protein in situ using affinity reagents, reporter labels are needed. A novel technique for labeling of antibodies on solid phase was developed. This method offers simultaneous purification, concentration and labeling of an antibody sample, giving highly predictable and reproducible results, in a miniaturized format.

Another study demonstrates the use of an alternative affinity reagent, the Affibody molecule, in bioimaging as well as other immunoassays. As a relevant proof-of-principle, an Affibody molecule binding the HER2 receptor was site-specificly labeled and employed for analysis of HER2 protein expression in cells and tissue using immunofluorescence (IF), immunohistochemistry (IHC), immunoprecipitation and flow cytometry.

Furthermore, it is shown how antibody-based bioimaging approaches can be applied for systematic analysis of protein expression in terms of subcellular localization and expression levels in cell lines. The systematic subcellular localization of nearly 500 proteins was performed using IF and confocal microscopy. Global analysis of expression levels of nearly 2000 proteins in a panel of cell lines using IHC and automated image analysis, revealed that most proteins are expressed in a cell size dependent manner. Two normalization approaches were evaluated and found to allow for protein profiling across the panel of morphologically diverse cells, revealing patterns of protein over- and underexpression, and proteins with stable as well as with lineage specific expression were identified.

Finally, the value of antibody-based, bioimaging proteomics as a platform for biomarker discovery is demonstrated. The identification and in depth study of a candidate biomarker for colorectal cancer, SATB2, is described using both IHC and IF bioimaging. Results from extended analyses of tumor biopsies showed that detection of SATB2 protein using IHC provides a clinically relevant diagnostic tool with high specificity and sensitivity to aid in diagnosis of colorectal cancer. Furthermore, the study demonstrated a potential prognostic role of SATB2, as decreased expression was associated with a significantly shorter overall survival in patients with advanced colorectal cancer.

Place, publisher, year, edition, pages
Stockholm: KTH, 2008. vii, 86 p.
Series
Trita-BIO-Report, ISSN 1654-2312 ; 2008:14
Keyword
Affibody, antibody, biomarker, cell line, cell microarray, colorectal cancer, confocal microscopy, HER2, immunohistochemistry, immunofluorescence, light microscopy, protein expression, protein localization, SATB2, tissue microarray
National Category
Industrial Biotechnology Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-4862 (URN)978-91-7415-096-4 (ISBN)
Public defence
2008-09-26, FD5, AlbaNova Universitetscentrum, Kungl Tekniska Högskolan, Roslagstullsbacken 21, Stockholm, 10:00 (English)
Opponent
Supervisors
Note
QC 20100824Available from: 2008-09-05 Created: 2008-09-05 Last updated: 2010-08-24Bibliographically approved
2. Global expression analysis of human cells and tissues using antibodies
Open this publication in new window or tab >>Global expression analysis of human cells and tissues using antibodies
2008 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

To construct a complete map of the human proteome landscape is a vital part of the total understanding of the human body. Such a map could enrich the mankind to the extent that many severe diseases could be fully understood and hence could be treated with appropriate methods.

In this study, immunohistochemical (IHC) data from ~6000 proteins, 65 cell types in 48 tissues and 47 cell lines has been used to investigate the human proteome regarding protein expression and localization. In order to analyze such a large data set, different statistical methods and algorithms has been applied and by using these tools, interesting features regarding the proteome was found. By using all available IHC data from 65 cell types in 48 tissues, it was found that the amount of tissue specific protein expression was surprisingly small, and the general impression from the analysis is that almost all proteins are present at all times in the cellular environment. Rather than tissue specific protein expression, the localization and minor concentration fluctuations of the proteins in the cell is responsible for molecular interaction and tissue specific cellular behavior. However, if a quarter of all proteins are used to distinguish different tissues types, there are a proportion of proteins that have certain expression profiles, which defines clusters of tissues of the same kind and embryonic origin.

The estimation of expression levels using IHC is a labor-intensive method, which suffers from large variation between manual annotators. An automated image software tool was developed to circumvent this problem. The automated image software was shown to be more robust then manual annotators, and the quantification of expressed protein levels of the stained imaged was in the same range as the manual annotations.

A more thorough investigation of the stained image estimations made by the automated software revield a significant correlation between the estimated protein expression and the cell size parameters provided by the automated software. To make it feasible to compare protein expression levels across different cell lines, without the cell line size bias, a normalization procedure was implemented and evaluated. It was found that when the normalization procedure was applied to the protein expression data, the correlation between protein expression values and cell size was minimized, and hence comparisons between cell lines regarding protein expression is possible.

In addition, using the normalized protein expression data, an analysis to investigate the degree of correlation between mRNA levels and proteins for 1065 gene products was performed. By using two individual microarray data sets for estimation of RNA levels, and normalized protein data measured by the automated software as estimation of the protein levels, a mean correlation of ~0.3 for was found. This result indicates that a significant proportion of the manufactured antibodies, when used in IHC setup, are indeed an accurate measurement of protein expression levels.

By using antibodies directed towards human proteins, plasma samples were investigated regarding metabolic dysfunctions. Since plasma is a complex sample, an optimization regarding protocol for quantification of expressed proteins was made. By using certain characteristics within the dataset, and by using a suspension bead microarray, the protocol could be evaluated. Expected characteristics within the dataset were found in the subsequent analysis, which showed that the protocol was functional. Using the same experimental outline will facilitate future applications, e.g. biomarker discovery. 

Place, publisher, year, edition, pages
Stockholm: KTH, 2008. xi, 53 p.
Series
Trita-BIO-Report, ISSN 1654-2312 ; 2008:17
Keyword
Immunohistochemistry, protein expression, Antibody, Tissue microarray, protein quanitification, RNA and protein correlation
National Category
Industrial Biotechnology
Identifiers
urn:nbn:se:kth:diva-9116 (URN)978-91-7415-113-8 (ISBN)
Public defence
2008-10-10, Oscar Klein auditorium, Roslagstullsbacken 21, floor 4, Stockholm, 09:00 (English)
Opponent
Supervisors
Projects
Human Proteome Resource
Note
QC 20100728Available from: 2008-09-26 Created: 2008-09-19 Last updated: 2010-07-28Bibliographically approved

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Lundberg, EmmaOksvold, PerUhlén, Mathias

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