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Systematic validation of antibody binding and protein subcellular localization using siRNA and confocal microscopy
KTH, Centres, Science for Life Laboratory, SciLifeLab.
KTH, School of Biotechnology (BIO), Proteomics (closed 20130101). KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0001-7375-9681
KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
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2012 (English)In: Journal of Proteomics, ISSN 1874-3919, E-ISSN 1876-7737, Vol. 75, no 7, 2236-2251 p.Article in journal (Refereed) Published
Abstract [en]

We have developed a platform for validation of antibody binding and protein subcellular localization data obtained from immunofluorescence using siRNA technology combined with automated confocal microscopy and image analysis. By combining the siRNA technology with automated sample preparation, automated imaging and quantitative image analysis, a high-throughput assay has been set-up to enable confirmation of accurate protein binding and localization in a systematic manner. Here, we describe the analysis and validation of the subcellular location of 65 human proteins, targeted by 75 antibodies and silenced by 130 siRNAs. A large fraction of (80%) the subcellular locations, including locations of several previously uncharacterized proteins, could be confirmed by the significant down-regulation of the antibody signal after the siRNA silencing. A quantitative analysis was set-up using automated image analysis to facilitate studies of targets found in more than one compartment. The results obtained using the platform demonstrate that siRNA silencing in combination with quantitative image analysis of antibody signals in different compartments of the cells is an attractive approach for ensuring accurate protein localization as well as antibody binding using immunofluorescence. With a large fraction of the human proteome still unexplored, we suggest this approach to be of great importance under the continued work of mapping the human proteome on a subcellular level.

Place, publisher, year, edition, pages
2012. Vol. 75, no 7, 2236-2251 p.
Keyword [en]
siRNA, Immunofluorescence, Subcellular location, Quantitative image analysis, Antibody validation
National Category
Biochemistry and Molecular Biology
Identifiers
URN: urn:nbn:se:kth:diva-95259DOI: 10.1016/j.jprot.2012.01.030ISI: 000303136600021PubMedID: 22361696Scopus ID: 2-s2.0-84858748188OAI: oai:DiVA.org:kth-95259DiVA: diva2:527382
Funder
Knut and Alice Wallenberg FoundationEU, European Research CouncilScience for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20120521

Available from: 2012-05-21 Created: 2012-05-21 Last updated: 2017-12-07Bibliographically approved
In thesis
1. Towards subcellular localization of the human proteome using bioimaging
Open this publication in new window or tab >>Towards subcellular localization of the human proteome using bioimaging
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Since the publication of the complete sequence of the human genome in 2003 there has been great interest in exploring the functions of the proteins encoded by the genes. To reveal the function of each and every protein, investigation of protein localization at the subcellular level has become a central focus in this research area, since the localization and function of a protein is closely related. The objective of the studies presented in this doctoral thesis was to systematically explore the human proteome at the subcellular level using bioimaging and to develop techniques for validation of the results obtained.

A common imaging technique for protein detection is immunofluorescence (IF), where antibodies are used to target proteins in fixated cells. A fixation protocol suitable for large-scale IF studies was developed and optimized to work for a broad set of proteins. As the technique relies on antibodies, validation of their specificity to the target protein is crucial. A platform based on siRNA gene silencing in combination with IF was set-up to evaluate antibody specificity by quantitative image analysis before and after suppression of its target protein. As a proof of concept, the platform was then used for validation of 75 antibodies, proving it to be applicable for validation of antibodies in a systematic manner.

Because of the fixation, there is a common concern about how well IF data reflects the in vivo subcellular distribution of proteins. To address this, 500 proteins were tagged with green fluorescent protein (GFP) and used to compare protein localization results between IF to those achieved using GFP tagged proteins in live cells. It was concluded that protein localization data from fixated cells satisfactory represented the situation in vivo and together exhibit a powerful approach for confirming localizations of yet uncharacterized proteins.

Finally, a global analysis based on IF data of approximately 20 % of the human proteome was performed, providing a first overview of the subcellular landscape in three different cell lines. It was found that the intracellular distribution of proteins is complex, with many proteins occurring in several organelles. The results also confirmed the close relationship between protein function and localization, which in a way further strengthens the accuracy of the IF approach for detection of proteins at the subcellular level.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. 60 p.
Series
Trita-BIO-Report, ISSN 1654-2312 ; 12:19
Keyword
Antibody, antibody validation, automated image analysis, automated microscopy, cell line, confocal microscopy, fixation, green fluorescent protein (GFP), immunofluorescence (IF), organelle, protein expression, siRNA, subcellular localization
National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-103616 (URN)978-91-7501-483-8 (ISBN)
Public defence
2012-11-09, MTC, Karolinska institutet, Stockholm, 10:00 (English)
Opponent
Supervisors
Projects
The Human Protein Atlas
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20121017

Available from: 2012-10-17 Created: 2012-10-16 Last updated: 2013-04-15Bibliographically approved

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Hjelmare, MartinUhlén, MathiasLundberg, Emma

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