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An automated analysis of highly complex flow cytometry-based proteomic data
J. Stuchlý, V. Kanderová, K. Fišer, D. Cerná, A. Holm, W. Wu, O. Hrušák, F. Lund-Johansen, T. Kalina,
Language English Country United States
Document type Journal Article, Research Support, Non-U.S. Gov't
Grant support
NS10473
MZ0
CEP Register
Digital library NLK
Full text - Article
Source
NLK
Free Medical Journals
from 2003 to 1 year ago
Medline Complete (EBSCOhost)
from 2012-06-01 to 1 year ago
Wiley Online Library (archiv)
from 1980-01-01 to 2012-12-31
Wiley Free Content
from 2003 to 1 year ago
PubMed
22213549
DOI
10.1002/cyto.a.22011
Knihovny.cz E-resources
- MeSH
- Algorithms MeSH
- Automation MeSH
- Color MeSH
- Fusion Proteins, bcr-abl metabolism MeSH
- Time Factors MeSH
- Databases, Protein MeSH
- Chromatography, Gel MeSH
- Humans MeSH
- Microspheres MeSH
- Cell Line, Tumor MeSH
- Neoplasm Proteins metabolism MeSH
- Piperazines pharmacology MeSH
- Proteome metabolism MeSH
- Proteomics methods MeSH
- Flow Cytometry methods MeSH
- Pyrimidines pharmacology MeSH
- Reference Standards MeSH
- Quality Control MeSH
- Software MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The combination of color-coded microspheres as carriers and flow cytometry as a detection platform provides new opportunities for multiplexed measurement of biomolecules. Here, we developed a software tool capable of automated gating of color-coded microspheres, automatic extraction of statistics from all subsets and validation, normalization, and cross-sample analysis. The approach presented in this article enabled us to harness the power of high-content cellular proteomics. In size exclusion chromatography-resolved microsphere-based affinity proteomics (Size-MAP), antibody-coupled microspheres are used to measure biotinylated proteins that have been separated by size exclusion chromatography. The captured proteins are labeled with streptavidin phycoerythrin and detected by multicolor flow cytometry. When the results from multiple size exclusion chromatography fractions are combined, binding is detected as discrete reactivity peaks (entities). The information obtained might be approximated to a multiplexed western blot. We used a microsphere set with >1,000 subsets, presenting an approach to extract biologically relevant information. The R-project environment was used to sequentially recognize subsets in two-dimensional space and gate them. The aim was to extract the median streptavidin phycoerythrin fluorescence intensity for all 1,000+ microsphere subsets from a series of 96 measured samples. The resulting text files were subjected to algorithms that identified entities across the 24 fractions. Thus, the original 24 data points for each antibody were compressed to 1-4 integrated values representing the areas of individual antibody reactivity peaks. Finally, we provide experimental data on cellular protein changes induced by treatment of leukemia cells with imatinib mesylate. The approach presented here exemplifies how large-scale flow cytometry data analysis can be efficiently processed to employ flow cytometry as a high-content proteomics method.
References provided by Crossref.org
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