An automated analysis of highly complex flow cytometry-based proteomic data
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
22213549
DOI
10.1002/cyto.a.22011
Knihovny.cz E-zdroje
- MeSH
- algoritmy MeSH
- automatizace MeSH
- barva MeSH
- bcr-abl fúzní proteiny metabolismus MeSH
- benzamidy MeSH
- časové faktory MeSH
- databáze proteinů * MeSH
- gelová chromatografie MeSH
- imatinib mesylát MeSH
- lidé MeSH
- mikrosféry MeSH
- nádorové buněčné linie MeSH
- nádorové proteiny metabolismus MeSH
- piperaziny farmakologie MeSH
- proteom metabolismus MeSH
- proteomika metody MeSH
- průtoková cytometrie metody MeSH
- pyrimidiny farmakologie MeSH
- referenční standardy MeSH
- řízení kvality MeSH
- software MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- bcr-abl fúzní proteiny MeSH
- benzamidy MeSH
- imatinib mesylát MeSH
- nádorové proteiny MeSH
- piperaziny MeSH
- proteom MeSH
- pyrimidiny 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.
Citace poskytuje Crossref.org
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