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Enhanced Sample Multiplexing of Tissues Using Combined Precursor Isotopic Labeling and Isobaric Tagging cPILOT
Published on: May 1, 2017
Enhanced Sample Multiplexing of Tissues Using Combined Precursor Isotopic Labeling and Isobaric Tagging (cPILOT)
Christina D King1, Joseph D Dudenhoeffer1, Liqing Gu2
1Department of Chemistry, University of Pittsburgh.
A new technique, combined precursor isotopic labeling and isobaric tagging (cPILOT), enables simultaneous analysis of 12 biological samples. This quantitative proteomics method reduces costs and experimental bias for disease biomarker discovery.
Area of Science:
- Proteomics
- Biomarker Discovery
- Quantitative Biology
Background:
- Increasing demand for analyzing multiple biological samples for disease understanding and biomarker discovery.
- Quantitative proteomics strategies enable simultaneous measurement of multiple samples, reducing costs and time.
- Traditional isotopic labeling or isobaric tagging approaches have limitations in sample multiplexing.
Purpose of the Study:
- To introduce and validate a novel technique, combined precursor isotopic labeling and isobaric tagging (cPILOT), for enhanced sample multiplexing in quantitative proteomics.
- To demonstrate the application of global cPILOT for analyzing protein abundances across diverse biological conditions.
- To showcase a 12-plex analysis of mouse tissues using cPILOT.
Main Methods:
- cPILOT combines low pH selective N-terminal dimethylation with high pH lysine residue labeling using isobaric reagents.
- The degree of multiplexing depends on the number of precursor labels and isobaric tagging reagents used.
- A 12-plex analysis was performed on mouse brain, heart, and liver tissues using light/heavy dimethylation and six-plex isobaric reagents.
Main Results:
- cPILOT successfully enabled a 12-plex quantitative proteomics analysis of mouse tissues in a single experiment.
- The approach allows for relative protein abundance measurements across multiple sample conditions, including disease models.
- Demonstrated application in comparing Alzheimer's disease mouse models with wild-type controls.
Conclusions:
- Global cPILOT significantly enhances sample multiplexing capabilities in quantitative proteomics.
- This method reduces experimental time and cost while minimizing experimental bias and error.
- cPILOT is applicable to various biological samples and can be adapted for multiplexing over 20 samples for broader biological studies.
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