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Sequential Multiplexed Analyte Quantification using Peptide Immunoaffinity Enrichment Coupled to Mass Spectrometry
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Sequential Multiplexed Analyte Quantification using Peptide Immunoaffinity Enrichment Coupled to Mass Spectrometry

Sequential Multiplexed Analyte Quantification using Peptide Immunoaffinity Enrichment Coupled to Mass Spectrometry
News

Sequential Multiplexed Analyte Quantification using Peptide Immunoaffinity Enrichment Coupled to Mass Spectrometry

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Abstract
Peptide immunoaffinity enrichment coupled to selected reaction monitoring (SRM) mass spectrometry (immuno-SRM) has emerged as a technology with great potential for quantitative proteomic assays. One advantage over traditional immunoassays is the tremendous potential for concurrent quantification of multiple analytes from a given sample (i.e. multiplex analysis). We sought to explore the capacity of the immuno-SRM technique for analyzing large numbers of analytes by evaluating the multiplex capabilities and demonstrating the sequential analysis of groups of peptides from a single sample. To evaluate multiplex analysis, immuno-SRM assays were arranged in groups of 10, 20, 30, 40, and 50 peptides using a common set of reagents. The multiplex immuno-SRM assays were used to measure synthetic peptides added to plasma covering several orders of magnitude concentration. Measurements made in large multiplex groups were highly correlated (r2 ≥ 0.98) and featured good agreement (bias ≤ 1%) compared to single plex assays or a 10-plex configuration. The ability to sequentially enrich sets of analyte peptides was demonstrated by enriching groups of 10 peptides from a plasma sample in a sequential fashion. The data show good agreement (bias ≤ 1.5%) and similar reproducibility regardless of enrichment order. These significant advancements demonstrate the utility of immuno-SRM for analyzing large numbers of analytes, such as in large biomarker verification experiments or in pathway-based targeted analysis.

The article is published online in Molecular & Cellular Proteomics and is free to access.

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