Evaluation of Deep Plasma Proteomic Analysis With the Proteograph Workflow and TMT Sample Labeling
This technical note describes the performance of the Proteograph workflow with TMT sample labeling compared to the data dependent acquisition method for label-free quantification.
Introduction
Human blood plasma is an easily accessible sample type for assessing individual health status. However, the large dynamic concentration range of circulating plasma proteins combined with the vast diversity of protein variants have prevented the comprehensive characterization of the plasma proteome in a high throughput manner. Conventional deep plasma proteomics workflows combine immunodepletion of highly abundant proteins and peptide prefractionation to access low abundant plasma proteins. These workflows, however, are time-, labor-, and cost-intensive, therefore alternative solutions to analyze the wide concentration range of the plasma proteome are needed.
Recent advancements in proteomic analysis like the Proteograph Product Suite coupled with mass spectrometry now enables the quantification of thousands of proteins from plasma without compromising throughput or reproducibility, creating a unique opportunity for robust detection of protein biomarkers from complex diseases. Moreover, the integration of the Proteograph workflow with tandem mass tag (TMT) labeling, which measures protein abundances across multiple samples at once, enables simultaneous protein quantification in large cohorts and thus can be a powerful tool for large-scale proteomics studies.
Here, we demonstrate the performance of the Proteograph workflow with TMT sample labeling in comparison to the Data Dependent Acquisition method (DDA) for Label Free Quantification (LFQ) by comparing a set of control plasma samples processed with Proteograph Assay Kit with LFQ DDA or TMT labeling workflows using high-resolution LC-MS analysis coupled with high-field asymmetric waveform ion mobility spectrometry (FAIMS) Pro interface.
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