dPC Analysis for Glycoproteomics
Charge-based separation of proteins is an important method to assess post-translational modifications such as phosphorylation and glycosylation. Protein glycosylation represents a major post-translational modification and can have significant effect on protein function. Changes in carbohydrate structure have been recognized as an important modification associated with cancer.
As an example, serum samples from diseased and healthy individuals were processed by an optimized glycoprotein sample-preparation protocol. The goal was to identify changes in the concentration level and/or the carbohydrate structure of the glycoprotein(s) found. Figure 3 shows alpha 1 antitrypsin, which showed a change in peptide counts after dPC separation.
dPC Separation Is Based on Parallel Isoelectric Focusing
Parallel isoelectric focusing was first explained in 2003 by scientists at Protein Forest. The dPC uses a discontinuous pH gradient, where each gel feature has a distinct pH (e.g., a dPC 4.20–6.20 has 41 gel features separated by 0.05 pH units) with the electrical field perpendicular to the orientation of the dPC. High electrical field strength is created, allowing rapid (30–45 min) separation wherein the proteins are separated and concentrated at or near the isoelectric point of the protein (Figure 4).
Achieving a durable preclinical role for biomarker discovery relies on methods that are reproducible and reliable. A new tool for biomarker discovery was created in response to the strong need for a simple, reliable, and reproducible method of protein prefractionation. Digitizing the separation of proteins by isoelectric point and changing the format to a parallel method has led to three measureable benefits: high reproducibility, improved coverage, and rapid separation.
Using dPC, complex protein samples such as plasma and cell lysates can be separated with a high degree of reproducibility in 30 minutes. The digital format dictates low lot-to-lot variability, leading to results that are repeatable across multiple laboratories using multiple MS platforms.
Coupled with the post-MSMS bioinformatics software platform, MSRAT™, which is platform- and search engine-independent, it is now possible to reliably identify new and repeatable biomarkers. Together dPC and MSRAT address sample reproducibility and the confounding effects of multiple-platform analysis that have limited proteomic biomarker identification and utility.