New Method Streamlines Sample Prep for Bottom-Up Glycoproteomics

A team of scientists has developed a low-cost, magnetic-bead-based method for studying glycoproteins—proteins with attached sugar molecules—in blood and tissue samples, an approach that could help diagnose and treat diseases including cancer. The work, published in Molecular & Cellular Proteomics, addresses a bottleneck facing Japan's Human Glycome Atlas (HGA) Project, launched in April 2023 to catalog disease-related glycans using glycoproteomics on a large sample cohort.

Glycoproteomics, a branch of proteomics, studies proteins with attached sugar molecules—a change called glycosylation, the most common modification a protein undergoes after a cell builds it, which shapes the protein's interactions with other cells. Scientists have observed altered glycosylation patterns in several diseases, including cancer, which damages these sugar molecules, so changed sugar-proteins serve as useful biomarkers, letting scientists track cancer through shifts in glycosylation.

One promising approach for finding such biomarkers is bottom-up glycoproteomics, which uses enzymes to cut glycoproteins into peptide fragments, purifies them via hydrophilic interaction liquid chromatography (HILIC), and analyzes them by mass spectrometry, revealing detailed information on carrier glycoproteins, glycosylation sites, and glycan composition. Its usefulness is limited, though: mass spectrometry struggles to detect glycopeptides amid an abundance of unmodified proteins, and sample impurities like salts and detergents can further interfere with analysis.

Single-pot, solid-phase-enhanced sample preparation (SP3), which uses magnetic beads for automated prep, has already proven useful in glycoproteomics. But according to Kazuki Nakajima, senior author of the paper, “seamless workflow in series of sample preparation using appropriate magnetic beads has not been reported.” His team evaluated a cost-effective SP3 method for N-glycopeptide preparation, comparing carboxylated polymer beads and cellulose resin. The cellulose particles proved more effective, capturing N-glycopeptides via HILIC while letting non-glycopeptides pass through. The team tested the approach on plasma, serum, and tissue samples, including gastric cancer patient samples, and detected cancer-related glycoprotein changes.

“The SP3-based N-glycopeptide preparation method using commercially available cellulose magnetic beads is a robust and automate-friendly approach for N-glycoproteomics,” Nakajima said, noting it showed higher glycopeptide recovery and non-glycopeptide removal efficiencies across sample types. “The method is believed to be a global standard method for analyzing glycoproteomics profiles,” he said.

Looking ahead, the team plans to scale the process up for automation. “In the HGA project, we are developing a homemade fully automated system implementing the robotic protocol,” Nakajima said, adding, “the system will be applied for plasma/serum and tissue sample preparation, and further in-depth glycoproteomics.”