Recent advances in analytical methods and bioinformatic tools for quantitative glycomics.

Abstract

The significance of glycans in various biological processes has been widely acknowledged. Quantitative glycomics is emerging as an important addition to clinical biomarker discovery, as it helps uncover disease-associated glycosylation patterns that are valuable for diagnosis, prognosis, and treatment evaluation. Compared to glycoproteomics and other established omics approaches, quantitative glycomics exhibits greater methodological diversity and it encounters various challenges in automation and standardization. Nonetheless, numerous advancements have been made in this field over the past 5 years. Here, we have reviewed recent progress in analytical methods and software to improve mass spectrometry-based quantitative glycomics primarily on N- and O-glycosylation. The discussion is organized into four sections: stable isotopic labeling, isobaric labeling, label-free, and fluorescence labeling strategies, with a particular emphasis on quantitative data interpretation. Novel derivatization methods and advanced techniques have been developed for high-throughput and highly sensitive glycan quantification with high accuracy. However, due to variations in glycan derivatization and difficulties in structural identification, most glycomic quantification methods are tailored to specific applications, and manual inspection is frequently necessary for precise data interpretation. Therefore, further advancements in glycan sample preparation, structural characterization, and automated data interpretation are essential to facilitate comprehensive and accurate quantification across a wide array of glycans.