Protein glycosylation, as one of the most widespread and complex post-translational modifications (PTMs), plays an important role in living organisms [1,2]. Mass spectrometry (MS)–based glycoproteomics, leveraging the high-throughput analytical capabilities of MS, aims to identify the whole glycoproteins with comprehensive information about the peptide sequences, glycosylation sites, and the attached glycans. However, due to the complex and diverse nature of glycan composition and structure, as well as the heterogeneity of glycosylation, comprehensive analysis faces significant challenges.

The initial challenge of limited availability of glycopeptides in MS analysis could be largely addressed through the development of various enrichment methods [3,4]. Nevertheless, despite the use of well-enriched glycopeptides, traditional approaches opt for the removal of glycans to circumvent the obstacles in intact glycopeptide identification, which unfortunately results in the loss of valuable glycan information [5]. Due to the interference between the fragmentation efficiency of the peptide and glycan component in MS, the acquiring adequate information within a single experimental workflow was one of the main challenges in intact glycopeptide identification until approximately five to ten years ago [6]. The advancements in MS instrumentation, fragmentation strategies, and high-throughput MS acquisition methods have now made this possible [7, 8, 9]. Various fragmentation mechanisms are now accessible through commercial MS instruments, each possessing unique characteristics for specialized glycopeptide analysis strategies [6]. Given that glycans tend to fragment more readily at lower energies, while peptide bonds necessitate higher energy levels for fragmentation, the sceHCD fragmentation technique is now widely employed [3,5,10, 11, 12, 13, 14∗∗, 15∗∗, 16]. This approach harnesses the combined energies to generate informative glycopeptide spectra in a single MS analysis, facilitating intact glycopeptide identification. Electron transfer dissociation (ETD) primarily cleaves N-Cα bonds, producing c/z ions, which could maintain the integrity of glycans while simultaneously breaking the peptide segments [5,6]. This makes it particularly valuable for multi-site localization. For instance, techniques like EThcD are now commonly used in conjunction with HCD for multi-site localization studies [16, 17∗∗, 18, 19, 20], especially those involving mucin-type glycosylation [9,21].

The fragmentation of both peptides and glycans in the spectrum, while efficient in providing abundant fragment information, introduces complexity that can be challenging to decipher. Over the past few decades, dedicated software tools for intact glycopeptide analysis have undergone remarkable development [6,8]. It has evolved from initially treating glycans as static peptide modifications, through the early necessity of establishing a deglycosylated peptide library to simplify the search process, and eventually advanced to allow direct interpretation of glycopeptide spectra following a single LC-MS/MS analysis [5, 6, 7,22, 23, 24]. In the last five years, there has been a rapid emergence of highly efficient glycopeptide interpretation software. Notable examples include the pGlyco series, which prioritizes glycan-first searching, and software such as Byonic and MSFragger-Glyco, which prioritize peptide-first searching [7,23]. Comprehensive reviews have effectively summarized these software advancements, detailing their underlying principles and distinctive features [24].

More recently, substantial advancements have been achieved in glycoproteomic software tools, enabling more precise and comprehensive identification of intact glycopeptides and efficient site-specific glycoproteome differential analysis. Alongside software tools, efficient glycopeptide enrichment remains a dynamic focus within the field of glycoproteomics [3,4], along with ongoing advancements in MS-based data acquisition methods in this regard [25]. Many up-to-date reviews offer comprehensive and detailed insights into the enrichment and MS approaches [26,27], but they are beyond the scope of this review and will not be discussed here. In this short review, our primary focus will be on the most recent advancements in MS-based glycoproteomic approaches, especially on the identification and quantification software tools published in the past two years. The rapid advancements in glycoproteomic tools provide substantial opportunities for advancing glycosylation research, albeit accompanied by new challenges.