De novo sequencing of glycans by ion mobility-mass spectrometry using a self-expanding database

Domain: biology
Published: 2025-12-13
Editorial outcome: major_revision

Abstract
It is essential to determine glycan structures in complex biological samples to understand their biology and exploit their diagnostics, therapeutics and nutraceuticals potential. An unresolved analytical challenge is the identification of isomeric glycan structures in complex biological samples. Ion mobility (IM) combined with MS enables separation of isomeric glycans and identification by comparing their intrinsic collision cross section (CCS) values with similar data of synthetic standards. To identify glycans without the need to synthesize all biologically occurring glycans, we describe here an IM-MS de novo sequencing method based on fragment identification and sequence assembly. CCS values of additional fragments from glycans in biological samples result in a self-expanding reference database, gradually facilitating the sequencing of glycans of increasing complexity and expanding the database from an initial 19 standards to 332 unique entries. The methodology is employed to determine structures of human milk oligosaccharides and N-glycans of biotherapeutics.

Introduction
All eukaryotic cells are covered by a dense layer of glycans that are mediators of many biological processes such as protein folding, cell proliferation and differentiation, modulation of cell signaling, fertilization and immune regulation. Specific changes in cell surface glycosylation are associated with diseases such as inflammatory bowel syndrome, septic shock and neurological disorders such as Alzheimer’s and Parkinson’s disease. Aberrant glycosylation is also a determinant of cancer cell proliferative, invasiveness and immune suppressive properties1–5. Furthermore, many pathogens employ glycans of host cells for attachment and/or entry and are factors of host range and tissue tropism6. Also, many biologicals, such as monoclonal antibodies, are modified by complex glycans, which determine biological activity and pharmacokinetic properties7–9.

To understand their functions at a molecular level, it is essential to determine glycan structures in complex biological samples. An understanding of glycan structures will make it possible to develop the next generation glycan-based diagnostics, therapeutics and nutraceuticals and will advance the development of therapeutic glycoproteins. Glycans are assembled from monosaccharides that can be linked at different sites and in different configurations, resulting in many possible isomeric structures that have the same molecular formula but differ in the stereochemistry of monosaccharides, anomeric configurations, linkage positions and branching9,10. Current analytical approaches to analyze complex mixtures of glycans are primarily based on mass spectrometry (MS)11,12. These methods provide in general compositions but not molecular structures because MS alone cannot readily differentiate between isomeric structures. Isomeric glycans usually have very different biological properties, and for example, α2,3-linked sialosides are employed as receptors by avian influenza A viruses (IAV), whereas human IAVs use α2,6-linked sialosides for cell attachment and entry6. Thus, it is critical to develop analytical methods that can determine the structures of glycans.

The hyphenation of MS to ion mobility spectrometry (IMS) adds a separation dimension and offers the prospect of isomeric glycan identification, including linkage isomers and stereoisomers13–15. In IMS, gas phase ions are separated based on their mobility through a drift cell filled with a static inert buffer gas under the influence of an electric field. Higher charge state ions migrate with a higher mobility in this field, while ions with larger surface areas experience more ion-neutral collisions with buffer gas molecules and therefore their mobility is more reduced. IMS makes it possible to calculate intrinsic rotationally averaged ion-neutral collision cross-section (CCS) values from drift or arrival times16. Isomeric intact glycan or fragment ions can have different surface areas15,17–20 and therefore may exhibit distinct CCS values and arrival timed distributions (ATDs) that can be exploited for glycan identification.

To make ion mobility (IM)-MS suitable for glycan structure determination, databases are needed that can correlate mass-to-charge ratios (m/z), ATDs and CCS values to isomeric glycan structures19,21–23. Advances in chemoenzymatic synthesis make it possible to prepare collections of isomeric glycans24–28 that can be subjected to IM-MS to establish CCS values of intact and fragment ions to populate the required database. For example, we subjected a library of synthetic O-acetylated sialosides29 to drift tube IM-MS and established intrinsic CCS values of diagnostic fragment ions which could be used to determine O-acetylation patterns and anomeric linkages of released O- and N-linked glycans30. Despite the attraction of this approach, it is not possible to prepare all possible naturally occurring glycans due to the enormous structural diversity31.

To address this limitation, we describe here an IM-MS methodology for high-throughput structure identification and de novo sequencing of glycans using a limited number of synthetic glycan standards having common glyco-epitopes. In this approach, the standards are subjected to in-source collision-induced dissociation (CID) to produce informative intact and fragment ions for an initial IM-MS reference database. Next, glycans obtained from a biological source can be subjected to IM-MS and rapid identification can be made for those compounds that have an entry (m/z and ATD or CCS values) of the intact ion in the reference database (steps 1–3, Fig. 1). Compounds that do not have an entry will be subjected to CID and de novo sequencing by identifying structures of fragment ions that can be puzzled together, leveraging the established biosynthesis pathways, to elucidate the glycan structure (steps 4–6, Fig. 1). The premise of the approach is that although the intact ion may be absent in the database, the presence of fragment ions will facilitate de novo sequencing. The m/z, ATD, and CCS values of the elucidated intact and fragment ions can be added to the reference database for rapid identification in other samples or for the de novo sequencing of larger and more complex structures (Fig. 1), creating a self-expanding reference database. Thus, the IM-MS methodology continuously exploits data from previous analyses of biological samples to elucidate other new glycan structures while at the same time expanding the reference database. We demonstrate here that by applying data of 12 glyco-epitope fragment ions in this iterative process, the reference database could be expanded to 332 entries. The IM-MS methodology with a self-expanding reference database will make it possible to identify structures rapidly and unambiguously in biological samples without the need for a large collection of standards.

Results
Identification of HMO structures
To develop the de novo sequencing methodology, we first prepared and analyzed human milk oligosaccharides (HMOs), which contain epitopes commonly found in other glycan classes. HMOs possess probiotic properties by serving as metabolic substrates for beneficial bacteria, thereby shaping the intestinal microbiota of breast-fed infants32–34. In addition, they protect from infections by acting as decoys for receptors of pathogens35,36. HMOs can also modulate epithelial and immune cell responses and reduce excessive mucosal leukocyte infiltration and activation. The health benefits of HMOs correlate to specific structures and their abundance37–39, which may vary between milk donors and change during lactation. Given the health benefits of HMOs, this class of compounds is receiving increasing attention for the development of functional foods.

All HMOs have a reducing lactose moiety that can be extended by N-acetyl lactosamine (LacNAc; galactose-β(1,4)-N-acetylglucosamine) to give a type II chain (compound 1, Fig. 2a) or Lacto-N-biose (LNB; galactose-β(1,3)-N-acetylglucosamine) to give a type I chain (compound 2, Fig. 2a). The resulting tetrasaccharides can be functionalized with fucosides or sialosides or be converted into an I-branched structure by the addition of N-acetylglucosamine (GlcNAc) to the penultimate galactose. Iterative additions of LacNAc or LNB structures, followed by fucosylation and sialylation, result in structurally very diverse compounds.

To develop an initial reference database of m/z and CCS values, a collection of HMOs having common epitopes was prepared (Supplementary Methods). Lacto-N-neotetraose (compound 1, Fig. 2a) and lacto-N-tetraose (compound 2, Fig. 2a) were used as starting materials, and a panel of glycosyltransferases was employed to install galactosides, N-acetylglucosaminosides, sialosides and fucosides to give Lewis and ABO blood group epitopes (Fig. 2a and Supplementary Fig. 1). The standards were derivatized at the reducing end with procainamide (ProcA)40 and analyzed in triplicate with drift tube (DT)IM-MS in positive ion mode. The MS spectra of intact ions showed protonated, sodiated and potassiated ions (Supplementary Data 1) and their CCS values were calculated from their IMS arrival times using single field CCS calibration employing a standard tuning mixture with known m/z and CCS values41. Most structures exhibited distinct m/z and CCS combinations for the different ion adducts, with maximum relative standard deviations of 0.3% for CCS values (Supplementary Data 1), allowing the use of multiple ions to improve identification accuracy in biological samples. This approach is particularly useful when CCS values for isomers with specific adductions differ by less than 1%41, as seen with protonated ions of 3 and 5 (Fig. 2a). The standards were also subjected to in-source CID in positive ion mode, which provided B-type fragment ions42, which are oxonium ions that retain the non-reducing end, originating from glycosidic bond fragmentation only42 (Supplementary Data 1). The fragments showed unique combinations of m/z and CCS values for isomeric structures, with maximum relative standard deviations of 0.4% for CCS values (Supplementary Data 1), such as for F1-F4 (Fig. 2b) that differ in sialic acid linkage, and F10-F11 (Fig. 2b) that differ in fucose linkages.

HMOs from five different commercially available human milk samples were extracted and separated into acidic or neutral HMO fractions. The HMOs were derivatized with ProcA and analyzed with liquid chromatography (LC)-IM-MS. Most of the extracted HMOs were resolved chromatographically, and 14 structures could be rapidly identified by matching their CCS and m/z values with reference data (Supplementary Data 1 and 2). To identify structures without an entry in the database, the HMOs were subjected to in-source CID in positive ion mode and de novo identified. Parent ions were detected as double-charged protonated, sodiated and potassiated ions in the fragmentation spectra, while fragment ions were mostly observed as single-charged protonated or oxonium ions. The accurate masses of the intact double-charged ions revealed the monosaccharide compositions, and by matching CCS and m/z values of fragment ions to entries in the reference database, the glycosidic linkages between monosaccharides could be determined. Full HMO structures could then be reconstructed by assembling the fragments, taking into consideration well-established biosynthesis pathways34. For example, a compound detected in all milk samples having an m/z of 1218.5 is composed of glucose (Glc), N-acetylneuraminic acid (Neu5Ac), GlcNAc, galactose (Gal), and the ProcA label (Fig. 2c). The CCS value of the fragment ion at m/z 657 corresponds to fragment ion F3 (Fig. 2b) in the reference database, revealing the presence of Neu5Ac α6-linked to a LacNAc moiety. This fragment can only be attached to lactose (F20) in a β3-linked fashion according to the biosynthetic rules, and therefore, the full structure was identified as α6-sialyllacto-N-tetraose c with a ProcA label at the reducing end. The correct structural assignment was validated by matching the CCS value of the protonated parent ion with the CCS value of standard 3 (Fig. 2a). The data of the other fragment ions were added to the reference database to progressively elucidate more complex structures having the same fragment ions.

The identification of fragments in fucosylated HMOs can be challenging using only MS, as fucosyl residues can rearrange within the structure upon ion activation. Fucosyl residues rearrange to nucleophilic acetamido moieties on Neu5Ac and GlcNAc residues, as well as nucleophilic sites on reducing-end labels43, which may lead to incorrect fucose linkage assignment. We determined the CCS value of a 3-fucosyllactose standard, with native α3-linked fucose on glucose (Supplementary Data 1)44, and compared it to isomeric fragment ions with rearranged fucose from all fucosylated standards having natively α2-, α3- or α4-linked fucose (Fig. 2a). The 3-fucosyllactose standard exhibited a CCS of 254.6 ± 0.1 Å² (n = 3), while fragments with a fucoside rearranged to the reducing-end label showed a CCS of 252.4 ± 0.5 Å² (n = 36, Supplementary Data 1), enabling the differentiation of isomeric fragments with native and rearranged fucose and highlighting the potential of IM-MS for accurate identification of fucosylated structures.

In addition to functionalization with sialosides and fucosides, HMOs can be elongated by LNB and LacNAc moieties that determine type I (F22) and type II chains (F23, Fig. 3a), respectively. Differentiation between type I and type II chains can be achieved through the identification of terminal (F3, Fig. 2c) or elongated B-type fragment ions. For example, sialyl Lewis x (sLex), which is a sialylated and fucosylated type II structure, has a CCS of 257.1 Å2 (Fig. 1b), whereas sialyl Lewis a (sLea), which is an isomeric type I structure, gives a CCS value of 244.2 Å2 (Fig. 1b) and thus can readily be differentiated. Other isomeric type I and II structures, such as Lewis x (Lex) vs. Lewis a (Lea) also pose different CCS values. Furthermore, the CCS values of linear B-type fragment ions having two or more LacNAc moieties or LacNAc moieties extended with one terminal LNB moiety can also differentiate chain type. For example, CID of compound 20 having a terminal LNB moiety gives B-fragment ion F22 (m/z = 731.3, CCS = 262.0 Å2) and Y-type fragment ion F20 (Fig. 3a). The latter moiety confirms that the B-ion is linked to the reducing lactose moiety. A similar fragmentation of compound 21, which has a terminal LacNAc moiety, gives fragment F23 (m/z = 731.3, CCS = 252.2 Å2) and F20. The CCS values of F22 and F23 are substantially different and can differentiate between a type I or II terminal unit.

I-branching provides further structural diversity to HMOs and constitutes the addition of GlcNAc to the C-6 hydroxyl of an internal Gal and can occur on a type I and II chain as in compounds 22 and 23, respectively. I-branching can generally be identified by the presence of several fragment ions derived from terminal glyco-epitopes and by the absence of linear complementary B- and Y-type fragment ions. I-branched type I chain 22 produces isomeric fragments F24 and 2, while type II chain 23 gives F24 and 1 (Fig. 3a) and were expected to determine the chain type. However, HMOs from milk samples having backbone structures 22 and 23 produced a single signal in the ATD for the isomeric fragments. This is likely due to the similarity in arrival times and CCS values between fragment ion F24 and ions 1 and 2 (Fig. 3a). To study the fragmentation preferences of I-branched structures and possible co-migration of these isomeric fragments in IMS, we enzymatically synthesized an I-branched type I chain HMO having a 13C6-labeled Gal on the β6-arm and analyzed this standard by IM-MS (24, Fig. 3a and Supplementarry Data 1). This isotopically labeled structure indeed produced similar fragments as for 23, but with one being heavier (F25, Fig. 3a). This facilitated the generation of extracted ion ATDs at their respective m/z values, revealing minimal separation in arrival times between the isotopologue fragments 2 (blue) and F25 (orange, Fig. 3b). In addition, it allowed the simulation of how 2 and F25 would appear in the ATD if they were isomers, by extracting an ATD based on the combined m/z value of both ions (green, Fig. 3b). This ATD exhibited a convoluted signal representing both 2 and F25 and showed a weighted average arrival time (t2+F25, Fig. 3b) and thus CCS, which depended on the abundances of the individual signals. The convoluted signal of compounds 1 and 2 (Fig. 3a) hindered chain type determination, and therefore CCS values of terminal epitope and backbone fragments from I-branched HMOs (22-23, Fig. 3a) were used accordingly. Distinct CCS values were observed for backbone fragments with type I (22, Fig. 3a; 334.7 ± 0.6 Å2, n = 5) and type II chains (23, Fig. 3a; 330.2 ± 0.6 Å2, n = 7 independent measurements) in I-branched structures from milk samples, with the type I chain values validated by standard 24 (Fig. 3a; 334.9 ± 0.0 Å2, n = 3 independent measurements). Further evidence, such as the presence of multiple terminal epitopes, also directly demonstrates I-branching.

Based on the gathered information, a structure with a degree of polymerization of 9 (DP9) was de novo sequenced as shown in Fig. 4. The composition was determined from the accurate mass of potassium and sodium adducted ions and contained three Gal, one Glc, two GlcNAc, two Fuc, and one Neu5Ac moiety and a ProcA label (step 1). A Glc, Gal and GlcNAc moiety are linked according to the well-established HMO biosynthesis, forming a core trisaccharide (GlcNAc-β(1,3-)Galβ(1,4)-Glc) and the ProcA label is attached to the reducing end (step 1). In steps 2 and 3, the fragments at m/z 657 and 658 showed overlapping isotope distributions that were filtered based on their distinct drift times to obtain individual isotopic envelopes. The fragments were identified as F3 and F11 (Fig. 2b), respectively, based on their m/z and CCS values. These fragments are terminal epitopes and therefore should occur on different arms indicating an I-branched structure. I-branching was further confirmed by the absence of complementary extended B-type fragment ions along with the Y-type lactose core fragment ion (step 4). The previously identified compound 3 (Fig. 2c) is a fragment ion in this structure (step 5), revealing a type II chain having a β3-linkage of F3 to Gal of lactose. The GlcNAc moiety, which is part of F11, is β6-linked to Gal of lactose based on biosynthetic rules of I-branched structures, and thus F11 must be attached to the β6-arm revealing compound 25 by de novo sequencing (Fig. 4). The identification of the structure of the β6-arm as fragment ion F26 (step 6), provided a new entry for the reference database facilitating the identification of other I-branched structures having a Ley motif at the β6-arm.

By analyzing the five donor milk samples (Supplementary Figs. 2–144), 186 new entries for the reference database were obtained (Supplementary Data 3). Structures of the 43 most abundant HMOs, having a complexity up to DP9 and encompassing both linear and I-branched structures with various terminal epitope motifs, were assigned (Fig. 5). The assignment of several HMOs with type II structures was validated by the analysis of synthetic standards44 (Supplementary Figs. 145–148) and comparison of their CCS values. Interestingly, for one of the identified compositions, comprising of Lacto-N-triose, two Gal, one N-GlcNAc, one Fuc and one Neu5Ac, in principle 36 different isomers are possible (Supplementary Fig. 149). However, only one of these structures was detected in all donor samples, and only three other isomers in one donor sample (Fig. 5). This observation indicates that the glycosyltransferases involved in the biosynthesis of HMOs have more intricate specificities and fine structural details determine acceptor capabilities.

Individual genetics of mothers play an important role in the variability of HMO structures, specifically by the expression of the fucosyltransferases FUT2 and FUT345. Milk from secretor mothers (Se+), for example, is characterized by high levels of α2-fucosylated HMOs, such as 2′-fucosyllactose and LNFPI. Non-Secretor mothers (Se-) lack a functional FUT2 enzyme and therefore have less α2-fucosylated HMOs in their milk. In addition, mothers classified as Le positive (Le+) express the FUT3 enzyme, which facilitates the addition of α4-linked Fuc to a GlcNAc residue. Conversely, milk from Le negative mothers (Le-) contains less α4-fucosylated HMOs, such as LNFPII34. Based on the elucidated structures, the five donors could be classified according to their Se and Le status into one of the four milk groups: Se+/Le-, Se-/Le-, Se+/Le+, and Se-/Le+46. Donor three was classified in milk group four (Se-/Le+), while the other donors were classified in milk group three (Se+/Le+). These classifications can provide insights into the diverse composition of human milk that impacts infant growth, development and overall health34,45.

Identification of N-glycan structures
Next, attention was focused on the identification of N-glycans, which have a common pentasaccharide core consisting of Man(α1-3)[Man(β1-6)]Man(α1-4)N-GlcNAc(β1-4)β-N-GlcNAc that can be further branched and extended with additional LacNAc moieties47. The resulting multi-antennae structures can be sialylated and fucosylated, generating terminal epitopes similar to those found on HMOs. Recently, we demonstrated that N-glycans can adopt several stable conformations in the gas phase, which can be separated in the IMS dimension and used for structure identification by comparing ATD fingerprints with reference database entries18. Here, a further collection of 49 chemoenzymatically synthesized complex N-glycan standards, including many isomeric structures (Supplementary Fig. 150)18,48–50, was subjected to IM-MS to expand the reference database with high resolution (HR-)ATDs. The standards include bi- and tri-antennary glycans having various numbers of LacNAc extensions modified with different linkage types of Neu5Ac and Fuc. The standards were derivatized with 2-aminobenzoic acid (2AA) by reductive amination and analyzed in triplicate by IM-MS in positive and negative ion mode with nitrogen as buffer gas. The HR-ATDs of the glycan standards showed unique fingerprints for each glycan (54, 55, 57 and 58 in Fig. 6a and Supplementary Figs. 151–156). The distributions are predominantly multimodal, having on average around three conformers in the ATDs for deprotonated, protonated, protonated-sodium and protonated-potassium adductions and were unique for all isomeric structures. The distributions were reproducible and not affected by eluent composition in LC-IM-MS experiments using an electrospray source (either a standard electrospray ionization source or the Jet Stream interface with superheated nitrogen; Supplementary Figs. 157–163), other than minor changes in peak intensities18.

The ATDs, CCS and m/z values of the standards were employed for the identification of N-glycans released from Aflibercept, which is an Fc fusion protein of the extracellular domain of the human VEGF receptor51, which is used for the treatment of macular degeneration52 and metastatic colorectal cancer. The N-glycans were released with PNGase F, derivatized with 2AA and analyzed by LC-IM-MS. By matching m/z and ATD fingerprints with those in the reference database, six structures could be identified (Supplementary Fig. 164). This includes glycans having a core fucoside and α2,3-linked Neu5Ac (compounds 56 and 59, Fig. 6a), which is consistent with production in Chinese hamster ovary cells that lack α2,6-sialyltransferase expression53.

De novo structure identification was performed for glycans without an entry in the reference database. For this purpose, PNGase F-released glycans were derivatized at the reducing end with ProcA, which offers greater sensitivity in positive ion mode compared to aromatic amines such as 2AA54, while providing glycosidic bond fragmentation only. Compositions of 19 N-glycans from Aflibercept could be determined by accurate mass measurement of the sodiated and potassiated doubly charged ions, which did not fragment at the applied activation energy. From the compositions, it could be established that all structures have a biantennary architecture, including hybrid and complex type glycans (Supplementary Fig. 166). Hybrid type structures have mono-, di- or tri-mannosyl residues at the α6-linked arm and a complex epitope at the α3-arm55. Therefore, structures of these compounds (66, 67, 72, and 73 Fig. 6c), could be identified from m/z and CCS values of previously identified fragment ions (Supplementary Figs. 168–171). For example, fragment ion F3 (Fig. 6b) demonstrated the presence of an α2,3-sialyl LacNAc moiety at the α3-mannosyl arm in compounds 72 and 73 (Fig. 6c and Supplementary Figs. 170 and 171).

To distinguish complex isomeric N-glycans having a unique epitope at each antenna, we analyzed standard 60 (Fig. 6b and Supplementary Fig. 165). It has an α2,6-linked Neu5Ac at the α3-mannosyl antenna, which upon activation produces the diagnostic primary fragment ions F27 and F28 (Fig. 6b). The structure of disialylated N-glycan 62 released from Aflibercept could readily be determined from its composition and the presence of fragment ion F4 (Fig. 6b and Supplementary Fig. 184). Upon activation, it produced multiple pairs of isomeric diagnostic fragment ions, including secondary fragment ion F30 (Fig. 6b). This fragment is isobaric to F27 but has a substantially different CCS value (354.7 Å² vs. 364.8 Å²) and therefore its structure could readily be identified as only one alternative isomer is possible. In a similar way, the primary fragment ions F29 and F31 were identified by using fragment ions of 61 as a reference (Fig. 6b). The structure of monosialylated 61 and 74 (Fig. 6c) could be determined from previously determined diagnostic fragment ions F27 and F30, respectively. The linkage type of Neu5Ac was determined by matching the corresponding fragment ion with F4 (Figs. 2b, 6b and Supplementary Figs. 180, 181). No isomers are possible for N-glycans 69 and 81 (Fig. 6c), allowing structural identification based on their fragment ions (Supplementary Figs. 167 and 172). The isomeric structures 68 and 70-71 (Fig. 6c, Supplementary Figs. 174-175 and 178) were identified by the presence of diagnostic fragment ions F27 and F30 (Fig. 6b). Following a similar approach, diagnostic fragment ions for core-fucosylated N-glycans 75–80 and 83 (Fig. 6c) were obtained through the identification of F27, F30 and F4 (Fig. 6b) in their fragmentation spectra (Supplementary Figs. 173, 176, 177, 179, 182, 183, and 185).

The new entries enable the identification of glycans with longer antennae and having various terminal epitopes. The database of CCS and m/z values was, for example, applied for the identification of isomeric glycans released from transferrin (Supplementary Fig. 186)56. The glycans of transferrin are employed as biomarkers for various diseases, and more accurate assignment of structures will increase prognostic and diagnostic value57. It made it possible to identify isomeric di-sialylated N-glycans having different combinations of 2,3- and 2,6-linked sialosides. In this respect, di-sialylated compounds, such as 64 (Fig. 6b and Supplementary Figs. 189, 190), could easily be identified using fragment ion F3 (Fig. 2b). Upon activation, structure 65 produced diagnostic fragments F28 and F32 (Fig. 6b), which were identified using fragments of 60 (Fig. 6b) as reference for comparative analysis (Supplementary Figs. 187, 189). Fragment ions F3 and F4 (Fig. 2b) demonstrated that di-sialylated glycan 65 is modified by an α3- and an α6-linked Neu5Ac. Fragments F28 and F31 (Fig. 6b) established that the bottom arm of 65 is modified by α2,6-linked Neu5Ac, revealing the structure of this glycan (Supplementary Fig. 191). The structural assignment of this compound was validated by comparing the ATDs and CCS values of the released glycan (Supplementary Fig. 227), labeled with 2AA at the reducing end, with those of a previously reported standard18. The isomeric fragments F27-F32 and their core-fucosylated glycoforms can be used to either directly identify all non-, mono- and disialylated structures of biantennary glycans or to uncover new pathways for identifying more extended N-glycans in biological samples.

Many common fragment ions were identified in the mass fragmentation spectra of the different N-glycans, which facilitated validation of assigned fragment ions and full structures. The assignments were also validated by matching ATD fingerprints and CCS values of identified structures from proteins with a library of ProcA-derivatized standards. In addition, the standards were also used to demonstrate that ATDs of N-glycans are minimally affected by variations in the energy applied during CID (Supplementary Figs. 192–226).

Methods
Materials and reagents
Sodium acetate, sodium cyanoborohydride, tris(hydroxymethyl)aminomethane (TRIS), acetic acid (LC-MS grade), ammonium hydroxide (LC-MS grade), formic acid (LC-MS grade), sodium acetate, DEAE Sepharose Fast Flow ion exchanger resin, ammonium bicarbonate, sulfuric acid, ethanol, trifluoroacetic acid (TFA), dimethylsulfoxide (DMSO), dichloromethane (DCM), 2-aminobenzoic acid (2AA), procainamide HCl (ProcA) and ammonium acetate were acquired from Merck (Darmstadt HE, Germany). Hypercarb 25 and 200 mg porous graphitized carbon (PGC) solid phase extraction (SPE) cartridges were obtained from Thermo Fisher Scientific (Waltham MA). Acetonitrile (LC-MS grade) was purchased from Biosolve B.V. (Valkenswaard, The Netherlands). Acetone (LC-MS grade) was obtained from Boom (Meppel, The Netherlands). Ultrapure water was produced by a Synergy UV water purification system from Merck-Millipore (Burlington MA). Peptide:N-glycosidase F (PNGase F) and glycosyltransferases were produced in-house. UDP-Gal, UDP-N-acetylglucosamine, UDP-N-acetylgalactosamine and CMP-Neu5Ac were purchased from Roche Diagnostics (Basel, Switserland). Calf intestine alkaline phosphatase (CIAP) was obtained from Thermo Fisher Scientific (Waltham, MA). GDP-fucose was prepared using L-fucokinase/GDP-fucose pyrophosphorylase. Lacto-N-tetraose was a gift from Friesland Campina (Amersfoort, The Netherlands) and purified by preparative LC before use. Endoglycosidase F2 (Endo-F2) was purchased from New England Biolabs (Ipswich, MA). D2O (99.9%) was purchased from Buchem (Apeldoorn, The Netherlands). Avantor C18 1 ml SPE cartridges (100 mg) were acquired from Baker (Radnor, PA). Minitrap G-10 cartridges were obtained from GE Healthcare (Chicago, IL) and Vivaspin 2 10 kD filters were acquired from Sartorius (Götingen NI, Germany). Bio-Gel P2 gel polyacrylamide beads were acquired from Bio-Rad (Hercules, CA). Human milk was purchased from Medix Biochemica (Epoo, Finland).

ProcA and 2AA labeling
Labels were attached to free reducing end glycans via reductive amination. A 120 µL volume of glycan standards or released glycans in water was mixed with 40 µL labeling solution (30 mg/mL ProcA or 2AA and 75 mg/mL sodium cyanoborohydride in DMSO) and 20 µL acetic acid. The mixture was vortexed and incubated at 68 °C for 2 h, unless specified otherwise. The reaction mix was evaporated under a nitrogen flow, and the residue was dissolved in 1 mL water for PGC SPE purification.

PGC SPE purification
Solutions of released or derivatized glycans were purified by PGC SPE with a 25 mg cartridge. The cartridge was conditioned with 1 mL ACN followed by 1 mL water. The sample was loaded on the cartridge and washed with 1 mL 0.05% TFA, followed by 1 mL ACN/water/TFA (5%/ 94.95%/ 0.05%). Glycans were eluted with 1 mL ACN/0.1% TFA (50%/ 50%). The eluent was evaporated under a nitrogen stream, and the sample was redissolved in water for LC-DTIMS-MS analysis.

For the analysis of ProcA-derivatized glycans, 15 µL sample was injected onto a 150 × 4.6 mm (3 µm) Thermo Fischer Scientific Hypercarb PGC column, which was maintained at 60 °C during analysis, and separated with a gradient using 0.1% formic acid (A) and ACN (B) at a flow rate of 1 mL/min. The gradient started at 25% B for 5 min and increased to 35% in 100 min. DTIMS-MS in positive ion mode used a fragmentor voltage of 550 V and a mass range of m/z 100–3200.

LC-DTIMS-MS
The LC-DTIMS-MS system consisted of an Agilent Technologies (Santa Clara, CA) Infinity LC system with a 1290 Binary pump, a 1290 sampler and a 1260 thermostatted column compartment. The LC system was coupled via electrospray ionization interface or a dual jet stream electrospray ionization interface to an Agilent Technologies 6560 Ion Mobility Q-TOF LC/MS system. The DTIMS-MS was used in both negative and positive ion modes. The MS source parameters with the dual jet stream interface were a capillary voltage of 3500 V, nozzle voltage of 1000 V, nebulizer gas pressure of 40 psi, N2 drying gas heated to 300 °C at 8 L/min and sheath gas heated to 350 °C at 11 L/min. The MS source parameters with the electrospray ionization interface were a capillary voltage of 3500 V, a drying gas flow of 10 L/min, a drying gas temperature of 300 °C, and a nebulizer gas pressure of 20 psi.

The ion mobility measurements were conducted using an DTIMS transient rate of 16 transients/frame, a trap fill time of 3900 µs, a trap release time of 250 µs, a drift tube entrance voltage of 1700 V for positive mode and −1700 V for negative ion mode (unless specified otherwise), a drift tube exit voltage of 250 V for positive and −250 V for negative ion mode, nitrogen as drift tube gas type, a drift tube pressure of 3.95 Torr, a trap funnel pressure of 3.80 Torr and a multiplexing pulsing sequence length of 4 bit. For in-source activation of HMO structures, a fragmentor voltage of 500 V was used. For N-glycans, a fragmentor voltage of 550 V was applied for fragmentation and 360 V for the analysis of intact structures.

Analysis of N-glycan reference standards derivatized with 2AA
Glycan standards were labeled with 2AA (38 N-glycans) or ProcA (3 N-glycans) at the reducing end and analyzed with hydrophilic interaction liquid chromatography (HILIC) with a 20 × 2.1 mm (5 µm) Merck SeQuant ZIC-HILIC column (Burlington, MA). Volumes of 1 µL of 1 µg/µL solutions were injected and analyzed with an eluent composition of ACN/water with 0.1% formic acid for positive ion mode analysis of N-glycans with a 2AA label (10 N-glycans; n = 3 measurements each) and a ProcA label (3 N-glycans; n = 3 measurements each), and ACN/10 mM ammonium acetate (pH 4.4) for negative ion mode MS (38 N-glycans; n = 3 measurements each), at a flow rate of 0.2 mL/min. The eluent compositions were adjusted for each compound to ensure proper retention on the chromatographic column.

Analysis of N-glycans from Aflibercept
Aflibercept solution of 1 mg/mL was loaded on a 10 kD aspin filter and centrifuged till near dryness at 4824 xg. A 4 × 1 mL volume of 100 mM sodium acetate (pH 4.5) was added, and the sample was centrifuged again (4824 xg, leaving at least 100 µl solution). N-glycans were released enzymatically from the biological Aflibercept by PNGase F, derivatized with 2AA or ProcA and further purified by PGC SPE before LC-DTIMS-MS analysis (n = 1 measurement).

2AA-derivatized N-glycans were analyzed on a 150 × 2.1 mm (3 µm) Merck Sequant ZIC-HILIC column using a gradient with 10 mM ammonium acetate (pH 4.4; A) and ACN (B, starting at 20% A for 5 min and increasing to 50 % A in 25 min at a flow rate of 1 mL/min. The column was maintained at 40 °C during analysis, and 15 µL of sample was injected for analysis. A mass range of m/z 100–3200 was used for DTIMS-MS measurements.

NMR Characterization of HMO structures
Standards were dissolved in D2O at concentrations of approximately 0.25 mM and measured with NMR at 298 K. Spectra were recorded on a Bruker 600 MHz Avance Neo NMR spectrometer (Billerica, MA) equipped with a 5 mm TCI Prodigy CryoProbeTM. Chemical shifts were referenced to the residual water signal (HOD) at δ 4.790 ppm. Assignments of 1H and 13C NMR resonances were performed using a combination of 1D and 2D experiments. All spectra were acquired with standard Bruker pulse sequences: 1H (zg30), COSY (cosygpppqf), TOCSY with a mixing time of 80 ms (mlevphpp), NOESY with a mixing time of 300 ms (noesygpphpp), and HSQC (hsqcedetgpsisp2.3). 1H Proton NMR spectra were acquired with a spectral width of 19.9 ppm, 200 scans, an acquisition time of 2.7 sec and a recycle delay of 1 sec. HSQC spectra were recorded with 256 data points in F1 dimension and 2048 in F2 dimension, using 8 scans. The spectral widths were 16 ppm for 1H and 165 ppm for 13C dimensions. Assignments of 13C NMR signals were deduced from 2D HSQC spectra. 2D COSY, TOCSY and NOESY spectra were all collected with a proton spectral width of 4.16 ppm in both dimensions, using 8 scans. Data acquisition was performed using Bruker TopSpin 4.5.0 software, and all spectra were processed and analyzed with MestReNova 12.0.4-22023 (Mestrelab Research S.L., Santiago de Compostela, Spain). NMR signals were described by their chemical shift, multiplicity (d=doublet, t=triplet, q=quartet, dd=doublet of doublets, app.=apparent), and J coupling constants when applicable.

Analysis of acidic and neutral HMOs in human milk
Human breast milk samples from 5 individuals were analyzed with IM-MS (n = 1 measurement each). Sex- and gender-based analyses were not performed, as the study involved the development of an analytical method for glycan analysis. Therefore, sex and gender were not relevant to the study design.

A volume of 1 mL milk from each individual was centrifuged at 4824 xg for 10 minutes. The solution was frozen to solidify the fat layer, and the supernatant was transferred to a clean tube. This process was repeated 3 times to ensure the removal of fat. Subsequently, the samples were loaded on 10 kD aspin filters and centrifuged at 2415 xg for 20 min to remove high molecular weight compounds. The filtrate was freeze-dried, and the residue was redissolved in 2 mL water for purification by SPE using a 200 mg PGC cartridge. The cartridge was conditioned with 2 mL 90% ACN/10% water, followed by 2 mL 0.05% TFA in water. The sample was loaded on the cartridge and washed with 2 mL 0.1% TFA in water, followed by 2 mL ACN/0.05% TFA in water (5%/ 95%, v/v). The HMOs were eluted with 2 mL ACN/0.05% TFA in water (50%/ 50%, v/v). The eluate was dried under a nitrogen flow, and the residue was redissolved in water. The HMO sample solution was loaded on a DEAE Sepharose Fast Flow ion exchange column with a 3 mL bed volume. The neutral HMOs were eluted with 6 ml water, and subsequently, the acidic HMOs were eluted with 1 M ammonium bicarbonate. All fractions were freeze-dried. Subsequently, the acidic HMO fractions were dissolved in 3 mL water, and the neutral HMO fractions in 1 ml water. The HMOs in these solutions were derivatized via reductive amination with ProcA by taking 500 µL of each sample solution and adding 100 µL acetic acid and 300 µL labeling solution, containing 30 mg/mL procainamide and 75 mg/mL cyanoborohydrate in DMSO. The mixture was incubated at room temperature overnight and then evaporated under a nitrogen flow. The residue was redissolved in 1 ml water and purified using 200 mg PGC SPE cartridges as described above. The eluate was freeze-dried and reconstituted in 300 µL water for PGC LC-DTIMS-MS.

A sample of 5 µL was injected onto a 150 × 4.6 mm Thermo Scientific Hypercarb PGC column with 3 µm particles, which was maintained at 60 °C during analysis, and separated with a gradient using 0.1% formic acid (A) and ACN (B) at a flow rate of 0.5 mL/min. The gradient started at 20% B for 5 min and increased to 40% in 90 min and then to 100% in 10 min and maintained at 100% for 15 min. DTIMS-MS was used in positive ion mode and used a drift tube entrance voltage of 1700 V, a fragmentor voltage of 500 V and a mass range of m/z 100–3200.

DTIMS-MS data processing and construction of the self-expanding database
Masses of raw 4 bit multiplexed DTIMS-MS data were recalibrated on reference masses with m/z 121 and m/z 922 using the DTIMS-MS Data File Reprocessing Utility in the Agilent Technologies MassHunter software (v10.0). Reprocessed data was demultiplexed using the PNNL Preprocessor software v4.0 (Pacific Northwest National Laboratory, Richland WA) using an interpolation of 3 drift bins and a 5 point moving average smoothing in the DTIMS dimension70. Features were identified with the Agilent Technologies MassHunter IMS Browser software v10.0 using an unbiased isotope model. The feature list was used to obtain high-resolution ATDs using Agilent Technologies HRdm v2.0 software with an m/z width multiplier of 12, saturation check of 0.40 and an IF multiplier of 1.125 with SSS and Post QC enabled71. CCS values of the ions were calculated from their IMS arrival times using single field CCS calibration employing a standard tuning mixture with known m/z and CCS values41.

For the reference database, data obtained for the reference standards (Fig. 2a, b) were organized into columns in a spreadsheet and included the following information: the theoretical m/z of the intact glycan ion or fragment ion, the ion structure, the CCS value, the type of adduction, and for fragment ions, the fragment ion type and the structure of the parent compound. A remarks column indicated the origin of the ion, which, in the case of the reference standards, was a synthetic standard.

These entries were used to manually identify novel structures in biological samples that were not yet present in the database. The unknown structures were first fragmented, then the compositions of the resulting ions were determined based on their m/z, and finally, the structures were identified based on their CCS values. This information was then used to reconstruct and identify the full glycan structures. Each newly identified structure generated additional fragment and intact ion entries, which were incorporated into the spreadsheet along with their corresponding biological origin. These new entries, in turn, enabled the identification of further structures in biological samples, creating a continuously expanding dataset with each new measurement.

The reference database (Supplementary Data 3) will continue to be extended and refined. Contributions from external data sources are welcome and encouraged.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Summary\nThis interesting manuscript describes very detailed MS/MS and IMS analysis by a highly experienced MS group, trying to provide a solution to resolving of glycan structural diversity by ion mobility mass spectrometry. The authors characterised the glycans by figuring out the CCS values of key diagnostic fragments of the various glycans, and uses them to build a library that can be expanded across various types of glycans that can contain these diagnostic ions/features to provide high throughput characterisation of glycans.\nComments\nThis is a massive amount of foundational work that the field will greatly appreciate if made widely available, or at the very least, other groups start to follow suit with the deeper level of glycan structural feature characterisation that is beyond glycan composition. Particularly, since these fragment ions should, to some extent, be observable in glycopeptide spectrums if acquired with appropriate fragmentation methods. Below are comments that require additional information or clarification:\n1) This method is reliant on the CCS of MS2 fragments from in source fragmentation/activation. Please elaborate on how transferable this instrument (Agilent) requirement/setting will be for other ion mobility instruments, such as Bruker’s TimsTOF, or Waters TWIMS for the broader audience.\n2) The error range for the CCS values of some of the fragments drawn in fig 2 is narrower than what can be seen on the spreadsheets in the supplementary. Such as fragment F3 is specified as 232.6 +- 0.1 A, but in the supplementary table ccs values of F3 was reported from 232.3 to 233.2.\n3) Also fig 2, and various supplementary spectrums, the 657 sialyl-lacNAc and 658 lewis b/y can be within the same isotopic envelope. With some of the supplementary spectrums, supp fig 35, where both are theoretically present and have very similar CCS values of 232.5 and 232.6, please explain how the library that is built can cope with this or is manual curation is still required.\n4) More information should be provided for the MS data processing and library building. What is the definition of “self-expanding database”? It is acknowledged that the self expanding database can be extended to O- glycans , GSLs but how is this to be achieved?\ni.e. There is room for expansion of the database after these 332 unique entries – will the database be maintained and able to accept external updates?\n5) Please share the glycan data on GlycoPost (https://glycopost.glycosmos.org/) instead of MassIVE, as glycopost is designed for glycomics data types.\nMinor comments\n1) Considering the current diversity of sialic acid linkages, and the synthesis capabilities shown in this manuscript, perhaps include a2,6sia-b1,3gal to finish the 2,3 2,6 sia with 1,3 1,4 gal combinations?\n2) For a number of supplementary spectrums (eg. supp F79, 80, 81), the sodiated adduct peak looks non-existent.\n3) Pg 13, “Bis-sialylated”. Please use di- or bi-sialylated. Di-sialylated is preferred as “Bis” in glyco usually refers to “bisecting”\n4) There are a number of acquisition types described in the methods, infusion-MS, HILIC-MS, PGC-MS. Please specify them in their respective figure legends.\n5) Please reference past efforts in CCS database building like https://doi.org/10.1021/acs.analchem.9b01476 and GlycoMob https://link.springer.com/article/10.1007/s10719-015-9613-7", "reviewer_2": "The manuscript by Torano and colleagues describe how to use IM-MS, a modern mass spectrometric technique, to manually determine isomeric glycan structures. Based on a small database containing 20 typical carbohydrate epitopes (peripheral sequence or determinants) synthesized by the authors specifically for this work, the authors established some important principles to deduce many more complex glycan structures.\nMethods for determination of isomeric glycan sequences based on mass spectral fragmentation patterns, such as multi-stage MS (MSn, N>2) have been well advanced.\nSince its development and application some 15 years ago, IMS has become an important part of MS-based strategies for sequencing isomeric glycans. To include the two important IMS parameters (CCS and ATD), in addition to m/z, for determining and deducing isomeric sequences is obviously more advantageous as has been recently demonstrated by many published works including those by the authors (e.g. Ref 27 of this manuscript and Agilent Application Note “Exact Structure Identification of Isomeric N-Glycans by High‑Resolution Ion Mobility LC/Q‑TOF”).\nThis reviewer is not convinced the use of the term “de novo” for the method developed in this work, as establishing fragmentation principles before their use for piecing together the fragmented MS information to determine an unknown glycan sequence are the norm in carbohydrate mass spectrometry. To this reviewer’s limited knowledge, “de novo” sequencing often refers to a method with the ability of deducing the sequence without relying on reference database and conventionally carried out by computer software.\nThere have been many works on software tools for computer-assisted automated or semi-automated glycan identification. For example, the sophisticated computational de novo algorithm described by Lapadula et al (Anal Chem 2005) based on MSn (m/z values of molecular and fragment ions and the connectivity of each structural fragment) can provide molecular topology without presumed biosynthetic constraints or external comparisons. Predicting glycan structure by de novo glycan annotation after deep learning and training on a large set of annotated MS/MS spectra from LC-MS/MS analysis is possible as has recently been demonstrated (Urban et al., Nat Methods 2024). However, at present the establishment of the fragmentation patterns and use of these unique and complex principles for detailed interpretation of naturally derived glycans still rely mainly on experienced carbohydrate chemists/biochemists such as the work presented in this manuscript. The lack of robust, dependable, and freely available software for automatic annotation of mass spectra is still a severe bottleneck that hampers their rapid interpretation.\nThis reviewer considers the work presented in this manuscript does not represent an important advance to the field of glycochemistry/glycobiology and lacks sufficient novelty.\nOne of the major concerns regarding this work is the relatively small reference database and the limited number of epitopes (antigens) in it. Although debatable, the numbers of peripheral sequences or glycan determinants have been estimated in the range of 4,000-7,000 (Cummings, Mol Biosyst, 2009). For the specific HMO database, internal Lewis epitopes were not considered which can be present in longer linear or branched chains, and for N-glycans, identification and differentiation of their phosphorylated and sulfated forms are important but these and the LacdiNAc epitope are not included. The method presented here may also be difficult for longer backbone sequences composed of mixed Type 1/Type 2 chains or for HMOs containing three branches (e.g. the octa- or decasaccharide backbones) which were not featured in the data presented. For the di-branched hexasaccharide backbones it seems that the evidence for branching pattern relies on the absence of linear complementary B- and Y-type fragments with no direct fragmentation evidence.\nThe other concern is the quality of the spectral data presented, relying on which many sequences proposed for glycans isolated from biological sample, e.g. the identified HMO sequences present in donor breast milk. There are a large number of unspecified ion peaks often with very high intensities. The authors picked up some ions with very low intensities to make the assignment without giving reasons. Many such examples can be found in the analytical results of oligosaccharides from breast milk: Suppl Figs 5-9 for the acidic fraction of milk from Donor 1; Suppl Figs 12, 14, 15, 19, and 22 for the acidic fraction from Donor 2; and many spectral figures for Donors 3-5. Similar spectra can be found in the neutral fractions from Donors 1-5, e.g. Suppl Figs 55, 62-64, 68 from Donor 1 and Suppl Fig 91 Donor 3. There are also many spectra (e.g. Suppl Fig 92) in which several different molecular structure formulars were marked (e.g. different [M+H]+ and [M+Na+H]+). It is not clear if these components/fractions after LC are still mixtures. The authors need to clarify these points.\nSome specific points\n1) Although there is no fucose residue rearrangement during MS/MS analysis in negative-ion detection, the authors prefer the use of positive-ion mode, in which the authors have previously reported Fuc rearrangement. However, here in this work the authors only mentioned that genuine 3-Fuc exhibited a CCS 254.6 while rearranged one at CCS 252.4. Does Fuc at positions other than 3 also undergo rearrangement, and if so whether the Fuc, originally at different positions (e.g. 2-Fuc or 4-Fuc), would rearrange to the same position and have the same CCS 252.4?\n2) The preparation of the 19 simple HMOs (tetra- to hexasaccharides) by enzymatic synthesis is straightforward as the laboratory has published many more complex HMOs and other types of glycans. For use as standards, it is important to have HPLC and MS data of the 22 HMOs to indicate purity. It does not seem to have the source/origin of the N-glycan standards.\n3) The authors introduced a term “Exact” structure of glycans and repeatedly used throughout the manuscript. Glycan structures normally contain sequence, linkage and alpha/beta anomeric configuration. It seems that the results provided in this work are only glycan sequences and linkages, and therefore perhaps the new term is mis-leading.\n4) Validation of glycans identified using the newly developed by standard is extremely important. However, the standard can be either well purified and characterized but the standard shouldn’t be defined as or restricted to “synthetic” only.\n5) Although it is stated in Abstract that 20 HMO standards were prepared for the initial reference database, in Fig 2a only 19 were shown. The synthesis of sample #20 with branching was described in Supplementary Information but another #20 with a linear sequence was listed in Fig 3a. The sources of standards #21-#24 were not shown or very difficult to find out.", "reviewer_3": "The present research article addresses the sequencing of complex human milk oligosaccharides and N-glycans by LC-CID-IM-MS using a self-expanding CCS library. The authors first describe the construction of a CCS library comprising intact ions and fragments of human milk oligosaccharide reference materials, which were synthesized chemoenzymatically. Based on this initial library, more complex human milk oligosaccharide structures were identified without the need for reference standards. In total, the authors analyzed 43 linear and branched human milk oligosaccharides up to a degree of polymerization (dp) of 9 from five donor milk samples, thereby expanding their library by 186 entries.\nIn the second part of the manuscript, the authors apply their approach to the class of N-glycans. Using a similar strategy, they enriched the CCS database with reference standards. Based on the updated library, N-glycans from Aflibercept and transferrin were analyzed, extending the CCS library to a total of 332 entries. Finally, the authors emphasize the significance of glycan sequencing and the potential impact of their method on the glycoscience field.\nThe CID-IMS data, methodology, and analysis are described in great detail and are supported by clear and informative figures. While glycan CCS databases have been reported previously—and some of them are cited here—the size and depth of the CCS database presented in this work are substantially greater and of considerable value to the glycoscience community. I am therefore pleased to recommend acceptance of the manuscript after a few minor changes.\nMinor Comments:\nOn page 2 “in-source collisional activated dissociation (CAD)“. It should be “collisionally” instead of “collisional”. Although CAD is fine, I would recommend to use collision-induced dissociation (CID) as CAD is often used for charged aerosol detection and CID is also more common in modern literature.\nOn page 4 the authors state \"The MS spectra of intact ions showed protonated, sodiated and potassiated ions and their CCS values were calculated from their IMS arrival times using single field CCS calibration employing calibration standards with known m/z and CCS values (Supplementary Dataset 1)38.” As far as I understand, the ProcA-labeled HMO standards in Supplementary Dataset 1 were used as a single field calibrant. This is a rather unusual calibration mixture, which I have not seen in the literature before. I don’t see any reference for the “known CCS values”. If there is no publication on this yet, it would be important to explain how the CCS values of Suppelementary Dataset 1 were determined. Single field with tuning mix or maybe using a stepped field approach? I think this is very important to explain in more detail as the whole CCS library is based on this calibration.\nOn page 4 the authors further state “Most structures exhibited distinct m/z and CCS combinations for the different ion adducts, allowing the use of multiple ions to enhance identification accuracy in biological samples. This approach is particularly useful when CCS values for isomers with specific adduct ions differ by less than 1%38, as seen with protonated ions of 3 and 5 (Fig. 2a).\" Reference 38 states “This single field calibration derived from the Mason-Schamp equation is analyte and charge state independent, meaning it can be used for any sample as long as both tune mix and analyte ions are acquired under the same experimental settings.” The low interlaboratory RSDs reported in reference 38 for single field calibrations were achieved for the tuning mix. Even with the interlaboratory RSD of the tuning mix (0.38 ± 0.19% in Ref 38) it would be very challenging to distinguish isomers 3 and 5. I can imagine that a glycan-based calibration mixture may achieve similar interlaboratory RSDs, however, this remains to be proven.\nOn the same note, there are CCS errors given for all library entries. I assume, they are derived from repflicates. I would recommend to add 1-2 sentences on the errors and overall reproducibility as this information is already available.\nFor the Leb Fragment F10, 2 CCS values are reported with a relatively high CCS difference, while there is only one CCS value for all other fragments. Does the second peak possibly arise due to fucose migration or do the authors have any idea why this only appears for this specific structure?\nOn page 14 figure 5a structure 55 : There is probably a typo in the CCS value of the last ion in the ATD. If 34.5 ms equals 460 A², 37 ms should be rather 487 A² instead of 187 A².\nI would recommend to revisit and harmonize the reference list. Sometimes the whole author list is given and sometimes et al. is used for more than 3 authors. There is information missing for reference 11. The author names in reference 57 are partially misspelled.\nI would recommend to check the Supplementary Datasets again. There are some minor errors like in dataset 3, the N-glycans with the m/z 1130 and 1152 have the same structures and are both [M+H]+. I assume 1152 is the sodium adduct. The second m/z 877 is said to be a BY fragment but the SNFG structure shows an intact structure and not a fragment."}, "author_response": "We thank the reviewers for the thorough examination of our paper and suggestions for improvement. We have addressed all issues and details are provided below.\nReviewer 1\nThis interesting manuscript describes very detailed MS/MS and IMS analysis by a highly experienced MS group, trying to provide a solution to resolving of glycan structural diversity by ion mobility mass spectrometry. The authors characterised the glycans by figuring out the CCS values of key diagnostic fragments of the various glycans, and uses them to build a library that can be expanded across various types of glycans that can contain these diagnostic ions/features to provide high throughput characterisation of glycans.\nRemark: This is a massive amount of foundational work that the field will greatly appreciate if made widely available, or at the very least, other groups start to follow suit with the deeper level of glycan structural feature characterisation that is beyond glycan composition. Particularly, since these fragment ions should, to some extent, be observable in glycopeptide spectrums if acquired with appropriate fragmentation methods. Below are comments that require additional information or clarification:\nResponse: We thank the reviewer for recognizing our research as a fundamental and impactful contribution to the glycoscience field, and for highlighting the value of our solution for addressing glycan structural diversity using IM-MS. The methodology holds great potential for broader application, such as in glycopeptide analysis, and can be adopted by other research groups aiming to achieve in-depth glycan structural characterization.\nRemark: This method is reliant on the CCS of MS2 fragments from in source fragmentation/activation. Please elaborate on how transferable this instrument (Agilent) requirement/setting will be for other ion mobility instruments, such as Bruker’s TimsTOF, or Waters TWIMS for the broader audience.\nResponse: The acquisition of glycan fragment ions is largely transferable, as diagnostic B- and Y-type fragments are reproducibly observed across instruments and CID fragmentation modes, although their relative abundances can vary depending on activation conditions and instrument settings. Their CCS values are an intrinsic molecular property that can be applied across various ion mobility spectrometry (IMS) platforms. However, CCS values may slightly vary depending on the employed instrument type. Exchangeable CCS data can, however, be achieved by proper calibration. In both TWIMS and TIMS measurements, CCS calibration is generally performed using standards with known CCS values determined by DTIMS. As a result, similar CCS values are to be expected for analytes across these platforms. In addition, N-glycan CCS values are not affected by differences in ion energies, such as those that may arise between different instruments. For example, sialyl-LacNAc fragment ions measured after activation using TWIMS (Hinneburg et al., 2016 and Feng et al. 2021) exhibited CCS values comparable to those obtained with our DTIMS instrument with deviations ranging from 1.1-1.4%. Therefore, the database will largely be applicable across different ion mobility instrument configurations. To elaborate on this, we have revised the following text: “Isomeric glycan structures and fragments can be separated by different types of IM-MS instruments, such as those with travelling wave (TWIMS), trapped (TIMS) and DTIMS59,60,61,62. The application of CID-IM-MS across the different platforms produces consistent fragment ions, although relative ion abundances may vary depending on activation conditions and instrument parameters63. Their CCS values are intrinsic molecular properties applicable across various IM-MS instruments, although CCS values may slightly vary depending on the employed instrument type. Highly comparable CCS values can be obtained, however, between different platforms by using standardized procedures64,65,66. For example, the permethylated HMOs LNT and LNnT showed comparable CCS values (within 0.7%) on TIMS and DTIMS instruments67. Similarly, sialyl-LacNAc fragment ions, obtained after activation and analyzed by TWIMS68,69, yielded CCS values within 1.4% of F3 and F4 measured with DTIMS in this study (Fig. 2b). Thus, it is the expectation that the de-novo sequencing approach can be employed across different instrument setups. However, due to inter-instrument variability, proper validation using a limited set of glycan standards is necessary to ensure the reproducibility of the approach.\nRemark: The error range for the CCS values of some of the fragments drawn in fig 2 is narrower than what can be seen on the spreadsheets in the supplementary. Such as fragment F3 is specified as 232.6 +- 0.1 A, but in the supplementary table CCS values of F3 was reported from 232.3 to 233.2.\nResponse: The reported variations reflects both intra-day consistency within single runs and inter-day differences across separate measurement sessions. Consequently, the values reported in Supplementary Dataset 1 for F3 (232.6±0.1, n = 3; measured within a single run) and those for the standard in Supplementary Dataset 3 are identical to the data shown in Fig. 2. In contrast, the average and precision of measurements in milk samples (232.7±0.2, n = 22; measured on different days; see Supplementary Dataset 3), show only slight variations, reflecting expected day-to-day variability.\nRemark: Also fig 2, and various supplementary spectrums, the 657 sialyl-lacNAc and 658 lewisb/y can be within the same isotopic envelope. With some of the supplementary spectrums, supp fig 35, where both are theoretically present and have very similar CCS values of 232.5 and 232.6, please explain how the library that is built can cope with this or is manual curation is still required.\nResponse: The signals of sialyl-LacNAc at m/z 657 and Leb/Ley at m/z 658 have indeed partially overlapping isotopic envelopes. This can be visualized in a heatmap with m/z vs. drift time data and the signal intensity. It shows the presence of both fragments with a different isotopic envelope. The different envelopes can be filtered based on their distinct drift times to obtain individual isotopic envelopes. Molecular feature finding options in IM-MS software detect these separate signals as two different molecular features. When drift times are too close, it becomes more difficult for the software to distinguish two compounds and manual curation is required. For clarification, we modified the following text in the manuscript on page 9:\n“In step 2 and 3, the fragments at m/z 657 and 658 showed overlapping isotope distributions that were filtered based on their distinct drift times to obtain individual isotopic envelopes. The fragments were identified as F3 and F11 (Fig. 2b), respectively, based on their m/z and CCS values.”\nRemark: More information should be provided for the MS data processing and library building.\nResponse: We have revised the data processing section and included library building: “Masses of raw 4 bit multiplexed DTIMS-MS data were recalibrated on reference masses with m/z 121 and m/z 922 using the DTIMS-MS Data File Reprocessing Utility in the Agilent Technologies MassHunter software (v10.0). Reprocessed data was demultiplexed using the PNNL Preprocessor software v4.0 (Pacific Northwest National Laboratory, Richland WA) using an interpolation of 3 drift bins and a 5 point moving average smoothing in the DTIMS dimension69. Features were identified with the Agilent Technologies MassHunter IMS Browser software v10.0 using an unbiased isotope model. The feature list was used to obtain high-resolution ATDs using Agilent Technologies HRdm v2.0 software with an m/z width multiplier of 12, saturation check of 0.40 and an IF multiplier of 1.125 with SSS and Post QC enabled70. CCS values of the ions were calculated from their IMS arrival times using single field CCS calibration employing a standard tuning mixture with known m/z and CCS values41.\nFor the reference database, data obtained for the reference standards (Fig. 2a and 2b) were organized into columns in a spreadsheet and included the following information: the theoretical m/z of the intact glycan ion or fragment ion, the ion structure, the CCS value, the type of adduct ion, and for fragment ions, the fragment ion type and the structure of the parent compound. A remarks column indicated the origin of the ion which, in the case of the reference standards, was a synthetic standard.\nThese entries were used to manually identify novel structures in biological samples that were not yet present in the database. The unknown structures were first fragmented, then the compositions of the resulting ions were determined based on their m/z, and finally the structures were identified based on their CCS values. This information was then used to reconstruct and identify the full glycan structures. Each newly identified structure generated additional fragment and intact ion entries, which were incorporated into the spreadsheet along with their corresponding biological origin. These new entries, in turn, enabled the identification of further structures in biological samples, creating a continuously expanding dataset with each new measurement.\nThe reference database (https://www.uu.nl/en/research/chemical-biology-and-drug-discovery/glycan-database; Supplementary Data 3) will continue to be extended and refined. Contributions from external data sources are welcome and encouraged.”\nRemark: What is the definition of “self-expanding database”?\nResponse: The m/z, ATD, and CCS values of the elucidated intact and fragment ions can be incorporated into a reference database to enable rapid identification in other samples or assist in the de novo sequencing of larger and more complex structures. This approach establishes a self-expanding reference database that leverages only previously characterized entries. To clarify the meaning of self-expanding database, we moved the term “self-expanding database” forward in the text and placed it before the definition: “The m/z, ATD, and CCS values of the elucidated intact and fragment ions can be added to the reference database for rapid identification in other samples or for the de novo sequencing of larger and more complex structures (Fig. 1), creating a self-expanding reference database. Thus, the IM-MS methodology continuously exploits data from previous analyses of biological samples to elucidate new glycan structures while at the same time expanding the reference database. We demonstrate here that by applying data of 12 glyco-epitope fragment ions in this iterative process, the reference database could be expanded to 332 entries.”\nRemark: It is acknowledged that the self-expanding database can be extended to O- glycans, GSLs but how is this to be achieved? i.e. There is room for expansion of the database after these 332 unique entries – will the database be maintained and able to accept external updates?\nResponse: The database, which is currently in a spreadsheet format, will be maintained and extended, including with external updates. The following text was included in the methods section:\n“The reference database (https://www.uu.nl/en/research/chemical-biology-and-drug-discovery/glycan-database; Supplementary Data 3) will continue to be extended and refined. Contributions from external data sources are welcome and encouraged.”\nRemark: In addition, the database can be extended to other glycan classes as many structures, that have different core structures, but sharing the same terminal epitopes, such as HMOs, O-glycans and GSLs.\nResponse: To elaborate, we have refined the following text in the discussion section: “It is the expectation that the methodology can be extended to other classes of glycans and glycoconjugates. For example, there are 8 common O-linked glycoprotein cores, some of which are isomeric. It is the expectation that the use of a limited number of synthetic standards can provide CCS values of diagnostic fragment ions to identify core type. Furthermore, the various classes of glycosphingolipids have also isomeric core structures that are expected to be distinguishable based on CCS values of fragment ions obtained using a limited number of standards. O-glycans and glycosphingolipids have extensions like those of HMOs, and thus the current database will make it possible to establish structural elements of these compound classes. To address potential sequencing challenges and obstacles in the de novo sequencing workflow, such as those arising from missing fragment data in the database, the strategy will prioritize the synthesis of specific target structures rather than complete glycan class libraries.”\nRemark: Please share the glycan data on GlycoPost (https://glycopost.glycosmos.org/) instead of MassIVE, as glycopost is designed for glycomics data types.\nResponse: The data has been shared on Glycopost with identifier GPST000611 (http://doi.org/10.50821/GLYCOPOST-GPST000611). The text reference was changed in the data availability section of the manuscript and in the reporting summary.\nMinor comments\n1) Considering the current diversity of sialic acid linkages, and the synthesis capabilities shown in this manuscript, perhaps include a2,6sia-b1,3gal to finish the 2,3 2,6 sia with 1,3 1,4 gal combinations?\nResponse: The strength of the de novo methodology lies in the ability to elucidate structures in biological samples without the need to synthesize every reference compound. HMOs with an a2,6Neu5Ac-b1,3Gal are naturally not occurring and therefore a standard was not included in the library. However, in the unlikely event that such a compound would be detected in a biological sample, it could most likely be identified when CCS values of the intact structure and the fragments do not match the current database entries.\n2) For a number of supplementary spectrums (eg. supp F79, 80, 81), the sodiated adduct peak looks non-existent.\nResponse: The sodiated adduct peaks are present in the spectra, however, due to the current zoom level and the presence of other peaks with significantly higher intensities, the sodiated peaks are not clearly visible in the displayed figures. In the raw data, these adducts are consistently detected with ion counts in the range of 10⁴–10⁵, confirming their presence. For clarity, these peaks have been labeled in the figures in the Supplementary Information.\n3) Pg 13, “Bis-sialylated”. Please use di- or bi-sialylated. Di-sialylated is preferred as “Bis” in glyco usually refers to “bisecting”.\nResponse: The sentence was changed into: “It made it possible to identify isomeric di-sialylated N-glycans having different combinations of 2,3- and 2,6-linked sialosides.”\n4) There are a number of acquisition types described in the methods, infusion-MS, HILIC-MS, PGC-MS. Please specify them in their respective figure legends.\nResponse: We have modified the caption of Fig. 2a into: “Structures, theoretical m/z values (as [M+H]+ ions) and measured DTCCS values (n=3 measurements) of synthetic HMO standards, N2 derivatized with procainamide (ProcA) at their reducing end by reductive amination, and measured with HILIC-IM-MS.”. We also changed the caption of Fig. 2b into: “B-type glyco-epitope fragments (as oxonium ions) of the standards measured with HILIC-IM-MS, m/z and DTCCS values (n=3 measurements).”, and of Fig 2c into: “ATD of the linear HMO α6-N2 sialyllacto-N-tetraose c (obtained with PGC LC-IM-MS analysis from human milk donor 1; n=1 measurement) and its fragment ions with their measured m/z and CCS values (as [M+H]+ or oxonium ions).“\nFor Fig. 3a we have changed the caption into: ”Linear extended structures (20-21 as [M+H]+ fragment ions of 51 and 52, Table 1; measured with PGC LC-IM-MS) give complementary Y-type fragment F20 (as [M+H]+ ion) and B-type fragments (F22 and F23 as oxonium ions) upon CID, that can be employed to determine the chain type.”, “When the complementary fragment ions are not present in the mass spectrum, the structure is I-branched (22 and 23, Table 1; as [M+H+]+ ion, measured with PGC LC-IM-MS). I-branched structures produce isomeric fragment ions F24 and 2 for type I (22), and F24 and 1 for type II structures (23).” and “The isotopically labeled type II structure 24 (as [M+H]+ ion, n=3 measurements, measured with HILIC-IM-MS) produces isotopologues 2 and F25 (as [M+H]+) ions.”\nFor Fig.4 we have changed the caption into: “De novo sequencing cycle of an I-branched structure derived from human milk (n=1 measurement with PGC LC-IM-MS).”\nFor table 1 we have changed the caption into “De novo identified HMO structures in the milk samples of donors 1-5, obtained with PGC LC-IM-MS.”\nFor Fig. 5 we have changed the caption into: “ATD fingerprinting identification and de novo sequencing of glycans derived from biological samples with PGC LC-IM-MS”.\n5) Please reference past efforts in CCS database building like https://doi.org/10.1021/acs.analchem.9b01476 and GlycoMob https://link.springer.com/article/10.1007/s10719-015-9613-7\nResponse: We have added the references Struwe et al. (2016), Wongtrakul-Kish (2022), Glaskin et al (2017), and Manabe et. al. (2022) to the following text in the introduction: “To make ion mobility (IM)-MS suitable for glycan structure determination, databases are needed that can correlate mass-to-charge ratios (m/z), ATDs and CCS values to isomeric glycan structures19, 21, 22, 23.”\nReviewer 2\nThe manuscript by Torano and colleagues describe how to use IM-MS, a modern mass spectrometric technique, to manually determine isomeric glycan structures. Based on a small database containing 20 typical carbohydrate epitopes (peripheral sequence or determinants) synthesized by the authors specifically for this work, the authors established some important principles to deduce many more complex glycan structures.\nMethods for determination of isomeric glycan sequences based on mass spectral fragmentation patterns, such as multi-stage MS (MSn, N>2) have been well advanced.\nSince its development and application some 15 years ago, IMS has become an important part of MS-based strategies for sequencing isomeric glycans. To include the two important IMS parameters (CCS and ATD), in addition to m/z, for determining and deducing isomeric sequences is obviously more advantageous as has been recently demonstrated by many published works including those by the authors (e.g. Ref 27 of this manuscript and Agilent Application Note “Exact Structure Identification of Isomeric N-Glycans by High-Resolution Ion Mobility LC/Q-TOF”).\nResponse: We thank the reviewer for the thoughtful evaluation of our manuscript highlighting the establishment of important principles for the elucidation of complex glycan structures. The combination of CCS, ATD and m/z for glycan identification is indeed very valuable for the accurate determination of structures and is expected to find wide applicability in glycoscience.\nRemark: This reviewer is not convinced the use of the term “de novo” for the method developed in this work, as establishing fragmentation principles before their use for piecing together the fragmented MS information to determine an unknown glycan sequence are the norm in carbohydrate mass spectrometry. To this reviewer’s limited knowledge, “de novo” sequencing often refers to a method with the ability of deducing the sequence without relying on reference database and conventionally carried out by computer software.\nResponse: We respectfully disagree regarding the use of the term de novo. The term de novo can have different interpretations depending on the field of research. The term is, however, not a critical point in our manuscript and, if needed, we are happy to adjust the wording in the text to avoid potential confusion.\nIn the context of this paper, de novo identification refers to the elucidation of unknown glycan structures directly from experimental IM-MS data, without relying on databases of these structures.. Importantly, de novo does not mean interpretation occurs without any prior chemical knowledge, but rather without prior knowledge of the specific analyte sequence. In our approach, we interpret IM-MS/MS spectra to deduce monosaccharide composition, linkage, and branching, and we reconstruct glycan structures. As with early peptide MS workflows, this is currently done manually, but we agree that automated software will be essential as data volume increases.\nRemark: There have been many works on software tools for computer-assisted automated or semi-automated glycan identification. For example, the sophisticated computational de novo algorithm described by Lapadula et al (Anal Chem 2005) based on MSn (m/z values of molecular and fragment ions and the connectivity of each structural fragment) can provide molecular topology without presumed biosynthetic constraints or external comparisons. Predicting glycan structure by de novo glycan annotation after deep learning and training on a large set of annotated MS/MS spectra from LC-MS/MS analysis is possible as has recently been demonstrated (Urban et al., Nat Methods 2024). However, at present the establishment of the fragmentation patterns and use of these unique and complex principles for detailed interpretation of naturally derived glycans still rely mainly on experienced carbohydrate chemists/biochemists such as the work presented in this manuscript. The lack of robust, dependable, and freely available software for automatic annotation of mass spectra is still a severe bottleneck that hampers their rapid interpretation.\nResponse: We thank the reviewer for the comment. We agree that despite advances in computational tools, such as the algorithm by Lapadula et al. and the deep learning-based approaches of Urban et al., the interpretation of MS/MS spectra still relies on manual analysis by experienced carbohydrate chemists. We appreciate the reviewer highlighting the role of large annotated datasets in addressing this challenge. It is our expectation that the annotated MS/MS spectra and associated CCS values presented in our study will contribute to the development and training of AI-driven tools for automated glycan annotation. We aim to engage in such efforts to help facilitate a transition toward more automated and scalable glycomics workflows.\nRemark: This reviewer considers the work presented in this manuscript does not represent an important advance to the field of glycochemistry/glycobiology and lacks sufficient novelty.\nResponse: We respectfully disagree with the referee. The importance of this paper is described in the last paragraph of the introduction and is highlighted in Figure 1. Previously, it has been demonstrated that IM-MS can distinguish isomeric glycan structures. To exploit this capability to determine glycan structures in biological samples, it is important to develop a database that can correlate mass-to-charge ratios (m/z) and CCS values to isomeric glycan structures. In principle, such a database can be developed by synthesizing reference glycans and establish CCS values of isomeric compounds. A major limitation of such an approach is that it is too laborious to prepare every possible glycan structure. This paper describes a method that addresses this problem. In our approach, a limited number of glycan standards is subjected to in-source collision-induced dissociation (CID) to produce informative intact and fragment ions for an initial IM-MS reference database. Next, glycans obtained from a biological source can be subjected to IM-MS and rapid identification can be made for those compounds that have an entry (m/z and ATD or CCS values) of the intact ion in the reference database. Compounds that do not have an entry are subjected to CAD and de novo sequencing by identifying structures of fragment ions that can be puzzled together, leveraging the established biosynthesis pathways, to elucidate the glycan structure. This approach moves beyond compositional profiling and determine glycan structures, which is a major goal in glycochemistry and glycobiology, as highlighted by reviewer 1: “This is a massive amount of foundational work that the field will greatly appreciate if made widely available, or at the very least, other groups start to follow suit with the deeper level of glycan structural feature characterisation that is beyond glycan composition”. Furthermore, our approach is not limited to a single glycan class. We demonstrate the versatility by applying it to both HMOs and N-glycans, each with distinct structural complexity. We show that once fragment CCS values are known, de novo annotation of unknown glycans becomes feasible without the need for synthetic standards, which facilitates structural glycomics and, as reviewer 3 noted, “provides substantial value to the glycoscience community”.\nOur manuscript thus offers conceptual and technical novelties"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have addressed all our comments satisfactorily such that the paper can be accepted.\nCurrently the link to their database is not yet active, which I assume will be when the paper is accepted.", "reviewer_2": "The authors have addressed my concerns appropriately.No further questions,", "reviewer_3": "The authors have addressed all concerns raised during the reviewing process and the manuscript is ready for publication now."}, "author_response": ""}]

Decision letter