# Top-Down and Middle-Down Mass Spectrometry of Antibodies

Nina A Khristenko, Konstantin O Nagornov, Camille Garcia, Natalia Gasilova, Megan Gant, Karen Druart, Anton N Kozhinov, Laure Menin, Julia Chamot-Rooke, Yury O Tsybin

► To cite this version:

Nina A Khristenko, Konstantin O Nagornov, Camille Garcia, Natalia Gasilova, Megan Gant, et al. Top-Down and Middle-Down Mass Spectrometry of Antibodies. Molecular and Cellular Proteomics, 2025, 24 (7), pp.100989. 10.1016/j.mcpro.2025.100989. pasteur-05086437

HAL Id: pasteur-05086437

https://pasteur.hal.science/pasteur-05086437v1

Submitted on 27 May 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Top-Down and Middle-Down Mass Spectrometry of Antibodies

## Authors

Nina A. Khristenko, Konstantin O. Nagornov, Camille Garcia, Natalia Gasilova, Megan Gant, Karen Druart, Anton N. Kozhinov, Laure Menin, Julia Chamot-Rooke, and Yury O. Tsybin

## Correspondence

tsybin@spectroswiss.ch

## In Brief

This review traces 3 decades of advancements in top-down and middle-down mass spectrometry (TD/MD MS) for antibody characterization. It highlights key technological and methodological developments enabling detailed analysis of intact antibodies and subunits, including sequence coverage, post-translational modifications, and structural heterogeneity. The review also explores emerging trends in instrumentation, data analysis, and applications to novel antibody formats, making TD/MD MS a powerful and evolving platform for therapeutic antibody analysis.

## Graphical Abstract

<figure><img src="image_2.png" /></figure>

## Highlights

* Reviews 30 years of top-down and middle-down MS for antibody analysis.

* Highlights advances in instrumentation and ion activation techniques.

* Emphasizes improvements in sequence coverage and PTM characterization.

* Discusses TD/MD MS applications to IgG and novel antibody formats, including ADCs.

* Covers recent trends in sample preparation, data acquisition, and analysis workflows.
# Top-Down and Middle-Down Mass Spectrometry of Antibodies

Nina A. Khristenko¹, Konstantin O. Nagornov², Camille Garcia³ ID, Natalia Gasilova⁴, Megan Gant³, Karen Druart³, Anton N. Kozhinov², Laure Menin⁴, Julia Chamot-Rooke³ ID, and Yury O. Tsybin¹,²,* ID

Therapeutic antibodies, primarily immunoglobulin G-based monoclonal antibodies, are developed to treat cancer, autoimmune disorders, and infectious diseases. Their large size, structural complexity, and heterogeneity pose significant analytical challenges, requiring advanced characterization techniques. This review traces the 30-year evolution of top-down (TD) and middle-down (MD) mass spectrometry (MS) for antibody analysis, beginning with their initial applications and highlighting key advances and challenges throughout this period. TD MS allows for the analysis of intact antibodies, and MD MS performs analysis of the antibody subunits, even in complex biological samples. Both approaches preserve critical quality attributes such as sequence integrity, post-translational modifications (PTMs), disulfide bonds, and glycosylation patterns. Key milestones in TD and MD MS of antibodies include the use of structure-specific enzymes for subunit generation, the implementation of high-resolution mass spectrometers, and the adoption of non-ergodic ion activation methods such as electron transfer dissociation (ETD), electron capture dissociation (ECD), ultraviolet photodissociation (UVPD), and matrix-assisted laser desorption/ionization in-source decay (MALDI-ISD). The combination of complementary dissociation methods and consecutive ion activation approaches has further enhanced TD/MD MS performance. The current TD MS record of antibody sequencing with terminal product ions is about 60% sequence coverage obtained using the activated ion-ETD approach on a high-resolution MS platform. Current MD MS analyses with about 95% sequence coverage were achieved using combinations of ion activation and dissociation techniques. The review explores TD and MD MS analysis of novel mAb modalities, including antibody-drug conjugates, bispecific antibodies, endogenous antibodies from biofluids, and immunoglobulin A and M-type classes.

Therapeutic antibodies (Abs), primarily immunoglobulin G (IgG)-based monoclonal antibodies (mAbs), are engineered to target specific molecules or cells to treat diseases such as

cancer, autoimmune disorders, and infectious (1-4). IgG-based Abs are classified into four subclasses: IgG1, IgG2, IgG3, and IgG4 (5). Their diversity arises from variations in amino acid sequences, disulfide bond connectivity, post-translational modifications (PTMs), and glycosylation patterns, all of which influence structure, stability, efficacy, and pharmacokinetics (6, 7). Beyond mAbs, antibody-drug conjugates (ADCs) (8) and engineered antibodies, including bispecific antibodies (BsAbs) (9), nanobodies, and single-chain antibodies, are expanding therapeutic possibilities (10, 11). Emerging Ab types, including IgA and IgM, are being investigated for their role in mucosal immunity and complement activation (5). This review will primarily focus on the analysis of IgG1 mAbs, while also addressing various other antibody modalities, Figure 1.

Structural analysis of IgG-based mAbs is essential for ensuring their quality and efficacy (1). They are complex glycoproteins of about ~150 kDa molecular weight (MW) that consist of two identical heavy (Hc) and two light chains (Lc) linked by disulfide bonds, forming a Y-shaped structure (Fig. 1). Beyond the arrangement of their chains, mAbs are defined by two distinct functional regions: the Fab (antigen-binding fragment) and the Fc (crystallizable fragment), Figure 2. The Fab region contains the hypervariable complementarity-determining regions (CDRs), which are responsible for antigen recognition, whereas the Fc region mediates immune effector functions. A short, flexible peptide segment known as the hinge region allows movement and spatial rearrangement of the Fab arms relative to the Fc region. Comprehensive structural characterization of mAbs involves primary structure analysis (amino acid sequencing), N- and O-glycosylation profiling, disulfide bond connectivity, and qualitative and quantitative assessment of post-translational modifications (PTMs). Among the most prevalent PTMs are N-terminal pyroglutamic acid formation (pyroQ), C-terminal amino acid truncation (e.g., Lys residue loss), deamidation, oxidation, glycation, phosphorylation, and isomerization. Assessing these

From the ¹Spectrotech SAS, Lyon, France; ²Spectroswiss Sarl, Lausanne, Switzerland; ³Institut Pasteur, Université Paris Cité, and CNRS UAR2024, Paris, France; ⁴Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

*For correspondence: Yury O. Tsybin, tsybin@spectroswiss.ch.
<figure><img src="image_3.png" /><figcaption>FIG. 1. Schematic overview of the different immunoglobulin (Ig) structures that have been studied with TD/MD MS: IgG1-4, IgA1, and IgM monomer. These Ig structures differ in disulfide bond connectivity and glycosylation sites and type. Red marks represent disulfide bonds and yellow marks indicate N-glycosylation sites. The IgG2-4 subclasses differ in the sequence of the heavy chain's hinge region domains.</figcaption></figure>

modifications is important as the most subtle change (such as deamidation, for instance) can alter the structure and function of mAbs, thereby affecting stability, activity, and immunogenicity. However, determining critical quality attributes (CQAs) of mAbs with high precision remains a significant analytical challenge (4).

Mass spectrometry (MS) has revolutionized the field of mAb characterization by offering high sensitivity, precision, and structural insights (12). Today, the MS approaches employed for mAb analysis include: intact and subunit (middle-up) mass analysis, top-down (TD) and middle-down (MD) MS, and bottom-up MS analysis (4, 7). Oftentimes, several of these

<figure><img src="image_4.png" /><figcaption>FIG. 2. Monoclonal antibody structural organization shown on the example of a NIST mAb. The structural components of the NIST mAb are depicted, showing the light chain (Lc), the heavy chain (Hc), the N-terminal part of the heavy chain (Fd), and the C-terminal part of the heavy chain (Fc/2) subunits, along with the Fab region and highlighted CDRs (137). Intra- and inter-chain disulfide bonds are marked in red. The expanded views outline the following structural features: (i) CDR3 of the heavy chain, (ii) the hinge region with cleavage sites for the IdeS and KGP enzymes, (iii) the N-terminus of the heavy chain modified with a pyroglutamate, (iv) the C-terminus of the heavy chain that is prone to the loss of Lys residue, and (v) the NST glycosylation sites on asparagine residues in the Fc region (yellow sticks) with complex N-linked glycans.</figcaption></figure>

<figure><img src="image_5.png" /></figure>
approaches are used in concert to deliver the most compre-
hensive structural analysis. Bottom-up MS relies on proteo-
lytic digestion(s) to generate peptides for subsequent tandem
(MS/MS) analysis and is the cornerstone approach for prote-
omics. However, while it is effective for identifying and
quantifying peptides and PTMs, bottom-up MS has several
key limitations (13, 14). Some PTMs may be under-
represented or missed entirely in the bottom-up MS anal-
ysis. The approach also results in a loss of connectivity
information such as disulfide bond linkages, which must be
inferred from separate experiments. Sample preparation can
introduce artifacts such as oxidation or deamidation, while
quantification at the peptide level remains indirect and is often
affected by ionization biases, as well as the presence of
numerous enzymatically derived modified and unmodified
peptides that share the same modification site. Critically,
bottom-up MS cannot resolve intact proteoforms, meaning it
cannot determine how PTMs or sequence variants co-occur
on the same molecule, thereby missing crucial information
about the diversity of the mAb population (10, 15).

To address these limitations, TD and MD MS methods are employed (13, 16). TD MS relies on the MS/MS analysis of intact proteins without prior digestion. In turn, MD MS is based on the gas phase fragmentation of antibody subunits, primarily in the 25 to 100 kDa mass range, and offers a balance between the high-level structural insights gained from intact protein MS/MS analysis and the more detailed sequence and PTMs information typically obtained from peptide-based bottom-up MS (17, 18). Two main approaches, used either independently or in combination, are used to generate mAb subunits for MD MS: disulfide bond reduction and digestion with structure-specific enzymes. The former one, S-S bond reduction, is limited to the generation of a 25 kDa Lc and a 50 kDa Hc for IgG1 mAb. The Hc is more complex than the Lc to analyze, not only because it is twice as larger but also because it is usually N-glycosylated and carries other common PTMs such as C-terminal clipping.

The breakthrough that led to a drastic improvement in MD
MS performance came with the development of structure-
specific and highly efficient enzymes that offered Hc cleav-
age in the hinge region. Initially, the immunoglobulin
G-degrading enzyme of *Streptococcus pyogenes* (IdeS) (19,
20) was used to cleave IgG below the hinge region, and the
cysteine protease Gingipain K (KGP) was used to cleave IgG1
above the hinge region, Figure 2 (21). Later, other enzymes
with similar or comparable specificity and improved ease of
use have been added, e.g., IgdE (22), SpeB (23), Bdpk (Fab-
DELLO) (24), and IdeZ. Combined with disulfide bond reduc-
tion, these structure-specific enzymes generate ~25 kDa mAb
subunits: the Lc, the N-terminal part of the Hc (Fd or Fd',
where the prime symbol (') indicates inclusion of the hinge
region), and the C-terminal part of the Hc (Fc/2), Figure 2. The
MS/MS analyses of 25 kDa subunits are simplified by the
isotopically resolved subunit intact mass (middle-up)

measurements, fragmentation efficiency of individually iso-
lated charge states of precursor ions, product ion detection,
and facilitated data analysis (25). Moreover, such enzymes
demonstrate negligible artifact introduction upon sample
preparation (26).

Since the pioneering TD MS analysis of an intact mAb in 1993 (27), MS techniques for antibody analysis have evolved significantly (17, 26). Researchers have achieved enhanced antibody structure characterization with the development of high-resolution Orbitrap Fourier transform mass spectrometry (FTMS) and advancements in time-of-flight (TOF) and FT ion cyclotron resonance (FT-ICR) MS. Introduction and application of the non-ergodic ion activation methods such as electron capture dissociation (ECD), electron transfer dissociation (ETD), matrix-assisted laser desorption/ionization in-source decay (MALDI-ISD), and ultraviolet photodissociation (UVPD) have enhanced the capabilities of TD and MD MS (28), enabling improved sequencing and detailed analysis of glycosylated regions and other challenging structural features (17, 26).

Advancements in the structural analysis of mAbs have been
driven by collaborations between academic researchers and
leaders in the biopharmaceutical industry. Notably, pioneering
work in TD/MD of mAbs was initiated and supported by Beck's
group at Pierre Fabre Laboratories in France and Zhang's group
at Amgen in the United States. Other companies, including
AbbVie, GSK, Roche Diagnostics, and Sanofi, later joined them.
These biopharmaceutical industrial research groups continue to
drive innovation in antibody TD and MD MS analysis by con-
ducting their own research and fueling academic efforts with
challenging samples and critical questions (4).

The ultimate goal of TD and MD MS antibody analysis, as
seen today, is to achieve: (i) 100% sequence coverage,
meaning cleavage of protein backbone bonds between each
pair of amino acids, with detection of at least one corre-
sponding product ion, including the distinction between
isoleucine and leucine; (ii) comprehensive identification of
common PTMs, such as deamidation, disulfide bond locali-
zation, N- and C-terminal modifications, oxidation, and
glycosylation; (iii) accurate site-specific PTM localization
within the antibody sequence; and (iv) relative quantification of
proteoforms. These objectives are interconnected, as
achieving complete sequence coverage is essential for ac-
curate PTM identification and localization. However, no TD/
MD MS study has reported complete sequence coverage of
an antibody, even for the well-characterized IgG1 subclass.
Identifying and localizing PTMs remains an ongoing challenge,
particularly for other Ig classes with more complex modifica-
tions and inter- and intra-chain connectivity (Fig. 1). In bio-
pharmaceutical studies, where the antibody sequences are
known, the focus shifts to confirming CDR sequences and
profiling proteoforms for major modifications.

This review offers a comprehensive overview of peer-
reviewed publications describing TD and MD MS for mAbs
and derived species, such as ADCs, from early studies to the latest advancements. It highlights the current advances and limitations in Ab analysis and ongoing progress. Specifically, the review emphasizes how TD/MD MS techniques constantly adapt to address the heterogeneity of Abs, including PTMs such as glycosylation. Furthermore, the review considers the application of TD/MD MS to novel antibody formats, such as ADCs, BsAbs, IgA, and IgM.

TOP-DOWN MS OF ANTIBODIES: METHOD DEVELOPMENT

Table 1 and Figures 3–5 summarize the advancements in mAbs sequence coverage achieved through diverse TD MS approaches reported over the past 30 years. In the following sections, references to entries in the tables will be indicated by the corresponding row number (e.g., row #1.1 or simply #1.1).

Collision-Induced Dissociation (CID) TD MS

The first instance of TD MS applied to an intact mAb occurred 30 years ago (27). In this original study, Feng and Konishi attempted to gain structural information on a mAb with a triple quadrupole mass spectrometer (QQQ MS). They applied an all-ion collision-induced dissociation (CID) to fragment the intact 150 kDa species, followed by product ion detection. However, the obtained structural information was limited (#1.1 in Table 1), demonstrating the need for more advanced MS instrumentation. Significant developments in CID-based TD MS occurred 14 years later with the advent of high-resolution Orbitrap and TOF mass spectrometers, which became available in biopharmaceutical industrial laboratories.

In 2007, Zhang and Shah employed the in-source CID (isCID) fragmentation of all charge states of a mAb on a legacy LTQ Orbitrap (Thermo Fisher Scientific) to yield *b*/*y* product ions covering the terminal 100 to 120 residues of the Lc and Hc (29). Although an intact mAb was introduced into the mass spectrometer's ion source, no precursor ion selection was carried out. Nevertheless, backbone cleavage events between the variable and constant domains led to the formation of *b*-type ions that retained the entire variable domain, enabling its characterization through the resulting product ions. These large *b*-ions were then submitted for MS/MS with CID in the linear ion trap (LTQ) for deep sequencing (the MS³ level or a pseudo-MS³ level, as there was no precursor ion isolation in the isCID event). The method was applied to analyze mAbs after forced oxidation with tert-butyl hydroperoxide, which successfully localized the oxidized methionine residue. In these experiments, weak backbone bonds were mostly cleaved, resulting in sequence coverage that did not exceed 10% (#1.2 in Table 1, Figs. 3 and 4). Two years later, in 2009, Zhang's group, in collaboration with Thermo Fisher Scientific, extended this experimental approach to an IgG2 mAb, yielding similar results (#1.3 in Table 1, Figs. 3, and 4) (30).

Electron Transfer Dissociation (ETD) TD MS

Introducing electron transfer dissociation (ETD) on high-resolution mass spectrometers was a breakthrough in TD MS analysis of intact mAbs. In 2011, the first TD MS application of ETD for the analysis of intact 150 kDa mAbs was performed using a high-resolution TOF MS (maXis Q-TOF MS, Bruker Daltonics) in a collaborative effort between Tsybin's group and Bruker Daltonics (31). They analyzed intact IgG1 species from murine myeloma cells and human anti-Rhesus D IgG1 species, including *via* isolation of precursor ions before ion activation and dissociation. Fragmentation of several isolated charge states of intact mAb species resulted in a sequence coverage of up to 20% for both Lc and Hc (#1.4 in Table 1, Figs. 3, and 4). Fragmentation patterns revealed mAb structural influences on the MS/MS efficiency: While several sites demonstrated enhanced propensity to the backbone cleavage, the S-S bond-protected regions were rarely sequenced. An expected increase in the baseline around the abundant remaining charge-reduced precursor ions (presumably, non-covalently bound electron transfer product ions, *i.e.*, ETnoD species (32)), along with overlapping product ions, was also responsible for limited sequence coverage.

To minimize baseline elevation around intense ion signals, caused by peak interference between product and precursor ions, including undissociated charge-reduced ETnoD species, a several-fold increase in mass spectral resolution was required. This was achieved by performing TD MS with ETD on a high-resolution Orbitrap platform, LTQ Orbitrap Velos, jointly by Tsybin's group and Thermo Fisher Scientific (#1.5 in Table 1 and Figs. 3–5) (33). Importantly, to enhance the performance of TD MS on the LTQ Orbitrap Velos, several methodological advancements were introduced or optimized, including: (i) TD MS measurements performed using an online LC-MS/MS experiment, supporting on-line sample purification and (limited) separation; (ii) reduced pressure in the C-trap, which later resulted in the development of the “protein mode” on the Orbitrap platforms; (iii) HCD-trapping used to assist in precursor ion transfer and, potentially, an early realization of the EThcD conditions; and (iv) acquisition and averaging of the unreduced data (time-domain ion signals or transients) from multiple technical replicates of the LC-MS/MS runs for the enhanced sensitivity and confidence in product ion detection. As a result, sequence coverage was almost doubled to reach 33% overall for a similar IgG1 species. Glycosylation of the Hc was not characterized, similar to the earlier ETD TOF MS measurements.

Electron Capture Dissociation (ECD) FT-ICR TD MS

Although the added value of ECD in the analysis of intact proteins was demonstrated as early as 1998 (34), its application to mAb analysis only emerged 15 years later and after the promising results obtained with ETD. In 2013, Marshall
<table><caption>TABLE 1
TD MS analysis of mAbs with single or multiple activation methods</caption><thead><tr><th>#</th><th>mAb or brand name</th><th>Separation method</th><th>MS/MS method</th><th>Instrument</th><th>Sequence coverage</th><th>Ref.</th></tr></thead><tbody><tr><td>1.1</td><td>Murine anti-(human q-acid glycoprotein) mAb (IgG1)</td><td>DI</td><td>CID</td><td>Triple quadrupole MS (API III MS/MS system, Sciex)</td><td>N/A</td><td>Feng and Konishi 1993 (27)</td></tr><tr><td>1.2</td><td>Amgen mAb (IgG1 and IgG2)</td><td>Off-line SEC - LC</td><td>isCID</td><td>LTQ Orbitrap (TFS)</td><td>&lt;10%</td><td>Zhang and Shah 2007 (29)</td></tr><tr><td>1.3</td><td>Amgen mAb (IgG2)</td><td>DI and RPLC</td><td>isCID</td><td>LTQ Orbitrap (TFS)</td><td>&lt;10%</td><td>Bondarenko et al. 2009 (30)</td></tr><tr><td>1.4</td><td>Human anti-Rhesus D mAb (IgG1)</td><td>RPLC</td><td>ETD</td><td>maXis UHR Q-TOF MS (Bruker Daltonics)</td><td>20%</td><td>Tsybin et al. 2011 (31)</td></tr><tr><td>1.5</td><td>Murine myeloma mAb (IgG1)</td><td>RPLC</td><td>ETD</td><td>LTQ Orbitrap Velos Pro (TFS)</td><td>33%</td><td>Fornelli et al. 2012 (33)</td></tr><tr><td>1.6</td><td>Recombinant humanized mAb (IgG1)</td><td>DI</td><td>ECD</td><td>9.4 T FT-ICR MS (NHMFL)</td><td>34%</td><td>Mao et al. 2013 (35)</td></tr><tr><td>1.7</td><td>Adalimumab (IgG1)</td><td>DI and RPLC</td><td>EThcD</td><td>LTQ Orbitrap Elite (TFS)</td><td>~35%</td><td>Fornelli et al. 2017 (37)</td></tr><tr><td>1.8</td><td>Rituximab (IgG1)</td><td>RPLC</td><td>UVPD, ETD</td><td>Fusion Lumos Orbitrap (TFS) – 213 nm UVPD</td><td>~40% (3 runs)</td><td>Fornelli et al. 2018 (38)</td></tr><tr><td>1.9</td><td>NIST mAb (IgG1)</td><td>RPLC</td><td>UVPD, ETD, UVPD, EThcD</td><td>15 T solarix XR FT-ICR MS equipped with a CombiSource and a ParaCell (Bruker Daltonics)</td><td>~90% (6 LC-MS runs)</td><td>van der Burgt et al. 2019 (40)</td></tr><tr><td>1.10</td><td>SiLuLite (MSQC4) (IgG1)</td><td>MALDI</td><td>MALDI-ISD</td><td>12 T solarix XR FT-ICR MS (Bruker Daltonics)</td><td>38–42% 51–55%</td><td>Jin et al. 2019 (36)</td></tr><tr><td>1.11</td><td>NIST mAb (IgG1)</td><td>DI</td><td>ECD, CID</td><td>Fusion Lumos Orbitrap (TFS) modified with a Firestar T-100 Synrad 60-W CO2 continuous wave laser</td><td>23% 76%</td><td>Lodge et al. 2020 (41)</td></tr></tbody></table>
<table><caption>TABLE 1—Continued</caption><thead><tr><th>#</th><th>mAb or brand name</th><th>Separation method</th><th>MS/MS method</th><th>Instrument</th><th>Sequence coverage</th><th>Ref.</th></tr></thead><tbody><tr><td>1.12</td><td>Trastuzumab (IgG1)</td><td>nTD: DI<br>DI<br><b>TD and MD (IdeS + KGP)</b></td><td>EChcD<br>UVPD<br>EChcD, UVPD</td><td>Q Exactive HF/UHMR<br>Orbitrap (TFS) modified<br>to enable UVPD (157 nm)<br>and ExD cell (e-MSion)</td><td>27%<br>22%<br>CDR</td><td>Shaw et al. 2020<br>(43)</td></tr><tr><td>1.13</td><td>Ang-2-VEGF BsAb</td><td>MALDI<br><b>TD and MD (IdeS + DTT)</b></td><td>MALDI-ISD</td><td>15 T solariX XR FT-ICR<br>MS equipped with a<br>CombiSource and a<br>ParaCell (Bruker<br>Daltonics)</td><td>~35%</td><td>Gstöttner et al.<br>2020 (63)</td></tr><tr><td>1.14</td><td>Monomer IgM<br>Pentamer (IgM)<sub>5</sub>J<br>Hexameric (IgG1)<sub>66</sub></td><td>RPLC<br><b>BU</b></td><td>HCD, ETD</td><td>Orbitrap Lumos (TFS)</td><td>81%</td><td>Greisch, den<br>Boer, Lai, et al.<br>2021 (44)</td></tr><tr><td>1.15</td><td>anti-CD20 (IgG1, IgA1)</td><td>DI<br><b>nTD and MD (IgdE)</b></td><td>ECD</td><td>Q Exactive UHMR Orbitrap<br>(TFS) with ExD cell<br>(e-MSion)</td><td>CDRs</td><td>Greisch, den<br>Boer,<br>Beurskens,<br>et al. 2021 (45)</td></tr><tr><td>1.16</td><td>NIST mAb (IgG1)<br>ADCs (IgG1)</td><td>DI</td><td>ECD, HCD</td><td>Q Exactive plus UHMR<br>Orbitrap (TFS) with ExD<br>cell (e-MSion)</td><td>75% (with internal<br>product ions)</td><td>Wei et al. 2023<br>(46)</td></tr><tr><td>1.17</td><td>Trastuzumab (IgG1)</td><td>DI<br><b>Native and<br>denaturing TD</b></td><td>HCD, ETD,<br>EThcD, UVPD</td><td>Orbitrap Eclipse (TFS)</td><td>49%</td><td>Oates, Lieu,<br>Srzentic,<br>et al. 2024 (39)</td></tr></tbody></table>

A “run” refers to repeated analyses conducted under different experimental conditions, and a “replicate” refers to repeated analyses performed under identical experimental conditions (DI - direct injection, TFS - Thermo Fisher Scientific).
<figure><img src="image_6.png" /><figcaption>FIG. 3. Advances in mAbs sequence coverage annotation through diverse TD/MD MS approaches developed over the past 30 years. Each data point corresponds to an approach with a specific MS/MS technique(s), plotted by increasing sequence coverage on the x-axis. Each point corresponds to a reference entry in Tables 1 and 2 and is labeled by the MS method and associated table row number (e.g., #1.1 – row one in Table 1).</figcaption></figure>

and co-workers at the National High Magnetic Field Labora-
tory (NHMFL) utilized ECD on a custom-built high-resolution
9.4 T FT-ICR MS for the direct infusion analysis of a purified
148 kDa mAb (35). Using the isolated single 51+ charge state,
they achieved 25% sequence coverage (#1.6 in Table 1,
Figs. 3 and 4). Results obtained in 2019 by Ying Ge and

colleagues using a commercial ECD-enabled 12 T FT-ICR MS
platform (SolariX XR, Bruker Daltonics) remained comparable.
Ge's team, also performing single-charge state TD MS anal-
ysis with ECD and CID, identified 172 product ions and ach-
ieved 23% sequence coverage for the SiLuLite mAb (#1.10 in
Table 1 and Figs. 3-5) (36).

<figure><img src="image_7.png" /><figcaption>FIG. 4. Sequence coverage that was achieved for antibodies using TD-MS, MD-MS, and combinations of these approaches with various fragmentation techniques as a function of precursor ion molecular weight. These molecular weights correspond to common antibody subunits generated via structure-specific enzymes or disulfide bond reduction. F(ab')₂ represents the ~100 kDa fragment produced by IdeS digestion, containing two Lc, two Fd, and part of the hinge region. Each data point represents an experiment with a specific technique, positioned according to its resulting sequence coverage. Each point marks a specific experiment and is annotated with the method and table row number (e.g., #1.1 = Table 1, row 1).</figcaption></figure>
<table><caption>FIG. 5. Sequence coverage (%) obtained for mAbs over the past 30 years using TD MS, MD MS, and combinations of these MS approaches with different fragmentation techniques. Each colored block represents a specific study, annotated with the applied MS method and the corresponding entry number from the review tables (e.g., #1.1 – row one in Table 1). The percentage of sequence coverage obtained in each study is displayed within its respective block.</caption><thead><tr><th rowspan="2">Methods</th><th rowspan="2"></th><th colspan="8">IgG1</th><th colspan="2">IgG2</th><th colspan="2">IgG4</th></tr><tr><th>Adalimumab</th><th>Bevacizumab</th><th>Cetuximab</th><th>Infliximab</th><th>NIST mAb</th><th>Rituximab</th><th>SiLuLite</th><th>Trastuzumab</th><th>Panitumumab</th><th>Natalizumab</th><th>SiLuLite K4</th></tr></thead><tbody><tr><td rowspan="4">Combined MS approaches</td><td>MD, MU and BU MALDI-ISO qTOF, (2.4)</td><td></td><td></td><td>100</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>TD and MD ETD, UVPD, EThcD (IdeS or KGP) OT, (1.8)</td><td></td><td></td><td></td><td></td><td></td><td>90</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>TD and MD ECD, CID (IdeS+TCEP) 12 FT-ICR, (1.10)</td><td></td><td></td><td></td><td></td><td></td><td></td><td>76</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>MALDI-ISO (IdeS or KGP) 15 FT-ICR, (1.9)</td><td></td><td></td><td></td><td></td><td>55</td><td></td><td></td><td>51</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="12">MD MS</td><td>EThcD / PTCR, UVPD / PTCR OT, (2.27)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>95</td><td></td><td></td><td></td><td></td></tr><tr><td>ETD / PTCR, HCD / PTCR, EThcD / PTCR OT, (2.25)</td><td></td><td></td><td></td><td></td><td></td><td>94.2</td><td></td><td></td><td></td><td>90</td><td>90</td><td></td></tr><tr><td>MALDI-ISO TOF/TOF, (2.9)</td><td></td><td></td><td>90</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>ECD, ECuvPD, EChcD OT, (2.14)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>86</td><td></td><td></td><td></td><td></td></tr><tr><td>UVPD OT (4 runs), (2.8)</td><td>77</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>HCD / PTCR, EThcD / PTCR OT, (2.25)</td><td></td><td></td><td></td><td>77</td><td></td><td></td><td></td><td>76.6</td><td></td><td></td><td></td><td>77.6</td></tr><tr><td>UVPD, ETD OT, (2.8)</td><td>72</td><td></td><td></td><td></td><td>73</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>ETD OT (6 runs), (2.21)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>70</td><td></td><td></td><td></td><td></td></tr><tr><td>ETD OT (10 runs), (2.6)</td><td>70</td><td>70</td><td></td><td></td><td></td><td></td><td>64</td><td>60</td><td></td><td></td><td></td><td></td></tr><tr><td>HCD OT (Astral), (2.28)</td><td></td><td></td><td></td><td></td><td>60</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CID, HCD and EThcD OT, (2.23)</td><td></td><td></td><td>80.2</td><td>97.1</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>UVPD OT, (2.8, 2.30)</td><td>60</td><td></td><td></td><td></td><td></td><td></td><td></td><td>60</td><td></td><td></td><td></td><td></td></tr><tr><td>ETD OT, (2.6)</td><td>50</td><td>50</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>MALDI-ISO 15 FT-ICR, (2.16)</td><td></td><td></td><td></td><td></td><td>50</td><td></td><td></td><td>50</td><td></td><td></td><td></td><td></td></tr><tr><td>HCD, CID, ETD, EThcD, UVPD OT, (2.15)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CID, ETD 21 FT-ICR, (2.11)</td><td></td><td>50</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>CID, ETD Q TOF, (2.20)</td><td></td><td></td><td>37</td><td></td><td></td><td></td><td></td><td></td><td>38</td><td></td><td></td><td></td></tr><tr><td rowspan="10">TD MS</td><td>HCD, ECD OT (internal product ions), (1.16)</td><td></td><td></td><td></td><td></td><td></td><td>75</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>AI-ETD OT, (1.11)</td><td></td><td></td><td></td><td></td><td></td><td>60</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Native and denaturing TD HCD, ETD, EThcD, UVPD OT, (1.17)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>49</td><td></td><td></td><td></td><td></td></tr><tr><td>MALDI-ISO 15 FT-ICR, (1.9)</td><td></td><td></td><td></td><td></td><td>38</td><td></td><td></td><td>42</td><td></td><td></td><td></td><td></td></tr><tr><td>UVPD, ETD OT, (1.8)</td><td></td><td></td><td></td><td></td><td></td><td></td><td>40</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EThcD OT, (1.7)</td><td>35</td><td></td><td></td><td></td><td></td><td></td><td></td><td>35</td><td></td><td>35</td><td></td><td></td></tr><tr><td>ETD OT, (1.5)</td><td>33</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>EChcD OT, (1.12)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>27</td><td></td><td></td><td></td><td></td></tr><tr><td>ECD, CID 12 FT-ICR, (1.10)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>23</td><td></td><td></td><td></td></tr><tr><td>UVPD OT, (1.12)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>22</td><td></td><td></td></tr></tbody></table>

In the same 2013 study, Marshall and co-workers reported an increased sequence coverage of 34% when ECD was applied on several charge states (#1.6 in Table 1, Figs. 3, and 4). These advances aligned with the results obtained using Orbitrap ETD for multiple charge states regarding total sequence coverage, cleavage preferences, and backbone cleavage localization. Additionally, Marshall and co-workers activated precursor ions with infrared photons before the ECD reaction (AI-ECD); however, this did not substantially enhance performance. The authors suggested that the high charge states of product ions caused sufficient Coulombic repulsion to disrupt non-covalent precursor or product ions interactions, reducing the need for additional activation (35).

## ETD with Supplemental Ion Activation (EThcD/ETciD)
TD MS

Although Tsybin and co-authors improved mAb sequence coverage using ETD by incorporating multiple charge states, varying ion-ion reaction times, and averaging several thousands of tandem mass spectra (via transients), the ETD-based TD MS approach still required further optimization (33). One proposed reason for the relatively limited mAb sequence coverage in ETD is the presence of non-covalent interactions between product ions (c/z-type), which hinder their separation and result in non-dissociative electron transfer (ETnoD). This behavior is particularly relevant for precursor ions with low charge density (e.g., one charge per 1000 Da), where secondary structure and disulfide bonds remain intact. As a next

step, Tsybin's group increased the additional vibration energy to the ion population following ETD activation, combining ETD and higher energy collisional dissociation (HCD), known as EThcD (37). The ETD- and EThcD-based TD MS analysis was applied to two IgG subclasses, IgG1 and IgG2, which differ in the number of interchain disulfide bonds within the antibody hinge region. The results demonstrated comparable sequence coverage of approximately 35% and similar patterns of backbone cleavage sites between the two IgG subclasses (#1.7 in Table 1 and Figs. 3–5).

Therefore, the original and follow-up results of CID- and ETD/ECD-based TD MS applied to the intact IgG1 analysis improved sequence coverage but left the glycosylation localization uncharacterized and S-S bond-protected regions largely uncovered. Additional vibrational activation, such as AI-ECD or EThcD, led to only a modest improvement in sequence coverage.

## UV Photodissociation (UVPD) and ETD TD MS

In 2018, Kelleher and colleagues set a new benchmark for IgG1 analysis, achieving approximately 40% sequence coverage of intact rituximab in TD MS experiments by combining UVPD and ETD techniques (#1.8 in Table 1 and Figs. 3–5) (38). They identified product ions with a mass accuracy of 10 ppm, as in previous studies, but enhanced their data analysis by incorporating deconvolution-free product ion validation using TDValidator (Proteinaceous). Product ion annotation was manually curated, and those that did not
match the isotopic fitter, e.g., detected with fewer than three correctly matched isotopologues for a large product ion, were not considered.

In 2024, an UVPD-related report from the Fornelli group compared native and denaturing TD MS analysis of trastuzumab (39). They benchmarked four fragmentation techniques: HCD, ETD, EThcD, and 213 nm UVPD. In their study, native TD MS achieved slightly higher sequence coverage than denaturing TD MS when using HCD and ETD, yielded comparable results with EThcD, and showed marginally lower coverage with UVPD (#1.17 in Table 1 and Figs. 3–5). Although more precursor ions were selected for native TD MS (due to the same AGC value used in both native and denaturing TD MS, with lower precursor charge states in the native analysis), the findings suggest the added value of native TD MS for primary structure analysis applications.

## MALDI In-Source Decay (ISD) TD MS

In 2019, MALDI-ISD was applied in the TD MS analysis of two antibodies: trastuzumab and the NIST mAb standard. The TD MS antibody analysis was conducted using a high-resolution 15 T FT-ICR MS (SolariX XR, Bruker Daltonics). The data analysis benefited from the enhanced resolution of absorption mode FT mass spectra, a technique adopted by Nicolardi's group and enabled by transient post-processing using the AutoVectis software package (40). As a result, TD MS analysis with a single activation method achieved an increased sequence coverage for trastuzumab and the NIST mAb standard at 38% and 42%, respectively (#1.9 in Table 1 and Figs. 3–5).

## Activated Ion Electron Transfer Dissociation (AI-ETD) TD MS

In 2020, the range of ETD-based TD methods applied to the intact mAbs analysis was expanded with the introduction of activated ion ETD (AI-ETD), developed by the Coon's group (41). In AI-ETD, precursor ions are irradiated with infrared photons before or during the ETD event, which helps break non-covalent interactions between product ions, thus enhances fragmentation efficiency. This concept was originally demonstrated in AI-ECD experiments for peptides and smaller proteins (42). However, in comparison with the limited performance improvement with AI-ECD of mAbs in FT-ICR MS, the Coon's group achieved a 60% sequence coverage of intact mAbs using TD MS analysis with AI-ETD on a hybrid Orbitrap platform (Orbitrap Fusion Lumos, Thermo Fisher Scientific), row #1.11 in Table 1 and Figures 3–5. Notably, varying the reaction conditions (e.g., from 18 W, 20 ms to 24 W, 180 ms) produced different types of product ions, offering deeper insights into disulfide-bonded regions (41).

## Electron Capture Dissociation (ECD) Orbitrap TD MS

During the same year, 2020, Voinov, Shaw, and colleagues reported on a method for cleaving the disulfide bonds that link

the Lc and Hc subunits of trastuzumab using ECD with a supplemental activation *via* higher energy collisions (EChcD) or *via* UVPD at 157 nm, or ECuvPD (43). Building on this concept, they demonstrated that isolating the intact antibody or its Fab subunit and performing on-the-flight disulfide bond reduction enabled direct determination of chain pairing, *i.e.* revealing which Lc is connected to which Hc (precise localization of the involved cysteines is not needed). This approach can be particularly valuable for analyzing complex antibody mixtures containing diverse light and heavy chain pairings. Their setup featured a modified Q Exactive HF/ultra-high mass-range (UHMR) Orbitrap mass spectrometer (Thermo Fisher Scientific) integrated with an electromagnetostatic E x D cell (e-MSion Inc., Corvallis, Oregon). These analyses yielded reliable identification of 27% and 22% of the antibody sequences with an improved mass tolerance of 5 ppm using EChcD and ECuvPD activation methods, respectively (#1.12 in Table 1 and Figs. 3–5). Notably, this study highlighted the advantages of performing native antibody MS analysis and selecting low-charge-state precursor ions, which helped to reduce spectral congestion and minimize interferences for product ions. Chronologically, the chain pairing TD MS application followed the original MD MS approach developed by Tsybin and co-workers in 2018, which utilized internal product ions for mAb chain pairing (#2.12 in Table 2, Figs. 3, and 4).

In 2021, the Heck group extended the application of TD MS to the analysis of sub-million Da IgM- and IgG-based oligomeric immunoglobulins, row #1.14 in Table 1 (44). A Q Exactive UHMR Orbitrap (Thermo Fisher Scientific) equipped with the E x D cell was employed to analyze pentameric IgM and hexameric IgG1. Interestingly, the ECD mass spectra acquired for both the multimeric and monomeric (Fig. 1) forms showed only a 20% difference, suggesting that the assembly of these complexes has a low impact on product ion formation.

In a subsequent study, Heck and colleagues compared native TD MS of IgG1 and IgA1 using ECD (#1.15 in Table 1) (45). Unlike IgG1, IgA1 exhibits significantly higher glycosylation and glycan complexity (Fig. 1), leading to charge state-unresolved ion signals which complicate intact mass measurement. Despite this complexity, the researchers obtained amino acid sequence ladders, limited to c-ions, that covered the CDR3s and other regions. Notably, there was minimal variation between the native TD ECD mass spectra of the heterogeneously N- and O-glycosylated IgA1, the N-glycosylated IgG1, and their Fab subunits. These findings suggested that key regions like CDR3s can be comprehensively characterized in IgGs, regardless of their class or subclass, even when dealing with highly glycosylated forms.

More recently, Loo and colleagues achieved up to 75% sequence coverage of the NIST mAb by including internal product ion annotations in addition to conventional terminal fragment analysis, #1.16 in Table 1 and Figures 3–5 (46). They employed a Q Exactive Plus Orbitrap outfitted with the UHMR
<table><caption>TABLE 2
MD MS analyses of mAbs with single or multiple activation methods</caption><thead><tr><th>#</th><th>mAb or brand name</th><th>Sample preparation</th><th>Separation method</th><th>MS/MS method</th><th>Instrument</th><th>Sequence coverage</th><th>Ref.</th></tr></thead><tbody><tr><td>2.1</td><td>Amgen mAb (IgG2)</td><td>DTT</td><td>RPLC</td><td>CID</td><td>LTQ Orbitrap (TFS)</td><td>~15%</td><td>Bondarenko et al. 2009 (30)</td></tr><tr><td>2.2</td><td>Amgen mAb (IgG)</td><td>TCEP</td><td>RPLC</td><td>isCID</td><td>LCT Premier TOF MS (Waters)</td><td>N/A</td><td>Ren et al. 2009 (47)</td></tr><tr><td>2.3</td><td>Nanobody (IgG heavy chain V<sub>H</sub>)</td><td>DNA MALDI matrix or TCEP</td><td>MALDI</td><td>MALDI-ISD</td><td>ultrafleXtreme MALDI-TOF/TOF MS (Bruker Daltonics)</td><td>100% (V<sub>H</sub>)</td><td>Resemann et al. 2010 (56)</td></tr><tr><td>2.4</td><td>Cetuximab (IgG1)</td><td>MD, MU, and BU (IdeS + TCEP)</td><td>DI or RPLC</td><td>MALDI-ISD<br>BU: MALDI-ISD and ESI CID</td><td>MU: maXis 4G high resolution Q-TOF<br>MD: rapifleX TOF/TOF bottom-up: LC-ESI-maXis impact high resolution Q-TOF and MALDI ultra-fleXtreme TOF/TOF (all Bruker Daltonics)</td><td>100%</td><td>Ayoub et al. 2013 (58)</td></tr><tr><td>2.5</td><td>Roche Diagnostics mAbs (IgG1)</td><td>Electrochemical cell</td><td>DI</td><td>CID</td><td>15 T Solarix FT-ICR MS (Bruker Daltonics)</td><td>N/A</td><td>Nicolardi et al. 2014 (48)</td></tr><tr><td>2.6</td><td>Adalimumab (IgG1)<br>Bevacizumab (IgG1)<br>Trastuzumab (IgG1)</td><td>IdeS + TCEP</td><td>RPLC</td><td>ETD</td><td>LTQ Orbitrap Elite (TFS)</td><td>~50% (1 run)<br>~70% (10 runs)</td><td>Fornelli et al. 2014 (52)</td></tr><tr><td>2.7</td><td>Adalimumab (IgG1)<br>Alemtuzumab (IgG1)</td><td>MD and BU (Papain + TCEP)</td><td>Chromato-focusing and RPLC</td><td>ETD, HCD</td><td>12 T Solarix FT-ICR MS (Bruker Daltonics) in-house ICR cell and 15 T Solarix FT-ICR MS (Bruker Daltonics)<br>LTQ Orbitrap Velos and Q Exactive (TFS)</td><td>100% (Fab)</td><td>Dekker et al. 2014 (64)</td></tr><tr><td>2.8</td><td>Trastuzumab (IgG1)<br>Adalimumab (IgG1)</td><td>IdeS + TCEP</td><td>RPLC</td><td>UVPD<br>UVPD + ETD</td><td>LTQ Orbitrap Elite (TFS) outfitted with a 193 nm ArF excimer laser (Coherent ExciStar XS)</td><td>~60% (1 run)<br>~77% (4 runs)<br>72-74%</td><td>Cotham and Brodbelt 2016 (67)</td></tr><tr><td>2.9</td><td>Cetuximab (IgG1)<br>Panitumumab (IgG2)<br>Natalizumab (IgG4)</td><td>EndoS + IdeS + TCEP/ DTT<br>+ for Cetuximab PNGase F</td><td>MALDI and RPLC</td><td>MALDI-ISD</td><td>ultrafleXtreme MALDI-TOF/TOF (Bruker Daltonics)</td><td>~90%</td><td>Resemann et al. 2016 (59)</td></tr><tr><td>2.10</td><td>Cetuximab (IgG1)</td><td>IdeS</td><td>CE</td><td>MALDI-ISD</td><td>Autoflex II MALDI-TOF (Bruker Daltonics)</td><td>9% (Fc/2)</td><td>Biacchi et al. 2017 (61)</td></tr><tr><td>2.11</td><td>Adalimumab (IgG1)</td><td>TCEP or IdeS + TCEP</td><td>RPLC</td><td>CID, ETD</td><td>21 T LTQ FT-ICR MS (NHMFL)</td><td>~50%</td><td>He et al. 2017 (65)</td></tr><tr><td>2.12</td><td>Trastuzumab (IgG1 Fab)</td><td>KGP</td><td>RPLC</td><td>ETD<br>HCD</td><td>LTQ Orbitrap Elite (TFS)<br>Q Exactive HF Orbitrap (TFS)</td><td>~24% (10 reps)<br>20.4% (10 reps)</td><td>Srzentić et al. 2018 (50)</td></tr></tbody></table>
<table><caption>TABLE 2—Continued</caption><thead><tr><th>#</th><th>mAb or brand name</th><th>Sample preparation</th><th>Separation method</th><th>MS/MS method</th><th>Instrument</th><th>Sequence coverage</th><th>Ref.</th></tr></thead><tbody><tr><td>2.13</td><td>IgG1</td><td>IdeS or IdeS + TCEP</td><td>CZE</td><td>HCD</td><td>Q Exactive Plus Orbitrap (TFS)</td><td>29%</td><td>Belov et al. 2018 (51)</td></tr><tr><td>2.14</td><td>SiLuLite mAb(MSQC4) (IgG1)</td><td>IdeS + DTT</td><td>RPLC</td><td>ECD, ECuvPD, EChcD</td><td>Q Exactive HF Orbitrap (TFS) modified to enable UVPD in the HCD cell and an ExD cell (e-MSion)</td><td>86%</td><td>Shaw et al. 2018 (69)</td></tr><tr><td>2.15</td><td>NIST mAb (IgG1)</td><td>TCEP</td><td>FAIMS</td><td>HCD, CID, ETD, EThcD, UVPD</td><td>Orbitrap Eclipse with FAIMS Pro (TFS)</td><td>~50%</td><td>Melani et al. 2019 (71)</td></tr><tr><td>2.16</td><td>SiLuLite mAb (IgG1) NIST mAb (IgG1)</td><td>IdeS</td><td>MALDI</td><td>MALDI-ISD</td><td>15 T solariX XR FT-ICR MS with a CombiSource and a ParaCell (Bruker Daltonics)</td><td>~50%</td><td>Nicolardi et al. 2020 (62)</td></tr><tr><td>2.17</td><td>ADC from AbbVie</td><td>IdeZ + TCEP</td><td>RPLC</td><td>UVPD-PTCR</td><td>Orbitrap Fusion Lumos (TFS) with a 193 nm excimer laser (Coherent Excistar XS)</td><td>74% (Lc + 1 payload)</td><td>Sanders et al. 2020 (72)</td></tr><tr><td>2.18</td><td>SiLuLite (IgG1) NIST mAb (IgG1) Trastuzumab (IgG1)</td><td>TCEP</td><td>RPLC</td><td>CID/PTCR + ETD/PTCR</td><td>21 T LTQ FT-ICR MS (NHMFL)</td><td>85% (Lc)</td><td>Srzentić et al. 2020 (14)</td></tr><tr><td>2.19</td><td>IgG1 - 4</td><td>IdeS</td><td>DI</td><td>nTD: ECD</td><td>Q Exactive UHMR Orbitrap (TFS) with ExD cell (e-MSion)</td><td>CDR3</td><td>den Boer et al. 2020 (53)</td></tr><tr><td>2.20</td><td>Trastuzumab (IgG1) Adalimumab (IgG1)</td><td>IdeS + TCEP</td><td>SEC- native RPLC- denaturing</td><td>CID, ETD</td><td>maXis II ETD UHR Q TOF MS (Bruker Daltonics)</td><td>38%</td><td>Zhu, Li, and Zhang 2021 (66)</td></tr><tr><td>2.21</td><td>NIST mAb (IgG1)</td><td>IdeS + DTT</td><td>RPLC</td><td>ETD</td><td>Orbitrap Fusion Lumos (TFS)</td><td>73% (6 runs)</td><td>Cejkov et al. 2021 (54)</td></tr><tr><td>2.22</td><td>NIST mAb (IgG1)</td><td>DTT</td><td>CE(SDS)-CZE</td><td>HCD, ETD, UVPD</td><td>Orbitrap Fusion Lumos (TFS)</td><td>64% (Lc)</td><td>Römer et al. 2021 (73)</td></tr><tr><td>2.23</td><td>SiLuLite (IgG1) NIST mAb (IgG1)</td><td>DTT</td><td>RPLC</td><td>CID, HCD, EThcD</td><td>Orbitrap Eclipse (TFS)</td><td>60%</td><td>Dhenin, Dupré, et al. 2023 (74)</td></tr><tr><td>2.24</td><td>GSKmAb biotinylated, goat-derived antihuman (IgG)</td><td>TCEP</td><td>RPLC</td><td>CID, ECD</td><td>ZenoTOF 7600 (Sciex)</td><td>30%</td><td>Kellie et al. 2023 (75)</td></tr><tr><td>2.25</td><td>NIST mAb (IgG1) SiLuLite (MSQC4) (IgG1) SiLuLite K4 (MSQC14) (IgG4)</td><td>IdeS + DTT/TCEP</td><td>RPLC</td><td>ETD/PTCR, HCD/PTCR, EThcD/PTCR</td><td>Orbitrap Eclipse (TFS) with ETD/PTCR, high mass range</td><td>94.2% (3 runs)</td><td>Oates, Lieu, Kline, et al. 2024 (76)</td></tr></tbody></table>
<table><caption>TABLE 2—Continued</caption><thead><tr><th>#</th><th>mAb or brand name</th><th>Sample preparation</th><th>Separation method</th><th>MS/MS method</th><th>Instrument</th><th>Sequence coverage</th><th>Ref.</th></tr></thead><tbody><tr><td>2.26</td><td>SILu SigmaMab ADC (MSQC8) (IgG)</td><td>IdeS + DTT/TCEP</td><td>RPLC</td><td>ETD/PTCR, HCD/PTCR, EThcD/PTCR, UVPD/PTCR</td><td>Orbitrap Ascend (TFS) with ETD, UVPD, PTCR</td><td>&gt;79.5% (Fd with 1 or 2 payload(s))</td><td>Lieu et al. 2024 (77)</td></tr><tr><td>2.27</td><td>Trastuzumab (IgG1)</td><td>IdeS + DTT</td><td>SEC- native RPLC- denaturing</td><td>EThcD/PTCR, UVPD/PTCR</td><td>Orbitrap Ascend (TFS)</td><td>95% (10 runs)</td><td>Huang et al. 2024 (102)</td></tr><tr><td>2.28</td><td>Trastuzumab (IgG1)<br>Rituximab (IgG1)<br>NISTmAb (IgG1)<br>SigmaMAb ADC Mimic (IgG1)</td><td>Intact mass (native, denaturing), MD, BU IdeS + TCEP</td><td>SEC- native RPLC- denaturing</td><td>HCD</td><td>Orbitrap Astral (TFS)</td><td>MD - 64%</td><td>Srzentić et al. 2024 (103)</td></tr><tr><td>2.29</td><td>Multiple myeloma mAb (IgG (Lc))</td><td>TCEP</td><td>RPLC</td><td>ECD</td><td>Q Exactive HF BioPharma (TFS) with an Omnitrap (Fasmatech) and FTMS Booster X2 (Spectroswiss)</td><td>93% (Lc)</td><td>Garcia et al. 2024 (121)</td></tr><tr><td>2.30</td><td>Infliximab (IgG1)<br>Cetuximab (IgG1)</td><td>IdeS + TCEP</td><td>RPLC</td><td>EThcD UVPD</td><td>Orbitrap Eclipse (TFS)<br>Orbitrap Fusion Lumos (TFS) with 193-nm ArF excimer laser (Gam laser)</td><td>97.1% 80.2%</td><td>Liu et al. 2025 (68)</td></tr><tr><td>2.31</td><td>Intact mAb Mass Check Standard</td><td>TCEP</td><td>RPLC</td><td>ECD</td><td>ZenoTOF 7600 (Sciex)</td><td>28%</td><td>Searfoss et al. 2025 (55)</td></tr></tbody></table>

Definitions and abbreviations are as in Table 1.
and E x D cell capabilities, using both HCD and ECD to generate *b*, *c*, *y*, and *z*-type product ions in native TD MS analysis. The study underscores the valuable insights potentially gained from internal product ion annotations within an intact mAb, such as enhanced sequence coverage, identification of intra-chain and inter-chain disulfide linkages, and localization of N-glycosylation sites. To ensure high confidence in annotations, they applied stringent criteria: a 3-ppm mass tolerance and a minimum product ion length of five amino acids, along with manual validation.

MIDDLE-DOWN MS OF ANTIBODIES: METHOD DEVELOPMENT

MS/MS analysis of antibody subunits, known as MD MS,
retains the key advantages of TD MS, such as minimal sample
preparation and reduced risk of unwanted modifications, while
offering more accurate subunit mass measurements and
improved sequence coverage, owing to the absence of intra-
and inter-chain disulfide bonds and the smaller size of the
protein subunits (30). Table 2 and Figure 4 illustrate the in-
crease in antibody sequence coverage achieved with
decreasing subunit MW from the inception of the method to
the current state-of-the-art. Each data point represents a
specific experiment, showing how breaking down antibodies
into several smaller subunits can enhance sequence coverage
across different MS approaches and fragmentation
techniques.

Collision-Induced Dissociation (CID) MD MS

In 2009, recombinant IgG1 and IgG2 antibodies were
analyzed for the first time using CID-based MD MS, in
conjunction with TD MS (30). In the MD MS experiments'
sample preparation, intact mAbs were separated into Lc and
Hc in-solution by reducing the inter-chain disulfide bonds.
These subunits were then subjected to MS/MS analysis, with
CID in the LTQ and product ion detection in the Orbitrap
mass analyzer. The MD MS analysis resulted in a higher
number of product ions and better structural resolution of
antibodies compared to the TD MS analysis; however,
sequence coverage still did not exceed 15% (#2.1 in Table 2,
Figs. 3, and 4).

In a parallel study, the isCID MS/MS analysis performed on separated Lc and Hc subunits using a TOF MS demonstrated comparable performance and limitations (#2.2 in Table 2), enabling the rapid sequencing of the first seven N-terminal residues and the characterization of pyroglutamic acid formation, Figure 2 (47). In addition to the low resolution of the employed TOF MS platform, among the reasons of this relatively low sequence coverage for both instruments were high mass and glycosylation heterogeneity of subunits (50 kDa for Hc) and CID cleavage preferences.

Five years later, a high-resolution FT-ICR MS instrument
was also employed for CID-based MD MS analysis of the
reduced IgG1 antibody. Notably, instead of the in-solution

disulfide bond reduction, Nicolardi and colleagues coupled
an electrochemical cell to a 15 T FT-ICR MS to perform online
MD MS analysis (48). The Lc and Hc subunits of intact IgG1
mAb were separated into individual free Hc and Lc, as well as
combinations of these (Lc + Hc and Lc+2Hc), using
electrochemical-assisted reduction of interchain disulfide
bonds. The isolated Lc precursor ions were then subjected to
MS/MS analysis with CID, which confirmed that two intrachain
disulfide bonds remained intact, including one located in the
variable region between Cys28 and Cys88 (#2.5 in Table 2).

Higher-Energy Collision-Induced Dissociation (HCD) MD
MS

Higher-energy collision-induced dissociation (HCD) was
implemented on the Orbitrap platforms already in 2007 and
became widely utilized instead of CID for peptide structural
analysis (49). However, as HCD MS/MS alone provided limited
sequence coverage for large proteins, including intact mAbs, it
has been employed as a complementary ion activation
method alongside electron-based MS/MS techniques in TD/
MD MS of mAbs. Like the HCD-based TD MS, the HCD-based
MD MS approach generally yields fewer product ions
compared to electron-based techniques, as exemplified
below, necessitating the complementary use of these
methods to achieve a more comprehensive analysis.

In one HCD-based MD MS study, the Tsybin and Menin
groups analyzed the Fab subunits of trastuzumab by com-
plementing the ETD-based measurements performed on the
LTQ Orbitrap Elite with HCD on a Q Exactive HF mass spec-
trometer (50). The Lc and Fd subunits were generated by
specific cleavage above the hinge region using the KGP
enzyme. Data from 10 LC-MS/MS runs were processed using
spectral averaging, comparing two types of FTMS data:
enhanced FT (eFT, reduced profile mode) and absorption
mode FT (aFT, full profile mode). Spectral averaging from the
aFT mode assigned nearly twice as many *b*- and *y*-type
product ions compared to eFT. Sequence coverage using
HCD for the Fd subunit reached 10.7% with eFT and 20.4%
with aFT. Overall, HCD provided sequence coverage
exceeding 20% for the whole Fab subunit (#2.12 in Table 2,
Figs. 3, and 4).

In another study, the MD MS analysis with the HCD
approach enabled the characterization of the deamidated
proteoforms and glycoforms of the Fc/2 domain, as well as the
confirmation of specific PTM sites (51). To achieve these re-
sults, Ivanov and colleagues employed a high-resolution
capillary zone electrophoresis (CZE)-MS setup to conduct
both intact mass analysis (without dissociation) and MD MS
analysis of antibody subunits. Intact antibody MS analysis
under both native and denaturing conditions revealed different
mAb populations, including doubly glycosylated, singly gly-
cosylated, and non-glycosylated structures, along with the
detection of dimers, dissociated Lc, and even Lc dimers
subunit (#2.13 in Table 2, Figs. 3, and 4).
Electron-Based Dissociation MD MS

In 2014, the IdeS enzyme was employed in the original implementation of ETD-based MD MS analysis by Tsybin's group to cleave IgG1 below the hinge region (50, 52). As a result, sequence coverage of IgG1 increased to 70% (#2.6 in Table 2 and Figs. 3-5), and PTMs, e.g., methionine oxidation, were more amenable to localization. In their follow up work on ETD-based MD MS, the same group used the KGP enzyme to cleave IgG1 above the hinge region (#2.12 in Table 2, Figs. 3, and 4). The ETD-based MD MS applied to the KGP-derived Fab subunit of trastuzumab allowed to identify chain pairing based on branched (internal) product ions, i.e. ions containing portions of both the heavy and light chains connected via a disulfide bond (50). Both MD MS studies confirmed the advantages of processing unreduced MS data, achieved through the analysis of either transients or aFT (full profile) mass spectra, which had previously proven successful in TD MS.

Heck and colleagues conducted a pure ECD-based native MD MS analysis of F(ab')₂ parts from four IgG subclasses cleaved using IdeS: IgG1, IgG2, IgG3, and IgG4 (53). They successfully applied a Q Exactive UHMR Orbitrap (Thermo Fisher Scientific) equipped with the E x D cell (e-MSion Inc.) as described earlier for TD MS. The generated c-ions produced straightforward-to-read sequence ladders, facilitating the *de novo* sequencing of IgG CDR3s (#2.19 in Table 2).

In the MD MS study listed as #2.21 in Table 2, the mAb sequence coverage was increased to 73% for entire NIST mAb (with 75%, 78%, and 64% for Fc/2, Lc, and Fd subunits, respectively) by applying a design of experiments (DoE) approach to optimize ETD parameters such as precursor ion isolation window, ETD reaction time, number of ETD reagent molecules, and number of precursor ions (via automatic gain control, AGC, optimization) (54). Additionally, the DoE models were developed to fine-tune ETD settings for generating product ions across different mass ranges: low (<5 kDa), medium (5–10 kDa), and high (>10 kDa). The ETD reaction time was identified as the primary factor influencing product ion size in these models. This observation aligns with TD MS-based ETD analysis of mAbs conducted by Fornelli et al., which demonstrated that ETD reaction time significantly impacts the diversity of product ions (37). The DoE models confirmed that shorter ETD reaction times generally produced larger product ions. In contrast, longer reaction times resulted in a greater abundance of smaller ions in the ETD MS/MS spectra.

As an alternative for electron-based techniques coupled to Orbitrap platforms, Garcia and colleagues employed the ZenoTOF system (Sciex) using electron-activated dissociation (EAD, a commercial form of ECD) to analyze a well-characterized antibody (Waters Intact mAb Mass Check) (55). Intact mass analysis revealed five glycoforms. Subsequent MD MS analysis of the 25 and 50 kDa subunits—generated via disulfide bond reduction—achieved 28% overall

sequence coverage (21% for the heavy chain and 42% for the light chain) (#2.31 in Table 2, Figs. 3, and 4).

MALDI In-Source Decay (ISD) MD MS

In 2010, MALDI-based in-source decay (ISD) approach was added to the arsenal of MS/MS methods employed for MD MS of mAbs. Suckau and colleagues from Bruker Daltonics analyzed Camelidae IgG heavy chain antibodies, which lack light chains and contain a single variable domain ($V_H H$ or nanobody, ~14 kDa) (56). The analysis was conducted using an ultraflexXtreme MALDI-TOF/TOF mass spectrometer (Bruker Daltonics) with 1,5-diaminonaphthalene (DAN) and super 2,5-dihydroxybenzoic acid (sDHB) matrices. DAN helps to reduce disulfide bonds, enhancing N-terminal (c-type ions) and C-terminal (z-type ions) fragmentation and simplifying sequence analysis. In contrast, sDHB with TCEP-reduced samples promoted stronger c-, z-, a-, and y-type ion formation. The complementary use of these matrices enabled targeted analysis of both termini, generating long sequence tags with uniform fragmentation. The singly charged nature of the resulting product ions further facilitated *de novo* sequencing by reducing spectral complexity and improving ion assignment. To extend sequence tags toward the protein's central part, a second level of sequence analysis, pseudo-MS³ or deep sequencing, was performed on the same MALDI-TOF/TOF instrument (57). This pseudo-MS³ approach further improved sequence coverage and terminal fragment identification. As a result, the entire 14 kDa nanobody sequence was correctly identified with 100% coverage, except for Leu/lle ambiguities, which were resolved by bottom-up MS analysis (#2.3 in Table 2).

In 2013, the Suckau group at Bruker Daltonics collaborated with Beck's group to integrate MD MS with middle-up and bottom-up MS strategies for a comprehensive analysis of the primary structure and glycosylation profiling of cetuximab (58). This study utilized four high-resolution TOF MS instruments (Bruker Daltonics), including maXis 4G LC-ESI-Q-TOF for middle-up MS, rapifleX MALDI-ISD TOF/TOF for MD MS, as well as LC-ESI-maXis impact high resolution Q-TOF and MALDI ultraflexXtreme TOF/TOF for bottom-up MS analysis. The LC-MS-based middle-up analysis enabled MW determination at the subunit level. The MALDI-ISD-based MD MS approach investigated glycosylation variants and the amino acid sequence, identifying two errors in the then-current cetuximab sequence: a missing $Cys_{214}$ and an incorrectly proposed $Glu_{213}$ instead of $Ala_{213}$. Further peptide mapping experiments using bottom-up LC-MS/MS with CID on tryptic and GluC digests achieved 100% sequence coverage for both Lc and Hc (#2.4 in Table 2 and Fig. 5), enabling the localization of PTMs and sequence variants.

In 2016, these groups achieved an almost complete sequence validation of IgGs demonstrated using the combination of accurate mass measurements of 25 kDa IgG subunits with an ESI-based Q-TOF MS (middle-up MS approach)
and MALDI ISD TOF MS/MS approach applied to the analysis of 25 kDa subunits of IgG1 (cetuximab, a chimeric IgG produced in Sp2/0 cells), IgG2 (panitumumab, a human IgG produced in CHO cells), and IgG4 (natalizumab, a humanized IgG produced in NS0 cells) (59). The antibody subunits were produced from the antibodies deglycosylated using EndoS by digestion with IdeS and disulfide bond reduction by TCEP or DTT. An additional deglycosylation of cetuximab was performed by PNGase F enzyme. The authors outlined that the MALDI-ISD TOF MS approach resulted in a preferential sequencing of the eighth-10th residues from each terminus and exhibited a prohibited cleavage of the N-Cα bond of proline residues (#2.9 in Table 2 and Figs. 3–5) (59). The latter is also a fundamental characteristic of ETD/ECD approaches (60). The following year, François' group, in collaboration with the same group of Beck from Pierre Fabre Laboratory, analyzed the Fc/2 subunit of cetuximab by coupling off-line CZE and MALDI ISD TOF MS (61). An overall sequence coverage of 9% for Fc/2 was obtained, and the detected mass shift in the y-ions series confirmed the CZE separation of Fc/2 dimers with and without C-terminal Lys truncation (#2.10 in Table 2).

In 2019, Nicolardi and co-workers complemented their TD MS experiments with the MD MS analysis of trastuzumab and NIST antibodies on a high-resolution 15 T FT-ICR MS instrument (40). Both IdeS and KGP enzymes were employed to generate various antibody subunits. The experiments were performed using an enhanced resolution of 660,000 at *m/z* 400 on a 15 T FT-ICR MS (SolariX XR, Bruker Daltonics). As a result, overall sequence coverage increased from 42% with TD MS alone to 55% through the integration of TD MS and MD MS data (#1.9 in Table 1 and Figs. 3–5). The confidence in product ion identification was supported by using mass tolerances of 10, 20, and 40 ppm for *m/z* ranges of 1012 – 5000, 1012 – 7000, and 2024 – 30,000, respectively. This study also provided insights into N-glycosylation of the Fc region in trastuzumab and NIST antibodies, with the most abundant glycoforms of the Fc regions detected as doubly charged ions and identified at isotopic level resolution.

One year later, Nicolardi and co-workers analyzed another pair of antibodies, SiLuLite and NIST, using MALDI-ISD on the same high-resolution 15 T FT-ICR MS (SolariX XR, Bruker Daltonics) both in positive and negative modes (62). While positive mode required presence of basic residues for extensive sequence readout, negative mode was particularly effective for antibodies with acidic residues in N- and C-termini sequences, extending the sequenced regions from both termini. This complementary approach enabled to achieve an overall sequence coverage of ~50% (#2.16 in Table 2 and Figs. 3–5).

In 2020, the Nicolardi group conducted an in-depth investigation of the primary structure and glycation of a BsAb, a recombinant protein with distinct Lc and Hc designed to bind two different epitopes or antigens (63). They employed TD and

MD MS approaches using MALDI-ISD on a 15 T FT-ICR MS (SolariX XR, Bruker Daltonics) and bottom-up MS using ESI-based LC-MS Lumos Orbitrap with HCD. In contrast to classical single-specificity mAb MD MS analysis, six different antibody subunits were obtained after IdeS digestion and chemical reduction of disulfide bonds. This approach successfully tracked glycation changes during a 168-h experiment and localized glycation hotspots by combining results from TD MS, MD MS, and bottom-up MS analyses. This work revealed 34% sequence coverage with TD/MD MS and 81% with bottom-up MS for the Ang-2-VEGF BsAb (#1.13 in Table 1 and Figs. 3, and 4).

## COMBINED MS/MS AND TD/MD MS TECHNIQUES

In the first section, we describe the early efforts to combine methods like CID, HCD, ETD, and UVPD for enhanced sequence coverage in mAbs and mAbs subunits. The next section focuses on the synergy between TD and MD MS, emphasizing complete structural insights through complementary methods. Finally, we highlight technological innovations and optimization strategies that have pushed the limits of TD and MD MS.

## Combining Fragmentation Techniques

The combination of fragmentation techniques was first exemplified in 2014 by Paša-Tolić and colleagues who improved sequence coverage of adalimumab's Fab subunit using HCD and ETD in LC-based MD MS analyses (64). For the Fd' subunit, expectedly, HCD resulted in 23% coverage, and ETD achieved 46%, leading to an overall combined Fd' sequence coverage of 53%. For the Lc, HCD alone provided a higher sequence coverage (46%) compared to ETD (28%), yielding a combined sequence coverage of 64%. The integration of MD and bottom-up MS approaches enabled complete Fab subunit sequence characterization for adalimumab and alemtuzumab (64). First, authors obtained antibody subunits via digestion with papain and successfully separated the Fab's of the two antibodies by utilizing a 2D LC approach, specifically chromate-focusing followed by RP separation, and coupling it with high-resolution FT-ICR and Orbitrap mass spectrometers. Second, through database searches using the Fab subunit sequences of adalimumab and alemtuzumab, they achieved nearly complete sequence coverage (100% for all but the Fd' of adalimumab, which reached 97%) (#2.7 in Table 2), though without addressing the challenge of distinguishing between Ile and Leu residues. To mimic the analysis of antibodies with unknown sequences, they implemented a multi-step data processing approach: (i) identifying sequences *via* a database search, (ii) applying peptide de novo sequencing, and (iii) repeating the database search with the tentative sequence. The tentative sequences derived from bottom-up MS data were further validated through measured intact masses of the Fd' and Lc subunits
and MD MS data. In 2014, it was one of the first studies of this kind, and most of the data were processed manually.

In 2017, further exploring these strategies, Marshall and colleagues combined CID and ETD to analyze adalimumab's Lc and Hc (65). These fragmentation events were carried out independently using an LTQ Velos Pro integrated with a custom-built 21 T FT-ICR MS. The combined results from eight targeted nano-LC FT-ICR MS/MS experiments, focusing on the 24+ charge state of the Lc and the 55+ charge state of the Hc, achieved an overall sequence coverage of 50%, with 81% coverage for the Lc and 38% for the Hc, all identified with a mass accuracy of better than 5 ppm (#2.11 in Table 2 and Figs. 3–5).

In 2021, Jinlan Zhang and colleagues optimized CID and ETD on a maxXis II ETD UHR Q-TOF mass spectrometer for MD MS analysis of trastuzumab and adalimumab (66). Both antibodies were enzymatically cleaved using IdeS and reduced using TCEP to generate 25-kDa subunits. The sequence coverage achieved was 38% for trastuzumab and 37% for adalimumab (#2.20 in Table 2 and Figs. 3–5). In addition, major glycoforms were distinguished through intact native and denaturing MS analysis, with their relative abundances quantified.

In parallel, the Brodbelt group demonstrated the utility of UVPD fragmentation in 2016, particularly its complementarity to ETD (67). Using UVPD-equipped Orbitrap platforms they unambiguously localized the glycosylation site and characterized CDRs, providing an overall 60% sequence coverage on an IgG1 in a single LC-MS/MS run and up to 77% in combined four LC-MS/MS runs collected with varied laser parameters (67). Combining the results from UVPD and ETD techniques the sequence coverage reached 72% for adalimumab and 74% for trastuzumab, further supporting the use of multiple MS/MS methods (#2.8 in Table 2 and Figs. 3–5). Recently, sequence coverages of up to 97.1% for infliximab and 80.2% for cetuximab IgG1 were achieved using solely UVPD MS/MS on an Orbitrap Fusion Lumos instrument (68). In the latter study, Wang and colleagues improved sequence coverage by combining product ions generated from 13 separately isolated precursor charge states, each fragmented with UV pulse energy optimized for its charge state. These results demonstrate the benefit of combining product ions from multiple precursor charge states (#2.30 in Table 2 and Figs. 3–5). The main drawback of UVPD is the variety of product ions that can be formed (a, b, c, x, y, z, w, and v-types) (28), which complicates a confident assignment.

## Integrating TD and MD MS Workflows

In 2018, Kelleher's group combined three activation techniques: UVPD, ETD, and EThcD, for the MD-MS analysis of rituximab. Specifically, by employing TD MS analysis with UVPD and ETD, and MD MS on KGP or IdeS-generated subunits utilizing UVPD, ETD, and EThcD, they achieved a 90% sequence coverage (#1.8 in Table 1 and Figs. 3–5).

Integrating TD and MD MS not only enabled comprehensive sequence coverage and PTM mapping comparable to bottom-up strategies but also provided more profound insights into rituximab's structure, including CDRs pairing, chain pairing, and intact mass, which are not accessible after extensive proteolysis (38). The confidence of these results was claimed to be ensured by maintaining a 10-ppm mass accuracy for product ion annotation, followed by isotopic fitting and manual curation of all the mismatched isotopic distributions.

In 2019, Ying Ge and colleagues conducted a comprehensive TD and MD-MS analysis of the SiLuLite mAb (Sigma mAb) (36). Using a high-resolution 12 T FT-ICR MS (SolariX XR, Bruker Daltonics), they performed a bird's eye view analysis of all proteoforms, achieving isotopic resolution for all IgG1 proteoforms. The latter is particularly impressive considering the 150 kDa MW of these species. Subsequent single (isolated) charge state TD MS analysis, utilizing ECD and CID, enabled 23% sequence coverage annotation. MD MS analysis of 25 kDa subunits of the IgG1 antibody, also using ECD and CID, revealed key modifications, including C-terminal amidation, C-terminal glycine clipping, and proline amidation. Together, the TD and MD-MS analyses resulted in 76% sequence coverage (#1.10 in Table 1 and Figs. 3–5).

## Innovations in Instrumentation and Workflow Optimization

In 2018, Voinov's group applied a hybrid ECD setup, combining UVPD and HCD (ECuvPD, EChcD) on a modified Orbitrap MS to analyze SiLuLite subunits. Antibody subunits were generated by IdeS digestion and disulfide bond reduction with DTT (69). The unique MS setup included an electromagnetostatic E x D cell (e-MSion Inc., Corvallis, Oregon) and a modified HCD cell enabling UVPD. ECD, ECuvPD, and EChcD were used to fragment the preselected 20+, 25+, and 24+ charge states of the Lc, Fc/2, and Fd subunits, respectively. All major types of product ions were formed and searched with 5 ppm mass accuracy. ECD and ECuvPD produced comparable results for each subunit and showed better performance than EChcD across all subunits. An overall sequence coverage of 86% was achieved in a single LC-MS/MS experiment (#2.14 in Table 2 and Figs. 3–5). As with UVPD, caution is advised when interpreting these results, given the inherent challenges in confidently assigning numerous product ion types. This MS setup was also used in TD/MD MS study of trastuzumab conducted by the Voinov and Shaw groups, mentioned in the TD MS chapter (#1.12 in Table 1 and Figs. 3–5) (43). Similarly, Stafford and colleagues demonstrated ECD-induced Lc cleavage from intact infliximab using an Agilent Q-TOF MS equipped with the E x D cell (70).

The field asymmetric ion mobility spectrometry (FAIMS) was added as a separation method for MD-MS of mAbs in 2019. Kelleher and colleagues utilized the FAIMS fractionation method to reduce the complexity of proteoform mass spectra and enhance the antibody sequence coverage (71). The
reduced NIST mAb standard was analyzed using an Orbitrap Eclipse Tribrid equipped with FAIMS by applying multiple fragmentation techniques. A cumulative sequence coverage of approximately 50% was achieved through the application of HCD, CID, ETD, and UVPD dissociation methods on the Lc and HCD, CID, ETD, and EThcD on the Hc (#2.15 in Table 2 and Figs. 3–5). The annotation included all types of product ions: c- and z-ions, b- and y-ions, and a- and x-ions. Beyond sequence annotation, this study also identified the most abundant proteoforms observed in the NIST mAb standard, such as pyroglutamic acid and N-linked glycan G1F post-translational modifications.

One of the key limitations of dissociation methods in TD and MD-MS is the generation of charge-reduced but undissociated complexes, which congest the mass spectra, increase the baseline, and hinder product ion identification. Voinov's and Shaw's groups observed that conducting TD-MS analysis in native mode helps mitigate spectral congestion, as native antibody conformations adopt lower charge states (43). Alternatively, Brodbelt's group implemented gas-phase proton transfer charge reduction (PTCR) to reduce the charge states of product ions, thereby dispersing their distribution across the mass spectrum and improving the identification of antibody fragments (72). In the UVPD/PTCR MD-MS analysis performed by Brodbelt group, the precursor ion was first subjected to UVPD, after which a selected group of product ions was isolated, subjected to PTCR, and then analyzed in the Orbitrap mass analyzer. This process was iteratively applied to cover congested spectral regions, ultimately achieving 74% sequence coverage for the Lc of an ADC with a single payload (#2.17 in Table 2).

The benefits of the combined use of PTCR with CID and ETD MD MS analysis were also highlighted in a large interlaboratory study focused on mAb characterization (14). Notably, one of the most comprehensive sequence coverages was achieved, with 86% for the Lc and 66% for the Fd' subunits of trastuzumab, and 76% for the Fd' subunit of the NIST mAb by combining CID and ETD, both enhanced by PTCR (#2.18 in Table 2). These fragmentation reactions were performed in the linear ion trap followed by product ion detection in a high-resolution ICR cell of the 21 T LTQ FT-ICR MS platform with prior LC separation.

Neusüß and colleagues developed a two-dimensional fractionation strategy using capillary electrophoresis to reduce the complexity of mass spectra and effectively characterize minor fragments of the NIST mAb (73). Their analysis of the reduced antibody was conducted using an on-line CE(SDS)-CZE-MD MS platform, using HCD, ETD, and UVPD. As a result, they achieved an overall sequence coverage of 64% for the Lc of the NIST mAb (#2.22 in Table 2).

Chamot-Rooke's group conducted approximately 200 MD MS experiments to determine the optimal combination of MS parameters, such as precursor ion charge state, activation technique and level (energy or time), and the number of

technical replicates (74). They achieved 60% sequence coverage for both reduced NIST mAb and SiLuLite (Sigma mAb) by combining the results from their three best experiments, which included two EThcD experiments and one HCD experiment (#2.23 in Table 2 and Figs. 3–5). This work highlights the importance of selecting precursor ions in several charge states in MD MS analysis for two key reasons: i) targeting different precursor charge states can yield complementary sequence information by activating distinct fragmentation pathways; and ii) multiplex selection reduces the number of experiments required to obtain optimal sequence coverage.

Expanding instrumentation options, the Sciex and GSK teams demonstrated the effectiveness of the ZenoTOF 7600 (Sciex), a quadrupole TOF MS equipped with a proprietary ECD (EAD) cell, for the MD MS analysis of a biotinylated, goat-derived antihuman GSK mAb (75) (#2.24 in Table 2, Figs. 3, and 4). By combining CID and ECD techniques, they achieved 49% sequence coverage and established a linear dynamic range of 2 – 50 µg/ml, enabling accurate quantitation of the intact antibody spiked into serum.

One of the latest studies from Fornelli and colleagues set a new benchmark in the MD-MS antibody analysis, achieving a 94.2% sequence coverage of the NIST mAb (#2.25 in Table 2 and Figs. 3–5) (76). This work employed Orbitrap Eclipse (Thermo Fisher Scientific) equipped with an ETD/PTCR source and high mass range option to conduct the ETD, HCD, EThcD MS/MS, and corresponding PTCR-MS³ analysis. The MD MS method developed for the NIST mAb was validated across different antibody subclasses using SiLuLite mAbs (IgG1 and IgG4). This report highlighted three important aspects and developments in PTCR MD-MS. First, all MS1, MS/MS, and MS³ were recorded in the Orbitrap analyzer. Whereas the total ion charge remains similar between MS1 and MS/MS, the PTCR-based MS³ substantially reduces the number of charges by deprotonation. It is crucial to control the number of charges (ions) introduced into the Orbitrap, as space-charge effects—proportional to the number of charges injected – result in peak interference and mass shift. To address this, the researchers measured a total ion current (TIC) directly in the Orbitrap to estimate the actual number of charges. Second, the MS/MS and MS³ spectra were recorded at a high resolution of 240,000 (at *m/z* 200), allowing for the confident identification of ion clusters that were detected but unassigned at lower resolution, leading to increased sequence coverage. Third, spectral decongestion improved the confidence in ion matching, reduced assignment ambiguity, and minimized false positive product ion identifications.

In their subsequent study, Fornelli's group applied this optimized MD MS workflow to ADCs, incorporating UVPD alongside the previously employed fragmentation techniques (77). The combination provided over 79.5% sequence coverage for Fd subunits carrying one or two payloads (#2.26 in Table 2).
<table><caption>TABLE 3
Application of TD/MD/BU methods for MS analyses of mAbs in complex mixture or clinical samples</caption><thead><tr><th>#</th><th>Application</th><th>mAb (antigen)</th><th>MS approaches</th><th>MS/MS method</th><th>Instrument</th><th>Sequence coverage</th><th>Ref.</th></tr></thead><tbody><tr><td>3.1</td><td>Characterization of the stoichiometry of the Fab-antigen complex</td><td>Fab-1-VEGF</td><td><strong>Native MD</strong><br><strong>MD (DTT)</strong></td><td>CID, ECD, and IRMPD</td><td>12 T SolariX XR FT-ICR MS and maXis 4G Q-TOF MS (Bruker Daltonics)</td><td>N/A</td><td>Zhang et al. 2016 (79)</td></tr><tr><td>3.2</td><td>Method development for analysis of IgGs spiked in human serum</td><td>Eculizumab, Rituximab, Vedolizumab, Infliximab, Adalimumab</td><td><strong>MD</strong><br>IdeS</td><td>CID; ETD</td><td>21 T LTQ FT-ICR MS (NHMFL)</td><td>33-50% (Lc)</td><td>He et al. 2017 (65)</td></tr><tr><td>3.3</td><td>Method development for analysis of the endogenous mIgs from the serum of patients with AL amyloidosis or multiple myeloma</td><td>Endogenous mIgs</td><td><strong>MD</strong> (IdeS + TCEP)</td><td>CID, ETD</td><td>21 T LTQ FT-ICR MS (NHMFL)</td><td>72% (Lc)</td><td>He et al. 2019 (93)</td></tr><tr><td>3.4</td><td>Characterization of the Igs from the serum of patients with systemic lupus erythematosus</td><td>12 standard Fabs Endogenous mIgs</td><td><strong>MD</strong> (papain + TCEP)</td><td>CID, HCD, and ETD</td><td>LTQ Orbitrap Velos Pro (TFS)</td><td>67% (Lc)<br>40% (Fab)</td><td>Wang et al. 2019 (91)</td></tr><tr><td>3.5</td><td>Characterization of the drug conjugation sites on a site-specific ADC</td><td>CBW-03-106 DAR4</td><td><strong>MD</strong> (IdeS + DTT)</td><td>HCD, ETD, UVPD</td><td>Orbitrap Fusion Lumos (TFS)</td><td>74%</td><td>Hernandez-Alba et al. 2019 (80)</td></tr><tr><td>3.6</td><td>Characterization of average DAR, positional isomers, conjugation sites, occupancy, and micro-variants for cysteine and lysine conjugated ADCs</td><td>Brentuximab -vedotin, Ado-trastuzumab - emtansine</td><td><strong>MD</strong> (IdeS + DTT or KGP + DTT)</td><td>ETD</td><td>maXis II ETD Q-TOF MS (Bruker Daltonics)</td><td>35%</td><td>Chen et al. 2019 (81)</td></tr><tr><td>3.7</td><td>Characterization of DAR and drug conjugation sites for an IgG1-based ADC</td><td>IgG1 based (AbbVie)</td><td><strong>BU</strong><br><strong>MD</strong> (IdeZ + TCEP)</td><td>HCD<br>UVPD, ETD, EthcD</td><td>LTQ Orbitrap Elite (TFS)<br>Orbitrap Fusion Lumos (TFS) equipped with a 193 nm excimer laser (Coherent ExciStar XS)</td><td>97%<br>~72% (Fab w/o payloads)</td><td>Watts et al. 2020 (82)</td></tr><tr><td>3.8</td><td>Analysis of the antibody-antigen interaction related to the influenza virus</td><td>D1 H1-17/H3-14 IgG mAb and influenza A hemagglutinin (HA)</td><td><strong>Native TD</strong> (amidase PNGase F)</td><td>HCD, UVPD</td><td>Q Exactive UHMR Orbitrap (TFS) equipped with a 193 nm ArF excimer laser (Coherent ExciStar XS)</td><td>UVPD - 42% (39% mAb & 49% HA1)</td><td>Mehaffey et al. 2020 (83)</td></tr><tr><td>3.9</td><td>Characterization of DAR, aa sequence and drug conjugation sites for cysteine-linked ADC</td><td>cysteine-linked ADC (AbbVie)</td><td><strong>MD</strong> (DTT)</td><td>CID</td><td>12 T SolariX XR FT-ICR MS (Bruker Daltonics)</td><td>52% (Lc0)<br>(7 runs)</td><td>Larson et al. 2020 (84)</td></tr></tbody></table>
<table><caption>TABLE 3—Continued</caption><thead><tr><th>#</th><th>Application</th><th>mAb (antigen)</th><th>MS approaches</th><th>MS/MS method</th><th>Instrument</th><th>Sequence coverage</th><th>Ref.</th></tr></thead><tbody><tr><td>3.10</td><td>Characterization of DAR, aa sequence and drug conjugation sites for cysteine-linked ADC</td><td>NIST mAb cysteine-linked ADC (AbbVie)</td><td>nTD</td><td>CID (MS<sup>2</sup> and MS<sup>3</sup>)</td><td>timsTOF Pro (Bruker Daltonics)</td><td>6.1% (Lc)</td><td>Larson et al. 2021 (85)</td></tr><tr><td>3.11</td><td>Characterization of the Fab (IgG1) from plasma of healthy donors and septic patients</td><td>Endogenous IgG1</td><td>MD and BU (IgdE and TCEP)</td><td>HCD or ETD</td><td>Orbitrap Fusion Lumos and Q Exactive HF-X Orbitrap (TFS)</td><td>100% (Fab) (BU &amp; MD)</td><td>Bondt et al. 2021 (94)</td></tr><tr><td>3.12</td><td>Characterization of the Lcs (IgGs) from the urine of patients with multiple myeloma</td><td>Endogenous Lc antibodies</td><td>TD and BU (with/without TCEP)</td><td>HCD, CID, EthcD, and UVPD</td><td>Q Exactive Plus and Orbitrap Fusion Lumos (TFS)</td><td>MD – 89% (Lc) – 12 runs<br>BU – 100% (Lc)</td><td>Dupre et al. 2021 (96)</td></tr><tr><td>3.13</td><td>Characterization of M-protein in the serum of kidney transplant patients</td><td>M-protein</td><td>MD and BU (IgdE + TCEP)</td><td>BU – HCD and EthcD; MD – EthcD</td><td>Orbitrap Fusion or Lumos (TFS)</td><td>43% (Fab)</td><td>Peng et al. 2023 (95)</td></tr><tr><td>3.14</td><td>Conducting pharmacokinetic studies of pembrolizumab spiked in mouse plasma</td><td>Pembrolizumab</td><td>MD (PNGase F, IdeS or IdeS + TCEP)</td><td>HCD or EthcD</td><td>Orbitrap Eclipse and Orbitrap Exploris 480 (TFS)</td><td>55% (with Eclipse at 100 µg/ml)</td><td>Dhenin, Lafont, et al. 2023 (92)</td></tr><tr><td>3.15</td><td>Method development for ADC analysis, including sequencing and characterization of drug conjugation sites</td><td>Trastuzumab deruxtecan</td><td>MD (IdeS + DTT)</td><td>CID, ETD, EthcD with PTCR</td><td>Orbitrap Eclipse (TFS)</td><td>100% (all methods + internal product ions)<br>50% (EthcD with PTCR)</td><td>Beaumal et al. 2024 (86)</td></tr><tr><td>3.16</td><td>Characterization of aa sequence and drug conjugation sites for single-domain ADC (sdADC)</td><td>anti EGFR sdADC</td><td>MD (DTT)</td><td>ETD, HCD, and 213 nm UVPD</td><td>Orbitrap Eclipse (TFS)</td><td>87% (sdADC)</td><td>Benazza et al. 2024 (87)</td></tr><tr><td>3.17</td><td>Glycosylation profiling and structural analysis of glycans of glycoengineered mAb</td><td>Glycoengineered SiLuLite, trastuzumab and rituximab</td><td>TD</td><td>MALDI-ISD, CID</td><td>15 T solarix 2xR FT-ICR MS equipped with a CombiSource and a ParaCell (Bruker Daltonics)</td><td>MS/MS glycan release</td><td>Senini et al. 2024 (90)</td></tr><tr><td>3.18</td><td>Glycosylation and glycoproteoform profiling</td><td>recombinant IgA1</td><td>Native TD and BU</td><td>BU (HCD, EthcD) Native (ECCR)</td><td>Q Exactive UHMR Orbitrap (TFS)</td><td>Glycoproteoform characterization</td><td>Peris-Diaz et al. 2024 (89)</td></tr><tr><td>3.19</td><td>Payload quantification</td><td>ADC2 DAR4, ADC2 DAR8, trastuzumab emtansine</td><td>MD</td><td>CID</td><td>ZenoTOF 7600 (Sciex)</td><td>Payload release</td><td>Yuan et al. 2024 (88)</td></tr></tbody></table>

Definitions and abbreviations are as in Table 1.
BEYOND THE ANALYSIS OF PURIFIED ANTIBODIES

Figure 5 provides a mAb-centric summary of sequence coverage values (%) reported in Tables 1, 2, Figures 3, and 4. Owing to advancements in TD and MD MS, the research community became better equipped to address complex biological questions. These include the analysis of antibodies in biological fluids, comprehensive proteoform profiling, PTM localization, and the characterization of emerging modalities, including BsAbs and ADCs. The studies conducted to date in these areas are reviewed in the following section.

Analysis of ADCs

ADCs combine the precision of antibodies with the potency of cytotoxic drugs, allowing for targeted destruction of cancer cells while sparing healthy tissue. This targeted approach enhances treatment effectiveness and reduces systemic toxicity, making ADCs a promising class of therapeutics that need to be characterized with high precision (78).

In 2016, Gross's group, in collaboration with researchers from Roche Group, analyzed structural aspects of the Fab-antigen complex using native TD-MS and denaturing MD-MS (#3.1 in Table 3) (79). The study confirmed a 2:2 binding stoichiometry between VEGF dimers and Fab-1, previously observed through X-ray crystallography. The locations of surface-exposed and flexible regions within the structure were identified through CID, ECD, and infrared multiple photon dissociation (IRMPD) MS/MS analyses. Specifically, CID was shown to facilitate desolvation, whereas ECD induced backbone cleavages to reveal flexible regions, and IRMPD generated product ions that remained bound in product ion complexes after ECD. The information obtained is valuable as a complement to X-ray crystallography, as flexible regions often complicate the crystallization process.

Important features to characterize in ADCs are the drug-to-
antibody ratios (DARs) as well as the payload location (if
possible). In 2019 Cianferani and colleagues analyzed DAR4
ADC complexes using MD-MS on the Orbitrap platform
combining HCD, ETD, and UVPD (80). Their study demon-
strated that UVPD, when used as a standalone method, out-
performed both HCD and ETD, not only in terms of overall
sequence coverage but also in the identification of drug and
glycosylation binding sites. By integrating the results from
these three activation techniques, the overall sequence
coverage of the ADC reached 74% (#3.5 in Table 3).

In the same 2019, the Ge group employed MD-MS with
ETD-enabled Q-TOF MS to assess multiple quality attributes
of two ADC variants: cysteine-conjugated brentuximab
vedotin (BV) and lysine-conjugated ado-trastuzumab emtan-
sine (T-DM1) (81). The ADCs were digested with IdeS and
subjected to disulfide bond reduction, generating seven
distinct subunits: Fc/2, Lc without drug (Lc0), Lc with one drug
(Lc1), and Fd' subunits conjugated with 0 to three drug mol-
ecules (Fd'0-Fd'3). The average DAR values were calculated

as 4.0 for BV and 3.5 for T-DM1. Sequence coverage for the
fully reduced subunits was approximately 35% (#3.6 in
Table 3). Given the small size of the drugs relative to the
antibody subunits, similar ionization efficiency was observed
between conjugated and unconjugated forms, enabling ac-
curate calculation of the relative proportions of drug-
conjugated subunits. Additionally, ETD applied to partially
reduced subunits enabled the resolution of positional isomers,
allowing precise localization of conjugation sites and deter-
mination of their relative abundance.

The group of Brodbelt, in collaboration with AbbVie, also studied IgG1-based ADC using MD-MS by combining UVPD, ETD, and EThcD techniques (82). While bottom-up MS analysis verified 97% of mAb sequence coverage (#3.7 in Table 3), it provided limited information about payload sites, with a few peptides containing payload identified. The MD MS analysis of seven ADC subunits obtained after digestion with IdeZ (a cysteine enzyme that cleaves mouse IgG2 and IgG3 below the hinge region) and reduction of disulfide bonds, yielded 74% sequence coverage. Among the methods, UVPD was found to generate the highest number of unique product ions, whereas ETD and EThcD yielded complementary product ions essential for accurate payload site determination, particularly in subunits with heterogeneous payload distribution. C-terminal ions carrying the payload were critical for confirming its location. Yet, the abundance of these ions decreased as more payloads were added to the subunits, likely due to truncation of the payload during MS/MS analysis, leading to unassignable product ions. Thus, combining these complementary activation methods produced a diverse set of C-terminal ions, facilitating the localization of payload conjugation sites.

Extending their exploration of antibody applications, Brodbelt's group also utilized native TD MS to investigate antibody-antigen interactions, combining HCD and UVPD to analyze the D1 H1-17/H3-14 antibody, which targets hemagglutinin (HA), a key antigen of the influenza virus (83). As expected, UVPD significantly outperformed HCD in sequence coverage, achieving 60% compared to 27% (#3.8 in Table 3). When analyzing the Ab-2HA1 complex, both activation methods produced lower sequence coverage for HA1 compared to its unbound form. Nevertheless, the presence of HA did not markedly affect sequence coverage of either antibody chain. Notably, UVPD produced only b- and y-type ions within the epitope regions of the bound complex, whereas in the unbound antibody, a more diverse array of fragment ions - including a/x, b/y and c/z types - was observed.

Ge's group, also in collaboration with AbbVie, conducted a
series of studies on cysteine-linked ADCs using both MD and
TD-MS approaches. In one study, they applied CID-based
MD-MS to reduced ADCs, using a 12 T FT-ICR MS (SolariX
XR, Bruker Daltonics), and combined product ions from seven
experiments with varying collision energies to achieve 52%
sequence coverage of the unconjugated light chain (Lc0) (#3.9
in Table 3) (84). Within a one-hour analysis time, approach provided information about DAR, primary sequence, and localization of drug conjugation sites.

In a subsequent study, the Ge team employed native TD-MS using a high-resolution trapped ion mobility spectrometry TOF MS (timsTOF Pro, Bruker Daltonics) to rapidly assess key ADC quality attributes (85). Within only 10 min of direct injection, ion mobility separation effectively resolved all DAR species, facilitated calculation of average DAR values, and detected low-abundance species such as DAR eight in the MS1 scan. Notably, the study revealed conformational changes induced by drug conjugation: the ADC structure became more compact compared to the unconjugated mAb, and higher drug loads correlated with increased collision cross section values. To further dissect structural details, an isCID-based MS/MS approach was used to dissociate non-covalently linked subunits, followed by CID-based MS³ on the isolated Lc with one payload (Lc1), achieving 6.1% residue cleavage (#3.10 in Table 3). These results highlight the potential of MS³-based approaches to perform deep sequencing of the ADC and represent a promising direction for future TD/MD MS method development.

## Advanced Workflows and Emerging ADC Modalities

Further advancing the field, Hernandez-Alba and colleagues applied TD and MD MS to study both conventional and single-domain ADCs (sdADCs). Their first investigation focused on trastuzumab deruxtecan, a therapeutic site-specific ADC (86). The team integrated intact MS with advanced MD MS techniques, including PTCR and internal product ion analysis. Adding PTCR after subunit fragmentation improved spectral clarity and enhanced product ion detection in congested regions by 1.5- to 2.5-fold, leading to a sequence coverage increase of 2% to 13% and an overall coverage of up to 87% (#3.15 in Table 3). Whereas internal product ion analysis presumably allowed full sequencing of the Fc/2, Lc, and Fd' subunits, it provided limited contribution to localizing the payload attachment, which was situated at the C-terminus.

Their second study focused on sdADCs—compact therapeutic constructs derived from Fd' subunits (87). Both TD and MD MS analyses were conducted using HCD, ETD, and UVPD. For non-reduced sdADCs, the sequence coverage was approximately 33%, whereas reduction of disulfide bonds improved sequence coverage to 85% (#3.16 in Table 3). In this instance, HCD was particularly informative for identifying the conjugation site, outperforming ETD and UVPD. This advantage was attributed to the C-terminal location of the conjugation site, which is easily accessible to HCD, and to the preservation of the attached drug molecule during fragmentation.

Finally, Rosenbaum and colleagues demonstrated the application of MD MS for analyzing payload release from ADCs spiked into plasma samples (88). Using a digestion-free workflow on a 7600 ZenoTOF MS (Sciex), they employed CID

to selectively dissociate the payload by applying optimized collision energies. This approach enabled quantification of ADCs based on characteristic MS/MS product ions derived from the payload (#3.19 in Table 3). Notably, the method proved effective for a range of linker-payload designs, including ADCs with non-cleavable linkers such as trastuzumab emtansine, underscoring its versatility for accurate ADC quantification in complex biological matrices.

## Novel Approaches to Glycosylation Analysis

The Heck group conducted a comprehensive analysis of the N- and O-glycosylation sites and glycoproteoforms of recombinant IgA1, an antibody characterized by extensive glycan heterogeneity due to multiple glycosylation sites (#3.18 in Table 3) (89). To achieve this, they applied both (glyco) peptide-centric and protein-centric mass spectrometry workflows, enabling the assignment of individual N- and O-glycosylation sites and the characterization of intact glycoproteoforms. In addition to classical bottom-up MS profiling, native MS was used to assess the intact glycoproteins, revealing highly congested mass spectra due to glycoform heterogeneity. To address this spectral complexity, native top-down MS employing electron-capture charge reduction (ECCR) was implemented. In ECCR, highly charged proteins interact with free electrons without undergoing fragmentation, effectively reducing charge states and shifting ions to higher *m/z* ranges - functionally analogous to PTCR. By performing “sliced” ECCR experiments, which involve sequential selection of narrow *m/z* windows across the native mass spectrum, the researchers identified asymmetrical N-glycan occupancy across the IgA1 molecule.

In 2024, Nicolardi and colleagues performed a detailed profiling of a glycoengineered mAb using TD MS with MALDI-ISD on a 15 T FT-ICR MS (90). The key innovation of this work is the direct characterization of glycosylation without the need for preliminary enzymatic glycan release. The MALDI matrix containing sodium selectively suppressed signals from product ions, which are more effectively detected as protonated ions rather than sodiated ions. This suppression improved the detection of glycans removed from the mAbs by ion activation and dissociation. The method allowed for identifying low-abundance glycoforms, such as the Man5/Man5 variants in SiLuLite mAb and rituximab, which are typically challenging to detect (#3.17 in Table 3). Notably, while these minor glycoforms had been previously detected by intact mass analysis, that approach required signal averaging of unreduced Orbitrap transients across multiple LC-MS runs (14). Additionally, Nicolardi and colleagues utilized CID to offer insights into the monosaccharide composition of the selected glycans enhancing the depth of glycosylation analysis.

## Antibody Mixture Analysis

An ETD-based MD-MS analysis of two simple antibody mixtures using an LTQ Orbitrap Elite instrument was reported
by Tsybin's group in 2014, later peer-reviewed in 2022 (17). Both mixtures were compiled of 50 kDa Fab subunits obtained by papain digestion: one from a two-antibody combination (IgG1 trastuzumab and rituximab), and another from a three-antibody set comprising trastuzumab (IgG1), adalimumab (IgG1), and natalizumab (IgG4). The study demonstrated high complexity of antibody mixture analysis, even at their subunit level and with only a few subunits present in the mixture. Indeed, baseline separation of the three Fab subunits with RPLC was not achieved, presumably due to their similar hydrophobic properties. Nevertheless, it was possible to isolate a group of three charge states per Fab, enabling the acquisition of good quality ETD MS/MS data. Although sequence coverage was limited, around 15% for both the Lc and Fd subunits forming the Fab, the results were sufficient to detect internal product ions indicative of heavy-light chain pairing. In case of trastuzumab and rituximab, co-elution prevented isolation of individual charge states. Nevertheless, ETD-based MD MS following co-isolation of several charge states from both Fabs resulted in unique product ions that covered the CDR3, supporting chain pairing analysis via internal (branched) product ions.

In 2017, Marshall and colleagues successfully identified five antibodies spiked in a serum sample (65). The MD MS analyses were performed using an LC system coupled with a custom-built 21 T FT-ICR mass spectrometer (NHMFL) with fragmentation by CID and ETD. The combined product ions resulted in Lc sequence coverages of 33%, 37%, 42%, 47%, and 50% for eculizumab, rituximab, vedolizumab, infliximab, and adalimumab, respectively (#3.2 in Table 3). Interestingly, the data showed greater mass error for product ions than precursor ions, with values ranging from 0.2 to 0.4 ppm for precursor ions compared to 2.9 to 4.7 ppm for product ions. Further analysis indicated that deconvolution introduced a 3- to 5-fold increase in mass error, highlighting a limitation of some current deconvolution algorithms—particularly those based on the averagine model.

Extending the application of TD MS to more complex mixtures, Wu and colleagues optimized an ultra-high-pressure (UHP)LC TD MS platform and applied it to analyze a mixture of 12 standard monoclonal antibody Fab fragments (91). The combination of CID, HCD, and ETD methods resulted in an average sequence coverage of 67% for the Lc and 40% for the Fd' subunits (#3.4 in Table 3). The confidence of these product ion annotations was manually verified and confirmed. This optimized (UHP)LC TD MS platform was subsequently employed to characterize auto-antibodies in human serum from a patient with systemic lupus erythematosus, successfully identifying 47 unique light chains and 16 Fd' subunits.

In collaboration with Sanofi, Chamot-Rooke's group addressed another problem in antibody analysis, such as the *in vivo* stability of antibodies (92). To achieve this, pharmacokinetics studies were conducted by spiking pembrolizumab into mouse plasma at concentrations ranging from 0.5 to

100 µg/ml, followed by automated immunocapture and analysis using TD and MD MS. Two cutting-edge Orbitrap platforms, the tribrid Orbitrap Eclipse and Orbitrap Exploris 480, were employed for the study. At a 100 µg/ml concentration, a maximum sequence coverage of 55% for pembrolizumab was achieved using the Orbitrap Eclipse (#3.14 in Table 3). Overall, the ETD-equipped Eclipse outperformed the HCD-equipped Exploris 480 in sequence coverage (62% vs. 28%), primarily due to the contributions of EThcD. However, sequence coverage decreased more rapidly with decreasing pembrolizumab concentration in the Orbitrap Eclipse platform, yielding exploitable results only down to 5 µg/ml. In contrast, HCD-based Exploris 480 analysis was less sensitive to antibody concentration, maintaining performance at lower concentrations.

## Antibody Repertoire Analysis

One of the first MD MS studies of antibody repertoire was reported by the Marshall group in 2019 (#3.3 in Table 3). It focused on analyzing endogenous antibodies in human serum samples by employing an LC system coupled with a custom-built 21 T FT-ICR MS (NHMFL) with fragmentation by CID and ETD (93). The main challenge was the reliable identification of antibody sequences in the absence of corresponding database entries, particularly those associated with diseases like amyloidosis and multiple myeloma. To address this, the authors developed a database-aided *de novo* sequencing approach. This approach first identified homologous antibody regions through database searches, then applied *de novo* sequencing to determine the short variable regions. This was achieved by comparing observed mass differences to an accurate mass database of 1 to 4 amino acid residues, using a 10-ppm mass error threshold.

In 2021, Heck and colleagues conducted a detailed qualitative and quantitative analysis of Fab subunits from endogenous IgG1 antibodies in human plasma from healthy donors and septic patients (94). Despite the immense theoretical diversity of human immunoglobulins, presumably extending beyond 10¹⁵, the study identified between 35 and 543 distinct IgG1 clones per sample, with a median of 196 dominant clones. For quantification, two monoclonal IgG1 antibodies at known concentrations were spiked into each sample. This revealed that the top 30 most abundant clones accounted for a median 71.8% of the total IgG1 molecules detected. The analysis of the most abundant clone was carried out using both bottom-up MS and MD-MS approaches. The bottom-up MS alone was insufficient for full sequence identification due to interference from co-isolated peptides derived from other plasma clones. Thus, researchers iteratively extended the sequence information obtained from the MD-MS approach with the *de novo*-identified peptides from the bottom-up MS approach. This integrative approach enabled complete sequence coverage of the endogenous IgG1 clone (#3.11 in Table 3).
This landmark study on antibody analysis using MS methods was followed by the analysis of M-protein (antibody) sequences directly from the blood of kidney transplant patients (95). Similar to the previous research, peptide de novo sequencing from bottom-up MS was validated using native MS and MD LC-MS/MS. ET hcD-based MD-MS analysis of the Lc and Fd' subunits yielded 43% sequence coverage (#3.13 in Table 3). During the Fab analysis, an unusual antibody profile was discovered in one of the patient samples: the IgG1 repertoire was dominated by a small number of highly abundant clones with elevated molecular masses. MS data provided detailed information into the glycosylation of the Fab region, including both the site and composition of glycan modifications on the Hc of the M-protein. Based on these data, combined with clinical assays such as serum immunofixation, a diagnosis of monoclonal gammopathy of undetermined significance was made, potentially avoiding the need for a bone marrow biopsy.

During the same 2021, Chamot-Rooke and colleagues applied a combined MD and bottom-up MS methods to comprehensively annotate antibody's Lc from patients with multiple myeloma (96). In this disease, B-cells produce large amounts of monoclonal Lcs and intact IgGs, resulting in a highly diverse Lc repertoire driven by somatic recombination and various mutations. The combined MD-MS and bottom-up MS-based workflow began with intact mass profiling, peptide-level de novo sequencing using multiple enzymes and bottom-up MS. Subsequent MD-MS analysis of disulfide-reduced subunits was used to define proteoform structures, which were further validated by bottom-up MS, including differentiation between Ile and Leu amino acids. MD MS analysis performed on an Orbitrap Eclipse platform, integrating results from multiple fragmentation methods (HCD, CID, ET hcD, and UVPD), enabled the researchers to achieve an 89% sequence coverage and identify 470 product ions (#3.12 in Table 3). The authors reported the discovery of a novel PTM, which appeared to result from the patient's treatment with a small-molecule chemotherapy adjuvant. Overall, 10 different Lc antibodies were characterized, demonstrating the effectiveness of the workflow.

OVERVIEW AND OUTLOOK

This comprehensive review of TD and MD-MS for antibody analysis provides an up-to-date overview of the literature and highlights the remarkable progress achieved over the past 30 years. The following sections first overview the key technical and methodological advancements that have shaped the field. This is followed by an outlook on emerging trends in sample preparation, instrumentation, ion activation and fragmentation strategies, and data analysis. While not exhaustive, this outlook presents selected examples that point toward promising directions for the continued evolution of TD/MD MS in antibody characterization.

Progress in TD/MD MS for Antibody Characterization

From an analyte perspective, the majority of studies have focused on IgG1 as a model antibody, owing to its widespread use in therapeutic applications and well-characterized structure, Figure 5. To date, TD/MD MS analyses with reported sequence coverage have been described in the peer-reviewed literature for the following IgGs: eight IgG1s (adalimumab, bevacizumab, cetuximab, infliximab, NIST mAb, rituximab, SiLuLite, and trastuzumab), one IgG2 (panitumumab), and two IgG4s (natalizumab and SiLuLite K4). Among these, trastuzumab has been the most extensively studied antibody with TD/MD MS, followed by adalimumab and the NIST mAb.

Sequence coverage remains the primary metric for evaluating method performance in TD/MD MS, as it reflects both the analytical complexity of the approach and the challenges associated with PTMs characterization, an aspect that could, in principle, serve as an alternative performance metric. Figures 3 and 4 illustrate the progression of TD/MD MS techniques over time, highlighting improvements in sequence coverage as a key indicator of methodological advancement. This progress is largely driven by the choice of MS/MS methods and their strategic application, such as the combination of complementary fragmentation techniques. Notably, electron-based dissociation methods, particularly ECD and ETD, have served as the foundation for TD/MD MS of antibodies. More recently, UVPD has enabled some of the most comprehensive sequencing results; however, the diversity of fragmentation pathways in UVPD necessitates careful validation of product ion assignments. Similarly, incorporating internal product ions into data analysis workflows has significantly enhanced TD/MD MS output but also requires meticulous assignment and validation. Currently, the most advanced methodologies integrate multiple MS/MS techniques with gas-phase charge reduction strategies, including ion-ion proton transfer charge reduction (PTCR) and ion-electron charge compensation reactions (ECCR) (97, 98), to further improve spectral clarity and sequence coverage.

In addition to sequence coverage and MS/MS methods, Tables 1 and 2 provide further details on the experimental workflows and techniques employed in each study. To date, the Orbitrap has been the mass spectrometer of choice for TD/MD MS of antibodies, featuring in over 60% of published studies. TOF MS and FT-ICR MS platforms have each been employed in approximately 20% of the studies. Most TD/MD MS analyses have been performed using ESI, typically *via* direct infusion under denaturing or native conditions. However, several studies have incorporated on-line separation techniques with ESI, such as micro- or nano-flow liquid LC, and, to a lesser extent, CZE. MALDI offers an attractive alternative, primarily due to its ISD capabilities, but its use in this context remains relatively limited.

TD/MD MS now supports analysis of several PTMs, such as N-terminal pyroglutamate formation and C-terminal
lysine/glycine clipping, using terminal product ions (29, 40, 51, 52). Disulfide bond mapping remains difficult, although fragmentation efficiency has been used to infer connectivity, as demonstrated in ETD-based TD MS (37) and AI-ETD studies using variable laser power and reaction times (41). More precise localization has been achieved *via* internal product ions (46) or electrochemical reduction coupled with high-resolution 15 T FT-ICR MS (48).

Oxidation detection and localization have been demonstrated using TD MS with in-source CID (pseudo-MS³) (29), and ETD-based MD MS in forced oxidation studies, particularly for methionine (52) and arginine residues (51). N-glycosylation has been detected in TD MS using AI-ETD (41) and internal product ions (46), albeit without precise site localization. In contrast, MD-MS studies have enabled both identification and localization of glycosylation sites using ETD (52), HCD with online CZE separation (51), and hybrid fragmentation techniques such as UVPD-ETD (67), CID-ETD (66), and ECD-ECuvPD-EChcD (69).

Although a broad range of applications has been demonstrated (Table 3), most of these studies have been conducted in just the past 5 years. Notably, method development has been closely linked to application-driven research, such as the analysis of complex antibody mixtures and non-standard modalities, underscoring the field's rapid evolution. These advancements have been made possible by strong collaborations between academic institutions and biopharmaceutical industry leaders, whose combined efforts have created a synergistic effect that continues to drive innovation across the field.

## Trends in Sample Preparation

Current and future developments in sample preparation for intact protein analysis and TD/MD MS have been reviewed elsewhere (99). Antibody-specific advancements include several structure-specific enzymes that specifically cleave various classes of antibodies. The recently introduced enzymes tend to complement the well-established IdeS and KGP-based workflows and to facilitate subunit separation and PTMs detection. These newer enzymes promise improved performance in mAb analysis by refining digestion workflows and reducing artifacts. Advances have also been made in chromatographic strategies tailored for antibody analysis. For instance, the integration of online hydrophobic interaction chromatography (HIC) with mass spectrometry has enabled efficient separation of intact antibodies and their multimers, while preserving non-covalent interactions (100). This development facilitates antibody complexes characterization under native-like conditions. In addition, the automated sample preparation, e.g., using the SampleStream technology (Integrated Protein Technologies Inc) (101), aims to integrate multiple steps (digestion and buffer exchange, including chemical reduction) into an automated, continuous-flow system. These recent innovations aim to minimize sample loss

and contamination and increase throughput and reliability, enabling a direct connection between sample preparation and MS, which is especially useful for large-scale mAb analysis.

## Trends in MS Instrumentation

Advances in MS instrumentation continue to drive progress in TD and MD antibody MS analysis. This is demonstrated by the highest reported 95% coverage of trastuzumab obtained using MD MS on the Orbitrap Ascend (#2.27 in Table 2 and Fig. 3) and the remarkable 64% sequence coverage achieved by HCD on the state-of-the-art Orbitrap Astral of three various antibodies (#2.28 in Table 2 and Fig. 3) (102, 103). The Orbitrap Ascend, particularly in its Structural Biology configuration, is arguably the most powerful and versatile commercially available instrument for TD/MD MS, offering ultra-high resolution, a wide mass range, and flexible multimodal MS/MS capabilities.

Currently, the two flagship FT-ICR MS instruments are a 21 T FT-ICR MS system interfaced to an Orbitrap Eclipse at NHMFL and a 21 T FT-ICR MS system interfaced to an Orbitrap Exploris 480 at PNNL. Both systems provide exceptional performance in TD/MD MS and are open to external users. The only FT-ICR MS manufacturing company, Bruker Daltonics, continues to enhance the performance of their commercial systems specifically for TD/MD MS, with the current developments aiming to integrate ion mobility, e.g., tims technology (104), into a single powerful platform.

Despite the exceptional performance of current ICR and Orbitrap FTMS platforms, there is still room for improvement in extracting maximal information from their time-domain ion signals (transients) through advanced real-time and post-acquisition processing. This potential is underscored by the demonstrated value of high-performance data acquisition systems interfaced with Orbitrap instruments (105). Post-processing approaches, such as transient averaging or selection of optimal transient lengths (78, 106), along with other strategies aimed at enhancing data quality, can significantly improve signal-to-noise ratios and resolution. Similar benefits have been observed on FT-ICR MS platforms, where external high-performance acquisition and processing systems, such as FTMS Boosters (Spectroswiss), interfaced with a 15 T FT-ICR MS (SolariX, Bruker Daltonics), have enhanced intact mass analysis of antibodies (107).

FTMS time-domain ion signals (transients) also open the door to novel ion measurement strategies, such as individual ion counting or charge detection mass spectrometry (CDMS) (108–110). In particular, Orbitrap-based CDMS offers promising capabilities for enhancing the performance of both intact mass analysis and TD/MD MS (110, 111). These advances apply not only to antibodies but also to larger biotherapeutics such as adeno-associated viruses (AAVs). AAVs consist of three viral proteins, VP1, VP2, and VP3, which range in molecular weight from approximately 60 to 80 kDa. Fornelli and colleagues applied conventional TD MS to these VP proteins
using various MS/MS techniques, achieving sequence coverages of up to 40% per protein (112).

Among recent innovations in TOF MS, the high-resolution timTOF, equipped with the multimodal MS⁴ capabilities of the integrated Omnitrap (113), is being advanced by Bruker Daltonics with a particular focus on TD/MD MS applications and is a much welcome advancement. Implementation of the Omnitrap on a high-resolution TOF MS system will expand the current offer of ECD-enabled TOF MS instruments that include a ZenoTOF MS from Sciex (55) and a 6545XT AdvanceBio LC/ Q-TOF from Agilent (70) and a SELECT SERIES Cyclic IMS TOF MS from Waters (114, 115). However, the resolution currently achievable with conventional TOF MS technology (typically up to ~100,000) may limit its utility in advanced TD/MD analyses of large proteins, including antibodies. As a result, emerging higher-resolution TOF MS instruments based on multiple ion reflections (MRT platforms), which offer resolution exceeding 100,000 across a wide mass range (116–118), are expected to become even more powerful additions to the TD/MD-MS platform landscape.

## Trends in Dissociation Techniques

In gas-phase techniques, developments in MS³ and MS⁴ approaches, which are built on sequential ion activation and dissociation schemes, offer more detailed structural insights by isolating and fragmenting ions through multiple stages (119). This increases the depth of structural information captured, especially for complex proteoforms, and enhances annotation accuracy, especially for internal product ions. The increasing use of PTCR combined with MS/MS methods, including in MS³ and MS⁴ formats, appears to be one of the main avenues for further progress in TD/MD MS development and applications. Recent studies achieved 94.2% and 95% antibody sequence coverage employing MD MS analysis with PTCR-MS³ on Orbitrap Eclipse and Orbitrap Ascend, respectively (#2.25 and #2.27 in Table 2 and Fig. 3) (76, 102). The AI-ETD-based TD MS result from Coon's group encourages current developments in the field, including the implementation of the AI-ECD approach in the Omnitrap-Orbitrap platform aiming at high-performance TD MS of proteins in mAbs subunits mass range (120). Even without supplemental ion activation with photons, the optimized Omnitrap-Orbitrap-FTMS Booster platform enabled comprehensive MD MS sequencing on a chromatographic time scale, as demonstrated in the analysis of a multiple myeloma light chain (#2.29 in Table 2) (121), achieving an exceptional ~93% sequence coverage in a single LC-MS/MS run.

## Trends in Data Analysis

On the data analysis side, the progress applies to all types of analytes and is not specific to antibody analysis. It is, however, probable that dedicated software tools for mAb analysis would significantly advance the field. Software advancements have driven the transition from manual to more

automated processing, significantly improving the accessibility, throughput, and efficiency of TD and MD-MS data analysis. Open-source tools such as ProSight Lite (122), TopPIC Suite (123), ClipsMS (124), and MASH Suite Pro (125), as well as commercial implementations of TD/MD MS workflows in ProSight PC and TDValidator (Proteinaceous), Expressionist (Genedata), OmniScape (Bruker Daltonics), BioPharma Finder (Thermo Fisher Scientific), MassHunter BioConfirm (Agilent), BioPharmaView (Sciex), Intact Mass (Protein Metrics), AutoVectis (Vibratlon), Peak-by-Peak BioPharma (Spectroswiss), and others are all critical and complementary, as they differ in the underlying algorithms and methodology.

Deconvolution methods continue to evolve, however, with most studies relying on a single algorithm. Presently, there is a trend toward integrating multiple deconvolution approaches to enhance confidence in data interpretation (126). At the same time, there is a noticeable shift in data analysis from mass spectra deconvolution to direct product ion isotopic distribution matching between the experimental and theoretical (simulated) datasets (127). Even though the validation of product ions involves stringent criteria, including mass tolerance distribution centered at 0 ppm with a standard deviation of 5 ppm, manual validation is still required to improve the reliability of the results. The latter remains challenging and not standardized. The analysis of internal product ions is gaining attention with several tools currently in development (128). However, despite their potential, internal ions annotation should be done with caution due to the vast number of theoretically possible candidates, which significantly increases the risk of false-positive product ion assignments (128). Additionally, improvements in spectral quality, particularly through improved ion detector sensitivity and higher-throughput mass analyzers, are complemented by enhanced computational abilities of modern tools. The latter can handle increasingly large sizes of mass spectral datasets, thus eliminating the need for extensive data reduction prior to data processing and analysis. For example, direct processing of transients or mass spectra acquired in full profile in Orbitrap-based TD/MD MS has proven to enhance sensitivity and annotate low-abundant product ions (50).

The enhanced spectral quality is particularly important when attempting *de novo* sequencing of antibodies in their intact or subunit form. Missing cleavage sites and relatively high mass errors may prohibit the progression of *de novo* sequencing algorithms (129). Therefore, it is not surprising that up to now only three studies have attempted protein-level *de novo* antibody sequencing, all of which remain either partial or rely on database-assisted searches (53, 56, 93). Significant advancements are still needed to automate protein-level MS *de novo* sequencing of antibodies (130, 131).

Finally, to tackle the challenges and limitations of the conventional sequencing approaches, other data analysis methods have been proposed specifically for TD/MD MS. For
<figure><img src="image_8.png" /><figcaption>**Fig. 6.** Research network graph generated based on co-authorship in TD and MD MS antibody analysis peer-reviewed publications. Each node symbolizes an individual researcher, with connecting lines indicating co-authorship links; stronger connections correspond to more frequent collaborations. A total of 62 research papers (listed in Tables 1–3) involving 319 authors were analyzed, with 80 authors contributing to at least two papers on TD and MD MS antibody analysis. Distinct colors denote clusters of closely collaborating researchers. This network was generated using VOSviewer version 1.6.20 (138).</figcaption></figure>

example, the All-Ion Differential Analysis (AIDA) method, which compares all product ions across different sample conditions (unmodified and variant) before spectral annotation, has been proposed as an alternative to classical TD/MD MS analysis (132, 133). The authors suggest that AIDA enhances TD/MD MS by characterizing sequence variations with higher sensitivity than conventional product ion annotation, enabling precise localization of modifications such as isomerization, deamidation, and oxidation in mAbs. However, they also note that AIDA may be limited by non-fragmented antibody regions and challenges in resolving multiple concomitant modifications, which could introduce biases in data interpretation (132).

Consortium for Top-Down Proteomics—A Collaborative Effort

The Consortium for Top-Down Proteomics, or CTDP (https://ctdp.org), leads efforts in standardizing protocols, ensuring that TD and MD MS approaches are robust and reproducible across different platforms (14, 134). Figure 6 describes the network of researchers involved in TD/MD MS studies and quantifies the interaction with other members

from the TD/MD MS community. Most of the researchers affiliated with CTDP are part of the largest network in the center of the visualization. Collaborative efforts like these create and offer access to large TD/MD MS databases and thus will be pivotal for integrating machine learning algorithms into data processing and further optimizing the most challenging algorithms, such as *de novo* sequencing.

Looking ahead, combining advancements in sample preparation, gas-phase methodologies, and data processing algorithms will significantly enhance the applicability of TD and MD MS in therapeutic antibody characterization in the bio-pharmaceutical industry and their acceptance among the regulatory agencies. Moreover, the increasing diversity and complexity of next-generation biotherapeutics can make them more prone to *in vivo* biotransformation than regular mAbs, which can impact both efficacy and safety. Biotransformation products are therefore now scrutinized (135, 136), which represents a new application area where improved MD and TD MS methods will be valuable.

**Acknowledgments**—The authors are grateful to many members of the TD/MD MS community for generously sharing
their expertise and enthusiasm over the years, with special thanks to Dr Luca Fornelli, Dr Kristina Srzentic, Dr Daniel Ayoub, Dr Alain Beck, and the CTDP. The authors also thank Dr Nees Jan van Eck and Dr Magnus Palmblad for their help with VOSviewer. This work was supported by the French Research Agency (ANR-23-CE44-0041, AntiboTOP project) and the European Union's Horizon 2020 Research and Innovation Program under grant no. 823839 (EPIC-XS).

**Author contributions**—L. M., A. N. K., K. D., C. G., K. O. N., M. G., N. G., J. C. R., N. A. K., and Y. O. T. writing – review & editing; Y. O. T., J. C. R., and N. A. K. writing – original draft; Y. O. T. and J. C. R. supervision; Y. O. T. project administration; Y. O. T. and J. C. R. funding acquisition; Y. O. T., J. C. R., and N. A. K. conceptualization.

**Conflict of interest**—The authors declare the following competing financial interest(s): N.A.K is an employee of Spectrotech SAS and A. N. K., K. O. N., and Y. O. T. are employees of Spectroswiss Sarl. Both companies develop and commercialize FTMS data acquisition, processing, and analysis tools.

**Abbreviations**—The abbreviations used are: ADC, antibody drug conjugate; aFT, absorption mode Fourier transform; Al-ETD, activated ion electron transfer dissociation; BsAbs, bispecific antibodies; CDR, complementarity-determining region; CHO, Chinese hamster ovary; CID, collision-induced dissociation; CQA, critical quality attribute; CTDP, consortium for top-down proteomics; CZE, capillary zone electrophoresis; DAR, drug-to-antibody ratio; DoE, design of experiment; DTT, dithiothreitol; ECD, electron capture dissociation; EAD, electron-activated dissociation; ECCR, electron-capture charge reduction; eFT, enhanced FT; ETD, electron transfer dissociation; ETcID, electron transfer collision-induced dissociation; EThcD, electron transfer higher-energy collisional dissociation; Fab, antigen-binding fragment; Fc, crystallizable fragment; FT-ICR MS, Fourier transform ion cyclotron resonance mass spectrometry; FTMS, Fourier transform mass spectrometry; Hc, heavy chains; HCD, higher-energy collision-induced dissociation; IgG, immunoglobulin G; IRMPD, infrared multiple photon dissociation; isCID, in-source collision-induced dissociation; KGP, Gingipain K; Lc, light chains; LC, liquid chromatography; LTQ, linear trap quadrupole (linear ion trap); mAb, monoclonal antibody; MALDI-ISD, matrix-assisted laser desorption/ionization in-source decay; MD MS, middle-down mass spectrometry; MS, mass spectrometry; mFT, magnitude mode Fourier transform; MS/MS, tandem mass spectrometry; MW, molecular weight; NHMFL, National High Magnetic Field Laboratory; PNNL, Pacific Northwest National Laboratory; PTCR, proton transfer charge reduction; PTM, post-translational modification; QQQ MS, triple quadrupole mass spectrometer; Q-TOF, quadrupole time-of-flight; RPLC, reversed-phase liquid chromatography; SEC, size-exclusion chromatography; TCEP, tris(2-carboxyethyl)phosphine; TD MS, top-down mass spectrometry; timsTOF, trapped ion mobility spectrometry time-of-flight; TOF, time-of-flight; UVPD, ultraviolet photodissociation.

Received January 15, 2025, and in revised form, April 19, 2025
Published, MCPro Papers in Press, May 12, 2025, https://doi.org/10.1016/j.mcpro.2025.100989

REFERENCES

1. Lu, R. M., Hwang, Y. C., Liu, I. J., Lee, C. C., Tsai, H. Z., Li, H. J., et al. (2020) Development of therapeutic antibodies for the treatment of diseases. *J. Biomed. Sci.* **27**, 1

2. Campuzano, I. D. G., and Sandoval, W. (2021) Denaturing and native mass spectrometric analytics for biotherapeutic drug discovery research: historical, current, and future personal perspectives. *J. Am. Soc. Mass Spectrom.* **32**, 1861–1885

3. Crescioli, S., Kaplon, H., Chenoweth, A., Wang, L., Visweswaraiah, J., and Reichert, J. M. (2024) Antibodies to watch in 2024. *mAbs* **16**, 2297450

4. Ladwig, P. M., Bamidge, D. R., and Willrich, M. A. V. (2017) Mass spectrometry approaches for identification and quantitation of therapeutic monoclonal antibodies in the clinical laboratory. *Clin. Vaccin. Immunol.* **24**, e00545-16

5. Schroeder, H. W., Jr., and Cavacini, L. (2010) Structure and function of immunoglobulins. *J. Allergy Clin. Immunol.* **125**, S41–S52

6. Liu, H., and May, K. (2012) Disulfide bond structures of IgG molecules: structural variations, chemical modifications and possible impacts to stability and biological function. *mAbs* **4**, 17–23

7. Robotham, A. C., and Kelly, J. F. (2020) LC-MS characterization of antibody-based therapeutics: recent highlights and future prospects. *Approaches Purification, Anal. Charact. of Antibody-Based Therap.* https://doi.org/10.1016/B978-0-08-103019-6.00001-1

8. Baah, S., Laws, M., and Rahman, K. M. (2021) Antibody-drug conjugates—A tutorial review. *Molecules* **26**, 2943

9. Goebeler, M. E., Stuhler, G., and Bargou, R. (2024) Bispecific and multispecific antibodies in oncology: opportunities and challenges. *Nat. Rev. Clin. Oncol.* **21**, 539–560

10. Snapkov, I., Chernigovskaya, M., Sinitcyn, P., Lê Quý, K., Nyman, T. A., and Greiff, V. (2022) Progress and challenges in mass spectrometry-based analysis of antibody repertoires. *Trends Biotechnol.* **40**, 463–481

11. Wang, M., Ying, T., and Wu, Y. (2024) Single-domain antibodies as therapeutics for solid tumor treatment. *Acta Pharm. Sin.* **B** **14**, 2854–2868

12. Mojumdar, A., Yoo, H. J., Kim, D. H., Park, J., Park, S. J., Jeon, E., et al. (2024) Advances in mass spectrometry-based approaches for characterizing monoclonal antibodies: resolving structural complexity and analytical challenges. *J. Anal. Sci. Technol.* **15**, 23

13. Roberts, D. S., Loo, J. A., Tsybin, Y. O., Liu, X., Wu, S., Chamot-Rooke, J., et al. (2024) Top-down proteomics. *Nat. Rev. Methods Primers* **4**, 39

14. Srzentić, K., Fornelli, L., Tsybin, Y. O., Loo, J. A., Seckler, H., Agar, J. N., et al. (2020) Interlaboratory study for characterizing monoclonal antibodies by top-down and middle-down mass spectrometry. *J. Am. Soc. Mass Spectrom.* **31**, 1783–1802

15. You, J., and Park, H.-M. (2023) Progress in top-down LC-MS analysis of antibodies: review. *Biotechnol. Bioproc. Eng.* **28**, 226–233

16. Murray, D. L., and Willrich, M. A. V. (2024) Applications of mass spectrometry proteomic methods to immunoglobulins in the clinical laboratory. *Clin. Chem.* **70**, 1422–1435

17. Fornelli, L., Ayoub, D., Srzentic, K., Nagornov, K. O., Kozhinov, A. N., Gasilova, N., et al. (2022) Structural analysis of monoclonal antibodies with top-down and middle-down electron transfer dissociation mass spectrometry: the first decade. *Chimia* **76**, 114

18. Castel, J., Delaux, S., Hernandez-Alba, O., and Cianférani, S. (2023) Recent advances in structural mass spectrometry methods in the context of biosimilarity assessment: from sequence heterogeneities to higher order structures. *J. Pharm. Biomed. Anal.* **236**, 115696

19. von Pawel-Rammingen, U., Johansson, B. P., and Bjorck, L. (2002) IdeS, a novel streptococcal cysteine proteinase with unique specificity for immunoglobulin G. *EMBO J.* **21**, 1607–1615

20. von Pawel-Rammingen, U., and Bjorck, L. (2003) IdeS and SpeB: immunoglobulin-degrading cysteine proteinases of Streptococcus pyogenes. *Curr. Opin. Microbiol.* **6**, 50–55

21. de Diego, I., Veillard, F., Sztukowska, M. N., Guevara, T., Potempa, B., Pomowski, A., et al. (2014) Structure and mechanism of cysteine peptidase gingipain K (Kgp), a major virulence factor of Porphyromonas gingivalis in periodontitis. *J. Biol. Chem.* **289**, 32291–32302
22. Spoerry, C., Seele, J., Valentin-Weigand, P., Baums, C. G., and von Pawel-Rammingen, U. (2016) Identification and characterization of IgdE, a novel IgG-degrading protease of Streptococcus suis with unique specificity for porcine IgG. *J. Biol. Chem.* **291**, 7915–7925

23. Persson, H., Vindebro, R., and von Pawel-Rammingen, U. (2013) The streptococcal cysteine protease SpeB is not a natural immunoglobulin-cleaving enzyme. *Infect. Immun.* **81**, 2236–2241

24. van Rijswijck, D. M. H., Bondt, A., de Kat, N., Lood, R., and Heck, A. J. R. (2024) Direct comparison of the hinge-cleaving proteases IgdE and BdpK for LC-MS-based IgG1 clonal profiling. *Anal. Chem.* **96**, 23–27

25. Nagy, C., Andrási, M., Hamidli, N., Gyémánt, G., and Gáspár, A. (2022) Top-down proteomic analysis of monoclonal antibodies by capillary zone electrophoresis-mass spectrometry. *J. Chromatogr. Open 2*, 100024

26. Kline, J. T., Melani, R. D., and Fornelli, L. (2023) Mass spectrometry characterization of antibodies at the intact and subunit levels: from targeted to large-scale analysis. *Int. J. Mass Spectrom.* **492**, 11717

27. Feng, R., and Konishi, Y. (1993) Collisionally-activated dissociation of multiply charged 150-kDa antibody ions. *Anal. Chem.* **65**, 645–649

28. Macias, L. A., Santos, I. C., and Brodbelt, J. S. (2020) Ion activation methods for peptides and proteins. *Anal. Chem.* **92**, 227–251

29. Zhang, Z., and Shah, B. (2007) Characterization of variable regions of monoclonal antibodies by top-down mass spectrometry. *Anal. Chem.* **79**, 5723–5729

30. Bondarenko, P. V., Second, T. P., Zabrouskov, V., Makarov, A. A., and Zhang, Z. (2009) Mass measurement and top-down HPLC/MS analysis of intact monoclonal antibodies on a hybrid linear quadrupole ion trap-orbitrap mass spectrometer. *J. Am. Soc. Mass Spectrom.* **20**, 1415–1424

31. Tsybin, Y. O., Fornelli, L., Stoermer, C., Luebeck, M., Parra, J., Nallet, S., et al. (2011) Structural analysis of intact monoclonal antibodies by electron transfer dissociation mass spectrometry. *Anal. Chem.* **83**, 8919–8927

32. Syka, J. E., Coon, J. J., Schroeder, M. J., Shabanowitz, J., and Hunt, D. F. (2004) Peptide and protein sequence analysis by electron transfer dissociation mass spectrometry. *Proc. Natl. Acad. Sci. U. S. A.* **101**, 9528–9533

33. Fornelli, L., Damoc, E., Thomas, P. M., Kelleher, N. L., Aizikov, K., Denisov, E., et al. (2012) Analysis of intact monoclonal antibody IgG1 by electron transfer dissociation Orbitrap FTMS. *Mol. Cell Proteomics* **11**, 1758–1767

34. Zubarev, R. A., Kelleher, N. L., and McLafferty, F. W. (1998) Electron capture dissociation of multiply charged protein cations. A nonergodic process. *J. Am. Chem. Soc.* **120**, 3265–3266

35. Mao, Y., Valeja, S. G., Rouse, J. C., Hendrickson, C. L., and Marshall, A. G. (2013) Top-down structural analysis of an intact monoclonal antibody by electron capture dissociation-fourier transform ion cyclotron resonance-mass spectrometry. *Anal. Chem.* **85**, 4239–4246

36. Jin, Y., Lin, Z., Xu, Q., Fu, C., Zhang, Z., Zhang, Q., et al. (2019) Comprehensive characterization of monoclonal antibody by Fourier transform ion cyclotron resonance mass spectrometry. *mAbs* **11**, 106–115

37. Fornelli, L., Ayoub, D., Aizikov, K., Liu, X., Damoc, E., Pevzner, P. A., et al. (2017) Top-down analysis of immunoglobulin G isotypes 1 and 2 with electron transfer dissociation on a high-field Orbitrap mass spectrometer. *J. Proteomics* **159**, 67–76

38. Fornelli, L., Srzentić, K., Huguet, R., Mullen, C., Sharma, S., Zabrouskov, V., et al. (2018) Accurate sequence analysis of a monoclonal antibody by top-down and middle-down Orbitrap mass spectrometry applying multiple ion activation techniques. *Anal. Chem.* **90**, 8421–8429

39. Oates, R. N., Lieu, L. B., Srzentic, K., Damoc, E., and Fornelli, L. (2024) Characterization of a monoclonal antibody by native and denaturing top-down mass spectrometry. *J. Am. Soc. Mass Spectrom.* **35**, 2197–2208

40. van der Burgt, Y. E. M., Kilgour, D. P. A., Tsybin, Y. O., Srzentić, K., Fornelli, L., Beck, A., et al. (2019) Structural analysis of monoclonal antibodies by ultrahigh resolution MALDI in-source decay FT-ICR mass spectrometry. *Anal. Chem.* **91**, 2079–2085

41. Lodge, J. M., Schauer, K. L., Brademan, D. R., Riley, N. M., Shishkova, E., Westphall, M. S., et al. (2020) Top-down characterization of an intact monoclonal antibody using activated ion electron transfer dissociation. *Anal. Chem.* **92**, 10246–10251

42. Tsybin, Y. O., He, H., Emmett, M. R., Hendrickson, C. L., and Marshall, A. G. (2007) Ion activation in electron capture dissociation to distinguish between N-terminal and C-terminal product ions. *Anal. Chem.* **79**, 7596–7602

43. Shaw, J. B., Liu, W., Vasil'ev, Y. V., Bracken, C. C., Malhan, N., Guthals, A., et al. (2020) Direct determination of antibody chain pairing by top-down and middle-down mass spectrometry using electron capture dissociation and ultraviolet photodissociation. *Anal. Chem.* **92**, 766–773

44. Greisch, J.-F., den Boer, M. A., Lai, S.-H., Gallagher, K., Bondt, A., Commandeur, J., et al. (2021) Extending native top-down electron capture dissociation to MDa immunoglobulin complexes provides useful sequence tags covering their critical variable complementarity-determining regions. *Anal. Chem.* **93**, 16068–16075

45. Greisch, J.-F., den Boer, M. A., Beurskens, F., Schuurman, J., Tamara, S., Bondt, A., et al. (2021) Generating informative sequence tags from antigen-binding regions of heavily glycosylated IgA1 antibodies by native top-down electron capture dissociation. *J. Am. Soc. Mass Spectrom.* **32**, 1326–1335

46. Wei, B., Lantz, C., Liu, W., Viner, R., Ogorzalek Loo, R. R., Campuzano, I. D. G., et al. (2023) Added value of internal fragments for top-down mass spectrometry of intact monoclonal antibodies and antibody-drug conjugates. *Anal. Chem.* **95**, 9347–9356

47. Ren, D., Pipes, G. D., Hambly, D., Bondarenko, P. V., Treuheit, M. J., and Gadgil, H. S. (2009) Top-down N-terminal sequencing of Immunoglobulin subunits with electrospray ionization time of flight mass spectrometry. *Anal. Biochem.* **384**, 42–48

48. Nicolardi, S., Deelder, A. M., Palmblad, M., and van der Burgt, Y. E. (2014) Structural analysis of an intact monoclonal antibody by online electrochemical reduction of disulfide bonds and Fourier transform ion cyclotron resonance mass spectrometry. *Anal. Chem.* **86**, 5376–5382

49. Olsen, J. V., Macek, B., Lange, O., Makarov, A., Horning, S., and Mann, M. (2007) Higher-energy C-trap dissociation for peptide modification analysis. *Nat. Methods* **4**, 709–712

50. Srzentić, K., Nagornov, K. O., Fornelli, L., Lobas, A. A., Ayoub, D., Kozhinov, A. N., et al. (2018) Multiplexed middle-down mass spectrometry as a method for revealing light and heavy chain connectivity in a monoclonal antibody. *Anal. Chem.* **90**, 12527–12535

51. Belov, A. M., Zang, L., Sebastiano, R., Santos, M. R., Bush, D. R., Karger, B. L., et al. (2018) Complementary middle-down and intact monoclonal antibody proteoform characterization by capillary zone electrophoresis – mass spectrometry. *Electrophoresis* **39**, 2069–2082

52. Fornelli, L., Ayoub, D., Aizikov, K., Beck, A., and Tsybin, Y. O. (2014) Middle-down analysis of monoclonal antibodies with electron transfer dissociation Orbitrap fourier transform mass spectrometry. *Anal. Chem.* **86**, 3005–3012

53. den Boer, M. A., Greisch, J.-F., Tamara, S., Bondt, A., and Heck, A. J. R. (2020) Selectivity over coverage in de novo sequencing of IgGs. *Chem. Sci.* **11**, 11886–11896

54. Cejkov, M., Greer, T., Johnson, R. O. B., Zheng, X., and Li, N. (2021) Electron transfer dissociation parameter optimization using design of experiments increases sequence coverage of monoclonal antibodies. *J. Am. Soc. Mass Spectrom.* **32**, 762–771

55. Searfoss, R. M., Zahn, E., Lin, Z., and Garcia, B. A. (2025) Establishing a top-down proteomics platform on a time-of-flight instrument with electron-activated dissociation. *J. Proteome Res.* **24**, 1230–1240

56. Resemann, A., Wunderlich, D., Rothbauer, U., Warscheid, B., Leonhardt, H., Fuchser, J., et al. (2010) Top-down de Novo protein sequencing of a 13.6 kDa camelid single heavy chain antibody by matrix-assisted laser desorption ionization-time-of-flight/time-of-flight mass spectrometry. *Anal. Chem.* **82**, 3283–3292

57. Suckau, D., and Resemann, A. (2003) T3-sequencing: targeted characterization of the N- and C-termini of undigested proteins by mass spectrometry. *Anal. Chem.* **75**, 5817–5824

58. Ayoub, D., Jabs, W., Resemann, A., Evers, W., Evans, C., Main, L., et al. (2013) Correct primary structure assessment and extensive glyco-profiling of cetuximab by a combination of intact, middle-up, middle-down and bottom-up ESI and MALDI mass spectrometry techniques. *mAbs* **5**, 699–710
59. Resemann, A., Jabs, W., Wiechmann, A., Wagner, E., Colas, O., Evers, W., et al. (2016) Full validation of therapeutic antibody sequences by middle-up mass measurements and middle-down protein sequencing. *mAbs* **8**, 318–330

60. Zhurov, K. O., Fornelli, L., Wodrich, M. D., Laskay, U. A., and Tsybin, Y. O. (2013) Principles of electron capture and transfer dissociation mass spectrometry applied to peptide and protein structure analysis. *Chem. Soc. Rev.* **42**, 5014–5030

61. Biacchi, M., Said, N., Beck, A., Leize-Wagner, E., and Francois, Y. N. (2017) Top-down and middle-down approach by fraction collection enrichment using off-line capillary electrophoresis - mass spectrometry coupling: application to monoclonal antibody F(c/2) charge variants. *J. Chromatogr. A.* **1498**, 120–127

62. Nicolardi, S., Kilgour, D. P. A., van der Burgt, Y. E. M., and Wuhrer, M. (2020) Improved N- and C-terminal sequencing of proteins by combining positive and negative ion MALDI in-source decay mass spectrometry. *Anal. Chem.* **92**, 12429–12436

63. Gstöttner, C., Reusch, D., Haberger, M., Dragan, I., Van Veelen, P., Kilgour, D. P. A., et al. (2020) Monitoring glycation levels of a bispecific monoclonal antibody at subunit level by ultrahigh-resolution MALDI FT-ICR mass spectrometry. *mAbs* **12**, 1682403

64. Dekker, L., Wu, S., Vanduijn, M., Tolic, N., Stingl, C., Zhao, R., et al. (2014) An integrated top-down and bottom-up proteomic approach to characterize the antigen-binding fragment of antibodies. *Proteomics* **14**, 1239–1248

65. He, L., Anderson, L. C., Barnidge, D. R., Murray, D. L., Hendrickson, C. L., and Marshall, A. G. (2017) Analysis of monoclonal antibodies in human serum as a model for clinical monoclonal gammopathy by use of 21 Tesla FT-ICR top-down and middle-down MS/MS. *J. Am. Soc. Mass Spectrom.* **28**, 827–838

66. Zhu, W., Li, M., and Zhang, J. (2021) Integrating intact mass analysis and middle-down mass spectrometry approaches to effectively characterize trastuzumab and adalimumab structural heterogeneity. *J. Proteome Res.* **20**, 270–278

67. Cotham, V. C., and Brodbelt, J. S. (2016) Characterization of therapeutic monoclonal antibodies at the subunit-level using middle-down 193 nm ultraviolet photodissociation. *Anal. Chem.* **88**, 4004–4013

68. Liu, J., Liu, Z., Zhao, H., Xiao, C., Yang, X., and Wang, F. (2025) Sequencing the monoclonal antibody variable regions using multiple charge integration middle-down strategy and ultraviolet photodissociation. *Anal. Chim. Acta* **1335**, 343450

69. Shaw, J. B., Malhan, N., Vasil'ev, Y. V., Lopez, N. I., Makarov, A., Beckman, J. S., et al. (2018) Sequencing grade tandem mass spectrometry for top-down proteomics using hybrid electron capture dissociation methods in a benchtop Orbitrap mass spectrometer. *Anal. Chem.* **90**, 10819–10827

70. Beckman, J. S., Voinov, V. G., Hare, M., Sturgeon, D., Vasil'ev, Y., Oppenheimer, D., et al. (2021) Improved protein and PTM characterization with a practical electron-based fragmentation on Q-TOF instruments. *J. Am. Soc. Mass Spectrom.* **32**, 2081–2091

71. Melani, R. D., Srzentić, K., Gerbasi, V. R., McGee, J. P., Huguet, R., Fornelli, L., et al. (2019) Direct measurement of light and heavy antibody chains using ion mobility and middle-down mass spectrometry. *mAbs* **11**, 1351–1357

72. Sanders, J. D., Mullen, C., Watts, E., Holden, D. D., Syka, J. E. P., Schwartz, J. C., et al. (2020) Enhanced sequence coverage of large proteins by combining ultraviolet photodissociation with proton transfer reactions. *Anal. Chem.* **92**, 1041–1049

73. Römer, J., Stolz, A., Kiessig, S., Moritz, B., and Neusüß, C. (2021) Online top-down mass spectrometric identification of CE(SDS)-separated antibody fragments by two-dimensional capillary electrophoresis. *J. Pharm. Biomed. Anal.* **201**, 114089

74. Dhenin, J., Dupré, M., Druart, K., Krick, A., Mauriac, C., and Chamot-Rooke, J. (2023) A multiparameter optimization in middle-down analysis of monoclonal antibodies by LC-MS/MS. *J. Mass Spectrom.* **58**, e4909

75. Kellie, J. F., Schneck, N. A., Causon, J. C., Baba, T., Mehl, J. T., and Pohl, K. I. (2023) Top-down characterization and intact mass quantification of a monoclonal antibody drug from serum by use of a quadrupole TOF MS system equipped with electron-activated dissociation. *J. Am. Soc. Mass Spectrom.* **34**, 17–26

76. Oates, R. N., Lieu, L. B., Kline, J. T., Mullen, C., Srzentić, K., Huguet, R., et al. (2024) Towards a universal method for middle-down analysis of antibodies via proton transfer charge reduction-Orbitrap mass spectrometry. *Anal. Bioanal. Chem.* https://doi.org/10.1007/s00216-024-05534-z

77. Lieu, L. B., Nagy, C., Huang, J., Mullen, C., McAlister, G. C., Zabrouskov, V., et al. (2024) Enhanced payload localization in antibody-drug conjugates using a middle-down mass spectrometry approach with proton transfer charge reduction. *Anal. Chem.* https://doi.org/10.1021/acs.analchem.4c03872

78. Nagornov, K. O., Gasilova, N., Kozhinov, A. N., Virta, P., Holm, P., Menin, L., et al. (2021) Drug-to-Antibody ratio estimation via proteoform peak integration in the analysis of antibody-oligonucleotide conjugates with orbitrap fourier transform mass spectrometry. *Anal. Chem.* **93**, 12930–12937

79. Zhang, Y., Cui, W., Wecksler, A. T., Zhang, H., Molina, P., Deperalta, G., et al. (2016) Native MS and ECD characterization of a Fab-antigen complex may facilitate crystallization for X-ray diffraction. *J. Am. Soc. Mass Spectrom.* **27**, 1139–1142

80. Hernandez-Alba, O., Houel, S., Hessmann, S., Erb, S., Rabuka, D., Huguet, R., et al. (2019) A case study to identify the drug conjugation site of a site-specific antibody-drug-conjugate using middle-down mass spectrometry. *J. Am. Soc. Mass Spectrom.* **30**, 2419–2429

81. Chen, B., Lin, Z., Zhu, Y., Jin, Y., Larson, E., Xu, Q., et al. (2019) Middle-down multi-attribute analysis of antibody-drug conjugates with electron transfer dissociation. *Anal. Chem.* **91**, 11661–11669

82. Watts, E., Williams, J. D., Miesbauer, L. J., Bruncko, M., and Brodbelt, J. S. (2020) Comprehensive middle-down mass spectrometry characterization of an antibody-drug conjugate by combined ion activation methods. *Anal. Chem.* **92**, 9790–9798

83. Mehaffey, M. R., Lee, J., Jung, J., Lanzillotti, M. B., Escobar, E. E., Morgenstern, K. R., et al. (2020) Mapping a conformational epitope of hemagglutinin A using native mass spectrometry and ultraviolet photodissociation. *Anal. Chem.* **92**, 11869–11878

84. Larson, E. J., Zhu, Y., Wu, Z., Chen, B., Zhang, Z., Zhou, S., et al. (2020) Rapid analysis of reduced antibody drug conjugate by online LC-MS/MS with fourier transform ion cyclotron resonance mass spectrometry. *Anal. Chem.* **92**, 15096–15103

85. Larson, E. J., Roberts, D. S., Melby, J. A., Buck, K. M., Zhu, Y., Zhou, S., et al. (2021) High-throughput multi-attribute analysis of antibody-drug conjugates enabled by trapped ion mobility spectrometry and top-down mass spectrometry. *Anal. Chem.* **93**, 10013–10021

86. Beaumal, C., Desligniere, E., Diemer, H., Carapito, C., Cianferani, S., and Hernandez-Alba, O. (2024) Improved characterization of trastuzumab deruxtecan with PTCR and internal fragments implemented in middle-down MS workflows. *Anal. Bioanal. Chem.* **416**, 519–532

87. Benazza, R., Letissier, L., Papadakos, G., Thom, J., Diemer, H., Cotton, G., et al. (2025) Development of top-down mass spectrometry strategies in the chromatographic time scale (LC-TD-MS) for the extended characterization of an anti-EGFR single-domain antibody-drug conjugate in both reduced and nonreduced forms. *Anal. Chem.* **97**, 2639–2647

88. Yuan, J., Tan, H. Y., Huang, Y., and Rosenbaum, A. I. (2024) Digestion-free middle-down mass spectrometry method for absolute quantification of conjugated payload from antibody-drug conjugates. *Anal. Chem.* **96**, 16475–16480

89. Peris-Diaz, M. D., Desligniere, E., Jager, S., Mokiem, N., Barendregt, A., Bondt, A., et al. (2024) Asymmetric N-glycosylation in the tailpiece of recombinant IgA1. *J. Am. Chem. Soc.* **146**, 34720–34732

90. Senini, I., Tengattini, S., Rinaldi, F., Massolini, G., Gstottner, C., Reusch, D., et al. (2024) Direct glycosylation analysis of intact monoclonal antibodies combining ESI MS of glycoforms and MALDI-in source decay MS of glycan fragments. *Commun. Chem.* **7**, 203

91. Wang, Z., Liu, X., Muther, J., James, J. A., Smith, K., and Wu, S. (2019) Top-down mass spectrometry analysis of human serum autoantibody antigen-binding fragments. *Sci. Rep.* **9**, 2345

92. Dhenin, J., Lafont, V., Dupré, M., Krick, A., Mauriac, C., and Chamot-Rooke, J. (2023) Monitoring mAb proteoforms in mouse plasma using an automated immunocapture combined with top-down and middle-down mass spectrometry. *Proteomics*. https://doi.org/10.1002/pmic.202300069
93. He, L., Anderson, L. C., Barnidge, D. R., Murray, D. L., Dasari, S., Dispenzieri, A., et al. (2019) Classification of plasma cell disorders by 21 Tesla fourier transform ion cyclotron resonance top-down and middle-down MS/MS analysis of monoclonal immunoglobulin light chains in human serum. *Anal. Chem.* **91**, 3263–3269

94. Bondt, A., Hoek, M., Tamara, S., de Graaf, B., Peng, W., Schulte, D., et al. (2021) Human plasma IgG1 repertoires are simple, unique, and dynamic. *Cell Syst.* **12**, 1131–1143.e1135

95. Peng, W., den Boer, M. A., Tamara, S., Mokiem, N. J., van der Lans, S. P. A., Bondt, A., et al. (2023) Direct mass spectrometry-based detection and antibody sequencing of monoclonal gammopathy of undetermined significance from patient serum: a case study. *J. Proteome Res.* **22**, 3022–3028

96. Dupre, M., Duchateau, M., Sternke-Hoffmann, R., Boquoi, A., Malosse, C., Fenk, R., et al. (2021) De novo sequencing of antibody light chain proteoforms from patients with multiple myeloma. *Anal. Chem.* **93**, 10627–10634

97. Shaw, J. B., Harvey, S. R., Du, C., Xu, Z., Edgington, R. M., Olmedillas, E., et al. (2024) Protein complex heterogeneity and topology revealed by electron capture charge reduction and surface induced dissociation. *ACS Cent. Sci.* **10**, 1537–1547

98. Le Huray, K. I. P., Worner, T. P., Moreira, T., Dembek, M., Reinhardt-Szyba, M., Devine, P. W. A., et al. (2024) To 200,000 m/z and beyond: native electron capture charge reduction mass spectrometry deconvolves heterogeneous signals in large biopharmaceutical analytes. *ACS Cent. Sci.* **10**, 1548–1561

99. Donnelly, D. P., Rawlins, C. M., DeHart, C. J., Fornelli, L., Schachner, L. F., Lin, Z., et al. (2019) Best practices and benchmarks for intact protein analysis for top-down mass spectrometry. *Nat. Methods* **16**, 587–594

100. Chen, B., Lin, Z., Alpert, A. J., Fu, C., Zhang, Q., Pritts, W. A., et al. (2018) Online hydrophobic interaction chromatography-mass spectrometry for the analysis of intact monoclonal antibodies. *Anal. Chem.* **90**, 7135–7138

101. Niu, B., Lee, B., Chen, W., Alberto, C., Betancourt Moreira, K., Compton, P., et al. (2024) End-to-end automated intact protein mass spectrometry for high-throughput screening and characterization of bispecific and multispecific antibodies. *Anal. Chem.* https://doi.org/10.1021/acs.anal-chem.4c04833

102. Huang, J., Mullen, C., Srzentić, K., McAlister, G., Zabrouskov, V., and Melani, R. (2024) In-depth characterization of monoclonal antibodies using intact mass analysis and middle-down approaches on an Orbitrap Ascend BioPharma Tribrid Mass Spectrometer. In: *Proceedings of the 72nd ASMS Conference on Mass Spectrometry and Allied Topics*. Anaheim, California

103. Srzentić, K., Criscuolo, A., Scheffler, K., and Damoc, E. (2024) Comprehensive characterization of monoclonal antibodies (mAbs) and Antibody Drug Conjugates (ADCs) on a novel high-resolution accurate mass platform. In: *Proceedings of the 72nd ASMS Conference on Mass Spectrometry and Allied Topics*. Anaheim, California

104. Fernandez-Lima, F. A., Kaplan, D. A., and Park, M. A. (2011) Note: integration of trapped ion mobility spectrometry with mass spectrometry. *Rev. Sci. Instrum* **82**, 126106

105. Kozhinov, A. N., Nagornov, K. O., and Tsybin, Y. O. (2025) High-performance data acquisition for fourier transform mass spectrometry. *Chimia (Aarau)* **79**, 77–83

106. Nagornov, K. O., Kozhinov, A. N., Gasilova, N., Menin, L., and Tsybin, Y. O. (2022) Characterization of the time-domain isotopic beat patterns of monoclonal antibodies in fourier transform mass spectrometry. *J. Am. Soc. Mass Spectrom.* **33**, 1113–1125

107. Campuzano, I. D. G., and Loo, J. A. (2025) Evolution of mass spectrometers for high m/z biological ion formation, transmission, analysis and detection: a personal perspective. *J. Am. Soc. Mass Spectrom.* **36**, 632–652

108. Jarrold, M. F. (2022) Applications of charge detection mass spectrometry in molecular biology and biotechnology. *Chem. Rev.* **122**, 7415–7441

109. Desligiere, E., Yin, V. C., Ebberink, E., Rolland, A. D., Barendregt, A., Worner, T. P., et al. (2024) Ultralong transients enhance sensitivity and resolution in Orbitrap-based single-ion mass spectrometry. *Nat. Methods* **21**, 619–622

110. Ebberink, E., Yin, V. C., Desligiere, E., Barendregt, A., Worner, T. P., Fort, K. L., et al. (2025) Prolonged trapping of adeno-associated virus capsids

reveals that genome packaging affects single-ion mass spectrometry measurements. *J. Am. Chem. Soc.* **147**, 10925–10934

111. Kafader, J. O., Durbin, K. R., Melani, R. D., Des Soye, B. J., Schachner, L. F., Senko, M. W., et al. (2020) Individual ion mass spectrometry enhances the sensitivity and sequence coverage of top-down mass spectrometry. *J. Proteome Res.* **19**, 1346–1350

112. Kline, J. T., Huang, J., Lieu, L. B., Srzentic, K., Bergen, D., Mullen, C., et al. (2025) Top-down mass spectrometry analysis of capsid proteins of recombinant adeno-associated virus using multiple ion activations and proton transfer charge reduction. *Proteomics* **25**, e2400223

113. Papanastasiou, D., Kounadis, D., Lekkas, A., Orfanopoulos, I., Mpozatzidis, A., Smyrnakis, A., et al. (2022) The Omnitrap platform: a versatile segmented linear ion trap for multidimensional multiple-stage tandem mass spectrometry. *J. Am. Soc. Mass Spectrom.* **33**, 1990–2007

114. Shaw, J. B., Cooper-Shepherd, D. A., Hewitt, D., Wildgoose, J. L., Beckman, J. S., Langridge, J. I., et al. (2022) Enhanced top-down protein characterization with electron capture dissociation and cyclic ion mobility spectrometry. *Anal. Chem.* **94**, 3888–3896

115. Arslanian, A. J., and Wysocki, V. H. (2025) Roughhousing with ions: surface-induced dissociation and electron capture dissociation as diagnostics of Q-cyclic IMS-TOF instrument tuning gentleness. *J. Am. Soc. Mass Spectrom.* **36**, 187–200

116. Verenchikov, A. N., Makarov, V. V., Vorobyev, A. V., and Kirillov, S. N. (2024) A perspective of multi-reflecting TOF MS. *Mass Spectrom. Rev.* https://doi.org/10.1002/mas.21915

117. Verenchikov, A. N., Kirillov, S. N., Vorobyev, A. V., and Makarov, V. V. (2025) Multi-reflecting TOF MS for analyzing proteins. *Int. J. Mass Spectrom.* **508**, 117389

118. Verenchikov, A. N., Kirillov, S. N., Vorobyev, A. V., Makarov, V. V., Yavor, M. I., Tonge, R. P., et al. (2025) Multi reflecting TOF MS approaching resolution of 1,000,000 in a wide mass range. *Int. J. Mass Spectrom.* **508**, 117395

119. Jeanne Dit Fouque, K., Miller, S. A., Pham, K., Bhanu, N. V., Cintron-Diaz, Y. L., Leyva, D., et al. (2022) Top-"Double-Down" mass spectrometry of histone H4 proteoforms: tandem ultraviolet-photon and mobility/mass-selected electron capture dissociations. *Anal. Chem.* **94**, 15377–15385

120. Smyrnakis, A., Levin, N., Kosmopoulou, M., Jha, A., Fort, K., Makarov, A., et al. (2023) Characterization of an omnitrap-orbitrap platform equipped with infrared multiphoton dissociation, ultraviolet photodissociation, and electron capture dissociation for the analysis of peptides and proteins. *Anal. Chem.* **95**, 12039–12046

121. Garcia, C., Druart, K., Nagornov, K., Smyrnakis, A., Kozhinov, A., Papanastasiou, D., et al. (2024) Improved top-down analysis of antibody subunits using the omnitrap-orbitrap-booster platform. In: *Proceedings of the 72nd ASMS Conference on Mass Spectrometry and Allied Topics*. Anaheim, California

122. Fellers, R. T., Greer, J. B., Early, B. P., Yu, X., LeDuc, R. D., Kelleher, N. L., et al. (2015) ProSight Lite: graphical software to analyze top-down mass spectrometry data. *Proteomics* **15**, 1235–1238

123. Kou, Q., Xun, L., and Liu, X. (2016) TopPIC: a software tool for top-down mass spectrometry-based proteoform identification and characterization. *Bioinformatics* **32**, 3495–3497

124. Lantz, C., Zenaidee, M. A., Wei, B., Hemminger, Z., Ogorzalek Loo, R. R., and Loo, J. A. (2021) ClipsMS: an algorithm for analyzing internal fragments resulting from top-down mass spectrometry. *J. Proteome Res.* **20**, 1928–1935

125. Cai, W., Guner, H., Gregorich, Z. R., Chen, A. J., Ayaz-Guner, S., Peng, Y., et al. (2016) MASH suite Pro: a comprehensive software tool for top-down proteomics. *Mol. Cell Proteomics* **15**, 703–714

126. Tabb, D. L., Jeong, K., Druart, K., Gant, M. S., Brown, K. A., Nicora, C., et al. (2023) Comparing top-down proteoform identification: deconvolution, PrSM overlap, and PTM detection. *J. Proteome Res.* **22**, 2199–2217

127. Robey, M. T., and Durbin, K. R. (2024) Improving top-down sequence coverage with targeted fragment matching. *J. Am. Soc. Mass Spectrom.* **35**, 3296–3300

128. Mikawy, N. N., Rojas Ramirez, C., DeFiglia, S. A., Szot, C. W., Le, J., Lantz, C., et al. (2024) Are internal fragments observable in electron based top-down mass spectrometry? *Mol. Cell Proteomics* **23**, 100814
129. Vyatkina, K. (2017) *De novo* sequencing of top-down tandem mass spectra: a next step towards retrieving a complete protein sequence. *Proteomes* **5**, 6

130. de Graaf, S. C., Hoek, M., Tamara, S., and Heck, A. J. R. (2022) *A perspective toward mass spectrometry-based de novo sequencing of endogenous antibodies*. *mAbs* **14**, 2079449

131. Vyatkina, K., Wu, S., Dekker, L. J., VanDuijn, M. M., Liu, X., Tolic, N., et al. (2016) Top-down analysis of protein samples by de novo sequencing techniques. *Bioinformatics* **32**, 2753-2759

132. Griaud, F., Denefeld, B., Kao-Scharf, C. Y., Dayer, J., Lang, M., Chen, J. Y., et al. (2019) All ion differential analysis refines the detection of terminal and internal diagnostic fragment ions for the characterization of biologics product-related variants and impurities by middle-down mass spectrometry. *Anal. Chem.* **91**, 8845-8852

133. Denefeld, B., Hajduk, J., Cerar, J., Rondeau, J. M., Dayer, J., Lang, M., et al. (2025) Revealing unpredicted aspartic acid isomerization hotspots by probing diagnostic fragmentation propensities in top-down and middle-down mass spectrometry. *J. Am. Soc. Mass Spectrom.* **36**, 969-979

134. Habeck, T., Brown, K. A., Des Soye, B., Lantz, C., Zhou, M., Alam, N., et al. (2024) Top-down mass spectrometry of native proteins and their complexes: a community study. *Nat. Methods* **21**, 2388-2396

135. Huang, Y., Mou, S., Wang, Y., Mu, R., Liang, M., and Rosenbaum, A. I. (2021) Characterization of antibody-drug conjugate pharmacokinetics and in vivo biotransformation using quantitative intact LC-HRMS and surrogate analyte LC-MRM. *Anal. Chem.* **93**, 6135-6144

136. Kellie, J. F., Pannullo, K. E., Li, Y., Fraley, K., Mayer, A., Sychterz, C. J., et al. (2020) Antibody subunit LC-MS analysis for pharmacokinetic and biotransformation determination from in-life studies for complex biotherapeutics. *Anal. Chem.* **92**, 8268-8277

137. Bergonzo, C., and Gallagher, D. T. (2021) Atomic model structure of the NIST monoclonal antibody (NISTmAb) reference material. *J. Res. Natl. Inst. Stand Technol.* **126**, 126012

138. Van Eck, N. J., and Waltman, L. (2007) VOS: a new method for visualizing similarities between objects. In: *Advances in Data Analysis: Proceedings of the 30th Annual Conference of the German Classification Society*. Springer, Berlin, Heidelberg