Prediction of Collision-Induced Dissociation Spectra of Common N-Glycopeptides for Glycoform Identification

Expanding N-glycopeptide identifications by modeling fragmentation, elution, and glycome connectivity

Accurate glycopeptide identification in mass spectrometry-based glycoproteomics is a challenging problem at scale. Recent innovation has been made in increasing the scope and accuracy of glycopeptide identifications, with more precise uncertainty estimates for each part of the structure. We present a dynamically adapting relative retention time model for detecting and correcting ambiguous glycan assignments that are difficult to detect from fragmentation alone, a layered approach to glycopeptide fragmentation modeling that improves N-glycopeptide identification in samples without compromising identification quality, and a site-specific method to increase the depth of the glycoproteome confidently identifiable even further. We demonstrate our techniques on a set of previously published datasets, showing the performance gains at each stage of optimization. These techniques are provided in the open-source glycomics and glycoproteomics platform GlycReSoft available at https://github.com/mobiusklein/glycresoft .

Fully Unattended Online Protein Digestion and LC-MS Peptide Mapping

LC-MS based peptide mapping, i.e., proteolytic digestion followed by LC-MS/MS analysis, is the method of choice for protein primary structural characterization. Manual proteolytic digestion is usually a labor-intensive procedure. In this work, a novel method was developed for fully automated online protein digestion and LC-MS peptide mapping. The method generates LC-MS data from undigested protein samples without user intervention by utilizing the same HPLC system that performs the chromatographic separation with some additional modules. Each sample is rapidly digested immediately prior to its LC-MS analysis, minimizing artifacts that can grow over longer digestion times or digest storage times as in manual or automated offline digestion methods. In this report, we implemented the method on an Agilent 1290 Infinity II LC system equipped with a Multisampler. The system performs a complete digestion workflow including denaturation, disulfide reduction, cysteine alkylation, buffer exchange, and tryptic digestion. We demonstrated that the system is capable of digesting monoclonal antibodies and other proteins with excellent efficiency and is robust and reproducible and produces fewer artifacts than manually prepared digests. In addition, it consumes only a few micrograms of material as most of the digested sample protein is subjected to LC-MS analysis.

Method for detecting rare differences between two LC-MS runs

LC-MS based multi-attribute methods (MAM) have drawn substantial attention due to their capability of simultaneously monitoring a large number of quality attributes of a biopharmaceutical product. For successful implementation of MAM, it is usually considered a requirement that the method is capable of detecting any new or missing peaks in the sample when compared to a control. Comparing a sample to a control for rare differences is also commonly practiced in many fields for investigational purpose. Because MS signal variability differs greatly between signals of different intensities, this type of comparison is often challenging, especially when the comparison is made without enough replicates. In this report we describe a statistical method for detecting rare differences between two very similar samples without replicate analyses. The method assumes that an overwhelming majority of components have equivalent abundance between the two samples, and signals with similar intensities have similar relative variability. By analyzing several monoclonal antibody peptide mapping datasets, we demonstrated that the method is suitable for new-peak detection for MAM as well as for other applications when rare differences between two samples need to be detected. The method greatly reduced false positive rate without a significant increase of false negative rate.

IgG1 and IgG4 antibodies sample initial structure dependent local conformational states and exhibit non-identical Fab dynamics

We have investigated the dynamics of two [Formula: see text]-immunoglobulin molecules, IgG1 and IgG4, using long all atom molecular dynamics simulations. We first show that the de novo structures of IgG1 and IgG4 predicted using AlphaFold, with no interactions between the fragment crystallizable (Fc) domain and the antigen fragment binding domain (Fab), eventually relaxes to a state with persistent Fc-Fab interactions that mirrors experimentally resolved structures. We quantified the conformational space sampled by antibody trajectories spawned from six different initial structures and show that the individual trajectories only sample states bound by a local minimum and display very little mixing in their conformational states. Furthermore, the dynamics of the individual Fab domains are strongly dependent on the initial crystal structure and isotype. In all conditions, we observe non-identical dynamics between the Fab arms in an antibody. For a six-bead coarse grained model, we show that non-covalent Fc-Fab interactions can modulate the stiffnesses associated with Fc-Fab distances, angles, and dihedral angles by up to three orders of magnitude. Our results clearly illustrate the inherent complexities in studying antibody dynamics and highlight the need to include non-identical Fab dynamics as an inherent feature in computational models of therapeutic antibodies.

Process Development of a SARS-CoV-2 Nanoparticle Vaccine

One of the outcomes from the global COVID-19 pandemic caused by SARS-CoV-2 has been an acceleration of development timelines to provide treatments in a timely manner. For example, it has recently been demonstrated that the development of monoclonal antibody therapeutics from vector construction to IND submission can be achieved in five to six months rather than the traditional ten-to-twelve-month timeline using CHO cells [1], [2]. This timeline is predicated on leveraging existing, robust platforms for upstream and downstream processes, analytical methods, and formulation. These platforms also reduce; the requirement for ancillary studies such as cell line stability, or long-term product stability studies. Timeline duration was further reduced by employing a transient cell line for early material supply and using a stable cell pool to manufacture toxicology study materials. The development of non-antibody biologics utilizing traditional biomanufacturing processes in CHO cells within a similar timeline presents additional challenges, such as the lack of platform processes and additional analytical assay development. In this manuscript, we describe the rapid development of a robust and reproducible process for a two-component self-assembling protein nanoparticle vaccine for SARS-CoV-2. Our work has demonstrated a successful academia-industry partnership model that responded to the COVID-19 global pandemic quickly and efficiently and could improve our preparedness for future pandemic threats.

Engineering protein glycosylation in CHO cells to be highly similar to murine host cells

Since 2015 more than 34 biosimilars have been approved by the FDA. This new era of biosimilar competition has stimulated renewed technology development focused on therapeutic protein or biologic manufacturing. One challenge in biosimilar development is the genetic differences in the host cell lines used to manufacture the biologics. For example, many biologics approved between 1994 and 2011 were expressed in murine NS0 and SP2/0 cell lines. Chinese Hamster ovary (CHO) cells, however, have since become the preferred hosts for production due to their increased productivity, ease of use, and stability. Differences between murine and hamster glycosylation have been identified in biologics produced using murine and CHO cells. In the case of monoclonal antibodies (mAbs), glycan structure can significantly affect critical antibody effector function, binding activity, stability, efficacy, and in vivo half-life. In an attempt to leverage the intrinsic advantages of the CHO expression system and match the reference biologic murine glycosylation, we engineered a CHO cell expressing an antibody that was originally produced in a murine cell line to produce murine-like glycans. Specifically, we overexpressed cytidine monophospho-N-acetylneuraminic acid hydroxylase (CMAH) and N-acetyllactosaminide alpha-1,3-galactosyltransferase (GGTA) to obtain glycans with N-glycolylneuraminic acid (Neu5Gc) and galactose-α-1,3-galactose (alpha gal). The resulting CHO cells were shown to produce mAbs with murine glycans, and they were then analyzed by the spectrum of analytical methods typically used to demonstrate analytical similarity as a part of demonstrating biosimilarity. This included high-resolution mass spectrometry, biochemical, as well as cell-based assays. Through selection and optimization in fed-batch cultures, two CHO cell clones were identified with similar growth and productivity criteria to the original cell line. They maintained stable production for 65 population doubling times while matching the glycosylation profile and function of the reference product expressed in murine cells. This study demonstrates the feasibility of engineering CHO cells to express mAbs with murine glycans to facilitate the development of biosimilars that are highly similar to marketed reference products expressed in murine cells. Furthermore, this technology can potentially reduce the residual uncertainty regarding biosimilarity, resulting in a higher probability of regulatory approval and potentially reduced costs and time in development.

Non-covalent Fc-Fab interactions significantly alter internal dynamics of an IgG1 antibody

The fragment-antigen-binding arms (Fab1 and Fab2) in a canonical immunoglobulin G (IgG) molecule have identical sequences and hence are always expected to exhibit symmetric conformations and dynamics. Using long all atom molecular simulations of a human IgG1 crystal structure 1HZH, we demonstrate that the translational and rotational dynamics of Fab1 and Fab2 also strongly depend on their interactions with each other and with the fragment-crystallizable (Fc) region. We show that the Fab2 arm in the 1HZH structure is non-covalently bound to the Fc region via long-lived hydrogen bonds, involving its light chain and both heavy chains of the Fc region. These highly stable interactions stabilize non-trivial conformer states with constrained fluctuations. We observe subtle modifications in Fab1 dynamics in response to Fab2-Fc interactions that points to novel allosteric interactions between the Fab arms. These results yield novel insights into the inter- and intra-fragment motions of immunoglobulins which could help us better understand the relation between their structure and function.

Non-targeted characterization of attributes affecting antibody-FcγRIIIa V158 (CD16a) binding via online affinity chromatography-mass spectrometry

Antibodies facilitate targeted cell killing by engaging with immune cells such as natural killer cells through weak binding interactions with Fcγ receptors on the cell surface. Here, we evaluate the binding affinity of the receptor FcγRIIIa V158 (CD16a) for several therapeutic antibody classes, isoforms, and Fc-fusion proteins using an immobilized receptor affinity liquid chromatography (LC) approach coupled with online mass spectrometry (MS) detection. Aglycosylated FcγRIIIa was used in the affinity chromatography and compared with published affinities using glycosylated receptors. Affinity LC-MS differentiated the IgG1 antibodies primarily according to their Fc glycosylation patterns, with highly galactosylated species having greater affinity for the immobilized receptors and thus eluting later from the column (M5< G0F < G0 afucosylated ≅ G1F < G2F). Sialylated species bound weaker to their asialylated counterparts as reported previously. High mannose glycoforms bound weaker than G0F, contrary to previously published studies using glycosylated receptors. Also, increased receptor binding affinity associated with afucosylated antibodies was not observed with the aglycosylated FcγRIIIa. This apparent difference from previous findings highlighted the importance of the glycans on the receptors for mediating stronger binding interactions. Characterization of temperature-stressed samples by LC-MS peptide mapping revealed over 200 chemical and post-translational modifications, but only the Fc glycans, deamidation of EU N325, and an unknown modification to either proline or cysteine residues of the hinge region were found to have a statistically significant impact on binding.

Abbreviations: Antibody-dependent cell-mediated cytotoxicity (ADCC), chimeric antigen receptor (CAR), Chinese hamster ovary (CHO), dithiothreitol (DTT), electrospray ionization (ESI), hydrogen-deuterium exchange (HDX), filter aided-sample preparation (FASP), Fcγ receptor (FcγR), fragment crystallizable (Fc), high-pressure liquid chromatography (HPLC), immunoglobulin G (IgG), liquid chromatography (LC), monoclonal antibody (mAb), mass spectrometry (MS), natural killer (NK), N-glycolylneuraminic acid (NGNA), N-acetylneuraminic acid (NANA), principal component analysis (PCA), surface plasmon resonance (SPR), trifluoroacetic acid (TFA), and extracted mass chromatogram (XMC).

Limited Proteolysis Coupled with Mass Spectrometry for Simultaneous Evaluation of a Large Number of Protein Variants for Their Impact on Conformational Stability

A stable molecular structure is important in the development of a protein candidate into a therapeutic product. A therapeutic protein often contains many different variants; some of them may have an impact on the conformational stability of the protein. Conventionally, to evaluate the impact of a variant on stability, the variant must be enriched to a reasonable purity, and then its stability characterized by chromatographic or biophysical techniques. However, it is often impractical to purify and characterize each variant in a therapeutic protein. A workflow, based on limited proteolysis followed by MS detection, was established to simultaneously assess the impact of a large number of variants on conformational stability without enrichment. Because a less stable domain is more susceptible to proteolytic degradation, conformational stability of the domain can be reported from the release rate of a proteolytic peptide. A kinetic model is established to quantitatively determine the extent of domain stabilization/destabilization of different variants. The methodology is demonstrated by examining variants known to affect the stability of immunoglobulin domains, such as different N-glycoforms, methionine oxidations, and sequence variants. With this methodology, near 100 variants may be evaluated within 2 days in a single experiment. Insights into the sequence-stability relationship will be obtained by monitoring the large number of low-level sequence variants, facilitating engineering of more stable molecules.

An evaluation of instrument types for mass spectrometry-based multi-attribute analysis of biotherapeutics

Multi-attribute methods (MAM), based on proteolytic digestion followed by liquid chromatography-mass spectrometry analysis of proteolytic peptides, have gained substantial attention in the biopharmaceutical industry for quantifying a variety of quality attributes for therapeutic proteins. Most MAM developed so far have been based on high-resolution mass spectrometers, due to their superb resolving power to distinguish analyte signals from interferences. Lower-resolution instruments, if demonstrated suitable, may further promote the adoption of the technology due to their low cost, small footprint, and ease of use. In this work, we compared the performance of a high-resolution instrument with a few low-resolution quadrupole-type instruments in quantifying a diverse set of quality attributes in a monoclonal antibody product. Different modes of operation for the quadrupole instruments, including scan mode, selected-ion monitoring and multiple-reaction monitoring, were evaluated. The high-resolution instrument has superb performance, with a quantitation limit of 0.002%. Single-quadrupole instruments in scan mode, on the other hand, provide a quantitation limit of about 1%, which may be fit-for-purpose for many routine MAM applications.

ANALYSIS OF CARBOHYDRATES AND GLYCOCONJUGATES BY MATRIX-ASSISTED LASER DESORPTION/IONIZATION MASS SPECTROMETRY: AN UPDATE FOR 2015-2016

This review is the ninth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2016. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation and arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals. Much of this material is presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented over 30 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show no sign of deminishing. © 2020 Wiley Periodicals, Inc.

Prediction of LC-MS/MS Properties of Peptides from Sequence by Deep Learning

Deep learning models for prediction of three key LC-MS/MS properties from peptide sequences were developed. The LC-MS/MS properties or behaviors are indexed retention times (iRT), MS1 or survey scan charge state distributions, and sequence ion intensities of HCD spectra. A common core deep supervised learning architecture, bidirectional long-short term memory (LSTM) recurrent neural networks was used to construct the three prediction models. Two featurization schemes were proposed and demonstrated to allow for efficient encoding of modifications. The iRT and charge state distribution models were trained with on order of 105 data points each. An HCD sequence ion prediction model was trained with 2 × 106 experimental spectra. The iRT prediction model and HCD sequence ion prediction model provide improved accuracies over the start-of-the-art models available in literature. The MS1 charge state distribution prediction model offers excellent performance. The prediction models can be used to enhance peptide identification and quantification in data-dependent acquisition and data-independent acquisition (DIA) experiments as well as to assist MRM (multiple reaction monitoring) and PRM (parallel reaction monitoring) experiment design.

Impact of Fc N-glycan sialylation on IgG structure

Human IgG antibodies containing terminal alpha 2,6-linked sialic acid on their Fc N-glycans have been shown to reduce antibody-dependent cell-mediated cytotoxicity and possess anti-inflammatory properties. Although terminal sialylation on complex N-glycans can happen via either an alpha 2,3-linkage or an alpha 2,6-linkage, sialic acids on human serum IgG Fc are almost exclusively alpha 2,6-linked. Recombinant IgGs expressed in Chinese hamster ovary (CHO) cells, however, have sialic acids through alpha 2,3-linkages because of the lack of the alpha 2,6-sialyltransferase gene. The impact of different sialylation linkages to the structure of IgG has not been determined. In this work, we investigated the impact of different types of sialylation to the conformational stability of IgG through hydrogen/deuterium exchange (HDX) and limited proteolysis experiments. When human-derived and CHO-expressed IgG1 were analyzed by HDX, sialic acid-containing glycans were found to destabilize the CH2 domain in CHO-expressed IgG, but not human-derived IgG. When structural isomers of sialylated glycans were chromatographically resolved and identified in the limited proteolysis experiment, we found that only alpha 2,3-linked sialic acid on the 6-arm (the major sialylated glycans in CHO-expressed IgG1) destabilizes the CH2 domain, presumably because of the steric effect that decreases the glycan-CH2 domain interaction. The alpha 2,6-linked sialic acid on the 3-arm (the major sialylated glycan in human-derived IgG), and the alpha 2,3-linked sialic acid on the 3-arm, do not have this destabilizing effect.

Reliable LC-MS Multiattribute Method for Biotherapeutics by Run-Time Response Calibration

A major challenge of a mass-spectrometry-based quantitative multiattribute method (MAM) for biotherapeutics is its high variability between instruments. For reproducible attribute measurements, not only is a similar instrument model required, but the instruments must also be tuned to the same condition. This poses great long-term challenges, considering the rapid development of new instrumentations. In addition, differences in digestion efficiency, peptide recovery, and artificial modifications during sample preparation also contribute to variability between laboratories. To overcome these challenges, new mathematical methods are developed to calculate the attribute abundance in the sample, using the reference standard (RS) material as calibrant. Most quality attributes in the RS remain constant throughout the life of the standard, and therefore, the RS can serve as a calibrant to correct for the difference between instruments or sample preparation procedures. Because RS data are usually collected in a MAM assay, no additional work is required from the analyst. Data from a large number of attributes demonstrated that these methodologies greatly reduced instrument-to-instrument and sample preparation variabilities. With these methodologies, a consistent instrument model and sample preparation procedure is no longer a requirement. As a result, changes in digestion procedure and advances in instrumentations will not significantly affect the assay result.

Recent advancements, challenges, and practical considerations in the mass spectrometry-based analytics of protein biotherapeutics: A viewpoint from the biosimilar industry

The extensive analytical characterization of protein biotherapeutics, especially of biosimilars, is a critical part of the product development and registration. High-resolution mass spectrometry became the primary analytical tool used for the structural characterization of biotherapeutics. Its high instrumental sensitivity and methodological versatility made it possible to use this technique to characterize both the primary and higher-order structure of these proteins. However, even by using high-end instrumentation, analysts face several challenges with regard to how to cope with industrial and regulatory requirements, that is, how to obtain accurate and reliable analytical data in a time- and cost-efficient way. New sample preparation approaches, measurement techniques and data evaluation strategies are available to meet those requirements. The practical considerations of these methods are discussed in the present review article focusing on hot topics, such as reliable and efficient sequencing strategies, minimization of artefact formation during sample preparation, quantitative peptide mapping, the potential of multi-attribute methodology, the increasing role of mass spectrometry in higher-order structure characterization and the challenges of MS-based identification of host cell proteins. On the basis of the opportunities in new instrumental techniques, methodological advancements and software-driven data evaluation approaches, for the future one can envision an even wider application area for mass spectrometry in the biopharmaceutical industry.

Molecular basis for the loss-of-function effects of the Alzheimer's disease-associated R47H variant of the immune receptor TREM2

Triggering receptor expressed on myeloid cells 2 (TREM2) is an immune receptor expressed on the surface of microglia, macrophages, dendritic cells, and osteoclasts. The R47H TREM2 variant is a significant risk factor for late-onset Alzheimer's disease (AD), and the molecular basis of R47H TREM2 loss of function is an emerging area of TREM2 biology. Here, we report three high-resolution structures of the extracellular ligand-binding domains (ECDs) of R47H TREM2, apo-WT, and phosphatidylserine (PS)-bound WT TREM2 at 1.8, 2.2, and 2.2 Å, respectively. The structures reveal that Arg⁴⁷ plays a critical role in maintaining the structural features of the complementarity-determining region 2 (CDR2) loop and the putative positive ligand-interacting surface (PLIS), stabilizing conformations capable of ligand interaction. This is exemplified in the PS-bound structure, in which the CDR2 loop and PLIS drive critical interactions with PS via surfaces that are disrupted in the variant. Together with in vitro and in vivo characterization, our structural findings elucidate the molecular mechanism underlying loss of ligand binding, putative oligomerization, and functional activity of R47H TREM2. They also help unravel how decreased in vitro and in vivo stability of TREM2 contribute to loss of function in disease.

Amino acid misincorporation in recombinant proteins

Proteins provide the molecular basis for cellular structure, catalytic activity, signal transduction, and molecular transport in biological systems. Recombinant protein expression is widely used to prepare and manufacture novel proteins that serve as the foundation of many biopharmaceutical products. However, protein translation bioprocesses are inherently prone to low-level errors. These sequence variants caused by amino acid misincorporation have been observed in both native and recombinant proteins. Protein sequence variants impact product quality, and their presence can be exacerbated through cellular stress, overexpression, and nutrient starvation. Therefore, the cell line selection process, which is used in the biopharmaceutical industry, is not only directed towards maximizing productivity, but also focuses on selecting clones which yield low sequence variant levels, thereby proactively avoiding potentially inauspicious patient safety and efficacy outcomes. Here, we summarize a number of hallmark studies aimed at understanding the mechanisms of amino acid misincorporation, as well as exacerbating factors, and mitigation strategies. We also describe key advances in analytical technologies in the identification and quantification of sequence variants, and some practical considerations when using LC-MS/MS for detecting sequence variants.

Tandem mass spectral libraries of peptides and their roles in proteomics research

Proteomics is a rapidly maturing field aimed at the high-throughput identification and quantification of all proteins in a biological system. The cornerstone of proteomic technology is tandem mass spectrometry of peptides resulting from the digestion of protein mixtures. The fragmentation pattern of each peptide ion is captured in its tandem mass spectrum, which enables its identification and acts as a fingerprint for the peptide. Spectral libraries are simply searchable collections of these fingerprints, which have taken on an increasingly prominent role in proteomic data analysis. This review describes the historical development of spectral libraries in proteomics, details the computational procedures behind library building and searching, surveys the current applications of spectral libraries, and discusses the outstanding challenges. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:634-648, 2017.

Effect of Fc-Glycan Structure on the Conformational Stability of IgG Revealed by Hydrogen/Deuterium Exchange and Limited Proteolysis

Human therapeutic immunoglobulin gamma (IgG) molecules contain an N-glycan on each of their Fc CH2 domains. These glycans include high-mannose, hybrid, and complex types. Recombinant IgG molecules containing high-mannose glycans have been shown to clear faster in human blood, and exhibit decreased thermal stability. The molecular mechanism behind these observations, however, is not well understood. In this work, we used hydrogen/deuterium exchange combined with mass spectrometry (HDX MS), as well as proteolytic degradation under a native-like condition, to assess the impact of different glycoforms on the molecular structure and stability of recombinant IgG1 and IgG2 molecules expressed from Chinese hamster ovary cells. Our HDX MS data indicate that the conformation of these IgG molecules was indeed influenced by the glycan structure. IgG molecules containing high-mannose and hybrid glycans showed more conformational flexibility in the CH2 domain. This conclusion was further supported by the analysis of glycopeptides released from these molecules by trypsin digestion under a native-like condition. The higher CH2 conformational flexibility of IgG molecules with high-mannose and hybrid glycans contributes to their decreased thermal stability. IgG molecules containing sialylated glycans in the CH2 domain exhibited similar enzymatic degradation behavior as high-mannose glycans, suggesting decreased CH2-domain stability compared to shorter complex glycans, likely resulting from steric effect that decreased the glycan-CH2 domain interaction.

Engaging challenges in glycoproteomics: recent advances in MS-based glycopeptide analysis

The proteomic analysis of glycosylation is uniquely challenging. The numerous and varied biological roles of protein-linked glycans have fueled a tremendous demand for technologies that enable rapid, in-depth structural examination of glycosylated proteins in complex biological systems. In turn, this demand has driven many innovations in wide ranging fields of bioanalytical science. This review will summarize key developments in glycoprotein separation and enrichment, glycoprotein proteolysis strategies, glycopeptide separation and enrichment, the role of mass measurement accuracy in glycopeptide detection, glycopeptide ion dissociation methods for MS/MS, and informatic tools for glycoproteomic analysis. In aggregate, this selection of topics serves to encapsulate the present status of MS-based analytical technologies for engaging the challenges of glycoproteomic analysis.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: an update for 2009-2010

This review is the sixth update of the original article published in 1999 on the application of MALDI mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2010. General aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, arrays and fragmentation are covered in the first part of the review and applications to various structural typed constitutes the remainder. The main groups of compound that are discussed in this section are oligo and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals. Many of these applications are presented in tabular form. Also discussed are medical and industrial applications of the technique, studies of enzyme reactions and applications to chemical synthesis.

LC-MS/MS peptide mapping with automated data processing for routine profiling of N-glycans in immunoglobulins

Protein N-Glycan analysis is traditionally performed by high pH anion exchange chromatography (HPAEC), reversed phase liquid chromatography (RPLC), or hydrophilic interaction liquid chromatography (HILIC) on fluorescence-labeled glycans enzymatically released from the glycoprotein. These methods require time-consuming sample preparations and do not provide site-specific glycosylation information. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) peptide mapping is frequently used for protein structural characterization and, as a bonus, can potentially provide glycan profile on each individual glycosylation site. In this work, a recently developed glycopeptide fragmentation model was used for automated identification, based on their MS/MS, of N-glycopeptides from proteolytic digestion of monoclonal antibodies (mAbs). Experimental conditions were optimized to achieve accurate profiling of glycoforms. Glycan profiles obtained from LC-MS/MS peptide mapping were compared with those obtained from HPAEC, RPLC, and HILIC analyses of released glycans for several mAb molecules. Accuracy, reproducibility, and linearity of the LC-MS/MS peptide mapping method for glycan profiling were evaluated. The LC-MS/MS peptide mapping method with fully automated data analysis requires less sample preparation, provides site-specific information, and may serve as an alternative method for routine profiling of N-glycans on immunoglobulins as well as other glycoproteins with simple N-glycans.

Assessment of naturally occurring covalent and total dimer levels in human IgG1 and IgG2

Antibody dimers, two self-associated monomers, have been detected on both recombinantly expressed and endogenous human IgG proteins. Nearly 10 years ago, Yoo et al. (2003) described low levels of IgG2 covalent dimer, in human serum, but did not quantify the levels. Here we quantify the total and covalent dimer levels of IgG2 and IgG1 in human blood, and study the origin of covalent dimer formation. Low levels (<1%) of total IgG1 and IgG2 dimers were measured in freshly prepared human plasma. Both IgG1 and IgG2 covalent dimers were also found in plasma. Whereas IgG1 covalent dimer levels were significantly reduced by steps intended to eliminate artifacts during sample preparation, IgG2 covalent dimer levels remain stable in such conditions. About 0.4% of IgG2 in plasma was in a covalent dimer form, yet very little (<0.03%) of IgG1 covalent dimer could be considered naturally occurring. IgG2 dimer also formed in vitro under conditions designed to mimic those in blood, suggesting that formation occurs in vivo during circulation. Thus, small amounts of covalent IgG2 dimer do appear to form naturally.

ADME of monoclonal antibody biotherapeutics: knowledge gaps and emerging tools

Absorption, distribution, metabolism and excretion (ADME) data are pivotal for small-molecule drug development, with well-developed in vitro and in vivo correlation tools and guidances from regulatory agencies. In the past two decades, monoclonal antibody (mAb) biotherapeutics have been successfully approved, including derived novel conjugates of active molecules (toxins or bioactive peptides) for specific target delivery or half-life extension. However, ADME information of mAb therapeutics lags behind that of small molecules due to the complex nature of the molecules and lack of appropriate tools to study drug exposure, biotransformation, and target engagement in the vascular and tissue spaces. In this perspective, the current knowledge gaps on ADME of mAb-related therapeutics are reviewed with potential solutions from emerging analytical technologies.

Gas-phase dissociation of glycosylated peptide ions

Among the myriad of protein post-translational modifications (PTMs), glycosylation presents a singular analytical challenge. On account of the extraordinary diversity of protein-linked carbohydrates and the great complexity with which they decorate glycoproteins, the rigorous establishment of glycan-protein connectivity is often an arduous experimental venture. Consequently, elaborating the interplay between structures of oligosaccharides and functions of proteins they modify is usually not a straightforward task. A more mature biochemical appreciation of carbohydrates as PTMs will significantly hinge upon analytical advances in the field of glycoproteomics. Undoubtedly, the analysis of glycosylated peptides by tandem mass spectrometry (MS/MS) will play a pivotal role in this regard. The goal of this review is to summarize, from an analytical and tutorial perspective, the present state of knowledge regarding the dissociation of glycopeptide ions as accomplished by various MS/MS methods. In addition, this review will endeavor to harmonize some seemingly disparate findings to provide a more complete and broadly applicable description of glycopeptide ion fragmentation. A fuller understanding of the rich variety of glycopeptide dissociation behaviors will allow glycoproteomic researchers to maximize the information yielded by MS/MS experiments, while also paving the way to new innovations in MS-based glycoproteomics.

Calculations of relative intensities of fragment ions in the MSMS spectra of a doubly charged penta-peptide

BACKGROUND

Currently, the tandem mass spectrometry (MSMS) of peptides is a dominant technique used to identify peptides and consequently proteins. The peptide fragmentation inside the mass analyzer typically offers a spectrum containing several different groups of ions. The mass to charge (m/z) values of these ions can be exactly calculated following simple rules based on the possible peptide fragmentation reactions. But the (relative) intensities of the particular ions cannot be simply predicted from the amino-acid sequence of the peptide. This study presents initial work towards developing a theoretical fundamental approach to ion intensity elucidation by utilizing quantum mechanical computations.

METHODS

MSMS spectra of the doubly charged GAVLK peptide were collected on electrospray ion trap mass spectrometers using low energy modes of fragmentation. Density functional theory (DFT) calculations were performed on the population of ion precursors to determine the fragment ion intensities corresponding to a Boltzmann distribution of the protonation of nitrogens in the peptide backbone amide bonds.

RESULTS

We were able to a) predict the y and b ions intensities order in concert with the experimental observation; b) predict relative intensities of y ions with errors not exceeding the experimental variation.

CONCLUSIONS

These results suggest that the GAVLK peptide fragmentation process in the ion trap mass spectrometer is predominantly driven by the thermodynamic stability of the precursor ions formed upon ionization of the sample. The computational approach presented in this manuscript successfully calculated ion intensities in the mass spectra of this doubly charged tryptic peptide, based solely on its amino acid sequence. As such, this work indicates a potential of incorporating quantum mechanical calculations into mass spectrometry based algorithms for molecular identification.

Automated precursor ion exclusion during LC-MS/MS data acquisition for optimal ion identification

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is widely used for characterizing multiple samples of complex mixtures with similar compositions. This article addresses a data acquisition strategy for collecting a maximal number of unique, high-quality MS/MS during LC-MS/MS analysis of multiple samples. Based on the concept that a component only needs to be identified once when analyzing multiple samples with similar compositions, an automated intersample data-dependent acquisition strategy was developed. The strategy is based on precursor ion exclusion (PIE) and is implemented in MassAnalyzer in an automated fashion for Thermo Scientific (San Jose, CA, USA) mass spectrometers. In this method, MassAnalyzer submits one sample at a time to the sample queue. After data acquisition of each sample, MassAnalyzer automatically analyzes the data to generate a PIE list based on the MS/MS precursor ions, merges this list with the list generated from previous runs, adds the list to the MS method file, and submits the next sample to the queue. The PIE list contains both m/z value and time window for each precursor ion, and is generated intelligently so that if an MS/MS is insufficient for identifying the peak of interest, it will be collected again near the top of the peak in the next run. Therefore, the strategy maximizes both quality and the number of unique MS/MS. When automated PIE was used to acquire LC-MS/MS data of an antibody tryptic digest and a soy hydrolysate sample, the number of identified ions increased by 52% and 93%, respectively, compared with data acquired without using PIE.

GlycoPep grader: a web-based utility for assigning the composition of N-linked glycopeptides

GlycoPep grader (GPG) is a freely available software tool designed to accelerate the process of accurately determining glycopeptide composition from tandem mass spectrometric data. GPG relies on the identification of unique dissociation patterns shown for high mannose, hybrid, and complex N-linked glycoprotein types, including patterns specific to those structures containing fucose or sialic acid residues. The novel GPG scoring algorithm scores potential candidate compositions of the same nominal mass against MS/MS data through evaluation of the Y(1) ion and other peptide-containing product ions, across multiple charge states, when applicable. In addition to evaluating the peptide portion of a given glycopeptide, the GPG algorithm predicts and scores product ions that result from unique neutral losses of terminal glycans. GPG has been applied to a variety of glycoproteins, including RNase B, asialofetuin, and transferrin, and the HIV envelope glycoprotein, CON-S gp140ΔCFI. The GPG software is implemented predominantly in PostgreSQL, with PHP as the presentation tier, and is publicly accessible online. Thus far, the algorithm has identified the correct compositional assignment from multiple candidate N-glycopeptides in all tests performed.