Progress and challenges in mass spectrometry-based analysis of antibody repertoires

Public antibodies: convergent signatures in human humoral immunity against pathogens

The human humoral immune system has evolved to recognize a vast array of pathogenic threats. This ability is primarily driven by the immense diversity of antibodies generated by gene rearrangement during B cell development. However, different people often produce strikingly similar antibodies when exposed to the same antigen-known as public antibodies. Public antibodies not only reflect the immune system's ability to consistently select for optimal B cells but can also serve as signatures of the humoral responses triggered by infection and vaccination. In this Minireview, we examine and compare public antibody identification methods, including the identification criteria used based on V(D)J gene usage and similarity in the complementarity-determining region three sequences, and explore the molecular features of public antibodies elicited against common pathogens, including viruses, protozoa, and bacteria. Finally, we discuss the evolutionary significance and potential applications of public antibodies in informing the design of germline-targeting vaccines, predicting escape mutations in emerging viruses, and providing insights into the process of affinity maturation. The ongoing discovery of public antibodies in response to emerging pathogens holds the potential to improve pandemic preparedness, accelerate vaccine design efforts, and deepen our understanding of human B cell biology.

Top-Down and Middle-Down Mass Spectrometry of Antibodies

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 the use of 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 the use of 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, and endogenous antibodies from biofluids as well as immunoglobulin A and M-type classes. Content.

A transformer-based semi-autoregressive framework for high-speed and accurate de novo peptide sequencing

De novo peptide sequencing directly identifies peptides from mass spectrometry data, playing a critical role in discovering novel proteins and analyzing complex biological samples without reliance on existing databases. To address challenges in both speed and accuracy, a transformer-based model, TSARseqNovo, incorporates two key innovations: a Semi-Autoregressive decoder for parallel prediction of multiple amino acids and a Masking Refinement decoder for refining low-confidence predictions. These features significantly enhance sequencing efficiency and accuracy. Evaluations on the Nine-Species, Aggregated, and Glycoproteomic datasets, demonstrate that TSARseqNovo outperforms state-of-the-art models, including CasaNovo, NovoB, InstaNovo + , and π-HelixNovo. Specifically, TSARseqNovo achieves up to a 2-fold speed increase over CasaNovo and π-HelixNovo, and approximately 10-fold over NovoB and InstaNovo + , while also showing substantial improvements in peptide prediction precision, especially for long peptides. These advancements position TSARseqNovo as a powerful tool for accelerating high-throughput proteomics research and addressing increasingly complex biological questions.

AntiBody Sequence Database

Antibodies play a crucial role in the humoral immune response against health threats, such as viral infections. Although the theoretical number of human immunoglobulins is well over a trillion, the total number of unique antibody protein sequences accessible in databases is much lower than the number found in a single individual. Training AI (Artificial Intelligence) models, for example to assist in developing serodiagnoses or antibody-based therapies, requires building datasets according to strict criteria to include as many standardized antibody sequences as possible. However, the available sequences are scattered across partially redundant databases, making it difficult to compile them into single non-redundant datasets. Here, we introduce ABSD (AntiBody Sequence Database, https://absd.pasteur.cloud), which contains data from major publicly available resources, creating the largest standardized, automatically updated and non-redundant source of public antibody sequences. This user-friendly and open website enables users to generate lists of antibodies based on selected criteria and download the unique sequence pairs of their variable regions.

Nanobodies: From High-Throughput Identification to Therapeutic Development

The camelid single-domain antibody fragment, commonly referred to as a nanobody, achieves the targeting power of conventional monoclonal antibodies (mAbs) at only a fraction of their size. Isolated from camelid species (including llamas, alpacas, and camels), their small size at ∼15 kDa, low structural complexity, and high stability compared with conventional antibodies have propelled nanobody technology into the limelight of biologic development. Nanobodies are proving themselves to be a potent complement to traditional mAb therapies, showing success in the treatment of, for example, autoimmune diseases and cancer, and more recently as therapeutic options to treat infectious diseases caused by rapidly evolving biological targets such as the SARS-CoV-2 virus. This review highlights the benefits of applying a proteomic approach to identify diverse nanobody sequences against a single antigen. This proteomic approach coupled with conventional yeast/phage display methods enables the production of highly diverse repertoires of nanobodies able to bind the vast epitope landscape of an antigen, with epitope sampling surpassing that of mAbs. Additionally, we aim to highlight recent findings illuminating the structural attributes of nanobodies that make them particularly amenable to comprehensive antigen sampling and to synergistic activity-underscoring the powerful advantage of acquiring a large, diverse nanobody repertoire against a single antigen. Lastly, we highlight the efforts being made in the clinical development of nanobodies, which have great potential as powerful diagnostic reagents and treatment options, especially when targeting infectious disease agents.

Direct Mapping of Polyclonal Epitopes in Serum by HDX-MS

Elucidating the interactions that drive antigen recognition is central to understanding antibody-mediated protection and is vital for the rational design of immunogens. Often, structural knowledge of epitopes targeted by antibodies is derived from isolated studies of monoclonal antibodies, for which numerous structural techniques exist. In contrast, there are very few approaches capable of mapping the full scope of antigen surfaces targeted by polyclonal sera through the course of a natural antibody response. Here, we develop an approach using immobilized antigen coupled to hydrogen/deuterium exchange with mass spectrometry (HDX-MS) to probe epitope targeting in the context of the fully native serum environment. Using the well-characterized Staphylococcal enterotoxin B (SEB) as a model system, we show that complex combinations of epitopes can be detected and subtle differences across different antisera can be discerned. This work reveals new insight into how neutralizing antibodies and antisera target SEB and, more importantly, establishes a novel method for directly mapping the epitope landscape of polyclonal sera.

Human milk proteins differentiate over the sex of newborns and across stages of lactation

BACKGROUND & AIMS

Human milk (HM) is a complete food that meets the nutritional and energy demands of the newborns. It contains numerous bioactive components, including functional proteins. Variations in HM energy and lipid content have already been reported related to the newborn's sex, but differences between protein profiles are still scarce. This work aimed to identify differences between HM proteins produced by mothers of female and male newborns, in the lactation stages of colostrum and mature milk, and the metabolic pathways involved.

METHODS

A total of 98 HM samples were collected from 39 lactating women and classified according to the newborn's sex, stages of lactation, and three mothers' age groups, and evaluated about protein concentration and one-dimensional electrophoretic profile. Next, to assess samples with the greatest differences, the HM proteins regarding the newborn's sex and the stages of lactation were compared using nano-LC-MS/MS, in 24 HM samples randomly rearranged into four groups: female and male infants, and colostrum and mature milk. Functional classification, metabolic pathways, and protein interaction networks were analyzed by Gene Ontology, KEGG, and STRING, respectively.

RESULTS

The soluble protein content of HM decreased throughout lactation, with differences regarding isolated factors, such as mothers' age group, child's sex and stages of lactation, and also in terms of their interactions. A total of 146 proteins were identified, 42 of which showed different abundances over the sexes of newborns and 53 between the stages of lactation. In general, proteins related to metabolic processes were up-regulated for mothers of male infants and in the mature stage of lactation, while proteins related to defense were up-regulated in mothers of female infants and in the colostrum phase.

CONCLUSION

This study indicated that there are differentiated and specific nutritional and defense needs of newborns, by sex and by lactation phase, which is highly relevant for a more appropriate supply of food to infants receiving HM from donor mothers.

Benchmarking and integrating human B-cell receptor genomic and antibody proteomic profiling

Immunoglobulins (Ig), which exist either as B-cell receptors (BCR) on the surface of B cells or as antibodies when secreted, play a key role in the recognition and response to antigenic threats. The capability to jointly characterize the BCR and antibody repertoire is crucial for understanding human adaptive immunity. From peripheral blood, bulk BCR sequencing (bulkBCR-seq) currently provides the highest sampling depth, single-cell BCR sequencing (scBCR-seq) allows for paired chain characterization, and antibody peptide sequencing by tandem mass spectrometry (Ab-seq) provides information on the composition of secreted antibodies in the serum. Yet, it has not been benchmarked to what extent the datasets generated by these three technologies overlap and complement each other. To address this question, we isolated peripheral blood B cells from healthy human donors and sequenced BCRs at bulk and single-cell levels, in addition to utilizing publicly available sequencing data. Integrated analysis was performed on these datasets, resolved by replicates and across individuals. Simultaneously, serum antibodies were isolated, digested with multiple proteases, and analyzed with Ab-seq. Systems immunology analysis showed high concordance in repertoire features between bulk and scBCR-seq within individuals, especially when replicates were utilized. In addition, Ab-seq identified clonotype-specific peptides using both bulk and scBCR-seq library references, demonstrating the feasibility of combining scBCR-seq and Ab-seq for reconstructing paired-chain Ig sequences from the serum antibody repertoire. Collectively, our work serves as a proof-of-principle for combining bulk sequencing, single-cell sequencing, and mass spectrometry as complementary methods towards capturing humoral immunity in its entirety.

Protein-Centric Analysis of Personalized Antibody Repertoires Using LC-MS-Based Fab-Profiling on a timsTOF

Endogenous antibodies, or immunoglobulins (Igs), abundantly present in body fluids, represent some of the most challenging samples to analyze, largely due to the immense variability in their sequences and concentrations. It has been estimated that our body can produce billions of different Ig proteins with different isotypes, making their individual analysis seemingly impossible. However, recent advances in protein-centric proteomics using LC-MS coupled to Orbitrap mass analyzers to profile intact Fab fragments formed by selective cleavage at the IgG-hinge revealed that IgG repertoires may be less diverse, albeit unique for each donor. Serum repertoires seem to be dominated by a few hundred clones that cumulatively make up 50-95% of the total IgG content. Enabling such analyses required careful optimization of the chromatography and mass analysis, as all Fab analytes are highly alike in mass (46-51 kDa) and sequence. To extend the opportunities of this mass-spectrometry-based profiling of antibody repertoires, we here report the optimization and evaluation of an alternative MS platform, namely, the timsTOF, for antibody repertoire profiling. The timsTOF mass analyzer has gained traction in recent years for peptide-centric proteomics and found wide applicability in plasma proteomics, affinity proteomics, and HLA peptidomics, to name a few. However, for protein-centric analysis, this platform has been less explored. Here, we demonstrate that the timsTOF platform can be adapted to perform protein-centric LC-MS-based profiling of antibody repertoires. In a side-by-side comparison of the timsTOF and the Orbitrap we demonstrate that the extracted serum antibody repertoires are alike qualitatively and quantitatively, whereby in particular the sensitivity of the timsTOF platform excels. Future incorporation of advanced top-down capabilities on the timsTOF may make this platform a very valuable alternative for protein-centric proteomics and top-down proteomics and thus also for personalized antibody repertoire profiling.

Innovations and trends in antibody repertoire analysis

Monoclonal antibodies have revolutionized the treatment of human diseases, which has made them the fastest-growing class of therapeutics, with global sales expected to reach $346.6 billion USD by 2028. Advances in antibody engineering and development have led to the creation of increasingly sophisticated antibody-based therapeutics (e.g. bispecific antibodies and chimeric antigen receptor T cells). However, approaches for antibody discovery have remained comparatively grounded in conventional yet reliable in vitro assays. Breakthrough developments in high-throughput single B-cell sequencing and immunoglobulin proteomic serology, however, have enabled the identification of high-affinity antibodies directly from endogenous B cells or circulating immunoglobulin produced in vivo. Moreover, advances in artificial intelligence offer vast potential for antibody discovery and design with large-scale repertoire datasets positioned as the optimal source of training data for such applications. We highlight advances and recent trends in how these technologies are being applied to antibody repertoire analysis.

Toolkit for mapping the clonal landscape of tumor-infiltrating B cells

Our current understanding of whether B cell involvement in the tumor microenvironment benefits the patient or the tumor - in distinct cancers, subcohorts and individual patients - is quite limited. Both statements are probably true in most cases: certain clonal B cell populations contribute to the antitumor response, while others steer the immune response away from the desired mechanics. To step up to a new level of understanding and managing B cell behaviors in the tumor microenvironment, we need to rationally discern these roles, which are cumulatively defined by B cell clonal functional programs, specificities of their B cell receptors, specificities and isotypes of the antibodies they produce, and their spatial interactions within the tumor environment. Comprehensive analysis of these characteristics of clonal B cell populations is now becoming feasible with the development of a whole arsenal of advanced technical approaches, which include (1) methods of single-cell and spatial transcriptomics, genomics, and proteomics; (2) methods of massive identification of B cell specificities; (3) methods of deep error-free profiling of B cell receptor repertoires. Here we overview existing techniques, summarize their current application for B cells studies and propose promising future directions in advancing B cells exploration.

Peptide Antibodies: Current Status

Peptide antibodies have become one of the most important classes of reagents in molecular biology and clinical diagnostics. For this reason, methods for their production and characterization continue to be developed, including basic peptide synthesis protocols, peptide-conjugate production and characterization, conformationally restricted peptides, immunization procedures, etc. Detailed mapping of peptide antibody epitopes has yielded important information on antibody-antigen interaction in general and specifically in relation to antibody cross-reactivity and theories of molecular mimicry. This information is essential for detailed understanding of paratope-epitope dynamics, design of antibodies for research, design of peptide-based vaccines, development of therapeutic peptide antibodies, and de novo design of antibodies with predetermined specificity.

Redefining serological diagnostics with immunoaffinity proteomics

Serological diagnostics is generally defined as the detection of specific human immunoglobulins developed against viral, bacterial, or parasitic diseases. Serological tests facilitate the detection of past infections, evaluate immune status, and provide prognostic information. Serological assays were traditionally implemented as indirect immunoassays, and their design has not changed for decades. The advantages of straightforward setup and manufacturing, analytical sensitivity and specificity, affordability, and high-throughput measurements were accompanied by limitations such as semi-quantitative measurements, lack of universal reference standards, potential cross-reactivity, and challenges with multiplexing the complete panel of human immunoglobulin isotypes and subclasses. Redesign of conventional serological tests to include multiplex quantification of immunoglobulin isotypes and subclasses, utilize universal reference standards, and minimize cross-reactivity and non-specific binding will facilitate the development of assays with higher diagnostic specificity. Improved serological assays with higher diagnostic specificity will enable screenings of asymptomatic populations and may provide earlier detection of infectious diseases, autoimmune disorders, and cancer. In this review, we present the major clinical needs for serological diagnostics, overview conventional immunoassay detection techniques, present the emerging immunoassay detection technologies, and discuss in detail the advantages and limitations of mass spectrometry and immunoaffinity proteomics for serological diagnostics. Finally, we explore the design of novel immunoaffinity-proteomic assays to evaluate cell-mediated immunity and advance the sequencing of clinically relevant immunoglobulins.

Database Creator for Mass Analysis of Peptides and Proteins, DC-MAPP: A Standalone Tool for Simplifying Manual Analysis of Mass Spectral Data to Identify Peptide/Protein Sequences

Proteomic studies typically involve the use of different types of software for annotating experimental tandem mass spectrometric data (MS/MS) and thereby simplifying the process of peptide and protein identification. For such annotations, these softwares calculate the m/z values of the peptide/protein precursor and fragment ions, for which a database of protein sequences must be provided as an input file. The calculated m/z values are stored as another database, which the user usually cannot view. Database Creator for Mass Analysis of Peptides and Proteins (DC-MAPP) is a novel standalone software that can create custom databases for "viewing" the calculated m/z values of precursor and fragment ions, prior to the database search. It contains three modules. Peptide/Protein sequences as per user's choice can be entered as input to the first module for creating a custom database. In the second module, m/z values must be queried-in, which are searched within the custom database to identify protein/peptide sequences. The third module is suited for peptide mass fingerprinting, which can be used to analyze both ESI and MALDI mass spectral data. The feature of "viewing" the custom database can be helpful not only for better understanding the search engine processes, but also for designing multiple reaction monitoring (MRM) methods. Post-translational modifications and protein isoforms can also be analyzed. Since, DC-MAPP relies on the protein/peptide "sequences" for creating custom databases, it may not be applicable for the searches involving spectral libraries. Python language was used for implementation, and the graphical user interface was built with Page/Tcl, making this tool more user-friendly. It is freely available at https://vit.ac.in/DC-MAPP/.

Defining and Studying B Cell Receptor and TCR Interactions

BCRs (Abs) and TCRs (or adaptive immune receptors [AIRs]) are the means by which the adaptive immune system recognizes foreign and self-antigens, playing an integral part in host defense, as well as the emergence of autoimmunity. Importantly, the interaction between AIRs and their cognate Ags defies a simple key-in-lock paradigm and is instead a complex many-to-many mapping between an individual's massively diverse AIR repertoire, and a similarly diverse antigenic space. Understanding how adaptive immunity balances specificity with epitopic coverage is a key challenge for the field, and terms such as broad specificity, cross-reactivity, and polyreactivity remain ill-defined and are used inconsistently. In this Immunology Notes and Resources article, a group of experimental, structural, and computational immunologists define commonly used terms associated with AIR binding, describe methodologies to study these binding modes, as well as highlight the implications of these different binding modes for therapeutic design.

Some structural features of the peptide profile of myelin basic protein-hydrolyzing antibodies in schizophrenic patients

The antibodies of schizophrenic patients that hydrolyze myelin basic protein (MBP) have been actively studied recently, but the mechanism of the catalytic properties of immunoglobulin molecules remains unknown. Determination of specific immunoglobulin sequences associated with the high activity of MBP proteolysis will help to understand the mechanisms of abzyme catalysis. In the course of comparative mass spectrometric analysis of IgG peptides from the blood serum of patients with acute schizophrenia and healthy people, 12 sequences were identified, which were found only in antibodies that hydrolyze MBP. These sequences belong to IgG heavy chains and κ- and λ-type light chains, with eight of them belonging to variable domains. The content of peptides from the variable regions of the light chains does not correlate with the proteolytic activity of IgG to MBP in patients with schizophrenia, whereas for two sequences from the variable regions of the heavy chains (FQ(+0.98)GWVTMTR and *LYLQMN(+0.98)SLR), an increase in activity with increasing their concentration. The results suggest that these sequences may be involved in one way or another in MBP hydrolysis.

Immunoglobulin repertoire restriction characterizes the serological responses of patients with predominantly antibody deficiency

BACKGROUND

Predominantly antibody deficiency (PAD) is the most common category of inborn errors of immunity and is underpinned by impaired generation of appropriate antibody diversity and quantity. In the clinic, responses are interrogated by assessment of vaccination responses, which is central to many PAD diagnoses. However, the composition of the generated antibody repertoire is concealed from traditional quantitative measures of serological responses. Leveraging modern mass spectrometry-based proteomics (MS-proteomics), it is possible to elaborate the molecular features of specific antibody repertoires, which may address current limitations of diagnostic vaccinology.

OBJECTIVES

We sought to evaluate serum antibody responses in patients with PAD following vaccination with a neo-antigen (severe acute respiratory syndrome coronavirus-2 vaccination) using MS-proteomics.

METHODS

Following severe acute respiratory syndrome coronavirus-2 vaccination, serological responses in individuals with PAD and healthy controls (HCs) were assessed by anti-S1 subunit ELISA and neutralization assays. Purified anti-S1 subunit IgG and IgM was profiled by MS-proteomics for IGHV subfamily usage and somatic hypermutation analysis.

RESULTS

Twelve patients with PAD who were vaccine-responsive were recruited with 11 matched vaccinated HCs. Neutralization and end point anti-S1 titers were lower in PAD. All subjects with PAD demonstrated restricted anti-S1 IgG antibody repertoires, with usage of <5 IGHV subfamilies (median: 3; range 2-4), compared to ≥5 for the 11 HC subjects (P < .001). IGHV3-7 utilization was far less common in patients with PAD than in HCs (2 of 12 vs 10 of 11; P = .001). Amino acid substitutions due to somatic hypermutation per subfamily did not differ between groups. Anti-S1 IgM was present in 64% and 50% of HC and PAD cohorts, respectively, and did not differ significantly between HCs and patients with PAD.

CONCLUSIONS

This study demonstrates the breadth of anti-S1 antibodies elicited by vaccination at the proteome level and identifies stereotypical restriction of IGHV utilization in the IgG repertoire in patients with PAD compared with HC subjects. Despite uniformly pauci-clonal antibody repertoires some patients with PAD generated potent serological responses, highlighting a possible limitation of traditional serological techniques. These findings suggest that IgG repertoire restriction is a key feature of antibody repertoires in PAD.

Single-cell transcriptomics combined with proteomics of intrathecal IgG reveal transcriptional heterogeneity of oligoclonal IgG-secreting cells in multiple sclerosis

The phenotypes of B lineage cells that produce oligoclonal IgG in multiple sclerosis have not been unequivocally determined. Here, we utilized single-cell RNA-seq data of intrathecal B lineage cells in combination with mass spectrometry of intrathecally synthesized IgG to identify its cellular source. We found that the intrathecally produced IgG matched a larger fraction of clonally expanded antibody-secreting cells compared to singletons. The IgG was traced back to two clonally related clusters of antibody-secreting cells, one comprising highly proliferating cells, and the other consisting of more differentiated cells expressing genes associated with immunoglobulin synthesis. These findings suggest some degree of heterogeneity among cells that produce oligoclonal IgG in multiple sclerosis.

Protocol to determine antibody affinity and concentration in complex solutions using microfluidic antibody affinity profiling

Conventional methods of measuring affinity are limited by artificial immobilization, large sample volumes, and homogeneous solutions. This protocol describes microfluidic antibody affinity profiling on complex human samples in solution to obtain a fingerprint reflecting both affinity and active concentration of the target protein. To illustrate the protocol, we analyze the antibody response in SARS-CoV-2 omicron-naïve samples against different SARS-CoV-2 variants of concern. However, the protocol and the technology are amenable to a broad spectrum of biomedical questions. For complete details on the use and execution of this protocol, please refer to Emmenegger et al. (2022),1 Schneider et al. (2022),2 and Fiedler et al. (2022).3.

[Antibody proteomics]

Antibodies represent an essential component of humoral immunity; therefore their study is important for molecular biology and medicine. The unique property of antibodies to specifically recognize and bind a certain molecular target (an antigen) determines their widespread application in treatment and diagnostics of diseases, as well as in laboratory and biotechnological practices. High specificity and affinity of antibodies is determined by the presence of primary structure variable regions, which are not encoded in the human genome and are unique for each antibody-producing B cell clone. Hence, there is little or no information about amino acid sequences of the variable regions in the databases. This differs identification of antibody primary structure from most of the proteomic studies because it requires either B cell genome sequencing or de novo amino acid sequencing of the antibody. The present review demonstrates some examples of proteomic and proteogenomic approaches and the methodological arsenal that proteomics can offer for studying antibodies, in particular, for identification of primary structure, evaluation of posttranslational modifications and application of bioinformatics tools for their decoding.

Comprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly

Monoclonal antibodies are biotechnologically produced proteins with various applications in research, therapeutics and diagnostics. Their ability to recognize and bind to specific molecule structures makes them essential research tools and therapeutic agents. Sequence information of antibodies is helpful for understanding antibody-antigen interactions and ensuring their affinity and specificity. De novo protein sequencing based on mass spectrometry is a valuable method to obtain the amino acid sequence of peptides and proteins without a priori knowledge. In this study, we evaluated six recently developed de novo peptide sequencing algorithms (Novor, pNovo 3, DeepNovo, SMSNet, PointNovo and Casanovo), which were not specifically designed for antibody data. We validated their ability to identify and assemble antibody sequences on three multi-enzymatic data sets. The deep learning-based tools Casanovo and PointNovo showed an increased peptide recall across different enzymes and data sets compared with spectrum-graph-based approaches. We evaluated different error types of de novo peptide sequencing tools and their performance for different numbers of missing cleavage sites, noisy spectra and peptides of various lengths. We achieved a sequence coverage of 97.69-99.53% on the light chains of three different antibody data sets using the de Bruijn assembler ALPS and the predictions from Casanovo. However, low sequence coverage and accuracy on the heavy chains demonstrate that complete de novo protein sequencing remains a challenging issue in proteomics that requires improved de novo error correction, alternative digestion strategies and hybrid approaches such as homology search to achieve high accuracy on long protein sequences.

The evolutionary and functional significance of germline immunoglobulin gene variation

The recombination between immunoglobulin (IG) gene segments determines an individual's naïve antibody repertoire and, consequently, (auto)antigen recognition. Emerging evidence suggests that mammalian IG germline variation impacts humoral immune responses associated with vaccination, infection, and autoimmunity - from the molecular level of epitope specificity, up to profound changes in the architecture of antibody repertoires. These links between IG germline variants and immunophenotype raise the question on the evolutionary causes and consequences of diversity within IG loci. We discuss why the extreme diversity in IG loci remains a mystery, why resolving this is important for the design of more effective vaccines and therapeutics, and how recent evidence from multiple lines of inquiry may help us do so.

Mass Spectrometry-Based Approaches for Clinical Biomarker Discovery in Traumatic Brain Injury

Purpose of Review

Precision treatments to address the multifaceted pathophysiology of traumatic brain injury (TBI) are desperately needed, which has led to the intense study of fluid-based protein biomarkers in TBI. Mass Spectrometry (MS) is increasingly being applied to biomarker discovery and quantification in neurological disease to explore the proteome, allowing for more flexibility in biomarker discovery than commonly encountered antibody-based assays. In this narrative review, we will provide specific examples of how MS technology has advanced translational research in traumatic brain injury (TBI) focusing on clinical studies, and looking ahead to promising emerging applications of MS to the field of Neurocritical Care.

Recent Findings

Proteomic biomarker discovery using MS technology in human subjects has included the full range of injury severity in TBI, though critically ill patients can offer more options to biofluids given the need for invasive monitoring. Blood, urine, cerebrospinal fluid, brain specimens, and cerebral extracellular fluid have all been sources for analysis. Emerging evidence suggests there are distinct proteomic profiles in radiographic TBI subtypes, and that biomarkers may be used to distinguish patients sustaining TBI from healthy controls. Metabolomics may offer a window into the perturbations of ongoing cerebral insults in critically ill patients after severe TBI.

Summary

Emerging MS technologies may offer biomarker discovery and validation opportunities not afforded by conventional means due to its ability to handle the complexities associated with the proteome. While MS techniques are relatively early in development in the neurosciences space, the potential applications to TBI and neurocritical care are likely to accelerate in the coming decade.

The human milk proteome and allergy of mother and child: Exploring associations with protein abundances and protein network connectivity

Background

The human milk proteome comprises a vast number of proteins with immunomodulatory functions, but it is not clear how this relates to allergy of the mother or allergy development in the breastfed infant. This study aimed to explore the relation between the human milk proteome and allergy of both mother and child.

Methods

Proteins were analyzed in milk samples from a subset of 300 mother-child dyads from the Canadian CHILD Cohort Study, selected based on maternal and child allergy phenotypes. For this selection, the definition of "allergy" included food allergy, eczema, allergic rhinitis, and asthma. Proteins were analyzed with non-targeted shotgun proteomics using filter-aided sample preparation (FASP) and nanoLC-Orbitrap-MS/MS. Protein abundances, based on label-free quantification, were compared using multiple statistical approaches, including univariate, multivariate, and network analyses.

Results

Using univariate analysis, we observed a trend that milk for infants who develop an allergy by 3 years of age contains higher abundances of immunoglobulin chains, irrespective of the allergy status of the mother. This observation suggests a difference in the milk's immunological potential, which might be related to the development of the infant's immune system. Furthermore, network analysis showed overall increased connectivity of proteins in the milk of allergic mothers and milk for infants who ultimately develop an allergy. This difference in connectivity was especially noted for proteins involved in the protein translation machinery and may be due to the physiological status of the mother, which is reflected in the interconnectedness of proteins in her milk. In addition, it was shown that network analysis complements the other methods for data analysis by revealing complex associations between the milk proteome and mother-child allergy status.

Conclusion

Together, these findings give new insights into how the human milk proteome, through differences in the abundance of individual proteins and protein-protein associations, relates to the allergy status of mother and child. In addition, these results inspire new research directions into the complex interplay of the mother-milk-infant triad and allergy.

Extrapolating missing antibody-virus measurements across serological studies

The development of new vaccines, as well as our understanding of key processes that shape viral evolution and host antibody repertoires, relies on measuring multiple antibody responses against large panels of viruses. Given the enormous diversity of circulating virus strains and antibody responses, comprehensively testing all antibody-virus interactions is infeasible. Even within individual studies with limited panels, exhaustive testing is not always performed, and there is no common framework for combining information across studies with partially overlapping panels, especially when the assay type or host species differ. Prior studies have demonstrated that antibody-virus interactions can be characterized in a vastly simpler and lower dimensional space, suggesting that relatively few measurements could predict unmeasured antibody-virus interactions. Here, we apply matrix completion to several large-scale influenza and HIV-1 studies. We explore how prediction accuracy evolves as the number of measurements changes and approximates the number of additional measurements necessary in several highly incomplete datasets (suggesting ∼250,000 measurements could be saved). In addition, we show how the method can combine disparate datasets, even when the number of available measurements is below the theoretical limit that guarantees successful prediction. This approach can be readily generalized to other viruses or more broadly to other low-dimensional biological datasets.

An Immunoproteomic Survey of the Antibody Landscape: Insights and Opportunities Revealed by Serological Repertoire Profiling

Immunoproteomics has emerged as a versatile tool for analyzing the antibody repertoire in various disease contexts. Until recently, characterization of antibody molecules in biological fluids was limited to bulk serology, which identifies clinically relevant features of polyclonal antibody responses. The past decade, however, has seen the rise of mass-spectrometry-enabled proteomics methods that have allowed profiling of the antibody response at the molecular level, with the disease-specific serological repertoire elucidated in unprecedented detail. In this review, we present an up-to-date survey of insights into the disease-specific immunological repertoire by examining how quantitative proteomics-based approaches have shed light on the humoral immune response to infection and vaccination in pathogenic illnesses, the molecular basis of autoimmune disease, and the tumor-specific repertoire in cancer. We address limitations of this technology with a focus on emerging potential solutions and discuss the promise of high-resolution immunoproteomics in therapeutic discovery and novel vaccine design.

Single-Cell Technologies for the Study of Antibody-Secreting Cells

Antibody-secreting cells (ASC), plasmablasts and plasma cells, are terminally differentiated B cells responsible for large-scale production and secretion of antibodies. ASC are derived from activated B cells, which may differentiate extrafollicularly or form germinal center (GC) reactions within secondary lymphoid organs. ASC therefore consist of short-lived, poorly matured plasmablasts that generally secrete lower-affinity antibodies, or long-lived, highly matured plasma cells that generally secrete higher-affinity antibodies. The ASC population is responsible for producing an immediate humoral B cell response, the polyclonal antibody repertoire, as well as in parallel building effective humoral memory and immunity, or potentially driving pathology in the case of autoimmunity. ASC are phenotypically and transcriptionally distinct from other B cells and further distinguishable by morphology, varied lifespans, and anatomical localization. Single cell analyses are required to interrogate the functional and transcriptional diversity of ASC and their secreted antibody repertoire and understand the contribution of individual ASC responses to the polyclonal humoral response. Here we summarize the current and emerging functional and molecular techniques for high-throughput characterization of ASC with single cell resolution, including flow and mass cytometry, spot-based and microfluidic-based assays, focusing on functional approaches of the secreted antibodies: specificity, affinity, and secretion rate.

A Direct MS-Based Approach to Profile Human Milk Secretory Immunoglobulin A (IgA1) Reveals Donor-Specific Clonal Repertoires With High Longitudinal Stability

Recently, a mass spectrometry-based approach was introduced to directly assess the IgG1 immunoglobulin clonal repertoires in plasma. Here we expanded upon this approach by describing a mass spectrometry-based technique to assess specifically the clonal repertoire of another important class of immunoglobulin molecules, IgA1, and show it is efficiently and robustly applicable to either milk or plasma samples. Focusing on two individual healthy donors, whose milk was sampled longitudinally during the first 16 weeks of lactation, we demonstrate that the total repertoire of milk sIgA1 is dominated by only 50-500 clones, even though the human body theoretically can generate several orders of magnitude more clones. We show that in each donor the sIgA1 repertoire only changes marginally and quite gradually over the monitored 16-week period of lactation. Furthermore, the observed overlap in clonal repertoires between the two individual donors is close to non-existent. Mothers provide protection to their newborn infants directly by the transfer of antibodies via breastfeeding. The approach introduced here, can be used to visualize the clonal repertoire transferred from mother to infant and to detect changes in-time in that repertoire adapting to changes in maternal physiology.