Automated Antibody De Novo Sequencing and Its Utility in Biopharmaceutical Discovery

A Handle on Mass Coincidence Errors in De Novo Sequencing of Antibodies by Bottom-up Proteomics

Antibody sequences can be determined at 99% accuracy directly from the polypeptide product by using bottom-up proteomics techniques. Sequencing accuracy at the peptide level is limited by the isobaric residues leucine and isoleucine, incomplete fragmentation spectra in which the order of two or more residues remains ambiguous due to lacking fragment ions for the intermediate positions, and isobaric combinations of amino acids, of potentially different lengths, for example, GG = N and GA = Q. Here, we present several updates to Stitch (v1.5), which performs template-based assembly of de novo peptides to reconstruct antibody sequences. This version introduces a mass-based alignment algorithm that explicitly accounts for mass coincidence errors. In addition, it incorporates a postprocessing procedure to assign I/L residues based on secondary fragments (satellite ions, i.e., w-ions). Moreover, evidence for sequence assignments can now be directly evaluated with the addition of an integrated spectrum viewer. Lastly, input data from a wider selection of de novo peptide sequencing algorithms are allowed, now including Casanovo, PEAKS, Novor.Cloud, pNovo, and MaxNovo, in addition to flat text and FASTA. Combined, these changes make Stitch compatible with a larger range of data processing pipelines and improve its tolerance to peptide-level sequencing errors.

Into the Dark Serum Proteome: Personalized Features of IgG1 and IgA1 Repertoires in Severe COVID-19 Patients

Serum proteomics has matured and is now able to monitor hundreds of proteins quantitatively in large cohorts of patients. However, the fine characteristics of some of the most dominant proteins in serum, the immunoglobulins, are in these studies often ignored, due to their vast, and highly personalized, diversity in sequences. Here, we focus exclusively on these personalized features in the serum proteome and distinctively chose to study individual samples from a low diversity population: elderly donors infected by severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). By using mass spectrometry-based methods, immunoglobulin IgG1 and IgA1 clonal repertoires were monitored quantitatively and longitudinally in more than 50 individual serum samples obtained from 17 Corona virus disease 2019 patients admitted to intensive care units. These clonal profiles were used to examine how each patient reacted to a severe SARS-CoV-2 infection. All 17 donors revealed unique polyclonal repertoires and substantial changes over time, with several new clones appearing following the infection, in a few cases leading to a few, very high, abundant clones dominating their repertoire. Several of these clones were de novo sequenced through combinations of top-down, middle-down, and bottom-up proteomics approaches. This revealed sequence features in line with sequences deposited in the SARS-CoV-specific antibody database. In other patients, the serological Ig profiles revealed the treatment with tocilizumab, that subsequently dominated their serological IgG1 repertoire. Tocilizumab clearance could be monitored, and a half-life of approximately 6 days was established. Overall, our longitudinal monitoring of IgG1 and IgA1 repertoires of individual donors reveals that antibody responses are highly personalized traits of each patient, affected by the disease and the chosen clinical treatment. The impact of these observations argues for a more personalized and longitudinal approach in patients' diagnostics, both in serum proteomics as well as in monitoring immune responses.

Multiplexed volumetric CLEM enabled by antibody derivatives provides new insights into the cytology of the mouse cerebellar cortex

Mapping neuronal networks that underlie behavior has become a central focus in neuroscience. While serial section electron microscopy (ssEM) can reveal the fine structure of neuronal networks (connectomics), it does not provide the molecular information that helps identify cell types or their functional properties. Volumetric correlated light and electron microscopy (vCLEM) combines ssEM and volumetric fluorescence microscopy to incorporate molecular labeling into ssEM datasets. We developed an approach that uses small fluorescent single-chain variable fragment (scFv) immuno-probes to perform multiplexed detergent-free immuno-labeling and ssEM on the same samples. We generated eight such fluorescent scFvs that targeted useful markers for brain studies (green fluorescent protein, glial fibrillary acidic protein, calbindin, parvalbumin, voltage-gated potassium channel subfamily A member 2, vesicular glutamate transporter 1, postsynaptic density protein 95, and neuropeptide Y). To test the vCLEM approach, six different fluorescent probes were imaged in a sample of the cortex of a cerebellar lobule (Crus 1), using confocal microscopy with spectral unmixing, followed by ssEM imaging of the same sample. The results show excellent ultrastructure with superimposition of the multiple fluorescence channels. Using this approach we could document a poorly described cell type in the cerebellum, two types of mossy fiber terminals, and the subcellular localization of one type of ion channel. Because scFvs can be derived from existing monoclonal antibodies, hundreds of such probes can be generated to enable molecular overlays for connectomic studies.

Multiplexed volumetric CLEM enabled by antibody derivatives provides new insights into the cytology of the mouse cerebellar cortex

Mapping neuronal networks that underlie behavior has become a central focus in neuroscience. While serial section electron microscopy (ssEM) can reveal the fine structure of neuronal networks (connectomics), it does not provide the molecular information that helps identify cell types or their functional properties. Volumetric correlated light and electron microscopy (vCLEM) combines ssEM and volumetric fluorescence microscopy to incorporate molecular labeling into ssEM datasets. We developed an approach that uses small fluorescent single-chain variable fragment (scFv) immuno-probes to perform multiplexed detergent-free immuno-labeling and ssEM on the same samples. We generated eight such fluorescent scFvs that targeted useful markers for brain studies (green fluorescent protein, glial fibrillary acidic protein, calbindin, parvalbumin, voltage-gated potassium channel subfamily A member 2, vesicular glutamate transporter 1, postsynaptic density protein 95, and neuropeptide Y). To test the vCLEM approach, six different fluorescent probes were imaged in a sample of the cortex of a cerebellar lobule (Crus 1), using confocal microscopy with spectral unmixing, followed by ssEM imaging of the same sample. The results show excellent ultrastructure with superimposition of the multiple fluorescence channels. Using this approach we could document a poorly described cell type in the cerebellum, two types of mossy fiber terminals, and the subcellular localization of one type of ion channel. Because scFvs can be derived from existing monoclonal antibodies, hundreds of such probes can be generated to enable molecular overlays for connectomic studies.

[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.

De novo assisted AFB1-Specific monoclonal antibody sequence assembly and comprehensive molecular characterization

Despite their widely used and access as biological reagents in analytical methods, the detailed structural features for most of the antibodies were rarely known. Here, a new antibody for AFB1 with high specificity in constructing ELISA was studied in detail. The molecular structure and modification were elucidated mainly by nano-electrospray ionization mass spectrometry. The mass experiments, including MALDI-TOF MS, revealed complete and specific fragments, including antibody molecular weight, peptides, glycopeptide, and N-glycoform. By proteolytic treatment of pepsin and trypsin and high-resolution tandem-MS, the primary structure of the newly developed anti-AFB1 antibody was assembled by several rounds of Database search process assisted with the de novo results. The antibody CDR annotation and constraint-based multiple alignment tool were used to differentiate and align the sequences. The method uses only two proteases to generate numerous peptides for de novo sequencing. This artificial assembled AFB1-specific monoclonal antibody sequence was validated by comparison with the sequencing results of the immunoglobulin gene. The results showed that this method achieves full sequence coverage of anti-AFB1 monoclonal antibody, with an accuracy of 100% in the CDR regions of light chain and four amino acid mismatch in heavy chain. This simple and low-cost method was confirmed by treating a public dataset. The secondary structure information of intact antibody was also elucidated from the results of circular dichroism spectrum.

Template-Based Assembly of Proteomic Short Reads For De Novo Antibody Sequencing and Repertoire Profiling

Antibodies can target a vast molecular diversity of antigens. This is achieved by generating a complementary diversity of antibody sequences through somatic recombination and hypermutation. A full understanding of the antibody repertoire in health and disease therefore requires dedicated de novo sequencing methods. Next-generation cDNA sequencing methods have laid the foundation of our current understanding of the antibody repertoire, but these methods share one major limitation in that they target the antibody-producing B-cells, rather than the functional secreted product in bodily fluids. Mass spectrometry-based methods offer an opportunity to bridge this gap between antibody repertoire profiling and bulk serological assays, as they can access antibody sequence information straight from the secreted polypeptide products. In a step to meeting the challenge of mass spectrometry (MS)-based antibody sequencing, we present a fast and simple software tool (Stitch) to map proteomic short reads to user-defined templates with dedicated features for both monoclonal antibody sequencing and profiling of polyclonal antibody repertoires. We demonstrate the use of Stitch by fully reconstructing two monoclonal antibody sequences with >98% accuracy (including I/L assignment); sequencing a Fab from patient serum isolated by reversed-phase liquid chromatography (LC) fractionation against a high background of homologous antibody sequences; sequencing antibody light chains from the urine of multiple-myeloma patients; and profiling the IgG repertoire in sera from patients hospitalized with COVID-19. We demonstrate that Stitch assembles a comprehensive overview of the antibody sequences that are represented in the dataset and provides an important first step toward analyzing polyclonal antibodies and repertoire profiling.

Template-Assisted De Novo Sequencing of SARS-CoV-2 and Influenza Monoclonal Antibodies by Mass Spectrometry

In this study, we used multiple enzyme digestions, coupled with higher-energy collisional dissociation (HCD) and electron-transfer/higher-energy collision dissociation (EThcD) fragmentation to develop a mass-spectrometric (MS) method for determining the complete protein sequence of monoclonal antibodies (mAbs). The method was refined on an mAb of a known sequence, a SARS-CoV-1 antireceptor binding domain (RBD) spike monoclonal antibody. The data were searched using Supernovo to generate a complete template-assisted de novo sequence for this and two SARS-CoV-2 mAbs of known sequences resulting in correct sequences for the variable regions and correct distinction of Ile and Leu residues. We then used the method on a set of 25 antihemagglutinin (HA) influenza antibodies of unknown sequences and determined high confidence sequences for >99% of the complementarity determining regions (CDRs). The heavy-chain and light-chain genes were cloned and transfected into cells for recombinant expression followed by affinity purification. The recombinant mAbs displayed binding curves matching the original mAbs with specificity to the HA influenza antigen. Our findings indicate that this methodology results in almost complete antibody sequence coverage with high confidence results for CDR regions on diverse mAb sequences.

Use of PASEF for Accelerated Protein Sequence Confirmation and De Novo Sequencing with High Data Quality

Biopharmaceutical sequences can be well confirmed by multiple protease digests-e.g., trypsin, elastase, and chymotrypsin-followed by LC-MS/MS data analysis. High quality data can be used for de novo sequencing as well. PASEF (Parallel Accumulation and Serial Fragmentation) on the timsTOF instrument has been used to accelerate proteome and protein sequence studies and increase sequence coverage concomitantly.Here we describe the protein chemical and LC-MS methods in detail to generate high quality samples for sequence characterization from only 3 digests. We applied PASEF to generate exhaustive protein sequence coverage maps by combination of results from the three enzyme digests using a short LC gradient. The data quality obtained was high and adequate for determining antibody sequences de novo.Nivolumab and dulaglutide were digested by 3 enzymes individually. For nivolumab, 94/94/90% sequence coverage and 86/84/85% fragment coverage were obtained from the individual digest analysis with trypsin/chymotrypsin/elastase, respectively. For dulaglutide, 96/100/90% sequence coverage and 92/90/83% fragment coverage were obtained. The merged peptide map from the 3 digests for nivolumab resulted in ∼550 peptides; enough to safely confirm the full sequences and to determine the nivolumab sequence de novo.

A perspective toward mass spectrometry-based de novo sequencing of endogenous antibodies

A key step in therapeutic and endogenous humoral antibody characterization is identifying the amino acid sequence. So far, this task has been mainly tackled through sequencing of B-cell receptor (BCR) repertoires at the nucleotide level. Mass spectrometry (MS) has emerged as an alternative tool for obtaining sequence information directly at the – most relevant – protein level. Although several MS methods are now well established, analysis of recombinant and endogenous antibodies comes with a specific set of challenges, requiring approaches beyond the conventional proteomics workflows. Here, we review the challenges in MS-based sequencing of both recombinant as well as endogenous humoral antibodies and outline state-of-the-art methods attempting to overcome these obstacles. We highlight recent examples and discuss remaining challenges. We foresee a great future for these approaches making de novo antibody sequencing and discovery by MS-based techniques feasible, even for complex clinical samples from endogenous sources such as serum and other liquid biopsies.

De novo sequencing and native mass spectrometry revealed hetero-association of dirigent protein homologs and potential interacting proteins in Forsythia × intermedia

The discovery of dirigent proteins (DPs) and their functions in plant phenol biochemistry was made over two decades ago with Forsythia × intermedia. Stereo-selective, DP-guided, monolignol-derived radical coupling in vitro was then reported to afford the optically active lignan, (+)-pinoresinol from coniferyl alcohol, provided one-electron oxidase/oxidant capacity was present. It later became evident that DPs have several distinct sub-families, presumably with different functions. Some known DPs require other essential enzymes/proteins (e.g. oxidases) for their functions. However, the lack of a fully sequenced genome for Forsythia × intermedia made it difficult to profile other components co-purified with the (+)-pinoresinol forming DP. Herein, we used an integrated bottom-up, top-down, and native mass spectrometry (MS) approach to de novo sequence the extracted proteins via adaptation of our initial report of DP solubilization and purification. Using publicly available transcriptome and genomic data from closely related species, we identified 14 proteins that were putatively associated with either DP function or the cell wall. Although their co-occurrence after extraction and chromatographic separation is suggestive for potential protein-protein interactions, none were found to form stable protein complexes with DPs in native MS under the specific experimental conditions we have explored. Interestingly, two new DP homologs were found and they formed hetero-trimers. Molecular dynamics simulations suggested that similar hetero-trimers were possible between Arabidopsis DP homologs with comparable sequence similarities. Nevertheless, our integrated mass spectrometry method development helped prepare for future investigations directed to the discovery of novel proteins and protein-protein interactions. These advantages can be highly beneficial for plant and microbial research where fully sequenced genomes may not be readily available.

Human plasma IgG1 repertoires are simple, unique, and dynamic

Although humans can produce billions of IgG1 variants through recombination and hypermutation, the diversity of IgG1 clones circulating in human blood plasma has largely eluded direct characterization. Here, we combined several mass-spectrometry-based approaches to reveal that the circulating IgG1 repertoire in human plasma is dominated by a limited number of clones in healthy donors and septic patients. We observe that each individual donor exhibits a unique serological IgG1 repertoire, which remains stable over time but can adapt rapidly to changes in physiology. We introduce an integrative protein- and peptide-centric approach to obtain and validate a full sequence of an individual plasma IgG1 clone de novo. This IgG1 clone emerged at the onset of a septic episode and exhibited a high mutation rate (13%) compared with the closest matching germline DNA sequence, highlighting the importance of de novo sequencing at the protein level. A record of this paper’s transparent peer review process is included in the supplemental information.

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Novel LC-MS-based methods enable personalized IgG1 profiling in plasma

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Each donor exhibits a simple but unique serological IgG1 repertoire

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This repertoire adapts to changes in physiology, e.g., sepsis

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Individual plasma IgG1 clones can be identified by combining top-down and bottom-up proteomics

De Novo Sequencing of Antibody Light Chain Proteoforms from Patients with Multiple Myeloma

In multiple myeloma diseases, monoclonal immunoglobulin light chains (LCs) are abundantly produced, with, as a consequence in some cases, the formation of deposits affecting various organs, such as the kidney, while in other cases remaining soluble up to concentrations of several g·L^-1 in plasma. The exact factors crucial for the solubility of LCs are poorly understood, but it can be hypothesized that their amino acid sequence plays an important role. Determining the precise sequences of patient-derived LCs is therefore highly desirable. We establish here a novel de novo sequencing workflow for patient-derived LCs, based on the combination of bottom-up and top-down proteomics without database search. PEAKS is used for the de novo sequencing of peptides that are further assembled into full length LC sequences using ALPS. Top-down proteomics provides the molecular masses of proteoforms and allows the exact determination of the amino acid sequence including all posttranslational modifications. This pipeline is then used for the complete de novo sequencing of LCs extracted from the urine of 10 patients with multiple myeloma. We show that for the bottom-up part, digestions with trypsin and Nepenthes digestive fluid are sufficient to produce overlapping peptides able to generate the best sequence candidates. Top-down proteomics is absolutely required to achieve 100% final sequence coverage and characterize clinical samples containing several LCs. Our work highlights an unexpected range of modifications.

Mass Spectrometry-Based De Novo Sequencing of Monoclonal Antibodies Using Multiple Proteases and a Dual Fragmentation Scheme

Antibody sequence information is crucial to understanding the structural basis for antigen binding and enables the use of antibodies as therapeutics and research tools. Here, we demonstrate a method for direct de novo sequencing of monoclonal IgG from the purified antibody products. The method uses a panel of multiple complementary proteases to generate suitable peptides for de novo sequencing by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in a bottom-up fashion. Furthermore, we apply a dual fragmentation scheme, using both stepped high-energy collision dissociation (stepped HCD) and electron-transfer high-energy collision dissociation (EThcD), on all peptide precursors. The method achieves full sequence coverage of the monoclonal antibody herceptin, with an accuracy of 99% in the variable regions. We applied the method to sequence the widely used anti-FLAG-M2 mouse monoclonal antibody, which we successfully validated by remodeling a high-resolution crystal structure of the Fab and demonstrating binding to a FLAG-tagged target protein in Western blot analysis. The method thus offers robust and reliable sequences of monoclonal antibodies.

Selectivity over coverage in de novo sequencing of IgGs

Although incredibly diverse in specificity, millions of unique Immunoglobulin G (IgG) molecules in the human antibody repertoire share most of their amino acid sequence. These constant parts of IgG do not yield any useful information in attempts to sequence antibodies de novo. Therefore, methods focusing solely on the variable regions and providing unambiguous sequence reads are strongly advantageous. We report a mass spectrometry-based method that uses electron capture dissociation (ECD) to provide straightforward-to-read sequence ladders for the variable parts of both the light and heavy chains, with a preference for the functionally important CDR3. We optimized this method on the therapeutic antibody Trastuzumab and demonstrate its applicability on two monoclonal quartets of the four IgG subclasses, IgG1, IgG2, IgG3 and IgG4. The method is based on proteolytically separating the variable F(ab')₂ part from the conserved Fc part, whereafter the F(ab')₂ portions are mass-analyzed and fragmented by ECD. Pure ECD, without additional collisional activation, leads to straightforward-to-read sequence tags covering the CDR3 of both the light and heavy chains. Using molecular modelling and structural analysis, we discuss and explain this selective fragmentation behavior and describe how structural features of the different IgG subclasses lead to distinct fragmentation patterns. Overall, we foresee that pure ECD on F(ab')₂ or Fab molecules can become a valuable tool for the de novo sequencing of serum antibodies.

Interlaboratory Study for Characterizing Monoclonal Antibodies by Top-Down and Middle-Down Mass Spectrometry

The Consortium for Top-Down Proteomics (www.topdownproteomics.org) launched the present study to assess the current state of top-down mass spectrometry (TD MS) and middle-down mass spectrometry (MD MS) for characterizing monoclonal antibody (mAb) primary structures, including their modifications. To meet the needs of the rapidly growing therapeutic antibody market, it is important to develop analytical strategies to characterize the heterogeneity of a therapeutic product's primary structure accurately and reproducibly. The major objective of the present study is to determine whether current TD/MD MS technologies and protocols can add value to the more commonly employed bottom-up (BU) approaches with regard to confirming protein integrity, sequencing variable domains, avoiding artifacts, and revealing modifications and their locations. We also aim to gather information on the common TD/MD MS methods and practices in the field. A panel of three mAbs was selected and centrally provided to 20 laboratories worldwide for the analysis: Sigma mAb standard (SiLuLite), NIST mAb standard, and the therapeutic mAb Herceptin (trastuzumab). Various MS instrument platforms and ion dissociation techniques were employed. The present study confirms that TD/MD MS tools are available in laboratories worldwide and provide complementary information to the BU approach that can be crucial for comprehensive mAb characterization. The current limitations, as well as possible solutions to overcome them, are also outlined. A primary limitation revealed by the results of the present study is that the expert knowledge in both experiment and data analysis is indispensable to practice TD/MD MS.

Flying blind, or just flying under the radar? The underappreciated power of de novo methods of mass spectrometric peptide identification

Mass spectrometry-based proteomics is a popular and powerful method for precise and highly multiplexed protein identification. The most common method of analyzing untargeted proteomics data is called database searching, where the database is simply a collection of protein sequences from the target organism, derived from genome sequencing. Experimental peptide tandem mass spectra are compared to simplified models of theoretical spectra calculated from the translated genomic sequences. However, in several interesting application areas, such as forensics, archaeology, venomics, and others, a genome sequence may not be available, or the correct genome sequence to use is not known. In these cases, de novo peptide identification can play an important role. De novo methods infer peptide sequence directly from the tandem mass spectrum without reference to a sequence database, usually using graph-based or machine learning algorithms. In this review, we provide a basic overview of de novo peptide identification methods and applications, briefly covering de novo algorithms and tools, and focusing in more depth on recent applications from venomics, metaproteomics, forensics, and characterization of antibody drugs.

Sequencing a Bispecific Antibody by Controlling Chain Concentration Effects When Using an Immobilized Nonspecific Protease

Complete sequence coverage of monospecific antibodies was previously achieved using immobilized aspergillopepsin I in a single LC-MS/MS analysis. Bispecific antibodies are asymmetrical compared to their monospecific antibody counterparts, resulting in a decrease in the concentration of individual subunits. Four standard proteins were used to characterize the effect of a decrease in concentration when using this immobilized enzyme reactor. Low concentration samples resulted in the elimination of large peptide products due to a greater number of enzymatic cleavages. A competitive inhibitor rich in arginine residues reduced the number of enzymatic cleavages to the protein and retained large molecular weight products. The digestion of a bispecific antibody with competitive inhibition of aspergillopepsin I maintained large peptide products better suited for sequence reconstruction, resulting in complete sequence coverage from a single LC-MS/MS analysis.

Lys-Sequencer: An algorithm for de novo sequencing of peptides by paired single residue transposed Lys-C and Lys-N digestion coupled with high-resolution mass spectrometry

RATIONALE

Database-dependent identification of proteins by mass spectrometry is well established, but has limitations when there are novel proteins, mutations, splice variants, and post-translational modifications (PTMs) not available in the established reference database. De novo sequencing as a database-independent approach could address these limitations by deducing peptide sequences directly from experimental tandem mass spectrometry spectra, while concomitantly yielding residue-by-residue confidence metrics.

METHODS

Equal amounts of bovine serum albumin (BSA) sample aliquots were digested separately with Lys-C and Lys-N complementary peptidases, separated by reversed-phase ultra-high-performance liquid chromatography (UPLC), and analyzed by collision-induced dissociation (CID)-based mass spectrometry on an Orbitrap mass spectrometer. In the Lys-Sequencer algorithm, matched tandem mass spectra with equal precursor ion mass from complementary digestions were paired, and fragment ion types were identified based on the unique mass relationship between fragment ions extracted from a spectrum pair followed by de novo sequencing of peptides with identification confidence assigned at the residue level.

RESULTS

In all the matched spectrum pairs, 34 top-ranked BSA peptides were identified, from which 391 amino acid residues were identified correctly, covering ~67% of the full sequence of BSA (583 residues) with only ~6% (35 residues) exhibiting ambiguity in the sequence order (although amino acid compositions were still correctly assigned). Of note, this approach identified peptide sequences up to 17 amino acids in length without ambiguity, with the exception of the N-terminal or C-terminal peptides containing lysine (18-mer).

CONCLUSIONS

The algorithm ("Lys-Sequencer") developed in this work achieves high precision for de novo sequencing of peptides. This method facilitates the identification of point mutation and new PTMs in the protein characterization and discovery of new peptides and proteins with varying levels of confidence.

Unambiguous Sequence Characterization of a Monoclonal Antibody in a Single Analysis Using a Nonspecific Immobilized Enzyme Reactor

Accurate sequence characterization is essential for the development of therapeutic antibodies by the pharmaceutical industry. Presented here is a methodology to obtain comprehensive sequence analysis of a monoclonal antibody. An enzyme reactor of immobilized Aspergillopepsin I, a highly stable nonspecific protease, was used to cleave reduced antibody subunits into a peptide profile ranging from 1 to 20 kDa. Utilizing the Thermo Orbitrap Fusion's unique instrument architecture combined with state-of-the-art instrument control software allowed for dynamic instrument methods that optimally characterize eluting peptides based on their size and charge density. Using a data-dependent instrument method, both collisional dissociation and electron transfer dissociation were used to fragment the appropriate charge state of analyte peptides. The instrument layout also allowed for scans to be taken in parallel using both the ion trap and Orbitrap concurrently, thus allowing larger peptides to be analyzed in high resolution using the Orbitrap while simultaneously analyzing tryptic-like peptides using the ion trap. We harnessed these capabilities to develop a custom method to optimally fragment the eluting peptides based on their mass and charge density. Using this approach, we obtained 100% sequence coverage of the total antibody in a single chromatographic analysis, enabling unambiguous sequence assignment of all residues.

A simplified workflow for monoclonal antibody sequencing

The diversity of antibody variable regions makes cDNA sequencing challenging, and conventional monoclonal antibody cDNA amplification requires the use of degenerate primers. Here, we describe a simplified workflow for amplification of IgG antibody variable regions from hybridoma RNA by a specialized RT-PCR followed by Sanger sequencing. We perform three separate reactions for each hybridoma: one each for kappa, lambda, and heavy chain transcripts. We prime reverse transcription with a primer specific to the respective constant region and use a template-switch oligonucleotide, which creates a custom sequence at the 5’ end of the antibody cDNA. This template-switching circumvents the issue of low sequence homology and the need for degenerate primers. Instead, subsequent PCR amplification of the antibody cDNA molecules requires only two primers: one primer specific for the template-switch oligonucleotide sequence and a nested primer to the respective constant region. We successfully sequenced the variable regions of five mouse monoclonal IgG antibodies using this method, which enabled us to design chimeric mouse/human antibody expression plasmids for recombinant antibody production in mammalian cell culture expression systems. All five recombinant antibodies bind their respective antigens with high affinity, confirming that the amino acid sequences determined by our method are correct and demonstrating the high success rate of our method. Furthermore, we also designed RT-PCR primers and amplified the variable regions from RNA of cells transfected with chimeric mouse/human antibody expression plasmids, showing that our approach is also applicable to IgG antibodies of human origin. Our monoclonal antibody sequencing method is highly accurate, user-friendly, and very cost-effective.

A Potential Golden Age to Come-Current Tools, Recent Use Cases, and Future Avenues for De Novo Sequencing in Proteomics

In shotgun proteomics, peptide and protein identification is most commonly conducted using database search engines, the method of choice when reference protein sequences are available. Despite its widespread use the database-driven approach is limited, mainly because of its static search space. In contrast, de novo sequencing derives peptide sequence information in an unbiased manner, using only the fragment ion information from the tandem mass spectra. In recent years, with the improvements in MS instrumentation, various new methods have been proposed for de novo sequencing. This review article provides an overview of existing de novo sequencing algorithms and software tools ranging from peptide sequencing to sequence-to-protein mapping. Various use cases are described for which de novo sequencing was successfully applied. Finally, limitations of current methods are highlighted and new directions are discussed for a wider acceptance of de novo sequencing in the community.

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.