Automated de novo protein sequencing of monoclonal antibodies.
Ontology highlight
ABSTRACT:
SUBMITTER: Bandeira N
PROVIDER: S-EPMC2891972 | biostudies-literature | 2008 Dec
REPOSITORIES: biostudies-literature
Publications
Automated de novo protein sequencing of monoclonal antibodies.
Bandeira Nuno N Pham Victoria V Pevzner Pavel P Arnott David D Lill Jennie R JR
Nature biotechnology 20081201 12
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Project description:The enormous diversity created by gene recombination and somatic hypermutation makes de novo protein sequencing of monoclonal antibodies a uniquely challenging problem. Modern mass spectrometry-based sequencing will rarely, if ever, provide a single unambiguous sequence for the variable domains. A more likely outcome is computation of an ensemble of highly similar sequences that can satisfy the experimental data. This outcome can result in the need for empirical testing of many candidate sequences, sometimes iteratively, to identity one which can replicate the activity of the parental antibody. Here we describe an improved approach to antibody protein sequencing by using phage display technology to generate a combinatorial library of sequences that satisfy the mass spectrometry data, and selecting for functional candidates that bind antigen. This approach was used to reverse engineer 2 commercially-obtained monoclonal antibodies against murine CD137. Proteomic data enabled us to assign the majority of the variable domain sequences, with the exception of 3-5% of the sequence located within or adjacent to complementarity-determining regions. To efficiently resolve the sequence in these regions, small phage-displayed libraries were generated and subjected to antigen binding selection. Following enrichment of antigen-binding clones, 2 clones were selected for each antibody and recombinantly expressed as antigen-binding fragments (Fabs). In both cases, the reverse-engineered Fabs exhibited identical antigen binding affinity, within error, as Fabs produced from the commercial IgGs. This combination of proteomic and protein engineering techniques provides a useful approach to simplifying the technically challenging process of reverse engineering monoclonal antibodies from protein material.
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Project description:One direct route for the discovery of therapeutic human monoclonal antibodies (mAbs) involves the isolation of peripheral B cells from survivors/sero-positive individuals after exposure to an infectious reagent or disease etiology, followed by single-cell sequencing or hybridoma generation. Peripheral B cells, however, are not always easy to obtain and represent only a small percentage of the total B-cell population across all bodily tissues. Although it has been demonstrated that tandem mass spectrometry (MS/MS) techniques can interrogate the full polyclonal antibody (pAb) response to an antigen in vivo, all current approaches identify MS/MS spectra against databases derived from genetic sequencing of B cells from the same patient. In this proof-of-concept study, we demonstrate the feasibility of a novel MS/MS antibody discovery approach in which only serum antibodies are required without the need for sequencing of genetic material. Peripheral pAbs from a cytomegalovirus-exposed individual were purified by glycoprotein B antigen affinity and de novo sequenced from MS/MS data. Purely MS-derived mAbs were then manufactured in mammalian cells to validate potency via antigen-binding ELISA. Interestingly, we found that these mAbs accounted for 1 to 2% of total donor IgG but were not detected in parallel sequencing of memory B cells from the same patient.
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Project description: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.
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Project description:QBEND/10 is a mouse immunoglobulin lambda-chain monoclonal antibody with strict specificity against human hematopoietic progenitor cell antigen CD34. Our in vitro study showed that QBEND/10 impairs the tube formation of human umbilical vein endothelial cells (HUVECs), suggesting that the antibody may be of potential benefit in blocking tumor angiogenesis. We provided a de novo protein sequencing method through tandem mass spectrometry to identify the amino acid sequences in the variable heavy and light chains of QBEND/10. To reduce immunogenicity for clinical applications, QBEND/10 was further humanized using the resurfacing approach. We demonstrate that the de novo sequenced and humanized QBEND/10 retains the biological functions of the parental mouse counterpart, including the binding kinetics to CD34 and blockage of the tube formation of the HUVECs.
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Project description:Applications of antibody de novo sequencing in the biopharmaceutical industry range from the discovery of new antibody drug candidates to identifying reagents for research and determining the primary structure of innovator products for biosimilar development. When murine, phage display, or patient-derived monoclonal antibodies against a target of interest are available, but the cDNA or the original cell line is not, de novo protein sequencing is required to humanize and recombinantly express these antibodies, followed by in vitro and in vivo testing for functional validation. Availability of fully automated software tools for monoclonal antibody de novo sequencing enables efficient and routine analysis. Here, we present a novel method to automatically de novo sequence antibodies using mass spectrometry and the Supernovo software. The robustness of the algorithm is demonstrated through a series of stress tests. Graphical Abstract ᅟ.
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Project description: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.
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Project description:Elucidating antibody sequences is crucial for understanding antigen binding and advancing therapeutic and research applications. However, current de novo sequencing technology is hindered by high costs, low throughput, missing ion information, and assembly limitations in accuracy and robustness. Here, we developed a refined sequencing solution by integrating Single-Pot Multi-Enzymatic Gradient Digestion (SP-MEGD) with a beam search-based assembler (Fusion) to decipher complete sequences. This solution achieved high accuracy (over 99%) in antibody reconstruction. Biological validation of multiple commercial antibodies with unavailable sequences further supports its effectiveness. Additionally, our solution can discriminate and achieve over 99% accurate sequence coverage of mixtures containing two or three COVID-19 neutralizing antibodies. To our knowledge, this is the first study to enable simultaneous sequencing of multiple antibodies using only bottom-up mass spectrometry, improving throughput without increasing duration or expense. In summary, our method advances antibody research by enhancing the accuracy and efficiency of complex antibody sequencing.
2025-02-05 | PXD060500 |
Project description:In this study, we used electron-transfer/higher energy collision dissociation (EThcD) fragmentation to develop a mass-spectrometric (MS) method for distinguishing between Ile and Leu in Bovine Serum Albumin (BSA) and a SARS-CoV-1 anti-receptor binding domain (RBD) Spike monoclonal antibody (mAb). Supplemental activation normalized collision energy (SA-NCE) values were optimized. Combinations of multiple enzyme digestions, coupled with higher-energy collisional dissociation (HCD) and EThcD fragmentation, were used to increase coverage of all amino acid residues of the antibody. The data was searched with Supernovo™, which generated a complete de novo sequence for the test mAb and two additional SARS-CoV-2 human mAbs, giving correct sequences for the variable regions and selection between Ile and Leu residues. We then used the method on an additional set of twenty-five anti-hemagglutinin (HA) influenza antibodies of unknown sequence and determined high confidence sequences for >99% of the complementarity determining regions (CDRs). Importantly, the recombinant expression of these mAbs verified their binding and specificity to the HA influenza antigen. Unique glycosylation sites were also identified for eight antibodies. Our findings indicate this methodology results in almost complete antibody sequence coverage with >90% of residues determined with high confidence. Ile/Leu residues can be differentiated and glycosylation sites can be reliably identified.
2022-06-03 | PXD030094 | Pride
Project description:MS/MS data upload for 2016 JPR submission "De Novo MS/MS Sequencing of Native Human Antibodies".
2016-08-12 | MSV000080039 | MassIVE
Project description:MOTIVATION:Recent technological advances have made high-resolution mass spectrometers affordable to many laboratories, thus boosting rapid development of top-down mass spectrometry, and implying a need in efficient methods for analyzing this kind of data. RESULTS:We describe a method for analysis of protein samples from top-down tandem mass spectrometry data, which capitalizes on de novo sequencing of fragments of the proteins present in the sample. Our algorithm takes as input a set of de novo amino acid strings derived from the given mass spectra using the recently proposed Twister approach, and combines them into aggregated strings endowed with offsets. The former typically constitute accurate sequence fragments of sufficiently well-represented proteins from the sample being analyzed, while the latter indicate their location in the protein sequence, and also bear information on post-translational modifications and fragmentation patterns. AVAILABILITY AND IMPLEMENTATION:Freely available on the web at http://bioinf.spbau.ru/en/twister CONTACT:vyatkina@spbau.ru or ppevzner@ucsd.edu SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.
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