Mass Spectrometry-Based De Novo Sequencing of Monoclonal Antibodies Using Multiple Proteases and a Dual Fragmentation Scheme.
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ABSTRACT:
SUBMITTER: Peng W
PROVIDER: S-EPMC8256418 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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: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:Mass spectrometry has become the method of choice for the qualitative and quantitative characterization of protein mixtures isolated from all kinds of living organisms. The raw data in these studies are MS/MS spectra, usually of peptides produced by proteolytic digestion of a protein. These spectra are "translated" into peptide sequences, normally with the help of various search engines. Data acquisition and interpretation have both been automated, and most researchers look only at the summary of the identifications without ever viewing the underlying raw data used for assignments. Automated analysis of data is essential due to the volume produced. However, being familiar with the finer intricacies of peptide fragmentation processes, and experiencing the difficulties of manual data interpretation allow a researcher to be able to more critically evaluate key results, particularly because there are many known rules of peptide fragmentation that are not incorporated into search engine scoring. Since the most commonly used MS/MS activation method is collision-induced dissociation (CID), in this article we present a brief review of the history of peptide CID analysis. Next, we provide a detailed tutorial on how to determine peptide sequences from CID data. Although the focus of the tutorial is de novo sequencing, the lessons learned and resources supplied are useful for data interpretation in general.
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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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