TY - JOUR A1 - Beslic, D. A1 - Tscheuschner, Georg A1 - Renard, B. Y. A1 - Weller, Michael G. A1 - Muth, Thilo T1 - Comprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly JF - Briefings in Bioinformatics N2 - 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. KW - De novo peptide sequencing KW - Bioinformatics KW - Benchmarking study KW - Monoclonal antibody KW - Mass spectrometry KW - Sequence coverage KW - Light chains KW - Heavy chains KW - IgG KW - Immunoglobulins KW - Error correction KW - Sequencing algorithm KW - Preprocessing KW - Missing fragmentation sites KW - Deep learning-based tools PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-570363 DO - https://doi.org/10.1093/bib/bbac542 VL - 24 IS - 1 SP - 1 EP - 12 PB - Oxford University Press AN - OPUS4-57036 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Carvalho, José Joao A1 - Walter, Astrid A1 - Baermann, Yvonne A1 - Weller, Michael G. A1 - Panne, Ulrich A1 - Schenk, J.A. A1 - Schneider, Rudolf T1 - Non-invasive monitoring of immunization progress in mice via IgG from feces JF - In vivo N2 - A non-invasive method to monitor the humoral immune response in mice after immunization is described. From fecal pellets of an individual mouse, a sufficient amount of active immunoglobulins or their fragments can be extracted to perform a regular examination of the status of the immune response by immunoassay. Hapten-specific antibodies from the feces of mice from three immunization trials showed very similar characteristics to those obtained from serum at a given date. Therefore, it can be suspected that some serum IgG enters the intestinal lumen and ends up in the feces, where they appear to be considerably stable. Hapten-specific IgAs were not found in the feces. Being able to analyze antibody titers in feces could be an interesting animal welfare refinement to standard practice that does not entail repeated blood sampling. KW - Immunization monitoring KW - IgG KW - Coproantibodies KW - Feces KW - Animal welfare KW - 3R concept PY - 2012 UR - http://iv.iiarjournals.org/content/26/1/63.full.pdf+html SN - 0258-851x VL - 26 IS - 1 SP - 63 EP - 70 PB - In vivo CY - Athens AN - OPUS4-25283 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -