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

peer-reviewed · Analytical Biochemistry · 2022

peer-reviewed · Analytical Biochemistry · 2022. Changrui Xing et al. Despite their widely used and access as biological reagents in analytical methods, the detailed structural…
Date 2022-11-01
Type peer-reviewed
Venue Analytical Biochemistry
Publisher Elsevier BV
Contribution downstream-application
DOI 10.1016/j.ab.2022.114883
Citations (OpenAlex) 3

Abstract

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.

Authors

  1. Changrui Xing · Nanjing University of Finance and Economics
  2. Chongjing Liu · Nanjing University of Finance and Economics
  3. Zhikang Kong · Nanjing University of Finance and Economics
  4. Kaidong Wei · Nanjing University of Finance and Economics
  5. Peng Li · Nanjing University of Finance and Economics
  6. Guanglei Li · Nanjing University of Finance and Economics
  7. Jian Yuan · Nanjing University of Finance and Economics
  8. Wenjing Yan · Nanjing Agricultural University

Methods and tools

Methods it uses

  • PEAKS: Commercial DP-based de novo

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