4.2 Article

Single amino acid fingerprinting of the human antibody repertoire with high density peptide arrays

期刊

JOURNAL OF IMMUNOLOGICAL METHODS
卷 443, 期 -, 页码 45-54

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jim.2017.01.012

关键词

Humoral immune system; Substitution analysis; Serology; Phage display; Next generation sequencing

资金

  1. ERC [277863]
  2. HRJRG [316]
  3. EU FP7 [256672]
  4. BMBF [031A170A, 03EK3030A, 031A095C]
  5. European Research Council (ERC) [277863] Funding Source: European Research Council (ERC)

向作者/读者索取更多资源

The antibody species that patrol in a patient's blood are an invaluable part of the immune system. While most of them shield us from life-threatening infections, some of them do harm in autoimmune diseases. If we knew exactly all the antigens that elicited all the antibody species within a group of patients, we could learn which ones correlate with immune protection, are irrelevant, or do harm. Here, we demonstrate an approach to this question: First, we use a plethora of phage-displayed peptides to identify many different serum antibody binding peptides. Next, we synthesize identified peptides in the array format and rescreen the serum used for phage panning to validate antibody binding peptides. Finally, we systematically vary the sequence of validated antibody binding peptides to identify those amino acids within the peptides that are crucial for binding their antibody species. The resulting immune fingerprints can then be used to trace them back to potential antigens. We investigated the serum of an individual in this pipeline, which led to the identification of 73 antibody fingerprints. Some fingerprints could be traced back to their most likely antigen, for example the immunodominant capsid protein VP1 of enteroviruses, most likely elicited by the ubiquitous poliovirus vaccination. Thus, With our approach, it is possible, to pinpoint those antibody species that correlate with a certain antigen, without any pre-information. This can help to unravel hitherto enigmatic diseases. (C) 2017 Elsevier B.V. All rights reserved.

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