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Extraction of the CDRH3 sequence of the mouse antibody repertoire selected upon influenza virus infection by subtraction of the background antibody repertoire.

Masashi ShingaiSayaka IidaNaoko KawaiMamiko KawaharaToshiki SekiyaMarumi OhnoNaoki NomuraChimuka HandabileTomomi KawakitaRyosuke OmoriJyunya YamagishiKaori SanoAkira AinaiTadaki SuzukiKazuo OhnishiKimihito ItoHiroshi Kida
Published in: Journal of virology (2024)
As specific interactions between antigens and cell-surface antibodies trigger the proliferation of B-cell clones, the frequency of each antibody sequence in the samples reflects the size of each clonal population. Nevertheless, it is extremely difficult to extract antigen-specific antibody sequences from the comprehensive bulk antibody sequences obtained from blood samples due to repertoire bias influenced by exposure to dietary antigens and other infectious agents. This issue can be addressed by subtracting the background noise from the post-immunization or post-infection repertoire data. In the present study, we propose a method to quantify repertoire data from comprehensive repertoire data. This method allowed subtraction of the background repertoire, resulting in more accurate extraction of expanded antibody repertoires upon influenza virus infection. This accurate extraction of antigen- or infection-specific repertoire information is a useful tool for vaccine evaluation.
Keyphrases
  • high throughput sequencing
  • electronic health record
  • big data
  • cell surface
  • healthcare
  • signaling pathway
  • dendritic cells
  • immune response
  • artificial intelligence
  • anti inflammatory