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Identification of common and distinct origins of human serum and breastmilk IgA1 by mass spectrometry-based clonal profiling.

Kelly A DingessMax HoekDanique M H van RijswijkSem TamaraMaurits A den BoerTim VethMirjam J A DamenArjan BarendregtMichelle RomijnHannah G JunckerBritt J van KeulenGestur VidarssonJohannes B van GoudoeverAlbert BondtAlbert J R Heck
Published in: Cellular & molecular immunology (2022)
The most abundant immunoglobulin present in the human body is IgA. It has the highest concentrations at the mucosal lining and in biofluids such as milk and is the second most abundant class of antibodies in serum. We assessed the structural diversity and clonal repertoire of IgA1-containing molecular assemblies longitudinally in human serum and milk from three donors using a mass spectrometry-based approach. IgA-containing molecules purified from serum or milk were assessed by the release and subsequent analysis of their Fab fragments. Our data revealed that serum IgA1 consists of two distinct structural populations, namely monomeric IgA1 (∼80%) and dimeric joining (J-) chain coupled IgA1 (∼20%). Also, we confirmed that IgA1 in milk is present solely as secretory (S)IgA, consisting of two (∼50%), three (∼33%) or four (∼17%) IgA1 molecules assembled with a J-chain and secretory component (SC). Interestingly, the serum and milk IgA1-Fab repertoires were distinct between monomeric, and J-chain coupled dimeric IgA1. The serum dimeric J-chain coupled IgA1 repertoire contained several abundant clones also observed in the milk IgA1 repertoire. The latter repertoire had little to no overlap with the serum monomeric IgA1 repertoire. This suggests that human IgA1s have (at least) two distinct origins; one of these produces dimeric J-chain coupled IgA1 molecules, shared in human serum and milk, and another produces monomeric IgA1 ending up exclusively in serum.
Keyphrases
  • mass spectrometry
  • endothelial cells
  • high resolution
  • oxidative stress
  • single cell
  • machine learning
  • ms ms
  • liquid chromatography
  • single molecule
  • bioinformatics analysis