4.7 Article

Optimization of a human milk-directed quantitative sIgA ELISA method substantiated by mass spectrometry

Journal

ANALYTICAL AND BIOANALYTICAL CHEMISTRY
Volume 413, Issue 20, Pages 5037-5049

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s00216-021-03468-4

Keywords

Human milk; sIgA; ELISA; Mass spectrometry; Proteomics

Funding

  1. Netherlands Organization for Scientific Research (NWO) [184.032.201]
  2. TOP-Punt Grant [718.015.003]
  3. Chinese Scholarship Council (CSC)
  4. Danone Nutricia Research

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Immunoglobulins in human milk, especially secretory immunoglobulin A (sIgA), play a crucial role in protecting breastfed infants from pathogens. Researchers developed a sIgA ELISA method for quantitative analysis of total sIgA in human milk, which showed strong correlation with mass spectrometry-detected IgA1, suggesting it as a superior indicator compared to standard serum IgA ELISA kits.
Immunoglobulins are the primary protective products in human milk and are responsible for transferring maternal pathogen memory to the infant, providing protection by binding to recognized pathogens and inhibiting virulence. To better understand potentially protective/anti-infective compounds in human milk, the establishment of human milk-tailored analytical approaches is crucial, as most contemporary analytical methods have been optimized for plasma or serum. One of the most prominent immunoglobulins in human milk is secretory immunoglobulin A (sIgA), which may be relevant for the protection of breastfed infants from harmful pathogens. Advanced sIgA detection methods can help monitor the immune status and development of the mother-infant dyad. We therefore developed an enzyme-linked immunosorbent assay (ELISA) sIgA method for the quantitative analysis of IgA plus secretory component (SC), validated with sIgA standards and substantiated by mass spectrometry (MS)-based proteomics. A very strong correlation was observed between the MS-detected IgA1 and the human milk-specific sIgA ELISA (r = 0.82). Overall, the MS data indicate that the developed human milk sIgA ELISA does not differentiate between sIgA1 and sIgA2 and is, therefore, a reflection of total sIgA. Furthermore, our MS data and the human milk-derived sIgA ELISA data are better correlated than data derived from a standard serum IgA ELISA kit (relative to MS IgA1 r = 0.82 and r = 0.42, respectively). We therefore propose our human milk-specific sIgA ELISA as an ideal quantitative indicator of total sIgA with advantages over current serum IgA ELISA kits.

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