Format

Send to

Choose Destination
See comment in PubMed Commons below
Vaccine. 2017 Aug 3. pii: S0264-410X(17)31019-8. doi: 10.1016/j.vaccine.2017.07.093. [Epub ahead of print]

Functional and structural characteristics of secretory IgA antibodies elicited by mucosal vaccines against influenza virus.

Author information

1
Department of Pathology, National Institute of Infectious Diseases, Tokyo 162-8640, Japan. Electronic address: tksuzuki@nih.go.jp.
2
Department of Pathology, National Institute of Infectious Diseases, Tokyo 162-8640, Japan.

Abstract

Mucosal tissues are major targets for pathogens. The secretions covering mucosal surfaces contain several types of molecules that protect the host from infection. Among these, mucosal immunoglobulins, including secretory IgA (S-IgA) antibodies, are the major contributor to pathogen-specific immune responses. IgA is the primary antibody class found in many external secretions and has unique structural and functional features not observed in other antibody classes. Recently, extensive efforts have been made to develop novel vaccines that induce immunity via the mucosal route. S-IgA is a key molecule that underpins the mechanism of action of these mucosal vaccines. Thus, precise characterization of S-IgA induced by mucosal vaccines is important, if the latter are to be used successfully in a clinical setting. Intensive studies identified the fundamental characteristics of S-IgA, which was first discovered almost half a century ago. However, S-IgA itself has not gained much attention of late, despite its importance to mucosal immunity; therefore, some important questions remain. This review summarizes the current understanding of the molecular characteristics of S-IgA and its role in intranasal mucosal vaccines against influenza virus infection.

KEYWORDS:

Influenza; Influenza virus; Intranasal inactivated influenza vaccine; Mucosal immunoglobulin; Mucosal vaccine; Secretory IgA

PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Elsevier Science
    Loading ...
    Support Center