Loading…
A Procedure for Alcian Blue Staining of Mucins on Polyvinylidene Difluoride Membranes
The isolation and characterization of mucins are critically important for obtaining insight into the molecular pathology of various diseases, including cancers and cystic fibrosis. Recently, we developed a novel membrane electrophoretic method, supported molecular matrix electrophoresis (SMME), whic...
Saved in:
Published in: | Analytical chemistry (Washington) 2012-10, Vol.84 (20), p.8461-8466 |
---|---|
Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | The isolation and characterization of mucins are critically important for obtaining insight into the molecular pathology of various diseases, including cancers and cystic fibrosis. Recently, we developed a novel membrane electrophoretic method, supported molecular matrix electrophoresis (SMME), which separates mucins on a polyvinylidene difluoride (PVDF) membrane impregnated with a hydrophilic polymer. Alcian blue staining is widely used to visualize mucopolysaccharides and acidic mucins on both blotted membranes and SMME membranes; however, this method cannot be used to stain mucins with a low acidic glycan content. Meanwhile, periodic acid–Schiff staining can selectively visualize glycoproteins, including mucins, but is incompatible with glycan analysis, which is indispensable for mucin characterizations. Here we describe a novel staining method, designated succinylation-Alcian blue staining, for visualizing mucins on a PVDF membrane. This method can visualize mucins regardless of the acidic residue content and shows a sensitivity 2-fold higher than that of Pro-Q Emerald 488, a fluorescent periodate Schiff-base stain. Furthermore, we demonstrate the compatibility of this novel staining procedure with glycan analysis using porcine gastric mucin as a model mucin. |
---|---|
ISSN: | 0003-2700 1520-6882 |
DOI: | 10.1021/ac301678z |