Chitosan Analysis by Enzymatic/Mass Spectrometric Fingerprinting and in Silico Predictive Modeling.

Abstract

Chitosans, β-1,4-linked partially N-acetylated linear polyglucosamines, are very versatile and promising functional biopolymers. Understanding their structure-function relationships requires sensitive and accurate structural analyses to determine parameters like degree of polymerization (DP), fraction of acetylation (FA), or pattern of acetylation (PA). NMR, the gold standard for FA analysis, requires large amounts of sample. Here, we describe an enzymatic/mass spectrometric fingerprinting method to analyze the FA of chitosan polymers. The method combines the use of chitinosanase, a sequence-specific hydrolase that cleaves chitosan polymers into oligomeric fingerprints, ultrahigh-performance liquid chromatography-electrospray ionization-mass spectrometry (UHPLC-ESI-MS), and partial least-squares regression (PLSR). We also developed a technique to simulate enzymatic fingerprints in silico that were used to build the PLS models for FA determination. Overall, we found our method to be as accurate as NMR while at the same time requiring only microgram amounts of sample. Thus, the method represents a powerful technique for chitosan analysis.