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

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 (F_A), or pattern of acetylation (P_A). NMR, the gold standard for F_A analysis, requires large amounts of sample. Here, we describe an enzymatic/mass spectrometric fingerprinting method to analyze the F_A 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 F_A 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.