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Chitosans, a family of ß-(1,4)-linked, partially Nacetylated polyglucosamines, are considered to be among the most versatile and most promising functional biopolymers. Chemical analysis and bioactivity studies revealed that the functionalities of chitosans strongly depend on the polymers' degree of polymerization and fraction of acetylation. More recently, the pattern of acetylation (P A ) has been proposed as another important parameter to influence functionalities of chitosans. We therefore carried out studies on the acetylation pattern of chitosan polymers produced by three recombinant fungal chitin deacetylases (CDAs) originating from different species, namely, Podospora anserina, Puccinia graminis f. sp. tritici, and Pestalotiopsis sp. We analyzed the chitosans by 1 H NMR, 13 C NMR, and SEC-MALS and established new methods for P A analysis based on enzymatic mass spectrometric fingerprinting and in silico simulations. Our studies strongly indicate that the different CDAs indeed produce chitosans with different P A . Finally, Zimm plot analysis revealed that enzymatically treated polymers differ with respect to their second virial coefficient and radius of gyration indicating an influence of P A on polymer−solvent interactions.

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

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