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Published on: April 18, 2020
Synergistic mechanism of GH11 xylanases with different action modes from Aspergillus niger An76
Shu Zhang1, Sha Zhao1,2, Weihao Shang1
1State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao, 266237, Shandong, China.
Background:
Xylan is the most abundant hemicellulose polysaccharide in nature, which can be converted into high value-added products. However, its recalcitrance to breakdown requires the synergistic action of multiple enzymes. Aspergillus niger, possessing numerous xylan degrading isozyme-encoding genes, are highly effective xylan degraders in xylan-rich habitats. Therefore, it is necessary to explore gene transcription, the mode of action and cooperation mechanism of different xylanase isozymes to further understand the efficient xylan-degradation by A. niger.
Results:
Aspergillus niger An76 encoded a comprehensive set of xylan-degrading enzymes, including five endo-xylanases (one GH10 and four GH11). Quantitative transcriptional analysis showed that three xylanase genes (xynA, xynB and xynC) were up-regulated by xylan substrates, and the order and amount of enzyme secretion differed. Specifically, GH11 xylanases XynA and XynB were initially secreted successively, followed by GH10 xylanase XynC. Biochemical analyses displayed that three GH11 xylanases (XynA, XynB and XynD) showed differences in catalytic performance and product profiles, possibly because of intricate hydrogen bonding between substrates and functional residues in the active site architectures impacted their binding capacity. Among these, XynB had the best performance in the degradation of xylan and XynE had no catalytic activity. Furthermore, XynA and XynB showed synergistic effects during xylan degradation.
Conclusions:
The sequential secretion and different action modes of GH11 xylanases were essential for the efficient xylan degradation by A. niger An76. The elucidation of the degradation mechanisms of these xylanase isozymes further improved our understanding of GH-encoding genes amplification in filamentous fungi and may guide the design of the optimal enzyme cocktails in industrial applications.
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