Principal component analysis facilitated fast and noninvasive Raman spectroscopic imaging of plant cell wall pectin distribution and interaction with enzymatic hydrolysis. (28th October 2020)

• Record Type: Journal Article
• Authors: He, Qing; Zabotina, Olga A.; Yu, Chenxu
• Is Part Of: Journal of Raman spectroscopy. Volume 51:Number 12(2020)
• Page Start: 2458
• Page End: 2467
• Publication Date: 2020-10-28
• Subjects: enzymatic hydrolysis -- HCA -- PCA -- polysaccharides -- Raman image; Raman spectroscopy -- Periodicals; 535.846
• DOI: 10.1002/jrs.6022
• Languages: English
• ISSNs: 0377-0486

Abstract

Abstract: The plant cell wall is a complex network of polysaccharides. A better understanding of the plant cell wall polysaccharide content, distribution, and interactions among them could be instrumental for our further understanding of plant cell wall in general. Confocal Raman microscopy (CRM) is a powerful tool that could reveal details about chemical landscape of the plant cell wall with micrometer resolution. However, the low signal‐to‐noise (S/N) ratio of Raman spectral signal led to low throughput of Raman imaging, which limited its application in plant cell wall study. In this study, the interaction between the cell wall polysaccharides and the pectin enzyme endo‐polygalacturonase (EPG) was characterized by analyzing Raman images collected before and after EPG treatment at high scanning speed. The obtained low S/N ratio Raman spectra were processed with principal component analysis (PCA) and hierarchical clustering analysis (HCA) to recover information‐rich signature changes in Raman signal dataset that reflected the changes in the polysaccharides caused specifically by the enzymatic hydrolysis. The PCA reconstruction technique significantly improved the S/N ratio of the spectra dataset while kept the Raman signal intact. Further analysis of principal components (PCs) revealed the pectin distribution and its interaction with the enzyme, which provided organizational details of pectin inside the onion plant cell wall. The technique could be used to reveal polysaccharide organization and distribution inside plant cell walls. Abstract : Enzymatic hydrolysis pattern of plant cell wall was analyzed by Raman spectroscopic imaging. The low SNR of the Raman signal was significantly improved via principal component analysis (PCA) and hierarchical clustering analysis (HCA) to recover information‐rich signature changes in Raman signal dataset that reflected the changes in the polysaccharides caused specifically by the enzymatic hydrolysis. The technique could be used to reveal polysaccharide organization and distribution inside plant cell walls.