Taxonomic discrimination of cyanobacteria by metabolic fingerprinting using proton nuclear magnetic resonance spectra and multivariate statistical analysis
- Authors
- Kim, Suk Weon; Ban, Sung Hee; Ahn, Chi Yong; Oh, Hee Mock; Chung, Hoeil; Cho, Soo Hwa; Park, Young Mok; Liu, Jang Ryol
- Issue Date
- Aug-2006
- Publisher
- 한국식물학회
- Keywords
- cyanobacteria; dendrogram; pattern recognition; principal component analysis; taxonomy
- Citation
- Journal of Plant Biology(한국식물학회지), v.49, no.4, pp 271 - 275
- Pages
- 5
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- Journal of Plant Biology(한국식물학회지)
- Volume
- 49
- Number
- 4
- Start Page
- 271
- End Page
- 275
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/181187
- DOI
- 10.1007/BF03031154
- ISSN
- 1226-9239
1867-0725
- Abstract
- When whole-cell extracts are analyzed, proton nuclear magnetic resonance (H-1 NMR) spectroscopy provides biochemical profiles that contain overlapping signals of the majority of the compounds. To determine whether cyanobacteria could be taxonomically discriminated on the basis of metabolic fingerprinting, we subjected whole-cell extracts of the cyanobacteria to H-1 NMR. The H-1 NMR spectra revealed a predominance of signals in the aliphatic region. Principal component analysis (PCA) of the data then enabled discrimination of the cyanobacteria. The hierarchical dendrogram, based on PCA of the aliphatic region data, showed that six cyanobacterial taxa were discriminated from two eukaryotic microalgal species, and that the six taxa could be subsequently divided into three groups. This agrees with the current taxonomy of cyanobacteria. Therefore, our overall results indicate that metabolic fingerprinting using 1H NMR spectra and multivariate statistical analysis provide a simple, rapid method for the taxonomical discrimination of cyanobacteria.
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