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Taxonomic discrimination of cyanobacteria by metabolic fingerprinting using proton nuclear magnetic resonance spectra and multivariate statistical analysis

Authors
Kim, Suk WeonBan, Sung HeeAhn, Chi YongOh, Hee MockChung, HoeilCho, Soo HwaPark, Young MokLiu, 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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