Metabolic profiling of cyanobacterial extracts using multivariate data analysis for their anti-obesity properties

Background. Obesity has become a major health issue worldwide. Progression of obesity has been linked to numerous of comorbidities such as coronary heart disease, heart failure, hypertension and diabetes mellitus. The urge for new anti-obesity drugs with less adverse effects is apparent. Metabolites from cyanobacteria have been associated with anti-obesity bioactivity and that has evoked increased interest of finding a new drug from that source. Aims. The aim of this study was to perform multivariate data analysis (MVDA) on 117 cyanobacterial extracts to identify potential biomarkers with anti-obesity properties. Methods. Obtained data from UPLC-QTOF-MS was preprocessed by MarkerLynx software to optimize the data evaluation. MVDA was performed utilizing SIMCA software. Principal component analysis (PCA) and orthogonal partial least squeares discriminant analysis (OPLS-DA) were applied to explore if there was any difference between strains which were „active“ versus „non-active“. Several biomarkers, with the highest variability were then selected from different fractions of cyanobacteria. Results and discussion. MVDA was performed on three different fractions, A, B and C of each cyanobacteria strain. From fraction A, only 3 potential biomarkers from 11 active extracts of A were discovered. However, for fraction B there were 15 potential biomarkers discovered from 11 active extracts of B, and 7 potential biomarkers were discovered from 6 active extracts of fraction C. Conclusions. The following strains, LEGE07159B, LEGE06147B, LEGE06105B, LEGE07459C, LEGE06114C showed the most promising results. These strains need to be cultured and tested again for bioactivity. If they test positive, then they need to be cultured in high quantity to conduct NMR analysis for structural elucidation.

Author dc:creator

• Baldvin Gestsson 1992-

Contributors dc:contributor

• Háskóli Íslands

• Lyfjafræði
• Offita
• Hjartasjúkdómar
• Sykursýki
• Lyfjagerð
• Rannsóknir

Language dc:language.iso

en

Handle dc:identifier.uri

http://hdl.handle.net/1946/32564

OAI identifier oai:identifier

oai:skemman.is:1946/32564