Metabolic profiling by ultra-performance liquid chromatography-mass spectrometry and parallel factor analysis for the determination of disease biomarkers in Eucalyptus

Abstract

In this article, we present and discuss an alternative for data analysis of the metabolic profiles of both healthy Eucalyptus globulus and those infected with the Mycosphaerella leaf disease. The crude extracts were analyzed by reversed-phase ultra performance liquid chromatography-mass spectrometry. In order to glean the most useful information from these complex measurements, parallel factor analysis (PARAFAC) was employed for pattern recognition. After PARAFAC modeling, inspection of the scores and loadings graph allowed distinction of the healthy from the infected E. globulus samples and determination of biomarkers related to the biotic stress. The assessment of the monoisotopic masses and the fragmentation patterns allowed the identification of these biomarkers. It is hoped that the proposed method can be used for the diagnosis of diseases in plants, as well as to provide additional insight into the plant's defense mechanism. Potentially, this may demonstrate the advantages of employing high order chemometric techniques in metabolomic data analysis.