In Journal of agricultural and food chemistry
Huanglongbing (HLB) is one of the most destructive citrus diseases, mainly caused by the Gram-negative bacteria Candidatus Liberibacter asiaticus. Aiming at unraveling the mechanisms of different scion/rootstock combinations on improving HLB-affected orange juice quality, the effects of rootstocks on the metabolites of HLB-affected sweet orange juices were investigated using a combined strategy of untargeted metabolomics and machine learning. A total of 2531 ion features were detected using UHPLC-Q-Orbitrap high-resolution electrospray ionization mass spectrometry, and 54 metabolites including amino acids, amines, flavonoids, coumarins, fatty acids, and glycosides were definitely or tentatively identified as the differential markers based on the random forest algorithm. Furthermore, 24 metabolites were verified and semi-quantified using authentic standards. Notably, the presence of specific amino acids and amines, especially polyamines, indicated that different rootstocks might affect glutamate, aspartate, proline, and arginine metabolism to regulate the physiological response against HLB. Meanwhile, the production of flavonoids and prenylated coumarins suggested that rootstocks influenced phenylalanine and phenylpropanoid metabolism. The possible metabolic pathways were proposed, and the important intermediates were verified by authentic standards. These results provide new insights on the effects of rootstocks on the metabolites of HLB-affected sweet orange juices.
Liu Xin, Wang Zhixin, Gmitter Frederick G, Grosser Jude W, Wang Yu
2023-Jan-06
Huanglongbing, citrus, random forest, rootstock, untargeted metabolomics
