Authentication of Zingiber Species Based on Analysis of Metabolite Profiles

Zingiber corallinum and Zingiber montanum, which belong to the Zingiberaceae family, are traditional Chinese folk medicinal herbs in Guizhou and Yunnan Province of China. They share great similarities in morphology, chemical constituent, and DNA barcoding sequence. The taxonomy of the two Zingiber species is controversial and discrimination of traditional Chinese medicines directly affects the pharmacological and clinical effects. In the present study, we performed a systemic analysis of super-barcode and untargeted metabolomics between Z. corallinum and Z. montanum using chloroplast (cp) genome sequencing and gas chromatography-mass spectrometry (GC-MS) analysis. Comparison and phylogenetic analysis of cp genomes of the two Zingiber species showed that the cp genome could not guarantee the accuracy of identification. An untargeted metabolomics strategy combining GC-MS with chemometric methods was proposed to distinguish the Zingiber samples of known variety. A total of 51 volatile compounds extracted from Z. corallinum and Z. montanum were identified, and nine compounds were selected as candidate metabolic markers to reveal the significant difference between Z. corallinum and Z. montanum. The performance of the untargeted metabolomic approach was verified with unknown Zingiber samples. Although the cp genomes could not be used to identify Zingiber species in this study, it will still provide a valuable genomics resource for population studies in the Zingiberaceae family, and the GC-MS based metabolic fingerprint is more promising for species identification and safe application of Z. corallinum and Z. montanum.

Automated summary

This study compared Zingiber corallinum and Zingiber montanum through chloroplast genome sequencing and gas chromatography-mass spectrometry analysis, finding that the chloroplast genome may not accurately identify the species. An untargeted metabolomics strategy was proposed to distinguish between the two Zingiber species using metabolic markers, and the performance of the approach was verified with unknown samples. The study suggests that the GC-MS based metabolic fingerprint is more promising for species identification and safe application of Z. corallinum and Z. montanum.