Metabolite Fingerprinting Using 1H-NMR Spectroscopy and Chemometrics for Classification of Three Curcuma Species from Different Origins

Curcuma longa, Curcuma xanthorrhiza, and Curcuma manga have been widely used for herbal or traditional medicine purposes. It was reported that turmeric plants provided several biological activities such as antioxidant, anti-inflammatory, hepatoprotector, cardioprotector, and anticancer activities. Authentication of the Curcuma species is important to ensure its authenticity and to avoid adulteration practices. Plants from different origins will have different metabolite compositions because metabolites are affected by soil nutrition, climate, temperature, and humidity. 1H-NMR spectroscopy, principal component analysis (PCA), and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) were used for authentication of C. longa, C. xanthorrhiza, and C. manga from seven different origins in Indonesia. From the 1H-NMR analysis it was obtained that 14 metabolites were responsible for generating classification model such as curcumin, demethoxycurcumin, alanine, methionine, threonine, lysine, alpha-glucose, beta-glucose, sucrose, alpha-fructose, beta-fructose, fumaric acid, tyrosine, and formate. Both PCA and OPLS-DA model demonstrated goodness of fit (R2 value more than 0.8) and good predictivity (Q2 value more than 0.45). All OPLS-DA models were validated by assessing the permutation test results with high value of original R2 and Q2. It can be concluded that metabolite fingerprinting using 1H-NMR spectroscopy and chemometrics provide a powerful tool for authentication of herbal and medicinal plants.

The Authentication of Java Turmeric (Curcuma xanthorrhiza) Using Thin Layer Chromatography and 1H-NMR Based-Metabolite Fingerprinting Coupled with Multivariate Analysis

The identification of adulteration practices of medicinal plants used as herbal medicine is very important to ensure the quality, safety, and efficacy. In this study, thin layer chromatography (TLC) and proton nuclear magnetic resonance (1H-NMR)-based metabolite fingerprinting coupled with multivariate analysis were used for authentication of Curcuma xanthorrhiza extract from Curcuma aeruginosa. Curcumin contents obtained from C. xanthorrhiza extract from various regions were in the range of 0.74%–1.23%. Meanwhile, curcumin contents obtained from C. xanthorrhiza extract adulterated with 0%, 10%, 25%, 40%, 50%, and 75% of C. aeruginosa were 1.02%, 0.96%, 0.86%, 0.69%, 0.43%, and 0.27%, respectively. The decreasing of curcumin contents in adulterant concentrations of 40% and more in C. xanthorrhiza rhizome could indicate the adulteration with other rhizomes. Multivariate analysis of PCA (principal component analysis) using data set obtained from 1H-NMR spectra clearly discriminated pure and adulterated C. xanthorrhiza with C. aeruginosa. OPLS-DA (orthogonal projections to latent structures-discriminant analysis) successfully classified pure and adulterated C. xanthorrhiza with higher R2X (0.965), R2Y (0.958), and Q2(cum) (0.93). It can be concluded that 1H-NMR-based metabolite fingerprinting coupled with PCA and OPLS-DA offers an adequate method to assess adulteration practice and to evaluate the authentication of C. xanthorrhiza extracts.

Metabolite fingerprinting of novel Streptomyces UK-238 from the Himalayan forest

Aims: Characterization of antimicrobial metabolites of novel Streptomyces sp. UK-238. Background: Novel antimicrobial drug discovery is urgently needed due to emerging multi antimicrobial drug resistance among pathogens. Since many years, natural products have provided the basic skeletons for many therapeutic compounds including antibiotics. Bioprospection of un/under explored habitats and focussing on selective isolation of actinobacteria as major reservoir of bio and chemodiversity has yielded good results. Objective: The main objectives of the study were the identification of UK-238 by 16S rDNA sequencing and antimicrobial metabolite fingerprinting of culture extracts. Method: In the present study, a promising isolate, UK-238, has been screened for antimicrobial activity and metabolite fingerprinting from the Himalayan Thano Reserve forest. It was identified by 16S rDNA sequencing. Ethyl acetate extract was partially purified by column chromatography. The pooled active fractions were fingerprinted by GC-MS and compounds were tentatively identified by collated data analysis based on Similarity Index, observed Retention Index from Databases and calculated Retention Index. Results: UK-238 was identified as Streptomyces sp. with 98.4% similarity to S. niveiscabiei. It exhibited broad-spectrum antibacterial and antifungal activity. GC-MS analysis of active fractions of ethyl acetate extract showed the presence of eighteen novel antimicrobial compounds belonging to four major categories- alcohols, alkaloid, esters and peptide. Conclusion: The study confirms that bioprospection of underexplored habitats can elaborate novel bio and chemodiversity.