Characterization of Red Yeast Rice Products and Raw Materials Using Accurate-Mass Q-TOF LC/MS and Principal Component Analysis

Applications | 2015 | Agilent TechnologiesInstrumentation
LC/TOF, LC/HRMS, LC/MS, LC/MS/MS
Industries
Food & Agriculture
Manufacturer
Agilent Technologies

Summary

Importance of the Topic



Red yeast rice (RYR) is widely used in traditional medicine and dietary supplements for its cholesterol-lowering monacolins. Variability in natural monacolin content, potential spiking with prescription lovastatin, and contamination with pigments or toxins such as citrinin and Sudan red G pose quality and safety challenges. A robust analytical strategy is essential to ensure product authenticity, label accuracy, and consumer protection.

Objectives and Study Overview



This application note describes a comprehensive approach to profile authentic RYR samples, raw materials, and commercial supplements. Key aims were to:
  • Identify and quantify monacolins, pigments, citrinin, and Sudan red G.
  • Differentiate authentic versus spiked or adulterated products.
  • Assess variation across multiple sample types.
  • Demonstrate the utility of principal component analysis (PCA) for classification.


Methodology and Instrumentation



Sample Preparation:
  • Authentic and raw RYR powders and dietary supplement tablets/capsules were extracted in methanol, sonicated, and filtered to yield concentrations of 50 mg/mL.

Chromatographic and Mass Spectrometric Analysis:
  • UHPLC-DAD (237 nm) using an Agilent 1290 Infinity LC system with ZORBAX SB-C18 column, gradient elution in 20 min.
  • Accurate-mass Q-TOF LC/MS (Agilent 6530) with Jet Stream ESI, 100–1,000 m/z range, reference mass correction for <2 ppm accuracy.
  • Collision-induced dissociation (CID) MS/MS for structural confirmation.

Data Processing and Chemometrics:
  • Feature extraction with MassHunter Qualitative Analysis, background subtraction using blank runs.
  • Alignment, filtering by abundance, ANOVA (p < 0.05), and fold-change thresholds in Mass Profiler Professional.
  • Unsupervised PCA to visualize sample clustering by pigment and monacolin profiles.


Key Results and Discussion



Quantitative Findings:
  • Authentic RYR: monacolin K 1.9–2.3 mg/g, monacolin K acid 1.3–1.6 mg/g; no citrinin or Sudan red G detected.
  • Raw materials: monacolin K ranged from undetectable to 24.3 mg/g; citrinin found in six samples at 10–80 µg/g.
  • Dietary supplements: monacolin K 0.03–2.62 mg per unit; no contaminants detected; large label-to-actual discrepancies.

PCA Classification:
  • Distinct clusters separated by component 1 (84% variance) into monacolin‐rich versus pigment‐rich groups.
  • Component 2 (5% variance) further resolved red versus yellow pigments among pigment-dominant samples.
  • Authentic samples grouped consistently with monacolin profiles, raw materials with predominant pigments.

High-accuracy MS enabled differentiation of isobaric species (e.g., monacolin K vs. analogues) and identification of over 30 compounds beyond DAD capabilities.

Benefits and Practical Applications



This workflow supports regulatory and quality control laboratories by providing:
  • Comprehensive profiling of RYR for active ingredients, adulterants, and toxins.
  • Accurate quantification across a wide dynamic range from ppb to ppm levels.
  • Data-driven classification of product authenticity and batch consistency.
  • Enhanced traceability of raw materials and finished supplements.


Future Trends and Potential Applications



Emerging directions include:
  • Integration of machine learning models for automated classification and anomaly detection.
  • Expansion of chemometric approaches to include hierarchical clustering and support vector machines.
  • High-resolution mass spectral libraries for rapid screening of novel contaminants.
  • Hyphenated techniques combining UPLC-QTOF with ion mobility spectrometry for enhanced separation of isomers.


Conclusion



The combination of UHPLC-DAD, accurate-mass Q-TOF LC/MS, and PCA provides a powerful platform for the characterization and quality assessment of RYR products. This approach yields high confidence in compound identification, uncovers significant sample variability, and enables robust classification of authenticity and safety.

References


  1. Avula B. et al. Chemical profiling and quantification of monacolins and citrinin in red yeast rice commercial raw materials and dietary supplements using liquid chromatography-accurate Q-TOF mass spectrometry: Chemometrics application. J. Pharm. Biomed. Anal. 100, 243-253 (2014).
  2. Endo A. The history and recent development of Anka and Monascus species. Ferment. Technol. 43, 544-552 (1985).
  3. Gordon R.Y. et al. Marked Variability of Monacolin Levels in Commercial Red Yeast Rice Products: Buyer Beware! Arch. Intern. Med. 170(19), 1722-1727 (2010).
  4. EFSA. Opinion of the Scientific Panel on Food Additives, Flavourings, Processing Aids and Materials in Contact with Food on dyes illegally present in food in the EU. The EFSA Journal 263 (2005).
  5. Chen M. and Jons M.R. Effect of pH and nitrogen source on pigment production of Monascus purpureus. Appl. Microbiol. Biotechnol. 40, 132-138 (1993).

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