Application of NMR-based metabolomics and multivariate data analysis

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					         Application of NMR-based metabolomics
         and multivariate data analysis for quality
               control of herbal materials

 Nancy Dewi Yuliana1,2, Hye Kyong Kim2, Frank van der Kooy2,
   Henrie Korthourt3, Young Hae Choi2, Robert Verpoorte2
1Dept.Food Science and Technology, Bogor Agricultural University, Bogor, Indonesia
2Dept.Pharmacognosy, Sect. Metabolomics, Leiden University, The Netherlands
3Fytagoras BV Plant Science, Leiden, The Netherlands




  A. Introduction
         Herbal medicines
           Access to modern medicines (poverty,
           geographical reason)
           Natural ~ safer (??)
           Modern medicine ~ side effects




                                                                                     1
         Herbal medicines: Safety & efficacy issues!

Contamination: metals, mycotoxins
Addition of synthetic active ingredients
Substitution/adulteration!
Aristolochic acid case in Belgium 1990s:
    Chinese slimming herbal ; a mixture of Stephania tetrandra and
    Magnolia officinalis → substitution of Stephania tetrandra (i) with
    Aristolochia fangchi (ii) →permanent kidney failure, death




          (i)                                    (ii)




 Quality control!!
   Commonly : standardization of active compounds
   (other markers)
      Toxic adulterants, or spiked by chemical active
      ingredients ?????
   Information about a wide range of metabolites
   present in herbal preparation for standardization is
   needed!
  → metabolomic
   = all metabolites present in biological organism as
   end product of gene expression (Sumner et al.,
   2003)




                                                                          2
        Metabolomic for QC herbal preparation?
        → complicated
             Plant: mixture of many different compounds
             Herbal preparation: mixture of 2/more plants
             reliable tool to detect diverse groups of plant
             metabolites in a single run, rapid, reproducible, and
             stable over time without an elaborative sample
             preparation is needed

                                         NMR √
                         (Nuclear Magnetic Spectroscopy)
                       (Choi et al., 2004, Jahangir et al., 2008).




NMR:
- Different protons of NMR sensitive nuclei (e.g. 1H, 13C) resonate at slightly
different frequency in a given magnetic field
- The difference between the frequency of the signal and the frequency of the
reference is divided by frequency of the reference signal → chemical shift, ppm
- Depending on their chemical environment: different peak shapes and chemical shift




             singlet      doublet        multiplet
                                                              Signal intensity




                   Chemical shift, ppm




                                                                                      3
      NMR data for metabolomic: multidimensional data, analyzed by
      multivariate data (MVA)
      E.g. principal component analysis (PCA), partial least square
      analysis (PLS)
      PCA: projecting the data into several new coordinate systems
      (principal component, PC) to obtain an overview from the data
                PC3, third biggest
                            PC2, second biggest



                                 PC1, the biggest variance


• Data dimensionality ↓, typical characteristics are preserved
• Creating clusters/groups of data, while only little information
  about the data is availabe
                               (Eriksson et al., 2006)




      PCA output:
                                              Compounds higher
                                              in A and B



                                                      7.12   4.38
            A                                            8.4
PC2                                                   2.00
                                              PC2             1.08
                                                       6.38
           B
                          C                                                       0.98
                                                                           1.79
                                                                                     6.94
                                                                           4.79

                                                                                   2.79


                                                                           Compounds higher
                   PC1                                               PC1   in C


      Score plot : grouping              Loading plot : which compound(s)
      A=B                                make the difference?




                                                                                              4
B. Application of NMR-metabolomics and PCA for
Herbal QC in Leiden University


1. Metabolic Fingerprinting of Ephedra Species
  (Kim et al., 2005)
  Ephedra species: Used as weight loss agent (thermogenic
  agent) and to boost performance of athletes (e.g. Maradona
  case 1994)
  Ephedrine type alkaloids (e.g. ephedrine, pseudoephedrine) as
  the primary active ingredients
  E. sinica: the main source of alkaloids, others species may not
  contain/contain less alkaloids




  Samples:
     E. sinica
     E. intermedia
     E. distachya var. distachya
     9 commercial Ephedra samples
   all extracted by CHCl3–MeOH–H2O–NH4OH, → 2
  layers; organic and aqueous fractions, both were
  dissolved in NMR solvent (CDCl3, MeOD/buffer
  phosphat) and analyzed by NMR (Bruker, 400 MHz)
  and PCA (SIMCA ver.10)




                                                                    5
                             500.00
                                                                                                                         4
                             400.00                                                                                                                               4
                                                                                                                                                                                      4
                             300.00                                                                                                                   4
                                                                                                                                              2                              8
                                                                                                                                                    8
                             200.00                                                                        3 3                                    89
                                                                                                                                     2                    8             2
                                                                                                                                         9 2
                             100.00                                                                                          9
             PC2 (18%)




                                                                       D                                                         1
                                                                                                                                         11       9
                               0.00                                                                                      3                            1
                                                                                                                                                                   5 5
                                                                                                 3
                         -100.00                                                                                                                                                                        S
                                           D           D                                                       I                                                  55     S
                                                                                                       I                                                                          S
                         -200.00                                                                             I I                                              S        7
                                                                                                                                                              7                                     6
                                                                                                                                                                    7 6
                                                                                                                                                      7
                         -300.00                                                                                                                                   6
                                                                                                                                                                   6
                         -400.00

                         -500.00

                                      -1400 -1300 -1200 -1100 -1000 -900 -800 -700 -600 -500 -400 -300 -200 -100                         0        100     200          300        400         500       600   700 800   900 1000 1100 1200 1300
                                                                                                                         PC1 (64%)




Score Plot of PC1 and PC2 of organic fractions of Ephedra samples
S=E. sinica, I =E. intermedia, D=E. distachya var. distachya, 1—9 = commercial Ephedra

Loading plot (not shown) : highly affected by alkaloid ephedrine (higher in
E.sinica, less in E. intermedia, not found in E. distachya)

Score plot : commercial samples are not well separated, check aqueous fractions!




                120
                                                                                         6
                                                                                         6
                100

                    80
                                                                                    66
                    60

                    40
                                                                   S
 PC2 (10%)




                                                                  S
                    20                                                                                                                                1                                   8
                                                                S                                                    I                                      8
                                                                S                                            I                                                                4                         45
                                                                                                                                              2          2 9
                                                                                                                                                      1 12                   5
                         0                                                                                                               4                                   8
                                                                                                                                                          4                       5
                                                                                                             I                                             7                                   5
                                                                                                                                                      87   9 99 7
                  -20                                                                                        3                                                  7
                                                                                                     I 3
                                                                                             3
                  -40                                                                                            3

                  -60                               D
                                                   DD
                  -80

             -100
                                                -200                         -100                                        0                                                   100                                        200
                                                                                                                     PC1 (80%)




Score Plot of PC1 and PC2 of aqueous fractions of Ephedra species
S=E. sinica, I =E. intermedia, D=E. distachya var. distachya, 1—9 = commercial Ephedra
Loading plot: E.intermedia contains more benzoic acid derivatives then E. sinica, while E.
distachya contains more phenylpropanoids
Commercial samples: close to E. intermedia, except number 6, a mixture ?

Check aqueous fractions of a mixture of S and I !




                                                                                                                                                                                                                                                  6
             140

             120                                         SI21
                                                        SI21
             100
                                               6    SI21                         SI12
                                                                                 SI12
              80                                     SI11
                                                6           SI11 SI11             SI12
              60

              40
                                               66
 PC2 (22%)




              20                                                                                 1               8
                                                                                             2             4              5
               0                                                                                  28 9
                                                                                                  2        5             4
                                    S                                        I           4       11        8 5       5
                                   S                                 I
              -20                                                                                   4 9
                                  S                                  I                               7 9 7
                                  S                                  3                               9
              -40                                                                                87      7
                                                                 3
              -60                                   3        I

                             DD                                          3
              -80
                              D
             -100

             -120

             -140
                      -200              -100                                     0                       100                  200
                                                                         PC1 (68%)




Score Plot of PC1 and PC2 of aqueous fractions of Ephedra samples
S=E. sinica, I =E. intermedia, D=E. distachya var. distachya, 1—9 = commercial Ephedra,
SI11, SI12, SI21 = a mixture of S and I (1:1, 1:2, 2:1)

Indeed sample 6 is a mixture of E. sinica and E. intermedia!




       2. Quality control of anti-malarial Artemisia annua
           herbal (van der Kooy et al., 2008)

                     Artemisia annua: anti-malarial herbal, artemisinin
                    as an active ingredient
                    Artemisia afra: cough, colds, fever, loss of appetite,
                    and also malaria, no scientific report for artemisinin
                    content
                    Company X produces anti-malarial capsules
                    claimed to content Artemisia afra. Artemisinin is
                    claimed as active ingredient
                    A. annua, A. afra, and capsules (the content) were
                    extracted with CDCl3 analyzed by NMR (Bruker,
                    500 MHz) and PCA (SIMCA ver.10)




                                                                                                                                    7
                                                                       Artemsia combined final.M1 (PCA-X)
                                                                       t[Comp. 1]/t[Comp. 2]



            0.6



            0.4

                                                                                                                    C
            0.2
                                                      A
     t[2]




            -0.0



            -0.2
                                                                                                                  B
            -0.4
                                                                                                            C
            -0.6




                   -1.0   -0.9   -0.8   -0.7   -0.6   -0.5   -0.4   -0.3   -0.2    -0.1   0.0     0.1       0.2   0.3   0.4     0.5   0.6   0.7   0.8   0.9   1.0
                                                                                          t[1]

                                        R2X[1] = 0.488958           R2X[2] = 0.254784            Ellipse: Hotelling T2 (0.95)




Score plot:         A = Artemisia annua
                    B = Artemisia afra
                    C=Commercial herbal
Loading plot (not shown): the difference is due to artemisinin content (only found in A)
Confirmed by LC-MS : A contains 0.078 – 0.84% artemisinin
                        B and C no artemisinin was found
Conclusion: Capsules produced by company X contain A. afra and don’t contain artemisinin




             Conclusion

                    NMR-based metabolomics couple to MVA (PCA) can be
                    applied for the quality control of herbal medicine
                    Adulterants or substitutes in commercial herbal
                    preparations can be identified very quickly with a simple
                    sample preparation




                                                                                                                                                                    8
  Acknowledgement
Prof. Rob Verpoorte      Dr. Frank van der Kooy




Dr. Young Hae Choi       Dr. Henrie Korthourt
Dr. Hye Kyong Kim




                  Thank you!




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