Head-to-Head Comparison of Ultra-High-Performance Liquid

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Head to head comparison of uHPLC-DAD versus qNMR for the quantitative analysis of the silymarin complex in Silybum marianum fruit extracts Antigoni Cheilari, Sonja Sturm, Daniel Intelmann, Christoph Seger, and Hermann Stuppner J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.5b05494 • Publication Date (Web): 23 Jan 2016 Downloaded from http://pubs.acs.org on January 25, 2016

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Journal of Agricultural and Food Chemistry

Head to Head Comparison of uHPLC-DAD versus qNMR for the Quantitative Analysis of the Silymarin Complex in Silybum marianum Fruit Extracts

Antigoni Cheilari1, Sonja Sturm1*, Daniel Intelmann2, Christoph Seger1, Hermann Stuppner1

Affiliation Institute of Pharmacy, Department of Pharmacognosy, CCB – Centrum of Chemistry and Biomedicine, University of Innsbruck, Innrain 80/82, 6020 Innsbruck, Austria Bionorica research GmbH, Mitterweg 24, 6020 Innsbruck, Austria

* Correspondence: Dr. Sonja Sturm, Institute of Pharmacy, Department of Pharmacognosy, CCB – Centrum of Chemistry and Biomedicine, University of Innsbruck, Innrain 80/82, 6020 Innsbruck, Austria Email: [email protected], Tel: 0043 512 507 58408, Fax: 0043 512 507 58499

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Abstract

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Quantitative NMR spectroscopy (qNMR) is known as excellent alternative to chromatography based

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mixture analysis. NMR spectroscopy is a non-destructive method, needs only limited sample

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preparation and can be readily automated. A head-to-head comparison of qNMR to an uHPLC-DAD

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based quantitative analysis of six flavonolignan congeners (silychristin, silydianin, silybin A, silybin B,

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isosilybin A, isosilybin B) of the Silybum marianum silymarin-complex is presented. Both assays

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showed similar performance characteristics (linear range, accuracy, precision, LOQs) with analysis

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times below 30 min / sample. The assays were applied to industrial S. marianum extracts (AC

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samples) and to extracts locally prepared from S. marianum fruits (PL samples). Assay comparison by

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Bland-Altman plots (relative method bias AC samples = -0.1%, 2S range ± 5.1%, relative method bias

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PL samples = -0.3%, 2S range ± 7.8%) and Passing-Bablok regression analysis (slope and intercept for

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AC and PL samples not significantly different from 1.00 and 0.00, respectively; Spearman’s coefficient

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of rank correlation >0.99) did show, that qNMR and uHPLC-DAD can be used interchangeably to

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quantitate flavonolignans in the silymarin complex.

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Key words

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Silybum marianum, Asteraceae, silymarin, flavonolignans, uHPLC-DAD, qNMR, quantitation

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Introduction

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NMR spectroscopy based analysis of mixtures is an appealing alternative to chromatographic analysis

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– both in the qualitative (metabolic profiling)1,2 and the quantitative (qNMR) context.3 The analytical

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concept of qNMR, usually performed using 1H NMR resonances, can be considered an untargeted

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approach (any analyte combination can be quantified if appropriate undisturbed signals can be

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identified) and offers some advantages over chromatographic analyses.4 It is non-destructive, sample

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preparation is of limited complexity and generally compatible to chromatography, can be automated,

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and provides – without the need of chromatographic separation or additional analytical devices

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(hyphenation) – both qualitative and quantitative analyte information. Aside quantitative

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information derived from carefully selected single NMR signals the complete 1H NMR spectrum of

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the targeted compound allows a deep insight into its chemical structure. A set of 1H NMR resonances

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can be utilized to confirm the identity of a targeted entity in a mixture – e.g. a methine 1H-NMR

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resonance is used for quantitation and the methyl group 1H-NMR signal pattern is used for

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qualification. In addition, an unbiased and holistic view of the total sample composition (alike the

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total ion current in LC-MS) is obtained and allows checking for sample adulterations, unusual signal

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pattern, solvent residuals and many other features.4,5,6

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From a practical point of view, quantitative and qualitative phytochemical analysis in research,

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production, and quality control is always constrained by limited availability of resources including

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sample material, access to instrumentation, and investigation time. Hence replacing technologies

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with low sample throughput, high personnel demand, and extensive sample workup requirements by

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alternative approaches is a central demand in such processes. Due to the advantages of NMR

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spectroscopy over chromatographic assays as listed above qNMR can be understood as such an

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alternative. However, although both qNMR and HPLC-UV are well established and frequently applied

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technologies in this context, head-to-head comparisons of quantitative assays have hardly been

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performed.

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The group around Verpoorte7 did report on artemisinin quantitation in eight samples by qNMR,

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HPLC-ELSD, HPLC-MS, and TLC regarding qNMR as gold standard. They reported qNMR easy to use

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and found all methods quantitatively comparable. Pieri et al. did compare NMR derived quantitative

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results to findings from chromatographic assays in comprehensive Thymus vulgaris metabolite

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profiling,8 in a targeted analysis of cynaropicrin from artichoke leaf extracts,9 and in an investigation

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devoted to quantitate steviol glycosides from Stevia rebaudiana.10 Pauli and co-workers did devote a

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recent publication to the analysis of green tea catechins by qNMR and LC-MS/MS.11 These authors



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used the qNMR/HiFSA (1H-NMR iterative full spin analysis) approach4 for NMR signal selection and

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validated their approach against the NIST reference material SRM3255. Seven analytes were

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quantified in two extracts and the SRM with LC-MS/MS and qNMR results showing high congruency.

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Milk thistle (Silybum marianum (L) GAERTN.) preparations have been used for centuries to treat a

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variety of illnesses, particularly liver maladies.12 The effective biological activities of the plant are

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credited to silymarin, an isomeric mixture of at least six flavonolignans (Figure 1), namely silychristin

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(1), silydianin (2), silybin A (3), silybin B (4), isosilybin A (5) and isosilybin B (6), and additionally

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taxifolin, a flavonoid. The fruits contain up to 9% of those compounds, which mainly accumulate in

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their external cover.13,14 The hepatoprotective activity of silymarin can be explained by the

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antioxidant properties due to the phenolic nature of flavonolignans, stimulating liver cells

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regeneration and cell membrane stabilization to prevent hepatotoxic agents from entering

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hepatocytes.15 Numerous studies have demonstrated the efficacy of silymarin as a hepatoprotective,

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but also as an anti-inflammatory, antioxidant, antifibrotic and cancer chemopreventive agent.15-18

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In herbal supplement preparations the amount of silymarin in S. marianum extracts varies from 55-

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85% with the exact composition still not completely unravelled.19 Up to now a number of HPLC-UV

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methods have been published to support quality control measures; some however with either rather

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long analysis times (30 min – 100 min)20-26 or limited validation data presentation.21,26 In addition LC-

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MS/MS instrumentation was used to characterize S. marianum extract constituents27-29 or to follow

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them in bio-analytical relevant matrices like plasma.30

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With these reports at hands it was envisioned to perform a head-to-head comparison of an HPLC

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platform with qNMR. Since there is still the need to prove the equivalence of qNMR to the

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phytoanalytical “gold-standard” methods due to its inherent orthogonality to HPLC, the

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establishment of a thoroughly validated HPLC method was considered as prerequisite in such

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approach and not as an “add-on” to prove the validity on NMR derived quantitative data.

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Consequently, it was decided to establish a state-of-the-art HPLC assay utilizing a modern stationary

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phase. Due to the chosen research object (the S. marianum derived silymarin complex) MS/MS

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detection was deemed unnecessary and UV/VIS detection was seen sufficient.

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Materials and Methods

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Chemicals and Reference Compounds

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Methanol and formic acid were of HPLC grade and purchased from Merck (Darmstadt, Germany) and

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Sigma-Aldrich (Vienna, Austria) respectively. Methanol-d4 (99.90% containing 0.03% TMS) was from


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Euriso-Top (Saint-Aubin, France). Water for HPLC was produced on site using an Arium611UV

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(Sartorius Stedim Biotech, Göttingen, Germany) water purification system. Reference compounds 1 -

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6 were purchased from PhytoLab (Vestenbergsgreuth, Germany) and anthracene from Sigma Aldrich

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(Vienna, Austria). Purity of all standard compounds was ≥98.5% (determined by HPLC and NMR).

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Plant material and sample preparation

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Bionorica Research GmbH (Innsbruck, Austria) provided dry S. marianum fruit extracts (extraction

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solvent acetone, AC) and dry S. marianum fruits (PL). Voucher specimens of these materials were

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deposited at the Institute of Pharmacy/Pharmacognosy. AC samples were weighted (10.0 ± 0.1 mg)

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into 1.5 ml polyethylene microcentrifuge tubes (Eppendorf, Hamburg, Germany). 1 mL methanol-d4

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containing anthracene (0.8 mg/mL) as internal standard (IS) was added and after vigorous mixing (1

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min) on a Vortex mixer (VWR, Vienna, Austria) samples were incubated at 24°C under mild agitation

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overnight to complete solvatization. After centrifugation (10 min at 24 oC and 20817 g) 650 μL of the

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supernatants was transferred to NMR tubes, 300 µl to HPLC vials. Each sample was prepared in

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triplicate. All samples were stored at 4°C until analysis. PL samples were ground and 100.0 ± 0.1 mg

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were extracted five times with 1 mL methanol in the Ultra Sonic bath for 15 minutes. After each

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extraction cycle, samples were centrifuged as given for the AC samples. Centrifugation supernatants

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were combined, evaporated, and redissolved in 2 mL of methanol-d4 fortified with the IS (0.8

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mg/mL). After centrifugation (5 min at 24 oC and 20817 g) 650 μL of the supernatants was transferred

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to NMR tubes, 300 µl to HPLC vials. Each sample was prepared in triplicate. All samples were stored

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at 4°C until analysis.

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NMR experimental parameters

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NMR spectra were acquired at 300 K with a Bruker Avance II 600 spectrometer (Bruker Biospin,

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Rheinstetten, Germany) equipped with a 5 mm Prodigy Cryo-probehead with Z-gradient.

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Experiments were performed in automation mode, using a Bruker BACS-60 sample changer operated

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by Bruker IconNMR. Data acquisition and processing were done with Bruker Topspin 3.1. 1H-NMR

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spectra were acquired using the Bruker zg0pr pulse program with the following settings: relaxation

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delay (d1) = 15 s; flip angle = 45o; acquisition time = 2.99 s; FID (free induction decay) data points = 64

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K; spectral width = 20 ppm; number of scans = 96. For experiments using presaturation, the

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transmitter offset was manually set in order to achieve optimal suppression of the residual water

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signal. In all cases the acquired FIDs were Fourier transformed to yield spectra with 128 K data points

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(zero filling). Manual phase correction and automatic polynomial baseline correction were always

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used. Chemical shift values were referenced to the calibration standard (TMS) signal. Inversion-

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recovery experiments were performed using the Bruker t1ir pulse program, with standard acquisition



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parameters, setting the τ (tau) parameter to 0.01, 0.05, 0.1, 0.25, 0.5, 1, 2, 4, 8, and 15 seconds. T1

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(longitudinal relaxation) values were calculated using the T1 relaxation routine (Topspin 3.1).

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HPLC-DAD and LC-MS conditions

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HPLC analyses were performed with a HP1260 system equipped with binary pump, auto sampler,

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column thermostat, and photodiode array detector (Agilent, Waldbronn, Germany). An Agilent

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Poroshell 120 EC-C18 column (3.0 x 50 mm, 2.7 μm particle size) was used as stationary phase and

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water (A) / methanol (B), both containing 0.1% formic acid, as mobile phase solvents. Separation of

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the analytes (1 µl injection volume) was achieved by applying a solvent gradient of 0 min 80% A; 3

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min 70% A; 6 min 60% A; 8 min 60% A; 12 min 55% A; 13 min 2% A, 17 min 2% A delivered at a flow

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rate of 0.6 ml/min. The gradient program was followed by a re-equilibration period of 10 min at 80%

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A. The column oven temperature was set to 50°C, the detection wavelength to 286 nm. HPLC-MS/MS

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experiments for HPLC-DAD peak assignment confirmation were performed on an amaZon SL ion-trap

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mass spectrometer (Bruker-Daltonics, Bremen, Germany) hyphenated to the Agilent HP1260 system

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operated under the given chromatography conditions. MS parameters: ESI alternating mode; spray

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voltage = 4.5 kV; dry gas = 8 L/min at 250°C; nebulizer = 30 psi; full scan mode = m/z 100-1500.

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MS/MS experiments were performed in the automatic mode.

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Calibration and Validation

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Both uHPLC and NMR methods were validated according to the ICH guidelines ‘’Validation of

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Analytical Procedures: Text and Methodology Q2 (R1)’’31 for linearity, limit of detection and

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quantitation, peak purity, accuracy, precision and repeatability. Standard stock solutions were

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prepared by dissolving compounds 1 – 6 in methanol-d4 containing the internal standard (IS) (0.8

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mg/mL). From these stock solutions nine calibrator levels (2000 μg/mL, 1000 μg/mL, 700 μg/mL, 500

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μg/mL, 310 μg/mL, 200 μg/mL, 45 μg/mL, 25 μg/mL, 10 μg/mL) were prepared. Calibration curves

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were obtained by plotting the peak areas of analytes 1 – 6 versus the concentrations of 1 – 6 in

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uHPLC and by plotting the respective ratios of areas and concentrations of 1 – 6 and IS in NMR. The

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regression parameters intercept, slope and correlation coefficient (R2) were calculated by linear

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regression analysis. The limit of detection (LOD) and the limit of quantitation (LOQ) for each analyte

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were calculated from the regression models including only the lowest three dilution levels. From the

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obtained regression equation data the LOD was calculated as three times the standard deviation (SD)

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of the y-intercept divided by the slope, whereas the LOQ was calculated as ten times the SD of the y-

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intercept divided by the slope. Accuracy was determined by recovery experiments spiking a dry

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extract (AC 01) and a fruit batch (PL 01) with known amounts of selected analytes prior to sample

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workup. All samples were prepared in triplicate. By analysing the variability (triplicate analysis) of all


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recovery samples on three consecutive days intra-day and inter-day precision of the assays was

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assessed. Quantitative results have not been corrected for residual traces of moisture or solvents.

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Statistics

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Data analysis for validation and calculation of analyte concentrations was done within Microsoft

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Excel 2011 (Redmond, WA, USA) spread sheets. Statistical data analysis (comparative Bland-Altman

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plots, Passing Bablok regression, rank correlation analysis) was done with MedCalc for Windows,

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version 15.8 (MedCalc Software, Ostend, Belgium)

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Results and Discussion

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Sample preparation for NMR and HPLC

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Two sample types were used in this investigation. Beside industry based plant extracts (extraction

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solvent acetone, AC) typically used as formulation basis in commercial milk thistle medications (>50%

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silymarin), laboratory prepared fruit extracts (PL) were additionally investigated to introduce broader

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sample variability into the investigation. Due to the distinctively different matrix properties, tailored

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sample preparation protocols for AC and PL had to be established. In a series of preliminary 1H-NMR

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experiments several deuterium labeled solvents including methanol-d4, aceton-d6, DMSO-d6,

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acetonitrile-d3, and deuterium oxide as well as mixtures thereof were tested as potential extraction

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solvents for both AC and PL samples and as solvents for pure reference materials. The obtained

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spectra showed that methanol-d4 was the solvent of choice enabling sufficient solubility of reference

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compounds and extracts. A good separation of NMR key resonances and a clean baseline in the

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relevant spectral regions was obtained. Anthracene was chosen as internal standard for qNMR due

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to its solubility and stability in methanol, its low volatility and its aromatic nature resulting neither in

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1

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were directly re-dissolved in methanol-d4, the preparation of PL extracts was optimized to get a

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maximum of secondary metabolites into solution. Different extraction solvents (ethanol, methanol,

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chloroform, hexane and mixtures of them with water) and extraction procedures (sonication,

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Eppendorf shaker) were evaluated. Sonication supported quantitative extraction of the ground plant

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material with methanol as solvent was found to be most efficient.

H NMR signal overlap with signals of 1 - 6 nor in HPLC co-elution with 1 - 6. Whereas AC extracts

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Validation of quantitative NMR analysis

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The application of quantitative 1H NMR (qNMR) requires that at least one non-overlapping signal for

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each molecule to be quantified is available for integration.5 The research efforts were concentrated

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to the principal components of silymarin – silybin A (1), silybin B (2), isosilybin A (3), isosilybin B (4),

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silychristin (5), silydianin (6) (Figure 1). All compounds are isobaric (MW 482) with compounds 3-6



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even representing isobaric pairs of diastereoisomers (3/4 and 5/6) with very similar 1H and 13C NMR

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spectra. Silybins (3/4) and isosilybins (5/6) have the same trans-conformation in the C ring of the

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flavonoid skeleton and opposite conformation and substitution pattern in the dioxan scaffold with

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1

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Pauli and co-workers have shown that applying quantum mechanical driven HiFSA even almost

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overlapping proton signals can be used for analyte quantitation – but this approach was not

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extended to S. marianum extracts.32 Having the complexity of an extract compared to a reference

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compound standard mixture in mind and since the HiFSA approach depends on software only

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commercially available; it was decided not to take up this approach but to quantitate 3,4 and 5,6 as

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compound pairs.

H-NMR shift differences (Δδ) not exceeding 0.02 ppm at 600 MHz 1H-NMR resonance frequency.

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Careful analysis of the 1H-NMR spectra of the single compounds and of mixtures in the extraction

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solvent led to a series of methine resonances suitable for analyte quantitation in mixtures (Table 1).

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For analyte pairs 3,4 and 5,6 aromatic doublets (JHH ≈ 2.1 Hz) between 7.08 ppm and 7.15 ppm have

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been chosen, for 1 an OCHCH doublet at 5.55 ppm (JHH ≈ 6.3 Hz) and for 2 a broadened methine

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singlet at 2.89 ppm (Figure 2). The peak purity of these signals was assured by the aid of homo- and

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heteronuclear 2D NMR experiments (COSY, HSQC, HMBC), which enabled unambiguous assignment

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of these resonances in the proton scaffold of compounds 1 – 6. The patterns of these key signals

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were identical in pure compounds and matrix containing sample materials, an influence of

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satellite signals in the signal pairs 3,4 and 5,6 can be excluded, since the distance between these

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resonances does not match the anticipated 1J(13C,1H) ≈ 120 – 150 Hz.

13

C

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A crucial parameter in qNMR is the relaxation delay, which enables equilibrium of the magnetization

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between pulses when accumulating co-added FIDs. It depends on the relaxation properties of the

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various nuclei in the mixture and is determined by inversion-recovery T1 experiments for all

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resonances of interest. The highest T1-value was calculated to be 4.7 s for the selected signal of

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anthracene; all Silybum constituents showed shorter T1-values between 1.54 s and 2.22 s (Table 1).

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In order to obtain a full relaxation of all nuclei of interest a relaxation delay of 5*T1 = 23.5 s was

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calculated for a flip angle of 90o. After optimization experiments a flip angle of 45o and a relaxation

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delay of 15 s (acquisition time 2.99 s) were chosen and resulted in a 99.9% recovery of the internal

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standard signal with the longest T1. The total analysis time including sample transfer, sample

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temperature equilibration, and sample shimming was about 35 min with a net acquisition time of

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about 29 min.

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NMR method validation covered assay linearity, limit of detection and quantitation, accuracy,

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precision, and repeatability. Based on the calibration models, linearity of the method was confirmed

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for the concentration range of 10 µg/mL to 2000 μg/mL for compound 2, 3, and 6 and 25 µg/mL to

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2000 μg/mL for 1, 4, and 5 (Table 2). In these ranges the correlation coefficient of the calibration

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function was better than 0.9986 for all analytes. Limits of detection (LOD) and limits of quantitation

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(LOQ) determined by an independent approach were found to range from 0.5 µg/mL to 3.4 µg/mL

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and 1.6 µg/mL to 10.4 μg/mL, respectively. The discrepancy between found LOQs and the lower limit

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of the linear range does prove, that for analyte concentration ranges between these figures of merit

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a separate calibration model must be implemented. Consequently in this investigation the LLOQs

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(lower limits of quantitation) were set to the lowest calibrator concentration in the linear range. The

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signal to noise ratios for these concentrations did exceed 20 units.

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Accuracy was determined in recovery experiments with three different concentrations of standard

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compounds spiked to AC samples or added to the plant material (PL) prior to extraction. All results

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were within the range of 90.7% – 106.4% of the amount fortified with no observable bias between

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the methods of the materials (Table 4). Hence for both assays the analytical analyte recovery is

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quantitative and the LOQs established for the solvent-based calibrators can be used for the AC and

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PL samples. Precision of the assay was determined by preparation and analysis of fortification

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samples on three days. Intra-day precision was better than 7.7% over all analytes and materials;

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inter-day precision was found to be better than 8.6% (Table 5). There was no precision difference

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between the materials AC and PL, result scatter for analyte 2, present in rather low concentrations

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(Table 6 and Table 7), was slightly increased compared to the other analytes.

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Validation of quantitative uHPLC analysis

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To allow head-to-head comparison of the silymarin complex qNMR assay with a more conventional

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analytical technique an uHPLC-DAD assay was established. As to be expected, the quite similar

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physicochemical properties of the diastereomeric analyte pairs 3/4 and 5/6 were the major hurdle in

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the development of a sufficient selective method. In a first round of experiments several silica based

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reverse phase materials (RP-12, RP-18, phenyl-, phenyl-hexyl) as stationary phases and different

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mobile phase conditions were evaluated. The use of acetonitrile in the mobile phase was clearly not

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appropriate, but methanol alone was also not giving satisfactory separation. Acidic mobile phase

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additives were improving peak shape; optimal results were achieved with water to methanol

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gradient elution using formic acid as modifier. Conventional stationary phase materials as the

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endcapped RP-18 column (Zorbax Eclipse) were found insufficient. Even under optimized and lengthy

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chromatographic conditions signal overlap at silydianin (2) led to a remarkable method bias with 2-3-



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fold concentrations in the chromatographic assay compared to qNMR (data not shown). Taking into

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account the selectivity of the chosen wavelength (286 nm) and the possibility of differences in

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UV/VIS detection response factors (molar extinction coefficients) it is likely that an unaddressed

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silydianin isomer or silydianin degradation product33 was co-eluting with silydianin (2) in this method.

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Only replacing the fully porous Zorbax column by a superficially porous particle stationary phase

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(Poroshell C18) led to baseline separation of all analytes including silydianin (2). To prove satisfactory

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analyte separation in chromatography in addition to spiking experiments and comparison of

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retention times and UV-spectra to reference materials, HPLC-MS/MS analysis was utilized to confirm

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the peak assignment of 2 (tR = 6.40 min) as silydianin (Figure 3) since this analyte yields a distinctive

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fragmentation pattern in MS/MS analysis (m/z = 151 and 169). The peak eluting shortly after 2 (tR =

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6.60 min) showed an identical mass spectrum (negative ESI base peak with m/z = 481) and a similar

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fragmentation pattern to compound 1 with m/z = 355 as most abundant fragment ion. Thus, this

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peak could be tentatively assigned to silychristin B, a diastereomer of silychristin (1).29 The analyte

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peak eluting between 1 and 2 (tR = 6.20 min) showed a significant different behaviour to compound 1

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in mass spectrometry with a negative ESI base peak at m/z = 383 and – in contrast to the other

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analytes – a favoured ionisation in the positive ESI modus (m/z = 385). Hence this analyte is most

283

likely not a flavonolignan derivative. The HPLC-DAD assay was validated according to the ICH-

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guidelines.31 Linearity was confirmed from 10 -1000 µg/mL for 1 and 4 and from 25-2000 µg/mL for

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2, 3, 5 and 6, correlation coefficients were higher than 0.999 in all cases (Table 3). LODs ranged from

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1.0 µg/mL to 6.0 µg/mL and LOQs from 2.0 µg/mL to 19.0 µg/mL respectively (S/N > 20). The results

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of accuracy experiments were comparable to qNMR data with recovery rates from 91.8 – 110.0 %

288

(Table 4). Intra-day variations less than 7.4% and within days variability did not exceed 5.9% (Table

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5).

290 291

Sample analysis

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The validated uHPLC-DAD and qNMR methods were subsequently applied for the quantitation of

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nine batches of AC extracts and ten batches of PL extracts (Tables 6 and 7). AC 01 – 09 showed

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relatively small variations in the contents of compounds 1 – 6, with AC 02 showing a slightly higher

295

amount of silybins (3,4) and AC 07 showing a higher content in isosilybin derivatives (5,6) and

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silychristin (1). The ratio of 3 to 4 was relatively constant in AC 01 – 09 and was determined as 1 : 1.7

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(± 3.3%) by HPLC-DAD, the ratio of 6 to 5 was 1 : 2.8 (± 0.5%). In all cases the total content of

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flavonolignans was 59.8 ± 2.4% of the total extract. The content of all other flavonolignans, except 5

299

and 6 was significantly decreased. PL extracts derived from plant raw material showed distinctive

300

higher concentration variations and – as to be expected – overall lower relative amounts of 1 – 6

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(silymarin complex content 9.4 ± 2.4%). Whereas the ratio of 3 to 4 in PL 01 – 10 was with 1 : 1.6 (±


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12.1%) comparable to the AC materials, the ratio of 6 to 5 was found to be significantly different with

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1 : 1.4 (± 4.3%).

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The comparison of uHPLC and qNMR data by statistical means did prove that both techniques are

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equivalent regarding the quantitative assessment of S. marianum flavonolignan congeners present in

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the “silymarin” compound complex. Passing-Bablok correlation analysis of qNMR (Table 6, analytes 1,

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2, 3/4, 5/6) and uHPLC (Table 7, analytes 1, 2 and sums of 3+4 and 5+6) derived analyte

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concentrations in AC and PL samples (separate analysis due to different concentration units) did

310

result in ideal correlation equations (Figure 4) with intercepts statistically not different from zero (AC:

311

intercept = 2.91, 95% CI = -1.02 to 18.66; PL: intercept = -4.61, 95% CI = -12.75 to 1.35) and slopes

312

statistically not different from one (AC: slope = 0.99, 95% CI = 0.98 to 1.01; PL: slope = 1.02, 95% CI =

313

1.00 to 1.07). Calculating the rank correlation coefficient (Speaman’s rho) confirmed the visually

314

impressive correlation with rho > 0.99 for both analyses (Figure 4). Relative Bland-Altman plot based

315

method comparison analysis (Figure 4) did confirm the results of the Passing-Bablok correlation

316

analysis and further unveiled that neither AC nor PL samples analysis did show any significant

317

concentration dependent bias. This does prove, that minor matrix constituents neighbouring the

318

NMR signals of compounds 1 and 5+6 (Figure 2) do not significantly perturbate the qNMR based

319

analyte quantification. The 2S confidence intervals of the AC and PL Bland-Altman plots (2S = 5.1%

320

and 7.8% respectively) were in good agreement with the inter-day RSD data gathered in the

321

validation process of the assays (Table 5) and the RSD data obtained from repeated analysis of the

322

samples (Table 6 and Table 7). No signs of additional sources of imprecision (e.g. bias related effects

323

from matrix interferences) were detected. If however, a compound-by-compound quantification is

324

desired, the presented uHPLC assay must be seen superior to the qNMR method due to partial signal

325

overlap in the latter one.

326 327

This presentation aims to prove, that qNMR and uHPLC analysis, although in principal orthogonal

328

instrumental analysis technologies, can be interchangeably used to quantitate secondary metabolites

329

from raw material (fruit extracts = PL) and enriched industry based extracts (acetone dry extracts =

330

AC). In this particular case study sample preparation protocols were identical for qNMR and uHPLC,

331

extracts solved in deuterated NMR solvents can be easily applied to chromatographic assays. Key

332

figures of merit of the assay validation – linear range, LOQ / LOD, repeatability were found to be

333

more the less identical for both assays – this is remarkably different from a recent report, were LC-

334

MS/MS analyses showed a distinctively higher RSD than qNMR.11 Both assays were applied to

335

nineteen sample batches – nine AC samples and ten PL samples. Identical quantitative results were

336

obtained, no statistical differences were found between the methods. From an economic point of



337

view, both approaches are comparable, too when used in routine analysis. Whilst NMR equipment is

338

usually more expensive than chromatography instrumentation, costs per sample are lower in NMR

339

due to reduced solvent use and less need for consumables. Also measurement times were

340

comparable, although not been fully optimized both techniques are capable of running several dozen

341

samples per day. With all the care needed judging such a limited investigation the obtained results

342

provide confidence that – proper assay design and assay validation provided – the concept to use

343

(automatable) qNMR and uHPLC interchangeably for quantitative analysis of primary and secondary

344

metabolites from rather crude mixtures, e.g. from fermentation processes, from extraction plants, or

345

within raw material entry control will inspire further investigations in this topic.

346 347

Acknowledgements

348

The authors acknowledge the substantial support by Bionorica SE, Neumarkt, Germany and Bionorica

349

Research GmbH, Innsbruck, Austria.

350


Page 12 of 28

Page 13 of 28

351


References

352 353 354 355 356 357 358 359 360 361 362 363

(1) Seger, C.; Sturm S. Analytical aspects of plant metabolite profiling platforms: current standings and future aims. J. Proteome Res. 2007, 6, 480-497. (2) Holmes, E.; Tang, H.; Wang, Y.; Seger C. The assessment of plant metabolite profiles by NMRbased methodologies. Planta Med. 2006, 72, 771-785. (3) Pauli, G. F.; Gödecke, T.; Jaki, B.U.; Lankin, D. C. Quantitative 1H NMR. Development and potential of an analytical method: an update. J. Nat. Prod. 2012, 75, 834-851. (4) Simmler, C.; Napolitano, J. G.; McAlpine, J. B.; Chen, S. N.; Pauli, G. F. Universal quantitative NMR analysis of complex natural samples. Curr. Opin. Biotechnol. 2014, 25 ,51-59. (5) Pauli, G. F.; Jaki, B. U.; Lankin, D. C. Quantitative 1H NMR: development and potential of a method for natural products analysis. J. Nat. Prod. 2005, 68, 133-149. (6) Maggio, R. M.; Calvo, N. L.; Vignaduzzo, S. E.; Kaufman, T. S. Pharmaceutical impurities and

364

degradation products: uses and applications of NMR techniques. J. Pharm. Biomed. Anal. 2014,

365

101, 102-122.

366 367

(7) Liu, N. Q.; Choi, Y. H; Verpoorte, R.; van der Kooy, F. Comparative quantitative analysis of artemisinin by chromatography and qNMR. Phytochem. Anal. 2010, 21, 451-456.

368

(8) Pieri, V.; Sturm, S.; Seger, C; Franz, C.; Stuppner, H. 1H NMR-based metabolic profiling and target

369

analysis: a combined approach for the quality control of Thymus vulgaris. Metabolomics 2012, 8,

370

335-346.

371 372 373

(9) Pieri, V.; Stuppner, H. Quantification of cynaropicrin in artichoke leaf extracts by ¹H NMR spectroscopy. Planta Med, 2011, 77, 1756-1758. (10) Pieri, V.; Belancic, A.; Morales, S.; Stuppner H. Identification and quantification of major steviol

374

glycosides in Stevia rebaudiana purified extracts by 1H NMR spectroscopy. J. Agric. Food Chem.

375

2011, 59, 4378-4384

376

(11) Napolitano, J. G.; Gödecke, T.; Lankin, D. C.; Jaki, B. U.; McAlpine, J. B.; Chen, S. N.; Pauli, G. F.

377

Orthogonal analytical methods for botanical standardization: determination of green tea

378

catechins by qNMR and LC-MS/MS. J. Pharm. Biomed. Anal. 2014, 93, 59-67.

379 380 381 382 383

(12) Flora, K.; Hahn, M.; Rosen, H.; Benner, K. Milk thistle (Silybum marianum) for the therapy of liver disease. Am. J. Gastroenterol. 1998, 93, 139-143. (13) Morazzoni, P.; Bombardelli, E. Silybum marianum (Carduus marianus). Fitoterapia 1995, 66, 342. (14) Madrid, E.; Corchete, P. Silymarin secretion and its elicitation by methyl jasmonate in cell

384

cultures of Silybum marianum is mediated by phospholipase D-phosphatidic acid. J. Exp. Bot.

385

2010, 61, 747-754.



386 387 388 389

(15) Fraschini, F.; Demartini, G.; Esposti, D. Pharmacology of Silymarin. Clin. Drug. Invest. 2002, 22, 51-65. (16) Abenavoli, L.; Capasso, R.; Milic, N.; Capasso F. Milk thistle in liver diseases: past, present, future. Phytother. Res. 2010, 24, 1423–1432.

390

(17) AbouZid, S. Silymarin, natural flavonolignans from milk thistle. In: Phytochemicals - A Global

391

Perspective of Their Role in Nutrition and Health; Rao, V. Ed.; InTech: Rijeka, Croatia, 2012; pp

392

255-272.

393

(18) Burczynski, F. J.; Yan, J.; Gong, Y.; Nguyen, D.; Wang, G.; Burczynski, S. D.; Smith, H. J.; Gong, Y.

394

The hepatoprotective effect of diltiazem and silymarin. Nat. Prod. Chem. Res. 2013, 1, 111.

395

(19) Kroll, D. J.; Shaw, H. S.; Oberlies, N. H. Milk thistle nomenclature: Why it matters in cancer

396 397 398 399

research and pharmacokinetic studies. Integr. Cancer Ther. 2007, 6, 110–119. (20) Kuki, A.; Nagy, L.; Deak, G.; Nagy, M., Zsuga, M.; Keki, S. Identification of Silymarin Constituents: An Improved HPLC―MS Method. Chromatographia 2012, 75, 175-180. (21) Saleh, I. A.; Vinatoru, M.; Mason, T. J.; Abdel-Azim, N. S.; Aboutabl, E. A.; Hammouda, F. M.

400

Ultrasonic-assisted extraction and conventional extraction of Silymarin from Silybum marianum

401

seeds; a comparison. Res. J. Pharm. Biol. Chem. Sci. 2015, 6, 709-717.

402 403 404

(22) Eklund, L.; Simon, J. P.; Ballenger, J. High Performance Liquid Chromatography of flavonolignans in commercial milk thistle supplements. Bios 2009, 80, 164-169. (23) Lee, J. I.; Narayan, M.; Barrett, J. S. Analysis and comparison of active constituents in commercial

405

standardized silymarin extracts by liquid chromatography-electrospray ionization mass

406

spectrometry. J. Chromatogr. B 2007, 845, 95-103.

407 408

(24) Kvasnicka, F.; Bíba, B.; Sevcík, R.; Voldrich, M.; Krátká, J. Analysis of the active components of silymarin. J. Chromatogr A. 2003, 990, 239-245.

409

(25) Omar, A.; Hadad, G.; Badr J. First detailed quantification of silymarin components in the leaves of

410

Silybum marianum cultivated in Egypt during different growth stages. Acta Chromtogr. 2012, 24,

411

463-474.

412 413 414

(26) Wianowska, D.; Wiśniewski, M. Simplified procedure of silymarin extraction from Silybum marianum L. Gaertner. J. Chromatogr. Sci. 2015, 53, 366-372. (27) Wang, K.; Zhang, H.; Shen, L.; Du, Q.; Li, J. Rapid separation and characterization of active

415

flavonolignans of Silybum marianum by ultra-performance liquid chromatography coupled with

416

electrospray tandem mass spectrometry. J. Pharm. Biomed. Anal. 2010, 53, 1053-1057.

417

(28) Lee, J. I.; Hsu, B. H.; Wu, D.; Barrett, J. S. Separation and characterization of silybin, isosilybin,

418

silydianin and silychristin in milk thistle extract by liquid chromatography-electrospray tandem

419

mass spectrometry. J. Chromatogr. A 2006, 1116, 57-68.


Page 14 of 28

Page 15 of 28

420


(29) Shibano, M.; Lin, A. S.; Itokawa, H.; Lee, K. H. Separation and characterization of active

421

flavonolignans of Silybum marianum by liquid chromatography connected with hybrid ion-trap

422

and time-of-flight mass spectrometry (LC-MS/IT-TOF). J. Nat. Prod. 2007, 70, 1424-1428.

423

(30) Brinda, B. J.; Zhu, H. J.; Markowitz, J. S. A sensitive LC-MS/MS assay for the simultaneous analysis

424

of the major active components of silymarin in human plasma. J. Chromatogr. B 2012, 902, 1-9.

425

(31) N.N. (2006) ICH Harmonized Tripartite Guideline Validation of Analytical Procedures: Text and

426

Methodology Q2(R1); http://www.ich.org/products/guidelines/quality/article/quality-

427

guidelines.html (accessed August 23, 2015)

428

(32) Napolitano, J. G.; Lankin, D. C.; Graf, T. N.; Friesen, J. B.; Chen, S. N.; McAlpine J. B.; Oberlies, N.

429

H; Pauli, G.F. HiFSA Fingerprinting applied to isomers with near-identical NMR spectra: The

430

Silybin/Isosilybin case. J. Org. Chem. 2013, 78, 2827-2839.

431 432 433

(33) Bilia, A.R.; Bergonzi, M.C.; Gallori, S.; Mazzi, G.; Vincieri, F. F. J. Pharm. Biomed. Anal. 2002, 30, 613-624. (34) Passing, H.; Bablok, W. A new biometrical procedure for testing the equality of measurements

434

from two different analytical methods. Application of linear regression procedures for method

435

comparison studies in Clinical Chemistry, Part I. J. Clin. Chem. Clin. Biochem. 1983, 21, 709-720.

436

(35) Dewitte, K.; Fierens, C.; Stöckl, D.; Thienpont, L. M. Application of the Bland-Altman plot for

437

interpretation of method-comparison studies: a critical investigation of its practice. Clin. Chem.

438

2002, 48, 799-801.

439



440

Figures Legends

441 442

Figure 1: Structures of major S. marianum flavonolignans (1 - 6). 1H NMR resonances of highlighted

443

protons were used for qNMR based analyte quantitation.

444 445

Figure 2: Representative 1H-NMR spectra of selected S. marianum AC and PL extracts recorded under

446

qNMR conditions. Highlighted inserts show NMR peaks (top in sample AC03, bottom in PL01) used

447

for analyte quantitation, numbers correspond to analytes 1 – 6.

448 449

Figure 3: Representative S. marianum uHPLC-DAD chromatograms of AC and PL extracts recorded at

450

286 nm. Numbers correspond to analytes 1 – 6.

451 452

Figure 4: Passing-Bablok correlation (left-hand column) and Bland-Altman plot (right-hand column)

453

analysis of AC (top row) and PL (bottom row) samples.

454


Page 16 of 28

Page 17 of 28


Tables

Table 1: 1H-NMR signal information (methanol-d4, 600 MHz) for NMR resonances used within the qNMR experiments for silymarin flavonolignans quantitation.

Compound

δH (ppm)

multiplicity, JHH (Hz)

T1 (sec)

1

5.55

d, 6.28

1.5

2

2.89

br s, -

2.0

3

7.10

d, 2.02

2.1

4

7.08

d, 2.02

2.1

5

7.15

d, 2.08

2.2

6

7.13

d, 2.08

2.2



Page 18 of 28

Table 2: qNMR based calibration function parameters for 1-6, including regression equations, correlation coefficients (R2), linearity range, LOD and LOQ.

Linearity range

LOD

(μg/mL)

(μg/mL)

0.9986

25-2000

2.9

8.8

y = 0.1476x - 0.0016

0.9998

10-2000

3.4

10.4

3

y = 0.1882x - 0.0002

0.9999

10-2000

0.6

1.8

4

y = 0.1878x - 0.0005

0.9994

25-2000

0.5

1.6

5

y = 0.1848x - 0.0004

1.0000

25-2000

2.3

7.0

6

y = 0.1626x + 0.0046

0.9997

10-2000

1.4

4.3

2

Y (peak area) = kcA+d

R

1

y = 0.1570x + 0.0189

2

Compound

LOQ (μg/mL)


Page 19 of 28


Table 3: uHPLC-DAD based calibration function parameters for 1-6, including regression equations, correlation coefficients (R2), linearity range, LOD and LOQ.

Ret. Time Compound (min)

Linearity

2

Y (peak area) = kcA+ d

R

LOD

LOQ

range (μg/mL) (μg/mL) (μg/mL)

1

5.86

y= 2374.1x – 8.4163

0.9993

10-2000

1.0

3.0

2

6.60

y= 1886.7x – 22.4990

0.9997

25-2000

4.0

12.0

3

8.38

y= 2667.6x – 26.5870

0.9994

25-2000

6.0

19.0

4

8.74

y= 2528.0x – 5.2708

0.9992

10-2000

1.0

3.0

5

10.01

y= 2710.3x – 60.6340

0.9994

25-2000

1.0

2.0

6

10.38

y= 2598.4x – 63.9100

0.9993

25-2000

1.0

3.0



Page 20 of 28

Table 4: qNMR and uHPLC-DAD assay accuracy for compounds 2, 3, and 4. Inter-day recovery values (n = 9) expressed in percentage amount added (mean ± RSD).

Compound

NMR Recovery

Compound for

uHPLC Recovery

for NMR

(% ± RSD)

uHPLC

(% ± RSD)

Amount added (µg) AC 500.0 250.0

AC 104.9 ± 2.7

2

91.2 ± 6.7

98.9 ± 3.1 2

100.7 ± 6.8

100.0

90.7 ± 5.1

103.1 ± 6.1

500.0

98.4 ± 0.7

97.2 ± 2.1

250.0

3

100.0

106.4 ± 2.2 101.8 ± 0.6

PL 500.0 250.0

3

103.6 ± 1.5 PL

95.3 ± 2.2 2

98.4 ± 2.0

91.2 ± 5.4

101.3 ± 3.6 2

94.7 ± 4.5

100.0

103.6 ± 3.3

102.1 ± 4.2

500.0

103.1 ± 0.9

106.5 ± 3.0

250.0 100.0

4

105.5 ± 1.0

4

100.8 ± 1.9


91.8 ± 2.4 110.0 ± 0.8

Page 21 of 28


Table 5: qNMR and uHPLC-DAD assay precision for compounds 2, 3, and 4. Intra-day (n = 3 on each day) and inter-day (n = 9) precision for both types of extracts.

RSD (%) Compound

Day 1 Day 2 Day 3

Day 1-3

NMR 2 (AC)

7.7

3.4

6.6

8.6

3 (AC)

1.4

0.9

2.0

1.4

2 (PL)

3.5

3.5

5.2

4.0

4 (PL)

2.3

1.4

2.9

2.3

uHPLC 2 (AC)

3.3

6.0

7.4

5.3

3 (AC)

3.8

1.4

1.8

2.9

2 (PL)

3.3

5.2

2.2

5.9

4 (PL)

2.5

2.9

2.8

3.0



Page 22 of 28

Table 6: Quantitative qNMR results for compounds 1 – 6 in S. marianum samples AC 01-09 and PL 0110 (RSD in parenthesis, n=3).

Samples

1

2

3+4

5+6

AC (µg / 10 mg AC material) AC 01

1388.5 (2.1)

43.1 (9.6)

3718.5 (1.5)

676.7 (1.0)

AC 02

1458.7 (0.67) 41.2 (6.8)

3854.7 (0.5)

659.3 (0.7)

AC 03

1593.8 (0.9)

46.0 (5.8)

3311.2 (0.6)

735.2 (1.7)

AC 04

1577.5 (0.9)

40.2 (6.0)

3410.4 (0.4)

729.0 (1.5)

AC 05

1666.4 (1.1)

41.0 (5.8)

3583.9 (0.8)

749.8 (3.3)

AC 06

1683.2 (1.0)

37.2 (1.7)

3619.8 (0.5)

756.5 (1.6)

AC 07

1869.9 (0.9)

39.6 (6.3)

3721.6 (0.9)

843.0 (2.5)

AC 08

1703.5 (0.9)

42.6 (5.5)

3411.3 (1.2)

778.1 (4.6)

AC 09

1752.4 (0.2)

47.5 (6.1)

3284.8 (1.8)

788.5 (0.6)

PL (µg / 100 mg PL) PL 01

372.3 (4.4)

34.0 (4.3)

860.7 (2.8)

221.5 (7.1)

PL 02

106.0 (6.5)

224.3 (6.3)

221.6 (8.2)

169.5 (5.3)

PL 03

114.3 (8.9)

169.0 (9.4)

241.1 (5.9)

181.4 (1.8)

PL 04

158.6 (9.0)

249.9 (4.2)

306.9 (1.0)

207.5 (3.2)

PL 05

144.0 (8.6)

260.0 (4.9)

311.0 (2.7)

201.9 (8.7)

PL 06

128.1 (7.1)

287.0 (6.6)

211.3 (4.6)

214.0 (3.6)

PL 07

151.0 (8.9)

301.2 (5.5)

301.4 (5.2)

201.2 (5.6)

PL 08

104.0 (2.3)

217.0 (3.7)

247.8 (6.7)

182.8 (7.2)

PL 09

148.0 (6.9)

273.2 (7.5)

281.8 (3.5)

196.4 (6.7)

PL 10

137.0 (6.5)

321.7 (6.1)

280.9 (5.5)

200.3 (7.8)


Page 23 of 28


Table 7: Quantitative uHPLC-DAD results for compounds 1-6 in S. marianum samples AC 01-09 and PL 01-10 (RSD in parenthesis, n=3) Sample

1

2

AC 01

1387.2 (1.7)

43.5 (6.9)

AC 02

1421.4 (4.2)

AC 03

3

4

3+4

5

6

5+6

AC (µg / 10 mg AC material) 1463.9 (1.9) 2293.1 (1.8) 3757.0

466.2 (1.5)

172.7 (1.8)

638.9

41.7 (7.5)

1527.1 (3.8)

2379.7 (3.9)

3906.8

477.7 (4.2)

183.8 (2.8)

661.5

1576.8 (0.8)

48.3 (3.5)

1275.8 (1.4)

2120.6 (1.2)

3396.4

528.0 (0.6)

176.7 (1.8)

704.7

AC 04

1566.5 (2.8)

41.6 (4.2)

1298.0 (2.9)

2140.1(3.0)

3438.1

527.2 (2.9)

181.8 (3.6)

709.0

AC 05

1644.0 (2.5)

40.6 (6.6)

1332.0 (2.9)

2207.0 (3.0)

3539.0

550.2 (2.7)

189.1 (3.7)

739.3

AC 06

1670.1 (5.1)

38.6 (6.2)

1389.6 (5.0)

2290.8 (5.1)

3680.4

561.8 (4.8)

193.2 (4.9)

754.8

AC 07

1868.7 (7.7)

41.6 (6.7)

1400.2 (7.4)

2378.6 (7.5)

3778.8

607.5 (7.1)

214.4 (5.4)

821.9

AC 08

1719.5 (2.1)

41.3 (3.6)

1279.1 (1.9)

2174.4 (2.0)

3453.5

559.9 (1.5)

196.4 (1.8)

756.4

AC 09

1710.1 (2.2)

48.6 (3.2)

1251.9 (2.2)

2141.4 (2.2)

3393.3

557.6 (2.1)

194.7 (2.2)

752.3

PL 01

382.1 (1.44)

30.5 (9.7)

PL (µg / 100 mg plant material) 325.8 (1.3) 536.9 (1.9) 862.8

153.3 (0.8)

70.4 (0.8)

223.7

PL 02

113.5 (7.89)

228.1 (5.4)

82.2 (5.6)

135.1 (6.2)

217.3

96.6 (4.2)

77.6 (2.8)

174.1

PL 03

118.8 (6.18)

162.1 (7.9)

98.0 (7.0)

139.0 (8.3)

237.0

105.0 (3.5)

84.0 (4.5)

189.0

PL 04

158.3 (1.91)

253.3 (5.9)

108.2 (8.6)

191.2 (1.5)

299.4

116.4 (0.6)

89.2 (0.5)

205.6

PL 05

146.1 (5.75)

243.5 (7.5)

103.3 (5.0)

190.8 (4.0)

294.1

123.5 (3.0)

89.9 (2.5)

213.4

PL 06

120.9 (8.12)

290.3 (5.4)

72.7 (8.4)

129.4 (8.2)

202.1

125.1 (4.2)

96.2 (2.9)

221.3

PL 07

157.5 (9.09)

300.7 (3.7)

107.2 (7.8)

184.6 (8.0)

291.8

120.7 (7.2)

87.5 (6.5)

208.2

PL 08

102.2 (2.69)

211.0 (8.7)

116.2 (6.3)

136.7 (3.9)

252.9

101.0 (6.2)

77.3 (6.6)

178.3

PL 09

141.0 (8.44)

264.2 (5.2)

106.0 (7.4)

170.0 (8.0)

276.0

109.0 (7.6)

86.0 (8.4)

195.0

PL 10

142.8 (8.51)

316.1 (9.7)

103.2 (9.0)

169.7 (8.6)

272.9

117.1 (4.3)

84.4 (4.8)

201.5



Page 24 of 28

Figures

OH O HO

H

O

HO

OH OH O silydianin (2)

silychristin (1) H H

H O

O

CH2OH

H OCH3

O OH

H

HO

O

O

CH2OH OCH3

O

OH

OH

OH O

H

OH

OH O

silybin A (3)

silybin B (4) OH

H H HO

OCH3

H

O

OH OH O

HO

OH

HO

OCH3 CH2OH

O

O

O

O

O OH

H

OCH3 CH2OH

HO

O

O

H

OH O

OH

H

O OH

H

OH O isosilybin A (5)

isosilybin B (6)

Figure 1


OCH3 CH2OH

Page 25 of 28


3,4 2

1 5,6

7.14

7.12

7.10

7.08

5.58

5.56

5.54

5.52

2.92

2.90

2.88

2.86

AC03 IS

PL01

8

6

4

2

0

[ppm] 3,4

1

2

5,6

7.14

7.12

7.10

7.08

5.58

5.56

5.54

5.52

Figure 2


2.92

2.90

2.88

2.86


Figure 3


Page 26 of 28

Page 27 of 28


4000

(uHPLC-qNMR)/Mean of methods (%)

6

AC – samples

Analyte concentration qNMR (µg / 10 mg extract)

y = 0.99 x + 2.91; rho = 0.996

3000

2000

1000

AC - samples

2

0

Mean = - 0.1 % -2

-4

-2SD = -5.2% -6

0 0

1000

2000

3000

4000

0

1000

Analyte concentration uHPLC (µg / 10 mg extract)

2000

3000

4000

Mean of methods (µg / 10 mg extract)

(uHPLC-qNMR)/Mean of methods (%)

10

1000

PL – samples y = 1.02 x – 4.61; rho = 0.994

Analyte concentration qNMR (µg / 100 mg plant)

+2SD = 5.0%

4

800 600 400 200

PL - samples +2SD = 7.5%

5

0

Mean = - 0.3 %

-5 -2SD = -8.1% -10

0 0

200

400

600

800

1000

0

200

Analyte concentration uHPLC (µg / 100 mg plant)

Figure 4


400

600

Mean of methods (µg / 100 mg plant material)

800

1000


”TOC” graphic


Page 28 of 28

Head-to-Head Comparison of Ultra-High-Performance Liquid

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