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Comparison of yeast estrogen screening on HPTLC and in microtiter plates

The Swiss Centre for Applied Ecotoxicology (Ecotox Centre) is the Swiss competence center for applied, practice-oriented ecotoxicology. It serves as the primary knowledge hub and discussion platform for research and development, consulting and education in that area (https://www.ecotoxcentre.ch). The Ecotox Centre has expertise in developing bioassay screening tools for environmental chemical mixtures and product leachates, and therefore is interested in new ways of analyzing complex samples. The current project, supported by the Swiss Food Safety and Veterinary Office and in collaboration with the Zurich University of Applied Sciences (Dr. Andreas Schönborn), is evaluating and applying HPTLC-based methods for the biological detection and subsequent identification of chemicals in food packaging and drinking water.

Introduction

Chemicals migrating into food from packaging materials can include unknown substances. To detect potentially toxic chemicals, we employ bioassays of effects including endocrine disruption. Bioassays such as the yeast estrogen screen (YES) are typically performed in 96-well microtiter plates (ISO standard [1]). Yeast cells modified for the YES produce ß-galactosidase upon induction of the embedded human estrogen receptor. This induction is ultimately quantified by monitoring ß-galactosidase-catalyzed production of colored or fluorescent substances.

In contrast to testing whole mixtures in microtiter plates, separation on HPTLC plates with subsequent bioassay detection has the potential to reveal multiple toxic chemicals, and help identify responsible entities. The planar-YES (P-YES) has been used to screen various samples on HPTLC plates [2–4], but there has been little to no comparison to the official method. Herein, the P-YES and the microtiter YES were compared in their sensitivity to screen for endocrine active compounds related to food packaging materials.

Standard solutions

Standards are prepared in ethanol at concentrations based on range-finding tests in both the P-YES and L-YES. Nine concentrations of each test chemical are prepared in 2-fold dilution series for application onto HPTLC plates.

Sample preparation

Chemical migration from coated metal cans is simulated according to European Commission guidelines for fatty foods [5]. Briefly, cans are loaded with 95% ethanol, sealed, and incubated at 60 °C for 10 days. Duplicate samples of three different can types are prepared simultaneously. Ninety-five percent ethanol in duplicate glass beakers mimick sample handling as negative controls. Migrates are concentrated under nitrogen to be tested in the bioassays at up to 2.4 mL migrate equivalents.

Chromatogram layer

HPTLC plate silica gel 60 (Merck), 20 x 10 cm, pre-washed with methanol

Sample application

Automatic TLC Sampler (ATS 4), application as bands, 15 tracks, band length 6.0 mm, distance from left edge 20.0 mm, at least 12.0 mm track distance, for tests without development, application in three rows at 15.0, 42.5, and 70.0 mm from the bottom of the plate, for tests with development, application at 8.0 mm from the lower edge, application volume of 5.0 μL for estradiol E2 standard solution, 20.0 μL for all other standard solutions and 40.0 μL of migrate samples, application of full concentration series (nine concentrations) of E2 and two test chemicals to each plate (n = 3)

Chromatography

AMD 2 development (isocratic) up to 80 mm with chloroform – acetone – petroleum ether 11:4:5 [4], followed by drying for 5 min with vacuum

Editor’s note: Development in the ADC 2 is also possible for this application.

P-YES

The bioassay is performed by spraying 2 mL yeast cells (McDonnell) [4] at 1000 ± 200 formazine attenuation units onto HPTLC plates (Derivatizer; red nozzle, spraying level 6) followed by incubation at 30°C for 3 hours. Then, plates are sprayed with 2 mL 0.5 mg/mL 4-methylumbelliferyl-ß-D-galactopyranoside (MUG) in buffer (Derivatizer; blue nozzle, spraying level 6), and incubated for 20 min at 37 °C.

Documentation

TLC Visualizer under white light and UV 366 nm

Microtiter bioassay (L-YES)

The L-YES (YES test assisted by enzymatic digestion with lyticase) is performed according to ISO standard [1]. Briefly, yeast cells are exposed to standard chemicals and samples in 96-well microtiter plates for 18 hrs. Detection occurred by monitoring cleavage of chlorophenol-red-ß-galactopyranoside.

Data analysis

Bioassay responses (peak height of fluorescence measurements for P-YES or absorbance at 540 nm for L-YES) are normalized to the maximum response of E2 and modelled in a four-parameter log logistic function. Median and 10 percent effective doses (ED50, ED10) are predicted with 95% confidence intervals.

Results and discussion

Our goal was to compare the P-YES with the standardized L-YES as a screening method for estrogenic effects of substances from food packaging. Towards that aim, we determined effect concentrations for 20 chemicals relevant to plastic packaging and screened example migrates of food packaging with both assays. Our interest was in the technical difference of the bioassays in microtiter plates on HPTLC plates. Therefore, we determined effective doses thoroughly without performing chromatography. This allowed us to eliminate chromatography as a factor in any differences we would see between the assays and increase the sample capacity on the plates. Separately, we also examined the effect of chromatography on model chemicals E2 and bisphenol A (BPA).

Dose responses of E2 and BPA are shown for the P-YES (without development) and L-YES. The doses producing 10% of the maximal E2 response (ED10) interpolated from the dose response curves were lower for the P-YES than the L-YES. This demonstrates greater sensitivity of the P-YES. We also examined assay parameters such as strain of yeast and indicator solution [6]. They were not able to explain the difference in sensitivity.

Thirteen of 20 chemicals were active at levels reaching at least 10% of the maximum E2 response. The ED10 of most of these chemicals were lower in the P-YES than the L-YES. This demonstrates that the P-YES is generally more sensitive than the L-YES, although that trend started to break down as potency of the chemicals decreases (higher EDs). The potency of each chemical relative to E2 is within a factor of two of its corresponding relative potency in the L-YES.

The P-YES is stable over time. We were able to obtain the same ED50 for E2 after one year.We also evaluated the effect of chromatographic development as shown with an asterisk. With tight 95% confidence intervals, the ED50 is different than without development on the same day. However, both with and without development were within historical variability of the P-YES without development. The historical range is consistently lower than for the L-YES (median L-YES ED50 > 1 x 10-14).

An example migrate of a metal can tested in the P-YES is shown below. This migrate had no estrogenic effect in the L-YES but did result in reduced cell growth. An estrogenic band of (an) unknown substance(s) in the migrate was revealed by testing with the P-YES. Spiked chemicals were also detectable in the migrate. BPA was detected at a concentration of 27 ng (1.2 x 10-10 mol), which is lower than would be required to detect BPA at its specific migration limit (2 μg, 8 x 10-9 mol/band) given the sample preparation used in this study.

This study showed that

  • P-YES is more sensitive than L-YES
  • P-YES results can be repeated up to one year later
  • P-YES with chromatographic development can reveal substances hidden in L-YES
  • P-YES and L-YES were sensitive enough to detect BPA within the European Commission specific migration limit [5]

  • TLC chromatograms at UV 254 nm of the crude product separated with different mobile phases

    01

    Dose response curves of E2 and BPA: P-YES (without development) measured in fluorescence at 366 nm illumination and L-YES measured in absorbance at 540 nm; shaded regions exhibit the modelled 95% confidence intervals; horizontal dotted lines show the 10, 50, and 100% effect levels; vertical dotted lines indicate the corresponding ED

  • HPTLC chromatograms at UV 254 nm of the crude product (10 g/L, 1 μL versus 100 g/L,15 μL) and mass spectra (left) versus 1H NMR spectra of isomeres (right)

    02

    The ED10 of chemicals that activated the estrogen receptor. Error bars (95% confidence interval of predicted value, dose response modeling based on triplicate plates) are often obscured by the data markers; replicate is a band in P-YES, and a microtiter well in L-YES. 2,2’-dihydroxy-4-methoxybenzophenone and benzylbutylphthalate produced a fluorescence response in P-YES but did not reach a 10% effect level. Reproduced with modifications from [6] (https://creativecommons.org/licenses/by/4.0/legalcode)

  • Online monitoring of the purification process by LC-UV (254 nm, left) versus offline by HPTLC-UV (individual fractions at 254 nm, right)

    03

    Repeatability of the median effective dose (ED50) of the reference chemical E2, over time in P-YES without development. Experiment days are shown that were performed within one month of each other, and up to a year later. Asterisk (*) indicates test with development (n=3). Reproduced from [6] (https://creativecommons.org/licenses/by/4.0/legalcode)

  • Online monitoring of the purification process by LC-UV (254 nm, left) versus offline by HPTLC-UV (individual fractions at 254 nm, right)

    04

    Detection of estrogen-active compounds in a migrate of a food contact material. Retention factor (RF) shown on left axis. Application position and the solvent front indicated by lower and upper dashed lines, respectively. Track 1: mixture of E2 (1 pg), 17∝-ethinylestradiol (1 pg), and estrone (10 pg) with increasing RF values, track 2: migrate of metal can, track 3: spiked migrate of metal can, track 4: spiked control migrate; samples on track 3 and 4 spiked with BPA (27 ng), benzophenone- 3 (140 ng), and estrone (0.2 ng); Zones marked with (a) native fluorescence of chemicals (i.e. not estrogenicity), (b) native estrogenicity, (c) co-eluting spiked chemicals estrone and benzophenone-3, (d) BPA.

Literature

[1] ISO. 19040-1. Water quality — Determination of the estrogenic potential of water and waste water — Part 1: Yeast estrogen screen (Saccharomyces cerevisiae), Geneva, Switzerland (2018)
[2] I. Klingelhofer, G.E. Morlock. Anal Chem (2015) 87(21):11098–104
[3] S. Buchinger et al. Anal Chem (2013) 85(15):7248-56
[4] A. Schoenborn et al. J Chromatogr A (2017) 1530:185-91
[5] European Commission. Commission Regulation (EU) No 10/2011 on plastic materials and articles intended to come into contact with food, Official Journal of the European Union (2011)
[6] A. J. Bergmann et al. Anal Bioanal Chem (2020) 412: 4527–4536

Further information on request from the authors.

Contact:

Dr. Alan Bergmann, Swiss Centre for Applied Ecotoxicology, Eawag, Überlandstrasse 133, 8600 Dübendorf, Switzerland, alanjames.bergmann@oekotoxzentrum.ch

mentioned products

The following products were used in this case study

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Characterization of E472 food emulsifiers by HPTLC fingerprints

The development of straightforward and simple HPTLC methods for the characterization and determination of the food emulsifiers E471 and E472 in dairy products is one of the research topics of Dr. Claudia Oellig at the Department of Food Chemistry and Analytical Chemistry (170a); directed by Prof. Dr. Michael Granvogl (Institute of Food Chemistry, University of Hohenheim, Stuttgart, Germany). This study presents a method for the characterization of E472 emulsifiers by HPTLC fingerprints and the identification of separated constituents by mass spectrometry.

Introduction

Esters of fruit acids as well as mono- and diacylglycerols (MAG and DAG) are often used as additives in foodstuff to adjust its techno-functional properties. Due to their surface-active properties, they are listed as emulsifiers, more precisely as E472 food emulsifiers. They are usually added to food products to regulate stability and viscosity, and, for example in dairy products, to adjust foaming and emulsion stability. Regulation (EC) No 1333/2008 approves fruit acid esters of MAG and DAG as food additives and categorizes them into six groups based on the respective acids [1]. The main categories comprise acetic acid esters (ACETEM, E472a), lactic acid esters (LACTEM, E472b), citric acid esters (CITREM, E472c), and mono- and diacetyl tartaric acid esters (DATEM, E472e). These emulsifiers are very complex and widely varying mixtures of fruit acid esters of MAG and DAG, along with MAG, DAG, and further constituents. Because techno-functionality strongly depends on the emulsifier’s composition, reliable and easy to perform analytical methods are of great interest to control the product quality. In the presented characterization of E472, the cost-effective and efficient HPTLC provides fast results for many samples in parallel, wherein the fingerprint technique allows immediate visual evaluation of the samples [2].

The characterization of E472 food emulsifiers through HPTLC fingerprints was successfully developed and applied to several samples of the categories ACETEM (E472a), LACTEM (E472b), CITREM (E472c), and DATEM (E472e). After dissolving in tert-butyl methyl ether, emulsifiers were directly applied onto normal phase HPTLC silica gel and separated with a two-fold development. Derivatization with primuline allowed for visualization and easy comparison of fluorescent lipid classes under UV 366 nm. Coupling to mass spectrometry offers fast identification of prominent constituents of the complex emulsifier mixtures.

Sample and standard solutions

Samples of E472 emulsifiers (ACETEM, LACTEM, CITREM, and DATEM) are dissolved in tert-butyl methyl ether (tBME) at a concentration of 1 mg/mL. A standard-mix solution containing mono-, di-, tristearin, and stearic acid (MSt, DSt, TSt, and SA) is prepared at 0.125 μg/μL, respectively.

Chromatogram layer

HPTLC silica gel 60 F254s MS plates (Merck), 20 x 10 cm

Sample application

With the Automatic TLC Sampler (ATS 4) as 6.0 mm bands, 18 tracks, track distance 10.0 mm, distance from the left plate edge 15.0 mm, distance from the lower plate edge 8.0 mm, application volume 10.0 μL for samples and standard for visual characterization by fingerprint and 75.0 μL for samples for identification by mass spectrometry, drying in a fume hood for 10 m

Chromatography

In the Automatic Developing Chamber (ADC 2) with chloroform – methanol – water – formic acid 670:80:19:2 for the first development, migration distance 50 mm, drying time 10 min and with n-heptane – diethyl ether – formic acid 55:45:1 for the second development, migration distance 80 mm, drying time 5 min, plate activation for 5min at 33% using a saturated solution of magnesium chloride before each of the developments

Post-chromatographic derivatization

The plate is immersed into a solution of primuline (0.05% in acetone – water 4:1) with the Chromatogram Immersion Device (immersion speed 1 cm/s, immersion time 3 s) and dried for 5 min in a stream of warm air.

Documentation

With TLC Visualizer under UV 366 nm

Mass spectrometry

Zones are eluted with the TLC–MS Interface (oval elution head) at a flow rate of 0.2 mL/min with methanol – 0.1% formic acid 9:1 for 40 s into a single quadrupole mass spectrometer equipped with an electrospray ionization interface (positive ionization, scan mode).

Results and discussion

The visual characterization and comparison of E472 food emulsifiers were performed by the straightforward HPTLC fingerprint technique. Food emulsifiers were simply dissolved in tBME and directly used for HPTLC. A two-fold development on HPTLC silica gel with chloroform – methanol – water – formic acid 670:80:19:2 for the first development and n-heptane – diethyl ether – formic acid 55:45:1 for the second development offered suitable separation of the constituents for the investigated E472 categories. The fingerprint under UV 366 nm directly visualized differences between the categories and the complexity of the classes comprising numerous components. For the compounds of the lipid classes MSt, 1,2-DSt, 1,3-DSt, SA, and TSt, hRF values of 35, 62, 65, 74, and 90 were obtained. CITREM showed citric acid esters in the hRF range 0–35, ACETEM acetic acid esters in the hRF range 60–74, LACTEM lactic acid esters in the hRF range 35–62, and DATEM different fruit acid esters in the ranges 0–35 and 60–74. Thus, the fingerprint allows to distinguish between emulsifier categories and to determine variations within the same category of E472.

Direct hyphenation with mass spectrometry provided mass specific information and offered the identification of individual components. Thus, more detailed information on the emulsifier’s composition was obtained. Hence, the coupling to mass spectrometry offered the identification of prominent zones (components) of the categories and of zones (components) that differ in the visual fingerprint between batches or formulations. In addition, deviations in the emulsifier’s composition that might occur during storage can be identified.

In summary, the fingerprint technique is a fast tool to determine the emulsifier’s composition, and to relate differences in the composition to differences in the detected techno-functional properties and the dosage of emulsifiers in the product. In addition, this elegantmethod can be used for simple and efficient quality control of incoming commercial emulsifiers, for example in the dairy industry.


  • HPTLC fingerprint of E472 emulsifiers under UV 366 nm

    01

    HPTLC fingerprint of E472 emulsifiers under UV 366 nm. Different batches (1–3) of (A) CITREM, (B) ACETEM, (C) LACTEM, and (D) DATEM with an amount of 10 μg emulsifier/zone and a (St) standard-mix containing MSt, 1,2-DSt, 1,3-DSt, SA, and TSt (1.25 μg/zone) for comparison.

  • Identification of constituents of E472 emulsifiers by HPTLC–MS

    02

    Identification of constituents of E472 emulsifiers by HPTLC–MS. (A) HPTLC separation of an ACETEM emulsifier (75 μg/zone) and (B) corresponding mass spectra extracted from the total ion current chronogram of the zones a and b after coupling toMS with the TLC–MS Interface and ESI+–MS analysis. Modified from [2].

Literature

[1] The European Parliament and the Council of the European Union, Regulation (EC)No 1333/2008 of the European Parliament and of the Council of 16 December 2008 on food additives, 2008.
[2] Oellig et al., J Chromatogr A (2020) 460874.

Further information on request from the authors.

Contact: Dr. Claudia Oellig, Department of Food Chemistry and Analytical Chemistry (170a), Institute of Food Chemistry, University of Hohenheim, 70599 Stuttgart, Germany, claudia.oellig[at]uni-hohenheim.de

mentioned products

The following products were used in this case study

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Screening for natural cosmetic preservatives by HPTLC-EDA

The Métabolome et Valorisation de la Biodiversité Végétale (MVBV) team of the Institut de Chimie de Nice (Université Côte d’Azur, France) is directed by Prof. Xavier Fernandez who works in the field of natural products analysis. Together with BotaniCert, an analytical laboratory directed by Dr. Francis Hadji-Minaglou and specialized in the analysis and authentication of plant material, the MVBV team has been working on a collaborative project to find new natural preservatives in Mediterranean plant species for the cosmetic industry.

Introduction

Plant extracts offer a large source of bioactive molecules. Most often, the screening for bioactivity is performed with the dilution method in 96 well plates. The major disadvantage of this method is the lack of information on the chemical class and number of active constituents of the extract. HPTLC is a widely employed technique for testing of natural products, e.g. identification and test for adulteration. Since the last decade, a growing interest in HPTLC hyphenated with bioassays (HPTLC-EDA) has been noted [1].

For a simplified identification of active ingredients in plant extracts we have chosen HPTLC bioautography. Due to the combination of chromatographic separation and effect-directed analyses, HPTLC allows to directly localize active ingredients, avoiding a time-consuming bio-guided fractionation. Up to 15 extracts can be analyzed at the same time. In our study, Aspergillus brasiliensis has been selected to screen for antifungal active ingredients. Positive compounds can be promising candidates as natural preservatives for cosmetic products.

Standard solutions

Glycyrrhizic acid, quercetin and rutin (0.5 mg/mL in methanol)

Sample preparation

Dry plant material is grounded and macerated in ethanol 75% (plant volume/solvent volume 1:10) for 2 h at room temperature. After centrifugation the supernatants are used as test solutions.

Chromatogram layer

HPTLC plate silica gel 60 F254 (Merck), 20 x 10 cm

Sample application

Automatic TLC Sampler (ATS 4), application as bands, 15 tracks, band length 8.0 mm, distance from left edge 20.0 mm, distance from lower edge 8.0 mm, application volume 20.0 μL for samples and 2.0 μL for standards

Chromatography

In the ADC 2 with chamber saturation with filter paper 20 min and after activation at 33% relative humidity for 10 min using a saturated solution of magnesium chloride, development with ethyl acetate – water – acetic acid – formic acid 100: 26:11:11 to the migration distance of 70 mm (from the lower edge), drying for 5 min

Post-chromatographic derivatization

    1. The plate is immersed into anisaldehyde-sulfuric acid reagent (10 mL sulfuric acid is added to 170 mL methanol, 20 mL acetic acid and then 1 mL anisaldehyde is added to that solution) using the Chromatogram Immersion Device (immersion speed 6cm/s, immersion time 0s), dried for 30s with cold air, and heating at 100 °C for 5 min using the TLC Plate Heater.
    2. The plate is heated for 3min at 100°C using the TLC Plate Heater then immersed in Natural product (NP) reagent (1 g diphenylborinic acid aminoethylester in 200 mL ethyl acetate) and in PEG solution (10 g polyethylene glycol 400 in 200mL dichloromethane) using the Chromatogram Immersion Device (immersion speed 6cm/s, immersion time 0 s).

    Editor’s Note: in many cases a sequential derivatization with first NP reagent and then with anisaldehyde reagent on the same plate is possible. The fluorescence enhancer (PEG) is then not used.

    Bioautography with Aspergillus brasiliensis

    The plate is conditioned with the culture broth (Sabouraud), then manually sprayed with a suspension of spores of A. brasiliensis at 105 spores/mL, and incubated at room temperature (25°C) 48 h to 72 h.

    Documentation

    TLC Visualizer under UV 254 nm, UV 366 nm, and white light

    Results and discussion

    The antifungal capacity of five Mediterranean plants (Santolina chamaecyparissus L., Asteraceae, flowering top; Cistus albidus L., Cistaceae, branches; Ruta chalepensis L., Rutaceae, top; Coronilla emerus L., Fabaceae, flowering top; Cupressus sempervirens L. Cupressaceae, branches) was studied using A. brasiliensis to discover new natural preservatives for the cosmetic industry. First, the raw extracts were screened following the dilution method in 96 well plates.

    Afterwards, in order to determine the family of compounds responsible for the antifungal activity, HPTLC bioautography was performed on the extracts.

    Except for C. sempervirens, the tested plants showed antifungal activity on the plate. Positive zones are located on top of the plates where unpolar compounds migrate. Terpenoids (purple zones after derivatization with anisaldehyde) and unpolar polyphenols (greenish-yellow zones after derivatization with NP-PEG) seem to bear the antifungal activity. C. sempervirens L. has no antifungal property as shown on the dilution assay.

    Further investigations [2] on Santolina chamaecyparissus L. extract led to the isolation and NMR identification of the active compound spiroketalenol ((5S,7Z)-7-(hexa-2,4-diyn-1-ylidene)-1,6-dioxaspiro [4.4]nona-2,8-dien-4-yl acetate). Therefore, Santolina extract seems to be a good candidate as a new natural preservative for cosmetics.


    • Antifungal activity against A. brasiliensis: +++: antifungal activity 90–100%; ++: 70–90%; +: 60–70%; ~: 40–60%; –: ≤ 40%

      01

      Antifungal activity against A. brasiliensis: +++: antifungal activity 90–100%; ++: 70–90%; +: 60–70%; ~: 40–60%; –: ≤ 40%

    • HPTLC chromatograms under white light after derivatization with anisaldehyde-sulfuric acid reagent (A, *glycyrrhizic acid, track1), under UV 366 nm after derivatization with NP-PEG (B, *quercetin, track1, *rutin, track3), and under white light after incubation with A. brasiliensis (C)

      02

      HPTLC chromatograms under white light after derivatization with anisaldehyde-sulfuric acid reagent (A, *glycyrrhizic acid, track 1), under UV 366 nm after derivatization with NP-PEG (B, *quercetin, track 1, *rutin, track 3), and under white light after incubation with A. brasiliensis (C)

    Literature

    [1] G. Morlock et al. J Chromatogr A 1217 (2010) 6600
    [2] A. Kerdudo et al. C R Chimie 19 (2016) 1077

    Further information on request from the authors.

    Contact: Prof. Xavier Fernandez, MVBV, Institut de Chimie de Nice, 28 avenue Valrose, 06108 Nice Cedex 2, France, xavier.fernandez[at]univ-cotedazur.fr

    mentioned products

    The following products were used in this case study

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    Evolution of plant defense compounds in the plantlitter continuum

    The subject of this article brings together two researchers who have a common interest in specialized metabolites involved in plant chemical defenses. Dr. Thomas Michel is analytical chemist at the Institute of Chemistry of Nice (Université Côte d’Azur, Nice, France) where he develops analytical tools for chemical ecology and for discovery of bioactive compounds from plant biodiversity. He employs HPTLC for analytical goals and TLC for preparative separations. Dr. Anne- Violette Lavoir, ecologist at the Institute Sophia Agrobiotech (INRAe, Université Côte d’Azur, Antibes, France) works on the chemical interaction between plants and insects (community ecology, chemical ecology). In this work, the authors employed HPTLC for secondary metabolites screening of different plant extracts in an ecological context.

    Introduction

    Ecosystems are complex systems, forming a vast network in which different actors – the living beings – interact with each other. The main trophic network is the “green world” [1,2], in which the chlorophyllous plants are the primary producers. They bring organic matter and energy into the network through the fixation of mineral matter by photosynthesis. In this green world, fresh plants are the basis as they are consumed by herbivores, which will in turn be consumed by predators. The “brown world” [1,2] is based on the litter, mostly formed from plant parts (e.g. leaves, bark, stems) that dry out and fall to the ground (inert organic matter). The litter is consumed by detritus feeders (or decomposers), which will then also be consumed by their predators. As litter are previously fresh leaves, the basis of the green and brown world is linked through the so-called plantlitter continuum.

    A change in plant or litter chemistry would impact not only their consumers, but all the trophic levels above. For instance, plants could modify their chemical defenses such as secondary metabolites, impacting all their consumers. Because of the plant-litter continuum, any modification in the chemistry of the fresh plants will in turn modify the chemistry of the litter and consequentially the brown trophic network.

    In this context, we studied the variation in content of secondary metabolites at five stages of the plant-litter continuum (young plants, mature plants, fresh litter, old litter and decomposer feces), from four plant species (Bromus erectus, Pilosella officinarum, Potentilla grandiflora and Sanguisorba minor). Each stage and plant species were sampled by our collaborators on grasslands of Les Causses (South of France) and each grassland was either fertilized or not. Our main objective was to compare the global chemistry of the four plant species throughout the plant-litter continuum and to see if the fertilization may modify such pattern.

    The great diversity of phytochemicals and their small quantities in plant species, and the number of samples to investigate led us to set up a large-scale HPTLC analysis. HPTLC was chosen because it offers numerous advantages such as versatility, capacity to run several samples in parallel and low solvent consumption. Additionally, detection using various derivatization reactions can provide crucial information about the nature of chemical substances present in samples. Furthermore, sample preparation in HPTLC is simple while other chromatographic techniques (e.g. GC and HPLC) usually require a time-consuming and expensive sample preparation prior to the analyses. Therefore, HPTLC is suitable as a high-throughput fingerprinting method in an ecological context.

    Standard solutions

    Quercetin, asiaticoside and betuline are dissolved in methanol at different concentration levels.

    Sample preparation

    20mg of ground plant are extracted in an ultrasonic bath with 1.6 mL ethanol – water 7:3. Extracts are then filtered and stored at –20 °C before HPTLC analysis.

    Chromatogram layer

    HPTLC plates silica gel 60 F254 (Merck), 20 x10 cm

    Sample application

    Automatic TLC Sampler (ATS 4), application as bands, 16 tracks, band length 8.0 mm, distance from left edge 15.0 mm, distance from lower edge 8.0 mm, application volume 2.0 μL for sample solutions and 2.0 μL for standard solutions

    Chromatography

    In the Automatic Developing Chamber (ADC 2) with ethyl acetate – formic acid – acetic acid – water 100:11:11:26 (polyphenols), chloroform – methanol – water 5:4:1 (glycosylated terpenoids), or hexane – ethyl acetate – water 4:1:0.5 (hydrophobic terpenoids) after chamber saturation (filter paper) and activation at 33% relative humidity for 10 min using a saturated solution of magnesium chloride, migration distance of 70 mm (from the lower edge), drying for 5 min

    Post-chromatographic derivatization

    All plates are immersed into specific reagents for 2 s using the Chromatogram Immersion Device. For phenolic compounds, the plate is immersed into NP reagent (1.25 g diphenyl borinic acid ethylamino ester in 250 mL of ethyl acetate) and then into PEG reagent (10% polyethylene glycol 400 in dichloromethane). For terpenoids, the plate is immersed into anisaldehyde-sulfuric acid reagent (0.5 mL anisaldehyde, 10 mL glacial acetic acid, 85 mL methanol, 5 mL sulfuric acid) and heated on the TLC Plate Heater at 105 °C for 5 min.

    Documentation

    TLC Visualizer under UV 254 nm, UV 366 nm, and white light

    Densitometry

    TLC Scanner 4 and winCATS, slit dimension 5.00 mm x 0.20 mm, scanning speed 50 mm/s, spectra recording from 190 to 450 nm, measurement after derivatization in fluorescence mode at 366/>400 nm with Hg lamp (polyphenols), in absorbance mode at 400 nm (polar terpenoids), and at 600 nm (apolar terpenoids) with tungsten lamp, evaluation via peak area and calibration curves of specific compounds (i.e. quercetin, asiaticoside, betuline)

    Statistical analyses

    Data are statistically analyzed by a Scheirer-Ray- Hare test using R software.

    Results and discussion

    To analyze and compare the diversity of the phytochemicals (i.e. polyphenols, terpenes, alkaloids) of the four plant species, the first step was to develop a suitable analytical workflow and to optimize the chromatographic conditions for separation of the different compound families.

    Quantitative estimation of each class of compounds was further performed by scanning densitometry. A typical HPTLC densitogram obtained at 366 nm after derivatization with NP reagent is shown below. The area under each peak was determined and compared to the calibration curves of specific compounds (e.g. quercetin for polyphenols). Results are then expressed in mg standard/g dry matter.

    For example, relative quantity of polyphenols (mg of quercetin/g dry mass) in Sanguisorba minor samples significantly decreases between the green and the brown world (p<0.0001). No significant differences were observed between samples from the same world (e.g. young and mature plant). On the contrary, the effect of fertilization is significant for both green and brown worlds (p < 0.0001). Polyphenols are more present in fertilized samples than in unfertilized ones.

    Using this HPTLC strategy, we were able to estimate the relative quantity of polyphenols (i.e. mg quercetin/g dry matter) and terpenoids (e.g. mg betulin/g dry matter) according to the plant species, to the stages in the plant-litter continuum and to the fertilization status. Furthermore, this strategy was also applied to tannins, terpenoids, and alkaloids (data not shown), giving us the possibility of a complete screening of secondary metabolites in all plant species studied. The complete results enable the determination of the evolution of secondary metabolites in the fresh plant-decomposed litter continuum:

    • There are more secondary metabolites in the green world compared to the brown world (i.e. in fresh and mature plants compared to litter), except for the apolar terpenes that have shown an opposite pattern.
    • There are more secondary metabolites in the mature plants compared to the youngest plants inside the green world.
    • Plant species show diverse metabolic strategies: Bromus erectus has significantly less secondary metabolites compared to other species.
    • The concentration of secondarymetabolites in plants of the same species is higher on the non-fertilized site.

    To conclude, this HPTLC strategy allowed us to highlight modifications of the plant secondary metabolites throughout the plant-litter food web but also to observe a link between the green and the brown world. Interestingly, even though plants show various strategies, we always observe a decrease of concentrations in the brown world. As secondary metabolites are mainly defense compounds, we hypothesize a decrease of such compounds in the leaf before they fall in order to recycle such compounds and/or to avoid a negative impact on detritus feeders which are consuming the litter. Analyzing the plant chemistry throughout the plant-litter continuum helps us to disentangle the complexity and the link structuring the green and brown worlds.


    • Analytical workflow used to extract, separate and quantify secondary metabolites of different plant species

      01

      Analytical workflow used to extract, separate and quantify secondary metabolites of different plant species

    • Typical HPTLC densitogramof samples obtained at 366/>400 nm after derivatization with NP reagent”>






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      Typical HPTLC densitogram of samples obtained at 366/>400 nm after derivatization with NP reagent

  1. Typical HPTLC fingerprints of the four analyzed plant species

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    Typical HPTLC fingerprints of the four analyzed plant species (above- and belowground samples) under UV 366 nm after derivatization with NP/PEG reagent and under white light after derivatization with anisaldehydesulfuric acid reagent (POS-1 = Potentilla grandiflora below, POA-1 Potentilla grandiflora above, PSS-1 = Pilosella officinarum below, PSA-1 = Pilosella officinarum above, BES-1 = Bromus erectus below, BEA-1 = Bromus erectus above, PTS-1: Sanguisorba minor below, PTA-1: Sanguisorba minor above)

  2. Relative quantity of polyphenols in mg of quercetin/g dry mass in the leaflitter continuum of Sanguisorba minor

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    Relative quantity of polyphenols in mg of quercetin/g dry mass in the leaflitter continuum of Sanguisorba minor. 1-young plant; 2-mature plant; 3-fresh litter; 4-decomposed litter; 5-faeces; green world gathers stages 1 and 2, brown world gathers stages 3 and 4; F: fertilized; NF: non-fertilized

  3. Literature

    [1] Wardle et al. Science (2004), 304, 1629
    [2] Wolkovich et al. Ecology (2014), 95–12

    Further information on request from the authors.

    Contact: Dr. Thomas Michel, Université Côte d’Azur, CNRS, Institut de Chimie de Nice UMR 7272, 06108 Nice, France, thomas.michel[at]univ-cotedazur.fr

    Acknowledgement: The authors acknowledge all the partners involved in the EC2CO COMODO project funded by CNRS (supervision: S. Coq), especially Florian Goettelmann and Louisa Saghir for their respective works.

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    Quantification of tetrahydrocannabinol in Cannabis sativa

    Introduction

    Cannabis sativa, the hemp plant, is one of the oldest crops of mankind and an important resource for the production of textile fibers, food products and medical drugs. Cannabinoids are the substances of medical interest in Cannabis, such as the analgesic cannabidiol (CBD). The cannabinoid tetrahydrocannabinol (THC), however, has an intoxicating effect, for which Cannabis is used as a narcotic drug. In the USA and Switzerland, industrial hemp may not contain more than 1% of THC. In Europe the limit is set to 0.2%. Based on the different intended usage, numerous genetic strains of Cannabis sativa have been developed, in which the content of cannabinoids varies greatly. This leads to different analytical tasks [1,2]. CBD, THC and cannabinol (CBN) are the three best studied cannabinoids and have been chosen for the System Suitability Test (SST). CBD and THC contents are used for classification in three main types: THC-rich (type 1), THC content similar to CBD (type 2), CBD-rich (type 3) [2]. CBN is produced during aging and is therefore regarded as a quality feature.

    HPTLC is a fast and simple solution for the analysis of Cannabis, especially in regard to different analytical goals. In a limit test numerous samples can be assessed in parallel as to their classification as narcotic drug. Detection and a precise assay of individual cannabinoids is also possible.

    Standard solutions

    Standards individually in methanol (10 and 100 ng/μL), for the SST a mixture of CBD, THC, and CBN in methanol (each 100 ng/μL).

    Sample preparation

    500 mg of dried, powdered Cannabis sativa were mixed with 5 mL of methanol – n-hexane 9:1 and sonicated for 15 min. The mixture was centrifuged for 5 min and the supernatant was used for analysis. For the quantitative assay the extracts were diluted 1:10 with methanol – n-hexane.

    Chromatogram layer

    HPTLC plates silica gel 60 F254 (Merck), 20 × 10 cm

    Sample application

    Bandwise with Automatic TLC Sampler (ATS 4), 15 tracks, band length 8 mm, distance from left edge 20 mm, distance from lower edge 8 mm, application volumes 2.0–10.0 μL

    Chromatography

    In the Automatic Developing Chamber (ADC 2) with chamber saturation (with filter paper) for 20 min and conditioning of the plate at 33% relative humidity for 10 min (using a saturated solution of magnesium chloride), development with n-heptane – diethyl ether – formic acid 75:25:0.3, migration distance 70 mm from lower plate edge, drying for 5 min

    Densitometry

    TLC Scanner 4 with visionCATS, absorption measurement at 210 nm prior to derivatization (for cannabinoid acids 285 nm [2])

    Postchromatographic derivatization

    Spraying with Derivatizer (green nozzle, level 3) with Fast Blue salt B reagent (250 mg of o-dianisidine bis(diazotized) zinc double salt dissolved in 10 mL of water, 25 mL of methanol and 15 mL of dichloromethane added)

    Documentation

    With TLC Visualizer under white light after derivatization

    Results and discussion

    HPTLC is the method of choice for the prompt analysis of numerous Cannabis samples. The SST and 2 μL of each undiluted sample extract are applied. The identification is based on the HPTLC chromatogram. After derivatization with Fast Blue salt B reagent the cannabinoids are detected as colored zones.

    For the screening of THC-free samples the limit test can be used. The sample extracts (diluted 1:10) and as standard solution, the limit amount of THC is applied at least in duplicate. The limit of 0.2% required by the EU is easily detected with or without derivatization. The standard deviation of the assay prior to derivatization is in this example 1.5% and after derivatization with the Derivatizer only 2.1%.

    For a highly precise assay we recommend multilevel calibration. Also in this case good quantitative results prior to and after derivatization with the Derivatizer can be achieved. Prior to derivatization the standard deviation was 1.1% and after derivatization 2.8%. As the limit of detection was 10 ng/ zone for both modes, the derivatization step is only advantageous for image evaluation. The following example shows the quantification of highly potent THC-containing samples with no or hardly any CBD. The extracts were applied 1:10 diluted to evaluate the samples in the linear working range.

    The described method is suitable for the qualitative and quantitative determination of cannabinoids in Cannabis sativa. Additionally, the easy, reproducible and cost efficient analysis of intermediate and finished products in the food and drug industry is possible [2]. Depending on the analytical goal, an optimization of the mobile phase or separation on RP-18 phase might be necessary for non baseline separated cannabinoids [2]. For the unequivocal detection of cannabinoid zones mass spectrometry can be used [1,2].


    • HPTLC chromatogram after derivatization with Fast Blue salt B reagent under white light, track 1: SST (CBN, THC and CBD, with increasing hRF value), tracks 2–7: different Cannabis samples

      01

      HPTLC chromatogram after derivatization with Fast Blue salt B reagent under white light, track 1: SST (CBN, THC and CBD, with increasing hRF value), tracks 2–7: different Cannabis samples

    • Limit test of a sample (duplicate, red circle) which exceeds the EU limit (≥ 0.2% THC), absorption measurement at 210 nm, evaluation via peak area with linear regression (linear-1); single level calibration

      02

      Limit test of a sample (duplicate, red circle) which exceeds the EU limit (≥ 0.2% THC), absorption measurement at 210 nm, evaluation via peak area with linear regression (linear-1); single level calibration

    • Quantification of THC in 2 Cannabis samples (triplicates, green circles) by a 5-level calibration (left), evaluation via peak area with linear regression (linear-2); densitograms (right) after absorption measurement at 210 nm

      03

      Quantification of THC in 2 Cannabis samples (triplicates, green circles) by a 5-level calibration (left), evaluation via peak area with linear regression (linear-2); densitograms (right) after absorption measurement at 210 nm

    Literature

    [1] CAMAG Application Note A-98.1: Confirming the presence of cannabinoids in Cannabis sativa by HPTLC-MS, www.camag.com
    [2] CAMAG Application Note A-108.1: Identification and quantification of different cannabinoids in Cannabis sativawww.camag.com

    Further information on request from the authors.

    Contact: Dr. Melanie Broszat, CAMAG, Sonnenmattstr. 11, 4132 Muttenz, Switzerland, melanie.broszat[at]camag.com

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