Development of an Analytical Method for Analyzing Pyrrolizidine

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Development of an analytical method for analyzing pyrrolizidine alkaloids in different groups of foods by UPLC-MS/MS Stephen Wai Cheung Chung, and Chi-ho LAM J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b06118 • Publication Date (Web): 27 Feb 2018 Downloaded from http://pubs.acs.org on February 27, 2018

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Journal of Agricultural and Food Chemistry

Development of an analytical method for analyzing pyrrolizidine alkaloids in different groups of food by UPLC-MS/MS

Stephen W.C. Chung1, Chi-Ho Lam

Food Research Laboratory, Centre for Food Safety, Food and Environmental Hygiene Department, 4/F Public Health Laboratory Centre, 382 Nam Cheong Street, Hong Kong

1 Author to whom correspondence should be addressed. e-mail: [email protected]

ACS Paragon Plus Environment


Abstract Suspected non-targeted, without analytical reference standard, pyrrolizidine alkaloids (PAs) were observed and interfered the determination of targeted PAs in complex food matrices, especially for spices samples. Selectivity and applicability of multiple reaction monitoring (MRM) transitions, multistage fragmentation (MS3) and MRM with differential ion mobility spectrometry (DMS) for eliminating false positive identifications were evaluated. Afterwards, a selective and sensitive LC-MS/MS method for determination of 15 PAs and 13 PA N-oxides in foodstuffs was developed. The sample preparation and cleanup are applicable to a wide range of foodstuffs including cereal products, dairy products, meat, eggs, honey, tea infusion and spices. Freezing out raw extract and water/acetonitrile washing step in solid phase extraction was found to be efficiently removing complex matrices. Method was validated at 0.05 µg kg-1 for general food and 0.5 µg kg-1 for spices, with reference to Eurachem Guide. Estimated limit of quantifications s of different PAs were ranged from 0.010 to 0.087 µg kg-1 for general food and 0.04 to 0.76 µg kg-1 for spices. Isotopically labelled PAs were used as internal standards to correct the variation of PAs/PANs performance in different food commodities. Matrix effects, were observed in complex food matrices, but could be reduced by solvent dilution. Recoveries of PAs and PA N-oxides were all felt within 50-120 %.


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Keywords: pyrrolizidine

alkaloid

(PA);

pyrrolizidine

alkaloid

N-oxide

(PAN);

liquid

chromatography-mass spectrometry (LC-MS); multiple reaction monitoring (MRM); multistage fragmentation (MS3); differential ion mobility spectrometry (DMS)



Page 4 of 36

Introduction Pyrrolizidine alkaloids (PAs) are a group of toxic compounds that are produced by plants all over the world.

PAs are reported as the most widely distributed natural toxins. Cases of

human toxicity include the use of toxic plant species as herbal teas or traditional medicines and the consumption of grain or grain products (flour or bread) contaminated with PA-containing seeds 1. To date over 660 PAs and PA N-oxides (PANs) has been identified from more than 6000 plant species, in particularly plants in the families Boraginaceae, Asteraceae and Fabaceae 2-3. PAs are esters composed of a necine base and one or more necic acids. base can either be saturated or contain a double bond in the 1,2 position.

The necine

Toxic PAs are

those which contain unsaturated necine bases whereas the ones with saturated necine bases are considered to be non-toxic but require metabolic activation to exert their toxicities

3-4

.

Toxicity of the 1,2-unsaturated PAs in animal studies is characterised by hepatotoxicity, genotoxicity and carcinogenicity as well as developmental toxicity

3

.

Although

1,2-unsaturated PAs may differ in potency, available data are not sufficient to identify relative potency factors for different PAs in order to evaluate the possible effects of combined exposure.

Thus, quantitation of PAs should be limited to 1,2-unsaturated PAs, not

compounds with necine base.

Otherwise, the health risk of intake of PAs would be

overestimated markedly.


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Different sample cleanup procedures were reported for PAs analyses. Hoogenboom described simple extract dilution for plant samples with high PAs content. a freezing out step was used with SPE.

For milk samples,

Defatting by n-hexane was employed by Mulder

for fatty food, such as egg, meat, liver and kidney, followed by SPE.

5

6

Although most

cleanup step involved a SPE cleanup, there are slightly difference in sample extraction and cleanup employed for different food commodities.

A single method suitable for the

determination of PAs in general food is not available. Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) has been employed to determinate individual PAs and respective N-oxides at low levels 6-8.

However,

these published methods were developed for limited commodities, such as milk, plant materials, honey, egg or meat, and were different in preparation procedures, instrumentation and reporting limits

5, 9-10

.

Owing to PAs get structural isomers, this is a challenge on

selectivity of mass spectrometric (MS) technique which is rarely observed in other trace level organic contaminants analyses.

Out of 600 PAs identified in plants 3, this study only

determined 15 PAs and 13 respective N-oxides, in which reference standards are commercially available.

Non-targeted PAs, without analytical reference standard, have

similar chemical properties and are unlikely to be removed by solid phase extraction (SPE) clean up step.

Structural similar or isobaric co-eluted PAs could produce same mass

fragments and cause ambiguity in identification.

Thus, the MS technique used should be



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able to differentiate targeted and non-targeted PAs. Monitoring of 2 MRM transitions, which representing 4 identification points widely accepted for trace organic contaminants analyses. 3 MRM transitions were monitored for each PAs. confirmation.

11

, is

To increase the method selectivity, Two MRM ratios were used for

MS3, which is a multistage fragmentation MS technique, involves second

fragmentation in the linear ion trap of the MS instrument.

It has been used to determinate

plant toxins or mycotoxins in complex matrix with high selectivity

12-13

.

Differential ion

mobility spectrometry (DMS) is considered as another dimension MS technique.

Isobaric

compounds could be separated in the DMS cell based on the difference in their high field and low field mobility 14-16.

As PAs is a large class of structural similar compounds while some

of them are known to be structural isomers, DMS could provide additional selectivity on isobaric PAs detection in addition to chromatographic separation and mass spectrometric selection.

In this work, these MS techniques were investigated and compared for their

selectivity and applicability on PAs determination in food. One of the aims of this manuscript is to develop a ‘single’ method that can analyze different groups of food, including cereal and cereal products, milk and dairy products, meat and liver, eggs, honey, tea infusion/herbal tea infusion/beverages and dried spices. We modified and validated an ultra-performance liquid chromatography – tandem mass spectrometry (UPLC-MS/MS) method using multiple reaction monitoring mode (MRM) with


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isotopically labelled internal standards to analyze PAs in large variety of food.

Furthermore,

the sensitivity and selectivity on analysis of PAs in PA-containing samples by 3MRMs, MS3 and DMS were investigated. Materials and methods Standards and reagents PAs and PANs standards, namely echimidine (Em), echimidine N-oxide (EmN), erucifoline (Er), erucifoline N-oxide (ErN), europine (as hydrochloride) (Eu), europine N-oxide (EuN), heliotrine (Hn), heliotrine N-oxide (HnN), intermedine (Im), intermedine N-oxide (ImN), jacobine (Jb), jacobine N-oxide (JbN), lasiocarpine (Lc), lasiocarpine N-oxide (LcN), lycopsamine (La), lycopsamine N-oxide (LaN), monocrotaline (Mc), monocrotaline N-oxide (McN), retrorsine (Re), retrorsine N-oxide (ReN), senecionine (Sc), senecionine

N-oxide

(ScN),

seneciphylline

(Sp),

seneciphylline

N-oxide

(SpN),

senecivernine (Sv), senecivernine N-oxide (SvN), senkirkine (Sk) and trichodesmine (Td) were obtained from PhytoLab GmbH & Co. KG (Vestenbergsgreuth, Germany). Isotopically labelled PA internal standards (ISs), namely D7–lycopsamine (La_IS), D7– lycopsamine N-oxide (LaN_IS), D3–senecionine (Sc_IS) and D3–senecionine N-oxide (ScN_IS) were obtained from Toronto Research Chemicals Inc. (Toronto, Ontario, Canada). Water was purified through a Milli-Q synthesis system integral with LC-Pak polisher from Millipore (Billerica, MA, USA).

LC-MS grade acetonitrile (ACN) and methanol



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(MeOH) were purchased from Anaqua Chemicals Supply (Houston, TX, USA) and Fisher Scientific (Waltham, MA, USA) respectively.

Concentrated sulfuric acid (H2SO4) and

ammonium hydroxide solution were purchased from BDH, VWR International (Radnor, PA, USA).

Puriss pro analysi (p.a.) grade ammonium formate (AmF) and formic acid (FA) were

purchased from Sigma–Aldrich Co (St. Louis, MO, USA).

HPLC grade isopropanol was

purchased from Tedia (Fairfield, OH, USA). Standard solutions Stock solutions were prepared by dissolving each standard in MeOH at about 1000 mg L-1, and were stored in a freezer at -20 °C.

Mixed intermediate solutions (10 mg L-1) for

standards and internal standards (1 mg L-1) were prepared by mixing and diluting appropriate amount of stock solutions in water, and were stored in a refrigerator at 4°C.

Working

solutions were prepared freshly with appropriate mixing and dilution of intermediate standard solutions in water with AmF and FA concentration of 0.5 mM and 2 mM respectively. Calibration/working range Calibration curves were established by standard solutions of 0.005, 0.05, 0.2, 0.4, 0.6, 0.8 and 1.0 µg L-1 while internal standard concentration were at 0.1 µg L-1 using weighted linear regression (1/x). It is sufficient for general foods. dried spices in parts per million levels. spices.

High levels of PAs were found in

One tenth sample size (0.2 g) was used for dried

If PAs concentrations still exceeded the calibration range, they were brought down


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by appropriate dilution of the sample extract by water containing 0.5 mM L-1 AmF, 2mM L-1 FA and 0.1 µg L-1 ISs. Sample homogenization For general food including egg, milk, meat, cereal and honey, samples were blended with domestic food processors.

To achieve sufficient sample homogeneity for dried herbal

samples, they were coarsely blended with domestic food processors and then finely grounded at low temperature by centrifugal mill, Retsch ZM200 (Haan, Germany) with solid CO2 or freezer mill SPEX SamplePrep 6870 (Metuchen, NJ, USA). Both mills are capable to pulverize fibrous plant tissue into fine powder with satisfactory performance in precision study. Sample preparation Two grams of sample (or 0.2 g dried spices samples) was weighed into a 50 mL polypropylene (PP) tube (Sarstedt, Nümbrecht, Germany) by an analytical balance (Mettler Toledo, Switzerland). 0.2 mL of mixed internal standard (IS) solution, containing 0.2 ng ISs each, was added.

For liquid samples, single extraction was done by 40 mL of 0.05 M H2SO4

and 15 min. sonication in an ultrasonic bath (5510 Branson, Danbury, Connecticut, USA). For solid samples, they were extracted twice for 15 min. with 20 mL of 0.05 M H2SO4 in an ultrasonic bath.

The resulting mixture was centrifuged for 10 min. at 8500 r.p.m. and

ambient temperature by high-speed refrigerated centrifuge (CR21G, Hitachi-Koki, Tokyo,



Japan).

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Supernatant was collected in another 50 mL PP tube and the pH of extract was

adjusted to pH 6-7 using aqueous ammonia solution.

The neutralized pH was confirmed by

a pH meter (Orion, Thermo Scientific, Waltham, Massachusetts, USA).

The solution was

frozen in a -80 °C freezer (Panasonic Biomedical, Netherlands) for overnight (> 15 hours). The extract was then thawed, centrifuged for 10 min. at 8500 r.p.m. and 10°C and filtered through 0.45 micron regenerated cellulose (RC) syringe filter (Sartorius AG, Goettingen, Germany).

A C18 cartridge (Supelco DSC-C18, 6 mL, 500 mg, Bellefonte, Pennsylvania,

USA) was conditioned by 5 mL of methanol and 5 mL of water.

Then, 20 mL of sample

extract was loaded onto the cartridge, followed by 10 mL of water and then 10 mL of ACN washing.

PAs were eluted by adding 10 mL of methanol and then 10 mL of 2.5 %

ammounium hydroxide in methanol.

The two eluates were collected separately.

Afterwards, 0.5 mL water containing 0.5 mM L-1 AmF/2mM L-1 FA was added to each eluates and then rotary evaporated to almost dryness (Buchi Labortechnik AG, Flawil, Switzerland).

They were reconstituted in 0.5 mL of water containing 0.5 mM L-1 AmF and

2mM L-1 FA.

The extracts were combined and filtered with 0.2 micron RC syringe filter

(Sartorius AG) into a vial (Waters, USA) before LC-MS analysis. UPLC, MRM, MS3, DMS and other MS conditions The chromatographic separation was carried out using an Acquity UPLC system, which consisted of a sample manager, a column manager and a binary solvent manager (Waters,


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Milford, MA, USA).

The UPLC system was coupled to a Qtrap 5500, a hybrid instrument

with a quadrupole-linear trap (Sciex, Framingham, USA) equipped with a TurboV ion source for analysis.

Software Acquity UPLC Console (Version 1.30, Waters) and Analyst (Version

1.6, Sciex) were used to operate the UPLC and MS respectively.

Software MultiQuant

(Version 2.0.2, Sciex) was used for data processing. Analytical column was a Waters UPLC column, Acquity CSH C18, 2.1 x 150 mm, 1.7 µm with corresponding pre-column.

Column temperature was set at 40 °C.

Gradient

elution with flow rate of 0.4 mL min-1 was made with ACN/water (80/20 v/v) as mobile phase A (MPA) and water as mobile phase B (MPB) that both mobile phases were buffered with 0.5 mM L-1 AmF and 2 mM L-1 FA.

Initially the composition of MPA was set at 3 % for 2 min.,

then increased to 20 % at 10 min., to 99 % at 13 min. and was held for 1 min. It was then reduced back to 3 % in 1 min. and held for 5 min. to re-conditioning of column.

The total

run time was 20 min. The 28 PAs were eluted within 12.5 min. (Figure S1).

Injection

volume was 10 µL.

Weak wash and strong wash solvents for washing were 900 µL water

and 300 µL ACN respectively.

Electrospray ionization (ESI) in positive mode was used.

Ionspray voltage (IS) was +3000V.

Source temperature was 600 °C.

collision gas (CAD) and set as ‘medium’ mode. GS2 were 20, 50 and 50 psi respectively. worked at unit resolution.

Nitrogen was used as

Curtain gas (CUR), ion source gas GS1 and

Both quadrupole 1 (Q1) and quadrupole 3 (Q3)

The entrance potential (EP) and cell exit potential (CXP) were



+10 V.

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The declustering potential (DP) was optimized at +120 V. Scheduled multiple

reaction monitoring (sMRM) algorithm mode was used with target scan time (TST) set at 0.5 s and MS detection window (DW) set at 60 s. all compounds. PAs.

Protonated ion [M+H]+ was monitored for

3 multiple reaction monitoring (MRM) transitions were monitored for each

Infusion analysis of PAs at concentration of 50 µg L-1 was used to optimize MRM,

multistage fragmentation (MS3) parameters.

Flow injection analysis was used to optimize

differential ion mobility spectrometry (DMS) conditions.

Retention times (RT), MRM

transitions, collision energies , internal standards used, product ions of third generation, excitation energy for MS3 (AF2), separation voltage

and compensation voltage (CoV) for

each PA were summarized in Table 1. For MS3 experiments, MS/MS/MS mode was used. ‘unit’ and ‘LIT’ respectively.

Q1 and Q3 resolutions were set as

Scan rate was 1,000 Da s-1.

Fixed LIT fill time was 200 msec.

Q0 trapping was set as ‘on’.

Excitation time was 25 ms.

For DMS experiments, differential ion mobility kit, SelexION (Sciex), was installed onto the MS.

sMRM mode was used.

modifier (MD) was 2-propanol. offset (DMO) was -3.0 V.

DMS temperature (DT) was set as ‘low’.

DMS

Modifier composition (MDC) was set as ‘low’.

DMS

DMS resolution enhancement (DR) was set as ‘off’.

MS/MS spectra were collected by Enhanced Product Ion mode.

For Em and the

closely eluted unknown compound, parent ion and CE were set at 398.2 m/z and 24 V


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respectively.

For ImN/LaN and the closely eluted unknown compound, parent ion and CE

were set at 316.2 m/z and 38 V respectively. For atmospheric pressure chemical ionization (APCI) experiments, APCI temperature was set at 600 °C.

All LC-MS conditions are the same except nebulizer current (NC) 2 mA

was used instead of Ionspray voltage. Validation Method was validated with reference to Eurachem Guide

17

.

For quantitative test for

trace contaminants, selectivity, linearity, trueness, precision and limit of quantification were validated. For evaluation of linearity with respect to Eurochem guidelines 17, 3 sets of calibration curves were prepared on different days.

The preparation was the same as calibration session

mentioned with 5 more concentrations (0.1, 0.3, 0.5, 0.7 and 0.9 µg L-1) were used to achieve the requirement of 10 ‘evenly spaced’ concentration levels (from 0.1 to 1.0 µg L-1) for linearity assessment.

Response ratios were plotted against concentration ratios using

weighted linear regression (1/x) with internal standard.

To evaluate the linearity of

calibration, residual plots and one-tailed F-tests were done. To obtain the method performance, 10 replicate spike measurements were performed at 0.05 and 0.5 µg kg-1 for general food and spices respectively. Blank samples of cow milk, tea infusion, cooked egg, cooked beef, barley flour and clove leave were used for spike



experiments. Blank honey sample was not found.

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Spike experiments were performed on

two honey samples that certain PAs were found to below limit of detections.

Trueness

(recovery) and repeatability (precision) were obtained by the same set of experiment, as matrix certified reference materials for PAs are not commercial available. The standard deviation (SD) values of the matrix spike measurements were used to obtain estimates of LOQ.

Estimates of LOD were also calculated for information from results of

10 replicate reagent blank spike measurements at LOD. Limits were raised 10-folded for dried spices because of the reduced sample size. Results and discussion Method development Removal of co-extracts by freeze-out steps The neutralized extracts were frozen overnight, followed by chilled centrifugation and syringe filtration.

Significant amount of co-extracts was precipitated out and removed by

centrifugation and filtration.

Clear solutions were obtained.

Freeze-out steps were

essential preparation for fat containing food samples, such as milk, egg and meat.

Without

these steps, turbid extracts blocked syringe filters and SPE cartridges (Figure S2). SPE clean up with acetonitrile washing Originally, ACN was tested for PAs elution but not for SPE cartridges washing. our expectation, none of the PAs was eluted out by ACN.

Out of

On the contrary, undesirable dark


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coloured co-extracts, which usually presence in tea and spices samples, were washed away. The final extracts before LC-MS analysis were much lighter in colour (Figure S3). Washing reverse phase SPE (C18) cartridges with ACN is uncommon practices, however, this case results in better samples clean up.

It is expected that injecting clean sample solution into the

LC-MS would increase the analytical column lifetime. Effect of pH of the raw extract on SPE elution profile and recover pH sensitive PAN Instead of using indicator strip to control the pH of sample extract during initial development stage, fixed volume of ammonium hydroxide solution, which obtained from blank spike experiments, was added to different real food samples.

However, poor recoveries were

obtained for certain PAs in all food samples and didn’t seem to relate to matrix complexity. Therefore, the loss of analytes during SPE cleanup was investigated with respect to pH of sample extract.

Blank spike experiments were performed under three pH conditions: i)

neutral pH at 6.7, obtained by adding the fixed volume of ammonium hydroxide solution, ii) acidic pH at 3.4, obtained by adding 1 drop of ammonium hydroxide solution less than the fixed volume, and iii) alkaline pH 8.4, obtained by adding 1 drop of ammonium hydroxide solution more than the fixed volume. neutral condition.

Alkaline condition shared same elution profile as

However, most PAs, in acidic condition, did not elute by MeOH but

recovered in 2.5 % ammonium hydroxide in MeOH.

Results were summarized in Table S1.



However, degradation of SpN was observed.

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It is expected that ammonia concentrated

during evaporation of MeOH and lead to degradation of SpN.

Similar observation was

reported on riddelline-N-oxide (which is also known as 18-hydroxyseneciphylline-N-oxide)6. To avoid degradation of PAs, the optimized pH of extracts was neutral. MeOH was tested as eluent.

Afterwards, pure

Most PAs, including SpN, were recovered.

On the other hand, incomplete elution (< 60 %) was noted for Sk. our targeted PAs, needs alkaline medium for complete elution.

Sk, the only otonecine in

As such, the PAs were eluted

by MeOH and then by 2.5 % ammonium hydroxide in MeOH.

The two eluates were

separately rotary evaporated. Most PAs/PANs, as well as SpN, were recovery in MeOH without degradation.

The otonecine was completely recovered in alkaline MeOH.

Although the sample preparation was complicated because of just one PA, Sk, such method can apply to other otonecines when more reference materials become commercial available. In real sample analyses, co-extracts affected the pH of extract and the volume of neutralizing solution.

The sample extract had to be carefully neutralized and checked with a pH meter

before loading onto the SPE cartridge. Reduction in response for PA diesters in water During initial method development, the response of Lc was found to be affected by the MeOH/water ratio of the reconstitution solvent. composition increases (Figure S4).

The response decreases when aqueous

Another hydroxylated 1-methylpyrrolizidine diester, Em,


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showed similar but weaker suppression effect.

The reduction of analyte response could be

due to inefficient desolvation of high aqueous proportion solvent during electrospray ionization.

We noted that more residual methanol in extracts after solvent evaporation, i.e.

increased the methanol/water ratio in reconstitution solvent, lower the suppression effect. Thus, Lc response increased and it biased the recovery.

It is improbable to control the

extent of residual methanol, especially in the presence of co-extracts of real samples. Therefore, we replaced methanol in reconstitution solvent by an ionic modifier, formate buffer.

The ionization efficiency was enhanced such that stable responses (which gave

almost identical responses of Lc and Em as they dissolved in MeOH/water 20:80 v/v) were obtained disregard of the composition of methanol. MS selectivity Selectivity achieved by monitoring 3MRM transition pairs of PAs Different 1,2-unsaturated PAs vary in toxicity 3. bases are considered to be non-toxic.

Moreover, PAs with saturated necine

Therefore, accurate identification is essential for both

routine monitoring and risk assessment.

Due to the variety and complexity of food samples,

presence of co-eluted interferences on MRM signals, which are within a tolerance of relative retention time (RRT) ± 2.5 % 11, is inevitable.

3 MRM transition pairs with 2 MRM ratios,

which were calculated as the qualifiers’ MRM responses against quantifier MRM response, that earned 5.5 identification points were used.

Even so, unknown co-eluted compounds



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with all 3 MRM transition pairs were often observed in spices samples. A cumin seed sample was suspected to contain Em (Figure 1a). transitions were detected and fulfilled tolerances of RRT and 1st MRM ratio. 2nd MRM ratio failed to comply with.

All 3 MRMs However, the

For further confirmation, the sample extract was

spiked with appropriate amount of standard and re-analyzed.

The duplet signal (Figure 1c)

proved that the suspected signal was not Em. MS/MS spectrum of the unknown showed that major fragments were almost same (Figure 1d-e) as Em.

Furthermore, respective

N-oxide was detected by the MRM pairs of EmN at RT 0.5 min. eluted earlier than EmN (data not shown).

These strongly suggested that the unknown peak obtained from a PA with

similar structure, for example, echivulgarine or heliosupine.

However, the identity of such

unknown peak could not be confirmed as no reference material was commercially available. Similarly, a cumin seed sample was suspected to contain ImN/LaN (Figure 2a). MRMs transitions were detected and fulfilled tolerances of RRT.

All 3

If only 2 MRM transitions,

via m/z 316/172 and 316/111, were monitored, the signal in the cumin seed sample fulfilled the identification criteria of both ImN and LaN. showed they were neither ImN nor LaN (Figure 2c).

However, spike standard experiment MS/MS spectra (Figure 2d-f) of the

unknown and ImN/LaN shown the unknown could be another structure similar PAN. Since MRM interferences usually come from structural similar PAs for positive samples, monitor 2 MRMs and using 1 MRM ratio to confirm the PA identity becomes insufficient.


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Besides, it is not practical to carry out addition standard spiking experiments for all samples detected with suspected PAs.

Monitoring of 3 MRM transition pairs becomes one of the

possible tools to eliminate false positive identification of targeted PAs. Selectively of MS3 and DMS+MRM Although monitoring of 2 MRM ratios is able to confirm the identity of targeted PAs, detection and quantification of analytes in the presence of closely eluted interferences are still undesirable.

MS3 and DMS are known to have superior selectivity to remove background

interferences with different ion selection mechanism.

The two techniques were investigated

for their selectivity to eliminate interference from structural similar PAs and applicability for confirmation. The above-mentioned PAN positive cumin seed sample spiked with standard was re-analyzed in MS3 mode.

Despite each MS3 transition had already earned 4 identification

points, detection of the 3 MS3 for the suspected PAN and ImN/LaN were still observed (Figure 3).

The selectivity was not much different from monitoring 3 MRMs.

confirmation is needed.

Further

The multistage fragmentation provided limited additional

selectivity to differentiate isobaric structural similar PAs.

On the contrary, the detection of

the unknown by MS3 further supported that the unknown contained a pyrrolizidine core structure. On the other hand, DMS improved selectively for isobaric compounds as it can separate



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and identify ionized molecules in the gas phase based on their mobility in a carrier buffer gas.

The

above-mentioned cumin seed sample spiked with Em was re-analyzed by DMS+MRM mode. The interference on Em was eliminated by the DMS at COV -0.5 (Figure 4).

The second

example depicted in lower part of Figure 4 better demonstrated the selectivity of DMS on separation of isobaric PAN isomers. COV -16.0 and LaN at COV -12.5.

The triplet signal became singlet signals of ImN at The co-eluted interferences from the unknown and the

isobaric PA isomer were removed. Comparing three different mass spectrometric techniques, MRMs, MS3, DMS+MRM, the latter two techniques have higher demand of mass spectrometer hardware and more MS conditions for optimization.

Moreover, the additional ion selection step, which either

performed in the linear ion trap for MS3 or the DMS cell for DMS, results in two major drawbacks.

Firstly, sensitivities of MS3 and DMS modes are much lower than MRM mode.

The detection limits could be raised for one order of magnitude. for MS scanning are comparatively long.

Secondly, their cycle times

The total cycle time for monitoring signals of 28

analytes and 4 ISs in a single run would be too long for collecting sufficient data points for quantitation. As the method would be used for a risk assessment study, monitoring of 3MRM transitions, which has advantages of high sensitivity and multi-residues monitoring, is employed.

Due to the advancement of MS instruments, there is no difficulty on monitoring


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of hundreds of MRM transitions in a single run. reference standards become commercial available.

More PAs could be monitored when more On the contrary, MS3 and DMS+MRM,

which provide better selectivity but limited by cycle time, could be more applicable for monitoring specific PAs with high toxicity. Validation Linearity of calibration Linearity of calibration curves of the 28 PAs quantitation MRMs was evaluated. of calibration curves were prepared in different days. 0.998.

3 sets

All correlation coefficients (r) were >

Residuals of the 10 evenly spaced concentration levels were calculated and plotted.

Residual plots were in general random distributed but indicated that residuals magnitude increased as concentration increased. used.

It was the reason why weighted linear regression was

One-tailed F-tests were conducted (α = 0.05).

Values of F < Fcrit, which indicated

the residual standard deviation values were not significantly greater than the repeatability. The results reflected satisfactory linearity of the calibration curves. Recovery and precision Recovery and precision results for the 10 replicate spike measurements at 0.05 µg kg-1 in different food matrices were in general within the range of 50-120 %

11

(Table 2).

Few

biased high recoveries (>120 %), which observed in egg, meat, cereal and spices, could be reduced to below 120 % after 10-folded solvent dilution.


For precision, the highest


percentage relative standard deviation (%RSD) obtained was 13.4 %.

Page 22 of 36

This single laboratory

repeatability value was multiplied by one and two thirds 11 to estimate a reproducibility value of 22 %.

It was lower than the recommended value 23 % for analyte concentration at 100

µg kg-1 and should be fulfilled the ‘as low as possible’ recommendation for sub-ppb level analyses. LOQ and LOD estimates Estimates of LOQ (Table S2) were obtained by multiplying the standard deviation (SD) values of spike measurements at 0.05 µg kg-1 by a factor of 10 as the RSDs were in general below 10 %17.

The LOQs estimated for 28 PAs were ranged from 0.010 to 0.087 µg kg-1.

For dried spices spike measurements at 0.5 µg kg-1 (which sample size reduced to 0.2 g), the LOQs estimated for 28 PAs were ranged from 0.04 to 0.76 µg kg-1.

The estimates of LOD

were calculated by multiplying a factor of 3 with SD values of 10 reagent blank spike measurements at 0.005 µg kg-1. Internal standards corrections Only four isotopically labelled PAs were commercially available and pre-spiked in samples as internal standards for corrections of various procedural and instrument errors. They worked perfectly well for their native counterparts, La, LaN, Sc, and ScN, in different food matrices with respective recoveries of 100 ± 12 %.

ISs corrections were also

applicable effectively to other PAs in milk, tea infusion and honey with recoveries fell within


Page 23 of 36


50-120 %. Biased high recoveries of several PA/PANs were observed in complex food matrices, egg, beef, barley flour and clove leave.

The respective responses (uncorrected by IS) of the

analytes and their corresponding ISs in the spike measurement were compared with those in calibration curves.

Although the recoveries (uncorrected by IS) of analytes and ISs were
120 %. Matrix effects evaluation To determine whether procedural losses or matrix effects made the differences in recoveries between ‘biased high’ analytes and their ISs, the final sample solutions were diluted 10-folds with reconstitution solvent and re-injected them into the LC-MS for quantitation.

The recoveries (uncorrected by IS) of analytes and ISs were calculated.

Sample dilution was used to reduce matrix effects 18-19, but has no effect on procedural losses. It was noted that differences in recoveries between ‘biased high’ analytes and their ISs were reduced in diluted sample solutions.

Analytes and ISs, which eluted at different RTs, were

subjected to different extends of matrix effects.

When the matrix effects were reduced by

sample dilution, the ISs made good corrections and all biased high recoveries were reduced to below 120 %.

The only drawback was weaker signals were obtained.


In real sample


analyses, the dilution step would be performed when PAs were positively identified with suspected matrix effects. Although calculating recoveries (uncorrected by IS) showed the presence of matrix effects in complex matrices, we did not proceed in-depth matrix effects evaluation. We attempted to use LC-APCI-MS as APCI is known to be less liable to matrix effects than ESI 20

.

However, significant losses of sensitivities were observed in APCI mode, especially for

PANs.

For examples, only 1/20 and 1/400 area counts were obtained for Hn and HnN

signals respectively.

Comparing matrix matched calibration curves against solution

calibration curves could better compensate the matrix effects but it involves large amount of additional sample preparation work such as finding representative blank samples and preparing enough blank sample solution for multi-point calibration curves which is extremely resource-demanding. In conclusion, a selective and sensitive method for determination of 28 PAs/PANs in food is established.

Monitoring of 3 MRM transitions is essential for differentiating

targeted 1,2-unsaturated PAs from isobaric ‘non-targeted’ PAs.

MS3 mode provides limited

improvement in selectivity whilst DMS+MRM mode provides better selectivity for PAs confirmation.

However, both of these confirmation techniques suffer from decreased

sensitivity and long cycle time.

We selected monitoring of 3 MRM transitions for our study.

Multi-residue monitoring (28 PAs) with ultra-low reporting limits (0.05 µg kg-1 for general


Page 24 of 36

Page 25 of 36


food) results were obtained for risk assessment calculation.

Matrix effects in complex food

matrices were reduced by solvent dilution instead of using matrix matched calibration. Internal standardization using 4 isotopically labelled PAs allows quantitation of 28 PAs for a wide variety of food.

MRM signals suspected to be ‘non-targeted’ PAs was observed.

However, lack of commercial available reference materials hinders identification and quantification of these unknown peaks. matrix in sample cleanup.

Freeze-out can remove significant amount of fatty

Besides, ACN was demonstrated to be an effective washing

solvent in SPE clean up to remove matrix from different types of food.

Recoveries of

different analogs of PAs/PANs are ensured by 2 steps-elution and pH control of loading extract.



References 1.

Wiedenfeld, H., Toxicity of pyrrolizidine alkaloids - a serious health problem. Journal of

Marmara University Institute of Health Sciences 2011, 1, 79-87. 2. Dreger, M.; Stanisławska, M.; Krajewska-Patan, A.; Mielcarek, S.; Mikołajczak, P. L.; Buchwald, W., Pyrrolizidine alkaloids - chemistry, biosynthesis, pathway, toxicity, safety and perspectives of medicinal usage. Journal Herba Polonica 2009, 55, 127-147. 3. European Food Safety Authoruty (EFSA), Scientific Opinion on Pyrrolizidine alkaloids in food and feed. EFSA Journal 2011, 9, 2406. 4. European Medicines Agency (EMA) Public statement on the use of herbal medicinal products containing toxic, unsaturated pyrrolizidine alkaloids (PAs). http://ehtpa.eu/pdf/EMA%20statement%202014.pdf (accessed December 22 2017). 5. Hoogenboom, L. A.; Mulder, P. P.; Zeilmaker, M. J.; van den Top, H. J.; Remmelink, G. J.; Brandon, E. F.; Klijnstra, M.; Meijer, G. A.; Schothorst, R.; Van Egmond, H. P., Carry-over of pyrrolizidine alkaloids from feed to milk in dairy cows. Food Addit Contam Part A Chem Anal Control Expo Risk Assess 2011, 28, 359-72. 6. Mulder, P. P.; López Sánchez, P.; These, A.; Preiss-Weigert, A.; Castellari, M., Occurrence of Pyrrolizidine Alkaloids in food. EFSA supporting publication 2015, EN-859. 7. German Federal Institute for Risk Assessment (BfR). Determination of PAs in plant material by SPE-LC-MS/MS 2014. 8. German Federal Institute for Risk Assessment (BfR), Pyrrolizidine alkaloids in herbal teas and teas. Opinion No. 018/2013 of 5 July 2013 2013. 9. Mudge, E. M.; Jones, A. M.; Brown, P. N., Quantification of pyrrolizidine alkaloids in North American plants and honey by LC-MS: single laboratory validation. Food Addit Contam Part A Chem Anal Control Expo Risk Assess 2015, 32, 2068-74. 10. Mulder, P. P.; de Witte, S. L.; Stoopen, G. M.; van der Meulen, J.; van Wikselaar, P. G.; Gruys, E.; Groot, M. J.; Hoogenboom, R. L., Transfer of pyrrolizidine alkaloids from various herbs to eggs and meat in laying hens. Food Addit Contam Part A Chem Anal Control Expo Risk Assess 2016, 33, 1826-1839. 11. European Commission (EC). 2002/657/EC: Commission decision of 12 August 2002 implementing council directive 96/23/EC concerning the performance of analytical methods and the interpretation of results Official Journal of the European Communities, 2002, p. 8–36. 12. Lim, C. W.; Tai, S. H.; Lee, L. M.; Chan, S. H., Analytical method for the accurate determination of tricothecenes in grains using LC-MS/MS: a comparison between MRM transition and MS3 quantitation. Anal Bioanal Chem 2012, 403, 2801-6. 13. Vaclavik, L.; Krynitsky, A. J.; Rader, J. I., Quantification of aristolochic acids I and II in herbal dietary supplements by ultra-high-performance liquid chromatography-multistage fragmentation mass spectrometry. Food Addit Contam Part A Chem Anal Control Expo Risk


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Page 27 of 36


Assess 2014, 31, 784-91. 14. Jin, W.; Jarvis, M.; Star-Weinstock, M.; Altemus, M., A sensitive and selective LC-differential mobility-mass spectrometric analysis of allopregnanolone and pregnanolone in human plasma. Anal Bioanal Chem 2013, 405, 9497-9508. 15. Bylda, C.; Thiele, R.; Kobold, U.; Bujotzek, A.; Volmer, D. A., Rapid quantification of digitoxin and its metabolites using differential ion mobility spectrometry-tandem mass spectrometry. Anal Chem 2015, 87, 2121-8. 16. Regueiro, J.; Giri, A.; Wenzl, T., Optimization of a Differential Ion Mobility Spectrometry-Tandem Mass Spectrometry Method for High-Throughput Analysis of Nicotine and Related Compounds: Application to Electronic Cigarette Refill Liquids. Anal Chem 2016, 88, 6500-8. 17. Magnusson, B.; Örnemark, U., Eurachem Guide: The Fitness for Purpose of Analytical Methods – A Laboratory Guide to Method Validation and Related Topics. 2nd ed.; Eurachem: 2014. 18. Hernando, M. D.; Suarez-Barcena, J. M.; Bueno, M. J.; Garcia-Reyes, J. F.; Fernandez-Alba, A. R., Fast separation liquid chromatography-tandem mass spectrometry for the confirmation and quantitative analysis of avermectin residues in food. J Chromatogr A 2007, 1155, 62-73. 19. Ferrer, C.; Lozano, A.; Aguera, A.; Giron, A. J.; Fernandez-Alba, A. R., Overcoming matrix effects using the dilution approach in multiresidue methods for fruits and vegetables. J Chromatogr A 2011, 1218, 7634-9. 20. Sargent, M. Guide to achieving reliable quantitative LC-MS measurements. http://www.rsc.org/images/AMC%20LCMS%20Guide_tcm18-240030.pdf (accessed December 22 2017).



Table 1

Page 28 of 36

MRM, MS3 and DMS parameters of PAs

PAs

Retention time (min.)

Q1 mass (m/z)

Q3 mass (m/z)

Echimidine (Em)

9.9

398.2

Echimidine N-oxide (EmN)

10.9

414.2

Erucifoline (Er)

2.8

350.2

Erucifoline N-oxide (ErN)

5.2

366.2

Europine (Eu)

3.4

330.2

Europine N-oxide (EuN)

4.9

346.2

Heliotrine (Hn)

6.2

314.2

Heliotrine N-oxide (HnN)

7.4

330.2

Intermedine (Im)

3.0

300.2

Intermedine N-oxide (ImN)

4.9

316.2

Jacobine (Jb)

4.0

352.2

120 220 336 254 352 396 120 138 136 118 136 120 138 156 254 172 111 328 138 156 120 172 111 136 138 156 120 172 138 111 120 155

Collision energy CE (V) 33 24 24 40 34 33 36 37 42 43 40 40 29 41 25 43 61 32 34 38 47 33 56 36 27 39 33 38 37 53 36 38

Internal standard

MS3 ion (m/z)

La_IS

103 120 238 106 254 254 103 94 108 91 94 103 96 94 156 136 94 172 96 94 103 136 94 94 94 96 103 137 94 94 103 109

LaN_IS

Sc_IS

ScN_IS

La_IS

LaN_IS

Sc_IS

ScN_IS

La_IS

LaN_IS

Sc_IS


Excitation energy AF2 (V) 0.06 0.09 0.08 0.08 0.08 0.08 0.07 0.06 0.07 0.06 0.05 0.06 0.06 0.07 0.08 0.06 0.06 0.09 0.07 0.07 0.07 0.07 0.06 0.08 0.07 0.06 0.07 0.06 0.06 0.07 0.07 0.08

SV (V)

COV (V)

2500

-0.5

3000

-4.0

3000

-7.5

2500

-4.0

3000

-3.0

3000

-3.0

3500

-7.0

2500

-1.0

4000

-11.0

3500

-16.0

3000

-7.5

Page 29 of 36


Jacobine N-oxide (JbN)

6.3

368.2

Lasiocarpine (Lc)

11.6

412.2

Lasiocarpine N-oxide (LcN)

11.9

428.2

Lycopsamine (La)

3.2

300.2

Lycopsamine N-oxide (LaN)

5.1

316.2

Monocrotaline (Mc)

1.6

326.2

Monocrotaline N-oxide (McN)

3.8

342.2

Retrorsine (Re)

6.0

352.2

Retrorsine N-oxide (ReN)

7.5

368.2

Senecionine (Sc)

8.2

336.2

Senecionine N-oxide (ScN)

9.8

352.2

Seneciphylline (Sp)

6.5

334.2

Seneciphylline N-oxide

8.3

350.2

280 296 120 324 120 220 336 254 136 352 138 156 120 172 138 111 120 237 194 137 118 120 120 138 324 118 120 136 120 138 308 118 120 136 120 138 306 120

31 33 42 31 27 22 26 39 38 34 28 39 33 37 38 54 45 32 37 39 61 42 38 39 37 41 45 44 37 37 33 39 42 43 35 36 35 44

ScN_IS

Sc_IS

ScN_IS

La_IS

LaN_IS

La_IS

LaN_IS

Sc_IS

ScN_IS

Sc_IS

ScN_IS

Sc_IS

ScN_IS


200 120 103 120 103 120 238 106 94 254 94 138 103 137 94 94 103 194 122 120 91 103 103 94 138 91 103 94 103 94 138 91 103 94 103 94 138 103

0.07 0.08 0.07 0.06 0.06 0.07 0.06 0.08 0.06 0.06 0.08 0.08 0.07 0.06 0.08 0.05 0.05 0.08 0.07 0.07 0.07 0.06 0.07 0.06 0.07 0.06 0.07 0.06 0.07 0.08 0.09 0.07 0.06 0.06 0.06 0.07 0.08 0.06

2500

-4.5

2000

-0.0

3000

-3.0

4000

-6.0

3500

-12.5

3000

-8.5

3000

-8.0

3000

-7.0

2000

-2.5

4000

-10.0*

4000

-9.5*

2500

-5.0

2500

-4.5


(SpN)

118 37 136 41 Senecivernine 7.9 336.2 120 38 (Sv) 138 39 308 37 Senecivernine N-oxide 9.6 352.2 118 41 (SvN) 120 46 136 45 Senkirkine 9.7 366.2 168 38 (Sk) 150 35 122 40 Trichodesmine 5.8 354.2 222 37 (Td) 120 44 308 33 D3-Senecionine 8.2 339.2 120 37 (Sc_IS) 138 38 311 36 D3-Senecionine N-oxide 9.8 355.2 118 39 (ScN_IS) 120 45 136 44 D7-Lycopsamine 3.2 307.2 120 35 (La_IS) 138 30 156 40 D7-Lycopsamine N-oxide 5.1 323.2 172 39 (LaN_IS) 138 39 111 55 Remarks: Underlined Q3 masses are quantifiers. Non-underlined Q3 masses are qualifiers. * Incomplete separation between Sc/Sv and ScN/SvN.

Sc_IS

ScN_IS

Sc_IS

La_IS


Page 30 of 36

91 94 103 94 138 91 103 94 150 122 94 140 103 265

0.07 0.07 0.05 0.07 0.07 0.08 0.07 0.08 0.07 0.06 0.08 0.07 0.07 0.08

4000

-14.5*

4000

-12.0*

2500

-5.5

2500

-5.5

Page 31 of 36


Table 2a Recovery and precision results for the 10 replicate spike measurements in different food matrices n =10 PAs Em EmN Er ErN Eu EuN Hn HnN Im ImN Jb JbN Lc LcN La LaN Mc McN Re ReN Sc ScN Sp SpN Sv SvN Sk Td

Cow milk Recovery (%) 92.3 101.6 87.0 56.9 100.2 105.8 96.0 117.2 91.6 89.2 82.6 107.2 81.2 61.2 96.7 93.0 80.5 88.5 90.3 119.9 97.5 100.8 95.1 94.2 101.4 97.1 96.6 72.2

RSD (%) 4.8 4.4 5.8 10.0 3.4 3.0 3.4 5.4 2.7 3.8 9.6 5.1 2.9 10.5 5.9 2.1 3.1 4.4 4.7 5.7 4.3 5.8 4.2 7.7 6.5 6.4 3.8 5.5

Tea infusion Recovery (%) 93.5 113.7 108.8 94.9 97.9 95.9 110.5 114.7 94.9 85.2 101.3 99.6 100.3 100.3 99.8 98.8 87.7 87.5 107.0 116.1 105.3 99.3 108.0 102.0 108.3 100.7 114.9 77.0


RSD (%) 7.5 7.6 4.1 10.1 3.4 5.9 13.4 5.4 3.2 5.1 8.0 6.2 13.1 9.0 4.6 4.0 3.2 5.0 8.8 6.6 5.4 4.7 3.4 9.7 5.2 7.7 11.3 6.6

Honey Recovery (%) 115.2 93.8 93.8 83.5 103.8 106.2 98.6 100.0 89.7 89.0 86.5 87.8 99.4 101.7 88.1 93.0 105.4 92.9 94.5 106.4 108.1 100.4 94.5 90.4 106.8 95.6 97.1 91.8

RSD (%) 5.0 8.2 8.2 6.6 2.7 4.7 5.3 3.5 3.7 3.7 13.0 4.3 3.9 5.7 10.4 4.9 8.3 4.4 3.7 4.5 6.1 3.7 6.4 7.4 11.4 4.3 6.5 8.8


Page 32 of 36

Table 2b Recovery and precision results for the 10 replicate spike measurements in different food matrices n =10 PAs Em EmN Er ErN Eu EuN Hn HnN Im ImN Jb JbN Lc LcN La LaN Mc McN Re ReN Sc ScN Sp SpN Sv SvN Sk Td

Cooked chicken Recovery (%) 94.7 117.3 118.8 94.9 96.8 109.3 120.0 111.4 96.5 87.3 99.1 142.2/113.1* 107.3 114.3 98.4 96.1 69.6 89.3 142.9/112.4* 113.6 96.5 103.7 119.0 100.0 107.7 107.8 119.8 77.6

egg RSD (%) 3.6 6.8 4.7 9.0 3.0 5.0 6.4 4.7 4.9 3.2 10.5 5.9/10.8* 5.3 5.3 4.3 3.7 9.9 5.8 7.2/12.1* 5.2 3.4 3.5 2.2 5.9 5.2 4.2 6.1 7.8

Cooked beef Recovery (%) 86.6 105.1 101.2 73.9 92.8 97.6 113.8 118.7 105.1 92.7 101.0 155.3/107.0* 80.0 118.8 99.2 94.0 109.0 80.2 100.2 105.5 94.5 103.2 111.0 115.0 103.3 113.9 99.7 71.7

RSD (%) 3.0 3.8 8.4 5.1 3.7 5.0 5.9 4.7 2.2 2.4 10.0 11.5/12.6* 5.3 3.7 6.0 3.7 7.5 5.9 8.5 5.5 6.8 5.7 4.6 7.2 8.9 4.8 7.1 5.1

Barley flour Recovery (%) 102.9 117.9 116.5 91.4 101.8 114.1 137.3/105.6* 113.2 92.2 101.1 85.3 120.0 84.9 76.7 92.7 99.7 75.8 99.6 133.0/113.0* 117.9 107.5 103.5 116.6 113.9 118.1 117.0 116.9 64.1

* Results obtained from 10-folded dilution of sample solution.


RSD (%) 4.0 3.7 10.8 8.2 4.2 5.1 2.9/6.1* 4.4 7.0 6.1 6.9 1.8 5.1 6.6 3.5 4.8 10.7 6.6 9.1/7.4* 4.1 6.5 5.8 4.9 4.8 5.0 5.1 5.2 11.3

Clove leave Recovery (%) 100.0 151.6/115.4* 99.4 87.1 112.7 105.2 145.3/119.9* 116.2 92.2 95.8 112.1 88.4 145.5/105.8* 119.5 105.8 96.0 105.3 83.1 92.8 99.4 127.5 84.7 82.1 91.3 80.0 108.5 132.7/112.4* 74.8

RSD (%) 10.4 9.1/8.4* 11.2 8.6 5.8 4.2 7.5/7.3* 4.1 4.8 3.3 10.5 8.5 6.0/5.3* 3.4 9.8 3.9 12.4 5.2 12.6 4.2 1.7 8.0 9.0 9.0 12.0 7.3 11.4/11.8 8.5

Page 33 of 36


Figure 1 Chromatograms of the 3 MRM transitions of Em of a) a cumin seed sample, b) Em standard solution, c) cumin seed sample spiked with Em standard and MS/MS spectra of d) the unknown, e) Em



Figure 2 Chromatograms of the 3 MRM transitions of ImN/LaN of a) a cumin seed sample, b) ImN and LaN standard solution, c) cumin seed sample spiked with ImN and LaN standard and MS/MS spectra of d) ImN, e) the unknown, f) LaN


Page 34 of 36

Page 35 of 36


Figure 3

Chromatograms of 3 MS3 of a cumin seed sample spiked with a) Em and b) ImN/LaN standards



Figure 4

Chromatograms of 3MRMs transitions of a cumin seed sample spiked with Em, LaN and ImN standards and with DMS mode a)

off and b) on


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Development of an Analytical Method for Analyzing Pyrrolizidine

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