Name: Detection of Regulated Ergot Alkaloids in Food Matrices by Liquid Chromatography-Trapped Ion Mobility Spectrometry-Time-of-Flight Mass Spectrometry (Video) | JoVE Journal
Uploaded: 2024-11-22T14:50:00.000+00:00
Duration: 8 min 56 s
Description: Learn liquid chromatography-ion mobility-mass spectrometry for detecting regulated ergot alkaloids in food matrices. This validated method enhances food safety through precise contaminant identification.

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This research was funded by the Consejer&#237;a de Universidad, Investigaci&#243;n e Innovaci&#243;n - Junta de Andaluc&#237;a (PROYEXCEL_00195) and the postdoctoral grant given by the Generalitat Valenciana and European Social Fund+ (CIAPOS/2022/049).&#160;The authors thank the &#34;Centro de Instrumentaci&#243;n Cient&#237;fica (CIC)&#34; at the University of Granada for providing access to the analytical instrumentation used in this protocol.

Enhanced Isomeric Separation of Ergot Alkaloids Using LC-IMS-MS

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<li>Regueiro, J., Negreira, N., Berntssen, M. H. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Ion-mobility-derived+collision+cross+section+as+an+additional+identification+point+for+multiresidue+screening+of+pesticides+in+fish+feed%5BTitle%5D)+AND+%22Anal+Chem%22%5BJournal%5D)">Ion-mobility-derived collision cross section as an additional identification point for multiresidue screening of pesticides in fish feed.</a> Anal Chem. 88 (22), 11169-11177 (2016).</li>
<li>Regueiro, J., Negreira, N., Hannisdal, R., Berntssen, M. H. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Targeted+approach+for+qualitative+screening+of+pesticides+in+salmon+feed+by+liquid+chromatography+coupled+to+traveling-wave+ion+mobility%2Fquadrupole+time-of-flight+mass+spectrometry%5BTitle%5D)+AND+%22Food+Control%22%5BJournal%5D)">Targeted approach for qualitative screening of pesticides in salmon feed by liquid chromatography coupled to traveling-wave ion mobility/quadrupole time-of-flight mass spectrometry.</a> Food Control. 78, 116-125 (2017).</li>
<li>Hernández-Mesa, M., Monteau, F., Le Bizec, B., Dervilly-Pinel, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Potential+of+ion+mobility-mass+spectrometry+for+both+targeted+and+non-targeted+analysis+of+phase+II+steroid+metabolites+in+urine%5BTitle%5D)+AND+%22Anal+Chim+Acta%3A+X%22%5BJournal%5D)">Potential of ion mobility-mass spectrometry for both targeted and non-targeted analysis of phase II steroid metabolites in urine.</a> Anal Chim Acta: X. 1, 100006(2019).</li>
<li>George, A. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Interplatform+comparison+between+three+ion+mobility+techniques+for+human+plasma+lipid+collision+cross+sections%5BTitle%5D)+AND+%22Anal+Chim+Acta%22%5BJournal%5D)">Interplatform comparison between three ion mobility techniques for human plasma lipid collision cross sections.</a> Anal Chim Acta. 1304, 342535(2024).</li>
<li>Mairinger, T., Causon, T. J., Hann, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+potential+of+ion+mobility-mass+spectrometry+for+non-targeted+metabolomics%5BTitle%5D)+AND+%22Curr+Opin+Chem+Biol%22%5BJournal%5D)">The potential of ion mobility-mass spectrometry for non-targeted metabolomics.</a> Curr Opin Chem Biol. 42, 9-15 (2018).</li>
<li>Hernández-Mesa, M., Escourrou, A., Monteau, F., Le Bizec, B., Dervilly-Pinel, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Current+applications+and+perspectives+of+ion+mobility+spectrometry+to+answer+chemical+food+safety+issues%5BTitle%5D)+AND+%22TrAC+Trend+Anal+Chem%22%5BJournal%5D)">Current applications and perspectives of ion mobility spectrometry to answer chemical food safety issues.</a> TrAC Trend Anal Chem. 94, 39-53 (2017).</li>
<li>European, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Commission+Regulation+%28EU%29+2023%2F915+of+25+April+2023+on+maximum+levels+for+certain+contaminants+in+food+and+repealing+Regulation+%28EC%29+No+1881%2F2006%5BTitle%5D)+AND+%22Off+J+Eur+Union%22%5BJournal%5D)">Commission Regulation (EU) 2023/915 of 25 April 2023 on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006.</a> Off J Eur Union. 119, 103-157 (2023).</li>
<li>Carbonell-Rozas, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Occurrence+of+egot+alkaloids+in+major+and+minor+cereals+from+Northern+Italy%3A+A+three+harvesting+years+scenario%5BTitle%5D)+AND+%22J+Agricl+Food+Chem%22%5BJournal%5D)">Occurrence of egot alkaloids in major and minor cereals from Northern Italy: A three harvesting years scenario.</a> J Agricl Food Chem. 71 (42), 15821-15828 (2023).</li>
<li>Arroyo-Manzanares, N., Gámiz-Gracia, L., García-Campaña, A. M., Diana Di Mavungu, J., De Saeger, S. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aArroyo-Manzanares%2C+N+%22Fungal+Metabolites%22">Fungal Metabolites</a>. Jean-Michel Mérillon, J. -M., Ramawat, K. G. , Springer International Publishing. (2016).</li>
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<li>European Food Safety Authority. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Human+and+animal+dietary+exposure+to+ergot+alkaloids%5BTitle%5D)+AND+%22EFSA+J%22%5BJournal%5D)">Human and animal dietary exposure to ergot alkaloids.</a> EFSA J. 15 (7), e04902(2017).</li>
<li>Nam, M., Kim, D., Kim, M. -S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Simultaneous+determination+of+total+ergot+alkaloids+in+wheat+flour+by+Orbitrap+mass+spectrometry%5BTitle%5D)+AND+%22Food+Chem%22%5BJournal%5D)">Simultaneous determination of total ergot alkaloids in wheat flour by Orbitrap mass spectrometry.</a> Food Chem. 441, 138363(2024).</li>
<li>García-Juan, A., León, N., Armenta, S., Pardo, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Development+and+validation+of+an+analytical+method+for+the+simultaneous+determination+of+12+ergot%2C+2+tropane%2C+and+28+pyrrolizidine+alkaloids+in+cereal-based+food+by+LC-MS%2FMS%5BTitle%5D)+AND+%22Food+Res+Int%22%5BJournal%5D)">Development and validation of an analytical method for the simultaneous determination of 12 ergot, 2 tropane, and 28 pyrrolizidine alkaloids in cereal-based food by LC-MS/MS.</a> Food Res Int. 174 (Pt 1), 113614(2023).</li>
<li>Carbonell-Rozas, L., Mahdjoubi, C. K., Arroyo-Manzanares, N., García-Campaña, A. M., Gámiz-Gracia, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Occurrence+of+ergot+alkaloids+in+barley+and+wheat+from+Algeria%5BTitle%5D)+AND+%22Toxins%22%5BJournal%5D)">Occurrence of ergot alkaloids in barley and wheat from Algeria.</a> Toxins. 13 (5), 316(2021).</li>
<li>Carbonell-Rozas, L., Gámiz-Gracia, L., Lara, F. J., García-Campaña, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Determination+of+the+main+ergot+alkaloids+and+their+epimers+in+oat-based+functional+foods+by+ultra-high+performance+liquid+chromatography+tandem+mass+spectrometry%5BTitle%5D)+AND+%22Molecules%22%5BJournal%5D)">Determination of the main ergot alkaloids and their epimers in oat-based functional foods by ultra-high performance liquid chromatography tandem mass spectrometry.</a> Molecules. 26 (12), 3717(2021).</li>
<li>Carbonell-Rozas, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Ion+mobility-mass+spectrometry+to+extend+analytical+performance+in+the+determination+of+ergot+alkaloids+in+cereal+samples%5BTitle%5D)+AND+%22J+Chromatogr+A%22%5BJournal%5D)">Ion mobility-mass spectrometry to extend analytical performance in the determination of ergot alkaloids in cereal samples.</a> J Chromatogr A. 1682, 463502(2022).</li>
<li>European Commission. Commission Implementing Regulation (EU) 2023/2782 of 14 December 2023 laying down the methods of sampling and analysis for the control of the levels of mycotoxins in food and repealing Regulation (EC) No 401/2006. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=%22Off+J+Eur+Union%22">Off J Eur Union</a>. , (2023).</li>
<li>Carbonell-Rozas, L., Vander Cruyssen, L., Dall'Asta, C., Leggieri, M. C., Battilani, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Fit-for-purpose+method+development+to+determine+co-occurring+multiclass+mycotoxins+in+apple+and+apple+puree+samples%5BTitle%5D)+AND+%22Food+Anal+Methods%22%5BJournal%5D)">Fit-for-purpose method development to determine co-occurring multiclass mycotoxins in apple and apple puree samples.</a> Food Anal Methods. 16 (8), 1403-1412 (2023).</li>
<li>Laouni, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Emerging+mycotoxin+occurrence+in+chicken+feed+and+eggs+from+Algeria%5BTitle%5D)+AND+%22Mycotoxin+Res%22%5BJournal%5D)">Emerging mycotoxin occurrence in chicken feed and eggs from Algeria.</a> Mycotoxin Res. 40, 447-456 (2024).</li>
<li>Ben Hassouna, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Mycotoxin+occurrence+in+milk+and+durum+wheat+samples+from+Tunisia+using+dispersive+liquid-liquid+microextraction+and+liquid+chromatography+with+fluorescence+detection%5BTitle%5D)+AND+%22Toxins%22%5BJournal%5D)">Mycotoxin occurrence in milk and durum wheat samples from Tunisia using dispersive liquid-liquid microextraction and liquid chromatography with fluorescence detection.</a> Toxins. 15 (11), 633(2023).</li>
<li>Narváez, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Occurrence+and+exposure+assessment+of+mycotoxins+in+ready-to-eat+tree+nut+products+through+ultra-high+performance+liquid+chromatography+coupled+with+high+resolution+Q-orbitrap+mass+spectrometry%5BTitle%5D)+AND+%22Metabolites%22%5BJournal%5D)">Occurrence and exposure assessment of mycotoxins in ready-to-eat tree nut products through ultra-high performance liquid chromatography coupled with high resolution Q-orbitrap mass spectrometry.</a> Metabolites. 10 (9), 344(2020).</li>
<li>Arroyo-Manzanares, N., Rodríguez-Estévez, V., García-Campaña, A. M., Castellón-Rendón, E., Gámiz-Gracia, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Determination+of+principal+ergot+alkaloids+in+swine+feeding%5BTitle%5D)+AND+%22J+Sci+Food+Agric%22%5BJournal%5D)">Determination of principal ergot alkaloids in swine feeding.</a> J Sci Food Agric. 101 (12), 5214-5224 (2021).</li>
<li>Pereira, V. L., Fernandes, J. O., Cunha, S. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Comparative+assessment+of+three+cleanup+procedures+after+QuEChERS+extraction+for+determination+of+trichothecenes+%28type+A+and+type+B%29+in+processed+cereal-based+baby+foods+by+GC-MS%5BTitle%5D)+AND+%22Food+Chem%22%5BJournal%5D)">Comparative assessment of three cleanup procedures after QuEChERS extraction for determination of trichothecenes (type A and type B) in processed cereal-based baby foods by GC-MS.</a> Food Chem. 182, 143-149 (2015).</li>
<li>Tuzimski, T., Szubartowski, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Method+development+for+selected+bisphenols+analysis+in+sweetened+condensed+milk+from+a+can+and+breast+milk+samples+by+HPLC-DAD+and+HPLC-QqQ-MS%3A+Comparison+of+sorbents+%28Z-SEP%2C+Z-SEP+Plus%2C+PSA%2C+C18%2C+chitin+and+EMR-lipid%29+for+clean-up+of+QuEChERS+extract%5BTitle%5D)+AND+%22Molecules%22%5BJournal%5D)">Method development for selected bisphenols analysis in sweetened condensed milk from a can and breast milk samples by HPLC-DAD and HPLC-QqQ-MS: Comparison of sorbents (Z-SEP, Z-SEP Plus, PSA, C18, chitin and EMR-lipid) for clean-up of QuEChERS extract.</a> Molecules. 24 (11), 2093(2019).</li>
<li>Łozowicka, B., Rutkowska, E., Jankowska, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Influence+of+QuEChERS+modifications+on+recovery+and+matrix+effect+during+the+multi-residue+pesticide+analysis+in+soil+by+GC%2FMS%2FMS+and+GC%2FECD%2FNPD%5BTitle%5D)+AND+%22Environ+Sci+Pollut+Res%22%5BJournal%5D)">Influence of QuEChERS modifications on recovery and matrix effect during the multi-residue pesticide analysis in soil by GC/MS/MS and GC/ECD/NPD.</a> Environ Sci Pollut Res. 24 (8), 7124-7138 (2017).</li>
<li>Schummer, C., Xandonella, I., van Nieuwenhuyse, A., Moris, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Epimerization+of+ergot+alkaloids+in+feed%5BTitle%5D)+AND+%22Heliyon%22%5BJournal%5D)">Epimerization of ergot alkaloids in feed.</a> Heliyon. 6 (6), e04336(2020).</li>
<li>Cherewyk, J. E., Grusie-Ogilvie, T. J., Parker, S. E., Blakley, B. R., Al-Dissi, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+impact+of+storage+temperature+and+time+on+ergot+alkaloid+concentrations%5BTitle%5D)+AND+%22Toxins%22%5BJournal%5D)">The impact of storage temperature and time on ergot alkaloid concentrations.</a> Toxins. 15 (8), 497(2023).</li>
<li>Silva, Â, Mateus, A. R., Barros, S. C., Silva, A. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Ergot+alkaloids+on+cereals+and+seeds%3A+Analytical+methods%2C+occurrence%2C+and+future+perspectives%5BTitle%5D)+AND+%22Molecules%22%5BJournal%5D)">Ergot alkaloids on cereals and seeds: Analytical methods, occurrence, and future perspectives.</a> Molecules. 28 (20), 7233(2023).</li>
</ol>

The authors have no conflicts of interest to disclose.

The successful use of this protocol is based on the optimization of the extraction procedure, previously carried out by Carbonell-Rozas et al.17, who implemented the use of an extraction solvent effective enough to extract EAs from complex food matrices such as barley and wheat, and a clean-up that provided relatively low SSE values. The choice of extraction solvent represents a critical step considering the chemical characteristics of the analytes and the lability of EAs to decomposition and epimerization but, at the same time, the composition of the matrix subjected to analysis. In this case, EAs (and mycotoxins in general) provide very good efficiencies when acetonitrile (a non-protic solvent that could prevent epimerization) is the selected solvent21,22,23,24. Moreover, in the case of EAs, the addition of ammonium carbonate increases the extraction efficiency by providing a basic pH25. Additionally, the solvent/sample ratio is something to consider since using low volumes of solvent could cause saturation26, which is reflected in poor recovery values. Furthermore, high solvent volumes imply greater dilution of the analyte solutions, hampering their detection and/or favoring the extraction of matrix compounds that may interfere with their determination. The next step in this extraction methodology-the clean-up step-must be designed from a fit-for-purpose perspective considering the composition of the matrix. This will ultimately determine how clean the extracts are and how strongly the matrix influences the analytical determination. In this protocol, a C18:Z-Sep+ mixture (1:1, w/w) was successfully used as a dispersive solid phase sorbent, as reflected by the relatively low SSE reported. Taking into account that EAs are well-extracted with acetonitrile, other weakly or non-polar co-elutants can also be expected in the extract. In this context, C18 is a cleaning sorbent traditionally used for general purposes,&#160;retaining non-polar compounds from the matrix, while Z-Sep+ is usually recommended for matrices containing a high percentage of fat or pigments27. It is important to note that most sorbents, also the widely used primary-secondary amine (PSA) or graphitized carbon black (GCB), can interact with the analytes, causing their retention in the solid phase and their loss for a later analytical determination28. Possible interactions between analytes and sorbents can also be a matter of study when optimizing the clean-up step, so changing the typology or, more importantly, the amount of sorbent can be a good starting point for optimization. In this protocol, a previously developed extraction method was applied despite the here-observed trueness for Etn strongly differed from the values obtained in the previous study. Although the pair Et/Etn has been reported as chemically stable29, inconsistencies have been previously observed after long-term storage30. This protocol was designed to preserve the integrity of the analytical standards by drying, storing, and then resuspending on the same day of analysis; nevertheless, the integrity of the analytical standards of EAs should be checked before starting the experimental part.
This protocol chooses LC-IMS-MS as the analytical platform to demonstrate its applicability and improved performance compared to traditional LC-MS approaches involving the determination of the same EAs. As shown in Figure 3, the chromatographic separation of the investigated EAs is optimal for five out of the six main EA-epimer pairs, meaning that an even more optimized chromatographic method can result in a complete separation of the peaks. Nevertheless, no extra effort was necessary to improve the chromatographic separation as the IMS dimension was able to mend the poor resolution shown in LC. The downside of reduced optimization in chromatographic separation is the increased complexity of data processing, due to the introduction of an additional separation stage that adds another dimension. Although this protocol is theoretically designed as a targeted method for the specific determination of EAs, data acquisition in high-resolution mass spectrometry (HRMS) was performed as a non-targeted screening. This means that the instrument was constantly scanning every feature coming from the sample, and, retrospectively, EAs were identified and quantified. This approach is known to reduce the sensitivity of the method but, on the contrary, allows the identification of unknown compounds. Nevertheless, the LOQs reported in Table 2 [0.65 - 2.6 ng/mL (0.49 - 1.95 &#956;g/kg in samples)]&#160;are comparable to those reported by traditional LC-MS methods for the determination of EAs, which operate through targeted acquisitions31. That may mean that the implementation of IMS provides an enhanced analytical signal that allows better discrimination from the background noise, directly affecting the sensitivity of the method. A crucial factor that also affects the intensity of the analytical signal relies on the efficiency of the ionization in the source. If the source is not providing optimal conditions in terms of, mainly, voltage, gas conditions, and temperature, not all analyte molecules will be ionized and detected; therefore, resulting in a loss of absolute intensity. Consequently, it is recommended to explore the ion source parameters for an enhanced analytical signal.
The goal of this protocol is to show the advantages of using LC-IMS-MS in food safety analysis, using EA determination as a case study. The integration of ion mobility spectrometry into liquid chromatography-mass spectrometry workflows provides increased sensitivity and better resolution to separate these compounds, which can become especially complex considering the isomerism of regulated ergot alkaloids. As shown, this analytical platform successfully overcame chromatographic challenges caused by the partial separation of the chromatographic peaks from epimers while, simultaneously, the non-targeted acquisition provided LOQs comparable to those reported by targeted methods. Based on its demonstrated performance, LC-IMS-MS proves to be a powerful analytical platform for developing multi-residue methodologies for food contaminants using non-targeted approaches.

Ion mobility mass spectrometry (IMS) is becoming a growingly used analytical technique, often presented as an additional separation dimension integrated into traditional liquid/gas chromatography (LC/GC) coupled to MS workflows. IMS consists of the separation of molecules along a mobility cell, filled with a buffer gas, under an electric field and at atmospheric pressure1. Depending on the mass-to-charge ratio (m/z) and the geometrical conformation, an ionized molecule will interact with the buffer gas as it moves across the mobility cell, which is reflected in the ion mobility (K) parameter2 and calculated through the following equation:
<img alt="Kinetic equation, K=D/(td×E), static equilibrium, formula, educational diagram." src="/files/ftp_upload/67484/67484eq01v2.jpg" style="margin: auto;" data-altupdatedat="1788304762000" data-alt="Equation 1">
where D represents the total drift length, td is the total drift time, and E is the electric field. Therefore, K is measured in m2 V−1 s−1, although for practical reasons it is often expressed as cm2 V−1 s−1. The intrinsic capability to move across the mobility cell can be measured by the drift time and later converted to the so-called collision cross section (CCS) value, which is a highly reproducible parameter for each molecule independently of the IMS instrument3. The CCS can be derived from the mobility following this equation:
<img alt="Ion mobility equation K=3q/16N×√(2π/μkBT)×1/CCS, used in mass spectrometry analysis." src="/files/ftp_upload/67484/67484eq02v2.jpg" style="margin: auto;" data-altupdatedat="1788304762000" data-alt="Equation 2">
q being the charge of the ion; N the buffer gas number density; µ the reduced mass of the collision partners buffer gas-ion; kB the Boltzmann constant; and T the buffer gas temperature. Therefore, IMS provides additional information complementary to the analytical data resulting from chromatography and MS analyses.
The implementation of IMS in LC-MS platforms has been shown to increase the reliability of analytical determinations, especially when working with compounds that are at trace concentrations. Several studies have reported that LC-IMS-MS methods improve the quality of mass spectra by reducing background noise, which ultimately affects the sensitivity of the method, and reduces the rate of false positives and negatives provided by multi-residue LC-MS methodologies4,5,6. Further, the reproducibility of CCS values allows the comparison not only between different instruments using the same technology, but also between different ion mobility technologies, namely traveling wave ion mobility spectrometry (TWIMS), trapped ion mobility spectrometry (TIMS), and drift tube ion mobility spectrometry (DTIMS)2,7, which are the most frequently used systems1. Thus, a remarkable consequence of the potential of CCS as an identification parameter lies in the possibility of building CCS libraries, reflected in its applicability in metabolomics studies8. Nonetheless, one of the most powerful features of IMS is the ability to separate isomeric and isobaric compounds that may not be sufficiently resolved by LC-MS methods. This may be the case when working with large sets of analytes of interest in complex matrices, which is a common situation in environmental and food analysis. In this context, LC-IMS-MS methods have been proposed for the monitoring of pesticides and, to a lesser extent, veterinary drugs and mycotoxins in food9.
Due to their high resolving power and selectivity, LC/GC-IMS-MS platforms emerge as the most useful tools to address some of the current challenges in food safety, especially those related to isomeric mixtures. The health concern related to isomeric mixtures as food contaminants has been reflected in the current European legislation, which, for instance, limits the maximum concentration of six main ergot alkaloids (EAs) and their corresponding six epimers in several food products10.
EAs constitute a family of toxic secondary metabolites produced by a wide range of fungi, mainly of the family Clavicipitaceae (e.g., Claviceps purpurea, the most important EA producer due to its wide host range), but also Trichocomaceae, which can parasitize the seed head of living plants (such as rye, barley, wheat, and oat) at the time of flowering11,12. Under specific conditions, especially temperature and water activity, Claviceps fungi can produce EAs that accumulate in fruiting bodies, known as sclerotia or ergot, in the host crop. To a certain extent, EAs can withstand the processing of the raw material until reaching the final product; therefore, breaking into the food chain. Ingestion of contaminated food can lead to EA intoxication, known as ergotism, which presents with acute symptoms such as abdominal pain, vomiting, burning sensation of the skin, insomnia, and hallucinations13. To reduce the impact of EAs on human health, the European Commission set maximum levels (MLs) in several foods for the sum of the main EAs: the R-epimers ergometrine (Em), ergotamine (Et), ergosine (Es), ergocristine (Ecr), ergokryptine (Ekr), and ergocornine (Eco) and their corresponding S-epimers: ergometrinine (Emn), ergosinine (Esn), ergotaminine (Etn), ergocorninine (Econ), ergokryptinine (Ekrn), and ergocristinine (Ecrn). These compounds can epimerize from R to S forms and vice versa, especially under exposure to strong light, prolonged storage, or contact with some solvents at high or low pH 12. Although the proportion of R and S forms may vary under different conditions, the EFSA CONTAM Panel reported a higher occurrence of R forms than S forms after reviewing available literature on EAs in food products14. Hence, the MLs vary depending on several factors, such as the susceptibility of the crop, degree of processing, or frequency of consumption. In the EU framework, MLs for milled products of barley, wheat, spelt, and oat have been set at 50 or 150 µg/kg (depending on the ash content lower or higher than 900 mg/100 g, respectively), whereas cereals intended directly for human consumption are subject to an ML of 150 µg/kg, except for cereal-based baby food, in which the ML is reduced to 20 µg/kg10.
This stringent legislation requires analytical methodologies sensitive enough to determine trace concentration (µg/kg) levels while properly identifying regulated EAs and their corresponding epimers, as both forms, R- and S-isomers, can be found together in contaminated samples. This task represents a major challenge since each toxin-epimer pair shares the same exact mass and fragmentation pattern. In addition, a proper chromatographic separation between both compounds may be complex. Therefore, well-optimized LC gradients are required to avoid misquantification when EA epimers co-occur in food samples. Although several studies have reported LC-MS methods for unambiguous determination of EAs15,16,17,18, the chromatographic method must be studied extensively to achieve adequate separation of the chromatographic peaks to unequivocally identify EAs. However, this is not usually feasible for multi-class methods in which contaminants belonging to different chemical families are simultaneously determined. In this context, a recent study conducted by Carbonell-Rozas, Hernández-Mesa, et al.19 reported an LC-IMS-MS method for the quantification of EAs in wheat and barley samples, using two different TWIMS instruments that provided reproducible CCS values and low limits of quantification (LOQs) to detect any non-compliance in accordance with current legislation. Therefore, the goal of this protocol is to show how the integration of IMS in LC-MS workflows contributes to the separation of isomeric EAs, enhancing the selectivity of the analytical method. Additionally, it illustrates how the generation of CCS libraries through the characterization of analytical standards provides higher confidence for mycotoxin identification. This protocol is designed to clearly explain the benefits of implementing IMS in food safety analysis, taking as an example the determination of EAs in cereals. This protocol addresses the sample treatment based on a QuEChERS procedure, sample analysis by LC-TIMS-MS, and IMS data extraction and interpretation.

<table><tbody><tr><td>Acetonitrile</td><td>VWR</td><td>83640.32</td><td></td></tr><tr><td>Amber glass tubes 4 mL</td><td>VWR</td><td>548-0052</td><td></td></tr><tr><td>Amber glass tubes 12 mL</td><td>VWR</td><td>548-0903</td><td></td></tr><tr><td>Amber vials 1.5 mL</td><td>Agilent</td><td>5190-9063</td><td></td></tr><tr><td>Ammonium carbonate</td><td>Fluka</td><td>9716</td><td></td></tr><tr><td>Analytical balance BAS 31&amp;nbsp;</td><td>Boeco</td><td>4400519</td><td></td></tr><tr><td>Balance CP 323 S&amp;nbsp;</td><td>Sartorius</td><td>23-84182</td><td></td></tr><tr><td>C18</td><td>Supelco</td><td>52604-U</td><td></td></tr><tr><td>Centrifuge tubes, 15 mL</td><td>VWR</td><td>525-1082</td><td></td></tr><tr><td>Centrifuge tubes, 50 mL</td><td>VWR</td><td>525-0155</td><td></td></tr><tr><td>Centrifuge Universal 320 R</td><td>Hettich</td><td>1406</td><td></td></tr><tr><td>Compass HyStar&amp;nbsp;</td><td>Bruker</td><td></td><td>Acquisition software</td></tr><tr><td>DataAnalysis</td><td>Bruker</td><td></td><td>Qualitative software</td></tr><tr><td>Elute PLUS&amp;nbsp;UHPLC</td><td>Bruker</td><td></td><td></td></tr><tr><td>EVA EC-S evaporator</td><td>VLM</td><td>V830.012.12</td><td></td></tr><tr><td>Formic acid GR for analysis ACS, Reag. Ph Eur</td><td>Merck</td><td>100264</td><td></td></tr><tr><td>Grinder TitanMill300</td><td>Cecotec</td><td>1559</td><td></td></tr><tr><td>Methanol</td><td>VWR</td><td>83638.32</td><td></td></tr><tr><td>Milli-Q water purification system (18.2 M&amp;Omega; cm)</td><td>Millipore</td><td>ZD5211584</td><td></td></tr><tr><td>Pipette tips 1- 5 mL</td><td>Labortecnic</td><td>162005</td><td></td></tr><tr><td>Pipette tips 100 - 1000 &amp;micro;L</td><td>Labortecnic</td><td>1622222</td><td></td></tr><tr><td>Pipette tips 5 - 200 &amp;micro;L</td><td>Labortecnic</td><td>162001</td><td></td></tr><tr><td>Pippette Transferpette S variable, DE-M 10 - 100 &amp;micro;L</td><td>BRAND</td><td>704774</td><td></td></tr><tr><td>Pippette Transferpette S variable, DE-M 100 - 1000 &amp;micro;L</td><td>BRAND</td><td>704780</td><td></td></tr><tr><td>Pippette Transferpette S variable, DE-M 500 - 5000 &amp;micro;L</td><td>BRAND</td><td>704782</td><td></td></tr><tr><td>Syringe 2 mL</td><td>VWR</td><td>613-2003</td><td></td></tr><tr><td>Syringe Filter 13 mm, 0.22&amp;micro;m</td><td>Phenomenex</td><td>AF-8-7707-12</td><td></td></tr><tr><td>TASQ</td><td>Bruker</td><td></td><td>Quantitative software</td></tr><tr><td>timsTOFPro2 IM-HRMS</td><td>Bruker</td><td></td><td></td></tr><tr><td>Vortex Genie 2</td><td>Scientific Industries</td><td>15547335</td><td></td></tr><tr><td>Zorbax Eclipse Plus RRHD C18 column (50&amp;nbsp;x&amp;nbsp;2.1 mm, 1.8 &amp;micro;m particle size)</td><td>Agilent&amp;nbsp;</td><td>959757-902</td><td></td></tr><tr><td>Z-Sep+</td><td>Supelco</td><td>55299-U</td><td>Zirconia-based sorbent</td></tr><tr><td>&lt;em&gt;Ergot alkaloids&lt;/em&gt;</td><td></td><td></td><td>&lt;strong&gt;CAS registry sorbent&lt;/strong&gt;</td></tr><tr><td>Ergocornine (Eco)</td><td>Techno Spec</td><td>E178</td><td>564-36-3</td></tr><tr><td>Ergocorninine (Econ)</td><td>Techno Spec</td><td>E130</td><td>564-37-4</td></tr><tr><td>Ergocristine (Ecr)</td><td>Techno Spec</td><td>E180</td><td>511-08-0</td></tr><tr><td>Ergocristinine (Ecrn)</td><td>Techno Spec</td><td>E188</td><td>511-07-9</td></tr><tr><td>Ergokryptine (Ekr)</td><td>Techno Spec</td><td>E198</td><td>511-09-1</td></tr><tr><td>Ergopkryptinine (Ekrn)</td><td>Techno Spec</td><td>E190</td><td>511-10-4</td></tr><tr><td>Ergometrine (Em)</td><td>Romer Labs</td><td>&quot;002067&quot;</td><td>60-79-7</td></tr><tr><td>Ergometrinine (Emn)</td><td>Romer Labs</td><td>LMY-090-5ML</td><td>479-00-5</td></tr><tr><td>Ergosine (Es)</td><td>Techno Spec</td><td>E184</td><td>561-94-4</td></tr><tr><td>Ergosinine (Esn)</td><td>Techno Spec</td><td>E194</td><td>596-88-3</td></tr><tr><td>Ergotamine (Et)</td><td>Romer Labs</td><td>&quot;002069&quot;</td><td>113-15-5</td></tr><tr><td>Ergotaminine (Etn)</td><td>Romer Labs</td><td>&quot;002075&quot;</td><td>639-81-6</td></tr></tbody></table>

detection of regulated ergot alkaloids in food matrices by liquid chromatography-trapped ion mobility spectrometry-time-of-flight mass spectrometry

Detection of Regulated Ergot Alkaloids in Food Matrices by Liquid Chromatography-Trapped Ion Mobility Spectrometry-Time-of-Flight Mass Spectrometry

Ion mobility mass spectrometry (IMS) acts as an additional separation dimension when integrated into liquid chromatography-mass spectrometry (LC-MS) workflows. LC-IMS-MS methods provide higher peak resolution, enhanced separation of isobaric and isomeric compounds, and improved signal-to-noise ratio (S/N) compared to traditional LC-MS methods. IMS provides another molecular characteristic for the identification of analytes, namely the collision cross section (CCS) parameter, reducing false positive results. Therefore, LC-IMS-MS methods address important analytical challenges in the field of food safety (i.e., detection of compounds at trace levels in complex food matrices and unambiguous identification of isobaric and isomeric molecules).
Ergot alkaloids (EAs) are a family of mycotoxins produced by fungi that attack a wide variety of grass species, including small grains such as rye, triticale, wheat, barley, millet, and oats. Maximum levels (MLs) of these mycotoxins have been established in several foodstuffs, as detailed in the Commission Regulation EC/2023/915. This new legislation includes six main EAs and their corresponding epimers, so an efficient methodology is required to properly distinguish these isomeric molecules considering their co-occurrence.
Therefore, the goal of this protocol is to show how the integration of IMS in LC-MS workflows contributes to the separation of isomeric EAs, enhancing the selectivity of the analytical method. Additionally, it illustrates how the generation of CCS libraries through the characterization of analytical standards provides higher confidence for the identification of mycotoxins. This protocol is designed to clearly explain the benefits of implementing IMS in food safety, taking as an example the determination of EAs in cereals. A QuEChERS-based extraction followed by an LC-trapped ion mobility spectrometry (TIMS)-MS analysis provided limits of quantification ranging from 0.65 to 2.6 ng/g with acceptable accuracy (although low recovery for ergotaminine) at 1.5x, 1x, and 0.5x the ML and exhibited a negligible matrix effect.

First, working standard solutions were injected into the LC-IMS-MS instrument to obtain all the identification features (i.e., retention time, CCS, and mass spectra) of each EA analyzed here. Since the identification parameters, except the exact mass, were initially unknown, the acquisition method was based on a two-scan event, starting with a full scan of the entire mass spectrum followed by a bbCID. The retrospective way of approaching this study is enabled by the Q-TOF high-resolution mass spectrometer, which acquires and generates data without any input or prior information about the analytes. The exact mass of each pair main EA-epimer was searched within the acquired data to also obtain their other identification characteristics (i.e., retention times and CCS values), that will be used to create a quantitative method for sample data processing. The experimental parameters obtained after the analysis are detailed in Table 1.
Chromatographic separation provided clear and well-resolved peaks for each main EA-epimer pair except for Et and Etn (Figure 3). The similarities between the retention times of the chromatographic peaks of Et (6.85 min) and Etn (6.98 min) provided inadequate resolution between them, which shows a slight overlap and, consequently, may lead to misquantification considering that retention times can drift throughout the runs. Nevertheless, a baseline separation of this same pair of molecules is observed in the ion mobility spectra (Figure 4), obtaining distinguishable CCS values for each analyte; therefore, showing the advantages of implementing IMS when working with a set of structurally similar compounds.
Once the identification parameters were established for each EA, the set of samples was prepared in accordance with current European legislation for the validation of analytical methodologies20. Three calibration levels were selected based on the ML established by the European authorities: the limit itself (150 µg/kg), 1.5x the ML (225 µg/kg), and 0.5x the ML (75 µg/kg). It is very important to keep in mind that this ML corresponds to the total sum of the 12 EAs. For validation purposes, an equal contribution for the ML was considered; thus, tested concentration levels correlated to 12.50, 18.75, and 6.25 µg/kg, respectively, for each EA. Moreover, a set of eight blank samples and two calibration curves were prepared in neat solvent (standard calibration curve) along with a matrix-matched calibration curve, and were analyzed within the same analytical batch. The linear range was evaluated across seven points in the concentration range of 0.08 to 41.6 ng/L (instrumental concentration levels for each EA). The method performance is shown in Table 2.
First, the calibration curves for each compound were built in the quantitative software and the linear range was evaluated using the peak area as a function of analyte concentration. It is important to achieve a good linear fit (R2 &gt; 0.99) while ensuring a relative standard deviation lower than 20% in terms of precision for each concentration level. To do that, the weighting of the curve can be switched to "1/x". Good linearity was observed for all analytes in the linear range 2.6-41.3 ng/mL (1.95-31.2 g/kg in samples); although for some analytes, the linear range was even wider with a lower limit at 0.65 ng/mL while maintaining a signal-to-noise ratio above 10. Figure 5 shows an example of the (a) standard and (b) matrix-matched calibration curve for Econ.
Comparison between the slopes of standard and matrix-matched calibration curves provides information on how the potential co-elutants from the matrix may affect the analysis. This disturbance is known as the signal suppression/enhancement effect (SSE) and can be assessed by comparing the slopes of both calibration curves and applying the following equation:
<img alt="SSE formula for calibration; equation for comparing standard and matrix-matched curves; data analysis." src="/files/ftp_upload/67484/67484eq03v3.jpg" style="margin: auto;" data-altupdatedat="1788304762000" data-alt="Equation 3">
As shown in Table 2, the SSE ranged from -23 to 18%, indicating that the presence of the matrix has almost no influence on the ionization of the analytes; therefore, their quantification can be carried out using the standard calibration curve.
Then, knowing the influence of the matrix, the next step consists of the quantification of the spiked samples at the three concentration levels previously mentioned, using the calibration curves, to evaluate how much of the initial EA is recovered after the extraction process. Due to the low SSE shown, the calibration curves prepared in solvent were used in the quantitative software to automatically determine the concentration of the spiked samples. To calculate the recovery, the measured concentration was then compared with the theoretical concentration following this equation:
<img alt="Recovery formula: 100 x (measured concentration/theoretical concentration); equation, calculation." src="/files/ftp_upload/67484/67484eq04.jpg" style="margin: auto;" data-altupdatedat="1788304762000" data-alt="Equation 4">
All analytes showed recovery values within the range of 72-117% for all concentration levels. This means that the method provided measurements of the concentration in the spiked samples close enough to the theoretical values, therefore showing proper trueness. Nevertheless, the method displayed limited trueness for Etn, whose concentration values ranged from 43% to 45% referring to the theoretical fortification levels. The precision of the measurements was assayed by calculating the relative standard deviation (RSD) of recoveries for each fortification level obtained within the same day (RSDr, n = 3) and throughout the whole study (RSDWR, n = 9). An acceptable precision was observed considering that all values varied below 20%.
Finally, to evaluate the sensitivity of the proposed method, LOQs were estimated based on the matrix-matched calibration curve. In this protocol, these values were determined as the lowest concentration within the linear range of the curve that showed a deviation below 20% from the theoretical value and a signal-to-noise ratio above 10. As shown in Table 2, LOQs ranged from 0.65 to 2.60 ng/mL (0.49 to 1.95 μg/kg in samples).
<img alt="Ergot alkaloid solution preparation chart, showing dilution steps and acetonitrile use for validation." class="xfigimg" src="/files/ftp_upload/67484/67484fig01.jpg" data-altupdatedat="1788304762000" data-alt="Figure 1"> 
Figure 1: Schematic workflow for the preparation of intermediate and working standard solutions. <a href="https://www.jove.com/files/ftp_upload/67484/67484fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Chromatography worklist diagram; solvent calibration, matrix-matched curves, cereal sample analysis." class="xfigimg" src="/files/ftp_upload/67484/67484fig02.jpg" data-altupdatedat="1788304762000" data-alt="Figure 2"> 
Figure 2: Worklist designed for LC-IMS-MS analysis in the validation study of pooled cereal samples. <a href="https://www.jove.com/files/ftp_upload/67484/67484fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Chromatography graph showing compound separation peaks; intensity vs. time data analysis results." class="xfigimg" src="/files/ftp_upload/67484/67484fig03.jpg" data-altupdatedat="1788304762000" data-alt="Figure 3"> 
Figure 3: Overlapped extracted ion chromatograms of the analyzed EAs. Abbreviations: EAs = ergot alkaloids; Eco = Ergocornine; Econ = Ergocorninine; Ecr = Ergocristine; Ecrn = Ergocristinine; Ekr = Ergokryptine; Ekrn = Ergokryptinine; Emn = Ergometrinine; Es = Ergosine; Esn = Ergosinine; Et = Ergotamine; Etn = Ergotaminine. <a href="https://www.jove.com/files/ftp_upload/67484/67484fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Chromatography graph showing Et, Etn intensity vs. time and mobility; separation analysis." class="xfigimg" src="/files/ftp_upload/67484/67484fig04.jpg" data-altupdatedat="1788304762000" data-alt="Figure 4"> 
Figure 4: Extracted ion chromatogram (upper) and ion mobility spectra (lower) of Et and Etn. Abbreviations: Et = Ergotamine; Etn = Ergotaminine. <a href="https://www.jove.com/files/ftp_upload/67484/67484fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Ergocorninine concentration vs. signal linearity, R²&gt;0.99, calibration graph, analytical chemistry." class="xfigimg" src="/files/ftp_upload/67484/67484fig05.jpg" data-altupdatedat="1788304762000" data-alt="Figure 5"> 
Figure 5: Calibration curves of Econ. (A) Neat solvent and (B) matrix-matched. Abbreviation: Econ = Ergocorninine. <a href="https://www.jove.com/files/ftp_upload/67484/67484fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Analytes</td>
			<td>Rt (min)</td>
			<td>CCS (Å2)</td>
			<td>[M+H]+ (m/z)</td>
		</tr>
		<tr>
			<td>Eco</td>
			<td>6.95</td>
			<td>231.67</td>
			<td>562.3029</td>
		</tr>
		<tr>
			<td>Econ</td>
			<td>8.21</td>
			<td>229.96</td>
			<td>562.3029</td>
		</tr>
		<tr>
			<td>Ecr</td>
			<td>8.61</td>
			<td>237.74</td>
			<td>610.3029</td>
		</tr>
		<tr>
			<td>Ercn</td>
			<td>9.85</td>
			<td>235.56</td>
			<td>610.3029</td>
		</tr>
		<tr>
			<td>Ekr</td>
			<td>8.15</td>
			<td>233.61</td>
			<td>576.3185</td>
		</tr>
		<tr>
			<td>Ekrn</td>
			<td>9.38</td>
			<td>229.93</td>
			<td>576.3185</td>
		</tr>
		<tr>
			<td>Em</td>
			<td>3.57</td>
			<td>179.35</td>
			<td>326.1668</td>
		</tr>
		<tr>
			<td>Emn</td>
			<td>4.48</td>
			<td>179.01</td>
			<td>326.1668</td>
		</tr>
		<tr>
			<td>Es</td>
			<td>6.41</td>
			<td>229.29</td>
			<td>548.2872</td>
		</tr>
		<tr>
			<td>Esn</td>
			<td>6.54</td>
			<td>226.65</td>
			<td>548.2872</td>
		</tr>
		<tr>
			<td>Et</td>
			<td>6.85</td>
			<td>230.33</td>
			<td>582.2716</td>
		</tr>
		<tr>
			<td>Etn</td>
			<td>6.98</td>
			<td>228.3</td>
			<td>582.2716</td>
		</tr>
	</tbody>
</table>
Table 1: Characterized LC-IMS-MS parameters for unambiguous identification of ergot alkaloids applying the method described in this protocol. Abbreviations: Rt = Retention time; CCS = Collision cross section; LC-IMS-MS = liquid chromatography-ion mobility-mass spectrometry.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td colspan="3">Recovery (%)</td>
			<td colspan="3">Precision (%) [RSDr, (RSDWR)]</td>
			<td></td>
		</tr>
		<tr>
			<td>Analytes</td>
			<td>Linearity (R2)</td>
			<td>SSE (%)</td>
			<td>0.5 ML</td>
			<td>ML</td>
			<td>1.5 ML</td>
			<td>0.5 ML</td>
			<td>ML</td>
			<td>1.5 ML</td>
			<td>LOQ in sample (µg/kg)</td>
		</tr>
		<tr>
			<td>Eco</td>
			<td>0.9937</td>
			<td>-23</td>
			<td>114</td>
			<td>111</td>
			<td>100</td>
			<td>6 (15)</td>
			<td>4 (19)</td>
			<td>13 (17)</td>
			<td>0.49</td>
		</tr>
		<tr>
			<td>Econ</td>
			<td>0.9915</td>
			<td>-12</td>
			<td>105</td>
			<td>117</td>
			<td>124</td>
			<td>6 (10)</td>
			<td>7 (18)</td>
			<td>8 (14)</td>
			<td>0.49</td>
		</tr>
		<tr>
			<td>Ecr</td>
			<td>0.9965</td>
			<td>18</td>
			<td>79</td>
			<td>107</td>
			<td>110</td>
			<td>13 (19)</td>
			<td>13 (18)</td>
			<td>6 (18)</td>
			<td>0.49</td>
		</tr>
		<tr>
			<td>Ercn</td>
			<td>0.9906</td>
			<td>-20</td>
			<td>99</td>
			<td>110</td>
			<td>104</td>
			<td>10 (15)</td>
			<td>11 (10)</td>
			<td>12 (10)</td>
			<td>0.49</td>
		</tr>
		<tr>
			<td>Ekr</td>
			<td>0.992</td>
			<td>-10</td>
			<td>106</td>
			<td>101</td>
			<td>93</td>
			<td>6 (9)</td>
			<td>7 (7)</td>
			<td>10 (9)</td>
			<td>0.49</td>
		</tr>
		<tr>
			<td>Ekrn</td>
			<td>0.9925</td>
			<td>-16</td>
			<td>97</td>
			<td>118</td>
			<td>114</td>
			<td>5 (11)</td>
			<td>7 (4)</td>
			<td>9 (9)</td>
			<td>0.98</td>
		</tr>
		<tr>
			<td>Em</td>
			<td>0.9947</td>
			<td>-9</td>
			<td>72</td>
			<td>79</td>
			<td>74</td>
			<td>7 (8)</td>
			<td>6 (5)</td>
			<td>9 (9)</td>
			<td>0.98</td>
		</tr>
		<tr>
			<td>Emn</td>
			<td>0.9909</td>
			<td>-32</td>
			<td>83</td>
			<td>87</td>
			<td>84</td>
			<td>6 (5)</td>
			<td>11 (10)</td>
			<td>7 (9)</td>
			<td>1.95</td>
		</tr>
		<tr>
			<td>Es</td>
			<td>0.9953</td>
			<td>-16</td>
			<td>89</td>
			<td>112</td>
			<td>111</td>
			<td>5 (7)</td>
			<td>8 (5)</td>
			<td>15 (8)</td>
			<td>0.98</td>
		</tr>
		<tr>
			<td>Esn</td>
			<td>0.9971</td>
			<td>-13</td>
			<td>86</td>
			<td>90</td>
			<td>81</td>
			<td>3 (6)</td>
			<td>14 (12)</td>
			<td>10 (10)</td>
			<td>0.49</td>
		</tr>
		<tr>
			<td>Et</td>
			<td>0.9953</td>
			<td>-16</td>
			<td>79</td>
			<td>88</td>
			<td>81</td>
			<td>12 (15)</td>
			<td>19 (18)</td>
			<td>11 (20)</td>
			<td>0.98</td>
		</tr>
		<tr>
			<td>Etn</td>
			<td>0.9997</td>
			<td>-1</td>
			<td>45</td>
			<td>43</td>
			<td>44</td>
			<td>9 (12)</td>
			<td>5 (13)</td>
			<td>12 (17)</td>
			<td>0.98</td>
		</tr>
	</tbody>
</table>
Table 2: Method performance of EAs in terms of linearity, matrix effect, recovery, precision and limits of quantification. Abbreviations: Eco = Ergocornine; Econ = Ergocorninine; Ecr = Ergocristine; Ecrn = Ergocristinine; Ergokryptine = Ekr; Ergokryptinine = Ekrn; Emn = Ergometrinine; Es = Ergosine; Esn = Ergosinine; Et = Ergotamine; Etn = Ergotaminine; LOQ = Limit of quantification; ML = Maximum level; RSDr = repeatibility relative standard deviation; RSDWR = within laboratory relative standard deviation; SEE = suppression/enhancement effect.

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Ion mobility mass spectrometry (IMS) acts as an additional separation dimension when integrated into liquid chromatography-mass spectrometry (LC-MS) ...

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