Ion mobility-mass spectrometry to extend analytical performance in the determination of ergot alkaloids in cereal samples

Carbonell‐Rozas, Laura; Hernández‐Mesa, Maykel; Righetti, Laura; Monteau, Fabrice; Lara, Francisco J.; Gámiz‐Gracia, Laura; Bizec, Bruno Le; Dall’Asta, Chiara; Garcı́a-Campaña, Ana M.

doi:10.1016/j.chroma.2022.463502

Cited by 12 publications

(9 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As mentioned earlier, CCSbase can be used for CCS prediction of peptides, carbohydrates, lipids, metabolites, and drugs 50,144,147,148,168 . The use of CCSbase has also been reported for the drug molecules metoprolol acid/atenolol acid in water samples by Hinnenkamp et al 173 and for ergot alkaloids (EA) in cereal samples by Carbonell‐Rozas et al 174 Moreover, Yang et al showed that CCSbase presented smaller error than AllCCS with CCS isomer difference of more than 16% on the study of ginsenoside isomers, 172 while in another study, CCSbase showed similar CCS behavior for per‐ and polyfluoroalkyl substances (PFAS) analysis 175 . Interestingly, Lenski et al developed a workflow that combined the CCSbase prediction method with a quantitative structure–retention relationship (QSRR) predictor for the prediction of CCS and RT, respectively, to reduce false positive annotations in nontargeted metabolomics, recently 176 …”

Section: Ccs Modelsmentioning

confidence: 91%

“…50 As mentioned earlier, CCSbase can be used for CCS prediction of peptides, carbohydrates, lipids, metabolites, and drugs. 50,144,147,148,168 The use of CCSbase has also been reported for the drug molecules metoprolol acid/atenolol acid in water samples by Hinnenkamp et al 173 and for ergot alkaloids (EA) in cereal samples by Carbonell-Rozas et al 174 The web server for this model is accessible through CCSondemand (waters.com). Later, the same ML model was compared with QM approaches using MOBCAL on glucuronides.…”

Section: Metccs and Lipidccsmentioning

confidence: 94%

See 1 more Smart Citation

Collision cross section measurement and prediction methods in omics

Kartowikromo,

Olajide,

Hamid

2023

J Mass Spectrom

View full text Add to dashboard Cite

Omics studies such as metabolomics, lipidomics, and proteomics have become important for understanding the mechanisms in living organisms. However, the compounds detected are structurally different and contain isomers, with each structure or isomer leading to a different result in terms of the role they play in the cell or tissue in the organism. Therefore, it is important to detect, characterize, and elucidate the structures of these compounds. Liquid chromatography and mass spectrometry have been utilized for decades in the structure elucidation of key compounds. While prediction models of parameters (such as retention time and fragmentation pattern) have also been developed for these separation techniques, they have some limitations. Moreover, ion mobility has become one of the most promising techniques to give a fingerprint to these compounds by determining their collision cross section (CCS) values, which reflect their shape and size. Obtaining accurate CCS enables its use as a filter for potential analyte structures. These CCS values can be measured experimentally using calibrant‐independent and calibrant‐dependent approaches. Identification of compounds based on experimental CCS values in untargeted analysis typically requires CCS references from standards, which are currently limited and, if available, would require a large amount of time for experimental measurements. Therefore, researchers use theoretical tools to predict CCS values for untargeted and targeted analysis. In this review, an overview of the different methods for the experimental and theoretical estimation of CCS values is given where theoretical prediction tools include computational and machine modeling type approaches. Moreover, the limitations of the current experimental and theoretical approaches and their potential mitigation methods were discussed.

show abstract

Section: Ccs Modelsmentioning

confidence: 91%

Section: Metccs and Lipidccsmentioning

confidence: 94%

Collision cross section measurement and prediction methods in omics

Kartowikromo,

Olajide,

Hamid

2023

J Mass Spectrom

View full text Add to dashboard Cite

show abstract

“…The elimination of background interference can also lead to an increased signal-to-noise (S/N) ratio; thus lower LODs for analytes of interest can be obtained, ,, The study of Carbonell-Rozas and co-workers showed that the integration of TWIMS in the LC–MS/MS workflow improves the S/N between 2.5 and 4 times . The decrease in LODs makes it possible to detect contaminants at lower concentrations in environmental samples.…”

Section: Benefits Of Ims and The Derived Ccs In Targeted Suspect And ...mentioning

confidence: 99%

“…Sometimes, isomers can only be separated and identified according to the CCS values of one specific adduct, for example, the ergot alkaloids and their corresponding epimers can be distinguished by the CCS values of their [M + Na] + adduct, but not from the CCS values of their [M + H] + adduct Figure shows the arrival time distributions of aldrin and isodrin; it is obvious to see that similar CCS values were obtained for their [M + H] + adducts, however, the CCS values of M + * ions were significantly different, enabling their unequivocal identification.…”

Section: Benefits Of Ims and The Derived Ccs In Targeted Suspect And ...mentioning

confidence: 99%

Application of Ion Mobility Spectrometry and the Derived Collision Cross Section in the Analysis of Environmental Organic Micropollutants

Song,

Canellas,

Dreolin

et al. 2023

Environ. Sci. Technol.

View full text Add to dashboard Cite

Ion mobility spectrometry (IMS) is a rapid gas-phase separation technique, which can distinguish ions on the basis of their size, shape, and charge. The IMS-derived collision cross section (CCS) can serve as additional identification evidence for the screening of environmental organic micropollutants (OMPs). In this work, we summarize the published experimental CCS values of environmental OMPs, introduce the current CCS prediction tools, summarize the use of IMS and CCS in the analysis of environmental OMPs, and finally discussed the benefits of IMS and CCS in environmental analysis. An up-to-date CCS compendium for environmental contaminants was produced by combining CCS databases and data sets of particular types of environmental OMPs, including pesticides, drugs, mycotoxins, steroids, plastic additives, per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs), as well as their well-known transformation products. A total of 9407 experimental CCS values from 4170 OMPs were retrieved from 23 publications, which contain both drift tube CCS in nitrogen ( DT CCS N 2 ) and traveling wave CCS in nitrogen ( TW CCS N 2 ). A selection of publicly accessible and in-house CCS prediction tools were also investigated; the chemical space covered by the training set and the quality of CCS measurements seem to be vital factors affecting the CCS prediction accuracy. Then, the applications of IMS and the derived CCS in the screening of various OMPs were summarized, and the benefits of IMS and CCS, including increased peak capacity, the elimination of interfering ions, the separation of isomers, and the reduction of false positives and false negatives, were discussed in detail. With the improvement of the resolving power of IMS and enhancements of experimental CCS databases, the practicability of IMS in the analysis of environmental OMPs will continue to improve.

show abstract

“…Bile acids comprise a structurally challenging subclass, due to the presence of numerous hydroxyl group positional and stereochemical isomers, but further incorporation of complementary computational modeling could assist in identification . IM-MS has even seen utility in identifying steroids in food safety applications. − Other steroid subclasses that have been profiled using IM-MS have included vitamin D metabolites, glucorocorticoids, and serum estrogens …”

Section: Introductionmentioning

confidence: 99%

Development of a Rapid, Targeted LC-IM-MS Method for Anabolic Steroids

Wedge,

Hoover,

Pettit-Bacovin

et al. 2023

J. Am. Soc. Mass Spectrom.

View full text Add to dashboard Cite

Anabolic steroids are of high biological interest due to their involvement in human development and disease progression. Additionally, they are banned in sport due to their performance-enhancing characteristics. Analytical challenges associated with their measurement stem from structural heterogeneity, poor ionization efficiency, and low natural abundance. Their importance in a variety of clinically relevant assays has prompted the consideration of integrating ion mobility spectrometry (IMS) into existing LC-MS assays, due primarily to its speed and structure-based separation capability. Herein we have optimized a rapid (2 min) targeted LC-IM-MS method for the detection and quantification of 40 anabolic steroids and their metabolites. First, a steroid-specific calibrant mixture was developed to cover the full range of retention time, mobility, and accurate mass. Importantly, this use of this calibrant mixture provided robust and reproducible measurements based on collision cross section (CCS) with interday reproducibility of <0.5%. Furthermore, the combined separation power of LC coupled to IM provided comprehensive differentiation of isomers/isobars within 6 different isobaric groups. Multiplexed IM acquisition also provided improved limits of detection, which were well below 1 ng/mL in almost all compounds measured. This method was also capable of steroid profiling, providing quantitative ratios (e.g., testosterone/epitestosterone, androsterone/etiocholanolone, etc.). Lastly, phase II steroid metabolites were probed in lieu of hydrolysis to demonstrate the ability to separate those analytes and provide information beyond total steroid concentration. This method has tremendous potential for rapid analysis of steroid profiles in human urine spanning a variety of applications from developmental disorders to doping in sport.

show abstract

Ion mobility-mass spectrometry to extend analytical performance in the determination of ergot alkaloids in cereal samples

Cited by 12 publications

References 54 publications

Collision cross section measurement and prediction methods in omics

Collision cross section measurement and prediction methods in omics

Application of Ion Mobility Spectrometry and the Derived Collision Cross Section in the Analysis of Environmental Organic Micropollutants

Development of a Rapid, Targeted LC-IM-MS Method for Anabolic Steroids

Contact Info

Product

Resources

About