Travelling wave ion mobility-derived collision cross section for mycotoxins: Investigating interlaboratory and interplatform reproducibility

Parent and modified mycotoxin analysis remains a challenge because of their chemical diversity, the presence of isomeric forms, and the lack of analytical standards. The creation and application of a collision cross section (CCS) database for mycotoxins may bring new opportunities to overcome these analytical challenges. However, it is still an open question whether common CCS databases can be used independently from the instrument type and ion mobility mass spectrometry (IM-MS) technologies, which utilize different methodologies for determining the gas-phase mobility. Here, we demonstrated the reproducibility of CCS measurements for mycotoxins in an interlaboratory study (average RSD 0.14% ± 0.079) and across different traveling wave IM-MS (TWIMS) systems commercially available (ΔCCS% < 2). The separation in the drift time dimension of critical pairs of isomers for modified mycotoxins was also achieved. In addition, the comparison of measured and predicted CCS values, including regulated and emerging mycotoxins, was addressed

Improving Target and Suspect Screening High-Resolution Mass Spectrometry Workflows in Environmental Analysis by Ion Mobility Separation

Currently, the most powerful approach to monitor organic micropollutants (OMPs) in environmental samples is the combination of target, suspect, and nontarget screening strategies using high-resolution mass spectrometry (HRMS). However, the high complexity of sample matrices and the huge number of OMPs potentially present in samples at low concentrations pose an analytical challenge. Ion mobility separation (IMS) combined with HRMS instruments (IMS−HRMS) introduces an additional analytical dimension, providing extra information, which facilitates the identification of OMPs. The collision cross-section (CCS) value provided by IMS is unaffected by the matrix or chromatographic separation. Consequently, the creation of CCS databases and the inclusion of ion mobility within identification criteria are of high interest for an enhanced and robust screening strategy. In this work, a CCS library for IMS−HRMS, which is online and freely available, was developed for 556 OMPs in both positive and negative ionization modes using electrospray ionization. The inclusion of ion mobility data in widely adopted confidence levels for identification in environmental reporting is discussed. Illustrative examples of OMPs found in environmental samples are presented to highlight the potential of IMS−HRMS and to demonstrate the additional value of CCS data in various screening strategies

Identification and Quantification of Protein Adducts Formed by Metabolites of 1‑Methoxy-3-indolylmethyl Glucosinolate <i>in Vitro</i> and in Mouse Models

1-Methoxy-3-indolylmethyl (1-MIM) glucosinolate (GLS) occurring in cabbage, broccoli, and other cruciferous plants is a potent mutagen requiring metabolic activation by myrosinase present in plant cells and intestinal bacteria. We previously reported that 1-MIM-GLS and its alcoholic breakdown product 1-MIM-OH, which requires additional activation by sulfotransferases, form DNA adducts in mice. In the present study, the formation of protein adducts was investigated. First, two major adducts obtained after incubation of individual amino acids, serum albumin, or hemoglobin with 1-MIM-GLS in the presence of myrosinase were identified as τ<i>N</i>-(1-MIM)-His and π<i>N</i>-(1-MIM)-His using MS and NMR spectroscopy. After the development of a specific detection method using isotope-dilution UPLC-ESI-MS/MS, adduct formation was confirmed in mice after oral treatment with 1-MIM-GLS. Adduct levels were highest in the cecum and colon, somewhat lower in serum albumin and the liver, and also readily detectable in the lung and hemoglobin. On the contrary, oral treatment with 1-MIM-OH produced the highest adduct levels in the liver. The higher ratio of albumin to hemoglobin adducts in 1-MIM-OH- compared to 1-MIM-GLS-treated animals (8.1 versus 3.5) suggests that in 1-MIM-OH-treated animals albumin adducts were produced mostly in the liver, the site of albumin synthesis. The formation of adducts was approximately linear over a range of single oral doses from 20 to 600 μmol/kg body mass. Repeated oral administration of 1-MIM-OH (up to 40 treatments, thrice per week) led to continuous accumulation of hemoglobin adducts, whereas the level of serum albumin adducts remained rather constant, which reflects the different turnover rates of these proteins (<i>t</i>_1/2 nearly 1.9 d for serum albumin and 25 d for hemoglobin in the mouse). Accumulation of adducts was also noticed in the lung. Adduct levels were higher, but their accumulation was weaker in the liver and kidney. The method developed will be useful to assess the exposure of humans to reactive metabolites formed from 1-MIM-GLS present in many foods

Interlaboratory and Interplatform Study of Steroids Collision Cross Section by Traveling Wave Ion Mobility Spectrometry

Collision cross section (CCS) databases based on single-laboratory measurements must be cross-validated to extend their use in peak annotation. This work addresses the validation of the first comprehensive TWCCSN2 database for steroids. First, its long-term robustness was evaluated (i.e., a year and a half after database generation; Synapt G2-S instrument; bias within ±1.0% for 157 ions, 95.7% of the total ions). It was further cross-validated by three external laboratories, including two different TWIMS platforms (i.e., Synapt G2-Si and two Vion IMS QToF; bias within the threshold of ±2.0% for 98.8, 79.9, and 94.0% of the total ions detected by each instrument, respectively). Finally, a cross-laboratory TWCCSN2 database was built for 87 steroids (142 ions). The cross-laboratory database consists of average TWCCSN2 values obtained by the four TWIMS instruments in triplicate measurements. In general, lower deviations were observed between TWCCSN2 measurements and reference values when the cross-laboratory database was applied as a reference instead of the single-laboratory database. Relative standard deviations below 1.5% were observed for interlaboratory measurements (<1.0% for 85.2% of ions) and bias between average values and TWCCSN2 measurements was within the range of ±1.5% for 96.8% of all cases. In the context of this interlaboratory study, this threshold was also suitable for TWCCSN2 measurements of steroid metabolites in calf urine. Greater deviations were observed for steroid sulfates in complex urine samples of adult bovines, showing a slight matrix effect. The implementation of a scoring system for the application of the CCS descriptor in peak annotation is also discussed