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Route Determination of Sulfur Mustard Using Nontargeted Chemical Attribution Signature Screening.

ABSTRACT: Route determination of sulfur mustard was accomplished through comprehensive nontargeted screening of chemical attribution signatures. Sulfur mustard samples prepared via 11 different synthetic routes were analyzed using gas chromatography/high-resolution mass spectrometry. A large number of compounds were detected, and multivariate data analysis of the mass spectrometric results enabled the discovery of route-specific signature profiles. The performance of two supervised machine learning algorithms for retrospective synthetic route attribution, orthogonal partial least squares discriminant analysis (OPLS-DA) and random forest (RF), were compared using external test sets. Complete classification accuracy was achieved for test set samples (2/2 and 9/9) by using classification models to resolve the one-step routes starting from ethylene and the thiodiglycol chlorination methods used in the two-step routes. Retrospective determination of initial thiodiglycol synthesis methods in sulfur mustard samples, following chlorination, was more difficult. Nevertheless, the large number of markers detected using the nontargeted methodology enabled correct assignment of 5/9 test set samples using OPLS-DA and 8/9 using RF. RF was also used to construct an 11-class model with a total classification accuracy of 10/11. The developed methods were further evaluated by classifying sulfur mustard spiked into soil and textile matrix samples. Due to matrix effects and the low spiking level (0.05% w/w), route determination was more challenging in these cases. Nevertheless, acceptable classification performance was achieved during external test set validation: chlorination methods were correctly classified for 12/18 and 11/15 in spiked soil and textile samples, respectively.

SUBMITTER: Hojer Holmgren K

PROVIDER: S-EPMC8041246 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Sulfur mustard (SM) is a potent vesicant that targets epithelial cells and tissues. Most vesicant research has been performed using bona fide SM; however, some studies have used simulants, most notably half mustard (2-chloroethyl ethylsulfide; CEES) and nitrogen mustard (mechlorethamine; NM). Although CEES and NM have similarities to SM and can cause vesication, there are distinct differences in the chemical structures and physical properties of these compounds that may impact their toxic effects. Microarray analysis of cultured primary human epidermal keratinocytes (HEK) exposed to each of these vesicants was performed to directly compare the transcriptional responses induced by these vesicants. HEK were exposed in triplicate to concentrations ranging from 0-1000 µM for SM and NM and 0-4000 µM for CEES. Cells were harvested at 1, 2, 4, 8, 16, and 24 h and the RNA isolated for microarray analysis. Transcriptional responses were phenotypically anchored to cell morphology. The dataset was filtered by exposure and timepoint, and an analysis of variance was performed using dose as the factor. The top 500 genes ranked by p-value were analyzed using gene ontology algorithms to identify biological pathways significantly affected by each vesicant. At 2 h post-exposure, p53 signaling, Erk/MAPK signaling, and BMP signaling were significantly affected by all three vesicants. At 4 h post-exposure, p53 signaling , B cell activating factor, and glucocorticoid receptor signaling were significantly affected by all three vesicants. At 8 h post-exposure, there were no significant pathways commonly affected by all three vesicants. These results suggest that, although there are similarities in the transcriptional responses to each of these vesicants, the transcriptional responses appear to differ over time. Thus, extrapolation of results obtained with one vesicant to other vesicants may be complex and may have important implications for the development of vesicant therapeutics.

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Route Determination of Sulfur Mustard Using Nontargeted Chemical Attribution Signature Screening.

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