Many environmental mutagens, including polyaromatic compounds are present in surface waters, often in complex mixtures and at low concentrations. The present study provides and applies a novel, integrated approach to isolate polyaromatic mutagens in river water using a sample from the River Elbe. The sample was taken downstream of industrial discharges using blue rayon (BR) as a passive sampler that selectively adsorbs polyaromatic compounds and was subjected to effect-directed fractionation in order to characterise the compounds causing the detected effect(s). The procedure relies on three complementary fractionation steps, the Ames fluctuation assay with strains TA98, YG1024 and YG1041 with and without S9 activation and analytical screening. Several mutagenic fractions were isolated by combining mutagenicity testing with fractionation. The enhanced mutagenicity in the nitroreductase and/or O-acetyltransferase overexpressing strains YG1024 and YG1041 strains suggested amino- and/or nitro-compounds causing mutagenicity in several fractions. Analytical screening of mutagenic fractions with LC-HRMS/MS provided a list of molecular formulas typically containing one to ten nitrogen and at least two oxygen atoms supporting the presence of amino and nitro-compounds in the mutagenic fractions.
Due to the production and use of a multitude of chemicals in modern society, waters, sediments, soils and biota may be contaminated
with numerous known and unknown chemicals that may cause adverse effects on ecosystems and human health. Effect-directed analysis
(EDA), combining biotesting, fractionation and chemical analysis, helps to identify hazardous compounds in complex environmental
mixtures. Confirmation of tentatively identified toxicants will help to avoid artefacts and to establish reliable cause–effect
relationships. A tiered approach to confirmation is suggested in the present paper. The first tier focuses on the analytical
confirmation of tentatively identified structures. If straightforward confirmation with neat standards for GC–MS or LC–MS
is not available, it is suggested that a lines-of-evidence approach is used that combines spectral library information with
computer-based structure generation and prediction of retention behaviour in different chromatographic systems using quantitative
structure–retention relationships (QSRR). In the second tier, the identified toxicants need to be confirmed as being the cause
of the measured effects. Candidate components of toxic fractions may be selected based, for example, on structural alerts.
Quantitative effect confirmation is based on joint effect models. Joint effect prediction on the basis of full concentration–response
plots and careful selection of the appropriate model are suggested as a means to improve confirmation quality. Confirmation
according to the Toxicity Identification Evaluation (TIE) concept of the US EPA and novel tools of hazard identification help
to confirm the relevance of identified compounds to populations and communities under realistic exposure conditions. Promising
tools include bioavailability-directed extraction and dosing techniques, biomarker approaches and the concept of pollution-induced
community tolerance (PICT).
Figure Toxicity confirmation in EDA as a tiered approach 相似文献
Pooled quality controls (QCs) are usually implemented within untargeted methods to improve the quality of datasets by removing features either not detected or not reproducible. However, this approach can be limiting in exposomics studies conducted on groups of exposed and nonexposed subjects, as compounds present at low levels only in exposed subjects can be diluted and thus not detected in the pooled QC. The aim of this work is to develop and apply an untargeted workflow for human biomonitoring in urine samples, implementing a novel separated approach for preparing pooled quality controls. An LC-MS/MS workflow was developed and applied to a case study of smoking and non-smoking subjects. Three different pooled quality controls were prepared: mixing an aliquot from every sample (QC-T), only from non-smokers (QC-NS), and only from smokers (QC-S). The feature tables were filtered using QC-T (T-feature list), QC-S, and QC-NS, separately. The last two feature lists were merged (SNS-feature list). A higher number of features was obtained with the SNS-feature list than the T-feature list, resulting in identification of a higher number of biologically significant compounds. The separated pooled QC strategy implemented can improve the nontargeted human biomonitoring for groups of exposed and nonexposed subjects. 相似文献
Sediment cores provide a valuable record of historical contamination, but so far, new analytical techniques such as high-resolution mass spectrometry (HRMS) have not yet been applied to extend target screening to the detection of unknown contaminants for this complex matrix. Here, a combination of target, suspect, and nontarget screening using liquid chromatography (LC)-HRMS/MS was performed on extracts from sediment cores obtained from Lake Greifensee and Lake Lugano located in the north and south of Switzerland, respectively. A suspect list was compiled from consumption data and refined using the expected method coverage and a combination of automated and manual filters on the resulting measured data. Nontarget identification efforts were focused on masses with Cl and Br isotope information available that exhibited mass defects outside the sample matrix, to reduce the effect of analytical interferences. In silico methods combining the software MOLGEN-MS/MS and MetFrag were used for direct elucidation, with additional consideration of retention time/partitioning information and the number of references for a given substance. The combination of all available information resulted in the successful identification of three suspect (chlorophene, flufenamic acid, lufenuron) and two nontarget compounds (hexachlorophene, flucofuron), confirmed with reference standards, as well as the tentative identification of two chlorophene congeners (dichlorophene, bromochlorophene) that exhibited similar time trends through the sediment cores. This study demonstrates that complementary application of target, suspect, and nontarget screening can deliver valuable information despite the matrix complexity and provide records of historical contamination in two Swiss lakes with previously unreported compounds. 相似文献
High-resolution tandem mass spectrometry (HRMS2) with electrospray ionization is frequently applied to study polar organic molecules such as micropollutants. Fragmentation provides structural information to confirm structures of known compounds or propose structures of unknown compounds. Similarity of HRMS2 spectra between structurally related compounds has been suggested to facilitate identification of unknown compounds. To test this hypothesis, the similarity of reference standard HRMS2 spectra was calculated for 243 pairs of micropollutants and their structurally related transformation products (TPs); for comparison, spectral similarity was also calculated for 219 pairs of unrelated compounds. Spectra were measured on Orbitrap and QTOF mass spectrometers and similarity was calculated with the dot product. The influence of different factors on spectral similarity [e.g., normalized collision energy (NCE), merging fragments from all NCEs, and shifting fragments by the mass difference of the pair] was considered. Spectral similarity increased at higher NCEs and highest similarity scores for related pairs were obtained with merged spectra including measured fragments and shifted fragments. Removal of the monoisotopic peak was critical to reduce false positives. Using a spectral similarity score threshold of 0.52, 40% of related pairs and 0% of unrelated pairs were above this value. Structural similarity was estimated with the Tanimoto coefficient and pairs with higher structural similarity generally had higher spectral similarity. Pairs where one or both compounds contained heteroatoms such as sulfur often resulted in dissimilar spectra. This work demonstrates that HRMS2 spectral similarity may indicate structural similarity and that spectral similarity can be used in the future to screen complex samples for related compounds such as micropollutants and TPs, assisting in the prioritization of non-target compounds.
Structure generation and mass spectral classifiers have been incorporated into a new method to gain further information from low-resolution GC-MS spectra and subsequently assist in the identification of toxic compounds isolated using effect-directed fractionation. The method has been developed for the case where little analytical information other than the mass spectrum is available, common, for example, in effect-directed analysis (EDA), where further interpretation of the mass spectra is necessary to gain additional information about unknown peaks in the chromatogram. Structure generation from a molecular formula alone rapidly leads to enormous numbers of structures; hence reduction of these numbers is necessary to focus identification or confirmation efforts. The mass spectral classifiers and structure generation procedure in the program MOLGEN-MS was enhanced by including additional classifier information available from the NIST05 database and incorporation of post-generation ‘filtering criteria’. The presented method can reduce the number of possible structures matching a spectrum by several orders of magnitude, creating much more manageable data sets and increasing the chance of identification. Examples are presented to show how the method can be used to provide ‘lines of evidence’ for the identity of an unknown compound. This method is an alternative to library search of mass spectra and is especially valuable for unknowns where no clear library match is available. 相似文献
