Nontargeted homologue series extraction from hyphenated high resolution mass spectrometry data

Loos, Martin; Singer, Heinz

doi:10.1186/s13321-017-0197-z

Cited by 53 publications

(52 citation statements)

References 45 publications

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“…Unidentified masses were tested for the presence of 37 Cl and 37 Cl 2 isotopes with the pattern.search() function in the R package nontarget 46 with retention time tolerance of ± 10 s and mass accuracy of ± 5 ppm.…”

Section: Methodsmentioning

confidence: 99%

High-resolution metabolomics of occupational exposure to trichloroethylene

et al. 2016

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Background: Occupational exposure to trichloroethylene (TCE) has been linked to adverse health outcomes including non-Hodgkin’s lymphoma and kidney and liver cancer; however, TCE’s mode of action for development of these diseases in humans is not well understood. Methods: Non-targeted metabolomics analysis of plasma obtained from 80 TCE-exposed workers [full shift exposure range of 0.4 to 230 parts-per-million of air (ppma)] and 95 matched controls were completed by ultra-high resolution mass spectrometry. Biological response to TCE exposure was determined using a metabolome-wide association study (MWAS) framework, with metabolic changes and plasma TCE metabolites evaluated by dose-response and pathway enrichment. Biological perturbations were then linked to immunological, renal and exposure molecular markers measured in the same population. Results: Metabolic features associated with TCE exposure included known TCE metabolites, unidentifiable chlorinated compounds and endogenous metabolites. Exposure resulted in a systemic response in endogenous metabolism, including disruption in purine catabolism and decreases in sulphur amino acid and bile acid biosynthesis pathways. Metabolite associations with TCE exposure included uric acid (β = 0.13, P-value = 3.6 × 10−5), glutamine (β = 0.08, P-value = 0.0013), cystine (β = 0.75, P-value = 0.0022), methylthioadenosine (β = −1.6, P-value = 0.0043), taurine (β = −2.4, P-value = 0.0011) and chenodeoxycholic acid (β = −1.3, P-value = 0.0039), which are consistent with known toxic effects of TCE, including immunosuppression, hepatotoxicity and nephrotoxicity. Correlation with additional exposure markers and physiological endpoints supported known disease associations. Conclusions: High-resolution metabolomics correlates measured occupational exposure to internal dose and metabolic response, providing insight into molecular mechanisms of exposure-related disease aetiology.

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Section: Methodsmentioning

confidence: 99%

High-resolution metabolomics of occupational exposure to trichloroethylene

et al. 2016

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“…N,34 S,37 Cl and 81 Br) with a rule-based algorithm. Homologue series detection[35] was carried out for four or more consecutive mass differences corresponding to CH 2 , CH 2 O, C 2 H 4 O, C 3 H 6 O, C 2 H 6 SiO, CF 2 and C 2 H 4 units for singly and doubly charged ions. Peaks were finally grouped into components, i.e., the monoisotopic peak and its associated isotope or adduct peaks representing an individual chemical compound.…”

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confidence: 99%

Prioritising site-specific micropollutants in surface water from LC-HRMS non-target screening data using a rarity score

et al. 2019

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Background: Current compound prioritisation and monitoring approaches within Europe focus mainly on widely occurring priority and river basin specific pollutants but may overlook site-specific contamination from local emission sources. Thus, we propose a robust and semiautomated approach for the identification of site-specific chemicals and a prioritisation of water bodies with specific contamination based on non-target screening data from liquid chromatography coupled to high-resolution mass spectrometry. Results: For prioritisation of site-specific contaminants, we calculated rarity scores for all peaks occurring in a set of 31 surface water samples, which combine the maximum signal intensity of a peak in a dataset with its frequency of occurrence in that dataset in one single number. These were a robust measure without the need to address the problems of missing data in more sophisticated multivariate statistical methods. For our dataset, site-specific compounds were defined for rarity scores > 1000, and the studied 31 sites showed a huge difference in the number of such peaks (0-91 in positive and 0-48 in negative ion mode). Together with isotopologue detection, the evaluation of mass defects and the occurrence of homologue series, which all could be obtained from automated data processing, a more detailed characterisation of these site-specific contaminations was possible. For three selected sites with a high number of site-specific peaks, novel or unexpected compounds could be identified, which stem from specific usage or (former) industrial production upstream of these sites. Conclusions and outlook: The proposed approach allows for a rapid screening of large non-target screening datasets for site-specific contaminants, the prioritisation of sites with such a specific contamination and the subsequent identification of these compounds. Thus, the risk of overlooking possibly hazardous chemicals (including unknowns) which are not covered in conventional monitoring and prioritisation schemes is reduced.

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“…PFAS compounds have negative mass defects ( Figure 6) due to their preponderance of fluorine atoms, and polyfluorinated compounds have positive, but substantially smaller mass defects than homologous organic materials 31,34 . A second method filtering step is to identify homologous series containing repeating units common to PFAS species, such as CF 2 or CF 2 O. Identifying these can be done using Kendrick Mass defect plots 17,36 , or software packages such as R's nontarget package 35 (Figure 7).…”

Section: Representative Resultsmentioning

confidence: 99%

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

McCord

Strynar²

2019

JoVE

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Historical and emerging per-and polyfluoroalkyl substances (PFASs) have garnered significant interest from the public and government agencies from the local to federal levels. The continuing evolution of PFAS chemistries presents a challenge to the environmental monitoring, where ongoing development of targeted methods necessarily lags the discovery of new chemical compounds. There is a need, therefore, to have forward-looking methodologies that can detect emerging and unexpected compounds, monitor these species over time, and resolve details of their chemical structure to enable future work in human health. To this end, non-targeted analysis by high-resolution mass spectrometry offers a broad base detection approach that can be combined with almost any sample preparation scheme and provides significant capabilities for compound identification after detection. Herein, we describe a solid-phase extraction (SPE) based sample concentration method tuned for shorter chain and more hydrophilic PFAS chemistries, such as per fluorinated ether acids and sulfonates, and describe analysis of samples prepared in this fashion in both targeted and non-targeted modes. Targeted methods provide superior quantification when reference standards are available but are intrinsically limited to expected compounds when performing analysis. In contrast, a non-targeted approach can identify the presence of unexpected compounds and provide some information about their chemical structure. Information about chemical features can be used to correlate compounds across sample locations and track abundance and occurrence over time.

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Nontargeted homologue series extraction from hyphenated high resolution mass spectrometry data

Cited by 53 publications

References 45 publications

High-resolution metabolomics of occupational exposure to trichloroethylene

High-resolution metabolomics of occupational exposure to trichloroethylene

Prioritising site-specific micropollutants in surface water from LC-HRMS non-target screening data using a rarity score

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

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