2014
DOI: 10.1002/rcm.7066
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Identification of xenobiotic metabolites from biological fluids using flow injection analysis high‐resolution mass spectrometry and post‐acquisition data filtering

Abstract: The use of FIA-HRMS in combination with dedicated bio-informatics data processing is shown to be an efficient approach for the rapid detection of metabolites in biological fluids. This is a very promising high-throughput approach for rapid characterization of the exposure status to xenobiotics.

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Cited by 9 publications
(12 citation statements)
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“…This spectrum was obtained in previous work using the DI-HRMS approach without either prior sample cleanup or chromatographic separation. [10] Seven metabolites of vinclozolin were detected: M1, M4, M5 and M6 as non-conjugated metabolites, the sulfate conjugate of M5, and glucuronide conjugates of M4 and of M5 (Table 1). However, such a manual search is time-consuming and cannot be easily applied for large size and complex spectral data, especially when there are low-abundance metabolites and presence of interfering ions with m/z values close to that of metabolites.…”
Section: Resultsmentioning
confidence: 99%
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“…This spectrum was obtained in previous work using the DI-HRMS approach without either prior sample cleanup or chromatographic separation. [10] Seven metabolites of vinclozolin were detected: M1, M4, M5 and M6 as non-conjugated metabolites, the sulfate conjugate of M5, and glucuronide conjugates of M4 and of M5 (Table 1). However, such a manual search is time-consuming and cannot be easily applied for large size and complex spectral data, especially when there are low-abundance metabolites and presence of interfering ions with m/z values close to that of metabolites.…”
Section: Resultsmentioning
confidence: 99%
“…Both flow injection analysis (FIA) and the LC/MS approach were performed as described in previous work. [10] MS/MS experiments were performed on both the monoisotopic and (M + 2) isotope peaks of vinclozolin metabolites using CID (collision-induced dissociation) conditions in the linear ion trap (LTQ) device. The following parameters were used: isolation width of precursor ions of 2 u, activation time of 30 ms, and normalized collision energy of about 20% (arbitrary units).…”
Section: Methodsmentioning
confidence: 99%
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“…One advantage of MS-based metabolomics is the ability to detect both endogenous and exogenous (i.e., xenobiotic) chemicals in the available biological matrix, including those with low abundances [32]. Indeed, xenobiotic metabolites have frequently been measured with this technique in biofluids such as fish bile and plasma [3], as well as rat urine [33], but have not commonly (if ever) been reported using fish skin mucus. As discussed in the section Predicting hepatic gene expression with skin mucus metabolome changes, the up-regulation of ugt1a1 in the present study is indicative of phase II transformations of several xenobiotics, including BPA, which is nearly ubiquitous in the environment and was detected in the effluent by Cavallin et al [9].…”
Section: Monitoring Phase II Metabolism Of Contaminants In Skin Mucusmentioning
confidence: 99%