TY - JOUR
T1 - Urinary exposure marker discovery for toxicants using ultra-high pressure liquid chromatography coupled with Orbitrap high resolution mass spectrometry and three untargeted metabolomics approaches
AU - Hsu, Jen Yi
AU - Hsu, Jing Fang
AU - Chen, Yet Ran
AU - Shih, Chia Lang
AU - Hsu, Yi Sheng
AU - Chen, Yi Jen
AU - Tsai, Shu Han
AU - Liao, Pao Chi
N1 - Funding Information:
This work was supported by grants ( NSC97-2113-M-006-005-MY3 MOST103-2113-M-006-003-MY3 , NSC100-2113-M-006-002-MY3 and NSC97-2113-M-006-005-MY3 ) from the National Science Council of Taiwan .
Publisher Copyright:
© 2016 Elsevier B.V.
PY - 2016/10/5
Y1 - 2016/10/5
N2 - Human biomonitoring is the assessment of actual internal contamination of chemicals by measuring exposure markers, chemicals or their metabolites, in human urine, blood, serum, and other body fluids. However, the metabolism of chemicals within an organism is extremely complex. Therefore, the identification of metabolites is often difficult and laborious. Several untargeted metabolomics methods have been developed to perform objective searching/filtering of accurate-mass-based LC-MS data to facilitate metabolite identification. In this study, three metabolomics data processing approaches were used for chemical exposure marker discovery in urine with an LTQ-Orbitrap high-resolution mass spectrometry (HRMS) dataset; di-isononyl phthalate (DINP) was used as an example. The data processing techniques included the SMAIT, mass defect filtering (MDF), and XCMS Online. Sixteen, 83, and 139 probable DINP metabolite signals were obtained using the SMAIT, MDF, and XCMS procedures, respectively. Fourteen probable metabolite signals mined simultaneously by the three metabolomics approaches were confirmed as DINP metabolites by structural information provided by LC-MS/MS. Among them, 13 probable metabolite signals were validated as exposure-related markers in a rat model. Six (m/z 319.155, 361.127, 373.126, 389.157, 437.112 and 443.130) of the 13 exposure-related DINP metabolite signals have not previously been reported in the literature. Our data indicate that SMAIT provided an efficient method to discover effectively and systematically urinary exposure markers of toxicant. The DINP metabolism information can provide valuable information for further investigations of DINP toxicity, toxicokinetics, exposure assessment, and human health effects.
AB - Human biomonitoring is the assessment of actual internal contamination of chemicals by measuring exposure markers, chemicals or their metabolites, in human urine, blood, serum, and other body fluids. However, the metabolism of chemicals within an organism is extremely complex. Therefore, the identification of metabolites is often difficult and laborious. Several untargeted metabolomics methods have been developed to perform objective searching/filtering of accurate-mass-based LC-MS data to facilitate metabolite identification. In this study, three metabolomics data processing approaches were used for chemical exposure marker discovery in urine with an LTQ-Orbitrap high-resolution mass spectrometry (HRMS) dataset; di-isononyl phthalate (DINP) was used as an example. The data processing techniques included the SMAIT, mass defect filtering (MDF), and XCMS Online. Sixteen, 83, and 139 probable DINP metabolite signals were obtained using the SMAIT, MDF, and XCMS procedures, respectively. Fourteen probable metabolite signals mined simultaneously by the three metabolomics approaches were confirmed as DINP metabolites by structural information provided by LC-MS/MS. Among them, 13 probable metabolite signals were validated as exposure-related markers in a rat model. Six (m/z 319.155, 361.127, 373.126, 389.157, 437.112 and 443.130) of the 13 exposure-related DINP metabolite signals have not previously been reported in the literature. Our data indicate that SMAIT provided an efficient method to discover effectively and systematically urinary exposure markers of toxicant. The DINP metabolism information can provide valuable information for further investigations of DINP toxicity, toxicokinetics, exposure assessment, and human health effects.
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U2 - 10.1016/j.aca.2016.07.032
DO - 10.1016/j.aca.2016.07.032
M3 - Article
C2 - 27639145
AN - SCOPUS:84989873669
SN - 0003-2670
VL - 939
SP - 73
EP - 83
JO - Analytica Chimica Acta
JF - Analytica Chimica Acta
ER -