Shotgun metabolomic approach based on mass spectrometry for hepatic mitochondria of mice under arsenic exposure

García-Sevillano, M. A.; García-Barrera, Tamara; Navarro, Francisco; Montero-Lobato, Zaida; Gómez-Ariza, José Luis

doi:10.1007/s10534-015-9837-9

Cited by 23 publications

(9 citation statements)

References 21 publications

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“…The data from the present study suggest that these differences in iAs metabolism as indicated by the iAs arsenical proportions may also be associated with metabolomic differences in the neonate. 45 …”

Section: Discussionmentioning

confidence: 99%

Neonatal Metabolomic Profiles Related to Prenatal Arsenic Exposure

Laine¹,

Bailey²,

Olshan³

et al. 2016

Environ. Sci. Technol.

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Prenatal inorganic arsenic (iAs) exposure is associated with health effects evident at birth and later in life. An understanding of the relationship between prenatal iAs exposure and alterations in the neonatal metabolome could reveal critical molecular modifications, potentially underpinning disease etiologies. In this study, nuclear magnetic resonance (NMR) spectroscopy-based metabolomic analysis was used to identify metabolites in neonate cord serum associated with prenatal iAs exposure in participants from the Biomarkers of Exposure to ARsenic (BEAR) pregnancy cohort, in Gómez Palacio, Mexico. Through multivariable linear regression, ten cord serum metabolites were identified as significantly associated with total urinary iAs and/or iAs metabolites, measured as %iAs, %monomethylated arsenicals (MMAs), and % dimethylated arsenicals (DMAs). A total of 17 metabolites were identified as significantly associated with total iAs and/or iAs metabolites in cord serum. These metabolites are indicative of changes in important biochemical pathways such as vitamin metabolism, the citric acid (TCA) cycle, and amino acid metabolism. These data highlight that maternal biotransformation of iAs and neonatal levels of iAs and its metabolites are associated with differences in neonate cord metabolomic profiles. The results demonstrate the potential utility of metabolites as biomarkers/indicators of in utero environmental exposure.

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Section: Discussionmentioning

confidence: 99%

Neonatal Metabolomic Profiles Related to Prenatal Arsenic Exposure

Laine¹,

Bailey²,

Olshan³

et al. 2016

Environ. Sci. Technol.

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“…This demonstrates that MRM-profiling can measure more analytes in a single injection than traditional LC-MS methods which is advantageous to metabolomics discovery methods. 2, 8 Furthermore, a few of the transitions which do have RT and exact mass were not found in the databases. Identification is not needed for classifying with MRM-profiling.…”

Section: Resultsmentioning

confidence: 99%

“…They are typically performed by high resolution mass spectrometry (HRMS) to provide accurate masses for molecular formula and/or by using data dependent product ion scans. 2, 7, 8 Data dependent product ion scan methods utilize algorithms which fragment peaks over a certain threshold (counts). Therefore, these methods are often biased toward peaks with the highest intensity, which causes data to be lost.…”

Section: Introductionmentioning

confidence: 99%

Multiple reaction monitoring (MRM)-profiling with biomarker identification by LC-QTOF to characterize coronary artery disease

Yannell

Ferreira

Tichy

et al. 2018

Analyst

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Metabolite profiling by mass spectrometry (MS) is an area of interest for disease diagnostics, biomarker discovery, and therapeutic evaluation. A recently developed approach, multiple reaction monitoring (MRM)-profiling, searches for metabolites with precursor (Prec) and neutral loss (NL) scans in a representative sample and creates a list of ion transitions. These are then used in an MRM method for fast screening of individual samples and discrimination between healthy and diseased. A large variety of functional groups are considered and all signals discovered are recorded in the individual samples, making this a largely unsupervised method. MRM-profiling is described here and then demonstrated with data for over 900 human plasma coronary artery disease (CAD) samples. Representative pooled samples for each condition were interrogated using a library of over a hundred Prec and NL scans on a triple quadrupole MS. The data from the Prec and NL experiments were converted into ion transitions, initially some 1266 transitions. Each ion transition was examined in the individual samples on a time scale of milliseconds per transition, which allows for rapid screening of large sample sets (<5 days for 1000 samples). Use of univariate and multivariate statistics allowed classification of the sample set with high accuracy. The metabolite profiles classified the CAD female, CAD male, and peripheral artery disease (PAD) samples relative to controls with an accuracy of 90%, 78%, and 85%, respectively. The compounds responsible for informative ion transitions were identified by chromatography and high resolution MS; some have been previously reported and found to be associated with coronary artery disease metabolism, indicating that the methodology generates a meaningful metabolite profile while being faster than traditional methodologies.

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“…It causes amino acids degradation and perturbations in creatine levels [56]. These are probably the main mechanisms for the decreasing motility and velocity in Daphnia.…”

Section: Discussionmentioning

confidence: 99%

Arsenic Pollution Measured with an online Monitoring System using Daphnia

Erzinger¹

2017

Open J Environ Biol

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Arsenic is a common pollutant in many water reservoirs around the world and is the cause of human mortality in many countries. The microcrustacean Daphnia can be cultured easily and is sensitive to many toxic substances including As. This bioindicator is the basis of the Daphniatox instrument which uses computerized image analysis of swimming organisms in real time. Fourteen endpoints are evaluated including motility, swimming velocity, orientation with respect to light or gravity as well as several cell size and form parameters. Using automatic track analysis of a large number of organisms warrants high statistical signifi cance. In a vertical swimming fl ask Daphnia shows pronounced gravitaxis moving upward and downward while in a horizontal fl ask the organisms swim in random directions. Exposure for up to 72 h to 0-10 mg/L NaAsO 2 (corresponding to 0-77.5 μM As) according to the standard NBR 12713 protocol showed an EC 50 value of 5.97 mg/L for motility after an exposure time of 7 h and 4.82 mg/L after 26 h. Comparably, the EC 50 value for velocity was 5.32 mg/L after an exposure time of 7 h and after 26 h it was 3.05 mg/L. As expected, the length of the organisms did not change over the exposure time because of their rigid exoskeleton, but the circularity which corresponds to the area divided by the perimeter squared decreased which is interpreted to be due to a release of water. The results indicate that this method provides a reliable, fast and inexpensive test for arsenic toxicity in drinking water from wells and reservoirs.

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Shotgun metabolomic approach based on mass spectrometry for hepatic mitochondria of mice under arsenic exposure

Cited by 23 publications

References 21 publications

Neonatal Metabolomic Profiles Related to Prenatal Arsenic Exposure

Neonatal Metabolomic Profiles Related to Prenatal Arsenic Exposure

Multiple reaction monitoring (MRM)-profiling with biomarker identification by LC-QTOF to characterize coronary artery disease

Arsenic Pollution Measured with an online Monitoring System using Daphnia

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