1H NMR metabonomic study of rat response to tri-phenyl phosphate and tri-butyl phosphate exposure

Abstract

The industrial application of organophosphates provides the opportunity for environmental exposure. While the toxicity of organophosphate compounds has been the target of significant work, studies directed towards the identification of metabolite markers to assess phosphate exposure are more limited. In this study the urine metabolite profiles for rats following single dose exposure to either tributyl phosphate (TBP, 15 mg/kg body weight) or triphenyl phosphate (TPP, 2 and 20 mg/kg body weight) were characterized using proton nuclear magnetic resonance ( 1 H NMR) and orthogonal-partial least squares discriminate analysis (O-PLSDA). Using the developed O-PLSDA models it was possible to clearly identify TBP or TPP exposed animals. The performance of these models was validated using cross validation and permutation testing. Utilizing the variable importance in projection (VIP) coefficients from the O-PLSDA the metabolites that were most responsible for the classification of TBP or TPP exposure were determined. This initial study demonstrates the potential for NMR metabonomic studies for the identification and separation of environmental exposure to organophosphates.

Earthworm Sublethal Responses to Titanium Dioxide Nanomaterial in Soil Detected by 1H NMR Metabolomics

“…44,45 In addition, as it has been suggested that misclassification rates provide a better metric for PLS-DA validation than Q 2 Y, 49 a permutation test (400-fold permutation of the class labels) was performed to obtain the expected distribution of model sensitivity (i.e., the rate of proper earthworm classification), and this was compared to the observed model sensitivity to assess model significance. 38,47,50 Statistical significance was assessed at α = 0.05. Means were reported as the mean value ± standard error unless otherwise noted.…”

1H NMR metabolomics of earthworm responses to polychlorinated biphenyl (PCB) exposure in soil

“…The data were normalized using Probabilistic Quotient Normalization (PQN) to correct for differences in the total NMR signal measured for each sample which can vary with factors such as the mass of tissue extracted (Brown et al 2009(Brown et al , 2010Craig et al 2006;McKelvie et al 2009McKelvie et al , 2010. PQN has been proposed to be a robust normalization method for metabolomic analysis of complex biological mixtures (Dieterle et al 2006) and has been applied in several recent environmental metabolomics studies (Alam et al 2010;Bohus et al 2009;Bundy et al 2008;Hughes et al 2009;Taylor et al 2009). In a test dataset of 24 healthy control earthworms, PQN decreased overall inter-individual metabolic variability in comparison to integral normalization [IN, 'scaled to total intensity', (Craig et al 2006)] and produced a pattern of pair-wise metabolic correlations which more closely matched that observed for quantified metabolite concentrations than did the pattern of pair-wise metabolic correlations calculated using IN data (Whitfield Å slund et al in press).…”

“…An alternative PLS model was also created using only 80% of the data and then used to predict the remaining data in order to simulate how well as PLS model built from this data could predict an external test set. In addition, the significance of each PLS model was estimated through response permutation testing (Alam et al 2010;Eriksson et al 2006; Section S2 in Supplementary Material).…”

Ecometabolomics: optimized NMR‐based method

“…), ecotoxicology (Robertson ; Alam et al . ), animals (Deyrup et al . ) and plant biology (Fiehn et al .…”

“…Metabolomics as a new research approach has been widely used in biomedicine (Nicholson, Lindon & Holmes 1999;Urban et al 2010), ecotoxicology (Robertson 2005;Alam et al 2010), animals (Deyrup et al 2011) and plant biology (Fiehn et al 2000;Weckwerth et al 2004;Scott et al 2010), and its application is increasing in ecological studies (Peñuelas & Sardans 2009a, b;Sardans, Peñuelas & Rivas-Ubach 2011). The metabolome is the entirety of molecules present in an organism as the final expression of its genotype at a particular moment (Fiehn 2002;Peñuelas & Sardans 2009a) and can be considered a molecular picture of biological diversity because each living species has its own metabolic profile (Gromova & Roby 2010).…”