1H NMR-Based Metabolomic Analysis of Sub-Lethal Perfluorooctane Sulfonate Exposure to the Earthworm, Eisenia fetida, in Soil

Abstract

1H NMR-based metabolomics was used to measure the response of Eisenia fetida earthworms after exposure to sub-lethal concentrations of perfluorooctane sulfonate (PFOS) in soil. Earthworms were exposed to a range of PFOS concentrations (five, 10, 25, 50, 100 or 150 mg/kg) for two, seven and fourteen days. Earthworm tissues were extracted and analyzed by 1H NMR. Multivariate statistical analysis of the metabolic response of E. fetida to PFOS exposure identified time-dependent responses that were comprised of two separate modes of action: a non-polar narcosis type mechanism after two days of exposure and increased fatty acid oxidation after seven and fourteen days of exposure. Univariate statistical analysis revealed that 2-hexyl-5-ethyl-3-furansulfonate (HEFS), betaine, leucine, arginine, glutamate, maltose and ATP are potential indicators of PFOS exposure, as the concentrations of these metabolites fluctuated significantly. Overall, NMR-based metabolomic analysis suggests elevated fatty acid oxidation, disruption in energy metabolism and biological membrane structure and a possible interruption of ATP synthesis. These conclusions obtained from analysis of the metabolic profile in response to sub-lethal PFOS exposure indicates that NMR-based metabolomics is an excellent discovery tool when the mode of action (MOA) of contaminants is not clearly defined.

Analysis of Eisenia fetida earthworm responses to sub-lethal C60 nanoparticle exposure using 1H-NMR based metabolomics

“…This is likely due to the different modes of exposure between the soil and contact tests. Similar differences between contact and soil exposures were reported by Lankadurai et al (2013b) after exposure of E. fetida earthworms to sub-lethal perfluorooctane sulfonate.…”

“…We also exposed E. fetida to C 60 nanoparticle concentrations of 300 and 3,000 mg/kg with exposure times of 2, 7 and 14 days in soil exposure tests. Our first objective was to determine if NMR-based metabolomics is able to detect significant metabolic changes in response to sub-lethal C 60 nanoparticle exposure via both soil and contact tests as previous studies have noted differences due to the mode of exposure (Lankadurai et al, 2012(Lankadurai et al, , 2013b. In addition, we also identified bioindicators of C 60 nanoparticle exposure and to delineate the MOA.…”

1H NMR-based metabolomics of Daphnia magna responses after sub-lethal exposure to triclosan, carbamazepine and ibuprofen

“…Partial least squares (PLS) regression analysis was performed in R (v. 3.1.2, The R Foundation, Vienna, Austria) using the Chemometrics package (Filzmoser and Varmuza, 2010) on the binned 1 H NMR spectra generated by the AMIX 3.9.7 statistics tool. PLS-regression was done via the NIPALS PLS algorithm using the normalized bucket intensities from the 1 H NMR spectra as the X matrix of multiple predictors and the exposure concentrations of the three tested contaminants as the Y (response) matrix (Åslund et al, 2011;Lankadurai et al, 2013). PLS models were cross validated using leave-one-out cross validation (Westerhuis et al, 2008;Varmuza and Filzmoser, 2009) and the optimal number of components for each final PLS model was determined by the single cross validation strategy (Westerhuis et al, 2008).…”

“…The PC3 vs PC4 scores plot also showed separation of triclosan exposed daphnids from the control that was not related to exposure concentration, with a statistically significant (p < 0.05) separation of the 100 µg/L exposure along PC3 ( Figure S1A in Supplementary Material). PLSregression models ( Figure 2) were developed to determine the strength and significance of the correlation between the metabolic profile and the triclosan exposure concentration (Lankadurai et al, 2013). Triclosan exposure produced a PLS-regression model that suggested a weak but significant linear relationship between the D. magna metabolic profile and the triclosan exposure concentration (cross-validated PLS-regression with 9 components, R 2 X=0.98, R 2 Y=0.78, Q 2 Y=0.34, P=9x10 -4 ; Figure 2A).…”

Entometabolomics: applications of modern analytical techniques to insect studies

“…There are already some excellent reviews of current uses of metabolomic technologies, along with an extensive background to the field and its history (Nicholson & Wilson, ; Rochfort, ; Lindon & Nicholson, ; Heather et al., ), and several have focused on the use of metabolomics in particular fields of study, such as ecology (ecometabolomics) (Bundy et al., ; Jones et al., ; Lankadurai et al., ). In this review, we focus on metabolomics studies as they have been, and can be, applied to insect study systems.…”