Final Report Summary - METOIL (METABOLOMICS OF TIDAL ORGANISMS TO INDICATE OIL POLLUTION)
Metabolomics is a new research field that evaluates the changes in the metabolite profiles within organisms as a result of normal physiological processes, from onset of disease, or from exposure to environmental pollutants or other stressors. The goal of the METOIL was to understand the metabolomic state of a subject by extracting, identifying and quantifying all the small molecule compounds (metabolites) to assess the toxicological risk and consequences of environmental pollution by oil hydrocarbons. Metabolomic profiles of marine organisms (polychaetes) were studied to determine whether they can be used as pollution indicators and sentinel biosensors in two different species Nereis virens and Nereis diversicolor. The analytical methods implemented to characterise the metabolomes of the study organisms were cutting-edge, powerful, reliable, mainly GC-MS and UHPLC-qTOF-MS. Data pre-processing and advanced chemometric methods were applied to develop a systematic methodology to ascertain how the metabolomes of the study species were affected and the metabolites that mostly determine that trends.
Tissue extraction is a key step, and high-quality and reproducible extractions are essential to the success of metabolomics studies. We have performed an comparison of different tissue extraction techniques with Nereis virens, comparing two different tissue disruption methods (including lyophilisation and wet ragworm), one solvent system (aqueous methanol), two different extraction methods (two-step extraction and pressurized liquid extraction) with exposed and unexposed organisms.
Here, we optimized the extraction strategy for present untargeted LC-MS metabolomics and GC-MS based metabolomics of marine polychaetes. All eight combinations were then compared by both analytical platforms.
Untargeted LC-MS is a robust and reliable technique for metabolomics applications. LC-MS metabolic fingerprinting approaches cover wide retention time and m/z ranges and generate extremely large, multivariate sets of data—typically more than 107 data-points per chromatographic run. However, the use of UHPLC-qTOF-MS in this particular case, did not turn out to be the preferred method due to large artifacts in the chromatography data (viz. retention time shifts in the chromatograms) that could not be sufficient corrected for although different alignment methods were tested.
GC-MS has been described as one gold standard for metabolomics studies, although it is biased against non-volatile, high-MW metabolites and requires the conversion of these compounds to volatile and thermal stables derivates. Due to wide range of chemical metabolites in these organisms, two-stage derivatization was employed to the simultaneous determination of organic acids, fatty acids, carbohydrates and amino acids.
The results were evaluated by both overall multivariate clustering approaches as well as distributions over individual metabolites/metabolite features of coefficient of variation and yield for both analytical platforms. Overall, we concluded that two-step extraction with 80% methanol solution on freeze dried ragworm was a good trade-off, showing a high extraction efficiency based of the yield and reproducibility (see Figure 1). Although it is important to note that the definition of the apparent “best” method depended on which analytical platform was used to evaluate the results.
These strategies could allow to discriminate between crude oil exposed and unexposed worms. However, an oil contamination dependency was too small compare to other sources of random variation (e.g. biological variability). Besides marine polychaetes exhibited significant perturbations in their metabolite profile after their exposure to different salinity levels. Despite an inevitable degree of confounding between, physicochemical biological variability al, and chemical stresses from oil hydrocarbon pollution, it was possible to identify metabolites involved in each type of stress condition. For instance, some amino acids (glycine, L-proline, alanine), carbohydrates (myo-inositol) and some unknown metabolites for salinity stress and some amino acids (L-valine, L-threonine, L-proline, L-lysine aspartic acid), some fatty acids (oleic acid, palmitoleic acid, propanoic acid) and some unknown metabolites for oil stress conditions.
Additional research using a larger range of oil concentration is required to fully understand the concentration and oil hydrocarbon dependency of marine polychaetes responses to oil contamination exposure.
METOIL was highly interdisciplinary as it involved analytical chemists, biologist, environmental metabolomics, ecotoxicological risk and chemometricians. It is worth noting that METOIL was applied to monitor the environmental situation at Bredemade Hage shoreline (Denmark), which was contaminated by heavy bunker oil during the 2001 Baltic Carrier oil spill and it can be applied to monitor other affected areas strongly affected by chronic hydrocarbon spillages caused by the intense traffic of oil tankers navigating. METOIL is relevant to protect intertidal areas which are relevant for seafood and seaweed growing and collection which are intended for human consumption. This study can be carried out using other types of marine organism (viz. seaweed, mussel, etc.).
Tissue extraction is a key step, and high-quality and reproducible extractions are essential to the success of metabolomics studies. We have performed an comparison of different tissue extraction techniques with Nereis virens, comparing two different tissue disruption methods (including lyophilisation and wet ragworm), one solvent system (aqueous methanol), two different extraction methods (two-step extraction and pressurized liquid extraction) with exposed and unexposed organisms.
Here, we optimized the extraction strategy for present untargeted LC-MS metabolomics and GC-MS based metabolomics of marine polychaetes. All eight combinations were then compared by both analytical platforms.
Untargeted LC-MS is a robust and reliable technique for metabolomics applications. LC-MS metabolic fingerprinting approaches cover wide retention time and m/z ranges and generate extremely large, multivariate sets of data—typically more than 107 data-points per chromatographic run. However, the use of UHPLC-qTOF-MS in this particular case, did not turn out to be the preferred method due to large artifacts in the chromatography data (viz. retention time shifts in the chromatograms) that could not be sufficient corrected for although different alignment methods were tested.
GC-MS has been described as one gold standard for metabolomics studies, although it is biased against non-volatile, high-MW metabolites and requires the conversion of these compounds to volatile and thermal stables derivates. Due to wide range of chemical metabolites in these organisms, two-stage derivatization was employed to the simultaneous determination of organic acids, fatty acids, carbohydrates and amino acids.
The results were evaluated by both overall multivariate clustering approaches as well as distributions over individual metabolites/metabolite features of coefficient of variation and yield for both analytical platforms. Overall, we concluded that two-step extraction with 80% methanol solution on freeze dried ragworm was a good trade-off, showing a high extraction efficiency based of the yield and reproducibility (see Figure 1). Although it is important to note that the definition of the apparent “best” method depended on which analytical platform was used to evaluate the results.
These strategies could allow to discriminate between crude oil exposed and unexposed worms. However, an oil contamination dependency was too small compare to other sources of random variation (e.g. biological variability). Besides marine polychaetes exhibited significant perturbations in their metabolite profile after their exposure to different salinity levels. Despite an inevitable degree of confounding between, physicochemical biological variability al, and chemical stresses from oil hydrocarbon pollution, it was possible to identify metabolites involved in each type of stress condition. For instance, some amino acids (glycine, L-proline, alanine), carbohydrates (myo-inositol) and some unknown metabolites for salinity stress and some amino acids (L-valine, L-threonine, L-proline, L-lysine aspartic acid), some fatty acids (oleic acid, palmitoleic acid, propanoic acid) and some unknown metabolites for oil stress conditions.
Additional research using a larger range of oil concentration is required to fully understand the concentration and oil hydrocarbon dependency of marine polychaetes responses to oil contamination exposure.
METOIL was highly interdisciplinary as it involved analytical chemists, biologist, environmental metabolomics, ecotoxicological risk and chemometricians. It is worth noting that METOIL was applied to monitor the environmental situation at Bredemade Hage shoreline (Denmark), which was contaminated by heavy bunker oil during the 2001 Baltic Carrier oil spill and it can be applied to monitor other affected areas strongly affected by chronic hydrocarbon spillages caused by the intense traffic of oil tankers navigating. METOIL is relevant to protect intertidal areas which are relevant for seafood and seaweed growing and collection which are intended for human consumption. This study can be carried out using other types of marine organism (viz. seaweed, mussel, etc.).