Fish metabolome from sub-urban lakes of the Paris area (France) and potential influence of noxious metabolites produced by cyanobacteria

Discovery of candidate biomarkers to discriminate between Korean and Japanese red seabream (Pagrus major) using metabolomics

Red seabream (Pagrus major) is widely consumed in East Asia. As nuclear wastewater is discharged into Japanese waterbodies, the country of origin of marine products must be accurately labeled. Here, we aimed to discover candidate metabolite biomarkers to discriminate between Korean and Japanese red seabream using LC-Orbitrap mass spectrometry. In total, 95 and 138 putative metabolites were detected via chromatographic separation of fish sampled in the warm and cold seasons, respectively. The spectrometric and chromatographic data were analyzed using principal component analysis and orthogonal partial least squares discriminant analysis. We identified 12 and 19 influential metabolites to discriminate between each origin fish in the warm and cold seasons, respectively, using variable importance in projection scores and p values. Anserine was further selected as a candidate biomarker based on receiver operating characteristic curve analysis. This study provides a basis for using anserine to determine the geographic origin of red seabream.

Insights on the Organ-Dependent, Molecular Sexual Dimorphism in the Zebra Mussel, Dreissena polymorpha, Revealed by Ultra-High-Performance Liquid Chromatography-Tandem Mass Spectrometry Metabolomics

The zebra mussel, Dreissena polymorpha, is extensively used as a sentinel species for biosurveys of environmental contaminants in freshwater ecosystems and for ecotoxicological studies. However, its metabolome remains poorly understood, particularly in light of the potential molecular sexual dimorphism between its different tissues. From an ecotoxicological point of view, inter-sex and inter-organ differences in the metabolome suggest variability in responsiveness, which can influence the analysis and interpretation of data, particularly in the case where males and females would be analyzed indifferently. This study aimed to assess the extent to which the molecular fingerprints of functionally diverse tissues like the digestive glands, gonads, gills, and mantle of D. polymorpha can reveal tissue-specific molecular sexual dimorphism. We employed a non-targeted metabolomic approach using liquid chromatography high-resolution mass spectrometry and revealed a significant sexual molecular dimorphism in the gonads, and to a lesser extent in the digestive glands, of D. polymorpha. Our results highlight the critical need to consider inter-sex differences in the metabolome of D. polymorpha to avoid confounding factors, particularly when investigating environmental effects on molecular regulation in the gonads, and to a lesser extent in the digestive glands.

A novel framework to predict chlorophyll-a concentrations in water bodies through multi-source big data and machine learning algorithms

Eutrophication happens when water bodies are enriched by minerals and nutrients. Dense blooms of noxious are the most obvious effect of eutrophication that harms water quality, and by increasing toxic substances damage the water ecosystem. Therefore, it is critical to monitor and investigate the development process of eutrophication. The concentration of chlorophyll-a (chl-a) in water bodies is an essential indicator of eutrophication in them. Previous studies in predicting chlorophyll-a concentrations suffered from low spatial resolution and discrepancies between predicted and observed values. In this paper, we used various remote sensing and ground observation data and proposed a novel machine learning-based framework, a random forest inversion model, to provide the spatial distribution of chl-a in 2 m spatial resolution. The results showed our model outperformed other base models, and the goodness of fit improved by over 36.6% while MSE and MAE decreased by over 15.17% and over 21.26% respectively. Moreover, we compared the feasibility of GF-1 and Sentinel-2 remote sensing data in chl-a concentration prediction. We found that better prediction results can be obtained by using GF-1 data, with the goodness of fit reaching 93.1% and MSE only 3.589. The proposed method and findings of this study can be used in future water management studies and as an aid for decision-makers in this field.

Dataset on metabolome dimorphism in different organs of mature Palaemon serratus prawn

The prawn Palaemon serratus exhibits a large distribution (occurring along the Northeastern Atlantic coast to the Mediterranean), and has thus been found suitable as model organism valuable for various ecotoxicological studies. However, little is still known about the potential input of its metabolome and particularly concerning a potential molecular sexual dimorphism observable in the different tissues of this organism. In an ecotoxicological point of view, inter-sex and inter-organ differences of the metabolomes may introduce analytical bias and impact the robustness of the analysis and its interpretation. To explore such possibilities, we obtained qualitative metabolomic data from the analysis of different organs of mature male and female Palaemon serratus. We used ultra-high-performance liquid chromatography-electrospray ionization-high resolution tandem mass spectrometry (UHPLC-ESI-HRMS on positive mode) to characterize the 75%-extracted metabolome of both gills, hepatopancreas, nervous gland, muscle and gonads. The data were dereplicated using specific metabolomic software (MetaboScape 4) and 2,782 features were extracted, 1,720 of them being also analysed on MS/MS mode, supporting molecular networking investigations with Metgem 1.3.6. These metabolites were thus putatively identified using GNPS (Global Natural Product Social) Molecular Networking databases for de-novo annotation followed by manual curation of 84 metabolites. This data provides essential information on the important sexual dimorphism occurring at the molecular level in the different organs and supports further research on physiology and ecotoxicology in common European prawn.

Metabolomics for in situ monitoring of attached Crassostrea gigas and Mytilus edulis: Effects of offshore wind farms on aquatic organisms

While offshore wind power has support from countries around the world, studies show that offshore wind farms (OWFs) may affect marine organisms. Environmental metabolomics is a high-throughput method that provides a snapshot of an organism's metabolic state. To elucidate the effects of OWFs on aquatic organisms, we studied, in situ, Crassostrea gigas and Mytilus edulis attached within and outside of OWFs and their reef areas. Our results show that epinephrine, sulphaniline, and inosine 5'-monophosphate were significantly increased and L-carnitine was significantly reduced in both Crassostrea and Mytilus species from the OWFs. This may be related to immune response, oxidative stress, energy metabolism and osmotic pressure regulation of aquatic organisms. Our study shows that active selection of biological monitoring methods for risk assessment is necessary and that metabolomics of attached shellfish is useful in elucidating the metabolic pathways of aquatic organisms in OWFs.

Strategies for structure elucidation of small molecules based on LC–MS/MS data from complex biological samples

LC–MS/MS is a major analytical platform for metabolomics, which has become a recent hotspot in the research fields of life and environmental sciences. By contrast, structure elucidation of small molecules based on LC–MS/MS data remains a major challenge in the chemical and biological interpretation of untargeted metabolomics datasets. In recent years, several strategies for structure elucidation using LC–MS/MS data from complex biological samples have been proposed, these strategies can be simply categorized into two types, one based on structure annotation of mass spectra and for the other on retention time prediction. These strategies have helped many scientists conduct research in metabolite-related fields and are indispensable for the development of future tools. Here, we summarized the characteristics of the current tools and strategies for structure elucidation of small molecules based on LC–MS/MS data, and further discussed the directions and perspectives to improve the power of the tools or strategies for structure elucidation.