The recent democratisation of high-throughput molecular phenotyping allows the rapid expansion of promising untargeted multi-dimensional approaches (e.g. epigenomics, transcriptomics, proteomics, metabolomics, as well as microbiome metabarcoding), that now represent innovative perspectives for environmental assessments. Indeed, when developed for ecologically relevant species, these emerging omics analyses may present valuable alternatives for the development of novel generations of ecological indicators, that in turn could provide early warnings of eco(toxico)logical impairments.
This pilot study investigates the bio-indicative potential of different multi-metric tools based on different high-throughput molecular phenotyping approaches (i.e. metabarcoding of the intestine microbiome, and liver metabolomics by nuclear magnetic resonance (NMR) and liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) on two sentinel fish species (Perca fluviatilis and Lepomis gibbosus) from a set of eight water bodies of the peri-urban area of Paris (France). We show that the LC-MS metabolome dataset allows remarkably clear separation of individuals according to the species but also according to their respective sampling lakes. Interestingly, the similar variations of Perca and Lepomis metabolomes occur locally indicating that local environmental constraints drive the observed metabolome variations beyond their obvious genetic differences. Thus, the development of such reliable molecular phenotyping for environmental monitoring constitutes a promising and innovative bio-indicative tool for environmental assessment.
Systematic Gene-to-Phenotype Arrays: A High-Throughput Technique for Molecular Phenotyping
