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Abstract :
[en] Natural microbial communities are heterogeneous and dynamic. Therefore, a major consideration for multiple omic data studies is the sample-to-sample heterogeneity, which can lead to inconsistent results if the different biomolecular fractions are obtained from distinct sub-samples. Conversely, systematic omic measurements, i.e. the standardised, reproducible and simultaneous measurement of multiple features from a single undivided sample, result in fully integrable datasets.
Objective
In order to prove the feasibility and benefits of such systematic measurements in the study of the respective contributions of different populations to the community-wide phenotype, we purified and analysed all biomolecular fractions, i.e. DNA, RNA, proteins and metabolites, obtained from a unique undivided sample of lipid accumulating microbial community (LAMC) from wastewater treatment plant and integrate the resulting datasets.
Methods
One time point of particular interest was first selected out of 4 LAMC samples for its high diversity and strong lipid accumulation phenotype. Then, the systematic measurement strategy was applied to the selected undivided LAMC sample and the purified biomolecules were analysed by high-throughput techniques. DNA and RNA sequencing reads were assembled at the population-level using different binning strategies. A database, containing predicted proteins, was constructed to identify the detected peptides. Finally, all biomolecular information was mapped onto the assembled composite genomes to identify the precise roles of the different populations in the community-wide lipid accumulation phenotype.
Results
Metabolomics and 16S diversity analyses were used to select the sample of highest interest for detailed analysis. The systematic measurements of the selected sample followed by data integration have allowed us to probe the functional relevance of the population-level composite genomes, leading to the identification of the LAMC key players.
Conclusion
As community phenotype is not the sum of the different partner phenotypes, understanding a microbial community system requires more than the study of isolated organisms. Even if both approaches are complementary, top-down systematic approached only provides a holistic perspective of micro-ecological processes.