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Zusammenfassung:
Stable isotope probing (SIP) approaches are a suitable tool to identify active organisms in bacterial communities, but adding isotopically labeled substrate can alter both the structure and the functionality of the community. Here, we validated and demonstrated a substrate-independent protein-SIP protocol using isotopically labeled water that captures the entire microbial activity of a community. We found that 18O yielded a higher incorporation rate into peptides and thus comprised a higher sensitivity. We then applied the method to an in vitro model of a human distal gut microbial ecosystem grown in two medium formulations, to evaluate changes in microbial activity between a high-fiber and high-protein diet. We showed that only little changes are seen in the community structure but the functionality varied between the diets. In conclusion, our approach can detect species-specific metabolic activity in complex bacterial communities and more specifically to quantify the amount of amino acid synthesis. Heavy water makes possible to analyze the activity of bacterial communities for which adding an isotopically labeled energy and nutrient sources is not easily feasible. SIGNIFICANCE: Heavy stable isotopes allow for the detection of active key players in complex ecosystems where many organisms are thought to be dormant. Opposed to the labelling with energy or nutrient sources, heavy water could be a suitable replacement to trace activity, which has been shown for DNA and RNA. Here we validate, quantify and compare the incorporation of heavy water either labeled with deuterium or 18‑oxygen into proteins of Escherichia coli K12 and of an in vitro model of a human gut microbial ecosystem. The significance of our research is in providing a freely available pipeline to analyze the incorporation of deuterium and 18‑oxygen into proteins together with the validation of the applicability of tracing heavy water as a proxy for activity. Our approach unveils the relative functional contribution of microbiota in complex ecosystems, which will improve our understanding of both animal- and environment-associated microbiomes and in vitro models.
