Tracking active groundwater microbes with D2O labeling to understand their ecosystem function

Microbial activity is key in understanding the contribution of microbial communities to ecosystem functions. Tracing turnover of individual13C labeled carbon sources provides limited information about in situ relevant environmental processes, therefore metabolic labeling with heavy water (D2O) has emerged as a promising tool to detect active microbial populations via the formation of carbon-deuterium bondsduring assimilation. When complex microbial communities are additionally spiked with organic compounds, D2O labeling should enable usto monitor their metabolic responses. To elucidate the responding microorganisms and the active metabolic pathways, we used D2Olabelingin combination with Raman microspectroscopy and SIP-metaproteomics.First, we showed that all bacterial cells from groundwater isolates growing in complex medium with D2O were labeled by applying Ramanmicrospectroscopy on the single cell level. Concomitantly, approximately 6 atom % of deuterium incorporation was found in their proteins.Next, we explored the response of the total groundwater microbiome to exogenous addition of two organic model compounds in D2Oamended microcosms. Interestingly, groundwater communities spiked with veratric acid, a lignin derivative, showed a higher extent oflabeling in individual cells than those spiked with methylamine, a degradation product of biomass. This difference in labeling can beexplained by the lower hydrogen:carbon ratio of veratric acid. In addition, we showed that veratric acid is the preferred substrate based onthe rate of mineralization and the four times higher relative abundance of organisms degrading this compound. SIP-metaproteomicsidentified Sphingomonadaceae and Microbacteriaceae as active key players in veratric acid degradation, and the metabolic pathwaysemployed. Methylamine, in contrast, led to the stimulation of various proteobacterial genera. The application of Raman microspectroscopyin conjunction with SIP-metaproteomics revealed discernable differences in labeling based on the organic compounds utilized byheterotrophic organisms. We propose this novel combined approach for elucidating the complex metabolic response of microbialsubpopulations to different stimuli.