Microbial communities are essential to the function of virtually all ecosystems and eukaryotes, including humans. However, it is still a major challenge to identify microbial cells active under natural conditions in complex systems. In this study, we developed a new method to identify and sort active microbes on the single-cell level in complex samples using stable isotope probing with heavy water (D 2 O) combined with Raman microspectroscopy. Incorporation of D 2 O-derived D into the biomass of autotrophic and heterotrophic bacteria and archaea could be unambiguously detected via C-D signature peaks in single-cell Raman spectra, and the obtained labeling pattern was confirmed by nanoscaleresolution secondary ion MS. In fast-growing Escherichia coli cells, label detection was already possible after 20 min. For functional analyses of microbial communities, the detection of D incorporation from D 2 O in individual microbial cells via Raman microspectroscopy can be directly combined with FISH for the identification of active microbes. Applying this approach to mouse cecal microbiota revealed that the host-compound foragers Akkermansia muciniphila and Bacteroides acidifaciens exhibited distinctive response patterns to amendments of mucin and sugars. By Ramanbased cell sorting of active (deuterated) cells with optical tweezers and subsequent multiple displacement amplification and DNA sequencing, novel cecal microbes stimulated by mucin and/ or glucosamine were identified, demonstrating the potential of the nondestructive D 2 O-Raman approach for targeted sorting of microbial cells with defined functional properties for singlecell genomics.ecophysiology | single-cell microbiology | carbohydrate utilization | nitrifier | Raman microspectroscopy M icroorganisms play a vital role in many environments. They mediate global biogeochemical cycles, catalyze biotechnological processes, and contribute to health and disease in the human body. The in situ study of microbial activity in natural and engineered ecosystems is therefore of great interest. For this purpose, several elegant methods have been established that use either transcriptional or translational activity of community members (i.e., metatranscriptomics, metaproteomics) (1-3) or the incorporation of isotopically labeled substrates into biomolecules (4-10) to infer the ecophysiology of microbes in such systems. However, these bulk techniques do not offer sufficient spatial resolution to study microbial activities at the micrometer scale. Therefore, important information can be overlooked because microbial communities are frequently spatially structured (e.g., biofilms) (11) and contain populations with life cycles (12,13). Furthermore, even apparently identical cells in clonal populations can have strongly divergent activities (14).Consequently, microbial ecophysiology is ideally studied also at the level of the single cell, but only a restricted number of approaches exist for determining physiological properties of individual cells in a microbial community. For exa...
Viral evolution is revealed by giant viruses encoding multiple components of the protein translation machinery.
Biological nitrogen fixation is an important component of sustainable soil fertility and a key component of the nitrogen cycle. We used targeted metagenomics to study the nitrogen fixation-capable terrestrial bacterial community by targeting the gene for nitrogenase reductase (nifH). We obtained 1.1 million nifH 454 amplicon sequences from 222 soil samples collected from 4 National Ecological Observatory Network (NEON) sites in Alaska, Hawaii, Utah, and Florida. To accurately detect and correct frameshifts caused by indel sequencing errors, we developed FrameBot, a tool for frameshift correction and nearest-neighbor classification, and compared its accuracy to that of two other rapid frameshift correction tools. We found FrameBot was, in general, more accurate as long as a reference protein sequence with 80% or greater identity to a query was available, as was the case for virtually all nifH reads for the 4 NEON sites. Frameshifts were present in 12.7% of the reads. Those nifH sequences related to the Proteobacteria phylum were most abundant, followed by those for Cyanobacteria in the Alaska and Utah sites. Predominant genera with nifH sequences similar to reads included Azospirillum, Bradyrhizobium, and Rhizobium, the latter two without obvious plant hosts at the sites. Surprisingly, 80% of the sequences had greater than 95% amino acid identity to known nifH gene sequences. These samples were grouped by site and correlated with soil environmental factors, especially drainage, light intensity, mean annual temperature, and mean annual precipitation. FrameBot was tested successfully on three ecofunctional genes but should be applicable to any.
e Biodiversities can differ substantially among different wastewater treatment plant (WWTP) communities. Whether differences in biodiversity translate into differences in the provision of particular ecosystem services, however, is under active debate. Theoretical considerations predict that WWTP communities with more biodiversity are more likely to contain strains that have positive effects on the rates of particular ecosystem functions, thus resulting in positive associations between those two variables. However, if WWTP communities were sufficiently biodiverse to nearly saturate the set of possible positive effects, then positive associations would not occur between biodiversity and the rates of particular ecosystem functions. To test these expectations, we measured the taxonomic biodiversity, functional biodiversity, and rates of 10 different micropollutant biotransformations for 10 full-scale WWTP communities. We have demonstrated that biodiversity is positively associated with the rates of specific, but not all, micropollutant biotransformations. Thus, one cannot assume whether or how biodiversity will associate with the rate of any particular micropollutant biotransformation. We have further demonstrated that the strongest positive association is between biodiversity and the collective rate of multiple micropollutant biotransformations. Thus, more biodiversity is likely required to maximize the collective rates of multiple micropollutant biotransformations than is required to maximize the rate of any individual micropollutant biotransformation. We finally provide evidence that the positive associations are stronger for rare micropollutant biotransformations than for common micropollutant biotransformations. Together, our results are consistent with the hypothesis that differences in biodiversity can indeed translate into differences in the provision of particular ecosystem services by full-scale WWTP communities. The microbial communities residing within wastewater treatment plants (WWTPs) provide ecosystem services that are important for maintaining the quality of our environment. They consume carbon-, nitrogen-, and phosphorous-containing substrates and biotransform organic pollutants present within WWTP influent (1, 2), thus mitigating the potentially deleterious effects of these chemicals on receiving waters. The ability to perform these ecosystem functions is to some extent related to the biodiversity present within WWTP communities (3). WWTP communities are estimated to contain many thousands of different microbial strains and to express tens of thousands of different genes (e.g., 4-7), thus providing a supply of functional traits that could enable and facilitate particular ecosystem functions.While biodiversity is thought to be important for enabling and facilitating particular ecosystem functions (3), biodiversity can also differ substantially both among different WWTP communities (4,5,7,8) and over time for a single WWTP community (9, 10). In one recent investigation, the taxonomic richness measur...
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