23 research outputs found

    Metabolic spatial variability in electrode-respiring Geobacter sulfurreducens biofilms

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    In this study, we quantified electron transfer rates, depth profiles of electron donor, and biofilm structure of Geobacter sulfurreducens biofilms using an electrochemical-nuclear magnetic resonance microimaging biofilm reactor. Our goal was to determine whether electron donor limitations existed in electron transfer processes of electrode-respiring G. sulfurreducens biofilms. Cells near the top of the biofilms consumed acetate and were metabolically active; however, acetate concentration decreased to below detection within the top 100 microns of the biofilms. Additionally, porosity in the biofilms fell below 10% near the electrode surface, exacerbating exclusion of acetate from the lower regions. The dense biofilm matrix in the acetate-depleted zone acted as an electrical conduit passing electrons generated at the top of the biofilm to the electrode. To verify the distribution of cell metabolic activity, we used uranium as a redox-active probe for localizing electron transfer activity and X-ray absorption spectroscopy to determine the uranium oxidation state. Cells near the top reduced U(VI) more actively than the cells near the base. High-resolution transmission electron microscopy images showed intact, healthy cells near the top and plasmolyzed cells near the base. Contrary to models proposed in the literature, which hypothesize that cells nearest the electrode surface are the most metabolically active because of a lower electron transfer resistance, our results suggest that electrical resistance through the biofilm does not restrict long-range electron transfer. Cells far from the electrode can respire across metabolically inactive cells, taking advantage of their extracellular infrastructure produced during the initial biofilm formation

    High-resolution phylogenetic microbial community profiling

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    Over the past decade, high-throughput short-read 16S rRNA gene amplicon sequencing has eclipsed clone-dependent long-read Sanger sequencing for microbial community profiling. The transition to new technologies has provided more quantitative information at the expense of taxonomic resolution with implications for inferring metabolic traits in various ecosystems. We applied single-molecule real-time sequencing for microbial community profiling, generating full-length 16S rRNA gene sequences at high throughput, which we propose to name PhyloTags. We benchmarked and validated this approach using a defined microbial community. When further applied to samples from the water column of meromictic Sakinaw Lake, we show that while community structures at the phylum level are comparable between PhyloTags and Illumina V4 16S rRNA gene sequences (iTags), variance increases with community complexity at greater water depths. PhyloTags moreover allowed less ambiguous classification. Last, a platform-independent comparison of PhyloTags and in silico generated partial 16S rRNA gene sequences demonstrated significant differences in community structure and phylogenetic resolution across multiple taxonomic levels, including a severe underestimation in the abundance of specific microbial genera involved in nitrogen and methane cycling across the Lake's water column. Thus, PhyloTags provide a reliable adjunct or alternative to cost-effective iTags, enabling more accurate phylogenetic resolution of microbial communities and predictions on their metabolic potential
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