ArticleThe ISME journal2020
Oxygen isotope effects during microbial sulfate reduction: applications to sediment cell abundances.
Article in The ISME journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Seasonal Changes Drive Shifts in Bacterial Community Structure and Functional Composition in the Yellow River (Zhengzhou Section).Current microbiology · 2025Article
- Marine sulphate captures a Paleozoic transition to a modern terrestrial weathering environment.Nature communications · 2025Article
- Laminarin stimulates single cell rates of sulfate reduction whereas oxygen inhibits transcriptomic activity in coastal marine sediment.The ISME journal · 2025Article
- The triple oxygen isotope composition of marine sulfate and 130 million years of microbial control.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Evidence for a Growth Zone for Deep-Subsurface Microbial Clades in Near-Surface Anoxic Sediments.Applied and environmental microbiology · 2020Article
- Proteomic and Isotopic Response ofFrontiers in microbiology · 2019Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The majority of anaerobic biogeochemical cycling occurs within marine sediments. To understand these processes, quantifying the distribution of active cells and gross metabolic activity is essential. We present an isotope model rooted in thermodynamics to draw quantitative links between cell-specific sulfate reduction rates and active sedimentary cell abundances. This model is calibrated using data from a series of continuous culture experiments with two strains of sulfate reducing bacteria (freshwater bacterium Desulfovibrio vulgaris strain Hildenborough, and marine bacterium Desulfovibrio alaskensis strain G-20) grown on lactate across a range of metabolic rates and ambient sulfate concentrations. We use a combination of experimental sulfate oxygen isotope data and nonlinear regression fitting tools to solve for unknown kinetic, step-specific oxygen isotope effects. This approach enables identification of key isotopic reactions within the metabolic pathway, and defines a new, calibrated framework for understanding oxygen isotope variability in sulfate. This approach is then combined with porewater sulfate/sulfide concentration data and diagenetic modeling to reproduce measured
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