Selective Pressure of Temperature on Competition and Cross-Feeding within Denitrifying and Fermentative Microbial Communities
Bibliographic record
Abstract
In coastal marine sediments, denitrification and fermentation are important processes in the anaerobic decomposition of organic matter. Microbial communities performing these two processes were enriched from tidal marine sediments in replicated, long term chemostat incubations at 10 and 25°C. Whereas denitrification rates at 25°C were more or less stable over time, at 10°C denitrification activity was unstable and could only be sustained either by repeatedly increasing the amount of carbon substrates provided or by repeatedly decreasing the dilution rate. Metagenomic and transcriptomic sequencing was performed at different time points and provisional whole genome sequences (WGS) and gene activities of abundant populations were compared across incubations. These analyses suggested that a temperature of 10°C selected for populations related to Vibrionales/Photobacterium that contributed to both fermentation (via pyruvate/formate lyase) and nitrous oxide reduction. At 25°C, denitrifying populations affiliated with Rhodobacteraceae were more abundant. The latter performed complete denitrification, and may have used carbon substrates produced by fermentative populations (cross-feeding). Overall, our results suggest that a mixture of competition-for substrates between fermentative and denitrifying populations, and for electrons between both pathways active within a single population -, and cross feeding-between fermentative and denitrifying populations-controlled the overall rate of denitrification. Temperature was shown to have a strong selective effect, not only on the populations performing either process, but also on the nature of their ecological interactions. Future research will show whether these results can be extrapolated to the natural environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".