Evidence of rapid non-targeted effects of cycloheximide on soil bacteria using <sup>13</sup>C-PLFA analysis
Bibliographic record
Abstract
Stable isotope probing of phospholipid fatty acids (PLFA-SIP) is useful when studying bacterial contributions to soil processes, and it is an effective way to separate fungal and bacterial activity by linking 13C enrichment to specific PLFAs. Distinguishing bacterial contributions to soil processes often employs selective inhibitors; however, studies demonstrating their efficacy when using PLFA-SIP are less common. Here, we determined the effect of the fungal inhibitor cycloheximide (4.8 mg g−1 dry soil) and the bacterial inhibitor bronopol (0.48 mg g−1 dry soil) on microbial communities white spruce [Picea glauca (Moench) Voss] forest floor by measuring the uptake of 13C-enriched glucose (2 mg g−1 dry soil) in microbial PLFAs. We targeted [13C]glucose uptake by the bacterial community conditioned to a stable soil environment of 23 °C for over 2 wk rather than new bacteria generated from active colony growth caused by glucose addition. Nearly all bacterial PLFAs exhibited pronounced inhibition of 13C enrichment in the presence of bronopol. Limited inhibition of 13C enrichment in the presence of cycloheximide was observed as bacterial PLFA affected by cycloheximide had roughly one third less 13C enrichment than samples emended with [13C]glucose alone. Inhibitory effects only reduced 13C enrichment and did not affect total PLFA concentrations, implying that the inhibitors in the concentrations applied were impeding bacterial activity without causing cell death. Based on this work, we conclude that bronopol is an effective inhibitor for bacteria. Additionally, non-targeted effects of cycloheximide on soil bacteria must be accounted for when it is used in soil incubations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".