Butyric Acid- and Dimethyl Disulfide-Assimilating Microorganisms in a Biofilter Treating Air Emissions from a Livestock Facility
Bibliographic record
Abstract
Biofiltration has proven an efficient tool for the elimination of volatile organic compounds (VOCs) and ammonia from livestock facilities, thereby reducing nuisance odors and ammonia emissions to the local environment. The active microbial communities comprising these filter biofilms have not been well characterized. In this study, a trickle biofilter treating air from a pig facility was investigated and proved efficient in removing carboxylic acids (>70% reduction), mainly attributed to the primary filter section within which reduced organic sulfur compounds were also depleted (up to 50%). The secondary filter eliminated several aromatic compounds: phenol (81%), p-cresol (89%), 4-ethylphenol (68%), indole (48%), and skatole (69%). The active butyric acid degrading bacterial community of an air filter sample was identified by DNA stable-isotope probing (DNA-SIP) and microautoradiography, combined with fluorescence in situ hybridization (MAR-FISH). The predominant 16S rRNA gene sequences from a clone library derived from "heavy" DNA from [(13)C(4)]butyric acid incubations were Microbacterium, Gordonia, Dietzia, Rhodococcus, Propionibacterium, and Janibacter, all from the Actinobacteria. Actinobacteria were confirmed and quantified by MAR-FISH as being the major bacterial phylum assimilating butyric acid along with several Burkholderiales-related Betaproteobacteria. The active bacterial community assimilating dimethyl disulfide (DMDS) was characterized by DNA-SIP and MAR-FISH and found to be associated with the Actinobacteria, along with a few representatives of Flavobacteria and Sphingobacteria. Interestingly, ammonia-oxidizing Betaproteobacteria were also implicated in DMDS degradation, as were fungi. Thus, multiple isotope-based methods provided complementary data, enabling high-resolution identification and quantitative assessments of odor-eliminating Actinobacteria-dominated populations of these biofilter environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".