Characterization of enriched aerotolerant cellulose-degrading communities for biofuels production using differing selection pressures and inoculum sources
Bibliographic record
Abstract
Ethanol production from direct cellulose fermentation has mainly been described as a strictly anaerobic process. The use of air-tolerant organisms or consortia for this process would reduce the need for prereduction of the medium and also permit continuous feed of aerobic feedstock. To this end, moderately thermophilic (60 °C) consortia of fermentative, cellulolytic bacteria were enriched from 3 distinct environments (manure, marsh, and rotten wood) from a farm in southeast Saskatchewan, Canada. Community phenotypic and metabolic profiles were characterized. Selection methods included direct plating under an aerobic atmosphere and repeated passaging; the methods were designed to select for robust, stable aerotolerant cellulose-degrading communities. Several of the isolated communities exhibited an increase in total cellulose degradation and total ethanol yield when compared with a monoculture of Clostridium thermocellum DSMZ 1237. Owing to stringent selection conditions, low diversity enrichments were found, and many appeared to be binary cultures via density gradient gel electrophoresis analysis. On the basis of 16S rRNA gene sequencing, aerobic conditions selected for a mix of organisms highly related to C. thermocellum and Geobacillus species, while anaerobic conditions led to the development of consortia containing strains related to C. thermocellum with strains from either the genus Geobacillus or the genus Thermoanaerobacter. The presence of a Geobacillus-like species appeared to be a prerequisite for aerotolerance of the cellulolytic enrichments, a highly desired phenotype in lignocellulosic consolidated bioprocessing.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".