Two-Stage Bioconversion of Cellulose to Single-Cell Protein and Oil via a Cellulolytic Consortium
Bibliographic record
Abstract
A novel approach for converting non-edible plant biomass into single-cell protein and oil (SCPO) via consolidated bioprocessing has been established, leveraging aerotolerant thermophilic cellulolytic consortia consisting mainly of Thermoanaerobacterium thermosaccharolyticum, Sporolactobacillus spp. and Clostridium sensu stricto to achieve the rapid and complete conversion of crystalline cellulose into a consistent cocktail of lactate, acetate and ethanol. This cocktail is an excellent substrate for cultivating organisms for SCPO production and food and feed applications, including Cyberlindnera jadinii, Yarrowia lipolytica and Corynebacterium glutamicum. Cultivation on this cocktail resulted in yields (YX/S) of up to 0.43 ± 0.012 g/g, indicating a yield from cellulose (YX/Cellulose) of up to 0.27 ± 0.007 g/g (dwb). The resulting SCPO was rich in protein (42.5% to 57.9%), essential amino acids (27.8% to 43.2%) and lipids (7.9% to 8.4%), with unsaturated fatty acid fractions of up to 89%. Unlike fermentation feedstocks derived from easily digested feedstocks (i.e., food waste), this approach has been applied to cellulosic biomass, and this mixed-culture bioconversion can be carried out without adding expensive enzymes. This two-stage cellulosic bioconversion can unlock non-edible plant biomass as an untapped feedstock for food and feed production, with the potential to strengthen resiliency and circularity in food systems.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".