Engineering anaerobic fungal-bacterial consortia for direct conversion of lignocellulosic biomass into medium-chain fatty acids
Bibliographic record
Abstract
Abstract Lignocellulosic biomass is a renewable feedstock for sustainable fuels and chemicals, yet industrial conversion remains constrained by carbohydrate solubilization. Inspired by herbivore rumen microbiomes, we engineered an anaerobic fungal-bacterial consortium converting native lignocellulose into medium-chain fatty acids (MCFAs) without pretreatment. Systematic screening identified a newly isolated anaerobic fungus, Neocallimastix sp. FC1, in co-culture with Megasphaera hexanoica as a top-performing pair, achieving a lignocellulose-to-MCFA yield of 21.0 % (carbon-to-carbon basis) through tight lactate cross-feeding without competition for soluble sugars. Because fungal lactate production rate constrained the growth of M. hexanoica , the bacterium reallocated protein from growth toward chain elongation, resulting in increased MCFAs production over butyrate. These results demonstrate that high lignocellulose-to-MCFA conversion by the consortium requires high lactate-producing capability and operating regimes sustaining low lactate concentrations at high flux. Technoeconomic analysis further identifies the cost and yield thresholds required for economically viable deployment, establishing quantitative design targets for pretreatment-free fungal-bacterial lignocellulose upgrading.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".