Engineering nonphotosynthetic carbon fixation for production of bioplastics by methanogenic archaea
Bibliographic record
Abstract
The conversion of CO2 to value-added products allows both capture and recycling of greenhouse gas emissions. While plants and other photosynthetic organisms play a key role in closing the global carbon cycle, their dependence on light to drive carbon fixation can be limiting for industrial chemical synthesis. Methanogenic archaea provide an alternative platform as an autotrophic microbial species capable of non-photosynthetic CO2 fixation, providing a potential route to engineered microbial fermentation to synthesize chemicals from CO2 without the need for light irradiation. One major challenge in this goal is to connect upstream carbon-fixation pathways with downstream biosynthetic pathways, given the distinct differences in metabolism between archaea and typical heterotrophs. We engineered the model methanogen, Methanococcus maripaludis, to divert acetyl-coenzyme A toward biosynthesis of value-added chemicals, including the bioplastic polyhydroxybutyrate (PHB). A number of studies implicated limitations in the redox pool, with NAD(P)(H) pools in M. maripaludis measured to be <15% of that of Escherichia coli, likely since methanogenic archaea utilize F420 and ferredoxins instead. Multiple engineering strategies were used to precisely target and increase the cofactor pool, including heterologous expression of a synthetic nicotinamide salvage pathway as well as an NAD+-dependent formate dehydrogenase from Candida boidinii. Engineered strains of M. maripaludis with improved NADH pools produced up to 171 ± 4 mg/L PHB and 24.0 ± 1.9% of dry cell weight. The metabolic engineering strategies presented in this study broaden the utility of M. maripaludis for sustainable chemical synthesis using CO2 and may be transferable to related archaeal species.
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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 | 0.001 | 0.001 |
| 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".