Rapid Enrichment of <i>Cupriavidus necator</i> in Mixed Microbial Cultures Using Autotrophic Growth: Mixed Microbial Cultures for Biodegradable Polymer Production Using CO <sub>2</sub> and Organic Wastes
Bibliographic record
Abstract
Polyhydroxyalkanoate (PHA) is a biodegradable polymer that can replace petroleum-based plastics. Cupriavidus necator has been extensively utilized in industrial PHA production because the bacterium can grow and accumulate high amounts of PHA in their cells under heterotrophic and/or autotrophic growth conditions. Microbial PHA production using mixed cultures reduces the high PHA production costs and allows for the utilization of waste organics as carbon sources. However, C. necator cultivation in mixed microbial cultures has not been investigated before. In this work, we developed innovative methods for rapid and selective enrichment of C. necator in mixed cultures, utilizing the unique metabolic characteristics of C. necator (i.e., the ability to grow heterotrophically and/or autotrophically). Three enrichment methods were proposed: autotrophic-only, alternating autotrophic–heterotrophic, and heterotrophic-only cycles. These methods were examined with two wastewater sources as initial mixed mixtures. In the autotrophic-only method, the fraction of C. necator exceeded 92% of the total microbial population in only 60 h, whereas the alternating autotrophic–heterotrophic cycles showed >81.3% selection of C. necator. However, the heterotrophic-only method resulted in practically no enrichment of C. necator after five repeated feast–famine cycles. When tested for PHA accumulation, enriched cultures using the autotrophic and alternating cycles accumulated significant amounts of PHA, confirming the selective and rapid enrichment of C. necator over other microorganisms. Based on the experimental results, the autotrophic-based enrichment is a potential approach for the cost-effective cultivation of C. necator, which can reduce PHA production costs.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".