Eliminating Genes for a Two Component System Increases PHB Productivity in <i>Cupriavidus basilensis</i> 4G11 Under PHB Suppressing, Non-Stress Conditions
Bibliographic record
Abstract
Abstract Species of bacteria from the genus Cupriavidus are known, in part, for their ability to produce high amounts of poly-hydroxybutyrate (PHB) making them attractive candidate bioplastic producers. The native production of PHB occurs during periods of metabolic stress, and the process regulating the initiation of PHB accumulation in these organisms is not fully understood. Screening an RB-TnSeq transposon library of Cupriavidus basilensis 4G11 allowed us to identify two genes of an apparent, uncharacterized two component system which, when omitted from the genome, are capable of increased PHB productivity in balanced, non-stress growth conditions. We observe average increases in PHB productivity of 56% and 41% relative to the wildtype parent strain, upon deleting each of two genes individually from the genome. The increased PHB phenotype disappears, however, in nitrogen-free unbalanced growth conditions suggesting the phenotype is specific to fast-growing, replete, non-stress growth. Bioproduction modeling suggests this phenotype could be due to a decreased reliance on metabolic stress induced by nitrogen limitation to initiate PHB production in the mutant strains. Such strains may allow for the use of single stage, continuous bioreactor systems, which are far simpler than PHB bioproduction schemes used previously. Bioproductivity modeling suggests that omitting this regulation in the cells may increase PHB productivity up to 24% relative to the wildtype organism when using single stage continuous systems. This work furthermore expands our understanding of the regulation of PHB accumulation in Cupriavidus , in particular the initiation of this process upon transition into unbalanced growth regimes.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".