Enabling Plasmid-based Expression in <i>Clostridium kluyveri</i> using a Biparental Methylation-Conjugation System
Bibliographic record
Abstract
Abstract Clostridium kluyveri is a promising biocatalyst for producing medium-chain fatty acids (MCFAs) from waste-derived carbon via chain elongation. MCFAs are platform chemicals with diverse applications across agriculture, food, cosmetics, and fuels, and could support efforts towards tandem resource recovery and sustainable chemical production. However, genetic intractability has hindered efforts to engineer C. kluyveri for improved product yields, control over chain length and selectivity, and production of non-native oleochemicals. Here, we report a streamlined, biparental methylation-conjugation system developed for C. kluyveri DSM555 T to bypass the organism’s restriction-modification barriers and enable stable plasmid delivery. We use this system to demonstrate heterologous expression of the Fluorescence-Activated absorption-Shifting Tag (FAST), an anaerobic fluorescent reporter. This system supports advances in metabolic engineering of C. kluyveri and the broader adoption of genetic tools in chain elongating bacteria to expand the applications of anaerobic chain elongation in industrial biomanufacturing. Lay Summary We developed a streamlined method for genetically modifying Clostridium kluyveri , a promising strain for industrial anaerobic biomanufacturing, and used it to express a fluorescent protein useful for downstream applications. Graphical Abstract
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".