An expanded genetic toolbox to accelerate the creation of <i>Acholeplasma laidlawii</i> driven by synthetic genomes
Bibliographic record
Abstract
ABSTRACT Assembling synthetic bacterial genomes in yeast and genome transplantation has enabled an unmatched level of bacterial strain engineering, giving rise to cells with minimal and chemically synthetic genomes. However, this technology is currently limited to members of the Spiroplasma phylogenetic group, mostly Mycoplasmas , within the Mollicute class. Here, we propose new genetic tools for developing these technologies for Acholeplasma laidlawii , which is phylogenetically distant from Mycoplasmas and, unlike most Mollicutes , uses a standard genetic code. We first investigated a donor-recipient relationship between two A. laidlawii strains through whole-genome sequencing. We then created multi-host shuttle plasmids and used them to optimize an electroporation protocol. We also demonstrated the use of evolution to create superior strains for DNA uptake via electroporation. For genome transplantation, we selected A. laidlawii 8195 as the recipient strain and created a PG-8A donor strain by inserting a Tn5 transposon carrying a tetracycline resistance gene. The tools presented here will improve Acholeplasma research and accelerate the effort toward creating A. laidlawii strains driven by synthetic genomes. 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".