Rebuilding microbial genomes
Bibliographic record
Abstract
Engineered microbes are of great potential utility in biotechnology and basic research. In principle, a cell can be built from scratch by assembling small molecule sets with auto-catalytic properties. Alternatively, DNA can be isolated or directly synthesized and molded into a synthetic genome using existing genomic blueprints and molecular biology tools. Activating such a synthetic genome will yield a synthetic cell. Here we examine obstacles associated with this latter approach using a model system whereby a donor genome from H. influenzae is fragmented, and the pieces are then modified and reassembled stepwise in an E. coli host cell. There are obstacles associated with this strategy related to DNA transfer, DNA replication, cross-talk in gene regulation and compatibility of gene products between donor and host. Encouragingly, analysis of gene expression indicates widespread transcription of H. influenzae genes in E. coli, and analysis of gap locations in H. influenzae and other microbial genome assemblies reveals few genes routinely incompatible with E. coli. In conclusion, rebuilding and booting a genome remains a feasible and pragmatic approach to creating a synthetic microbial cell.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".