Genome-Wide Screening of Genes Whose Enhanced Expression Affects Glycogen Accumulation in Escherichia coli
Bibliographic record
Abstract
Using a systematic and comprehensive gene expression library (the ASKA library), we have carried out a genome-wide screening of the genes whose increased plasmid-directed expression affected glycogen metabolism in Escherichia coli. Of the 4123 clones of the collection, 28 displayed a glycogen-excess phenotype, whereas 58 displayed a glycogen-deficient phenotype. The genes whose enhanced expression affected glycogen accumulation were classified into various functional categories including carbon sensing, transport and metabolism, general stress and stringent responses, factors determining intercellular communication, aggregative and social behaviour, nitrogen metabolism and energy status. Noteworthy, one-third of them were genes about which little or nothing is known. We propose an integrated metabolic model wherein E. coli glycogen metabolism is highly interconnected with a wide variety of cellular processes and is tightly adjusted to the nutritional and energetic status of the cell. Furthermore, we provide clues about possible biological roles of genes of still unknown functions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".