Role of Maltose Enzymes in Glycogen Synthesis by Escherichia coli
Bibliographic record
Abstract
Mutants with deletion mutations in the glg and mal gene clusters of Escherichia coli MC4100 were used to gain insight into glycogen and maltodextrin metabolism. Glycogen content, molecular mass, and branch chain distribution were analyzed in the wild type and in ΔmalP (encoding maltodextrin phosphorylase), ΔmalQ (encoding amylomaltase), ΔglgA (encoding glycogen synthase), and ΔglgA ΔmalP derivatives. The wild type showed increasing amounts of glycogen when grown on glucose, maltose, or maltodextrin. When strains were grown on maltose, the glycogen content was 20 times higher in the ΔmalP strain (0.97 mg/mg protein) than in the wild type (0.05 mg/mg protein). When strains were grown on glucose, the ΔmalP strain and the wild type had similar glycogen contents (0.04 mg/mg and 0.03 mg/mg protein, respectively). The ΔmalQ mutant did not grow on maltose but showed wild-type amounts of glycogen when grown on glucose, demonstrating the exclusive function of GlgA for glycogen synthesis in the absence of maltose metabolism. No glycogen was found in the ΔglgA and ΔglgA ΔmalP strains grown on glucose, but substantial amounts (0.18 and 1.0 mg/mg protein, respectively) were found when they were grown on maltodextrin. This demonstrates that the action of MalQ on maltose or maltodextrin can lead to the formation of glycogen and that MalP controls (inhibits) this pathway. In vitro, MalQ in the presence of GlgB (a branching enzyme) was able to form glycogen from maltose or linear maltodextrins. We propose a model of maltodextrin utilization for the formation of glycogen in the absence of glycogen synthase.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".