The uridylyltransferase GlnD and tRNA modification GTPase MnmE allosterically control Escherichia coli folylpoly-γ-glutamate synthase FolC
Bibliographic record
Abstract
Folate derivatives are important cofactors for enzymes in several metabolic processes. Folate-related inhibition and resistance mechanisms in bacteria are potential targets for antimicrobial therapies and therefore a significant focus of current research. Here, we report that the activity of Escherichia coli poly-γ-glutamyl tetrahydrofolate/dihydrofolate synthase (FolC) is regulated by glutamate/glutamine-sensing uridylyltransferase (GlnD), THF-dependent tRNA modification enzyme (MnmE), and UDP-glucose dehydrogenase (Ugd) as shown by direct in vitro protein–protein interactions. Using kinetics analyses, we observed that GlnD, Ugd, and MnmE activate FolC many-fold by decreasing the K half of FolC for its substrate l-glutamate. Moreover, FolC inhibited the GTPase activity of MnmE at low GTP concentrations. The growth phenotypes associated with these proteins are discussed. These results, obtained using direct in vitro enzyme assays, reveal unanticipated networks of allosteric regulatory interactions in the folate pathway in E. coli and indicate regulation of polyglutamylated tetrahydrofolate biosynthesis by the availability of nitrogen sources, signaled by the glutamine-sensing GlnD protein.
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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) | 0.000 | 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) | 0.001 | 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".