The phosphocarrier protein HPr of the bacterial phosphotransferase system globally regulates energy metabolism by directly interacting with multiple enzymes in Escherichia coli
Bibliographic record
Abstract
The histidine-phosphorylatable phosphocarrier protein (HPr) is an essential component of the sugar-transporting phosphotransferase system (PTS) in many bacteria. Recent interactome findings suggested that HPr interacts with several carbohydrate-metabolizing enzymes, but whether HPr plays a regulatory role was unclear. Here, we provide evidence that HPr interacts with a large number of proteins in Escherichia coli . We demonstrate HPr-dependent allosteric regulation of the activities of pyruvate kinase (PykF, but not PykA), phosphofructokinase (PfkB, but not PfkA), glucosamine-6-phosphate deaminase (NagB), and adenylate kinase (Adk). HPr is either phosphorylated on a histidyl residue (HPr-P) or non-phosphorylated (HPr). PykF is activated only by non-phosphorylated HPr, which decreases the PykF K half for phosphoenolpyruvate by 10-fold (from 3.5 to 0.36 mm), thus influencing glycolysis. PfkB activation by HPr, but not by HPr-P, resulted from a decrease in the K half for fructose-6-P, which likely influences both gluconeogenesis and glycolysis. Moreover, NagB activation by HPr was important for the utilization of amino sugars, and allosteric inhibition of Adk activity by HPr-P, but not by HPr, allows HPr to regulate the cellular energy charge coordinately with glycolysis. These observations suggest that HPr serves as a directly interacting global regulator of carbon and energy metabolism and probably of other physiological processes in enteric bacteria.
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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".