Context-Dependent Flux Coupling via Conserved Small-Molecule Regulatory Structures
Bibliographic record
Abstract
Summary Small-molecule regulation modulates enzyme activity and is widespread in metabolic networks. However, the organization of small-molecule regulatory networks and its generalized role is not well understood. We analyze the structure of the genome-wide Escherichia coli small-molecule regulatory network (SMRN) to reveal that it optimizes controllability in the metabolic network. This is achieved by conserved, highly overabundant incoherent feedforward loops. Using multi-omics data, we characterize loop examples in central carbon metabolism. These use signals from hypothesized flux-sensing metabolites phosphoenolpyruvate, α -ketoglutarate, citrate, and malate to distinguish between glycolysis, gluconeogenesis, and glyoxylate shunt activity to differentially couple fluxes across these major modes of metabolism. Our results suggest that coupling of fluxes by direct modulation of enzyme activity is an emergent property of the SMRN that depends heavily on both regulatory structure and metabolic context via the metabolome, and further that flux sensing and coupling may be a global property of the metabolic network.
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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 | 0.001 |
| 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 | 0.001 | 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".