Structural insights into the Escherichia coli lysine decarboxylases and molecular determinants of interaction with the AAA+ ATPase RavA
Bibliographic record
Abstract
The inducible lysine decarboxylase LdcI is an important enterobacterial acid stress response enzyme whereas LdcC is its close paralogue thought to play mainly a metabolic role. A unique macromolecular cage formed by two decamers of the Escherichia coli LdcI and five hexamers of the AAA+ ATPase RavA was shown to counteract acid stress under starvation. Previously, we proposed a pseudoatomic model of the LdcI-RavA cage based on its cryo-electron microscopy map and crystal structures of an inactive LdcI decamer and a RavA monomer. We now present cryo-electron microscopy 3D reconstructions of the E. coli LdcI and LdcC, and an improved map of the LdcI bound to the LARA domain of RavA, at pH optimal for their enzymatic activity. Comparison with each other and with available structures uncovers differences between LdcI and LdcC explaining why only the acid stress response enzyme is capable of binding RavA. We identify interdomain movements associated with the pH-dependent enzyme activation and with the RavA binding. Multiple sequence alignment coupled to a phylogenetic analysis reveals that certain enterobacteria exert evolutionary pressure on the lysine decarboxylase towards the cage-like assembly with RavA, implying that this complex may have an important function under particular stress conditions.
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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".