Bibliographic record
Abstract
The MoxR family of AAA+ proteins is widespread throughout bacteria and archaea, but surprisingly little is known about their function. Here I present experimental characterization, bioinformatics analysis and an in-depth literature review of the MoxR family. My study reveals at least seven distinct MoxR lineages (subfamilies) including the MoxR Proper (MRP), TM0930, RavA, CGN, APE2220, PA2707 and YehL, and supports a role for these proteins in a variety of different systems. Despite their diversity, however, MoxR proteins appear to share a common method of action, namely an involvement in the assembly of multimeric complexes and a possible role in metal insertion. My gene neighbourhood analysis reveals a clear association between MoxR AAA+ and Von Willebrand Factor Type A (VWA) protein-encoding genes, in addition to a number of subfamily specific associations. I also present an in-depth analysis of the RavA subfamily, including a phylogenetic profiling study across a subset of RavA-containing organisms and extensive experimental characterization of a representative RavA protein from Eschcrichia coli K12 MG 1655. My experimental work includes biochemical, structural, and gene expression analysis. I demonstrate that RavA is a functional ATPase, which forms hexameric rings in the presence of nucleotide. Expression of RavA is under the control of the sigma S promoter, suggesting that it is important under stress response conditions. In addition, I provide evidence supporting an interaction between RavA and its corresponding VWA-encoding protein ViaA, suggesting the two proteins function as a system. RavA also interacts with the inducible lysine decarboxylase enzyme, Ldcl, forming a large cage-like structure which may be important in the regulation of RavA activity. The results of my profiling study and a microarray analysis using RavA/ViaA deletion and overexpression strains identify a number of candidate substrates, interaction partners and systems with which RavA and ViaA appear to be involved. My work provides invaluable information regarding the MoxR proteins and presents a useful groundwork upon which to base future studies.
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 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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".