Cloning, over-expression and purification of<i>Pseudomonas aeruginosa murC</i>encoding uridine diphosphate<i>N</i>-acetylmuramate: L-alanine ligase
Bibliographic record
Abstract
We cloned and sequenced the murC gene from Pseudomonas aeruginosa encoding a protein of 53 kDa. Multiple alignments with 20 MurC peptide sequences from different bacteria confirmed the presence of highly conserved regions having sequence identities ranging from 22-97% including conserved motifs for ATP-binding and the active site of the enzyme. Genetic complementation was done in Escherichia coli (murCts) suppressing the lethal phenotype. The murC gene was subcloned into the expression vector pET30a and overexpressed in E. coli BL21(lambdaDE3). Three PCR cloning strategies were used to obtain the three recombinant plasmids for expression of the native MurC, MurC His-tagged at N-terminal and at C-terminal, respectively. MurC His-tagged at C-terminal was chosen for large scale production and protein purification in the soluble form. The purification was done in a single chromatographic step on an affinity nickel column and obtained in mg quantities at 95% homogeneity. MurC protein was used to produce monoclonal antibodies for epitope mapping and for assay development in high throughput screenings. Detailed studies of MurC and other genes of the bacterial cell cycle will provide the reagents and strain constructs for high throughput screening and for design of novel antibacterials.
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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 | 0.001 |
| 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".