Semi‐rational evolution of the 3‐(3‐hydroxyalkanoyloxy)alkanoate (<scp>HAA</scp>) synthase RhlA to improve rhamnolipid production in <i>Pseudomonas aeruginosa</i> and <i>Burkholderia glumae</i>
Bibliographic record
Abstract
The 3-(3-hydroxyalkanoyloxy)alkanoate (HAA) synthase RhlA is an essential enzyme involved in the biosynthesis of HAAs in Pseudomonas and Burkholderia species. RhlA modulates the aliphatic chain length in rhamnolipids, conferring distinct physicochemical properties to these biosurfactants exhibiting promising industrial and pharmaceutical value. A detailed molecular understanding of substrate specificity and catalytic performance in RhlA could offer protein engineering tools to develop designer variants involved in the synthesis of novel rhamnolipid mixtures for tailored eco-friendly products. However, current directed evolution progress remains limited due to the absence of high-throughput screening methodologies and lack of an experimentally resolved RhlA structure. In the present work, we used comparative modeling and chimeric-based approaches to perform a comprehensive semi-rational mutagenesis of RhlA from Pseudomonas aeruginosa. Our extensive RhlA mutational variants and chimeric hybrids between the Pseudomonas and Burkholderia homologs illustrate selective modulation of rhamnolipid alkyl chain length in both Pseudomonas aeruginosa and Burkholderia glumae. Our results also demonstrate the implication of a putative cap-domain motif that covers the catalytic site of the enzyme and provides substrate specificity to RhlA. This semi-rational mutant-based survey reveals promising 'hot-spots' for the modulation of RL congener patterns and potential control of enzyme activity, in addition to uncovering residue positions that modulate substrate selectivity between the Pseudomonas and Burkholderia functional homologs. DATABASE: Model data are available in the PMDB database under the accession number PM0081867.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".