Heterologous expression and biochemical characterisation of the recombinant β-carbonic anhydrase (MpaCA) from the warm-blooded vertebrate pathogen <i>malassezia pachydermatis</i>
Bibliographic record
Abstract
Warm-blooded animals may have Malassezia pachydermatis on healthy skin, but changes in the skin microenvironment or host defences induce this opportunistic commensal to become pathogenic. Malassezia infections in humans and animals are commonly treated with azole antifungals. Fungistatic treatments, together with their long-term use, contribute to the selection and the establishment of drug-resistant fungi. To counteract this rising problem, researchers must find new antifungal drugs and enhance drug resistance management strategies. Cyclic adenosine monophosphate, adenylyl cyclase, and bicarbonate have been found to promote fungal virulence, adhesion, hydrolase synthesis, and host cell death. The CO2/HCO3-/pH-sensing in fungi is triggered by HCO3- produced by metalloenzymes carbonic anhydrases (CAs, EC 4.2.1.1). It has been demonstrated that the growth of M. globosa can be inhibited in vivo by primary sulphonamides, which are the typical CA inhibitors. Here, we report the cloning, purification, and characterisation of the β-CA (MpaCA) from the pathogenic fungus M. pachydermatis, which is homologous to the enzyme encoded in the genome of M. globosa and M. restricta, that are responsible for dandruff and seborrhoeic dermatitis. Fungal CAs could be thus considered a new pharmacological target for combating fungal infections and drug resistance developed by most fungi to the already used drugs.
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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".