Molecular mechanism of Aspergillus fumigatus biofilm disruption by fungal and bacterial glycoside hydrolases
Bibliographic record
Abstract
During infection, the fungal pathogen Aspergillus fumigatus forms biofilms that enhance its resistance to antimicrobials and host defenses. An integral component of the biofilm matrix is galactosaminogalactan (GAG), a cationic polymer of α-1,4-linked galactose and partially deacetylated N -acetylgalactosamine (GalNAc). Recent studies have shown that recombinant hydrolase domains from Sph3, an A. fumigatus glycoside hydrolase involved in GAG synthesis, and PelA, a multifunctional protein from Pseudomonas aeruginosa involved in Pel polysaccharide biosynthesis, can degrade GAG, disrupt A. fumigatus biofilms, and attenuate fungal virulence in a mouse model of invasive aspergillosis. The molecular mechanisms by which these enzymes disrupt biofilms have not been defined. We hypothesized that the hydrolase domains of Sph3 and PelA (Sph3 h and PelA h , respectively) share structural and functional similarities given their ability to degrade GAG and disrupt A. fumigatus biofilms. MALDI-TOF enzymatic fingerprinting and NMR experiments revealed that both proteins are retaining endo-α-1,4- N- acetylgalactosaminidases with a minimal substrate size of seven residues. The crystal structure of PelA h was solved to 1.54 Å and structure alignment to Sph3 h revealed that the enzymes share similar catalytic site residues. However, differences in the substrate-binding clefts result in distinct enzyme-substrate interactions. PelA h hydrolyzed partially deacetylated substrates better than Sph3 h , a finding that agrees well with PelA h 's highly electronegative binding cleft versus the neutral surface present in Sph3 h . Our insight into PelA h 's structure and function necessitate the creation of a new glycoside hydrolase family, GH166, whose structural and mechanistic features, along with those of GH135 (Sph3), are reported here.
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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) | 0.000 | 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 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".