Functional analysis of the protocatechuate branch of the β-ketoadipate pathway in Aspergillus niger
Bibliographic record
Abstract
Bacteria and fungi catabolize plant-derived aromatic compounds by funneling into one of seven dihydroxylated aromatic intermediates, which then undergo ring fission and conversion to TCA cycle intermediates. Two of these intermediates, protocatechuic acid and catechol, converge on β-ketoadipate which is further cleaved to succinyl-CoA and acetyl-CoA. These β-ketoadipate pathways have been well characterized in bacteria. The corresponding knowledge of these pathways in fungi is incomplete. Characterization of these pathways in fungi would expand our knowledge and improve the valorization of lignin-derived compounds. Here, we used homology to characterize bacterial or fungal genes to predict the genes involved in the β-ketoadipate pathway for protocatechuate utilization in the filamentous fungus Aspergillus niger. We further used the following approaches to refine the assignment of the pathway genes: whole transcriptome sequencing to reveal genes upregulated in the presence of protocatechuic acid; deletion of candidate genes to observe their ability to grow on protocatechuic acid; determination by mass spectrometry of metabolites accumulated by deletion mutants; and enzyme assays of the recombinant proteins encoded by candidate genes. Based on the aggregate experimental evidence, we assigned the genes for the five pathway enzymes as follows: NRRL3_01405 (prcA) encodes protocatechuate 3,4-dioxygenase; NRRL3_02586 (cmcA) encodes 3-carboxy-cis,cis-muconate cyclase; NRRL3_01409 (chdA) encodes 3-carboxymuconolactone hydrolase/decarboxylase; NRRL3_01886 (kstA) encodes β-ketoadipate:succinyl-CoA transferase; and NRRL3_01526 (kctA) encodes β-ketoadipyl-CoA thiolase. Strain carrying ΔNRRL3_00837 could not grow on protocatechuic acid, suggesting that it is essential for protocatechuate catabolism. Its function is unknown as recombinant NRRL3_00837 did not affect the in vitro conversion of protocatechuic acid to β-ketoadipate.
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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".