The Homogentisate Pathway: a Central Catabolic Pathway Involved in the Degradation of <scp>l</scp> -Phenylalanine, <scp>l</scp> -Tyrosine, and 3-Hydroxyphenylacetate in <i>Pseudomonas putida</i>
Bibliographic record
Abstract
Pseudomonas putida metabolizes Phe and Tyr through a peripheral pathway involving hydroxylation of Phe to Tyr (PhhAB), conversion of Tyr into 4-hydroxyphenylpyruvate (TyrB), and formation of homogentisate (Hpd) as the central intermediate. Homogentisate is then catabolized by a central catabolic pathway that involves three enzymes, homogentisate dioxygenase (HmgA), fumarylacetoacetate hydrolase (HmgB), and maleylacetoacetate isomerase (HmgC), finally yielding fumarate and acetoacetate. Whereas the phh, tyr, and hpd genes are not linked in the P. putida genome, the hmgABC genes appear to form a single transcriptional unit. Gel retardation assays and lacZ translational fusion experiments have shown that hmgR encodes a specific repressor that controls the inducible expression of the divergently transcribed hmgABC catabolic genes, and homogentisate is the inducer molecule. Footprinting analysis revealed that HmgR protects a region in the Phmg promoter that spans a 17-bp palindromic motif and an external direct repetition from position -16 to position 29 with respect to the transcription start site. The HmgR protein is thus the first IclR-type regulator that acts as a repressor of an aromatic catabolic pathway. We engineered a broad-host-range mobilizable catabolic cassette harboring the hmgABC, hpd, and tyrB genes that allows heterologous bacteria to use Tyr as a unique carbon and energy source. Remarkably, we show here that the catabolism of 3-hydroxyphenylacetate in P. putida U funnels also into the homogentisate central pathway, revealing that the hmg cluster is a key catabolic trait for biodegradation of a small number of aromatic compounds.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".