The interplay between glucose and aromatic compound regulation by two IclR-type transcription factors, LigR1 and LigR2, in Pseudomonas putida KT2440
Bibliographic record
Abstract
Carbon utilization strategies are fundamental to microbial proliferation within complex ecosystems like the soil microbiome. These strategies dictate how microbes prioritize, and metabolize available carbon compounds, shaping community dynamics and ecological outcomes. Pseudomonas putida KT2440, a soil bacterium renowned for its metabolic versatility, exemplifies this adaptive capacity. However, the regulatory mechanism it employs to prioritize sugars vs aromatic compounds for their energy requirement remains poorly understood. Here, we investigated two IclR-type transcriptional regulators, LigR1 and LigR2, which control expression of the lig1 and lig2 operons. Functional analyses reveal that LigR1 and LigR2 activate lig1 but repress the lig2 operon. 4-hydroxybenzoate binding to LigR1 represses gene expression, whereas quinate, protocatechuate, and 4-hydroxybenzoate bind to LigR2 to induce lig2 operon expression. Additionally, ligR1 deletion causes growth defects on glucose and 4-hydroxybenzoate, accompanied by cell elongation and aggregation. We propose that the lig1 operon mediates dual influx of glucose and aromatics via its major facilitator superfamily transporter, while the lig2 operon catalyzes aromatic breakdown through a protocatechuate intermediate and meta-cleavage pathway, supplying oxaloacetate to the TCA cycle. Importantly, P. putida prioritizes shikimate pathway intermediates as energy sources under specific metabolic conditions, such as their accumulation. Overall, these findings redefine the metabolic flexibility of soil pseudomonads and reveal a novel mechanism for thriving in chemically diverse environments. By illuminating a dual regulatory system, our study offers new insight into microbial carbon flux and on the traditional biosynthetic paradigm of the shikimate pathway, revealing its unexpected role in supplying the organism with energy generating 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) | 0.000 | 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".