Proteomic and Transcriptomic Analyses to Decipher the Chitinolytic Response of Jeongeupia spp.
Bibliographic record
Abstract
In nature, chitin, the most abundant marine biopolymer, does not accumulate due to the action of chitinolytic organisms, whose saccharification systems provide instructional blueprints for effective chitin conversion. Therefore, discovery and deconstruction of chitinolytic machineries and associated enzyme systems are essential for the advancement of biotechnological chitin valorization. Through combined investigation of the chitin-induced secretome with differential proteomic and transcriptomic analyses, a holistic system biology approach has been applied to unravel the chitin response mechanisms in the Gram-negative Jeongeupia wiesaeckerbachi. Hereby, the majority of the genome-encoded chitinolytic machinery, consisting of various glycoside hydrolases and a lytic polysaccharide monooxygenase, could be detected extracellularly. Intracellular proteomics revealed a distinct translation pattern with significant upregulation of glucosamine transport, metabolism, and chemotaxis-associated proteins. While the differential transcriptomic results suggested the overall recruitment of more genes during chitin metabolism compared to that of glucose, the detected protein-mRNA correlation was low. As one of the first studies of its kind, the involvement of over 350 unique enzymes and 570 unique genes in the catabolic chitin response of a Gram-negative bacterium could be identified through a three-way systems biology approach. Based on the cumulative data, a holistic model for the chitinolytic machinery of Jeongeupia spp. is proposed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".