Proteomic data on enzyme secretion and activity in the bacterium Chitinophaga pinensis
Bibliographic record
Abstract
The secretion of carbohydrate-degrading enzymes by a bacterium sourced from a softwood forest environment has been investigated by mass spectrometry. The findings are discussed in full in the research article “Proteomic insights into mannan degradation and protein secretion by the forest floor bacterium Chitinophaga pinensis” in Journal of Proteomics by Larsbrink et al. ([1], doi: 10.1016/j.jprot.2017.01.003). The bacterium was grown on three carbon sources (glucose, glucomannan, and galactomannan) which are likely to be nutrient sources or carbohydrate degradation products found in its natural habitat. The bacterium was grown on solid agarose plates to mimic the natural behaviour of growth on a solid surface. Secreted proteins were collected from the agarose following trypsin-mediated hydrolysis to peptides. The different carbon sources led to the secretion of different numbers and types of proteins. Most carbohydrate-degrading enzymes were found in the glucomannan-induced cultures. Several of these enzymes may have biotechnological potential in plant cell wall deconstruction for biofuel or biomaterial production, and several may have novel activities. A subset of carbohydrate-active enzymes (CAZymes) with predicted activities not obviously related to the growth substrates were also found in samples grown on each of the three carbohydrates. The full dataset is accessible at the PRIDE partner repository (ProteomeXchange Consortium) with the identifier PXD004305, and the full list of proteins detected is given in the supplementary material attached to this report.
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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 | 0.001 | 0.001 |
| 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".