Streptomyces venezuelae uses secreted chitinases and a designated ABC transporter to support the competitive saprophytic catabolism of chitin
Bibliographic record
Abstract
More than a billion tons of chitin are produced on earth each year. Chitin is rich in nitrogen and carbon, making it a valuable resource in competitive microbial ecosystems. However, almost all chitin is found in large, insoluble structures like insect and crustacean exoskeletons. For this material to enter a microorganism's primary metabolism, it must be degraded extracellularly through a saprophytic process. The extracellular nature of this process means that liberated oligomers may also become accessible to other microorganisms. How microbes navigate this challenge in terrestrial ecosystems remains largely unclear. Here, we show that Streptomyces venezuelae thrives on raw, insoluble chitin as its sole carbon and nitrogen source, outperforming glucose in metabolic activity and sporulation. This was facilitated by a chitinolytic system encompassing up to 10 chitinases and the DasABC chitobiose importer. While deleting some chitinases affected growth on chitin, others did not, implying some degree of functional redundancy. A dasBC null mutation conferred a severe growth defect suggesting that chitobiose is a key breakdown product during chitin-based metabolism in S. venezuelae. The DasABC transporter also played a crucial role in preventing the built-up of chitobiose extracellularly, thereby restricting its access to Bacillus subtilis in co-cultures. Given the global ubiquity of Streptomyces in soil, this pathway likely plays a significant role in soil ecology as well as carbon and nitrogen turnover on a global scale.
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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) | 0.001 | 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".