Genome Mining of Fungal Unique Trichodiene Synthase-like Sesquiterpene Synthases
Bibliographic record
Abstract
Sesquiterpenoids served as an important source for natural product drug discovery. Although genome mining approaches have revealed numerous novel sesquiterpenoids and biosynthetic enzymes, the comprehensive landscape of fungal sesquiterpene synthases (STSs) remains elusive. In this study, 123 previously reported fungal STSs were subjected to phylogenetic analysis, resulting in the identification of a fungi-specific STS family known as trichodiene synthase-like sesquiterpene synthases (TDTSs). Subsequently, the application of hidden Markov models allowed the discovery of 517 TDTSs from our in-house fungi genome library of over 400 sequenced genomes, and these TDTSs were defined into 79 families based on a sequence similarity network. Based on the novelty of protein sequences and the completeness of their biosynthetic gene clusters, 23 TDTS genes were selected for heterologous expression in Aspergillus oryzae. In total, 10 TDTSs were active and collectively produced 12 mono- and sesquiterpenes, resulting in the identification of the first chamipinene synthase, as well as the first fungi-derived cedrene, sabinene, and camphene synthases. Additionally, with the guidance of functionally characterized TDTSs, we found that TDTSs in Family 1 could produce bridged-cyclic sesquiterpenes, while those in Family 2 could synthesize spiro- and bridged-cyclic sesquiterpenes. Our research presents a new avenue for the genome mining of fungal sesquiterpenoids.
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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".