A functional genomics screen identifies diverse transcription factors that regulate alkaloid biosynthesis in Nicotiana benthamiana
Bibliographic record
Abstract
Biosynthesis of the alkaloid nicotine in Nicotiana species is induced by insect damage and jasmonate application. To probe the transcriptional regulation of the nicotine pathway, we constructed two subtracted cDNA libraries from methyl jasmonate (MeJA)-treated Nicotiana benthamiana roots directly in a viral vector suitable for virus-induced gene silencing (VIGS). Sequencing of cDNA inserts produced a data set of 3271 expressed sequence tags (ESTs; 1898 unigenes), which were enriched in jasmonate-responsive genes, and included 69 putative transcription factors (TFs). After a VIGS screen to determine their effect on nicotine metabolism, six TFs from three different TF families altered constitutive and MeJA-induced leaf nicotine levels. VIGS of a basic helix-loop-helix (bHLH) TF, NbbHLH3, and an auxin response factor TF, NbARF1, increased nicotine content compared with control plants; silencing the bHLH family members, NbbHLH1 and NbbHLH2, an ethylene response factor TF, NbERF1, and a homeobox domain-like TF, NbHB1, reduced nicotine levels. Transgenic N. benthamiana plants overexpressing NbbHLH1 or NbbHLH2 showed increased leaf nicotine levels compared with vector controls. RNAi silencing led to both reduced nicotine and decreased levels of transcript encoding of enzymes of the nicotine pathway. Electrophoretic mobility shift assays showed that recombinant NbbHLH1 and NbbHLH2 directly bind G-box elements identified from the putrescine N-methyltransferase promoter. We conclude that NbbHLH1 and NbbHLH2 function as positive regulators in the jasmonate activation of nicotine biosynthesis.
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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) | 0.001 | 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".