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Record W2444500095 · doi:10.7554/elife.13664

A new synthetic biology approach allows transfer of an entire metabolic pathway from a medicinal plant to a biomass crop

2016· article· en· W2444500095 on OpenAlexaff
Paulina Fuentes, Fei Zhou, Alexander Erban, Daniel Karcher, Joachim Kopka, Ralph Bock

Bibliographic record

VenueeLife · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant biochemistry and biosynthesis
Canadian institutionsUniversity of British Columbia
FundersEuropean Research CouncilMax-Planck-Gesellschaft
KeywordsArtemisininSynthetic biologyMetabolic engineeringBiologyMetabolic pathwayBiotechnologyBiomass (ecology)Computational biologyCropMalariaBotanyBiochemistryGenePlasmodium falciparumEcology

Abstract

fetched live from OpenAlex

Artemisinin-based therapies are the only effective treatment for malaria, the most devastating disease in human history. To meet the growing demand for artemisinin and make it accessible to the poorest, an inexpensive and rapidly scalable production platform is urgently needed. Here we have developed a new synthetic biology approach, combinatorial supertransformation of transplastomic recipient lines (COSTREL), and applied it to introduce the complete pathway for artemisinic acid, the precursor of artemisinin, into the high-biomass crop tobacco. We first introduced the core pathway of artemisinic acid biosynthesis into the chloroplast genome. The transplastomic plants were then combinatorially supertransformed with cassettes for all additional enzymes known to affect flux through the artemisinin pathway. By screening large populations of COSTREL lines, we isolated plants that produce more than 120 milligram artemisinic acid per kilogram biomass. Our work provides an efficient strategy for engineering complex biochemical pathways into plants and optimizing the metabolic output.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.011
GPT teacher head0.221
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations204
Published2016
Admission routes1
Has abstractyes

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