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Targeted metabolite and transcript profiling for elucidating enzyme function: isolation of novel <i>N‐</i> methyltransferases from three benzylisoquinoline alkaloid‐producing species

2009· article· en· W2117361767 on OpenAlexaff
David K. Liscombe, Jörg Ziegler, Jürgen Schmidt, Christian Ammer, Peter J. Facchini

Bibliographic record

VenueThe Plant Journal · 2009
Typearticle
Languageen
FieldMedicine
TopicBerberine and alkaloids research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBenzylisoquinolineAlkaloidBiologyMetaboliteExpressed sequence tagBiochemistryComplementary DNAEnzymeGeneBiosynthesisBotany

Abstract

fetched live from OpenAlex

An integrated approach using targeted metabolite profiles and modest EST libraries each containing approximately 3500 unigenes was developed in order to discover and functionally characterize novel genes involved in plant-specialized metabolism. EST databases have been established for benzylisoquinoline alkaloid-producing cell cultures of Eschscholzia californica, Papaver bracteatum and Thalictrum flavum, and are a rich repository of alkaloid biosynthetic genes. ESI-FTICR-MS and ESI-MS/MS analyses facilitated unambiguous identification and relative quantification of the alkaloids in each system. Manual integration of known and candidate biosynthetic genes in each EST library with benzylisoquinoline alkaloid biosynthetic networks assembled from empirical metabolite profiles allowed identification and functional characterization of four N-methyltransferases (NMTs). One cDNA from T. flavum encoded pavine N-methyltransferase (TfPavNMT), which showed a unique preference for (+/-)-pavine and represents the first isolated enzyme involved in the pavine alkaloid branch pathway. Correlation of the occurrence of specific alkaloids, the complement of ESTs encoding known benzylisoquinoline alkaloid biosynthetic genes and the differential substrate range of characterized NMTs demonstrated the feasibility of bilaterally predicting enzyme function and species-dependent specialized metabolite profiles.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.188
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.061
GPT teacher head0.281
Teacher spread0.221 · 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 teacher head, 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

Citations70
Published2009
Admission routes1
Has abstractyes

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