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Record W2755099462 · doi:10.1139/cjm-2017-0383

Multiple metabolic pathways for metabolism of <scp>l</scp>-tryptophan in <i>Fusarium</i> <i>graminearum</i>

2017· article· en· W2755099462 on OpenAlexaffvenue
Kun Luo, Caro-Lyne DesRoches, Anne Johnston, Linda J. Harris, Huiyan Zhao, Thérèse Ouellet

Bibliographic record

VenueCanadian Journal of Microbiology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsFusariumMycotoxinTryptophanBiochemistryMetabolismBiologySecondary metabolismMetabolic pathwayGibberella zeaeCitric acid cycleGeneIndole-3-acetic acidAuxinBiosynthesisBotanyAmino acid

Abstract

fetched live from OpenAlex

Fusarium graminearum is a plant pathogen that can cause the devastating cereal grain disease fusarium head blight in temperate regions of the world. Previous studies have shown that F. graminearum can synthetize indole-3-acetic acid (auxin) using l-tryptophan (L-TRP)-dependent pathways. In the present study, we have taken a broader approach to examine the metabolism of L-TRP in F. graminearum liquid culture. Our results showed that F. graminearum was able to transiently produce the indole tryptophol when supplied with L-TRP. Comparative gene expression profiling between L-TRP-treated and control cultures showed that L-TRP treatment induced the upregulation of a series of genes with predicted function in the metabolism of L-TRP via anthranilic acid and catechol towards the tricarboxylic acid cycle. It is proposed that this metabolic activity provides extra energy for 15-acetyldeoxynivalenol production, as observed in our experiments. This is the first report of the use of L-TRP to increase energy resources in a Fusarium species.

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 score0.004
Threshold uncertainty score0.008

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.204
Teacher spread0.185 · 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

Citations10
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Microbiology→Same topicMycotoxins in Agriculture and Food→French-language works237,207→