MétaCan
Menu
Back to cohort
Record W4307940888 · doi:10.3390/metabo12111043

Bacterial Volatile Isovaleric Acid Triggers Growth Alteration of Arabidopsis Seedlings

2022· article· en· W4307940888 on OpenAlexfundno aff
Jun Murata, Takehiro Watanabe, Hajime Komura

Bibliographic record

VenueMetabolites · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsnot available
FundersInstitute of GeneticsJapan Society for the Promotion of ScienceSuntory FoundationMinistry of Education, Culture, Sports, Science and TechnologySuntory Foundation for Life Sciences
KeywordsArabidopsisBioassayPlant growthArabidopsis thalianaBacteriaBacterial growthChemistryBiologyBotanyFood scienceBiochemistryGeneEcology

Abstract

fetched live from OpenAlex

Bacterial volatile organic compounds (BVOCs) released from selected soil microbes have been shown to trigger the alteration of plant growth. However, the substances responsible for such bioactivity and the mechanism of how plants interpret and respond to BVOCs remain largely elusive. Here, we established a model bioassay system using Arabidopsis and Bacillus spp. and found that Bacillus BVOCs interfere with the normal growth of Arabidopsis seedlings. Moreover, through a bioassay-guided purification, we identified isovaleric acid (IVA) as a volatile compound that exhibits inhibitory growth activity towards Arabidopsis seedlings. Our data provide novel molecular insights into how short-chain fatty acids released from soil microbes can affect plant growth through interkingdom signals.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.011
GPT teacher head0.196
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

Citations8
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueMetabolitesSame topicPlant Parasitism and ResistanceFrench-language works237,207