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Record W1867489969 · doi:10.1186/s12870-015-0594-2

Metabolome analysis of 20 taxonomically related benzylisoquinoline alkaloid-producing plants

2015· article· en· W1867489969 on OpenAlexafffund
Jillian M. Hagel, Rupasri Mandal, Jun Han, Donald Dinsmore, Christoph H. Borchers, David S. Wishart, Peter J. Facchini

Bibliographic record

VenueBMC Plant Biology · 2015
Typearticle
Languageen
FieldMedicine
TopicBerberine and alkaloids research
Canadian institutionsUniversity of VictoriaUniversity of AlbertaUniversity of Calgary
FundersGenome AlbertaGovernment of AlbertaGenome Canada
KeywordsMetabolomicsBiologyMetabolomeBenzylisoquinolineBiochemistryHydroxycinnamic acidAlkaloidBotanyComputational biologyBiosynthesisBioinformaticsGene

Abstract

fetched live from OpenAlex

BACKGROUND: Recent progress toward the elucidation of benzylisoquinoline alkaloid (BIA) metabolism has focused on a small number of model plant species. Current understanding of BIA metabolism in plants such as opium poppy, which accumulates important pharmacological agents such as codeine and morphine, has relied on a combination of genomics and metabolomics to facilitate gene discovery. Metabolomics studies provide important insight into the primary biochemical networks underpinning specialized metabolism, and serve as a key resource for metabolic engineering, gene discovery, and elucidation of governing regulatory mechanisms. Beyond model plants, few broad-scope metabolomics reports are available for the vast number of plant species known to produce an estimated 2500 structurally diverse BIAs, many of which exhibit promising medicinal properties. RESULTS: We applied a multi-platform approach incorporating four different analytical methods to examine 20 non-model, BIA-accumulating plant species. Plants representing four families in the Ranunculales were chosen based on reported BIA content, taxonomic distribution and importance in modern/traditional medicine. One-dimensional (1)H NMR-based profiling quantified 91 metabolites and revealed significant species- and tissue-specific variation in sugar, amino acid and organic acid content. Mono- and disaccharide sugars were generally lower in roots and rhizomes compared with stems, and a variety of metabolites distinguished callus tissue from intact plant organs. Direct flow infusion tandem mass spectrometry provided a broad survey of 110 lipid derivatives including phosphatidylcholines and acylcarnitines, and high-performance liquid chromatography coupled with UV detection quantified 15 phenolic compounds including flavonoids, benzoic acid derivatives and hydroxycinnamic acids. Ultra-performance liquid chromatography coupled with high-resolution Fourier transform mass spectrometry generated extensive mass lists for all species, which were mined for metabolites putatively corresponding to BIAs. Different alkaloids profiles, including both ubiquitous and potentially rare compounds, were observed. CONCLUSIONS: Extensive metabolite profiling combining multiple analytical platforms enabled a more complete picture of overall metabolism occurring in selected plant species. This study represents the first time a metabolomics approach has been applied to most of these species, despite their importance in modern and traditional medicine. Coupled with genomics data, these metabolomics resources serve as a key resource for the investigation of BIA biosynthesis in non-model plant 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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.089
GPT teacher head0.330
Teacher spread0.241 · 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 designObservational
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

Citations53
Published2015
Admission routes2
Has abstractyes

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