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Record W2580888726 · doi:10.1055/s-0035-1556408

Temperature-dependent metabolite production by Arctic actinomycetes

2015· article· en· W2580888726 on OpenAlexaffabout
Bradley Haltli, Alyssa L. Grunwald, NICHOLAS I. DUNCAN, Hebelin Correa, Martin Lanteigne, Patricia Boland, R.S. Kerr

Bibliographic record

VenuePlanta Medica · 2015
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsNautilus Biosciences (Canada)
Fundersnot available
KeywordsAntimicrobialMetaboliteFermentationMetabolomicsBiologySecondary metaboliteBacteriaFood scienceArcticMicrobiologyBiotechnologyBiochemistryEcologyBioinformaticsGene

Abstract

fetched live from OpenAlex

Actinomycetes are a well-established source of natural products with therapeutic potential, particularly for the treatment of infectious diseases. The exploration of microbes from underexplored habitats and the application of novel cultivation conditions are proven strategies for the discovery of novel bioactive metabolites. We set out to explore the metabolic diversity of cold-adapted actinomycetes isolated from marine sediments collected from Canada's Arctic. To screen for metabolites differentially regulated by temperature, 45 strains were fermented at 15 °C and 30 °C and the resulting chemical extracts were tested for antimicrobial activity. Seventy-six percent of the strains exhibited antimicrobial activity against one or more pathogens. Strikingly, extracts prepared from fermentations incubated at 15 °C generated double the number of hits than fermentations conducted at 30 °C. Overall, the majority (44%) of strains exhibited a greater frequency of antimicrobial activity when fermented at 15 °C. Metabolomic analysis (LC-HRMS) was utilized to assess the differential production of metabolites in response to temperature. The results of these experiments will be presented.

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)0.001
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 score0.049
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.018
GPT teacher head0.245
Teacher spread0.227 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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