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Record W2044515683 · doi:10.1007/s10295-009-0678-9

Fermentative production of self-toxic fungal secondary metabolites

2009· article· en· W2044515683 on OpenAlexaff
Maya P. Singh, Margaret Leighton, Laurel R. Barbieri, Deborah M. Roll, Susan E. Urbance, Linda Hoshan, Leonard A. McDonald

Bibliographic record

VenueJournal of Industrial Microbiology & Biotechnology · 2009
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsMicrobiologyChemistryIndustrial microbiologySecondary metabolismFermentationBiotechnologyFood scienceBiologyBiochemistryBiosynthesisEnzyme

Abstract

fetched live from OpenAlex

Fungi are well known for their vast diversity of secondary metabolites that include many life-saving drugs and highly toxic mycotoxins. In general, fungal cultures producing such metabolites are immune to their toxic effects. However, some are known to produce self-toxic compounds that can pose production optimization challenges if the metabolites are needed in large amounts for chemical modification. One such culture, LV-2841, was identified as the lead for one of our exploratory projects. This culture was found to be a slow grower that produced trace amounts of a known metabolite, cercosporamide, under the standard flask fermentation conditions, and extensive medium optimization studies failed to yield higher titers. Poor growth of the culture in liquid media was attributed to the self-toxicity of cercosporamide to the producing organism, and the minimum inhibitory concentration (MIC) of cercosporamide was estimated to be in the range of 8-16 microg/ml. Fermentations carried out in media containing Diaion HP20 resin afforded significantly higher titers of the desired compound. While several examples of resin-based fermentations of soil streptomyces have been published, this approach has rarely been used for fungal fermentations. Over a 100-fold increase in the production titer of cercosporamide, a self-toxic secondary metabolite, was achieved by supplementing the production medium with a commercially available neutral adsorbent resin.

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 score0.035
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0010.001
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 head0.253
Teacher spread0.235 · 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

Citations40
Published2009
Admission routes1
Has abstractyes

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