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Record W2956606079 · doi:10.1007/s10295-019-02198-y

Advances in microbial culturing conditions to activate silent biosynthetic gene clusters for novel metabolite production

2019· review· en· W2956606079 on OpenAlexafffund
Hailey Tomm, Lorena Ucciferri, Avena C. Ross

Bibliographic record

VenueJournal of Industrial Microbiology & Biotechnology · 2019
Typereview
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaQueen's University
KeywordsGeneBiologyBacteriaComputational biologyGenomeMetaboliteSecondary metaboliteEnzymeBiochemistryBiotechnologyGenetics

Abstract

fetched live from OpenAlex

Natural products (NPs) produced by bacteria and fungi are often used as therapeutic agents due to their complex structures and wide range of bioactivities. Enzymes that build NPs are encoded by co-localized biosynthetic gene clusters (BGCs), and genome sequencing has recently revealed that many BGCs are "silent" under standard laboratory conditions. There are numerous methods used to activate "silent" BGCs that rely either upon altering culture conditions or genetic modification. In this review, we discuss several recent microbial cultivation methods that have been used to expand the scope of NPs accessible in the laboratory. These approaches are divided into three categories: addition of a physical scaffold, addition of small molecule elicitors, and co-cultivation with another microbe.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.067
GPT teacher head0.334
Teacher spread0.267 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations78
Published2019
Admission routes2
Has abstractyes

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