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Record W2579645842 · doi:10.1021/acschembio.6b01002

An Engineered Allele of <i>afsQ1</i> Facilitates the Discovery and Investigation of Cryptic Natural Products

2017· article· en· W2579645842 on OpenAlexafffund
Martin Daniel-Ivad, Stephanie Tan, Rachna Dhanjal, Daniel Socko, Patricia Pak, Tomas Gverzdys, Marie A. Elliot, Justin R. Nodwell

Bibliographic record

VenueACS Chemical Biology · 2017
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsMcMaster UniversityUniversity of Toronto
FundersCanadian Institutes of Health ResearchCystic Fibrosis CanadaGovernment of Canada
KeywordsBiologyStreptomycesComputational biologyDrug discoveryGeneAntibioticsMultiple drug resistanceAntimicrobialRegulatorAntibiotic resistanceGeneticsMicrobiologyBacteriaBioinformatics

Abstract

fetched live from OpenAlex

New approaches to antimicrobial discovery are needed to address the growing threat of antibiotic resistance. The Streptomyces genus, a proven source of antibiotics, is recognized as having a large reservoir of untapped secondary metabolic genes, many of which are likely to produce uncharacterized compounds. However, most of these compounds are currently inaccessible, as they are not expressed under standard laboratory conditions. Here, we present a novel methodology for activating these "cryptic" metabolites by heterologously expressing a constitutively active pleiotropic regulator. By screening wild Streptomyces isolates, we identified the antibiotic siamycin-I, a lasso peptide that we show is active against multidrug pathogens. We further revealed that siamycin-I interferes with cell wall integrity via lipid II. This new technology has the potential to be broadly applied for use in the discovery of additional "cryptic" metabolites.

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)0.000
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 score0.006
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.015
GPT teacher head0.249
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

Citations45
Published2017
Admission routes2
Has abstractyes

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