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Record W3092703989 · doi:10.1038/s41467-020-19138-5

GPAHex-A synthetic biology platform for Type IV–V glycopeptide antibiotic production and discovery

2020· article· en· W3092703989 on OpenAlexafffund
Min Xu, Wenliang Wang, Nicholas Waglechner, Elizabeth Culp, Allison K. Guitor, Gerard D. Wright

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health Research
KeywordsGlycopeptideGlycopeptide antibioticAntibioticsSynthetic biologyBiologyComputational biologyDrug discoveryMicrobiologyBioinformaticsBacteriaGeneticsVancomycinStaphylococcus aureus

Abstract

fetched live from OpenAlex

Glycopeptide antibiotics (GPAs) are essential for the treatment of severe infectious diseases caused by Gram-positive bacteria. The emergence and spread of GPA resistance have propelled the search for more effective GPAs. Given their structural complexity, genetic intractability, and low titer, expansion of GPA chemical diversity using synthetic or medicinal chemistry remains challenging. Here we describe a synthetic biology platform, GPAHex (GPA Heterologous expression), which exploits the genes required for the specialized GPA building blocks, regulation, antibiotic transport, and resistance for the heterologous production of GPAs. Application of the GPAHex platform results in: (1) a 19-fold increase of corbomycin titer compared to the parental strain, (2) the discovery of a teicoplanin-class GPA from an Amycolatopsis isolate, and (3) the overproduction and characterization of a cryptic nonapeptide GPA. GPAHex provides a platform for GPA production and mining of uncharacterized GPAs and provides a blueprint for chassis design for other natural product classes.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.782
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0000.001
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 head0.050
GPT teacher head0.320
Teacher spread0.270 · 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

Citations46
Published2020
Admission routes2
Has abstractyes

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