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Record W2967671156 · doi:10.1038/s41467-019-11673-0

An anaerobic bacterium host system for heterologous expression of natural product biosynthetic gene clusters

2019· article· en· W2967671156 on OpenAlexaff
Tingting Hao, Zhoujie Xie, Min Wang, Liwei Liu, Yuwei Zhang, Weicang Wang, Zhao Zhang, Xuejin Zhao, Pengwei Li, Zhengyan Guo, Shu‐Shan Gao, Chunbo Lou, Guodong Zhang, Justin Merritt, Geoff P. Horsman, Yihua Chen

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsWilfrid Laurier University
FundersNational Institute of Dental and Craniofacial ResearchNational Natural Science Foundation of ChinaMikrobiologický Ústav, Akademie Věd České RepublikyUniversity of Oklahoma Health Sciences CenterUniversity of Massachusetts AmherstUniversity of Oklahoma
KeywordsHeterologous expressionHeterologousHost (biology)GeneBacteriaBiologyGene expressionGene clusterNatural productGeneticsComputational biologyMicrobiologyBiochemistryRecombinant DNA

Abstract

fetched live from OpenAlex

Anaerobic bacteria represent an overlooked rich source of biological and chemical diversity. Due to the challenge of cultivation and genetic intractability, assessing the capability of their biosynthetic gene clusters (BGCs) for secondary metabolite production requires an efficient heterologous expression system. However, this kind of host system is still unavailable. Here, we use the facultative anaerobe Streptococcus mutans UA159 as a heterologous host for the expression of BGCs from anaerobic bacteria. A natural competence based large DNA fragment cloning (NabLC) technique was developed, which can move DNA fragments up to 40-kb directly and integrate a 73.7-kb BGC to the genome of S. mutans UA159 via three rounds of NabLC cloning. Using this system, we identify an anti-infiltration compound, mutanocyclin, from undefined BGCs from human oral bacteria. We anticipate this host system will be useful for heterologous expression of BGCs from anaerobic bacteria.

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)0.000
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 score0.017
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.013
GPT teacher head0.273
Teacher spread0.260 · 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

Citations60
Published2019
Admission routes1
Has abstractyes

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