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Record W2017760728 · doi:10.1038/sj.jim.7000102

Development of an Escherichia coli expression system and thermostability screening assay for libraries of mutant xylanase

2000· article· en· W2017760728 on OpenAlexafffund
R Ebanks, M. Susan DuPont, F. Shareck, Rolf Morosoli, D. Kluepfel, Claude Dupont

Bibliographic record

VenueJournal of Industrial Microbiology & Biotechnology · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsArmand Frappier MuseumInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThermostabilityMutantEscherichia coliBiologyStreptomycesMolecular biologyXylanaseDirected evolutionBiochemistryMicrobiologyBacteriaGeneEnzymeGenetics

Abstract

fetched live from OpenAlex

A thermostability screening assay was developed using an Escherichia coli expression system to express Streptomyces lividans xylanase A (XlnA). The screening system was tested using mutants randomized at position 49 of the S. lividans XlnA gene, a position previously shown to confer thermostability with a I49P point mutation. The library was cloned into an E. coli expression vector and transformed into XL1-blue bacteria. The resulting clones were screened for increased thermostability with respect to wild-type XlnA. Using this assay, we isolated the I49P mutant previously shown to be thermostable, as well as novel I49A and I49C mutants. The I49A and I49C mutants were shown to have 2.8- to 8-fold increase in thermostability over that of wild-type XlnA. The results show that the screening assay can selectively enrich for clones with increased thermostability and is suitable for screening small- to medium-sized libraries of 5000-20,000 clones.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.022
GPT teacher head0.233
Teacher spread0.211 · 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 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

Citations10
Published2000
Admission routes2
Has abstractyes

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