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Record W4283021992 · doi:10.1093/g3journal/jkac154

The MyLO CRISPR-Cas9 toolkit: a markerless yeast localization and overexpression CRISPR-Cas9 toolkit

2022· article· en· W4283021992 on OpenAlexafffund
Björn D. M. Bean, Malcolm Whiteway, Vincent J. J. Martin

Bibliographic record

VenueG3 Genes Genomes Genetics · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsConcordia University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaConcordia UniversityUniversity of Texas at Austin
KeywordsCRISPRCas9BiologyGenome editingComputational biologyPlasmidTrans-activating crRNAGuide RNAGeneGeneticsGreen fluorescent proteinSelectable marker

Abstract

fetched live from OpenAlex

The genetic tractability of the yeast Saccharomyces cerevisiae has made it a key model organism for basic research and a target for metabolic engineering. To streamline the introduction of tagged genes and compartmental markers with powerful Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) - CRISPR-associated protein 9 (Cas9)-based genome editing tools, we constructed a Markerless Yeast Localization and Overexpression (MyLO) CRISPR-Cas9 toolkit with 3 components: (1) a set of optimized Streptococcus pyogenes Cas9-guide RNA expression vectors with 5 selectable markers and the option to either preclone or cotransform the gRNAs; (2) vectors for the one-step construction of integration cassettes expressing an untagged or green fluorescent protein/red fluorescent protein/hemagglutinin-tagged gene of interest at one of 3 levels, supporting localization and overexpression studies; and (3) integration cassettes containing moderately expressed green fluorescent protein- or red fluorescent protein-tagged compartmental markers for colocalization experiments. These components allow rapid, high-efficiency genomic integrations and modifications with only transient selection for the Cas9 vector, resulting in markerless transformations. To demonstrate the ease of use, we applied our complete set of compartmental markers to colabel all target subcellular compartments with green fluorescent protein and red fluorescent protein. Thus, the MyLO toolkit packages CRISPR-Cas9 technology into a flexible, optimized bundle that allows the stable genomic integration of DNA with the ease of use approaching that of transforming plasmids.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.011

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 communication0.0010.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.006

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 head0.007
GPT teacher head0.266
Teacher spread0.259 · 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
GenreMethods

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

Citations27
Published2022
Admission routes2
Has abstractyes

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