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Record W3187929447 · doi:10.3389/fgene.2021.733674

Rapid CRISPR/Cas9 Editing of Genotype IX African Swine Fever Virus Circulating in Eastern and Central Africa

2021· article· en· W3187929447 on OpenAlexfundno aff
Hussein M. Abkallo, Nicholas Svitek, Bernard Oduor, Elias Awino, Sonal Henson, Samuel O. Oyola, Stephen Mwalimu, Nacrya Assad-Garcia, W. H. Fuchs, Sanjay Vashee, Lucilla Steinaa

Bibliographic record

VenueFrontiers in Genetics · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
FundersConsortium of International Agricultural Research CentersInternational Development Research Centre
KeywordsCRISPRVirologyAfrican swine fever virusBiologyCas9VirusGenotypeGenome editingRecombinant DNAVirulenceGeneGenetics

Abstract

fetched live from OpenAlex

African swine fever virus (ASFV) is the etiological agent of a contagious and fatal disease of domestic pigs that has significant economic consequences for the global swine industry. Due to the lack of effective treatment and vaccines against African swine fever, there is an urgent need to leverage cutting-edge technologies and cost-effective approaches for generating and purifying recombinant virus to fast-track the development of live-attenuated ASFV vaccines. Here, we describe the use of the CRISPR/Cas9 gene editing and a cost-effective cloning system to produce recombinant ASFVs. Combining these approaches, we developed a recombinant virus lacking the non-essential gene A238L (5EL) in the highly virulent genotype IX ASFV (ASFV-Kenya-IX-1033) genome in less than 2 months as opposed to the standard homologous recombination with conventional purification techniques which takes up to 6 months on average. Our approach could therefore be a method of choice for less resourced laboratories in developing nations.

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 score0.039
Threshold uncertainty score0.794

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 science0.0000.000
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 head0.010
GPT teacher head0.247
Teacher spread0.238 · 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

Citations24
Published2021
Admission routes1
Has abstractyes

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