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Record W3097404115 · doi:10.1186/s12863-020-00925-4

Functional analysis of bovine interleukin-10 receptor alpha in response to Mycobacterium avium subsp. paratuberculosis lysate using CRISPR/Cas9

2020· article· en· W3097404115 on OpenAlexafffund
S. Mallikarjunappa, Umesh K. Shandilya, Ankita Sharma, Kristen Lamers, Nathalie Bissonnette, Niel A. Karrow, Kieran G. Meade

Bibliographic record

VenueBMC Genetics · 2020
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaTeagasc
KeywordsParatuberculosisLysisMycobacterium avium subsp. paratuberculosisCRISPRAlpha (finance)BiologyMicrobiologyMycobacteriumMolecular biologyBacteriaMedicineGeneticsGene

Abstract

fetched live from OpenAlex

BACKGROUND: The interleukin-10 receptor alpha (IL10RA) gene codes for the alpha chain of the IL-10 receptor which binds the cytokine IL-10. IL-10 is an anti-inflammatory cytokine with immunoregulatory function during the pathogenesis of many inflammatory disorders in livestock, including Johne's disease (JD). JD is a chronic enteritis in cattle caused by Mycobacterium avium subsp. paratuberculosis (MAP) and is responsible for significant economic losses to the dairy industry. Several candidate genes including IL10RA have been found to be associated with JD. The aim of this study was to better understand the functional significance of IL10RA in the context of immune stimulation with MAP cell wall lysate. RESULTS: An IL10RA knock out (KO) bovine mammary epithelial cell (MAC-T) line was generated using the CRISPR/cas9 (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9) gene editing system. These IL10RA KO cells were stimulated with the immune stimulant MAP lysate +/- IL-10, or with LPS as a positive control. In comparison to unedited cells, relative quantification of immune-related genes after stimulation revealed that knocking out IL10RA resulted in upregulation of pro-inflammatory cytokine gene expression (TNFA, IL1A, IL1B and IL6) and downregulation of suppressor of cytokine signaling 3 (SOCS3), a negative regulator of pro-inflammatory cytokine signaling. At the protein level knocking out IL10RA also resulted in upregulation of inflammatory cytokines - TNF-α and IL-6 and chemokines - IL-8, CCL2 and CCL4, relative to unedited cells. CONCLUSIONS: The findings of this study illustrate the broad and significant effects of knocking out the IL10RA gene in enhancing pro-inflammatory cytokine expression and further support the immunoregulatory role of IL10RA in eliciting an anti-inflammatory response as well as its potential functional involvement during the immune response associated with JD.

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)0.000
metaresearch head score (Gemma)0.000
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
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.076
GPT teacher head0.331
Teacher spread0.255 · 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

Citations34
Published2020
Admission routes2
Has abstractyes

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