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Record W3000300130 · doi:10.3389/fimmu.2019.02874

Transcriptome Profiling of Bovine Macrophages Infected by Mycobacterium avium spp. paratuberculosis Depicts Foam Cell and Innate Immune Tolerance Phenotypes

2020· article· en· W3000300130 on OpenAlexafffund
Olivier Ariel, Daniel Gendron, Pier-Luc Dudemaine, Nicolas Gévry, Eveline M. Ibeagha‐Awemu, Nathalie Bissonnette

Bibliographic record

VenueFrontiers in Immunology · 2020
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsAgriculture and Agri-Food CanadaUniversité de Sherbrooke
FundersAgriculture and Agri-Food CanadaUniversité de SherbrookeNatural Sciences and Engineering Research Council of CanadaCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaCompute CanadaDairy Farmers of Canada
KeywordsParatuberculosisBiologyInnate immune systemImmune systemImmunologyTranscriptomeGene expression profilingMicrobiologyGeneGene expressionMycobacteriumGenetics

Abstract

fetched live from OpenAlex

Mycobacterium avium ssp. paratuberculosis (MAP) is the causative agent of Johne’s disease (JD), also known as paratuberculosis, in ruminants. The mechanisms of JD pathogenesis are not fully understood, but it is known that MAP subverts the host immune system by using macrophages as its primary reservoir. Infection of MAP on macrophages is often studied in healthy cows or experimentally infected calves, but reports on macrophages from naturally infected cows are lacking. In our study, primary monocyte-derived macrophages (MDMs) from cows diagnosed as positive (+) or negative (−) for JD were challenged in vitro with live MAP. Analysis using next-generation RNA sequencing revealed that macrophages from JD(+) cows did not present a definite pattern of response to MAP infection. Interestingly, a considerable number of genes, up to 1,436, were differentially expressed in JD(−) macrophages. The signatures of the infection time course of 1h, 4h, 8h, and 24h revealed differential expression of ARG2, COL1A1, CCL2, CSF3, IL1A, IL6, IL10, PTGS2, PTX3, SOCS3, TNF, and TNFAIP6 among other genes, with major effects on host signaling pathways. While several immune pathways were affected by MAP, other pathways related to hepatic fibrosis/hepatic stellate cell activation, lipid homeostasis, such as LXR/RXR (liver X receptor/retinoid X receptor) activation pathways, and autoimmune diseases (rheumatoid arthritis or atherosclerosis) also reponsed to the presence of live MAP. Comparison of the profiles of the unchallenged MDMs from JD(+) versus JD(−) cows showed that 868 genes were differentially expressed suggesting these genes were already affected before monocytes differentiated into macrophages. The downregulated genes predominantly modified the general cell metabolism by downregulating amino acid synthesis and affecting cholesterol biosynthesis and other energy production pathways while introducing a pro-fibrotic pattern associated with foam cells. The upregulated genes indicated that lipid homeostasis was already supporting fat storage in uninfected JD(+) MDMs. For JD(+) MDMs, differential gene expression expounds long-term mechanisms established during disease progression of paratuberculosis. Therefore, MAP could further promote disease persistence by influencing long-term macrophage behavior by using both tolerance and fat-storage states. This report contributes to a better understanding of MAP’s controls over the immune cell response and mechanisms of MAP survival.

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 categoriesMeta-epidemiology (narrow)
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 score0.071
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.232
Teacher spread0.224 · 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.

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

Citations71
Published2020
Admission routes2
Has abstractyes

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