Evidence map›Paper›PMID 41547986›Full record

ArticleScientific reports2026

Integrated in vivo and in silico analysis of immune gene expression in cattle infected with Brucella abortus.

Dalia M Mabrouk, Mohamed El-Diasty, Sekena H Abdel-Aziem

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In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Dalia M MabroukDepartment of Cell Biology, National Research Centre, Giza, 12622, Egypt. Dalia.mamdouh@ymail.com.
Mohamed El-DiastyAgricultural Research Center (ARC), Animal Health Research Institute-Mansoura provincial Laboratory (AHRI-Mansoura)-Giza, Cairo, 12618, Egypt.
Sekena H Abdel-AziemDepartment of Cell Biology, National Research Centre, Giza, 12622, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brucella abortus is an intracellular pathogen that causes infection in cattle, leading to reproductive losses and posing a zoonotic risk to humans. Understanding host immune responses at the molecular level is essential for developing targeted diagnostics and control strategies. This study aimed to investigate the expression of immune-related genes in Bos taurus naturally infected with Brucella abortus using integrated in vivo and in silico approaches. The infection was characterized as chronic based on persistent seropositivity and historical herd records of infection for 12–18 months prior to sampling. Gene expression analysis revealed significant upregulation of NOD2 and IL10, indicating simultaneous activation of pro-inflammatory signaling and regulatory responses during chronic infection. In contrast, TLR9 was markedly downregulated, suggesting immune evasion mechanisms that suppress endosomal DNA recognition pathways. The expression levels of TLR5 and TLR6 remained unchanged, possibly due to the pathogen’s avoidance of flagellin and lipoprotein recognition. Venn diagram and protein–protein interaction (PPI) analyses highlighted functional overlaps among genes involved in infection response, Toll-like receptor signaling, and KEGG Brucella pathways. GO and KEGG enrichment further confirmed the involvement of the MyD88-dependent TLR signaling pathway, nitric oxide biosynthesis, and pathogen recognition mechanisms. These findings emphasize the complexity of the host immune response to chronic brucellosis, where the immune system attempts to control infection while being subverted by bacterial strategies. The identified gene expression patterns not only enhance our understanding of Brucella pathogenesis but also provide potential molecular markers that could guide future strategies for disease diagnosis and therapeutic intervention. Overall, this study contributes valuable insights into the host-pathogen interactions that define chronic Brucella abortus infection in cattle.

Indexed as

Brucella abortusBrucellosis, BovineAnimalsCattleComputer SimulationGene Expression ProfilingGene Expression RegulationHost-Pathogen InteractionsNod2 Signaling Adaptor ProteinSignal TransductionNod2 Signaling Adaptor ProteinBos taurusBrucella abortusGene expressionInnate immunityTLR signaling

Identifiers

PMID41547986
PMCPMC12820187

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.