Evidence map›Paper›PMID 39392284›Full record

ArticleVeterinary medicine and science2024

Network and systems biology approaches help investigate gene regulatory interactions between Salmonella disease and host in chickens: Model-based in silico evidence combined with gene expression assays.

Reza Tohidi, Hoda Javaheri Bargourooshi, Arash Javanmard

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Article in Veterinary medicine and science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Reza TohidiDepartment of Animal Science, Faculty of Agriculture, University of Torbat-e Jam, Torbat-e Jam, Iran.ORCID 0000-0002-4643-7836
Hoda Javaheri BargourooshiDepartment of Animal Production Management, Animal Science Research Institute of Iran (ASRI), Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran.ORCID 0000-0001-6244-8984
Arash JavanmardDepartment of Animal Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.ORCID 0000-0001-7998-9875

Funding

ASRIUniversity of Torbat-e Jam
6 · The paper itself

Abstract

backgroundSalmonella enteritidis (SE), a previously widespread infectious disease, is still cited as a major factor in economic losses in commercial chicken production. The host's genetic immune system determines the pathogenicity of a particular bacterium. To shed light on this topic, it was necessary to understand the key candidate genes essential for regulating susceptibility and resistance to the target disease. The field of poultry farming in particular has benefited greatly from the connection between quantitative and molecular genetics.

objectivesThis study aims to identify the most important immune-related genes and their signalling pathways (gene ontology, co-expression and interactions) and to analyse their accumulation in host-resistant SE diseases by combining gene expression assays with model-based in silico evidence.

methodsA two-step experimental design is followed. To start, we used free computational tools and online bioinformatics resources, including predicting gene function using a multiple association network integration algorithm (geneMania), the Kyoto Encyclopedia of Genes and Genomes, the Annotation, Visualization and Integrated Discovery (DAVID) database and the stimulator of interferon genes. Natural resistance-associated macrophage protein 1 (NRAMP1), Toll-like receptor 4 (TLR4), interferon-γ (IFNγ), immunoglobulin Y (IgY) and interleukin 8 (IL8) were among the five genes whose expression levels in liver, spleen, and cecum were evaluated at 1107 SE after 48 h of inoculation. This molecular study was developed in the second phase of research to validate the in silico observations. Next, we use five promising biomarkers for relative real-time polymerase chain reaction (PCR) quantification: TLR4, IL8, NRAMP1, IFNγ and IgY genes in two case and control assays. The 2

resultsInterestingly, the results of our study suggest the involvement of various factors in the host immune response to Salmonella. These include inducible nitric oxide synthase, NRAMP1, immunoglobulin light chain (IgL), transforming growth factor B family (TGFb2, TGFb3 and TGFb4), interleukin 2 (IL2), apoptosis inhibitor protein 1 (IAP1), TLR4, myeloid differentiation protein 2 (MD2), IFNγ, caspase 1 (CASP1), lipopolysaccharide-induced tumour necrosis factor (LITAF), cluster of differentiation 28 (CD28) and prosaposin (PSAP). The summary of gene ontology and related genes found for SE resistance was surprisingly comprehensive and covered the following topics: positive regulation of endopeptidase activity, interleukin-8 production, chemokine production, interferon-gamma production, interleukin-6 production, positive regulation of mononuclear cell proliferation and response to interferon-gamma. The role of these promising biomarkers in our networks against SE susceptibility is essentially confirmed by these results. After 48 h, the spleen showed significant expression of the tissue-specific gene expression patterns for NRAMP1 and IL8 in the cecum, spleen and liver. Based on this information, this report searches for resistance and susceptibility lineages in most genomic regions for SE.

conclusionsIn conclusion, the development of an appropriate selection program to improve resistance to salmonellosis can be facilitated by a comprehensive understanding of the immune responses of the chicken immune system after SE exposure.

Indexed as

ChickensComputer SimulationPoultry DiseasesSalmonella enteritidisSalmonella Infections, AnimalSystems BiologyAnimalsGene ExpressionGene Regulatory Networkscandidate genegenetic resistancepolymorphismSalmonella enteritidis

Identifiers

PMID39392284
PMCPMC11467963

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