Dataset Information

Transcriptomic in silico analysis of bovine Escherichia coli mastitis highlights its immune-related expressed genes as an effective biomarker.

ABSTRACT:

Background

Mastitis is one of the major diseases causing economic loss to the dairy industry by reducing the quantity and quality of milk. Thus, the objective of this scientific study was to find new biomarkers based on genes for the early prediction before its severity.

Methods

In the present study, advanced bioinformatics including hierarchical clustering, enrichment analysis, active site prediction, epigenetic analysis, functional domain identification, and protein docking were used to analyze the important genes that could be utilized as biomarkers and therapeutic targets for mastitis.

Results

Four differentially expressed genes (DEGs) were identified in different regions of the mammary gland (teat cistern, gland cistern, lobuloalveolar, and Furstenberg's rosette) that resulted in 453, 597, 577, and 636 DEG, respectively. Also, 101 overlapped genes were found by comparing 27 different expressed genes. These genes were associated with eight immune response pathways including NOD-like receptor signaling pathway (IL8, IL18, IL1B, PYDC1) and chemokine signaling pathway (PTK2, IL8, NCF1, CCR1, HCK). Meanwhile, 241 protein-protein interaction networks were developed among overlapped genes. Fifty-seven regulatory events were found between miRNAs, expressed genes, and the transcription factors (TFs) through micro-RNA and transcription factors (miRNA-DEG-TF) regulatory network. The 3D structure docking model of the expressed genes proteins identified their active sites and the binding ligands that could help in choosing the appropriate feed or treatment for affected animals.

Conclusions

The novelty of the distinguished DEG and their pathways in this study is that they can precisely improve the detection biomarkers and treatments techniques of cows' Escherichia coli mastitis disease due to their high affinity with the target site of the mammary gland before appearing the symptoms.

SUBMITTER: Farmanullah F

PROVIDER: S-EPMC8511192 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Publications

Transcriptomic in silico analysis of bovine Escherichia coli mastitis highlights its immune-related expressed genes as an effective biomarker.

Farmanullah Farmanullah F Liang Xianwei X Khan Faheem Ahmed FA Salim Mohammad M Rehman Zia Ur ZU Khan Momen M Talpur Hira Sajjad HS Schreurs N M NM Gouda Mostafa M Khan Sami Ullah SU Shujun Zhang Z

Journal, genetic engineering & biotechnology 20211012 1

<h4>Background</h4>Mastitis is one of the major diseases causing economic loss to the dairy industry by reducing the quantity and quality of milk. Thus, the objective of this scientific study was to find new biomarkers based on genes for the early prediction before its severity.<h4>Methods</h4>In the present study, advanced bioinformatics including hierarchical clustering, enrichment analysis, active site prediction, epigenetic analysis, functional domain identification, and protein docking were ...[more]

PMID: 34637035

Similar Datasets

Project description:BackgroundEscherichia coli bovine mastitis is a disease of significant economic importance in the dairy industry. Molecular characterization of mastitis-associated E. coli (MAEC) did not result in the identification of common traits. Nevertheless, a mammary pathogenic E. coli (MPEC) pathotype has been proposed suggesting virulence traits that differentiate MAEC from commensal E. coli. The present study was designed to investigate the MPEC pathotype hypothesis by comparing the genomes of MAEC and commensal bovine E. coli.ResultsWe sequenced the genomes of eight E. coli isolated from bovine mastitis cases and six fecal commensal isolates from udder-healthy cows. We analyzed the phylogenetic history of bovine E. coli genomes by supplementing this strain panel with eleven bovine-associated E. coli from public databases. The majority of the isolates originate from phylogroups A and B1, but neither MAEC nor commensal strains could be unambiguously distinguished by phylogenetic lineage. The gene content of both MAEC and commensal strains is highly diverse and dominated by their phylogenetic background. Although individual strains carry some typical E. coli virulence-associated genes, no traits important for pathogenicity could be specifically attributed to MAEC. Instead, both commensal strains and MAEC have very few gene families enriched in either pathotype. Only the aerobactin siderophore gene cluster was enriched in commensal E. coli within our strain panel.ConclusionsThis is the first characterization of a phylogenetically diverse strain panel including several MAEC and commensal isolates. With our comparative genomics approach we could not confirm previous studies that argue for a positive selection of specific traits enabling MAEC to elicit bovine mastitis. Instead, MAEC are facultative and opportunistic pathogens recruited from the highly diverse bovine gastrointestinal microbiota. Virulence-associated genes implicated in mastitis are a by-product of commensalism with the primary function to enhance fitness in the bovine gastrointestinal tract. Therefore, we put the definition of the MPEC pathotype into question and suggest to designate corresponding isolates as MAEC.

Dataset Information

Transcriptomic in silico analysis of bovine Escherichia coli mastitis highlights its immune-related expressed genes as an effective biomarker.

Background

Methods

Results

Conclusions

Publications

Transcriptomic in silico analysis of bovine Escherichia coli mastitis highlights its immune-related expressed genes as an effective biomarker.

Similar Datasets

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