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. Graphical abstract

Molecular Genomic Study of Inhibin Molecule Production through Granulosa Cell Gene Expression in Inhibin-Deficient Mice

“…The ODEGs were used as characteristic genes in hCG stimulation and Inhibin α knockout (Inha−/−) female mice granulosa cells. This observation is in agreement with FarmanUllah, Liang, Khan, Salim, Rehman, Khan, Talpur, Schreurs, Gouda, Khan and Shujun [ 22 ] who mentioned that ODEGs can effectively work as biomarkers for immune-related tumors. In which, 341 DEGs had high relevance, with a significant correlation coefficient ( p < 0.000001) in both Inha−/− vs. WT group and Inha−/− (hCG) vs. WT(hCG) group which means that they could be used as characteristic genes in hCG stimulation and Inhibin α knockout (Inha−/−) female mice granulosa cells.…”

“…MicroRNAs (miRNAs) assume a pivotal role in controlling inborn and versatile immunity in humans and animals [ 22 , 23 ]. A total number of eight miRNAs and seven TFs that have the potential to regulate ODEGs in the co-expression network are listed in Table 4 and Table 5 , respectively.…”

Elucidating ascorbate and aldarate metabolism pathway characteristics via integration of untargeted metabolomics and transcriptomics of the kidney of high-fat diet-fed obese mice

“…Farmanullah et al . [ 20 ] used advanced bioinformatics methods such as hierarchical clustering, enrichment analysis, active site prediction, and functional domain identification through transcriptomics to analyze important genes that could be used as biomarkers and therapeutic targets for mastitis. Talpur et al .…”

SNPs in splicing region and miRNA binding region of Bos taurus TREM-1 gene reveals its association with mastitis

“…A healthy immune system is key to the high quality and quantity of milk in dairy cows. Mastitis remains a major concern to the dairy industry and a robust breeding plan that can assure improvements against prevailing concerns of mastitis is highly encouraged (Farmanullah et al, 2021). The intramammary infection that includes 75% of leukocytes and 25% of epithelial cells is determined as somatic cell count and is considered a good predictor of mastitis (Sharma et al, 2011).…”

“…The genetic evaluation of mastitis is carried out by an algorithm where somatic cell count is transformed into somatic cell score to maintain distribution normality (Alam et al 2015). Several research groups investigate the host genome for suitable targets that can bring resistance against mastitis especially the SNPs in immune-related genes (Bhattarai et al 2017, Farmanullah et al, 2021. TREM-1, or Triggering Receptor Expressed on Myeloid Cells 1, a cell surface receptor protein primarily found on neutrophils and monocytes (myeloid cells), plays an important role in the regulation of the immune response, particularly in the context of inflammation and innate immunity (Pandupuspitasari et al, 2016).…”