Systems Biology–Derived Genetic Signatures of Mastitis in Dairy Cattle: A New Avenue for Drug Repurposing

Animals

James M. Reecy¹  Hadi Atashi²  Abbas Pakdel³  Somayeh Sharifi³  Mahmood Motamedi⁴  Maryam Lotfi Shahreza⁵  Nasser Ghadiri⁶  Esmaeil Ebrahimie⁷ 

[1] Department of Animal Science, Iowa State University, Ames, IA 50011, USA;Department of Animal Science, Shiraz University, Shiraz 71946-84334, Iran;Department of Animal Sciences, College of Agriculture, Isfahan University of Technology, Isfahan 84156-83111, Iran;Department of Animal Sciences, University of Tehran, Tehran 1417935840, Iran;Department of Computer Engineering, Shahreza Campus, University of Isfahan, Isfahan 86149-56841, Iran;Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran;Genomics Research Platform, School of Life Sciences, College of Science, Health and Engineering, La Trobe University, Melbourne, VIC 3086, Australia;

关键词: drug repositioning;    drug targets;    E. coli;    mastitis;    gene regulation;    inflammation;   

DOI  :  10.3390/ani12010029

来源: DOAJ

【 摘 要 】

Mastitis, a disease with high incidence worldwide, is the most prevalent and costly disease in the dairy industry. Gram-negative bacteria such as Escherichia coli (E. coli) are assumed to be among the leading agents causing acute severe infection with clinical signs. E. Coli, environmental mastitis pathogens, are the primary etiological agents of bovine mastitis in well-managed dairy farms. Response to E. Coli infection has a complex pattern affected by genetic and environmental parameters. On the other hand, the efficacy of antibiotics and/or anti-inflammatory treatment in E. coli mastitis is still a topic of scientific debate, and studies on the treatment of clinical cases show conflicting results. Unraveling the bio-signature of mastitis in dairy cattle can open new avenues for drug repurposing. In the current research, a novel, semi-supervised heterogeneous label propagation algorithm named Heter-LP, which applies both local and global network features for data integration, was used to potentially identify novel therapeutic avenues for the treatment of E. coli mastitis. Online data repositories relevant to known diseases, drugs, and gene targets, along with other specialized biological information for E. coli mastitis, including critical genes with robust bio-signatures, drugs, and related disorders, were used as input data for analysis with the Heter-LP algorithm. Our research identified novel drugs such as Glibenclamide, Ipratropium, Salbutamol, and Carbidopa as possible therapeutics that could be used against E. coli mastitis. Predicted relationships can be used by pharmaceutical scientists or veterinarians to find commercially efficacious medicines or a combination of two or more active compounds to treat this infectious disease.

【 授权许可】

Unknown