Insights Into the Resistome of Bovine Clinical Mastitis Microbiome, a Key Factor in Disease Complication

• Published in: Frontiers in microbiology 2020-06, Vol.11
• Main Authors: Hoque, M. Nazmul, Istiaq, Arif, Clement, Rebecca A., Gibson, Keylie M., Saha, Otun, Islam, Ovinu Kibria, Abir, Ruhshan Ahmed, Sultana, Munawar, Siddiki, AMAM Zonaed, Crandall, Keith A., Hossain, M. Anwar
• Format: Article
• Language: English
• Subjects: clinical mastitis; in vitro resistance assays; Microbiology; microbiome; resistome; whole metagenome sequencing
• ISSN: 1664-302X; 1664-302X
• DOI: 10.3389/fmicb.2020.00860

Bovine clinical mastitis (CM) is one of the most prevalent diseases caused by a wide range of resident microbes. The emergence of antimicrobial resistance in CM bacteria is well-known, however, the genomic resistance composition (the resistome) at the microbiome-level is not well characterized. In this study, we applied whole metagenome sequencing (WMS) to characterize the resistome of the CM microbiome, focusing on antibiotics and metals resistance, biofilm formation (BF), and quorum sensing (QS) along with in vitro resistance assays of six selected pathogens isolated from the same CM samples. The WMS generated an average of 21.13 million reads (post-processing) from 25 CM samples that mapped to 519 bacterial strains, of which 30.06% were previously unreported. We found a significant ( P = 0.001) association between the resistomes and microbiome composition with no association with cattle breed, despite significant differences in microbiome diversity among breeds. The in vitro investigation determined that 76.2% of six selected pathogens considered “biofilm formers” actually formed biofilms and were also highly resistant to tetracycline, doxycycline, nalidixic acid, ampicillin, and chloramphenicol and remained sensitive to metals (Cr, Co, Ni, Cu, Zn) at varying concentrations. We also found bacterial flagellar movement and chemotaxis, regulation and cell signaling, and oxidative stress to be significantly associated with the pathophysiology of CM. Thus, identifying CM microbiomes, and analyzing their resistomes and genomic potentials will help improve the optimization of therapeutic schemes involving antibiotics and/or metals usage in the prevention and control of bovine CM.