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
Department of Microbiology, University of Dhaka, Dhaka, Bangladesh.
Department of Gynecology, Obstetrics and Reproductive Health, Faculty of Veterinary Medicine and Animal Science, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh.
Front Microbiol. 2020 Jun 3;11:860. doi: 10.3389/fmicb.2020.00860. eCollection 2020.
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 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 ( = 0.001) association between the resistomes and microbiome composition with no association with cattle breed, despite significant differences in microbiome diversity among breeds. The 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.
牛临床乳腺炎（CM）是由多种常驻微生物引起的最常见疾病之一。CM细菌中抗菌药物耐药性的出现是众所周知的，然而，微生物群落水平的基因组耐药组成（耐药组）尚未得到很好的表征。在本研究中，我们应用全宏基因组测序（WMS）来表征CM微生物群落的耐药组，重点关注抗生素和金属耐药性、生物膜形成（BF）和群体感应（QS），以及从相同CM样本中分离出的六种选定病原体的耐药性测定。WMS从25个CM样本中平均产生了2113万个读数（后处理），这些读数映射到519个细菌菌株，其中30.06%以前未被报道。我们发现耐药组与微生物群落组成之间存在显著关联（P = 0.001），与牛的品种无关，尽管不同品种之间微生物群落多样性存在显著差异。调查确定，六种被认为是“生物膜形成者”的选定病原体中，76.2%实际上形成了生物膜，并且对四环素、强力霉素、萘啶酸、氨苄青霉素和氯霉素也具有高度耐药性，并且对不同浓度的金属（铬、钴、镍、铜、锌）保持敏感。我们还发现细菌鞭毛运动和趋化性、调节和细胞信号传导以及氧化应激与CM的病理生理学显著相关。因此，识别CM微生物群落，并分析它们的耐药组和基因组潜力将有助于优化涉及抗生素和/或金属使用的治疗方案，以预防和控制牛CM。
