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Microbiome dynamics and genomic determinants of bovine mastitis.
Hoque, M Nazmul; Istiaq, Arif; Rahman, M Shaminur; Islam, M Rafiul; Anwar, Azraf; Siddiki, A M A M Zonaed; Sultana, Munawar; Crandall, Keith A; Hossain, M Anwar.
Afiliação
  • Hoque MN; Department of Microbiology, University of Dhaka, Dhaka 1000, Bangladesh; Department of Gynecology, Obstetrics and Reproductive Health, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur 1706, Bangladesh.
  • Istiaq A; Department of Microbiology, University of Dhaka, Dhaka 1000, Bangladesh; Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
  • Rahman MS; Department of Microbiology, University of Dhaka, Dhaka 1000, Bangladesh.
  • Islam MR; Department of Microbiology, University of Dhaka, Dhaka 1000, Bangladesh.
  • Anwar A; 47-07 41st Street, New York, USA.
  • Siddiki AMAMZ; Department of Pathology and Parasitology, Chattogram Veterinary and Animal Sciences University, Chattogram 4202, Bangladesh.
  • Sultana M; Department of Microbiology, University of Dhaka, Dhaka 1000, Bangladesh.
  • Crandall KA; Computational Biology Institute and Department of Biostatistics & Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA.
  • Hossain MA; Department of Microbiology, University of Dhaka, Dhaka 1000, Bangladesh. Electronic address: hossaina@du.ac.bd.
Genomics ; 112(6): 5188-5203, 2020 11.
Article em En | MEDLINE | ID: mdl-32966856
ABSTRACT
The milk of lactating cows presents a complex ecosystem of interconnected microbial communities which can influence the pathophysiology of mastitis. We hypothesized possible dynamic shifts of microbiome composition and genomic features with different pathological conditions of mastitis (Clinical Mastitis; CM, Recurrent CM; RCM, Subclinical Mastitis; SCM). To evaluate this hypothesis, we employed whole metagenome sequencing (WMS) in 20 milk samples (CM, 5; RCM, 6; SCM, 4; H, 5) to unravel the microbiome dynamics, interrelation, and relevant metabolic functions. The WMS data mapped to 442 bacterial, 58 archaeal and 48 viral genomes with distinct variation in microbiome composition (CM > H > RCM > SCM). Furthermore, we identified a number of microbial genomic features, including 333, 304, 183 and 50 virulence factors-associated genes (VFGs) and 48, 31, 11 and 6 antibiotic resistance genes (ARGs) in CM, RCM, SCM, and H-microbiomes, respectively. We also detected different metabolic pathway and functional genes associated with mastitis pathogenesis. Therefore, profiling microbiome dynamics in different conditions of mastitis and associated microbial genomic features contributes to developing microbiome-based diagnostics and therapeutics for bovine mastitis.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Microbiota / Mastite Bovina Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Microbiota / Mastite Bovina Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article