Resistome and microbiome profiling of bovine milk following antimicrobial dry cow therapy: insights from short- and long-read metagenomic sequencing

抗菌干奶期牛乳耐药组和微生物组分析:来自短读长和长读长宏基因组测序的启示

阅读:2

Abstract

Selective antimicrobial dry cow therapy (DCT) is implemented as part of mastitis control programs, particularly in dairy cows with recent clinical episodes or elevated somatic cell counts. In this study, we investigated the effects of the use of antimicrobials at drying-off on the milk microbiota and resistome by comparing treated (T, n=18) and untreated (NT, n=13) cows. Milk samples from all animals were analyzed using short-read Illumina shotgun sequencing and a subset of 10 samples were also subjected to long-read Oxford Nanopore Technologies (ONT) sequencing. No significant differences in microbial composition or diversity were observed between treated and untreated groups with either technique, indicating that antimicrobial DCT may not induce long-term shifts in the milk microbiota. However, cows receiving antibiotic treatment showed a higher diversity and abundance of genetic determinants of resistance (GDRs) in their milk resistome. Findings from the two sequencing platforms revealed limited concordance in antimicrobial resistance gene content, highlighting that sequencing platform and bioinformatic pipeline choices substantially influence resistome profiling outcomes. Furthermore, the high proportion of host DNA limited sequencing depth and sensitivity, underscoring the need for improved host DNA depletion or targeted enrichment strategies. This study provides insights into the biological and methodological challenges of milk resistome characterization, particularly in low-biomass, host-DNA-rich samples and demonstrates the lack of standardized analytical approaches in resistome studies. Overall, our findings support the prudent use of antibiotics and highlight the need for further longitudinal studies to clarify the temporal dynamics of antimicrobial DCT effects on the milk resistome and microbiota.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。