An in vitro fermentation model to study the impact of bacteriophages targeting Shiga toxin-encoding Escherichia coli on the colonic microbiota

NPJ BIOFILMS AND MICROBIOMES(2022)

引用 2|浏览14
暂无评分
摘要
Lytic bacteriophages are considered safe for human consumption as biocontrol agents against foodborne pathogens, in particular in ready-to-eat foodstuffs. Phages could, however, evolve to infect different hosts when passing through the gastrointestinal tract (GIT). This underlines the importance of understanding the impact of phages towards colonic microbiota, particularly towards bacterial families usually found in the colon such as the Enterobacteriaceae. Here we propose in vitro batch fermentation as model for initial safety screening of lytic phages targeting Shiga toxin-producing Escherichia coli (STEC). As inoculum we used faecal material of three healthy donors. To assess phage safety, we monitored fermentation parameters, including short chain fatty acid production and gas production/intake by colonic microbiota. We performed shotgun metagenomic analysis to evaluate the outcome of phage interference with colonic microbiota composition and functional potential. During the 24 h incubation, concentrations of phage and its host were also evaluated. We found the phage used in this study, named E. coli phage vB_EcoS_Ace (Ace), to be safe towards human colonic microbiota, independently of the donors' faecal content used. This suggests that individuality of donor faecal microbiota did not interfere with phage effect on the fermentations. However, the model revealed that the attenuated STEC strain used as phage host perturbed the faecal microbiota as based on metagenomic analysis, with potential differences in metabolic output. We conclude that the in vitro batch fermentation model used in this study is a reliable safety screening for lytic phages intended to be used as biocontrol agents.
更多
查看译文
关键词
Antimicrobials,Applied microbiology,Metagenomics,Microbiota,Next-generation sequencing,Life Sciences,general,Microbiology,Medical Microbiology,Microbial Ecology,Microbial Genetics and Genomics
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要