five

Omics-based insights into flavor development and microbial succession within surface-ripened cheese

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://www.ncbi.nlm.nih.gov/sra/ERP017154
下载链接
链接失效反馈
官方服务:
资源简介:
In this study, a young Cheddar curd was used to produce two types of surface-ripened cheese, using two commercial smear-culture mixes of yeasts and bacteria. Whole-metagenome shotgun sequencing was used to screen the microbial population within the smear-culture mixes, and on the cheese surface, comparing microorganisms both at species and strain level. The use of two smear mixes, resulted in the development of distinct microbiota on the surface of the two test cheeses. In one case, most of the species inoculated on the cheese established themselves successfully on the cheese surface during ripening; while in the other, some of species inoculated were not detected during ripening and the most dominant bacterial species, Glutamicibacter arilaitensis, was not a constituent of the culture mix. Generally, yeast species, such as Debaryomyces hansenii and Geotrichum candidum, were the dominant duringin the first stage of ripening, but were overtaken by bacterial species, such as Brevibacterium linens and G. arilaitensis, in the later stages of ripening. Using a correlation analysis, it was possible to associate individual microorganisms with volatile compounds detected by GC-MS on the cheese surface. Specifically, D. hansenii correlated with the production of alcohols and carboxylic acids, G. arilaitensis with alcohols, carboxylic acids and ketones and B. linens and G. candidum with sulfur compounds. In addition, metagenomic sequencing was used to analyze the metabolic potential of the microbial population on the surface of the test cheeses, which was involved in important metabolic processes during ripening, presentingrevealing a high relative abundance of metagenomic clusters associated with , related to the modification of color, variation of pH and flavor development.
创建时间:
2021-02-04
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作