five

High quality food bacterial genomic ressources from fermented vegetables

收藏
DataCite Commons2025-05-16 更新2025-04-16 收录
下载链接:
https://entrepot.recherche.data.gouv.fr/citation?persistentId=doi:10.57745/O4OJA2
下载链接
链接失效反馈
官方服务:
资源简介:
This dataset is associated with a collection of 39 complete bacterial genomes (157 replicons in total) of high sequencing quality and submitted in May 2024 to European Nucleotide Archive (ENA). These strains belong predominantly to homo- and hetero-lactic acid bacteria pivotal in the fermentation process of various vegetables, although other taxa (e.g. Hafnia, Rahnella, Bacillus, Enterococcus and Pseudomonas) were also considered. This dataset also includes the production of genomes for lactic acid bacteria species that have rarely been sequenced, such as Levilactobacillus cerevisiae, Levilactobacillus yonginensis or Pediococcus parvulus. The strains demonstrated optimal growth performance during vegetable fermentation and their genome was sequenced using a combination of third generation long-reads ONT and short-reads Illumina technologies. These bacterial ressources and associated genomic data were characterized during the Agence Nationale de la Recherche (ANR) Metasimfood project (https://www.metasimfood.inrae.fr/) and are subsequently made publicly available for academic research purpose on fermented foods. These strains will be used in the frame of ANR metasimfood project, as core microbial ressources for the design of microbial consortia for pant-based fermented foods. The various files of the dataset summarize either genomic data (metasimfood_genomic_data.csv) such as accession numbers, size of replicons, sequencing coverage; or metadata associated with the strains (metasimfood_metadata_strains.csv) such as isolation sources, availibility, owner's contac. Specific genomic features detection such as prophages and plasmid (metasimfood_provirus_summary.csv; metasimfood_provirus-results.csv; metasimfood_plasmid_results.csv) are also available.
提供机构:
Recherche Data Gouv
创建时间:
2024-08-08
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