FoodMicroDB: A microbiome database for composition and time‐series research in food
Abstract Microorganisms are crucial for food fermentation, preservation, and safety, directly impacting human health. The number of studies on the food microbiome has surged recently, along with a substantial increase in data. However, there is a notable lack of databases specialized for this field....
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| Format: | Article |
| Language: | English |
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Wiley
2024-12-01
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| Series: | iMetaOmics |
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| Online Access: | https://doi.org/10.1002/imo2.40 |
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| author | Yahui Li Hujie Lyu Haifei Yang Zhicheng Ju Chuang Ma Huiyu Hou Yao Wang Yuanping Zhou Yunyun Gao Junbo Yang Shanshan Xu Defeng Bai Hao Luo Salsabeel Yousuf Tianyuan Zhang Jiani Xun Meiyin Zeng Heyuan Qi Tong Chen Yong‐Xin Liu |
| author_facet | Yahui Li Hujie Lyu Haifei Yang Zhicheng Ju Chuang Ma Huiyu Hou Yao Wang Yuanping Zhou Yunyun Gao Junbo Yang Shanshan Xu Defeng Bai Hao Luo Salsabeel Yousuf Tianyuan Zhang Jiani Xun Meiyin Zeng Heyuan Qi Tong Chen Yong‐Xin Liu |
| author_sort | Yahui Li |
| collection | DOAJ |
| description | Abstract Microorganisms are crucial for food fermentation, preservation, and safety, directly impacting human health. The number of studies on the food microbiome has surged recently, along with a substantial increase in data. However, there is a notable lack of databases specialized for this field. To address this gap, we developed Food Microbiome Database (FoodMicroDB), a platform aimed at enhancing the reusability and accessibility of food microbiome data through comprehensive data management and data visualization tools. FoodMicroDB aggregates 6358 amplicon data from 108 meta‐taxonomic projects covering 62 foods, and harbors 4710 taxa of bacteria, archaea, and fungi. The collected data were consistently analyzed and curated, then visualized using versatile utilities, including unique tools for visualizing microbial composition and time‐series microbiome data. It also includes advanced modules for microbial abundance analysis, cross‐host abundance comparison, and cross‐food analysis. FoodMicroDB will be a valuable resource platform for the food microbiome research field. The database is freely accessible at: https://www.bic.ac.cn/FoodMicro/. |
| format | Article |
| id | doaj-art-cce034ef297d420b84e45dbd8e39b8d5 |
| institution | Kabale University |
| issn | 2996-9506 2996-9514 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | iMetaOmics |
| spelling | doaj-art-cce034ef297d420b84e45dbd8e39b8d52025-01-31T16:15:24ZengWileyiMetaOmics2996-95062996-95142024-12-0112n/an/a10.1002/imo2.40FoodMicroDB: A microbiome database for composition and time‐series research in foodYahui Li0Hujie Lyu1Haifei Yang2Zhicheng Ju3Chuang Ma4Huiyu Hou5Yao Wang6Yuanping Zhou7Yunyun Gao8Junbo Yang9Shanshan Xu10Defeng Bai11Hao Luo12Salsabeel Yousuf13Tianyuan Zhang14Jiani Xun15Meiyin Zeng16Heyuan Qi17Tong Chen18Yong‐Xin Liu19Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaDepartment of Life Sciences Imperial College of London London UKAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaDepartment of Ocean Science The Hong Kong University of Science and Technology Hong Kong SAR ChinaAnhui Agricultural University Hefei ChinaAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaSchool of Food and Biological Engineering Hefei University of Technology Hefei ChinaAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaInstitute of Microbiology Chinese Academy of Sciences Beijing ChinaState Key Laboratory for Quality Ensurance and Sustainable Use of Dao‐di Herbs, National Resource Center for Chinese Materia Medica China Academy of Chinese Medical Science Beijing ChinaAgricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen ChinaAbstract Microorganisms are crucial for food fermentation, preservation, and safety, directly impacting human health. The number of studies on the food microbiome has surged recently, along with a substantial increase in data. However, there is a notable lack of databases specialized for this field. To address this gap, we developed Food Microbiome Database (FoodMicroDB), a platform aimed at enhancing the reusability and accessibility of food microbiome data through comprehensive data management and data visualization tools. FoodMicroDB aggregates 6358 amplicon data from 108 meta‐taxonomic projects covering 62 foods, and harbors 4710 taxa of bacteria, archaea, and fungi. The collected data were consistently analyzed and curated, then visualized using versatile utilities, including unique tools for visualizing microbial composition and time‐series microbiome data. It also includes advanced modules for microbial abundance analysis, cross‐host abundance comparison, and cross‐food analysis. FoodMicroDB will be a valuable resource platform for the food microbiome research field. The database is freely accessible at: https://www.bic.ac.cn/FoodMicro/.https://doi.org/10.1002/imo2.40databasefood microbiomefermented foodmicrobial compositionmicrobiome analysistime‐series |
| spellingShingle | Yahui Li Hujie Lyu Haifei Yang Zhicheng Ju Chuang Ma Huiyu Hou Yao Wang Yuanping Zhou Yunyun Gao Junbo Yang Shanshan Xu Defeng Bai Hao Luo Salsabeel Yousuf Tianyuan Zhang Jiani Xun Meiyin Zeng Heyuan Qi Tong Chen Yong‐Xin Liu FoodMicroDB: A microbiome database for composition and time‐series research in food iMetaOmics database food microbiome fermented food microbial composition microbiome analysis time‐series |
| title | FoodMicroDB: A microbiome database for composition and time‐series research in food |
| title_full | FoodMicroDB: A microbiome database for composition and time‐series research in food |
| title_fullStr | FoodMicroDB: A microbiome database for composition and time‐series research in food |
| title_full_unstemmed | FoodMicroDB: A microbiome database for composition and time‐series research in food |
| title_short | FoodMicroDB: A microbiome database for composition and time‐series research in food |
| title_sort | foodmicrodb a microbiome database for composition and time series research in food |
| topic | database food microbiome fermented food microbial composition microbiome analysis time‐series |
| url | https://doi.org/10.1002/imo2.40 |
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