FACdb: a comprehensive resource for genes, gut microbiota, and metabolites in farm animals

被引:0
作者
Zhang, Ze [1 ,2 ]
Li, Yang [1 ]
Zhang, Di [1 ]
Chen, Shuai [1 ]
Lu, Sien [1 ]
Wang, Kang [1 ]
Zhou, Miao [3 ]
Song, Zehe [3 ]
Li, Qingcui [4 ]
Yin, Jie [3 ]
Liu, Xiaoping [1 ]
机构
[1] Univ Chinese Acad Sci, Hangzhou Inst Adv Study, Sch Life Sci, Key Lab Syst Hlth Sci Zhejiang Prov, Hangzhou, Peoples R China
[2] BGI Res, Hangzhou, Peoples R China
[3] Hunan Agr Univ, Coll Anim Sci & Technol, Changsha, Peoples R China
[4] Univ Chinese Acad Sci, Sch Pharmaceut Sci & Technol, Hangzhou Inst Adv Study, Hangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
farm animal; connectome database; gene expression; gut microbiota; metabolites; association networks; DATABASE; PANCREATITIS; INSIGHTS;
D O I
10.3389/fmicb.2025.1557285
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Farm animals, including livestock and poultry, play essential economic, social, and cultural roles and are indispensable in human welfare. Farm Animal Connectome database (FACdb) is a comprehensive resource that includes the association networks among gene expression, gut microbiota, and metabolites in farm animals. Although some databases present the relationship between gut microbes, metabolites, and gene expression, these databases are limited to human and mouse species, with limited data for farm animals. In this database, we calculate the associations and summarize the connections among gene expression, gut microbiota, and metabolites in farm animals using six correlation or distance calculation (including Pearson, Spearman, Cosine, Euclidean, Bray-Curtis, and Mahalanobis). FACdb contains over 55 million potential interactions of 73,571 genes, 11,046 gut microbiota, and 4,540 metabolites. It provides an easy-to-use interface for browsing and searching the association information. Additionally, FACdb offers interactive visualization tools to effectively investigate the relationship among the genes, gut microbiota, and metabolites in farm animals. Overall, FACdb is a valuable resource for understanding interactions among gut microbiota, metabolites, and gene expression. It contributes to the further utilization of microbes in animal products and welfare promotion. Compared to mice, pigs or other farm animals share more similarities with humans in molecular, cellular, and organ-level responses, indicating that our database may offer new insights into the relationship among gut microbiota, metabolites, and gene expression in humans.
引用
收藏
页数:14
相关论文
共 66 条
[1]  
Aggarwal CC, 2001, LECT NOTES COMPUT SC, V1973, P420
[2]   Treatment of Recurrent Clostridioides difficile Infection Using Fecal Microbiota Transplantation in Iranian Patients with Underlying Inflammatory Bowel Disease [J].
Azimirad, Masoumeh ;
Yadegar, Abbas ;
Gholami, Fatemeh ;
Shahrokh, Shabnam ;
Aghdaei, Hamid Asadzadeh ;
Ianiro, Gianluca ;
Suzuki, Hidekazu ;
Cammarota, Giovanni ;
Zali, Mohammad Reza .
JOURNAL OF INFLAMMATION RESEARCH, 2020, 13 :563-570
[3]   Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research [J].
Baker, Jonathon L. .
FEMS MICROBIOLOGY REVIEWS, 2023, 47 (05)
[4]   Distinct signals from the microbiota promote different aspects of zebrafish gut differentiation [J].
Bates, Jennifer M. ;
Mittge, Erika ;
Kuhlman, Julie ;
Baden, Katrina N. ;
Cheesman, Sarah E. ;
Guillemin, Karen .
DEVELOPMENTAL BIOLOGY, 2006, 297 (02) :374-386
[5]   Gut microbiome composition differences among breeds impact feed efficiency in swine [J].
Bergamaschi, Matteo ;
Tiezzi, Francesco ;
Howard, Jeremy ;
Huang, Yi Jian ;
Gray, Kent A. ;
Schillebeeckx, Constantino ;
McNulty, Nathan P. ;
Maltecca, Christian .
MICROBIOME, 2020, 8 (01)
[6]   Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2′s q2-feature-classifier plugin [J].
Bokulich, Nicholas A. ;
Kaehler, Benjamin D. ;
Rideout, Jai Ram ;
Dillon, Matthew ;
Bolyen, Evan ;
Knight, Rob ;
Huttley, Gavin A. ;
Caporaso, J. Gregory .
MICROBIOME, 2018, 6
[7]   Trimmomatic: a flexible trimmer for Illumina sequence data [J].
Bolger, Anthony M. ;
Lohse, Marc ;
Usadel, Bjoern .
BIOINFORMATICS, 2014, 30 (15) :2114-2120
[8]   Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2 [J].
Bolyen, Evan ;
Rideout, Jai Ram ;
Dillon, Matthew R. ;
Bokulich, NicholasA. ;
Abnet, Christian C. ;
Al-Ghalith, Gabriel A. ;
Alexander, Harriet ;
Alm, Eric J. ;
Arumugam, Manimozhiyan ;
Asnicar, Francesco ;
Bai, Yang ;
Bisanz, Jordan E. ;
Bittinger, Kyle ;
Brejnrod, Asker ;
Brislawn, Colin J. ;
Brown, C. Titus ;
Callahan, Benjamin J. ;
Caraballo-Rodriguez, Andres Mauricio ;
Chase, John ;
Cope, Emily K. ;
Da Silva, Ricardo ;
Diener, Christian ;
Dorrestein, Pieter C. ;
Douglas, Gavin M. ;
Durall, Daniel M. ;
Duvallet, Claire ;
Edwardson, Christian F. ;
Ernst, Madeleine ;
Estaki, Mehrbod ;
Fouquier, Jennifer ;
Gauglitz, Julia M. ;
Gibbons, Sean M. ;
Gibson, Deanna L. ;
Gonzalez, Antonio ;
Gorlick, Kestrel ;
Guo, Jiarong ;
Hillmann, Benjamin ;
Holmes, Susan ;
Holste, Hannes ;
Huttenhower, Curtis ;
Huttley, Gavin A. ;
Janssen, Stefan ;
Jarmusch, Alan K. ;
Jiang, Lingjing ;
Kaehler, Benjamin D. ;
Bin Kang, Kyo ;
Keefe, Christopher R. ;
Keim, Paul ;
Kelley, Scott T. ;
Knights, Dan .
NATURE BIOTECHNOLOGY, 2019, 37 (08) :852-857
[9]   AN ORDINATION OF THE UPLAND FOREST COMMUNITIES OF SOUTHERN WISCONSIN [J].
BRAY, JR ;
CURTIS, JT .
ECOLOGICAL MONOGRAPHS, 1957, 27 (04) :326-349
[10]  
Callahan BJ, 2016, NAT METHODS, V13, P581, DOI [10.1038/nmeth.3869, 10.1038/NMETH.3869]