Host and microbiome multi-omics integration: applications and methodologies

被引:66
作者
Wang Q. [1 ,2 ,3 ]
Wang K. [1 ,2 ]
Wu W. [1 ,2 ]
Giannoulatou E. [3 ,4 ]
Ho J.W.K. [3 ,4 ,5 ]
Li L. [1 ,2 ]
机构
[1] State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, No.79 Qingchun Road, Hangzhou, 310003, Zhejiang
[2] Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou
[3] Victor Chang Cardiac Research Institute, Darlinghurst, 2010, NSW
[4] St Vincent’s Clinical School, University of New South Wales, Sydney, 2010, NSW
[5] School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam
基金
中国国家自然科学基金; 英国医学研究理事会;
关键词
Big data; Epigenome; Genome; Metabolome; Microbiome; Network analysis; Transcriptome;
D O I
10.1007/s12551-018-0491-7
中图分类号
学科分类号
摘要
The study of the microbial community—the microbiome—associated with a human host is a maturing research field. It is increasingly clear that the composition of the human’s microbiome is associated with various diseases such as gastrointestinal diseases, liver diseases and metabolic diseases. Using high-throughput technologies such as next-generation sequencing and mass spectrometry–based metabolomics, we are able to comprehensively sequence the microbiome—the metagenome—and associate these data with the genomic, epigenomics, transcriptomic and metabolic profile of the host. Our review summarises the application of integrating host omics with microbiome as well as the analytical methods and related tools applied in these studies. In addition, potential future directions are discussed. © 2019, International Union for Pure and Applied Biophysics (IUPAB) and Springer-Verlag GmbH Germany, part of Springer Nature.
引用
收藏
页码:55 / 65
页数:10
相关论文
共 94 条
[31]  
Igartua C., Davenport E.R., Gilad Y., Et al., Host genetic variation in mucosal immunity pathways influences the upper airway microbiome, Microbiome, 5, (2017)
[32]  
The integrative human microbiome project: dynamic analysis of microbiome-host omics profiles during periods of human health and disease, Cell Host Microbe, 16, pp. 276-289, (2014)
[33]  
Imhann F., Vila A.V., Bonder M.J., Et al., Interplay of host genetics and gut microbiota underlying the onset and clinical presentation of inflammatory bowel disease, Gut, 67, pp. 108-119, (2018)
[34]  
Jolliffe I.T., Cadima J., Principal component analysis: a review and recent developments, Phil Trans R Soc A, 374, (2016)
[35]  
Kellermayer R., Challenges for epigenetic research in inflammatory bowel diseases, Epigenomics, 9, pp. 527-538, (2017)
[36]  
Knights D., Silverberg M.S., Weersma R.K., Et al., Complex host genetics influence the microbiome in inflammatory bowel disease, Genome Med, 6, (2014)
[37]  
Kostic A.D., Gevers D., Siljander H., Et al., The dynamics of the human infant gut microbiome in development and in progression toward type 1 diabetes, Cell Host Microbe, 17, pp. 260-273, (2015)
[38]  
Kreznar J.H., Keller M.P., Traeger L.L., Et al., Host genotype and gut microbiome modulate insulin secretion and diet-induced metabolic phenotypes, Cell Rep, 18, pp. 1739-1750, (2017)
[39]  
Kroemer G., Zitvogel L., Cancer immunotherapy in 2017: the breakthrough of the microbiota, Nat Rev Immunol, 18, pp. 87-88, (2018)
[40]  
Kumar H., Lund R., Laiho A., Et al., Gut microbiota as an epigenetic regulator: pilot study based on whole-genome methylation analysis, mBio, 5, pp. e02113-e02114, (2014)