Exploring Host-Microbe Interactions in Lung Cancer.
Exploring Host-Microbe Interactions in Lung Cancer.
复制标题
探索肺癌中宿主-微生物的相互作用。
DOI：
10.1164/rccm.201807-1225ed
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发表时间：
2018
影响因子：
24.7
通讯作者：
Johnson,WEvan
中科院分区：
文献类型：
--
作者：
Zhao,Yue;Johnson,WEvan
随着我们对生物系统的“高通量”理解的增长，宿主基因组的作用及其与微生物组的相互作用正在成为人类疾病研究中快速发展的焦点。宿主基因组通常通过调节微生物组来影响健康(1)，而微生物组通过调整其组成和改变其自身以及宿主的代谢来影响健康。因此，人们正在努力确定和描述宿主-微生物相互作用的潜在因果关系(2)。整合多组学是一个新兴的领域，在阐明驱动人类健康和疾病的宿主-微生物相互作用方面具有重要的潜力。综合人类微生物组计划和人类微生物组计划的第二阶段都是多组学分析工作(3)，将微生物组分析与其他组学数据结合起来，包括宿主和微生物的转录组、蛋白质组和代谢物。综合人类微生物组计划在其纵向研究设计中特别关注妊娠、肠道疾病和2型糖尿病(3)，尽管许多其他疾病，包括许多癌症，也将受益于类似的多组学分析工作。结合宿主转录组学和宏基因组学测序数据已经有报道（4-6）。在这一期的Journal中，Tsay和他的同事（第1188-1198页）结合了RNA-Seq和16S rRNA测序来分析宿主转录组和微生物组。我们之前的工作使用双RNA-Seq同时识别哮喘儿童鼻道中低多样性、病原体主导的微生物谱(6)，并将宿主免疫应答信号的强度与微生物丰度谱联系起来——即，已知病原体的高流行率对应于更强的炎症信号强度。未来，基于总rna - seq的微生物组分析方法(7)可能是一种趋势，所有的reads将同时与人类参考基因组和微生物参考基因组进行比对，从而可以保留更多的微生物reads，以减少实际与测序的微生物组之间的偏差。
With our growing “high-throughput” understanding of biological systems, the roles of the host genome and their interplay with microbiome are becoming a rapidly evolving focus in human disease research. The host genome often influences health by modulating the microbiome (1), while the microbiome impacts health by adjusting its composition and altering its own as well as the host’s metabolism. Therefore, much effort is being made to identify and characterize a potential causal relationship from the host–microbe interaction (2).Integrative multi-omics is a new and burgeoning field with significant potential for elucidating the host–microbial interplay that drives human health and disease. Both the Integrative Human Microbiome Project and the second phase of the Human Microbiome Project are multi-omic profiling efforts (3) that are combining microbiome profiling with other-omics data, including transcriptome, proteome, and metabolites for both the host and microbes. The Integrative Human Microbiome Project in particular is focused on pregnancy, gut disease, and type 2 diabetes in their longitudinal study design (3), although many other diseases, including many cancers, would benefit from similar multi-omic profiling efforts. Combining host transcriptomics and metagenomics sequencing data has been reported previously (4–6). In this issue of the Journal, Tsay and colleagues (pp. 1188–1198) combined RNA-Seq and 16S rRNA sequencing to profile the host transcriptome and microbiome. Our previous work used dual RNA-Seq to simultaneously identify low-diversity, pathogen-dominated microbial profiles in the nasal passages of children with asthma (6), and link the strength of host immune response signatures to microbial abundance profiles—that is, higher prevalence of known pathogens corresponded to stronger inflammatory signature strength. In future, total RNA-Seq–based microbiome profiling methods (7) might be a trend while all the reads will be aligned to the human reference genome and microbial reference genome in parallel, so that more microbial reads could be reserved to decrease the bias between the actual and sequenced microbiome.
影响因子：
11.1
作者：
Goodrich JK;Davenport ER;Clark AG;Ley RE
通讯作者：
Ley RE
影响因子：
12.3
作者：
Segata N;Izard J;Waldron L;Gevers D;Miropolsky L;Garrett WS;Huttenhower C
通讯作者：
Huttenhower C