Title: Combining metagenomics, metatranscriptomics and viromics to explore novel microbial interactions: towards a systems-level understanding of human microbiome
Author: Shirley Bikel, etc.
Available online 9 June 2015
Abstract
The advances in experimental methods and the development of high performance bioinformatic tools have substantially improved our understanding of microbial communities associated with human niches. Many studies have documented that changes in microbial abundance and composition of the human microbiome is associated with human health and diseased state. The majority of research on human microbiome is typically focused in the analysis of one level of biological information, i.e., metagenomics or metatranscriptomics. In this review, we describe some of the different experimental and bioinformatic strategies applied to analyze the 16S rRNA gene profiling and shotgun sequencing data of the human microbiome. We also discuss how some of the recent insights in the combination of metagenomics, metatranscriptomics and viromics can provide more detailed description on the interactions between microorganisms and viruses in oral and gut microbiomes. Recent studies on viromics have begun to gain importance due to the potential involvement of viruses in microbial dysbiosis. In addition, metatranscriptomic combined with metagenomic analysis have shown that a substantial fraction of microbial transcripts can be differentially regulated relative to their microbial genomic abundances. Thus, understanding the molecular interactions in the microbiome using the combination of metagenomics, metatranscriptomics and viromics is one of the main challenges towards a system level understanding of human microbiome.
1. Introduction
2.Sequencing and bioinformatics strategies to study the human microbiome
2.1. 16S rRNA gene profile analysis
2.2. Metagenomic analysis
2.3. Metatranscriptomic analysis
2.4. Viromic analysis
3.Characteristics of oral and gut microbiomes
3.1.Metagenomic and 16S rRNA profiling combined with viromic analyses
3.2. Metagenomic combined with metatranscriptomic analyses
4.Perspectives and future trends of the human microbiome analyses
正文摘錄
abstract
宏基因組學，宏轉錄組學，病毒組學 這三者，宏轉錄組學應該是屬於宏基因組學吧？然後宏基因組學是研究病毒組學的一種方法？宏基因組學還可以研究微生物組學。
We also discuss how some of the recent insights in the combination of metagenomics, metatranscriptomics and viromics can provide more detailed description on the interactions between microorganisms and viruses in oral and gut microbiomes.
還是說，宏基因組學是指那些提取DNA的方法，而轉錄組學是提取RNA的方法，所以還是不一樣的？
In addition, metatranscriptomic combined with metagenomic analysis have shown that a substantial fraction of microbial transcripts can be differentially regulated relative to their microbial genomic abundances.
Thus, understanding the molecular interactions in the microbiome using the combination of metagenomics, metatranscriptomics and viromics is one of the main challenges towards a system level understanding of human microbiome.
更多的是關於微生物組學，但是也有病毒組學的內容
對於宏基因組學、宏轉錄組學、病毒組學的定義，病毒組學是研究病毒之間相互作用的
The study of interactions between the DNAs, RNAs, and viruses that are present in the microbiome, are the main interest of metagenomics, metatranscriptomics, and viromics, respectively.
宏基因組學有16S rRNA方法，鳥槍法；宏轉錄組學就是所有RNA；另外virome是指總病毒顆粒進行測序來分析微生物組
For studying the microbial community of the human microbiome using high throughput sequencing technologies, there are several types of large scale analyses: the 16S profiling analysis which is based in sequencing the hypervariable regions of the 16S rRNA gene and the shotgun analysis which is based in direct sequencing of the total DNA (metagenome) and/or total RNA (metatranscriptome). In addition, the viral component of the microbiome (virome) can be also analyzed by sequencing the total viral particles.
宏基因組學和宏轉錄組學主要的功能
The metagenomic analysis also identifies the abundance and diversity of microbial community, but additionally can identify the gene content and inferred functional potential of proteins encoded in the genomes of the microbial community. The metatranscriptomic analysis allows the identification of expressed transcripts in the microbiome. The transcript numbers can also be used to compare the gene expression profiles between microbial communities.
2.3. Metatranscriptomic analysis
宏基因組學的缺陷，宏轉錄組學可以彌補
Metagenomics is a powerful tool used to describe the gene content and potential functions encoded in sequenced genomes.
However, metagenomics approaches have a very limited role in revealing the microbial activity measured by gene expression. The metatranscriptomic shotgun sequencing (RNAseq) provides the access to the metatranscriptome of the microbiome allowing the whole-genome analysis profiling of the active microbial community under different conditions. In this regard, sequencing of metatranscriptomes has been recently employed to identify RNA-based regulation and expressed biological signatures in human microbiome [78].
影響跨轉錄組學大規模應用的幾個技術問題：
There are several technical issues affecting the large-scale application of metatranscriptomics:(1) the collection and storage procedures to preserve the RNA of the sample, (2) the limitation to obtain high-quality and sufficient quantity of RNA from human microbiome samples, (3) the mRNA enrichment procedures by removing ribosomal RNA (rRNAs) which represent over 90% of the RNA, (4) the average useful life of mRNA leads to difficulty in the detection of rapid and short-term responses to environmental changes, (5) the transcriptome databases are insufficient, (6) the host RNA contamination which cannot be removed by currently available rRNA purification methods and (7) the poly-A RNA selection kits to capture the mRNA population are not feasible in prokaryotes.
宏轉錄組學的兩種策略
The typical bioinformatics pipeline to analyze the data obtained from a metatranscriptomic experiment is similar to the one used in metagenomics and it is also divided in two strategies: (1) mapping sequence reads to reference genomes and genes and (2) de novo assembly of new transcriptomes (Fig. 1).
2.4. Viromic analysis
病毒比微生物細胞多10：1。然而，病毒DNA僅佔微生物羣落總DNA的0.1％
Viruses outnumber microbial cells 10:1 in most environments; however, viral DNA only represents 0.1% of the total DNA in a microbial community [6]. Hence, to obtain a deep sequence coverage of the human viruses that are present in the microbiome, the isolation of viral particles (VPs) becomes necessary [95], [96], [97], [98].
組合分析的作用
Fig. 4. Towards a systems level understanding of human microbiome. 挺有意思的一個圖
The use of only one analysis to study the human microbiome (viromics, metagenomics or metatranscriptomics) provides a partial view of the complete ecological system. In a combined approach, the metagenomic analysis can give us a view of the microorganism's abundance and functions available in the microbiome, while the metatranscriptomic analyses combined with metagenomics can show us which of these microorganisms and functions are actually active. Finally, the integration of viromics analysis with the other omics data can provide information about the role that viruses play within the microbiome. The combined analyses can offer a better understanding of the role that external factors like diet, immune system and probiotics are playing in shaping the human microbiome abundance and composition. Thus, an integrated systems analysis (orange circle) seems necessary to have a better understanding of molecular mechanisms and their interactions in human microbiome.
組合分析方法，基因，疾病表型
Furthermore, these combined omics analyses provide useful insights about the microorganisms that have relevant functions and at the same time it allows knowing the active genes and pathways that can be related to a diseased phenotype (Fig. 4).
4. Perspectives and future trends of the human microbiome analyses
The study of human microbiome through the combination of metagenomic, metatranscriptomic and viromic analyses allows a deep understanding of molecular interactions within microorganisms and their role in human health and disease (Fig. 4).
Of these combined analyses the identification of potential genes, pathways and viruses that can be associated with health and disease is also possible. These driver genes and pathways could be explored as a potential pharmacological target to treat diseases that are associated with a microbiome dysbiosis.
病毒基因組中缺乏保守區域（如細菌的16S rRNA基因），使得在大型人羣中研究病毒更加困難
However, the lack of a conserved region in virus genomes (like the 16S rRNA gene of bacteria), make the study of viruses more difficult to analyze in large cohorts.