基于核糖体RNA高通量测序分析微生物群落结构
摘要
微生物群落多样性是微生物生态学和环境学研究的重点之一。分子生物学方法应用于微生物群落结构分析使得对环境样品中占大多数的不可培养微生物的研究成为了可能。由于功能上高度保守,序列上的不同位置具有不同的变异速率,核糖体RNA (rRNA)是目前在微生物分子生态学上最为有用以及应用最广泛的分子标记,通过rRNA序列比对,可以分析不同分类水平的系统发育关系。目前,较为常用的分析微生物群落结构的方法大多是建立在对于小亚基(SSU) rRNA上的全长或某个片段进行PCR扩增的基础上的。
然而,PCR过程中的偏差(bias)会引起结果并不能如实地再现原始的群落结构,随着多个宏基因组项目的研究,通过把现有的rRNA基因的“通用引物”与这些不依赖于PCR扩增得到的序列比对,发现所谓的“通用引物”并不能覆盖全部的微生物类型,即使可以添加简并碱基,也无法与通过宏基因组得到的rRNA序列完全匹配,这导致了在诸多研究中会忽略环境中的某些含量较少的微生物群落(rare biosphere)。因此,本研究采用了一种新的研究策略(sequencing of SSU rRNA without specific PCR amplification, SROP),对复杂环境样品提取总RNA,通过电泳使SSU rRNA和大亚基(LSU) rRNA分离,对含有SSU rRNA的部分割胶回收,对于富集的SSU rRNA使用随机引物合成cDNA并以cDNA为模板合成双链DNA,使用高通量焦磷酸测序对双链DNA直接测序,这一方法不使用特异性PCR扩增,避免了PCR过程中产生的诸多偏差,可以同时定量地分析细菌、古生菌、真核微生物的群落结构,从而真实、全面地反映环境样品中微生物群落结构的特征。由于通过SROP方法得到的序列是分布在rRNA上的不同位置并且较为集中地分布于16S rRNA的V3高变区,为了验证这一序列分布是否适合于微生物分类信息的确定以及群落结构的分析,从rRNA公共数据库(RDP和Silva)中抽取细菌、古生菌和真核生物的接近全长的SSU rRNA序列,模拟实验过程,形成了400bp的片段,通过与原始序列比较,确定了在任何一个分类水平,都能对99%以上的序列正确分类,并且不同分布的序列与这些序列中属于V3高变区的序列的所展现的群落结构是基本一致的,通过上述结论证明本研究中的得到的序列对于分类和表现群落结构是适合的。本研究通过SROP方法对两个复杂环境样品进行了分析,活性污泥样品中以细菌和真核微生物为主,厌氧颗粒污泥样品中以细菌和古生菌为主,这两个样品中的微生物包含了三个域,并且具有较高的多样性,具有一定的代表意义。其中,活性污泥样品中的细菌主要以Proteobacteria中的Rhodocyclaceae为主,真核生物主要以Metazoa和Alveolata两个门为主；厌氧颗粒污泥中细菌主要是Proteobacteria和Synergistetes两个门,其中Desulfovibrionaceae和Synergistaceae两个科所占比例最高,古生菌主要是Euryarchaeota中的Methanosaeta这个科,除此之外,还有大量的序列是不能确定分类信息甚至不能确定类型的,暗示了实际样品中更高的微生物多样性。通过将这些SROP方法得到的序列所展示的群落结构与经过PCR扩增的序列相比,发现了一定的差异,通过多样性指数分析,SROP方法得到的序列可以展现更高的多样性。将通过SROP方法得到的序列与PCR扩增时使用的引物进行比较,发现了这些“通用引物”中具有较多不匹配的情况,并且引物上没有一个位点是与所有的序列完全匹配的。本文提供了一种可以不依赖于PCR扩增的直接对复杂环境中具有活性的微生物进行定量的分析的方法,相信可以为更深入了解微生物世界提供更有利的工具。
使用微生物分子生物学手段同样可以对生产过程中的微生物进行监测。通过在不同的样品的PCR引物上添加不同的标记(barcode)可以在一个高通量反应中同时分析多个样品,使得对生产过程中的微生物的动态监测成为了可能。本研究选择了中国清香型白酒中的代表汾酒作为研究对象,对其中大曲的一种红心曲的制作过程以及在地缸中的发酵过程进行了监测,针对不同的微生物类型设计了不同的实验方案,对于真菌使用了添加barcode的焦磷酸测序的方法,对于细菌使用了克隆文库的方法,并分别对两者进行了定量PCR。这是焦磷酸高通量测序第一次用于食品真菌群落分析。酒曲样品中的细菌主要的门为Firmicutes (89.2%),主要的科为Lactobacillaceae (35.4%)和Bacillaceae (28.1%),前者在生产过程中占优势,而后者在成曲后6个月样品中占优势。发酵过程中的细菌基本都是Lactobacillaceae (90.8%)。对于真菌,酒曲中主要存在的科是Saccharomycetaceae (96.9%),而发酵过程中主要的真菌则是Saccharomycetaceae (60.1%)和Saccharomycopsidaceae (28.8%)。通过对细菌和真菌的定量PCR分析,整个制曲过程中细菌16S rRNA基因和真菌ITS区域的整体趋势都是下降的,发酵过程前期,细菌16S rRNA基因的拷贝数增加,而真菌ITS区域的拷贝数基本保持稳定。
Microbial community diversity is an essential issue in both microbial ecology and environmental microbiology. The features and characteristics of uncultured microorganisms, also known as the majority population in environments, could be accomplished because of the introduction of molecular methods. Ribosomal RNA (rRNA), is the most widely used and useful molecular marker for molecular ecological researches, which caused by its highly functional conservation and diverse mutation rates in different positions. Phylogenetic analysis at different taxonomic level could be done by the comparison of rRNA sequences. Nowadays, PCR amplification of whole length or partial small subunit (SSU) rRNA is the most common used method for the investigation of microbial community diversity.
However, the PCR bias caused by PCR amplification especially by primer mismatches usually makes quantitative analysis of microbial communities inaccessible and hampered the analysis of "rare" biosphere even with massive sequencing. When compared with the rRNA received from the metagenomic projects, the "universal primers" cannot cover the majority organisms that comprise the "rare" biosphere especially when using the degenerate "universal" primers. Here, a new method is presented in this study, which achieved by sequencing SSU rRNA without specific PCR amplification. The three domains (Bacteria, Archaea and Eukaryota) microorganisms in the complex environmental samples can be quantificationally analyzed simultaneously without specific PCR amplification, so the microbial community can be reconstructed more integrally. The rRNA sequences from reverse transcription reaction by random primer distributed in different region and concentrated in V3 hypervariable region in the 16S rRNA sequences. To test if this sequences set is suitable to analyze the community diversity and taxonomic annotations, nearly full length of sequences from the rRNA database (RDP and Silva) are extracted and simulated the reverse transcription reaction to form a 400 bp sequences set. That 400 bp sequences are annotated the taxonomy information and compared with the nearly full length sequences and more than 99%of sequences can be annotated correctly at all taxonomic levels.This result showed that the sequences obtained by this method are appropriate for the community diversity and taxonomic annotations analysis. Two complex environmental samples (activated sludge and anaerobic sludge) are analyzed in this study. Most of the microorganisms in the activated sludge sample are Bacteria and Eukaryota while that in the anaerobic sludge sample are Bacteria and Archaea. The microbial community diversities in both samples are very high. In the activated sludge sample, the dominant Bacteria are from the family Rhodocyclaceae, the phylum Proteobacteria and the dominant Eukaryota are the phyla Metazoa and Alveolata. In the anaerobic sludge sample, the dominant Bacteria are the families Desulfovibrionaceae and Synergistaceae in the phyla Proteobacteria and Synergistetes and the dominant Archaea are the family Methanosaeta in the phylum Euryarchaeota. In addition, the sequences which cannot be assigned to any microorganisms are abundant, which suggests that the higher microbial community diversity. When compared the sequences obtained from PCR amplification and our methods, difference are detected in the communities. The diversity index calculated from the the PCR independent rRNA sequences and the PCR amplification sequences show that the PCR independent rRNA sequences is a powerful technique to determine more broad range of microbial populations. The primer sets used in this study are compared with the PCR independent rRNA sequences and many types of mismathches are detected. Remarkable, no site in the primers can match all the PCR independent rRNA sequences. The method in this study will contribute significantly to our understanding of the diversity of complex microbial communities and expand our knowledge of the "rare" biosphere.
Microbial molecular methods have been widely used to monitor the microbial community diversity during the production process. The barcoded primers for pyrosequencing can be used to process many samples in a single pyrosequencing run making it possible to monitor the microbial community diversity in many samples. In this study, the starter production and the fermentation process of one of the most renowned "light-fragrance" liquors in China Fen liquor were analyzed using different strategies aiming at different microbial types. Bacterial diversity was analyzed using the 16S rRNA gene clone library and sequencing. Fungal diversity was analyzed using the ITS1 region via pyrosequencing. Quantitative real-time PCR (qPCR) helped us compare the quantity of bacteria and fungi during the starter production and fermentation process. To the best of our knowledge, this is the first report to reveal the fungal diversity within the food- fermentation process by using the pyrosequencing. In bacteria, the abundant families were Lactobacillaceae (35.4%) and Bacillaceae (28.1%) in the starter samples. However, during the fermentation process, Lactobacillaceae (90.8%) dominated nearly all the samples. As to fungi, Saccharomycetaceae (96.9%) dominated the starter samples while Saccharomycetaceae (60.1%) and Saccharomycopsidaceae (28.8%) coexisting in the fermentation process samples. The results of qPCR showed that the content of bacteria was increased while that of fungi was more stable in the fermentation process and both of bacteria and fungi decreased after the starters had produced.
然而,PCR过程中的偏差(bias)会引起结果并不能如实地再现原始的群落结构,随着多个宏基因组项目的研究,通过把现有的rRNA基因的“通用引物”与这些不依赖于PCR扩增得到的序列比对,发现所谓的“通用引物”并不能覆盖全部的微生物类型,即使可以添加简并碱基,也无法与通过宏基因组得到的rRNA序列完全匹配,这导致了在诸多研究中会忽略环境中的某些含量较少的微生物群落(rare biosphere)。因此,本研究采用了一种新的研究策略(sequencing of SSU rRNA without specific PCR amplification, SROP),对复杂环境样品提取总RNA,通过电泳使SSU rRNA和大亚基(LSU) rRNA分离,对含有SSU rRNA的部分割胶回收,对于富集的SSU rRNA使用随机引物合成cDNA并以cDNA为模板合成双链DNA,使用高通量焦磷酸测序对双链DNA直接测序,这一方法不使用特异性PCR扩增,避免了PCR过程中产生的诸多偏差,可以同时定量地分析细菌、古生菌、真核微生物的群落结构,从而真实、全面地反映环境样品中微生物群落结构的特征。由于通过SROP方法得到的序列是分布在rRNA上的不同位置并且较为集中地分布于16S rRNA的V3高变区,为了验证这一序列分布是否适合于微生物分类信息的确定以及群落结构的分析,从rRNA公共数据库(RDP和Silva)中抽取细菌、古生菌和真核生物的接近全长的SSU rRNA序列,模拟实验过程,形成了400bp的片段,通过与原始序列比较,确定了在任何一个分类水平,都能对99%以上的序列正确分类,并且不同分布的序列与这些序列中属于V3高变区的序列的所展现的群落结构是基本一致的,通过上述结论证明本研究中的得到的序列对于分类和表现群落结构是适合的。本研究通过SROP方法对两个复杂环境样品进行了分析,活性污泥样品中以细菌和真核微生物为主,厌氧颗粒污泥样品中以细菌和古生菌为主,这两个样品中的微生物包含了三个域,并且具有较高的多样性,具有一定的代表意义。其中,活性污泥样品中的细菌主要以Proteobacteria中的Rhodocyclaceae为主,真核生物主要以Metazoa和Alveolata两个门为主；厌氧颗粒污泥中细菌主要是Proteobacteria和Synergistetes两个门,其中Desulfovibrionaceae和Synergistaceae两个科所占比例最高,古生菌主要是Euryarchaeota中的Methanosaeta这个科,除此之外,还有大量的序列是不能确定分类信息甚至不能确定类型的,暗示了实际样品中更高的微生物多样性。通过将这些SROP方法得到的序列所展示的群落结构与经过PCR扩增的序列相比,发现了一定的差异,通过多样性指数分析,SROP方法得到的序列可以展现更高的多样性。将通过SROP方法得到的序列与PCR扩增时使用的引物进行比较,发现了这些“通用引物”中具有较多不匹配的情况,并且引物上没有一个位点是与所有的序列完全匹配的。本文提供了一种可以不依赖于PCR扩增的直接对复杂环境中具有活性的微生物进行定量的分析的方法,相信可以为更深入了解微生物世界提供更有利的工具。
使用微生物分子生物学手段同样可以对生产过程中的微生物进行监测。通过在不同的样品的PCR引物上添加不同的标记(barcode)可以在一个高通量反应中同时分析多个样品,使得对生产过程中的微生物的动态监测成为了可能。本研究选择了中国清香型白酒中的代表汾酒作为研究对象,对其中大曲的一种红心曲的制作过程以及在地缸中的发酵过程进行了监测,针对不同的微生物类型设计了不同的实验方案,对于真菌使用了添加barcode的焦磷酸测序的方法,对于细菌使用了克隆文库的方法,并分别对两者进行了定量PCR。这是焦磷酸高通量测序第一次用于食品真菌群落分析。酒曲样品中的细菌主要的门为Firmicutes (89.2%),主要的科为Lactobacillaceae (35.4%)和Bacillaceae (28.1%),前者在生产过程中占优势,而后者在成曲后6个月样品中占优势。发酵过程中的细菌基本都是Lactobacillaceae (90.8%)。对于真菌,酒曲中主要存在的科是Saccharomycetaceae (96.9%),而发酵过程中主要的真菌则是Saccharomycetaceae (60.1%)和Saccharomycopsidaceae (28.8%)。通过对细菌和真菌的定量PCR分析,整个制曲过程中细菌16S rRNA基因和真菌ITS区域的整体趋势都是下降的,发酵过程前期,细菌16S rRNA基因的拷贝数增加,而真菌ITS区域的拷贝数基本保持稳定。
Microbial community diversity is an essential issue in both microbial ecology and environmental microbiology. The features and characteristics of uncultured microorganisms, also known as the majority population in environments, could be accomplished because of the introduction of molecular methods. Ribosomal RNA (rRNA), is the most widely used and useful molecular marker for molecular ecological researches, which caused by its highly functional conservation and diverse mutation rates in different positions. Phylogenetic analysis at different taxonomic level could be done by the comparison of rRNA sequences. Nowadays, PCR amplification of whole length or partial small subunit (SSU) rRNA is the most common used method for the investigation of microbial community diversity.
However, the PCR bias caused by PCR amplification especially by primer mismatches usually makes quantitative analysis of microbial communities inaccessible and hampered the analysis of "rare" biosphere even with massive sequencing. When compared with the rRNA received from the metagenomic projects, the "universal primers" cannot cover the majority organisms that comprise the "rare" biosphere especially when using the degenerate "universal" primers. Here, a new method is presented in this study, which achieved by sequencing SSU rRNA without specific PCR amplification. The three domains (Bacteria, Archaea and Eukaryota) microorganisms in the complex environmental samples can be quantificationally analyzed simultaneously without specific PCR amplification, so the microbial community can be reconstructed more integrally. The rRNA sequences from reverse transcription reaction by random primer distributed in different region and concentrated in V3 hypervariable region in the 16S rRNA sequences. To test if this sequences set is suitable to analyze the community diversity and taxonomic annotations, nearly full length of sequences from the rRNA database (RDP and Silva) are extracted and simulated the reverse transcription reaction to form a 400 bp sequences set. That 400 bp sequences are annotated the taxonomy information and compared with the nearly full length sequences and more than 99%of sequences can be annotated correctly at all taxonomic levels.This result showed that the sequences obtained by this method are appropriate for the community diversity and taxonomic annotations analysis. Two complex environmental samples (activated sludge and anaerobic sludge) are analyzed in this study. Most of the microorganisms in the activated sludge sample are Bacteria and Eukaryota while that in the anaerobic sludge sample are Bacteria and Archaea. The microbial community diversities in both samples are very high. In the activated sludge sample, the dominant Bacteria are from the family Rhodocyclaceae, the phylum Proteobacteria and the dominant Eukaryota are the phyla Metazoa and Alveolata. In the anaerobic sludge sample, the dominant Bacteria are the families Desulfovibrionaceae and Synergistaceae in the phyla Proteobacteria and Synergistetes and the dominant Archaea are the family Methanosaeta in the phylum Euryarchaeota. In addition, the sequences which cannot be assigned to any microorganisms are abundant, which suggests that the higher microbial community diversity. When compared the sequences obtained from PCR amplification and our methods, difference are detected in the communities. The diversity index calculated from the the PCR independent rRNA sequences and the PCR amplification sequences show that the PCR independent rRNA sequences is a powerful technique to determine more broad range of microbial populations. The primer sets used in this study are compared with the PCR independent rRNA sequences and many types of mismathches are detected. Remarkable, no site in the primers can match all the PCR independent rRNA sequences. The method in this study will contribute significantly to our understanding of the diversity of complex microbial communities and expand our knowledge of the "rare" biosphere.
Microbial molecular methods have been widely used to monitor the microbial community diversity during the production process. The barcoded primers for pyrosequencing can be used to process many samples in a single pyrosequencing run making it possible to monitor the microbial community diversity in many samples. In this study, the starter production and the fermentation process of one of the most renowned "light-fragrance" liquors in China Fen liquor were analyzed using different strategies aiming at different microbial types. Bacterial diversity was analyzed using the 16S rRNA gene clone library and sequencing. Fungal diversity was analyzed using the ITS1 region via pyrosequencing. Quantitative real-time PCR (qPCR) helped us compare the quantity of bacteria and fungi during the starter production and fermentation process. To the best of our knowledge, this is the first report to reveal the fungal diversity within the food- fermentation process by using the pyrosequencing. In bacteria, the abundant families were Lactobacillaceae (35.4%) and Bacillaceae (28.1%) in the starter samples. However, during the fermentation process, Lactobacillaceae (90.8%) dominated nearly all the samples. As to fungi, Saccharomycetaceae (96.9%) dominated the starter samples while Saccharomycetaceae (60.1%) and Saccharomycopsidaceae (28.8%) coexisting in the fermentation process samples. The results of qPCR showed that the content of bacteria was increased while that of fungi was more stable in the fermentation process and both of bacteria and fungi decreased after the starters had produced.
引文
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