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A Modified Low-quantity RNA-Seq Method for Microbial Community and Diversity Analysis Using Small Subunit Ribosomal RNA
改良的低量 RNA-Seq法通过检测小亚基核糖体RNA以分析微生物群落和多样性   

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本实验方案简略版
PLOS ONE
Oct 2017

Abstract

We propose a modified RNA-Seq method for small subunit ribosomal RNA (SSU rRNA)-based microbial community analysis that depends on the direct ligation of a 5’ adaptor to RNA before reverse-transcription. The method requires only a low-input quantity of RNA (10-100 ng) and does not require a DNA removal step. Using this method, we could obtain more 16S rRNA sequences of the same regions (variable regions V1-V2) without the interference of DNA in order to analyze OTU (operational taxonomic unit)-based microbial communities and diversity. The generated SSU rRNA sequences are also suitable for the coverage evaluation for bacterial universal primer 8F (Escherichia coli position 8 to 27), which is commonly used for bacterial 16S rRNA gene amplification. The modified RNA-Seq method will be useful to determine potentially active microbial community structures and diversity for various environmental samples, and will also be useful for identifying novel microbial taxa.

Keywords: RNA-Seq (RNA-Seq), Low quantity (低量), SSU rRNA (SSU rRNA), OTU (OTU), Microbial community (微生物群落)

Background

Ribosomal RNA (rRNA) accounts for more than 90% of the total microbial RNA, and is suitable for the analysis of microbial communities as an indicator of microbial physiological activity to synthesize proteins (Blazewicz et al., 2013). The study of microbial community transcripts, including rRNA and mRNA, in a particular environment (Double RNA metatranscriptomics) has advantages in providing both functional and taxonomic information on microbes (Urich et al., 2008), but has failed to perform OTU-based community comparisons. Although diversity indices could be calculated and compared using the V3 region of 16S rRNA sequences when gel-extracted SSU rRNA is analyzed, only a third of the resulting 16S rRNA sequences were found to be suitable for such analyses (Li et al., 2014). Besides, such method usually requires high quantities of RNA (Li et al., 2014). We recently developed a modified RNA-Seq method that uses an immediate adaptor ligation step at the 5’ end of the RNA prior to reverse transcription. Consequently, we can obtain more 16S RNA reads which can be used for OTU-based community and diversity analysis especially regarding low-RNA-yield samples such as tap water, shower curtain and human skin (Yan et al., 2017), and also mudflat sediment samples (Yan et al., 2018).

Materials and Reagents

  1. RNA extraction
    1. Glass beads, acid-washed (≤ 106 μm) (Sigma-Aldrich, catalog number: G4649 )
    2. 2 ml bead beating tubes (QIAGEN, catalog number: 13118-400 )
    3. mirVANATM miRNA Isolation Kit (Thermo Fisher Scientific, InvitrogenTM, catalog number: AM1560 )

  2. RNA-Seq library preparation
    1. PCR tubes (Corning, Axygen®, catalog number: PCR-02-L-C )
    2. RNA-Seq Library Preparation Kit for Whole Transcriptome Discovery–Illumina Compatible (Gnomegen, catalog number: K02421-T )
    3. DNase/RNase free water (Thermo Fisher Scientific, InvitrogenTM, catalog number: AM9932 )
    4. QubitTM RNA HS Assay Kit (Thermo Fisher Scientific, InvitrogenTM, catalog number: Q32855 )
    5. RNaseOUTTM Recombinant Ribonuclease Inhibitor (Thermo Fisher Scientific, InvitrogenTM, catalog number: 10777019 )
    6. QubitTM dsDNA HS Assay Kit (Thermo Fisher Scientific, InvitrogenTM, catalog number: Q32854 )
    7. Gnome Size Selector (Gnomegen, catalog number: R02424S )

  3. Other materials
    1. Pipette tips (10 μl, 200 μl, 1,000 μl) (Corning, Axygen®, catalog numbers: TF-300-R-S , TF-200-R-S , TF-1000-R-S )
    2. 1.5 ml Eppendorf tubes (Eppendorf, catalog number: 022363204 )
    3. 100% ethanol
    4. RNase-free 70% ethanol
    5. Agarose (Biowest, catalog number: 111860 )
    6. 50x TAE Buffer (Sangon Biotech, catalog number: B548101-0500 )
    7. DL2,000 DNA Marker (Takara Bio, catalog number: 3427A )

Equipment

  1. Pipettes (0-10 μl, 10-100 μl, 100-1,000 μl) (Eppendorf, catalog numbers: k03030 , k03031 , k03032 )
  2. Vortex-genieTM 2 (QIAGEN, model: Vortex-Genie® 2 )
  3. Fresco 17 centrifuge (Thermo Fisher Scientific, Thermo ScientificTM, model: HeraeusTM FrescoTM 17 )
  4. Qubit 2.0 Fluorometer (Thermo Fisher Scientific, model: Qubit 2.0 )
  5. Automated thermal cycler TP600 (Takara Bio, model: TP600 )
  6. MagneSphere® Technology Magnetic Separation Stand (twelve-position) (Promega, catalog number: Z5342 )
  7. Electrophoresis apparatus (Bio-Rad Laboratories)
  8. Gel imaging system

Software

  1. Sickle v1.33 (Joshi and Fass, 2011)
  2. Mothur v1.33.3 (Schloss et al., 2009)
  3. QIIME v1.8.0 (Caporaso et al., 2010)
  4. MIPE (Zou et al., 2017)

Procedure

Note: Details of sample collection, storage and transport for low-biomass samples (tap water, shower curtain, mudflat water, leaf surface and human skin) please see the method described by Yan et al. (2017). Regarding mudflat sediment samples, details of sample collection and nucleic acid extraction are described in our recent work (Yan et al., 2018).

  1. Nucleic acid extraction
    1. Extract total RNA or total nucleic acids from low-biomass samples, which are unsuitable for DNase I digestion, using a mirVANATM miRNA Isolation Kit. Five or more swabs are preferred to be pooled for nucleic acid extraction, while a whole piece of filter membrane is preferred to be cut into small pieces (~0.5 mm2) for extraction. To completely disrupt microbial cell walls, vortex such preprocessed samples with 0.7 g glass beads and 0.7 ml Lysis/Binding Buffer in a 2 ml bead beating tube at maximum speed prior to extraction. After centrifugation at 13,000 x g for 5 min at 4 °C, transfer the supernatant to a new 1.5 ml tube and extract total RNA strictly following the manufacturer’s instructions.
    2. Visualize the RNA samples in a 1% (w/v) agarose gel after electrophoresis to assess the RNA integrity (Figure 1). Store total RNA or total nucleic acids at -80 °C. Quantify total RNA using a QubitTM RNA HS Assay Kit on Qubit 2.0 fluorometer before the preparation of RNA-Seq libraries.


      Figure 1. Total RNA electrophoresis for low-biomass samples. M: DL2,000 DNA marker; TW: tap water; SC; shower curtain; MW: mudflat surface water; LS: leaf surface; FH: forehead of human skin. Only TW and MW display integral 23S and 16S rRNA bands when 10 μl RNA is loaded, in contrast to samples that yield a very low concentration of RNA (< 2 ng/μl).

  2. Preparation of RNA-Seq libraries
    This RNA-Seq library preparation protocol is modified from the Gnomegen RNA-Seq Library Preparation Kit protocol (catalog number: K02421-T). Prepare RNA-Seq libraries following the steps described below.
    1. Total RNA denaturation
      1. Add total RNA (10-100 ng) and DNase/RNase free water into a 0.2 ml PCR tube to make a 20-μl reaction volume.
      2. Mix well and incubate at 65 °C for 5 min using a thermal cycler program. Place the tube on ice immediately after the incubation and leave for at least 5 min.
        Note: We use this step to substitute the original fragmentation step as to keep the integrity of the RNA and directly ligate the RNA-Seq adaptor to the 5’ end of the rRNA in the following step.
    2. Adaptor ligation to 5’ end of RNA
      1. Add the following reagents sequentially to the denatured RNA, and make a reaction volume of 40.6 μl:
        10x ligation buffer
        3.6 μl (Final ~0.9x)
        10 mM ATP
        4 μl (Final ~1 mM)
        Ligation enzyme mix
        1 μl
        Ligation enzyme supplement
        1 μl
        RNaseOUT (40 U/μl)
        1 μl (Final ~1 U/μl)
        Ligation enhancer mix
        8 μl
        RNA Seq 5’ Adaptor B
        2 μl
      2. Mix well and incubate at 37 °C for 2 h using a thermal cycler program. Place the tube on ice after incubation.
        Note: RNaseOUT is a separately-purchased reagent. Such specific ligation between single-stranded Adaptor B and RNA avoids the interference of DNA for the community analysis.
    3. Purification of ligation product
      Transfer 40 μl ligation product to a new 1.5 ml tube, and purify the product using a Gnome Size Selector, strictly following the manufacturer’s instructions. A total volume of 10-μl purified product is obtained for the next step.
      Note: Warm Gnome Size Selector to room temperature, and completely resuspend the Size Selector before use. Accurately use the volume that is recommended.
    4. Synthesize the first strand of cDNA with a tagged random hexamer.
      1. Denaturation of ligation product
        1. Add 1 μl tagged RT primer and 1 μl dNTP (10 mM) to the purified ligation product in a 12-μl denaturation volume.
        2. Mix well and incubate at 65 °C for 5 min using a thermal cycler program. Place the tube on ice immediately after the incubation and leave for at least 5 min.
      2. Reverse transcription
        1. Add the following reagents sequentially into the denatured ligation product, and make a final 20-μl reaction volume:
          5x First Strand Buffer
          4 μl
          100 mM DTT
          2 μl
          RNaseOUT (40 U/μl)
          1 μl
          Reverse Transcriptase
          1 μl
        2. Mix well and use the following thermal cycler program to synthesize the cDNA:
          25 °C for 12 min;
          42 °C for 40 min;
          70 °C for 15 min;
          Hold at 4 °C.
    5. cDNA purification
      Purification is performed using a Gnome Size Selector strictly according to the manufacturer’s instructions. 20 μl purified cDNA is obtained for the next step.
      Note: Warm Gnome Size Selector to room temperature, and completely resuspend the Size Selector before use. Accurately use the volume that is recommended.
    6. PCR amplification
      The complete reagent mixture contains:
      Purified single-stranded cDNA
      20 μl
      2x HiFi PCR Master Mix
      25 μl
      PCR Primer F
      1.25 μl
      Barcoded reverse primer bcX
      1.25 μl
      DNAse/RNase free water
      2.5 μl
      Note: Forward and reverse primers are designed based on the RNA Seq 5’ Adaptor B and tag sequences, and are complementary to the standard Illumina forward and reverse primers. Therefore, the whole process avoids the utilization of microbe-related universal primers. The reverse primer also contains an 8-nucleotide (nt) indexing sequence to allow for multiplexing.
      The PCR amplification conditions are as follows:
      98 °C for 45 sec;
      15 cycles of: 98 °C for 15 sec, 60 °C for 30 sec, 72 °C for 30 sec;
      72 °C for 1 min;
      Hold at 4 °C.
      Note: Usually, 1-2 μl PCR products is enough for visualization on a 1% agarose gel. As a result, a wide range of clear and smear bands (100-2,000 bp) will be observed.
    7. Purification of PCR product
      Size select the 400-600 base pair (bp) PCR product using a Gnome Size Selector strictly according to the manufacturer’s instructions.
      Note: Warm Gnome Size Selector to room temperature, and completely resuspend the Size Selector before use. Accurately use the volume that is recommended. Other size ranges of PCR product can also be obtained using Gnome Size Selector according to the manufacturer’s instructions.
  3. High-throughput sequencing
    Quantify barcoded PCR product from different samples using a QubitTM dsDNA HS Assay Kit on Qubit 2.0 fluorometer. Mix together PCR product from different samples with equal quantity (at least 10 ng for each sample) and sequence on an Illumina MiSeq platform using the 2 x 300 paired end protocol. For each sample, paired-end reads formatted as two FASTQ files will be obtained.

Data analysis

  1. Pre-process paired-end reads with Sickle software v1.33 using the command pe to trim and filter reads with a Phred quality score below 20.
  2. De novo merge paired-end reads using the command join_paired_end.py with default parameters in QIIME v1.8.0.
  3. Transform FASTQ files into fasta format using the command fastq.info in mothur v1.33.3.
  4. Remove merged sequences containing ambiguous nucleotides and homopolymer lengths longer than eight nucleotides using the command screen.seqs in mothur v1.33.3.
  5. Remove merged sequences shorter than 250 bp using the command screen.seqs in mothur v1.33.3.
  6. Classify the reads against the SILVA SSU v119 database in MIPE (Zou et al., 2017) with a bootstrap cut-off of 80% and remove SSU rRNA reads identified as chloroplast, mitochondria or human. Mismatches of the primer 8F (5’-AGAGTTTGAT (C/T) (A/C) TGGCTCAG-3’) (Mao et al., 2012) in all the bacterial 16S rRNA sequences are also identified with this software (Table 1).

    Table 1. Non-coverage rates of the bacterial universal primer 8F

    aThe non-coverage rates were calculated by dividing non-coverage sequences (at least one mismatch within primer 8F) of taxa with their relative total sequences. The phyla with less than 10 non-coveraged sequences in the datasets are not shown.
    bTW: tap water; SC; shower curtain; MW: mudflat surface water; LS: leaf surface; FH: forehead of human skin.

  7. For each sample, extract all the identified prokaryotic 16S rRNA reads using get.seqs command and deposit the reads in a fasta file. Merge all the fasta files of all the samples using cat command in Linux, and use count.seqs command in mothur v1.33.3 to differentiate sequences according to samples.
  8. Align and trim sequences to leave the 8F-V1-V2 regions (E. coli position 8 to 242) using align.seqs and pcr.seqs commands in mothur v1.33.3 respectively.
  9. Analyze OTU based community structures (Figure 2) and calculate diversity indices following the MiSeq SOP pipeline (https://www.mothur.org/wiki/MiSeq_SOP) as described in Kozich et al. (2013). Representative OTU sequences at a cut-off of 0.03 are taxonomically classified against the SILVA SSU v119 database with a bootstrap cut-off of 50%. OTUs belonging to chloroplasts or mitochondria are also removed from the analysis.
    Note: All scripts for computational analysis are available in our supplementary material “Supplementary.docx”.


    Figure 2. Comparisons of OTU-based bacterial communities in different samples at the phylum level. ‘Other phyla' includes taxa that made up of small fractions (< 1%). ‘Unclassified’ includes sequences under a bootstrap cut-off value of 50% for bacteria. TW: tap water; SC; shower curtain; MW: mudflat surface water; LS: leaf surface; FH: forehead of human skin.

Notes

  1. All the RNA samples and reaction reagents should be thawed and operated on ice. Once the reaction mix is prepared, perform the thermal cycler program as soon as possible.
  2. For different samples, the optimum cycles used in the PCR amplification step can be determined using a 10-μl preliminary reaction system.

Acknowledgments

This protocol was adopted from our previous study (Yan et al., 2017). This work was supported by the National Natural Science Foundation of China (NSFC) [grant number 31170114]. We declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Blazewicz, S. J., Barnard, R. L., Daly, R. A. and Firestone, M. K. (2013). Evaluating rRNA as an indicator of microbial activity in environmental communities: limitations and uses. ISME J 7(11): 2061-2068.
  2. Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Pena, A. G., Goodrich, J. K., Gordon, J. I., Huttley, G. A., Kelley, S. T., Knights, D., Koenig, J. E., Ley, R. E., Lozupone, C. A., McDonald, D., Muegge, B. D., Pirrung, M., Reeder, J., Sevinsky, J. R., Turnbaugh, P. J., Walters, W. A., Widmann, J., Yatsunenko, T., Zaneveld, J. and Knight, R. (2010). QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7(5): 335-336.
  3. Joshi, N. A., and Fass, J. N. (2011). Sickle: A sliding-window, adaptive, quality-based trimming tool for FastQ files (Version 1.33).
  4. Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K. and Schloss, P. D. (2013). Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 79(17): 5112-5120.
  5. Li, X. R., Lv, Y., Meng, H., Gu, J. D. and Quan, Z. X. (2014). Analysis of microbial diversity by pyrosequencing the small-subunit ribosomal RNA without PCR amplification. Appl Microbiol Biotechnol 98(8): 3777-3789.
  6. Mao, D. P., Zhou, Q., Chen, C. Y. and Quan, Z. X. (2012). Coverage evaluation of universal bacterial primers using the metagenomic datasets. BMC Microbiol 12: 66.
  7. Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., Lesniewski, R. A., Oakley, B. B., Parks, D. H., Robinson, C. J., Sahl, J. W., Stres, B., Thallinger, G. G., Van Horn, D. J. and Weber, C. F. (2009). Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75(23): 7537-7541.
  8. Urich, T., Lanzen, A., Qi, J., Huson, D. H., Schleper, C. and Schuster, S. C. (2008). Simultaneous assessment of soil microbial community structure and function through analysis of the meta-transcriptome. PLoS One 3(6): e2527.
  9. Yan, Y. W., Jiang, Q. Y., Wang, J. G., Zhu, T., Zou, B., Qiu, Q. F. and Quan, Z. X. (2018). Microbial communities and diversities in mudflat sediments analyzed using a modified metatranscriptomic method. Front Microbiol 9: 93.
  10. Yan, Y. W., Zou, B., Zhu, T., Hozzein, W. N. and Quan, Z. X. (2017). Modified RNA-seq method for microbial community and diversity analysis using rRNA in different types of environmental samples. PLoS One 12(10): e0186161.
  11. Zou, B., Li, J., Zhou, Q. and Quan, Z. X. (2017). MIPE: A metagenome-based community structure explorer and SSU primer evaluation tool. PLoS One 12(3): e0174609.

简介

我们提出了一种用于小亚基核糖体RNA(SSU rRNA)的微生物群落分析的经修改的RNA-Seq方法,其依赖于在逆转录之前将5'衔接子直接连接至RNA。 该方法仅需要低输入量的RNA(10-100ng),并且不需要DNA去除步骤。 使用这种方法,我们可以在不受DNA干扰的情况下获得相同区域(可变区V1-V2)的更多16S rRNA序列,以便分析OTU(经营分类单元)的微生物群落和多样性。 所产生的SSU rRNA序列也适用于通常用于细菌16S rRNA基因扩增的细菌通用引物8F(大肠杆菌8至27位)的覆盖度评估。 修改的RNA-Seq方法将有助于确定各种环境样品的潜在活性微生物群落结构和多样性,并且还可用于鉴定新型微生物类群。

【背景】核糖体RNA(rRNA)占总微生物RNA的90%以上,适合微生物群落分析作为合成蛋白质的微生物生理活性指标(Blazewicz et。,2013年)。微生物群落转录物(包括rRNA和mRNA)在特定环境(双RNA转录组学)中的研究在提供微生物功能和分类信息方面具有优势(Urich等人,2008年)未能进行基于OTU的社区比较。尽管当分析凝胶提取的SSU rRNA时,可以使用16S rRNA序列的V3区来计算和比较多样性指数,但是发现仅有三分之一的所得16S rRNA序列适合于这种分析(Li等人,2014)。此外,这种方法通常需要大量的RNA(Li等人,2014年)。我们最近开发了一种改进的RNA-Seq方法,在逆转录之前在RNA的5'末端使用立即衔接子连接步骤。因此,我们可以获得更多的16S RNA读数,这些读数可以用于基于OTU的群落和多样性分析,特别是关于低RNA产量的样品,例如自来水,浴帘和人体皮肤(Yan等人,2017)以及泥滩沉积物样品(Yan等人,2018)。

关键字:RNA-Seq, 低量, SSU rRNA, OTU, 微生物群落

材料和试剂

  1. RNA提取

    1. 酸洗(≤106μm)(Sigma-Aldrich,目录号:G4649)的玻璃珠
    2. 2毫升珠打浆管(QIAGEN,目录号:13118-400)
    3. mirVANA TM miRNA分离试剂盒(Thermo Fisher Scientific,Invitrogen TM,目录号:AM1560)
  2. RNA-Seq文库制备
    1. PCR管(Corning,Axygen,目录号:PCR-02-L-C)
    2. RNA-Seq文库制备试剂盒,用于全转录组发现 - Illumina兼容(侏儒,目录号:K02421-T)
    3. DNase / RNase游离水(Thermo Fisher Scientific,Invitrogen TM,目录号:AM9932)
    4. Qubit TM RNA HS测定试剂盒(Thermo Fisher Scientific,Invitrogen TM,目录号:Q32855)
    5. RNaseOUT TM重组核糖核酸酶抑制剂(Thermo Fisher Scientific,Invitrogen TM,目录号:10777019)
    6. Qubit TM dsDNA HS分析试剂盒(Thermo Fisher Scientific,Invitrogen TM,目录号:Q32854)
    7. 侏儒大小选择器(侏儒,目录号:R02424S)
  3. 其他材料
    1. 移液管吸头(10μl,200μl,1,000μl)(Corning,Axygen®,产品目录号:TF-300-R-S,TF-200-R-S,TF-1000-R-S)

    2. 1.5 ml Eppendorf管(Eppendorf,目录号:022363204)
    3. 100%乙醇

    4. 无RNA酶70%乙醇
    5. 琼脂糖(Biowest,目录号:111860)
    6. 50x TAE缓冲液(Sangon Biotech,目录号:B548101-0500)
    7. DL2,000 DNA Marker(Takara Bio,目录号:3427A)

设备

  1. 移液器(0-10μl,10-100μl,100-1,000μl)(Eppendorf,产品目录号:k03030,k03031,k03032)
  2. Vortex-genie TM 2(QIAGEN,型号:Vortex-Genie 2)
  3. Fresco 17离心机(Thermo Fisher Scientific,Thermo Scientific TM,型号:Heraeus TM Fresco TM 17)。
  4. Qubit 2.0荧光计(Thermo Fisher Scientific,型号:Qubit 2.0)
  5. 自动热循环仪TP600(Takara Bio,型号:TP600)
  6. MagneSphere ®技术磁性分离架(12个位置)(Promega,产品目录号:Z5342)
  7. 电泳仪(Bio-Rad Laboratories)
  8. 凝胶成像系统

软件

  1. 镰刀v1.33(Joshi和Fass,2011)
  2. Mothur v1.33.3(Schloss et。,2009)
  3. QIIME v1.8.0(Caporaso et。,2010)
  4. MIPE(Zou et。,2017)

程序

注:低生物量样品(自来水,浴帘,泥滩水,叶面和人体皮肤)的样品采集,储存和运输详情请参见Yan等人所述的方法。 (2017年)。关于泥滩沉积物样本,样本采集和核酸提取的细节在我们最近的工作中进行了描述(Yan et al。,2018)。

  1. 核酸提取
    1. 使用mirVANA TM miRNA分离试剂盒从不适合DNase I消化的低生物量样品中提取总RNA或总核酸。优选将五个或更多个拭子合并用于核酸提取,而整片过滤膜优选被切成小块(〜0.5mm 2)用于提取。为了完全破坏微生物细胞壁,用0.7g玻璃珠和0.7ml溶解/结合缓冲液在提取前以最大速度在2ml珠子打浆管中涡旋此预处理的样品。在4℃以13,000xg离心5分钟后,将上清液转移到新的1.5ml管中并严格按照生产商的说明提取总RNA。
    2. 电泳后在1%(w / v)琼脂糖凝胶中观察RNA样品以评估RNA完整性(图1)。在-80°C储存总RNA或总核酸。在制备RNA-Seq文库之前,使用Qubit 2.0荧光计上的Qubit TM RNA HS Assay Kit量化总RNA。

    “”src
    图1.低生物量样品的总RNA电泳M:DL2,000 DNA标记物; TW:自来水; SC;浴帘; MW:泥滩地表水; LS:叶表面; FH:人体皮肤的额头。当加载10μlRNA时,与产生非常低浓度的RNA(<2ng /μl)的样品相比,仅TW和MW显示积分的23S和16S rRNA条带。

  2. 制备RNA-Seq文库
    该RNA-Seq文库制备方案由Gnomegen RNA-Seq文库制备试剂盒方案(目录号:K02421-T)修改。按照下述步骤准备RNA-Seq文库。
    1. 总RNA变性
      1. 将总RNA(10-100 ng)和不含DNase / RNase的水加入0.2 ml PCR管中以制备20-μl反应体积。
      2. 充分混合,并使用热循环仪程序在65℃孵育5分钟。
        孵化后立即放置在冰上,离开至少5分钟。
        注意:我们使用这一步取代原始的片段化步骤,以保持RNA的完整性,并在下一步中直接将RNA-Seq接头连接到rRNA的5'末端。 />
    2. 衔接子连接到RNA的5'末端
      1. 依次向变性的RNA中加入以下试剂,并使反应体积为40.6μl:

        10倍连接缓冲液
        3.6μl(最终〜0.9x)
        10 mM ATP
        4μl(最终〜1 mM)
        连接酶混合物
        1微升
        连接酶补充
        1微升
        RNaseOUT(40 U /μl)
        1μl(最终〜1U /μl)
        连接增强剂混合
        8微升
        RNA Seq 5'适配器B
        2微升
      2. 充分混合,并使用热循环仪程序在37℃孵育2小时。
        孵化后将试管置于冰上。
        注意:RNaseOUT是一种单独购买的试剂。单链衔接子B和RNA之间的这种特异性连接避免了DNA对社区分析的干扰。
      3. 结扎产物的纯化
        将40μl连接产物转移到新的1.5 ml试管中,并严格按照制造商的说明使用Gnome Size Selector纯化产品。
        在下一步中获得总体积为10-μl的纯化产品。
        注:将侏儒尺寸选择器暖至室温,并在使用前完全重新悬浮尺寸选择器。准确使用推荐的音量。
      4. 用标记的随机六聚体合成cDNA的第一链。
        1. 连接产物的变性
          1. 在12μl变性体积中加入1μl标记的RT引物和1μldNTP(10 mM)至纯化的连接产物中。
          2. 充分混合,并使用热循环仪程序在65℃孵育5分钟。
            孵化后立即放置在冰上,离开至少5分钟。
        2. 逆转录
          1. 依次将以下试剂加入变性的连接产物中,并制成最终的20-μl反应体积:
            5x第一股缓冲
            4微升
            100 mM DTT
            2微升
            RNaseOUT(40 U /μl)
            1微升
            逆转录酶
            1微升
          2. 充分混合,并使用以下热循环仪程序来合成cDNA:
            25℃12分钟;
            42℃40分钟;
            70°C 15分钟;
            保持在4°C。
          3. cDNA纯化
            严格按照制造商的说明使用Gnome Size Selector进行纯化。为下一步获得20μl纯化的cDNA。
            注:将侏儒尺寸选择器暖至室温,并在使用前完全重新悬浮尺寸选择器。准确使用推荐的音量。
          4. PCR扩增
            完整的试剂混合物含有:
            纯化的单链cDNA
            20微升
            2x HiFi PCR Master Mix
            25微升
            PCR引物F
            1.25微升
            条形码反向引物bcX
            1.25微升
            DNAse / RNase free water
            2.5微升
            注:正向和反向引物基于RNA Seq 5'衔接子B和标签序列设计,并与标准Illumina正向和反向引物互补。因此,整个过程避免了微生物相关通用引物的利用。反向引物还含有8个核苷酸(nt)的索引序列以允许多路复用。
            PCR扩增条件如下:
            98℃45秒;
            15个循环:98℃15秒,60℃30秒,72℃30秒;
            72℃1分钟;
            保持在4°C。
            注意:通常,1-2μlPCR产物足以在1%琼脂糖凝胶上显示。因此,将观察到广泛的清晰和涂片条带(100-2,000bp)。
          5. 纯化PCR产物
            使用Gnome Size Selector严格按照制造商的说明选择400-600碱基对(bp)PCR产物。
            注:将侏儒尺寸选择器暖至室温,并在使用前完全重新悬浮尺寸选择器。准确使用推荐的音量。其他尺寸范围的PCR产物也可以根据制造商的说明使用Gnome Size Selector获得。
          6. 高通量测序
            使用Qubit 2.0荧光计上的Qubit TM dsDNA HS Assay Kit对来自不同样品的条形码化PCR产物进行定量。使用2 x 300配对末端方案,将来自不同样品的PCR产物以等量(每个样品至少10 ng)和Illumina MiSeq平台上的序列混合在一起。对于每个样本,将获得格式为两个FASTQ文件的配对结束读取。
          7. 数据分析

            1. 使用命令pe,使用Sickle软件v1.33预处理配对结束读取,修剪并过滤Phred质量分数低于20的读取。
            2. De novo 使用带有QIIME v1.8.0中的默认参数的join_paired_end.py命令合并配对结束读取。

            3. 在voth v1.33.3中使用命令fastq.info将FASTQ文件转换为fasta格式。
            4. 使用命令screen.seqs在mothur v1.33.3中移除含有模糊核苷酸和长于8个核苷酸的均聚物长度的合并序列。

            5. 使用命令screen.seqs在v1.33.3中删除短于250 bp的合并序列。
            6. 将MIPE中的SILVA SSU v119数据库的读数分类(Zou et al。,2017),启动截止值为80%,并去除鉴定为叶绿体,线粒体或人的SSU rRNA读数。还鉴定了所有细菌16S rRNA序列中引物8F(5'-AGAGTTTGAT(C / T)(A / C)TGGCTCAG-3')的错配(Mao等人,2012)用这个软件(表1)。

              表1.细菌通用引物8F的未覆盖率

              通过将分类群的非覆盖序列(至少一个引物8F内的不匹配)与其相对总序列相除来计算未覆盖率。没有显示数据集中少于10个未覆盖序列的门。
              TW:自来水;自来水; SC;浴帘; MW:泥滩地表水; LS:叶表面; FH:人体皮肤的额头。

            7. 对于每个样品,使用get.seqs命令提取所有鉴定的原核16S rRNA读数,并将读数存入fasta文件。在Linux中使用cat命令合并所有样本的所有fasta文件,并使用mothur v1.33.3中的count.seqs命令根据样本区分序列。
            8. 使用align.seqs和pcr.seqs命令分别在v1.33.3中对齐和修剪序列以离开8F-V1-V2区域( E.coli 位置8至242)。
            9. 分析基于OTU的社区结构(图2)并计算MiSeq SOP管道之后的多样性指数( https:// www。 mothur.org/wiki/MiSeq_SOP ),如Kozich等人(2013)中所述。代表性的OTU序列在0.03的截止值处分类地针对SILVA SSU v119数据库进行分类,其自引导截止值为50%。属于叶绿体或线粒体的OTUs也从分析中删除。
              注:所有用于计算分析的脚本都可以在我们的补充材料“ Supplementary.docx “。


              图2.不同样品中门的水平上OTU基细菌群落的比较'其他物种'包括由小分数(<1%)组成的分类群。 “未分类”包括对于细菌的50%自助截止值的序列。 TW:自来水; SC;浴帘; MW:泥滩地表水; LS:叶表面; FH:人体皮肤的额头。

            笔记

            1. 所有RNA样品和反应试剂都应解冻并在冰上运行。一旦准备好反应混合物,尽快执行热循环仪程序。
            2. 对于不同的样品,PCR扩增步骤中使用的最佳循环可以使用10-μl初步反应体系来确定。

            致谢

            该协议是从我们以前的研究中采纳的(Yan等人,2017年)。这项工作得到了国家自然科学基金委的支持[资助号31170114]。我们声明,该研究是在没有任何可能被视为潜在利益冲突的商业或财务关系的情况下进行的。

            参考

            1. Blazewicz,S. J.,Barnard,R. L.,Daly,R. A.和Firestone,M. K.(2013)。 评估rRNA作为环境群落中微生物活动的指标:限制和用途 ISME J 7(11):2061-2068。
            2. Caporaso,JG,Kuczynski,J.,Stombaugh,J.,Bittinger,K.,Bushman,FD,Costello,EK,Fierer,N.,Pena,AG,Goodrich,JK,Gordon,JI,Huttley,GA,Kelley, ST,Knights,D.,Koenig,JE,Ley,RE,Lozupone,CA,McDonald,D.,Muegge,BD,Pirrung,M.,Reeder,J.,Sevinsky,JR,Turnbaugh,PJ,Walters,WA, Widmann,J.,Yatsunenko,T.,Zaneveld,J.和Knight,R。(2010)。 QIIME允许分析高通量的社区测序数据。 Nat Methods < / em> 7(5):335-336。
            3. Joshi,N.A。和Fass,J.N。(2011)。 镰刀:适用于FastQ文件的滑动窗口,自适应,基于质量的修剪工具(版本1.33)。 < br />
            4. Kozich,J.J.,Westcott,S.L.,Baxter,N.T。,Highlander,S.K。和Schloss,P.D。(2013)。 开发用于分析MiSeq Illumina测序的扩增子序列数据的双指标测序策略和调控管线平台。 Appl Environ Microbiol 79(17):5112-5120。
            5. Li,X.R.,Lv,Y.,Meng,H.,Gu,J.D。和Quan,Z.X.(2014)。 通过在没有PCR扩增的情况下焦磷酸测序小亚基核糖体RNA来分析微生物多样性 Appl Microbiol Biotechnol 98(8):3777-3789。
            6. Mao,D.P.,Zhou,Q.,Chen,C.Y。和Quan,Z.X.(2012)。 使用宏基因组数据集进行通用细菌引物的覆盖率评估 12:66.
            7. Schloss,PD,Westcott,SL,Ryabin,T.,Hall,JR,Hartmann,M.,Hollister,EB,Lesniewski,RA,Oakley,BB,Parks,DH,Robinson,CJ,Sahl,JW,Stres,B. ,Thallinger,GG,Van Horn,DJ和Weber,CF(2009)。 介绍mothur:开源,独立于平台的社区支持的软件,用于描述和比较微生物群落。 Appl Environ Microbiol 75(23):7537-7541。
            8. Urich,T.,Lanzen,A.,Qi,J。,Huson,D.H。,Schleper,C。和Schuster,S.C。(2008)。 通过分析元转录组同时评估土壤微生物群落结构和功能。 PLoS One 3(6):e2527。
            9. Yan,Y.W.,Jiang,Q.Y.,Wang,J.G.,Zhu,T.,Zou,B.,Qiu,Q.F。和Quan,Z.X.(2018)。 使用改进的元转换方法分析泥滩沉积物中的微生物群落和多样性。 Front Microbiol 9:93。
            10. Yan,Y.W.,Zou,B.,Zhu,T.,Hozzein,W.N。和Quan,Z.X.(2017)。 修正的RNA-seq方法用于在不同类型的环境样品中使用rRNA进行微生物群落和多样性分析< / PLoS One 12(10):e0186161。
            11. Zou,B.,Li,J.,Zhou,Q。和Quan,Z.X.(2017)。 MIPE:基于宏基因组的社区结构探索者和SSU引物评估工具。 PLoS One 12(3):e0174609。
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Copyright: © 2018 The Authors; exclusive licensee Bio-protocol LLC.
引用:Yan, Y., Zhu, T., Zou, B. and Quan, Z. (2018). A Modified Low-quantity RNA-Seq Method for Microbial Community and Diversity Analysis Using Small Subunit Ribosomal RNA. Bio-protocol 8(9): e2828. DOI: 10.21769/BioProtoc.2828.
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