Summary

在酵母S.酵母缺氧反应期间, 测量一段时间内的 mRNA 水平

Published: August 10, 2017
doi:

Summary

在这里, 我们提出了一个协议使用 RNA 序列监测 mRNA 水平随着时间的推移在缺氧反应的S. 酿酒酵母细胞。这种方法可以适应于分析基因表达在任何细胞反应。

Abstract

基因表达的复杂变化通常会调节细胞反应的很大一部分。每个基因都可能改变表达与独特的动力学, 因为该基因是由特定的时间, 其中一个许多刺激, 信号通路或次要的影响调节。为了在酵母S.酵母中捕获对缺氧的整个基因表达反应, 使用 RNA 序列分析在接触缺氧后的特定时间内监测所有基因的 mRNA 水平。缺氧是由生长在 100% N2气体中的细胞建立的。重要的是, 不像其他的缺氧研究, 麦角固醇和不饱和脂肪酸不添加到媒体, 因为这些代谢物影响基因表达。时间点选择在 0-4 小时的范围内缺氧, 因为该时期捕获的主要变化的基因表达。在每个时间点, mid-log 缺氧细胞迅速过滤和冻结, 限制暴露于 O2和伴随变化的基因表达。总 RNA 从细胞被提取并且用于丰富为 mRNA, 然后被转换成 cDNA。从这个 cDNA 中, 创建了多个复合库, 并在下一代排序器的一个泳道中测序了八或更多的样本。描述了 post-sequencing 管道, 包括质量基础修剪、读取映射和确定每个基因的读取数。DESeq2 在 R 统计环境中被用来识别在任何一个缺氧时间点发生显著变化的基因。对三生物复制的分析显示, 高重现性, 不同动力学的基因和大量预期 O2调控基因。这些方法可用于研究各种生物体的细胞如何随着时间的推移对缺氧反应, 并适应在其他细胞反应过程中研究基因表达。

Introduction

许多生物体反应缺氧, 或低 O2, 通过改变基因表达式1,2,3。这种反应可以帮助细胞应对缺乏对有氧呼吸和一些生物合成反应至关重要的基质, 而且还能改变氧化还原状态4。在S. 酿酒酵母中进行的几个微阵列研究表明, 数百个基因的 mRNA 水平因缺氧而发生变化56789,10,11,12. 最近, RNA seq 被用来表征在缺氧时的基因表达变化13。在此, 对实验细节进行了介绍和讨论。

缺氧可以以各种方式实现, 每种方法都产生不同级别的 O2。在这里, 缺氧是建立在连续流动超高纯度 N2成烧瓶, 这降低 [O2] 立即溶解与可再生动力学10。这是可能的, 有一些 O2分子存在, 有助于新陈代谢和基因表达, 但这种环境被认为非常接近厌氧。在没有 O2的情况下, 酵母细胞不能合成血红素、麦角甾醇和不饱和脂肪酸41214。因此, 以往的研究包括这些代谢物时, 生长酵母没有氧气5,10,15。然而, 许多缺氧反应是介导的这些代谢物的损耗, 从而补充他们逆转缺氧基因表达反应12,16。为了模拟自然缺氧, 这些代谢物没有添加到媒体。在短时间内, 细胞暴露在缺氧状态, 没有这些必需的代谢物, 没有明显增加细胞死亡 (数据没有显示), 也没有长期的压力响应13

反应也取决于菌株及其基因型。特别重要的是已知的低氧反应调节器的等位基因2。S288C 应变背景是高度理想的, 以便结果可以与其他基因组研究与此菌株进行比较。然而, S288C 包含了一个部分功能等位基因的HAP1吉恩17, 转录调节器对缺氧反应至关重要。此等位基因在 S288C 中修复, 使用Σ1278b 应变背景下的野生拷贝11

基因表达高度依赖于细胞环境。因此, 在进行全基因组的 mRNA 分析时, 保持一个恒定的环境是很重要的, 同时改变另一个参数, 例如时间、刺激或基因型。为了获得高度重现性的结果, 请考虑这三项研究的实践及其所有的生物或技术复制。首先, 同样的实验者应该进行这项研究, 因为技术实践可能在实验者中有所不同。第二, 在培养基中应使用相同批次的配料, 因为每个批次都有一个稍有不同的成分, 可以影响基因表达。第三, 为了最小化细胞周期效应, 每个时间点应该由生长 mid-log 阶段的异步细胞组成 (1-2 x 107细胞/mL)。

当表征一个复杂的反应, 如基因表达反应的缺氧, 一个时间的过程是有利的, 以确定动力学的各种事件。应选择特定的时间点来捕获响应的主要变化。在这项研究中, 观察到0和 4 h 之间的时间点, 因为过去的实验揭示了在这一期间的基因表达的广泛变化13

为了测量全球基因表达, RNA seq 使用了18,19。这个方法使用下一代测序来确定每个基因转录的相对丰度。与 DNA 微阵列分析相比, RNA 序列表现出更高的灵敏度 (以检测更少的抄本), 更大的动态范围 (测量更大的褶皱变化) 和优异的重现性 (准确地跟随基因表达随着时间的推移)。通常, 大多数细胞 rna 是核糖体 rna, 因此许多方法已经开发, 以丰富的特定 RNA 种类20。在这里, 聚 T 珠被用来纯化多含 A 的 mrna 转录, 虽然各种商业可用的 rRNA 耗竭套件也可以有效的 mrna 丰富。

在这里, 对缺氧的S 酿酒酵母基因表达反应进行了表征。细胞暴露在缺氧, 然后取样在八时间点 (0, 5, 10, 30, 60, 120, 180 和240分钟)。为了确认重复性和识别统计变化的成绩单, 三进行了生物复制。rna 是由机械破坏和柱纯化提取, 然后处理 rna 序列分析。描述了 post-sequencing 管道, 并提供了允许精确复制所执行的分析的编程脚本。具体来说, Trimmomatic 21、TopHat2 22、HTseq 23、R 统计环境24和 DESeq2 包25用于处理 RNA 序列数据, 并识别607基因在缺氧.主成分分析 (PCA) 和基因表达的复制表明该技术的重现性。聚类和 heatmaps 揭示了 wide-ranging 表达动力学, 而基因本体 (GO) 分析表明, 许多细胞过程, 如有氧呼吸, 是丰富的一套氧调节基因。

Protocol

1. 诱导缺氧 前一天或更早的缺氧时间课程: 准备孵化器, 细胞过滤系统, 真空, 气罐, 烧瓶, 塞子, 玻璃管, 和油管, 如在材料表。 将 N 个2容器、孵化器、真空和过滤系统放在接近的位置, 以便能够快速处理电池。 通过将玻璃瓶和灭菌中的成分混合, 制备无菌液体 YPD 培养基 (1% 酵母提取物, 2% 蛋白胨, 2% 葡萄糖)。 规划孵化器的烧瓶布局。注: 从 N<su…

Representative Results

三次独立进行缺氧时间过程和 RNA 序列分析。为了检验三复制的重现性, 利用主成分分析 (PCA) 对所有基因的基因表达数据进行了分析。图 2显示了示例在前两个主要组件上的变化情况, 它们一起表示58.9% 的可变性。这一分析表明, 每一次课程都有类似的变化 (如每条曲线的相似形状所示)。另外, 最后两个复制比第一个复制更相似。这与最后两次复制是由…

Discussion

在本研究中, 对所有基因的 mRNA 水平进行了测试, 在低氧的酵母S酵母。目的是分析全球基因表达在受控近缺氧环境中的生长变化。采取了若干步骤, 以确保此处所述的方法是经过严格控制和重现的。首先, 细胞暴露在一个精确定义的缺氧环境中: 富媒体 (YPD) 中的 99.999% N2 。其他缺氧的研究已经关闭了烧瓶或管空气32, 使用缺氧模拟氯化钴33, 或雇用缺…

Declarações

The authors have nothing to disclose.

Acknowledgements

我们感谢刘易斯-杰瑞·斯格勒研究所的综合基因组测序核心设施在普林斯顿大学为技术咨询和 RNA 图书馆的准备和测序。这项工作得到了罗恩大学和 NIH 研究院 R15GM113187 对 M.J.H. 的资助。

Materials

Enclosed dry incubator Thermo Scientific MaxQ 4000 Set at 30°C. Modify the door to allow entry of one Tygon tube. Alternatively, use the New Brunswick G25 incubator, which contains a tube port. Do not use an open-air water shaker, as condensation will collect in the tubes between flasks, possibly cross-contaminating cultures.
Micro-analysis Filter Holder Millipore XX1002530 25mm diameter, stainless steel support, no. 5 perforated silicone stopper mounts in standard 125mL filtering flask
Strong vacuum Edwards E-LAB 2 The “house” vacuum may be too weak. Alternatively, use an electric-power portable vacuum pump like the one listed here.
1000-mL flask To act as vacuum trap.
~2-foot lengths of Heavy Wall Vacuum Tubing, inner diameter 3/8 in, outer diameter 7/8 in Tygon 38TT Two pieces: the first connects vacuum to trap, and the second connects trap to filter system.
High-pressure N2 gas tank 99.999% purity, >1000psi, with a regulator and gas flow controller
Autoclaved 500mL flask Opening covered with aluminum foil. One for each yeast strain.
Autoclaved 250mL flasks Openings covered with aluminum foil. One for each time point plus two for water traps.
Flask stoppers (size 6, two holes with 5mm diameter) Sterilized with 70% ethanol. One for each flask.
Glass tubing, length 9 cm or 17 cm, inner diameter 2 mm, outer diameter 5 mm Sterilized with 70% ethanol. Two tubes for each flask. Place into the holes of each stopper. See Figure 1 for placement of 9- vs 17- cm tubes.
~25-cm lengths of plastic tubing, inner diameter 5 mm Tygon E-3603 One piece for each flask. Sterilized with 70% ethanol.
Sterile filter discs Millipore HAWP02500 25mm diameter, 0.45 µm pore size, one for each time point
Sterile dH2O (~100mL)
1-mL cuvettes For measuring OD600 (i.e., cell concentration)
50-mL sterile centrifuge tubes One for each time point
Clean and sterile tweezers
liquid nitrogen For freezing cells
acid-washed beads Sigma G8772 Keep at 4°C for lysing cells
Qiagen RNeasy Mini Kit Qiagen 74104 For RNA column purification
Qiagen RLT buffer Prepare by adding 10µL of β-Mercaptoethanol per 1mL of RLT buffer, keep at 4C.
2-mL collection tubes Qiagen included in the Qiagen Rneasy Mini Kit
Buffer RPE Qiagen included in the Qiagen Rneasy Mini Kit
Buffer RW1 Qiagen included in the Qiagen Rneasy Mini Kit
DNase I stock and working solutions Qiagen 79254 The DNase I enzyme comes as lyophilized powder in a glass vial. Using a sterile needle and syringe, inject 550µL of RNase-free water (provided in Qiagen kit) into the vial. Mix by gently inverting the bottle. To avoid denaturing the enzyme, do not vortex. Using a pipet, remove this stock solution from the vial and store in freezer (-20°C) in single-use aliquots (80µL each). The stock solution should not be thawed and refrozen.
Buffer RDD Qiagen included in the Qiagen DNase Kit
Ice cold 2-mL screw-cap tubes For lysing cells during RNA extraction
bead mill homogenizer Biospec Mini-Beadbeater-24 112011 Keep in cold room
Bacto Peptone BD DF0118 for liquid YPD media
Bacto Yeast Extract BD DF0886 for liquid YPD media
glucose Fisher D16 for liquid YPD media
Qubit assay tubes Thermo Fisher Q32856 for measuring nucleic acid concentration
Quant-iTTM dsDNA BR Assay Kit Thermo Fisher Q32853 for measuring nucleic acid concentration
Quant-iTTM RNA Assay Kit Thermo Fisher Q32855 for measuring nucleic acid concentration
Qubit Fluorometer Thermo Fisher Q33216 for measuring nucleic acid concentration
Commercial electrophoresis system Agilent Bioanalyzer 2100 for measuring nucleic acid quality
Next-generation sequencer Illumina HiSeq 2500 for sequencing libraries
automated liquid handling system Wafergen Apollo 324 for creating sequencing libraries
PrepX PolyA mRNA Isolation Kit Wafergen 400047 for isolating mRNA from total RNA
PrepX RNA SEQ for Illumina Library Kit Wafergen 400039 for creating strand-specific sequencing libraries from total RNA
Barcode Splitter https://toolshed.g2.bx.psu.edu/repository?repository_id=7119c4f7a89efa57&changeset_revision=e7b7cdc1834d
Samtools, which includes the gzip command http://www.htslib.org/download/
Trimmomatic http://www.usadellab.org/cms/?page=trimmomatic
Bowtie2 (installed before TopHat) http://bowtie-bio.sourceforge.net/bowtie2/index.shtml
TopHat https://ccb.jhu.edu/software/tophat/index.shtml
HTSeq http://www-huber.embl.de/HTSeq/doc/overview.html
R (installed before R Studio) https://cran.rstudio.com
R Studio (free version) https://www.rstudio.com/products/rstudio/download/

Referências

  1. Semenza, G. L. Oxygen sensing, homeostasis, and disease. New Eng. J Med. 365 (6), 537-547 (2011).
  2. Butler, G. Hypoxia and gene expression in eukaryotic microbes. Annu. Rev. Micro. 67, 291-312 (2013).
  3. Ratcliffe, P. J. Oxygen sensing and hypoxia signalling pathways in animals: the implications of physiology for cancer. J. Physiol. 591 (Pt 8), 2027-2042 (2013).
  4. Rosenfeld, E., Beauvoit, B. Role of the non-respiratory pathways in the utilization of molecular oxygen bySaccharomyces cerevisiae. Yeast. 20 (13), 1115-1144 (2003).
  5. Ter Linde, J. J., et al. Genome-wide transcriptional analysis of aerobic and anaerobic chemostat cultures of Saccharomyces cerevisiae. J. Bacteriol. 181 (24), 7409-7413 (1999).
  6. Ter Linde, J. J., Steensma, H. Y. A microarray-assisted screen for potential Hap1 and Rox1 target genes in Saccharomyces cerevisiae. Yeast. 19 (10), 825-840 (2002).
  7. Kwast, K. E., et al. Genomic analyses of anaerobically induced genes in Saccharomyces cerevisiae: functional roles of Rox1 and other factors in mediating the anoxic response. J. Bacteriol. 184 (1), 250-265 (2002).
  8. Becerra, M., et al. The yeast transcriptome in aerobic and hypoxic conditions: effects of hap1, rox1, rox3 and srb10 deletions. Mol. Microbiol. 43 (3), 545-555 (2002).
  9. Lai, L. -. C., Kosorukoff, A. L., Burke, P. V., Kwast, K. E. Dynamical remodeling of the transcriptome during short-term anaerobiosis in Saccharomyces cerevisiae: differential response and role of Msn2 and/or Msn4 and other factors in galactose and glucose media. Mol. Cell. Biol. 25 (10), 4075-4091 (2005).
  10. Lai, L. C., Kosorukoff, A. L., Burke, P. V., Kwast, K. E. Metabolic-State-Dependent Remodeling of the Transcriptome in Response to Anoxia and Subsequent Reoxygenation in Saccharomyces cerevisiae. Euk. Cell. 5 (9), 1468-1489 (2006).
  11. Hickman, M. J., Winston, F. Heme levels switch the function of Hap1 of Saccharomyces cerevisiae between transcriptional activator and transcriptional repressor. Mol. Cell. Biol. 27 (21), 7414-7424 (2007).
  12. Hickman, M. J., Spatt, D., Winston, F. The Hog1 mitogen-activated protein kinase mediates a hypoxic response in Saccharomyces cerevisiae. Genética. 188 (2), 325-338 (2011).
  13. Bendjilali, N., et al. Time-Course Analysis of Gene Expression During the Saccharomyces cerevisiae Hypoxic Response. G3. 7 (1), 221-231 (2017).
  14. Chellappa, R., et al. The membrane proteins, Spt23p and Mga2p, play distinct roles in the activation of Saccharomyces cerevisiae OLE1 gene expression. Fatty acid-mediated regulation of Mga2p activity is independent of its proteolytic processing into a soluble transcription activator. J. Biol. Chem. 276 (47), 43548-43556 (2001).
  15. Abramova, N. E., et al. Regulatory mechanisms controlling expression of the DAN/TIR mannoprotein genes during anaerobic remodeling of the cell wall in Saccharomyces cerevisiae. Genética. 157 (3), 1169-1177 (2001).
  16. Hughes, A. L., Todd, B. L., Espenshade, P. J. SREBP Pathway Responds to Sterols and Functions as an Oxygen Sensor in Fission Yeast. Cell. 120 (6), 831-842 (2005).
  17. Gaisne, M., Bécam, A. M., Verdière, J., Herbert, C. J. A "natural" mutation in Saccharomyces cerevisiae strains derived from S288c affects the complex regulatory gene HAP1 (CYP1). Curr. Gen. 36 (4), 195-200 (1999).
  18. Wang, Z., Gerstein, M., Snyder, M. RNA-Seq: a revolutionary tool for transcriptomics. Nat. Rev. Gen. 10 (1), 57-63 (2009).
  19. Anders, S., Huber, W. Differential expression analysis for sequence count data. Genome Biol. 11 (10), R106 (2010).
  20. Conesa, A., et al. A survey of best practices for RNA-seq data analysis. Genome Biol. 17 (1), 13 (2016).
  21. Bolger, A. M., Lohse, M., Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinf. 30 (15), 2114-2120 (2014).
  22. Kim, D., Pertea, G., Trapnell, C., Pimentel, H., Kelley, R., Salzberg, S. L. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14 (4), R36 (2013).
  23. Anders, S., Pyl, P. T., Huber, W. HTSeq–A Python framework to work with high-throughput sequencing data. Bioinf. 31 (2), 166-169 (2015).
  24. . R: A Language and Environment for Statistical Computing Available from: https://www.R-project.org (2015)
  25. Love, M. I., Huber, W., Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15 (12), 550 (2014).
  26. Brown, T., Mackey, K., Du, T. Analysis of RNA by Northern and Slot Blot Hybridization. Curr. Prot. Mol. Biol. 74, 4.9.1-4.9.19 (2004).
  27. Edgar, R., Domrachev, M., Lash, A. E. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nuc. Acids Res. 30 (1), 207-210 (2002).
  28. Cherry, J. M., et al. Saccharomyces Genome Database: the genomics resource of budding yeast. Nuc. Acids Res. 40, D700-D705 (2012).
  29. Hothorn, T., Everitt, B. S. . A Handbook of Statistical Analyses using R. , (2014).
  30. Saldanha, A. J. Java Treeview–extensible visualization of microarray data. Bioinformatics. 20 (17), 3246-3248 (2004).
  31. Eisen, M. B., Spellman, P. T., Brown, P. O., Botstein, D. Cluster analysis and display of genome-wide expression patterns. Proc. Nat. Acad. Sci. 95 (25), 14863-14868 (1998).
  32. Davies, B. S. J., Rine, J. A Role for Sterol Levels in Oxygen Sensing in Saccharomyces cerevisiae. Genética. 174 (1), 191-201 (2006).
  33. Meena, R. C., Kumar, N., Nath, S., Chakrabarti, A. Homologous Recombination is Activated at Early Time Points Following Exposure to Cobalt Chloride Induced Hypoxic Conditions in Saccharomyces cerevisiae. Ind. J. Microb. 52 (2), 209-214 (2012).
  34. Snoek, I. S. I., Tai, S. L., Pronk, J. T., Yde Steensma, H., Daran, J. -. M. Involvement of Snf7p and Rim101p in the transcriptional regulation of TIR1 and other anaerobically upregulated genes in Saccharomyces cerevisiae. FEMS Yeast Res. 10 (4), 367-384 (2010).
  35. Ellahi, A., Thurtle, D. M., Rine, J. The Chromatin and Transcriptional Landscape of Native Saccharomyces cerevisiae Telomeres and Subtelomeric Domains. Genética. 200 (2), 505-521 (2015).
  36. Collart, M. A., Oliviero, S., et al. Preparation of yeast RNA. Curr. Prot. Mol. Biol. , (2001).
  37. Blankenberg, D., et al. Manipulation of FASTQ data with Galaxy. Bioinf. 24 (14), 1783-1785 (2010).
  38. Martini, P., et al. timeClip: pathway analysis for time course data without replicates. BMC Bioinf. 15, (2014).
  39. Oh, S., Song, S., Grabowski, G., Zhao, H., Noonan, J. P. Time series expression analyses using RNA-seq: a statistical approach. BioMed Res. Int. 2013, 1-16 (2013).
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Willis, S. D., Hossian, A. K. M. N., Evans, N., Hickman, M. J. Measuring mRNA Levels Over Time During the Yeast S. cerevisiae Hypoxic Response. J. Vis. Exp. (126), e56226, doi:10.3791/56226 (2017).

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