Summary

大豆共生结节多聚体纯化

Published: July 01, 2022
doi:

Summary

该协议描述了从完整的大豆结节中纯化真核多体的方法。测序后,基因表达分析的标准管道可用于鉴定转录组和翻译组水平的差异表达基因。

Abstract

该协议的目的是为研究大豆(甘氨酸max)共生结节的真核翻译组提供策略。本文描述了优化的方法,以分离植物来源的多核糖体及其相关的mRNA,以使用RNA测序进行分析。首先,通过在保存多小体和RNA的条件下从整个冷冻大豆结节中匀浆获得细胞质裂解物。然后,通过低速离心清除裂解物,并使用15%的上清液进行总RNA(TOTAL)分离。剩余的澄清裂解物用于通过两层蔗糖垫(12%和33.5%)超速离心分离多聚体。重悬后从多粒体沉淀中纯化多聚体相关mRNA(PAR)。TOTAL和PAR均通过高灵敏度毛细管电泳进行评估,以满足RNA-seq测序文库的质量标准。作为下游应用的一个例子,测序后,基因表达分析的标准管道可用于获得转录组和翻译组水平的差异表达基因。总之,该方法与RNA-seq相结合,可以研究复杂组织(例如共生结节)中真核mRNA的翻译调节。

Introduction

豆科植物,如大豆(Glycine max),可以与称为根瘤菌的特定土壤细菌建立共生关系。这种互惠关系导致植物根部形成新的器官,即共生结节。结节是寄存细菌的植物器官,由宿主细胞组成,其细胞质定植于一种称为拟杆菌的特殊形式的根瘤菌。这些拟杆菌催化大气氮(N 2)还原成氨,氨被转移到植物中以换取碳水化合物12

尽管这种固氮共生是研究最充分的植物-微生物共生之一,但许多方面仍有待更好地理解,例如受到不同非生物胁迫条件的植物如何调节它们与共生伙伴的相互作用以及这如何影响结节代谢。通过分析结节翻译组(即主动翻译的信使RNA[mRNA]的子集),可以更好地理解这些过程。多核糖体或多核糖体是与mRNA相关的多个核糖体的复合物,通常用于研究翻译3。多聚体分析方法包括分析与多聚体相关的mRNA,并已成功用于研究控制不同生物过程中发生的基因表达的转录后机制45

从历史上看,基因组表达分析主要集中在确定mRNA丰度6789然而,由于基因表达转录后调控的不同阶段,特别是翻译101112转录本和蛋白质水平之间缺乏相关性。此外,在转录组水平上的变化与在翻译组水平上发生的变化之间没有观察到依赖性13。对正在翻译的mRNA集的直接分析可以比仅分析mRNA水平时获得的细胞基因表达(其终点是蛋白质丰度)更准确和完整的测量141516

该协议描述了如何通过两层蔗糖垫的差异离心从完整的大豆结节中纯化植物来源的多聚体(图1)。然而,由于拟杆菌衍生的核糖体也存在于结节中,因此核糖体和RNA物种的混合物被纯化,即使真核糖体占主要部分(90%-95%)。还描述了随后的RNA分离、定量和质量控制(图1)。该协议与RNA-seq相结合,应提供有关复杂组织(例如共生结节)中真核mRNA的翻译调节的实验结果。

Figure 1
图1:从共生结节纯化真核多体的拟议方法的示意图概述。 该方案概述了方案中遵循的步骤,从(1)植物生长和(2)结节收获到(3)制备胞质提取物,(3)获得总样品和(4)PAR样品,以及(5)RNA提取和质量控制。缩写:PEB = 多聚体提取缓冲液;RB = 重悬缓冲液;总 = 总核糖核酸;PAR = 多聚体相关的 mRNA。 请点击此处查看此图的大图。

Protocol

1. 植物生长和根瘤菌接种 为了产生所需的结节,请在受控条件下将所选的大豆种子播种在生长室的选定基质中。注意:在该协议中,种子播种在装有沙子:蛭石(1:1)混合物的0.5升塑料瓶中。生长室的昼/夜循环温度分别为28 °C / 20 °C,光/暗光周期分别为16 h/8 h。光合有效辐射强度为620 μmol·m−2·s−1. 提前准备液体酵母提取物甘露醇(YEM)培养基?…

Representative Results

使用上述程序纯化的TOTAL和PAR级分的数量和质量评估是决定其成功与否的关键,因为对于大多数下游应用,例如RNA测序,高质量样品是文库制备和测序的基础。此外,RNA分子的完整性允许在样品收集时捕获基因表达谱的快照18。在这种情况下,使用生物分析仪进行这些测量时会获得RNA完整性数(RIN)。RIN 用于以稳健、可靠且独立于用户的方式分配完整性值,范围从 10(完整)到 1…

Discussion

在翻译水平上研究基因表达调控对于更好地理解不同的生物学过程至关重要,因为细胞基因表达的终点是蛋白质丰度1314。这可以通过分析感兴趣的组织或生物体的翻译组来评估,其中应纯化多体部分并分析其相关的mRNA

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Disclosures

The authors have nothing to disclose.

Acknowledgements

这项研究由CSIC I + D 2020年第282号资助,FVF 2017年第210号资助和PEDECIBA(玛丽亚·玛莎·塞恩斯)资助。

Materials

Plant growth and rhizobia inoculation
Orbital shaker Daihan Scientific Model SHO-1D
YEM-medium Amresco J850 (yeast extract) 0122 (mannitol)
Water deficit treatment
KNO3 Merck 221295
Porometer Decagon Device Model SC-1
Scalpel
Preparation of cytosolic extracts
Brij L23 Sigma-Aldrich P1254
Centrifuge Sigma Model 2K15
Chloranphenicol Sigma-Aldrich C0378
Cycloheximide Sigma-Aldrich C7698
DOC Sigma-Aldrich 30970
DTT Sigma-Aldrich D9779
EGTA Sigma-Aldrich E3889
Igepal CA 360 Sigma-Aldrich I8896
KCl Merck 1.04936
MgCl2 Sigma-Aldrich M8266
Plastic tissue grinder Fisher Scientific 12649595
PMSF Sigma-Aldrich P7626
PTE Sigma-Aldrich P2393
Tris Invitrogen 15504-020
Triton X-100 Sigma-Aldrich T8787
Tween 20 Sigma-Aldrich P1379
Weighing dish  Deltalab 1911103
Preparation of sucrose cushions
Sucrose Invitrogen 15503022
SW 40 Ti rotor Beckman-Coulter
Ultracentrifuge Beckman-Coulter Optima L-100K
Ultracentrifuge tubes Beckman-Coulter 344059 13.2 mL tubes
RNA extraction and quality control
Agarose Thermo scientific R0492
Bioanalyzer Agilent Model 2100. Eukaryote total RNA nano assay
Chloroform DI 41191
Ethanol Dorwil UN1170
Isopropanol Mallinckrodt 3032-06
Glycogen Sigma 10814-010
TRIzol LS Ambion 102960028
Miscellaneous
Falcon tubes 15 mL Biologix 10-0152
Filter tips 10 µL BioPointe Scientific 321-4050
Filter tips 1000 µL BioPointe Scientific 361-1050
Filter tips 20 µL BioPointe Scientific 341-4050
Filter tips 200 µL Tarsons 528104
Microcentrifuge tubes 1.5 mL Tarsons 500010-N
Microcentrifuge tubes 2.0 mL Tarsons 500020-N
Sequencing company Macrogen
Sterile 250 mL flask Marienfeld 4110207

References

  1. Limpens, E., et al. Cell- and tissue-specific transcriptome analyses of Medicago truncatula root nodules. PLoS ONE. 8 (5), 64377 (2013).
  2. Masson-Boivin, C., Giraud, E., Perret, X., Batut, J. Establishing nitrogen-fixing symbiosis with legumes: How many rhizobium recipes. Trends in Microbiology. 17 (10), 458-466 (2009).
  3. King, H. A., Gerber, A. P. Translatome profiling: Methods for genome-scale analysis of mRNA translation. Briefings in Functional Genomics. 15 (1), 22-31 (2014).
  4. Chassé, H., Boulben, S., Costache, V., Cormier, P., Morales, J. Analysis of translation using polysome profiling. Nucleic Acids Research. 45 (3), 15 (2017).
  5. Yángüez, E., Castro-Sanz, A. B., Fernández-Bautista, N., Oliveros, J. C., Castellano, M. M. Analysis of genome-wide changes in the translatome of Arabidopsis seedlings subjected to heat stress. PloS ONE. 8 (8), 71425 (2013).
  6. Brown, P. O., Botstein, D. Exploring the new world of the genome with DNA microarrays. Nature Genetics. 21, 33-37 (1999).
  7. Krishnamurthy, A., Ferl, R. J., Paul, A. -. L. Comparing RNA-Seq and microarray gene expression data in two zones of the Arabidopsis root apex relevant to spaceflight. Applications in Plant Sciences. 6 (11), 1197 (2018).
  8. Shulse, C. N., et al. High-throughput single-cell transcriptome profiling of plant cell types. Cell Reports. 27 (7), 2241-2247 (2019).
  9. Wang, Z., Gerstein, M., Snyder, M. RNA-Seq: A revolutionary tool for transcriptomics. Nature Reviews Genetics. 10 (1), 57-63 (2009).
  10. Kawaguchi, R., Girke, T., Bray, E. A., Bailey-Serres, J. Differential mRNA translation contributes to gene regulation under non-stress and dehydration stress conditions in Arabidopsis thaliana. The Plant Journal. 38 (5), 823-839 (2004).
  11. Larsson, O., Tian, B., Sonenberg, N. Toward a genome-wide landscape of translational control. Cold Spring Harbor Perspectives in Biology. 5 (1), 012302 (2013).
  12. Vogel, C., Marcotte, E. M. Insights into regulation of protein abundance from proteomics and transcriptomis analyses. Nature Reviews Genetics. 13 (4), 227-232 (2013).
  13. Tebaldi, T., et al. Widespread uncoupling between transcriptome and translatome variations after a stimulus in mammalian cells. BMC Genomics. 13 (220), 1-15 (2012).
  14. Wang, T., et al. Translating mRNAs strongly correlate to proteins in a multivariate manner and their translation ratios are phenotype specific. Nucleic Acids Research. 41 (9), 4743-4754 (2013).
  15. Ingolia, N. T. Ribosome profiling: New views of translation, from single codons to genome scale. Nature Reviews Genetics. 15 (3), 205-213 (2014).
  16. Lukoszek, R., Feist, P., Ignatova, Z. Insights into the adaptive response of Arabidopsis thaliana to prolonged thermal stress by ribosomal profiling and RNA-Seq. BMC Plant Biology. 16 (1), 1-13 (2016).
  17. Broughton, W. J., Dilworth, M. J. Control of leghaemoglobin synthesis in snake beans. Biochemical Journal. 125 (4), 1075-1080 (1971).
  18. Schroeder, A., et al. The RIN: An RNA integrity number for assigning integrity values to RNA measurements. BMC Molecular Biology. 7, 1-14 (2006).
  19. Rio, D. C., Ares, M., Hannon, G. J., Nilsen, T. W. Nondenaturing agarose gel electrophoresis of RNA nondenaturing agarose gel electrophoresis of RNA. Cold Spring Harbor Protocols. 2010 (6), 1-3 (2012).
  20. Ewels, P., Magnusson, M., Lundin, S., Käller, M. MultiQC: Summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 32 (19), 3047-3048 (2016).
  21. Bolger, A. M., Lohse, M., Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics. 30 (15), 2114-2120 (2014).
  22. Marcel, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal. 17 (1), 10-12 (2011).
  23. . Sickle: A sliding-window, adaptive, quality-based trimming tool for FastQ files (Version 1.33) Available from: https://github.com/najoshi/sickle (2011)
  24. Langmead, B., Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nature Methods. 9 (4), 357-359 (2012).
  25. Kim, D., et al. TopHat2: Accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biology. 14 (4), 1-13 (2013).
  26. Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nature Methods. 14 (4), 417-419 (2017).
  27. Liao, Y., Smyth, G. K., Shi, W. featureCounts: An efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 30 (7), 923-930 (2013).
  28. Robinson, M. D., McCarthy, D. J., Smyth, G. K. edgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 26 (1), 139-140 (2010).
  29. Love, M. I., Huber, W., Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology. 15 (550), 1-21 (2014).
  30. Ritchie, M. E., et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research. 43 (7), 47 (2015).
  31. Afgan, E., et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update. Nucleic Acids Research. 46, 537-544 (2018).
  32. Hunt, G. P., et al. GEOexplorer: A webserver for gene expression analysis and visualisation. Nucleic Acids Research. , (2022).
  33. Imbeaud, S., et al. Towards standardization of RNA quality assessment using user-independent classifiers of microcapillary electrophoresis traces. Nucleic Acids Research. 33 (6), 1-12 (2005).
  34. Di Paolo, A., et al. PDCD4 regulates axonal growth by translational repression of neurite growth-related genes and is modulated during nerve injury responses. RNA. 26 (11), 1637-1653 (2020).
  35. Smircich, P., et al. Ribosome profiling reveals translation control as a key mechanism generating differential gene expression in Trypanosoma cruzi. BMC Genomics. 16 (1), 443 (2015).
  36. Eastman, G., Sharlow, E. R., Lazo, J. S., Bloom, G. S., Sotelo-Silveira, J. R. Transcriptome and translatome regulation of pathogenesis in Alzheimer’s disease model mice. Journal of Alzheimer’s Disease. 86 (1), 365-386 (2022).
  37. Zanetti, M. E., Chang, I. -. F., Gong, F., Galbraith, D. W., Bailey-Serres, J. Immunopurification of polyribosomal complexes of Arabidopsis for global analysis of gene expression. Plant physiology. 138 (2), 624-635 (2005).
  38. Mustroph, A., et al. Profiling translatomes of discrete cell populations resolves altered cellular priorities during hypoxia in Arabidopsis. Proceedings of the National Academy of Sciences of the United States of America. 106 (44), 18843-11848 (2009).
  39. Ingolia, N. T., Ghaemmaghami, S., Newman, J. R. S., Weissman, J. S. Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science. 324 (5924), 218-223 (2009).
  40. Brar, G. A., Weissman, J. S. Ribosome profiling reveals the what, when, where and how of protein synthesis. Nature Reviews. Molecular Cell Biology. 16 (11), 651-664 (2015).
  41. Eastman, G., Smircich, P., Sotelo-Silveira, J. R. Following ribosome footprints to understand translation at a genome wide level. Computational and Structural Biotechnology Journal. 16, 167-176 (2018).
  42. Westermann, A. J., Gorski, S. A., Vogel, J. Dual RNA-seq of pathogen and host. Nature Reviews Microbiology. 10 (9), 618-630 (2012).

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Cite This Article
Sainz, M. M., Filippi, C. V., Eastman, G., Sotelo-Silveira, M., Martinez, C. M., Borsani, O., Sotelo-Silveira, J. Polysome Purification from Soybean Symbiotic Nodules. J. Vis. Exp. (185), e64269, doi:10.3791/64269 (2022).

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