使用液体色谱加上串联质谱法的 糖核 酸菌的定量元细胞学
Summary
我们提出了一个协议，用于识别和量化主要类别的水溶性代谢物在酵母 糖体中。所述方法通用、坚固且灵敏。它允许结构异构体和立体形式的水溶性代谢物彼此分离。
Abstract
代谢学是一种用于识别和量化细胞、组织、器官、生物流体或生物体内许多低分子量中间体和代谢产物的方法。代谢学传统上侧重于水溶性代谢物。水溶性代谢体是综合细胞网络的最终产物，它集成了各种基因组、表观基因组、转录学、蛋白质组学和环境因素。因此，代谢分析直接评估了在各种生物体中过多的生物过程中对所有这些因素的行动结果。其中一种生物是初露头角的酵母 糖核酸，一种具有完全测序基因组的单细胞真核生物。由于 S.Cerevisiae 是适应综合分子分析，它被用作解剖真核细胞内许多生物过程背后的机制的模型。一种多功能的分析方法，用于对水溶性代谢体进行可靠、敏感和准确的定量评估，将为剖析这些机制提供基本方法。在这里，我们提出了一个协议，为代谢活性的优化条件淬火和水溶性代谢物提取从 S.Cerevisiae 细胞。该协议还描述了使用液相色谱加上串联质谱法（LC-MS/MS）对提取的水溶性代谢物进行定量分析。此处描述的非目标代谢学的 LC-MS/MS 方法用途广泛且坚固。它能够识别和量化370多种具有不同结构、物理和化学特性的水溶性代谢物，包括这些代谢物的不同结构异构体和立体体形式。这些代谢物包括各种能量载体分子、核苷酸、氨基酸、单糖、糖解中间体和三碳循环中间体。非靶向代谢的LC-MS/MS方法非常敏感，允许在低至0.05pmol/μL的浓度下识别和量化某些水溶性代谢物。该方法已成功用于评估在不同条件下培养的野生型和突变酵母细胞的水溶性代谢体。
Introduction
水溶性代谢物是低分子量中间体和新陈代谢产物，有助于基本的细胞过程。这些进化保存的过程包括将营养转化为可用能量、大分子的合成、细胞生长和信号、细胞周期控制、基因表达的调节、应激反应、新陈代谢的转化后调节、线粒体功能的维持、车辆细胞贩运、自噬、细胞老化以及调节细胞死亡1、2、3。
水溶性代谢物的许多基本作用是通过研究在萌芽酵母S.Cerevisiae1，3，4，7，9，14，15，16，17，18，19，20，21，22发现。这种单细胞真核生物是一个有用的模型有机体，通过解剖机制，水溶性代谢物有助于细胞过程，因为它的适应先进的生化，遗传和分子生物分析23，24，25，26。虽然非靶向代谢的LC-MS/MS方法已用于研究水溶性代谢物在萌芽酵母3、18、22、27中的作用，但这种分析需要改进其多功能性、稳健性、灵敏度，以及区分这些代谢物的不同结构异构体和立体体形式的能力。
近年来，在将非靶向代谢物的LC-MS/MS方法应用于体内水溶性代谢物的分析方面取得了重大进展。然而，使用这种方法的许多挑战仍然是2，28，29，30，31，32，33，34，35，36。这些挑战包括以下挑战。首先，许多水溶性代谢物的细胞内浓度低于目前使用的方法的敏感阈值。二是代谢活性淬火效率过低，细胞内代谢物淬火相关细胞泄漏程度过高，不适合现行方法：因此，目前使用的方法低估了水溶性代谢物的细胞内浓度。第三，现有方法不能区分特定代谢物的结构异构体（即具有相同化学公式但原子连接性的分子）或立体体（即具有相同化学公式和原子连接性的分子，但具有空间中不同的原子排列）：这防止了某些代谢物的正确注释，目前使用的方法。第四，现有的母离子（MS1）和二次离子（MS2）质量光谱在线数据库不完整：这会影响使用当前方法产生的原始 LC-MS/MS 数据对特定代谢物的正确识别和量化。第五，现有方法不能使用单一类型的代谢物提取来回收所有或大多数类型的水溶性代谢物。第六，现有方法不能使用单一类型的LC柱来分离所有或大多数类型的水溶性代谢物。
在这里，我们优化了在 S.cerevisiae 细胞内淬火的条件，在提取之前保持这些细胞内的大部分水溶性代谢物，并从酵母细胞中提取大多数类型的水溶性代谢物。我们开发了一种多功能、坚固和敏感的方法，用于基于LC-MS/MS的识别和量化从 S.Cerevisiae 细胞中提取的370多种水溶性代谢物。这种非靶向代谢方法能够评估各种能量载体分子、核苷酸、氨基酸、单糖、糖解中间体和三碳基循环中间体的细胞内浓度。开发的LC-MS/MS方法允许识别和量化具有不同结构、物理和化学特性的不同结构异构体和立体形式的水溶性代谢物。
Protocol
1. 制造和消毒一种生长酵母的媒介 用巴托普酮 （YP） 介质制作 180 mL 的完整酵母提取物。完整的 YP 介质包含 1% （w/v） 酵母提取物和 2% （w/v） 巴托普酮。 将 180 mL 的 YP 介质均匀地分配到四个 250 mL 的埃伦迈尔烧瓶中。每个烧瓶都含有 45 mL 的 YP 介质。 在 15 psi/121 °C 下自动包装 45 分钟，用 YP 介质对烧瓶进行消毒。 2. 野生型酵母菌株 使用 BY…
Representative Results
为了改进酵母细胞内水溶性代谢物的定量评估，我们优化了细胞淬火的条件，以便检测代谢物。为此目的的细胞淬火涉及快速逮捕细胞内的所有酶反应31，33，37，38。这种细胞代谢活性的抑制是任何方法在体内量化水溶性代谢物的重要步骤，因为它防止低估其细胞内浓?…
Discussion
要成功使用此处描述的协议，请遵循下面描述的预防措施。氯仿和甲醇从实验室塑料制品中提取各种物质。因此，请谨慎处理。避免使用塑料的步骤，涉及接触这两种有机溶剂中的任何一个。使用硅酸盐玻璃移液器进行这些步骤。使用前用氯仿和甲醇将这些移液器升起。仅使用抗有机溶剂的聚丙烯制成的微管尖和管。在 LC-MS/MS 的样品准备过程中，在将气泡插入井板之前，先消除玻璃瓶中的所有气…
Disclosures
The authors have nothing to disclose.
Acknowledgements
我们感谢蒂托连科实验室的现任和前任成员进行讨论。我们感谢质谱学生物应用中心、结构和功能基因组学中心以及显微镜和细胞成像中心（均在康科迪亚大学）提供出色的服务。这项研究得到了加拿大自然科学和工程研究理事会（NSERC）的资助（RGPIN 2014-04482和CRDPJ 515900-17）。K.M得到了康科迪亚大学阿曼德·阿坎巴尔特奖学金和康科迪亚大学艺术与科学系主任卓越奖的支持。
Materials
| Chemicals | |||
| Acetonitrile | Fisher Scientific | A9554 | |
| Ammonium acetate | Fisher Scientific | A11450 | |
| Ammonium bicarbonate | Sigma | 9830 | |
| Bactopeptone | Fisher Scientific | BP1420-2 | |
| Chloroform | Fisher Scientific | C297-4 | |
| Glucose | Fisher Scientific | D16-10 | |
| L-histidine | Sigma | H8125 | |
| L-leucine | Sigma | L8912 | |
| L-lysine | Sigma | L5501 | |
| Methanol | Fisher Scientific | A4564 | |
| Methanol | Fisher Scientific | A4564 | |
| Propidium iodide | Thermo Scientific | R37108 | |
| Uracil | Sigma | U0750 | |
| Yeast extract | Fisher Scientific | BP1422-2 | |
| Hardware equipment | |||
| 500 ml centrifuge bottles | Beckman | 355664 | |
| Agilent 1100 series LC system | Agilent Technologies | G1312A | |
| Beckman Coulter Centrifuge | Beckman | 6254249 | |
| Beckman Coulter Centrifuge Rotor | Beckman | JA-10 | |
| Centra CL2 clinical centrifuge | Thermo Scientific | 004260F | |
| Digital thermometer | Omega | HH509 | |
| Foam Tube Holder Kit with Retainer | Thermo Scientific | 02-215-388 | |
| SeQuant ZIC-pHILIC zwitterionic-phase column (5µm polymer 150 x 2.1 mm) | Sigma Milipore | 150460 | |
| Thermo Orbitrap Velos MS | Fisher Scientific | ETD-10600 | |
| Ultrasonic sonicator | Fisher Scientific | 15337416 | |
| Vortex | Fisher Scientific | 2215365 | |
| ZORBAX Bonus-RP, 80Å, 2.1 x 150 mm, 5 µm | Agilent Technologies | 883725-901 | |
| Laboratory materials | |||
| 2-mL Glass sample vials with Teflon lined caps | Fisher Scientific | 60180A-SV9-1P | |
| Glass beads (acid-washed, 425-600 μm) | Sigma-Aldrich | G8772 | |
| Hemacytometer | Fisher Scientific | 267110 | |
| 15-mL High-speed glass centrifuge tubes with Teflon lined caps | PYREX | 05-550 | |
| Software | |||
| Compound Discoverer 3.1 | Fisher Scientific | V3.1 | |
| Yeast strain | |||
| Yeast strain BY4742 | Dharmacon | YSC1049 | |
References
- Hackett, S. R., et al. Systems-level analysis of mechanisms regulating yeast metabolic flux. Science. 354 (6311), aaf2786 (2016).
- Johnson, C. H., Ivanisevic, J., Siuzdak, G. Metabolomics: beyond biomarkers and towards mechanisms. Nature Reviews Molecular Cell Biology. 17 (7), 451-459 (2016).
- Mülleder, M., et al. Functional metabolomics describes the yeast biosynthetic regulome. Cell. 167 (2), 553-565 (2016).
- López-Otín, C., Galluzzi, L., Freije, J., Madeo, F., Kroemer, G. Metabolic control of longevity. Cell. 166 (4), 802-821 (2016).
- Krishnaiah, S. Y., et al. Clock regulation of metabolites reveals coupling between transcription and metabolism. Cell Metabolism. 25 (4), 961-974 (2017).
- Lee, H. J. Proteomic and metabolomic characterization of a mammalian cellular transition from quiescence to proliferation. Cell Reports. 20 (3), 721-736 (2017).
- Stryeck, S., Birner-Gruenberger, R., Madl, T. Integrative metabolomics as emerging tool to study autophagy regulation. Microbial Cell. 4 (8), 240-258 (2017).
- Babst, M. Eisosomes at the intersection of TORC1 and TORC2 regulation. Traffic. 20 (8), 543-551 (2019).
- Pedro, J., Sica, V., Madeo, F., Kroemer, G. Acyl-CoA-binding protein (ACBP): the elusive ‘hunger factor’ linking autophagy to food intake. Cell Stress. 3 (10), 312-318 (2019).
- Rahmani, S., Defferrari, M. S., Wakarchuk, W. W., Antonescu, C. N. Energetic adaptations: Metabolic control of endocytic membrane traffic. Traffic. 20 (12), 912-931 (2019).
- Viltard, M., et al. The metabolomic signature of extreme longevity: naked mole rats versus mice. Aging. 11 (14), 4783-4800 (2019).
- Zhu, J., Thompson, C. B. Metabolic regulation of cell growth and proliferation. Nature Reviews Molecular Cell Biology. 20 (7), 436-450 (2019).
- Morrison, A. J. Chromatin-remodeling links metabolic signaling to gene expression. Molecular Metabolism. 38, 100973 (2020).
- Bitterman, K. J., Medvedik, O., Sinclair, D. A. Longevity regulation in Saccharomyces cerevisiae: linking metabolism, genome stability, and heterochromatin. Microbiology and Molecular Biology Reviews. 67 (3), 376-399 (2003).
- Carmona-Gutierrez, D. Apoptosis in yeast: triggers, pathways, subroutines. Cell Death and Differentiation. 17 (5), 763-773 (2010).
- Minois, N., Carmona-Gutierrez, D., Madeo, F. Polyamines in aging and disease. Aging. 3 (8), 716-732 (2011).
- Ring, J., et al. The metabolism beyond programmed cell death in yeast. Experimental Cell Research. 318 (11), 1193-1200 (2012).
- Ibáñez, A. J., et al. Mass spectrometry-based metabolomics of single yeast cells. Proceedings of the National Academy of Sciences of the United States of America. 110 (22), 8790-8794 (2013).
- Pietrocola, F., et al. Acetyl coenzyme A: a central metabolite and second messenger. Cell Metabolism. 21 (6), 805-821 (2015).
- Carmona-Gutierrez, D., et al. Guidelines and recommendations on yeast cell death nomenclature. Microbial Cell. 5 (1), 4-31 (2018).
- Zimmermann, A., et al. Yeast as a tool to identify anti-aging compounds. FEMS Yeast Research. 18 (6), foy020 (2018).
- Leupold, S., et al. Saccharomyces cerevisiae goes through distinct metabolic phases during its replicative lifespan. eLife. 8, e41046 (2019).
- Weissman, J., Guthrie, C., Fink, G. R. . Guide to Yeast Genetics: Functional Genomics, Proteomics, and Other Systems Analyses. , (2010).
- Botstein, D., Fink, G. R. Yeast: an experimental organism for 21st century biology. 遗传学. 189 (3), 695-704 (2011).
- Duina, A. A., Miller, M. E., Keeney, J. B. Budding yeast for budding geneticists: a primer on the Saccharomyces cerevisiae model system. 遗传学. 197 (1), 33-48 (2014).
- Strynatka, K. A., Gurrola-Gal, M. C., Berman, J. N., McMaster, C. R. How surrogate and chemical genetics in model organisms can suggest therapies for human genetic diseases. 遗传学. 208 (3), 833-851 (2018).
- Boer, V. M., et al. Growth-limiting intracellular metabolites in yeast growing under diverse nutrient limitations. Molecular Biology of the Cell. 21 (1), 198-211 (2010).
- Clish, C. B. Metabolomics: an emerging but powerful tool for precision medicine. Cold Spring Harbor Molecular Case Studies. 1 (1), a000588 (2015).
- Fuhrer, T., Zamboni, N. High-throughput discovery metabolomics. Current Opinion in Biotechnology. 31, 73-78 (2015).
- Liu, X., Locasale, J. W. Metabolomics: A primer. Trends in Biochemical Sciences. 42 (4), 274-284 (2017).
- Lu, W., et al. Metabolite measurement: pitfalls to avoid and practices to follow. Annual Review of Biochemistry. 86, 277-304 (2017).
- Riekeberg, E., Powers, R. New frontiers in metabolomics: from measurement to insight. F1000 Reseach. 6, 1148 (2017).
- Gertsman, I., Barshop, B. A. Promises and pitfalls of untargeted metabolomics. Journal of Inherited Metabolic Disease. 41 (3), 355-366 (2018).
- Cui, L., Lu, H., Lee, Y. H. Challenges and emergent solutions for LC-MS/MS based untargeted metabolomics in diseases. Mass Spectrometry Reviews. 37 (6), 772-792 (2018).
- Ivanisevic, J., Want, E. J. From samples to insights into metabolism: Uncovering biologically relevant information in LC-HRMS metabolomics data. Metabolites. 9 (12), 308 (2019).
- Srivastava, S. Emerging insights into the metabolic alterations in aging using metabolomics. Metabolites. 9 (12), 301 (2019).
- Chetwynd, A. J., Dunn, W. B., Rodriguez-Blanco, G. Collection and preparation of clinical samples for metabolomics. Advances in Experimental Medicine and Biology. 965, 19-44 (2017).
- Pinu, F. R., Villas-Boas, S. G., Aggio, R. Analysis of intracellular metabolites from microorganisms: quenching and extraction protocols. Metabolites. 7 (4), (2017).
- Zhang, N., et al. Cell permeability and nuclear DNA staining by propidium iodide in basidiomycetous yeasts. Applied Microbiology and Biotechnology. 102 (9), 4183-4191 (2018).
- Tu, B. P., et al. Cyclic changes in metabolic state during the life of a yeast cell. Proceedings of the National Academy of Sciences of the United States of America. 104 (43), 16886-16891 (2007).
- Walvekar, A., Rashida, Z., Maddali, H., Laxman, S. A versatile LC-MS/MS approach for comprehensive, quantitative analysis of central metabolic pathways. Wellcome Open Research. 3, 122 (2018).
- Buescher, J. M., Moco, S., Sauer, U., Zamboni, N. Ultrahigh performance liquid chromatography-tandem mass spectrometry method for fast and robust quantification of anionic and aromatic metabolites. Analytical Chemistry. 82 (11), 4403-4412 (2010).
- Cui, L., Lu, H., Lee, Y. H. Challenges and emergent solutions for LC-MS/MS based untargeted metabolomics in diseases. Mass Spectrometry Reviews. 37 (6), 772-792 (2018).
- Oberacher, H., et al. Annotating nontargeted LC-HRMS/MS data with two complementary tandem mass spectral libraries. Metabolites. 9 (1), 3 (2018).
- Tada, I., et al. Creating a reliable mass spectral-retention time library for all ion fragmentation-based metabolomics. Metabolites. 9 (11), 251 (2019).
- Villas-Bôas, S. G., et al. Global metabolite analysis of yeast: evaluation of sample preparation methods. Yeast. 22 (14), 1155-1169 (2005).
- Crutchfield, C. A., Lu, W., Melamud, E., Rabinowitz, J. D. Mass spectrometry-based metabolomics of yeast. Methods in Enzymology. 470, 393-426 (2010).
- Zhang, T., Creek, D. J., Barrett, M. P., Blackburn, G., Watson, D. G. Evaluation of coupling reversed phase, aqueous normal phase, and hydrophilic interaction liquid chromatography with Orbitrap mass spectrometry for metabolomic studies of human urine. Analytical Chemistry. 84 (4), 1994-2001 (2012).
- Villas-Bôas, S. G., Moxley, J. F., Akesson, M., Stephanopoulos, G., Nielsen, J. High-throughput metabolic state analysis: the missing link in integrated functional genomics of yeasts. Biochemical Journal. 388 (Pt 2), 669-677 (2005).
- Buescher, J. M., Moco, S., Sauer, U., Zamboni, N. Ultrahigh performance liquid chromatography-tandem mass spectrometry method for fast and robust quantification of anionic and aromatic metabolites. Analytical Chemistry. 82 (11), 4403-4412 (2010).
Cite This Article
Mohammad, K., Jiang, H., Titorenko, V. I. Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry. J. Vis. Exp. (167), e62061, doi:10.3791/62061 (2021).