图1:细胞存活率检测 A)原生细胞的体积分布图,虚线为平均值,点线为最大值和最小值;B)细胞提取体积与活细胞数之间的关系。C)活细胞细胞核提取后GFP 的变化;D)死细胞细胞核提取后GFP 的变化;E)活细胞提取后(2.9 pL)后对细胞形态的连续观测。
3.使用FluidFM 单细胞提取物的三种应用
3.1 透射电镜负染色观测
对于细胞亚结构的观察,往往对于揭示细胞病变有着重要的意义。然而细胞裂解的传统手段往往会产生大量的碎片,因此对细胞器的观察造成了诸多困难。在本篇报道中,作者通过使用FluidFM 设备提取细胞内容物,在低温环境下转移到透射电镜的铜网上,然后进行负染色和挥干,之后将片子放到透射电镜下观察,并使用传统裂解方法得到单细胞溶液同时铺设在铜网上进行对比。通过观察他们发现,使用FluidFM 技术得到的细胞提取物能够观察到大泡状的结构、小球状的结构和长丝类的结构,如图2C 所示。而相比之下细胞裂解法得到的结果却不尽人意,如图2D 所示。
图2:细胞提取物负染色电镜图 A)电镜样本制作的示意图;B)提取液滴在电镜铜网上的放大图;C)FluidFM 技术的细胞提取物电镜下的图像;D)普通裂解法的细胞提取物电镜下的图像。
3.2 酶活力的检测
酶活力的检测对于探寻细胞异质性有着十分重要的意义。因此作者也对FluidFM 提取的细胞提取物进行了对比。首先作者通过β-半乳糖苷酶实验来测定提取蛋白的完整性。通过测定酶解底物产生的荧光素的荧光强度,他们成功观察到荧光强度随时间而增加,说明提取物中的蛋白没有被破坏,如图3C、D 所示。随后作者又对不同细胞进行了不同酶活力的检验,结果显示无论是LacZ 转基因HeLa 细胞上还是在测定HeLa 细胞的Caspase3 酶上均取得了成功,如图3 E、F 所示。
图3:酶活性分析 A)细胞提取分析的示意图;B)将提取的3 pL 细胞提取物放到预先液封的微孔中;C)酶解底物产生荧光素的荧光强度变化,荧光在1 小时后可见。D)图形量化荧光强度时间表;E)LacZ 转基因细胞和非转基因细胞之间β-半乳糖苷酶活性的差异;F)Caspase3 酶活力测定。
4.3 单细胞级转录检测
单细胞层面的基因表达通常需要反转录或者PCR 扩增,之后使用qPCR 测定。而在此之前往往需要将细胞裂解,而作者他们采用了与传统方法不同的策略。他们首先创建了使用FluidFM 直接从活细胞中提取大约0.01 pg RNA,并用普通PCR 管合成cDNA 并进行qPCR 检测,如图4A 所示。由于如此小的提取量是不能直接放到PCR 管里面的,所以他们采取的策略是首先将提取液注入1uL 水中,然后再转移到PCR 管中,进行合成和检测如图6B 所示。他们检测了两种管家基因beta-actin (ACTB)beta-2-microglobulin (B2M)以及GFP mRNA 的表达量。在21 个样本中有90%的样本成功检测到至少1 中基因的表达,其中2/3 的样本可以同时检测到三种基因的表达。而对细胞核的检测中,也能够检测到至少一种基因的表达,如图4C 所示。在对比同一细胞同时提取细胞质(1.7 pL)和细胞核(1.3 pL)中这三种基因的表达时,可以发现两者基本相同,如图4D 所示。
图4: A)单细胞提取mRNA 转录实验的示意图;B)将提取物放入液滴中的方法;C) ERCC spike 为对照,测定细胞质中GFP、B2M、ACTB 的Ct 值;D)对同一细胞的细胞质与细胞核进行提取并测定Ct 值。
总结
随着生物研究越发趋于微观化,对于分析单个细胞的需求变得越来越大。但是由于单个细胞体积小,所能够提取出的物质相比以前细胞群落分析来说,难度显著提高。这不仅对检测仪器的灵敏度有了新的更高的要求,也同时对样本本身的质量也提出了更高的指标。本篇中使用FluidFM 提取活细胞所取得的样本质量相比于传统裂解手段有了明显的提高,从而取得了令人满意的结果。另外这种方法控制提取量后,甚至能够做到不杀死细胞的情况下完成提取,这使得对于对单个细胞代谢测定的追踪成为了可能。
多功能单细胞显微操作系统
瑞士 Cytosurge FluidFM BOT
 |
产品简介:
多功能单细胞显微操作系统--FluidFM BOT,是将原子力系统、微流控系统、细胞培养系统为一体的单细胞操作系统。主要功能包括单细胞注射、单细胞提取以及单细胞分离。
FluidFM BOT 极大的方便了单细胞水平的研究,尤其适合应用于精准医疗、单细胞生物学、单细胞质谱、单细胞基因编辑、药物研发等领域。
注射、提取、分选
一体化的单细胞操纵解决方案
|
参考文献
1. Actis, P., Maalouf, M.M., Kim, H.J., Lohith, A., Vilozny, B., Seger, R.A., and Pourmand, N. (2014). Compartmental genomics in living cells revealed by single- cell nanobiopsy. ACS Nano 8, 546–553.
2. Amara, A., and Mercer, J. (2015). Viral apoptotic mimicry. Nat. Rev. Microbiol. 13, 461–469.
3. Bengtsson, M., Sta° hlberg, A., Rorsman, P., and Kubista, M. (2005). Gene expression profiling in single cells from the pancreatic islets of Langerhans reveals lognormal distribution of mRNA levels. Genome Res. 15, 1388–1392.
4. Bertrand, R., Solary, E., O’Connor, P., Kohn, K.W., and Pommier, Y. (1994). Induction of a common pathway of apoptosis by staurosporine. Exp. Cell Res. 211, 314–321.
5. Cai, X., Evrony, G.D., Lehmann, H.S., Elhosary, P.C., Mehta, B.K., Poduri, A., and Walsh, C.A. (2014). Single-cell, genomewide sequencing identifies clonal somatic copy-number variation in the human brain. Cell Rep. 8, 1280–1289.
6. Grindberg, R.V., Yee-Greenbaum, J.L., McConnell, M.J., Novotny, M., O’Shaughnessy, A.L., Lambert, G.M., Arau´ zo-Bravo, M.J., Lee, J., Fishman, M., Robbins, G.E., et al. (2013). RNA-sequencing from single nuclei. Proc. Natl. Acad. Sci. USA 110, 19802–19807.
7. Guillaume-Gentil, O., Potthoff, E., Ossola, D., Do¨ rig, P., Zambelli, T., and Vorholt, J.A. (2013). Force-controlled fluidic injection into single cell nuclei. Small 9, 1904–1907.
8. Guillaume-Gentil, O., Potthoff, E., Ossola, D., Franz, C.M., Zambelli, T., and Vorholt, J.A. (2014). Force-controlled manipulation of single cells: from AFM to FluidFM. Trends Biotechnol. 32, 381–388.
9. Hashimshony, T., Wagner, F., Sher, N., and Yanai, I. (2012). CEL-Seq: singlecell RNA-Seq by multiplexed linear amplification. Cell Rep. 2, 666–673.
10. Jiang, L., Schlesinger, F., Davis, C.A., Zhang, Y., Li, R., Salit, M., Gingeras, T.R., and Oliver, B. (2011). Synthetic spike-in standards for RNA-seq experiments. Genome Res. 21, 1543–1551.
11. Kovarik, M.L., and Allbritton, N.L. (2011). Measuring enzyme activity in single cells. Trends Biotechnol. 29, 222–230.
12. Kuipers, M.A., Stasevich, T.J., Sasaki, T., Wilson, K.A., Hazelwood, K.L., McNally, J.G., Davidson, M.W., and Gilbert, D.M. (2011). Highly stable loading of Mcm proteins onto chromatin in living cells requires replication to unload. J. Cell Biol. 192, 29–41.
13. Liebherr, R.B., Hutterer, A., Mickert, M.J., Vogl, F.C., Beutner, A., Lechner, A., Hummel, H., and Gorris, H.H. (2015). Threein-one enzyme assay based on single molecule detection in femtoliter arrays. Anal. Bioanal. Chem. 407, 7443–7452.
14. Lo, S.J., and Yao, D.J. (2015). Get to understand more from single-cells: current studies of microfluidic-based techniques for single-cell analysis. Int. J. Mol. Sci. 16, 16763–16777.
15. Meister, A., Gabi, M., Behr, P., Studer, P., Vo¨ ro¨ s, J., Niedermann, P., Bitterli, J., Polesel-Maris, J., Liley, M., Heinzelmann, H., and Zambelli, T. (2009). FluidFM: combining atomic force microscopy and nanofluidics in a universal liquid delivery system for single cell applications and beyond. Nano Lett. 9, 2501–2507.
16. Nagaraj, N., Wisniewski, J.R., Geiger, T., Cox, J., Kircher, M., Kelso, J., Pa¨ a¨ bo, S., and Mann, M. (2011). Deep proteome and transcriptome mapping of a human cancer cell line. Mol. Syst. Biol. 7, 548.
17. Nawarathna, D., Turan, T., and Wickramasinghe, H.K. (2009). Selective probing of mRNA expression levels within a living cell. Appl. Phys. Lett. 95, 83117. O’Huallachain, M., Karczewski, K.J., Weissman, S.M., Urban, A.E., and Snyder, M.P. (2012). Extensive genetic variation in somatic human tissues. Proc. Natl. Acad. Sci. USA 109, 18018–18023.
18. Osada, T., Uehara, H., Kim, H., and Ikai, A. (2003). mRNA analysis of single living cells. J. Nanobiotechnology 1, 2.
19. Pfeiffer-Guglielmi, B., Dombert, B., Jablonka, S., Hausherr, V., van Thriel, C., Scho¨ bel, N., and Jansen, R.P. (2014). Axonal and dendritic localization of mRNAs for glycogen-metabolizing enzymes in cultured rodent neurons. BMC Neurosci. 15, 70.
20. Picelli, S., Faridani, O.R., Bjo¨ rklund, A.K., Winberg, G., Sagasser, S., and Sandberg, R. (2014). Full-length RNA-seq from single cells using Smartseq2. Nat. Protoc. 9, 171–181.
21. Raj, A., Peskin, C.S., Tranchina, D., Vargas, D.Y., and Tyagi, S. (2006). Stochastic mRNA synthesis in mammalian cells. PLoS Biol. 4, e309.
22. Ramsko¨ ld, D., Luo, S., Wang, Y.C., Li, R., Deng, Q., Faridani, O.R., Daniels, G.A., Khrebtukova, I., Loring, J.F., Laurent, L.C., et al. (2012). Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nat. Biotechnol. 30, 777–782.
23. Rissin, D.M., Kan, C.W., Campbell, T.G., Howes, S.C., Fournier, D.R., Song, L., Piech, T., Patel, P.P., Chang, L., Rivnak, A.J., et al. (2010). Single-molecule enzyme-linked immunosorbent assay detects serum proteins at subfemtomolar concentrations. Nat. Biotechnol. 28, 595–599.
24. Rondelez, Y., Tresset, G., Tabata, K.V., Arata, H., Fujita, H., Takeuchi, S., and Noji, H. (2005). Microfabricated arrays of femtoliter chambers allow single molecule enzymology. Nat. Biotechnol. 23, 361–365.
25. Saha-Shah, A., Weber, A.E., Karty, J.A., Ray, S.J., Hieftje, G.M., and Baker, L.A. (2015). Nanopipettes: probes for local sample analysis. Chem. Sci. 6, 3334–3341.
26. Sarkar, A., Kolitz, S., Lauffenburger, D.A., and Han, J. (2014). Microfluidic probe for single-cell analysis in adherent tissue culture. Nat. Commun. 5, 3421.
27. Schmid, A., Kortmann, H., Dittrich, P.S., and Blank, L.M. (2010). Chemical and biological single cell analysis. Curr. Opin. Biotechnol. 21, 12–20.
28. Tang, F., Barbacioru, C., Nordman, E., Li, B., Xu, N., Bashkirov, V.I., Lao, K., and Surani, M.A. (2010). RNA-Seq analysis to capture the transcriptome landscape of a single cell. Nat. Protoc. 5, 516–535.
29. Taniguchi, K., Kajiyama, T., and Kambara, H. (2009). Quantitative analysis of gene expression in a single cell by qPCR. Nat. Methods 6, 503–506.
30. Van Gelder, R.N., von Zastrow, M.E., Yool, A., Dement, W.C., Barchas, J.D., and Eberwine, J.H. (1990). Amplified RNA synthesized from limited quantities of heterogeneous cDNA. Proc. Natl. Acad. Sci. USA 87, 1663–1667.
31. Veyer, D.L., Maluquer de Motes, C., Sumner, R.P., Ludwig, L., Johnson, B.F., and Smith, G.L. (2014). Analysis of the antiapoptotic activity of four vaccinia virus proteins demonstrates that B13 is the most potent inhibitor in isolation and during viral infection. J. Gen. Virol. 95, 2757–2768.
32. Wachsmuth, M., Weidemann, T., Mu¨ ller, G., Hoffmann-Rohrer, U.W., Knoch, T.A., Waldeck, W., and Langowski, J. (2003). Analyzing intracellular binding and diffusion with continuous fluorescence photobleaching. Biophys. J. 84, 3353–3363.
33. Wang, D., and Bodovitz, S. (2010). Single cell analysis: the new frontier in ‘omics’. Trends Biotechnol. 28, 281–290.
34. Wasilenko, S.T., Stewart, T.L., Meyers, A.F., and Barry, M. (2003). Vaccinia virus encodes a previously uncharacterized mitochondrial-associated inhibitor of apoptosis. Proc. Natl. Acad. Sci. USA 100, 14345–14350.
35. Weis, K. (2003). Regulating access to the genome: nucleocytoplasmic transport throughout the cell cycle. Cell 112, 441–451.
36. Wu, M., and Singh, A.K. (2012). Single-cell protein analysis. Curr. Opin. Biotechnol.23, 83–88.
37. Zhao, L., Kroenke, C.D., Song, J., Piwnica-Worms, D., Ackerman, J.J., and Neil, J.J. (2008). Intracellular water-specific MR of microbead-adherent cells: the HeLa cell intracellular water exchange lifetime. NMR Biomed. 21, 159–164.