Single cell cytometry of protein function in RNAi treated cells and in native populations

BMC Cell Biology

Steven A Haney³  Andrew Hill⁴  Jing Pan¹  Jing Zhang¹  Peter LaPan² 

[1] Department of Biological Technologies, Oncology Research, Wyeth Research, 87 Cambridge Park Drive, Cambridge, MA 02140, USA;Department of Biological Technologies, Section of Biologic Research, Wyeth Research, 87 Cambridge Park Drive, Cambridge, MA 02140, USA;Pfizer Research Technology Center, 620 Memorial Drive, Cambridge, MA 02139;Department of Biological Technologies, Bioinformatics, Wyeth Research, 87 Cambridge Park Drive, Cambridge, MA 02140, USA

Others  :  1086995
DOI  :  10.1186/1471-2121-9-43

 received in 2007-12-14, accepted in 2008-08-01,  发布年份 2008

【 摘 要 】

Background

High Content Screening has been shown to improve results of RNAi and other perturbations, however significant intra-sample heterogeneity is common and can complicate some analyses. Single cell cytometry can extract important information from subpopulations within these samples. Such approaches are important for immune cells analyzed by flow cytometry, but have not been broadly available for adherent cells that are critical to the study of solid-tumor cancers and other disease models.

Results

We have directly quantitated the effect of resolving RNAi treatments at the single cell level in experimental systems for both exogenous and endogenous targets. Analyzing the effect of an siRNA that targets GFP at the single cell level permits a stronger measure of the absolute function of the siRNA by gating to eliminate background levels of GFP intensities. Extending these methods to endogenous proteins, we have shown that well-level results of the knockdown of PTEN results in an increase in phospho-S6 levels, but at the single cell level, the correlation reveals the role of other inputs into the pathway. In a third example, reduction of STAT3 levels by siRNA causes an accumulation of cells in the G1 phase of the cell cycle, but does not induce apoptosis or necrosis when compared to control cells that express the same levels of STAT3. In a final example, the effect of reduced p53 levels on increased adriamycin sensitivity for colon carcinoma cells was demonstrated at the whole-well level using siRNA knockdown and in control and untreated cells at the single cell level.

Conclusion

We find that single cell analysis methods are generally applicable to a wide range of experiments in adherent cells using technology that is becoming increasingly available to most laboratories. It is well-suited to emerging models of signaling dysfunction, such as oncogene addition and oncogenic shock. Single cell cytometry can demonstrate effects on cell function for protein levels that differ by as little as 20%. Biological differences that result from changes in protein level or pathway activation state can be modulated directly by RNAi treatment or extracted from the natural variability intrinsic to cells grown under normal culture conditions.

【 授权许可】

   
2008 LaPan et al; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

【 参考文献 】

• [1]Hannon GJ: RNAi: A Guide to Gene Silencing. 1st edition. Cold Spring Harbor, NY, USA , Cold Spring Harbor Press; 2003:436.
• [2]Appasani K: RNA Interference Technology: From Basic Science to Drug Development. 1st edition. Edited by Appasani K. Cambridge, UK , Cambridge University Press; 2005:510.
• [3]Aza-Blanc P, Cooper CL, Wagner K, Batalov S, Deveraux QL, Cooke MP: Identification of modulators of TRAIL-induced apoptosis via RNAi-based phenotypic screening. Molecular Cell 2003, 12:627-637.
• [4]Berns K, Hijmans EM, Mullenders J, Brummelkamp TR, Velds A, Heimerikx M, Kerkhoven RM, Madiredjo M, Nijkamp W, Weigelt B, Agami R, Ge W, Cavet G, Linsley PS, Beijersbergen RL, Bernards R: A large-scale RNAi screen in human cells identifies new components of the p53 pathway. Nature 2004, 428:431-437.
• [5]Downward J: Use of RNA interference libraries to investigate oncogenic signalling in mammalian cells. Oncogene 2004, 23:8376-8383.
• [6]Willingham AT, Deveraux QL, Hampton GM, Aza-Blanc P: RNAi and HTS: exploring cancer by systematic loss-of-function. Oncogene 2004, 23:8392-8400.
• [7]Wheeler DB, Bailey SN, Guertin DA, Carpenter AE, Higgins CO, Sabatini DM: RNAi living-cell microarrays for loss-of-function screens in Drosophila melanogaster cells. Nat Methods 2004, 1:127-132.
• [8]Sonnichsen B, Koski LB, Walsh A, Marschall P, Neumann B, Brehm M, Alleaume AM, Artelt J, Bettencourt P, Cassin E, Hewitson M, Holz C, Khan M, Lazik S, Martin C, Nitzsche B, Ruer M, Stamford J, Winzi M, Heinkel R, Roder M, Finell J, Hantsch H, Jones SJ, Jones M, Piano F, Gunsalus KC, Oegema K, Gonczy P, Coulson A, Hyman AA, Echeverri CJ: Full-genome RNAi profiling of early embryogenesis in Caenorhabditis elegans. Nature 2005, 434:462-469.
• [9]Whitehurst AW, Bodemann BO, Cardenas J, Ferguson D, Girard L, Peyton M, Minna JD, Michnoff C, Hao W, Roth MG, Xie XJ, White MA: Synthetic lethal screen identification of chemosensitizer loci in cancer cells. Nature 2007, 446:815-819.
• [10]Swanton C, Marani M, Pardo O, Warne PH, Kelly G, Sahai E, Elustondo F, Chang J, Temple J, Ahmed AA, Brenton JD, Downward J, Nicke B: Regulators of mitotic arrest and ceramide metabolism are determinants of sensitivity to Paclitaxel and other chemotherapeutic drugs. Cancer Cell 2007, 11:498-512.
• [11]Elbashir SM, Harborth J, Weber K, Tuschl T: Analysis of gene function in somatic mammalian cells using small interfering RNAs. Methods 2002, 26(2):199-213.
• [12]Huppi K, Martin SE, Caplen NJ: Defining and Assaying RNAi in Mammalian Cells. Molecular Cell 2005, 17:1-10.
• [13]Fitzgerald K: RNAi versus small molecules: Different mechanisms and specificities can lead to different outcomes. Current Opinion in Drug Discovery & Development 2005, 8:557-566.
• [14]Jackson AL, Linsley PS: Noise amidst the silence: off-target effects of siRNAs? Trends in Genetics 2004, 20:521-524.
• [15]Echeverri CJ, Perrimon N: High-throughput RNAi screening in cultured cells: a user's guide. Nature Reviews Genetics 2006, 7:373-384.
• [16]Haney SA: RNAi and high-content screening in target identification and validation. IDrugs 2006, 8(12):997-1001.
• [17]Comley J: High content screening-Emerging importance of novel reagents/probes and pathway analysis. Drug Discovery World 2005, 6:31-54.
• [18]Zhou X, Cao X, Perlman Z, Wong ST: A computerized cellular imaging system for high content analysis in Monastrol suppressor screens. J Biomed Inform 2005, 39:115-125.
• [19]Carpenter AE, Jones TE, Wheeler DB, Lamprecht M, Clarke C, Friman O, Guertin DA, Kang IH, Ma S, Lindquist R, Chang JH, Moffat J, Golland P, Sabatini DM: CellProfiler: open-source, versatile software for high throughput cell image analysis. Genome Biology 2006, 7:R100.
• [20]Tencza SB, Sipe MA: Detection and classification of threat agents via high-content assays of mammalian cells. J Appl Toxicol 2004, 24(5):371-377.
• [21]Perfetto SP, Chattopadhyay PK, Roederer M: Seventeen-colour flow cytometry: unravelling the immune system. Nature Reviews Immunology 2004, 4:648-655.
• [22]Lang P, Yeow K, Nichols A, Sheer A: Cellular imaging in drug discovery. Nature Reviews Drug Discovery 2006, 5:343-356.
• [23]Krutzik PO, Irish JM, Nolan GP, Perez OD: Analysis of protein phosphorylation and cellular signaling events by flow cytometry: techniques and clinical applications. Clinical Immunology 2004, 110:206-221.
• [24]Sachs K, Perez O, Pe'er D, Lauffenburger DA, Nolan GP: Causal protein-signaling networks derived from multiparameter single-cell data. Science 2005, 308:523-529.
• [25]Irish JM, Hovland R, Krutzik PO, Perez OD, Bruserud O, Gjertsen BT, Nolan GP: Single cell profiling of potentiated phospho-protein networks in cancer cells. Cell 2004, 118:217-228.
• [26]Stitz J, Krutzik PO, Nolan GP: Screening of retroviral cDNA libraries for factors involved in protein phosphorylation in signaling cascades. Nucleic Acids Research 2005, 33:e39.
• [27]Giuliano KA, Chen YT, Taylor DL: High-content screening with siRNA optimizes a cell biological approach to drug discovery: defining the role of P53 activation in the cellular response to anticancer drugs. J Biomol Screen 2004, 9:557-568.
• [28]Loo LH, Wu LF, Altschuler SJ: Image-based multivariate profiling of drug responses from single cells. Nature Methods 2007, 4:445-453.
• [29]Perlman ZE, Slack MD, Feng Y, Mitchison TJ, Wu LF, Altschuler SJ: Multidimensional drug profiling by automated microscopy. Science 2004, 306:1194-1198.
• [30]de Jager W, te Velthuis H, Prakken BJ, Kuis W, Rijkers GT: Simultaneous detection of 15 human cytokines in a single sample of stimulated peripheral blood mononuclear cells. Clin Diagn Lab Immunol 2003, 10(1):133-139.
• [31]Janes KA, Albeck JG, Gaudet S, Sorger PK, Lauffenburger DA, Yaffe MB: A systems model of signaling identifies a molecular basis set for cytokine-induced apoptosis. Science 2005, 310:1646-1653.
• [32]Natarajan M, Lin KM, Hsueh RC, Sternweis PC, Ranganathan R: A global analysis of cross-talk in a mammalian cellular signalling network. Nature Cell Biology 2006, 8:571-580.
• [33]Caplen NJ, Fleenor J, Fire A, Morgan RA: dsRNA-mediated gene silencing in cultured Drosophila cells: a tissue culture model for the analysis of RNA interference. Gene 2000, 252:95-105.
• [34]Liu J, Valencia-Sanchez MA, Hannon GJ, Parker R: MicroRNA-dependent localization of targeted mRNAs to mammalian P-bodies. Nature Cell Biology 2005, 7:719-723.
• [35]Sen GL, Blau HM: Argonaute 2/RISC resides in sites of mammalian mRNA decay known as cytoplasmic bodies. Nature Cell Biology 2005, 7:633-636.
• [36]Eulalio A, Behm-Ansmant I, Schweizer D, Izaurralde E: P-Body Formation Is a Consequence, Not the Cause, of RNA-Mediated Gene Silencing. Molecular and Cellular Biology 2007, 27:3970-3981.
• [37]Chiu YL, Ali A, Chu C, Cao H, Rana TM: Visualizing a correlation between siRNA localization, cellular uptake, and RNAi in living cells. Chem Biol 2004, 11:1165-1175.
• [38]Hung CF, Lu KC, Cheng TL, Wu RH, Huang LY, Teng CF, Chang WT: A novel siRNA validation system for functional screening and identification of effective RNAi probes in mammalian cells. Biochem Biophys Res Commun 2006, 346(3):707-720.
• [39]Cao M, Ren H, Pan X, Pan W, Qi ZT: Inhibition of EGFP expression by siRNA in EGFP-stably expressing Huh-7 cells. Journal of Virological Methods 2004, 119:189-194.
• [40]Choi I, Cho BR, Kim D, Miyagawa S, Kubo T, Kim JY, Park CG, Hwang WS, Lee JS, Ahn C: Choice of the adequate detection time for the accurate evaluation of the efficiency of siRNA-induced gene silencing. Journal of Biotechnology 2005, 120:251-261.
• [41]Zhang M, Bai CX, Zhang X, Chen J, Mao L, Gao L: Downregulation enhanced green fluorescence protein gene expression by RNA interference in mammalian cells. RNA Biology 2004, 1:74-77.
• [42]Halter M, Tona A, Bhadriraju K, Plant AL, Elliott JT: Automated live cell imaging of green fluorescent protein degradation in individual fibroblasts. Cytometry A 2007, 71:827-834.
• [43]Swenson ES, Price JG, Brazelton T, Krause DS: Limitations of green fluorescent protein as a cell lineage marker. Stem Cells 2007, 2007:2593-2600.
• [44]Stampfer MR, Bodnar A, Garbe J, Wong M, Pan A, Villeponteau B, Yaswen P: Gradual phenotypic conversion associated with immortalization of cultured human mammary epithelial cells. Mol Biol Cell 1997, 8(12):2391-2405.
• [45]Romanov S, Kozakiewicz K, Holst C, Stampfer MR, Haupt LM, Tlsty TD: Normal human mammary epithelial cells spontaneously escape senescence and aquire genomic changes. Nature 2001, 409:633-637.
• [46]Li Y, Pan J, Li J, Lee JH, Tunkey C, Saraf K, Garbe JC, M.Z. W, Jelinsky SA, Stampfer MR, Haney SA: Transcriptional Changes Associated with Breast Cancer Occur as Normal Human Mammary Epithelial Cells Overcome Senescence Barriers and Become Immortalized. Molecular Cancer 2007, 6:7.
• [47]Brenner AJ, Stampfer MR, Aldaz CM: Increased p16 expression with first senescence arrest in human mammary epithelial cells and extended growth capacity with p16 inactivation. Oncogene 1998, 17:199-205.
• [48]Kiyono T, Foster SA, Koop JI, McDougall JK, Galloway DA, Klingelhutz AJ: Both Rb/p16INK4a inactivation and telomerase activity are required to immortalize human epithelial cells. Nature 1998, 396:84-88.
• [49]Galanis E, Buckner JC, Maurer MJ, Kreisberg JI, Ballman K, Boni J, Peralba JM, Jenkins RB, Dakhil SR, Morton RF, Jaeckle KA, Scheithauer BW, Dancey J, Hidalgo M, Walsh DJ, Group. NCCT: Phase II trial of temsirolimus (CCI-779) in recurrent glioblastoma multiforme: a North Central Cancer Treatment Group Study. Journal of Clinical Oncology 2005, 23:5294-5304.
• [50]Witzig TE, Geyer SM, Ghobrial I, Inwards DJ, Fonseca R, Kurtin P, Ansell SM, Luyun R, Flynn PJ, Morton RF, Dakhil SR, Gross H, Kaufmann SH: Phase II trial of single-agent temsirolimus (CCI-779) for relapsed mantle cell lymphoma. Journal of Clinical Oncology 2005, 23:5347-5356.
• [51]Luo J, Manning BD, Cantley LC: Targeting the PI3K-Akt pathway in human cancer: rationale and promise. Cancer Cell 2003, 4:257-262.
• [52]Sansal I, Sellers WR: The biology and clinical relevance of the PTEN tumor suppressor pathway. Journal of Clinical Oncology 2004, 22:2954-2963.
• [53]Sarbassov DD, Guertin DA, Ali SM, Sabatini DM: Phosphorylation and regulation of Akt.PKB by the rictor-mTor complex. Science 2005, 307:1098-1101.
• [54]Manning BD: Balencing Akt with S6K: implications for both metabolic diseases and tumorogenesis. Journal of Cell Biology 2004, 167:399-403.
• [55]Hara K, Yonezawa K, Weng QP, Kozlowski MT, Belham C, Avruch J: Amino acid sufficiency and mTOR regulate p70 S6 kinase and eIF-4E BP1 through a common effector mechanism. Journal of Biological Chemistry 1998, 273:14484-14494.
• [56]Haney SA, Zhang J, Pan J, LaPan P: HCS in cellular oncology and tumor biology. In High Content Screening: Science, Techniques and Applications. Edited by Haney SA. Hoboken, NJ , John Wiley Press; 2008:113-143.
• [57]Chow S, Minden MD, Hedley DW: Constitutive phosphorylation of the S6 ribosomal protein via mTOR and ERK signaling in the peripheral blasts of acute leukemia patients. Experimental Hematology 2006, 34:1183-1191.
• [58]Lerma E, Peiro G, Ramón T, Fernandez S, Martinez D, Pons C, Muñoz F, Sabate JM, Alonso C, Ojeda B, Prat J, Barnadas A: Immunohistochemical heterogeneity of breast carcinomas negative for estrogen receptors, progesterone receptors and Her2/neu (basal-like breast carcinomas). Modern Pathology 2007, 20:1200-1207.
• [59]Giuliano KA, Chen YT, Taylor DL: High-Content Screening with siRNA Optimizes a Cell Biological Approach to Drug Discovery: Defining the Role of P53 Activation in the Cellular Response to Anticancer Drugs. J Biomol Screen 2004, 9:557-568.
• [60]Konnikova L, Kotecki M, Kruger MM, Cochran BH: Knockdown of STAT3 expression by RNAi induces apoptosis in astrocytoma cells. BMC Cancer 2003, 3:23.
• [61]Lee SO, Lou W, Qureshi KM, Mehraein-Ghomi F, Trump DL, Gao AC: RNA interference targeting Stat3 inhibits growth and induces apoptosis of human prostate cancer cells. Prostate 2004, 60:303-309.
• [62]Ling X, Arlinghaus RB: Knockdown of STAT3 expression by RNA interference inhibits the induction of breast tumors in immunocompetent mice. Cancer Research 2005, 65:2532-2536.
• [63]Weinstein IB, Joe AK: Mechanisms of disease: Oncogene addiction-a rationale for molecular targeting in cancer therapy. Nature Clinical Practice Oncology 2006, 3:448-457.
• [64]Sharma SV, Gajowniczek P, Way I, Lee D, Jiang J, Yuza Y, Classon M, Haber DA, Settleman J: A common signaling cascade may underlie "addiction" to the Src, BCR-ABL, and EGF receptor oncogenes. Cancer Cell 2006, 10:425-435.
• [65]Grove LE, Ghosh RN: Quantitative characterization of mitosis-blocked tetraploid cells using high content analysis. Assay Drug Dev Technol 2006, 4(4):421-442.
• [66]Bakal C, Aach J, Church G, Perrimon N: Quantitative morphological signatures define local signaling networks regulating cell morphology. Science 2007, 316:1753-1756.
• [67]Giuliano KA: High-Content Profiling of Drug-Drug Interactions: Cellular Targets Involved in the Modulation of Microtubule Drug Action by the Antifungal Ketoconazole. Journal of Biomolecular Screening 2003, 8(2):125-135.
• [68]Perlman ZE, Slack MD, Feng Y, Mitchison TJ, Wu LF, Altschuler SJ: Automatic identification of subcellular phenotypes on human cell arrays. Science 2004, 306:1194-1198.
• [69]Hill A, Li Y, LaPan P, Haney S: Analysis of multiparametric high-content data. In High Content Screening: Science, Techinques and Applications. Edited by Haney S. Hoboken, NJ , Wiley Interscience; 2008:329-353.
• [70]Eggert US, Kiger AA, Richter C, Perlman ZE, Perrimon N, Mitchison TJ, Field CM: Parallel chemical genetic and genome-wide RNAi screens identify cytokinesis inhibitors and targets. PLoS Biology 2004., 2(e379)
• [71]Mukhopadhyay UK, Senderowicz AM, Ferbeyre G: RNA silencing of checkpoint regulators sensitizes p53-defective prostate cancer cells to chemotherapy while sparing normal cells. Cancer Research 2005, 65:2872-2881.
• [72]Burma S, Chen BP, Murphy M, Kurimasa A, Chen DJ: ATM phosphorylates histone H2AX in response to DNA double-strand breaks. Journal of Biological Chemistry 2001, 276:42462-42467.
• [73]Kang J, Ferguson D, Song H, Bassing C, Eckersdorff M, Alt FW, Xu Y: Functional interaction of H2AX, NBS1, and p53 in ATM-dependent DNA damage responses and tumor suppression. Mol Cell Biol 2005, 25(2):661-670.
• [74]Haney S: Increasing the robustness and validity of RNAi screening data. Pharmacogenomics 2007, 8:1037-1049.
• [75]Zhang XD, Ferrer M, Espeseth AS, Marine SD, Stec EM, Crackower MA, Holder DJ, Heyse JF, Strulovici B: The Use of Strictly Standardized Mean Difference for Hit Selection in Primary RNA Interference High-Throughput Screening Experiments. Journal of Biomolecular Screening 2007, 12:497-509.
• [76]Jackson AL, Burchard J, Schelter J, Chau BN, Cleary M, Lim L, Linsley PS: Widespread siRNA "off-target" transcript silencing mediated by seed region sequence complementarity. RNA 2006, 12:1-9.
• [77]Jackson AL, Bartz SR, Schelter J, Kobayashi SV, Burchard J, Mao M, Li B, Cavet G, Linsley PS: Expression profiling reveals off-target gene regulation by RNAi. Nat Biotechnol 2003, 21:635-637.
• [78]Birmingham A, Anderson EM, Reynolds A, Ilsley-Tyree D, Leake D, Fedorov Y, Baskerville S, Maksimova E, Robinson K, Karpilow J, Marshall WS, Khvorova A: 3' UTR seed matches, but not overall identity, are associated with RNAi off-targets. Nature Methods 2006, 3:199-204.
• [79]MacKeigan JP, Murphy LO, Blenis J: Sensitized RNAi screen of human kinases and phosphatases identifies new regulators of apoptosis and chemoresistance. Nature Cell Biology 2005, 7:591-600.
• [80]Hsieh AC, Bo R, Manola J, Vazquez F, Bare O, Khvorova A, Scaringe S, Sellers WR: A library of siRNA duplexes targeting the phosphoinositide 3-kinase pathway: determinants of gene silencing for use in cell-based screens. Nucleic Acids Research 2004, 32:893-901.
• [81]Echeverri CJ, Beachy PA, Baum B, Boutros M, Buchholz F, Chanda SK, Downward J, Ellenberg J, Fraser AG, Hacohen N, Hahn WC, Jackson AL, Kiger A, Linsley PS, Lum L, Ma Y, Mathey-Prevot B, Root DE, Sabatini DM, Taipale J, Perrimon N, Bernards R: Minimizing the risk of reporting false positives in large-scale RNAi screens. Nature Methods 2006, 3:777-779.
• [82]Haney S: Increasing the robustness and validity of RNAi screening data. Pharmacogenomics 2007, 8:1037-1049.
• [83]Kittler R, Putz G, Pelletier L, Poser I, Heninger AK, Drechsel D, Fischer S, Konstantinova I, Habermann B, Grabner H, Yaspo ML, Himmelbauer H, Korn B, Neugebauer K, Pisabarro MT, Buchholz F: An endoribonuclease-prepared siRNA screen in human cells identifies genes essential for cell division. Nature 2004, 432:1036-1040.
• [84]Mousses S, Caplen NJ, Cornelison R, Weaver D, Basik M, Hautaniemi S, Elkahloun AG, Lotufo RA, Choudary A, Dougherty ER, Suh E, Kallioniemi O: RNAi microarray analysis in cultured mammalian cells. Genome Research 2003, 13:2341-2347.
• [85]Neumann B, Held M, Liebel U, Erfle H, Rogers P, Pepperkok R, Ellenberg J: High-throughput RNAi screening by time-lapse imaging of live human cells. Nature Methods 2006, 3:385-390.
• [86]Sabatini DM: mTOR and cancer: insights into a complex relationship. Nature Reviews Cancer 2006, 6:729-734.
• [87]Sarbassov DD, Ali SM, Sabatini DM: Growing roles for the mTOR pathway. Current Opinion in Cell Biology 2005, 17:596-603.
• [88]Janes KA, Gaudet S, Albeck JG, Nielsen UB, Lauffenburger DA, Sorger PK: The response of human epithelial cells to TNF involves an inducible autocrine cascade. Cell 2006, 124:1225-1239.
• [89]Hornberg JJ, Bruggeman FJ, Westerhoff HV, Lankelma J: Cancer: a systems biology disease. Biosystems 2006, 83:81-90.
• [90]Cully M, You H, Levine AJ, Mak TW: PTEN mutations: the PI3K pathway as an integrator of multiple inputs during tumorigenesis. Nat Rev Cancer 2006, 6(3):184-192.