Tools for single-cell kinetic analysis of virus-host interactions

PLoS ONE

Volumn 11, Issue 1, 2016, Pages

  Warrick, Jay W ^a   Timm, Andrea ^a,b   Swick, Adam ^a,c   Yin, John ^a  

^a University of Wisconsin Madison   (United States)

^b OAK RIDGE NATIONAL LABORATORY   (United States)

^c UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GREEN FLUORESCENT PROTEIN; RED FLUORESCENT PROTEIN; DDX58 PROTEIN, HUMAN; DEAD BOX PROTEIN; FLUORESCENT DYE; IFIT2 PROTEIN, HUMAN; INTERFERON; INTERFERON REGULATORY FACTOR 3; INTERFERON REGULATORY FACTOR 7; IRF3 PROTEIN, HUMAN; IRF7 PROTEIN, HUMAN; PHOTOPROTEIN; PROTEIN; RETINOIC ACID INDUCIBLE PROTEIN I;

ARTICLE; CELL ISOLATION; COMPUTER PROGRAM; EXPERIMENTAL STUDY; FLOW CYTOMETRY; FLUORESCENCE MICROSCOPY; GENE EXPRESSION; HOST PATHOGEN INTERACTION; IMAGE ANALYSIS; MICROWELL PLATE; PIPETTE; PROCESS DEVELOPMENT; SINGLE CELL ANALYSIS; VALIDATION PROCESS; VESICULOVIRUS; VIRUS CELL INTERACTION; VIRUS EXAMINATION; VIRUS STRAIN; DEVICES; EPITHELIUM CELL; GENE EXPRESSION REGULATION; GENETICS; HIGH THROUGHPUT SCREENING; HUMAN; KINETICS; MALE; METABOLISM; PATHOLOGY; PROSTATE; REPORTER GENE; SIGNAL TRANSDUCTION; SOFTWARE; TUMOR CELL LINE; VIROLOGY;

CELL LINE, TUMOR; DEAD BOX PROTEIN 58; DEAD-BOX RNA HELICASES; EPITHELIAL CELLS; FLUORESCENT DYES; GENE EXPRESSION REGULATION; GENES, REPORTER; GREEN FLUORESCENT PROTEINS; HIGH-THROUGHPUT SCREENING ASSAYS; HOST-PATHOGEN INTERACTIONS; HUMANS; INTERFERON REGULATORY FACTOR-3; INTERFERON REGULATORY FACTOR-7; INTERFERON TYPE I; KINETICS; LUMINESCENT PROTEINS; MALE; PROSTATE; PROTEINS; SIGNAL TRANSDUCTION; SINGLE-CELL ANALYSIS; SOFTWARE; VESICULOVIRUS;

EID: 84954562995     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0145081     Document Type: Article

References (68)

1. Marjanovic ND, Weinberg RA, Chaffer CL. Cell plasticity and heterogeneity in cancer. Clin Chem. 2013 Jan; 59(1):168-79. doi: 10.1373/clinchem.2012.184655 PMID: 23220226
2. Meacham CE, Morrison SJ. Tumour heterogeneity and cancer cell plasticity. Nature. 2013 Sep; 501(7467):328-37. doi: 10.1038/nature12624 PMID: 24048065
3. Rand U, Rinas M, Schwerk J, Nöhren G, Linnes M, Kröger A, et al. Multi-layered stochasticity and paracrine signal propagation shape the type-I interferon response. Mol Syst Biol. 2012; 8:584. doi: 10.1038/msb.2012.17 PMID: 22617958
4. Tonegawa S. Somatic generation of antibody diversity. Nature. 1983 Apr; 302(5909):575-81. doi: 10.1038/302575a0 PMID: 6300689
5. Abbas AK, Murphy KM, Sher A. Functional diversity of helper T lymphocytes. Nature. 1996 Oct; 383(6603):787-93. doi: 10.1038/383787a0 PMID: 8893001
6. Huang S. Non-genetic heterogeneity of cells in development: more than just noise. Development. 2009 Dec; 136(23):3853-62. doi: 10.1242/dev.035139 PMID: 19906852
7. Zernicka-Goetz M, Huang S. Stochasticity versus determinism in development: a false dichotomy? Nat Rev Genet. 2010 Nov; 11(11):743-4. PMID: 20877326
8. Snijder B, Sacher R, Rämö P, Damm EM, Liberali P, Pelkmans L. Population context determines cellto-cell variability in endocytosis and virus infection. Nature. 2009 Sep; 461(7263):520-3. doi: 10.1038/nature08282 PMID: 19710653
9. Muzzey D, van Oudenaarden A. Quantitative time-lapse fluorescence microscopy in single cells. Annu Rev Cell Dev Biol. 2009; 25:301-27. doi: 10.1146/annurev.cellbio.042308.113408 PMID: 19575655
10. Pelkmans L. Cell Biology. Using cell-to-cell variability-a new era in molecular biology. Science. 2012 Apr; 336(6080):425-6. doi: 10.1126/science.1222161 PMID: 22539709
11. Sisan DR, Halter M, Hubbard JB, Plant AL. Predicting rates of cell state change caused by stochastic fluctuations using a data-driven landscape model. Proc Natl Acad Sci U S A. 2012 Nov; 109(47): 19262-7. doi: 10.1073/pnas.1207544109 PMID: 23115330
12. Patil S, Fribourg M, Ge Y, Batish M, Tyagi S, Hayot F, et al. Single-cell analysis shows that paracrine signaling by first responder cells shapes the interferon-β response to viral infection. Sci Signal. 2015 Feb; 8(363):ra16. doi: 10.1126/scisignal.2005728 PMID: 25670204
13. Rand U, Hillebrand U, Sievers S, Willenberg S, Köster M, Hauser H, et al. Uncoupling of the dynamics of host-pathogen interaction uncovers new mechanisms of viral interferon antagonism at the single-cell level. Nucleic Acids Res. 2014 Jul; 42(13):e109. doi: 10.1093/nar/gku492 PMID: 24895433
14. Shalek AK, Satija R, Shuga J, Trombetta JJ, Gennert D, Lu D, et al. Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature. 2014 Jun; 510(7505):363-9. doi: 10.1038/nature13437 PMID: 24919153
15. Zhao M, Zhang J, Phatnani H, Scheu S, Maniatis T. Stochastic expression of the interferon-β gene. PLoS Biol. 2012 Jan; 10(1):e1001249. doi: 10.1371/journal.pbio.1001249 PMID: 22291574
16. Hensel SC, Rawlings JB, Yin J. Stochastic kinetic modeling of vesicular stomatitis virus intracellular growth. Bull Math Biol. 2009 Oct; 71(7):1671-92. doi: 10.1007/s11538-009-9419-5 PMID: 19459014
17. Srivastava R, You L, Summers J, Yin J. Stochastic vs. deterministic modeling of intracellular viral kinetics. J Theor Biol. 2002 Oct; 218(3):309-21. doi: 10.1006/jtbi.2002.3078 PMID: 12381432
18. Zhu Y, Yongky A, Yin J. Growth of an RNA virus in single cells reveals a broad fitness distribution. Virology. 2009 Mar; 385(1):39-46. doi: 10.1016/j.virol.2008.10.031 PMID: 19070881
19. Timm A, Yin J. Kinetics of virus production from single cells. Virology. 2012 Mar; 424(1):11-7. doi: 10.1016/j.virol.2011.12.005 PMID: 22222212
20. Castellarnau M, Szeto GL, Su HW, Tokatlian T, Love JC, Irvine DJ, et al. Stochastic particle barcoding for single-cell tracking and multiparametric analysis. Small. 2015 Jan; 11(4):489-98. doi: 10.1002/smll. 201401369 PMID: 25180800
21. Di Carlo D, Wu LY, Lee LP. Dynamic single cell culture array. Lab Chip. 2006 Nov; 6(11):1445-9. doi: 10.1039/b605937f PMID: 17066168
22. Jaqaman K, Loerke D, Mettlen M, Kuwata H, Grinstein S, Schmid SL, et al. Robust single-particle tracking in live-cell time-lapse sequences. Nat Methods. 2008 Aug; 5(8):695-702. doi: 10.1038/nmeth.1237 PMID: 18641657
23. Kretzschmar K, Watt FM. Lineage tracing. Cell. 2012 Jan; 148(1-2):33-45. doi: 10.1016/j.cell.2012.01. 002 PMID: 22265400
24. Mali P, Aach J, Lee JH, Levner D, Nip L, Church GM. Barcoding cells using cell-surface programmable DNA-binding domains. Nat Methods. 2013May; 10(5):403-6. doi: 10.1038/nmeth.2407 PMID: 23503053
25. Valero A, Post JN, van Nieuwkasteele JW, Ter Braak PM, Kruijer W, van den Berg A. Gene transfer and protein dynamics in stem cells using single cell electroporation in a microfluidic device. Lab Chip. 2008 Jan; 8(1):62-7. doi: 10.1039/B713420G PMID: 18094762
26. Wheeler AR, Throndset WR, Whelan RJ, Leach AM, Zare RN, Liao YH, et al. Microfluidic device for single-cell analysis. Anal Chem. 2003 Jul; 75(14):3581-6. doi: 10.1021/ac0340758 PMID: 14570213
27. Yamanaka YJ, Szeto GL, Gierahn TM, Forcier TL, Benedict KF, Brefo MSN, et al. Cellular barcodes for efficiently profiling single-cell secretory responses by microengraving. Anal Chem. 2012 Dec; 84(24): 10531-6. doi: 10.1021/ac302264q PMID: 23205933
28. Maška M, Ulman V, Svoboda D, Matula P, Matula P, Ederra C, et al. A benchmark for comparison of cell tracking algorithms. Bioinformatics. 2014 Jun; 30(11):1609-17. doi: 10.1093/bioinformatics/btu080 PMID: 24526711
29. Kan A, Chakravorty R, Bailey J, Leckie C, Markham J, Dowling MR. Automated and semi-automated cell tracking: addressing portability challenges. J Microsc. 2011 Nov; 244(2):194-213. doi: 10.1111/j. 1365-2818.2011.03529.x PMID: 21895653
30. Li K, Miller ED, Chen M, Kanade T, Weiss LE, Campbell PG. Cell population tracking and lineage construction with spatiotemporal context. Med Image Anal. 2008 Oct; 12(5):546-66. doi: 10.1016/j.media. 2008.06.001 PMID: 18656418
31. Swick A, Baltes A, Yin J. Visualizing infection spread: dual-color fluorescent reporting of virus-host interactions. Biotechnol Bioeng. 2014 Jun; 111(6):1200-9. doi: 10.1002/bit.25170 PMID: 24338628
32. Fensterl V, Wetzel JL, Ramachandran S, Ogino T, Stohlman SA, Bergmann CC, et al. Interferoninduced Ifit2/ISG54 protects mice from lethal VSV neuropathogenesis. PLoS Pathog. 2012; 8(5): e1002712. doi: 10.1371/journal.ppat.1002712 PMID: 22615570
33. Müller U, Steinhoff U, Reis LF, Hemmi S, Pavlovic J, Zinkernagel RM, et al. Functional role of type I and type II interferons in antiviral defense. Science. 1994 Jun; 264(5167):1918-21. doi: 10.1126/science. 8009221 PMID: 8009221
34. Ahmed M, Lyles DS. Identification of a consensus mutation in M protein of vesicular stomatitis virus from persistently infected cells that affects inhibition of host-directed gene expression. Virology. 1997 Oct; 237(2):378-88. doi: 10.1006/viro.1997.8808 PMID: 9356348
35. Lyles DS, Rupprecht CE. Fields Virology: Rhabdoviridae. pp 1363-1408, 5th ed. Knipe DM, Howley P, editors. Philadelphia, PA: Lippincott Williams & Wilkins; 2007.
36. Barr JN, Whelan SP, Wertz GW. Role of the intergenic dinucleotide in vesicular stomatitis virus RNA transcription. J Virol. 1997 Mar; 71(3):1794-801. PMID: 9032308
37. Flanagan EB, Zamparo JM, Ball LA, Rodriguez LL, Wertz GW. Rearrangement of the genes of vesicular stomatitis virus eliminates clinical disease in the natural host: new strategy for vaccine development. J Virol. 2001 Jul; 75(13):6107-14. doi: 10.1128/JVI.75.13.6107-6114.2001 PMID: 11390612
38. Sen GC, Sarkar SN. The interferon-stimulated genes: targets of direct signaling by interferons, doublestranded RNA, and viruses. Curr Top Microbiol Immunol. 2007; 316:233-50. PMID: 17969451
39. Carey BL, Ahmed M, Puckett S, Lyles DS. Early steps of the virus replication cycle are inhibited in prostate cancer cells resistant to oncolytic vesicular stomatitis virus. J Virol. 2008 Dec; 82(24):12104-15. doi: 10.1128/JVI.01508-08 PMID: 18829743
40. Yamanaka YJ, Berger CT, Sips M, Cheney PC, Alter G, Love JC. Single-cell analysis of the dynamics and functional outcomes of interactions between human natural killer cells and target cells. Integr Biol (Camb). 2012 Oct; 4(10):1175-84. doi: 10.1039/c2ib20167d
41. Roach KL, King KR, Uygun BE, Kohane IS, Yarmush ML, Toner M. High throughput single cell bioinformatics. Biotechnol Prog. 2009; 25(6):1772-9. doi: 10.1002/btpr.289 PMID: 19830811
42. Ozawa T, Kinoshita K, Kadowaki S, Tajiri K, Kondo S, Honda R, et al. MAC-CCD system: a novel lymphocyte microwell-array chip systemequipped with CCD scanner to generate humanmonoclonal antibodies against influenza virus. Lab Chip. 2009 Jan; 9(1):158-63. doi: 10.1039/B810438G PMID: 19209349
43. Nagai H, Murakami Y, Morita Y, Yokoyama K, Tamiya E. Development of a microchamber array for picoliter PCR. Anal Chem. 2001 Mar; 73(5):1043-7. doi: 10.1021/ac000648u PMID: 11289415
44. Gong Y, Ogunniyi AO, Love JC. Massively parallel detection of gene expression in single cells using subnanolitre wells. Lab Chip. 2010 Sep; 10(18):2334-7. doi: 10.1039/c004847j PMID: 20686711
45. Choi J, Love KR, Gong Y, Gierahn TM, Love JC. Immuno-hybridization chain reaction for enhancing detection of individual cytokine-secreting human peripheral mononuclear cells. Anal Chem. 2011 Sep; 83(17):6890-5. doi: 10.1021/ac2013916 PMID: 21812465
46. Ogunniyi AO, Story CM, Papa E, Guillen E, Love JC. Screening individual hybridomas by microengraving to discover monoclonal antibodies. Nat Protoc. 2009; 4(5):767-82. doi: 10.1038/nprot.2009.40 PMID: 19528952
47. Love KR, Bagh S, Choi J, Love JC. Microtools for single-cell analysis in biopharmaceutical development and manufacturing. Trends Biotechnol. 2013 May; 31(5):280-6. doi: 10.1016/j.tibtech.2013.03. 001 PMID: 23582471
48. Warrick JW, Berthier E. Je'Xperiment (JEX);. Available from: https://github.com/jaywarrick/JEX.
49. Schneider CA, Rasband WS, Eliceiri KW. NIH Image to Image J: 25 years of image analysis. Nat Methods. 2012 Jul; 9(7):671-5. doi: 10.1038/nmeth.2089 PMID: 22930834
50. Rueden C, Schindelin J, Hiner M, DeZonia B, Kamentsky L, Eliceiri K. ImageJ2;. Available from: http://imagej.net.
51. Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, et al. Fiji: an open-source platform for biological-image analysis. Nat Methods. 2012 Jul; 9(7):676-82. doi: 10.1038/nmeth.2019 PMID: 22743772
52. Carpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, et al. CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 2006; 7(10):R100. doi: 10.1186/gb-2006-7-10-r100 PMID: 17076895
53. Berthold MR, Cebron N, Dill F, Gabriel TR, Kötter T, Meinl T, et al. KNIME: The Konstanz Information Miner. In: Studies in Classification, Data Analysis, and Knowledge Organization (GfKL 2007). Springer; 2007. Available from: http://tech.knime.org/community/image-processing.
54. de Chaumont F, Dallongeville S, Chenouard N, Hervé N, Pop S, Provoost T, et al. Icy: an open bioimage informatics platform for extended reproducible research. Nat Methods. 2012 Jul; 9(7):690-6. doi: 10.1038/nmeth.2075 PMID: 22743774
55. Allan C, Burel JM, Moore J, Blackburn C, Linkert M, Loynton S, et al. OMERO: flexible, model-driven data management for experimental biology. Nat Methods. 2012 Mar; 9(3):245-53. doi: 10.1038/nmeth. 1896 PMID: 22373911
56. R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria; 2014. Available from: http://www.R-project.org/.
57. Hornik K, Leisch F, Zeileis A, editors. Rserve: A Fast Way to Provide R Functionality to Applications; 2003. ISSN 1609-395X.
58. Urbanek S. rJava: Low-Level R to Java Interface;. Available from: http://www.rforge.net/rJava/.
59. Eaton JW, Bateman D, Hauberg S. GNU Octave version 3.0.1 manual: a high-level interactive language for numerical computations. CreateSpace Independent Publishing Platform; 2009. ISBN 1441413006. Available from: http://www.gnu.org/software/octave/doc/interpreter.
60. Hansen K. Java Octave;. Available from: https://kenai.com/projects/javaoctave/pages/Home.
61. Lyles DS, McKenzie MO. Activity of vesicular stomatitis virusM protein mutants in cell rounding is correlated with the ability to inhibit host gene expression and is not correlated with virus assembly function. Virology. 1997 Mar; 229(1):77-89. doi: 10.1006/viro.1996.8415 PMID: 9123880
62. Jones TR, Carpenter AE, Lamprecht MR, Moffat J, Silver SJ, Grenier JK, et al. Scoring diverse cellular morphologies in image-based screens with iterative feedback and machine learning. Proc Natl Acad Sci U S A. 2009 Feb; 106(6):1826-31. doi: 10.1073/pnas.0808843106 PMID: 19188593
63. Lindström S, Hammond M, Brismar H, Andersson-Svahn H, Ahmadian A. PCR amplification and genetic analysis in a microwell cell culturing chip. Lab Chip. 2009 Dec; 9(24):3465-71. doi: 10.1039/b912596e PMID: 20024024
64. Love JC, Ronan JL, Grotenbreg GM, van der Veen AG, Ploegh HL. A microengraving method for rapid selection of single cells producing antigen-specific antibodies. Nat Biotechnol. 2006 Jun; 24(6):703-7. doi: 10.1038/nbt1210 PMID: 16699501
65. Haselgrübler T, Haider M, Ji B, Juhasz K, Sonnleitner A, Balogi Z, et al. High-throughput, multiparameter analysis of single cells. Anal Bioanal Chem. 2013 Dec;. PMID: 24292433
66. Rettig JR, Folch A. Large-scale single-cell trapping and imaging using microwell arrays. Anal Chem. 2005 Sep; 77(17):5628-34. doi: 10.1021/ac0505977 PMID: 16131075
67. Matlin KS, Reggio H, Helenius A, Simons K. Pathway of vesicular stomatitis virus entry leading to infection. J Mol Biol. 1982 Apr; 156(3):609-31. doi: 10.1016/0022-2836(82)90269-8 PMID: 6288961
68. Akpinar F, Timm A, Yin J. High-throughput single-cell kinetics of virus infections in the presence of defective interfering particles. Journal of Virology. 2015;(accepted). doi: 10.1128/JVI.02190-15 PMID: 26608322