Quantitative in vivo microscopy: the return from the 'omics'

Current Opinion in Biotechnology

Volumn 17, Issue 5, 2006, Pages 501-510

  Fernández González, Rodrigo ^a,b   Muñoz Barrutia, Arrate ^c   Barcellos Hoff, Mary Helen ^a   Ortiz de Solorzano, Carlos ^c  

^a LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF NAVARRA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

CELL FUNCTIONS; GENE EXPRESSION; GFP-TAGGED PROTEINS; TEMPORAL CONTEXTS;

BIOCHEMICAL ENGINEERING; BIOTECHNOLOGY; CELLS; DRUG PRODUCTS; IMAGE ANALYSIS; IMAGE SEGMENTATION; MICROSCOPIC EXAMINATION; PROTEINS;

GENES;

GREEN FLUORESCENT PROTEIN; HYBRID PROTEIN;

ALGORITHM; AMINO TERMINAL SEQUENCE; AUTOMATION; BACTERIUM; BIOLUMINESCENCE; CARBOXY TERMINAL SEQUENCE; CELL FUNCTION; COMPUTER; CONCENTRATION (PARAMETERS); DNA SEQUENCE; GENE EXPRESSION; GENETIC TRANSFECTION; IMAGE ANALYSIS; IMMUNOBLOTTING; IN VIVO STUDY; INTERFEROMETRY; JELLYFISH; KARYOTYPE; MICROSCOPY; MORPHOLOGY; NEMATODE; NONHUMAN; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROMOTER REGION; QUANTITATIVE ANALYSIS; REVIEW; VIRUS;

ANIMALS; BIOLOGY; GREEN FLUORESCENT PROTEINS; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; METABOLIC NETWORKS AND PATHWAYS; MICROSCOPY, FLUORESCENCE;

EID: 33748978371     PISSN: 09581669     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.copbio.2006.07.005     Document Type: Review

References (75)

1. Venter J.C., Adams M.D., Myers E.W., Li P.W., Mural R.J., Sutton G.G., Smith H.O., Yandell M., Evans C.A., Holt R.A., et al. The sequence of the human genome. Science 291 (2001) 1304-1351
2. McPherson J.D., Marra M., Hillier L., Waterston R.H., Chinwalla A., Wallis J., Sekhon M., Wylie K., Mardis E.R., Wilson R.K., et al. A physical map of the human genome. Nature 409 (2001) 934-941
3. Caron H., van Schaik B., van der Mee M., Baas F., Riggins G., van Sluis P., Hermus M.C., van Asperen R., Boon K., Voute P.A., et al. The human transcriptome map: clustering of highly expressed genes in chromosomal domains. Science 291 (2001) 1289-1292
4. Strausberg R.L., and Riggins G.J. Navigating the human transcriptome. Proc Natl Acad Sci USA 98 (2001) 11837-11838
5. Walter G., Bussow K., Lueking A., and Glokler J. High-throughput protein arrays: prospects for molecular diagnostics. Trends Mol Med 8 (2002) 250-253
6. Figeys D. Functional proteomics: mapping protein-protein interactions and pathways. Curr Opin Mol Ther 4 (2002) 210-215
7. Cahalan M.D., Parker I., Wei S.H., and Miller M.J. Two-photon tissue imaging: seeing the immune system in a fresh light. Nat Rev Immunol 2 (2002) 872-880
8. Mempel T.R., Scimone M.L., Mora J.R., and von Andrian U.H. In vivo imaging of leukocyte trafficking in blood vessels and tissues. Curr Opin Immunol 16 (2004) 406-417
9. Shimizu N., Kamezaki F., and Shigematsu S. Tracking of microinjected DNA in live cells reveals the intracellular behavior and elimination of extrachromosomal genetic material. Nucleic Acids Res 33 (2005) 6296-6307
10. Glotzer J.B., Saffrich R., Glotzer M., and Ephrussi A. Cytoplasmic flows localize injected oskar RNA in Drosophila oocytes. Curr Biol 7 (1997) 326-337
11. Shan J., Munro T.P., Barbarese E., Carson J.H., and Smith R. A molecular mechanism for mRNA trafficking in neuronal dendrites. J Neurosci 23 (2003) 8859-8866
12. Dickinson M.E., Murray B.A., Haynes S.M., Waters C.W., and Longmuir K.J. Using electroporation and lipid-mediated transfection of GFP-expressing plasmids to label embryonic avian cells for vital confocal and two-photon microscopy. Differentiation 70 (2002) 172-180
13. Maletic-Savatic M., Malinow R., and Svoboda K. Rapid dendritic morphogenesis in CA1 hippocampal dendrites induced by synaptic activity. Science 283 (1999) 1923-1927
14. Lorenz M.R., Holzapfel V., Musyanovych A., Nothelfer K., Walther P., Frank H., Landfester K., Schrezenmeier H., and Mailander V. Uptake of functionalized, fluorescent-labeled polymeric particles in different cell lines and stem cells. Biomaterials 27 (2006) 2820-2828
15. Molenaar C., Wiesmeijer K., Verwoerd N.P., Khazen S., Eils R., Tanke H.J., and Dirks R.W. Visualizing telomere dynamics in living mammalian cells using PNA probes. EMBO J 22 (2003) 6631-6641
16. Win K.Y., and Feng S.S. Effects of particle size and surface coating on cellular uptake of polymeric nanoparticles for oral delivery of anticancer drugs. Biomaterials 26 (2005) 2713-2722
17. Lin R., Shi Ng L., and Wang C.H. In vitro study of anticancer drug doxorubicin in PLGA-based microparticles. Biomaterials 26 (2005) 4476-4485
18. Shimomura O., Johnson F.H., and Saiga Y. Extraction, purification and properties of aequorin, a bioluminescent protein from the luminous hydromedusan, Aequorea. J Cell Comp Physiol 59 (1962) 223-239
19. Prasher D.C., Eckenrode V.K., Ward W.W., Prendergast F.G., and Cormier M.J. Primary structure of the Aequorea victoria green fluorescent protein. Gene 111 (1992) 229-233
20. Chalfie M., Tu Y., Euskirchen G., Ward W.W., and Prasher D.C. Green fluorescent protein as a marker for gene expression. Science 263 (1994) 802-805
21. Shaner N.C., Campbell R.E., Steinbach P.A., Giepmans B.N., Palmer A.E., and Tsien R.Y. Improved monomeric red, orange and yellow fluorescent proteins derived from Discosoma sp. red fluorescent protein. Nat Biotechnol 22 (2004) 1567-1572
22. Karasawa S., Araki T., Nagai T., Mizuno H., and Miyawaki A. Cyan-emitting and orange-emitting fluorescent proteins as a donor/acceptor pair for fluorescence resonance energy transfer. Biochem J 381 (2004) 307-312
23. Rekas A., Alattia J.R., Nagai T., Miyawaki A., and Ikura M. Crystal structure of venus, a yellow fluorescent protein with improved maturation and reduced environmental sensitivity. J Biol Chem 277 (2002) 50573-50578
24. Nagai T., Ibata K., Park E.S., Kubota M., Mikoshiba K., and Miyawaki A. A variant of yellow fluorescent protein with fast and efficient maturation for cell-biological applications. Nat Biotechnol 20 (2002) 87-90
25. Wiedenmann J., Ivanchenko S., Oswald F., Schmitt F., Rocker C., Salih A., Spindler K.D., and Nienhaus G.U. EosFP, a fluorescent marker protein with UV-inducible green-to-red fluorescence conversion. Proc Natl Acad Sci USA 101 (2004) 15905-15910
26. Wiedenmann J., Vallone B., Renzi F., Nienhaus K., Ivanchenko S., Rocker C., and Nienhaus G.U. Red fluorescent protein eqFP611 and its genetically engineered dimeric variants. J Biomed Opt 10 (2005) 14003
27. Zapata-Hommer O., and Griesbeck O. Efficiently folding and circularly permuted variants of the Sapphire mutant of GFP. BMC Biotechnol 3 (2003) 5
28. Shaner N.C., Steinbach P.A., and Tsien R.Y. A guide to choosing fluorescent proteins. Nat Methods 2 (2005) 905-909. Essential and exhaustive review of the biochemical and optical properties of most available GFP-like fluorescent proteins. The authors advance their recommendations on the appropriate fluorescent protein per spectral class as well as the optimum filter sets for both single and multiple labeling experiments.
29. Zimmermann T. Spectral imaging and linear unmixing in light microscopy. Adv Biochem Eng Biotechnol 95 (2005) 245-265. A useful review of the microscope techniques available for spectral imaging and the theory of linear unmixing. Possible limitations and approaches for image optimization are discussed to help realize the full potential of this novel method. Biological applications that can be improved by spectral imaging and linear unmixing are presented.
30. Liyanage M., Coleman A., du Manoir S., Veldman T., McCormack S., Dickson R.B., Barlow C., Wynshaw-Boris A., Janz S., Wienberg J., et al. Multicolour spectral karyotyping of mouse chromosomes. Nat Genet 14 (1996) 312-315
31. Schrock E., du Manoir S., Veldman T., Schoell B., Wienberg J., Ferguson-Smith M.A., Ning Y., Ledbetter D.H., Bar-Am I., Soenksen D., et al. Multicolor spectral karyotyping of human chromosomes. Science 273 (1996) 494-497
32. Tsurui H., Nishimura H., Hattori S., Hirose S., Okumura K., and Shirai T. Seven-color fluorescence imaging of tissue samples based on Fourier spectroscopy and singular value decomposition. J Histochem Cytochem 48 (2000) 653-662
33. Wachman E.S., Niu W., and Farkas D.L. AOTF microscope for imaging with increased speed and spectral versatility. Biophys J 73 (1997) 1215-1222
34. Lansford R., Bearman G., and Fraser S.E. Resolution of multiple green fluorescent protein color variants and dyes using two-photon microscopy and imaging spectroscopy. J Biomed Opt 6 (2001) 311-318
35. Dickinson M.E., Bearman G., Tille S., Lansford R., and Fraser S.E. Multi-spectral imaging and linear unmixing add a whole new dimension to laser scanning fluorescence microscopy. Biotechniques 31 (2001) 1272-1278
36. Keshava N., and Mustard J.F. Spectral unmixing. IEEE Signal Proc Mag 19 (2002) 44-56
37. Zimmermann T., Rietdorf J., and Pepperkok R. Spectral imaging and its applications in live cell microscopy. FEBS Lett 546 (2003) 87-92
38. Hutter H. Five-colour in vivo imaging of neurons in Caenorhabditis elegans. J Microsc 215 (2004) 213-218
39. Teddy J.M., Lansford R., and Kulesa P.M. Four-color, 4-D time-lapse confocal imaging of chick embryos. Biotechniques 39 (2005) 703-710
40. Van Munster E.B., Kremers G.J., Adjobo-Hermans M.J., and Gadella Jr. T.W. Fluorescence resonance energy transfer (FRET) measurement by gradual acceptor photobleaching. J Microsc 218 (2005) 253-262. Reports the delivery of multiple (up to four), multicolour fluorescent protein constructs and uses four-dimensional, multispectral time-lapse confocal imaging of cell movements in living chick embryos.
41. Zimmermann T., Rietdorf J., Girod A., Georget V., and Pepperkok R. Spectral imaging and linear un-mixing enables improved FRET efficiency with a novel GFP2-YFP FRET pair. FEBS Lett 531 (2002) 245-249
42. Hiraoka Y., Shimi T., and Haraguchi T. Multispectral imaging fluorescence microscopy for living cells. Cell Struct Funct 27 (2002) 367-374
43. Neher R., and Neher E. Optimizing imaging parameters for the separation of multiple labels in a fluorescence image. J Microsc 213 (2004) 46-62. The authors provide a theoretical analysis on how spectral fingerprinting can be used to separate the fluorescence of FRET pairs from that originating from unpaired donors and acceptors and how to select imaging parameters to optimize the signal-to-noise ratio of the estimates.
44. Chorvat Jr. D., Kirchnerova J., Cagalinec M., Smolka J., Mateasik A., and Chorvatova A. Spectral unmixing of flavin autofluorescence components in cardiac myocytes. Biophys J 89 (2005) L55-L57
45. Cardoso J.F. Blind signal separation: statistical principles. Proc IEEE 9 (1998) 2009-2025
46. Kisilev P., Zibulevsky M., and Zeevi Y.Y. A multiscale framework for blind separation of linearly mixed signals. J Mach Learn Res 4 (2003) 1334-1364
47. Hirschberg K., Miller C.M., Ellenberg J., Presley J.F., Siggia E.D., Phair R.D., and Lippincott-Schwartz J. Kinetic analysis of secretory protein traffic and characterization of golgi to plasma membrane transport intermediates in living cells. J Cell Biol 143 (1998) 1485-1503
48. Chiu C.S., Kartalov E., Unger M., Quake S., and Lester H.A. Single-molecule measurements calibrate green fluorescent protein surface densities on transparent beads for use with 'knock-in' animals and other expression systems. J Neurosci Methods 105 (2001) 55-63
49. Dundr M., McNally J.G., Cohen J., and Misteli T. Quantitation of GFP-fusion proteins in single living cells. J Struct Biol 140 (2002) 92-99
50. Wu J.Q., and Pollard T.D. Counting cytokinesis proteins globally and locally in fission yeast. Science 310 (2005) 310-314. A comprehensive attempt to calculate absolute protein concentrations in live cells using external controls. The authors showed consistent linear relationships between the intensity of 27 fluorescent protein fusions measured using microscopy and the intensity measured using quantitative immunoblotting. From the corresponding known immunoblotting concentrations, they created a calibration table than can be used to calculate concentration of other fused proteins.
51. Wilson T. Three-dimensional imaging in confocal systems. J Microsc 153 (1989) 161-169
52. Ichihara A., Tanaami T., Isozaki K., Sugiyama Y., Kosugi Y., Mikuriya K., Abe M., and Uemura I. High-speed confocal fluorescence microscopy using a Nipkow scanner with microlenses fro 3D-imaging of single fluorescent molecule in real time. Bioimages 4 (1996) 52-62
53. Hell S.W., and Andresen V. Space-multiplexed multifocal nonlinear microscopy. J Microsc 202 (2001) 457-463
54. Adiga P.S., and Chaudhuri B.B. Efficient cell segmentation tool for confocal microscopy tissue images and quantitative evaluation of FISH signals. Microsc Res Tech 44 (1999) 49-68
55. Lockett S.J., Sudar D., Thompson C.T., Pinkel D., and Gray J.W. Efficient, interactive, and three-dimensional segmentation of cell nuclei in thick tissue sections. Cytometry 31 (1998) 275-286
56. Ortiz de Solorzano C., Garcia Rodriguez E., Jones A., Pinkel D., Gray J.W., Sudar D., and Lockett S.J. Segmentation of confocal microscope images of cell nuclei in thick tissue sections. J Microsc 193 (1999) 212-226
57. De Solorzano C.O., Malladi R., Lelievre S.A., and Lockett S.J. Segmentation of nuclei and cells using membrane related protein markers. J Microsc 201 (2001) 404-415
58. Lin G., Adiga U., Olson K., Guzowski J.F., Barnes C.A., and Roysam B. A hybrid 3D watershed algorithm incorporating gradient cues and object models for automatic segmentation of nuclei in confocal image stacks. Cytometry A 56 (2003) 23-36
59. Lin G., Chawla M.K., Olson K., Guzowski J.F., Barnes C.A., and Roysam B. Hierarchical, model-based merging of multiple fragments for improved three-dimensional segmentation of nuclei. Cytometry A 63 (2005) 20-33
60. Cheezum M.K., Walker W.F., and Guilford W.H. Quantitative comparison of algorithms for tracking single fluorescent particles. Biophys J 81 (2001) 2378-2388
61. Dufour A., Shinin V., Tajbakhsh S., Guillen-Aghion N., Olivo-Marin J.C., and Zimmer C. Segmenting and tracking fluorescent cells in dynamic 3-D microscopy with coupled active surfaces. IEEE Trans Image Process 14 (2005) 1396-1410. First integrated solution for segmenting and tracking cells in three dimensions. The authors of this elegant study use multiple implicit active surfaces to segment and track cells separately, and impose a constraint to avoid merging of neighboring cells.
62. Kozubek M., Matula P., Matula P., and Kozubek S. Automated acquisition and processing of multidimensional image data in confocal in vivo microscopy. Microsc Res Tech 64 (2004) 164-175
63. Gerlich D., Beaudouin J., Kalbfuss B., Daigle N., Eils R., and Ellenberg J. Global chromosome positions are transmitted through mitosis in mammalian cells. Cell 112 (2003) 751-764
64. Chen X, Murphy RF: Objective clustering of proteins based on subcellular location patterns. J Biomed Biotechnol 2005, 2005:87-95. The authors classified protein location patterns using morphological, intensity and texture measurements of GFP-fused protein expression in fluorescence images.
65. Knowles D.W., Sudar D., Bator-Kelly C., Bissell M.J., and Lelievre S.A. Automated local bright feature image analysis of nuclear protein distribution identifies changes in tissue phenotype. Proc Natl Acad Sci USA 103 (2006) 4445-4450
66. Huang K., and Murphy R.F. Boosting accuracy of automated classification of fluorescence microscope images for location proteomics. BMC Bioinformatics 5 (2004) 78
67. Zhao T., Velliste M., Boland M.V., and Murphy R.F. Object type recognition for automated analysis of protein subcellular location. IEEE Trans Image Process 14 (2005) 1351-1359
68. Zallen J.A., and Zallen R. Cell-pattern disordering during convergent extension in Drosophila. J Phys Condens Matter 16 (2004) S5073-S5080. Tissue disorder was quantified in Drosophila embryos at different stages of development using 2D-confocal microscopy images. The cell classification method (automatic or manual) was not mentioned, although the images shown are amenable to automatic watershed segmentation and classification based on the number of neighbors.
69. Carretta D., Santarelli M., Sbriccoli A., Pinto F., Catini C., and Minciacchi B. Spatial analysis reveals alterations of parvalbumin- and calbindin-positive local circuit neurons in the cerebral cortex of mutant mdx mice. Brain Res 1016 (2004) 1-11
70. Palanza L., Jhaveri S., Donati S., Nuzzi R., and Vercelli A. Quantitative spatial analysis of the distribution of NADPH-diaphorase-positive neurons in the developing and mature rat retina. Brain Res Bull 65 (2005) 349-360. This very quantitative approach was also used to validate a computational model of the retina that allowed the authors to gain further insight into the patterning mechanism.
71. Cameron D.A., and Carney L.H. Cellular patterns in the inner retina of adult zebrafish: quantitative analyses and a computational model of their formation. J Comp Neurol 471 (2004) 11-25
72. Tyler M.J., Carney L.H., and Cameron D.A. Control of cellular pattern formation in the vertebrate inner retina by homotypic regulation of cell-fate decisions. J Neurosci 25 (2005) 4565-4576
73. Fernandez-Gonzalez R., Barcellos-Hoff M.H., and Ortiz de Solorzano C. A tool for the quantitative spatial analysis of complex cellular systems. IEEE Trans Image Process 14 (2005) 1300-1313. The graph used here (a refined relative neighborhood graph) has the cell nuclei as nodes. The nodes corresponding to neighbor nuclei are automatically detected and linked by edges. This graph is then used to determine the neighborhood between cells and to measure distances between them with a normalized distance unit: the graph edge. Statistical significance is assessed by comparison to Monte Carlo simulations of random (in the single population case) or independent (for multiple populations) distributions.
74. Landini G., and Othman I.E. Architectural analysis of oral cancer, dysplastic, and normal epithelia. Cytometry A 61 (2004) 45-55
75. Neumann B., Held M., Liebel U., Erfle H., Rogers P., Pepperkok R., and Ellenberg J. High-throughput RNAi screening by time-lapse imaging of live human cells. Nat Methods 3 (2006) 385-390. A beautiful example of integration of automated acquisition and tracking for high-throughput parallel in vivo genomic analysis. The authors spotted 49 different siRNAs in live-cell chambers and periodically captured images of each of the cell cultures. They then used image analysis tools to segment and classify nuclei in each of the sequences and quantified the rate of nuclear division and apoptosis. In this way they could comparatively assess the role of those 49 genes in the completion and dynamics of cell mitosis.