Hostname: page-component-76fb5796d-wq484 Total loading time: 0 Render date: 2024-04-26T16:16:13.364Z Has data issue: false hasContentIssue false
  • English
  • Français

Imaging and Analysis of Cellular Locations in Three-Dimensional Tissue Models

Published online by Cambridge University Press:  11 March 2019

Warren Colomb ,
Matthew Osmond ,
Charles Durfee ,
Melissa D. Krebs  and
Susanta K. Sarkar Open the ORCID record for Susanta K. Sarkar [Opens in a new window]
Warren Colomb
Affiliation:
Department of Physics, Colorado School of Mines, Golden, Colorado, USA
Matthew Osmond
Affiliation:
Department of Chemical & Biological Engineering, Colorado School of Mines, Golden, Colorado, USA
Charles Durfee
Affiliation:
Department of Physics, Colorado School of Mines, Golden, Colorado, USA
Melissa D. Krebs
Affiliation:
Department of Chemical & Biological Engineering, Colorado School of Mines, Golden, Colorado, USA
Susanta K. Sarkar*
Affiliation:
Department of Physics, Colorado School of Mines, Golden, Colorado, USA
*
*Author for correspondence: Susanta K. Sarkar, E-mail: ssarkar@mines.edu
Get access

Abstract

The absence of quantitative in vitro cell–extracellular matrix models represents an important bottleneck for basic research and human health. Randomness of cellular distributions provides an opportunity for the development of a quantitative in vitro model. However, quantification of the randomness of random cell distributions is still lacking. In this paper, we have imaged cellular distributions in an alginate matrix using a multiview light sheet microscope and developed quantification metrics of randomness by modeling it as a Poisson process, a process that has constant probability of occurring in space or time. We imaged fluorescently labeled human mesenchymal stem cells embedded in an alginate matrix of thickness greater than 5 mm with $\sim\! {\rm 2}{\rm. 9} \pm {\rm 0}{\rm. 4}\,\mu {\rm m}$ axial resolution, the mean full width at half maximum of the axial intensity profiles of fluorescent particles. Simulated randomness agrees well with the experiments. Quantification of distributions and validation by simulations will enable quantitative study of cell–matrix interactions in tissue models.

Keywords

multiview light sheet microscopePoisson processrandomness of cellular distributions
Type
Biological Applications
Information
Microscopy and Microanalysis , Volume 25 , Issue 3 , June 2019 , pp. 753 - 761
Copyright
Copyright © Microscopy Society of America 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ahrens, MB, Orger, MB, Robson, DN, Li, JM & Keller, PJ (2013). Whole-brain functional imaging at cellular resolution using light-sheet microscopy. Nat Methods 10, 413–420.10.1038/nmeth.2434Google Scholar
Alexander, N, Moyeed, R & Stander, J (2000). Spatial modelling of individual-level parasite counts using the negative binomial distribution. Biostatistics 1, 453–463.10.1093/biostatistics/1.4.453Google Scholar
Andersen, T, Auk-Emblem, P & Dornish, M (2015). 3D cell culture in alginate hydrogels. Microarrays 4, 133–161.10.3390/microarrays4020133Google Scholar
Andrey, P, Kiêu, K, Kress, C, Lehmann, G, Tirichine, L, Liu, Z, Biot, E, Adenot, P-G, Hue-Beauvais, C & Houba-Hérin, N (2010). Statistical analysis of 3D images detects regular spatial distributions of centromeres and chromocenters in animal and plant nuclei. PLoS Comput Biol 6, e1000853.10.1371/journal.pcbi.1000853Google Scholar
Baddeley, A, Moyeed, R, Howard, C & Boyde, A (1993). Analysis of a three-dimensional point pattern with replication. Appl Stat 4, 641–668.10.2307/2986181Google Scholar
Baddeley, A, Rubak, E & Turner, R (2015). Spatial Point Patterns: Methodology and Applications with R. Florida, USA: CRC Press.10.1201/b19708Google Scholar
Barkai, N & Leibler, S (2000). Biological rhythms: Circadian clocks limited by noise. Nature 403, 267–268.10.1038/35002258Google Scholar
Beaurepaire, E (2014). Laboratoire Optique et Biosciences-Two-photon light sheet microscopy (2P-SPIM). Nat Methods 11, 600–601.Google Scholar
Berg, OG, Paulsson, J & Ehrenberg, M (2000). Fluctuations and quality of control in biological cells: Zero-order ultrasensitivity reinvestigated. Biophys J 79, 1228–1236.10.1016/S0006-3495(00)76377-6Google Scholar
Bidarra, SJ & Barrias, CC (2018). 3D Culture of Mesenchymal Stem Cells in Alginate Hydrogels. In: Methods in Molecular Biology. New York, USA: Humana Press.Google Scholar
Bielecka, ZF, Maliszewska-Olejniczak, K, Safir, IJ, Szczylik, C & Czarnecka, AM (2017). Three-dimensional cell culture model utilization in cancer stem cell research. Biol Rev 92, 1505–1520.10.1111/brv.12293Google Scholar
Breslin, S & O'Driscoll, L (2013). Three-dimensional cell culture: The missing link in drug discovery. Drug Discov Today 18, 240–249.10.1016/j.drudis.2012.10.003Google Scholar
Bumb, A, Sarkar, SK, Wu, XS, Brechbiel, MW & Neuman, KC (2011). Quantitative characterization of fluorophores in multi-component nanoprobes by single-molecule fluorescence. Biomed Opt Express 2, 2761–2769.10.1364/BOE.2.002761Google Scholar
Caló, E & Khutoryanskiy, VV (2015). Biomedical applications of hydrogels: A review of patents and commercial products. Eur Polym J 65, 252–267.10.1016/j.eurpolymj.2014.11.024Google Scholar
Chen, B-C, Legant, WR, Wang, K, Shao, L, Milkie, DE, Davidson, MW, Janetopoulos, C, Wu, XS, Hammer, JA & Liu, Z (2014). Lattice light-sheet microscopy: Imaging molecules to embryos at high spatiotemporal resolution. Science 346, 1257998.10.1126/science.1257998Google Scholar
Chung, K & Deisseroth, K (2013). CLARITY for mapping the nervous system. Nat Methods 10, 508–513.10.1038/nmeth.2481Google Scholar
Dean, KM & Fiolka, R (2014). Uniform and scalable light-sheets generated by extended focusing. Opt Express 22, 26141–26152.10.1364/OE.22.026141Google Scholar
Decaestecker, C, Debeir, O, Van Ham, P & Kiss, R (2007). Can anti-migratory drugs be screened in vitro? A review of 2D and 3D assays for the quantitative analysis of cell migration. Med Res Rev 27, 149–176.10.1002/med.20078Google Scholar
Diggle, PJ (2013). Statistical Analysis of Spatial and Spatio-Temporal Point Patterns. Florida, USA: CRC Press.10.1201/b15326Google Scholar
Elliott, NT & Yuan, F (2011). A review of three-dimensional in vitro tissue models for drug discovery and transport studies. J Pharm Sci 100, 59–74.10.1002/jps.22257Google Scholar
Fahrbach, FO, Voigt, FF, Schmid, B, Helmchen, F & Huisken, J (2013). Rapid 3D light-sheet microscopy with a tunable lens. Opt Express 21, 21010–21026.10.1364/OE.21.021010Google Scholar
Gao, L, Shao, L, Chen, B-C & Betzig, E (2014). 3D live fluorescence imaging of cellular dynamics using Bessel beam plane illumination microscopy. Nat Protoc 9, 1083–1101.10.1038/nprot.2014.087Google Scholar
Gillespie, DT (1977). Exact stochastic simulation of coupled chemical reactions. J Phys Chem 81, 2340–2361.10.1021/j100540a008Google Scholar
Green, RH (1966). Measurement of non-randomness in spatial distributions. Res Popul Ecol (Kyoto) 8, 1–7.10.1007/BF02524740Google Scholar
Hama, H, Kurokawa, H, Kawano, H, Ando, R, Shimogori, T, Noda, H, Fukami, K, Sakaue-Sawano, A & Miyawaki, A (2011). Scale: A chemical approach for fluorescence imaging and reconstruction of transparent mouse brain. Nat Neurosci 14, 1481–1488.10.1038/nn.2928Google Scholar
Hinderer, S, Layland, SL & Schenke-Layland, K (2016). ECM and ECM-like materials—biomaterials for applications in regenerative medicine and cancer therapy. Adv Drug Delivery Rev 97, 260–269.10.1016/j.addr.2015.11.019Google Scholar
Horton, NG, Wang, K, Kobat, D, Clark, CG, Wise, FW, Schaffer, CB & Xu, C (2013). In vivo three-photon microscopy of subcortical structures within an intact mouse brain. Nat Photonics 7, 205–209.10.1038/nphoton.2012.336Google Scholar
Huang, F, Sirinakis, G, Allgeyer, ES, Schroeder, LK, Duim, WC, Kromann, EB, Phan, T, Rivera-Molina, FE, Myers, JR & Irnov, I (2016). Ultra-high resolution 3D imaging of whole cells. Cell 166, 1028–1040.Google Scholar
Illian, J, Penttinen, A, Stoyan, H & Stoyan, D (2008). Statistical Analysis and Modelling of Spatial Point Patterns. New Jersey, USA: John Wiley & Sons.Google Scholar
Keller, PJ & Dodt, H-U (2012). Light sheet microscopy of living or cleared specimens. Curr Opin Neurobiol 22, 138–143.10.1016/j.conb.2011.08.003Google Scholar
Keller, PJ, Schmidt, AD, Santella, A, Khairy, K, Bao, Z, Wittbrodt, J & Stelzer, EH (2010). Fast, high-contrast imaging of animal development with scanned light sheet-based structured-illumination microscopy. Nat Methods 7, 637–642.10.1038/nmeth.1476Google Scholar
Keller, PJ, Schmidt, AD, Wittbrodt, J & Stelzer, EH (2008). Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy. Science 322, 1065–1069.Google Scholar
König, K (2000). Multiphoton microscopy in life sciences. J Microsc 200, 83–104.10.1046/j.1365-2818.2000.00738.xGoogle Scholar
Krzic, U, Gunther, S, Saunders, TE, Streichan, SJ & Hufnagel, L (2012). Multiview light-sheet microscope for rapid in toto imaging. Nat Methods 9, 730–733.Google Scholar
Levene, MJ, Dombeck, DA, Kasischke, KA, Molloy, RP & Webb, WW (2004). In vivo multiphoton microscopy of deep brain tissue. J Neurophysiol 91, 1908–1912.Google Scholar
Mahou, P, Vermot, J, Beaurepaire, E & Supatto, W (2014). Multicolor two-photon light-sheet microscopy. Nat Methods 11, 600–601.10.1038/nmeth.2963Google Scholar
Maia, FR, Fonseca, KB, Rodrigues, G, Granja, PL & Barrias, CC (2014). Matrix-driven formation of mesenchymal stem cell–extracellular matrix microtissues on soft alginate hydrogels. Acta Biomater 10, 3197–3208.10.1016/j.actbio.2014.02.049Google Scholar
Marycz, K, Szarek, D, Grzesiak, J & Wrzeszcz, K (2014). Influence of modified alginate hydrogels on mesenchymal stem cells and olfactory bulb-derived glial cells cultures. Bio-Med Mater Eng 24, 1625–1637.Google Scholar
Mertz, J (2011). Optical sectioning microscopy with planar or structured illumination. Nat Methods 8, 811–819.10.1038/nmeth.1709Google Scholar
Mertz, J & Kim, J (2010) Scanning light-sheet microscopy in the whole mouse brain with HiLo background rejection. J Biomed Opt 15, 016027-1–016027-7.Google Scholar
Mlodzianoski, MJ, Juette, MF, Beane, GL & Bewersdorf, J (2009). Experimental characterization of 3D localization techniques for particle-tracking and super-resolution microscopy. Opt Express 17, 8264–8277.Google Scholar
Nicodemus, GD & Bryant, SJ (2008). Cell encapsulation in biodegradable hydrogels for tissue engineering applications. Tissue Eng, Part B 14, 149–165.10.1089/ten.teb.2007.0332Google Scholar
Ozbudak, EM, Thattai, M, Kurtser, I, Grossman, AD & Van Oudenaarden, A (2002). Regulation of noise in the expression of a single gene. Nat Genet 31, 69–73.10.1038/ng869Google Scholar
Pan, C, Cai, R, Quacquarelli, FP, Ghasemigharagoz, A, Lourbopoulos, A, Matryba, P, Plesnila, N, Dichgans, M, Hellal, F & Ertürk, A (2016). Shrinkage-mediated imaging of entire organs and organisms using uDISCO. Nat Methods 13, 859–867.Google Scholar
Pertuz, S, Puig, D, Garcia, MA & Fusiello, A (2013). Generation of all-in-focus images by noise-robust selective fusion of limited depth-of-field images. IEEE Trans Image Process 22, 1242–1251.10.1109/TIP.2012.2231087Google Scholar
Pittenger, MF, Mackay, AM, Beck, SC, Jaiswal, RK, Douglas, R, Mosca, JD, Moorman, MA, Simonetti, DW, Craig, S & Marshak, DR (1999). Multilineage potential of adult human mesenchymal stem cells. Science 284, 143–147.10.1126/science.284.5411.143Google Scholar
Planchon, TA, Gao, L, Milkie, DE, Davidson, MW, Galbraith, JA, Galbraith, CG & Betzig, E (2011). Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination. Nat Methods 8, 417–423.Google Scholar
Preibisch, S, Saalfeld, S, Schindelin, J & Tomancak, P (2010). Software for bead-based registration of selective plane illumination microscopy data. Nat Methods 7, 418–419.10.1038/nmeth0610-418Google Scholar
Preibisch, S, Saalfeld, S & Tomancak, P (2009). Globally optimal stitching of tiled 3D microscopic image acquisitions. Bioinformatics 25, 1463–1465.Google Scholar
Qiao, S-P, Zhao, Y-F, Li, C-F, Yin, Y-B, Meng, Q-Y, Lin, F-H, Liu, Y, Hou, X-L, Guo, K & Chen, X-B (2016). An alginate-based platform for cancer stem cell research. Acta Biomater 37, 83–92.10.1016/j.actbio.2016.04.032Google Scholar
Ragan, T, Kadiri, LR, Venkataraju, KU, Bahlmann, K, Sutin, J, Taranda, J, Arganda-Carreras, I, Kim, Y, Seung, HS & Osten, P (2012). Serial two-photon tomography for automated ex vivo mouse brain imaging. Nat Methods 9, 255–258.10.1038/nmeth.1854Google Scholar
Reynaud, EG, Kržič, U, Greger, K & Stelzer, EH (2008). Light sheet-based fluorescence microscopy: More dimensions, more photons, and less photodamage. HFSP J 2, 266–275.10.2976/1.2974980Google Scholar
Ripley, BD (1976). The second-order analysis of stationary point processes. J Appl Probab 13, 255–266.10.2307/3212829Google Scholar
Ripley, BD (1977). Modelling spatial patterns. Journal of the Royal Statistical Society. Series B (Methodological) 1977 (Jan 1), 172–212.10.1111/j.2517-6161.1977.tb01615.xGoogle Scholar
Ritter, JG, Spille, J-H, Kaminski, T & Kubitscheck, U (2011). A cylindrical zoom lens unit for adjustable optical sectioning in light sheet microscopy. Biomed Opt Express 2, 185–193.10.1364/BOE.2.000185Google Scholar
Ritter, JG, Veith, R, Veenendaal, A, Siebrasse, JP & Kubitscheck, U (2010). Light sheet microscopy for single molecule tracking in living tissue. PLoS ONE 5, e11639.10.1371/journal.pone.0011639Google Scholar
Robinson, BK, Cortes, E, Rice, AJ, Sarper, M & del Río Hernández, A (2016). Quantitative analysis of 3D extracellular matrix remodelling by pancreatic stellate cells. Biol Open 0, 1–8. doi:10.1242/bio.017632.Google Scholar
Rodriguez, A, Ehlenberger, D, Kelliher, K, Einstein, M, Henderson, SC, Morrison, JH, Hof, PR & Wearne, SL (2003). Automated reconstruction of three-dimensional neuronal morphology from laser scanning microscopy images. Methods 30, 94–105.Google Scholar
Rowley, JA, Madlambayan, G & Mooney, DJ (1999). Alginate hydrogels as synthetic extracellular matrix materials. Biomaterials 20, 45–53.Google Scholar
Ruedinger, F, Lavrentieva, A, Blume, C, Pepelanova, I & Scheper, T (2015). Hydrogels for 3D mammalian cell culture: A starting guide for laboratory practice. Appl Microbiol Biotechnol 99, 623–636.10.1007/s00253-014-6253-yGoogle Scholar
Sarkar, SK (2016). Single Molecule Biophysics and Poisson Process Approach to Statistical Mechanics. California, USA: Morgan & Claypool Publishers.10.1088/978-1-6817-4116-1Google Scholar
Sbalzarini, IF & Koumoutsakos, P (2005). Feature point tracking and trajectory analysis for video imaging in cell biology. J Struct Biol 151, 182–195.10.1016/j.jsb.2005.06.002Google Scholar
Shapiro, L & Cohen, S (1997). Novel alginate sponges for cell culture and transplantation. Biomaterials 18, 583–590.Google Scholar
Silvestri, L, Allegra Mascaro, AL, Costantini, I, Sacconi, L & Pavone, FS (2014). Correlative two-photon and light sheet microscopy. Methods 66, 268–272.10.1016/j.ymeth.2013.06.013Google Scholar
Summers, HD, Wills, JW, Brown, MR & Rees, P (2015). Poisson-event-based analysis of cell proliferation. Cytometry Part A 87, 385–392.10.1002/cyto.a.22620Google Scholar
Susaki, EA, Tainaka, K, Perrin, D, Kishino, F, Tawara, T, Watanabe, TM, Yokoyama, C, Onoe, H, Eguchi, M & Yamaguchi, S (2014). Whole-brain imaging with single-cell resolution using chemical cocktails and computational analysis. Cell 157, 726–739.Google Scholar
Tibbitt, MW & Anseth, KS (2009). Hydrogels as extracellular matrix mimics for 3D cell culture. Biotechnol Bioeng 103, 655–663.10.1002/bit.22361Google Scholar
Till, JE, McCulloch, EA & Siminovitch, L (1964). A stochastic model of stem cell proliferation, based on the growth of spleen colony-forming cells. Proc Natl Acad Sci USA 51, 29–36.Google Scholar
Tinevez, J-Y, Perry, N, Schindelin, J, Hoopes, GM, Reynolds, GD, Laplantine, E, Bednarek, SY, Shorte, SL & Eliceiri, KW (2017). Trackmate: An open and extensible platform for single-particle tracking. Methods 115, 80–90.10.1016/j.ymeth.2016.09.016Google Scholar
Tomer, R, Khairy, K, Amat, F & Keller, PJ (2012). Quantitative high-speed imaging of entire developing embryos with simultaneous multiview light-sheet microscopy. Nat Methods 9, 755–763.Google Scholar
Tsimring, LS (2014). Noise in biology. Rep Prog Phys 77, 026601.10.1088/0034-4885/77/2/026601Google Scholar
Vettenburg, T, Dalgarno, HI, Nylk, J, Coll-Lladó, C, Ferrier, DE, Čižmár, T, Gunn-Moore, FJ & Dholakia, K (2014). Light-sheet microscopy using an Airy beam. Nat Methods 11, 541–544.10.1038/nmeth.2922Google Scholar
Wearne, S, Rodriguez, A, Ehlenberger, D, Rocher, A, Henderson, S & Hof, P (2005). New techniques for imaging, digitization and analysis of three-dimensional neural morphology on multiple scales. Neuroscience 136, 661–680.Google Scholar
Weber, M, Mickoleit, M & Huisken, J (2013). Light sheet microscopy. Methods Cell Biol 123, 193–215.10.1016/B978-0-12-420138-5.00011-2Google Scholar
Weiswald, L-B, Bellet, D & Dangles-Marie, V (2015). Spherical cancer models in tumor biology. Neoplasia 17, 1–15.Google Scholar
Wu, Y, Wawrzusin, P, Senseney, J, Fischer, RS, Christensen, R, Santella, A, York, AG, Winter, PW, Waterman, CM & Bao, Z (2013). Spatially isotropic four-dimensional imaging with dual-view plane illumination microscopy. Nat Biotechnol 31, 1032–1038.Google Scholar
Yang, X, Sarvestani, SK, Moeinzadeh, S, He, X & Jabbari, E (2012). Three-dimensional-engineered matrix to study cancer stem cells and tumorsphere formation: Effect of matrix modulus. Tissue Eng, Part A 19, 669–684.10.1089/ten.tea.2012.0333Google Scholar
Zipfel, WR, Williams, RM & Webb, WW (2003). Nonlinear magic: Multiphoton microscopy in the biosciences. Nat Biotechnol 21, 1369–1377.10.1038/nbt899Google Scholar