Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-24T14:30:06.220Z Has data issue: false hasContentIssue false
  • English
  • Français

Image-based Characterization of 3D Collagen Networks and the Effect of Embedded Cells

Published online by Cambridge University Press:  18 June 2019

Vanesa Olivares ,
Mar Cóndor ,
Cristina Del Amo ,
Jesús Asín ,
Carlos Borau  and
José Manuel García-Aznar Open the ORCID record for José Manuel García-Aznar [Opens in a new window]
Vanesa Olivares
Affiliation:
Multiscale in Mechanical and Biological Engineering (Department of Mechanical Engineering), University of Zaragoza, Zaragoza, Spain Aragon Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain
Mar Cóndor
Affiliation:
Multiscale in Mechanical and Biological Engineering (Department of Mechanical Engineering), University of Zaragoza, Zaragoza, Spain Aragon Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain Biomechanics Section, Department of Mechanical Engineering, KU Leuven, Belgium
Cristina Del Amo
Affiliation:
Multiscale in Mechanical and Biological Engineering (Department of Mechanical Engineering), University of Zaragoza, Zaragoza, Spain Aragon Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain
Jesús Asín
Affiliation:
Department of Statistical Methods, University of Zaragoza, Zaragoza, Spain
Carlos Borau
Affiliation:
Multiscale in Mechanical and Biological Engineering (Department of Mechanical Engineering), University of Zaragoza, Zaragoza, Spain Aragon Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain University Center for Defense, Zaragoza, Spain
José Manuel García-Aznar*
Affiliation:
Multiscale in Mechanical and Biological Engineering (Department of Mechanical Engineering), University of Zaragoza, Zaragoza, Spain Aragon Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain
*
*Author for correspondence: José Manuel García-Aznar, E-mail: [email protected]
Get access

Abstract

Collagen microstructure is closely related to the mechanical properties of tissues and affects cell migration through the extracellular matrix. To study these structures, three-dimensional (3D) in vitro collagen-based gels are often used, attempting to mimic the natural environment of cells. Some key parameters of the microstructure of these gels are fiber orientation, fiber length, or pore size, which define the mechanical properties of the network and therefore condition cell behavior. In the present study, an automated tool to reconstruct 3D collagen networks is used to extract the aforementioned parameters of gels of different collagen concentration and determine how their microstructure is affected by the presence of cells. Two different experiments are presented to test the functionality of the method: first, collagen gels are embedded within a microfluidic device and collagen fibers are imaged by using confocal fluorescence microscopy; second, collagen gels are directly polymerized in a cell culture dish and collagen fibers are imaged by confocal reflection microscopy. Finally, we investigate and compare the collagen microstructure far from and in the vicinities of MDA-MB 23 cells, finding that cell activity during migration was able to strongly modify the orientation of the collagen fibers and the porosity-related values.

Keywords

collagen gelconfocal microscopyextracellular matrixmicrostructurescaffold morphology3D reconstruction
Type
Biological Applications
Information
Microscopy and Microanalysis , Volume 25 , Issue 4 , August 2019 , pp. 971 - 981
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

Adams, JC & Watt, FM (1993). Regulation of development and differentiation by the extracellular matrix. Development 117, 1183–1198.Google Scholar
Ahrens, J, Geveci, B & Law, C (2005). ParaView: An End-User Tool for Large Data Visualization, Visualization Handbook. Elsevier, ISBN-13: 978-0123875822.Google Scholar
Alberts, B, Johnson, A & Lewis, J (2002). The extracellular matrix of animals. Mol Biol Cell i, 1–25. Retrieved from http://www.ncbi.nlm.nih.gov/books/NBK26810/Google Scholar
Anguiano, M, Castilla, C, Maška, M, Ederra, C, Peláez, R, Morales, X, Muñoz-Arrieta, G, Mujika, M, Kozubek, M, Muñoz-Barrutia, A, Rouzaut, A, Arana, S, Garcia-Aznar, JM & Ortiz-de-Solorzano, C (2017). Characterization of three-dimensional cancer cell migration in mixed collagen-Matrigel scaffolds using microfluidics and image analysis. PLOS ONE 12(2), e0171417. https://doi.org/journal.pone/journal.pone.0171417.Google Scholar
Arevalo, RC, Urbach, JS & Blair, DL (2010). Size-dependent rheology of type-I collagen networks. Biophys J 99, 65–67. https://doi.org/10.1016/j.bpj.2010.08.008Google Scholar
Aumailley, M & Gayraud, B (1998). Structure and biological activity of the extracellular matrix. J Mol Med (Berlin, Germany) 76(3–4), 253–265. https://doi.org/10.1007/s001090050215Google Scholar
Berthiaume, F, Moghe, PV, Toner, M & Yarmush, ML (1996). Effect of extracellular matrix topology on cell structure, function, and physiological responsiveness: Hepatocytes cultured in a sandwich configuration. FASEB J 10(13), 1471–1484. https://doi.org/10.1096/FASEBJ.10.13.8940293Google Scholar
Bouix, S, Siddiqi, K & Tannenbaum, A (2005). Flux driven automatic centerline extraction. Med Image Anal 9(3), 209–221. https://doi.org/10.1016/j.media.2004.06.026Google Scholar
Bredfeldt, JS, Liu, Y, Pehlke, CA, Conklin, MW, Szulczewski, JM, Inman, DR, Keely, PJ, Nowak, RD, Mackie, TR & Eliceiri, KW (2014). Computational segmentation of collagen fibers from second-harmonic generation images of breast cancer. J Biomed Opt 19(1), 16007. https://doi.org/10.1117/1.JBO.19.1.016007.Google Scholar
Chung, BG, Lee, KH, Khademhosseini, A & Lee, SH (2012). Microfluidic fabrication of microengineered hydrogels and their application in tissue engineering. Lab Chip 12(1), 45–59. https://doi.org/10.1039/c1lc20859dGoogle Scholar
Cóndor, M, Mark, C, Gerum, RC, Grummel, NC, Bauer, A, García-Aznar, JM & Fabry, B (2019). Breast cancer cells adapt contractile forces to overcome steric hindrance. Biophys J 116(7), 1305–1312. https://doi.org/10.1016/J.BPJ.2019.02.029.Google Scholar
Cóndor, M, Steinwachs, J, Mark, C, García-Aznar, JM & Fabry, B (2017). Traction force microscopy in 3-dimensional extracellular matrix networks. Curr Protoc Cell Biol 75, 10.22.1–10.22.20. https://doi.org/10.1002/cpcb.24Google Scholar
Cox, TR & Erler, JT (2011). Remodeling and homeostasis of the extracellular matrix: Implications for fibrotic diseases and cancer. Dis Model Mech 4(2), 165–178. https://doi.org/10.1242/dmm.004077Google Scholar
Del Amo, C, Olivares, V, Cóndor, M, Blanco, A, Santolaria, J, Asín, J, Borau, C & Garcia-Aznar, JM (2018). Matrix architecture plays a pivotal role in 3D osteoblast migration: The effect of interstitial fluid flow. J Mech Behav Biomed Mater 83, 52–62.Google Scholar
Di Lullo, GA, Sweeney, SM, Körkkö, J, Ala-Kokko, L & San Antonio, JD (2002). Mapping the ligand-binding sites and disease-associated mutations on the most abundant protein in the human, type I collagen. J Biol Chem 277(6), 4223–4231. https://doi.org/10.1074/jbc.M110709200Google Scholar
Discher, DE, Janmey, P & Wang, Y (2005). Tissue cells feel and respond to the stiffness of their substrate. Science 310(5751), 1139–1143.Google Scholar
Doyle, AD, Carvajal, N, Jin, A, Matsumoto, K & Yamada, KM (2015). Local 3D matrix microenvironment regulates cell migration through spatiotemporal dynamics of contractility-dependent adhesions. Nat Commun 6, 1–15. https://doi.org/10.1038/ncomms9720.Google Scholar
Doyle, AD, Yamada, KM & Section, CB (2017). Mechanosensing via cell-matrix adhesions in 3D microenvironments. Exp Cell Res 343(1), 60–66. https://doi.org/10.1016/j.yexcr.2015.10.033.MechanosensingGoogle Scholar
Fitton, JH, Dalton, BA, Beumer, G, Johnson, G, Griesser, HJ & Steele, JG (1998). Surface topography can interfere with epithelial tissue migration. J Biomed Mater Res 42(2), 245–257.Google Scholar
Gardel, ML (2004). Elastic behavior of cross-linked and bundled actin networks. Science 304(5675), 1301–1305. https://doi.org/10.1126/science.1095087Google Scholar
Han, YL, Ronceray, P, Xu, G, Malandrino, A, Kamm, RD, Lenz, M, Broedersz, CP & Guo, M (2018). Cell contraction induces long-ranged stress stiffening in the extracellular matrix. Proc Natl Acad Sci USA 115(16), 4075–4080. https://doi.org/10.1073/pnas.1722619115.Google Scholar
Kraning-Rush, CM, Califano, JP & Reinhart-King, CA (2012). Cellular traction stresses increase with increasing metastatic potential. PLoS ONE 7(2), 1–10. https://doi.org/10.1371/journal.pone.0032572.Google Scholar
Krauss, P, Metzner, C, Lange, J, Lang, N & Fabry, B (2012). Parameter-free binarization and skeletonization of fiber networks from confocal image stacks. PLoS ONE 7(5), 1–8. https://doi.org/10.1371/journal.pone.0036575Google Scholar
Kueng, W, Silber, E & Eppenberger, U (1989). Quantification of cells cultured on 96-well plates. Anal Biochem 182(1), 16–19. https://doi.org/10.1016/0003-2697(89)90710-0Google Scholar
Lang, NR, Münster, S, Metzner, C, Krauss, P, Schürmann, S, Lange, J, Aifantis, KE, Friedrich, O & Fabry, Ben (2013). Estimating the 3D pore size distribution of biopolymer networks from directionally biased data. Biophys J 105(9), 1967–1975. https://doi.org/10.1016/j.bpj.2013.09.038.Google Scholar
Lebbink, MN, Geerts, WJC, van der Krift, TP, Bouwhuis, M, Hertzberger, LO, Verkleij, AJ & Koster, AJ (2007). Template matching as a tool for annotation of tomograms of stained biological structures. J Struct Biol 158(3), 327–335. https://doi.org/10.1016/j.jsb.2006.12.001Google Scholar
Leclerc, E, Sakai, Y & Fujii, T (2003). Cell culture in 3-dimensional microfluidic structure of PDMS (polydimenthylsiloxane). Biomed Microdevices 5(2), 109–114. https://doi.org/10.1023/A:1024583026925Google Scholar
Lee, B, Zhou, X, Riching, K, Eliceiri, KW, Keely, PJ, Guelcher, SA, Weaver, AM, Jiang, Y & Kumar, S (2014). A three-dimensional computational model of collagen network mechanics. PLoS One 9(11), e111896.Google Scholar
Ma, CM & Sonka, M (1996). A fully parallel 3D thinning algorithm and its applications. Comput Vis Image Underst 64(3), 420–433. Retrieved from https://ac.els-cdn.com/S1077314296900697/1-s2.0-S1077314296900697-main.pdf?_tid=bcc04b14-bfed-11e7-be95-00000aacb360&acdnat=1509641525_fe0bc579eae455eb1ca85cd8c9559a2aGoogle Scholar
Mehlen, P & Puisieux, A (2006). Metastasis: A question of life or death. Nat Rev Cancer 6(6), 449–458. https://doi.org/10.1038/nrc1886Google Scholar
Mishchenko, Y (2015). A fast algorithm for computation of discrete Euclidean distance transform in three or more dimensions on vector processing architectures. Signal Image Video Process 9(1), 19–27. https://doi.org/10.1007/s11760-012-0419-9Google Scholar
Moreno-Arotzena, O, Meier, J, Del Amo, C & García-Aznar, JM (2015). Characterization of fibrin and collagen gels for engineering wound healing models. Materials (Basel) 8(4), 1636–1651. https://doi.org/10.3390/ma8041636Google Scholar
Pedersen, JA & Swartz, MA (2005). Mechanobiology in the third dimension. Ann Biomed Eng 33(11), 1469–1490. https://doi.org/10.1007/s10439-005-8159-4Google Scholar
Petrie, RJ & Yamada, KM (2012). At the leading edge of three-dimensional cell migration. J Cell Sci 125, 5917–5926. https://doi.org/10.1242/jcs.093732Google Scholar
Piechocka, IK, Van Oosten, ASG, Breuls, RGM & Koenderink, GH (2011). Rheology of heterotypic collagen networks. Biomacromolecules 12, 2797–2805. https://doi.org/10.1021/bm200553xGoogle Scholar
Pudney, C (1998). Distance-Ordered homotopic thinning: A skeletonization algorithm for 3D digital images. Comput Vis Image Underst 72(3), 404–413. Retrieved from https://ac.els-cdn.com/S1077314298906804/1-s2.0-S1077314298906804-main.pdf?_tid=874c8bb4-bfed-11e7-80fc-00000aab0f02&acdnat=1509641435_12d4605db75314cfb7f59dab527824e1Google Scholar
Ranucci, CS, Kumar, A, Batra, SP & Moghe, PV (2000). Control of hepatocyte function on collagen foams: Sizing matrix pores toward selective induction of 2-D and 3-D cellular morphogenesis. Biomaterials 21(8), 783–793. https://doi.org/10.1016/S0142-9612(99)00238-0Google Scholar
Rigort, A, Günther, D, Hegerl, R, Baum, D, Weber, B, Prohaska, S, Medalia, O, Baumeister, W & Hege, H-C (2012). Automated segmentation of electron tomograms for a quantitative description of actin filament networks. J Struct Biol 177(1), 135–144. https://doi.org/10.1016/j.jsb.2011.08.012.Google Scholar
Roeder, BA, Kokini, K, Sturgis, JE, Robinson, JP & Voytik-Harbin, SL (2002). Tensile mechanical properties of three-dimensional type I collagen extracellular matrices with varied microstructure. J Biomech Eng 124(2), 214. https://doi.org/10.1115/1.1449904Google Scholar
Sharma, A, Licup, AJ, Jansen, KA, Rens, R, Sheinman, M, Koenderink, GH & MacKintosh, FC (2016). Strain-controlled criticality governs the nonlinear mechanics of fibre networks. Nat Phys 12(6), 584–587. https://doi.org/10.1038/nphys3628Google Scholar
Shoulders, MD & Raines, RT (2010). Collagen structure and stability. Annu Rev Biochem 78, 929–958. https://doi.org/10.1146/annurev.biochem.77.032207.120833.COLLAGENGoogle Scholar
Stein, AM, Vader, DA, Jawerth, LM, Weitz, DA & Sander, LM (2008). An algorithm for extracting the network geometry of three-dimensional collagen gels. J Microsc 232(3), 463–475. https://doi.org/10.1111/j.1365-2818.2008.02141.xGoogle Scholar
Stein, AM, Vader, DA, Weitz, DA & Sander, LM (2011). The micromechanics of three-dimensional collagen-I gels. Complexity 16(4), 22–28. https://doi.org/10.1002/cplx.20332Google Scholar
Streuli, C (1999). Extracellular matrix remodelling and cellular differentiation. Curr Opin Cell Biol 11(5), 634–640.Google Scholar
Sung, KE, Su, G, Pehlke, C, Trier, SM, Eliceiri, KW, Keely, PJ, Friedl, A & Beebe, DJ (2009). Control of 3-dimensional collagen matrix polymerization for reproducible Human Mammary Fibroblast cell culture in microfluidic devices Kyung. Biomaterials 30(27), 4833–4841. https://doi.org/10.1016/j.biomaterials.2009.05.043.Control.Google Scholar
Tondon, A & Kaunas, R (2014). The direction of stretch-induced cell and stress fiber orientation depends on collagen matrix stress. PLoS ONE 9(2), 1–10. https://doi.org/10.1371/journal.pone.0089592.Google Scholar
Valero, C, Amaveda, H, Mora, M & Garcia-aznar, JM (2018). Combined experimental and computational characterization of crosslinked collagen-based hydrogels. PLoS ONE 13(4), 1–16. https://doi.org/10.1371/journal.pone.0195820.Google Scholar
Wang, T & Basu, A (2007). A note on “A fully parallel 3D thinning algorithm and its applications.” Pattern Recognit Lett 28(4), 501–506. https://doi.org/10.1016/j.patrec.2006.09.004Google Scholar
Wolf, K, Te Lindert, M, Krause, M, Alexander, S, Te Riet, J, Willis, AL, Hoffman, RM, Figdor, CG, Weiss, SJ & Friedl, P (2013). Physical limits of cell migration: Control by ECM space and nuclear deformation and tuning by proteolysis and traction force. J Cell Biol 201(7), 1069–1084. https://doi.org/10.1083/jcb.201210152.Google Scholar
Wu, J, Rajwa, B, Filmer, DL, Hoffmann, CM, Yuan, B, Chiang, C, Sturgis, J & Robinson, JP (2003). Automated quantification and reconstruction of collagen matrix from 3D confocal datasets. J Microsc 210(2), 158–165. https://doi.org/10.1046/j.1365-2818.2003.01191.x.Google Scholar
Zaman, MH, Trapani, LM, Sieminski, AL, MacKellar, D, Gong, H, Kamm, RD, Wells, A, Lauffenburger, DA & Matsudaira, P (2006). Migration of tumor cells in 3D matrices is governed by matrix stiffness along with cell-matrix adhesion and proteolysis. Proc Natl Acad Sci USA 103(29), 10889–10894. https://doi.org/10.1073/pnas.0604460103.Google Scholar
Supplementary material: File

Olivares et al. supplementary material

Olivares et al. supplementary material 1

Download Olivares et al. supplementary material(File)
File 133.4 KB