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Cheung BCH, Abbed RJ, Wu M, Leggett SE. 3D Traction Force Microscopy in Biological Gels: From Single Cells to Multicellular Spheroids. Annu Rev Biomed Eng 2024; 26:93-118. [PMID: 38316064 DOI: 10.1146/annurev-bioeng-103122-031130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
Cell traction force plays a critical role in directing cellular functions, such as proliferation, migration, and differentiation. Current understanding of cell traction force is largely derived from 2D measurements where cells are plated on 2D substrates. However, 2D measurements do not recapitulate a vital aspect of living systems; that is, cells actively remodel their surrounding extracellular matrix (ECM), and the remodeled ECM, in return, can have a profound impact on cell phenotype and traction force generation. This reciprocal adaptivity of living systems is encoded in the material properties of biological gels. In this review, we summarize recent progress in measuring cell traction force for cells embedded within 3D biological gels, with an emphasis on cell-ECM cross talk. We also provide perspectives on tools and techniques that could be adapted to measure cell traction force in complex biochemical and biophysical environments.
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Affiliation(s)
- Brian C H Cheung
- Department of Biological and Environmental Engineering, Cornell University, Ithaca, New York, USA;
| | - Rana J Abbed
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, Illinois, USA;
| | - Mingming Wu
- Department of Biological and Environmental Engineering, Cornell University, Ithaca, New York, USA;
| | - Susan E Leggett
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, Illinois, USA;
- Cancer Center at Illinois, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
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Lejeune E, Khang A, Sansom J, Sacks MS. FM-Track: A fiducial marker tracking software for studying cell mechanics in a three-dimensional environment. SOFTWAREX 2020; 11:100417. [PMID: 34291145 PMCID: PMC8291167 DOI: 10.1016/j.softx.2020.100417] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Tracking the deformation of fiducial markers in the vicinity of living cells embedded in compliant synthetic or biological gels is a powerful means to study cell mechanics and mechanobiology in three-dimensional environments. However, current approaches to track and quantify three-dimensional (3D) fiducial marker displacements remain ad-hoc, can be difficult to implement, and may not produce reliable results. Herein, we present a compact software package entitled "FM-Track," written in the popular Python language, to facilitate feature-based particle tracking tailored for 3D cell micromechanical environment studies. FM-Track contains functions for pre-processing images, running fiducial marker tracking, and post-processing and visualization. FM-Track can thus aid the study of cellular mechanics and mechanobiology by providing an extensible software platform to more reliably extract complex local 3D cell contractile information in transparent compliant gel systems.
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Affiliation(s)
- Emma Lejeune
- James T. Willerson Center for Cardiovascular Modeling and Simulation, Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin, Austin TX, United States
- The Department of Mechanical Engineering, Boston University, Boston MA, United States
| | - Alex Khang
- James T. Willerson Center for Cardiovascular Modeling and Simulation, Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin, Austin TX, United States
| | - Jacob Sansom
- James T. Willerson Center for Cardiovascular Modeling and Simulation, Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin, Austin TX, United States
- The Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin TX, United States
| | - Michael S Sacks
- James T. Willerson Center for Cardiovascular Modeling and Simulation, Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin, Austin TX, United States
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Mulligan JA, Feng X, Adie SG. Quantitative reconstruction of time-varying 3D cell forces with traction force optical coherence microscopy. Sci Rep 2019; 9:4086. [PMID: 30858424 PMCID: PMC6411852 DOI: 10.1038/s41598-019-40608-4] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 02/19/2019] [Indexed: 12/18/2022] Open
Abstract
Cellular traction forces (CTFs) play an integral role in both physiological processes and disease, and are a topic of interest in mechanobiology. Traction force microscopy (TFM) is a family of methods used to quantify CTFs in a variety of settings. State-of-the-art 3D TFM methods typically rely on confocal fluorescence microscopy, which can impose limitations on acquisition speed, volumetric coverage, and temporal sampling or coverage. In this report, we present the first quantitative implementation of a new TFM technique: traction force optical coherence microscopy (TF-OCM). TF-OCM leverages the capabilities of optical coherence microscopy and computational adaptive optics (CAO) to enable the quantitative reconstruction of 3D CTFs in scattering media with minute-scale temporal sampling. We applied TF-OCM to quantify CTFs exerted by isolated NIH-3T3 fibroblasts embedded in Matrigel, with five-minute temporal sampling, using images spanning a 500 × 500 × 500 μm3 field-of-view. Due to the reliance of TF-OCM on computational imaging methods, we have provided extensive discussion of the equations, assumptions, and failure modes of these methods. By providing high-throughput, label-free, volumetric imaging in scattering media, TF-OCM is well-suited to the study of 3D CTF dynamics, and may prove advantageous for the study of large cell collectives, such as the spheroid models prevalent in mechanobiology.
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Affiliation(s)
- Jeffrey A Mulligan
- School of Electrical and Computer Engineering, Cornell University, Ithaca, New York, 14853, USA
| | - Xinzeng Feng
- Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas, 78712, USA
| | - Steven G Adie
- Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, 14853, USA.
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Patel M, Leggett SE, Landauer AK, Wong IY, Franck C. Rapid, topology-based particle tracking for high-resolution measurements of large complex 3D motion fields. Sci Rep 2018; 8:5581. [PMID: 29615650 PMCID: PMC5882970 DOI: 10.1038/s41598-018-23488-y] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 03/12/2018] [Indexed: 12/12/2022] Open
Abstract
Spatiotemporal tracking of tracer particles or objects of interest can reveal localized behaviors in biological and physical systems. However, existing tracking algorithms are most effective for relatively low numbers of particles that undergo displacements smaller than their typical interparticle separation distance. Here, we demonstrate a single particle tracking algorithm to reconstruct large complex motion fields with large particle numbers, orders of magnitude larger than previously tractably resolvable, thus opening the door for attaining very high Nyquist spatial frequency motion recovery in the images. Our key innovations are feature vectors that encode nearest neighbor positions, a rigorous outlier removal scheme, and an iterative deformation warping scheme. We test this technique for its accuracy and computational efficacy using synthetically and experimentally generated 3D particle images, including non-affine deformation fields in soft materials, complex fluid flows, and cell-generated deformations. We augment this algorithm with additional particle information (e.g., color, size, or shape) to further enhance tracking accuracy for high gradient and large displacement fields. These applications demonstrate that this versatile technique can rapidly track unprecedented numbers of particles to resolve large and complex motion fields in 2D and 3D images, particularly when spatial correlations exist.
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Affiliation(s)
- Mohak Patel
- School of Engineering, Brown University, Providence, RI, 02912, USA.
| | - Susan E Leggett
- School of Engineering, Brown University, Providence, RI, 02912, USA.,Center for Biomedical Engineering, Brown University, Providence, RI, 02912, USA.,Pathobiology Graduate Program, Brown University, Providence, RI, 02912, USA
| | | | - Ian Y Wong
- School of Engineering, Brown University, Providence, RI, 02912, USA.,Center for Biomedical Engineering, Brown University, Providence, RI, 02912, USA.,Pathobiology Graduate Program, Brown University, Providence, RI, 02912, USA
| | - Christian Franck
- School of Engineering, Brown University, Providence, RI, 02912, USA. .,Center for Biomedical Engineering, Brown University, Providence, RI, 02912, USA.
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Mulligan JA, Bordeleau F, Reinhart-King CA, Adie SG. Traction Force Microscopy for Noninvasive Imaging of Cell Forces. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018; 1092:319-349. [PMID: 30368759 DOI: 10.1007/978-3-319-95294-9_15] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The forces exerted by cells on their surroundings play an integral role in both physiological processes and disease progression. Traction force microscopy is a noninvasive technique that enables the in vitro imaging and quantification of cell forces. Utilizing expertise from a variety of disciplines, recent developments in traction force microscopy are enhancing the study of cell forces in physiologically relevant model systems, and hold promise for further advancing knowledge in mechanobiology. In this chapter, we discuss the methods, capabilities, and limitations of modern approaches for traction force microscopy, and highlight ongoing efforts and challenges underlying future innovations.
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Affiliation(s)
- Jeffrey A Mulligan
- School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA
| | - François Bordeleau
- Centre de Recherche du CHU de Québec, Université Laval, Québec, Qc, Canada
- Départment of Biologie Moléculaire, Biochimie Médicale et Pathologie, Université Laval, Québec, Qc, Canada
| | - Cynthia A Reinhart-King
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA
| | - Steven G Adie
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA.
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Fibrous nonlinear elasticity enables positive mechanical feedback between cells and ECMs. Proc Natl Acad Sci U S A 2016; 113:14043-14048. [PMID: 27872289 DOI: 10.1073/pnas.1613058113] [Citation(s) in RCA: 225] [Impact Index Per Article: 28.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
In native states, animal cells of many types are supported by a fibrous network that forms the main structural component of the ECM. Mechanical interactions between cells and the 3D ECM critically regulate cell function, including growth and migration. However, the physical mechanism that governs the cell interaction with fibrous 3D ECM is still not known. In this article, we present single-cell traction force measurements using breast tumor cells embedded within 3D collagen matrices. We recreate the breast tumor mechanical environment by controlling the microstructure and density of type I collagen matrices. Our results reveal a positive mechanical feedback loop: cells pulling on collagen locally align and stiffen the matrix, and stiffer matrices, in return, promote greater cell force generation and a stiffer cell body. Furthermore, cell force transmission distance increases with the degree of strain-induced fiber alignment and stiffening of the collagen matrices. These findings highlight the importance of the nonlinear elasticity of fibrous matrices in regulating cell-ECM interactions within a 3D context, and the cell force regulation principle that we uncover may contribute to the rapid mechanical tissue stiffening occurring in many diseases, including cancer and fibrosis.
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