Quantitative reconstruction of time-varying 3D cell forces with traction force optical coherence microscopy

Abstract

11Cellular traction forces (CTFs) play an integral role in both physiological processes and disease, and are a topic of 12 interest in mechanobiology. Traction force microscopy (TFM) is a family of methods used to quantify CTFs in a 13 variety of settings. State-of-the-art 3D TFM methods typically rely on confocal fluorescence microscopy, which can 14 impose limitations on acquisition speed, volumetric coverage, and temporal sampling or coverage. In this report, we 15 present the first quantitative implementation of a new TFM technique: traction force optical coherence microscopy 16(TF-OCM). TF-OCM leverages the capabilities of optical coherence microscopy and computational adaptive optics 17(CAO) to enable the quantitative reconstruction of 3D CTFs in scattering media with minute-scale temporal 18 resolution. We applied TF-OCM to quantify CTFs exerted by isolated NIH-3T3 fibroblasts embedded in Matrigel, 19with five-minute temporal sampling, using images which spanned a 500×500×500 μm 3 field-of-view. Due to the 20 reliance of TF-OCM on computational imaging methods, we have provided extensive discussion of the underlying 21 equations, assumptions, and failure modes of these methods. TF-OCM has the potential to advance studies of 22 biomechanical behavior in scattering media, and may be especially well-suited to the study of cell collectives such 23as spheroids, a prevalent model in mechanobiology research. 24

Light-sheet photonic force optical coherence elastography for high-throughput quantitative 3D micromechanical imaging

“…The latter behaviour is consistent with previous reports 32,33 , and may be attributed to the "relaxation" of cell-force-mediated ECM stiffening governed by CytoD inhibition of actin polymerization 44 . Notably, both G' and R stabilize after approximately 2 hr, consistent with the amount of time taken for the total cell force to approach zero following CytoD treatment in a previous traction force microscopy study 44 . The former behaviour, which has not been reported previously, may be attributed to the redistribution of fibrin network in the pericellular space (see discussion of Fig.…”

“…We applied LS-pfOCE to characterize the micromechanical heterogeneity in fibrous collagen matrices, and for the first time, characterized the 3D spatial variations and temporal dynamics of cellmediated ECM micromechanical properties via live-cell imaging of fibroblasts within 3D fibrin constructs. The 3D imaging of cell boundaries based on OCT speckle fluctuations 6,44 , as well as ECM deformations and micromechanical properties allows the measurements of pericellular mechanical properties to be interpreted within the context of the cell orientation (i.e., extension direction) and cell-induced ECM deformations.…”

Microrheological quantification of viscoelastic properties with photonic force optical coherence elastography

“…The optical design of the PF-OCE system and the acquisition scheme utilized in each experiment can be adapted to optimize the desired information in an application-specific manner, using the system noise performance and data requirements for quantitative PF-OCE investigated in this paper as a guide. For instance, a study of the spatiotemporal variation ECM mechanical properties induced by the contractile dynamics of a single cell over minuteto-hour timescale may benefit from a relatively high-NA system with limited depth-coverage but large maximum detectable stiffness within 1-10 minutes of acquisition time [49,50]. On the other hand, dynamics over a longer timescale such as the phenotypic change of cells or the migration of cancer cells from cellular spheroids may benefit from a long time-lapsed imaging study with extended depth coverage (on the order of 10 2 µm), but with temporal resolution of 20-40 minutes per volume [51][52][53].…”

Automated sensorless single-shot closed-loop adaptive optics microscopy with feedback from computational adaptive optics

“…The phase stability that AutoAO demands for optimal performance is the same as the phase stability needed for implementing CAO on in vivo samples. CAO has been successfully used for wavefront sensing or aberration correction for ex vivo, in vitro, and in vivo OCM volumes of various biological samples [45,46,66,67]. Also, the optimal pattern can be estimated for an initial volume of a smaller size and field of view, thereby reducing the effect of motion artifacts.…”