Biodynamic imaging for phenotypic profiling of three-dimensional tissue culture

Abstract

Three-dimensional (3-D) tissue culture represents a more biologically relevant environment for testing new drugs compared to conventional two-dimensional cancer cell culture models. Biodynamic imaging is a high-content 3-D optical imaging technology based on low-coherence interferometry and digital holography that uses dynamic speckle as high-content image contrast to probe deep inside 3-D tissue. Speckle contrast is shown to be a scaling function of the acquisition time relative to the persistence time of intracellular transport and hence provides a measure of cellular activity. Cellular responses of 3-D multicellular spheroids to paclitaxel are compared among three different growth techniques: rotating bioreactor (BR), hanging-drop (HD), and nonadherent (U-bottom, UB) plate spheroids, compared with ex vivo living tissues. HD spheroids have the most homogeneous tissue, whereas BR spheroids display large sample-to-sample variability as well as spatial heterogeneity. The responses of BR-grown tumor spheroids to paclitaxel are more similar to those of ex vivo biopsies than the responses of spheroids grown using HD or plate methods. The rate of mitosis inhibition by application of taxol is measured through tissue dynamics spectroscopic imaging, demonstrating the ability to monitor antimitotic chemotherapy. These results illustrate the potential use of low-coherence digital holography for 3-D pharmaceutical screening applications.

Figures

Fig. 1

Fourier domain low-coherence digital holography system with a Mach–Zehnder off-axis configuration recording on the FP. The object light backscattered by the target is collected and projected onto the FP at the CCD by lenses L1, L2, and L3 with intermediate image plane and FP.

Fig. 2

NSD as a function of the scaling parameter q2v2τT, where q is the momentum transfer, v is the organelle speed, and τ is the persistence time of the random flights. Monte Carlo simulation of flights were performed with 500 frames at 25 fps for T=20  s. The NSD data are accumulated from simulations using different organelle velocities and persistence times, demonstrating the scaling relationship between NSD and the transport properties. For q2v2τT≫1, the NSD approaches unity.

Fig. 3

(a) The measured fluctuation power spectra of A2780 and DLD-1 spheroids for three growth techniques: BR, bioreactor (red); UB, U-bottom (blue); and HD, hanging drop (green). The data are plotted on double log10. The knee frequencies are in the range of 0.02 to 0.03 Hz. The slope parameters are around −1.5 to −1.7, and the dynamic range is ∼1000∶1. The tumors from the BR have lower knee frequencies than tumors from the HD method. (b) Mouse (red) and human esophageal biopsies (blue) have lower dynamic range relative to the spectra of A2780 (green) and DLD-1 (black) tumor spheroids obtained from the BR.

Fig. 4

(a) MCI of A2780 and DLD-1 spheroids for three different growth methods: BR, bioreactor; UB, U-bottom; and HD, hanging-drop, and compared with ovarian tumor xenografts. The color scale ranges from 0.6 to 1. The BR spheroids have lower NSD in the core area because the BR spheroids are tighter and denser. UB and HD spheroids have higher NSD because of lower adhesions. (b) Bar chart of knee frequency and (c) NSD of spheroids and biopsies. BR spheroids have a large variability. HD spheroids have the most uniform properties.

Fig. 5

NSD correlated against other properties of the tissue. (a) NSD versus knee frequency of the fluctuation power spectrum for A2780 and DLD-1 spheroids. (b) NSD versus BB for A2780 and DLD-1 spheroids. The BR samples have higher BB because they are more optically heterogeneous. UB and HD spheroids are more transparent. The HD method produces the most uniform tumor spheroid properties.

Fig. 6

(a) Paclitaxel time-frequency dose-response averaged spectrograms of A2780 and DLD-1 for three growth methods (BR, bioreactor; UB, U-bottom plate; and HD, hanging drop). The 4-h baseline is under the control medium (DMSO carrier), and 10  μM paclitaxel was added at t0=0. Red and blue colors correspond to increase or decrease in the differential power density, respectively. The response of the paclitaxel shows mid-frequency suppression from inhibited mitosis. The right-most graphs are the averaged responses from control media. (b) Bar chart of three biodynamic biomarkers: QDIP, SDIP, and APOP that capture symmetric and asymmetric frequency patterns, respectively, and apoptotic behavior. (c) Format for the time-frequency spectrograms.

Fig. 7

Average time dependence of the NSD [related to cellular activity through Eq. (3)] and the BB for the three growth techniques (BR, bioreactor; UB, U-bottom; and HD, hanging drop) responding to 10  μM paclitaxel. The NSD trends for A2780 and DLD-1 versus time are shown in (a) and (b). The normalized light scattering is shown in (c) and (d). The cellular activity is inhibited most strongly in the BR case, although the light scattering shows no consistent trends for the two cell lines. The average response times to Taxol are ∼3  h.

Fig. 8

Mitotic index change caused by the application of 10  μM paclitaxel shown as a function of time for (a) A2780 and (b) DLD-1. The response time of ∼3  h for each cell line is almost identical for the three growth methods.