Strain and rate-dependent neuronal injury in a 3D in vitro compression model of traumatic brain injury

Abstract

In the United States over 1.7 million cases of traumatic brain injury are reported yearly, but predictive correlation of cellular injury to impact tissue strain is still lacking, particularly for neuronal injury resulting from compression. Given the prevalence of compressive deformations in most blunt head trauma, this information is critically important for the development of future mitigation and diagnosis strategies. Using a 3D in vitro neuronal compression model, we investigated the role of impact strain and strain rate on neuronal lifetime, viability, and pathomorphology. We find that strain magnitude and rate have profound, yet distinctively different effects on the injury pathology. While strain magnitude affects the time of neuronal death, strain rate influences the pathomorphology and extent of population injury. Cellular injury is not initiated through localized deformation of the cytoskeleton but rather driven by excess strain on the entire cell. Furthermore we find that, mechanoporation, one of the key pathological trigger mechanisms in stretch and shear neuronal injuries, was not observed under compression.

Figure 1. 3D in vitro neuronal compression model.

(a) Schematic representation of the cell compression device fitted onto a confocal microscope for spatiotemporal cell injury analysis. (b) Schematic representation of the 3D collagen culture system. Linear motion of the voice coil actuator piston drives the displacement of the cover slip, inducing far-field compressive deformation in the collagen culture. (c) Maximum intensity confocal micrographs of collagen culture at 7 days in vitro. Neurons are stained with calcein AM. Scale bar, 50 µm. (d) Maximum intensity projection of a neuron (green) encapsulated in a dense fibrillar collagen matrix (magenta) imaged with confocal reflectance microscopy. Scale bar, 50 µm. (e) Impact strain profiles generated by the cell compression device used in this study.

Figure 2. Characterization of the applied far-field compressive strain, E^∞, under quasistatic (10⁻⁴) loading.

(a) Maximum intensity confocal micrographs of a collagen gel embedded with neurons (green) and 0.5 µm fluorescent beads (blue) used to characterize the deformation field. Two neurons are tagged (magenta arrowheads) to show the incremental compression of the collagen. Scale bar, 50 µm. (b) Plot of the mean and standard deviation of the transverse (E₁₁, blue triangle and E₂₂, red square) and axial (E₃₃, black circle) components of the mean Lagrangian strain tensor per loading increment as computed from the volumetric images shown in (a) using fast iterative digital volume correlation. (c) Contour plot of the vertical displacement, u₃, in the collagen matrix surrounding the neurons (green). Scal bar, 50 µm. (d) Zoomed-in view of the data subset (white box) shown in (c). Scale bar 20 µm.

Figure 3. Morphological injury assessment after compressive impact.

Maximum intensity projections of three representative neurons stained with calcein AM after mechanical loading at (top) and (middle), and a no-impact control. Arrows (magenta) indicate locations of bleb formation. Scale bars, 20 µm.

Figure 4. Analysis of the local and mean axial strains.

(a) Computed local compressive axial strain E_c for a representative neuron. Scale bar, 20 µm. (b) Maximum intensity projection of the same neuron shown in (a) stained with calcein AM 8 hrs after impact at (bottom). Scale bar, 20 µm. (c) (left) Axial shear strain E_s at each bleb location for eight neurons at . Alternate shading (light blue) pattern denotes data points for each cell at . (center) Corresponding cumulative probability distribution function with box and whisker plot. Probability of finding a bleb given a certain value of E_s is multiplied by 64% (the percentage of bleb formation at ). (right) Corresponding histogram normalized by total count. (d) The same computation in (c) for the compressive axial strain E_c. (e) Stacked bar plots of the percentage of neuron death for (n = 46, N = 5) and (n = 45, N = 8) for cells exhibiting non-bleb (white) and bleb (gray) formation. Dead neuron percentages were normalized by the 7 days in vitro control viability (see Supplementary Fig. S1). (f) Mean axial shear strain 〈E_s〉 computed for all cells exhibiting bleb formation at (yellow diamond, n = 7) and (purple triangle, n = 12), non-bleb formation at (orange circle, n = 14) and (black square, n = 8) as a function of time of cell death, t_d. (g) Mean compressive axial strain 〈E_c〉 computed for all cells exhibiting bleb formation at (yellow diamond, n = 7) and (purple triangle, n = 12), non-bleb formation at (orange circle, n = 14) and (black square, n = 8) as a function of time of cell death, t_d. The ellipse (green) represents an isocontour at 95% confidence of the bivariate normal distribution fit with mean value μ and major and minor axes a₁ and a₂. (inset) Contour map of the bivariate probability density p of all data points (green circle).

Figure 5. Cell permeability after compressive impact.

(a) Minimum intensity projections of a representative neuron showing the spatiotemporal intensity distribution of cell-impermeant Alexa Fluor 568 hydrazide (AFH) after compression at strain rates of 10 s⁻¹ (top) and 75 s⁻¹ (bottom). Scale bar, 20 µm. (b) Mean fluorescence intensity within the cell boundary (inset) for (solid triangle), (solid circle), a positive control (long dash) with Triton X-100, and a negative control (short dash) without compressive loading. Scale bar, 20 µm. (c) AFH influx time (mean ± standard deviation), or peak rise in internal fluorescence, for (solid white; n = 16 cells, N = 5 experiments) and (solid gray; n = 23, N = 8), and cellular death time for (hatched white; n = 19, N = 8) and (hatched gray; n = 22, N = 8). No significant difference was found via t-test comparison.