Investigation of wound healing process guided by nano-scale topographic patterns integrated within a microfluidic system

<div><p>When living tissues are injured, they undergo a sequential process of homeostasis, inflammation, proliferation and maturation, which is called wound healing. The working mechanism of wound healing has not been wholly understood due to its complex environments with various mechanical and chemical factors. In this study, we propose a novel <i>in vitro</i> wound healing model using a microfluidic system that can manipulate the topography of the wound bed. The topography of the extracellular matrix (ECM) in the wound bed is one of the most important mechanical properties for rapid and effective wound healing. We focused our work on the topographical factor which is one of crucial mechanical cues in wound healing process by using various nano-patterns on the cell attachment surface. First, we analyzed the cell morphology and dynamic cellular behaviors of NIH-3T3 fibroblasts on the nano-patterned surface. Their morphology and dynamic behaviors were investigated for relevance with regard to the recovery function. Second, we developed a highly reproducible and inexpensive research platform for wound formation and the wound healing process by combining the nano-patterned surface and a microfluidic channel. The effect of topography on wound recovery performance was analyzed. This <i>in vitro</i> wound healing research platform will provide well-controlled topographic cue of wound bed and contribute to the study on the fundamental mechanism of wound healing.</p></div

Wound generation and healing processes in the microfluidic devices.

<p><b>(A)</b> Schematic of wound formation and healing processes in a nano-pattern integrated microfluidic device. First, the wound is formed due to the layered flow of trypsin/EDTA. The enzyme induces cell detachment from the nano-patterned surface within a selective region. Trypsin/EDTA is replaced with culture medium after wound formation is finished. Leading cells on the wound edge recover into the cell-free area (wound healing process). <b>(B)</b> Micrographs of the wound formation and healing processes. Sequentially, from the top: the cell culture, wound formation and wound healing stages.</p

Cell culture on various nano-pattern densities.

<p><b>(A)</b> SEM images of the nano-patterns (1:1, 1:2 and 1:5). Dimensions of the nanostructure were measured as width 560 ± 20 nm and depth 325 ± 3 nm. The gap between the structures varies for each case. A gap equal to the width of the nanostructure was considered the 1:1 ratio nano-pattern. Further, we constructed 1:2 and 1:5 ratio nano-patterns in which the dimension of the gap was 2 or 5 times broader than the width of the ridge. <b>(B)</b> Microscopic images of NIH-3T3 fibroblasts cultured on the nano-pattern (cell density = 300–400 cells/mm², scale bar = 100 μm). <b>(C)</b> Fluorescence images of stained cells on nano-patterned surface using nuclei (DAPI) and F-actin (Phalloidin).</p

Cell migration on nano-patterned surfaces.

<p><b>(A)</b> Micrographs of NIH-3T3 fibroblast migration on the nano-patterned surfaces. Colored lines indicate the distance and orientation of cell migration. After cell seeding, cell movements were captured every 2 hours for 6 hours. <b>(B)</b> Distribution of cell migration orientation and distance (n = 39). Orientation angle was the averaged value, and distance was summed over 3 measurement points over a total of 6 hours. <b>(C)</b> Average values of the migrated distance and orientation of cells cultured on nano-patterns and the control surface (n = 39, **p < 0.01).</p

Nano-pattern integrated microfluidic system used to reproduce the wound healing process.

<p><b>(A)</b> CAD design of the microfluidic device, which includes 2 inlets, 1 outlet and a cell culture region. <b>(B)</b> Process used to fabricate the microfluidic channel and nano-pattern. The device and nano-patterns were irreversibly combined through plasma bonding methods. <b>(C)</b> 3D image of the combined microfluidic device with the nano-pattern. Schematic of the <i>in vitro</i> wound formation process in the microfluidic channel using the layered flow of trypsin/EDTA. Due to trypsinization, cells detached from the microfluidic channel, allowing the selective formation of a cell-free area.</p

Orientation and elongation of cells on the nano-patterns.

<p>NIH-3T3 fibroblasts on nano-patterns were investigated based on their elongation and orientation following two indices to validate the contact guidance effect from various densities of nano-patterned surfaces. <b>(A)</b> Definition of the indices for cell body orientation and elongation. Orientation angle, <i>θ</i>, is the angle between the nano-pattern and longitudinal length of the cell body. Elongation index, <i>E</i>, is the aspect ratio of the long axis to the short axis of the cell body. <b>(B)</b> Orientation angle and elongation index of cells on the various nano-patterns: 1:1, 1:2 and 1:5 nano-pattern ratios and control (no-pattern). Cellular shape was captured using a microscope at 12 and 24 hours after cell seeding. Average values of <b>(C)</b> orientation angle, <i>θ</i>, and <b>(D)</b> elongation index, <i>E</i> (n = 30, *p < 0.05 and **p < 0.01).</p

Computational Simulation of the Activation Cycle of Gα Subunit in the G Protein Cycle Using an Elastic Network Model - Fig 3

<p><b>Mobility change of Gαs after the initial binding to β</b>_<b>2</b><b>AR either at the C-terminus (A) or the N-terminus (B).</b> The theoretical value at each residue was calculated by mean squared fluctuation between Gαβγ(GDP) and pre-R-Gαβγ(GDP) in percentile and is displayed according to the indicated color map. The residue in blue (red) is considered to become rigid (flexible). (C) Schematic of the proposed binding event between Gαs (gray) and β₂AR (blue). Activated β₂AR may initially be bound to the N terminus of Gα, leading to a relatively flexible C terminus, which increases the probability that it will find its proper binding position to the receptor. Eventually, this binding event is completed by the C terminal binding.</p

Topological changes of the Gαs protein upon β₂AR binding.

<p>The Gαs structures in the Gαβγ(GDP) and R-Gαβγ(GDP) states are colored in gray and red, respectively. (A) Comparison of the structures of Gα with and without β₂AR. Compared to the GαsAH domain, the GαsRas domain shows marked displacement. (B) Topological change (displacement and torsional angle) of Gαs upon β₂AR binding. (C) The receptor-binding interface of Gαs. The distance between the α5 helix and α4-β6 decreases to 7 Å, which is within the interaction range. Red dotted lines represent new interactions between α5 helix and α4-β6 (D) Nucleotide-binding pocket (switch 2, P-loop, β6-α5 loop, and α5 helix). A significant change in the topology occurs near the nucleotide-binding pocket. The directions of movement of the α5 helix and P-loop are indicated by the yellow arrows.</p

Role of GTP and its hydrolysis in Gαs mobility.

<p>(A) Change in mean squared fluctuation of Gαs in R-Gαβγ(0) following the addition of GTP. Receptor binding regions (N terminus, C terminus, α4-β6 loop) and Gβγ binding regions (switch 2) became highly mobile for easy dissociation of bound structures. In contrast, the mean squared fluctuation values of nucleotide-binding pocket regions (P-loop, switch 1) decreased, thereby blocking the opening motion between the two sub-domains of Gαs. (B) Change in mean squared fluctuation of Gαs following formation of Gαβγ(GDP) relative to Gαs in Gα(GTP). The change in mobility reflects the effects that GTP hydrolysis and Gβγ binding have on Gα.</p

Ribbon diagrams of various components of the β₂AR-Gs heterodimer complex.

<p>(A) β₂AR is shown in blue, Gαs in gray, Gβs in green, Gγs in cyan and GDP in magenta. (B) Gαs structure represented by its major components for G protein activation. (C) β₂AR-binding interface of GαsRas.</p