Single-cell, high-throughput analysis of cell docking to vessel wall

Abstract

Therapeutic potential of mesenchymal stem cells (MSCs) has been reported consistently in animal models of stroke, with mechanism mainly through immunomodulation and paracrine activity. Intravenous injection has been a prevailing route for MSCs administration, but cell quantities needed when scaling-up from mouse to human are extremely high putting into question feasibility of that approach. Intra-arterial delivery directly routes the cells to the brain thus lowering the required dose. Cell engineering may additionally improve cell homing, further potentiating the value of intra-arterial route. Therefore, our goal was to create microfluidic platform for screening and fast selection of molecules that enhance the docking of stem cells to vessel wall. We hypothesized that our software will be capable of detecting distinct docking properties of naïve and ITGA4-engineered MSCs. Indeed, the cell flow tracker analysis revealed positive effect of cell engineering on docking frequency of MSCs (42% vs. 9%, engineered vs. control cells, p < 0.001). These observations were then confirmed in an animal model of focal brain injury where cell engineering resulted in improved homing to the brain. To conclude, we developed a platform to study the docking of cells to the vessel wall which is highly relevant for intraarterial cell targeting or studies on neuroinflammation.

Introduction

Mesenchymal stem cells (MSCs) were shown to be therapeutic in animal models of stroke, regardless of the delivery route.¹ However, certain routes have important limitations in the acute stage of stroke. For intravenous delivery, the therapeutic effect is dose-dependent and requires very large cell doses that are difficult to achieve clinically.² Furthermore, the high doses may lead to pulmonary embolism.³ Intraparenchymal deliveries require neurosurgery, and, on admission, patients with stroke receive blood-thinning agents; thus, they are poor candidates for surgeries due to the high risk of intracerebral hematoma formation. In contrast, blood thinning facilitates intra-arterial interventions. The recent advances in thrombectomy have rapidly revolutionized the effective management of stroke beyond the acute phase,⁴ thus it has provided substantial support for intra-arterial procedures. Following that path, there is a significant effort to design post-thrombectomy intra-arterial adjuvant therapies.⁵ Intra-arterial delivery of MSCs at optimized, low dose has already been shown effective in a rodent model of stroke.⁶ However, the low engraftment rate⁷ requires strategies that would increase docking and transmigration of intra-arterially delivered stem cells to further advance the therapeutic effects. It was shown initially that neural stem cells (NSCs) sorted for the high expression of integrin alpha 4 (ITGA4), a subunit of the VLA-4 heterodimer adhesion molecule, more effectively engrafted after intra-arterial delivery, which translated to a better behavioral effect in a mouse stroke model.⁸ In further studies, the expression of both subunits of VLA-4 was achieved in glial-restricted precursors (GRPs) through DNA plasmid-based genetic engineering, and both docking to the inflamed endothelium⁹ and transmigration¹⁰ were demonstrated in an animal model of stroke. MSCs abundantly express the integrin β₁ subunit (ITGB1),¹¹ but scarcely express ITGA4, which is required to produce the complete VLA-4 heterodimer. Since DNA plasmid-based transfection is challenging in MSCs, we have developed an mRNA-based strategy to express ITGA4 in MSCs.¹² Here, we studied the docking of mRNA-ITGA4-engineered MSCs in an in vitro model of inflamed endothelium and in vivo in animals with focal brain injury.

To date, in vitro microfluidic assays were used to study the docking properties of stem cells, but the analysis was manual, tedious, and time-consuming, which prevented large-scale studies. Therefore, our goal was to create a robust and stringent platform for the evaluation of molecules enhancing vascular capture and homing of stem cells. We hypothesized that overexpression of ITGA4 in hBM-MSCs would improve their docking ability and we validated our experimental setup comparing their properties against native cells. For this purpose, we have developed advanced software for automated, high-throughput, and comprehensive analysis of cell interactions using a surface of VCAM-1 coated microfluidic channels, and have validated it against a manual procedure. Large numbers of cells are simultaneously tracked and the entire flow and docking phases are captured, including rolling, arrest, and crawling. Molday ION Rhodamine B™ (MIRB; BioPAL) was selected as a cell tag due to its neutrality to MSCs,¹³ as well as dual fluorescent (rhodamine) and magnetic (iron oxide) properties that are convenient for cell tracking both in a microfluidic assay (fluorescence) and after transplantation in animals (MRI). We have considered several cell sources to be used in this study. While NSCs seem to be an optimal choice for therapeutic intervention in the central nervous system; however, to date, majority of studies report trophic and immunomodulatory effect rather than neuronal replacement as primary therapeutic mechanisms. Previous work with NSCs indicates that long-term survival and integration with host tissue are not observed and therapeutic effects could rather be linked to the paracrine activity.¹⁴ With this evidence, it was prudent to switch to MSCs, which are known for paracrine and immunomodulatory potential, as well as they are easily obtainable from various sources such as bone marrow, adipose tissue and others. Moreover, the extensive meta-analysis of preclinical studies supports the therapeutic value of MSCs.¹ We previously established mRNA-based engineering of MSCs to overexpress the adhesion molecule ITGA4,¹² which has been shown formerly to play an important role in docking to the vessel wall⁹ and transmigration of cells from vessels to the brain parenchyma.¹⁰

Material and methods

Experimental design

Initially, the hBM-MSCs were engineered with mRNA-ITGA4 and the functionality of the ITGA4 protein, including proper routing to the cellular membrane, was confirmed by flow cytometry. We then established a microfluidic assay and generated the necessary data to develop a software program for single-cell, high-throughput, real-time analysis of cell docking in a model of activated blood vessel, with subsequent validation against the manual analysis. In the next step, we compared the interaction of mRNA ITGA4 engineered and naïve hBM-MSCs in a microfluidic model of activated blood vessel, and, finally, we compared the docking of engineered versus naïve cells in an animal model of focal brain injury (Figure 1).

Figure 1.

Experimental study design. Initially, the hBM-MSCs were engineered with mRNA-ITGA4 and the functionality of the ITGA4 protein was analysed. We established a microfluidic assay and generated the necessary data to develop a software program for single-cell, high-throughput, real-time analysis of cell docking in a model of activated blood vessel, with subsequent validation against the manual analysis. In the next step, we compared the interaction of engineered and naïve hBM-MSCs during the flow in channel microfluidic chamber coated with VCAM-1, and, finally, we compared the docking of engineered vs. naïve cells in an animal model of focal brain injury.

MSC culture and labeling

Human bone marrow mesenchymal stem cells (hBM-MSCs; Lonza) were seeded in 75 cm² flasks with MSCBM medium (Lonza) supplemented with 10% MCGS, L-glutamine, and gentamicin at a cell density of 1 × 10⁴/cm², grown to 70% of confluence at 37℃ and 5% CO₂, and passaged five to six times until used for experiments. The labeling was performed through overnight incubation with MIRB at a concentration of 20 µg Fe/ml.

Induction of alpha 4 (ITGA4) integrin expression in hBM-MSCs using mRNA transfection

MIRB-labeled hBM-MSCs were washed three times with PBS and transfected with ITGA4-mRNA as previously described by us.¹² Briefly, The ITGA4 gene cDNA was cloned to the pSP72 vector (P2191-Promega) and used as a template for mRNA production in vitro with the mMessage mMachine® T7 Ultra Kit (AM1345, Ambion), which included an anti-reverse-cap-analogue (ARCA cap). Then, mRNA-ITGA4 was mixed with Lipofectamine 2000 and incubated for 20 min at RT for lipoplex formation, and then was added to the hBM-MSC culture. After 4 h of incubation, the lipoplex-containing medium was removed and replaced with standard medium (see above) and cells were kept for additional 4–6 h to allow for ITGA4 protein production and transport to the membrane of the ITGA4 protein.

Flow cytometry of mRNA-ITGA4-engineered hBM-MSCs

Control or mRNA ITGA4-transfected MSC at 4, 8, 12, and 24 h after transfection were harvested with trypsin, suspended in PBS, centrifuged twice at 1200 r/min and fixed in 2% PFA over 10-min incubation with shaking (1000 r/min). Cells were washed twice by centrifugation at 1200 r/min, suspended in PBS, and stored in 4℃ for 4–6 h for flow cytometry analysis. Directly before the analysis, cells were incubated for 40 min with antibody solutions: BV421 mouse anti-human α4 (CD49d, BD), and APC mouse anti-human (CD90, BD) (1:200) containing 1% BSA. Unbound antibodies were removed with two washes by centrifugation. Samples were analysed on a BD Canto II cytometer using FACSDiva software (BD). The percentage of ITGA4 (CD49d)-positive cells and the intensity of fluorescence was measured and expressed as a median for 1 × 10⁴ cells in three repeats.

Microfluidic cell adhesion assay

The syringe was placed in an infusion/withdrawal GenieTouch™ Syringe Pump (Kent Scientific), and silicone tubing (Dow Corning Silastic) was used for coupling with the outlet port of a custom-made microfluidic chamber. The channels of the microfluidic device were covered with Recombinant Human VCAM-1 Protein (Life Technologies). The coating was accomplished by perfusion of 10 µg/ml VCAM-1 over 1.5 h followed by a 15-min wash with distilled water. To reduce non-specific cell binding, VCAM-1-coated channels were incubated for 1 h with 1% BSA followed by a PBS wash. The mRNA-ITGA4- (8–10 h after transfection), or naive hBM-MSCs labeled with MIRB, were introduced into the inlet port of the microfluidic chamber using a pipette and perfused through the channel over 10 min at a physiologic wall shear stress of 1 dyne/cm². The experiments were recorded as movies at a high frequency of 250 Hz using a semi-confocal Colibri system with LED as the light source in a 540–580 nm spectrum installed on a Cell Observer SD microscope (Carl Zeiss Inc). The acceleration of image capture was achieved by 3 × 3 binning.

Analysis of MSC interactions with the surface of microfluidic channels

We performed an analysis of three independent perfusion experiments for both the control and mRNA-ITGA4-transfected hBM-MSCs.

MSC interactions with a model of activated blood vessel

Transit speed was calculated based on the average distance travelled by a single cell between the consecutive frames, and this was a main readout used to determine various types of interactions between MSCs and VCAM-1. We distinguished four types of interactions: (1) no interaction (characterized by high transit speed with no declines below one pixel per frame); (2) cell arrest (docking) expressed as a decrease in cell movement velocity exceeding one pixel/frame); (3) rolling (defined as a cell velocity preceding its arrest); and (4) crawling (defined as a cell velocity after the arrest of the cell).

Development of software for high-throughput analysis of MSC interactions

We used C# language, the.NET framework, and the MVVM (Model-View-Viewmodel) pattern to develop dedicated software (cell flow tracker) for automatic analysis of MSC – VCAM-1 interactions in microfluidic channels based on the recorded videos. Connected-component labeling algorithm was used to analyze objects, which are called blobs and correspond to single cells. The movement of blobs between frames is detected based on matching blobs through defined criteria: (1) major – distance between blobs; and (2) minor – image moments and blob boundaries. After contest, the best matching frames added to the blob sequence, which represents object movement. This application requires Windows and the.NET Framework 4. It allows a user to process video frames, and detect and analyze objects (blobs) flowing through visible areas. The workflow of cell flow tracker consists of: (1) loading a video file; (2) reading the current video frame (image) to bitmap using the Video for Windows framework; and (3) analyzing a frame and detecting blobs. The application performs a statistical analysis of blob speed and a simple analysis to mark blobs that stopped in the visible area, and provides an option for correcting sequences by adding or removing blobs, as well as cropping or merging sequences. Moreover, sequences can be filtered by multiple parameters, such as duration (in frames) and speed (standard deviation, mean, median, minimum and maximum values). There is also the functionality to export sequences as videos with marked relevant blobs and as CSV files that can be imported into an excel spreadsheet. Therefore, the cell flow tracker allows for instant measurement of cell velocities. Applying thresholds at various speeds provides an insight into the time course of cell interaction with VCAM-1.

Validation of cell flow tracker

The automatic measurement capability of the cell flow tracker was validated using ImageJ by manually assessing the distance a single cell travelled between each frame on the movie. A multi-point tool was used to mark tracked cells on each frame, with a straight freehand line to measure the distance. The comparison was performed for cells from five videos (20 cells per each movie) and the analysis was performed in five independent trials.

Analysed variables

We quantified and compared the movement pattern of the control and ITGA4-MSCs based on cell flow tracker output. Three records for each cell group were analysed. We compared (1) the percentage of cells subjected to arrest, (2) the time period of the arrest, and (3) the average speed of flowing cells. Moreover, we investigated the incidence of rolling and crawling. Due to the fact that one frame of each movie is an equivalent to 4 ms, we assigned all arrested cells to four groups with an arrest period in the range of: (1) 4–40 ms; (2) 40–400 ms; (3) 400–4000 ms; and (4) >4000 ms. Then, we defined the percentage of cells in each of these groups, assuming the population of all arrested cells as 100%. Since we defined rolling as the deceleration of cell velocity leading up to attachment, rolling was investigated only in the group of cells that were previously identified as arrested cells. In order to investigate this phenomenon, we viewed the data strings describing the speed of arrested cells and identified the first frame where the distance travelled was lower than or equal to one pixel – defined as the beginning of the arrest. In further calculations, we used only data preceding this time interval and we assessed the average speed of these cells and ascribed it to rolling. We compared our results to the general average speed of all flowing cells in the same experimental/control group.

Crawling was described as an event following arrest, so it was investigated only within the group of cells that were previously identified as arrested. In order to investigate crawling, we analyzed the data strings describing the speed of arrested cells and identified the first and the following frames where the travelled speed was higher than one pixel – defined as the end of the arrest. We compared our results to the general average speed of all flowing cells in the same group (Supplementary Data Figure 1).

Cell size measurement

MSCs were harvested by trypsinization, centrifuged at 1200 r/min, and suspended in their culture medium. Cell suspension (50 µl) was transferred onto microscopy slides and cover-slipped. Phase contrast photomicrographs were acquired using an Axiovert 25 microscope (Zeiss) equipped with a monochromatic camera (Canon). The measurement of cell size was performed in ImageJ by manual marking of the cell circumference with a polygon tool. This study was performed in three independent trials for control and mRNA ITGA4-transfected cells.

Rat model of stroke

Animal experiments were performed in accordance with the Guidelines for the Care and Use of Laboratory Animals approved by the Institutional Animal Care and Use Committee of the Mossakowski Medical Research Centre, Warsaw, Poland and reported according to the ARRIVE (Animal Research: Reporting In Vivo Experiments) guidelines. Experimental protocols involving animals care and surgery were approved by the IV local ethics committee in Warsaw (agreement no 17/2012). Twelve adult male Wistar rats, weighing 250 g and housed in cages with a 12-h light-dark cycle and free access to food and water under standard humidity and temperature, were used in all experiments. The experiments were designed to use the smallest number of animals to minimize their suffering. The model was performed as previously described by us.¹⁴ Briefly, a burr hole was drilled in the skull and the needle (length 15 mm, gage 33), connected to a 10 μl syringe (Hamilton, Switzerland), was lowered into the right striatum (coordinates A 0.5, L 3.8, D 4.7 mm). Then, 1 μl of 5 nmol ouabain (Sigma, Poland) was injected into the brain at a speed of 1 µl/min using a microinfusion pump (Stoelting, USA). The needle was then withdrawn and the skin was closed with a suture. After the procedure, all animals were treated with an antibiotic (Baytril; Bayer; 0.4 mg/ml) and an analgesic (Rycarfa; Krka; 5 mg/ml).

Intra-arterial transplantation of hBM-MSCs

Intra-arterial infusion of hBM-MSCs was performed 48 h after the induction of focal brain injury as previously described by us.¹⁵ Briefly, under general anesthesia (2% isoflurane), the common carotid artery (CCA), the external carotid artery (ECA), and the internal carotid artery (ICA) were exposed and the occipital artery branching off the ECA was coagulated, the pterygopalatine artery branching off the ICA was ligated, as well as the proximal segments of the ECA and CCA. Then, the vascular clip (FT 180 T, Aesculap, Center Valley, PA, USA) was applied to the ICA proximal to the pterygopalatine artery to prevent backflow, the incision into the CCA was performed distal to the ligature, and the catheter was inserted into the CCA, followed by the suture tightening on the artery over the catheter to prevent bleeding. Then, the clip was removed, the animal was placed inside the gantry of the MR scanner and 5 × 10⁵ MIRB-labeled mRNA-ITGA-engineered or control (non-engineered genetically) hBM-MSCs suspended in 1 ml of PBS were injected at a safe speed of 0.2 ml/min.

Magnetic resonance imaging and quantitative image analysis

The infusion of hBM-MSCs was imaged with a 7T Biospec 70/30 MR scanner (Bruker), with a transmit cylindrical radiofrequency coil (8.6 cm inner diameter) and a rat brain-dedicated, receive-only array coil (2 × 2 elements) positioned over the animal’s head. Directly before and after transplantation, animals were imaged using a T2 sequence (RARE, TR = 4000 ms, TE = 58.5 ms, TA = 2 m8 s, FOV = 2.69/2.35, MTX = 256/128) to detect brain injury and with a T2* sequence (FLASH, TR = 500 ms, TE = 5 ms, FA = 40°, TA = 48 s, FOV = 2.69/2.35, MTX = 256/128) to detect injected cells. The docking of hBM-MSC was calculated as follows: in ImageJ, the polygon tool was used to outline, in each scan, ROIs that encompassed the left hemisphere (LH) area and the right hemisphere (RH) area from a particular rat before (before Tx) and after (after Tx) transplantation. The mean signal intensity within the ROI was measured. The change in signal intensity value caused by cell influx was calculated as: [before: (Tx LH – before Tx RH)] – [(after: (Tx LH – after Tx RH)]. Five slices in each of six rats per group were analysed. Person performing the calculations was not aware of the animal's assignment to the experimental or control group.

Statistical analysis and data presentation

The majority of statistical calculations (except correlations) were performed using PROC MIXED (SAS 9.4). The type III test of fixed effects was used to determine statistical significance, and the least mean square (LMS) difference test was employed for comparison between means. In cases justified by the data structure, the multilevel hierarchical mixed models with random and fixed variables were employed. If more than one variable was present in the model, multivariate regression was used to provide a variance of variables to better understand the sources of variability. The correlations were calculated using the r Pearson coefficient embedded within PROC CORR (SAS 9.4). The level of statistical significance was set at P < 0.05: P < 0.05 (*); P < 0.01(**); P < 0.001(***). The absolute values are presented as box plots with the upper and lower bounds of the box the first and third quartile, and the median drawn as a line inside the box. The whiskers extend from the box to the fences, which are placed at ± 1.5 interquartile range units. Data points beyond the fences are considered outliers and are shown as circles. The circles inside the boxes point to the means. The relative values (percentages) are shown as pie charts.

Results

ITGA4 expression in mRNA-engineered hBM-MSCs

We have found, based on flow cytometry, that the expression of ITGA4 in control hBM-MSCs was at 4% and it did not change over the first 4 h after transfection. Eight h after transfection, the number of ITGA4 (+) cells increased to 39% and reached a maximum level of 73% after 12 h and remained unchanged until 24 h (Figure 2(a) and (b)). However, the signal intensity of ITGA4 staining after the initial increases until 12 h, decreased by 24 h, which suggests the gradual decrease of protein synthesis (Figure 2(c)). Therefore, the peak of ITGA4 expression was at the 12-h time-point, and this time interval should be considered as optimal in the context of future in vivo and potentially clinical applications, as the diapedesis of MSCs is a process that requires several hours.¹⁶

Figure 2.

Flow cytometry of control and engineered hBM-MSCs at various time points after mRNA-ITGA4 transfection. The visual illustration of flow cytometry results (a), the graphical presentation of the percentage of ITGA (+) hBM-MSCs (b) and the changes in the fluorescence signal intensity generated by an antibody attached to the ITGA4 antigen on the surface of the cells (c).

Validation of cell flow tracker

The manual and automatic measurements of the distance that cells traveled between consecutive frames were highly correlated (r = 0.99, p < 0.001) (Figure 3(a)). The other analysis included the hierarchical multilevel model with the three hierarchically positioned random variables (1) videos, (2) single cells within each video, and (3) measurements of particular distances each cell traveled between frames. This did not show a difference between the manual and automatic method of measurement (df = 7004, F = 1.75, p < 0.19). Finally, multivariate regression with variables—video, cell measurement, and method (manual vs. automatic)—were performed (df = 6801), and, as expected, we observed differences between videos (F = 238.22, p < 0.001), including videos of engineered and control cells, between single cells within each video (F = 56.42, p < 0.001), and between measurements of distance each cell traveled between frames (F = 5.16, p < 0.001), but no difference was found between the methods of measurement (manual vs. automatic; F = 2.43, p = 0.11). Therefore, the use of three statistical methods provided strong evidence for the accuracy of cell flow tracker. We also illustrate the high overlap of velocity diagrams of single cells with their speeds sampled at a frequency of 250 Hz using both the manual and automatic methods (Figure 3(b)). The successful validation of the accuracy of the cell flow tracker legitimized the automation of the analysis of interactions of MSCs with VCAM-1, which is instrumental for single-cell, high-throughput, real-time analysis of a microfluidic assay.

Figure 3.

The correlation analysis of the distance traveled by single cells, assessed manually in the ImageJ program and automatically by the cell flow tracker software (a). The speed pattern curves of three random cells measured by the cell flow tracker (red line) and measured manually (blue line) (b).

In vitro docking of mRNA-ITGA4-engineered hBM-MSCs

We observed a few main kinds of hBM-MSCs movement pattern during flow through microfluidic chamber which resemble leukocytes diapedesis stages (flow, rolling, arrest, and crawling) (Figure 4).

Figure 4.

The example of movement patterns typical for hBM-MSCs during their interactions with microfluidic channels decorated with the VCAM-1 protein which resembles steps of the leukocyte transmigration process. The flow of unstopped cells (a), rolling (b), arrest (c), and crawling (d).

Cells in both experimental and control groups were capable of docking to the surface of microfluidic channels; however, the percentage of arrested cells was significantly higher in case of mRNA-ITGA4-engineered cells than control hBM-MSCs (42.01% vs. 9.41%, p < 0.001) (Figure 5(a)). There was no statistically significant difference between the mRNA-ITGA4-engineered cells and control cells in the length of arrest (p = 0.95), although there was a trend toward a longer arrest for control cells (Figure 5(b)). We have shown that a longer arrest was inversely correlated with the number of cells subjected to such arrest (r = −0.87, p < 0.001) (Figure 5(c)).

Figure 5.

The functional effects of mRNA-ITGA4 engineering of hBM-MSCs in vitro. The percentage of mRNA-ITGA4-engineered cells or control hBM-MSCs, which docked in the model of the activated vessel wall (a). The relative ratio of mRNA-ITGA4 engineered to control hBM-MSCs across ranges of the arrest lengths (b). The correlation between the percentage of docked cells and the length of their arrest (c).

We have observed that arrest phase was preceded by a lower velocity with irregularities, compared to the flow velocity of non-arrested cells, which corresponds to the occurrence of rolling in mRNA ITGA4 (p < 0.05) and control (p < 0.01) hBM-MSCs groups (Figure 6(a)). Similarly, the arrest was also followed by the lower velocity, which resembles crawling (mRNA ITGA4 transfected p < 0.01; control hBM-MSCs p < 0.001) in both experimental and control groups (Figure 6(b)). Surprisingly, the average speed of mRNA-ITGA4-engineered cells, as well as the average speed of rolling and crawling was higher than that in control cells (Figure 6(c)). We found no difference in cell size between the groups, which excluded the contribution of cell size to the observed differences in cell velocity (Figure 6(d)).

Figure 6.

Analysis of the movement dynamics of hBM-MSCs flowing through microfluidic chamber. The rolling of hBM-MSCs prior to their attachment compared to cell flow (a). The crawling of hBM-MSCs prior to their attachment compared to cell flow (b). The comparison of the average speed of mRNA-ITGA4-engineered cells to control hBM-MSCs (c). The comparison of cell size between mRNA-ITGA4-engineered cells and control hBM-MSCs (d).

In vivo docking of mRNA-ITGA4-engineered hBM-MSCs

MRI scans showed that intra-arterially infused cells were captured in the cerebral endothelium in the area of brain injury (Figure 6(a)). The quantitative analysis of acquired images confirmed in vitro findings that more mRNA-ITGA4-engineered hBM-MSCs docked to the inflamed cerebral vasculature, compared to control cells (Figure 7(b) and (c)).

Figure 7.

The comparison of in vivo docking efficacy between mRNA-ITGA4-engineered cells and control hBM-MSCs in an animal model of focal brain injury under MRI guidance. Examples of MR images (a). The quantification of docking efficacy in both mRNA-ITGA4-engineered cells and control hBM-MSCs (b), with a distribution of difference across brain cross-sections to illustrate the multilevel model used for statistical calculations (c) (control cell group n = 6, mRNA ITGA4 hBM-MSCs group n = 6).

Discussion

We have developed and validated a software application (cell flow tracker) capable of single-cell, high-throughput, real-time, fully automated analysis of the process of cell docking in vitro, using a microfluidic assay. The precise capture of cell transition distance at a frequency of 250 Hz provides a matrix of data from which various parameters can be calculated, such as arrest, rolling, crawling, and flow velocity. The software provides a high degree of flexibility, and additional customized parameters can be programmed. Therefore, the cell flow tracker adds a new dimension to studies of cell docking in a model of the arterial wall by enabling large-scale analyses of microfluidic assays.

We were the first to show that hBM-MSC docking can be enhanced through mRNA-ITGA4 engineering, and such modified cells can potentially be a valuable tool for regenerative medicine, including neurological disorders. To date, only blocking strategies have been used to study the interactions of hBM-MSCs in flow chamber assays, which provided not only basic knowledge, but also served as the basis for the current engineering-oriented study.¹⁷

In our study, we used the microfluidic model of activated endothelium consisting of a channel coated with VCAM-1 protein since this receptor is abundantly expressed on activated endothelial cells. Moreover, our aim was to investigate the mechanisms rely exclusively on the interaction between α4 integrin, which overexpression we induced by mRNA ITGA4 introduction and its main ligand VCAM-1 protein. The behavior of hBM-MSCs follows a movement pattern that is similar to the diapedesis of leukocytes through the blood–brain barrier (BBB), including rolling and crawling. This is in contrast to other reports, which did not find any interactions between mouse MSCs and mouse-activated endothelial cells, but their sampling frequency of 0.07 Hz was dramatically lower than in our system (250 Hz), so they certainly missed interactions that occurred within the time frame of milliseconds.¹⁸ These authors also did not investigate the presence of adhesion molecules on the surface of their population of MSCs. Mouse cells can also behave differently than human cells.

Our study focused on investigating initial steps of diapedesis as they are indispensable for transmigration and effective homing of cells administered intra-arterially. We successfully developed a system for fast and high quality assessment of stem cell docking after induced expression of adhesion molecules. This tool will facilitate effective screening and selection of most potent adhesion molecule combinations streamlining future studies on diapedesis.

We have shown that only 4% of hBM-MSCs naturally express ITGA4, while 9.4% of control cells were subjected to arrest, which suggests that these cells bear other mechanisms that allow them to anchor to the VCAM-1 protein. The homing efficacy of performed by us cell engineering is relatively high (42%) compared to that of control cells (9.4%). Moreover, there was no statistical difference in the length of arrest between mRNA-ITGA4-engineered cells and control cells.

We have validated our in vitro results with in vivo experiments showing the functionality of our system. This will be of interest for others who utilize various engineering approaches and/or other cell types to precisely tune their properties prior to in vivo applications. Therefore, our system meets the growing interest in the intra-arterial route of stem cell delivery in neurological disorders. Indeed, intraarterial injection facilitates selective and precise delivery, bypassing the systemic circulation, and thus, enabling a lower cell dose and preventing systemic adverse effects, including pulmonary embolism. Intra-arterial administration is associated with the risk of micro-embolism due to the occlusion of small diameter vessels in the brain caused by injected cells. We previously reported formation of microemboli in stroke animal models together with decreased cerebral blood flow during infusion.¹⁹ However, other of our studies indicate that it is possible to avoid undesirable side effects of intra-arterial administration by precise adjustment of the amount and speed of infusion in relation to the size of the transplanted cells.²⁰ In the current study, we used injection parameters elaborated by us which were safe in this particular experimental design and we did not observe any signs of micro-embolism formation after transplantation. Introduction of the catheter into the artery can disturb laminar flow which further may lead to inhomogeneous distribution of transplanted cells due to streaming effect.^21,22 However, this challenge can be managed by monitoring of intra-arterial stem cell delivery in real-time using MRI.¹⁵

The advantage of our mRNA-based ITGA4 induction method is that only one protein is required to enhance the docking, while others have shown the need for three proteins to achieve positive results.²³ Such an approach is much more difficult from the technical and regulatory point of view to be translated into the clinic for the benefit of patients.

In a rat model, a relatively good number of control hBM-MSCs stopped in the cerebral vasculature, which could indicate that some cells can be passively entrapped, a phenomenon reported by others,²⁴ but still, mRNA-ITGA4 engineering provided a statistically significant increase of homing.

Limitations

Our system enables the study of cell docking to VCAM-1, which initiates extravasation; however, for in vitro execution of the entire process of diapedesis, a more complex microfluidic system needs to be developed. Nevertheless, our software should be flexible enough to add the additional commands required for highly efficient quantification of the process of diapedesis. In vivo, we have also focused on the validation of the process of docking in the acute setting, and additional studies are needed to investigate the entire process of diapedesis and the potential gain in therapeutic effect.

Conclusions

The cell flow tracker software that we developed and validated is a precise and reliable tool with which to study the interactions of flowing cells, such as rolling, docking (arrest), and crawling, with decorated microfluidic channels at the single-cell level, with high-throughput analysis that enables large-scale experiments. We used the cell flow tracker to prove that the overexpression of ITGA4 by the introduction of exogenous mRNA leads to proper routing and a functional receptor on the surface of hBM-MSCs, resulting in enhanced docking in vitro. Furthermore, the efficacy of mRNA-ITGA engineering was confirmed in vivo after intra-arterial administration of hBM-MSCs in an animal model of focal brain injury where modified hBM-MSCs revealed increased brain homing ability. The higher accumulation of systemically transplanted hBM-MSCs in the area of injury achieved due to mRNA ITGA4 transfection can potentially enhance the effect of stem cells treatment; however, this hypothesis has to be verified in separated study.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by NCR&D grant EXPLORE ME within the “STRATEGMED I” program and by NIH R01 NS091100-01A1. MRI experiments carried out with the use of the CePT infrastructure were financed by the European Union – the European Regional Development Fund in the Operational Programme “Innovative Economy” for 2007–2013.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Authors’ contributions

MJ, BL and PW designed the initial project. AN carried out the hBM-MSCs culture and mRNA-ITGA4 transfection. AA prepared the microfluidic platform and performed microfluidic experiments. TG developed the microfluidic experiments recording protocol. AA and SD performed stereotaxic surgeries and intra-arterial cells transplantations. JO carried out MRI scans and together with AA conducted MRI pictures analysis. MJ performed the statistical analysis of all data. MJ, BL, PW and AA analyzed and interpreted data from all experiments and prepared the initial manuscript. All authors contributed to manuscript processing.

Supplementary material

Supplementary material for this paper can be found at the journal website: http://journals.sagepub.com/home/jcb