Tunable and Reversible Substrate Stiffness Reveals Dynamic

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Biological and Medical Applications of Materials and Interfaces

Tunable and Reversible Substrate Stiffness Reveals Dynamic Mechanosensitivity of Cardiomyocytes Elise Corbin, Alexia Vite, Eliot G Peyster, Myan Bhoopalam, Jeffrey Brandimarto, Xiao Wang, Alexander I Bennett, Andy T Clark, Xuemei Cheng, Kevin T. Turner, Kiran Musunuru, and Kenneth Margulies ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.9b02446 • Publication Date (Web): 10 May 2019 Downloaded from http://pubs.acs.org on May 11, 2019

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ACS Applied Materials & Interfaces

Tunable and Reversible Substrate Stiffness Reveals Dynamic Mechanosensitivity of Cardiomyocytes Elise A. Corbin1,2,3,†, Alexia Vite3,†, Eliot G. Peyster3, Myan Bhoopalam4, Jeffrey Brandimarto3, Xiao Wang3, Alexander I. Bennett5, Andy T. Clark6, Xuemei Cheng6, Kevin T. Turner5, Kiran Musunuru3, and Kenneth B. Margulies3,* Department of Biomedical Engineering, University of Delaware, Newark, DE, 19716 Department of Materials Science and Engineering, University of Delaware, Newark, DE, 19716 3 Department of Medicine, Division of Cardiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104 4 School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, 19104 5 Department of Mechanical Engineering and Applied Mechanics, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, 19104 6 Department of Physics, Bryn Mawr College, Bryn Mawr, PA, 19010 1 2

E. A. Corbin and A. Vite contributed equally to this work * Corresponding author email: [email protected] †

Abstract New directions in material applications have allowed for fresh insight into the coordination of biophysical cues and regulators. While the role of the mechanical microenvironment on cell responses and mechanics is often studied, most analyses only consider static environments and behavior, however, cells and tissues are themselves dynamic materials that adapt in myriad ways to alterations in their environment. Here, we introduce an approach, through the addition of magnetic inclusions into a soft PDMS elastomer, to fabricate a substrate that can be stiffened nearly instantaneously in the presence of cells through the use of a magnetic gradient to investigate short-term cellular responses to dynamic stiffening or softening. This substrate allows us to observe time-dependent changes, such as spreading, stress fiber formation, Yesassociated protein translocation, and sarcomere organization. The identification of temporal dynamic changes on a short time-scale suggests that this technology can be more broadly applied to study targeted mechanisms of diverse biologic processes, including cell division, differentiation, tissue repair, pathological adaptations, and cell-death pathways. Our method provides a unique in vitro platform for studying dynamic cell behavior by better mimicking more complex and realistic microenvironments. This

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platform will be amenable to future studies aimed at elucidating the mechanisms underlying mechanical sensing and signaling that influence cellular behaviors and interactions.

Introduction Non-physiological, stiff materials have been the primary substrates for understanding cell-based processes in vitro. However, it has become increasingly clear that these materials fall short in recapitulating the in vivo cellular microenvironment1–3. The physical properties of the extracellular matrix (ECM), including stiffness and viscoelasticity, play key roles in the development of hypertensive and hypertrophic cardiac diseases at the cellular level that affect the morphology and function of heart tissue4. Specifically, ECM stiffness is a key determinant of cellular properties in cardiomyocytes (CM) and cardiac fibroblasts including, but not limited to, cell spreading5, fibroblast activation6, cardiomyocyte contractility7, Yesassociated protein (YAP) activation4,5, and actin filament organization8. The ECM is a dynamic structure that is continuously changing in both normal9 and diseased10–12 tissue. Our understanding of cells sensing their mechanical environment has evolved in complexity to include responses to topographic cues13,14 and material stress relaxation5,15, but it also appears that cells have a memory of past environments16–18, indicating a temporal dependence of the cell-environment interaction. Incorporating different time-scales in studying mechanical regulation has emerged as an important concept in the interrogation of cellular signaling through in vitro microenvironments. Recently, there has been interest in developing in vitro systems with tunable material stiffness through a variety of approaches, including applying light1, changes in temperature19,20, changes in pH21,22 or addition of biomolecules23–25. Phototunability of hydrogels is one strategy to initiate controlled crosslinking1 or degradation26, leading to stiffening or softening of the material, respectively. These methods, however, allow only permanent, unidirectional changes in stiffness, or, in the case of one photoswitchable hydrogel27, bidirectional stiffness change can only occur once and does not offer repeated stiffening and softening. In this paper, we overcome the limitations of previous unidirectional and irreversible materials by instead controlling stiffness via applied magnetic fields to a magnetorheological 2


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elastomer (MRE) – an elastomeric polymer with embedded iron particles. Applied magnetic field gradients induce rapid stiffening of the MRE material that then rapidly relaxes back to its soft ground state when the magnetic field is removed. Thus, this material stiffness control is rapid, reversible, and tunable in that different stiffnesses can be generated simply by varying the magnitude of the applied magnetic field gradient. These MRE materials offer unique capabilities ideal for studying mechanosensing and mechanotransduction pathways by quickly modulating the stiffness of the surrounding environment. In particular, there is a growing interest in how the phenotype of cardiac cells differ and change based on substrate stiffness7,28,29. Such stiffness changes are possible in vivo: normal myocardium has an elastic modulus of 10-15 kPa whereas diseased myocardium – such as following myocardial infarction – can have stiffnesses ranging from 35-70 kPa28. Embryonic cardiomyocytes cultured on a material with stiffness akin to normal myocardium preserve their differentiated state and beat, and neonatal cardiomyocytes elongate with myofibril alignment, as compared to cultures on non-physiologically stiff substrates7,29–31. Whereas cardiomyocytes cultured on substrates with pathologic stiffness manifest fewer striations, decreased beating frequency, and lower proportions of contracting cells7. While the role of the mechanical microenvironment on cell responses and mechanics is often studied, most analyses only consider static environments and behavior; however, cells and tissues are themselves dynamic. Examples of dynamic changes include the loading difference during in vivo development and adaptation to stiffening or softening during disease progression or regeneration of function32–34. Here, we investigate the role of short-time-scale, reversible, biomechanical transients on humanderived induced pluripotent stem cell cardiomyocytes (iPSC-CMs) and fibroblasts. Human-derived iPSCs are a unique and promising translational tool for studying human disease35–37 and can be differentiated into every type of tissue including cardiomyocytes and cardiac fibroblasts that comprise human cardiac tissue. In these studies, we use a 2D active stiffening and softening system to evaluate mechanosensing responses in these cells separately. Specifically, we interrogate how mechanical dosing affects time-dependent cellular transitions on the same substrate. These materials expand current methods for investigating and 3



manipulating cellular responses in short time-scales to provide new insights into dynamic cell behavior. Using this material to study the behavior of iPSCs in vitro while controlling microenvironment stiffness provides a translational model to better understand the effects of mechanics in loading of varying durations on the dynamic cellular responses of the human heart.

Methods An expanded Methods section is available in the Supplemental Information. Magnetorheological Elastomer Preparation. Sylgard 527 Elastomer (Dow Corning, Midland, MI, USA) and carbonyl iron micro-spheres (3-4 µm diameter) were used to fabricate polydimethylsiloxane (PDMS)-based MREs that form the cyto-compatible substrate. Sylgard 527 was prepared per manufacturer’s directions by mixing equal weights of part A and part B and was then thoroughly mixed with Carbonyl Iron Powder (CIP-CC, BASF, Ludwigshafen, Germany) at a 1:1 ratio by mass (50 wt.% iron, 12% volume fraction iron). The mixture was stirred for 5-10 min until all the components were evenly dispersed. The mixture was degassed for 10 min, poured into 35 mm culture dishes (5 g per dish), degassed for another 10 minutes, and baked for 24 hr at 60 °C. Manipulating Magnetic Field Strength. By applying a magnetic field gradient to the backside of the 35 mm dish, we can achieve changes in elastic modulus by simply varying the distance of a permanent magnet. More specifically, we can ramp up the stiffness by moving the magnet closer to the material by removing spacers between the sample and magnet. We can ramp down the stiffness by moving the magnet away from the material by adding additional spacers between the sample and magnet. For these experiments, we used a cylindrical, axially magnetized N45 neodymium rare earth magnet (1.26” diameter x 0.25” thick; CMS Magnets, Garland, TX, USA), with a magnetic flux density of 175.4 mT at the surface of the magnet in the center (figure S1). The field strength was manipulated by changing the distance between the magnet and the composite (figure 1A). Magnetic field strength for a permanent magnet is given as follows:

4


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𝐵(𝑚,𝑟,𝜆) =

𝜇𝑜𝑚 4𝜋𝑟3

1 + 3𝜆

(1)

Where B is the strength of the field in Teslas, r is the distance from the center of the magnet measured in meters, λ is the magnetic latitude from the center dipole axis of the magnet, m is the dipole moment measured in joules per tesla, and µo is the permeability of free space. In our MRE system we achieve varied magnetic flux density (B) felt by the sample by changing the distance between the magnet and the sample (r). Mechanical Property Measurement. The shear and elastic moduli of the MRE were characterized in response to the changing magnetic field. Rheological characterization was performed with a RFS3 straincontrolled rheometer (TA Instruments), using 25 mm circular parallel plate geometry to extract shear storage modulus (G’) and loss modulus (G’’). The frequency dependence of the MRE properties was characterized with a frequency sweep from 0.02 Hz to 20 Hz at 2% strain, while the strain dependence was characterized with a strain sweep from 2-22% at 1 rad/s. We also determined the loss tangent, a dimensionless ratio of viscoelastic energy loss and energy storage – a measure of the viscoelasticity of soft materials – which is defined as the ratio of G” to G’ for both the frequency sweep and strain sweep. An indentation technique for soft materials was used to measure the elastic modulus of the material. An 11 mm diameter aluminum sphere was attached to a standoff and then inserted into the load cell and served as the indenting probe. The load cell was attached to a linear, worm-drive motor, and the stage movement was controlled using Matlab, as well as recording of position and force. Indentations were performed at 10 µm/s to obtain force-displacement curves. Using the classical adhesive contact model by Johnson et al.38 (eqn. 2), the unloading curves obtained were fit to extract the elastic modulus and work of adhesion of the MRE-probe contact pair. 2

𝛿=

(

1 3𝑅 (𝐹 + 3𝛥𝛾𝜋𝑅 + 6𝛥𝛾𝜋𝑅𝐹 + (3𝛥𝛾𝜋𝑅)2) 𝑅 4𝐸 ∗

5


)

3

(2)


Ramp Experiment Design. For the cell culture experiments, devices were prepared through sterilization with 70% ethanol for 20 min; washing with 1 mL of phosphate buffered saline (PBS) 3x; incubation at 37 °C with 10 µg/mL concentration of fibronectin for 1.5 hr; then final washing with PBS 3x. Human-stem-cell derived cardiac fibroblasts (Ncardia, Cologne, Germany) were seeded at 100 cells/mm2. Prior to performing the time-dependent stiffening and softening experiments, we determined the plateau of cells spreading by incrementing every 15 min until 1 hr; every 30 mins until 3 hr; every 2 hr until 7 hr; and then overnight. We determined that the spreading plateaued at 3 hr and subsequently used this as the minimum time increment to examine changes in other mechanosensitive phenotypes. The stiffness of the device was then modulated by placing the magnet to the backside of the MRE devices and varying the spacing between the magnet and device. We performed two general experiments: material stiffness ramp up and ramp down. In the first, the stiffness was increased monotonically by decreasing the spacing between the magnet and the MRE with 3-hour time intervals between adjustments. In the second, the stiffness was monotonically decreased using an opposite procedure as the first, with spacing between the MRE and magnet progressively increased in 3-hour intervals, after cells had been cultured in the stiffer state overnight. When changing the magnet distance, the spacing is carefully increased or decreased without removing the magnet from the sample, thus avoiding rapid softening then re-stiffening during these adjustments. As controls, separate populations of cells were kept on either the soft or the stiff condition for the same duration as the ramp up or ramp down, respectively. At each time interval, samples were stained to capture spreading, YAP translocation, and percent alpha-smooth muscle actin activation (full details in Supplemental Information). Cardiomyocyte Sarcomere Maturation Analysis. Since there is no gold standard for mature sarcomere identification beyond researcher impression of the morphologic appearance upon manual inspection, we developed an automated classifier to extract the percentage of mature sarcomeres in images. Employing Ilastik, a ‘machine learning’ application designed for automated classification and segmentation39 for a range quantitative analysis40,41, we used a subset of 15 images as a training set that we manually annotated. Annotations for pixel classification identified three different pixel classes: 6


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‘background’, ‘mature sarcomere’, and ‘other cell’. Labeled pixels serve as the inputs for a random forest classifier, which utilized 35 pixel-level feature detection algorithms to analyze color/intensity, texture, orientation, and edge relations at a range of sigmas from 0.3 to 3.5 pixels. A threshold for the pixel-level predictions of 0.4 and a minimum size of 200 pixels in area was then applied to the pixel map to generate a preliminary segmentation of objects. Finally, we analyzed both pixel-level prediction features within the objects themselves and within the neighborhood of objects at a neighborhood size of 30 pixels. The end result of object-level training was two classes of objects: confirmed mature sarcomeres and other cells. We performed a validation experiment designed to assess whether the classifier performs within the range of inter-observer variability seen between human researchers performing the same task. A more complete description of the process and the validation can be found in the Supplemental Information. Fibroblast Stress Fiber Analysis. We used the CellProfiler application for rapid, unbiased, automated quantification algorithms42,43. To quantify the stress fiber intensity, thresholds were used for artifact removal and object segmentation. Objects were then filtered by size parameters to remove clustered cells based on a liberal range of single-cell sizes estimated from manually surveying fibroblasts in the images. The objects remaining after size filtering represented single or abutting pairs of fibroblasts that were deemed amenable to analyses including counting, area measuring, and integrated intensity-area measuring. The corresponding DAPI-stained (nuclei) images underwent cell-counting so that quantified fibroblast metrics could be normalized to overall cell count. This was included as a valuable safeguard against pairs of abutting fibroblasts being counted as a single object. A more complete description of the process and can be found in the Supplemental Information. Alpha-SMA Analysis. The total number of cells was determined by manual counting. Additionally, we counted the number of activated cells, indicated by α-SMA stress fiber formation. Statistical Analysis. Outcome measures were first tested using one-way analysis of variance (ANOVA) to determine if they depend on substrate stiffness (both ramp up and ramp down tested separately). If the omnibus test indicated a significant dependence on stiffness, post hoc Tukey tests

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compared values between each stiffness. Differences were considered to be statistically significant when p-values were < 0.05.

Results To explore the influence of substrate stiffness change on cardiomyocytes, we used PDMS as the base material in which iron particles were embedded to create a magnetorheological elastomer (MRE) shown in figure 1A. The MRE substrates reproducibly stiffen in response to magnetic field44–46: as the magnet gets closer or farther from the MRE substrate, the matrix stiffens or softens, respectively (figure 1B). We simulated and experimentally verified the effect of the magnet on the sample to determine the magnetic flux density at the surface and experienced by the cell (full details found in Supplemental Information). Figure 1C shows how magnetic flux density changes in space and across the sample, with nonuniformities arising at the edges of the magnet. Changing the spacer distances between magnet and sample resulted in different magnetic flux densities at the sample surface of up to 95 mT when there is no spacer present. The magnetic flux density exhibited reasonable uniformity across the radial direction of the sample, with most of the variation occurring at the edges outside the observable area. The stiffness of the material was confirmed using both rheology and microindentation at different magnet distances. Rheological characterization was employed to determine the shear modulus. Figure 2A shows both shear storage and loss moduli from frequency and strain sweeps. In general, there was minimal dependence of properties on either parameter save for G’’ which increased with frequency; this is further observed in the loss tangent (figure S2). Shear storage modulus ranged from 6.7 kPa with no magnet up to 20.8 kPa with magnet and no spacer at 1 rad/s, while loss modulus ranged between 0.5 kPa and 2.5 kPa under the same conditions. Figure 2B shows the force-indentation curves at various magnet distances from which elastic moduli is extracted. Elastic modulus ranged from 9.3 kPa with no magnet up to 54.3 kPa with magnet and no spacer. Figure 2C shows the dynamic range of the substrate in both shear and indentation, which correspond to a range of physiological and pathological myocardial stiffnesses47. We additionally confirmed the biocompatibility of the system for culture by verifying neither the 8


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MRE nor applied magnetic field adversely affected cells. Using a live/dead assay over three days, we demonstrated the viability of primary neonatal rat fibroblasts cultured on PDMS with iron and two controls: glass and PDMS with no iron; there was no significant difference in cell viability between conditions (figure S3A). For this specific control, we used primary cells to measure biocompatibility of the materials because they are expected to be more sensitive to toxicity factors. Cardiomyocytes differentiated from human iPSC-CMs were cultured on MREs coated with fibronectin to study phenotypical and morphological changes with dynamic variation in substrate stiffness. We seeded cells at a density of ~100 cells/mm2 and allowed the cells to adhere and equilibrate for two days, after which we began to either stiffen or soften the substrate by moving a magnet closer to or further from the substrate every 3 hours, for up to 12 hr (figure 3A). Here, the iPSC-CMs seeded on the soft (no magnet) condition exhibit a small spread area; however, as the substrate becomes stiffer by decreasing magnet distance, the cells spread with surprising rapidity (figure 3B). This spreading effect is also seen in reverse: cells seeded on the stiff substrate, with the magnet initially in close proximity, exhibit a large spread area that decreases as the magnet is withdrawn and the substrate becomes softer. We saw the same trends in cardiac fibroblast spreading with increasing or decreasing substrate stiffness (figure S4A); however, there were quantitative differences in the cell area changes: the iPSC-CMs spread from ~2600 to 4800 µm2, whereas the cardiac fibroblasts spread from ~3500 to 4500 µm2, which agrees well with literature48,49. Importantly, iPSC-CMs and fibroblasts maintain a stable surface area when maintained at constant stiffness for the same duration. We did not observe a change in the shape of the iPSC-CM with different substrate stiffness. The iPSC-CM has a "star-like" shape on every substrate, presumably due to their immature state. We additionally examined YAP nuclear translocation in response to substrate stiffening or softening. YAP acts as a mechanosensitive switch that is regulated by the rigidity and deformability of the ECM50. As the actin cytoskeleton reorganizes in response to increases or decreases in substrate stiffness, YAP nuclear localization is directly coupled by either moving into or out of the nucleus, respectively50. For this analysis, we classified the cell into three categories based on the amount of YAP translocated: no translocation, partial translocation, or complete translocation into the nucleus. Figure 3C exclusively shows 9



percent of cardiomyocytes with complete YAP translocation in response to substrate stiffness (figure S4CD shows the complete breakdowns of each category). There is a fast translocation of YAP into the nucleus as the substrate is stiffened (from 48.5% up to 60.6%), but this is reversed and YAP moves back to the cytoskeleton from the nucleus as the substrate is softened, similar to the reversible spreading behavior. These YAP translocation trends with substrate stiffness are also observed in cardiac fibroblasts (figure S4B). We used the MRE substrates to investigate the contribution of stiffness changes to myofibroblast activation. As cardiac fibroblasts differentiate into myofibroblasts they exhibit characteristic phenotypic shifts including ECM deposition, chemical and mechanical signaling, and expression of alpha-smooth muscle actin51, all of which profoundly influence myocardial function. We observed an increase in the percentage of activated myofibroblasts when the stiffness of the substrate is increased (up to 12.4%) and a decrease in activation as the stiffness is decreased (down to 4.2%), using alpha-smooth muscle actin (αSMA) as an activation marker (figure 4A). As a control, cardiac fibroblasts were cultured on an MRE substrate without a magnetic field applied, and the activation was preserved over the same short time-scale. As additional controls, we demonstrated that magnetic field application did not alter cell spreading, myofibroblast activation or YAP translocation during culture on glass or PDMS without iron substrates (figure S3B-C). These results demonstrate that MRE substrates can model the mechanically dynamic features of ECM during cardiac fibrosis, where the activation of cardiac fibroblasts is promoted by substrate stiffening. Representative images of the myofibroblast activation during both progressive stiffening and softening protocols are shown in figure 4B, where the white arrows indicate the activated myofibroblasts. At higher magnification, we examined actin stress fiber formation by examining at the average phalloidin intensity of a single cell over the area covered. As the magnet is applied, the total phalloidin intensity increases, and, as the magnet is removed, it decreases, as shown in figure 4C. It is important to note that the data presented in figure 4C is stress fiber concentration per area, which increases with substrate stiffness. When considering that the area of cells is also increasing – i.e. cells are spreading (figure S5) –

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the total number of stress fibers is much greater on stiffer substrates than on softer substrates. Representative images of the stress fibers on both stiff and soft substrates are shown in figure 4D. Human iPSC-CMs exhibit a functionally immature, disorganized, fetal-like phenotype, and mechanical factors, such as stiffness, are among the influences reported to affect the rate and magnitude of iPSC-CM maturation32,52. Prior studies have identified several protein isoforms that mark progressive maturation of iPSC-CMs. For example, myosin heavy chain (MHC) exhibits a maturational transition from alpha-myosin heavy chain (MYH6) predominance in immature cardiomyocytes to beta-myosin heavy chain (MYH7) in more mature human cardiomyocytes32,53. Accordingly, we used an iPSC cell line with a GFP tag linked to MYH7 as a means of reporting the maturation of iPSC-CM populations in response to alternative substrate stiffnesses. After initial culturing on a very stiff polystyrene substrate during a longterm differentiation protocol, on day 30 of differentiation we re-plated iPSC-CMs on alternative MREs (with or without magnet for stiffer or softer materials) or continued polystyrene for 48 hrs before detachment and flow cytometry (full protocol in Supplemental Information). Figure 5A-B shows that there is a dramatic increase in the amount of MYH7 on softer substrates with a graded increase in MYH7 expression with decreasing substrate stiffness, indicating enhanced molecular maturation. In complementary studies, we examined the effects of changing substrate stiffness on morphological maturation in cultured iPSC-CMs, based on the formation of organized sarcomeres. Employing α-actinin staining and a machine learning classifier trained to identify organized sarcomeres based on staining color/intensity, texture, orientation, and edge relation, we identified and quantified sarcomeres within iPSC-CMs on various substrate stiffnesses. Figure 5C shows representative images of (i) cardiomyocytes with an organized and disorganized sarcomeric structure, (ii) an example of the predictive algorithm showing both the original image and post-processed image highlighting in red the area of identified sarcomeres, and (iii) an example of object classification showing objects classified as having mature sarcomere pattern (green) and other cell areas (purple). Figure 5D shows that sarcomere organization tended to increase as substrate stiffness was decreased in cultures of pure iPSC-CMs. Recognizing that there are interactions between cardiomyocytes and fibroblasts during development and 11



maturation, figure 5E shows the change in organized sarcomeres as a function of the balance between cardiac fibroblasts and iPSC-CMs in the culture dish at different substrate stiffnesses. As the proportion of cardiomyocytes increased, sarcomere formation was positively correlated with the degree of myocyte enrichment. Moreover, the softer substrate (MRE without magnet) as compared to the stiffer substrate (MRE with magnet) tended to produce more organized sarcomeres at each of the co-culture ratios tested. Predictable phenotypic shifts observed during dynamic changes in substrate stiffness provide an opportunity to identify which molecular markers of mechanosensing and transduction are most correlated with induced changes in substrate stiffness. To this end, quantitative RT-PCR was performed on iPSC-CMs cultured on MREs with varying stiffnesses using the ramp up and ramp down protocols (figure 3A-B). As candidate markers, we considered several direct targets of YAP (AURKA, CCNB1, and CTGF), markers of cardiovascular development (MYH7, NKX2.5, RXRA, and SEMA3A), and markers of cardiomyocyte hypertrophy (FN1, ANP, and BNP). Initially, during the stiffness ramp up, several transcripts tend to change with substrate stiffness (figure 6A), but only aurora kinase (AURKA) exhibits a statistically-significant difference (figure 6B). Then, during the ramp down, the genes AURKA, CNNB1, CTGF, and FN1 all exhibit significant decreases in expression, while only MYH7 shows an increase in expression (figure 6B). The switch in MHC isoform agrees with our data using the reporter cell line. Thus, in this preliminary survey, AURKA transcript abundance is best correlated with the overall phenotypic responses of iPSC-CMs to graded increases or decreases in substrate stiffness during the time-scale evaluated in these studies.

Discussion Biomechanical stimuli are fundamental physiological and pathological drivers of cell and tissue structure and function with particularly prominent roles in the cardiovascular system. In addition to their influence on normal developmental and homeostatic processes, most cardiovascular disease states and their experimental model analogues directly or indirectly involve alterations in biomechanical factors acting on the heart and/or vasculature54,55. Here, we present an approach to mimic dynamic changes through an in vitro model with the ability to modulate the environment stiffness bi-directionally. Our MRE devices are 12


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simple to fabricate and allow for easy control of stiffness through the use of permanent magnets placed at varying distances on the backside of the device, with consistent control of substrate stiffness from approximately 10 kPa to 55 kPa. Additionally, we chose to use a viscoelastic substrate that exhibits stress relaxation because most biological tissues exhibit viscoelastic behaviors, and cells cultured on viscoelastic substrates have been shown to respond differently when compared to culture on purely elastic substrates5,56. These devices are robust, reproducible, and allow measurements in standard format dishes. We demonstrate the effect of changes in substrate stiffness on both iPSC cardiomyocytes and cardiac fibroblasts with morphological, maturational, and gene expression changes. Dynamic Biophysical Responses: Spreading, YAP Translocation, and Maturation.

To

demonstrate that our system can produce changes equivalent with prior observations, we considered cell spreading and YAP translocation on soft and stiff substrates. We observed changes in cell spreading between our terminal soft and stiff substrates equivalent to those seen in conventional static controls57. Owing to the ability to produce graded stiffness, we observed transient spreading profiles between the two extremes, demonstrating that the speed at which these phenotypes develop is rapid. This rapid and dynamic reorganization of actin cytoskeleton in response to dynamic changes in substrate stiffness can induce the transcriptional co-activator YAP to translocate from the cytoskeleton to the nucleus. On a stiff substrate YAP is translocated to the nucleus whereas on a soft substrate, YAP remains in the cytoplasm, as has been shown with other cell types. Through an incremental stiffening protocol, we can see the relatively fast timescale at which this occurs. Of particular importance, our bi-directionally tunable substrate demonstrates the reversibility of these canonical cardiomyocyte responses to changes in substrate stiffness. Fibroblasts are the most abundant cell type and they take on a crucial role in extracellular matrix remodeling in health and disease58. Cardiac fibroblasts can be stimulated, through injury or mechanical activation, to exhibit a myofibroblast phenotype; however, continuous activation leads to excess production of ECM proteins, which results in fibrosis59–64. In myofibroblasts, ɑ-SMA is a marker of the activated state and may serve as a mechanotransducer based on force-induced expression59–64. Through increasing and decreasing the MRE substrate stiffness, we can model the activation and deactivation of cardiac fibrosis 13



through the mechanically dynamic features of ECM. As the substrate is stiffened, the cardiac fibroblasts show an increase in ɑ-SMA expression, but will revert to a quiescent state when the substrate is softened. It is known that myofibroblast activation has a time-dependency6, however, our results show that ɑ-SMA tracks very well within the short time frame exhibited in this demonstration, indicating that we remain below the time and stiffness threshold of irreversible activation. There is growing interest in the potential use of cardiac myocytes derived from iPSCs for preclinical drug testing and disease modeling35. However, iPSC-CMs exhibit an immature phenotype, including atypical beating pattern, a disorganized sarcomere, and mononucleated cells32. We specifically focused on tracking changes in the protein β-MHC, which is more prevalent in adult than fetal human myocardium, through the use of a gene-edited MYH7 reporter iPSC-CM line. We show changes in β-MHC expression with decreasing stiffness (i.e. moving toward a more physiologically relevant stiffness). Through complementary immunocytochemistry, we show maturation of cardiomyocytes through the change in the quantity of organized sarcomeres with changes in stiffness and how the proportion of fibroblasts influences that difference. Overall, the softer substrates (MRE without magnet) yielded more organized sarcomeres, and sarcomere formation was positively correlated with the degree of myocyte enrichment. The combination of predictable and controllable mechanoactivation responses provides new opportunities to identify and confirm specific mechanosensing and mechanotransduction pathways and mechanisms. Our preliminary gene expression profiling illustrated this potential by focusing on a limited set of molecular targets previously implicated by studies using alternative in vivo and in vitro experimental approaches. These experiments identified aurora kinase as particularly well-linked to the in vitro cellular responses to timed alterations in extracellular substrate stiffness, during both extracellular matrix stiffening and softening protocols. Prior studies have identified aurora kinase as one of several cell cycle checkpoint proteins linked to cancer cell proliferation65 and as a promoter of stiffness-dependent microtubule proliferation in cultured endothelial cells66. In this context, the present studies extend to cardiac myocytes this mechanoresponsive role of aurora kinase. Advantages of the Present Model. Elucidating emergent time-dependent cellular responses 14


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requires the creation of systems with tunable and dynamic stiffness. This work demonstrates that the MRE substrates are mechanically dynamic and their tunable stiffness can direct fast, reversible and irreversible cell responses on the same substrate. Matrix stiffness varies with the strength and direction of the field gradient, allowing stiffness-dependent assessments with time, including return to a relaxed state following removal of the magnet. The capabilities of this system are useful in cell biology, as the dynamic stiffness of the material is both tunable (i.e., can achieve different stiffnesses in a single culture) and reversible (i.e., can be returned to a relaxed state). Such a system allows for measurement of the temporal remodeling and alterations in cell mechanics, and significantly advances previous tunable in vitro substrates that used unidirectional property changes. This versatility permits many scientific and engineering opportunities for probing physiological and mechanical changes in tissue. With the growing interest in the potential use of iPSC-CMs, this data suggests that this system might be useful for disease modeling. Identifying multiple proteins that are affected by changes in the mechanical environment to form a response “signature” is a potentially powerful and reliable method to more completely model disease. By dynamically manipulating the stiffness of the culture condition and examining the gene expression, we can pinpoint the genes/proteins directly related to mechanosensitivity and response to environmental stimuli while identifying the most robust biomarkers of cellular mechanosensing. The combination of reversibility and temporal control will afford the opportunity to interrogate time-dependent phenomena including mechanical memory, whereby the duration of time at a particular stiffness affects the persistence of the evoked response. The presented material adds multiple levels of functionality beyond previously developed dynamic materials: (1) physiologically relevant bi-directional control of stiffness, (2) reversible stiffening/softening, (3) incremental changes in stiffness, and (4) nearly instantaneous stiffness response to allow for time-dependent studies. Limitations. The MRE material and dynamic stiffening technique presented in this paper still has a few limitations. First, the size and density of iron particle inclusions make the material opaque thus requiring an upright microscope to visualize the cells on the surface. This limits the ability to use standard phase contrast or brightfield methods with an inverted microscope. Future experiments requiring less 15



dynamic stiffness range maybe be able to overcome this limitation by reducing the iron particle content or by altering the magnetic field gradient strength or direction. Second, technical challenges have impeded our ability to characterize microscale local mechanical properties of these MRE devices, which might differ from macroscale properties because of inhomogeneities resulting from localized differences in particle density and configuration. The use of a strong permanent magnet to stiffen the MREs limits the use of sensitive measurements such as with atomic force microscopy, and such characterization merits further investigation for more complete assessment of material properties at the microscale. Third, as a consequence of the stiffening mechanism, the substrate surface roughness also varies as the magnet approaches the device. This may have the undesired effect of simultaneously changing cellular focal adhesion locations during dynamic stiffening, thus entangling potential biophysical responses. However, future studies will likely be able to characterize and control this substrate property. In its current form, and with further refinement, the MRE substrate described in this manuscript will provide numerous opportunities to probe mechanobiology relevant to cardiovascular homeostasis and disease while also empowering numerous non-cardiovascular applications.

Acknowledgements This research was supported, in part by a grant from the state of Pennsylvania Department of Health, with additional funding from Merck, Sharp and Dohme, the National Center for Advancing Translational Sciences of the National Institutes of Health under award number TL1TR001880 and the Center for Engineering Mechanobiology (CEMB) under grant agreement CMMI: 15-48571.

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Figure 1. Overview of the magnetorheological elastomer. (A) Composite consisting of polymer matrix and iron particles. When a magnetic field is applied the particles rearrange and cause a change in material stiffness. (B) Dynamic control of the matrix stiffness is possible by varying the magnetic field gradient through the addition of spacers in between the magnet and the substrate. The material stiffens as the magnet is placed close to the material, and softens as spacers are added and there is a greater distance between material and magnet. (C) (i) Simulation showing the magnetic flux density of the magnet with a shadow drawing of the placement of the MRE within a 35 mm dish and the dashed box indicated the location of

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cells on the surface. (ii) Line snapshots from the simulation show the z component of the magnetic flux density at the surface of the MRE measured along the radial direction at the specified spacer distances between the base of the dish and the magnet. Symbols (∎ and ×) represent experimental results for the z component of the magnetic flux density (Bz) measured by a Lakeshore model 410 Gauss meter at the location of the cells with and without the MRE below, respectively.

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Figure 2. Mechanical characterization of the viscoelastic magnetorheological elastomers subjected to different magnetic fields. (A) Frequency and strain dependence of the storage modulus (G’ – filled symbols) and loss modulus (G” – open symbols) for four magnetic flux densities (from different distances from sample to magnet). (B) Force-indentation curves of the same sample subject to different magnetic flux density applied to the sample through varying distance. (C) Plot showing the elastic modulus, shear storage modulus, and shear loss modulus values for different applied magnetic flux densities to stiffen or soften the material. Achievable elastic moduli range from ~10-55 kPa and achievable shear moduli range from ~7-21 kPa. (Elastic Modulus: 3 samples were tested at 3 locations on the surface for all magnetic flux densities. Shear Modulus: 3 samples were tested for all magnetic flux densities. Data presented at mean ± SD.)

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Figure 3. Mechanosensitive phenotypes responsive to reversible MRE stiffness. (A) Experimental design of temporal stiffness increases (ramp up) and decreases (ramp down). For the ramp up, at t=0 hr cells were in culture for 2 days after seeding. For the ramp down, at t=0 hr cells were in culture for 2 days

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and the magnet was applied 12 hr prior to starting the experiment. Green dots indicate individual devices serving as controls and white dots indicate the time points at which the experimental device was imaged as it was taken through whole protocol. (B) Cardiomyocyte cell areas were measured to quantify cell spreading as a function of stiffness in both the ramp up (blue) and ramp down (orange). Green dots indicate the positive (stiff) time controls and the negative (soft) time controls. (3-4 ramp up and ramp down experiments were performed with 3 technical replicates per time/magnet distance, totaling a minimum of 9 dishes analyzed per time point. An average of 141 cells were analyzed at each time point across all experiments and dishes. Data presented as mean ± SEM. Significance difference is indicated by *, #, and † as compared with 0 mm, 4 mm, and 8 mm magnet distances, respectively.) (C) Cardiomyocyte YAP nuclear translocation was determined as a function of stiffness for both the ramp up and ramp down. (3-5 ramp up and ramp down experiments were performed with 3 technical replicates per time/magnet distance, totaling a minimum of 9 dishes analyzed per time point. An average of 420 cells were analyzed at each time point across all experiments and dishes. Data presented as mean ± SEM. Significance difference is indicated by * and # as compared with 0 mm and 4 mm magnet distances, respectively.) (D) Representative images of YAP translocation in cardiac fibroblasts of the ascending and descending translocation (scale bar 25 µm).

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Figure 4. Stiffening of PDMS substrates promotes myofibroblast activation and actin stress fiber formation. (A) Myofibroblast activation based on ɑ-SMA quantification of cardiac fibroblasts as both ascending stiffening and a descending stiffening effects 3 hr apart. (3 ramp up and ramp down experiments were performed with 3 technical replicates per time/magnet distance, totaling 9 dishes analyzed per time point. An average of 210 cells were analyzed at each time point across all experiments and dishes. Data presented as mean ± SEM. Significance difference is indicated by * and # as compared with 0 mm and 4 mm magnet distances, respectively.) (B) Representative images for cardiac fibroblasts on the stiff and soft substrate with white arrows indicating activated cells with bright striated appearances. (scale bar 50µm). Cells were stained for α-SMA (green) and nuclei (blue). (C) Actin stress fiber intensity quantification of cardiac fibroblasts as both ascending stiffening and a descending stiffening effects 3 hr apart using an automated algorithm. Intensity was normalized between 0-1. (3 ramp up and ramp down experiments were performed with 3 technical replicates per time/magnet distance, totaling 9 dishes analyzed per time point. An average of 125 cells were analyzed at each time point across all experiments and dishes. Data presented

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as mean ± SEM. Significance difference is indicated by * and # as compared with 0 mm and 4 mm magnet distances, respectively.) (D) Representative images for cardiac fibroblasts on the stiff and soft substrate (scale bar 50µm). Cells were stained for phalloidin (green) and nuclei (blue).

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Figure 5. Increased cardiomyocyte maturation markers on softer substrates. (A) MYH7 reporter cell line representative fluorescence-activated cell sorting (FACS) analyses of beta-myosin heavy chain expression in the human induced pluripotent stem cell (iPSC)-derived cells. (B) Overview of β-MHC expression with respect to stiffness and controls – increase in β-MHC expression with a decrease in stiffness. (n ≥ 3 per group. Data presented as mean ± SEM. Significance difference is indicated by *, **,

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and *** with p-values < 0.05, < 0.01, and < 0.001, respectively.) (C) Overview of the sarcomere organization analysis utilizing a machine learning algorithm – (i) representative confocal images of organized and disorganized sarcomere structures, (ii) raw image from data set and processed image indicating the region of sarcomere organization (red), which has an identified 78.3% organized sarcomeres, and (iii) raw image from data set and object classification showing objects classified as having mature sarcomere pattern (green) and other cell areas that did not meet the thresholds based on size, pixel-map probability at the object-classification stage (purple). (D) Time-dependent percent sarcomere organization over the ascending and descending stiffening curves in cultures comprised exclusively of iPSC-derived cardiac myocytes. (Data presented as mean ± SEM. Significance difference is indicated by † as compared with 8 mm magnet distance.) (E) Percent sarcomere organization in co-cultures with varying fractions of cardiomyocytes and fibroblasts on both stiff (magnet) and soft (no magnet) substrates showing that fibroblasts influence how stiffness affects cardiomyocytes. (Data presented as mean ± SEM. Significance difference is indicated by *, #, and † as compared with 100%, 90%, and 75% cardiomyocyte fraction of corresponding stiffnesses, respectively.)

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Figure 6. Changes in qRT-PCR gene expression on both ascending and descending stiffness substrates. (A) Change in gene expression with YAP nuclear translocation: proliferation (AURKA, CCNB1 and CTGF), cardiovascular development (MCF7, NKX2.5, RXRA and SEMA3A), and hypertrophic (FN1, ANP and BNP). (B) Genes with significant differences in expression between magnet and no magnet conditions on either the ramp up or ramp down. (n = 6 per group. Data presented as mean ± SEM. Significance difference is indicated by *, **, and *** with p-values < 0.05, < 0.01, and < 0.001, respectively.)

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Tunable and Reversible Substrate Stiffness Reveals Dynamic

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