Topological Control of Extracellular Matrix Growth: A Native-Like

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Topological control of extracellular matrix growth: a native-like model for cell morphodynamics studies David Caballero, and Josep Samitier ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.6b13063 • Publication Date (Web): 09 Jan 2017 Downloaded from http://pubs.acs.org on January 12, 2017

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ACS Applied Materials & Interfaces

Topological control of extracellular matrix growth: a native-like model for cell morphodynamics studies David Caballero1,2,3,*, Josep Samitier1,2,3* 1

Nanobioengineering group, Institute for Bioengineering of Catalonia (IBEC), Baldiri Reixac 15-21, 08028, Barcelona, Spain.

2

Department of Engineering: Electronics, University of Barcelona, 08028, Barcelona, Spain. 3

Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain.

ABSTRACT

The interaction of cells with their natural environment influences a large variety of cellular phenomena, including cell adhesion, proliferation, and migration. The complex extracellular matrix network has challenged the attempts to replicate in vitro the heterogeneity of the cell environment and has threatened, in general, the relevance of in vitro studies. In this work, we describe a new and extremely versatile approach to generate native-like extracellular matrices

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with controlled morphologies for the in vitro study of cellular processes. This general approach combines the confluent culture of fibroblasts with microfabricated guiding templates to direct the three dimensional growth of well-defined extracellular networks which recapitulate the structural and biomolecular complexity of features typically found in vivo. To evaluate its performance, we studied fundamental cellular processes, including cell cytoskeleton organization, cell-matrix adhesion, proliferation, and protrusions morphodynamics. In all cases, we found striking differences depending on matrix architecture, and in particular, when compared to standard two dimensional environments. We also assessed whether the engineered matrix networks influenced cell migration dynamics and locomotion strategy, finding enhanced migration efficiency for cells seeded on aligned matrices. Altogether, our methodology paves the way to the development of high performance models of the extracellular matrix for potential applications in tissue engineering, diagnosis, or stem cell biology.

KEYWORDS: Extracellular matrix; Engineered cell-derived matrices; Cell migration; Biomimetics; In vitro model.

1. INTRODUCTION The interaction of cells with the surrounding extracellular matrix (ECM) plays a critical role in both physiological and pathological processes by regulating cellular functions and tissue homeostasis 1. In vivo, cells encounter a broad range of ECM topologies, such as isotropic networks of collagen in connective tissue or aligned collagen bundles in the dermis. These have a major impact on the regulation of cellular processes by providing spatial and mechanical cues to which cells respond. These physical factors synergize with biomolecular cues to influence


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normal homeostasis and tissue phenotype

2-3

. Perturbation of normal homeostasis leads to the

development of abnormal ECM structural properties and dynamics impacting on cell behavior. This can promote epithelial-to-mesenchymal transition in tumor cells facilitating rapid cancer cell invasion 4-5. Cell morphodynamics have been widely investigated in vitro using a large plethora of microengineered assays, mostly based on two-dimensional (2D) models 6. However, the complexity of the ECM network has threatened, in general, their physiological relevance. Two dimensional assays do not reproduce the structural and molecular complexity of the in vivo environment; important intracellular signals are lost leading to a perturbation in cell phenotype 7. Microengineered three-dimensional (3D) models mimicking with higher fidelity the mechanical and chemical signals of cellular environments have also been described 8. Typically, cells have been confined within synthetic or ECM-derived gels and used to study a diverse variety of cellular phenomena. The mechanical properties of gels are easily tunable even though they lack, in general, the control on matrix architecture and molecular heterogeneity. Aligned fiber control can be easily achieved on synthetic fibers using electrospinning 9. Cells seeded on aligned electrospun fibers have revealed that cells polarize, orient and migrate along fiber main axis 10-13. Nevertheless, electrospun fibers do not provide complete biomolecular and mechanical cues and therefore are far from being physiologically-relevant. In this regard, cell-derived matrices (CDMs) are natural ECMs assembled by cells resulting in a matrix which closely mimics the stromal fiber random organization and molecular content

14-17

. The in-vivo-like molecular cues

provided by CDMs stimulate signaling pathways that regulate adhesion, survival, proliferation, polarity, and migration of cells. However, certain physiopathological events, tissues, or organs, show complex ECM architectures limiting the applicability of CDMs. For instance, during


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cancer metastasis, cancer-associate fibroblasts reorganize the matrix into fibrillar ordered structures along which metastatic cancer cells migrate and invade the surrounding stroma 3. Other examples include the corneal stroma, which is formed by a highly-ordered structure made of aligned collagen lamellae 18. Similarly, ECM assembly into a fibrillar network was shown to be critical during wound healing where cells migrate into a wounded area guiding the closure of the wound 19. Taken together, these studies reveal the critical regulatory role of the ECM where both the structural and biochemical cues influence cell behavior. There is the need to create new in vitro models of the ECM that better mimic the cellular microenvironment combining in vivolike composition and controlled matrix architecture to achieve a better understanding of cellECM interaction and subsequent cellular responses. These advanced in vitro models may be applied in clinical diagnosis to study the interaction of cells with the surrounding stroma, such as during tumor growth, cancer metastasis, or the effect of changes in the stroma architecture during tumor invasiveness

20-21

. Finally, the fabrication of advanced biomimetic environments with

controlled morphologies is also amenable to assess the molecular mechanisms involved in a diverse variety of physiopathological processes, embryogenesis

22

, or even for drug screening

applications 23. In this work, we engineered CDMs (eCDMs) with well-defined 3D architectures which recapitulated the structural and biomolecular complexity of features typically found in vivo. We found that the engineered matrix architectures had a critical impact on fundamental cellular processes, including adhesion, proliferation and migration

24

. We propose that the developed

matrices could have potential clinical applications for assessing in vitro fundamental biological processes.


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2. EXPERIMENTAL PROCEDURES 2.1. Guiding template fabrication Figure 1a-b shows the methodology used to generate ordered eCDMs. First, a PDMS guiding template made of parallel or orthogonal micro-sized grooves (1 µm x 1 µm x 1 µm, height, width, pitch) was replicated in PDMS (Sylgard 184, Dow Corning, pre-polymer:crosslinker 10:1 w/w) from an AZ resist master (AZ 1512HS, Microchemicals GmbH) fabricated by direct writing laser lithography (DWL 66FS, Heidelberg Instruments). The PDMS replica was activated using O2 plasma (Harrick) for 30 s, silanized with trichloro(1H,1H,2H,2Hperfluorooctyl)silane (TCS) (Sigma-Aldrich) by vapour phase (1h, room temperature – RT), and cured for 1h at 65ºC. Next, a thin PDMS layer was spin-coated at 2000 rpm for 30 s on top of the micro-structures. After curing for 4h at 65ºC, the PDMS and a glass coverslip (Menzel-Gläser #1, 25 mm in diameter) were O2 plasma-activated and bounded. After 1h at 65ºC, the PDMS replica was released liberating the guiding micro-structures on top of the glass surface (see Fig.1c).23 For 2D experiments, a thin layer of PDMS was spin-coated (2000 rpm, 30 s) on top of an O2-plasma activated glass coverslip (Menzel-Gläser #1, 25 mm in diameter ) and cured (65ºC, 4h).

2.2. eCDM fabrication The protocol for eCDM growth was adapted from existing methods (see Fig.1b)

20, 25

. The

guiding template was first sterilized under UV for 5 min, activated with O2 plasma (30 s), and incubated with 1% gelatin (Sigma-Aldrich) for 1h at 37ºC to promote fibronectin binding

25

.

Next, it was rinsed twice with PBS 1x and incubated with 1% glutaraldehyde (Sigma-Aldrich) for 20 min at RT. The sample was rinsed twice with PBS 1x and incubated with a 1M glycine


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(Sigma-Aldrich) PBS solution for 30 min at RT. Next, the sample was rinsed with PBS 1x and cell culture medium (DMEM 10% BCS, 1% Pen Strep). Finally, 1 ml of medium containing 5·105 NIH3T3 (ATCC) ´sacrificial´ fibroblasts (5·105 cells ml-1) was added on the functionalized guiding template. Cells adhered and aligned along the direction set by the micro-structures, guiding eCDM growth (see Fig.1d). NIH3T3 fibroblasts were kept in culture adding 50 µg ml-1 ascorbic acid (A.A.) (Sigma-Aldrich) every other day during 8 days to stimulate the generation of collagen and stabilize the generated matrix. Finally, cells were lysed using extraction buffer (20 mM NH4OH, 0.5% Triton-X-100 in PBS 1x) (Sigma-Aldrich), liberating the eCDM (see Fig.1e). The engineered matrix was rinsed twice with PBS 1x and next, with cell culture medium to ensure a complete removal of ´sacrificial´ fibroblasts. Matrices were optically checked to confirm their quality (free of cellular debris) prior starting the experiments. A basic molecular characterization was performed to visualize the expected main components of the generated matrices

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: collagen and fibronectin. For 2D experiments, the PDMS-coated coverslip was O2-

activated (30 s) and functionalized with 20 µg ml-1 fibronectin (FN) (Sigma-Aldrich) in PBS 1x overnight at 4ºC (Flat FN sample). The coverslip was rinsed twice with PBS 1x and cell culture media prior cell seeding.

2.3. Cell culture NIH3T3 mouse fibroblasts and MG63 human osteosarcoma fibroblasts (ATCC) were grown in high glucose Dulbecco’s Modified Eagle’s Medium (DMEM) (Invitrogen) supplemented with 1% Pen Strep antibiotics (Invitrogen) and 10% bovine calf serum (Sigma-Aldrich) at 37ºC and 5% CO2. Madin-Darby canine kidney (MDCK) epithelial cells (ATCC) were grown under the same conditions using DMEM low glucose medium (Invitrogen). Finally, human spleen


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endothelial cells (hSECs) (ScienCell) were grown using endothelial cell medium supplemented with 1% Pen Strep antibiotics, 1% ECGS and 10% fetal calf serum (ScienCell) at 37ºC and 5% CO2. For experiments, cells were trypsinized (0.25% Trypsin-EDTA) (Invitrogen), centrifuged, and seeded on the sample (eCDM and Flat FN) at low density (1-2·104 cells ml-1). For highly adherent cells (NIH3T3 and MG63 fibroblasts), the medium was replaced with fresh medium after 20 min to remove non-adherent cells. This time period was chosen to allow only few cells to adhere and therefore avoid cell-cell interaction during experiments for all the studied conditions. For loosely adherent cells (MDCK epithelial and hSEC endothelial), cells were let to adhere for 3-4 hours. Cells were allowed to spread prior starting the experiments. In all cases, we measured the average surface cell density (ρ) prior starting the experiment (t=0), with ρFlat FN = 25 ± 14 cells mm-2 and ρeCDM = 37 ± 24 cells mm-2, suggesting a larger adhesion kinetics for cells seeded on eCDMs. These densities allowed us to have enough cells for quantification while minimizing cell-cell interaction.

2.4. Cell fixation and staining Cells were fixed with formalin (Sigma-Aldrich) for 20 min and permeabilized for 3 min using 0.5% Triton (Sigma-Aldrich) at RT. Next, the samples were washed twice with PBS 1x for 5 min. Phalloidin–tetramethylrhodamine B isothiocyanate (Sigma-Aldrich) was used for actin staining. Focal contacts were stained with mouse anti-paxillin (Molecular Probes) (1:1000). Alexa 488 goat anti-rabbit (Molecular Probes) (1:1000) was used as a secondary antibody. The incubations were performed for 45 min at RT in PBS 1x with 3% BSA. After each incubation the samples were rinsed twice with PBS 1x.


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2.5. eCDM staining The generated matrices were fixed with formalin (Sigma-Aldrich) for 20 min, rinsed with PBS 1x twice, and blocked with 6% donkey serum for 1h at RT. Next, the matrices were rinsed twice with PBS 1x and stained with rabbit polyclonal anti-fibronectin antibody (Abcam) (1:200). Alexa Fluor 568 goat anti-mouse (Molecular Probes) was used as a secondary antibody (1:1000). The incubations were performed for 45 min at RT in PBS 1x with 3% BSA. After each incubation the samples were rinsed twice with PBS 1x.

2.6. Optical microscopy eCDMs were visualized using second harmonic generation (SHG) and confocal microscopy (Leica TCS SP5 MP System) equipped with a 20X air (NA 0.75) and 63X oil objectives (NA 1.4). Z-stacks separated no more than 0.5 µm were collected. Long-term cell imaging was performed using an inverted microscope (Olympus IX71) equipped with a 4X phase-contrast air objective (NA 0.25). The microscope was equipped with a CCD camera (Hamamatsu), an Olympus Hg lamp for epifluorescence experiments, and a red filter (Thorslab) to prevent phototoxicity. An environmental chamber (Okolab) was used to maintain physiological conditions (37ºC, 5% CO2).

2.7. Biophysical parameters The SHG images were z-projected (Maximal Projection plug-in, ImageJ, NIH) and thresholded for morphological characterization. eCDM fiber length (LF), diameter (φF), and orientation (αF) were manually measured. Angle values were determined as depicted in Figure 2. Projected pore area (AP) and volume (VP), and orientation (αP) were measured by fitting an ellipse within the


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pores and measuring the angle with respect PDMS micro-grooves orientation (see Fig.2). Cell protrusions orientation (β),division angle (θ), and the number of protrusions during spreading and division, were manually measured. Cell migration trajectories were tracked using the Pointing Cell Tracking plug-in (ImageJ, NIH). The total number of cells analyzed was >200 cells with at least three independent biological repeats (N=3). Acquisition frequency was set at 1 image each 5 min for 24 h. No significant evidence of cell apoptosis was observed during the time-frame of the experiments. Data are provided as the mean ± SD. Statistical analysis was performed using Student’s t-test, and significance was accepted at P < 0.05.

Figure 1. eCDM fabrication procedure. (a-b) Schemes showing the fabrication of the PDMS guiding templates and eCDM growth, respectively. After eCDM extraction by cell lysis, cells of


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interest were deposited at the optimal density. (c-d) Phase-contrast microscopy images of the fabricated PDMS (upper) flat surface, and (mid and lower) micro-grooves (orthogonal and parallel), and NIH3T3 fibroblasts seeded on top of them, respectively. (e) SHG images of the extracted eCDMs showing different porous architectures. (Upper) Disordered, (mid) Jagged, and (lower) aligned eCDMs, respectively. Scale bars: 100 µm.

3. RESULTS 3.1. Adhesion geometry directs the growth of native-like extracellular matrices with controlled architecture. We combined the culture of ´sacrificial´ fibroblasts in a confluent state with microfabricated guiding templates to direct the ordered growth of three-dimensional native-like eCDMs (see Fig.1a-b and Methods) 20, 25. When ´sacrificial´ fibroblasts were grown on uniform flat polymeric surfaces (see Fig.1c-d, upper), disordered cell-derived matrices (Dis eCDM) were generated (see Fig.1e). The resulting matrices showed a meshwork of disordered collagen fibers of different lengths, diameters, and orientations, with no preferential fiber alignment (see Fig.2a-c, left). Orthogonal PDMS micro-grooves directed the formation of jagged-like eCDMs (Jag eCDMs) (see Fig.1e, mid). Fibroblasts aligned along the direction set by the imposed adhesion geometry generating a polarized matrix composed of tightly-packed and oriented fiber bundles (see Fig.1de). Collagen bundles were more numerous on Jag eCDMs than on Dis eCDMs, most probably as a consequence of the lateral restriction in motion of cells along the guiding template. Finally, cells seeded on an array of parallel micro-grooves (see Fig.1c-d, lower) induced the formation of aligned cell-derived matrices (Alig eCDMs) (see Fig.1e, lower). Similar to Jag eCDMs, tightlypacked fiber bundles were observed, most likely due to the lateral restriction in cell motion. On


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both cases (Jag and Alig), collagen fibers (F) and pores (P) were mainly oriented along αF ≈ αP ≈ ±45º and 0º, respectively, where -90º≤αF,αP≤90º (see Fig.2a-b). These angles matched the main orientation axis of the respective guiding templates (see Fig.1c). This alignment was not observed when eCDMs were grown on flat surfaces, where fibers and pores were randomly oriented in all directions confirming the disordered nature of the matrix (see Fig.2a-b). These observations were supported by the measurement of the Fast Fourier Transform (FFT) on the SHG images (see Fig.1e), where the main orientation peaks were located at the expected angles, except for Jag eCDMs, where the expected peaks at ±45º were not very prominent (see Fig. 2c). Note that the FFT analysis describes the bulk measurement of the alignment degree of the images as a whole and does not account for local alignment of fibers. We next studied whether the morphology of the generated matrix was perturbed after cell extraction. For this, we visualized the matrix before and after cell lysis (see Fig.S1). Strikingly, we found that matrix morphology was not significantly altered after cell extraction. However, some matrix features were locally – at the scale of the cell – modified, such as pore morphology or size, most likely a consequence of matrix stress relaxation (see Fig.S1). Finally, to demonstrate that the SHG images were representative of the actual morphology of the generated matrices we stained the generated eCDMs for fibronectin (see Fig.3). We found that the matrices were rich in fibronectin and displayed architectures similar to collagen. In particular, for Dis eCDMs, we obtained a meshwork of disordered fibronectin fibers and pores of different sizes and orientations (see Fig.3a). For Jag and Alig eCDMs, we found that fibronectin fibers and pores oriented along the main orientation axis of the guiding template (see Fig.3b). Altogether, these results show that both SHG and fibronectin images are indeed representative of the actual matrix architecture and that matrix morphology is not significantly affected after cell extraction.


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Figure 2. Characterization of eCDM alignment. (a) Distribution of fiber (αF), and (b) pore (αP) orientation angles for Dis, Jag and Alig eCDMs. Alig eCDMs show a main orientation peak centered at 0º. Jag eCDMs show two main peaks centered around ±45º. Dis eCDMs show no preferential orientation. (c) FFT analysis of eCDM morphology for Dis, Jag and Alig eCDMs. The latter shows a clear intensity peak centered at 135º which matches the main orientation angle of the matrix network and guiding template (0º). Note that this value was considered as 0º for simplicity in the FFT analysis. (d) Fiber length (LF), and (e) projected pore area (AP) analysis for


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all conditions. No significant difference was obtained for LF between all three conditions, whereas AP was larger for Dis and Jag eCDM conditions. Upper panels in (d) and (e) display an scheme of the measured parameters. (Data set: N=3, n>500 fibers, 1000 pores). Data: mean ± SD; *P95%) migrated along the direction set by the topography. This pore variation is in contrast with other collagen-based in vitro models which yield homogeneous fibrillar texture and pore size variation 26

. Finally, we measured matrix porosity and found larger values for Alig and Jag eCDMs (see

Table 1). In our work, the obtained results suggest that the pore size could be controlled within a range by means of selecting the adequate guiding template, paving the way to the development of a pore-controlled ECM fabrication technique. Altogether, the obtained results reveal that adhesion geometry of cells favors the growth of in-vivo-like ECM matrices with specific meshwork architectures, fiber orientations and pore sizes. Note that similar structures to the ones developed in this work have been observed in vivo

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, and therefore, the developed matrices could be

applied as native-like in vitro models of the ECM to study a diverse variety of biological phenomena, such as cell adhesion, division, migration and invasion.

Table 1. Morphological characterization of eCDMs

eCDM

LF (µm)

φF (nm)

AP (µm2)

VP (µm3)

a (µm)

b (µm)

Porosity (%)

Dis

38.6 ± 19.4

99.8 ± 28.3

225 ± 11

3030 ± 61

10.3 ± 6.5

6.9 ± 4.4

30.0 ± 11.6

Jag

36.9 ± 19.9

100.4 ± 27.1

205 ± 11

2761 ± 58

9.8 ± 4.3

6.7 ± 4.7

40.3 ± 4.5

Alig

36.9 ± 22.9

95.2 ± 31.1

139 ± 6

1872 ± 48

9.2 ± 5.1

4.8 ± 3.0

39.9 ± 8.7


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Fig. 3. Comparison of collagen and fibronectin matrix morphology. (Left) SHG imaging of eCDM collagen, and (mid) fibronectin immunostaining (in red) for (a) Dis eCDM and (b) Alig eCDM, respectively. Right images show the merge. Lower images show eCDM z-profiles. Scale bars: 100 µm. Scale bars in z-profiles: 20 µm.

3.2. eCDM architecture controls cell morphology, spreading, and division axis. We next studied how the topology of the eCDM influenced cell morphology in terms of actin cytoskeleton and focal adhesions organization. We seeded again NIH3T3 fibroblasts on Dis, Jag, and Alig eCDMs, and on fibronectin (FN)-coated flat surfaces as control. Fibronectin, and not collagen, was selected as control because the former was identified in CDMs with larger (but similar) quantities (see Fig 3), in agreement with previous works 16. The majority of cells seeded on flat surfaces showed a characteristic spread phenotype with enhanced stress fibers and focal adhesions (FA), mainly focal contacts, located mostly at the cell periphery (see Fig.4a, Table 2, and Movie S1). Very few cells showed a spindle-like morphology (see Table 2). In contrast, cells


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seeded on Dis, Jag, and Alig eCDMs showed a spindle-like and dendritic phenotype, with multiple thin protrusions growing along matrix fibers, which directed the growth of FA (see white arrowheads highlighting the overlaps of FA with matrix fibers in Fig.4b-c right, Table 2, and Movie S1). However, on Alig and Jag eCDMs (Alig/Jag eCDMs), the local organization of the matrix (at the scale of the cell) led to equal elongated and oriented cell phenotypes; no significant differences on cell morphology were observed. Differences were only appreciated for long-term dynamic processes. In all eCDM cases, cells displayed a reduced number of stress fibers and, strikingly, a large number of small FA distributed all across the cell body, in contrast to 2D (see Fig.4b-c left, and Table 2). On Alig/Jag eCDMs, FA were aligned mainly along the eCDM orientation axis (see yellow arrow in Fig.4c), whereas they were randomly distributed on Dis eCDMs (see Fig.4c, right). Finally, we observed that cells were distributed on top, bottom and embedded within the eCDM (see Fig.4b-c, right green arrowheads and Table 2), revealing the 3D nature of the engineered matrices. Taken together, these results show that engineered matrices impact on cell morphology, orientation and cytoskeleton organization, favoring the oriented growth of protrusions and focal adhesions along the direction set by the matrix fibers.

Table 2. Morphological characterization of cells Phenotype (%)

Distribution (%)

Focal Adhesions ( # FA·cell-1)

Top

Inside

Spread

Spindle

Stress Fibers (High/Low)

Flat – FN

86 ± 3

14 ± 3

High

28 ± 16

N/A

N/A

Dis eCDM

41 ± 28

59 ± 28

Low

65 ± 27

43 ± 8

58 ± 8

Alig/Jag eCDM

3±4

97 ± 4

Low

75 ± 48

51 ± 1

49 ± 1

Condition


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Figure 4. eCDM architecture impacts on cell cytoskeleton phenotype. NIH3T3 fibroblasts deposited on (a) flat FN-coated surfaces, (b) Dis eCDMs, and (c) Alig/Jag eCDMs, and stained for F-actin (in red), and paxillin (in green). The right columns show magnified images. In white, the SHG image of the eCDM showing the collagen. The yellow arrows in (c) show the main eCDM orientation axis. White arrowheads show the overlap between matrix architecture and protrusions orientation. Green arrowheads highlight cells embedded within the 3D matrix. Scale bars: 100 µm. We next studied how cellular protrusions organized during protrusions elongation (spreading). On FN-coated surfaces, protrusions were widely distributed and oriented towards the front edge displaying well-defined filopodial and lamellipodial morphologies (see Fig.5a-b and Movie S1). Analysis of protrusions distribution showed that protrusions were oriented mainly towards the direction of cell motion (β≈0º, 0º≤β≤360º) (see Fig.5c, left), but also distributed all around the cell periphery, including the back edge of the cell (β≈180º). In this case, long-lasting non-


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efficient protrusions were observed 24. We also found that, in average, cells maintained the same number of protrusions (lamellipodia and filopodia) during time (see Table 3). On the contrary, cells seeded on Dis and Alig/Jag eCDMs grew multiple and highly elongated thin protrusions (see Fig.5a mid and lower, Table 3, and Movie S1). This is a consequence of eCDM architecture where fibers acted as a guide to direct protrusions growth. Large magnification images showed the morphology of protrusions (see Fig.5b). On both Dis and Alig/Jag eCDMs, protrusions displayed a highly branched, lobopodial-like morphology with the presence of membrane blebs. This is in contrast to flat surfaces where protrusions showed a smooth and spread morphology. Protrusions were again oriented around β≈0º (direction of cell motion) but with higher frequency compared to 2D, and the number of back protrusions (β≈180º) was significantly reduced (see Fig.5c). Similarly, the average number of protrusions was significantly reduced for Alig/Jag eCDM (see Table 3), in contrast to Dis eCDM and 2D conditions, highlighting the spindle-like morphology of cells. Finally, we analyzed how cell microenvironment influenced the length and growing kinetics of protrusions during migration. For this, we measured cell protrusions length (LP) at the cell front (FP) and back (BP) at different time points for 24h (see Fig.5d). Back protrusions length grew linearly for cells seeded on flat surfaces, whereas it remained constant over time on eCDMs (Dis and Alig/Jag). At 24h, LP was about 4-fold larger in 2D compared to eCDMs. Front protrusions showed larger LP values on Alig/Jag eCDMs for all time points, displaying a continuous – slight – increase over time for all conditions. The obtained results in protrusions length are directly related to cell morphodynamics properties. The structural properties of the ECM directs the growth of cellular protrusions by reorganizing the inner actin cytoskeleton which impacts on cell phenotype, cell migration mode and dynamics, and persistence

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. Our data suggest that the longer LP (FP), the more directional the cell motion is


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with larger polarity. We qualitatively assessed this assumption finding that longer (shorter) front (back) protrusions corresponded to spindle-like cell phenotypes displaying lobopodial-like protrusions, leading to a more directed cell motion and larger persistence (length and time) (see Fig.6a). This suggests that the actin gel is mainly localized at the cell front and used to polarize the cell, build long lobopodia-like protrusions, and initiate directed locomotion. In contrast, shorter (longer) front (back) protrusions corresponded to more spread phenotypes (lamellipodiadriven protrusions), displaying shorter cell persistence (see Fig.6a). This suggests that rear protrusions are non-efficient which act as a dragging force. Finally, we assessed whether matrix architecture influenced cell cytokinesis morphodynamics. Cells seeded on flat surfaces displayed the canonical morphology of dividing cells, with two rounded-shaped cells physically divided by the cytokinetic ring, with no preferential orientation (−90º≤θ≤90º) during division (see Fig.5e-g, and Movie S2). In this case, external forces applied on the body of cells were reported to be the responsible of controlling cell division axis during mitosis.28 On 3D environments this regulation is less understood. To shed light into it, we next seeded cells on Dis eCDMs (see Fig.5e, mid). In this scenario, cells displayed a similar stochastic orientation distribution (see Fig.5g, mid). However, cell morphology during division was completely different as a result of the different physical interaction between the cell and the 3D environment. Surprisingly, cells maintained intact protrusions (mainly two) and remained anchored to the cell body throughout division, in contrast to flat surfaces, where cells showed a rounded-shaped morphology displaying mainly short retraction fibres linking the cell to the underlying surface 1 (see Table 3). Multiple blebs both on the cell body and, in particular, along protrusions were frequently observed during division (see Fig.5e, Fig.5f, mid, and Table 3). The latter was most probably a consequence of the disruption of the cytoskeleton caused by the


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structural properties of the eCDM, known as ´pearling transition´

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29

. This is supported by the

reduced values obtained in 2D surfaces (see Table 3). Note that similar structures have already been observed in live cells when depleted of cortical actin 30. Cells seeded on Alig/Jag eCDMs showed similar morphological features (see Fig.5e lower, and Movie S2). Prior division, cells displayed an elongated morphology with long protrusions (see Fig.5e). Similar to Dis eCDM, cells showed multiple blebbing and maintained intact ´pearling´-like protrusions during division (see Table 3). As the cell began to divide, the cellular protrusions became thinner and oriented perpendicular to the cell division axis (θ≈0º), i.e. along the Alig eCDM main orientation (α≈0º) (see Fig.5e) 31. After division, the daughter cells spread and started migrating along the same orientation, suggesting that the mechanical interaction of cells with the physical 3D environment regulate cytokinesis orientation by controlling the orientation of cell protrusions. The average cell division plane confirmed this hypothesis; it was distributed along θ≈0º, (see Fig.5g, right). Previous studies of cell division in 2D and 3D have reported the importance of protrusions in guiding cell division axis 28, 31-32. However, they did not report the presence of ´pearling´ transition in the anchored protrusions during mitosis. We propose that an interplay between mechanical forces (transmitted by the 3D microenvironment) and inner cytoskeleton disruption (by means of ´pearling´-like protrusions) may regulate cell division in native-like environments. Finally, it is worth mentioning that division kinetics (cell proliferation) was shown to be larger on eCDMs (both Dis and Alig/Jag) compared to flat FNcoated surfaces (see Fig.5h), even though no significant difference was observed in the division time of cells, in agreement with former works

28, 31

. This is most likely a consequence of the

biomolecular cues experienced by cells in the native-like matrices, and highlights the artificial nature of 2D environments for the study of cellular phenomena 7, 33.


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Altogether, the obtained results reveal that the architecture of the cell microenvironment governs both the spreading and length of protrusions, and determines the type of protrusion and the growing kinetics. Most importantly, the obtained results also show that the topology of the cell microenvironment critically influences cell morphodynamics, protrusion phenotypes and cytokinesis.

Figure 5. eCDM architecture governs protrusion elongation and orientation and cell division axis. (a) Time sequence showing the growth and orientation of representative cellular protrusions of NIH3T3 cells seeded on (upper) flat FN-coated, (mid) Dis eCDM, and (lower)


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Alig/Jag eCDM samples, respectively. (b) Magnified image of an elongating protrusion for all conditions. (c) Distribution of protrusion orientation angle β for all conditions. (d) Protrusions length (LP) at the cell front (FP) and back (BP) for all conditions and different time points. (e) Time sequence showing cell division on (upper) flat FN-coated, (mid) Dis eCDM, and (lower) Alig/Jag eCDM, respectively. (f) Magnified image of a dividing cell for all conditions. Note the significant blebbing of cells seeded on eCDMs. (g) Distribution histograms of cell division angle θ for all conditions. (h) Cell growth kinetics. Data: mean ± SD (Data set: flat, N=3, n>100 cells; Dis and Alig/Jag N=5, n>200 cells). Time in hh:mm. Scale bars: 50 µm. Table 3. Characterization of protrusion morphodynamics during cell spreading and division Condition

Spreading

Division # extended protrusions

# protrusions

Blebbing

0h

12h

24h

During division

Protrusions

Cell body

Flat – FN

4.0 ± 1.2

3.8 ± 1.1

3.9 ± 1.4

0.3 ± 0.4

19%

50%

Dis eCDM

3.1± 1.1

3.5± 1.6

3.7± 1.6

1.6 ± 0.6

70%

100%

Alig/Jag eCDM

1.5± 0.6

1.5± 0.9

1.5± 0.7

1.7 ± 0.8

78%

80%

3.3. eCDM topology determines cell invasion and migration strategy. We assessed the impact of matrix topology on cell migration. NIH3T3 cells seeded on flat FNcoated surfaces moved randomly leading to isotropically-distributed migration tracks (see Fig.6a and Movie S3). Flat collagen-coated surfaces were also studied leading to similar cell phenotypes and dynamics (see Fig.S2 and Supporting Methods). Similarly, on Dis eCDM, cells displayed Brownian-like behaviors, even though individual cell trajectories were more linear (see Fig.6a, and Movie S3). In contrast, cells seeded on Jag eCDMs guided their motion along the


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direction set by the jagged-like network with α=±45º (see Fig. 6a, and Movie S3). Similarly, cells seeded on Alig eCDMs oriented the direction of long-term cell motion along α=0º, displaying high directionality (see Fig.6a and Movie S3). We next explored the invasion capability of cells which is a critical parameter for the development of scaffolds for tissue engineering applications. Indeed, we observed cells passing through matrix pores demonstrating again the 3D nature of the engineered matrices (see Fig.6b and Movie S4). During invasion on Dis and Alig/Jag eCDMs, cell nucleus physically interacted with matrix pores and fibers, being frequently deformed influencing cell trajectories (see Fig.6c yellow arrowhead, and Movie S4). We did not observe a significant difference in cell invasion efficiency for the three different conditions even though the larger pore size for Dis eCDM may suggest larger invasion efficiency in this condition (see Fig.2e). This result highlights the role of the cell nucleus in setting the direction and invasion capability of cells in 3D environments. Finally, we observed that cells seeded on eCDMs displayed unconventional migration strategies compared to the canonical ´tadpole´ phenotype – triangular – of cells seeded on flat surfaces. On eCDMs multiple lobopodial-like protrusions and blebs were frequently observed, in particular on Alig/Jag eCDMs, where the formation of these structures was more frequent due to the matrix morphology (see Fig.6d yellow arrowheads, and Movie S4). Altogether, we found that cell motion was governed by a well-regulated interplay between cell-ECM interaction and the orientation of matrix bundles and nanofibers, enabling contact guidance of cells

11, 34

. This

reveals that matrix topology critically impacts on actomyosin cytoskeleton organization and dynamics and determines the locomotion mode of cells and protrusions type.


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Figure 6. eCDM topology influences cell migration, invasion and locomotion strategy. (a) (Upper) NIH3T3 migration trajectories on flat FN-coated surfaces, Dis eCDMs, Jag eCDMs, and Alig eCDMs, respectively, for 24h. (Lower) Typical examples of migrating cells for each condition. (b-c) Cell invasion through a matrix pore and nucleus deformation, respectively. (d) NIH3T3 cell with branched lobopodial-like protrusions (see yellow arrowheads) migrating linearly. Data set in (a): n>30 cells. Scale bars: 100 µm.

Finally, we studied how eCDMs influenced the morphodynamics of different cell types. For this, we seeded MG63 human osteosarcoma fibroblasts, MDCK epithelial, and hSEC endothelial


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cells on FN-coated flat surfaces, and Dis and Alig/Jag eCDMs (see Fig.7 and Movie S5). We found that MDCK seeded on FN-coated surfaces displayed the canonical phenotype composed of one-cell thick coherent sheet of spread cells tightly connected, with cell-cell junctions clearly visible (see Fig.7). Cells migrated collectively relatively fast, with cell fingers growing at the border of the colony. In contrast, cells seeded on both Dis and Alig/Jag eCDMs organized into multicellular 3D spherical structures reminiscent to features of epithelial tissues in vivo (see Fig.7 and Movie S5) 35. Previous works have reported that MDCK cells embedded in a collagen type I matrix form cysts 36-37. Strikingly, live cell imaging showed that the generated small cysts were highly motile whereas larger ones did not migrate. This observation suggests that eCDMs could be a good model to elucidate how extracellular factors impact on tissue morphogenesis to specify the architecture of epithelial tissues. We next seeded MG63 fibroblasts on FN-coated surfaces (see Fig.7). Cells were highly motile and migrated individually with a highly polarized phenotype following random paths. When seeded on eCDMs, cells showed a highly elongated, spindle-like phenotype with long protrusions, migrating linearly along randomly-distributed matrix fibers. Migration speed was lower compared to FN-coated surfaces, most probably due to higher cell-matrix adhesion (see Movie S5). We finally seeded hSEC endothelial cells on FNcoated surfaces. Cells showed a very spread phenotype with multiple growing and retracting protrusions (see Fig.7). Strikingly, hSECs migrated as individual cells following random walk trajectories. On the contrary, hSECs seeded on Dis and Alig/Jag eCDMs cells showed a completely different phenotype with organoid-like morphology. Further, on Alig/Jag eCDMs, cells showed an elongated structure, suggesting that the architecture of the matrix guided the collective organization of the cell organoid (see Movie S5).


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Altogether, the obtained results demonstrate that matrix topology critically influences cell migration morphodynamics. The observed morphological and functional differences for all cell types in 2D and 3D environments indicates that eCDMs provide a reliable ECM in vitro model to understand the structure and dynamics of cells in a native-like environment.

Figure 7. Different cell types seeded on eCDMs. MDCK epithelial, MG63 osteosarcoma, and hSECs endothelial cells seeded on flat, Dis eCDM and Alig/Jag eCDM, respectively. Yellow arrows indicate the orientation of the matrix (see also Movie S5). Scale bars: 50 µm.

4. DISCUSSION Recent discoveries of in vivo cellular processes have generated the need for physiologicallyrelevant in vitro ECM models in which cell-cell, cell-ECM, and structural properties can all be controlled. This accounts for reproducing not only the native-like composition of matrices but also its architecture 14, 38. To this aim, we have developed a new methodology to generate highly organized and in-vivo-like 3D extracellular matrices with pre-defined – complex – architectures. The growth of the matrices was performed by using ´sacrificial´ fibroblasts seeded on polymeric guiding templates. We generated native-like matrix networks which were used to study how cells responded to the surrounding environment. We focused on analyzing cell protrusion, division,


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and migration morphodynamics obtaining striking differences when compared to 2D condition. We revealed how fiber alignment enhanced cellular protrusions orientation and length. We found that cell cytokinesis was strongly affected by matrix dimensionality by guiding cell division axis. Finally, we studied how matrix anisotropy impacted on cell migration. Cells deposited on Dis eCDMs displayed random-like behaviors, but with long linear paths, whereas cells seeded on Alig and Jag eCDMs displayed highly directional motions (linear and jagged-like). The developed matrices are far from synthetic fibers which are typically used for similar studies which, in general, lack of the composition and mechanical properties of native ECM. Further, the engineered cell-derived matrices are significantly different from traditional physiological materials, such as MatrigelTM. Matrigel consists mainly of basement membrane molecules (Laminin, Collagen IV, Perlecan, and other non-fibrous proteins), which makes it more comparable to the composition of the basement membrane 39. In contrast, the (engineered) CDMs are mainly composed of Collagen I and III, but not IV, Fibronectin, together with small traces of non-organized Laminin, and Perlecan

25

. This makes CDMs to be comparable to the

fibrous mesh that characterizes a mesenchymal stroma, in which predominate proteins such as Fibronectin and Collagen I and III 40. Our methodology is very versatile allowing different architectures and morphologies to be tested recreating different in vivo scenarios. This allows, for example, to mimic in vitro physiological and pathological events and to test new therapeutic strategies. In this regard, the generated polarized (aligned) matrices are reminiscent of tumoral tissues, such as breast cancer, which contains a large amount of aligned collagen bundles. Further, helical structures observed in malignant ovarian tumours are similar to the developed jagged-like microstructures 41. These


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bundles alter normal cellular responses and facilitate invasion by providing tracks on which cells escape from the tumor 42. Altogether, the developed matrices provide a physiologically-relevant environment to assess the molecular mechanisms involved in these in vivo phenomena, in a well-controlled and simple manner. Note finally that the experimental conditions used to generate the matrices (cell types, culture timings and conditions, and cell extraction protocols) may impact on their molecular composition, morphology, and mechanical properties, and therefore, may influence the behavior of cells seeded on them. 43

5. CONCLUSIONS We have developed a novel and highly versatile methodology to generate native-like extracellular matrices with well-defined architectures which recapitulate the structural and biochemical complexity of certain features of the in vivo environment. The combination of micro/nanofabrication tools with cell biology techniques enabled a tight control on matrix architecture as well as in pore and fiber orientation. We applied the developed platform to study the behavior of cells in terms of cytoskeleton morphology, protrusions activity, cytokinesis, and locomotion. We found that Alig and Jag eCDMs acted as a guide to direct cell protrusions growth and whole cell migration. Cells displayed longer front protrusions, larger proliferation, and migration capabilities compared to 2D assays, where cell activity was significantly perturbed, highlighting their artificial nature for the study of cellular phenomena. Altogether, the obtained results show that the developed platform provides a reliable model of the native ECM. This allows recreating in vitro ECM morphologies typically encountered in vivo during physiopathological processes.


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ASSOCIATED CONTENT Supporting information. Supporting Figures, Methods, Movies of cells on eCDMs and captions. AUTHOR INFORMATION Corresponding Author * David Caballero and Josep Samitier Nanobioengineering group – IBEC, C/ Baldiri Reixac 15-21, Barcelona Science Park, 08028 Barcelona, Spain; Tel: +34 93 403 71 85. E-mail: (D.C.) [email protected]; (J.S.) [email protected] Author Contributions D.C. and J.S. designed research. D.C. performed experiments and analyzed data. The manuscript was written through contributions of both authors. Both authors have given approval to the final version of the manuscript. Funding Sources D.C. acknowledges the support of the Secretary for Universities and Research of the Ministry of Economy and Knowledge of the Government of Catalonia and the COFUND program of the Marie Curie Actions of the 7th R&D Framework Program of the European Union (2013 BP_B 00103). This work was supported by Networking Biomedical Research Center (CIBER), Spain. CIBER is an initiative funded by the VI National R&D&I Plan 2008-2011, Iniciativa Ingenio 2010, Consolider Program, CIBER Actions, and the Instituto de Salud Carlos III, with the support of the European Regional Development Fund. This work has been financially supported


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by the Commission for Universities and Research of the Department of Innovation, Universities, and Enterprise of the Generalitat de Catalunya (2014 SGR 1442). This work was partially supported by the project MINDS (TEC2015-70104-P), awarded by the Spanish Ministry of Economy and Competitiveness. ACKNOWLEDGMENTS The authors acknowledge the ICTS “NANBIOSIS” Nanotechnology Platform Unit of the CIBER in Bioengineering, Biomaterials & Nanomedicine (CIBER-BBN) at the Institute for Bioengineering of Catalonia for assistance in the microfabrication. IRB Imaging facility and D.Izquierdo (Nanobioengineering group – IBEC) are acknowledged for technical support. I.Cano and E.Engel (Biomaterials for Regenerative Medicine group IBEC) are acknowledged for supplying the anti-fibronectin antibody.

ABBREVIATIONS Alig eCDM, aligned engineered cell-derived matrices; Dis eCDM, disordered engineered cellderived matrices; eCDM, engineered cell-derived matrices; ECM, extracellular matrix; FN, fibronectin; Jag eCDM, jagged engineered cell-derived matrices; RT, room temperature.

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Figure 1. eCDM fabrication procedure. (a-b) Schemes showing the fabrication of the PDMS guiding templates and eCDM growth, respectively. After eCDM extraction by cell lysis, cells of interest were deposited at the optimal density. (c-d) Phase-contrast microscopy images of the fabricated PDMS (upper) flat surface, and (mid and lower) micro-grooves (orthogonal and parallel), and NIH3T3 fibroblasts seeded on top of them, respectively. (e) SHG images of the extracted eCDMs showing different porous architectures. (Upper) Disordered, (mid) Jagged, and (lower) aligned eCDMs, respectively. Scale bars: 100 um. 132x100mm (300 x 300 DPI)


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Figure 2. Characterization of eCDM alignment. (a) Distribution of fiber (a_F), and (b) pore (a_P) orientation angles for Dis, Jag and Alig eCDMs. Alig eCDMs show a main orientation peak centered at 0º. Jag eCDMs show two main peaks centered around ±45º. Dis eCDMs show no preferential orientation. (c) FFT analysis of eCDM morphology for Dis, Jag and Alig eCDMs. The latter shows a clear intensity peak centered at 135º which matches the main orientation angle of the matrix network and guiding template (0º). Note that this value was considered as 0º for simplicity in the FFT analysis. (d) Fiber length (LF), and (e) projected pore area (AP) analysis for all conditions. No significant difference was obtained for LF between all three conditions, whereas AP was larger for Dis and Jag eCDM conditions. Upper panels in (d) and (e) display an scheme of the measured parameters. (Data set: N=3, n>500 fibers, 1000 pores). Data: mean ± SD; *P100 cells; Dis and Alig/Jag N=5, n>200 cells). Time in hh:mm. Scale bars: 50 um. 158x135mm (300 x 300 DPI)


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Figure 6. eCDM topology influences cell migration, invasion and locomotion strategy. (a) (Upper) NIH3T3 migration trajectories on flat FN-coated surfaces, Dis eCDMs, Jag eCDMs, and Alig eCDMs, respectively, for 24h. (Lower) Typical examples of migrating cells for each condition. (b-c) Cell invasion through a matrix pore and nucleus deformation, respectively. (d) NIH3T3 cell with branched lobopodial-like protrusions (see yellow arrowheads) migrating linearly. Data set in (a): n>30 cells. Scale bars: 100 um. 162x132mm (300 x 300 DPI)



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Figure 7. Different cell types seeded on eCDMs. MDCK epithelial, MG63 osteosarcoma, and hSECs endothelial cells seeded on flat, Dis eCDM and Alig/Jag eCDM, respectively. Yellow arrows indicate the orientation of the matrix (see also Movie S5). Scale bars: 50 um. 49x28mm (300 x 300 DPI)


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Topological Control of Extracellular Matrix Growth: A Native-Like

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