Hydrogels with stiffness-degradation spatial patterns control anisotropic 3D cell response

Abstract

In nature, tissues are patterned, but most biomaterials used in human applications are not. Patterned biomaterials offer the opportunity to mimic spatially segregating biophysical and biochemical properties found in nature. Engineering such properties allows to study cell-matrix interactions in anisotropic matrices in great detail. Here, we developed alginate-based hydrogels with patterns in stiffness and degradation, composed of distinct areas of soft non-degradable (Soft-NoDeg) and stiff degradable (Stiff-Deg) material properties. The hydrogels exhibit emerging patterns in stiffness and degradability over time, taking advantage of dual crosslinking: Diels-Alder covalent crosslinking (norbornene-tetrazine, non degradable) and UV-mediated peptide crosslinking (matrix metalloprotease sensitive peptide, enzymatically degradable). The materials were mechanically characterized using rheology for single-phase and surface micro-indentation for patterned materials. 3D encapsulated mouse embryonic fibroblasts (MEFs) allowed to characterize the anisotropic cell-matrix interaction in terms of cell morphology by employing a novel image-based quantification tool. Live/dead staining showed no differences in cell viability but distinct patterns in proliferation, with higher cell number in Stiff-Deg materials at day 14. Patterns of projected cell area became visible already at day 1, with larger values in Soft-NoDeg materials. This was inverted at day 14, when larger projected cell areas were identified in Stiff-Deg. This shift was accompanied by a significant decrease in cell circularity in Stiff-Deg. The control of anisotropic cell morphology by the material patterns was also confirmed by a significant increase in filopodia number and length in Stiff-Deg materials. The novel image-based quantification tool was useful to spatially visualize and quantify the anisotropic cell response in 3D hydrogels with stiffness-degradation spatial patterns. Our results show that patterning of stiffness and degradability allows to control cell anisotropic response in 3D and can be quantified by image-based strategies. This allows a deeper understanding of cell-matrix interactions in a multicomponent material.

Full text

Biomaterials Advances 151 (2023) 213423
Available online 25 April 2023
2772-9508/© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-
nc-nd/4.0/).
Hydrogels with stiffness-degradation spatial patterns control anisotropic 3D
cell response
Claudia A. Garrido
a
,
b
, Daniela S. Garske
a
,
b
, Mario Thiele
b
, Shahrouz Amini
a
, Samik Real
e
,
Georg N. Duda
b
, Katharina Schmidt-Bleek
b
, Amaia Cipitria
a
,
c
,
d
,
*
a
Max Planck Institute for Colloids and Interfaces, Potsdam, Germany
b
Julius Wolff Institute, Berlin Institute of Health at Charit´
e - Universit¨
atsmedizin Berlin, Berlin, Germany
c
Group of Bioengineering in Regeneration and Cancer, Biodonostia Health Research Institute, San Sebasti´
an, Spain
d
IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
e
Digital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany
ARTICLE INFO
Keywords:
Biomaterials
Stiffness
Degradation
3D cell-matrix interaction
Anisotropic cell response
Cell morphology
Image-based quantication tool
ABSTRACT
In nature, tissues are patterned, but most biomaterials used in human applications are not. Patterned bio-
materials offer the opportunity to mimic spatially segregating biophysical and biochemical properties found in
nature. Engineering such properties allows to study cell-matrix interactions in anisotropic matrices in great
detail. Here, we developed alginate-based hydrogels with patterns in stiffness and degradation, composed of
distinct areas of soft non-degradable (Soft-NoDeg) and stiff degradable (Stiff-Deg) material properties. The
hydrogels exhibit emerging patterns in stiffness and degradability over time, taking advantage of dual cross-
linking: Diels-Alder covalent crosslinking (norbornene-tetrazine, non degradable) and UV-mediated peptide
crosslinking (matrix metalloprotease sensitive peptide, enzymatically degradable). The materials were me-
chanically characterized using rheology for single-phase and surface micro-indentation for patterned materials.
3D encapsulated mouse embryonic broblasts (MEFs) allowed to characterize the anisotropic cell-matrix
interaction in terms of cell morphology by employing a novel image-based quantication tool. Live/dead
staining showed no differences in cell viability but distinct patterns in proliferation, with higher cell number in
Stiff-Deg materials at day 14. Patterns of projected cell area became visible already at day 1, with larger values in
Soft-NoDeg materials. This was inverted at day 14, when larger projected cell areas were identied in Stiff-Deg.
This shift was accompanied by a signicant decrease in cell circularity in Stiff-Deg. The control of anisotropic cell
morphology by the material patterns was also conrmed by a signicant increase in lopodia number and length
in Stiff-Deg materials. The novel image-based quantication tool was useful to spatially visualize and quantify
the anisotropic cell response in 3D hydrogels with stiffness-degradation spatial patterns. Our results show that
patterning of stiffness and degradability allows to control cell anisotropic response in 3D and can be quantied
by image-based strategies. This allows a deeper understanding of cell-matrix interactions in a multicomponent
material.
1. Introduction
Patterns are naturally occurring in nature, macroscopically and
microscopically. The constant remodeling of the extracellular matrix
(ECM) leads to emergent patterns of cells, ECM properties and cell
behavior [1,2]. Biomaterials like hydrogels are a useful tool to study
cell-matrix interaction as they can mimic various characteristics of the
cell niche [3]. Multiple approaches have been taken to study cell
response to specic ECM properties, for example: materials with
different stiffness to study focal adhesions [4] and mechanosensation
[5], stress relaxing materials to mimic the viscoelastic behavior of bio-
logical tissues [6], independent control of mechanical properties and
bronectin presentation for stem cell engineering [7], modications in
the scaffold architecture and pore distribution [8], or biomolecule pre-
senting/releasing materials [9]. Patterned materials will offer the op-
portunity of imitating and guiding cell behavior with a closer relation to
the natural counterpart.
Alginate is a natural, biocompatible and inert polymer. Its versatile
* Corresponding author at: Max Planck Institute for Colloids and Interfaces, Potsdam, Germany
E-mail address: Amaia.Cipitria@mpikg.mpg.de (A. Cipitria).
Contents lists available at ScienceDirect
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journal homepage: www.journals.elsevier.com/materials-science-and-engineering-c
https://doi.org/10.1016/j.bioadv.2023.213423
Received 24 January 2023; Received in revised form 3 April 2023; Accepted 5 April 2023

Biomaterials Advances 151 (2023) 213423
2
structure allows modications to modulate key biophysical cues.
Chemical modications of the alginate structure, such as thiolation [10],
oxidation [11], amidation [12] and Diels-Alder addition [13,14] can be
the base to implement additional crosslinking, improve or control
degradation behavior or enable a controlled drug release. Alginate is
capable to be crosslinked by various means such as ionic and covalent
crosslinking [15]. That capability opens the possibility to mimic and
control distinct ECM properties. Alginate can thus be made such that a
relatively broad range of mechanical properties can be covered or a
dynamic environment can be provided to cells [11,16].
Multiple biophysical and biochemical factors contribute to the
complexity of the ECM. The interplay between these factors is a current
topic of research. The mechanical properties of the ECM have been
examined in single-phase 3D hydrogels with different elastic modulus,
showing that the stiffness has an effect on cell phenotype [17,18] and
cell migration [19]. The degradability of the material is important to
create dynamic 3D matrices and it can affect cell spreading, cell in-
teractions [20] and morphology [21,22]. Fewer studies investigate the
interaction of stiffness and degradation on cell behavior in 3D encap-
sulated cells. Previous research showed that the simultaneous modula-
tion of stiffness and degradation can inuence cell proliferation or
differentiation [23] and thereby control cell phenotype [24].
The combination and spatial patterning of biophysical and
biochemical cues can replicate complex structures of a native ECM and
allow structural properties to emerge. Previous research on photo-
patterning showed the potential of tuning biophysical and biochemical
cues in patterned materials [25]. To study the effect of stiffness and
degradation on 3D cell behavior, we use the combination of two
different types of crosslinking. The rst type of crosslinking is covalent
Diels-Alder click chemistry, which offers an efcient and versatile re-
action for hydrogel formation [11,13]. The second type of crosslinking,
UV-mediated thiol-ene peptide binding, offers tunable degradability by
the matrix metalloprotease enzymes secreted by encapsulated cells [16].
Despite the numerous research performed on single-phase materials,
fewer investigations are looking at cell response in multicomponent
matrices such as patterned materials.
Dual crosslinked, patterned hydrogels previously described have
shown an effect on cells attached to 2D substrates, such as in cell
alignment [26], protein expression and differentiation [27,26]. Previous
research in 3D cell encapsulation showed that patterns in biochemical
cues can inuence cell migration [28] and localized growth [29],
whereas patterns in biophysical cues can inuence cell interactions [30].
Research performed on patterning multiple mechanical or biochemical
characteristics has shown promising results on guiding cell behavior
[31]. Our research focuses on evaluating the cell response in patterned
hydrogels with spatially discrete patterns in degradation and stiffness.
Furthermore, the evaluation of the cell response in patterned materials
has been limited to the independent evaluation of each phase; no
method has been proposed to quantitatively assess patterned cell
response in a multicomponent matrix. To achieve this, an image-based
analysis tool is required.
Here we present alginate-based hydrogels with anisotropic stiffness-
degradation spatial patterns and compatible with 3D cell encapsulation.
The hydrogels exhibit emerging patterns in stiffness and degradability
over time, taking advantage of dual covalent Diels-Alder click cross-
linking and UV-mediated peptide crosslinking. Further, we develop a
novel quantitative, image-based analysis tool to evaluate the emerging
anisotropic cell behavior in 3D and over time. We characterize cell
morphology and proliferation in photopatterned materials and compare
the results with equivalent single-phase materials. Such patterned ma-
terials allowing the emergence of 3D anisotropic cell response, together
with the image-based analysis method, are valuable tools to understand
cell-matrix interactions in multicomponent materials.
2. Materials and methods
2.1. Alginate modication
To form the click-crosslinking, norbornene and tetrazine must be
added in the alginate backbone. The alginate used was low molecular
weight, high guluronic acid sodium alginate (MW 75 kDa Pronova UP
VLVG; NovaMatrix). The coupling of norbornene (N, TCI Chemicals,
#N0907) and tetrazine (T, Conju-probe, #CP-6021) to the alginate
molecule was performed as previously described [27], adapting the
molecular weight (<75 kDa, information given by provider). Alginate
modication with norbornene was performed with a theoretical degree
of substitution (DS
theo
) of DS
theo
500. Alginate modication with tetra-
zine was performed with a DS
theo
170. To determine the actual DS
(DS
actual
) required to ensure appropriate norbornene to tetrazine (N:T)
ratios for crosslinking, NMR measurements were performed, using a 1.5
% w/v alginate solution in deuterium oxide (64 scans; Agilent 400 MHz
Premium COMPACT equipped with Agilent OneNMR Probe) and
analyzed using MestreNova Software (version 12.03) (Supplementary
Fig. S1; Supplementary Table S1).
2.2. Mouse embryonic broblast (MEF) cell culture
Mouse embryonic broblasts (SCRC-1040; ATCC) were cultured in
Dulbecco's Modied Eagle's Medium (Sigma, #D5546) supplemented
with 3.5 g/L glucose (VWR, # 0188), 15 % v/v fetal bovine serum
(Biochrom, #S0615), and 1 % penicillin/streptomycin (Gibco,
#15140–122). Cells were maintained in a 5 % CO
2
environment at 37 ◦C
and passaged every 3–5 days. For 3D encapsulation, cells were used at
passage 16.
2.3. Hydrogel formation
The hydrogel formation was performed based on previously estab-
lished protocols [27] with modications in N:T ratios and alginate
concentration, as described below.
2.3.1. Non-degradable matrix: click-crosslinked hydrogels
The precursors for the hydrogel were dissolved in phosphate-
buffered saline (PBS, without Ca
2+
, Mg
2+
and phenol red; Biozym)
and distributed into 2 tubes. The rst tube contained norbornene-
modied alginate (N-alg); MMP-sensitive (MMPsens) peptide (GCRD-
VPMS↓MRGG-DRCG, 98 % purity; WatsonBio) at a nal concentration
of 10 mg/mL of hydrogel, thiolated RGD-peptide (CGGGGRGDSP; Pep-
tide 2.0) at a concentration of 5 molecules of RGD per alginate chain (DS
5, 1.17 mM), and the cell suspension at a nal concentration of 5 ×10
6
cells/mL of hydrogel. The second tube contained tetrazine-modied
alginate (T-alg) and the photoinitiator (Irgacure 2959; Sigma-Aldrich,
#410896) at a nal concentration of 3 mg/mL of hydrogel. The total
nal concentration of alginate was 2 % w/v at an N:T ratio of 1.5.
The two solutions were mixed by pipetting and cast on top of a glass
plate, with the casting area being restricted on three sides by glass
spacers, and immediately covered with a glass slide previously treated
with SigmaCoat (≥99.5 %; Sigma-Aldrich, #SL2) to prevent adhesion.
The gel height was constrained to 2 mm by the thickness of the glass
spacers. Spontaneous click-crosslinking for 50 min at room temperature
(RT) and in the dark allowed the N:T covalent bonds to form. Despite
MMPsens and the photoinitiator being present, these were not activated
due to the lack of UV exposure. Nevertheless, the MMPsens and photo-
initiator need to be present to allow for patterned materials (see Section
2.3.3).
In order to ensure a homogeneous binding of the RGD-peptide,
crosslinked gels were exposed to 2 min UV light (365 nm) at 10 mW/
cm
2
(Omnicure S2000) in a custom-built exposure chamber. The cylin-
drical hydrogels were punched from the cast gel sheet using 5 mm bi-
opsy punches (Integra Miltex) and placed in growth media at 37 ◦C and
C.A. Garrido et al.

Biomaterials Advances 151 (2023) 213423
3
5 % CO
2
.
2.3.2. Degradable matrix: MMPsens peptide crosslinked hydrogels
The production of degradable materials followed the same procedure
as described in Section 2.3.1, with an additional step for the MMPsens
peptide crosslinking. After casting the hydrogel solution between the
glass plates, the material was exposed to UV light at 10 mW/cm
2
for 10
min to initiate the coupling of the degradable MMPsens peptide to the
norbornene-modied alginate via thiol-ene crosslinking. After the UV
exposure, the materials were placed for an additional 50 min at RT in the
dark to allow for the N:T covalent bonds to be formed. To ensure a
homogenous binding of RGD, the hydrogels were exposed again to UV
for 2 min. Hydrogels were punched out and incubated in growth media
at 37 ◦C and 5 % CO
2
.
As negative control materials, hydrogels were fabricated with pep-
tide crosslinkers not susceptible to degradation, MMP-scramble
(VpMSmRGG). In this case, the peptide contained the same sequence
as the degradable isoform but with some amino acids in the D-form
(indicated in lower case letters), rendering them unrecognizable to
matrix metalloprotease enzymes.
2.3.3. Patterned matrix: Dual crosslinked hydrogels
The creation of patterned materials followed the same procedure as
described in Section 2.3.2, with the addition of a photomask placed on
top of the cover glass during the UV mediated thiol-ene coupling of the
MMPsens peptide. The photomask had a pattern of straight lines with
500
μ
m thickness (UV light blocking sections, non-degradable matrix
equivalent to 2.3.1) placed 250
μ
m apart (UV light permitting sections,
degradable matrix equivalent to 2.3.2). A macroscopic view of the
pattern in the gel is included in Supplementary Fig. S2. After the 50 min
at RT incubation, in which all the N-T bonds were formed and therefore
no additional grafting of MMP peptides was expected, crosslinked gels
were exposed to 2 min UV light (365 nm) at 10 mW/cm
2
without a
photomask to ensure a homogeneous distribution of the RGD-peptide.
2.4. Mechanical characterization
Mechanical characterization was performed on day 1 and day 14. All
mechanical characterization was performed with cell-loaded materials
to quantify the enzymatic degradation of the hydrogels in stiff and
degradable (Stiff-Deg) materials. This was also true for soft and non-
degradable (Soft-NoDeg) materials to keep comparable conditions.
The material degradation was evaluated via three different methods:
unconned compression testing for measuring bulk elastic modulus of
single-phase materials, rheology to quantify loss and storage modulus of
single-phase materials and microindentation to estimate the surface
elastic modulus of single-phase and patterned materials.
2.5. Unconned compression testing
Single-phase materials were subjected to uniaxial unconned
compression testing (BOSE Test Bench LM1 system) with a 250 g load
cell (Model 31 Low, Honeywell) at 0.016 mm/s without preload as
previously described [11]. The elastic modulus E was calculated as the
slope of the linear region of the generated stress vs. strain curve, in the
2–10 % strain range, using a MATLAB (R2019b) script (n =6). The
required MATLAB inputs of hydrogel height and diameter were deter-
mined by lowering down the BOSE system top plate until contact with
the gel surface was established and by using calipers, respectively.
2.6. Rheology
Storage and loss modulus of single-phase hydrogels were determined
with a rheometer (Anton Paar MCR301) via frequency sweeps with a
parallel plate geometry of 8 mm (PP08, Anton Paar). The frequency
sweep was performed from 0.01 to 10 Hz and at 0.1 % shear strain at RT
(n =6). Once contact with the gel surface was established, a pre-
compression of 10 % of the height of the hydrogel was applied prior
to the measurement. No additional hydration was needed as the
experiment lasted <10 min. To obtain the elastic modulus, rst the shear
modulus (G) was derived from the storage (G') and loss (G") modulus
using Rubber's elasticity theory (Eq. (1)).
G=
G′2+G˝2
(1)
The elastic modulus (E) was calculated using the values of the shear
modulus obtained from Eq.1 [32] and the approximation of Poisson's
ratio (ϑ)equal to 0.5 [33] (Eq. (2)).
E=2G(1+ϑ)(2)
The mesh size (ξ) was approximated by Eq. (3), proposed for alginate
hydrogels, in which the storage modulus G' in low frequencies (0.1-1 Hz)
was used [34], with Nav being avogadro's number (6.022 10
23
1/mol), R
being the ideal gas constant (8,314 m
3
Pa/Kmol) and T being the room
temperature (293 K).
ξ=
6RT
G
´
π
Nav
3
(3)
2.7. Microindentation
2.7.1. Depth-sensing indentation/air-indent method
Depth-sensing microindentation measurements were done using a
Triboindenter TI-950 (Hysitron-Bruker, MN, USA) equipped with an XZ-
500 extended displacement stage, allowing a vertical displacement of up
to 500
μ
m [35]. After the rst contact to detect the surface, the tip was
retracted for ~300
μ
m. Next, the measurements were conducted using
the “air-indent” mode, allowing a reliable indentation curve without any
additional sample pre-contact. The measurements were done using a
cono-spherical tip of 50
μ
m radius and in automated mode to map an
area of 6 ×6 matrix, with an indentation spacing of 300
μ
m in single-
phase materials and 18 ×11 matrix, with an indentation spacing of
150
μ
m in patterned materials. The measurements were done in
displacement control mode, using a displacement function of 250
μ
m
retraction and 300
μ
m approach, with a strain rate of ~30
μ
m/s. To
ensure that samples remained hydrated during the experiment, these
were xed on top of a sponge using needles and partially submerged in
PBS.
2.7.2. Analysis of load-displacement curves
To meet the Hertzian contact model requirement, the rst 30
μ
m of
contact depth after initial contact, in which the tip geometry stays
spherical, was used for curve tting and calculation of the indentation
elastic modulus (Eq. (4)). This model was chosen as it describes the
contact mechanics of 3D solids and correlates the elastic modulus (E)
with the contact surface radius (R, 50
μ
m), load (y) and contact depth (x)
y=4
3×E×R0.5×x1.5(4)
Considering the high number of indents, the analysis of the load-
displacement curves was automated by a custom-made Python3 script.
The depth of the gel and the load of the indenter (both ordered by time)
are the main data vectors used for the analysis. This automation is
divided into four main parts: [1] identifying the point of interest (POI),
[2] extracting the curve segment, [3] tting the Hertzian model on the
extracted segment and [4] obtaining the indentation E value per
indentation point, collected in a matrix and depicted in a heat map.
Further information can be found in Supplementary Fig. S3.
2.8. Cell viability by live/dead staining
Cell viability was assessed after 1 and 14 days using Live/Dead
C.A. Garrido et al.

Biomaterials Advances 151 (2023) 213423
4
staining. The hydrogels were taken out from the incubation media and
washed with PBS. Then the cells were stained with a solution of 4 mM
calcein AM (TRC, #C125400) and 4 mM ethidium homodimer-1
(Thermo Fisher, #L3224) dissolved in PBS to identify live and dead
cells, respectively. The staining solution volume was 400
μ
L per
hydrogel, stained for 12 min in a cell culture incubator at 37 ◦C, 5 % CO
2
in the darkness. A nal washing step was performed with 400
μ
L of PBS
per hydrogel at RT for 5 min and protected from light.
Imaging was performed on a confocal microscope (Leica SP5, Ger-
many). Quantication of cell number and viability at each time point
was performed using ImageJ software (ImageJ 1.53 s) [36]. Hydrogels
were placed on thin cover glass to maximize the working distance and
allow a deeper z-stack. To ensure gel hydration during long confocal
image acquisition time, a drop of PBS was reapplied every 20 min.
In single phase materials, three independent positions per gel were
acquired at the gel center at 10×magnication, from 2 independent
samples, resulting in n =6 elds of view containing multiple single cells
(n >100). In patterned materials three independent positions per gel
were acquired at the gel center at 10×magnication with 2 ×2 tile
merging, to cover more stripes from the pattern in the eld of view, from
2 independent samples, resulting in n =6 elds of view containing
multiple single cells (n >100).
To assess cell proliferation (cell number per unit volume), differen-
tial swelling of soft and stiff hydrogels was taken into account, as
explained in Supplementary Information S4.
2.9. Cell morphology by DAPI/Phalloidin staining
To evaluate cell morphology, DAPI/Phalloidin staining was per-
formed after 1 and 14 days, visualizing nuclei and actin, respectively. All
steps were performed under orbital shaking, in a 24 well plate and using
a volume of 400 uL per gel. Encapsulated cells were xed in 4 % para-
formaldehyde solution (Sigma Aldrich, Sigma, #158127) for 45 min at
RT, then permeabilized with 0.3 % Triton X-100 (Sigma Aldrich,
#11488696) for 15 min, washed twice with 3 % bovine serum albumin
(BSA, Sigma, #A2153) in PBS for 5 min and stained in the dark with 4,6-
diamidino-2-phenylindole (DAPI; Sigma, #MBD0015) and TRITC-
conjugated Phalloidin (Cell Signaling, #8878S) for 3 h. A nal wash
was performed with 3 % BSA in PBS for 5 min at RT.
Three independent positions per gel were acquired at the gel center
using a confocal microscope (Leica SP5, Germany). For a general
quantication of cell morphology, 25×magnication was used and n =
6 elds of view (3 different images from 2 independent samples) were
taken, containing multiple single cells (n >50). In addition, ten single
cell images per gel (5 cells from 2 different hydrogels) were analyzed for
quantication of lopodia number and length. Images were obtained
from the center of the gel using 64×magnication.
2.10. Image-based analysis tool to study anisotropic multicomponent
materials
A custom-made image-based analysis tool in the form of a macro
written in ImageJ (ImageJ 1.53 s) [37] has been created to analyze
cellular readouts obtained from z-stack projections from anisotropic
patterned materials. The macro offers the possibility to freely divide an
image into rectangular units, which leads to a heat map in which the
results are later depicted. The background is separated from the cells via
a threshold. To compensate for pixel noise from the raw data, a denoise
function (median lter) is built in, which can be used with different
strengths depending on the image. In this way, a binary mask is created,
which is used for most of the calculations. For details on the binning size
optimization, refer to Supplementary Fig. S5.
Three readouts are calculated for every tile within the heat map:
Projected cell area, cell circularity and cell number. Projected cell area is
calculated for each cell as number of pixels and converted into
μ
m
2
or
mm
2
. Cell circularity is calculated for each cell as 4
π
*area/perimeter
2
,
where 1 indicates a perfect circle and values towards 0 indicate elon-
gated cells. Cell number is calculated as number of DAPI nuclei within
each tile. Every cell in a tile will be individually calculated and the mean
of all cells in a tile is used. Cells touching the tile border are excluded.
For further details, refer to Supplementary Fig. S6.
2.11. Statistical analysis
Results are depicted as bar graphs with mean and standard deviation,
or box plots with median, 1
st
and 3
rd
quartile, using OriginLab (Pro
2022b). Normal distribution of the data was checked using D'Agostino-
Pearson and Shapiro-Wilk test. Comparison of hydrogel mechanical
properties were performed using Student t-test (p <0.05). Comparison
of cellular read-outs were performed using Student t-test (p <0.05) for
normally distributed data and Wilcoxon Signed Rank test (p <0.05) for
not normally distributed data.
3. Results
3.1. Mechanical characterization
Single-phase Stiff-Deg and Soft-NoDeg materials were characterized
for their bulk elastic and viscoelastic properties at day 1 and day 14, as
well as changes over time, using rheology and unconned compression
testing. The hydrogels for mechanical testing had encapsulated mouse
embryonic broblasts, 5 ×10
6
cells/mL of hydrogel, with the purpose of
evaluating mechanical changes due to cell-secreted enzymatic degra-
dation. The storage modulus (G') of Stiff-Deg is higher than Soft-NoDeg
materials with average values of 3353 ±36 Pa and 530 ±10 Pa,
respectively, at day 1 (Fig. 1A) and 1848 ±41 Pa and 776 ±26 Pa at day
14 (Fig. 1B). The values of G' showed a decrease at day 14 (Fig. 1B)
compared to day 1 (Fig. 1A) for Stiff-Deg materials, whereas G" modulus
presented a similar behavior at day 1 and day 14 for both materials.
Bulk elastic modulus was characterized by unconned compression
testing (Fig. 1C). At day 1, there is a signicant difference between the
Soft-NoDeg (2 ±0.3 kPa) and Stiff-Deg (10 ±0.6 kPa) materials. At day
14, there is a signicant decrease of elastic modulus in Stiff-Deg mate-
rials (6 ±0.6 kPa) with respect to day 1. The Soft-NoDeg materials
showed a constant elastic modulus at day 14 (2 ±0.2 kPa).
The dynamic behavior of degradable materials is also evident in the
change of the mesh size (Fig. 1D). The mesh size increases signicantly
in degradable materials from 13.0 ±0.1 nm on day 1 to 34 ±3 nm on
day 14. In contrast, Soft-NoDeg materials maintain the mesh size over
14 days, as the values of day 1 (24 ±0.3 nm) and day 14 (26 ±2 nm) are
not signicantly different.
To characterize the anisotropic mechanical properties of patterned
hydrogels we used the method of microindentation. Patterned materials
show a clear difference in the elastic modulus between the 2 phases, on
day 1 (Fig. 2A) and day 14 (Fig. 2D). The corresponding single-phase
materials showed similar values of elastic modulus. The surface elastic
modulus of Soft-NoDeg materials was comparable between day 1
(Fig. 2B) and day 14 (Fig. 2E) and the elastic modulus of the Stiff-Deg
materials decreased visibly between day 1 (Fig. 2C) and day 14 (Fig. 2F).
3.2. Cell viability and proliferation in 3D single-phase and patterned
materials
Mouse embryonic broblasts were encapsulated in 3D single-phase
and patterned hydrogels. Cell viability was evaluated at day 1 and day
14 by staining live cells with calcein (green) and dead cells with
ethidium homodimer-1 (red).
Single-phase materials showed high viability (Fig. 3A), as the frac-
tion of viable cells remained above 90 % for all materials and time points
(Fig. 3B). The cell number corrected to the swelling factor (Fig. 3C)
shows that the cell proliferation was higher in Stiff-Deg materials
compared to Soft-NoDeg, with signicantly higher cell number at day 14
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Biomaterials Advances 151 (2023) 213423
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compared to day 1 and compared to the Soft-NoDeg counterpart at day
14. In contrast, no signicant differences over time were seen in the cell
number for Soft-NoDeg materials.
The macro function “cell number” allowed the quantication and
visualization of cell viability and proliferation in patterned materials.
Comparable to single-phase materials, patterned materials also showed
high viability in both phases and over time (Fig. 3D). No visible patterns
or changes were shown in viability, neither at day 1 (Fig. 3E) or day 14
(Fig. 3G).
Encapsulated cell number showed an initial homogeneous distribu-
tion of cells, as on day 1 there are no visible patterns (Fig. 3F). However,
patterns in cell proliferation are evident at day 14, which show higher
cell number in the Stiff-Deg areas compared to the Soft-NoDeg zones
(Fig. 3H).
3.3. Cell morphology in 3D single-phase materials
Staining of the nuclei (DAPI, cyan) and the actin cytoskeleton
(phalloidin, green) in single-phase materials was used to analyze the
effect of material properties on cell morphology (Fig. 4A).
On day 1, cells in Soft-NoDeg materials displayed signicantly
greater projected cell area compared to cells in Stiff-Deg materials
(Fig. 4B). 14 days after encapsulation, when the Stiff-Deg materials
degraded and consequently softened, the projected cell area increased
signicantly compared to the initial time point and also in comparison
with the Soft-NoDeg materials at day 14.
Differences in cell circularity at day 14 are signicant between the 2
materials (Fig. 4C). The cells in Stiff-Deg materials show signicantly
lower circularity compared to the initial time point and to cells in Soft-
NoDeg hydrogels at day 14.
In Fig. 4D, single cell images are shown, depicting detailed cell
morphology and lopodia. On day 1, early lopodia formation can be
seen in Stiff-Deg materials, whereas no lopodia were formed in Soft-
NoDeg hydrogels. After 14 days, the lopodia number and length
increased signicantly in Stiff-Deg compared to the initial time point
and to Soft-NoDeg at day 14 (Fig. 4E, F). In Soft-NoDeg materials, lo-
podia number and length increased after 14 days of encapsulation, yet
they remained lower compared to Stiff-Deg materials.
Fig. 1. Mechanical characterization of single-phase materials: Soft-NoDeg (black) and Stiff-Deg (red). (A) Day 1 and (B) day 14 of storage (G', ●) and loss (G",
○)
modulus in Pa obtained by rheology, n =6 gels. (C) Elastic modulus determined by unconned compression testing in kPa, n =6 gels. (D) Mesh size estimated from
the storage modulus in nm, n =6 gels. Statistical signicance with Student t-test for differences between groups is indicated with * and differences between time
points with # (*/# =p <0.05, **/## =p <0.01). (For interpretation of the references to colour in this gure legend, the reader is referred to the web version of
this article.)
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Biomaterials Advances 151 (2023) 213423
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3.4. Cell response in 3D patterned materials
The photopatterning of single-phase materials created anisotropic
hydrogels with spatially distinct degradation and stiffness characteris-
tics. Fig. 5 shows the effect of patterned materials on the morphology of
MEFs (Fig. 5A-F), the evaluation and heat map representation using the
novel image-based analysis tool (Fig. 5G-J) and the quantication of the
individual material phases (Fig. 5K-N). On day 1 (Fig. 5A, C, E), there are
patterns in projected cell area (Fig. 5G) as the Soft-NoDeg phase shows
cells with signicantly larger projected cell area compared to Stiff-Deg
(Fig. 5K). Initially, no signicant patterns in circularity are visible
(Fig. 5H, L) as most of the cells present a round morphology. At day 14
after encapsulation (Fig. 5B, D, F), there is a signicant increase of the
projected cell area in the Stiff-Deg (Fig. 5K) and even stronger signicant
decrease in cell circularity (Fig. 5L). This is visualized in the heat maps
with emerging spatial patterns in cell circularity at day 14 compared to
day 1 (Fig. 5J, H) and less visible, even reverted patterns in projected
cell area (Fig. 5I, G).
Regarding cell morphology, single cell images at day 1 (Fig. 5E)
showed that lopodia are mainly formed in the Stiff-Deg phase, with
signicantly greater number (Fig. 5M) and length (Fig. 5N) of the lo-
podia. This trend is amplied at day 14 (Fig. 5F), with signicantly
increased lopodia number and length compared to day 1 and compared
to cells in the Soft-NoDeg phase (Fig. 5M, N).
4. Discussion
The presented 3D hydrogels with stiffness-degradation spatial pat-
terns allow cell encapsulation with high cell viability and anisotropic
cell response. The hydrogel casting procedure offers the possibility of
photopatterning, combining the properties of two single-phase materials
in one single, multicomponent matrix, which allows emerging patterns
in cell behavior in 3D. Evaluation of cell behavior in multicomponent
materials is crucial in order to understand how these platforms guide cell
response. In our case, we choose patterns in stiffness-degradation and
evaluate anisotropic broblast cell morphology, as an example of the
application of an image-based quantication method.
All methods used for mechanical characterization led to consistent
and comparable results of mechanical properties and changes over time
caused by degradation. First, the methods show a decrease over time of
the elastic modulus of Stiff-Deg materials compared Stiff-NoDeg mate-
rials. Second, the bulk elastic modulus of the single-phase materials is
comparable to the surface elastic modulus of single-phase materials, and
importantly, also consistent with the mechanical properties of the
respective phases of patterned multicomponent materials.
The decrease in the elastic modulus of the degradable material can be
attributed to the degradation of the MMPsens peptide bonds due to the
action of the enzymes secreted by the cells. A consequence of this
degradation can be shown in the signicant increase of the mesh size
over time. There is no signicant change in the mesh size of Soft-NoDeg
materials, as the covalent bonds of these hydrogels are non-degradable.
Our results showed that the projected cell area of 3D encapsulated
cells is dependent on the matrix stiffness. At day 1, the signicantly
lower elastic modulus of Soft-NoDeg vs. Stiff-Deg results in signicantly
higher projected cell area in both single-phase and patterned materials.
However, at day 14, when the elastic modulus of Stiff-Deg signicantly
drops compared to day 1, the projected cell area signicantly increases
and cell circularity decreases as degradation promotes cell spreading.
Fig. 2. Microindentation of single-phase and patterned materials. (A, D) Patterned materials, (B, E) Soft-NoDeg single-phase materials and (C, F) Stiff-Deg single-
phase materials, on day 1 and day 14, respectively. Each matrix is the visual representation of the indentation elastic modulus (kPa) at the material surface. Single-
phase materials (6 ×6 matrix, indentation spacing of 300
μ
m), patterned materials (18 ×11 matrix, indentation spacing of 150
μ
m).
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Biomaterials Advances 151 (2023) 213423
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Fig. 3. Viability and proliferation of encapsulated cells in single-phase and patterned materials on day 1 and day 14. (A) Live/Dead staining of Soft-NoDeg and Stiff-
Deg single-phase materials at day 1 and day 14, 25×magnication, 250
μ
m z-stack, and corresponding (B) cell viability in % (viable cells/total cells) and (C) cell
number (cells per mL of hydrogel). (D) Live/Dead staining of patterned materials at day 1 and day 14, with 2 ×2 tile merging of 10×magnication, 250
μ
m z-stack.
The macro function “cell number” was used to quantify and plot the heat maps corresponding to cell viability in patterned materials at (E) day 1 and (G) day 14, as
well as total cell number at (F) day 1 and (H) day 14. The bars in B and C represent the mean and standard deviation of n =6 elds of view containing multiple single
cells (n >100). Statistical signicance with Student t-test for differences between groups is indicated with * and differences between time points with # (*/# =p <
0.05, **/## =p <0.01). Scale bar: 500
μ
m (A), 1 mm (D).
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Biomaterials Advances 151 (2023) 213423
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Fig. 4. Morphology of encapsulated cells in single-phase materials at day 1 and day 14. (A) Phalloidin (green)/ DAPI (cyan) staining of multiple cell images with 25×
magnication, 250
μ
m z-stack to determine (B) projected cell area in
μ
m
2
and (C) circularity (−). (D) Higher 40×magnication of single cell z-stack to determine (E)
lopodia number (−) and (F) lopodia length in
μ
m. Boxes represent the median and 1
st
and 3
rd
quartile of (B, C) multiple cells (>50 cells) in n =6 elds of view or
(E, F) n =10 cells. Statistical signicance with Wilcoxon Signed Rank test for differences between groups is indicated with * and differences between time points with
# (*/# =p <0.05, **/## =p <0.01). Scale bar: 200
μ
m (A), 25
μ
m (D). (For interpretation of the references to colour in this gure legend, the reader is referred to
the web version of this article.)
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Biomaterials Advances 151 (2023) 213423
9
Fig. 5. Morphology of encapsulated cells in patterned materials at day 1 and day 14. Phalloidin (green)/ DAPI (cyan) staining overview images at (A) day 1 and (B)
day 14, with indicated pattern areas, 2 ×2 tile image, 10×magnication, 250
μ
m z-stack. Zoom-in on the individual regions of the pattern at (C) day 1 and (D) day
14, 25×magnication, 250
μ
m z-stack. Single cell images z-stack at (E) day 1 and (F) day 14, 40×magnication. Heat map representation of (G, I) the mean
projected cell area in
μ
m
2
and (H, J) circularity (−) in the overview images, at day 1 (G, H) and day 14 (I, J). Box plots quantifying (K) projected cell area, (L)
circularity, (M) lopodia number (−) and (N) lopodia length in
μ
m, at day 1 and day 14, showing the median and 1
st
and 3
rd
quartile of n =6 elds of view
containing multiple single cells (n >50, for K and L) or n =10 cells (for M and N) in patterned materials. Statistical signicance with Wilcoxon Signed Rank test for
differences between groups is indicated with * and differences between time points with # (*/# =p <0.05, **/## =p <0.01). Scale bar: (A, B) 500
μ
m, (C, D) 200
μ
m, (E, F) 25
μ
m. (For interpretation of the references to colour in this gure legend, the reader is referred to the web version of this article.)
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Biomaterials Advances 151 (2023) 213423
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Cell area and circularity in 3D matrices is limited by the pore size offered
by the surroundings, which can vary in degradable materials [38]. These
results are supported by previous work related to 3D broblast encap-
sulation and in contrast to cell behavior on 2D surfaces with patterns in
stiffness [27], as expected. Fibroblasts on 2D stiffness patterned alginate
hydrogels exhibit an increased cell area and reduced circularity on stiff
regions compared to soft substrates [27].
Matrix remodeling and dynamic environments are crucial to stimu-
late cell response [39]. Degradation is essential for the formation of
protrusions and we observe that Stiff-Deg materials promote longer and
higher lopodia number compared to Soft-NoDeg materials. The higher
initial stiffness of the degradable material, might also lead to a quicker
degradation, as MMP production is increased in stiffer matrices [40].
The control hydrogels formed with a non-degradable version of the
peptide (MMP-scramble), showed that cells do not form lopodia in non-
degradable materials (Supplementary Fig. 7). These results are sup-
ported by previous ndings on the effect of matrix deformation energy
in the actin cytoskeleton of the cell, which has been proven to have a
greater effect compared to the intrinsic matrix stiffness [41]. Such
ndings highlight the importance of matrix degradability in enabling
cell protrusions to invade into the surrounding environment, as they
regulate more advanced cell processes like migration, motility,
communication and differentiation [42].
One important feature of this work is the combination of Stiff-Deg
and Soft-NoDeg phases in one single, multicomponent matrix. Differ-
ences in cell response observed in single-phase materials are recapitu-
lated in patterned stiffness-degradation materials and, importantly,
anisotropic cell behavior emerges with time as the Stiff-Deg component
degrades. This sets the basis for future work looking at sharper material
interfaces, or in contrast, gradients of stiffness-degradability by manip-
ulating the photomask. Such multicomponent materials open opportu-
nities to investigate anisotropic 3D cell migration, proliferation or
differentiation across a cell-relevant stiffness-degradability range.
To evaluate anisotropic 3D cell response in patterned materials, we
have developed a new image-based analysis tool and visual presentation
of spatial anisotropies of material and cellular characteristics using heat
maps. Various research groups have evaluated patterned materials as
independent phases, not as a single, multicomponent matrix. The
developed image-based method and the heat map representation of cell
number and morphology (projected cell area and circularity) showed to
be a valid tool to characterize and quantify anisotropic 3D cell behavior
in patterned materials, as it consistently represented the anisotropic cell
behavior in each phase compared to the corresponding single-phase
controls. This image-based analysis could be extended to other image-
based cellular read-outs.
Despite the great advantage of our novel image-based analysis tool,
there are some limitations. As input for this analysis tool, images
covering the entire gel or stitched multi-tiles images are required.
However, for certain features such as lopodia formation, high magni-
cation images are necessary. Multi-tiles high magnication imaging
covering the entire gel currently requires long acquisition times, which
would lead to dehydration of the hydrogel. Moreover, the evaluation of
the encapsulated cells in the hydrogel relies on the orthogonal projec-
tion of z-stack images, a method that can lead to cells in close proximity
or cell overlap. However, the projected cell area and circularity of single
cells was similar to the values obtained with the overview z-stack im-
ages. Therefore, we conclude that the image acquisition with z-stack was
optimal to capture a high number of cells avoiding problems due to cell
overlap.
The presented study investigates anisotropic 3D cell response in
stiffness-degradation patterned materials. The versatile material plat-
form can be tuned with anisotropic mechanical and degradation prop-
erties and thereby guide cell response within a single matrix. While this
work focused on broblast proliferation, cell shape, projected cell area
and lopodia formation, analogous analyses could be extended to other
cell types, cell-matrix interaction such as differentiation and
extracellular matrix deposition.
Our research demonstrates a relevant approach to investigate
emerging anisotropic 3D cell behavior in stiffness-degradation patterned
materials. The developed image-based analysis method provides the
basis for visualizing and quantifying 3D anisotropic cell behavior with
regard to cell number, projected cell area and circularity. This aniso-
tropic 3D cell response was conrmed with high resolution quantica-
tion of lopodia number and length. Such stiffness-degradation
patterned hydrogels allowing the emergence of 3D anisotropic cell
response, together with the image-based analysis method for visualiza-
tion and quantication of cellular read-outs, are valuable tools to un-
derstand cell-matrix interactions in multicomponent materials with
potential applications in regenerative medicine.
CRediT authorship contribution statement
A Cipitria conceived the idea. CA Garrido and DS Garske performed
the experiments. S Amini supported the microindentation experiments.
S Real developed the algorithm for analysis of the microindentation
data. CA Garrido quantied and analyzed the data. M Thiele developed
the image-based analysis macro. K Schmidt-Bleek and GN Duda evalu-
ated the methods and results. CA Garrido and A Cipitria drafted the
manuscript. All authors discussed the results and contributed to the nal
manuscript.
Funding
This work was funded by the Deutsche Forschungsgemeinschaft
(DFG) CRC 1444 grant. A Cipitria also thanks the funding from the DFG
Emmy Noether grant (CI 203/2-1), IKERBASQUE Basque Foundation for
Science and from the Spanish Ministry of Science and Innovation
(PID2021-123013OB-I00) (Ministerio de Ciencia e Innovaci´
on, la
Agencia y del Fondo Europeo de Desarrollo Regional, Proyecto PID2021-
123013OB-I00 nanciado por MCIN/AEI/10.13039/501100011033/
FEDER.UE).
Declaration of competing interest
The authors declare that the research was conducted in the absence
of any commercial or nancial relationships that could be considered as
a potential conict of interest.
Data availability
All raw and processed data, and the MATLAB and Python scripts are
available in a publicly accessible repository of the Max Planck Society
https://doi.org/10.17617/3.NEHZN1.
Acknowledgments
The authors acknowledge the support from all group members of
Cipitria, Schmidt-Bleek and Duda's laboratories.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.bioadv.2023.213423.
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