Kaizheng Liu1, Silvia M Mihaila2, Alan Rowan3, Egbert Oosterwijk2, Paul H J Kouwer1. 1. Radboud University , Institute for Molecules and Materials , Heyendaalseweg 135 , 6525 AJ Nijmegen , The Netherlands. 2. Radboud University Medical Centre and Radboudumc Amalia Childern's hospital , Radboud Institute for Molecular Life Sciences, Department of Urology , Geert Grooteplein 26-28 , PO Box 9101, 6500 HB Nijmegen , The Netherlands. 3. The University of Queensland, Australian Institute for Bioengineering and Nanotechnology , Brisbane , QLD 4072 , Australia.
Abstract
One of the promises of synthetic materials in cell culturing is that control over their molecular structures may ultimately be used to control their biological processes. Synthetic polymer hydrogels from polyisocyanides (PIC) are a new class of minimal synthetic biomaterials for three-dimensional cell culturing. The macromolecular lengths and densities of biofunctional groups that decorate the polymer can be readily manipulated while preserving the intrinsic nonlinear mechanics, a feature commonly displayed by fibrous biological networks. In this work, we propose the use of PIC gels as cell culture platforms with decoupled mechanical inputs and biological cues. For this purpose, different types of cells were encapsulated in PIC gels of tailored compositions that systematically vary in adhesive peptide (GRGDS) density, polymer length, and concentration; with the last two parameters controlling the gel mechanics. Both cancer and smooth muscle cells grew into multicellular spheroids with proliferation rates that depend on the adhesive GRGDS density, regardless of the polymer length, suggesting that for these cells, the biological input prevails over the mechanical cues. In contrast, human adipose-derived stem cells do not form spheroids but rather spread out. We find that the morphological changes strongly depend on the adhesive ligand density and the network mechanics; gels with the highest GRGDS densities and the strongest stiffening response to stress show the strongest spreading. Our results highlight the role of the nonlinear mechanics of the extracellular matrix and its synthetic mimics in the regulation of cell functions.
One of the promises of synthetic materials in cell culturing is that control over their molecular structures may ultimately be used to control their biological processes. Synthetic polymer hydrogels from polyisocyanides (PIC) are a new class of minimal synthetic biomaterials for three-dimensional cell culturing. The macromolecular lengths and densities of biofunctional groups that decorate the polymer can be readily manipulated while preserving the intrinsic nonlinear mechanics, a feature commonly displayed by fibrous biological networks. In this work, we propose the use of PIC gels as cell culture platforms with decoupled mechanical inputs and biological cues. For this purpose, different types of cells were encapsulated in PIC gels of tailored compositions that systematically vary in adhesive peptide (GRGDS) density, polymer length, and concentration; with the last two parameters controlling the gel mechanics. Both cancer and smooth muscle cells grew into multicellular spheroids with proliferation rates that depend on the adhesive GRGDS density, regardless of the polymer length, suggesting that for these cells, the biological input prevails over the mechanical cues. In contrast, human adipose-derived stem cells do not form spheroids but rather spread out. We find that the morphological changes strongly depend on the adhesive ligand density and the network mechanics; gels with the highest GRGDS densities and the strongest stiffening response to stress show the strongest spreading. Our results highlight the role of the nonlinear mechanics of the extracellular matrix and its synthetic mimics in the regulation of cell functions.
An increasing number
of reports reveal that the mechanical properties
of the extracellular matrix (ECM) play a crucial role in the regulation
of cell function.[1,2] Adherent cells attach to the matrix
via integrin–matrix protein binding and sense ECM mechanics
with the aid of a large number of adhesion-associated proteins and
mechanotransduction pathways.[1] These physical
signals synergize with the chemical signals and simultaneously and
coherently orchestrate cell fate, including cellular organization,
proliferation, migration, (stem cell) differentiation, and self-renewal.[2,3] It should be noted that in vivo, cells reside in a soft three-dimensional
(3D) microenvironment and it has become increasingly clear that (stiffer)
2D substrates are insufficiently capable to simulate the complex processes
that occur in 3D and thus are not representative of a realistic situation.
When 3D cell–matrix adhesion interactions are taken as an example,
they differ from their 2D counterpart in the content of α5β1 and αvβ3 integrins, paxillin, tyrosine phosphorylation of focal adhesion
kinase (FAK), and other cytoskeleton proteins.[4] Hence, to replicate the in vivo-like settings, the establishment
of accurate 3D culture models has become crucial.[4,5]The natural ECM is a sophisticated system that is composed of numerous
elements that together provide the right chemical, biological, and
mechanical environment for cells. From an architectural point of view,
the fibrous components of the ECM play a main role in maintaining
the structural integrity of the system and, as such, contribute to
the bulk mechanical properties.[6] As a result
of their fibrous nature and high persistence lengths, these biopolymers
are able to form stiff networks at very low concentrations, with large
pores that allow for diffusion of large molecules as well as cell
migration. In addition, these biopolymer networks typically possess
intriguing mechanical properties: they become many times stiffer when
a small strain is applied. This effect, which is known as stress-stiffening
or strain-stiffening,[7] enables natural
tissues to dynamically adjust the local mechanics in response to small
cellular forces, generated when cells anchor to the network and physically
pull it. Stress-stiffening is believed to play a role in the prevention
of tissue rupture, transduction of cellular forces,[8] enabling of contractile cells to communicate their local
position,[9] and in guiding stem cell differentiation.[10] Note that this effect is not to be confused
with stiffening through the irreversible (strain-induced) formation
of additional cross-links in the gel.[11,12] Recently,
there have been an increasing number of reports identifying the possible
roles of a dynamic microenvironment as well as the reproduction of
the dynamics of natural tissues.[13] In fact,
many reconstituted gels of ECM proteins (collagen, fibrin, etc.) exhibit
some degree of stress relaxation,[14] which
reduces the stiffness of the matrix in time when the material is strained.
Through this mechanism, cellular traction forces relax, which allows
for matrix remodeling. Although different groups are studying these
phenomena separately in the field of biomechanics, it is important
to underline that nonlinear mechanics and viscoelasticity exist and
function simultaneously in the dynamic remodeling of the matrix,[15] albeit at different time scales.Current
3D cell culture studies employ a large number of natural
and semisynthetic polymer hydrogels based on, for instance, collagen,
fibrin, hyaluronic acid, elastin, alginate, chitosan, etc.[16−18] Some of these materials possess nonlinear mechanical properties;
however, it is extremely difficult to control their properties precisely.
For most of these materials, the characteristic approach for the manipulation
of the (non)linear mechanics is to change the concentration of the
polymers, which simultaneously impacts other features of the microenvironment
such as the density of biological ligands, pore size, and porosity
to name a few.[18] Although many synthetic
polymer hydrogels have been developed and utilized intensively for
biomechanics studies,[19,20] their architecture and linear
mechanical properties make them often inadequate mimics to understand
in vivo cell–matrix interactions. Despite the tremendous advances
in the design of synthetic matrices, there is still an urgent need
for synthetic polymer hydrogels that permit the independent decoupling
of biochemical properties from the biomimetic mechanical properties.
Such systems would enable the development of in vitro microenvironments
that can be truly tailored to any biomedical application.Recently,
we introduced polyiscocyanide (PIC)-based hydrogels that
are fully synthetic but strongly biomimetic in architecture and mechanics.[21] On deformation beyond a critical stress, σc, PIC gels can stiffen up a factor of 100, analogous to fibrin
and collagen. The key mechanical parameters in PIC gels, i.e., σc and the stiffening index m, metrics for
the sensitivity and the responsiveness toward stress, respectively,
indeed are similar to those found in these nature-derived gels. More
importantly, in PIC gels, these parameters are readily controlled
by the molecular structure, the concentration and external conditions,
such as temperature and salt concentrations.[22−26] Moreover, as a thermoresponsive polymer, PIC chains
bundle up and form interconnected fibers above the gelation temperature
(typically Tgel ∼ 20 °C) and
the gels disassemble back to polymer solutions below Tgel, which enables researchers to easily encapsulate and
harvest their cells. Earlier work has explored the use of PIC hydrogels
as a guide for stem cell differentiation in 2D[27] and 3D[10] cultures, to support
prevascularization, and as organotypic culturing support.[28]In this manuscript, we study how changes
in the structure of the
PICpolymer, i.e., the contour length LC and the adhesive peptide density D on the polymer
chain impact cellular behavior. For this study, we prepared a series
of PIC polymers of different molecular weights and equipped them with
adhesive peptides based on GRGDS (Figure a,b). We hypothesize that upon integrin-mediated
binding of cells to the adhesive peptides on the polymer, the cells
are able to generate internal stresses within the network and, as
a result of the stress-sensitivity of PIC hydrogels, they are able
to change the local mechanical microenvironment. By increasing/decreasing LC, we change the gel stiffness, but more importantly,
the sensitivity to stress without changing its concentration.[22] Through the peptide density, we tune the number
of cell-polymer contacts and with that, the efficiency of stress transfer
from the cell to its microenvironment. In our study, we first probed
different cell lines. As the most stringent effects were noticed with
adipose-derived stem cells, we subsequently studied those more in-depth.
Figure 1
Structure
and hierarchical assembly of the polyisocyanide (PIC)-based
gels as a reductionist model for the ECM. (a) The semiflexible network
is composed of bundles of polymer chains with a broad pore size distribution
ranging from nanometers to microns. The polymer contour length, LC, and the density of peptide adhesion sites,
given by the average distance d between two adjacent
groups, was varied in this work. (b) The molecular structure of the
polymer is shown in red, the GRGDS peptide is shown in blue, and the
linking group is shown in pink, matching with the colors in panel
a. (c) The PIC polymers reversibly gel above the gelation temperature Tgel ∼ 20 °C.
Structure
and hierarchical assembly of the polyisocyanide (PIC)-based
gels as a reductionist model for the ECM. (a) The semiflexible network
is composed of bundles of polymer chains with a broad pore size distribution
ranging from nanometers to microns. The polymer contour length, LC, and the density of peptide adhesion sites,
given by the average distance d between two adjacent
groups, was varied in this work. (b) The molecular structure of the
polymer is shown in red, the GRGDS peptide is shown in blue, and the
linking group is shown in pink, matching with the colors in panel
a. (c) The PIC polymers reversibly gel above the gelation temperature Tgel ∼ 20 °C.
Experimental Section
Synthesis of Polyisocyanides
Polyisocyanides were synthesized
as previously reported.[29] In short, the
isocyanide monomer was dissolved in freshly distilled toluene and
stirred. Two parameters were adjusted: (i) the ratio of azide-functionalized
and total monomer and (ii) the ratio Ni2+ to total monomer.
All ratios are given in Table . The appropriate amounts of monomers and catalyst solution
Ni(ClO4)2·6H2O (0.1 mg ml–1 in freshly distilled toluene/absolute ethanol 9:1)
were dissolved in toluene, and the final isocyanide concentration
was adjusted to 50 mg mL–1. The mixture
was stirred at room temperature, and the progress of the reaction
was followed by IR-ATR (disappearance of the characteristic isocyanide
absorption at 2140 cm–1). Once the polymerization
was complete, the polymer was precipitated in diisopropyl ether under
vigorous stirring and collected by centrifugation. The polymer was
dissolved in dichloromethane, precipitated for another two rounds,
and air-dried to yield the polymers as off-white solids. The molecular
weight of the polymer was determined by viscometry (dilute solutions
in acetonitrile) using the empirical Mark–Houwink equation
[η] = KMv, where [η] is the
experimentally determined intrinsic viscosity, Mv
is the viscosity-determined molecular weight, and the Mark–Houwink
constants K and a depend on polymer
characteristics and solvent, temperature, etc. We use parameters previously
determined[30] for other polyisocyanides: K = 1.4 × 10–9 and a = 1.75. The results are given in Table .
Table 1
Polymers and Characterization
polymer
[Ni2+]:[M] ratioa
Mvb (kg mol–1)
LCc (nm)
<d>d (nm)
PIC1
1:5000
562
223
3
PIC2
1:5000
575
228
10
PIC3
1:5000
558
221
25
PIC4
1:5000
539
214
50
PIC5
1:5000
568
225
100
PIC6
1:5000
568
225
e
PIC7
1:1000
263
106
10
PIC2
1:5000
575
228
10
PIC8
1:7000
589
236
10
Catalyst:monomer ratio for the polymerization
reaction.
Mv =
Viscosity-based molecular weight of azide-appended polymers.
Average contour length based on Mv.
Average distance between peptides
based on feed ratio in the polymerization.
No GRGDS present in PIC6.
Catalyst:monomer ratio for the polymerization
reaction.Mv =
Viscosity-based molecular weight of azide-appended polymers.Average contour length based on Mv.Average distance between peptides
based on feed ratio in the polymerization.No GRGDS present in PIC6.
Conjugation of Adhesive Peptides
The peptide GRGDS
was first conjugated to the BCN-containing spacer following earlier
described protocols.[10] The peptide (H-Gly-Arg-Gly-Asp-Ser-OH,
Bachem, Germany) was dissolved in borate buffer (pH = 8.4) at 6 mg mL–1. The dissolved BCN-NHS linker (Synaffix, The Netherlands)
in DMSO (6 mg mL–1) was added to the
peptide solution in borate buffer in a 1.1:1 molar ratio and
stirred on the stirring plate for 24 h at room temperature. The formation
of the BCN–GRGDS conjugate was confirmed by mass spectrometry
(M = 911.4 g mol–1). The azide-appended
polymer (PIC1–PIC5, PIC7, PIC8) was dissolved in acetonitrile (2.5 mg mL–1), and the appropriate volume of the BCN–GRGDS
solution in borate buffer (95% molar equivalent of the corresponding
azide amount on the polymer) was added. The solution was stirred for
24 h at room temperature. The polymer–peptide conjugates were
precipitated in diisopropyl ether, collected by centrifugation, and
air-dried for 24 h.
Rheological Analysis of Polymer Hydrogels
For the mechanical
analysis of the gels, a stress-controlled rheometer (Discovery HR-1
or HR-2, TA Instruments) with an aluminum or steel parallel plate
geometry was used (diameter = 40 mm, gap = 500 μm).
All samples were loaded onto the rheometer plate in the liquid state
at T = 5 °C followed by a temperature
ramp to T = 37 °C at a rate of 1.0 °C min–1. The moduli were measured in the linear viscoelastic
regime at amplitude of γ = 0.02 or 0.04 and a frequency
of ω = 1.0 Hz. The sample was allowed to equilibrate
at 37 °C prior to the nonlinear measurements. Here, the gel was
subjected to a constant prestress of σ0 = 0.5 to
200 Pa, and the differential modulus K′
was probed with a small superposed oscillatory stress at frequencies
of ω = 10 to 0.1 Hz (reported data at ω = 1 Hz).
The oscillatory stress was at least 10 times smaller than the applied
prestress.
Cell Culture and Encapsulation
Human
bladder smooth
muscle cells were purchased from ScienCell and cultured in smooth
muscle cell medium with growth supplement (ScienCell, USA). T24 and
Hela cells were purchased from ATCC; SKRC52 cells were obtained from
a mediastinal metastasis of a primary RCC2. All cancer cells were
cultured in RPMI 1640 with GlutaMax (Gibco, Thermo Fisher, USA). Human
adipose-derived stem cells were obtained from the Radboud Biobank
and cultured in minimum essential medium eagle (α-MEM) (Invitrogen,
Thermo Fisher, USA). All media were supplemented with 10% fetal bovine
serum (Sigma-Aldrich, USA) and 1% penicillin/streptomycin (final concentration
of 100 IU/mL penicillin and 100 μg/mL streptomycin, Gibco, Thermo
Fisher, USA).Dry PIC polymers were sterilized by UV for 20
min and then dissolved in medium for 24 h at 4 °C. Cells were
harvested by trypsin treatment once they reached 100% confluence and
were resuspended in fresh medium. Cell densities were determined by
a LUNA-FL dual fluorescence cell counter. Cells were mixed with the
polymer solution on ice with a predetermined ratio to achieve the
required cell density and polymer concentration. After mixing, the
solutions were transferred to 48-well plates (Corning, USA) or 8-well
chambered cover slides (Sigma-Aldrich, USA) and heated to 37 °C
where gelation occurred. After gel formation, culture medium (at 37
°C) was added onto the samples. Then all samples were subject
to standard cell culture conditions (37 °C, 5% CO2). Note that no stem cell differentiation kit was added into the
culture medium of the hACSs, and the cells are expected to maintain
the stemness.[10]
Bright Field Imaging and
Cell Morphology Analysis
Bright
field images of cells encapsulated in hydrogels were acquired on a
Leica DC200 microscope. Outlines of representative hASCs were plotted
manually, and the quantitative analysis of circularity was performed
by Fiji. A paired sample t test was used to determine
the statistical significance.
Cytoskeleton Staining and
Confocal Microscope Imaging
Gels with encapsulated cells
were washed with 0.9% NaCl and then
fixed with 3% paraformaldehyde in 0.9% NaCl for 40 min. After fixation,
the samples were permeabilized with 0.1% Triton X-100 in 0.9% NaCl
for 10 min and blocked with 1% BSA in 0.9% NaCl for 30 min. They were
then incubated with Texas Red-X Phalloidin (50 IU/mL in 1% BSA/0.9%
NaCl, Sigma-Aldrich, USA) for 1 h and DAPI (5 mg mL–1 in 0.9% NaCl, Thermo Fisher, USA) for 10 min. All procedures above
were performed at 37 °C. An Olympus FluoView 1000 confocal laser
scanning microscope was used for fluorescence imaging. The temperature
of the sample was kept at 37 °C by the heating element of the
microscope.
Cell Proliferation Assay
(a) WST-1:
Culture medium
was gently removed, the new medium supplemented with the cell proliferation
reagent WST-1 (Roche, Switzerland) at a final concentration of 1:10
(WST-1 stock solution/total working solution) was added, and the culture
plates were incubated at 37 °C, 5% CO2 for 2 h. The
absorbance was measured at λ = 450 nm with a plate reader (PerkinElmer
1420 Multilabel Counter). All samples were measured in triplicates.
(b) Quant-iT PicoGreen dsDNA Assay Kit: The amount of dsDNA in each
sample was quantified according to the kit manual (Invitrogen, Thermo
Fisher, USA). In brief, 28.7 μL of sample, 71.3 μL of
1X PicoGreen solution, and 100 μL 1× TE were mixed and
incubated in a 96-well plate in the dark for 10 min and the fluorescence
was read with a plate reader (λexcitation = 485 nm,
λemission = 528 nm). All samples were measured in
triplicates.
Results and Discussion
Synthesis of the PIC-GRGDS
Polymers and Gel Preparation
The generic polymer structure
of the materials used in this work
is shown in Figure b. For precursors, we prepared azide-appended PIC polymersPIC1–PIC8 by copolymerization of the N3-functionalized monomer with the nonfunctional monomer, following
earlier reported procedures.[10] The polymer
contour length, LC, was tuned by changing
the total monomer to initiator ratio and calculated from the viscosity
averaged molecular weight.[22] Although at
gel formation, the polymers bundle and form infinitely long networks,
the length of the individual polymer chains is an important parameter
in the linear and nonlinear mechanical properties of the gels.[22] After purification of the polymers, the appropriate
amounts of the GRGDS peptide, previously equipped with a BCN group,[10] were added to the polymers, and the GRGDS-decorated
polymers were collected after precipitation. As their concentration
is very low, a quantitative characterization of the degree of peptide
conjugation is challenging. On the basis of the high reaction rate
of this conjugation chemistry[31] and the
results of earlier reports,[29] we assume
complete conversion and we present GRGDS spacings, d, based on the azide monomer fractions (Table , series polymerPIC1–PIC6). To vary LC, we prepared
a series of three polymers with the same spacing (d = 10 nm) and different catalyst/monomer ratios (PIC7–PIC2–PIC8). Although the
experimental values of the viscosity-averaged molecular weights, Mv, of PIC2 and PIC8 are very similar, we do find the expected differences in the mechanical
properties of the corresponding gels.For analysis and cell
culture studies, the appropriate amount of the azide or GRGDS-functionalized
polymers were dissolved in α-MEM medium at 4 °C for 24
h. Instantaneous and reversible gelation takes place upon heating
above Tgel (Figure c).
Mechanical Characterization
The
PIC hydrogels were
subjected to rheological analysis (Table ). At low strain, we measure the storage
modulus G′ in the linear viscoelastic regime
as a function of temperature (Figure S1). At high stresses, the gels reversibly stiffen and we describe
the mechanical properties by the more relevant differential modulus K′ = ∂σ/∂γ, where σ
and γ are the stress and strain, respectively. Note that below
a critical stress σc, i.e., at σ < σc, K′ = G′,
and at σ > σc, K′
depends
on the applied stress G′; G′ ∼ σ, where m is the stiffening index. The parameters σc and m represent the sensitivity and responsiveness
to macroscopic deformation.
Table 2
Hydrogel Samples
for Cell Culture
Experiments
hydrogel
polymer
ca (g L –1)
Db (μM)
G′c (Pa)
σcc (Pa)
P1
PIC1
2.0
181
228
19.1
P2
PIC2
2.0
55
347
26.6
P3
PIC3
2.0
22
442
33.3
P4
PIC4
2.0
11
586
35.3
P5
PIC5
2.0
5
388
29.9
P6
PIC6
2.0
d
382
23.5
S1
PIC7
1.5
41
128
14.6
S2
PIC2
1.5
41
177
19.1
S3
PIC8
1.5
41
247
21.4
S4
PIC7
3.0
83
463
29.5
S5
PIC2
3.0
83
647
39.7
S6
PIC8
3.0
83
831
47.4
S7e
PIC7
2.0
55
287
22.4
S8e
PIC8
2.0
55
489
35.7
c = polymer concentration.
D = density of
conjugated GRGDS peptide.
Shear modulus (G′) and critical stress (σc) measured at T = 37 °C in α-MEM
medium.
No GRGDS conjugated
to PIC6.
S7 and S8 were not used for cell experiments
but were included for a comprehensive
view of the mechanical properties of the PIC gels.
c = polymer concentration.D = density of
conjugated GRGDS peptide.Shear modulus (G′) and critical stress (σc) measured at T = 37 °C in α-MEM
medium.No GRGDS conjugated
to PIC6.S7 and S8 were not used for cell experiments
but were included for a comprehensive
view of the mechanical properties of the PIC gels.PolymersPIC1–PIC6 have the same
contour length LC but different GRGDS
loading (d), and all form soft hydrogels with G′ = 230 to 590 Pa at polymer concentration c = 2 mg mL–1 in medium at a physiological
temperature of T = 37 °C (Figure a). Beyond the linear viscoelastic regime,
the gels stiffen. Again at 2 mg mL–1, we find for P1–P6, a critical stress σc = 19 to 35 Pa and a stiffening index m ≈
1. As expected, for polymers with the same molecular weight,[22] the curves collapse to a single master curve
when the data is scaled to the storage modulus in the linear viscoelastic
regime G′ and σc (Figure S1). We do not find a clear correlation
between the mechanical properties of the gel and the peptide loading
(Table ). Low peptide
densities stiffen the gel slightly, but at the highest GRGDS densities,
the gel softens. This nonlinear behavior results from a balance in
effects introduced with the peptide. On one hand, the peptide makes
the polymer slightly more hydrophilic, which increases Tgel and thus decreases at T = 37 °C. On the other hand, the peptides
add physical interactions between polymer chains, which will increase . Overall, however, all gels are
relatively soft, i.e., much softer than many other (synthetic) gels
used for cell culture experiments, and display stress sensitivities
that are biologically accessible.[32] Gels S1–S6 of polymers with the same peptide
density D but of different lengths show an increase
in both G′ and σc with increasing LC (Figure b). We used the gels at two different concentrations: c = 1.5 and 3 mg mL–1, which gives gels
with G′ = 100 to 1000 Pa, σc = 14 to 41 Pa, and D = 41 or 83 μM. The adhesive
peptide concentrations in our gels are typically about an order of
magnitude lower than in other commonly used synthetic gels.[14,33−35]
Figure 2
Mechanical properties of PIC gels used in this work. (a)
Differential
modulus K′ as a function of applied stress
(c = 2 mg mL–1 in medium, T = 37 °C) for gels P1–P6. The plateau values at σ < 10 Pa correspond to the modulus
in the linear viscoelastic regime. (b) K′ of
gels S1–S6 (from PIC7, PIC2, and PIC8) with different length LC but a fixed ligand density, at polymer concentrations c = 1.5 mg mL–1 (solid symbols) and 3.0
mg mL–1 (open symbols) in medium. (c,d) Linear correlations
between the critical stress σc and the storage modulus G′ and between the stiffening index m and σc for S1–S6; 1.5 mg mL–1 (solid symbols) and 3.0 mg mL–1 (open symbols). The dashed line is a guide to the
eye. The last two diagrams clearly show that the more stress-sensitive
gels are both softer and more responsive toward applied stress. All
measurements were done in α-MEM medium at 37 °C.
Mechanical properties of PIC gels used in this work. (a)
Differential
modulus K′ as a function of applied stress
(c = 2 mg mL–1 in medium, T = 37 °C) for gels P1–P6. The plateau values at σ < 10 Pa correspond to the modulus
in the linear viscoelastic regime. (b) K′ of
gels S1–S6 (from PIC7, PIC2, and PIC8) with different length LC but a fixed ligand density, at polymer concentrations c = 1.5 mg mL–1 (solid symbols) and 3.0
mg mL–1 (open symbols) in medium. (c,d) Linear correlations
between the critical stress σc and the storage modulus G′ and between the stiffening index m and σc for S1–S6; 1.5 mg mL–1 (solid symbols) and 3.0 mg mL–1 (open symbols). The dashed line is a guide to the
eye. The last two diagrams clearly show that the more stress-sensitive
gels are both softer and more responsive toward applied stress. All
measurements were done in α-MEM medium at 37 °C.We find that softer gels are more
stress-responsive (Figure c), that is, they stiffen at
lower stresses (low σc). Interestingly, the stiffening
index of gel series S1–S6 negatively
correlates to the critical stress (Figure d), which underlines that softer PIC hydrogels
with a higher stress-sensitivity also possess a higher responsiveness
(high m). The fibrous architecture of the gels does
not change significantly with the polymer chain length (in this studied
regime)[24,36] which means that only a change in the architecture
of the network is expected from the change in concentration, which
for a concentration doubling gives a minor reduction of the mesh size
ξ as follows: ξ ∼ c–0.5.
Adhesive Peptide Density: Cell Proliferation vs Spreading
For cell culture studies, the cells were suspended in a cold (0–5
°C) polymer solution in medium and immediately warmed to 37 °C
to form 3D cell–gel constructs. Then the samples were cultured
at standard conditions for 7 days. Bright field images show that the
cell morphologies depend on the cell type and GRGDS concentration
but much less on the gel properties (Figure a,b). Human bladder smooth muscle cells (hbSMCs),
HeLa, SKRC52, and T24 cells tend to proliferate and organize into
multicellular spheroids with diameters of tens of microns in all polymers
(see Figure a and Figures S2–S5 for a full overview). The
spatial distribution of cell nuclei and the arrangement of F-actin,
however, differs for each cell type (Figure c). The proliferation rates of these cell
types are positively correlated to the density of adhesive ligands
(Figure d–g):
gels with the highest GRGDS loading show highest proliferation rates.
The relatively small difference in the mechanical properties in P1–P6 has a minor effect on cell behavior.
Human adipose-derived stem cells (hASCs) do not organize into large
multicellular spheroids but rather show distinct morphological changes
with peptide density. Cell protrusion and elongation are seen earlier
(day one, see Figure S6) in gels with higher
GRGDS densities (P1 and P2), compared to
the other gels. After 7 days, the stem cells adopted a flattened morphology
in P1 and P2, while only small protrusions
developed in P3–P5, and no protrusions
were observed in P6 (Figure b).
Figure 3
Cell behavior in PIC gels with different GRGDS
densities based
on P1–P6. (a) SKRC52s, T24s, HeLas,
and SMCs in P1 and P6 after 7 days of culturing.
Irrespective of the peptide density, cell spheroids are formed for
all cell types. (b) hACSs show strongly different morphologies in P1–P6 after 7 days of culturing: elongated
morphologies at the highest GRGDS densities and spherical morphologies
at low densities. (c) Fluorescence staining with Phalloidin (red,
F-actin) and DAPI (blue, cell nuclei) of different cell types after
7 days of culturing in P2 show that the multicellular
aggregate differs in nuclear and cytoskeletal arrangement. Contrarily,
hACSs show single elongated morphologies. (d–h) Proliferation,
normalized to absorbance of P1 at day 3, for different
cell types after 3 and 7 days of culturing in P1–P6. SKRC52s, T24s, HeLas, and SMCs show increased proliferation
with higher peptide densities. For hASCs, proliferation in all gels
is low. Note that the colors in d–h match those in Figure a. For all samples,
the PIC concentration c = 2 mg mL–1 and cell density is 20000 cells mL–1. The scale
bar for all figures is 70 μm. The error bars in d–h represent
standard deviations of three experiments.
Cell behavior in PIC gels with different GRGDS
densities based
on P1–P6. (a) SKRC52s, T24s, HeLas,
and SMCs in P1 and P6 after 7 days of culturing.
Irrespective of the peptide density, cell spheroids are formed for
all cell types. (b) hACSs show strongly different morphologies in P1–P6 after 7 days of culturing: elongated
morphologies at the highest GRGDS densities and spherical morphologies
at low densities. (c) Fluorescence staining with Phalloidin (red,
F-actin) and DAPI (blue, cell nuclei) of different cell types after
7 days of culturing in P2 show that the multicellular
aggregate differs in nuclear and cytoskeletal arrangement. Contrarily,
hACSs show single elongated morphologies. (d–h) Proliferation,
normalized to absorbance of P1 at day 3, for different
cell types after 3 and 7 days of culturing in P1–P6. SKRC52s, T24s, HeLas, and SMCs show increased proliferation
with higher peptide densities. For hASCs, proliferation in all gels
is low. Note that the colors in d–h match those in Figure a. For all samples,
the PIC concentration c = 2 mg mL–1 and cell density is 20000 cells mL–1. The scale
bar for all figures is 70 μm. The error bars in d–h represent
standard deviations of three experiments.We observe that the number of stem cells decreases slightly
in
samples with low peptide densities, which we attribute to an insufficient
adhesive ligand density. For the other four cell types, this was not
the case; after 7 days, their cell number increased despite the lack
of adhesive sites. We attribute this relatively efficient proliferation
to the cell–cell interactions in the multicellular spheroids.
In addition, the formation of multicellular structures is a very complex
mechanism with rich biological content, where besides cell–matrix
interactions, cell–cell contacts play a major role.[37] In this work, however, we will not discuss this
in further detail but restrict ourselves to the stem cells that seem
most sensitive to the RGD concentrations of the synthetic biomimetic
hydrogels.We studied cell spreading as an indicator for a plethora
of cell
functions.[38] Although commonly used in
2D cell studies, spreading studies seem less popular in 3D culture
studies. Earlier work that actually focused on cell spreading on planar
surfaces proved the existence of a critical adhesive ligand density
(e.g., 70 nm for mesenchymal stem cells on nanopatterned PEG matrix)
for efficient cell spreading and focal adhesion formation.[39] 3D cell–matrix adhesions, however, are
distinct from focal adhesions that are found on two-dimensional planar
surfaces.[4] In this work, we focus on cell
spreading in a 3D fibrous network with a controlled ligand density.When polymer length and polymer concentration are fixed, our results
reveal that microenvironments rich in adhesion sites promote stem
cell spreading and the formation of cellular networks by providing
more molecular anchoring points for integrins on the cell membrane.
In other words, it is easier for cells to anchor to the artificial
ECM and initiate actin polymerization, myosin contraction, and adhesion
protein recruitment.[40] In our case, the
minimum required adhesive peptide density for hASCs to spread is ∼55
μM (Figure b).
This density corresponds to a ∼10 nm distance between adjacent
peptides on a polymer chain, a distance that is of the same order
of magnitude as the length of the α5β1 integrin head[41] (that is overexpressed
in human mesenchymal stem cells). When two adjacent peptides are too
far apart, hASCs seem unable to generate enough traction to modulate
their morphology. Once more, we iterate that the RGD density used
in our study is low compared to the RGD content inside other synthetic
cell-laden hydrogels.[14,33−35] We propose
that the bundling of PIC polymers results in the clustering of RGD
peptides, which results in more effective cell spreading.[42] Notably, we also encapsulated hASCs in P1–P6 with a higher cell density (200000
cells mL–1) and found a similar trend in morphology
and proliferation (Figures S8 and S9).
Nonlinear Mechanics of the ECM Regulates the Organization of
hASCs
Nonlinear mechanics is frequently observed in gels
of natural polymers, but to this date, many biological effects of
stress-stiffening and their mechanisms still remain to be unravelled.[1,10] We prepared six gels S1–S6 with
different critical stresses and thus different responses to stress
that is applied externally (rheometer) or internally (cells) to screen
the influence of ECM stress-stiffening on cell spreading of 3D hASC
cultures. The PIC polymers were conjugated with a fixed density of
adhesive peptides with = 10 nm to provide
the essential amount of attachment sites. After culturing for 3 days,
the cells encapsulated in S1–S6 were
analyzed (Figure )
using bright field microscopy (Figure a) and after staining the nuclei and F-actin, the cells
were analyzed using confocal microscopy (Figure b). The extent of spreading of the cells
was quantified by plotting and measuring the circularity of ten representative
cells (Figure c,d).
At low gel concentrations (c = 1.5 mg mL–1), the stem cells show significantly better spreading (smaller circularity)
in samples with a smaller critical stress (series S1–S3). At 3 mg mL–1 (S4–S6), a plateau is reached (Figure e). We did not detect any significant proliferation
until day 3, which is in line with the results from P1–P6 (Figure f).
Figure 4
Influence of nonlinear mechanics of the PIC matrix on
the spreading
of hASCs. (a) Representative bright field images of hASCs. (b) Representative
fluorescence images of hASCs; nuclei are stained with DAPI (in blue),
and F-actin is stained using Texas Red Phalloidin (in red). (c) Cell
outlines of ten representative cells. All images were taken 3 days
after cell encapsulation; cell density = 200000 cells mL–1, scale bars = 70 μm. (d) Quantified circularity of the cells
in panel c for gel S1–S6. (e) Averaged
circularity as a function of the corresponding critical stress σc of the gels. (f) Quantified cell proliferation using a PicoGreen
assay, normalized by day 0. Note that the colors in d–f match
those in Figure b–d.
For each sample, 10 cells were analyzed. Statistics: n.s. = not significant
(p > 0.05), ** p < 0.01, *** p < 0.001.
Influence of nonlinear mechanics of the PIC matrix on
the spreading
of hASCs. (a) Representative bright field images of hASCs. (b) Representative
fluorescence images of hASCs; nuclei are stained with DAPI (in blue),
and F-actin is stained using Texas Red Phalloidin (in red). (c) Cell
outlines of ten representative cells. All images were taken 3 days
after cell encapsulation; cell density = 200000 cells mL–1, scale bars = 70 μm. (d) Quantified circularity of the cells
in panel c for gel S1–S6. (e) Averaged
circularity as a function of the corresponding critical stress σc of the gels. (f) Quantified cell proliferation using a PicoGreen
assay, normalized by day 0. Note that the colors in d–f match
those in Figure b–d.
For each sample, 10 cells were analyzed. Statistics: n.s. = not significant
(p > 0.05), ** p < 0.01, *** p < 0.001.A wide variety of cellular processes, including sensing of
ECM
mechanics, cell–cell communication, on/off switching of functional
binding sites, and alteration of enzymatic ECM degradation,[43] involve cell anchoring to the ECM fibers and
the straining of the fibers that induces a stiffening response in
the matrix. The storage modulus (i.e., the stiffness in the linear
viscoelastic regime) of the PIC gels falls into the category of soft
biomaterials,[18] which means that primarily the difference in critical stress governs the real mechanical
properties of the microenvironment of the encapsulated cells. A lower
critical stress implies that the material is more sensitive to cell-induced
matrix stiffening. For gels that display large stiffening indices,
i.e., gels that are more responsive toward contractile stresses applied
by the cell, this effect is further enhanced. In these fibrous gels,
cells are able to adhere and pull the PIC fibers, stiffen them, and
accumulate enough traction force for the observed morphological changes.
The culturing in gels that have a higher σc and a
lower m leads to the opposite effect. These materials
remain relatively static; i.e., the cells are able to anchor due to
the sufficient amount of adhesive peptides present but are unable
to generate sufficient traction force to spread. Therefore, cells
tend to maintain the rounded morphology and do not spread out. Despite
the difference in initial low-stress plateau moduli, the role of nonlinear
mechanics at higher stress is more dominant as these soft gels can
stiffen up to kilopascals with external stress (Figure b).In addition to the effects originating
from changes in the macroscopic
(nonlinear) mechanical properties, we observed cell alignment in some
experiments. Despite the low cell density in the samples (down to
20000 hASCs mL–1), we found that in some of our
gels, cells aligned and protrusions form in a common direction (Figure a panel S1). The
alignment implicates that isolated cells are able to induce long-range
interactions by matrix remodeling and/or that fiber alignment occurs
in the semiflexible polymer network, which allows neighboring cells
to sense the fiber orientation and align. Similar findings have been
observed and discussed earlier by several research groups.[8,44] These observations are in agreement with cell studies in collagen
and fibrin. We note that fiber alignment will enhance (local) stress-stiffening
behavior in PIC gels[45] and subsequently
influence cellular behavior. In addition, we point out that, over
time, stem cells will secrete natural ECM that will contribute to
the mechanical microenvironment of the cell.
Conclusions
It is universally acknowledged that the storage modulus is a key
component of hydrogel mechanics that affect cellular behavior in 3D
cell cultures. More recently, stress relaxation was identified as
another important contributor. We wish to add to this perspective
that nonlinear mechanics also strongly contribute to the mechanical
spectra that cells are able to sense. In this work, we provide insight
into the correlations between cellular biophysics and stress-stiffening
of biomimetic polymer gels. In the presence of cells that apply contraction
forces to the gel, the stiffness no longer remains a “static”
constant but becomes a dynamic parameter that responds to cell–gel
interactions, which can be tuned by the design of the polymer. In
biological or biomimetic, fibrillar, and strain-stiffening matrices,
it is insufficient to describe the mechanical properties of the gel
by its “static” stiffness alone.For cell culturing
in synthetic matrices, which offer the advantage
of tunable mechanical properties, one needs to engineer cell attachment
sites. The density and distribution of adhesive peptides will play
yet another important role in the accomplishment of desired cell behavior.
Finally, different cells, cultured in the same matrix, will also respond
differently. Our results once more underline that all these factors
should be included in a comprehensive experimental design, but at
the same time, it is still difficult to predict which of the parameters
will dominate behavior and therefore be the most urgent to optimize.Our minimal PIC hydrogel model is particularly suitable as a guide
to further design soft biomimetic materials. As the next step of research,
mechanical analyses of both bulk tissue constructs and the local niche
is needed, for instance, it would be of great interest to characterize
the (variation in) local matrix stiffness using microrheology. Ultimately,
the comprehensive understanding of interactions at the cell–matrix
interface should be utilized to benefit regenerative medicine and
tissue engineering.
Authors: Paula de Almeida; Maarten Jaspers; Sarah Vaessen; Oya Tagit; Giuseppe Portale; Alan E Rowan; Paul H J Kouwer Journal: Nat Commun Date: 2019-02-05 Impact factor: 14.919
Authors: Michaël Schreurs; C Maarten Suttorp; Henricus A M Mutsaers; Anne Marie Kuijpers-Jagtman; Johannes W Von den Hoff; Edwin M Ongkosuwito; Paola L Carvajal Monroy; Frank A D T G Wagener Journal: Med Res Rev Date: 2019-05-18 Impact factor: 12.944
Authors: Ying Zhang; Mirjam M P Zegers; Anika Nagelkerke; Alan E Rowan; Paul N Span; Paul H J Kouwer Journal: Adv Sci (Weinh) Date: 2020-12-11 Impact factor: 16.806
Authors: Dirk Rommel; Matthias Mork; Sitara Vedaraman; Céline Bastard; Luis P B Guerzoni; Yonca Kittel; Rostislav Vinokur; Nikolai Born; Tamás Haraszti; Laura De Laporte Journal: Adv Sci (Weinh) Date: 2022-01-14 Impact factor: 16.806
Authors: Ciqing Tong; Joeri A J Wondergem; Marijn van den Brink; Markus C Kwakernaak; Ying Chen; Marco M R M Hendrix; Ilja K Voets; Erik H J Danen; Sylvia Le Dévédec; Doris Heinrich; Roxanne E Kieltyka Journal: ACS Appl Mater Interfaces Date: 2022-04-10 Impact factor: 10.383