Biohybrid machines that utilize muscle cells to actuate compliant artificial scaffolds are
emerging as novel platforms for bioengineering and soft robotics applications (see the study
by Ricotti et al. for a
recent review). Several biohybrid machines capable of untethered locomotion have been
developed over the past decade, using cardiac or skeletal muscle cells. More recently, a biohybrid swimmer actuated by
neuromuscular units has been demonstrated whereby contractions of an engineered skeletal
muscle tissue were evoked by stimulation of co-cultured motor neurons (MNs) on a
free-standing scaffold. Since animals
use their nervous system to orchestrate complex motor patterns and adaptively respond to
their environment, neuronal control of skeletal muscle bioactuators could potentially enable
the development of future biohybrid machines capable of exhibiting the high-level locomotor
behaviors observed in animals. Advances toward this goal currently require a deeper
understanding of neuromuscular development.A high degree of cross talk between neurons and muscles comes into play during the
development of neuromuscular units. Such cross talk entails reciprocal biochemical and biophysical
interactions, which can be dependent upon spontaneous activity or be mediated by soluble
factors. These bidirectional interactions are thought to play key roles in attaining
neuromuscular units with a proper form and function. Furthermore, in vertebrates, MNs in
the spinal cord participate in neural networks where interactions among large populations of neurons lead to robust
and coordinated firing activity typically in the form of synchronous bursting patterns. The design of next-generation
neuromuscular bioactuators therefore warrants an investigation of how muscles and neural
networks may co-develop in a biohybrid setting.To address this question, we demonstrate here a 3D neuron-muscle co-culture platform to
serve as a test-bed for neuromuscular bioactuator development. The platform architecture
allows co-culture of a neuronal cluster with up to four separate target tissues. The targets
comprise free-standing engineered tissue constructs that are anchored by compliant pillars,
which allow the measurement of contraction forces. First, we co-cultured optogenetic mouse
embryonic stem cell (mESC)-derived neurospheres containing MNs with skeletal muscle strips
as target tissues and verified the formation of functional neuromuscular junctions (NMJs).
We then demonstrated the effects of target-specific long-range interactions on neuronal
outgrowth patterns by using muscles, fibroblasts, and acellular matrix as targets. Next, we
showed that muscles co-cultured with neurons exhibit a significant increase in spontaneous
contractility and a correspondingly higher degree of sarcomere assembly following NMJ
formation compared to muscles in mono-culture. Finally, we performed a separate
microelectrode array (MEA) electrophysiology assay to investigate neural network activity.
We compared firing patterns of networks cultured in regular medium with those cultured in
muscle conditioned medium (CM). Our results revealed that muscle CM significantly enhances
the overall bursting rate as well as the emergence of synchronous bursting of neural
networks. Taken together, our results illustrate improved functional outcomes of both
muscles and neural networks as they co-develop, and our platform provides an avenue for
further inquiry into the roles of synergistic interactions in neuromuscular bioactuator
development.
RESULTS AND DISCUSSION
Multi-target 3D neuron-muscle co-culture platform
We designed and microfabricated a polydimethylsiloxane (PDMS) platform for multi-target
neuron-muscle co-culture in a 3D and compartmentalized setting. The platform has a central
compartment to host a neurosphere surrounded by four target compartments each containing a
pair of T-shaped pillars to anchor the target tissues and measure contraction forces
[Fig. 1(a)]. All compartments have a nominal depth
of 200 μm, enabling 3D culture settings while still allowing
visualization of tissues under a light microscope. Neuron-muscle co-culture is achieved in
two stages [Fig. 1(b)]: first, the target muscle
tissues are formed by mixing skeletal myoblasts with an extracellular matrix (ECM)
solution consisting of type I collagen and Matrigel and seeding the mixture directly into
the target wells by the pipette. The muscle tissues are anchored by the two compliant
pillars [Fig. 1(c)], which allows us to quantify
muscle contraction forces by optically measuring pillar deflections. In the second stage,
a neurosphere containing motor neurons is seeded in the center and the entire platform is
filled with ECM [Fig. 1(d)].
FIG. 1.
3D co-culture in the engineered platform. (a) SEM images of (i) the full platform and
(ii) one of the target wells showing the pillar profile. (b) Schematic of the tissue
seeding process illustrating (i) target cell-ECM seeding, (ii) compacted target
tissues, (iii) neurosphere seeding, and (iv) co-culture tissue. (c) Phase contrast
images of a muscle strip from (i) top and (ii) side views. (d) Phase contrast image of
the full platform after neurosphere seeding. Scale bars: [(a-i) and (d)]
500 μm and [(a-ii), (c-i), and (c-ii)] 200 μm.
3D co-culture in the engineered platform. (a) SEM images of (i) the full platform and
(ii) one of the target wells showing the pillar profile. (b) Schematic of the tissue
seeding process illustrating (i) target cell-ECM seeding, (ii) compacted target
tissues, (iii) neurosphere seeding, and (iv) co-culture tissue. (c) Phase contrast
images of a muscle strip from (i) top and (ii) side views. (d) Phase contrast image of
the full platform after neurosphere seeding. Scale bars: [(a-i) and (d)]
500 μm and [(a-ii), (c-i), and (c-ii)] 200 μm.The simple approach of seeding tissues directly by pipetting makes it possible to design
a multi-target platform, which improves the experimental yield by increasing the number of
target tissues per neuronal cluster. This multi-target architecture may also allow our
platform to serve as a useful test-bed for modeling bioactuators that employ multiple
muscle tissues such as the system recently demonstrated by Morimoto et
al., which involved a pair of antagonistic muscles on a compliant
scaffold. Furthermore, the present
platform design provides about 500 μm separation between the neurosphere
and target tissues [Fig. 1(d)], thus allowing the use
of the platform to investigate long-range interactions. This compartmentalization is
enabled by the hydrophobicity of PDMS: In each target well, the side that faces the
central compartment has three posts separated by small (120 μm) gaps.
When the liquid cell-ECM mixture is seeded only into the target wells, hydrophobicity of
PDMS induces the formation of menisci between the posts, preventing the liquid cell-ECM mixture from leaking into the
central compartment (Fig. S1). After the compaction of cell-laden ECM gels into tissues
inside the four target wells, the neurosphere is then seeded in the center and all five
compartments are filled with ECM, thereby creating a continuous yet compartmentalized
co-culture. Moreover, the PDMS posts that surround the neurosphere and the muscle
compartments may also help maintain compartmentalization throughout co-culture since
confinement by PDMS posts has been shown to reduce the collective migration rates of 3D
multicellular tissue constructs.
Characterization of neuromuscular bioactuators
We developed co-cultures in our platform using C2C12 mouse skeletal myoblasts to create
target muscle strips and co-culture them with neurospheres that were obtained by directed
differentiation of an optogenetic mESC line toward motor neurons (see Methods). After
initiating co-culture, we observed neuronal outgrowth during the first 2–3 days. We then
monitored co-cultures and performed optical stimulation to assess the formation of NMJs.
In all optical stimulation assays, the entire field of view was illuminated with blue
light for 1 s while continuously recording the video of the sample to capture muscle
activity before, during, and after stimulation. To confirm that illuminating the entire
sample does not lead to unintended stimulation of muscle strips, we prepared muscle-only
control samples where muscle strips were formed and embedded in 3D ECM gel without a
neurosphere. Muscle activity was quantified in terms of the contraction force produced by
the muscle strips.We began to observe muscle contractions in response to optical stimulation of MNs around
day 4–5 of co-culture, corresponding to about 2 days after neurites reach the target
muscle strips. In terms of the NMJ formation timeline, this is in agreement with the
previously reported results using the same cell sources. Interestingly, in addition to contractions evoked by stimulation
of MNs, some muscle strips also developed rhythmic spontaneous contraction patterns that
were present before neuronal stimulation (Movie S1). By day 7, we identified three
different muscle behaviors in response to optical stimulation of neurons [Fig. 2(a-i)]: no change in the contraction pattern (21/88
muscle strips), evoked contractions in muscles that were quiescent before stimulation
(19/88 muscle strips), and evoked as well as spontaneous contractions (48/88 muscle
strips). The presence of evoked muscle contractions in the latter two groups suggests the
formation of functional NMJs, and these groups comprised 76% of the muscle strips. For
further analysis, we refer to muscles that are quiescent before stimulation as group 1 and
muscles spontaneously contracting before stimulation as group 2 [Fig. 2(a-ii)].
FIG. 2.
Formation of functional neuromuscular junctions. (a) (i) Muscle strips categorized by
their contraction pattern in response to optical stimulation of neurons. (ii)
Force-time traces of representative samples from groups 1 and 2. The blue rectangle
indicates the optical stimulation. (iii) Definitions of contraction force and period.
(iv) and (v) Comparison of spontaneous and evoked contraction forces in groups 1 and
2. (vi) Comparison of spontaneous and evoked contraction rates in group 2. The values
in panels iv, v, and vi are averaged over the ten contractions immediately preceding
and following optical stimulation for spontaneous and evoked contractions,
respectively. Box plots represent the 25th, 50th, and 75th percentiles with whiskers
representing 1.5×IQR, n = 19 muscle strips for group 1, n = 48 muscle strips for group
2, and **p < 0.005 (student's t-test). (b) (i) Brightfield image of a
muscle strip and (ii) confocal image of the region outlined in (i) illustrating muscle
fibers. (iii) Zoomed views of the region outlined in (ii) showing a muscle fiber with
cross-striations. (c) (i) Confocal images illustrating a neurite (β-tubulin III,
green) extending toward and making connections with post-synaptic receptor clusters on
the muscle (AChR, red). (ii) and (iii) Orthogonal views of the regions indicated by
the arrowheads in the rightmost panel in (c-i). Scale bars: (b-i)
100 μm and [(b-ii) and (c)] 10 μm.
Formation of functional neuromuscular junctions. (a) (i) Muscle strips categorized by
their contraction pattern in response to optical stimulation of neurons. (ii)
Force-time traces of representative samples from groups 1 and 2. The blue rectangle
indicates the optical stimulation. (iii) Definitions of contraction force and period.
(iv) and (v) Comparison of spontaneous and evoked contraction forces in groups 1 and
2. (vi) Comparison of spontaneous and evoked contraction rates in group 2. The values
in panels iv, v, and vi are averaged over the ten contractions immediately preceding
and following optical stimulation for spontaneous and evoked contractions,
respectively. Box plots represent the 25th, 50th, and 75th percentiles with whiskers
representing 1.5×IQR, n = 19 muscle strips for group 1, n = 48 muscle strips for group
2, and **p < 0.005 (student's t-test). (b) (i) Brightfield image of a
muscle strip and (ii) confocal image of the region outlined in (i) illustrating muscle
fibers. (iii) Zoomed views of the region outlined in (ii) showing a muscle fiber with
cross-striations. (c) (i) Confocal images illustrating a neurite (β-tubulin III,
green) extending toward and making connections with post-synaptic receptor clusters on
the muscle (AChR, red). (ii) and (iii) Orthogonal views of the regions indicated by
the arrowheads in the rightmost panel in (c-i). Scale bars: (b-i)
100 μm and [(b-ii) and (c)] 10 μm.To quantify the effect of optical stimulation, we analyzed the muscle contraction
dynamics. For each muscle strip, we computed the force and contraction rate averaged over
the ten contractions immediately before and the ten immediately after stimulation. Here,
we define the contraction rate as 1/τ, where τ is the contraction period measured as the
time between two consecutive contractions [Fig.
2(a-iii)]. In group 1, the effect of neuronal stimulation is self-evident since
muscle strips are quiescent before stimulation and produce contractions with a force of
39.0 ± 34.4 μN upon neuronal stimulation [Fig.2(a-iv)]. In group 2, there was no significant difference in contraction
force before and after stimulation. There was also no significant difference in the
strength of evoked contractions in groups 1 and 2 [Fig.
2(a-v)]. However, the evoked contractions in group 2 can be quantitatively
distinguished from spontaneous contractions by their significantly higher rate [Fig. 2(a-vi)]. In addition, we observed no effect of
light on the contraction dynamics in muscle-only control samples, indicating that
contractions evoked by optical stimulation in co-culture samples are due to the formation
of NMJs between muscle strips and MNs.Furthermore, we performed immunofluorescence assay to confirm the morphology of
neuromuscular units. The C2C12 myoblasts embedded in 3D ECM had differentiated to form
multinucleated muscle fibers with cross-striations [Fig.
2(b)], and neurites extended toward the fibers and made physical connections with
post-synaptic acetylcholine receptor clusters [Fig.
2(c)]. Taken together, these results illustrate the formation of optically
excitable functional NMJs between MNs in stem cell-derived neurospheres and engineered
skeletal muscle tissue constructs in our co-culture platform.
Neuronal outgrowth toward different targets
In the formation of neuromuscular units discussed above, we observed neuronal outgrowth
toward the muscle tissues during the first 2–3 days of co-culture. There has been
experimental evidence suggesting that soluble factors secreted by muscles promote neuronal
outgrowth from MNs in both isolated cultures and co-cultures. To investigate if such an effect is present in our co-culture
platform, we capitalized on the multi-target and compartmentalized design of the platform
and cultured neurospheres with different targets. We performed two sets of experiments
where the targets were muscle tissues and acellular ECM in case 1 [Fig. 3(a)] and muscle tissues and fibroblast tissues in case 2 [Fig. 3(b)]. We allowed the co-cultures 3 days and then
took fluorescence microscopy images of Hb9-GFP+ MNs to visualize outgrowth. To
compare outgrowth toward different targets, we draw an annulus centered around the
neurosphere, divide it into four sectors corresponding to the regions between the
neurosphere and each target, and for each sector quantify the ratio of total fluorescence
light intensity in that sector to the total intensity in the entire annulus as a measure
of the relative degree of outgrowth toward that target [Fig.
3(c-i)].
FIG. 3.
Neuronal outgrowth toward different targets. Brightfield and corresponding confocal
images of representative samples from (a) case 1 and (b) case 2. (c) (i) Confocal
image of motor neurons with the outlines in dashed lines illustrating the four
different sectors that correspond to the regions between the neurosphere and the
different targets and the definition of % outgrowth where “I” refers to the total
fluorescence light intensity. (ii) Comparison of relative outgrowth toward the
different targets in cases 1 and 2. Values are % outgrowth toward each type of target,
and box plots represent the 25th, 50th, and 75th percentiles with whiskers
representing 1.5×IQR, n = 5 co-culture samples each for cases 1 and 2,
**p < 0.005, and **p < 0.0005 (student's t-test). All
scale bars: 500 μm.
Neuronal outgrowth toward different targets. Brightfield and corresponding confocal
images of representative samples from (a) case 1 and (b) case 2. (c) (i) Confocal
image of motor neurons with the outlines in dashed lines illustrating the four
different sectors that correspond to the regions between the neurosphere and the
different targets and the definition of % outgrowth where “I” refers to the total
fluorescence light intensity. (ii) Comparison of relative outgrowth toward the
different targets in cases 1 and 2. Values are % outgrowth toward each type of target,
and box plots represent the 25th, 50th, and 75th percentiles with whiskers
representing 1.5×IQR, n = 5 co-culture samples each for cases 1 and 2,
**p < 0.005, and **p < 0.0005 (student's t-test). All
scale bars: 500 μm.In case 1, we observed significantly more outgrowth toward muscle tissues compared to
acellular ECM. While this result does support the idea that the presence of muscles can
enhance neuronal outgrowth, the mechanism of interaction is ambiguous in this case: As
engineered tissue constructs form, due to compaction and remodeling of the ECM, their
rigidity increases from initial levels comparable to that of acellular ECM to as much as
an order of magnitude higher values.
This can lead to muscle strips and acellular ECM, providing different mechanical cues, and
therefore makes it difficult to ascertain whether the biased outgrowth is due to
mechanical or biochemical signals. To resolve this issue, we performed the experiments in
case 2 where the alternate targets were fibroblast tissues. Fibroblasts embedded in ECM
generate compaction and remodeling of the ECM, the same as muscles, thus eliminating the asymmetry in
mechanical cues. Analysis of the case 2 samples also revealed biased outgrowth toward
muscles [Fig. 3(c-ii)], suggesting that neuronal
outgrowth toward muscles may indeed be enhanced due to muscle-specific soluble
factors.
Co-development of muscle tissues and neural networks through bi-directional
interactions
During the development of neuromuscular units in our platform, we observed an emergence
of spontaneous contraction patterns in a majority of samples [see Figs. 2(a-i) and 2(a-ii)].
Developing skeletal muscle fibers can exhibit spontaneous action potentials and
corresponding contractions even in the absence of neurons possibly due to self-activation of acetylcholine receptors
(AChRs) by endogenous secretion of acetylcholine (ACh). However, the abundance of spontaneous contractions in our
co-cultures prompted us to ask whether they may also be neural induced. To investigate, we
monitored the spontaneous contractions of muscle strips cultured alone and those
co-cultured with neurospheres in our platform. Activity of muscles from both groups was
recorded at days 3, 5, and 7 without external stimulation. In co-cultures, the relative
number of muscle strips that exhibited spontaneous contractions (i.e., active muscle
strips) began to increase at day 5, reaching 67% at day 7 [Fig. 4(a-i)], whereas in the muscle only group, the relative number of active
muscle strips remained below 30% [Fig. 4(a-ii)].
FIG. 4.
Bidirectional cross talk in developing co-cultures. (a) Representative brightfield
images and overall time course of the ratio of active vs quiescent muscle strips in
(i) co-cultures and (ii) muscle-only cultures. (b) Spontaneous contraction forces in
muscle-only and co-culture samples at days 3, 5, and 7. Values are spontaneous
contraction force averaged over a 30 s recording per muscle strip at each day, and box
plots represent the 25th, 50th, and 75th percentiles with whiskers representing
1.5×IQR, n = 27 muscle strips for co-culture, n = 20 muscle strips for muscle-only at
each day, *p < 0.05, and **p < 0.005 (Mann Whitney U
test). (c) Comparison of the percentage of cross-striated muscle fibers between
muscle-only and co-culture groups. Bars represent mean ± SD, n = 6 muscle strips for
each group, and **p < 0.005 (Mann Whitney U test). Confocal images at
the right show sample muscle fibers with and without cross-striations. (d) MEA raster
plots of representative samples from (i) control and (ii) CM groups at day 9. Black
dashed lines represent the individual spikes, blue dashed lines represent the bursts,
and pink boxes outline the synchronous bursts. (e) Time evolution of the MEA burst
rate of neurons in control and muscle CM groups. Box plots represent the 25th, 50th,
and 75th percentiles with whiskers representing 1.5×IQR, the values are average burst
rates per electrode over 10 min recording from the entire well, n = 12 wells each for
control and CM at each day, **p < 0.005, and ***p < 0.0005
(student's t-test). (f) Conceptual illustration of bidirectional cross talk and its
functional outcomes. Scale bars: (a) 500 μm and (c)
10 μm.
Bidirectional cross talk in developing co-cultures. (a) Representative brightfield
images and overall time course of the ratio of active vs quiescent muscle strips in
(i) co-cultures and (ii) muscle-only cultures. (b) Spontaneous contraction forces in
muscle-only and co-culture samples at days 3, 5, and 7. Values are spontaneous
contraction force averaged over a 30 s recording per muscle strip at each day, and box
plots represent the 25th, 50th, and 75th percentiles with whiskers representing
1.5×IQR, n = 27 muscle strips for co-culture, n = 20 muscle strips for muscle-only at
each day, *p < 0.05, and **p < 0.005 (Mann Whitney U
test). (c) Comparison of the percentage of cross-striated muscle fibers between
muscle-only and co-culture groups. Bars represent mean ± SD, n = 6 muscle strips for
each group, and **p < 0.005 (Mann Whitney U test). Confocal images at
the right show sample muscle fibers with and without cross-striations. (d) MEA raster
plots of representative samples from (i) control and (ii) CM groups at day 9. Black
dashed lines represent the individual spikes, blue dashed lines represent the bursts,
and pink boxes outline the synchronous bursts. (e) Time evolution of the MEA burst
rate of neurons in control and muscle CM groups. Box plots represent the 25th, 50th,
and 75th percentiles with whiskers representing 1.5×IQR, the values are average burst
rates per electrode over 10 min recording from the entire well, n = 12 wells each for
control and CM at each day, **p < 0.005, and ***p < 0.0005
(student's t-test). (f) Conceptual illustration of bidirectional cross talk and its
functional outcomes. Scale bars: (a) 500 μm and (c)
10 μm.In addition to overall contractile activity, we measured and compared the force magnitude
of spontaneous contractions [Fig. 4(b)]. At day 3,
muscles in both groups either were quiescent or had relatively weak spontaneous
contractions with no significant difference in magnitude between muscle-only and
co-culture samples. However, starting at day 5, the co-cultured muscle strips had
significantly higher spontaneous contraction force compared to the muscle-only group. By
day 7, spontaneous contraction forces as high as 102 μN were recorded in
co-culture, whereas the maximum spontaneous contraction force in the muscle-only group was
18.8 μN [Fig. 4(b) and Movie S2].
Given this significantly higher spontaneous contraction force in co-cultured muscle
strips, we performed immunofluorescence staining of sarcomeric α-actinin on muscle strips
from both groups at day 7. In each muscle strip, we observed cross-striated muscle fibers
as well as fibers without cross-striations. The relative number of cross-striated muscle
fibers was significantly higher in co-cultured muscle strips (70 ± 8%, n = 6 muscle
strips) compared to muscle-only (41 ± 6%, n = 6 muscle strips) [Fig. 4(c)], indicating that muscles in co-culture had a relatively high
degree of contractile apparatus assembly. This offers a possible explanation for the
measurement of higher spontaneous contraction force in co-cultures.These results prompt the question of how co-culture with neurons could induce higher
levels of spontaneous muscle contractility. Previous in vivo and
ex vivo studies on neuromuscular units have shown that MNs
spontaneously secrete ACh during development, that there is a marked increase in spontaneous neural
activity shortly after neurons come into contact with muscles, and that this activity can induce contractions in the
innervated muscle. Furthermore, recent
in vivo work has demonstrated that spontaneous muscle contractions
precede and contribute to sarcomere assembly. Spontaneous firing of neurons and corresponding synaptic
transmission is therefore a likely explanation of how the muscles in co-culture in our
platform develop more and stronger spontaneous contractions and the associated increase in
contractile apparatus assembly. This is further supported by the observation that in our
platform, the effect of NMJ formation (i.e., muscle contractions in response to optical
stimulation of MNs) begins to appear around day 4–5 of co-culture and that the significant
increase in spontaneous muscle contractility also begins at day 5.To test if our stem cell-derived neurons can develop spontaneous firing patterns, we used
microelectrode arrays (MEAs). In MEA electrophysiology of developing neural cultures, the
following spontaneous activity pattern can typically be observed: First, cells begin
firing randomly, with spikes corresponding to single action potentials observed scattered
throughout the MEA. Cells then begin firing in bursts or trains of spikes. Finally, as
neural connectivity increases, the neural networks begin to fire in synchronized
bursts. We dissociated
our neurospheres at the last day of neural differentiation (corresponding to day 0 of
co-culture in the 3D NMJ platform), plated them on MEAs at high cell density, and recorded
electrical activity over time. After 9 days in culture, we observed spiking and bursting
activity in a few electrodes, indicating spontaneous neural activity, but the activity
level across the entire culture was relatively low as most electrodes were quiescent
[Fig. 4(d-i)]. This is not surprising since it has
been shown that with stem cell-derived neurons, the development of robust bursting
activity can take several weeks.However, considering the fact that spontaneous neural activity during in
vivo NMJ development increases markedly shortly after neurons come into contact
with muscles, we postulated that
muscle-secreted factors may enhance neural firing. To test this, we cultured neurons on
MEAs in muscle-conditioned medium (CM, collected from separate C2C12 cultures) to emulate
the postulated soluble factor-mediated retrograde signaling. Strikingly, neurons cultured
in muscle CM had substantially improved spontaneous activity [Fig. 4(d-ii)], with robust synchronous busts appearing as early as day 7
in culture (Fig. S2). Quantitatively, the effect of muscle CM corresponded to increased
bursting rates with the difference to the control group becoming significant starting at
day 5 [Fig. 4(e)]. In terms of the timeline, this
matches closely with the increase in muscle contractility that we observed in co-cultures
starting around day 5.
CONCLUSION
We have developed a relatively simple yet versatile 3D co-culture platform as a test-bed
for neuromuscular bioactuator development. Using our platform in conjunction with MEA
electrophysiology, we investigated the roles of activity-dependent and soluble
factor-mediated reciprocal interactions in the co-development of muscle tissues and neural
networks. Taken together, our results illustrate synergistic outcomes of neuron-muscle
interactions during in vitro neuromuscular development [Fig. 4(f)]: muscles secrete soluble factors that enhance
spontaneous neural firing and the development of neural networks with synchronous bursting
patterns. Neural firing in turn facilitates muscle contractility and the corresponding
maturation of contractile apparatus. Our findings illustrate the potential value of
identifying mechanisms for modulating these reciprocal interactions for the development of
future neuromuscular bioactuators that can achieve predictable and tunable motor
patterns.
METHODS
Cell culture
C2C12 skeletal myoblasts and NIH/3T3 fibroblasts (both from ATCC) were maintained below
70% confluency in growth medium consisting of high-glucose Dulbecco's modified Eagle's
medium (DMEM), 10% v/v fetal bovine serum (FBS), and 2 mM L-glutamine. To facilitate
myotube formation by C2C12, they were cultured in muscle differentiation medium consisting
of high-glucoseDMEM, 10% v/v horse serum, and 2 mM L-glutamine (all reagents from Gibco).
All C2C12 and NIH/3T3 cells were used at passage number 5. The optogenetic mouse ESC line
ChR2H134R-HBG3 Hb9-GFP, a
generous gift from Professor Roger Kamm's lab, Massachusetts Institute of Technology, MA,
was maintained in an undifferentiated state on a feeder layer of CF-1 mouse embryonic
fibroblasts (Applied Stem Cell) in growth medium consisting of EmbryoMax DMEM (EMD
Millipore), 15% v/v ESC-qualified FBS (Gibco), 1X Nonessential Amino Acids (Gibco), 1X
EmbryoMax nucleosides (EMD Millipore), 2 mM L-glutamine (Gibco), 0.1 mM β-mercaptoethanol
(Gibco), and 103 units/ml leukemia inhibitory factor (EMD Millipore).
Neurospheres with MNs were obtained by differentiating ESCs using an established
protocol. On day −6
(i.e., 6 days before initiation of co-culture), ESCs were plated in a
tissue culture dish in neural differentiation medium (NDM) consisting of Advanced
DMEM/F-12 and Neurobasal medium at a volume ratio of 1:1, 10% v/v KnockOut serum
replacement, 2 mM L-glutamine, and 0.1 mM β-mercaptoethanol (all from Gibco). Cells were
allowed to aggregate into embryoid bodies (EBs) in NDM for 2 days. On day -4, floating
aggregates were collected and plated in a new dish in NDM supplemented with
1 μM retinoic acid (RA) (Sigma) and 1 μM sonic
hedgehog agonist purmorphamine (PM) (EMD Millipore) to direct differentiation to MNs.
Cells were allowed to differentiate for 3 days. On day −1, EBs were collected and
re-plated in NDM supplemented with fresh 1 μM RA and
1 μM PM, as well as 10 ng/ml glial derived neurotrophic factor (GDNF)
(Neuromics) and 10 ng/ml ciliary neurotrophic factor (CNTF) (Sigma). On day 0, EBs
(neurospheres) were collected and seeded either into the PDMS platform for co-culture or
dissociated and seeded onto MEAs for electrical recordings in NDM supplemented with GDNF
and CNTF at 10 ng/ml each. The work presented here was based on the use of mouse cell
lines mentioned above and did not involve any human subjects, human materials, or live
animals. Therefore, there was no requirement for institutional ethics approval for this
study.
PDMS platform fabrication
PDMS platforms were fabricated using microfabricated silicon molds and manual
post-processing (Fig. S3). Silicon wafers were patterned by photolithography, etched using
the Bosch process, and subsequently coated with polytetrafluoroethylene to facilitate
removal of PDMS from the mold. PDMS (Sylgard 184) base and cross-linker were mixed at a
ratio of 10:1 by weight, poured onto the silicon molds, and degassed using a vacuum
desiccator. Samples were cured at 60 °C for 12 h and peeled off the silicon mold. To
achieve the T-shape of the pillars, which is necessary to anchor muscle strips, we
attached caps onto the pillars, using a process adapted from previously published
studies. Approximately
200 × 150 μm pieces were cut from spin-coated PDMS films of
30 μm nominal thickness using a razor blade mounted on an xyz stage.
These caps were then manually glued onto the pillars using uncured PDMS.
Tissue seeding in PDMS platforms
Prior to tissue seeding, platforms were cleaned by first sonicating in ethanol for 20 min
and then autoclaving at 121 °C for 45 min while immersed in DI water. Platforms were then
blow dried and sterilized by autoclaving at 121 °C for another 45 min with a drying time
of 30 min. For all tissue seeding procedures, ECM solution was prepared on ice by first
neutralizing type I collagen from the rat tail (Corning) with 1 N sodium hydroxide, 10×
phosphate buffered saline (PBS), and molecular biology grade water and then mixing
neutralized collagen thoroughly with growth factor reduced Matrigel (Corning). Collagen
and Matrigel were used at final concentrations of 2 mg/ml each. To form muscle or
fibroblast strips, C2C12 or NIH/3T3 were suspended in ECM solution at a density of
2.5 × 106 cells/ml. Approximately 0.2 μl of cell-ECM mixture was pipetted
into each target well and polymerized at room temperature for 30 min. Samples were then
inundated in growth medium and incubated for 1 day, while they compacted the ECM gel and
formed a strip. After 1 day, culture medium was switched to muscle differentiation medium
to facilitate myotube formation in muscle strips. Samples were kept in muscle
differentiation medium for 6 days with daily medium replacements. To initiate
neuron-muscle co-culture, medium was aspirated, the entire platform was filled with a
fresh ECM solution, and a neurosphere with a diameter of 300–400 μm was
manually pipetted into the central well. ECM solution was then allowed to polymerize at
room temperature for 30 min. Samples were incubated in NDM with GDNF and CNTF at 10 ng/ml
each, with daily medium replacements until experiments were terminated.
Image acquisition and optical stimulation
All live imaging was performed on an Olympus IX81 inverted microscope (Olympus America)
with a digital CMOS camera (Hamamatsu), mounted on a vibration isolation table. The
microscope was equipped with an environmental chamber to maintain samples at 37 °C and 5%
CO2 during imaging. For muscle contraction assays, phase contrast images were
taken at 100 fps using a 4× air objective to have the entire sample in the field of view.
For optical stimulation, a GFP filter coupled to an X-Cite 120PC Q widefield fluorescent
light source (Excelitas Technologies) was used to deliver blue light with a wavelength of
470 nm at 3.9 mW/mm2 as measured using a power meter at the sample plane.
Samples were stimulated with a 1-second-long bout of light by controlling the motorized
shutter of the fluorescent light source.
Muscle strip force measurement
Pillar deflections caused by muscle contractions were measured from video recordings
using the image analysis software Tracker (http://physlets.org/tracker). To
compute contraction force, the measured deflections were multiplied by pillar stiffness.
Pillar stiffness was estimated using a finite element model of the PDMS pillar created in
Comsol Multiphysics (Fig. S4). The elastic modulus of PDMS was measured by
nano-indentation to be 1.72 ± 0.14 MPa (mean ±SD, n = 6). The pillar width, thickness,
height, and cap height were measured by optical microscopy to be
128.9 ± 1.1 μm, 90.0 ± 1.2 μm,
192.7 ± 5.1 μm, and 26.6 ± 2.1 μm, respectively (mean
± SD, n = 30). A linear elastic constitutive model was used with an elastic modulus of
1.72 MPa and Poisson's ratio of 0.5. Side views of the muscle strips show that muscles
wraparound the pillar caps. Thus, to approximate experimental loading conditions in the
finite element model, force was applied to the pillar cap [Fig. S4(b)]. The fixed boundary
condition (zero displacement) was prescribed at the bottom surface of the pillar. Pillar
geometry was meshed using tetrahedral elements. Forces ranging from 0 to
200 μN were applied, and pillar deformation was monitored. The slope of
the force-displacement curve, i.e., pillar stiffness, was found to be
4.0 μN/μm.
Immunofluorescence
To visualize muscle fibers and cross-striations, samples were fixed in 4% v/v
paraformaldehyde in PBS for 4 h at 4 °C, permeabilized with 0.2% v/v Triton X-100 for
30 min at room temperature (RT), and then incubated in blocking buffer consisting of 5%
v/v goat serum, 1% w/v bovine serum albumin, and 0.05% v/v Tween-20 in PBS (all reagents
from Sigma) for 2 h at RT. Samples were then incubated overnight at 4 °C in rabbit
anti-α-actinin (1:250, Abcam) primary antibody diluted in blocking buffer, followed by 2 h
at RT in Alexa Fluor 488goat-anti-rabbit IgG H&L (1:1000, Abcam) secondary antibody
diluted in blocking buffer. Nuclei were stained with DAPI (5 μg/ml,
Invitrogen) for 30 min at RT. To visualize neuromuscular units, AChRs were labeled with
Alexa Fluor 647-conjugated α-bungarotoxin (2 μg/ml, Invitrogen) for 1 h
at 37 °C, and samples were fixed, permeabilized, and blocked as before. Samples were then
incubated overnight at 4 °C in rabbit anti-β-tubulin III (1:1000, Synaptic Systems)
primary antibody diluted in blocking buffer, followed by 2 h at RT in Alexa Fluor 488goat-anti-rabbit IgG H&L (1:1000, Abcam) secondary antibody diluted in blocking
buffer. In all experiments, samples were rinsed 3 × 5 min with PBS between each
incubation. Samples were embedded in ProLong Glass Antifade mountant (Invitrogen), covered
with a glass coverslip, allowed 24 h at RT for the mountant to cure, and then imaged on a
Zeiss LSM 710 confocal microscope.
Conditioned medium
C2C12 was plated in tissue culture flasks, allowed to reach full confluency, and then
cultured in muscle differentiation medium for 6 days with daily medium replacements. On
day 6, muscle differentiation medium was aspirated, and cells were rinsed with PBS and
incubated in 0.1 ml/cm2 of Advanced DMEM/F-12 and Neurobasal medium at a volume
ratio of 1:1 supplemented with 2 mM L-glutamine (all from Gibco). After 24 h, this basal
CM was collected, filtered using syringe filters with a pore size of
0.22 μm, and neutralized to pH 7–7.4 using 1N sodium hydroxide. The
full CM consists of basal CM, Advanced DMEM/F-12, and Neurobasal medium at a volume ratio
of 2:1:1, with 10% v/v KnockOut serum replacement, 2 mM L-glutamine, 0.1 mM
β-mercaptoethanol, and GDNF and CNTF at 10 ng/ml each. NDM with 10 ng/ml each of GDNF and
CNTF was used as control.
MEA preparation, recording, and data analysis
12-well MEA plates (Axion BioSystems) contained 64 embedded
30 μm-diameter gold microelectrodes per well, spaced
200 μm apart. Plates were prepared for cell seeding according to the
manufacturer's protocols. Wells were coated with 0.1% polyethyleneimine for 1 h at 37 °C,
then rinsed 3 times with PBS, and allowed to air dry in a biosafety cabinet overnight. The
following day, wells were coated with 20 μg/ml of laminin (Sigma) for 2 h
at 37 °C before cell seeding. Neurospheres were dissociated in 0.05% w/v trypsin at 37 °C
for ∼5 min and passed through a 40 μm strainer to obtain a cell
suspension. Dissociated cells were suspended in a 1:1 mixture of 20 μg/ml
laminin and NDM supplemented with 10 ng/ml GDNF and 10 ng/ml CNTF and seeded on MEA plates
as a droplet centered over the electrode grid, at a density of 80 000 cells/well. Cells
were incubated for 2 h at 37 °C to allow for attachment and then inundated in NDM
supplemented with 10 ng/ml GDNF and 10 ng/ml CNTF. Plates received medium changes every
other day. Electrical activity on the MEAs was recorded using the Maestro system and AxIS
software (both from Axion BioSystems), using the following settings: bandpass filter
(Butterworth, 300–5000 Hz), spike detector (adaptive threshold crossing, 8×SD of RMS
noise), and burst detector (100 ms maximum inter-spike interval, five spikes minimum, ten
spikes minimum for network bursts, and tens mean firing rate detection window). Recordings
were performed daily for 15 min at 37 °C. Raw files were processed offline, skipping the
first 5 min of each recording as an acclimation period. Raster plots were generated using
the Neural Metric tool (Axion BioSystems).See the supplementary
material for supplementary figures illustrating separate
muscle tissue seeding (Fig. S1), time evolution of neural activity on MEAs (Fig. S2),
schematic of the PDMS platform fabrication process (Fig. S3), and pillar stiffness
calculation (Fig. S4) and supplementary movies showing muscle contractions of a co-culture
sample (Movie S1) and spontaneous contractions of muscle strips from co-culture and
muscle-only groups.
Authors: Adam W Feinberg; Alex Feigel; Sergey S Shevkoplyas; Sean Sheehy; George M Whitesides; Kevin Kit Parker Journal: Science Date: 2007-09-07 Impact factor: 47.728
Authors: Michael A Fox; Joshua R Sanes; Dorin-Bogdan Borza; Veraragavan P Eswarakumar; Reinhard Fässler; Billy G Hudson; Simon W M John; Yoshifumi Ninomiya; Vadim Pedchenko; Samuel L Pfaff; Michelle N Rheault; Yoshikazu Sado; Yoav Segal; Michael J Werle; Hisashi Umemori Journal: Cell Date: 2007-04-06 Impact factor: 41.582
Authors: Caroline Cvetkovic; Ritu Raman; Vincent Chan; Brian J Williams; Madeline Tolish; Piyush Bajaj; Mahmut Selman Sakar; H Harry Asada; M Taher A Saif; Rashid Bashir Journal: Proc Natl Acad Sci U S A Date: 2014-06-30 Impact factor: 11.205
Authors: Sung-Jin Park; Mattia Gazzola; Kyung Soo Park; Shirley Park; Valentina Di Santo; Erin L Blevins; Johan U Lind; Patrick H Campbell; Stephanie Dauth; Andrew K Capulli; Francesco S Pasqualini; Seungkuk Ahn; Alexander Cho; Hongyan Yuan; Ben M Maoz; Ragu Vijaykumar; Jeong-Woo Choi; Karl Deisseroth; George V Lauder; L Mahadevan; Kevin Kit Parker Journal: Science Date: 2016-07-08 Impact factor: 47.728
Authors: Teemu J Heikkilä; Laura Ylä-Outinen; Jarno M A Tanskanen; Riikka S Lappalainen; Heli Skottman; Riitta Suuronen; Jarno E Mikkonen; Jari A K Hyttinen; Susanna Narkilahti Journal: Exp Neurol Date: 2009-04-22 Impact factor: 5.330
Authors: Sebastien G M Uzel; Randall J Platt; Vidya Subramanian; Taylor M Pearl; Christopher J Rowlands; Vincent Chan; Laurie A Boyer; Peter T C So; Roger D Kamm Journal: Sci Adv Date: 2016-08-03 Impact factor: 14.136
Authors: Miriam Filippi; Oncay Yasa; Roger Dale Kamm; Ritu Raman; Robert K Katzschmann Journal: Proc Natl Acad Sci U S A Date: 2022-08-24 Impact factor: 12.779
Authors: Onur Aydin; Austin P Passaro; Ritu Raman; Samantha E Spellicy; Robert P Weinberg; Roger D Kamm; Matthew Sample; George A Truskey; Jeremiah Zartman; Roy D Dar; Sebastian Palacios; Jason Wang; Jesse Tordoff; Nuria Montserrat; Rashid Bashir; M Taher A Saif; Ron Weiss Journal: APL Bioeng Date: 2022-03-02