Shuo Yang1, Pascal A Pieters1, Alex Joesaar1, Bas W A Bögels1, Rens Brouwers1, Iuliia Myrgorodska2, Stephen Mann2, Tom F A de Greef1,3. 1. Laboratory of Chemical Biology, Department of Biomedical Engineering, Computational Biology Group, Department of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, P.O. Box 513, Eindhoven 5600 MB, The Netherlands. 2. Centre for Protolife Research and Max Planck Bristol Centre for Minimal Biology, School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom. 3. Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, Nijmegen 6525 MB, The Netherlands.
Abstract
Collective decision making by living cells is facilitated by exchange of diffusible signals where sender cells release a chemical signal that is interpreted by receiver cells. A variety of nonliving artificial cell models have been developed in recent years that mimic various aspects of diffusion-based intercellular communication. However, localized secretion of diffusive signals from individual protocells, which is critical for mimicking biological sender-receiver systems, has remained challenging to control precisely. Here, we engineer light-responsive, DNA-encoded sender-receiver architectures, where protein-polymer microcapsules act as cell mimics and molecular communication occurs through diffusive DNA signals. We prepare spatial distributions of sender and receiver protocells using a microfluidic trapping array and set up a signaling gradient from a single sender cell using light, which activates surrounding receivers through DNA strand displacement. Our systematic analysis reveals how the effective signal range of a single sender is determined by various factors including the density and permeability of receivers, extracellular signal degradation, signal consumption, and catalytic regeneration. In addition, we construct a three-population configuration where two sender cells are embedded in a dense array of receivers that implement Boolean logic and investigate spatial integration of nonidentical input cues. The results offer a means for studying diffusion-based sender-receiver topologies and present a strategy to achieve the congruence of reaction-diffusion and positional information in chemical communication systems that have the potential to reconstitute collective cellular patterns.
Collective decision making by living cells is facilitated by exchange of diffusible signals where sender cells release a chemical signal that is interpreted by receiver cells. A variety of nonliving artificial cell models have been developed in recent years that mimic various aspects of diffusion-based intercellular communication. However, localized secretion of diffusive signals from individual protocells, which is critical for mimicking biological sender-receiver systems, has remained challenging to control precisely. Here, we engineer light-responsive, DNA-encoded sender-receiver architectures, where protein-polymer microcapsules act as cell mimics and molecular communication occurs through diffusive DNA signals. We prepare spatial distributions of sender and receiver protocells using a microfluidic trapping array and set up a signaling gradient from a single sender cell using light, which activates surrounding receivers through DNA strand displacement. Our systematic analysis reveals how the effective signal range of a single sender is determined by various factors including the density and permeability of receivers, extracellular signal degradation, signal consumption, and catalytic regeneration. In addition, we construct a three-population configuration where two sender cells are embedded in a dense array of receivers that implement Boolean logic and investigate spatial integration of nonidentical input cues. The results offer a means for studying diffusion-based sender-receiver topologies and present a strategy to achieve the congruence of reaction-diffusion and positional information in chemical communication systems that have the potential to reconstitute collective cellular patterns.
Collective
behavior in cellular
systems emerges from a tightly choreographed interplay between cellular
communication and intracellular signaling processes.[1] Sender–receiver architectures, where sender cells
secrete soluble signals which form a concentration gradient that is
interpreted by receiver cells, are ubiquitous in biological systems.[2] Sender–receiver topologies allow cellular
populations to collectively regulate key intracellular events such
as cellular growth,[3−5] cell death,[4] and cell
differentiation[6] and orchestrate diverse
multicellular functions such as tissue regeneration,[7] cell migration,[8] immune response
amplificatio,n[9−12] and robust positioning[13−17] of cells within a tissue. The effective communication distance over
which a single sender can propagate a soluble signal is determined
by a number of physicochemical and biological determinants.[18] Previous work suggests that for many living
sender–receiver systems this characteristic length scale is
in the order of 50–500 μm[7,19−21] and can be modulated by diverse factors such as cell density,[9] signal diffusivity,[18] extracellular signal degradation,[22] and
signal consumption[9] by receiver cells.
However, how each of these factors individually controls the signaling
length scale remains unclear.Synthetic sender–receiver
architectures[2,23,24] based on genetically engineered cells have
emerged as excellent tools to establish population-level behaviors
such as morphogen reconstitution,[17,25] artificial
networks,[26−29] Boolean logic gates,[30,31] and pattern formation,[32,33] which all arise from the complex interplay of cell–cell communication
and intracellular processes. However, quantitative analysis of sender–receiver
systems in living cells is complicated by the large number of variables
and context/pathway-specific responses of individual cells. Therefore,
a generic platform that would allow quantitative spatiotemporal analysis
of sender–receiver architectures remains to be developed. A
promising approach to circumvent the use of real cells is to implement
synthetic communication modules using protocells which serve as minimalistic
model systems for living cells.[34−37] While current protocell-based systems do not display
the rich information processing capabilities of living cells, their
minimalistic design allows for rudimentary biological processes to
be mimicked with high degrees of control over experimental conditions.
Diffusion-mediated communication has been established in bead-based[38−41] and structurally more cell-like protocell-based systems using a
range of soluble signaling factors such as small molecules,[42,43] proteins,[44] and DNA.[45] However, currently no methods exist that can spatially
control diffusive signal release at the single protocell level, which
is a prerequisite to engineer complex sender–receiver architectures.
In addition, while concentration gradients and spatial integration
of multiple diffusive signals have been reported for bead-based systems[38,46] and compartmentalized Belousov–Zhabotinsky (BZ) reactions,[47] similar advances are less developed for protocells
based on biochemical components.Previously, we have developed
the general and scalable platform
BIO-PC[45] (Biomolecular Implementation of
Protocellular Communication) capable of distributed interprotocellular
molecular communication through DNA strand displacement (DSD) reactions.[48] Proteinosomes[49] are
used as cell-like semipermeable compartments, which contain localized
DNA gate complexes and are permeable to short DNA strands that can
initiate DSD reactions. Due to the excellent programmability and predictability
of DSD,[50,51] BIO-PC has great potential in mimicking
key features of cell–cell communication in living systems.
However, spatial control over signal release is absent in the original
BIO-PC implementation, which restricts quantitative analysis of sender–receiver
systems. In the present work, we adapted the BIO-PC platform for implementation
of diffusion-based sender–receiver architectures (Figure A). We established
sender–receiver systems by sequential localization of a single
sender and receiver protocells in a microfluidic trapping array. Spatially
controlled signal release from the sender was initiated by light activation
resulting in receiver activation by a diffusion-consumption mechanism.[9] Our work revealed how the corresponding signaling
length scale depends on the density and permeability of receivers,
signal consumption as a result of receiver activation, and extra-protocellular
signal degradation. We then constructed a sender–transceiver
system where the diffusible signal responsible for activation of receivers
was recycled by a fuel-driven catalytic DSD reaction and revealed
an increase in signaling length scale. Finally, we established a spatially
encoded Boolean AND gate at the population level where the receiver
population integrates nonidentical signals released from two distant
senders. Our spatially controlled, DNA-encoded protocell system allows
quantitative analysis of diffusion-based sender–receiver architectures
and has the potential to uncover design principles of natural cell–cell
communication modules.
Figure 1
Light-activated DNA-encoded sender–receiver spatial
system.
(A) A single sender protocell and multiple receiver protocells are
localized on a 2D spatial grid using a PDMS-based trapping array.
Light-activated release of a ssDNA signal from the sender protocell
sets up a signaling gradient which activates nearby receiver protocells.
By controlling the characteristics of the protocells and environmentalfactors,
this architecture enables quantitative analysis of diffusive signal
propagation in space and time and programmable properties. (B) The
sender protocell contains a fluorescently quenched internalized gate
complex F1Q1 anchored to streptavidin using
a biotinylated DNA gate strand (F1). Signal release from
the sender protocell is triggered by laser irradiation resulting in
photocleavage of strand Q1, concomitant dissociation of
the two cleaved parts (A and B) and Cy5 fluorescence. Signaling strand
A activates the surrounding receiver protocells by displacement of
a quencher strand (Q2) from an internalized streptavidin-anchored
gate complex F2Q2 to produce an Alexa546 fluorescence
output and consumption of strand A. (C) Confocal micrographs of one
sender protocell showing time-dependent increase in Cy5 fluorescence
upon laser (405 nm) irradiation, indicating signal release. The plot
shows the background-corrected fluorescence trace and exponential
fit of the photocleavage reaction with a first-order rate constant
of 0.0278 min–1. Experiments were performed in independent
triplicates. (D) Confocal micrographs of one sender and multiple receivers
(FITC-labeled proteinosome membrane, green) showing time-dependent
increase in Cy5 fluorescence (red) and Alexa546 (yellow) fluorescence
associated with signal release and activation, respectively. (E) Binning
method employed to analyze spatial receiver activation. Protocells
are binned in concentric shells based on their distance from the sender
(left images). Plots (right) show time-dependent changes in the concentration
of activated DNA gates associated with receiver protocells in different
concentric shells arranged around the central sender. Shell 1 (dark
red) is closest to the sender. The upper limit of the distance from
the receiver protocells to the sender protocell of each shell is listed
next to the color bars. (F) Concentration of activated DNA gate complexes
in receiver protocells plotted for different times as a function of
distance to the sender. The fluorescence intensity of each protocell
at intervals of exactly 10 min was obtained through linear interpolation
and the average of each distance bin (50 μm per bin) was plotted
for these time points (Supporting Information, Supplemental Methods). (G) Plots of concentrations of activated
DNA gates in individual receivers positioned at different distances
from the sender protocell. Data collected after 2 h of signal release.
The color code corresponds to the different concentric shells as shown
in (E). Line represents fit of the data with Gaussian function. Sender
protocells and receiver protocells were prepared using 10 and 4 μM
streptavidin, respectively. Experiments were performed at room temperature.
All scale bars are 100 μm.
Light-activated DNA-encoded sender–receiver spatial
system.
(A) A single sender protocell and multiple receiver protocells are
localized on a 2D spatial grid using a PDMS-based trapping array.
Light-activated release of a ssDNA signal from the sender protocell
sets up a signaling gradient which activates nearby receiver protocells.
By controlling the characteristics of the protocells and environmentalfactors,
this architecture enables quantitative analysis of diffusive signal
propagation in space and time and programmable properties. (B) The
sender protocell contains a fluorescently quenched internalized gate
complex F1Q1 anchored to streptavidin using
a biotinylated DNA gate strand (F1). Signal release from
the sender protocell is triggered by laser irradiation resulting in
photocleavage of strand Q1, concomitant dissociation of
the two cleaved parts (A and B) and Cy5 fluorescence. Signaling strand
A activates the surrounding receiver protocells by displacement of
a quencher strand (Q2) from an internalized streptavidin-anchored
gate complex F2Q2 to produce an Alexa546 fluorescence
output and consumption of strand A. (C) Confocal micrographs of one
sender protocell showing time-dependent increase in Cy5 fluorescence
upon laser (405 nm) irradiation, indicating signal release. The plot
shows the background-corrected fluorescence trace and exponential
fit of the photocleavage reaction with a first-order rate constant
of 0.0278 min–1. Experiments were performed in independent
triplicates. (D) Confocal micrographs of one sender and multiple receivers
(FITC-labeled proteinosome membrane, green) showing time-dependent
increase in Cy5 fluorescence (red) and Alexa546 (yellow) fluorescence
associated with signal release and activation, respectively. (E) Binning
method employed to analyze spatial receiver activation. Protocells
are binned in concentric shells based on their distance from the sender
(left images). Plots (right) show time-dependent changes in the concentration
of activated DNA gates associated with receiver protocells in different
concentric shells arranged around the central sender. Shell 1 (dark
red) is closest to the sender. The upper limit of the distance from
the receiver protocells to the sender protocell of each shell is listed
next to the color bars. (F) Concentration of activated DNA gate complexes
in receiver protocells plotted for different times as a function of
distance to the sender. The fluorescence intensity of each protocell
at intervals of exactly 10 min was obtained through linear interpolation
and the average of each distance bin (50 μm per bin) was plotted
for these time points (Supporting Information, Supplemental Methods). (G) Plots of concentrations of activated
DNA gates in individual receivers positioned at different distances
from the sender protocell. Data collected after 2 h of signal release.
The color code corresponds to the different concentric shells as shown
in (E). Line represents fit of the data with Gaussian function. Sender
protocells and receiver protocells were prepared using 10 and 4 μM
streptavidin, respectively. Experiments were performed at room temperature.
All scale bars are 100 μm.
Results
and Discussion
Construction of a Light-Activated Spatial
DNA-Encoded Sender-Receiver
System
We adapted the BIO-PC platform to function as a sender–receiver
architecture by employing two types of streptavidin-containing proteinosome-based
semipemeable protocells which were loaded with biotinylated DNA gate
complexes capable of sending or receiving short single-stranded DNA
strands, respectively (Figure B). Our setup is based on preparation of multimodal protocell
populations consisting of a single sender and multiple receiver protocells
(average protocellular diameter 33.84 μm ± 5.99 μm, Figure S1) using a microfluidic trapping array.
Diffusive molecular communication from the sender to surrounding receiver
protocells is initiated by applying laser irradiation to the sender
protocell, resulting in cleavage of an internalized photocleavable
nitrobenzyl linker and concomitant release of DNA strand A. Strand
A functions as the diffusible signal that is secreted from the sender
protocell and migrates through the medium, thereby activating surrounding
receiver protocells and resulting in a fluorescent response which
can be probed with high spatiotemporal resolution (vide infra). Specifically, the sender protocell contains an encapsulated DNA
gate complex F1Q1 consisting of a fluorophore
(Cy5)-labeled gate strand F1 and strand Q1 functionalized
with a quencher and photocleavable nitrobenzyl moiety (Figure B). Upon laser irradiation,
strand Q1 is cleaved into two shorter ssDNA strands A and
B which dissociate from the F1 strand at room temperature
(Table S1). We characterized the photocleavage
of the internalized F1Q1 gate complex by localizing
a single sender protocell in the trapping array followed by irradiation
with laser light, resulting in an increase in Cy5 fluorescence of
the sender protocell over time due to the cleavage of Q1 and dissociation of the quencher-labeled fragment B (Figure C and Movie S1). The photocleavage process is observed to follow first
order kinetics (Figures C and S2). Furthermore, photocleavage
of the nitrobenzyl linker inside the sender protocell is localized
to the illuminated area and a specific wavelength (Figures S3 and S4). Together, these results validate that
the photocleavage of internalized DNA gate complexes inside a sender
protocell can be achieved with a high spatial resolution.Next,
we assembled a multimodal sender–receiver population by sequential
loading of a single sender and multiple (∼150) receiver protocells.
The receiver protocells contain an encapsulated DNA gate complex F2Q2 consisting of a fluorophore (Alexa 546)-labeled
gate strand F2 with an exposed toehold domain and a quencher-labeled
strand Q2 (Figure B) resulting in quenching of the Alexa fluorescence. Activation
of the receiver protocells is initiated by toehold-mediated strand
displacement of Q2 by signal strand A released from the
sender protocell. Experiments were initiated by laser irradiation
(405 nm laser, 2h) of the single sender protocell resulting in photocleavage
of the F1Q1 gate complex which could be monitored
by an increase in Cy5 fluorescence (Figure D, red). We confirmed successful activation
of the receiver protocells by signal strand A by monitoring an increase
in Alexa546 fluorescence in individual receivers (Figure D, yellow, and Movie S2). To analyze receiver activation dynamics
under the signaling gradient we binned receivers in concentric shells
based on their radial distance from the sender and plotted the average
fluorescence traces (Figure E). Receivers in close proximity to the sender protocell are
activated first and to a higher extent, confirming that the diffusible
signal released from the central sender is consumed by the surrounding
receivers, which therefore limits the activation of receivers at larger
distances from the sender. To further quantify the spatiotemporal
data, we plotted the spatial distribution of the receiver protocells’
activation states at different time points (Figure F). The spatiotemporal data displayed an
activation front stabilized after 100–120 min. This pseudo
steady-state resulted from the diminished signals release from the
sender protocell after 2 h of illumination (Figure C). We defined the characteristic signaling
length scale λ (Supplemental Methods and Figure S5) as the distance at which the receiver activation
has dropped off to 1/e (37%) of its maximum amplitude
at pseudo-steady-state. We determined λ from the image taken
after 2 h of illumination and found a characteristic signaling length
scale λ of approximately 226 μm (Figure G). This value is well in the range of many
natural systems that communicate via soluble factors, i.e., morphogens[52] (40–200 μm), cytokines[9] (30–150 μm), and retinoic acid[19] (300–500 μm).To validate
the experimental observations, we performed 2D reaction-diffusion
(RD) simulations of the sender–receiver population using the
Visual DSD software.[45,53,54] The numerical model was parametrized using the average signal release
rate constant, DSD rate constant, and membrane permeability obtained
in separate experiments (Supporting Information, Supplemental Methods). The obtained activation dynamics and signaling
length-scale (Figure S6) are in agreement
with the experimental results. Collectively, these results establish
that spatially controlled light-induced signal release from an individual
sender protocell results in a distance-dependent activation of surrounding
receivers in agreement with a diffusion-consumption mechanism.
Modulation
of Signaling Range
Intercellular communication
distances established by soluble factors in multicellular populations
are regulated by both internal and external physicochemical factors,
such as signal secretion, diffusion, and consumption rates.[11,13] How each of these determinants modulates the signaling length scale
has remained difficult to analyze due to the intrinsic complexity
of natural sender–receiver systems. Here we employ our synthetic
sender–receiver architecture and quantitatively analyze the
contribution of individual determinants to the signaling length scale.
Specifically, we constructed multimodal sender–receiver populations
through sequential loading of a single sender and multiple (100–150)
receiver protocells. Using this setup, we determined the internal
and external determinants leading to changes in effective signaling
length scale associated with variations in the capacity and rate of
signal consumption, and levels of signal degradation in the environment
(Figure A). To quantify
the influence of the variations, we calculated the signaling length
scale from images taken after 2 h illumination (Supporting Information, Supplemental Methods).
Figure 2
Tuning of the signaling
length scale in light-activated DNA-encoded
sender–receiver spatial systems. (A) Changes in internal factors
such as signal consumption capacity (receiver DNA gate complex concentration)
and consumption rate (receiver membrane permeability) and external
factors such as interprotocellular distance (protocell trap density)
and signal degradation (exonuclease concentration) influence the signaling
length scale (left and center). Plots show typical experimental data
used for the determination of the signaling length scale (right).
Data collected after 2h of signal release from the sender. Scale bars
150 μm. (B–E) Modulation of signaling length scale at t = 2 h for changes in receiver consumption capacity (B),
consumption rate (membrane permeability) (C), protocell trap density
(D), and signal degradation (E). High, medium, and low levels of the
receiver protocell-entrapped DNA gate complex relate to changes in
receiver-encapsulated streptavidin concentrations ([SA]) of 4, 1,
and 0.4 μM, respectively (B). High (202.8 μm min–1) and low (2.16 μm min–1) receiver permeabilities
relate to modifications in the protocell membrane cross-linking density;
[SA] = 1 μM (C). High and low receiver number densities relate
to the use of 90 or 70 microfluidic traps per mm2, respectively;
[SA] = 4 μM (D). High and low levels of signal degradation arise
from the presence of 0.1 and 0.05 unit/μL of exonuclease I,
respectively; [SA] = 1 μM. The control experiment is performed
in the absence of exonuclease I (E). For all experiments, the concentration
of encapsulated streptavidin in the sender protocells was 10 μM.
All experiments were performed in independent triplicates at room
temperature. All the experimental conditions are summarized in Table S2. Data are presented as means ±
SD. A P-value less than 0.05 is considered to be
statistically significant.
Tuning of the signaling
length scale in light-activated DNA-encoded
sender–receiver spatial systems. (A) Changes in internal factors
such as signal consumption capacity (receiver DNA gate complex concentration)
and consumption rate (receiver membrane permeability) and external
factors such as interprotocellular distance (protocell trap density)
and signal degradation (exonuclease concentration) influence the signaling
length scale (left and center). Plots show typical experimental data
used for the determination of the signaling length scale (right).
Data collected after 2h of signal release from the sender. Scale bars
150 μm. (B–E) Modulation of signaling length scale at t = 2 h for changes in receiver consumption capacity (B),
consumption rate (membrane permeability) (C), protocell trap density
(D), and signal degradation (E). High, medium, and low levels of the
receiver protocell-entrapped DNA gate complex relate to changes in
receiver-encapsulated streptavidin concentrations ([SA]) of 4, 1,
and 0.4 μM, respectively (B). High (202.8 μm min–1) and low (2.16 μm min–1) receiver permeabilities
relate to modifications in the protocell membrane cross-linking density;
[SA] = 1 μM (C). High and low receiver number densities relate
to the use of 90 or 70 microfluidic traps per mm2, respectively;
[SA] = 4 μM (D). High and low levels of signal degradation arise
from the presence of 0.1 and 0.05 unit/μL of exonuclease I,
respectively; [SA] = 1 μM. The control experiment is performed
in the absence of exonuclease I (E). For all experiments, the concentration
of encapsulated streptavidin in the sender protocells was 10 μM.
All experiments were performed in independent triplicates at room
temperature. All the experimental conditions are summarized in Table S2. Data are presented as means ±
SD. A P-value less than 0.05 is considered to be
statistically significant.In cellular populations, binding of soluble factors to receptors
on neighboring cells results in consumption of the available signal
and therefore influences the effective signaling range.[11,13,18] In the BIO-PC platform, the consumption
capacity of individual receiver protocells can be varied by changing
the concentration of the encapsulated F2Q2 DNA
gate complex, which depletes the diffusible signal by strand displacement.
We performed the sender–receiver experiments using receiver
protocells with three different DNA gate complex concentrations (Figure S7) and calculated the corresponding signaling
length-scales (Figures B, S5, and S8–S15). In general,
for the 20–40 μm sized receiver protocells used in this
study, the effective signaling length scale ranges between 200 and
500 μm. In agreement with our expectations, increasing the consumption
capacity of individual receiver protocells results in lower effective
communication distances due to a higher local depletion of the soluble
signal. Besides consumption capacity, the consumption rate of a soluble
signal can also modulate the signaling length scale. In multicellular
populations, the consumption rate of a morphogen or cytokine can be
regulated by controlling the rate of endocytosis.[11] Here, we modulate the consumption rate by tuning the membrane
permeability of receiver protocells. We have previously shown that
the permeability (P) of proteinosomes can be tuned using protein-cross-linking
reagents of different length and revealed how the permeability influences
the compartmentalized DSD reaction kinetics.[45] We prepared high-P and low-P receiver protocells (Supporting Information, Supplemental Methods), quantified
their permeability, and confirmed they have approximately similar
binding capacity for biotin-labeled DNA (Figure S16). As expected, the experimentally derived signaling length
scale is higher for low-P receiver protocells (Figures C, S10–S12, and S17–S19) as the soluble signal is consumed at a lower
rate.Because an individual sender is surrounded by multiple
receivers,
the effective signaling distance not only depends on the consumption
rate and consumption capacity of individual receivers but also on
the cumulative signal consumption which can be varied by modulating
the protocell number density in the spatial array.[9] We fabricated microfluidic trapping arrays with two different
densities of protocell traps and determined the effective signaling
range from the experimental data (Figure S20). Our data shows that the signaling length scale increases when
protocell density is decreased (Figures D, S5, S8, S9, and S21–S23). This increasing communication distance can be explained by lower
total signal consumption capacity as the number density of receiver
protocell decreases.Biochemical degradation of diffusible factors
is a key regulatory
mechanism in morphogenesis and can control both the signaling range
and sharpness of the diffusion front.[13,14,55] To mimic signal degradation, we added exonuclease
I (3′ to 5′) to the trapped proteinosomes before initiating
the photocleavage reaction. Exonuclease I selectively degrades the
diffusible signal from its free 3′ end. Control experiments
using proteinosomes containing an encapsulated 3′ fluorescently
labeled ssDNA show that exonuclease is capable of diffusing across
the proteinosome membrane (Figure S24)
resulting in the presence of exonuclease inside and outside the protocells.
However, the encapsulated DNA gate complexes in the sender and receivers
lack a free 3′ end, preventing their degradation (Figure S25). Laser-irradiation of the sender
protocell cleaves the internalized DNA gate complex and yields a diffusible
signal strand with a free 3′ end that is amenable for exonuclease
degradation. Because the 3′ end of the diffusible signal contains
the toehold binding domain required for strand-displacement with the
receiver gate complex, enzymatic degradation strongly inhibits receiver
activation. We performed sender–receiver experiments for two
different concentrations of exonuclease I added to the medium (Figure E) and calculated
the signaling length scale from the experimental data Figures S10–S12 and S26–S31. As
expected, higher concentrations of exonuclease result in decreasing
signaling length scales. Taken together, these findings reveal how
a fully synthetic sender–receiver protocell platform can be
used to systematically study the effect of isolated physicochemical
factors on the diffusive communication range.
Signal Regeneration
In living cells, intercellular
amplification of soluble signaling molecules is a ubiquitous mechanism
employed to direct and control downstream cell fate decisions.[56,57] Here we implement nonenzymatic DNA-based catalytic reaction networks[58] and realize interprotocellular signal amplification
by engineering the sender–receiver architecture into a sender–transceiver
system, where transceiver protocells can be activated by the diffusible
signal but are also capable of regenerating this signal in the presence
of excess fuel strand (Figure A). Similar to the sender–receiver experiments, sender
protocells contain encapsulated DNA gate complex F1Q1. Transceiver protocells contain encapsulated DNA gate complex
F3Q3 where the streptavidin-bound biotinylated
strand F3 is labeled with Alexa546 while strand Q3 is modified with a quencher. Laser irradiation triggers the release
of signal A from the sender protocell, which activates the transceiver
gate complex by displacing Q3. The activated transceiver
gate complex F3A exposes the toehold on the F3 strand, allowing an abundantly present fuel strand to bind F3 and regenerate signal strand A. We prepared a bimodal protocell
population consisting of a single sender and multiple receivers (∼150)
by sequential loading of protocells in the trapping device. Next,
the trapping chamber was filled with fuel strand to a final concentration
of 0.1 μM and the experiment was initiated by laser irradiation
(405 nm, 2 h) of the sender protocell. Comparison of the fluorescent
micrographs obtained in the presence and absence of fuel (Figure B) clearly reveals
transceiver activation at larger distances from the sender in the
presence of the fuel, indicative of successful recycling of the diffusing
signal. To further characterize sender–transceiver protocell
communication, we plotted the transceiver activation dynamics for
increasing distances from the sender (Figure C) and the response time of each transceiver
(Figure D). We observed
significant higher activation of transceivers at short distances from
the sender in the presence of fuel while a significantly higher fraction
of transceivers is activated at larger distances from the sender (Figures S32–S37). Importantly, a control
experiment in which the individual sender protocell was not irradiated
displays low leakage in the presence of fuel (Figure C, black line), which is characteristic for
catalytic DSD systems.[58] We also computed
the characteristic length scale in the presence and absence of the
fuel which reveals a larger signaling range as a result of regeneration
of the soluble signal by fuel-driven DSD cycles (Figure E). Simulations using a 2D
reaction-diffusion model that incorporates the effect of the fuel-driven
signal regeneration confirm this experimental observation (Figure S38). Collectively, these results show
that signal regeneration can be integrated into spatial-controlled
sender–receiver architectures and leads to an increase in the
signaling length scale.
Figure 3
Signal regeneration in a light-activated spatial
DNA-encoded sender–transceiver
system. (A) The encapsulated sender gate complex is identical to that
used for the sender–receiver system. Upon laser irradiation,
signal strand A is released to generate Cy5 fluorescence and activates
the surrounding transceiver protocells by displacement of a quencher
strand (Q3) from encapsulated gate complex F3Q3 to produce Alexa546 fluorescence and consumption of
strand A. After the initial response, a nonenzymatic DNA catalytic
reaction recycles the signal strand A by consuming a fuel strand.
(B) Confocal micrographs of one sender and multiple transceivers (FITC-labeled
proteinosome membrane, green) recorded at t = 0 (top
left) showing minimal Cy5 and Alexa546 fluorescence before signal
activation (top right) in the presence of a fuel strand; corresponding
images 60 min after light-induced signal generation show increases
in Cy5 fluorescence in the sender (red, release of signal A) and Alexa546
fluorescence (yellow, activation of F3Q3) in
the surrounding transceivers (bottom left). The control experiment
was performed without fuel and shows lower levels of Alexa546 fluorescence
after 60 min due to the absence of signal regeneration (bottom right).
(C) Binning of transceiver protocell activation (left) and corresponding
time traces within different concentric shells for changes in the
concentration of transceiver DNA gate activation (right). Shell 1
(dark red) is closest to the sender. The upper limit of the distance
from the receiver protocells to the sender protocell of each shell
is listed next to the color bars. To analyze spontaneous triggering
of the transceiver gates by the fuel, the mean concentration of activated
transceiver gate without signal release (i.e., no laser irradiation)
is also plotted (black line). (D) Spatial barcode image of response
time of transceiver protocells. The response time is defined as the
time in which a transceiver reaches 50% of its final activated concentration;
short “on” time (red), long “on” time
(blue). To remove background noise, any protocells with an absolute
increase less than 20 RFU are excluded and labeled with gray (n.d.).
(E) Calculated signaling length-scales in a sender–transceiver
system. Data are presented as means ± SD. A P-value less than 0.05 is considered to be statistically significant.
Sender and transceiver protocells were prepared using 10 and 1 μM
streptavidin, respectively. The concentration of fuel was 0.1 μM.
All experiments were performed in independent triplicates at room
temperature. Scale bars, 150 μm.
Signal regeneration in a light-activated spatial
DNA-encoded sender–transceiver
system. (A) The encapsulated sender gate complex is identical to that
used for the sender–receiver system. Upon laser irradiation,
signal strand A is released to generate Cy5 fluorescence and activates
the surrounding transceiver protocells by displacement of a quencher
strand (Q3) from encapsulated gate complex F3Q3 to produce Alexa546 fluorescence and consumption of
strand A. After the initial response, a nonenzymatic DNA catalytic
reaction recycles the signal strand A by consuming a fuel strand.
(B) Confocal micrographs of one sender and multiple transceivers (FITC-labeled
proteinosome membrane, green) recorded at t = 0 (top
left) showing minimal Cy5 and Alexa546 fluorescence before signal
activation (top right) in the presence of a fuel strand; corresponding
images 60 min after light-induced signal generation show increases
in Cy5 fluorescence in the sender (red, release of signal A) and Alexa546
fluorescence (yellow, activation of F3Q3) in
the surrounding transceivers (bottom left). The control experiment
was performed without fuel and shows lower levels of Alexa546 fluorescence
after 60 min due to the absence of signal regeneration (bottom right).
(C) Binning of transceiver protocell activation (left) and corresponding
time traces within different concentric shells for changes in the
concentration of transceiver DNA gate activation (right). Shell 1
(dark red) is closest to the sender. The upper limit of the distance
from the receiver protocells to the sender protocell of each shell
is listed next to the color bars. To analyze spontaneous triggering
of the transceiver gates by the fuel, the mean concentration of activated
transceiver gate without signal release (i.e., no laser irradiation)
is also plotted (black line). (D) Spatial barcode image of response
time of transceiver protocells. The response time is defined as the
time in which a transceiver reaches 50% of its final activated concentration;
short “on” time (red), long “on” time
(blue). To remove background noise, any protocells with an absolute
increase less than 20 RFU are excluded and labeled with gray (n.d.).
(E) Calculated signaling length-scales in a sender–transceiver
system. Data are presented as means ± SD. A P-value less than 0.05 is considered to be statistically significant.
Sender and transceiver protocells were prepared using 10 and 1 μM
streptavidin, respectively. The concentration of fuel was 0.1 μM.
All experiments were performed in independent triplicates at room
temperature. Scale bars, 150 μm.
Spatial Integration of Diffusible Signals by Boolean Receivers
Spatial integration of chemical signals by Boolean operations is
essential to generate collective behavior in multicellular populations
as exemplified by the immune and nervous systems.[59,60] Although Boolean reaction-diffusion systems have been implemented
using the Belousov–Zhabotinsky reaction,[61−65] a versatile and tunable platform based on biomolecular
reactions is currently lacking. We previously showed the possibilities
of implementing Boolean AND logic using BIO-PC, which relied on the
sequential hybridization of two different DNA signals in DSD circuitry.[45] However, this configuration does not allow distinct
signal gradients to be integrated spatially, since the AND gate localized
in the receiver protocells will sequester one of the signals in the
absence of the other. Here, we reveal how the BIO-PC platform can
be adapted to integrate nonidentical gradients by localized AND operations
based on a cooperative DSD mechanism. Using a sequential loading procedure,
we implemented a three-population configuration consisting of two
nonidentical sender protocells embedded in a high density of receivers
that implement Boolean AND logic (Figure A). The two senders contain gate complexes
F4Q4 and F5Q5, respectively,
which upon simultaneous laser illumination (405 nm, 1.8 h) secrete
two distinct Cy3-labeled signal strands A2 and A3 as monitored by the decrease in Cy3 fluorescence of the sender protocells
(Figure B yellow).
Receiver protocells contain an encapsulated DNA gate complex which
is activated by a cooperative hybridization mechanism[66] (Figure S39) where both A2 and A3 need to be simultaneously present to release
quencher labeled strand Q6, resulting in an increase in
Quasar 670 fluorescence (Figure B, red). We analyzed spatiotemporal AND-gate receiver
activation by binning receiver protocells into shells based on the
maximum of the two distances to the senders and calculated the average
fluorescence per bin over time (Figure C and Figure S40). The experimental
curves reveal that activation of the receivers is initiated at positions
equidistant to the two senders, in agreement with AND-type logic.
Our observations are also supported by 2D RD simulations using realistic
parameters (Figure S41). Furthermore, we
plotted the response time of each receiver as a function of the distance
to both senders and find the lowest response time for receivers at
equidistant position of both senders (Figure D). Together, these results indicate that
receiver protocells are activated by two nonidentical signaling gradients
of distributed spatial origins and demonstrate Boolean AND logic.
Figure 4
Spatial
integration of nonidentical signals by 2D-arrayed AND-gate
protocells. (A) Two fluorescent sender protocells (1 and 2) containing
internalized gate complexes F4Q4 or F5Q5, respectively, are embedded in a high number density
of nonfluorescent AND-gate receivers. Signal release from sender protocells
is triggered by laser irradiation resulting in photocleavage of Q4 and Q5, concomitant dissociation of the cleaved
parts, A2+B and A3+B, and loss of Cy3 fluorescence.
The Cy3-labeled dissociated strand A2 and nonfluorescent
strand A3 activate Quasar 670-quenched receiver protocells
containing an encapsulated AND gate (F6Q6) through
cooperative hybridization (64) to produce a Cy3/Quasar670 fluorescence
output. (B) Confocal micrographs of two sender protocells (1 and 2)
and multiple AND gate receivers recorded at t = 0
(top) showing Cy3 fluorescence in the spatially separated transmitters.
Light-induced activation leads to a reduction in Cy3 fluorescence
(yellow) in the senders, and progressive increase in Quasar 670 fluorescence
(red) associated with activation of receiver protocells. (C) Binning
method used to analyze spatiotemporal activation of receiver protocells.
Protocells are binned based on the maximum of the two distances to
the senders, which yields bins with outer bounds that are the intersection
of the equivalent bounds of single sender systems, as illustrated
by the black lines (left). Corresponding time traces of AND gate receiver
activation within different bins. Shell 1 (dark red) is closest to
the two senders. The maximum of the two distances from the receiver
protocells to the sender protocell of each shell is listed next to
the color bars. (D) Response time of individual Boolean receivers
upon simultaneous laser irradiation of two senders for 1.8 h plotted
as a function of their distance to each of the two senders. The response
time is defined as the time taken for an individual receiver to reach
50% of its final activated concentration. Two senders are marked as
1 and 2 in green. To remove background noise, any protocells with
an absolute increase less than 1 RFU are excluded and labeled in hollow
circles. (E) Response time of individual Boolean receivers upon sequential
laser irradiation showing spatial bias in activation of receiver protocells.
Sender 1 is irradiated for 18 min, followed by irradiation of both
senders for 1.5 h. Sender protocells and receiver protocells were
prepared using 30 and 1 μM streptavidin, respectively. Scale
bars are 150 μm. Experiments were performed at room temperature.
Spatial
integration of nonidentical signals by 2D-arrayed AND-gate
protocells. (A) Two fluorescent sender protocells (1 and 2) containing
internalized gate complexes F4Q4 or F5Q5, respectively, are embedded in a high number density
of nonfluorescent AND-gate receivers. Signal release from sender protocells
is triggered by laser irradiation resulting in photocleavage of Q4 and Q5, concomitant dissociation of the cleaved
parts, A2+B and A3+B, and loss of Cy3 fluorescence.
The Cy3-labeled dissociated strand A2 and nonfluorescent
strand A3 activate Quasar 670-quenched receiver protocells
containing an encapsulated AND gate (F6Q6) through
cooperative hybridization (64) to produce a Cy3/Quasar670 fluorescence
output. (B) Confocal micrographs of two sender protocells (1 and 2)
and multiple AND gate receivers recorded at t = 0
(top) showing Cy3 fluorescence in the spatially separated transmitters.
Light-induced activation leads to a reduction in Cy3 fluorescence
(yellow) in the senders, and progressive increase in Quasar 670 fluorescence
(red) associated with activation of receiver protocells. (C) Binning
method used to analyze spatiotemporal activation of receiver protocells.
Protocells are binned based on the maximum of the two distances to
the senders, which yields bins with outer bounds that are the intersection
of the equivalent bounds of single sender systems, as illustrated
by the black lines (left). Corresponding time traces of AND gate receiver
activation within different bins. Shell 1 (dark red) is closest to
the two senders. The maximum of the two distances from the receiver
protocells to the sender protocell of each shell is listed next to
the color bars. (D) Response time of individual Boolean receivers
upon simultaneous laser irradiation of two senders for 1.8 h plotted
as a function of their distance to each of the two senders. The response
time is defined as the time taken for an individual receiver to reach
50% of its final activated concentration. Two senders are marked as
1 and 2 in green. To remove background noise, any protocells with
an absolute increase less than 1 RFU are excluded and labeled in hollow
circles. (E) Response time of individual Boolean receivers upon sequential
laser irradiation showing spatial bias in activation of receiver protocells.
Sender 1 is irradiated for 18 min, followed by irradiation of both
senders for 1.5 h. Sender protocells and receiver protocells were
prepared using 30 and 1 μM streptavidin, respectively. Scale
bars are 150 μm. Experiments were performed at room temperature.Because receiver protocells are activated by gradients
from both
senders, we wondered if we could spatially control initiation of receiver
activation by sequential laser irradiation of the two senders. This
would result in the development of a signal gradient from one of the
two senders before the other gradient is established. Due to the reversible
nature of the cooperative DSD mechanism,[66] signal strands from one sender that bind to the AND-gate are preferentially
released in the absence of the other signal, preventing signal consumption
by receivers. We first irradiated sender 1 for 18 min, followed by
exposure of both senders for 1.5 h, and calculated the response time
for each receiver (Figures E and S42). We observe a skewed
activation pattern where receiver activation is initiated in receivers
in close proximity to sender 2, in agreement with the presence of
spatial bias in the established signal gradients. Together, these
results show that a population of protocells could be programmed to
integrate two nonidentical cues and perform spatially encoded Boolean
operations using encapsulated DSD based reactions.
Conclusions
Cellular communication by soluble factors allows populations of
cells to coordinate their behavior. Secretion of diffusible messengers
is often spatially localized resulting in local gradients near sender
cells and the emergence of spatial niches characterized by a high
concentration of a specific signal.[9] For
nonmigrating, micrometer-sized cells, the characteristic signaling
length scale of these gradients, i.e., the distance
over which diffusive communication persists, appears to be around
50–500 μm[9,19,52] and can be dynamically adjusted by competition between diffusion
and signal consumption by receiver cells[9] and active signal degradation.[15] In this
work, we demonstrate a fully synthetic soft matter system based on
semipermeable microcompartments that communicate via short DNA strands
under a light-induced local signaling gradient arising from a single
sender protocell. We prepared multimodal protocell arrays consisting
of a single sender protocell and a polydisperse receiver population
using a microfluidic trapping device and systematically quantified
how individual parameters control the signaling length scale typically
between 100 and 700 μm. The simplicity of the system allows
variation of the consumption capacity and consumption rate of receiver
protocells and introduction of active signal regeneration and degradation
pathways. As a further showcase of our cytomimetic technology, we
revealed how two local signaling gradients can be spatially integrated
by employing receiver protocells containing Boolean AND gates.As an artificial communication platform designed for simplicity
and tunability, the adapted BIO-PC has its limitations. Living cells
can translate extracellular signals into intracellular signals and
perform subsequent processing of these signals through highly complex
interaction networks of nodes, modules, and pathways.[67] In contrast, there is no clear distinction between extracellular
and intracellular signals in our system, which does not allow coordination
of responses via combinatorial signaling. Additional research is needed
to construct more complicated DNA-based networks for signal reception
and processing.[68−71] Second, negative feedback control is often employed in multicellular
organisms to regulate intercellular communication and guarantees precision,
robustness, and versatility.[57] Because
our system is based on enzyme-free DNA circuity, it is difficult to
realize negative feedback control. Negative feedback loops can be
implemented in BIO-PC using enzyme-assisted DNA circuits, which could
be utilized to construct protocell communities with much spatiotemporal
behavior.[72] Moreover, in nature, sender
cells consume a fraction of the signal they produced via an autocrine
signaling loop.[73] An artificial autocrine
pathway could be created in our system by colocalization of signal
and receiver gates inside the protocell or modification of receiver
gates onto the protocellular membrane.For future research,
we envision that the BIO-PC platform could
form the basis for implementing a deterministic cellular automaton
based on chemical reaction-diffusion networks which would be able
to perform universal computation and permanently store the chemical
state of each protocell.[74] In order to
construct a DNA-based cellular automaton, additional DNA-based Boolean
operations such as NOR, XOR, and NAND gates, which have been shown
to work in bulk,[70] need to be introduced
into the protocell platform. Second, the position of each protocell
should be independently addressable, which could be achieved using
either acoustic[75] or magnetic[76] driven manipulation. The development of minimally
synthetic cellular communities with programmable communication protocols
is a key goal in bottom-up synthetic biology[77] and has the potential to inform the design rules of collective decision
making in multicellular populations.
Methods
Streptavidin-containing proteinosomes were prepared similarly to
our previously reported procedures.[45] All
DNA sequences are listed in Table S3. DNA
oligonucleotides were purchased from Integrated DNA Technologies and
Biosearch Technologies. A two-layer PDMS microfluidic chip was produced
using standard soft lithographic techniques.[78] To perform an experiment, protocells were first suspended in the
buffer solution and delivered to the trapping chamber in the microfluidic
device by a compressed air line. Photocleavage of gate complexes inside
a sender protocell was triggered by a 405 nm laser from a confocal
laser scanning microscope (Leica SP8). The confocal microscope was
also used to measure fluorescence of protocells in the trap array.
Data analysis and 2D reaction-diffusion simulation were performed
using Matlab and Vissual DSD. Full details are given in the Supporting Information.
Authors: Albert Gidon; Timothy Adam Zolnik; Pawel Fidzinski; Felix Bolduan; Athanasia Papoutsi; Panayiota Poirazi; Martin Holtkamp; Imre Vida; Matthew Evan Larkum Journal: Science Date: 2020-01-03 Impact factor: 47.728
Authors: Ignacio Gispert; James W Hindley; Colin P Pilkington; Hansa Shree; Laura M C Barter; Oscar Ces; Yuval Elani Journal: Proc Natl Acad Sci U S A Date: 2022-10-12 Impact factor: 12.779
Authors: Shuo Yang; Alex Joesaar; Bas W A Bögels; Stephen Mann; Tom F A de Greef Journal: Angew Chem Int Ed Engl Date: 2022-04-26 Impact factor: 16.823
Authors: David T Gonzales; Naresh Yandrapalli; Tom Robinson; Christoph Zechner; T-Y Dora Tang Journal: ACS Synth Biol Date: 2022-01-04 Impact factor: 5.110