Systems chemistry aims to emulate the functional behavior observed in living systems by constructing chemical reaction networks (CRNs) with well-defined dynamic properties. Future expansion of the complexity of these systems would require external control to tune behavior and temporal organization of such CRNs. In this work, we design and implement a photolabile probe, which upon irradiation strengthens the negative feedback loop of a CRN that produces oscillations of trypsin under out-of-equilibrium conditions. By changing the timing and duration of irradiation, we can tailor the temporal response of the network.
Systems chemistry aims to emulate the functional behavior observed in living systems by constructing chemical reaction networks (CRNs) with well-defined dynamic properties. Future expansion of the complexity of these systems would require external control to tune behavior and temporal organization of such CRNs. In this work, we design and implement a photolabile probe, which upon irradiation strengthens the negative feedback loop of a CRN that produces oscillations of trypsin under out-of-equilibrium conditions. By changing the timing and duration of irradiation, we can tailor the temporal response of the network.
A discipline
of “systems
chemistry” is developing, which aims to capture the complexity
observed in natural systems within a synthetic chemical framework.[1−3] In recent years, significant progress has been made, including the
design of oscillating reaction networks,[4,5] the formation
of transient gels[6] and vesicles,[7] self-replicating systems,[8,9] DNA-based
controllers and oscillators,[10,11] self-organizing ensembles
of nanoparticles,[12] and catalytic reactions
with chemo-mechanical feedback.[13] A major
challenge for systems chemistry is to translate the design principles
of living systems, based on feedback loops and reaction networks,
into functional synthetic equivalents.We are inspired by the
regularly recurring motifs of coupled feedback
loops generating much of the functional behavior in biological networks.[14,15] We recently reported an oscillating out-of-equilibrium CRN, consisting
of one positive feedback loop (the autocatalytic production of enzyme
trypsin (Tr) from trypsinogen (Tg)) and one negative feedback loop
(Figure a).[5]Figure a gives a schematic overview of the processes that dominate
during different stages of the oscillation. The negative feedback
loop starts with the activation of a pro-inhibitor (Pro-I), by Tr,
into an intermediate inhibitor that produces active inhibitor of Tr
by the action of the enzyme aminopeptidase (Ap). The two-step negative
feedback loop produces a delay in Tr inhibition, which is a key requirement
for producing oscillations in flow conditions.[14] We can tailor the system-level properties of these networks
(i.e., robustness and resilience of the functional output) by changing
the precise structure of the small molecules.[16,17] However, incorporation of simple designs into more complex out-of-equilibrium
networks will make it ever more difficult to ensure that each reaction
in the network has a suitable reaction rate. Thus, we will require
a method to regulate individual rates in the network, without disrupting
others.
Figure 1
Introduction of a control node. (a) Schematic representation of
the out-of-equilibrium system and the key processes during oscillations.
(b) Details of the original network (light blue box) and the photochemical
control node (orange box).
Introduction of a control node. (a) Schematic representation of
the out-of-equilibrium system and the key processes during oscillations.
(b) Details of the original network (light blue box) and the photochemical
control node (orange box).Light is an attractive external control element, as it can
selectively
and rapidly change reactions rates (in contrast to changes in concentration,
solvent quality, or temperature). Research on the well-known BZ (Belousov–Zhabotinsky)
system has shown that light can be used to alter frequency and phase
of the oscillations[18] and induce formation
of specific patterns.[19]Here, we
demonstrate photochemical regulation of an oscillating
enzymatic reaction network. In our design, the concentration of active
trypsin (Tr) is expected to fully control the output of the network.
In order to change the level of active [Tr] instantaneously, external
regulation is obtained via a photolabile inhibitor (Figure b). Upon irradiation with light
at 380 nm, the active inhibitor concentration is increased, strengthening
the final step in the negative feedback. We will demonstrate how light
can be used to induce delay, perturb or entrain oscillations, and
synchronize oscillations in separate reactors.The photolabile
inhibitor (Photo-I) consists of an inhibitor moiety
coupled to a well-known methyl-6-nitroveratryloxycarbonyl (MeNVOC)
photoprotection group,[20,21] further functionalized with poly
ethylene glycol tails (PEG) to increase water solubility. The synthesis
of Photo-I was completed in 5 steps; full experimental details and
characterization can be found in the Supporting Information S2. Before introducing the Photo-I into the network,
we studied the cleavage reaction as a function of UV irradiation.
We first verified that Tr remains stable upon irradiation (Supporting Information S3.5). Next, we determined
the apparent rate constant of the cleavage reaction, and found a cleavage
rate constant of 33 h–1. In comparison to the typical
time scales of our oscillations (periods ∼ 5 h), active inhibitor
formation from the Photo-I can be considered an instantaneous process.
Furthermore, the inhibition by the uncleaved photolabile inhibitor
(kinhPhoto-I = 1.4 mM–1 h–1) is roughly 40 times slower in comparison with inhibition by active
inhibitor (kinhI = 52.7 mM–1 h–1). The apparent inhibition rate constant of the uncleaved photoinhibitor
is similar to other background inhibition reactions in the network
(Supporting Information S3.4), and can
therefore be treated as a background reaction. See Supporting Information S3 for full details on kinetic and
spectral properties of Photo-I, including the photocleavage rate,
background inhibition, background hydrolysis of the sulfonyl fluoride
group, and absorbance spectra.Simulations are required to establish
the starting concentrations
of Tg, Tr, and small molecules, as well as suitable flow rates and
the importance of timing of irradiation. Therefore, we added the kinetic
parameters of the photochemical production of inhibitor to the set
of differential equations in MATLAB (see Supporting Information S4) that we previously used to simulate the dynamics
of the network.[5] We simulated the response
of the system to different concentrations of the Photo-I, as well
as the duration and the precise timing of the irradiation. Figure a shows the simulated
response of the network upon three min irradiation pulses at different
phases (denoted here in radians from 0 to 2π) of the oscillation.
We note that only upon irradiation during the rise in Tr concentration
(around 1.66π; Figure a, iv), we see a marked damping of the amplitude followed
by a slow recovery in the oscillations. In all other cases, the effect
of a short pulse is quite similar and results mostly in a small delay.
A closer look at irradiation around 1.66π (Figure b) shows that the system is
rather sensitive to the precise timing of irradiation, as the sustained
oscillations recover differently from perturbations at 1.50π
and 1.66π.
Figure 2
Modeling of a short single irradiation pulse (a) irradiation
for
3 min at different phases of oscillations: 0, 0.24π, 1π,
1.66π, solid lines depict simulations with irradiation and dashed
gray lines without irradiation, orange stars indicate a time point
of irradiation. (b) Zoom with irradiations at 1.50π and 1.66π
for different times. The conditions used for simulations: [Tg]0 = 167 μM, [Pro-I] 0 = 1.5 mM, [Ap]0 = 0.28 U/mL, [Photo-I]0 = 100 μM, [Tr]0 = 0.2 μM, kf = 0.37 h–1.
Modeling of a short single irradiation pulse (a) irradiation
for
3 min at different phases of oscillations: 0, 0.24π, 1π,
1.66π, solid lines depict simulations with irradiation and dashed
gray lines without irradiation, orange stars indicate a time point
of irradiation. (b) Zoom with irradiations at 1.50π and 1.66π
for different times. The conditions used for simulations: [Tg]0 = 167 μM, [Pro-I] 0 = 1.5 mM, [Ap]0 = 0.28 U/mL, [Photo-I]0 = 100 μM, [Tr]0 = 0.2 μM, kf = 0.37 h–1.First, we carried out a preliminary
test of the photochemical switching
of the inhibitor in the full network. The full network was studied
experimentally in a flow reactor fed by four different syringes with
Tg, Tr, Ap, combined ProInh and Photo-I. A computer-controlled circuit
with three LEDs placed around the flow reactor was used to control
length and timing of irradiations. The outflow of the reactor was
coupled to a microfluidic chip that served as an online detection
system where active [Tr] was quantified in flow by a fluorogenic assay
based on benzoyl-l-arginine-7-amido-4-methylcoumarin (see Supporting Information S5 for details). As shown
in Figure a, the network
shows sustained oscillations without UV exposure, and complete inhibition
of Tr during continuous irradiation of the flow reactor.
Figure 3
Dependency on time of irradiation. Three separate experiments
performed
with identical starting conditions, namely 1.4 mM Pro-I, 0.05 mM Photo-I,
0.34 U/mL Ap, kf = 0.34 h–1. Irradiation pulse was 3 min. The orange stars depict time of irradiation.
Next,
we confirmed the effect observed in simulations by performing
two experiments with exactly the same starting conditions and irradiated
for 3 min at different phases of oscillation. Figure b shows an overlay
of two irradiated experiments in comparison with nonirradiated oscillations.
Although there are some fluctuations in the amplitude, we observed
that irradiating the reactor during the initial rise in trypsin concentration,
yielded a stronger perturbation, and a similar slow recovery of the
amplitude as observed in the simulations shown in Figure b. Qualitatively, the phase
dependence can be explained by considering the amount of active Tr
present in the system (see also Figure a). When no active Tr is present, the formation of
additional inhibitor will not have much impact. Similarly, when the
oscillation is past its peak, the negative feedback loop has already
started to outcompete the autocatalytic production of Tr, and hence
the impact of additional inhibitor will be small. Therefore, the perturbation
of the system will be largest during the (initial) rise in [Tr] (i.e.,
during the start of the autocatalytic positive feedback loop). A detailed,
experimental study into the underlying mechanisms of the sensitivity
of the system to the precise timing of irradiation is beyond the scope
of this work.Dependency on time of irradiation. Three separate experiments
performed
with identical starting conditions, namely 1.4 mM Pro-I, 0.05 mM Photo-I,
0.34 U/mL Ap, kf = 0.34 h–1. Irradiation pulse was 3 min. The orange stars depict time of irradiation.In a next experiment, we studied
the effect of irradiation on a
network that operated outside the regime of sustained oscillations.
External pulsing with light might “rescue” the functionality
of the system. For example, it is possible to entrain a system that
is in a regime of damped oscillations, by a series of irradiation
pulses, to produce a forced oscillating system (Figure ). Simulations indicate (see Supporting Information S4.2) that irradiation
during the rise in Inh oscillations, which are shifted by 0.5π
phase from Tr oscillations, is most suitable if entrainment into sustained
oscillations are desired. For the damped oscillations shown in Figure , there is insufficient
active inhibitor to bring [Tr] back to baseline levels, leading to
a steady state [Tr] of ∼1.5 μM. Upon each irradiation,
the additional active inhibitor lowers the active [Tr] to baseline
levels, and subsequently the autocatalytic, positive feedback loop
restarts. Remarkably, even after the irradiation pulses have terminated,
the system is able to oscillate for some time more, before eventually
reaching a damped state.
Figure 4
Demonstration of entrainment of oscillations.
Experiment showing
entrainment of damped oscillations by a series of 10 min irradiations.
Demonstration of entrainment of oscillations.
Experiment showing
entrainment of damped oscillations by a series of 10 min irradiations.We have demonstrated how we can
use light to modulate the output
of the network. As explained earlier, future work will show the integration
of multiple networks. To demonstrate how light-induced inhibition
of Tr can be used in a control systems engineering approach in coupled
reaction networks, we ran two oscillating networks (containing Photo-I)
in separate reactors and then combined the outflow of the reactors
in a Y-junction prior to analyzing the functional output of the combined
set (Figure a). In Figure b, we started the
two oscillating reactions with a delay of 3 h, leading to a significant
phase difference between the two reactors. The first part of Figure shows the oscillations
of both reactors combined, and one can clearly distinguish peaks from
both oscillating reactors (reactor started first depicted as the solid
blue line and second reactor as the dashed red line). By irradiating
both reactors for 45 min, we flood both networks with active inhibitor
and thus bring the system back to a state where the concentration
of active Tr is minimal. Subsequently, both reactors “restart”
with the positive feedback loop initiating the cycle, synchronizing
the two reactors and producing a single oscillation in the combined
output.
Figure 5
Phasing of two coupled oscillators. (a) Schematic representation
of the experimental setup, (b) phasing of two oscillators by simultaneous
irradiation of both reactor for 45 min.
Phasing of two coupled oscillators. (a) Schematic representation
of the experimental setup, (b) phasing of two oscillators by simultaneous
irradiation of both reactor for 45 min.In summary, we have shown how a light-induced local perturbation
of the network (i.e., we only affect concentration of a single component)
can be used to gain external influence over its out-of-equilibrium
function. Experimental realization of the photochemical control over
the phase and amplitude of the oscillations shows strong similarity
with simulations. As a first demonstration, we have shown how we can
synchronize multiple oscillators, a useful feature for more integrated
systems where the timing of different modules needs to be controlled.
Our concept is general and we envision applications to other CRNs,
whether they are based on small molecules,[4] synthetic gene networks,[22] or DNA PEN
toolbox.[23] We have also observed subtle
changes in the response of the network to short exposures to light
at different phases of the oscillation. These results indicate that
we might be able to study the dynamics of the network (robustness,
resilience) using photocleavage of Photo-I as a probe.
Authors: Ximin He; Michael Aizenberg; Olga Kuksenok; Lauren D Zarzar; Ankita Shastri; Anna C Balazs; Joanna Aizenberg Journal: Nature Date: 2012-07-11 Impact factor: 49.962
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