Modeling of bioprocess pre-stages for optimization of perfusion profiles and increased process understanding.

Improving bioprocess efficiency is important to reduce the current costs of biologics on the market, bring them faster to the market, and to improve the environmental footprint. The process intensification efforts were historically focused on the main stage, while intensification of pre-stages has started to gain attention only in the past decade. Performing bioprocess pre-stages in the perfusion mode is one of the most efficient options to achieve higher viable cell densities over traditional batch methods. While the perfusion-mode operation allows to reach higher viable cell densities, it also consumes large amount of medium, making it cost-intensive. The change of perfusion rate during a process (perfusion profile) determines how much medium is consumed, thereby running a process in optimal conditions is key to reduce medium consumption. However, the selection of the perfusion profile is often made empirically, without full understanding of bioprocess dynamics. This fact is hindering potential process improvements and means for cost reduction. In this study, we propose a process modeling approach to identify the optimal perfusion profile during bioprocess pre-stages. The developed process model was used internally during process development. We could reduce perfused medium volume by 25%-45% (project-dependent), while keeping the difference in the final cell within 5%-10% compared to the original settings. Additionally, the model helps to reduce the experimental workload by 30%-70% and to predict an optimal perfusion profile when process conditions need to be changed (e.g., higher seeding density, change of operating mode from batch to perfusion, etc.). This study demonstrates the potential of process modeling as a powerful tool for optimizing bioprocess pre-stages and thereby guiding process development, improving overall bioprocess efficiency, and reducing operational costs, while strongly reducing the need for wet-lab experiments.

Reversible Photoswitchable Inhibitors Generate Ultrasensitivity in Out-of-Equilibrium Enzymatic Reactions.

Ultrasensitivity is a ubiquitous emergent property of biochemical reaction networks. The design and construction of synthetic reaction networks exhibiting ultrasensitivity has been challenging, but would greatly expand the potential properties of life-like materials. Herein, we exploit a general and modular strategy to reversibly regulate the activity of enzymes using light and show how ultrasensitivity arises in simple out-of-equilibrium enzymatic systems upon incorporation of reversible photoswitchable inhibitors (PIs). Utilizing a chromophore/warhead strategy, PIs of the protease α-chymotrypsin were synthesized, which led to the discovery of inhibitors with large differences in inhibition constants (Ki) for the different photoisomers. A microfluidic flow setup was used to study enzymatic reactions under out-of-equilibrium conditions by continuous addition and removal of reagents. Upon irradiation of the continuously stirred tank reactor with different light pulse sequences, i.e., varying the pulse duration or frequency of UV and blue light irradiation, reversible switching between photoisomers resulted in ultrasensitive responses in enzymatic activity as well as frequency filtering of input signals. This general and modular strategy enables reversible and tunable control over the kinetic rates of individual enzyme-catalyzed reactions and makes a programmable linkage of enzymes to a wide range of network topologies feasible.

Dynamic Environments as a Tool to Preserve Desired Output in a Chemical Reaction Network.

Current efforts to design functional molecular systems have overlooked the importance of coupling out-of-equilibrium behaviour with changes in the environment. Here, the authors use an oscillating reaction network and demonstrate that the application of environmental forcing, in the form of periodic changes in temperature and in the inflow of the concentration of one of the network components, removes the dependency of the periodicity of this network on temperature or flow rates and enforces a stable periodicity across a wide range of conditions. Coupling a system to a dynamic environment can thus be used as a simple tool to regulate the output of a network. In addition, the authors show that coupling can also induce an increase in behavioural complexity to include quasi-periodic oscillations.

Modular Design of Small Enzymatic Reaction Networks Based on Reversible and Cleavable Inhibitors.

Systems chemistry aims to mimic the functional behavior of living systems by constructing chemical reaction networks with well-defined dynamic properties. Enzymes can play a key role in such networks, but there is currently no general and scalable route to the design and construction of enzymatic reaction networks. Here, we introduce reversible, cleavable peptide inhibitors that can link proteolytic enzymatic activity into simple network motifs. As a proof-of-principle, we show auto-activation topologies producing sigmoidal responses in enzymatic activity, explore cross-talk in minimal systems, design a simple enzymatic cascade, and introduce non-inhibiting phosphorylated peptides that can be activated using a phosphatase.

Bottom-Up Construction of an Adaptive Enzymatic Reaction Network.

The reproduction of emergent behaviors in nature using reaction networks is an important objective in synthetic biology and systems chemistry. Herein, the first experimental realization of an enzymatic reaction network capable of an adaptive response is reported. The design is based on the dual activity of trypsin, which activates chymotrypsin while at the same time generating a fluorescent output from a fluorogenic substrate. Once activated, chymotrypsin counteracts the trypsin output by competing for the fluorogenic substrate and producing a non-fluorescent output. It is demonstrated that this network produces a transient fluorescent output under out-of-equilibrium conditions while the input signal persists. Importantly, in agreement with mathematical simulations, we show that optimization of the pulse-like response is an inherent trade-off between maximum amplitude and lowest residual fluorescence.

Photochemical Control over Oscillations in Chemical Reaction Networks.

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.

Molecular Engineering of Robustness and Resilience in Enzymatic Reaction Networks.

Living systems rely on complex networks of chemical reactions to control the concentrations of molecules in space and time. Despite the enormous complexity in biological networks, it is possible to identify network motifs that lead to functional outputs such as bistability or oscillations. One of the greatest challenges in chemistry is the creation of such functionality from chemical reactions. A key limitation is our lack of understanding of how molecular structure impacts on the dynamics of chemical reaction networks, preventing the design of networks that are robust (i.e., function in a large parameter space) and resilient (i.e., reach their out-of-equilibrium function rapidly). Here we demonstrate that reaction rates of individual reactions in the network can control the dynamics by which the system reaches limit cycle oscillations, thereby gaining information on the key parameters that govern the dynamics of these networks. We envision that these principles will be incorporated into the design of network motifs, enabling chemists to develop "molecular software" to create functional behavior in chemical systems.