Quantitative Online Monitoring of an Immobilized Enzymatic Network by Ion Mobility-Mass Spectrometry.

The forward design of in vitro enzymatic reaction networks (ERNs) requires a detailed analysis of network kinetics and potentially hidden interactions between the substrates and enzymes. Although flow chemistry allows for a systematic exploration of how the networks adapt to continuously changing conditions, the analysis of the reaction products is often a bottleneck. Here, we report on the interface between a continuous stirred-tank reactor, in which an immobilized enzymatic network made of 12 enzymes is compartmentalized, and an ion mobility-mass spectrometer. Feeding uniformly 13C-labeled inputs to the enzymatic network generates all isotopically labeled reaction intermediates and products, which are individually detected by ion mobility-mass spectrometry (IMS-MS) based on their mass-to-charge ratios and inverse ion mobilities. The metabolic flux can be continuously and quantitatively monitored by diluting the ERN output with nonlabeled standards of known concentrations. The real-time quantitative data obtained by IMS-MS are then harnessed to train a model of network kinetics, which proves sufficiently predictive to control the ERN output after a single optimally designed experiment. The high resolution of the time-course data provided by this approach is an important stepping stone to design and control sizable and intricate ERNs.

How Droplets Can Accelerate Reactions─Coacervate Protocells as Catalytic Microcompartments.

ConspectusCoacervates are droplets formed by liquid-liquid phase separation (LLPS) and are often used as model protocells-primitive cell-like compartments that could have aided the emergence of life. Their continued presence as membraneless organelles in modern cells gives further credit to their relevance. The local physicochemical environment inside coacervates is distinctly different from the surrounding dilute solution and offers an interesting microenvironment for prebiotic reactions. Coacervates can selectively take up reactants and enhance their effective concentration, stabilize products, destabilize reactants and lower transition states, and can therefore play a similar role as micellar catalysts in providing rate enhancement and selectivity in reaction outcome. Rate enhancement and selectivity must have been essential for the origins of life by enabling chemical reactions to occur at appreciable rates and overcoming competition from hydrolysis.In this Accounts, we dissect the mechanisms by which coacervate protocells can accelerate reactions and provide selectivity. These mechanisms can similarly be exploited by membraneless organelles to control cellular processes. First, coacervates can affect the local concentration of reactants and accelerate reactions by copartitioning of reactants or exclusion of a product or inhibitor. Second, the local environment inside the coacervate can change the energy landscape for reactions taking place inside the droplets. The coacervate is more apolar than the surrounding solution and often rich in charged moieties, which can affect the stability of reactants, transition states and products. The crowded nature of the droplets can favor complexation of large molecules such as ribozymes. Their locally different proton and water activity can facilitate reactions involving a (de)protonation step, condensation reactions and reactions that are sensitive to hydrolysis. Not only the coacervate core, but also the surface can accelerate reactions and provides an interesting site for chemical reactions with gradients in pH, water activity and charge. The coacervate is often rich in catalytic amino acids and can localize catalysts like divalent metal ions, leading to further rate enhancement inside the droplets. Lastly, these coacervate properties can favor certain reaction pathways, and thereby give selectivity over the reaction outcome.These mechanisms are further illustrated with a case study on ribozyme reactions inside coacervates, for which there is a fine balance between concentration and reactivity that can be tuned by the coacervate composition. Furthermore, coacervates can both catalyze ribozyme reactions and provide product selectivity, demonstrating that coacervates could have functioned as enzyme-like catalytic microcompartments at the origins of life.

Chemical reservoir computation in a self-organizing reaction network.

Chemical reaction networks, such as those found in metabolism and signalling pathways, enable cells to process information from their environment1,2. Current approaches to molecular information processing and computation typically pursue digital computation models and require extensive molecular-level engineering3. Despite considerable advances, these approaches have not reached the level of information processing capabilities seen in living systems. Here we report on the discovery and implementation of a chemical reservoir computer based on the formose reaction4. We demonstrate how this complex, self-organizing chemical reaction network can perform several nonlinear classification tasks in parallel, predict the dynamics of other complex systems and achieve time-series forecasting. This in chemico information processing system provides proof of principle for the emergent computational capabilities of complex chemical reaction networks, paving the way for a new class of biomimetic information processing systems.

Leveraging Active Learning to Establish Efficient In Vitro Transcription and Translation from Bacterial Chromosomal DNA.

Gene expression is a fundamental aspect in the construction of a minimal synthetic cell, and the use of chromosomes will be crucial for the integration and regulation of complex modules. Expression from chromosomes in vitro transcription and translation (IVTT) systems presents limitations, as their large size and low concentration make them far less suitable for standard IVTT reactions. Here, we addressed these challenges by optimizing lysate-based IVTT systems at low template concentrations. We then applied an active learning tool to adapt IVTT to chromosomes as template DNA. Further insights into the dynamic data set led us to adjust the previous protocol for chromosome isolation and revealed unforeseen trends pointing at limiting transcription kinetics in our system. The resulting IVTT conditions allowed a high template DNA efficiency for the chromosomes. In conclusion, our system shows a protein-to-chromosome ratio that moves closer to in vivo biology and represents an advancement toward chromosome-based synthetic cells.

SecYEG-mediated translocation in a model synthetic cell.

Giant unilamellar vesicles (GUVs) provide a powerful model compartment for synthetic cells. However, a key challenge is the incorporation of membrane proteins that allow for transport, energy transduction, compartment growth and division. Here, we have successfully incorporated the membrane protein complex SecYEG-the key bacterial translocase that is essential for the incorporation of newly synthesized membrane proteins-in GUVs. Our method consists of fusion of small unilamellar vesicles containing reconstituted SecYEG into GUVs, thereby forming SecGUVs. These are suitable for large-scale experiments while maintaining a high protein:lipid ratio. We demonstrate that incorporation of SecYEG into GUVs does not inhibit its translocation efficiency. Robust membrane protein functionalized proteo-GUVs are promising and flexible compartments for use in the formation and growth of synthetic cells.

ARTseq-FISH reveals position-dependent differences in gene expression of micropatterned mESCs.

Differences in gene-expression profiles between individual cells can give rise to distinct cell fate decisions. Yet how localisation on a micropattern impacts initial changes in mRNA, protein, and phosphoprotein abundance remains unclear. To identify the effect of cellular position on gene expression, we developed a scalable antibody and mRNA targeting sequential fluorescence in situ hybridisation (ARTseq-FISH) method capable of simultaneously profiling mRNAs, proteins, and phosphoproteins in single cells. We studied 67 (phospho-)protein and mRNA targets in individual mouse embryonic stem cells (mESCs) cultured on circular micropatterns. ARTseq-FISH reveals relative changes in both abundance and localisation of mRNAs and (phospho-)proteins during the first 48 hours of exit from pluripotency. We confirm these changes by conventional immunofluorescence and time-lapse microscopy. Chemical labelling, immunofluorescence, and single-cell time-lapse microscopy further show that cells closer to the edge of the micropattern exhibit increased proliferation compared to cells at the centre. Together these data suggest that while gene expression is still highly heterogeneous position-dependent differences in mRNA and protein levels emerge as early as 12 hours after LIF withdrawal.

A Prebiotic Precursor to Life's Phosphate Transfer System with an ATP Analog and Histidyl Peptide Organocatalysts.

Biochemistry is dependent upon enzyme catalysts accelerating key reactions. At the origin of life, prebiotic chemistry must have incorporated catalytic reactions. While this would have yielded much needed amplification of certain reaction products, it would come at the possible cost of rapidly depleting the high energy molecules that acted as chemical fuels. Biochemistry solves this problem by combining kinetically stable and thermodynamically activated molecules (e.g., ATP) with enzyme catalysts. Here, we demonstrate a prebiotic phosphate transfer system involving an ATP analog (imidazole phosphate) and histidyl peptides, which function as organocatalytic enzyme analogs. We demonstrate that histidyl peptides catalyze phosphorylations via a phosphorylated histidyl intermediate. We integrate these histidyl-catalyzed phosphorylations into a complete prebiotic scenario whereby inorganic phosphate is incorporated into organic compounds though physicochemical wet-dry cycles. Our work demonstrates a plausible system for the catalyzed production of phosphorylated compounds on the early Earth and how organocatalytic peptides, as enzyme precursors, could have played an important role in this.

Exploring Emergent Properties in Enzymatic Reaction Networks: Design and Control of Dynamic Functional Systems.

The intricate and complex features of enzymatic reaction networks (ERNs) play a key role in the emergence and sustenance of life. Constructing such networks in vitro enables stepwise build up in complexity and introduces the opportunity to control enzymatic activity using physicochemical stimuli. Rational design and modulation of network motifs enable the engineering of artificial systems with emergent functionalities. Such functional systems are useful for a variety of reasons such as creating new-to-nature dynamic materials, producing value-added chemicals, constructing metabolic modules for synthetic cells, and even enabling molecular computation. In this review, we offer insights into the chemical characteristics of ERNs while also delving into their potential applications and associated challenges.

Unveiling the Intricate Connection: Cell Volume as a Key Regulator of Mechanotransduction.

The volumes of living cells undergo dynamic changes to maintain the cells' structural and functional integrity in many physiological processes. Minor fluctuations in cell volume can serve as intrinsic signals that play a crucial role in cell fate determination during mechanotransduction. In this review, we discuss the variability of cell volume and its role in vivo, along with an overview of the mechanisms governing cell volume regulation. Additionally, we provide insights into the current approaches used to control cell volume in vitro. Furthermore, we summarize the biological implications of cell volume regulation and discuss recent advances in understanding the fundamental relationship between cell volume and mechanotransduction. Finally, we delve into the potential underlying mechanisms, including intracellular macromolecular crowding and cellular mechanics, that govern the global regulation of cell fate in response to changes in cell volume. By exploring the intricate interplay between cell volume and mechanotransduction, we underscore the importance of considering cell volume as a fundamental signaling cue to unravel the basic principles of mechanotransduction. Additionally, we propose future research directions that can extend our current understanding of cell volume in mechanotransduction. Overall, this review highlights the significance of considering cell volume as a fundamental signal in understanding the basic principles in mechanotransduction and points out the possibility of controlling cell volume to control cell fate, mitigate disease-related damage, and facilitate the healing of damaged tissues.

Iterative design of training data to control intricate enzymatic reaction networks.

Kinetic modeling of in vitro enzymatic reaction networks is vital to understand and control the complex behaviors emerging from the nonlinear interactions inside. However, modeling is severely hampered by the lack of training data. Here, we introduce a methodology that combines an active learning-like approach and flow chemistry to efficiently create optimized datasets for a highly interconnected enzymatic reactions network with multiple sub-pathways. The optimal experimental design (OED) algorithm designs a sequence of out-of-equilibrium perturbations to maximize the information about the reaction kinetics, yielding a descriptive model that allows control of the output of the network towards any cost function. We experimentally validate the model by forcing the network to produce different product ratios while maintaining a minimum level of overall conversion efficiency. Our workflow scales with the complexity of the system and enables the optimization of previously unobtainable network outputs.

Dynamic hydrogen peroxide levels reveal a rate-dependent sensitivity in B-cell lymphoma signaling.

Although in vivo extracellular microenvironments are dynamic, most in vitro studies are conducted under static conditions. Here, we exposed diffuse large B-cell lymphoma (DLBCL) cells to gradient increases in the concentration of hydrogen peroxide (H2O2), thereby capturing some of the dynamics of the tumour microenvironment. Subsequently, we measured the phosphorylation response of B-cell receptor (BCR) signalling proteins CD79a, SYK and PLCγ2 at a high temporal resolution via single-cell phospho-specific flow cytometry. We demonstrated that the cells respond bimodally to static extracellular H2O2, where the percentage of cells that respond is mainly determined by the concentration. Computational analysis revealed that the bimodality results from a combination of a steep dose-response relationship and cell-to-cell variability in the response threshold. Dynamic gradient inputs of varying durations indicated that the H2O2 concentration is not the only determinant of the signalling response, as cells exposed to more shallow gradients respond at lower H2O2 levels. A minimal model of the proximal BCR network qualitatively reproduced the experimental findings and uncovered a rate-dependent sensitivity to H2O2, where a lower rate of increase correlates to a higher sensitivity. These findings will bring us closer to understanding how cells process information from their complex and dynamic in vivo environments.

Direct Analysis of Complex Reaction Mixtures: Formose Reaction.

Complex reaction mixtures, like those postulated on early Earth, present an analytical challenge because of the number of components, their similarity, and vastly different concentrations. Interpreting the reaction networks is typically based on simplified or partial data, limiting our insight. We present a new approach based on online monitoring of reaction mixtures formed by the formose reaction by ion-mobility-separation mass-spectrometry. Monitoring the reaction mixtures led to large data sets that we analyzed by non-negative matrix factorization, thereby identifying ion-signal groups capturing the time evolution of the network. The groups comprised ≈300 major ion signals corresponding to sugar-calcium complexes formed during the formose reaction. Multivariate analysis of the kinetic profiles of these complexes provided an overview of the interconnected kinetic processes in the solution, highlighting different pathways for sugar growth and the effects of different initiators on the initial kinetics. Reconstructing the network's topology further, we revealed so far unnoticed fast retro-aldol reaction of ketoses, which significantly affects the initial reaction dynamics. We also detected the onset of sugar-backbone branching for C6  sugars and cyclization reactions starting for C5  sugars. This top-down analytical approach opens a new way to analyze complex dynamic mixtures online with unprecedented coverage and time resolution.

Quantifying the deformability of malaria-infected red blood cells using deep learning trained on synthetic cells.

Several hematologic diseases, including malaria, diabetes, and sickle cell anemia, result in a reduced red blood cell deformability. This deformability can be measured using a microfluidic device with channels of varying width. Nevertheless, it is challenging to algorithmically recognize large numbers of red blood cells and quantify their deformability from image data. Deep learning has become the method of choice to handle noisy and complex image data. However, it requires a significant amount of labeled data to train the neural networks. By creating images of cells and mimicking noise and plasticity in those images, we generate synthetic data to train a network to detect and segment red blood cells from video-recordings, without the need for manually annotated labels. Using this new method, we uncover significant differences between the deformability of RBCs infected with different strains of Plasmodium falciparum, providing clues to the variation in virulence of these strains.

Correction to "Strategies for Transferring Photobiocatalysis to Continuous Flow Exemplified by the Photodecarboxylation of Fatty Acids".

[This corrects the article DOI: 10.1021/acscatal.2c04444.].

A catalytically active oscillator made from small organic molecules.

Oscillatory systems regulate many biological processes, including key cellular functions such as metabolism and cell division, as well as larger-scale processes such as circadian rhythm and heartbeat1-4. Abiotic chemical oscillations, discovered originally in inorganic systems5,6, inspired the development of various synthetic oscillators for application as autonomous time-keeping systems in analytical chemistry, materials chemistry and the biomedical field7-17. Expanding their role beyond that of a pacemaker by having synthetic chemical oscillators periodically drive a secondary function would turn them into significantly more powerful tools. However, this is not trivial because the participation of components of the oscillator in the secondary function might jeopardize its time-keeping ability. We now report a small molecule oscillator that can catalyse an independent chemical reaction in situ without impairing its oscillating properties. In a flow system, the concentration of the catalytically active product of the oscillator shows sustained oscillations and the catalysed reaction is accelerated only during concentration peaks. Augmentation of synthetic oscillators with periodic catalytic action allows the construction of complex systems that, in the future, may benefit applications in automated synthesis, systems and polymerization chemistry and periodic drug delivery.

Noise Minimization in Cell-Free Gene Expression.

Biochemical reactions that involve small numbers of molecules are accompanied by a degree of inherent randomness that results in noisy reaction outcomes. In synthetic biology, the ability to minimize noise particularly during the reconstitution of future synthetic protocells is an outstanding challenge to secure robust and reproducible behavior. Here we show that by encapsulation of a bacterial cell-free gene expression system in water-in-oil droplets, in vitro-synthesized MazF reduces cell-free gene expression noise >2-fold. With stochastic simulations we identify that this noise minimization acts through both increased degradation and the autoregulatory feedback of MazF. Specifically, we find that the expression of MazF enhances the degradation rate of mRNA up to 18-fold in a sequence-dependent manner. This sequence specificity of MazF would allow targeted noise control, making it ideal to integrate into synthetic gene networks. Therefore, including MazF production in synthetic biology can significantly minimize gene expression noise, impacting future design principles of more complex cell-free gene circuits.

In Vitro Transcription-Translation in an Artificial Biomolecular Condensate.

Biomolecular condensates are a promising platform for synthetic cell formation and constitute a potential missing link between the chemical and cellular stage of the origins of life. However, it has proven challenging to integrate complex reaction networks into biomolecular condensates, such as a cell-free in vitro transcription-translation (IVTT) system. Integrating IVTT into biomolecular condensates successfully is one precondition for condensation-based synthetic cell formation. Moreover, it would provide a proof of concept that biomolecular condensates are in principle compatible with the central dogma, one of the hallmarks of cellular life. Here, we have systemically investigated the compatibility of eight different (bio)molecular condensates with IVTT incorporation. Of these eight candidates, we have found that a green fluorescent protein-labeled, intrinsically disordered cationic protein (GFP-K72) and single-stranded DNA (ssDNA) can form biomolecular condensates that are compatible with up to µM fluorescent protein expression. This shows that biomolecular condensates can indeed integrate complex reaction networks, confirming their use as synthetic cell platforms and hinting at a possible role in the origin of life.

Cell-Free Expression System Derived from a Near-Minimal Synthetic Bacterium.

Cell-free expression (CFE) systems are fundamental to reconstituting metabolic pathways in vitro toward the construction of a synthetic cell. Although an Escherichia coli-based CFE system is well-established, simpler model organisms are necessary to understand the principles behind life-like behavior. Here, we report the successful creation of a CFE system derived from JCVI-syn3A (Syn3A), the minimal synthetic bacterium. Previously, high ribonuclease activity in Syn3A lysates impeded the establishment of functional CFE systems. Now, we describe how an unusual cell lysis method (nitrogen decompression) yielded Syn3A lysates with reduced ribonuclease activity that supported in vitro expression. To improve the protein yields in the Syn3A CFE system, we optimized the Syn3A CFE reaction mixture using an active machine learning tool. The optimized reaction mixture improved the CFE 3.2-fold compared to the preoptimized condition. This is the first report of a functional CFE system derived from a minimal synthetic bacterium, enabling further advances in bottom-up synthetic biology.

Structure-Property Relationships Governing Membrane-Penetrating Behaviour of Complex Coacervates.

Complex coacervates are phase-separated liquid droplets composed of oppositely charged multivalent molecules. The unique material properties of the complex coacervate interior favours the sequestration of biomolecules and facilitates reactions. Recently, it is shown that coacervates can be used for direct cytosolic delivery of sequestered biomolecules in living cells. Here, it is studied that the physical properties required for complex coacervates composed of oligo-arginine and RNA to cross phospholipid bilayers and enter liposomes penetration depends on two main parameters: the difference in ζ-potential between the complex coacervates and the liposomes, and the partitioning coefficient (Kp ) of lipids into the complex coacervates. Following these guidelines, a range of complex coacervates is found that is able to penetrate the membrane of living cells, thus paving the way for further development of coacervates as delivery vehicles of therapeutic agents.

Mechanosensitive non-equilibrium supramolecular polymerization in closed chemical systems.

Chemical fuel-driven supramolecular systems have been developed showing out-of-equilibrium functions such as transient gelation and oscillations. However, these systems suffer from undesired waste accumulation and they function only in open systems. Herein, we report non-equilibrium supramolecular polymerizations in a closed system, which is built by viologens and pyranine in the presence of hydrazine hydrate. On shaking, the viologens are quickly oxidated by air followed by self-assembly of pyranine into micrometer-sized nanotubes. The self-assembled nanotubes disassemble spontaneously over time by the reduced agent, with nitrogen as the only waste product. Our mechanosensitive dissipative system can be extended to fabricate a chiral transient supramolecular helix by introducing chiral-charged small molecules. Moreover, we show that shaking induces transient fluorescence enhancement or quenching depending on substitution of viologens. Ultrasound is introduced as a specific shaking way to generate template-free reproducible patterns. Additionally, the shake-driven transient polymerization of amphiphilic naphthalenetetracarboxylic diimide serves as further evidence of the versatility of our mechanosensitive non-equilibrium system.