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Catalytic nucleic acids are regarded as potential therapeutic agents and biosensors. The catalytic activities of nucleic acid enzymes are usually investigated in dilute aqueous solutions, although the physical properties of the reaction environment inside living cells and that in the area proximal to the surface of biosensors in which they operate are quite different from those of pure water. The effect of the molecular environment is also an important focus of research aimed at improving and expanding nucleic acid function by addition of organic solvents to aqueous solutions. In this study, the catalytic activities of RNA and DNA enzymes (hammerhead ribozyme, 17E DNAzyme, R3C ribozyme, and 9DB1 DNAzyme) were investigated using 21 different mixed aqueous solutions comprising organic compounds. Kinetic measurements indicated that these enzymes can display enhanced catalytic activity in mixed solutions with respect to the solution containing no organic additives. Correlation analyses revealed that the turnover rate of the reaction catalyzed by hammerhead ribozyme increased in a medium with a lower dielectric constant than water, and the turnover rate of the reaction catalyzed by 17E DNAzyme increased in conditions that increased the strength of DNA interactions. On the other hand, R3C ribozyme and 9DB1 DNAzyme displayed no significant turnover activity, but their single-turnover rates increased in many mixed solutions. Our data provide insight into the activity of catalytic nucleic acids under various conditions that are applicable to the medical and technology fields, such as in living cells and in biosensors.

The endoergic nature of protein and nucleic acid assembly in aqueous media presents two questions that are fundamental to the understanding of life’s origins: (i) how did the polymers arise in an aqueous prebiotic world; and (ii) once formed in some manner, how were they sufficiently persistent to engage in further chemistry. We propose here a quantitative resolution of these issues that evolved from recent accounts in which RNA-like polymers were produced in evaporation/rehydration cycles. The equilibrium Nm + Nn ↔ Nm+n + H2O is endoergic by about 3.3 kcal/mol for polynucleotide formation, and the system thus lies far to the left in the starting solutions. Kinetic simulations of the evaporation showed that simple Le Châtelier’s principle shifts were insufficient, but the introduction of oligomer-stabilizing factors of 5–10 kcal/mol both moved the process to the right and respectively boosted and retarded the elongation and hydrolysis rates. Molecular crowding and excluded volume effects in present-day cells yield stabilizing factors of that order, and we argue here that the crowded conditions in the evaporites generate similar effects. Oligomer formation is thus energetically preferred in those settings, but the process is thwarted in each evaporation step as diffusion becomes rate limiting. Rehydration dissipates disordered oligomer clusters in the evaporites, however, and subsequent dry/wet cycling accordingly “ratchets up” the system to an ultimate population of kinetically trappedthermodynamically preferred biopolymers.

Cells alter their mechanical properties in response to their local microenvironment; this plays a role in determining cell function and can even influence stem cell fate. Here, we identify a robust and unified relationship between cell stiffness and cell volume. As a cell spreads on a substrate, its volume decreases, while its stiffness concomitantly increases. We find that both cortical and cytoplasmic cell stiffness scale with volume for numerous perturbations, including varying substrate stiffness, cell spread area, and external osmotic pressure. The reduction of cell volume is a result of water efflux, which leads to a corresponding increase in intracellular molecular crowding. Furthermore, we find that changes in cell volume, and hence stiffness, alter stem-cell differentiation, regardless of the method by which these are induced. These observations reveal a surprising, previously unidentified relationship between cell stiffness and cell volume that strongly influences cell biology.

Genome‐scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance and turnover number. We applied GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between and within metabolic pathways. The developed method and model are expected to increase the use of model‐based design in metabolic engineering. Synopsis The GECKO method takes into account enzyme abundances and kinetics to enhance genome‐scale models of metabolism (GEMs). An implementation for Saccharomyces cerevisiae gives insight into metabolism and enzyme usage. GECKO is a method that enhances a GEM with enzyme constraints, using both kinetic and omics data. The enzyme‐constrained ecYeast7 model of S. cerevisiae outperforms previous models in simulation capabilities and allows exploring enzyme usage. Directly integrating quantitative proteomic data in ecYeast7 significantly reduces the inherent flux variability of model simulations. Physiological behavior such as maximum specific growth rate, overflow metabolism and gene deletion response can be explained by a limited enzyme pool in cell. Graphical Abstract The GECKO method takes into account enzyme abundances and kinetics to enhance genome‐scale models of metabolism (GEMs). An implementation for Saccharomyces cerevisiae gives insight into metabolism and enzyme usage.

The intracellular environment is crowded and heterogeneous. Although the thermodynamic stability of nucleic acid duplexes is predictable in dilute solutions, methods of predicting such stability under specific intracellular conditions are not yet available. We recently showed that the nearest-neighbor model for self-complementary DNA is valid under molecular crowding condition of 40% polyethylene glycol with an average molecular weight of 200 (PEG 200) in 100 mM NaCl. Here, we determined nearest-neighbor parameters for DNA duplex formation under the same crowding condition to predict the thermodynamics of DNA duplexes in the intracellular environment. Preferential hydration of the nucleotides was found to be the key factor for nearest-neighbor parameters in the crowding condition. The determined parameters were shown to predict the thermodynamic parameters (ΔH°, ΔS°, and ΔG°37) and melting temperatures (T m) of the DNA duplexes in the crowding condition with significant accuracy. Moreover, we proposed a general method for predicting the stability of short DNA duplexes in different cosolutes based on the relationship between duplex stability and the water activity of the cosolute solution. The method described herein would be valuable for investigating biological processes that occur under specific intracellular crowded conditions and for the application of DNA-based biotechnologies in crowded environments.

The motility of biological molecular motors has typically been analyzed by in vitro reconstitution systems using motors isolated and purified from organs or expressed in cultured cells. The behavior of biomolecular motors within cells has frequently been reported to be inconsistent with that observed in reconstituted systems in vitro. Although this discrepancy has been attributed to differences in ionic strength and intracellular crowding, understanding how such parameters affect the motility of motors remains challenging. In this report, we investigated the impact of intracellular crowding in vitro on the mechanical properties of kinesin under a high ionic strength that is comparable to the cytoplasm. Initially, we characterized viscosity in a cell by using a kinesin motor lacking the cargo-binding domain. We then used polyethylene glycol to create a viscous environment in vitro comparable to the intracellular environment. Our results showed that kinesin frequently dissociated from microtubules under high ionic strength conditions. However, under conditions of both high ionic strength and crowding with polymers, the processive movement of kinesin persisted and increased in frequency. This setting reproduces the significant variations in the mechanical properties of motors measured in the intracellular environment and suggests a mechanism whereby kinesin maintains motility under the high ionic strengths found in cells.Key words: Kinesin motility, molecular crowding, ionic strength, intracellular transport, processivity of molecular motors

Noncanonical DNA structures that stall DNA replication can cause errors in genomic DNA. Here, we investigated how the noncanonical structures formed by sequences in genes associated with a number of diseases impacted DNA polymerization by the Klenow fragment of DNA polymerase. Replication of a DNA sequence forming an i-motif from a telomere, hypoxia-induced transcription factor, and an insulin-linked polymorphic region was effectively inhibited. On the other hand, replication of a mixed-type G-quadruplex (G4) from a telomere was less inhibited than that of the antiparallel type or parallel type. Interestingly, the i-motif was a better inhibitor of replication than were mixed-type G4s or hairpin structures, even though all had similar thermodynamic stabilities. These results indicate that both the stability and topology of structures formed in DNA templates impact the processivity of a DNA polymerase. This suggests that i-motif formation may trigger genomic instability by stalling the replication of DNA, causing intractable diseases.

Protein dynamics in cells are essential for metabolic processes that rely on protein encounter and transport. In order to understand this process, namely, the impact of the crowding nature of the cytoplasmic space, advanced ensemble and single-molecule experimental approaches have been applied. This review summarizes recent literature by first considering the application of neutron scattering techniques that can probe protein internal and global dynamics in different types of crowded conditions. The results from other experimental approaches and computational studies are also presented. Finally, we review studies in which the dynamics in the cytoplasm are a proxy of different cellular conditions, from approaching thermal death to starvation.

Executing gene circuits by cell-free transcription–translation into cell-sized compartments, such as liposomes, is one of the major bottom-up approaches to building minimal cells. The dynamic synthesis and proper self-assembly of macromolecular structures inside liposomes, the cytoskeleton in particular, stands as a central limitation to the development of cell analogs genetically programmed. In this work, we express the Escherichia coli gene mreB inside vesicles with bilayers made of lipid-polyethylene glycol (PEG). We demonstrate that two-dimensional molecular crowding, emulated by the PEG molecules at the lipid bilayer, is enough to promote the polymerization of the protein MreB at the inner membrane into a sturdy cytoskeleton capable of transforming spherical liposomes into elongated shapes, such as rod-like compartments. We quantitatively describe thismechanism with respect to the size of liposomes, lipid composition of the membrane, crowding at the membrane, and strength of MreB synthesis. So far unexplored, molecular crowding at the surface of synthetic cells emerges as an additional development with potential broad applications. The symmetry breaking observed could be an important step toward compartment self-reproduction.

The cytoophidium is a unique type of membraneless compartment comprising of filamentous protein polymers. Inosine monophosphate dehydrogenase (IMPDH) catalyzes the rate-limiting step of de novo GTP biosynthesis and plays critical roles in active cell metabolism. However, the molecular regulation of cytoophidium formation is poorly understood. Here we show that human IMPDH2 polymers bundle up to form cytoophidium-like aggregates in vitro when macromolecular crowders are present. The self-association of IMPDH polymers is suggested to rely on electrostatic interactions. In cells, the increase of molecular crowding with hyperosmotic medium induces cytoophidia, while the decrease of that by the inhibition of RNA synthesis perturbs cytoophidium assembly. In addition to IMPDH, CTPS and PRPS cytoophidium could be also induced by hyperosmolality, suggesting a universal phenomenon of cytoophidium-forming proteins. Finally, our results indicate that the cytoophidium can prolong the half-life of IMPDH, which is proposed to be one of conserved functions of this subcellular compartment.