Enhanced Diffusion and Chemotaxis of Enzymes

Chemotactic particles as strong electrolytes: Debye-Hückel approximation and effective mobility law

We consider a binary mixture of chemically active particles that produce or consume solute molecules and that interact with each other through the long-range concentration fields they generate. We analytically calculate the effective phoretic mobility of these particles when the mixture is submitted to a constant, external concentration gradient, at leading order in the overall concentration. Relying on an analogy with the modeling of strong electrolytes, we show that the effective phoretic mobility decays with the square root of the concentration: our result is, therefore, a nonequilibrium counterpart to the celebrated Kohlrausch and Debye-Hückel-Onsager conductivity laws for electrolytes, which are extended here to particles with long-range nonreciprocal interactions. The effective mobility law we derive reveals the existence of a regime of maximal mobility and could find applications in the description of nanoscale transport phenomena in living cells.

Artificial Molecular Ratchets: Tools Enabling Endergonic Processes

Non-equilibrium chemical systems underpin multiple domains of contemporary interest, including supramolecular chemistry, molecular machines, systems chemistry, prebiotic chemistry, and energy transduction. Experimental chemists are now pioneering the realization of artificial systems that can harvest energy away from equilibrium. In this tutorial Review, we provide an overview of artificial molecular ratchets: the chemical mechanisms enabling energy absorption from the environment. By focusing on the mechanism type-rather than the application domain or energy source-we offer a unifying picture of seemingly disparate phenomena, which we hope will foster progress in this fascinating domain of science.

Dual enzyme-powered chemotactic cross β amyloid based functional nanomotors

Nanomotor chassis constructed from biological precursors and powered by biocatalytic transformations can offer important applications in the future, specifically in emergent biomedical techniques. Herein, cross β amyloid peptide-based nanomotors (amylobots) were prepared from short amyloid peptides. Owing to their remarkable binding capabilities, these soft constructs are able to host dedicated enzymes to catalyze orthogonal substrates for motility and navigation. Urease helps in powering the self-diffusiophoretic motion, while cytochrome C helps in providing navigation control. Supported by the simulation model, the design principle demonstrates the utilization of two distinct transport behaviours for two different types of enzymes, firstly enhanced diffusivity of urease with increasing fuel (urea) concentration and secondly, chemotactic motility of cytochrome C towards its substrate (pyrogallol). Dual catalytic engines allow the amylobots to be utilized for enhanced catalysis in organic solvent and can thus complement the technological applications of enzymes.

Network Effects Lead to Self-Organization in Metabolic Cycles of Self-Repelling Catalysts

Mixtures of particles that interact through phoretic effects are known to aggregate if they belong to species that exhibit attractive self-interactions. We study self-organization in a model metabolic cycle composed of three species of catalytically active particles that are chemotactic toward the chemicals that define their connectivity network. We find that the self-organization can be controlled by the network properties, as exemplified by a case where a collapse instability is achieved by design for self-repelling species. Our findings highlight a possibility for controlling the intricate functions of metabolic networks by taking advantage of the physics of phoretic active matter.

On the utility of microfluidic systems to study protein interactions: advantages, challenges, and applications

Within the complex milieu of a cell, which comprises a large number of different biomolecules, interactions are critical for function. In this post-reductionist era of biochemical research, the 'holy grail' for studying biomolecular interactions is to be able to characterize them in native environments. While there are a limited number of in situ experimental techniques currently available, there is a continuing need to develop new methods for the analysis of biomolecular complexes that can cope with the additional complexities introduced by native-like solutions. We think approaches that use microfluidics allow researchers to access native-like environments for studying biological problems. This review begins with a brief overview of the importance of studying biomolecular interactions and currently available methods for doing so. Basic principles of diffusion and microfluidics are introduced and this is followed by a review of previous studies that have used microfluidics to measure molecular diffusion and a discussion of the advantages and challenges of this technique.

The formation and function of plant metabolons

Metabolons are temporary structural-functional complexes of sequential enzymes of a metabolic pathway that are distinct from stable multi-enzyme complexes. Here we provide a brief history of the study of enzyme-enzyme assemblies with a particular focus on those that mediate substrate channeling in plants. Large numbers of protein complexes have been proposed for both primary and secondary metabolic pathways in plants. However, to date only four substrate channels have been demonstrated. We provide an overview of current knowledge concerning these four metabolons and explain the methodologies that are currently being applied to unravel their functions. Although the assembly of metabolons has been documented to arise through diverse mechanisms, the physical interaction within the characterized plant metabolons all appear to be driven by interaction with structural elements of the cell. We therefore pose the question as to what methodologies could be brought to bear to enhance our knowledge of plant metabolons that assemble via different mechanisms? In addressing this question, we review recent findings in non-plant systems concerning liquid droplet phase separation and enzyme chemotaxis and propose strategies via which such metabolons could be identified in plants. We additionally discuss the possibilities that could be opened up by novel approaches based on: (i) subcellular-level mass spectral imaging, (ii) proteomics, and (iii) emergent methods in structural and computational biology.

Single-Molecule Tracking of Reagent Diffusion during Chemical Reactions

Recent experiments have shown that the diffusion of reagent molecules is inconsistent with what the Stokes-Einstein equation predicts during a chemical reaction. Here, we used single-molecule tracking to observe the diffusion of reactive reagent molecules during click and Diels-Alder (DA) reactions. We found that the diffusion coefficient of the reagents remained unchanged within the experimental uncertainty upon the DA reaction. Yet, diffusion of reagent molecules is faster than predicted during the click reaction when the reagent concentration and catalyst concentration exceed a threshold. A stepwise analysis suggested that the fast diffusion scenario is due to the reaction but not the involvement of the tracer with the reaction itself. The present results provide experimental evidence on the faster-than-expected reagent diffusion during a CuAAC reaction in specific conditions and propose new insights into understanding this unexpected behavior.

Kinetic Asymmetry versus Dissipation in the Evolution of Chemical Systems as Exemplified by Single Enzyme Chemotaxis

Single enzyme chemotaxis is a phenomenon by which a nonequilibrium spatial distribution of an enzyme is created and maintained by concentration gradients of the substrate and product of the catalyzed reaction. These gradients can arise either naturally through metabolism or experimentally, e.g., by flow of materials through microfluidic channels or by use of diffusion chambers with semipermeable membranes. Numerous hypotheses regarding the mechanism of this phenomenon have been proposed. Here, we discuss a mechanism based solely on diffusion and chemical reaction and show that kinetic asymmetry, a difference in the transition state energies for dissociation/association of substrate and product, and diffusion asymmetry, a difference in the diffusivities of the bound and free forms of the enzyme, are the determinates of the direction of chemotaxis and can result in either positive or negative chemotaxis, both of which have been demonstrated experimentally. Exploration of these fundamental symmetries that govern nonequilibrium behavior helps to distinguish between possible mechanisms for the evolution of a chemical system from initial to the steady state and whether the principle that determines the direction a system shifts when exposed to an external energy source is based on thermodynamics or on kinetics with the latter being supported by the results of the present paper. Our results show that, while dissipation ineluctably accompanies nonequilibrium phenomena, including chemotaxis, systems do not evolve to maximize or minimize dissipation but rather to attain greater kinetic stability and accumulate in regions where their effective diffusion coefficient is as small as possible. The chemotactic response to the chemical gradients formed by other enzymes participating in a catalytic cascade provides a mechanism for forming loose associations known as metabolons. Significantly, the direction of the effective force due to these gradients depends on the kinetic asymmetry of the enzyme and so can be nonreciprocal, where one enzyme is attracted to another enzyme, but the other enzyme is repelled by the one, in seeming contradiction to Newtons third law. This nonreciprocity is an important ingredient in the behavior of active matter.

Dynamics of a spherical self-propelled tracer in a polymeric medium: interplay of self-propulsion, stickiness, and crowding

We employ computer simulations to study the dynamics of a self-propelled spherical tracer particle in a viscoelastic medium, made of a long polymer chain. Here, the interplay between viscoelasticity, stickiness, and activity (self-propulsion) brings additional complexity to the tracer dynamics. Our simulations show that on increasing the stickiness of the tracer particle to the polymer beads, the dynamics of the tracer particle slows down as it gets stuck to the polymer chain and moves along with it. But with increasing self-propulsion velocity, the dynamics gets enhanced. In the case of increasing stickiness as well as activity, the non-Gaussian parameter (NGP) exhibits non-monotonic behavior, which also shows up in the re-scaled self part of the van-Hove function. Non-Gaussianity results owing to the enhanced binding events and the sticky motion of the tracer along with the chain with increasing stickiness. On the other hand, with increasing activity, initially non-Gaussianity increases as the tracer moves through the heterogeneous polymeric environment but for higher activity, the tracer escapes resulting in a negative NGP. For higher values of stickiness, the trapping time distributions of the passive tracer particle broaden and have long tails. On the other hand, for a given stickiness with increasing self-propulsion force, the trapping time distributions become narrower and have short tails. We believe that our current simulation study will be helpful in elucidating the complex motion of activity-driven probes in viscoelastic media.

Diffusion coefficient and power spectrum of active particles with a microscopically reversible mechanism of self-propelling

Catalytically active macromolecules are envisioned as key building blocks in development of artificial nanomotors. However, theory and experiments report conflicting findings regarding their dynamics. The lack of consensus is mostly caused by a limited understanding of specifics of self-propulsion mechanisms at the nanoscale. Here, we study a generic model of a self-propelled nanoparticle that does not rely on a particular mechanism. Instead, its main assumption is the fundamental symmetry of microscopic dynamics of chemical reactions: the principle of microscopic reversibility. Significant consequences of this assumption arise if we subject the particle to an action of an external time-periodic force. The particle diffusion coefficient is then enhanced compared to the unbiased dynamics. The enhancement can be controlled by the force amplitude and frequency. We also derive the power spectrum of particle trajectories. Among new effects stemming from the microscopic reversibility are the enhancement of the spectrum at all frequencies and sigmoid-shaped transitions and a peak at characteristic frequencies of rotational diffusion and external forcing. The microscopic reversibility is a generic property of a broad class of chemical reactions, therefore we expect that the presented results will motivate new experimental studies aimed at testing of our predictions. This could provide new insights into dynamics of catalytic macromolecules.

Perpetuating enzymatically induced spatiotemporal pH and catalytic heterogeneity of a hydrogel by nanoparticles

The attainment of spatiotemporally inhomogeneous chemical and physical properties within a system is gaining attention across disciplines due to the resemblance to environmental and biological heterogeneity. Notably, the origin of natural pH gradients and how they have been incorporated in cellular systems is one of the most important questions in understanding the prebiotic origin of life. Herein, we have demonstrated a spatiotemporal pH gradient formation pattern on a hydrogel surface by employing two different enzymatic reactions, namely, the reactions of glucose oxidase (pH decreasing) and urease (pH increasing). We found here a generic pattern of spatiotemporal change in pH and proton transfer catalytic activity that was completely altered in a cationic gold nanoparticle containing hydrogel. In the absence of nanoparticles, the gradually generated macroscopic pH gradient slowly diminished with time, whereas the presence of nanoparticles helped to perpetuate the generated gradient effect. This behavior is due to the differential responsiveness of the interface of the cationic nanoparticle in temporally changing surroundings with increasing or decreasing pH or ionic contents. Moreover, the catalytic proton transfer ability of the nanoparticle showed a concerted kinetic response following the spatiotemporal pH dynamics in the gel matrix. Notably, this nanoparticle-driven spatiotemporally resolved gel matrix will find applicability in the area of the membrane-free generation and control of spatially segregated chemistry at the macroscopic scale.

Fluorescent Microswimmers Based on Cross-β Amyloid Nanotubes and Divergent Cascade Networks

Shaped through millions of years of evolution, the spatial localization of multiple enzymes in living cells employs extensive cascade reactions to enable highly coordinated multimodal functions. Herein, by utilizing a complex divergent cascade, we exploit the catalytic potential as well as templating abilities of streamlined cross-β amyloid nanotubes to yield two orthogonal roles simultaneously. The short peptide based paracrystalline nanotube surfaces demonstrated the generation of fluorescence signals within entangled networks loaded with alcohol dehydrogenase (ADH). The nanotubular morphologies were further used to generate cascade-driven microscopic motility through surface entrapment of sarcosine oxidase (SOX) and catalase (Cat). Moreover, a divergent cascade network was initiated by upstream catalysis of the substrate molecules through the surface mutation of catalytic moieties. Notably, the resultant downstream products led to the generation of motile fluorescent microswimmers by utilizing the two sets of orthogonal properties and, thus, mimicked the complex cascade-mediated functionalities of extant biology.

Regulating Spatial Localization and Reactivity Biasness of DNAzymes by Metal Ions and Oligonucleotides

Chemical gradient sensing behavior of catalytically active colloids and enzymes is an area of immense interest owing to their importance in understanding fundamental spatiotemporal complexity pattern in living systems and designing of dynamic materials. Herein, we have shown peroxidase activity of DNAzyme (G-quadruplex-hemin complex tagged in a micron-sized glass bead) can be modulated by metal ions and metal ion-binding oligonucleotides. Next we demonstrated both experimentally and theoretically that the localization and product formation ability of the DNAzyme containing particle remains biased to the more catalytically active zone where concentration of metal ion (Hg2+) inhibitor is low. Interestingly, this biased localization can be broken by introduction of Hg2+ binding oligonucleotide in the system. Additionally, macroscopically asymmetric catalytic product distributed zone has also been achieved on this process, showing possibility in regulation in autonomous spatially controlled chemical process. This demonstration of autonomous modulation of the localization pattern and spatially specific enhanced product forming ability of DNAzymes will further enable in designing of responsive nucleic acid-based motile materials and surfaces.

Enhanced Mobility during Diels-Alder Reaction: Results of Molecular Simulations

Recent measurements indicate enhanced mobility of solvent molecules during Diels-Alder (DA) and other common chemical reactions. We present results of molecular dynamics simulations of the last stages of the DA cycloaddition reaction, from the transition state configuration to product, of furfurylamine and maleimide in acetonitrile at reactant concentrations studied experimentally. We find enhanced mobility of solvent and reactant molecules up to at least a nanometer from the DA product over hundreds of picoseconds. Local heating is ruled out as a factor in the enhanced mobility observed in the simulations, which is instead found to be due to solvent relaxation following the formation of the DA product.

Enzyme Purification Improves the Enzyme Loading, Self-Propulsion, and Endurance Performance of Micromotors

Enzyme-powered micro- and nanomotors make use of biocatalysis to self-propel in aqueous media and hold immense promise for active and targeted drug delivery. Most (if not all) of these micro- and nanomotors described to date are fabricated using a commercially available enzyme, despite claims that some commercial preparations may not have a sufficiently high degree of purity for downstream applications. In this study, the purity of a commercial urease, an enzyme frequently used to power the motion of micro- and nanomotors, was evaluated and found to be impure. After separating the hexameric urease from the protein impurities by size-exclusion chromatography, the hexameric urease was subsequently characterized and used to functionalize hollow silica microcapsules. Micromotors loaded with purified urease were found to be 2.5 times more motile than the same micromotors loaded with unpurified urease, reaching average speeds of 5.5 μm/s. After comparing a number of parameters, such as enzyme distribution, protein loading, and motor reusability, between micromotors functionalized with purified vs unpurified urease, it was concluded that protein purification was essential for optimal performance of the enzyme-powered micromotor.

Enhanced diffusivity in microscopically reversible active matter

The physics of self-propelled objects at the nanoscale is a rapidly developing research field where recent experiments have focused on the motion of individual catalytic enzymes. Contrary to the experimental advancements, theoretical understanding of the possible self-propulsion mechanisms at these scales is limited. A particularly puzzling question concerns the origins of the reportedly high diffusivities of the individual enzymes. Here we start with the fundamental principle of microscopic reversibility (MR) of chemical reactions powering self-propulsion and demonstrate that MR can lead to an increase of the particle mobility and of the short- and long-time diffusion coefficients as compared to dynamics where MR is neglected. Furthermore, the derived diffusion coefficients are enhanced due to the action of an external force. These results can shed new light on interpretations of the measured diffusivities and help to test the relevance of MR for the active motion of individual nanoswimmers.

Perspective: a stirring role for metabolism in cells

Based on recent findings indicating that metabolism might be governed by a limit on the rate at which cells can dissipate Gibbs energy, in this Perspective, we propose a new mechanism of how metabolic activity could globally regulate biomolecular processes in a cell. Specifically, we postulate that Gibbs energy released in metabolic reactions is used to perform work, allowing enzymes to self-propel or to break free from supramolecular structures. This catalysis-induced enzyme movement will result in increased intracellular motion, which in turn can compromise biomolecular functions. Once the increased intracellular motion has a detrimental effect on regulatory mechanisms, this will establish a feedback mechanism on metabolic activity, and result in the observed thermodynamic limit. While this proposed explanation for the identified upper rate limit on cellular Gibbs energy dissipation rate awaits experimental validation, it offers an intriguing perspective of how metabolic activity can globally affect biomolecular functions and will hopefully spark new research.

Displacement Statistics of Unhindered Single Molecules Show no Enhanced Diffusion in Enzymatic Reactions

Recent studies have sparked debate over whether catalytic reactions enhance the diffusion coefficients D of enzymes. Through high statistics of the transient (600 μs) displacements of unhindered single molecules freely diffusing in common buffers, we here quantify D for four enzymes under catalytic turnovers. We thus formulate how ∼ ±1% precisions may be achieved for D, and show no changes in diffusivity for catalase, urease, aldolase, and alkaline phosphatase under the application of wide concentration ranges of substrates. Our single-molecule approach thus overcomes potential limitations and artifacts underscored by recent studies to show no enhanced diffusion in enzymatic reactions.

A simple theory for molecular chemotaxis driven by specific binding interactions

Recent experiments have suggested that enzymes and other small molecules chemotax toward their substrates. However, the physical forces driving this chemotaxis are currently debated. In this work, we consider a simple thermodynamic theory for molecular chemotaxis that is based on the McMillan-Mayer theory of dilute solutions and Schellman's theory for macromolecular binding. Even in the absence of direct interactions, the chemical binding equilibrium introduces a coupling term into the relevant free energy, which then reduces the chemical potential of both enzymes and their substrates. Assuming a local thermodynamic equilibrium, this binding contribution to the chemical potential generates an effective thermodynamic force that promotes chemotaxis by driving each solute toward its binding partner. Our numerical simulations demonstrate that, although small, this thermodynamic force is qualitatively consistent with several experimental studies. Thus, our study may provide additional insight into the role of the thermodynamic binding free energy for molecular chemotaxis.

Relative Diffusivities of Bound and Unbound Protein Can Control Chemotactic Directionality

Enzyme-based systems have been shown to undergo chemotactic motion in response to their substrate gradient. This phenomenon has been exploited to direct the motion of enzymes and enzyme-attached particles to specific locations in space. Here, we propose a new kinetic model to analyze the directional movement of an ensemble of protein molecules in response to a gradient of the ligand. We also formulate a separate model to probe the motion of enzyme molecules in response to a gradient of the substrate under catalytic conditions. The only input for the new enzymatic model is the Michaelis-Menten constant which is the relevant measurable constant for enzymatic reactions. We show how our model differs from previously proposed models in a significant manner. For both binding and catalytic reactions, a net movement up the ligand/substrate gradient is predicted when the diffusivity of the ligand/substrate-bound protein is lower than that of the unbound protein (positive chemotaxis). Conversely, movement down the ligand/substrate gradient is expected when the diffusivity of the ligand/substrate-bound protein is higher than that of the unbound protein (negative chemotaxis). However, there is no net movement of protein/enzyme when the diffusivities of the bound and free species are equal. The work underscores the critical importance of measuring the diffusivity of the bound protein and comparing it with that of the free protein.

Non-equilibrium phase separation in mixtures of catalytically active particles: size dispersity and screening effects

Biomolecular condensates in cells are often rich in catalytically active enzymes. This is particularly true in the case of the large enzymatic complexes known as metabolons, which contain different enzymes that participate in the same catalytic pathway. One possible explanation for this self-organization is the combination of the catalytic activity of the enzymes and a chemotactic response to gradients of their substrate, which leads to a substrate-mediated effective interaction between enzymes. These interactions constitute a purely non-equilibrium effect and show exotic features such as non-reciprocity. Here, we analytically study a model describing the phase separation of a mixture of such catalytically active particles. We show that a Michaelis-Menten-like dependence of the particles' activities manifests itself as a screening of the interactions, and that a mixture of two differently sized active species can exhibit phase separation with transient oscillations. We also derive a rich stability phase diagram for a mixture of two species with both concentration-dependent activity and size dispersity. This work highlights the variety of possible phase separation behaviours in mixtures of chemically active particles, which provides an alternative pathway to the passive interactions more commonly associated with phase separation in cells. Our results highlight non-equilibrium organizing principles that can be important for biologically relevant liquid-liquid phase separation.

Active, Yet Little Mobility: Asymmetric Decomposition of H2O2 Is Not Sufficient in Propelling Catalytic Micromotors

A popular principle in designing chemical micromachines is to take advantage of asymmetric chemical reactions such as the catalytic decomposition of H₂O₂. Contrary to intuition, we use Janus micromotors half-coated with platinum (Pt) or catalase as an example to show that this ingredient is not sufficient in powering a micromotor into self-propulsion. In particular, by annealing a thin Pt film on a SiO₂ microsphere, the resulting microsphere half-decorated with discrete Pt nanoparticles swims ∼80% more slowly than its unannealed counterpart in H₂O₂, even though they both catalytically produce comparable amounts of oxygen. Similarly, SiO₂ microspheres half-functionalized with the enzyme catalase show negligible self-propulsion despite high catalytic activity toward decomposing H₂O₂. In addition to highlighting how surface morphology of a catalytic cap enables/disables a chemical micromotor, this study offers a refreshed perspective in understanding how chemistry powers nano- and microscopic objects (or not): our results are consistent with a self-electrophoresis mechanism that emphasizes the electrochemical decomposition of H₂O₂ over nonelectrochemical pathways. More broadly, our finding is a critical piece of the puzzle in understanding and designing nano- and micromachines, in developing capable model systems of active colloids, and in relating enzymes to active matter.

Nanoscale Catalyst Chemotaxis Can Drive the Assembly of Functional Pathways

Recent experiments demonstrate molecular chemotaxis or altered diffusion rates of enzymes in the presence of their own substrates. We show here an important implication, namely, that if a nanoscale catalyst A produces a small-molecule ligand product L which is the substrate of another catalyst B, the two catalysts will attract each other. We explore this nonequilibrium producer recruitment force (ProRec) in a reaction-diffusion model. The predicted cat-cat association will be the strongest when A is a fast producer of L and B is a tight binder to it. ProRec is a force that could drive a mechanism (the catpath mechanism) by which catalysts could become spatially localized into functional pathways, such as in the biochemical networks in cells, which can achieve complex goals.

Conformation-changing enzymes and macromolecular crowding

We study how crowding affects the activity and catalysis-enhanced diffusion of enzymes and passive tracers by employing a fluctuating-dumbbell model of conformation-changing enzymes. Our Brownian dynamics simulations reveal that the diffusion of enzymes depends qualitatively on the type of crowding. If only enzymes are present in the system, the catalysis-induced enhancement of the enzyme diffusion - somewhat counter-intuitively - increases with crowding, while it decreases if crowding is due to inert particles. For the tracers, the diffusion enhancement increases with increasing the enzyme concentration. We also show how the enzyme activity is reduced by crowding and propose a simple expression to describe this reduction. Our results highlight subtle effects at play concerning enzymatic activity and macromolecular transport in crowded systems, such as, e.g., the interior of living cells.

Immune phase transition under steroid treatment

The steroid hormone glucocorticoid (GC) is a well-known immunosuppressant that controls T-cell-mediated adaptive immune response. In this work, we have developed a minimal kinetic network model of T-cell regulation connecting relevant experimental and clinical studies to quantitatively understand the long-term effects of GC on pro-inflammatory T-cell (T_{pro}) and anti-inflammatory T-cell (T_{anti}) dynamics. Due to the antagonistic relation between these two types of T cells, their long-term steady-state population ratio helps us to characterize three classified immune regulations: (i) weak ([T_{pro}]>[T_{anti}]), (ii) strong ([T_{pro}]<[T_{anti}]), and (iii) moderate ([T_{pro}]∼[T_{anti}]), holding the characteristic bistability. In addition to the differences in their long-term steady-state outcome, each immune regulation shows distinct dynamical phases. In the presteady state, a characteristic intermediate stationary phase is observed to develop only in the moderate regulation regime. In the medicinal field, the resting time in this stationary phase is distinguished as a clinical latent period. GC dose-dependent steady-state analysis shows an optimal level of GC to drive a phase transition from the weak or autoimmune prone to the moderate regulation regime. Subsequently, the presteady state clinical latent period tends to diverge near that optimal GC level where [T_{pro}]:[T_{anti}] is highly balanced. The GC-optimized elongated stationary phase explains the rationale behind the requirement of long-term immune diagnostics, especially when long-term GC-based chemotherapeutics and other immunosuppressive drugs are administrated. Moreover, our study reveals GC sensitivity of clinical latent period, which might serve as an early warning signal in diagnosing different immune phases and determining immune phasewise steroid treatment.

Chemically-powered swimming and diffusion in the microscopic world

The past decade has seen intriguing reports and heated debates concerning the chemically-driven enhanced motion of objects ranging from small molecules to millimetre-size synthetic robots. These objects, in solutions in which chemical reactions were occurring, were observed to diffuse (spread non-directionally) or swim (move directionally) at rates exceeding those expected from Brownian motion alone. The debates have focused on whether observed enhancement is an experimental artefact or a real phenomenon. If the latter were true, then we would also need to explain how the chemical energy is converted into mechanical work. In this Perspective, we summarize and discuss recent observations and theories of active diffusion and swimming. Notably, the chemomechanical coupling and magnitude of diffusion enhancement are strongly size-dependent and should vanish as the size of the swimmers approaches the molecular scale. We evaluate the reliability of common techniques to measure diffusion coefficients and finish by considering the potential applications and chemical to mechanical energy conversion efficiencies of typical nanoswimmers and microswimmers.

Driving forces in the origins of life

What were the physico-chemical forces that drove the origins of life? We discuss four major prebiotic ‘discoveries’: persistent sampling of chemical reaction space; sequence-encodable foldable catalysts; assembly of functional pathways; and encapsulation and heritability. We describe how a ‘proteins-first’ world gives plausible mechanisms. We note the importance of hydrophobic and polar compositions of matter in these advances.

Comment on “Boosted molecular mobility during common chemical reactions”

The apparent “boosted mobility” observed by Wang et al. (Reports, 31 July 2020, p. 537) is the result of a known artifact. When signal intensities are changing during a nuclear magnetic resonance (NMR) diffusion measurement for reasons other than diffusion, the use of monotonically increasing gradient amplitudes produces erroneous diffusion coefficients. We show that no boosted molecular mobility is observed when shuffled gradient amplitudes are applied.

Membrane Surface Modulates Slow Diffusion in Small Crowded Droplets

Membranes are ubiquitous structures in cells. The effects of membranes on various functional molecules have been reported, but their behaviors under macromolecular crowding and cell-sized confinement have not fully been understood. In this study, we model an intracellular environment by crowding micrometer-sized droplets and investigate the effects of membrane properties on molecular diffusion. The molecular diffusion inside small droplets covered with a lipid layer of phosphatidylcholine (PC) becomes slower compared with that of the corresponding bulk solutions under a crowding condition of polysaccharide dextran but not of its monomer unit, glucose. The addition of a poly(ethylene glycol) conjugated lipid (PEGylated lipid) to the PC membrane significantly alters the degree of slow diffusion observed inside small droplets of concentrated dextran. Interestingly, the change is not monotonic against dextran concentration; that is, the PEGylated membrane increases and decreases the degree of slow diffusion with increasing dextran concentration. We explain the nonmonotonic alternation from the increase in effective dextran concentration and the hindered temporal adsorption of dextran to the membrane. Because diffusion alteration by adding PEGylated lipid is observed for condensed small droplets of linear polymer PEG and hydrophilic protein bovine serum albumin, the phenomenon is general for other polymer systems as well. Furthermore, our findings may facilitate the understanding of intracellular molecular behaviors based on membrane effects as well as the development of numerous applications using polymer droplets.

Master curve of boosted diffusion for 10 catalytic enzymes

The literature is inconsistent regarding evidence for boosted molecular mobility during enzyme catalysis, a phenomenon that challenges the common tenet that enzyme mobility is governed solely by Brownian motion. This paper surveys 10 different catalytic enzymes and shows that magnitude of enhanced diffusion scales with energy release rate, the Gibbs free energy of reaction multiplied by the Michaelis–Menten reaction rate. A practical implication is that boosted effective diffusivity can be used to determine the energetics associated with enzyme action, since effective enzyme diffusivity is simply proportional to the change in free energy associated with the biochemical conversion. This master curve to predict the magnitude of boosted molecular mobility may be useful for estimating the effect in as-yet untested enzymes.

Molecular agitation more rapid than thermal Brownian motion is reported for cellular environments, motor proteins, synthetic molecular motors, enzymes, and common chemical reactions, yet that chemical activity coupled to molecular motion contrasts with generations of accumulated knowledge about diffusion at equilibrium. To test the limits of this idea, a critical testbed is the mobility of catalytically active enzymes. Sentiment is divided about the reality of enhanced enzyme diffusion, with evidence for and against. Here a master curve shows that the enzyme diffusion coefficient increases in proportion to the energy release rate—the product of Michaelis-Menten reaction rate and Gibbs free energy change (ΔG)—with a highly satisfactory correlation coefficient of 0.97. For 10 catalytic enzymes (urease, acetylcholinesterase, seven enzymes from the glucose cascade cycle, and one other), our measurements span from a roughly 40% enhanced diffusion coefficient at a high turnover rate and negative ΔG to no enhancement at a slow turnover rate and positive ΔG. Moreover, two independent measures of mobility show consistency, provided that one avoids undesirable fluorescence photophysics. The master curve presented here quantifies the limits of both ideas, that enzymes display enhanced diffusion and that they do not within instrumental resolution, and has possible implications for understanding enzyme mobility in cellular environments. The striking linear dependence of ΔG for the exergonic enzymes (ΔG <0), together with the vanishing effect for endergonic enzyme (ΔG >0), are consistent with a physical picture in which the mechanism boosting the diffusion is an active one, utilizing the available work from the chemical reaction.

Boosted molecular mobility during common chemical reactions

Mobility of reactants and nearby solvent is more rapid than Brownian diffusion during several common chemical reactions when the energy release rate exceeds a threshold. Screening a family of 15 organic chemical reactions, we demonstrate the largest boost for catalyzed bimolecular reactions, click chemistry, ring-opening metathesis polymerization, and Sonogashira coupling. Boosted diffusion is also observed but to lesser extent for the uncatalyzed Diels-Alder reaction, but not for substitution reactions SN1 and SN2 within instrumental resolution. Diffusion coefficient increases as measured by pulsed-field gradient nuclear magnetic resonance, whereas in microfluidics experiments, molecules in reaction gradients migrate “uphill” in the direction of lesser diffusivity. This microscopic consumption of energy by chemical reactions transduced into mechanical motion presents a form of active matter.

Enzyme catalysis powered micro/nanomotors for biomedical applications

This review provides insights on enzyme powered motors using fuels present in biological environments for biomedical applications.