Effects of macromolecular crowding on genetic networks

Field theory of enzyme-substrate systems with restricted long-range interactions

Enzyme-substrate kinetics form the basis of many biomolecular processes. The interplay between substrate binding and substrate geometry can give rise to long-range interactions between enzyme binding events. Here we study a general model of enzyme-substrate kinetics with restricted long-range interactions described by an exponent -γ. We employ a coherent-state path integral and renormalization group approach to calculate the first moment and two-point correlation function of the enzyme-binding profile. We show that starting from an empty substrate the average occupancy follows a power law with an exponent 1/(1-γ) over time. The correlation function decays algebraically with two distinct spatial regimes characterized by exponents -γ on short distances and -(2/3)(2-γ) on long distances. The crossover between both regimes scales inversely with the average substrate occupancy. Our work allows associating experimental measurements of bound enzyme locations with their binding kinetics and the spatial conformation of the substrate.

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments

Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.

Molecular crowding effect in Hantzch pyridine synthesis in polyethylene glycol aqueous solution

In a molecular crowding environment, the kinetics and thermodynamics differ from those in a diluted solution. Although the molecular crowding effect has been extensively investigated, its fundamental kinetics and thermodynamics remain unclear. In this study, we investigated the change in the rate constant (k) of the Hantzch pyridine reaction in a molecular crowding environment using polyethylene glycol (PEG). While the k value increased to a PEG concentration (CPEG) of 10 vol%, a decreasing trend was observed for CPEG > 20 vol%. This intriguing behavior was analyzed based on the increase in reactant activity due to volume exclusion and the decrease in water activity due to osmotic pressure. Volume exclusion and osmotic pressure had opposing effects on the reaction, which were positive for volume exclusion and negative for osmotic pressure. We found that k decreased when the negative effect of the osmotic pressure surpassed the volume exclusion effect.

Hydrogel-Based Multi-enzymatic System for Biosynthesis

Biosynthesis involving multi-enzymatic reactions is usually an efficient and economic method to produce plentiful important molecules. To increase the product yield in biosynthesis, the involved enzymes can be immobilized to carriers for enhancing enzyme stability, increasing synthesis efficiency and improving enzyme recyclability. Hydrogels with three-dimensional porous structures and versatile functional groups are promising carriers for enzyme immobilization. Herein, we review the recent advances of the hydrogel-based multi-enzymatic system for biosynthesis. First, we introduce the strategies of enzyme immobilization in hydrogel, including the pros and cons of the strategies. Then we overview the recent applications of the multi-enzymatic system for biosynthesis, including cell-free protein synthesis (CFPS) and non-protein synthesis, especially high value-added molecules. In the last section, we discuss the future perspective of the hydrogel-based multi-enzymatic system for biosynthesis.

J-aggregation of 5, 10, 15, 20-tetraphenyl-21H, 23H-porphinetetrasulfonic acid in a molecular crowding environment simulated using dextran

In a molecular crowding environment, different thermodynamics is often observed in a dilute solution. One such example is the promotion of the formation of amyloids, which are causal agents of Alzheimer's disease. Although a considerable number of molecular crowding studies have been reported, its effect remains unclear. In this study, we investigated a J-aggregation of a porphyrin derivative, 5, 10, 15, 20-tetraphenyl-21H,23H-porphinetetrasulfonic acid (TPPS), in a molecular crowding environment simulated by dextran (Dex) in HClO₄, HCl, and NaCl solutions. The changes in the number of monomers in the J-aggregate (n) with the concentration of Dex (C_Dex) depended on the type of solution. No change in n was observed in the NaCl solution, which indicated that the Dex solution did not affect the J-aggregation because of the ionic strength effect. In the HCl solution, the aggregation behavior changed with the pH. Further, at a low pH, the electrostatic interactions promoted J-aggregation by the volume exclusion of Dex, while the aggregation was suppressed at a high pH owing to steric hindrance. A different aggregation mechanism, involving the hydrogen bonding between NH in the center of the TPPS macrocyclic frame and the SO₃H and ClO₄^- functional groups, was responsible for the J-aggregation in the HClO₄ solution. Moreover, the n value increased owing to the volume exclusion effect. We expect that this study will be useful for further elucidation of the molecular crowding effect.

Influence of Nonspecific Interactions between Proteins and In Vivo Cytoplasmic Crowders in Facilitated Diffusion of Proteins: Theoretical Insights

The binding of proteins to their respective specific sites on the DNA through facilitated diffusion serves as the initial step of various important biological processes. While this search process has been thoroughly investigated via in vitro studies, the cellular environment is complex and may interfere with the protein's search dynamics. The cytosol is heavily crowded, which can potentially modify the search by nonspecifically interacting with the protein that has been mostly overlooked. In this work, we probe the target search dynamics in the presence of explicit crowding agents that have an affinity toward the protein. We theoretically investigate the role of such protein-crowder associations in the target search process using a discrete-state stochastic framework that allows for the analytical description of dynamic properties. It is found that stronger nonspecific associations between the crowder and proteins can accelerate the facilitated diffusion of proteins in comparison with a purely inert, rather weakly interacting cellular environment. This effect depends on how strong these associations are, the spatial positions of the target with respect to the crowders, and the size of the crowded region. Our theoretical results are also tested with Monte Carlo computer simulations. Our predictions are in qualitative agreement with existing experimental observations and computational studies.

Comparative study of SARS-CoV-2 infection in different cell types: Biophysical-computational approach to the role of potential receptors

Cellular susceptibility to SARS-CoV-2 infection in the respiratory tract has been associated with the ability of the virus to interact with potential receptors on the host membrane. We have modeled viral dynamics by simulating various cellular systems and artificial conditions, including macromolecular crowding, based on experimental and transcriptomic data to infer parameters associated with viral growth and predict cell susceptibility. We have accomplished this based on the type, number and level of expression of the angiotensin-converting enzyme 2 (ACE2), transmembrane serine 2 (TMPRSS2), basigin2 (CD147), FURIN protease, neuropilin 1 (NRP1) or other less studied candidate receptors such as heat shock protein A5 (HSPA5) and angiotensin II receptor type 2 (AGTR2). In parallel, we studied the effect of simulated artificial environments on the accessibility to said proposed receptors. In addition, viral kinetic behavior dependent on the degree of cellular susceptibility was predicted. The latter was observed to be more influenced by the type of proteins and expression level, than by the number of potential proteins associated with the SARS CoV-2 infection. We predict a greater theoretical propensity to susceptibility in cell lines such as NTERA-2, SCLC-21H, HepG2 and Vero6, and a lower theoretical propensity in lines such as CaLu3, RT4, HEK293, A549 and U-251MG. An important relationship was observed between expression levels, protein diffusivity, and thermodynamically favorable interactions between host proteins and the viral spike, suggesting potential sites of early infection other than the lungs. This research is expected to stimulate future quantitative experiments and promote systematic investigation of the effect of crowding presented here.

In vitro cell cycle oscillations exhibit a robust and hysteretic response to changes in cytoplasmic density

Cells control the properties of the cytoplasm to ensure proper functioning of biochemical processes. Recent studies showed that cytoplasmic density varies in both physiological and pathological states of cells undergoing growth, division, differentiation, apoptosis, senescence, and metabolic starvation. Little is known about how cellular processes cope with these cytoplasmic variations. Here, we study how a cell cycle oscillator comprising cyclin-dependent kinase (Cdk1) responds to changes in cytoplasmic density by systematically diluting or concentrating cycling Xenopus egg extracts in cell-like microfluidic droplets. We found that the cell cycle maintains robust oscillations over a wide range of deviations from the endogenous density: as low as 0.2× to more than 1.22× relative cytoplasmic density (RCD). A further dilution or concentration from these values arrested the system in a low or high steady state of Cdk1 activity, respectively. Interestingly, diluting an arrested cytoplasm of 1.22× RCD recovers oscillations at lower than 1× RCD. Thus, the cell cycle switches reversibly between oscillatory and stable steady states at distinct thresholds depending on the direction of tuning, forming a hysteresis loop. We propose a mathematical model which recapitulates these observations and predicts that the Cdk1/Wee1/Cdc25 positive feedback loops do not contribute to the observed robustness, supported by experiments. Our system can be applied to study how cytoplasmic density affects other cellular processes.

Modulating internal transition kinetics of responsive macromolecules by collective crowding

Packing and crowding are used in biology as mechanisms to (self-)regulate internal molecular or cellular processes based on collective signaling. Here, we study how the transition kinetics of an internal "switch" of responsive macromolecules is modified collectively by their spatial packing. We employ Brownian dynamics simulations of a model of Responsive Colloids, in which an explicit internal degree of freedom-here, the particle size-moving in a bimodal energy landscape self-consistently responds to the density fluctuations of the crowded environment. We demonstrate that populations and transition times for the two-state switching kinetics can be tuned over one order of magnitude by "self-crowding." An exponential scaling law derived from a combination of Kramers' and liquid state perturbation theory is in very good agreement with the simulations.

Macromolecular cryoprotectants for the preservation of mammalian cell culture: lessons from crowding, overview and perspectives

Cryopreservation is a process used for the storage of mammalian cells at a very low temperature, in a state of 'suspended animation.' Highly effective and safe macromolecular cryoprotectants (CPAs) have gained significant attention as they obviate the toxicity of conventional CPAs like dimethyl sulfoxide (DMSO) and reduce the risks involved in the storage of cultures at liquid nitrogen temperatures. These agents provide cryoprotection through multiple mechanisms, involving extracellular and intracellular macromolecular crowding, thereby impacting the biophysical and biochemical dynamics of the freezing medium and the cryopreserved cells. These CPAs vary in their structures and physicochemical properties, which influence their cryoprotective activities. Moreover, the introduction of polymeric crowders in the cryopreservation media enables serum-free storage at low-DMSO concentrations and high-temperature vitrification of frozen cultures (-80 °C). This review highlights the need for macromolecular CPAs and describes their mechanisms of cryopreservation, by elucidating the role of crowding effects. It also classifies the macromolecules based on their chemistry and their structure-activity relationships. Furthermore, this article provides perspectives on the factors that may influence the outcomes of the cell freezing process or may help in designing and evaluating prospective macromolecules. This manuscript also includes case studies about cellular investigations that have been conducted to demonstrate the cryoprotective potential of macromolecular CPAs. Ultimately, this review provides essential directives that will further improve the cell cryopreservation process and may encourage the use of macromolecular CPAs to fortify basic, applied, and translational research.

Effect of Molecular Crowding on Complexation of Metal Ions and 8-Quinolinol-5-Sulfonic Acid

The effect of molecular crowding on macromolecular reactions has been revealed by many researchers. In this study, we investigate the complexation of metal ions (Zn, Co, and Cd) with 8-quinolinol-5-sulfonic acid as a model of small-molecular reactions in molecular crowding. The complexation constants for 1:1, 1:2, and total complexation in the presence of polyethylene glycol (PEG, a molecular crowding reagent) are evaluated based on the increase in the reactant activity by volume exclusion and the decrease in the water activity due to the change in osmotic pressure. All complexation constants are enhanced by increasing the concentration of PEG. Its mechanisms differ for 1:1, 1:2, and total complexation. The 1:1 complexation is promoted only by the influence of the water activity, while the reactant and water activities influence the increase in the 1:2 complexation constant. Increasing the molecular weight of PEG further increases the complexation constants, as dehydration of the complex is promoted by a higher hydration number of PEG. Because this study gives the fundamental knowledge for the protein-metal interaction, in which solvation is an important factor, in molecular crowding, it provides new insights into molecular crowding studies and should attract the attention of a broad spectrum of biochemistry researchers.

It is time to crowd your cell culture media - Physicochemical considerations with biological consequences

In vivo, the interior and exterior of cells is populated by various macromolecules that create an extremely crowded milieu. Yet again, in vitro eukaryotic cell culture is conducted in dilute culture media that hardly imitate the native tissue density. Herein, the concept of macromolecular crowding is discussed in both intracellular and extracellular context. Particular emphasis is given on how the physicochemical properties of the crowding molecules govern and determine kinetics, equilibria and mechanism of action of biochemical and biological reactions, processes and functions. It is evidenced that we are still at the beginning of appreciating, let alone effectively implementing, the potential of macromolecular crowding in permanently differentiated and stem cell culture systems.

Concentration sensing in crowded environments

Signal transduction within crowded cellular compartments is essential for the physiological function of cells. Although the accuracy with which receptors can probe the concentration of ligands has been thoroughly investigated in dilute systems, the effect of macromolecular crowding on the inference of concentration remains unclear. In this work, we develop an algorithm to simulate reversible reactions between reacting Brownian particles. Our algorithm facilitates the calculation of reaction rates and correlation times for ligand-receptor systems in the presence of macromolecular crowding. Using this method, we show that it is possible for crowding to increase the accuracy of estimated ligand concentration based on receptor occupancy. In particular, we find that crowding can enhance the effective association rates between small ligands and receptors to a degree sufficient to overcome the increased chance of rebinding due to caging by crowding molecules. For larger ligands, crowding decreases the accuracy of the receptor's estimate primarily by decreasing the microscopic association and dissociation rates.

Bioinspired in vitro microenvironments to control cell fate: focus on macromolecular crowding

The development of therapeutic regenerative medicine and accurate drug discovery cell-based products requires effective, with respect to obtaining sufficient numbers of viable, proliferative, and functional cell populations, cell expansion ex vivo. Unfortunately, traditional cell culture systems fail to recapitulate the multifaceted tissue milieu in vitro, resulting in cell phenotypic drift, loss of functionality, senescence, and apoptosis. Substrate-, environment-, and media-induced approaches are under intense investigation as a means to maintain cell phenotype and function while in culture. In this context, herein, the potential of macromolecular crowding, a biophysical phenomenon with considerable biological consequences, is discussed.

Growth factor and macromolecular crowding supplementation in human tenocyte culture

Cell-assembled tissue engineering strategies hold great potential in regenerative medicine, as three-dimensional tissue-like modules can be produced, even from a patient's own cells. However, the development of such implantable devices requires prolonged in vitro culture time, which is associated with cell phenotypic drift. Considering that the cells in vivo are subjected to numerous stimuli, multifactorial approaches are continuously gaining pace towards controlling cell fate during in vitro expansion. Herein, we assessed the synergistic effect of simultaneous and serial growth factor supplementation (insulin growth factor-1, platelet-derived growth factor ββ, growth differentiation factor 5 and transforming growth factor β3) to macromolecular crowding (carrageenan) in human tenocyte function; collagen synthesis and deposition; and gene expression. TGFβ3 supplementation (without/with carrageenan) induced the highest (among all groups) DNA content. In all cases, tenocyte proliferation was significantly increased as a function of time in culture, whilst metabolic activity was not affected. Carrageenan supplementation induced significantly higher collagen deposition than groups without carrageenan (without/with any growth factor). Of all the growth factors used, TGFβ3 induced the highest collagen deposition when used together with carrageenan in both simultaneous and serial fashion. At day 13, gene expression analysis revealed that TGFβ3 in serial supplementation to carrageenan upregulated the most and downregulated the least collagen- and tendon- related genes and upregulated the least and downregulated the most osteo-, chondro-, fibrosis- and adipose- related trans-differentiation genes. Collectively, these data clearly advocate the beneficial effects of multifactorial approaches (in this case, growth factor and macromolecular crowding supplementation) in the development of functional cell-assembled tissue surrogates.

Development of a robust Escherichia coli-based cell-free protein synthesis application platform

•

A robust cell-free protein synthesis platform has been developed.

•

Engineering strategies were explored to improve the synthesis efficiency.

•

The platform has been applied in prototyping, screening and on-demand synthesis.

Since the cell-free protein synthesis system is not limited by the cell growth, all the substrates are used to produce the protein of interest, and the reaction environment can be flexibly controlled. All the advantages allow it to synthesize toxic proteins, membrane proteins, and unnatural proteins that are difficult to make in vivo. However, one typical reason why the cell-free system has not been widely accepted as a practical alternative, is its expression efficiency problem. The Escherichia coli-based system was chosen in this study, and the model protein deGFP was expressed to explore a more efficient cell-free system. The results showed that Mg²⁺ with a concentration of 15 mM in the cell-free system with BL21 Star (DE3) as the extract could better synthesize protein. The smaller the vectors, the lighter the burden, the higher the protein synthesis. Simulating the crowding effect in the cell does not improve the protein expression efficiency of the optimized cell-free protein synthesis system. Based on the optimized system, the cell-free fundamental research platform, primary screening platform, and portable biomolecular synthesis platform were established. This study provides a robust cell-free protein synthesis toolbox with easy extract preparation and high protein yield. It also enables more researchers to reap the benefits from the cell-free biosynthesis platform.

Silk fibroin as an additive for cell-free protein synthesis

Cell-free systems contain many proteins and metabolites required for complex functions such as transcription and translation or multi-step metabolic conversions. Research into expanding the delivery of these systems by drying or by embedding into other materials is enabling new applications in sensing, point-of-need manufacturing, and responsive materials. Meanwhile, silk fibroin from the silk worm, Bombyx mori, has received attention as a protective additive for dried enzyme formulations and as a material to build biocompatible hydrogels for controlled localization or delivery of biomolecular cargoes. In this work, we explore the effects of silk fibroin as an additive in cell-free protein synthesis (CFPS) reactions. Impacts of silk fibroin on CFPS activity and stability after drying, as well as the potential for incorporation of CFPS into hydrogels of crosslinked silk fibroin are assessed. We find that simple addition of silk fibroin increased productivity of the CFPS reactions by up to 42%, which we attribute to macromolecular crowding effects. However, we did not find evidence that silk fibroin provides a protective effects after drying as previously described for purified enzymes. Further, the enzymatic crosslinking transformations of silk fibroin typically used to form hydrogels are inhibited in the presence of the CFPS reaction mixture. Crosslinking attempts did not impact CFPS activity, but did yield localized protein aggregates rather than a hydrogel. We discuss the mechanisms at play in these results and how the silk fibroin-CFPS system might be improved for the design of cell-free devices.

Molecular crowding and conserved interface interactions of human argonaute protein-miRNA-target mRNA complex

RNA interference (RNAi) has been of interest given its role in genetic interference. More significantly, recent studies provided evidence of it being one of the antiviral response mechanisms in humans. Argonaute (Ago) protein plays a central role in the RNA-induced silencing complex (RISC) that cleaves mRNA. Molecular crowding in cellular systems is known to impact dynamics and interactions of biomolecules. We present here the results from our molecular dynamics simulations based study on the interfaces between Ago, miRNA and Target RNA in presence of molecular crowders. 6 simulations at 3 crowder concentrations, including the aqueous condition, were performed. Our results indicate that crowding changes the dynamics, makes the complex stabler and aids binding free energy. More importantly, features conserved across the three systems and amino acid residues with crowding resilient interactions with RNA are identified.Communicated by Ramaswamy H. Sarma.

A comparative study of semi-flexible linear and ring polymer conformational change in an anisotropic environment

We adopt a Langevin-dynamics based simulation to systematically study the conformational change of a semi-flexible probed polymer in a rod crowding environment. Two topologically different probed polymer types, linear and ring polymers, are specifically considered. Our results unravel the significance of the interplay of probed polymer's semi-flexibility and crowding anisotropy. Firstly, both ring and linear polymers show a non-trivial dimensional change including nonmonotonicity and collapse-swelling crossover as their stiffness increases. Secondly, we modulate rod crowder length to investigate the anisotropic effect. We reveal that the formation of an ordered parallel arrangement of the environment can effectively lead to a remarkable stretching effect on the probed polymer. The coupling between the crowding anisotropy-induced stretching and the polymer stiffness can account for the unusual swelling behavior. Lastly, nonmonotonic swelling and shape change of the ring polymer are analyzed. We find out that the ring polymer is subject to most pronounced swelling at robust stiffness. Moreover, the maximum prolate shape is also observed at the same robust location.

Structural Basis of Enhanced Facilitated Diffusion of DNA-Binding Protein in Crowded Cellular Milieu

Although the fast association between DNA-binding proteins (DBPs) and DNA is explained by a facilitated diffusion mechanism, in which DBPs adopt a weighted combination of three-dimensional diffusion and one-dimensional (1D) sliding and hopping modes of transportation, the role of cellular environment that contains many nonspecifically interacting proteins and other biomolecules is mostly overlooked. By performing large-scale computational simulations with an appropriately tuned model of protein and DNA in the presence of nonspecifically interacting bulk and DNA-bound crowders (genomic crowders), we demonstrate the structural basis of the enhanced facilitated diffusion of DBPs inside a crowded cellular milieu through, to our knowledge, novel 1D scanning mechanisms. In this one-dimensional scanning mode, the protein can float along the DNA under the influence of nonspecific interactions of bulk crowder molecules. The search mode is distinctly different compared to usual 1D sliding and hopping dynamics in which protein diffusion is regulated by the DNA electrostatics. In contrast, the presence of genomic crowders expedites the target search process by transporting the protein over DNA segments through the formation of a transient protein-crowder bridged complex. By analyzing the ruggedness of the associated potential energy landscape, we underpin the molecular origin of the kinetic advantages of these search modes and show that they successfully explain the experimentally observed acceleration of facilitated diffusion of DBPs by molecular crowding agents and crowder-concentration-dependent enzymatic activity of transcription factors. Our findings provide crucial insights into gene regulation kinetics inside the crowded cellular milieu.

Disordered chromatin packing regulates phenotypic plasticity

Three-dimensional supranucleosomal chromatin packing plays a profound role in modulating gene expression by regulating transcription reactions through mechanisms such as gene accessibility, binding affinities, and molecular diffusion. Here, we use a computational model that integrates disordered chromatin packing (CP) with local macromolecular crowding (MC) to study how physical factors, including chromatin density, the scaling of chromatin packing, and the size of chromatin packing domains, influence gene expression. We computationally and experimentally identify a major role of these physical factors, specifically chromatin packing scaling, in regulating phenotypic plasticity, determining responsiveness to external stressors by influencing both intercellular transcriptional malleability and heterogeneity. Applying CPMC model predictions to transcriptional data from cancer patients, we identify an inverse relationship between patient survival and phenotypic plasticity of tumor cells.

Hyaluronic acid as a macromolecular crowding agent for production of cell-derived matrices

Cell-derived matrices (CDMs) provide an exogenous source of human extracellular matrix (ECM), with applications as cell delivery vehicles, substrate coatings for cell attachment and differentiation, and as biomaterial scaffolds. However, commercial application of CDMs has been hindered due to the prolonged culture time required for sufficient ECM accumulation. One approach to increasing matrix deposition in vitro is macromolecular crowding (MMC), which is a biophysical phenomenon that limits the diffusion of ECM precursor proteins, resulting in increased ECM accumulation at the cell layer. Hyaluronic acid (HA), a natural MMC highly expressed in vivo during fetal development, has been shown to play a role in ECM production, but has not been investigated as a macromolecule for increasing cell-mediated ECM deposition in vitro. In the current study, we hypothesized that HA can act as a MMC, and increase cell-mediated ECM production. Human dermal fibroblasts were cultured for 3, 7, or 14 days with 0%, 0.05%, or 0.5% high molecular weight HA. Ficoll 70/400 was used as a positive control. SDS-PAGE, Sircol, and hydroxyproline assays indicated that 0.05% HA-treated cultures had significantly higher mean collagen deposition at 14 days, whereas Ficoll 70/400-treated cultures had significantly lower collagen production compared to the HA and untreated controls. However, fluorescent immunostaining of ECM proteins and quantification of mean gray values did not indicate statistically significant differences in ECM production in HA or Ficoll 70/400-treated cultures compared to untreated controls. Raman imaging (a marker-free spectral imaging method) indicated that HA increased ECM deposition in human dermal fibroblasts. These results are consistent with decreases in CDM stiffness observed in Ficoll 70/400-treated cultures by atomic force microscopy. Overall, these results indicate that there are macromolecule- and cell type- dependent effects on matrix assembly, turnover, and stiffness in cell-derived matrices. STATEMENT OF SIGNIFICANCE: Cell-derived matrices (CDMs) are versatile biomaterials with many regenerative medicine applications, including as cell and drug delivery vehicles and scaffolds for wound healing and tissue regeneration. While CDMs have several advantages, their commercialization has been limited due to the prolonged culture time required to achieve CDM synthesis in vitro. In this study, we explored the use of hyaluronic acid (HA) as a macromolecular crowder in human fibroblast cell cultures to support production of CDM biomaterials. Successful application of macromolecular crowding will allow development of human cell-derived, xeno-free biomaterials that re-capitulate the native human tissue microenvironment.

Understanding biochemical processes in the presence of sub-diffusive behavior of biomolecules in solution and living cells

In order to maintain cellular function, biomolecules like protein, DNA, and RNAs have to diffuse to the target spaces within the cell. Changes in the cytosolic microenvironment or in the nucleus during the fulfillment of these cellular processes affect their mobility, folding, and stability thereby impacting the transient or stable interactions with their adjacent neighbors in the organized and dynamic cellular interior. Using classical Brownian motion to elucidate the diffusion behavior of these biomolecules is hard considering their complex nature. The understanding of biomolecular diffusion inside cells still remains elusive due to the lack of a proper model that can be extrapolated to these cases. In this review, we have comprehensively addressed the progresses in this field, laying emphasis on the different aspects of anomalous diffusion in the different biochemical reactions in cell interior. These experiment-based models help to explain the diffusion behavior of biomolecules in the cytosolic and nuclear microenvironment. Moreover, since understanding of biochemical reactions within living cellular system is our main focus, we coupled the experimental observations with the concept of sub-diffusion from in vitro to in vivo condition. We believe that the pairing between the understanding of complex behavior and structure-function paradigm of biological molecules would take us forward by one step in order to solve the puzzle around diseases caused by cellular dysfunction.

Mechanical Interaction between Cells Facilitates Molecular Transport

In vivo, eukaryotic cells are embedded in a matrix environment, where they grow and develop. Generally, this extracellular matrix (ECM) is an anisotropic fibrous structure, through which macromolecules and biochemical signaling molecules at the nanometer scale diffuse. The ECM is continuously remodeled by cells, via mechanical interactions, which lead to a potential link between biomechanical and biochemical cell-cell interactions. Here, it is studied how cell-induced forces applied on the ECM impact the biochemical transport of molecules between distant cells. It is experimentally observed that cells remodel the ECM by increasing fiber alignment and density of the matrix between them over time. Using random walk simulations on a 3D lattice, elongated fixed obstacles are implemented that mimic the fibrous ECM structure. Both diffusion of a tracer molecule and the mean first-passage time a molecule secreted from one cell takes to reach another cell are measured. The model predicts that cell-induced remodeling can lead to a dramatic speedup in the transport of molecules between cells. Fiber alignment and densification cause reduction of the transport dimensionality from a 3D to a much more rapid 1D process. Thus, a novel mechanism of mechano-biochemical feedback in the regulation of long-range cell-cell communication is suggested.

eGFRD in all dimensions

Biochemical reactions often occur at low copy numbers but at once in crowded and diverse environments. Space and stochasticity therefore play an essential role in biochemical networks. Spatial-stochastic simulations have become a prominent tool for understanding how stochasticity at the microscopic level influences the macroscopic behavior of such systems. While particle-based models guarantee the level of detail necessary to accurately describe the microscopic dynamics at very low copy numbers, the algorithms used to simulate them typically imply trade-offs between computational efficiency and biochemical accuracy. eGFRD (enhanced Green's Function Reaction Dynamics) is an exact algorithm that evades such trade-offs by partitioning the N-particle system into M ≤ N analytically tractable one- and two-particle systems; the analytical solutions (Green's functions) then are used to implement an event-driven particle-based scheme that allows particles to make large jumps in time and space while retaining access to their state variables at arbitrary simulation times. Here we present "eGFRD2," a new eGFRD version that implements the principle of eGFRD in all dimensions, thus enabling efficient particle-based simulation of biochemical reaction-diffusion processes in the 3D cytoplasm, on 2D planes representing membranes, and on 1D elongated cylinders representative of, e.g., cytoskeletal tracks or DNA; in 1D, it also incorporates convective motion used to model active transport. We find that, for low particle densities, eGFRD2 is up to 6 orders of magnitude faster than conventional Brownian dynamics. We exemplify the capabilities of eGFRD2 by simulating an idealized model of Pom1 gradient formation, which involves 3D diffusion, active transport on microtubules, and autophosphorylation on the membrane, confirming recent experimental and theoretical results on this system to hold under genuinely stochastic conditions.

Multiscale simulations of anisotropic particles combining molecular dynamics and Green's function reaction dynamics

The modeling of complex reaction-diffusion processes in, for instance, cellular biochemical networks or self-assembling soft matter can be tremendously sped up by employing a multiscale algorithm which combines the mesoscopic Green's Function Reaction Dynamics (GFRD) method with explicit stochastic Brownian, Langevin, or deterministic molecular dynamics to treat reactants at the microscopic scale [A. Vijaykumar, P. G. Bolhuis, and P. R. ten Wolde, J. Chem. Phys. 143, 214102 (2015)]. Here we extend this multiscale MD-GFRD approach to include the orientational dynamics that is crucial to describe the anisotropic interactions often prevalent in biomolecular systems. We present the novel algorithm focusing on Brownian dynamics only, although the methodology is generic. We illustrate the novel algorithm using a simple patchy particle model. After validation of the algorithm, we discuss its performance. The rotational Brownian dynamics MD-GFRD multiscale method will open up the possibility for large scale simulations of protein signalling networks.

Transcription factor target site search and gene regulation in a background of unspecific binding sites

Response time and transcription level are vital parameters of gene regulation. They depend on how fast transcription factors (TFs) find and how efficient they occupy their specific target sites. It is well known that target site search is accelerated by TF binding to and sliding along unspecific DNA and that unspecific associations alter the occupation frequency of a gene. However, whether target site search time and occupation frequency can be optimized simultaneously is mostly unclear. We developed a transparent and intuitively accessible state-based formalism to calculate search times to target sites on and occupation frequencies of promoters of arbitrary state structure. Our formalism is based on dissociation rate constants experimentally accessible in live cell experiments. To demonstrate our approach, we consider promoters activated by a single TF, by two coactivators or in the presence of a competitive inhibitor. We find that target site search time and promoter occupancy differentially vary with the unspecific dissociation rate constant. Both parameters can be harmonized by adjusting the specific dissociation rate constant of the TF. However, while measured DNA residence times of various eukaryotic TFs correspond to a fast search time, the occupation frequencies of target sites are generally low. Cells might tolerate low target site occupancies as they enable timely gene regulation in response to a changing environment.

Sugar osmolytes-induced stabilization of RNase A in macromolecular crowded cellular environment

Organisms synthesize sugar osmolytes during environmental stresses to protect proteins against denaturation. These studies were carried out in dilute buffer whereas intracellular milieu within cells has cytoplasmic concentration of macromolecules in the range of 80-400 mg ml^-1. Is the stabilizing effect of sugar osmolytes on the protein in dilute buffer different from that when protein is in cellular environment? To answer this question, we have measured and analysed the effect of sugar osmolytes on the structural and thermodynamic stability of ribonuclease A in the presence of dextran 70 at multiple concentrations of six sugars at different pH values. It was found that (i) each sugar osmolyte in the crowded environment provides stability to the protein in terms of T_m (midpoint of denaturation) and ∆G_D° (Gibbs energy change) and this stabilizing effect is under entropic control, (ii) the extent of osmolyte-induced stabilization of RNase A is pH dependent, and (iii) effect of sugars on the stability of protein in presence of the crowding agent remains unchanged. This study concludes that crowding does not affect the efficacy of osmolytes and vice versa; and emphasizes on understanding of internal architecture of the cellular environment with respect to molecular and macromolecular crowding.

Automated cell cycle and cell size measurements for single-cell gene expression studies

OBJECTIVES

Recent rise of single-cell studies revealed the importance of understanding the role of cell-to-cell variability, especially at the transcriptomic level. One of the numerous sources of cell-to-cell variation in gene expression is the heterogeneity in cell proliferation state. In order to identify how cell cycle and cell size influences gene expression variability at the single-cell level, we provide an universal and automatic toxic-free label method, compatible with single-cell high-throughput RT-qPCR. The method consists of isolating cells after a double-stained, analyzing their morphological parameters and performing a transcriptomic analysis on the same identified cells.

RESULTS

This led to an unbiased gene expression analysis and could be also used for improving single-cell tracking and imaging when combined with cell isolation. As an application for this technique, we showed that cell-to-cell variability in chicken erythroid progenitors was negligibly influenced by cell size nor cell cycle.

Macrogenomic engineering via modulation of the scaling of chromatin packing density

Many human diseases result from the dysregulation of the complex interactions between tens to thousands of genes. However, approaches for the transcriptional modulation of many genes simultaneously in a predictive manner are lacking. Here, through the combination of simulations, systems modelling and in vitro experiments, we provide a physical regulatory framework based on chromatin packing-density heterogeneity for modulating the genomic information space. Because transcriptional interactions are essentially chemical reactions, they depend largely on the local physical nanoenvironment. We show that the regulation of the chromatin nanoenvironment allows for the predictable modulation of global patterns in gene expression. In particular, we show that the rational modulation of chromatin density fluctuations can lead to a decrease in global transcriptional activity and intercellular transcriptional heterogeneity in cancer cells during chemotherapeutic responses to achieve near-complete cancer cell killing in vitro. Our findings represent a 'macrogenomic engineering' approach to modulating the physical structure of chromatin for whole-scale transcriptional modulation.

The Role of Chromatin Density in Cell Population Heterogeneity during Stem Cell Differentiation

We incorporate three-dimensional (3D) conformation of chromosome (Hi-C) and single-cell RNA sequencing data together with discrete stochastic simulation, to explore the role of chromatin reorganization in determining gene expression heterogeneity during development. While previous research has emphasized the importance of chromatin architecture on activation and suppression of certain regulatory genes and gene networks, our study demonstrates how chromatin remodeling can dictate gene expression distribution by folding into distinct topological domains. We hypothesize that the local DNA density during differentiation accentuate transcriptional bursting due to the crowding effect of chromatin. This phenomenon yields a heterogeneous cell population, thereby increasing the potential of differentiation of the stem cells.

Model studies of the effects of intracellular crowding on nucleic acid interactions

Molecular interactions and reactions in living cells occur with high concentrations of background molecules and ions. Many research studies have shown that intracellular molecules have characteristics different from those obtained using simple aqueous solutions. To better understand the behavior of biomolecules in intracellular environments, biophysical experiments were conducted under cell-mimicking conditions in a test tube. It has been shown that the molecular environments at the physiological level of macromolecular crowding, spatial confinement, water activity and dielectric constant, have significant effects on the interactions of DNA and RNA for hybridization, higher-order folding, and catalytic activity. The experimental approaches using in vitro model systems are useful to reveal the origin of the environmental effects and to bridge the gap between the behaviors of nucleic acids in vitro and in vivo. This paper highlights the model experiments used to evaluate the influences of intracellular environment on nucleic acid interactions.

Facilitated diffusion in the presence of obstacles on the DNA

Biological functions of DNA depend on the sequence-specific binding of DNA-binding proteins to their corresponding binding sites. Binding of these proteins to their binding sites occurs through a facilitated diffusion process that combines three-dimensional diffusion in the cytoplasm with one-dimensional diffusion (sliding) along the DNA. In this work, we use a lattice model of facilitated diffusion to study how the dynamics of binding of a protein to a specific site (e.g., binding of an RNA polymerase to a promoter or of a transcription factor to its operator site) is affected by the presence of other proteins bound to the DNA, which act as 'obstacles' in the sliding process. Different types of these obstacles with different dynamics are implemented. While all types impair facilitated diffusion, the extent of the hindrance depends on the type of obstacle. As a consequence of hindrance by obstacles, more excursions into the cytoplasm are required for optimal target binding compared to the case without obstacles.

Manipulation and Motion of Organelles and Single Molecules in Living Cells

The biomolecule is among the most important building blocks of biological systems, and a full understanding of its function forms the scaffold for describing the mechanisms of higher order structures as organelles and cells. Force is a fundamental regulatory mechanism of biomolecular interactions driving many cellular processes. The forces on a molecular scale are exactly in the range that can be manipulated and probed with single molecule force spectroscopy. The natural environment of a biomolecule is inside a living cell, hence, this is the most relevant environment for probing their function. In vivo studies are, however, challenged by the complexity of the cell. In this review, we start with presenting relevant theoretical tools for analyzing single molecule data obtained in intracellular environments followed by a description of state-of-the art visualization techniques. The most commonly used force spectroscopy techniques, namely optical tweezers, magnetic tweezers, and atomic force microscopy, are described in detail, and their strength and limitations related to in vivo experiments are discussed. Finally, recent exciting discoveries within the field of in vivo manipulation and dynamics of single molecule and organelles are reviewed.

The Global Relationship between Chromatin Physical Topology, Fractal Structure, and Gene Expression

Most of what we know about gene transcription comes from the view of cells as molecular machines: focusing on the role of molecular modifications to the proteins carrying out transcriptional reactions at a loci-by-loci basis. This view ignores a critical reality: biological reactions do not happen in an empty space, but in a highly complex, interrelated, and dense nanoenvironment that profoundly influences chemical interactions. We explored the relationship between the physical nanoenvironment of chromatin and gene transcription in vitro. We analytically show that changes in the fractal dimension, D, of chromatin correspond to simultaneous increases in chromatin accessibility and compaction heterogeneity. Using these predictions, we demonstrate experimentally that nanoscopic changes to chromatin D within thirty minutes correlate with concomitant enhancement and suppression of transcription. Further, we show that the increased heterogeneity of physical structure of chromatin due to increase in fractal dimension correlates with increased heterogeneity of gene networks. These findings indicate that the higher order folding of chromatin topology may act as a molecular-pathway independent code regulating global patterns of gene expression. Since physical organization of chromatin is frequently altered in oncogenesis, this work provides evidence pairing molecular function to physical structure for processes frequently altered during tumorigenesis.

Reaction–diffusion with stochastic decay rates

Microscopic physical and chemical fluctuations in a reaction–diffusion system lead to anomalous chemical kinetics and transport on the mesoscopic scale. Emergent non-Markovian effects lead to power-law reaction times and localization of reacting species.

Macromolecular Crowding Regulates the Gene Expression Profile by Limiting Diffusion

We seek to elucidate the role of macromolecular crowding in transcription and translation. It is well known that stochasticity in gene expression can lead to differential gene expression and heterogeneity in a cell population. Recent experimental observations by Tan et al. have improved our understanding of the functional role of macromolecular crowding. It can be inferred from their observations that macromolecular crowding can lead to robustness in gene expression, resulting in a more homogeneous cell population. We introduce a spatial stochastic model to provide insight into this process. Our results show that macromolecular crowding reduces noise (as measured by the kurtosis of the mRNA distribution) in a cell population by limiting the diffusion of transcription factors (i.e. removing the unstable intermediate states), and that crowding by large molecules reduces noise more efficiently than crowding by small molecules. Finally, our simulation results provide evidence that the local variation in chromatin density as well as the total volume exclusion of the chromatin in the nucleus can induce a homogenous cell population.

The cellular nucleus is packed with macromolecules such as DNAs and proteins, which leaves limited space for other molecules to move around. Recent experimental results by C. Tan et al. have shown that macromolecular crowding can regulate gene expression, resulting in a more homogenous cell population. We introduce a computational model to uncover the mechanism by which macromolecular crowding functions. Our results suggest that macromolecular crowding limits the diffusion of the transcription factors and attenuates the transcriptional bursting, which leads to a more homogenous cell population. Regulation of gene expression noise by macromolecules depends on the size of the crowders, i.e. larger macromolecules can reduce the noise more effectively than smaller macromolecules. We also demonstrate that local variation of chromatin density can affect the noise of gene expression. This shows the importance of the chromatin structure in gene expression regulation.

Unexpected Swelling of Stiff DNA in a Polydisperse Crowded Environment

We investigate the conformations of DNA-like stiff chains, characterized by contour length (L) and persistence length (lp), in a variety of crowded environments containing monodisperse soft spherical (SS) and spherocylindrical (SC) particles, a mixture of SS and SC, and a milieu mimicking the composition of proteins in the Escherichia coli cytoplasm. The stiff chain, whose size modestly increases in SS crowders up to ϕ ≈ 0.1, is considerably more compact at low volume fractions (ϕ ≤ 0.2) in monodisperse SC particles than in a medium containing SS particles. A 1:1 mixture of SS and SC crowders induces greater chain compaction than the pure SS or SC crowders at the same ϕ, with the effect being highly nonadditive. We also discover a counterintuitive result that the polydisperse crowding environment, mimicking the composition of a cell lysate, swells the DNA-like polymer, which is in stark contrast to the size reduction of flexible polymers in the same milieu. Trapping of the stiff chain in a fluctuating tube-like environment created by large-sized crowders explains the dramatic increase in size and persistence length of the stiff chain. In the polydisperse medium, mimicking the cellular environment, the size of the DNA (or related RNA) is determined by L/lp. At low L/lp, the size of the polymer is unaffected, whereas there is a dramatic swelling at an intermediate value of L/lp. We use these results to provide insights into recent experiments on crowding effects on RNA and also make testable predictions.

Conditions for positioning of nucleosomes on DNA

Positioning of nucleosomes along a eukaryotic genome plays an important role in its organization and regulation. There are many different factors affecting the location of nucleosomes. Some can be viewed as preferential binding of a single nucleosome to different locations along the DNA and some as interactions between neighboring nucleosomes. In this study, we analyze positioning of nucleosomes and derive conditions for their good positioning. Using analytic and numerical approaches we find that, if the binding preferences are very weak, an interplay between the interactions and the binding preferences is essential for a good positioning of nucleosomes, especially on correlated energy landscapes. Analyzing the empirical energy landscape, we conclude that good positioning of nucleosomes in vivo is possible only if they strongly interact. In this case, our model, predicting long-length-scale fluctuations of nucleosomes' occupancy along the DNA, accounts well for the empirical observations.

Synthetic Biology: A Bridge between Artificial and Natural Cells

Artificial cells are simple cell-like entities that possess certain properties of natural cells. In general, artificial cells are constructed using three parts: (1) biological membranes that serve as protective barriers, while allowing communication between the cells and the environment; (2) transcription and translation machinery that synthesize proteins based on genetic sequences; and (3) genetic modules that control the dynamics of the whole cell. Artificial cells are minimal and well-defined systems that can be more easily engineered and controlled when compared to natural cells. Artificial cells can be used as biomimetic systems to study and understand natural dynamics of cells with minimal interference from cellular complexity. However, there remain significant gaps between artificial and natural cells. How much information can we encode into artificial cells? What is the minimal number of factors that are necessary to achieve robust functioning of artificial cells? Can artificial cells communicate with their environments efficiently? Can artificial cells replicate, divide or even evolve? Here, we review synthetic biological methods that could shrink the gaps between artificial and natural cells. The closure of these gaps will lead to advancement in synthetic biology, cellular biology and biomedical applications.

Synthetic biology outside the cell: linking computational tools to cell-free systems

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Macromolecular crowding as a regulator of gene transcription

Studies of macromolecular crowding have shown its important effects on molecular transport and interactions in living cells. Less clear is the effect of crowding when its influence is incorporated into a complex network of interactions. Here, we explore the effects of crowding in the cell nucleus on a model of gene transcription as a network of reactions involving transcription factors, RNA polymerases, and DNA binding sites for these proteins. The novelty of our approach is that we determine the effects of crowding on the rates of these reactions using Brownian dynamics and Monte Carlo simulations, allowing us to integrate molecular-scale information, such as the shapes and sizes of each molecular species, into the rate equations of the model. The steady-state cytoplasmic mRNA concentration shows several regimes with qualitatively different dependences on the volume fraction, ϕ, of crowding agents in the nucleus, including a broad range of parameter values where it depends nonmonotonically on ϕ, with maximum mRNA production occurring at a physiologically relevant value. The extent of this crowding dependence can be modulated by a variety of means, suggesting that the transcriptional output of a gene can be regulated jointly by the local level of macromolecular crowding in the nucleus, together with the local concentrations of polymerases and DNA-binding proteins, as well as other properties of the gene's physical environment.