Crowded Cellular Environment Research Articles

Kinesin motility is driven by subdomain dynamics.

The microtubule (MT)-associated motor protein kinesin utilizes its conserved ATPase head to achieve diverse motility characteristics. Despite considerable knowledge about how its ATPase activity and MT binding are coupled to the motility cycle, the atomic mechanism of the core events remain to be found. To obtain insights into the mechanism, we performed 38.5 microseconds of all-atom molecular dynamics simulations of kinesin-MT complexes in different nucleotide states. Local subdomain dynamics were found to be essential for nucleotide processing. Catalytic water molecules are dynamically organized by the switch domains of the nucleotide binding pocket while ATP is torsionally strained. Hydrolysis products are 'pulled' by switch-I, and a new ATP is 'captured' by a concerted motion of the α0/L5/switch-I trio. The dynamic and wet kinesin-MT interface is tuned for rapid interactions while maintaining specificity. The proposed mechanism provides the flexibility necessary for walking in the crowded cellular environment.

Investigating molecular crowding within nuclear pores using polarization-PALM.

The key component of the nuclear pore complex (NPC) controlling permeability, selectivity, and the speed of nucleocytoplasmic transport is an assembly of natively unfolded polypeptides, which contain phenylalanine-glycine (FG) binding sites for nuclear transport receptors. The architecture and dynamics of the FG-network have been refractory to characterization due to the paucity of experimental methods able to probe the mobility and density of the FG-polypeptides and embedded macromolecules within intact NPCs. Combining fluorescence polarization, super-resolution microscopy, and mathematical analyses, we examined the rotational mobility of fluorescent probes at various locations within the FG-network under different conditions. We demonstrate that polarization PALM (p-PALM) provides a rich source of information about low rotational mobilities that are inaccessible with bulk fluorescence anisotropy approaches, and anticipate that p-PALM is well-suited to explore numerous crowded cellular environments. In total, our findings indicate that the NPC's internal organization consists of multiple dynamic environments with different local properties.

Convolutional neural networks for automated annotation of cellular cryo-electron tomograms.

Cellular Electron Cryotomography (CryoET) offers the ability to look inside cells and observe macromolecules frozen in action. A primary challenge for this technique is identifying and extracting the molecular components within the crowded cellular environment. We introduce a method using neural networks to dramatically reduce the time and human effort required for subcellular annotation and feature extraction. Subsequent subtomogram classification and averaging yields in-situ structures of molecular components of interest.

UsnRNP biogenesis: mechanisms and regulation.

Macromolecular complexes composed of proteins or proteins and nucleic acids rather than individual macromolecules mediate many cellular activities. Maintenance of these activities is essential for cell viability and requires the coordinated production of the individual complex components as well as their faithful incorporation into functional entities. Failure of complex assembly may have fatal consequences and can cause severe diseases. While many macromolecular complexes can form spontaneously in vitro, they often require aid from assembly factors including assembly chaperones in the crowded cellular environment. The assembly of RNA protein complexes implicated in the maturation of pre-mRNAs (termed UsnRNPs) has proven to be a paradigm to understand the action of assembly factors and chaperones. UsnRNPs are assembled by factors united in protein arginine methyltransferase 5 (PRMT5)- and survival motor neuron (SMN)-complexes, which act sequentially in the UsnRNP production line. While the PRMT5-complex pre-arranges specific sets of proteins into stable intermediates, the SMN complex displaces assembly factors from these intermediates and unites them with UsnRNA to form the assembled RNP. Despite advanced mechanistic understanding of UsnRNP assembly, our knowledge of regulatory features of this essential and ubiquitous cellular function remains remarkably incomplete. One may argue that the process operates as a default biosynthesis pathway and does not require sophisticated regulatory cues. Simple theoretical considerations and a number of experimental data, however, indicate that regulation of UsnRNP assembly most likely happens at multiple levels. This review will not only summarize how individual components of this assembly line act mechanistically but also why, how, and when the UsnRNP workflow might be regulated by means of posttranslational modification in response to cellular signaling cues.

Distribution and evolution of stable single α-helices (SAH domains) in myosin motor proteins.

Stable single-alpha helices (SAHs) are versatile structural elements in many prokaryotic and eukaryotic proteins acting as semi-flexible linkers and constant force springs. This way SAH-domains function as part of the lever of many different myosins. Canonical myosin levers consist of one or several IQ-motifs to which light chains such as calmodulin bind. SAH-domains provide flexibility in length and stiffness to the myosin levers, and may be particularly suited for myosins working in crowded cellular environments. Although the function of the SAH-domains in human class-6 and class-10 myosins has well been characterised, the distribution of the SAH-domain in all myosin subfamilies and across the eukaryotic tree of life remained elusive. Here, we analysed the largest available myosin sequence dataset consisting of 7919 manually annotated myosin sequences from 938 species representing all major eukaryotic branches using the SAH-prediction algorithm of Waggawagga, a recently developed tool for the identification of SAH-domains. With this approach we identified SAH-domains in more than one third of the supposed 79 myosin subfamilies. Depending on the myosin class, the presence of SAH-domains can range from a few to almost all class members indicating complex patterns of independent and taxon-specific SAH-domain gain and loss.

Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm.

Biological macromolecules function in highly crowded cellular environments. The structure and dynamics of proteins and nucleic acids are well characterized in vitro, but in vivo crowding effects remain unclear. Using molecular dynamics simulations of a comprehensive atomistic model cytoplasm we found that protein-protein interactions may destabilize native protein structures, whereas metabolite interactions may induce more compact states due to electrostatic screening. Protein-protein interactions also resulted in significant variations in reduced macromolecular diffusion under crowded conditions, while metabolites exhibited significant two-dimensional surface diffusion and altered protein-ligand binding that may reduce the effective concentration of metabolites and ligands in vivo. Metabolic enzymes showed weak non-specific association in cellular environments attributed to solvation and entropic effects. These effects are expected to have broad implications for the in vivo functioning of biomolecules. This work is a first step towards physically realistic in silico whole-cell models that connect molecular with cellular biology.

Peptide binding landscapes: Specificity and homophilicity across sequence space in a lattice model.

Peptide aggregation frequently involves sequences with strong homophilic binding character, i.e., sequences that self-assemble with like species in a crowded cellular environment, in the face of a multitude of other peptides or proteins as potential heterophilic binding partners. What kinds of sequences display a strong tendency towards homophilic binding and self-assembly, and what are the origins of this behavior? Here, we consider how sequence specificity in oligomerization processes plays out in a simple two-dimensional (2D) lattice statistical-thermodynamic peptide model that permits exhaustive examination of the entire sequence and configurational landscapes. We find that sequences with strong self-specificities have either alternating hydrophobic and hydrophilic residues or short patches of hydrophobic residues, both which minimize intramolecular hydrophobic interactions in part due to the constraints of the 2D lattice. We also find that these specificities are highly sensitive to entropic and free energetic features of the unbound conformational state, such that direct binding interaction energies alone do not capture the complete behavior. These results suggest that the ability of particular peptide sequences to self-assemble and aggregate in a many-protein environment reflects a precise balance of direct binding interactions and behavior in the unbound (monomeric) state.

Dynamics of proteins aggregation. I. Universal scaling in unbounded media

It is well understood that in some cases proteins do not fold correctly and, depending on their environment, even properly-folded proteins change their conformation spontaneously, taking on a misfolded state that leads to protein aggregation and formation of large aggregates. An important factor that contributes to the aggregation is the interactions between the misfolded proteins. Depending on the aggregation environment, the aggregates may take on various shapes forming larger structures, such as protein plaques that are often toxic. Their deposition in tissues is a major contributing factor to many neuro-degenerative diseases, such as Alzheimer's, Parkinson's, amyotrophic lateral sclerosis, and prion. This paper represents the first part in a series devoted to molecular simulation of protein aggregation. We use the PRIME, a meso-scale model of proteins, together with extensive discontinuous molecular dynamics simulation to study the aggregation process in an unbounded fluid system, as the first step toward MD simulation of the same phenomenon in crowded cellular environments. Various properties of the aggregates have been computed, including dynamic evolution of aggregate-size distribution, mean aggregate size, number of peptides that contribute to the formation of β sheets, number of various types of hydrogen bonds formed in the system, radius of gyration of the aggregates, and the aggregates' diffusivity. We show that many of such quantities follow dynamic scaling, similar to those for aggregation of colloidal clusters. In particular, at long times the mean aggregate size S(t) grows with time as, S(t) ∼ tz, where z is the dynamic exponent. To our knowledge, this is the first time that the qualitative similarity between aggregation of proteins and colloidal aggregates has been pointed out.

Simulating cryo electron tomograms of crowded cell cytoplasm for assessment of automated particle picking.

BackgroundCryo-electron tomography is an important tool to study structures of macromolecular complexes in close to native states. A whole cell cryo electron tomogram contains structural information of all its macromolecular complexes. However, extracting this information remains challenging, and relies on sophisticated image processing, in particular for template-free particle extraction, classification and averaging. To develop these methods it is crucial to realistically simulate tomograms of crowded cellular environments, which can then serve as ground truth models for assessing and optimizing methods for detection of complexes in cell tomograms.ResultsWe present a framework to generate crowded mixtures of macromolecular complexes for realistically simulating cryo electron tomograms including noise and image distortions due to the missing-wedge effects. Simulated tomograms are then used for assessing the template-free Difference-of-Gaussian (DoG) particle-picking method to detect complexes of different shapes and sizes under various crowding and noise levels. We identified DoG parameter settings that maximize precision and recall for detecting particles over a wide range of sizes and shapes. We observed that medium sized DoG scaling factors showed the overall best performance. To further improve performance, we propose a combination strategy for integrating results from multiple parameter settings. With increasing macromolecular crowding levels, the precision of particle picking remained relatively high, while the recall was dramatically reduced, which limits the detection of sufficient copy numbers of complexes in a crowded environment. Over a wide range of increasing noise levels, the DoG particle picking performance remained stable, but dramatically reduced beyond a specific noise threshold.ConclusionsAutomatic and reference-free particle picking is an important first step in a visual proteomics analysis of cell tomograms. However, cell cytoplasm is highly crowded, which makes particle detection challenging. It is therefore important to test particle-picking methods in a realistic crowded setting. Here, we present a framework for simulating tomograms of cellular environments at high crowding levels and assess the DoG particle picking method. We determined optimal parameter settings to maximize the performance of the DoG particle-picking method.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1283-3) contains supplementary material, which is available to authorized users.

A Simple Model of Protein Domain Swapping in Crowded Cellular Environments

Domain swapping in proteins is an important mechanism of functional and structural innovation. However, despite its ubiquity and importance, the physical mechanisms that lead to domain swapping are poorly understood. Here, we present a simple two-dimensional coarse-grained model of protein domain swapping in the cytoplasm. In our model, two-domain proteins partially unfold and diffuse in continuous space. Monte Carlo multiprotein simulations of the model reveal that domain swapping occurs at intermediate temperatures, whereas folded dimers and folded monomers prevail at low temperatures, and partially unfolded monomers predominate at high temperatures. We use a simplified amino acid alphabet consisting of four residue types, and find that the oligomeric state at a given temperature depends on the sequence of the protein. We also show that hinge strain between domains can promote domain swapping, consistent with experimental observations for real proteins. Domain swapping depends nonmonotonically on the protein concentration, with domain-swapped dimers occurring at intermediate concentrations and nonspecific interactions between partially unfolded proteins occurring at high concentrations. For folded proteins, we recover the result obtained in three-dimensional lattice simulations, i.e., that functional dimerization is most prevalent at intermediate temperatures and nonspecific interactions increase at low temperatures.

Correlative Imaging of Intracellular Transport Processes at High Resolution

Intracellular transport plays an essential role in maintaining the healthy organization and function of cells. Motor proteins like dynein and kinesin actively transport vesicles and organelles through the crowded cellular environment. In doing so, they must overcome traffic jams and roadblocks to effectively deliver their cargo to the right place and at the right time. Understanding the mechanisms that motors use for achieving efficient transport in vivo can give important clues into how transport may fail in neurodegenerative diseases. Over the years, we have been developing new tools that take advantage of single particle tracking and super-resolution microscopy to visualize intracellular transport with high spatio-temporal resolution inside living cells. These methods have helped us gain new insights into the biophysical mechanisms that motors use to move their vesicles along the complex microtubule network in an efficient manner.

Using Single Molecule Chemo-Mechanical Unfolding to Probe the Effect of Environmental Conditions on the Protein Folding Pathway

A fundamental question in protein folding is whether proteins fold through one or multiple trajectories. Although most protein folding experiments indicate a single pathway, we have demonstrated the presence of multiple unfolding pathways in a simple, two-state folding protein using a combination of chemical denaturant, mechanical force and site-directed mutations. This raises the question of how environmental conditions affect the folding mechanism. We find that under most conditions a single pathway is dominant, but seemingly small changes in force, denaturant concentration and protein sequence can strongly modulate the flux between the pathways. This result suggests that in vivo, the heterogeneous crowded cellular environment could strongly influence the mechanisms of protein folding and unfolding. Another perturbant that could affect the folding pathway in vivo is the ribosome since many proteins fold while they are being translated. Comparison of the pathway in experiments on and off the ribosome will reveal how the ribosome affects the folding mechanism.

E.Coli RNA Polymerase Activity under Crowding

Biological reactions in the cellular environment differ physicochemically from those performed in dilute buffer solutions due to the high viscosity and crowding effects associated with the high density of macromolecules in the cell. Earlier work has shown that in vivo bacterial transcription is affected by the cellular environment, involving slower diffusion of various components in the cellular milieu (due to high viscosity), increase in their local concentrations, and modulation of their binding affinities. However, since most studies are focused on multiple cycles of either transcription or association of DNA and RNA Polymerase (RNAP) to make RNAP open complex (RPo), the effect of the crowded environment on a single transcription run is still poorly understood. Here, we have developed and applied a novel transcription quenched-kinetics assay using single-molecule detection to investigate the size/concentration effects of various osmolytes and macromolecular crowding agents, which mimic the crowded cellular environment, on actively-transcribing RNAP. Our results demonstrate an expected slowdown of transcription kinetics due to increased viscosity, and unexpected enhancement in transcription activity by larger crowding agents at the same viscosity. These findings suggest that crowding agents affect the transcription reaction after RPo formation through volume exclusion.

Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell.

All soluble proteins populate conformational ensembles that together constitute the native state. Their fluctuations in water are intrinsic thermodynamic phenomena, and the distributions of the states on the energy landscape are determined by statistical thermodynamics; however, they are optimized to perform their biological functions. In this review we briefly describe advances in free energy landscape studies of protein conformational ensembles. Experimental (nuclear magnetic resonance, small-angle X-ray scattering, single-molecule spectroscopy, and cryo-electron microscopy) and computational (replica-exchange molecular dynamics, metadynamics, and Markov state models) approaches have made great progress in recent years. These address the challenging characterization of the highly flexible and heterogeneous protein ensembles. We focus on structural aspects of protein conformational distributions, from collective motions of single- and multi-domain proteins, intrinsically disordered proteins, to multiprotein complexes. Importantly, we highlight recent studies that illustrate functional adjustment of protein conformational ensembles in the crowded cellular environment. We center on the role of the ensemble in recognition of small- and macro-molecules (protein and RNA/DNA) and emphasize emerging concepts of protein dynamics in enzyme catalysis. Overall, protein ensembles link fundamental physicochemical principles and protein behavior and the cellular network and its regulation.

Anions in Nucleic Acid Crystallography.

Nucleic acid crystallization buffers contain a large variety of chemicals fitting specific needs. Among them, anions are often solely considered for pH-regulating purposes and as cationic co-salts while their ability to directly bind to nucleic acid structures is rarely taken into account. Here we review current knowledge related to the use of anions in crystallization buffers along with data on their biological prevalence. Chloride ions are frequently identified in crystal structures but display low cytosolic concentrations. Hence, they are thought to be distant from nucleic acid structures in the cell. Sulfate ions are also frequently identified in crystal structures but their localization in the cell remains elusive. Nevertheless, the characterization of the binding properties of these ions is essential for better interpreting the solvent structure in crystals and consequently, avoiding mislabeling of electron densities. Furthermore, understanding the binding properties of these anions should help to get clues related to their potential effects in crowded cellular environments.

The impact of physiological crowding on the diffusivity of membrane bound proteins.

Diffusion of transmembrane and peripheral membrane-bound proteins within the crowded cellular membrane environment is essential to diverse biological processes including cellular signaling, endocytosis, and motility. Nonetheless we presently lack a detailed understanding of the influence of physiological levels of crowding on membrane protein diffusion. Utilizing quantitative in vitro measurements, here we demonstrate that the diffusivities of membrane bound proteins follow a single linearly decreasing trend with increasing membrane coverage by proteins. This trend holds for homogenous protein populations across a range of protein sizes and for heterogeneous mixtures of proteins of different sizes, such that protein diffusivity is controlled by the total coverage of the surrounding membrane. These results demonstrate that steric exclusion within the crowded membrane environment can fundamentally limit the diffusive rate of proteins, regardless of their size. In cells this "speed limit" could be modulated by changes in local membrane coverage, providing a mechanism for tuning the rate of molecular interaction and assembly.

Transient Interactions of a Cytosolic Protein with Macromolecular and Vesicular Cosolutes: Unspecific and Specific Effects.

Cytosolic proteins do not occur as isolated but are exposed to many interactions within a crowded cellular environment. We investigated the associations between a test cytosolic protein, human ileal bile acid binding protein (IBABP), and model cosolutes mimicking macromolecular and lipid membrane intracellular components. Using fluorescence spectroscopy, heteronuclear NMR, and molecular dynamics, we found that IBABP associated weakly with anionic lipid vesicles and experienced transient unspecific contacts with albumin. Localized dynamic perturbations were observed even in the case of apparent unspecific binding. IBABP and ubiquitin did not display mutually attractive forces, whereas IBABP associated specifically with lysozyme. A structural model of the IBABP-lysozyme complex was obtained by data-driven docking simulation. Presumably, all the interactions shown here contribute to modulating functional communication of a protein in its native environment.

Large-scale analysis of macromolecular crowding effects on protein aggregation using a reconstituted cell-free translation system.

Proteins must fold into their native structures in the crowded cellular environment, to perform their functions. Although such macromolecular crowding has been considered to affect the folding properties of proteins, large-scale experimental data have so far been lacking. Here, we individually translated 142 Escherichia coli cytoplasmic proteins using a reconstituted cell-free translation system in the presence of macromolecular crowding reagents (MCRs), Ficoll 70 or dextran 70, and evaluated the aggregation propensities of 142 proteins. The results showed that the MCR effects varied depending on the proteins, although the degree of these effects was modest. Statistical analyses suggested that structural parameters were involved in the effects of the MCRs. Our dataset provides a valuable resource to understand protein folding and aggregation inside cells.

Reconstituting Intracellular Vesicle Fusion Reactions: The Essential Role of Macromolecular Crowding.

Intracellular vesicle fusion is mediated by SNAREs and Sec1/Munc18 (SM) proteins. Despite intensive efforts, the SNARE-SM mediated vesicle fusion reaction has not been faithfully reconstituted in biochemical assays. Here, we present an unexpected discovery that macromolecular crowding is required for reconstituting the vesicle fusion reaction in vitro. Macromolecular crowding is known to profoundly influence the kinetic and thermodynamic behaviors of macromolecules, but its role in membrane transport processes such as vesicle fusion remains unexplored. We introduced macromolecular crowding agents into reconstituted fusion reactions to mimic the crowded cellular environment. In this crowded assay, SNAREs and SM proteins acted in concert to drive efficient membrane fusion. In uncrowded assays, by contrast, SM proteins failed to associate with the SNAREs and the fusion rate decreased more than 30-fold, close to undetectable levels. The activities of SM proteins were strictly specific to their cognate SNARE isoforms and sensitive to biologically relevant mutations, further supporting that the crowded fusion assay accurately recapitulates the vesicle fusion reaction. Using this crowded fusion assay, we also showed that the SNARE-SM mediated fusion reaction can be modulated by two additional factors: NSF and α-SNAP. These findings suggest that the vesicle fusion machinery likely has been evolutionarily selected to function optimally in the crowded milieu of the cell. Accordingly, macromolecular crowding should constitute an integral element of any reconstituted fusion assay.

Large oligomeric complex structures can be computationally assembled by efficiently combining docked interfaces.

ABSTRACTMacromolecular oligomeric assemblies are involved in many biochemical processes of living organisms. The benefits of such assemblies in crowded cellular environments include increased reaction rates, efficient feedback regulation, cooperativity and protective functions. However, an atom‐level structural determination of large assemblies is challenging due to the size of the complex and the difference in binding affinities of the involved proteins. In this study, we propose a novel combinatorial greedy algorithm for assembling large oligomeric complexes from information on the approximate position of interaction interfaces of pairs of monomers in the complex. Prior information on complex symmetry is not required but rather the symmetry is inferred during assembly. We implement an efficient geometric score, the transformation match score, that bypasses the model ranking problems of state‐of‐the‐art scoring functions by scoring the similarity between the inferred dimers of the same monomer simultaneously with different binding partners in a (sub)complex with a set of pregenerated docking poses. We compiled a diverse benchmark set of 308 homo and heteromeric complexes containing 6 to 60 monomers. To explore the applicability of the method, we considered 48 sets of parameters and selected those three sets of parameters, for which the algorithm can correctly reconstruct the maximum number, namely 252 complexes (81.8%) in, at least one of the respective three runs. The crossvalidation coverage, that is, the mean fraction of correctly reconstructed benchmark complexes during crossvalidation, was 78.1%, which demonstrates the ability of the presented method to correctly reconstruct topology of a large variety of biological complexes. Proteins 2015; 83:1887–1899. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.