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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2016

Optogenetically controlled cargo shows full length human myosin VI integrates activation signals in vivo and in vitro

Myosins play countless critical roles in the cell, each requiring it to be activated at a specific location and time. To control myosin VI with this specificity, we created a novel optogenetic tool for activating myosin VI by fusing the light-sensitive Avena sativa phototropin1 LOV2 domain to a peptide from Dab2 (LOVDab), a myosin VI cargo protein. Our approach harnesses the native targeting and activation mechanism of myosin VI, allowing direct inferences on myosin VI function. LOVDab robustly recruits human full length myosin VI to various organelles in vivo and hinders peroxisome motion in a light-controllable manner. LOVDab also activates myosin VI in an in vitro gliding filament assay. Our data suggest that protein and lipid cargoes cooperate to activate myosin VI, allowing myosin VI to integrate Ca2+, lipid, and protein cargo signals in the cell to deploy in a site-specific manner.\n\nSignificance StatementMyosins are a broad class of motor proteins that generate force on actin filaments and fulfill contractile, transport, and anchoring roles. Myosin VI, the only myosin to walk toward the pointed end of actin filaments, is implicated in cancer metastasis and deafness. Intriguingly, myosin VI may play both transport and anchoring roles, depending upon where it is activated in the cell. Here we develop an optogenetic tool for studying myosin VI activation with high spatial and temporal resolution. Our approach photoactivates unmodified myosin VI through its native cargo pathway, enabling investigation of motor function and activation partners with minimal perturbation. This approach allows us to detect how and where myosin VI integrates multiple protein and second messenger signals to activate.

Biophysics↗

bioRxiv2016

Physical model of the sequence-to-function map of proteins

How DNA is mapped to functional proteins is a basic question of living matter. We introduce and study a physical model of protein evolution which suggests a mechanical basis for this map. Many proteins rely on large-scale motion to function. We therefore treat protein as learning amorphous matter that evolves towards such a mechanical function: Genes are binary sequences that encode the connectivity of the amino acid network that makes a protein. The gene is evolved until the network forms a shear band across the protein, which allows for long-range, soft modes required for protein function. The evolution reduces the high-dimensional sequence space to a low-dimensional space of mechanical modes, in accord with the observed dimensional reduction between genotype and phenotype of proteins. Spectral analysis of the space of 106 solutions shows a strong correspondence between localization around the shear band of both mechanical modes and the sequence structure. Specifically, our model shows how mutations are correlated among amino acids whose interactions determine the functional mode.\n\nPACS numbers: 87.14.E-, 87.15.-v, 87.10.-e

Biophysics↗

bioRxiv2016

A Single Nucleotide Resolution Model for Large-Scale Simulations of Double Stranded DNA

The computational modelling of DNA is becoming crucial in light of new advances in DNA nanotechnology, single-molecule experiments and in vivo DNA tampering. Here we present a mesoscopic model for double stranded DNA (dsDNA) at the single nucleotide level which retains the characteristic helical structure, while being able to simulate large molecules -- up to a million base pairs -- for time-scales which are relevant to physiological processes. This is made possible by an efficient and highly-parallelised implementation of the model which we discuss here. We compare the behaviour of our model with single molecule experiments where dsDNA is manipulated by external forces or torques. We also present some results on the kinetics of denaturation of linear DNA.

Biophysics↗

bioRxiv2016

Modeling and docking antibody structures with Rosetta

We describe Rosetta-based computational protocols for predicting the three-dimensional structure of an antibody from sequence and then docking the antibody-protein-antigen complexes. Antibody modeling leverages canonical loop conformations to graft large segments from experimentally-determined structures as well as (1) energetic calculations to minimize loops, (2) docking methodology to refine the VL-VH relative orientation, and (3) de novo prediction of the elusive complementarity determining region (CDR) H3 loop. To alleviate model uncertainty, antibody-antigen docking resamples CDR loop conformations and can use multiple models to represent an ensemble of conformations for the antibody, the antigen or both. These protocols can be run fully-automated via the ROSIE web server or manually on a computer with user control of individual steps. For best results, the protocol requires roughly 2,500 CPU-hours for antibody modeling and 250 CPU-hours for antibody-antigen docking. Tasks can be completed in under a day by using public supercomputers.

Biophysics↗

bioRxiv2016

Mathematical Methods for Modeling Chemical Reaction Networks

Cancers cellular behavior is driven by alterations in the processes that cells use to sense and respond to diverse stimuli. Underlying these processes are a series of chemical processes (enzyme-substrate, protein-protein, etc.). Here we introduce a set of mathematical techniques for describing and characterizing these processes.

Biophysics↗

bioRxiv2016

Pulsatile lipid vesicles under osmotic stress

The response of lipid bilayers to osmotic stress is an important part of cellular function. Previously, in (Oglecka et al., 2014), we reported that cell-sized giant unilamellar vesicles (GUVs) exposed to hypotonic media, respond to the osmotic assault by undergoing a cyclical sequence of swelling and bursting events, coupled to the membranes compositional degrees of freedom. Here, we seek to deepen our quantitative understanding of the essential pulsatile behavior of GUVs under hypotonic conditions, by advancing a comprehensive theoretical model for vesicle dynamics. The model quantitatively captures our experimentally measured swell-burst parameters for single-component GUVs, and reveals that thermal fluctuations enable rate dependent pore nucleation, driving the dynamics of the swell-burst cycles. We further identify new scaling relationships between the pulsatile dynamics and GUV properties. Our findings provide a fundamental framework that has the potential to guide future investigations on the non-equilibrium dynamics of vesicles under osmotic stress.

Biophysics↗

bioRxiv2016

Protein Collapse is Encoded in the Folded State Architecture

Folded states of single domain globular proteins, the workhorses in cells, are compact with high packing density. It is known that the radius of gyration, Rg, of both the folded and unfolded (created by adding denaturants) states increase as N{nu} where N is the number of amino acids in the protein. The values of the celebrated Flory exponent{nu} are, respectively, [Formula], and {approx} 0.6 in the folded and unfolded states, which coincide with those found in homopolymers in poor and good solvents, respectively. However, the extent of compaction of the unfolded state of a protein under low denaturant concentration, conditions favoring the formation of the folded state, is unknown. This problem which goes to the heart of how proteins fold, with implications for the evolution of foldable sequences, is unsolved. We develop a theory based on polymer physics concepts that uses the contact map of proteins as input to quantitatively assess collapsibility of proteins. The model, which includes only two-body excluded volume interactions and attractive interactions reflecting the contact map, has only expanded and compact states. Surprisingly, we find that although protein collapsibility is universal, the propensity to be compact depends on the protein architecture. Application of the theory to over two thousand proteins shows that the extent of collapsibility depends not only on N but also on the contact map reflecting the native fold structure. A major prediction of the theory is that {beta}-sheet proteins are far more collapsible than structures dominated by -helices. The theory and the accompanying simulations, validating the theoretical predictions, fully resolve the apparent controversy between conclusions reached using different experimental probes assessing the extent of compaction of a couple proteins. As a by product, we show that the theory correctly predicts the scaling of the collapse temperature of homopolymers as a function of the number of monomers. By calculating the criterion for collapsibility as a function of protein length we provide quantitative insights into the reasons why single domain proteins are small and the physical reasons for the origin of multi-domain proteins. We also show that non-coding RNA molecules, whose collapsibility is similar to proteins with {beta}-sheet structures, must undergo collapse prior to folding, adding support to \"Compactness Selection Hypothesis\" proposed in the context of RNA compaction.

Biophysics↗

bioRxiv2016

Molecular Counting with Localization Microscopy: A Redundant Labeling Approach

Super-resolved localization microscopy (SLM) has the potential to serve as an accurate, singlecell technique for counting the abundance of intracellular molecules. However, the stochastic blinking of single fluorophores can introduce large uncertainties into the final count. Here we provide a theoretical foundation for applying SLM to the problem of molecular counting based on the distribution of blinking events from a single fluorophore. We also show that by redundantly tagging single-molecules with multiple, blinking fluorophores, the accuracy of the technique can be enhanced by harnessing the central limit theorem. The coefficient of variation (CV) then, for the number of molecules M estimated from a given number of blinks B, scales like [Formula], where Nl is the mean number of labels on a target. As an example, we apply our theory to the challenging problem of quantifying the cell-to-cell variability of plasmid copy number in bacteria.

Biophysics↗

bioRxiv2016

Unlocked capacity of proteins to attack membranes characteristic of aggregation: the evil for diseases and aging from Pandora’s box

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=193 SRC=\"FIGDIR/small/071274_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (61K):\norg.highwire.dtl.DTLVardef@3e897borg.highwire.dtl.DTLVardef@1b429f6org.highwire.dtl.DTLVardef@12f0dbeorg.highwire.dtl.DTLVardef@2f5d8f_HPS_FORMAT_FIGEXP M_FIG C_FIG AbstractAggregation of specific proteins is characteristic of a large spectrum of human diseases including all neurodegenerative diseases, while aggregation of non-specific proteins has been now identified to be a biomarker for cellular aging down to Escherichia coli. Previously, as facilitated with our discovery in 2005 that \"completely insoluble\" proteins could be all solubilized in unsalted water [Song (2009) FEBS Lett. 583: 953], we found that the TDP-43 prion-like domain in fact contains an intrinsic membrane-interacting subdomain [Lim et al. [2016] PLoS Biol. 14, e1002338]. We decrypted that ALS-causing mutations/cofactor-depletion act to render the wellstructured folds of cytosolic VAPB-MSP domain and SOD1 into highly disordered states, thus becoming buffer-insoluble. Most surprisingly, this also unlocks the amphiphilic/hydrophobic regions universally exiting in proteins, which thus acquire a novel capacity in abnormally interacting with membranes [Qin et al. (2013) F1000Res 2-221.v2; Lim (2016) BBA-Biomembranes. 1858: 2223]. Here we aimed extend our discovery to address two fundamental questions: 1) why many E. coli proteins become aggregated in aging; and 2) whether aggregation-prone proteins can also acquire a novel capacity in interacting with membranes; by dissecting the 557-residue S1 ribosomal protein into 7 fragments to disrupt its 6 S1 folds, followed by extensive CD and NMR characterizations. The results reveal that we have successfully eliminated all 6 S1 folds and fragment 4 becomes highly disordered and thus buffer-insoluble. Most strikingly, F4 does acquire a capacity in transforming into a helical conformation in membrane environments. Here, for the first time, our study deciphers that like ALScausing mutants, the disruption of a well-folded E. coli cytosolic protein also unlocks its amphiphilic/hydrophobic regions which are capable of abnormally interacting with membranes. Therefore, proteins, the most important functional players for all forms of life, can transform into membrane-toxic forms triggering diseases and aging, if their hydrophobic/amphiphilic regions are unlocked by genetic, pathological or/and environmental factors, which is characteristic of severe aggregation.

Biophysics↗

bioRxiv2016

Robust nonparametric descriptors for clustering quantification in single-molecule localization microscopy

We report a robust nonparametric descriptor, J'(r), for quantifying the spatial organization of molecules in singlemolecule localization microscopy. J'(r), based on nearest neighbor distribution functions, does not require any parameter as an input for analyzing point patterns. We show that J'(r) displays a valley shape in the presence of clusters of molecules, and the characteristics of the valley reliably report the clustering features in the data. More importantly, the position of the J'(r) valley (rJ'm) depends exclusively on the density of clustering molecules ({rho}c). Therefore, it is ideal for direct measurements of clustering density of molecules in single-molecule localization microscopy.

Biophysics↗

bioRxiv2016

Cooperativity and modularity in protein folding

A simple statistical mechanical model proposed by Wako and Saito has explained the aspects of protein folding surprisingly well. This model was systematically applied to multiple proteins by Munoz and Eaton and has since been referred to as the Wako-Saito-Munoz-Eaton (WSME) model. The success of the WSME model in explaining the folding of many proteins has verified the hypothesis that the folding is dominated by native interactions, which makes the energy landscape globally biased toward native conformation. Using the WSME and other related models, Saito emphasized the importance of the hierarchical pathway in protein folding; folding starts with the creation of contiguous segments having a native-like configuration and proceeds as growth and coalescence of these segments. The{phi} -values calculated for barnase with the WSME model suggested that segments contributing to the folding nucleus are similar to the structural modules defined by the pattern of native atomic contacts. The WSME model was extended to explain folding of multi-domain proteins having a complex topology, which opened the way to comprehensively understanding the folding process of multi-domain proteins. The WSME model was also extended to describe allosteric transitions, indicating that the allosteric structural movement does not occur as a deterministic sequential change between two conformations but as a stochastic diffusive motion over the dynamically changing energy landscape. Statistical mechanical viewpoint on folding, as highlighted by the WSME model, has been renovated in the context of modern methods and ideas, and will continue to provide insights on equilibrium and dynamical features of proteins.

Biophysics↗

bioRxiv2016

Direct and Indirect Models for Protein Chemical Denaturation are Characteristic of Opposite Dynamic Properties

Two major models, namely direct and indirect models, have been proposed for the protein chemical denaturation but it remains challenging to experimentally demonstrate and distinguish between them. Here, by use of CD and NMR spectroscopy, we succeeded in differentiating the effects on a small but well-folded protein WW4, of GdmCl and NaSCN at diluted concentrations ([≥]200 mM). Both denaturants up to 200 mM have no alternation of its average structure but do reduce its thermodynamic stability to different degrees. Despite acting as the stronger denaturant, GdmCl only weakly interacts with amide protons, while NaSCN shows extensive interactions with both hydrophobic side chains and amide protons. Although both denaturants show no significant perturbation on overall ps-ns backbone dynamics of WW4, GdmCl suppresses while NaSCN enhances its s-ms backbone dynamics in a denaturant concentration dependent manner. Quantitative analysis reveals that although they dramatically raise exchange rates, GdmCl slightly increases while NaSCN reduces the population of the major conformational state. Our study represents the first report deciphering that GdmCl and NaSCN appear to destabilize a protein following two models respectively, which are characteristic of opposite s-ms dynamics.

Biophysics↗

bioRxiv2016

Predicting binding free energies: Frontiers and benchmarks

Binding free energy calculations based on molecular simulations provide predicted affinities for biomolecular complexes. These calculations begin with a detailed description of a system, including its chemical composition and the interactions between its components. Simulations of the system are then used to compute thermodynamic information, such as binding affinities. Because of their promise for guiding molecular design, these calculations have recently begun to see widespread applications in early stage drug discovery. However, many challenges remain to make them a robust and reliable tool. Here, we briefly explain how the calculations work, highlight key challenges, and argue for the development of accepted benchmark test systems that will help the research community generate and evaluate progress.\n\nManuscript version 1.1.1 pre-release See https://github.com/mobleylab/benchmarksets for all versions.

Biophysics↗

bioRxiv2016

Architecture and Co-Evolution of Allosteric Materials

We introduce a numerical scheme to evolve functional materials that can accomplish a specified mechanical task. In this scheme, the number of solutions, their spatial architectures and the correlations among them can be computed. As an example, we consider an \"allosteric\" task, which requires the material to respond specifically to a stimulus at a distant active site. We find that functioning materials evolve a less-constrained trumpet-shaped region connecting the stimulus and active sites, and that the amplitude of the elastic response varies non-monotonically along the trumpet. As previously shown for some proteins, we find that correlations appearing during evolution alone are sufficient to identify key aspects of this design. Finally, we show that the success of this architecture stems from the emergence of soft edge modes recently found to appear near the surface of marginally connected materials. Overall, our in silico evolution experiment offers a new window to study the relationship between structure, function and correlations emerging during evolution.

Biophysics↗

bioRxiv2016

Single variant bottleneck in the early dynamics of H. influenzae bacteremia in neonatal rats questions the theory of independent action

There is an abundance of information about the genetic basis, physiological and molecular mechanisms of bacterial pathogenesis. In contrast, relatively little is known about population dynamic processes, by which bacteria colonize hosts and invade tissues and cells and thereby cause disease. In an article published in 1978, Moxon and Murphy presented evidence that, when inoculated intranasally with a mixture streptomycin sensitive and resistant (SmS and SmR) and otherwise isogenic stains of Haemophilus influenzae type b (Hib), neonatal rats develop a bacteremic infection that often is dominated by only one strain, SmS or SmR. After rulling out other possibilities through years of related experiments, the field seems to have settled on a plausible explanation for this phenomenon: the first bacterium to invade the host activates the host immune response that shuts the door on the second invading strain. To explore this hypothesis in a necessarily quantitative way, we modeled this process with a set of mixed stochastic and deterministic differential equations. Our analysis of the properties of this model with realistic parameters suggests that this hypothesis cannot explain the experimental results of Moxon and Murphy, and in particular the observed relationship between the frequency of different types of blood infections (bacteremias) and the inoculum size. We propose modifications to the model that come closer to explaining these data. However, the modified and better fitting model contradicts the common theory of independent action of individual bacteria in establishing infections. We discuss the implications of these results.

Biophysics↗

bioRxiv2016

Length control of filamentous structures in cells by the limiting pool mechanism

How the size of organelles in cells is controlled despite a constant turnover of their constituent parts is a central problem in cell biology. A general mechanism has been proposed based on the idea that an organelle grows by self-assembly of molecular subunits that freely diffuse in the cytoplasm. Assembly continues until the available pool of subunits is depleted to the point when the stochastic addition and removal of subunits is balanced, leading to a structure of well-defined size. Here we focus on length control of multiple filamentous structures in cells, such as actin cables and flagella. Using queueing theory and computation we show that the limiting pool mechanism leads to three different phases of assembly, starting with a rapid growth phase when all filaments quickly accumulate a large number of available subunits. Then, the slower growing filamentous structures enter a disassembly phase as they gradually lose all of their subunits to the faster growing structures. Finally, when multiple, equivalent fast-growing filaments are present, their lengths undergo protracted diffusive dynamics due to the stochastic swapping of subunits between them. This eventually leads to a broad, power-law distribution of filament lengths in steady state. Our findings demonstrate that the limiting-pool mechanism is incapable of controlling lengths of multiple filamentous structures that are assembled from a common pool of subunits, and at best, can produce only one filament of a well-defined size. Overall, our theoretical results reveal physical limitations of the limiting-pool mechanism of organelle size control.\n\nSignificance StatementWhat determines the size of organelles in cells is a classic problem in cell biology. Recent experiments on mitotic spindles, and nucleolus have singled out the limiting-pool mechanism of size control. As these structures assemble, they deplete a finite pool of subunits present in the cell, thereby reducing the rate of subunit addition. Eventually the stochastic addition and removal of subunits are balanced and a well-defined size is achieved. We find that, while the limiting-pool mechanism does control the size of an individual structure, it fails when multiple structures are competing for the same pool of subunits. In that case we predict large size fluctuations and that the fastest growing structure takes up practically all the subunits from the pool.

Biophysics↗

bioRxiv2016

Ripping RNA by Force using Gaussian Network Models

Using force as a probe to map the folding landscapes of RNA molecules has become a reality thanks to major advances in single molecule pulling experiments. Although the unfolding pathways under tension are complicated to predict studies in the context of proteins have shown that topology plays is the major determinant of the unfolding landscapes. By building on this finding we study the responses of RNA molecules to force by adapting Gaussian network model (GNM) that represents RNAs using a bead-spring network with isotropic interactions. Cross-correlation matrices of residue fluctuations, which are analytically calculated using GNM even upon application of mechanical force, show distinct allosteric communication as RNAs rupture. The model is used to calculate the force-extension curves at full thermodynamic equilibrium, and the corresponding unfolding pathways of four RNA molecules subject to a quasi-statically increased force. Our study finds that the analysis using GNM captures qualitatively the unfolding pathway of T. ribozyme elucidated by the optical tweezers measurement. However, the simple model is not sufficient to capture subtle features, such as bifurcation in the unfolding pathways or the ion effects, in the forced-unfolding of RNAs.

Biophysics↗

bioRxiv2016

Diffusion of lipids and GPI-anchored proteins in actin-free plasma membrane vesicles measured by STED-FCS

Diffusion and interaction dynamics of molecules at the plasma membrane play an important role in cellular signalling. These have been suggested to be strongly associated with the actin cytoskeleton. Here, we utilise super-resolution STED microscopy combined with fluorescence correlation spectroscopy (STED-FCS) to access the sub-diffraction diffusion regime of different fluorescent lipid analogues and GPI-anchored proteins (GPI-APs) in the cellular plasma membrane, and compare it to the diffusion regime of these molecules in cell-derived actin-free giant plasma membrane vesicles (GPMVs). We show that phospholipids and sphingomyelin, which undergo hindered diffusion in the live cell membrane, diffuse freely in the GPMVs. In contrast to sphingomyelin, which is transiently trapped on molecular-scale complexes in intact cells, diffusion of the ganglioside lipid GM1 suggests transient incorporation into nanodomains, which is less influenced by the actin cortex. Finally, our data on GPI-APs indicate two molecular pools in living cells, one pool showing high mobility with trapped and compartmentalized diffusion, and the other forming immobile clusters both of which disappear in GPMVs. Our data underlines the crucial role of the actin cortex in maintaining hindered diffusion modes of most but not all membrane molecules.

Biophysics↗