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bioRxiv2017

Bacterial Communication And Relevance Of Quantum Theory

The recent findings confirm that bacteria communicate each other through chemical and electrical signals. Bacteria use chemical signaling molecules which are called as quorum sensing molecules(QSMs) or autoinducers. Moreover, the ion channels in bacteria conduct a long-range electrical signaling within biofilm communities through propagated waves of potassium ions and biofilms attracts other bacterial species too. Both communication process are used by bacteria to make their own survival strategies. In this article, we model this bacterial communication mechanism by complex Ginzburg- Landau equation and discuss the formation of patterns depending on kinematic viscosity associated with internal noise. Again, the potassium wave propagation is described by the non-linear Schrodinger equation in a dissipative environment. By adding perturbation to non-linear Schrodinger equation one arrives at Complex Ginzburg-Landau equation. In this paper we emphasize that at the cellular level(bacteria) we use Complex Ginzburg - Landau equation as a perturbed Nonlinear Schrodinger equation to understand the bacterial communication as well as pattern formation in Biofilms for certain range of kinematic viscosity which can be tested in laboratory experiment. Here, the perturbation is due to the existence of non thermal fluctuations associated to the finite size of the bacteria. It sheds new light on the relevance of quantum formalism in understanding the cell to cell communication.

biophysics↗

bioRxiv2017

Compartmental and spatial rule-based modeling with Virtual cell (VCell)

In rule-based modeling, molecular interactions are systematically specified in the form of reaction rules that serve as generators of reactions. This provides a way to account for all the potential molecular complexes and interactions among multivalent or multistate molecules. Recently, we introduced rule- based modeling into the Virtual Cell (VCell) modeling framework, permitting graphical specification of rules and merger of networks generated automatically (using the BioNetGen modeling engine) with hand-specified reaction networks. VCell provides a number of ordinary differential equation (ODE) and stochastic numerical solvers for single-compartment simulations of the kinetic systems derived from these networks, and agent-based network-free simulation of the rules. In this work, compartmental and spatial modeling of rule-based models has been implemented within VCell. To enable rule-based deterministic and stochastic spatial simulations and network-free agent-based compartmental simulations, the BioNetGen and NFSim engines were each modified to support compartments. In the new rule-based formalism, every reactant and product pattern and every reaction rule are assigned locations. We also introduce the novel rule-based concept of molecular anchors. This assures that any species that has a molecule anchored to a predefined compartment will remain in this compartment. Importantly, in addition to formulation of compartmental models, this now permits VCell users to seamlessly connect reaction networks derived from rules to explicit geometries to automatically generate a system of reaction-diffusion equations. These may then be simulated using either the VCell partial differential equations (PDE) deterministic solvers or the Smoldyn stochastic simulator.

biophysics↗

bioRxiv2017

qSR: A software for quantitative analysis of single molecule and super-resolution data

Single-molecule based super-resolution microscopy (Betzig et al., 2006; Hess et al., 2006; Rust et al., 2006) provides insight into the spatiotemporal organization and dynamics of biomolecules at the length scale of ten to hundreds of nanometers, which is most relevant to protein clustering in a broad range of cellular processes. A series of quantitative analysis approaches have been developed to infer the characteristic size of protein clustering via pair correlation analysis (Sengupta et al., 2013; Sengupta et al., 2011; Veatch et al., 2012) or to merge multiple blinking localizations from single fluorophores (Annibale et al., 2011), to identify clusters based on density of detections (Ester, 1996), and to measure temporal dynamics of protein clustering in living cells (Cho et al., 2016a; ...

biophysics↗

bioRxiv2017

A Bayesian computational approach to explore the optimal duration of a cell proliferation assay

Cell proliferation assays are routinely used to explore how a low density monolayer of cells grows with time. For a typical cell line with a doubling time of 12 hours (or longer), a standard cell proliferation assay conducted over 24 hours provides excellent information about the low-density exponential growth rate, but limited information about crowding effects that occur at higher densities. To explore how we can best detect and quantify crowding effects, we present a suite of in silico proliferation assays where cells proliferate according to a generalised logistic growth model. Using approximate Bayesian computation we show that data from a standard cell proliferation assay cannot reliably distinguish between classical logistic growth and more general non-logistic growth models. We then explore, and quantify, the trade-off between increasing the duration of the experiment and the associated decrease in uncertainty in the crowding mechanism.

biophysics↗

bioRxiv2017

eIF4A is stimulated by the pre-initiation complex and enhances recruitment of mRNAs regardless of structural complexity

eIF4A is a DEAD-box RNA-dependent ATPase thought to unwind RNA secondary structure in the 5'-untranslated regions (UTRs) of mRNAs to promote their recruitment to the eukaryotic translation pre-initiation complex (PIC). We show that eIF4As ATPase activity is markedly stimulated in the presence of the PIC, independently of eIF4E*eIF4G, but dependent on subunits i and g of the heteromeric eIF3 complex. Surprisingly, eIF4A accelerated the rate of recruitment of all mRNAs tested, regardless of their degree of structural complexity. Structures in the 5'-UTR and 3' of the start codon synergistically inhibit mRNA recruitment in a manner relieved by eIF4A, indicating that the factor does not act solely to melt hairpins in 5'-UTRs. Our findings that eIF4A functionally interacts with the PIC and plays important roles beyond unwinding 5-UTR structure is consistent with a recent proposal that eIF4A modulates the conformation of the 40S ribosomal subunit to promote mRNA recruitment.

biophysics↗

bioRxiv2017

Near-Atomic Resolution Structure Determination in Over-Focus with Volta Phase Plate by Cs-corrected Cryo-EM

Volta phase plate (VPP) is a recently developed transmission electron microscope (TEM) apparatus that can significantly enhance the image contrast of biological samples in cryo-electron microscopy (cryo-EM) therefore impose the possibility to solve structures of relatively small macromolecules at high resolution. In this work, we performed theoretical analysis and found that using phase plate on objective lens spherical aberration (Cs)-corrected TEM may gain some interesting optical properties, including the over-focus imaging of macromolecules. We subsequently evaluated the imaging strategy of frozen-hydrated apo-ferritin with VPP on a Cs-corrected TEM and obtained the structure of apo-ferritin at near atomic resolution from both under- and over-focused dataset, illustrating the feasibility and new potential of combining VPP with Cs-corrected TEM for high resolution cryo-EM.\n\nHighlightsThe successful combination of volta phase plate and Cs-corrector in single particle cryo-EM.\n\nNear-atomic structure determined from over-focused images by cryo-EM. VPP-Cs-corrector coupled EM provides interesting optical properties.\n\nIn BriefWe took the unique advantage of the optical system by combining the volta phase plate and Cs-corrector in a modern TEM to collect high resolution micrographs of frozen-hydrated apo-ferritin in over-focus imaging conditions and determined the structure of apo-ferritin at 3.0 Angstrom resolution.

biophysics↗

bioRxiv2017

A First Order Phase Transition Underlies the Formation of Sub-Diffractive Protein Aggregates in Mammalian Cells

Failure in protein quality control can often lead to protein aggregation, yet in neuro-degenerative diseases, by the time aggregates can be seen, the cells have advanced well into the disease pathology. Here, we develop a quantitative imaging approach to study the protein aggregation process in living mammalian cells with unprecedented spatio-temporal resolution. We find that sub-diffractive precursor aggregates may form even in untreated cells, and their size distribution is exactly as predicted for a system undergoing a first order phase transition. Practically, this implies that as soon as aggregates reach a critical size (Rc = 162 {+/-} 4 nm untreated cells), they will spontaneously grow into large inclusions. Our data suggest that a previously uncharacterized, RuvBL1 dependent mechanism clears aggregates above the critical size. Our study unveils the existence of sub-diffractive aggregates in living cells; and the strong agreement between cellular data and a nucleation theory, based on first order phase transition, provides insight into regulatory steps in the early stages of aggregate formation in vivo.

biophysics↗

bioRxiv2017

Sperm chemotaxis is driven by the slope of the chemoattractant concentration field

Spermatozoa of marine invertebrates are attracted to their conspecific female gamete by diffusive molecules, called chemoattractants, released from the egg investments in a process known as chemotaxis. The information from the egg chemoattractant concentration field is decoded into intracellular Ca2+ concentration ([Ca2+]i) changes that regulate the internal motors that shape the flagellum as it beats. By studying sea urchin species-specific differences in sperm chemoattractant-receptor characteristics we show that receptor density constrains the steepness of the chemoattractant concentration gradient detectable by spermatozoa. Through analyzing different chemoattractant gradient forms, we demonstrate for the first time that Strongylocentrotus purpuratus sperm are chemotactic and this response is consistent with frequency entrainment of two coupled physiological oscillators: i) the stimulus function and ii) the [Ca2+]i changes. We demonstrate that the slope of the chemoattractant gradients provides the coupling force between both oscillators, arising as a fundamental requirement for sperm chemotaxis.

biophysics↗

bioRxiv2017

Real-time detection of condensin-driven DNA compaction reveals a multistep binding mechanism

Condensin, a conserved member of the SMC protein family of ring-shaped multi-subunit protein complexes, is essential for structuring and compacting chromosomes. Despite its key role, its molecular mechanism has remained largely unknown. Here, we employ single-molecule magnetic tweezers to measure, in real-time, the compaction of individual DNA molecules by the budding yeast condensin complex. We show that compaction proceeds in large (~200nm) steps, driving DNA molecules into a fully condensed state against forces of up to 2pN. Compaction can be reversed by applying high forces or adding buffer of high ionic strength. While condensin can stably bind DNA in the absence of ATP, ATP hydrolysis by the SMC subunits is required for rendering the association salt-insensitive and for subsequent compaction. Our results indicate that the condensin reaction cycle involves two distinct steps, where condensin first binds DNA through electrostatic interactions before using ATP hydrolysis to encircle the DNA topologically within its ring structure, which initiates DNA compaction. The finding that both binding modes are essential for its DNA compaction activity has important implications for understanding the mechanism of chromosome compaction.

biophysics↗

bioRxiv2017

Predicting DNA Hybridization Kinetics from Sequence

Hybridization is a key molecular process in biology and biotechnology, but to date there is no predictive model for accurately determining hybridization rate constants based on sequence information. To approach this problem systematically, we first performed 210 fluorescence kinetics experiments to observe the hybridization kinetics of 100 different DNA target and probe pairs (subsequences of the CYCS and VEGF genes) at temperatures ranging from 28 {degrees}C to 55 {degrees}C. Next, we rationally designed 38 features computable based on sequence, each feature individually correlated with hybridization kinetics. These features are used in our implementation of a weighted neighbor voting (WNV) algorithm, in which the hybridization rate constant of an unknown sequence is predicted based on similarity reactions with known rate constants (a.k.a. labeled instances). Automated feature selection and weighting optimization resulted in a final 6-feature WNV model, which can predict hybridization rate constants of new sequences to within a factor of 2 with {approx}74% accuracy and within a factor of 3 with {approx}92% accuracy, based on leave-one-out cross-validation. Predictive understanding of hybridization kinetics allows more efficient design of nucleic acid probes, for example in allowing sparse hybrid-capture panels to more quickly and economically enrich desired regions from genomic DNA.

biophysics↗

bioRxiv2017

Hemodynamic forces can be accurately measured in vivo with optical tweezers

Force sensing and generation at the tissular and cellular scale is central to many biological events. There is a growing interest in modern cell biology for methods enabling force measurements in vivo. Optical trapping allows non-invasive probing of pico-Newton forces and thus emerged as a promising mean for assessing biomechanics in vivo. Nevertheless, the main obstacles rely in the accurate determination of the trap stiffness in heterogeneous living organisms, at any position where the trap is used. A proper calibration of the trap stiffness is thus required for performing accurate and reliable force measurements in vivo. Here, we introduce a method that overcomes these difficulties by accurately measuring hemodynamic profiles in order to calibrate the trap stiffness. Doing so, and using numerical methods to assess the accuracy of the experimental data, we measured flow profiles and drag forces imposed to trapped red blood cells of living zebrafish embryos. Using treatments enabling blood flow tuning, we demonstrated that such method is powerful in measuring hemodynamic forces in vivo with high accuracy and confidence. Altogether, this study demonstrates the power of optical tweezing in measuring low range hemodynamic forces in vivo and offers an unprecedented tool in both cell and developmental biology.

biophysics↗

bioRxiv2017

Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations

The drug design data resource (D3R) consortium organises blinded challenges to address the latest advances in computational methods for ligand pose prediction, affinity ranking, and free energy calculations. Within the context of the second D3R Grand Challenge several blinded binding free energies predictions were made for two congeneric series of FXR inhibitors with a semi-automated alchemical free energy calculations workflow featuring the FESetup and SOMD tools. Reasonable performance was observed in retrospective analyses of literature datasets. Nevertheless blinded predictions on the full D3R datasets were poor due to difficulties encountered with the ranking of compounds that vary in their net-charge. Performance increased for predictions that were restricted to subsets of compounds carrying the same net-charge. Disclosure of X-ray crystallography derived binding modes maintained or improved the correlation with experiment in a subsequent rounds of predictions. The best performing protocols on D3R set1 and set2 were comparable or superior to predictions made on the basis of analysis of literature SARs only, and comparable or slightly inferior, to the best submissions from other groups.

biophysics↗

bioRxiv2017

Triazavirine supramolecular complexes as modifiers of the peptide oligomeric structure

In this study we present molecular dynamics simulations of the antiviral drug triazavirine, that affects formation of amyloid-like fibrils of the model peptide (SI). According to our simulations, triazavirine is able to form linear supramolecular structures which can act as shields and prevent interactions between SI monomers. This model, as validated by simulations, provides an adequate explanation of triazavirines mechanism of action as it pertains to SI peptide fibril formation.

biophysics↗

bioRxiv2017

Out-of-equilibrium statistical dynamics of spatial pattern generating cellular automata

How living systems generate order from disorder is a fundamental question1-5. Metrics and ideas from physical systems have elucidated order-generating collective dynamics of mechanical, motile, and electrical living systems such as bird flocks and neuronal networks6-8. But suitable metrics and principles remain elusive for many networks of cells such as tissues that collectively generate spatial patterns via chemical signals, genetic circuits, and dynamics representable by cellular automata1,9-11. Here we reveal such principles through a statistical mechanics-type framework for cellular automata dynamics in which cells with ubiquitous genetic circuits generate spatial patterns by switching on and off each others genes with diffusing signalling molecules. Lattices of cells behave as particles stochastically rolling down a pseudo-energy landscape - defined by a spin glass-like Hamiltonian - that is shaped by \"macrostate\" functions and genetic circuits. Decreasing the pseudo-energy increases the spatial patterns orderliness. A new kinetic trapping mechanism - \"pathway trapping\" - yields metastable spatial patterns by preventing minimization of the particles pseudo-energy. Noise in cellular automata reduces the trapping, thus further increases the spatial order. We generalize our framework to lattices with multiple types of cells and signals. Our work shows that establishing statistical mechanics of computational algorithms can reveal collective dynamics of signal-processing in biological and physical networks.

biophysics↗

bioRxiv2017

Bridging the dynamics and organization of chromatin domains by mathematical modeling

The genome is three-dimensionally organized in the cell, and the mammalian genome DNA is partitioned into submegabase-sized chromatin domains. Genome functions are regulated within and across the domains according to their organization, whereas the chromatin itself is highly dynamic. However, the details of such dynamic organization of chromatin domains in living cells remain unclear. To unify chromatin dynamics and organization, we recently demonstrated that structural information of chromatin domains in living human cells can be extracted from analyses of the subdiffusive nucleosome movement using mathematical modeling. Our mathematical analysis suggested that as the chromatin domain becomes smaller and more compact, nucleosome movement becomes increasingly restricted. Here, we show the implication of these results for bridging the gap between chromatin dynamics and organization, and provide physical insight into chromatin domains as efficient units to conduct genome functions in the thermal noisy environment of the cell.\n\nExtra View toShinkai S, Nozaki T, Maeshima K, Togashi Y. Dynamic Nucleosome Movement Provides Structural Information of Topological Chromatin Domains in Living Human Cells. PLoS Comput Biol. 2016;12(10):e1005136. doi: 10.1371/journal.pcbi.1005136. PubMed PMID: 27764097; PubMed Central PMCID: PMCPMC5072619.\n\nFundingThis work was supported by Platform Project for Supporting in Drug Discovery and Life Science Research (Platform for Dynamic Approaches to Living System) from MEXT and AMED; KAKENHI under Grant JP16H01408, JP23115007, JP23115005, JP16H04746; CREST grant (JPMJCR15G2) from JST; and Research Fellowship for Young Scientists under Grant JP13J04821, JP16J07205.\n\nDisclosureNo potential conflicts of interest were disclosed.\n\nAcknowledgementsWe would like to thank Dr. Takashi Toda for comments regarding the manuscript.

biophysics↗

bioRxiv2017

Partitioning and Enhanced Self-Assembly of Actin in Polypeptide Coacervates

Biomolecules exist and function in cellular micro-environments that control their spatial organization, local concentration and biochemical reactivity. Due to the complexity of native cytoplasm, the development of artificial bioreactors and cellular mimics to compartmentalize, concentrate and control the local physicochemical properties is of great interest. Here, we employ self-assembling polypeptide coacervates to explore the partitioning of the ubiquitous cytoskeletal protein actin into liquid polymer-rich droplets. We find that actin spontaneously partitions into coacervate droplets and is enriched by up to {approx}30-fold. Actin polymerizes into micrometer-long filaments and, in contrast to the globular protein BSA, these filaments localize predominately to the droplet periphery. We observe up to a 50-fold enhancement in the actin filament assembly rate inside coacervate droplets, consistent with the enrichment of actin within the coacervate phase. Together these results suggest that coacervates can serve as a versatile platform in which to localize and enrich biomolecules to study their reactivity in physiological environments.\n\nSIGNIFICANCE STATEMENTLiving cells harbor many protein-rich membrane-less organelles, the biological functions of which are defined by compartment composition and properties. Significant differences between the physico-chemical properties of these crowded compartments and the dilute solutions in which biochemical reactions are traditionally studied pose a major challenge for understanding regulation of organelle composition and component activity. Here, we report the spontaneous partitioning and accelerated polymerization of the cytoskeletal protein actin inside model polypeptide coacervates as a proof-of-concept demonstration of coacervates as bioreactors for studying biomolecular reactions in cell-like environments. Our work introduces exciting avenues for the use of synthetic polymers to control the physical and biological properties of bioreactors in vitro, enabling studies of biochemical reactions in cell-like micro-environments.

biophysics↗

bioRxiv2017

Molecular insights into conformational dynamics associated with the open-closed-phosphorylated states of PITPα

Phosphatidylinositol transfer proteins (PITP) are lipid carrier proteins that are involved in replenishing the phosphatidylinositol lipid molecules on the plasma membranes. Transitions between the open and closed state conformations are necessary steps in the mechanism of lipid transfer by PITP. The apo (open state) conformation is assumed to occur at the membrane surface during the lipid exchange while the lipid bound (closed state) conformation is required for transfer activity. The transfer of phosphatidylinositol by PITP is controlled by the phosphorylation of S166 in its regulatory region. We wanted to decipher the molecular basis for structure-function relationship between the open-closed-phosphorylated states of PITP. We used all-atom Molecular Dynamics Simulations to study the conformational dynamics in each of these states. Our study shows that the open state is highly dynamic and its transition to closed state would stabilize PITP. We observed restricted conformational sampling of the phosphorylated state which provide basis for its decreased lipid transfer activity. Further, using analysis of residue-residue contact maps and hydrogen bond interactions we discuss the impact of phosphorylation on the global conformation of PITP. Overall, our work provides insights into the structural dynamics in each state and their functional significance.

biophysics↗

bioRxiv2017

Impact of fluorescent protein fusions on the bacterial flagellar motor

Fluorescent fusion proteins open a direct and unique window onto protein function. However, they also introduce the risk of perturbation of the function of the native protein. Successful applications of fluorescent fusions therefore rely on a careful assessment and minimization of the side effects. Such insight, however, is still lacking for many applications of fluorescent fusions. This is particularly relevant in the study of the internal dynamics of motor protein complexes, where both the chemical and mechanical reaction coordinates can be affected. Fluorescent proteins fused to the stator of the bacterial flagellar motor (BFM) complex have previously been used to successfully unveil the internal subunit dynamics of the motor. Here we report the effects of three different fluorescent proteins fused to the stator, all of which altered BFM behavior. The torque generated by individual stators was reduced while their stoichiometry in the complex remained unaffected. MotB fusions decreased the rotation-direction switching frequency of single motors and induced a novel BFM behavior: a bias-dependent asymmetry in the speed attained in the two rotation directions. All these effects could be mitigated by the insertion of a linker at the fusion point. These findings provide a quantitative account of the effects of fluorescent fusions on BFM dynamics and their alleviation--new insights that advance the use of fluorescent fusions to probe the dynamics of protein complexes.\n\nAuthor summaryMuch of what is known about the biology of proteins was discovered by fusing them to fluorescent proteins that allow detection of their location. But the label comes at a cost: the presence of the tag can alter the behavior of the protein of interest in unforeseen, yet biologically relevant ways. These side effects limit the depth to which fluorescent proteins can be used to probe protein function. One of the systems that has been successfully studied with fluorescent fusions for which these effects have not been addressed are dynamic protein complexes that carry out mechanical work. We examined how fluorescent proteins fused to a component of the bacterial flagellar motor complex impacts its function. Our findings show that the fusion proteins altered biologically relevant dynamical properties of the motor, including induction of a novel mechanical behavior, and demonstrate an approach to alleviate this. These results advance our ability to dissect the bacterial flagellar motor, and the internal dynamics of protein complexes in general, with fluorescent fusion proteins while causing minimal perturbation.

biophysics↗