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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2014

A statistical mechanics model for the collective epigenetic histone modification dynamics

Epigenetic histone modifications play an important role in the maintenance of different cell phenotypes. The exact molecular mechanism for inheritance of the modification patterns over cell generations remains elusive. We construct a Potts-type model based on experimentally observed nearest-neighbor enzyme lateral interactions and nucleosome covalent modification state biased enzyme recruitment. The model can lead to effective nonlocal interactions among nucleosomes suggested in previous theoretical studies, and epigenetic memory is robustly inheritable against stochastic cellular processes.\n\nPACS numbers: 82.39.Rt, 87.17.Aa, 87.16.Yc, 87.16.A

Biophysics↗

bioRxiv2014

Shifts in stability and control effectiveness during evolution of Paraves support aerial maneuvering hypotheses for flight origins

The capacity for aerial maneuvering was likely a major influence on the evolution of flying animals. Here we evaluate consequences of paravian morphology for aerial performance by quantifying static stability and control effectiveness of physical models for numerous taxa sampled from within the lineage leading to birds (Paraves). Results of aerodynamic testing are mapped phylogenetically to examine how maneuvering characteristics correspond to tail shortening, forewing elaboration, and other morphological features. In the evolution of Paraves we observe shifts from static stability to inherently unstable aerial planforms; control effectiveness also migrated from tails to the forewings. These shifts suggest that some degree of aerodynamic control and and capacity for maneuvering preceded the evolution of strong power stroke. The timing of shifts also suggests features normally considered in light of development of a power stroke may play important roles in control.

Biophysics↗

bioRxiv2014

Quantification of nuclear transport in single cells

Nuclear transport is an essential part of eukaryotic cell function. Several assays exist to measure the rate of this process, but not at the single-cell level. Here, we developed a fluorescent recovery after photobleaching (FRAP)- based method to determine nuclear import and export rates independently in individual live cells. To overcome the inherent noise of single-cell measurements, we performed sequential FRAPs on the same cell. We found large cell-to-cell variation in transport rates within isogenic yeast populations. Our data suggest that a main determinant of this heterogeneity may be variability in the number of nuclear pore complexes (NPCs). For passive transport, this component explained most of the variability. Actively transported proteins were influenced by variability in additional components, including general factors such as the Ran-GTP gradient as well as specific regulators of the export rate. By considering mother-daughter pairs, we showed that mitotic segregation of the transport machinery is too noisy to control cellular inheritance. Finally, we studied mother-daughter cell asymmetry in the localization of the transcription factor Ace2, which is specifically concentrated in daughter cell nuclei. We found that this asymmetry is the outcome of a higher ratio of import rate to export rate in daughters. Interestingly, rather than reduced export in the daughter cell, as previously hypothesized, rates of both import and export are faster in daughter cells than in mother cells, but the magnitude of increase is greater for import. These results shed light into cell-to-cell variation in cellular dynamics and its sources.

Biophysics↗

bioRxiv2014

Bayesian Energy Landscape Tilting: Towards Concordant Models of Molecular Ensembles

Predicting biological structure has remained challenging for systems such as disordered proteins that take on myriad conformations. Hybrid simulation/experiment strategies have been undermined by difficulties in evaluating errors from computa- tional model inaccuracies and data uncertainties. Building on recent proposals from maximum entropy theory and nonequilibrium thermodynamics, we address these issues through a Bayesian Energy Landscape Tilting (BELT) scheme for computing Bayesian \"hyperensembles\" over conformational ensembles. BELT uses Markov chain Monte Carlo to directly sample maximum-entropy conformational ensembles consistent with a set of input experimental observables. To test this framework, we apply BELT to model trialanine, starting from disagreeing simulations with the force fields ff96, ff99, ff99sbnmr-ildn, CHARMM27, and OPLS-AA. BELT incorporation of limited chemical shift and 3J measurements gives convergent values of the peptides , {beta}, and PPII conformational populations in all cases. As a test of predictive power, all five BELT hyperensembles recover set-aside measurements not used in the fitting and report accu- rate errors, even when starting from highly inaccurate simulations. BELTs principled fxramework thus enables practical predictions for complex biomolecular systems from discordant simulations and sparse data.

Biophysics↗

bioRxiv2014

Genetic drift suppresses bacterial conjugation in spatially structured populations

Conjugation is the primary mechanism of horizontal gene transfer that spreads antibiotic resistance among bacteria. Although conjugation normally occurs in surface-associated growth (e.g., biofilms), it has been traditionally studied in well-mixed liquid cultures lacking spatial structure, which is known to affect many evolutionary and ecological processes. Here we visualize spatial patterns of gene transfer mediated by F plasmid conjugation in a colony of Escherichia coli growing on solid agar, and we develop a quantitative understanding by spatial extension of traditional mass-action models. We found that spatial structure suppresses conjugation in surface-associated growth because strong genetic drift leads to spatial isolation of donor and recipient cells, restricting conjugation to rare boundaries between donor and recipient strains. These results suggest that ecological strategies, such as enforcement of spatial structure and enhancement of genetic drift, could complement molecular strategies in slowing the spread of antibiotic resistance genes.

Biophysics↗

bioRxiv2014

Chromatin Loops as Allosteric Modulators of Enhancer-Promoter Interactions

The classic model of eukaryotic gene expression requires direct spatial contact between a distal enhancer and a proximal promoter. Recent Chromosome Conformation Capture (3C) studies show that enhancers and promoters are embedded in a complex network of looping interactions. Here we use a polymer model of chromatin fiber to investigate whether, and to what extent, looping interactions between elements in the vicinity of an enhancer-promoter pair can influence their contact frequency. Our equilibrium polymer simulations show that a chromatin loop, formed by elements flanking either an enhancer or a promoter, suppresses enhancer-promoter interactions, working as an insulator. A loop formed by elements located in the region between an enhancer and a promoter, on the contrary, facilitates their interactions. We find that different mechanisms underlie insulation and facilitation; insulation occurs due to steric exclusion by the loop, and is a global effect, while facilitation occurs due to an effective shortening of the enhancer-promoter genomic distance, and is a local effect. Consistently, we find that these effects manifest quite differently for in silico 3C and microscopy. Our results show that looping interactions that do not directly involve an enhancer-promoter pair can nevertheless significantly modulate their interactions. This phenomenon is analogous to allosteric regulation in proteins, where a conformational change triggered by binding of a regulatory molecule to one site affects the state of another site.\n\nAuthor SummaryIn eukaryotes, enhancers directly contact promoters over large genomic distances to regulate gene expression. Characterizing the principles underlying these long-range enhancer-promoter contacts is crucial for a full understanding of gene expression. Recent experimental mapping of chromosomal interactions by the Hi-C method shows an intricate network of local looping interactions surrounding enhancers and promoters. We model a region of chromatin fiber as a long polymer and study how the formation of loops between certain regulatory elements can insulate or facilitate enhancer-promoter interactions. We find 2-5 fold insulation or facilitation, depending on the location of looping elements relative to an enhancer-promoter pair. These effects originate from the polymer nature of chromatin, without requiring additional mechanisms beyond the formation of a chromatin loop. Our findings suggest that loop-mediated gene regulation by elements in the vicinity of an enhancer-promoter pair can be understood as an allosteric effect. This highlights the complex effects that local chromatin organization can have on gene regulation.

Biophysics↗

bioRxiv2014

Does ‘information control the living state’?

We generalize the recently-uncovered Data Rate Theorem in the context of cognitive systems having a dual information source, including those of the living state that is particularly characterized by cognition at every scale and level of organization. The unification of information theory and control theory via the Data Rate Theorem is not additive, but synergistic, generating new statistical tools that greatly constrain the possible dynamics of that state. Thus, in addition to providing novel conceptual approaches, this emerging body of theory permits construction of models that, like those of regression analysis, can provide benchmarks against which to compare experimental or observational data.

Biophysics↗

bioRxiv2014

Spatial epidemiology of networked metapopulation: An overview

An emerging disease is one infectious epidemic caused by a newly transmissible pathogen, which has either appeared for the first time or already existed in human populations, having the capacity to increase rapidly in incidence as well as geographic range. Adapting to human immune system, emerging diseases may trigger large-scale pandemic spreading, such as the transnational spreading of SARS, the global outbreak of A(H1N1), and the recent potential invasion of avian influenza A(H7N9). To study the dynamics mediating the transmission of emerging diseases, spatial epidemiology of networked metapopulation provides a valuable modeling framework, which takes spatially distributed factors into consideration. This review elaborates the latest progresses on the spatial metapopulation dynamics, discusses empirical and theoretical findings that verify the validity of networked metapopulations, and the application in evaluating the effectiveness of disease intervention strategies as well.

Biophysics↗

bioRxiv2014

Cell size regulation in bacteria

Various bacteria such as the canonical gram negative Escherichia coli or the well-studied gram positive Bacillus subtilis divide symmetrically after they approximately double their volume. Their size at division is not constant, but is typically distributed over a narrow range. Here, we propose an analytically tractable model for cell size control, and calculate the cell size and inter-division time distributions, and the correlations between these variables. We suggest ways of extracting the model parameters from experimental data, and show that existing data for E. coli supports partial size control, and a particular explanation: a cell attempts to add a constant volume from the time of initiation of DNA replication to the next initiation event. This hypothesis accounts for the experimentally observed correlations between mother and daughter cells as well as the exponential dependence of size on growth rate.\n\nPACS numbers: 87.17.Ee, 87.17.Aa, 87.10.Mn, 87.81Tt

Biophysics↗

bioRxiv2014

Bio-inspired design of ice-retardant devices based on benthic marine invertebrates: the effect of surface texture

Growth of ice on surfaces poses a challenge for both organisms and for devices that come into contact with liquids below the freezing point. Resistance of some organisms to ice formation and growth, either in subtidal environments (e.g. Antarctic anchor ice), or in environments with moisture and cold air (e.g. plants, intertidal) begs examination of how this is accomplished. Several factors may be important in promoting or mitigating ice formation. As a start, here we examine the effect of surface texture alone. We tested four candidate surfaces, inspired by hard-shelled marine invertebrates and constructed using a three-dimensional printing process. We screened biological and artifical samples for ice formation and accretion in submerged conditions using previous methods, and developed a new test to examine ice formation from surface droplets as might be encountered in environments with moist, cold air. It appears surface texture plays only a small role in delaying the onset of ice formation: a stripe feature (corresponding to patterning found on valves of blue mussels, Mytilus edulis, or on the spines of the Antarctic sea urchin Sterechinus neumayeri) slowed ice formation an average of 25% compared to a grid feature (corresponding to patterning found on sub-polar butterclams, Saxidomas nuttalli). The geometric dimensions of the features have only a small ([~]6%) effect on ice formation. Surface texture affects ice formation, but does not explain by itself the large variation in ice formation and species-specific ice resistance observed in other work. This suggests future examination of other factors, such as material elastic properties and coatings, and their interaction with surface pattern.

Biophysics↗

bioRxiv2014

The dynamics of sperm cooperation in a competitive environment

Sperm cooperation has evolved in a variety of taxa and is often considered a response to sperm competition, yet the benefit of this form of collective movement remains unclear. Here we use fine-scale imaging and a minimal mathematical model to study sperm aggregation in the rodent genus Peromyscus. We demonstrate that as the number of sperm cells in an aggregate increase, the group moves with more persistent linearity but without increasing speed; this benefit, however, is offset in larger aggregates as the geometry of the group forces sperm to swim against one another. The result is a non-monotonic relationship between aggregate size and average velocity with both a theoretically predicted and empirically observed optimum of 6-7 sperm/aggregate. To understand the role of sexual selection in driving these sperm group dynamics, we compared two sister-species with divergent mating systems and find that sperm of P. maniculatus (highly promiscuous), which have evolved under intense competition, form optimal-sized aggregates more often than sperm of P. polionotus (strictly monogamous), which lack competition. Our combined mathematical and experimental study of coordinated sperm movement reveals the importance of geometry, motion and group size on sperm velocity and suggests how these physical variables interact with evolutionary selective pressures to regulate cooperation in competitive environments.

Biophysics↗

bioRxiv2014

Null Models for Community Detection in Spatially-Embedded, Temporal Networks

In the study of networks, it is often insightful to use algorithms to determine mesoscale features such as \"community structure\", in which densely connected sets of nodes constitute \"communities\" that have sparse connections to other communities. The most popular way of detecting communities algorithmically is to optimize the quality function known as modularity. When optimizing modularity, one compares the actual connections in a (static or time-dependent) network to the connections obtained from a random-graph ensemble that acts as a null model. The communities are then the sets of nodes that are connected to each other densely relative to what is expected from the null model. Clearly, the process of community detection depends fundamentally on the choice of null model, so it is important to develop and analyze novel null models that take into account appropriate features of the system under study. In this paper, we investigate the effects of using null models that take incorporate spatial information, and we propose a novel null model based on the radiation model of population spread. We also develop novel synthetic spatial benchmark networks in which the connections between entities are based on distance or flux between nodes, and we compare the performance of both static and time-dependent radiation null models to the standard (\"Newman-Girvan\") null model for modularity optimization and a recently-proposed gravity null model. In our comparisons, we use both the above synthetic benchmarks and time-dependent correlation networks that we construct using countrywide dengue fever incidence data for Peru. We also evaluate a recently-proposed correlation null model, which was developed specifically for correlation networks that are constructed from time series, on the epidemic-correlation data. Our findings underscore the need to use appropriate generative models for the development of spatial null models for community detection.\n\nPACS numbers87.19.Xx,89.20.-a,89.75.Fb,05.45.Tp

Biophysics↗

bioRxiv2014

Side-binding proteins modulate actin filament dynamics

Actin filament dynamics govern many key physiological processes from cell motility to tissue morphogenesis. A central feature of actin dynamics is the capacity of the filament to polymerize and depolymerize at its ends in response to cellular conditions. It is currently thought that filament kinetics can be described by a single rate constant for each end. Here, using direct visualization of single actin filament elongation, we show that actin polymerization kinetics at both filament ends are strongly influenced by proteins that bind to the lateral filament surface. We also show that the less dynamic end, called the pointed-end, has a non-elongating state that dominates the observed filament kinetic asymmetry. Estimates of filament flexibility and Brownian dynamics simulations suggest that the observed kinetic diversity arises from structural alteration. Tuning filament kinetics by exploiting the natural malleability of the actin filament structure may be a ubiquitous mechanism to generate the rich variety of observed cellular actin dynamics.

Biophysics↗

bioRxiv2014

A Fast 3 x N Matrix Multiply Routine for Calculation of Protein RMSD

The bottleneck for the rapid calculation of the root-mean-square deviation in atomic coordinates (RMSD) between pairs of protein structures for large numbers of conformations is the evaluation of a 3 x N x N x 3 matrix product over conformation pairs. Here we describe two matrix multiply routines specialized for the 3 x N case that are able to significantly outperform (by up to 3X) off-the-shelf high-performance linear algebra libraries for this computation, reaching machine limits on performance. The routines are implemented in C and Python libraries, and are available at https://github.com/simtk/IRMSD.

Biophysics↗

bioRxiv2014

Oncogenic mutations of the EGF-Receptor ectodomain reveal an unexpected mechanism for ligand-independent activation

Epidermal Growth Factor Receptor (EGFR) signaling is supposed to be triggered by a dramatic ligand-induced conformational change of the extracellular domain from a closed, self-inhibited tethered monomer, to an open untethered state, which exposes a loop required for dimerization and activation. The ectodomain also untethers spontaneously, but the molecular mechanism is still unknown. Experiments with the mAb806 antibody have suggested the existence of a third untethered state, still uncharacterized, appearing transiently during the tethered to untethered transition, and which exposes a cryptic epitope hidden in the known structures. Here, molecular dynamics simulations of two ectodomain mutants (R84K and G39R) targeting a hinge at domain I-II interface highlight the possibility of such additional intermediate conformer. The new conformation is untethered but surprisingly compact, and originates from a large rotation of domain I that exposes the mAb806 epitope, in a similar way as the EGFRvIII deletion does. The present findings not only point to different molecular processes for ligand-dependent and spontaneous untethering, but also suggest that domain I-II mutation clusters and the EGFRvIII deletion may share a common structural mechanism, based on the removal of an steric hindrance from domain I that restricts dimerization.

Biophysics↗

bioRxiv2014

DNA Denaturing through UV-C Photon Dissipation: A Possible Route to Archean Non-enzymatic Replication

Formidable difficulties arise when attempting to explain the non-enzymatic replication, proliferation, and the acquisition of homochirality and information content, of RNA and DNA at the beginnings of life. However, new light can be shed on these problems by viewing the origin of life as a non-equilibrium thermodynamic process in which RNA, DNA and other fundamental molecules of life arose as structures to dissipate the prevailing solar spectrum. Here we present experimental results which demonstrate that the absorption and dissipation of UV-C light by DNA at temperatures below their melting temperature leads to complete and reversible denaturing for small synthetic DNA of 25 base pairs (bp), and to partial and reversible denaturing for 48 bp DNA and for large salmon sperm and yeast DNA of average size 100 kbp. This result has direct bearing on the above mentioned problems and thereby opens the door to a possible thermodynamic route to the origin of life.

Biophysics↗

bioRxiv2014

Exact solutions of linear reaction-diffusion processes on a uniformly growing domain: Criteria for successful colonization

Many processes during embryonic development involve transport and reaction of molecules, or transport and proliferation of cells, within growing tissues. Mathematical models of such processes usually take the form of a reaction-diffusion partial differential equation (PDE) on a growing domain. Previous analyses of such models have mainly involved solving the PDEs numerically. Here, we present a framework for calculating the exact solution of a linear reaction-diffusion PDE on a growing domain. We derive an exact solution for a general class of one-dimensional linear reaction-diffusion process on 0 < x < L(t), where L(t) is the length of the growing domain. Comparing our exact solutions with numerical approximations confirms the veracity of the method. Furthermore, our examples illustrate a delicate interplay between: (i) the rate at which the domain elongates, (ii) the diffusivity associated with the spreading density profile, (iii) the reaction rate, and (iv) the initial condition. Altering the balance between these four features leads to different outcomes in terms of whether an initial profile, located near x = 0, eventually overcomes the domain growth and colonizes the entire length of the domain by reaching the boundary where x = L(t).

Biophysics↗

bioRxiv2014

Phase transitions in tumor growth: II prostate cancer cell lines

We propose a mechanism for prostate cancer cell lines growth, e.g., LNCaP and PC3 based on a Gompertz dynamics. This growth exhibits a multifractal behavior and a \"second order\" phase transition. Finally, it was found that the cellular line PC3 exhibits a higher value the entropy production rate compared to LNCaP, which is indicative of the robustness of PC3, over to LNCaP and may be a quantitative index of metastatic potential tumors.\n\nHighlightsO_LICancer is an open, complex, dynamic and self-organizing system.\nC_LIO_LIProstate cancer cell lines growth follows a Gompertz dynamics\nC_LIO_LIProstate cancer cell lines exhibit a multifractal behavior\nC_LIO_LIThe entropy production rate may be considered as metastatic potential marker\nC_LI

Biophysics↗