Journal Cover PLoS Computational Biology
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   ISSN (Print) 1553-734X - ISSN (Online) 1553-7358
   Published by PLoS Homepage  [13 journals]
  • The Pathway Coexpression Network: Revealing pathway relationships

    • Authors: Yered Pita-Juarez Gabriel Altschuler Sokratis Kariotis Wenbin Wei Katjusa Koler Claire Green Rudolph Tanzi Winston Hide
      Abstract: by Yered Pita-Juarez, Gabriel Altschuler, Sokratis Kariotis, Wenbin Wei, Katjusa Koler, Claire Green, Rudolph Tanzi, Winston HideA goal of genomics is to understand the relationships between biological processes. Pathways contribute to functional interplay within biological processes through complex but poorly understood interactions. However, limited functional references for global pathway relationships exist. Pathways from databases such as KEGG and Reactome provide discrete annotations of biological processes. Their relationships are currently either inferred from gene set enrichment within specific experiments, or by simple overlap, linking pathway annotations that have genes in common. Here, we provide a unifying interpretation of functional interaction between pathways by systematically quantifying coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) to establish the Pathway Coexpression Network (PCxN). We estimated the correlation between canonical pathways valid in a broad context using a curated collection of 3,207 microarrays from 72 normal human tissues. PCxN accounts for shared genes between annotations to estimate significant correlations between pathways with related functions rather than with similar annotations. We demonstrate that PCxN provides novel insight into mechanisms of complex diseases using an Alzheimer’s Disease (AD) case study. PCxN retrieved pathways significantly correlated with an expert curated AD gene list. These pathways have known associations with AD and were significantly enriched for genes independently associated with AD. As a further step, we show how PCxN complements the results of gene set enrichment methods by revealing relationships between enriched pathways, and by identifying additional highly correlated pathways. PCxN revealed that correlated pathways from an AD expression profiling study include functional clusters involved in cell adhesion and oxidative stress. PCxN provides expanded connections to pathways from the extracellular matrix. PCxN provides a powerful new framework for interrogation of global pathway relationships. Comprehensive exploration of PCxN can be performed at
      PubDate: 2018-03-19T21:00:00Z
      DOI: 10.1371/journal.pcbi.1006042
  • The exclusive effects of chaperonin on the behavior of proteins with
           52 knot

    • Authors: Yani Zhao Pawel Dabrowski-Tumanski Szymon Niewieczerzal Joanna I. Sulkowska
      Abstract: by Yani Zhao, Pawel Dabrowski-Tumanski, Szymon Niewieczerzal, Joanna I. SulkowskaThe folding of proteins with a complex knot is still an unresolved question. Based on representative members of Ubiquitin C-terminal Hydrolases (UCHs) that contain the 52 knot in the native state, we explain how UCHs are able to unfold and refold in vitro reversibly within the structure-based model. In particular, we identify two, topologically different folding/unfolding pathways and corroborate our results with experiment, recreating the chevron plot. We show that confinement effect of chaperonin or weak crowding greatly facilitates folding, simultaneously slowing down the unfolding process of UCHs, compared with bulk conditions. Finally, we analyze the existence of knots in the denaturated state of UCHs. The results of the work show that the crowded environment of the cell should have a positive effect on the kinetics of complex knotted proteins, especially when proteins with deeper knots are found in this family.
      PubDate: 2018-03-16T21:00:00Z
      DOI: 10.1371/journal.pcbi.1005970
  • PLOS Computational Biology 2017 Reviewer and Editorial
           Board Thank You

    • PubDate: 2018-03-15T21:00:00Z
      DOI: 10.1371/journal.pcbi.1006066
  • Epigenetic regulation of cell fate reprogramming in aging and disease: A
           predictive computational model

    • Authors: Núria Folguera-Blasco Elisabet Cuyàs Javier A. Menéndez Tomás Alarcón
      Abstract: by Núria Folguera-Blasco, Elisabet Cuyàs, Javier A. Menéndez, Tomás AlarcónUnderstanding the control of epigenetic regulation is key to explain and modify the aging process. Because histone-modifying enzymes are sensitive to shifts in availability of cofactors (e.g. metabolites), cellular epigenetic states may be tied to changing conditions associated with cofactor variability. The aim of this study is to analyse the relationships between cofactor fluctuations, epigenetic landscapes, and cell state transitions. Using Approximate Bayesian Computation, we generate an ensemble of epigenetic regulation (ER) systems whose heterogeneity reflects variability in cofactor pools used by histone modifiers. The heterogeneity of epigenetic metabolites, which operates as regulator of the kinetic parameters promoting/preventing histone modifications, stochastically drives phenotypic variability. The ensemble of ER configurations reveals the occurrence of distinct epi-states within the ensemble. Whereas resilient states maintain large epigenetic barriers refractory to reprogramming cellular identity, plastic states lower these barriers, and increase the sensitivity to reprogramming. Moreover, fine-tuning of cofactor levels redirects plastic epigenetic states to re-enter epigenetic resilience, and vice versa. Our ensemble model agrees with a model of metabolism-responsive loss of epigenetic resilience as a cellular aging mechanism. Our findings support the notion that cellular aging, and its reversal, might result from stochastic translation of metabolic inputs into resilient/plastic cell states via ER systems.
      PubDate: 2018-03-15T21:00:00Z
      DOI: 10.1371/journal.pcbi.1006052
  • Imbalanced amplification: A mechanism of amplification and suppression
           from local imbalance of excitation and inhibition in cortical circuits

    • Authors: Christopher Ebsch Robert Rosenbaum
      Abstract: by Christopher Ebsch, Robert RosenbaumUnderstanding the relationship between external stimuli and the spiking activity of cortical populations is a central problem in neuroscience. Dense recurrent connectivity in local cortical circuits can lead to counterintuitive response properties, raising the question of whether there are simple arithmetical rules for relating circuits’ connectivity structure to their response properties. One such arithmetic is provided by the mean field theory of balanced networks, which is derived in a limit where excitatory and inhibitory synaptic currents precisely balance on average. However, balanced network theory is not applicable to some biologically relevant connectivity structures. We show that cortical circuits with such structure are susceptible to an amplification mechanism arising when excitatory-inhibitory balance is broken at the level of local subpopulations, but maintained at a global level. This amplification, which can be quantified by a linear correction to the classical mean field theory of balanced networks, explains several response properties observed in cortical recordings and provides fundamental insights into the relationship between connectivity structure and neural responses in cortical circuits.
      PubDate: 2018-03-15T21:00:00Z
      DOI: 10.1371/journal.pcbi.1006048
  • Meet-U: Educating through research immersion

    • Authors: Nika Abdollahi Alexandre Albani Eric Anthony Agnes Baud Mélissa Cardon Robert Clerc Dariusz Czernecki Romain Conte Laurent David Agathe Delaune Samia Djerroud Pauline Fourgoux Nadège Guiglielmoni Jeanne Laurentie Nathalie Lehmann Camille Lochard Rémi Montagne Vasiliki Myrodia Vaitea Opuu Elise Parey Lélia Polit Sylvain Privé Chloé Quignot Maria Ruiz-Cuevas Mariam Sissoko Nicolas Sompairac Audrey Vallerix Violaine Verrecchia Marc Delarue Raphael Guérois Yann Ponty Sophie Sacquin-Mora Alessandra Carbone Christine Froidevaux Stéphane Le Crom Olivier Lespinet Martin Weigt Samer Abboud Juliana Bernardes Guillaume Bouvier Chloé Dequeker Arnaud Ferré Patrick Fuchs Gaëlle Lelandais Pierre Poulain Hugues Richard Hugo Schweke Elodie Laine Anne Lopes
      Abstract: by Nika Abdollahi, Alexandre Albani, Eric Anthony, Agnes Baud, Mélissa Cardon, Robert Clerc, Dariusz Czernecki, Romain Conte, Laurent David, Agathe Delaune, Samia Djerroud, Pauline Fourgoux, Nadège Guiglielmoni, Jeanne Laurentie, Nathalie Lehmann, Camille Lochard, Rémi Montagne, Vasiliki Myrodia, Vaitea Opuu, Elise Parey, Lélia Polit, Sylvain Privé, Chloé Quignot, Maria Ruiz-Cuevas, Mariam Sissoko, Nicolas Sompairac, Audrey Vallerix, Violaine Verrecchia, Marc Delarue, Raphael Guérois, Yann Ponty, Sophie Sacquin-Mora, Alessandra Carbone, Christine Froidevaux, Stéphane Le Crom, Olivier Lespinet, Martin Weigt, Samer Abboud, Juliana Bernardes, Guillaume Bouvier, Chloé Dequeker, Arnaud Ferré, Patrick Fuchs, Gaëlle Lelandais, Pierre Poulain, Hugues Richard, Hugo Schweke, Elodie Laine, Anne LopesWe present a new educational initiative called Meet-U that aims to train students for collaborative work in computational biology and to bridge the gap between education and research. Meet-U mimics the setup of collaborative research projects and takes advantage of the most popular tools for collaborative work and of cloud computing. Students are grouped in teams of 4–5 people and have to realize a project from A to Z that answers a challenging question in biology. Meet-U promotes "coopetition," as the students collaborate within and across the teams and are also in competition with each other to develop the best final product. Meet-U fosters interactions between different actors of education and research through the organization of a meeting day, open to everyone, where the students present their work to a jury of researchers and jury members give research seminars. This very unique combination of education and research is strongly motivating for the students and provides a formidable opportunity for a scientific community to unite and increase its visibility. We report on our experience with Meet-U in two French universities with master’s students in bioinformatics and modeling, with protein–protein docking as the subject of the course. Meet-U is easy to implement and can be straightforwardly transferred to other fields and/or universities. All the information and data are available at
      PubDate: 2018-03-15T21:00:00Z
      DOI: 10.1371/journal.pcbi.1005992
  • A FAIR guide for data providers to maximise sharing of human genomic data

    • Authors: Manuel Corpas Nadezda V. Kovalevskaya Amanda McMurray Fiona G. G. Nielsen
      Abstract: by Manuel Corpas, Nadezda V. Kovalevskaya, Amanda McMurray, Fiona G. G. NielsenIt is generally acknowledged that, for reproducibility and progress of human genomic research, data sharing is critical. For every sharing transaction, a successful data exchange is produced between a data consumer and a data provider. Providers of human genomic data (e.g., publicly or privately funded repositories and data archives) fulfil their social contract with data donors when their shareable data conforms to FAIR (findable, accessible, interoperable, reusable) principles. Based on our experiences via Repositive (, a leading discovery platform cataloguing all shared human genomic datasets, we propose guidelines for data providers wishing to maximise their shared data’s FAIRness.
      PubDate: 2018-03-15T21:00:00Z
      DOI: 10.1371/journal.pcbi.1005873
  • iDREM: Interactive visualization of dynamic regulatory networks

    • Authors: Jun Ding James S. Hagood Namasivayam Ambalavanan Naftali Kaminski Ziv Bar-Joseph
      Abstract: by Jun Ding, James S. Hagood, Namasivayam Ambalavanan, Naftali Kaminski, Ziv Bar-JosephThe Dynamic Regulatory Events Miner (DREM) software reconstructs dynamic regulatory networks by integrating static protein-DNA interaction data with time series gene expression data. In recent years, several additional types of high-throughput time series data have been profiled when studying biological processes including time series miRNA expression, proteomics, epigenomics and single cell RNA-Seq. Combining all available time series and static datasets in a unified model remains an important challenge and goal. To address this challenge we have developed a new version of DREM termed interactive DREM (iDREM). iDREM provides support for all data types mentioned above and combines them with existing interaction data to reconstruct networks that can lead to novel hypotheses on the function and timing of regulators. Users can interactively visualize and query the resulting model. We showcase the functionality of the new tool by applying it to microglia developmental data from multiple labs.
      PubDate: 2018-03-14T21:00:00Z
      DOI: 10.1371/journal.pcbi.1006019
  • Closely related, yet unique: Distinct homo- and heterodimerization
           patterns of G protein coupled chemokine receptors and their fine-tuning by

    • Authors: Stefan Gahbauer Kristyna Pluhackova Rainer A. Böckmann
      Abstract: by Stefan Gahbauer, Kristyna Pluhackova, Rainer A. BöckmannChemokine receptors, a subclass of G protein coupled receptors (GPCRs), play essential roles in the human immune system, they are involved in cancer metastasis as well as in HIV-infection. A plethora of studies show that homo- and heterodimers or even higher order oligomers of the chemokine receptors CXCR4, CCR5, and CCR2 modulate receptor function. In addition, membrane cholesterol affects chemokine receptor activity. However, structural information about homo- and heterodimers formed by chemokine receptors and their interplay with cholesterol is limited. Here, we report homo- and heterodimer configurations of the chemokine receptors CXCR4, CCR5, and CCR2 at atomistic detail, as obtained from thousands of molecular dynamics simulations. The observed homodimerization patterns were similar for the closely related CC chemokine receptors, yet they differed significantly between the CC receptors and CXCR4. Despite their high sequence identity, cholesterol modulated the CC homodimer interfaces in a subtype-specific manner. Chemokine receptor heterodimers display distinct dimerization patterns for CXCR4/CCR5 and CXCR4/CCR2. Furthermore, associations between CXCR4 and CCR5 reveal an increased cholesterol-sensitivity as compared to CXCR4/CCR2 heterodimerization patterns. This work provides a first comprehensive structural overview over the complex interaction network between chemokine receptors and indicates how heterodimerization and the interaction with the membrane environment diversifies the function of closely related GPCRs.
      PubDate: 2018-03-12T21:00:00Z
      DOI: 10.1371/journal.pcbi.1006062
  • LAILAPS-QSM: A RESTful API and JAVA library for semantic query suggestions

    • Authors: Jinbo Chen Uwe Scholz Ruonan Zhou Matthias Lange
      Abstract: by Jinbo Chen, Uwe Scholz, Ruonan Zhou, Matthias LangeIn order to access and filter content of life-science databases, full text search is a widely applied query interface. But its high flexibility and intuitiveness is paid for with potentially imprecise and incomplete query results. To reduce this drawback, query assistance systems suggest those combinations of keywords with the highest potential to match most of the relevant data records. Widespread approaches are syntactic query corrections that avoid misspelling and support expansion of words by suffixes and prefixes. Synonym expansion approaches apply thesauri, ontologies, and query logs. All need laborious curation and maintenance. Furthermore, access to query logs is in general restricted. Approaches that infer related queries by their query profile like research field, geographic location, co-authorship, affiliation etc. require user’s registration and its public accessibility that contradict privacy concerns. To overcome these drawbacks, we implemented LAILAPS-QSM, a machine learning approach that reconstruct possible linguistic contexts of a given keyword query. The context is referred from the text records that are stored in the databases that are going to be queried or extracted for a general purpose query suggestion from PubMed abstracts and UniProt data. The supplied tool suite enables the pre-processing of these text records and the further computation of customized distributed word vectors. The latter are used to suggest alternative keyword queries. An evaluated of the query suggestion quality was done for plant science use cases. Locally present experts enable a cost-efficient quality assessment in the categories trait, biological entity, taxonomy, affiliation, and metabolic function which has been performed using ontology term similarities. LAILAPS-QSM mean information content similarity for 15 representative queries is 0.70, whereas 34% have a score above 0.80. In comparison, the information content similarity for human expert made query suggestions is 0.90. The software is either available as tool set to build and train dedicated query suggestion services or as already trained general purpose RESTful web service. The service uses open interfaces to be seamless embeddable into database frontends. The JAVA implementation uses highly optimized data structures and streamlined code to provide fast and scalable response for web service calls. The source code of LAILAPS-QSM is available under GNU General Public License version 2 in Bitbucket GIT repository:
      PubDate: 2018-03-12T21:00:00Z
      DOI: 10.1371/journal.pcbi.1006058
  • Relatively slow stochastic gene-state switching in the presence of
           positive feedback significantly broadens the region of bimodality through
           stabilizing the uninduced phenotypic state

    • Authors: Hao Ge Pingping Wu Hong Qian Sunney Xiaoliang Xie
      Abstract: by Hao Ge, Pingping Wu, Hong Qian, Sunney Xiaoliang XieWithin an isogenic population, even in the same extracellular environment, individual cells can exhibit various phenotypic states. The exact role of stochastic gene-state switching regulating the transition among these phenotypic states in a single cell is not fully understood, especially in the presence of positive feedback. Recent high-precision single-cell measurements showed that, at least in bacteria, switching in gene states is slow relative to the typical rates of active transcription and translation. Hence using the lac operon as an archetype, in such a region of operon-state switching, we present a fluctuating-rate model for this classical gene regulation module, incorporating the more realistic operon-state switching mechanism that was recently elucidated. We found that the positive feedback mechanism induces bistability (referred to as deterministic bistability), and that the parameter range for its occurrence is significantly broadened by stochastic operon-state switching. We further show that in the absence of positive feedback, operon-state switching must be extremely slow to trigger bistability by itself. However, in the presence of positive feedback, which stabilizes the induced state, the relatively slow operon-state switching kinetics within the physiological region are sufficient to stabilize the uninduced state, together generating a broadened parameter region of bistability (referred to as stochastic bistability). We illustrate the opposite phenotype-transition rate dependence upon the operon-state switching rates in the two types of bistability, with the aid of a recently proposed rate formula for fluctuating-rate models. The rate formula also predicts a maximal transition rate in the intermediate region of operon-state switching, which is validated by numerical simulations in our model. Overall, our findings suggest a biological function of transcriptional “variations” among genetically identical cells, for the emergence of bistability and transition between phenotypic states.
      PubDate: 2018-03-12T21:00:00Z
      DOI: 10.1371/journal.pcbi.1006051
  • Gap junction plasticity as a mechanism to regulate network-wide

    • Authors: Guillaume Pernelle Wilten Nicola Claudia Clopath
      Abstract: by Guillaume Pernelle, Wilten Nicola, Claudia ClopathCortical oscillations are thought to be involved in many cognitive functions and processes. Several mechanisms have been proposed to regulate oscillations. One prominent but understudied mechanism is gap junction coupling. Gap junctions are ubiquitous in cortex between GABAergic interneurons. Moreover, recent experiments indicate their strength can be modified in an activity-dependent manner, similar to chemical synapses. We hypothesized that activity-dependent gap junction plasticity acts as a mechanism to regulate oscillations in the cortex. We developed a computational model of gap junction plasticity in a recurrent cortical network based on recent experimental findings. We showed that gap junction plasticity can serve as a homeostatic mechanism for oscillations by maintaining a tight balance between two network states: asynchronous irregular activity and synchronized oscillations. This homeostatic mechanism allows for robust communication between neuronal assemblies through two different mechanisms: transient oscillations and frequency modulation. This implies a direct functional role for gap junction plasticity in information transmission in cortex.
      PubDate: 2018-03-12T21:00:00Z
      DOI: 10.1371/journal.pcbi.1006025
  • Particle-based simulations of polarity establishment reveal stochastic
           promotion of turing pattern formation

    • Authors: Michael Pablo Samuel A. Ramirez Timothy C. Elston
      Abstract: by Michael Pablo, Samuel A. Ramirez, Timothy C. ElstonPolarity establishment, the spontaneous generation of asymmetric molecular distributions, is a crucial component of many cellular functions. Saccharomyces cerevisiae (yeast) undergoes directed growth during budding and mating, and is an ideal model organism for studying polarization. In yeast and many other cell types, the Rho GTPase Cdc42 is the key molecular player in polarity establishment. During yeast polarization, multiple patches of Cdc42 initially form, then resolve into a single front. Because polarization relies on strong positive feedback, it is likely that the amplification of molecular-level fluctuations underlies the generation of multiple nascent patches. In the absence of spatial cues, these fluctuations may be key to driving polarization. Here we used particle-based simulations to investigate the role of stochastic effects in a Turing-type model of yeast polarity establishment. In the model, reactions take place either between two molecules on the membrane, or between a cytosolic and a membrane-bound molecule. Thus, we developed a computational platform that explicitly simulates molecules at and near the cell membrane, and implicitly handles molecules away from the membrane. To evaluate stochastic effects, we compared particle simulations to deterministic reaction-diffusion equation simulations. Defining macroscopic rate constants that are consistent with the microscopic parameters for this system is challenging, because diffusion occurs in two dimensions and particles exchange between the membrane and cytoplasm. We address this problem by empirically estimating macroscopic rate constants from appropriately designed particle-based simulations. Ultimately, we find that stochastic fluctuations speed polarity establishment and permit polarization in parameter regions predicted to be Turing stable. These effects can operate at Cdc42 abundances expected of yeast cells, and promote polarization on timescales consistent with experimental results. To our knowledge, our work represents the first particle-based simulations of a model for yeast polarization that is based on a Turing mechanism.
      PubDate: 2018-03-12T21:00:00Z
      DOI: 10.1371/journal.pcbi.1006016
  • In silico study of multicellular automaticity of heterogeneous cardiac
           cell monolayers: Effects of automaticity strength and structural linear

    • Authors: James Elber Duverger Vincent Jacquemet Alain Vinet Philippe Comtois
      Abstract: by James Elber Duverger, Vincent Jacquemet, Alain Vinet, Philippe ComtoisThe biological pacemaker approach is an alternative to cardiac electronic pacemakers. Its main objective is to create pacemaking activity from added or modified distribution of spontaneous cells in the myocardium. This paper aims to assess how automaticity strength of pacemaker cells (i.e. their ability to maintain robust spontaneous activity with fast rate and to drive neighboring quiescent cells) and structural linear anisotropy, combined with density and spatial distribution of pacemaker cells, may affect the macroscopic behavior of the biological pacemaker. A stochastic algorithm was used to randomly distribute pacemaker cells, with various densities and spatial distributions, in a semi-continuous mathematical model. Simulations of the model showed that stronger automaticity allows onset of spontaneous activity for lower densities and more homogeneous spatial distributions, displayed more central foci, less variability in cycle lengths and synchronization of electrical activation for similar spatial patterns, but more variability in those same variables for dissimilar spatial patterns. Compared their isotropic counterparts, in silico anisotropic monolayers had less central foci and displayed more variability in cycle lengths and synchronization of electrical activation for both similar and dissimilar spatial patterns. The present study established a link between microscopic structure and macroscopic behavior of the biological pacemaker, and may provide crucial information for optimized biological pacemaker therapies.
      PubDate: 2018-03-12T21:00:00Z
      DOI: 10.1371/journal.pcbi.1005978
  • Across-subjects classification of stimulus modality from human MEG high
           frequency activity

    • Authors: Britta U. Westner Sarang S. Dalal Simon Hanslmayr Tobias Staudigl
      Abstract: by Britta U. Westner, Sarang S. Dalal, Simon Hanslmayr, Tobias StaudiglSingle-trial analyses have the potential to uncover meaningful brain dynamics that are obscured when averaging across trials. However, low signal-to-noise ratio (SNR) can impede the use of single-trial analyses and decoding methods. In this study, we investigate the applicability of a single-trial approach to decode stimulus modality from magnetoencephalographic (MEG) high frequency activity. In order to classify the auditory versus visual presentation of words, we combine beamformer source reconstruction with the random forest classification method. To enable group level inference, the classification is embedded in an across-subjects framework. We show that single-trial gamma SNR allows for good classification performance (accuracy across subjects: 66.44%). This implies that the characteristics of high frequency activity have a high consistency across trials and subjects. The random forest classifier assigned informational value to activity in both auditory and visual cortex with high spatial specificity. Across time, gamma power was most informative during stimulus presentation. Among all frequency bands, the 75 Hz 95 Hz band was the most informative frequency band in visual as well as in auditory areas. Especially in visual areas, a broad range of gamma frequencies (55 Hz 125 Hz) contributed to the successful classification. Thus, we demonstrate the feasibility of single-trial approaches for decoding the stimulus modality across subjects from high frequency activity and describe the discriminative gamma activity in time, frequency, and space.
      PubDate: 2018-03-12T21:00:00Z
      DOI: 10.1371/journal.pcbi.1005938
  • The importance of geometry in the corneal micropocket angiogenesis assay

    • Authors: James A. Grogan Anthony J. Connor Joe M. Pitt-Francis Philip K. Maini Helen M. Byrne
      Abstract: by James A. Grogan, Anthony J. Connor, Joe M. Pitt-Francis, Philip K. Maini, Helen M. ByrneThe corneal micropocket angiogenesis assay is an experimental protocol for studying vessel network formation, or neovascularization, in vivo. The assay is attractive due to the ease with which the developing vessel network can be observed in the same animal over time. Measurements from the assay have been used in combination with mathematical modeling to gain insights into the mechanisms of angiogenesis. While previous modeling studies have adopted planar domains to represent the assay, the hemispherical shape of the cornea and asymmetric positioning of the angiogenic source can be seen to affect vascular patterning in experimental images. As such, we aim to better understand: i) how the geometry of the assay influences vessel network formation and ii) how to relate observations from planar domains to those in the hemispherical cornea. To do so, we develop a three-dimensional, off-lattice mathematical model of neovascularization in the cornea, using a spatially resolved representation of the assay for the first time. Relative to the detailed model, we predict that the adoption of planar geometries has a noticeable impact on vascular patterning, leading to increased vessel ‘merging’, or anastomosis, in particular when circular geometries are adopted. Significant differences in the dynamics of diffusible aniogenesis simulators are also predicted between different domains. In terms of comparing predictions across domains, the ‘distance of the vascular front to the limbus’ metric is found to have low sensitivity to domain choice, while metrics such as densities of tip cells and vessels and ‘vascularized fraction’ are sensitive to domain choice. Given the widespread adoption and attractive simplicity of planar tissue domains, both in silico and in vitro, the differences identified in the present study should prove useful in relating the results of previous and future theoretical studies of neovascularization to in vivo observations in the cornea.
      PubDate: 2018-03-09T22:00:00Z
      DOI: 10.1371/journal.pcbi.1006049
  • Use of temperature to improve West Nile virus forecasts

    • Authors: Nicholas B. DeFelice Zachary D. Schneider Eliza Little Christopher Barker Kevin A. Caillouet Scott R. Campbell Dan Damian Patrick Irwin Herff M. P. Jones John Townsend Jeffrey Shaman
      Abstract: by Nicholas B. DeFelice, Zachary D. Schneider, Eliza Little, Christopher Barker, Kevin A. Caillouet, Scott R. Campbell, Dan Damian, Patrick Irwin, Herff M. P. Jones, John Townsend, Jeffrey ShamanEcological and laboratory studies have demonstrated that temperature modulates West Nile virus (WNV) transmission dynamics and spillover infection to humans. Here we explore whether inclusion of temperature forcing in a model depicting WNV transmission improves WNV forecast accuracy relative to a baseline model depicting WNV transmission without temperature forcing. Both models are optimized using a data assimilation method and two observed data streams: mosquito infection rates and reported human WNV cases. Each coupled model-inference framework is then used to generate retrospective ensemble forecasts of WNV for 110 outbreak years from among 12 geographically diverse United States counties. The temperature-forced model improves forecast accuracy for much of the outbreak season. From the end of July until the beginning of October, a timespan during which 70% of human cases are reported, the temperature-forced model generated forecasts of the total number of human cases over the next 3 weeks, total number of human cases over the season, the week with the highest percentage of infectious mosquitoes, and the peak percentage of infectious mosquitoes that on average increased absolute forecast accuracy 5%, 10%, 12%, and 6%, respectively, over the non-temperature forced baseline model. These results indicate that use of temperature forcing improves WNV forecast accuracy and provide further evidence that temperature influences rates of WNV transmission. The findings provide a foundation for implementation of a statistically rigorous system for real-time forecast of seasonal WNV outbreaks and their use as a quantitative decision support tool for public health officials and mosquito control programs.
      PubDate: 2018-03-09T22:00:00Z
      DOI: 10.1371/journal.pcbi.1006047
  • 4Cin: A computational pipeline for 3D genome modeling and virtual Hi-C
           analyses from 4C data

    • Authors: Ibai Irastorza-Azcarate Rafael D. Acemel Juan J. Tena Ignacio Maeso José Luis Gómez-Skarmeta Damien P. Devos
      Abstract: by Ibai Irastorza-Azcarate, Rafael D. Acemel, Juan J. Tena, Ignacio Maeso, José Luis Gómez-Skarmeta, Damien P. DevosThe use of 3C-based methods has revealed the importance of the 3D organization of the chromatin for key aspects of genome biology. However, the different caveats of the variants of 3C techniques have limited their scope and the range of scientific fields that could benefit from these approaches. To address these limitations, we present 4Cin, a method to generate 3D models and derive virtual Hi-C (vHi-C) heat maps of genomic loci based on 4C-seq or any kind of 4C-seq-like data, such as those derived from NG Capture-C. 3D genome organization is determined by integrative consideration of the spatial distances derived from as few as four 4C-seq experiments. The 3D models obtained from 4C-seq data, together with their associated vHi-C maps, allow the inference of all chromosomal contacts within a given genomic region, facilitating the identification of Topological Associating Domains (TAD) boundaries. Thus, 4Cin offers a much cheaper, accessible and versatile alternative to other available techniques while providing a comprehensive 3D topological profiling. By studying TAD modifications in genomic structural variants associated to disease phenotypes and performing cross-species evolutionary comparisons of 3D chromatin structures in a quantitative manner, we demonstrate the broad potential and novel range of applications of our method.
      PubDate: 2018-03-09T22:00:00Z
      DOI: 10.1371/journal.pcbi.1006030
  • Neuronal gain modulability is determined by dendritic morphology: A
           computational optogenetic study

    • Authors: Sarah Jarvis Konstantin Nikolic Simon R. Schultz
      Abstract: by Sarah Jarvis, Konstantin Nikolic, Simon R. SchultzThe mechanisms by which the gain of the neuronal input-output function may be modulated have been the subject of much investigation. However, little is known of the role of dendrites in neuronal gain control. New optogenetic experimental paradigms based on spatial profiles or patterns of light stimulation offer the prospect of elucidating many aspects of single cell function, including the role of dendrites in gain control. We thus developed a model to investigate how competing excitatory and inhibitory input within the dendritic arbor alters neuronal gain, incorporating kinetic models of opsins into our modeling to ensure it is experimentally testable. To investigate how different topologies of the neuronal dendritic tree affect the neuron’s input-output characteristics we generate branching geometries which replicate morphological features of most common neurons, but keep the number of branches and overall area of dendrites approximately constant. We found a relationship between a neuron’s gain modulability and its dendritic morphology, with neurons with bipolar dendrites with a moderate degree of branching being most receptive to control of the gain of their input-output relationship. The theory was then tested and confirmed on two examples of realistic neurons: 1) layer V pyramidal cells—confirming their role in neural circuits as a regulator of the gain in the circuit in addition to acting as the primary excitatory neurons, and 2) stellate cells. In addition to providing testable predictions and a novel application of dual-opsins, our model suggests that innervation of all dendritic subdomains is required for full gain modulation, revealing the importance of dendritic targeting in the generation of neuronal gain control and the functions that it subserves. Finally, our study also demonstrates that neurophysiological investigations which use direct current injection into the soma and bypass the dendrites may miss some important neuronal functions, such as gain modulation.
      PubDate: 2018-03-09T22:00:00Z
      DOI: 10.1371/journal.pcbi.1006027
  • ChromoTrace: Computational reconstruction of 3D chromosome configurations
           for super-resolution microscopy

    • Authors: Carl Barton Sandro Morganella Øyvind Ødegård-Fougner Stephanie Alexander Jonas Ries Tomas Fitzgerald Jan Ellenberg Ewan Birney
      Abstract: by Carl Barton, Sandro Morganella, Øyvind Ødegård-Fougner, Stephanie Alexander, Jonas Ries, Tomas Fitzgerald, Jan Ellenberg, Ewan BirneyThe 3D structure of chromatin plays a key role in genome function, including gene expression, DNA replication, chromosome segregation, and DNA repair. Furthermore the location of genomic loci within the nucleus, especially relative to each other and nuclear structures such as the nuclear envelope and nuclear bodies strongly correlates with aspects of function such as gene expression. Therefore, determining the 3D position of the 6 billion DNA base pairs in each of the 23 chromosomes inside the nucleus of a human cell is a central challenge of biology. Recent advances of super-resolution microscopy in principle enable the mapping of specific molecular features with nanometer precision inside cells. Combined with highly specific, sensitive and multiplexed fluorescence labeling of DNA sequences this opens up the possibility of mapping the 3D path of the genome sequence in situ. Here we develop computational methodologies to reconstruct the sequence configuration of all human chromosomes in the nucleus from a super-resolution image of a set of fluorescent in situ probes hybridized to the genome in a cell. To test our approach, we develop a method for the simulation of DNA in an idealized human nucleus. Our reconstruction method, ChromoTrace, uses suffix trees to assign a known linear ordering of in situ probes on the genome to an unknown set of 3D in-situ probe positions in the nucleus from super-resolved images using the known genomic probe spacing as a set of physical distance constraints between probes. We find that ChromoTrace can assign the 3D positions of the majority of loci with high accuracy and reasonable sensitivity to specific genome sequences. By simulating appropriate spatial resolution, label multiplexing and noise scenarios we assess our algorithms performance. Our study shows that it is feasible to achieve genome-wide reconstruction of the 3D DNA path based on super-resolution microscopy images.
      PubDate: 2018-03-09T22:00:00Z
      DOI: 10.1371/journal.pcbi.1006002
  • Stoichiometric balance of protein copy numbers is measurable and
           functionally significant in a protein-protein interaction network for
           yeast endocytosis

    • Authors: David O. Holland Margaret E. Johnson
      Abstract: by David O. Holland, Margaret E. JohnsonStoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that ‘leftover’ proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module allows cells to tune where endocytosis occurs, providing sensitive control over cargo uptake via clathrin-coated vesicles.
      PubDate: 2018-03-08T22:00:00Z
      DOI: 10.1371/journal.pcbi.1006022
  • Bat detective—Deep learning tools for bat acoustic signal detection

    • Authors: Oisin Mac Aodha Rory Gibb Kate E. Barlow Ella Browning Michael Firman Robin Freeman Briana Harder Libby Kinsey Gary R. Mead Stuart E. Newson Ivan Pandourski Stuart Parsons Jon Russ Abigel Szodoray-Paradi Farkas Szodoray-Paradi Elena Tilova Mark Girolami Gabriel Brostow Kate E. Jones
      Abstract: by Oisin Mac Aodha, Rory Gibb, Kate E. Barlow, Ella Browning, Michael Firman, Robin Freeman, Briana Harder, Libby Kinsey, Gary R. Mead, Stuart E. Newson, Ivan Pandourski, Stuart Parsons, Jon Russ, Abigel Szodoray-Paradi, Farkas Szodoray-Paradi, Elena Tilova, Mark Girolami, Gabriel Brostow, Kate E. JonesPassive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. To better assess bat population trends there is a critical need for accurate, reliable, and open source tools that allow the detection and classification of bat calls in large collections of audio recordings. The majority of existing tools are commercial or have focused on the species classification task, neglecting the important problem of first localizing echolocation calls in audio which is particularly problematic in noisy recordings. We developed a convolutional neural network based open-source pipeline for detecting ultrasonic, full-spectrum, search-phase calls produced by echolocating bats. Our deep learning algorithms were trained on full-spectrum ultrasonic audio collected along road-transects across Europe and labelled by citizen scientists from When compared to other existing algorithms and commercial systems, we show significantly higher detection performance of search-phase echolocation calls with our test sets. As an example application, we ran our detection pipeline on bat monitoring data collected over five years from Jersey (UK), and compared results to a widely-used commercial system. Our detection pipeline can be used for the automatic detection and monitoring of bat populations, and further facilitates their use as indicator species on a large scale. Our proposed pipeline makes only a small number of bat specific design decisions, and with appropriate training data it could be applied to detecting other species in audio. A crucial novelty of our work is showing that with careful, non-trivial, design and implementation considerations, state-of-the-art deep learning methods can be used for accurate and efficient monitoring in audio.
      PubDate: 2018-03-08T22:00:00Z
      DOI: 10.1371/journal.pcbi.1005995
  • Ten simple rules to create a serious game, illustrated with examples from
           structural biology

    • Authors: Marc Baaden Olivier Delalande Nicolas Ferey Samuela Pasquali Jérôme Waldispühl Antoine Taly
      Abstract: by Marc Baaden, Olivier Delalande, Nicolas Ferey, Samuela Pasquali, Jérôme Waldispühl, Antoine Taly
      PubDate: 2018-03-08T22:00:00Z
      DOI: 10.1371/journal.pcbi.1005955
  • Method for the simulation of blood platelet shape and its evolution during

    • Authors: Alexander E. Moskalensky Maxim A. Yurkin Artem R. Muliukov Alena L. Litvinenko Vyacheslav M. Nekrasov Andrei V. Chernyshev Valeri P. Maltsev
      Abstract: by Alexander E. Moskalensky, Maxim A. Yurkin, Artem R. Muliukov, Alena L. Litvinenko, Vyacheslav M. Nekrasov, Andrei V. Chernyshev, Valeri P. MaltsevWe present a simple physically based quantitative model of blood platelet shape and its evolution during agonist-induced activation. The model is based on the consideration of two major cytoskeletal elements: the marginal band of microtubules and the submembrane cortex. Mathematically, we consider the problem of minimization of surface area constrained to confine the marginal band and a certain cellular volume. For resting platelets, the marginal band appears as a peripheral ring, allowing for the analytical solution of the minimization problem. Upon activation, the marginal band coils out of plane and forms 3D convoluted structure. We show that its shape is well approximated by an overcurved circle, a mathematical concept of closed curve with constant excessive curvature. Possible mechanisms leading to such marginal band coiling are discussed, resulting in simple parametric expression for the marginal band shape during platelet activation. The excessive curvature of marginal band is a convenient state variable which tracks the progress of activation. The cell surface is determined using numerical optimization. The shapes are strictly mathematically defined by only three parameters and show good agreement with literature data. They can be utilized in simulation of platelets interaction with different physical fields, e.g. for the description of hydrodynamic and mechanical properties of platelets, leading to better understanding of platelets margination and adhesion and thrombus formation in blood flow. It would also facilitate precise characterization of platelets in clinical diagnosis, where a novel optical model is needed for the correct solution of inverse light-scattering problem.
      PubDate: 2018-03-08T22:00:00Z
      DOI: 10.1371/journal.pcbi.1005899
  • Correction: Effect of Ionic Diffusion on Extracellular Potentials in
           Neural Tissue

    • Authors: The PLOS Computational Biology Staff
      Abstract: by The PLOS Computational Biology Staff
      PubDate: 2018-03-07T22:00:00Z
      DOI: 10.1371/journal.pcbi.1006050
  • Deploying digital health data to optimize influenza surveillance at
           national and local scales

    • Authors: Elizabeth C. Lee Ali Arab Sandra M. Goldlust Cécile Viboud Bryan T. Grenfell Shweta Bansal
      Abstract: by Elizabeth C. Lee, Ali Arab, Sandra M. Goldlust, Cécile Viboud, Bryan T. Grenfell, Shweta BansalThe surveillance of influenza activity is critical to early detection of epidemics and pandemics and the design of disease control strategies. Case reporting through a voluntary network of sentinel physicians is a commonly used method of passive surveillance for monitoring rates of influenza-like illness (ILI) worldwide. Despite its ubiquity, little attention has been given to the processes underlying the observation, collection, and spatial aggregation of sentinel surveillance data, and its subsequent effects on epidemiological understanding. We harnessed the high specificity of diagnosis codes in medical claims from a database that represented 2.5 billion visits from upwards of 120,000 United States healthcare providers each year. Among influenza seasons from 2002-2009 and the 2009 pandemic, we simulated limitations of sentinel surveillance systems such as low coverage and coarse spatial resolution, and performed Bayesian inference to probe the robustness of ecological inference and spatial prediction of disease burden. Our models suggest that a number of socio-environmental factors, in addition to local population interactions, state-specific health policies, as well as sampling effort may be responsible for the spatial patterns in U.S. sentinel ILI surveillance. In addition, we find that biases related to spatial aggregation were accentuated among areas with more heterogeneous disease risk, and sentinel systems designed with fixed reporting locations across seasons provided robust inference and prediction. With the growing availability of health-associated big data worldwide, our results suggest mechanisms for optimizing digital data streams to complement traditional surveillance in developed settings and enhance surveillance opportunities in developing countries.
      PubDate: 2018-03-07T22:00:00Z
      DOI: 10.1371/journal.pcbi.1006020
  • Cytosolic proteins can exploit membrane localization to trigger functional

    • Authors: Osman N. Yogurtcu Margaret E. Johnson
      Abstract: by Osman N. Yogurtcu, Margaret E. JohnsonCell division, endocytosis, and viral budding would not function without the localization and assembly of protein complexes on membranes. What is poorly appreciated, however, is that by localizing to membranes, proteins search in a reduced space that effectively drives up concentration. Here we derive an accurate and practical analytical theory to quantify the significance of this dimensionality reduction in regulating protein assembly on membranes. We define a simple metric, an effective equilibrium constant, that allows for quantitative comparison of protein-protein interactions with and without membrane present. To test the importance of membrane localization for driving protein assembly, we collected the protein-protein and protein-lipid affinities, protein and lipid concentrations, and volume-to-surface-area ratios for 46 interactions between 37 membrane-targeting proteins in human and yeast cells. We find that many of the protein-protein interactions between pairs of proteins involved in clathrin-mediated endocytosis in human and yeast cells can experience enormous increases in effective protein-protein affinity (10–1000 fold) due to membrane localization. Localization of binding partners thus triggers robust protein complexation, suggesting that it can play an important role in controlling the timing of endocytic protein coat formation. Our analysis shows that several other proteins involved in membrane remodeling at various organelles have similar potential to exploit localization. The theory highlights the master role of phosphoinositide lipid concentration, the volume-to-surface-area ratio, and the ratio of 3D to 2D equilibrium constants in triggering (or preventing) constitutive assembly on membranes. Our simple model provides a novel quantitative framework for interpreting or designing in vitro experiments of protein complexation influenced by membrane binding.
      PubDate: 2018-03-05T22:00:00Z
      DOI: 10.1371/journal.pcbi.1006031
  • Free energy profiles for unwrapping the outer superhelical turn of
           nucleosomal DNA

    • Authors: Hidetoshi Kono Shun Sakuraba Hisashi Ishida
      Abstract: by Hidetoshi Kono, Shun Sakuraba, Hisashi IshidaThe eukaryotic genome is packaged into a nucleus in the form of chromatin. The fundamental structural unit of chromatin is a protein-DNA complex, the nucleosome, where 146 or 147 base pairs of DNA wrap 1.75 times around a histone core. To function in cellular processes, however, nucleosomal DNA must be unwrapped. Although this unwrapping has been experimentally investigated, details of the process at an atomic level are not yet well understood. Here, we used molecular dynamics simulation with an enhanced sampling method to calculate the free energy profiles for unwrapping the outer superhelical turn of nucleosomal DNA. A free energy change of about 11.5 kcal/mol for the unwrapping agrees well with values obtained in single molecule experiments. This simulation revealed a variety of conformational states, indicating there are many potential paths to outer superhelicdal turn unwrapping, but the dominant path is likely asymmetric. At one end of the DNA, the first five bps unwrap, after which a second five bps unwrap at the same end with no increase in free energy. The unwrapping then starts at the other end of the DNA, where 10 bps are unwrapped. During further unwrapping of 15 bps, the unwrapping advances at one of the ends, after which the other end of the DNA unwraps to complete the unwrapping of the outer superhelical turn. These results provide insight into the construction, disruption, and repositioning of nucleosomes, which are continuously ongoing during cellular processes.
      PubDate: 2018-03-05T22:00:00Z
      DOI: 10.1371/journal.pcbi.1006024
  • Factors affecting basket catheter detection of real and phantom rotors in
           the atria: A computational study

    • Authors: Laura Martinez-Mateu Lucia Romero Ana Ferrer-Albero Rafael Sebastian José F. Rodríguez Matas José Jalife Omer Berenfeld Javier Saiz
      Abstract: by Laura Martinez-Mateu, Lucia Romero, Ana Ferrer-Albero, Rafael Sebastian, José F. Rodríguez Matas, José Jalife, Omer Berenfeld, Javier SaizAnatomically based procedures to ablate atrial fibrillation (AF) are often successful in terminating paroxysmal AF. However, the ability to terminate persistent AF remains disappointing. New mechanistic approaches use multiple-electrode basket catheter mapping to localize and target AF drivers in the form of rotors but significant concerns remain about their accuracy. We aimed to evaluate how electrode-endocardium distance, far-field sources and inter-electrode distance affect the accuracy of localizing rotors. Sustained rotor activation of the atria was simulated numerically and mapped using a virtual basket catheter with varying electrode densities placed at different positions within the atrial cavity. Unipolar electrograms were calculated on the entire endocardial surface and at each of the electrodes. Rotors were tracked on the interpolated basket phase maps and compared with the respective atrial voltage and endocardial phase maps, which served as references. Rotor detection by the basket maps varied between 35–94% of the simulation time, depending on the basket’s position and the electrode-to-endocardial wall distance. However, two different types of phantom rotors appeared also on the basket maps. The first type was due to the far-field sources and the second type was due to interpolation between the electrodes; increasing electrode density decreased the incidence of the second but not the first type of phantom rotors. In the simulations study, basket catheter-based phase mapping detected rotors even when the basket was not in full contact with the endocardial wall, but always generated a number of phantom rotors in the presence of only a single real rotor, which would be the desired ablation target. Phantom rotors may mislead and contribute to failure in AF ablation procedures.
      PubDate: 2018-03-05T22:00:00Z
      DOI: 10.1371/journal.pcbi.1006017
  • A computational model for how cells choose temporal or spatial sensing
           during chemotaxis

    • Authors: Rui Zhen Tan Keng-Hwee Chiam
      Abstract: by Rui Zhen Tan, Keng-Hwee ChiamCell size is thought to play an important role in choosing between temporal and spatial sensing in chemotaxis. Large cells are thought to use spatial sensing due to large chemical difference at its ends whereas small cells are incapable of spatial sensing due to rapid homogenization of proteins within the cell. However, small cells have been found to polarize and large cells like sperm cells undergo temporal sensing. Thus, it remains an open question what exactly governs spatial versus temporal sensing. Here, we identify the factors that determines sensing choices through mathematical modeling of chemotactic circuits. Comprehensive computational search of three-node signaling circuits has identified the negative integral feedback (NFB) and incoherent feedforward (IFF) circuits as capable of adaptation, an important property for chemotaxis. Cells are modeled as one-dimensional circular system consisting of diffusible activator, inactivator and output proteins, traveling across a chemical gradient. From our simulations, we find that sensing outcomes are similar for NFB or IFF circuits. Rather than cell size, the relevant parameters are the 1) ratio of cell speed to the product of cell diameter and rate of signaling, 2) diffusivity of the output protein and 3) ratio of the diffusivities of the activator to inactivator protein. Spatial sensing is favored when all three parameters are low. This corresponds to a cell moving slower than the time it takes for signaling to propagate across the cell diameter, has an output protein that is polarizable and has a local-excitation global-inhibition system to amplify the chemical gradient. Temporal sensing is favored otherwise. We also find that temporal sensing is more robust to noise. By performing extensive literature search, we find that our prediction agrees with observation in a wide range of species and cell types ranging from E. coli to human Fibroblast cells and propose that our result is universally applicable.
      PubDate: 2018-03-05T22:00:00Z
      DOI: 10.1371/journal.pcbi.1005966
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