PLoS Computational Biology
by Roy Malka, Francisco Feijó Delgado, Scott R. Manalis, John M. HigginsHuman red blood cells (RBCs) lose ∼30% of their volume and ∼20% of their hemoglobin (Hb) content during their ∼100-day lifespan in the bloodstream. These observations are well-documented, but the mechanisms for these volume and hemoglobin loss events are not clear. RBCs shed hemoglobin-containing vesicles during their life in the circulation, and this process is thought to dominate the changes in the RBC physical characteristics occurring during maturation. We combine theory with single-cell measurements to investigate the impact of vesiculation on the reduction in volume, Hb mass, and membrane. We show that vesicle shedding alone is sufficient to explain membrane losses but not volume or Hb losses. We use dry mass measurements of human RBCs to validate the models and to propose that additional unknown mechanisms control volume and Hb reduction and are responsible for ∼90% of the observed reduction. RBC population characteristics are used in the clinic to monitor and diagnose a wide range of conditions including malnutrition, inflammation, and cancer. Quantitative characterization of cellular maturation processes may help in the early detection of clinical conditions where maturation patterns are altered.
by Marco Mauri, Stefan KlumppSigma factors control global switches of the genetic expression program in bacteria. Different sigma factors compete for binding to a limited pool of RNA polymerase (RNAP) core enzymes, providing a mechanism for cross-talk between genes or gene classes via the sharing of expression machinery. To analyze the contribution of sigma factor competition to global changes in gene expression, we develop a theoretical model that describes binding between sigma factors and core RNAP, transcription, non-specific binding to DNA and the modulation of the availability of the molecular components. The model is validated by comparison with in vitro competition experiments, with which excellent agreement is found. Transcription is affected via the modulation of the concentrations of the different types of holoenzymes, so saturated promoters are only weakly affected by sigma factor competition. However, in case of overlapping promoters or promoters recognized by two types of sigma factors, we find that even saturated promoters are strongly affected. Active transcription effectively lowers the affinity between the sigma factor driving it and the core RNAP, resulting in complex cross-talk effects. Sigma factor competition is not strongly affected by non-specific binding of core RNAPs, sigma factors and holoenzymes to DNA. Finally, we analyze the role of increased core RNAP availability upon the shut-down of ribosomal RNA transcription during the stringent response. We find that passive up-regulation of alternative sigma-dependent transcription is not only possible, but also displays hypersensitivity based on the sigma factor competition. Our theoretical analysis thus provides support for a significant role of passive control during that global switch of the gene expression program.
by Christoph Feinauer, Marcin J. Skwark, Andrea Pagnani, Erik AurellCorrelation patterns in multiple sequence alignments of homologous proteins can be exploited to infer information on the three-dimensional structure of their members. The typical pipeline to address this task, which we in this paper refer to as the three dimensions of contact prediction, is to (i) filter and align the raw sequence data representing the evolutionarily related proteins; (ii) choose a predictive model to describe a sequence alignment; (iii) infer the model parameters and interpret them in terms of structural properties, such as an accurate contact map. We show here that all three dimensions are important for overall prediction success. In particular, we show that it is possible to improve significantly along the second dimension by going beyond the pair-wise Potts models from statistical physics, which have hitherto been the focus of the field. These (simple) extensions are motivated by multiple sequence alignments often containing long stretches of gaps which, as a data feature, would be rather untypical for independent samples drawn from a Potts model. Using a large test set of proteins we show that the combined improvements along the three dimensions are as large as any reported to date.
by Benedikt Obermayer, Erel LevinePost-transcriptional regulation by miRNAs is a widespread and highly conserved phenomenon in metazoans, with several hundreds to thousands of conserved binding sites for each miRNA, and up to two thirds of all genes under miRNA regulation. At the same time, the effect of miRNA regulation on mRNA and protein levels is usually quite modest and associated phenotypes are often weak or subtle. This has given rise to the notion that the highly interconnected miRNA regulatory network exerts its function less through any individual link and more via collective effects that lead to a functional interdependence of network links. We present a Bayesian framework to quantify conservation of miRNA target sites using vertebrate whole-genome alignments. The increased statistical power of our phylogenetic model allows detection of evolutionary correlation in the conservation patterns of site pairs. Such correlations could result from collective functions in the regulatory network. For instance, co-conservation of target site pairs supports a selective benefit of combinatorial regulation by multiple miRNAs. We find that some miRNA families are under pronounced co-targeting constraints, indicating a high connectivity in the regulatory network, while others appear to function in a more isolated way. By analyzing coordinated targeting of different curated gene sets, we observe distinct evolutionary signatures for protein complexes and signaling pathways that could reflect differences in control strategies. Our method is easily scalable to analyze upcoming larger data sets, and readily adaptable to detect high-level selective constraints between other genomic loci. We thus provide a proof-of-principle method to understand regulatory networks from an evolutionary perspective.
The SH2 Domain Regulates c-Abl Kinase Activation by a Cyclin-Like Mechanism and Remodulation of the Hinge Motion
by Nicole Dölker, Maria W. Górna, Ludovico Sutto, Antonio S. Torralba, Giulio Superti-Furga, Francesco L. GervasioRegulation of the c-Abl (ABL1) tyrosine kinase is important because of its role in cellular signaling, and its relevance in the leukemiogenic counterpart (BCR-ABL). Both auto-inhibition and full activation of c-Abl are regulated by the interaction of the catalytic domain with the Src Homology 2 (SH2) domain. The mechanism by which this interaction enhances catalysis is not known. We combined computational simulations with mutagenesis and functional analysis to find that the SH2 domain conveys both local and global effects on the dynamics of the catalytic domain. Locally, it regulates the flexibility of the αC helix in a fashion reminiscent of cyclins in cyclin-dependent kinases, reorienting catalytically important motifs. At a more global level, SH2 binding redirects the hinge motion of the N and C lobes and changes the conformational equilibrium of the activation loop. The complex network of subtle structural shifts that link the SH2 domain with the activation loop and the active site may be partially conserved with other SH2-domain containing kinases and therefore offer additional parameters for the design of conformation-specific inhibitors.
Beyond Muscles Stiffness: Importance of State-Estimation to Account for Very Fast Motor Corrections
by Frédéric Crevecoeur, Stephen H. ScottFeedback delays are a major challenge for any controlled process, and yet we are able to easily control limb movements with speed and grace. A popular hypothesis suggests that the brain largely mitigates the impact of feedback delays (∼50 ms) by regulating the limb intrinsic visco-elastic properties (or impedance) with muscle co-contraction, which generates forces proportional to changes in joint angle and velocity with zero delay. Although attractive, this hypothesis is often based on estimates of limb impedance that include neural feedback, and therefore describe the entire motor system. In addition, this approach does not systematically take into account that muscles exhibit high intrinsic impedance only for small perturbations (short-range impedance). As a consequence, it remains unclear how the nervous system handles large perturbations, as well as disturbances encountered during movement when short-range impedance cannot contribute. We address this issue by comparing feedback responses to load pulses applied to the elbow of human subjects with theoretical simulations. After validating the model parameters, we show that the ability of humans to generate fast and accurate corrective movements is compatible with a control strategy based on state estimation. We also highlight the merits of delay-uncompensated robust control, which can mitigate the impact of internal model errors, but at the cost of slowing feedback corrections. We speculate that the puzzling observation of presynaptic inhibition of peripheral afferents in the spinal cord at movement onset helps to counter the destabilizing transition from high muscle impedance during posture to low muscle impedance during movement.
by Jonathan Barnoud, Giulia Rossi, Siewert J. Marrink, Luca MonticelliCell membranes have a complex lateral organization featuring domains with distinct composition, also known as rafts, which play an essential role in cellular processes such as signal transduction and protein trafficking. In vivo, perturbations of membrane domains (e.g., by drugs or lipophilic compounds) have major effects on the activity of raft-associated proteins and on signaling pathways, but they are difficult to characterize because of the small size of the domains, typically below optical resolution. Model membranes, instead, can show macroscopic phase separation between liquid-ordered and liquid-disordered domains, and they are often used to investigate the driving forces of membrane lateral organization. Studies in model membranes have shown that some lipophilic compounds perturb membrane domains, but it is not clear which chemical and physical properties determine domain perturbation. The mechanisms of domain stabilization and destabilization are also unknown. Here we describe the effect of six simple hydrophobic compounds on the lateral organization of phase-separated model membranes consisting of saturated and unsaturated phospholipids and cholesterol. Using molecular simulations, we identify two groups of molecules with distinct behavior: aliphatic compounds promote lipid mixing by distributing at the interface between liquid-ordered and liquid-disordered domains; aromatic compounds, instead, stabilize phase separation by partitioning into liquid-disordered domains and excluding cholesterol from the disordered domains. We predict that relatively small concentrations of hydrophobic species can have a broad impact on domain stability in model systems, which suggests possible mechanisms of action for hydrophobic compounds in vivo.
Predicting the Functions and Specificity of Triterpenoid Synthases: A Mechanism-Based Multi-intermediate Docking Approach
by Bo-Xue Tian, Frank H. Wallrapp, Gemma L. Holiday, Jeng-Yeong Chow, Patricia C. Babbitt, C. Dale Poulter, Matthew P. JacobsonTerpenoid synthases construct the carbon skeletons of tens of thousands of natural products. To predict functions and specificity of triterpenoid synthases, a mechanism-based, multi-intermediate docking approach is proposed. In addition to enzyme function prediction, other potential applications of the current approach, such as enzyme mechanistic studies and enzyme redesign by mutagenesis, are discussed.
Depletion of the Chromatin Looping Proteins CTCF and Cohesin Causes Chromatin Compaction: Insight into Chromatin Folding by Polymer Modelling
by Mariliis Tark-Dame, Hansjoerg Jerabek, Erik M. M. Manders, Dieter W. Heermann, Roel van DrielFolding of the chromosomal fibre in interphase nuclei is an important element in the regulation of gene expression. For instance, physical contacts between promoters and enhancers are a key element in cell-type–specific transcription. We know remarkably little about the principles that control chromosome folding. Here we explore the view that intrachromosomal interactions, forming a complex pattern of loops, are a key element in chromosome folding. CTCF and cohesin are two abundant looping proteins of interphase chromosomes of higher eukaryotes. To investigate the role of looping in large-scale (supra Mb) folding of human chromosomes, we knocked down the gene that codes for CTCF and the one coding for Rad21, an essential subunit of cohesin. We measured the effect on chromosome folding using systematic 3D fluorescent in situ hybridization (FISH). Results show that chromatin becomes more compact after reducing the concentration of these two looping proteins. The molecular basis for this counter-intuitive behaviour is explored by polymer modelling usingy the Dynamic Loop model (Bohn M, Heermann DW (2010) Diffusion-driven looping provides a consistent framework for chromatin organization. PLoS ONE 5: e12218.). We show that compaction can be explained by selectively decreasing the number of short-range loops, leaving long-range looping unchanged. In support of this model prediction it has recently been shown by others that CTCF and cohesin indeed are responsible primarily for short-range looping. Our results suggest that the local and the overall changes in of chromosome structure are controlled by a delicate balance between short-range and long-range loops, allowing easy switching between, for instance, open and more compact chromatin states.
Complete Mapping of Substrate Translocation Highlights the Role of LeuT N-terminal Segment in Regulating Transport Cycle
by Mary Hongying Cheng, Ivet BaharNeurotransmitter: sodium symporters (NSSs) regulate neuronal signal transmission by clearing excess neurotransmitters from the synapse, assisted by the co-transport of sodium ions. Extensive structural data have been collected in recent years for several members of the NSS family, which opened the way to structure-based studies for a mechanistic understanding of substrate transport. Leucine transporter (LeuT), a bacterial orthologue, has been broadly adopted as a prototype in these studies. This goal has been elusive, however, due to the complex interplay of global and local events as well as missing structural data on LeuT N-terminal segment. We provide here for the first time a comprehensive description of the molecular events leading to substrate/Na+ release to the postsynaptic cell, including the structure and dynamics of the N-terminal segment using a combination of molecular simulations. Substrate and Na+-release follows an influx of water molecules into the substrate/Na+-binding pocket accompanied by concerted rearrangements of transmembrane helices. A redistribution of salt bridges and cation-π interactions at the N-terminal segment prompts substrate release. Significantly, substrate release is followed by the closure of the intracellular gate and a global reconfiguration back to outward-facing state to resume the transport cycle. Two minimally hydrated intermediates, not structurally resolved to date, are identified: one, substrate-bound, stabilized during the passage from outward- to inward-facing state (holo-occluded), and another, substrate-free, along the reverse transition (apo-occluded).
Linear Motif-Mediated Interactions Have Contributed to the Evolution of Modularity in Complex Protein Interaction Networks
by Inhae Kim, Heetak Lee, Seong Kyu Han, Sanguk KimThe modular architecture of protein-protein interaction (PPI) networks is evident in diverse species with a wide range of complexity. However, the molecular components that lead to the evolution of modularity in PPI networks have not been clearly identified. Here, we show that weak domain-linear motif interactions (DLIs) are more likely to connect different biological modules than strong domain-domain interactions (DDIs). This molecular division of labor is essential for the evolution of modularity in the complex PPI networks of diverse eukaryotic species. In particular, DLIs may compensate for the reduction in module boundaries that originate from increased connections between different modules in complex PPI networks. In addition, we show that the identification of biological modules can be greatly improved by including molecular characteristics of protein interactions. Our findings suggest that transient interactions have played a unique role in shaping the architecture and modularity of biological networks over the course of evolution.
Reconstruction of the Gene Regulatory Network Involved in the Sonic Hedgehog Pathway with a Potential Role in Early Development of the Mouse Brain
by Jinhua Liu, Xuelong Wang, Juan Li, Haifang Wang, Gang Wei, Jun YanThe Sonic hedgehog (Shh) signaling pathway is crucial for pattern formation in early central nervous system development. By systematically analyzing high-throughput in situ hybridization data of E11.5 mouse brain, we found that Shh and its receptor Ptch1 define two adjacent mutually exclusive gene expression domains: Shh+Ptch1− and Shh−Ptch1+. These two domains are associated respectively with Foxa2 and Gata3, two transcription factors that play key roles in specifying them. Gata3 ChIP-seq experiments and RNA-seq assays on Gata3-knockdown cells revealed that Gata3 up-regulates the genes that are enriched in the Shh−Ptch1+ domain. Important Gata3 targets include Slit2 and Slit3, which are involved in the process of axon guidance, as well as Slc18a1, Th and Qdpr, which are associated with neurotransmitter synthesis and release. By contrast, Foxa2 both up-regulates the genes expressed in the Shh+Ptch1− domain and down-regulates the genes characteristic of the Shh−Ptch1+ domain. From these and other data, we were able to reconstruct a gene regulatory network governing both domains. Our work provides the first genome-wide characterization of the gene regulatory network involved in the Shh pathway that underlies pattern formation in the early mouse brain.
Tracking the Sleep Onset Process: An Empirical Model of Behavioral and Physiological Dynamics
by Michael J. Prerau, Katie E. Hartnack, Gabriel Obregon-Henao, Aaron Sampson, Margaret Merlino, Karen Gannon, Matt T. Bianchi, Jeffrey M. Ellenbogen, Patrick L. PurdonThe sleep onset process (SOP) is a dynamic process correlated with a multitude of behavioral and physiological markers. A principled analysis of the SOP can serve as a foundation for answering questions of fundamental importance in basic neuroscience and sleep medicine. Unfortunately, current methods for analyzing the SOP fail to account for the overwhelming evidence that the wake/sleep transition is governed by continuous, dynamic physiological processes. Instead, current practices coarsely discretize sleep both in terms of state, where it is viewed as a binary (wake or sleep) process, and in time, where it is viewed as a single time point derived from subjectively scored stages in 30-second epochs, effectively eliminating SOP dynamics from the analysis. These methods also fail to integrate information from both behavioral and physiological data. It is thus imperative to resolve the mismatch between the physiological evidence and analysis methodologies. In this paper, we develop a statistically and physiologically principled dynamic framework and empirical SOP model, combining simultaneously-recorded physiological measurements with behavioral data from a novel breathing task requiring no arousing external sensory stimuli. We fit the model using data from healthy subjects, and estimate the instantaneous probability that a subject is awake during the SOP. The model successfully tracked physiological and behavioral dynamics for individual nights, and significantly outperformed the instantaneous transition models implicit in clinical definitions of sleep onset. Our framework also provides a principled means for cross-subject data alignment as a function of wake probability, allowing us to characterize and compare SOP dynamics across different populations. This analysis enabled us to quantitatively compare the EEG of subjects showing reduced alpha power with the remaining subjects at identical response probabilities. Thus, by incorporating both physiological and behavioral dynamics into our model framework, the dynamics of our analyses can finally match those observed during the SOP.
Expression Profile of the Schistosoma japonicum Degradome Reveals Differential Protease Expression Patterns and Potential Anti-schistosomal Intervention Targets
by Shuai Liu, Pengfei Cai, Xianyu Piao, Nan Hou, Xiaosu Zhou, Chuang Wu, Heng Wang, Qijun ChenBlood fluke proteases play pivotal roles in the processes of invasion, nutrition acquisition, immune evasion, and other host-parasite interactions. Hundreds of genes encoding putative proteases have been identified in the recently published schistosome genomes. However, the expression profiles of these proteases in Schistosoma species have not yet been systematically analyzed. We retrieved and culled the redundant protease sequences of Schistosoma japonicum, Schistosoma mansoni, Echinococcus multilocularis, and Clonorchis sinensis from public databases utilizing bioinformatic approaches. The degradomes of the four parasitic organisms and Homo sapiens were then comparatively analyzed. A total of 262 S. japonicum protease sequences were obtained and the expression profiles generated using whole-genome microarray. Four main clusters of protease genes with different expression patterns were identified: proteases up-regulated in hepatic schistosomula and adult worms, egg-specific or predominantly expressed proteases, cercaria-specific or predominantly expressed proteases, and constantly expressed proteases. A subset of protease genes with different expression patterns were further validated using real-time quantitative PCR. The present study represents the most comprehensive analysis of a degradome in Schistosoma species to date. These results provide a firm foundation for future research on the specific function(s) of individual proteases and may help to refine anti-proteolytic strategies in blood flukes.
by Andrew J. Fritz, Branislav Stojkovic, Hu Ding, Jinhui Xu, Sambit Bhattacharya, Ronald BerezneyThe interchromosomal organization of a subset of human chromosomes (#1, 4, 11, 12, 16, 17, and 18) was examined in G1 and S phase of human WI38 lung fibroblast and MCF10A breast epithelial cells. Radial positioning of the chromosome territories (CTs) was independent of gene density, but size dependent. While no changes in radial positioning during the cell cycle were detected, there were stage-specific differences between cell types. Each CT was in close proximity (interaction) with a similar number of other CT except the gene rich CT17 which had significantly more interactions. Furthermore, CT17 was a member of the highest pairwise CT combinations with multiple interactions. Major differences were detected in the pairwise interaction profiles of MCF10A versus WI38 including cell cycle alterations from G1 to S. These alterations in interaction profiles were subdivided into five types: overall increase, overall decrease, switching from 1 to ≥2 interactions, vice versa, or no change. A global data mining program termed the chromatic median determined the most probable overall association network for the entire subset of CT. This probabilistic interchromosomal network was nearly completely different between the two cell lines. It was also strikingly altered across the cell cycle in MCF10A, but only slightly in WI38. We conclude that CT undergo multiple and preferred interactions with other CT in the nucleus and form preferred -albeit probabilistic- interchromosomal networks. This network of interactions is altered across the cell cycle and between cell types. It is intriguing to consider the relationship of these alterations to the corresponding changes in the gene expression program across the cell cycle and in different cell types.
Confidence Sharing: An Economic Strategy for Efficient Information Flows in Animal Groups
by Amos Korman, Efrat Greenwald, Ofer FeinermanSocial animals may share information to obtain a more complete and accurate picture of their surroundings. However, physical constraints on communication limit the flow of information between interacting individuals in a way that can cause an accumulation of errors and deteriorated collective behaviors. Here, we theoretically study a general model of information sharing within animal groups. We take an algorithmic perspective to identify efficient communication schemes that are, nevertheless, economic in terms of communication, memory and individual internal computation. We present a simple and natural algorithm in which each agent compresses all information it has gathered into a single parameter that represents its confidence in its behavior. Confidence is communicated between agents by means of active signaling. We motivate this model by novel and existing empirical evidences for confidence sharing in animal groups. We rigorously show that this algorithm competes extremely well with the best possible algorithm that operates without any computational constraints. We also show that this algorithm is minimal, in the sense that further reduction in communication may significantly reduce performances. Our proofs rely on the Cramér-Rao bound and on our definition of a Fisher Channel Capacity. We use these concepts to quantify information flows within the group which are then used to obtain lower bounds on collective performance. The abstract nature of our model makes it rigorously solvable and its conclusions highly general. Indeed, our results suggest confidence sharing as a central notion in the context of animal communication.
Evidence of Conformational Selection Driving the Formation of Ligand Binding Sites in Protein-Protein Interfaces
by Tanggis Bohnuud, Dima Kozakov, Sandor VajdaMany protein-protein interactions (PPIs) are compelling targets for drug discovery, and in a number of cases can be disrupted by small molecules. The main goal of this study is to examine the mechanism of binding site formation in the interface region of proteins that are PPI targets by comparing ligand-free and ligand-bound structures. To avoid any potential bias, we focus on ensembles of ligand-free protein conformations obtained by nuclear magnetic resonance (NMR) techniques and deposited in the Protein Data Bank, rather than on ensembles specifically generated for this study. The measures used for structure comparison are based on detecting binding hot spots, i.e., protein regions that are major contributors to the binding free energy. The main tool of the analysis is computational solvent mapping, which explores the surface of proteins by docking a large number of small “probe” molecules. Although we consider conformational ensembles obtained by NMR techniques, the analysis is independent of the method used for generating the structures. Finding the energetically most important regions, mapping can identify binding site residues using ligand-free models based on NMR data. In addition, the method selects conformations that are similar to some peptide-bound or ligand-bound structure in terms of the properties of the binding site. This agrees with the conformational selection model of molecular recognition, which assumes such pre-existing conformations. The analysis also shows the maximum level of similarity between unbound and bound states that is achieved without any influence from a ligand. Further shift toward the bound structure assumes protein-peptide or protein-ligand interactions, either selecting higher energy conformations that are not part of the NMR ensemble, or leading to induced fit. Thus, forming the sites in protein-protein interfaces that bind peptides and can be targeted by small ligands always includes conformational selection, although other recognition mechanisms may also be involved.
Natural Isotopic Signatures of Variations in Body Nitrogen Fluxes: A Compartmental Model Analysis
by Nathalie Poupin, François Mariotti, Jean-François Huneau, Dominique Hermier, Hélène FouilletBody tissues are generally 15N-enriched over the diet, with a discrimination factor (Δ15N) that varies among tissues and individuals as a function of their nutritional and physiopathological condition. However, both 15N bioaccumulation and intra- and inter-individual Δ15N variations are still poorly understood, so that theoretical models are required to understand their underlying mechanisms. Using experimental Δ15N measurements in rats, we developed a multi-compartmental model that provides the first detailed representation of the complex functioning of the body's Δ15N system, by explicitly linking the sizes and Δ15N values of 21 nitrogen pools to the rates and isotope effects of 49 nitrogen metabolic fluxes. We have shown that (i) besides urea production, several metabolic pathways (e.g., protein synthesis, amino acid intracellular metabolism, urea recycling and intestinal absorption or secretion) are most probably associated with isotope fractionation and together contribute to 15N accumulation in tissues, (ii) the Δ15N of a tissue at steady-state is not affected by variations of its P turnover rate, but can vary according to the relative orientation of tissue free amino acids towards oxidation vs. protein synthesis, (iii) at the whole-body level, Δ15N variations result from variations in the body partitioning of nitrogen fluxes (e.g., urea production, urea recycling and amino acid exchanges), with or without changes in nitrogen balance, (iv) any deviation from the optimal amino acid intake, in terms of both quality and quantity, causes a global rise in tissue Δ15N, and (v) Δ15N variations differ between tissues depending on the metabolic changes involved, which can therefore be identified using simultaneous multi-tissue Δ15N measurements. This work provides proof of concept that Δ15N measurements constitute a new promising tool to investigate how metabolic fluxes are nutritionally or physiopathologically reorganized or altered. The existence of such natural and interpretable isotopic biomarkers promises interesting applications in nutrition and health.
Fast Synchronization of Ultradian Oscillators Controlled by Delta-Notch Signaling with Cis-Inhibition
by Hendrik B. Tiedemann, Elida Schneltzer, Stefan Zeiser, Wolfgang Wurst, Johannes Beckers, Gerhard K. H. Przemeck, Martin Hrabě de AngelisWhile it is known that a large fraction of vertebrate genes are under the control of a gene regulatory network (GRN) forming a clock with circadian periodicity, shorter period oscillatory genes like the Hairy-enhancer-of split (Hes) genes are discussed mostly in connection with the embryonic process of somitogenesis. They form the core of the somitogenesis-clock, which orchestrates the periodic separation of somites from the presomitic mesoderm (PSM). The formation of sharp boundaries between the blocks of many cells works only when the oscillators in the cells forming the boundary are synchronized. It has been shown experimentally that Delta-Notch (D/N) signaling is responsible for this synchronization. This process has to happen rather fast as a cell experiences at most five oscillations from its ‘birth’ to its incorporation into a somite. Computer simulations describing synchronized oscillators with classical modes of D/N-interaction have difficulties to achieve synchronization in an appropriate time. One approach to solving this problem of modeling fast synchronization in the PSM was the consideration of cell movements. Here we show that fast synchronization of Hes-type oscillators can be achieved without cell movements by including D/N cis-inhibition, wherein the mutual interaction of DELTA and NOTCH in the same cell leads to a titration of ligand against receptor so that only one sort of molecule prevails. Consequently, the symmetry between sender and receiver is partially broken and one cell becomes preferentially sender or receiver at a given moment, which leads to faster entrainment of oscillators. Although not yet confirmed by experiment, the proposed mechanism of enhanced synchronization of mesenchymal cells in the PSM would be a new distinct developmental mechanism employing D/N cis-inhibition. Consequently, the way in which Delta-Notch signaling was modeled so far should be carefully reconsidered.
Mesoscopic Model and Free Energy Landscape for Protein-DNA Binding Sites: Analysis of Cyanobacterial Promoters
by Rafael Tapia-Rojo, Juan José Mazo, José Ángel Hernández, María Luisa Peleato, María F. Fillat, Fernando FaloThe identification of protein binding sites in promoter sequences is a key problem to understand and control regulation in biochemistry and biotechnological processes. We use a computational method to analyze promoters from a given genome. Our approach is based on a physical model at the mesoscopic level of protein-DNA interaction based on the influence of DNA local conformation on the dynamics of a general particle along the chain. Following the proposed model, the joined dynamics of the protein particle and the DNA portion of interest, only characterized by its base pair sequence, is simulated. The simulation output is analyzed by generating and analyzing the Free Energy Landscape of the system. In order to prove the capacity of prediction of our computational method we have analyzed nine promoters of Anabaena PCC 7120. We are able to identify the transcription starting site of each of the promoters as the most populated macrostate in the dynamics. The developed procedure allows also to characterize promoter macrostates in terms of thermo-statistical magnitudes (free energy and entropy), with valuable biological implications. Our results agree with independent previous experimental results. Thus, our methods appear as a powerful complementary tool for identifying protein binding sites in promoter sequences.