Thorsten Lenser

Dynamics of component exchange at PML nuclear bodies.

PML nuclear bodies (NBs) are involved in the regulation of key nuclear pathways but their biochemical function in nuclear metabolism is unknown. In this study PML NB assembly dynamics were assessed by live cell imaging and mathematic modeling of its major component parts. We show that all six nuclear PML isoforms exhibit individual exchange rates at NBs and identify PML V as a scaffold subunit. SP100 exchanges at least five times faster at NBs than PML proteins. Turnover dynamics of PML and SP100 at NBs is modulated by SUMOylation. Exchange is not temperature-dependent but depletion of cellular ATP levels induces protein immobilization at NBs. The PML-RARα oncogene exhibits a strong NB retention effect on wild-type PML proteins. HIPK2 requires an active kinase for PML NB targeting and elevated levels of PML IV increase its residence time. DAXX and BLM turn over rapidly and completely at PML NBs within seconds. These findings provide a kinetics model for factor exchange at PML NBs and highlight potential mechanisms to regulate intranuclear trafficking of specific factors at these domains.

Rule-based spatial modeling with diffusing, geometrically constrained molecules

BackgroundWe suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined.For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided.ResultsOur simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa.ConclusionsWe conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly.

Assembly dynamics of PML nuclear bodies in living cells

The mammalian cell nucleus contains a variety of organelles or nuclear bodies which contribute to key nuclear functions. Promyelocytic leukemia nuclear bodies (PML NBs) are involved in the regulation of apoptosis, antiviral responses, the DNA damage response and chromatin structure, but their precise biochemical function in these nuclear pathways is unknown. One strategy to tackle this problem is to assess the biophysical properties of the component parts of these macromolecular assemblies in living cells. In this study we determined PML NB assembly dynamics by live cell imaging, combined with mathematical modeling. For the first time, dynamics of PML body formation were measured in cells lacking endogenous PML. We show that all six human nuclear PML isoforms are able to form nuclear bodies in PML negative cells. All isoforms exhibit individual exchange rates at NBs in PML positive cells but PML I, II, III and IV are static at nuclear bodies in PML negative cells, suggesting that these isoforms require additional protein partners for efficient exchange. PML V turns over at PML Nbs very slowly supporting the idea of a structural function for this isoform. We also demonstrate that SUMOylation of PML at Lysine positions K160 and/or K490 are required for nuclear body formation in vivo.We propose a model in which the isoform specific residence times of PML provide both, structural stability to function as a scaffold and flexibility to attract specific nuclear proteins for efficient biochemical reactions at the surface of nuclear bodies. MCS code: 92C37

Developmental Robustness by Obligate Interaction of Class B Floral Homeotic Genes and Proteins

DEF-like and GLO-like class B floral homeotic genes encode closely related MADS-domain transcription factors that act as developmental switches involved in specifying the identity of petals and stamens during flower development. Class B gene function requires transcriptional upregulation by an autoregulatory loop that depends on obligate heterodimerization of DEF-like and GLO-like proteins. Because switch-like behavior of gene expression can be displayed by single genes already, the functional relevance of this complex circuitry has remained enigmatic. On the basis of a stochastic in silico model of class B gene and protein interactions, we suggest that obligate heterodimerization of class B floral homeotic proteins is not simply the result of neutral drift but enhanced the robustness of cell-fate organ identity decisions in the presence of stochastic noise. This finding strongly corroborates the view that the appearance of this regulatory mechanism during angiosperm phylogeny led to a canalization of flower development and evolution.

TassDB2 - A comprehensive database of subtle alternative splicing events

BackgroundSubtle alternative splicing events involving tandem splice sites separated by a short (2-12 nucleotides) distance are frequent and evolutionarily widespread in eukaryotes, and a major contributor to the complexity of transcriptomes and proteomes. However, these events have been either omitted altogether in databases on alternative splicing, or only the cases of experimentally confirmed alternative splicing have been reported. Thus, a database which covers all confirmed cases of subtle alternative splicing as well as the numerous putative tandem splice sites (which might be confirmed once more transcript data becomes available), and allows to search for tandem splice sites with specific features and download the results, is a valuable resource for targeted experimental studies and large-scale bioinformatics analyses of tandem splice sites. Towards this goal we recently set up TassDB (Tandem Splice Site DataBase, version 1), which stores data about alternative splicing events at tandem splice sites separated by 3 nt in eight species.DescriptionWe have substantially revised and extended TassDB. The currently available version 2 contains extensive information about tandem splice sites separated by 2-12 nt for the human and mouse transcriptomes including data on the conservation of the tandem motifs in five vertebrates. TassDB2 offers a user-friendly interface to search for specific genes or for genes containing tandem splice sites with specific features as well as the possibility to download result datasets. For example, users can search for cases of alternative splicing where the proportion of EST/mRNA evidence supporting the minor isoform exceeds a specific threshold, or where the difference in splice site scores is specified by the user. The predicted impact of each event on the protein is also reported, along with information about being a putative target for the nonsense-mediated decay (NMD) pathway. Links are provided to the UCSC genome browser and other external resources.ConclusionTassDB2, available via http://www.tassdb.info, provides comprehensive resources for researchers interested in both targeted experimental studies and large-scale bioinformatics analyses of short distance tandem splice sites.

REGISTER MACHINE COMPUTATIONS ON BINARY NUMBERS BY OSCILLATING AND CATALYTIC CHEMICAL REACTIONS MODELLED USING MASS-ACTION KINETICS

Biocomputing emerged as a promising paradigm capable of coping efficiently with challenges of programming decentralized but concerted reaction systems. The chemical programming metaphor subsumes different encoding techniques into molecular or spatial structures in conjunction with artificial reaction networks. Here, a variety of supplementary assumptions like predefined polymeric sequences or availability of inhibiting reactions is frequently used. Inspired by the idea to build chemical computers based on minimal requirements in chemistry from a theoretical perspective, we introduce a pure chemical register machine model operating on binary numbers. The register machine architecture is composed of reaction network motifs acting as fast switching logic gates, oscillators, and self-reproducible bit storage units. The dynamical machine behavior consistently employs mass-action kinetics. Two case studies, calculating the maximum of three natural numbers as well as numerical addition, illustrate the practicability of the design along with dynamical simulations.

Hill kinetics meets P systems: a case study on gene regulatory networks as computing agents in silico and in vivo

Modeling and simulation of biological reaction networks is an essential task in systems biology aiming at formalization, understanding, and prediction of processes in living organisms. Currently, a variety of modeling approaches for specific purposes coexists. P systems form such an approach which owing to its algebraic nature opens growing fields of application. Here, emulating the dynamical system behavior based on reaction kinetics is of particular interest to explore network functions. We demonstrate a transformation of Hill kinetics for gene regulatory networks (GRNs) into the P systems framework. Examples address the switching dynamics of GRNs acting as NAND gate and RS flip-flop. An adapted study in vivo experimentally verifies both practicability for computational units and validity of the system model.

Towards evolutionary network reconstruction tools for systems biology

Systems biology is the ever-growing field of integrating molecular knowledge about biological organisms into an understanding at the systems level. For this endeavour, automatic network reconstruction tools are urgently needed. In the present contribution, we show how the applicability of evolutionary algorithms to systems biology can be improved by a domain-specific representation and algorithmic extensions, especially a separation of network structure evolution from evolution of kinetic parameters. In a case study, our presented tool is applied to a model of the mitotic spindle checkpoint in the human cell cycle.

A protein substructure based p system for description and analysis of cell signalling networks

The way how cell signals are generated, encoded, transferred, modified, and utilized is essential for understanding information processing inside living organisms. The tremendously growing biological knowledge about proteins and their interactions draws a more and more detailed image of a complex functional network. Considering signalling networks as computing devices, the detection of structural principles, especially modularization into subunits and interfaces between them, can help to seize ideas for their description and analysis. Algebraic models like P systems prove to be appropriate to this. We utilize string-objects to carry information about protein binding domains and their ligands. Embedding these string-objects into a deterministic graph structured P system with dynamical behavior, we introduce a model that can describe cell signalling pathways on a submolecular level. Beyond questions of formal languages, the model facilitates tracing the evolutionary development from single protein components towards functional interacting networks. We exemplify the model by means of the yeast pheromone pathway.

Modelling signalling networks with incomplete information about protein activation states: a p system framework of the KaiABC oscillator

Reconstruction of signal transduction network models based on incomplete information about network structure and dynamical behaviour is a major challenge in current systems biology. In particular, interactions within signalling networks are frequently characterised by partially unknown protein phosphorylation and dephosphorylation cascades at a submolecular description level. For prediction of promising network candidates, reverse engineering techniques typically enumerate the reaction search space. Considering an underlying amount of phosphorylation sites, this implies a potentially exponential number of individual reactions in conjunction with corresponding protein activation states. To manage the computational complexity, we extend P systems with string-objects by a subclass for protein representation able to process wild-carded together with specific information about protein binding domains and their ligands. This variety of reactants works together with assigned term-rewriting mechanisms derived from discretised reaction kinetics. We exemplify the descriptional capability and flexibility of the framework by discussing model candidates for the circadian clock formed by the KaiABC oscillator found in the cyanobacterium Synechococcus elongatus. A simulation study of its dynamical behaviour demonstrates effects of superpositioned protein abundance courses based on regular expressions corresponding to dedicated protein activation states.