Constraint-based simulation of multiple interactive elemental cycles in biogeochemical systems

Simulating multiple linked elemental cycles is a frontier in the field of biogeochemistry. The Generalized Algorithm for Nutrient, Growth, Stoichiometric and Thermodynamic Analysis (GANGSTA) is a software framework that automates the instantiation of formalized, user-defined conceptual models of linked elemental cycles as simulation model code. The GANGSTA employs first principles of stoichiometry and thermodynamics to generate models that simulate any suite of elemental cycles, compounds, metabolic processes, and microorganisms. Results demonstrated, e.g., that simulating the oxygen (O) cycle, rather than oxic versus anoxic conditions, fundamentally altered carbon (C) and nitrogen (N) cycling - despite holding the compounds and processes involved in the C and N cycles constant. Additionally, incorporating the sulfur (S) cycle substantively changed C and N cycling, largely via shifts in the O cycle. Thus, emergent dynamics from GANGSTA-derived models can aid in the development of hypotheses to describe the specific mechanisms of interdependence among linked elemental cycles.     

ABPL

Computer analysis of biological systems, using approaches such as metabolic control analysis is common. A typical example is a language like Herbert Sauro's SCAMP (Sauro & Fell, 1991), which allows simulations of enzyme systems, and calculation of control coefficients and elasticities. However such systems are motivated by the underlying biochemical theory and often have limitations as programming languages which mean that they can only be applied to particular classes of problems. ABPL (a biochemical programming language) extends these ideas by adding all the facilities of a fully-fledged programming language, together with some of the capabilities of a modern computer algebra system. Syntactically it derives from the programming language LISP, while the underlying functionality is that of iMAP, the successor to SCAMP. This provides us with a computer system capable of performing most of the tasks undertaken by existing packages, but more importantly, a system which can be easily extended into new areas. Key features of the work are:

- Ability to use the language both interactively and as a batch programming language

- Ability to work both symbolically and numerically

- Ability to handle matrices and vectors

- Ability to define and manipulate reaction schemes

- Common techniques are built in to the language

- Ability to add new operations to the language

The implementation is in ANSI standard C for portability.     

GEPASI: a software package for modelling the dynamics, steady states and control of biochemical and other systems

GEPASI is a software system for modelling chemical and biochemicalreaction networks on computers running Microsoft Windows. Forany system of up to 45 metabolites and 45 reactions, each withany user-defined or one of 35 predefined rate equations, onecan produce trajectories of the metabolite concentrations andobtain a steady state (if it does exist). When steady-statesolutions are produced, elasticity and control coefficients,as defined in metabolic control analysis, are calculated. GEPASIalso allows the automatic generation of a sequence of simulationswith different combinations of parameter values, effectivelyscanning a hyper-solid in parameter space. Together with theability to produce user-defined columnar data files, these featuresallow for both very quick and systematic study of biochemicalpathway models. The source code (in C) is available on requestfrom the author, and while the user interface is dependent onhaving MS-Windows as the operating system, the numerical partis portable to other operating systems. GEPASI is suitable bothfor research and educational purposes. Although GEPASI was writtenwith biochemical pathways in mind, it can equally be used tosimulate other dynamical systems.     

NERDSS: A Nonequilibrium Simulator for Multibody Self-Assembly at the Cellular Scale

Currently, a significant barrier to building predictive models of cellular self-assembly processes is that molecular models cannot capture minutes-long dynamics that couple distinct components with active processes, whereas reaction-diffusion models cannot capture structures of molecular assembly. Here, we introduce the nonequilibrium reaction-diffusion self-assembly simulator (NERDSS), which addresses this spatiotemporal resolution gap. NERDSS integrates efficient reaction-diffusion algorithms into generalized software that operates on user-defined molecules through diffusion, binding and orientation, unbinding, chemical transformations, and spatial localization. By connecting the fast processes of binding with the slow timescales of large-scale assembly, NERDSS integrates molecular resolution with reversible formation of ordered, multisubunit complexes. NERDSS encodes models using rule-based formatting languages to facilitate model portability, usability, and reproducibility. Applying NERDSS to steps in clathrin-mediated endocytosis, we design multicomponent systems that can form lattices in solution or on the membrane, and we predict how stochastic but localized dephosphorylation of membrane lipids can drive lattice disassembly. The NERDSS simulations reveal the spatial constraints on lattice growth and the role of membrane localization and cooperativity in nucleating assembly. By modeling viral lattice assembly and recapitulating oscillations in protein expression levels for a circadian clock model, we illustrate the adaptability of NERDSS. NERDSS simulates user-defined assembly models that were previously inaccessible to existing software tools, with broad applications to predicting self-assembly in vivo and designing high-yield assemblies in vitro.     

MEG (Model Extender for Gepasi): a program for the modelling of complex, heterogeneous, cellular systems

SUMMARY: We describe a program for the construction of spatially distributed metabolic models, which may then be simulated using the metabolic simulator GEPASI: This is useful for the modelling of heterogeneous systems whether as liquid cultures or as spatially organised systems with specified interconnections.     

A specification language for planning and fault recovery in manufacturing systems

This paper presents the syntax and semantics of a component-oriented rule-based language for specifying the formal models of manufacturing systems. A model captures the state of a component of the system in a set of first-order logic predicates, and it captures the semantics of the operations performed by this component in a set of rules that determine the preconditions and postconditions of an operation. The models are then used to plan the sequence of operations of each class of jobs to be manufactured by these systems. A plan-oriented fault detection and correction strategy is proposed. This strategy can automatically handle any combination of faults that may occur when monitoring the operations of manufacturing systems. A fault-tree is consulted prior to executing the scheduled operations of a plan, and the faults that affect the execution of these operations are handled subsequently. Resuming the original cyclic schedule is attempted, whenever feasible. As a proof of concept, a prototype implementation of both the main constructs of the component-oriented rule-based language and the planning and fault-recovery algorithms presented in this paper have been completed. This prototype is implemented on a Unix-based system in the Ada programming language. The specification of a manufacturing system is first expressed in the proposed language. These statements are then translated into Ada code. This code is next compiled by a Verdix Ada compiler and is executed in order to create and populate the model data structure of the system. A detailed plan of execution and a set of fault-recovery plans may then be derived for a job to be manufactured on this system.     

Secretory carrier membrane protein 2 regulates exocytic insertion of NKCC2 into the cell membrane

The renal-specific Na-K-2Cl co-transporter, NKCC2, plays a pivotal role in regulating body salt levels and blood pressure. NKCC2 mutations lead to type I Bartter syndrome, a life-threatening kidney disease. Regulation of NKCC2 trafficking behavior serves as a major mechanism in controlling NKCC2 activity across the plasma membrane. However, the identities of the protein partners involved in cell surface targeting of NKCC2 are largely unknown. To gain insight into these processes, we used a yeast two-hybrid system to screen a kidney cDNA library for proteins that interact with the NKCC2 C terminus. One binding partner we identified was SCAMP2 (secretory carrier membrane protein 2). Microscopic confocal imaging and co-immunoprecipitation assays confirmed NKCC2-SCAMP2 interaction in renal cells. SCAMP2 associated also with the structurally related co-transporter NCC, suggesting that the interaction with SCAMP2 is a common feature of sodium-dependent chloride co-transporters. Heterologous expression of SCAMP2 specifically decreased cell surface abundance as well as transport activity of NKCC2 across the plasma membrane. Co-immunolocalization experiments revealed that intracellularly retained NKCC2 co-localizes with SCAMP2 in recycling endosomes. The rate of NKCC2 endocytic retrieval, assessed by the sodium 2-mercaptoethane sulfonate cleavage assay, was not affected by SCAMP2. The surface-biotinylatable fraction of newly inserted NKCC2 in the plasma membrane was reduced by SCAMP2, demonstrating that SCAMP2-induced decrease in surface NKCC2 is due to decreased exocytotic trafficking. Finally, a single amino acid mutation, cysteine 201 to alanine, within the conserved cytoplasmic E peptide of SCAMP2, which is believed to regulate exocytosis, abolished SCAMP2-mediated down-regulation of the co-transporter. Taken together, these data are consistent with a model whereby SCAMP2 regulates NKCC2 transit through recycling endosomes and limits the cell surface targeting of the co-transporter by interfering with its exocytotic trafficking.     

Using Biological Pathway Data with Paxtools

A rapidly growing corpus of formal, computable pathway information can be used to answer important biological questions including finding non-trivial connections between cellular processes, identifying significantly altered portions of the cellular network in a disease state and building predictive models that can be used for precision medicine. Due to its complexity and fragmented nature, however, working with pathway data is still difficult. We present Paxtools, a Java library that contains algorithms, software components and converters for biological pathways represented in the standard BioPAX language. Paxtools allows scientists to focus on their scientific problem by removing technical barriers to access and analyse pathway information. Paxtools can run on any platform that has a Java Runtime Environment and was tested on most modern operating systems. Paxtools is open source and is available under the Lesser GNU public license (LGPL), which allows users to freely use the code in their software systems with a requirement for attribution. Source code for the current release (4.2.0) can be found in Software S1. A detailed manual for obtaining and using Paxtools can be found in Protocol S1. The latest sources and release bundles can be obtained from biopax.org/paxtools.

This is a PLOS Computational Biology Software Article

     

Secretory carrier membrane protein SCAMP2 and phosphatidylinositol 4,5-bisphosphate interactions in the regulation of dense core vesicle exocytosis

Secretory carrier membrane protein 2 (SCAMP2) functions in late steps of membrane fusion in calcium-dependent granule exocytosis. A basic/hydrophobic peptide segment within SCAMP2 (SCAMP2 E: CWYRPIYKAFR) has been implicated in this function and shown to bind and sequester phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2 or PIP2] within membranes through an electrostatic mechanism. We now show that alanine substitution of tryptophan W2 within SCAMP2 E substantially weakens peptide binding to negatively charged liposomes; other substitutions for arginine R4 and lysine K8 have only limited effects on binding. Electron paramagnetic resonance analysis of liposomes containing spin-labeled PIP2 shows that R4 but not K8 is critical for SCAMP E binding to PIP2. The interfacial locations of SCAMP E and its structural variants within lipid bicelles measured by oxygen enhancement of nuclear relaxation are all similar. Corresponding point mutations within full-length SCAMP2 (SC2-R204A, SC2-K208A, and SC2-W202A) have been analyzed for biological effects on dense core vesicle exocytosis in neuroendocrine PC12 cells. With the same level of overexpression, SC2-R204A but not SC2-K208A inhibited secretion of cotransfected human growth hormone and of noradrenalin. Inhibition by SC2-R204A was the same as or greater than previously observed for SC2-W202A. Analysis of noradrenalin secretion by amperometry showed that inhibitory mutants of SCAMP2 decrease the probability of fusion pore opening and the stability of initially opened but not yet expanded fusion pores. The strong correlation between SCAMP2 E interactions with PIP2 and inhibition of exocytosis, particularly by SC2-R204A, led us to propose that SCAMP2 interaction with PIP2 within the membrane interface regulates fusion pore formation during exocytosis.     

Analysis of SCAMP1 function in secretory vesicle exocytosis by means of gene targeting in mice.

Secretory carrier membrane proteins (SCAMPs) comprise a family of ubiquitous membrane proteins of transport vesicles with no known function. Their universal presence in all cells suggests a fundamental role in membrane traffic. SCAMPs are particularly highly expressed in organelles that undergo regulated exocytosis, such as synaptic vesicles and mast cell granules. Of the three currently known SCAMPs, SCAMP1 is the most abundant. To investigate the possible functions of SCAMP1, we generated mice that lack SCAMP1. SCAMP1-deficient mice are viable and fertile. They exhibit no changes in the overall architecture or the protein composition of the brain or alterations in peripheral organs. Capacitance measurements in mast cells demonstrated that exocytosis could be triggered reliably by GTPgammaS in SCAMP1-deficient cells. The initial overall capacitance of mast cells was similar between wild type and mutant mice, but the final cell capacitance after completion of exocytosis, was significantly smaller in SCAMP1-deficient cells than in wild type cells. Furthermore, there was an increased proportion of reversible fusion events, which may have caused the decrease in the overall capacitance change observed after exocytosis. Our data show that SCAMP1 is not essential for exocytosis, as such, and does not determine the stability or size of secretory vesicles, but is required for the full execution of stable exocytosis in mast cells. This phenotype could be the result of a function of SCAMP1 in the formation of stable fusion pores during exocytosis or of a role of SCAMP1 in the regulation of endocytosis after formation of fusion pores.     

A rule-based model of barley morphogenesis, with special respect to shading and gibberellic acid signal transduction

BACKGROUND AND AIMS: Functional-structural plant models (FSPM) constitute a paradigm in plant modelling that combines 3D structural and graphical modelling with the simulation of plant processes. While structural aspects of plant development could so far be represented using rule-based formalisms such as Lindenmayer systems, process models were traditionally written using a procedural code. The faithful representation of structures interacting with functions across scales, however, requires a new modelling formalism. Therefore relational growth grammars (RGG) were developed on the basis of Lindenmayer systems. METHODS: In order to implement and test RGG, a new modelling language, the eXtended L-system language (XL) was created. Models using XL are interpreted by the interactive, Java-based modelling platform GroIMP. Three models, a semi-quantitative gibberellic acid (GA) signal transduction model, and a phytochrome-based shade detection and object avoidance model, both coupled to an existing morphogenetic structural model of barley (Hordeum vulgare L.), serve as examples to demonstrate the versatility and suitability of RGG and XL to represent the interaction of diverse biological processes across hierarchical scales. KEY RESULTS: The dynamics of the concentrations in the signal transduction network could be modelled qualitatively and the phenotypes of GA-response mutants faithfully reproduced. The light model used here was simple to use yet effective enough to carry out local measurement of red:far-red ratios. Suppression of tillering at low red:far-red ratios could be simulated. CONCLUSIONS: The RGG formalism is suitable for implementation of multi-scaled FSPM of plants interacting with their environment via hormonal control. However, their ensuing complexity requires careful design. On the positive side, such an FSPM displays knowledge gaps better thereby guiding future experimental design.     

A federated design for a neurobiological simulation engine: the CBI federated software architecture

Simulator interoperability and extensibility has become a growing requirement in computational biology. To address this, we have developed a federated software architecture. It is federated by its union of independent disparate systems under a single cohesive view, provides interoperability through its capability to communicate, execute programs, or transfer data among different independent applications, and supports extensibility by enabling simulator expansion or enhancement without the need for major changes to system infrastructure. Historically, simulator interoperability has relied on development of declarative markup languages such as the neuron modeling language NeuroML, while simulator extension typically occurred through modification of existing functionality. The software architecture we describe here allows for both these approaches. However, it is designed to support alternative paradigms of interoperability and extensibility through the provision of logical relationships and defined application programming interfaces. They allow any appropriately configured component or software application to be incorporated into a simulator. The architecture defines independent functional modules that run stand-alone. They are arranged in logical layers that naturally correspond to the occurrence of high-level data (biological concepts) versus low-level data (numerical values) and distinguish data from control functions. The modular nature of the architecture and its independence from a given technology facilitates communication about similar concepts and functions for both users and developers. It provides several advantages for multiple independent contributions to software development. Importantly, these include: (1) Reduction in complexity of individual simulator components when compared to the complexity of a complete simulator, (2) Documentation of individual components in terms of their inputs and outputs, (3) Easy removal or replacement of unnecessary or obsoleted components, (4) Stand-alone testing of components, and (5) Clear delineation of the development scope of new components.     

Concerns with computational protein engineering programmes IPRO and OptMAVEn and metabolic pathway engineering programme optStoic

It has become customary in engineering to require a modelling component in research endeavours. In addition, as the code for these models becomes more byzantine in complexity, it is difficult for reviewers and readers to discern their value and understand the underlying code. This opinion piece summarizes the negative experience of the author with the IPRO and OptMAVEn computational protein engineering models as well as problems with the optStoic metabolic pathway model. In our hands, these models often fail to predict reliable ways to engineer proteins and metabolic pathways.     

Chebanov law and Vakar formula in mathematical models of complex systems

Ecological models written in a mathematical language L(M) or model language, with a given style or methodology can be considered as a text. It is possible to apply statistical linguistic laws and the experimental results demonstrate that the behaviour of a mathematical model is the same of any literary text of any natural language. A text has the following characteristics: (a) the variables, its transformed functions and parameters are the lexic units or LUN of ecological models; (b) the syllables are constituted by a LUN, or a chain of them, separated by operating or ordering LUNs; (c) the flow equations are words; and (d) the distribution of words (LUM and CLUN) according to their lengths is based on a Poisson distribution, the Chebanov's law. It is founded on Vakar's formula, that is calculated likewise the linguistic entropy for L(M). We will apply these ideas over practical examples using MARIOLA model. In this paper it will be studied the problem of the lengths of the simple lexic units composed lexic units and words of text models, expressing these lengths in number of the primitive symbols, and syllables. The use of these linguistic laws renders it possible to indicate the degree of information given by an ecological model.     

Metabolic engineering in silico

This review briefs on the main directions in the field of mathematical modeling of metabolic processes aimed at a rational design of genetically modified organisms. The class of generalized Hill functions is described, and their application to modeling of nonlinear processes in Escherichia coli metabolic systems is illustrated by several examples. A model for the pyrimidine biosynthesis in E. coli, taking into account the nonlinear effects of a negative allosteric regulation of enzyme activities involved in the control of the subsequent stages by the end products of synthesis, is considered. It has been shown that the model displays its own continuous oscillation mode of functioning with a period of approximately 50 min, which is close to the duration of E. coli cell cycle. The need in considering the nonlinear effects in the models as essential elements in the function of metabolic systems far from equilibrium is discussed.     

The secretory carrier membrane protein family: structure and membrane topology

Secretory carrier membrane proteins (SCAMPs) are integral membrane proteins found in secretory and endocytic carriers implicated to function in membrane trafficking. Using expressed sequence tag database and library screens and DNA sequencing, we have characterized several new SCAMPs spanning the plant and animal kingdoms and have defined a broadly conserved protein family. No obvious fungal homologue has been identified, however. We have found that SCAMPs share several structural motifs. These include NPF repeats, a leucine heptad repeat enriched in charged residues, and a proline-rich SH3-like and/or WW domain-binding site in the N-terminal domain, which is followed by a membrane core containing four putative transmembrane spans and three amphiphilic segments that are the most highly conserved structural elements. All SCAMPs are 32-38 kDa except mammalian SCAMP4, which is approximately 25 kDa and lacks most of the N-terminal hydrophilic domain of other SCAMPs. SCAMP4 is authentic as determined by Northern and Western blotting, suggesting that this portion of the larger SCAMPs encodes the functional domain. Focusing on SCAMP1, we have characterized its structure further by limited proteolysis and Western blotting with the use of isolated secretory granules as a uniformly oriented source of antigen and by topology mapping through expression of alkaline phosphatase gene fusions in Escherichia coli. Results show that SCAMP1 is degraded sequentially from the N terminus and then the C terminus, yielding an approximately 20-kDa membrane core that contains four transmembrane spans. Using synthetic peptides corresponding to the three conserved amphiphilic segments of the membrane core, we have demonstrated their binding to phospholipid membranes and shown by circular dichroism spectroscopy that the central amphiphilic segment linking transmembrane spans 2 and 3 is alpha-helical. In the intact protein, these segments are likely to reside in the cytoplasm-facing membrane interface. The current model of SCAMP1 suggests that the N and C termini form the cytoplasmic surface of the protein overlying a membrane core, which contains a functional domain located at the cytoplasmic interface with little exposure of the protein on the ectodomain.     

mGrid: A load-balanced distributed computing environment for the remote execution of the user-defined Matlab code

Background  

Matlab, a powerful and productive language that allows for rapid prototyping, modeling and simulation, is widely used in computational biology. Modeling and simulation of large biological systems often require more computational resources then are available on a single computer. Existing distributed computing environments like the Distributed Computing Toolbox, MatlabMPI, Matlab*G and others allow for the remote (and possibly parallel) execution of Matlab commands with varying support for features like an easy-to-use application programming interface, load-balanced utilization of resources, extensibility over the wide area network, and minimal system administration skill requirements. However, all of these environments require some level of access to participating machines to manually distribute the user-defined libraries that the remote call may invoke.