Short-term information processing, long-term responses: Insights by mathematical modeling of signal transduction. Early activation dynamics of key signaling mediators can be predictive for cell fate decisions

How do cells interpret information from their environment and translate it into specific cell fate decisions? We propose that cell fate is already encoded in early signaling events and thus can be predicted from defined signal properties. Specifically, we hypothesize that the time integral of activated key signaling molecules can be correlated to cellular behavior such as proliferation or differentiation. The identification of these decisive key signal mediators and their connection to cell fate is facilitated by mathematical modeling. A possible mechanistic linkage between signaling dynamics and cellular function is the directed control of gene regulatory networks by defined signals. Targeted experiments in combination with mathematical modeling can increase our understanding of how cells process information and realize distinct cell fates.     

The Virtual Cell: a software environment for computational cell biology

The newly emerging field of computational cell biology requires software tools that address the needs of a broad community of scientists. Cell biological processes are controlled by an interacting set of biochemical and electrophysiological events that are distributed within complex cellular structures. Computational modeling is familiar to researchers in fields such as molecular structure, neurobiology and metabolic pathway engineering, and is rapidly emerging in the area of gene expression. Although some of these established modeling approaches can be adapted to address problems of interest to cell biologists, relatively few software development efforts have been directed at the field as a whole. The Virtual Cell is a computational environment designed for cell biologists as well as for mathematical biologists and bioengineers. It serves to aid the construction of cell biological models and the generation of simulations from them. The system enables the formulation of both compartmental and spatial models, the latter with either idealized or experimentally derived geometries of one, two or three dimensions.     

ALES: cell lineage analysis and mapping of developmental events

MOTIVATION: Animals build their bodies by altering the fates of cells. The way in which they do so is reflected in the topology of cell lineages and the fates of terminal cells. Cell lineages should, therefore, contain information about the molecular events that determined them. Here we introduce new tools for visualizing, manipulating, and extracting the information contained in cell lineages. Our tools enable us to analyze very large cell lineages, where previously analyses have only been carried out on cell lineages no larger than a few dozen cells. RESULTS: Ales (A Lineage Evaluation System) allows the display, evaluation and comparison of cell lineages with the aim of identifying molecular and cellular events underlying development. Ales introduces a series of algorithms that locate putative developmental events. The distribution of these predicted events can then be compared to gene expression patterns or other cellular characteristics. In addition, artificial lineages can be generated, or existing lineages modified, according to a range of models, in order to test hypotheses about lineage evolution. AVAILABILITY: The program can run on any operating system with a compliant Java 2 environment. Ales is free for academic use and can be downloaded from http://mbi.dkfz-heidelberg.de/mbi/research/cellsim/ales.     

Modular modeling of cellular systems with ProMoT/Diva

MOTIVATION: Need for software to setup and analyze complex mathematical models for cellular systems in a modular way, that also integrates the experimental environment of the cells. RESULTS: A computer framework is described which allows the building of modularly structured models using an abstract, modular and general modeling methodology. With this methodology, reusable modeling entities are introduced which lead to the development of a modeling library within the modeling tool ProMot. The simulation environment Diva is used for numerical analysis and parameter identification of the models. The simulation environment provides a number of tools and algorithms to simulate and analyze complex biochemical networks. The described tools are the first steps towards an integrated computer-based modeling, simulation and visualization environment Availability: Available on request to the authors. The software itself is free for scientific purposes but requires commercial libraries. SUPPLEMENTARY INFORMATION: http://www.mpi-magdeburg.mpg.de/projects/promot     

Robust polarity establishment occurs via an endocytosis-based cortical corralling mechanism

Formation of a stable polarity axis underlies numerous biological processes. Here, using high-resolution imaging and complementary mathematical modeling we find that cell polarity can be established via the spatial coordination of opposing membrane trafficking activities: endocytosis and exocytosis. During polarity establishment in budding yeast, these antagonistic processes become apposed. Endocytic vesicles corral a central exocytic zone, tightening it to a vertex that establishes the polarity axis for the ensuing cell cycle. Concomitantly, the endocytic system reaches an equilibrium where internalization events occur at a constant frequency. Endocytic mutants that failed to initiate periodic internalization events within the corral displayed wide, unstable polarity axes. These results, predicted by in silico modeling and verified by high resolution in vivo studies, identify a requirement for endocytic corralling during robust polarity establishment.     

Cellular-based modeling of oscillatory dynamics in brain networks

Oscillatory, population activities have long been known to occur in our brains during different behavioral states. We know that many different cell types exist and that they contribute in distinct ways to the generation of these activities. I review recent papers that involve cellular-based models of brain networks, most of which include theta, gamma and sharp wave-ripple activities. To help organize the modeling work, I present it from a perspective of three different types of cellular-based modeling: 'Generic', 'Biophysical' and 'Linking'. Cellular-based modeling is taken to encompass the four features of experiment, model development, theory/analyses, and model usage/computation. The three modeling types are shown to include these features and interactions in different ways.     

Modeling regulatory networks at Virginia Tech

The life of a cell is governed by the physicochemical properties of a complex network of interacting macromolecules (primarily genes and proteins). Hence, a full scientific understanding of and rational engineering approach to cell physiology require accurate mathematical models of the spatial and temporal dynamics of these macromolecular assemblies, especially the networks involved in integrating signals and regulating cellular responses. The Virginia Tech Consortium is involved in three specific goals of DARPA's computational biology program (Bio-COMP): to create effective software tools for modeling gene-protein-metabolite networks, to employ these tools in creating a new generation of realistic models, and to test and refine these models by well-conceived experimental studies. The special emphasis of this group is to understand the mechanisms of cell cycle control in eukaryotes (yeast cells and frog eggs). The software tools developed at Virginia Tech are designed to meet general requirements of modeling regulatory networks and are collected in a problem-solving environment called JigCell.     

Localised interventions in cellular processes

The once linear view of cell regulatory processes is now changing as we begin to overlay spatial and temporal characteristics onto signalling pathways and dynamic membranous events. To better understand the properties of these spatially restricted processes we must refine our targeting of these events with acute localised manipulations. We review here the diverse application of a dimerisation system, which exploits immunosuppressor/immunophilin biology to provide a route to drug-inducible subdomain interventions. This article is part of a Special Issue entitled: Inhibitors of Protein Kinases (2012).     

The deformation behavior and viscoelastic properties of chondrocytes in articular cartilage

Chondrocytes in articular cartilage utilize mechanical signals in conjunction with other environmental factors to regulate their metabolic activity. However, the sequence of biomechanical and biochemical events involved in the process of mechanical signal transduction has not been fully deciphered. A fundamental step in determining the role of various factors in regulating chondrocyte activity is to characterize accurately the biophysical environment within the tissue under physiological conditions of mechanical loading. Microscopic imaging studies have revealed that chondrocytes as well as their nuclei undergo shape and volume changes in a coordinated manner with deformation of the tissue matrix. Through micromechanical experiments, it has been shown that the chondrocyte behaves as a viscoelastic solid material with a mechanical stiffness that is several orders of magnitude lower than that of the cartilage extracellular matrix. These properties seem to be due to the structure of the chondrocyte cytoskeleton, and in part, the viscoelastic properties of the cell nucleus. The mechanical properties of the pericellular matrix that immediately surrounds the chondrocyte significantly differ from those of the chondrocyte and the extracellular matrix, suggesting that the pericellular matrix plays an important role in defining the mechanical environment of the chondrocyte. These experimentally measured values for chondrocyte and cartilage mechanical properties have been used in combination with theoretical constitutive modeling of the chondrocyte within articular cartilage to predict the non-uniform and time-varying stress-strain and fluid flow environment of the cell. The ultimate goal of these studies has been to elucidate the sequence of biomechanical and biochemical events through which mechanical stress influences chondrocyte activity in both health and in disease.     

What is the minimum number of dedicated functions required for a basic cell cycle?

The genome of Escherichia coli has a coding capacity for about 4500 proteins but only a small number of these appear to be specific for the periodic events (initiation of DNA replication, chromosome partitioning and cell division) that punctuate the cell-duplication cycle: furthermore, many of these cell cycle dedicated functions are dispensible under certain conditions, although their presence undoubtedly increases the fitness of the organism to survive in a competitive environment. A simplified but effective cell replication cycle can probably operate with only a few cycle-dedicated proteins, in addition to those required for cell growth itself.     

Combined experimental and computational analysis of DNA damage signaling reveals context‐dependent roles for Erk in apoptosis and G1/S arrest after genotoxic stress

Following DNA damage, cells display complex multi‐pathway signaling dynamics that connect cell‐cycle arrest and DNA repair in G1, S, or G2/M phase with phenotypic fate decisions made between survival, cell‐cycle re‐entry and proliferation, permanent cell‐cycle arrest, or cell death. How these phenotypic fate decisions are determined remains poorly understood, but must derive from integrating genotoxic stress signals together with inputs from the local microenvironment. To investigate this in a systematic manner, we undertook a quantitative time‐resolved cell signaling and phenotypic response study in U2OS cells receiving doxorubicin‐induced DNA damage in the presence or absence of TNFα co‐treatment; we measured key nodes in a broad set of DNA damage signal transduction pathways along with apoptotic death and cell‐cycle regulatory responses. Two relational modeling approaches were then used to identify network‐level relationships between signals and cell phenotypic events: a partial least squares regression approach and a complementary new technique which we term ‘time‐interval stepwise regression.’ Taken together, the results from these analysis methods revealed complex, cytokine‐modulated inter‐relationships among multiple signaling pathways following DNA damage, and identified an unexpected context‐dependent role for Erk in both G1/S arrest and apoptotic cell death following treatment with this commonly used clinical chemotherapeutic drug.     

The statistical dynamics of recurrent biological events

In this paper we develop a general modeling framework within which many models for systems which produce events at irregular times through a combination of probabilistic and deterministic dynamics can be comprehended. We state and prove new sufficient conditions for the global asymptotic behaviour of the density evolution in these systems, and apply our results to many previously published models for the cell division cycle. In addition, we develop a new interpretation for the statistics of action potential production in excitable cells.To whom correspondence should be sent     

Hybrid mathematical model of glioma progression

Objectives:  Gliomas are an important form of brain cancer, with high mortality rate. Mathematical models are often used to understand and predict their behaviour. However, using current modeling techniques one must choose between simulating individual cell behaviour and modeling tumours of clinically significant size.
Materials and Methods:  We propose a hybrid compartment-continuum-discrete model to simulate glioma growth and malignant cell invasion. The discrete portion of the model is capable of capturing intercellular interactions, including cell migration, intercellular communication, spatial cell population heterogeneity, phenotype differentiation, epigenetic events, proliferation, and apoptosis. Combining this with a compartment and continuum model allows clinically significant tumour sizes to be evaluated.
Results and Conclusions:  This model is used to perform multiple simulations to determine sensitivity to changes in important model parameters, specifically, the fundamental length parameter, necrotic cell degradation rate, rate of cell migration, and rate of phenotype transformation. Using these values, the model is able to simulate tumour growth and invasion behaviour, observed clinically. This mathematical model provides a means to simulate various tumour development scenarios, which may lead to a better understanding of how altering fundamental parameters can influence neoplastic progression.     

SwarnSeq: An improved statistical approach for differential expression analysis of single-cell RNA-seq data

Single-cell RNA sequencing (scRNA-seq) is a powerful technology that is capable of generating gene expression data at the resolution of individual cell. The scRNA-seq data is characterized by the presence of dropout events, which severely bias the results if they remain unaddressed. There are limited Differential Expression (DE) approaches which consider the biological processes, which lead to dropout events, in the modeling process. So, we develop, SwarnSeq, an improved method for DE, and other downstream analysis that considers the molecular capture process in scRNA-seq data modeling. The performance of the proposed method is benchmarked with 11 existing methods on 10 different real scRNA-seq datasets under three comparison settings. We demonstrate that SwarnSeq method has improved performance over the 11 existing methods. This improvement is consistently observed across several public scRNA-seq datasets generated using different scRNA-seq protocols. The external spike-ins data can be used in the SwarnSeq method to enhance its performance.Availability and implementationThe method is implemented as a publicly available R package available at https://github.com/sam-uofl/SwarnSeq.     

Second international conference on F-BAR proteins

Architectural beauty attracts many travelers to Europe. The participants of this conference were also attracted by architectural beauty, however the focus in our case was on the architectural beauty of the living cell. The living cell is not only an architectural masterpiece, but possesses fluidity and dynamism even the most gifted artisans would have found impossible to represent in stone. The architectural beauty of the living cell is created by a complex interplay between lipid bilayer membranes and the proteins that lie underneath them at the cortex. The architecture of the living cell is extraordinarily responsive to changes that occur within cells (intrinsic events) and in the extracellular environment (extrinsic events). Complex and interwoven signaling pathways link the intrinsic and extrinsic events to changes in cell shape and behavior and those that have been identified and studied probably represent only a minority. What has become apparent, however, is the central and unique role of a group of phospholipid-binding and signaling proteins in these various pathways: the BAR, F-BAR and I-BAR domain proteins.     

Imaging single events at the cell membrane

The ability to sense and respond to the environment is a hallmark of living systems. These processes occur at the levels of the organism, cells and individual molecules. Sensing of extracellular changes could result in a structural or chemical alteration in a molecule, which could in turn trigger a cascade of intracellular signals or regulated trafficking of molecules at the cell surface. These and other such processes allow cells to sense and respond to environmental changes. Often, these changes and the responses to them are spatially and/or temporally localized, and visualization of such events necessitates the use of high-resolution imaging approaches. Here we discuss optical imaging approaches and tools for imaging individual events at the cell surface with improved speed and resolution.     

Culture strategies for maturation of carnivore oocytes

In vitro maturation (IVM) of carnivore oocytes is still under investigation. It is well known that oocytes must accomplish nuclear and cytoplasmic maturation to acquire developmental competence. However, little is known about mechanisms regulating these events in carnivore oocytes. Consequently, IVM rates are still lower than those obtained in other species. To improve results in carnivores, two strategies have to be investigated: one finalized towards preserving in vitro functional integrity and potentiality to accomplish complete maturation of cumulus-oocyte complexes (COCs), the other finalized towards providing culture conditions adequate for sustaining complete maturation of these oocytes. Thus, modifications of the culture environment during IVM, by addition of substances that stimulate endogenous systems of cell defence and modulate the intracellular levels of regulatory molecules, or by use of sequentially different culture systems, are interesting strategies for enhancing viability and competence in terms of complete maturation of carnivore oocytes. This review is focused on recent advances in the study of these aspects developed in feline and/or canine oocytes.