DIMACS Workshop on Complexity in Biosystems: Innovative Approaches at the Interface of Experimental and Computational Modeling

April 8 - 10, 2002
DIMACS Center, CoRE Building, Rutgers University, Piscataway, NJ

Thomas Deisboeck, Harvard Medical School, deisboec@helix.mgh.harvard.edu
Lee Segel, Weizmann Institute, lee@wisdom.weizmann.ac.il
Eduardo Sontag, Rutgers University, sontag@gauss.rutgers.edu
Raimond Winslow, The Johns Hopkins University, rwinslow@bme.jhu.edu
Presented under the auspices of the Special Year on Computational Molecular Biology.


Albert-Laszlo Barabasi (University of Notre-Dame)

Title: "The Architecture of Complexity: From the Topology of the World Wide Web to the Cell's Protein and Metabolic Network"

Abstract: Networks with complex topology describe systems as diverse as the cell or the World Wide Web. The emergence of these networks is driven by self-organizing processes that are governed by simple but generic laws. The analysis of the metabolic and protein network of various organisms shows that cells and complex man-made networks, such as the Internet or the world wide web, share the same large-scale topology. Uncovering these organizing principles, and exploring their biological consequences is among the major goals of post-genomic biology. I will show that the scale-free topology of these complex webs have important consequences on their robustness against failures and attacks, with implications on drug design and our ability to understand the functional role of genes in model organisms. For further information and papers, see http://www.nd.edu/~networks

J. Cassatt, NIH (NIGMS)

Title: "NIH Funding at the Interface"

For the last half of the twentieth century, biology has focused on the reductionist approach-break the cell down to its smallest functional level and study that level in exquisite detail-with the expectation that this information could be compiled and the cell reconstructed from its component parts. The former approach has been enormously successful. We have a good understanding of basic biological processes, like transcription and translation, have used structures of these components to design drugs used, for example against AIDS, and can even visualize these processes molecule by molecule. The challenge for the twenty-first century is to take these parts and actually do the hard work of reconstructing the cell. Meeting this challenge will require expertise outside of the biologically oriented disciplines, such as engineering, mathematics, and computer science. The challenge to the NIH is the design of research and training programs targeted at the boundaries of these disciplines and biology. These programs will be discussed.

James J. Collins (Boston University)

Title: "Designer Gene Networks"

Abstract: Many fundamental cellular processes are governed by genetic programs, which employ protein-DNA interactions in regulating function. Owing to recent technological advances, it is now possible to design synthetic gene regulatory networks, and the stage is set for the notion of engineered cellular control at the DNA level. Theoretically, the biochemistry of the feedback loops associated with protein-DNA interactions often leads to nonlinear equations, and the tools of nonlinear analysis become invaluable. In this talk, we describe how techniques from nonlinear dynamics and molecular biology can be utilized to model, design and construct synthetic gene regulatory networks. We present examples in which we integrate the development of a theoretical model with the construction of an experimental system. We also discuss the implications of synthetic gene regulatory networks for gene therapy, biotechnology, biocomputing and nanotechnology.

Thomas S. Deisboeck (Massachusetts General Hospital, Harvard Medical School)

Title: "Modeling Malignant Brain Tumors as Complex Dynamic BioSystems"

Abstract: There is growing evidence that malignant tumors indeed behave a self-organizing and adaptive multicellular systems rather than as unorganized cell masses. To investigate this paradigm-shifting hypothesis we employ an interdisciplinary approach combining cancer research, biomedical imaging, statistical physics, mathematical biology, materials science, computational and complex systems science. Findings from novel in vitro settings are presented in the context of innovative computational models, using techniques from cellular automata to agent-based modeling. Implications for future biomedical research and clinical concepts are discussed.

Ary L. Goldberger (Beth Israel Deaconess Medical Center, Harvard Medical School)

Title: "Nonlinear Dynamics, Chaos, and Complexity in Bedside Medicine"

Abstract: According to conventional physiologic principles, healthy systems are self-regulated to reduce variability and restore constancy. However, contrary to the predictions of homeostasis, under healthy conditions, many physiologic signals, such as the normal human heartbeat, fluctuate in a complex manner, even under resting conditions. Quantitative analysis using techniques adapted from statistical physics and nonlinear dynamics reveals the presence of long-range power-law correlations extending over thousands of heartbeats. This scale-invariant (fractal) behavior suggests that the regulatory systems generating these fluctuations may be operating far from equilibrium. In contrast, for subjects at high risk of sudden death, this fractal organization breaks down. Physiologic aging is associated with more subtle alterations in fractal correlations. Application of fractal scaling analysis and related techniques provides new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as monitoring the aging process and the effects of interventions designed to maintain or restore healthy function in a wide range of disorders. Open-source data and software to facilitate a wide range of studies on typically nonlinear, nonstationary signals in basic physiology and bedside medicine are now available via PhysioNet, the NIH/NCRR Research Resource for Complex Physiologic Signals (www.physionet.org).

Leroy Hood (Institute for Systems Biology)

Title: "Integrative Systems Biology: Genomics, Proteomics, and Computation"

Abstract: The Human Genome Project has altered the view and practice of biology and has led to several paradigm changes--systems biology, and predictive and preventive medicine. I will discuss these changes and consider the analysis of two biological systems: galactose metabolism in yeast, and sea urchin development, using integrative systems approaches.

Donald E. Ingber (Children's Hospital, Harvard Medical School)

Title: "Structural Complexity and Cellular Information Processing in Living Cells"

Abstract: Exploration of the mechanism by which cells sense and respond to mechanical forces has led to the discovery that cells control their shape, biochemistry, and gene expression through use of a tension-dependent architectural system from the Buckminster Fuller world of geodesic architecture, known as "Tensegrity". This presentation will review this work and show that tensegrity governs how cytoskeletal networks are mechanically stabilized and integrated with solid-state biochemistry involved in signal transduction to provide mechanisms for integrating structure and function in living cells. This work emphasizes the importance of taking into account structural and mechanical aspects of highly complex, hierarchical, network systems when trying to model how they form and function.

Lewis Lipsitz (Harvard Medical School)

Title: "Loss of Complexity with Aging: The Physiologic Basis of Frailty"

Abstract: Under basal resting conditions most healthy physiologic systems demonstrate highly irregular, complex dynamics that represent interacting regulatory processes operating over multiple time scales. These processes prime the organism for an adaptive response, making it ready and able to react to sudden physiologic stresses. Aging and disease are associated with a loss of complexity in the dynamics of a variety of systems, and consequently lead to functional decline and frailty once an individual's adaptive capacity is compromised. Nonlinear mathematical techniques that quantify physiologic dynamics may predict the onset of frailty, and interventions aimed toward restoring healthy dynamics may prevent functional decline.

Alan S. Perelson (Los Alamos National Laboratory)

Title: "Modeling T Lymphocyte Dynamics"

Abstract: HIV infection is characterized by the progressive loss of CD4+ T lymphocytes. To understand the nature of this loss, we and others have developed dynamic models and undertaken varying labeling studies in both humans and monkeys aimed at providing quantitative information about T lymphocyte dynamics in both health and during HIV infection. A review of this work will be presented.

Scott Rifkin (Yale University)

Title: "Structure of Gene Expression"

As early as the 1940s, C.H. Waddington and M. Delbruck speculated on a dynamical nature of molecular interactions, especially about whether the entire genome is strongly coupled or compartmentalized and whether the molecular dynamics traverses a sequence of stable internal states. Unfortunately, the number of measurements required to characterize the biochemistry of a cell made any empirical explorations of these ideas unfeasible. These yet unanswered questions have important implications for how we understand the cell as a coherent system in both development and evolution.

Large-scale gene expression analyses, while not characterizing all of the relevant variables in the cell, now enable us to make reasonable approximations to the states of cells under certain conditions. Many approaches to this data focus on building graphical models, genetic networks, consisting at first solely of connections between genes and eventually of some dynamics over them. We can also, however, take a more systems oriented approach and try to identify constraints on the structure of molecular interactions which any eventual network dynamics would have to obey. Understanding these constraints will be an important step in investigating the stability of genomic interactions. I will illustrate this structural approach using data from yeast physiology and Drosophila evolution.

John Rinzel (New York University)

Title: "Modeling Spontaneous Rhythms in Developing Spinal Cord"

Abstract: Many developing circuits show spontaneous oscillations. We study models for the very slow burst-like population rhythms seen in chick embryonic spinal cord. We use mean field and cell-based models for the population activity in a recurrent network of excitatory-coupled cells. Rhythmogenesis appears to involve coupling mechanisms, e.g. synaptic depression, rather than intrinsically oscillating cells with coupling involved only for synchronization.

Lee A. Segel (Weizmann Institute)

Title: "Distributed Feedbacks toward Multiple Conflicting Goals in the Immune System"

Abstract: Evidence for the following scenario will be presented. It is useful to regard the immune system as having short term goals -- which are overlapping and even contradictory. Sensors monitor progress toward the goals. Information from sensor readings is broadcast to the system via "vectors" of signaling chemicals (cytokines). Sensors drive "distributed feedbacks" that (i) improve the performance of a given type of effector cell, (ii) cause the preferential amplification of more potent effectors, and thus, more generally, (iii) in some sense improve goal achievement. Comparison will be made with other autonomous decentralized systems, notably the metabolic system.

Stanislav Y. Shvartsman (Princeton University) and Cyrill B. Muratov (NJIT)

Title: "Modeling Cell Communication in Drosophila Oogenesis"

Abstract: Autocrine signaling through the Epidermal Growth Factor Receptor (EGFR) is highly conserved across species and operates at various stages of development, patterning the developing tissues and organs. A recent hypothesis suggested that a distributed network of positive and negative EGFR autocrine feedback loops in Drosophila oogenesis is capable of spatially modulating a simple single-peaked input into a more complex two-peaked signaling pattern, specifying the formation of a pair organ (a pair of respiratory appendages). To test this hypothesis, we have integrated genetic and biochemical information about the EGFR network into a mechanistic model of transport and signaling. We use the model to estimate the spatial ranges and the times scales of the relevant feedback loops, to interpret the phenotypic transitions in eggshell morphology, and to predict the effects of new genetic manipulations.

Greg Stephanopoulos (MIT)

Title: "Linking Genomics to Function via Metabolic Phenotyping"

Elucidation of biological function requires holistic approaches that make use of extensive sets of data about important classes of intracellular molecules. mRNA transcript levels is one such set containing information about the transcriptional state of the cell. This set, however, is not self sufficient and needs to be complemented with other data, such as data about cell physiology. This presentation will describe approaches for the generation of measurements of the cellular physiological state along with methods for linking expression data to function.

Raimond L. Winslow and Joseph L. Greenstein (The Johns Hopkins University School of Medicine)

Title: "An Integrative Model of the Cardiac Ventricular Myocyte Incorporating Local-Control of JSR Ca2+ Release"

All integrative models of the myocyte developed to date are of a type known as "common pool" models (Stern, Biophys. J. 63: 497). In such models, Ca2+ flux through L-type Ca2+ channels (LCCs) and ryanodine sensitive Ca2+ release channels (RyRs) in the junctional sarcoplasmic reticulum (JSR) membrane is directed into a common Ca2+ compartment. Ca2+ within this common pool also serves as activator Ca2+ triggering JSR Ca2+ release. Stern has demonstrated that common pool models are structurally unstable, exhibiting all-or-none Ca2+ release except (possibly) over some narrow range of model parameters. Despite this inability to reproduce experimentally measured properties of graded JSR Ca2+ release, common pool models have been very successful in reproducing and predicting a range of myocyte behaviors. This includes properties of interval-force relationships that depend heavily on intracellular Ca2+ uptake and release mechanisms (Rice et al. Am. J. Physiol. 278: H913). Given these findings, one may wonder whether or not it is important to incorporate an accurate biophysical description of graded JSR Ca2+ release in computational models of the cardiac myocyte.

Stern went on to propose the "local-control" theory of Ca2+ release. In this theory, individual LCCs, the set of RyR with which they communicate, and the subspace within which they communicate, defines a functional release unit (FRU). Local control theory holds that while Ca2+ release within each FRU may be all or none, the averaged behavior of many independent FRUs reflects the probability of opening of LCCs. We have previously developed a model of the functional release unit (FRU) consisting of one LCC, eight RyR, and the volume in which they are enclosed (Biophys J 77:1871-84). To study the impact of local Ca2+ control in the context of the whole cell AP, we have developed a new class of ventricular cell model which combines the stochastic simulation of a large number of independent FRUs with the solution of a system of coupled ordinary differential equations describing the full complement of cardiac membrane currents and intracellular fluxes. We will describe development of this local-control myocyte model, and numerical methods used for efficient simulation of model properties. We will demonstrate that this model exhibits the graded release property, as well as a voltage-dependent EC coupling gain function which agrees well with experimental data. Further, we will show that the graded release property determines fundamental properties of the cardiac action potential.

(Supported by NIH HL60133, the NIH Specialized Center of Research on Sudden Cardiac Death P50 HL52307, the Whitaker Foundation, the Falk Medical Trust, and IBM Corporation)