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Complex Systems Biology @ Case Status and a Vision for the Future ComplexComplex SystemsSystems BiologyBiology SessionSession atat ICSBICSB 20062006 YokohomaYokohoma JapanJapan Kwang-Hyun Cho Sree N. Sreenath Director, Systems Biology Lab Director, Case Complex Systems Biology Center College of Medicine & Bio-MAX Case Western Reserve University, Institute, Seoul National University, Cleveland OHIO, USA Korea Case Complex ICSBICSBICSB 200620062006 Systems Biology YokohomaYokohomaYokohoma,,, JapanJapanJapan Center ComplexityComplexity andand SystemsSystems BiologyBiology “What is the difference between a live cat and a dead one? One scientific answer is systems biology. A live cat is the emergent behavior of the system incorporating those parts.” - Editorial, Nature, May 2005. What is Complex Systems Biology? DEFINITION: Applying “Complex Systems” knowledge to understanding biological problems. ComplexComplexSystems Systems Systems Biology Discovery of organizing principles Hierarchical systems, Bounded autonomy of levels, (Biological emergence, dynamics Uncertainty Principle) (chaos, equilibria), etc. Interaction Balance Principle: coordination of multi-level behavior Focus on “vertical” interaction (between levels) Goes beyond emergence Integration of data-driven modeling (e.g., Laufenberger's) with rigorous mathematical modeling (e.g., Cho, Doyle, Klipp, Tyson ,Wolkenhauer). Biological Processes Variance A. In Time Illustration of how a signal is relayed Process time constants example(adapted from through sequential activation of proteins Fell D., Understanding the Control of in the Ras/Raf/MEK/REK pathway. Metabolism, Portland Press, 1997). B. In Space Hierarchical, multi-level representation example Tumor Tissue Faster Spatial Reaction size Cellular Time increase Nucleus Other Intra-Cellular (R)Evolutionary View of Systems Biology MODULARIZATION Step 1 Step 2 * * * * * ** * * * * * * * ** * * Biological Network Systems Biology System Dynamics Data and Connectivity, clustering, Dynamics - evolution in topology time, feedback, Knowledge Search for drug targets in homeostasis the entire network using (resistance to change) Complex Systems ad hoc methods such as /adaptation, etc. Biology deletion experiments and Search for therapeutics Paradigm of Organized randomized searches. (devices, drug targets, Complexity Bioinformatics etc.) guided by Search for organizing biological principles principles Chemical Engineering Search for therapeutics and Bioengineering (devices, drug targets, etc.) guided by organizing principles HistoryHistory ofof SystemsSystems BiologyBiology - According to Wolkenhauer, Kitano & Cho, IEEE Control Sys. Mag., pp 38-48,Aug 2003. “Systems Biology” - Origin of Concept in Proc. Intl. Symposium at Case in 1968. - Mihajlo Mesarovic Complex Systems Biology - ICSB, October 11, 2006 (9:15-10:30) Session organizers: Peter Wellstead, Kwang-Hyun Cho and Sree N. Sreenath Chairs: Kwang-Hyun Cho (Seoul National Univ.), Sree N. Sreenath (Case Western Univ.) Mihajlo D. Mesarovic (Case Western Reserve University) "Interaction Balance Coord as Org. Principle in Complex Systems Biology" Jack Donald Keene (Duke University Medical Center) "Coordination of Gene Expression by RNA Operons" Kenneth Alan Loparo (Case Western Reserve University) "Applications of Complex Systems Biology to the Study of Neural Systems " Interaction Balance Coordination as Organizing Principle in Complex Systems Biology Mihajlo Mesarovic, Sree N. Sreenath and Girish Balakrishnan Complex Systems Biology Center Case Western Reserve University Cleveland, Ohio, U.S.A Case Complex Systems Biology Center AGENDA o Complex Systems Biology o Biological Complexity o Conceptual Framework oCoordination o Higher Level Regulatory Function o Motifs in Complex Systems Biology o Mathematical General Systems Theory Proof of Universality of IBCP Systems Biologies 1. Mathematical Systems Biology Dynamic Systems and Control Theory Motivation Homeostasis: Cannon Cybernetics: Control and Information in Human /Animal, Nobert Wiener 2. Computational Biology Data based modeling using computer algorithms “Systems biology is a scientific discipline that endeavors to quantify all of the molecular elements of a biological system to assess their interaction into graphical network models that serve as predictive hypothesis to explain emergent behavior.” [1] - Leroy Hood, 2005 Systems Biologies (contd.) Complex Systems Biology Multilevel, Hierarchical, Systems Theory (Mesarovic and Takahara, 1976 [2] ) Motivation “Connecting different levels-from molecules through module to organisms is essential for an understanding of biology.” [3] - Leyland Hartwell, 1999. “… epigenetic cell-cell and extracellular influences are pivotal in tumor progression beyond genetic mutation.” [4] -Judah Folkman, 2006. “Progress in biology benefits greatly from technology but ultimately the more fundamental changes will be conceptual.” [5] - Douglas Hanahan and Robert A. Weinberg, 2000 On Complex Systems Biology Complex Systems Paradigm • Complex system is a relation on systems (i.e., a system of systems) •Minimum two levels - Individual levels follow their own laws •Organizing principles govern System structure and function Complex Systems Biology •Objective: To advance understanding of biological complexity. •Through search for organizing principles (our research) •Organizing principles in biology are akin to the natural laws in physics. • Complexity - function of regulatory multilevel, hierarchical, organization. •Coordination • Higher level regulatory/decision function. • Implemented by organizing principles •Such as Interaction Balance Coordination Principle. Biological Complexity Paradigm of control – feedback or otherwise – is insufficient to address the problem of complexity in biology as demonstrated in eukaryotes •99% of the human proteins have recognizable equivalent in mice. • Relation between the amount of nonprotein-coding DNA sequences and organism complexity is more consistent [6]. • Protein coding genes are 2%< of human genome. •Noncoding genes (introns and transposons) • Perform regulation function governing organized complexity of eukaryotes [6]. UNICELLULAR LIFE, primarily prokaryotes, ruled the earth for billions of years. When multicellular life appeared, however, its complexity rose with dizzying speed. The evolution of an additional genetic regulatory system might explain both the jump to multicellularity and the rapid diversification into complexity. [6] Coordination: Higher Level Regulatory Function Coordination •An organizing principle in a complex system. •A higher level decision function. •Influence subsystems to achieve goal (desired behavior) of the overall system • Coordination is distinct from control. •Control: A “directive/order” to achieve certain objectives/goals in spite of variability. •Objective of coordination is not to control but to harmonize •Influence/motivate interacting subsystems (with distinct functions) to advances overall system objective •Modules have to be coordinated to produces required cell functions. Coordination (contd.) Coordination is a generic concept •Similar to feedback (an organizing principle for homeostasis) •Feedback - all levels of the human body’s hierarchy, from genome to brain functions and the whole body. Perform. regulatory/control functions. •Implemented in different circumstances by specific coordination principles. •Coordination Principles • ”Laws" (logic) of coordination as implemented in specific situations. •Interaction Balance Coordination Coordination Principle (IBCP) •Has been proved to have the broadest application in: •Environmental studies, Management, Global issues, Engineering, etc Appears to be promising for biology. METHODOLOGY Hierarchical Systems Theory Interaction Balance Coordination Principle (IBCP) In a complex system, S(Δ) functioning of a S0(Δ0) subsystem Coordination depends on the interactions with ε1 ε2 other subsystems. c1 c2 u1d + + u2d IBCP then states: The overall system is S1(Δ) coordinated/- u21a S2(Δ) harmonized if the Control Control actual and desired u12a interactions for each and every subsystem y y1 2 are balanced, i.e., Process Process uija -uijd ≤ εj x1 x2 x1, x2: inputs u12a, u21a: actual interaction y1, y2: outputs u12d, u21d: desired interaction ε1, ε2: imbalance c1, c2: coordination action Interaction Balance Coordination Principle, IBCP Objective of coordination •Influence subsystems In a perturbed state for overall system state to be near original quiescent state but within a harmonious domain of the overall systems behavior. •In quiescent state: interactions are considered as balanced. •In perturbed state: objective of coordination by IBCP is to influence the subsystems so that interaction balance is restored as required under newly perturbed conditions; •i.e. “desired” and actual interactions are balanced. •IBCP can be implemented by either • endogenous adaptation of the subsystems •a distributed process. METHODOLOGY Hierarchical Systems Theory Coordination In a multilevel, hierarchical system the task of the higher-level is not to control but to coordinate/harmonize the functioning of the lower subsystems which are pursuing their own objectives so as to meet the requirement of the overall system. Robustness Resources The overall system objective Blue dots indicate states has been violated and a shift Coordination of subsystems; the overall is implemented by the coordination system objective (blue circle) by shifting blue circle to red circle. is being satisfied. Coordination The subsystem has received a new is indicated by blue lines.
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