2. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Designing and Constructing a Set of Fundamental Cell Models: Application to Cardiac Disease James B.Bassingthwaighte University of Washington Seattle

3. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Engineering and reverse engineering the route from Genome to Function: (Integrating Biological Systems Knowledge) Genes Health Organism Organ Tissue Cell Molecule The Physiome Project http://www.physiome.org Structure and Function: Biomedical Problem Formulation Quantitative Approaches Engineering Methods Mechanistic System Modeling Databasing & Dissemination

4. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 The Physiome and the Physiome Project The “Physiome”, like the Genome, is a quantitative description of the functional behavior of the physiological state of an individual of a species. In its fullest form it should define relationships from organism to genome and vice versa. The “Physiome Project” is a concerted effort to define the Physiome through databasing and through the development of a sequence of model types: schema of interactions, descriptions of structure and function, logical prediction, and integrative quantitative modeling for critical projections.

5. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Physiome and Physiome Project The models of genomic, metabolic, or integrative systems should, via iteration with carefully designed experiments, resolve contradictions amongst prior observations and interpretations. Reasonably comprehensive and accurate models will demonstrate emergent properties. This is the “reverse engineering” of biology. Some of these will be applied to clinical diagnosis and the evaluation of care. Databases, concepts, descriptions, and models are to be put in the public domain, an open system.

6. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Structure with Function The Genome, and the Transcriptome. THE PHYSIOME: The physico-chemical status. Descriptions of the Proteome, of solutes, bilayers, organelles, organs, organisms. Quantitative measures of structural components, e.g. protein and solute levels in cells and organelles, volumes, surface areas, material properties, etc. (The Morphome) Schema of interactions between the components. Regulatory apparatus for gene expression and metabolism. (The Metabolome) Computational models (genes +milieu  organism).

7. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Three Incentives for Developing the Physiome To develop understanding of a mechanism or a phenomenom: basic science. To determine the most effective targets for therapy, either pharmaceutic or genomic. To design artificial or tissue-engineered, biocompatible implants.

8. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 An example: LBBB Left Bundle Branch Block of the Cardiac Conduction System Auscultation: Reverse splitting of the second heart sound ECG: Wide QRS complex and often late T wave X-ray: Moderate cardiac enlargement Thallium scan: Low flow in the septum PET scan: Decreased septal glucose uptake, but normal septal fatty acid uptake. The imaging gave three clues to the physiology. How can the observations be explained?

9. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Electrical activation of the normal heart Prinzen et al., 2000

10. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 RV apex pacingleft bundle branch block Schematics of electrical activation X Prinzen et al., 2000

11. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Explaining what is observed in Left Bundle Branch Block ECG: Wide QRS complex and often late T wave The RBB is activated normally, and excitation proceeds normally over the RV, but since the left branch of the bundle of His is blocked the spread of activation into the left ventricular muscle is delayed 50 to 100 ms, broadening the QRS complex, and delaying the repolarization phase (late T wave)

12. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 ECG Tagging pulse Delay = 50 msDelay = 90 msDelay = 130 ms 50ms 90ms 130ms... Pacing spike Gx RF Presat. pulse MRI tagging of Cardiac Contraction (Prinzen, Hunter, Zerhouni,1999)

13. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Explaining what is observed in Left Bundle Branch Block Auscultation: Reversed splitting of S2 (second heart sound) The RBB is activated normally, but activation of the left ventricle is delayed 50 to 100 ms, so that aortic valve closing is delayed and is later than pulmonic closing, rather than earlier. During inspiration increased RV filling, delaying pulmonic valve closure, shortens (rather than lengthening) the interval between pulmonic and aortic valve closure: reversed respiratory influence on second sound splitting interval. Normally, Insp  longer A 2 –P 2, but here Insp  shorter P 2 –A 2

14. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Effect of RV apex pacing on regional LV epicardial fiber strain early-activated late-activated Prinzen et al, Am. J. Physiol, 1990  Segment length 

15. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Atrial pacing RV apex pacingLV free wall pacing apex base anterior posterior septum Prinzen et al, J Am Coll Cardiol, 1999 0 (mJ/g) 8 Distribution of external work in the LV wall 0

16. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 To explain what is seen in LBBB: Thallium scans: Decreased septal blood flow relative to rest of LV because local demand is reduced. Decreased septal mass due to local atrophy. PET Glucose Uptake: Decreased septal uptake due to shift away from glucose with diminished demand relative to supply. PET data show normal FA uptake. Regional FA uptake is matched to local flow. X-ray: LV hypertrophy: Hypertrophic free wall due to increased workload and low contractile efficiency. This is partially attributable to increased wall tension with LV cavity volume increase: T=PxR.

17. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Cardiac fiber structuring: LV base LV near the apex From Torrent-Guasp, 1998

18. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Rabbit Heart: Epicardial fibers – blue Subendocardial fibers - yellow From Vetter and McCulloch, UCSD

19. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Integration by Computation: The Cardiome Transport: UW: Flows, uptake (O 2, fats) Cardiac Mechanics: Auckland Univ: P.Hunter UCSD: McCulloch Maastricht: Arts, Prinzen, Reneman JHU: W.Hunter Action Potentials: Oxford U: D. Noble Johns Hopkins: Winslow Case-Western: Rudy Cardiac excitatory spread: CWRU: Rudy et al. Johns Hopkins: Winslow Syracuse: Jalife UCSD: McCulloch N.Smith, P. Hunter,et al. 1998

20. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 What are the mechanisms for the responses in Left Bundle Branch Block? Thallium scans: How is local flow regulated? PET Glucose Uptake: How is glycolysis regulated? MR Strain Patterns: How do structure, excitation, and contraction combine to produce these? X-ray LV hypertrophy: What regulates actin and myosin expression?

21. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Excitation-Contraction Coupling Cooperativity Mechanical Feedback

22. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 The Motor Units

23. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 f STRONG g +g V Energy Use depends on shortening velocity: WEAK ADP ATP 0 1 ADP Weak-Strong vs. Attached-Detached  Weak-Strong vs. Attached-Detached ATP Mechanical Feedback  Mechanical Feedback Landesberg/Sideman, 1998

24. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 The Conservative Phys-chem cell (no protein synthesis or proteolyis) Balances mass, charge, volume, energy, reducing equivalents, concentrations Serves as a primitive for expanded models RBC, prokaryote, eukaryote, myocyte, B-cell Serve as entry to databases Component of healthy and diseased tissues Basis for multicellular integrated systems models Understanding via metabolic control analysis of networks Test bed for mechanistic pharmacodynamic models and selection for drug design and for genomic intervention

25. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 The glycolytic conservative cell (with eternal proteins) Na +  Ca 2  Ca   Ca 2 + 3Na +  ATP 3Na +  ATP   Na + Substrates Glycolysis pH balance ~P balance Purine balance Osmotic balance Water balance Charge neutrality Redox state Free Energy RBC e.g. arep.med.harvard.edu, Edwards, Palsson,Church et al. Metabolites

26. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 The conservative cell with eternal proteins Na +   I NaK   Ca 2 + I p(Ca) Ca 2 + I NaCa Na + Endoplasmic reticulum  ATP   Na + Substrates Glycolysis, fatty acid pH ~P balance Purine balance Osmotic balance Water balance Charge neutrality Redox state Free Energy TCA OxPhosph

27. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 The sustainable metabolic muscle cell Na + K+K+ K+K+ K+K+ K+K+             Ca 2 + I p(Ca) I Ca,K K+K+ Ca 2 + I Ca,b Ca 2+ TRPN T-tubule Ca 2 +   Na + Sarcoplasmic reticulum I Ca Ca 2 + subspace calseq calmodulin RyR Ca 2 + ATP K+K+   K+K+   H+H+ Na + TCA OxPhosph Substrates ATP regulation pH, P & Charge neutrality Leak

28. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 The cardiac muscle cell Na + K+K+ K+K+ K+K+ K+K+  Kp      NaK  Na I Na,b Ca 2 + I p(Ca) I Ca,K K+K+ Ca 2 + I Ca,b T-tubule Ca 2 +   aCa Na + Sarcoplasmic reticulum I Ca Ca 2 + subspace calseq calmodulin RyR Ca 2 + ATP K+K+  Ks K+K+  to1 H+H+ Na + Substrates Leak (building from Luo-Rudy 1994-2001 and Winslow et al. 1999) OxPhosph TCA Glycolysis

29. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 Conclusions: Conservative cell models provide a basis for a host of specific applications. Their behavior is innately complex and highly dependent on the conditions. Computability is a major issue if models are to be used are practical aids to thinking. Even now they provide short-term prediction of the consequences of intervention.

30. 20jun01: http://nsr.bioeng.washington.edu Silico.6.01 END www.physiome.org