First q-bio Summer School: Other Topics in Biological Modeling

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This series of lectures will showcase some quantitative biological modeling efforts at Los Alamos National Lab.

Lecture 1

Scope

Virus Infection Dynamics or Immunology Modeling

Lecturer

Alan Perelson

Materials

PDF lecture notes

Lecture 2

Scope

The Tumor Microenvironment and 3-D Tumor Models

Lecturer

Jim Freyer

Materials

PDF lecture notes

Abstract

A solid tumor in a human is arguably one of the most unique, complex and chaotic biological systems in existence. Contributing greatly to this complexity is the highly heterogeneous tumor microenvironment, which has both spatial and temporal variations in an unaccountably large number of parameters (extracellular chemistry, cellular physiology, metabolism, gene expression and protein composition, to name a few). Unfortunately, this unique microenvironment has numerous adverse effects on the response of a tumor to essentially every therapy that has been devised to date. Thus, improving our understanding of this extremely complex biological system will have benefits for cancer therapy as well as for basic biology. An increasingly important tool in this field is the use of model systems, both experimental and theoretical. This lecture will start with a basic description of the tumor microenvironment, including mechanisms behind the heterogeneity, recent advances in assaying the microenvironment, and impacts on cancer therapy. This will be followed by a description of three-dimensional (3-D) experimental tumor models, focusing on the multicellular spheroid that we use in our laboratory. Two examples of our recent experimental work with spheroids will demonstrate how this system can be used to answer basic questions on the regulation of the cell cycle and protein expression. A new application for spheroids will be presented, along with a new experimental model system we have under development. The lecture will conclude with a description of theoretical models used to describe tumor growth and the tumor microenvironment, including an introduction to a multiscale model developed at Los Alamos that will be presented in much more detail in a subsequent lecture in this series.

Lecture 3

Scope

Modeling tumor growth

Lecturer

Yi Jiang

Materials

Abstract

Cancer has become the leading cause of disease death for middle aged Americans. At the same time, after a quarter century of rapid advances, cancer research has generated a rich a complex body of knowledge. We have developed a cell-based, multiscale modeling framework to model cancer development based on this body of knowledge. Our model includes a cellular model for cell dynamics (cell growth, division, death, migration and adhesion), an intracellular protein regulatory network for cell cycle control and a signaling network for cell decision-making, and extracellular reaction-diffusion chemical dynamics. This model has produced avascular tumor growth dynamics that agree with tumor spheroid experiments; it has generated realistic sprout patterns in tumor-induced angiogenesis; it has also shown potential for investigating chemotherapeutic strategies for tumor. Given the biological flexibility of the model, we believe that it can facilitate a deeper understanding of the cellular and molecular interactions associated with cancer progression and treatment, and potentially guide experimental design and interpretation.

Relevant websites

References

Lecture 4

Scope

Modeling Collective Behavior in Myxobacteria

Lecturer

Yi Jiang

Materials

dictyBase home

Myxobacteria website by Dworkin at UMN

Myxococcus xanthus website by Kaiser at Stanford

Dale Kaiser. Bacterial Swarming: A re-examination of cell-movement patterns. Current Bio. 17. R561-R570. 2007.

Lecture 5

Scope

Modeling allosteric effects in proteins

Lecturer

Michael Wall

Materials

PDF Lecture notes

Lecture 6

Scope

Modeling metabolism

Lecturer

Jeremy S. Edwards, University of New Mexico

Materials

PDF Lecture notes

Lecture 7

Scope

Using Mathematical Models to Gain Insight into Understanding and Controlling the Spread of Epidemics

Lecturer

James Mac Hyman

Abstract

Mathematical models based on the underlying transmission mechanisms of the disease can help the medical/scientific community understand and anticipate the spread of an epidemic and evaluate the potential effectiveness of different approaches for bringing an epidemic under control. Even more important than the successes with these specific diseases has been the development of frameworks and concepts for understanding epidemiology. I will describe some of our mathematical modeling efforts to understand the spread of infectious diseases, including influenza, smallpox, foot and mouth disease, and HIV to estimate and subsequently predict the impact of control measures on their spread. I will describe how mathematical models can reduce the uncertainty of the estimates of disease prevalence and aid in the development of scientific understanding of the mechanisms of the disease and of the epidemic. Thus, the modeling techniques can join with biological, epidemiological, behavioral, and social science studies to produce better projections and better understanding of the epidemic.

Materials

Lecture notes

Relevant websites

References

Lecture 8

Scope

Designing Vaccines for Variable Pathogens

Lecturer

Bette Korber

References

Consensus and ancestral vaccine design and first tests:

1. Gaschen B, Taylor J, Yusim K, Foley B, Gao F, Lang D, Novitsky V, Haynes B, Hahn BH, Bhattacharya T, Korber B. Diversity considerations in HIV-1 vaccine selection. Science. 2002 Jun 28;296(5577):2354-60 (2002). PMID: 12089434

2. Weaver EA, Lu Z, Camacho ZT, Moukdar F, Liao H-X, Ma B-J, Kepler T, Nabel GJ, Letvin NL, Korber BT, Hahn BH, Haynes BF and Gao F. Cross-subtype T Cell Immune Responses induced by an HIV-1 Group M Consensus Env Immunogen. J Virol. 2006 Jul;80(14):6745-56, 2006. PMID: 16809280

3. Liao HX, Sutherland LL, Xia SM, Brock ME, Scearce RM, Vanleeuwen S, Alam SM, McAdams M, Weaver EA, Camacho Z, Ma BJ, Li Y, Decker JM, Nabel GJ, Montefiori DC, Hahn BH, Korber BT, Gao F, Haynes B. A Group M Consensus Envelope Glycoprotein Induces Antibodies That Neutralize Subsets of Subtype B and C HIV-1 Primary Viruses. Virology, 2006 Sep 30;353(2):268-82., 2006. PMID: 17039602

Signature sites:

1. Bhattacharya T, Daniels M, Heckerman D, Foley B, Frahm N, Kadie C, Carlson J, Yusim K, McMahon B, Gaschen B, Mallal S, Mullins JI, Nickle DC, Herbeck J, Rousseau C, Learn GH, Miura T, Brander C, Walker B, Korber B. Founder Effects in the Assessment of HIV Polymorphisms and HLA Allele Associations. Science. 2007 Mar 16;315(5818):1583-6. PMID: 17363674

2. Brumme ZL, Brumme CJ, Heckerman D, Korber BT, Daniels M, Carlson J, Kadie C, Bhattacharya T, Chui C, Szinger J, Mo T, Hogg RS, Montaner JS, Frahm N, Brander C, Walker BD, Harrigan PR. PLoS Pathog. 2007 Jul 6;3(7):e94 [Epub ahead of print] PMID: 17616974

Mosaic vaccines:

1. William Fischer, Simon Perkins, James Theiler, Tanmoy Bhattacharya, Karina Yusim, Robert Funkhouser, Carla Kuiken, Barton Haynes, Norman L. Letvin, Bruce D. Walker, Beatrice H. Hahn, Bette Korber. Designing polyvalent HIV-1 vaccines for optimal coverage of potential T-cell epitopes in diverse global variants. Nat Med. 2007 Jan;13(1):100-6. Epub 2006 Dec 24 PMID: 17187074 LA-UR-06-3608.

The other sections of the talk are taken from work still under review or not yet written up and are not yet public. More information is available at http://www.t10.lanl.gov/btk/