Flow cytometry is a widely used experimental tool that scientists use to characterize cells' phenotype by using a combination of fluidics, optics, and electronics. Fluorescent-labeled antibodies are used as well as size in order to describe a cell type. An instrument (flow cytometer) is then used to measure the fluorescence and a separate software program analyzes the results. A brief overview of flow cytometry will be discussed. An experimental protocol will also be explained using the murine model as an example along with data taken from an experiment. Cells will be counted and stained in a laboratory setting and collected with various flow cytometers.

This session consists of three talks. First Dr. Hulin Wu will give an overview of our Center's effort in developing mathematical models, statistical estimation methods and computing and simulation tools for immune responses to influenza virus. In particular, we will demonstrate how an inter-disciplinary team can work together to develop quantitative models and computer simulation tools for immune responses to pathogens. Dr. Ha Youn Lee will introduce the adaptive immune response model for influenza virus that is developed by our Center. The primary cellular immune response to influenza is complex. Although some response functions can be measured directly, many others cannot. In addition, it is often difficult to determine how viral clearance, T and B cell responses, and antigen presentation in different compartments interact with each other in a dynamic fashion. Therefore, we developed a two-compartment set of time-delay ordinary differential equations for airway/lung and lymph node/spleen, forming a global flu model. Our objective is to use a mathematical model to predict the characteristics of primary influenza response when virulence or certain arms of the immune system are altered. By comparing our global flu model with experimental data on the kinetics of the cellular responses, we initially addressed the dependence of viral clearance on CD8 T cell and antiviral B cell responses in primary influenza infection, and the role of CD4 T cell help in the persistence of antibody after primary infection. The developed mathematical model was used to guide the design of new experiments quantifying different arms of the immune response to influenza infection. Finally, our presentations will be followed by hands-on software demonstration of "XDE Pro" given by Dr. Hulin Wu and Mr. Canglin Wu. "XDE Pro" is a cross-platform software tool for differential equation model simulation and estimation developed by the University of Rochester Center for Biodefense Immune Modeling. It was designed with special attention to the features necessary for modeling the interaction between the immune system and viral infection. The presentation will provide an overview of design and the features of "XDE Pro" simulation tool, as well as a hands-on demonstration "XDE Pro" allows the user to manually enter a differential equation model or to select from a set of pre-defined models, specified as either ordinary differential equations or delay differential equations. "XDE Pro" provides both simulation and parameter estimation tools, which can be selected, configured and controlled using a simple visual interface. Experimental data, necessary for estimation, can be loaded from standard spreadsheet formats. Simulation is performed in real time, allowing interactive exploration of the effect of varying model parameters. Parameter estimation can be accomplished using several provided algorithms with estimation progress displayed during computation. Results are displayed in both tabular and graphical forms and can be exported to standard file formats. Further, the system has been designed using a "plug-in" architecture to allow easy addition of new models, model parsers, differential equation solvers, and statistical estimation methods. This work is part of the multidisciplinary efforts of investigators from the Center for Biodefence Immune Modeling funded by NIAID/NIH contract no. N01-AI-50020.

In the post-genomic era of biomedical research understanding the functionality of molecules at the cellular and subcellular level in living systems will become predominant. In this era we must move beyond static “snapshots” of the cellular state to an understanding of the biology of cells over time and in 3-dimentional- space. Within the cellular environment it is expected that we will be able to study the expression, the functional role(s) and interactions of multiple unique molecules concurrently. Furthermore, it will be desirable to determine the effects of these molecules on cell development, organization and fate over extended periods of time. To perform these types of studies it is necessary to develop new methodologies that will allow multiparametric analysis of cells while maintaining their functional viability. In the past this goal would have been extraordinarily difficult to achieve. However, developments in optical and computational technology have empowered modern microscopists to undertake these previously forbidding tasks. This two session workshop will discuss live cell imaging tools, the expectations of the technology and limitations of optical tools within the context of current scientific efforts principally focusing on the use of fluorescent proteins and ratiometric tools in live cell methodologies. The first session in this workshop will focus on: optical principals, principals of fluorescence and, detector and microscope design. The second session will focus on actual methods: Multicolor fluorescence, FRET, TIRF, GFP and, Live cell confocal.

An immunological research always involves different types of data and information, like biological samples of participating subjects, experiment raw data from immunological laboratories, processed data by computation tools, and various documents for studies. It also needs an efficient way to handle tremendous phenotype data generated by immunological assays which include flow cytometry, enzyme-linked immunosorbent assay (ELISA), and enzyme-linked immunospot (ELISPOT). In addition, researchers need a standardized tool to record all data and documents based on research workflows, an easy way to save and query data/documents from distributed locations, and an efficient platform for data sharing to broad research community. To achieve those goals we present a comprehensive Web-based system, DataTrans, for managing data and information in the studies of immunological researches.

The DataTrans is developed in ASP.NET using C# language with Microsoft .NET Framework. ASP.NET (ASP-Active Server Pages) is a set of technologies in the .NET Framework that make it much easier to create Web applications. It provides a means to program Web pages on the Web server facilities of Internet Information Services (IIS). The relational database is implemented with Microsoft SQL Server 2005. ADO.NET (ADO-ActiveX Data Objects) is used as a means of accessing and storing data in the database. The DataTrans will run on a Web server computer, where the Windows 2003 Operating System is installed. The Web server must run IIS, FrontPage Server Extensions and will have the .Net Framework installed. As a Web application, the DataTrans system will be effectively used by investigators through the Internet for data saving, retrieving and sharing.

The modeling and simulation tool Simmune (http://www3.niaid.nih.gov/labs/aboutlabs/psiim/computationalBiology/) allows for the definition of detailed models of cell biological processes ranging from interactions between molecular binding sites to the behavior of populations of cells. Based on the inputs the user provides through a graphical interface, the software automatically constructs the resulting sets of partial differential equations describing intra- and extra-cellular reaction-diffusion and integrates them, providing numerous ways to display the behavior of the simulated systems and to interact in a way that closely resembles wet-lab manipulations with running simulations. In the talk, I will explain the technical foundations and typical use cases for simmune.

Agent Based Modeling (ABM) is a form of complex system analysis. It views a system as populations of various types of components (agents). ABMs are very intuitive and thus suited to the translation of “real-world” observations into a simulation. This session will focus on a toolkit called Netlogo™ that is freely available for download at: http://ccl.northwestern.edu/netlogo/download.shtml . Students in this session are strongly encouraged to download version Netlogo 3.1.4 onto their laptops, pre-examine the Tutorial, view the Biology Sample Models “Slime” and “Virus,” and bring their laptops to class, as the session will consist of a step-by-step construction of a “Toy” Inflammatory Response ABM.

Aspergillus fumigatus is a ubiquitous fungus that causes infections in highly immunocompromised individuals, particularly following allogeneic bone marrow transplantation. Inhalation of A. fumigatus spores can also elicit allergic immune responses that exacerbate asthma. Our laboratory is investigating CD4 T cell responses to inhaled A. fumigatus spores in a murine model, with the goal of identifying factors that promote T cell priming, trafficking and differentiation. Because rapid recruitment of inflammatory cells is essential for defense against respiratory fungal infection, we are also studying pulmonary innate immune responses to A. fumigatus spores and hyphae.

Tuberculosis (TB) remains a serious public health problem in the United States and worldwide. The high risk of developing multidrug-resistant M. tuberculosis is a serious limitation to drug therapy, and consequently development of efficacious vaccines is critical for the successful eradication of TB. T-helper (Th) 1 immunity is critical for protection against TB, however the role of innate cells and innate immune mechanisms in initiating and regulating Th1 immunity remain largely uncharacterized. The presentation will review recent progress made in this area, and summarize our studies examining the molecular regulation of M. tuberculosis-induced interleukin-12, and the role of Toll-like receptors and costimulatory molecules in host resistance against M. tuberculosis.

Systems biology approaches to the study of the immune and other systems require biomolecular interaction data as a framework for analysis. This data includes both physical and functional interactions between biomolecules, as well knowledge of regulatory events. Several databases storing this information exist that can be of utility to the immune researcher. These will be discussed in this session, with an emphasis on the upcoming InnateDB database. Methods for visualizing and interacting with interaction data, such as Cytoscape, will also be briefly covered.