| 1
|
| 2 |
3 |
4 |
| 5 |
|
A multi-scale and multi-system approach to understand granuloma formation in TB
|
|
|
|
|
Other PIs on this project:
Students and postdoctoral Fellows on this project:
Technical support:
Project Summary:
Tuberculosis is responsible for 2 million deaths per year. The interplay
between host and bacterial factors leads to different disease outcomes
(latency, primary tuberculosis, reactivation tuberculosis). A key outcome is
the formation of a collection of immune cells termed the granuloma. This
structure acts not only as an immune microenvironment and a barrier to
dissemination but also as a niche for long-term bacterial survival. The
long-term goal of this project is to identify factors that contribute to
different outcomes of M. tuberculosis infection. We hypothesize that these
different infection outcomes are reflected locally at the level of the
granuloma and that granuloma structure is the result of the interplay of
events at organ, tissue, cellular, and molecular scales over the time course
of minutes to years. Several models of granuloma formation in tuberculosis
will be integrated: pulmonary granulomas induced by M. tuberculosis antigen
(PPD) coated beads in vivo, M. tuberculosis infection in mice and non-human
primates, and multi-scale in silico models. Our studies will include
multiple spatial and temporal scales to address the following aims. Aim 1:
Determine how specific immune cells and effector molecules in the lung
influence the formation of different granuloma structures. Aim 2: Determine
the role of dendritic cell and T cell trafficking between lung granuloma and
draining lymph nodes in influencing granuloma development. Aim 3: Identify
the mechanisms that determine TNF availability for the purpose of
understanding how granulomas form as well as how treatment with
anti-TNF-therapies leads to TB reactivation. Our interdisciplinary team's
approach for integrating data and in silico models over the relevant
biological and temporal scales will allow us to predict and test hypotheses
regarding key factors that influence granuloma formation and structure.
These factors are likely central to determining different disease outcomes
following M. tuberculosis infection and will provide a new tool for testing
therapies and vaccines against M. tuberculosis.
Disclaimer: The reprints available here are provided for your
personal use only and may not be used for any commercial purpose
without prior written permissions from the paper's publisher and
author. The violation is subject to the U.S. Copyright Act of 1976,
Title 17 U.S.C.
Publications:
1) Publications derived from this project:
J. Christian J. Ray, JoAnne L. Flynn, and Denise E. Kirschner
A Synergy between Individual TNF-Dependent Functions
Determines Granuloma Performance for Controlling
Mycobacterium tuberculosis Infection.
Journal of Immunology, 2009, 182: pp 3706-3717
Denise E. Kirschner and Jennifer J. Linderman
Mathematical and computational approaches
can complement experimental studies of
host pathogen interactions.
Cellular Microbiology (2009) 11(4), doi:10.1111/j.1462-5822.2
009.01281.x
Jennifer J. Linderman, Thomas Riggs, Manjusha Pande, Mark Miller, Simeone Marino,
and Denise E. Kirschner
Characterizing the Dynamics of CD4+ T Cell Priming within
a Lymph Node.
Journal of Immunology (2010) - in press
Fallahi-Sichani, M., M. Schaller, D. Kirschner, S. Kunkel, and J. Linderman
Identification of key processes that control tumor necrosis factor availability in a tuberculosis granuloma.
(in revision for PLoS Computational Biology, 2009)
Simeone Marino, Amy Myers, JoAnne L. Flynn, Denise E. Kirschner
TNF
and IL-10 are major factors in modulation of the phagocytic cell environment
in lung and lymph node in tuberculosis: a next generation two compartmental
model.
(submitted to JTB) February 2010 to Journal of Theoretical Biology
2) Publications related to this project:
Jose L. Segovia-Juarez, Suman Ganguli, and Denise Kirschner,
Identifying control mechanism of granuloma
formation during M. tuberculosis infection using an agent based
model, Journal of Theoretical Biology. 231, Issue 3,
Pages 357-376 2004.
Stewart T. Chang, Jennifer J. Linderman, and Denise E. Kirschner
A role for multiple mechanisms in the inhibition of MHC class II-
mediated antigen presentation by Mycobacterium
tuberculosis, Proceedings of the National
Academy of Sciences, USA, pps. 4530-4535
March 22, 2005 vol. 102 no. 12, 2005
David Gammack, Jose L. Segovia-Juarez, Suman Ganguli,
Simeone Marino, and Denise Kirschner,
Understanding the Immune Response in Tuberculosis
Using Different Mathematical Models and
Biological Scales,
SIAM Journal of Multiscale Modeling and Simulation,
Vol. 3, No. 2, pp. 312-345, 2005
Denise E. Kirschner,
Stewart T. Chang,
Thomas W. Riggs,
Nicolas Perry,
Jennifer J. Linderman,
Toward a multi scale model of antigen
presentation in immunity
,
Immunological Reviews 2007
Vol. 216:,pp. 93-118; Edited by: J. Mata and J. Cohen
Denise Kirschner,
The Multi-scale Immune Response to Pathogens:
M. tuberculosis as an Example
,
In Silico Immunology,
Springer US,
pp. 289-311,
2007,
DOI 10.1007/978-0-387-39241-7, edited by J. Timmis
and D. Flower
Modeling Methods and Tools:
Ordinary Differential Equations (several non-linear types, all continuous,
determistic approaches) and Agent-based Model (stochastic, discrete
approach)
Software Development:
Languages and Tools:
C++/C OOP, JAVA
Framework / Sharing Environment:
Open source software used in the lab, not
currently involved in development frameworks.
http://innoculant.micro.med.umich.edu/ftp
Available PROGRAMS from this project:
Sensitivity and Uncertainty Analysis Methods
Exectuable for 2-Dimensional granuloma simulator
IMAG and Mutliscale modeling Consortium Group Website:
http://www.imagwiki.org/mediawiki/index.php?title=Main_Page
Secured Collaboration Environment:
Limited-access shared collaboration resource (requires login).
http://innoculant.micro.med.umich.edu/ftp2-login
Software Sharing Programs:
MATLAB codes and documentation for shareware analysis tools created
by our group.
http://malthus.micro.med.umich.edu/MSMgranuloma/shareware
SBML format of Models:
To make our models "sharing-friendly", we have prepared SBML format
for the models in the papers in the following
link that are derived from this study:
http://malthus.micro.med.umich.edu/MSMgranuloma/sbml
|
|
|
|
6 |
| 7 |
8 |
9 |
|
University of Michigan
UofM Medical School
UofM Rackham Graduate School
UofM Microbiology & Immunology
UofM Libraries
UofM Computing Services
UofM Maps
|
