Mathematical and computational approaches can complement experimental studies of host–pathogen interactions
dc.contributor.author | Kirschner, Denise E. | en_US |
dc.contributor.author | Linderman, Jennifer J. | en_US |
dc.date.accessioned | 2010-06-01T20:10:53Z | |
dc.date.available | 2010-06-01T20:10:53Z | |
dc.date.issued | 2009-04 | en_US |
dc.identifier.citation | Kirschner, Denise E.; Linderman, Jennifer J. (2009). "Mathematical and computational approaches can complement experimental studies of host–pathogen interactions." Cellular Microbiology 11(4): 531-539. <http://hdl.handle.net/2027.42/73304> | en_US |
dc.identifier.issn | 1462-5814 | en_US |
dc.identifier.issn | 1462-5822 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/73304 | |
dc.identifier.uri | http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=19134115&dopt=citation | en_US |
dc.description.abstract | In addition to traditional and novel experimental approaches to study host–pathogen interactions, mathematical and computer modelling have recently been applied to address open questions in this area. These modelling tools not only offer an additional avenue for exploring disease dynamics at multiple biological scales, but also complement and extend knowledge gained via experimental tools. In this review, we outline four examples where modelling has complemented current experimental techniques in a way that can or has already pushed our knowledge of host–pathogen dynamics forward. Two of the modelling approaches presented go hand in hand with articles in this issue exploring fluorescence resonance energy transfer and two-photon intravital microscopy. Two others explore virtual or ‘ in silico ’ deletion and depletion as well as a new method to understand and guide studies in genetic epidemiology. In each of these examples, the complementary nature of modelling and experiment is discussed. We further note that multi-scale modelling may allow us to integrate information across length (molecular, cellular, tissue, organism, population) and time (e.g. seconds to lifetimes). In sum, when combined, these compatible approaches offer new opportunities for understanding host–pathogen interactions. | en_US |
dc.format.extent | 334329 bytes | |
dc.format.extent | 3109 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.publisher | Blackwell Publishing Ltd | en_US |
dc.rights | © 2009 Blackwell Publishing Ltd | en_US |
dc.title | Mathematical and computational approaches can complement experimental studies of host–pathogen interactions | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Molecular, Cellular and Developmental Biology | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Microbiology and Immunology, 6730 Medical Science Bldg. II, University of Michigan Medical School, Ann Arbor, MI, USA. | en_US |
dc.contributor.affiliationum | Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA. | en_US |
dc.identifier.pmid | 19134115 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/73304/1/j.1462-5822.2009.01281.x.pdf | |
dc.identifier.doi | 10.1111/j.1462-5822.2009.01281.x | en_US |
dc.identifier.source | Cellular Microbiology | en_US |
dc.identifier.citedreference | Alarcon, T., Byrne, H.M., and Maini, P.K. ( 2004 ) Towards whole-organ modelling of tumour growth. Prog Biophys Mol Biol 85: 451 – 472. | en_US |
dc.identifier.citedreference | Alcais, A., Remus, N., Abel, L., and Casanova, J.L. ( 2001 ) Genetic susceptibility to tuberculosis: from monogenic to polygenic inheritance. Sepsis 4: 237 – 246. | en_US |
dc.identifier.citedreference | von Andrian, U.H., and Mempel, T.R. ( 2003 ) Homing and cellular traffic in lymph nodes. Nat Rev Immunol 3: 867 – 878. | en_US |
dc.identifier.citedreference | Beltman, J.B., Maree, A.F., Lynch, J.N., Miller, M.J., and de Boer, R.J. ( 2007 ) Lymph node topology dictates T cell migration behavior. J Exp Med 204: 771 – 780. | en_US |
dc.identifier.citedreference | Blythe, M.J., Doytchinova, I.A., and Flower, D.R. ( 2002 ) JenPep: a database of quantitative functional peptide data for immunology. Bioinformatics 18: 434 – 439. | en_US |
dc.identifier.citedreference | Castellino, F., Huang, A.Y., Altan-Bonnet, G., Stoll, S., Scheinecker, C., and Germain, R.N. ( 2006 ) Chemokines enhance immunity by guiding naive CD8+ T cells to sites of CD4+ T cell–dendritic cell interaction. Nature 440: 890 – 895. | en_US |
dc.identifier.citedreference | Catron, D.M., Itano, A.A., Pape, K.A., Mueller, D.L., and Jenkins, M.K. ( 2004 ) Visualizing the first 50 h of the primary immune response to a soluble antigen. Immunity 21: 341 – 347. | en_US |
dc.identifier.citedreference | Celli, S., Garcia, Z., Beuneu, H., and Bousso, P. ( 2008 ) Decoding the dynamics of T cell–dendritic cell interactions in vivo. Immunol Rev 221: 182 – 187. | en_US |
dc.identifier.citedreference | Chang, S.T., Linderman, J.J., and Kirschner, D.E. ( 2005 ) Multiple mechanisms allow Mycobacterium tuberculosis to continuously inhibit MHC class II-mediated antigen presentation by macrophages. Proc Natl Acad Sci USA 102: 4530 – 4535. | en_US |
dc.identifier.citedreference | Chang, S.T., Ghosh, D., Kirschner, D.E., and Linderman, J.J. ( 2006 ) Peptide length-based prediction of peptide-MHC class II binding. Bioinformatics 22: 2761 – 2767. | en_US |
dc.identifier.citedreference | Chang, S.T., Linderman, J.J., and Kirschner, D.E. ( 2008 ) Effect of multiple genetic polymorphisms on antigen presentation and susceptibility to Mycobacterium tuberculosis infection. Infect Immun 76: 3221 – 3232. | en_US |
dc.identifier.citedreference | Dietz, K., and Heesterbeek, J.A.P. ( 2000 ) Bernoulli was ahead of modern epidemiology. Nature 408: 513 – 514. | en_US |
dc.identifier.citedreference | Farr, W. ( 1866 ) On the cattle plague. J Soc Sci 1: 349 – 351. | en_US |
dc.identifier.citedreference | Franke, R., Muller, M., Wundrack, N., Gilles, E.D., Klamt, S., Kahne, T., and Naumann, M. ( 2008 ) Host-pathogen systems biology: logical modelling of hepatocyte growth factor and Helicobacter pylori induced c-Met signal transduction. BMC Syst Biol 2: 4. | en_US |
dc.identifier.citedreference | Ganusov, V.V., and Antia, R. ( 2005 ) Pathology during acute infections: contributions of intracellular pathogens and the CTL response. Biol Lett 1: 239 – 242. | en_US |
dc.identifier.citedreference | Goldstein, B., Faeder, J.R., and Hlavacek, W.S. ( 2004 ) Mathematical and computational models of immune-receptor signalling. Nat Rev Immunol 4: 445 – 456. | en_US |
dc.identifier.citedreference | Hanna, P.C., Acosta, D., and Collier, R.J. ( 1993 ) On the role of macrophages in anthrax. Proc Natl Acad Sci USA 90: 10198 – 10201. | en_US |
dc.identifier.citedreference | Hoppe, A.D., Shorte, S.L., Swanson, J.A., and Heintzmann, R. ( 2008 ) Three-dimensional FRET reconstruction microscopy for analysis of dynamic molecular interactions in live cells. Biophys J 95: 400 – 418. | en_US |
dc.identifier.citedreference | Hoppe, A.D., Seveau, S., and Swanson, J.A. ( 2009 ) Live cell fluorescence microscopy to study microbial pathogenesis. Cell Micro 11: in press. DOI: 10.1111/j.1462-5822.2009. 01283.x | en_US |
dc.identifier.citedreference | Kemp, M.L., Wille, L., Lewis, C.L., Nicholson, L.B., and Lauffenburger, D.A. ( 2007 ) Quantitative network signal combinations downstream of TCR activation can predict IL-2 production response. J Immunol 178: 4984 – 4992. | en_US |
dc.identifier.citedreference | Kenworthy, A.K. ( 2001 ) Imaging protein–protein interactions using fluorescence resonance energy transfer microscopy. Methods 24: 289 – 296. | en_US |
dc.identifier.citedreference | Kermack, W.O., and McKendrick, A.G. ( 1927 ) A contribution to the mathematical theory of epidemics. Proc R Soc Lond B Biol Sci 115: 700 – 721. | en_US |
dc.identifier.citedreference | Kinzer-Ursem, T.L., Sutton, K.L., Waller, A., Omann, G.M., and Linderman, J.J. ( 2006 ) Multiple receptor states are required to describe both kinetic binding and activation of neutrophils via N-formyl peptide receptor ligands. Cell Signal 18: 1732 – 1747. | en_US |
dc.identifier.citedreference | Kirschner, D.E., Chang, S.T., Riggs, T.W., Perry, N., and Linderman, J.J. ( 2007 ) Toward a multiscale model of antigen presentation in immunity. Immunol Rev 216: 93 – 118. | en_US |
dc.identifier.citedreference | Konjufca, V., and Miller, M.J. ( 2009 ) Two-photon microscopy of host–pathogen interactions: acquiring a dynamic picture of infection in vivo. Cell Micro 11: in press. DOI: 10.1111/1462-5822.2009.01289.x | en_US |
dc.identifier.citedreference | Lazarevic, V., Nolt, D., and Flynn, J.L. ( 2005 ) Long-term control of Mycobacterium tuberculosis infection is mediated by dynamic immune responses. J Immunol 175: 1107 – 1117. | en_US |
dc.identifier.citedreference | Lio, D., Marino, V., Serauto, A., Gioia, V., Scola, L., Crivello, A., et al. ( 2002 ) Genotype frequencies of the +874T→A single nucleotide polymorphism in the first intron of the interferon-gamma gene in a sample of Sicilian patients affected by tuberculosis. Eur J Immunogenet 29: 371 – 374. | en_US |
dc.identifier.citedreference | Lu, Y.J., Gross, J., Bogaert, D., Finn, A., Bagrade, L., Zhang, Q., et al. ( 2008 ) Interleukin-17A mediates acquired immunity to pneumococcal colonization. PLoS Pathog 4: e1000159. | en_US |
dc.identifier.citedreference | Miller, M.J., Wei, S.H., Parker, I., and Cahalan, M.D. ( 2002 ) Two-photon imaging of lymphocyte motility and antigen response in intact lymph node. Science 296: 1869 – 1873. | en_US |
dc.identifier.citedreference | Miller, M.J., Safrina, O., Parker, I., and Cahalan, M.D. ( 2004a ) Imaging the single cell dynamics of CD4+ T cell activation by dendritic cells in lymph nodes. J Exp Med 200: 847 – 856. | en_US |
dc.identifier.citedreference | Miller, M.J., Hejazi, A.S., Wei, S.H., Cahalan, M.D., and Parker, I. ( 2004b ) T cell repertoire scanning is promoted by dynamic dendritic cell behavior and random T cell motility in the lymph node. Proc Natl Acad Sci USA 101: 998 – 1003. | en_US |
dc.identifier.citedreference | Moran, A., Ma, X., Reich, R.A., and Graviss, E.A. ( 2007 ) No association between the +874T/A single nucleotide polymorphism in the IFN-gamma gene and susceptibility to TB. Int J Tuberc Lung Dis 11: 113 – 115. | en_US |
dc.identifier.citedreference | Nielsen, M., Lundegaard, C., Blicher, T., Peters, B., Sette, A., Justesen, S., et al. ( 2008 ) Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan. PLoS Comput Biol 4: e1000107. | en_US |
dc.identifier.citedreference | Nowak, M., and May, R. ( 2000 ) Virus Dynamics – Mathematical Principles of Immunology and Virology. Oxford, NY: Oxford Press. | en_US |
dc.identifier.citedreference | Perelson, A.S. ( 1989 ) Immune network theory. Immunol Rev 110: 5 – 36. | en_US |
dc.identifier.citedreference | Perelson, A.S. ( 1999 ) Viral kinetics and mathematical models. Am J Med 107: 49S – 52S. | en_US |
dc.identifier.citedreference | Peters, B., Sidney, J., Bourne, P., Bui, H.H., Buus, S., Doh, G., et al. ( 2005 ) The immune epitope database and analysis resource: from vision to blueprint. PLoS Biol 3: e91. | en_US |
dc.identifier.citedreference | Preston, S.P., Waters, S.L., Jensen, O.E., Heaton, P.R., and Pritchard, D.I. ( 2006 ) T-cell motility in the early stages of the immune response modeled as a random walk amongst targets. Phys Rev E Stat Nonlin Soft Matter Phys 74: 011910. | en_US |
dc.identifier.citedreference | Riggs, T., Walts, A., Perry, N., Bickle, L., Lynch, J.N., Myers, A., et al. ( 2008 ) A comparison of random vs. chemotaxis-driven contacts of T cells with dendritic cells during repertoire scanning. J Theor Biol 250: 732 – 751. | en_US |
dc.identifier.citedreference | Ross, R. ( 1916 ) An application of the theory of probabilities to the study of a priori pathometry. Part I. Proc R Soc Lond B Biol Sci 92: 204 – 230. | en_US |
dc.identifier.citedreference | Segel, L. ( 1984 ) Modeling Dynamic Phenomena in Molecular and Cellular Biology. New York: Cambridge University Press. | en_US |
dc.identifier.citedreference | Segel, L., and Cohen, I. ( 2001 ) Design Principles for the Immune System and Other Distributed Autonomous Systems. New York: Oxford University Press. | en_US |
dc.identifier.citedreference | Sud, D., Bigbee, C., Flynn, J.L., and Kirschner, D.E. ( 2006 ) Contribution of CD8+ T cells to control of Mycobacterium tuberculosis infection. J Immunol 176: 4296 – 4314. | en_US |
dc.identifier.citedreference | Sullivan, A.D., Wigginton, J., and Kirschner, D. ( 2001 ) The coreceptor mutation CCR5Delta32 influences the dynamics of HIV epidemics and is selected for by HIV. Proc Natl Acad Sci USA 98: 10214 – 10219. | en_US |
dc.identifier.citedreference | Teran-Escandon, D., Teran-Ortiz, L., Camarena-Olvera, A., Gonzalez-Avila, G., Vaca-Marin, M.A., Granados, J., and Selman, M. ( 1999 ) Human leukocyte antigen-associated susceptibility to pulmonary tuberculosis: molecular analysis of class II alleles by DNA amplification and oligonucleotide hybridization in Mexican patients. Chest 115: 428 – 433. | en_US |
dc.identifier.citedreference | Wallis, R.S., Broder, M.S., Wong, J.Y., Hanson, M.E., and Beenhouwer, D.O. ( 2004 ) Granulomatous infectious diseases associated with tumor necrosis factor antagonists. Clin Infect Dis 38: 1261 – 1265. | en_US |
dc.identifier.citedreference | Wigginton, J.E., and Kirschner, D. ( 2001 ) A model to predict cell-mediated immune regulatory mechanisms during human infection with Mycobacterium tuberculosis. J Immunol 166: 1951 – 1967. | en_US |
dc.identifier.citedreference | Witt, C., Raychaudhuri, S., and Chakraborty, A.K. ( 2005 ) Movies, measurement, and modeling: the three Ms of mechanistic immunology. J Exp Med 201: 501 – 504. | en_US |
dc.identifier.citedreference | Wu, J.Q., and Pollard, T.D. ( 2005 ) Counting cytokinesis proteins globally and locally in fission yeast. Science 310: 310 – 314. | en_US |
dc.identifier.citedreference | Yates, A., Bergmann, C., Hemmen, J., Stark, J., and Callard, R. ( 2000 ) Cytokine-modulated regulation of helper T cell populations. J Theor Biol 206: 539 – 560. | en_US |
dc.identifier.citedreference | Yates, A., Callard, R., and Stark, J. ( 2004 ) Combining cytokine signalling with T-bet and GATA-3 regulation in Th1 and Th2 differentiation: a model for cellular decision-making. J Theor Biol 231: 181 – 196. | en_US |
dc.identifier.citedreference | Young, D., and Dye, C. ( 2006 ) The development and impact of tuberculosis vaccines. Cell 124: 683 – 687. | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.