Denise E Kirschner, PhD
Program Director, Microbiology and Immunology Mentoring Program
Professor of Microbiology and Immunology
Microbiology and Immunology
1150 W. Medical Center Drive, 6730 MedSci II
Ann Arbor, MI 48109
[email protected]

Available to mentor

Denise E Kirschner, PhD
Professor
  • About
  • Links
  • Qualifications
  • Center Memberships
  • Research Overview
  • Recent Publications
  • About

    Dr. Kirschner is a professor in the department of Microbiology and Immunology at the University of Michigan. She received her Bachelors, Masters and PhD in applied mathematics from Tulane University. She did graduate work also at Los Alamos National Labs and a postdoctoral fellowship at Vanderbilt University joint with the departments of Mathematics and Infectious Diseases. For the past 25 years, her research focus has been on building multi-scale models to describe the host immune response to M. tuberculosis at multiple spatial and time scales and in multiple physiological sites including lung, lymph nodes and blood. To date she have worked and collaborated with experimentalists generating data on TB with mouse, non-human primate and human studies. Dr. Kirschner currently serves (and has for the past 20 years) as Editor-in-Chief of the Journal of Theoretical Biology. She serves as the founding co-director of The Center for Systems Biology at the University of Michigan, an interdisciplinary center at the University of Michigan aimed to facilitate research and training between wet-lab and theoretical scientists.

    Links
    • Denise Kirschner Home Page
    • Kirschner Lab
    Qualifications
    • Postdoctoral Fellow
      Vanderbilt University Medical Center, Mathematical Modeling, 1994
    • PhD
      Tulane University, New Orleans, 1991
    • MS
      Tulane University, New Orleans, 1988
    • BS
      Tulane University, New Orleans, 1985
    Center Memberships
    • Center Member
      Center for Computational Medicine and Bioinformatics
    Research Overview

    The work in my laboratory focuses mainly on questions related to host-pathogen interactions in infectious diseases. This means defining both the immune responses and the microbial characteristics that lead to infection and disease. In particular, our main focus is studying persistent infections - infections that the host is not able to clear. The persistent pathogens we focus on include both bacteria (e.g. Helicobacter pylori and Mycobacterium tuberculosis) and HIV-1. Such pathogens have evolved strategies to evade or circumvent the host-immune response and our goal is to understand the complex dynamic involved in host-pathogen interactions, together with how perturbations to this interaction (via treatment with chemotherapies or immunotherapies) can lead to prolonged or permanent health of the patient. Drug-resistance and the effects of treatment can be efficiently studied in this setting.

    Currently, our research focus is on the role of the host response in pathogenesis at multiple spatial and time scales. The grants funding our work aim to examine the immune responses in the lymph nodes and lung also during TB infection. There are unique structures, granulomas, which are involved in the immune response to M. tuberculosis and we are developing methods to better understand their formation and function. This data could have a profound impact on our understanding the different disease trajectories seen in patients infected with persistent pathogens.

    We apply a range of computational tools from deterministic mathematical models to more discrete stochastic ones such as Agent Based Models and PDEs to examine spatial questions as well. We are focused on not only building multi-scale models, as that is key to studying these more complex biological systems but using them to study large open-questions related to biomarker discovery, treatment and vaccine development and testing.

    Recent Publications See All Publications
    • Journal Article
      Forum on immune digital twins: a meeting report.
      Laubenbacher R, Adler F, An G, Castiglione F, Eubank S, Fonseca LL, Glazier J, Helikar T, Jett-Tilton M, Kirschner D, Macklin P, Mehrad B, Moore B, Pasour V, Shmulevich I, Smith A, Voigt I, Yankeelov TE, Ziemssen T. NPJ Syst Biol Appl, 2024 Feb 16; 10 (1): 19 DOI:10.1038/s41540-024-00345-5
      PMID: 38365857
    • Journal Article
      A systematic efficacy analysis of tuberculosis treatment with BPaL-containing regimens using a multiscale modeling approach.
      Budak M, Via LE, Weiner DM, Barry CE, Nanda P, Michael G, Mdluli K, Kirschner D. CPT Pharmacometrics Syst Pharmacol, 2024 Feb 26; DOI:10.1002/psp4.13117
      PMID: 38404200
    • Preprint
      Development and Analysis of Multiscale Models for Tuberculosis: From Molecules to Populations.
      Nanda P, Budak M, Michael CT, Krupinsky K, Kirschner DE. 2023 Nov 15; DOI:10.1101/2023.11.13.566861
      PMID: 38014103
    • Journal Article
      Semi-automated colony-forming unit counting for biosafety level 3 laboratories.
      Janakiraman S, Engels S, Nanda P, Budak M, Greenstein T, Moraes MP, Aldridge BB, Kirschner DE. STAR Protoc, 2023 Sep 15; 4 (3): 102442 DOI:10.1016/j.xpro.2023.102442
      PMID: 37549035
    • Journal Article
      Optimizing tuberculosis treatment efficacy: Comparing the standard regimen with Moxifloxacin-containing regimens.
      Budak M, Cicchese JM, Maiello P, Borish HJ, White AG, Chishti HB, Tomko J, Frye LJ, Fillmore D, Kracinovsky K, Sakal J, Scanga CA, Lin PL, Dartois V, Linderman JJ, Flynn JL, Kirschner DE. PLoS Comput Biol, 2023 Jun; 19 (6): e1010823 DOI:10.1371/journal.pcbi.1010823
      PMID: 37319311
    • Journal Article
      Macrophages and neutrophils in lymph node granulomas from Mycobacterium tuberculosis -infected macaques have immunoregulatory phenotypes
      Mattila JT, Simonson AW, Krupinsky KC, Kirschner DE, Flynn JL. The Journal of Immunology, 2023 May 1; 210 (1_Supplement): 71.26 - 71.26. DOI:10.4049/jimmunol.210.supp.71.26
    • Journal Article
      Calibration methods to fit parameters within complex biological models.
      Nanda P, Kirschner DE. Front Appl Math Stat, 2023 9: DOI:10.3389/fams.2023.1256443
      PMID: 38222943
    • Journal Article
      Disease phenotypic and geospatial features vary across genetic lineages for Tuberculosis within Arkansas, 2010-2020.
      Renardy ME, Gillen C, Yang Z, Mukasa L, Bates J, Butler R, Kirschner DE. PLOS Glob Public Health, 2023 3 (2): e0001580 DOI:10.1371/journal.pgph.0001580
      PMID: 36963087