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Title: Computational and empirical studies predict Mycobacterium tuberculosis-specific T cells as a biomarker for infection outcome

Abstract

Identifying biomarkers for tuberculosis (TB) is an ongoing challenge in developing immunological correlates of infection outcome and protection. Biomarker discovery is also necessary for aiding design and testing of new treatments and vaccines. To effectively predict biomarkers for infection progression in any disease, including TB, large amounts of experimental data are required to reach statistical power and make accurate predictions. We took a two-pronged approach using both experimental and computational modeling to address this problem. We first collected 200 blood samples over a 2-year period from 28 non-human primates (NHP) infected with a low dose of Mycobacterium tuberculosis. We identified T cells and the cytokines that they were producing (single and multiple) from each sample along with monkey status and infection progression data. Machine learning techniques were used to interrogate the experimental NHP datasets without identifying any potential TB biomarker. In parallel, we used our extensive novel NHP datasets to build and calibrate a multi-organ computational model that combines what is occurring at the site of infection (e.g., lung) at a single granuloma scale with blood level readouts that can be tracked in monkeys and humans. We then generated a large in silico repository of in silico granulomas coupled tomore » lymph node and blood dynamics and developed an in silico tool to scale granuloma level results to a full host scale to identify what best predicts Mycobacterium tuberculosis (Mtb) infection outcomes. The analysis of in silico blood measures identifies Mtb-specific frequencies of effector T cell phenotypes at various time points post infection as promising indicators of infection outcome. As a result, we emphasize that pairing wetlab and computational approaches holds great promise to accelerate TB biomarker discovery.« less

Authors:
 [1];  [2];  [1];  [3];  [1];  [4];  [5];  [2];  [1]
  1. Univ. of Michigan Medical School, Ann Arbor, MI (United States)
  2. Univ. of Pittsburgh, Pittsburgh, PA (United States)
  3. Univ. of Maryland, College Park, MD (United States)
  4. Univ. of Pittsburgh of UPMC, Pittsburgh, PA (United States)
  5. Univ. of Michigan, Ann Arbor, MI (United States)
Publication Date:
Research Org.:
Univ. of Michigan, Ann Arbor, MI (United States)
Sponsoring Org.:
USDOE Office of Science (SC); National Energy Research Scientific Computing Center (NERSCC); National Science Foundation (Open Science Grid); National Institutes of Health (NIH)
OSTI Identifier:
1262275
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
PLoS Computational Biology (Online)
Additional Journal Information:
Journal Name: PLoS Computational Biology (Online); Journal Volume: 12; Journal Issue: 4; Journal ID: ISSN 1553-7358
Publisher:
Public Library of Science
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; immune-response; cynomolgus macaques; active tuberculosis; protective immunity; latent tuberculosis; granuloma-formation; antibody profiles; systems biology; dendritic cells; memory; T cells; granulomas; blood; tuberculosis; cytotoxic T cells; mycobacterium tuberculosis; biomarkers

Citation Formats

Marino, Simeone, Gideon, Hannah P., Gong, Chang, Mankad, Shawn, McCrone, John T., Lin, Philana Ling, Linderman, Jennifer J., Flynn, JoAnne L., and Kirschner, Denise E. Computational and empirical studies predict Mycobacterium tuberculosis-specific T cells as a biomarker for infection outcome. United States: N. p., 2016. Web. doi:10.1371/journal.pcbi.1004804.
Marino, Simeone, Gideon, Hannah P., Gong, Chang, Mankad, Shawn, McCrone, John T., Lin, Philana Ling, Linderman, Jennifer J., Flynn, JoAnne L., & Kirschner, Denise E. Computational and empirical studies predict Mycobacterium tuberculosis-specific T cells as a biomarker for infection outcome. United States. https://doi.org/10.1371/journal.pcbi.1004804
Marino, Simeone, Gideon, Hannah P., Gong, Chang, Mankad, Shawn, McCrone, John T., Lin, Philana Ling, Linderman, Jennifer J., Flynn, JoAnne L., and Kirschner, Denise E. Mon . "Computational and empirical studies predict Mycobacterium tuberculosis-specific T cells as a biomarker for infection outcome". United States. https://doi.org/10.1371/journal.pcbi.1004804. https://www.osti.gov/servlets/purl/1262275.
@article{osti_1262275,
title = {Computational and empirical studies predict Mycobacterium tuberculosis-specific T cells as a biomarker for infection outcome},
author = {Marino, Simeone and Gideon, Hannah P. and Gong, Chang and Mankad, Shawn and McCrone, John T. and Lin, Philana Ling and Linderman, Jennifer J. and Flynn, JoAnne L. and Kirschner, Denise E.},
abstractNote = {Identifying biomarkers for tuberculosis (TB) is an ongoing challenge in developing immunological correlates of infection outcome and protection. Biomarker discovery is also necessary for aiding design and testing of new treatments and vaccines. To effectively predict biomarkers for infection progression in any disease, including TB, large amounts of experimental data are required to reach statistical power and make accurate predictions. We took a two-pronged approach using both experimental and computational modeling to address this problem. We first collected 200 blood samples over a 2-year period from 28 non-human primates (NHP) infected with a low dose of Mycobacterium tuberculosis. We identified T cells and the cytokines that they were producing (single and multiple) from each sample along with monkey status and infection progression data. Machine learning techniques were used to interrogate the experimental NHP datasets without identifying any potential TB biomarker. In parallel, we used our extensive novel NHP datasets to build and calibrate a multi-organ computational model that combines what is occurring at the site of infection (e.g., lung) at a single granuloma scale with blood level readouts that can be tracked in monkeys and humans. We then generated a large in silico repository of in silico granulomas coupled to lymph node and blood dynamics and developed an in silico tool to scale granuloma level results to a full host scale to identify what best predicts Mycobacterium tuberculosis (Mtb) infection outcomes. The analysis of in silico blood measures identifies Mtb-specific frequencies of effector T cell phenotypes at various time points post infection as promising indicators of infection outcome. As a result, we emphasize that pairing wetlab and computational approaches holds great promise to accelerate TB biomarker discovery.},
doi = {10.1371/journal.pcbi.1004804},
journal = {PLoS Computational Biology (Online)},
number = 4,
volume = 12,
place = {United States},
year = {Mon Apr 11 00:00:00 EDT 2016},
month = {Mon Apr 11 00:00:00 EDT 2016}
}

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Works referenced in this record:

A methodology for performing global uncertainty and sensitivity analysis in systems biology
journal, September 2008

  • Marino, Simeone; Hogue, Ian B.; Ray, Christian J.
  • Journal of Theoretical Biology, Vol. 254, Issue 1
  • DOI: 10.1016/j.jtbi.2008.04.011

A hybrid multi-compartment model of granuloma formation and T cell priming in Tuberculosis
journal, July 2011

  • Marino, Simeone; El-Kebir, Mohammed; Kirschner, Denise
  • Journal of Theoretical Biology, Vol. 280, Issue 1
  • DOI: 10.1016/j.jtbi.2011.03.022

Biomarkers of tuberculosis: a research roadmap
journal, June 2013

  • Whitworth, Hilary S.; Aranday-Cortes, Elihu; Lalvani, Ajit
  • Biomarkers in Medicine, Vol. 7, Issue 3
  • DOI: 10.2217/bmm.13.53

The spectrum of latent tuberculosis: rethinking the biology and intervention strategies
journal, October 2009

  • Barry, Clifton E.; Boshoff, Helena I.; Dartois, Véronique
  • Nature Reviews Microbiology, Vol. 7, Issue 12
  • DOI: 10.1038/nrmicro2236

Missing value estimation methods for DNA microarrays
journal, June 2001


Multiscale Computational Modeling Reveals a Critical Role for TNF-α Receptor 1 Dynamics in Tuberculosis Granuloma Formation
journal, February 2011

  • Fallahi-Sichani, Mohammad; El-Kebir, Mohammed; Marino, Simeone
  • The Journal of Immunology, Vol. 186, Issue 6
  • DOI: 10.4049/jimmunol.1003299

Immunological consequences of intragenus conservation of Mycobacterium tuberculosis T-cell epitopes
journal, December 2014

  • Lindestam Arlehamn, Cecilia S.; Paul, Sinu; Mele, Federico
  • Proceedings of the National Academy of Sciences, Vol. 112, Issue 2
  • DOI: 10.1073/pnas.1416537112

Immunogenicity and protective efficacy of novel Mycobacterium tuberculosis antigens
journal, September 2013


Synergy between Individual TNF-Dependent Functions Determines Granuloma Performance for Controlling Mycobacterium tuberculosis Infection
journal, March 2009

  • Ray, J. Christian J.; Flynn, JoAnne L.; Kirschner, Denise E.
  • The Journal of Immunology, Vol. 182, Issue 6
  • DOI: 10.4049/jimmunol.0802297

Understanding Latent Tuberculosis: A Moving Target
journal, June 2010


Infection of Human Macrophages and Dendritic Cells with Mycobacterium tuberculosis Induces a Differential Cytokine Gene Expression That Modulates T Cell Response
journal, June 2001


Dynamics of T Lymphocyte Responses: Intermediates, Effectors, and Memory Cells
journal, October 2000


Mycobacterium tuberculosis -specific CD8 + T cells are functionally and phenotypically different between latent infection and active disease: Immunity to infection
journal, June 2013

  • Rozot, Virginie; Vigano, Selena; Mazza-Stalder, Jesica
  • European Journal of Immunology, Vol. 43, Issue 6
  • DOI: 10.1002/eji.201243262

The Immune Response in Tuberculosis
journal, March 2013


Identification of Tuberculosis Susceptibility Genes with Human Macrophage Gene Expression Profiles
journal, December 2008


A metabolic biosignature of early response to anti-tuberculosis treatment
journal, January 2014

  • Mahapatra, Sebabrata; Hess, Ann M.; Johnson, John L.
  • BMC Infectious Diseases, Vol. 14, Issue 1
  • DOI: 10.1186/1471-2334-14-53

Is the development of a new tuberculosis vaccine possible?
journal, September 2000

  • Kaufmann, Stefan H. E.
  • Nature Medicine, Vol. 6, Issue 9
  • DOI: 10.1038/79631

Transcriptional control of effector and memory CD8+ T cell differentiation
journal, October 2012

  • Kaech, Susan M.; Cui, Weiguo
  • Nature Reviews Immunology, Vol. 12, Issue 11
  • DOI: 10.1038/nri3307

Immunological Memory and Protective Immunity: Understanding Their Relation
journal, April 1996


C entral M emory and E ffector M emory T C ell S ubsets : Function, Generation, and Maintenance
journal, April 2004


The Immunological Footprint of Mycobacterium tuberculosis T-cell Epitope Recognition
journal, May 2012

  • Axelsson-Robertson, Rebecca; Magalhaes, Isabelle; Parida, Shreemanta K.
  • The Journal of Infectious Diseases, Vol. 205, Issue suppl_2
  • DOI: 10.1093/infdis/jis198

Interferon-  release assays for the diagnosis of active tuberculosis: a systematic review and meta-analysis
journal, September 2010


Extent of T cell receptor ligation can determine the functional differentiation of naive CD4+ T cells.
journal, November 1995

  • Constant, S.; Pfeiffer, C.; Woodard, A.
  • Journal of Experimental Medicine, Vol. 182, Issue 5
  • DOI: 10.1084/jem.182.5.1591

T cell fitness determined by signal strength
journal, March 2003

  • Gett, Amanda V.; Sallusto, Federica; Lanzavecchia, Antonio
  • Nature Immunology, Vol. 4, Issue 4
  • DOI: 10.1038/ni908

Identification of Probable Early-Onset Biomarkers for Tuberculosis Disease Progression
journal, September 2011


Penalized classification using Fisher's linear discriminant: Penalized Classification
journal, August 2011

  • Witten, Daniela M.; Tibshirani, Robert
  • Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 73, Issue 5
  • DOI: 10.1111/j.1467-9868.2011.00783.x

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
journal, August 2010


Dendritic Cell Trafficking and Antigen Presentation in the Human Immune Response to Mycobacterium tuberculosis
journal, June 2004


Macrophages and control of granulomatous inflammation in tuberculosis
journal, March 2011

  • Flynn, J. L.; Chan, J.; Lin, P. L.
  • Mucosal Immunology, Vol. 4, Issue 3
  • DOI: 10.1038/mi.2011.14

Modeling Tuberculosis in Nonhuman Primates
journal, September 2014


Predicting lymph node output efficiency using systems biology
journal, October 2013


Lessons learnt from the first efficacy trial of a new infant tuberculosis vaccine since BCG
journal, March 2013


Identifying control mechanisms of granuloma formation during M. tuberculosis infection using an agent-based model
journal, December 2004

  • Segovia-Juarez, Jose L.; Ganguli, Suman; Kirschner, Denise
  • Journal of Theoretical Biology, Vol. 231, Issue 3
  • DOI: 10.1016/j.jtbi.2004.06.031

The Role of Naive T Cell Precursor Frequency and Recruitment in Dictating Immune Response Magnitude
journal, April 2012


Immunology studies in non-human primate models of tuberculosis
journal, February 2015

  • Flynn, JoAnne L.; Gideon, Hannah P.; Mattila, Joshua T.
  • Immunological Reviews, Vol. 264, Issue 1
  • DOI: 10.1111/imr.12258

Sterilization of granulomas is common in active and latent tuberculosis despite within-host variability in bacterial killing
journal, December 2013

  • Lin, Philana Ling; Ford, Christopher B.; Coleman, M. Teresa
  • Nature Medicine, Vol. 20, Issue 1
  • DOI: 10.1038/nm.3412

A comparison of random vs. chemotaxis-driven contacts of T cells with dendritic cells during repertoire scanning
journal, February 2008

  • Riggs, Thomas; Walts, Adrienne; Perry, Nicolas
  • Journal of Theoretical Biology, Vol. 250, Issue 4
  • DOI: 10.1016/j.jtbi.2007.10.015

Immune biomarkers: the promises and pitfalls of personalized medicine
journal, March 2015

  • Willis, Joanna C. D.; Lord, Graham M.
  • Nature Reviews Immunology, Vol. 15, Issue 5
  • DOI: 10.1038/nri3820

Biomarkers of Inflammation, Immunosuppression and Stress Are Revealed by Metabolomic Profiling of Tuberculosis Patients
journal, July 2012


Mtb-Specific CD27low CD4 T Cells as Markers of Lung Tissue Destruction during Pulmonary Tuberculosis in Humans
journal, August 2012


Monitoring CD27 Expression to Evaluate Mycobacterium Tuberculosis Activity in HIV-1 Infected Individuals In Vivo
journal, November 2011


Variability in Tuberculosis Granuloma T Cell Responses Exists, but a Balance of Pro- and Anti-inflammatory Cytokines Is Associated with Sterilization
journal, January 2015


Microenvironments in Tuberculous Granulomas Are Delineated by Distinct Populations of Macrophage Subsets and Expression of Nitric Oxide Synthase and Arginase Isoforms
journal, June 2013

  • Mattila, Joshua T.; Ojo, Olabisi O.; Kepka-Lenhart, Diane
  • The Journal of Immunology, Vol. 191, Issue 2
  • DOI: 10.4049/jimmunol.1300113

18F-FDG PET/CT in tuberculosis: an early non-invasive marker of therapeutic response
journal, September 2012

  • Martinez, V.; Castilla-Lievre, M. A.; Guillet-Caruba, C.
  • The International Journal of Tuberculosis and Lung Disease, Vol. 16, Issue 9
  • DOI: 10.5588/ijtld.12.0010

Regularization Paths for Generalized Linear Models via Coordinate Descent
journal, January 2010

  • Friedman, Jerome; Hastie, Trevor; Tibshirani, Robert
  • Journal of Statistical Software, Vol. 33, Issue 1
  • DOI: 10.18637/jss.v033.i01

In search of a new paradigm for protective immunity to TB
journal, March 2014

  • Nunes-Alves, Cláudio; Booty, Matthew G.; Carpenter, Stephen M.
  • Nature Reviews Microbiology, Vol. 12, Issue 4
  • DOI: 10.1038/nrmicro3230

Plasma antibody profiles in non‐human primate tuberculosis
journal, January 2014

  • Ravindran, Resmi; Krishnan, Viswanathan V.; Dhawan, Rajeev
  • Journal of Medical Primatology, Vol. 43, Issue 2
  • DOI: 10.1111/jmp.12097

Loss of Receptor on Tuberculin-Reactive T-Cells Marks Active Pulmonary Tuberculosis
journal, August 2007


Immunological biomarkers of tuberculosis
journal, April 2011

  • Walzl, Gerhard; Ronacher, Katharina; Hanekom, Willem
  • Nature Reviews Immunology, Vol. 11, Issue 5
  • DOI: 10.1038/nri2960

Harnessing the Heterogeneity of T Cell Differentiation Fate to Fine-Tune Generation of Effector and Memory T Cells
journal, January 2014


Tuberculosis biomarkers discovery: developments, needs, and challenges
journal, April 2013


Exploratory Study on Plasma Immunomodulator and Antibody Profiles in Tuberculosis Patients
journal, June 2013

  • Ravindran, Resmi; Krishnan, Viswanathan V.; Khanum, Azra
  • Clinical and Vaccine Immunology, Vol. 20, Issue 8
  • DOI: 10.1128/CVI.00213-13

Quantitative Comparison of Active and Latent Tuberculosis in the Cynomolgus Macaque Model
journal, July 2009

  • Lin, P. L.; Rodgers, M.; Smith, L.
  • Infection and Immunity, Vol. 77, Issue 10
  • DOI: 10.1128/IAI.00592-09

Assessment of the novel T-cell activation marker–tuberculosis assay for diagnosis of active tuberculosis in children: a prospective proof-of-concept study
journal, October 2014


Origin of tuberculosis in the Paleolithic predicts unprecedented population growth and female resistance
journal, January 2020


Circulating Proteomic Signature of Early Death in Heart Failure Patients with Reduced Ejection Fraction
journal, January 2019

  • Cuvelliez, Marie; Vandewalle, Vincent; Brunin, Maxime
  • SSRN Electronic Journal
  • DOI: 10.2139/ssrn.3396013

Monitoring CD27 expression to evaluate Mycobacterium tuberculosis activity in HIV-1 infected individuals in vivo.
text, January 2011

  • Schuetz, Alexandra; Haule, Antelmo; Reither, Klaus
  • Universitätsbibliothek der Ludwig-Maximilians-Universität München
  • DOI: 10.5282/ubm/epub.15587

Homing of naive, memory and effector lymphocytes
journal, June 1993


Identifying control mechanisms of granuloma formation during M. tuberculosis infection using an agent-based model
journal, December 2004

  • Segovia-Juarez, Jose L.; Ganguli, Suman; Kirschner, Denise
  • Journal of Theoretical Biology, Vol. 231, Issue 3
  • DOI: 10.1016/j.jtbi.2004.06.031

A comparison of random vs. chemotaxis-driven contacts of T cells with dendritic cells during repertoire scanning
journal, February 2008

  • Riggs, Thomas; Walts, Adrienne; Perry, Nicolas
  • Journal of Theoretical Biology, Vol. 250, Issue 4
  • DOI: 10.1016/j.jtbi.2007.10.015

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
journal, August 2010


A hybrid multi-compartment model of granuloma formation and T cell priming in Tuberculosis
journal, July 2011

  • Marino, Simeone; El-Kebir, Mohammed; Kirschner, Denise
  • Journal of Theoretical Biology, Vol. 280, Issue 1
  • DOI: 10.1016/j.jtbi.2011.03.022

Immunogenicity and protective efficacy of novel Mycobacterium tuberculosis antigens
journal, September 2013


Novel biomarkers for paediatric tuberculosis
journal, October 2014


Macrophages and control of granulomatous inflammation in tuberculosis
journal, March 2011

  • Flynn, J. L.; Chan, J.; Lin, P. L.
  • Mucosal Immunology, Vol. 4, Issue 3
  • DOI: 10.1038/mi.2011.14

T cell fitness determined by signal strength
journal, March 2003

  • Gett, Amanda V.; Sallusto, Federica; Lanzavecchia, Antonio
  • Nature Immunology, Vol. 4, Issue 4
  • DOI: 10.1038/ni908

Sterilization of granulomas is common in active and latent tuberculosis despite within-host variability in bacterial killing
journal, December 2013

  • Lin, Philana Ling; Ford, Christopher B.; Coleman, M. Teresa
  • Nature Medicine, Vol. 20, Issue 1
  • DOI: 10.1038/nm.3412

Immunological biomarkers of tuberculosis
journal, April 2011

  • Walzl, Gerhard; Ronacher, Katharina; Hanekom, Willem
  • Nature Reviews Immunology, Vol. 11, Issue 5
  • DOI: 10.1038/nri2960

Transcriptional control of effector and memory CD8+ T cell differentiation
journal, October 2012

  • Kaech, Susan M.; Cui, Weiguo
  • Nature Reviews Immunology, Vol. 12, Issue 11
  • DOI: 10.1038/nri3307

Immune biomarkers: the promises and pitfalls of personalized medicine
journal, March 2015

  • Willis, Joanna C. D.; Lord, Graham M.
  • Nature Reviews Immunology, Vol. 15, Issue 5
  • DOI: 10.1038/nri3820

Extent of T cell receptor ligation can determine the functional differentiation of naive CD4+ T cells.
journal, November 1995

  • Constant, S.; Pfeiffer, C.; Woodard, A.
  • Journal of Experimental Medicine, Vol. 182, Issue 5
  • DOI: 10.1084/jem.182.5.1591

Missing value estimation methods for DNA microarrays
journal, June 2001


The Immunological Footprint of Mycobacterium tuberculosis T-cell Epitope Recognition
journal, May 2012

  • Axelsson-Robertson, Rebecca; Magalhaes, Isabelle; Parida, Shreemanta K.
  • The Journal of Infectious Diseases, Vol. 205, Issue suppl_2
  • DOI: 10.1093/infdis/jis198

Modeling Tuberculosis in Nonhuman Primates
journal, September 2014


Penalized classification using Fisher's linear discriminant: Penalized Classification
journal, August 2011

  • Witten, Daniela M.; Tibshirani, Robert
  • Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 73, Issue 5
  • DOI: 10.1111/j.1467-9868.2011.00783.x

Immunological Memory and Protective Immunity: Understanding Their Relation
journal, April 1996


Dynamics of T Lymphocyte Responses: Intermediates, Effectors, and Memory Cells
journal, October 2000


The Immune Response in Tuberculosis
journal, March 2013


Interferon-  release assays for the diagnosis of active tuberculosis: a systematic review and meta-analysis
journal, September 2010


Loss of Receptor on Tuberculin-Reactive T-Cells Marks Active Pulmonary Tuberculosis
journal, August 2007


Identification of Probable Early-Onset Biomarkers for Tuberculosis Disease Progression
journal, September 2011


Monitoring CD27 Expression to Evaluate Mycobacterium Tuberculosis Activity in HIV-1 Infected Individuals In Vivo
journal, November 2011


Identification of Tuberculosis Susceptibility Genes with Human Macrophage Gene Expression Profiles
journal, December 2008


Variability in Tuberculosis Granuloma T Cell Responses Exists, but a Balance of Pro- and Anti-inflammatory Cytokines Is Associated with Sterilization
journal, January 2015


Regularization Paths for Generalized Linear Models via Coordinate Descent
journal, January 2010

  • Friedman, Jerome; Hastie, Trevor; Tibshirani, Robert
  • Journal of Statistical Software, Vol. 33, Issue 1
  • DOI: 10.18637/jss.v033.i01

Biomarkers of tuberculosis: a research roadmap
journal, June 2013

  • Whitworth, Hilary S.; Aranday-Cortes, Elihu; Lalvani, Ajit
  • Biomarkers in Medicine, Vol. 7, Issue 3
  • DOI: 10.2217/bmm.13.53

Understanding Latent Tuberculosis: A Moving Target
journal, June 2010


Multiscale Computational Modeling Reveals a Critical Role for TNF-α Receptor 1 Dynamics in Tuberculosis Granuloma Formation
journal, February 2011

  • Fallahi-Sichani, Mohammad; El-Kebir, Mohammed; Marino, Simeone
  • The Journal of Immunology, Vol. 186, Issue 6
  • DOI: 10.4049/jimmunol.1003299

Infection of Human Macrophages and Dendritic Cells with Mycobacterium tuberculosis Induces a Differential Cytokine Gene Expression That Modulates T Cell Response
journal, June 2001


Dendritic Cell Trafficking and Antigen Presentation in the Human Immune Response to Mycobacterium tuberculosis
journal, June 2004


Works referencing / citing this record:

A Multi-Compartment Hybrid Computational Model Predicts Key Roles for Dendritic Cells in Tuberculosis Infection
journal, October 2016


The Role of Dimensionality in Understanding Granuloma Formation
journal, November 2018


CD 4 CD 8 Double Positive T cell responses during Mycobacterium tuberculosis infection in cynomolgus macaques
journal, February 2019

  • Diedrich, Collin Richard; Gideon, Hannah Priyadarshini; Rutledge, Tara
  • Journal of Medical Primatology, Vol. 48, Issue 2
  • DOI: 10.1111/jmp.12399

Dynamic balance of pro- and anti-inflammatory signals controls disease and limits pathology
journal, August 2018

  • Cicchese, Joseph M.; Evans, Stephanie; Hult, Caitlin
  • Immunological Reviews, Vol. 285, Issue 1
  • DOI: 10.1111/imr.12671

Addressing diversity in tuberculosis using multidimensional approaches
journal, June 2018

  • Lerm, M.; Dockrell, H. M.
  • Journal of Internal Medicine, Vol. 284, Issue 2
  • DOI: 10.1111/joim.12776

PET CT Identifies Reactivation Risk in Cynomolgus Macaques with Latent M. tuberculosis
journal, July 2016


Comparing efficacies of moxifloxacin, levofloxacin and gatifloxacin in tuberculosis granulomas using a multi-scale systems pharmacology approach
journal, August 2017


Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment
journal, January 2019

  • Norton, Kerri-Ann; Gong, Chang; Jamalian, Samira
  • Processes, Vol. 7, Issue 1
  • DOI: 10.3390/pr7010037

Deletion of TGF-β1 Increases Bacterial Clearance by Cytotoxic T Cells in a Tuberculosis Granuloma Model
journal, December 2017

  • Warsinske, Hayley C.; Pienaar, Elsje; Linderman, Jennifer J.
  • Frontiers in Immunology, Vol. 8
  • DOI: 10.3389/fimmu.2017.01843

Heterogeneity in tuberculosis
journal, July 2017

  • Cadena, Anthony M.; Fortune, Sarah M.; Flynn, JoAnne L.
  • Nature Reviews Immunology, Vol. 17, Issue 11
  • DOI: 10.1038/nri.2017.69

Integrating Non-human Primate, Human, and Mathematical Studies to Determine the Influence of BCG Timing on H56 Vaccine Outcomes
journal, August 2018


A computational model tracks whole-lung Mycobacterium tuberculosis infection and predicts factors that inhibit dissemination
journal, May 2020


CD 4 CD 8 Double Positive T cell responses during Mycobacterium tuberculosis infection in cynomolgus macaques
journal, February 2019

  • Diedrich, Collin Richard; Gideon, Hannah Priyadarshini; Rutledge, Tara
  • Journal of Medical Primatology, Vol. 48, Issue 2
  • DOI: 10.1111/jmp.12399

Comparing efficacies of moxifloxacin, levofloxacin and gatifloxacin in tuberculosis granulomas using a multi-scale systems pharmacology approach
journal, August 2017


Do Xpert MTB/RIF Cycle Threshold Values Provide Information about Patient Delays for Tuberculosis Diagnosis?
journal, September 2016


Integrating Non-human Primate, Human, and Mathematical Studies to Determine the Influence of BCG Timing on H56 Vaccine Outcomes
journal, August 2018