Evidence map›Paper›PMID 31381766›Full record

ReviewPathogens and disease2019

The current state of animal models and genomic approaches towards identifying and validating molecular determinants of Mycobacterium tuberculosis infection and tuberculosis disease.

Allison N Bucsan, Smriti Mehra, Shabaana A Khader, Deepak Kaushal

Abstract readReview
In one paragraph

Review in Pathogens and disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Therapeutic remodeling of the tuberculosis granuloma with 1-methyl-D-tryptophan enhances CD8Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Review
  4. Article
  5. Pathogens (Basel, Switzerland) · 2025
    Review
  6. Article
  7. Model systems to studyFrontiers in cellular and infection microbiology · 2025
    Review
  8. Experimental dissection of tuberculosis protective immunity: a human perspective.Frontiers in cellular and infection microbiology · 2025
    Review
  9. Immunopathology of PulmonaryInternational journal of molecular sciences · 2024
    Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Review
  15. Review
  16. Article
  17. Review
  18. Article
  19. Spatial Resolution ofFrontiers in immunology · 2022
    Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Allison N BucsanTulane Center for Tuberculosis Research, Covington, LA, USA.
Smriti MehraTulane National Primate Research Center, Covington, LA, USA.
Shabaana A KhaderWashington University in St Louis, St Louis, MO, USA.
Deepak KaushalTulane Center for Tuberculosis Research, Covington, LA, USA.

Funding

Tulane NPRC SPF Sheltered Outdoor Enclosure ExpansionP51OD011104 · OD · TULANE UNIVERSITY OF LOUISIANA · PI L Lee HAMM · 2012 to 2026
$142.4M
The Southwest National Primate Research Center Supplement- Infrastructure improvements of ABSL2 holding areasP51OD011133 · OD · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI Larry S. Schlesinger · 2012 to 2026
$129.7M
ROLE OF INDUCIBLE BRONCHUS ASSOCIATED LYMPHOID TISSUE IN LATENT TUBERCULOSISR01AI111914 · NIAID · WASHINGTON UNIVERSITY · PI KAUSHAL, DEEPAK, KHADER, SHABAANA A. · 2015 to 2025
$11.1M
Myeloid and lymphoid immunity-specific mechanisms of IDO mediated immunosuppression and its reversal, during TBR01AI134245 · NIAID · TULANE UNIVERSITY OF LOUISIANA · PI Smriti Mehra · 2018 to 2026
$6.2M
Immune Correlates of Protection from TBR01AI134240 · NIAID · TULANE UNIVERSITY OF LOUISIANA · PI KAUSHAL, DEEPAK · 2017 to 2022
$4.8M
Perturbation of antigen-specific T cell responses in latent TB/SIV co-infectionR01AI111943 · NIAID · TULANE UNIVERSITY OF LOUISIANA · PI KAUSHAL, DEEPAK, RENGARAJAN, JYOTHI · 2015 to 2019
$3.9M
COMMON IMMUNE CORRELATES OF RISK OF TB DISEASE IN ANIMAL MODELS AND HUMANSR01AI123780 · NIAID · WASHINGTON UNIVERSITY · PI KAUSHAL, DEEPAK, KHADER, SHABAANA A. · 2016 to 2019
$2.9M
NIAID NIH HHS R01 AI111914NIAID NIH HHS R01 AI111943NIAID NIH HHS R01 AI123780NIAID NIH HHS R01 AI134240NIAID NIH HHS R01 AI134245NIH HHS P51 OD011104NIH HHS P51 OD011133
6 · The paper itself

Abstract

Animal models are important in understanding both the pathogenesis of and immunity to tuberculosis (TB). Unfortunately, we are beginning to understand that no animal model perfectly recapitulates the human TB syndrome, which encompasses numerous different stages. Furthermore, Mycobacterium tuberculosis infection is a very heterogeneous event at both the levels of pathogenesis and immunity. This review seeks to establish the current understanding of TB pathogenesis and immunity, as validated in the animal models of TB in active use today. We especially focus on the use of modern genomic approaches in these models to determine the mechanism and the role of specific molecular pathways. Animal models have significantly enhanced our understanding of TB. Incorporation of contemporary technologies such as single cell transcriptomics, high-parameter flow cytometric immune profiling, proteomics, proteomic flow cytometry and immunocytometry into the animal models in use will further enhance our understanding of TB and facilitate the development of treatment and vaccination strategies.

Indexed as

Disease Models, AnimalHost-Pathogen InteractionsAnimalsCytological TechniquesGene Expression ProfilingMycobacterium tuberculosisProteomicsTuberculosisanimal modelsMycobacterium tuberculosistranslation

Identifiers

PMID31381766
PMCPMC6687098

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.