Evidence map›Paper›PMID 38995971›Full record

ArticlePLoS computational biology2024

Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma.

Alexa Petrucciani, Alexis Hoerter, Leigh Kotze, Nelita Du Plessis, Elsje Pienaar

Abstract read
In one paragraph

Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. 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

5 authors.

Alexa PetruccianiWeldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America.
Alexis HoerterWeldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America.
Leigh KotzeDSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medical and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Nelita Du PlessisDSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medical and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Elsje PienaarWeldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America.ORCID 0000-0002-5408-8795

Funding

IMMUNE MECHANISMS OF PROTECTION AGAINST MYCOBACTERIUM TUBERCULOSIS CENTER (IMPAC-TB) - SARS-CoV-2 RELATED RESEARCH75N93019C00070 · NIAID · SEATTLE CHILDREN'S HOSPITAL · PI URDAHL, KEVIN · 2019 to 2025
$86.6M
NRSA Training CoreTL1TR002531 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI FOTI, DANIEL JUSTIN, HURLEY, THOMAS D. · 2018 to 2022
$2.5M
NCATS NIH HHS TL1 TR002531NIAID NIH HHS 75N93019C00070
6 · The paper itself

Abstract

Tuberculosis (TB) remains a global public health threat. Understanding the dynamics of host-pathogen interactions within TB granulomas will assist in identifying what leads to the successful elimination of infection. In vitro TB models provide a controllable environment to study these granuloma dynamics. Previously we developed a biomimetic 3D spheroid granuloma model that controls bacteria better than a traditional monolayer culture counterpart. We used agent-based simulations to predict the mechanistic reason for this difference. Our calibrated simulations were able to predict heterogeneous bacterial dynamics that are consistent with experimental data. In one group of simulations, spheroids are found to have higher macrophage activation than their traditional counterparts, leading to better bacterial control. This higher macrophage activation in the spheroids was not due to higher counts of activated T cells, instead fewer activated T cells were able to activate more macrophages due to the proximity of these cells to each other within the spheroid. In a second group of simulations, spheroids again have more macrophage activation but also more T cell activation, specifically CD8+ T cells. This higher level of CD8+ T cell activation is predicted to be due to the proximity of these cells to the cells that activate them. Multiple mechanisms of control were predicted. Simulations removing individual mechanisms show that one group of simulations has a CD4+ T cell dominant response, while the other has a mixed/CD8+ T cell dominant response. Lastly, we demonstrated that in spheroids the initial structure and movement rules work synergistically to reduce bacterial load. These findings provide valuable insights into how the structural complexity of in vitro models impacts immune responses. Moreover, our study has implications for engineering more physiologically relevant in vitro models and advancing our understanding of TB pathogenesis and potential therapeutic interventions.

Indexed as

Bacterial LoadGranulomaMycobacterium tuberculosisCD8-Positive T-LymphocytesComputational BiologyComputer SimulationHost-Pathogen InteractionsHumansLymphocyte ActivationMacrophage ActivationMacrophagesModels, BiologicalSpheroids, CellularTuberculosis

Identifiers

PMID38995971
PMCPMC11288457

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.