ArticleFrontiers in microbiology2016
Quantifying Limits on Replication, Death, and Quiescence of Mycobacterium tuberculosis in Mice.
Article in Frontiers in microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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.
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.
Who cites it
18 citing papers in PubMed, 19 citations in OpenAlex.
- Monocytic niches escape T cell surveillance and promote Mycobacterium tuberculosis persistence in lymph nodes.Immunity · 2026Article
- Immortal genome assumption significantly underestimates replication and death rates ofMicrobiology spectrum · 2026Article
- Immortal genome assumption significantly underestimates replication and death rates ofbioRxiv : the preprint server for biology · 2026Article
- BCG vaccination reduces the rate of Mycobacterium tuberculosis dissemination between murine lungs.Research square · 2026Article
- Adaptive immunity shapes baseline physiology ofbioRxiv : the preprint server for biology · 2026Article
- BCG vaccination reduces the rate of Mycobacterium tuberculosis dissemination between murine lungs.bioRxiv : the preprint server for biology · 2026Article
- Mathematical modeling suggests heterogeneous replication of Mycobacterium tuberculosis in rabbits.PLoS computational biology · 2024Article
- Mathematical modeling suggests heterogeneous replication ofbioRxiv : the preprint server for biology · 2024Article
- A brief overview of mathematical modeling of the within-host dynamics of Mycobacterium tuberculosis.Frontiers in applied mathematics and statistics · 2024Article
- Heterogeneity in immune cell composition is associated withFrontiers in immunology · 2024Article
- Long-term effects of prenatal arsenic exposure from gestational day 9 to birth on lung, heart, and immune outcomes in the C57BL/6 mouse model.Toxicology letters · 2023Article
- Mathematical Modeling to Guide Experimental Design: T Cell Clustering as a Case Study.Bulletin of mathematical biology · 2022Article
- Extremely lethal and hypervirulentEmerging microbes & infections · 2021Article
- Mycobacterium tuberculosis precursor rRNA as a measure of treatment-shortening activity of drugs and regimens.Nature communications · 2021Article
- Ultra-low Dose Aerosol Infection of Mice with Mycobacterium tuberculosis More Closely Models Human Tuberculosis.Cell host & microbe · 2021Article
- The Many Hosts of Mycobacteria 8 (MHM8): A conference report.Tuberculosis (Edinburgh, Scotland) · 2020Review
- The Rate of CD4 T Cell Entry into the Lungs during Mycobacterium tuberculosis Infection Is Determined by Partial and Opposing Effects of Multiple Chemokine Receptors.Infection and immunity · 2019Article
- Linking Individual Natural History to Population Outcomes in Tuberculosis.The Journal of infectious diseases · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
When an individual is exposed to Mycobacterium tuberculosis (Mtb) three outcomes are possible: bacterial clearance, active disease, or latent infection. It is generally believed that most individuals exposed to Mtb become latently infected and carry the mycobacteria for life. How Mtb is maintained during this latent infection remains largely unknown. During an Mtb infection in mice, there is a phase of rapid increase in bacterial numbers in the murine lungs within the first 3 weeks, and then bacterial numbers either stabilize or increase slowly over the period of many months. It has been debated whether the relatively constant numbers of bacteria in the chronic infection result from latent (dormant, quiescent), non-replicating bacteria, or whether the observed Mtb cell numbers are due to balance between rapid replication and death. A recent study of mice, infected with a Mtb strain carrying an unstable plasmid, showed that during the chronic phase, Mtb was replicating at significant rates. Using experimental data from this study and mathematical modeling we investigated the limits of the rates of bacterial replication, death, and quiescence during Mtb infection of mice. First, we found that to explain the data the rates of bacterial replication and death could not be constant and had to decrease with time since infection unless there were large changes in plasmid segregation probability over time. While a decrease in the rate of Mtb replication with time since infection was expected due to depletion of host's resources, a decrease in the Mtb death rate was counterintuitive since Mtb-specific immune response, appearing in the lungs 3-4 weeks after infection, should increase removal of bacteria. Interestingly, we found no significant correlation between estimated rates of Mtb replication and death suggesting the decline in these rates was driven by independent mechanisms. Second, we found that the data could not be explained by assuming that bacteria do not die, suggesting that some removal of bacteria from lungs of these mice had to occur even though the total bacterial counts in these mice always increased over time. Third and finally, we showed that to explain the data the majority of bacterial cells (at least ~60%) must be replicating in the chronic phase of infection further challenging widespread belief of nonreplicating Mtb in latency. Our predictions were robust to some changes in the structure of the model, for example, when the loss of plasmid-bearing cells was mainly due to high fitness cost of the plasmid. Further studies should determine if more mechanistic models for Mtb dynamics are also able to accurately explain these data.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.