Evidence map›Paper›PMID 32298242›Full record

ArticleThe Journal of clinical investigation2020

Macrophages use a bet-hedging strategy for antimicrobial activity in phagolysosomal acidification.

Quigly Dragotakes, Kaitlin M Stouffer, Man Shun Fu, Yehonatan Sella, Christine Youn, Olivia Insun Yoon, Carlos M De Leon-Rodriguez, Joudeh B Freij, Aviv Bergman, Arturo Casadevall

Abstract read
In one paragraph

Article in The Journal of clinical investigation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Polymeric Nanomaterials for Atherosclerosis Diagnosis and Treatment.Polymer science & technology (Washington, D.C.) · 2025
    Review
  5. Review
  6. Article
  7. Article
  8. Free Energy Barriers for Passive Drug Transport through theInternational journal of molecular sciences · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. ReplicativebioRxiv : the preprint server for biology · 2023
    Article
  13. Article
  14. Article
  15. Persistence ofFrontiers in cellular and infection microbiology · 2022
    Article
  16. microLife · 2022
    Article
  17. Real-time visualization of phagosomal pH manipulation byFrontiers in cellular and infection microbiology · 2022
    Article
  18. Bet-hedging in innate and adaptive immune systems.Evolution, medicine, and public health · 2022
    Article
  19. Article
  20. Article
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

10 authors.

Quigly DragotakesDepartment of Molecular Microbiology and Immunology, Johns Hopkins School of Public Health, Baltimore, Maryland, USA.
Kaitlin M StoufferDepartment of Molecular Microbiology and Immunology, Johns Hopkins School of Public Health, Baltimore, Maryland, USA.
Man Shun FuDepartment of Molecular Microbiology and Immunology, Johns Hopkins School of Public Health, Baltimore, Maryland, USA.
Yehonatan SellaDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, USA.
Christine YounDepartment of Dermatology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Olivia Insun YoonJohns Hopkins University, Krieger School of Arts and Sciences, Baltimore, Maryland, USA.
Carlos M De Leon-RodriguezDepartment of Molecular Microbiology and Immunology, Johns Hopkins School of Public Health, Baltimore, Maryland, USA.
Joudeh B FreijDepartment of Molecular Microbiology and Immunology, Johns Hopkins School of Public Health, Baltimore, Maryland, USA.
Aviv BergmanDepartment of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, New York, USA.
Arturo CasadevallDepartment of Molecular Microbiology and Immunology, Johns Hopkins School of Public Health, Baltimore, Maryland, USA.

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007309 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI COX, ANDREA L · 1985 to 2019
$43.2M
Medical Scientist Training ProgramT32GM136577 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI ANDREA L COX · 2020 to 2026
$13.4M
Synergy of Host Defense Mechanisms in the LungR01HL059842 · NHLBI · YESHIVA UNIVERSITY · PI CASADEVALL, ARTURO · 1997 to 2023
$7.4M
Biology of Fungal MelaninR01AI052733 · NIAID · YESHIVA UNIVERSITY · PI CASADEVALL, ARTURO · 2003 to 2019
$6.6M
PROTECTIVE ANTIBODIES FOR CRYPTOCOCCAL INFECTIONSR01AI033774 · NIAID · YESHIVA UNIVERSITY · PI CASADEVALL, ARTURO · 1994 to 2014
$5.6M
Molecular Characterization of C. neoformans AntibodiesR37AI033142 · NIAID · JOHNS HOPKINS UNIVERSITY · PI CASADEVALL, ARTURO · 2007 to 2016
$3.9M
NHLBI NIH HHS R01 HL059842NIAID NIH HHS R01 AI033774NIAID NIH HHS R01 AI052733NIAID NIH HHS R37 AI033142NIGMS NIH HHS T32 GM007309NIGMS NIH HHS T32 GM136577
6 · The paper itself

Abstract

Microbial ingestion by a macrophage results in the formation of an acidic phagolysosome but the host cell has no information on the pH susceptibility of the ingested organism. This poses a problem for the macrophage and raises the fundamental question of how the phagocytic cell optimizes the acidification process to prevail. We analyzed the dynamical distribution of phagolysosomal pH in murine and human macrophages that had ingested live or dead Cryptococcus neoformans cells, or inert beads. Phagolysosomal acidification produced a range of pH values that approximated normal distributions, but these differed from normality depending on ingested particle type. Analysis of the increments of pH reduction revealed no forbidden ordinal patterns, implying that the phagosomal acidification process was a stochastic dynamical system. Using simulation modeling, we determined that by stochastically acidifying a phagolysosome to a pH within the observed distribution, macrophages sacrificed a small amount of overall fitness to gain the benefit of reduced variation in fitness. Hence, chance in the final phagosomal pH introduces unpredictability to the outcome of the macrophage-microbe, which implies a bet-hedging strategy that benefits the macrophage. While bet hedging is common in biological systems at the organism level, our results show its use at the organelle and cellular level.

Indexed as

AnimalsCell LineCryptococcosisCryptococcus neoformansFemaleHumansHydrogen-Ion ConcentrationMacrophagesMicePhagosomesCell BiologyFungal infectionsImmunologyInnate immunityMacrophages

Identifiers

PMID32298242
PMCPMC7346583

What OpenQuestion holds

Textmetadata
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.