Evidence map›Paper›PMID 34775384›Full record

ArticleJournal of innate immunity2022

Innate Immune Training with Bacterial Extracts Enhances Lung Macrophage Recruitment to Protect from Betacoronavirus Infection.

Manuel Salzmann, Patrick Haider, Christoph Kaun, Mira Brekalo, Boris Hartmann, Theresia Lengheimer, Rebecca Pichler, Thomas Filip, Sophia Derdak, Bruno Podesser and 5 more

Open access · goldAbstract read
In one paragraph

Article in Journal of innate immunity, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.5field-weighted citation impact, top 6% of its field
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

14 citing papers in PubMed, 30 citations in OpenAlex.

  1. Review
  2. Article
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  5. Review
  6. Article
  7. Article
  8. Diverging patterns in innate immunity against respiratory viruses during a lifetime: lessons from the young and the old.European respiratory review : an official journal of the European Respiratory Society · 2024
    Review
  9. Article
  10. The OM-85 bacterial lysate: a new tool against SARS-CoV-2?Multidisciplinary respiratory medicine · 2023
    Article
  11. Article
  12. Pharmacologic modulation of intracellular NaProceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  13. Article
  14. 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

15 authors at 3 institutions in 1 country.

Manuel SalzmannDepartment of Internal Medicine II/Cardiology, Medical University of Vienna, Vienna, Austria.
Patrick HaiderDepartment of Internal Medicine II/Cardiology, Medical University of Vienna, Vienna, Austria.
Christoph KaunDepartment of Internal Medicine II/Cardiology, Medical University of Vienna, Vienna, Austria.
Mira BrekaloDepartment of Internal Medicine II/Cardiology, Medical University of Vienna, Vienna, Austria.
Boris HartmannInstitute of Veterinary Disease Control, AGES, Mödling, Vienna, Austria.
Theresia LengheimerCenter for Biomedical Research, Medical University of Vienna, Vienna, Austria.
Rebecca PichlerCenter for Biomedical Research, Medical University of Vienna, Vienna, Austria.
Thomas FilipCenter for Biomedical Research, Medical University of Vienna, Vienna, Austria.
Sophia DerdakMedical University of Vienna, Core Facilities, Vienna, Austria.
Bruno PodesserLudwig Boltzmann Cluster for Cardiovascular Research, Vienna, Austria.
Christian HengstenbergDepartment of Internal Medicine II/Cardiology, Medical University of Vienna, Vienna, Austria.
Walter S SpeidlDepartment of Internal Medicine II/Cardiology, Medical University of Vienna, Vienna, Austria.
Johann WojtaDepartment of Internal Medicine II/Cardiology, Medical University of Vienna, Vienna, Austria.
Roberto PlasenzottiCenter for Biomedical Research, Medical University of Vienna, Vienna, Austria.
Philipp J HohensinnerLudwig Boltzmann Cluster for Cardiovascular Research, Vienna, Austria.
Medical University of Vienna · ATLudwig Boltzmann Institute for Cardiovascular Research · ATUniversity of Veterinary Medicine Vienna · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Training of the innate immune system with orally ingested bacterial extracts was demonstrated to have beneficial effects on infection clearance and disease outcome. The aim of our study was to identify cellular and molecular processes responsible for these immunological benefits. We used a murine coronavirus (MCoV) A59 mouse model treated with the immune activating bacterial extract Broncho-Vaxom (BV) OM-85. Tissue samples were analysed with qPCR, RNA sequencing, histology, and flow cytometry. After BV OM-85 treatment, interstitial macrophages accumulated in lung tissue leading to a faster response of type I interferon (IFN) signalling after MCoV infection resulting in overall lung tissue protection. Moreover, RNA sequencing showed that lung tissue from mice receiving BV OM-85 resembled an intermediate stage between healthy and viral infected lung tissue at day 4, indicating a faster return to normal tissue homoeostasis. The pharmacologic effect was mimicked by adoptively transferring naive lung macrophages into lungs from recipient mice before virus infection. The beneficial effect of BV OM-85 was abolished when inhibiting initial type I IFN signalling. Overall, our data suggest that BV OM-85 enhances lung macrophages allowing for a faster IFN response towards a viral challenge as part of the oral-induced innate immune system training.

Indexed as

Adjuvants, ImmunologicBetacoronavirusAnimalsBacteriaImmunity, InnateLungMacrophagesMiceAdjuvants, ImmunologicBacterial extractMacrophageMouse coronavirusTrained immunity

Identifiers

PMID34775384
PMCPMC9059017
OpenAlexW3211714291

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.