Evidence map›Paper›PMID 37208676›Full record

ArticleJournal of nanobiotechnology2023

Detoxified synthetic bacterial membrane vesicles as a vaccine platform against bacteria and SARS-CoV-2.

Kyong-Su Park, Kristina Svennerholm, Rossella Crescitelli, Cecilia Lässer, Inta Gribonika, Mickael Andersson, Jonas Boström, Hanna Alalam, Ali M Harandi, Anne Farewell and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of nanobiotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

15 citing papers in PubMed, 23 citations in OpenAlex.

  1. Virulence · 2026
    Review
  2. Targeting Outer Membrane Vesicles ofJournal of microbiology and biotechnology · 2026
    Review
  3. Review
  4. Article
  5. Review
  6. Development of a Promising Bivalent Vaccine AgainstExploration (Beijing, China) · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. 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

11 authors at 2 institutions in 2 countries.

Kyong-Su ParkKrefting Research Centre, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. kyong-su.park@gu.se.
Kristina SvennerholmDepartment of Anesthesiology and Intensive Care Medicine, Institute of Clinical Science, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Rossella CrescitelliDepartment of Surgery, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Cecilia LässerKrefting Research Centre, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Inta GribonikaDepartment of Microbiology and Immunology, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden.
Mickael AnderssonDepartment of Chemistry and Molecular Biology, Centre for Antibiotic Resistance, University of Gothenburg, Gothenburg, Sweden.
Jonas BoströmDepartment of Chemistry and Molecular Biology, Centre for Antibiotic Resistance, University of Gothenburg, Gothenburg, Sweden.
Hanna AlalamDepartment of Chemistry and Molecular Biology, Centre for Antibiotic Resistance, University of Gothenburg, Gothenburg, Sweden.
Ali M HarandiDepartment of Microbiology and Immunology, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden.
Anne FarewellDepartment of Chemistry and Molecular Biology, Centre for Antibiotic Resistance, University of Gothenburg, Gothenburg, Sweden.
Jan LötvallKrefting Research Centre, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. jan.lotvall@gu.se.
University of Gothenburg · SEBritish Columbia Children's Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of vaccines based on outer membrane vesicles (OMV) that naturally bud off from bacteria is an evolving field in infectious diseases. However, the inherent inflammatory nature of OMV limits their use as human vaccines. This study employed an engineered vesicle technology to develop synthetic bacterial vesicles (SyBV) that activate the immune system without the severe immunotoxicity of OMV. SyBV were generated from bacterial membranes through treatment with detergent and ionic stress. SyBV induced less inflammatory responses in macrophages and in mice compared to natural OMV. Immunization with SyBV or OMV induced comparable antigen-specific adaptive immunity. Specifically, immunization with Pseudomonas aeruginosa-derived SyBV protected mice against bacterial challenge, and this was accompanied by significant reduction in lung cell infiltration and inflammatory cytokines. Further, immunization with Escherichia coli-derived SyBV protected mice against E. coli sepsis, comparable to OMV-immunized group. The protective activity of SyBV was driven by the stimulation of B-cell and T-cell immunity. Also, SyBV were engineered to display the SARS-CoV-2 S1 protein on their surface, and these vesicles induced specific S1 protein antibody and T-cell responses. Collectively, these results demonstrate that SyBV may be a safe and efficient vaccine platform for the prevention of bacterial and viral infections.

Indexed as

BacteremiaCOVID-19Escherichia coli InfectionsVaccinesAnimalsAntibodies, BacterialBacteriaBacterial Outer Membrane ProteinsEscherichia coliHumansMiceSARS-CoV-2Antibodies, BacterialBacterial Outer Membrane ProteinsVaccinesCOVID-19Outer membrane vesiclesPulmonary inflammationSepsisSynthetic bacterial vesiclesVaccine

Identifiers

PMID37208676
PMCPMC10196325
OpenAlexW4377139575

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.