Evidence map›Paper›PMID 30397270›Full record

ReviewNature reviews. Microbiology2019

Types and origins of bacterial membrane vesicles.

Masanori Toyofuku, Nobuhiko Nomura, Leo Eberl

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 761 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
761citing papers in PubMed, 1 pooled it
44.6field-weighted citation impact, top 1% 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

761 citing papers in PubMed, 1 synthesis or guideline pooled it, 1,242 citations in OpenAlex.

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  19. Towards a Scalable Production ofInternational journal of molecular sciences · 2026
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701 more citing papers are in PubMed but not listed here.

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

3 authors at 2 institutions in 2 countries.

Masanori ToyofukuDepartment of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan. toyofuku.masanori.gf@u.tsukuba.ac.jp.
Nobuhiko NomuraDepartment of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan.
Leo EberlDepartment of Plant and Microbial Biology, University of Zurich, Zurich, Switzerland. leberl@botinst.uzh.ch.ORCID http://orcid.org/0000-0002-7241-0864
University of Tsukuba · JPUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most bacteria release membrane vesicles (MVs) that contain specific cargo molecules and have diverse functions, including the transport of virulence factors, DNA transfer, interception of bacteriophages, antibiotics and eukaryotic host defence factors, cell detoxification and bacterial communication. MVs not only are abundant in nature but also show great promise for applications in biomedicine and nanotechnology. MVs were first discovered to originate from controlled blebbing of the outer membrane of Gram-negative bacteria and are therefore often called outer-membrane vesicles (OMVs). However, recent work has shown that Gram-positive bacteria can produce MVs, that different types of MVs besides OMVs exist and that, in addition to membrane blebbing, MVs can also be formed by endolysin-triggered cell lysis. In this Review, we provide an overview of the structures and compositions of the various vesicle types and discuss novel formation routes, which may lead to distinct vesicle types that serve particular functions.

Indexed as

Anti-Bacterial AgentsBacterial Outer MembraneBacterial ProteinsBiological TransportCytoplasmic VesiclesEndopeptidasesGram-Negative BacteriaGram-Positive BacteriaAnti-Bacterial AgentsBacterial ProteinsendolysinEndopeptidases

Identifiers

PMID30397270
OpenAlexW2899663373

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.