Evidence map›Paper›PMID 28204504›Full record

ReviewFEMS microbiology reviews2016

Profiling the metabolic signals involved in chemical communication between microbes using imaging mass spectrometry.

Nikolas M Stasulli, Elizabeth A Shank

Abstract readReview
In one paragraph

Review in FEMS microbiology reviews, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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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

2 authors.

Nikolas M StasulliDepartment of Biology, University of North Carolina at Chapel Hill, NC, USA.
Elizabeth A ShankDepartment of Biology, University of North Carolina at Chapel Hill, NC, USA.

Funding

SEEDING POSTDOCTORAL INNOVATORS IN RESEARCH &EDUCATIONK12GM000678 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DONALD T LYSLE, Kathryn Joanna Reissner · 1999 to 2026
$30.9M
Using Co-culture and Bioinformatics to Discover New Antibiotic BioactivitiesR01GM112981 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SHANK, ELIZABETH ANNE · 2016 to 2020
$1.4M
NIGMS NIH HHS K12 GM000678NIGMS NIH HHS R01 GM112981
6 · The paper itself

Abstract

The ability of microbes to secrete bioactive chemical signals into their environment has been known for over a century. However, it is only in the last decade that imaging mass spectrometry has provided us with the ability to directly visualize the spatial distributions of these microbial metabolites. This technology involves collecting mass spectra from multiple discrete locations across a biological sample, yielding chemical ‘maps’ that simultaneously reveal the distributions of hundreds of metabolites in two dimensions. Advances in microbial imaging mass spectrometry summarized here have included the identification of novel strain- or coculture-specific compounds, the visualization of biotransformation events (where one metabolite is converted into another by a neighboring microbe), and the implementation of a method to reconstruct the 3D subsurface distributions of metabolites, among others. Here we review the recent literature and discuss how imaging mass spectrometry has spurred novel insights regarding the chemical consequences of microbial interactions.

Indexed as

BacteriaCoculture TechniquesMass SpectrometryMetabolomeMetabolomicsMicrobial Interactionsimaging mass spectrometryMALDI-TOFmicrobial coculturemicrobial interactionsmolecular networking

Identifiers

PMID28204504
PMCPMC5091037

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.