Evidence map›Paper›PMID 37674095›Full record

ReviewNature protocols2023

Visualization of metabolites and microbes at high spatial resolution using MALDI mass spectrometry imaging and in situ fluorescence labeling.

Patric Bourceau, Benedikt Geier, Vincent Suerdieck, Tanja Bien, Jens Soltwisch, Klaus Dreisewerd, Manuel Liebeke

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature protocols, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
9.1field-weighted citation impact, top 2% 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

33 citing papers in PubMed, 59 citations in OpenAlex.

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  16. Dissecting the role ofFrontiers in microbiology · 2026
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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

7 authors at 4 institutions in 2 countries.

Patric Bourceau *Max Planck Institute for Marine Microbiology, Bremen, Germany.
Benedikt Geier *Max Planck Institute for Marine Microbiology, Bremen, Germany.ORCID 0000-0002-2942-2624
Vincent SuerdieckInstitute of Hygiene, University of Münster, Münster, Germany.
Tanja BienInstitute of Hygiene, University of Münster, Münster, Germany.ORCID 0000-0002-6080-548X
Jens SoltwischInstitute of Hygiene, University of Münster, Münster, Germany.ORCID 0000-0002-0258-1561
Klaus DreisewerdInstitute of Hygiene, University of Münster, Münster, Germany.
Manuel LiebekeMax Planck Institute for Marine Microbiology, Bremen, Germany. mliebeke@mpi-bremen.de.ORCID 0000-0002-2339-1409
University of Münster · DEHochschule für Angewandte Wissenschaften Kiel · DEMax Planck Institute for Marine Microbiology · DEUniversity of Bremen · DE

Funding

Deutsche Forschungsgemeinschaft (German Research Foundation) CRC TRR332 (Z1)Deutsche Forschungsgemeinschaft (German Research Foundation) DR 416/12-1Deutsche Forschungsgemeinschaft (German Research Foundation) O976/41Deutsche Forschungsgemeinschaft (German Research Foundation) SO976/5-1Human Frontier Science Program (HFSP) LT0015/2022-L
6 · The paper itself

Abstract

Label-free molecular imaging techniques such as matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) enable the direct and simultaneous mapping of hundreds of different metabolites in thin sections of biological tissues. However, in host-microbe interactions it remains challenging to localize microbes and to assign metabolites to the host versus members of the microbiome. We therefore developed a correlative imaging approach combining MALDI-MSI with fluorescence in situ hybridization (FISH) on the same section to identify and localize microbial cells. Here, we detail metaFISH as a robust and easy method for assigning the spatial distribution of metabolites to microbiome members based on imaging of nucleic acid probes, down to single-cell resolution. We describe the steps required for tissue preparation, on-tissue hybridization, fluorescence microscopy, data integration into a correlative image dataset, matrix application and MSI data acquisition. Using metaFISH, we map hundreds of metabolites and several microbial species to the micrometer scale on a single tissue section. For example, intra- and extracellular bacteria, host cells and their associated metabolites can be localized in animal tissues, revealing their complex metabolic interactions. We explain how we identify low-abundance bacterial infection sites as regions of interest for high-resolution MSI analysis, guiding the user to a trade-off between metabolite signal intensities and fluorescence signals. MetaFISH is suitable for a broad range of users from environmental microbiologists to clinical scientists. The protocol requires ~2 work days.

Indexed as

BacteriaIn Situ Hybridization, FluorescenceMicrobiotaMolecular ImagingSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationAnimalsMiceMicroscopy, Fluorescence

Identifiers

PMID37674095
OpenAlexW4386482751

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.