Evidence map›Paper›PMID 30833957›Full record

ArticleFrontiers in plant science2019

Live Single-Cell Metabolomics With Matrix-Free Laser/Desorption Ionization Mass Spectrometry to Address Microalgal Physiology.

Tim U H Baumeister, Marine Vallet, Filip Kaftan, Aleš Svatoš, Georg Pohnert

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

18 citing papers in PubMed, 34 citations in OpenAlex.

  1. Review
  2. Review
  3. Plant Metabolomics: The Future of Anticancer Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2024
    Review
  4. Article
  5. Lipid biomarkers for algal resistance to viral infection in the ocean.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  6. Article
  7. Review
  8. Review
  9. Review
  10. Influence of Ion Source Geometry on the Repeatability of Topographically Guided LAESI-MSI.Journal of the American Society for Mass Spectrometry · 2022
    Article
  11. The limitless applications of single-cell metabolomics.Current opinion in biotechnology · 2021
    Review
  12. Review
  13. Article
  14. Plant Single-Cell Metabolomics-Challenges and Perspectives.International journal of molecular sciences · 2020
    Review
  15. Article
  16. Review
  17. Review
  18. Article
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

5 authors at 1 institution in 1 country.

Tim U H BaumeisterMax Planck Fellow Group on Plankton Community Interaction, Max Planck Institute for Chemical Ecology, Jena, Germany.
Marine ValletMax Planck Fellow Group on Plankton Community Interaction, Max Planck Institute for Chemical Ecology, Jena, Germany.
Filip KaftanResearch Group Mass Spectrometry/Proteomics, Max Planck Institute for Chemical Ecology, Jena, Germany.
Aleš SvatošResearch Group Mass Spectrometry/Proteomics, Max Planck Institute for Chemical Ecology, Jena, Germany.
Georg PohnertMax Planck Fellow Group on Plankton Community Interaction, Max Planck Institute for Chemical Ecology, Jena, Germany.
Max Planck Institute for Chemical Ecology · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unicellular phototrophic algae can form massive blooms with up to millions of individual cells per milliliter in freshwater and marine ecosystems. Despite the temporal dominance of bloom formers many algal species can co-exist and compete for nutrients and space, creating a complex and diverse community. While microscopy and single cell genomics can address the taxonomic inventory, the cellular metabolome has yet to be thoroughly explored to determine the physiological status of microalgae. This might, however, provide a key to understand the observed species diversity in the homogeneous environment. Here, we introduce an effective, rapid and versatile method to analyze living single cells from aqueous substrata with laser-desorption/ionization mass spectrometry (LDI-MS) using a simple and inexpensive matrix-free support. The cells deposited on a cultivation-medium wetted support are analyzed with minimal disturbance as they remain in their natural viable state until their disruption during LDI-MS. Metabolites desorbed from single cells are analyzed on High-Resolution Mass Spectrometry (HR-MS) using the Orbitrap FT-MS technology to fingerprint cellular chemistry. This live single-cell mass spectrometry (LSC-MS) allows assessing the physiological status and strain-specifics of different microalgae, including marine diatoms and freshwater chlorophytes, at the single-cell level. We further report a reliable and robust data treatment pipeline to perform multivariate statistics on the replicated LSC-MS data. Comparing single cell MS spectra from natural phytoplankton samples and from laboratory strains allows the identification and discrimination of inter and intra-specific metabolic variability and thereby has promising applications in addressing highly complex phytoplankton communities. Notably, the herein described matrix-free live-single-cell LDI-HR-MS approach enables monitoring dynamics of the plankton and might explain why key-players survive, thrive, avoid selective feeding or pathogenic virus and bacteria, while others are overcome and die.

Indexed as

chlorophyceae Haematococcus pluvialisdiatoms Coscinodiscus (Bacillariophyceae)live single cell mass spectrometrymatrix-free laser desorption/ionization-mass spectrometrymicroalgaemultivariate statisticssingle-cell metabolomics

Identifiers

PMID30833957
PMCPMC6387974
OpenAlexW2917587079

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.