Evidence map›Paper›PMID 28135079›Full record

ArticleJournal of the American Chemical Society2017

Categorizing Cells on the Basis of their Chemical Profiles: Progress in Single-Cell Mass Spectrometry.

Troy J Comi, Thanh D Do, Stanislav S Rubakhin, Jonathan V Sweedler

Abstract read
In one paragraph

Article in Journal of the American Chemical Society, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.

0numbers the graph read from it
0cells of the map it votes in
73citing 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

73 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Non-Mass Spectrometric Targeted Single-Cell Metabolomics.Trends in analytical chemistry : TRAC · 2023
    Article
  8. Rapid, One-Step Sample Processing for Label-Free Single-Cell Proteomics.Journal of the American Society for Mass Spectrometry · 2023
    Article
  9. Review
  10. Article
  11. Single cell metabolism: current and future trends.Metabolomics : Official journal of the Metabolomic Society · 2022
    Review
  12. Article
  13. Mass spectrometry imaging to explore molecular heterogeneity in cell culture.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Review
  19. Review
  20. Article

13 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

4 authors.

Troy J ComiDepartment of Chemistry and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.
Thanh D DoDepartment of Chemistry and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.ORCID 0000-0002-1978-4365
Stanislav S RubakhinDepartment of Chemistry and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.
Jonathan V SweedlerDepartment of Chemistry and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.ORCID 0000-0003-3107-9922

Funding

The UIUC Neuroproteomics Center on Cell-Cell SignalingP30DA018310 · NIDA · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI Elena V Romanova · 2004 to 2026
$24.9M
Training Program in Chemistry-Interface with BiologyT32GM070421 · NIGMS · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI HERGENROTHER, PAUL · 2005 to 2019
$5.4M
BRAIN Initiative: Integrated Multimodal Analysis of Cell- and Circuit-Specific Processes in Hippocampal FunctionU01MH109062 · NIMH · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI SWEEDLER, JONATHAN V. · 2015 to 2017
$2.3M
NIDA NIH HHS P30 DA018310NIGMS NIH HHS T32 GM070421NIMH NIH HHS U01 MH109062
6 · The paper itself

Abstract

The chemical differences between individual cells within large cellular populations provide unique information on organisms' homeostasis and the development of diseased states. Even genetically identical cell lineages diverge due to local microenvironments and stochastic processes. The minute sample volumes and low abundance of some constituents in cells hinder our understanding of cellular heterogeneity. Although amplification methods facilitate single-cell genomics and transcriptomics, the characterization of metabolites and proteins remains challenging both because of the lack of effective amplification approaches and the wide diversity in cellular constituents. Mass spectrometry has become an enabling technology for the investigation of individual cellular metabolite profiles with its exquisite sensitivity, large dynamic range, and ability to characterize hundreds to thousands of compounds. While advances in instrumentation have improved figures of merit, acquiring measurements at high throughput and sampling from large populations of cells are still not routine. In this Perspective, we highlight the current trends and progress in mass-spectrometry-based analysis of single cells, with a focus on the technologies that will enable the next generation of single-cell measurements.

Indexed as

Single-Cell AnalysisHumansMass Spectrometry

Identifiers

PMID28135079
PMCPMC5364434

What OpenQuestion holds

Textmetadata
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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.