Evidence map›Paper›PMID 34163866›Full record

ArticleChemical science2020

Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell.

Yongzheng Cong, Khatereh Motamedchaboki, Santosh A Misal, Yiran Liang, Amanda J Guise, Thy Truong, Romain Huguet, Edward D Plowey, Ying Zhu, Daniel Lopez-Ferrer and 1 more

Abstract read
In one paragraph

Article in Chemical science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 132 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
132citing papers in PubMed, 1 pooled it
–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

132 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Mass Spectrometry-based Solutions for Single-cell Proteomics.Genomics, proteomics & bioinformatics · 2025
    Review
  20. Article

72 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

11 authors.

Yongzheng CongDepartment of Chemistry and Biochemistry, Brigham Young University Provo UT 84602 USA ryan@chem.byu.edu.
Khatereh MotamedchabokiThermo Fisher Scientific San Jose CA 95134 USA.
Santosh A MisalDepartment of Chemistry and Biochemistry, Brigham Young University Provo UT 84602 USA ryan@chem.byu.edu.ORCID https://orcid.org/0000-0002-8835-0130
Yiran LiangDepartment of Chemistry and Biochemistry, Brigham Young University Provo UT 84602 USA ryan@chem.byu.edu.
Amanda J GuiseBiogen, Inc. Cambridge MA 02142 USA.
Thy TruongDepartment of Chemistry and Biochemistry, Brigham Young University Provo UT 84602 USA ryan@chem.byu.edu.
Romain HuguetThermo Fisher Scientific San Jose CA 95134 USA.
Edward D PloweyBiogen, Inc. Cambridge MA 02142 USA.
Ying ZhuEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory Richland WA 99354 USA.ORCID https://orcid.org/0000-0002-5416-0566
Daniel Lopez-FerrerThermo Fisher Scientific San Jose CA 95134 USA.
Ryan T KellyDepartment of Chemistry and Biochemistry, Brigham Young University Provo UT 84602 USA ryan@chem.byu.edu.ORCID https://orcid.org/0000-0002-3339-4443

Funding

Area A: In-Depth Proteome Mapping of the Tumor Microenvironment with Single-Cell ResolutionR33CA225248 · NCI · BRIGHAM YOUNG UNIVERSITY · PI KELLY, RYAN T · 2017 to 2017
$1.7M
Fully automated and ultra-high-throughput platform for in-depth single-cell proteomicsR01GM138931 · NIGMS · BRIGHAM YOUNG UNIVERSITY · PI KELLY, RYAN T · 2020 to 2023
$1.6M
NCI NIH HHS R33 CA225248NIGMS NIH HHS R01 GM138931
6 · The paper itself

Abstract

We report on the combination of nanodroplet sample preparation, ultra-low-flow nanoLC, high-field asymmetric ion mobility spectrometry (FAIMS), and the latest-generation Orbitrap Eclipse Tribrid mass spectrometer for greatly improved single-cell proteome profiling. FAIMS effectively filtered out singly charged ions for more effective MS analysis of multiply charged peptides, resulting in an average of 1056 protein groups identified from single HeLa cells without MS1-level feature matching. This is 2.3 times more identifications than without FAIMS and a far greater level of proteome coverage for single mammalian cells than has been previously reported for a label-free study. Differential analysis of single microdissected motor neurons and interneurons from human spinal tissue indicated a similar level of proteome coverage, and the two subpopulations of cells were readily differentiated based on single-cell label-free quantification.

Identifiers

PMID34163866
PMCPMC8178986

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.