Evidence map›Paper›PMID 34328739›Full record

ArticleJournal of proteome research2021

Proteomics for Low Cell Numbers: How to Optimize the Sample Preparation Workflow for Mass Spectrometry Analysis.

Sara Kassem, Kyra van der Pan, Anniek L de Jager, Brigitta A E Naber, Inge F de Laat, Alesha Louis, Jacques J M van Dongen, Cristina Teodosio, Paula Díez

Abstract read
In one paragraph

Article in Journal of proteome research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Single-cell multi-omics in the study of digestive system cancers.Computational and structural biotechnology journal · 2024
    Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Review
  19. 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

9 authors.

Sara KassemDepartment of Immunology, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333ZA Leiden, Netherlands.
Kyra van der PanDepartment of Immunology, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333ZA Leiden, Netherlands.
Anniek L de JagerDepartment of Immunology, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333ZA Leiden, Netherlands.
Brigitta A E NaberDepartment of Immunology, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333ZA Leiden, Netherlands.
Inge F de LaatDepartment of Immunology, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333ZA Leiden, Netherlands.
Alesha LouisDepartment of Immunology, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333ZA Leiden, Netherlands.
Jacques J M van DongenDepartment of Immunology, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333ZA Leiden, Netherlands.ORCID 0000-0002-3650-7087
Cristina TeodosioDepartment of Immunology, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333ZA Leiden, Netherlands.
Paula DíezDepartment of Immunology, Leiden University Medical Center (LUMC), Albinusdreef 2, 2333ZA Leiden, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nowadays, massive genomics and transcriptomics data can be generated at the single-cell level. However, proteomics in this setting is still a big challenge. Despite the great improvements in sensitivity and performance of mass spectrometry instruments and the better knowledge on sample preparation processing, it is widely acknowledged that multistep proteomics workflows may lead to substantial sample loss, especially when working with paucicellular samples. Still, in clinical fields, frequently limited sample amounts are available for downstream analysis, thereby hampering comprehensive characterization at protein level. To aim at better protein and peptide recoveries, we compare existing and novel approaches in the multistep sample preparation protocols for mass spectrometry studies, from sample collection, cell lysis, protein quantification, and electrophoresis/staining to protein digestion, peptide recovery, and LC-MS/MS instruments. From this critical evaluation, we conclude that the recent innovations and technologies, together with high quality management of samples, make proteomics on paucicellular samples possible, which will have immediate impact for the proteomics community.

Indexed as

ProteomicsTandem Mass SpectrometryChromatography, LiquidPeptidesWorkflowPeptidesmass spectrometrypaucicellular samplesample preparationsingle-cell proteomics

Identifiers

PMID34328739
PMCPMC8419858

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.