Evidence map›Paper›PMID 37839701›Full record

ArticleMolecular & cellular proteomics : MCP2023

An Automated Nanowell-Array Workflow for Quantitative Multiplexed Single-Cell Proteomics Sample Preparation at High Sensitivity.

Claudia Ctortecka, David Hartlmayr, Anjali Seth, Sasha Mendjan, Guilhem Tourniaire, Namrata D Udeshi, Steven A Carr, Karl Mechtler

Open access · goldAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed
15.2field-weighted citation impact, top 1% 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

67 citing papers in PubMed, 100 citations in OpenAlex.

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  13. Plasma-Derived Extracellular Vesicle Proteomics.Journal of proteome research · 2025
    Review
  14. Review
  15. Review
  16. Mass Spectrometry-based Solutions for Single-cell Proteomics.Genomics, proteomics & bioinformatics · 2025
    Review
  17. Article
  18. Article
  19. Article
  20. Article

7 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

8 authors at 3 institutions in 2 countries.

Claudia CtorteckaResearch Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. Electronic address: cctortec@broadinstitute.org.
David HartlmayrResearch Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Cellenion SASU, Lyon, France.
Anjali SethCellenion SASU, Lyon, France.
Sasha MendjanInstitute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, Austria.
Guilhem TourniaireCellenion SASU, Lyon, France.
Namrata D UdeshiBroad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
Steven A CarrBroad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. Electronic address: scarr@broad.mit.edu.
Karl MechtlerResearch Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Cellenion SASU, Lyon, France; Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, Austria; The Gregor Mendel Institute of Molecular Plant Biology of the Austrian Academy of Sciences (GMI), Vienna BioCenter (VBC), Vienna, Austria. Electronic address: Karl.mechtler@imp.ac.at.
Broad Institute · USInstitute of Molecular Biotechnology · ATResearch Institute of Molecular Pathology · AT

Funding

ProteomicsP01CA206978 · NCI · DANA-FARBER CANCER INST · PI WU, CATHERINE JU-YING · 2016 to 2025
$17.0M
Center of Excellence for High Throughput Proteogenomic CharacterizationU24CA270823 · NCI · BROAD INSTITUTE, INC. · PI STEVEN A CARR, MICHAEL A GILLETTE · 2022 to 2026
$5.3M
Proteogenomic Predictors of Recurrence in Non-small Cell Lung CancerU01CA271402 · NCI · WASHINGTON UNIVERSITY · PI STEVEN A CARR, MICHAEL A GILLETTE · 2022 to 2026
$5.0M
Austrian Science Fund FWF P 35045NCI NIH HHS P01 CA206978NCI NIH HHS U01 CA271402NCI NIH HHS U24 CA270823
6 · The paper itself

Abstract

Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lags. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation including multiplexed labeling up to 16-plex with high sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE, reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1500 protein groups per TMT10-plex with reduced or eliminated need for a carrier proteome. We evaluated the effect of wider precursor isolation windows at single-cell input levels and found that using 2 Da isolation windows increased overall sensitivity without significantly impacting interference. Using the dedicated mass spectrometry acquisition strategies detailed here, we identified on average close to 2000 proteins per TMT10-plex across 170 multiplexed single cells that readily distinguished human cell types. Overall, our workflow combines highly efficient sample preparation, chromatographic and ion mobility-based filtering, rapid wide-window data-dependent acquisition analysis, and intelligent data analysis for optimal multiplexed single-cell proteomics. This versatile and automated proteoCHIP-based sample preparation approach is sufficiently sensitive to drive biological applications of single-cell proteomics and can be readily adopted by proteomics laboratories.

Indexed as

ProteomeProteomicsHumansMass SpectrometryWorkflowProteomeautomated sample preparationhigh field asymmetric waveform ion mobility spectrometryisobaric peptide labelingproteoCHIPsingle-cell proteomics

Identifiers

PMID37839701
PMCPMC10684380
OpenAlexW4387641289

What OpenQuestion holds

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LicenceCC BY
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.