Evidence map›Paper›PMID 39117766›Full record

ArticleNature protocols2024

Massively parallel sample preparation for multiplexed single-cell proteomics using nPOP.

Andrew Leduc, Luke Khoury, Joshua Cantlon, Saad Khan, Nikolai Slavov

Abstract read
In one paragraph

Article in Nature protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Article
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  4. Review
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  9. Review
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  11. Slice-PASEF: Maximising Ion Utilisation in LC-MS Proteomics.bioRxiv : the preprint server for biology · 2025
    Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Spatial Proteomics towards cellular Resolution.Expert review of proteomics · 2024
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Andrew LeducDepartments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA, USA. leduc.an@northeastern.edu.
Luke KhouryDepartments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA, USA.ORCID 0000-0001-7794-6812
Joshua CantlonSCIENION US Inc., Phoenix, AZ, USA.
Saad KhanDepartments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA, USA.
Nikolai SlavovDepartments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA, USA. nslavov@northeastern.edu.ORCID 0000-0003-2035-1820

Funding

Single-cell proteomic identification of novel markers of senescenceUH3CA268117 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI DOU, ZHIXUN, RAJAGOPAL, JAYARAJ · 2023 to 2024
$1.9M
Molecular and metabolic influences on the activation of monocytes and macrophages at single-cell resolutionR35GM148218 · NIGMS · NORTHEASTERN UNIVERSITY · PI Nikolai Slavov · 2023 to 2026
$1.5M
Collaborative Research: DMS/NIGMS 2: Methods for Systematic Analysis of Post-transcriptional Regulation in Single CellsR01GM144967 · NIGMS · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI FRANKS, ALEXANDER, SLAVOV, NIKOLAI · 2021 to 2024
$779k
NCI NIH HHS UH3 CA268117NIGMS NIH HHS R01 GM144967NIGMS NIH HHS R35 GM148218Paul G. Allen Family Foundation NA
6 · The paper itself

Abstract

Single-cell proteomics by mass spectrometry (MS) allows the quantification of proteins with high specificity and sensitivity. To increase its throughput, we developed nano-proteomic sample preparation (nPOP), a method for parallel preparation of thousands of single cells in nanoliter-volume droplets deposited on glass slides. Here, we describe its protocol with emphasis on its flexibility to prepare samples for different multiplexed MS methods. An implementation using the plexDIA MS multiplexing method, which uses non-isobaric mass tags to barcode peptides from different samples for data-independent acquisition, demonstrates accurate quantification of ~3,000-3,700 proteins per human cell. A separate implementation with isobaric mass tags and prioritized data acquisition demonstrates analysis of 1,827 single cells at a rate of >1,000 single cells per day at a depth of 800-1,200 proteins per human cell. The protocol is implemented by using a cell-dispensing and liquid-handling robot-the CellenONE instrument-and uses readily available consumables, which should facilitate broad adoption. nPOP can be applied to all samples that can be processed to a single-cell suspension. It takes 1 or 2 d to prepare >3,000 single cells. We provide metrics and software (the QuantQC R package) for quality control and data exploration. QuantQC supports the robust scaling of nPOP to higher plex reagents for achieving reliable and scalable single-cell proteomics.

Indexed as

Mass SpectrometryProteomicsSingle-Cell AnalysisHumansNanotechnology

Identifiers

PMID39117766
PMCPMC11614709

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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.