Evidence map›Paper›PMID 36700448›Full record

ArticleJournal of proteome research2023

Time-of-Flight Fragmentation Spectra Generated by the Proteomic Analysis of Single Human Cells Do Not Exhibit Atypical Fragmentation Patterns.

Benjamin C Orsburn

Abstract read
In one paragraph

Article in Journal of proteome research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Analyzing Posttranslational Modifications in Single Cells.Methods in molecular biology (Clifton, N.J.) · 2024
    Review
  7. Article
  8. Review
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

1 author.

Benjamin C OrsburnThe Department of Pharmacology and Molecular SciencesThe Johns Hopkins University School of Medicine, Baltimore, Maryland21205, United States.ORCID 0000-0002-0774-3750

Funding

Cellular Signaling in Drug Induced ToxicityR01GM103853 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI ORSBURN, BENJAMIN CARL · 2013 to 2022
$3.6M
Drug Phosphorylation and AgingR01AG064908 · NIA · JOHNS HOPKINS UNIVERSITY · PI ORSBURN, BENJAMIN CARL · 2020 to 2023
$2.4M
NIA NIH HHS R01 AG064908NIGMS NIH HHS R01 GM103853
6 · The paper itself

Abstract

Recent work detailed the unique characteristics of fragmentation spectra derived from peptides from single human cells. This valuable report utilized an ultrahigh-field Orbitrap and directly compared the spectra obtained from high-concentration bulk cell HeLa lysates to those obtained from nanogram dilutions of the same and from nanowell-processed single HeLa cells. The analysis demonstrated marked differences between the fragmentation spectra generated at high and single-cell loads, most strikingly, the loss of high-mass y-series fragment ions. As significant differences exist in the physics of Orbitrap and time-of-flight mass analyzers, a comparison appeared warranted. A similar analysis was performed using isolated single pancreatic cancer cells compared to pools consisting of 100 cells. While a reanalysis of the prior Orbitrap data supports the author's original findings, the same trends are not observed in time-of-flight mass spectra of peptides from single human cells. The results are particularly striking when directly comparing the matched intensity fragment values between bulk and single-cell data generated on the same mass analyzers. Instrument acquisition files, processed data, and spectrum libraries are publicly available on MASSIVE via accession MSV000090635.

Indexed as

ProteomicsTandem Mass SpectrometryHeLa CellsHumansPeptidesPeptidesOrbitrap single cellsingle-cell proteomicsTIMSTOF single cell

Identifiers

PMID36700448
PMCPMC10502792

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Registered trials

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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.