Evidence map›Paper›PMID 38014012›Full record

ArticleResearch square2023

In-capillary sample processing coupled to label-free capillary electrophoresis-mass spectrometry to decipher the native N-glycome of single mammalian cells and ng-level blood isolates.

Alexander Ivanov, Anne-Lise Marie, Yunfan Gao

Open access · greenAbstract readPreprint
In one paragraph

Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Alexander IvanovNortheastern University.ORCID https://orcid.org/0000-0002-4691-8488
Anne-Lise MarieNortheastern University.ORCID https://orcid.org/0000-0002-7461-1838
Yunfan GaoNortheastern University.
Universidad del Noreste · MX

Funding

Effect of methodological and biological variability on molecular profiling of extracellular vesicles in cancer detectionR01CA218500 · NCI · NORTHEASTERN UNIVERSITY · PI GHIRAN, IONITA CALIN, IVANOV, ALEXANDER R. · 2018 to 2022
$4.0M
Robust ultra-high sensitivity proteomic technologies for limited samplesR35GM136421 · NIGMS · NORTHEASTERN UNIVERSITY · PI Alexander R. Ivanov · 2020 to 2026
$3.4M
NCI NIH HHS R01 CA218500NIGMS NIH HHS R35 GM136421
6 · The paper itself

Abstract

The development of reliable single-cell dispensers and substantial sensitivity improvement in mass spectrometry made proteomic profiling of individual cells achievable. Yet, there are no established methods for single-cell glycome analysis due to the inability to amplify glycans and sample losses associated with sample processing and glycan labeling. In this work, we developed an integrated platform coupling online in-capillary sample processing with high-sensitivity label-free capillary electrophoresis-mass spectrometry for N-glycan profiling of single mammalian cells. Direct and unbiased characterization and quantification of single-cell surface N-glycomes were demonstrated for HeLa and U87 cells, with the detection of up to 100 N-glycans per single cell. Interestingly, N-glycome alterations were unequivocally detected at the single-cell level in HeLa and U87 cells stimulated with lipopolysaccharide. The developed workflow was also applied to the profiling of ng-level amounts of blood-derived protein, extracellular vesicle, and total plasma isolates, resulting in over 170, 220, and 370 quantitated N-glycans, respectively.

Identifiers

PMID38014012
PMCPMC10680937
OpenAlexW4388653571

What OpenQuestion holds

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LicenceCC BY
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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.