Evidence map›Paper›PMID 42461610›Full record

ArticleAnalytical chemistry2026

Top-Down versus Bottom-Up Proteomics in Highly Sensitive LC-MS-Based Profiling of Limited Samples.

Yunfan Gao, Michal Greguš, James C Kostas, Anne-Lise Marie, Alexander R Ivanov

Abstract read
In one paragraph

Article in Analytical chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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.

No citing paper in PubMed yet.

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

5 authors.

Yunfan GaoDepartment of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts02115, United States.ORCID 0000-0002-2132-582X
Michal GregušDepartment of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts02115, United States.ORCID 0000-0003-3815-1448
James C KostasDepartment of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts02115, United States.
Anne-Lise MarieDepartment of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts02115, United States.ORCID 0000-0002-7461-1838
Alexander R IvanovDepartment of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts02115, United States.ORCID 0000-0002-4691-8488

Funding

Effect of methodological and biological variability on molecular profiling of extracellular vesicles in cancer detectionR01CA218500 · NCI · NORTHEASTERN UNIVERSITY · PI DEL MONTE, FEDERICA, GHIRAN, IONITA CALIN · 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
Next-generation nanoflow LC column technology to enable high sensitivity proteomics of limited samplesR41GM156145 · NIGMS · MIXEDLCMEDIA LLC · PI IVANOV, ALEXANDER R · 2024 to 2024
$307k
ASMS Research Award NADFCI/NU Program in Cancer Drug Development at Northeastern University NANational Institutes of Health (NIH) R35GM136421National Institutes of Health (NIH) R41GM156145NCI NIH HHS R01 CA218500NCI NIH HHS R01CA218500NIGMS NIH HHS R35 GM136421NIGMS NIH HHS R41 GM156145Thermo Fisher Scientific NA
6 · The paper itself

Abstract

The advantages of top-down proteomics (TDP) in the characterization of proteoforms, resulting from genetic variations, alternative splicing, and post-translational modifications (PTMs), have been well documented. However, TDP applications on limited samples have been less explored, and no direct comparison with the bottom-up proteomics (BUP) approach for the same scarce amounts of samples has been conducted to date. In this work, we processed ∼100-1000 HeLa cells using bottom-up and top-down workflows and subjected sample volumes equivalent to ∼25 and up to ∼250 HeLa cells to liquid chromatography-mass spectrometry (LC-MS)-based TDP and BUP analyses. Porous layer open-tubular (PLOT) columns were used for the separation of intact proteins in TDP MS, while traditional bead-packed columns were used for the BUP workflow. Up to 500 proteoforms and nearly 1300 proteins from cell lysates equivalent to ∼25 HeLa cells were identified in TDP and BUP, respectively. Interestingly, among all the unambiguously identified proteins from both ∼25 HeLa and ∼250 HeLa cell lysates in TDP, ∼20-30% were not identified in BUP under the same sample loading, suggesting significant complementarity between TDP and BUP approaches. Additionally, biologically relevant PTMs (e.g., acetylation, phosphorylation, and methylation) were reliably characterized in TDP as different proteoforms. We anticipate that TDP, enhanced by ultralow-flow PLOT chromatography columns coupled to MS, could be a supplementary or an alternative approach for limited-sample analysis, as it eliminates the need for protein digestion and minimizes sample cleanup, enabling rapid sample preparation while preserving proteoform information.

Indexed as

Liquid Chromatography-Mass SpectrometryProteinsProteomicsChromatography, LiquidHeLa CellsHumansProtein Processing, Post-TranslationalProteins

Identifiers

PMID42461610
PMCPMC13425565

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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.