ArticleAnalytical chemistry2024
Isotopic Depletion Increases the Spatial Resolution of FPOP Top-Down Mass Spectrometry Analysis.
Article in Analytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Isotope Decluttering Reduces Spectral Complexity while Maintaining Protein Structure.Analytical chemistry · 2026Article
- Absorption Mode Broadband 2D MS for Proteomics and Metabolomics.Journal of the American Society for Mass Spectrometry · 2026Article
- Impact of Charge Reduction on Sequence Coverage of Proteins by 193 nm Ultraviolet Photodissociation.Journal of the American Society for Mass Spectrometry · 2025Article
- Data-Independent Acquisition Represents a Promising Alternative for Fast Photochemical Oxidation of Proteins (FPOP) Samples Analysis.Analytical chemistry · 2024Article
- The path forward for protein footprinting, covalent labeling, and mass spectrometry-based protein conformational analyses.Journal of mass spectrometry : JMS · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein radical labeling, like fast photochemical oxidation of proteins (FPOP), coupled to a top-down mass spectrometry (MS) analysis offers an alternative analytical method for probing protein structure or protein interaction with other biomolecules, for instance, proteins and DNA. However, with the increasing mass of studied analytes, the MS/MS spectra become complex and exhibit a low signal-to-noise ratio. Nevertheless, these difficulties may be overcome by protein isotope depletion. Thus, we aimed to use protein isotope depletion to analyze FPOP-oxidized samples by top-down MS analysis. For this purpose, we prepared isotopically natural (IN) and depleted (ID) forms of the FOXO4 DNA binding domain (FOXO4-DBD) and studied the protein-DNA interaction interface with double-stranded DNA, the insulin response element (IRE), after exposing the complex to hydroxyl radicals. As shown by comparing tandem mass spectra of natural and depleted proteins, the ID form increased the signal-to-noise ratio of useful fragment ions, thereby enhancing the sequence coverage by more than 19%. This improvement in the detection of fragment ions enabled us to detect 22 more oxidized residues in the ID samples than in the IN sample. Moreover, less common modifications were detected in the ID sample, including the formation of ketones and lysine carbonylation. Given the higher quality of ID top-down MSMS data set, these results provide more detailed information on the complex formation between transcription factors and DNA-response elements. Therefore, our study highlights the benefits of isotopic depletion for quantitative top-down proteomics. Data are available via ProteomeXchange with the identifier PXD044447.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.