Evidence map›Paper›PMID 32459233›Full record

ArticleThe Analyst2020

Distinct classes of multi-subunit heterogeneity: analysis using Fourier Transform methods and native mass spectrometry.

Sean P Cleary, James S Prell

Abstract read
In one paragraph

Article in The Analyst, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Nanodiscs and Mass Spectrometry: Making Membranes Fly.International journal of mass spectrometry · 2020
    Article
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

2 authors.

Sean P ClearyDepartment of Chemistry and Biochemistry, 1253 University of Oregon, Eugene, OR 97403-1253, USA. jprell@uoregon.edu.
James S Prell

Funding

Mass Spectrometry Analysis of Lipid-Protein Interactions and Structural Heterogeneity in the Anthrax Toxin PoreR21AI125804 · NIAID · UNIVERSITY OF OREGON · PI PRELL, JAMES STEPHEN · 2017 to 2018
$424k
NIAID NIH HHS R21 AI125804
6 · The paper itself

Abstract

Native electrospray mass spectrometry is a powerful method for determining the native stoichiometry of many polydisperse multi-subunit biological complexes, including multi-subunit protein complexes and lipid-bound transmembrane proteins. However, when polydispersity results from incorporation of multiple copies of two or more different subunits, it can be difficult to analyze subunit stoichiometry using conventional mass spectrometry analysis methods, especially when m/z distributions for different charge states overlap in the mass spectrum. It was recently demonstrated by Marty and co-workers (K. K. Hoi, et al., Anal. Chem., 2016, 88, 6199-6204) that Fourier Transform (FT)-based methods can determine the bulk average lipid composition of protein-lipid Nanodiscs assembled with two different lipids, but a detailed statistical description of the composition of more general polydisperse two-subunit populations is still difficult to achieve. This results from the vast number of ways in which the two types of subunit can be distributed within the analyte ensemble. Here, we present a theoretical description of three common classes of heterogeneity for mixed-subunit analytes and demonstrate how to differentiate and analyze them using mass spectrometry and FT methods. First, we first describe FT-based analysis of mass spectra corresponding to simple superpositions, convolutions, and multinomial distributions for two or more different subunit types using model data sets. We then apply these principles with real samples, including mixtures of single-lipid Nanodiscs in the same solution (superposition), mixed-lipid Nanodiscs and copolymers (convolutions), and isotope distribution for ubiquitin (multinomial distribution). This classification scheme and the FT method used to study these analyte classes should be broadly useful in mass spectrometry as well as other techniques where overlapping, periodic signals arising from analyte mixtures are common.

Indexed as

1,2-DipalmitoylphosphatidylcholineFourier AnalysisMass SpectrometryMembrane ProteinsNanostructuresPhosphatidylcholinesPolyethylene GlycolsPropylene GlycolsProtein Subunits1,2-Dipalmitoylphosphatidylcholine1-palmitoyl-2-oleoylphosphatidylcholineMembrane ProteinsPhosphatidylcholinespoly(ethylene glycol)-block-poly(propylene glycol)-block-poly(ethylene glycol) copolymerPolyethylene GlycolsPropylene GlycolsProtein Subunits

Identifiers

PMID32459233
PMCPMC8483610

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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.