Jove
Visualize
Contact Us

Related Concept Videos

Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

782
Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...
782
Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

6.4K
Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
6.4K
Mass Spectrometry: Overview01:19

Mass Spectrometry: Overview

5.2K
Mass spectrometry is an analytical technique used to determine the molecular mass and molecular formula of a compound. The basic principle of mass spectrometry is to generate ions from the analyte molecule and measure these ion abundances against their molecular mass.  One common type of ionization, known as electrospray ionization or EI, bombards the analyte molecules in the gas phase with high-energy electron beams. The electron beams displace an electron from the molecule and leave...
5.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Arf1 is involved in Neisseria meningitidis-induced cortical branched F-actin network reorganization.

EMBO reports·2026
Same author

Automated Optimization of Bacterial Tracking Pipelines With TrackMate 8.

Current protocols·2026
Same author

A family of ribosome hibernation factors widespread in Archaea.

Nature communications·2026
Same author

Top-Down Mass Spectrometry of a Clinical Antibody Light Chain Using the Omnitrap-Orbitrap-Booster Platform.

Journal of the American Society for Mass Spectrometry·2025
Same author

Mass Spectrometry Reveals Novel Features of Tubulin Polyglutamylation in the Flagellum of <i>Trypanosoma brucei</i>.

Journal of proteome research·2025
Same author

Structures of Saccharolobus solfataricus initiation complexes with leaderless mRNAs highlight archaeal features and eukaryotic proximity.

Nature communications·2025
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jul 4, 2025

Combining Chemical Cross-linking and Mass Spectrometry of Intact Protein Complexes to Study the Architecture of Multi-subunit Protein Assemblies
10:01

Combining Chemical Cross-linking and Mass Spectrometry of Intact Protein Complexes to Study the Architecture of Multi-subunit Protein Assemblies

Published on: November 28, 2017

19.7K

Do Not Waste Time─Ensure Success in Your Cross-Linking Mass Spectrometry Experiments before You Begin.

Lucienne Nouchikian1, David Fernandez-Martinez2, Pierre-Yves Renard3

  • 1Institut Pasteur, Université Paris Cité, CNRS UAR 2024, Mass Spectrometry for Biology Unit, Paris 75015, France.

Analytical Chemistry
|January 31, 2024
PubMed
Summary

Predicting cross-linking mass spectrometry (XL-MS) success is now possible. Proteins in the top 20% abundance range are more likely to yield successful XL-MS data for studying protein interactions.

More Related Videos

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions
10:52

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions

Published on: September 28, 2017

8.1K
Quaternary Structure Modeling Through Chemical Cross-Linking Mass Spectrometry: Extending TX-MS Jupyter Reports
05:18

Quaternary Structure Modeling Through Chemical Cross-Linking Mass Spectrometry: Extending TX-MS Jupyter Reports

Published on: October 20, 2021

2.4K

Related Experiment Videos

Last Updated: Jul 4, 2025

Combining Chemical Cross-linking and Mass Spectrometry of Intact Protein Complexes to Study the Architecture of Multi-subunit Protein Assemblies
10:01

Combining Chemical Cross-linking and Mass Spectrometry of Intact Protein Complexes to Study the Architecture of Multi-subunit Protein Assemblies

Published on: November 28, 2017

19.7K
Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions
10:52

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions

Published on: September 28, 2017

8.1K
Quaternary Structure Modeling Through Chemical Cross-Linking Mass Spectrometry: Extending TX-MS Jupyter Reports
05:18

Quaternary Structure Modeling Through Chemical Cross-Linking Mass Spectrometry: Extending TX-MS Jupyter Reports

Published on: October 20, 2021

2.4K

Area of Science:

  • Biochemistry
  • Proteomics
  • Structural Biology

Background:

  • Cross-linking mass spectrometry (XL-MS) is vital for studying protein complexes and interactions in native states.
  • XL-MS provides unbiased protein interaction data and restraints for integrative modeling.
  • Challenges arise when low-abundance proteins of interest are obscured by more abundant proteins, limiting data quality.

Purpose of the Study:

  • To establish a predictive guideline for the success of XL-MS experiments.
  • To determine the minimum protein abundance required for obtaining sufficient cross-linking data.
  • To aid researchers in planning successful XL-MS studies.

Main Methods:

  • Utilized intensity-based absolute quantification (iBAQ) analysis on trypsin digest data.
  • Compared iBAQ results with large-scale XL-MS data from diverse biological systems.
  • Correlated protein abundance levels with the number of cross-links identified per protein.

Main Results:

  • iBAQ analysis effectively predicts the likelihood of successful XL-MS experiments.
  • Proteins must be in at least the top 20% abundance range to yield more than one cross-link per protein.
  • This abundance threshold is a reliable indicator for experimental success.

Conclusions:

  • Protein abundance, assessed via iBAQ, is a critical factor for successful XL-MS.
  • This guideline helps researchers select appropriate targets and optimize experimental design.
  • Ensures efficient use of resources and maximizes the potential for meaningful structural and interaction insights.