Mass Spectrometry Overview

Principles

Definition

Mass spectrometry is an analytical technique that measures the mass-to-charge ratio of ions, enabling the identification, quantification, and structural elucidation of molecules within a sample. This methodology is fundamental across numerous scientific disciplines for characterizing complex mixtures and determining isotopic composition.

Ontological type

Ionization Methods

Instrumentation

Data Analysis

Key developments

Key Figures

Instrumental Foundations and Fragmentation era

Ragnar Ryhage [1] operated within Karolinska Institutet [3] and the University of Gothenburg [4] during this era. His 1960 work Mass spectrometry in lipid research [6] demonstrated the applicability of mass spectrometry to lipid analysis, establishing early quantitative and interpretive capabilities that underpinned instrumental foundations of the field. Fred W. McLafferty [2] was affiliated with Purdue University West Lafayette [5] during this era. His 1957 paper Mass Spectrometric Analysis...Aliphatic Ethers [7] helped establish practical MS methods for analyzing aliphatic ethers, contributing crucial fragmentation understanding that advanced the practical and theoretical base of mass spectrometry in this period.

Proteomics and Computational Integration era

Matthias Mann [1] is a leading mass spectrometry scientist whose work in this era spanned Harvard University [3] and the Massachusetts Institute of Technology [4]. He contributed to core proteomics milestones through mass spectrometric sequencing of proteins from silver-stained gels [6], femtomole sequencing from polyacrylamide gels [8], and the SILAC approach to expression proteomics [7], each advancing sensitivity, throughput, and quantitative capabilities essential for MS-driven workflows. Ruedi Aebersold [2] is a central figure associated with Rockefeller University [5] and Harvard University [3] during this era. His development of empirical and statistical models to assess peptide identifications [9], proteins by tandem MS [10], and glycoprotein identification and quantification using hydrazide chemistry and stable isotope labeling [11] underpinned automated identification, statistical confidence, and quantitative multiplexing in proteomics.

Data-Driven Multidimensional Mass Spectrometry era

Matthias Mann [1] with affiliations across Rockefeller University [3] and Heidelberg University [4] epitomizes the data-driven multidimensional mass spectrometry era. His key contributions include the MaxQuant platform [7], enabling high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification, which propelled reproducible, large-scale proteomics in this era. Jürgen Cox [2] has worked with University of Dundee [5] and University of Copenhagen [6], highlighting his role within this era's collaborative network. His central contributions center on co-developing the MaxQuant framework [7], advancing data-centered quantitative proteomics and enabling cross-platform, library-free identification that underpins the era's reproducible, multidimensional MS workflows.