Two-Dimensional Tandem Mass Spectrometry for Biopolymer Structural Analysis.
MyPhuong T LeDylan T HoldenJeremy M ManheimEric T DziekonskiKiran IyerRobert Graham CooksPublished in: Angewandte Chemie (International ed. in English) (2024)
Biopolymer analysis, including proteomics and glycomics, relies heavily on the use of mass spectrometry for structural elucidation, including sequence determination. Novel methods to improve sample workup, instrument performance, and data analysis continue to be developed to address shortcomings associated with sample preparation, analysis time, data quality, and data interpretation. Here, we present a new method that couples in-source collision-induced dissociation (IS-CID) with two-dimensional tandem mass spectrometry (2D MS/MS) as a way to simplify proteomics and glycomics workflows while also providing additional insight into analyte structures over traditional MS/MS experiments. Specifically, IS-CID is employed as a gas-phase digestion method, i.e., to break down intact full-length polysaccharide or peptide ions prior to mass analysis. The resulting mixtures of oligomeric ions are analyzed by 2D-MS/MS, a technique that allows association of product ions with their precursor ions without isolation of the latter. A novel data analysis strategy is introduced to leverage the second dimension of 2D MS/MS spectra, in which stairstep patterns, representing outputs of a molecule's MS n scans, are extracted for structural interconnectivity information on the oligomer. The results demonstrate the potential applicability of 2D MS/MS strategies to the modern omics workflow and structural analysis of various classes of biopolymers.
Keyphrases
- ms ms
- data analysis
- tandem mass spectrometry
- mass spectrometry
- high performance liquid chromatography
- ultra high performance liquid chromatography
- liquid chromatography
- gas chromatography
- solid phase extraction
- liquid chromatography tandem mass spectrometry
- simultaneous determination
- high resolution
- quantum dots
- electronic health record
- water soluble
- multiple sclerosis
- molecularly imprinted
- healthcare
- risk assessment
- health information
- social media
- human health
- deep learning
- single cell