Mass spectrometry method development

Mixed-metal cluster generating reaction solutions contain several species of similar composition and structure that often result in hard-to-separate product mixtures. Here, the authors analyze elemental compositions obtained via high-resolution mass spectrometry with a computational permutative approach and assign individual structures of nickel gallium intermetalloid clusters without the need to isolate pure clusters.

The use of one dimensional devices in nanomechanical mass spectrometry leads to a trade-off between analysis time and resolution. Here, the authors report single-particle mass spectrometry using integrated optomechanical resonators, impervious to particle position, stiffness or shape.

Electrospray ionization loses most ions upon transfer into high vacuum in a mass spectrometer. Here, the authors present a nanopore ion source that emits ions directly into vacuum from aqueous solutions, achieving an ion transmission efficiency of over 90%.

Untargeted metabolomic analysis provides comprehensive metabolic profiling but faces challenges in medical application. Here, the authors present an explainable deep learning method for end-to-end analysis on raw metabolic signals to differentiate metabolomic profiles of cancers with high accuracy.

Protein phosphorylation plays critical roles in myriad cell processes. In this work, the authors apply new mass spectrometer technology to detect and quantify tens of thousands of protein phosphorylation sites within one hour or less of analysis. This technology has potential to greatly accelerate biological discovery.

Collision-induced dissociation tandem mass spectrometry offers to resolve molecular structures through library searches, however, for de novo identifications, one must often rely on in silico-generated spectra as reference. Here, the authors evaluate in silico generated MSⁿ product ion structures by comparison with spectroscopically established structures and find that for 36 randomly selected MS/MS product ions, the vast majority of annotations in three major libraries are incorrect, primarily due to unaccounted for cyclization rearrangements.

Native mass spectrometry of membrane proteins in commonly used detergents are not ideal for preserving non-covalent interactions. Here, the authors develop new detergents for native MS of intact membrane proteins, opening new opportunities to study membrane proteins in various detergents.

The existence of large number of isomers poses challenges for lipidomic analysis. The authors integrate hydrophilic interaction liquid chromatography, trapped ion mobility, and isomer-resolved MS/MS into a single system, enabling deep profiling of phospholipidomes at fast speed and wide coverage.

Identification of chemical compounds, present in a sample, is a fundamental task of chemical analysis, but matching obtained spectra with chemical databases is limited to identifying known molecules. Here, the authors report a deep learning architecture for recommending molecular structures, including those of novel molecules, given sample mass spectra alone.

Ozone-induced dissociation (OzID) coupled with ion mobility spectrometry-mass spectrometry (IMS-MS) provides the capacity for in-depth structural elucidation of lipids with isomer separation and confident assignment of double bond positions, however, OzID data analysis remains very challenging. Here, the authors develop a Python tool, LipidOz, for the automated determination of lipid double bond locations from complex LC-OzID-IMS-MS data, with a combination of traditional automation and deep learning approaches.

Heavy water metabolic labeling followed by liquid chromatography coupled mass spectrometry (LC-MS) is a powerful approach to characterize in vivo protein turnover rates, however, peptide co-elution causes overlap of their isotope profiles in LC-MS and affects the proteome coverage. Here, the authors develop an approach to increase the proteome coverage for in vivo protein turnover by using partial isotope profiles from two mass isotopomers.

Mass spectrometry is a powerful approach for untargeted lipidomics, however, the unambiguous determination of double bond positions remains challenging. Here, the authors present an approach for double bond position-resolved untargeted lipidomics using a combination of oxygen attachment dissociation and computational mass spectrometry to accurately annotate the biologically relevant lipidome.

There is a need for dataset-dependent MS² acquisition in trapped ion mobility spectrometry imaging. Here the authors report spatial ion mobility-scheduled exhaustive fragmentation (SIMSEF) which enables on-tissue metabolite and lipid annotation in mass spectrometry bioimaging studies, and use this to visualise the chemical space in rat brains.

Mass spectrometry imaging is a suitable tool for the analysis of non-cohesive materials. Here, authors show that it can be used to detect persistent organic pollutants (POPs) and heavy metals (HMs) in biosolids using small amounts of material with speed and safety.