High-throughput deconvolution of native protein mass spectrometry imaging datasets for mass domain analysis.

21 July 2023, Version 2
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Protein mass spectrometry imaging (MSI) with electrospray-based ambient ionization techniques, such as nanospray-desorption electrospray ionization (nano-DESI), generates datasets in which each pixel corresponds to a mass spectrum populated by peaks corresponding to multiply-charged protein ions. Importantly, the signal associated with each protein is split among multiple charge states. These peaks can be transformed into the mass domain by spectral deconvolution. When proteins are imaged under native/non-denaturing conditions to retain non-covalent interactions, deconvolution is particularly valuable in helping interpret the data. To improve acquisition speed, signal-to-noise ratio, and sensitivity, native MSI is usually performed using mass resolving powers that do not provide isotopic resolution, and conventional algorithms for deconvolution of lower-resolution data are not suitable for these large data sets. UniDec was originally developed to enable rapid deconvolution of complex protein mass spectra. Here, we developed an updated feature set harnessing the high-throughput module, MetaUniDec, to deconvolve each pixel of native MSI datasets and transform m/z-domain image files to the mass domain. New tools enable reading, processing, and output of open format .imzML files for downstream analysis. Transformation of data into the mass domain also provides greater accessibility, with mass information readily interpretable by users of established protein biology tools such as SDS-PAGE.

Keywords

mass spectrometry imaging
MSI
native mass spectrometry
intact proteoform
nano-DESI
imzML
open-source
software

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