Recent Advances of Ambient Mass Spectrometry Imaging and Its Applications in Lipid and Metabolite Analysis

Qi, K. H.; Wu, Lisheng; Liu, Chengyuan; Pan, Yang

doi:10.3390/metabo11110780

Cited by 25 publications

(20 citation statements)

References 142 publications

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“…Besides, due to variables like solvent composition, capillary dimensions, and air ow velocity, DESI-MSI has lesser spatial resolution than non-ambient techniques like MALDI-MSI (∼30 m). 120 Recent studies have used nano-DESI-MSI to overcome constraints and enhance spatial resolution (10 m), illustrating the potential future improvements of DESI-MSI. 121,122…”

Section: Limitationsmentioning

confidence: 99%

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview

Kumar¹

2023

Anal. Methods

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Section: Limitationsmentioning

confidence: 99%

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview

Kumar¹

2023

Anal. Methods

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“…Recently, a group shows that doping the solvent with silver ions may be able to improve the sensitivity and specificity of the DESI-MSI ( 41 ). Moreover, DESI-MSI also has lower spatial resolution than MALDI-MSI (30-50 µm) due to factors such as solvent composition, capillary size, and gas flow rate ( 42 ). To combat such limitations, several recent studies have used nano-DESI-MSI to achieve lower spatial resolutions (10 µm), demonstrating the potential advancements of DESI-MSI in the future ( 43 , 44 ).…”

Section: Common Techniques For Spatial Metabolomicsmentioning

confidence: 99%

Comparing DESI-MSI and MALDI-MSI Mediated Spatial Metabolomics and Their Applications in Cancer Studies

Wang

et al. 2022

Front. Oncol.

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Metabolic heterogeneity of cancer contributes significantly to its poor treatment outcomes and prognosis. As a result, studies continue to focus on identifying new biomarkers and metabolic vulnerabilities, both of which depend on the understanding of altered metabolism in cancer. In the recent decades, the rise of mass spectrometry imaging (MSI) enables the in situ detection of large numbers of small molecules in tissues. Therefore, researchers look to using MSI-mediated spatial metabolomics to further study the altered metabolites in cancer patients. In this review, we examined the two most commonly used spatial metabolomics techniques, MALDI-MSI and DESI-MSI, and some recent highlights of their applications in cancer studies. We also described AFADESI-MSI as a recent variation from the DESI-MSI and compare it with the two major techniques. Specifically, we discussed spatial metabolomics results in four types of heterogeneous malignancies, including breast cancer, esophageal cancer, glioblastoma and lung cancer. Multiple studies have effectively classified cancer tissue subtypes using altered metabolites information. In addition, distribution trends of key metabolites such as fatty acids, high-energy phosphate compounds, and antioxidants were identified. Therefore, while the visualization of finer distribution details requires further improvement of MSI techniques, past studies have suggested spatial metabolomics to be a promising direction to study the complexity of cancer pathophysiology.

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“…Analysis of the spatial distribution of biomolecules in tissue is an important aspect of life sciences research and involves a wide range of techniques. − Mass spectrometry imaging (MSI) is routinely used to map the spatial distribution of metals and small molecules (e.g., metabolites and lipids , ) with a variety of different sampling techniques. MSI of intact proteins is much less common due to the technical challenges of ionizing proteins directly from a substrate and manipulating large ions in the gas phase.…”

Section: Introductionmentioning

confidence: 99%

High-Throughput Deconvolution of Native Protein Mass Spectrometry Imaging Data Sets for Mass Domain Analysis

Hale,

Cooper,

Marty

2023

Anal. Chem.

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Protein mass spectrometry imaging (MSI) with electrospray-based ambient ionization techniques, such as nanospray desorption electrospray ionization (nano-DESI), generates data sets 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 the 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 data sets and transform m/z-domain image files to the mass domain. New tools enable the 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 sodium dodecyl sulfate polyacrylamide gel electrophoresis.

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Recent Advances of Ambient Mass Spectrometry Imaging and Its Applications in Lipid and Metabolite Analysis

Cited by 25 publications

References 142 publications

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview

Comparing DESI-MSI and MALDI-MSI Mediated Spatial Metabolomics and Their Applications in Cancer Studies

High-Throughput Deconvolution of Native Protein Mass Spectrometry Imaging Data Sets for Mass Domain Analysis

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