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Applications of the Single-probe: Mass Spectrometry Imaging and Single Cell Analysis under Ambient Conditions
Published on: June 14, 2016
Mass spectrometry imaging under ambient conditions
Chunping Wu1, Allison L Dill, Livia S Eberlin
1Department of Chemistry, Purdue University, West Lafayette, Indiana 47907, USA.
Mass Spectrometry Reviews
|September 22, 2012
Summary
Mass spectrometry imaging (MSI) offers label-free molecular mapping. Recent ambient ionization techniques enable versatile, in-situ analysis of untreated samples, advancing various scientific fields.
Area of Science:
- Analytical Chemistry
- Molecular Imaging
- Biotechnology
Background:
- Mass spectrometry imaging (MSI) provides label-free, spatially resolved molecular information.
- Traditional MSI methods often require vacuum conditions and sample preparation.
- Ambient ionization techniques have emerged as a significant advancement, enabling analysis under atmospheric pressure.
Purpose of the Study:
- To review recent developments and applications of Mass Spectrometry Imaging (MSI).
- To highlight the capabilities of various ambient ionization techniques within MSI.
- To discuss the role of bioinformatics and future challenges in ambient MSI.
Main Methods:
- Review of recent literature on Mass Spectrometry Imaging (MSI).
- Focus on ambient ionization techniques including DESI, LAESI, PESI, DAPPI, fs-LDI, LEMS, IR-LAMICI, LMJ-SSP MS, nano-DESI, LTP, and LA-FAPA.
- Discussion of tandem mass spectrometry and bioinformatics applications in MSI.
Main Results:
- Ambient ionization techniques allow MSI on untreated samples under atmospheric pressure.
- MSI can provide multiplexed molecular information without labeling or staining.
- Tandem MS and bioinformatics enhance specificity, structural identification, and data interpretation.
Conclusions:
- Ambient MSI techniques offer powerful, versatile tools for molecular analysis in diverse fields.
- The integration of chemical reactions and tandem MS expands the analytical capabilities of MSI.
- Bioinformatics plays a crucial role in interpreting complex MSI data, particularly for biological applications.
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