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Sample Preparation Strategies for Mass Spectrometry Imaging of 3D Cell Culture Models
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Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry
Janina Oetjen1, Kirill Veselkov2, Jeramie Watrous3
1MALDI Imaging Lab, University of Bremen, Bremen, Germany.
Gigascience
|May 6, 2015
Summary
Researchers have released 3D imaging mass spectrometry (MS) datasets to advance computational analysis. These high-quality, publicly available datasets will serve as benchmarks for developing new algorithms in 3D imaging MS.
Area of Science:
- Analytical Chemistry
- Bioinformatics
- Computational Biology
Background:
- Three-dimensional (3D) imaging mass spectrometry (MS) offers unique advantages for molecular analysis in biological and medical research.
- Challenges exist in visualizing, analyzing, and interpreting large 3D imaging MS datasets.
- Bioinformatics research is limited by the absence of standardized benchmark datasets for algorithm evaluation.
Purpose of the Study:
- To provide high-quality 3D imaging MS datasets for computational research.
- To stimulate the development and comparison of algorithms for 3D imaging MS data analysis.
Main Methods:
- Acquisition and curation of 3D imaging MS datasets from various biological systems.
- Data deposited into the open metabolomics data repository, MetaboLights.
- Utilized two types of 3D imaging MS: MALDI-MS and DESI-MS.
Main Results:
- High-quality 3D imaging MS datasets from five samples were generated and made publicly available.
- Datasets include murine pancreas, murine kidney, human oral squamous cell carcinoma, microbial colonies, and human colorectal adenocarcinoma.
- Overview images and data access scripts are provided.
Conclusions:
- The released datasets serve as valuable benchmarks for computational 3D imaging MS algorithm development.
- Facilitates reproducible research and comparison of analytical methods.
- Aims to advance the routine application of 3D imaging MS in biology and medicine.
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