Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry

GigaScience

Theodore Alexandrov⁷  Zoltan Takats⁶  Pieter C Dorrestein^1,12  Peter Maass³  Axel Walch⁴  Kathrin Maedler⁹  Herbert Thiele²  Ferdinand von Eggeling^1,11  Orlando Guntinas-Lichius^1,11  Robert Goldin^1,13  Michaela Aichler⁴  Klaus Steinhorst^1,10  Stefan Schiffler^1,10  Andrew Palmer⁷  Dennis Trede^1,10  Franziska Hoffmann^1,11  Anna K Mróz⁶  Nicole Strittmatter⁶  Jan Hendrik Kobarg²  Lena Hauberg-Lotte²  Michael Becker⁸  James S McKenzie⁶  Jeramie Watrous¹  Kirill Veselkov⁶  Janina Oetjen⁵ 

[1] Department of Medicine, Biomedical Research Facility II, University of California, San Diego, USA;Steinbeis Center SCiLS Research, Bremen, Germany;Center for Industrial Mathematics, University of Bremen, Bremen, Germany;Research Unit Analytical Pathology, Institute of Pathology, Helmholtz Center Munich, Munich, Germany;MALDI Imaging Lab, University of Bremen, Bremen, Germany;Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK;European Molecular Biology Laboratory, Heidelberg, Germany;Bruker Daltonik GmbH, Bremen, Germany;Islet Research Lab, Center for Biomolecular Interactions, University of Bremen, Bremen, Germany;SCiLS GmbH, Bremen, Germany;Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany;Skaggs School of Pharmacy & Pharmaceutical Sciences, University of California, San Diego, USA;Department of Medicine, Faculty of Medicine, Imperial College London, London, UK

关键词: imzML;    DESI;    MALDI;    Three-dimensional;    3D imaging mass spectrometry;    Benchmark datasets;   

Others  :  1204333
DOI  :  10.1186/s13742-015-0059-4

 received in 2014-11-05, accepted in 2015-04-09,  发布年份 2015

【 摘 要 】

Background

Three-dimensional (3D) imaging mass spectrometry (MS) is an analytical chemistry technique for the 3D molecular analysis of a tissue specimen, entire organ, or microbial colonies on an agar plate. 3D-imaging MS has unique advantages over existing 3D imaging techniques, offers novel perspectives for understanding the spatial organization of biological processes, and has growing potential to be introduced into routine use in both biology and medicine. Owing to the sheer quantity of data generated, the visualization, analysis, and interpretation of 3D imaging MS data remain a significant challenge. Bioinformatics research in this field is hampered by the lack of publicly available benchmark datasets needed to evaluate and compare algorithms.

Findings

High-quality 3D imaging MS datasets from different biological systems at several labs were acquired, supplied with overview images and scripts demonstrating how to read them, and deposited into MetaboLights, an open repository for metabolomics data. 3D imaging MS data were collected from five samples using two types of 3D imaging MS. 3D matrix-assisted laser desorption/ionization imaging (MALDI) MS data were collected from murine pancreas, murine kidney, human oral squamous cell carcinoma, and interacting microbial colonies cultured in Petri dishes. 3D desorption electrospray ionization (DESI) imaging MS data were collected from a human colorectal adenocarcinoma.

Conclusions

With the aim to stimulate computational research in the field of computational 3D imaging MS, selected high-quality 3D imaging MS datasets are provided that could be used by algorithm developers as benchmark datasets.

【 授权许可】

   
2015 Oetjen et al.; licensee BioMed Central.

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