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Metabolite Imager: customized spatial analysis of metabolite distributions in mass spectrometry imaging

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Abstract

Mass spectrometry (MS) is currently the most utilized analytical instrument for evaluating the metabolite composition of a biological sample at both the qualitative and quantitative level. The exponential growth of raw data generated through increasingly versatile mass spectrometers requires sophisticated algorithms to process and visualize the raw data to address biological questions. The structural and quantitative diversity of a single species’ metabolome (e.g. all metabolite species) under different experimental conditions itself forms a very large and complex dataset to analyze. We have developed a free, Java-based metabolomics application “Metabolite Imager” (www.metaboliteimager.com) that enables customized analysis and visualization of the metabolite distributions in tissues acquired through MS-based imaging approaches. Metabolite Imager algorithms perform customized targeted searching of metabolites through user-defined and publicly-available databases enabling the analysis of spatial distributions of large metabolite numbers in tissue sections. Metabolite Imager’s automated, two-dimensional image generator has several customizable features for producing high-resolution images. Additional Metabolite Imager algorithms support identifying targeted and unknown detected metabolites in selected tissue regions using spatially-based enrichment analysis that could impact metabolic engineering strategies. Co-localization algorithms of metabolites and selected ions by m/z enable analysis of precursor-product relationships in situ that will be important for expanding the biological context of metabolic pathways.

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Acknowledgements

Application development is supported in part by grants from the US Department of Energy, BER Division, DE-FG02-09ER64812 and Cotton Incorporated (Agreement# 08-395) to KDC. The MSI facilities are supported by the Hoblitzelle Foundation. We thank Kerstin Strupat and Mari Prieto Conaway of Thermo-Fisher Scientific for technical support in MSI experiments. Mr. Patrick Horn was supported through the UNT Doctoral Fellowship program. We thank Dr. Markus Lange, Washington State University, and Dr. Vladimir Shulaev, University of North Texas, for their helpful comments on the manuscript. We also thank Drew Sturtevant, Danielle Anderson, Clayton Rowe, and Dr. Sarah Holt for testing and providing feedback on application.

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Correspondence to Patrick J. Horn or Kent D. Chapman.

Electronic supplementary material

Below is the link to the electronic supplementary material.

11306_2013_575_MOESM1_ESM.pdf

Online Resource 1. Generalized processing schematic mapping the entities necessary to generate a 2D imaging in Metabolite Imager (PDF 636 kb)

11306_2013_575_MOESM2_ESM.txt

Online Resource 2. Example tab-delimited, text file representing a single raw spectral scan converted using Metabolite Imager (TXT 60 kb)

Online Resource 3. Example imaging setup file for Metabolite Imager 2D image processing (XLSX 17 kb)

11306_2013_575_MOESM4_ESM.txt

Online Resource 4. Example list of all ions to search for in a particular 2D imaging process with conflicts representing peaks that might not be resolved due to the selected searching tolerances (TXT 98 kb)

Online Resource 5. Table of parameters defining a single metabolite species in Metabolite Imager (PDF 151 kb)

Online Resource 6. Example metabolite database file (CSV 6 kb)

Online Resource 7. Example results output of phosphatidylcholine absolute intensity analysis (XLS 1503 kb)

11306_2013_575_MOESM8_ESM.xls

Online Resource 8. Example results from searching and annotating all peaks within a scan from an cottonseed section (XLS 848 kb)

11306_2013_575_MOESM9_ESM.txt

Online Resource 9. Example seed imaging filter file with values (1 or 0) designating either the inclusion or exclusion of this spot from additional analysis (TXT 82 kb)

11306_2013_575_MOESM10_ESM.pdf

Online Resource 10. Analysis of standard, free gossypol for detection of in-source fragments. (a) MALDI-MS full scan, negative mode acquisition of gossypol standard. Peaks with the selected red box are amplified in part (b) showing low amounts of hemigossypol likely produced through in-source fragmentation and the absence of desoxyhemigossypol (PDF 264 kb)

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Horn, P.J., Chapman, K.D. Metabolite Imager: customized spatial analysis of metabolite distributions in mass spectrometry imaging. Metabolomics 10, 337–348 (2014). https://doi.org/10.1007/s11306-013-0575-0

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