scholarly journals Multimodal Imaging Mass Spectrometry of Murine Gastrointestinal Tract with Retained Luminal Content Shows Molecular Localization Patterns

2021 ◽  
Author(s):  
Emma R. Guiberson ◽  
Aaron G. Wexler ◽  
Christopher J. Good ◽  
Eric P. Skaar ◽  
Jeffrey M. Spraggins ◽  
...  

ABSTRACTDigestive diseases impact 62 million people a year in the United States. Despite the central role of the gut to human health, past imaging mass spectrometry (IMS) investigations into the gastrointestinal tract are incomplete. The gastrointestinal tract, including luminal content, harbors a complex mixture of microorganisms, host dietary content, and immune factors. Existing imaging approaches remove luminal content, and images focus on small regions of tissue. Here, we demonstrate the use of a workflow to collect multimodal imaging data for both intestinal tissue and luminal content. This workflow for matrix-assisted laser desorption/ionization imaging mass spectrometry retains luminal content and expands the amount of tissue imaged on one slide. Results comparing tissue and luminal content show unique molecular distributions using multimodal imaging modalities including protein, lipid, and elemental imaging. Leveraging this method to investigate intestinal tissue infected with Clostridioides difficile compared to control tissue shows clear differences in lipid abundance of various lipid classes in luminal content during infection. These data highlight the potential for this approach to detect unique biological and markers of infection in the gut.

2020 ◽  
Vol 3 (1) ◽  
pp. 61-87 ◽  
Author(s):  
Theodore Alexandrov

Spatial metabolomics is an emerging field of omics research that has enabled localizing metabolites, lipids, and drugs in tissue sections, a feat considered impossible just two decades ago. Spatial metabolomics and its enabling technology—imaging mass spectrometry—generate big hyperspectral imaging data that have motivated the development of tailored computational methods at the intersection of computational metabolomics and image analysis. Experimental and computational developments have recently opened doors to applications of spatial metabolomics in life sciences and biomedicine. At the same time, these advances have coincided with a rapid evolution in machine learning, deep learning, and artificial intelligence, which are transforming our everyday life and promise to revolutionize biology and healthcare. Here, we introduce spatial metabolomics through the eyes of a computational scientist, review the outstanding challenges, provide a look into the future, and discuss opportunities granted by the ongoing convergence of human and artificial intelligence.


2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Stefania Alexandra Iakab ◽  
Lluc Sementé ◽  
María García-Altares ◽  
Xavier Correig ◽  
Pere Ràfols

Abstract Background Multimodal imaging that combines mass spectrometry imaging (MSI) with Raman imaging is a rapidly developing multidisciplinary analytical method used by a growing number of research groups. Computational tools that can visualize and aid the analysis of datasets by both techniques are in demand. Results Raman2imzML was developed as an open-source converter that transforms Raman imaging data into imzML, a standardized common data format created and adopted by the mass spectrometry community. We successfully converted Raman datasets to imzML and visualized Raman images using open-source software designed for MSI applications. Conclusion Raman2imzML enables both MSI and Raman images to be visualized using the same file format and the same software for a straightforward exploratory imaging analysis.


2020 ◽  
Vol 31 (12) ◽  
pp. 2401-2415
Author(s):  
Elizabeth K. Neumann ◽  
Katerina V. Djambazova ◽  
Richard M. Caprioli ◽  
Jeffrey M. Spraggins

2019 ◽  
Vol 116 (44) ◽  
pp. 21980-21982 ◽  
Author(s):  
William J. Perry ◽  
Jeffrey M. Spraggins ◽  
Jessica R. Sheldon ◽  
Caroline M. Grunenwald ◽  
David E. Heinrichs ◽  
...  

Siderophores, iron-scavenging small molecules, are fundamental to bacterial nutrient metal acquisition and enable pathogens to overcome challenges imposed by nutritional immunity. Multimodal imaging mass spectrometry allows visualization of host−pathogen iron competition, by mapping siderophores within infected tissue. We have observed heterogeneous distributions of Staphylococcus aureus siderophores across infectious foci, challenging the paradigm that the vertebrate host is a uniformly iron-depleted environment to invading microbes.


2014 ◽  
Vol 46 (S1) ◽  
pp. 375-378 ◽  
Author(s):  
Jörg Hanrieder ◽  
Oskar Karlsson ◽  
Eva B. Brittebo ◽  
Per Malmberg ◽  
Andrew G. Ewing

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