Integrated molecular imaging reveals tissue heterogeneity driving host-pathogen interactions

James E. Cassat, Jessica L. Moore, Kevin J. Wilson, Zach Stark, Boone M. Prentice, Raf Van De Plas, William J. Perry, Yaofang Zhang, John Virostko, Daniel C. Colvin, Kristie L. Rose, Audra M. Judd, Michelle L. Reyzer, Jeffrey M. Spraggins, Caroline M. Grunenwald, John C. Gore, Richard M. Caprioli, Eric P. Skaar

Research output: Contribution to journalArticleScientificpeer-review

27 Citations (Scopus)


Diseases are characterized by distinct changes in tissue molecular distribution. Molecular analysis of intact tissues traditionally requires preexisting knowledge of, and reagents for, the targets of interest. Conversely, label-free discovery of disease-Associated tissue analytes requires destructive processing for downstream identification platforms. Tissue-based analyses therefore sacrifice discovery to gain spatial distribution of known targets or sacrifice tissue architecture for discovery of unknown targets. To overcome these obstacles, we developed a multimodality imaging platform for discovery-based molecular histology. We apply this platform to a model of disseminated infection triggered by the pathogen Staphylococcus aureus, leading to the discovery of infection-Associated alterations in the distribution and abundance of proteins and elements in tissue in mice. These data provide an unbiased, three-dimensional analysis of how disease affects the molecular architecture of complex tissues, enable culture-free diagnosis of infection through imaging-based detection of bacterial and host analytes, and reveal molecular heterogeneity at the host-pathogen interface.

Original languageEnglish
Article numbereaan6361
JournalScience Translational Medicine
Issue number432
Publication statusPublished - 2018

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