Speaker: Alison Scott, University of Maryland
Topic: Exploring the spatially-resolved lipidome during lung infection by Gram-negative pathogens using mass spectrometry imaging
Date: Monday, January 13th, 2020
Time: 6:15 pm Dinner, 7:15 pm Presentation
Location: Shimadzu Scientific Instruments, Inc. Training Center 7100 Riverwood Drive, Columbia, MD 21046 (Directions)
Dinner: Please RSVP to Meghan Burke (firstname.lastname@example.org) by Friday, January 10th if you will be attending the dinner.
Abstract: Mass spectrometry imaging (MSI) is a technique for mapping the spatial distributions of molecules in sectioned tissue. Histology-preserving tissue preparation methods are central to successful MSI studies. Common fixation methods, used to preserve tissue morphology, can result in artifacts in the resulting MSI experiment including delocalization of analytes, altered adduct profiles, and loss of key analytes due to irreversible cross-linking and diffusion. This is especially troublesome in lung and airway samples, in which histology and morphology is best interpreted from 3D reconstruction, requiring the large and small airways to remain inflated during analysis. We developed an MSI-compatible inflation containing as few exogenous components as possible, forgoing perfusion, fixation, and addition of salt solutions upon inflation that resulted in an ungapped 3D molecular reconstruction through more than 300 microns. We characterized a series of polyunsaturated phospholipids (PUFA-PLs), specifically phosphatidylinositol (-PI) lipids linked to lethal inflammation in bacterial infection and mapped them in serial sections of inflated mouse lung. PUFA-PIs were identified using spatial lipidomics and determined to be spatially determinant markers of major airway features using unsupervised hierarchical clustering. Using this preparation in combination with high-content lipidome imaging, we characterized the dynamic response of the same host lipids in the context of infection by Gram-negative pathogens in mouse lungs. Two infection models were used (Francisella novicida and Pseudomonas aeruginosa) to illustrate the divergent innate immune lipid response from Toll-like receptor 4 (TLR4)-silent and TLR4-stimulating pathogens, respectively. Network analysis of the lipid response was indicative of a neutrophil-driven response to TLR4-stimulating infection. In combination, the lung inflation method and infection modeling facilitate a new portal to understand the complex role of host lipid remodeling in the innate immune response.