PROJECT SUMMARY. The chemical interplay within cellular networks facilitates diverse functions of organ systems and contributes to human health and disease. The human kidney is a complex organ composed of an average of one million nephrons that individually contain at least 26 distinct cell types. Nephrons then form a network consisting of a glomerulus that is linked to various tubular segments, capillaries, lymphatics, and peritubular interstitial spaces. This dynamic cellular network not only varies from one individual to another but throughout the kidney itself. Because the kidney is responsible for waste management, electrolyte balance, blood pressure control, and red blood cell production, differences in cellular composition or chemistry can greatly impact efficiency or disease progression. To date, there is not complete understanding of the natural variance in the numbers of specific cell types nor their respective chemistries within the kidney. Even less is known about how these metrics relate to sex and race. Here, we propose to use a combination of imaging mass spectrometry (IMS) and co-detection by indexing multiplexed immunofluorescence (CODEX IF) to establish a baseline of what molecules and cellular populations constitute a normal, healthy kidney as well as how these change as a function of specific patient demographics. While understanding the cellular and molecular constituents of healthy kidney tissue is important by itself, this knowledge has clear implications in the definition of different disease states and phenotypes, such as diabetic nephropathy and organ failure. We predict accomplishing these tasks through two key aims: 1. determine the molecular profiles of functional tissue regions (e.g. glomeruli, cortex, and medulla) within the human kidney as the function of sex and race using imaging mass spectrometry and 2. investigate the composition of cell types within the medulla, cortex, and renal pelvis as a function of these demographics using CODEX IF. In brief, IMS allows visualization of hundreds to thousands of endogenous metabolites and lipids, while CODEX IF labels cell types and structures at a higher plexity than traditional IF methods. Though both approaches provide essential information on their own, we can synergistically combine the data to obtain molecular profiles of individual cell types to better parse the chemical differences between regions of tissue and human patients. Ultimately, there will be molecules that are detected within every tissue as well as cell compositions that are conserved among all the assayed patients. Additionally, there will likely be rare molecules or unique cellular profiles that differ from the average. Both events are essential for understanding heathy function with a longer-term goal of determining how these similarities and differences contribute to disease development and progression. While a large-scale project, I am aided by many scientific leaders (see letters of support) who a...