Spatial Metabolomics for Human Kidneys
EMSL Project ID
50130
Abstract
Acute kidney injury (AKI) and chronic kidney disease (CKD) are major contributors to overall morbidity and mortality in patients in the US. However, we lack a clear understanding of the major pathways that initiate and cause progression of disease in patients with AKI and CKD. We have recently developed a spatial metabolomics approach to image small molecules in human kidneys1. Here, we propose to establish a Tissue Interrogation Site to employ untargeted and targeted spatial metabolomics analysis of tissues from normal and diseased kidneys to assess cellular metabolic “states” associated with healthy function, activation of disease, acute injury, chronic condition, and recovery. Comparing diseased versus healthy areas of the kidney, our hypothesis is that diseased cells have a recognizable shift in metabolism that can be captured by spatial metabolomics. Human kidney tissue will be assessed on a molecular level employing ultra-high resolution imaging mass spectrometry (IMS) complemented with an open bioinformatics platform for metabolite annotation and big data interrogation (Fig. 1). An untargeted approach will be used to identify dominant pathways in an agnostic manner. In addition, specific metabolic pathways will be characterized through targeted spatial metabolomics. Statistical analysis will be applied to accurately phenotype individuals with AKI or CKD. Utilizing IMS we will investigate cell and disease heterogeneity, generate high quality data for a kidney tissue atlas, facilitate structural and molecular assessment of cellular states associated with healthy and diseased function, andidentify robust signatures and pathways to accurately phenotype AKI and CKD disease subgroups. Specific metabolites, pathways, targets, and critical cells that are associated with each form of kidney diseases will help identify preventive, diagnostic, prognostic, or therapeutic strategies for precision medicine for kidney disease. With our combined expertise at University of California, San Diego (UCSD), Pacific Northwest National Laboratory (PNNL), and the European Molecular Biology Laboratory (EMBL) we have already established methods for identifying metabolites in human kidneys, employed ultra-high mass resolution IMS for tissue analysis, and developed a bioinformatics resource (METASPACE) to annotate metabolites for anatomical localization and 3-D reconstruction.
Project Details
Start Date
2017-11-21
End Date
2020-09-30
Status
Closed
Released Data Link
Team
Principal Investigator
Team Members
Related Publications
Sharma K., and L. Pasa Tolic. 2018. "Towards Individual Glomerular Phenotyping: Advent of Precision Medicine in Kidney Biopsies." PNNL-SA-135626. Richland, WA: Pacific Northwest National Laboratory.
Velickovic D., G. Zhang, D. Bezbradica, A. Bhattacharjee, L. Pasa Tolic, K. Sharma, and T. Alexandrov, et al. 2020. "Response Surface Methodology as a New Approach for Finding Optimal MALDI Matrix Spraying Parameters for Mass Spectrometry Imaging." Journal of the American Society for Mass Spectrometry 31, no. 3:508-516. PNNL-SA-147292. doi:10.1021/jasms.9b00074
Zhang G., J. Zhang, R. Dehoog, M. Darshi, S. Pennathur, C.R. Anderton, and M.A. Venkatachalam, et al. 2020. "DESI-MSI Based Spatial Metabolomics and METASPACE Indicates RNA and Mitochondrial Dysfunction in Renal Proximal Tubules of Mice with Diabetes Running Title: MS Imaging in DKD." Metabolomics. PNNL-SA-132461. doi:10.1007/s11306-020-1637-8