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Nathan Chiappa
Biomedical Engineering Ph.D. Thesis Defense
Date: Thursday, March 14, 2019
Time: 1:00pm-2:00pm
Location: CHOA Seminar Room, EBB 1005
Advisor:
Edward Botchwey, PhD
Committee Members:
Clinton Joiner, MD, PhD
Wilbur Lam, MD, PhD
Alfred Merrill, PhD
Mark Styscynski, PhD
Eberhard Voit, PhD
Title: Combining Sphingolipidomics and Computational Systems Biology to Study Red Blood Cell Sphingolipid Metabolism in Health and Disease
Abstract:
Sickle cell disease is among the most common hematologic diseases, affecting over 4 million people worldwide. Despite knowing the genetic origin of this disease for decades, our ability to treat sickle cell disease is still limited. Thus, an improved understanding of the mechanisms of sickle cell pathology is desperately needed. One aspect of sickle cell disease pathology that has not received much attention is the alteration of the membrane lipids. Sickle red blood cell membranes are subject to intense physical and oxidative damage from sickle hemoglobin. Thus, it is reasonable to hypothesize that sickle red blood cell lipid metabolism is dysfunctional. One branch of lipid metabolism that may be particularly important in red blood cells is sphingolipid metabolism. Research has shown that red blood cell sphingolipids regulate numerous process including cell death, adhesion to endothelial cells, and antioxidant defense of other lipids, all of which are areas relevant to sickle cell pathology. Despite this, little is known about red blood cell sphingolipid metabolism under normal or sickle conditions.
In this thesis, we combine liquid chromatography-tandem mass spectrometry with computational modeling to characterize red blood cell sphingolipid metabolism under normal conditions and in the context of sickle cell disease. First, we collected mechanistic information on red blood cell sphingolipid metabolism from the literature and integrated it into a computational model. This model was used as a tool for interpreting both steady-state and dynamic data from different experiments throughout the thesis. Second, we measured the steady-state and dynamic concentrations of sphingolipids in normal and sickle cell red blood cells using LC-MS/MS. From these measurements, we were able to determine that sickle red blood cells have significantly higher concentrations of many different sphingolipid classes compared to normal red blood cells and that a specific lipid transporter may be involved. Finally, we investigated the contribution of a specific subset of red blood cells, the reticulocytes, to the alterations in sphingolipid concentrations observed in sickle cell disease. We isolated reticulocyte-enriched and reticulocyte-depleted sickle red blood cell populations and then measured their steady-state and dynamic sphingolipid concentrations using LC-MS/MS. Our analysis showed that sickle reticulocytes have elevated concentrations of sphingolipids compared to sickle erythrocytes.
The results of this work represent significant contributions to our understanding of basic red blood cell biology and to sickle cell disease pathology. Further, the modeling work helps advance the field of mathematical biology by providing a template for how to address some of the challenges involved with creating models of lipid metabolic systems. The model can be modified and expanded in the future to serve as tool to predict how red blood cell sphingolipid metabolism will behave under novel pathologic and pharmacologic situations.
