Elucidation of Leukocyte and Macrophage Biomarker Signatures from Drugs of Abuse Project Summary/Abstract. Drugs of abuse are metabolized by the cells of the body including macrophages and leukocytes. Macrophages are primarily responsible for the detection, phagocytosis and digestion of toxins in the bloodstream and peripheral tissues. Normal cellular metabolism of macrophages and other cells are permanently affected by the presence of toxins in the blood which may include illicit substances such as cocaine and alcohol. We propose to study macrophages and other blood cells from normal and cocaine addicted rats and mice in automated, high-throughput biomicroelectromechanical systems (BioMEMS) coupled to ion mobility mass spectrometers and obtain comprehensive measurements of metabolic precursors, products and signaling molecules in real time. We will analyze the wide-spectrum of temporally varying biochemical signature of the living cells before and during exposure to precise doses of cocaine and alcohol administered to cells in the traps using automatic inference of mathematical models. We hypothesize that the resulting metabolic models and biochemical signatures from the cells of addicted animals and normal animals will differ significantly due to permanent alterations in cell physiology brought about by prior exposure. Passive observations and those made during simple interventions can tell much about the response of the cells to a drug or toxin, but the specification of many of the interlocking and nonlinear control systems of individual cells is hidden by the very nature of closed-loop control and requires experiments that measure very large numbers of variables. The automated inference presents daunting challenges that cannot be addressed by a single discipline and hence signifies an exciting frontier for interdisciplinary research. A group of biomedical, chemical and computer engineers, chem- ists, molecular biologists and physicists at Vanderbilt, Cornell, Duke and CFD Research Corporation, propose to merge their talents and optimize computer-controlled nanoliter bioreactors that would use optical, electrical, and electrochemical sensors, two-dimensional mass spectrometry, and novel computer algorithms to design and conduct experiments on small populations of living cells. The goal of this work is to automatically infer the underlying nonlinear dynamical equations governing the behavior of the cells and their environment in the presence and absence of cocaine and alcohol. We will address this challenge by applying Cornell's Symbolic Regression and Exploration-Estimation Algorithms that use in silico coevolution of both the model and tests of the model to experimentally determine which conditions are best suited for further evolution. Our suite of micro- fabricated BioMEMS nanobioreactors, dynamic sensors, and cellular control technologies ensures that we will have adequate dynamical data to create sophisticated metabolic and signaling models of macrophages and leukocytes. This research will have a unique and remarkable educational, intellectual, medical and societal value.
The proposed work will impact public health by more accurately characterizing drug abuse and the history of drug abuse in individuals so as to tailor methods of intervention and treatment strategies on a case-by-case basis, thereby increasing the effectiveness of assisting addicted individuals in relinquishing drug-seeking behavior. This approach aims to decrease long-term medical costs associated with prolonged drug and alcohol abuse using a novel approach in the identification of off target leukocyte and macrophage biomarker signatures for rapid and reliable diagnostics of drug use/abuse history. The technology developed will be utilized to gain further understanding of the underlying biological pathways that control addictive behav- ior, which is the first step to addressing destructive behavior on the personal level.
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