(2cn) Development and Implementation of Organic Color Center Nanosensors for Biomedical Applications

My research goal is the development of novel nanosensor technology to investigate disease biology and address current diagnostic challenges. My group will utilize organic color centers (OCCs, synthetic sp3 defect center covalently incorporated into fluorescent carbon nanotubes) as next-generation optical biosensors. Specific problems that my group will tackle include 1) the dearth of robust tools available to quantify bioanalytes in live cells and in vivo and 2) the lack of impactful diagnostic methods for cancers and many other diseases. To address these problems, I propose to investigate 1) synthetic strategies to elicit molecular sensitivity of OCC-based nanosensors using our expertise in nanoscale engineering and data analytics, 2) machine learning-based nanosensor array platform to improve diagnostic accuracy, 3) the potential of the array to facilitate identification of novel biomarkers, and 4) biological processes with focusing problems in lysosome biology and autophagy by using OCC nanosensors via following Specific Aims:

Specific Aim 1: Systematic Design and Synthesis of Optical Nano-Bio Sensors
Organic color centers are promising candidates for bioimaging and sensing because of the highly photostable near-infrared emission, biocompatibility, and optical responsivity to the local chemical environment. However, there is no intuition or established workflow to effectively design OCC-based nanosensors. We will investigate two different approaches, 1) molecularly specific interactions with bioconjugation and 2) corona phase molecular recognition, to sensitize the nanosensors to the targets of interest (protein and/or small metabolites). Advanced data analyses will be employed to establish the design rules and workflow of the sensor development.
Specific Aim 2: Develop Machine Perception Nanosensor Array to Capture a Whole Disease Fingerprint
Serum biomarker measurements have been widely used as diagnostic/prognostic indicators, but many markers are not sufficiently sensitive and/or specific to accurately identify the disease state. This project aims to build a machine perception nanosensor array platform technology to detect whole disease fingerprints from patient biofluids. The sensor technology will be optimized and validated for pancreatic cancer to improve diagnoses and biomarker discovery processes.
Specific Aim 3: Finding Metabolic Vulnerabilities in Autophagy Dysregulated Cancers
OCC-based lysosomal pH nanosensors are capable of quantifying endolysosomal pH transiently in live cells and in vivo. The sensor-enabled biological finding that cancer cell lines exhibit heterogenous lysosomal acidification caused by mTORC inhibition, suggesting potential autophagic vulnerabilities in certain cancers. We will utilize OCC-based nanosensors as a biochemical research tool to investigate the mechanism of heterogenous lysosomal dysregulation upon autophagy activation in cancers and identify new therapeutic targets in combination with conventional cell biology assays.

Teaching Interests:
I am immediately able to teach courses in materials science, thermodynamics, kinetics, bionanotechnology, and any of core undergraduate and graduate classes in chemistry. I would be interested in developing new courses the incorporation of advanced data analytics and nanotechnology into translational diagnostics. In my classroom, I will strive to incorporate both my research and other work at the forefront of the field in reading materials, laboratory investigation, and critical thinking.