This program aims to develop a suite of intelligent nanoparticles (iNPs) – novel interactive in vivo tools for neuroscience. With their sophisticated adaptive behaviors and context-dependent functions, the intelligent nanoparticles will sense key molecules in the brain in real-time, and respond by precise delivery of small molecules to functionally activated cells. This will make a critical difference in the leading neuroscience approach of chemogenetics where it will help unravel causal relationships between molecular events and high-level brain activity.
The iNPs will help solve key problems of chemical neuroreceptor control, by providing
(i) spatial selectivity in the presence of multiple unknown cell types;
(ii) ways to establish causation, by the capacity for in vivomonitoring of molecular processes in real time;
(iii) adaptive, conditional responses driven by molecules secreted by cells;
(iv) immunity to complex background interference.These technological barriers currently prevent and /or limit the determination of functional brain circuits underpinning physiology and behavior.
The iNPs will have broad impact beyond neuroscience. With their capacity for real time sensing and precise delivery in complex biological samples, they will address the challenges of the current molecular diagnostic technology. They will be able to selectively perform their actions in a functionally heterogeneous mixture of different cell types communicating via secreted products (signalling molecules, cytokines, exosomes etc). Such environments are highly relevant across the whole spectrum of the life sciences, including for the study of the immune system, for biomarker diagnostics, and in the rapidly advancing areas of commercial cell technologies and food safety.
1. G. Liu*, et al., iScience, 2019, 20, 137-147.
2. K. Ma, G. Liu*, Nanomedicine, 2019, 14(9). 1-11
3. K. Wen, et al., G. Liu, H. Huang*, ACS Appl. Mater. Interfaces, 2019, 11, 19, 17884-17893
4. T. Jiang, et al., G. Liu, P. Zhang*, Anal. Chem., 2019, 91, 11, 6996-7000
5. K. Ma, et al.,G. Liu*, ACS Sens., 2018, 3(2), 320-326
6. G. Liu*, et al., Nanoscale, 2017, 9(15), 4934-4943
Prof Ewa Goldys, UNSW
Prof Hong Qiao, Sydney University
Prof Guojun Liu, ANSTO
Prof Pengfei Zhang, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences
Prof Hui Huang, University of Chinese Academy of Sciences