Automation of Robot-Assisted Optical Manipulation of Biological Cells

With advantages such as non-physical cell contact and relatively high efficiency, the application of optical tweezers for manipulation of biological objects such as cells has received increasing attention both for medical applications and for making fundamental advances in biological sciences. However, manual intervention and the low throughput of existing optical manipulation systems create substantial hurdles that prevent the widespread adaptation of this emerging new technology. The automation of such techniques has hence become a key enabler for further advancement of optical cell manipulation. In this proposed research, we will show how automation technology considerably improves the optical manipulation of cells.This proposal will address four important issues in the development of automatic cell manipulation tools with robotically controlled optical tweezers. The first issue is characterizing the dynamics model of optically trapped cells. With this modeling information, we will determine how various environmental factors affect cell behavior and thus control these influences and optimize the manipulation setup for automatic operations. The second issue is developing a closed-loop control methodology for rapid and accurate positioning of single cells while locating the trapped cell within the optical trap. This will provide substantial technological development by controlling both cell positioning and cell trapping simultaneously. The third issue is extending the single-cell controller towards a parallelized control mechanism for manipulating multiple cells in parallel. This research outcome will enable many biomedical applications that must be done automatically, e.g., the transport of a group of human embryonic stem cells (hESC) into an array in right pairs for fusion, and manipulating multiple T cells while maintaining the fixed cell patterns for study of cell-to-cell interactions. The last issue is studying motion planning for automatically transporting the cells to a user-defined goal region while avoiding collisions with other cells and obstacles present in the workspace. The minimization of optical damage to the trapped cells is treated as a new important criterion aside from the criteria of obstacle avoidance and shortest path, among others.This research represents an important step in determining how engineering can provide new fundamental knowledge and advance cell-based medicine. Many cellular studies are limited by the availability of novel high-resolution, high-throughput tools. Automation technology will greatly advance the field of cell manipulation and profoundly affect the device industry for health care in the near future.