New Imaging Platform Can Snap Selfie of Single Cells
Nov. 6, 2024 – UC Irvine biomedical engineers have developed a microfluidic system capable of capturing 3D images of groups of single cells. The system can rotate the cells in an assembled format to inspect free-floating individual cells encapsulated in droplets. This new arrayed-droplet optical projection tomography (ADOPT) technology allowed the researchers to take a T-cell “selfie” that could potentially be applied to assessing the body’s health status, including vitality and disease progression.
The biomedical engineers envision the system could become a powerful metric for an integrative health status, capturing a “health photo” of the individual from the image analyses of hundreds to thousands of single cells.
The ADOPT system enables fast acquisition – approximately 5 seconds per cell – of live 3D single-cell fluorescence data. The researchers inspected hundreds of T-cells, a type of white blood cell with critical immune function, and they were able to quantify and correlate cell nuclear shape to status of immune health.
A panel of single T-cell images provides a signature that captures the overall health of the immune system status, explains Abraham Lee, Chancellor’s Professor of biomedical engineering and senior author on the research, published in the Proceedings of the National Academy of Sciences.
“The shape and the roughness of the cell membrane as well as the cell nucleus reflects the ‘composite’ state of the immune system’s status,” said Lee. “So, if a cancer patient is on the mend, the immune system would have a certain ‘fingerprint’ and if the patient is losing the battle, there would be a different signature, which can be much more accurate than the current method of just counting the number of cells.”
“Typically for every immune state, there is an equilibrium that is obtained, and that means there is a distribution of different states of cells that is a result of the overall health status,” Lee said. “Other technologies take too long with low throughput and simply don’t capture the ‘dynamics’ of the cells interacting with each other and with other factors in the body.”
Braulio Cardenas, first author and graduate student, explains that the ADOPT system could help link drug treatments to specific disease states by examining the shape and condition of a person’s T-cells. “Going forward, our plan is to use deep-learning techniques to facilitate the interpretation of the data and correlation of cell morphology to health status,” said Cardenas.
– Lori Brandt
