Deep-learning based three-dimensional label-free tracking and analysis of immunological synapses of chimeric antigen receptor T cells

Abstract

We propose and experimentally validate a label-free, volumetric, and automated assessment method of immunological synapse dynamics using a combinational approach of optical diffraction tomography and deep learning-based segmentation. The proposed approach enables automatic and quantitative spatiotemporal analyses of immunological synapse kinetics regarding morphological and biochemical parameters related to the total protein densities of immune cells, thus providing a new perspective for studies in immunology.

Three-dimensional label-free observation of individual bacteria upon antibiotic treatment using optical diffraction tomography

“…The lifetime of the bulge can also be measured. In this case, combination with the segmentation method will serve as the key to analysis [24]. We believe that the methods presented in this paper will provide microbiologists with broader insights into the various responses of bacteria to antibiotics.…”

“…Because RI distributi ons serve as both intrinsic cell markers and indicators of protein densities, ODT meets the demands of quantitative phenotypic imaging of unlabeled live cells. Thus, its applications have been rapidly expanded for investigations on hematology [22], microalgae [23], immunology [24], infectious diseases [25,26], plant biology [27], cell biology [27,28], neuroscience [29], and drug discovery [30]. Some bacterial studies have also used ODT [31,32], but its application for bacterial microbiology is in a nascent stage.…”

Interleukin‑18 and ‑10 may be associated with lymph node metastasis in breast cancer

“…Therefore, it can be used as a diagnostic index of breast cancer; it may also function as a potential target of breast cancer treatment. However, considering that monocytes, Th2 cells, macrophages and activated B cells are all able to secrete IL-10, further studies are needed to determine the source of IL-10 using the Th2 trace-labeling method (38) to further validate the findings of this study.…”

Live Cell Imaging with Holotomography and Fluorescence

“…Some of the latest work to be published using HT exploits the computing power that accompanies many high-end microscopy systems. Investigating the 4D interaction dynamics of T cells and their targets in the immunological synapse (IS), the joint team from Tomocube and the Korea Advanced Institute of Science and Technology (KAIST) used the reconstructed RI map from the HT-2 microscope (see Figure 6) as input for a machine-learning model to segment CD19-positive K562 cells and CD19-specific chimeric antigen receptor T cells (CAR-T19 cells), considered in some circles as the next-generation, personalized, anti-cancer treatment [8]. Their results can be found at bioRxiv (https://doi.org/10.1101/539858).…”