2019 Fiscal Year Annual Research Report
Immune cell-to-cell communication studied through label-free microscopy combined with machine learning
| Project/Area Number |
18K14695
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| Research Institution | Osaka University |
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Principal Investigator |
パヴィヨン ニコラ 大阪大学, 免疫学フロンティア研究センター, 特任助教(常勤) (80644525)
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| Project Period (FY) |
2018-04-01 – 2020-03-31
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| Keywords | immune response / cell-to-cell / label-free microscopy / live cell imaging / macrophage / lymphocyte / Raman spectroscopy / quantitative phase |
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| Outline of Annual Research Achievements |
During the second year of the project, we employed the label-free microscopy system that was refined during the first year to further study cell responses and cell-to-cell relations in the context of immune activation.
We first pursued our studies on macrophage activation, where we validated our approach on primary cells, and demonstrated that we can achieve over 90% of accuracy when detecting the activation state of both cell lines (Raw264) and peritoneal macrophages. Furthermore, we could also detect different sub-types of macrophages that originate from different progenitors within primary cell populations.
We then further studied lymphocytes cells and their activation process, by first studied different stimulation routes on cells lines, and could show that we can distinguish the effect of a drug cocktail that bypasses standard signaling processes) and the effect of the exposure to artificial antibody presenting cells (APC), which mimic in vivo stimulation.
We then reproduced these results with primary T cells, and showed that the differences are even larger compared to cell lines, demonstrating the ability of our approach to detect lymphocyte activation, and to distinguish purely chemical stimulation and physiological activation through the creation of an immune synapse on the T cell receptor.
Finally, we obtained preliminary results in cell-to-cell interaction. We developed protocols to create immune synapses between T cells and B cells acting as antigen-presenting cells, and obtained first results with our multimodal system.
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