Graduate School of Science, Nagoya City University
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In our laboratory, we develop and use cutting-edge technologies for measuring and reproducing odor concentrations in microenvironments, analyzing the movement of animals and cells, and processing three-dimensional images using microscopes .
In addition, the nematode C. elegans, which is easy to breed and analyze, can be used as an assay system to analyze the effects of taste substances, odor substances, drugs, and other physiologically active substances on living organisms using a variety of imaging technologies and artificial intelligence .
Please feel free to contact us regarding joint research etc.
1) Measurement and reproduction of odor concentration in a microenvironment
Since it is necessary to aspirate air to measure odors, it is difficult to measure odor concentrations in a microenvironment. By developing our own technology, we have succeeded in actually measuring odor concentration gradients formed by volatilization and diffusion in a 9 cm diameter plastic petri dish. We have also succeeded in accurately creating odor time gradients under a microscope. (Yamazoe-Umemotoo et al., Neurosci Res 2015; Tanimoto et al., eLife 2017; Yamazoe et al., Bio-protocol 2018; Tanimoto and Kimura, Bio-protocol 2021)
2) Analysis of animal and cell migration
Various technological developments have made it easier to measure "movement." For human and animal movements, small GPS devices and cameras are used, and for cell movements, cutting-edge microscopes are used. However, it is extremely difficult to find the "reason for movement" of humans, animals, and cells from the measured data. We have developed classical and cutting-edge artificial intelligence technologies to understand the "reason for movement." (Yamazaki et al., Front Neurosci 2019; Maekawa et al., Nat Commun 2020; Kimura, Experimental Medicine Special Edition "Using Machine Learning in Life Sciences!" 2020)
3) Image processing for microscopes, etc.
Advances in microscopy technology have made it possible to acquire 3D images at high speeds, allowing the dynamic activity of tissues and cells to be recorded as images. However, it is difficult to identify individual "cells" from a stack of multiple 2D images, especially in time-series 3D image data, and to track the positional changes of each cell. By developing our own deep learning technology, we have made it possible to identify and track cells from various time-series 3D image data. (Voleti et al., Nat Meth 2019; Wen et al., bioRxiv 2018 and paper in revision)
4) Searching for drug/biologically active substance target molecules at the individual level using artificial intelligence technology
Using C. elegans, we can search for target proteins of drugs and other bioactive substances at the individual level. For example, TOR, the target protein of the immunosuppressant rapamycin, was identified by forward genetic screening using yeast. Of course, there are issues such as sub-type specificity, but it is true that drugs and bioactive substances act on orthologs of evolutionarily conserved genes. In fact, we found that a C. elegans D2 dopamine receptor-deficient strain and treatment with the D2 dopamine receptor antagonist haloperidol showed the same behavioral abnormalities (J Neurosci 2010).
In the nervous system of C. elegans, various neurotransmitters such as glutamate, GABA, acetylcholine, serotonin, and dopamine, as well as their ionotropic or metabotropic receptors, are evolutionarily conserved and function. Therefore, it is possible to rapidly identify target molecules of psychotropic drugs, whose in vivo actions are still largely unknown, by the following procedure: treatment of wild-type C. elegans → discovery of phenotypes → isolation of resistant strains by genetic screening → identification of genes by whole genome sequencing.
We have a wealth of experience in quantitative analysis of C. elegans behavior and have recently introduced artificial intelligence technology (Neurosci Res 2015; Sci Rep 2016; eLife 2017; Front Neurosci 2019; Nat Commun 2020), which allows us to efficiently detect behavioral abnormalities caused by drugs, etc. Furthermore, we can rapidly elucidate where and what abnormalities are occurring in neural circuits by using whole-brain activity measurement by three-dimensional high-speed imaging using our unique artificial intelligence technology (bioRxiv 2018; in revision) and whole-neuron identification technology by multicolor imaging by international collaboration (Yemini et al., Cell 2020).
In other words, we can elucidate when, where and how drugs and biologically active substances act to affect individual functions across all hierarchical levels: genes, cells and the individual.