著者

Shinji C. Nagasaki Tomonori D. Fukuda Mayumi Yamada Yusuke III Suzuki Ryo Kakutani Adam T. Guy Itaru Imayoshi

出版者

Japan Society for Cell Biology

雑誌

Cell Structure and Function (ISSN:03867196)

巻号頁・発行日

pp.22074, (Released:2022-12-16)

被引用文献数

1

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The Gal4/UAS system is a versatile tool to manipulate exogenous gene expression of cells spatially and temporally in many model organisms. Many variations of light-controllable Gal4/UAS system are now available, following the development of photo-activatable (PA) molecular switches and integration of these tools. However, many PA-Gal4 transcription factors have undesired background transcription activities even in dark conditions, and this severely attenuates reliable light-controlled gene expression. Therefore, it is important to develop reliable PA-Gal4 transcription factors with robust light-induced gene expression and limited background activity. By optimization of synthetic PA-Gal4 transcription factors, we have validated configurations of Gal4 DNA biding domain, transcription activation domain and blue light-dependent dimer formation molecule Vivid (VVD), and applied types of transcription activation domains to develop a new PA-Gal4 transcription factor we have named eGAV (enhanced Gal4-VVD transcription factor). Background activity of eGAV in dark conditions was significantly lower than that of hGAVPO, a commonly used PA-Gal4 transcription factor, and maximum light-induced gene expression levels were also improved. Light-controlled gene expression was verified in cultured HEK293T cells with plasmid-transient transfections, and in mouse EpH4 cells with lentivirus vector-mediated transduction. Furthermore, light-controlled eGAV-mediated transcription was confirmed in transfected neural stem cells and progenitors in developing and adult mouse brain and chick spinal cord, and in adult mouse hepatocytes, demonstrating that eGAV can be applied to a wide range of experimental systems and model organisms.Key words: optogenetics, Gal4/UAS system, transcription, gene expression, Vivid

著者

Shinji C. Nagasaki Tomonori D. Fukuda Mayumi Yamada Yusuke III Suzuki Ryo Kakutani Adam T. Guy Itaru Imayoshi

出版者

Japan Society for Cell Biology

雑誌

Cell Structure and Function (ISSN:03867196)

巻号頁・発行日

vol.48, no.1, pp.31-47, 2023 (Released:2023-02-08)

参考文献数

77

被引用文献数

1

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The Gal4/UAS system is a versatile tool to manipulate exogenous gene expression of cells spatially and temporally in many model organisms. Many variations of light-controllable Gal4/UAS system are now available, following the development of photo-activatable (PA) molecular switches and integration of these tools. However, many PA-Gal4 transcription factors have undesired background transcription activities even in dark conditions, and this severely attenuates reliable light-controlled gene expression. Therefore, it is important to develop reliable PA-Gal4 transcription factors with robust light-induced gene expression and limited background activity. By optimization of synthetic PA-Gal4 transcription factors, we have validated configurations of Gal4 DNA biding domain, transcription activation domain and blue light-dependent dimer formation molecule Vivid (VVD), and applied types of transcription activation domains to develop a new PA-Gal4 transcription factor we have named eGAV (enhanced Gal4-VVD transcription factor). Background activity of eGAV in dark conditions was significantly lower than that of hGAVPO, a commonly used PA-Gal4 transcription factor, and maximum light-induced gene expression levels were also improved. Light-controlled gene expression was verified in cultured HEK293T cells with plasmid-transient transfections, and in mouse EpH4 cells with lentivirus vector-mediated transduction. Furthermore, light-controlled eGAV-mediated transcription was confirmed in transfected neural stem cells and progenitors in developing and adult mouse brain and chick spinal cord, and in adult mouse hepatocytes, demonstrating that eGAV can be applied to a wide range of experimental systems and model organisms.Key words: optogenetics, Gal4/UAS system, transcription, gene expression, Vivid

著者

Ayako Imanishi Tomokazu Murata Masaya Sato Kazuhiro Hotta Itaru Imayoshi Michiyuki Matsuda Kenta Terai

出版者

Japan Society for Cell Biology

雑誌

Cell Structure and Function (ISSN:03867196)

巻号頁・発行日

vol.43, no.2, pp.129-140, 2018 (Released:2018-08-10)

参考文献数

49

被引用文献数

3 10

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For more than a century, hematoxylin and eosin (H&E) staining has been the de facto standard for histological studies. Consequently, the legacy of histological knowledge is largely based on H&E staining. Due to the recent advent of multi-photon excitation microscopy, the observation of live tissue is increasingly being used in many research fields. Adoption of this technique has been further accelerated by the development of genetically encoded biosensors for ions and signaling molecules. However, H&E-based histology has not yet begun to fully utilize in vivo imaging due to the lack of proper morphological markers. Here, we report a genetically encoded fluorescent marker, NuCyM (Nucleus, Cytosol, and Membrane), which is designed to recapitulate H&E staining patterns in vivo. We generated a transgenic mouse line ubiquitously expressing NuCyM by using a ROSA26 bacterial artificial chromosome (BAC) clone. NuCyM evenly marked the plasma membrane, cytoplasm and nucleus in most tissues, yielding H&E staining-like images. In the NuCyM-expressing cells, cell division of a single cell was clearly observed as five basic phases during M phase by three-dimensional imaging. We next crossed NuCyM mice with transgenic mice expressing an ERK biosensor based on the principle of Förster resonance energy transfer (FRET). Using NuCyM, ERK activity in each cell could be extracted from the FRET images. To further accelerate the image analysis, we employed machine learning-based segmentation methods, and thereby automatically quantitated ERK activity in each cell. In conclusion, NuCyM is a versatile cell morphological marker that enables us to grasp histological information as with H&E staining.Key words: in vivo imaging, histology, machine learning, molecular activity