Fluorescence microscopy videos of mitochondria and endosomes in H9c2 cardiomyoblasts

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Opstad, Ida, 2023, "Fluorescence microscopy videos of mitochondria and endosomes in H9c2 cardiomyoblasts", https://doi.org/10.18710/HQDBYF, DataverseNO, V3

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Description	This dataset contains a series of three-dimensional fluorescence microscopy videos of the rat cardiomyoblast cell-line H9c2. The outer mitochondrial membrane is labeled with either mCherry (a red fluorescent protein) or eGFP (enhanced green fluorescent protein). Membrane-bound vesicles called endosomes are labeled using mCLING-ATTO647n. A portion of the data is further labeled for acidic vesicles (LysoTracker) and/or has correlative images in brightfield mode (label-free, transmission microscopy). This data is a collection of fluorescence microscopy videos acquired to study the dynamics of mitochondria and the interaction of different subcellular vesicles. Correlative transmission microscopy images (trans) were provided for machine learning to later enable label-free detection of mitochondria and distinguish between different types of vesicles. As three different cameras were used to enable the fast multi-color acquisition, all data has been "channel aligned", i.e., registered to the same sample coordinate system for accurate colocalization of different cellular components. Both unprocessed widefield images and deconvolved data are provided (dimensions: 3D-channels-time) plus maximum intensity z-projected data and AVI-movies of the deconvolved images to enable a quick and easy visualization of the else large image files. (2023-07-03)
Subject	Medicine, Health and Life Sciences
Keyword	fluorescence microscopy, brightfield, label-free, correlative imaging, mitochondria, endosomes, lysosomes, cardiomyoblasts, deconvolution, virtual labeling
Related Publication	Somani, Ayush, Arif Ahmed Sekh, Ida S. Opstad, Åsa Birna Birgisdottir, Truls Myrmel, Balpreet Singh Ahluwalia, Alexander Horsch, Krishna Agarwal, and Dilip K. Prasad. "Virtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learning." Biomedical Optics Express 13, no. 10 (2022): 5495-5516 doi: 10.1364/BOE.464177
License/Data Use Agreement	CC0 1.0

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	20190717_H9c2-G3_eGFP-OMP_LTR50nM_mC1to2000-40min_1520_convTL_002_ALX_D3D.dv endo_lyso_eGFP-mito/decon3D/Unknown - 6.7 GB Published Jul 13, 2023 8 Downloads MD5: 5fa845c72ac5cd512124bd0c4985e1ff	Access File File Access Public Download Options Original File Format Download Metadata Data File Citation EndNote XML RIS BibTeX
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Citation Metadata

Persistent Identifier	doi:10.18710/HQDBYF
Publication Date	2023-07-13
Title	Fluorescence microscopy videos of mitochondria and endosomes in H9c2 cardiomyoblasts
Author	Opstad, Ida (UiT The Arctic University of Norway) - ORCID: 0000-0003-4462-4600
Point of Contact	Use email button above to contact. Opstad, Ida (UiT The Arctic University of Norway) Agarwal, Krishna (UiT The Arctic University of Norway)
Description	This dataset contains a series of three-dimensional fluorescence microscopy videos of the rat cardiomyoblast cell-line H9c2. The outer mitochondrial membrane is labeled with either mCherry (a red fluorescent protein) or eGFP (enhanced green fluorescent protein). Membrane-bound vesicles called endosomes are labeled using mCLING-ATTO647n. A portion of the data is further labeled for acidic vesicles (LysoTracker) and/or has correlative images in brightfield mode (label-free, transmission microscopy). This data is a collection of fluorescence microscopy videos acquired to study the dynamics of mitochondria and the interaction of different subcellular vesicles. Correlative transmission microscopy images (trans) were provided for machine learning to later enable label-free detection of mitochondria and distinguish between different types of vesicles. As three different cameras were used to enable the fast multi-color acquisition, all data has been "channel aligned", i.e., registered to the same sample coordinate system for accurate colocalization of different cellular components. Both unprocessed widefield images and deconvolved data are provided (dimensions: 3D-channels-time) plus maximum intensity z-projected data and AVI-movies of the deconvolved images to enable a quick and easy visualization of the else large image files. (2023-07-03)
Subject	Medicine, Health and Life Sciences
Keyword	fluorescence microscopy brightfield label-free correlative imaging mitochondria endosomes lysosomes cardiomyoblasts deconvolution virtual labeling
Related Publication	Somani, Ayush, Arif Ahmed Sekh, Ida S. Opstad, Åsa Birna Birgisdottir, Truls Myrmel, Balpreet Singh Ahluwalia, Alexander Horsch, Krishna Agarwal, and Dilip K. Prasad. "Virtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learning." Biomedical Optics Express 13, no. 10 (2022): 5495-5516 doi: 10.1364/BOE.464177 https://doi.org/10.1364/BOE.464177 Sekh, Arif Ahmed, Ida S. Opstad, Gustav Godtliebsen, Åsa Birna Birgisdottir, Balpreet Singh Ahluwalia, Krishna Agarwal, and Dilip K. Prasad. "Physics-based machine learning for subcellular segmentation in living cells." Nature Machine Intelligence 3, no. 12 (2021): 1071-1080. doi: 10.1038/s42256-021-00420-0 https://doi.org/10.1038/s42256-021-00420-0 Sekh, Arif Ahmed, Ida Sundvor Opstad, Asa Birna Birgisdottir, Truls Myrmel, Balpreet Singh Ahluwalia, Krishna Agarwal, and Dilip K. Prasad. "Learning nanoscale motion patterns of vesicles in living cells." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 14014-14023. 2020. doi: 10.1109/CVPR42600.2020.01403 https://doi.org/10.1109/CVPR42600.2020.01403
Language	English
Producer	UiT The Arctic University of Norway (UiT) https://en.uit.no/
Production Location	Tromsø, Norway
Contributor	Research Group : Agarwal, Krishna Research Group : Birgisdottir, Åsa B. Research Group : Ahluwalia, Balpreet S. Data Curator : Conzett, Philipp
Funding Information	UiT The Arctic University of Norway: Tematiske satsinger (VirtualStain; project number 2061348) Helse Nord RHF: Grant number HNF1449-19
Distributor	UiT The Arctic University of Norway (UiT The Arctic University of Norway) https://dataverse.no/dataverse/uit
Depositor	Opstad, Ida Sundvor
Deposit Date	2023-07-03
Time Period	Start Date: 2019-01-01 ; End Date: 2019-08-01
Date of Collection	Start Date: 2019-07-17 ; End Date: 2019-07-17
Data Type	Experimental, volumetric microscopy videos
Software	Fiji/ImageJ
Related Dataset	Opstad, Ida, 2023, "Fluorescence microscopy videos of mitochondria in H9c2 cardiomyoblasts", https://doi.org/10.18710/11LLTW, DataverseNO

Geospatial Metadata

Geographic Coverage	Norway, Troms, Tromsø

Life Sciences Metadata

Design Type	Other
Factor Type	Cell Type/Cell Line
Organism	Rattus norvegicus
Measurement Type	Other
Other Measurement Type	fluorescence
Technology Type	Other
Other Technology Type	fluorescence and brightfield microscopy
Cell Type	H9c2

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