Detail of Fig5-6_RFP

(Too many images for preview; see images in SSBD:OMERO Dataset)


Project
SSBD:Repository
Title
Fluoresence imaging of D. discoideum expressing RFP on a centimeter scale.
Description
Fluoresence imaging of D. discoideum expressing RFP on a centimeter scale.
Release, Updated
2022-11-23
License
CC BY-NC
Kind
Image data
File Formats
uncompressed TIFF
Data size
217.8 GB

Organism
Dictyostelium discoideum ( NCBI:txid44689 )
Strain(s)
-
Cell Line
-
Protein tags
RFP

Datatype
-
Molecular Function (MF)
Biological Process (BP)
calcium-mediated signaling ( GO:0019722 ) cAMP-mediated signaling ( GO:0019933 )
Cellular Component (CC)
nucleus ( GO:0005634 )
Biological Imaging Method
fluorescence microscopy ( Fbbi:00000246 )
X scale
1.1 micrometer/pixel
Y scale
1.1 micrometer/pixel
Z scale
-
T scale
30 seconds per frame

Image Acquisition
Experiment type
-
Microscope type
-
Acquisition mode
-
Contrast method
-
Microscope model
-
Detector model
-
Objective model
-
Filter set
-

Summary of Methods
See details in Ichimura T, et. al. (2021) Sci Rep. 2021 Aug 16;11(1):16539.
Related paper(s)

T Ichimura, T Kakizuka, K Horikawa, K Seiriki, A Kasai, H Hashimoto, K Fujita, T M Watanabe, T Nagai (2021) Exploring rare cellular activity in more than one million cells by a transscale scope., Scientific reports, Volume 11, Number 1, pp. 16539

Published in 2021 Aug 16 (Electronic publication in Aug. 16, 2021, midnight )

(Abstract) In many phenomena of biological systems, not a majority, but a minority of cells act on the entire multicellular system causing drastic changes in the system properties. To understand the mechanisms underlying such phenomena, it is essential to observe the spatiotemporal dynamics of a huge population of cells at sub-cellular resolution, which is difficult with conventional tools such as microscopy and flow cytometry. Here, we describe an imaging system named AMATERAS that enables optical imaging with an over-one-centimeter field-of-view and a-few-micrometer spatial resolution. This trans-scale-scope has a simple configuration, composed of a low-power lens for machine vision and a hundred-megapixel image sensor. We demonstrated its high cell-throughput, capable of simultaneously observing more than one million cells. We applied it to dynamic imaging of calcium ions in HeLa cells and cyclic-adenosine-monophosphate in Dictyostelium discoideum, and successfully detected less than 0.01% of rare cells and observed multicellular events induced by these cells.
(MeSH Terms)
Related paper(s)

Ichimura, T., Kakizuka, T., Horikawa, K., Seiriki, K., Kasai, A., Hashimoto, H., Fujita, K., Watanabe, T. M., Nagai, T. (2021/01/01), Exploring rare cellular activity in more than one million cells by a trans-scale-scope, bioRxiv, 2020.06.29.179044

Published in 2021/01/01

(Abstract) In many phenomena of biological systems, not a majority, but a minority of cells act on the entire multicellular system causing drastic changes in the system properties. To understand the mechanisms underlying such phenomena, it is essential to observe the spatiotemporal dynamics of a huge population of cells at sub-cellular resolution, which is difficult with conventional tools such as microscopy and flow cytometry. Here, we describe an imaging system named AMATERAS that enables optical imaging with an over-one-centimeter field-of-view and a-few-micrometer spatial resolution. This trans-scale-scope has a simple configuration, composed of a low-power lens for machine vision and a hundred-megapixel image sensor. We demonstrated its high cell-throughput, capable of simultaneously observing more than one million cells. We applied it to dynamic imaging of calcium ions in HeLa cells and cyclic-adenosine-monophosphate in Dictyostelium discoideum, and successfully detected less than 0.01% of rare cells and observed multicellular events induced by these cells.Competing Interest StatementThe authors have declared no competing interest.

Contact
Takeharu Nagai , Osaka University, SANKEN (The Institute of Scientific and Industrial Research)
Contributors

OMERO Dataset
OMERO Project
Source