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Functional Calcium Imaging in Developing Cortical Networks
Published on: October 22, 2011
Spontaneous network activity visualized by ultrasensitive Ca(2+) indicators, yellow Cameleon-Nano
Kazuki Horikawa1, Yoshiyuki Yamada, Tomoki Matsuda
1Research Institute for Electronic Science, Hokkaido University, Sapporo, Hokkaido, Japan.
Nature Methods
|August 10, 2010
Summary
New ultrasensitive calcium indicators, yellow cameleon-Nano (YC-Nano), detect subtle calcium transients in large cell networks. These tools advance the study of intercellular signaling and neuronal activity.
Area of Science:
- Biochemistry
- Molecular Biology
- Neuroscience
Background:
- Genetically encoded calcium indicators (GECIs) are crucial for monitoring cellular calcium dynamics.
- Existing indicators may lack the sensitivity or dynamic range for certain biological processes.
- Understanding intercellular signaling and neuronal activity requires precise calcium measurements.
Purpose of the Study:
- To develop novel ultrasensitive genetically encoded calcium indicators.
- To engineer enhanced calcium-binding domains for improved indicator performance.
- To enable the detection of subtle calcium transients in complex biological systems.
Main Methods:
- Engineering the calcium-sensing domain of yellow cameleon (YC) indicators (YC2.60, YC3.60).
- Characterization of the developed yellow cameleon-Nano (YC-Nano) indicators for calcium affinity and signal change.
- Application of YC-Nano in large multicellular networks to detect calcium dynamics.
Main Results:
- Development of YC-Nano with high calcium affinities (K(d) = 15-140 nM).
- Achieved a large signal change of 1,450% in YC-Nano indicators.
- Successful detection of subtle calcium transients in networks of up to 100,000 cells.
Conclusions:
- YC-Nano represents a significant advancement in ultrasensitive calcium indicator technology.
- These indicators are effective for studying intercellular signaling and neuronal activity.
- YC-Nano will be valuable tools for investigating information processing in living multicellular networks.
