Three papers are out online in Nature Methods that show big improvements in calcium imaging with genetically encoded sensors. They are are based on the fluorescence intensity indicator, GCaMP. GCaMP, first developed by Junichi Nakai, consists of a GFP that has been circularly permuted so that the N and C termini are fused and new termini are made in the middle of the protein. Fused to one terminus is calmodulin and the other is a peptide, M13, that calmodulin (CaM) binds to in the presence of calcium. The name is supposed to look like GFP with a CaM inserted into it, G-CaM-P. Normally the GFP is dim, as there is a hole from the outside of its barrel into the chromophore. Upon binding calcium, this hole is plugged and fluorescence increases.
The first paper, A genetically encoded reporter of synaptic activity in vivo, from Leon Lagnado’s group, targets GCaMP2 to the outer surface of synaptic vesicles. This localization allows the fluorescence signal to be confined to the presynaptic terminal, where calcium fluxes in response to action potentials are high. This targeting improves the response magnitude of GCaMP2 and permits the optical recording of synaptic inputs into whatever region of the brain one looks at. They demonstrate the technique in live zebrafish.
In the second paper, Optical interrogation of neural circuits in Caenorhabditis elegans, from Sharad Ramanathan’s group, GCaMP2 has been combined with Channelrhodopsin-2 to perform functional circuit mapping in the worm. Since the worm’s structural wiring diagram has been essentially solved, functional data could say much about how “thick” the wires between each cell are. Unfortunately, with GCaMP2, the responses are too slow and weak to distinguish direct from indirect connections.
Finally, we have published a paper, Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators, describing the improved GCaMP3. This indicator has between 2-10x better signal to noise than GCaMP2, D3cpv and TN-XXL, depending on the system you are using. It’s kinetics are faster and it is more photostable than FRET indicators, and the responses are huge. When expressed in motor cortex of the mouse, neuronal activity is easily seen directly in the raw data. Furthermore, the sensor can be expressed stably for months, making it a potential tool for observing how learning reshapes the patterns of activity in the cortex.
GCaMP3 is not perfect. It cannot reliably detect single action potential in vivo in mammals, though I doubt that any existing GECI can. Work continues on future generations of GCaMP that may achieve 100% fidelity in optical reading of the bits in the brain. However, there is considerable evidence from a number of groups that have been beta-testing the sensor, including the Tank lab of “quake mouse” fame, that it is a significant leap forward and unlocks much of the fantastic and fantasized potential of genetically-encoded calcium indicators.
I will try to post a more complete writeup of GCaMP3 for Brain Windows soon, with an unbiased eye to its strengths and weaknesses. We worked very hard to carefully characterize this sensor’s effects on cellular and circuit properties. If you have any questions about GCaMP3, please post them to the comments.
For further info about strategies for GECI use and optimization, check out our previous paper, Reporting neural activity with genetically encoded calcium indicators in Brain Cell Biology.
The official press release from HHMI regarding GCaMP3 is available here.