Three Cheers for GCaMP : Optogenetic Brain Reading

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.

Imaging of mouse motor cortex (M1) expressing the genetically-encoded calcium indicator GCaMP3 through a cortical window. After 72 days of GCaMP3 expression, large fluorescence transients can be seen in many neurons that are highly correlated with mouse running.

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.

Comparison of fluorescence changes in response to trains of action potentials in acute cortical slices.

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.

Annual Reviews worth reading

Annual Reviews of Neuroscience published their 2009 issue recently.  These articles are usually a great way to catch up with a field, particularly when they are recently published.  Here are a few that might be of interest to the Brain Windows reader.

Synaptic Mechanisms for Plasticity in Neocortex

Daniel E. Feldman

Sensory experience and learning alter sensory representations in cerebral cortex. The synaptic mechanisms underlying sensory cortical plasticity have long been sought. Recent work indicates that long-term cortical plasticity is a complex, multicomponent process involving multiple synaptic and cellular mechanisms. Sensory use, disuse, and training drive long-term potentiation and depression (LTP and LTD), homeostatic synaptic plasticity and plasticity of intrinsic excitability, and structural changes including formation, removal, and morphological remodeling of cortical synapses and dendritic spines. Both excitatory and inhibitory circuits are strongly regulated by experience. This review summarizes these findings and proposes that these mechanisms map onto specific functional components of plasticity, which occur in common across the primary somatosensory, visual, and auditory cortices.

Using Diffusion Imaging to Study Human Connectional Anatomy

Heidi Johansen-Berg and Matthew F.S. Rushworth

Diffusion imaging can be used to estimate the routes taken by fiber pathways connecting different regions of the living brain. This approach has already supplied novel insights into in vivo human brain anatomy. For example, by detecting where connection patterns change, one can define anatomical borders between cortical regions or subcortical nuclei in the living human brain for the first time. Because diffusion tractography is a relatively new technique, however, it is important to assess its validity critically. We discuss the degree to which diffusion tractography meets the requirements of a technique to assess structural connectivity and how its results compare to those from the gold-standard tract tracing methods in nonhuman animals. We conclude that although tractography offers novel opportunities it also raises significant challenges to be addressed by further validation studies to define precisely the limitations and scope of this exciting new technique.

The Science of Neural Interface Systems

Nicholas G. Hatsopoulos and John P. Donoghue

The ultimate goal of neural interface research is to create links between the nervous system and the outside world either by stimulating or by recording from neural tissue to treat or assist people with sensory, motor, or other disabilities of neural function. Although electrical stimulation systems have already reached widespread clinical application, neural interfaces that record neural signals to decipher movement intentions are only now beginning to develop into clinically viable systems to help paralyzed people. We begin by reviewing state-of-the-art research and early-stage clinical recording systems and focus on systems that record single-unit action potentials. We then address the potential for neural interface research to enhance basic scientific understanding of brain function by offering unique insights in neural coding and representation, plasticity, brain-behavior relations, and the neurobiology of disease. Finally, we discuss technical and scientific challenges faced by these systems before they are widely adopted by severely motor-disabled patients.

Advances in Light Microscopy for Neuroscience

Brian A. Wilt, Laurie D. Burns, Eric Tatt Wei Ho, Kunal K. Ghosh, Eran A. Mukamel, and Mark J. Schnitzer

Since the work of Golgi and Cajal, light microscopy has remained a key tool for neuroscientists to observe cellular properties. Ongoing advances have enabled new experimental capabilities using light to inspect the nervous system across multiple spatial scales, including ultrastructural scales finer than the optical diffraction limit. Other progress permits functional imaging at faster speeds, at greater depths in brain tissue, and over larger tissue volumes than previously possible. Portable, miniaturized fluorescence microscopes now allow brain imaging in freely behaving mice. Complementary progress on animal preparations has enabled imaging in head-restrained behaving animals, as well as time-lapse microscopy studies in the brains of live subjects. Mouse genetic approaches permit mosaic and inducible fluorescence-labeling strategies, whereas intrinsic contrast mechanisms allow in vivo imaging of animals and humans without use of exogenous markers. This review surveys such advances and highlights emerging capabilities of particular interest to neuroscientists.

Previews : sCRACM, Red PA-FPs, ATP sensor, Deep tissue PALM

Here is a quick list of papers Brain Windows will be covering in greater depth the next two weeks.

The subcellular organization of neocortical excitatory connections : A new technique, subcellular ChR2-assisted circuit mapping (sCRACM), is used to map neuronal circuitry.  

A genetically encoded fluorescent reporter of ATP:ADP ratio : A new single-FP indicator that reports the relative concentration of ATP to ADP in a cells. 

A bright and photostable photoconvertible fluorescent protein : Evolution of monomeric Eos into a fluorescent protein with better properties for super-resolution imaging.

Photoactivatable mCherry for high-resolution two-color fluorescence microscopy : Evolution of mCherry into a photoactivatable fluorescent protein with better properties for super-resolution imaging.

Multilayer three-dimensional super resolution imaging of thick biological samples : Advanced laser pulse shaping techniques to achieve super-resolution imaging in thick samples.

Journal Club : Rodent Secondary Somatosensory Cortex SII

Who were the primary developers of two-photon microscopy for visualizing brain activity?  Following Watt Webb’s seminal work, it was Winfried Denk, David Tank, Karel Svoboda, and David Kleinfeld. What do these four have in common?  They all worked at Bell Labs, and they all do imaging in rodent somatosensory cortex.  Primary somatosensory cortex (SI), particularly barrel cortex has many advantages. You can directly observe the input (whisker touching), you can get behavioral output, the cortex is smooth, has a vivid characteristic pattern of cytochrome oxidase staining and is accessible to a cortical window. Consequently, SI is one of the best characterized regions of cortex.  Far less understood is the structure and function of secondary somatosensory cortex (SII), but it likely plays an essential role in rodent sensory perception. For Journal Club #3, I review what is know of the location, structure, connectivity, physiology and function of SII.

Mice aren’t that blind

Just saw a cool informal talk from Andreas Burkhalter about the mouse visual cortex.  He has a fascinating paper, Area Map of Mouse Visual Cortex, in the Journal of Comparative Neurology, in which he identifies not just three or four areas of mouse visual cortex, but twelve! Each area has a complete map of the entire visual field.  He combines triplet injections of Di-I, Di-O and BDA as fiducial markers with a label for callosal connections. He fixes the tissue in a manner that allows the unrolling and flattening of the entire mouse cortex. This allows him to segment and show the orientation of each field in a single cortical layer in the same slice. Different layers give different patterns of projection. Given the richness of the data obtained, I’m surprised that more systems neuroscientists don’t use identical techniques.

Triple labeling of mouse visual cortex

He has also created a wiring diagram of each of these and shown that receptive field size increases with the depth in the visual system hierarchy. He also noted that although Michael Stryker finds 50% of visual cortex neurons are direction selection (when stimulated by drifting gratings), he finds only 10% are direction selective when using random dot patterns. Presumably, drifting gratings provide additional cues beyond direction of motion that confound analysis. For such a ‘blind’ creature, mice sure have a complex pattern of circuitry to process visual information.

Brainbow mice are out

Jeff Lichtman’s Brainbow mouse paper is out! Not that I really need to report that news, as it is, of course, on the cover of Nature. Jean Livet comes up with some really clever genetic strategies involving incompatible, overlapping Lox sites to generate random, combinatorial patterns of multiple fluorescent proteins inside the cell. Around 90 different shades can be discerned by spectral deconvolution.

Besides making pretty covers, why is this so cool?

Well, this technique provides a method for generating high resolution maps of the brain. With a single fluorescent tag, the processes of neighboring cells blur together and became impossible to trace unambiguously. With brainbow, many neighboring axons are clearly resolvable. This is the perfect genetic tool to use for a large-scale, all-out effort for the complete mapping of the circuitry of the mouse brain. It would be a tremendous challenge, but perhaps no more difficult than the human genome project. A large public consortium, or a Celera of the brain can really attack the connectivity problem now.

Of course, there still is the more difficult problem of showing the functional connectivity of the circuit map. Then again, this technique isn’t limited to swapping in static fluorescent tags. The insert cassette could be doped with a single FP functional indicator like G-CaMP2… Would this allow the combination of static circuit mapping with functional testing?