Cell Cycle Visualization in Development

Atsushi Miyawaki’s lab has developed a series of neat tools for visualizing cell cycle progress.

For zebrafish, the zFucci system consists of two fluorescent proteins, mKO2 and mAG, that are fused to Cdt1 and geminin genes.  Cell cycle- regulated proteolysis of these fusion proteins causes each cell to display orange fluorescence in G₁ phase nuclei and green fluorescence in both the nucleus and cytoplasm of S/G₂/M phase cells.

Video of cell cycle transitions in culture. Click for the video.

The last time I saw Atsushi give a talk, he showed an incredible time lapse video from the zebrafish cleavage stage that I haven’t been able to find online.  However, here is a video from later in development of the zebrafish that is still pretty remarkable.

Development of a zebrafish visualized by zFucci. Click to see the video.

This two component system has been adapted for watching the transition from neural stem cells to differentiated neurons in living mice. The Color-Timer system uses double transgenics with the fluorescent protein KOr fused to nestin and EGFP fused to doublecortin.  In this system, neural stem cells fluoresce orange, while newly differentiated neurons fluoresce green.

The cerebral cortex of an E14.5 double Tg mouse embryo of nestin/KOr was time-lapse imaged. Click for video

Sugiyama, M., Sakaue-Sawano, A., Iimura, T., Fukami, K., Kitaguchi, T., Kawakami, K., Okamoto, H., Higashijima, S., & Miyawaki, A. (2009). Illuminating cell-cycle progression in the developing zebrafish embryo Proceedings of the National Academy of Sciences, 106 (49), 20812-20817 DOI: 10.1073/pnas.0906464106

Kanki, H., Shimabukuro, M., Miyawaki, A., & Okano, H. (2010). “Color Timer” mice: visualization of neuronal differentiation with fluorescent proteins Molecular Brain, 3 (1) DOI: 10.1186/1756-6606-3-5

CNiFERS of Acetylcholine and Attention

“If you find yourself needing to reread this paragraph, perhaps it’s not that well written. Or it may be that you are low on acetylcholine.” Acetylcholine (ACh) is a major modulator of brain activity in vivo and its release strongly influences attention. If we could visualize when and where ACh is released, we could more fully understand the large trial to trial variance found in many in vivo recordings of spike activity, and perhaps correlate that to attentional and behavioral states mediated by ACh transmission.

Back in grad school, when I was desperately trying to figure out what biological question to answer with my GluSnFR glutamate sensor, I ended up in a meeting with Kleinfeld, his grad student Lee Schroder and Palmer Taylor. We plotted a strategy to make a FRET sensor for acetylcholine.  Palmer had recently solved crystal structures of an acetylcholine binding protein bound to agonists and antagonists.  Snails secrete this binding protein into their ACh synapses to modulate their potency.  The structures showed a conformational change upon agonist binding.  The hope was that by fusing CFP and YFP to the most translocated bits of the protein, they would be able to see an ACh dependent FRET change.  I was skeptical that it would work, as the translocation was much less than with calmodulin-M13 or periplasmic binding proteins used in Cameleon and GluSnFR, but thought was at least worth a shot.  FRET efficiency is highly dependent on dipole orientation, not just dipole distance, and you never know how a small conformational change might rearrange the FP dipoles…

Of course, the simple idea didn’t work.  Instead of giving up on the first dozen attempts, they kept plugging away at alternative strategies for measuring ACh release, and eventually succeeded.  In this Nature Neuroscience report, An in vivo biosensor for neurotransmitter release and in situ receptor activity, Nguyen et al demonstrate a mammalian cell based system for optically measuring ACh levels in an intact brain.  They coexpressed M1 muscarinic receptors with the genetically-encoded calcium indicator TN-XXL in HEK293 cells.  ACh binding to the M1 receptor induced IP₃-mediated calcium influx.  This calcium rise was then picked up by the TN-XXL and reported as a change in CFP/YFP fluorescence.  The crazy part is that they took this cell culture assay and implanted the cells into the brains of living rats!

The CNiFER in vivo experimental paradigm

In culture, the response was highly sensitive and monotonic (for phasic response section, EC₅₀ of 11 nM, a Hill coefficient of 1.9 and a maximum of ΔR/R = 1.1). In vivo, using two-photon imaging through a cortical window, they were able to see clear ACh responses in frontal cortex from electrical stimulation of the nucleus basalis magnocellularis, typically 200-μs current pulses of 200 μA @ 100Hz for 20-500ms.

This was essentially a in vivo proof of principal experiment, showing that one could image ACh release in spatially and temporally precise regions of the brain.  However, the imaging was done under urethane anesthesia, which is a much different brain state than an awake, behaving animal.  Are CNiFERs sensitive, powerful and stable enough to determine behavioral states via imaging in an awake animal?  Would expressing GCaMP3 (an indicator with greater fluorescence dynamic range) improve the performance of the CNiFER system? We used a very similar assay with ACh applied to HEK cells during the initial screens for better GCaMPs. Or, is the performance more limited by the properties of the M1 receptor and the adapting nature of IP3-mediated calcium dynamics?  CNiFERS provide an interesting platform for looking at ACh and potentially other G-protein mediated signaling, but it remains to be seen if labs that aren’t as technically proficient with two-photon rig will find it more useful than cyclic voltammetry for measuring acetylcholine levels.

Nature Neuroscience, 13 (1), 127-132 DOI: 10.1038/nn.2469
Nguyen, Q., Schroeder, L., Mank, M., Muller, A., Taylor, P., Griesbeck, O., & Kleinfeld, D. (2009). An in vivo biosensor for neurotransmitter release and in situ receptor activity

Free Will – Choose Your Own Adventure

Another take on Free Will from Luke Surl comics…

Journal Scan – Calcium Imaging in Auditory and Visual Cortex

A few papers on in vivo calcium imaging have just come out and are worth a careful read.

The first two examine the fine organization of layer 2/3 of the mouse auditory cortex.  The canonical view of auditory cortex organization is that neurons are arranged in a tonotopic pattern, with a smooth gradient in auditory frequency tuning across the surface of the cortex.  Using two-photon imaging in anesthetized mice, the groups saw that, while there was an overall gradient, the tuning of neighboring neurons was highly variable.  These are similar results to what Sato et al and Kerr et al found in the whisker barrel cortex back in 2007.  Moral of the story : mapping brain organization by microstimulation or sparse sampling (as in the classic papers) can be very misleading.

UPDATE : David Kleinfeld kindly directed me to the 40 year old work by Moshe Abeles and others that showed a similar spread in frequency tuning using microelectrodes…

Now, back to the more recent papers…

Functional organization and population dynamics in the mouse primary auditory cortex – Rothschild G, Nelken I, Mizrahi A. Nat Neurosci. 2010 Mar;13(3):353-60. Epub 2010 Jan 31.

Cortical processing of auditory stimuli involves large populations of neurons with distinct individual response profiles. However, the functional organization and dynamics of local populations in the auditory cortex have remained largely unknown. Using in vivo two-photon calcium imaging, we examined the response profiles and network dynamics of layer 2/3 neurons in the primary auditory cortex (A1) of mice in response to pure tones. We found that local populations in A1 were highly heterogeneous in the large-scale tonotopic organization. Despite the spatial heterogeneity, the tendency of neurons to respond together (measured as noise correlation) was high on average. This functional organization and high levels of noise correlations are consistent with the existence of partially overlapping cortical subnetworks. Our findings may account for apparent discrepancies between ordered large-scale organization and local heterogeneity.

In vivo two-photon calcium imaging from dozens of neurons simultaneously in A1.

Dichotomy of functional organization in the mouse auditory cortex – Bandyopadhyay S, Shamma SA, Kanold PO. Nat Neurosci. 2010 Mar;13(3):361-8. Epub 2010 Jan 31.

The sensory areas of the cerebral cortex possess multiple topographic representations of sensory dimensions. The gradient of frequency selectivity (tonotopy) is the dominant organizational feature in the primary auditory cortex, whereas other feature-based organizations are less well established. We probed the topographic organization of the mouse auditory cortex at the single-cell level using in vivo two-photon Ca(2+) imaging. Tonotopy was present on a large scale but was fractured on a fine scale. Intensity tuning, which is important in level-invariant representation, was observed in individual cells, but was not topographically organized. The presence or near absence of putative subthreshold responses revealed a dichotomy in topographic organization. Inclusion of subthreshold responses revealed a topographic clustering of neurons with similar response properties, whereas such clustering was absent in supra-threshold responses. This dichotomy indicates that groups of nearby neurons with locally shared inputs can perform independent parallel computations in the auditory cortex.

Tonotopy exists in A1 and AAF on a large scale, but not on small spatial scales.

The third paper uses a GECI (YC3.6) to do chronic imaging in visual cortex. Their results are noteworthy in that they look at visual responses to both a passive viewing and an ACTIVE discrimination task in an awake, head-fixed mouse.  The patterns of neural activity between anesthetized, awake but passively receiving sensory input, and awake while paying attention and using the sensory input are likely to be hugely different. Recording from neurons that are actively involved in a discrimination task is essential to understanding how the cortex is actually processing information.  Although this paper is more focused on simply presenting the technique rather than in depth analysis of the activity, we will be seeing more of this style of neuroscience in high-profile journals very soon…

Chronic cellular imaging of mouse visual cortex during operant behavior and passive viewing  -  Andermann ML, Kerlin AM and Reid RC, Front. Cell. Neurosci. 4:3.

Nearby neurons in mammalian neocortex demonstrate a great diversity of cell types and connectivity patterns. The importance of this diversity for computation is not understood. While extracellular recording studies in visual cortex have provided a particularly rich description of behavioral modulation of neural activity, new methods are needed to dissect the contribution of specific circuit elements in guiding visual perception. Here, we describe a method for three-dimensional cellular imaging of neural activity in the awake mouse visual cortex during active discrimination and passive viewing of visual stimuli. Head-fixed mice demonstrated robust discrimination for many hundred trials per day after initial task acquisition. To record from multiple neurons during operant behavior with single-trial resolution and minimal artifacts, we built a sensitive microscope for two-photon calcium imaging, capable of rapid tracking of neurons in three dimensions. We demonstrate stable recordings of cellular calcium activity during discrimination behavior across hours, days, and weeks, using both synthetic and genetically-encoded calcium indicators. When combined with molecular and genetic technologies in mice (e.g., cell-type specific transgenic labeling), this approach allows the identification of neuronal classes in vivo. Physiological measurements from distinct classes of neighboring neurons will enrich our understanding of the coordinated roles of diverse elements of cortical microcircuits in guiding sensory perception and perceptual learning. Further, our method provides a high-throughput, chronic in vivo assay of behavioral influences on cellular activity that is applicable to a wide range of mouse models of neurologic disease.

Mapping visual responses in identified excitatory and inhibitory neurons in awake mice

Compressed Sensing in Neuroscience

Wired has a nice lay-person write-up of the rapidly developing field of compressed sensing. This is a technique that allows accurate reconstructions of highly undersampled sparse datasets. This field really took off in 2004 when Emmanuel J. Candès discovered that a tomography phantom image could be reconstructed exactly even with data deemed insufficient by the Nyquist-Shannon criterion. It is probably the hottest topic in imaging theory today.

Modified Shepp-Logan phantom with enhanced contrast for visual perception.

According to this review, Compressed Sensing MRI, its successful application requires three conditions to be met :

• Transform Sparsity: The desired image must have a sparse representation in a known transform domain (i.e., it must be compressible by transform coding),
• Incoherence of Undersampling Artifacts: The aliasing artifacts in a linear reconstruction caused by k-space undersampling must be incoherent (noise-like) in the sparsifying transform domain.
• Nonlinear Reconstruction: The image must be reconstructed by a non-linear method which enforces both sparsity of the image representation and consistency of the reconstruction with the acquired samples.

These conditions are well met by MRI imaging.  This decoding technique dramatically shortens the required sampling times in an MRI magnet, which reduces the impact of motion artifacts, the bane of high-resolution MRI.

Unfortunately, I don’t think it is very applicable to situations where signal/noise of the underlying source is poor, like counting action potentials in shot-noise limited in vivo calcium imaging. But it’s use is spreading into other related problems, such as mapping the functional connectivity of neural circuitry.  Tao Hu and Mitya Chklovvskii apply the compressed sensing algorithms in Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME) from the latest Advances in Neural Information Processing Systems journal. They measure a post-synaptic neuron’s voltage while stimulating sequentially random subsets of multiple potentially pre-synaptic neurons. The sparseness of connectivity allows them to map connectivity much faster than by a sequential method.

UPDATE: If you want to get a better sense of the breadth and depth of the applications of compressed sensing, check out Igor Carron’s comprehensive site, Compressive Sensing : The Big Picture.

Expert Research Blog of the Year?

Whoa!  ResearchBlogging.org just listed the finalists for their 2010 blogging awards.  Brain Windows is one of five finalists for Expert-Level research blog of the year.

Cynics might say that giving out small monetary awards ($50, oh yeah baby!) and allowing voting only by bloggers registered by researchblogging.org is a cost-effective way to promote their site. This is hardly the only promotional tactic out there though.  About once a week, I get an email from some firm that wants link share or have a service giveaway to influence content on Brain Windows to drive traffic to their site.  I’ve never posted those things because the message never serves the readership of Brain Windows. However, Researchblogging.org does serve a useful purpose beyond just a content aggregator. Posts within that network, as well as Postgenomic, Nature Blogs, and Bloglines feed into the new PLoS One article-level metrics which give an idea about the impact of a publication long before additional journal publications have a chance to cite it.  These metrics are another welcome step towards the validation of alternative, democratic models of content distribution in science.

So, if you are a believer in science blogs, alternative metrics of research output, and want to help me with my beer fund, head over to researchblogging.org, register and vote for Brain Windows.  Voting invitations are sent out to registered users on March 4th.

Journal Club – In Vivo Inhibition Dynamics

Inhibition has a powerful role shaping the network dynamics of the cortex, but most studies of inhibitory circuitry are done in brain slice or anesthetized animals. In Membrane potential dynamics of GABAergic neurons in barrel cortex of behaving mice, Gentet et al use two-photon imaging to guide dual, whole-cell patch clamp of inhibitory and excitatory neurons in the mouse barrel cortex.  These mice are head fixed, but awake and naturally whisking.  The authors can then see how the membrane dynamics of both subthreshold and suprathreshold voltages are correlated across pairs of cells.  Differences between the correlations for excitatory and inhibitory neurons shed light on how cortical circuitry processes sensory information in natural brain states.

For Journal Club #5, Mac Hooks, a post-doc here at Janelia working with Gordon Shepard and Karel Svoboda, walks us through these results.  Also, there is a video introduction of the work by the lab head of the paper, Carl Petersen, provided by Cell Press.

Gentet, L., Avermann, M., Matyas, F., Staiger, J., & Petersen, C. (2010). Membrane Potential Dynamics of GABAergic Neurons in the Barrel Cortex of Behaving Mice Neuron, 65 (3), 422-435 DOI: 10.1016/j.neuron.2010.01.006

Monte Carlo Calcium Spike Detection

I somehow missed that Josh Vogelstein’s method on action potential detection was published last summer. In Spike Inference from Calcium Imaging Using Sequential Monte Carlo Methods, the authors use a Monte Carlo approach to determine spike times from calcium imaging with superior performance to other deconvolution methods.  It does a great job on simulated and in vitro data, I’d love to see performance on real in vivo recordings.  If you are serious about calcium imaging, you should definitely get in touch with Josh and see what magic he can do with all that math.  You should also ask him about the benefits of linen pants vs. denim, he’s got strong opinions on that subject as well…

Using only strongly saturating and very noisy in vitro fluorescence measurements to infer precise spike times in a ‘‘naturalistic’’ spike train recorded in vitro

Ultrafast optogenetic control with ChETA

The Deisseroth and Hegemann groups have just published a newly engineered channelrhodopsin, ChETA, in the Nature Neuroscience paper, Ultrafast optogenetic control.  Gunaydin et al rationally targeted mutations to the opsin pocket of channelrhodopsin-2 to increase the speed of channel deactivation/closing. ChETA provides higher fidelity optical control of spiking at high expression levels or firing frequencies (up to 200Hz!) and eliminates plateau potentials during sustained spike trains.

ChETA improves spike train fidelity

ChETA clearly provides higher precision in optical control of spiking, particularly at high spike rates.  However, a big problem limiting some in vivo channelrhodopsin use has been insufficient conductance. Some groups have sought to increase single channel conductance, but this approach can lead to increased ChR toxicity and/or spurious spikes. At first glance, increasing deactivation rates, and thus decreasing single channel current from a brief light pulse, seems to make life MORE difficult for situations where light and conductance levels are limiting. ChETA produces a very low number of successful spikes at 1ms illumination (Fig 3f), as compared to ChR2. ChETA response peaks within 1ms but requires 2ms illumination and >10Hz trains to induces spikes more reliably than ChR2. Is this due to a decreased peak single channel conductance in ChETA or just the activation/deactivation rate differences?  I couldn’t find a direct single-channel conductance comparison in the paper.

ChETA requires a longer light pulse than ChR2 to generate spikes.

A reduced conductance might not be a bad thing though. ChETA’s increased deactivation rate might make less toxic to cells, allowing a higher expression level, which would compensate for a reduced single channel current flow. It all depends on what causes ChR2 toxicity.  Is toxicity caused by a non-illuminated leak current or something else?  Is the deactivation rate correlated with a leak current and/or toxicity?  I would love to see a quantitative comparison of expression level and toxicity between wt ChR2  and ChETA.  Maybe our readers can post their experiences with it in the coming weeks.

Adaptive Optics for In Vivo Microscopy

Imaging fluorescence in an intact, living brain is difficult due to absorption and scattering of excitation and emission light.  Two photon microscopy uses excitation light in the narrow optical window (700-950nm) where water and hemoglobin do not significantly absorb, which allows structure determination and functional imaging down to depths of ~600nm from the surface of the brain.  However, scattering of the excitation light still occurs at these wavelengths, which distorts the excitation volume and causes a rapidly increasing fluorescent background at greater depths.

The vasculature was labeled by injecting flourescein dextran into the circulatory stream. The light source was a regenerative amplifier. ‘‘0 mm’’ corresponds to the top of the brain. Left, XZ projection. Right, examples of XY projections. Note the increase in background fluo- rescence deeper than 600 mm in the brain due to out-of-focus 2PE. (Theer et al., 2003)

In order to reduce this background and sharpen the two-photon excitation volume, Ji et al in Adaptive optics via pupil segmentation for high-resolution imaging in biological tissues adapt tricks from astronomy (see also Rueckel et al 2006). Depending on where each ray of excitation light enters the brain, the angles of scattering are different.  By sequentially illuminating with spatially restricted subsections of full illumination beam, they see how the brain warps the light from each part of the beam.  Then they use a flexible mirror and to change the angle and phase of the excitation beam so that each part of the beam comes together in the same place and phase. Since two-photon fluorescence scales as the square of the intensity of the excitation light, this dramatically improves both the resolution and the signal to noise of the fluorescence image.

Scattering in the brain warps two-photon excitation light, but adaptive optics can correct this.

Pre-warping the excitation light to cancel the scattering improves fluorescence localization and intensity.

How well will this work in the brain of a living animal?  It’s not clear. Large differences in scattering paths across a field of view may dramatically slow the determination of optimal excitation beam warping and make it difficult to scan across a field of view quickly. Motion of the brain may change the pattern of scattering faster than the system can adapt.  Still, the use of adaptive optics is one of the few promising techniques for increasing penetration depth and signal in optical brain imaging (not counting sucking off the bits of the brain that are “in the way” of the excitation beam.) There are other optical tricks in astronomy that have not yet been mined for neuroscience applications.  Hopefully these will one day allow the functional imaging of all layers of the mammalian cortex, not just layer 2/3.