Tag Archives: Brain

Looking at single mRNAs in neurons hints at memory formation

It is postulated that learning and memory are modulated by synaptic plasticity – molecular changes  that result in changes in the synapse morphology and signaling capacity. Local protein translation is considered important for synaptic plasticity. Two works from our lab were published last month (back to back!) in Science. Both papers deal with how beta-actin mRNA localization and dynamics in neurons may account for local protein translation upon stimulation, and hence, may supply insight into memory formation.

The first paper by Adina Buxbaum shows that beta-actin mRNAs in dendrites are “unmasked” upon activation of the dendrites. Using single molecule FISH, She noticed that the average number of probes bound to the mRNAs in dendrites (but not in adjacent glia cells) was lower than expects, and this number increased upon stimulation. Not only that, there were more mRNAs in the stimulated dendrites. This indicated masking by a protein “coating” that prevented FISH probe binding in the unstimulated cells. A modified FISH protocol which included a protease digestion step prior to probe hybridization showed that indeed the mRNAs were masked by proteins.

single molecule FISH for beta-actin mRNA in dendrites shows that mRNAs in unstimulated neurons are masked. A) Unstimulated neuron. B) stimulated neuron showing increased number of spots. C) Unstimulated neuron, in which the fixed cells were digested with protease prior to FISH probe hybridization. Source: Buxbaum, Wu & Singer (2014). Science Vol. 343  pp. 419-422

single molecule FISH for beta-actin mRNA in dendrites shows that mRNAs in unstimulated neurons are masked. A) Unstimulated neuron. B) stimulated neuron showing increased number of spots. C) Unstimulated neuron, in which the fixed cells were digested with protease prior to FISH probe hybridization. Source: Buxbaum, Wu & Singer (2014). Science Vol. 343 pp. 419-422

 

She further showed that this masking relates to other mRNAs, as well as to ribosomes, and that this is due to a metabolic process resulting from stimulation. Thus, this unmasking process may be a way to “activate” localized mRNAs for translation.

Apart from being a very neat paper technically and biologically, I think it was exceptionally entertaining to begin her paper by quoting an 1894 work by Cajal, the father of neuroscience.

The second paper by Hye-Yoon Park follows the dynamics of single molecule endogenous beta-actin mRNAs in neurons by live imaging, using the MS2 system. She shows movement of mRNAs along dendrites, as well as some events of merging or splitting – suggesting that some mRNAs are packed together in larger granules – which may regulate local translation. She also looked at brain slices, visualizing beta actin transcription dynamics. This is an important achievement since it is much harder to look at mRNA dynamics in tissue slices than in single cells on plate, due to background fluorescence. Though some biological insight is derived here, this is more of a “new technology” report.

Live imaging of beta-actin mRNAs in dendrites (movie. Source: Park HY et al. (2014) Science Vol. 343 pp. 422-424)

These papers are just the beginning of a long-term story of how mRNA localization and local translation are regulated in neurons.  A lot of cool experiments are being done in our lab in this regard and I’ll report more as they are published.

ResearchBlogging.orgBuxbaum AR, Wu B, & Singer RH (2014). Single β-actin mRNA detection in neurons reveals a mechanism for regulating its translatability. Science (New York, N.Y.), 343 (6169), 419-22 PMID: 24458642
Park HY, Lim H, Yoon YJ, Follenzi A, Nwokafor C, Lopez-Jones M, Meng X, & Singer RH (2014). Visualization of dynamics of single endogenous mRNA labeled in live mouse. Science (New York, N.Y.), 343 (6169), 422-4 PMID: 24458643

Looking through the brain with CLARITY!

Imaging single layers of cells is very easy since the light can penetrate the cells quite easily. Imaging a tissue sample of several layers of cells is more difficult, because the passage of light is gradually blocked. To image a whole organ without slicing it was near-impossible, until now.

CLARITY is a new method, developed by the lab of Karl Deisseroth, a neuroscientists from Stanford university and published in the Nature Online. In essence, they took a whole mouse brain, infused it with a hydrogel, which was cross-linked to all the “important” biomolecules (proteins & nucleic acids). They then removed all the lipids and other “non-important” molecules (which were not cross-linked to the hydrogel), with a detergent, SDS.

The result was a transparent mouse brain, that maintained all of it original cellular (and presumably sub-cellular) structure.

Mouse brain before & after CLARITY. Source: Chung, K. et al Nature (2013)

They could then image into the brain, using pre-expressed fluorescent proteins, immunofluorescence (IF) or FISH. Importantly, they claim that one can perform several rounds of IF (and similarly FISH) and they show images to proved that.

They also show that the signal intensity of the IF signal does not diminish when going deeper into the tissue, or using different z-sections.

Structural and molecular phenotyping of a piece of human brain using CLARITY. Source: Chung, K. et al Nature (2013).

Structural and molecular phenotyping of a piece of human brain using CLARITY. Source: Chung, K. et al Nature (2013).

It is my understanding that people in the Neuroscience field have known about CLARITY for quite some time, just waited for it to get published already. It IS very exciting and amazing.

Watch the Clarity Video:

Once CLARITY becomes widespread, we should get immense amount of data on the cellular & molecular structure of many types of whole (unsliced) tissues.  We could follow development, disease and much more.

Perhaps one day even whole animals will be imaged.

ResearchBlogging.orgChung, K., Wallace, J., Kim, S., Kalyanasundaram, S., Andalman, A., Davidson, T., Mirzabekov, J., Zalocusky, K., Mattis, J., Denisin, A., Pak, S., Bernstein, H., Ramakrishnan, C., Grosenick, L., Gradinaru, V., & Deisseroth, K. (2013). Structural and molecular interrogation of intact biological systems Nature DOI: 10.1038/nature12107

Watching Neurons in action

Fluorescent sensors are important tools that can allow real-time, live, single molecule imaging of microscopic millisecond scale events. It is even better if these sensors are genetically encoded sensors (i.e. fluorescent proteins). We have already encountered the pH sensors pHluorin and pHTomato and the Ca2+ sensor GCaMP. There have been a few others, such as HyPer that detects H2O2 or ArcLight and ElectrikPk which are voltage sensors.

Now, the group of Loren Looger from HHMI Janelia  developed a sensor for a very important molecule: L-glutamate. Continue reading

Sensing pH in neurons

A recent paper in Nature Neuroscience demonstrates the usefulness of the pH sensitivity of fluorescent proteins.

I have briefly mentioned the importance of pH when I discussed mKeima. Here I will describe the work from Richard Tsien’s lab which utilizes the effect of pH on FP in order to study synaptic activity.

One avenue of communication between synapse is vesicle exocytosis, i.e. the release of neurotransmitter-containing vesicles from the pre-synaptic cell. A surge of calcium ions in the postsynaptic cell follows vesicle exocytosis. Interestingly, when a vesicle is exocytosed, the lumen of the vesicle changes its pH from 5.5 to 7.4.

A pH sensitive GFP-based protein called pHluorin was developed as early as 1998. pHluorin was fused to a vesicle protein called VAMP2. Thus, a pH change from 5.5 to 7.5 increase the emission intensity (i.e.the protein becomes brighter when excited).

Although this is a good tool, the fact that it is GFP based limits the use of dual-color microscopy, particularly with other types of fluorescent sensors since most of them are GFP, CFP or YFP based, which makes spectral distinction difficult. Therefore, the authors set out to develop a RFP based pH sensor. After several rounds of mutagenesis and shuffling of mRFP and mStrawberry, they identified a bright pH sensor which they named pHTomato since its ex/em peaks (550nm/580nm) are similar to those of dTomato. Importantly, increasing the pH has increase the brightness of the protein, without affecting the ex/em peaks (unlike mKeima which I mentioned above). Furthermore, fusion to VAMP2 did not change its characteristics; the pH dependence is reversible (i.e. once pH is acidic again, the intensity decreases).

Since VAMP2 gives them a high background expression on the membrane, the authors decided to fuse pHTomato to a protein called synaptophysin (sy), which is more vesicle specific. sypHTomato was then compared to sypHluorin in the same neuronal cell. The authors show (by graph) that both proteins perform similarly. However, it would be nice to also show an image.

Once the authors establish that pHTomato is a good pH-sensor, they turn to the real exciting work of dual color sensing. As mentioned above, following exocytosis, there is a Ca2+ increase at the post-synapse. Electrical stimuli also cause a Ca2+ surge in the presynaptic cell. The authors then used a Ca2+ sensor called GCaMP3. Briefly, GCaMP3 is a GFP-based protein that was modified such that that the two part of the protein are fused to Calmodulin (CaM) and a peptide called M13. In the presence of Ca2+, CaM binds M13, thus bringing the two parts of the GFP together, which results in fluorescence (ex/em 489/509 – similar to EGFP).

Expressing both sensors in the same neurons allowed them to visualize the spike in Ca2+ (green spike) concurrent with an increase in red signal, that deteriorates slowly, upon stimuli to the neurons. I am not a neuroscientist, so I cannot evaluate their system regards to choice of cells/stimuli, but the fluorescence response following the different stimuli they give seems distinct and impressive. However, it is very difficult to see it in the snapshot images of the cells.

Expressing each sensor in a different cell allowed the authors to distinctly visualized pre and post synaptic cells at the same synapse. What they looked at are pre synaptic sypHTomato-positives cells, in contact with post-synaptic GCaMP3 positive cells. I think that the image is beautiful:

Figure 3: Dual-color imaging of synaptic connection by sypHTomato and GCaMP3. (partial figure)

Now that the technical issues have been address, it was time to ask some meaningful biological questions. The first question which they asked is whether the vesicle content at presynaptic termini (called boutons) of the same cell is the same in all synapses of the same cell, or are there differences based on the target, postsynaptic cell (obviously a pre-synaptic cell can create synapses with multiple post-synaptic cells).

They used stimuli to measure the volume of the readily-releasable vesicles, and ammonium chloride (NH4Cl), a strong base, to measure the total volume of all vesicles in each synapse. They found that synapses that were targeted to the same postsynaptic neuron had reduced variability in total and readily-releasable vesicle volume, compared to the variability of synapses targeted to different cells. This indicates that there is some reverse feedback from the post-synaptic cell to the pre-synapses.

It would have been interesting to see if pre-synaptic boutons from different cells also have less variability if they are targeted to the same post-synaptic cell. However, the authors did not measure that.

They then looked what happens when you stimulate the cells electrically. As ecpected, there is an immediate increase in sypHTomato signal (vesicle exocytosis) with an almost immediate increase in GCaMP3 signal (Ca2+surge) in the post synaptic cell. This Ca2+ surge begins at the synapse but propagates along the dendrites, indicating opening of voltage-gated Ca2+ channels with the propagation of the ation potential. They confirmed that the Ca2+ surge is due to the vesicle release by adding inhibitors for the neurotransmitter receptors on the post-synaptic cell, and detecting little or no Ca2+ increase (The inhibitors did not affect vesicle release). This approach, then, was capable to image neuronal activity at single synapse resolution.

But the authors went one step further, to get achieve an all-optical system.

The experiment described above was performed by electrically stimulating the cells. However, such methods are invasive and affect the entire cell. An alternative strategy to activate cells is by chemical application of agonists or antagonists. However, addition of drugs or neurotransmitters to the cell culture media will affect all cells in the media. Here comes optogenetics – a system that allows optical activation of a single cell, or part of it. I do not want to discuss optogenetics here; this should get a post or two of its own. The basic idea is to use genetically encoded light-responsive ion channels. Once you shine light (at a specific wavelength) on the part of the cell you want to activate, the ion channel opens and you get action potential originating from the part of the cell you shined on. So here comes the cool stuff:

The authors co-expressed channelrhodopsin2 (ChR2) with a pHluorin-tagged vesicular glutamate transporter (vGluTpH). ChR2 gets to the plasma membrane, whereas vGluTpH to the vesicles. When they shined blue light (to activate ChR2 and excite pHluorin) they get an increase in the green signal, which is abolished by a drug that inhibits action potential. Similarly, co-expression of VChR1 (another optogenetic tool) with stpHTomato and shining green light (to activate VChR1 and excite pHTomato) led to an increase in red emission, that was abolished by the drug.

Better yet, co-expressing ChR2 with sypHTomato showed an increase in red signal only when cells were illuminated by blue light (that activates ChR2) and not green light (Which doesn’t). This figure should have been a main figure. I don’t know why they put it in the supplementary.

Fig S6(b) Tests of ChR2 in combination with sypHTomato as proof-of-principle of all-optical yet independent monitoring and stimulation. Left, interrogation of sypHTomato with Green light (546 -566nm) excitation alone without activation of ChR2-driven vesicular turnover. Right, positive control with blue light (457-482 nm), showing robust ChR2-driven sypHTomato transient (right).

And there you have it – an all optical system to study vesicle release in neurons.

So what can we do with this system?

The authors state several exciting possibilities:

  1. Perform dual color experiments with other green sensors.
  2. Deciphering pre and post synaptic strength in different scenarios.
  3. Probing neuronal circuits: combining optogenetic photostimulation of two spectrally distinct channlerhodopsins with two spectrally distinct sensors (pH sensors in this case) will allows us to follow the neural pathway when we activate a distinct neuron with a specific color.

But I could think of other options. For instance, the authors did not discuss at all the growing use of caged molecules. In brief, caged molecules are biologically relevant molecules that are in an inactive state. These molecules can be activated by shining light of a specific waveband. Thus, if you have a caged neurotransmitter and you shine the light at a specific location, synapses can be activated only if the uncaged molecule is at high enough concentration (i.e. where you shined your light).

The authors kind of ignored it, but there seems to be a difference in the sypHTomato intensity, and signal decay, when comparing electrical and optical stimulation. This difference could be biologically meaningful and could be further explored.

All in all, I think it is a very nice paper, describing a new system to study neurons.

Further reading:

Yulong Li & Richard W Tsien (2012) pHTomato, a red, genetically encoded indicator that enables multiplex interrogation of synaptic activity. Nature Neuroscience 15, 1047–1053.

A good post on GCaMP at “brain Windows” blog.

Optogenetics resource center

Info on chemical synapses, from Wikipedia

ResearchBlogging.org
Li Y, & Tsien RW (2012). pHTomato, a red, genetically encoded indicator that enables multiplex interrogation of synaptic activity. Nature neuroscience, 15 (7), 1047-53 PMID: 22634730