Three ways of looking at touch coding

20 09 2012

At SfN, a block of three posters by myself, Simon Peron and Daniel O’Connor will showcase three ways to approach the problem of touch coding.

My work on whisker force measurements, and single cell and silicon probe based cortical recordings during active objection localization :

Program#/Poster#: 677.18/KK18
Presentation Title: Encoding whisking-related variables in the mouse barrel cortex during object localization
Location: Hall F-J
Presentation time: Tuesday, Oct 16, 2012, 2:00 PM – 3:00 PM
Authors: *S. A. HIRES, D. O’CONNOR, D. GUTNISKY, K. SVOBODA;
Janelia Farm Res. Campus, ASHBURN, VA

Simon Peron’s work on recording a complete representation of touch using in-vivo imaging with new G-CaMP variants during a similar behavior :

Program#/Poster#: 677.12/KK12
Presentation Title: Towards imaging complete representations of whisker touch in the mouse barrel cortex
Location: Hall F-J
Presentation time: Tuesday, Oct 16, 2012, 4:00 PM – 5:00 PM
Authors: *S. P. PERON1, V. IYER2, Z. GUO2, T.-W. CHEN2, D. KIM2, D. HUBER3, K. SVOBODA2;

Daniel O’Connor’s work on constructing synthetic perception of touch and object localization via cortical cell-type specific optogenetic stimulation during behavior :

Program#/Poster#: 677.06/KK6
Presentation Title: Neural coding for object location revealed using synthetic touch
Location: Hall F-J
Presentation time: Tuesday, Oct 16, 2012, 2:00 PM – 3:00 PM
Authors: *D. H. O’CONNOR1, S. A. HIRES1, Z. GUO1, Q.-Q. SUN2, D. HUBER1, K. SVOBODA1;

This is a must-see session for people interested in touch coding, the whisker system, in-vivo cortical imaging, or synthetic perception via optogenetics.

I hope to see you there.

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Optical control of gene expression in mammalian cells

2 02 2011

Trying to start a reboot of the posts here on Brain Windows. Lots of great stuff has come out since the last regular posting period, and unfortunately I don’t have the time to cover it all. One of the most exciting papers of the last few months was Rapid blue-light–mediated induction of protein interactions in living cells published in Nature Methods. This paper reports the  logical extension of previous technologies for photoactivatable transcription we previously covered here, here, and here.

There are two key technical improvements in the system from the Tucker Lab.  First, the genetic light switch, a cryptochrome 2 (CRY2) interaction with cryptochrome-interacting basic-helix-loop-helix protien (CIB1), is activated by blue light rather than the red light of previous switches based on phycocyanobilins.  Second, and more importantly, the cofactors necessary for the switch action (flavin and pterin chromophores), are endogenously expressed in mammalian tissues.  Thus, these switches should be usable in vivo without potentially tricky loading of the cofactors.

Upon illumination, the authors observed rapid translocation (in 1 second!) of fluorescent proteins tagged with CRY2 to cell membranes with CIB1 anchored to it.  They also were able to couple it to Gal4-UAS and Split-Cre expression systems, which let them drive reporter genes such as GFP by blue-light illumination.  I was a bit underwhelmed by the efficacy of the cre-induction, only around 15% of cells expressed the cre-driven EGFP after 24 hours of illumination, but maybe that is due to my ignorance of the current limits of the split-cre system.  That efficacy will certainly need to be improved for the REALLY cool stuff one can imagine doing with this.

What are the cool things?  Well, say you are doing some GCAMP3 imaging of a few hundred cells in the cortex during an awake behavior.  You see an ensemble of neurons whose activity is correlated to some aspect of the behavior, like a motor command, a perception or a decision. You want to prove the function of these neurons, to investigate their coding by subtracting or adding activity directly into this specific functional group. How do we control ONLY this group?

A pan-neuronal channelrhodopsin, or even one packaged in a cre-dependent virus injected into a cre reporter line will not allow you to change the spike patterns of only this ensemble. This ensemble is not differentiable from its neighbors by genetic type, only by functional relevance.  You have to hit its neighbors or shared genetic subtype with the same hammer.  But if you have one of these CRY2-CIB1 split cre switches that drive ChR2 expressed across the cortex, you could shine a blue laser (or presumably a two-photon laser) onto the members of the ensemble and turn on optical control of only that functional group.

Details of course still need to be worked out. What is the 2p cross-section of the system? How do you make it compatible with optical imaging and optical control?  How do you improve the speed and efficacy of the switch? These are things that will come with time.  The power of this technique is even recognized by apparent competitors in the field; Anselm Levskaya closed his packed SfN talk on phycocyanobilin-based optical switches with a shout out to this work.

Stay tuned…
Kennedy MJ, Hughes RM, Peteya LA, Schwartz JW, Ehlers MD, & Tucker CL (2010). Rapid blue-light-mediated induction of protein interactions in living cells. Nature methods, 7 (12), 973-5 PMID: 21037589





Software Update : Ephus, ScanImage & Neuroptikon

20 08 2010

Three excellent pieces of neuroscience software have been recently updated or freshly released.  I have used two of them, Ephus and ScanImage, on a daily basis as primary data collection tools. The third, Neuroptikon, is quite useful for post-hoc illustration of neural circuits.

Ephus is a modular Matlab-based electrophysiology program that can control and record many channels of tools and data simultaneously.  Under control of a sophisticated internal looper or external trigger, you can initiate an ephys recording, trigger camera frames, adjust galvo positions, open/close shutters, trigger optical stimulation, punishments, rewards, etc.  It is a workhorse program for non-imaging related in vitro and in vivo electrophysiology experiments.  Ephus is named for the fabled baseball pitch, and pronounced as “EFF-ess”. As with the pitch, it may trick you at first, but eventually you’re sure to hit a home run. Of course, the name also evokes electrophysiology, which is the fundamental orientation of the project, be it optical or electrical.

Ephus 2.1.0 is a major release, and the only official version at this time.  The software is fully described in a publication in Frontiers in Neuroscience. New features include unlimited recording time, with disk streaming, for applications such as EEGs and long traces during in-vivo behavior. A number of additional scripts for in-the-loop control have been added. New configuration/start-up files have been created, with a template to help get up and running quickly. This release also includes a number of bug fixes.

ScanImage is another Matlab-related software program that is used for optical imaging and stimulation of neurons in vitro and in vivo.  It finds much use a control platform for 2-photon imaging, glutamate uncaging and laser-scanning photostimulation.  An early incarnation is described in this paper by Pologruto, et al.  It provides a lot of power right out of the box (bidirectional scanning @ 0.5ms/line, etc) and is easily extensible via custom user function plugins.

Neuroptikon is a sophisticated network visualization tool.  It can build Van Essen-like diagrams of any circuit you like, but it is so much more.  The direction of communication is animated, and subsets of regions and connections can be brought into focus, which greatly eases the clarity of the network.  The diagrams can be built in three-dimensions, to preserve relative topography, or functional grouping.  There is simple GUI-based control, while more complex tasks can use a scripting interface.  This is great software for anyone who needs to imagine information flow in a complex network.

All three tools are released for free use under the HHMI/Janelia Farm open source license.

Download Here :

Ephus 2.1.0

ScanImage 2.6.1

Neuroptikon 0.9.9





Cameleon-Nanos : High Affinity GECIs

9 08 2010

Takeharu Nagai’s lab has published in Nature Methods, Spontaneous network activity visualized by ultrasensitive Ca2+ indicators, yellow Cameleon-Nano, demonstrating a new set of calcium indicators based on yellow cameleon. Back when he was still Take-san, Take’s ability to churn out and manually screen hundreds of cameleon variants was impressive and inspiring. With high-throughput GECI pipelines now ramping up at Janelia, the idea of laboriously screening 200 variations on a theme (be it cameleons or GluSnFRs), seems a bit archaic. However, this paper is a good example of the progress that can still be made by understanding the needed sensor parameters and fiddling with the primary amino acid structure in a relatively low-throughput way. Take-sensei’s results are another example of the pramatic rule in protein design, “when in doubt, tinker with the linker.”

The cameleon-nano family achieves greater apparent calcium affinity than YC2.60-4.60, reaching levels of up to 15nM.  They did this by increasing the flexibility of the linker by extending the standard Tsien/Miyawaki/Baird Gly-Gly-Ser linker with additional glycines.  In this case, the longer the linker between the CaM and M13 segments, the greater the apparent affinity. Interestingly, improvement by increasing linker flexibility is precisely the opposite the advice Atsushi and Take gave me for achieving high ratio changes with FRET reporters.  Back at RIKEN in 2002, they suggested I use short, stiff linkers to restrict the rotational freedom of the fluorescent pairs.  Then one could find orientations where relative rotation of dipole moment gave much greater FRET changes than would be expected from changes in FP distance alone. Take and Atsushi’s big YC2.60/3.60 paper strongly supported this idea!  However, as our understanding of the ideal parameters of calcium sensor’s for in vivo imaging has grown, development directions have adjusted.

Cameleon-Nanos achieve higher signal/noise for sparse action potentials at the expense of linearity.  Like Fluo-4, the signal saturates at relatively low AP frequencies.  I think the absolute affinities measured for this family (15, 30, 50 and 140nM) should be considered very rough estimates. They extrapolated these values from stopped-flow binding experiments, because

Although we would like to measure the koff of YC2.60 and its high affinity variants such as YC-Nano15, we could not do it because it was very difficult to precisely control free Ca2+ concentration at around few tens of nM as far as we used EGTA (Kd for Ca2+ = 151 nM in 0.1 M ionic strength, pH 7.2 at 25 oC). For this purpose, much stronger Ca2+ chelator with a smaller Kd value was required. However there is no such Ca2+ chelator available now.

I’m not sure why they didn’t just use the higher affinity, Mg++ insensitive, chelator BAPTA to make the Kd measurements the right way, with a linear regression of log-log fluorescence/concentration values.  Due to instrument dead time, and the high affinity, I didn’t like stopped-flow based Kd measurements in the early GCaMP papers, and I don’t like them now.  Also, the apparent calcium Kd will be highly dependent on solution ionic strength and [Mg++] which is unreported. Despite these quibbles, which are important only inasmuch as they give insight into the mechanism of improvement and the direction of future development, the cameleon-nano family looks promising for mammalian brain imaging.  I still wonder if, assuming the reported Kd values are relevant in vivo, YC2.60 would be the best of the bunch, since cortical neurons have a resting Kd of ~50nM, which implies that a single AP transient of say 200nM free [Ca++] increase would push the calcium levels right up into the sweet-spot of YC2.60’s sensitivity.

This is all the more interesting given the recent results in YC3.60 imaging from Maz Hasan’s group.  Previously, he had shown that transgenic YC animals were pretty bad for imaging.  However, AAV-mediated gene delivery of YC3.60 has significantly improved the responses of the YC family. I’m not sure if they are really up to GCaMP3 levels under identical in vivo conditions, but they might have better long-term protein stability (or that might depend on which viral serotype is used.) What about cameleon-nanos, what about YC2.60?





UPDATE : Bi-Directional Optogenetic Control

26 03 2010

The Deissseroth lab has released an updated version of their optical neuronal silencing gene Natronomonas halorhodopsin. In Molecular and Cellular Approaches for Diversifying and Extending Optogenetics, Gradinaru et al review current optogenetic methodology, and introduce eNpHR3.0-2A-ChR2, a genetic vector whose expression allows both action potential silencing and firing via illumination. This vector uses post-translational cleavage (via cis-acting hydrolase elements) of the 2A peptide to coexpress channelrhodopsin and halorohdopsin at high levels via a single promoter. The use of 2A provides a more balanced level of relative expression compared to the traditional strategy of using an IRES site, though differing degradation rates of the two proteins cause expression to not be truly stoichiometric.

eNpHR3.0 has superior cellular membrane expression

The improved eNpHR 3.0 contains additional trafficking sequences that greatly reduce expression in intracelluar compartments.  This results in enhanced surface expression a 20-fold increase in photocurrents over eNpHR1 and large, near-nanoampere currents at modest 3.5mW/mm^2 light intensities.  The paper implies superior performance over the Boyden group’s Arch optogenetic silencer technology, but shows no head to head data.  As always, testing both in your own system is the best way to evaluate their relative merits.

Activation spectrum for eNPAC (left), and for ChR2(H134R) (right, blue) and eNpHR3.0 (right, yellow) alone. Maximum eNPAC steady-state excitation was 567 ± 49 pA at 427 nm (n = 9), 62% of the value for ChR2(H134R) alone (916 ± 185 pA; n = 5). Similarly, maximum eNPAC inhibition was 679 ± 109 pA at 590 nm (n = 9), 61% of the value for eNpHR3.0 alone (1110 ± 333 pA; n = 4). Output power density for peak eNpHR3.0 current values was 3.5–5 mW/mm2 (3.5 mW/mm2 at 590 nm).


ResearchBlogging.org
Gradinaru, V., Zhang, F., Ramakrishnan, C., Mattis, J., Prakash, R., Diester, I., Goshen, I., Thompson, K., & Deisseroth, K. (2010). Molecular and Cellular Approaches for Diversifying and Extending Optogenetics Cell DOI: 10.1016/j.cell.2010.02.037

ResearchBlogging.org

Tang, W., Ehrlich, I., Wolff, S., Michalski, A., Wolfl, S., Hasan, M., Luthi, A., & Sprengel, R. (2009). Faithful Expression of Multiple Proteins via 2A-Peptide Self-Processing: A Versatile and Reliable Method for Manipulating Brain Circuits Journal of Neuroscience, 29 (27), 8621-8629 DOI: 10.1523/JNEUROSCI.0359-09.2009