Download Enlightenment - The Dartmouth Undergraduate Journal of Science

Neurology
Enlightenment
Optogenetic Tools for Understanding the Brain
Hannah Payne ‘11
N
euroscientists are scrambling
to play with the new toys of optogenetic technology, but with
the explosion of popular science articles and even videos of light-controlled
dancing mice (1), it is important to
step back and evaluate how this technology can be most effectively used to
solve meaningful problems in neuroscience. Optogenetics serve as a remote
control of neural activity. Groups of
cells are genetically encoded to produce light-sensitive proteins, allowing
high levels of control of neural activity in specific populations of neurons.
This review will focus on optogenetic
actuators, which drive activity using
light, as opposed to sensors, which
report activity, beginning with a brief
overview of optogenetic technology.
The review will then synthesize recent
progress that optogenetics has allowed
in teasing apart the role of specific subpopulations and patterns of activity
in network dynamics and ultimately
how complex behaviors emerge from
these elements. Finally, future applications for both neuroscientific research
and human disease will be discussed.
The Optogenetic Toolbox
The capabilities of optogenetic
technology for controlling activity have
expanded tremendously since Karl Deisseroth’s group first demonstrated the
efficacy of channelrhodopsin-2 (ChR2)
in 2005 (2). ChR2 was taken from the
green algae Clamydomonas reinhardtii
and successfully used to drive activity in mammalian neurons, and is still
the most commonly used optogenetic
tool, although improved engineered
versions such as ChETA and ChIEF
will likely replace it in the future (3,4).
Similar to opsins found in the retina,
ChR2 responds to light in the presence
of the commonly occurring cofactor,
all-trans retinal. However, instead of
triggering a G-protein coupled signaling cascade as do opsins in mammalian
Winter 2011
retinas, ChR2 responds to 460 nm blue
light by opening the ion channel at the
core of its seven transmembrane domains, allowing positive ions to pass
through (Fig. 1). The result is a sensitive and rapid depolarization of the cell
in response to light, allowing neuronal
spiking to be reliably elicited (2). Furthermore, some optogenetic tools can
decrease neuronal activity, which is
not easily controlled with conventional
stimulating electrodes. For example,
halorhodopsin (Halo) is a light-activated chloride pump isolated from the archaebacterium Natronomas pharaonis
(5). Upon exposure to yellow light (560
nm), the influx of chloride ions hyperpolarizes the cell and prevents action
potentials. Due to the different wavelengths of activation for ChR2 and halorhodopsin, it is possible to express
both proteins in the same neuron, allowing for bidirectional control of activity at the millisecond timescale (6).
The main labs involved in pioneering optogenetic technology, those
of Karl Deisseroth at Stanford University and Ed Boyden at Massachusetts
Institute of Technology, are attempting
to make the process as transparent as
possible by providing detailed protocols and genetic sequences freely online
(openoptogenetics.org, optogenetics.
org, and syntheticneurobiology.org).
Together they have distributed plasmids containing the ChR2 gene to hundreds of other laboratories. Overall, the
process can be divided into three steps:
expressing the gene in desired cells,
delivering light to control activity, and
recording output (behavioral and/or
electrophysiological) (7). Gene expression is a well-established problem, and
is acheived using transgenic animals,
viral infection, or electroporation (7).
Light is typically delivered using fiber
optic cables which in rodents or monkeys are attached to the head, while
smaller organisms (nematodes, xenopus, or drosophila) are simply exposed
to full-field light. Behavioral output
can be observed with the use of flexible
fiber optic cables and has resulted in
dramatic demonstrations of the direct
link between neural activity and behavior (8). Multielectrode arrays or single
electrodes can record extracellular signals from both single cells and population activity (local field potentials);
patch clamping methods are used to
record with great precision from single
neurons; and optogenetic voltage or
calcium sensors that can report activity are an ongoing area of development.
Pros and Cons
Light-years ahead
Optogenetics has several key advantages over previous methods of controlling neuronal activity, such as electrical stimulation or neurotransmitter
uncaging. Optogenetics is less invasive than electrical stimulation, since
light can penetrate several millimeters
into brain tissue (7). Neurotransmitter uncaging, in which special caged
particles containing glutamate or other
neurotransmitters are injected into
the brain, also requires invasive injection procedures, which may be avoided
by using transgenic optogenetic lines
(7). Compared to both methods, the
optogenetic response time is faster
and spikes are more reliable (2). Additionally, the specificity of genetic encoding via promoters for specific cell
types makes this technique extremely
powerful for distinguishing functions of different neural populations.
Limitations
A main limitation of optogenetic probes is their low sensitivity—
compared to human photoreceptors,
light-activated proteins are nearly
blind. In a photoreceptor-lacking retina expressing ChR2, about 1015 photons cm-2 s-1 are needed to produce a
response, compared to only 106 photons cm-2 s-1 for rod photoreceptors,
a billion-fold increase (9). For most
19
experimental applications this is not
a problem as bright light sources are
readily available; however one must
consider that the visual system might
be inadvertently activated in small organisms such as fruit flies and tadpoles.
However, the most salient limitation may the difficulty in translating the
power of optogenetics into therapeutic
approaches to human disease. There
are many technical and ethical difficulties faced in introducing a foreign gene
to human cells, let alone into the brain.
Virus particles may cause adverse reactions, and precise expression of the
gene may be hard to control. Also, fiber
optics would have to be permanently
affixed to the head, potentially causing
infection, discomfort, and the need to
carry heavy batteries. Finally, the ethical considerations of having such direct
control over human neural activity must
be very carefully considered. At present,
optogenetics remains extremely powerful for purposes of scientific research.
Illuminating Neural
Networks
Currently, optogenetic technology
is being applied somewhat haphazardly to a great variety of problems (1, 8).
While these “proof-of-principle” demonstrations are useful, they do not necessarily constitute experiments. Overall, neuroscience seeks to understand
the brain from the most basic molecular level up through complex human
behavior, and optogenetics holds the
most promise for understanding the
brain at the intermediate level of neural networks. First, optogenetics can be
used to manipulate activity of individual neurons, or small subpopulations
of neurons, and one can then observe
the effects on the activity of the entire
local circuit. Second, optogenetics can
be used to manipulate activity with extreme temporal precision, allowing the
function of patterns of activity to be
studied. Third, these elements can then
be combined to connect neuronal activity to complex brain functions such as
perception and learning and memory.
Subpopulation contributions
to network dynamics
A main strength of optogenetics is
20
that it allows detailed genetic specificity. Different promoters can target very
specific types of neurons. Furthermore,
electroporation of DNA by applying a
brief electric current to open temporary
pores in a cell membrane allows for labeling of just one or a few cells. These
techniques allow for an understanding
of neural network activity at the most
basic functional level. For example, researchers led by Michael Hausser at the
University College in London recently
used ChR2 to investigate the role of individual somatostatin interneurons in
visual processing. Somatostatin inhibitory neurons make up roughly 15% of
the interneurons in the cortex and synapse primarily on pyramidal cell apical dendrites, but their function is unknown (10). The researchers expressed
ChR2 in two to five somatostatin neurons in mouse visual cortex. They then
recorded from neighboring pyramidal
cells while stimulating the visual system
with a series of moving visual stimuli.
As expected, activation of the inhibitory somatostatin neurons reduced the
response of some neighboring pyramidal cells, but surprisingly some pyramidal cells actually increased firing
when the somatostatin neurons were
activated. Although the mechanism for
the paradoxical enhancement of some
pyramidal cells is not known, it could
be due either to inhibition of other
neighboring interneurons, or by direct
integration properties on the pyramidal cell dendrites (10). It is tempting to
think that interneurons might be wired
to affect pyramidal cells differently
depending on whether they convey information from the center or surround
of the pyramidal cell’s receptive field.
The role of patterned activity
in network dynamics
In addition to genetic specificity,
the temporal precision of optogentics
is also invaluable. The ability to control exactly when a neuron fires or does
not fire with millisecond precision is
beginning to allow researchers to dissect the role that a specific observed
pattern of activity, such as oscillation at a specific frequency, has on the
overall performance of the network.
The experiment described above
used a regular train of light pulses at
40 Hz to drive the somatostatin inhibi-
tory neurons, but no other frequency
was tested (10). This frequency was
likely chosen because oscillations between 30-60 Hz, known as the gamma
frequency band, have been commonly
observed in the cortex, especially during activity and memory retrieval (11).
The Hausser lab examined the effect
of changing the oscillation frequency
of both excitatory and inhibitory neuron populations in V1 cortex in another
recent abstract (12). Interestingly, regardless of the frequency enforced in
either subpopulation by ChR2 activation (5, 25, 40, and 75 Hz), local field
potentials from layer 2/3 recorded enhanced oscillations around the intrinsic
frequency of the network (20-35 Hz).
Oscillations were increased more when
the animals were under anesthesia than
when they were awake and moving on a
treadmill, which is somewhat puzzling
since gamma oscillations are typically
linked with active behavior (11). A final interesting finding from this study
was that when optogenetic stimulation was applied in concert with visual stimulation, oscillation power was
enhanced in an additive manner (12).
Overall, this study demonstrates the
power of ChR2 to reveal a new wealth
of information about the effects of patterned activity on network dynamics.
However, there is still disagreement about exactly how these gamma
oscillations arise. In a study published
in Nature last year, both fast-spiking
interneurons and excitatory pyramidal cells were controlled with ChR2 in
the mouse somatosensory barrel cortex
(13). Like Havenith et al., the group
found that regardless of the imposed
frequency of fast-spiking interneurons,
local field potentials were enhanced
within the gamma range. However, activation of pyramidal cells only increased
lower frequency oscillations (Fig. 2).
This cell-type specific dissociation in
network oscillatory activity is an interesting property that may be important
in brain disorders with deficits in gamma oscillation, and optogenetics will be
instrumental in working out the details.
Dartmouth Undergraduate Journal of Science
a.
b.
c.
Image retrieved from http://www.nature.com/nature/journal/v459/n7247/images/nature08002-f3.2.jpg (Accessed 29 Jan 2011).
Fig. 2: a. Example of natural gamma oscillations phase shifted by blue light pulse. b,c. Local field
potential enhancement at 40 Hz was only driven by fast-spiking (FS) interneuron oscillation, not
regular-spiking (RS) pyramidal cells.
Connecting Neuronal
Activity to Brain Function
shifted responses towards the preferred
octave of the activated region in a behavioral tone discrimination task (18).
While the above studies begin to reveal the precise connection
of individual neurons and activity
patterns to the dynamics of the surrounding network, optogenetics can
also link network elements directly to higher-order brain function.
Learning and memory
Perception
Gamma oscillations driven by inhibitory neurons have been theorized to
control the gain of sensory input, to act
as an attentional mechanism (14), and
to influence working memory (11). Failure of gamma oscillation is associated
with brain disorders such as autism
(15) and schizophrenia (16, 17). Cardin
et al. therefore investigated the role of
the precise timing of oscillatory activity on neural coding of whisker stimulation (13). Using a mouse expressing
ChR2 in fast-spiking interneurons,
they applied blue light at 40 Hz to induce gamma oscillations phase-locked
to the light pulses. They then stimulated a whisker at various time points
(Fig. 3a). Remarkably, precision of pyramidal cell responses increased when
the whisker was stimulated at specific
phases of the oscillation (Fig. 3b-f).
The authors conclude that sensory
transmission is decreased during the
peak of the interneuron inhibitory neurotransmitter release, leading to temporal sharpening of the response during inhibitory neuron oscillation(14).
Optogenetics have also been used
in simpler experiments to link neuronal activity to perception. For example, stimulation of auditory cortex
using nonspecifically expressed ChR2
Winter 2011
Optogenetics is also beginning to
reveal novel aspects of learning and
memory. For example, a recent optogenetic study found intriguingly different
results when using a light-activated activity block compared to a pharmocological block (19). When tetrodotoxin
(TTX) was injected to inactivate the
CA1 region of the hippocampus, a timedependent affect on memory retrieval
in a contextual fear conditioning task
was found: when injected before training, or right before testing one day after
training, TTX blocked memory of the
feared context. But when TTX was injected just prior to testing after 28 days,
both control and TTX-injected rats still
froze in response to the context, corroborating the generally accepted hypothesis that CA1 of the hippocampus is
involved in the formation and consolidation of memories, but not long term
storage. However, injection of pharmacological agents necessarily takes
time on the order of 30-60 minutes, a
relatively long time when one considers
that new memories can be formed on
the scale of minutes and even seconds.
Therefore, the researchers employed the light-activated chloride
pump halorhodopsin (Halo) to rapidly
and reversibly block activity in CA1
(19). Halo was expressed in excitatory
neurons in CA1 and effectively blocked
activity when activated by light. Turning the light on during training or during testing one day after training impaired recall of the context. However,
unlike TTX, activation of Halo during
testing 28 days later also significantly
blocked the fear response. Activating
Halo 30 minutes before the 28-day
testing phase did not cause any impairments in memory recall, and auditory cued-fear responses were not affected by light activation in CA1 at any
stage of testing or training. Together,
these novel results may indicate that
the hippocampus does in fact store
long-term memories, but may not be
necessary for long-term memory recall if the brain has sufficient time to
recruit alternate mechanisms (19).
Future Experimental
Directions
Overall, the sampling of findings above, although incomplete,
provides a broad picture of how optogenetics are beginning to reveal
the neural mechanisms underlying
complex brain functions. By linking
individual neurons and specific patterns of activity to network dynamics, and then linking these elements
to complex tasks such as perception
or learning and memory, optogenetics
should make it possible to understand
the brain in unprecedented detail.
Many other brain functions are
promising candidates for optogenetic
research. In particular, Robert Wurtz
has suggested that optogenetic perturbation of neuronal activity will be useful
in correlating neural activity to behavior in order to dissect the mechanisms
of visual attention and suppression
during saccades (20). Similarly, studies of motivation have thus far relied
on recording neural activity in different
brain regions in response to behavior
(21); by expressing optogenetic controls
in dopaminergic or seratoninergic systems and directly stimulating or inactivating those neurons, the reverse experiment could be conducted in which
neural activity might be shown to cause
the specific motivational behaviors.
The genetic specificity of lightcontrolled neurons is especially promising for studying the balance of excitation and inhibition. Excitatory/
Inhibitory (E/I) balance changes drastically during development, from mainly excitatory in childhood to roughly
equal in adulthood. This shift in E/I
balance is essential for proper timing
of the “critical period” during which
21
Image retrieved from http://www.nature.com/nature/journal/v459/n7247/images/
nature08002-f4.2.jpg (Accessed 29 Jan 2011).
Fig. 3: a. A whisker was stimulated at five
different points during the light-induced
oscillation. b. Baseline response histogram.
c. Responses with gamma oscillation d. Spike
count was reduced for some stimulation phases
e. Some spike latencies increased f. Spike
precision was increased in a phase dependent
manner.
experience-dependent plasticity can
shape the developing nervous system
(22). Monocular deprivation during
this critical period causes a cortical bias
towards the contralateral eye which is
normally irreversible. However, some
manipulations such as demyelination or decreasing cortical inhibition
using pharmacology can return the
brain to a plastic state (22). Optogenetics would allow more precise investigation of how E/I balance regulates
the boundaries of the critical period.
Treatment of Disease
Since optogenetics has already
been used to selectively activate or suppress specific populations of excitatory
or inhibitory neurons, it could conceivably be used to correct E/I balance in
certain brain disorders. For example,
schizophrenics have decreased myelin
and too much excitatory activity—in a
way the brain is developmentally immature (22). Increasing activity in in22
hibitory neurons, or alternatively suppressing activity in excitatory neurons,
might help correct the balance. Increasing inhibition may also help restore
normal gamma oscillations, which are
dysfunctional in schizophrenics (16,
17). Conversely, if the critical period
has passed without the opportunity for
normal experience, as it has for patients
who only gain sight after childhood
(23), a shift in the excitatory direction
might aid the development of a functional visual system even late in life.
Other potential therapeutic approaches include cell-type specific versions of deep-brain stimulation with
potential for treating Parkinson’s,
epilepsy, severe depression and mood
disorders, sleep disorders, and phobias. Additionally, some groups have
begun engineering retinas with ChR2
to replace damaged photoreceptors
(24,25). Perhaps if multiple opsins
were expressed, such as ChR2 plus a
red-shifted version, or ChR2 plus Halo
(6), then functionally distinct populations of neurons in the retina could be
activated differentially to provide more
biologically realistic inputs. However,
although the possibilities for therapeutic approaches are limited only by
the imagination, any use of optogenetics in humans is light-years away due
to the difficulty of introducing genes
into the human brain and the ethics
of directly controlling neural activity.
Conclusion
In a way, the timing of optogenetic’s entrance on the stage of neuroscience is ideal. Other techniques have
shown how environmental stimuli and
behavioral outputs correlate with patterns of neuronal activity; the next step
is to directly manipulate activity with
genetic and temporal precision to elucidate the neural basis of perception,
behavior, and everything in between.
References
4. L. A. Gunaydin et al., Nature Neuroscience.
13, 387–392 (2010).
5. B. Schobert and J. K. Lanyi, The Journal of
Biological Chemistry, 257, 10306-10313 (1982).
6. X. Han, E. S. Boyden, PLoS ONE 2, 299
(2007).
7. F. Zhang, et al. Nature Protocols,
5(3):439-456. (2010).
8. M. Rizzi et al., Program No. 388.8. 2009
Neuroscience Meeting Planner. San Diego, CA:
Society for Neuroscience. Online. (2009).
9. E. Ivanova, Z. H. Pan, Mol Vis. 15,
1680–1689 (2009).
10. J. C. Cottam, S. L. Smith, M. Hausser,
Program No. 450.21. 2010 Neuroscience
Meeting Planner. San Diego, CA: Society for
Neuroscience. Online. (2010).
11. M. W. Howard et al., Cereb. Cortex. 13,
1369-1374 (2003).
12. M. N. Havenith, H. Langeslag, J. Cottam,
M. Hausser, Program No. 673.13. 2010
Neuroscience Meeting Planner. San Diego, CA:
Society for Neuroscience. Online. (2010).
13. J. A. Cardin et al., Nature. 459, 663-667
(2009).
14. U. Knoblich, C. I. Moore, Program No.
673.14. 2010 Neuroscience Meeting Planner.
San Diego, CA: Society for Neuroscience.
Online. (2010).
15. E. V. Orekhova et al., Biol. Psychiatry 62:
1022–1029. (2007).
16. K. M. Spencer, M. A. Niznikiewicz, M. E.
Shenton, R. W. McCarley, Biol. Psychiatry 63,
744–747 (2008).
17. P. J. Uhlhaas, C. Haenschel, D. Nikolic, W.
Singer, Schizophr. Bull. 34, 927–943 (2008).
18. P. Znamenskiyi, A. M. Zador. Program No.
805.13. 2010 Neuroscience Meeting Planner.
San Diego, CA: Society for Neuroscience.
Online. (2010).
19. I. Goshen et al., Program No. 412.3. 2010
Neuroscience Meeting Planner. San Diego, CA:
Society for Neuroscience. Online. (2010).
20. Wurtz, Peter and Patricia Gruber
Lecture: Brain Circuits for Active Vision. 2010
Neuroscience Meeting Planner. San Diego, CA:
Society for Neuroscience. Online. (2010).
21. O. Hikosaka, Program No. 218: Presidential
Special Lecture. 2010 Neuroscience
Meeting Planner. San Diego, CA: Society for
Neuroscience. Online. (2010).
22. T. Hensch, Program No. 213.2. Molecular
brakes on plasticity. 2010 Neuroscience
Meeting Planner. San Diego, CA: Society for
Neuroscience. Online. (2010).
23. P. Sinha, Program No. 422. Presidential
Special Lecture. 2010 Neuroscience
Meeting Planner. San Diego, CA: Society for
Neuroscience. Online. (2010).
24. P. S. Lagali, et al., Nature Neuroscience. 11,
667 – 675 (2008).
25. S. Thyagarajan et al., The Journal of
Neuroscience, 30(26): 8745-8758 (2010).
1. Anonymous. “Optogenetics and mouse (with
music)” 25 May, 2010. YouTube. Accessed
Dec 5, 2010. http://www.youtube.com/
watch?v=obJjXRyDcYE (2010).
2. E. S. Boyden, F. Zhang, E. Bamberg, E.
Nagel, L. Deisseroth, Nature Neuroscience. 8,
1263-8 (2005).
3. J. Lin, Program No. 314.4. 2010
Neuroscience Meeting Planner. San Diego, CA:
Society for Neuroscience, 2010. Online. (2010).
Dartmouth Undergraduate Journal of Science