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Optogenetic control tools clearly made their breakthrough in neuroscience with manipulations at the level of cell populations while observing the consequences at the systems and behavioral levels (Carter and de Lecea, 2011). However, it is also clear that a detailed mechanistic analysis and understanding of brain function will require simultaneous observation and/or manipulation of various neuronal types at the same cellular or circuit level. This can be partially implemented by using optogenetics in conjunction with existing techniques like electrical recordings. But we believe that this methodological challenge will be eventually more perfectly met by combining optogenetic tools within the same experiment, an important step which will unleash the full power of optogenetics.
See it, block it, move it
To understand and demonstrate how a biological phenomenon works ultimately requires using a canonical scientific methodology often summarized by the formula “see it, block it, move it.” The first step is to identify the conditions for this phenomenon to occur (see it); the second step is trying to find out which of these conditions are necessary using loss-of-function experiments (block it); the third step is to test the sufficiency of one or more conditions through gain-of-function experiments (move it). The first step aims at establishing a correlation, while the two others aim at demonstrating causation. Correlation in neuroscience has been investigated in particular using invasive electrical recordings in order to match neuronal activity with behavior. Although such recordings can provide hints on possible causal relationships (e.g., when identified electrical events precede or follow behavioral events), causation is traditionally approached using genetic (KOs and overexpression), electrical (stimulations), surgical (lesions), or pharmacological (agonists and antagonists) interventions. None of these techniques alone provides both high temporal and spatial (cellular) specificity. Electrical stimulations and recordings of neuronal firing display exquisite microsecond-scale temporal resolution but are usually unable to discriminate between neurochemical cell types. In addition, electrical stimulations do not discriminate between axons and cell bodies, which seriously limits their interpretative value. Conversely, pharmacological interventions are hampered by their poor temporal resolution although they can provide very good neurochemical specificity.
Optogenetics is considered a true technological breakthrough because it makes it possible to implement the “see it, block it, move it” approach with both high temporal resolution and high cellular (even subcellular and molecular) resolution. Thus compared to standards of the past decade, modern optogenetic studies might bring more definitive answers and allow biologists to form stronger interpretations. More remarkably, combining optogenetic tools will offer the possibility of implementing this approach in the same experiment, which will dramatically increase the yield of individual studies.
Multicolor control of neuronal populations
Combining several light-gated actuators in the same experiment requires the ability to recruit one with minimal cross-excitation of the others. Maybe because they were isolated from organisms living in very different ecosystems, microbial opsins display a great diversity of spectral sensitivities. A few of them can be excited almost separately using different wavelengths. The best example so far is the association of ChR2 and NpHR which allows bidirectional control of firing of the same cells using blue- and yellow light (Zhang et al., 2007) opening the possibility of performing loss-of-function and gain-of-function experiments (block it and move it) on the same preparation.
Other “optically compatible” opsin pairs include the blue- and yellow light-gated channelrhodopsin variants ChR2 and VChR1 (Zhang et al., 2008) and the blue- and red-light drivable ion pumps Mac and NpHR (Chow et al., 2010). In theory, these tools allow multicolor control of separate populations of neurons simultaneously. A new generation of red-shifted actuators includes novel channelrhodopsins such as MChR1 from M. viride (Govorunova et al., 2011) and C1V1s, a family of ChR1/VChR1 chimera displaying large photocurrents and minimal cross-activation with ChR2 (Yizhar et al., 2011a,b,c) as well as new lightdriven pumps such as Halo57, a naturally occurring halorhodopsin displaying larger photocurrents than NpHR when excited in the far red (Klapoetke et al., 2010). These new opsins are expanding the catalog of compatible actuators for multicolor control of neural circuits. Optogenetic control tools can also be combined physically as a unique protein. Recently a tandem gene fusion strategy was proposed for co-localized and stoichiometric expression of opsin pairs (Kleinlogel et al., 2011). This approach has a number of potential applications. Precise bidirectional control of firing with low cell-to-cell variability of the excitation-to-inhibition ratios can be achieved by fusing a ChR variant and a light-driven pump. This strategy is also a useful way of creating new tools with new properties: for example,ChRvariants with different excitation spectra can be combined to create a hybrid tool with a wider action spectrum.
Multicolor probing of neuronal activity
Contrary to microbial opsins, most genetically encoded reporters were not isolated from ecologically diverse species but were engineered based on a very limited number of FPs (GFP or YFP for single FP sensors and CFP and YFP for FRET sensors). However, the color palette of available FP variants has been continuously expanding for the past 10 years, and available FPs now span almost the entire visible spectrum (Chudakov et al., 2010; Day and Davidson, 2009). This opens the door for a new generation of genetically encoded probes with diversified and minimally overlapping spectral characteristics. These novel tools will be used to visualize the activity of distinct neuronal populations in parallel or to image multiple parameters in the same cells.
FRET sensors were the first category of optical reporters to be spectrally diversified. Indeed, grafting a new pair of FPs in an existing FRET sensor scaffold is relatively straightforward since it does not require major modifications of the FPs. In contrast, updating single FP sensors can require more work since they often incorporatemodified versions of the FP (e.g., circularly permutated FPs). New blue- and red-shifted spectral variants were already produced for several FRET sensors including the voltage sensors VSFP2s (Akemann et al., 2010), sensors of cyclic nucleotides (Niino et al., 2009), reporters of enzymatic activities (Ai et al., 2008; Grant et al., 2008; Ouyang et al., 2010), or protein translocation (Piljic and Schultz, 2008). Some of these variantswere used to demonstrate the feasibility of double and triple FRET measurements (Ai et al., 2008; Grant et al., 2008; Niino et al., 2009; Ouyang et al., 2010; Piljic and Schultz, 2008).
FRET sensors have the advantage of enabling ratiometric measurements but the inconvenience of using two FPs (one donor and one acceptor). For this reason, combining more than two or three spectrally nonoverlapping FRET sensors is very challenging. A smart workaround is to free up one color channel by using a nonfluorescent (dark) acceptor which acts as a dynamic quencher for the donor fluorescence (Ganesan et al., 2006; Niino et al., 2010). Still, single FP sensors provide a simpler andmore flexible solution to the problemof spectral crossover. Single FP sensors are still almost exclusively based on GFP or YFP variants except for the blue-shifted kinase activity sensor Cyan Sinphos (Kawai et al., 2004) and the red-shifted monochromatic voltage sensors VSFP3s (Perron et al., 2009). However, the attractiveness of multicolor imaging should promote the construction of additional spectral variants of single FP sensors in the near future. Recent efforts have focused on mutating the calcium indicator scaffold introduced as GCaMP (Nakai et al., 2001) to obtain hue-shifted variants. Using a “molecular evolution strategy” (iterative rounds of mutagenesis and screening of bacterial colonies), Zhao et al. (2011) have engineered a new set of GCaMP mutants called GECOs, comprising blue and red variants. Another initiative which will accelerate the development of new calcium sensors is the GECI project from the HHMI Janelia Farm research campus (http://www.janelia.org/team-project/geci). This project uses a highthroughput, mammalian neuron-based imaging platform to screen through libraries of variants. Current lead variants include blue, cyan, and yellow versions of the GCaMP scaffold (BCaMP, CyCaMP, and YCaMP) as well as a red version (RCaMP) which was engineered from scratch using the red FP mRuby (Loren L. Looger, personal communication).
Combined optogenetic monitoring and control of neuronal activity
The next big step remains the association of optical reporters and control tools within the same experiment to allow all-optical interrogation of neural circuits. To date, only one study has employed this type of strategy: the work by the team of Sharad Ramanathan described how ChR2 and GCaMP can be combined to map functional connections between groups of neurons in C. elegans (Guo et al., 2009). Because ChR2 and GCaMP have highly overlapping excitation spectra, the authors had to separate the excitation channels of the two proteins both temporally and spatially. Similar experiments should be greatly simplified by the use of red-shifted activity reporters such as RCaMP and VSFP3s (Perron et al., 2009) or alternatively by the combination of red-shifted opsins with blue-shifted reporters.
Given the current rate of expansion of the optogenetic toolkit, the number of possible tool combinations might soon become overwhelming, giving unprecedented latitude for the experimenter’s imagination. Most important, the analytical power of “all-optogenetic” approaches is potentially mind-blowing: combining monitoring and control will allow researchers to establish correlation and causation in the same experiment. This should increase the yield of individual experiments and raise the standards in many fields of neurobiological research.