Several design strategies have been used to engineer genetically-encoded sensors that provide a fluorescence readout for the level of an analyte (small molecule or ion) or the activity of a signaling system (). We refer to this broad class of sensors as genetically-encoded indicators (GEIs), borrowing terminology from genetically-encoded calcium indicators (GECIs). A GEI has two functional units, the sensor domain and the reporter domain. The reporter domain is a single FP or a pair of FPs that provides the fluorescence readout. The sensing domain can be a peptide motif, a full protein, or a combination of the two that senses the target of interest. In practice, the coupling between the sensor and reporter domains influences most of the GEI characteristics, including fluorescence spectra, type of response, and the dynamic range. We discuss different GEI design and sensing parameters in this section.
Figure 1 Design strategies for engineering genetically-encoded indicators. Fluorescent proteins are shown as cylinders. Sensor domains are boxes or spheres in orange or purple. Target ligands are shown in red. Examples are shown for indicators of small molecule (more ...)
Once a target of interest has been identified, the choice and design of the sensor domain is the first consideration for GEI construction. In order to elicit a fluorescence response from the GEI, ligand binding or enzymatic modification must cause a change in molecular conformation. Although some artificial sensing scaffolds have been engineered, these often lack specificity for the intended target (Vinkenborg et al., 2010
). Rather, a highly successful strategy relies on naturally-occurring sensor domains that can be adapted for GEI construction. For example, the Cameleon family of Ca2+
sensors exploits Ca2+
-dependent binding of calmodulin (CaM) and the M13 peptide (Miyawaki et al., 1997
; Romoser et al., 1997
). The physical change induced by Ca2+
is coupled to a perturbation of the reporting domain, that is, the Ca2+
·CaM-M13 binding energy is used to do work to alter the GEI fluorescence.
The choice of the color and the number of FPs for the reporter domain is the next design consideration. We consider reporter domains that consist of either one or two FPs. In single FP GEIs, the physical change in the sensor domain causes a chemical or structural change in the local environment of the FP chromophore, altering its intrinsic fluorescence characteristics. The sensitivity to this structural change can be natural, engineered through point mutations, or engineered by a circular permutation strategy. In dual FP GEIs, the physical change in the sensor domain causes a change in resonance energy transfer between the two FPs. We discuss each of these strategies in greater detail in later sections.
After choosing sensor and reporter domains, engineering the coupling between the domains is the most critical process of GEI development, and coupling must be optimized to obtain desirable GEI characteristics. Structure-guided design can significantly aid the rational development of GEIs (Wang et al., 2008a
; Akerboom et al., 2009
), but empirical discovery remains a substantial component of the process. For example, optimizing the length and composition of the peptide linkers connecting the sensor and reporter domains is often a critical process, but it is also a major hurdle that largely relies on random trial and error. The process of optimizing the coupling between domains can entail screening many libraries of mutants and iteratively improving the sensor’s characteristics. In this development stage several parameters are considered, including the GEI’s affinity for the target, the sensing range, the sensing kinetics, the type of fluorescence response, the dynamic range of the fluorescence response, the specificity of the response, and the perturbations expression of the sensor may cause.
The levels and dynamics of ions, metabolites, and enzymatic substrates are tightly regulated in biological systems, and thus the GEI’s target affinity, sensing range, and sensing kinetics must be well-tuned to respond to physiological changes. The GEI’s apparent affinity for its target (Kapp) describes the point of half-maximal activation or saturation by a target ligand. The sensing range describes the range of target concentrations or activities over which distinct signals can be detected. Both are described by the GEI’s dose-response curve (). The sensing range is dictated by the steepness of the dose-response. For example, a sensor domain with multiple ligand binding sites may exhibit large positive cooperativity and a steep response curve, resulting in a narrow sensing range. This type of sensing may be useful for a binary readout or an “on-off” sensor, but it is not ideal for monitoring graded responses. Related to the affinity, the sensing kinetics are determined by the on and off rates of the target, the rate of the conformational change of the sensor domain, and the rate of coupling between the sensor and reporter domains. Ideally, the Kapp and sensing range will match the physiological midpoint and target level range, and the response time will be faster than the kinetics of endogenous signaling.
Figure 2 A hypothetical GEI dose-response curve. The physiologically relevant dynamic range (FHigh/FLow) is usually smaller than the GEI’s maximum fluorescence dynamic range (FCeiling/FFloor) because only a portion of the total sensing range is sampled (more ...)
When optically monitoring GEIs, the fluorescence response can be either a simple intensity change or a ratiometric change that affects the relative intensity at different wavelengths. Intensity-based measurements use a single excitation wavelength and monitor fluorescence changes at a single emission wavelength. However, the fluorescence intensity also depends on the concentration of the fluorophore, and comparison of absolute intensity changes is usually not possible because of cell-to-cell and experiment-to-experiment variability in GEI expression levels. Instead, intensity measurements generally are used to monitor relative changes during an experimental manipulation. Ratiometric measurements eliminate the dependence on fluorophore concentration, enabling direct comparisons between experiments that facilitate quantitative analysis. Ratiometric measurements can either use two excitation wavelengths and monitor a single emission (excitation ratiometric) or use a single excitation and monitor two emission wavelengths (emission ratiometric). For example, an excitation ratiometric GEI exhibits two peaks in its basal fluorescence excitation spectrum. When the GEI senses its target, the excitation spectrum changes in a specific manner: one peak increases, the other peak decreases, and there exists a wavelength that shows no intensity change called the isosbestic point. The ratio of the peak intensities is the readout of the ratiometric GEI.
Regardless of whether it is an intensity or ratiometric change, the dynamic range of the fluorescence response must also be maximized to improve the signal-to-noise and detection of changes. The fluorescence dynamic range describes the maximal detectable change in the fluorescence response. Although the two are functionally related, the dynamic range of the fluorescence response and the sensing range are distinct parameters (). It is important to note that the dynamic range of the fluorescence response may differ substantially between purified protein in solution and protein expressed intracellularly because of environmental factors.
In the process of optimizing the GEI’s characteristics, it is critical to verify the specificity of the response to the target. The sensor domain may have substantial affinity for structurally related analytes or closely-related enzyme activities, or there may be naturally occurring allosteric modulators. Rational mutagenesis and screening in some cases can reduce off-target interference, especially if structure-function studies of the endogenous sensor domain are available to guide mutagenesis. At the very least, a reasonable effort should be made to identify interfering factors so that the proper experimental controls can be conducted when using the GEI. Interference can also result from environmental sensitivity of the FPs, for example to pH, as will be discussed in a later section.
Finally, care must be taken when using naturally-occurring sensing domains because they can interact with and alter endogenous processes, especially if the sensing domain has a natural enzymatic activity. To diminish interference by Cameleon, the CaM and M13 were mutated in parallel to maintain recognition for one another but abrogate recognition by endogenous CaM (Palmer et al., 2006
). Another approach is to choose a sensing domain from a species different from that under study. For example, bacterial periplasmic proteins have been exploited for sensing analytes in mammalian systems to reduce the possibility of biological cross-talk (Okumoto et al., 2008
). A related concern is that the GEI itself can cause pathological buffering of the analyte, interfering with endogenous signaling by changing the free concentration. FPs and GEIs may reach micromolar concentrations when expressed in cells, and analytes whose intracellular concentration is near or less than this may be affected. Some analytes occur at low free concentrations but have a much higher total concentrations due to endogenous buffering, and these analytes may be less affected by sensor expression. However, pathological buffering by the GEI can be a large problem for analytes that occur at low total concentrations.
Clearly, engineering an optimal GEI with respect to all of these parameters is not trivial, but many useful GEIs have been developed that have provided important insight into brain function, despite deficiencies in one or more of their sensing properties. We next describe in greater detail design strategies based on single FP environmental sensitivity, circular permutation of a single FP, resonance energy transfer between two FPs, or translocation of FPs.