Fluorescent biosensors of protein function
Introduction
With the expanding list of completely sequenced genomes, scientists in the ‘post-genomic’ era are charged with identifying the function of each gene product and determining how each acts in time and space to orchestrate cellular functions. The primary challenge is to build a map detailing how proteins interact with each other and with other cellular cues, such as signaling molecules or ions. A complete map of such interactions would illuminate crosstalk between signaling cascades to build an integrated network of how proteins function synergistically and antagonistically to control cellular phenotypes. This systems approach is crucial if we as a scientific community are to convert information gleaned from genome sequencing into information that will be useful for treating human disease. While genomics and proteomics approaches provide insight into protein functions and enable quantification of protein levels under different cellular conditions, they are incapable of addressing when and where a protein is active. Yet protein localization and protein function are intricately linked [1]. Moreover, compartmentalized signaling reactions may lead to different cellular phenotypes. Thus, imaging protein activity and the cellular cues that stimulate activity in living cells can provide an important complement to classical genomic and proteomic approaches. The advantage of genetically encoded fluorescent biosensors is that they enable the researcher to study a specific protein or cellular signal within the complex environment of the living cell. This approach preserves the spatial and temporal control of protein function and signaling cascades. Thus, the researcher can assess when and where a protein is active in a cell; as well as identify how a stimulus influences the dynamics of signaling cues, which in turn dictate protein function.
Genetically encoded sensors are generated by translation of a nucleic acid sequence, and are incorporated into cells, tissues, and whole organisms by transfection of plasmid DNA or transgenic technologies. In order to convert protein activity or ligand-binding into an optical response, these sensors are usually comprised of one or more fluorescent proteins. There are a number of key advantages of genetically encoded sensors. (1) They can be easily incorporated into cells, tissues, and even organisms. Once they are loaded, the sensors permit long-term imaging over days or longer (in the case of stable incorporation). (2) The sensors can be explicitly targeted to defined regions in the cell either by attaching signal sequences or by fusing the sensor to a protein that localizes to a specific domain. This feature is critical for monitoring the spatial heterogeneity of the cellular signals and protein activities being interrogated. (3) The concentration of sensor can be regulated if the sensor is put under control of an inducible promoter (such as the Tet-on or Tet-off promoter). This enables variation of the sensor concentration and critical evaluation of the extent to which the sensor perturbs the cellular environment.
This review focuses on recent developments in genetically encoded fluorescent sensors of cellular signals and protein activities, highlighting the insights provided by localized sensors. We comment on approaches for the design and optimization of fluorescent biosensors, as these ultimately are key to creating robust sensors for use in high-throughput assays. We suggest these sensors can be very useful in screening whether a chemical influences the activity of a specific protein, or a signaling pathway, and as such, can be an important complement to genomics and proteomics.
Section snippets
Summary of available sensors
A number of different platforms have been used to generate genetically encoded fluorescent biosensors (Figure 1). These platforms are divided into three classes: sensors in which protein activity or ligand-binding (1) alters fluorescence resonance energy transfer between two fluorescent proteins; (2) modulates the optical properties of a single fluorescent protein; or (3) causes a fluorescent protein reporter to translocate within the cell. Fluorescence resonance energy transfer (FRET) is a
Localized sensors illuminate the spatial heterogeneity of signaling reactions
The location of a protein with respect to other proteins or signals it interacts with has a profound impact on its activity. To use just one example, Protein kinase A (PKA) is notorious for being partitioned into different cellular subdomains as a result of binding to A Kinase anchoring proteins [5]. Zhang et al. [6] showed that in adipocytes chronically high insulin levels inhibited β-adrenergic activation of PKA and they suggested that this inhibition results from disruption of PKA
Optimizing FRET-based biosensors for high-throughput screening assays
One of the biggest drawbacks of the ever-expanding family of FRET-based biosensors is the rather limited dynamic range, where the dynamic range is defined as the difference between the minimum and maximum signal. In order to be useful in high-throughput screening assays, the sensors need to exhibit a robust and reproducible signal. This is typically measured as the Z-factor, a statistical parameter that compares the dynamic range to data variation [8]. Increasing the dynamic range of a given
Applications of genetically encoded sensors in high throughput screens
Genetically encoded fluorescent sensors show tremendous promise for conducting live-cell screens in a high throughput fashion. Cell-based assays using genetically encoded sensors have been used to screen for agonists of the cystic fibrosis transmembrane conductance regulator (CTFR) [19], and various forms of capases [20, 21, 22]. Allen et al. [23••] report the first true high throughput screen of a chemical library using genetically encoded sensors, namely sensors for cAMP (ICUE) and PKA
Conclusions and outlook
Genetically encoded biosensors fill an important niche in the post-genomic era as tools to define the spatiotemporal activities of signaling cues in the context of living cells. Important future goals for new biosensor designs should focus on the use of library based screening methods. This will ensure that new sensors will be robust enough to provide the sensitivities and large dynamic ranges required for implementing high-throughput screens. In addition, developing new genetically encoded
Conflict of interest statement
We declare no competing conflicts of interest.
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgements
We would like to acknowledge the Creative Training in Molecular biology Grant (NIH 5 T32 GM07135-33), the Whitehall Foundation, and the University of Colorado for financial support.
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