Genetically Encoded Fluorescent Biosensors for Biomedical Applications
Abstract
:1. Introduction
2. General Characteristics of Genetically Encoded Fluorescent Biosensors
3. Key Parameters in Biosensor Design
- (1)
- Ease of use. One of the critical factors when choosing a biosensor is the availa-bility of the equipment needed for the measurements. For example, ratiometric biosensors based on FRET require sophisticated microscopic equipment to quickly (or simultaneously) collect data from two or more fluorescence channels. At the same time, for biosensors that measure fluorescence intensity, uninvolved instruments are needed to collect data. It is also necessary to consider the availability of the materials used. Finally, many luminescent biosensors require an additional step of adding a substrate such as coelenterazine.
- (2)
- Sensitivity of a biosensor is the dynamic range, which is the ratio between the minimum and maximum values that the biosensor can detect. The sensitivity of the biosensor used is application-specific. For example, to measure constant concentrations of a molecule or ion, it is recommended to choose a sensor with a dissociation constant equal to or close to the expected concentration. An even more rigorous approach is to measure the concentration at rest using several biosensors, each of which has a slightly different dissociation constant value. If the goal is to measure a change in concentration or activity when the signal is expected to be weak, then the biosensor with the highest dynamic range and dissociation constant value, at which the concentration change will be within 5 dissociation constant, will be most sensitive.
- (3)
- The detection limit of a sensor is defined often by the range in which the binding isotherm has near-linear characteristics, that is, between 10% and 90% saturation; often two orders of magnitude for a FRET sensor with a Hill coefficient of 1. Due to the dramatic intensity changes caused by ligand binding in fluorescent sensors, the dynamic range can be extended beyond the linear range. Signal-to-background ratio depends not only on sensor properties, but importantly on the background fluorescence in the specimen under investigation. Autofluorescence can differ substantially. Handling, stress conditions can trigger production of fluorigenic compounds.
- (4)
- Selectivity and specificity are two important features to consider when developing or using existing biosensors. Selectivity and specificity are determined by the structure and conformational flexibility of a protein. The terms are often used interchangeably, but are best used for different aspects: specificity is defined as how restrictive a protein is in its choice of substrate (fewer vs. more substrates). Selectivity is defined by substrate properties and is a quantitative measure of the rate constants for interaction of the protein with the substrate [15]. As Peracchi put it elegantly [16]: “Substrate specificity cannot be absolute and is inherently limited. … discrimination between alternative substrates can be relatively low, … Substrate promiscuity helps to fuel an ‘underground’ network of reactions which may represent a basis for further evolution and diversification of metabolism”. Notably, binding protein selectivity is tested with only few analytes, while the in vivo environment presents a highly complex set of molecules. Rarely, binding protein affinity is suitable for in vivo analyses. Affinity has to be adjusted by mutagenesis and affinity series of the sensors might be required. Mutations in the binding pocket may impact ligand selectivity.
- (5)
- Cytotoxicity and biostability. From first principles, one could argue that the higher the sensor level is, the brighter the signal and the better the ability to discern changes in analyte levels or activity. Strong promoters provide high levels, yet besides likely triggering gene silencing, high sensor levels impact physiology. While sensors are minimally invasive, they can affect cellular functions, either by acting as scavengers or by interacting with other cellular components; essentially posing an “Observer Effect” problem. In the absence of novel, even less invasive technologies, it will be important perform proper controls. Biostability of the biosensor is a very important characteristic especially for biosensors used for continuous monitoring. This feature determines the ability of the biosensor device to resist change in its performance over a period of time in response to interruptions arising from external factors.
4. Biomedical Applications
4.1. Cancer
4.1.1. Protein Kinase Activity
4.1.2. pH Level
4.1.3. Other
4.2. Neurological Disorders
4.2.1. Measurements of Lactate Level
4.2.2. pH Level
4.2.3. Other
4.3. Inflammation
4.4. Other Diseases
5. Advantages, Challenges, and Prospects for the Use of Genetically Encoded Fluorescent Biosensors in Biomedical Research
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Kinase | Name | Type of Sensors | Proteins | Reference |
---|---|---|---|---|
Protein kinase A | AKAR | FRET | ECFP/YFP | [20] |
AKAR2 | FRET | ECFP/Citrine | [24] | |
AKAR3 | FRET | YPet | [25] | |
Rluc-PCA | Bioluminescence | Renilla luciferase | [26] | |
FLIM-AKAR | FLIM–FRET | meGFPΔ/cpsREACH | [27] | |
ExRai-AKAR | Ratiometric | EGFP | [28] | |
BimAKAR | FRET | YPet | [21] | |
Protein kinase A/Extracellular signal-regulated kinase | ERK/PKA biosensors | FLIM–FRET | sREAChet/EGFP | [29] |
Protein kinase B | AktAR | FRET | CFP/Venus | [30] |
Protein kinase C | BimCKAR | Bioluminescence | Renilla luciferase | [21] |
CKAR | FRET | CFP/YFP | [31] | |
Protein tyrosine kinases Src, Abl | Src/Abl indicator | FRET | CFP/YFP | [32] |
Protein tyrosine kinase Src | Src reporterr | FRET | CFP/YFP | [33] |
BCR-ABL kinase | Pickles | FRET | CFP/Venus | [34] |
Serine/threonine protein kinase | TORCAR | FRET | Cerulean/YPet | [35] |
LATS kinase | LATS-BS | Bioluminescence | Photinus Pyralis luciferase | [36] |
P38 MAP kinase | PerKy-38 | FRET | YPet/CFP | [37] |
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Ovechkina, V.S.; Zakian, S.M.; Medvedev, S.P.; Valetdinova, K.R. Genetically Encoded Fluorescent Biosensors for Biomedical Applications. Biomedicines 2021, 9, 1528. https://doi.org/10.3390/biomedicines9111528
Ovechkina VS, Zakian SM, Medvedev SP, Valetdinova KR. Genetically Encoded Fluorescent Biosensors for Biomedical Applications. Biomedicines. 2021; 9(11):1528. https://doi.org/10.3390/biomedicines9111528
Chicago/Turabian StyleOvechkina, Vera S., Suren M. Zakian, Sergey P. Medvedev, and Kamila R. Valetdinova. 2021. "Genetically Encoded Fluorescent Biosensors for Biomedical Applications" Biomedicines 9, no. 11: 1528. https://doi.org/10.3390/biomedicines9111528
APA StyleOvechkina, V. S., Zakian, S. M., Medvedev, S. P., & Valetdinova, K. R. (2021). Genetically Encoded Fluorescent Biosensors for Biomedical Applications. Biomedicines, 9(11), 1528. https://doi.org/10.3390/biomedicines9111528