development of fret biosensors for mammalian and plant systems

SPECIAL ISSUE: NEW/EMERGING TECHNIQUES IN BIOLOGICAL MICROSCOPY

Development of FRET biosensors for mammalianand plant systems

Danny Hamers & Laura van Voorst Vader &

Jan Willem Borst & Joachim Goedhart

Received: 14 November 2013 /Accepted: 19 November 2013 /Published online: 12 December 2013# Springer-Verlag Wien 2013

Abstract Genetically encoded biosensors are increasinglyused in visualising signalling processes in different organisms.Sensors based on green fluorescent protein technology areproviding a great opportunity for using Förster resonanceenergy transfer (FRET) as a tool that allows for monitoringdynamic processes in living cells. The development of theseFRET biosensors requires careful selection of fluorophores,substrates and recognition domains. In this review, we willdiscuss recent developments, strategies to create and optimiseFRET biosensors and applications of FRET-based biosensorsfor use in the twomajor eukaryotic kingdoms and elaborate ondifferent methods for FRET detection.

Keywords FRET biosensors . Fluorescent protein . Secondmessengers . Plants .Mammalian cells . Biosensor design

AbbreviationsFRET Förster resonance energy transferDNA Deoxyribonucleic acidFP Fluorescent proteinFLIM Fluorescence lifetime imagingcAMP Cyclic adenosine monophosphateAvGFP Aequorea victoria GFPGFP Green fluorescent proteincpGFP Circular permuted green fluorescent protein

BFP Blue fluorescent proteinECFP Enhanced cyan fluorescent proteinEPAC Exchange protein activated by cAMPEYFP Enhanced yellow fluorescent proteinmRFP Monomeric red fluorescent proteinYC3.60 Yellow cameleon version 3.60cp Circular permutationER Endoplasmic reticulumGTP Guanosine-5′-triphosphate

Introduction

Cells can be seen as systems in which biochemical events takeplace in response to inter- and intracellular changes. Theseresponses are relayed through signal-transduction cascades in-volving a number of components such as receptors, ligands,kinases, phosphatases and secondary messengers, which subse-quently result in downstream responses thereby regulating cel-lular processes. Tight spatiotemporal regulation of these process-es is essential for proper cellular functioning in a system inwhicha large number of regulators may play a role in multiple path-ways, complicating the elucidation of signalling events. Under-standing distinct temporal and spatial biochemical signals pro-vide insight into the fundamental processes that regulate “life.”

Classical biochemical methods are commonly used to ana-lyse the production of second messengers or the occurrence ofprotein–protein interactions. Currently, the application of ad-vanced methods, such as mass spectrometry (Giavalisco et al.2008) and metabolite flux analysis (Giavalisco et al. 2009), areused to reveal protein complex assembly and turnover of bio-molecules or metabolites. However, these methods are limitedin temporal information and hamper in vivo measurements.Complicated lengthy fractionation procedures can providevaluable results, but as a consequence, cellular integrity is

Handling Editor: David Robinson

D. Hamers : J. W. BorstLaboratory of Biochemistry and Microspectroscopy Centre,Wageningen University, Wageningen, The Netherlands

L. van Voorst Vader : J. Goedhart (*)Molecular Cytology, Swammerdam Institute for Life Sciences, vanLeeuwenhoek Centre for Advanced Microscopy, University ofAmsterdam, Amsterdam, The Netherlandse-mail: [email protected]

Protoplasma (2014) 251:333–347DOI 10.1007/s00709-013-0590-z

completely disrupted. Application of biosensor technology al-lows detection of changes in concentration of biomolecules, orreports on their activation state in living cellular systems.Ideally, biosensors should give rapid, sensitive, quantifiableand local responses in vivo, with high signal/noise ratios with-out disturbing the endogenous system that is being monitored.

There are many different types of biosensors that allow formeasuring different kinds of biological processes. The major-ity of these biosensors can be divided into two classes: elec-trochemical or fluorescent sensors, or a combination of both.Examples of biosensors reporting on electrochemical changesare used for detecting lactic acid (Haccoun et al. 2004),phenolic compounds (Tembe et al. 2007) and phytohormones(Mancuso et al. 2005). Fluorescence-based biosensors moni-toring calcium (Miwa et al. 2006b), phytohormones (Brunoudet al. 2012) and carbohydrates (Meyer et al. 2007) are basedon changes of fluorescence properties (see Fig. 2).

The first biochemical biosensor developed for commercialuse was a sensor for measuring glucose levels in blood. Thissensor is based on measuring a current change at the platinumelectrode when electrons from the glucose oxidase cofactorflavin adenine dinucleotide are transferred to oxygen, yieldinghydrogen peroxide (Mang et al. 2005). Despite the fact thatthis system is very sensitive, the main problem with electro-chemical sensors is the lack of spatial information since thesemeasurements occur at a macroscopic scale. Nevertheless, theuse of redox potential sensors might still be useful in plantawhere a majority of the plant hormones are inactivated byoxygenase/dehydrogenase activities, which in theory could bemonitored by measuring electron transfer to an acceptor(Sadanandom and Napier 2010).

Other types of sensors that exhibit high sensitivity areaffinity-based. These sensors make use of antibodies, whichcan be raised against a variety of analytes permitting sensitivehigh affinity recognition. Recently, a new class of affinity-based sensors have been developed which make use ofconformat ion-speci f ic s ingle-domain ant ibodies(nanobodies) (Irannejad et al. 2013) or short stretches ofDNA called aptamers (Sadanandom and Napier 2010). Thesenanobodies are much smaller than a typical antibody, therebyimproving spatial resolution. Application of antibody-basedsystems is predominantly used in fixed tissue and yieldsrelatively low temporal information. Temporal informationcan be obtained but requires the use of time series or time-fractionated samples. It has to be mentioned that these types ofsensors are very suited for diagnostic purposes that do notrequire temporal information, but need high sensitivity. Arelatively new class of biosensors is protein-based and, hence,completely genetically encoded. The sensing domain recog-nises a signal (arising from, e.g., ligand binding, enzymeactivity, posttranslational modification) that is translated in achange in an optical signal, which is provided by proteins thatare fluorescent or luminescent. Here, we focus on genetically

encoded biosensors incorporating fluorescent proteins thatprovide a Förster resonance energy transfer (FRET) basedchange in the optical signal. Combining advanced fluores-cence microscopy techniques such as fluorescence lifetimeimaging microscopy (FRET-FLIM), fluorescence cross-correlation spectroscopy and fluorescence recovery afterphotobleaching with genetically encoded sensors provides atoolbox allowing for real-time in vivo visualisation of cellularprocesses with minor perturbation of the cellular system.

In this review, we will briefly discuss GFP technology,fluorescence and FRET. A detailed overview of several engi-neering strategies to optimise biosensor performance will begiven, and finally, we will discuss the application of biosen-sors in mammalian systems as well as in plants.

GFP technology

The first completely genetically encoded fluorescent probewas isolated from the jellyfish Aequorea victoria and isknown as green fluorescent protein (GFP). The implementa-tion of GFP in biology has been demonstrated to be invaluablefor imaging of intracellular proteins in their natural environ-ment (Tsien 1998). A variety of differently coloured GFPmutants have been developed, e.g. using directed evolution,which have found widespread application as natural, brightlyfluorescent markers in cell biology (Nienhaus 2008).

The crystal structure of GFP was elucidated in 1996, show-ing a barrel-like structure composed of 11 beta-strands. Thechromophore is formed by three amino acids: serine-65,tyrosine-66 and glycine-67, which are part of the alpha helixrunning through the inside of the barrel. The three residues areconverted into a fluorophore by an autocatalytic mechanism ofcyclisation, dehydration and oxidation, a process that is termedmaturation (Chudakov et al. 2010). Some GFP variants, espe-cially red-shifted variants, undergo additional chromophoremodification. The maturation time for most fluorescent proteinsranges fromminutes to hours, but can be days in the case of the“Timer” type of fluorescent proteins (Terskikh et al. 2000;Subach et al. 2009). In general, relatively fast maturation ratesare desired. In addition, the different colour variants provide anopportunity to employ genetically encoded probes for FRET.

Fluorescence principles and FRET

Fluorescence is a process that occurs in certain molecules(poly-aromatic hydrocarbons and/or heterocyclic compounds)that are able to absorb light, thereby raising an electron to anunstable excited state. The excess of energy can be convertedinto a photon, which is emitted during return of the electron tothe ground state. This process is called fluorescence. Thefluorescence principle can be illustrated with the Jablonskienergy diagram (see Fig. 1) (Lakowicz et al. 1999; Valeur andDegli Agosti 2002). Important and measurable parameters in

334 D. Hamers et al.

fluorescence are quantum yield (Q), molar extinction coeffi-cient (ε) and the fluorescence lifetime (τ). The quantum yield isa measure of the fluorescence emission efficiency of thefluorophore and gives the probability of light emission relativeto that of other energy losses. The most commonly used fluo-rescent molecules have quantum yields between 0.2 and 0.9.The molecular extinction coefficient reflects the efficiency withwhich a chromophore absorbs light. It is directly related to thelight absorption cross-section of the chromophore and, conse-quently, to its size. Fluorescence intensity is not a quantitativemeasure without calibration of the experimental setup, but atrue quantitative parameter is fluorescence lifetime. The fluo-rescence lifetime is defined as the average time a fluorophore

resides in the excited state before returning to the ground state.Typical fluorescence lifetimes range from 100 ps to 100 ns,depending on the photophysical properties of the fluorophore.The fluorescence lifetime can be affected by the local environ-ment, by the refractive index (Suhling et al. 2005; Borst et al.2005), by collisional quenching or by FRET (Suhling et al.2005; Bollmann et al. 1998). Fluorescence lifetime measure-ments gain information about these processes and local condi-tions independent of fluorophore concentrations.

Another important property to take into account whenchoosing an appropriate fluorophore is photostability and theassociated photoconversion processes that may occur.Photostability can be described by the amount of excitation/

Fig. 1 Schematic illustration of the Jablonski energy diagram (a). Ab-sorption of a photon results in the transition to the excited state S1 or S2.Vibrational relaxation occurs within each electronic state and internalconversion takes place as a non-radiative process from one electronicstate (e.g. S2) to a lower one (S1). The emission of a photon (at longerwavelength) starts from the lowest vibrational level of S1, shown asfluorescence emission. Energy losses other than fluorescence (kem) indi-cate all radiationless decay processes (knr). In addition, excitation energycan be transferred from a donor fluorophore to an acceptor chromophore

through nonradiative dipole–dipole coupling, which is called Försterresonance energy transfer (FRET). b Some prerequisites for FRET arespectral overlap between donor emission and acceptor absorption spectra,distance between donor and acceptor and adequate dipole orientation. cThe transfer rate is proportional to the inverse 6th power of the distanceR ,which makes this method extremely sensitive for distances at proteinlevel dimensions (<0 nm). d Parameters that determine the critical trans-fer distance (R0) is characteristic for each FRET pair and is typicallygiven at 50 % FRET efficiency

FRET biosensors for mammalian and plant systems 335

emission and relaxation “cycles” the fluorophore undergoesbefore it is modified due to processes such as photoconversionor photobleaching. This property is not only determined by theintrinsic fluorophore properties but also by environmental andillumination conditions such as excitationwavelength, presenceof oxygen, light source characteristics, intensity and pulsefrequency of the excitation source (Chudakov et al. 2010).One way to measure this property is by determining thephotobleaching halftime, which is defined as the time necessaryto reduce the emission rate to 50% of the initial emission rate of1,000 photons/s per fluorescent protein (Shcherbo et al. 2009a).

Detection of FRET

Methods such as yeast two-hybrid (Fields and Song 1989) andco-immunoprecipitation (co-IP) (Fiil et al. 2008) are used todetect and validate protein–protein interactions. The maindownside of these methods is that it is difficult or impossibleto investigate the location and timing of the interactions. Theapplication of FRET provides a powerful alternative because itis able to spatially resolve molecular interactions and confor-mations in real time. It is widely used to monitor inter- or intra-molecular protein interactions. In the late 1940s, Theodor För-ster developed the quantitative theory for resonance energytransfer (Förster 1948), which involves the transfer of excitationenergy of a donor fluorophore to an acceptor chromophorethrough nonradiative weak dipole–dipole coupling. The meth-odology enables detection of distances between donor andacceptor molecules on the low nanometer scale.

The occurrence of FRET manifests itself in many ways,and for a comprehensive review, see (Jares-Erijman and Jovin2003). There are a number of different methods that canquantify FRET, of which the most robust method is FRET-FLIM. This method is based on monitoring changes in donorfluorescence lifetimes. Other methods that can be employedare intensity-based methods such as reduction of donor inten-sity, acceptor photobleaching, fluorescence anisotropy, ormonitoring of sensitised acceptor emission upon donor exci-tation. Measuring the ratio of the intensity of sensitised emis-sion over the intensity of the donor emission allows quantifi-cation of biosensor responses. Fluorescence intensity-basedFRET measurements are frequently used methods becausethese can be performed using a wide field microscope, makingit accessible for a broad scientific community for economicalreasons. For quantification, spectral bleed through correctionsare needed due to the overlap between the donor and acceptoremission spectra. In addition, cross-excitation of acceptormolecules upon donor excitation can occur and therefore theoverlapping fractions must be determined in order to calculatecorrect FRET efficiencies (van Rheenen et al. 2004). Further-more, differences in relative donor and acceptor concentra-tions hamper quantitative FRET analysis.

The use of intramolecular FRET biosensors (several de-signs are shown in Fig. 2) avoids concentration issues becausethese sensors contain defined amounts of donor- acceptormolecules, thus allowing for ratiometric analysis. This typeof measurement relies on displaying donor/acceptor emissionratios, ensuring limited acquisition times compared to otherFRET methods and is therefore very useful to study dynamicprocesses in vivo. Even though ratiometric imaging seemsrather straightforward, corrections regarding backgroundlevels, illumination/shading conditions, donor and acceptorconcentration levels, pixel-shift between the fluorescence de-tection channels, spectral bleed through, cross-excitation andphotobleaching should be addressed before drawing any validconclusions (Spiering et al. 2013). Because these conditionsare very much dependent on the setup being used, it is difficultto compare ratios of a specific sensor between different setups.

Occasionally, the biosensor response is quantified bymeasuring the (change in) excited state lifetime. The useof FLIM is very attractive because it allows robust quanti-fication of FRET, which has been demonstrated for anumber of sensors (Klarenbeek et al. 2011; Shcherboet al. 2009b). However, for some biosensors that show alarge ratio-change, e.g. YC3.60, the lifetime contrast canbe limited (Santiago et al. 2013), restricting the use ofFLIM. The performance of biosensors in FLIM should beexamined on a case-by-case basis.

Design considerations

Biosensor design requires several elements to consider such asthe characteristics of recognition elements regarding associa-tion and dissociation constants, interference with endogenousprocesses and stable interaction in possibly changing environ-ments. In case of genetically encoded sensors, the recognitiondomain can consist of a protein (domain) or moiety thatinteracts with a target, for example a ligand or a protein thatchanges its posttranslational modification status. If the specif-ic recognition results in a conformational change orrelocalisation of the domain, it could be used, in theory, as arecognition domain. It is important to realise that the timescaleon which processes take place should fit the experimentalconditions. It is advised that, in an early stage of sensordevelopment, the binding affinity and association/dissociation rate of the recognition domain should be estimat-ed or examined, to judge whether they satisfy the intendedapplication (Okumoto et al. 2012).

While FRET-based sensors can be accompanied byover-expression artifacts, they still can be used to monitorendogenous responses, i.e. cAMP levels or phosphoryla-tion states. However, it should be realised that buffering oramplification of the signal may take place (Haugh 2012)thereby dampening or increasing signal transduction. An-other issue is the interaction of the recognition elements


with other targets in the biological system. Using domainsfrom heterologous systems can possibly prevent sensormolecules interacting with native proteins. Another wayto avoid unwanted interactions with endogenous compo-nents is the redesigning of the recognition module (Palmeret al. 2006). Careful checking if the introduced sensor doesnot interfere with the endogenous system is essential andnormal performance of the target process should be tested,for example, using inactive recognition domains or consti-tutive active sensors in native backgrounds.

Spatial and temporal control over biosensor expression

The main advantage of genetically encoded sensors is therelative easy expression in single cells or even in wholeorganisms. Moreover, these sensors can be imaged over long

time periods, i.e. multiple cell generations, allowing for bothspatial and temporal information to be obtained. Anotheradvantage of these sensors is the specific targeting to differentorganelles using signal peptides (see Fig. 3) resulting in highspatial information. Especially in planta, where the majority ofthe cell interior is occupied by vacuoles, makes distinguishingsignals from different organelles without signal cross-contamination difficult. Therefore, the ability to target biosen-sors to these specific membrane enclosed compartments al-lows for better spatial information and may prove essential forbiosensor application in the eukaryotic field (Jones et al.2013a).

The expression of the sensors can be regulated at thegenetic level using cell-specific promoters. One strategy isthe use of an inducible promoter system, thus minimisingpossible perturbation of the native cellular processes

Fig. 2 Genetically encoded (FRET-based) biosensors can be divided intotwo classes: intra- and intermolecular sensors. Intramolecular sensors arecomprised of one molecule consisting of a binding and/or recognitiondomain flanked by two reporter moieties for example CFP and YFP.FRET is used to determine the state of the sensor. Intermolecular probesreport by changes in spectral shift or the appearance of fluorescence (forexample bimolecular fluorescence complementation assay) or FRET.

Intermolecular FRET probes show high signal to noise because the initialFRET signal is very low. However, varying expression levels of the twodomains complicates quantitative analysis. Both intra- and intermolecularsensors can be analysed by monitoring ratiometric changes of fluores-cence intensities of the donor and acceptor or by determining the donorfluorescence lifetime by FLIM


(VanEngelenburg and Palmer 2008). Combining biosensortargeting with regulated expression is a powerful approachto study endogenous processes with minimal perturbation ofthe biological system investigated.

FRET-based biosensor engineering

A FRET-based biosensor generally consists of a sensory/recognition domain and a pair of fluorescent proteins. Thissensory domain can bind to a molecule of interest or it can bemodified (e.g. by enzyme activity) leading to a change inconformation. This conformational change can be detectedby a FRET signal change because FRET is sensitive to boththe distance between and the orientation of the donor–acceptorpair. For simplicity, we assume here that the biosensor canexist in two states, an “on” state with high FRET efficiencyand an “off” state with low FRET efficiency.

To create a FRET-based biosensor, several conditions haveto be met (Okumoto et al. 2012). First, the sensor domain needsto show a response in the physiological range. Secondly, thesensor domain should undergo a conformational change thatleads to an altered FRETsignal. Furthermore, it is desirable thatthe fluorescent signals be insensitive to environmental changessuch as pH, ions, temperature or refractive index.

Over the years, a tremendous effort has been invested inoptimising the performance of FRET-based biosensors, andthere has been a strong focus on improving the contrast. Here,we outline several approaches to improve FRET contrast ofFRET-based biosensors.

Optimisation of fluorescent proteins

The need for different colors allows multi-colour imaging,which has resulted in a wide range of GFP variants. In 1996,the first spectral variants were reported, including blue and cyanfluorescent proteins (Heim and Tsien 1996). These blue-shiftedvariants were used for the development of the first GFP-basedgenetically encoded FRET biosensor. This biosensor consistedof a fusion of BFP with GFP, which was connected by aprotease-sensitive linker. Because a BFP-GFP FRET pair re-quires UV excitation, which can be phototoxic and since BFPphotobleaches rather fast, a red-shifted FRET pair composed ofECFP-EYFP was developed permitting excitation with visiblelight (440 nm). Since then, the CFP-YFP pair is the mostpopular and widely applied combination of fluorescent proteinsfor FRET-based techniques (Griesbeck et al. 2001). Develop-ment of novel CFP-YFP variants has further improved sensortechnology in terms of probe brightness, FRET contrast,photostability and environmental insensitivity.

The first ECFP variant has been widely used eventhough it has a low-quantum yield and exhibits fluores-cence lifetime heterogeneity. Optimisation efforts have re-sulted in the bright variant mTurquoise (Goedhart et al.2010). A structure-guided evolution of mTurquoise result-ed in variant mTurquoise2 with a Q of 0.93 (Goedhart et al.2012). This variant shows a mono-exponential fluorescencedecay, which makes it an excellent donor molecule forFRET-FLIM applications.

Among the different GFP variants, EYFP is notoriously pHsensitive (pKa 6.9–7.1), shows quenching by chloride anions,is poorly expressed at 37 °C and is prone to photobleaching(Griesbeck et al. 2001). Mutation Q69K lowered the pKa to6.1 hence reducing its pH sensitivity. Additional mutationshave resulted in Citrine, which is an YFP variant with a lowpKa (5.7), reduced sensitivity to Cl−, better photostability andexhibits higher expression at 37 °C. Another improved versionof YFP was developed (Venus), containing new mutations,which led to improved folding and maturation rates (Nagaiet al. 2002). Nowadays, both Venus and Citrine are widelyused as acceptor molecules in FRET-based applications. How-ever, the remaining weak point of these two variants is theirpoor photostability compared to EGFP (Chudakov et al. 2010).

Recent attempts to improve green/yellow FPs have resultedin two new variants: Clover (Lam et al. 2012) andmNeonGreen (Shaner et al. 2013). Both variants are blue-shifted relative to YFP and can be used as acceptor moleculesin combination with CFP. mNeonGreen is derived from

Fig. 3 Genetically encoded fluorescent protein based sensors can betargeted to subcellular compartments revealing local substrate levelchanges or enzyme activities. Cytosol (1): untargeted, nucleoplasm withnuclear localisation signal (NLS), or extranuclear cytoplasm (2) withnuclear export signal (NES). ER (3): ER targeting sequence, retain withER retention signal (KDEL). Golgi (4): Golgi retention signal.Mitochon-dria (5): targetingwith mitochondrial signal sequence. PM (6): display onsurface using membrane anchor, for example, platelet-derived growthfactor (PDGF) receptor transmembrane (TM) domain; membrane integralwith sensing domain cytosolic. Apoplasm (7): secrete with export se-quence. Vacuole (8): lumen with vacuolar signal sequence, vacuole withtargeting peptide


lanYFP, which is isolated from Branchiostoma lanceolatum(Shaner et al. 2013). The fluorescence emission peak ofmNeonGreen (517 nm) is between that of EGFP and EYFP.With a quantum yield of 0.80 and a molar extinction coeffi-cient of 116 (mM−1 cm−1) mNeonGreen is the brightest mo-nomeric green/yellow fluorescent protein yet described.Moreover, utilisation of mNeonGreen as a FRET acceptor incombination with mTurquoise showed higher FRET efficien-cies compared to the acceptors Clover and mVenus, due to ahigher extinction coefficient. However, performance of themTurquoise (2)-mNeonGreen pair in biosensors remains tobe investigated.

A disadvantage of the CFP-YFP FRET pair is the occur-rence of recombination events during molecular cloning be-cause these proteins are highly homologous. A solution toavoid this problem is the use of FPs from different origins e.g.instead of ECFP from A. victoria , monomeric teal fluorescentprotein 1 (mTFP) originating from a Clavularia soft coral as adonor (Fritz et al. 2013; Aoki et al. 2012), or to use codondiversification (Mues et al. 2013). Other issues are poorphotostability of the acceptor and excitation/emission of thedonor in a wavelength range where autofluorescence can berelatively high. Shifting FRET pairs towards the red part of thespectrum generally reduces interference from background andincreases the Förster radius (R0). A side by side comparison ofdifferent red-shifted FRET pairs was done with yellow ororange FPs fused to red fluorescent proteins (Goedhart et al.2007), showing that mCherry is the most optimal acceptor forboth yellow and orange fluorescent proteins. A particularlyhigh FRET efficiency was observed for the mKO–mCherrypair, which is also characterised by a high R0 of 6.4 nm.

Other options for FRET pairs have been explored usingOrange fluorescent proteins (OFP) or RFPs as acceptor mol-ecules with GFP as a donor. However, OFPs show poormaturation, rapid photobleaching and photoconversion com-pared to far-red species. In addition, mRFP and mCherry havelow quantum yields (Q ) and show weak sensitised emissionupon donor excitation in FRET imaging experiments. Recent-ly, a novel green-red FRET pair was developed based onClover and mRuby2 (Lam et al. 2012). The main improve-ment of this FRET pair is the acceptor, which has a highextinction coefficient, a large amount of spectral absorptionoverlap with clover emission, high-quantum yield, fast matu-ration and high photostability. Due to the improved quantumyield the amount of sensitised emission is increased, which isnecessary to detect FRET changes by ratiometric methods.Good performance of Clover-mRuby2 has been demonstratedfor several FRET-based biosensors, which were used to mea-sure kinase activity, GTP binding and transmembrane voltage(Lam et al. 2012). Whether this can be extended to otherFRET-based biosensors remains to be demonstrated. Anotherapproach to improve sensitised emission is the use of doubleacceptors (van der Krogt et al. 2008).

The development of brighter probes that show improvedfolding and reduced environmental sensitivity is an importantstep in the improvement of FRET-based biosensors for study-ing spatiotemporal cell dynamics (Okumoto et al. 2012).There are several examples demonstrating that exchangingfluorescent proteins in existing biosensors by enhanced vari-ants leads to improved spectral properties (Klarenbeek et al.2011; Adjobo-Hermans et al. 2011; Lam et al. 2012). Besidesoptimisation of spectral characteristics, also other features ofthe probes can bemodified, such as dimerisation tendency andmutual orientation. These issues will be discussed below.

Dimerisation between fluorescent proteins

Native A. victoria GFP (AvGFP) exists as an antiparalleldimer, which effectively increases FRET from the lumines-cent aequorin donor. AvGFP dimerisation is relatively weak,but fluorescent proteins derived from corals usually showstrong di- or tetramerisation (Baird et al. 2000). While themultimerisation tendency is a nuisance for proteinlocalisation, it has been shown that (weak) dimerisation canbe beneficial for FRET sensor applications. Dimerisation be-tween the donor and acceptor will decrease their distance andtherefore increases the FRET efficiency of the high-FRETstate, which can greatly increase the contrast between the“on” and “off” states (Nguyen and Daugherty 2005).

In a screen for improving FRET between ECFP and EYFP,several mutations were identified, which are located at theoutside of the beta-barrel, near the dimerisation interface.These mutations probably increase the dimerisation tendencyand by employing these mutations, i.e. substituting the hydro-philic serine at 208 by the more hydrophobic phenylalanine,the FRET efficiency was increased between ECFP and EYFP(Vinkenborg et al. 2007). Mutation V224L further enhancedthe energy transfer efficiency in combination with the S208Fmutation, probably because these two proteins become slight-ly reoriented. In this study, increasing the dimerisation ten-dency substantially increased the FRET contrast in a FRET-based biosensor for zinc (Vinkenborg et al. 2007).

However, too strong a dimerisation can be detrimental(Kotera et al. 2010). Several biosensors (with the acronymsCameleon, TN-XL and ATeam) and their variants have beenanalysed using fluorescence spectroscopy. Various FPmutantshave been incorporated in these biosensors to change FPdimerisation properties. The results showed that weaklydimerising FPs gave the highest FRET contrast. Weakdimerisation increased interaction between donor and accep-tor in the “on” state, without interaction in the “off” state.However, the dimer enhancing mutations S208F and V224Lreduced the dynamic range of the indicators by increasing thebasal FRET efficiency, possibly by increased intermoleculardimerisation. It can be concluded that dimerisation can bebeneficial, but the extent of it should be carefully tuned. Only


a limited number of mutations that either prevent (A206K,L221R, and F223R) or stimulate dimerisation (S208F and206A) between AvGFP variants have been identified. There-fore, additional mutagenesis of the dimer interface can beperformed to identify novel mutations that influence thedimerisation efficiency and thereby allowing tuning of theFRET contrast. Furthermore, engineering reversibledimerisation for FRET pairs that do not consist of two AvGFPvariants (e.g. mTurquoise2-mNeonGreen or Clover-mRuby2), is possibly a fruitful strategy to improve the con-trast of biosensors.

Serrano and co-workers (Grunberg et al. 2013) used anoth-er strategy to increase the detection of FRET by adding a weakinteraction domain between the two FPs. The added affinityeffectively increased the formation of the donor–acceptorcomplex and will most likely be less sensitive to competitionby endogenous proteins. Although this strategy has beenshown to improve the contrast of a FRET sensor for caspaseactivities, it remains to be examined if it can be applied toother FRET-based biosensors.

Circular-permutated proteins

Most biosensors have CFP and YFP variants as a FRET pair,but show a poor dynamic range, which can hamper detectionof subtle but important signals. By changing the relativeorientation between donor and acceptor dipoles toward themost favorable position, the dynamic range of the biosensorcan be increased. This effect was shown for the Ca2+ indicatoryellow cameleon (YC) (Nagai et al. 2004). The relative ori-entation of the two FPs was altered by attaching the YFPacceptor at a new N-terminus and was created by circularpermutation (cp). In circular permutation, the existing C-and N-termini are fused by a short peptide sequence and novelC- and N-termini are created in the loops that connect the betasheets. Circular permutated YFPs show good maturation andacid stability. One of the circularly permutated variants, with anew terminus at residue 173 (cp173Venus) of the YC sensorsshowed a tremendously improved FRETcontrast compared tothe original Venus. This variant (YC3.60) showed an in-creased FRET efficiency in the “on” state and both in cellcultures and in live mice this biosensor allows better spatialand temporal resolution. From these findings, it can be arguedthat FRET efficiency is highly dependent on the relativeorientation as well as on the distance between the two FPs.

Subsequent studies have identified surprisingly often thatthe permutated variant cp173Venus or cp174Citrine is themost optimal acceptor (van der Krogt et al. 2008). In orderfor FPs to dimerise, the two beta-barrels have to be in anantiparallel orientation, explaining why cpFPs show increasedFRET efficiencies: the circular permutated acceptor has thefavorable antiparallel orientation relative to the donor, provid-ing the best orientation for dimerisation, rather than putting

the donor and acceptor dipole moments in a favorableorientation.

Recently, Pertz and co-workers (Fritz et al. 2013) generateda library of donor–acceptor pairs containing both circularpermutated donors and acceptors. It is proposed to be aconstruction toolkit, which should enable rapid generation ofsensitive biosensors. Another way to change the relative ori-entation of the fluorescent proteins is to alter linkers thatinterconnect the different modules.

Engineering of linkers

Alteration of linker properties such as length or flexibility canalso change the FRET efficiency by increasing the distanceand/or relative orientation between donor and acceptor mole-cules. This in turn allows for changing the ratio between the“on” and “off” state of the FRET biosensor. The linker canhave effect on the FRET performance as a longer linker canincrease the distance between the donor and acceptor. A rigidlinker, however, can fix a particular favorable orientation thatmay produce especially high or low FRET-efficiencies.

A clear example of the effect of linker lengths on the FRETefficiency is provided in a study in which the linker betweenECFP and Venus was systematically truncated. There was nostrict correlation between linker length and FRET efficiency,probably because the orientation between donor and acceptorchanges if the linker is altered. The most efficient FRET wasobserved upon deleting the C-terminus of the CFP and the N-terminus of YFP by respectively 11 and 5 amino acids andfusing these termini using a leucine-glutamate dipeptideforming CY11.5. Fully folded CY11.5 resulted in an incred-ible FRET efficiency of 98 % (Shimozono et al. 2006).

To test the effect of linker lengths on the efficiency ofvarious biosensors an approach was developed to analyseFRET-biosensors in a simple manner (Piljic et al. 2011). Thisapproach includes a set of up to 36 vectors coding for a varietyof FPs and different linker lengths permitting unrestrictedexchange between all construct components. The FPs usedin these sensors are mECFP, mTurquoise, mTurquoiseDEL,Venus, cp49Venus, cp157Venus, cp173Venus andcp229Venus. The various constructed vectors were appliedto two calmodulin-binding proteins: death-associated proteinkinase 1 (DAPK1) and a calcium/calmodulin dependent pro-tein kinase II (Camk2a) and their efficiencies were tested invarious biological situations. In another study, linkers weresystematically altered to generate a FRETsensor for glutamate(Hires et al. 2008). Only one out of 176 constructs was farbetter than all others (44 % ratio change with a Kd of 2.5 μM,if the sensor was expressed at the extracellular surface ofneurons), though there was a general improvement in sensorresponse, if the linker was truncated. This finding suggeststhat the orientation of FPs is very important, next to thedistance between donor and acceptor molecules.


To reduce basal FRET levels, the so-called low-FRET or“off” state, a very long flexible linker can be exploited. To thisend, a backbone (Eevee) was designed to generate a predom-inantly “distance-dependent” FRETsensor and thereby reduc-ing “orientation-dependency” (Komatsu et al. 2011). For a“distance-dependent” FRET sensor various flexible linkersranging from 52 to 244 amino acids were tested. The optimallinker length with reduced basal FRET signals consists of 116amino acids and has been shown to improve the contrast ofseveral sensors (Komatsu et al. 2011).

In conclusion, there are two effective ways to alter FRET-efficiencies of FRET-based biosensors by tweaking thelinkers. Firstly, introduction of a long flexible linker createsa predominantly “distance-dependent” FRET sensor. Second-ly, introduction of a short (rigid) linker that fixes the fluores-cent pairs in the most effective orientation generates an opti-mal “orientation-dependent” FRET biosensor.

Recommendations

After the first report on FRET-based biosensors for calcium in1997 (Miyawaki et al. 1997), an incredible effort has been putinto optimisation, which ultimately has resulted in a high-contrast sensor for studying calcium levels in whole organ-isms. Although this is a major achievement, it is clear thatdeveloping high-contrast biosensors is rather labour intensive,and unfortunately, there is no foolproof tactic to accomplishhigh-contrast FRET sensors. However, some guidelines canbe followed. First, the FRET biosensor should be composedof two bright fluorophores (e.g. Turquoise2 or mTFP andVenus or Citrine) fused through a sensory domain. Next, tryto identify point mutations that push the sensor in the “on”- or“off” state. If a FRETsensor displays a response, meaning thatthe sensor toggles between the two states, several additionaloptimisation methods can be employed. The FPs used can beexchanged for circular permutated variants using the availabletoolkits (Piljic et al. 2011; Fritz et al. 2013). In addition linkertruncations can be considered. In general, sensor developmentwill benefit from medium/high-throughput cloning proce-dures and rapid fluorescence-based screening (Hires et al.2008; Piljic et al. 2011) and analysis (Stein et al. 2013) ofeither purified proteins or proteins expressed in living cells.

While screening is readily achieved in mammalian cellcultures, it is rather impractical for plant cells because ofmorphological differences between plant and animal systems.Because the available transformation methods in plants re-quire more time compared to mammalian systems, screeningof possible candidates is slow. It is however possible to screenfor desired biosensor activity in transient systems such asAgrobacterium , gene gun mediated transformed Nicotianabenthamiana leaves or transfected plant protoplasts. The mainproblem using these expression systems is that adequate con-trols have to be taken into account to ensure that the sensor

output reflects native process responses. Nevertheless, heter-ologous systems are predominantly used to screen for betterbiosensor variants.

Signalling in mammalian and plant cells imaged usingfluorescent biosensors

Second messengers, kinases and GTPases are molecular com-ponents of many signal transduction cascades that can conveysignals from receptors to cellular targets both in plant andmammalian cells. The use of biosensors has greatly aided toimprove our understanding of signalling processes in thesetwo kingdoms indicated by the numerous applications ofFRET-biosensor systems.

Calcium

Calcium (Ca2+) is a very important ion for maintaining thephysiological and biochemical balance in organisms and isone of the most widespread second messengers. Calciumfluxes are tightly regulated using subcellular storage compart-ments such as mitochondria and the endoplasmic reticulum(ER). Spatial control of the Ca2+ concentration as well astemporal Ca2+ signalling allows regulation of different pro-cesses with one common messenger. In the past, syntheticCa2+-chelating indicator dyes have been used to monitorintracellular Ca2+ concentrations, which have provided greatinsight in various signalling pathways. Application of genet-ically encoded calcium biosensors (cameleon) allows study-ing dynamic calcium fluxes providing a detailed picture ofsignalling events in vivo (Roderick and Bootman 2006).

Cameleons typically consists of the calcium-binding sub-unit calmodulin (CaM) domain and a myosin light chainkinase fragment (M13) flanked by two different FP variants.Upon binding of calcium to calmodulin, it wraps around theM13 helix resulting in a conformational change and increasedFRET signal. Several cameleons are available, with varyingcontrasts and affinities (Hess et al. 2007). Tuning of theaffinity is very important since calcium levels can vary severalorders of magnitude between different subcellular compart-ments. Taking full advantage of targeting the sensor andtweaking the affinity, several research groups have revealedwith unprecedented detail calcium signalling at different sub-cellular regions (Lin et al. 2013; Geldner et al. 2007).

The calcium sensor (YC3.60), which displays the largestdynamic range in mammalian cells, has also been used inplant applications by Gilroy and coworkers (Monshausenet al. 2009). Up to now the involvement of calcium in plantshas been demonstrated for various processes such as theformation of pollen tubes and polar growth. Expression ofthe YC3.60 in pollen tubes revealed that calcium oscillationsbetween 100 and 500 μM are essential for pollen tube growth.


Application of the ER type Ca2+ ATPase inhibitorcyclopiazonic acid inhibited growth and showed clear de-creased levels of calcium in the ER (Wilmes et al. 2012).

Spatiotemporal regulation of calcium is very important forpolar growth; in particular, calcium oscillations are essentialfor transcriptional regulation. Ca2+ responsive promoter ele-ments and protein phosphorylation results in a tip-focusedcalcium gradient and redirecting of cytoskeletal and secretoryelements to the tip, facilitating polar tip growth (Betzig2005a).

Calcium is also involved in stomatal closing in leaves(Allen et al. 2000). Abolished calcium fluctuations were ob-served using the biosensor YC2.1 in the V-ATPase (det3)mutant upon external application of non-oscillatory calciumflux or oxidative stress. External introduction of calciumoscillations led to a reduction in stomatal closure, indicatingthat specific calcium oscillations are essential.

Subcellular-targeted YC3.60 was also used to investigatedistinct temporal responses of calcium in the plasma mem-brane, cytoplasm and nucleus upon exogenous application ofATP inArabidopsis roots (Krebs et al. 2012). Nuclear calciumoscillations could be observed after 15 min in epidermal rootcells upon exogenous application of 100 μM calcium. Similarresults were found after application of 1 mM calcium onArabidopsis seedlings expressing a plasma membranetargeted YC3.60.

Calcium plays an important role in Nodulation (Nod) factorsignalling during Rhizobium–legume symbiosis. Nod factorshave been found to induce rapid calcium fluxes using acalcium biosensor and subsequent gene expression. Mutationsand inhibitors that interfere with calcium spiking resulted inabolished Nod factor induced gene expression indicting theinvolvement of temporal Ca2+ fluxes in Nod factor inducedgene expression (Kosuta et al. 2008; Miwa et al. 2006a).

Cyclic-AMP

Cyclic AMP (cAMP) is a second messenger that is producedby adenylate cyclases and transduces extracellular messagesfrom hormones like glucagon and adrenaline into the cell bythe activation of protein kinase A (PKA). Another target ofcAMP is the exchange protein activated by cAMP (Epac). ThecAMP sensitivity of both PKA and Epac was used to developcAMP FRET sensors.

In 1991, the first biosensor for cAMP was reported (Gaoet al. 2012), which was based on FRET between PKA sub-units labeled with small fluorophores. The availability offluorescent proteins has facilitated the development of severalgenetically encoded FRET-based sensors for monitoringcAMP (Giurumescu et al. 2012; Roh-Johnson et al. 2012),which have revealed details on temporal aspects of cAMPproduction. In addition, it was shown that cAMP/PKA activitycan be compartmentalised. Over the last few years, the cellular

significance of cAMP has become more clear using eitherEpac or PKA based biosensors (Allen and Zhang 2006;Werthmann et al. 2009).

Kinase activity

A number of different of FRET-based kinase biosensors de-signs exist (Zhou et al. 2012). The most common modulardesign uses a kinase activity reporter (KAR), which is akinase-inducible molecular switch that contains a kinase-specific substrate region and a phospho-amino acid-bindingdomain (PAABD) flanked by a FP pair (Ni et al. 2006). Forexample “C kinase activity reporter” (CKAR) is a FRETbiosensor that reports on the activation of protein kinase C(PKC) in a reversible manner (Violin et al. 2003). CKARconsists of ECFP, the forkhead-associated (FHA2) domainof Rad53p as PAABD, a PKC-specific substrate sequenceand EYFP. Phosphorylation of the PKC substrate allows bind-ing of the FHA2 domain to this phosphorylated substrate,thereby inducing a conformational change resulting in achange of the FRETsignal. Careful strategy should be follow-ed concerning substrate design, as it should be specificallyphosphorylated and subsequently being recognisable by thePAABD. For example, the FHA1 domain typically recognisesphosphorylated threonine if at the +3 position an aspartic acid(D) is located (Aucher et al. 2010). This creates a challenge forprobe design, as the three-dimensional structure of most ki-nases is still unknown. Until now, there are no examplesknown of kinase-based (FRET) biosensors in plants. Howev-er, transferring FRET-based kinase sensor technology fromthe mammalian field towards plant systems might be veryappealing because of the enormous number (>600) of receptorkinases present in plants.

Activity of G-proteins

Guanosine nucleotide-binding proteins, also known as G-proteins, are essential regulators in signalling processes,where they are able to transmit signals from different stimulifrom outside of the cell into inside of the cell. G-proteins cyclebetween an inactive guanosine diphosphate bound state andan active guanosine triphosphate (GTP) bound state. Exam-ples for G-proteins are Ras, Rho and heterotrimeric G-proteins. Several FRET-based sensors have been developedthat measure the nucleotide binding state of a G-protein. Ingeneral, a bindingmoiety or effector protein is used that has anaffinity for the G-protein in the GTP-bound state, which istranslated into increased FRET signal (Ji et al. 2008b, 2012;Wysocki et al. 2011). Application of these biosensors have ledto novel insights into temporal aspects of activation but, moreimportantly, have revealed highly spatially confined activitiesof Ras (Shroff et al. 2008b) and RhoGTPases (Ji et al. 2008b).


Another approach that allows measuring the activation ofheterotrimeric G-proteins is based on subunit dissociation or aconformational change. The activation is measured as a loss ofFRET between the fluorescently labelled subunits after GTPbinding (Shroff et al. 2008a). These sensors do not generallyoperate intramolecularly, but rather use intermolecular FRET.To circumvent some of the problems of intermolecular FRET,a single-plasmid system for producing the labelled subunits ata defined ratio has been developed (Ji et al. 2008a). The use ofFRET sensors for measuring heterotrimeric G-protein activa-tion has provided detailed information on the kinetics activa-tion by G-protein coupled receptors (Manley et al. 2008).

Genetically encoded biosensor design and applicationin planta

Several plant-specific FRET biosensors have been developedto detect plant metabolites and messengers in some detailcompared to the animal field, with glucose and arginine asclear examples. In addition, the use of an entire organism as asensing platform has been demonstrated with the developmentof a zinc sensor in Popular. In the next paragraphs, examplesof FRET biosensors applied in plant systems will bedescribed.

Carbohydrate flux of glucose

The majority of biosensors that respond to varying levels ofcarbohydrates such as glucose or sucrose have been developedfor mammalian systems, but there are also examples describedfor the plant field (Chaudhuri et al. 2008, 2011). These bio-sensors are called “FLIP” sensors and are composed of arecognition element consisting of a bacterial periplasmic-binding protein flanked by CFP and YFP. The sensitivity ofthis sensor is in a similar range to the binding constant of therecognition element used in the sensor. By employing differ-ent sensors with different affinities enables investigatinglevels of carbohydrates over a much wider range. It was evenpossible to screen for mutants affected in sugar metabolism,signalling and transport through the combination of thesemultiple sensors (Chaudhuri et al. 2011). “FLIP” sensors havealso been used to determine steady-state levels of glucose inthe cytosol. It was shown that cytosolic glucose levels in rootsas well as in leaves were below 90 nM (Deuschle et al. 2006).Furthermore, it was determined that the concentration of cy-toplasmic glucose is not under tight homeostatic regulation(Deuschle et al. 2006).

Arginine

Amino acids are the core elements of proteins and are neededfor the synthesis of various metabolites. It is also thought that

amino acids have a role in signalling (Coruzzi and Bush 2001)besides acting as fundamental building blocks. An arginine-sensitive sensor was constructed by combining a periplasmicbacterial protein that undergoes a conformational change uponbinding of arginine (Bogner and Ludewig 2007) with ECFPand Citrine as sensor moieties. This sensor showed an affinityfor arginine of 2 mM in vitro. Utilisation of different sensorvariants in multiplex imaging configurations allows the studyof endogenous arginine fluxes and responses to external stim-uli. Periplasmic bacterial protein variants that recognise otheramino acids as a template can be used to create similar aminoacid sensors in planta.

Zinc

Until now, the majority of biosensor applications just de-scribed were mainly focused to determine and understandcellular processes in animal systems and plants. However,biosensors can also be used as detection units for environmen-tal applications such as soil pollution. An example of such anapplication is the construction of a zinc-sensitive sensor plat-form in Popular. The main advantage of using perennial treespecies such as Poplar (Populus trichocarpa ) is that they growrelatively fast, grow in wide range of environments and canact as a large sink source (Adams et al. 2012).

A zinc-sensitive sensor was constructed using the zinctransporter gene ZNT1 from Thlaspi caerulescens homologin Populus trichocarpa , which was flanked with DsRed andECFP as a reporter platform. Unfortunately, Adams et al.(2012) found that using popular as a host organism has certaindrawbacks regarding the imaging of the sensor due to in-creased leaf thickness and dimensional structure comparedto the more commonly used host Arabidopsis thaliana . Nev-ertheless, plants as sensing platforms might have interesting,alternative applications and can be adapted for use inphytomediation in order to clean polluted soil (Kramer 2005).

Currently, the selection of genetically encoded biosensorsin plants is rather scarce compared to biosensor applications inmammalian systems. An illustrative example of used sensorsis given by Jones and co-workers (Jones et al. 2013b). Thedevelopment and application of biosensors in plants is laggingbehind when compared to the animal field, but a steadyincrease in the application of biosensors in planta can beobserved.

Future perspectives

FRET-based biosensors offer an ideal toolbox to study dy-namic processes with minimal perturbation and have providednew insights in cellular signalling networks. The use of bio-sensors enables investigating specific outputs in various sub-cellular compartments at high spatial and temporal resolution


in both mammalian and plant systems. Determination of spa-tial and temporal FRET changes by ratiometric imaging ofdonor and sensitised emission is the most widely used ap-proach. However, it should be realised that this method isoften qualitative in terms of FRET efficiency, and results(especially dynamic range) may vary between labs. Effortscan still be made into standardising the output of FRETbiosensors and investigating the deviations that occur betweendifferent FRET analysis methods. A more robust, laboratory-independent, method to quantify FRET is offered by FLIM.

Improving the sensitivity and contrast of existing and novelsensors will remain an active area of research. In this respect,the recent development of approaches allowing medium-throughput analysis and characterisation of sensors will havegreat potential. However, the development of biosensors forplant systems will still remain a challenge because screeningcannot be performed in the cell or tissue of interest. Rapidgeneration of transformed plant cells would therefore be ofgreat help for developing plant specific sensors.

Application of multiple sensors simultaneously can offeradditional information because it allows for precise correlationof temporal profiles of multiple signalling molecules therebyomitting cell-to-cell variations. Recent improvements in mi-croscopy and fluorophore development allow for such multi-plex imaging approaches. Multiplex FRET seems promising,but this method is still in its infancy. Multiplex FRET imagingrequires the use of two or more biosensors that can be sepa-rated based on their spectral properties or location(Shcherbakova et al. 2012; Ai et al. 2008; Piljic and Schultz2008). The main challenge is to be able to detect FRETchanges while dealing with overlapping spectral propertiesof the fluorophores. Therefore, multiplex imaging will benefitfrom the development of novel red-shifted FRET-based sen-sors that can be co-imaged with existing CFP-YFP-basedbiosensors.

The applications of FRET sensors in multicellular organ-isms including vertebrates and plants are still rather limited.Challenges that are faced include imaging through multicel-lular layers, which cause increased scattering and backgroundsignals and movement of the sample due to growth or migra-tion and poor signal/background ratio. Another concern is thecontrast of the FRET biosensor, which usually decreases dueto dilution of the FRETsignals. Nonetheless, several examplesof FRET biosensor applications have been described for mul-ticellular systems (Shroff et al. 2007) including mice (Betziget al. 2006) and plants (Krebs et al. 2012). The integration ofnovel optical techniques that monitor multicellular systems,such as selective plane illumination microscopy (Betzig2005b) with the application of FRET-based biosensors willprovide a way to investigate complex systems.

There are overwhelming numbers of examples in whichFRET-based biosensors have contributed to understanding thespatial and temporal aspects of cellular processes. This notion

should be encouraging to anyone that is interested in studyingcellular processes with FRET-based sensors. Although theapplication of FRET-based sensors is now an establishedtechnology, we anticipate an exciting future with new devel-opments in probe design, improved analysis methods that willincrease our understanding of cellular function.

Acknowledgments We are very grateful to Prof. Dr. A.J.W.G. Visserand A.H.Westphal for critical reading of this manuscript. J.G and L.v.V.Vare supported by NanoNextNL, a micro- and nanotechnology consortiumof the Government of The Netherlands and 130 partners. DH is funded byThe Netherlands Organisation for Scientific Research (NWO) in theframework of Earth and Life Sciences open program.

Conflict of interest The authors declare that they have no conflict ofinterest.

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development of fret biosensors for mammalian and plant systems

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