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From principles to practice: a comprehensive guide to FRET-FLIM in plants

  • Ali Eljebbawi , Anika Dolata , Vivien I. Strotmann , Stefanie Weidtkamp-Peters and Yvonne Stahl ORCID logo EMAIL logo
Published/Copyright: January 30, 2025
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Abstract

Förster Resonance Energy Transfer combined with Fluorescence Lifetime Imaging Microscopy (FRET-FLIM) is revolutionizing plant biology, by enabling the study of protein–protein interactions (PPIs) within live cells. This manuscript describes the principles of FRET and the practical application of FRET acceptor photobleaching (FRET-APB) in exploring PPIs in vivo. It mainly focuses on the superior characteristics of FRET-FLIM and details the materials and methods for implementing this technique in plants. It provides a profound overview about the required instruments, protocols for sample preparation, methods for calibration and acquisition, and pipelines for data analyses including novel analyses for binding and FRET efficiencies. Furthermore, it discusses the potential pitfalls and challenges related to the sample autofluorescence, protein expression heterogeneity, and acquisition photodamage or bleaching. This works aims to highlight the great prospects of FRET-FLIM in advancing our understanding of PPIs in living plant cells.

1 Introduction

1.1 Overview

Proteins are the most abundant biomolecules in cells, playing critical roles in nearly every biological process. Over the years, their structure, localization, and indispensable roles in structural support, enzymatic catalysis, transport and storage, signaling, and defense were vastly explored. Traditionally, protein biochemistry is studied by their extraction, purification, and in vitro characterization via diverse techniques, such as electrophoresis and chromatography. Additionally, other advanced techniques, such as X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy, allow the precise and accurate characterization of protein structures, providing insights into their functions. Later on, protein studies which were performed in simplified in vitro environments expanded to real-time observations within live systems. This breakthrough was made possible by the discovery and use of fluorescent proteins (FPs), such as the green fluorescent protein (GFP) from Aequorea victoria [1], [2]. FP-fusion and FP-based confocal microscopy allow real-time observations of protein localization and dynamics in diverse systems including plants [3]. In fact, plants present unique challenges due to their relatively high autofluorescence, arising from pigments such as chlorophyll and carotenoids in plastids, as well as lignin and other phenolic compounds in cell walls [4]. Nevertheless, advanced microscopes offering enhanced sensitivity, superior signal-to noise ratio, and broad spectral variability enable the detection of weak and often mixed signals, offering more accurate analyses of protein behavior in live plant systems.

Within cells, proteins do not exist as isolated entities, they rather interact and form dynamic interaction networks that regulate intricate biological processes. The discovery of diverse FPs with different excitation and emission spectra enabled tagging and visualizing multiple proteins within the same system, allowing the in vivo study of protein complexes. Yet, the co-localization of proteins does not necessarily indicate their physical interaction, it merely serves as a prerequisite, constrained by the diffraction limit (∼250 nm) inherent to light microscopy. Therefore, further techniques were developed to investigate protein–protein interactions (PPIs) in vivo, such as techniques based on Förster resonance energy transfer (FRET), which enables high precision measurements of PPIs beyond the diffraction limit [5]. In plants, FRET is now commonly used to investigate PPIs, including those among transcription factors, signaling proteins, and membrane transporters [6]. For instance, several studies unravelled the formation of homo- and heterodimers [7], [8], [9], [10], [11], as well as higher order complexes among proteins [12]. Additionally, functional analyses were performed to investigate which protein domains serve as interaction sites [13]. This has been achieved in various plant organelles, such as the plasma membrane [7], [8], Golgi stacks [10], [11], [14], [15], endoplasmic reticulum [9], plasmodesmata [16] and nuclei [13]. In this context, it is worth noting that despite the profound capabilities of super resolution microscopy, it faces several challenges in plants, including complex tissue structure, dynamic growth and movement, sensitivity to photobleaching, cell wall thickness, and high levels of autofluorescence.

1.2 FRET principles

FRET was described by Theodor Förster in 1948 and refers to the non-radiative transfer of energy from an excited donor fluorophore to an acceptor fluorophore [17]. The process begins when a donor fluorophore absorbs a photon, promoting its electrons to a higher energy state. In this excited state, the donor can transfer energy to an acceptor fluorophore through a quantum mechanical process known as dipole-dipole coupling. As the energy is transferred, the donor returns to its ground state, while the acceptor becomes excited and subsequently emits light.

However, FRET occurs only when there is an overlap between the emission spectrum of the donor and the excitation spectrum of the acceptor. Additionally, the two fluorophores should be in a very close vicinity (<10 nm), and their transition dipole moments should ideally be oriented in parallel. Upon FRET, the fluorescence intensity and lifetime of the donor decrease, while the fluorescence intensity of the acceptor increases. These changes in the fluorescence parameters are measurable, and they provide the foundation for using FRET to asses PPIs [18].

Accordingly, the FRET transfer rate (k FRET ) is dependent on the distance between the donor and acceptor fluorophores (R) as well as their relative orientation. Therefore, any conformational changes in protein complexes impact this rate. Additionally, k FRET is inversely related to the sixth power of the donor-to-acceptor separation distance (R0), reflecting the dipole-dipole coupling mechanism. R0 represents the Förster radius, which is the distance between the donor and acceptor at which the FRET efficiency is 50 %. τ D represents the excited state lifetime of the donor fluorophore in the absence of the acceptor [19].

(1) kFRET=1τDR0R6

1.3 FRET-based techniques

FRET can be measured using mainly three microscopic methods. Here, we discriminate between the two intensity-based approaches sensitized emission FRET (SE-FRET) and FRET-Acceptor photobleaching (FRET-APB) and the non-intensity-based FRET-Fluorescence Lifetime Imaging Microscopy (FRET-FLIM). SE-FRET monitors the changes in donor and acceptor emission by acquiring either a complete spectrum or by using appropriate filters for donor and acceptor. In case the two fluorophores are not in close proximity, excitation of the donor does not lead to excitation of the acceptor and therefore no detectable emission of the acceptor. In the case of FRET, due to the radiation-free transfer from the donor to the acceptor, the emission of the acceptor will increase while the emission of the donor decreases. SE-FRET is often used for FRET-based biosensors to monitor real-time metabolite concentrations and cellular processes such as phytohormone and calcium signaling [20], [21], [22]. When using FRET-APB, the acceptor fluorophore is bleached, resulting in a measurable increase of the donor fluorescence in case of FRET. While FRET-APB is simple and practical, it has two main limitations. First, it involves photobleaching the acceptor which prevents repeated measurements on the same cell. Second, it is intensity-dependent as it relies on the expression levels of the FP-tagged proteins, which can be highly heterogeneous in biological systems. Interestingly, FRET-FLIM can surpass these challenges as it needs only low excitation power, reducing the risks of photobleaching and phototoxic processes. Also, it measures the fluorescence lifetimes of fluorophores, an intrinsic characteristic unique to each fluorophore, rather than their intensities. Therefore, FLIM enables studying the dynamics of proteins complexes with high spatial and temporal resolutions, offering more robust and reproducible in vivo measurements.

1.4 FRET pairs

Optimal FRET measurements require FRET pairs with spectral overlap, photostability, and compatibility with the plant autofluorescence [23]. For instance, ECFP and EYFP is a commonly used FRET pair with high spectral overlap. However, the donor ECFP is prone to photobleaching and is relatively dim due to its low quantum yield [24]. Also, it shows a multi-exponential fluorescence lifetime decay, i.e., its intensity decreases over time at varying rates, with each rate corresponding to a different fluorescence lifetime, complicating FRET-FLIM analyses. Therefore, mCerulean, which is brighter and in the same spectral range, presents an alternative FRET pair with mVenus [25]. Moreover, the FRET pair should not have crosstalk with the autofluorescence of the studied tissue or cellular compartment while preserving the correct localization of the fluorescent protein. A previous study compared 12 different FRET pairs in transient Nicotiana benthamiana experiments and showed that eGFP-mCherry is still a good choice [26]. However, several alternative FRET pairs have been tested in plants i.e. mVenus that could serve as a donor for mRuby3 or mKate2 as well as an acceptor for mTurquoise2. Furthermore, a combination of mTurquoise2 and mNeonGreen proved to be an efficient FRET pair [26]. Since improved versions of well-studied fluorophores are developed regularly, the FPbase (www.fpbase.org/) offers an invaluable tool for selecting potential FRET pairs as it provides detailed descriptions of fluorescent protein properties, including spectral attributes, FRET relationships, and compatibility with various filters and light sources (Figure 1) [27].

Figure 1: 
Spectral characteristics and FRET parameters for mV and mCh. (A) Excitation and emission spectra of the fluorescent proteins mV (donor) and mCh (acceptor). The integral overlap area, J(λ), highlights the spectral overlap between mV emission and mCh excitation. Figure data obtained from the fluorescent protein database (FPbase) [27]. (B) Table summarizing key photophysical properties of mV and mCh including quantum yield (QY), extinction coefficient of the acceptor (ECAcc), Förster radius (R0, in Å), and overlap integral (J(λ)).
Figure 1:

Spectral characteristics and FRET parameters for mV and mCh. (A) Excitation and emission spectra of the fluorescent proteins mV (donor) and mCh (acceptor). The integral overlap area, J(λ), highlights the spectral overlap between mV emission and mCh excitation. Figure data obtained from the fluorescent protein database (FPbase) [27]. (B) Table summarizing key photophysical properties of mV and mCh including quantum yield (QY), extinction coefficient of the acceptor (ECAcc), Förster radius (R0, in Å), and overlap integral (J(λ)).

The following sections entail a detailed overview of the practical application of FRET-APB and FRET-FLIM in plants.

2 FRET acceptor photobleaching (FRET-APB)

FRET-APB is a fast and straightforward method to measure FRET by comparing the donor fluorescence intensity before and after photobleaching the acceptor. It involves measuring the donor fluorescence intensity before bleaching, photobleaching the acceptor, and remeasuring the donor fluorescence intensity after bleaching. If FRET occurs, the excitation of the donor leads to an energy transfer from the donor to the acceptor. The principle of FRET-APB is to block this energy transfer by destroying the acceptor via a strong laser pulse, i.e., photobleaching. Consequently, the donor fluorescence intensity increases because no energy is transferred to the acceptor anymore. This increase is measurable and provides a direct fluorescence intensity-based readout of FRET. The FRET efficiency (E app ) is calculated accordingly:

(2) Eapp=IntensityDonorafterbleachingIntensityDonorbeforebleachingIntensityDonorbeforebleaching×100

However, this equation does not correct for background fluorescence or the recovery of the donor during the bleaching time. Therefore, the efficiency of the energy transfer is referred to as an apparent efficiency (E app ). Further, control experiments with the donor-only sample are needed to determine the recovery rate of donor fluorescence under similar bleaching conditions [28].

2.1 Materials

FRET-APB requires a microscope with a strong laser or appropriate illumination source, such as a confocal or wide-field microscope with suitable filter sets and mirrors to bleach the acceptor. The tools needed for preparing a plant sample include microscope slides, coverslips (#1.5, 170 μm thickness), razor blades or biopsy puncher, forceps, and fluorescence-free water. The plant material should express an appropriate FRET pair, such as mVenus and mCherry, for accurate FRET measurement. In the absence of stable transgenic lines, transient expression systems, such as N. benthamiana (N. benthamiana), offer a useful alternative for FRET experiments. To illustrate, N. benthamiana can be transformed with FRET constructs via Agrobacterium tumefaciens-mediated infiltration, allowing the visualization and analyses of proteins within a few days [29]. However, the expression of FRET constructs under strong constitutive or native promoters can lead to a rapid protein overexpression, creating artifacts that can influence FRET measurements. Therefore, the use of inducible expression systems, such as estradiol-inducible promoters, allows a precise control of gene expression preventing protein overaccumulation [30], [31].

2.2 Methods

2.2.1 Sample preparation

The living plant sample can be a leaf or a root and is prepared in water as a mounting solution. It is recommended to use a water or silicon immersion objective to match the refractive index of the mounting solution, minimizing reflection, refraction, or diffraction that occurs at the interfaces. In case of transient expression in N. benthamiana, a piece of the leaf is cut by a razor blade, and its abaxial (lower) side is placed facing the coverslip. It is important to remove the trapped air from the leaf tissue either through applying pressure to the leaf by rolling the razor blade over the coverslip or through infiltrating water into the leaf [32]. Air removal should be done gently as the destruction of the sample can lead to increased autofluorescence. Indeed, the prepared samples include several controls: two negative controls, one expressing only the donor FP tagged protein of interest (POI) and another together with free acceptor FP, a positive control, expressing a fusion of the donor and acceptor fluorophores on the same vector, and the FRET sample expressing the two studied proteins each tagged with a fluorophore from the selected FRET pair.

2.2.2 Acquisition

FRET-APB acquisition does not aim for high-resolution images, but rather for fast measurements while avoiding acquisition bleaching. Ideally, the image size, pixel dwell time, laser power, and bleaching region should be fixed throughout the experiment. Yet, the heterogeneity in the signal intensity between cells can still be addressed by adjusting the detector gain. It is important not to saturate the detector assigned to the donor channel, as the donor intensity is expected to increase after photobleaching the acceptor. Additionally, the spectral overlap of the FRET pairs necessitates avoiding crosstalk between the two different channels (donor and acceptor channel), which are imaged simultaneously. A fast line-wise switching mode of channels can prevent such crosstalk. The acquisition experiment is usually designed with a total of twenty frames of 256 × 256 pixels, with a pixel dwell time of around 1–3 μs without line averaging. After the acquisition of five frames, the region of interest is bleached at 100 % laser power at the acceptor excitation wavelength aiming to reduce acceptor intensity to a sufficiently low level without damaging the cells. Then, fifteen more frames are recorded after bleaching.

2.2.3 Data analyses

After acquisition, the measured intensities of the donor are used to calculate the FRET efficiency (E app ) as in Equation (2). The IntensityDonor before bleaching is the average of its measured intensities in the first five frames, while the IntensityDonor after bleaching is the average of its measured intensities in the five frames after bleaching. It is important to control the acquisition bleaching by ensuring that the donor intensity do not decrease more than 10 % in the first five frames. In our experience, the expected range of FRET efficiency measured by FRET-APB can range between 10 and 60 % [30], [31].

3 FRET fluorescence lifetime imaging microscopy (FRET-FLIM)

When a fluorophore is excited by a photon, it seeks to return to its ground state through a decay process, which can be either radiative or non-radiative. In radiative decay, a fluorophore emits a photon of longer wavelength than the absorbed photon due to Stokes shift. However, in non-radiative decay, the absorbed energy dissipates without photon emission through heat dissipation or molecular collisions, or transferred to another molecule via processes like FRET. Whether the decay occurs at a uniform mono-exponential or varying multi-exponential rates is determined by the fluorophore’s photophysical properties. The decay rate which measures how fast the fluorescence diminishes is the reciprocal of the fluorescence lifetime. The fluorescence lifetime is the average time a fluorophore spends in its excited state before returning back to its ground state [33]. Changes in the fluorescence lifetime report changes in the fluorophore environment such as pH levels, binding states, surrounding molecules, and importantly FRET [34].

One of the most accurate methods for measuring the fluorescence lifetime is time-correlated single photon counting (TCSPC). Initially, a fluorophore is excited by a pulsed laser, and the time is measured between the excitation pulse and the emission of the first photon. This measurement requires single-photon sensitive detectors, and photon counting electronics. The excitation-detection process is repeated multiple times (millions of pulses), and a histogram of photon arrival times is built along. This histogram represents the exponential decay behavior of the fluorophore, from which the fluorescence lifetime can be calculated.

FRET-FLIM monitors the donor fluorescence lifetime which decreases upon FRET. To illustrate, when an excited donor is in close proximity to an acceptor, it can transfer its energy through FRET, resulting in a faster depopulation of the excited state. Therefore, the mean fluorescence lifetime of the donor is shortened as a reflection to FRET. In contrary to the intensity-dependent FRET-APB, the lifetime-dependent FRET-FLIM does not depend on the donor concentration, and it enables robust quantitative FRET measurements to study PPIs. With enough photons collected in single pixels, it allows for PPIs analyses with high spatiotemporal resolution at different subcellular domains. Moreover, it can estimate the stringency of interactions by identifying the proportion of interacting versus non-interacting molecules [35]. Furthermore, FRET-FLIM can provide a better understanding of PPIs by characterizing the efficiency of energy transfer and the binding affinities between interacting proteins which is available for monoexponentially decaying donor fluorophores, as described in a technical note by PicoQuant [36], and was recently established for biexponentially decaying fluorophores, termed one pattern analysis (OPA) [37]. The initial motivation for developing the OPA fitting routine comes from the observation that most of the fluorescent proteins like, e.g., EGFP and Cerulean, serving as donor fluorophores in many FRET pairs, show already in a “donor only” situation an at least bi-exponential decay behavior of their fluorescence lifetime, with two distinct lifetime components. The OPA fitting routine in a first step determines the two lifetime components and the ratio of their amplitudes. When the FRET decay is fitted three lifetime components are considered, with two lifetime components set to the values determined from the donor-only measurement, and the amplitude of lifetime 1 set to 1.0 and the amplitude of lifetime 2 set to the fraction determined in the donor-only measurement. This is the so called “pattern”, which describes the “donor-only” decay. This pattern is only adjusted for its height by a proportionality parameter in the fit of the FRET measurement, along with the fit of a third lifetime and its amplitude to describe the FRET species. Theoretically, the FRET species could show bi-exponential decay behavior, as the donor is already bi-exponential, however, practically, until now good agreement was found for mono-exponential fitting of the FRET species. By applying the OPA fitting routine, even from a bi-exponential donor information about the FRET efficiency and binding affinities of the investigated PPI can be extracted.

It is worth noting that FRET efficiency is influenced by the ratio of the acceptor to donor. Therefore, controlling the expression levels of the donor and acceptor is important to ensure robust quantitative FRET-FLIM analyses. For instance, a coexpression system where both donor and acceptor fusion proteins are expressed from a single T-DNA reduces the variability in the donor to acceptor ratio, compared to coexpression from separate T-DNAs. This method improved the FRET efficiency, enhanced the coexpression rates, and ensured reproducibility of the system [26].

3.1 Materials

FRET-FLIM requires a confocal microscope equipped with pulsed lasers, single-photon sensitive detectors such as avalanche photodiodes (APDs), hybrid detectors (HyDs), or fast photo multiplier tubes (PMTs), in addition to the FLIM module, i.e., TCSPC (time-correlated single photon counting) electronics. Additionally, a power meter to measure the power of the excitation light at the objective is needed. The tools and plant material are the same as in FRET-APB. Additionally, rhodamine 110 or Atto425, and erythrosine B solutions are needed for calibration. Rhodamine 110 has a stable fluorescence lifetime (4 ns in water), a high quantum yield, photostability, and it shows a mono-exponential decay behavior. These measurements are not necessary for the fitting process but are needed to verify the accuracy of the FRET-FLIM setup. When the donor fluorophore is in the blue spectrum, Atto425 can be used for a similar calibration. Atto425 has a shorter fluorescence lifetime (3.6 ns in water), making it convenient for comparisons with donor fluorophores of shorter lifetimes. Erythrosine B has an extremely short lifetime and can therefore be used to record the instrument response function (IRF). The IRF measurement reflects the influence of all components of the instrument on the incoming photons and is therefore individual for each setup. The IRF is later on used to deconvolve the whole decay histogram during the fitting process. Alternatively, a mirror can be used to record the IRF [38].

3.2 Methods

3.2.1 Sample preparation

The FRET samples tested in FRET-FLIM are prepared in the same way as in FRET-APB. It is also necessary to include the positive and negative controls to assess the changes in the fluorescence lifetime caused by FRET. Calibration solutions are also prepared. For rhodamine 110, a working solution is prepared by diluting concentrated stock solutions in water, where this dilution should ensure that the count rate at the detectors is within the expected range of the sample signals. If the donor falls in the blue spectrum, Atto425 is used for calibration, where it is diluted tenfold in water. As for erythrosine B, its powder is dissolved in water, and NaI or KI are added until saturation to further quench erythrosine B. The saturated solution is stable for at least a month. For IRF measurements, the undiluted solution is used, and if the signal is too high, optical attenuation is applied to achieve the appropriate count rate signal.

3.2.2 Calibration

Prior to each experimental day, calibration measurements must be performed to verify the performance of the FLIM setup. First, the pulsed laser is set at an appropriate frequency, typically at 32–40 MHz for donors like EGFP, YFP, or mVenus, to record their complete fluorescence lifetime decay. While performing the measurements, it is important to shield the solutions and samples from external light sources, such as room light. The first calibration measurement controls the overall performance of the FLIM setup, through a 60-s acquisition of rhodamine 110. Next, the general background can be measured by a 120-s acquisition of water. This measurement of “dark” counts can also help to judge the performance of the detectors, i.e., high dark counts may indicate inefficient cooling or aging of detectors.

The third calibration measures the instrument response function (IRF), which reflects the timing precision of the TCSPC system, determined by laser and detector performance. The IRF is required for the deconvolution of the decay histogram in the lifetime fitting procedure. For IRF measuring, counts from erythrosine B are collected within the count rates of the measured sample to ensure accurate fitting. Finally, the excitation laser power should be minimized to reduce acquisition bleaching. A recommended starting value is 1–2 µW, especially because the power density (W/m2) increases upon zooming into the sample. Ideally, the excitation power should be adjusted to collect sufficient photons and kept constant throughout the experiment.

3.2.3 Acquisition

As previously described, FRET-FLIM monitors the donor fluorescence lifetime which decreases in case of FRET. First, a donor-only control is measured to investigate the fluorescence lifetime behavior of the FP-tagged protein alone before measuring samples expressing both donor and acceptor. Also, a protein known not to interact, tagged with the acceptor FP, or if not available free acceptor FP, is used to control for non-specific interactions. Each dataset should include at least ten individual measurements reproducible throughout the experimental days. It is recommended to conduct measurements over three separate days to enhance reliability and consistency. FLIM acquisition involves repetitive scanning of images to accumulate sufficient photon counts per pixel. A recommended image size of 256 × 256 pixels is used to reduce the data size for pixel-wise fluorescence lifetime analysis. Typically, it is recommended to acquire 300–400 photons per pixel, with a minimum of 100 counts per pixel for standard measurements. For more complex multicomponent fitting models, at least 1,000 counts per pixel are required [31], [39]. Acquisition can be stopped after enough photon counts are collected or after acquiring around 40–60 frames. As the pixel dwell time is around 10 µs, one measurement takes about 1 min. The resulting file size strongly depends on the time resolution of the decay histogram. Typically, a resolution of 8 or 16 ps is sufficient for precise analysis and fitting of the measured decay curves. If photon counts are rather low, even a resolution of 64 or 128 ps/channel is sufficient for performing a FRET-FLIM analysis.

Furthermore, it is important to work with low excitation power and avoid bleaching in the sample, to avoid production of reactive oxygen species (ROS) in the cells, that could influence the fluorescence lifetime. Therefore, it is advisable to scan more frames with shorter pixel dwell time, rather than fewer frames at a longer dwell time. Moreover, if the experiment requires better time resolution to track fast changes, the FLIM measurement time can be reduced by slightly increasing the laser power, thus collecting more counts in a shorter period. This approach should be validated by a control experiment to ensure the fluorescence lifetime remains unaffected by the increased laser power. Finally, while FLIM primarily monitors the donor fluorescence lifetime, it is also useful to simultaneously track the intensity of the acceptor fluorescence. This provides an internal control to the possible heterogeneity of protein expression between cells.

During FLIM acquisition in plant samples, managing autofluorescence is crucial for obtaining high-quality data. For instance, chloroplasts have intense autofluorescence over a broad spectrum with very short fluorescence lifetime (<1 ns). Therefore, it is recommended to avoid FLIM measurements near chloroplasts and to collect high photon counts per pixel to obscure the effect of autofluorescence in the overall data. Another key consideration is maintaining low excitation laser power to minimize acquisition bleaching which can disturb the fluorescence lifetime.

Moreover, moderate protein expression can further enhance the data quality. To illustrate, low protein expression reduces the photon counts per pixel, while overexpression oversaturates the detectors, especially APDs, leading to a pile-up effect resulting in an artificial shortening of the fluorescence lifetime due to the dead times of the TCSPC electronics, as discussed in a technical note by PicoQuant (https://www.picoquant.com/images/uploads/page/files/7253/technote_tcspc.pdf). However, most modern TCSPC systems, such as PicoQuant’s MultiHarp 150, have effectively mitigated the pile-up effect by reducing the unit’s dead time, leading to higher tolerance for high count rates. Indeed, a balance is key, and the use of estradiol-inducible promoters in N. benthamiana transient expression system provides an optimal platform for FRET-FLIM measurements, allowing for controlled expression levels [30]. However, heterogeneous and occasionally high protein abundance, such as during the formation of biomolecular condensates, is sometimes unavoidable in living samples. This factor must be taken into account during analysis. In such cases, the use of hybrid detectors is preferable as they are less prone to pile-up effects.

3.2.4 Data analyses

After acquisition, FLIM data analyses is performed using specialized software such as Symphotime by PicoQuant (www.picoquant.com), SPCImage by Becker & Hickl (www.becker-hickl.de), and AnI (www.mpc.hhu.de). Initially, the recorded decay histograms are fitted to mono-exponential decay models to gain a preliminary overview. If the fluorescence decay does not conform to mono-exponential pattern, bi- or multi-exponential decay models are applied to accurately estimate donor lifetimes. These fittings require the IRF, measured during calibration with erythrosine B.

Additionally, fluorescence lifetimes in different regions of interests (ROIs) can be extracted from each image. Artifacts and overexpressed regions can be excluded by filtering out extreme values through thresholding. When FRET occurs between fluorescent proteins, the donor fluorescence lifetime is reduced, however, the expected quenching of the donor lifetime is usually not as strong as in in vitro FRET-studies with small dye molecules attached to purified proteins. A typical value of donor quenching between a FRET-pair like EGFP and mCherry would be around 300 ps, but even a lower value of 100 ps could indicate ongoing FRET between fluorescent proteins. In addition, in biological systems, this reduction can vary remarkably due to the interference of autofluorescence, fluorophore orientation, and other interactions that might influence FRET. To ensure significant results, it is recommended to perform multiple sample combinations and experimental repetitions. Furthermore, the fraction of interacting molecules undergoing FRET requires at least a bi-exponential decay model to capture the complexity of the decay curve [40]. After fitting the data, the FRET efficiency is then calculated from the donor fluorescence lifetimes in the FRET sample versus the donor-only sample.

(3) E=1τDonorinFRETsampleτDonorindonoronlysample×100

Furthermore, alternative fitting approaches enhance the accuracy of FLIM measurements allowing to distinguish between different interaction scenarios, such as high affinity but low proximity or low affinity but high proximity of the studied proteins [36]. Therefore, it provides deeper insights into the interactions and spatial relationships between proteins. Recently, the fitting model termed OPA was established to extract this important information also from multi-exponentially decaying fluorophores. To do so, donor-only decay components are identified as a predefined pattern, allowing for the extraction of FRET efficiency and binding parameters. Subsequently, binding, i.e., the relative amplitude of the FRET fraction which reflects the number of molecules engaged in FRET within the sample, is determined. Additionally, the FRET efficiency, derived from the reduction in the donor fluorescence lifetime due to energy transfer to the acceptor, can be calculated [37].

4 Case study

PLETHORA 3 (PLT3) and WUSCHEL-RELATED HOMEOBOX 5 (WOX5) encode transcription factors (TFs) that are essential for maintaining the root apical meristem (RAM) in Arabidopsis thaliana [13]. PLT3, amongst other PLTs, forms concentration gradients within the RAM, controlling root cell fate and differentiation, by supporting stem cell maintenance and meristematic activity [41]. On the other hand, WOX5 is largely restricted to the quiescent centre (QC), where it maintains the stemness of the adjacent columella stem cells by repressing differentiation signals [42]. Together with other actors, PLT3 and WOX5 play crucial roles in the root organization and RAM maintenance.

At the subcellular level, the two proteins were shown to colocalize in the nucleus, which correlates with their roles in transcriptional regulation. Notably, PLT3 contains prion-like domains (PrDs) within its sequence, which are low-complexity domains allowing for condensate formation likely by phase separation. Accordingly, PLT3 forms dynamic nuclear condensates, presumably acting as regulatory or interactive hubs with other proteins or nucleic acids [13]. As the expression patterns of PLT3 and WOX5 overlap in the RAM and the two proteins colocalize in the nucleus at the subcellular level, their interaction is studied using FRET-APB and FRET-FLIM in the transient expression system N. benthamiana.

4.1 PLT3-WOX5 interaction using FRET-APB

PLT3 tagged with mVenus (PLT3-mV) and WOX5-tagged to mCherry (WOX5-mCh) were co-expressed in N. benthamiana leaves using A. tumefaciens-mediated transformation [13], [29]. PLT3-mV localized in the nucleus, where it formed biomolecular condensates. WOX5-mCh colocalized with PLT3-mV and was recruited into its condensates. FRET-APB was performed as described, measuring the fluorescence intensity of the two FP-tagged proteins before and after bleaching the WOX5-mCh acceptor (Figure 2A–C).

Figure 2: 
FRET-APB experiment in nuclei of transiently expressing N. benthamiana leaf epidermis cells. PLT3-mV and WOX5-mCh intensity before (A–C) and after bleaching (A′–C′) of the acceptor. The white square indicates the bleached area. (D) Graphic representation of the fluorescence intensity of mV and mCh, the black arrow indicates the time point of bleaching. Scale bars represent 5 μm.
Figure 2:

FRET-APB experiment in nuclei of transiently expressing N. benthamiana leaf epidermis cells. PLT3-mV and WOX5-mCh intensity before (A–C) and after bleaching (A′–C′) of the acceptor. The white square indicates the bleached area. (D) Graphic representation of the fluorescence intensity of mV and mCh, the black arrow indicates the time point of bleaching. Scale bars represent 5 μm.

Before bleaching the acceptor, the intensity of the FP-tagged proteins slightly decreased due to acquisition bleaching, which should not exceed 10 %. Upon bleaching the acceptor, the intensity of WOX5-mCh dropped to nearly zero and then gradually recovered. However, PLT3-mV intensity increased after bleaching, indicating FRET occurrence (Figure 2D). Measurements were conducted on a minimum of ten nuclei, with the experiment repeated at least three times. Consequently, the FRET efficiency E app calculated as per equation (2) was 21 %.

4.2 PLT3-WOX5 interaction using FRET-FLIM

PLT3-WOX5 interaction was further investigated via FRET-FLIM [12], [13], determining the intensity-weighted fluorescence lifetime measurements and the relative number of molecules undergoing FRET, known as binding, by using OPA (Figure 3, Table 1). First, WOX5-mV was expressed alone to measure the donor-only fluorescence lifetime. Second, WOX5-mV was co-expressed with free mCherry to control for background fluorescence, spectral crosstalk, or non-specific FRET between free mCherry and WOX5-mV. Finally, two FRET samples were analyzed, one with WOX5-mV and full-sequence PLT3-mCh which contains three PrDs, and the other expressing WOX5-mV and PLT3 with mutated or deleted PrDs (PLT3ΔPrD-mCh). In the PLT3ΔPrD-mCh construct, PrD1 at the N-terminus was substituted by a 27 amino acid linker, while PrD2 and PrD3 at the C-terminus were deleted, to test whether the PrDs serve as interaction sites between PLT3 and WOX5.

Figure 3: 
Comparison of traditional FRET-FLIM analysis and OPA. Summary of quantification of (A) intensity weighted fluorescence lifetime [in ns] of WOX5-mV and (B) one pattern analysis. Statistical groups were assigned after non-parametric Kruskal Wallis with post-hoc Dunn’s test (α = 0.05, p-values adjusted after Benjamini and Hochberg). (C–F) Representative images of fluorescence lifetime imaging microscopy (FLIM) measurements of nuclei in N. benthamiana epidermal leaf cells after pixel-wise multiexponential fitting. The fluorescence lifetime of the donor WOX5-mV in absence or presence of the indicated acceptor (mCherry-NLS, PLT3-mCh or PLT3ΔPrD-mCh) is color-coded: blue (2.5) refers to low fluorescence lifetime [in ns], red (3.1) indicates high fluorescence lifetime. Scale bars represent 6 µm.
Figure 3:

Comparison of traditional FRET-FLIM analysis and OPA. Summary of quantification of (A) intensity weighted fluorescence lifetime [in ns] of WOX5-mV and (B) one pattern analysis. Statistical groups were assigned after non-parametric Kruskal Wallis with post-hoc Dunn’s test (α = 0.05, p-values adjusted after Benjamini and Hochberg). (C–F) Representative images of fluorescence lifetime imaging microscopy (FLIM) measurements of nuclei in N. benthamiana epidermal leaf cells after pixel-wise multiexponential fitting. The fluorescence lifetime of the donor WOX5-mV in absence or presence of the indicated acceptor (mCherry-NLS, PLT3-mCh or PLT3ΔPrD-mCh) is color-coded: blue (2.5) refers to low fluorescence lifetime [in ns], red (3.1) indicates high fluorescence lifetime. Scale bars represent 6 µm.

Table 1:

Summary of FRET-FLIM results showing the average intensity-weighted fluorescence lifetime [ns] with standard deviation (STD), the FRET efficiency [%] with SD and binding [%] with SD.

Sample Average intensity-weighted fluorescence lifetime [ns] ±SD FRET efficiency [%] ±SD Binding [%] ±SD
WOX5-mV 3.03 0.03 37.32 31.88 2.27 3.12
WOX5-mV free mCherry 2.97 0.07 30.21 15.99 7.4 6.99
WOX5-mV PLT3-mCh 2.74 0.17 39.49 12.8 30.55 13.29
WOX5-mV PLT3ΔPrD-mCh 2.88 0.13 35.77 8.19 18.49 12.37

The fluorescence lifetime of WOX5-mV decreased significantly when co-expressed with PLT3-mCh, indicating FRET and thereby confirming an interaction between PLT3 and WOX5 (Table 2). This lifetime reduction was notably diminished when WOX5-mV was co-expressed with PLT3ΔPrD-mCh, suggesting that the PrDs in PLT3 are critical for the interaction between these two proteins (Figure 3A, C–F, Table 1).

Table 2:

Exact p-values for the average intensity-weighted fluorescence lifetime of the indicated samples after independent non-parametric Kruskal Wallis with post-hoc Dunn’s test (α = 0.05) and p-value adjustment after Benjamini and Hochberg.

WOX5-mV WOX5-mV free mCherry WOX5-mV PLT3-mCh
WOX5-mV free mCherry 0.0018
WOX5-mV PLT3-mCh 2.7 × 10−20 4.8 × 10−08
WOX5-mV PLT3ΔPrD-mCh 1.8 × 10−09 0.0048 0.0164

Furthermore, using equation (3) allows for the calculation of the FRET efficiency based on the lifetime reduction and results in a FRET efficiency of around 10 %. This value is lower than that obtained from the FRET-APB approach. This discrepancy possibly results from the choice of the donor molecule, WOX5 or PLT3, respectively. PLT3 causes the formation of nuclear condensates that exhibit a strong fluorescence signal which can cause an artificial lifetime reduction when using detectors, that have a long dead time, triggering the so called pile-up effect. OPA provided further insights, showing that while FRET efficiency remained unchanged, WOX5 binding to full-length PLT3 was significantly stronger than to PLT3ΔPrD. This result reflects a higher affinity between the full-length proteins, highlighting the added detail and value OPA offers (Figure 3B, Tables 1, 3 and 4).

Table 3:

Exact p-values for the binding of the indicated samples after independent non-parametric Kruskal Wallis with post-hoc Dunn’s test (α = 0.05) and p-value adjustment after Benjamini and Hochberg.

WOX5-mV WOX5-mV free mCherry WOX5-mV PLT3-mCh
WOX5-mV free mCherry 0.0023
WOX5-mV PLT3-mCh 3.5 × 10−21 1.1 × 10−08
WOX5-mV PLT3ΔPrD-mCh 6.5 × 10−10 0.0025 0.0148
Table 4:

Exact p-values for the FRET efficiency of the indicated samples after independent non-parametric Kruskal Wallis with post-hoc Dunn’s test (α = 0.05) and p-value adjustment after Benjamini and Hochberg.

WOX5-mV free mCherry WOX5-mV PLT3-mCh
WOX5-mV PLT3-mCh 0.0012
WOX5-mV PLT3ΔPrD-mCh 0.0203 0.1527

5 Conclusions

Studying PPIs in vivo is crucial for advancing plant biology. In this scope, FRET-based techniques provide invaluable insights into these interactions. FRET-APB is practical and offers direct readout of FRET efficiency, where its ease of use can provide first hints on PPIs. However, it cannot be repeated on the same sample and offers limited spatiotemporal resolution, due to its reliance on fluorescence intensity and bleaching of the sample. On the other hand, FRET-FLIM is a more robust and reliable technique. Measuring the fluorescence lifetime enables quantitative analyses with high spatiotemporal resolution. Despite challenges posed by autofluorescence and the plant tissue complexity, FLIM offers a powerful technique to study dynamic PPIs in vivo. It can overcome these obstacles with careful experimental design and provide accurate measurements of protein interaction dynamics and even binding.


Corresponding author: Yvonne Stahl, Faculty of Biosciences, Institute for Molecular Biosciences, Goethe University, Max-von-Laue Str. 9, D-60438 Frankfurt am Main, Germany, E-mail: 

Acknowledgments

We thank Rebecca C. Burkart for providing raw data for FLIM. We thank Jan E. Maika for support with data analysis.

  1. Research ethics: The conducted research is not related to either human or animals use.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: Authors state no conflicts of interest.

  6. Research funding: None declared.

  7. Data availability: Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

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Received: 2024-10-31
Accepted: 2025-01-15
Published Online: 2025-01-30
Published in Print: 2025-04-28

© 2025 the author(s), published by De Gruyter on behalf of Thoss Media

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