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Abstract
Two-photon excited fluorescence (TPEF) is a powerful technique that enables the examination of intrinsic retinal fluorophores involved in cellular metabolism and the visual cycle. Although previous intensity-based TPEF studies in non-human primates have successfully imaged several classes of retinal cells and elucidated aspects of both rod and cone photoreceptor function, fluorescence lifetime imaging (FLIM) of the retinal cells under light-dark visual cycle has yet to be fully exploited. Here we demonstrate a FLIM assay of photoreceptors and retinal pigment epithelium (RPE) that reveals key insights into retinal physiology and adaptation. We found that photoreceptor fluorescence lifetimes increase and decrease in sync with light and dark exposure, respectively. This is likely due to changes in all-trans-retinol and all-trans-retinal levels in the outer segments, mediated by phototransduction and visual cycle activity. During light exposure, RPE fluorescence lifetime was observed to increase steadily over time, as a result of all-trans-retinol accumulation during the visual cycle and decreasing metabolism caused by the lack of normal perfusion of the sample. Our system can measure the fluorescence lifetime of intrinsic retinal fluorophores on a cellular scale, revealing differences in lifetime between retinal cell classes under different conditions of light and dark exposure.
© 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
1. Introduction
Photoreceptors and the retinal pigment epithelium (RPE) are essential components of the visual system, playing crucial roles in vision and the regulation of visual cycle reactions [1,2]. Photoreceptors, including rods and cones, are specialized light-sensitive cells located in the retina. They are responsible for capturing and converting light into electrical signals, which are then transmitted to the brain for visual processing. The RPE, on the other hand, is a layer of pigmented cells located between the photoreceptors and the underlying choroid. It provides essential support functions to maintain the integrity and functionality of the photoreceptor cells.
The visual cycle is a complex process involving the continuous recycling of retinoids, which are vitamin A derivatives, within the photoreceptor and RPE cells [3]. The visual cycle plays a critical role in the regeneration of photopigments required for vision. During phototransduction, retinoids undergo isomerization and conversion, allowing the photoreceptors to respond to light stimuli. The visual cycle ensures the replenishment of retinoids and enables the photoreceptors to maintain their light-sensing capabilities.
Although intensity-based TPEF ophthalmoscopy in non-human primates has successfully visualized several classes of retinal structures and probed both rod and cone function [4,5], fluorescence lifetime imaging at the cellular scale has the potential to provide further insight into both basic physiology and pathology of the retina [6–8]. Being an intrinsic property of a fluorescent molecule, fluorescence lifetime measured by a FLIM system is not biased by excitation power [9–11] or probe concentration [12,13]. In addition, lifetime reading is not prone to photobleaching [14] and can shed light on the microenvironment surrounding the fluorophore [9,15,16]. This is of particular importance when imagining the outer retinal layers, which require passage of both excitation and emission through several layers of vasculature and inner retina cell classes. In vivo, one-photon fluorescence lifetime imaging ophthalmoscopy (FLIO) has been conducted in both rodent and human fundus using a scanning laser ophthalmoscope [17,18]. FLIO shows potential to quantitatively measure retinal physiology, enabling in vivo study of biochemical processes before structural changes become apparent [19]. Notably, alterations in retinal fluorescence lifetime are associated with various retinal diseases, including age-related macular degeneration [20–22], retinitis pigmentosa [23], Stargardt disease [24], and choroideremia [25], among others [10,26]. By measuring the fluorescence signals emitted by retinoids and their condensation products [27] in response to light or chemical stimuli, we can assess the efficiency of the visual cycle and detect any abnormalities or dysfunctions [4,5]. Multiphoton imaging techniques can offer improved contrast and resolution, enabling high-throughput screening of retinal tissues at the single-cell level [7,28,29].
In this work, we developed a custom multimodal FLIM instrument to image the intrinsic fluorescence signatures of the retina at subcellular resolution. We demonstrated the application of two-photon FLIM to visualize retinal function during the visual cycle. Using a rabbit model, we show FLIM’s ability to provide novel insights into photoreceptor and RPE physiology during light/dark cycles. The dependence of fluorescence lifetime on light-dark cycles reveals the potential of FLIM to shed light on basic retinal function in health and disease. Additionally, we introduced a new method to evaluate the health of photoreceptors and RPE cells corresponding to light-dark visual cycles using fluorescence lifetime data. We have employed time domain analysis to assess the correlation between photoreceptor and RPE lifetimes and the light-dark exposure function. This novel approach offers a single factor to quantify the response effectively, providing valuable insights into retinal physiology during light-dark visual cycles.
2. Methods
2.1 Two-photon fluorescence lifetime ophthalmoscopy (2P-FLIO)
The experimental setup of 2P-FLIO is depicted in Fig. 1(a). We used a fiber-based femtosecond laser (CFL-04RFF, Calmar Laser), providing 90-fs pulses at the central wavelength of 780 nm with pulse repetition frequency (PRF) at 80 MHz, which is suitable for two-photon excitation of endogenous retinal fluorophores. The excitation beam is then guided through a prism pair compressor to pre-compensate for the chromatic dispersion by subsequent optical elements and the eye itself. As a result, 100-fs pulses with close to transform-limited temporal shape were delivered to the retinal plane. After dispersion pre-compensation, the beam entered a 2P-FLIO with x-y galvanometer scanners (GM) and a telescope relaying the GM’s plane to the pupil plane of the eye or the front focal plane of the 60x, NA 1.3 silicone immersion objective (UPLSAPO60XS2, Olympus). This paper only discusses results with the high NA objective and freshly dissected retinal flat mounts, although the same experimental set-up can be used with low NA lenses to image the living eye. The 2P-FLIO allows for simultaneous frame registration in 2 channels, de-scanned fluorescence and reflectance. Reflectance images were obtained with the same light as for 2P-FLIO images and served to adjust eye position before imaging as guidance for subsequent alignment of fluorescence frames and to correct motion artifacts within the frame (SI Note 1). The two-photon excited fluorescence (TPEF) emission was collected with a 500-720 nm emission filter by a cooled low dark count photomultiplier tube (PMT) (H74229-40, Hamamatsu Corp.) and amplified with 2 GHz cutoff bandwidth preamplifiers (HFAC-26, Becker and Hickl GmbH). The amplified signal was then measured and correlated to the reference clock of the femtosecond laser with a time-correlated single photon counting (TCSPC) module (PicoHarp 300, PicoQuant). Collected TPEF photons were assigned to one of 98 time bins for each pixel, depending on arrival time with respect to the synchronization pulse of the femtosecond laser. For comparison purposes, we also installed a 470 nm picosecond pulse laser (LDH-D-C-470, PicoQuant) for one-photon fluorescence lifetime ophthalmoscopy (1P-FLIO). The 470 nm laser beam followed the same excitation path as the 2P-FLIO. The one-photon excited fluorescence was collected through a 150 µm pinhole and focused on the same PMT. In the case of 1P-FLIO, the amplified signal is correlated to the reference clock of the picosecond pulse laser.
Fig. 1. (a) Schematic of 2P-FLIO system with raw data presentation, (b) Multiple retinal layers imaging and unmixing with endogenous fluorophores (c) Photoreceptor and retinal pigment epithelium lifetime images after unmixing. Abbreviations: PMT, photomultiplier tube; 1P, one-photon; 2P, two-photon; FLIO, fluorescence lifetime ophthalmoscopy; TCSPC, time-correlated single photon counting; SLO, scanning laser ophthalmoscopy; IP, image plane; P, pinhole; L, lens; PBS, polarizing beam splitter; EM, emission filter; M, mirror; DM, dichroic mirror; GM, galvo mirror; NZW, New Zealand White rabbit; DB, Dutch-Belted rabbit; GMM, Gaussian Mixture Models; PR, photoreceptor; RPE, retinal pigment epithelium. DM1 and DM2 were mounted on flip mounts (TRF90, Thorlabs) to select 2P-FLIO mode or 1P-FLIO mode. Scale bar is 50 µm.
In our 2P-FLIO, lifetime information is sampled in 98 bins (from 0 to 12.5 ns), which creates a FLIM dataset with the size of 256(x: pixels) × 256(y: pixels) × 98(t: time bins). This dataset, denoted as xyt, is a multidimensional array where x and y represent the spatial dimensions (0.3 µm wide per pixel), and t represents the fluorescence in a time bin (128 ps long each bin). At each pixel, there is a 98 × 1 sub-dataset termed fluorescence decay curve. This fluorescence decay curve can be transformed into a point (gτ, sτ) called a lifetime phasor through the Discrete Fourier Transform (DFT) (Fig. 1(b)) (Section 2.2). From there, a phasor plot can be built, which is denoted as τ phasors (or lifetime phasors), and the plot contains the lifetime information of the embedded fluorophores (Fig. 1(b)). Our customized 2P-FLIO unmixing software (termed UT-2P-FLIO on GitHub) takes τ phasors as inputs and outputs the weight of each fluorophore at each pixel, which can be used to segment photoreceptors and RPE and calculate lifetime for each segmented cell (Fig. 1(b)). We then test our 2P-FLIO imaging method on fixed and live cells labeled with diverse fluorescent dyes, before applying it to rabbit retina samples.
2.2 Lifetime phasor analysis
For lifetime phasors (τ phasors), the multi-exponential fluorescence decay at each pixel in the xyt dataset is transformed to a point (gτ, sτ) called a lifetime phasor through the Discrete Fourier Transform (DFT), given by Eq. (1) [30]:
The mx,y and $\varphi $x,y are the modulation ratio m and the phase delay $\varphi $ measured at pixel location (x, y) are calculated by Eq. (2) [30]. The phasor of a single-exponential decay should be positioned on the universal semicircle (Fig. 2(a)):
The $g{\tau _{x,y}}$ and $s{\tau _{x,y}}$ also can be expressed in the function of mx,y and $\varphi $x,y as shown in Eq. (3).
Fig. 2. (a) Lifetime phasors can be obtained from time-domain decay data, after conducting Fourier transform [33,34]. For a single species, lifetime decreases clockwise along the universal semicircle. (b) Lifetime phasor calibration using fluorescein (4 ns, excited by 780 nm femtosecond laser) for 2P-FLIO. (c) τ phasor plot of a convallaria sample. (d) False-colored FLIM image of the convallaria. Scale bar is 5 µm.
To eliminate the artifacts given by the instrument response function and the delays of the electronics, phase $\varphi $ and modulation m of the phasor cloud [31] are first calibrated using well-characterized dyes, such as fluorescein (lifetime of 4 ns [32]). Figure 2(b) shows τ phasor calibration procedure based on fluorescein, where m can be corrected by multiplying a constant factor α and $\varphi $ can be corrected by adding a constant offset Δ$\varphi $ to the initial value $\varphi $i, given by the following formulas:
Since the phasor cloud of a two-component mixture lies on a straight line joining the phasors of two individual components, the phasor cloud can be used to uncover the fractions of individual components at each pixel (Fig. 3(c, d)).
For multiple fluorescent species, the relationships between phasors and lifetimes are given by Eq. (6):
In our retinal imaging, the detected fluorescence signal comes from multiple fluorophores. The fit of the decay in the time- and the frequency-domains to recover the lifetime of an unknown number of fluorophores by trial-and-error is time-consuming [35,36]. Furthermore, when the photon counts are very low as we image the endogenous retinal fluorophores, the estimation of the statistics of the time histogram is also difficult.
Instead, with the phasor plot method, given the phase $\varphi $ and modulation m at a given angular frequency $\mathrm{\omega }$ it is possible to rapidly calculate the phase lifetime ${\tau _\varphi }$ and the modulation lifetime ${\tau _m}$ by simple formulas [37,38].
The phasor lifetime calculation is advantageous for large datasets due to its fit-free nature and faster analysis times [31,36]. In applications related to Förster resonance energy transfer (FRET) or tracking lifetime changes, the phase lifetime ${\tau _\varphi }$ has been used as a metric for determining lifetime alteration [39–43]. To simplify our analysis, the lifetime we reported in this article is phase lifetime ${\tau _\varphi }$ at a laser repetition rate of 80 MHz.
2.3 Light-dark visual cycles experimental setup
The procedure of our light-dark visual cycles experiment is illustrated in Fig. 4(a). Subjects initially were dark adapted for 30 to 35 minutes. Retina autofluorescence was monitored with our 2P-FLIO while the retina adapted to stimulation from the white light exposure and from the dark cycle. The experiment was performed in dark surroundings to prevent any unwanted stimulation to the rabbit retina. We built optical enclosures using black hardboard (XE25C9, Thorlabs) to cover the whole system and the rabbit. We collected two-photon autofluorescence lifetime images over 5 minutes at the end of each light and dark cycle interval. For our experiment, the white light power was kept at 0.5 mW and the power of the fiber-based femtosecond laser was set at 3 mW. The experimental protocol is shown below:
- (1) The selected field of view (FOV) was first exposed to the white light for 5 minutes (red lines, Fig. 4(a)).
- (2) After each exposure, the retinal autofluorescence was recorded by our 2P-FLIO for 5 minutes (blue box, Fig. 4(a)).
- (3) Following the imaging interval, the retina prep was allowed to recover in the dark for 15 minutes (dark boxes, Fig. 4(a)).
- (4) After each recovery period, the retinal autofluorescence was recorded to investigate dark cycles (blue box, Fig. 4(a)).
- (5) We will repeat the abovementioned steps to image multiple light-dark visual cycles.
2.4 Data analysis procedure with Gaussian mixture models
Here we present a new approach that leverages our 2P-FLIO excitation/detection scheme and the Gaussian Mixture Models (GMM, see Section 2.5) [33,44] to unmix fluorescence signals from multiple fluorophores in photoreceptors and retinal pigment epithelium cells based on their distinguished fluorescence lifetimes. The six-step workflow is described below, with a schematic shown in Fig. 3.
- (1) The 98 × 1 fluorescence decay curve I(t) at each pixel is separately transformed into τ phasors by Eq. (1) (Fig. 3(a)). To reduce the background effect on our phasor plot, an intensity threshold and 3 × 3 median filter are applied to the τ phasors to reduce the noise of the phasor location (Fig. 3(b)) [30,45]. When the image size is 256 × 256 pixels, this creates 256 × 256 sets of τ phasors (gτ, sτ). In other words, temporally resolved fluorescence detection at each pixel eventually leads to one τ phasor set at that pixel.
- (2) The 256 × 256 τ phasor sets (gτ, sτ) are used as inputs for the GMM (Fig. 3(b)), with initial guesses on the number of species and their associated mean phasors.
- (3) To further mitigate the effect of high background, we employ GMM algorithm (Section 2.5, SI Note 2) to cluster each pixel into one of three groups: photoreceptors, RPE cells or background (Fig. 3(d)). Subsequently, we exclude all pixels classified as background, utilizing those belonging to the photoreceptor cluster to create the photoreceptor lifetime image (Fig. 3(b), PR), and those belonging to the RPE cluster to generate the RPE lifetime image (Fig. 3(b), RPE). We note that the fluorescence signal of photoreceptors and RPE cells can still be contaminated with the decay of background components such as autofluorescence from other retinal layers. The background fluorescence introduces a displacement of the lifetime phasor plot points towards regions corresponding to longer fluorescence lifetimes on the left side of the phasor plot’s semicircle. However, the observed shift does not significantly affect the interpretation of the lifetime changes during light-dark visual cycles as our reported photoreceptors and RPE lifetimes align well with findings from other publications [6,46].
- (4) Photoreceptors are segmented using the watershed algorithm (SI Note 3) on the photoreceptor lifetime image, with mean phase lifetimes ${\tau _\varphi }$ calculated for each photoreceptor.
- (5) RPE cells are segmented using the k-nearest neighbors (KNN) algorithm on the RPE lifetime image (SI Note 4), with mean phase lifetimes ${\tau _\varphi }$ computed for each RPE cell (Fig. 3(c)).
- (6) Repeat step (1) to step (5) for each timepoint in the light-dark visual cycles experiments (t1 to t6) and then, summarize lifetime changes during light-dark visual cycles with box plot and histogram (Fig. 3(d)).
With the advantage of the fast phase lifetime ${\tau _\varphi }$ calculation, the median execution time for lifetime calculation, running the GMM unmixing and segmentation algorithms, based on 10 fields of view, is under 50 ms, meaning that our lifetime analysis can be conducted in nearly real-time following data acquisition at each FOV.
Fig. 3. Data analysis procedure with Gaussian Mixture Models. (a) The 98 × 1 fluorescence decay curve I(t) at each pixel is separately transformed into τ phasors. (b) The 256 × 256 τ phasor sets (gτ, sτ) are used as inputs for the GMM, after GMM unmixing, the corresponding clusters for photoreceptor and RPE cells are selected. (c) Photoreceptors segmentation with the watershed algorithm and RPE segmentation with the k-nearest neighbors (KNN) algorithm. (d) Summary of lifetime changes during light-dark visual cycles. Abbreviations: KNN, k-nearest neighbors algorithm; PR, photoreceptor; RPE, retinal pigment epithelium; BG, background. Scale bars are 50 µm.
2.5 Gaussian mixture models
GMM is a probabilistic model widely used for clustering tasks [47]. It posits that observed data points originate from a combination of several Gaussian distributions, each representing a distinct cluster within the data. The GMM learns parameters such as mean, covariance, and weight for each Gaussian distribution, enabling the characterization of the underlying data distribution.
For our application, we adapted the GMM to unmix fluorescence signals in live-cell imaging based on the fluorescence lifetime of retinal fluorophores [33]. The GMM assumes that the observed fluorescence lifetime phasor plot can be represented as linear combinations of Gaussian components. GMM aims to estimate the parameters (means, covariances, and weights) that best describe the observed fluorescence lifetime distribution. The estimation is done using the Expectation-Maximization (EM) algorithm [48], which iteratively maximizes the likelihood of the observed data. Each Gaussian component within the GMM corresponds to a specific fluorophore in the sample. The mean of a Gaussian component signifies the fluorescence lifetime, while the weight represents the proportion or abundance of that fluorophore in the mixture. To build up the input dataset for our GMM, the fluorescence I(t) for each pixel is transformed into τ phasors to form a vector of 2 features: (gτ, sτ) - τ phasor.
Estimating the number of distinct fluorophores in a sample is critically challenging. To address this issue, we establish an automated approach that determines the optimal number of clusters using the Bayesian Information Criterion (BIC) [49,50]. By fitting the GMM with varying numbers of clusters, we compute BIC values and select the model that best balances goodness of fit and model complexity. This automatic estimation of cluster numbers gives more flexibility to our approach. For rabbit retina preps, the BIC algorithm suggested that the model with 3 clusters offers the best balance goodness of fit and model complexity, as corresponding to autofluorescence from photoreceptors, RPE cells, and background (Fig. 3(a), (b)).
Our GMM is fitted with an EM algorithm [51,52], which iteratively estimates the parameters of the Gaussian components and assigns phasor points to clusters based on the estimated probabilities. This process continues until convergence, and the resulting model outputs the unmixing results at each pixel. Each pixel has a weight for each of the clusters/fluorophores, where the largest weight determines the assigned cluster of that pixel.
The unmixed clusters of data points within those clusters are visualized with τ phasor plots, and unmixed fluorescence lifetime image of each cluster (photoreceptors and RPE cells) (Fig. 3(b)). After the GMM, we can visualize 3 distinct unmixed gaussian distributions corresponding to photoreceptors (PR, red), retinal pigment epithelium cells (RPE, blue) and the background (BG, green). The unmixed phasor contour shows how the abovementioned gaussian distributions overlap. The comprehensive visualization allows us to intuitively assess the quality of unmixing and the accuracy of photoreceptors and RPE cells identification. The Gaussian Mixture Models Unmixing pseudocode is provided in SI Note 2.
2.6 Evaluating the correlation between photoreceptor and retinal pigment epithelium lifetimes with light-dark visual cycles in the time domain
In the time domain, the normalized cross-correlation method is employed to evaluate the similarities and correlation between photoreceptor and retinal pigment epithelium lifetime response functions (the red dashed line in Fig. 6(a), (b) and Fig. 7(a), (b)) and the light-dark exposure function (the red solid line in Fig. 6(a), (b) and Fig. 7(a), (b)). The lifetime response functions are calculated by interpolating the line equation between the mean lifetime of photoreceptors and the mean lifetime of RPE cells at two consecutive time points. We first normalized both the lifetime response function and the light-dark exposure function and then applied cross-correlation to identify the lag at which the correlation is maximized [53,54].
The cross-correlation between the lifetime response functions and light-dark exposure functions is defined as:
where E[] is the estimation operator, ${f_e}$ is the light-dark exposure function, ${f_r}$ is the lifetime response function of photoreceptor or retinal pigment epithelium, and d is the displacement in time or lag. Assuming ergodicity, for single time-limited realizations of each random process, this is determined using the integral:The cross-correlation coefficient has been calculated over the entire possible range (-75 mins to +75 mins, 75 mins for 3 light-dark cycles, Fig. 4(a)). Causality requires that the lag has a negative value. It is also expected that it should be within the period of the dark/light cycles which is 30 minutes. Therefore, we will use the cross-correlation coefficient peak (Xcorr. Peak) from 0 to -30 minutes as a correlation index. The higher the Xcorr. Peak shows stronger photoreceptor and retinal pigment lifetime response to light-dark visual cycles. The result is displayed along with the cross-correlation coefficient plot (Fig. 5, Fig. 6, Fig. 7, and Fig. 8, 3rd row).
2.7 Rabbit surgical procedure
The experimental procedures adhere to the ARVO Statement for the Use of Animals in Ophthalmic and Vision Research and were conducted under the IACUC protocol AUP-2021-00191. New Zealand White (NZW) and Dutch-Belted (DB) rabbits weighing 4 kg and 2.2 kg respectively were pre-medicated with a mixture of 5 mg/kg Ketamine and 20 mg/kg Xylazine and euthanized using 4 ml of diluted Euthasol IV. The rabbits were immediately enucleated. Each eye was then surgically prepared for imaging. A stab incision was made 3 mm posterior to the limbus using a BP #11 blade, and a 360-degree peritomy was performed using curved corneal-scleral scissors. The anterior segment, consisting of the ciliary body, lens, and cornea, was then removed, leaving an intact eye cup. The eye cup was then divided into four quadrants with the optic streak at the apex using Wescott scissors. The vitreous was surgically dissected from the anterior surface of the retina. A thin layer of vitreous was left at the inner limiting membrane interface to avoid neural-retinal detachment by sharp dissection using Wescott scissors. The retinal explants were prepared with careful attention to preserve the photoreceptor-RPE interface. Each quadrant consisting of sclera, choroid, RPE, and retina was placed on a microscope slide and a cover slip was placed on top. The retina explants were not perfused with any solution to prolong the viability of the retina during the experiment on purpose. An important endpoint of the light-dark visual cycle experiment was to observe the change in the response of the retina prep as the biochemical metabolism decreased with time. The lack of response in 4 + hour measurements supports the hypothesis that the mechanism of the fluorescence lifetime changes due to light-dark cycles is biochemical (metabolism) and not a result of the fluorescence excitation source (Section 3.4).
The full-thickness retina prep was then imaged. The hematoxylin and eosin (H&E) stain histology results shown in Fig. S1 were used to demonstrate the integrity of our retina prep, as the photoreceptors and RPE stay intact with normal cell structure.
3. Results
3.1 Retina heating induced by near-infrared lasers and white light exposure during light-dark visual cycles
Flexible thermocouple probes (IT24P; Physitemp) were mounted in rigid capillary glass, leaving 2 mm of the probe exposed at the tip (Fig. 4(a)). The maximum diameter of the probe entering the retina prep was 220 µm. The retina prep and environment temperature were recorded simultaneously with a two-channel thermometer/calibrator (CL3515R; Omega).
Thermometry in the retina prep during light-dark visual cycles: In the current study we used thermocouple probes to measure temperature changes induced by two-photon microscopy and white light exposure in the rabbit retina prep. We characterized heating as a function of two-photon laser power following each step of light-dark visual cycles (Fig. 4(b)). The thermocouple was inserted 100 µm below the retina surface using a micromanipulator. The retina prep temperature was monitored for 1.5 hours during light-dark visual cycles experiments. We performed the thermometry measurement for three laser power, 100 mW, 20 mW and 5 mW, with the white light power set at 0.5 mW.
Fig. 4. Retina heating induced by near-infrared laser and white light exposure during light-dark visual cycles. (a) Near-infrared laser (blue box) and white light exposure scheme (red line). (b) Retina’s temperature changes during light-dark visual cycles, red circle denoted white light exposure.
As shown in Fig. 4(b), with the laser power set at 100 mW, the temperature increases when exposed to two-photon excitation during imaging time and decreases to the baseline temperature when exposed to white light or resting in the dark. With the lower laser power settings (20 mW and 5 mW), we did not see significant temperature change during the light-dark visual cycles experiment. When the femtosecond laser power was set at 100 mW, the maximum temperature difference was 0.9°C. The minimum temperature difference was 0.1°C when the femtosecond laser power was set at 5 mW. Following this experiment, we set the 2P excitation laser power at 5 mW to minimize the temperature change during light-dark visual cycles.
3.2 Photoreceptor and retinal pigment epithelium lifetimes decrease and increase in sync with light-dark cycles in Dutch-belted rabbits
We collected the photoreceptors and RPE cells’ lifetime changes during light-dark visual cycles on multiple retina preps from 2 DB rabbits and 2 NZW rabbits. We follow the light-dark visual cycles experimental setup (Section 2.3) to collect 8 data sets to quantify differences between the 2 species.
We can observe that the photoreceptors’ lifetime in both DB rabbits and NZW rabbits ranges from 0.5 to 3 ns. The RPE cells have a much lower lifetime, which ranges from 0 to 1.5 ns. As shown in Fig. 5(a) and Fig. 6(a), the photoreceptor and RPE lifetimes decrease and increase in sync with light-dark cycles in Dutch-Belted rabbits’ fresh retina preps. This relationship was clearly shown in the shape of the lifetime response function of the photoreceptor (Fig. 5(a), 1st row and Fig. 6(a), 1st row) and the lifetime response function of RPE cells (Fig. 5(a), 2nd row and Fig. 6(a), 2nd row). The relationships are shown in time domain cross-correlation analysis as the correlation coefficients were higher than 0.5 for photoreceptors and higher than 0.3 for RPE cells (Fig. 5(a), 3rd row and Fig. 6(a), 3rd row).
Fig. 5. 1st Dutch-Belted rabbit - retina prep - (a) FOV 1–15 minutes after euthanized (b) FOV 2–1 hour and 45 minutes after euthanized. 1st row - Photoreceptor lifetime changes during light-dark visual cycles. 2nd row - RPE lifetime changes during light-dark visual cycles. 3rd row - Quantify photoreceptor and RPE lifetime changes during light-dark visual cycles with normalized cross-correlation in the time domain. Abbreviations: DB, Dutch-Belted rabbits, PR, photoreceptor; RPE, retinal pigment epithelium; Xcorr. Peak, time domain cross-correlation peak.
Fig. 6. 2nd Dutch-Belted rabbit - retina prep - (a) FOV 1–1 hour after euthanized (b) FOV 2–4 hours after euthanized. 1st row - Photoreceptor lifetime changes during light-dark visual cycles. 2nd row - RPE lifetime changes during light-dark visual cycles. 3rd row - Quantify photoreceptor and RPE lifetime changes during light-dark visual cycles with normalized cross-correlation in the time domain. Abbreviations: PR, photoreceptor; RPE, retinal pigment epithelium; Xcorr. Peak, time domain cross-correlation peak.
3.3 Photoreceptor and retinal pigment epithelium lifetimes gradually increase with light-dark cycles in New Zealand white rabbits
As shown in Fig. 7(a) and Fig. 8(a), the photoreceptor and retinal pigment epithelium lifetimes gradually increase with light-dark cycles in New Zealand White rabbits’ fresh retina preps. This relationship was clearly shown in the shape of the lifetime response function of the photoreceptor (Fig. 7(a), 1st row and Fig. 8(a), 1st row) and the lifetime response function of RPE cells (Fig. 7(a), 2nd row and Fig. 8(a), 2nd row). The relationships render a much lower time domain cross-correlation peak (0.1-0.3) when compared to Dutch-Belted rabbits’ fresh retina preps.
Fig. 7. 1st New Zealand White rabbit - retina prep - (a) FOV 1–30 minutes after euthanized (b) FOV 2–2 hours after euthanized. 1st row - Photoreceptor lifetime changes during light-dark visual cycles. 2nd row - RPE lifetime changes during light-dark visual cycles. 3rd row - Quantify photoreceptor and RPE lifetime changes during light-dark visual cycles with normalized cross-correlation in the time domain. Abbreviations: PR, photoreceptor; RPE, retinal pigment epithelium; Xcorr. Peak, time domain cross-correlation peak.
Fig. 8. 2nd New Zealand White rabbit - retina prep - (a) FOV 1–1 hour after euthanized (b) FOV 2–2 hours and 30 minutes after euthanized. 1st row - Photoreceptor lifetime changes during light-dark visual cycles. 2nd row - RPE lifetime changes during light-dark visual cycles. 2nd row - Quantify photoreceptor and RPE lifetime changes during light-dark visual cycles with normalized cross-correlation in the time domain. Abbreviations: PR, photoreceptor; RPE, retinal pigment epithelium; Xcorr. Peak, time domain cross-correlation peak.
3.4 Correlation between photoreceptor and retinal pigment epithelium lifetimes with light-dark visual cycles degenerate as the enucleated samples die in both Dutch-Belted rabbits and New Zealand White rabbits
As shown in Fig. 5(b), Fig. 6(b), Fig. 7(b) and Fig. 8(b), the correlation between photoreceptor and retinal pigment epithelium lifetimes with light-dark visual cycles degenerate as the enucleated samples die in both Dutch-Belted rabbits and New Zealand White rabbits. This relationship was clearly shown in the shape of the lifetime response function of photoreceptor (Fig. 5(b), Fig. 6(b), Fig. 7(b), and Fig. 8(b), 1st row) and the lifetime response function of RPE cells (Fig. 5(b), Fig. 6(b), Fig. 7(b) and Fig. 8(b), 2nd row). The relationships render a significant decrease in time domain cross-correlation peak (Fig. 5(b), Fig. 6(b), Fig. 7(b) and Fig. 8(b), 3rd row) (Table 1).
Table 1. Summary table of photoreceptor lifetime changes and RPE lifetime changes during light-dark visual cycles.
4. Discussion
The change in fluorescence lifetime with light-dark cycles was most likely due to changes in the concentrations of all-trans-retinol (AT-ROL) and all-trans-retinal (AT-RAL). The temperature changes induced by the white light exposure and the 5 mW laser were very small and the fluorescence lifetime changes due to light-dark cycles decreased significantly as the biochemical processes wound down in the retina prep. This interpretation emphasizes the central role of biochemical dynamics in modulating fluorescence lifetime changes with light-dark cycles.
After the absorption of photons by the photopigment in photoreceptors, the chromophore 11-cis-retinal undergoes isomerization into all-trans-retinal. This all-trans-retinal must be transformed back into 11-cis-retinal in order to reattach to the opsin through the visual cycle [55] (Fig. 9). This regeneration process starts with the conversion of all-trans-retinal into all-trans-retinol within the photoreceptor outer segments. Subsequently, all-trans-retinol is transported to retinal pigment epithelium (RPE) cells, where it is converted into all-trans-retinyl esters (AT-RE) and stored in retinosomes until needed. These all-trans-retinyl esters are then transformed into 11-cis-retinol (11-cis-ROL) and eventually into 11-cis-retinal (11-cis-RAL). The 11-cis-retinal is then transported to the photoreceptor outer segment to rebind with the opsin, thereby completing the visual cycle (Fig. 9 rod and cone). The fluorescence lifetimes of all-trans-retinal (AT-RAL) and all-trans-retinol (AT-ROL) differ, with AT-RAL having a shorter lifetime (56 ps for RAL Schiff base in ethanol [56]) than AT-ROL (3 ns in ethanol [57], 3.4 ns [58]). Additionally, the emission spectrum of AT-ROL is slightly shifted towards the blue compared to AT-RAL [58,59].
Fig. 9. Schematic representation of the pigment epithelium visual cycle for rod and cone photoreceptors and Müller cells. Abbreviations: ROS, rod outer segment; RIS, rod inner segment; COS, cone outer segment; CIS, cone inner segment, RPE, retinal pigment epithelium; 11-cis-RAL, 11-cis-retinal; 11-cis-ROL, 11-cis-retinol; 11-cis-RE, 11-cis- retinyl esters; AT-ROL, all-trans-retinol; AT-RAL, all-trans-retinal; AT-RE, all-trans-retinyl esters.
Cones, in addition to following the conventional visual cycle for chromophore regeneration, have an alternative pathway involving Müller cells [60] for photopigment regeneration (Fig. 9 Müller cell, Fig. S2). In this alternative cycle specific to cones, all-trans-retinol is transported to Müller cells, where it undergoes conversion into 11-cis-retinol, after which it is carried back to the cones. A unique feature of cones, as opposed to rods, is their ability to directly transform 11-cis-retinol into 11-cis-retina. This alternative mechanism stands out for its remarkable efficiency in producing the requisite 11-cis-retinal promptly, facilitating the binding with opsin to create cone photopigment [60].
The lifetime of a single fluorophore is not affected by its concentration. However, our system simultaneously detected the fluorescence signal from multiple fluorophores in photoreceptors and RPE such as AT-ROL and AT-RAL. The fluorophores are all two-photon excited by a 780 nm femtosecond laser (equivalent to 390 nm under one-photon excitation [61]), and the fluorescence emission is collected with a 500-720 nm emission. The 500-720 emission filter was selected to conduct FLIO with both 1P excitation at 470 nm and 2P excitation at 780 nm for a head-to-head comparison (SI Note 5). The lifetime we detected in each pixel will be the mean lifetime of the mixture, therefore, the concentration of the fluorophores affects our lifetime measurement.
Our findings demonstrate dynamic changes in photoreceptor lifetimes and RPE lifetimes during the light-dark visual cycles. One possible explanation for the changes that we measured is as follows:
When exposed to white light:
- • The concentration of AT-ROL inside the photoreceptor increases, while AT-RAL and 11-cis-RAL decrease [62]. Consequently, the mean lifetime of photoreceptors increases.
- • Simultaneously, a portion of the newly formed AT-ROL transfers back to the RPE, leading to an increase in RPE mean lifetime.
When left in the dark:
- • AT-ROL continues to transfer from photoreceptors to the RPE, resulting in a decrease in photoreceptor mean lifetime.
- • Additionally, the AT-ROL, which transferred back to the RPE continued to convert into AT-retinyl ester causing a corresponding decrease in RPE mean lifetime.
It is worth noting that the RPE lifetime response differs between NZW rabbits and DB rabbits. In DB rabbits, the RPE lifetime synchronizes with the light-dark visual cycles, while in NZW rabbits, the RPE lifetime continues to increase throughout these cycles.
Photoreceptors and the retinal pigment epithelium play critical roles in the visual cycle and vision. By monitoring the functional readout signature of photoreceptors and the retina, we can gain a better understanding of the mechanisms underlying age-related macular diseases. Early detection and monitoring of functional changes in the visual cycle can facilitate timely interventions and personalized treatment strategies, ultimately improving the management and prognosis of patients with AMD. Furthermore, these techniques hold promise for identifying novel therapeutic targets and evaluating the efficacy of potential interventions aimed at preserving photoreceptor function and preventing vision loss.
The next challenge will be to measure the light-dark cycle in the living eye. We have not been able to measure the light-dark cycles in live rabbit eyes using 1P excitation and low NA optics, and 2P excitation in live eyes poses significant challenges. Motion is a significant challenge and the low NA optics of the live eye make it impossible to resolve the photoreceptors without adaptive optics. Motion artifacts can be minimized by decreasing acquisition time. The 2P excitation has improved depth resolution compared with 1P excitation but the eye must be stable to realize the improved depth resolution.
5. Conclusions
In this paper, we have described a two-photon FLIM assay that measures a change in the fluorescence lifetime of endogenous fluorophores in the photoreceptors and RPE of freshly dissected rabbit retina in response to light-dark visual cycles. The measured lifetime changes are the result of both concentration variation of the photopigments and binding alteration of the photopigments to substrates in the photoreceptors and RPE, where the photopigments (i.e., endogenous fluorophores) can be AT-ROL and AT-RAL. Future studies will need to elucidate the biochemical pathways that are photobleached.
Funding
University of Texas at Austin (Texas Global Faculty Research Seed Grant); National Science Foundation (CBET 2235455); National Eye Institute (EY033106).
Acknowledgments
The authors thank Dr. Maciej Wojtkowski and Dr. Jakub Bogusławski from Institute of Physical Chemistry at Polish Academy of Sciences, for the discussion on the prism pair compressor for the femtosecond fiber laser. We also thank Dr. Lorenzo Scipioni from the Laboratory for Fluorescence Dynamics at University of California, Irvine for his input on lifetime phasor plots visualization.
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented can be obtained from the authors upon reasonable request.
Supplemental document
See Supplement 1 for supporting content.
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