In Vivo Visualization of Intravascular Patrolling Immune Cells in the Primate Eye

Abstract

Purpose: Insight into the immune status of the living eye is essential as we seek to understand ocular disease and develop new treatments. The nonhuman primate (NHP) is the gold standard preclinical model for therapeutic development in ophthalmology, owing to the similar visual system and immune landscape in the NHP relative to the human. Here, we demonstrate the utility of phase-contrast adaptive optics scanning light ophthalmoscope (AOSLO) to visualize immune cell dynamics on the cellular scale, label-free in the NHP.

Methods: Phase-contrast AOSLO was used to image preselected areas of retinal vasculature in five NHP eyes. Images were registered to correct for eye motion, temporally averaged, and analyzed for immune cell activity. Cell counts, dimensions, velocities, and frequency per vessel were determined manually and compared between retinal arterioles and venules. Based on cell appearance and circularity index, cells were divided into three morphologies: ovoid, semicircular, and flattened.

Results: Immune cells were observed migrating along vascular endothelium with and against blood flow. Cell velocity did not significantly differ between morphology or vessel type and was independent of blow flood. Venules had a significantly higher cell frequency than arterioles. A higher proportion of cells resembled “flattened” morphology in arterioles. Based on cell speeds, morphologies, and behaviors, we identified these cells as nonclassical patrolling monocytes (NCPMs).

Conclusions: Phase-contrast AOSLO has the potential to reveal the once hidden behaviors of single immune cells in retinal circulation and can do so without the requirement of added contrast agents that may disrupt immune cell behavior.

The immune system defends against a multitude of pathogens, toxins, and even the body's own aberrant cells. It is made up of a complex and dynamic network of cells, proteins, and signaling pathways that work in concert to carry out a variety of functions, ultimately maintaining homeostasis. Understanding the immune system is not only essential for the development of novel therapeutics, but also for gaining deeper insight into various autoimmune disorders and chronic infections. 

While in vitro studies have furthered our understanding of immune system components and mechanisms, there remains an inherent limitation in truly comprehending its functionality without studying it in its natural, in vivo context. Current in vivo approaches utilize invasive surgical procedures or injectable radiotracers,¹ potentially disturbing the immune system from its native state. Few studies have successfully examined in vivo immune cell behavior noninvasively, and those which have are limited to handheld microscopy in human oral mucosal microcirculation,^2,3 third-harmonic generation microscopy combined with flow cytometry,⁴ and two-photon-induced autofluorescence in the skin.⁵ The eye provides the optimal environment to noninvasively study the immune system as it is the only transparent organ in the body.⁶ Furthermore, it is a direct extension of the central nervous system and represents a unique immune environment. Commonly described as “immune-privileged,” the eye immune response in a way that other organs do not, making it especially important to study immune interactions in this tissue.^7,8 

To visualize immune activity on the cellular scale, we incorporated phase-contrast into a custom-built adaptive optics scanning light ophthalmoscope (AOSLO).^9,10 The integration of adaptive optics and phase-contrast techniques allow for the measurement and correction of the eye’s aberrations while simultaneously enhancing the contrast of normally translucent structures.^11–13 These advancements have enabled label-free imaging of retinal erythrocytes,¹⁴ ganglion cells,¹⁵ photoreceptor inner segments,¹⁶ and most recently individual motile immune cells responding to an inflammatory stimulus in the mouse.^17,18 

This breakthrough in mouse models suggests that this approach could be adapted to visualize ocular inflammation in the human and nonhuman primate (NHP) eye. However, the numerical aperture of the primate eye is lower, reducing the contrast and resolution.¹⁹ Although the mouse offers many advantages for preclinical work, the NHP has visual and immune systems that more closely resemble that of the human.^20,21 Importantly, NHPs offer the potential to study the direct response to interventions, such as gene or cell-based therapies, at the preclinical stage to better inform clinical trials in humans. In this study, we aim to visualize immune surveillance in the NHP retina to enable more rapid adoption of this in vivo approach and demonstrate what is possible for systemic immune cell imaging in the living eye without contrast agents. 

Methods

Animal Care

All macaques in this study were maintained in an animal facility accredited by the Assessment and Accreditation of Laboratory Animal Care committee. They received attentive care from a team consisting of veterinarians, veterinary technicians, and an animal behaviorist. Their diet included a balanced chow and water available at all times, supplemented with green vegetables, trail mix, and other treats. The animals were closely monitored by animal care staff, including periodic check-ups at least twice daily. Stimulating activities were provided, such as puzzle feeders, mirrors, movies, and music in addition to a weekly novel item (treat-filled bags, eggs, maple branches, snow, etc.). Social enrichment was provided via access to a larger play space.²² This study adhered strictly to ethical guidelines, following the standards outlined in the Association for Research in Vision and Ophthalmology (ARVO) Statement for the Use of Animals, as well as the recommendations in the Guide for the Care and Use of Laboratory Animals from the National Institutes of Health. All protocols were approved by the University Committee on Animal Resources of the University of Rochester (PHS assurance number: D16-00188[A3292-01]). 

Preparation for Imaging

The macaques underwent anesthetic induction with ketamine (5–20 mg/kg), midazolam (0.25 mg/kg), and glycopyrrolate (0.017 mg/kg), followed by maintenance with 1% to 3% isoflurane mixed with supplemental oxygen. Pupils were dilated with 1 to 2 drops each of 2.5% phenylephrine hydrochloride and 1% tropicamide (Akorn Operating Co., Gurnee, IL, USA). A custom rigid gas-permeable contact lens (Oxyflow QC Paraperm O2 GP, ABB Optical Group) lubricated with genteal ointment (Alcon Laboratories, Fort Worth, TX, USA) was applied to the eye of each NHP for protection, correction of refractive error (−2 to +2 diopters), and moisture conservation. The macaque was aligned with the adaptive optics ophthalmoscope via a stereotaxic device. To minimize eye movements, the animals were administered vecuronium (60 µg/kg/h) to induce paralysis. At the conclusion of the imaging session, neostigmine (0.05 mg/kg) and glycopyrrolate (0.01 mg/kg) were administered to reverse the anesthesia. 

Experimental Design

Prior to AOSLO imaging, fundus pictures were obtained as described previously.²² Retinal locations were preselected to include vasculature that could easily be identified on fundus images, ranging between 10 degrees and 30 degrees from the foveal pit. Six-minute videos were taken in each location with minimal downtime between locations. A total of 81 fields of view (FOVs) were surveyed across 5 eyes of 4 male M. fascicularis (see Table 1, Supplementary Fig. S1 for numbers and locations of FOVs in each eye). Each imaging session ranged from 90 to 126 minutes corresponding to 10 to 16 locations in one eye per session and 30 minutes for optimization of the photomultiplier tube (PMT) for offset imaging prior to data collection. An outline of the experimental design is shown in Figure 1. 

Table 1.

 

Summary of NHPs

 

Figure 1.

 

Schematic for in vivo imaging of NHP retinal vasculature. (A) Our AOSLO system allows us to look directly into the NHP eye and focus on preselected areas of retinal vasculature, with a field-of-view of 1.5 degrees × 1.5 degrees. Retinal arterioles and venules are identified on fundus photography prior to imaging. (B) Images are acquired and processed, allowing for cell and vessel dimensions and cell velocities to be measured. Created with BioRender.com.

In Vivo Phase-Contrast Imaging

Adaptive optics phase-contrast imaging was performed using a previously described AOSLO instrument.^9,10 An 840 nm laser diode (QPhotonics, 400 uW/mm²) was used in combination with a Shack-Hartman wavefront sensor and deformable mirror (ALPAO) for measuring and correcting the optical aberrations of the eye. A 790 nm superluminescent diode (Superlum, 2 mW/mm²) was used to image the cone photoreceptor layer using a 2-airy disc (2P Reflectance Channel, 50 um) pinhole. A tunable ultrashort pulsed Ti-sapphire laser (tuned to 730 nm, 30 mW/mm², approximately 55 femtosecond, and 80 MHz repetition rate; Mai Tai, Newport Spectra-Physics) equipped with second order dispersion compensation (Deepsee, Newport Spectra-Physics) was used to concurrently image the vasculature using a three-airy disc (Reflectance channel, 75 um) pinhole. A visible light PMT with no pinhole was used to guide dispersion compensation during calibration at the start of each imaging session by detecting and maximizing two photon fluorescence. Although fluorescence was not used in the study, this allowed us to ensure peak power at the retina was consistent between animals and imaging sessions. Laser powers were calibrated prior to every imaging session to ensure consistency across sessions. Detector positions were initially optimized to the photoreceptor layer using motorized stages. The detector pinhole was then offset 10 airy discs (250 um) at an angle of 300 degrees. Adaptive optics facilitated fine focus on the vasculature at each imaging location. Images were taken with an FOV of 1.5 degrees × 1.5 degrees. 

Image Registration and Time-Lapse Analysis

A cross-correlation based approach was used to remove frame-to-frame eye motion.²³ ImageJ and Fiji (National Institutes of Health, USA) was used to create time-lapse videos (Supplementary Videos S1, S2, S3) by temporally averaging 81 frames.²⁴ Brightness and contrast were adjusted to optimize visualization for publication, but did not impact the raw data. 

Data Analysis

Following image registration, all 81 videos were temporally averaged by a factor of 27 frames and examined manually by one blinded grader for the presence of intravascular cells. Out of the 81 videos, 56 were determined to have cells and were used for further quantification and analysis. Cell counts were determined manually and any cell that appeared throughout the duration of the 6-minute video not previously accounted for contributed to the final count. Image quality was consistent across experiments included in this study. If image quality was poor at the start of the imaging session, steps were taken to troubleshoot this. If that was not possible, data collection was not pursued, which occurred for only 2 of the original 83 FOVs. Accordingly, discrepancies between videos that displayed cells and videos that did not were attributed to cell scarcity rather than poor image quality. To measure cell dimensions, the scale was first set based on each eye's axial length, determined by optical biometry (Zeiss IOLMaster 500). The built-in ImageJ line tool was then used to manually measure the length and width of each cell.²⁵ Cell length was defined as the measurement parallel to the vessel walls, whereas width was measured perpendicular to the closest vessel wall (see Fig. 1B). This definition was maintained for both cells appearing in the middle of the vessel or migrating along the vessel wall. Each measurement was taken three times and the average of the values was used in data analysis. Circularity index was measured using the built-in circularity index feature in ImageJ, which uses the formula: C = 4*π*area/perimeter^2. Values ranged from 0.297 to 0.981 with a value of 1 indicating a perfect circle. Cell morphologies were determined by the following criteria: cells which did not appear to have any flat edges and had a circularity index >0.9 were classified as ovoid, cells with one flat side and a rounded opposing side with a circularity index between 0.8 and 0.9 were classified as semicircular, and cells that had a circularity index <0.8 and appeared to have thin processes extending out from one or both sides were classified as flattened (Table 2). If a cell changed morphology during the course of the video, the cell was classified as the morphology that it spent the greatest time in. 

Table 2.

 

In Vivo Quantification of Patrolling Immune Cells Located in Primate Retinal Vasculature

 

Cell velocity was computed using the MTrackJ plugin (Biomedical Imaging Group Rotterdam, The Netherlands) to first manually track frame-by-frame cell movement.²⁶ Cell displacement was calculated based on coordinates provided from MTrackJ and then divided by the time the cell was tracked (number of frames × frame rate), yielding velocity. Cells that were stationary or were present in the video for <10 seconds were excluded from velocity measurements. 

To determine cell frequency based on vessel type, retinal arterioles and venules were identified on fundus photography prior to imaging (see Fig. 1A). The ImageJ line tool was used to measure the length of the most prominent vessel along with any visible major branches in all 81 videos (see Fig. 1B).²⁵ The average of three measurements was used as the final length. The number of cells was divided by the total length of vasculature in each respective video, yielding cell frequency. Cell frequency was grouped based on vessel type and averaged. Direction of blood flow was estimated based on the type of vessel and its relation to the optic disc. 

Statistical Analysis

Unpaired 2-sided t-tests and 1-way ANOVA were computed by Prism version 10.1.0 (Graphpad Software). All values were reported as mean ± standard deviation (SD). An alpha level of 0.05 was used as a value of statistical significance for all tests. 

Results

Using label-free phase-contrast AOSLO, we were able to image the dynamics of putative immune cells within primate retinal vasculature in real-time. In the otherwise healthy primate eyes, cells were found flowing, crawling, and adhering to the luminal endothelial walls of both arterioles and venules. We did not observe cells moving within the neural parenchyma or extravasating from retinal vessels in the five eyes that we imaged. The size, localization, speed, and behavior of these cells were consistent with patrolling monocytes. 

Whereas circulating cells may be found in a continuum of morphologies, we categorized the cells into three morphologies based on circularity index: ovoid, semicircular, and flattened. Ovoid cells were localized to the vascular endothelium and typically found moving in the same direction as blood flow (Fig. 2A, see Supplementary Video S1). The dimensions of these cells were 8.9 ± 1.5 µm × 8.3 ± 1.2 µm (n = 45; mean ± 1 SD) along the longest and shortest axes with a circularity index of 0.93 ± 0.02. Semicircular and flattened cells were found exclusively on the luminal endothelium, either adhered to or migrating along the endothelium. In some cases, semicircular and flattened cells traveled against the direction of blood flow in both arterioles and venules (see Supplementary Videos S2, S3). Semicircular cells measured to be 13.9 ± 3.1 µm × 6.3 ± 1.0 µm (n = 42; Fig. 2B, see Supplementary Video S2) with a circularity index of 0.84 ± 0.03, and flattened cells measured to be 19.4 ± 4.3 µm × 5.4 ± 0.7 µm (n = 31; Fig. 2C, see Supplementary Video S3) with a circularity index of 0.50 ± 0.11. Across all cells, the average velocity was 0.23 ± 0.11 µm/s and did not differ significantly between cell morphologies (F(2, 98) = 1.551, P = 0.2172). A summary of cell quantifications can be found in Table 2. 

Figure 2.

 

Label-free phase contrast AOSLO of various morphologies of patrolling monocytes in living primate retinal vasculature. (A) Images showing a patrolling monocyte taking on an ovoid morphology migrating along the wall of a venule at 0.26 µm/s. (B) A patrolling monocyte exhibiting a semicircular morphology moving against blood flow in a venule at 0.28 µm/s. (C) A patrolling monocyte changing from a flattened morphology to semicircular at 6 minutes. Migrating against arteriolar flow at 0.25 µm/s. Scale bars = 25 µm.

We found that venules had a significantly greater frequency of immune cells/mm of vasculature than arterioles. Venules had an average of 4.8 ± 3 cells/mm of vasculature, approximately 3.5 fold more numerous than the 1.4 ± 2 cells/mm of vasculature in arterioles (see Fig. 3A). By contrast, immune cell velocity did not differ between vessel types, with 0.23 ± 0.12 µm/s in venules and 0.24 ± 0.06 µm/s in arterioles (Fig. 3B). Among all 6 imaging sessions, approximately 50% of the cells found in arterioles had flattened morphologies, whereas only 20% of the cells were flattened in venules. The remaining 50% of cells in arterioles and 80% of cells in venules were evenly distributed between ovoid and semicircular morphologies (Fig. 3C). 

Figure 3.

 

Comparison of cell velocity and density between retinal arterioles and venules. (A) Immune cells were found to be significantly more numerous in retinal venules (M = 4.8, SD = 3) than retinal arterioles (M = 1.2, SD = 2), t(84) = 5.4, P < 0.001. Thirty-nine retinal arterioles and 47 retinal venules were measured, amassing to a total length of 18.4 mm and 20.5 mm, respectively. (B) Immune cell velocity in venules (M = 0.23, SD = 0.12) and arterioles (M = 0.24, SD = 0.06) did not significantly differ, t(99) = 0.08, P = 0.94. (C) Distribution of immune cells among ovoid, semi-circular, and flattened morphologies. ***P < 0.001; ns = not statistically significant.

Discussion

This study demonstrates that it is possible to image and characterize dynamic immune cell activity noninvasively at the cellular scale in the living NHP retina. Based on morphology, size, and behavior these cells are consistent with patrolling monocytes surveilling the vascular endothelium. These findings not only shed light on the immunological landscape of the healthy primate eye, but also hold implications for our ability to investigate the ocular immune system at the cellular scale in disease states. 

The average cell velocity in the healthy eye was 0.23 µm/s (approximately 14 µm/min), which did not depend on the type of vessel the cell was located in and was not influenced by the direction of blood flow. These speeds are notably faster than resident retinal microglia (0.02 µm/s)²⁷ but slower than rolling leukocytes responding to inflammation (5–10 µm/s).²⁸ Additionally, we found cells to measure between 8.9 and 19.4 µm along the longest axis, consistent with values obtained when nonclassical patrolling monocytes (NCPMs) are stained in murine lung tissue²⁹ and glomeruli.³⁰ Although shape is not explicitly discussed in these studies, NCPMs are observed adopting a range of morphologies,³⁰ which resemble the ovoid, semicircular, and flattened shapes we describe. These characteristics and the lack of extravasation are consistent with the archetype of the NCPMs.³¹ The NCPMs actively monitor vascular endothelium in both homeostatic and inflammatory conditions, acting as de facto tissue-resident macrophages of the vasculature. It is widely thought that these cells are anti-inflammatory, may express higher levels of adhesion-related receptor CX3CR1, and remove cellular debris.^31,32 However, an accumulation of these cells has also been linked with systemic conditions, such as atherosclerosis, lupus, and inflammatory arthritis.³¹ 

Previous studies examining murine NCPMs in vivo have relied on intravital microscopy. This approach involves the creation of a window in the skin of the animal to view the organ of interest, followed by the administration of a fluorescent label.³³ Intravital microscopy has been used to image murine vascular beds, including venules in the kidney cortex, dermal microcirculation, and carotid arteries, with cell velocities reported as 9, 17, and 36 µm/min, respectively.³² Our study imaged vessels with calibers ranging from 12 to 68 µm, comparable to that of dermal microcirculation.³⁴ Other studies involving the transfusion of fluorescently labeled human NCPMs into mice found cell velocities to be approximately 12 µm/min in microvessels regardless of the direction of blood flow.^31,35 Our study reports an average velocity of approximately 14 µm/min, consistent with NCPM activity, with the advantage of being label-free and noninvasive. 

In retinal arterioles, we found that approximately 50% of the observed patrolling cells had a flattened morphology, whereas this was true of only 20% of cells in retinal venules. It has previously been established that vascular patrolling by monocytes is a universal mechanism that occurs across all types of vessels throughout the body, yet the exact differences between patrolling in different vessel types remains unclear.³² Likewise, visualization of these specialized events in the eye has been lacking. Besides differing in the physical and biochemical makeup of their endothelial cells, arterioles and venules are also set apart by wall shear stress.^36,37 Integrins LFA-1 and VLA-4, which mediate the interaction between patrolling monocytes and vascular endothelium, vary in density based on vessel type and are found to function differently.^38,39 This may explain our findings to some degree. The vascular wall shear stress is much higher in arterioles compared to venules, necessitating a stronger interaction between patrolling monocytes and the endothelium. The flattened appearance of patrolling monocytes that we observed in arterioles may be a product of both the high wall shear stress, forcing the cells against the wall, and the additional integrins, creating stronger bonds with the endothelium. 

Many systemic conditions involving NCPMs, most notably atherosclerosis, affect retinal vasculature.⁴⁰ The degree of monocytic involvement in the development and progression of atherosclerotic plaques could now be studied on the cellular scale using our approach. Moreover, the precise role that NCPMs play in endothelial maintenance and in the recruitment of macrophages and neutrophils during inflammation can be further explored. More broadly, this method may allow label-free assessment of how the immune system reacts in chronic disease or in response to therapeutics. 

It is important to note that the eye has historically been considered “immune privileged,” and although this idea has increasingly been challenged, the ocular environment may have a different immune response compared to other tissues, requiring independent assessment. Recently, progress has been made in imaging immune activity in the human eye. Phase-contrast AOSLO has been used to image retinal microglia in patients with uveitis.^27,41 Other studies have improved AOSLO to further enhance image contrast by incorporating four-quadrant detection, combined with emboss filtering, enabling visualization of human vitreous cortex hyalocytes.⁴² Further, putative macrophage imaging has been accomplished with adaptive optics optical coherence tomography (OCT).⁴³ Yet, there remains a lack of human and non-murine animal studies examining intravascular ocular immune cell activity, an essential regulator of inflammation. Despite being under anesthesia, which may affect the measurements to a small degree,⁴⁴ the primate affords the ability to measure the temporally complex, preliminary stages of immune cell regulation, distinguish the role of patrolling monocytes, and facilitates long-term, time-lapse imaging which will be challenging in human populations. 

In summary, these first images of in vivo vascular immune surveillance in the primate eye provide a new window into baseline immune cell activity in the living body. Using phase-contrast AOSLO, we observed putative NCPMs in healthy retinal vasculature and quantified their prevalence, morphology, and motility. This approach offers the opportunity to assess the immune status of the eye, monitor outcomes in preclinical trials, and function as a clinical tool to evaluate the eye's response to inflammation. 

Acknowledgments

The authors thank Amber Walker and Jennifer LaPorta for assistance with animal care and anesthesia, Qiang Yang for his image acquisition, stabilizing, and registration software, and Rachel Hollar for assistance with fundoscopic imaging. We are grateful to Andrea Campbell and Khosha Dholakia for assistance in refining techniques used in data analysis. 

Supported by the National Eye Institute of National Institutes of Health under the AGI initiative NIH U24 EY033275 (McGregor), R01 EY028293 (Schallek), CVS core support from NIH P30 EY0001319. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Additional funding from the Steven E. Feldon Scholarship from the Flaum Eye Institute (McGregor), Genentech Inc. (Schallek), and an Unrestricted Grant to the University of Rochester Department of Ophthalmology, as well as a Career Advancement Award (Schallek) from Research to Prevent Blindness, New York, New York. 

Author Contributions: D.A. and J.E.M. designed the experiments. H.C.B., K.K., and D.A. performed the experiments and acquired data. D.A. performed data analyses and interpreted the data with some assistance from R.E.K. J.S., D.P., and C.J.C. provided critical expertise. D.A. wrote the manuscript. J.E.M., J.S., D.P., C.J.C., and H.C.B. revised the manuscript. 

Disclosure: D. Ashbery, None; H.C. Baez, None; R.E. Kanarr, None; K. Kunala, None; D. Power, None; C.J. Chu, None; J. Schallek, University of Rochester (P), Genentech (F); J.E. McGregor, None 

Supplementary Material

. A patrolling monocyte classified as ovoid in a retinal venule. 730 nm phase contrast AOSLO images showing an ovoid patrolling monocyte rolling along the venular endothelium in the same direction as blood flow at 0.26 µm/s. Images taken over the course of six minutes with 81 frame temporal averaging. Scale bar = 25 µm. 

. A patrolling monocyte classified as semi-circular in a retinal venule. 730 nm phase contrast AOSLO images with 81 frame temporal averaging showing a semi-circular patrolling monocyte migrating against venular blood flow at 0.28 µm/s. Scale bar = 25 µm. 

. A patrolling monocyte classified as flattened in a retinal arteriole. 730 nm phase contrast AOSLO images showing a flattened patrolling monocyte moving against arteriolar blood flow at 0.25 µm/s. Halfway through the video, the patrolling monocyte begins to change morphologies and appears more semi-circular. Scale bar = 25 µm.