Scientists developed a new therapeutic approach to restore light sensitivity in retinal degeneration


Humans rely dominantly on their eyesight.

Losing vision means inability to read, recognize faces or find objects. Macular degeneration is one of the major causes of visual impairment around the globe; close to 200 million people are affected.

Photoreceptors in the retina are responsible for capturing the light coming from the environment. Diseased photoreceptors lose their sensitivity to light, which can lead to impaired vision or even complete blindness.

Scientists of the Institute of Molecular and Clinical Ophthalmology Basel (IOB), together with colleagues from the German Primate Center (DPZ) – Leibniz Institute for Primate Research in Göttingen, have developed a completely new therapeutic approach based on gene therapy.

They managed to activate degenerated photoreceptors using near-infrared light.

Three-component system: Antibodies (blue), gold nanorod (gold) and heat-sensitive channel (structure in the membrane; below the antibody-gold nanorod-conjugate). Credit: Dasha Nelidova / Institute of Clinical and Molecular Ophthalamogy Basel (IOB)

The research is published in the journal Science.

During the progression of degenerative photoreceptor diseases, light-sensitive and light-insensitive photoreceptor regions in the retina coexist. For example, macular degeneration patients lose vision in the central portion of their retina, but retain peripheral eyesight.

Scientists have now succeeded in developing a new therapeutic approach to restore light sensitivity in degenerating retina without negatively affecting remaining vision. They were inspired by species such as bats and snakes that can localize near-infrared light emitted by the bodies of their preys.

This is done by using heat-sensitive ion channels that are able to detect the heat of the near-infrared light. This enables the bats and snakes to superimpose thermal and visual images in the brain and thus react to their environment with greater precision.

To equip retinal photoreceptors with near-infrared sensitivity, the researchers devised a three-component system. The first component contains engineered DNA that ensures that the gene coding for the heat-sensitive channel is only expressed in photoreceptors.

The second component is a gold nanorod, a small particle that efficiently absorbs near-infrared light. The third component is an antibody that ensures strong binding between the heat-sensitive channel expressed in photoreceptors and the gold nanorods that locally capture near-infrared light and locally release heat.

The researchers first tested their system in engineered mice with retinal degeneration, confirming that near-infrared light effectively excites photoreceptors and that this signal is transmitted to retinal ganglion cells, the latter representing the output of the retina towards higher visual centers in the brain.

Next, they showed that stimulating the mouse eye with near-infrared light is also picked up by neurons in a brain area that is important for conscious vision, the primary visual cortex.

They also designed a behavioral test in which untreated blind mice were not able to use near-infrared stimulation to learn a simple task whereas blind mice treated with the three-component system could perform the task related to near-infrared stimulus.

In collaboration with Arnold Szabo, a co-author of the paper and assistant professor at the Semmelweis University in Hungary, the researchers could test their new approach on human retinas kept alive in a culture medium for months, though blindness sets in a day or so after death as photoreceptors lose their ability to detect light.

Experimental results showed that following treatment with the three-component gene therapy method, near-infrared light exposures reactivated the human retina’s visual circuitry.

“We believe that near-infrared stimulation is an important step toward providing useful vision to blind patients so that they can regain their ability to read or see faces”, says Daniel Hillier, head of the junior research group Visual Circuits and Repair at DPZ.

“We want to give hope to blind people with these findings and will further intensify our research activities in this area here at DPZ within our main project, which focuses on the restoration of vision.”

Perimetry is a psychophysical method used to assess retinal function at various locations of the visual field and is an important component of ophthalmological practice [1]. This examination is used as a tool for detecting the progression and diagnosis of many eye diseases [2].

One perimetric technique, called microperimetry allows examiners to localize the position of the light stimulus applied to the retina and compare the visual function outcome with the underlying fundus image [3–6].

Microperimetry is an extension of classical perimetry used to localize the position of an applied stimulus by regular SLO. Therefore, it relates to the accuracy of localization rather than to the size of the target or to the extent of the visual field measured [1,7].

Further improvement of the localization was achieved by using Adaptive Optics techniques incorporated into Scanning Laser Ophthalmoscopy (AO-SLO). As it already has been demonstrated the combination of AO-SLO with an eye tracking system enables psychophysical studies to be performed on a cellular scale with microscopic precision [8–10].

Similar to standard perimetry, microperimetry permits the acquisition of information about the differential light sensitivity (DLS). DLS is the minimum luminance of a white-spot stimulus superimposed on a white background of uniform luminance.

Recently, it has been reported that inconsistencies associated with microperimetry and the analysis of DLS limit conclusions regarding the use of microperimetry in the diagnosis of many eye diseases, especially in Age Related Macular Degeneration (AMD) [11].

The perception of infrared light through two-photon (2P) excitation of visual pigments was initially demonstrated in 2014 [12].

In this process, IR light activates retinal pigments through 2P absorptions that lead to photoisomerization of the chromophore, 11-cis-retinylidene, of both rod and cone pigments.

The human macula, about 5.5 mm in diameter, represents the cone-rich, center portion of the retina [13–16]. In this region, comprised of the fovea, parafovea and perifovea, age-related retinal degeneration such as AMD as well as juvenal forms of retinal degeneration such as Stargardt disease, take place [17].

In contrast, retinitis pigmentosa (RP), a genetically inherited progressive retinal degeneration occurs in the rod-rich peripheral section of the retina [18]. The ability to measure and map the retinal function of rods and cones at predefined regions of the retina is indispensable for identifying and monitoring the progression of retinal dystrophies as well as the impact of therapeutic interventions.

We assume that the perception of infrared light through two-photon (2P) excitation of visual pigments will improve the sensitivity of microperimetry when applied to aged eyes suffering from increased optical opacities.

Near IR light is scattered less by the ocular media and is less affected by the aging process. Additionally, nonlinear optical processes like 2P excitation require delivering short pulses to well-defined regions of the outer segments of photoreceptors and therefore can be more precise in identifying dysfunctional retinal locations.

In this report, we introduce for the first time 2P microperimetry. This new method permits the measurement of IR light sensitivity in human subjects topologically as well as temporal changes in rod and cone dark adaptation. Notably, near infra-red light (IR) ranging from 700 to 1100 nm penetrates the aged front of the eye better than visible light, allowing improved simultaneous imaging and functional diagnostics in patients with age-related visual disorders.

Furthermore, we designed a novel instrument for studying 2P vision in humans using a psychophysical method. By measuring visual sensitivity thresholds in dark- and light-adapted subjects, we establish for the first time that both cone and rod mediated human IR vision is triggered by 2P absorption.

Moreover, psychometric functional studies indicated that visual sensitivity threshold measurements with visible light had a larger spread in comparison to measurements with IR. Finally, we demonstrated that visual function measurements with IR light are impacted less by lens opacities present in the aged eye, as compared to measurements with visible light.

Although 1P and 2P vision can result in almost identical vision sensations, i.e. green light perception during stimulation with either short pulses of IR at 1045 nm or 523 nm light, there are advantages for choosing an IR stimulus for microperimetry testing. Infra-red light is less absorbed and less scattered in the eye in comparison to visible light.

Experimental data from bovine eyes together with Monte Carlo simulation revealed that IR has better performance in all tested eye compartments [32]. Specifically, in the retina the photon mean free path was ∼2 times longer at 1045 nm as compared with 523 nm.

Furthermore, direct transmittances of the human lens and cornea at 523 nm decrease with age. For example, direct transmittance of the lens from a 75-year old donor is only ∼30% of that from a 4.5-year-old donor; in contrast at 1045 nm, direct transmittance of the lens from a 75-year old donor is ∼75% of that from a 4.5-year-old donor [31].

Moreover, VIS light is perceived by 1P vision, producing retinal stimulation by photons arriving at focus and out-of-focus, as well as internally reflected from other locations in the eye.

Because of the presence of eye opacities in the anterior segment of the eye, the number of out-of-focus photons can be substantial, resulting in blurred stimuli patterns on the retina. In contrast, in the case of 2P vision, the retina is stimulated near the focal plane, where the photon flux is highest.

The intensities of scattered and out-of-focus IR light are too small to induce 2P or 1P isomerization of visual pigments, resulting in smaller spread of IR visual sensitivity measurements in comparison to measurements with VIS light. Precise stimulation of individual foveal cone photoreceptors with VIS light at 543 nm can also be achieved with advanced optical instrumentation involving Adaptive Optics Scanning Laser Ophthalmoscopy (AO-SLO) and a cascade of acousto-optics modulators [33].

Currently, this method represents an excellent research tool, and also holds great potential for future routine testing of patients. Future combination of AO-SLO together with our 2P microperimetery potentially could improve stimuli delivery localization.

With a newly designed and constructed instrument for studying 2P vision we performed psychophysical tests of visual sensitivity thresholds and dark adaptation in selected retinal locations in response to IR and VIS stimuli.

Both beams, i.e. IR at 1045 nm and visible light at 523 nm were perceived as green. Furthermore, by measuring IR and VIS responses to different pulse durations of the stimuli and by measuring IR and VIS sensitivity thresholds on the variable photopic retinal illuminance backgrounds we demonstrated that a 2P process is responsible for IR vision.

Robustness and the cost efficiency of the proposed system can be optimized in the future by using compact fiber-based short pulse lasers instead of expensive solid-state femtosecond lasers. It has been already demonstrated that fiber-based lasers produce sub-picosecond pulses in the desired range of optical frequencies [34].

It is also worth mentioning that further optimization of pulse length toward longer pulses will make the system less sensitive to dispersion introduced by ocular media.

Dark adaptation measurements revealed the differences between IR and VIS stimuli. Previously, delayed rod-mediated dark adaption has been associated with early AMD [2].

Moreover, individuals with delayed rod-mediated dark adaptation were found to be twice as likely to develop AMD, 3 years after their initial evaluation as compared to those subjects without delayed dark adaptation after the same period [2].

Delay of rod-mediated dark adaptation has also been associated with retinitis pigmentosa (RP) [35]. Finally, slower rates of dark adaptation with advancing age also have been reported for cones [36,37].

Considering the dark adaptation curves presented in Fig. 3(e) and Fig. 5, the relative difference between rods and cones was smaller for two-photon induced light perception than for normal vision.

Consequently, the cone phase was relatively longer in the IR recovery plot in comparison to the VIS plot in the dark adaptation experiments. Although our experiments do not provide a conclusive explanation of this observation, this effect is likely related to the shifted spectral sensitivity of green/red cones (∼530 and 560 nm, respectively) compared to rods (500 nm), making them more likely to undergo 2P activation by 1040 nm stimulation.

Conveniently, the longer cone phase of dark adaptation should enable an expanded study of cone function with IR light. Observed differences between rod and cone plateaus in dark adaptation measurements are also evidence that perception of pulsed infrared stimuli is not simply caused by visible light produced in retinal tissue by other optical nonlinear process, e.g. second harmonic generation.

The pulsed infrared stimuli, although seen as green, was due to infrared light activating the retina by two-photon absorption.

One possible explanation of this phenomenon is based on the finding that two-photon absorption probability depends strongly on light flux density. Photoreceptors are believed to act as waveguides, however, because of differences in size and shape, cones might be more effective than rods in collecting light, especially for a two photon process that requires well-defined localization of the delivered stimulus.

It would result in higher flux density at cone outer segments than at rod outer segments. Another possible explanation is that the highest probability of absorption is different for cones and rods, meaning that the wavelength-dependent cross-section for the two photon absorption process can be different for cone opsins than for rhodopsin, considering the shifted spectral sensitivity of green/red cones (∼530 and 560 nm, respectively) compared to rods (500 nm), Hence, the efficiency of the process may vary, and it can be reflected by the difference in the relaxation times.

Furthermore, we observed preservation of the visual stimulation pattern generated with IR but not with VIS light in lens opacities mimicking age-related effects (Fig. 4).

An external file that holds a picture, illustration, etc.
Object name is boe-10-9-4551-g004.jpg
Fig. 4.
Stimulation with infrared (IR) light is impacted less than stimulation with visible light (VIS) by human eye light opacities. (a) VIS (black) and IR (red) light visual sensitivity thresholds measured in a 33-year old subject with and without diffusers are shown. Diffuser consisted of a human donor lens submerged in PBS in a quartz cuvette as shown in the inset. Filled symbols represent data obtained with the lens from a 64-year-old human donor, and unfilled symbols correspond to the lens from a 45-year old human donor. Plots were normalized by dividing the visual sensitivity threshold value, by the average sensitivity value measured without a diffuser for VIS and for IR. Error bars represent standard deviations, n = 4. (b) Shown are transmittance spectra from the 64-year old human donor lens (filled black circles), 45-year-old human donor lens (unfilled circles) and the RTV diffuser (blue line). (c-d) VIS (c) and IR (d) light intensity profiles were measured with a beam profiling camera system without and with RTV diffuser. Both: VIS and IR stimuli consisted of six vertical lines separated by 0.32 mm. VIS light stimuli were at 70 nW and IR stimuli 20 nW. Upper row insets show color scale images of beam profiles obtained without a diffuser, and images obtained with a diffuser are shown in the lower row.

Our newly developed method enabled 2P excitation of visual pigments with IR light and measurements of visual sensitivity in humans within well-defined, focal regions of the retina.

Findings presented in this manuscript demonstrate that a newly developed method and instrumentation are capable of providing new results that are unique for two photon vision and that cannot be explained by a simple extrapolation based on the existing knowledge of normal visual processing. Yet, there is further need for additional tests – for example to explain the delay in the recovery time for the cone phase observed in our IR recovery plot and differences between rod and cones in visual sensitivity thresholds and in the dark adaptation measurements.

Based on the psychophysical data presented here, the technique could be used to obtain colocalized structural and functional measurements for patients suffering from eye diseases such as AMD, RP and cataract.


1. Crossland M., Jackson M.-L., Seiple W. H., “Microperimetry: a review of fundus related perimetry,” Optometry Rep. 2(1), 2 (2012).10.4081/optometry.2012.e2 [CrossRef] [Google Scholar]

2. Owsley C., McGwin G., Clark M. E., Jackson G. R., Callahan M. A., Kline L. B., Witherspoon C. D., Curcio C. A., “Delayed Rod-Mediated Dark Adaptation Is a Functional Biomarker for Incident Early Age-Related Macular Degeneration,” Ophthalmology 123(2), 344–351 (2016).10.1016/j.ophtha.2015.09.041 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

3. Landa G., Su E., Garcia P. M., Seiple W. H., Rosen R. B., “Inner segment–outer segment junctional layer integrity and corresponding retinal sensitivity in dry and wet forms of age-related macular degeneration,” Retina 31(2), 364–370 (2011).10.1097/IAE.0b013e3181e91132 [PubMed] [CrossRef] [Google Scholar]

4. Acton J. H., Bartlett N. S., Greenstein V. C., “Comparing the Nidek MP-1 and Humphrey field analyzer in normal subjects,” Optom. Vis. Sci. 88(11), 1288–1297 (2011).10.1097/OPX.0b013e31822b3746 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

5. Chen F. K., Patel P. J., Xing W., Bunce C., Egan C., Tufail A. T., Coffey P. J., Rubin G. S., Da Cruz L., “Test–Retest Variability of Microperimetry Using the Nidek MP1 in Patients with Macular Disease,” Invest. Ophthalmol. Visual Sci. 50(7), 3464–3472 (2009).10.1167/iovs.08-2926 [PubMed] [CrossRef] [Google Scholar]

6. Rohrschneider K., Becker M., Krastel H., Kruse F., Völcker H., Fendrich T., “Static fundus perimetry using the scanning laser ophthalmoscope with an automated threshold strategy,” Graefe’s Arch. Clin. Exp. Ophthalmol. 233(12), 743–749 (1995).10.1007/BF00184084 [PubMed] [CrossRef] [Google Scholar]

7. Markowitz S. N., Reyes S. V., “Microperimetry and clinical practice: an evidence-based review,” Can. J. Ophthalmol. 48(5), 350–357 (2013).10.1016/j.jcjo.2012.03.004 [PubMed] [CrossRef] [Google Scholar]

8. Tuten W. S., Tiruveedhula P., Roorda A., “Adaptive optics scanning laser ophthalmoscope-based microperimetry,” Optom. Vis. Sci. 89(5), 563–574 (2012).10.1097/OPX.0b013e3182512b98 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

9. Sincich L. C., Zhang Y., Tiruveedhula P., Horton J. C., Roorda A., “Resolving single cone inputs to visual receptive fields,” Nat. Neurosci. 12(8), 967–969 (2009).10.1038/nn.2352 [PMC free article] [PubMed] [CrossRef] [Google Scholar]10. Rossi E. A., Roorda A., “The relationship between visual resolution and cone spacing in the human fovea,” Nat. Neurosci. 13(2), 156–157 (2010).10.1038/nn.2465 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

11. Cassels N. K., Wild J. M., Margrain T. H., Chong V., Acton J. H., “The use of microperimetry in assessing visual function in age-related macular degeneration,” Surv. Ophthalmol. 63(1), 40–55 (2018).10.1016/j.survophthal.2017.05.007 [PubMed] [CrossRef] [Google Scholar]

12. Palczewska G., Vinberg F., Stremplewski P., Bircher M. P., Salom D., Komar K., Zhang J., Cascella M., Wojtkowski M., Kefalov V. J., Palczewski K., “Human infrared vision is triggered by two-photon chromophore isomerization,” Proc. Natl. Acad. Sci. U. S. A. 111(50), E5445–E5454 (2014).10.1073/pnas.1410162111 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

13. Mustafi D., Engel A. H., Palczewski K., “Structure of cone photoreceptors,” Prog. Retinal Eye Res. 28(4), 289–302 (2009).10.1016/j.preteyeres.2009.05.003 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

14. Curcio C. A., Sloan K. R., Jr., Packer O., Hendrickson A. E., Kalina R. E., “Distribution of cones in human and monkey retina: individual variability and radial asymmetry,” Science 236(4801), 579–582 (1987).10.1126/science.3576186 [PubMed] [CrossRef] [Google Scholar]

15. Curcio C. A., Sloan K. R., Kalina R. E., Hendrickson A. E., “Human photoreceptor topography,” J. Comp. Neurol. 292(4), 497–523 (1990).10.1002/cne.902920402 [PubMed] [CrossRef] [Google Scholar]

16. Masland R. H., “The neuronal organization of the retina,” Neuron 76(2), 266–280 (2012).10.1016/j.neuron.2012.10.002 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

17. Ambati J., Fowler B. J., “Mechanisms of age-related macular degeneration,” Neuron 75(1), 26–39 (2012).10.1016/j.neuron.2012.06.018 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

18. Rivolta C., Sharon D., DeAngelis M. M., Dryja T. P., “Retinitis pigmentosa and allied diseases: numerous diseases, genes, and inheritance patterns,” Hum. Mol. Genet. 11(10), 1219–1227 (2002).10.1093/hmg/11.10.1219 [PubMed] [CrossRef] [Google Scholar]

19. LaRocca F., Dhalla A. H., Kelly M. P., Farsiu S., Izatt J. A., “Optimization of confocal scanning laser ophthalmoscope design,” J. Biomed. Opt. 18(7), 076015 (2013).10.1117/1.JBO.18.7.076015 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

20. Thomas M. M., Lamb T. D., “Light adaptation and dark adaptation of human rod photoreceptors measured from the a-wave of the electroretinogram,” J. Physiol. 518(2), 479–496 (1999).10.1111/j.1469-7793.1999.0479p.x [PMC free article] [PubMed] [CrossRef] [Google Scholar]

21. Graham C. H., Vision and visual perception (Wiley, New York, 1965), pp. vii, 637 p. [Google Scholar]

22. Treutwein B., Strasburger H., “Fitting the psychometric function,” Perception and Psychophysics 61(1), 87–106 (1999).10.3758/BF03211951 [PubMed] [CrossRef] [Google Scholar]

23. Treutwein B., “Adaptive psychophysical procedures,” Vision Res. 35(17), 2503–2522 (1995).10.1016/0042-6989(95)00016-X [PubMed] [CrossRef] [Google Scholar]

24. Bland J. M., Altman D. G., “Statistical methods for assessing agreement between two methods of clinical measurement,” Lancet 327(8476), 307–310 (1986).10.1016/S0140-6736(86)90837-8 [PubMed] [CrossRef] [Google Scholar]

25. Anastasakis A., McAnany J. J., Fishman G. A., Seiple W. H., “Clinical value, normative retinal sensitivity values, and intrasession repeatability using a combined spectral domain optical coherence tomography/scanning laser ophthalmoscope microperimeter,” Eye (London, U. K.) 25(2), 245–251 (2011).10.1038/eye.2010.158 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

26. Hunter J. D., “Matplotlib: A 2D graphics environment,” Comput. Sci. Eng. 9(3), 90–95 (2007).10.1109/MCSE.2007.55 [CrossRef] [Google Scholar]

27. World Medical A., “World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects,” JAMA 310(20), 2191–2194 (2013).10.1001/jama.2013.281053 [PubMed] [CrossRef] [Google Scholar]

28. Denk W., Strickler J. H., Webb W. W., “Two-photon laser scanning fluorescence microscopy,” Science 248(4951), 73–76 (1990).10.1126/science.2321027 [PubMed] [CrossRef] [Google Scholar]

29. Watson A. B., “QUEST plus : A general multidimensional Bayesian adaptive psychometric method,” Journal of Vision 17(3), 10 (2017).10.1167/17.3.10 [PubMed] [CrossRef] [Google Scholar]

30. Lamb T. D., Pugh E. N., Jr., “Dark adaptation and the retinoid cycle of vision,” Prog. Retinal Eye Res. 23(3), 307–380 (2004).10.1016/j.preteyeres.2004.03.001 [PubMed] [CrossRef] [Google Scholar]

31. Boettner E. A., Wolter J. R., “Transmission of the Ocular Media,” Invest. Ophthalmol. Visual Sci. 1, 776–783 (1962). [Google Scholar]

32. Hammer M., Roggan A., Schweitzer D., Muller G., “Optical-Properties of Ocular Fundus Tissues – an in-Vitro Study Using the Double-Integrating-Sphere Technique and Inverse Monte-Carlo Simulation,” Phys. Med. Biol. 40(6), 963–978 (1995).10.1088/0031-9155/40/6/001 [PubMed] [CrossRef] [Google Scholar]

33. Domdei N., Domdei L., Reiniger J. L., Linden M., Holz F. G., Roorda A., Harmening W. M., “Ultra-high contrast retinal display system for single photoreceptor psychophysics,” Biomed. Opt. Express 9(1), 157–172 (2018).10.1364/BOE.9.000157 [PMC free article] [PubMed] [CrossRef] [Google Scholar]

34. Szczepanek J., Kardas T. M., Michalska M., Radzewicz C., Stepanenko Y., “Simple all-PM-fiber laser mode-locked with a nonlinear loop mirror,” Opt. Lett. 40(15), 3500–3503 (2015).10.1364/OL.40.003500 [PubMed] [CrossRef] [Google Scholar]

35. Omar R., Herse P., “Quantification of dark adaptation dynamics in retinitis pigmentosa using non-linear regression analysis,” Clinical & Experimental Optometry 87(6), 386–389 (2004).10.1111/j.1444-0938.2004.tb03099.x [PubMed] [CrossRef] [Google Scholar]

36. Gaffney A. J., Binns A. M., Margrain T. H., “Aging and cone dark adaptation,” Optom. Vis. Sci. 89(8), 1219–1224 (2012).10.1097/OPX.0b013e318263c6b1 [PubMed] [CrossRef] [Google Scholar]

37. Coile D. C., Baker H. D., “Foveal dark adaptation, photopigment regeneration, and aging,” Vis. Neurosci. 8(1), 27–39 (1992).10.1017/S0952523800006465 [PubMed] [CrossRef] [Google Scholar]

More information: “Restoring light sensitivity using tunable near-infrared sensors” Science (2020). … 1126/science.aaz5887


Please enter your comment!
Please enter your name here

Questo sito usa Akismet per ridurre lo spam. Scopri come i tuoi dati vengono elaborati.