Quantitative metabolomics of photoreceptor degeneration and the effects of stem cell-derived retinal pigment epithelium transplantation

Abstract

Photoreceptor degeneration is characteristic of vision-threatening diseases including age-related macular degeneration. Photoreceptors are metabolically demanding cells in the retina, but specific details about their metabolic behaviours are unresolved. The quantitative metabolomics of retinal degeneration could provide valuable insights and inform future therapies. Here, we determined the metabolomic ‘fingerprint’ of healthy and dystrophic retinas in rat models using optimized metabolite extraction techniques. A number of classes of metabolites were consistently dysregulated during degeneration: vitamin A analogues, fatty acid amides, long-chain polyunsaturated fatty acids, acyl carnitines and several phospholipid species. For the first time, a distinct temporal trend of several important metabolites including DHA (4Z,7Z,10Z,13Z,16Z,19Z-docosahexaenoic acid), all-trans-retinal and its toxic end-product N-retinyl-N-retinylidene-ethanolamine were observed between healthy and dystrophic retinas. In this study, metabolomics was further used to determine the temporal effects of the therapeutic intervention of grafting stem cell-derived retinal pigment epithelium (RPE) in dystrophic retinas, which significantly prevented photoreceptor atrophy in our previous studies. The result revealed that lipid levels such as phosphatidylethanolamine in eyes were restored in those animals receiving the RPE grafts. In conclusion, this study provides insight into the metabolomics of retinal degeneration, and further understanding of the efficacy of RPE transplantation.

This article is part of the themed issue ‘Quantitative mass spectrometry’.

1. Background

The leading cause of central vision loss in industrialized countries is age-related macular degeneration (AMD), which could be caused by ageing, smoking and obesity [1–3]. AMD is caused by dysfunction or loss of a neighbouring transporting epithelium, i.e. the retinal pigment epithelium (RPE). RPE cells physically contact the tips of photoreceptors and provide critical metabolic support, recycling light-sensitive pigments required for vision. The photoreceptors are the most numerous and metabolically demanding cells in the retina; the RPE and photoreceptors are considered to be one functional unit due to their co-dependency [4]. The risk of AMD can be reduced through low-glucose and omega-6-enriched diets. Numerous small molecules such as polyunsaturated fatty acids (PUFAs), fatty acid primary amines and amides, amino acids, vitamin A analogues, phospholipids, oxidized species and lipofuscin pigments are enriched in the outer retina. Therefore, the correct balance of these metabolites may be critical for maintaining retinal homeostasis.

A more complete understanding of metabolic pathways of retinal development and pathogenesis may be very useful for developing therapeutic interventions to prevent or slow disease progression. To date, no cure for the most common form of AMD, geographical atrophy or ‘dry’ AMD, has been identified, but it is possible that RPE transplantation could offer a promising therapeutic approach. We and others have shown that transplantation of healthy RPE cells is effective in preclinical studies to significantly, albeit transiently [5], promote photoreceptor survival in the face of RPE-mediated retinal degeneration [6–10]; clinical trials are underway to test the safety and efficacy of stem cell-derived RPE grafts in different types of retinal degeneration [11]. Whether the grafted RPE cells provide essential functional or trophic (or both) support remains unresolved. We have previously examined some of the functional effects of grafted RPE, but changes to the metabolome post transplantation have not been investigated. As retinal metabolism is greatly understudied, and the metabolic pathways that are most essential for vision and retinal homeostasis are not completely understood, we set out to perform a comprehensive metabolomic analysis of the retinal degeneration metabolome. Identification of important classes of metabolites that are important for photoreceptor survival and incorporating them into current therapeutic algorithms may have broad clinical value for treating retinal degeneration.

In this study, analyses were carried out on ocular lysates from wild-type and dystrophic rats that received RPE cell grafts to identify key metabolic changes associated with photoreceptor atrophy and potential therapeutic strategies. We also present an approach here that uses tandem mass spectral fragmentation data (i.e. neutral loss and characteristic fragment ions) combined with METLIN database mining (https://metlin.scripps.edu/index.php) to characterize an array of metabolites across multiple subclasses from the rat ocular extracts. A number of endogenous molecules were identified across the samples as potential key biomarkers of retinal degeneration. Our study not only provides data that correlate well with previous reports, but also reveals new potential candidates for biomarkers, pathological changes or potential neurotrophic agents directly associated with retinal degeneration.

2. Material and methods

(a). Chemicals and materials

N-retinyl-N-retinylidene-ethanolamine (A2E) was synthesized as previously described from ethanolamine and all-trans-retinal [12]. Briefly, a mixture of all-trans-retinal (25 mg, 88 µM) and ethanolamine (3 µl, more than 99% 38.7 µM; Sigma-Aldrich) in ethanol (1.0 ml) was stirred in the presence of acetic acid (3 µl, 52 µM) at room temperature with a sealed cap in the dark for 3 days. After the mixture was concentrated in vacuo, the residue was purified by silica gel column chromatography. 1-(9Z-octadecenoyl)-sn-glycero-3-phosphoethanolamine (PE) (18 : 1(9Z)/0 : 0) was purchased from Avanti Polar Lipids, Inc. (Alabaster, AL, USA). Liquid chromatography (LC)/mass spectrometry (MS) grade methanol, acetonitrile and water were purchased from J. T. Baker (Phillipsburg, NJ, USA). All commercially available pure standards, chloroform, formic acid and acetic acid were purchased from Sigma-Aldrich (St Louis, MO, USA).

(b). Ocular metabolite extraction and sample storage

Induced pluripotent stem (iPS) cell reprogramming with OCT4 and small molecules [13], iPS-RPE-directed differentiation [7,8,14] and subretinal injections in three-week-old rats were performed as previously described [8,15]. Royal College of Surgeons (RCS) dystrophic rats were generously provided by Dr Matthew LaVail (UCSF, San Francisco, CA, USA), and age-matched Sprague Dawley rats were obtained from Charles River Laboratories for use as wild-type controls. Whole eyes were used, n = 8–10 eyes (from four or five rats), for each time point examined (1.5, 3, 8, 11, 13 and 52 weeks). The animals were euthanized and whole eyes enucleated and placed in phosphate-buffered saline. The eyes were snap frozen with dry ice and the metabolites were extracted by grinding with an extraction solvent consisting of a mixture of methanol/chloroform/water/acetic acid (60 : 25 : 14 : 1 (v/v)), which gave a fully miscible solvent. The eye lysate was transferred into a clean 2 ml glass homogenizer (Wheaton, USA), and ground with the pestle for 30 s. Subsequently, 200 µl of cold (4°C) methanol/chloroform/water/acetic acid (60 : 25 : 14 : 1 (v/v)) was added into the tissue, and grinding was continued for 90 s. Afterwards, the homogenate was transferred to a glass vial on dry ice. Another two repeats of homogenization were carried out by adding 600 and 400 µl of extraction solvent, respectively. At the end of each repeat, the homogenizer and pestle were rinsed thoroughly and carefully to reduce the sample loss. The homogenate vial was placed into liquid nitrogen (LN) for 1 min to quench remaining chemical reactions. The vial was stored on dry ice until all samples were homogenized; homogenates were thawed on water/ice (4°C), then centrifuged in a 1.5 ml Eppendorf microcentrifuge tube for 10–15 min at 13 000 r.p.m. at 4°C. The supernatant was collected (stored at −20°C overnight is preferable but optional) in a clean vial. The combined supernatant was dried using a Speedvac without heating and reconstituted in acetonitrile/water/methanol/choloroform/formic acid (10/8/1/1/0.2 (v/v/v/v/v)) by normalization with wet tissue weight. Samples were vortexed rigorously and sonicated before being stored at 4°C for approximately 1 h. Samples were centrifuged again and the supernatant was transferred to LC vials and stored at −80°C before MS analysis.

(c). LC/MS and MS/MS analysis

Analyses were performed using an HPLC system (1260; Agilent Technologies) coupled to a 6538 UHD Accurate Mass quadrupole time-of-flight (Q-TOF) (Agilent Technologies) operated in electrospray positive (ESI+) mode. Standards or eye extracts were separated using a Waters XBridge C18, 3.5 µm, 135 Å, 150 mm × 1.0 mm i.d. The solvent system was A = 0.1% formic acid in water, and B = 0.1% formic acid in acetonitrile. The gradient elution used started with 100% A for injection at 0 min, increased to 80% A at 5 min and reached 0% A at 43 min, then decreased B from 100% to 98% from 43 to 55 min, then quickly dropped to 5% at 60 min. The flow rate was 45 µl min⁻¹ and the injection volume was 4 µl. ESI+ conditions were: gas temperature 325°C, drying gas 11 l min⁻¹, nebulizer 30 psig, fragmentor 124 V, skimmer 65 V and capillary voltage 3500 V. The instrument was set to acquire over the m/z range 80−1500 with an acquisition rate of 1.3 spectra s⁻¹. MS/MS was performed in auto mode, and the instrument was set to acquire over the m/z range 25−1500, an acquisition rate of 2 spectra s⁻¹ for MS, 1.5 spectra s⁻¹ for MS/MS with an iso-width of 1.3 m/z. MS/MS scans a maximum of five precursor ions at the same time, it stops after three scans for the same ions, and then releases after 0.4 min. The cycle time is 3.934 s. Collision energies ranged from 5 to 60 eV.

(d). Data processing and statistical analysis

In this study, we used high-resolution and accurate mass data for elemental composition prediction and relied on the tandem mass spectral fragmentation data (i.e. neutral loss and characteristic fragment ions) from METLIN (currently includes approx. 14 000 known metabolites with high-resolution tandem MS) to make identifications [16]. LC/MS data from the extracted samples of eyes were automatically processed using laboratory-developed open access bioinformatic software XCMS Online (https://xcmsonline.scripps.edu/). Pairwise analysis was conducted to compare the healthy and dystrophic retinas collected at different weeks and multi-group analysis was used to investigate the temporal changes. The Welch t-test and two-way ANOVA were used for the statistical analysis. Manual data processing including MS/MS spectra mining through extracted ion chromatograms (EICs), phospholipid data mining through precursor neutral loss chromatography (pNLC) and base peak chromatography (BPC) were conducted using Qualitative Analysis of MassHunter Workstation v.B0403 (Agilent Technologies, Santa Clara, CA, USA). In general, the mass tolerance for full scan-related spectra extraction was 10 ppm and for fragment-involved spectra was 20 ppm.

3. Results

(a). Quantitative analysis of metabolite extraction

Sample preparation is critical for optimal metabolite recovery [17,18] and should yield a reasonable number of metabolites with high coverage and reproducible chromatographic data. Various extraction methods have been developed for different types of samples for metabolomic analyses. Conventional approaches involve removing proteins/particulates from the tissue or cell samples with an organic solvent such as acetonitrile/methanol followed by quenching in LN with repeated freeze and thaw cycles. This approach was initially used to extract ocular metabolites but obtained a low yield (approx. 800 significant features by XCMS) with significant contamination from proteins. For this study, we developed an extraction approach that uses a cold (4°C) miscible cocktail of methanol/chloroform/water/acetic acid at a 60 : 25 : 14 : 1 ratio (cocktail mix). Manual grinding and homogenization of the samples in the ‘cocktail mix’ yielded a substantial number of metabolites that included both polar and non-polar species.

The utilization of methanol/chloroform at 60/25 was adapted from methods reported by Folch et al. [19] and has been successfully used for decades to extract lipophilic molecules and precipitate proteins. The addition of 1% acetic acid lowers the pH of the solvent to approximately 2 to inhibit the enzymes that catalyse metabolic reactions. Lastly, the water in the ‘cocktail mix’ (14%) was designed to enhance dissolution of polar and water-solvable metabolites (e.g. amino acids). In fact, the data from the extracted BPCs revealed that the ‘cocktail mix’ approach was more effective (yielding 6–300× higher sensitivity) and extracted more polar (retention time (RT) < 5 min) and non-polar (RT 20–60 min) species than the LN freeze and thaw method (figure 1a). Very polar compounds, i.e. hypoxanthine (figure 1b) and phenylalanine (figure 1c) that eluted at approximately 3–4 min under current LC conditions, were readily detectable using both methods. However, the lipophilic species, including lysophosphatidylcholine (16 : 0/0 : 0), palmitoyl ethanolamide and omega-3 docosahexaenoic acid (DHA) (figure 1d–f) that eluted at 24–42 min, were not readily detectable using the LN-based extraction. Additionally, retinol (also known as vitamin A) is only seen in the ‘cocktail mix’ protocol (figure 1g), indicating that the ‘cocktail mix’ with grinding technique is superior for tissue type sample metabolite extraction. This ratio of solvent mixture should be recommended for other metabolomics and/or lipidomics sample preparation from retinal tissue.

Figure 1.

(a) Quantitative LC/Q-TOF-MS base peak chromatograms of ocular metabolites extracted using the cocktail mix with grinding (black), and methanol/acetonitrile with LN freeze and thaw circles (blue). (b–g) EICs of six representative metabolites comparing MS signals using the two different extraction approaches. EA, ethanolamide; FA, formic acid; S/N, signal to noise ratio.

(b). Metabolomic analysis of retinal degeneration

Using the metabolite extraction and identification workflow, comparative quantitative metabolomics was employed to identify metabolic shifts during photoreceptor degeneration in 52-week-old RCS dystrophic rats (n = 4) compared with age-matched Sprague Dawley (wild-type) rat controls (n = 4). Significant differences between the healthy and dystrophic eyes were observed at week 3 and showed the most changes at week 52 (data not shown). LC/MS and XCMS were used to generate and align LC chromatographic peaks, and perform statistical and multivariate analyses to distinguish and compare the metabolite features (figure 2a) [20,21]. For the 52-week-old healthy and dystrophic eyes, the cloud plot showed 2150 features (without excluding isotopic peaks) that were statistically significant (p-values ≤ 0.001 and fold change ≥ 2), accounting for approximately 9% of the total number of recovered features. The number increased to 6042 when the p-value threshold was increased to 0.01. Manual inspection of chromatograms to verify those with good peak shape and high intensity reduced the number to 620. Re-analysis using LC-MS/MS and identification of the fragmentation patterns according to the METLIN MS/MS database refined the number of peaks to approximately 200. Figure 2b shows the significantly up- (green) and downregulated (red) features in diseased samples, suggesting that the dysregulated features occurred across the entire reverse-phase separation.

Figure 2.

Cloud plot of global metabolomic analyses showing up- and downregulated metabolic features comparing ocular lysates from 52-week-old wild-type and dystrophic RCS rats. (a) From the 24 000 total features observed, 2150 were found to be dysregulated with a p-value ≤ 0.001 and fold change ≥2. Features with good peak shape and high intensity (602) were subjected to MS/MS; 203 were subsequently identified. (b) The cloud plot generated by XCMS showing overlaid chromatograms of wild-type and RCS ocular lysates (n = 4/group). Green bubbles show significantly upregulated features in the RCS samples (upper panel) and red bubbles downregulated features (lower panel). The size of the circle represents fold change, colour intensity p-value, and position within the plot provides m/z and RT information.

Of the 203 metabolites identified, there were a large number in the same subclasses: 57 glycerophosphocholines (PCs and oxidized PCs), 53 glycerophosphoethanolamines (PEs and oxidized PEs), 32 long-chain acylcarnitines (ACs) and hydroxyacylcarnitines, 12 monoacylglycerols, 11 fatty acid amides, seven long-chain PUFAs, six amino acids, five bases, three retinoids and one novel glycerophosphoserine. Therefore, more than half of these compounds were phospholipids (phosphatidylethanolamines (PEs), phosphatidylcholines (PCs), phosphatidylserines (PSs)) and oxidized species. The fold changes of these compounds are shown in the electronic supplementary material, tables S1–S6. Overall, the phospholipid levels were significantly higher in the RCS rats than in the wild-type, which could imply highly activated lipid metabolism in the diseased eyes.

One interesting family of metabolites identified in this study is the ACs and reflects defects in energy homeostasis and lipid catabolism, both important for RPE function. Table 1 shows the putatively identified AC ocular species. The most abundant AC species in the eyes were acetyl- (C2 : 0), palmitoyl- (C16 : 0) and stearoylcarnitine (C18 : 0). As shown in the electronic supplementary material, table S3, most were downregulated in the dystrophic eyes collected at 52 weeks, though the fold changes were generally less than 3. Alterations in their levels were all within 20% (p < 0.01) in the 52-week rat eyes and they could be identified using multiple databases including METLIN, KEGG, Human Metabolome Database and LIPID MAPS Structure Database [29–33]. Some metabolites (e.g. AC20 : 4 and hydroxy-AC C20 : 4) could only be found in other databases of chemicals (e.g. Chemical Abstracts Service), suggesting those metabolites could also be novel identities.

Table 1.

Putatively identified AC ocular species.

common name	predicted formula	calculated m/z	observed m/z	Δppm	database ID	systematic name
C0 : 0	C7H15NO3	162.1125	162.1116	−5.6	MID52,a C00318	carnitine or l-carnitine
C2 : 0	C9H17NO4	204.1230	204.1219	−6.4	MID956,a C02571	acetylcarnitine
C3 : 0	C10H19NO4	218.1387	218.1375	−5.5	MID965, C03017	propionyl-l-carnitine
C4 : 0	C11H21NO4	232.1544	232.1537	−3.0	MID964,a C02862	isobutyryl carnitine
C5 : 0	C12H23NO4	246.1700	246.1689	−4.5	MID5367, HMDB00378	2-methylbutyroyl carnitine
C6 : 0	C13H25NO4	260.1856	260.1841	−5.8	MID3548, HMDB00705	hexanoylcarnitine
C8 : 0	C15H29NO4	288.2165	288.2155	−3.5	MID960, C02838, HMDB00791	l-octanoylcarnitine
C12 : 1	C19H35NO4	342.2639	342.2625	−4.1	HMDB13326	trans-2-dodecenoyl carnitine
C12 : 0	C19H37NO4	344.2795	344.2780	−4.4	MID6573,a HMDB02250	dodecanoyl carnitine
C14 : 1	C21H39NO4	370.2952	370.2931	−5.7	MID6437, HMDB13329	trans-2-or cis-5- tetradecenoyl carnitine
C14 : 0	C21H41NO4	372.3108	372.3088	−5.4	MID58293, HMDB05066	tetradecanoyl carnitine
C16 : 1	C23H43NO4	398.3265	398.3240	−6.3	MID58388, HMDB13207	trans-hexadec-2-enoyl carnitine
C16 : 0	C23H45NO4	400.3421	400.3398	−5.7	MID961, LMFA07070004	palmitoyl-l-carnitine
C18 : 2	C25H45NO4	424.3421	424.3395	−6.1	MID58412, HMDB06461	linoleyl carnitine
C18 : 1	C25H47NO4	426.3578	426.3558	−4.7	MID58415, HMDB06464, HMDB05065	elaidic carnitine
C18 : 0	C25H49NO4	428.3717	428.3694	−5.4	MID5811, HMDB00848, LMFA07070008	stearoylcarnitine
C20 : 4	C27H45NO4	448.3421	448.3403	−4.0	—	—
C20 : 2	C27H49NO4	452.3734	452.3711	−5.1	CAS1003003-78-8	[22]
C20 : 1	C27H51NO4	454.3891	454.3869	−4.8	CAS1003003-77-7	[22]
C20 : 0	C27H53NO	456.4047	456.4022	−5.5	MID58411, HMDB06460	arachidyl carnitine
C22 : 6	C29H45NO4	472.3421	472.3395	−5.5	MID58436, HMDB06510	cervonyl carnitine
C22 : 5	C29H47NO4	474.3578	474.3552	−5.5	MID58428, HMDB06496	clupanodonyl carnitine
C22 : 4	C29H49NO4	476.3734	476.3718	−3.4	—	—
C12 : 1OH	C19H35NO5	358.2583	358.2564	−5.3	CAS1292321-18-6	hydroxy-2-dodecenoyl carnitine [23]
C12 : 0OH	C19H37NO5	360.2744	360.2732	−3.3	CAS1292321-17-5
C14 : 1OH	C21H39NO5	386.2901	386.2888	−3.4	CAS282523-64-2	[24,25]
C16 : 2OH	C23H41NO5	412.3063	412.3045	−4.4	CAS1261030-17-4
C16 : 1OH	C23H43NO5	414.3214	414.3195	−4.6	CAS1265678-85-0	[26]
C16 : 0OH	C23H45NO5	416.3371	416.3352	−4.6	CAS1041323-14-1, 309752-61-2	hydroxypalmitoyl carnitine [24,27]
C18 : 1OH	C25H47NO5	442.3517	442.3495	−5.0	CAS863493-88-3, 309752-63-4	hydroxyoleoyl carnitine [28]
C18 : 0OH	C25H49NO5	444.3658	444.3634	−5.4	CAS309752-62-3	[27]
C20 : 4OH	C27H45NO5	464.3366	464.3342	−5.2	—	—

^aThese metabolites were confirmed with the standard MS/MS in METLIN.

Another AC, 7Z,10Z,13Z,16Z-docosatetraenoylcarnitine, was tentatively identified in this study (figure 3a). The observed m/z of 476.37 correlates with a predicted formula of C₂₉H₄₉NO₄ or C22 : 4 AC, although it could not be found in any metabolite database. The EIC and fold change (3.5) for this metabolite feature in ocular extracts from three-week-old control and RCS rats can be seen in figure 3c, and the MS/MS data for these diagnostic AC ion species is shown in figure 3d. A characteristic fragmentation pattern for this compound that included fragment ions m/z 85.028, m/z 60.081 and m/z 144.132, and an M-59.07 ion (figure 3a) was observed. These ions were entered into METLIN and searched by ‘multiple fragments’. The MS/MS spectra for the METLIN AC standards, including palmitoyl-AC (C16 : 0) (figure 3b), share these ion distributions. The structure was putatively designated as an AC with a 7Z,10Z,13Z,16Z-docosatetraenoyl acyl chain, since this chain is commonly observed in lipids and fatty acids in nature. ACs and hydroxy-ACs share the same ions except for m/z 144.132, which is m/z 145.10 in OH-ACs [34]. Unlike other ACs, C22 : 4 acylcarnitine was downregulated 3.5-fold in RCS rat eyes (three weeks) as compared with controls, but was not dysregulated in older rats. The biological relevance of this shift is unknown.

Figure 3.

(a) LC/Q-TOF MS/MS spectra of precursor ion m/z 476.37; (b) METLIN MS/MS of palmitoyl carnitine standard; (c) EIC, fold change and p-value of docosatetraenoyl carnitine in the eyes from three-week-old RCS rats. (d) Structural fragments. WT, wild-type.

(c). Differential regulation of DHA and related species

The omega-3 fatty acid DHA (4Z,7Z,10Z,13Z,16Z,19Z-DHA, C₂₂H₃₂O₂) is essential for retinal homeostasis. In this study, DHA was downregulated in the RCS dystrophic rats by 2.4-fold compared with wild-type (figure 4a) at 52 weeks. In fact, our results showed progressive loss of DHA in RCS eyes at all time points from 1.5 weeks to 52 weeks (data not shown).

Figure 4.

Dysregulation of DHA and DHA-lipids in RCS eyes. MS/MS spectra, structural fragments, EICs, fold changes and p-values (a) of DHA at 52 weeks; (b) of lysoPS (22 : 6); (c) of lysoPC (22 : 6); (d) of lysoPE (22 : 6) at three weeks. (e) MS/MS pNLC showing the abundance of all PE species in normal, RCS and contralateral RCS eyes, eight weeks post injection with iPS-RPE cells. WT, wild-type.

The alkyl chains of fatty acids are assembled into lipid structures through a lipid synthesis process. DHA is the precursor of many DHA-containing phospholipids, including PE, PC and PS. Several classes of highly enriched phospholipids in the outer segment membrane of the retina are known to be involved in free fatty acid generation, and fuel for β-oxidation in mitochondria. In this study, we identified a number of phospholipids, including the aforementioned three lysophospholipid species that contain polyunsaturated docosahexaenoyl omega-3 chains. Statistically significant (p-value < 0.005) lower levels of lysoPE (22 : 6), lysoPC (22 : 6) and lysoPS (22 : 6) were observed with a 1.3-fold, 3.2-fold and 1.6-fold change in the degenerating eyes of three-week-old RCS rats (figure 4b–d), respectively. This correlated with the parallel decrease of DHA in the diseased eyes (approx. 1.5-fold decrease at three weeks, p = 0.005). PE (22 : 6/22 : 6) and PC (22 : 6/22 : 6) were also detected at abundant levels in the eyes, which was consistent with the fact that, in the outer segments, 22 : 6n-3 accounts for 34.2% of the fatty acid in PE and 34.1% of the fatty acid in PC species [35]. The PEs are especially interesting as they could conjugate with all-trans-retinal to form different condensation (and toxic) end-products including N-retinylidene-N-retinyl-phosphatidylethanolamine (A2PE), A2-dihydropyridine-phosphatidylethanolamine (A2-DHP-PE), all-trans-retinal dimer-PE and A2E [36].

(d). Temporal trend of all-trans-retinal and N-retinyl-N-retinylidene-ethanolamine

Maintenance of the visual cycle and synthesis of toxic end-products in the eye is also of utmost clinical interest. 11-cis-retinal is a polyene chromophore that is required for vision. Light isomerizes 11-cis-retinal to generate all-trans-retinal (atRAL) in photoreceptor outer segments but must be re-isomerized in RPE cells. Dysregulation of this process results in blindness and photoreceptor degeneration [37]. The LC/MS detection of atRAL, including structure, RT, EIC and MS/MS matching with a standard, is shown in figure 5a. Consistent with the pattern of DHA degeneration, a clear temporal trend of atRAL was observed in the wild-type rats and was strongly dysregulated in RCS rats (figure 6a). The abundance of atRAL increased from 1.5 weeks to 11 weeks when photoreceptors were developing and maturing, and levels spiked during postnatal 13–52 weeks. This increase was unexpected and merits future study. In the degenerating eyes, however, the atRAL levels stayed relatively stable through week 8; then the levels steadily decreased with time, which was consistent with photoreceptor degeneration. Cumulatively, these data confirm that atRAL levels may serve as a biomarker of photoreceptor degeneration progression. The temporal trend in levels is interesting and warrants future studies since photoreceptor development is thought to be complete at earlier postnatal stages.

Figure 5.

(a) All-trans-retinal and (b) A2E: (i) structure, (ii) LC RT matching, and (iii) MS/MS spectra matching with synthetic standards.

Figure 6.

Dynamic quantitative changes of (a) A2E and (b) all-trans-retinal (atRAL) at different time points in normal rat eyes and in RCS eyes with the retinal degeneration progression. y-axis: peak area of LC/MS, x-axis: time points. Biological replicates, n = 8, ***p < 0.0001, **p < 0.001, *p < 0.01.

The inefficient clearance of atRAL can result in the formation of the A2E fluorophore, a protonated Schiff base conjugate of atRAL and PE, which accumulates with age in the AMD eye and can reach toxic levels [36]. Since its discovery, there have been intense efforts to understand the mechanisms of A2E biosynthesis and to correlate A2E levels with photoreceptor and RPE degeneration. Despite previous reports suggesting that A2E cannot be detected in RCS retinas, we consistently detected A2E (m/z 592.45) in degenerating eyes from week 3 to week 52 at very high abundance [38]. To further validate this contradictory result, we synthesized chemical standards with the same reported method [12] and ran LC-MS/MS fragmentation to verify the structural information. Interestingly, the endogenous A2E was found to have up to four iosmers instead of two as previously expected, which might be caused by the isomerization of atRAL to 13-cis-retinal under the light-exposure experimental conditions. The peak numbers, RTs and MS/MS fragmentation matched well with synthetic standards (figure 5b) that were analysed under similar settings. Additionally, the Schiff base conjugate could not be fragmented; virtually no MS/MS fragments were generated when a collision energy of less than 40 eV was used (data not shown). When the collision energy was increased to 60 eV, the molecules were fragmented and the pattern was dramatically different from that previously reported [39]. The MS/MS pattern below m/z 250 matched well with the all-trans-retinal fragments, confirming the composition of two atRAL tails in A2E. However, the MS/MS patterns of all four isomers are indistinguishable.

Furthermore, A2E levels at different time points were also relatively quantified and an interesting temporal trend of A2E was observed in the dystrophic and healthy eyes (figure 6b). Generally, the trends of A2E levels and the ratios in RCS versus wild-type were similar to those of atRAL. In the healthy eyes, an increasing accumulation of A2E was observed. The relative levels of A2E were lower in the early stages of the RCS eyes than in the wild-type (1.5 and 3 weeks); however, it increased in RCS eyes at weeks 8–13, when the level of atRAL was lower at the same ages in RCS. This might suggest that the decrease in atRAL was caused by transformation into its toxic product A2E. At the late stage (52 weeks), since the biosynthesis or uptake of atRAL in RCS decreases greatly (33-fold), it might account for the significant decrease of A2E (sevenfold) in dystrophic eyes. The decreased PEs (as mentioned earlier, figure 4d) could also affect the A2E level and further investigation is needed. To the best of our knowledge, this is the first study that showed a distinct temporal trend of atRAL and A2E between dystrophic and healthy eyes.

(e). The quantitative effect of stem cell-derived retinal pigment epithelium transplantation

At present, no treatments are available for photoreceptor degeneration in AMD patients although preclinical studies have shown that transplantation of viable stem cell-derived RPE cells can mediate anatomical and functional photoreceptor rescue in RCS rats [6–9]. While we would expect to observe increased levels of photoreceptor-specific long-chain PCs, PEs and PSs in eyes injected with stem cell-derived RPE, the effects on other classes of metabolites are more difficult to predict. In this study, the results showed that DHA-lipids can in fact be rescued by RPE transplantation. Figure 4e is a pNLC that extracted the neutral loss of 141.018 Da from MS/MS spectra of all selected precursors in the MS/MS analysis. The loss of fragment 141.018 Da is a characteristic neutral loss in MS/MS fragmentation of PE species and this identification method has been described previously [18]. Therefore, the pNLC basically shows the intensity and RT distribution of the whole PE species in the LC-MS/MS analysis. As shown in figure 4e, either the PEs contain one DHA acyl chain (PE (20 : 4/22 : 6)) or two PE chains (PE (22 : 6/22 : 6)) were very abundant in the wild-type rat eyes (black pNLC trace). While these DHA-PEs were observed to be much lower in the diseased RCS eyes (almost completely disappeared, red pNLC trace), their levels seemed to be significantly rescued in the eyes with RPE grafts (blue pNLC trace). A BPC extraction for PCs (base peak 184.073) and pNLC for PSs (neutral loss: 185.01) was conducted and the result showed again that RPE injection could also rescue those types of lipids that contain the PUFA DHA acyl chain(s) (data not shown). Those observations were consistent with the previous finding that RPE could significantly rescue the level of all-trans-retinal in the RCS eyes [8,15]. As mentioned above, we have observed that the all-trans-retinal levels dropped steadily in RCS rat eyes at time points consistent with photoreceptor degeneration. Similar to PE changes in this study, we have reported that, in the iPS-RPE transplanted eyes, all-trans-retinal levels were significantly elevated by 1.74-fold and 1.69-fold at 8 and 10 weeks post injection, respectively [8,15]. The results of these studies further illustrate that RPE transplantation also mediates metabolite rescue, adding to mounting evidence that this therapeutic intervention may represent a very effective treatment for AMD [11].

4. Summary

In this study, we applied an LC/MS global metabolomics approach to quantitatively study metabolite change in ocular samples from wild-type and RCS rats. To accomplish this, we developed an effective quantitative protocol that allowed the extraction of both polar metabolites and lipids to comprehensively cover the eye metabolome. This study revealed the dysregulation of a number of metabolites related to retinal degeneration and a distinct temporal trend of several metabolites including all-trans-retinal and DHA-related compounds. The comparisons of the metabolomes between wild-type, uninjected RCS and RCS eyes injected with RPE cells provide insight that will benefit basic research and therapeutic studies of photoreceptor degeneration. We have shown diverse classes of metabolites that are dysregulated during retinal degeneration, and exogenous RPE transplantation results in the restoration of some of these to healthy levels. Therefore, we conclude that RPE transplantation strategies are successful for promoting photoreceptor survival at least in part by enhancing nutrition for photoreceptors. Lastly, the results of these studies may inform therapeutic interventions for retinal degeneration either by identifying candidate dietary supplements to slow or prevent photoreceptor cell death or by translating the quantitative metabolic information into identifying biochemical pathways that may be commonly perturbed in various ocular diseases.

Ethics

All animals used in these studies were treated in adherence to the guidelines for ethical treatment at The Scripps Research Institute (TSRI, La Jolla, CA, USA) and according to the NIH Guide for the Care and Use of Laboratory Animals.

Data accessibility

The supporting data are available in the electronic supplementary material.

Authors' contributions

J.W. and P.D.W. contributed equally to this research. J.W. designed and performed the experiments including the metabolomic and bioinformatic analyses and co-authored the manuscript. P.D.W. generated the stem cell-derived RPE cells, performed the subretinal injections, characterized the effects, harvested the samples and co-authored the manuscript. M. Fang analysed the metabolomic data and critically revised the manuscript and co-authored the manuscript. G.S. and M. Friedlander designed the experiments, analysed the metabolomics and bioinformatics data and co-authored the manuscript. All co-authors gave final approval for this manuscript to be published.

Competing interests

We declare no financial or non-financial competing interests.

Funding

We gratefully acknowledge financial support from the National Institutes of Health (grant nos. R01 GM114368-02, R01 EY11254, R24 EY017540-04, P30 MH062261-10, P01 DA026146-02). Financial support was also received from the Lowy Medical Research Institute National Institutes and from the California Institute of Regenerative Medicine (TR1-01219). P.D.W. was supported by an NIH Ruth L. Kirschstein National Research Service Award (EY021416).