RGC-ADOA/ref/sciadv.adx7815/parts/sciadv.adx7815_part02.md

MALDI- TOF MS imaging

To investigate metabolomics changes in the mouse retina, MALDITOF MS imaging was performed at the MALDI MS Imaging Facility, Advanced Science Research Center, The City University of New York. Mouse eyeballs were harvested at 200 days of age, embedded in 4% CMC (no. 419273, Sigma- Aldrich) at −10°C, and snap frozen on dry ice. Cryosections (10- μm thickness) were prepared using a CryoStar NX70 (Thermo Fisher Scientific), mounted on indium tin oxide–coated slides (no. 8237001, Bruker Daltonics), and desiccated under vacuum for 30 min. Matrix deposition was performed with an HTX M5 sprayer (HTX Technologies) using 2,5- dihydroxybenzoic acid (DHB) (no. D2933, TCI Chemicals) 40 mg/ml in methanol/water, 70/30 at 85°C for 8 cycles or N - (1- naphthyl) ethylenediamine dihydrochloride (NEDC, no. 222488, Sigma- Aldrich) 10 mg/ml in isopropanol/water, 70/30 at 80°C for 30 cycles. The same spray parameters were used for both matrices: velocity of 1300 mm/min; track spacing of 2 mm; N2 pressure of 10 psi (68.95 kPa); flow rate of 3 liters/min; and nozzle height of 40 mm. Initial spectra acquisition was conducted using a MALDI- TOF MS Autoflex (Bruker Daltonics) in positive ion (DHB) or negative ion (NEDC) mode, which was calibrated with red phosphorus (no. 343242, Sigma- Aldrich). The following settings were used for both ion modes: raster width of 25 μm, laser smartbeam of “minimum,” laser frequency of 500 Hz, 500 shots per position, and mass/charge ratio ( m / z ) range of 60 to 1200. Ion images were processed using FlexImaging (v3.0) and SCiLS Lab (v2015b), normalized via root mean square, and a bin width of ±0.10 to ±0.20 according to peak width at a certain m / z . The spectra were interpreted manually, and the analytes were assigned according to a method described previously ( 106 ). To validate and extend metabolic coverage, high- resolution imaging was subsequently performed using a timsTOF fleX MALDI- 2 instrument (Bruker Daltonics) in both positive (DHB)

and negative (NEDC) ion modes. The instrument was operated with the following settings: raster width 20 μm, SmartBeam laser in “Single” mode, laser frequency 10,000 Hz, 200 shots per pixel (positive mode), 250 shots per pixel (negative mode), and an m / z acquisition range of 50 to 1000. Data were acquired using timsControl software and processed with SCiLS Lab using the same normalization strategy described above. Key metabolites were detected as follows: AMP at m / z 346.1 as [AMP- H]− , G6P at m / z 171.0 as [G6P- H]− , pyruvate at m / z 87.0 as [pyruvate- H]− , and ATP at m / z 508.0 as [ATP + H]+ . Quantification was performed within defined regions of interest in the tissue.

Hematoxylin and eosin staining

Hematoxylin and eosin staining was performed on tissue sections after MALDI imaging, to access the histology of the MALDI images. The residual matrix was removed by rinsing slides with 95% ethanol, after which the sections were stained with Hematoxylin Gill No. 1 and Eosin Y (Sigma- Aldrich) according to the manufacturer’s instructions. The stained sections were imaged using a Leica Aperio CS2 slide scanner at ×20 magnification with a 0.75–numerical aperture Plan Apo objective. These images provided anatomical context for mass spectral data, allowing the establishment of precise correlations between molecular and histological features. Quantification was performed within defined regions of interest in the tissue.

Immunostaining

To assess protein expression distribution in mouse retinal histology, immunofluorescence was performed on cryosections of mouse retinas at 360 days of age according to previously established protocols ( 100 ). Briefly, slides were prepared using mouse retinas embedded in optimal cutting temperature compound (Tissue- Tek O.C.T. Compound, Sakura Finetek). The primary and secondary antibodies listed in table S4 were used for staining. Imaging was carried out using a Zeiss LSM 900 microscope equipped with an Airyscan super- resolution image scanning system (Carl Zeiss, Germany). Z- stack images spanning 5 μm with a step size of 0.3 μm were acquired from all retinal sections. Postacquisition processing and deconvolution were performed using the Airyscan Joint Deconvolution feature in the ZEN Blue software (v3.7). Images from matched mutant and WT samples were captured during the same experimental session under identical imaging settings. The fluorescence intensity in each maximum projection image was manually segmented and quantitatively measured using the ImageJ software (https://imagej.net/ij/).

ATP measurements from mouse retinas

ATP levels were measured in the retinas using a commercially available kit [ab83355, ATP Assay Kit (Colorimetric), Abcam] according to the manufacturer’s instructions. Fresh retinal tissue from both eyes of each mouse was carefully dissected and homogenized in the assay buffer. The homogenate was centrifuged at 13,000 g for 5 min at 4°C, and the resulting supernatant was collected for protein quantification and subsequent analysis. To prevent enzyme interference in the assay, deproteinization was performed using a kit (ab204708, Deproteinizing Sample Preparation Kit, Abcam). After a 30- min incubation, the ATP assay was conducted, and optical density readings were taken at 570 nm using a microplate reader.

NAD****+** **measurements from mouse retinas

To assess the levels of NAD+ and NADH in mice, we used a commercially available kit [ab65348, NAD+ /NADH Assay Kit (Colorimetric),

Abcam] following the manufacturer’s instructions. We collected retinas from each mouse, homogenized them, and centrifuged the mixture at 14,000 g for 5 min at 4°C. Next, we transferred the supernatant to a 10- kDa spin column (ab93349, 10kD Spin Column, Abcam) and centrifuged it at 10,000 g for 20 min at 4°C. The filtrate was collected for protein quantification and the NAD assay. Optical density readings were taken at 450 nm using a microplate reader at room temperature 1 hour after the procedure.

GSH measurements from mouse retinas

Total GSH and reduced GSH levels were measured using a commercially available kit [ab239709, GSH+GSSG/GSH Assay Kit (Colorimetric), Abcam], following the manufacturer’s instructions. Retinal tissues were collected from both eyes of each mouse and homogenized in the buffer supplied with the kit. Protein quantification was conducted before adding 5% 5- sulfosalicylic acid to precipitate the proteins in the samples. Next, the reaction mix and substrate solution were added to the samples and incubated for 10 min. Optical density readings were taken at 415 nm using a microplate reader at room temperature 10 min after the procedure. The levels of GSH and GSSG were calculated on the basis of the optical density readings.

SOD measurements from mouse retinas

SOD levels were measured using a commercial kit [ab65354, Superoxide Dismutase Activity Assay Kit (Colorimetric), Abcam] following the manufacturer’s instructions. Retinal samples were homogenized in ice- cold immunoprecipitation lysis buffer (no. 87787, Thermo Fisher Scientific) that contained 1 mM phenylmethylsulfonyl fluoride protease inhibitor (no. 36978, Thermo Fisher Scientific). The homogenates were then centrifuged at 14,000 g for 5 min at 4°C, and the supernatants were collected for analysis. The SOD assay was performed by mixing the supernatant with the working solution provided in the kit, followed by incubation at 37°C for 20 min. Optical density readings were obtained at 450 nm using a microplate reader to quantify SOD activity.

Lactate measurements in mouse retinas

The levels of lactate in the retinas were measured using a commercially available kit [ab65331, l- Lactate Assay Kit (Colorimetric), Abcam] according to the manufacturer’s instructions. Fresh retinal tissue from both eyes of each mouse was carefully dissected and homogenized. The homogenate was then centrifuged at 14,000 g for 5 min at 4°C, and the resulting supernatant was collected. Deproteinization (ab204708, Deproteinizing Sample Preparation Kit, Abcam) was carried out to prevent lactate degradation by endogenous LDH. The deproteinized supernatant was then used for the assay. After a 30- min incubation at room temperature, the optical density was measured at 450 nm on a microplate reader.

Single- nucleus RNA sequencing

To investigate the impact of this Opa1 variant on the retinal transcriptomes at the single- cell level, we performed snRNA- seq on pooled frozen retinal tissues. Nucleus extraction was performed using the Miltenyi Nuclei Extraction Buffer (Miltenyi Biotec) according to the manufacturer’s guidelines. Upon isolation, the nuclei were counted using trypan blue and a Countess III Automated Cell Counter (Thermo Fisher Scientific, Waltham, MA, USA). snRNA libraries were prepared using the Chromium Single Cell 3′ kit (10x Genomics) and sequenced on an Illumina platform using standard protocols. After obtaining the sequencing data, we used Cell Ranger

(v8.0) with default parameters to generate a filtered_feature_bc_ matrix.h5 file containing cell barcodes and transcript counts for each sample. The data were aggregated using the Cell Ranger aggr program. The integrated dataset was first imported into the Rosalind platform (www.rosalind.bio/) for dimension reduction and unsupervised clustering using Cell Ranger Graph Based Clustering (10x Genomics). The dataset was then loaded into R (v4.2) and the Seurat package (v5.0) ( 107 ). Cell types were annotated using SC- type (v1.0) ( 108 ) with cell markers for major retinal cells (table S3). A pathway enrichment analysis was performed using clusterProfiler (v4.10.1) ( 109 ) with the REACTOME ( 110 ) and WikiPathways ( 111 ) databases. The results of differential gene expression analyses were visualized using heatmaps and dot plots wrapped in the Seurat package, and normalization was performed using log2 transformation. The snRNA- seq data have been deposited into the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus repository (GSE292269).

High- resolution spatial transcriptomics of the mouse retinas

Mouse eyes from 280- day WT and Opa1__V291D/+ mice were enucleated after euthanasia. Whole eyecups were fixed in 10% neutralbuffered formalin for 12 to 24 hours, dehydrated, and paraffin embedded using standard histological procedures. Retinal sections (10- μm thickness) were collected onto 10x Genomics Visium HD FFPE Spatial Gene Expression slides. Sections were deparaffinized, stained with hematoxylin and eosin, and imaged to document tissue morphology and orientation. Target retrieval, probe hybridization, and on- slide chemistry were performed according to the 10x Genomics Visium HD FFPE protocol, with minor optimizations for retinal tissue integrity. Spatial gene expression libraries were constructed per manufacturer instructions, sequenced on an Illumina platform, and processed using Space Ranger (10x Genomics) for alignment, segmentation, and feature quantification. Annotation of ganglion cell–enriched regions was done by using QuPath ( 112 ). Downstream spot- level analysis and clustering were performed in Seurat package (v5.0) ( 107 ).

Generation of RGC- specific** **MitoLbNOX overexpression in

Opa1****V291D/+** **mice

In this study, we generated Rosa26__LSL- MitoLbNOX ( LoxP- Stop- Lox[LSL]MitoLbNOX ) mice using a method similar to that used for the Rosa26__LSL- MitoTag line (JAX no. 032290, the Jackson Laboratory), which incorporates 3XHA- EGFP- OMP25 ( MitoTag cassette) into the Rosa26 locus for targeted mitochondrial EGFP expression ( 113 ). We constructed a targeting vector containing a CAG promoter, a loxP - flanked reversed neomycin cassette, an SV40 poly- adenylation sequence, and cDNA encoding MitoLbNOX from the pUC57- mito Lb NOX plasmid (Addgene plasmid no. 74448), which was linearized and targeted to intron 1 of the mouse Rosa26 gene. To achieve conditional mitoLbNOX overexpression in Opa1__V291D/+ mice, we crossed LSL- MitoLbNOX mice with Opa1__V291D/+ mice, generating Opa1__V291D/+ ; Rosa26__LSL- MitoLbNOX/+ offspring ( V291D- MitoLbNOX ). For the RGC- specific mitochondrial reporter Cre line, we created double homozygous Vglut2__Cre ; Rosa26__LSL- MitoTag ( VG2- MitoTag ) mice by crossing Vglut2- Ires- Cre mice (JAX no. 28863, the Jackson Laboratory) with MitoTag reporter mice (JAX no. 032290, the Jackson Laboratory) over two generations. Last, to compare mice with and without mitoLbNOX overexpression in the RGC of Opa1__V291D/+ mice, we crossbred V291D- MitoLbNOX mice with VG2- MitoTag mice and selected V291D- VG2- MitoTag and V291DVG2- MitoTag- MitoLbNOX offspring for experiments (Fig. 8A).

Statistical analysis

Study mice were matched for sex and age between the littermatecontrolled WT and mutant groups. Statistical analyses were conducted using GraphPad Prism (v10.4), SPSS Statistics (v21), and R (v4.2). Unpaired independent t tests or linear regression analyses were used to compare the continuous parameters between the two groups. One- way analysis of variance (ANOVA) was used for comparisons of the continuous parameters between three groups. Continuous variables are expressed as the means ± SEM in the plots. P values derived from multiple testing were corrected using the BenjaminiHochberg method. A two- tailed P value of <0.05 and a q value of <0.1 indicated statistical significance.

Supplementary Materials

The PDF file includes: Figs. S1 to S9 tables S1 to S4 legends for supplementary excel files

Other Supplementary Material for this manuscript includes the following:

Supplementary excel Files

REFERENCES

1. n. J. van Bergen, R. chakrabarti, e. c. O’neill, J. G. crowston, i. A. trounce, Mitochondrial disorders and the eye. Eye Brain 3 , 29–47 (2011).

2. P. Yu- Wai- Man, P. F. chinnery, dominant optic atrophy: novel OPA1 mutations and revised prevalence estimates. Ophthalmology 120 , 1712–1712.e1 (2013).

3. G. lenaers, c. hamel, c. delettre, P. Amati- Bonneau, v. Procaccio, d. Bonneau, P. Reynier, d. Milea, dominant optic atrophy. Orphanet J. Rare Dis. 7 , 46 (2012).

4. c. delettre, G. lenaers, J. M. Griffoin, n. Gigarel, c. lorenzo, P. Belenguer, l. Pelloquin, J. Grosgeorge, c. turc- carel, e. Perret, c. Astarie- dequeker, l. lasquellec, B. Arnaud, B. ducommun, J. Kaplan, c. P. hamel, nuclear gene OPA1 , encoding a mitochondrial

• dynamin- related protein, is mutated in dominant optic atrophy. Nat. Genet. 26 , 207–210 (2000).

5. c. Alexander, M. votruba, U. e. Pesch, d. l. thiselton, S. Mayer, A. Moore, M. Rodriguez, U. Kellner, B. leo- Kottler, G. Auburger, S. S. Bhattacharya, B. Wissinger, OPA1 , encoding a dynamin- related GtPase, is mutated in autosomal dominant optic atrophy linked to chromosome 3q28. Nat. Genet. 26 , 211–215 (2000).

6. c. delettre, J. M. Griffoin, J. Kaplan, h. dollfus, B. lorenz, l. Faivre, G. lenaers, P. Belenguer, c. P. hamel, Mutation spectrum and splicing variants in the OPA1 gene. Hum. Genet. 109 , 584–591 (2001).

7. c. Frezza, S. cipolat, O. Martins de Brito, M. Micaroni, G. v. Beznoussenko, t. Rudka, d. Bartoli, R. S. Polishuck, n. n. danial, B. de Strooper, l. Scorrano, OPA1 controls apoptotic cristae remodeling independently from mitochondrial fusion. Cell 126 , 177–189 (2006).

8. S. cipolat, O. Martins de Brito, B. dal Zilio, l. Scorrano, OPA1 requires mitofusin 1 to promote mitochondrial fusion. Proc. Natl. Acad. Sci. U.S.A. 101 , 15927–15932 (2004).

9. S. cogliati, c. Frezza, M. e. Soriano, t. varanita, R. Quintana- cabrera, M. corrado, S. cipolat, v. costa, A. casarin, l. c. Gomes, e. Perales- clemente, l. Salviati, P. Fernandez- Silva, J. A. enriquez, l. Scorrano, Mitochondrial cristae shape determines respiratory chain supercomplexes assembly and respiratory efficiency. Cell 155 , 160–171 (2013).

10. t. varanita, M. e. Soriano, v. Romanello, t. Zaglia, R. Quintana- cabrera, M. Semenzato, R. Menabò, v. costa, G. civiletto, P. Pesce, c. viscomi, M. Zeviani, F. di lisa, M. Mongillo, M. Sandri, l. Scorrano, the OPA1- dependent mitochondrial cristae remodeling pathway controls atrophic, apoptotic, and ischemic tissue damage. Cell Metab. 21 , 834–844 (2015).

11. P. Amati- Bonneau, A. Guichet, A. Olichon, A. chevrollier, F. viala, S. Miot, c. Ayuso, S. Odent, c. Arrouet, c. verny, M. n. calmels, G. Simard, P. Belenguer, J. Wang, J. l. Puel, c. hamel, Y. Malthièry, d. Bonneau, G. lenaers, P. Reynier, OPA1 R445h mutation in optic atrophy associated with sensorineural deafness. Ann. Neurol. 58 , 958–963 (2005).

12. A. Olichon, t. landes, l. Arnauné- Pelloquin, l. J. emorine, v. Mils, A. Guichet, c. delettre, c. hamel, P. Amati- Bonneau, d. Bonneau, P. Reynier, G. lenaers, P. Belenguer, effects of OPA1 mutations on mitochondrial morphology and apoptosis: Relevance to AdOA pathogenesis. J. Cell. Physiol. 211 , 423–430 (2007).

13. A. chevrollier, v. Guillet, d. loiseau, n. Gueguen, M. A. de crescenzo, c. verny, M. Ferre, h. dollfus, S. Odent, d. Milea, c. Goizet, P. Amati- Bonneau, v. Procaccio, d. Bonneau, P. Reynier, hereditary optic neuropathies share a common mitochondrial coupling defect. Ann. Neurol. 63 , 794–798 (2008).

14. M. Zaninello, K. Palikaras, d. naon, K. iwata, S. herkenne, R. Quintana- cabrera,

• M. Semenzato, F. Grespi, F. n. Ross- cisneros, v. carelli, A. A. Sadun, n. tavernarakis, l. Scorrano, inhibition of autophagy curtails visual loss in a model of autosomal dominant optic atrophy. Nat. Commun. 11 , 4029 (2020).

15. P. Yu- Wai- Man, P. G. Griffiths, P. F. chinnery, Mitochondrial optic neuropathies–disease mechanisms and therapeutic strategies. Prog. Retin. Eye Res. 30 , 81–114 (2011).

16. e. Y. Kang, P. K. liu, Y. t. Wen, P. M. J. Quinn, S. R. levi, n. K. Wang, R. K. tsiai, Role of oxidative stress in ocular diseases associated with retinal ganglion cells degeneration. Antioxidants 10 , 1948 (2021).

17. v. J. davies, A. J. hollins, M. J. Piechota, W. Yip, J. R. davies, K. e. White, P. P. nicols, M. e. Boulton, M. votruba, Opa1 deficiency in a mouse model of autosomal dominant optic atrophy impairs mitochondrial morphology, optic nerve structure and visual function. Hum. Mol. Genet. 16 , 1307–1318 (2007).

18. S. Sun, i. erchova, F. Sengpiel, M. votruba, Opa1 deficiency leads to diminished mitochondrial bioenergetics with compensatory increased mitochondrial motility. Invest. Ophthalmol. Vis. Sci. 61 , 42 (2020).

19. P. A. Williams, J. e. Morgan, M. votruba, Opa1 deficiency in a mouse model of dominant optic atrophy leads to retinal ganglion cell dendropathy. Brain 133 , 2942–2951 (2010).

20. Y. Kushnareva, Y. Seong, A. Y. Andreyev, t. Kuwana, W. B. Kiosses, M. votruba, d. d. newmeyer, Mitochondrial dysfunction in an Opa1Q285StOP mouse model of dominant optic atrophy results from Opa1 haploinsufficiency. Cell Death Dis. 7 , e2309 (2016).

21. e. Sarzi, c. Angebault, M. Seveno, n. Gueguen, B. chaix, G. Bielicki, n. Boddaert, A. l. Mausset- Bonnefont, c. cazevieille, v. Rigau, J. P. Renou, J. Wang, c. delettre, P. Brabet, J. l. Puel, c. P. hamel, P. Reynier, G. lenaers, the human OPA1__delTTAG mutation induces premature age- related systemic neurodegeneration in mouse. Brain 135 , 3599–3613 (2012).

22. e. Sarzi, M. Seveno, c. Piro- Mégy, l. elzière, M. Quilès, M. Péquignot, A. Müller, c. P. hamel, G. lenaers, c. delettre, OPA1 gene therapy prevents retinal ganglion cell loss in a dominant Optic Atrophy mouse model. Sci. Rep. 8 , 2468 (2018).

23. M. v. Alavi, S. Bette, S. Schimpf, F. Schuettauf, U. Schraermeyer, h. F. Wehrl, l. Ruttiger, S. c. Beck, F. tonagel, B. J. Pichler, M. Knipper, t. Peters, J. laufs, B. Wissinger, A splice site mutation in the murine Opa1 gene features pathology of autosomal dominant optic atrophy. Brain 130 , 1029–1042 (2007).

24. clinvar (national library of Medicine); www.ncbi.nlm.nih.gov/clinvar/?term=OPA1[all].

25. lOvdv3.0 (leiden University Medical center); https://databases.lovd.nl/shared/genes/ OPA1.

26. t. Ozaki, S. Utsumi, t. iwamoto, M. tanaka, h. tomita, e. Sugano, e. ishiyama, K. ishida, data on mitochondrial ultrastructure of photoreceptors in pig, rabbit, and mouse retinas. Data Brief 30 , 105544 (2020).

27. J. Kouassi nzoughet, J. M. chao de la Barca, K. Guehlouz, S. leruez, l. coulbault, S. Allouche, c. Bocca, J. Muller, P. Amati- Bonneau, P. Gohier, d. Bonneau, G. Simard, d. Milea, G. lenaers, v. Procaccio, P. Reynier, nicotinamide deficiency in primary open- angle glaucoma. Invest. Ophthalmol. Vis. Sci. 60 , 2509–2514 (2019).

28. c. Bocca, M. S. Kane, c. veyrat- durebex, S. chupin, J. Alban, J. Kouassi nzoughet, M. le Mao, J. M. chao de la Barca, P. Amati- Bonneau, d. Bonneau, v. Procaccio, G. lenaers, G. Simard, A. chevrollier, P. Reynier, the metabolomic bioenergetic signature of Opa1 - disrupted mouse embryonic fibroblasts highlights aspartate deficiency. Sci. Rep. 8 , 11528 (2018).

29. G. lenaers, A. neutzner, Y. le dantec, c. Jüschke, t. Xiao, S. decembrini, S. Swirski, S. Kieninger, c. Agca, U. S. Kim, P. Reynier, P. Yu- Wai- Man, J. neidhardt, B. Wissinger, dominant optic atrophy: culprit mitochondria in the optic nerve. Prog. Retin. Eye Res. 83 , 100935 (2021).

30. J. R. tribble, A. Otmani, S. Sun, S. A. ellis, G. cimaglia, R. vohra, M. Jöe, e. lardner, A. P. venkataraman, A. domínguez- vicent, e. Kokkali, S. Rho, G. Jóhannesson, R. W. Burgess, P. G. Fuerst, R. Brautaset, M. Kolko, J. e. Morgan, J. G. crowston, M. votruba, P. A. Williams, nicotinamide provides neuroprotection in glaucoma by protecting against mitochondrial and metabolic dysfunction. Redox Biol. 43 , 101988 (2021).

31. B. Petriti, P. A. Williams, G. lascaratos, K. Y. chau, d. F. Garway- heath, neuroprotection in glaucoma: nAd+ /nAdh redox state as a potential biomarker and therapeutic target. Cells 10 , 1402 (2021).

32. l. R. Stein, S. imai, the dynamic regulation of nAd metabolism in mitochondria. Trends Endocrinol. Metab. 23 , 420–428 (2012).

33. P. A. Williams, J. M. harder, n. e. Foxworth, K. e. cochran, v. M. Philip, v. Porciatti, O. Smithies, S. W. John, vitamin B3 modulates mitochondrial vulnerability and prevents glaucoma in aged mice. Science 355 , 756–760 (2017).

34. F. Fang, P. Zhuang, X. Feng, P. liu, d. liu, h. huang, l. li, W. chen, l. liu, Y. Sun, h. Jiang, J. Ye, Y. hu, nMnAt2 is downregulated in glaucomatous RGcs, and RGc- specific gene therapy rescues neurodegeneration and visual function. Mol. Ther. 30 , 1421–1431 (2022).

35. P. A. Williams, J. M. harder, n. e. Foxworth, B. h. cardozo, K. e. cochran, S. W. M. John, nicotinamide and WldS act together to prevent neurodegeneration in glaucoma. Front. Neurosci. 11 , 232 (2017).

36. J. Bureau, F. Manero, O. Baris, A. Bodin, c. verny, A. chevrollier, G. lenaers, P. codron, Opa1 and Mt- nd6 mutations induce early mitochondrial changes in the retina and prelaminar optic nerve of hereditary optic neuropathy mouse models. Brain Commun. 6 , fcae404 (2024).

37. S. c. Payne, c. A. Bartlett, A. R. harvey, S. A. dunlop, M. Fitzgerald, Myelin sheath decompaction, axon swelling, and functional loss during chronic secondary degeneration in rat optic nerve. Invest. Ophthalmol. Vis. Sci. 53 , 6093–6101 (2012).

38. J. lavie, h. de Belvalet, S. Sonon, A. M. ion, e. dumon, S. Melser, d. lacombe, J. W. dupuy, c. lalou, G. Bénard, Ubiquitin- dependent degradation of mitochondrial proteins regulates energy metabolism. Cell Rep. 23 , 2852–2863 (2018).

39. v. del dotto, P. Mishra, S. vidoni, M. Fogazza, A. Maresca, l. caporali, J. M. Mccaffery, M. cappelletti, e. Baruffini, G. lenaers, d. chan, M. Rugolo, v. carelli, c. Zanna, OPA1 isoforms in the hierarchical organization of mitochondrial functions. Cell Rep. 19 , 2557–2571 (2017).

40. R. Acin- Perez, i. Y. Benador, A. Petcherski, M. veliova, G. A. Benavides, S. lagarrigue, A. caudal, l. vergnes, A. n. Murphy, G. Karamanlidis, R. tian, K. Reue, J. Wanagat, h. Sacks, F. Amati, v. M. darley- Usmar, M. liesa, A. S. divakaruni, l. Stiles, O. S. Shirihai, A novel approach to measure mitochondrial respiration in frozen biological samples. EMBO J. 39 , e104073 (2020).

41. c. Osto, i. Y. Benador, J. ngo, M. liesa, l. Stiles, R. Acin- Perez, O. S. Shirihai, Measuring mitochondrial respiration in previously frozen biological samples. Curr. Protoc. Cell Biol. 89 , e116 (2020).

42. l. Fernandez- del- Rio, c. Benincá, F. villalobos, c. Shu, l. Stiles, M. liesa, A. S. divakaruni, R. Acin- Perez, O. S. Shirihai, A novel approach to measure complex v AtP hydrolysis in frozen cell lysates and tissue homogenates. Life Sci. Alliance 6 , e202201628 (2023).

43. c. n. Okoye, S. A. Koren, A. P. Wojtovich, Mitochondrial complex i ROS production and redox signaling in hypoxia. Redox Biol. 67 , 102926 (2023).

44. l. trachsel- Moncho, S. Benlloch- navarro, Á. Fernández- carbonell, d. t. Ramírez- lamelas, t. Olivar, d. Silvestre, e. Poch, M. Miranda, Oxidative stress and autophagy- related changes during retinal degeneration and development. Cell Death Dis. 9 , 812 (2018).

45. J. B. hurley, K. J. lindsay, J. du, Glucose, lactate, and shuttling of metabolites in vertebrate retinas. J. Neurosci. Res. 93 , 1079–1092 (2015).

46. h. liu, v. Prokosch, energy metabolism in the inner retina in health and glaucoma. Int. J. Mol. Sci. 22 , 3689 (2021).

47. A. O. chertov, l. holzhausen, i. t. Kuok, d. couron, e. Parker, J. d. linton, M. Sadilek, i. R. Sweet, J. B. hurley, Roles of glucose in photoreceptor survival. J. Biol. Chem. 286 , 34700–34711 (2011).

48. W. W. Pan, t. J. Wubben, c. G. Besirli, Photoreceptor metabolic reprogramming: current understanding and therapeutic implications. Commun. Biol. 4 , 245 (2021).

49. F. M. nadal- nicolás, c. Galindo- Romero, F. lucas- Ruiz, n. Marsh- Amstrong, W. li, M. vidal- Sanz, M. Agudo- Barriuso, Pan- retinal ganglion cell markers in mice, rats, and rhesus macaques. Zool. Res. 44 , 226–248 (2023).

50. n. M. tran, K. Shekhar, i. e. Whitney, A. Jacobi, i. Benhar, G. hong, W. Yan, X. Adiconis, M. e. Arnold, J. M. lee, J. Z. levin, d. lin, c. Wang, c. M. lieber, A. Regev, Z. he, J. R. Sanes, Single- cell profiles of retinal ganglion cells differing in resilience to injury reveal neuroprotective genes. Neuron 104 , 1039–1055.e12 (2019).

51. d. v. titov, v. cracan, R. P. Goodman, J. Peng, Z. Grabarek, v. K. Mootha, complementation of mitochondrial electron transport chain by manipulation of the nAd+ /nAdh ratio. Science 352 , 231–235 (2016).

52. Y. dong, M. A. digman, G. J. Brewer, Age- and Ad- related redox state of nAdh in subcellular compartments by fluorescence lifetime imaging microscopy. Geroscience 41 , 51–67 (2019).

53. t. liufu, h. Yu, J. Yu, M. Yu, Y. tian, Y. Ou, J. deng, G. Xing, Z. Wang, complex i deficiency in m.3243A>G fibroblasts is alleviated by reducing nAdh accumulation. Front. Physiol. 14 , 1164287 (2023).

54. v. del dotto, M. Fogazza, F. Musiani, A. Maresca, S. J. Aleo, l. caporali, c. la Morgia, c. nolli, t. lodi, P. Goffrini, d. chan, v. carelli, M. Rugolo, e. Baruffini, c. Zanna, deciphering OPA1 mutations pathogenicity by combined analysis of human, mouse and yeast cell models. Biochim. Biophys. Acta Mol. Basis Dis. 1864 , 3496–3514 (2018).

55. J. P. harvey, P. Yu- Wai- Man, M. e. cheetham, characterisation of a novel OPA1 splice variant resulting in cryptic splice site activation and mitochondrial dysfunction. Eur. J. Hum. Genet. 30 , 848–855 (2022).

56. P. Yu- Wai- Man, P. G. Griffiths, G. S. Gorman, c. M. lourenco, A. F. Wright, M. Auer- Grumbach, A. toscano, O. Musumeci, M. l. valentino, l. caporali, c. lamperti, c. M. tallaksen, P. duffey, J. Miller, R. G. Whittaker, M. R. Baker, M. J. Jackson, M. P. clarke, B. dhillon, B. czermin, J. d. Stewart, G. hudson, P. Reynier, d. Bonneau, W. Marques Jr., G. lenaers, R. McFarland, R. W. taylor, d. M. turnbull, M. votruba, M. Zeviani, v. carelli, l. A. Bindoff, R. horvath, P. Amati- Bonneau, P. F. chinnery, Multi- system neurological disease is common in patients with OPA1 mutations. Brain 133 , 771–786 (2010).

57. d. c. S. Wong, J. P. harvey, n. Jurkute, S. M. thomasy, M. Moosajee, P. Yu- Wai- Man, M. J. Gilhooley, OPA1 dominant optic atrophy: Pathogenesis and therapeutic targets. J. Neuroophthalmol. 43 , 464–474 (2023).

58. v. carelli, O. Musumeci, l. caporali, c. Zanna, c. la Morgia, v. del dotto, A. M. Porcelli, M. Rugolo, M. l. valentino, l. iommarini, A. Maresca, P. Barboni, M. carbonelli, c. trombetta, e. M. valente, S. Patergnani, c. Giorgi, P. Pinton, G. Rizzo, c. tonon, R. lodi, P. Avoni, R. liguori, A. Baruzzi, A. toscano, M. Zeviani, Syndromic parkinsonism and dementia associated with OPA1 missense mutations. Ann. Neurol. 78 , 21–38 (2015).

59. B. cartes- Saavedra, d. lagos, J. Macuada, d. Arancibia, F. Burté, M. K. Sjöberg- herrera, M. e. Andrés, R. horvath, P. Yu- Wai- Man, G. hajnóczky, v. eisner, OPA1 disease- causing mutants have domain- specific effects on mitochondrial ultrastructure and fusion. Proc. Natl. Acad. Sci. U.S.A. 120 , e2207471120 (2023).

60. S. caglayan, A. hashim, A. cieslar- Pobuda, v. Jensen, S. Behringer, B. talug, d. t. chu, c. Pecquet, M. Rogne, A. Brech, S. h. Brorson, e. A. nagelhus, l. hannibal, A. Boschi, K. taskén, J. Staerk, Optic atrophy 1 controls human neuronal development by preventing aberrant nuclear dnA methylation. iScience 23 , 101154 (2020).

61. M. liesa, O. S. Shirihai, Mitochondrial dynamics in the regulation of nutrient utilization and energy expenditure. Cell Metab. 17 , 491–506 (2013).

62. M. t. couvillion, i. c. Soto, G. Shipkovenska, l. S. churchman, Synchronized mitochondrial and cytosolic translation programs. Nature 533 , 499–503 (2016).

63. d. G. hardie, F. A. Ross, S. A. hawley, AMPK: A nutrient and energy sensor that maintains energy homeostasis. Nat. Rev. Mol. Cell Biol. 13 , 251–262 (2012).

64. P. M. Quirós, A. Mottis, J. Auwerx, Mitonuclear communication in homeostasis and stress. Nat. Rev. Mol. Cell Biol. 17 , 213–226 (2016).

65. l. W. Finley, M. c. haigis, the coordination of nuclear and mitochondrial communication during aging and calorie restriction. Ageing Res. Rev. 8 , 173–188 (2009).

66. d. Mastroeni, O. M. Khdour, e. delvaux, J. nolz, G. Olsen, n. Berchtold, c. cotman, S. M. hecht, P. d. coleman, nuclear but not mitochondrial- encoded oxidative phosphorylation genes are altered in aging, mild cognitive impairment, and Alzheimer’s disease. Alzheimers Dement. 13 , 510–519 (2017).

67. e. A. Schon, G. Manfredi, neuronal degeneration and mitochondrial dysfunction. J. Clin. Invest. 111 , 303–312 (2003).

68. J. Yang, J. luo, X. tian, Y. Zhao, Y. li, X. Wu, Progress in understanding oxidative stress, aging, and aging- related diseases. Antioxidants 13 , 394 (2024).

69. c. Bamshad, n. najafi- Ghalehlou, Z. Pourmohammadi- Bejarpasi, K. tomita, Y. Kuwahara, t. Sato, A. Feizkhah, A. M. Roushnadeh, M. h. Roudkenar, Mitochondria: how eminent in ageing and neurodegenerative disorders? Hum. Cell 36 , 41–61 (2023).

70. A. verma, G. Azhar, X. Zhang, P. Patyal, G. Kc, S. Sharma, Y. che, J. Y. Wei, P. gingivalis - lPS induces mitochondrial dysfunction mediated by neuroinflammation through oxidative stress. Int. J. Mol. Sci. 24 , 950 (2023).

71. d. F. dai, Y. A. chiao, d. J. Marcinek, h. h. Szeto, P. S. Rabinovitch, Mitochondrial oxidative stress in aging and healthspan. Longev. Healthspan. 3 , 6 (2014).

72. t.- h. Yang, e. Y.- c. Kang, P.- h. lin, B. B.- c. Yu, J. h.- h. Wang, v. chen, n.- K. Wang, Mitochondria in retinal ganglion cells: Unraveling the metabolic nexus and oxidative stress. Int. J. Mol. Sci. 25 , 8626 (2024).

73. c. S. lin, M. S. Sharpley, W. Fan, K. G. Waymire, A. A. Sadun, v. carelli, F. n. Ross- cisneros, P. Baciu, e. Sung, M. J. McManus, B. X. Pan, d. W. Gil, G. R. Macgregor, d. c. Wallace, Mouse mtdnA mutant model of leber hereditary optic neuropathy. Proc. Natl. Acad. Sci. U.S.A. 109 , 20065–20070 (2012).

74. t. Klopstock, P. Yu- Wai- Man, K. dimitriadis, J. Rouleau, S. heck, M. Bailie, A. Atawan, S. chattopadhyay, M. Schubert, A. Garip, M. Kernt, d. Petraki, c. Rummey, M. leinonen, G. Metz, P. G. Griffiths, t. Meier, P. F. chinnery, A randomized placebo- controlled trial of idebenone in leber’s hereditary optic neuropathy. Brain 134 , 2677–2686 (2011).

75. G. Amore, M. Romagnoli, M. carbonelli, P. Barboni, v. carelli, c. la Morgia, therapeutic options in hereditary optic neuropathies. Drugs 81 , 57–86 (2021).

76. P. Yu- Wai- Man, d. Soiferman, d. G. Moore, F. Burté, A. Saada, evaluating the therapeutic potential of idebenone and related quinone analogues in leber hereditary optic neuropathy. Mitochondrion 36 , 36–42 (2017).

77. A. danese, S. Patergnani, A. Maresca, c. Peron, A. Raimondi, l. caporali, S. Marchi, c. la Morgia, v. del dotto, c. Zanna, A. iannielli, A. Segnali, i. di Meo, A. cavaliere, M. lebiedzinska- Arciszewska, M. R. Wieckowski, A. Martinuzzi, M. n. Moraes- Filho, S. R. Salomao, A. Berezovsky, R. Belfort Jr., c. Buser, F. n. Ross- cisneros, A. A. Sadun, c. tacchetti, v. Broccoli, c. Giorgi, v. tiranti, v. carelli, P. Pinton, Pathological mitophagy disrupts mitochondrial homeostasis in leber’s hereditary optic neuropathy. Cell Rep. 40 , 111124 (2022).

78. A. S. Monzel, J. A. enríquez, M. Picard, Multifaceted mitochondria: Moving mitochondrial science beyond function and dysfunction. Nat. Metab. 5 , 546–562 (2023).

79. d. nolfi- donegan, A. Braganza, S. Shiva, Mitochondrial electron transport chain: Oxidative phosphorylation, oxidant production, and methods of measurement. Redox Biol. 37 , 101674 (2020).

80. d. Ramonet, c. Perier, A. Recasens, B. dehay, J. Bové, v. costa, l. Scorrano, M. vila, Optic atrophy 1 mediates mitochondria remodeling and dopaminergic neurodegeneration linked to complex i deficiency. Cell Death Differ. 20 , 77–85 (2013).

81. c. Zanna, A. Ghelli, A. M. Porcelli, M. Karbowski, R. J. Youle, S. Schimpf, B. Wissinger, M. Pinti, A. cossarizza, S. vidoni, M. l. valentino, M. Rugolo, v. carelli, OPA1 mutations

associated with dominant optic atrophy impair oxidative phosphorylation and mitochondrial fusion. Brain 131 , 352–367 (2008).

82. Q. lei, K. Xiang, l. cheng, M. Xiang, human retinal organoids with an OPA1 mutation are defective in retinal ganglion cell differentiation and function. Stem Cell Rep. 19 , 68–83 (2024).

83. t. Bahr, K. Welburn, J. donnelly, Y. Bai, emerging model systems and treatment approaches for leber’s hereditary optic neuropathy: challenges and opportunities. Biochim. Biophys. Acta Mol. Basis Dis. 1866 , 165743 (2020).

84. Y. A. ito, A. di Polo, Mitochondrial dynamics, transport, and quality control: A bottleneck for retinal ganglion cell viability in optic neuropathies. Mitochondrion 36 , 186–192 (2017).

85. t. léveillard, J. A. Sahel, Metabolic and redox signaling in the retina. Cell. Mol. Life Sci. 74 , 3649–3665 (2017).

86. n. Aït- Ali, R. Fridlich, G. Millet- Puel, e. clérin, F. delalande, c. Jaillard, F. Blond, l. Perrocheau, S. Reichman, l. c. Byrne, A. Olivier- Bandini, J. Bellalou, e. Moyse, F. Bouillaud, X. nicol, d. dalkara, A. van dorsselaer, J. A. Sahel, t. léveillard, Rod- derived cone viability factor promotes cone survival by stimulating aerobic glycolysis. Cell 161 , 817–832 (2015).

87. l. Wang, J. dong, G. cull, B. Fortune, G. A. cioffi, varicosities of intraretinal ganglion cell axons in human and nonhuman primates. Invest. Ophthalmol. Vis. Sci. 44 , 2–9 (2003).

88. v. todorova, M. F. Stauffacher, l. Ravotto, S. nötzli, d. Karademir, l. J. A. ebner, c. imsand, l. Merolla, S. M. hauck, M. Samardzija, A. S. Saab, l. F. Barros, B. Weber, c. Grimm, deficits in mitochondrial tcA cycle and OXPhOS precede rod photoreceptor degeneration during chronic hiF activation. Mol. Neurodegener. 18 , 15 (2023).

89. Y. chinchore, t. Begaj, d. Wu, e. drokhlyansky, c. l. cepko, Glycolytic reliance promotes anabolism in photoreceptors. eLife 6 , e25946 (2017).

90. Y. chen, l. Zizmare, v. calbiague, l. Wang, S. Yu, F. W. herberg, O. Schmachtenberg, F. Paquet- durand, c. trautwein, Retinal metabolism displays evidence for uncoupling of glycolysis and oxidative phosphorylation via cori- , cahill- , and mini- Krebs- cycle. eLife 12 , RP91141 (2024).

91. Y. Zilberter, O. Gubkina, A. i. ivanov, A unique array of neuroprotective effects of pyruvate in neuropathology. Front. Neurosci. 9 , 17 (2015).

92. i. Martínez- Reyes, l. P. diebold, h. Kong, M. Schieber, h. huang, c. t. hensley, M. M. Mehta, t. Wang, J. h. Santos, R. Woychik, e. dufour, J. n. Spelbrink, S. e. Weinberg, Y. Zhao, R. J. deBerardinis, n. S. chandel, tcA cycle and mitochondrial membrane potential are necessary for diverse biological functions. Mol. Cell 61 , 199–209 (2016).

93. e. Balderas, d. R. eberhardt, S. lee, J. M. Pleinis, S. Sommakia, A. M. Balynas, X. Yin, M. c. Parker, c. t. Maguire, S. cho, M. W. Szulik, A. Bakhtina, R. d. Bia, M. W. Friederich, t. M. locke, J. l. K. van hove, S. G. drakos, Y. Sancak, M. tristani- Firouzi, S. Franklin, A. R. Rodan, d. chaudhuri, Mitochondrial calcium uniporter stabilization preserves energetic homeostasis during complex i impairment. Nat. Commun. 13 , 2769 (2022).

94. G. hong, d. Zheng, l. Zhang, R. ni, G. Wang, G. c. Fan, Z. lu, t. Peng, Administration of nicotinamide riboside prevents oxidative stress and organ injury in sepsis. Free Radic. Biol. Med. 123 , 125–137 (2018).

95. n. Xie, l. Zhang, W. Gao, c. huang, P. e. huber, X. Zhou, c. li, G. Shen, B. Zou, nAd+ metabolism: Pathophysiologic mechanisms and therapeutic potential. Signal Transduct. Target. Ther. 5 , 227 (2020).

96. R. P. Goodman, A. l. Markhard, h. Shah, R. Sharma, O. S. Skinner, c. B. clish, A. deik, A. Patgiri, Y. h. hsu, R. Masia, h. l. noh, S. Suk, O. Goldberger, J. n. hirschhorn, G. Yellen, J. K. Kim, v. K. Mootha, hepatic nAdh reductive stress underlies common variation in metabolic traits. Nature 583 , 122–126 (2020).

97. M. J. Mattapallil, e. F. Wawrousek, c. c. chan, h. Zhao, J. Roychoudhury, t. A. Ferguson, R. R. caspi, the Rd8 mutation of the Crb1 gene is present in vendor lines of c57Bl/6n mice and embryonic stem cells, and confounds ocular induced mutant phenotypes. Invest. Ophthalmol. Vis. Sci. 53 , 2921–2927 (2012).

98. t. h. chou, J. Bohorquez, J. toft- nielsen, O. Ozdamar, v. Porciatti, Robust mouse pattern electroretinograms derived simultaneously from each eye using a common snout electrode. Invest. Ophthalmol. Vis. Sci. 55 , 2469–2475 (2014).

99. v. Porciatti, t. h. chou, Modeling retinal ganglion cell dysfunction in optic neuropathies. Cells 10 , 1398 (2021).

100. n. K. Wang, P. K. liu, Y. Kong, S. R. levi, W. c. huang, c. W. hsu, h. h. Wang, n. chen, Y. J. tseng, P. M. J. Quinn, M. h. tai, c. S. lin, S. h. tsang, Mouse models of achromatopsia in addressing temporal “Point of no Return” in gene- therapy. Int. J. Mol. Sci. 22 , 8069 (2021).

101. Y. Kong, P. K. liu, Y. li, n. d. nolan, P. M. J. Quinn, c. W. hsu, l. A. Jenny, J. Zhao, X. cui, Y. J. chang, K. J. Wert, J. R. Sparrow, n. K. Wang, S. h. tsang, hiF2α activation and mitochondrial deficit due to iron chelation cause retinal atrophy. EMBO Mol. Med. 15 , e16525 (2023).

102. n. K. Wang, c. c. lai, c. h. liu, l. K. Yeh, c. l. chou, J. Kong, t. nagasaki, S. h. tsang, c. l. chien, Origin of fundus hyperautofluorescent spots and their role in retinal degeneration in a mouse model of Goldmann- Favre syndrome. Dis. Model. Mech. 6 , 1113–1122 (2013).

103. h. J. Wu, R. J. hazlewood, J. Kuchtey, R. W. Kuchtey, enlarged optic nerve axons and reduced visual function in mice with defective microfibrils. eNeuro 5 , eneURO.0260- 18.2018 (2018).

104. J. tosi, n. K. Wang, J. Zhao, c. l. chou, J. M. Kasanuki, S. h. tsang, t. nagasaki, Rapid and noninvasive imaging of retinal ganglion cells in live mouse models of glaucoma. Mol. Imaging Biol. 12 , 386–393 (2010).

105. c. Y. lin, K. Y. Wu, l. M. chi, Y. h. tang, h. J. huang, c. h. lai, c. n. tsai, c. l. tsai, Starvation- inactivated MtOR triggers cell migration via a UlK1- Sh3PXd2A/tKS5- MMP14 pathway in ovarian carcinoma. Autophagy 19 , 3151–3168 (2023).

106. n. Sun, A. ly, S. Meding, M. Witting, S. M. hauck, M. Ueffing, P. Schmitt- Kopplin, M. Aichler, A. Walch, high- resolution metabolite imaging of light and dark treated retina using MAldi- FticR mass spectrometry. Proteomics 14 , 913–923 (2014).

107. Y. hao, t. Stuart, M. h. Kowalski, S. choudhary, P. hoffman, A. hartman, A. Srivastava, G. Molla, S. Madad, c. Fernandez- Granda, R. Satija, dictionary learning for integrative, multimodal and scalable single- cell analysis. Nat. Biotechnol. 42 , 293–304 (2024).

108. A. ianevski, A. K. Giri, t. Aittokallio, Fully- automated and ultra- fast cell- type identification using specific marker combinations from single- cell transcriptomic data. Nat. Commun. 13 , 1246 (2022).

109. t. Wu, e. hu, S. Xu, M. chen, P. Guo, Z. dai, t. Feng, l. Zhou, W. tang, l. Zhan, X. Fu, S. liu, X. Bo, G., clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation 2 , 100141 (2021).

110. A. Fabregat, S. Jupe, l. Matthews, K. Sidiropoulos, M. Gillespie, P. Garapati, R. haw, B. Jassal, F. Korninger, B. May, M. Milacic, c. d. Roca, K. Rothfels, c. Sevilla, v. Shamovsky, S. Shorser, t. varusai, G. viteri, J. Weiser, G. Wu, l. Stein, h. hermjakob, P. d’eustachio, the reactome pathway knowledgebase. Nucleic Acids Res. 46 , d649–d655 (2018).

111. d. n. Slenter, M. Kutmon, K. hanspers, A. Riutta, J. Windsor, n. nunes, J. Mélius, e. cirillo, S. l. coort, d. digles, F. ehrhart, P. Giesbertz, M. Kalafati, M. Martens, R. Miller, K. nishida, l. Rieswijk, A. Waagmeester, l. M. t. eijssen, c. t. evelo, A. R. Pico, e. l. Willighagen, WikiPathways: A multifaceted pathway database bridging metabolomics to other omics research. Nucleic Acids Res. 46 , d661–d667 (2018).

112. P. Bankhead, M. B. loughrey, J. A. Fernández, Y. dombrowski, d. G. McArt, P. d. dunne, S. McQuaid, R. t. Gray, l. J. Murray, h. G. coleman, J. A. James, M. Salto- tellez, P. W. hamilton, QuPath: Open source software for digital pathology image analysis. Sci. Rep. 7 , 16878 (2017).

113. e. c. Bayraktar, l. Baudrier, c. Özerdem, c. A. lewis, S. h. chan, t. Kunchok, M. Abu- Remaileh, A. l. cangelosi, d. M. Sabatini, K. Birsoy, W. W. chen, MitO- tag Mice enable rapid isolation and multimodal profiling of mitochondria from specific cell types in vivo. Proc. Natl. Acad. Sci. U.S.A. 116 , 303–312 (2019).

Acknowledgments: We would like to express our gratitude to t. c. Swayne and the confocal and Specialized Microscopy Shared Resource at the herbert irving comprehensive cancer center, columbia University, for technical assistance. We also thank n. nolan, J. Zhao, c. P.- Y. Su, and S. chang from the department of Ophthalmology at columbia University irving Medical center for support and A. h.- F. lin and B. Y.- l. chou from Raising Statistic consultant inc. for

assistance with the statistical analyses. the salary of S.h.t. was supported by the national eye institute (nei), national institutes of health, under awards U01eY034590, R24eY028758, P30eY019007, R01eY033770, R01eY018213, and R01eY024698, and by the Richard Jaffe Foundation, the nYee Foundation, the Rosenbaum Family Foundation, and unrestricted funds from Research to Prevent Blindness (RPB). Funding: this work was funded by chang Gung Memorial hospital, taiwan (cMRPG3n1001 and cMRPG3Q0451) (e.Y.- c.K.); national Science and technology council, taiwan (nStc 113- 2314- B- 182A- 150- MY3) (e.Y.- c.K.); chang Gung University, taiwan (UARPd1n0031 and UARPd1P0261) (e.Y.- c.K.); national eye institute of the national institutes of health grant R01eY033359 (G.t.); national eye institute of the national institutes of health grants R01eY031354 and R21eY037007 (n.- K.W.); Gerstner Philanthropies (n.- K.W.); the United Mitochondrial disease Foundation (n.- K.W.); Genetically Modified Mouse Model Shared Resource irving comprehensive cancer center at columbia University, national institutes of health nci cancer center Support Grant P30cA013696 (c.- S.l.); national institute of General Medical Sciences of the national institutes of health grant 1S10Od030401- 01A1 (t.- d.l.) and S10Od036268 (Y. h.); national eye institute of the national institutes of health Shared instrument grant S10Od028637 and national eye institute of the national institutes of health grants U01eY034590, R24eY028758, 5P30eY019007, R01eY033770, R01eY018213, and R01eY024698 (S.h.t.); the Richard Jaffe Foundation (S.h.t.); the nYee Foundation (S.h.t.); the Rosenbaum Family Foundation (S.h.t.); and an unrestricted grant to the department of Ophthalmology, columbia University, from Research to Prevent Blindness, new York, nY. Author contributions: conceptualization: c.- n.t., e.Y.- c.K., c.- c.l., c.- S.l., n.- K.W., S.h.t., Y.- J.t., and O.S. Methodology: t.- d.l., i.Y.- F.c., J.P., e.Y.- c.K., c.- c.l., c.K., G.t., h.- c.h., c.- S.l., n.- K.W., S.h.t., J.c., c.- Y.h., e.h.W., and Y.- J.t. investigation: t.- d.l., c.- n.t., J.P., e.Y.- c.K., P.- h.l., c.- c.l., K.P.M., c.- l.t., c.- S.l., n.- K.W., S.h.t., J.c., l.S., W.- h.P., e.h.W., and Y.- J.t. visualization: Y.- c.t., Y.h., i.Y.- F.c., c.- c.l., K.P.M., c.- S.l., n.- K.W., J.c., e.h.W., and Y.- J.t. validation: t.- d.l., c.- n.t., i.Y.- F.c., J.P., e.Y.- c.K., c.- c.l., c.- S.l., n.- K.W., S.h.t., J.c., W.- h.P., e.h.W., and Y.- J.t. data curation: Y.- c.t., c.- n.t., i.Y.- F.c., e.Y.- c.K., c.K., c.- S.l., n.- K.W., J.c., c.- Y.h., e.h.W., and Y.- J.t. Formal analysis: Y.- c.t., i.Y.- F.c., e.Y.- c.K., c.- l.t., c.K., c.- S.l., n.- K.W., S.h.t., J.c., W.- h.P., c.- Y.h., e.h.W., e.S., and Y.- J.t. Software: Y.- c.t., i.Y.- F.c., G.t., n.- K.W., c.- Y.h., and e.h.W. Resources: t.- d.l., c.- n.t., J.P., e.Y.- c.K., G.t., h.- c.h., c.- S.l., n.- K.W., and Y.- J.t. Funding acquisition: e.Y.- c.K., G.t., c.- S.l., and n.- K.W. Project administration: e.Y.- c.K., c.- S.l., n.- K.W., and S.h.t. Supervision: c.- n.t., i.Y.- F.c., e.Y.- c.K., c.- c.l., G.t., c.- S.l., n.- K.W., S.h.t., and O.S. Writing—original draft: Y.- c.t., e.Y.- c.K., c.- c.l., c.- S.l., n.- K.W., S.h.t., J.c., and e.h.W. Writing—review and editing: t.- d.l., c.- n.t., i.Y.- F.c., e.Y.- c.K., c.- c.l., G.t., c.- S.l., n.- K.W., S.h.t., J.c., l.S., c.- Y.h., e.h.W., Y.- J.t., and O.S. Competing interests: the authors declare that they have no competing interests. Data, code, and materials availability: snRnA- seq data have been deposited into the ncBi GeO repository (GSe292269, www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSe292269). All data and code needed to evaluate and reproduce the results in the paper are present in the paper and/or the Supplementary Materials. this study did not generate any new materials.

Submitted 27 March 2025 Accepted 13 January 2026 Published 18 February 2026 10.1126/sciadv.adx7815