Vitamin B3 Treatment Reverses Mitochondrial Dysfunction in Glaucoma Model

Using scRNA-seq, we sequenced 17,914 cells from dissected limbal tissue (contains drainage structures) of 2-month-old mice. The dataset included 13,251 cells from strain C57BL/6J (B6) and 4663 cells from strain 129/Sj (129). The data for both strains were integrated (Figure 1—figure supplement 1). Computational analysis revealed six distinct clusters of cells that were TM-containing, epithelia, pigmented epithelia (iris and ciliary body), endothelial, immune, and neuron (Figure 1A). The identity of each of these cell clusters was based on various well-characterized marker genes (Figure 1—figure supplement 2A–B; Thomson et al., 2021; Balasubramanian et al., 2024; van Zyl et al., 2020). There were no major differences in the distributions of strain B6 and strain 129 cells within the relevant cell-type clusters (Figure 1—figure supplement 3A–C). Therefore, to improve statistical power, downstream analyses used the integrated dual-strain dataset. Cells of cluster 1 expressed various TM genes, including Acta2 (α-SMA), Pitx2, Tfap2b, and Myoc (Figure 1—figure supplement 2A; Balasubramanian et al., 2024; van Zyl et al., 2020; Akula et al., 2020; Ostojic et al., 2008; de Kater et al., 1992). Unbiased sub-clustering of Cluster 1 revealed 10 distinct sub-clusters (Figure 1B), which included three TM cell clusters based on signature gene expression (Figure 1D–E). We named these clusters TM1, TM2, and TM3. Hierarchical clustering of these cell types indicated that TM1 and TM2 are more molecularly similar to each other than to TM3 (Figure 1C). The remaining seven clusters were identified as cells from other ocular tissue including the iris stroma, sclera, corneal keratocytes, corneal endothelium, ciliary muscle, pericytes, and Schwann cells (Figure 1—figure supplement 2C; van Zyl et al., 2022; Patel and Parker, 2015; Lopez et al., 2009; Liu et al., 2003; Toyono et al., 2015; Monje et al., 2018; Stratton et al., 2017; Nitzan et al., 2013). Next, we integrated an additional limbal tissue scRNA-seq dataset (14,912 cells, Duke University) from 3 months old C57BL/6J mice with our initial 2 months old C57BL/6J dataset. Due to batch effects most likely based on differences in cell isolation techniques and environment (Columbia University vs. Duke University, see Materials and methods), TM cells from these datasets occupied adjacent, partially overlapping, but not identical UMAP space (Figure 1—figure supplement 4). Individual analysis of the Duke dataset also identified three TM cell subtypes with the same marker gene expression and enriched molecular pathways compared to the Columbia University data (Figure 1—figure supplement 4B–E, Supplementary file 1). In datasets from previous mouse limbal scRNA-seq studies, there was also a high degree of overlap of marker gene expression with our three TM cell clusters (Figure 1—figure supplement 5A–B; Thomson et al., 2021; van Zyl et al., 2020; Ujiie et al., 2023). However, some TM subtype clusters reported in previous studies expressed genes that overlapped with both of our TM2 and scleral cell clusters (Figure 1—figure supplement 5B–C; Thomson et al., 2021; van Zyl et al., 2020). To resolve this discrepancy, we performed IF for two of the discordantly annotated markers previously reported to be expressed in TM cells but present in our scleral cluster (CD34 and LY6C1). This immunolabeling showed that these markers are expressed in scleral but not TM cells (Figure 2—figure supplement 1A–B). In addition, in previous studies, cells with markers matching TM3 (e.g. Lypd1) were named uveal cells without IF confirmation (Thomson et al., 2021; van Zyl et al., 2020; Ujiie et al., 2023). IF revealed that our TM3 cells are neither located in the uvea nor abundant in the uveal adjacent TM but primarily reside in the anterior TM closer to the cornea (see below). To further explore the sub-anatomical localization of the TM cell subtypes, we used a combination of IF and ISH to identify subtype markers. Each TM cell subtype had a higher percentage of cells expressing, and an increased average expression of, its respective subtype markers (all p<1E-100 enriched compared to other TM cells, Figure 2—figure supplement 2A). To analyze the distribution of subtypes, we first divided the TM into zones along its anterior/posterior and inner/outer axes (Figure 2—figure supplement 2B–E). The total area of TM occupied by each individual subtype marker was assessed in each zone on more than 150 tissue sections. This detected biases for the subtypes to be differentially localized in specific TM zones (Figure 2A–F). For instance, TM1 cells were significantly more frequent in the posterior and outer TM zones, while TM3 cells were overrepresented in the anterior and inner zones (all p<0.01). The different marker molecules that were assessed for each TM cell subtype gave highly consistent results regarding zonal occupancy (Figure 2—figure supplement 3A–B, Figure 2—figure supplement 4). In addition, we confirmed the localization biases in 3D whole mounts of the mouse limbus (Figure 2G–H, TM1 – MYOC, TM3 – α-SMA) (Kizhatil et al., 2014). Collectively, these data indicate clear localization biases that differ for the TM1 and TM3 subtypes. To better understand the location of TM cell subtypes, we analyzed marker expression patterns in 50–60 exceptionally high-quality sections for each marker of each TM cell subtype (see Materials and methods). For this analysis, the TM was divided into eight regions (Figure 2—figure supplement 2F). Not only did this refine the localization bias of TM1 and TM3 cells, but it discovered that TM2 cells are most concentrated in the mid-posterior two-thirds of the TM (mid regarding inner-outer axis, all p<0.01, Figure 2I–K). Despite their biased distributions, some cells of each TM subtype were detected in most TM regions. To determine the molecular functions of TM cells, we first conducted gene ontology (GO) analysis using genes that were differentially expressed genes (DEGs) in all TM cells as a group compared to other sequenced cells (Supplementary file 2). Additionally, we used gene set enrichment analysis (GSEA) to assess whether these GO pathways are relatively enriched or underrepresented in TM cells. Compared to other cells, TM cells were enriched for pathways associated with extracellular matrix (ECM) structure and function, including signaling associated with collagens, proteases, integrins, and glycosaminoglycans (Figure 3A, Figure 3—figure supplement 1A, Supplementary file 3). TM cells were also enriched for growth factor signaling. Conversely, underrepresented pathways in TM cells were associated with desmosomes, peroxisomes, and certain cytoskeletal and plasma membrane elements. These pathways help define TM cells relative to other cells in the region. Next, we compared TM cell subtypes to each other (Figure 3B–D). TM1 cells were most enriched for ECM pathways, particularly structural components such as collagens, integrins, and other ECM elements (Figure 3B, Figure 3—figure supplement 1). The expression of several ECM genes that are reported to impact IOP is heightened in TM1 cells, including Type VIII collagens, fibronectin, and Ltbp2 (Desronvil et al., 2010; Ali et al., 2009; Roberts et al., 2020). Both TM1 and TM2 cells have enriched expression of glycosaminoglycan (GAG) genes (Figure 3B–C, Figure 3—figure supplement 1B–C). GAGs in the JCT and intertrabecular spaces form a gel-like consistency and changes in GAG abundance correlate with altered AH outflow resistance (Knepper et al., 1981; Knepper and McLone, 1985; Knepper et al., 1996). TM2 cells are uniquely enriched for the laminin complex, a key component of basement membranes (Aumailley, 2013). Pathways related to clearing debris and monitoring the extracellular environment including phagocytic vesicles, antigen presentation, and lysosomal function are also enhanced in TM2 cells. In contrast, TM3 cells are underrepresented for ECM-related pathways compared to other TM cells but are enriched for pathways related to actin binding and mitochondrial metabolism (Figure 3D, Figure 3—figure supplement 1D). The actomyosin system plays a crucial role in maintaining TM cell contractility and in regulating outflow facility (Zhang and Rao, 2005; Thieme et al., 2000; Rao et al., 2005; Syriani et al., 2009; Tian and Kaufman, 2005). The enrichment of mitochondrial metabolism pathways in TM3 cells emphasizes their energetic needs and their expected heightened susceptibility to genetic and environmental contexts that compromise metabolic functions. Importantly, genetic variation in mitochondrial/metabolic pathways contributes risk for IOP elevation and glaucoma (Aboobakar et al., 2023; Zhang et al., 2023; Xin et al., 2022; Khawaja et al., 2016). We next compared growth factor signaling and ligand-target interactions between TM cell subtypes and other cells. TM1 cells were enriched for transforming growth factor beta (TGF-β) pathway signaling (Figure 3B). Receptor ligand activity was enriched in TM2 cells while the membrane raft pathway (a site of signal transduction) was enriched in TM3 cells (Figure 3C–D). Next, we used LRLoop (Xin et al., 2022), which was developed based on NicheNet (Browaeys et al., 2020), to predict significant ligand-target interactions between TM cells and other local endothelial cells that are relevant to AH drainage (Figure 4A–D). TGF-β ligands (Tgfb1, 2, and 3) were predominantly expressed in TM1 cells. By contrast, TM2 cells expressed molecules critical for vascular function, such as Angpt1, Vegfa, and Edn3 (Figure 4—figure supplement 1A–D; Shibuya, 2011; Saharinen et al., 2017; Genovesi et al., 2022). These TM-secreted molecules have been directly associated with SC maintenance and IOP (Thomson et al., 2020; Fujimoto et al., 2016; Reina-Torres et al., 2017; Comes and Borrás, 2009). We next worked to relate our findings to human data. We compared marker genes for each of our TM cell subtypes to sequenced human TM cells from two previous studies (van Zyl et al., 2020; Patel et al., 2020). These previous studies differed in the number of human TM cell subtypes that they reported and in the identities of their clusters. van Zyl et al. identified three TM cell subtypes that they called JCT, beam A, and beam B (van Zyl et al., 2020), whereas Patel et al. identified two subtypes that they called fibroblast-like and myofibroblast-like (Patel et al., 2020). TM1 marker genes were most enriched in van Zyl et al’s human JCT cells (Figure 3—figure supplement 2A). Similarly, Dcn was expressed in mouse TM1 cells and was localized to fibroblast-like TM cells adjacent to SC by Patel et al. TM1 cell nuclei were typically shorter with greater sphericity than the elongated endothelial-like nuclei of TM3 cells (Figure 3—figure supplement 3A–D). This nuclear morphology was more consistent with a JCT than beam cell identity. Together, these data support a JCT identity for TM1 cells. TM2 cells were more closely related to human beam A and beam B cells than to the JCT cells reported by van Zyl et al. (Figure 3—figure supplement 2B). TM2 cells also shared expression of the RSPO2 marker gene with the human myofibroblast-like cells reported by Patel et al. Together, this suggests that TM2 cells are myofibroblast-like beam cells. TM3 cells also shared marker genes with Patel et al’s myofibroblast-like cells (TAGLN and ACTA2), suggesting TM3 cells are also beam cells. There was relatively equal TM3 marker gene enrichment across all human TM cell subtypes of van Zyl et al. (Figure 3—figure supplement 2C). Nuclei immediately adjacent to TM2 and TM3 cell marker staining had an elongated, endothelial-like shape (Figure 3—figure supplement 3A–C). This nuclear morphology was also consistent with the location of TM2 and TM3 cells on beams and analogous to the endothelial-like morphology of human beam cells (Stamer and Clark, 2017). Next, we evaluated the expression of genes implicated in elevated IOP and glaucoma by genome-wide association studies (GWAS). TM1 and TM2 cells had similar expression levels of GWAS genes associated with IOP elevation and primary open-angle glaucoma (POAG), respectively (Figure 3—figure supplement 4A). TM3 cells had slightly less expression of these GWAS genes compared to TM1 and TM2. To better understand the genes driving GWAS gene enrichment in different TM subtypes, we studied pathways that are significantly enriched for GWAS genes (Figure 3—figure supplement 4B–C, see Supplementary file 4 for complete list). TM1 cells were the most enriched for genes involved in ECM organization, cell-substrate adhesion, and growth factor stimulus (Figure 3—figure supplement 4D). All 3 TM subtypes had similar expression of GWAS genes associated with hormone stimulus, Vegf signaling, and Rho kinase signaling. TM3 cells expressed lipid and carbohydrate mitochondrial metabolism pathway genes at higher expression levels and in more cells than did TM1 and TM2 cells (Figure 3—figure supplement 4E). The same was true for actin binding-associated GWAS genes in TM3 cells versus TM1 and TM2. Genetic variation in lipid and carbohydrate mitochondrial metabolism pathways is associated with IOP elevation and glaucoma (Khawaja et al., 2016). To evaluate the utility of our new TM cell atlas, we used it to examine how Lmx1b mutations affect the TM cell transcriptome and to identify potential mechanisms underlying IOP elevation. We selected LMX1B because it causes IOP elevation and glaucoma in humans and was identified as a highly active transcription factor in our TM cell dataset. To do this, we analyzed scRNA-seq data generated for limbal cells from mice with a dominant mutation in Lmx1b (Lmx1bV265D/+), which included 2491 V265D mutant TM cells. These mutant C57BL/6J mice develop early onset IOP elevation (Cross et al., 2014; Tolman et al., 2021; Zhang et al., 2024). We compared gene expression in V265D mutant TM cells after integration with our wild-type data (all data B6 background and postnatal day 60, Figure 6A, Figure 6—figure supplement 1A). Results show that Lmx1b is minimally expressed in TM1 and TM2 but is highly expressed in TM3 cells (Figure 6B). Next, we analyzed DEGs and pathway differences between WT and V265D/+ cells across each TM cell subtype. Across all TM subtypes, various genes related to ECM function and growth factor signaling were downregulated in mutants, including glycosaminoglycans and insulin growth factor binding proteins (Figure 6C, see Supplementary file 6 for complete list of pathways). Pathways enriched in mutant TM cells were associated with ribosomes and calcium signaling. We then examined the differential responses to the Lmx1b mutation by analyzing pathways dysregulated in each TM subtype that were not common across all TM cells (Figure 6D–F, Figure 6—figure supplement 1B). V265D mutant TM1 cells had a downregulation of collagen synthesis/metabolism gene expression relative to WT cells, particularly in the production and turnover of fibrillar collagens. TM2 cells with Lmx1b mutations had upregulation of immune signaling pathways. The highly Lmx1b-expressing TM3 cells exhibited perturbed mitochondrial metabolism, with a downregulation of genes in complex I and ATP synthase. In addition, mutant TM3 cells showed an upregulation of protein tagging genes. However, there was a downregulation of the polyubiquitin precursor gene (Ubb, p=4.5E-30), indicating a general dysregulation of pathways that tag proteins for degradation. These results document altered mitochondrial function and proteostasis in TM3 cells. Although the documented gene expression changes strongly suggest metabolic and mitochondrial dysfunction, they do not directly prove it. Using electron microscopy to directly evaluate mitochondria in the TM, we found a reduction in total mitochondria number per cell in mutants (p=0.015, Figure 6G). In addition, mitochondria in mutants had increased area and reduced cristae (inner membrane folds), consistent with mitochondrial swelling and metabolic dysfunction (all p<0.001 compared to WT, Figure 6G–H). Our findings most strongly implicate perturbed metabolism within TM3 cells as responsible for IOP elevation in an Lmx1b glaucoma model. Nicotinamide (NAM) is known to boost nicotinamide adenine dinucleotide (NAD), supporting healthy metabolism/ mitochondrial function (Schöndorf et al., 2018; Williams et al., 2017b). Thus, we hypothesized that the metabolic abnormalities in TM3 cells underlie the IOP elevation that causes glaucoma, and that NAM treatment may protect the Lmx1b mutant TM. Beyond LMX1B, this hypothesis is relevant more commonly to POAG treatment because metabolism-relevant genes are implicated by GWAS (and their expression is enriched in TM3 cells, Figure 3—figure supplement 4E). To test our hypothesis, we treated mice by adding NAM to their drinking water starting at postnatal day 2 and continuing into adulthood. Results showed that NAM supplementation significantly protected against anterior chamber deepening (ACD, a symptom of IOP elevation, Figure 7A–B) and IOP elevation (Figure 7C–D). These results support NAM as a treatment to prevent TM damage and IOP elevation in LMX1B-mediated glaucoma with potential general relevance to POAG. Figure 7 Here, we provide evidence for three TM cell subtypes in mice that are robust across datasets from different institutions, using different tissue processing and sequencing protocols. Although others (Thomson et al., 2021; Ujiie et al., 2023) subdivided TM cell subtypes beyond the three defined in the present study, at this point, we decided against further subdivision (See Figure 1—figure supplement 5) for the following reasons. We lacked confidence in the higher resolution clustering, as it was not consistent across datasets, did not produce unique marker gene sets, and could have resulted in over-clustering due to stochastic or stress-induced differences between subpopulations of cells. Moreover, the number of reported mouse TM cell clusters in previous studies was inconsistent. Although three TM subtypes were reported by van Zyl et al. and Ujiie et al. (van Zyl et al., 2020; Ujiie et al., 2023), the molecular features of cells in these clusters were not the same across these studies. Differences between studies may be due to batch effects, different computational methods, and possibly over-clustering. Most importantly, there was very limited validation by IF, IHC, or other methods in previous studies. Only the JCT type of TM cell in these previous studies was assessed by means other than scRNA-seq (IF and ISH; van Zyl et al., 2020). Additionally, Thompson et al. treated cells with Y27632, a ROCK inhibitor, which could alter TM cell transcriptomes. It is also important to point out that both Thompson et al. and van Zyl et al. used albino mouse strains, which can impact TM cell development and function (Libby et al., 2003). Finally, Ujiie et al. sequenced TM cells at 3–4 weeks, which is prior to full maturation of the TM structure (Smith et al., 2001), while our ongoing developmental studies show substantial molecular maturation of TM cells between P21 and P60. As van Zyl et al.’s data is deposited in the Broad Institute’s single-cell portal, we further compared their data with ours. Although both van Zyl et al. and our current paper identified three TM subtypes, our work does not fully agree. Some of the cells named beam A and beam Y by van Zyl et al. express markers present in our TM2 cell subtype, while others express markers that are absent in TM2 cells but present in our scleral cells. Our IF studies confirm that these discordant markers are not expressed in TM cells, but instead show that they are in fact scleral cells. These scleral cells highly express fibroblast markers including Mfap5, Clec3b, and Tnxb, suggesting they are scleral fibroblasts. Cells initially named uveal cells by van Zyl et al. (and subsequently by Ujiie et al. and Thompson et al.) express markers of our TM3 cells. Consistent with our gene expression data, our IF shows that these van Zyl markers are expressed by cells that are primarily located in the TM region that is closer to the cornea and not in the uvea or the TM region adjacent to the uvea. Thus, our current study resolves some previous inconsistencies in classifying mouse TM cell subtypes. It lays a firmer foundation for continued understanding of TM cell types and their biology. Moving ahead, sequencing cells at greater depths will enhance TM cell characterization and improve comparisons between datasets. As a group, all TM cells share various molecular properties that distinguish them from other ocular cells. Our analyses determine the expression of IOP and glaucoma genes identified by GWAS in TM cell subtypes as well as in other limbal cells. Pathways enriched across all TM cell subtypes based on RNA-seq are largely related to ECM (including collagens, integrins, and glycosaminoglycan pathways), cell-cell signaling, and growth factor signaling. This fits with an essential role of the TM in both ECM synthesis/turnover and in signaling to the SC to maintain IOP (Thomson et al., 2021; Balasubramanian et al., 2024; Stamer and Acott, 2012; Keller et al., 2009; Fuchshofer and Tamm, 2009). In addition, the expression of genes that we document generally agrees with the literature. For example, the following genes and signaling molecules have been reported in TM cells: WNT signaling (Wang et al., 2008), TGF-β signaling (McDowell et al., 2013; Shepard et al., 2010; Rudzitis et al., 2025; Fleenor et al., 2006; Gottanka et al., 2004; Mody et al., 2021; Wordinger et al., 2007), integrin binding (Gagen et al., 2014; Faralli et al., 2019; Yang et al., 2022), actin cytoskeletal networks (Bermudez et al., 2017), calcification genes (Xue et al., 2007; Borrás and Comes, 2009), and Myocillin (Borrás and Comes, 2009; Saccuzzo et al., 2023; Fingert et al., 2002; Sharma and Grover, 2021). Additionally, genes associated with intermediate filaments, which function in determining cell shape and structure and can also act as mechanical stress absorbers (Herrmann et al., 2007), are underrepresented in TM cells. Lower levels of intermediate filaments may enable TM cells to alter their shape to respond to changes in IOP. Mouse TM1 cells closely resemble sequenced human JCT cells. Like human JCT cells, the majority of TM1 cells are located nearest to the SC inner wall, particularly adjacent to the posterior of the mouse SC. Human JCT cells are generally accepted to be embedded in a more diffuse ECM and to not cover the collagenous trabecular beams (Stamer and Clark, 2017; Vranka et al., 2015; Keller and Acott, 2013). In vivo, a proportion of TM1 cells have a shorter, more spherical nuclear morphology, consistent with JCT cell identity. Importantly, the JCT region is critical in determining resistance to AH outflow and in regulating IOP (Acott and Kelley, 2008; Johnson, 2006; Stamer and Acott, 2012; Ethier, 2002). JCT cells have fibroblast-like properties, including the secretion of ECM proteins and degradation enzymes to support continuous ECM remodeling (Stamer and Clark, 2017; Keller et al., 2009; Acott et al., 1988). The subset of TM1 cells that lie distant from SC has a more beam cell-like, elongated nuclear morphology. This suggests that either our TM1 cluster contains more than 1 TM cell subtype or that the morphology of a single TM1 cell subtype is influenced by local environment. This needs to be resolved by future studies. Compared to the other TM cell subtypes, TM1 cell pathways are enriched in both ECM structural molecules, such as collagens and integrins, and TGF-β signaling, which increases ECM production (Munger and Sheppard, 2011). Notably, excessive TGF-β signaling and ECM production can lead to fibrosis and elevate IOP (Fleenor et al., 2006; Fuchshofer and Tamm, 2009; Meng et al., 2016; Frangogiannis, 2020; Biernacka et al., 2011; Fuchshofer and Tamm, 2012). TGFβ2 has also been shown to cause ocular hypertension both in vivo (McDowell et al., 2013; Shepard et al., 2010; Rudzitis et al., 2025) and ex vivo (Fleenor et al., 2006; Gottanka et al., 2004) and is elevated in POAG patients (Tripathi et al., 1994; Min et al., 2006). These data suggest that TM1 cells play an important role in the constant remodeling of the ECM. However, dysregulation of these pathways can be pathogenic. TM2 cells molecularly resemble previously sequenced human TM beam cells (van Zyl et al., 2020; Patel et al., 2020). This includes overlap of expression of top TM2 signature gene expression with sequenced human beam cells. Consistent with a beam cell identity, TM2 cells are located more towards the mid and inner TM than most TM1 cells. TM2 cells have an elongated nuclear morphology, consistent with the previously established beam cell morphology of cells in the regions they occupy (Stamer and Clark, 2017; Smith et al., 2001; Overby et al., 2014). Beam cells have endothelial-like properties, such as maintaining the patency of the AH outflow tract through the production of antithrombotic molecules. Proteases and molecules classically known as antithrombotic and thrombolytic maintain fluid flow through the TM by preventing build-up of protein aggregates to maintain fluid drainage (Acott and Kelley, 2008; Stamer and Acott, 2012). Such molecules include glycosaminoglycans, like heparin, the serine protease tPA, and matrix metalloprotease that are all highly expressed in TM2 cells. Beam cells are also phagocytic, and this activity, along with turnover of ECM, further cleans the TM (called filtering) to enhance fluid drainage (Stamer and Clark, 2017). Human beam cells also participate in antigen presentation and modulation of inflammation through cytokines and major histocompatibility proteins (Stamer and Clark, 2017; Shifera et al., 2010), consistent with TM2 cells being enriched for these immune pathways/molecules. Additionally, our data suggest that signaling from TM2 cells to SC endothelial cells is mediated by soluble molecules including Vegfa, Edn3, and Angpt1, which are critical for SC maintenance and function. This links TM2 cells to ocular development and glaucoma. VEGF receptor and ANGPT signaling genes modulate SC development/function as well as contribute to developmental and primary open-angle glaucoma (Kizhatil et al., 2014; Khawaja et al., 2018; MacGregor et al., 2018; Thomson et al., 2020; Souma et al., 2016; Kabra et al., 2017; Aspelund et al., 2014). TM3 cells also have a location and elongated nuclear morphology resembling beam cells with enriched localization in the inner, anterior TM. TM3 cell-enriched processes include actin binding and modulation of the actomyosin system, which are known to modulate outflow resistance and IOP (Rao et al., 2001; Yu et al., 2008). As such, TM3 cells highly express a large percentage of glaucoma-associated genes involved in actin binding. Importantly, TM3 cells are enriched for various mitochondrial metabolic and antioxidant pathways, including those associated with IOP elevation and glaucoma (Aboobakar et al., 2023; Khawaja et al., 2016). Inhibiting metabolic pathways alters AH outflow resistance (Bermudez et al., 2017). Since maintaining contractile tone is an energy-intensive process (DeWane et al., 2021), this could explain the enrichment of energy metabolism pathways in TM3 cells compared to other TM cells. In addition to being enriched in mitochondrial/ energy metabolism processes, TM3 cells express Lmx1b at significantly higher levels than both the other TM cell subtypes and other limbal cells. Importantly, in heterozygous mutant V265D mice, TM3 cells had pronounced gene expression changes that implicate mitochondrial dysfunction but that were absent or much lower in other cells including TM1 and TM2. In sections of the inner TM (enriched for TM3 cells), we show that the inner membrane folds known as cristae are disrupted or lacking in mutant mitochondria. Cristae disruptions are well established to disrupt cellular metabolism, impair oxidative phosphorylation, reduce ATP synthesis, alter mitochondrial membrane potential, and elevate ROS production (Baker et al., 2019; Jenkins et al., 2024; Golombek et al., 2024; Huang et al., 2023; Ježek et al., 2023). Together, these data suggest that mutation of Lmx1b has a primary effect on metabolism in TM3 cells that subsequently leads to IOP elevation and then glaucoma. Relevantly, homozygous conditional knockout of both Lmx1b and Lmx1a, as well as siRNA knockdown of Lmx1b alone, impacts mitochondrial functions in neurons and may contribute to Parkinson’s disease (Jiménez-Moreno et al., 2023; Doucet-Beaupré et al., 2016; Bergman et al., 2009). Our data extend these published findings by showing that inheritance of a single dominant mutation in Lmx1b similarly affects mitochondria in TM cells. Although our studies show a clear effect of the Lmx1b mutation on TM mitochondria, it is not clear whether these are primary effects of the mutation or secondary effects. Future studies are needed to determine whether LMX1B directly modulates mitochondrial function in V265D mutant TM3 cells, which will require technological advances to define the molecular etiology and nature of mitochondrial defects in Lmx1b mutant TM cells, their relationship to outflow dysfunction/IOP elevation, and the effects of NAM on TM cell mitochondria performance. In addition to modulating mitochondria, LMX1B was recently identified as a TF that regulates responses to cell stress. This includes promotion of autophagy under stress conditions to enable recycling of cellular resources to maintain cellular functions and enable survival (Jiménez-Moreno et al., 2023). Thus, mutation of Lmx1b may also result in a deficiency of the beneficial autophagic response to stress (Jiménez-Moreno et al., 2023). Although further experiments are needed, dysfunctional autophagy may further prolong and exacerbate TM cell stress, resulting in more extensive depletion of cellular resources, exacerbated cellular dysfunction, and IOP elevation. Other consequences of the Lmx1b mutation that were evident in the V265D cells may also contribute to IOP elevation, including the overexpression of genes associated with ribosomes and calcium signaling, and depletion of genes involved with ECM synthesis and metabolism. However, these processes were not limited to TM3 cells or even to cell types that express detectable Lmx1b, suggesting that they are secondary damaging processes that are subsequent to the initiating, Lmx1b-induced perturbations in TM3 cells. Thus, we hypothesize that mitochondrial abnormalities in TM3 cells are of primary importance to IOP elevation in V265D glaucomatous mice. Based on our findings in TM3 cells, we tested if mitochondrial and metabolic disturbances are important in IOP elevation by administering nicotinamide (NAM). NAM is a form of vitamin B3 that is well-established to boost NAD+ levels, promote mitochondrial health and energy metabolism, relieve oxidative stress and thus promote cellular resilience (Williams et al., 2017b; Jang et al., 2012; Verdin, 2015; Mouchiroud et al., 2013; Gomes et al., 2013; Imai and Guarente, 2014; Song et al., 2021; Kang and Hwang, 2009). Supporting our hypothesis of primary metabolic dysfunction in TM3 cells, NAM treatment strongly protected V265D mice from IOP elevation. Thus, treatments that support normal metabolism may protect from IOP elevation in individuals with LMX1B variants including both developmental glaucoma and POAG patients (Gharahkhani et al., 2021; Khawaja et al., 2018; MacGregor et al., 2018; Choquet et al., 2018; Gao et al., 2018; Sweeney et al., 2003; Chen et al., 1998; Vollrath et al., 1998; Choquet et al., 2017). As NAM and other NAD+ boosting treatments are also known to be directly neuroprotective in glaucoma (Williams et al., 2017b; Hui et al., 2020; Williams et al., 2017a; Williams et al., 2018; de Moraes et al., 2022), our current data suggest that such treatments will have a double benefit for patients. As mitochondrial defects are becoming broadly associated with glaucoma risk and progression (Abu-Amero et al., 2006; Lo Faro et al., 2021; Petriti et al., 2024; Venkatesan and Bernstein, 2025a; Venkatesan et al., 2025b), these treatments could have wide-ranging potential to complement and augment existing IOP-lowering therapeutics through a completely distinct mechanism. Our results provide a thorough molecular characterization of mouse TM cells, providing much-needed molecular information on subtype specializations in regulating IOP and the roles of specific subtypes in glaucoma. This comprehensive TM atlas provides a new foundation to guide development of new glaucoma treatments. We validate its utility by implicating metabolic changes in a single TM cell subtype in glaucoma, with success of a metabolic treatment in a glaucoma model. We defined the TM as the region between the inner wall of Schlemm’s canal (SC, outer TM) and the anterior chamber (inner TM), extending from the anterior edge of the pars plana (posterior TM) to the posterior edge of Descemet’s membrane of the corneal endothelium (anterior TM). The SC was defined using a panel of validated markers that varied to allow for different antibody species and different secondary antibodies to be used in conjunction with the SC markers (Key resources table; Kizhatil et al., 2014). Sections were only included in the scoring analysis if they met the following criteria: Absence of obvious sectioning artifacts or abnormalities in the SC or TM region. Distinguishability of all landmarks defining the TM. Acceptably low background signal and absence of staining for non-specific or non-biological entities within the section. For each section, the TM was segmented and analyzed in two separate ways. The anterior-posterior distance was measured, and the TM was divided in half along this axis at the midway point (Figure 2—figure supplement 2C–D). Using the surface feature in Imaris, the area of individual marker staining was measured, and the total area in both the anterior and posterior zones was calculated. Because markers are expressed at different levels, we normalized across markers by calculating the percent of individual marker expression in the anterior and posterior halves within each section. These percentage values in anterior and posterior halves were compared both within markers and across all markers of a given TM cell subtype by Student’s t-test. The same analysis was repeated for the inner-outer halves by measuring the inner-outer TM distance at the midpoint of the TM (anterior-posterior axis) and dividing the TM in half at this value. A total of 130–160 sections were examined for markers of each individual TM cell subtype. These sections were from 10 to 12 individual eyes per cluster. All eyes were from WT mice of C57BL/6J background and between 3 and 6 months of age. Additional analysis was performed by selecting a subset of examined sections with staining for select markers (TM1: MYOC antibody, TM2: CRYM antibody, Inmt in situ, TM3: α-SMA antibody). These sections were of exceptionally high quality and had: (1) Anterior-posterior TM length between 125 and 200 µm. (2) Inner-outer TM distance is between 15 and 30 µm. With these selected sections, we subdivided the TM into eight different zones along both inner/outer and anterior/posterior axes (Figure 2—figure supplement 2F). For each individual section, we used Imaris to measure the anterior-posterior distance and divide the TM into three equal sectors (anterior, central, and posterior). Within each sector, the average depth of the TM was measured in Imaris. This calculation was used to divide the central and posterior sectors into three zones each (inner, intermediate, and outer). Because the anterior TM depth is thinner, we divided the anterior sector into two zones (inner and outer). In total, there were eight distinct zones. The percent of total marker area was calculated for each of the eight zones for each individual section as described above. Percent of marker area in each zone was compared as shown in Figure 2 by one-way ANOVA followed by Tukey’s honestly significant difference test. Mice were euthanized, and eyes were enucleated into DBG buffer containing 1X Dulbecco’s phosphate-buffered saline with 5.5 mM D-glucose (Sigma-Aldrich). Eyes were immediately dissected in DBG buffer to generate anterior segment eye cups, with centripetal relaxing cuts in the cornea to allow flattening (Figure 1—figure supplement 1). The tissue was fixed at room temperature for 30 min in a solution of 0.8% paraformaldehyde, 1.2% glutaraldehyde, and 0.08 M phosphate buffer (Smith-Rudt). Following fixation, each anterior segment was mounted on a slide and flattened under a coverslip overnight at 4°C. A 1 g weight was placed on top of the coverslip to aid in flattening the limbal region. The eyes were then washed three times in 1X PBS for 15 min each and stored in PBS under the same slide/coverslip setup to maintain flattening until embedding. Before further processing, individual limbal strips of the four quadrants of each were dissected from the surrounding cornea and sclera (Figure 1—figure supplement 1). These strips were post-fixed in 2% aqueous osmium tetroxide, rinsed in PBS, and dehydrated for epoxy resin embedding using EMBED 812 (Electron Microscopy Sciences). Embedding was performed while preserving the orientation of the limbal strip, with the TM (inner side) and cornea / sclera (outer side) clearly maintained. Embedded strips were imaged using computed tomography to locate the tissue, confirm TM orientation and flattening for en face sectioning, and to guide the sectioning process. Ultrathin, 70 nm, enface sections of the inner side of the limbal strip were taken using a Leica ultramicrotome (inner TM is the most superficial tissue being sectioned). Sections were placed onto formvar-coated slot grids then stained en grid using a combination of 5% Uranyl Acetate and Reynold’s lead citrate (Reynolds, 1963) for 17 and 7 min, respectively. Large mosaic regions of the TM were imaged at ×5000 magnification (2.18 nm/px) using a JEOL 1400FLASH TEM operating at 80 kV, equipped with a Gatan OneView camera. Mosaics were then computationally reconstructed using custom nornir-buildscripts (https://nornir.github.io/) and initially visualized in the Software suite Viking (http://connectomes.utah.edu). From each TM section, 20 cells with sampled nuclei were randomly selected from evenly spaced regions throughout the imaged area (approximately 25,000 μm² per eye). In the perinuclear area of each selected cell, up to 3 (typically 2–3) mitochondria were randomly selected and analyzed. The perimeter of the mitochondrial outer membrane (area) and inner membrane (cristae) was traced in ImageJ according to established protocols (Lam et al., 2021; Neikirk et al., 2023). The percentage of cristae area compared to the whole mitochondrial area was calculated (cristae fraction) for each mitochondrion. The number of mitochondria was counted in the perinuclear region of each analyzed cell. This number was normalized to an area of 100 μm² and averaged across cells. As each en face section sampled a large area of the TM, three sections from different eyes were examined for each genotype. All mice were 14 days old. A total of 178 mitochondria from WT eyes and 161 from V265D eyes were analyzed. Groups were compared by Student’s t-test.