Slc22a17 governs postnatal neurogenesis by maintaining the iron homeostasis in hippocampus

Domain: physics
Published: 2025-12-15
Editorial outcome: minor_revision

Abstract
Iron transporters are essential for numerous iron-dependent biological processes. Among them, SLC22A17 plays a key role in lipocalin-2 (LCN2)-mediated iron transport and is implicated in several human diseases. However, its precise molecular and physiological functions remain poorly understood. In this study, we demonstrate that Slc22a17 is critical for postnatal neurogenesis through its regulation of iron homeostasis in the hippocampus. Conditional knockout of Slc22a17 in the murine brain results in early postnatal mortality, severe growth retardation, excessive neural stem cell (NSC) apoptosis, and cognitive impairments, all driven by oxidative stress caused by iron overload. Mechanistically, using TurboID-based proximity labeling and immunoprecipitation, we identify an interaction between Slc22a17 and p62, which modulates Nrf2 activity. Loss of Slc22a17 activates the Nrf2/HO-1 pathway, paradoxically enhancing iron release while impairing iron efflux. This imbalance triggers the production of iron-catalyzed reactive oxygen species (ROS), leading to oxidative stress. Together, our findings highlight Slc22a17 as a potential therapeutic target for neurological disorders associated with iron dysregulation.

Introduction
The generation of functional neurons from neural stem cells (NSCs) is a crucial step in mammalian brain development, occurring primarily during the embryonic and early postnatal stages1,2. This neurogenic process is most active in two specific regions: the subventricular zone adjacent to the lateral ventricles and the sub-granular zone of the dentate gyrus3,4. During these stages, mammals experience an increased demand for iron to support various developmental processes, including neurogenesis, synaptogenesis, and the initiation of myelination5. Despite its importance, the relationship between iron metabolism and neurogenesis has received limited attention6. In contrast, excess iron accelerates the production of reactive oxygen species (ROS), triggering a cascade that results in cellular oxidative stress, which can lead to apoptosis or ferroptosis7–9. The harmful effects of ROS on cellular integrity not only compromise the self-renewal capacity of NSCs but also disrupt neurogenesis, long-term potentiation in the hippocampus, and, ultimately, cognitive function in mice4,10,11.

Among iron-homeostasis proteins, SLC22A17 was initially identified as a cell-surface receptor for lipocalin-2 (LCN2), also referred to as 24p3R, NGALR, or LCN2R12,13. Upon binding to SLC22A17, both apo-LCN2 (iron-free) and holo-LCN2 (iron-loaded) are internalized, facilitating iron efflux or influx, respectively12. SLC22A17 is highly expressed in the mammalian brain, particularly in neurons and oligodendrocytes14–16. Clinically, SLC22A17 has been implicated in the pathogenesis of several cancers, including glioma, as well as other diseases17–20. Despite extensive studies on its ligand LCN2, the physiological and molecular roles of SLC22A17 in the brain and the mechanisms underlying its function remain poorly understood.

Disruptions in iron metabolism promote cell death and contribute to human diseases by increasing the production of ROS9. In response to oxidative stress, nuclear factor erythroid 2-related factor 2 (Nrf2) provides well-established protective and neuroprotective effects by mitigating oxidative damage and mitochondrial dysfunction21,22. Within this critical ROS-response pathway, Kelch-like ECH-associated protein 1 (Keap1) regulates Nrf2 activity through ubiquitination and proteasome-dependent degradation23, maintaining oxidative balance. Sequestome1 (SQSTM1/p62) regulates the Nrf2-Keap1 signaling pathway by binding to Keap1, thereby disrupting Nrf2 ubiquitination and degradation24. Among the key targets of Nrf2, heme oxygenase-1 (Hmox1, HO-1) is induced by oxidative peroxides and catalyzes the degradation of heme to carbon monoxide, free iron, and biliverdin25,26. Biliverdin is subsequently reduced to bilirubin, which exhibits antioxidant properties27,28. On the other hand, HO-1 can also generate reactive iron, which can become toxic if it accumulates excessively27,29. Under disease conditions, overexpression of HO-1 may release pro-oxidative heme and hemoproteins, further exacerbating oxidative stress30,31. Elevated HO-1 levels are commonly observed in age-related neurodegenerative diseases, such as Alzheimer’s and Parkinson’s diseases32,33.

In this study, we characterized the unique physiological and molecular roles of Slc22a17 in iron homeostasis and hippocampal neurogenesis. We observed that whole-brain knockout of Slc22a17 in mice resulted in significant body weight loss, severe impairment of hippocampal NSC development, and early postnatal mortality. We demonstrated that Slc22a17, localized in the endoplasmic reticulum, regulates iron export in NSCs through an endosomal recycling pathway, thereby maintaining iron homeostasis. Furthermore, we found that Slc22a17 interacts with p62, and its loss activates the Nrf2/HO-1 pathway, leading to intracellular ROS accumulation. This accumulation results from the dual effects of increased iron release and impaired iron efflux. Notably, deletion of Nrf2 or pharmacological inhibition of HO-1 alleviated ROS-induced deficits in hippocampal neurogenesis. Together, these findings suggest that Slc22a17 cKO severely impairs neuronal development in the hippocampus.

Results
Slc22a17 conditional knockout (cKO) mice exhibit postnatal lethality and impaired neuronal development
Slc22a17 is one of the most highly expressed iron transporters in the hippocampus, second only to ferritin, as revealed by our transcriptomic analysis of hippocampal tissues (Fig. 1A; Supplementary Data 1). We first performed immunoblotting of Slc22a17 in 12 mouse organs and tissues, which revealed its high expression levels in the brain (Fig. S1A). To investigate its distribution, we used immunofluorescence staining on mouse brain sections. This analysis showed that Slc22a17 is present across various brain regions, including the hippocampus (Fig. S1B). These findings align with previous studies20 and underscore the functional importance of Slc22a17 in hippocampal processes. We next quantified Slc22a17 levels in the hippocampus at different developmental stages. Slc22a17 expression was low in neonatal mice (postnatal day 0, P0) but increased during development, paralleling the expression of the presynaptic marker Synapsin I (Fig. S1C). To further investigate, we assessed iron levels in fluorescence-activated cell sorting (FACS)-isolated neural progenitor cells (NPCs) at multiple time points, starting from embryonic day 14 (E14). Our analysis revealed a progressive increase in iron content from E14, peaking at birth, followed by a sharp decline between P7 and P14. This iron accumulation pattern was inversely correlated with Slc22a17 expression in NPCs during these developmental stages (Fig. 1B). These observations suggest a potential role of Slc22a17 in early neurogenesis and its involvement in iron homeostasis within NSCs.

We generated conditional knockout mice by crossing Slc22a17flox/flox mice with Nestin-Cre mice (Slc22a17flox/flox; Nestin-Cre, cKO). In these cKO mice, Slc22a17 mRNA was nearly undetectable in the hippocampus and cortex (Fig. S1D), and they exhibited marked postnatal lethality. Notably, 80% of the cKO mice died by postnatal day 21 (P21), whereas none of the wild-type (Slc22a17flox/flox, WT) littermates succumbed (Fig. 1C). The cKO mice also displayed significantly reduced body weight compared to WT, Nestin-Cre, and Het (Slc22a17 flox/+; Nestin-Cre) mice (Fig. 1D and Fig. S1E). This body weight discrepancy became more pronounced by P7 and persisted until P21 (Fig. 1E). At P14, cKO mice exhibited a significantly increased brain-to-body mass ratio, indicating a disproportionate reduction in body weight relative to brain weight (Fig. S1F). In contrast, no significant difference was observed in other cell-type-specific knockout mice (Fig. S1G).

To assess the effect of Slc22a17 deletion on postnatal neurogenesis, we examined the hippocampal structure of WT and cKO littermates at P14. The cKO mice exhibited nearly a 40% reduction in the number of Nestin+ NSCs (Fig. 1F, H) and a 20% decrease in the dentate gyrus (DG) volume compared to WT (Fig. S1H). Similarly, the number of immature neurons, as indicated by Dcx and Neurod1 markers, was significantly reduced in the cKO mice (Fig. 1G, H). Our data indicate that deletion of Slc22a17 disrupts hippocampal neurogenesis, particularly affecting postnatal hippocampal development.

Next, we examined neuronal morphology in the cKO hippocampus at P14 by crossing WT and cKO mice with Thy1-EGFP mice16. We found that Slc22a17 deletion reduced dendrite complexity and spine density in cKO GFP+ granule cells (Fig. 1I–K). Similar results were obtained using Golgi-Cox staining (Fig. 1I and Fig. S1I). Quantification of proteins involved in the pre- and postsynaptic compartments, including Synapsin I (Syn), NMDAR2A, GluR1, and neuronal nuclear protein NeuN, revealed significant decreases in all these proteins in cKO mice compared to WT littermates (Fig. 1L). In vitro culture of primary hippocampal neurons confirmed that Slc22a17 cKO neurons exhibited significantly reduced total neurite length (Fig. 1M) and lower Synapsin levels (Fig. S1J). Additionally, we observed an increase in the relative fluorescence intensity of the astrocytic marker GFAP, but no change in the number of Iba1+ microglia (Fig. S1K, L), which may indicate the presence of reactive astrocytes triggered by synaptic loss34. Together, these findings suggest that Slc22a17 cKO severely impairs neuronal development in the hippocampus.

Neural stem cell (NSC) proliferation and differentiation are impaired in the hippocampus of Slc22a17 cKO mice
A previous study demonstrated that Slc22a17 is expressed in Sox2+ and Nestin+ NSCs in mice and cultured neurospheres35, although its precise functions remain unclear. We first quantified the number of Pax6+ NSCs, Sox2+ NSCs, and Ki67+ proliferating cells and found a reduction in proliferating NSCs in the cKO DG at P14 (Fig. S2A, B). To further assess the impact of Slc22a17 deletion on NSC proliferation, we injected BrdU intraperitoneally into WT and cKO mice 2h before sacrifice at P14 to label proliferating cells. Quantifications showed that the number of BrdU+/Ki67+ and BrdU+/Sox2+ cells was significantly lower in the cKO DG compared with WT, indicating a reduced proliferation rate of NSCs in Slc22a17 cKO mice (Fig. 2A, B, and Fig. S2C). Next, we conducted clonal neurosphere culture assays and confirmed the deletion of Slc22a17 in cKO neurospheres using real-time qPCR and immunofluorescence (Fig. S2D, E). The number of primary and secondary neurospheres derived from cKO hippocampus revealed a significant reduction, as quantified per 1000 plated cells. Moreover, the diameter of primary and secondary neurospheres was also significantly decreased (Fig. 2C–E). In line with this, the number of BrdU+/Ki67+ and BrdU+/Sox2+ cells was also significantly decreased in cKO neurospheres (Fig. 2F, G). These results collectively suggest that Slc22a17 is essential for NSC proliferation.

We then analyzed NSC differentiation 7 days after BrdU injection at P1436. The number of NeuN+/BrdU+ cells in the DG of Slc22a17 cKO mice was significantly lower than in WT mice, indicating that Slc22a17 deletion disrupted NSC differentiation in the hippocampus (Fig. 2H, I and Fig. S2F). Furthermore, we cultured neurospheres in neuronal differentiation medium supplemented with fibronectin for 7 or 14 days. Immunofluorescence staining revealed that the proportion of neurons differentiated from cKO neurospheres was reduced by more than half compared to WT after 7 days of culture (Fig. 2J). Additionally, cKO neurosphere-derived neurons exhibited neurites that were, on average, 50% shorter than those of WT counterparts at both time points (Fig. 2K). Together, these findings suggest that Slc22a17 regulates hippocampal neuron development by modulating NSC proliferation and differentiation.

Slc22a17 deficiency impairs hippocampal adult neurogenesis and spatial learning and memory
After observing postnatal lethality and impaired NSC development in Slc22a17 cKO mice during the neonatal stage, we next sought to determine whether similar effects would occur in adult hippocampal neurogenesis. To investigate this, we generated inducible conditional knockout (iKO) mice by crossing Slc22a17flox/flox mice with tamoxifen-inducible Nestin-CreERT2 transgenic mice. Administration of intraperitoneal tamoxifen efficiently induced Cre-mediated recombination at LoxP sites in Nestin+ cells. To assess changes in NSCs in the DG, we used a Rosa26R-CAG::tdTomato Cre-reporter, which labels NSCs and their progeny, including proliferating cells (Ki67+), stem-like cells (Sox2+), immature neurons (Dcx+), and mature neurons (NeuN+) with tdTomato fluorescence (Fig. 3A). qPCR analysis confirmed a significant reduction in Slc22a17 mRNA expression in iKO hippocampus and neural progenitor cells (NPCs) isolated from iKO mice (Fig. S3A). We compared the number of tdTomato+ cells in the hippocampus of WT and iKO mice at 7, 14, and 28 days post-injection (dpi). In WT hippocampus, the number of tdTomato+ cells increased rapidly after 7 dpi, whereas in iKO hippocampus, this increase was slower (Fig. 3B, C). Immunofluorescence staining of brain sections revealed a significant reduction in the density of Ki67+, Sox2+, and Dcx+ cells (Fig. 3D, E). Moreover, the relative proportion of these cells among BrdU+ cells was also significantly decreased in the DG of iKO mice compared with WT (Fig. 3F, G). These results indicate that deletion of Slc22a17 impairs adult hippocampal neurogenesis.

Impaired adult neurogenesis has been linked to deficits in learning and memory37. To assess whether learning and memory were affected in iKO mice, we performed behavioral tests in 8-week-old animals. The Morris Water Maze (MWM) test, widely used to evaluate spatial learning and memory38, was employed to assess cognitive function in these mice. We recorded the latency of WT and iKO mice in finding the hidden platform during the 6-day training period, followed by probe trials on the 7th day after removing the platform. iKO mice displayed a significant deficit in spatial memory acquisition compared to their WT littermates. This was evidenced by a longer latency to locate the platform during training (Fig. 3H and Fig. S3B), more erratic movement paths (Fig. 3I), reduced time spent in the target quadrant after the platform was removed (Fig. 3J), and fewer platform crossings (Fig. 3K). To further assess hippocampal function, we conducted a contextual fear conditioning task. Although there was no difference in freezing behavior between iKO and WT mice during the training phase, iKO mice exhibited a significant decrease in freezing percentage when re-exposed to the conditioning context 24 h later (Fig. 3L and Fig. S3C). Collectively, these results indicate that impaired adult hippocampal neurogenesis in iKO mice leads to deficits in hippocampal-dependent brain functions.

Given the neuronal expression pattern of Slc22a17 illustrated in whole-brain immunofluorescence staining (Fig. S1B), we next examined the effects of Slc22a17 knockout in specific mature neuron populations. We crossed Slc22a17 flox/flox mice with transgenic lines expressing CaMKIIα-Cre (for glutamatergic neurons) and VGAT-Cre (for GABAergic inhibitory neurons)39. Slc22a17 flox/flox, CaMKIIα-Cre mice exhibited longer latency in the MWM and swam longer distances to find the platform compared to WT controls (Fig. S3D–F). In contrast, Slc22a17 flox/flox, VGAT-Cre mice showed no significant differences in behavior compared to WT mice (Fig. S3G–I). These findings suggest that Slc22a17 may play a functional role in glutamatergic neurons.

Slc22a17 deficiency induces iron accumulation and oxidative damage
We performed RNA sequencing (RNA-seq) analysis of primary cultured neurospheres from control and cKO mice, and revealed a set of 209 differentially expressed genes (DEGs) under Slc22a17 deletion (Supplementary Data 2). Up-regulated DEGs were enriched in iron-responsive cues and neuron apoptotic process in cKO neurospheres, while down-regulated DEGs were enriched for cell cycle, neuron migration, and neuron differentiation (Fig. S4A). Since Slc22a17 has been reported to mediate iron trafficking12, we measured the concentration of several divalent metal ions in the brain, liver, and spleen of cKO and WT mice at P14 using inductively coupled plasma-mass spectrometry (ICP-MS). The results revealed that iron concentrations were elevated in the whole brain (Fig. 4A) and hippocampus (Fig. 4B) of cKO mice, whereas zinc, copper, and manganese levels remained unchanged (Fig. S4B), indicating that Slc22a17 specifically mediates iron transport. In line with these findings, non-heme iron concentrations were also markedly increased in the brains of cKO mice (Fig. 4C), further supporting a selective role of Slc22a17 in regulating brain iron homeostasis. In the liver and spleen—two primary storage organs for iron—only iron concentrations were significantly higher in cKO mice compared to WT mice (Fig. S4C, D)40, potentially due to brain-specific Slc22a17 deletion indirectly causing tissue iron accumulation via central-peripheral regulation. We further observed increased hepatic hepcidin expression and elevated serum hepcidin levels in cKO mice (Fig. S4E). These changes in hepatic hepcidin could impair iron export, leading to increased tissue iron levels, which may contribute to the elevated liver iron content, or alternatively, may result from the increased liver iron levels. We also measured metal ion levels in neurospheres and observed a significant increase in iron concentration in cKO neurospheres, while the culture medium showed no change (Fig. 4D and Fig. S4F). To confirm this, we utilized Perl’s staining to visualize hippocampal iron accumulation in cKO mice and employed the iron-sensitive probes FerroOrange and Calcein to demonstrate elevated cellular iron levels in cKO neurospheres (Fig. 4E, F), where the fluorescence of Calcein is quenched by iron, allowing for the detection of increased cellular iron. These findings indicate that Slc22a17 deficiency leads to severe iron overload.

Excessive iron accumulation promotes oxidative stress by generating ROS, which can cause DNA damage, cell cycle arrest, and cell death41. To investigate this, we evaluated ROS levels and found that intracellular ROS was significantly higher in cKO neurospheres compared to WT. This ROS increase was abolished following 24 h of exposure to the iron chelator deferoxamine (DFO) or the antioxidant N-acetylcysteine (NAC) (Fig. 4G). To investigate DNA damage associated with oxidative stress, we used 8-hydroxy-2’-deoxyguanosine (8-OHdG), a marker of oxidized guanine lesions. As expected, elevated 8-OHdG intensity was detected in cKO neurospheres, which was reduced upon treatment with the iron chelator DFO or the NAC (Fig. 4H). Consistent with this, the malondialdehyde (MDA) level, a marker of lipid peroxidation, was also significantly higher in cKO neurospheres (Fig. 4I).

Excessive ROS levels often trigger apoptotic cell death. To assess apoptosis, we performed flow cytometry, western blotting, and immunofluorescence analysis. Flow cytometry revealed a significant increase in the proportion of apoptotic cells in cKO neurospheres, an effect that was reversed by DFO treatment (Fig. 4J, K). Western blot analysis showed elevated levels of pro-apoptotic proteins, including cleaved PARP, cytochrome c, cleaved Caspase-9, and cleaved Caspase-3 in cKO neurospheres (Fig. 4L). Immunofluorescence staining for cleaved caspase-3 further confirmed neuronal apoptosis in the cKO hippocampus (Fig. 4M). The release of cytochrome c and activation of caspases suggested mitochondrial dysfunction, which was further supported by JC-1 staining and electron microscopy. These techniques revealed severe mitochondrial damage in cKO neurospheres, including mitochondrial depolarization and swelling (Fig. 4N, O). To determine whether elevated iron exacerbated mitochondrial damage, we added ferric ammonium citrate (FAC), a soluble iron supplement, to increase intracellular iron levels. This treatment further aggravated mitochondrial damage in cKO neurospheres (Fig. 4N). Notably, the oxidative damage caused by Slc22a17 deficiency appears to be independent of ferroptosis, as the expression of ferroptosis-related drivers and suppressors remained unchanged between WT and cKO groups at both the RNA and protein levels (Fig. S4 G–I). Together, these findings demonstrate that Slc22a17 deficiency leads to iron overload-induced oxidative stress, resulting in ROS-dependent cell death.

Slc22a17 facilitates cellular iron efflux in response to iron overload
To investigate the effects of aberrant iron accumulation in the cKO hippocampus and neurospheres, we examined the expression of key proteins involved in iron uptake and storage. We observed decreased levels of transferrin receptor (TfR) and its regulator IREB2, as well as increased levels of Ferritin-H and Ferritin-L, which are indicative of iron overload in the cKO hippocampus (Fig. 5A). Based on these findings, we hypothesized that Slc22a17 may facilitate iron efflux in neural cells in response to elevated intracellular iron levels. Interestingly, we did not observe compensatory upregulation of ferroportin (Fpn, Slc40a1), but rather a reduction in Fpn protein levels in the hippocampus, suggesting that Fpn-mediated iron export may be impaired in the absence of Slc22a17. To test this hypothesis, we performed iron release experiments. Primary neurons were pre-incubated with FAC, cultured in fresh medium, and then analyzed for a decrease in intracellular iron content. The results showed that the rate of iron release was significantly reduced in cKO neurons compared to WT (Fig. 5B and Fig. S5A). Additionally, we generated transgenic mice overexpressing Slc22a17 in the brain (Slc22a17 OE/OE mice, OE) by crossing them with the Nestin-Cre mouse line. Using calcein staining, we visualized iron content in organotypic hippocampal slice cultures and found that FAC failed to elevate iron levels in the DG of the OE hippocampus (Fig. 5C), as calcein fluorescence decreases upon Fe³⁺ binding. Immunoblot analysis revealed that overexpression of Slc22a17 resulted in decreased levels of the iron storage protein Ferritin-H (Fig. 5D). These results obtained from both Slc22a17 knockout and overexpressing mice confirm that Slc22a17 plays a role in mediating iron export in the hippocampus.

Interestingly, we examined the endogenous localization of Slc22a17 in primary neurons, revealing its predominant intracellular distribution (Fig. 5E). This finding contrasts with its previously described role as a cell-surface receptor12 and suggests a potential relationship between the intracellular localization of Slc22a17 and its function in iron efflux. To investigate the subcellular localization of Slc22a17 and its role in iron trafficking, we generated HEK293 and HT22 cell lines overexpressing Slc22a17 tagged with GFP (Fig. S5B). Confocal microscopy confirmed its intracellular localization, and we observed co-localization of recombinant Slc22a17 with an endoplasmic reticulum (ER)-targeting fluorescent probe (Fig. 5F). We then conducted an iron release experiment using Slc22a17-OE cells. Overexpression of Slc22a17 accelerated iron transport out of the cells following 24-h FAC treatment (Fig. 5G), which was consistent with the reduced iron release rate observed in cKO neurons. We also analyzed the expression of two key genes involved in iron transport, Tfrc and Slc40a1, which are up-regulated and down-regulated, respectively, when intracellular iron levels decrease (Fig. S5C). Collectively, these results confirm that a portion of Slc22a17 is localized to the ER, and that overexpression of Slc22a17 facilitates iron export after FAC treatment.

Next, we investigated whether ER-localized Slc22a17 regulates iron export via the recycling endosome pathway, similar to the classical mechanism of Slc22a17-mediated iron trafficking12. To test this hypothesis, we examined our transcriptomic data, which revealed significant changes in the expression of several endosome markers (Fig. S5D). Notably, we observed downregulation of Rab11a, a recycling endosome marker, in cKO neurospheres. We then transfected Slc22a17-OE cells with plasmids encoding mCherry-Rab11 and BFP-Lcn2 fusion proteins, and used long-term live-cell imaging to monitor their behavior. The imaging data showed that BFP-Lcn2 and mCherry-Rab11 colocalized with GFP-Slc22a17 on the ER (Fig. 5H), suggesting that ER-localized Slc22a17 is associated with recycling endosomes.

To further investigate the role of Slc22a17 in cellular iron export, we compared the iron export ability between Slc22a17 and Slc40a1. We performed siRNA-mediated knockdown of SLC22A17 and SLC40A1 in HEK293 cells (Fig. S5E). Cells were exposed to FAC, and extracellular iron levels were measured using a non-heme iron assay at 4, 8, and 24 h after FAC removal. Knockdown of SLC40A1 significantly reduced iron efflux, while SLC22A17 knockdown also impaired iron export, particularly at later time points. Dual knockdown of both genes further blocked iron efflux compared to the siSLC22A17 group, suggesting the cooperative role of FPN in the SLC22A17-mediated iron efflux mechanism (Fig. S5F). siRNA targeting SLC22A17 or SLC40A1 were co-transfected with a plasmid encoding mCherry into cells, and fluorescence imaging 48 h post-transfection showed that SLC22A17 knockdown led to a moderate decrease in calcein green fluorescence intensity, while SLC40A1 knockdown caused more pronounced fluorescence quenching (Fig. S5G). Additionally, real-time monitoring using calcein green fluorescence revealed that SLC22A17 knockdown accelerated iron accumulation, while SLC40A1 knockdown led to more severe intracellular iron retention (Fig. S5H). Overexpression of Slc22a17 had no significant effect on iron accumulation in the short term, but over a longer period, it showed similar iron export effects as Slc40a1 (Fig. S5I, J). These results indicate that Slc40a1 directly mediates iron export, while Slc22a17 may function upstream, playing a key role in iron transport from the ER to the cytoplasm.

Slc22a17 interacted with p62 to regulate the activity of Nrf2/HO-1 pathway
The deletion of Slc22a17 led to the upregulation of gene sets associated with oxidative stress response and iron homeostasis, as revealed by correlation network analysis (Fig. 6A). Notably, several mRNAs that were significantly up-regulated in cKO neurospheres were encoded by redox-regulated genes. Among them, Hmox1, a gene containing antioxidant response elements (ARE), was identified as a downstream target of the transcription factor Nrf2 (Fig. 6B)42. Further analysis revealed an enrichment of Nrf2-activated genes among the up-regulated genes in cKO neurospheres, providing additional evidence for the activation of the Nrf2 signaling pathway (Fig. 6C). QPCR analysis confirmed a marked reduction in the expression of neurogenesis-related genes, such as Bmp4 and Bdnf (Fig. S6A), and an increase in the expression of oxidative stress response genes, including Hmox1 and Aox1 (Fig. S6B). In addition, ATAC-seq analysis of neurospheres from cKO and WT mice identified 1528 loci with increased chromatin accessibility, the majority of which were localized to promoters, while only seven loci exhibited reduced accessibility (p<0.05, Fig. S6C–E and Supplementary Data 3). Consistent with our RNA-seq findings, we observed increased chromatin accessibility at the Nfe2l2 and Hmox1 loci in cKO neurospheres (Fig. 6D).

Nrf2 translocates to the nucleus in response to oxidative stress, where it binds to AREs and activates the transcription of target genes, such as Hmox1. This process may facilitate heme degradation and the release of free iron43. We observed increased expression of Nrf2, phosphorylated Nrf2 (p-Nrf2), and HO-1 in cKO neurospheres, accompanied by elevated levels of p62, which binds to Keap1 and promotes Nrf2 nuclear translocation (Fig. 6E). Immunoblot analysis revealed upregulation of nuclear Nrf2 and cytosolic HO-1 protein levels in cKO neurospheres compared to WT controls (Fig. 6F). Next, we examined the expression of proteins involved in the Nrf2/HO-1 pathway in Slc22a17-overexpressing (Slc22a17-OE) cell lines and OE mice. In these models, we observed a significant downregulation of nuclear Nrf2 and cytosolic p62 levels upon Slc22a17 overexpression (Fig. 6G and Fig. S6F). Additionally, we detected reduced Nrf2 ubiquitination in the cKO hippocampus, a finding consistent with enhanced nuclear translocation, as confirmed by confocal microscopy (Fig. 6H, I). This effect resembled the response observed with the known Nrf2 activator, cobalt protoporphyrin (CoPP)44. To further investigate the role of Nrf2 in this context, we infected cKO neurospheres with lentiviruses expressing shNrf2 and observed that Nrf2 knockdown significantly reduced the aberrant induction of HO-1 in cKO neurospheres (Fig. S6G).

To identify SLC22A17-interacting proteins, we performed TurboID-based proximity labeling45, followed by quantitative proteomic analysis. This revealed that p62 may serve as a potential interacting partner of SLC22A17 (Fig. S6H and Supplementary Data 4). To validate this interaction, we conducted co-immunoprecipitation (co-IP) analysis. Flag-tagged Slc22a17 efficiently co-immunoprecipitated with p62-HA, confirming their association (Fig. 6J). Confocal imaging further showed that a portion of Slc22a17 colocalized with p62, and this co-localization increased after iron addition, in line with the proteomic results (Fig. 6K and Fig. S6H). Although we observed that p62 was up-regulated in the cKO hippocampus, the mechanism by which Slc22a17 regulates p62 remains unclear. To investigate this further, we expressed GFP-p62 in a CRISPR/Cas9-mediated SLC22A17 knockout cell line (SLC22A17-/-) and labeled lysosomes with LysoTracker Red to track their intracellular localization. Live-cell imaging revealed that, in the control group, p62 predominantly fused with lysosomes, entering the autophagic pathway for degradation. In contrast, p62 showed minimal co-localization with lysosomes in SLC22A17-/- cells, resulting in failure in degradation and accumulation of large p62 droplets (Fig. 6L). p62 droplets are known to act as receptors for autophagy, where autophagosomes form at the droplet surface, mediated by LC3-conjugated membranes46. Using live-cell imaging to explore Slc22a17’s role in autophagy, we observed that Slc22a17 colocalized with both p62 and LC3. Furthermore, Slc22a17 formed small puncta at the surface of p62 droplets, similar to LC3 (Fig. S6I). Additionally, we found that vesicular Slc22a17 colocalized with the late endosome marker Rab7 (Fig. S6J). These findings suggest that Slc22a17 participates in the endocytic-autophagic pathway, facilitating p62 degradation. In the absence of Slc22a17, p62 accumulates, which inhibits Keap1 and activates the Nrf2 signaling pathway. Collectively, these data highlight a functional link between Slc22a17 deficiency and Nrf2/HO-1 pathway activation, which may exacerbate oxidative injury and disrupt neurogenesis.

Reducing iron levels or inhibition of Nrf2/HO-1 signaling rescues learning and memory deficits in Slc22a17 iKO mice
To assess whether iron overload is critical for triggering abnormal neurogenesis and impairing learning and memory, we fed 8-week-old WT and iKO mice diets with varying iron levels. After four weeks, iKO mice on a low-iron diet showed significantly improved performance in MWM tests compared to those on normal- or high-iron diets. Furthermore, Slc22a17 iKO mice treated with membrane-permeable DFO also exhibited recovery in learning and memory responses (Fig. 7A–D). Consistently, the numbers of Ki67⁺, Nestin⁺, NeuroD1⁺, and Dcx⁺ cells in the hippocampus were markedly restored in iKO mice following either a low-iron diet or DFO treatment, indicating a rescue of impaired neurogenesis (Fig. S7A, B). In contrast, WT mice on different iron diets did not show significant performance differences in MWM tests (Fig. S7C–E).

To explore the role of HO-1 in oxidative damage, we treated mice with the competitive HO-1 inhibitor zinc protoporphyrin IX (ZnPP). Chronic ZnPP administration significantly improved learning and memory in iKO mice (Fig. 7E–H). We next examined the regulatory role of Nrf2 in hippocampal structure and functions. To determine whether activation of Nrf2/HO-1 signaling contributed to impaired learning and memory in iKO mice, we bred iKO mice with Nrf2 knockout (Nrf2-/-) mice. The resulting double knockout (Slc22a17 flox/flox, Nestin-CreERT2; Nrf2-/-; DKO) mice showed alleviated learning and memory impairments in MWM tests (Fig. 7I–L). Additionally, the number of Ki67+, Sox2+, NeuroD1+, and Dcx+ cells in the DG was significantly higher in DKO mice compared to iKO mice (Fig. 7M, N). These cumulative findings demonstrate that Slc22a17/Nrf2/HO-1 signaling plays a crucial role in maintaining iron homeostasis, adult hippocampal neurogenesis, and learning and memory. Slc22a17 deficiency promotes nuclear accumulation of Nrf2, thereby enhancing Nrf2-dependent HO-1 expression, which ultimately disrupts neurogenesis in the brain.

Methods
Animals
All animal experiments were performed in accordance with guidelines of the Institute of Laboratory Animal Research Center of Tsinghua University. All animal procedures used in the study were approved by the Administrative Committee of Experimental Animal Care and Use of Tsinghua University. They licensed by the Science and Technology Commission of Beijing Municipality (SYXK-2014-0024). Mice were housed in a temperature (22°C RT) and light (12-h light/dark cycle) regulated room in a SPF facility and received food and water ad libitum.

Slc22a17 floxed mice (Slc22a17flox/flox) were purchased from Shanghai Biomodel Organism Science & Technology Development Co., Ltd. Slc22a17flox/flox mice were crossed with the Nestin-Cre (JAX:003771, kindly provided by Bailong Xiao, Tsinghua University, China) line to generate Slc22a17flox/flox; Nestin-Cre (defined as conditional knockout, cKO) mice and Slc22a17flox/flox littermates (defined as Wild-type, WT). Inducible conditional knockout mice were generated by crossing Slc22a17flox/flox mice with the Nestin-CreERT2 (JAX:016261, kindly provided by Qin Shen, Tongji University, China) line carrying a Cre-dependent tdTomato reporter (JAX:007909), followed by tamoxifen administration. Thy1-GFP-M mice (JAX: 007788, kindly provided by Zengqiang Yuan, Beijing Institute of Basic Medical Sciences, China) were crossed with WT or cKO mice to label a variety of neuronal subsets. Slc22a17flox/flox mice were also crossbred with CaMKIIα-Cre (JAX:005359, kindly provided by Yichang Jia, Tsinghua University, China), Emx1-Cre (JAX:005628), VGAT-Cre (JAX:016962), Olig1-Cre (JAX:011105), and Lepr-Cre60 mice to generate neuron or glia-specific knockout mice. To overexpress Slc22a17 in the brain, ROSA26loxP-stop-loxP-Slc22a17-3XFlag mice (Slc22a17OE/OE) were purchased from Cyagen US Inc. and mated with the Nestin-Cre mice to obtain Slc22a17OE/OE; Nestin-Cre mice. The resulting Slc22a17OE/OE (defined as Wild-type, WT) and Slc22a17OE/OE; Nestin-Cre (defined as overexpressed, OE) littermate mice were used for the experiments. Nrf2 knockout (Nrf2-/-) mice (JAX:017009, kindly provided by Fudi Wang, Zhejiang University, China) were crossbred with cKO mice to generate Slc22a17 and Nrf2 double knockout (defined as double knockout, DKO) mice.

Mice of either sex on C57BL/6 were used in the majority of this study. In experiments involving adult neurogenesis and behavioral assays, we exclusively used male mice. All mice used in behavioral assays adhered to animal welfare guidelines, and data from mice that were injured or died during behavioral assays were removed. The influence of sex was not evaluated in this study. Age is specified in the main text.

Drug administration
Tamoxifen (Sigma-Aldrich, T5648) was prepared in 100 mL corn oil to mixture 10 mg/mL. For adult male mice, Tamoxifen (100 mg/kg) was administered by intraperitoneal injection once a day for five consecutive days.

Mice were intraperitoneally injected with 100 mg/kg deferoxamine (DFO, Sigma-Aldrich) seven days before examination or sacrifice.

Mice were intraperitoneally injected with 10 mg/kg ZnPP (Milipore, 691550) seven days before examination or sacrifice.

Mice were fed with standard rodent laboratory diet (TROPHIC Animal Feed High-Tech Co. Ltd) containing 47 ppm iron (standard diet), 12 ppm iron (Low-iron-diet), or 912 ppm iron (High-iron-diet).

Immunofluorescence staining
Animals were perfused with cold 4% paraformaldehyde (in 0.1 M PBS, pH 7.4) and post-fixed overnight, cryoprotected with 20% and 30% sucrose. For immunofluorescence staining in tissues, cryo-sections (30 μm) were permeabilized and blocked in the blocking buffer (5% BSA and 0.4% Triton X-100 in PBS) for 1 h at room temperature (r.t.) and incubated overnight (4°C) with primary antibody. For staining in cells, cells in confocal dishes were fixed with 4% PFA for 10 min and then permeabilized and blocked in the blocking buffer (5% BSA and 0.2% Triton X-100 in PBS) for 1 h r.t. and incubated overnight (4°C) with primary antibody.

Antibodies used in the study were: Rabbit anti-Nestin (Abcam, ab221660); Rabbit anti-Neurod1 (Proteintech, 12081); Rabbit anti-Dcx (Abcam, ab207175); Mouse anti-Tuj1 (Biolegend, 801201); Rat anti-BrdU (Abcam, ab6326); Rabbit anti-Ki67 (Abcam, ab15580); Rabbit anti-Pax6 (Abcam, ab195045); Rabbit anti-Sox2 (Abcam, ab92494); Rabbit anti-NeuN (Abcam, ab177487); Rabbit anti-8OHdG (Abnova, MAB6638); Rabbit anti-Cleaved Caspase-3 (Cell Signaling Technology, 9664); Rabbit anti-Slc22a17 (Sigma-Aldrich, SAB3500306); Mouse anti-Nrf2 (Abcam, ab62352); Mouse anti-GFAP (Cell Signaling Technology, 3670S); Mouse anti-Iba1 (Abcam, ab283319).

After washing with PBS, sections were incubated with secondary antibody for 1 h r.t.. and counterstained with DAPI for 10 min. Slides were mounted in Fluoromount (SouthernBiotech, 0100-01) and visualized by Leica STELLARIS 8 FALCON confocal microscopy.

For stereological analysis, consecutive brain tissue sections were procured to quantify the number of labeled cells. Quantifications of marker-positive cells were performed in at least three sections containing the Dentate Gyrus (DG) from at least three different animals. The exact value of n is described in the figure legends.

BrdU treatment
For analysis of cell proliferation in the dentate gyrus, mice were injected with BrdU (50 mg/kg body weight, i.p., Sigma-Aldrich) and analyzed 2 h later. For analysis of cell differentiation, mice were injected with BrdU and analyzed 7 days later. For BrdU immunostaining, these sections were subjected to DNA denaturation with 1 N HCl for 30 min at 37°C. The following procedures were immunofluorescence staining.

Golgi-Cox staining
The brains were stored in the dark for 2 days (37°C) in the Golgi-Cox solution and then sectioned at a thickness of 200 μm in the coronal plane with a vibratome. All the sections were collected and stained with ammonia, Kodak Film Fix, and then dehydrated, cleaned, and mounted using resinous medium.

Fluorescence-activated cell sorting (FACS) of neural progenitor cells
Neural progenitor cells (NPCs) were isolated using fluorescence-activated cell sorting (FACS) based on established protocols described by Liu et al.61. Briefly, NPCs were obtained from mouse brain tissues at multiple developmental stages, including embryonic day 14 (E14), embryonic day 18 (E18), postnatal day 0 (P0), P7, P14, and P21. Tissues were enzymatically dissociated to single-cell suspensions, stained with fluorophore-conjugated antibodies, and sorted for CD24-Thy1-/lo cells using a FACSAria III (BD Biosciences). The following antibodies were used: anti-CD90.2 (Thy-1)-APC (1:400, BD Biosciences, 561641) and anti-CD24-PE (1:400, BD Biosciences, 553262). Dead cells were excluded using Fixable Viability Dye EF506 (Thermo Scientific).

Primary NSCs culture
NSCs were isolated from the hippocampus of P0 WT and Slc22a17 cKO mice (within 24 h after birth) based on previously published methods with some modifications62. Mouse hippocampal tissues were acutely dissected and dissociated in 2 mL of Accutase (GIBCO) for 20 min, and 3 mL of DMEM-F12 (Procell, PM150312) containing 1% B27 (GIBCO), 1% N2 (Invitrogen), 20 ng/mL epidermal growth factor (EGF) (Peprotech, 100-15), 10 ng/mL basic fibroblast growth factor (bFGF) (Peprotech, 100-18B), and penicillin/streptomycin (Beyotime, ST488S) was added into each sample to stop digestion. After filtering through a 70-μm cell strainer (Falcon, 352350) and washing with DMEM-F12 containing penicillin/streptomycin, the single-cell suspension (approximately 5×106 per mouse) was collected and cultured with DMEM-F12 containing 1% B27, 1% N2, 20 ng/mL EGF, and 10 ng/mL bFGF in a 5% CO2 incubator at 37°C. After 14 days of culture, neurospheres were used to both western blot analysis and immunofluorescence. Primary neurospheres were collected after 14 days of culture, dissociated into single cells using Neurocult dissociation kit (StemCell, 05702) and seeded again to obtain secondary NSCs.

Fibronectin-induced neurosphere differentiation assay
24-well plates containing sterile glass coverslips were pre-coated with 0.01% poly-D-ornithine overnight at 4°C, washed with PBS, and further coated with fibronectin (5 μg/mL, MCE, HY-P3160) for 2 h at 37°C. Neurospheres (~100–200 μm in diameter) were gently dissociated with Accutase at 37°C for 5–10 min into small clusters and seeded at a density of 1×105 cells per well in neurobasal medium (Invitrogen, 21103049) supplemented with B27 (GIBCO), GlutaMax (GIBCO, 35050061). Cultures were maintained for 7–14 days with half-medium changes every 2–3 days, and neuronal differentiation was evaluated by immunostaining for neuronal markers.

Primary neuron culture
Primary mouse hippocampal neurons were acutely dissociated according to the previously described method with some modifications63. Briefly, the hippocampal tissues were dissected from P0 WT and Slc22a17 cKO mice (within 24 h after birth), and dissociated in 0.25% trypsin-EDTA (GIBCO, 1798279) for 15 min to obtain a single-cell suspension. The cells suspension was centrifuged to collect cells after terminating the digestion process. Cells were re-suspended in neurobasal medium (Invitrogen, 21103049) supplemented with B27, GlutaMax (GIBCO, 35050061), and penicillin/streptomycin and cultured on 0.1 mg/mL poly-L-lysine (PLL) (Sigma-Aldrich, P2636) coated plates at 37°C in a humidified incubator containing 5% CO2. After 14 days of culture, neurons were used for both Western blot analysis and immunofluorescence.

Western blot
Tissues and cells were lysed with RIPA buffer containing Protease Inhibitor for 1 h on ice, then centrifuged at 14,000×g for 15 min. Collected the supernatant with SDS loading buffer, 100°C, 10 min. Total protein was loaded into a 10% SDS-PAGE gel and then transferred onto PVDF membranes. Membranes were blocked in 5% nonfat milk in PBST before incubation with primary antibodies overnight at 4°C. Secondary antibodies used for 1 h r.t.. Antibodies used in the study were: Rabbit anti-Slc22a17 (Abcam, ab124506); Rabbit anti-NeuN (Abcam, ab177487); Rabbit anti-Synapsin I (Abcam, ab64581); Rabbit anti-NMDAR2A (Abcam, ab124913); Rabbit anti-GluR1 (Abcam, ab109450); Rabbit anti-PARP (Cell signaling Technology, 9532); Mouse anti-Cytochrome c (BD Biosciences, 556433); Mouse anti-Caspase-9 (Cell Signaling Technology, 9508); Rabbit anti-Caspase-3 (Cell Signaling Technology, 9662); Rabbit anti-IRP2 (Cell Signaling Technology, 37135); Rabbit anti-Transferrin Receptor (Abcam, ab214039); Rabbit anti-Ferroportin (Thermo Fisher, PA5-22993); Rabbit anti-Ferritin Heavy Chain (Abcam, ab183781); Rabbit anti-Ferritin Light Chain (Abcam, ab109019); Rabbit anti-Nrf2 (phosph S40) (Abcam, ab76026); Mouse anti-Nrf2 (Abcam, ab62352); Rabbit anti-Heme Oxygenase 1 (Abcam, ab68477); Rabbit anti-Keap1 (Cell Signaling Technology, 8047); Rabbit anti-p62 (Proteintech, 18420-1-AP); Rabbit anti-xCT (Cell Signaling Technology, 12691); Rabbit anti-GPX4 (Cell Signaling Technology, 52455); Rabbit anti-NCOA4 (Cell Signaling Technology, 66849); Mouse anti-DMT1 (Abcam, ab123085); Mouse anti-GAPDH (Proteintech, 60004); Mouse anti-Beta Actin (Proteintech, 66009); Mouse anti-Beta Tubulin (Beyotime, AF2835); Rabbit anti-Lamin B1 (Proteintech, 12987-1-AP); Rabbit anti-Histone H3 (Abcam, ab32388). In Western blot quantifications, target proteins were first normalized to their respective loading controls and further normalized by adjusting to the average expression of inner reference proteins across all groups.

Annexin V/PI staining
Neurospheres were collected, washed in cold PBS, and binding buffer. FITC-conjugated Annexin V 5 μL and propidium iodide 50 μg/mL were added to the cells, incubated for 15 min at RT in the dark. Propidium iodide signals were measured using the FACSCaliber 2 flow cytometer. Analysis was further performed using the FlowJo 7.6.

Intracellular ROS measurement
Neurospheres were incubated with 10 μM of DCFH-DA dye for 30 min at 37°C. After washing with DMEM medium, cells were further washed with PBS. The amount of intracellular ROS levels was analyzed on a BD Calibur flow cytometer, and data were analyzed using FlowJo 7.6.

MDA measurement
MDA levels were determined using the thiobarbituric acid method by a commercial kit (Solarbio, BC0025) according to the manufacturer’s instructions.

JC-1 analysis
Mitochondrial membrane potential was measured by the JC-1 fluorescent probe (Beyotime, C2003S). FAC-treated or non-treated cells were analyzed according to the manufacturer’s instructions.

Plasmid construction
GFP-fusion expressed Slc22a17 plasmid (Slc22a17-GFP), mCherry-fusion expressed Slc22a17 plasmid (Slc22a17-mCherry), mCherry-fusion expressed Rab11a plasmid (Rab11a-mCherry), mCherry-fusion expressed Rab7a plasmid (Rab7a-plasmid), BFP-fusion expressed Lcn2 plasmid (Lcn2-BFP), GFP-fusion expressed p62 plasmid (p62-GFP), and BFP-fusion expressed Lc3b plasmid (Lc3b-BFP) were generated by PCR-subcloning. Plasmid vectors were co-transfected into the HEK293 or HT22 cell line using PEI or Lipofectamine 3000 (Invitrogen, L3000001). Live-cell imaging was performed using Zeiss LSM980 Airyscan 2 confocal microscopy.

Overexpressing stable cell line
HT22 (Cat# CL-0697, Procell) or HEK293T (CRL-3216, ATCC) cells were maintained in Dulbecco’s Modified Eagle Medium (DMEM, Cytiva) supplemented with 10% FBS at 37°C with 5% CO2. The gene encoding Slc22a17 or Slc40a1 was cloned into the Pljm1-Puro vector. Cells were co-transfected with Pljm1-Slc22a17 or Pljm1-Slc40a1, psPAX2, and pMD2.G using PEI (Polyscience). Viral supernatants were collected at 72 h post-transfection, filtered through a 0.45 μm filter, and stored at −80°C. Cells were seeded at 2×105 cells/well in 6-well plates and transduced with lentiviral supernatants in the presence of 8 μg/mL polybrene (Yeasen). After 24 h, the medium was replaced with fresh DMEM containing 10% FBS. Selection with 3 μg/mL puromycin (Solarbio) began 24 h post-transduction. Single colonies were isolated and expanded. Total RNA extracted from puromycin-resistant clones was used to quantify overexpression levels of Slc22a17 and Slc40a1 using qPCR.

CRISPR-Cas9-mediated SLC22A17 knockout cell line
CRISPR-Cas9-mediated knockout of SLC22A17 was performed using the pX458 plasmid containing sgRNAs targeting the third and tenth exons of SLC22A17 (SLC22A17-sgRNA1: 5’-ACCTGTCTGCGGGGTAACCC-3’; SLC22A17-sgRNA2: 5’-TAGGATGCTCACAATCCCAC-3’). Cells were co-transfected with the plasmid using PEI. GFP-positive cells were sorted by flow cytometry to isolate single clones 48 h post-transfection. Selected clones were seeded into 96-well plates and cultured. After 3 weeks, cells from selected clones were split: half were expanded into 6-well plates for further culture, and the other half had genomic DNA extracted using the TIANamp Genomic DNA Kit (TIANGEN) for sequencing to confirm SLC22A17 knockout.

Transmission electron microscopy
Tissue processing was carried out as previously described64. Briefly, mice were anesthetized and perfused with 2% PFA/2% glutaraldehyde in PBS. Tissues were dissected and postfixed in 1% OsO4. Ultrathin sections were stained with lead citrate for electron microscopy imaging.

Perl’s staining
DAB-enhanced Perl’s iron staining was performed according to what was described previously65. After deparaffinization, tissue slides were incubated in freshly prepared, acidified 1% potassium ferrocyanide (Sigma-Aldrich) in distilled water (pH ~1.0 to 1.5) solution for 40 min r.t.. Afterward, slides were washed three times in distilled water and incubated in methanol containing 0.01 M NaN3 and 0.3% H2O2 for 75 min r.t.. Slides were washed three times in 0.1 M PBS (pH 7.4) and then incubated in PBS containing 0.025% DAB and 0.005% H2O2 for 40 min r.t. in the dark and counterstained with Hematoxylin. As a negative control, one duplicate slide was incubated with non-acidified ferrocyanide solution (pH ~8.0), which did not show any staining. Additionally, coverslips with cells permeabilized with Triton X-100 prior to Perl’s staining as a negative control did not show iron staining.

Iron measurement
The brain, liver, spleen, and neurosphere were collected, weighed, and sent for quantitative elemental analysis with inductively coupled plasma-mass spectrometry (ICP-MS) XII by the Department of Physics of Tsinghua University.

Brain non-heme iron was measured as described previously66. Brain tissue samples were digested in NHI acid (10% trichloroacetic acid (Aladdin, T104257) in 3 M HCl) at 65–70°C for 48 h. Equal volumes of sample or iron standard (500 μg/dl) were incubated with buffer (0.2% thioglycolic acid (Aladdin, T501446) and 0.02% disodium-4,7-diphenyl-1,10-phenanthroline disulfonate (Aladdin, B339500) in 50% saturated NaAc solution) for 10 min r.t.. Absorbance of the samples was read at 535 nm, and unknowns were quantified using a standard curve. Results are reported as micrograms of iron per gram of wet tissue weight.

Intracellular iron was measured using FerroOrange (DOJINDO, F374) and Calcein-AM (Invitrogen, C1430) as described12. Cells were stained with 1 μM FerroOrange or 0.5 mM Calcein-AM in PBS for 10–30 min r.t. and then washed three times with PBS. Fluorescence images were captured using Leica STELLARIS 8 FALCON confocal microscopy and processed using Leica Application Suite X (LASX).

To dynamically monitor cellular iron uptake, transfected HEK293 cells were seeded into 96-well black-wall clear-bottom plates (Beyotime-FCP965) at a density of 3×105 cells/well. After 48 h, cells were incubated with 0.5 μM calcein-AM for 30 min, washed, and immediately subjected to live fluorescence measurement using a Multimode plate reader (PerkinElmer, 494/514 nm). Ferrous chloride (FeCl₂, 100 μM) was added directly to the wells during measurement, and fluorescence intensity was continuously recorded every 10 s for 400 s to assess the kinetics of iron uptake and calcein quenching.

Organotypic slice culture assay
Organotypic cultures were prepared as previously described67. Brains from WT and Slc22a17-OE mice (P14) were dissected and glued (Super Glue Loctite) onto the chuck of an ice-cooled vibratome Leica VT1200S. 300 μm coronal sections were cut and collected in chilled 20% DMEM. The coronal slices were cultured in confocal dishes, and FAC (Sigma-Aldrich) was added to a randomly selected group of slices for 2 h. Fluorescence images were acquired using Leica STELLARIS 8 FALCON confocal microscopy.

TurboID-based proximity labeling and mass spectrometry
The pLX304-lgK-V5-TurboID-KDEL plasmid was obtained from Dr. Wei Qin (Tsinghua University). According to the method reported previously68, the TurboID gene was amplified with pLX304-lgK-V5-TurboID-KDEL plasmid as a template. The SLC22A17 gene was amplified with human cDNA as a template. pLX304-lgK-V5-TurboID-KDEL used restriction sites BamHI and AgeI, and the SLC22A17 and TurboID fragments were recombined into the linearized pLX304-lgK-V5-TurboID-KDEL plasmid. The successfully sequenced plasmid was named SLC22A17-TurboID.

The SLC22A17-TurboID plasmid was transfected into HEK293T cells. After 24 h of transfection, cells were treated with 100 μM of DFO for 12 h. Subsequently, cells were treated with DMEM containing 50 μM Biotin for 10 min (Sigma-Aldrich, B4639). After washing with cold PBS (repeated washing twice), the cells were lysed with RIPA to obtain protein samples. Negative controls were included in which either the DFO or the biotin was omitted.

Incubate 100 μL streptavidin agarose resin beads (Thermo Scientific, 20353) with 2 mg protein from each sample with rotation overnight at 4°C. After overnight incubation, the supernatant was discarded, and the beads were washed with 1 mL of RIPA buffer (repeated washing twice). Biotinylated proteins were eluted by boiling each sample in 60 μL of 1× protein loading. Biotinylated proteins were subjected to mass spectrometry identification in the Protein Core Facility of Tsinghua University.

Co-immunoprecipitation
The pLJM1-p62-HA and pCMV-Slc22a17-3xFLAG plasmids were also constructed through homologous recombination. Cell lysates derived from HEK293T cells transiently transfected with plasmids were prepared using a lysis buffer (Beyotime, P0013) and protease inhibitor cocktail (Roche, 04693116001). The anti-Flag magnetic beads (Bimake, B26101) or anti-HA magnetic beads (Bimake, B26201) were incubated with cell lysates with rotation overnight at 4°C and subsequently washed five times with a washing buffer (TBS buffer, Beyotime, ST661) containing protease Inhibitor cocktail. The immunoprecipitated proteins were eluted with 1× SDS loading buffer.

Nrf2 ubiquitination assay
Tissues were lysed with lysis buffer (TBS buffer containing 0.3% Triton X-100 and protease Inhibitor cocktail) for 1 h on ice, then centrifuged at 14,000×g for 15 min to collect the supernatant. Protein A/G Immunoprecipitation Magnetic Beads (Bimake, B23201) were incubated with 20 μg/mL of Nrf2 antibodies for 15 min to bind the antibody. Equal amounts of lysates were incubated with Nrf2-beads with rotation overnight at 4°C and subsequently washed five times with a washing buffer (TBS buffer containing 0.3% Triton X-100 and protease Inhibitor). The immunoprecipitated proteins were eluted with 1× SDS loading buffer, and the ubiquitination levels of Nrf2 were detected by Western Blot.

RNA-seq and data processing
For RNA-seq analysis, total RNA was extracted using the RNeasy Lipid Mini Kit (QIAGEN, 74134). 1 μg RNA sample. RNA quality was determined by Agilent 2100. The RNA samples were sent to Huada (Wuhan) Sequencing Company for RNA sequence establishment. Gene counts were calculated for each transcript and normalized to determined differentially expressed genes using DESeq2 (v1.38.3)69, with significance defined by p<0.05 and fold change >1.5. GSEA (Gene Set Enrichment Analysis) was performed using the default parameters of the clusterProfiler R package (v4.7.1.2), with significance defined by a false discovery rate (FDR)<0.25. The list of NRF2-activating genes used in GSEA was obtained from available dataset70. Gene enrichment and interaction network were analyzed using Cytoscape (v3.7.1)71.

ATAC-seq and data processing
ATAC-seq was performed using the previously mentioned protocol72. Briefly, Nuclei isolated from 5×104 neural stem cells were used for ATAC-seq. Cells were harvested at 500×g 4°C for 5 min, and then cell pellets were re-suspended in 100 μL of lysis buffer (10 mM Tris-HCl, pH 7.4, 10 mM NaCl, 3 mM MgCl2, 0.5% NP-40) and then nuclei were centrifuged at 500×g 4°C for 15 min. The nuclei pellets were re-suspended in the transposition reaction mix containing Tn5 transposase (Vazyme Biotech, S602). Reactions were incubated for 30 min at 37°C. The transposed DNA fragments were purified using the MinElute Kit (QIAGEN, 28004,) and the library was amplified using primers with unique barcodes (Vazyme Biotech), which were selected by the AMPure XP beads (Agencourt, 20508200) to establish the library. The library was sequenced on an Illumina HiSeq X Ten sequencer for an average of 20 million unique reads per sample to obtain 150 bp paired-end reads.

ATAC-seq data analysis was performed as described previously72. Reads were trimmed to remove adapter sequences using TrimGalore (v0.6.2) with options ‘-q 25 –paired’, and trimmed reads were aligned to mm10 reference genome using Bowtie2 (v2.3.5.1)73. Alignments were filtered using SAMtools (v1.9)74 to retain only uniquely mapping read pairs and remove duplicates using Sambamba (v0.7.0)75. Peak calling was performed using the MACS2 (v2.1.2)76 callpeak command with parameters ‘-q 0.01’. A matrix of non-nucleosomal Tn5 insertion counts was generated for the common set of peaks using BEDtools (v2.29.2)77. The count matrix was used to identify differentially accessible peaks with DESeq2 (v1.38.3)69. Differential peaks at FDR <0.05 were retained for analysis. The peaks were annotated to RefSeq (mm10) using ChIPseeker (v1.20.0)78. Mean-normalized Tn5 insertions at differential peaks were computed for pooled replicates in both WT and cKO mice and smoothed over a 100-bp window. Average signal values were plotted using deepTools (v3.3.0)79.

Real-time quantitative PCR (qPCR) analysis
qPCR analyses were performed both on hippocampal tissues and on NSCs. Total RNA extraction using Trizol reagent, reverse transcription, and SYBR green quantitative real-time PCR were performed according to the manufacturer’s instructions using gene-specific primers (listed in Supplementary Data 5).

Behavioral analysis
Morris water maze experiments were performed as previously described with minor modifications64. The animals were released from different positions in the water maze and performed four trials daily for 6 days. On the seventh day, the mice were given a 1 min probe trial in which the platform was removed. Mice were tracked by a video camera, the latency, velocity and distance traveled to the platform were collected and analyzed by software. The platform crossings were recorded. The water temperature was controlled at 22±1°C during the experiments.

Contextual fear conditioning was conducted for 2 days. On the training day, mice were exposed to the conditioning chamber for 7 min. Within the following 3 min, mice were trained with a 1 s, 0.5 mA foot-shocks for three times, separated by a 60 s interval. After the last shock, the mice stayed in the chamber for 1 min, then were put back in their cages. Contextual testing was executed 24 h after the training. The mice were placed into the same chamber and stayed there for 7 min with no foot-shock. The percentage of freezing time at each experiment was recorded, and contextual fear memory was measured by the software.

siRNA transfection
HEK293 cells were transfected with siRNAs targeting SLC40A1 and SLC22A17 (designed and purchased from Tsingke Biotechnology Co., Ltd, Beijing, China) using Lipofectamine 2000 (YEASEN, Cat# 40802ES03) according to the manufacturer’s instructions. To label transfected cells, an mCherry-expressing empty plasmid was co-transfected in the same liposome complex. Transfected cells were incubated for 48 h before further analysis.

Lentivirus construction
Lentivirus was produced as described. HEK293T cells were transfected with the lentiviral packaging plasmid PSPAX2, VSVG, and the target plasmid, using PEI (Polyscience). 48–72 h after transfection, collect viral supernatants and centrifuge at 1000×g to pellet cellular debris. Add 5X PEG8000 overnight, 2500×g, 4°C, 30 min to obtain high-titer virus. Pelleted virus was re-suspended in 200 μL phosphate-buffered saline (PBS). Infection of cells by adding the virus to the media supplemented with 8 μg/mL polybrene overnight. Cells were collected after 48 h.

Separation of cytoplasmic and nuclear fraction
Nuclear, cytoplasm, and cell membrane proteins were extracted using the total protein extraction kit for animal cultured cells and tissues (Invent, SC-003).

Statistics and reproducibility
All experiments in this paper were carried out with more than three biological replicates. All experiments were performed under the same conditions, and results were consistently reproducible across independent replicates. Representative data from one of these experiments are shown in the figures. GraphPad Prism 8.0 and ImageJ (v1.53t) were used as statistical analysis software. Comparisons between two groups were assessed using unpaired two-tailed Student’s t-test or one-way ANOVA with Scheffe’s multiple comparisons test, or one-way ANOVA with Tukey’s multiple comparisons test, or two-way ANOVA, or two-way ANOVA with Scheffe’s multiple comparisons test, or Chi-square test with Bonferroni correction, wherever applicable. All data were presented as mean ± SEM. Significance is indicated by an asterisk (*p<0.05, **p<0.01, ***p<0.001).

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this manuscript, Tao and colleagues show that the iron transporter SLC22A17 plays a physiological role in mediating postnatal hippocampal neurogenesis via the regulation of iron homeostasis. Overall, the manuscript is well written and comprehensive and uses a wide range of techniques and multiple transgenic animal models to reach this conclusion. Overall, this is a very interesting study. However, several key points should be addressed before this manuscript would be suitable for publication in Nature Communications.\n\nMajor questions:\n1. In Figure 1I the authors state that dendrite complexity and spine density were altered in the cKO mice using Golgi-Cox staining, but this data is not shown (only a representative image). Quantification should be performed to support this statement.\n2. Extended data Fig1K- For the Iba1 quantification only 3 mice were included and there is a large variation in the counts in the cKO hippocampus. More brains should be assessed to strengthen the conclusion that there is no change in Iba1+ cells in the cKO hippocampus.\n3. Sox2 alone is not an ideal marker of the NSCs as it is quite widely expressed as evidenced by the image in Ext data 2A.\n4. The authors state that the “number” of BrdU+/Ki67+ and BrdU+/Sox2+ cells are shown in Fig. 2B. However, in the figure this data is expressed as a % BrdU+/Ki67+cells / total BrdU cells. This data would be more informative if displayed as the number of BrdU/Ki67+ cells per DG rather than as a %.\n5. The manuscript states that “clonal neurosphere culture assays” were performed. I couldn’t find any reference to the density the cells were plated in this assay and the resulting neurospheres appear from the representative images to be very densely plated with a lot of spheres looking like they are merging which can alter the counts. Also, the neurosphere counts in Fig. 2D are from the secondary neurospheres – primary neurosphere counts would be much more informative. In addition, the neurosphere number in Fig. 2D should be displayed as Neurospheres per hippocampus or per XX number of cells.\n6. In Fig 2H it would be more meaningful to display the counts as “Number of NeuN+BrdU+ cells “(double positive cells) per DG rather than as a %.\n7. In Fig 2J – did the cKO neurospheres generate fewer neurons than the WT? It would be interesting to also include this data.\n8. In Ext data 3A – how were the NPCs isolated for the qPCR analyses? I couldn’t find this in the methods section.\n9. Fig. 3D It is unclear why the quantification of the Ki67, Sox2 and DCX are expressed as % marker cells/DG. These should be counts per DG (mm2) as in Fig 3C for the Tdtomato cells.\n10. Are the loss or dysfunction of mature CamKIIa mature neurons typically associated with spatial learning and memory deficits in the water maze? This section is brief and could be explored more fully.\n11. I am a bit unclear regarding the data showing a decrease in Calcein levels in the cKO spheres (Fig 4E). The text states that this “demonstrates elevated cellular iron levels in the cKO spheres”. I thought that this dye is a calcium detector that is typically used for live/dead cell analyses? Would this data indicate that there is less cell death in the cKO neurospheres?\n12. Fig. 4I Does Annexin V detect other forms of cell death apart from apoptosis?\n13. Why weren’t neurogenesis levels evaluated in the Slc22a7 OE mice? It would be very interesting to determine if Slc22a7 overexpression can enhance hippocampal neurogenesis levels in these mice.\n14. It would be interesting to show the matched neurogenesis data for the behaviour experiments shown in Fig 7A-C.\n15. In Fig 7 K-N the double knockout mice show similar learning and neurogenesis levels to the NRF2-/- mice. How can you be sure that the deficit observed in the DKO is not just due to Nrf2 KO?\n\nMinor points:\n1. I couldn’t find mention of Fig1A (including the data) in the manuscript text.\n2. Ext data 4F – states there is an increase in Tfrc expression in high iron diet but there are no significance stars on the graph.", "reviewer_2": "Tao L et al utilized an expansive and comprehensive set of multidisciplinary experiments to uncover the role of SLC22A17 as an important regulator of intracellular iron homeostasis and provide evidence supporting novel molecular roles of SLC22A17 in maintenance of NSC and intracellular redox machinery independent of its role as LCN2 receptor. These discoveries warrant the study’s impact in the field as it paves a new pathway for investigation into the maintenance of physiological iron homeostasis in the context of neurodevelopment and neuropathologies. As such, there are substantial concerns that prevent its acceptance for publication in the current form (see below). The authors are encouraged to address these concerns for further consideration.\n\n1. Was there any evidence of suckling failure that could contribute to the growth impairment of the NesCre cKO pups? Evidence of milk present in the pup gut would suffice.\n2. Line 165-169, Since 80% cKO pups died by P21, would the results shown in Fig.2g,h be biased in favor of less severe phenotypes (e.g., survivors beyond P21)? In another word, they could underestimate the real effect on neuronal differentiation.\n3. Was there any evidence for sex-specific effects of the cKO mice?\n4. In the behavioral assays (MWM, Contextual FC), how old were the adult mice used in these assays? Could the abnormal dendritic and synaptic structures also contribute to the impaired learning and memory in the adult iKO mice? Fig.1b showed significant decline of Slc22a17 transcript in NSC of P14 and beyond; it would be helpful to show number of SLC22A17+ NSC in adult WT control in order to accurately interpret the behavioral effect of the iKO mice.\n5. Line 213, please provide a reference.\n6. Does Nes-Cre express and thus delete SLC22A17 function in the liver and spleen? What could account for the accumulation of iron in these peripheral tissues shown in Supplemental Fig.4C?\n7. Line 243-246, Either remove this analysis from the report or provide more details of this study for duration of the feeding and data demonstrating the effect of these diets on hematocrit and liver TfRc. As such, the TfRc expression shown in the Supplemental Fig.4F was contradictory to its known downregulation in response to low iron diet (See work from Georgieff MK’s group).\n8. Fig.4G, the 8-OHdG labeling was not in cell nucleus, suggesting non-specific labeling. Consider using another marker (e.g., g-H2AX) to assess DNA damage.\n9. Fig.4L, please report the difference of apoptotic cells in cKO vs WT hippocampus, which would be important to support the in vivo effect of SLC22A17 LOF.\n10. (Minor) Fig.4N, please add arrows indicate abnormal features shown in the figure.\n11. Line 272 -277, the present data were unclear regarding the implication of ferroptosis for at least two reasons: (1) It is unclear whether actin expression was not altered in cKO (vs WT) neurospheres, which could compromise its use as a normalizer for WB (This may also apply to the expression of GAPDH given the mitochondrial effects), and (2) expression profiles for ferroptosis regulators (Supplemental Fig.4h,i) appear to differ between cKO and WT, invoking a possibility of upregulation for both positive and negative regulators in the cKO neurosphere.\n12. Fig.5B, please provide data for cultured cells grown in control media to serve as baseline. Given the evidence for reduced iron uptake (lower TfR) and elevated iron storage (higher ferritin) in cKO (vs WT) cultured neurons, whether the rate of iron efflux is compromised in the cKO neurons remains unclear without the baseline level.\n13. Fig.5C is confusing. If the signal intensity represents level of iron content, then why WT slice showed little evidence iron accumulation, whereas OE slice showed evidence of iron accumulation following FAC exposure given the hypothesis that SLC22A17 regulates cellular iron efflux? Please confirm that the background signals were similar in the image captured and analysis for both groups.\n14. (Minor) Add an arrow to the complex at the bottom left corner, which shows the co-localization of all three markers, and provide an enlarged image of this area.\n15. (Minor) Fig.6E, p62 WB image appears to be upside down. Please confirm and make correction as needed. Same comment for GAPDH in fig.6H.\n16. Data presented in Fig.6F and 6I seem to be contradictory as WB showed higher nuclear Nrf2 level in cKO vs WT, whereas IF showed no signal of Nrf2 in the nuclei of cKO cells.\n17. Please state and confirm the number of mouse/groups that were used for behavioral assays. Provide more details the duration of DFO and ZnPP treatments and whether the treatments altered systemic iron homeostasis as this could confound the central iron homeostasis.\n18. Fig.7i-l, these results seem to be contradictory to the previously reported role of Nrf2 in learning and memory (PMID: 29036636, PMID: 30194014, PMID: 19805328), raising doubt about the validity of these analyses. These findings need more in-depth discussion.", "reviewer_3": "The study by Tao et al. describes a new Slc22a17-dependent pathway to remove iron from cells through an endosomal recycling that can be used by mammals. This is an important finding because so far the only known regulated pathway of iron expelling from the cells is attributed to ferroportin (Fpn) (Drakesmith et al., 2015). It seems that this new mechanism is mostly restricted to the brain where the expression of Slc22a17 is much higher than in other organs (in many of them barely detectable) [Extended Data Fig. 1A]. The Authors show how deletion of the Slc22a17 gene leads to iron accumulation in hipopcampus, oxidative stress, severe impairment of hippocampal NSC development, and in consequence early postnatal mortality. The methodology is sound. The Authors use a wide range of cellular and molecular methods. Presentation of results is clear. Blots and stainings are of high quality.\n\nMy main objection to the Authors is that they propose a new mechanism of iron efflux from the cells mediated by Slc22a17 without seriously referring to the well-established ferroportin/ferroxidase-dependent pathway of iron export. It is largely known that disruption of this pathway underlies many neurological diseases associated with excessive iron accumulation. We do not really know how the Fpn/ferroxidase (most probably ceruloplasmin) pathway is regulated under conditions of decreased Scl22a17 protein level. Is it enhanced or quite the opposite – reduced ? According to my comments below it is tempting to propose that the amount of iron exported by Fpn from the cells lacking Slc22a17 should be increased. In this context it is interesting What is the quantitative potential to transport iron to extracellular environment by Slc22a17 system compared to Fpn pathway ?\n\nFigure 1A-B shows increase in iron level in the hippocampus of Slc22a17 cKO mice at P14 and respective changes in the the expression of key iron proteins responsible for the maintenance of intracellular iron balance. In Figure 1C an opposite effect (decreased iron in hippocampus of mice overexpressing the Slc22a17 gene) is shown. It seems that these changes are due to the post-transcriptional regulation mediated by IREB2 (Iron Regulatory Protein 2) that post-transcriptionally controls mRNAs (encoding proteins involved in cellular iron regulation ) containing IRE (Iron Responsive Element), regulatory sequence localized in 5’ or 3’ UTR. Under high iron level in hipocampus of cKO mice, IRP2 is probably down-regulated (degraded) and in consequence the expression of TfR1 (few IRE copies in 3’ UTR) is decreased and the expression of H- and L- ferritin subunits is increased (1 IRE copy in 5’ UTR). To complete the expression pattern of iron metabolism proteins, an evaluation of Fpn protein by Western blot should be added. Considering that Fpn mRNA contains IRE in 5’UTR, Fpn protein should be regulated similarly to ferritin subunits i.e., increased. Potential up-regulation of Fpn could be considered as a regulatory mechanism attenuating iron accumulation in the Slc22a17 cKO hippocampus, which is due to the inhibition of iron efflux in the absence of Slc22a17 protein.. By the way, there is also another IRP – IRP1, which regulates intracellular iron as a holo- [4Fe-4S] or apo-form These post-translational modification in the IRP1 molecyles are not only regulated by iron but also by oxidative stress reported by Authors . What could be the role if any of IRP1 in the regulation of iron netabolism in cKO hippocampus ? In my opinion all these this aspects need a deeper discution in the manuscript\n\nThe Authors clearly show [Figure 6F-E] that Slc22a17 regulates the p62/Nrf2/HO-1 signaling axis and that HO-1 inhibition and Nrf2 KO significantly rescued neurogenesis in Slc22a17 cKO mice. This strongly suggest that the amount of iron released intracellularly (from heme molecules) exceeds the transport capacity to the extracellular space. Importantly, the Slc40a1 gene is also transcriptionally regulated by Nrf2 through the MARE/ARE sequence motif present in the Slc40a1 promoter (Marro et al., 2010). It is puzzling why among genes targeted and activated by Nrf2 through their promoters upon Slc22a17 deletion is there no the Slc40a1 gene [Figure 6B-C] ? This question is all the more relevant because in cells overexpressing Slc22a17 (supposed to decrease intracellular iron) expression of the Slca40a1 and showing decreased iron content, this gene is significantly (*) decreased. Here, again evaluation of Fpn protein would be useful because IRP/IRE system does not influence Fpn mRNA level but only the efficiency if its translation.\n\nIn conclusion, I strongly recommend analysis of ferroportin protein expression in Slc22a17 cKO hipocampus and adding to the discussion some conclusion resulting from this assay.", "reviewer_4": "Dear authors,\nThank you for the chance to review this paper. This is a very well-written, well-executed study that demonstrates that the transport protein Slc22a17 regulates iron homeostasis in hippocampus, which is essential for postnatal neurogenesis. The data support a model in which Slc22a17 localizes to the ER, regulates iron export through the endosomal recycling pathway, and interacts with p62, a modulator of the Nrf2/HO-1 pathway. The study employs in vitro and in vivo models and multiple technical approaches. Overall, the interpretations and conclusions are sound, but we do have several comments that we would like to see addressed by the authors.\n\n-On line 108, the authors state that “these observations highlight the critical role of Slc22a17 in early neurogenesis and its importance in maintaining iron homeostasis within NSCs.” At this early point in the manuscript, this is an over-statement. The results thus far had only shown associations, not a causal link.\n-Please express brain weight as % body weight in Extended Data Fig. 1F. When this is done, the authors may discover that the brain weight is not actually small but rather just proportionate to body weight.\n-On page 12, line 209, the authors state “additionally, iKO mice showed a slightly reduced freezing behavior when exposed to the shock context (Extended Data Fig. 3C).” Is there a p-value here? None is depicted in the figure.\n-Non-heme iron levels should be measured in addition to total iron levels. Non-heme iron levels are a standard measurement in studies of iron biology, particularly when there may be changes in red blood cell parameters that could impact tissue heme iron levels.\n-For the experiments related to Extended Data Fig. 4F, iron and ferritin levels should also be measured when mice are placed on high-iron diets, as the fact that Tfrc levels don’t change significantly suggest that iron levels don’t change.\n-Figure panels would be easier to interpret if the tissue type was included in the graphs (i.e. primary cell lines vs. tissue).\n-On line 271, the authors state “this treatment further aggravated mitochondrial damage in cKO neurospheres (Fig. 4 M).” Is there quantification for these data?\n-The authors used overexpression in cell lines to examine Slc22a17 localization. This is less than ideal as it could introduce artifacts. Given that an antibody to Slc22a17 is available and used by the authors in this paper, why was this approach used?\n-Why was sex not evaluated in this study?\n-This study would benefit greatly from a model figure in which the authors depict the proposed mechanism of action of Slc22a17 in hippocampal iron homeostasis at the cellular and organelle level.\n-The authors found altered liver and spleen iron levels in their mutant mice (Extended Data Fig. 4C, D). Were hepcidin levels changed in these mice? Did other organs have altered iron levels?\nWere there any changes in red blood cell parameters (e.g. hematocrit, hemoglobin, RBC count)? Also, why do the authors think that liver and spleen iron levels change when Slc22a17 impacts hippocampal iron homeostasis? Could Slc22a17 expression in other cell types play a critical role? It is difficult to imagine a scenario where Slc22a17-dependent iron regulation in discrete regions in the brain impact iron levels in other organs...", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Point-by-Point Responses\nThank the reviewers very much for their great efforts and very constructive comments on our\nmanuscript. We have carefully revised the manuscript according to the reviewers’ comments (with\ntext changes highlighted in Bold). Our point-by-point responses are summarized below. Each\noriginal comment is presented, followed by our “Response”.\nReviewer #1 (Remarks to the Author):\nIn this manuscript, Tao and colleagues show that the iron transporter SLC22A17 plays a\nphysiological role in mediating postnatal hippocampal neurogenesis via the regulation of iron\nhomeostasis. Overall, the manuscript is well written and comprehensive and uses a wide range of\ntechniques and multiple transgenic animal models to reach this conclusion.\nOverall, this is a very interesting study. However, several key points should be addressed before this\nmanuscript would be suitable for publication in Nature Communications.\nResponse #1:\nWe greatly thank the reviewer for these positive comments on our work and for giving us important\nsuggestions to improve our manuscript.\nMajor questions:\n1. In Figure 1I the authors state that dendrite complexity and spine density were altered in the cKO\nmice using Golgi-Cox staining, but this data is not shown (only a representative image).\nQuantification should be performed to support this statement.\nResponse #1-1:\nThank you for pointing this out. We have now included quantitative analysis of dendritic complexity\nand spine density based on Golgi-Cox staining (see the new data in Extended Data Fig. 1 I). The\nquantification results are consistent with those obtained from Thy1-GFP reporter mice, further\nsupporting our conclusion.\nThe quantified data are now presented below:\nExtended Data Fig. 1 I Statistical analysis of Golgi staining showing reduced primary basal dendrite numbers and\ndendritic spine numbers in cKO hippocampus at P14 (n = 24 cells from 3 mice/group). Data are presented as mean\n± SEM. Student’s t-test was used. *p<0.05, ***p<0.001.\n2. Extended data Fig1K- For the Iba1 quantification only 3 mice were included and there is a large\nvariation in the counts in the cKO hippocampus. More brains should be assessed to strengthen the\nconclusion that there is no change in Iba1+ cells in the cKO hippocampus.\nResponse #1-2:\nWe appreciate the reviewer’s concern regarding the sample size for Iba1 quantification. In response,\nwe have performed additional Iba1 immunostaining on hippocampal sections from three more cKO\nand control mice, increasing the robustness of our analysis. The expanded dataset confirmed that\nthere is no significant difference in Iba1⁺ cell numbers in the cKO hippocampus, supporting our\noriginal conclusion.\nThe updated Extended data Fig. 1L (previously Extended data Fig. 1K) has been shown below:\nExtended Data Fig. 1 L Quantifications of microglial marker Iba1 in the hippocampus at P14 showing similar\nIba1+ cells amount (n = 6 mice/group). Data are presented as mean ± SEM. Student’s t-test was used.\n3. Sox2 alone is not an ideal marker of the NSCs as it is quite widely expressed as evidenced by the\nimage in Ext data 2A.\nResponse #1-3:\nThank the reviewer for the thoughtful comment. We agree that Sox2 alone is not an ideal marker due\nto its broader expression pattern. To address this concern, we have additionally performed Pax6\nimmunostaining, a well-established marker for neural stem cells 1. The results showed a consistent\nreduction of Pax6⁺ cells in the cKO hippocampus (see the new Extended Data Fig. 2A and B), in line\nwith our Sox2-based observations. These findings further support the conclusion that neural stem\ncell numbers are decreased in the cKO hippocampus.\nThe Pax6 staining results and corresponding quantification are shown below:\nA B\nSox2 DAPI\nTW\nOKc\nKi67 DAPI Pax6 DAPI\n400 **\n300\n200\n***\n100\n)2mm(\nGD\n/\nsllec\n+rekraM\nWT\ncKO\n***\nPax6+\nExtended data Fig. 2 A Representative images of the DG of cKO and WT mice stained with anti-Ki67, anti-Pax6\nand anti-Sox2 antibodies. Scale bar, 50 μm.\nExtended data Fig. 2 B Decreased number of the Ki67+, Pax6+ and Sox2+ cells in the DG of cKO mice (n > 3\nmice/group). Data are presented as mean ± SEM. Student’s t-test was used. **p<0.01, ***p<0.001.\n4. The authors state that the “number” of BrdU+/Ki67+ and BrdU+/Sox2+ cells are shown in Fig. 2B.\nHowever, in the figure this data is expressed as a % BrdU+/Ki67+cells / total BrdU cells. This data\nwould be more informative if displayed as the number of BrdU/Ki67+ cells per DG rather than as\na %.\nResponse #1-4:\nThank you for your valuable suggestion. We used BrdU labeling to assess the proportion of cells that\ncontinued to proliferate within 24 hours post-labeling, and this data is shown as the percentage of\nBrdU+/Ki67+ cells relative to total BrdU+ cells in Fig. 2B. However, we agree with your point that\npresenting the number of BrdU+/Ki67+ and BrdU+/Sox2+cells would provide additional useful\ninformation. As a result, we have included the cell counts of BrdU+/Ki67+ and BrdU+/Sox2+\ndouble-positive cells in the Extended Data Fig. 2C, as shown in the updated figure below.\nExtended Data Fig. 2 C Decreased number of the BrdU+/Ki67+ and BrdU+/Sox2+ cells in the DG of cKO mice\n(n > 5 mice/group). Data are presented as mean ± SEM. Student’s t-test was used. ***p<0.001.\n5. The manuscript states that “clonal neurosphere culture assays” were performed. I couldn’t find\nany reference to the density the cells were plated in this assay and the resulting neurospheres appear\nfrom the representative images to be very densely plated with a lot of spheres looking like they are\nmerging which can alter the counts. Also, the neurosphere counts in Fig. 2D are from the secondary\nneurospheres – primary neurosphere counts would be much more informative. In addition, the\nneurosphere number in Fig. 2D should be displayed as Neurospheres per hippocampus or per XX\nnumber of cells.\nResponse #1-5:\nThank the reviewer for the insightful suggestions. We apologize for not providing sufficient details\nregarding the clonal neurosphere assay protocol in the manuscript. As correctly pointed out, the lack\nof cell plating density and clarity on neurosphere quantification may have led to confusion. In our\nexperiments, neurospheres were generated from the hippocampus of individual mice. After\ndissection, hippocampal tissue was enzymatically dissociated to obtain approximately 5 × 10⁶ cells\nper mouse, which were plated into 6-well plates and cultured for 14 days under neurosphere-\nforming conditions.\nIn response to the reviewer’s valuable suggestion, we have now repeated the neurosphere culture\nexperiments, and quantified both primary and secondary neurosphere numbers. To improve data\nclarity and comparability, we have normalized neurosphere counts to “Neurospheres Counts per\n1000 plated cells”.\nWe have updated Fig. 2 D and E, the corresponding legend, and the “Methods” section (Lines\n629-630) to reflect these changes and provide a clearer description of the neurosphere assay protocol\nand quantification strategy. The revised figure and legend are shown below:\nFig. 2 D Quantifications of primary and secondary neurospheres formed per 1000 plated cells derived from WT\nand cKO hippocampus (n = 8 mice/group). Data are presented as mean ± SEM. Student’s t-test was used.\n***p<0.001\nFig. 2 E Quantifications of the diameter of cultured primary and secondary neurospheres. Data are presented as\nmean ± SEM. Student’s t-test was used. ***p<0.001.\n6. In Fig 2H it would be more meaningful to display the counts as “Number of NeuN+BrdU+ cells\n“(double positive cells) per DG rather than as a %.\nResponse #1-6:\nThank you for your helpful comment. In Fig. 2I (previously Fig. 2H), we quantified the proportion of\nBrdU+/NeuN+ double-positive cells 7 days after BrdU labeling, which was employed to assess the\nchanges in the differentiation potential of neural stem cells. However, we acknowledge that\npresenting the counts of BrdU+/NeuN+ double-positive cells per DG would provide more meaningful\ndata. In response to your recommendation, we have now included the cell counts for BrdU+/NeuN+\ndouble-positive cells in Extended Data Fig. 2F, which we believe will further substantiate our\nconclusions.\nThe updated Extended Data Fig. 2F has been shown below:\nExtended Data Fig. 2 F Decreased number of the BrdU+/NeuN+ cells in the DG of cKO mice (n = 9 mice/group).\nQuantifications of the diameter of cultured primary and secondary neurospheres. Data are presented as mean ±\nSEM. Student’s t-test was used. ***p<0.001.\n7. In Fig. 2J – did the cKO neurospheres generate fewer neurons than the WT? It would be\ninteresting to also include this data.\nResponse #1-7:\nWe thank the reviewer for the insightful suggestion. In response, we have quantified the proportion\nof neurons generated from WT and cKO neurospheres following fibronectin-induced neurosphere\ndifferentiation assay. This data has now been included in Fig. 2J, showing that the neuronal\ndifferentiation capacity of cKO neurospheres is significantly reduced compared to WT. The main\ntext and figure legend have been revised accordingly (Results section, Line 175-181).\nJ K\nWT DIV14\ncKO\n400 *** ***\n** **\n200\n100\nFig. 2 J Quantification of neuronal differentiation from WT and cKO neurosphere after 7 days of induction. The\npercentage of MAP2⁺ neurons relative to total DAPI⁺ cells was calculated. Data are presented as mean ± SEM.\nStudent’s t-test was used. ***p<0.001\nFig. 2 K Left: Representative images for Tuj1 and MAP2 staining in neurons differentiated from neurospheres after\n7 and 14 days of culture. Scale bar, 100 μm. Right: Quantification of neurite length for neurons differentiated from\nWT and cKO neurosphere. Data are presented as mean ± SEM. Student’s t-test was used. **p<0.01, ***p<0.001.\n8. In Ext data 3A – how were the NPCs isolated for the qPCR analyses? I couldn’t find this in the\nmethods section.\nResponse #1-8:\nWe sincerely apologize for not providing sufficient detail regarding the isolation of neural progenitor\ncells (NPCs). The NPCs used for iron content assessment and qPCR analyses in Fig. 1B and\nExtended Data Fig. 3A were isolated by fluorescence-activated cell sorting (FACS) based on the\nmethod described by Liu et al. 2. We have now added a detailed description of this procedure in the\nMethods section (Lines 610-619) of the revised manuscript as follow:\n“Fluorescence-activated cell sorting (FACS) of neural progenitor cells\nNeural progenitor cells (NPCs) were isolated using fluorescence-activated cell sorting (FACS)\nbased on established protocols described by Liu et al 2. Briefly, NPCs were obtained from\nmouse brain tissues at multiple developmental stages, including embryonic day 14 (E14),\nembryonic day 18 (E18), postnatal day 0 (P0), P7, P14, and P21. Tissues were enzymatically\ndissociated to single-cell suspensions, stained with fluorophore-conjugated antibodies, and\nfo\nhtgnel\netirueN\n)mμ(\nnoruen\nyramirp\nTuj1 MAP2\nTW\nOKc\nDay 7 Day 14\nTuj1 MAP2\n80\n60\n40\n20\nnoruen\n+2PAM\n%\n***\nsCSN\ndetnalp\nlatot\n/\nsorted for CD24-Thy1-/lo cells using a FACSAria III (BD Biosciences). The following\nantibodies were used: anti-CD90.2 (Thy-1)-APC (1:400, BD Biosciences, 561641) and\nanti-CD24-PE (1:400, BD Biosciences, 553262). Dead cells were excluded using Fixable\nViability Dye EF506 (Thermo Scientific).”\n9. Fig. 3D It is unclear why the quantification of the Ki67, Sox2 and DCX are expressed as %\nmarker cells/DG. These should be counts per DG (mm2) as in Fig 3C for the Tdtomato cells.\nResponse #1-9:\nThank you for pointing out this issue. We sincerely apologize for the labeling error in Fig. 3D and E.\nAs you mentioned, the quantifications of Ki67⁺, Sox2⁺, and DCX⁺ cells were performed as the\nnumber of marker-positive cells per DG area (mm²), consistent with the analysis used in Fig. 3C for\nTdTomato⁺ cells. We have corrected the labeling in Fig. 3E to accurately reflect this, and the revised\nfigure is provided below:\nFig. 3 E Quantification of the numbers of Ki67+, Sox2+, and Dcx+ cells in the DG of WT and iKO mice (n = 5\nmice/group). Data are presented as mean ± SEM. Student’s t-test was used. **p<0.01.\n10. Are the loss or dysfunction of mature CamKIIa mature neurons typically associated with spatial\nlearning and memory deficits in the water maze? This section is brief and could be explored more\nfully.\nResponse #1-10:\nWe sincerely thank the reviewer for raising this important question.\nIn our study, we primarily focused on the physiological role of Slc22a17 in neurogenesis. To this end,\nwe utilized the Nestin-CreERT2 model and conducted behavioral tests, including the Morris water\nmaze, four weeks after TAM induction. We found that deletion of Slc22a17 significantly impaired\nadult neurogenesis, resulting in abnormal neuronal morphology (as shown in Response Fig. 1A\nbelow), accompanied by marked deficits in learning and memory. These results suggest that\nSlc22a17 plays a critical role in the differentiation and maturation of neurons derived from neural\nstem cells.\nMoreover, we considered that Slc22a17 is also expressed in mature neurons (as shown in Response\nFig. 1B below), and that dysfunction of mature neurons is frequently associated with\nhippocampus-dependent spatial learning and memory deficits 3. To explore the potential role of\nSlc22a17 in mature neurons, we generated conditional knockout models driven by CaMKIIa-Cre and\nVGAT-Cre. In the CaMKIIa-Cre model, we observed impaired spatial learning and memory in the\nMorris water maze test (see Extended Data Fig. 3D-F). However, in contrast to the Nestin-CreERT2\nmodel, no significant changes in neuronal morphology were detected in this model (as shown in\nResponse Fig. 1C below).\nThese findings suggest that Slc22a17 may indeed participate in intracellular signaling or synaptic\nfunctions within mature excitatory neurons. Nevertheless, the learning and memory impairments\nobserved in the Nestin-CreERT2 model may be more attributable to the physiological role of\nSlc22a17 in adult neurogenesis, rather than in mature neurons per se. The precise mechanisms of\nSlc22a17 function in mature excitatory neurons remain to be elucidated, and we are currently\nconducting further studies to address this question, which will be reported in future work.\nThis point has been addressed in the Discussion section (Lines 463-466) as follow:\n“Among the several cell-type specific knockout mouse models we generated, only the\nNestin-Cre-induced Slc22a17 cKO mice exhibited severe weight loss, early postnatal death,\ndisrupted neurogenesis, and excessive NSC apoptosis, indicating a close association between\nSlc22a17 and the development of neural stem and progenitor cells. Additionally, the expression\npattern of known iron-transporting genes suggests that Slc22a17 is likely the principal regulator of\niron homeostasis in hippocampal NSCs. Notably, although CaMKIIa-Cre-driven cKO mice also\nexhibited spatial learning and memory impairments, they showed no neuronal morphological\nabnormalities, suggesting distinct functions of Slc22a17 in adult neurogenesis and mature\nneurons, the latter of which we are currently investigating.”\n200\n150\n100\n50\n0\n0 2 4 6 8\nDistance (μm)\nResponse Fig. 1 CaMKIIa-Cre-driven cKO mice showed no neuronal morphological abnormalities.\nytisnetnI\nSlc22a17MAP2DAPI Slc22a17 MAP2\nSlc22a17\nMAP2\nf/f\nerC-αIIKMaC;f/f\nThy1-GFP\nTW\nOKi\nNeuNtdTomatoDAPI\n10\n8\n6\n4\n2\n0\nf/f Cre\nKIIα-\nM\nCa\nf/f;\nrebmun\netirdned\nlasab\nyramirP\n20\n15\n10\n5\n0\nf/f Cre\nKIIα-\nM\nCa\nf/f;\nmµ\n02\n/ ytisned\nenipS\n10\n8\n6\n4\n2\nrebmun\netirdned\nlasab\nyramirP\n** 20\n15\n10\n5\nmµ\n02\n/\nytisned\nenipS\nA\n***\nB C\n(A) Representative photos and statistical analysis showing dendrite numbers and dendritic spine numbers in the\ntdTomato+ neurons of WT and iKO mice (n = 16 cells from 3 mice/group). Left: Scale bar, 50 μm; Right: Scale bar,\n5 μm.\n(B) Top: Representative images of immunofluorescence staining of Slc22a17 and MAP2 in the cortex. Scale bar,\n10 μm; Bottom: Representative confocal images and line intensity plots.\n(C) Representative photos and statistical analysis showing dendrite numbers and dendritic spine numbers in the\nThy1-GFP+ neurons of f/f and f/f; CaMKIIa-Cre mice (n = 11 cells from 3 mice/group). Left: Scale bar, 50 μm;\nRight: Scale bar, 5 μm.\nData are presented as mean ± SEM. Student’s t-test was used. **p<0.01, ***p<0.001.\n11. I am a bit unclear regarding the data showing a decrease in Calcein levels in the cKO spheres\n(Fig 4E). The text states that this “demonstrates elevated cellular iron levels in the cKO spheres”. I\nthought that this dye is a calcium detector that is typically used for live/dead cell analyses? Would\nthis data indicate that there is less cell death in the cKO neurospheres?\nResponse #1-11:\nWe thank the reviewer for pointing this out and would like to clarify a potential misunderstanding\nregarding the use of Calcein in our experiments.\nIn our study, Calcein was used as an iron probe, not as a cell viability indicator. After Calcein-AM\nenters the cells, it is hydrolyzed by intracellular esterases to generate Calcein, which exhibits strong\ngreen fluorescence. Calcein is a well-established metal-chelating indicator, and under physiological\npH, its fluorescence is quenched upon binding to Fe³⁺. Therefore, a decrease in Calcein fluorescence\nindicates an increase in intracellular iron levels. This application of Calcein as an iron sensor has\nbeen widely used in previous studies 4.\nIn Fig. 4F (previously Fig. 4E), we employed two independent iron probes—FerroOrange and\nCalcein. The results from both probes were consistent and mutually supportive: in Slc22a17\nknockout neurospheres, FerroOrange fluorescence intensity was significantly increased, while\nCalcein fluorescence was markedly decreased, indicating iron accumulation in the cKO\nneurospheres.\n12. Fig. 4I Does Annexin V detect other forms of cell death apart from apoptosis?\nResponse #1-12:\nThanks for the reviewer’s insightful comment. As the reviewer rightly points out, Annexin V is a\nreporter of phosphatidylserine (PS) externalization, but not a specific marker for apoptosis, as PS\nexposure can also occur during pyroptosis and ferroptosis 5,6.\nIn our experiments, we used Annexin V/PI co-staining to evaluate apoptotic cell populations, where\nAnnexin V⁺/PI⁻ cells were classified as early apoptotic, and Annexin V⁺/PI⁺ cells as late apoptotic, to\nassess whether Slc22a17 knockout induced apoptosis. To further validate our findings, we\nadditionally examined cleaved caspase-3 and PARP cleavage, which confirmed the presence of\napoptosis in the cKO hippocampus. We also assessed GPX4 and other ferroptosis-related markers to\nrule out the contribution of ferroptosis in this context.\n13. Why weren’t neurogenesis levels evaluated in the Slc22a7 OE mice? It would be very interesting\nto determine if Slc22a7 overexpression can enhance hippocampal neurogenesis levels in these mice.\nResponse #1-13:\nWe appreciate the reviewer’s insightful suggestion. Indeed, we also hypothesized that\noverexpressing Slc22a17 might enhance hippocampal neurogenesis, which would be of great interest.\nTo test this, we generated a conditional Slc22a17 overexpression mouse model (OE), and examined\nhippocampal morphology, the number of neural stem cells (NSCs) and immature neurons during\nearly postnatal development (as shown in Response Fig. 2A below). However, no significant\ndifferences were observed between OE and wild-type mice.\nWe believe this may be due to the fact that Slc22a17 primarily regulates iron homeostasis in NSCs.\nUpon knockout, the loss of the major iron efflux pathway leads to intracellular iron accumulation\nand consequent apoptosis. However, under Slc22a17 overexpression condition, we found that the\nintracellular iron levels in NSCs remained comparable to wild-type. Furthermore, when both OE and\nwild-type brain slices were challenged with exogenous iron, the overexpression model maintained\nnormal iron levels, avoiding iron overload (as shown in Response Fig. 2B below). Therefore, the\neffect of Slc22a17 overexpression may lie more in enhancing the buffering capacity of NSCs under\nhigh iron conditions, rather than in directly promoting neurogenesis.\nResponse Fig. 2 No significant differences in neurogenesis were observed in Slc22a17-OE mice.\n(A) Left: Representative photos showing immunostaining of Nestin, Neurod1 and Dcx in the DG of WT and cKO\nmice at P14. Scale bar, 50 μm. Right: Quantifications of Nestin+, Neurod1+ and Dcx+ in the DG of WT and cKO\nmice (n = 4 mice/group).\n(B) Representative images showing iron contents labeled by iron probe Calcein in the organotypic brain slice with\nor without FAC treatment. Scale bar, 50 μm.\nData are presented as mean ± SEM. Student’s t-test was used.\nTW\nEO\nNestin Neurod1 Dcx\n1500\n1000\n500\n)2mm(\nGD\n/\nsllec\n+rekraM\nWT\nOE\nControl FAC\nCalcein\nTW\nEO\nA\nB\n14. It would be interesting to show the matched neurogenesis data for the behaviour experiments\nshown in Fig 7A-C.\nResponse #1-14:\nThank you for this insightful suggestion. We have now included immunofluorescence analyses of\nneurogenesis-related markers corresponding to the behavioral experiments shown in Fig. 7A–C.\nThese data have been added as Extended Data Fig. 7A and B, illustrating the effects of high-iron diet,\nlow-iron diet, and DFO treatment on neurogenesis in the dentate gyrus (as shown in Figure below).\nT O O-\nD F O\nO-\nHigh\niron\nO-Lo w\niron\nW K K K K\ni i i i\nKi67DAPI\n400\nExtended Data Fig. 7 A Immunostaining for DG with Ki67, Nestin, NeuroD1, Dcx and DAPI in WT, iKO,\niKO-DFO, iKO-High iron and iKO-Low iron mice. Scale bar, 50 μm.\nExtended Data Fig. 7 B Quantification of the numbers of WT, iKO, iKO-DFO, iKO-High iron and iKO-Low iron\nmice (n = 4 mice/group). Data are presented as mean ± SEM. One-way ANOVA, Tukey’s multiple comparisons\ntest was used. *p<0.05.\n15. In Fig 7 K-N the double knockout mice show similar learning and neurogenesis levels to the\nNRF2-/- mice. How can you be sure that the deficit observed in the DKO is not just due to Nrf2 KO?\nResponse #1-15:\nThank you for your thoughtful question. Consistent with previously reported 7, Nrf2 knockout alone\nin adult mice did not significantly affect neurogenesis or learning and memory abilities in our\nbehavioral and neurogenesis analyses, with statistical performance comparable to WT controls. In\ncontrast, Slc22a17/Nrf2 double knockout (DKO) mice showed a marked rescue of the neurogenesis\nand behavioral deficits observed in Slc22a17 conditional knockout (iKO) mice, restoring both\nparameters to WT-like levels. These findings suggest that the improvements seen in the DKO mice\nare not attributable to the loss of Nrf2 alone, but rather indicate that Nrf2 ablation functionally\ncompensates for the detrimental effects caused by Slc22a17 deficiency.\nMinor points:\n1. I couldn’t find mention of Fig1A (including the data) in the manuscript text.\n)2mm(\nGD\n/\nsllec\n+1dorueN\n*\n*\n* 2000\n1500\n1000\n500\n0\n)2mm(\nGD\n/\nsllec\n+xcD\nA B\n*\n150 *\n100\n50\n)2mm(\nGD /\nsllec\n+76iK\n1500\n1000\n500\n0\n)2mm(\nGD\n/\nsllec\n+nitseN\n***\n*\n*\nW i K i K T O O i K - - H O i D K ig F O h O - L ir o o w n iron\nResponse #1-16:\nThank you for pointing this out. We apologize for not clearly describing the origin of the data shown\nin Fig. 1A. These data were derived from our own transcriptomic analysis, which was performed to\ninvestigate the regulatory mechanisms of iron metabolism in the hippocampus. We have now\nprovided a detailed explanation of the dataset in the main text (Results section, Line 96-98), and the\nraw FPKM expression values from this RNA-seq analysis are included in Supplementary Table 1:\n“Slc22a17 is one of the most highly expressed iron transporters in the hippocampus, second\nonly to ferritin, as revealed by our transcriptomic analysis of hippocampal tissues (Fig. 1 A;\nSupplementary Table 1).”\n2. Ext data 4F – states there is an increase in Tfrc expression in high iron diet but there are no\nsignificance stars on the graph.\nResponse #1-17:\nWe thank the reviewer for the careful observation and helpful comment. In this experiment, adult\nmice were continuously fed a high-iron (912 ppm) or low-iron (12 ppm) diet for four weeks. We\nobserved that Tfrc mRNA levels showed a mild upward trend under high-iron diet conditions, but\nthis increase did not reach statistical significance. Under low-iron diet, no significant change in Tfrc\nexpression was detected. These findings suggest that iron metabolism in adult mice remains\nrelatively stable, and dietary iron supplementation or depletion may exert only limited effects on the\nmRNA expression of iron-related proteins in the brain. To maintain the rigor and clarity of the\nmanuscript, we have therefore decided to remove this result from the revised version.\nWe sincerely thank the reviewer for the valuable suggestion, which has helped us further improve\nthe quality of the manuscript.\nReviewer #2 (Remarks to the Author):\nTao L et al utilized an expansive and comprehensive set of multidisciplinary experiments to uncover\nthe role of SLC22A17 as an important regulator of intracellular iron homeostasis and provide\nevidence supporting novel molecular roles of SLC22A17 in maintenance of NSC and intracellular\nredox machinery independent of its role as LCN2 receptor. These discoveries warrant the study’s\nimpact in the field as it paves a new pathway for investigation into the maintenance of physiological\niron homeostasis in the context of neurodevelopment and neuropathologies. As such, there are\nsubstantial concerns that prevent its acceptance for publication in the current form (see below). The\nauthors are encouraged to address these concerns for further consideration.\nResponse #2:\nWe sincerely thank the reviewers for their constructive feedback and recognition of the\ncomprehensive approach in our study. We appreciate their acknowledgment of the novel insights on\nSLC22A17’s role in intracellular iron homeostasis and its impact on NSC maintenance and redox\nregulation. We are committed to addressing the concerns raised and improving the manuscript for\nfurther consideration.\n1. Was there any evidence of suckling failure that could contribute to the growth impairment of the\nNesCre cKO pups? Evidence of milk present in the pup gut would suffice.\nResponse #2-1:\nThank you for this insightful question. We also considered the possibility that postnatal lethality in\ncKO pups might be due to suckling failure. However, we observed visible milk in the stomachs of\ncKO pups (as shown in Response Fig. 3 below), indicating that they were successfully nursing.\nFurthermore, we conducted separate rearing experiments in which cKO pups were raised without\nwild-type littermates to eliminate competition for maternal milk. Despite the absence of suckling\ncompetition, cKO pups still exhibited early postnatal lethality. Therefore, we believe that the growth\nimpairment and postnatal death in cKO mice are not due to suckling failure.\nResponse Fig. 3 Representative image of postnatal WT and cKO pups showing visible milk in the stomach (arrow),\nindicating successful suckling.\n2. Line 165-169, Since 80% cKO pups died by P21, would the results shown in Fig.2g,h be biased in\nfavor of less severe phenotypes (e.g., survivors beyond P21)? In another word, they could\nunderestimate the real effect on neuronal differentiation.\nResponse #2-2:\nWe fully agree with the reviewer’s insightful comment. It is indeed possible that the data presented\nin Fig. 2 may underestimate the severity of the neurogenesis phenotype due to the early lethality of\nthe majority (~80%) of cKO pups before P21. To address this concern, we also examined\nneurogenesis-related phenotypes in the small subset of cKO mice that survived beyond P21 (as\nshown in Response Fig. 4 below). Interestingly, the degree of impairment in these survivors was\ncomparable to that observed in P14 cKO mice. This leads us to speculate that more severe\nneurogenesis defects may result in early postnatal death and therefore cannot be captured by\nconventional neurobiological analyses at later time points.\nResponse Fig. 4 Impaired neural development in cKO mice at P28.\n(A) Representative photos showing immunostaining of Nestin, Neurod1 and Dcx in the dentate gyrus (DG) of WT\nand cKO mice at P28. Scale bar, 50 μm.\n(B) Quantifications of Nestin+, Neurod1+ and Dcx+ cells in the DG of cKO mice compared with WT mice at P28 (n\n= 3 mice/group).\nData are presented as mean ± SEM. Student’s t-test was used. *p<0.05, **p<0.01, ***p<0.001.\n3. Was there any evidence for sex-specific effects of the cKO mice?\nResponse #2-3:\nThank you for raising this important point. We have considered the possibility of sex-specific effects\nin the cKO mice. Survival rates and neurogenesis-related phenotypes were examined separately in\nmale and female mice, and we did not observe any significant differences between sexes (see\nResponse Fig. 5 below). Therefore, data from both sexes were included in the analysis unless\notherwise specified.\nTW\nOKc\nNestin Neurod1 Dcx\n5000\n4000\n3000\n2000\n1000\n2mm\n/\nsllec\n+rekraM\nWT\ncKO\n***\n*\n**\nP28\nA B\nWT\ncKO_M Neurod1\n75 cKO_F\n50\n25\n0\n0 7 14 21\nResponse Fig. 5 No significant differences in neurogenesis were observed between male and female mice.\n(A) Survival curves of the WT, male cKO and female cKO mice. Most cKO mice died by P21 (n > 30 mice/group).\n(B) Representative photos showing immunostaining of Neurod1 in the DG of WT, male cKO and female cKO mice\nat P14. Scale bar, 50 μm.\n4. In the behavioral assays (MWM, Contextual FC), how old were the adult mice used in these\nassays? Could the abnormal dendritic and synaptic structures also contribute to the impaired learning\nand memory in the adult iKO mice? Fig.1b showed significant decline of Slc22a17 transcript in NSC\nof P14 and beyond; it would be helpful to show number of SLC22A17+ NSC in adult WT control in\norder to accurately interpret the behavioral effect of the iKO mice.\nResponse #2-4:\nWe sincerely thank the reviewer for the thoughtful and insightful comments. We have addressed\nthese concerns point-by-point as follows:\nRegarding point (1):\nWe appreciate the reviewer’s attention to detail. All behavioral experiments, including Morris Water\nMaze and Contextual Fear Conditioning, were performed on 8-week-old adult mice. We have now\nadded this information to the relevant section in the main text for clarification.\nRegarding point (2):\nWe agree with the reviewer that the neuronal morphological abnormalities could significantly affect\ncognitive performance. In adult iKO mice, we indeed observed prominent morphological defects in\nneurons, including a reduced number of primary dendrites and decreased spine density. These\nabnormalities are likely a consequence of impaired adult neurogenesis due to Slc22a17 deletion.\nImportantly, conditional deletion of Slc22a17 in mature excitatory neurons did not result in such\nmorphological changes (see the Response Fig. 6A below), reinforcing our interpretation that the\nlearning and memory deficits observed in the Nestin-CreERT2 model may be more attributable to the\nphysiological role of Slc22a17 in adult neurogenesis, rather than in mature neurons per se.\nRegarding point (3):\nAlthough Slc22a17 expression peaks during the early postnatal period, our data show that a\nsubstantial number of NSCs continue to express Slc22a17 in adulthood. By analyzing the publicly\navailable single-cell RNA-seq dataset (GSE104323), we identified NSC clusters and quantified\nSlc22a17-expressing cells, showing that approximately 25% of adult NSCs express Slc22a17.\nFurthermore, in Nestin-CreERT2;Ai14 reporter mice, we confirmed the presence of Slc22a17\nexpression in tdTomato⁺ NSCs via immunofluorescence staining (see the Response Fig. 6B below).\nThese findings support the notion that Slc22a17 remains functionally relevant in adult neurogenesis.\n)%(\nlavivrus\nnoitcarF\nA B\ncKO_M cKO_F\nPostnatal Days\nResponse Fig. 6 Slc22a17 deficiency resulting in neuronal morphological abnormalities during adult\nneurogenesis.\n(A) Representative photos and statistical analysis showing dendrite numbers and dendritic spine numbers in the\ntdTomato+ neurons of WT and iKO mice (n = 16 cells from 3 mice/group) and Thy1-GFP+ neurons of f/f and f/f;\nCaMKIIa-Cre mice (n = 11 cells from 3 mice/group). Left: Scale bar, 50 μm; Right: Scale bar, 5 μm.\n(B) Left: Bar plot showing age-dependent changes in the proportion of Slc22a17⁺ NSCs among total NSCs,\nquantified from single-cell RNA-seq data (GSE104323). Right: Representative immunofluorescence staining\nshowing Slc22a17 protein expression in tdTomato⁺ NSCs from Nestin-CreERT2;Ai14 adult mice.\nData are presented as mean ± SEM. Student’s t-test was used. **p<0.01, ***p<0.001.\n5. Line 213, please provide a reference.\nResponse #2-5:\nThank you for pointing this out. We apologize for the lack of clarity in the original sentence. In our\nown experiments, we observed Slc22a17 expression in neurons through whole-brain\nimmunofluorescence staining as shown below (Response Fig. 7). This finding prompted us to further\ninvestigate whether neuron-specific deletion of Slc22a17 would lead to corresponding phenotypic\nchanges.\nWe have revised the sentence accordingly to better reflect this rationale (Line 221-222). The updated\nsentence now reads:\nTW\nOKi\n6\n4\n2\nrebmun\netirdned\nlasab\nyramirP\n** 20\n15\n10\n5\nmµ\n02\n/\nytisned\nenipS\nA ***\nB\n60.2%\n60\n45.9%\n40\n40.3%39.0% Slc22a17tdTomatoDAPI\n34.6%\n27.9% 27.5%\n24.8%\n20\n)%(\nsCSN\n+71a22clS\nfo\negatnecreP\nf/f\nerC-αIIKMaC;f/f\nThy1-GFP\n10\n8\n6\n4\n2\n0\nf/f Cre\nα-\nKII\nM\nCa\nf/f;\nrebmun\netirdned\nlasab\nyramirP\n20\n15\n10\n5\n0\nf/f Cre\nα-\nKII\nM\nCa\nf/f;\nmµ\n02\n/\nytisned\nenipS\n“Given the neuronal expression pattern of Slc22a17 illustrated in whole-brain\nimmunofluorescence staining (Extended Data Fig. 1 B), we next examined the effects of\nSlc22a17 knockout in specific mature neuron populations.”\n200\n150\n100\n50\n0\n0 2 4 6 8\nDistance (μm)\nResponse Fig. 7 Slc22a17 expression in mature neurons.\n(A) Immunofluorescence staining results showed that Slc22a17 is widely distributed in the adult mouse brain. Left:\nScale bar, 500 μm; Right: Scale bar, 50 μm.\n(B) Top: Representative images of immunofluorescence staining of Slc22a17 and MAP2 in the cortex. Scale bar,\n10 μm; Bottom: Representative confocal images and line intensity plots.\n6. Does Nes-Cre express and thus delete SLC22A17 function in the liver and spleen? What could\naccount for the accumulation of iron in these peripheral tissues shown in Supplemental Fig.4C?\nResponse #2-6:\nWe thank the reviewer for raising this important point.\nWhile it has been reported that Nestin-Cre may exhibit occasional peripheral leakage 8, we\nspecifically examined the expression of Slc22a17 in peripheral tissues, including the liver and spleen,\nof our cKO mice. Our qPCR analysis confirmed that Slc22a17 expression levels in these organs\nremained unchanged (as shown in Response Fig. 8A below), indicating no detectable Slc22a17\ndeletion outside the central nervous system.\nAlthough our Slc22a17 knockout was restricted to the brain, we observed iron accumulation in the\nliver and spleen. This phenomenon could be explained by a central-peripheral regulatory mechanism,\nwhereby disrupted iron homeostasis in neural stem cells triggers systemic responses. Previous\nstudies have suggested that central nervous system iron overload can alter systemic iron distribution\n9. Inflammation in the central nervous system or iron overload in specific brain regions induced by\nPfn2 deletion can influence peripheral iron metabolism through the modulation of hepatic hepcidin\nexpression 10,11.\nTo further explore the observed systemic iron accumulation, we measured serum levels of hepcidin,\nas well as hepatic Hamp mRNA expression (as shown in Response Fig. 8B and C below). We found\nthat serum hepcidin and hepatic Hamp mRNA levels were significantly upregulated in cKO mice,\nsuggesting that deletion of Slc22a17 in the central nervous system may lead to altered hepatic\nytisnetnI\nA B\nSlc22a17 Slc22a17 DAPI Slc22a17MAP2DAPI Slc22a17 MAP2\nSlc22a17\nMAP2\nhepcidin secretion, contributing to whole-body iron accumulation. These mechanisms are currently\nunder further investigation in our lab.\nInterestingly, although hepcidin is a key regulator of iron metabolism, its role in brain iron\nhomeostasis appears to be less decisive, as systemic hepcidin deficiency does not significantly alter\nbrain iron load 12. Consistent with this, when we pharmacologically blocked peripheral hepcidin in\ncKO mice using Compound C (10 mg/kg, intravenously once 13), brain iron accumulation was not\nrescued (as shown in Response Fig. 8D below), supporting the notion that the neural iron\ndysregulation is a direct consequence of Slc22a17 deficiency in neural stem cells.\nThis point has been addressed in the Results section (Line 246-250) as follow:\n“In the liver and spleen—two primary storage organs for iron—only iron concentrations were\nsignificantly higher in cKO mice compared to WT mice (Extended Data Fig. 4, C and D) 14,\npotentially due to brain-specific Slc22a17 deletion indirectly enhancing hepatic hepcidin\nexpression and systemic iron accumulation via central-peripheral regulation.”\nResponse Fig. 8 Systemic iron accumulation may due to brain-specific Slc22a17 deletion indirectly\nenhancing hepatic hepcidin expression.\n(A) qPCR analysis showing similar Slc22a17 expression level in the liver and spleen of cKO mice compared to WT\nlittermates (n = 3 mice/group).\n(B) Increased Hamp mRNA level in the liver of cKO mice compared to WT littermates (n = 3 mice/group).\n(C) ELISA analysis revealed elevated hepcidin level in the serum of cKO mice. (n = 3 mice/group)\n(D) Non-heme iron levels in brain tissues of WT, cKO and cKO mice administered with Compound C\nintravenously measured by the standard colorimetric kit (n = 3 mice/group).\nData are presented as mean ± SEM. Student’s t-test and one-way ANOVA, Tukey’s multiple comparisons test were\nused. *p<0.05, **p<0.01, ***p<0.001.\n7. Line 243-246, Either remove this analysis from the report or provide more details of this study for\nduration of the feeding and data demonstrating the effect of these diets on hematocrit and liver TfRc.\nAs such, the TfRc expression shown in the Supplemental Fig.4F was contradictory to its known\ndownregulation in response to low iron diet (See work from Georgieff MK’s group).\nResponse #2-7:\nWe sincerely thank the reviewer for the insightful comment. We now provide a detailed clarification\nof the experimental design of this dietary iron manipulation model. In our study, adult mice (after\nSlc22a17 iKO was induced by tamoxifen injection) were fed with low iron diet (12 ppm) or high iron\ndiet (912 ppm) continuously for four weeks. The purpose of this dietary iron intervention experiment\nwas to explore whether the expression of Slc22a17 is regulated by systemic iron levels.\nWith respect to Tfrc expression changes, we have carefully reviewed the literature. The classical\nstudies from Dr. Georgieff’s group mainly focused on perinatal iron deficiency models, in which the\ndeveloping brain has high iron demand and immature blood-brain barrier function. In these models,\niron deficiency consistently induces a significant upregulation of Tfrc mRNA expression in brain\nregions such as hippocampus and cortex 15-17. However, to our knowledge, systematic studies\ninvestigating brain Tfrc expression following dietary iron deficiency in adult animals remain very\nlimited. Available studies suggest that, in adult brain, the iron homeostasis is relatively stable, and\ndietary iron deficiency may exert minimal effects on Tfrc mRNA expression 18,19.\nConsidering the limited regulatory effect of dietary iron on the mRNA levels of transporters related\nto brain iron metabolism in adult animals, and to maintain the logical consistency and rigor of the\nmanuscript, we have decided to remove this result from the revised version.\nWe sincerely thank the reviewer again for the thoughtful suggestion, which has helped us to improve\nthe quality and logical consistency of the manuscript.\n8. Fig.4G, the 8-OHdG labeling was not in cell nucleus, suggesting non-specific labeling. Consider\nusing another marker (e.g., g-H2AX) to assess DNA damage.\nResponse #2-8:\nWe sincerely thank the reviewer for the thoughtful comment and suggestion.\nIndeed, following oxidative stress-induced DNA damage, 8-OHdG staining is often observed in\nextranuclear compartments, which may reflect either mitochondrial DNA damage or cytoplasmic\nredistribution. As also shown in a previously published study (Fig. 5G of Zhao et al. 20), the 8-OHdG\nsignal was largely extranuclear, consistent with our observations in Fig. 4H (previously Fig. 4G).\nNevertheless, to strengthen the reliability of our conclusions and address potential concerns\nregarding antibody specificity, we performed additional immunofluorescence staining using γ-H2AX\nas a complementary marker of DNA damage in neurospheres. The results showed a significant\nincrease in γ-H2AX signal in cKO samples, consistent with our 8-OHdG data. These new results\nhave been shown below:\ncKO\nWT - +DFO +NAC\n8-OHdG DAPI 60\n40\n20\nγ-Η2ΑΧ DAPI 10\n5\nK K c c\naera\n/\nytisnetni\nGdHO8\nevitaleR\n***\n***\n*** 50\n40\n30\n20\n10\n0\naera\n/ ytisnetni\nXA2H-γ\nevitaleR\n***\n***\n***\nT O O C W K F A c D N O- O-\nK K c c\nResponse Fig. 9 Representative images of neurosphere immunostained with antibody recognizing DNA damage\n(8-OHdG and γ-H2AX) and quantification of relative marker intensity per DAPI area. Scale bar, 20 μm. Data are\npresented as mean ± SEM. One-way ANOVA, Scheffe’s multiple comparisons test was used. ***p<0.001.\n9. Fig.4L, please report the difference of apoptotic cells in cKO vs WT hippocampus, which would\nbe important to support the in vivo effect of SLC22A17 LOF.\nResponse #2-9:\nWe sincerely thank the reviewer for this valuable suggestion.\nIn response, we have quantified the number of cleaved Caspase-3 (Casp3)-positive apoptotic cells in\nthe hippocampus, as shown in Fig. 4M (previously Fig. 4L). The results revealed a significant\nincrease in apoptotic cells in the cKO hippocampus compared to WT controls, supporting the in vivo\neffect of SLC22A17 loss-of-function. We have now included the corresponding quantification in the\nrevised Fig. 4M and updated the main text to reflect this addition.\nM\nCasp3\nFig. 4 M Left: IF staining of cleaved Caspase3 in the DG of WT and cKO hippocampus. Scale bar, 50 μm. Right:\nQuantification of Casp3+ cells per DG (n = 4 mice/group). Data are presented as mean ± SEM. Student’s t-test was\nused. **p<0.01.\n10. (Minor) Fig.4N, please add arrows indicate abnormal features shown in the figure.\nResponse #2-10:\nThank the reviewer for this helpful suggestion. We have added red arrows in Fig. 4O (previously Fig.\n4N) to indicate the abnormal mitochondrial cristae. These markings help highlight the morphological\nalterations observed in the cKO hippocampus.\nTW\nOKc\nC\nA\nN\nO-\nK\nc\n60\n40\n20\n)2mm(\nGD\n/\nsllec\n+3psaC\n**\nO\nTW\nOKc\nP14\nHippocampus\nFig. 4 O Representative TEM images depicting the ultrastructure of mitochondria in WT and cKO hippocampus.\nMitochondrial swelling and cristae disorganization indicate defective or atypical mitochondria. Red arrows indicate\nabnormal mitochondrial cristae. Scale bar, 200 nm.\n11. Line 272 -277, the present data were unclear regarding the implication of ferroptosis for at least\ntwo reasons: (1) It is unclear whether actin expression was not altered in cKO (vs WT) neurospheres,\nwhich could compromise its use as a normalizer for WB (This may also apply to the expression of\nGAPDH given the mitochondrial effects), and (2) expression profiles for ferroptosis regulators\n(Supplemental Fig.4h,i) appear to differ between cKO and WT, invoking a possibility of\nupregulation for both positive and negative regulators in the cKO neurosphere.\nResponse #2-11:\nWe thank the reviewer for this insightful and constructive comment.\nRegarding point (1):\nTo address this concern, we repeated the Western blot analysis on neurospheres using both β-actin\nand GAPDH as internal controls. We found that the expression levels of both β-actin and GAPDH\nremained stable between cKO and WT samples, and their normalization yielded consistent results for\nGPX4 (please see Response Fig. 10A and C below).\nFurthermore, analysis of our neurosphere RNA-seq dataset revealed no significant difference in the\ntranscript levels of Actb and Gapdh between cKO and WT groups (as shown in Response Fig. 10B\nbelow). These results support the use of β-actin and GAPDH as valid loading controls in our Western\nblot analysis and confirm that GPX4 levels are not significantly altered in cKO neurospheres.\nRegarding point (2):\nTo further explore the possibility of ferroptosis occurring in cKO neurospheres, we performed gene\nset enrichment analysis (GSEA) based on our RNA-seq data. Specifically, we used curated gene sets\nrepresenting canonical ferroptosis drivers and suppressors to assess their collective expression\npatterns. The GSEA results indicated no significant enrichment for either driver or suppressor gene\nsets in cKO compared to WT, suggesting that there is no consistent or directional regulation of the\nferroptosis pathway in cKO neurospheres. This analysis further supports the conclusion that\nferroptosis is unlikely to be activated under these conditions.\nResponse Fig. 10 Validation of loading controls and GPX4 expression in cKO and WT neurospheres.\n(A) Western blot analysis of GPX4 expression in neurospheres from cKO and WT mice, with β-actin and GAPDH\nas internal controls. Both β-actin and GAPDH levels were stable between cKO and WT samples, confirming their\nreliability as loading controls.\n(B) RNA-seq analysis of Actb and Gapdh transcript levels in cKO and WT neurospheres, showing no significant\ndifference.\n(C) Full, uncropped Western blot membranes showing consistent expression for β-actin and GAPDH.\n12. Fig.5B, please provide data for cultured cells grown in control media to serve as baseline. Given\nthe evidence for reduced iron uptake (lower TfR) and elevated iron storage (higher ferritin) in cKO\n(vs WT) cultured neurons, whether the rate of iron efflux is compromised in the cKO neurons\nremains unclear without the baseline level.\nResponse #2-12:\nWe sincerely thank the reviewer for the insightful comment. To clarify this experiment, we have now\nincluded the original intracellular iron content curves in Extended Data Fig. 5A.\nAs shown, under baseline (untreated) conditions, neurons isolated from cKO mice exhibited\nsignificantly higher iron content than those from WT mice. In our iron efflux assay, both WT and\ncKO neurons were first pre-loaded with 100 μM FAC for 2 hours, which saturated intracellular iron\nlevels and resulted in comparable iron content between the two groups before the iron efflux assay.\nSubsequently, we replaced the medium with fresh, iron-free culture medium and collected\nintracellular iron measurements at multiple time points (e.g., 0.5 h, 2 h, 4 h). These measurements\nallowed us to calculate iron efflux kinetics. The iron efflux rate shown in Fig. 5B was calculated as\nthe percentage of iron lost after 2 h relative to the initial iron content (i.e., [Fe_0h − Fe_2h]/Fe_0h).\nWe observed that cKO neurons exhibited a significantly lower iron release rate compared to WT\nneurons. This finding aligns well with our previous observations that Slc22a17 deletion led to\nintracellular iron accumulation, evidenced by elevated total iron content, increased ferritin\nexpression (elevated iron storage), and decreased TfR levels (due to negative feedback regulation\nunder high intracellular iron conditions).\nWe have now added the corresponding data in the revised manuscript. We thank the reviewer again\nfor raising this important point, which has allowed us to strengthen the rigor of our experimental\ndesign and data interpretation.\nExtented Data Fig. 5 A Residual intracellular iron contents are determined for the indicated periods after iron\npreload in primary neurons derived from WT and cKO mice.\n13. Fig.5C is confusing. If the signal intensity represents level of iron content, then why WT slice\nshowed little evidence iron accumulation, whereas OE slice showed evidence of iron accumulation\nfollowing FAC exposure given the hypothesis that SLC22A17 regulates cellular iron efflux? Please\nconfirm that the background signals were similar in the image captured and analysis for both groups.\nResponse #2-13:\nWe appreciate the reviewer’s thoughtful comment and apologize for not clearly explaining the\nmechanism of the Calcein–based iron measure assay. After entering cells, Calcein-AM is hydrolyzed\nby intracellular esterases to produce Calcein, which emits strong green fluorescence. Calcein is a\nwell-established metal-chelating indicator 4, and its fluorescence is quenched upon binding to Fe³⁺ at\nphysiological pH. Therefore, a decrease in Calcein fluorescence reflects an increase in intracellular\nlabile iron levels.\nIn Fig. 5C, we observed that under untreated conditions, the Calcein fluorescence intensities—and\nthus the basal iron levels—were comparable between WT and OE brain slices. However, upon FAC\ntreatment, Calcein fluorescence was markedly quenched in WT slices, indicating increased iron\naccumulation, while OE slices showed only a mild reduction in fluorescence. These results suggest\nthat overexpression of Slc22a17 enhances iron efflux under iron overload conditions, thereby\nmaintaining intracellular iron homeostasis more effectively after FAC treatment. We have confirmed\nthat background fluorescence and image acquisition settings were consistent across all groups and\nhave clarified this information in the revised manuscript as below (Results section, Line 305-306):\n“Using calcein staining, we visualized iron content in organotypic hippocampal slice cultures and\nfound that FAC failed to elevate iron levels in the DG of the OE hippocampus (Fig. 5 C),\nas calcein fluorescence decreases upon Fe³⁺ binding.”\n14. (Minor) Add an arrow to the complex at the bottom left corner, which shows the co-localization\nof all three markers, and provide an enlarged image of this area.\nResponse #2-14:\nThank the reviewer for the helpful suggestion. We have now revised Fig. 5H by adding an arrow\npointing to the complex at the bottom left corner that shows the co-localization of all three markers.\nIn addition, we have provided an enlarged image of this area to better highlight the co-localization\nsignal. The enlarged region is shown at the bottom of the panel, with the co-localization indicated by\na white arrowhead.\nH Rab11 Lcn2 Slc22a17\n0 min 1 min 2 min 5 min\nFig. 5 H Live cell imaging showing localization of Slc22a17 to Lcn2 and recycling endosome marked by Rab11.\nWhite arrow indicates the complex shown in the upper enlarged panel, and white arrowhead points to the region\nshown in the lower enlarged panel. Scale bar, 5 μm.\n15. (Minor) Fig.6E, p62 WB image appears to be upside down. Please confirm and make correction\nas needed. Same comment for GAPDH in fig.6H.\nResponse #2-15:\nWe thank the reviewer for pointing this out, and we sincerely apologize for the confusion. For Fig.\n6E, the p62 Western blot was derived from different experimental replicates, which may have caused\nthe discrepancy in presentation. To address this, we have repeated the p62 Western blot and now\nprovide the original, uncropped image from the same membrane probed for both p62 and Actin (as\nshown in Response Fig. 11A).\nAs for Fig. 6H, we have carefully re-verified the GAPDH band, and confirm that it is correctly\noriented (as shown in Response Fig. 11B). To ensure transparency, we also provide the original blot\nimage used for this figure.\nResponse Fig. 11 Full Western blot membrane showing the expression levels of the analyzed proteins.\n16. Data presented in Fig.6F and 6I seem to be contradictory as WB showed higher nuclear Nrf2\nlevel in cKO vs WT, whereas IF showed no signal of Nrf2 in the nuclei of cKO cells.\nResponse #2-16:\nWe thank the reviewer for this important observation, and we apologize for the confusion caused by\nthe immunofluorescence images initially provided. Upon re-evaluation, we realized that the IF\nimages for Fig. 6I, especially those representing the cKO neurospheres, were not representative—\nprimarily due to the compromised morphology and health status of the cKO NSCs at the time of\nimaging, which may have affected nuclear visualization.\nTo resolve this discrepancy, we have repeated the immunofluorescence staining experiment. In the\nupdated images, we were able to clearly observe nuclear translocation of Nrf2 in cKO NSCs, which\nis consistent with the increased nuclear Nrf2 signal seen in the Western blot shown in Fig. 6F.\nWe have updated Fig. 6I with the new representative images as below:\nI\nFig. 6 I Confocal microscopy images of NSCs stained for Nrf2 and DAPI. Scale bar, 20 μm.\n17. Please state and confirm the number of mouse/groups that were used for behavioral assays.\nProvide more details the duration of DFO and ZnPP treatments and whether the treatments altered\nsystemic iron homeostasis as this could confound the central iron homeostasis.\nResponse #2-17:\nThank you for your insightful comment. We have now clearly stated the number of mice used per\ngroup for each behavioral assay in the figure legends. Regarding the DFO and ZnPP treatment\nprotocols, we administered intraperitoneal injections of DFO (100 mg/kg) and ZnPP (10 mg/kg)\nonce daily for seven consecutive days prior to tissue collection or behavioral testing, as now detailed\nin the Methods section (Line 566-569).\nAs for your important concern about potential alterations of DFO and ZnPP treatments in systemic\niron homeostasis, we measured serum iron levels seven days post-treatment and found no significant\nchanges between the experimental and control groups (see Response Fig. 12). This suggests that\nsystemic iron homeostasis was not substantially altered by the treatments. Therefore, we can\nconclude that the alterations observed in central iron homeostasis are unlikely to be confounded by\nchanges in systemic iron levels, and that the treatments did not cause a major disruption to\nwhole-body iron metabolism.\nResponse Fig. 12 Serum iron levels after DFO or ZnPP treatment (n = 3 mice/group). Data are presented as mean ±\nSEM. One-way ANOVA, Tukey’s multiple comparisons test was used.\n18. Fig.7i-l, these results seem to be contradictory to the previously reported role of Nrf2 in learning\nTW\nOKc\nJ\nNrf2 DAPI\nand memory (PMID: 29036636, PMID: 30194014, PMID: 19805328), raising doubt about the\nvalidity of these analyses. These findings need more in-depth discussion.\nResponse #2-18:\nThank you very much for your thoughtful comment and for directing us to the relevant studies\n(PMID: 29036636, 30194014, 19805328) that underscore the well-recognized role of Nrf2 in\nlearning and memory, particularly in the context of Alzheimer's disease (AD). Indeed, as\ndemonstrated in these studies, Nrf2 deletion in AD mouse models often leads to increased Aβ\ndeposition and worsened cognitive deficits, while Nrf2 activation facilitates Aβ clearance and\nneuroprotection. However, these effects are highly context-dependent.\nImportantly, in our study, Nrf2 was deleted in an otherwise healthy background. As reported in the\nstudy by Gergues et al. 7, Nrf2 knockout in normal adult mice does not impair learning and memory.\nIn the Morris Water Maze (MWM) test, both Nrf2+/+ and Nrf2−/− mice showed similar performance\nin hidden platform trials, indicating intact spatial learning and memory capacities. This is consistent\nwith our own findings, in which adult Nrf2 knockout mice did not exhibit significant deficits in\nlearning or memory compared with wild-type littermates.\nWe further observed that Nrf2 deletion was able to rescue the neurogenesis deficits and learning\nimpairments caused by Slc22a17 deficiency, highlighting a distinct and pathological role of\nsustained Nrf2 activation in this context. This indicates that Nrf2 serves as a key pathological\nmediator linking Slc22a17 deficiency to impaired hippocampal neurogenesis and cognitive function.\nWe have revised the Discussion section of the main text to emphasize that the function of Nrf2 is\ncontext-dependent, as supported by both previous studies and our findings. The revised sentence now\nreads (Line 513-517):\n“Although Nrf2 activation is generally considered neuroprotective in disease models such as\nAlzheimer's disease 7,21,22, our results show that its sustained activation in Slc22a17-deficient\nmice impairs neurogenesis and learning, highlighting a context-dependent role of Nrf2\nsignaling that may be detrimental under conditions of Slc22a17 deficiency.”\nReviewer #3 (Remarks to the Author):\nThe study by Tao et al. describes a new Slc22a17-dependent pathway to remove iron from cells\nthrough an endosomal recycling that can be used by mammals. This is an important finding because\nso far the only known regulated pathway of iron expelling from the cells is attributed to ferroportin\n(Fpn) (Drakesmith et al., 2015). It seems that this new mechanism is mostly restricted to the brain\nwhere the expression of Slc22a17 is much higher than in other organs (in many of them barely\ndetectable) [Extended Data Fig. 1A]. The Authors show how deletion of the Slc22a17 gene leads to\niron accumulation in hipocampus, oxidative stress, severe impairment of hippocampal NSC\ndevelopment, and in consequence early postnatal mortality. The methodology is sound. The Authors\nuse a wide range of cellular and molecular methods. Presentation of results is clear. Blots and\nstainings are of high quality.\nResponse #3:\nWe sincerely thank the reviewer for their positive feedback and recognition of the novel\nSlc22a17-dependent iron expulsion mechanism. We also appreciate the acknowledgment of our\nmethodology and data presentation quality.\nMy main objection to the Authors is that they propose a new mechanism of iron efflux from the cells\nmediated by Slc22a17 without seriously referring to the well-established ferroportin/ferroxidase-\ndependent pathway of iron export. It is largely known that disruption of this pathway underlies many\nneurological diseases associated with excessive iron accumulation. We do not really know how the\nFpn/ferroxidase (most probably ceruloplasmin) pathway is regulated under conditions of decreased\nScl22a17 protein level. Is it enhanced or quite the opposite – reduced? According to my comments\nbelow it is tempting to propose that the amount of iron exported by Fpn from the cells lacking\nSlc22a17 should be increased.\nResponse #3-1:\nThank you for your thoughtful and insightful comments. We appreciate your valuable suggestions,\nwhich have greatly contributed to improving the quality of our manuscript. Below is our response to\nyour specific points.\nWe have now added Fpn Western blot data in Fig. 5A, with the corresponding description of the\nchanges in the classical Fpn/ferroxidase pathway in Results section (Line 295-297). Since it is\nwell-established that Fpn plays a central role in iron export, even with a higher capacity than\nSlc22a17 (as discussed in Response #3-2), we speculated that Fpn expression might be upregulated\nas a compensatory mechanism following the deletion of Slc22a17. However, our experimental\nfindings do not support this hypothesis.\nSpecifically, we observed a reduction in Fpn protein levels in the hippocampal tissue of Slc22a17\nKO mice (as detected by Western blot in Response Fig. 13A below). Additionally, we detected\nastrocytic iron overload and increased hepcidin levels in cKO mice (see the Response Fig. 13B and\nC below). These observations suggest that Slc22a17 deletion does not activate a compensatory\nupregulation of Fpn. Instead, we speculate that the upregulation of hepcidin may lead to Fpn\ninternalization and degradation 23. Notably, our RNA-seq data showed that the Slc40a1 mRNA levels\nremained unchanged, which is characteristic of hepcidin’s post-transcriptional regulation of Fpn\nlevels 24(see the Response Fig. 13D below). We hypothesize that this may be due to astrocytic iron\noverload in the brain, which triggers the increased secretion of hepcidin, leading to the observed\nreduction in Fpn levels 25. This mechanism likely contributes to the further blockade of iron export in\nthe absence of Slc22a17.\nWe have now updated the corresponding main text as below:\n“We observed decreased levels of transferrin receptor (TfR) and its regulator IREB2, as well as\nincreased levels of Ferritin-H and Ferritin-L, which are indicative of iron overload in the cKO\nhippocampus (Fig. 5 A). Based on these findings, we hypothesized that Slc22a17 may facilitate iron\nefflux in neural cells in response to elevated intracellular iron levels. Interestingly, we did not\nobserve compensatory upregulation of ferroportin (Fpn, Slc40a1), but rather a reduction in\nFpn protein levels in the hippocampus, suggesting that Fpn-mediated iron export may be\nimpaired in the absence of Slc22a17.”\n**\n2.0\n1.5\n1.0\n0.5\n0.0\nWT cKO\nResponse Fig. 13 Reduction of Fpn expression in cKO mice.\n(A) Western blotting analysis of IREB2, TfR, Slc40a1, Ferritin-H and Ferritin-L protein levels in WT and cKO\nhippocampus at P14.\n(B) Western blotting analysis of Ferritin-H in WT and cKO astrocyte at P14.\n(C) Increased Hamp mRNA level in the astrocyte derived from cKO mice compared to WT littermates (n = 3\nmice/group).\n(D) Bar plot showing the mRNA levels of Slc40a1 in NSCs derived from WT and cKO mice, as determined by\nRNA-seq analysis (n = 3 mice/group).\nData are presented as mean ± SEM. Student’s t-test was used. **p<0.01.\nIn this context it is interesting What is the quantitative potential to transport iron to extracellular\nenvironment by Slc22a17 system compared to Fpn pathway?\nResponse #3-2:\nWe greatly appreciate the reviewer’s insightful suggestion. In response, we have now performed a\nquantitative comparison of the iron efflux capacities of Slc22a17 and Fpn in an in vitro transport\nsystem (see the updated Extended Data Fig. 5E-J), and have accordingly updated the main text\nResults section (Line 337-355) and Discussion section (Line 475-478) to reflect these findings.\nnoisserpxe\npmaH\nevitaleR\n)nitca\not\ndezilamron(\nA B C D\nWT cKO Astrocyte\nIREB2 Astrocyte\n0.3\nTfR WT cKO\nSlc40a1 0.2\nFerritin-H\nFerritin-H\nGAPDH\n0.1\nFerritin-L\nFerritin-H fold: 1.0 1.1 0.9 1.4 2.1 2.1\nGAPDH 0.0\nWT cKO\nIREB2 fold: 1.0 1.0 0.7 0.5\nTfR fold: 1.0 1.0 0.5 0.3\nSlc40a1 fold: 0.9 1.1 0.7 0.6\nFerritin-H fold: 1.2 0.8 1.5 2.0\nFerritin-L fold: 1.0 1.0 1.2 1.2\n1a04clS\nfo\nMKPF\nNSC\nWe first knocked down SLC22A17 and SLC40A1 (FPN) in HEK293 cells using siRNA targeting\nthese genes, and performed dual knockdown of SLC22A17 and SLC40A1 (siSLC22A17 +\nsiSLC40A1) to evaluate their impact on cellular iron export (Extended Data Fig. 5E). Cells were\nexposed to 100 µM FAC in the culture medium for 24 hours, followed by replacement with fresh\nmedia without FAC. At 4, 8, and 24 hours after FAC removal, we collected the medium and\nmeasured the extracellular iron concentration using the iron colorimetric assay. The results showed\nthat SLC40A1 knockdown led to a significant reduction in iron efflux ability, with the iron\nconcentration in the medium remaining at a lower level. SLC22A17 knockdown also resulted in\ndecreased iron export capacity, especially at later time points (24h), where extracellular iron\naccumulation slowed. Dual knockdown of both genes further blocked iron efflux, indicating that\nboth proteins cooperate in maintaining iron homeostasis (Extended Data Fig. 5F).\nsiRNAs targeting SLC22A17 or SLC40A1 were co-transfected with a plasmid encoding mCherry into\ncells using a single lipid nanoparticle complex, allowing for identification of successfully transfected\ncells. Fluorescence was captured 48 hours post-transfection. In SLC22A17-silenced cells, a moderate\ndecrease in calcein green fluorescence intensity was observed, indicating an increase in labile iron.\nNotably, knockdown of SLC40A1 resulted in a more pronounced fluorescence quenching, suggesting\na greater accumulation of intracellular iron (Extended Data Fig. 5G). Furthermore, using calcein\ngreen as an iron probe, we also performed real-time dynamic monitoring of intracellular iron levels\nunder conditions of knockdown and overexpression of these two genes. The results showed that\nSLC22A17 knockdown significantly accelerated iron accumulation, while SLC40A1 knockdown\ncaused more severe intracellular iron retention, indicating that both proteins participate in iron efflux\nregulation, with SLC40A1 having a more direct and pronounced effect (Extended Data Fig. 5H). In\noverexpression experiments, while overexpression of Slc22a17 had no significant impact on the iron\naccumulation rate in the short term, it achieved a similar iron export effect as Slc40a1 over time,\ndemonstrating its capacity for regulating iron efflux at longer time points (Extended Data Fig. 5I and\nJ).\nThese results suggest that Slc40a1 functions as a potent iron exporter, directly mediating\ntransmembrane iron transport, whereas Slc22a17 plays a crucial upstream role in the process of iron\nexport, specifically in the transition of iron from the endoplasmic reticulum to the cytoplasm.\nTherefore, we propose that Slc22a17 is an upstream iron transporter involved in regulating iron\nefflux, particularly in tissues such as the nervous system, which are highly sensitive to iron\nhomeostasis.\nE\n1.5\n1.0\n0.5\n0.0\nsi\nNe\ns\ng\ni SL\nC22\nA17\nsi SL\nC40\nA1\nExtended Data Fig. 5 E qPCR analysis showing relative mRNA levels in cells transfected with specific siRNAs\ntargeting SLC22A17 or SLC40A1. Data are presented as mean ± SEM. Student’s t-test was used. ***p<0.001.\nExtended Data Fig. 5 F Extracellular iron contents were measured at 4, 8, 24 hours after FAC removal in\nsiRNA-treated cells.\nExtended Data Fig. 5 G Representative fluorescence images showing calcein green signal in siRNA-treated\nmCherry+ cells. Scale bar, 50 μm.\nExtended Data Fig. 5 H Real-time monitoring of intracellular iron levels using calcein fluorescence intensity in\nsiRNA-treated cells. At 60 seconds, FeCl₂ was added to the cells to simulate iron influx.\nExtended Data Fig. 5 I qPCR analysis showing >500 times increase in the expression of Slc40a1 in Slc40a1-OE\nHT22 cell lines. Data are presented as mean ± SEM. Student’s t-test was used. ***p<0.001.\nExtended Data Fig. 5 J Real-time monitoring of intracellular iron levels using calcein fluorescence intensity in\nSlc22a17-OE and Slc40a1-OE cells. At 60 seconds, FeCl₂ was added to the cells to simulate iron influx.\nFigure 1A-B shows increase in iron level in the hippocampus of Slc22a17 cKO mice at P14 and\nrespective changes in the the expression of key iron proteins responsible for the maintenance of\nintracellular iron balance. In Figure 1C an opposite effect (decreased iron in hippocampus of mice\noverexpressing the Slc22a17 gene) is shown. It seems that these changes are due to the\npost-transcriptional regulation mediated by IREB2 (Iron Regulatory Protein 2) that post-\ntranscriptionally controls mRNAs (encoding proteins involved in cellular iron regulation ) containing\nIRE (Iron Responsive Element), regulatory sequence localized in 5’ or 3’ UTR. Under high iron\nlevel in hippocampus of cKO mice, IRP2 is probably down-regulated (degraded) and in consequence\nthe expression of TfR1 (few IRE copies in 3’ UTR) is decreased and the expression of H- and L-\nferritin subunits is increased (1 IRE copy in 5’ UTR). To complete the expression pattern of iron\nmetabolism proteins, an evaluation of Fpn protein by Western blot should be added. Considering that\nFpn mRNA contains IRE in 5’UTR, Fpn protein should be regulated similarly to ferritin subunits i.e.,\nincreased. Potential up-regulation of Fpn could be considered as a regulatory mechanism attenuating\nnoisserpxe\nANRm\nevitaleR\n***\n*** )nitca\not\ndezilamron(\n80\n60\n40\n20\n0\n4h 8h 24h\n)Mµ(\ntnetnoc\nnorI\nralullecartxE\nsiNeg\nsiSLC22A17\nsiSLC40A1\nsiSLC22A17+siSLC40A1\nsiNeg+mCherry siSLC22A17+mCherry siSLC40A1+mCherry\nnieclaC\n1.05\n1.00\n0.95\n0.90\n0.85\n0 100 200 300 400\nTime (s)\nytisnetni\necnecseroulf\nnieclaC\nsiNeg\nsiNeg+FeCl\n2\nsiSLC22A17+FeCl 2 1.05\nsiSLC40A1+FeCl 2\n1.00\n0.95\n0.90\n0 100 200 300 400\nTime(s)\nytisnetni\necnecseroulf\nnieclaC\nF G\nEV\nH I EV+FeCl\n2 1600 Slc40a1-OE+FeCl\n1400 2\n1200\n1000\n800\n600\n2\n1\nSlc40a1-\nnoisserpxe\n1a04clS\nevitaleR\n)nitca\not\ndezilamron(\nJ\n***\niron accumulation in the Slc22a17 cKO hippocampus, which is due to the inhibition of iron efflux in\nthe absence of Slc22a17 protein.\nResponse #3-3:\nWe sincerely thank the reviewer for the valuable suggestion.\n1. Regarding IREB2 down-regulation:\nWe agree with your observation regarding the potential down-regulation (degradation) of IRP2 under\nhigh iron levels in the hippocampus of cKO mice, which could lead to decreased TfR1 expression\nand increased ferritin subunits expression. Therefore, we measured IREB2 protein levels and found a\nsignificant reduction in IREB2 levels in the hippocampus of cKO mice (as shown in Fig. 5A), which\ncorresponds to our expectation and further supports the idea of post-transcriptional regulation\nmediated by IREB2.\n2. Regarding Fpn expression:\nWe thank you for the suggestion to evaluate Fpn protein levels. Following your recommendation, we\nhave now added the Western blot results for Fpn in Fig. 5A. As shown, we observed a decrease in\nFpn protein levels in the hippocampus of cKO mice. We hypothesize that this reduction is due to the\nupregulation of astrocytic hepcidin, which may lead to the internalization and degradation of Fpn,\nthereby preventing iron export 23.\nWe have made the appropriate revisions in the manuscript to reflect these findings.\n** 2.0\n1.5\n1.0\n0.5\n0.0\nWT cKO\nResponse Fig. 14 Reduction of IREB2 and Fpn expression in cKO mice.\n(A) Western blotting analysis of IREB2, TfR, Slc40a1, Ferritin-H and Ferritin-L protein levels in WT and cKO\nhippocampus at P14.\n(B) Western blotting analysis of Ferritin-H in WT and cKO astrocyte at P14.\n(C) Increased Hamp mRNA level in the astrocyte derived from cKO mice compared to WT littermates (n = 3\nmice/group).\nData are presented as mean ± SEM. Student’s t-test was used. **p<0.01.\nBy the way, there is also another IRP – IRP1, which regulates intracellular iron as a holo- [4Fe-4S]\nor apo-form. These post-translational modifications in the IRP1 molecules are not only regulated by\niron but also by oxidative stress reported by Authors. What could be the role if any of IRP1 in the\nregulation of iron metabolism in cKO hippocampus? In my opinion all these aspects need a deeper\ndiscussion in the manuscript.\nResponse #3-4:\nnoisserpxe\npmaH\nevitaleR\n)nitca\not\ndezilamron(\nA B C\nWT cKO Astrocyte\nIREB2 Astrocyte\nTfR WT cKO\nSlc40a1\nFerritin-H\nFerritin-H\nGAPDH\nFerritin-L\nFerritin-H fold:1.0 1.1 0.9 1.4 2.1 2.1\nGAPDH\nIREB2 fold:1.0 1.0 0.7 0.5\nTfR fold:1.0 1.0 0.5 0.3\nSlc40a1 fold:0.9 1.1 0.7 0.6\nFerritin-H fold:1.2 0.8 1.5 2.0\nFerritin-L fold:1.0 1.0 1.2 1.2\nWe appreciate the reviewer’s thoughtful comment regarding the potential role of IRP1 in the\nregulation of iron metabolism in the cKO hippocampus. In response to your suggestion, we have\nmeasured IRP1 levels using Western blot analysis and our result indicates that IRP1 levels do not\nshow significant differences between the cKO and WT groups (as shown in the Response Fig. 15\nbelow). As you suggested, IRP1 primarily regulate iron homeostasis through its conformational\nchanges between the apo- and holo- forms rather than through changes in protein levels.\nPrevious studies have reported that under conditions of iron overload, IRP1 tends to adopt the\nholo-IRP1 form, which cannot bind to IREs 26, and in this case, Fpn expression should increase.\nHowever, our results show a decrease in Fpn levels, suggesting that in the context of Slc22a17\nknockout, it is likely hepcidin, rather than IRP1, that plays the dominant role in regulating Fpn\nexpression.\nWe have updated the manuscript to better explain the observed reduction in Fpn levels in cKO\nhippocampus.\nResponse Fig. 15 Western blotting analysis of IRP1 and Slc40a1 protein levels in WT and cKO hippocampus at\nP14.\nThe Authors clearly show [Figure 6F-E] that Slc22a17 regulates the p62/Nrf2/HO-1 signaling axis\nand that HO-1 inhibition and Nrf2 KO significantly rescued neurogenesis in Slc22a17 cKO mice.\nThis strongly suggest that the amount of iron released intracellularly (from heme molecules) exceeds\nthe transport capacity to the extracellular space. Importantly, the Slc40a1 gene is also\ntranscriptionally regulated by Nrf2 through the MARE/ARE sequence motif present in the Slc40a1\npromoter (Marro et al., 2010). It is puzzling why among genes targeted and activated by Nrf2\nthrough their promoters upon Slc22a17 deletion is there no the Slc40a1 gene [Figure 6B-C]? This\nquestion is all the more relevant because in cells overexpressing Slc22a17 (supposed to decrease\nintracellular iron) expression of the Slc40a1 and showing decreased iron content, this gene is\nsignificantly (*) decreased. Here, again evaluation of Fpn protein would be useful because IRP/IRE\nsystem does not influence Fpn mRNA level but only the efficiency if its translation.\nIn conclusion, I strongly recommend analysis of ferroportin protein expression in Slc22a17 cKO\nhipocampus and adding to the discussion some conclusion resulting from this assay.\nResponse #3-5:\nThank you very much for raising this important question. We observed that Nrf2 was significantly\nactivated, and HO-1 was upregulated in the cKO mice, participating in heme iron release; however,\nthe Slc40a1 mRNA levels were not significantly upregulated, and the protein levels were decreased.\nWe hypothesize that the deletion of Slc22a17 activates the Nrf2 signaling axis through p62\naccumulation, which represents a non-canonical activation mechanism dependent on autophagy\nblockade. Previous studies have shown that p62-mediated Nrf2 activation primarily induces the\nexpression of antioxidant and autophagy-related genes 27, with limited transcriptional activation of\niron export-related genes such as Slc40a1. Additionally, hepcidin secreted by astrocytes strongly\nreduces Fpn protein levels. Even though Nrf2 activation may have the potential to upregulate Fpn\ntranscription 28, it cannot counteract the protein-level degradation. These findings highlight the\ncomplex regulatory network of iron homeostasis regulated by Slc22a17.\nWe have now added additional content regarding Fpn in both the main text and the discussion, as per\nyour suggestion. Thank you once again for your insightful recommendation.\nReviewer #4 (Remarks to the Author):\nDear authors,\nThank you for the chance to review this paper. This is a very well-written, well-executed study that\ndemonstrates that the transport protein Slc22a17 regulates iron homeostasis in hippocampus, which\nis essential for postnatal neurogenesis. The data support a model in which Slc22a17 localizes to the\nER, regulates iron export through the endosomal recycling pathway, and interacts with p62, a\nmodulator of the Nrf2/HO-1 pathway. The study employs in vitro and in vivo models and multiple\ntechnical approaches. Overall, the interpretations and conclusions are sound, but we do have several\ncomments that we would like to see addressed by the authors.\nResponse #4:\nWe sincerely thank the reviewer for their thoughtful and positive feedback. We greatly appreciate\ntheir recognition of the study's quality and the novel insights into Slc22a17’s role in regulating iron\nhomeostasis in the hippocampus.\n-On line 108, the authors state that “these observations highlight the critical role of Slc22a17 in early\nneurogenesis and its importance in maintaining iron homeostasis within NSCs.” At this early point in\nthe manuscript, this is an over-statement. The results thus far had only shown associations, not a\ncausal link.\nResponse #4-1:\nThank the reviewer for this helpful comment. We fully agree that, at this stage of the manuscript, our\nfindings primarily demonstrated a correlation rather than a definitive causal relationship at this early\npoint. In response, we have revised the sentence to adopt a more open and cautious tone as follows\n(Line 112-114). We believe this revision better reflects the nature of our data at this point in the\nmanuscript.\n“These observations suggest a potential role of Slc22a17 in early neurogenesis and its\ninvolvement in iron homeostasis within NSCs.”\n-Please express brain weight as % body weight in Extended Data Fig. 1F. When this is done, the\nauthors may discover that the brain weight is not actually small but rather just proportionate to body\nweight.\nResponse #4-2:\nWe sincerely thank the reviewer for this insightful suggestion. As advised, we recalculated the brain\nweight as a percentage of body weight in both WT and cKO mice. Interestingly, we found that the\nbrain-to-body mass ratio was significantly increased in cKO mice (now presented in Extended Data\nFig. 1F). This result suggests that although the absolute brain weight was slightly reduced, the\nreduction in body weight was even more pronounced. This further supports the notion that\nbrain-specific deletion of Slc22a17 has a profound impact on overall growth and development in\nmice.\nExtended data Fig. 1 F Brain-to-body mass ratio of WT and cKO mice at P14 (n = 4 mice/group). Data are\npresented as mean ± SEM. Student’s t-test was used. ***p<0.001.\n-On page 12, line 209, the authors state “additionally, iKO mice showed a slightly reduced freezing\nbehavior when exposed to the shock context (Extended Data Fig. 3C).” Is there a p-value here? None\nis depicted in the figure.\nResponse #4-3:\nWe sincerely thank the reviewer for pointing out the omission of the p-value. In Extended Data Fig.\n3C, we performed a two-way ANOVA analysis and obtained a p-value of 0.00035, indicating that\nthe observed reduction in freezing behavior of iKO mice was statistically significant. We have now\nincluded the p-value in the revised version of the figure. Thank you once again for your careful\nreview.\nExtended Data Fig. 3 C Time-course analysis of freezing percentage in iKO and WT mice (n = 5 mice/group).\nData are presented as mean ± SEM. Two-way ANOVA was used. ***p<0.001.\n-Non-heme iron levels should be measured in addition to total iron levels. Non-heme iron levels are a\nstandard measurement in studies of iron biology, particularly when there may be changes in red\nblood cell parameters that could impact tissue heme iron levels.\nResponse #4-4:\nWe sincerely thank the reviewer for this insightful suggestion. We fully agree that non-heme iron\nmeasurements are particularly informative in the context of potential alterations in red blood cell\nparameters, which may affect tissue heme iron levels. In accordance with the established methods\nreported by Wang et al. 29, we measured non-heme iron levels in brain tissues from both WT and\ncKO mice. Consistent with our ICP-MS measurements of total iron content, non-heme iron levels\nwere also significantly elevated in the cKO group compared to WT (see the new Fig. 4C below). We\nhave included these new results in Fig. 4C and corresponding methodological details in the revised\nmanuscript (Results section, Line 243-245).\nFig. 4 C Non-heme iron levels in brain tissues of WT and cKO mice measured by the standard chromogen method\n(n = 6 mice/group). Data are presented as mean ± SEM. Student’s t-test was used. *p<0.05.\n-For the experiments related to Extended Data Fig. 4F, iron and ferritin levels should also be\nmeasured when mice are placed on high-iron diets, as the fact that Tfrc levels don’t change\nsignificantly suggest that iron levels don’t change.\nResponse #4-5:\nWe sincerely thank the reviewer for this insightful and constructive comment.\nTo directly address the reviewer’s concern, we have quantified total iron content and ferritin protein\nlevels in brain tissues from both dietary groups. The results confirmed that brain iron levels and\nferritin content are indeed altered by the dietary iron manipulation (Response Fig. 16 shown below).\nRegarding the unaltered expression of Tfrc in the high-iron diet experiments, available studies\nsuggest that in the adult brain, iron homeostasis remains relatively stable, and dietary iron changes\nhave minimal impact on Tfrc mRNA expression 18,19. Furthermore, the IRP/IRE system mediates\npost-transcriptional regulation of TfR1, so while mRNA levels may not change significantly, protein\nlevels can still be modulated by alterations in mRNA stability and translation efficiency 30.\nThe original aim of the experiment related to Extended Data Fig. 4F was to explore how systemic\niron homeostasis affects iron transporter mRNA levels. However, due to the limited effect of dietary\niron on Tfrc mRNA expression in the adult brain, we have decided to remove this result from the\nrevised version to maintain the logical consistency and rigor of the manuscript.\nWe hope this clarification addresses the reviewer’s concern and improves the clarity of our\nmanuscript. Thank you again for your valuable input.\nResponse Fig. 16 Iron contents and ferritin levels in the brain of iron-treated mice.\n(A) Iron concentrations in the brain of WT and iron-treated WT mice determined by inductively coupled plasma\nmass spectroscopy (n = 4 mice/group).\n(B) Western blotting analysis of Ferritin-H and Ferritin-L protein levels in WT and iron-treated WT mice.\nData are presented as mean ± SEM. One-way ANOVA, Tukey’s multiple comparisons test was used. *p<0.05.\n-Figure panels would be easier to interpret if the tissue type was included in the graphs (i.e. primary\ncell lines vs. tissue).\nResponse #4-6:\nThank you very much for your thoughtful suggestion. We sincerely appreciate your feedback. To\naddress your comment, we have now added the sample type labels in the updated figure. This\naddition should make the results much clearer and easier to interpret, enhancing the overall\npresentation. We hope this improves the clarity of our data and helps to convey our findings more\neffectively.\n-On line 271, the authors state “this treatment further aggravated mitochondrial damage in cKO\n\nneurospheres (Fig. 4 M).” Is there quantification for these data?\nResponse #4-7:\nWe thank the reviewer for the helpful suggestion. Quantification of mitochondrial damage has now\nbeen included in Fig. 4N (previously Fig. 4M) to support the observation described in previously line\n271. The corresponding legend and text have been revised accordingly.\nN\nFig. 4 N Left: Large fraction of JC1 monomers showing destabilization of mitochondrial membrane potential in\ncKO neurosphere. Scale bar, 20 μm. Right: The ratio of red (J-aggregates, high membrane potential) to green\n(monomers, low membrane potential) fluorescence intensity was calculated to reflect mitochondrial membrane\npotential. Data are presented as mean ± SEM. One-way ANOVA, Scheffe’s multiple comparisons test was used.\n***p<0.001\n-The authors used overexpression in cell lines to examine Slc22a17 localization. This is less than\nideal as it could introduce artifacts. Given that an antibody to Slc22a17 is available and\nused by the authors in this paper, why was this approach used?\nResponse #4-8:\nWe thank the reviewer for raising this important point. As shown in Fig. 5E and F, we have\nperformed localization studies using both endogenous and overexpression systems. Specifically, in\nFig. 5E, we examined the endogenous localization of Slc22a17 in primary cultured neurons using\nour validated Slc22a17 antibody, and observed that intracellular Slc22a17 was highly expressed. To\nfurther delineate its subcellular localization, we utilized an Slc22a17-GFP fusion construct in HT22\ncells and conducted live-cell imaging as shown in Fig. 5F. This approach revealed that Slc22a17\nlargely colocalized with ER-Tracker, suggesting its localization in the endoplasmic reticulum.\nWe have revised the manuscript to better describe our localization experiments as below (Results\nsection, Line 311-312):\n“Interestingly, we examined the endogenous localization of Slc22a17 in primary neurons,\nrevealing its predominant intracellular distribution (Fig. 5 E).”\n-Why was sex not evaluated in this study?\nResponse #4-9:\nThank you for raising this important point. In this study, we did examine survival rates and\nneurogenesis-related phenotypes separately in male and female mice. Our results showed no\nsignificant differences between sexes (see the Response Fig. 17 below). Therefore, we did not\nconsider sex as a factor in the analysis and included data from both sexes unless otherwise specified.\nsremiD-1CJ\nsremonoM-1CJ\negreM\nControl FAC\nWT cKO WT cKO\n5\n4\n3\n2\n1\nW K A A\nc F F\n+ +\nT O\nW K\nc\noitar\nneerG/deR\n1-CJ\n***\n***\n***\n***\nWT\ncKO_M Neurod1\n75 cKO_F\n50\n25\n0\n0 7 14 21\nResponse Fig. 17 No significant differences in neurogenesis were observed between male and female mice.\n(A) Survival curves of the WT, male cKO and female cKO mice. Most cKO mice died by P21 (n > 30 mice/group).\n(B) Representative photos showing immunostaining of Neurod1 in the DG of WT, male cKO and female cKO mice\nat P14. Scale bar, 50 μm.\n-This study would benefit greatly from a model figure in which the authors depict the proposed\nmechanism of action of Slc22a17 in hippocampal iron homeostasis at the cellular and organelle\nlevel.\nResponse #4-10:\nWe appreciate the reviewer’s suggestion. In response, we have included a schematic model\nillustrating the proposed role of Slc22a17 in hippocampal iron homeostasis at both the cellular and\nsubcellular levels, as shown in Extended Data Fig. 7I (previously Extended Data Fig. 7G). This\nmodel summarizes our current working hypothesis, incorporating our findings that Slc22a17 deletion\nin neural stem/progenitor cells leads to dysregulated intracellular iron handling, accumulation of\nnon-heme iron in neurons, and potential feedback mechanisms affecting systemic iron metabolism.\nExtended data Fig. 7 I Schematic summary of NSC Slc22a17 function in regulating hippocampal neurogenesis.\n-The authors found altered liver and spleen iron levels in their mutant mice (Extended Data Fig. 4C,\nD).\n)%\n(\nlavivrus\nnoitcarF\nA B\ncKO_M cKO_F\nPostnatal Days\nWere hepcidin levels changed in these mice?\nResponse #4-11:\nThank you for this constructive comment. We appreciate your insightful question regarding systemic\niron regulation. We measured serum hepcidin levels by ELISA in both WT and cKO mice and found\nthat hepcidin was significantly upregulated in the cKO group (Response Fig. 18). This increase in\nhepcidin likely accounts for the elevated iron content observed in the liver and spleen—two major\niron storage organs. These findings suggest that central nervous system alterations in our model may\ninfluence peripheral iron homeostasis.\nResponse Fig. 18 ELISA analysis revealed elevated hepcidin level in the serum of cKO mice (n = 3 mice/group).\nData are presented as mean ± SEM. Student’s t-test was used. *p<0.05.\nDid other organs have altered iron levels?\nResponse #4-12:\nThank the reviewer for this important question. To address this, we measured the iron levels in\nseveral peripheral organs, including the heart, kidney, and colon (Response Fig. 19). We found that\niron levels in the heart and kidney remained largely unchanged between WT and cKO mice.\nHowever, in the colon, iron content was elevated in cKO mice. We speculate that this may be also a\nconsequence of increased serum hepcidin levels, which can restrict iron export from colon. These\nfindings have now been shown in the figure below:\nResponse Fig. 19 Iron concentrations in the heart, kidney and colon of WT and cKO mice at P14 (n = 3\nmice/group). Data are presented as mean ± SEM. Student’s t-test was used. *p<0.05.\nWere there any changes in red blood cell parameters (e.g. hematocrit, hemoglobin, RBC count)?\nResponse #4-13:\nWe appreciate the reviewer’s suggestion. To address this point, we performed complete blood count\n(CBC) analyses in both WT and cKO mice at P14. CBC parameters were within the normal range for\nP14 mice (HCT 32–40%, Hb 10–13 g/dL, RBC 5.5–8.5 ×10⁶/µL, MCV 47–57 fL, MCH 15–18 pg,\nMCHC 31–34 g/dL). The results showed no significant differences in hematocrit, hemoglobin levels,\nRBC count, MCV, MCH, or MCHC between groups (see the Response Fig. 20 below), suggesting\nthat the observed tissue iron accumulation is not due to alterations in systemic erythropoiesis or red\nblood cell iron parameters.\nResponse Fig. 20 Complete blood count parameters in WT and cKO mice at P14 (n = 3 mice/group).\nData are presented as mean ± SEM. Student’s t-test was used.\nAlso, why do the authors think that liver and spleen iron levels change when Slc22a17 impacts\nhippocampal iron homeostasis? Could Slc22a17 expression in other cell types play a critical role? It\nis difficult to imagine a scenario where Slc22a17-dependent iron regulation in discrete regions in the\nbrain impact iron levels in other organs...\nResponse #4-14:\nWe sincerely thank the reviewer for this insightful comment. Indeed, this is a very important and\nthought-provoking question. After observing significant iron accumulation in the brain upon\nSlc22a17 deletion, we extended our analysis to peripheral tissues to assess potential systemic effects.\nSurprisingly, we found that iron levels were also markedly elevated in major iron storage organs\nsuch as the liver and spleen.\nGiven these findings, we carefully considered the possibility of potential Slc22a17 deletion outside\nthe central nervous system due to Nestin-Cre recombination leakage 8. To address this, we measured\nSlc22a17 mRNA levels in the liver and spleen of both WT and cKO mice. The results showed no\nsignificant differences between the two groups, and overall Slc22a17 expression in these peripheral\ntissues was substantially lower than that in the brain. These data suggest that the observed peripheral\niron accumulation is unlikely due to direct deletion of Slc22a17 in liver or spleen (see the Response\nFig. 21A and B below).\nTherefore, we hypothesize that the peripheral iron accumulation may result from a central-peripheral\nregulatory mechanism 9-11. The disruption of iron homeostasis in neural stem cells following\nSlc22a17 ablation may trigger a feedback response that alters hepatic iron metabolism, potentially\nthrough the modulation of hepcidin expression. Supporting this hypothesis, we found that hepatic\nHamp mRNA levels were significantly upregulated in cKO mice, and ELISA analysis further\nconfirmed elevated serum hepcidin levels (see the Response Fig. 21C and D below). These data\nprovide preliminary evidence for a possible central regulation of peripheral iron homeostasis\nmediated by Slc22a17. We acknowledge that the exact mechanisms underlying this\ncentral-peripheral crosstalk require further investigation, which we plan to address in our future\nstudies.\nThis point has been addressed in the Results section (Line 246-250) as follow:\n“In the liver and spleen—two primary storage organs for iron—only iron concentrations were\nsignificantly higher in cKO mice compared to WT mice (Extended Data Fig. 4, C and D) 14,\npotentially due to brain-specific Slc22a17 deletion indirectly enhancing hepatic hepcidin\nexpression and systemic iron accumulation via central-peripheral regulation.”\nResponse Fig. 21 Systemic iron accumulation may due to brain-specific Slc22a17 deletion indirectly\nenhancing hepatic hepcidin expression.\n(A) Western blot analysis of Slc22a17 levels in 12 organs and tissues of mice.\n(B) qPCR analysis showing similar Slc22a17 expression level in the liver and spleen of cKO mice compared to WT\nlittermates (n = 3 mice/group).\n(C) Increased Hamp mRNA level in the liver of cKO mice compared to WT littermates (n = 3 mice/group).\n(D) ELISA analysis revealed elevated hepcidin level in the serum of cKO mice. (n = 3 mice/group).\nData are presented as mean ± SEM. Student’s t-test was used. *p<0.05.\nReviewer #5 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part\nof the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nResponse #5:\nWe sincerely thank the reviewer for their involvement in co-reviewing the manuscript. We\nappreciate their valuable feedback.\nReference\nderived from human trisomic ipscs reveals the abnormalities during neural differentiation of down\nsyndrome. Front Mol Neurosci 16, 1137123, (2023).\n1179-1194 e1115, (2023).\nca1 neurons. J. Physiol. 590, 4917-4932, (2012).\nmediates apoptosis and iron uptake. Cell 123, 1293-1305, (2005).\nros/txnip/nlrp3/caspase-1 signaling pathway. Biomed. Pharmacother. 177, 116894, (2024).\nthrough psr-1 condensation. Nat. Commun. 16, 1079, (2025).\nimpaired performance in memory tasks and hyperactivity in mature and aged mice. Brain Res. 1701,\n103-111, (2018).\nnes-cre1 mediates highly efficient cre/loxp mediated recombination in the nervous system, kidney, and\nsomite-derived tissues. Genesis 44, 355-360, (2006).\nhypotransferrinemic mice. Brain Res. 912, 154-161, (2001).\n1934-1945, (2017).\nlipopolysaccharide up-regulates hepatic hepcidin expression by activating the il-6/jak2/stat3 pathway in\nmice. Front. Nutr. 8, 649640, (2021).\n(2018).\nChem Biol 4, 33-41, (2008).\nvalues and a genotype. Clin. Radiol. 76, 863 e811-863 e817, (2021).\ndeveloping memory systems. J Neurodev Disord 2, 133-143, (2010).\nthe perinatal rat brain. Pediatr. Res. 53, 800-807, (2003).\nneurodevelopmental outcomes. Nutrients 15, (2023).\nadult mouse increases brain endothelial uptake and blood-brain barrier transport of a high-affinity,\nanti-transferrin receptor antibody. bioRxiv, 2024.2012.2019.629470, (2024).\nferritin heavy chain. Cell Metab. 32, 259-272 e210, (2020).\nlearning in a mouse model of alzheimer's disease. Proc. Natl. Acad. Sci. U.S.A. 106, 16505-16510, (2009).\ndisease. Hum Mol Genet 26, 4823-4835, (2017).\ninternalization. Science 306, 2090-2093, (2004).\nand subsequent ferroptosis in the postischemic brain. Exp Mol Med 55, 2402-2416, (2023).\nferroportin 1 of microvascular endothelial cells. Cell Death Dis 13, 667, (2022).\nregulatory proteins irp1 and irp2 is mediated by feeding rhythms. Genome Biol. 25, 128, (2024).\nsignaling molecules in redox homeostasis. Trends Biochem Sci 50, 179-205, (2025).\nsequence motif at position -7007 of the fpn1 promoter. Haematologica 95, 1261-1268, (2010).\n(2025).\nPharmacol. 5, 176, (2014)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have addressed all of my concerns in this revised version of the manuscript.", "reviewer_2": "This is a revised manuscript titled \"Slc22a17 governs the postnatal neurogenesis by maintaining the iron homeostasis in hippocampus\" by Tao L. et al. The authors addressed my prior concerns and provided additional clarifying data. I have no additional major concerns and therefore recommend its acceptance for publication.\n\nMinor points:\n1. Fig.1L - Is it NMDAR-2A? or NMDA-2A?\n2. Lines 243-247 and 485-487 - Expand this important observation, especially in the context of hepcidin upregulation, and contextualize it with regard to AD/PD pathogenesis (in discussion) as it implicates that iron dyshomeostasis in the CNS can lead to abnormal iron accumulation in the peripheral tissues. For example, can this be translated into a potential peripheral bioindicator for the inception of iron-overload associated neuropathology?\n3. Lines 251-252 - Add clarification for the reduced Calcein's fluorescence due to Fe-sequestration/chelation as similar to lines 302-303. This is the first report of its use in this context.\n4. Lines 340-341 - It is unclear if there is a cooperative roles for SLC22A17 and FPN as the blue and yellow bars do not appear to be significantly different in extended figure 5F.", "reviewer_3": "The Authors have convicingly demonstrated decreased ferroportin protein levels in cKO hipocampus at P14. However, the mechanism of this reduction is not as obvious as the Authors suggest. First, in accordance with the logic of the IRP/IRE regulation, in iron rich cells IRP2 is degraded (as shown in the Figure) and IRP1 is in a holo-[4Fe-4S] form. In consequence, Fpn protein level should be elevated as in the case of H- and L-ferritin (in both ferritin transcripts and Fpn one the IRE loop is found in their 5’UTRs). The potential influence of increased hepcidin in astrocytes on the down-regulation of Fpn is largely debatable. We really do not know whether hepcidin synthesized in astrocytes may affect in a paracrine way Fpn in hippocampus. Such local autonomous regulation has been only described for heart (Lakhal-Littleton et al., 2016) and kidney (Mohammad et al., 2021).\n\nRegarding IRP1, an Electrophoretic Mobility Shift Assay (using IRE probe and hippocampal cytoplasmic extracts) would be much more appropriate than WB to visualise IRP1-IRE interaction. WB analysis is not informative in this case.", "reviewer_4": "Dear authors\nYou have done an impressive amount of work addressing the issues raised by reviewers! All of my comments have been addressed except for one issue related to hepcidin. Please move hepcidin levels to one of the main figures, given that hepcidin is a key systemic regulator of iron homeostasis. Also, I would ask that you revise your interpretation and discussion of hepcidin and its impact. In your paper, you state: \"In the liver and spleen—two primary storage organs for iron—only iron concentrations were significantly higher in cKO mice compared to WT mice (Extended Data Fig. 4, C and D) 40, potentially due to brain-specific Slc22a17 deletion indirectly enhancing hepatic hepcidin expression and systemic iron accumulation via central-peripheral regulation.\" Increased hepcidin expression would lead to decreased systemic iron levels, yet you observe increased tissue iron levels. Therefore, if hepcidin is relevant to the phenotype of your mice, it is more likely that brain Slc22a17 deletion indirectly causes increased liver iron levels and then the liver responds physiologically by increasing hepcidin levels.", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Point-by-Point Responses\nThank the reviewers very much for their great efforts and very constructive comments on our\nmanuscript. We have carefully revised the manuscript according to the reviewers’ comments (with\ntext changes highlighted in Bold). Our point-by-point responses are summarized below. Each\noriginal comment is presented, followed by our “Response”.\nReviewer #1 (Remarks to the Author)\nThe authors have addressed all of my concerns in this revised version of the manuscript.\nResponse #1:\nWe greatly thank the reviewer for your positive feedback. We are glad to hear that the revised\nversion of the manuscript has addressed all of your concerns.\nReviewer #2 (Remarks to the Author)\nThis is a revised manuscript titled \"Slc22a17 governs the postnatal neurogenesis by maintaining the\niron homeostasis in hippocampus\" by Tao L. et al. The authors addressed my prior concerns and\nprovided additional clarifying data. I have no additional major concerns and therefore recommend its\nacceptance for publication.\nResponse #2:\nThank the reviewer for the thoughtful review and for recommending our manuscript for publication.\nMinor points:\n1. Fig.1L - Is it NMDAR-2A? or NMDA-2A?\nResponse #2-1:\nWe apologize for the confusion. We have corrected the labeling in both Fig. 1L and Fig. S1J to\n\"NMDAR2A\" as suggested. Thank the reviewer for pointing this out.\nFig. 1 L Western blotting results showing synaptic components changes in the hippocampus of WT and cKO mice\nat P14. Syn, Synapsin1.\n2. Lines 243-247 and 485-487 - Expand this important observation, especially in the context of\nhepcidin upregulation, and contextualize it with regard to AD/PD pathogenesis (in discussion) as it\nimplicates that iron dyshomeostasis in the CNS can lead to abnormal iron accumulation in the\nperipheral tissues. For example, can this be translated into a potential peripheral bioindicator for the\ninception of iron-overload associated neuropathology?\nResponse #2-2:\nThank the reviewer very much for this insightful suggestion. We have expanded the discussion (Line\n477-488) about brain-specific Slc22a17 deletion indirectly causing increased hepcidin expression,\nwhich in turn leads to iron accumulation in peripheral organs. This observation aligns with iron\ndysregulation seen in neurodegenerative diseases like Alzheimer’s and Parkinson’s, where brain iron\nimbalance may contribute to peripheral iron overload and altered serum hepcidin levels. This could\npotentially serve as a biomarker for iron-overload related neuropathology. We will continue to\ninvestigate the central-peripheral iron axis mediated by Slc22a17 in future studies, which may offer\nvaluable insights for early diagnosis of neurodegenerative diseases.\n“Additionally, we observed that brain-specific deletion of Slc22a17 led to iron dysregulation,\nwhich may indirectly enhance hepatic hepcidin expression and cause iron accumulation in\nperipheral organs. This phenomenon is reminiscent of the iron dysregulation observed in\nneurodegenerative diseases like Alzheimer's and Parkinson’s disease, where central iron\nimbalance may drive peripheral iron accumulation and alter hepcidin expression. For example,\na study has reported that participants with a higher amyloid-beta load show significantly\nelevated serum hepcidin levels 1. Taken together, these findings suggest that Slc22a17 may\nfunction as a key regulator of the central-peripheral iron axis, responding to both cellular and\nextracellular iron levels to maintain iron balance and redox homeostasis. Further studies on\nSlc22a17 in the central nervous system could provide valuable insights into the mechanisms of\ncentral-peripheral iron metabolism, which may ultimately aid in the early diagnosis of\nneurodegenerative diseases.”\n3. Lines 251-252 - Add clarification for the reduced Calcein's fluorescence due to\nFe-sequestration/chelation as similar to lines 302-303. This is the first report of its use in this\ncontext.\nResponse #2-3:\nWe thank the reviewer for the suggestion. We have clarified the reduced Calcein fluorescence due to\nFe-sequestration/chelation in Line 247-248.\n“To confirm this, we utilized Perl’s staining to visualize hippocampal iron accumulation in cKO\nmice and employed the iron-sensitive probes FerroOrange and Calcein to demonstrate elevated\ncellular iron levels in cKO neurospheres (Fig. 4 E and F), where the green fluorescence of Calcein\nis quenched by iron, allowing for the detection of increased cellular iron.”\n4. Lines 340-341 - It is unclear if there is a cooperative role for SLC22A17 and FPN as the blue and\nyellow bars do not appear to be significantly different in extended figure 5F.\nResponse #2-4:\nWe thank the reviewer for this helpful comment. We agree that our original wording regarding the\ncooperative role of SLC22A17 and FPN was not sufficiently precise. We observed that there was no\nsignificant difference between the siSLC22A17 and siSLC40A1 groups at 4h or 24h time point,\nwhereas a significant difference was found between the siSLC22A17 and dual knockdown groups.\nThis suggests a cooperative role for SLC22A17 and FPN in iron efflux. However, as pointed out by\nthe reviewer, no significant difference was observed between the siSLC40A1 and dual knockdown\ngroups. In light of this, we have revised the original sentence as below (Line 335-336):\n“Knockdown of SLC40A1 significantly reduced iron efflux, while SLC22A17 knockdown also\nimpaired iron export, particularly at later time points. Dual knockdown of both genes further\nblocked iron efflux compared to siSLC22A17 group, suggesting the cooperative role of FPN in\nthe SLC22A17-mediated iron efflux mechanism.”\nReviewer #3 (Remarks to the Author)\nThe Authors have convincingly demonstrated decreased ferroportin protein levels in cKO\nhipocampus at P14. However, the mechanism of this reduction is not as obvious as the Authors\nsuggest. First, in accordance with the logic of the IRP/IRE regulation, in iron rich cells IRP2 is\ndegraded (as shown in the Figure) and IRP1 is in a holo-[4Fe-4S] form. In consequence, Fpn protein\nlevel should be elevated as in the case of H- and L-ferritin (in both ferritin transcripts and Fpn one\nthe IRE loop is found in their 5’UTRs). The potential influence of increased hepcidin in astrocytes\non the down-regulation of Fpn is largely debatable. We really do not know whether hepcidin\nsynthesized in astrocytes may affect in a paracrine way Fpn in hippocampus. Such local autonomous\nregulation has been only described for heart (Lakhal-Littleton et al., 2016) and kidney (Mohammad\net al., 2021).\nRegarding IRP1, an Electrophoretic Mobility Shift Assay (using IRE probe and hippocampal\ncytoplasmic extracts) would be much more appropriate than WB to visualise IRP1-IRE interaction.\nWB analysis is not informative in this case.\nResponse #3:\nThank you for your thoughtful comments. We agree that, in the classical IRP/IRE model, an increase\nin cellular iron levels typically leads to elevated Fpn expression. However, in certain conditions,\nparticularly in the context of astrocytes and hepcidin, the regulation of Fpn may deviate from this\nmodel, and further investigation is necessary to better understand these mechanisms.\nRegarding your query about whether hepcidin synthesized in astrocytes can influence Fpn expression\nin a paracrine manner, previous studies have demonstrated paracrine effects of hepcidin on iron\nmetabolism in organs such as the heart and kidney 2. Furthermore, there is evidence that\nastrocyte-secreted hepcidin can regulate iron uptake across the blood-brain barrier, and\noverexpression of hepcidin in astrocytes leads to the degradation of Fpn on brain microvascular\nendothelial cells 3,4. Although direct evidence supporting a similar role for hepcidin in astrocytes\naffecting hippocampal Fpn levels is currently lacking, these findings provide a basis for\nhypothesizing that astrocyte-derived hepcidin may indeed exert a paracrine effect on neighboring\ncells, including those in the hippocampus, particularly when iron homeostasis is disrupted.\nIn addition, we sincerely thank the reviewer for this valuable suggestion and performed an\nElectrophoretic Mobility Shift Assay (EMSA) using a biotin-labeled IRE probe and hippocampal\ncytoplasmic extracts. Consistent with our previous WB results, we observed a reduced binding signal\nto the IRE element in cKO mice compared to controls, indicating decreased IRE-binding activity in\nthe absence of Slc22a17. We further carried out a supershift assay by incubating the reaction with an\nIRP1-specific antibody to confirm the identity of the binding protein. However, no clear supershifted\nband was detected, which we suspect may be due to suboptimal antibody performance under native\nEMSA conditions. We will continue to optimize the supershift experiment to clarify the specific\ncontribution of IRP1 to the observed binding complex. We greatly appreciate the reviewer’s\ninsightful recommendation, which has helped us strengthen our experimental approach.\nResponse Fig. 1 Electrophoretic Mobility Shift Assay (EMSA) showing reduced IRE-binding activity in\nhippocampal cytoplasmic extracts from cKO mice compared to controls, with no detectable supershift upon\naddition of IRP1 antibody.\nReviewer #4 (Remarks to the Author)\nDear authors\nYou have done an impressive amount of work addressing the issues raised by reviewers! All of my\ncomments have been addressed except for one issue related to hepcidin. Please move hepcidin levels\nto one of the main figures, given that hepcidin is a key systemic regulator of iron homeostasis. Also,\nI would ask that you revise your interpretation and discussion of hepcidin and its impact. In your\npaper, you state: \"In the liver and spleen—two primary storage organs for iron—only iron\nconcentrations were significantly higher in cKO mice compared to WT mice (Fig. S4, C and D) 40,\npotentially due to brain-specific Slc22a17 deletion indirectly enhancing hepatic hepcidin expression\nand systemic iron accumulation via central-peripheral regulation.\" Increased hepcidin expression\nwould lead to decreased systemic iron levels, yet you observe increased tissue iron levels. Therefore,\nif hepcidin is relevant to the phenotype of your mice, it is more likely that brain Slc22a17 deletion\nindirectly causes increased liver iron levels and then the liver responds physiologically by increasing\nhepcidin levels.\nResponse #4:\nWe thank the reviewer for the valuable comment and for pointing out the discrepancy in our\ninterpretation of hepcidin's role. We have revised the manuscript based on the reviewer’s suggestion\nand included the results on hepcidin upregulation in Fig. S4E.\nWe agree that increased hepcidin expression leads to decreased systemic iron levels due to its effects\non iron efflux. However, we would like to clarify that increased hepcidin levels in the liver can also\nlead to an increase in tissue iron levels, as hepcidin reduces iron export by downregulating\nferroportin, the iron exporter 5. This mechanism is consistent with our findings of elevated iron levels\nin both the liver and spleen of cKO mice. In addition, we acknowledge that the reviewer’s proposed\nhypothesis is also feasible: brain-specific Slc22a17 deletion could result in increased liver iron\naccumulation, which may subsequently trigger a compensatory increase in hepatic hepcidin\nexpression. We have now revised the manuscript (Line 234-241) as below to offer a more\ncomprehensive interpretation of the results and we will continue to explore the underlying\nmechanisms in future studies.\nWe once again thank the reviewer for their thoughtful and constructive suggestions.\n“In the liver and spleen—two primary storage organs for iron—only iron concentrations were\nsignificantly higher in cKO mice compared to WT mice (Fig. S4 C and D), potentially due to\nbrain-specific Slc22a17 deletion indirectly causing tissue iron accumulation via\ncentral-peripheral regulation. We further observed increased hepatic hepcidin expression and\nelevated serum hepcidin levels in cKO mice (Fig. S4 E). These changes in hepatic hepcidin\ncould impair iron export, leading to increased tissue iron levels, which may contribute to the\nelevated liver iron content, or alternatively, may result from the increased liver iron levels.”\nFig. S4 E Left: Increased Hamp mRNA level in the liver of cKO mice compared to WT littermates. Right: ELISA\nanalysis revealed elevated hepcidin level in the serum of cKO mice (n=3). Statistical significance was determined\nby using Student’s t-test. Data are presented as mean ± SEM.\nReviewer #5 (Remarks to the Author)\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part\nof the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nResponse #5:\nWe greatly thank the reviewer for your positive feedback.\nReference\namyloid-beta load. J. Alzheimers Dis. 76, 291-301, (2020).\n5, (2016).\noxidative stress in app/ps1 mice. Free Radic. Biol. Med. 158, 84-95, (2020).\namyloid-beta induced brain damage in mice. Cell Death Discov 6, 113, (2020).\ndisease: A review. Medicine (Baltimore) 102, e33225, (2023)."}]

Decision letter