ᴅ-serine suppresses one-carbon metabolism by competing with mitochondrial ʟ-serine transport

Reviewer #1 (Public review):

Summary:

The authors demonstrate the stereoselective role of D-serine in 1C metabolism showing that D-serine competes with L-serine and inhibits mitochondrial L-serine transport. They observe expression of 1C metabolites in their metabolomics approach in primary cortical neurons treated with L-serine, D-serine and mixture of both. Their conclusions are based on the reduction in levels of glycine, polyamines and their intermediates and formate. Single cell RNA sequencing of N2a cells showed that cells treated with D-serine enhanced expression of genes associated with mitochondrial functions such as respiratory chain complex assembly and mitochondrial functions with downregulation of genes related to amino acid transport, cellular growth and neuron projection extension. Their work demonstrates that D-serine inhibits tumor cell proliferation and induces apoptosis in neural progenitor cells highlighting the importance of D-serine in neurodevelopment.

Strengths:

D-amino acids do not merely function as ligands at receptors but have underlying roles in signaling and metabolism. These roles are just beginning to be uncovered. The authors elucidate the metabolic role of D-serine in the context of neuronal maturation by its suppression of mitochondrial L-serine availability for SHMT2 and 1C flux. This is the strength of the manuscript. The implications for the metabolic role of D-serine in neurons is a highlight and underlines its roles in neuronal metabolism.

Weaknesses:

These are some minor issues that come up on critical assessment of the manuscript and is only intended to strengthen the manuscript. The comments below are based on the revisions made by the authors including the justification of their approach and rebuttal.

(1) Kinetic assessment of D-serine versus L-serine: The authors have made reference to prior work by Miyamoto et al. and justify their rationale. This is acceptable.

(2) Molecular Dynamics simulations while a good first step in modeling interactions at the active site, relies on force fields. The authors state that any elaborate study into longer simulations is beyond the scope and their simulations data are supported by other experimental work. This is justified.

(3) The use of N2a cell line is also justified to reflect the proliferative nature of immature neurons.

(4) With regards to caspase 3 comment, the whole blot is convincing and shows cleaved caspase-3 band at approx. 15 kDa.

(5) Scale Bars are clearly visible and Fig S6 which was earlier S5 is legible. If possible, the authors can include an magnified inset in the merged image to show the clear activation of caspase-3.

(6) Issue of phosphatidyl serine standard in LC-MS is justified by the use of L-serine standard due to lack of availability.

(7) The authors mention about enantiomeric shift of serine metabolism during neural development which appears to be a discussion of prior published data from Hubbard et al 2013, Burk et al 2020, and Bella et al 2021 in Supplementary Figure panels 8 A-E.
The authors justify by citing references to the work which may be acceptable and also the current norms of publication. This reviewer felt contrary to the fact, however it is left to the editors to make a decision on this.

(8) The discussion section has been substantially revised and now reads well.

(9) The relevant references have been cited. In doing so, the work integrates and elucidates a mechanistic and functional role of D-serine in neurons.

(10) Figure S7A in the revised manuscript shows the specificity of D-serine in the cleaved caspase-3 assay which is informative.

Comments on revised version.

This reviewer is satisfied by the effort made by the authors based on the prior comments raised.

Reviewer #2 (Public review):

Summary:

This study by Suzuki et al. reports an interesting stereo-selective role of D-serine in regulating one-carbon metabolism during neurodevelopment to adapt the functional transition, probably through the competition with mitochondrial transport of L-serine. The authors provide a multi-layered set of evidence, including metabolomics, enzyme assays, mitochondrial transport competition and functional assays in immature/neural progenitor cells, to build up a conceptual integration of D-serine as both a neurotransmitter and a metabolic regulator in central neural system, which raises a broad potential interest to the neuroscience and metabolism communities.

Strengths:

This work provides a conceptual advance that D-serine is not only serves as a traditional neurotransmitter in central neural system but also critically contributes to metabolic regulation of neural cells. The authors performed solid metabolomic assays to validate the suppressive effect of D-serine on one-carbon metabolic pathway, providing some evidence that D-serine competitively inhibits mitochondrial serine transport, but not directly impairs SHMT2 enzymatic activity. All these data indicate a critical role of D-serine synthesis during neural maturation and suggest a potential translational strategy for targeting serine metabolism in neural tumors.

Comments on revised version.

My previous concerns have been appropriately addressed or discussed in this revised version of manuscript. I have to say that, at this stage, I have no further questions.

Reviewer #3 (Public review):

Summary:

This manuscript presents a comprehensive and well-executed investigation into the metabolic role of D-serine in the central nervous system. The authors provide solid evidence that D-serine competitively inhibits mitochondrial L-serine transport, thereby impairing one-carbon metabolism. This stereoselective mechanism reduces glycine and formate production, suppresses cellular proliferation, and induces apoptosis in immature neural cells and glioblastoma stem cells. Developmental analyses further reveal a physiological enantiomeric shift in serine metabolism during neurogenesis, aligning with the transition from proliferation to maturation. Overall, the study bridges developmental neurobiology, cancer metabolism, and amino acid transport, uncovering a previously unrecognized metabolic function of D-serine beyond its role in neurotransmission.

Strengths:

(1) The discovery that D-serine inhibits one-carbon metabolism by competing for mitochondrial L-serine transport-rather than through enzymatic inhibition or receptor-mediated signaling-represents a significant and previously underappreciated mechanism. This finding has broad implications for understanding metabolic regulation during neurodevelopment and offers potential relevance for targeting metabolic vulnerabilities in cancer.

(2) The authors integrate metabolomics, mitochondrial transport assays, molecular dynamics simulations, genetic and pharmacologic perturbations, transcriptomics, and both in vitro and ex vivo models. The breadth of experimental approaches, combined with the coherence of the findings across systems, provides strong support for the central conclusions and enhances the overall impact of the study.

(3) The temporal shift in D-/L-serine levels during neurodevelopment is elegantly linked to the transition from proliferative to mature neuronal states. The selective vulnerability of neural progenitors and tumor cells-contrasted with the resistance of mature neurons-highlights a biologically meaningful and potentially targetable metabolic distinction.

Weaknesses:

(1) While the authors attribute D-serine's metabolic effects to competition with mitochondrial L-serine transport, the specific identity of the transporter(s) mediating this process remains undefined. This represents a meaningful mechanistic gap, as the central conclusion depends on D-serine limiting mitochondrial L-serine availability to inhibit one-carbon metabolism.

(2) The effective concentrations of D-serine used in vitro (IC₅₀ ≈ 1-2 mM) exceed typical brain levels (~0.3 mM). While the authors acknowledge this, a more focused discussion on whether higher local D-serine concentrations could arise in specific microenvironments-such as synaptic compartments, tumor niches, or pathological states-would help contextualize the in vitro findings and strengthen their physiological relevance. For example, disruptions in D-serine clearance or altered expression of serine racemase and transporters in disease contexts could lead to localized accumulation. Moreover, differences between extracellular and intracellular D-serine pools-and the mechanisms governing their regulation-may further influence its metabolic impact in vivo.

(3) While the manuscript focuses on neural stem/progenitor cells and neural tumors, it remains unclear whether the anti-proliferative effects of D-serine are specific to neural lineages or extend to other highly proliferative non-neural cell types. A brief discussion addressing this point would help clarify the scope of D-serine's metabolic impact and whether its mechanism of action reflects a unique vulnerability in neural cells or a more general feature of proliferative metabolism. This distinction is particularly relevant for assessing the broader therapeutic potential of targeting mitochondrial L-serine transport.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

Summary:

The authors demonstrate the stereoselective role of D-serine in 1C metabolism, showing that D-serine competes with L-serine and inhibits mitochondrial L-serine transport. They observe expression of 1C metabolites in their metabolomics approach in primary cortical neurons treated with L-serine, D-serine, and a mixture of both. Their conclusions are based on the reduction in levels of glycine, polyamines, and their intermediates and formate. Single-cell RNA sequencing of N2a cells showed that cells treated with D-serine enhanced expression of genes associated with mitochondrial functions, such as respiratory chain complex assembly, and mitochondrial functions, with downregulation of genes related to amino acid transport, cellular growth, and neuron projection extension. Their work demonstrates that D-serine inhibits tumor cell proliferation and induces apoptosis in neural progenitor cells, highlighting the importance of D-serine in neurodevelopment.

Strengths:

D-amino acids are a marvel of nature. It is fascinating that nature decided to make two versions of the same molecule, in this case, an amino acid. While the L-stereoisomer plays well-known roles in biology, the D-stereoisomer seems to function in obscurity. Research into these novel signaling molecules is gathering momentum, with newer stereoisomers being discovered. D-serine has been the most well-studied among the different stereoisomers, and we still continue to learn about this novel neurotransmitter. The roles of these molecules in the context of metabolism is not well studied. The authors aim to elucidate the metabolic role of D-serine in the context of neuronal maturation with implications for 1C metabolism and in cell proliferation. The metabolic role of these molecules is just beginning to be uncovered, especially in the context of mammalian biology. This is the strength of the manuscript. The authors have done important work in prior publications elucidating the role of D-amino acids. The advancement of the field of D-amino acids in mammalian biology is significant, as not much is known. The presentation of RNA seq data is a valuable resource to the community, however, with caveats as mentioned below.

Weaknesses:

The following are some of the issues that come out in a critical reading of the manuscript. Addressing these would only strengthen and clarify the work.

(1) Kinetic assessment of D-serine versus L-serine: While the authors mention that D-serine is not a good substrate for SHMT2 compared to L-serine, the kinetic data are presented for only D-serine. In a substrate comparison with an enzyme, data must be presented for L-serine as well to make the conclusion about substrate specificity and affinity. Since the authors talk about one versus another substrate, there needs to be a kinetic comparison of both with Km (affinity). (Ref Figure 2 panel).

We agree with the reviewer that kinetic parameters for l-serine are important for evaluating the substrate specificity of SHMT2. The hydroxymethyl-transferase activity of SHMT2 toward l-serine has been previously characterized by our co-author Tetsuya Miyamoto (Miyamoto et al., FEBS Journal, 2024; PMID: 37700610), which is appropriately cited in the manuscript (line 143). In that study, the kinetic parameters for l-serine were determined, with a Km of 0.07 ± 0.009 mM and a Kcat of 33.5 ± 0.9 min^-1. The strong chiral selectivity of SHMT2 for the l-enantiomer in the hydroxymethyl-transferase reaction was also demonstrated in that work. On the other hand, the primary aim of the present study is different from characterizing d-serine as a catalytic substrate for SHMT2. Rather, our goal was to determine whether d-serine interferes with the hydroxymethyl-transferase reaction of SHMT2 by interacting with the l-serine binding site. Accordingly, the analyses shown in Fig. 2B-D were designed to evaluate whether d-serine could structurally occupy or interfere with the l-serine binding pocket of SHMT2. Therefore, our experiments focused on assessing the potential inhibitory effect of d-serine rather than performing a full kinetic comparison of d-serine and l-serine as substrates.

(2) Molecular Dynamics simulations, while a good first step in modeling interactions at the active site, rely on force fields. These force fields are approximations and do not represent all interactions occurring in the natural world. Setting up the initial conditions in the simulations can impact the final results in non-equilibrium scenarios. The basic question here is this: Is the simulated trajectory long enough so that the system reaches thermodynamic equilibrium and the measured properties converge? Prior studies have shown mixed results with the conclusion that properties of biological systems tend to converge in multi-second trajectories (not nanosecond scales as reported by the authors) and transition rates to low probability conformations require more time. (Ref Figure 2C).

We thank the reviewer for raising the important point regarding the limitations of molecular dynamics (MD) simulations, including the dependence on force fields and the potential effects of simulation length and initial conditions. We agree that MD simulations represent approximations of molecular behavior and that longer trajectories may be required to fully explore rare conformational states in biological systems.

In the present study, however, the MD simulations were not intended to provide a comprehensive thermodynamic description of SHMT2 conformational dynamics. Rather, they were used as a structural assessment to evaluate whether d-serine could plausibly occupy the canonical l-serine binding site of SHMT2. As shown in Fig. 2BC and supplementary movie 1, the simulations did not support stable occupation of the l-serine binding pocket by d-serine. Importantly, this structural observation is consistent with our biochemical data showing that d-serine does not inhibit the hydroxymethyl-transferase activity of SHMT2 when l-serine is used as the substrate (Fig. 2D). Together, these results indicate that the inhibitory effect of d-serine on one-carbon metabolism is unlikely to be mediated through direct inhibition of SHMT2.

As the reviewer correctly notes, it remains possible that d-serine interacts with SHMT2 at sites distinct from the canonical l-serine binding pocket and could exert potential allosteric effects. Indeed, previous work by Miyamoto et al. (FEBS Journal, 2024) demonstrated that SHMT2 exhibits dehydratase activity toward d-serine. However, this reaction is not directly linked to mitochondrial one-carbon metabolism. Therefore, further extensive simulations exploring alternative conformational states or potential allosteric interactions would extend beyond the scope of the present study.

Importantly, the key conclusions of this study do not rely solely on MD simulations but are supported by multiple independent experimental approaches, including metabolomics, enzymatic assays, and mitochondrial transport analyses.

(3) The authors use N2a cell line to demonstrate D-serine burden on primary cortical neurons. N2a is an immortalized cell line, and its properties are very different from primary neurons. The authors need to mention a rationale for the use of an immortalized cell line versus primary neurons. The transcriptomic profile of an immortalized cell line is different compared to a primary cell. Hence, the response to D-serine may vary between the two different cell types.

We thank the reviewer for raising this important point regarding the differences between immortalized cell lines and primary neurons. As the reviewer notes, N2a cells and primary cortical neurons (PCNs) differ in several aspects, including their degree of differentiation and proliferative capacity. We appreciate the opportunity to clarify the rationale for using both systems in this study.

One-carbon metabolism is known to be particularly active in highly proliferative or relatively undifferentiated cells. Primary cortical neurons are initially obtained as immature neuronal populations and gradually undergo maturation during culture (Fig. S6). In our experiments, we observed that sensitivity to d-serine and dependence on one-carbon metabolism were primarily evident in immature neuronal states rather than in fully mature neurons (Fig. 4EF).

In this context, immature PCNs share certain metabolic characteristics with proliferative neural cell lines such as N2a cells. Consistent with this idea, the inhibitory effects of d-serine on one-carbon metabolism and cell proliferation were observed in both immature PCNs and N2a cells (Fig. 1E–G, Fig. 2E, Fig. 3AB, and Fig. 4F). Thus, the use of N2a cells provides a complementary experimental model for studying the metabolic vulnerability of immature neural cells that depend on one-carbon metabolism. Importantly, the key findings were consistently reproduced in primary cortical neurons, supporting the physiological relevance of the observations made in N2a cells. For clarity, we added descriptions in lines 107-108 and 167-168 in our revised manuscript.

(4) In Figure 4D, the authors mention that D-serine activates the cleavage of caspase 3. Figure 4D shows only cleaved caspase 3 as a single band. They need to show the full blot that contains the cleaved fragments along with the major caspase 3 band.

In our experiments, we used an antibody that specifically recognizes cleaved caspase-3 and does not recognize full-length caspase-3 (Cell Signaling Technology, anti-cleaved caspase-3 antibody, clone 5A1E). Therefore, the Western blot detects only the cleaved caspase-3 fragment at approximately 17 kDa, which appears as a single band in the blot (please see Author response image 1). For clarity, we have also included the antibody information in the Western blot section in the revised Materials and Methods (lines 501-502).

Author response image 1.

An original image of western blot for Fig. 4D. An arrow indicates the bands of cleaved caspase-3 (17 kDa).

(5) In Figure panel 4, the authors use neural progenitor cells (NPCs). They need to demonstrate that the population they are working with is NPCs and not primary neurons. There must be a figure panel staining for NPC markers like SOX2 and PAX6. Also, Figure S5 needs to be properly labeled. It is confusing from the legend what panels B-E refer to? Also, scale bars are not indicated.

We thank the reviewer for pointing out these issues. First, we have relabeled and rearranged the figure panels in revised Figure S6B-E, and revised the figure legend to provide a clearer description of each panel. We have also added scale bars to the revised images.

To confirm the identity of neural progenitor cells (NPCs), we performed immunostaining for Nestin, a well-established marker for NPCs, instead of Sox2 and Pax6 (Fig. S6B). Nestin is widely used as a marker for NPCs(Bernal and Arranz, 2018; Bott et al., 2019; Lendahl et al., 1990), and is known to be co-expressed with Sox2 in the mouse embryonic brain(Graham et al., 2003). In addition, Nestin has been identified as a Pax6-bound gene associated with the transcriptional program regulating neural progenitor identity (Thakurela et al., 2016). Consistent with these observations, analysis of published scRNA-seq data from the developing mouse brain (Bella et al., 2021) shows that the RNA expression profile of Nestin (Nes) closely parallels those of Sox2 and Pax6 (new Fig. S9C). Based on these lines of evidence, we consider Nestin-positive cells in our cultures to represent NPCs. Importantly, Nestin-positive cells were co-stained with cleaved caspase-3, suggesting that the apoptotic population corresponds to NPCs (Fig. S6B). Together, these observations support that the apoptotic cells observe in our culture correspond to NPCs rather than differentiated neurons.

(6) In Supplementary Figure panel 7F, the authors mention phosphatidyl L-serine and phosphatidyl D-serine. A chromatogram of the two species would clarify their presence as they used 2D-HPLC. On an MS platform, these 2 species are not distinguishable. Including a chromatogram of the 2 species would be helpful to the readers.

We thank the reviewer for this helpful suggestion. As the reviewer correctly noted, mass spectrometry alone cannot distinguish phosphatidyl-d-serine and phosphatidyl-l-serine. To quantify these species separately, lipids were first extracted from cells using the Bligh and Dyer method, followed by phospholipase D treatment to cleave the serine moiety from phosphatidylserine (a schematic of the procedure is shown in Fig. S8D). The released serine was then derivatized with NBD-F and analyzed by 2D-HPLC for enantioselective separation and quantification of d- and l-serine, as described in the Materials and Methods section (“Quantification of glycine and serine enantiomers”). Phosphatidyl-l-serine (Sigma-Aldrich: P0474) was used to generate a standard curve for quantification (Fig. S8E). Because phosphatidyl-d-serine is not commercially available, and because the peak height of free d-serine is equivalent to that of free l-serine in the chromatograms of our 2D-HPLC system, the same standard curve was used to estimate phosphatidyl-d-serine levels.

As requested by the reviewer, we have now added representative chromatograms of d- and l-serine derived from phosphatidyl-serine in NPC samples (new Fig. S8F).

(7) The authors mention about enantiomeric shift of serine metabolism during neural development, which appears to be a discussion of prior published data from Hubbard et al, 2013, Burk et al, 2020, and Bella et al, 2021, in Supplementary Figure panels 8 A-E. This should not be presented as a figure panel, as it gives the false impression that the authors have performed the experiment, which is clearly not the case. However, its discussion can well serve as part of the manuscript in the discussion section.

We appreciate this helpful suggestion. The datasets used in Fig. 4K and Fig. S9 were derived from previously published transcriptomic studies (Hubbard et al, 2013; Burk et al, 2020; Bella et al, 2021). While these studies reported transcriptomic profiles during neuronal development in vitro or in vivo, they did not specifically analyze serine metabolism, one-carbon metabolism, or d-serine biosynthesis, which are the focus of the present study. Therefore, we reanalyzed these publicly available datasets from a metabolic perspective, focusing on genes involved in serine metabolism and one-carbon metabolism. This re-analysis allowed us to examine a developmental shift in serine enantiomer metabolism, we presented the results as figure panels rather than simply citing the datasets in the Discussion. Re-analysis of publicly available transcriptomic datasets to address new biological questions has become a common approach in genomics and transcriptomics studies.

To avoid the impression that these experiments were performed in this study, we have clearly indicated the original references and clarified this point in the figure legends (Fig. 4K and Fig. S9). These panels are intended to provide supportive evidence for the developmental shift in serine enantiomer metabolism discussed in this study.

(8) The entire presentation of the section on enantiomeric shift of serine metabolism during neural development (lines 274-312) is a discussion and should be part of the discussion section and not in the results section. This is misleading.

We thank the reviewer for this comment. This point overlaps with the concern raised in comment 7. Please see our response to comment 7 for a detailed explanation and the revisions made in the manuscript.

(9) The discussion section is not well written. There is no mention of recent work related to D-serine that has a direct bearing on its metabolic properties. In the discussion section, paragraph 1, the authors mention that their work demonstrates the selective synthesis of D-serine in mature neurons as opposed to neural progenitor cells. This concept has been referred to in prior publications:

(a) Spatiotemporal relationships among D-serine, serine racemase, and D-amino acid oxidase during mouse postnatal development. PMID:14531937.

(b) D-cysteine is an endogenous regulator of neural progenitor cell dynamics in the mammalian brain. PMID:34556581.

We thank the reviewer for this helpful suggestion and for drawing our attention to these studies. We have revised the Discussion to better place our findings in the context of previous work related to d-serine.

Specifically, we have added references describing the spatiotemporal relationship between d-serine and serine racemase (Srr) during brain development (PMIDs 14531937 and 33592203) (line 333). These studies highlighted the tissue-level (PMID 14531937) and cellular-level (PMID: 33592203) relationship between Srr expression and development. These studies highlighted the role of d-serine in supporting the functional maturation of neurons during postnatal development. In contrast, our study addresses a complementary question of why d-serine is NOT present during embryonic and early postnatal stages of brain development, when proliferative metabolic activity is high. This question is fundamentally different from the previous reports. Our point is that d-serine is not favorable because it interferes with one-carbon metabolism, which is essential for cell proliferation. Therefore, this concept has not been referred to in prior publications. To clarify this point, we added the following sentence to the Discussion (line 325-328): “In addition to the known role of d-serine in the functional maturation of differentiated neurons, our findings highlight a previously unrecognized, stereoselective regulation of cellular metabolism by d-serine, and provide a rationale for its selective synthesis in mature neurons where proliferative metabolic activity is no longer required’.

We also appreciate the reviewer bringing our attention to the study describing d-cysteine as a regulator of neural progenitor cell dynamics (PMID: 34556581). We have added the description regarding the overlapping and distinct functions of d-cysteine and d-serine to the Discussion (lines 418-436).

(10) In the abstract, in lines 101 and 102, the authors mention "how d-serine contributes to cellular metabolism beyond neurotransmission remains largely unknown". In 2023, a paper in Stem Cell Reports by Roychaudhuri et al (PMID:37352848) showed that d and l-serine availability impacts lipid metabolism in the subventricular zone in mice, affecting proliferative properties of stem-cell derived neurons using a comprehensive lipidomics approach. There is no mention of this work even in the discussion section, as it bears directly on l and d-serine availability in neurons, which the authors are investigating. In the discussion section in lines 410-411, the authors mention the role of d-serine in neurogenesis, but surprisingly don't refer to the above reference. The role of d-serine in neurogenesis has been demonstrated in the Sultan et al (lines 855-857) and Roychaudhuri et al references.

We thank the reviewer for highlighting these relevant studies. We have revised the statement in line 99 to avoid overgeneralization and to reflect that the metabolic roles of d-serine are incompletely understood rather than largely unknown. In addition, we have incorporated discussion of previous works, including the work by Roychaudhuri et al. (2023), into the Discussion section (lines 418-436) of our revised manuscript.

(11) Both D-serine and the structurally similar stereoisomer D-cysteine (sulfur versus oxygen atom) have a bearing on 1C metabolism and the folate cycle. With reference to the folate cycle, Roychaudhuri et al in 2024 (PMID:39368613) have shown in rescue experiments in mice that supplementing a higher methionine diet provides folate cycle precursors to rescue the high insulin phenotype in SR-deficient mice. Since 1C metabolism is being discussed in this manuscript, the authors seem to overlook prior work in the field and not include it in their discussion, even when it is the same enzyme (SR) that synthesizes both serine and cysteine. Since the field of D-amino acid research is in its infancy, the authors must make it a point to include prior work related to D-serine at least, and not claim that it is not known. The known D-stereoisomers are not many, hence any progress in the area must include at least a discussion of the other structurally related stereoisomers.

We are grateful to the reviewer for drawing our attention to this relevant study.

We have now incorporated the findings from Roychaudhuri et al. 2024 into the Discussion. In that study, Srr-/- mice exhibited reduced levels of DNMT1 and DNMT3A, resulting in reduced DNA methylation activity. Notably, supplementation with a methyl-donor diet (containing choline, betaine, and methionine) restored the aberrant insulin phenotype in Srr-/- mice. These findings are relevant to our study, as DNA methylation depends on S-adenosyl-methionine (SAM), which is generated through one-carbon metabolism.

We have expanded the Discussion to include the relationship between d-serine and d-cysteine, both of which are synthesized by Srr in the revised manuscript (lines 418-436).

(12) Racemases (serine and aspartate) in general are promiscuous enzymes and known to synthesize other stereoisomers in addition to D-serine, D-cysteine, and D-aspartate. A few controls, like D-aspartate, D-cysteine, or even D-alanine must be included in their study to demonstrate the specific actions of D-serine, especially in the N2a cell treatment experiments. Cysteine and Serine are almost identical in structure (sulfur versus oxygen atom), and both are synthesized by serine racemase (published). Cysteine has also been very recently shown to inhibit tumor growth and neural progenitor cell proliferation. (PMIDs: 40797101 and 34556581). How the authors' work relates to the existing findings must be discussed, and this would put things in perspective for the reader.

We thank the reviewer for this comment regarding the need to demonstrate the specificity of d-serine. As shown in Fig. S7A, d-serine, but not other d-amino acids commonly detected in mammals (Gonda et al., 2023), including d-aspartate, d-alanine, and d-proline, induced the cleavage of caspase-3 under the same experimental conditions, supporting the specific effect of d-serine in our system. We agree that d-cysteine shares structural similarity with d-serine and is also synthesized by Srr, suggesting potential functional overlap with d-serine. To place our findings in this context, we have added a paragraph in the Discussion (lines 418-436) describing the similarities of d-serine and d-cysteine. While both molecules may exert anti-proliferative effects, their underlying mechanisms appear to differ. Notably, supplementation with SAM, methionine, or glutathione did not rescue d-serine-induced growth inhibition in our system (Fig. S5J), suggesting that its effects are not primarily mediated through methylation or sulfur metabolic pathways. Instead, d-serine suppresses cellular proliferation by limiting mitochondrial l-serine availability and one-carbon metabolism. These observations highlight mechanistic divergence between d-serine and d-cysteine.

Reviewer #2 (Public review):

Summary:

This study by Suzuki et al. reports an interesting stereo-selective role of D-serine in regulating one-carbon metabolism during neurodevelopment to adapt the functional transition, probably through the competition with mitochondrial transport of L-serine. The authors provide a multi-layered set of evidence, including metabolomics, enzyme assays, mitochondrial transport competition, and functional assays in immature/neural progenitor cells, to build up a conceptual integration of D-serine as both a neurotransmitter and a metabolic regulator in the central neural system, which raises a broad potential interest to the neuroscience and metabolism communities.

Strengths:

This work provides a conceptual advance that D-serine not only serves as a traditional neurotransmitter in the central neural system but also critically contributes to metabolic regulation of neural cells. The authors performed solid metabolomic assays to validate the suppressive effect of D-serine on the one-carbon metabolic pathway, providing some evidence that D-serine competitively inhibits mitochondrial serine transport, but not directly impairs SHMT2 enzymatic activity. All these data indicate a critical role of D-serine synthesis during neural maturation and suggest a potential translational strategy for targeting serine metabolism in neural tumors.

Weaknesses:

(1) The detailed mechanism by which D-serine competes with L-serine for its mitochondrial transport is not investigated. For example, although the authors made some discussion, they did not provide direct genetic or biochemical evidence linking these effects to the specific transporters, such as SFXN1.

We thank the reviewer for this important comment regarding the mitochondrial l-serine transport mechanism. To address this point, we performed additional experiments using N2a cells in which Sfxn1 was knocked down by siRNA. Under semi-permeabilized cell conditions, we newly examined the effect of d-serine on mitochondrial L-serine transport.

Interestingly, even under conditions where Sfxn1 expression was markedly suppressed, d-serine still inhibited mitochondrial d-serine transport. Given that SFXN1 is known to function redundantly with its paralogs (SFXN2–SFXN5) in mitochondrial serine transport (Kory et al., 2018), these findings suggest that d-serine may interfere with l-serine transport not only through SFXN1 but potentially through multiple members of the SFXN transporter family. These new data have been added as Fig. S3, and the corresponding results and discussion have been incorporated into the revised manuscript (lines 158–165 and 379-385).

(2) Unlike tumor cells, where SHMT2 usually plays a predominant role in catalyzing serine/THF-derived one-carbon metabolism, normal cells may employ both SHMT1 and SHMT2 to do the work. Even under certain conditions that SHMT2-mediated one-carbon metabolism is suppressed, the activity of SHMT1 could be elevated for compensation. Thus, it is important to investigate whether D-serine affects SHMT1 activity or changes the balance between SHMT1- and SHMT2-mediated one-carbon metabolism. To this aim, the authors are strongly encouraged to perform a metabolic flux assay (MFA) by using 13C-labeled L-serine in the model cells in the presence and absence of D-serine.

We thank the reviewer for this thoughtful comment regarding the potential contribution of cytosolic SHMT1 to one-carbon metabolism. As the reviewer notes, while mitochondrial SHMT2 is generally considered the predominant enzyme supporting one-carbon metabolism in proliferating or tumor cells, SHMT1 in the cytosol may function in a complementary manner in normal cells. In our experiments using primary cortical neurons, we indeed observed that the sensitivity to d-serine differed between immature and mature neuronal states (Fig. 4E). This observation suggests that the relative contribution of SHMT1- and SHMT2-mediated one-carbon metabolism may vary depending on the differentiation status of the cells.

However, the primary focus of the present study was to investigate the mechanism underlying the anti-proliferative effect of d-serine in proliferative or undifferentiated neural cells. Our data demonstrate that d-serine inhibits one-carbon metabolism primarily by limiting mitochondrial l-serine availability through inhibition of mitochondrial l-serine transport. Therefore, a detailed analysis of the compensatory balance between SHMT1 and SHMT2 after disruption of mitochondrial serine transport falls beyond the central scope of the present study. Importantly, previous work by Miyamoto et al. (FEBS Journal, 2024) demonstrated that both SHMT1 and SHMT2 exhibit strong stereoselectivity for l-serine in their hydroxymethyl-transferase activity and do not utilize d-serine as a substrate. These findings make a direct effect of d-serine on hydroxymethyl-transferase activity of SHMT1 unlikely.

Nevertheless, we agree that differences in the anti-proliferative effects of d-serine across cell types or differentiation states could reflect variations in cellular dependence on one-carbon metabolism or potential compensation by SHMT1. To address this point, we have expanded the Discussion section to clarify the possible contribution of SHMT1 and the limitations of the present study (lines 367–376). While isotope tracing analysis would be valuable for further dissecting compartmentalized one-carbon fluxes, such analyses would primarily address the relative contributions of SHMT1 and SHMT2 rather than the mitochondrial serine transport step that constitutes the central mechanism identified in this study.

(3) A defect in serine-derived one-carbon metabolism may cause multiple cellular stress responses. It is valuable to detect whether cellular NADPH/NADH, GSH, or ROS is altered before and after D-serine treatment.

We appreciate this insightful comment regarding potential cellular stress responses associated with impaired one-carbon metabolism. Consistent with the reviewer’s suggestion, we examined markers related to redox status. Transcriptomic analysis revealed compensatory changes in genes involved in mitochondrial metabolic function, including components of the NADH dehydrogenase complex (Fig. 2IJ and Fig. S4A), suggesting metabolic adaptation to d-serine treatment. In response to the reviewer’s comment, we measured GSH levels in NPCs and found that d-serine treatment led to a reduction of GSH (new Fig. S7F), indicating altered redox balance. However, supplementation with exogenous GSH did not rescue d-serine-induced cell death (Fig. S7E). These results suggest that while d-serine induces changes in cellular redox status, including GSH depletion, redox imbalance alone is unlikely to be the primary driver of cell death in this context.

(4) The physiological relevance between D-serine and neural cell maturation/death should be further tested and discussed, since the dosage of D-serine used in the in vitro assay is much higher than that in physiological conditions.

We thank the reviewer for this comment regarding the physiological relevance of the d-serine concentrations used in our study. We agree that the concentrations of d-serine required to compete with l-serine for mitochondrial transport are higher than those typically observed under physiological conditions, which we acknowledged in the Discussion of our manuscript (lines 386-388). Importantly, however, in vivo, d-serine levels are tightly regulated in a spatiotemporal manner during brain development, with low levels during embryonic and early postnatal stages and increased levels upon neural maturation. This temporal regulation coincides with the transition from proliferative neural progenitor states to differentiated neurons, thereby limiting the potential for d-serine to interfere with one-carbon metabolism during periods of active cell proliferation. Thus, while the concentrations used in vitro may exceed physiological levels, they allow us to uncover a latent metabolic effect of d-serine that may become relevant under specific cellular or developmental contexts. To clarify these points, we have revised the Discussion (lines 388-395) in the revised manuscript to more explicitly address the relationship between d-serine dosage and physiological relevance.

Reviewer #3 (Public review):

Summary:

This manuscript presents a comprehensive and well-executed investigation into the metabolic role of D-serine in the central nervous system. The authors provide solid evidence that D-serine competitively inhibits mitochondrial L-serine transport, thereby impairing one-carbon metabolism. This stereoselective mechanism reduces glycine and formate production, suppresses cellular proliferation, and induces apoptosis in immature neural cells and glioblastoma stem cells. Developmental analyses further reveal a physiological enantiomeric shift in serine metabolism during neurogenesis, aligning with the transition from proliferation to maturation. Overall, the study bridges developmental neurobiology, cancer metabolism, and amino acid transport, uncovering a previously unrecognized metabolic function of D-serine beyond its role in neurotransmission.

Strengths:

(1) The discovery that D-serine inhibits one-carbon metabolism by competing for mitochondrial L-serine transport-rather than through enzymatic inhibition or receptor-mediated signaling-represents a significant and previously underappreciated mechanism. This finding has broad implications for understanding metabolic regulation during neurodevelopment and offers potential relevance for targeting metabolic vulnerabilities in cancer.

(2) The authors integrate metabolomics, mitochondrial transport assays, molecular dynamics simulations, genetic and pharmacologic perturbations, transcriptomics, and both in vitro and ex vivo models. The breadth of experimental approaches, combined with the coherence of the findings across systems, provides strong support for the central conclusions and enhances the overall impact of the study.

(3) The temporal shift in D-/L-serine levels during neurodevelopment is elegantly linked to the transition from proliferative to mature neuronal states. The selective vulnerability of neural progenitors and tumor cells-contrasted with the resistance of mature neurons-highlights a biologically meaningful and potentially targetable metabolic distinction.

Weaknesses:

(1) While the authors attribute D-serine's metabolic effects to competition with mitochondrial L-serine transport, the specific identity of the transporter(s) mediating this process remains undefined. This represents a meaningful mechanistic gap, as the central conclusion depends on D-serine limiting mitochondrial L-serine availability to inhibit one-carbon metabolism.

We thank the reviewer for this insightful comment regarding the identity of the mitochondrial l-serine transporter. As this concern overlaps with the point raised by Reviewer 2 (Weakness 1), we refer the reviewer to our response there for a detailed description of the additional experiments performed. Briefly, we conducted new experiments using siRNA-mediated knockdown of Sfxn1 in N2a cells and examined mitochondrial l-serine transport under semi-permeabilized conditions. Notably, even with marked suppression of Sfxn1 expression, d-serine continued to inhibit mitochondrial l-serine transport. Given that SFXN family members (SFXN1–SFXN5) are reported to function redundantly in mitochondrial serine transport (Kory et al., 2018), these findings suggest that d-serine may interfere with l-serine transport not only via SFXN1 but potentially across multiple SFXN paralogs. These results have been incorporated into the revised manuscript and are presented in Fig. S3, with the corresponding discussion added to the Results and Discussion sections (lines 158–164 and 379-385).

(2) The effective concentrations of D-serine used in vitro (IC₅₀ ≈ 1-2 mM) exceed typical brain levels (~0.3 mM). While the authors acknowledge this, a more focused discussion on whether higher local D-serine concentrations could arise in specific microenvironments - such as synaptic compartments, tumor niches, or pathological states-would help contextualize the in vitro findings and strengthen their physiological relevance. For example, disruptions in D-serine clearance or altered expression of serine racemase and transporters in disease contexts could lead to localized accumulation. Moreover, differences between extracellular and intracellular D-serine pools - and the mechanisms governing their regulation - may further influence its metabolic impact in vivo.

We appreciate this insightful comment regarding the physiological relevance of the d-serine concentrations used in vitro. We agree that the effective concentrations observed in our assays exceed typical bulk brain levels. To address this point, we have expanded the Discussion (lines 386-399) to consider conditions under which locally elevated d-serine concentrations may arise in vivo. These additions provide a more nuanced interpretation of the relationship between the concentrations used in vitro and the potential physiological contexts in which d-serine may exert metabolic effects.

(3) While the manuscript focuses on neural stem/progenitor cells and neural tumors, it remains unclear whether the anti-proliferative effects of D-serine are specific to neural lineages or extend to other highly proliferative non-neural cell types. A brief discussion addressing this point would help clarify the scope of D-serine's metabolic impact and whether its mechanism of action reflects a unique vulnerability in neural cells or a more general feature of proliferative metabolism. This distinction is particularly relevant for assessing the broader therapeutic potential of targeting mitochondrial L-serine transport.

We thank the reviewer for this comment regarding the potential generality of the anti-proliferative effects of d-serine. We agree that it is important to clarify whether the observed effects are specific to neural lineages or reflect a broader vulnerability of proliferative cells. In our study, we focused on neural progenitor cells and neural tumour models. However, the mechanism identified here, namely limitation of mitochondrial L-serine availability, targets a fundamental metabolic pathway that supports cell proliferation. Therefore, it is possible that similar effects may extend to other highly proliferative cell types beyond the neural lineage. To address this point, we have expanded the Discussion (lines 408-410) to clarify that the observed effects of d-serine may reflect a general metabolic vulnerability associated with proliferative states, while also noting that the degree of sensitivity is likely to depend on cell-type-specific reliance on mitochondrial one-carbon metabolism.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Minor issues:

The authors mention terms like neural tissue (line 109) and neural tumor cells (line 182). Neural tissue can mean anything under the sun. They need to mention the specific tissue being studied or investigated.

We have changed the terms.

Reviewer #2 (Recommendations for the authors):

(1) The figure items were not well organized, and the legends were difficult to read since they apparently lacked key information. For example, in Figure 2D, did the author intend to show SHMT2 activity? It is not clear how this assay was performed (in vitro or in vivo experiment?). Additionally, more detailed information should be provided in the Methods section.

We have improved the organization of figures and revised figure legends for better readability.

(2) The writing of the manuscript should be significantly improved, using a professional editing service, in order to increase the readability.

We appreciate the reviewer’s comment. The manuscript was professionally edited prior to submission. Nevertheless, we have made targeted revisions to the Introduction and Discussion sections to improve overall readability. We hope that these revisions have improved the clarity of the manuscript.

Reviewer #3 (Recommendations for the authors):

(1) The core mechanism centers on competition for mitochondrial L-serine transport, yet the identity of the transporter(s) involved remains speculative. While Kory et al. (2018) identified SFXN1 as a mitochondrial L-serine transporter, this connection is not directly addressed in the current study. It would strengthen the manuscript to clarify whether SFXN1 or related isoforms are expressed in the neural cell models used and whether their expression patterns correspond with the observed D-serine sensitivity. Even if functional validation is beyond the current scope, a more detailed discussion of potential transporter candidates and the limitations of existing data would provide important mechanistic context and help frame future directions.

We thank the reviewer for this insightful comment regarding the mitochondrial l-serine transporter and the potential involvement of SFXN family members. As this concern overlaps with the point raised by Reviewer 2 (Weakness 1), we refer the reviewer to our response there for a detailed description of the additional experiments performed.

Briefly, we performed siRNA-mediated knockdown of Sfxn1 in N2a cells and examined mitochondrial l-serine transport under semi-permeabilized conditions. Even under conditions of marked suppression of Sfxn1 expression, d-serine continued to inhibit mitochondrial l-serine transport. Given that members of the SFXN family have been reported to function redundantly in mitochondrial serine transport (e.g., Kory et al., 2018), these findings suggest that d-serine may affect l-serine transport not only through SFXN1 but potentially across multiple SFXN paralogs.

These new results have been incorporated into the revised manuscript (Fig. S3), and the relevant discussion has been expanded to clarify the potential roles of SFXN family transporters and the current limitations in defining the exact transporter responsible (lines 158–165 and 379-385).

(2) The authors use ex vivo brain slice cultures with tumor xenografts to demonstrate tissue-level relevance, which is a valuable strength of the study. However, additional context would enhance its translational significance. It would be helpful to discuss whether in vivo D-serine administration (e.g., ICV or systemic) is feasible and safe, especially given the high concentrations required in vitro. Briefly addressing whether genetic models, such as Srr knockout mice, support a role for D-serine in tumor progression or neurodevelopment would also strengthen the interpretation.

We thank the reviewer for this important comment regarding the translational relevance of d-serine administration in vivo. To address this point, we performed additional exploratory experiments using a subcutaneous tumour xenograft model in nude mice. Because the inhibitory effect of d-serine on one-carbon metabolism becomes evident under l-serine–limited conditions, tumor-bearing mice were fed an l-serine/glycine–deficient diet and administered d-serine in drinking water.

However, when d-serine was provided at high concentrations (≥ 500 mM) in drinking water, the mice exhibited marked behavioral abnormalities, including increased aggression and other abnormal behaviors. Due to these adverse effects, the experiment was ethically terminated. While our study focuses on the inhibitory effect of d-serine on one-carbon metabolism, d-serine is also a physiological co-agonist of the NMDA receptors, and therefore high systemic concentrations may influence neuronal excitability in vivo. These observations suggest that the concentrations required to achieve antitumor effects may be associated with significant neurological side effects.

Based on these findings, we consider that direct administration of d-serine itself may have limited therapeutic applicability as an antitumor reagent. Instead, future development of derivatives or strategies that retain the metabolic inhibitory effect while minimizing NMDA receptor–mediated effects may be required.

Regarding serine racemase (Srr) knockout models, xenograft tumour experiments would require an immunodeficient background, which makes the generation and use of such compound models technically challenging. Therefore, we did not pursue this approach in the present study. We have incorporated these considerations into the revised Discussion (lines 413-417) to clarify the translational implications and current limitations of our findings.

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