Abstract

   The long-term maintenance of hematopoietic stem cells (HSCs) relies on
   the regulation of endoplasmic reticulum (ER) stress at a low level, but
   the underlying mechanism remains poorly understood. Here, we
   demonstrate that suppression of ER stress improves the functions of
   HSCs and protects HSCs against ionizing radiation (IR)-induced injury.
   We identify epithelial membrane protein 1 (EMP1) as a key regulator
   that mitigates ER stress in HSCs. Emp1 deficiency leads to the
   accumulation of protein aggregates and elevated ER stress, ultimately
   resulting in impaired HSC maintenance and self-renewal.
   Mechanistically, EMP1 is located within the ER and interacts with
   ceramide synthase 2 (CERS2) to limit the production of a class of
   sphingolipids, dihydroceramides (dhCers). DhCers accumulate in
   Emp1-deficient HSCs and induce protein aggregation. Furthermore, Emp1
   deficiency renders HSCs more susceptible to IR, while overexpression of
   Emp1 or inhibition of CERS2 protects HSCs against IR-induced injury.
   These findings highlight the critical role played by the
   EMP1-CERS2-dhCers axis in constraining ER stress and preserving HSC
   potential.

   Subject terms: Haematopoietic stem cells, Endoplasmic reticulum,
   Self-renewal
     __________________________________________________________________

   A new study shows EMP1 protects hematopoietic stem cells by suppressing
   sphingolipid metabolism and ER stress. EMP1 interacts with CERS2 to
   limit dihydroceramide production, which causes protein aggregation when
   elevated.

Introduction

   The blood system is sustained by a pool of hematopoietic stem cells
   (HSCs) that are responsible for the production of all blood
   lineages^[48]1,[49]2. HSCs possess the capacity for self-renewal to
   ensure their long-term maintenance. Consequently, HSCs are exposed to
   multiple stress stimuli, including nutrient fluctuation, reactive
   oxygen species (ROS), endoplasmic reticulum (ER) stress, DNA damage,
   and replication stress^[50]3–[51]7. The molecular regulatory networks
   in HSCs tightly control stress-induced damage to prevent loss of
   function or the risk of leukemogenesis^[52]8. However, there still
   exist major gaps in understanding how HSCs respond to stress, which
   hinders the development of strategies to maintain or expand functional
   HSCs in vivo.

   ER is the largest organelle in eukaryotic cells and is responsible for
   various important cellular functions^[53]9. Various stimuli can lead to
   the accumulation of unfolded and misfolded proteins, which is a major
   cause of ER stress^[54]10. The response to ER stress, also known as the
   unfolded protein response (UPR), involves multiple reactions aimed at
   restoring protein folding homeostasis by reducing protein synthesis and
   improving the capacity of the ER for protein folding and degradation.
   If ER stress cannot be relieved, proapoptotic signaling will be
   initiated to clear the damaged cells^[55]11. Human HSCs are susceptible
   to ER stress and initiate apoptosis relative to other hematopoietic
   progenitors^[56]5,[57]12,[58]13. Enhanced ER protein folding
   significantly improves the reconstitution capacity of HSCs. By
   contrast, the deletion of the most conserved UPR transducer
   inositol-requiring enzyme 1α (IRE1α) impairs it^[59]5,[60]12. It has
   been demonstrated that IRE1α safeguards HSCs by restricting
   pro-leukemogenic gene programs^[61]14. Moreover, suppression of protein
   aggregation and ER stress by bile acids is necessary for promoting HSC
   proliferation during fetal hematopoiesis^[62]15. These findings
   indicate that HSCs require restricted levels of ER stress for their
   long-term maintenance; however, the mechanisms by which HSCs regulate
   or constrain this level of ER stress remain poorly understood.

   Epithelial membrane protein 1 (EMP1) is an integral membrane
   glycoprotein and belongs to the peripheral myelin protein 22-kDa
   (PMP22) gene family^[63]16. EMP1 has been identified as an oncogene in
   multiple cancers, including leukemia^[64]16,[65]17. High expression of
   EMP1 has been observed in prednisolone-resistant patients compared to
   -sensitive patients. Additionally, knock-down of EMP1 significantly
   reduces the migration capacity of acute lymphoblastic leukemia (ALL)
   cell lines. Furthermore, EMP1 has been recognized as a prognostic
   factor in myelodysplastic syndrome (MDS) and acute myeloid leukemia
   (AML)^[66]18,[67]19, and it is also considered a stemness-related gene
   in leukemia stem cells (LSCs)^[68]20. These findings underscore the
   critical roles of EMP1 in hematologic disorders; however, its exact
   functions in normal hematopoiesis, particularly in HSCs, remain
   unknown.

   In this study, we confirmed the susceptibility of HSCs to ER stress. We
   observed that suppression of ER stress enhances HSC maintenance and
   repopulation capacity both in vitro and in vivo while also providing
   protection against ionizing radiation (IR)-induced injury. Moreover, we
   have identified a gene, EMP1, that constrains ER stress in HSCs under
   homeostatic or IR conditions. Loss of Emp1 impairs HSC maintenance and
   self-renewal. The ER-localized EMP1 binds ceramide synthase 2 (CERS2)
   to constrain the production of dihydroceramides, thereby preventing the
   formation of protein aggregation within HSCs. Our findings emphasize
   the crucial role of EMP1 in preserving HSC potential and reveal a link
   between sphingolipid metabolism and HSC homeostasis.

Results

Suppression of ER stress contributes to the preservation of HSC potential

   It has been demonstrated that human HSCs exhibit a higher sensitivity
   to ER stress compared to progenitor cells in vitro, as evidenced by
   more pronounced apoptosis^[69]5. To investigate the sensitivity of HSCs
   to ER stress in vivo, wild-type C57BL/6J mice were treated with
   tunicamycin (2 mg/kg) (Fig. [70]S1A), an inhibitor of glycosylation to
   disturb the protein folding^[71]21. The fluorogenic assay utilizing the
   ProteoStat dye has been developed to monitor protein aggregation within
   cells^[72]15 (Fig. [73]S1B). Twenty-four hours after the administration
   of tunicamycin, we performed ProteoStat dye staining and observed the
   significant increase in aggregated protein levels in bone marrow (BM)
   HSCs (Fig. [74]S1C), which are usually characterized as
   CD48^−CD150^+LSK (LSK refers to Lineage^−Sca-1^+c-kit^+ cells)^[75]22.
   This increase was most pronounced in HSCs compared to other
   hematopoietic cell types (Fig. [76]S1C). The accumulation of
   unfolded/aggregated proteins triggers UPR, which is regulated by three
   branches: the PRKR-like ER kinase (PERK), inositol-requiring enzyme 1
   (IRE1), and activating transcription factor (ATF6)^[77]11. Our
   observations indicated that the UPR response of HSCs to tunicamycin
   treatment was more robust compared to LK cells (Lin^−Sca-1^−c-kit^+
   cells; Lin^− refers to lineage^− cells) and LSK cells, as evidenced by
   increased phosphorylation of IRE1 and PERK (Fig. [78]S1D, E). These
   data suggest that HSCs are susceptible to ER stress in vivo.

   To further investigate the impact of ER stress on HSC maintenance in
   vitro, we cultured BM Lin^− cells from wild-type mice in a liquid
   medium. The cultures were treated with either dimethyl sulfoxide
   (DMSO), tunicamycin (5 μM) to induce ER stress, or azoramide (15 μM) to
   enhance ER protein folding and increase chaperone activity for a
   duration of 24 h (Fig. [79]1A). Compared to the DMSO-treated culture
   samples, those treated with tunicamycin exhibited a reduced frequency
   of LSK and HSCs among the cultured cells; however, treatment with
   azoramide appeared to mitigate this effect and even promote the
   preservation of HSCs when compared to the DMSO group (0.049% versus
   0.025%) (Fig. [80]1B). We also cultured sorted HSCs (CD48^−CD150^+LSK)
   under the same conditions, followed by a serial colony-forming unit
   (CFU) assay. Our findings indicated that tunicamycin significantly
   inhibited the colony-forming capacity of HSCs. In contrast, the
   suppression of ER stress through azoramide substantially enhanced the
   number of CFUs generated by HSCs (Fig. [81]1C).

Fig. 1. Suppression of ER stress contributes to HSC maintenance during in
vitro culture and IR-induced injury.

   [82]Fig. 1
   [83]Open in a new tab

   A Experimental scheme. Lineage negative cells (Lin^− cells) or HSCs
   (CD48^−CD150^+LSK) were cultured in a liquid medium with DMSO,
   tunicamycin (5 μM), or azoramide (15 μM) for 24 h, followed by
   subsequent experiments. B Representative flow plots of the LSK
   (Lin^−Sca-1^+c-Kit^+) and HSCs (CD48^−CD150^+LSK) populations. Right
   graph represents the cell frequency of LSK and HSCs in cultured cells
   (n = 3 samples per group). C Representative images of the first (1st)
   and second (2nd) plating colonies. The scale bar represents 100 µm.
   Right graph represents the colony numbers (n = 3 samples per group). D
   Representative flow plots of the chimerism of peripheral blood (PB)
   from recipients at 1 and 4 months after transplantation. E The
   percentages of donor-derived cells in PB (n = 5 recipients per group).
   F The percentages of donor-derived BM cells, LK (Lin^−Sca-1^−c-Kit^+),
   LSK, and HSCs in BM of recipients at 4 months after transplantation
   (n = 5 recipients per group). G Experimental scheme. H Flow cytometry
   analysis of protein aggregate levels in HSCs (CD48^−CD150^+LSK) using
   ProteoStat staining. Right graph represents the mean fluorescence
   intensity (MFI) of ProteoStat in HSCs (n = 4 mice per group). FMO,
   Fluorescence-Minus-One Control. I Flow cytometry analysis of p-IRE1 and
   p-PERK staining in HSCs. Right graph represents the MFI of p-IRE1 and
   p-PERK in HSCs (n = 4 mice per group). J Experimental scheme. HSCs were
   treated with DMSO or azoramide (15 μM) for 24 h, followed by a dose of
   2 Gy γ-irradiation and subsequent competitive transplantation. K The
   percentages of donor-derived cells in PB at indicated times (n = 5
   recipients per group). L The percentages of donor-derived myeloid cells
   (CD11b^+), B cells (B220^+), and T cells (CD3^+) in PB cells of
   recipient mice at 4 months after transplantation (n = 5 recipients per
   group). M The percentages of donor-derived BM cells, LK, LSK, and HSCs
   in BM of recipients at 4 months after transplantation (n = 5 recipients
   per group). All statistical analyses were performed using two-tailed
   unpaired Student’s t-test. Data are shown as mean ± SD. Results are
   representative of two independent experiments. Source data are provided
   as a Source Data file.

   Competitive BM transplantation is enabled by antibodies that
   specifically recognize hematopoietic cells from congenic mouse strains
   due to variants of the cell surface protein CD45, designated CD45.1 and
   CD45.2. The C57BL/6J background mice express the CD45.2 allele, whereas
   B6.SJL mice express the CD45.1 allele. Offspring resulting from the
   crossbreeding of these two mouse strains simultaneously express both
   CD45.1 and CD45.2 alleles^[84]23. To further assess the reconstitution
   potential of HSCs in vivo, drug-treated HSCs (CD45.2) derived from
   wild-type C57BL/6J mice were mixed with competitor BM cells (CD45.1)
   and transplanted into lethally irradiated recipient mice
   (CD45.1CD45.2). Our findings indicate that treatment with azoramide or
   tunicamycin resulted in the highest and lowest chimeric percentages of
   donor-derived peripheral blood (PB), respectively (Fig. [85]1D, E). The
   chimeric percentages of mature cells, including myeloid, B, and T cells
   in PB, exhibited a consistent change at 4 months post-transplantation
   (Fig. [86]S1F). Furthermore, azoramide or tunicamycin treatment led to
   the highest and lowest chimeric percentages observed in BM cells, LK
   cells, LSK cells, and HSCs within recipient mice, respectively
   (Fig. [87]1F). Taken together, these data suggest that suppression of
   ER stress improves both in vitro maintenance and in vivo repopulation
   potential for HSCs.

Alleviation of ER stress protects HSCs against radiation-induced injury

   IR is known to cause hematopoietic toxicity, leading to severe
   consequences such as BM failure, immune dysfunction, and even
   leukemia/lymphoma development^[88]24. HSCs are highly susceptible to
   IR, which causes HSC dysfunction^[89]25,[90]26. However, effective
   strategies for protecting HSCs from IR-induced injury are currently
   limited. A dosage of 2–5 Gy is commonly utilized for evaluating the
   impact of IR on HSCs, both in vivo and in vitro^[91]27–[92]29. To
   investigate the impact of IR on HSCs in vitro, HSCs (CD48^−CD150^+LSK)
   were isolated from wild-type C57BL/6J mice and then exposed to a dose
   of 2 Gy of γ-irradiation (Fig. [93]S2A). Subsequent analyses at various
   time points post-irradiation (6–72 h) revealed that 6 h after exposure,
   the levels of aggregated proteins in HSCs were significantly
   upregulated, peaking at 24 h and then decreasing dramatically; however,
   these levels remained elevated compared to non-IR-treated HSCs
   (Fig. [94]S2B). Additionally, key markers of the UPR, specifically
   p-IRE1 and p-PERK, exhibited significant elevation in IR-treated HSCs
   relative to control groups, with peak expression observed at 24 h
   post-exposure (Fig. [95]S2C). To further explore the effect of IR on
   HSCs in vivo, wild-type C57BL/6J mice were exposed to sublethal doses
   (2 or 5 Gy) of γ-irradiation (Fig. [96]1G). Twenty-four hours after
   exposure, the number of LK, LSK, and HSCs in IR-treated mice was
   significantly reduced compared to non-IR-treated counterparts
   (Fig. [97]S2D, E). Consistent with previous findings^[98]24, we
   observed that IR caused substantial DNA damage in HSCs, as indicated by
   increased levels of γ-H2AX (Fig. [99]S2F, G). Notably, IR resulted in a
   significant increase in aggregated protein levels in HSCs
   (Fig. [100]1H). The hallmarks of UPR, p-IRE1 and p-PERK, were also
   remarkably elevated in IR-treated HSCs compared to control HSCs
   (Fig. [101]1I). Collectively, these data suggest that IR induces the
   formation of protein aggregates and elicits ER stress in HSCs both in
   vitro and in vivo.

   To investigate whether the alleviation of ER stress could protect HSCs
   from IR exposure, murine HSCs (CD48^−CD150^+LSK) were treated with
   azoramide to enhance ER protein folding and increase the activity of ER
   chaperones. Subsequently, the HSCs were exposed to IR at a dose of 2 Gy
   and then transplanted into recipient mice (Fig. [102]1J). It was
   observed that IR treatment significantly decreased the chimeric
   percentages of donor-derived PB, BM cells, LK, LSK, and HSCs in
   recipient mice compared to non-IR-treated group. Encouragingly,
   azoramide treatment markedly enhanced the reconstitution capacity of
   HSCs in recipient mice (Fig. [103]1k–m). These findings collectively
   demonstrate that ER stress plays a pivotal role in IR-induced injury in
   HSCs, while alleviating ER stress effectively improves HSC function
   under IR conditions.

ER stress induces the expression of EMP1 in HSCs, where it is localized
within the ER

   Currently, the mechanisms by which HSCs respond to ER stress remain
   largely unknown. In this study, we sorted HSCs from DMSO- and
   tunicamycin-treated mice and performed RNA sequencing (RNA-seq). We
   observed that tunicamycin-induced ER stress significantly altered gene
   expression in HSCs, resulting in both upregulated and downregulated
   genes (>twofold change, p < 0.05) (Fig. [104]2A). Gene set enrichment
   analysis (GSEA) revealed that ER stress activates specific pathways
   such as apoptosis, p53, and TNF signaling via NF-κB pathway
   (Fig. [105]2B). To further investigate the response of HSCs to ER
   stress, an assay for transpose-accessible chromatin sequencing
   (ATAC-seq) was performed. We found that tunicamycin-treated HSCs
   displayed global chromatin opening, as evidenced by a significant
   increase in global ATAC-seq compared to DMSO-treated HSCs
   (Fig. [106]2C, D). The major signaling pathways enriched with the genes
   whose loci were associated with significantly changed ATAC-seq peaks
   upon ER stress are shown in Fig. [107]2E. Additionally, we conducted an
   overlap analysis of the RNA-seq and ATAC-seq databases focusing on
   genes showing upregulated ATAC peak and expression. Bcl2a1a was one of
   the mostly upregulated genes (Fig. [108]2F), which has been
   demonstrated the anti-apoptotic function in hematopoietic stem and
   progenitor cells^[109]30. Among other notable genes, we identified an
   intriguing gene, Emp1 (Fig. [110]2F), which is a member of the PMP22
   gene family^[111]16. Previous studies have reported that EMP1 plays
   critical roles in various stem cell types, including colorectal cancer
   stem-like cells and LSCs^[112]17,[113]18. The increased expression of
   Emp1 in HSCs under ER stress suggests its significant involvement in
   the ER response. To clarify the expression of EMP1 in human
   hematopoietic cells, we analyzed published single-cell RNA sequencing
   (scRNA-seq) data^[114]31 from human BM cells of five healthy donors.
   Our findings indicate that EMP1 is most highly expressed in HSCs
   (Fig. [115]S3A, B). Next, we characterized the expression of Emp1 in
   subsets of primitive and mature BM cells from mice through quantitative
   reverse transcription polymerase chain reaction (qRT-PCR). Our findings
   revealed that Emp1 exhibited the highest expression in HSCs
   (CD48^−CD150^+LSK) compared to LSK, LK, multipotent progenitor cells
   (MPPs), and mature cells (Fig. [116]2G). Collectively, these data
   demonstrate that EMP1 is highly expressed in HSCs and may function as a
   potential responder to ER stress within this cell population.

Fig. 2. ER stress induces the expression of EMP1 in HSCs, where it is
localized within the ER.

   [117]Fig. 2
   [118]Open in a new tab

   A A representative volcano plot of the gene expression changes between
   HSCs from DMSO-treated and tunicamycin-treated mice (n = 5 mice per
   group). All significantly changed genes (>twofold change, P < 0.05) are
   indicated by blue or red dots. B GSEA shows that apoptosis, p53, and
   TNF signaling via NF-κB pathways are significantly upregulated in
   tunicamycin-treated HSCs compared to DMSO-treated HSCs. C
   Representative heatmaps show ATAC-seq peaks ± 5 kb from transcriptional
   start site (TSS) in HSCs. Top, line plots of relative quantifications
   based on average intensities of all ATAC peaks detected. D Statistics
   and quantification of genomic-wide ATAC signal (n = 2 samples per
   group). Violin plot of the log[2](normalized RPKM) of peaks under
   different conditions. The box plot represents the minimum, median, and
   maximum values. E The KEGG analysis of the enrichment and
   classification of the significantly changed peaks. F The quadrant chart
   shows the distribution of genes with both differential ATAC peaks and
   differential expression in the tunicamycin-treated HSCs compared with
   the control group. G qRT-PCR analysis of Emp1 expression in different
   hematopoietic cell subsets in wild-type mice (n = 3 mice per group),
   including BM cells, Lin^− cells, LK, LSK, MPP (CD48^+CD150^−LSK),
   myeloid cells (Gr1^+CD11b^+), B cells (B220^+), and T cells (CD3^+). H
   Immunofluorescence staining of EMP1 (green) and Calreticulin (red) in
   murine HSCs (CD48^−CD150^+LSK). Nuclei are stained with DAPI (blue). I
   Flow cytometry analysis of EMP1 staining in LK cells and HSCs
   (CD48^−CD150^+LSK) from DMSO-treated and tunicamycin-treated mice.
   Right graph represents the MFI of EMP1 in hematopoietic cells (n = 3
   mice per group). J qRT-PCR analysis of Emp1 expression in HSCs
   (CD48^−CD150^+LSK). HSCs are isolated from wild-type mice that were
   exposed to 0 or 5 Gy radiation (n = 5 mice per group). K Flow cytometry
   analysis of EMP1 staining in HSCs. Right graph represents the MFI of
   EMP1 in HSCs (n = 5 mice per group). All statistical analyses were
   performed using two-tailed unpaired Student’s t-test. Data are shown as
   mean ± SD. Results are representative of two independent experiments.
   Source data are provided as a Source Data file.

   To ascertain whether EMP1 is an ER protein, we isolated the ER from BM
   Lin^−c-Kit^+ cells derived from wild-type C57BL/6J mice, along with
   residual components. Western blot analysis demonstrated that EMP1 was
   predominantly present in ER extracts, as indicated by established ER
   markers such as protein disulfide isomerase and Calreticulin;
   conversely, it was absent in extracts devoid of ER (Fig. [119]S3C).
   Similar results were observed in CD34^+ cells derived from human cord
   blood (Fig. [120]S3C). Furthermore, immunofluorescence staining
   revealed that EMP1 co-localized with established ER marker Calreticulin
   in HSCs (CD48^−CD150^+LSK) (Fig. [121]2H). These findings confirm that
   EMP1 primarily resides within the ER in HSCs. Further characterization
   revealed that under ER stress, there was a significant increase in EMP1
   protein levels in HSCs as determined by intracellular protein staining
   for flow cytometry (Fig. [122]2I). Given that IR induces ER stress in
   HSCs, we investigated the effect of IR on EMP1 expression and observed
   a significant elevation at both mRNA and protein levels in IR-treated
   HSCs compared to control (Fig. [123]2J, K). Collectively, these
   findings indicate that EMP1 is localized to the ER in HSCs, and that ER
   stress triggers the expression of EMP1.

Emp1 deficiency impairs HSC maintenance and self-renewal

   To investigate the role of EMP1 in HSCs, we generated a conditional
   knock-out allele of Emp1 (Emp1^fl/+), in which exons 3 to 4 are flanked
   with loxP sites. We then bred Emp1^fl/+ mice with Tie2-Cre mice, in
   which Cre recombinase is expressed in endothelial and hematopoietic
   cells under the control of Tie2 promoter, to generate control
   Emp1^fl/fl mice and Emp1^fl/fl, Tie2-Cre, with conditional deletion of
   Emp1 (named as Emp1-cKO mice) (Fig. [124]S4A). The efficiency of Emp1
   deletion in BM cells and HSCs was validated through western blot
   analysis and qRT-PCR, respectively (Fig. [125]S4B). At 2 months of age,
   Emp1-cKO mice showed no obvious changes in hematological parameters
   compared to Emp1^fl/fl mice (Fig. [126]S4C). The frequency of myeloid,
   red, B, and T cells was similar between Emp1^fl/fl and Emp1-cKO mice
   (Fig. [127]S4D–O). However, BM cellularity was decreased in Emp1-cKO
   mice compared to controls (Fig. [128]3A). Subsequent cell surface
   marker staining revealed that there were significantly fewer
   hematopoietic stem and progenitor cells in BM of Emp1-cKO mice than
   that of Emp1^fl/fl mice. This included LK cells (common myeloid
   progenitors [CMPs], granulocyte-erythroid progenitors, and
   megakaryocyte-erythroid progenitors [MEPs]), LSK cells, and short-time
   HSCs (ST-HSCs), multipotent progenitors (MPPs), lymphoid-primed
   multipotent progenitors (LMPPs), and HSCs (defined as CD48^−CD150^+LSK
   or CD34^−CD135^−LSK) (Fig. [129]3B–F). To further determine the
   abundance of functional HSCs, we performed a limiting dilution assay
   and observed a significant reduction in the frequency of functional
   HSCs in Emp1-cKO mice compared to that in Emp1^fl/fl mice (1/40916 in
   Emp1-cKO versus 1/5852 in Emp1^fl/fl) (Fig. [130]3G).

Fig. 3. Emp1 deficiency impairs HSC maintenance and self-renewal.

   [131]Fig. 3
   [132]Open in a new tab

   A Quantification of BM cellularity of Emp1^fl/fl and Emp1^fl/fl,
   Tie2-Cre (named Emp1-cKO) mice at 2 months of age (n = 10 mice per
   group). B Representative flow plots of LK (Lin^−Sca-1^−c-Kit^+), LSK
   (Lin^−Sca-1^+c-Kit^+), CMP (CD34^+CD16/32^medLK), MEP
   (CD34^−CD16/32^−LK), GMP (CD34^+CD16/32^+LK), MPP (CD34^+CD135^+LSK),
   LMPP (CD135^highLSK), ST-HSC (CD34^+CD135^−LSK), CD34^−LSK, HSC
   (CD48^−CD150^+LSK or CD34^−CD135^−LSK) population in BM of Emp1^fl/fl
   and Emp1-cKO mice. C–F Graphs represent the cell count of different
   hematopoietic cell subsets in BM of mice (C and D, n = 10 mice per
   group; E and F, n = 6 mice per group). G The HSC frequency was
   calculated and the log-fraction plot was generated using extreme
   limiting dilution analysis (n = 5 recipient mice at each cell
   concentration). A positive response was considered if donor engraftment
   in the BM of recipient mice exceeded 1% for both lymphoid and myeloid
   lineages at 12 weeks post-transplantation. H Experimental schematic for
   the competitive transplantation assay. I Representative flow plots of
   the chimerism of PB from recipients in serial competitive
   transplantation assay. Donor-derived cells, CD45.2^+;
   competitor-derived cells, CD45.1^+CD45.2^+. J The percentages of
   donor-derived cells in PB at indicated times (n = 6 recipients per
   group). K The percentages of donor-derived myeloid cells, B cells, and
   T cells in PB cells of recipient mice at 4 months after first and
   second transplantation (n = 6 recipients per group). L The percentages
   of donor-derived BM cells, LK, LSK, and HSCs in BM of recipients at 4
   months after first and second transplantation (n = 6 recipients per
   group). All statistical analyses were performed using two-tailed
   unpaired Student’s t-test. Data are shown as mean ± SD. Results are
   representative of two independent experiments. Source data are provided
   as a Source Data file.

   The CFU assay demonstrated that Emp1-deficient HSCs produced a
   significantly reduced number of total colonies compared to Emp1^fl/fl
   HSCs in the first and second plating (Fig. [133]S5A, B), indicating
   that Emp1 deficiency impaired the proliferation of Emp1-cKO HSCs in
   vitro. Additionally, we administered the cell cycle-dependent
   myelotoxic agent 5-fluorouracil (5-FU) into mice on a weekly basis. The
   poor survival of Emp1-cKO mice indicated defective hematopoiesis in
   comparison to control mice (Fig. [134]S5C). To further assess the
   hematopoietic potential of HSCs in vivo, we transplanted HSCs into
   lethally irradiated recipient mice (CD45.1) and evaluated the
   hematopoiesis of recipients at two months post-transplantation
   (Fig. [135]S5D). Our findings revealed that Emp1 deficiency compromised
   the repopulation potential of HSCs, as evidenced by significantly
   reduced PB cells and BM cellularity in recipient mice (Fig. [136]S5E,
   F). Furthermore, the recipient mice derived from Emp1-cKO HSCs
   exhibited a considerably decreased number of LK, LSK, MPP, LMPP,
   ST-HSCs, and HSCs in BM compared to control recipients
   (Fig. [137]S5G–J). Taken together, these data suggest that Emp1 is
   crucial for maintaining HSC function and supporting hematopoiesis.

   To further evaluate the long-term self-renewal capacity of HSCs, we
   performed a competitive serial transplantation assay. The sorted
   Emp1^fl/fl or Emp1-cKO HSCs (CD45.2) were mixed with competitive BM
   cells (CD45.1CD45.2) and then transplanted into lethally irradiated
   recipient mice (CD45.1) (Fig. [138]S6A). Donor-derived PB cells from
   Emp1-cKO HSCs showed continuously decreased chimeric percentages
   compared to control (Fig. [139]S6B, C). Additionally, the chimeric
   percentages of mature cells in PB showed a consistent decrease as well
   (Fig. [140]S4D). The reduced percentages of BM cells, LK, LSK, and HSCs
   in recipient mice indicate that Emp1 deficiency impairs the
   self-renewal of HSCs (Fig. [141]S6E). To investigate whether Emp1
   regulates the self-renewal of HSCs in a cell-intrinsic manner, BM cells
   (CD45.2) from Emp1^fl/fl and Emp1^fl/fl, Mx1-Cre mice were mixed with
   competitor BM cells (CD45.1CD45.2) and transplanted into lethally
   irradiated recipient mice (CD45.1). Subsequently, the recipient mice
   received injections of polyinosinic:polycytidylic acid (pIpC) at 1
   month after transplantation to induce Emp1 deletion, followed by
   chimerism analysis and second transplantation (Fig. [142]3H). The
   decreased chimeric percentages of PB, BM cells, LK, LSK, and HSCs
   suggested that Emp1 loss impaired the self-renewal of HSCs in a
   cell-intrinsic manner (Fig. [143]3I–L). Additionally, we enforced Emp1
   expression in HSCs via retrovirus and transplanted transduced HSCs
   (CD45.1) into lethally irradiated recipient mice (CD45.2) with
   competitor BM cells (CD45.1CD45.2) (Fig. [144]S6F). We observed that
   the donor-derived cells from Emp1-overexpressed HSCs exhibited
   continuously increased chimeric percentages of PB and BM cells in
   recipient mice compared to control group (Fig. [145]S6G–I), indicating
   that Emp1 overexpression promoted self-renewal of HSCs. Collectively,
   these data demonstrate that Emp1 is essential for long-term
   self-renewal of HSCs.

Emp1 deficiency leads to the formation of protein aggregates and ER stress in
HSCs

   Quiescence is a fundamental characteristic of HSCs that ensures
   longevity^[146]8. In this study, we conducted Ki-67 + DAPI staining and
   observed a lower proportion of quiescent CD48^−CD150^+LSK (G0 phase) in
   Emp1-cKO mice (47.4%) compared to control mice (62.0%) (Fig. [147]4A).
   Additionally, staining with annexin-V and DAPI revealed an increased
   rate of early/late apoptosis in CD48^−CD150^+LSK lacking Emp1 function
   (Fig. [148]4B). To investigate the molecular mechanisms underlying
   Emp1-regulated HSC homeostasis, we performed RNA-seq analysis on
   freshly sorted HSCs from both Emp1^fl/fl and Emp1-cKO mice. Our
   analysis identified 163 significantly upregulated genes and 316
   considerably downregulated genes (>twofold change; p < 0.05) in
   Emp1-cKO HSCs compared to controls (Fig. [149]4C). Furthermore, gene
   ontology (GO) analysis of the RNA-seq data highlighted significant
   dysregulation in genes associated with myeloid cell differentiation and
   regulation of hematopoiesis in HSCs lacking EMP1 function
   (Fig. [150]4D). E2F1 is known as a positive regulator for cell cycle
   progression^[151]32. GSEA of the RNA-seq data demonstrated a
   significant up-enrichment of E2F1 target-associated genes in Emp1-cKO
   HSCs compared to control. Moreover, GSEA also revealed an up-enrichment
   of genes associated with ER stress response, also known as UPR, in
   Emp1-cKO HSCs (Fig. [152]4E).

Fig. 4. Emp1 deficiency leads to the formation of protein aggregates and
induces ER stress in HSCs.

   [153]Fig. 4
   [154]Open in a new tab

   A Representative flow plots of the Ki-67 and DAPI staining of HSCs
   (CD48^−CD150^+LSK). Right graph represents the percentages of
   cell-cycle distribution of HSCs (n = 5 mice per group). B
   Representative flow plots of the Annexin-V and DAPI staining of HSCs
   (CD48^−CD150^+LSK). Right graph represents the percentages of apoptotic
   HSCs (n = 5 mice per group). Early apoptotic cells, Annexin-V^+DAPI^−;
   Late apoptotic cells, Annexin-V^+DAPI^+. C A representative volcano
   plot of the gene expression changes between Emp1^fl/fl and Emp1-cKO
   HSCs (CD48^−CD150^+LSK) (n = 3 samples per group). All significantly
   changed genes (>twofold change, P < 0.05) are indicated by blue or red
   dots. D The Gene Ontology (GO) analysis of the enrichment and
   classification of the differentially expressed genes. E GSEA shows that
   E2F targets and ER stress response pathways are significantly
   upregulated in Emp1-cKO HSCs compared to Emp1^fl/fl HSCs. F Flow
   cytometry analysis of protein aggregate levels in HSCs using ProteoStat
   staining. Right graph represents the MFI of ProteoStat in HSCs
   (CD48^−CD150^+LSK) (n = 5 mice per group). G A graph represents the MFI
   of indicated proteins in HSCs (CD48^−CD150^+LSK) using flow cytometry
   staining and analysis (n = 5 mice per group). H qRT-PCR analysis of
   Chop expression in Emp1^fl/fl and Emp1-cKO HSCs (CD48^−CD150^+LSK)
   (n = 5 mice per group). I Representative electron microscopic images of
   Emp1^fl/fl and Emp1-cKO HSCs (CD48^−CD150^+LSK). The white arrows
   indicate the presence of changed ER morphology. J Flow cytometry
   analysis of protein aggregate levels in human cord blood CD34^+ cells
   using ProteoStat staining. CD34^+ cells were infected with shRNA
   lentivirus targeting EMP1 and control shRNA lentivirus. Right graph
   represents the MFI of ProteoStat (n = 4 samples per group). K A graph
   represents the percentages of apoptotic human cord blood CD34^+ cells
   (n = 4 samples per group). All statistical analyses were performed
   using two-tailed unpaired Student’s t-test. Data are shown as
   mean ± SD. Results shown in (A, B and F–K) are representative of two
   independent experiments. Source data are provided as a Source Data
   file.

   Based on previous findings, including the localization of EMP1 to ER
   (Fig. [155]2H), upregulation of Emp1 in HSCs in response to ER stress
   (Fig. [156]2I), and the observation that Emp1 deficiency leads to an ER
   stress response at the transcriptional level in HSCs (Fig. [157]4E), it
   is suspected that EMP1 plays a role in governing ER stress in HSCs.
   Notably, Emp1-cKO HSCs exhibited a significantly increased level of
   protein aggregates compared to Emp1^fl/fl HSCs (Fig. [158]4F).
   Furthermore, key markers of ER stress response, such as Glucose
   regulatory protein 78, p-PERK, p-eIF2α, ATF4, and p-IRE1 were found to
   be significantly elevated in Emp1-cKO HSCs compared to Emp1^fl/fl HSCs
   (Fig. [159]4G). Additionally, there was an observed increase in
   expression of CCAAT-enhancer-binding protein homologous protein (CHOP)
   in Emp1-cKO HSCs (Fig. [160]4H), a molecule involved in ER
   stress-induced apoptosis^[161]33. Elevated ER stress often causes ER
   morphology change^[162]34. Compared to normal ER morphology of
   Emp1^fl/fl HSCs, ER of Emp1-cKO HSCs showed intensified edema and
   expansion, as noted by white arrows (Fig. [163]4I). Heat stress serves
   as an additional induction condition for the formation of protein
   aggregates and subsequent ER stress^[164]35. We cultured HSCs at
   temperatures of 37 °C or 42 °C for a duration of one hour
   (Fig. [165]S7A). Our observation revealed that Emp1-cKO HSCs exhibited
   a higher level of protein aggregates compared to Emp1^fl/fl HSCs
   (Fig. [166]S7B), along with elevated levels of key markers associated
   with the ER stress response, specifically p-IRE1 and p-PERK
   (Fig. [167]S7C).

   To further investigate the function of EMP1 in regulating human
   hematopoietic stem and progenitor cells (HSPCs), we utilized short
   hairpin RNA (shRNA) lentivirus to knock down EMP1 expression
   specifically within CD34^+ hematopoietic cells derived from human cord
   blood. The results showed a significant increase in protein aggregates
   when EMP1 expression was reduced (Fig. [168]4J), along with an elevated
   rate of apoptosis among shEMP1-transduced CD34^+ cells as opposed to
   shControl cells (Fig. [169]4K). Additionally, we observed a decrease in
   the frequency of quiescent CD34^+ cells (cells in G0 phase) when EMP1
   expression was diminished through shRNA intervention (Fig. [170]S7D).
   In summary, these data demonstrate that knock-out or knock-down of EMP1
   results in protein aggregation and subsequent induction of ER stress in
   murine HSCs and human HSPCs, respectively.

Loss of Emp1 aggravates HSC defects under IR conditions

   Given that radiation induces ER stress in HSCs, we hypothesize that
   EMP1 might play a crucial role in regulating the susceptibility of HSCs
   to IR. To investigate this hypothesis, Emp1^fl/fl and Emp1-cKO mice
   were exposed to various doses (2, 5, or 7.5 Gy) of γ-irradiation
   (Fig. [171]5A). The loss of Emp1 significantly reduced the survival
   time of mice compared to control mice under IR-induced injury
   (Fig. [172]5B), indicating increased susceptibility of Emp1-cKO mice to
   IR. Furthermore, we observed intensified loss of hematopoietic cells in
   Emp1-cKO mice compared with Emp1^fl/fl mice under IR conditions (2 Gy),
   as evidenced by significantly reduced numbers of BM cells, LK, LSK, and
   HSCs (Fig. [173]5C–G). Additionally, we found that the loss of Emp1
   aggravated HSC defects under IR conditions, as indicated by higher
   levels of protein aggregates (Fig. [174]5H), markers of ER stress
   response such as phosphorylated IRE1 and PERK proteins (p-IRE1 and
   p-PERK) (Fig. [175]5I, J), and increased apoptosis rates
   (Fig. [176]5K). In addition to inducing apoptosis, IR also facilitates
   the exit of HSCs from quiescence, thereby further accelerating HSC
   exhaustion^[177]24. Staining with Ki-67 and DAPI revealed that the
   proportion of quiescent HSCs in IR-treated Emp1^fl/fl mice was lower
   than that observed in non-IR-treated Emp1^fl/fl mice (34.6% versus
   59.2%) (Fig. [178]5L). Moreover, the deficiency of Emp1 exacerbated
   this phenomenon, resulting in the lowest proportion of quiescent HSCs
   in IR-treated Emp1-cKO mice (18.9%) (Fig. [179]5L). Collectively, these
   findings demonstrate that the loss of Emp1 aggravates HSC defects under
   IR conditions.

Fig. 5. Loss of Emp1 aggravates HSC defects under IR conditions.

   [180]Fig. 5
   [181]Open in a new tab

   A Experimental schematic. Emp1^fl/fl and Emp1-cKO mice were exposed to
   various doses (2, 5, or 7.5 Gy) of γ-irradiation. B Survival curves of
   Emp1^fl/fl and Emp1-cKO mice after exposure to γ-irradiation (n = 7
   mice per group). C Experimental schematic. Emp1^fl/fl and Emp1-cKO mice
   were exposed to a dose of 2 Gy γ-irradiation, followed by flow
   cytometry analysis. D–G Graphs represent the cell count of different
   hematopoietic cell subsets in BM of mice (n = 5 mice per group). H Flow
   cytometry analysis of protein aggregate levels in HSCs
   (CD48^−CD150^+LSK) using ProteoStat staining. Right graph represents
   the MFI of ProteoStat in HSCs (n = 5 mice per group). I, J Graphs
   represent the MFI of p-IRE1 (I) and p-PERK (J) in HSCs
   (CD48^−CD150^+LSK) using flow cytometry staining and analysis (n = 5
   mice per group). K A graph represents the percentages of apoptotic HSCs
   (CD48^−CD150^+LSK) (n = 5 samples per group). L Representative flow
   plots of the Ki-67 and DAPI staining of HSCs (CD48^−CD150^+LSK).
   Emp1^fl/fl and Emp1-cKO mice were exposed to a dose of 2 Gy
   γ-irradiation, followed by flow cytometry analysis. Right graph
   represents the percentages of cell-cycle distribution of HSCs (n = 5
   mice per group). Statistical analyses were performed using log-rank
   test for 5B; two-tailed unpaired Student’s t-test for all other
   analyses. Data are shown as mean ± SD. Results are representative of
   two independent experiments. Source data are provided as a Source Data
   file.

Loss of Emp1 results in the accumulation of dhCer in HSCs

   To further investigate the underlying cause of protein aggregate
   accumulation in HSCs due to Emp1 deficiency, we performed an untargeted
   metabolomics analysis utilizing ultra-high-performance liquid
   chromatography-mass spectrometry (UHPLC-MS/MS) on sorted Emp1^fl/fl and
   Emp1-cKO HSCs. A total of 283 metabolites with MS/MS matching score
   >0.3 have been identified, revealing 33 differential metabolites
   between Emp1^fl/fl and Emp1-cKO HSCs (Variable Importance in the
   Project [VIP] > 1.0; p < 0.05) (Fig. [182]6A) (Supplementary
   Data [183]1). KEGG analysis of the metabolomics data indicated that the
   sphingolipid signaling pathway was significantly dysregulated between
   Emp1^fl/fl and Emp1-cKO HSCs (Fig. [184]6B). Sphingolipids are
   ubiquitous and essential components of all eukaryotic
   membranes^[185]36. Ceramide is the central component of all complex
   sphingolipids, including sphingomyelin and glycosphingolipids
   (Fig. [186]6C)^[187]37. Bioactive sphingolipid metabolites have been
   recognized as important molecular players in metabolic diseases, and
   perturbed sphingolipid metabolism contributes to HSC
   dysfunction^[188]38. Subsequent lipidomic analysis using UHPLC-MS/MS
   revealed a significant increase in dihydroceramides (dhCer),
   particularly dhCer (d18:0/24:1), in HSCs as a result of Emp1 deficiency
   (Fig. [189]6D) (Supplementary Data [190]2).

Fig. 6. Emp1 deficiency results in dhCer accumulation that induces the
formation of protein aggregates.

   [191]Fig. 6
   [192]Open in a new tab

   A A representative volcano plot of the metabolite content change
   between Emp1^fl/fl and Emp1-cKO HSCs (CD48^−CD150^+LSK) using
   untargeted metabolomic analysis (n = 5 samples per group). All
   significantly changed metabolites (Variable Importance in the Project
   [VIP] > 1.0; p < 0.05) are indicated by blue or red dots. B The KEGG
   analysis of the enrichment and classification of the significantly
   changed metabolites. C Summary of the sphingolipid metabolism. D
   Relative quantification of dihydroceramide (dhCer) and ceramide (Cer)
   levels in Emp1^fl/fl and Emp1-cKO HSCs (CD48^−CD150^+LSK) through
   lipidomic analysis (n = 4 samples per group). The box plot represents
   the minimum, median, and maximum values. E Experimental scheme for the
   assessment of the impact of dhCer(d18:0/24:1) on HSC function. HSCs
   (CD48^−CD150^+LSK) were isolated from wild-type C57BL/6J mice and
   treated with dhCer(d18:0/24:1) for 24 h, followed by flow cytometry
   analysis, colony-forming unit assay, and competitive transplantation
   assay. For competitive transplantation assay, 500 HSCs (CD45.2) were
   mixed with 1.5 × 10^6 competitor BM cells (CD45.1) and transplanted
   into recipient mice (CD45.1CD45.2). F Flow cytometry analysis of
   protein aggregate levels in HSCs using ProteoStat staining. Right graph
   represents the MFI of ProteoStat in HSCs (n = 5 samples per group). G A
   graph represents the colony numbers from dhCer-treated HSCs (n = 3
   samples per group). H Representative flow plots of the chimerism of PB
   from recipients at 1 and 4 months after transplantation. Donor-derived
   cells, CD45.2^+; competitor-derived cells, CD45.1^+. I The percentages
   of donor-derived cells in PB at indicated times (n = 5 recipients per
   group). J The percentages of donor-derived myeloid cells, B cells, and
   T cells in PB cells of recipient mice at 4 months after transplantation
   (n = 5 recipients per group). K The percentages of donor-derived BM
   cells, LK, LSK, and HSCs in BM of recipients at 4 months after
   transplantation (n = 5 recipients per group). All statistical analyses
   were performed using two-tailed unpaired Student’s t-test. Data are
   shown as mean ± SD. Results are representative of two independent
   experiments. Source data are provided as a Source Data file.

   The recent findings demonstrate that the ratio of protein to
   sphingolipids directly determines the rate of protein
   aggregates^[193]39. To explore the effect of dhCers on HSC function, we
   cultured murine HSCs (CD48^−CD150^+LSK) in vitro and introduced BODIPY
   TR C5-Ceramide into the medium for a duration of 30 min. Following this
   treatment, we observed pronounced red fluorescence in HSCs
   (Fig. [194]S8A), indicating that these cells can take up ceramide.
   Subsequently, we directly added dhCer(d18:0/24:1) to the culture medium
   of HSCs and assessed their function in vitro and in vivo
   (Fig. [195]6E). Our observations revealed that the addition of
   dhCer(d18:0/24:1) significantly increased the level of protein
   aggregates in HSCs in vitro (Fig. [196]6F), leading to a remarkable
   decrease in colony-forming capacity of HSCs (Fig. [197]6G).
   Furthermore, pre-treatment with dhCer(d18:0/24:1) substantially
   impaired the reconstitution capacity of HSCs, as evidenced by
   continuously decreased chimeric percentages of PB and BM cells in
   recipient mice compared to control group (Fig. [198]6H–K). These data
   collectively indicate that the loss of Emp1 leads to the accumulation
   of dhCer in HSCs. Furthermore, this accumulation of dhCer results in
   the formation of protein aggregates and adversely affects both in vitro
   and in vivo functions of HSCs.

EMP1 binds CERS2 to restrict dhCer production

   The increased production or decreased consumption of dhCers could
   result in dhCer accumulation, a process catalyzed by several enzymes
   (Fig. [199]7A)^[200]40. As EMP1 is located within the ER, we aimed to
   screen for EMP1-interacting proteins to uncover the exact mechanisms by
   which EMP1 restricts dhCer accumulation. We overexpressed EMP1 (with HA
   tag) in BM Lin^−c-Kit^+ cells derived from wild-type mice.
   Subsequently, we performed co-immunoprecipitation (co-IP) followed by
   mass spectrometry using IgG or HA antibodies (Fig. [201]7B). Compared
   to the group using IgG antibody, 336 proteins were pulled down by the
   HA antibody, suggesting potential EMP1-interacting partners. Among
   these proteins, it was observed that EMP1 might interact with ceramide
   synthase 2 (CERS2) (Fig. [202]7C). The complete list of interacting
   proteins can be found in Supplementary Data [203]3. There are six
   enzymes in the CERS family, which are located in the ER
   membrane^[204]41. CERS2 prefers to use C22–C24-CoAs for the N-acylation
   of dihydrospingosine, resulting in the production of C22–C24
   dhCers^[205]40. Considering the findings that Emp1 deficiency resulted
   in a significant increase in the accumulation of dhCer(d18:0/22:0),
   dhCer(d18:0/22:1), and dhCer(d18:0/24:1) (Fig. [206]6D), along with the
   observation that neither tunicamycin-induced ER stress nor Emp1
   deficiency had a notable impact on the mRNA levels of CERS2 in HSCs
   (Fig. [207]S8B), these results collectively suggest that EMP1 may limit
   dhCer accumulation by inhibiting CERS2 activity through protein
   interactions. To investigate this further, we overexpressed HA-EMP1 in
   BM Lin^−c-Kit^+ cells derived from wild-type mice. The interaction
   between EMP1 and CERS2 was confirmed through co-immunoprecipitation
   followed by immunoblot analysis (Fig. [208]7D). Additionally, an in
   situ proximity ligation assay (PLA) revealed that EMP1 physically
   interacted with CERS2 in HSCs (Fig. [209]7E).

Fig. 7. EMP1 binds the Lag1p domain of CERS2 to restrict dhCer production.

   [210]Fig. 7
   [211]Open in a new tab

   A Summary of the pathway of ceramide synthesis. B Experimental scheme.
   BM Lin^−c-Kit^+ cells derived from wild-type mice were infected with
   retrovirus to force EMP1 overexpression (with HA tag). Then IgG or HA
   antibodies were used to conduct co-immunoprecipitation (co-IP),
   followed by and mass spectrometry analysis. C Venn diagrams represent
   proteins pulled down by IgG or HA antibodies. D The interaction between
   EMP1 and CERS2. IgG, CERS2, or HA antibodies were used to conducted
   co-immunoprecipitation (co-IP), followed by immunoblot analysis. Bands
   representative of two independent experiments with similar results are
   shown. E In situ proximity ligation assay to detect EMP1/CERS2
   interaction in murine HSCs (CD48^−CD150^+LSK) by utilizing antibodies
   (rabbit anti-EMP1 and mouse anti-CERS2). Nuclei are stained with DAPI
   (blue). The scale bar represents 5 µm. F Molecular docking of EMP1
   (AlphaFold prediction: AF-[212]P47801-F1) and CERS2 (AlphaFold
   prediction: AF-[213]Q924Z4-F1) using ClusPro2.0 server. G Presentation
   of structure domains of EMP1 and CERS2, along with the design of CERS2
   mutations (indicated with red font). H The interaction between EMP1 and
   CERS2 is revealed by co-IP followed by immunoblot analysis. BM
   Lin^−c-Kit^+ cells were infected with retrovirus to express Flag-CERS2
   or Flag-mutant CERS2, together with HA-EMP1 overexpression, followed by
   co-IP. IgG antibody was used as the negative control. Bands
   representative of two independent experiments with similar results are
   shown. I Experimental schematic. J Flow cytometry analysis of protein
   aggregate levels in HSCs (CD48^−CD150^+LSK) using ProteoStat staining.
   Right graph represents the MFI of ProteoStat in HSCs (n = 5 mice per
   group). K Graphs represent the MFI of p-IRE1 (left) and p-PERK (right)
   in HSCs (CD48^−CD150^+LSK) using flow cytometry staining and analysis
   (n = 5 mice per group). L Representative flow plots of the LK
   (Lin^−Sca-1^−c-Kit^+), LSK (Lin^−Sca-1^+c-Kit^+), and HSC
   (CD48^−CD150^+LSK) populations in BM cells from mice. M–O Graphs
   represent the cell count of different hematopoietic cell subsets in BM
   of mice (n = 5 mice per group). All statistical analyses were performed
   using two-tailed unpaired Student’s t-test. Data are shown as
   mean ± SD. Results are representative of two independent experiments.
   Source data are provided as a Source Data file.

   To delve deeper into the molecular mechanism of interaction between
   EMP1 (AlphaFold prediction: AF-[214]P47801-F1) and CERS2 (AlphaFold
   prediction: AF-[215]Q924Z4-F1), we conducted a molecular docking assay
   and found an interaction between amino acid residues of EMP1 and the
   Tram-Lag-CLN8 (TLC) domain of CERS2, particularly within the Lag1p
   motif (Fig. [216]7G). It has been demonstrated that the Lag1p motif
   imparts acyl chain substrate specificity to the protein and is part of
   the catalytic domain of CERS2^[217]41. Furthermore, we forced
   expression of Flag-CERS2 or its mutant proteins—involving a total of 8
   mutations on amino acid residues within the laglp motif—in BM
   Lin^−c-Kit^+ cells derived from wild-type mice, along with HA-EMP1
   (Fig. [218]7G). The co-IP followed by immunoblot analysis confirmed the
   interaction between EMP1 and wild-type CERS2, but not with mutant CERS2
   (Fig. [219]7H). To further investigate the universality of the protein
   interaction between EMP1 and CERS2 in other cell types, we performed a
   PLA assay using HEK293T cells; however, we did not observe obvious
   interaction signal between EMP1 and CERS2 in HEK293T cells
   (Fig. [220]S8C). Furthermore, the knock-down of EMP1 did not result in
   a notable change in protein aggregation levels (Fig. [221]S8D, E) or ER
   stress response in HEK293T cells (Fig. [222]S8F), indicating that the
   EMP1-CERS2 axis is not universally applicable to various cell types.

   To determine whether the dysregulation of CERS2 activity in
   Emp1-deficient HSCs contributes to the impaired maintenance of HSCs, we
   administrated pIpC injection to induce Emp1 deletion and treated these
   mice with an inhibitor of CERSs, fumonisin B1 (FB1) (Fig. [223]7I). FB1
   efficiently reduced the level of protein aggregates in Emp1-deficient
   HSCs (Fig. [224]7J). Importantly, FB1 treatment partially abolished the
   increased levels of p-IRE1 and p-PERK in Emp1-deficient HSCs,
   indicating alleviated ER stress (Fig. [225]7K). Furthermore,
   FB-1-treated Emp1-deficient mice showed significant restoration in the
   numbers of BM cells, LK, LSK, and HSCs (CD48^−CD150^+LSK) compared with
   their DMSO-treated counterparts (Fig. [226]7L–O). These findings
   collectively suggest that EMP1 interacts with the enzyme CERS2 to
   restrict dhCer accumulation, thereby constraining ER stress and
   preserving HSC maintenance.

Emp1 overexpression or CERS2 inhibition protects HSCs against IR-induced
injury

   To further evaluate whether overexpression of EMP1 protects HSCs
   against IR-induced injury, we enforced the expression of Emp1 in
   wild-type HSCs (CD48^−CD150^+LSK) and subjected these transduced cells
   to a dose of 2 Gy IR followed by a competitive transplantation assay
   (Fig. [227]8A). Flow cytometry analysis demonstrated that irradiated
   HSCs exhibited less than 10% chimerism in PB and BM of recipient mice.
   However, in contrast, overexpression of Emp1 substantially enhanced the
   engraftment capacity of IR-treated HSCs, as evidenced by the gradually
   increased donor-derived cells in PB and BM (Fig. [228]8B–D).

Fig. 8. Emp1 overexpression or CERS2 inhibition protects HSCs against
IR-induced injury.

   [229]Fig. 8
   [230]Open in a new tab

   A Experimental schematic. HSCs from wild-type C57BL/6J mice were
   infected with retrovirus to force Emp1 overexpression, followed by a
   dose of 2 Gy γ-irradiation. Two hours after radiation exposure, a
   competitive transplantation assay was conducted in which IR-treated
   HSCs were used. B The percentages of donor-derived cells in PB at
   indicated times (n = 5 recipients per group). C The percentages of
   donor-derived myeloid cells, B cells, and T cells in PB cells of
   recipient mice at 4 months after transplantation (n = 5 recipients per
   group). D The percentages of donor-derived BM cells, LK, LSK, and HSCs
   in BM of recipients at 4 months after transplantation (n = 5 recipients
   per group). E Experimental scheme. HSCs from wild-type C57BL/6J mice
   were treated with DMSO or fumonisin B1 (10 μM) for 24 h, followed by a
   dose of 2 Gy γ-irradiation. Two hours after radiation exposure, a
   competitive transplantation assay was conducted in which IR-treated
   HSCs were used. Additionally, another group of HSCs was cultured for
   24 h post-irradiation, followed by flow cytometry analysis. F Flow
   cytometry analysis of protein aggregate levels in HSCs
   (CD48^−CD150^+LSK) using ProteoStat staining. Right graph represents
   the MFI of ProteoStat in HSCs (n = 5 mice per group). G Graphs
   represent the MFI of p-IRE1 (left) and p-PERK (right) in HSCs
   (CD48^−CD150^+LSK) using flow cytometry staining and analysis (n = 5
   mice per group). H The percentages of donor-derived cells in PB at
   indicated times (n = 5 recipients per group). I The percentages of
   donor-derived myeloid cells, B cells, and T cells in PB cells of
   recipient mice at 4 months after transplantation (n = 5 recipients per
   group). J The percentages of donor-derived BM cells, LK, LSK, and HSCs
   in BM of recipients at 4 months after transplantation (n = 5 recipients
   per group). K A proposed model scheme represents the roles and
   molecular mechanisms of EMP1 safeguarding HSCs via CERS2-mediated
   sphingolipid metabolism. All statistical analyses were performed using
   two-tailed unpaired Student’s t-test. Data are shown as mean ± SD.
   Results are representative of two independent experiments. Source data
   are provided as a Source Data file.

   Given that EMP1 primarily interacts with CERS2, we hypothesized that
   the inhibition of CERS2 could protect HSCs from IR exposure. To explore
   this hypothesis, HSCs (CD48^−CD150^+LSK) derived from wild-type mice
   were treated with FB1 (10 μM) for 24 h to inhibit CERS2 activity.
   Subsequently, the HSCs were exposed to a dose of IR (2 Gy), and after
   24 h, they were analyzed by flow cytometry for phenotypic
   characterization or transplanted into recipient mice (Fig. [231]8E).
   Our findings indicated that the inhibition of CERS2 partially mitigated
   HSC defects under IR conditions, as evidenced by reduced levels of
   protein aggregates (Fig. [232]8F) and markers related to ER stress
   response, including phosphorylated IRE1 and PERK proteins
   (Fig. [233]8G). For the competitive transplantation assay, it was
   observed that IR treatment significantly reduced the chimeric
   percentages of donor-derived PB, BM cells, LSK, and HSCs in recipient
   mice compared to the non-IR-treated group. The administration of FB1
   did not significantly impact the reconstitution capacity of HSCs that
   were not subjected to IR treatment. Encouragingly, it markedly enhanced
   the reconstitution capacity of IR-treated HSCs in recipient mice
   (Fig. [234]8H–J). These findings collectively demonstrate that Emp1
   overexpression or CERS2 inhibition effectively protects HSCs against
   IR-induced injury. These findings highlight the critical role played by
   the EMP1-CERS2-dhCers axis in constraining ER stress and preserving HSC
   potential (Fig. [235]8K).

Discussion

   EMP1 has been identified as a prognostic factor in MDS^[236]18 and
   AML^[237]19, as well as a stemness-related gene in LSCs^[238]20,
   suggesting the crucial functions of EMP1 in leukemogenesis. In addition
   to its role in leukemia, EMP1 is highly expressed in several cancers
   and regulates their proliferation, migration, and stemness^[239]16.
   EMP1^+ cells are responsible for the metastatic recurrence in
   colorectal cancer^[240]17. It has been reported that EMP1 regulates the
   PI3K-AKT signaling in gliomas cells^[241]42 and the gastric cancer
   cells^[242]43, and activates MAPK pathway in ovarian cancer
   cells^[243]44. However, the exact molecular function of EMP1 in cells
   has long been unknown. Here, we have identified a previously
   unrecognized role for EMP1 in the maintenance and self-renewal of HSCs.
   Deletion of Emp1 leads to quiescence exit and apoptosis of HSCs,
   exhaustion of the HSC pool and eventually defective hematopoiesis.
   Mechanistically, EMP1 localizes to the ER in HSCs and directly binds
   CERS2 to restrict dhCer production. HSCs are susceptible to dhCer
   accumulation, which impairs HSC function by inducing protein
   aggregation and ER stress. Therefore, EMP1 safeguards HSC function by
   constraining ER stress. This study uncovers the precise localization
   and molecular function of EMP1. Further investigation is needed to
   determine whether the EMP1-CERS2-sphingolipid metabolism-ER stress
   pathway exists in other cell types, particularly in leukemia cells.

   To ensure the long-term health of HSCs, it is crucial to maintain
   protein homeostasis^[244]45. HSCs rely on unique strategies to
   precisely regulate the process of protein synthesis, folding, and
   quality control^[245]46. In comparison to other hematopoietic cells,
   HSCs exhibit the lowest rate of protein synthesis, even under
   conditions of cell division^[246]47. To achieve diverse functions,
   proteins fold into specific enabling structures or ensembles. However,
   this process inevitably causes protein misfolding, leading to the
   generation of protein aggregates and resulting in ER stress. The
   SEL1L-HRD1 complex, which is the most conserved branch of ER-associated
   degradation, is highly expressed in HSCs, indicating its efficiency in
   degrading misfolded proteins^[247]13. Additionally, it has been
   reported that HSCs preferentially traffic misfolded proteins to
   aggresomes and depend on aggrephagy to maintain protein
   homeostasis^[248]46. This study defines that the production of dhCers
   in the ER is restricted to prevent the accumulation of protein
   aggregates in HSCs. Thus, we uncover an unrecognized proteostasis
   mechanism to safeguard the HSC pool through sphingolipid metabolism,
   along with mechanisms for constraining protein synthesis and degrading
   misfolded proteins. Although the maintenance of HSCs requires a
   low-dose ER stress response, both intrinsic and extrinsic signaling
   often lead to elevated ER stress, ultimately impairing HSC
   function^[249]11. The loss of CHOP, a factor that induces cell death in
   response to ER stress, significantly improves the repopulation capacity
   of HSCs^[250]48. Additionally, deletion of transmembrane protein 166, a
   downstream factor of CHOP, efficiently enhances the regeneration
   capacity of HSCs by inhibiting ER stress-induced apoptosis^[251]49.
   HSCs rely on several critical factors to constrain ER stress. For
   example, hypoxia-inducible factor 2α (HIF-2α) protects HSCs by reducing
   ROS and ER stress^[252]50, while the RNA binding protein Dppa5 is
   highly expressed in HSCs and improves their function by reducing ER
   stress^[253]51. In this study, we found that loss of Emp1 resulted in
   the accumulation of dhCer and increased ER stress in HSCs. This
   suggests a protective role for EMP1 in HSCs by constraining ER stress.
   Together, these findings suggest a complex network within HSCs that
   constrains ER stress involving factors such as HIF-2α, Dppa5, and EMP1.
   The interplay or coordination between these factors needs to be further
   clarified.

   Sphingolipids are a diverse group of structurally complex lipids, and
   maintaining sphingolipid homeostasis is crucial for the proper function
   of HSCs^[254]36. The loss of serine palmitoyltransferase (SPT)
   long-chain base subunit 1 (SPTLC1), which catalyzes the initial and
   rate-limiting step in sphingolipid biosynthesis, leads to the
   accumulation of fatty acids and subsequent ER stress in HSPCs^[255]38.
   Sphingolipid delta4-desaturase (DEGS1) is an ER-membrane-spanning
   protein that serves as the final enzyme in de novo sphingolipid
   synthesis, converting dhCers to Cers^[256]41. Knock-down of DEGS1 in
   human cord blood stem cells results in an increased ratio of
   dhCers/Cers and ultimately impairs the reconstitution capacity of
   HSPCs^[257]52, indicating that timely conversion of dhCers to Cers is
   essential for HSPC homeostasis. Given the higher expression of DEGS1
   and lower levels of dhCers in HSCs compared to hematopoietic progenitor
   cells and mature cells^[258]52, it appears that HSCs particularly
   require low levels of dhCers. Recent research has identified
   sphingolipids as critically important bioactive substances. Very long
   chain ceramides (VLC Cers) are significant contributors to inflammation
   and directly regulate the nuclear translocation of key immune-related
   transcription factor REL. A hypothesis has been proposed suggesting
   that “the pool size of VLC Cers may directly regulate REL
   activity.”^[259]53. A more direct finding indicates that, compared to
   conditions without the addition of Cers, the presence of a 1:1 ratio of
   protein to Cers significantly increases the level of protein
   aggregation^[260]39. These findings suggest that sphingolipids directly
   alter the properties and functions of proteins. In this study, we
   demonstrate that dhCers are bioactive molecules. Their accumulation
   leads to protein aggregation and ER stress in HSCs. DhCers within the
   ER may directly interact with proteins in the ER lumen, hindering their
   proper folding and leading to the formation of protein aggregates,
   which ultimately results in excessive ER stress. These findings expand
   our understanding of how sphingolipid metabolism regulates HSC
   homeostasis and reveal an unrecognized source of ER stress—namely,
   accumulation of dhCers.

   CERS2 is the most abundantly expressed member of the CERS gene family,
   responsible for mediating N-acylation of dihydrospingosine to form
   dhCers^[261]54. The activity of CERS2 supports various biological
   functions, including the maintenance of myelin, stabilization of the
   cerebellar, protection against hepatocarcinomas^[262]54, maintenance of
   colonic macrophage populations^[263]53, and muscle homeostasis^[264]55.
   The precise regulation of CERS2 activity largely depends on partner
   interaction. Acyl-coenzyme A-binding protein (ACBP) binds long-chain
   and very-long-chain acyl-CoA esters to increase the activity of
   CERS2^[265]56. BCL2-like 13 (BCL2L13) protein has been shown to bind
   CERS2 and inhibit its activity in glioblastoma^[266]57. In this study,
   we have identified EMP1 as a CERS2 inhibitor through direct binding to
   the Lag1p domain of CERS2 in murine Lin^−c-Kit^+ cells, suggesting cell
   type specificity in terms of CERS2 partners. Moreover, we observed an
   accumulation of C22–C24-dhCers, which are products generated by CERS2,
   in HSCs. There are six enzymes in the CERS family, namely CERS1-6, each
   with a specific preference for the length of acyl-CoA chain used for
   Cer synthesis^[267]37. Based on these findings, further assessment is
   required to determine whether other types of CERS (1, 3–6) and
   downstream dhCers (C18-C22- and C26-dhCers) impact the protein
   homeostasis of HSCs.

   Preserving and improving the potential of HSCs for clinical use has
   long been a challenge^[268]58. Exposure to high doses of IR can induce
   long-term BM suppression, but there are limited efficient strategies to
   protect HSCs^[269]25,[270]26. Increased ER stress has been observed in
   HSCs during hematopoietic stress^[271]49. In this study, we have
   demonstrated that suppressing ER stress efficiently improves HSC
   potential and protects HSCs against IR-induced injury. HSCs primarily
   reside in the BM under hypoxic conditions^[272]8, and in vitro culture
   and IR often result in ROS production in HSCs^[273]59. It is possible
   that elevated ROS levels lead to ER stress in HSCs under in vitro
   culture and IR conditions. Given that several targets have been
   identified to preserve HSC function under various
   conditions^[274]60,[275]61, it is appealing to develop collaborative
   strategies aimed at enhancing HSC potential, along with EMP1-CERS2
   targets.

Methods

Resources

   All the reagents and resources, including antibodies, chemicals, and
   commercial kits, can be found in Supplementary Table [276]1.

Mice

   Wild-type (WT), Emp1^fl/+, Tie2-Cre, and Mx1-Cre were obtained from the
   Cyagen and on C57BL/6J background (CD45.2). The B6.SJL (CD45.1) were
   also obtained from the Cyagen. To achieve inducible or tissue-specific
   deletion of Emp1, Emp1^fl/fl mice aged 8–12 weeks were crossbred with
   Mx1-Cre or Tie2-Cre mice. All genotyping primers are detailed in
   Supplementary Table [277]2. The Emp1^fl/fl, Mx1-Cre cohort received
   polyinosinic:polycytidylic acid (pIpC) (GE Healthcare) injections at a
   dosage of 10 mg/kg every other day for a total of three administrations
   to induce Cre recombinase expression. CD45.1CD45.2 mice were generated
   by the crossbreeding of B6.SJL (CD45.1) mice with C57BL/6J (CD45.2)
   mice. Age- and sex-matched littermates served as controls for all
   experimental procedures. All mice utilized in the experiments comprised
   a mix of both male and female subjects. At the time of experimentation,
   10–12-week-old mice were randomly assigned to various experimental
   groups. All animals were housed under specific pathogen-free conditions
   and group-housed in a temperature-controlled environment (23 °C) on a
   12 h (h) light/dark cycle with ad libitum access to standard rodent
   chow (Keao Xieli Feed Co., Ltd) at the Experimental Animal Center of
   Chongqing Medical University. The ambient humidity was maintained at
   40–60%. All procedures received approval from the Institutional Animal
   Care and Use Committee at Chongqing Medical University.

Human cord blood CD34+ cells

   Human donor samples were obtained with informed consent at the First
   Affiliated Hospital of Chongqing Medical University in congruence with
   the protocol approved by the Medical Ethics Committee of Chongqing
   Medical University (#2025-014). Cord blood samples were subjected to
   blood cell lysis buffer (Solarbio) to remove red blood cells.
   Subsequently, hematopoietic progenitor cells were enriched using the
   EasySep™ Human Progenitor Cell Enrichment Kit II (STEMCELL
   Technologies). Then the enriched cells were then incubated with an
   anti-CD34 antibody (BioLegend), followed by sorting of CD34^+ cells via
   flow cytometry.

Cell lines

   HEK293T cells were cultured in DMEM (Hyclone), containing 10% FBS
   (Hyclone) and 1% penicillin/streptomycin (Solarbio).

Primary cell culture

   Human cord blood CD34^+ cells were cultured in IMDM medium (Hyclone)
   supplemented with the following components: 10% human serum (Gemini),
   1 × penicillin/streptomycin, 100 ng/mL SCF, 20 ng/mL FLT3L, and
   10 ng/mL IL-7 (Beyotime). Murine Lin^− cells were enriched using the
   EasySep™ Mouse Hematopoietic Progenitor Cell Isolation Kit (STEMCELL
   Technologies). Murine Lin^−c-kit^+ cells, LSK cells
   (Lin^−Sca-1^+c-kit^+), and HSCs (CD48^−CD150^+LSK) were sorted by flow
   cytometry. These sorted cells were cultured in IMDM medium supplemented
   with 10% FBS (STEMCELL Technologies), 1 × penicillin/streptomycin,
   0.05 mM 2-mercaptoethanol, 100 ng/mL SCF, 10 ng/mL IL-3, and 10 ng/mL
   IL-6 (Beyotime).

γ-Irradiation

   For cell irradiation, the cells were cultured in 96-well plates and
   subjected to a single dose of 2 or 5 Gy γ-irradiation using a
   ^60Coγ-ray generator (Radiation Center, Department of Preventive
   Medicine, Third Military Medical University, China) at approximate dose
   rates of 92.8-95.5 cGy/min. For mice irradiation, mice were subjected
   to a single dose of 2, 5, 7.5, or 9 Gy γ-irradiation (whole-body) using
   a ^60Co γ-ray generator at approximate dose rates of 92.8-95.5 cGy/min.

Drug and dhCer treatment

   In vitro, HSCs were cultured with azoramide (15 μM, Selleck),
   tunicamycin (5 μM, MCE) or fumonisin B1 (10 μM, Aladdin) for indicated
   times. For dhCer treatment, HSCs were cultured with different
   concentrations of C24:1 Dihydroceramide (d18:0/24:1(15Z))
   (Sigma-Aldrich). To induce an acute ER stress in mice, C57BL/6J mice
   were intraperitoneally injected with a dose of tunicamycin (2 mg/kg).
   For rescue experiments, Emp1^fl/fl and Emp1^fl/fl, Mx1-Cre mice were
   injected with pIpC (10 mg/kg, every other day, thrice) to induce Emp1
   deletion, followed by fumonisin B1 (FB1) injection (2 mg/kg,
   thrice/week) for two weeks. All the chemical reagents were dissolved in
   DMSO and their details can be found in Supplementary Table [278]1.

Plasmids and virus production

   To knock down EMP1, we designed shRNA oligonucleotides (Supplementary
   Table [279]1) and cloned them into the pLKO.1-puro-CMV-GFP vector. For
   the generation of vectors expressing HA-Emp1, Flag-Cers2, and mutant
   Cers2, the coding sequences (CDS) were synthesized by Tsingke and then
   cloned into the pMSCV-GFP vector. HEK293T cells (ATCC, CRL-3216) were
   utilized for virus production; these cells were transfected with
   lentiviral or retroviral plasmids along with helper plasmids.
   Supernatants were collected 48- and 72-h post-transfection, filtered
   through a 0.22 μm membrane, and concentrated using an Amicon® Ultra-15
   10 K (Millipore). For in vitro viral infection of hematopoietic cells,
   spin infection was performed at 250 g at room temperature for 2 h in
   the presence of polybrene (8 µg/mL).

Colony-forming unit (CFU) assay

   Approximately 100 to 300 HSCs characterized as CD48^−CD150^+LSK were
   cultured in either 12-well or 6-well culture plates, respectively,
   using Methylcellulose Complete Media M3434 (STEMCELL Technologies).
   Following an incubation period of 7 to 10 days, the colonies of
   granulocytes, erythroid cells, macrophages, and megakaryocytes were
   enumerated. The cells obtained from the initial culture cycle were
   subsequently collected and re-seeded into a new culture dish.

Transplantation assay

   For non-competitive transplantation assay, a total of 500 HSCs
   (CD48^−CD150^+LSK) from donor mice (CD45.2) were transplanted into
   lethally irradiated recipient mice (CD45.1). Two months
   post-transplantation, the recipient mice were sacrificed for analysis.
   For the competitive transplantation assay utilizing BM cells,
   1.5 × 10^6 BM cells from Emp1^fl/fl or Emp1^fl/fl, Mx1-Cre mice
   (CD45.2) were transplanted into lethally irradiated (9.0 Gy) recipient
   mice (CD45.1), along with 1.5 × 10^6 competitive BM cells from
   wild-type mice (CD45.1CD45.2). One month post-transplantation, the
   recipient mice were administered intraperitoneal injections of 10 mg/kg
   pIpC three times to induce the deletion of Emp1. After a duration of
   four months, 2 × 10^6 chimeric BM cells from the primary recipients
   were subsequently transplanted into the second recipient mice. For
   competitive transplantation assay utilizing HSCs, a total of 500 HSCs
   (CD48^−CD150^+LSK) obtained from donor mice (CD45.2) were mixed with
   competitor BM cells (1.5 × 10^6) from wild-type mice (CD45.1CD45.2),
   and this mixture was then transplanted into lethally irradiated
   (9.0 Gy) recipient mice (CD45.1). After a duration of four months,
   2 × 10^6 chimeric BM cells from the primary recipients were
   transplanted into the second recipient mice. The chimerism was analyzed
   monthly using anti-mouse CD45.1 and anti-mouse CD45.2 antibodies, along
   with various cell surface markers.

In vivo limiting dilution assay

   5 × 10^3, 1 × 10^4, 5 × 10^4, and 1 × 10^5 BM cells from Emp1^fl/fl or
   Emp1^fl/fl,Tie2-Cre mice (CD45.2) were transplanted into lethally
   irradiated CD45.1 mice, along with 5 × 10^5 competing BM cells from
   CD45.1CD45.2 mice. A cell dose was considered to contain at least one
   competitive repopulation unit if donor engraftment in the BM of
   recipient mice exceeded 1% of both lymphoid and myeloid lineages at 12
   weeks post-transplantation. Extreme limiting dilution analysis is a
   coherent approach to limiting dilution analysis which includes extreme
   data situations, multiple populations and non-Poisson
   situations^[280]62. The HSC frequency was calculated and the
   log-fraction plot was generated using extreme limiting dilution
   analysis ([281]https://bioinf.wehi.edu.au/software/elda/).

Flow cytometric analysis and cell sorting

   All utilized antibodies can be found in the Supplementary Table [282]1.
   Cell suspensions from PB, spleen, thymus, and BM were harvested. To
   analyze myeloid differentiation, cells were stained with fluorescent
   dye-labeled antibodies, including antibodies anti-Gr-1, anti-Mac,
   anti-Ter119, anti-CD71, anti-IgM, anti-B220, anti-CD8a, and anti-CD4.
   When analyzing HSPCs, staining with biotin-conjugated antibodies
   (lineage antibodies) was performed, followed by staining with
   anti-Streptavidin-PE/Cyanamide5 and fluorescent dye-labeled antibodies.
   The following are cell surface markers for different populations: Lin^−
   cells (Gr-1^-Ter119^−B220^−CD19^−Rat IgM^−IL-7R^−CD3ε^−), LK cells
   (Lin^−Sca-1^−c-kit^+), LSK cells (Lin^−Sca-1^+c-kit^+), ST-HSCs
   (CD34^+CD135^−LSK), HSCs (CD48^−CD150^+LSK or CD34^−CD135^−LSK), MPP
   (CD34^+CD135^+LSK), LMPP (CD135^highLSK), CMP
   (Lin^−Sca-1^−c-kit^+CD16/32^medCD34^+), GMP
   (Lin^−Sca-1^−c-kit^+CD16/32^+CD34^+), and MEP
   (Lin^−Sca-1^−c-kit^+CD16/32^−CD34^−). The characterization of cell
   populations can be found in the Supplementary Table [283]3. Flow
   cytometric detection was conducted using a BD FACS Canto II (BD
   Biosciences), and all data were analyzed using FlowJo 10.0 Software
   (TreeStar). Cell sorting was performed using a BD FACS Aria^TMIII (BD
   Biosciences).

5-FU treatment

   5-FU (150 mg/kg, Sigma) was administered to mice via intraperitoneal
   injection once a week for a duration of three weeks. The survival of
   each individual mouse was monitored daily.

Cell cycle and apoptosis analysis

   All utilized antibodies can be found in the Supplementary Table [284]1.
   For the cell cycle analysis of HSCs, BM cells were harvested from mice,
   labeled with specific cell surface markers as previously described, and
   subsequently fixed and permeabilized using the Cytofix/Cytoperm™
   Fixation/Permeabilization Kit (BD Biosciences). HSCs were then stained
   with Ki-67 FITC (1:50) and DAPI (5 µg/mL), followed by flow cytometric
   analysis. For apoptosis assessment of HSCs, BM cells from mice were
   collected, stained with cell surface markers, and subsequently treated
   with Annexin-V APC (1:20) and DAPI (0.5 µg/mL), followed by flow
   cytometric analysis.

Quantification of aggregated proteins

   The aggregated protein levels of HSCs were analyzed using the
   ProteoStat Staining Kit (Enzo Life Sciences). The ProteoStat dye
   functions as a molecular rotor. In solution, free intramolecular
   rotation along a single central bond prevents fluorescence. The
   ProteoStat dye specifically intercalates into the cross-beta spine of
   quaternary protein structures typically found in misfolded and
   aggregated proteins, which will inhibit the dye’s rotation and lead to
   a strong fluorescence. BM cells from mice were collected and stained
   with cell surface markers as previously described. Subsequently,
   fixation and permeabilization were performed using the
   Cytofix/Cytoperm™ Fixation/Permeabilization Kit (554714, BD
   Biosciences), following the manufacturer’s instructions. Fixed cells
   were then stained with a 1:10,000 dilution of ProteoStat dye in
   permeabilization solution for 30 min. Then, the cells were washed with
   FACS buffer prior to flow cytometric analysis.

RNA extraction and quantitative RT-PCR (qRT-PCR) analysis

   Total RNA was extracted from FACS-sorted cells using an miRNeasy Mini
   Kit (QIAGEN) according to the manufacturer’s instructions. Then, total
   RNA was reverse transcribed using the PrimeScript^TM RT reagent Kit
   with gDNA Eraser (Takara). PCR reactions were conducted using 2×
   Universal SYBR Green Fast qPCR Mix (Takara). The relative expression of
   each gene was normalized to actin and quantified using the 2^−ΔΔCT
   methods. Each reaction was performed in triplicate. Primer sequences
   are provided in Supplementary Table [285]2.

Immunoprecipitation assays and western blot

   Immunoprecipitation was conducted utilizing the Immunoprecipitation Kit
   with Protein A + G Agarose Gel (Beyotime). The products obtained from
   co-immunoprecipitation were subsequently analyzed through proteomics
   and western blotting. For the western blot analysis, cells were lysed
   using RIPA lysis buffer (1× PBS, 1% NP-40, 0.1% SDS, 0.5% sodium
   deoxycholate, 1 mM EDTA), and the resulting protein extracts were
   subjected to electrophoresis on polyacrylamide gels before being
   transferred to nitrocellulose membranes. Following a one-hour
   incubation in blocking buffer at room temperature, the membranes were
   incubated overnight at 4 °C with the appropriate antibodies. The
   antibodies employed in this study are detailed in Supplementary
   Table [286]1. All antibodies were utilized at a dilution ratio of
   1:1000. The HRP-conjugated secondary antibodies used included goat
   anti-rabbit or goat anti-mouse (dilution of 1:1000). The ER was
   isolated using a Reagent Kit for Protein Extraction from the ER
   (Solarbio), in accordance with the manufacturer’s instructions.

Immunofluorescence assay

   The HSCs (CD48^−CD150^+LSK) were sorted and evenly spread on a glass
   slide coated with poly-lysine, followed by fixed with 4%
   paraformaldehyde (PFA) at room temperature for 30 min, permeabilized
   with 0.1% Triton X-100 for 5 min, and blocked with 5% goat serum at
   room temperature for 1 h. Dilutions of anti-Emp1 (bs-0558R, Bioss) and
   anti-Calreticulin ([287]A27115, Abclonal) antibodies were prepared in
   accordance with the manufacturer’s instructions using 5% goat serum.
   These dilutions were then applied to the glass slide and incubated
   overnight at 4 °C. Then the slides were incubated with secondary
   antibodies conjugated to ABflo®488 (AS053, Abclonal) and ABflo®594
   (AS054, Abclonal). The cell nuclei were stained with DAPI (D8417,
   Sigma-Aldrich), after which they were analyzed using fluorescence
   microscopy.

Dulink proximity ligation assay (PLA)

   Duolink PLA was performed according to the manufacturer’s instructions
   (DUO92101, Sigma-Aldrich). The HSC suspension obtained by sorting was
   evenly spread on a glass slide coated with poly-lysine, fixed with 4%
   PFA at room temperature for 20 min, permeabilized with 0.1% Triton
   X-100 for 5 min. Cells were then blocked in 5% BSA and incubated with
   primary antibodies (rabbit anti-EMP1 and mouse anti-CERS2). After
   washing the cells, PLA probes were added, followed by hybridization,
   ligation, and amplification for 90 min at 37 °C. Finally, cells were
   incubated with the detection solution and visualized by fluorescence
   microscopy.

Molecular docking

   The three-dimensional structure PDB files of EMP1 (AF-[288]P47801-F1
   predicted by AlphaFold) and CERS2 (AF-[289]Q924Z4-F1 predicted by
   AlphaFold) were submitted to the ClusPro 2.0 server for protein-protein
   docking prediction. The optimal model was selected from the predicted
   results and displayed using the molecular visualization tool PyMOL 2.6.

scRNA-seq data analysis

   The scRNA-seq datasets of BM cells derived from five healthy donors,
   with associated cell annotation information, were collected from the
   Gene Expression Omnibus (GEO) database ([290]GSE116256)^[291]31. R
   package Seurat (version 5.0.1) was employed for clustering and
   differential expression analysis was conducted with the built-in
   FindMarkers function.

RNA-seq and data analysis

   HSCs (CD48^−CD150^+LSK) were directly sorted into TRIzol-LS (Thermo
   Fisher Scientific), at a density of approximately 500–1000 cells per
   sample^[292]63. Total RNA was extracted using the miRNeasy kit
   (QIAGEN). The mRNA was reverse transcribed and amplified following the
   Geo-seq method, and the library was constructed using the TruePrep DNA
   Library Preparation Kit V2 (Vazyme) according to the manufacturer’s
   instructions. The library was sequenced using the Illumina NovaSeq 6000
   platform, with sequencing comprising 150-bp of paired-end reads. For
   data processing, RNA-seq reads were aligned to the mm10 using Hisat2.
   Aligned reads were counted with HTSeq (a Python framework to work with
   high-throughput sequencing data). Fragments per kilobase per million
   estimation was performed with Cufflinks v2.1.1. Differential expression
   analysis was performed with limma-voom pipeline in R. Differentially
   expressed genes were selected using a cutoff P value of <0.05 (false
   discovery rate adjusted for multiple testing). The volcano of gene
   expression was plotted using R. GSEA was performed using GSEA software
   (v4.1.0) ([293]http://www.broadinstitute.org/gsea) with 1000
   permutations.

ATAC-sequence and data processing

   Briefly, approximately 5000 HSCs (CD48^−CD150^+LSK) were sorted into EP
   tubes and kept on ice. The cells were lysed with a lysis buffer
   prepared as follows: 10 mM Tris-HCl, 10 mM NaCl, 3 mM MgCl[2], and 0.1%
   IGEPAL CA-630^[294]63. The nuclei were collected following
   centrifugation at 4 °C. The DNA fragmentation mix was prepared
   according to the instructions provided with the Novoprotein Chromatin
   Profile Kit for Illumina (Novoprotein). The reaction was conducted
   using a PCR instrument at 37 °C for 30 min, after which the DNA
   fragmentation products were recovered and purified. PCR amplification
   was performed following the instructions provided with the Novoprotein
   NovoNGS® Index Kit for Illumina® (Novoprotein). The number of
   amplification cycles was precisely adjusted based on the cell number.
   The PCR products were subsequently purified and recovered using
   Novoprotein DNA Clean Beads (Novoprotein). Finally, the library
   concentration was assessed using Qubit (Thermo Fisher Scientific), and
   the library distribution was evaluated using the Agilent 2100.
   Libraries were sequenced by the Illumina NovaSeq 6000 platform as
   150-bp pair-ended reads.

   For data processing, low-quality reads and adaptor sequences were
   removed by Trim Galore v0.4.4 with parameters “-q 10 -length 30
   -stringency 5′”. Paired-end reads were mapped to the mm10 reference
   genome using BWA. Reads that aligned to the mitochondrial genome were
   filtered, and PCR duplicates were removed with sambamba-markdup. To
   identify peaks, the bam files containing unique, nonchrM reads were
   used to call peaks with MACS2 using parameters
   “–nomodel–shift-100–extsize 200”. For differential coverage,
   corresponding bam files were merged to call peaks to get a union peak
   set. For each peak in the peak set, raw ATACseq reads were counted by
   featureCounts. Differentially expressed peaks were identified by at
   least a 1.5-fold change and false discovery rate adjusted P value of
   0.01. The deepTools compute matrix (reference point) function was used
   to calculate the ATAC signal and create heat maps; the volcano of
   differentially expressed peaks and violin plots of the ATAC signal
   (log2(normalized RPKM)) at specified regions were plotted using R. A
   Student’s t-test was used to test the significance. The Integrative
   Genomics Viewer tool was used for visualizing the ATAC-seq data.

UHPLC-MS/MS-based untargeted metabolomics

   For untargeted metabolomics, approximately 50,000 HSCs
   (CD48^−CD150^+LSK) were sorted and were rapidly frozen in liquid
   nitrogen for 30 s and stored at −80 °C until use. The UHPLC-MS/MS-based
   untargeted metabolomics analysis was conducted by BIOTREE Biomedical
   Technology (Shanghai, China). An extract solution of 1000 μL (methanol:
   acetonitrile: water = 2:2:1, containing an isotopically labeled
   internal standard mixture) was added to the samples. Subsequently, the
   samples underwent three freeze-thaw cycles using liquid nitrogen. They
   were then sonicated for 10 min in an ice-water bath. Following this
   step, the samples were incubated for one hour at −40 °C and centrifuged
   at 10,000 × g for 15 min at a temperature of 4 °C. The resulting
   supernatant was transferred to a fresh glass vial for subsequent
   analysis. LC-MS/MS analyses were performed utilizing a Vanquish UHPLC
   system (Thermo Fisher Scientific), equipped with a UPLC BEH Amide
   column (2.1 mm × 100 mm; particle size: 1.7 μm), coupled to an Orbitrap
   Exploris 120 mass spectrometer (Thermo Fisher Scientific). The mobile
   phase comprised of aqueous solutions containing ammonium acetate and
   ammonia hydroxide at a concentration of 25 mmol/L each (pH = 9.75) as
   component A and acetonitrile as component B. The auto-sampler
   temperature was maintained at 4 °C with an injection volume set to
   2 μL. MS/MS spectra were acquired on information-dependent acquisition
   mode in the acquisition software (Xcalibur, version 4.2 SP1). ESI
   source conditions were established as follows: sheath gas flow rate set
   to 50 Arb; auxiliary gas flow rate set to 15 Arb; capillary temperature
   maintained at 320 °C; full MS resolution configured at 60,000; MS/MS
   resolution set to 15,000; collision energy adjusted to 10/30/60 in NCE
   mode; spray voltage applied at 3.8 kV (for positive ionization) or
   −3.4 kV (for negative ionization), respectively.

   The raw data were converted to the mzXML format using ProteoWizard and
   subsequently processed with an in-house program developed in R, which
   is based on XCMS for peak detection, extraction, alignment, and
   integration. An internal MS2 database (BiotreeDB) was utilized for
   metabolite annotation. In this study, 7388 peaks were detected and 7381
   metabolites were left after relative standard deviation de-noising. An
   internal standard normalization method was utilized in the analysis of
   this data. The final dataset, as detailed in Supplementary Data [295]1,
   which includes the sample names and normalized peak areas, was imported
   to SIMCA16.0.2 software package for multivariate analysis. Metabolites
   with MS/MS matching score (MS2 score) > 0.3 were included for
   subsequent analysis, with a total of 283 annotated MS/MS metabolites.
   To visualize group separation and find significantly changed
   metabolites, orthogonal projections to latent structures-discriminant
   analysis (OPLS-DA) were conducted using a permutation test in SIMCA
   16.0.2 software. The value of variable importance in the projection
   (VIP) of the first principal component in OPLS-DA analysis was
   obtained. The metabolites with VIP > 1 and p < 0.05 (Student’s t-test)
   were considered as significantly changed metabolites. In addition,
   commercial databases including [296]KEGG and MetaboAnalyst
   ([297]http://www.metaboanalyst.ca/) were used for pathway enrichment
   analysis.

UHPLC-MS/MS-based lipidomics

   For lipidomics, approximately 500,000 HSCs (CD48^−CD150^+LSK) were
   sorted and were rapidly frozen in liquid nitrogen for 30 s and stored
   at −80 °C until use. The UHPLC-MS/MS-based lipidomics was performed by
   BIOTREE Biomedical Technology (Shanghai, China). The entire cell sample
   was mixed with 200 μL of water and vortexed for 60 s. The samples
   underwent three freeze-thaw cycles using liquid nitrogen, followed by
   sonication in an ice-water bath for 20 min. Subsequently, the
   homogenate (200 μL) was combined with 480 μL of extraction solution
   (MTBE: MeOH = 5:1), which contained the internal standard. After
   vortexing for an additional 60 s, the samples were sonicated again for
   10 min in an ice-water bath. Next, the samples were centrifuged at
   2000 × g for 15 min at a temperature of 4 °C. A volume of 250 μL of
   supernatant was transferred to a fresh tube. The remaining sample
   received an addition of another 250 μL of MTBE, followed by vortexing,
   sonication, and centrifugation; another aliquot of 250 μL supernatant
   was then collected. This step was repeated once more. The combined
   supernatants were concentrated under vacuum at a temperature of 37 °C
   until dry. The dried residues were subsequently reconstituted in 80 μL
   of resuspension buffer (DCM: MeOH: H[2]O = 60:30:4.5). Following this,
   the samples were vortexed for approximately 30 s and subjected to
   sonication in an ice-water bath for another ten minutes. Finally, the
   resulting suspension was centrifuged at a speed of 10,000 × g for
   fifteen minutes at a temperature of four degrees Celsius; thereafter, a
   volume of thirty-five microliters from the supernatant was transferred
   into a fresh glass vial for LC/MS analysis.

   The UHPLC separation was performed using an ACQUITY Premier series
   UHPLC System (Waters). The mobile phase A comprised 40% water, 60%
   acetonitrile, and 10 mmol/L ammonium formate. Mobile phase B consisted
   of 10% acetonitrile, 90% isopropanol, and 10 mmol/L ammonium formate.
   The column temperature was maintained at 45 °C. The auto-sampler
   temperature was set to 10 °C, with an injection volume of 2 μL. For
   assay development, a Triple Quad™ 6500+ mass spectrometer (SCIEX) was
   utilized. Typical ion source parameters included: IonSpray Voltage:
   +5500/−4500 V; Curtain Gas: 40 psi; Temperature: 350 °C; Ion Source Gas
   1:50 psi; Ion Source Gas 2:50 psi; DP: ±80 V. Biobud-v2.1.4.1 software
   was employed for the quantification of the target compounds. The
   absolute content of individual lipids was calculated based on peak area
   and the actual concentration of the identical lipid class internal
   standard (IS), as detailed in Supplementary Data [298]2.

UHPLC-MS/MS-based proteomics

   UHPLC-MS/MS-based proteomics was performed by PTM BIO (Hangzhou,
   China). In brief, each protein sample was taken in equal amounts for
   enzymatic digestion. The volume was adjusted to be consistent using
   lysis buffer, followed by the addition of dithiothreitol (DTT) to
   achieve a final concentration of 5 mM. The mixture was then reduced at
   56 °C for 30 min. Subsequently, iodoacetamide (IAA) was added to reach
   a final concentration of 11 mM, and the solution was incubated at room
   temperature in the dark for 15 min. TEAB was used to dilute urea,
   ensuring that its concentration remained below 2 M. Trypsin was added
   at a ratio of 1:50 (protease:protein, w/w) for overnight digestion.
   Afterward, trypsin was again added at a ratio of 1:100
   (protease:protein, w/w), and digestion continued for an additional 4 h.
   The peptide segments were dissolved in mobile phase A and separated
   using the EASY-nLC 1000 UHPLC system (Thermo Fisher Scientific). After
   separation by the UHPLC system, the peptides were injected into the NSI
   ion source for ionization before being analyzed by Q Exactive Plus mass
   spectrometry (Thermo Fisher Scientific). The ion source voltage was set
   at 2100 V, allowing for detection and analysis of both precursor ions
   and their secondary fragments using high-resolution Orbitrap
   technology. The scanning range for primary mass spectrometry was
   established between 350 and 1600 m/z with a scanning resolution set at
   70,000. The secondary scan resolution was configured at 17,500. Data
   acquisition utilized data-dependent acquisition (DDA) mode whereby
   after each primary scan, the top ten precursor ions exhibiting the
   highest signal intensity were sequentially directed into the HCD
   collision cell utilizing 28% fragmentation energy for dissociation
   followed by subsequent secondary mass spectrometric analysis.

   The raw data obtained from the mass spectrometer were processed using
   MaxQuant search engine (v.1.6.15.0). The search parameters were
   configured as follows: the database used was
   Mus_musculus_10090_SP_20230103.fasta, containing 17,132 sequences. The
   tolerances for precursor ion mass error during First Search and Main
   Search were set at 20 ppm and 4.5 ppm, respectively, while fragment ion
   mass error tolerance was also maintained at 20 ppm. Carbamidomethyl on
   Cys was specified as fixed modification, and acetylation on protein
   N-terminal and oxidation on Met were specified as variable
   modifications. FDR was adjusted to <1%. To qualify as identified
   proteins, each must contain at least one unique peptide segment.

Statistics and reproducibility

   All experiments included at least three biological replicates.
   Comparisons between two groups were analyzed using a two-tailed
   unpaired Student’s t-test. The Cox–Mantel test was used to compare two
   survival curves. Values of p < 0.05 were considered statistically
   significant. All data are means ± SD. No statistical method was used to
   predetermine the sample size. No data were excluded from the analyses.
   Blinding was not applicable to this study. Statistical analyses were
   performed using GraphPad Prism9.5 or Microsoft Excel.

Reporting summary

   Further information on research design is available in the [299]Nature
   Portfolio Reporting Summary linked to this article.

Supplementary information

   [300]Supplementary Information^ (3MB, pdf)
   [301]Supplementary Data 1^ (1.6MB, xlsx)
   [302]Supplementary Data 2^ (138.4KB, xlsx)
   [303]Supplementary Data 3^ (107KB, xlsx)
   [304]Reporting Summary^ (3.2MB, pdf)
   [305]Peer Review file^ (8.9MB, pdf)

Source data

   [306]Source Data^ (6.6MB, xlsx)

Acknowledgements