Tmem110 regulates the conformation of TRPML1 to maintain endolysosomal homeostasis and prevent mitochondrial DNA leakage and pathological self-DNA processing

Zunyong Feng; Yuanbo Pan; Jing Zhou; Liuxi Chu; Qiang Li; Xuanbo Zhang; Ping Wu; Zhiliang Xu; Yanjiao Huang; Jianhua Zou; Xiaokun Li; Xiaoyuan Chen; Zhouguang Wang

doi:10.1038/s41467-026-68382-8

. 2026 Jan 15;17:1678. doi: 10.1038/s41467-026-68382-8

Tmem110 regulates the conformation of TRPML1 to maintain endolysosomal homeostasis and prevent mitochondrial DNA leakage and pathological self-DNA processing

Zunyong Feng ^1,^✉,^#, Yuanbo Pan ^2,^#, Jing Zhou ^1,^#, Liuxi Chu ^3,^#, Qiang Li ⁴, Xuanbo Zhang ⁵, Ping Wu ¹, Zhiliang Xu ⁴, Yanjiao Huang ⁴, Jianhua Zou ⁵, Xiaokun Li ^1,^✉, Xiaoyuan Chen ^5,^6,^7,^8,^✉, Zhouguang Wang ^3,^9,^✉

PMCID: PMC12910075 PMID: 41540067

Abstract

The mechanisms by which phagocytes handle large quantities of internalized organelles, such as mitochondria released during tissue injury, remain unclear. Here we show that the endoplasmic reticulum transmembrane regulator TMEM110 is a key determinant of disease severity in traumatic brain injury-associated multiple organ dysfunction. Loss of TMEM110 impairs the clearance of mitochondria aberrantly released into the circulation, leading to heightened autoimmune-mediated tissue injury and mortality. TMEM110 maintains lysosomal function by controlling the conformational transition of the lysosomal ion channel TRPML1 and generating localized calcium efflux sites, thereby preventing calcium overload, membrane disruption, and leakage of mitochondrial DNA into the cytosol. We further find that TMEM110 expression is restrained by the nucleic acid sensor STING under basal conditions, and that a naturally occurring interface mutation between TMEM110 and STING causes defective lysosomal DNA disposal and aberrant type I interferon activity. These findings identify a feedback pathway linking cytosolic DNA sensing to organelle homeostasis.

Subject terms: Mechanisms of disease, Autoimmunity, Lysosomes

Phagocytes must safely remove mitochondria released after tissue injury to prevent harmful immune activation. Here, the authors show that TMEM110 preserves lysosomal function to clear mitochondrial DNA, thereby limiting organ damage and mortality after traumatic brain injury.

Introduction

Severe trauma is a leading cause of approximately 10% of global deaths and 16% of disability-adjusted life years lost¹. Advances in post-traumatic hemorrhage control and coagulopathy management have significantly improved survival rates among patients with severe injuries who would have otherwise succumbed². However, many survivors develop systemic inflammatory response syndrome (SIRS) and multiple organ dysfunction syndrome (MODS), conditions driven by excessive systemic immune activation in response to severe injury, severely impacting clinical outcomes and prognosis³. The innate immune mechanisms by which traumatic brain injury (TBI) induces MODS beyond the brain remain incompletely understood. Recent studies have highlighted the critical interplay between self-nucleic acids, such as mitochondrial DNA (mtDNA), nuclear DNA (nDNA), and innate immune responses in trauma and infectious diseases⁴. Mitochondrial DNA (mtDNA), a circular double-stranded DNA (dsDNA) with limited coding capacity and CpG-rich sequences⁵, is released from damaged mitochondria during trauma and can trigger systemic immune activation⁶, contributing to SIRS, MODS, and secondary mortality⁷. Investigating the autoimmune mechanisms of TBI-induced MODS provides insights into how the innate immune system rapidly detects, internalizes, and processes self-DNA–containing organelles released upon trauma-induced cell death.

Under physiological conditions, cells degrade damaged or aging mitochondria and escaped DNA through the autophagosome/endosome-lysosome acidic compartment system, thereby preventing type I interferon activation and autoantibody-mediated attack⁸. Disorders associated with defective self-DNA clearance, collectively termed type I interferonopathies, include systemic lupus erythematosus, Sjögren’s syndrome, and Aicardi-Goutières syndrome⁹. In most cases, endogenous mtDNA triggers activation of the cytosolic DNA sensor cGAS and its downstream STING pathway, inducing the expression of interferon-stimulated genes (ISGs), a key mechanism underlying these diseases¹⁰. Mitochondria released during non-apoptotic, unprogrammed cell death can also drive type I interferonopathy-like phenotypes via cGAS-STING activation. For example, tumor radiotherapy induces internalization of tumor-derived DNA by dendritic cells, leading to cGAS-STING signaling activation¹¹; cardiomyocyte death following acute ischemic injury triggers STING-dependent inflammation¹²; and adjuvant-mediated cell death similarly promotes immune activation via STING¹³. Additionally, during neutrophil extracellular trap (NET) formation, dying neutrophils release DNA-protein complexes into the extracellular space, further activating STING⁶. These STING activation events predominantly occur in myeloid cells, suggesting that the endo-lysosomal system frequently fails to prevent uncontrolled type I interferon responses when clearing large amounts of extracellular mtDNA. Thus, it is plausible that autoimmune injury in TBI-induced MODS is linked to excessive mtDNA internalization, cytosolic escape, and subsequent cGAS-STING pathway activation. However, how these internalized DNA-containing organelles overwhelm lysosomal homeostatic mechanisms, whether cytosolic self-DNA sensing can regulate mtDNA escape via lysosomal pathways, and how endo-lysosomal homeostasis is maintained under such conditions remain to be elucidated.

Studies have shown that the endoplasmic reticulum (ER) Ca²⁺ sensor STIM1 tethers STING to the ER, preventing spontaneous type I interferon responses¹⁴. Additionally, STIM1 has been implicated in promoting phagolysosome formation¹⁵. Another ER transmembrane protein, TMEM110, interacts with the cytosolic domain of STIM1 via its polybasic C-terminal tail¹⁶ and dynamically remodels ER-plasma membrane junctions during signal transduction. Due to this function, TMEM110 is referred to as a STIM-activating enhancer (STIMATE) and is thought to have potential regulatory activity on Ca²⁺ channels¹⁷. However, the role of TMEM110 in the lysosomal system and nucleic acid sensing remains largely unknown. In this study, we identified TMEM110, an endoplasmic reticulum transmembrane protein, as a physiological suppressor of cytosolic STING activation through its C-terminal K/R domain. Additionally, TMEM110 regulates the conformational state of the lysosomal calcium channel TRPML1 via its D/E domain, thereby preventing lysosomal Ca²⁺ overload, membrane destabilization, and cytosolic leakage of mtDNA during the endocytosis of aberrantly released mitochondria. Acting as a signaling and effector molecule linking the cytosolic nucleic acid sensing machinery with the endolysosomal system, dysfunction of the TMEM110-TRPML1 axis may underlie the autoimmune features associated with peripheral organ damage in patients with TBI-MODS.

Results

TMEM110-deficient mice exhibit exacerbated type I interferon-associated TBI-MODS

To investigate the role of TMEM110 in monocyte-macrophage–mediated immune responses, we generated TMEM110 conditional knockout mice (TMEM110^flox/flox; Lyz2-cre, referred to as TMEM110 cKO), in which TMEM110 expression was specifically ablated in Lyz2-positive myeloid cells. Using flow cytometric sorting, we analyzed the bone marrow, peripheral myeloid cells, and tissue-resident macrophages-including microglia in the brain, alveolar macrophages in the lung, Kupffer cells in the liver, and renal macrophages-in both WT and TMEM110 cKO mice (Fig. S1A–S1F). We found that TMEM110 deficiency did not significantly affect the numbers or proportions of these cells. Further sorting revealed that TMEM110 was highly expressed only in peripheral monocytes and tissue-resident macrophages (Fig. S2A–S2F). Compared to WT mice, TMEM110 expression in peripheral and tissue-resident monocyte-macrophage populations was reduced by over 90% in TMEM110 cKO mice (Fig. S2A–S2F).

A standardized weight-drop device was used to induce controlled cortical impact (CCI) and establish the traumatic brain injury (TBI) model (Fig. S2G). At 4 h post-TBI, the proportion of Ly6C^hi monocytes—characterized by high TMEM110 expression—was significantly increased (Fig. S2H). However, no significant differences were observed between WT and TMEM110 cKO mice in peripheral granulocyte-monocyte mobilization (Fig. S2I), early TNF-α/IL-1β release (Fig. S2J), chemokine receptor CCR2 and phagocytic activity CD64 expression (Fig. S2K). Notably, following TBI, TMEM110 cKO mice exhibited significantly elevated serum levels of IFN-α/β (Fig. 1A), along with markedly increased expression of interferon-stimulated genes (ISGs) in peripheral monocytes compared to wild-type mice (Fig. 1B). Similarly, elevated IFN-α/β levels were also observed in the cerebrospinal fluid (Fig. 1C). However, no significant difference in interferon-stimulated genes (ISGs) expression was detected in brain microglia between TMEM110cKO and WT mice (Fig. 1D), suggesting that Tmem110 deficiency-induced hyperactivation of type I interferon responses primarily occurs in peripheral monocytes.

Histopathological analysis revealed that TMEM110 cKO mice exhibited significantly more severe injury in peripheral organs—including the lungs, liver, and kidneys—compared to WT mice (Fig. 1E). During a subsequent one-month observation period, the cumulative mortality rate in WT mice reached 50%, while TMEM110 cKO mice showed a significantly higher mortality rate (Fig. 1F). TMEM110 cKO mice also displayed more severe ventilatory dysfunction, accompanied by marked increases in biochemical markers such as serum creatinine and total bilirubin (Fig. 1H–J). Brain sections revealed significant injury differences between WT and TMEM110cKO mice at sites remote from the trauma (Fig. 1E). Correspondingly, peripheral blood glial fibrillary acidic protein (GFAP) levels, a brain injury marker, also showed notable differences (Fig. 1K).

Notably, TMEM110 cKO mice exhibited significant lymphadenopathy (Fig. 1E), and multiple autoantibodies were detected in the supernatant of serum (Fig. S3A). These autoantibodies likely originated from infiltrating peripheral immune cells, as the expression levels of ISGs in organ-resident fibroblasts and neuronal cells remained unchanged (Fig. S3B-S3E). To investigate the role of type I interferon (IFN-I) responses in the development of multiple organ dysfunction syndrome (MODS) in TMEM110 cKO mice, we crossed TMEM110 cKO mice with IFN-I receptor-deficient mice (Ifnar^-/-) to block IFN-I signaling. The results showed that Tmem110 cKO; Ifnar^-/- double knockout mice exhibited significantly reduced autoimmune organ damage (Figs. 1E, H, K and S3A) and markedly decreased post-TBI mortality (Fig. 1G).

To determine whether the increased mortality associated with Tmem110 deficiency is mediated by peripheral rather than central IFN-I signaling, we established bone marrow chimeric mouse models to assess the role of peripheral monocytes in TBI-associated mortality. Specifically, WT and TMEM110 cKO mice underwent total body irradiation to ablate their hematopoietic systems, followed by reciprocal bone marrow transplantation (BMT) to generate chimeric mice (Fig. S4A). The efficiency of peripheral blood monocyte reconstitution was confirmed by flow cytometry (Fig. S4B). The results showed that TMEM110 cKO recipient mice receiving WT bone marrow exhibited significantly reduced organ damage (Fig. S4C–S4F), attenuated aberrant IFN-I responses (Fig. S4G), and decreased mortality following TBI (Fig. S4H).

To investigate whether the IFN-I response was compartment-dependent, we crossed TMEM110^cKO mice with Tlr7^⁻/⁻ (lacking the lysosomal dsRNA sensor TLR7) and Mb21d1^⁻/⁻ (lacking the cytosolic dsDNA sensor cGAS) mice. As shown in Figs. S5A–S5F and S5G-S5L, TMEM110^cKOMb21d1^⁻/⁻ mice—but not TMEM110^cKOTlr7^⁻/⁻ mice—exhibited reduced organ damage and mortality. These findings indicate that TMEM110 deficiency leads to IFN-I activation through the cytosolic DNA sensor cGAS rather than lysosomal TLR7.

In summary, this study demonstrates that under traumatic stress conditions, TMEM110 deficiency significantly increases susceptibility to multiple organ dysfunction syndrome (MODS) by activating a cGAS-dependent type I interferon (IFN-I) signaling pathway in peripheral monocytes, leading to characteristic multi-organ injury and autoimmune responses.

TMEM110 deficiency leads to Ca²⁺ overload, lysosomal membrane damage, and mtDNA escape

Deficiency of the lysosomal nuclease DNase II is embryonically lethal¹⁸, as fetal macrophages fail to degrade nuclear DNA expelled from erythroid precursor cells, triggering excessive interferon production and embryonic lethality¹⁹. Ifnar1 deletion rescues DNase II^⁻/⁻ embryonic lethality²⁰. Notably, TMEM110^cKO monocytes exhibited impaired DNase II cleavage activity within lysosomes (Fig. 2A). DNase II activity is pH-dependent and inhibited by high intralysosomal Ca²⁺ levels²¹. To monitor lysosomal pH and Ca²⁺ levels, we utilized CalipHuor, a fluorescence-based sensor to measure intralysosomal H⁺ and Ca²⁺ concentrations²⁰. Compared to WT monocytes, TMEM110-deficient cells exhibited a 3.8-fold increase in lysosomal [Ca²⁺] and a ~ 3.3-fold decrease in [H⁺] (Fig. 2B). The inactivation of DNase II caused by TMEM110 deficiency may be associated with impaired lysosomal acidification and Ca²⁺ overload, both of which can contribute to the suppression of DNase II activity.

A Four hours post-TBI, Ly6C^hi monocytes from TMEM110^cKO and WT mice (n = 6 per group) were sorted, lysosomes and cytosol were separated, and DNase II cleavage activity was assessed using the JESS automated Western blot system, with LAMP1 as the loading control. B Ly6C^hi monocytes (n = 6 per group) were loaded with CalipHuor to assess lysosomal pH and Ca²⁺ concentrations based on O/R and D/A fluorescence ratio pairs.Representative pseudocolor fluorescence images acquired from the same cells (same field of view) in the indicated fluorescence channels are shown on the left; quantitative pH and [Ca²⁺] values calculated from calibration curves are shown on the right. C Schematic illustrating unprogrammed mitochondrial DNA (URmtDNA) endocytosis by hMoCD14⁺ monocytes cells following co-culture with donor fibroblasts expressing mKeima. D Representative confocal fluorescence images of TMEM110^-/- and WT hMoCD14⁺ cells at 1, 4, and 8 h after engulfment of donor mitochondria (left). The middle panel shows mean λEm = 620 nm / λEx = 440 nm fluorescence intensity per cell, reflecting acidified organelles; the right panel shows λEm = 510 nm/λEx = 440 nm intensity, indicating cytosolic mtDNA leakage (n = 6 biological replicates). E Representative fluorescence microscopy images of TMEM110^-/- and WT hMoCD14⁺ cells 8 h after engulfing Cy5-labeled donor mitochondria, with Pitstop 2 as an endocytosis inhibitor control (left). The right panel shows mean λEm = 670 nm/ λEx = 651 nm fluorescence intensity per cell (n = 6 biological replicates). F Cytosolic fractions were isolated from TMEM110^-/- and WT hMoCD14⁺ cells, and cytosolic mtDNA (nd1) abundance 8 h after URmtDNA endocytosis was quantified by qPCR using β-actin as the internal reference (n = 6). G Lysosomal membrane integrity was assessed by flow cytometry in TMEM110^-/- and WT hMoCD14⁺ cells 8 h after URmtDNA endocytosis using Acridine Orange staining. Representative flow plots are shown (left), and mean fluorescence intensities at λEm = 617 nm / λEx = 555 nm and λEm = 528 nm / λEx = 490 nm are quantified (right) (n = 6). H Representative confocal fluorescence images of TMEM110^-/- and WT hMoCD14⁺ cells expressing CHMP4A-mCherry and LAMP1-eGFP reporters 8 h after URmtDNA endocytosis (merged channels shown). I Free Ca²⁺ released and exchanged by isolated mitochondria in buffers of pH 4.5, 5.0, 6.5, and 7.2 over 1 h (n = 6). J Schematic model summarizing lysosomal Ca²⁺ overload/insufficient acidification, membrane destabilization, and cytosolic mtDNA escape following URmtDNA engulfment. Data are presented as mean ± SD. For cell experiments, n denotes biologically independent replicates from three independent experiments, each with three technical replicates per group. Western blot data are representative of three independent biological replicates. Statistical analyses were performed using two-sided tests: Welch’s t-test for panels B and D, and one-way ANOVA followed by Tukey’s multiple-comparison correction for (F) and (G). Figure 2C was created in BioRender. Dwad, D. (2025) https://BioRender.com/sjs47bj; Fig. 2J was created in BioRender. Dwad, D. (2025). Source data are provided as a Source Data file.

Non-apoptotic, unprogrammed cell death following traumatic injury induces a rapid and extensive extracellular release of mitochondrial DNA (mtDNA), often as whole mitochondria, distinct from mitophagy in type I interferonopathies. We employed a TOM22-based ELISA to assess the release of free mitochondria into the peripheral circulation following traumatic brain injury (TBI) in mice (Fig. S6A), using a doxorubicin-induced mouse model as a control for programmed mitochondrial release. Since doxorubicin-mediated programmed/apoptotic mitochondrial release typically involves encapsulation within intact mitochondrial membranes²¹, such membrane-enclosed mitochondria are not efficiently detected by TOM22-based ELISA. However, elevated TOM22 protein levels were consistently observed in serum precipitates from these mice (Fig. S6B). In stark contrast, in the serum of TBI model mice, we detected a substantial amount of free, non-membrane-enclosed mitochondria (Fig. S6C). Notably, TMEM110 cKO mice exhibited a markedly impaired capacity to clear these circulating, non-programmatically released mitochondria from the peripheral blood. More importantly, intravenous pre-administration of the anti-TOM22 antibody (TOM22 IgG4-S228P) in TBI mice significantly reduces the number of aberrantly released mitochondria (Fig. S6D), thereby alleviating type I interferon-associated mortality (Fig. S6E–S6F).

To investigate the role of TMEM110 in unprogrammed release of mitochondrial DNA-induced endocytosis (URmtDNA endocytosis), we examined the engulfment of mitochondria detached from donor human fibroblasts by monocytes in vitro (Fig. 2C). We employed mKeima-labeled donor mitochondria, a pH-sensitive construct that fluoresces green at pH 7.0 (cytosolic) and magenta at pH 4.0 (lysosomal)²². Following co-incubation with hMoCD14⁺ monocytes, we observed robust internalization of exogenous mitochondria. Notably, TMEM110-deficient monocytes exhibited impaired acidic degradation of mtDNA, leading to its leakage into the cytoplasm (Fig. 2D).

To further assess endocytic escape, Cy5-labeled donor mitochondria were used. TMEM110-deficient cells exhibited significantly increased cytosolic accumulation of mtDNA (Fig. 2E), consistent with qPCR quantification (Fig. 2F). This process was abolished by Pitstop2, a clathrin-mediated endocytosis inhibitor, which also suppressed aberrant interferon-stimulated gene (ISG) expression following URmtDNA endocytosis in TMEM110^⁻/⁻ hMoCD14⁺ cells (Fig. S7A). Similarly, ethidium bromide (EtBr)-mediated depletion of cytosolic mtDNA abolished ISG upregulation (Fig. S7B). Notably, TMEM110 deficiency did not impair phagolysosome biogenesis and function, as expression of lysosome-related genes²³ and nuclear localization of transcription factor EB (TFEB) remained unaffected (Fig. S7C, S7D). Meanwhile, this process does not affect the expression of key genes involved in mitochondrial engulfment and degradation, including Lc3 for recognizing exposed cardiolipin, Rac1 for cytoskeletal remodeling and phagosome formation, Rab5 for phagosome maturation, and Rnase2 and Ctsb for degradation functions (Fig. S7E).

Lysosomal membrane integrity was assessed using acridine orange (AO), a pH-sensitive dye that fluoresces upon protonation in intact lysosomes. TMEM110-deficient cells exhibited a marked reduction in AO oligomeric fluorescence, indicating lysosomal membrane instability (Fig. 2G). Additionally, live-cell imaging of CHMP4A-mCherry and LAMP1-GFP reporters revealed that TMEM110-deficient cells exhibited diminished CHMP4A recruitment to lysosomes, suggesting defective ESCRT-dependent lysosomal membrane repair (Fig. 2H). However, TMEM110 deficiency did not alter the expression of ESCRT components or ESCRT-III-associated factors (Fig. S7F, S7G). Given the critical role of lysosomal Ca²⁺ flux in ESCRT-mediated membrane fusion^24,25 and emergency repair^26,27, we hypothesized that TMEM110 regulates lysosomal Ca²⁺ homeostasis.

Mitochondria serve as a major intracellular Ca²⁺ reservoir, storing Ca²⁺ predominantly in an insoluble, precipitated form complexed with phosphate, proteins, and ribonucleotides²⁸. Mitochondrial matrix Ca²⁺ concentration can reach up to 1 M, approximately 1000- to 2000-fold higher than basal lysosomal free Ca²⁺ level (0.5–1 mM)²⁹. Upon acidification, isolated mitochondria release substantial amounts of Ca²⁺ into the extracellular environment (Fig. 2I).

Intriguingly, Ca²⁺ overload can destabilize lysosomal membranes and facilitate mtDNA escape. This phenomenon is reminiscent of cationic lipid nanoparticles enriched in Ca²⁺ or Zn²⁺, which enhance mRNA vaccine endosomal escape, potentially via osmotic destabilization of lysosomal membranes³⁰. Similar to the phenotype observed in Ly6C^hi monocytes in vivo, TMEM110-deficient hMoCD14⁺ cells exhibited significantly elevated lysosomal [Ca²⁺] and decreased [H⁺] following endocytosis of URmtDNA, compared to WT cells (Fig. S8A, S8B). Elevated lysosomal Ca²⁺ severely inhibited DNase II activity (Fig. S8C) while exacerbating membrane instability, collectively leading to defective mtDNA degradation and cytosolic escape.

Our findings reveal a critical role for TMEM110 in maintaining lysosomal Ca²⁺ homeostasis and acidification during mitochondrial engulfment. Deficiency in TMEM110 results in lysosomal Ca²⁺ overload and impaired acidification, leading to membrane destabilization, mtDNA escape, and defective cytosolic mtDNA clearance (Fig. 2J).

Loss of lysosomal Ca²⁺ efflux hotspots in TMEM110-deficient cells mediates type I interferon response

To determine whether lysosomal Ca²⁺ overload in TMEM110-deficient cells results from impaired Ca²⁺ efflux, we performed lysosomal patch-clamp recordings to assess cation currents (Fig. 3A)³¹. TMEM110^⁻/⁻hMoCD14⁺ cells were co-transfected with TMEM110-mCherry and LAMP1-YFP reporters (Fig. 3D, left panel), and lysosomal membrane potential was recorded from chemically expanded lysosomes³². A pH 4.5 pipette solution triggered an inward rectifying current in mCherry⁺YFP⁺ lysosomes (I-130 mV = 90.27 pA, n = 70 vesicles), whereas mCherry⁻YFP⁺ lysosomes exhibited a significantly reduced inward current (I-130 mV = 16.1 pA, n = 35) (Fig. 3B, C), suggesting that TMEM110 deficiency impairs lysosomal cation efflux. To further investigate ion specificity, Na⁺, K⁺, and Ca²⁺ were individually supplemented at cytosolic-exceeding concentrations in the pipette solution. Only Ca²⁺ efflux was selectively impaired in TMEM110-deficient lysosomes (Fig. S8A–S8C).

Fig. 3 — A Schematic illustrating the experimental design for monitoring cation efflux from lysosomes using a lysosomal membrane patch-clamp approach. B TMEM110^-/- hMoCD14⁺ cells expressing TMEM110-mCherry and LAMP1-YFP were treated with vacuolin-1 to enlarge endosomal/lysosomal vacuoles. TRPML1-mediated inwardly rectifying currents (I_TRPML1) were recorded under stimulation with pH 4.5 Tyrode’s solution. I_TRPML1 was activated by repeated voltage ramps (−140 to +140 mV; 400 ms), with 4-s intervals, and representative current traces are shown (black: baseline; red: post-stimulation; holding potential = 0 mV). C I_TRPML1 current amplitudes at −130 mV recorded in mCherry+YFP+ lysosomes (n = 6; 35 measurements total) and mCherry-YFP⁺ lysosomes (n = 6; 74 measurements total) were quantified and statistically analyzed. D, E TMEM110^-/- and WT hMoCD14⁺ cells expressing LAMP1 CT-YFP and TMEM110 CT-mCherry were preloaded with Fluo8-AM. Representative time-lapse confocal fluorescence images were captured (same field of view), and fluorescence within a 750-nm radius surrounding YFP⁺mCherry⁺ puncta was analyzed 1 min after URmtDNA endocytosis. F Scatter plots (left) show changes in mean fluorescence within 750 nm of each fluorescent punctum (λEm = 514 nm / λEx = 494 nm). The right panel shows cumulative Fluo8-AM fluorescence intensity within 2 min in TMEM110^-/- and WT hMoCD14⁺ cells (n = 8). G Representative confocal images of the same cells (same field of view) acquired in the LAMP1 CT-YFP and Fluo8-AM fluorescence channels at 2 min after URmtDNA endocytosis (left). The right bar graph shows cumulative Fluo8-AM fluorescence intensity within 2 min in WT hMoCD14⁺ cells pretreated with BAPTA-AM (n = 9). H Representative confocal fluorescence images of the same cells (same field of view) acquired in the indicated fluorescence channels (left) and quantification (right) showing cumulative Fluo8-AM fluorescence intensity within 2 min in TMEM110^-/- hMoCD14⁺ cells pre-transfected with PNPs-Ca²⁺ (n = 9). I, J Expression of ISGs in BAPTA-AM-pretreated WT hMoCD14⁺ cells and PNPs-Ca²⁺ -transfected TMEM110^-/- hMoCD14+ cells (n = 6) was measured by qPCR and normalized to gapdh. Data are presented as mean ± SD. For cell experiments, n denotes biologically independent replicates from three independent experiments, each including three technical replicates per group. Representative images are shown for all microscopy data. Statistical analyses were performed using two-sided Welch’s t-test (C–J). Figure 3A was created in BioRender. Dwad, D. (2025) https://BioRender.com/sjs47bj. Source data are provided as a Source Data file.

To visualize lysosomal Ca²⁺ release events, Fluo8-AM was used to label intracellular Ca²⁺. In wild-type monocytes, Ca²⁺ hotspots were observed around LAMP1⁺ lysosomes and colocalized with TMEM110 at the lysosomal membrane (Fig. 3D, right panel). Confocal microscopy revealed that the fluorescence intensity of Ca²⁺ hotspots surrounding LAMP1⁺ lysosomes was reduced by 70% in TMEM110^⁻/⁻ monocytes within 2 min of URmtDNA endocytosis (Fig. 3E, F).

To assess the functional contribution of TMEM110-dependent Ca²⁺ hotspots to lysosomal acidification and membrane integrity, two experimental approaches were employed (Fig. 3G, H). Treatment with BAPTA-AM, a cytosolic Ca²⁺ chelator, abrogated lysosomal Ca²⁺ hotspots in wild-type monocytes, whereas photothermal nanoparticles loaded with Ca²⁺ (PNPs-Ca²⁺), a nanoparticle system designed to trigger lysosomal Ca²⁺ release waves³³, restored lysosomal Ca²⁺ hotspots in TMEM110^⁻/⁻ cells. In WT cells, the elimination of Ca²⁺ hotspots leads to DNase II inactivation (Fig. S9D), cytosolic leakage of mtDNA (Fig. S9E), and activation of ISG expression (Fig. 3I). Conversely, restoration of Ca²⁺ hotspots in TMEM110^-/- cells reactivates DNase II (Fig. S9D), reduces cytosolic mtDNA leakage (Fig. S9E), and suppresses ISG activation (Fig. 3J).

These findings highlight the critical role of lysosomal Ca²⁺ hotspots in ensuring the timely degradation of endocytosed mtDNA. Given the Ca²⁺ overload observed in TMEM110-deficient cells, we propose that these phenotypes arise due to disrupted Ca²⁺ efflux, likely resulting from impaired function of a yet-to-be-identified lysosomal Ca²⁺ channel.

TMEM110 induces conformational activation of TRPML1 and Ca²⁺ efflux hotspots in response to cytosolic mtDNA escape

To elucidate the mechanism underlying lysosomal Ca²⁺ hotspot formation following URmtDNA endocytosis, we examined several candidate lysosomal Ca²⁺ channels. Among them, only TRPML1 depletion completely abolished URmtDNA-induced Ca²⁺ hotspots (Fig. S10A). Notably, TMEM110 exhibited strong colocalization with TRPML1 (Fig. 4A), and reciprocal immunoprecipitation assays confirmed their direct interaction (Fig. 4B, C). URmtDNA endocytosis slightly enhanced TMEM110-TRPML1 complex formation, whereas depletion of cytosolic mtDNA using ethidium bromide drastically reduced their interaction (Fig. 4D).

TRPML1, a selective cation channel, forms a homotetrameric structure composed of six transmembrane domains and two pore helices (Fig. 4E), playing a crucial role in lysosomal homeostasis and Ca²⁺ signaling³⁴. To identify the TMEM110-binding region within TRPML1, we performed CoIP domain mapping, pinpointing the TM2 domain (residues 295–327) as the minimal interaction site (Fig. 4F).

TRPML1 undergoes a conformational shift to increase Ca²⁺ permeability by physically constricting its TM6 domain within the tetrameric ion channel complex³⁵. To monitor this conformational change in real time, we developed a FRET-based sensor by fusing CFP and YFP to the N- and C-termini of TRPML1, respectively (Fig. 4G). URmtDNA endocytosis induced a significant increase in FRET signal, indicating TM6 domain opening, which was abolished in TRPML1-TM2 (∆295-327) mutant cells (Fig. 4H).

TMEM110 consists of five transmembrane regions and a long cytosolic C-terminal domain (residues 214–294) enriched in D/E, K/R, and poly-basic motifs (Fig. 4I)¹⁶. Under resting conditions, both the N-terminus and C-terminus of TMEM110 are localized to the endoplasmic reticulum. Following URmtDNA endocytosis, the C-terminus of TMEM110 dissociates from the ER and relocates to the lysosome (Fig. S11A–S11C). Structural modeling predicted that the D/E domain (residues 251–273) interacts with TRPML1-TM2 (residues 295–327) to form a binding interface (Fig. 4J). Although TMEM110 deficiency does not affect TRPML1 expression, it completely abolishes its permeability conformational transition (Fig. 4K–L). Consecutive amino acid mutations within the TMEM110 D/E domain (ESES, EILI, SADD, EMEE) revealed that this entire domain is critical for TRPML1 conformational activation and Ca²⁺ permeability (Fig. 4M). Additionally, these mutations significantly impaired lysosomal Ca²⁺ hotspot formation (Fig. S10B).

The TRPML1-TM2 domain and its interaction with the TMEM110-D/E domain were essential for URmtDNA endocytosis-induced DNase II activation (Fig. S10C), suppression of mtDNA cytosolic leakage (Fig. S10D), and inhibition of aberrant ISG expression (Fig. S10E).

In summary, upon cytosolic mtDNA escape, TMEM110 binds to the TM2 domain of TRPML1 within its six-transmembrane lysosomal architecture, triggering a conformational shift that facilitates selective cation channel activation and Ca²⁺ efflux hotspot formation. However, the precise mechanism by which TMEM110 senses cytosolic mtDNA following lysosomal escape remains to be further investigated.

Cytosolic escape of mtDNA activates STING, relieving TMEM110-K/R inhibition and inducing TRPML1 conformational transition

Previous studies have shown that the poly-basic tail of TMEM110 extends into the cytoplasm and interacts with STIM1¹⁶. STIM1, an ER-resident Ca²⁺ sensor, has been implicated in promoting phagolysosome formation¹⁵. More importantly, STIM1 tethers STING to the ER, preventing spontaneous type I interferon (IFN-I) responses¹⁴. These findings suggest a potential regulatory link between STING and TMEM110-TRPML1. However, in our system, the function of TMEM110 appears to be independent of STIM1, as deletion of STIM1 fails to reproduce the cellular phenotypes observed in TMEM110-deficient cells (Fig. S12A–S12D). Moreover, overexpression of TMEM110 plasmid fully rescues the phenotypes caused by TMEM110 deficiency, including the loss of TRPML1 permeability-associated conformational switching, the disappearance of Ca²⁺ hotspots, mtDNA leakage, and excessive type I interferon responses (Fig. S12E–S12H).

Co-immunoprecipitation (Co-IP) assays confirmed an resting-state interaction between TMEM110 and STING, which was disrupted upon URmtDNA endocytosis in a cGAS-dependent manner (Fig. 5A). Stimulation with the STING agonist 2’,3’-cGAMP enhanced TMEM110-TRPML1 interaction (Fig. 5B) and concurrently promoted the conformational transition of TRPML1, facilitating its ion permeability, which was abolished in TRPML1-TM2 (∆295-327) mutant cells (Fig. 5C). In STING-deficient cells, TMEM110-TRPML1 interaction was constitutively enhanced and unresponsive to URmtDNA endocytosis (Fig. 5D). Furthermore, FRET-based structural analysis and lysosomal patch-clamp recordings highlighted STING’s crucial role in lysosomal Ca²⁺ efflux (Fig. 5E, 5F), suggesting that TMEM110 activity may be contingent on STING activation.

Both STING and TMEM110 contain extended cytosolic domains (Fig. 5G). Co-IP experiments identified a direct interaction between the TMEM110-CT K/R domain (residues 213-289) and the STING-CDN domain (residues 183-339) (Fig. 5H, 5I). Neither the deletion of the full-length TMEM110 nor the deletion of its K/R domain affects STING activation (Fig. 5J). FRET analysis revealed that deletion of TMEM110-K/R led to spontaneous TRPML1 channel opening (Fig. 5K), a phenomenon also observed in STING-CDN-deficient cells (Fig. 5L). Additionally, confocal imaging confirmed that TMEM110-K/R is essential for the punctate co-localization of TMEM110 and TRPML1 upon URmtDNA escape (Fig. 5M). Due to the constitutive dissociation of TMEM110 from STING, TMEM110-∆K/R cells exhibited enhanced processing of internalized URmtDNA, thereby attenuating ISG activation (Fig. 5N, O).

Collectively, cytosolic mtDNA escape triggers STING-CDN dissociation from TMEM110-K/R, exposing the TMEM110-D/E domain, which subsequently activates TRPML1-mediated lysosomal Ca²⁺ efflux stabilization.

Naturally occurring STING mutations affect lysosomal stability via TMEM110

Structural predictions indicate that the TMEM110-K/R domain forms an interaction interface with the ligand-binding domain (LBD) of STING, involving three distinct regions: LBDα3, the LBDβ1-LBDβ2 linker, and the LBDβ5-LBDα4 linker (Fig. 6A). To validate this interaction, we performed FRET-based experiments to examine their binding states in living cells (Fig. 6B). Under resting conditions, TMEM110 and STING exhibited strong interaction, as evidenced by high FRET signals, whereas deletion of the TMEM110 K/R domain disrupted TMEM110-STING interaction (Fig. 6C), a phenomenon similarly observed in STING-CDN-deficient cells (Fig. 6D).

Fig. 6 — A Molecular docking prediction of the protein-protein interaction (PPI) interface between the TMEM110 K/R275-289 α-helix and the STING ligand-binding domain (LBD). The upper-right panel highlights human STING residues predicted to interact with TMEM110 (shown in red), with clinically reported pathogenic STING mutations indicated (*). B Schematic illustration of TMEM110-CFP and STING-YFP co-transfection for live-cell FRET analysis to monitor the spatial distance between TMEM110-CT and STING-CT. Under resting conditions, close proximity yields high FRET efficiency; upon STING activation, CTD displacement increases donor-acceptor separation and reduces FRET. C Apparent FRET efficiency (Eapp) recorded in TMEM110-CT-CFP/STING-CT-YFP co-transfected WT and TMEM110-ΔK/R hMoCD14⁺ cells (n = 3) 150 min after URmtDNA endocytosis; representative FRET images (same field of view) are shown (right). D Apparent FRET efficiency recorded in WT and STING-Δ181-339 hMoCD14⁺ cells (n = 3) 150 min after URmtDNA endocytosis; representative FRET images (same field of view) are shown (right). E Expression of ISGs in three STING point-mutant hMoCD14⁺ cell lines (n = 6), measured by qPCR and normalized to gapdh; results are shown as bar graphs. F Immunoprecipitation analysis of TMEM110-STING interactions in the three STING point-mutant hMoCD14⁺ cell lines before and after URmtDNA endocytosis. G–I Apparent FRET efficiency recorded in the three STING point-mutant hMoCD14+ cell lines (n = 3) 150 min after URmtDNA endocytosis; representative FRET images (same field of view) are shown (right). J Survival of STING^G207E (n = 22) and WT mice (n = 20) was monitored for 28 days following TBI, and Kaplan-Meier survival curves were generated. Survival outcomes of TM4-5 D/E IVT mRNA-LNP-treated mice (n = 24 and n = 21) versus mock LNP controls are also shown. K Representative H&E-stained sections of lung, liver, and kidney tissue collected 28 days after TBI. L ISG expression in Ly6C+ monocytes from mice 4 h post-injury (n = 6), measured by qPCR and normalized to gapdh; results are shown as bar graphs. Data are presented as mean ± SD. For cell experiments, n denotes biologically independent replicates from three independent experiments, each including three technical replicates per group. For immunoprecipitation and Western blotting, representative images from three independent biological replicates are shown. Statistical analyses were performed using two-sided one-way ANOVA followed by Tukey’s multiple-comparison correction for (E) and (L), and the log-rank (Mantel-Cox) test for survival analysis in (J). Figure 6B was created in BioRender. Dwad, D. (2025) https://BioRender.com/mpg8ec2. Source data are provided as a Source Data file.

Several pathogenic STING mutations have been reported within the LBD region, including G207E, R281Q, and R284G^36–39, which lead to a severe autoinflammatory disorder known as STING-associated vasculopathy with onset in infancy (SAVI). SAVI is characterized by recurrent fevers, ulcerative skin lesions, vasculitis, and interstitial lung disease, with hyperactivated type I interferon signaling in patient-derived cells^40,41. Coincidentally, these mutations are all located in the region that binds to TMEM110-K/R. Our experiments showed that STING G207E, R281Q, and R284G mutations significantly upregulated ISG mRNA expression in hMoCD14⁺ cells (Fig. 6E). Notably, these mutations did not disrupt TMEM110-K/R binding (Fig. 6F); instead, they impaired URmtDNA-induced dissociation of STING from TMEM110 (Fig. 6G–I).

Given that STING mutations may perturb TMEM110-mediated lysosomal Ca²⁺ homeostasis, we examined STING mutant mice in a traumatic brain injury (TBI) model to determine whether they recapitulate defective self-DNA degradation observed in TMEM110-deficient cells. Additionally, we designed an IVT mRNA-based therapeutic (TM4-5 D/E mRNA) targeting the TMEM110 D/E domain (Fig. S13A). When encapsulated in LNPs and transfected into hMoCD14⁺ cells, TM4-5 D/E mRNA localized to the lysosomal membrane via an N-terminal lysosomal-targeting sequence (Fig. S13B), reducing excessive lysosomal DNA overload (Fig. S13C) and cGAS-STING activation (Fig. S13D). We hypothesized that TM4-5 D/E mRNA-LNP could ameliorate TBI-induced autoimmunity.

STING^G207E mutant mice exhibited a significantly higher mortality rate following TBI compared to WT mice (Death Rate: 90.9% vs. 50%, P < 0.0001) (Fig. 6J), along with severe multi-organ damage (Fig. 6K and S13E–S13G), increased ISG activation (Fig. 6L), and elevated anti-dsDNA autoantibody titers (Fig. S6H). Intravenous administration of TM4-5 D/E IVT mRNA-LNP (1 μg/kg) within 12 h post-TBI substantially reduced mortality in both WT mice (Death Rate: 8.3% vs. 50%, P = 0.0031) and STING^G207E mutant mice (Death Rate: 37.5% vs. 90.9%, P < 0.0001) (Fig. 6J), while alleviating multi-organ damage and autoimmune symptoms (Figs. 6K, 6L and S13E-S13H).

Together, these findings describe a mechanism for maintaining intracellular DNA homeostasis. Excessive self-DNA endocytosis overwhelms lysosomes, triggering DNA escape and subsequent activation of the cytosolic cGAS-cGAMP-STING pathway. The dissociation of STING from TMEM110-K/R exposes the TMEM110-D/E domain, thereby facilitating TRPML1 conformational changes and promoting lysosomal Ca²⁺ efflux stabilization.

Clinical evidence links TMEM110 to impaired lysosomal DNA clearance in TBI-MODS Patients

To investigate the clinical relevance of TMEM110 in trauma-induced multiple organ dysfunction syndrome (TBI-MODS), we analyzed a cohort of 142 confirmed cases. Based on disease severity and recovery patterns, we identified a subset of 40 patients with prolonged organ dysfunction (prolonged subtype, ptTBI-MODS), defined as a Sequential Organ Failure Assessment (SOFA) score >6 on day 3 post-injury. These patients exhibited a significantly higher long-term mortality rate than those with early resolving TBI-MODS (etTBI-MODS) (65% vs. 13.7%, Table 1). This finding aligns with prior observations that sustained organ injury is a key determinant of secondary mortality following TBI⁴².

Table 1.

Baseline characteristics of patients with TBI

Demographics	ptTBI(n = 40)	etTBI (n = 103)
Age (yr)	49.9 ± 9.9	41.2 ± 7.8
Sex, male, n (%)	22(55%)	65(63.1%)
Clinical variables (Mean + SD)
on admission Blood pressure, mm Hg
Systolic blood pressure	92.1 ± 27.3	97.3 ± 20.9
Diastolic blood pressure	61.7 ± 11.9	66.5 ± 9.8
Mean arterial pressure	70.6 ± 11.2	75 ± 10.6
Heart rate, beats/min	104.1 ± 30.6	101.3 ± 35.8
APACHE III score	156.9 ± 11.7	92.3 ± 9.8
Nonpulmonary organ failures	2.4 ± 1.2	1.8 ± 1.1
Respiratory variables (Mean + SD)
Minute ventilation, L/min	14.2 ± 4.5	11.8 ± 3.9
Vt, ml	755 ± 121	706 ± 116
Respiratory rate, breaths/min	15.8 ± 6.6	14.6 ± 7.7
Peak inspiratory pressure, cm H2O	41 ± 1.3	34 ± 4.2
Plateau pressure, cm H2O	35 ± 7	31 ± 6
Mean airway pressure, cm H2O	21 ± 1.4	18 ± 1.2
PEEP, cm H2O	8.8 ± 1.11	8.2 ± 1.17
Arterial pH	7.44 ± 0.11	7.28 ± 0.14
PaCO2, mm Hg	42 ± 7.2	38 ± 5.5
PaO2, mm Hg	85.8 ± 14.3	92 ± 13.8
PaO2 /Fi O2 ratio	191.15 ± 64.3	220 ± 48.5
Injury characteristics (Median)
ISS	36	27
Preintubation GCS	10	12
BD (mmol/L)	7.2	6.7
Shock Index	1.2	1.1
Lactate (mmol/L)	5.8	5.0
AIS Head and Neck	3	2
AIS Face	2	2
AIS Thorax	3	2
AIS Abdo/Pelvis	4	2
AIS Extremity/Pelvis	3	2
Outcomes
28-day mortality (%)	65	13.7

Open in a new tab

APACHE III Acute physiology and chronic health evaluation III, AIS Abbreviated Injury Scale, BD base deficit, GCS Glasgow Coma Score, ICU intensive care unit, ISS Injury Severity Score, SBP systolic blood pressure.

At 4 h post-injury, ptTBI-MODS patients exhibited a markedly lower proportion of TMEM110^hiCD14⁺ monocytes in peripheral blood compared to etTBI-MODS patients (Fig. S14A and 7A), accompanied by significantly elevated levels of circulating cell-free mtDNA (Fig. 7B). Using a TOM22-based ELISA assay, we detected a substantial amount of non-programmatically released mitochondria in ptTBI-MODS plasma (Fig. 7C). A linear correlation analysis revealed a negative association between TMEM110^hi CD14⁺ monocyte frequency and plasma mtDNA abundance (Fig. S14B). Similarly, high concentrations of nuclear DNA (nDNA) were detected in both peripheral blood and cranial fracture fluid ultracentrifugates (Fig. S14C), while bacterial 16S-rRNA and endotoxin contamination were undetectable (Fig. S14D-E).

Fig. 7 — A CD14⁺CD16^- monocytes were sorted from peripheral blood of TBI-MODS patients 4 h post-injury, with the gating/sorting strategy shown in Fig. S7A. Representative flow cytometry histograms of intracellular TMEM110 fluorescence in early-stage TBI-MODS (etTBI-MODS; n = 102) and progressive-stage TBI-MODS (ptTBI-MODS; n = 40) patients are shown, and the proportion of TMEM110^hi CD14⁺CD16^- monocytes (MFI ≥ 10³) is quantified. B Serum mitochondrial DNA levels (cytB, Nadh, Cox2) in TBI-MODS patients 4 h post-injury (n = 20) were quantified by qPCR and expressed as ΔCt relative to gapdh. C Abundance of circulating decellularized mitochondria in TBI-MODS patients (n = 20) 4 h post-injury measured by ELISA using TOM22 with a recombinant TOM22 standard curve. D Based on median TMEM110 expression, ptTBI-MODS patients were stratified into TMEM110-high (n = 20) and TMEM110-low (n = 20) groups, and 28-day survival was monitored using Kaplan-Meier analysis. E SOFA scores on day 2 after admission in TMEM110^high and TMEM110^low ptTBI-MODS patients (n = 20 per group). F, G Serum IFN-α and IFN-β levels in ptTBI-MODS patients (n = 20) measured by ELISA. H ISG expression in sorted CD14⁺CD16^- monocytes within 12 h of admission (n = 20), quantified by qPCR and normalized to gapdh. I CD14⁺CD16^- monocytes from TBI-MODS patients were loaded with CalipHuor to assess lysosomal [H⁺] and [Ca²⁺]. Lysosomal pH and Ca²⁺ concentrations were calculated from O/R and D/A fluorescence ratio pairs. Representative pseudocolor fluorescence images acquired from the same cells (same field of view) in the indicated fluorescence channels are shown (left), with quantitative data presented (right). J Autoantibody abundance in serum from patients who died of multiple organ failure on day 10 post-injury, assessed using a Human Autoimmune Disease IgG Autoantibody Array G1. K Working model illustrating how TMEM110^hi CD14⁺ monocytes with impaired self-DNA handling may contribute to systemic immune dysregulation and disease progression in TBI-MODS. Data are presented as mean ± SD. For clinical datasets, n indicates the number of individual patients. Statistical analyses were performed using two-sided Mann–Whitney U tests (A–C), two-sided Welch’s t-test (F–I), and log-rank (Mantel-Cox) test for survival analysis (D). Representative images are shown for flow cytometry, fluorescence microscopy, and array data. Figure 7K was created in BioRender. Dwad, D. (2025) https://BioRender.com/sjs47bj. Source data are provided as a Source Data file.

Stratifying ptTBI-MODS patients based on median TMEM110 expression levels revealed that those in the low-TMEM110 group had significantly worse survival outcomes (Fig. 7D) and higher SOFA scores indicative of more severe organ dysfunction (Fig. 7E). This phenotype was associated with defective dsDNA clearance and an exacerbated type I interferon (IFN-I) response. At 24 h post-injury, serum levels of IFN-α and IFN-β were significantly elevated in the low-TMEM110 group (Fig. 7F, G), along with increased ISG mRNA expression (Fig. 7H). TMEM110 expression also influenced lysosomal ionic homeostasis: monocytes from the high-TMEM110 group exhibited lysosomal Ca²⁺ levels and pH values that were 0.25-fold and 1.92-fold those of the low-TMEM110 group, respectively (Fig. 7I).

In patients who succumbed to multi-organ failure by day 10 post-injury, we detected not only anti-dsDNA autoantibodies but also high titers of anti-nuclear (CENP-A/B, HisRS, PCNA) and anti-cytoplasmic (C-ANCA, SSB) autoantibodies in circulation (Fig. 7J). These findings suggest that low quantity TMEM110hi CD14⁺ monocytes is associated with poor prognosis in TBI-MODS and that TMEM110hi CD14⁺ monocytes may play a critical role in clearing non-programmatically released mitochondria from circulation. Moreover, TMEM110 expression is closely linked to post-TBI lysosomal Ca²⁺ overload during the hyperacute phase, early IFN-I cascade activation, and late-stage multi-organ autoimmune-associated injury (Fig. 7K).

Discussion

TBI remains a leading cause of death and permanent disability worldwide⁴³. Current treatment options are limited, and most candidate therapeutics have shown minimal benefit in clinical trials^44,45, largely due to the complexity of secondary injuries following TBI. The pathophysiology of TBI is characterized by irreversible primary damage at the site of impact, followed by progressive neuronal death in surrounding brain regions⁴⁶ and secondary injuries to distal peripheral organs⁴⁷. These processes are closely linked to the activation of resident glial cells (microglia and astrocytes)⁴⁸ and the mobilization of peripheral leukocytes, including monocytes and neutrophils^49,50. In animal models of controlled cortical impact (CCI)-induced TBI, suppression of IFN-I signaling alleviates neuroinflammation, reduces lesion volume⁵¹, and mitigates neurodegeneration⁵². Various strategies targeting IFN-I have been shown to attenuate MODS induced by brain trauma—manifested as cognitive impairment, lymphadenopathy, acute kidney and liver injury, and respiratory failure—which are major determinants of TBI-associated mortality⁴⁷. Therefore, understanding the mechanisms of IFN-I–mediated neurodegeneration and peripheral organ injury is crucial for developing effective long-term therapeutic strategies for TBI.

Mitochondrial disposal defects—including impaired mitochondrial delivery to lysosomes⁴³, defective lysosomal degradation^44–46, or disrupted mitochondrial quality control⁴⁷—represent potential shared mechanisms contributing to both secondary brain injury and peripheral organ failure following TBI. The cGAS–STING pathway plays a key role in innate immune sensing of cytosolic DNA. Cytosolic cGAS detects mitochondrial DNA (mtDNA) and generates cGAMP, which activates STING on the endoplasmic reticulum (ER) membrane^10,53. Regardless of the upstream stimulus, translocation of STING out of the ER is a critical step for the initiation of downstream IFN-I signaling. STING traffics along the ER–Golgi axis, where it recruits TBK1 and IRF3 to induce IFN-I production⁵⁴. Several ER-localized proteins have been identified as positive or negative regulators of STING, including ZDHHC1 (which promotes STING dimerization)⁵⁵, iRhom2 (which mediates vesicular transport of STING to the Golgi)⁵⁶, AMFR and INSIG (which assist in TBK1/IRF3 recruitment)⁵⁷, and STIM1 (which constitutively restrains STING in the ER)¹⁴. However, none of these regulators function as feedback mediators that maintain lysosomal homeostasis after STING exits the ER. This is crucial because the cytosolic accumulation of mtDNA must be promptly cleared by the lysosomal system to prevent hyperactivation of STING and overproduction of IFN-I.

STIM1, as an “ER-retention factor,” preserves STING in its inactive state under homeostasis. Its deficiency results in spontaneous STING activation and elevated IFN-I expression in both mice and patients with combined immunodeficiency¹⁴. The regulatory function of STIM1 as an ER calcium sensor is further enhanced by STIMATE, encoded by the TMEM110 gene¹⁶. In our study, TMEM110 displayed broader functions beyond STIM1 assistance. Through immunoprecipitation and protein interaction analyses, we identified TMEM110 as both an “ER-resident STING suppressor” and a “lysosomal TRPML1 activator,” acting as a feedback mediator between cytosolic nucleic acid sensors and lysosomal stability. Notably, TMEM110 regulates STING and TRPML1 independently of STIM1. In our previous work, TMEM110 deficiency in alveolar epithelial cells disrupted the immune-metabolic state of alveolar macrophages, resulting in spontaneous inflammation and respiratory dysfunction⁴⁹.

The lysosomal system plays an essential role in the clearance of self-DNA. One classical example is DNase II deficiency, which causes double-stranded DNA accumulation in microglia, leading to neuroinflammation and neurodegeneration via cGAS–STING activation⁵⁸. In this study, we identify and characterize an IFN-I–driven pathomechanism: phagolysosomal destabilization. In TBI models, phagocytosed mitochondria from necrotic debris displace protons within lysosomes, triggering calcium overload and membrane rupture. This leads to mtDNA leakage into the cytosol and activation of the cGAS–STING pathway. This mechanism is prominent in TBI-induced MODS, where IFN-I–related injury phenotypes are observed in distal brain regions and peripheral organs such as the lungs, liver, kidneys, and lymphatic tissues. We further found that TMEM110 is broadly expressed in peripheral monocytes. Under resting conditions, TMEM110 keeps STING sequestered in the ER. Upon stimulation, STING dissociates from the K/R region of TMEM110, exposing its D/E domain, which acts as a molecular “bait” to activate the lysosomal Ca²⁺ channel TRPML1, thereby initiating a homeostatic feedback loop. This mechanism is crucial for mtDNA clearance, lysosomal integrity, calcium balance, and suppression of aberrant nucleic acid–induced inflammation.

Importantly, naturally occurring STING mutations such as G207E and R281Q disrupt its interaction with TMEM110, resulting in constitutive STING activation. These mutations underlie SAVI and other interferonopathies⁴⁰. In our TBI model, mice carrying the STING G207E mutation exhibited increased mortality, supporting the central role of the TMEM110–TRPML1 axis in STING gatekeeping. Clinical sample analysis further revealed inter-individual heterogeneity in TMEM110 expression. TBI patients with higher TMEM110 levels had milder organ damage and reduced autoimmune features, suggesting a protective effect against distal organ injury. Notably, lysosomally targeted mRNA therapeutics encoding the TMEM110 D/E domain suppressed IFN-I responses, indicating its therapeutic potential for interferonopathies.

In conclusion, we identify a TMEM110-regulated STING–TRPML1–lysosome axis that is essential for maintaining immune homeostasis in response to cytosolic and extracellular DNA. This mechanism deepens our understanding of trauma, aging, neurodegeneration, and autoimmunity, while offering a therapeutic avenue for targeting dysregulated nucleic acid sensing. Sustained cGAS–STING activation also contributes to the pathogenesis of neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and ALS⁵⁹. Moreover, recent studies have shown that in lysosomal storage disorders (LSDs), neuronal cGAS–STING signaling is pathologically activated by undigested DNA, leading to neuronal death⁶⁰. Our proposed “phagolysosomal destabilization” model offers a unifying explanation by linking lysosomal dysfunction to cytosolic DNA accumulation and aberrant IFN-I signaling in neuronal degeneration. Finally, we acknowledge certain limitations in our study: tissue-resident macrophages such as microglia—key immune sentinels in TBI—are embryonically derived⁶¹, and do not appear to rely on TMEM110 for IFN-I regulation within their ER–lysosomal axis. Thus, future studies should investigate alternative mechanisms by which these macrophages handle mitochondrial debris after necrotic cell death.

Methods

Patient candidate cohort and inclusion criteria

This study is a prospective investigation approved by the Ethics Review Board of the Second Affiliated Hospital of Zhejiang University. All adult trauma patients (≥18 years old) who met the candidate cohort criteria were screened and included by the Department of Neurosurgery’s Trauma and Critical Care Center at the Second Affiliated Hospital of Zhejiang University. The candidate cohort consisted of high-energy extracranial trauma patients, defined by the following criteria: falls from a height (>3 meters), road traffic collisions (>30 mph), pedestrian/bicyclist/motorcyclist collisions with vehicles, ejection from a vehicle, death of co-occupants in a vehicle, crush injuries, or blast injuries. All data were obtained through post hoc interviews with patients or their legal representatives, with written informed consent signed. This follows the conventions of trauma-critical care prospective studies. Data from patients who did not provide informed consent were not publicly disclosed. All study procedures adhered to the ethical principles outlined in the Declaration of Helsinki.

Blood samples were collected within 2 h of admission, and Injury Severity Score (ISS)⁶² and Abbreviated Injury Scale (AIS)⁶³ for head and neck injuries were assessed. The Sequential Organ Failure Assessment (SOFA) score⁶⁴ was used to evaluate whether the patient developed Multiple Organ Dysfunction Syndrome (MODS). Patients with moderate or severe head injury (total ISS ≥ 25), SOFA score > 5, and involvement of two or more organs were included in the candidate cohort. Within 36 h of admission, clinical coordinators and research physicians assessed the primary clinical risk factors for MODS in each patient. These primary risk factors were classified as pneumonia, sepsis, aspiration pneumonia, trauma, or other (including drug overdose, multiple transfusions, and extracorporeal circulation). After excluding all major risk factors unrelated to trauma, a final cohort with a single clinical risk factor, unaffected by other factors, was determined. All subjects were excluded if they had multisystem diseases, infections, or recent drug treatments.

A total of 319 patients were included in the candidate cohort, of which 143 met the study criteria and were ultimately enrolled. Based on follow-up data, traumatic brain injury-related MODS (TBI-MODS) was classified into two subtypes: early recovery MODS (etTBI, n = 103), defined as a SOFA score dropping below 6 within 7 days; and delayed recovery MODS (ptTBI, n = 40), defined as a SOFA score dropping below 6 prior to death or between 8-28 days. Baseline characteristics of all candidate cohorts are summarized in Table 1. The study site was equipped with trained personnel who could perform flow cytometry, blood gas analysis, complete blood counts, and blood component testing at any time.

Transgenic mouse models

As previously described⁴⁹, we generated TMEM110 conditional knockout mice (TMEM110^cKO). Using CRISPR/Cas9-mediated genome editing technology, we inserted the TMEM110^flox/+ allele carrying a Flox site into the C57BL/6 J background mice (NCBI reference sequence: NM_028839.4; Ensembl: ENSMUSG00000006526). TMEM110^flox/flox mice were crossed with Lyz2-Cre tool mice (Lyz2 specifically expresses Cre recombinase in monocytes) to generate TMEM110^flox/+; Lyz2-Cre mice. Further backcrossing resulted in the generation of TMEM110^flox/flox; Lyz2-Cre homozygous mice, namely TMEM110^cKO mice.

To construct STING point mutation mice, we synthesized Donor Oligos containing the TMEM173 gene Chr5 (GRCh38): g.139478409 C > T mutation site, and injected these along with Cas9 protein and mRNA into fertilized eggs. Positive F0 mice were screened by sequencing and used to breed the offspring. F0 mice were crossed with wild-type mice and backcrossed, resulting in the generation of STING G207E point mutation mice (homozygous). These STING mutant mice were constructed with the assistance of Cyagen Biosciences (Suzhou, CHN). Additionally, Ifnar KO (stock no. 032045) and mb21d1 KO (stock no. 026554) mice were purchased from Jackson Laboratory, and Tlr7 KO mice (stock no. 02979) were provided by Cyagen Biosciences. All of these mice have immune dysfunction and should be strictly housed in SPF-level animal facilities.

TBI model and evaluation

A controlled cortical impact (CCI) model was established using a standardized weight-drop device to induce experimental closed traumatic brain injury (TBI). Briefly, 8-week-old mice were anesthetized with ether anesthesia, a longitudinal midline scalp incision was made to expose the skull. Mice were placed on a stereotaxic frame to ensure head immobilization and positioning accuracy. Core body temperature was monitored and maintained at 37 ± 0.5 °C using a heating pad throughout the procedure. After immobilizing the mouse head, a 20 g weight was dropped vertically from a height of 20 cm onto the left hemisphere to induce localized blunt force injury. Following the injury, the scalp incision was sutured, and all mice were given 100% oxygen support until full recovery from anesthesia. Post-operative care included subcutaneous injection of 0.5 mL sterile saline to prevent dehydration. Analgesia was provided through intraperitoneal injections of fentanyl (0.05 mg/kg) every 12 h.

Twelve hours post-injury, mice were administered 100 μg/mL of TM4-5 D/E mRNA-LNP via intraperitoneal injection. LNPs were freshly prepared and filtered through a 0.22 μm sterile membrane before use. Blood samples were collected at designated time points for the evaluation of multi-organ damage and dysfunction, including liver function (AST/ALT), kidney function (serum creatinine and blood urea nitrogen) and indicator of blood-brain barrier function (GFAP). Tissues from the lungs, liver, and kidneys were fixed in 4% paraformaldehyde for 48 h. Following standard histological procedures, the tissues were paraffin-embedded and sectioned for hematoxylin and eosin (HE) staining and immunohistochemical analysis. Images were captured using an Olympus BX51 microscope equipped with a DP72 camera. The pathological tissue scoring was performed independently by three board-certified pathologists based on standardized injury scoring criteria (Supplementary Table S1). Inter-rater reliability was statistically analyzed to ensure scoring consistency.

Tissue processing and flow cytometric analysis of myeloid cells

Mouse anesthesia and euthanasia. Mice were anesthetized by intraperitoneal injection of 250 μL 0.9% sodium pentobarbital solution. For organ collection, mice were euthanized by cervical dislocation. Peripheral blood was collected via cardiac puncture into anticoagulant tubes on ice.

For peripheral blood processing. Collected blood was transferred into a 50 mL conical tube containing 10 mL of 1× ACK lysis buffer and incubated at room temperature (20–26 °C) for 5 min. Lysis was stopped by adding 20 mL PBS, followed by centrifugation at 1350 rpm (375 ×g) for 5 min at 4 °C. The cell pellet was resuspended in 5 mL ACK buffer, incubated for another 5 min at room temperature, then washed again with 20 mL PBS and centrifuged. The final cell pellet was resuspended in 2 mL FACS buffer and kept on ice until staining.

For bone marrow cell preparation. Femurs and tibias were isolated immediately post-mortem and cleaned of muscle tissue in ice-cold PBS. Bone marrow was flushed using a 25 G needle with PBS into a Petri dish, dissociated by pipetting, and filtered through a 40 μm cell strainer into a 15 mL tube. Red blood cells were lysed with 2–3 mL ACK buffer on ice for 1–2 min, and the reaction was stopped with 10 mL PBS. Cells were centrifuged at 300 ×g for 5 min at 4 °C and washed once with PBS.

For organ dissociation. Lungs, liver (one lobe), kidney (one side), and whole brain were collected post-euthanasia and immediately placed in ice-cold PBS. For brain tissue, the sample was minced into small pieces in a 2 mL round-bottom tube, then transferred to a 6-well plate with a total of 3 mL of tissue digestion solution and incubated at 37 °C for 60 min. Tissues were further dissociated using a 1.2 mm internal diameter syringe until no visible clumps remained. The suspension was filtered through a 70 μm cell strainer into a 50 mL tube and washed with 10 mL PBS. Cells were centrifuged at 1350 rpm (375 ×g) for 5 min at 4 °C and resuspended in 8 mL of 40% Percoll. This was gently layered onto 5 mL of 80% Percoll in a 15 mL tube and centrifuged at 2800 rpm (1578 ×g) for 20 min at room temperature. Mononuclear cells at the interphase were collected, washed with PBS, and resuspended in 2 mL FACS buffer on ice.

For lung, liver, and kidney samples, the same digestion protocol was applied. Briefly, tissues were minced, incubated in 3 mL digestion solution at 37 °C for 60 min, dissociated with a 1.2 mm syringe, filtered through a 70 μm cell strainer, and washed with 10 mL PBS. Cells were centrifuged at 1350 rpm (375 ×g) for 5 min at 4 °C, treated with 5 mL ACK buffer at room temperature for 5 min, washed again with 20 mL PBS, and resuspended in 2 mL FACS buffer on ice.

For each sample, approximately 2 × 10⁶ cells were transferred into a labeled FACS tube containing 1 mL FACS buffer and centrifuged at 1350 rpm (375 ×g) for 5 min at 4 °C. Cells were resuspended in 70 μL Fc-blocking buffer and incubated on ice for 15 min. Then, antibody cocktails were added, vortexed briefly, and incubated in the dark at 4 °C for 30 min. After staining, cells were washed with 1 mL FACS buffer and centrifuged. For non-lung and non-brain tissues, cells were resuspended in 120 μL FACS buffer and 40 μL DAPI (final concentration: 250 ng/mL). For lung and brain samples, cells were first incubated with 0.25 μL PE-Cy7–conjugated streptavidin in 70 μL FACS buffer for 30 min in the dark, washed, and then stained with DAPI as above.

Samples were acquired on a BD Symphony flow cytometer. Unstained and single-stained controls were used for PMT voltage adjustment and compensation to ensure clear separation of positive and negative populations.

Bone marrow transplantation and chimerism assessment

Donor mice were C57BL/6-CD45.1⁺ WT(6–8 weeks old; Jackson Laboratory). Recipient mice were C57BL/6-CD45.2⁺ TMEM110cKO (6–8 weeks old). Recipient mice were lethally irradiated prior to transplantation to ablate endogenous hematopoiesis.

Donor mice were euthanized via CO₂ asphyxiation and sterilized with 70% ethanol. Under aseptic conditions, femurs and tibias were harvested, and bone marrow was flushed using a 25 G needle with ice-cold PBS containing 2% FBS. The cell suspension was filtered through a 70 μm cell strainer and red blood cells were lysed using ACK lysis buffer (Thermo Fisher) for 2 min at room temperature. Cells were washed twice with PBS and resuspended at a concentration of 5 × 10⁶ cells/mL in sterile PBS.

Irradiation and transplantation. Recipient mice received a split-dose total body γ-irradiation (4.5 Gy × 2, 4 h apart) using a ^137Cs source (X-RAD 320, Precision X-Ray). Within 24 h after irradiation, each mouse was injected intravenously via the tail vein with 1 × 10⁶ donor bone marrow cells in 200 μL PBS using a 29 G insulin syringe. Mice were maintained on autoclaved chow and acidified drinking water supplemented with 1.1 g/L neomycin (Sigma) for 14 days post-transplantation.

Chimerism analysis. Eight weeks after transplantation, peripheral blood was collected via retro-orbital bleeding into EDTA-coated microtubes. Red blood cells were lysed, and leukocytes were stained with anti-CD45.1-FITC (BioLegend) and anti-CD45.2-APC (BioLegend) for 30 min at 4 °C in the dark. Samples were washed and analyzed on a BD FACSCanto II flow cytometer. Chimerism was calculated as the percentage of CD45.1⁺ cells among total CD45⁺ leukocytes.

Cell culture and reagents

Human monocyte-derived CD14⁺ cells (hMoCD14⁺, Cat. No. C-12909) were purchased from PromoCell (Germany). These cells were cultured in Dendritic Cell Generation Medium (PromoCell) and maintained at 37 °C with 5% CO2. Cells were passaged 2-3 times per week at a 1:3 ratio. For confocal imaging experiments, cells were cultured in medium without 2-mercaptoethanol for 48 h prior to the experiment to induce mild cell adherence. For URmtDNA endocytosis experiments, mitochondria/cytoplasm separation was performed using a Mitochondria/Cytosol Fractionation Kit (Biovision, CA, USA) according to the manufacturer’s instructions. Briefly, approximately 10⁶ cells were resuspended in 2 mL of 1× cytosolic extraction buffer. Cells were processed with a Potter-Elvehjem PTFE grinder and glass tube (Sigma, P7859-1EA). After grinding, cells were centrifuged at 1200 rpm for 10 min at 4 °C to collect the supernatant. The supernatant was then centrifuged at 12,000 rpm for 10 min at 4 °C, with the final supernatant representing the cytosolic fraction. The pellet was washed with 1 mL of cytosolic extraction buffer and centrifuged to isolate the mitochondrial-enriched pellet.

hMoCD14⁺ cells (2.5 × 10⁴) were plated into 6-well plates and treated with 100 ng/mL exogenous mitochondria (quantified using the BCA method) for 4 h. After treatment, cells were washed once with culture medium and collected for further experiments. Pitstop 2 (MedChemExpress, NJ, USA), BAPTA-AM (MedChemExpress), and ethidium bromide (MedChemExpress) were used for endocytosis inhibition, calcium depletion, and mtDNA depletion experiments, respectively.

Plasmid construction and gene knockout

TMEM110, LAMP1, CHMP4A, TRPML1, and STING gene fragments were amplified from a human cDNA library using restriction enzyme sites KasI/SbfI. The PCR products were digested with KasI/SbfI (New England Biolabs, MA, USA) and ligated into similarly digested PUC19 cloning vector (New England Biolabs) using T4 DNA ligase to create the initial clones.

Using the Gateway cloning system, the LAMP1 fragment was inserted into the pEYFP-N1d vector (Life Technologies, Shanghai, CHN) at the restriction enzyme sites to generate the LAMP1-YFP construct. The TMEM110 fragment was inserted into the pcDNA-3.1 vector (Life Technologies) to create the TMEM110-mCherry overexpression vector. The CHMP4A fragment was inserted into pcDNA-3.1 (Genscript, NJ, USA) to generate the CHMP4A-mCherry reporter vector. The TRPML1 fragment was inserted into pCDNA-DEST54 (Life Technologies) to construct the GFP-TRPML1 vector. Similarly, TRPML1 fragments were cloned into either pEYFP-N1 or pECFP-N1 (ClonTech, Beijing, CHN) to generate TRPML1-YFP and TRPML1-CFP constructs. TMEM110 was cloned into pEYFP-N1 to generate the TMEM110-CFP construct, and STING was inserted into pECFP-N1 to construct the STING-CFP vector.

Shortened mutant variants of TMEM110, TRPML1, and STING were generated by PCR amplification using specific primers and cloned into the BamHI and XhoI sites of the pProEX HTb vector (Life Technologies) or Flag-tagged plasmids to express His6 and Flag fusion-tagged proteins. Site-directed mutagenesis of STING-CFP point mutants and TMEM110 D/E variants was performed using the Q5 Site-Directed Mutagenesis Kit (New England Biolabs) and confirmed by Sanger sequencing. Sequence deletion mutants for TRPML1 295–327 (TM2), STING 181–339 (CDN), and TMEM110 275–289 (K/R) were generated using SOE primers and verified by Sanger sequencing.

Gene knockout of TMEM110, cGAS, STING, and STIM1 was achieved using the CRISPR-Cas9 system. Exonic sgRNAs, designed using the online tool (http://crispr.mit.edu/), were inserted into the pSpCas9(BB)−2A-Puro vector (Addgene, MA, USA) at the appropriate restriction sites. The human monocytic cell line hMoCD14+ cells was cultured in RPMI 1640 supplemented with 10% FBS at 37 °Cunder 5% CO₂. For transfection, cells in logarithmic growth (2-5×10⁵ cells/mL) were transfected with endotoxin-free plasmid DNA (1 μg total per 24-well) using Lipofectamine 3000, following the manufacturer’s protocol. Briefly, plasmids were diluted in Opti-MEM, mixed with Lipofectamine 3000 (1:1.5 mass/volume ratio), and incubated for 15 min at room temperature to form complexes. The mixture was added dropwise to cells in antibiotic-free medium. After 6-8 h, the medium was replaced with complete medium. The cells were treated with 2 μg/mL Puromycin for 48-72 h to eliminate untransfected cells, followed by fluorescence-activated cell sorting to isolate the GFP-positive population. The sorted cells were then subjected to limiting dilution (0.5-1 cell/well) in a 96-well plate and cultured for 2-3 weeks under optimal conditions to obtain monoclonal stable cell lines. For functional assays, cells were harvested at 48-72 h post-transfection for Western blot analysis. The sequences of all sgRNAs are provided in Supplementary Table S2.

Total RNA was extracted from TRIzol-treated cells using the Direct-zol RNA isolation kit (Zymo Research, CA, USA), and RNA concentration and quality were measured using a NanoDrop ND-1000 spectrophotometer. cDNA synthesis was carried out using 2-3 μg of total RNA, oligo(dT) primers, and Maxima Reverse Transcriptase (Thermo Fisher Scientific, MA, USA). Real-time quantitative PCR was performed with iTaq Universal SYBR Green Supermix (Bio-Rad, CA, USA) using a iCycler IQ5 system (Bio-Rad) and gene-specific primers. For cytosolic mtDNA detection, mitochondria/cytosolic fractions were isolated using the Mitochondria/Cytosol Fractionation Kit (Biovision, CA, USA). Total DNA was extracted from 300 μL of cell cytosol using the QIAquick Nucleotide Removal Kit (Qiagen, Düsseldorf, Germany), with elution in 30 μL buffer. mtDNA quantification was carried out on the QX200 Droplet Digital PCR System (Bio-Rad), using ND1 (Bio-Rad) and β-actin as internal controls. The primer sequences required for all PCR assays are also listed in Supplementary Table S2.

Co-immunoprecipitation (Co-IP) and western blot analysis

Plasmids encoding full-length or truncated FLAG-tagged TMEM110 and 6×His-tagged TRPML1 or His-STING were transfected into 2×10⁷ hMoCD14⁺ cells. Following cell lysis with IP buffer (20 mM Tris-HCl [pH 7.4], 100 mM NaCl, 0.1% NP-40, 1 mM EDTA, 5% glycerol, 10 mM NaF, 1 mM sodium orthovanadate, and 0.1 mM PMSF), the lysates were centrifuged at 100,000 × g for 1 h at 4 °C and precleared with Protein G-Sepharose beads. The lysates were then incubated with FLAG-conjugated resin for 6 h to perform immunoprecipitation. After washing the immunoprecipitates five times with lysis buffer, the target proteins were detected using the JESS automated Western blot analysis system (Bio-Techne, ProteinSimple, CA, USA).

For endogenous immunoprecipitation, hMoCD14⁺ cells were lysed with the same lysis buffer, and the lysates were centrifuged at 100,000 × g for 1 h. The pre-cleared lysates were incubated overnight with 2 μg of anti-STING antibody (Abcam) and further incubated for 2 h with Protein G-Sepharose. The total protein concentration of the cell lysates was quantified using the BCA Protein Assay Kit. For each sample, 5 μg of total protein was loaded onto the JESS system, and capillary electrophoresis was performed using a 12–230 kDa separation module (SM-W008) according to the manufacturer’s instructions. Western blot results were analyzed using Compass software (Protein Simple) to determine the relative expression of the proteins.

Fluorescence imaging

hMoCD14⁺ cells transfected with either single-expression (LAMP1-GFP) or dual-expression (TMEM110-CT-mCherry, TRPML1-GFP) plasmids were seeded at a very low density in 35 mm glass-bottom culture dishes and cultured overnight. Non-adherent cells were removed by washing with DMEM containing 10 mM HEPES, 100 μg/ml penicillin, 100 μg/ml streptomycin, and 10% heat-inactivated fetal bovine serum (Gibco, CA, USA). Following URmtDNA endocytosis stimulation, cells were pre-stained with anti-CD14 antibody and a secondary antibody labeled with Dylight 405. GFP was excited with a 488 nm laser, while mCherry was excited with a 561 nm laser, and images were acquired using confocal microscopy. For the TMEM110-CT-mCherry and STING-GFP dual-expression vectors, the same treatment was applied for TIRF imaging.

Confocal images were acquired on a Leica STELLARIS DIVE Confocal System (Wetzlar, Germany), and TIRF images were obtained using a NIKON Eclipse Ti-E microscope (Tokyo, Japan). Intracellular Ca²⁺ fluorescence was measured using Fura-2 AM dye (MedChemExpress), and the fluorescence intensity ratio between 340 nm and 380 nm excitation wavelengths was used to calculate intracellular Ca²⁺ concentration, following our previously established methodology⁴⁹. For URmtDNA-induced Ca²⁺ release measurements, the fluorescence intensity ratio (340 nm/380 nm) was recorded in the LAMP1-YFP-positive lysosomal peripheral region (550 nm–750 nm concentric circle). The total accumulated value of lysosomal Ca²⁺ hotspots was determined by calculating the area under the curve (AUC) for the fluorescence intensity ratio curve within 0–120 s. All experiments were performed at room temperature.

Fluorescence resonance energy transfer (FRET) measurements

FRET measurements were conducted in hMoCD14⁺ cells expressing the fluorescence probes YFP-TM6-TRPML1-TM1-CFP to induce URmtDNA endocytosis. The system, equipped with an Optosplit II image splitter (Andor Technology, UK), captured raw fluorescence data through the following filters (FCFP, FYFP, and Fraw), recording every 10 min at room temperature. The CFP channel used 428.9 ± 5.5 nm excitation and 465 ± 32 nm emission, the YFP channel used 502.6 ± 11.2 nm excitation and 549 ± 21 nm emission, and the FRETraw channel used 428.9 ± 5.5 nm excitation and 549 ± 21 nm emission. Fluorescence images were collected and processed using MetaFluor software (Molecular Devices, CA, USA), and the data were further analyzed using Matlab R2012b (MathWorks, MA, USA). The FRET efficiency (Eapp) was calculated according to the formula described by Jing et al.¹⁶.

Lysosome analysis

Peripheral blood mononuclear cells were isolated from WT or TMEM110 cKO mice via density gradient centrifugation. Briefly, whole blood was collected from anesthetized mice via cardiac puncture into heparin-coated tubes and diluted 1:1 with PBS containing 1% FBS. The diluted blood was carefully layered over 3 mL of Ficoll-Paque PLUS in a 15 mL conical tube and centrifuged at 400 ×g for 20–30 min (room temperature, without brake). The PBMC layer (white interface) was collected, washed twice with PBS (300 × g, 10 min), and residual red blood cells were lysed using ACK buffer. Cells were resuspended in RPMI-1640 medium, counted via trypan blue exclusion, and processed for downstream applications. For monocyte subset isolation, cells were labeled with anti-CD11b and anti-Ly6C antibodies followed by magnetic sorting. For lysosomal pH/[Ca²⁺] measurement, PBMC or hMoCD14⁺ cells were treated with 500 nM CalipHluormLy for 1 h and then cultured for 9 h at a very low density in culture dishes. After washing with PBS, the cells were imaged in Hank’s balanced salt solution. Imaging and data acquisition were performed on an IX83 research inverted microscope (Olympus, Tokyo, Japan) using a 100×, 1.42 NA, DIC oil-immersion objective and an Evolve Delta 512 EMCCD camera. Fluorescence intensities were acquired using the following wavelengths: Alexa 488 (480/20 nm excitation, 520/40 nm emission), Alexa 647 (640/30 nm excitation, 705/72 nm emission), FRET (480/20 nm excitation, 705/72 nm emission), and Rhod-5F (545/25 nm excitation, 595/50 nm emission). The fluorescence intensities of the four channels (O/R ratio, D/A ratio) were used to evaluate lysosomal pH and [Ca²⁺], following the formula described by Narayanaswamy N²⁰. To generate calibration curves for intracellular pH and calcium levels, cells were incubated in calcium-clamping buffer composed of 10 mM HEPES, 10 mM MES, 10 mM sodium acetate, 10 mM EGTA, 140 mM KCl, 5 mM NaCl, and 1 mM MgCl₂. Free calcium concentrations were titrated from 1 μM to 10 mM, and buffer pH values were adjusted to span the desired calibration range. The buffer was supplemented with 50 μM nigericin, 50 μM monensin, and 20 μM ionomycin to facilitate ion equilibration across intracellular compartments. Cells were incubated in the calibration buffer at room temperature for 2 h.

For lysosomal membrane permeability (LMP) and membrane integrity detection, acridine orange assay was performed according to the manufacturer’s protocol. Briefly, 1×10^6 cells were collected, centrifuged at 300 g for 5 min, and the supernatant was removed. The cell pellet was resuspended in 100 μl pre-warmed clearing solution and centrifuged again. After removing the supernatant, 100 μl of acridine orange (fluorescent dye) was added, and the cells were incubated for 15 min at 37 °C, avoiding light. After centrifugation, the supernatant was removed, and the cells were resuspended in pre-warmed clearing solution for flow cytometry analysis. LMP was evaluated by detecting FL1 (488 nm excitation, 528 nm emission) and FL3 (555 nm excitation, 617 nm emission) fluorescence. A right shift in FL1 and a left shift in FL3 indicate enhanced membrane permeability or compromised membrane integrity.

For lysosomal membrane ESCRT repair efficiency, hMoCD14⁺ cells co-transfected with CHMP4A-mCherry and LAMP1-GFP were seeded at a very low density in culture dishes. After URmtDNA endocytosis stimulation, cells were imaged by confocal microscopy, and the overlap of CHMP4A and LAMP1 fluorescence points was analyzed using ImageJ. For lysosomal DNAase II activity detection, lysosomes and cytosolic fractions were isolated using the Lysosome Isolation Kit (Merck, Darmstadt, Germany) following the manufacturer’s instructions. After protein lysis, DNAase II activity was assessed by Fully Automated Western Blot analysis.

For lysosomal ion outflow monitoring, lysosomal ion outflow was monitored using an improved patch-clamp technique for isolated intralysosomal electrophysiology. All experiments were performed using hMoCD14⁺ cells transfected with TRPML1-mCherry and Lamp1-YFP plasmids via Lipofectamine 2000 (Invitrogen, CA, USA). The cells were treated with 1 µM vacuolin-1 for approximately 1 h to selectively enlarge endosomes and lysosomes. The enlarged LELs were recorded for all-intralysosomal currents. Briefly, the patch pipette was pressed onto the cell and rapidly pulled to cut the cell membrane. The enlarged LEL was released into the culture dish and monitored by the fluorescence of EGFP-TRPML1, mCherry-TRPML1, or EGFP-Lamp1. The bath solution (internal/cytoplasm) contained 140 mM K-Gluconate, 4 mM NaCl, 1 mM EGTA, 2 mM Na2-ATP, 2 mM MgCl2, 0.39 mM CaCl2, 0.1 mM GTP, 10 mM HEPES (adjusted to pH 7.2, with free [Ca²⁺]i about 100 nM). The pipette solution was a standard extracellular solution (modified Tyrode’s solution) with a pH of 4.6, containing 145 mM NaCl, 5 mM KCl, 2 mM CaCl2, 1 mM MgCl2, 20 mM HEPES, and 10 mM glucose (adjusted to pH 7.4). All bath solutions were applied via a rapid perfusion system for complete solution exchange within a few seconds. Data were collected using an Axopatch 2 A patch-clamp amplifier, Digidata 1440, and pClamp 10.0 software (Axon Instruments, CA, USA). The all-intralysosomal current was digitized at 10 kHz and filtered at 2 kHz. All experiments were performed at room temperature (21–23 °C), and the recordings were analyzed using pCLAMP 10 (Axon Instruments, Union City).

TM4-5 D/E mRNA-LNP construction

TM4-5 D/E mRNA-LNP construction was carried out by cloning the TM4-5-D/E sequence, mCherry sequence, and an artificially synthesized lysosomal targeting sequence (LTS) DNA fragment into the pIVTRup-T7 plasmid vector (Biovector) via a Golden Gate reaction. The plasmid product (2 µl) was transformed into Turbo Competent cells and plated on agar plates containing kanamycin. Non-green colonies were selected for small-scale preparation and sequencing. The pIVTRup-T7 plasmid was linearized by primer amplification for 30 cycles to obtain template DNA, which was then purified using a column before RNA synthesis. In vitro transcription (IVT) was performed using T7 RNA polymerase (NEB) with 1 µg mRNA template in a 20 µl reaction. The reaction was incubated at 37 °C for 2 h with shaking at 1000 rpm. After the IVT reaction, 2 µl of DNase I was used to degrade the IVT template, and the reaction was incubated at 37 °C for 20 min, followed by column purification of the IVT mRNA product. TM4-5 D/E mCherry mRNA-LNPs were formed by self-assembling the negatively charged mRNA with ionizable lipids. Specifically, a lipid solution containing ionizable lipids, 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), cholesterol, and polyethylene glycol lipid (molar ratio 50:10:38.5:1.5) was mixed with mRNA citrate buffer in a 1:2 ratio using a syringe pump and microfluidic chip system. After mixing, the solution was filtered through a 0.22 μm filter and stored at 4 °C for future use.

Autoantigen detection

For autoantigen detection, patient and mouse lung homogenates were analyzed using the Human Autoimmune Disease IgG Autoantibody Array G1 (Raybiotec, GA, USA) according to the manufacturer’s instructions. For the matrix, the instructions were followed. For detection of autoantibodies in mouse peripheral plasma, Anti-dsDNA IgG, IgA, IgE, IgM ELISA kits (Alpco, Wuhan, CHN) were used.

Protein interaction prediction

Protein interaction prediction was performed using AlphaFold 3.0 (Google DeepMind, CA, USA) with the multimer prediction model (https://alphafoldserver.com/) to model interactions between TMEM110/TRPML1 and TMEM110-STING. Visualization and analysis of protein interaction interfaces were done using PyMOL (eLano Scientific LLC).

Statistics & reproducibility

No statistical method was used to predetermine sample size in all the highly controlled in vitro or in vivo experiments, but our sample sizes are similar to those reported in previous publications. For each experiment, we aimed for at least three samples or animals per group to allow basic statistical significance. The exact sample sizes used for each experiment are provided in the corresponding figure legends.

No data were excluded from the analyses.

All experiments were reliably reproduced, and data are presented as mean ± s.d. unless otherwise stated. All experiments were repeated with at least three independent biological donors or performed independently three times. Statistical significance between experimental groups was assessed using two-tailed Student’s t-tests or one-way or two-way analysis of variance (ANOVA) followed by the appropriate post hoc test or other specified statistical methods, as indicated in the respective figure legends. A P value of 0.05 or less was considered statistically significant.

For in vitro experiments, cells were randomly allocated into control and experimental groups. For in vivo experiments, age- and sex-matched mice were randomized into control and experimental groups.

Investigators responsible for data collection were blinded to treatment allocation. No blinding was used for in vitro experiments. The majority of data collection involved quantifiable endpoints for which blinding would not influence measurement bias.

Ethical statement

All specimens were obtained through the Department of Neurosurgery’s Trauma and Critical Care Center at the Second Affiliated Hospital of Zhejiang University with full ethical compliance. Each sample is accompanied by a post-donation signed informed consent form from the donor, explicitly permitting the use of their bodily fluid samples for scientific research. The study protocol was approved by the Medical Ethics Committee of the Second Affiliated Hospital of Zhejiang University (approval number: 1350-1362-20220228).

All protocols involving animals in this study were approved by the Institutional Animal Care and Use Committee (IACUC) of Second Affiliated Hospital of Zhejiang University and were carried out in accordance with the approved guidelines (approval no. 1776-1789-20210228).

Reporting summary

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

Supplementary information

Supplementary Information File^{(6.1MB, pdf)}

Reporting summary^{(7.9MB, pdf)}

Transparent Peer Review file^{(18.9KB, pdf)}

Source data

Source Data Excel file^{(1.3MB, zip)}

Acknowledgements

This research was supported by the National Natural Science Foundation of China (32471002, 82401829, 82472617, and 82404553; F.Z.Y.), the National University of Singapore (NUHSRO/2020/133/Startup/08, NUHSRO/2023/008/NUSMed/TCE/LOA, NUHSRO/2021/034/TRP/09/Nanomedicine, NUHSRO/2021/044/Kickstart/09/LOA, 23-0173-A0001; C.X.Y.), the National Medical Research Council (MOH-001388-00, CG21APR1005, MOH-001500-00, MOH-001609-00; C.X.Y.), the Singapore Ministry of Education (MOE-000387-00; C.X.Y.), the National Research Foundation (NRF-000352-00; C.X.Y.), the Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang (2023R01002; Z.G.W.), the Distinguished Young Scientists Fund of Zhejiang (LR25H250001; Z.G.W.), and the National Science and Technology Major Project of China (No. 2025ZD1802201; Z.G.W.).

Author contributions

FZY, PYB, ZJ, and CLX designed and performed the majority of experiments, analyzed data, and contributed equally to this work. LQ, ZXB, WP, XZL, and HYJ assisted with animal studies, histopathological evaluations, and technical validations. ZJH supported imaging analysis and provided critical methodological input. LXK, CXY, and WZG supervised the project, provided conceptual guidance, and secured funding. FZY wrote the manuscript with input from all authors. All authors reviewed and approved the final manuscript.

Peer review

Peer review information

Nature Communications thanks John R Lukens, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Data availability

Raw fluorescence microscopy and hematoxylin and eosin (H&E) staining images are not publicly available due to large file sizes, instrument-specific formats, and institutional data management restrictions; however, all processed and representative images supporting the findings of this study are included in the paper and its supplementary materials. All other data, including raw imaging data, are available from the corresponding author upon request. Source data are provided with this paper.

Competing interests

Xiaoyuan Chen is a co-founder of and holds shares in Yantai Lannacheng Biotechnology Co., Ltd. The remaining authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Zunyong Feng, Yuanbo Pan, Jing Zhou, Liuxi Chu.

Contributor Information

Zunyong Feng, Email: fengzy@wmu.edu.cn.

Xiaokun Li, Email: xiaokunli@wmu.edu.cn.

Xiaoyuan Chen, Email: chen9647@gmail.com, Email: chen.shawn@nus.edu.sg.

Zhouguang Wang, Email: wangzhouguang@wmu.edu.cn.

Supplementary information

The online version contains supplementary material available at 10.1038/s41467-026-68382-8.

References

1.GBD 2017 Disease and Injury Incidence and Prevalence Collaborators Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet392, 1789–1858 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Gruen, R. L. et al. Haemorrhage control in severely injured patients. Lancet380, 1099–1108 (2012). [DOI] [PubMed] [Google Scholar]
3.Krishnamoorthy, V., Komisarow, J. M., Laskowitz, D. T. & Vavilala, M. S. Multiorgan dysfunction after severe traumatic brain injury: epidemiology, mechanisms, and clinical management. Chest160, 956–964 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Zhang, Q. et al. Circulating mitochondrial DAMPs cause inflammatory responses to injury. Nature464, 104–107 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
5.West, A. P. & Shadel, G. S. Mitochondrial DNA in innate immune responses and inflammatory pathology. Nat. Rev. Immunol.17, 363–375 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Lood, C. et al. Neutrophil extracellular traps enriched in oxidized mitochondrial DNA are interferogenic and contribute to lupus-like disease. Nat. Med22, 146–153 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Simmons, J. D. et al. Elevated levels of plasma mitochondrial DNA DAMPs are linked to clinical outcome in severely injured human subjects. Ann. Surg.258, 591–596 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Li, Z. & Nakatogawa, H. Degradation of nuclear components via different autophagy pathways. Trends Cell Biol.32, 574–584 (2022). [DOI] [PubMed] [Google Scholar]
9.Liddicoat, B. J. et al. RNA editing by ADAR1 prevents MDA5 sensing of endogenous dsRNA as nonself. Science349, 1115–1120 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Decout, A., Katz, J. D., Venkatraman, S. & Ablasser, A. The cGAS-STING pathway as a therapeutic target in inflammatory diseases. Nat. Rev. Immunol.21, 548–569 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Deng, L. et al. STING-dependent cytosolic DNA sensing promotes radiation-induced type I interferon-dependent antitumor immunity in immunogenic tumors. Immunity41, 843–852 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
12.King, K. R. et al. IRF3 and type I interferons fuel a fatal response to myocardial infarction. Nat. Med23, 1481–1487 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Marichal, T. et al. DNA released from dying host cells mediates aluminum adjuvant activity. Nat. Med17, 996–1002 (2011). [DOI] [PubMed] [Google Scholar]
14.Srikanth, S. et al. The Ca2+ sensor STIM1 regulates the type I interferon response by retaining the signaling adaptor STING at the endoplasmic reticulum. Nat. Immunol.20, 152–162 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Nunes, P. et al. STIM1 juxtaposes ER to phagosomes, generating Ca²⁺ hotspots that boost phagocytosis. Curr. Biol.22, 1990–1997 (2012). [DOI] [PubMed] [Google Scholar]
16.Jing, J. et al. Proteomic mapping of ER-PM junctions identifies STIMATE as a regulator of Ca²⁺ influx. Nat. Cell Biol.17, 1339–1347 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Quintana, A. et al. TMEM110 regulates the maintenance and remodeling of mammalian ER-plasma membrane junctions competent for STIM-ORAI signaling. Proc. Natl. Acad. Sci. USA112, E7083–E7092 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Lan, Y. Y., Londoño, D., Bouley, R., Rooney, M. S. & Hacohen, N. Dnase2a deficiency uncovers lysosomal clearance of damaged nuclear DNA via autophagy. Cell Rep.9, 180–192 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Kawane, K. et al. Chronic polyarthritis caused by mammalian DNA that escapes from degradation in macrophages. Nature443, 998–1002 (2006). [DOI] [PubMed] [Google Scholar]
20.Narayanaswamy, N. et al. A pH-correctable, DNA-based fluorescent reporter for organellar calcium. Nat Methods. 1695–102 (2019) [DOI] [PMC free article] [PubMed]
21.Choong, C. J. et al. Alternative mitochondrial quality control mediated by extracellular release. Autophagy17, 2962–2974 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Katayama, H., Kogure, T., Mizushima, N., Yoshimori, T. & Miyawaki, A. A sensitive and quantitative technique for detecting autophagic events based on lysosomal delivery. Chem. Biol.18, 1042–1052 (2011). [DOI] [PubMed] [Google Scholar]
23.Di Malta, C., Cinque, L. & Settembre, C. Transcriptional regulation of autophagy: mechanisms and diseases. Front Cell Dev. Biol.7, 114 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Pryor, P. R., Mullock, B. M., Bright, N. A., Gray, S. R. & Luzio, J. P. The role of intraorganellar Ca(2+) in late endosome-lysosome heterotypic fusion and in the reformation of lysosomes from hybrid organelles. J. Cell Biol.149, 1053–1062 (2000). [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Skowyra, M. L., Schlesinger, P. H., Naismith, T. V. & Hanson, P. I. Triggered recruitment of ESCRT machinery promotes endolysosomal repair. Science360, eaar5078 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
26.McNeil, P. L. & Kirchhausen, T. An emergency response team for membrane repair. Nat. Rev. Mol. Cell Biol.6, 499–505 (2005). [DOI] [PubMed] [Google Scholar]
27.Andrews, N. W., Almeida, P. E. & Corrotte, M. Damage control: cellular mechanisms of plasma membrane repair. Trends Cell Biol.24, 734–742 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Chinopoulos, C. & Adam-Vizi, V. Mitochondrial Ca2+ sequestration and precipitation revisited. FEBS J.277, 3637–3651 (2010). [DOI] [PubMed] [Google Scholar]
29.Narayanaswamy, N. et al. Author Correction: A pH-correctable, DNA-based fluorescent reporter for organellar calcium. Nat. Methods16, 205 (2019). [DOI] [PubMed] [Google Scholar]
30.Chatterjee, S., Kon, E., Sharma, P. & Peer, D. Endosomal escape: A bottleneck for LNP-mediated therapeutics. Proc. Natl. Acad. Sci. USA121, e2307800120 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Dong, X. P. et al. PI(3,5)P(2) controls membrane trafficking by direct activation of mucolipin Ca(2+) release channels in the endolysosome. Nat. Commun.1, 38 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Huynh, C. & Andrews, N. W. The small chemical vacuolin-1 alters the morphology of lysosomes without inhibiting Ca2+-regulated exocytosis. EMBO Rep.6, 843–847 (2005). [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Zhu, D., Feng, L., Feliu, N., Guse, A. H. & Parak, W. J. Stimulation of local cytosolic calcium release by photothermal heating for studying intra- and intercellular calcium waves. Adv. Mater.33, e2008261 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Chen, Q. et al. Structure of mammalian endolysosomal TRPML1 channel in nanodiscs. Nature550, 415–418 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Schmiege, P., Fine, M., Blobel, G. & Li, X. Human TRPML1 channel structures in open and closed conformations. Nature550, 366–370 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Melki, I. et al. Disease-associated mutations identify a novel region in human STING necessary for the control of type I interferon signaling. J. Allergy Clin. Immunol.140, 543–552.e5 (2017). [DOI] [PubMed] [Google Scholar]
37.Konno, H. et al. Pro-inflammation associated with a gain-of-function mutation (R284S) in the innate immune sensor STING. Cell Rep.23, 1112–1123 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Saldanha, R. G. et al. A mutation outside the dimerization domain causing Atypical STING-associated vasculopathy with onset in infancy. Front Immunol.9, 1535 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Keskitalo, S. et al. Novel TMEM173 mutation and the role of disease modifying alleles. Front Immunol.10, 2770 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Jeremiah, N. et al. Inherited STING-activating mutation underlies a familial inflammatory syndrome with lupus-like manifestations. J. Clin. Invest124, 5516–5520 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Liu, Y. et al. Activated STING in a vascular and pulmonary syndrome. N. Engl. J. Med371, 507–518 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Cole, E., Gillespie, S., Vulliamy, P. & Brohi, K. Organ Dysfunction in Trauma (ORDIT) study collaborators. Multiple organ dysfunction after trauma. Br. J. Surg.107, 402–412 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Caielli, S. et al. Oxidized mitochondrial nucleoids released by neutrophils drive type I interferon production in human lupus. J. Exp. Med213, 697–713 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Gkirtzimanaki, K. et al. IFNα impairs autophagic degradation of mtDNA promoting autoreactivity of SLE monocytes in a STING-dependent fashion. Cell Rep.25, 921–933.e5 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Monteith, A. J. et al. Defects in lysosomal maturation facilitate the activation of innate sensors in systemic lupus erythematosus. Proc. Natl. Acad. Sci. USA113, E2142–E2151 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Caza, T. N. et al. HRES-1/Rab4-mediated depletion of Drp1 impairs mitochondrial homeostasis and represents a target for treatment in SLE. Ann. Rheum. Dis.73, 1888–1897 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Rai, P. et al. IRGM1 links mitochondrial quality control to autoimmunity. Nat. Immunol.22, 312–321 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Lord, J. M. et al. The systemic immune response to trauma: an overview of pathophysiology and treatment. Lancet384, 1455–1465 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Feng, Z. et al. Exosomal STIMATE derived from type II alveolar epithelial cells controls metabolic reprogramming of tissue-resident alveolar macrophages. Theranostics13, 991–1009 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Hazeldine, J., Hampson, P., Opoku, F. A., Foster, M. & Lord, J. M. N-Formyl peptides drive mitochondrial damage associated molecular pattern induced neutrophil activation through ERK1/2 and P38 MAP kinase signalling pathways. Injury46, 975–984 (2015). [DOI] [PubMed] [Google Scholar]
51.Karve, I. P. et al. Ablation of Type-1 IFN signaling in hematopoietic cells confers protection following traumatic brain injury. eNeuro3, ENEURO.0128-15.2016 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
52.Abdullah, A. et al. STING-mediated type-I interferons contribute to the neuroinflammatory process and detrimental effects following traumatic brain injury. J. Neuroinflammation15, 323 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
53.Ishikawa, H., Ma, Z. & Barber, G. N. STING regulates intracellular DNA-mediated, type I interferon-dependent innate immunity. Nature461, 788–792 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Dobbs, N. et al. STING activation by translocation from the ER is associated with infection and autoinflammatory disease. Cell Host Microbe18, 157–168 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
55.Zhou, Q. et al. The ER-associated protein ZDHHC1 is a positive regulator of DNA virus-triggered, MITA/STING-dependent innate immune signaling. Cell Host Microbe16, 450–461 (2014). [DOI] [PubMed] [Google Scholar]
56.Luo, W. W. et al. iRhom2 is essential for innate immunity to DNA viruses by mediating trafficking and stability of the adaptor STING. Nat. Immunol.17, 1057–1066 (2016). [DOI] [PubMed] [Google Scholar]
57.Wang, Q. et al. The E3 ubiquitin ligase AMFR and INSIG1 bridge the activation of TBK1 kinase by modifying the adaptor STING. Immunity41, 919–933 (2014). [DOI] [PubMed] [Google Scholar]
58.Li, L. J. et al. Microglial double stranded DNA accumulation induced by DNase II deficiency drives neuroinflammation and neurodegeneration. J. Neuroinflammation22, 11 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
59.Glass, C. K., Saijo, K., Winner, B., Marchetto, M. C. & Gage, F. H. Mechanisms underlying inflammation in neurodegeneration. Cell140, 918–934 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
60.Van Acker, Z. P. et al. Phospholipase D3 degrades mitochondrial DNA to regulate nucleotide signaling and APP metabolism. Nat. Commun.14, 2847 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
61.Nayak, D., Roth, T. L. & McGavern, D. B. Microglia development and function. Annu Rev. Immunol.32, 367–402 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
62.Baker, S. P., O’Neill, B., Haddon, W. Jr & Long, W. B. The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J. Trauma14, 187–196 (1974). [PubMed] [Google Scholar]
63.Copes, W. S. et al. Progress in characterizing anatomic injury. J. Trauma30, 1200–1207 (1990). [DOI] [PubMed] [Google Scholar]
64.Antonelli, M. et al. Application of SOFA score to trauma patients. Sequential Organ Failure Assessment. Intensive Care Med25, 389–394 (1999). [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Information File^{(6.1MB, pdf)}

Reporting summary^{(7.9MB, pdf)}

Transparent Peer Review file^{(18.9KB, pdf)}

Source Data Excel file^{(1.3MB, zip)}

Data Availability Statement

[CR1] 1.GBD 2017 Disease and Injury Incidence and Prevalence Collaborators Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet392, 1789–1858 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR2] 2.Gruen, R. L. et al. Haemorrhage control in severely injured patients. Lancet380, 1099–1108 (2012). [DOI] [PubMed] [Google Scholar]

[CR3] 3.Krishnamoorthy, V., Komisarow, J. M., Laskowitz, D. T. & Vavilala, M. S. Multiorgan dysfunction after severe traumatic brain injury: epidemiology, mechanisms, and clinical management. Chest160, 956–964 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR4] 4.Zhang, Q. et al. Circulating mitochondrial DAMPs cause inflammatory responses to injury. Nature464, 104–107 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR5] 5.West, A. P. & Shadel, G. S. Mitochondrial DNA in innate immune responses and inflammatory pathology. Nat. Rev. Immunol.17, 363–375 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR6] 6.Lood, C. et al. Neutrophil extracellular traps enriched in oxidized mitochondrial DNA are interferogenic and contribute to lupus-like disease. Nat. Med22, 146–153 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR7] 7.Simmons, J. D. et al. Elevated levels of plasma mitochondrial DNA DAMPs are linked to clinical outcome in severely injured human subjects. Ann. Surg.258, 591–596 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.Li, Z. & Nakatogawa, H. Degradation of nuclear components via different autophagy pathways. Trends Cell Biol.32, 574–584 (2022). [DOI] [PubMed] [Google Scholar]

[CR9] 9.Liddicoat, B. J. et al. RNA editing by ADAR1 prevents MDA5 sensing of endogenous dsRNA as nonself. Science349, 1115–1120 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR10] 10.Decout, A., Katz, J. D., Venkatraman, S. & Ablasser, A. The cGAS-STING pathway as a therapeutic target in inflammatory diseases. Nat. Rev. Immunol.21, 548–569 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR11] 11.Deng, L. et al. STING-dependent cytosolic DNA sensing promotes radiation-induced type I interferon-dependent antitumor immunity in immunogenic tumors. Immunity41, 843–852 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR12] 12.King, K. R. et al. IRF3 and type I interferons fuel a fatal response to myocardial infarction. Nat. Med23, 1481–1487 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR13] 13.Marichal, T. et al. DNA released from dying host cells mediates aluminum adjuvant activity. Nat. Med17, 996–1002 (2011). [DOI] [PubMed] [Google Scholar]

[CR14] 14.Srikanth, S. et al. The Ca2+ sensor STIM1 regulates the type I interferon response by retaining the signaling adaptor STING at the endoplasmic reticulum. Nat. Immunol.20, 152–162 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR15] 15.Nunes, P. et al. STIM1 juxtaposes ER to phagosomes, generating Ca²⁺ hotspots that boost phagocytosis. Curr. Biol.22, 1990–1997 (2012). [DOI] [PubMed] [Google Scholar]

[CR16] 16.Jing, J. et al. Proteomic mapping of ER-PM junctions identifies STIMATE as a regulator of Ca²⁺ influx. Nat. Cell Biol.17, 1339–1347 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR17] 17.Quintana, A. et al. TMEM110 regulates the maintenance and remodeling of mammalian ER-plasma membrane junctions competent for STIM-ORAI signaling. Proc. Natl. Acad. Sci. USA112, E7083–E7092 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR18] 18.Lan, Y. Y., Londoño, D., Bouley, R., Rooney, M. S. & Hacohen, N. Dnase2a deficiency uncovers lysosomal clearance of damaged nuclear DNA via autophagy. Cell Rep.9, 180–192 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR19] 19.Kawane, K. et al. Chronic polyarthritis caused by mammalian DNA that escapes from degradation in macrophages. Nature443, 998–1002 (2006). [DOI] [PubMed] [Google Scholar]

[CR20] 20.Narayanaswamy, N. et al. A pH-correctable, DNA-based fluorescent reporter for organellar calcium. Nat Methods. 1695–102 (2019) [DOI] [PMC free article] [PubMed]

[CR21] 21.Choong, C. J. et al. Alternative mitochondrial quality control mediated by extracellular release. Autophagy17, 2962–2974 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR22] 22.Katayama, H., Kogure, T., Mizushima, N., Yoshimori, T. & Miyawaki, A. A sensitive and quantitative technique for detecting autophagic events based on lysosomal delivery. Chem. Biol.18, 1042–1052 (2011). [DOI] [PubMed] [Google Scholar]

[CR23] 23.Di Malta, C., Cinque, L. & Settembre, C. Transcriptional regulation of autophagy: mechanisms and diseases. Front Cell Dev. Biol.7, 114 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR24] 24.Pryor, P. R., Mullock, B. M., Bright, N. A., Gray, S. R. & Luzio, J. P. The role of intraorganellar Ca(2+) in late endosome-lysosome heterotypic fusion and in the reformation of lysosomes from hybrid organelles. J. Cell Biol.149, 1053–1062 (2000). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR25] 25.Skowyra, M. L., Schlesinger, P. H., Naismith, T. V. & Hanson, P. I. Triggered recruitment of ESCRT machinery promotes endolysosomal repair. Science360, eaar5078 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR26] 26.McNeil, P. L. & Kirchhausen, T. An emergency response team for membrane repair. Nat. Rev. Mol. Cell Biol.6, 499–505 (2005). [DOI] [PubMed] [Google Scholar]

[CR27] 27.Andrews, N. W., Almeida, P. E. & Corrotte, M. Damage control: cellular mechanisms of plasma membrane repair. Trends Cell Biol.24, 734–742 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR28] 28.Chinopoulos, C. & Adam-Vizi, V. Mitochondrial Ca2+ sequestration and precipitation revisited. FEBS J.277, 3637–3651 (2010). [DOI] [PubMed] [Google Scholar]

[CR29] 29.Narayanaswamy, N. et al. Author Correction: A pH-correctable, DNA-based fluorescent reporter for organellar calcium. Nat. Methods16, 205 (2019). [DOI] [PubMed] [Google Scholar]

[CR30] 30.Chatterjee, S., Kon, E., Sharma, P. & Peer, D. Endosomal escape: A bottleneck for LNP-mediated therapeutics. Proc. Natl. Acad. Sci. USA121, e2307800120 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR31] 31.Dong, X. P. et al. PI(3,5)P(2) controls membrane trafficking by direct activation of mucolipin Ca(2+) release channels in the endolysosome. Nat. Commun.1, 38 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR32] 32.Huynh, C. & Andrews, N. W. The small chemical vacuolin-1 alters the morphology of lysosomes without inhibiting Ca2+-regulated exocytosis. EMBO Rep.6, 843–847 (2005). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR33] 33.Zhu, D., Feng, L., Feliu, N., Guse, A. H. & Parak, W. J. Stimulation of local cytosolic calcium release by photothermal heating for studying intra- and intercellular calcium waves. Adv. Mater.33, e2008261 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR34] 34.Chen, Q. et al. Structure of mammalian endolysosomal TRPML1 channel in nanodiscs. Nature550, 415–418 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR35] 35.Schmiege, P., Fine, M., Blobel, G. & Li, X. Human TRPML1 channel structures in open and closed conformations. Nature550, 366–370 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR36] 36.Melki, I. et al. Disease-associated mutations identify a novel region in human STING necessary for the control of type I interferon signaling. J. Allergy Clin. Immunol.140, 543–552.e5 (2017). [DOI] [PubMed] [Google Scholar]

[CR37] 37.Konno, H. et al. Pro-inflammation associated with a gain-of-function mutation (R284S) in the innate immune sensor STING. Cell Rep.23, 1112–1123 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR38] 38.Saldanha, R. G. et al. A mutation outside the dimerization domain causing Atypical STING-associated vasculopathy with onset in infancy. Front Immunol.9, 1535 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR39] 39.Keskitalo, S. et al. Novel TMEM173 mutation and the role of disease modifying alleles. Front Immunol.10, 2770 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR40] 40.Jeremiah, N. et al. Inherited STING-activating mutation underlies a familial inflammatory syndrome with lupus-like manifestations. J. Clin. Invest124, 5516–5520 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR41] 41.Liu, Y. et al. Activated STING in a vascular and pulmonary syndrome. N. Engl. J. Med371, 507–518 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR42] 42.Cole, E., Gillespie, S., Vulliamy, P. & Brohi, K. Organ Dysfunction in Trauma (ORDIT) study collaborators. Multiple organ dysfunction after trauma. Br. J. Surg.107, 402–412 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR43] 43.Caielli, S. et al. Oxidized mitochondrial nucleoids released by neutrophils drive type I interferon production in human lupus. J. Exp. Med213, 697–713 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR44] 44.Gkirtzimanaki, K. et al. IFNα impairs autophagic degradation of mtDNA promoting autoreactivity of SLE monocytes in a STING-dependent fashion. Cell Rep.25, 921–933.e5 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR45] 45.Monteith, A. J. et al. Defects in lysosomal maturation facilitate the activation of innate sensors in systemic lupus erythematosus. Proc. Natl. Acad. Sci. USA113, E2142–E2151 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR46] 46.Caza, T. N. et al. HRES-1/Rab4-mediated depletion of Drp1 impairs mitochondrial homeostasis and represents a target for treatment in SLE. Ann. Rheum. Dis.73, 1888–1897 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR47] 47.Rai, P. et al. IRGM1 links mitochondrial quality control to autoimmunity. Nat. Immunol.22, 312–321 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR48] 48.Lord, J. M. et al. The systemic immune response to trauma: an overview of pathophysiology and treatment. Lancet384, 1455–1465 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR49] 49.Feng, Z. et al. Exosomal STIMATE derived from type II alveolar epithelial cells controls metabolic reprogramming of tissue-resident alveolar macrophages. Theranostics13, 991–1009 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR50] 50.Hazeldine, J., Hampson, P., Opoku, F. A., Foster, M. & Lord, J. M. N-Formyl peptides drive mitochondrial damage associated molecular pattern induced neutrophil activation through ERK1/2 and P38 MAP kinase signalling pathways. Injury46, 975–984 (2015). [DOI] [PubMed] [Google Scholar]

[CR51] 51.Karve, I. P. et al. Ablation of Type-1 IFN signaling in hematopoietic cells confers protection following traumatic brain injury. eNeuro3, ENEURO.0128-15.2016 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR52] 52.Abdullah, A. et al. STING-mediated type-I interferons contribute to the neuroinflammatory process and detrimental effects following traumatic brain injury. J. Neuroinflammation15, 323 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR53] 53.Ishikawa, H., Ma, Z. & Barber, G. N. STING regulates intracellular DNA-mediated, type I interferon-dependent innate immunity. Nature461, 788–792 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR54] 54.Dobbs, N. et al. STING activation by translocation from the ER is associated with infection and autoinflammatory disease. Cell Host Microbe18, 157–168 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR55] 55.Zhou, Q. et al. The ER-associated protein ZDHHC1 is a positive regulator of DNA virus-triggered, MITA/STING-dependent innate immune signaling. Cell Host Microbe16, 450–461 (2014). [DOI] [PubMed] [Google Scholar]

[CR56] 56.Luo, W. W. et al. iRhom2 is essential for innate immunity to DNA viruses by mediating trafficking and stability of the adaptor STING. Nat. Immunol.17, 1057–1066 (2016). [DOI] [PubMed] [Google Scholar]

[CR57] 57.Wang, Q. et al. The E3 ubiquitin ligase AMFR and INSIG1 bridge the activation of TBK1 kinase by modifying the adaptor STING. Immunity41, 919–933 (2014). [DOI] [PubMed] [Google Scholar]

[CR58] 58.Li, L. J. et al. Microglial double stranded DNA accumulation induced by DNase II deficiency drives neuroinflammation and neurodegeneration. J. Neuroinflammation22, 11 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR59] 59.Glass, C. K., Saijo, K., Winner, B., Marchetto, M. C. & Gage, F. H. Mechanisms underlying inflammation in neurodegeneration. Cell140, 918–934 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR60] 60.Van Acker, Z. P. et al. Phospholipase D3 degrades mitochondrial DNA to regulate nucleotide signaling and APP metabolism. Nat. Commun.14, 2847 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR61] 61.Nayak, D., Roth, T. L. & McGavern, D. B. Microglia development and function. Annu Rev. Immunol.32, 367–402 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR62] 62.Baker, S. P., O’Neill, B., Haddon, W. Jr & Long, W. B. The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J. Trauma14, 187–196 (1974). [PubMed] [Google Scholar]

[CR63] 63.Copes, W. S. et al. Progress in characterizing anatomic injury. J. Trauma30, 1200–1207 (1990). [DOI] [PubMed] [Google Scholar]

[CR64] 64.Antonelli, M. et al. Application of SOFA score to trauma patients. Sequential Organ Failure Assessment. Intensive Care Med25, 389–394 (1999). [DOI] [PubMed] [Google Scholar]

PERMALINK

Tmem110 regulates the conformation of TRPML1 to maintain endolysosomal homeostasis and prevent mitochondrial DNA leakage and pathological self-DNA processing

Zunyong Feng

Yuanbo Pan

Jing Zhou

Liuxi Chu

Qiang Li

Xuanbo Zhang

Ping Wu

Zhiliang Xu

Yanjiao Huang

Jianhua Zou

Xiaokun Li

Xiaoyuan Chen

Zhouguang Wang

Abstract

Introduction

Results

TMEM110-deficient mice exhibit exacerbated type I interferon-associated TBI-MODS

Fig. 1. Phenotypic analysis of TMEM110 conditional knockout mice in the TBI model.

TMEM110 deficiency leads to Ca²⁺ overload, lysosomal membrane damage, and mtDNA escape

Fig. 2. Lysosomal homeostatic imbalance in TMEM110-deficient cells.

Loss of lysosomal Ca²⁺ efflux hotspots in TMEM110-deficient cells mediates type I interferon response

Fig. 3. Formation of lysosomal Ca2+ hotspots in TMEM110-deficient cells.

TMEM110 induces conformational activation of TRPML1 and Ca²⁺ efflux hotspots in response to cytosolic mtDNA escape

Fig. 4. TMEM110 regulates TRPML1 interaction and conformational dynamics.

Cytosolic escape of mtDNA activates STING, relieving TMEM110-K/R inhibition and inducing TRPML1 conformational transition

Fig. 5. Cytosolic STING constitutive inactivation requires TMEM110.

Naturally occurring STING mutations affect lysosomal stability via TMEM110

Fig. 6. STING regulates type I interferon responses through TMEM110.

Clinical evidence links TMEM110 to impaired lysosomal DNA clearance in TBI-MODS Patients

Table 1.

Fig. 7. Prognostic significance of monocyte TMEM110 in TBI-MODS and association with disease progression.

Discussion

Methods

Patient candidate cohort and inclusion criteria

Transgenic mouse models

TBI model and evaluation

Tissue processing and flow cytometric analysis of myeloid cells

Bone marrow transplantation and chimerism assessment

Cell culture and reagents

Plasmid construction and gene knockout

Co-immunoprecipitation (Co-IP) and western blot analysis

Fluorescence imaging

Fluorescence resonance energy transfer (FRET) measurements

Lysosome analysis

TM4-5 D/E mRNA-LNP construction

Autoantigen detection

Protein interaction prediction

Statistics & reproducibility

Ethical statement

Reporting summary

Supplementary information

Source data

Acknowledgements

Author contributions

Peer review

Peer review information

Data availability

Competing interests

Footnotes

Contributor Information

Supplementary information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases

Fig. 3. Formation of lysosomal Ca²⁺ hotspots in TMEM110-deficient cells.