cGAS-IFN-I responses by extracting nuclear DNA from dying cells via nucleocytosis

Domain: physics
Published: 2026-02-18
Editorial outcome: minor_revision

Abstract
Self-DNA triggers cGAS-STING-mediated type I interferon (IFN-I) to induce both protective and pathogenic immune responses; however, how self-DNA activates the cytosolic cGAS-STING pathway remains unclear. Here we show that the cGAS/STING/IFN-I axis is activated by self-DNA via a process termed ‘nucleocytosis’, in which nuclear DNA is extracted from dying cells by macrophages. Mechanistically, lysosomal malfunction, via both proton loss and palmitoyl-protein thioesterase 1 (PPT1) inhibition, triggers cell death and calreticulin accumulation in the nuclei. Live-cell imaging of secretion activity reveals that macrophages access the calreticulin-enriched nuclei of dying cells and extract DNA for cGAS-STING activation. Consistent with these findings, PPT1-targeting cationic amphiphilic drugs induce a cGAS-STING-dependent IFN-I response in vitro and in vivo. Our findings thus identify nucleocytosis as a macrophage function for nuclear DNA extraction and induction of the cGAS/IFN-I axis, and suggest that nucleocytosis-inducing cell death could be a druggable target for treating self-DNA-related inflammatory diseases.

Introduction
Cyclic GMP-AMP (cGAMP) synthase (cGAS) is a B-form DNA (B-DNA)-sensing pattern recognition receptor (PRR) that plays a critical role in host defence1–5. It induces a robust type I IFN (IFN-I) response upon recognising pathogen-derived cytosolic DNA and activates a protective innate immune response1–6. For activation of the cGAS-IFN-I axis, B-DNA must be delivered to the cytosol by specific delivery mechanisms such as viruses, cationic lipids, or exosomes1–7. Alternatively, the cGAS-IFN-I axis is involved in a wide range of diseases, including autoimmune diseases, inflammatory diseases, and cancers1–5,8. In these cases, the cGAS-IFN-I axis is activated by endogenous cytosolic self-B-DNA1–4. Despite its critical role in various diseases, the magnitude of cGAS-IFN-I response by endogenous B-DNA is not as clear as that observed with the response to delivered B-DNA. Most reports have focused on the IFN-I signature rather than the production of IFN-I itself1,2; however, a few studies have indicated that low levels of IFN-I production occur via the self-DNA-cGAS axis9. Thus, it remains unclear whether a robust cGAS-IFN-I response can be activated by self-DNA.

As an endogenous ligand of cGAS, considerable attention has been focused on cytosolic self-DNA released from the cytosolic organelles within IFN-inducing cells in response to various cellular stresses, injury, or DNase defects1–4,10. However, the above cases may be subject to quantitative limitation, and large amounts of self-DNA are presumed to be mainly derived from dead cells11,12. It is well known that dead cells often expose ‘eat-me’ signals on their surface, leading to the uptake of whole cells or cellular fragments via phagocytosis or endocytosis, a process also implicated in the activation of immune responses13,14. Recent reports indicate that lysosome-dependent cell death induced by anticancer drugs can also expose eat-me signals on the cell surface, which contribute to immune activation13. In these cases, it is likely that certain immunostimulatory components from engulfed dead cells or cellular debris contribute to the activation of immune responses; however, a mechanism to selectively extract only these immune-activating components, such as nucleic acids, has not been identified. Moreover, a recent report showed that extracellular self-DNA incorporated via endocytosis is recognised by Toll-like receptors (TLRs) but not by cGAS in autoimmune diseases15. Therefore, it remains unclear whether and how external self-double stranded DNA (dsDNA) directly activates cytosolic cGAS.

During the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, considerable efforts were devoted to antiviral drug development16–18. However, in most of the cases, the underlying molecular mechanisms remain unclear. One such candidate is hydroxychloroquine (HCQ)19–21, a well-known drug for treating autoimmune diseases and malaria that is being investigated in clinical trials for cancer16–18,22,23. In addition to HCQ, the lysosome-tropic antivirals, cationic amphiphilic drugs (CADs), exhibit broad antiviral effects, which are not attributed to the inhibition of viral components17,24. Although their mechanisms of viral inhibition remain unclear, the most widely presumed mechanism is the inhibition of viral entry22,25. Relatedly, one study reported possible concerns in the screening of antiviral drugs, demonstrating that certain CADs exhibited anti-SARS-CoV-2 activity in vitro, but this activity was not reflected in antiviral activity in vivo26. However, they focused on the effect of CADs on infected cells rather than on other non-infected cells. It is worth noting that some CADs, including HCQ, CQ, and amodiaquine (ADQ), exhibit in vivo activity against specific viruses27–29. These reports indicate that some of the valuable antiviral CADs have virus species-specific in vivo antiviral effects mediated by unknown mechanisms other than direct inhibition in infected cells; however, such indirect inhibition by CADs has not been studied in detail.

In this study, we provide evidence on how antiviral CADs exert an indirect antiviral response. Our results suggest that palmitoyl-protein thioesterase 1 (PPT1)-targeting antiviral CADs induce lysosomal dysfunction by both increasing pH and inhibiting PPT1, leading to cell death with accumulation of nuclear calreticulin. Consequently, macrophages access the nucleus and extract DNA via nucleocytosis to activate the cGAS-IFNI axis. Nucleocytosis is clearly demonstrated by live-cell imaging (LCI), including LCI of secretion activity (LCI-S), which shows IFN-β secretion following DNA extraction. The concept of nucleocytosis offers a new perspective on how self-nucleic acids activate cytosolic nucleic acid-sensing pathways, with implications not only for the mechanism of antiviral CADs but also for a range of self-DNA-related diseases, including autoimmune diseases, cancer, and infectious diseases.

Results
IFN-I production by antivirals
As a possible indirect mechanism of antiviral CADs, we focused on the IFN-I response, a crucial response against viruses. During the study, we first discovered the potential of HCQ to induce IFN-β production from granulocyte-macrophage colony-stimulating factor (GM-CSF)-cultured bone marrow cells (GM-BMCs). Notably, HCQ induced Ifnb1 gene expression with a slow time course, reaching a level similar to that induced by cGAMP, one of the most potent IFN-I inducers and ligand of stimulator of IFN genes (STING) (Fig. 1a, b and Supplementary Fig. 1a). Consistently, HCQ induced the expression of IFN-inducible genes and various genes related to PRR pathways and viruses (Fig. 1a, b and Supplementary Fig. 1a–c). Of note, HCQ-specific genes (category 4) were induced early in the time course (as shown in Supplementary Fig. 1a), potentially indicating or contributing to HCQ-specific cellular stress or programmed cell death processes (see below). These results suggest that HCQ has the potential to induce an antiviral response similar to that of cGAMP. Given that HCQ is used as an inhibitor of the IFN-I response to treat autoimmune diseases22, these results are surprising and suggest the possible existence of similar IFN-I inducers among antiviral CADs. Therefore, we performed further screening of IFN-β inducers among antiviral CADs and their related agents (Supplementary Fig. 1d). We identified HCQ, CQ, ADQ, tilorone, quinacrine (QC), and AQ-13 as IFN-β inducers (Fig. 1c and Supplementary Fig. 1e). Notably, their potential to induce IFN-β production was comparable to that of pathogen-associated molecular patterns such as cGAMP and lipopolysaccharide (LPS). As HCQ is a well-known inhibitor of endosomal TLR responses22, we further investigated the underlying mechanism by focusing on cytosolic PRRs and cell surface TLR pathways. HCQ induced the phosphorylation of IFN regulatory factor 3 a critical transcription factor for Ifnb1 gene expression. Consistently, TANK-binding kinase 1 (TBK1) and mitogen-activated protein kinases (MAPKs) were also phosphorylated by HCQ (Fig. 1d and Supplementary Fig. 1f), indicating the potential involvement of the TBK1-dependent pathway. Subsequently, we investigated the involvement of PRR pathways related to TBK1 and found that HCQ-mediated IFN-β production was completely abolished in Tbk1, Sting1, and Cgas (Mb21d1)-deficient GM-BMCs (Fig. 1e–g). The contribution of STING was further supported by inhibition with H-151 (Supplementary Fig. 1h). Conversely, HCQ-mediated IFN-β production was normal in TIR domain-containing adaptor-inducing IFN-β (Trif)-deficient GM-BMCs and partially decreased in IFN-β promoter stimulator 1 (Ips1)-deficient GM-BMCs (Supplementary Fig. 1i), indicating the critical role of the cGAS-STING axis. Comprehensive analysis of HCQ-inducible genes using RNA sequencing (RNA-seq) analysis showed that HCQ induced not only Ifnb1 but also various genes in a STING-dependent manner (Fig. 1h and Supplementary Fig. 1a). Importantly, IFN-β production by all IFN-β-inducing CADs was also diminished in Cgas-deficient GM-BMCs (Fig. 1i and Supplementary Fig. 1j), suggesting a common mechanism of IFN-β production. To further clarify their commonalities, we performed in silico analysis to identify conserved structural features. As shown in Supplementary Fig. 1k, l, two-dimensional (2D) structural analysis involving 2,048 parameters revealed conserved 2D structures in five (HCQ, CQ, ADQ, QC, and AQ-13), but not all, IFN-β inducers. Conversely, 3D pharmacophore analysis identified five conserved pharmacophore features unique to all IFN-β inducers and not found in any of the other 38 non-inducers (Fig. 1j, k and Supplementary Fig. 1m), indicating the importance of these five conserved pharmacophore features in IFN-β induction. Notably, we examined several antimalarial drugs, including piperaquine and artemisinin, but found no activity in IFN-β production from any of them (Supplementary Fig. 1e). These results suggest that antimalarial activity is not related to IFN-β production. Furthermore, typical lysosome-tropic agents, including Bafilomycin A (BafA), showed no potential (Supplementary Fig. 1n), indicating that the inhibition of lysosomes by CADs is not sufficient for IFN-β production. Therefore, our results suggest a previously unrecognised commonality among IFN-β inducers regarding their 3D structure and their mechanism of IFN-β induction, suggesting an unknown conserved target.

Robust IFN-β production by limited cells
To further examine the mechanism of antiviral CAD-mediated IFN-β production, we established a time-lapse monitoring system for IFN-β secretion using LCI-S30,31. LCI-S revealed significant variation in the pattern of IFN-β secretion, including differences in the time course, dose, and shape of secreted IFN-β, even among cGAMP-treated cells (Fig. 2a–d, Supplementary Fig. 2a and Supplementary Movies 1, 2). Only a subset of cells secreted IFN-β, and each of these IFN-β-producing cells exhibited one-time secretion despite surviving the secretion process. Conversely, HCQ induced IFN-β secretion more slowly and less frequently than cGAMP (Fig. 2a–d, Supplementary Fig. 2a and Supplementary Movies 1, 2), although the total IFN-β production by HCQ was comparable to that by cGAMP (Fig. 1c). These results suggest that compared with cGAMP, HCQ induces robust IFN-β production from a limited number of cells. Of note, the perforated shape of secreted IFN-β indicated strong cell attachment on culture plates induced by HCQ (Fig. 2c and Supplementary Movies 3, 4). Consistent with these results, single-cell RNA-seq (scRNA-seq) analysis revealed a divergence of the gene expression pattern in IFN-β-expressing cells between HCQ and cGAMP treatments (Fig. 2e, f and Supplementary Fig. 2b). Interestingly, Ifnb1 expression was induced by HCQ only in macrophage cell clusters, whereas cGAMP induced Ifnb1 expression in both macrophage and dendritic cell (DC) clusters (Fig. 2e, f), indicating that a macrophage-specific function is required for HCQ-mediated IFN-β production. scRNA-seq analysis also confirmed a lower number of IFN-β-expressing cells but a higher expression level of strong inducers with HCQ treatment (Fig. 2f, g), confirming robust IFN-β production in a limited number of cells. Notably, there was no remarkable difference in IFN-inducible gene expression between HCQ and cGAMP (Supplementary Fig. 2c), consistent with their similar total production of IFN-β (Fig. 1a–c). These results demonstrate the potential of HCQ to induce IFN-β production from a limited number of cells and a significant difference in cell behaviour during IFN-β secretion between HCQ and cGAMP.

Time-lapse analysis revealed the induction of cell death by HCQ but not cGAMP (Fig. 2a, b, d, Supplementary Fig. 2a and Supplementary Movies 1, 2). scRNA-seq analysis also confirmed a higher frequency of injured or dying cells with HCQ treatment compared to cGAMP (Fig. 2g, h)32. Consistently, HCQ induced cell death in a dose-dependent manner, and the dose-response curve of IFN-β exhibited a bell-shaped pattern (Fig. 2i), indicating that high HCQ concentrations induce cell death in IFN-β-producing cells. Notably, cell death was observed with all of the other IFN-β inducers (Supplementary Fig. 2d). These results indicate the involvement of cell death-related events in IFN-β production by antiviral CADs.

Direct access to the dead cell nucleus and DNA extraction
As HCQ-mediated IFN-β production is dependent on cGAS (Fig. 1g), the above results indicate the possible involvement of dead cells as a source of B-DNA for cGAS-mediated IFN-β production. We further examined interactions among dying cells within HCQ-treated cell populations using an imaging flow cytometer. Consistently, HCQ treatment increased the SYTOX green-positive population, indicating the induction of cell death (Fig. 3a). This increase was significant, affecting not only singlets but also multiplets that included both living and dying cells (Fig. 3a, b and Supplementary Fig. 3a). Furthermore, the importance of dsDNA transfer, but not cGAMP, was confirmed by the diminished production of IFN-β from mixed cells of Cgas-/- and sting1-/- cells (Fig. 3c). These results suggest the possibility that dsDNA transfer may occur from dying cells to living cells during HCQ-induced IFN-β production.

Nuclear components, such as dsDNA and histone H3, were not released into the culture supernatant following HCQ treatment (Supplementary Fig. 4a). In this case, IFN-β-producing cells must directly access the nucleus to obtain B-DNA for cGAS-mediated IFN-β production. Based on the above mentioned results (Fig. 3a–c), we hypothesised that, through contact between dead and live cells, DNA is transferred to IFN-β-producing cells, thereby activating the STING-cGAS response. According to the results of LCI-S, within 6 h of HCQ treatment, at which time IFN-β secretion was observed, the nuclear structures of SYTOX-positive dead cells could be detected (Fig. 2b, d). Given the fact that HCQ induced robust IFN-β production, enough DNA was efficiently taken up from dead cells. Therefore, we next used microscopic analysis to determine whether live cells make contact with dead cell nuclei and subsequently take up DNA. The results showed that despite variations in the distance between dead and live cells and the degree of dead cell disintegration, in all cases both maximum intensity projection and slice images revealed protrusion-like structures and direct access to the nucleus (Fig. 3d). Remarkably, time-lapse analysis further demonstrated a decrease in DNA intensity in dead cell nuclei accompanied by an increase in DNA intensity in live cells (Fig. 3e, Supplementary Fig. 3b, c). Likewise, holographic microscopy confirmed the presence of protrusion-like structures, and importantly, DNA signals within the protrusion were also detected (Fig. 3f, g). Cross-sectional image analysis revealed that this protrusion extended into the nucleus, and that low-density regions were observed inside the nuclei at sites of contact (Fig. 3g, h). Consistent with these findings, inhibitors of actin polymerisation specifically suppressed HCQ-induced IFN-β production (Fig. 3i). Collectively, these results suggest that live cells directly access the nuclei of dead cells and extract DNA.

Nucleocytosis before IFN-β secretion
To further clarify the detailed mechanism, we performed high-resolution LCI-S and monitored the interaction between dying cells and IFN-β-secreting cells. Consistently, we observed interactions between dead cells and IFN-β-secreting cells before IFN-β production (Fig. 4a, Supplementary Fig. 4b, c, Supplementary Movies 5–7). Notably, IFN-β-secreting cells were observed to attach to dead cells near the nucleus, with dsDNA transfer into the cytosol occurring before IFN-β secretion (Fig. 4a, Supplementary Fig. 4b, c, Supplementary Movies 5–7). These results indicate that HCQ-induced IFN-β secretion is triggered by nuclear invasion to extract dsDNA. Consistently, imaging flow cytometry revealed that living cells interacted with dying cells within the dsDNA-positive population (Fig. 4b, c).

The above observations represent unique phenomena for obtaining nuclear components by IFN-I-inducing cells, which we named nucleocytosis. We further examined the molecules that can trigger the induction of nucleocytosis. As a candidate, we focused on calreticulin, which is known as an eat-me signal in the immunogenic cell death (ICD) of tumour cells33,34. Notably, HCQ induces ICD in certain types of tumour cells with calreticulin translocation to the cell surface33,34. Another reason for focusing on calreticulin is that it triggers dendrite extension via Rho/Rho-associated protein kinase (ROCK) signalling35–38. Therefore, we focused on calreticulin and examined its localisation in HCQ-treated cells. Notably, calreticulin was detected in DNA-positive regions after HCQ treatment, indicating its translocation from the cytosol to the nucleus (Fig. 4d–g, Supplementary Fig. 4d, e and Supplementary Movie 8). To exclude the possibility that this observation was due to HCQ-induced morphological changes, we performed nuclear western blotting and confirmed calreticulin nuclear translocation (Supplementary Fig. 4f). These results indicate the role of calreticulin in the nucleus34. To further examine the nuclear translocation of calreticulin, we performed imaging cytometry. Interestingly, although nuclear western blotting (Supplementary Fig. 4f) showed no marked changes in calreticulin protein levels after HCQ treatment, intracellular staining revealed increased signals, particularly in dead cells (Fig. 4h, i). Calreticulin gene expression was also examined, but no increase was observed with HCQ (Supplementary Fig. 4g). These findings indicate that HCQ induces structural or localisation changes in calreticulin that affect its antibody reactivity or accessibility. We further assessed the relationship between calreticulin and the nucleus, and found that the correlation was significantly stronger in cells with high calreticulin signals than in those with low levels (Fig. 4j, k). Of note, BafA treatment also enhanced calreticulin signals, particularly in live cells (Fig. 4h, i). Taken together, these results suggest that lysosomal inhibition induces some changes in the structure or localisation of calreticulin, and that a fraction of the protein translocates into the nucleus. As extracellular calreticulin is important for the extension of dendrites35–38, we next examined dendrite extension toward the nucleus using LCI-S. To examine dendrite extension, we focused on IFN-β-producing cells near, but not attached to, dying cells. Interestingly, we observed dendrite extension to dying cells and further interaction with the nucleus during IFN-β secretion (Fig. 4l and Supplementary Movie 9), which is consistent with microscopic analysis, as shown in Fig. 3d–h. Notably, the dendrite was still connected to the nucleus following IFN-β secretion, indicating a robust connection, which was supported by the nuclear accumulation of calreticulin in HCQ-treated cells (Fig. 4d–k). To further explore the importance of calreticulin in nucleocytosis, we investigated the involvement of Rho kinase, which plays a critical role in calreticulin-induced dendrite extension35–38. The inhibition of Rho kinase resulted in the inhibition of IFN-β production, while cell death remained unaffected (Fig. 4m). This inhibition was further confirmed by LCI-S (Fig. 4n). Interestingly, however, the Rho kinase inhibitor did not block calreticulin nuclear translocation by HCQ or IFN-β production induced by cGAMP (Supplementary Fig. 4h–k). These results suggest that Rho kinase functions after calreticulin nuclear translocation but before cGAS-STING activation during nucleocytosis. Taken together with previous reports35–38, our findings support a possible involvement of Rho kinase in dendrite extension toward calreticulin during nucleocytosis.

Lysosomal malfunction to IFN-β production
Our results showed that the inhibition of lysosomes was not sufficient for robust IFN-β production (Supplementary Fig. 1d, e, n), although BafA induced a similar change in the calreticulin signal in living cells (Fig. 4h). These results indicate the existence of an unknown common target of IFN-inducing CADs that triggers cell death after calreticulin accumulation in the nucleus. As HCQ is a direct inhibitor of palmitoyl-protein thioesterase 1 (PPT1)39, a lysosomal depalmitoylating enzyme, and CQ is a direct agonist of Mas-related G protein-coupled receptor A3 (MRGPA3)40, a sensory neuron-specific receptor implicated in itch sensation, we examined the involvement of PPT1 and MRGPA3 in IFN-β production. The PPT1 inhibitor DC661, but not MRGPA3 agonists, induced IFN-β production, although the level was considerably lower than that induced by cGAMP (Fig. 5a and Supplementary Fig. 5a). Conversely, compensation of esterase activity of PPT1 by N-(tert-butyl) hydroxylamine39 resulted in the inhibition of HCQ-induced IFN-β production (Fig. 5b). Similar inhibitory effects of N-(tert-butyl) hydroxylamine were observed for all IFN-β inducers (Supplementary Fig. 5b), suggesting a common involvement of PPT1 inhibition in their IFN-β production. To examine the relationship between PPT1 and IFN-β inducers, we performed in silico analysis. HCQ bound to the central pocket of PPT1 (Fig. 5c and Supplementary Fig. 5c), masking the binding region of the substrate41. Based on pharmacophore analysis (Fig. 1j, k), we examined the importance of the five conserved pharmacophore features in HCQ and identified the predicted interacting amino acids near all five conserved pharmacophore features (Fig. 5d). Consistently, the binding affinity of modified HCQ, which lacks each conserved pharmacophore feature but not the non-conserved pharmacophore features, decreased to a level similar to that of the substrate (Fig. 5e), indicating the importance of conserved structures in binding to PPT1. Consistently, all IFN-β inducers with conserved pharmacophore features bound to the central pocket of PPT1 and masked the binding region of the substrate, similar to the PPT1 inhibitors DC661 and Lys05 (Fig. 5f). Moreover, their binding affinity was stronger than that of the substrate (Fig. 5g). Conversely, non-IFN-β inducers did not mask the binding region of PPT1 to the substrate, and the affinity was lower than that of the substrate (Fig. 5f, g). Furthermore, we observed a strong correlation between binding affinity to PPT1 and the potential to induce IFN-β (Fig. 5h). These results suggest that PPT1 is the target of IFN-β inducers.

We also examined the binding affinity of IFN-β inducers to PPT1 under acidic conditions similar to those in the lysosome. Notably, the binding affinity of IFN inducers, with the exception of DC661, decreased in acidic conditions (Fig. 5i). We further found that hydronium (H3O+) bound strongly to the conserved HY3 structure of HCQ under acidic conditions (Fig. 5j). Similar results were obtained with CQ and ADQ, but not with DC661 (Fig. 5j). These results suggest that IFN-β inducers cannot inhibit lysosomal PPT1 by binding H3O+ before the increase of lysosomal pH by their accumulation and inhibition of protons via their reactivity as CADs. Conversely, DC661 was expected to inhibit PPT1 before proton inhibition but could not induce robust IFN-β production (Fig. 5a), indicating the possible importance of proton inhibition in robust IFN-β production. We further examined the contribution of lysosomal proton inhibition to IFN-β production. Interestingly, DC661 treatment under proton inhibition by Baf A enhanced IFN-β production in a cGAS-dependent manner (Fig. 5k and Supplementary Fig. 5d). LCI-S observed interactions involving dying cells, a DNA signal in IFN-β-producing cells, and IFN-β secretion following DC661 and Baf A treatment (Fig. 5l and Supplementary Fig. 5e). These results suggest that PPT1 inhibition can trigger IFN-β production, but proton inhibition is required for a robust response via nucleocytosis (Fig. 5a, k, l). As shown in Fig. 4h, Baf A treatment led to relocalisation of calreticulin mainly in living cells but induced only weak cell death and failed to trigger IFN-β production (Supplementary Fig. 1n). By contrast, DC661 induced cell death but elicited only minimal IFN-β production (Fig. 5a). Taken together, these findings indicate that proton inhibition-induced calreticulin relocalisation and PPT1 inhibition-induced cell death both contribute to robust IFN-β induction.

In the case of ICD in tumours, PPT1 inhibition induces multiple types of cell death accompanied by surface calreticulin expression13. We further examined the cell death pathways involved in HCQ-mediated IFN-β production. HCQ-induced IFN-β production was observed even in cells deficient in Z-DNA binding protein 1 (Zbp1), mixed lineage kinase domain-like protein (Mlkl), or gasdermin D (Gsdmd) (Supplementary Fig. 5f–h), although the peak concentration was affected in Gsdmd-deficient cells, indicating a slight but not essential contribution of these molecules. We subsequently investigated the effect of various cell death inhibitors on HCQ-induced IFN-β production; these inhibitors did not inhibit IFN-β production (Supplementary Fig. 5i, j), suggesting that HCQ-mediated cell death leading to IFN-β production involves unknown pathways or a combination of multiple pathways.

Nucleocytosis in tumour cells
The above results suggest a previously unrecognised function of macrophages in inducing an IFN-I response via nucleocytosis. Consistently, we could not detect IFN-β production using various cell types, including splenocytes, peritoneal macrophages, and cell lines, indicating the unique mechanism of IFN-β production by specific cell subsets in GM-BMCs (Supplementary Fig. 6a). Conversely, GM-BMCs produced IFN-β after mixing with HCQ-treated dying tumour cells (Fig. 6a, b). Consistently, HCQ-induced nuclear translocation of calreticulin was observed in these cells (Fig. 6c and Supplementary Fig. 6b, c), indicating that nucleocytosis-inducing cell death is induced in these two types of tumour cells.

HCQ-induced local IFN-I response in vivo
Finally, we examined the physiological effect of severe lysosomal inhibition by HCQ treatment. As previous reports have shown the in vivo effects of HCQ against viruses, including respiratory viruses27,28, we examined the HCQ-induced IFN-I response in the lung by scRNA-seq analysis (Fig. 6d). First, we classified the cell types detected in the scRNA-seq analysis and found that the Sting1 gene was expressed in macrophage subsets, including monocyte-derived macrophages (MoMFs) and alveolar macrophages (Fig. 6e, f). Interestingly, when we analysed the gene expression patterns across the detected cell types, the IFN-I response emerged as one of the most prominent subsets among both the total gene set and the STING-dependent genes (Fig. 6g). Importantly, IFN-I-related genes were expressed in a STING-dependent manner in multiple cell types, particularly MoMFs, epithelial cells, and neutrophils, and IFN-stimulated gene signatures were also induced in these cells (Fig. 6h, i). These results indicate that HCQ triggers a STING-dependent IFN-I response in the lung. Based on the pattern of Sting1 expression, these findings suggest that MoMFs initiate STING-dependent IFN-I responses, which in turn activate the expression of secondary IFN-stimulated genes in other cell types (Fig. 6e–i and Supplementary Fig. 6e, f). This is consistent with our in vitro observations of nucleocytosis by macrophages within GM-BMCs (Fig. 2e, f), indicating that MoMFs are candidate inducers of nucleocytosis in vivo. Notably, systemic production of IFN-β was not observed (Supplementary Fig. 6d), indicating a local effect of HCQ on the lung. Considering the different magnitudes of the STING-dependent IFN-I responses across cell types (Fig. 6h, i and Supplementary Fig. 6e, f), such cell type-dependent responses may underlie the localised IFN-I response in the lung. In conclusion, these results demonstrate the physiological relevance of HCQ in inducing a STING-dependent local IFN-I response in vivo.

Methods
Reagents
HCQ was purchased from Tokyo Chemical Industry (Tokyo, Japan). DNA primers were obtained from Fasmac (Kanagawa, Japan). Details of the antiviral agents and cell death inhibitors used in this study are summarised in the Supplementary Tables 1 and 2.

Mice
C57BL/6 mice were purchased from CLEA Japan (C57BL/6Jcl; Tokyo, Japan). Sting1-/- mice were generated as previously described59. Tnf-/-/Tbk1-/- and Zbp1-/- mice were established as previously described60. Ips1-/- and Trif-/- mice were kindly provided by Dr. Shizuo Akira61,62. Mlkl-/- mice were kindly provided by Dr. Manolis Pasparakis63. Gsdmd-/- mice were provided by RIKEN BioResource Research Center (RBRC10761; Tsukuba, Ibaraki, Japan) through the National BioResource Project of the MEXT, Japan64. Mice (male and female, all C57BL/6 background) were used at 7–16 weeks of age, unless otherwise specified. Mice were maintained under specific pathogen-free conditions with a 12h/12h light/dark cycle, with a controlled room temperature of 22 ± 2 °C and relative humidity of 55 ± 5 %. CO₂ gas was used for euthanasia. All animal experiments were conducted in accordance with the guidelines of the University of Tokyo (Tokyo, Japan). Permission was granted to perform animal experiments by the Animal Experiment Committee at The University of Tokyo (Tokyo, Japan). Cgas-/- mice were generated in the Research Institute for Microbial Diseases (Osaka University; Osaka, Japan) by following method65. The sgRNA sequence 5′-gaaagctgcggcccgcaaag-3′, or 5′-gggggctcgatcgcggcggg-3′ targeting exon 1 of the mouse cGAS gene, was cloned into the BbsI site of the pX330_hSpCas9 vector (Addgene, Watertown, MA, USA). C57BL/6N female mice (6 weeks old) were superovulated and mated with C57BL/6N males; fertilised one-cell-stage embryos were collected from the oviducts and injected into the pronucleus or cytoplasm with the sgRNA-expressing pX330_hSpCas9 plasmids. Then the injected embryos were transferred into the oviducts of pseudopregnant ICR females at 0.5 days post coitum. F0 founder males carrying the mutation were crossed with C57BL/6N females, and germline transmission was confirmed by sequencing. For sequence, genomic DNA was extracted from tail or ear tissue using the NucleoSpin Tissue kit (MACHEREY-NAGEL GmbH & Co. KG, Düren, Germany) according to the manufacturer’s instructions, and the region surrounding the sgRNA target site in the cGAS locus was amplified by PCR using forward primer 5′-AAGCTAGCCACGCGTGCTCCTGCGCCTGCTCGCGG CGG-3′ and reverse primer 5′-AAGTCGACACAACTTTATTCACCGT CTCGGCCGCCTCC-3′. PCR products were purified with the FastGene Gel/PCR Extraction Kit (Nippon Genetics Co., Ltd., Tokyo, Japan) and sequenced by FASMAC Co., Ltd. (Kanagawa, Japan). The primer for sequencing was 5′-CACGCGTGCTCCTGCGCCTGCTCGC-3′, and chromatograms from wild-type and cGAS−/− alleles were aligned to confirm disruption of exon 1. Related information is summarised in Supplementary Fig. 9.

Cell culture
GM-BMCs were prepared according to a standard method66. Briefly, BMCs were isolated from the legs of mice and cultured in RPMI 1640 (Nacalai Tesque) containing 10% foetal bovine serum (FBS; Sigma-Aldrich, St. Louis, MO, USA) and 10ng/mL GM-CSF (PeproTech, Cranbury, NJ, USA). Red blood cells (RBCs) were removed with RBC lysis buffer (Thermo Fisher Scientific, Waltham, MA USA) prior to culture. After 4 days, additional GM-CSF was added (10ng/mL) and used for the experiment on days 6–7. Splenocytes were also prepared using a standard method. Spleens were isolated from mice and mashed through a cell strainer (Corning, Corning, NY, USA) and then used for experiments after the removal of RBCs using RBC lysis buffer (Thermo Fisher Scientific). Peritoneal macrophages were isolated by peritoneal gavage with phosphate-buffered saline (PBS) (Nacalai Tesque) containing 2% FBS. B16 cells and NIH3T3 cells were obtained from RIKEN BioResource Research Center.

RNA analysis
Total RNA was extracted using TRIsure (Nippon Genetics, Tokyo, Japan) with the Direct-zol RNA Kit (Zymo Research, Irvine, CA, USA) or NucleoSpin RNA (Takara Bio, Shiga, Japan). RNA-seq was performed by ImmunoGeneTeqs, Inc. (Chiba, Japan).

Cytokine analysis
Mouse IFN-β concentrations in the culture supernatant or plasma were measured using an enzyme-linked immunosorbent assay (ELISA) (R&D Systems, Minneapolis, MN, USA).

Immunoblot analysis
Whole cell lysates were prepared in M-PER Mammalian Protein Extraction Reagent (Thermo Fisher Scientific) containing a protease inhibitor cocktail (Sigma-Aldrich). Proteins were resolved on the NuPAGE 4–12% Bis-Tris Gel (Thermo Fisher Scientific), and electro-transferred to nitrocellulose membranes included in the iBlot Transfer Stack using the iBlot Dry Blotting System (Thermo Fisher Scientific). The membranes were blocked in 5% bovine serum albumin (BSA) in PBS with 0.1% Tween 20 and then incubated with primary antibodies against GAPDH (14C10; Cell Signalling Technology [CST], Danvers, MA, USA), IRF-3 (D83B9; CST), phosphorylated IRF-3 (p-IRF-3, Ser396) (4D4G; CST), TBK1/NAK (CST), p-TBK1/NAK (Ser172)(D52C2; CST), p44/42 MAPK (ERK1/2)(137F5; CST), p-p44/42 MAPK (ERK1/2, Thr202/Tyr204)(197G2; CST), stress activated protein kinase (SAPK)/c-Jun N-terminal kinase (JNK)(CST), and p-SAPK/JNK (Thr183/Tyr185)(G9; CST). After washing, the membranes were incubated with anti-rabbit horseradish peroxidase (HRP)-conjugated secondary antibody (CST) or anti-mouse IgG HRP-conjugated secondary antibody (CST), and detected by HRP chemiluminescence.

Nuclear and cytoplasmic proteins were collected using NE-PER extraction reagents (Thermo Fisher Scientific) according to the manufacturer’s instructions. Protein concentrations were determined using the Bradford assay, and equal amounts of protein from each fraction were separated by SDS-PAGE and analysed by western blotting using an anti-calreticulin antibody (1:1000, ab92516; Abcam, Cambridge, UK) and an anti-histone H3 antibody (1:1000, #9715; CST).

Principal component analysis of compounds and machine learning
Principal component analysis (PCA) was used to obtain a panoramic view of the structural features of the active compounds. Extended-connectivity fingerprints with a diameter of 4 (ECFP4) was calculated and used as the feature vector for the compounds. ECFP4 has a length of 2,048 bits. RDKit (version 2023.03.2) was used to calculate ECFP4, and scikit-learn was used for the PCA.

Derivation of the pharmacophore model
The main goal of 3D ligand-based pharmacophore modelling is to construct a common 3D pharmacophore for active compounds. To construct the pharmacophore model, six active compounds were used. The “idbgen” module of LigandScout 4.467,68 was used for conformer generation of the active compounds. The parameters for conformer generation were set to the “icon-best” option. Pharmacophore models were constructed from six active compounds using the ligand-based pharmacophore creation mode of LigandScout 4.4 with default parameters. After the pharmacophore creation, 10 pharmacophore models were proposed, and the pharmacophore model with the best score was selected.

Pharmacophore screening
Using the pharmacophore model derived from six active compounds, pharmacophore screening was performed to assure that only active compounds were selected from a compound library consisting of 44 compounds. In the pharmacophore screening process, we utilised the “iscreen” module within LigandScout 4.4. The scoring function chosen was “Relative Pharmacophore-Fit,” the conformation match mode was set to “BEST,” and the check for exclusion volume clashes was set to “disabled.” The Relative Pharmacophore-Fit score was obtained from the number of matching pharmacophore features and the root mean square deviation of the pharmacophore alignment, normalised by [0,1]67,68. Compounds that did not match the pharmacophore were assigned a score of zero.

Immunofluorescence staining and imaging
Cells attached to glass coverslips for overnight culture were stimulated with HCQ (100 or 250 µM) for the indicated time periods, fixed in 100% MeOH (Nacalai Tesque) for 5 min, and permeabilised with 0.1% Triton X-100 (Nacalai Tesque) for 5 min. After washing twice with PBS (Nacalai Tesque), the cells were incubated in Block Ace (Snow Brand Milk Products, Tokyo, Japan) for 1 h and then incubated with an anti-calreticulin antibody (1:500, ab92516; Abcam) in PBS containing 2% BSA (Nacalai Tesque) for 6 h at 4°C. After washing three times with PBS, a secondary antibody (anti-rabbit IgG, 1:2000, A-21246; Thermo Fisher Scientific) was applied and incubated in the dark for 1 h at room temperature. DNA staining was performed with DAPI (0.025 μg/mL; Sigma-Aldrich) during the staining with the secondary antibody. Finally, the cells were washed three times with PBS and mounted in Fluorsave (345789; Merck, Darmstadt, Germany). Confocal images were captured using the Nikon A1Rsi laser scanning microscopy system (Nikon, Tokyo, Japan). Fluorescence intensity profile analysis and 3D image reconstruction were performed using Nikon NIS-Elements software. Fluorescence images were also obtained with the BZ-X800 all-in-one fluorescence microscope (KEYENCE, Osaka, Japan). The nuclear and cytoplasmic areas and the fluorescence intensity of calreticulin were automatically calculated using the Hybrid Cell Counting application BZ-H4C (KEYENCE) of the BZ-X Analyser software BZ-H4A (KEYENCE).

scRNA-seq
scRNA-seq was performed by KOTAI Biotechnologies (Osaka, Japan). Sequencing was performed in paired-end mode (read 1: 28 bp; read 2: 100 bp) using the DNBSEQ-G400 sequencer (MGI Tech, Shenzhen, China). The resulting scRNA-seq data were processed using the CellRanger pipeline (ver. 7.2.0) configured for 3’ v3 chemistry, and aligned to the refdata-gex-mm10-2020-A reference genome (10x Genomics, Pleasanton, CA, USA). Subsequent analysis was performed using the Seurat R package (ver. 5.0.2). Cells were filtered based on thresholds of 200–10,000 detected genes and a minimum unique molecular identifier count of 1000. Data were normalised by the NormalizeData function and integrated by the IntegrateData function for reference-based integration69. Canonical correlation analysis was used as the reduction method to identify anchors using the FindIntegrationAnchors function. Cluster identification of cells was performed by a shared nearest neighbour modularity optimisation-based algorithm using the FindNeighbors and FindClusters functions. Cell types for each cluster were annotated based on differentially expressed genes identified by the FindAllMarkers function and known marker genes. Uniform Manifold Approximation and Projection (UMAP) and violin plots were generated by the DimPlot and VlnPlot functions, respectively. Gene expression and density on the UMAP plots were visualised using the FeaturePlot_scCustom and Plot_Density_Custom functions, respectively, from the scCustomize package (ver. 2.0.1). IFN-stimulated gene signature score was calculated using the AddModuleScore_UCell function from the UCell package (ver. 2.6.2) with IFN-induced protein with tetratricopeptide repeats 1 (Ifit1), Ifit3, 2’−5’-oligoadenylate synthetase 1, Irf7, and Zbp1 genes as input. Gene set enrichment analysis (GSEA) was conducted with the fgsea package (ver. 1.28.0) and mouse MSigDB hallmark gene sets. The results were visualised using the geom_point function from the ggplot2 package (ver. 3.4.4). Statistical comparisons between groups of cells were conducted using the Wilcoxon rank sum test.

Flow cytometry
For the nuclear staining of dying cells, the cells were incubated with SYTOX green (0.5 µM; Thermo Fisher Scientific) for 10 min. After washing, the cells were analysed using the BD FACS Discover S8 Cell Sorter (Becton, Dickinson and Company [BD], Franklin Lakes, NJ, USA). To analyse cell surface calreticulin, the cells were stained with Alexa Fluor® 405 calreticulin antibody (Abcam) after blocking the Fc receptor with anti-CD16/32 antibody (BioLegend, San Diego, CA, USA). Then the cells were incubated with SYTOX green (0.5 µM; Thermo Fisher Scientific) for 10 min and measured using the BD LSR Fortessa flow cytometer (BD). For intracellular staining of calreticulin, the cells were stained with LIVE/DEAD® Fixable Near-IR stain (Thermo Fisher Scientific). After fixation and permeabilisation with Foxp3/Transcription Factor Staining Buffer (Thermo Fisher Scientific), non-specific staining was blocked with mouse serum. Then the cells were stained with the Alexa Fluor 488 anti-calreticulin antibody (Abcam). After washing, the cells were stained with DRAQ5 (5 µM; Thermo Fisher Scientific) for 10 min and analysed using the BD FACS Discover S8 Cell Sorter.

Analysis of images by flow cytometry
Cell regions were cropped from grayscale images and underwent brightness correction using Contrast Limited Adaptive Histogram Equalisation. Noise was then reduced by Gaussian filtering, and the image was binarised using Otsu’s method. Holes in the resulting binary image were filled to define cellular regions. The Watershed algorithm was utilised to segment these cells. Within each segmented cell region, the number of DNA pixels was quantified. The region with the higher DNA pixel count was selected for further analyses, provided that the original cell region was a singular entity capable of being subdivided into two distinct segments. For the selected cell, the boundary delineated using the Watershed segmentation was dilated twice, effectively expanding it by two pixels. An AND operation was then performed between this expanded boundary and the mask of the analysed cell. This procedure identified the adjacent contact area of the cells. Finally, we measured the number of pixels in this adjacent contact surface area, as well as the count of DNA pixels within it. DNA ratios are calculated as the ratio of the number of DNA pixels to the number of pixels in the adjacent contact surface area.

Concurrent detection of IFN-β secretion and nuclear staining using LCI-S
Imaging of IFN-β secretion using LCI-S was performed as previously described with some modifications30,31. Briefly, the time-resolved measurement was performed with a completely automated inverted microscope ECLIPSE Ti2-E (Nikon) equipped with a high numerical aperture (NA) objective lens (CFI Apo TIRF 60× Oil, NA = 1.49; Nikon), the INUBG2TF-WSKM stage-top incubator (Tokai Hit, Shizuoka, Japan), and the ORCA-flash 4.0 V3 digital CMOS camera (Hamamatsu Photonics K.K., Shizuoka, Japan). A light-emitting diode (D-LEDI; Nikon) and laser diode (640 nm, LDI-7; 89 North, Williston, VT, USA) were used as light sources. The following sets of excitation and emission filters and a dichroic mirror were used: for epi-illumination of SYTOX Blue, a fluorescence filter cube for large field of view (FOV) imaging (CFPC-FLL-C) from Nikon was used; for total internal reflection fluorescence (TIRF) illumination of LCI-S of IFN-β, the ZET405/470/555/640x excitation filter (Chroma Technology, Bellows Falls, VT, USA), ZT561dcrb-UF2 dichroic beamsplitter (Chroma Technology), and ZT405/470/555/640rpc-UF1 multiband dichroic beamsplitter (Chroma Technology) were used. Cells were suspended in medium at a density of 2.5 × 106 cells/mL and added to each chamber (5 mm diameter) of a 4-condition LCI-S chip (LCI-SPQ002; Live Cell Diagnosis, Saitama, Japan) at 50 µL, where the anti-IFN-β antibody (capture antibody from the Mouse IFN-beta DuoSet ELISA, DY8234-05; R&D Systems) was immobilised. Immediately before observation, the culture supernatant was replaced with freshly prepared culture medium containing 0.1 µM SYTOX Blue and 30 nM biotinylated antibody against IFN-β (detection antibody from the Mouse IFN-beta DuoSet ELISA, DY8234-05; R&D Systems) coupled with CF660R-labelled streptavidin (29040; Biotium, Fremont, CA, USA). Stimuli (80 or 100 µM HCQ and 5 µg/mL cGAMP) were replaced immediately before observation. Mineral oil (M5310; Merck, Darmstadt, Germany) was layered on top of the medium to prevent evaporation. A total of 169 fields of view were scanned in each chamber repetitively to continuously detect extracellular release of IFN-β using LCI-S, and dead cell nuclei were stained with SYTOX Blue.

LCI-S imaging analysis
Microscopic data obtained underwent image analysis using NIS-Elements 5.4 (Nikon). To visualise the IFN-β secretion activity at a moment in each frame, we determined the incremental fluorescence intensity at every time point using a specific image analysis procedure. First, we corrected for the small pixel drift occurring during each scanning cycle. Subsequently, noise reduction was applied, followed by a rolling minimisation over six frames to eliminate fluorescence spots from intracellular vesicles formed by pinocytosis of the fluorescent detection antibody. To obtain consecutive images, the fluorescence intensity from the previous time point was subtracted to derive the fluorescence intensity increment for each time point. To track changes over time in the number of IFN-β-secreting cells and damaged cells, we developed an artificial intelligence model for cell recognition. For this purpose, images of total and damaged cells in 10% and 1% of the total field, respectively, were manually identified in brightfield and SYTOX Blue-stained images, and the model was trained using NIS.ai on NIS-Elements. The time-dependent increase in cell damage was assessed as the proportion of the number of damaged cells at each time point to the total number of cells at the start of observation in each FOV. Moreover, the frequency and intensity of IFN-β secretion were evaluated by the time of appearance and maximum brightness of each spot in the IFN-β secretion activity signal (incremental images) stitched over the entire area of observation. Each spot was identified by spot detection and tracking methods using NIS-Elements. To evaluate the effects of inhibitors, imaging was performed using the same inverted microscope setup equipped with a wide-field LCI-S module (wfLCI-S illuminator; Live Cell Diagnosis, Saitama, Japan) and an LCI-S chip (model LCI-SWFP6002; Live Cell Diagnosis) in combination with a 10× objective lens (CFI Plan Apochromat Lambda D 10×; Nikon). Differential interference contrast optics were used for transmitted light observations.

In silico analysis
In silico analysis was conducted based on the quantum molecular dynamics method70,71 using DMol372,73 in Materials Studio Dassault Systemes and parallel computers with 100 TFLOPS. The simulations were performed based on the density functional theory72, and the functional used in this study is a hybrid functional called the B3LYP74 functional, which stands for “Becke, 3-parameter, Lee–Yang–Parr.” Instead of using pseudopotentials as core treatment, all-electron calculations were conducted, and double numerical plus d-functions75 were used as the atomic basis sets. The time step of the dynamics simulations was set at 0.1 fs. By putting a compound molecule at an initial position on the PPT1 surface, the molecule was observed to move to an energetically stable position as a result of molecular dynamics simulation. By randomly changing the initial position on the PPT1 surface 100 times, the stable position was confirmed to always be the same and independent of the initial position. Thus, the stable state of the system where the compound molecule adheres to PPT1 was obtained, and the energy of this state, E_cP, was calculated. The binding energy of the compound to human PPT1, E_bin, was defined as E_bin = |E_cP + E_c - E_P|, where E_c and E_P are the energies of the isolated compound and isolated PPT1, respectively74,76,77. The binding energy is often called the adhesion energy.

Microscopic analysis
Cells were suspended in RPMI 1640 without phenol red (Nacalai Tesque) containing 10% FBS (Sigma-Aldrich) and seeded into each well (2.25 or 2.0 × 10⁵ cells/well) of a 96-well glass-bottom plate (Matsunami Glass Ind., Ltd., Osaka, Japan). Before observations, HCQ and SYTOX Green were added to a final concentration of 80 or 100 µM, and 0.1 µM, respectively. After 1 h, microscopic analysis was performed with the BZ-X1000 fluorescence microscope (KEYENCE). Images were obtained every 600 s for 12 h using a 60x objective lens (Plan Apochromat 60x Oil/N.A. 1.40/WD 0.13). Statistical analyses were carried out with the BZ-X1000 Analyser application (KEYENCE).

Holographic analysis
Cells were suspended in RPMI 1640 without phenol red (Nacalai Tesque) containing 10% FBS (Sigma-Aldrich) and seeded into each well (2.0 × 105 cells/well) of a 96-well plate that was coated with polylysine (Sigma-Aldrich). Before observations, HCQ and SYTOX Red (Thermo Fisher Scientific) were added to a final concentration of 80 or 100 µM, and 0.167 µM, respectively. Holotomographic imaging was performed using the 3D Cell Explorer microscope (Nanolive SA, Tolochenaz, Switzerland) according to the standard protocol provided by the manufacturer. After 1 h, images were obtained every 10 min for 12 h with an acquisition area of XY = 217 µm × 217 µm with a Z-stack range of 30 µm for each position. Holotomographic images were obtained using EVE Version 2.2 operating software. Sytox images were also obtained every 10 min using the inbuilt fluorescence unit.

3D holotomography
Cells were suspended in RPMI 1640 without phenol red (Nacalai Tesque) containing 10% FBS (Sigma-Aldrich) and seeded into each well (4.0 or 6.0 × 106 cells/well) of a 6-well plate (IWAKI, Tokyo, Japan). Before observations, HCQ and SYTOX Green were added to a final concentration of 80 or 100 µM, and 0.01 µM, respectively. After 30 min, holotomography imaging was conducted with the HT-X1 microscope (Tomocube Inc., Daejeon, South Korea). Images were obtained every 100 s for 12 h with an acquisition area of XY = 164.7 µm × 164.7 µm with a Z-stack range of 60 µm for each position. 3D HT images were obtained using the operating software (TomoStudio X, Tomocube Inc.). Sytox images were obtained every 4 h.

Statistical analyses
Data are expressed as the mean ± standard deviation or as described in each figure legend. Statistical analyses were performed using GraphPad Prism 8 (GraphPad Software, Boston, MA, USA). The results are shown in each figure or described in each figure legend.

Materials availability
The mouse lines generated in this study will be deposited to the RIKEN BioResource Research Center after acceptance for publication. Any additional data will be provided by the corresponding author upon request.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Negishi et al., investigate the direct role of CADs (focusing mostly on HCQ) for inducing an antiviral (i.e. IFN) response in BMDCs. The authors find that CAD treatment promotes cell death (mechanism unclear) leading to sensing of cell death-derived DNA by neighbouring viable cells and induction of the antiviral cGAS-STING-IFN response. The detection of exogenous DNA remains an important outstanding in the field. The authors utilise an elegant imaging system to visualise DNA uptake by subsequent IFN-inducing cells and propose a new mechanism for the transfer of stimulatory DNA termed “nucleocytosis”. However, multiple experiments would be required to confirm this novel phenomenon.\nGeneral points:\n-the abstract and title do not mention CAD (or HCQ) which is the main focus of the paper. The abstract should be updated to reflect the context of this nucleocytosis as it appears distinct from other forms of lysosomal disruption (e.g. Bafilomycin A)\n-perhaps the best data supporting that cGAS-STING activity is induced by exposure to extracellular self DNA comes from the findings that cGAS, STING or IFNAR co-deletion can rescue the embryonic lethality in DNase II deficient mice. Mice lacking the DNase II cannot degrade excessive DNA following apoptosis in embryonic development suggesting phagocytosis of DNA into endolysosomal compartments is important for degrading extracellular DNA. Reference/discussion of this data is completely lacking from the manuscript.\n-it is not made clear how this nucleocytosis phenomenon differs from engulfment of dying cells via calreticulin detection (e.g. via LRP) and phagocytosis of cell debris. Please also see below (points for fig 3). For example, LCI-S imaging of phagocytosis of apoptotic debris by BMDCs may act a nice comparison (focusing on the DNA localisation similarly using sytox). There are also several questions remaining which need to be addressed or at a aminimum discussed - e.g. Is nucleocytosis also dependent on canonical phagocytosis machinery? How is this detected via recipient cells? How does the DNA get out of the nuclear membrane? Etc.\n-molecular weight markers should be indicated for all western blots\n-discussion point – CQ, Bafilomycin A and other drugs affecting lysosomal function prevent STING degradation and lead to enhanced activation. (e.g 10.1016/j.celrep.2017.11.061 amongst others). This could also boost the IFN activity observed. This is particularly relevant for lines 295-300 where perhaps the increased activity by proton inhibition is rather just enhancing the STING activity.\n-while the use of structural analysis and the identification of 5 conserved structural elements in the IFN-inducing CADs is well utilised, conclusions are drawn from in silico predictions only (i.e. Fig 4) and findings are generalised to these 5 CADs, although often only experimentally proven for HCQ. The authors should perform key mechanistic experiments (e.g. IFN blockade with N-(tert-Butyl)-hydroxylamine) for remaining IFN-inducing CADs.\n-while a portion of the manuscript focuses on PPT1 its function as a palmitate hydrolase is largely ignored. The authors should discuss the role of protein palmitoylation in the mechanism and discuss the role of potential de-palmitoylation events.\nFigure 1:\n-the authors swap between uM and ug/mL units for HCQ making it difficult to compare data across figures. Please select one notation and be consistent\n-Fig 1a-b: it is already observable that HCQ induced delayed kinetics compared to cGAMP. This should be noted in the text when explaining fig 1.\n-Fig 1b: it is not clear what is plotted in Fig 1b (e.g. replicates) and no error bars for variability between replicates are included\n-in Extended fig 1b there appears to be a HCQ-specific cluster induced early (i.e. 3h, shown in purple). This is very interesting, important to consider and should be mentioned in the text.\n-Fig 1f,g: It is well known that cGAS-STING is important for maintaining basal IFN tone. Therefore, in addition to utilising STING knockout BMDCs (which may exhibit different basal activation) the authors should also confirm that short-term pharmacological STING inhibition (e.g. H151) can also block HCQ-induced IFN.\nFigure 2:\n-the authors should also provide references for the LCI-S approach on line 166 (not only in the methods)\n-please also show the corresponding brightfield image for all LCI-S figures (e.g. Fig 2a-c) as this helps to orient the reader and IFN spots and sytox accumulation is related to the cell density and total number of cells in the FOV\n-the authors only quantify the number of IFN spots. In addition, it may be worthwhile to also quantify and plot the intensity and also area of IFN spots for HCQ vs cGAMP.\n-fig 2i: the gating/arrow is confusing here as it looks like only the sytox + cells are gated in the panel below (however I believe this is not the case). It is also not exactly clear how the sytox positive gates were chosen, especially as the cells look rather different for untreated vs HCQ (e.g. in terms of FSC). Please also show the unstained populations in the extended figures (to show where sytox positive cells are positioned within the plot – relevant for Fig 2 I and j. (The labelling of gates in Fig 2j is also confusing)\n-line 188-190 – it is not clear to me how expression of mitochondrial genes is confirming cell injury/death. The altered genes and\nFigure 3:\n-it appears that after HCQ treatment cells shrink in size, but also display a larger nucleus (Fid 3d, also observed as reduction in FSC while HCQ treatment in Fig 2i). The authors propose that calreticulin translocates from the cytosol to the nucleus. However, from the images it could be possible that rather there are considerable changes in cell morphology including the break down of the nuclear membrane, leading to leakage of DNA content into the cell cytosol, a portion of which is phagocytosed by recipient cells. To confirm this the authors should further stain for additional ER and organelle markers and/or the nuclear membrane (e.g. Lamin B1) to confirm the integrity of the nucleus. Furthermore, the authors could quantify the cellular size, we well as the size of the nucleus (both for all and sytox positive cells). In addition, could it be that the increase in MFI of calreticulin (particular in dead cells prone to increased autofluorescence) is due to cell shrinkage and concentration of fluorescent signal. The authors should perform a western blot to verify the increased calreticulin expression (referred to on line 235-236).\n-staining of calreticulin is only performed on permeabilised cells. It would also be of interest to assess surface expression of calreticulin via flow cytometry (without cellular permeabilisation) as membrane calreticulin is a known eat me signal for apoptotic cells. Nuclear calreticulin in the absence of cell surface would further support a novel transfer of DNA to surrounding BMDCs.\n-line 261/262: please define and introduce the function of PPT1 and MRGPA3\n-fig 3m,n: the authors show that Rho/ROCK kinase inhibition reduces HCQ IFN production without affecting cytotoxicity. The authors must therefore confirm whether Rho/ROCK kinase inhibition affects direct cGAS-STING mediated IFN (i.e. via cGAMP) or whether this inhibition is upstream/involved in DNA uptake. Furthermore, the authors should show whether Rho/ROCK kinase inhibition prevents DNA uptake via affecting interaction between damaged cells and IFN-inducing cells via either LCI-S or imaging flow cytometry, and further assess the impact on localisation of calreticulin (as proposed).\nFig 4:\n-the authors show that combination of DC661 (PPT1 inhibition) and Bafilomycin A (proton inhibition) recapitulates the IFN response, proposedly similarly to HCQ/CADs. The authors should confirm via LCI-S and/or imaging flow cytometry that a similar cell-cell transfer of DNA occurs.\nFig 5:\n-line 331-332: the cell type specific effect does not necessarily mean a local effect. The specificity may be due to the phagocytic potential of the cells, the expressed receptors etc. This should be amended in the text.", "reviewer_2": "The article by Negishi et al. entitled \"Phased lysosomal malfunction triggers nucleocytosis to the cGAS-IFN-I axis\" is interesting and well written, but some data have to be added/modified to be more convincing (only few cells observed, correlation of calreculin staining but no demonstration, or n=3 biological replicates, etc….).\nIndeed, in this article, the authors have demonstrated with the help of 5 figures that:\n1. IFN-beta is induced in vitro by antivirals cationic amphiphilic drugs (CADs) such as hydroxychloroquine (HCQ) on mouse BM-DCs and that this production is coming from a limited number of cells.\n2. This process involves cell death-related events (no pathway identified) and the STING pathway (using cGAS and STING Ko BM-DCs).\n3. DNA can be transfer from one DC (or tumor cells) to BM-DC by videomicroscopy (nucleocytosis)\n4. Rho/ROCK kinases are involved in the IFN-b production through calreticulin engagement\nFor Fig 1.\n-As DCs can mature spontaneously, removal and activation with PBS 12h as a real negative control has to be done.\n-Gene enrichement analysis has also to be done using for example The Molecular Signatures Database (MSigDB) in order to better characterize pathways activated by CAD.\n-All the data in figure 1 represent n=3 donors which is not enough to perform a t-test.\nFig2.\n-The limited number of cells producing type I IFN is a known phenomenon in many cells (observed by intracellular FACS staining) and more precisely on pDC which are specialized for this function. It is also well known that the level of IFN type I secretion is very different between donors, it’s why the use of only n=3 donors here is not enough to conclude. Statistical analysis is not appropriate for example for Fig 2k as a two way ANOVA couldn’t be done with n=3 biological replicate.\n-Line 206, authors have to be more cautious and used « support the notion that maybe … »\n-in Fig 2j, author may include the % of sytotox green postive cells in non-multiplet cells.\n-scRNAseq performed on treated DC is not very informative because only few genes are shown. It seems like one or two clusters of cells respond to HCQ. DEG analysis have to be done to further characterize DCs responding to HCQ. Indeed, a specific cell subsets (or cell state) producing IFN-b in BM-DC is thus not identified.\nDo this HCQ activation is conserved with other DC subsets ? Flt3l generated cDC1 ? pDC ? on blood circulating DC and not BM-derived ? monocytes ?\nFig3.\nFig3a. : IFN-b expression is not visible on pictures !? and the graph on the right is not clear. The Y axis has to better indicates: “DNA intensity”\n-The DNA transfer from one DC to another is based on data in fig 3a and is not very clear (very diffuse) and video microscopy allows the observation of only limited number of cells. This has to be better demonstrated.\nFig3b. : the legend is not clear and the data already shown in fig 2.\nNumbers in white (legend ?) : not visible\nDefine P1 and P2 ?\nFig3d-g :« calreticulin accumulated in the DNA-positive region of HCQ-induced dying cells » is overinterpretation as the figure 3g gave us only the proportion of calreticulin in the nucleus compared to the cytosol which is very clear on figure 3d.\nFig3i : Authors have to use the same scale for comparison and specify in the caption that this is an intracellular staining.\nFig3j: too much pixelization, not very clear and may be not useful\n-line 266 “inhibition of HCQ-induced IFNβ production (Extended 267 Data Fig. 4b), suggesting the involvement of PPT1 inhibition in IFNβ production. ». This have to be included as main result.\nFig4.\nLine 300 –“our results indicate that both calreticulin accumulation via proton inhibition and cell -death via PPT1 inhibition are important for robust IFNβ production (Fig. 4j)”. Authors have to be more cautious here as a PTT1 KO was not evaluated.\n-again, a two way anova couldn’t be done with n=3 biological replicates.\nFig5.\n-only one cell in image 5c. Authors should show us a wider field and more cells have to be analyzed.\n-Legend on histogram is missing (X axis?)\n-Title Fig5 “Various type…” replace by “Two types of tumor cell…”\n-Fig5e: Instead of using a single gene to annotate clusters, authors could use other tools such as Ucell. Again, better analysis of the scRNAseq data could help to understand the full effect of HCQ and not just to analyze IFN-related genes, otherwise simple qPCR would be enough.\nThe number of cells analyzed by scRNAseq is certainly not enough to have DC subsets which is missing in regard to the rest of the paper.\n-For example, -what is the expression of STING in the different clusters?\n-Endothelial cells highly respond in vivo to HCQ. Do their express STING? This is not discussed or described.\n-scRNAseq data generated in vivo is not well described (see the last paragraph of the Result section) and discussed.\nIn conclusion, my opinion is to accept this paper but with major modifications. Indeed, the possible acquisition of DNA by nucleocytosis, the direct induction of IFN-b by HCQ during a cell-death process is very interesting, but\n1/all the paper is made with in-vitro-generated BM-DCs\n2/The pathway involved in CAD mediated cell-death is not identified.\n3/The nucleocytosis is not enough demonstrated and the molecular mechanism not identified\n4/There are many over-interpretations and sometimes correlations more than demonstrations.\n5/many data in the paper concern few cells or are generated with only n=3 biological replicates with sometimes two variables/experiment and thus statistics not suitable."}, "author_response": "Dear Reviewers,\nWe sincerely thank all reviewers for their thorough reading of our manuscript and for the\ninsightful and constructive comments. We have carefully addressed all the comments and\nrevised the manuscript by including additional experiments and analyses. Please find our\ndetailed point-by-point responses below. We hope that the revisions have strengthened\nthe manuscript and that it will now be suitable for publication.\nSincerely,\nKen J. Ishii\nREVIEWER COMMENTS\nReviewer #1 (cGAS/STING, inflammation) (Remarks to the Author):\nComment 1:\nNegishi et al., investigate the direct role of CADs (focusing mostly on HCQ) for inducing an\nantiviral (i.e. IFN) response in BMDCs. The authors find that CAD treatment promotes cell death\n(mechanism unclear) leading to sensing of cell death-derived DNA by neighbouring viable cells\nand induction of the antiviral cGAS-STING-IFN response. The detection of exogenous DNA\nremains an important outstanding in the field. The authors utilise an elegant imaging system to\nvisualise DNA uptake by subsequent IFN-inducing cells and propose a new mechanism for the\ntransfer of stimulatory DNA termed “nucleocytosis”. However, multiple experiments would be\nrequired to confirm this novel phenomenon.\nResponse 1:\nWe sincerely appreciate your thoughtful and careful evaluation of our manuscript. Your\nvaluable comments have greatly helped us to clarify our results and conclusions and to\nfurther strengthen the study. In response to your suggestions, we performed additional\nexperiments and revised the text accordingly. Our detailed responses are provided below,\nand all additions and revisions are indicated inbluein the response document.\nComment 2:\nGeneral points:\n-the abstract and title do not mention CAD (or HCQ) which is the main focus of the paper. The\nabstract should be updated to reflect the context of this nucleocytosis as it appears distinct from\nother forms of lysosomal disruption (e.g. Bafilomycin A)\nResponse 2:\nThank you for your valuable comment. We agree that this is an important point. We have\nadded the following sentence to the abstract.\nChange: Abstract, Line 65\nBefore:\nWe found that lysosomal inhibition, including both lysosomal proton and PPT1, triggers cell\ndeath with nuclear calreticulin, followed by local but robust IFN-I production via cGAS-\nSTING.\nAfter:\nWe found that lysosomal inhibition, including both lysosomal proton and PPT1 by anti-viral\ncationic amphiphilic drugs, triggers cell death with nuclear calreticulin, followed by local but\nrobust IFN-I production via cGAS-STING.\nComment 3:\n-perhaps the best data supporting that cGAS-STING activity is induced by exposure to\nextracellular self DNA comes from the findings that cGAS, STING or IFNAR co-deletion can\nrescue the embryonic lethality in DNase II deficient mice. Mice lacking the DNase II cannot\ndegrade excessive DNA following apoptosis in embryonic development suggesting phagocytosis\nof DNA into endolysosomal compartments is important for degrading extracellular DNA.\nReference/discussion of this data is completely lacking from the manuscript.\nResponse 3:\nThank you for pointing this out. We agree that the relationship between the phenotypes of\nDNase II-deficient mice and the roles of cGAS, STING, or IFNAR represents an important\nprecedent in this field. We have now cited the following papers and added a discussion on the\nrelationship between our findings and these studies.\nChange: Discussion, Line 420-432\nAddition:\nAn important previous discovery relevant to the discussion of the uniqueness of nucleocytosis\nis the developmental abnormality observed in DNase II-deficient mice (Nature Immunology\nvolume 6, pages 49‒56 (2005), Proc Natl Acad Sci U S A. 2012 Nov 19;109(47):19386-91.).\nIn the absence of DNase II, self-DNA derived from apoptotic cells is engulfed by macrophages\nbut fails to undergo degradation, resulting in its abnormal accumulation within endosomes.\nConsequently, this leads to exposure of DNA to the cytosol and activation of the cGAS-\nSTING pathway. These findings clearly demonstrate the critical role of extracellular DNA\ndegradation within endosomes and provide a rational mechanism by which dead cells can be\nprocessed without triggering inflammation. In this sense, when considering how normal\ncells with DNases activate an immune response via the cGAS-STING, another mechanism\nthat bypasses the endosomal route is necessary. In this context, the discovery of nucleocytosis\nfurther advances our understanding of self-nucleic acid-mediated activation of the cGAS-\nSTING pathway, and future studies are expected to elucidate its involvement in diverse\nimmune responses and diseases.\nAdditional Reference:\nNature Immunology volume 6, pages 49‒56 (2005)\nProc Natl Acad Sci U S A. 2012 Nov 19;109(47):19386-91.\nComment 4:\n-it is not made clear how this nucleocytosis phenomenon differs from engulfment of dying cells\nvia calreticulin detection (e.g. via LRP) and phagocytosis of cell debris. Please also see below\n(points for fig 3). For example, LCI-S imaging of phagocytosis of apoptotic debris by BMDCs\nmay act a nice comparison (focusing on the DNA localisation similarly using sytox). There are\nalso several questions remaining which need to be addressed or at a aminimum discussed - e.g. Is\nnucleocytosis also dependent on canonical phagocytosis machinery? How is this detected via\nrecipient cells? How does the DNA get out of the nuclear membrane? Etc.\nResponse 4:\nThank you for this insightful comment. We agree that distinguishing nucleocytosis from\nconventional phagocytosis is an important and intriguing aspect of our study. While a visual\ncomparison under identical conditions would be ideal, our LCI-S imaging did not reveal clear\nengulfment during IFN production under the current experimental settings. Therefore, we\nhave referred to a comprehensive review describing representative features of phagocytosis\n(Nat Rev Immunol. 2019 Dec 10; 20(4):254‒267). To further clarify the morphological\nfeatures of nucleocytosis, we performed additional analyses using Z-stack imaging and\nholographic microscopy. These analyses enabled us to visualize direct access of live cells to\nthe nuclei of dying cells and the subsequent movement of nucleic acids. We also observed\nvariations in the spatial relationships between dying and live cells, where protrusion-like\nstructures were consistently present (Fig. 3d‒h, Extended Data Fig. 3b, c), clearly distinct\nfrom engulfment-like morphology. Consistent with these observations, IFN production was\nsuppressed by cytoskeletal inhibitors (Fig. 3i), suggesting that cytoskeletal dynamics are\nrequired for nucleocytosis. This requirement appears to be similar to that in phagocytosis.\nInterestingly, cytoskeletal inhibitors enhanced cGAMP-induced IFN production (Fig. 3i),\nconsistent with previous findings showing that cytoskeletal transport converges on STING\nsignaling within the cell (J Exp Med. 2023; 220(3): e20220990). Nevertheless, the observation\nthat HCQ-induced IFN production was inhibited by cytoskeletal inhibitors suggests that\nupstream events of cGAS-STING activation are disrupted̶likely due to inhibition of\nprotrusion-mediated interactions. This finding is also consistent with the results of Rho kinase\ninhibition (Fasudil) shown in Fig. 4m. Regarding the mechanism by which dying cells are\nrecognized, we added a discussion considering its potential relationship with phagocytosis.\nOur imaging analyses suggest that DNA is transferred through protrusion-like structures,\nalthough the distance between the dying cell and the IFN-producing cell can vary, which may\naffect the observed appearance of these protrusion-like structures. Notably, DNA signals were\ndetected within these protrusions (Fig. 3g). In addition, as shown in Fig. 4l, thin tubular\nconnections remained even after nuclear detachment from dying cells. These observations\nmay indicate the potential involvement of tunneling nanotube (TNT) formation. Previous\nstudies have reported that stressed cells can form TNTs, contributing to viral transmission\nand nucleic acid transport, and that Rho kinase is involved in TNT formation (Mol Pharm.\nformation and nucleocytosis represents an important direction for future investigation. Based\non your comment, we have added these new results and the corresponding discussion with\nappropriate references. We sincerely appreciate your suggestion, which has helped us to\ndescribe our findings more clearly.\nChange: Figure, Fig. 3d-i, Extended Data Fig. 3b, c\nAddition: (Please see the revised figure for details; the following is a summary.)\nFig. 3d-I. Extended Data Fig. 3b, c\nChange: Legend, Fig. 3, Extended Data Fig. 3\nAddition:\nFig. 3. d-h. Microscopic analysis of HCQ-treated GM-BMCs. d. Snapshot analysis of GM-\nBMCs treated with HCQ (80 µM) for indicated time periods. Bright field with DNA staining\nis shown in both MIP and Z-slice images. e. Time-laps analysis of GM-BMCs treated with\nHCQ (80 µM). Bright field with DNA staining is shown in left five panels. DNA intensity is\nsummarised in the middle. Z-slice picture at indicated time point is shown in the right. f.\nHolotomographic analysis of GM-BMCs treated with HCQ (80 µM). Snapshot images in\nindicated time points are shown in both MIP and Z-slice pictures. g, h. Holotomographic\ntime-laps analysis of GM-BMCs treated with HCQ (100 µM) for indicated time periods. DNA\nstaining is shown in red in MIP images. Z-slice images at indicated time point are shown in\nh. i. Concentration of IFNβ in the culture supernatant of GM-BMCs treated with HCQ (100\nµM) in the presence of indicated concentration of inhibitor.\nExtended Data Fig. 3. b, c. Time-laps analysis of GM-BMCs treated with HCQ (80 µM).\nBright field with DNA staining is shown in left six panels. DNA intensity is summarized in\nthe right. Z-slice picture at indicated time point is shown in c.\nChange: Result, Line 223-242\nAddition:\nFrom above results (Fig. 3a-c), we hypothyzed that, through contact between dead and live\ncells, DNA is transferred to IFN-producing cells, thereby activating the STING-cGAS\nresponse. According to the results of LCI-S, within 6 hours after HCQ treatment, at which\ntime IFN secretion is observed, nuclear structures of sytox-positive dead cells can be\ndetected (Fig. 2b, d). Given the fact that HCQ induced strong IFN production, enough\namount of DNA is efficiently taken up from dead cells. Therefore, we next examined whether\ncontact of live cells with dead cell nuclei and subsequent DNA uptake occurs by microscopic\nanalysis. As a result, although the distance between dead and live cells and the degree of dead\ncell disintegration varied, in all cases both MIP and slice images revealed protrusion-like\nstructures and direct access to the nucleus (Fig. 3d). Remarkably, time-lapse analysis further\ndemonstrated a decrease in DNA intensity in dead cell nuclei accompanied by an increase in\nDNA intensity in live cells (Fig. 3e, Extended Data Fig. 3b, c). Likewise, holographic\nmicroscopy confirmed the presence of protrusion-like structures, and importantly, DNA\nsignals within the protrusion was also detected (Fig. 3f, g). Cross-sectional image analysis\nrevealed that these protrusion extended into the nucleus and that low-density regions was\nobserved inside the nuclei at sites of contact (Fig. 3g, h). Consistent with these findings,\ninhibitors of actin polymerization specifically suppressed HCQ-induced IFN production (Fig.\n3i). Collectively, these results suggest that live cells directly access the nuclei of dead cells and\nextract DNA.\nChange: Discussion, Line 433-448\nAddition:\nAs shown in Fig. 3d-h, nucleocytosis is markedly different from phagocytosis both\nmorphologically and mechanistically. In conventional phagocytosis (Nat Rev Immunol. 2019\nDec 10;20(4):254‒267.), cells or cellular fragments are engulfed and internalized through\nendocytosis, after which their contents are digested. In contrast, in nucleocytosis, protrusion-\nlike structures were observed (Fig. 3d-h). Consistent with this, inhibitors that suppress\nprotrusion formation or extension also reduced IFN production (Fig. 3i and 4m). These\nobservations indicate that, while the morphological differences are clear, they share the\ncommon feature that cellular shape changes are required. How dead cells are recognized\nbefore nucleocytosis remains to be elucidated, and future studies are needed to determine\nwhether common \"eat-me signals,\" as in phagocytosis, are involved. Moreover, regarding the\nmechanism by which protrusion-like structures incorporate nucleic acids, a potential\nrelationship with tunneling nanotubes (TNTs) represents an interesting issue for future\ninvestigation, because TNTs enable the transfer of cytosolic molecules, including nucleic acids,\nto the cytosol of other cells, and the involvement of Rho kinase in TNT formation has been\nreported (Mol Pharm. 2024 Oct 7;21(11):5413‒5429). Further analyses of TNT between ʻthe\ncytosol and the nucleusʼ present an intriguing avenue for future research.\nAdditional Reference:\nNat Rev Immunol. 2019 Dec 10;20(4):254‒267.\nMol Pharm. 2024 Oct 7;21(11):5413‒5429.\nComment 5:\n-molecular weight markers should be indicated for all western blots\nResponse 5:\nThank you for pointing this out, and we apologize for the lack of this information. We have\nnow added molecular weight markers to all relevant western blots. Please see Fig. 1d and\nExtended Fig. 1f in the revised manuscript.\nChange: Fig. 1\nFig. 1d. (corrected) Extended Data Fig. 1f (corrected)\nComment 6:\n-discussion point ‒ CQ, Bafilomycin A and other drugs affecting lysosomal function prevent\nSTING degradation and lead to enhanced activation. (e.g 10.1016/j.celrep.2017.11.061 amongst\nothers). This could also boost the IFN activity observed. This is particularly relevant for lines\n295-300 where perhaps the increased activity by proton inhibition is rather just enhancing the\nSTING activity.\nResponse 6:\nThank you for this valuable comment. As you pointed out, lysosomal inhibition may enhance\nIFN production by preventing the negative feedback regulation of STING signaling in IFN-\nproducing cells. We have now cited the paper you suggested and added a discussion\naddressing this possibility.\nChange: Discussion, Lines 495‒498\nAddition:\nOf note, as reported previously, lysosomal proton inhibition in IFN-producing cells by Baf\nA may also block the negative feedback regulation of STING activity through STING\ndegradation (Cell Rep. 2017 Dec 12;21(11):3234-3242.), thereby contributing to the\nenhanced STING response observed by Baf A treatment under PPT1 inhibition.\nAdditional Reference:\nCell Rep. 2017 Dec 12;21(11):3234-3242.\nComment 7:\n-while the use of structural analysis and the identification of 5 conserved structural elements in the\nIFN-inducing CADs is well utilised, conclusions are drawn from in silico predictions only (i.e. Fig\n4) and findings are generalised to these 5 CADs, although often only experimentally proven for\nHCQ. The authors should perform key mechanistic experiments (e.g. IFN blockade with N-(tert-\nButyl)-hydroxylamine) for remaining IFN-inducing CADs.\nResponse 7:\nThank you for your constructive comment. We have examined this point and added new\nexperimental data. N-(tert-Butyl)-hydroxylamine inhibited IFN production by other IFN-\ninducing CADs as well (Extended Fig. 5b). Together with our findings that IFN induction by\nthese CADs is all cGAS-dependent (Fig. 1i), these results further support the shared\nmechanism among IFN-inducing CADs.\nChange: Figure, Extended Data Fig. 5b\nAddition:\nChange: Legend, Extended Fig. 5b\nAddition:\nExtended Data Fig. 5. b. IFNβ concentration in the culture supernatant of GM-BMCs treated\nwith indicated IFNβ inducers in the presence or absence of N-(tert-Butyl) hydroxylamine\n(10 mM) for 16 h.\nChange: Result, Line 313-315\nAddition:\nSimilar inhibitory effects of N-(tert-butyl) hydroxylamine were observed for all IFNβ inducers\n(Extended Data Fig. 5b), suggesting a common involvement of PPT1 inhibition in their IFNβ\nproduction.\nComment 8:\n-while a portion of the manuscript focuses on PPT1 its function as a palmitate hydrolase is\nlargely ignored. The authors should discuss the role of protein palmitoylation in the mechanism\nand discuss the role of potential de-palmitoylation events.\nResponse 8:\nThank you for this helpful comment. We agree that our explanation of the relationship\nbetween inhibition of palmitate hydrolase activity and cell death was insufficient, which may\nhave hindered understanding of the cell death‒inducing mechanism of the IFN-I-\ninducers. We have now added a discussion on this point, as described below.\nChange: Discussion, Line 503-513\nAddition:\nPPT1, the molecular target of IFN inducers, is an intriguing molecule that has also attracted\nattention as a therapeutic target in cancer (Cell Death Discovery 2025; 11:331). PPT1 is a\nlysosome-resident palmitoyl-protein thioesterase that primarily contributes to protein\ndegradation by depalmitoylating lysosomal proteins (Cell Death Discovery 2025; 11:331).\nInhibition of PPT1 activity is known to trigger various forms of cell death through the\naccumulation of undegraded proteins and activation of stress pathways (Cell Death Discovery\n2025; 11:331). In our study, the binding affinity of antiviral CADs to the active pocket of\nPPT1 correlated with their ability to induce type I IFN (Fig. 5h). These findings suggest that\ncell death caused by inhibition of palmitoyl-protein hydrolase activity plays a critical role in\ndriving nucleocytosis. Given that depalmitoylation also regulates protein localization, a role\nfor PPT1 in calreticulin relocalization warrants further investigation.\nAdditional Reference:\nCell Death Discovery (2025) 11:331\nComment 9:\nFigure 1:\n-the authors swap between uM and ug/mL units for HCQ making it difficult to compare data\nacross figures. Please select one notation and be consistent\nResponse 9:\nThank you for pointing this out, and we apologize for the inconsistency in unit notation. We\nhave now standardized all HCQ concentrations to μM throughout the manuscript. Please see\nFig. 1d, and Extended Fig. 1f.\nComment 10:\n-Fig 1a-b: it is already observable that HCQ induced delayed kinetics compared to cGAMP. This\nshould be noted in the text when explaining fig 1.\nResponse 10:\nThank you for this valuable comment. We agree with you. We have added a statement noting\nthe delayed kinetics of HCQ compared to cGAMP in the Results section of Fig. 1.\nChange: Result, Line 124-126\nAddition:\nNotably, HCQ strongly induced Ifnb1 gene expression with a slower time course, reaching a\nlevel similar to that induced by cGAMP, one of the most potent IFN-I inducers acting as a\nligand of STING (Fig. 1a, b, Extended Data Fig. 1a).\nComment 11:\n-Fig 1b: it is not clear what is plotted in Fig 1b (e.g. replicates) and no error bars for variability\nbetween replicates are included\nResponse 11:\nThank you for pointing this out. The original RNA-seq analysis was performed with N=1, and\nconfirmation was conducted by qPCR (Extended Fig. 1a). We apologize for the lack of\ninformation and replicates. To address this issue, we have repeated the experiments with\nbiological triplicates (N=3). Accordingly, Fig. 1a, Fig. 1b, Fig. 1h, Extended Fig. 1a‒c, and\nExtended Fig. 4g have been updated. The previous qPCR confirmation (Extended Fig. 1a)\nhas been removed.\nChange: Figure, Fig.1, Extended Data Fig.1, Extended Fig.3\nBefore: Fig.1\nFig.1a, b. (replaced) Fig.1h (replaced)\nAfter: Fig.1\nFig.1a, b. Fig.1h\nBefore: Ex Fig.1, Ex Fig.3\nBefore: Ex Fig.1, Ex Fig.3\nEx Fig.1a. (deleted) Ex Fig.1c(replaced)\nEx Fig.1b(replaced)\nEx Fig.3f (replaced)\nAfter: Ex Fig.1, Ex Fig.3\nEx Fig.1a.\nEx Fig.1b, c.\nEx Fig.3g\nComment 12:\n-in Extended fig 1b there appears to be a HCQ-specific cluster induced early (i.e. 3h, shown in\npurple). This is very interesting, important to consider and should be mentioned in the text.\nResponse 12:\nThank you for pointing this out. We have mentioned this in theResultssection.\nChange: Result, Line 128-130\nAddition:\nOf note, HCQ specific genes (category 3) are induced in early time course as shown in Ex Fig.\n1a, which may reflect or contribute HCQ-specific stress or cell death process (see below).\nComment 13:\n-Fig 1f,g: It is well known that cGAS-STING is important for maintaining basal IFN tone.\nTherefore, in addition to utilising STING knockout BMDCs (which may exhibit different basal\nactivation) the authors should also confirm that short-term pharmacological STING inhibition (e.g.\nH151) can also block HCQ-induced IFN.\nResponse 13:\nThank you for this valuable suggestion. We have now tested the effect of pharmacological\nSTING inhibition using H151 and confirmed that HCQ-induced IFN production is inhibited.\nThe result has been added to Extended Fig. 1h, and this finding is mentioned in the Results\nsection.\nChange: Figure, Extended Fig. 1h\nAddition:\nChange: Legend, Extended Fig. 1\nAddition:\nExtended Data Fig. 1h. IFN concentration in the culture supernatant of WT GM-BMCs\ntreated with HCQ (100 uM) for 16 h in the presence or absence of H-151 (3 µM).\nChange: Result, line 146-147\nAddition:\nThe contribution of STING was further supported by inhibition with H-151 (Extended Data\nFig. 1h).\nComment 14:\nFigure 2:\n-the authors should also provide references for the LCI-S approach on line 166 (not only in the\nmethods)\nResponse 14:\nThank you for pointing this out. We have added the reference for the LCI-S approach at line\n174 (corresponding to line 166 before revision).\nComment 15:\n-please also show the corresponding brightfield image for all LCI-S figures (e.g. Fig 2a-c) as this\nhelps to orient the reader and IFN spots and sytox accumulation is related to the cell density and\ntotal number of cells in the FOV\nResponse 15:\nThank you for this helpful comment. We have added the corresponding brightfield images to\nFig. 2a‒c. In addition, brightfield images have also been included in Extended Data Fig. 2a.\nExplanations are provided in each figure legend.\nChange: Figure, Fig. 2a‒c, Extended Data Fig. 2a.\nAddition: (Please see the revised figure for details; the following is a summary.)\nFig. 2a‒c,\nExtended Data Fig. 2a.\nComment 16:\n-the authors only quantify the number of IFN spots. In addition, it may be worthwhile to also\nquantify and plot the intensity and also area of IFN spots for HCQ vs cGAMP.\nResponse 16:\nThank you for this thoughtful suggestion. We agree that quantification of the area and\nintensity of IFN spots would be informative when conditions allow for a direct comparison\nbetween HCQ and cGAMP stimulation. However, as shown in Fig. 2a‒c, the secretion\npatterns differ markedly between these two conditions. In HCQ-treated cells, strong adhesion\nto the plate surface is observed, and the secretory signal is often not captured at the cell‒plate\ninterface. This morphological context has been mentioned in the text (line 183). Under such\nconditions, the intensity of IFN signals can appear lower for adherent cells compared with\nless adherent ones. Furthermore, imaging suggests that cells stimulated with HCQ may\nrelease IFN laterally or upward from the plate surface, allowing more rapid diffusion into the\nculture medium. In contrast, cGAMP stimulation likely induces IFN release in multiple\ndirections, including toward the culture plate, enabling more efficient capture near the plate\nsurface. The observation of stronger central signals in cGAMP-stimulated cells supports this\ninterpretation (Fig. 2c).\nBecause of these morphological differences, quantification of spot area or intensity\nwould not accurately reflect the actual secretion behavior. Therefore, we considered the\nnumber of IFN spots, which is independent of cell adhesion, to be the most reliable and\nrepresentative parameter under these conditions. We believe that quantitative analyses from\nother assays sufficiently support our conclusions, and we hope this rationale is acceptable.\nComment 17:\n-fig 2i: the gating/arrow is confusing here as it looks like only the sytox + cells are gated in the\npanel below (however I believe this is not the case). It is also not exactly clear how the sytox\npositive gates were chosen, especially as the cells look rather different for untreated vs HCQ\n(e.g. in terms of FSC). Please also show the unstained populations in the extended figures (to show\nwhere sytox positive cells are positioned within the plot ‒ relevant for Fig 2 I and j. (The labelling\nof gates in Fig 2j is also confusing)\nResponse 17:\nThank you for your valuable comment and for pointing out the confusion caused by the gating\nand arrows. We apologize for this oversight. We have removed the incorrect arrows.\nSpecifically, the upper panel of Fig. 3a shows gating of the entire cell population into SYTOX-\npositive and SYTOX-negative cells, whereas the lower panel displays the distribution of the\nwhole population based on FSC-W and FSC-A parameters. The SYTOX-positive gate was\ndetermined by identifying the cell population shifted upwards upon HCQ treatment. The\nunstained populations are also included in the upper panel of the figure to clarify the position\nof SYTOX-positive cells within the plot.\nFig. 3b is a further analysis of multiplets from Fig. 3aʼs lower plot using FSC-W and FSC-A to\nhelp distinguish singlets from aggregates. We apologize for the earlier confusing and incorrect\nfigure and have now revised the figure and its legend to improve clarity and avoid\nmisinterpretation.\nChange: Figure, Fig. 2\nBefore: Fig. 2i, j (Correction)\nAfter: Fig. 3a, b.\nComment 18:\n-line 188-190 ‒ it is not clear to me how expression of mitochondrial genes is confirming cell\ninjury/death. The altered genes and\nResponse 18:\nThank you for your comment. It is well known in single-cell RNA sequencing studies that an\nincreased level of mitochondrial genes often reflects cell injury or death. This occurs because\ndamaged or dying cells lose nuclear DNA, leading to a relative increase in mitochondrial gene\nreads. Detection of mitochondrial RNA or DNA is commonly used as a marker to identify\ndead or damaged cells. We have now cited relevant references in the text to clarify this point.\nAdditional Reference: Line 201\nGenome Biology (2016) volume 17, Article number: 29\nComment 19:\nFigure 3:\n-it appears that after HCQ treatment cells shrink in size, but also display a larger nucleus (Fid\n3d, also observed as reduction in FSC while HCQ treatment in Fig 2i). The authors propose that\ncalreticulin translocates from the cytosol to the nucleus. However, from the images it could be\npossible that rather there are considerable changes in cell morphology including the break down\nof the nuclear membrane, leading to leakage of DNA content into the cell cytosol, a portion of\nwhich is phagocytosed by recipient cells. To confirm this the authors should further stain for\nadditional ER and organelle markers and/or the nuclear membrane (e.g. Lamin B1) to confirm\nthe integrity of the nucleus. Furthermore, the authors could quantify the cellular size, we well as\nthe size of the nucleus (both for all and sytox positive cells).\nResponse 19:\nThank you very much for your detailed and insightful comments. We agree that HCQ\ntreatment induces morphological changes including cell shrinkage and death, with more than\nhalf of the cells dying after 16 hours (Fig. 2i; LDH assay). Therefore, some cells may exhibit\ncompromised nuclear integrity due to shrinkage, making it difficult to assess the nucleus solely\nby immunostaining in 16 hours. In addition, 16 hours is long after the peak IFN induction\n(Fig. 2d; LCI-S). Therefore, showing immunostaining results at 16 hours after HCQ\ntreatment might is misleading, and we apologize for this.\nTo better clarify calreticulin nuclear translocation, we performed nuclear western\nblotting, which confirmed calreticulin presence in the nucleus 6 hours after HCQ treatment.\nWe have added these results to Extended Fig. 4f and removed the 16-hour immunostaining\ndata from Fig. 4d-g, Extended Figs. 4d, 4e, Fig. 6c, and Extended Fig. 6c. We also mentioned\nthe possible effect of morphological changes on these findings in the Results section.\nRegarding nuclear accessibility, please also refer to Fig. 3d-h, where multiple lines\nof evidence demonstrate that the nuclear signal is clearly distinguishable from the cytoplasm\nand accessible to recipient cells even when nuclear structure remains intact. These results are\nconsistent with the nuclear fractionation data and support the concept that nuclear access\noccurs without complete nuclear membrane breakdown.\nChange: Figure, Fig. 4, Ex Fig. 4, Fig.6, Ex Fig.6\nBefore:\nFig. 3 (Correction)\nExtended Fig. 3 (Correction)\nFig. 5(Correction) Extended Fig. 5(Correction)\nAfter:\nFig. 4\nExtended Data Fig. 4\nFig.6 Extended Data Fig.6\nAddition: Extended Fig. 4f\nChange: Result, Line 265-267\nAddition:\nTo exclude the possibility that this observation was due to HCQ-induced morphological\nchanges, we performed nuclear western blotting and confirmed calreticulin nuclear\ntranslocation (Extended Data Fig. 4f).\nComment 20:\nIn addition, could it be that the increase in MFI of calreticulin (particular in dead cells prone to\nincreased autofluorescence) is due to cell shrinkage and concentration of fluorescent signal. The\nauthors should perform a western blot to verify the increased calreticulin expression (referred to\non line 235-236).\nResponse 20:\nWe agree that cell shrinkage can occur during cell death by HCQ; however, our current data\ndo not support the idea that shrinkage itself enhances the fluorescent signal of calreticulin.\nComparing populations P3 and P4 in Fig. 4h across HCQ-treated and Baf A-treated\nconditions, we do not observe a shift of the entire dead cell population toward calreticulin\npositivity. Moreover, calreticulin signals increase even in the live cell population P1 under\nboth HCQ treatment and Baf A treatment. These observations make it unlikely that the\nincrease in calreticulin signal is solely due to morphological changes caused by cell death.\nOn the other hand, we also agree that verification by Western blot (WB) analysis of\nactual protein levels, as you suggested, is important. We evaluated protein levels by nuclear\nWB, and interestingly, no significant increase in calreticulin protein was detected (Extended\nData Fig. 4f). Although these results may appear contradictory at first glance, discrepancies\nbetween WB̶which analyzes denatured proteins from lysed cells̶and flow cytometry or\nimmunostaining̶which analyze proteins with more preserved cellular and structural\nconformations̶have been documented previously (Cell Death and Differentiation (1998) 5,\n678‒686; Mediators of Inflammation 2017, Article ID 9096829, 14 pages). Based on this\nunderstanding, we speculate that changes in calreticulin structure or localization after HCQ\ntreatment may alter epitope exposure.\nConsidering both the FACS and WB results, it is plausible that HCQ induces\nstructural or localization changes in calreticulin rather than a simple increase in total protein\nlevels. This interpretation aligns with observed nuclear translocation of calreticulin in\npopulations P1 and P2 showing altered fluorescence intensity after HCQ treatment (Fig. 4j,\nk). Immunostaining also reveals calreticulin granules distributed throughout the cell (Fig. 4d),\nfurther suggesting notable alterations in intracellular localization regulated by complex\nmechanisms possibly induced by HCQ.\nIn any case, it is clear that simple accumulation of calreticulin protein does not occur.\nWe have revised the Results, Discussion, and related sections accordingly based on this\nunderstanding. Your insightful comments helped deepen our interpretation, for which we are\nvery grateful.\nChange: Result, Line 269-281\nBefore:\nTo further examine the nuclear translocation of calreticulin, we performed imaging cytometry.\nCalreticulin expression was enhanced by HCQ treatment, and calreticulin levels were\nparticularly high in dead cells (Fig. 3h, i). We further examined the correlation between the\nnucleus and calreticulin and found that it was significantly stronger in the population with\nhigh levels of calreticulin than in those with low levels (Fig. 3j, k). Of note, Baf A treatment\nalso enhanced the expression of calreticulin, particularly in live cells (Fig. 3h, i). As calreticulin\ngene expression was not induced by HCQ (Extended Data Fig. 3f), these results suggest that\nlysosomal inhibition resulted in the blockade of calreticulin degradation.\nAfter:\nInterestingly, although nuclear western blotting (Extended Data Fig. 4f) showed no marked\nchanges in calreticulin protein levels after HCQ treatment, intracellular staining revealed\nincreased signals, particularly in dead cells (Fig. 4h,i). Calreticulin gene expression was also\nexamined, but no increase was observed with HCQ (Extended Data Fig. 4g). These findings\nindicate that HCQ induces structural or localization changes in calreticulin that affect its\nantibody reactivity or accessibility. We further assessed the relationship between calreticulin\nand the nucleus, and found that the correlation was significantly stronger in cells with high\ncalreticulin signals than in those with low levels (Fig. 4j, k). Of note, Baf A treatment also\nenhanced calreticulin signals, particularly in live cells (Fig. 4h, i). Taken together, these results\nsuggest that lysosomal inhibition induces some changes in the structure or localization of\ncalreticulin, and that a fraction of the protein translocates into the nucleus.\nChange: Discussion, Line 514-519\nAddition:\nIn addition to lysosomal PPT1 inhibition, our results suggest the importance of calreticulin\nrelocalization induced by lysosomal proton inhibition in nucleocytosis (Fig. 5f‒l). As shown\nin Fig. 4h and Extended Data Fig. 4f, calreticulin protein levels remained unchanged, yet\nFACS analysis detected increased signals. This finding suggests the possibility of structural\nchanges in calreticulin, which is future interesting issue to be clarify.\nAdditional Reference:\nCell Death and Differentiation (1998) 5, 678 ± 686\nMediators of Inflammation Volume 2017, Article ID 9096829, 14 pages\nIn relation to this, we have also appropriately revised the description concerning changes\nin calreticulin protein levels.\nChange: Result, Line 302-303\nBefore:\nalthough Baf A increased the protein level of calreticulin in living cells (Fig. 3h).\nAfter:\nalthough Baf A induces similar change of calreticulin signal as HCQ in living cells (Fig. 4h).\nComment 21:\n-staining of calreticulin is only performed on permeabilised cells. It would also be of interest to\nassess surface expression of calreticulin via flow cytometry (without cellular permeabilisation) as\nmembrane calreticulin is a known eat me signal for apoptotic cells. Nuclear calreticulin in the\nabsence of cell surface would further support a novel transfer of DNA to surrounding BMDCs.\nResponse 21:\nThank you for your insightful comment. We agree that this is an interesting aspect to consider.\nUpon reviewing the literature, we found examples where calreticulin surface staining is\nperformed after permeabilization (e.g., Communications Biology 7, Article number: 1234\n(2024), Fig. 7a). Even with permeabilization methods, calreticulin completely relocates to the\nplasma membrane and is no longer detected in the cytoplasm. In contrast, our\nimmunostaining results differ substantially from these reports. Calreticulin remains\nintracellular, and no accumulation at the plasma membrane is observed (Fig. 4d). This finding\naligns with our observation that not all dead cells are phagocytosed during nucleocytosis.\nBased on these points, we have added relevant references and included an appropriate\ndiscussion in the revised manuscript section.\nChange: Discussion, Line 519-527\nAddition:\nThe localization pattern of calreticulin is also of particular interest. In cancer cells, calreticulin\nis known to relocalize to the cell surface upon treatment with certain chemotherapeutic agents,\nshowing a striking redistribution from the intracellular compartment to the plasma membrane\n(Ref; Communications Biology 7, 1234 (2024)). In contrast, in our case, calreticulin was\ndispersed throughout the cytoplasm, with granule formation and partial nuclear translocation\nobserved, indicating a clearly distinct intracellular dynamics (Fig. 4d). This observation is also\nconsistent with the fact that entire dead cells were not phagocytosed. As noted above, why\ncalreticulin exhibits such intracellular localization remains to be elucidated.\nAdditional Reference:\nCommunications Biology 7, Article number: 1234 (2024)\nComment 22:\n-line 261/262: please define and introduce the function of PPT1 and MRGPA3\nResponse 22:\nThank you for your comment. We have added explanations for PPT1 and MRGPRA3 as\nrequested.\nChange: Result, Line 305-309\nAddition: (blue literature)\nAs HCQ is known as a direct inhibitor of Palmitoyl-protein thioesterase 1 (PPT1)35, a\nlysosomal depalmitoylating enzyme, and CQ is a direct agonist of Mas-related G protein-\ncoupled receptor A3 (MRGPA3)36, a sensory neuron-specific receptor implicated in itch\nsensation, we examined the involvement of PPT1 and MrgpA3 in IFN production.\nComment 22:\n-fig 3m,n: the authors show that Rho/ROCK kinase inhibition reduces HCQ IFN production\nwithout affecting cytotoxicity. The authors must therefore confirm whether Rho/ROCK kinase\ninhibition affects direct cGAS-STING mediated IFN (i.e. via cGAMP) or whether this inhibition\nis upstream/involved in DNA uptake. Furthermore, the authors should show whether\nRho/ROCK kinase inhibition prevents DNA uptake via affecting interaction between damaged\ncells and IFN-inducing cells via either LCI-S or imaging flow cytometry, and further assess the\nimpact on localisation of calreticulin (as proposed).\nResponse 22:\nThank you for your valuable comments. We investigated the effect on cGAMP and confirmed\nthat Rho kinase inhibitors do not suppress cGAMP-induced IFN production. However,\nregarding ROCK inhibitors, we observed a weak inhibitory effect on cGAMP-induced IFN,\nand we judged that further detailed studies would be required to clarify ROCKʼs involvement.\nTherefore, we have removed the data and descriptions related to ROCK inhibition. For Rho\ninhibition, we confirmed its suppressive effect using LCI-S and also verified that it does not\naffect calreticulin nuclear translocation by HCQ treatment. These results provide stronger\nsupport for the importance of cellular protrusions.\nTogether, these analyses reinforced the critical role of Rho signaling in the extension\nof protrusions involved in calreticulin dynamics. These findings, along with results from\ncytoskeleton inhibitors, strongly suggest the importance of protrusions. We appreciate your\ninsightful suggestions, which helped us obtain more robust conclusions.\nData for reviewer#1\nEffect of ROCK inhibitor on cGAMP induced IFN production in GM-BMCs.\nIFN\nproduction was examined 16 h after cGAMP stimulation (5 ug/ml) in the presence or absence\nof ROCK inhibitor. IFN production by cGAMP was decreased by ROCK inhibitor.\nChange: Figure, Fig. 4, Extended Data Fig. 4\nBefore: Fig.4\nAfter: Fig.4 (replacement and addition)\nAddition: Extended Fig.4\nChange: Legend, Fig. 4. Extended Data Fig. 4\nAddition:\nFig. 4. Nucleocytosis and nuclear translocation of calreticulin\nn. LCI-S of GM-BMCs treated with HCQ (100 µM) in the presence or absence of Fasudil\n(100 µM). Representative image of endpoint (12 h) is shown in left. Quantitative analysis of\nthree independent experiments are shown in the right with the number of IFN spots detected.\nExtended Data Fig. 4. HCQ-induced cell death and nucleocytosis.\n(h) Calreticulin (green) and DNA (blue) staining. (i) Intensity at the site of white lines. The\nX-axis indicates the distance from the left edge of the white lines. (j) Statistical analysis of\nnuclear calreticulin intensity in each cell. Data are presented as means ± s.e.m. (-; 67, HCQ;\n108, HCQ + Fasudil; 75) k. Concentration of IFNβ in the culture supernatant of GM-BMCs\ntreated with cGAMP (5 µg/ml) in the presence of the indicated concentrations of inhibitors.\nChange: Result, Line 289-298\nBefore:\nTo further explore the importance of calreticulin in nucleocytosis, we investigated the\ninvolvement of Rho/ROCK kinases, which play a critical role in calreticulin-induced dendrite\nextension28-31. The inhibition of these kinases resulted in the inhibition of IFNβ production\nwithout inhibiting cell death (Fig. 3m, n). These results suggest the possible involvement of\nnuclear calreticulin in HCQ-mediated IFNβ production.\nAfter:\nTo further explore the importance of calreticulin in nucleocytosis, we investigated the\ninvolvement of Rho kinase, which play a critical role in calreticulin-induced dendrite\nextension31-34. The inhibition of Rho kinase resulted in the inhibition of IFNβ production\nwithout inhibiting cell death (Fig. 4m). This inhibition was further confirmed by LCI-S (Fig.\n4n). Interestingly, however, the Rho kinase inhibitor did not block calreticulin nuclear\ntranslocation by HCQ or IFN production induced by cGAMP (Extended Data Fig. 4g-j).\nThese results suggest that Rho kinase functions after calreticulin nuclear translocation but\nbefore cGAS-STING activation during nucleocytosis. Taken together with previous reports31-\n34, our findings support a possible involvement of Rho kinase in dendrite extension toward\ncalreticulin during nucleocytosis.\nComment 24:\nFig 4:\n-the authors show that combination of DC661 (PPT1 inhibition) and Bafilomycin A (proton\ninhibition) recapitulates the IFN response, proposedly similarly to HCQ/CADs. The authors\nshould confirm via LCI-S and/or imaging flow cytometry that a similar cell-cell transfer of DNA\noccurs.\nResponse 24:\nThank you for your valuable comment. We have added LCI-S analysis to further investigate\nthis point and included the results in the manuscript. We confirmed interactions with dead\ncells and detected cytoplasmic DNA before IFN secretion, showing a trend similar to HCQ\ntreatment. These results have been added to Fig. 5l and Extended Fig. 5e.\nChange: Figure, Fig. 5, Extended Data Fig. 5\nAddition: Fig. 5I\nAddition: Extended Data Fig. 5e\nChange: Legend, Fig. 5, Extended Data Fig. 5\nAddition:\nFig. 5. l. LCI-S of GM-BMCs treated with DC661 (3 µM) in combination with Baf A (15 nM).\nIFNsecretion (blue) and DNA staining (magenta) are shown. DNA intensity is summarised\nin the lower right.\nExtended Data Fig. 5. e. LCI-S of GM-BMCs treated with DC661 (3 µM) in combination\nwith Baf A (15 nM). IFNβ secretion (blue) and DNA staining (magenta) are shown in left\ntwo panels. Emphasised DNA images are shown in the right two panels (DNA; green). Lower\npanel: Intensities of DNA were calculated between the indicated sites.\nChange: Result, Line 344-348\nBefore:\nThese results suggest that PPT1 inhibition can trigger IFNβ production, but proton\ninhibition is required for a robust response (Fig. 4a, j).\nAfter:\nCell-dying cell interactions, DNA signal in IFNβ-producing cells, and IFNβ secretion were\nobserved by LCI-S following DC661 and Baf A treatment (Fig. 5l, Extended Data Fig. 5i, 5e).\nThese results suggest that PPT1 inhibition can trigger IFNβ production, but proton\ninhibition is required for a robust response via nucleocytosis (Fig. 5a, k, l).\nComment 24:\nFig 5:\n-line 331-332: the cell type specific effect does not necessarily mean a local effect. The specificity\nmay be due to the phagocytic potential of the cells, the expressed receptors etc. This should be\namended in the text.\nResponse 24:\nThank you for your valuable comment. We have carefully considered this point and revised\nthe manuscript accordingly.\nIn relation to this, we also apologize for the previously insufficient description of this\ndata. We have appropriately revised the text concerning local effects. In addition, we\nincorporated analyses of cell type-specific gene expression patterns and STING expression\nstatus, substantially revising the text accordingly. As a result, we found that IFN responses are\nparticularly strong in macrophages of the MoMF subtype that express STING. For further\ndetails on this point, please refer to our response to referee #2.\nBased on these points, we have substantially revised this section. These new analyses\nand findings have been fully described in the revised manuscript. We sincerely appreciate your\ninsightful suggestion, which has helped improve our study.\nChange: Result, Line 378-398\nBefore:\nWe observed increased expression of IFN-inducible genes in lung cells from HCQ-treated\nmice, all of which were induced in a STING-dependent manner, confirming the potential of\nHCQ to induce an IFN-I response in vivo (Fig. 5f, g). Notably, systemic production of IFNβ\nwas not observed, indicating a local effect of HCQ (Extended Data Fig. 5c). Moreover, the\nmagnitude of STING-dependent IFN-I response by HCQ was cell type-specific (Fig. 5f and\nExtended Data Fig. 5d), indicating local IFN-I response. In conclusion, these results show the\nphysiological relevance of lysosomal dysfunction induced by HCQ in activating a local IFN-I\nresponse in vivo.\nAfter:\nAt first, we classified the cell types detected in the scRNA-seq analysis and found that the\nSting1 gene was expressed in macrophage subsets, including monocyte-derived macrophages\n(MoMFs) and alveolar macrophages (AMFs) (Fig. 6d, e). Interestingly, when we analyzed the\ngene expression patterns across the detected cell types, the IFN-I response emerged as one of\nthe most prominent subsets among both the total gene set and the STING-dependent genes\n(Fig. 6f). Importantly, IFN-I-related genes were expressed in a STING-dependent manner in\nmultiple cell types, particularly MoMFs, epithelial cells, and neutrophils, and IFN-stimulated\ngene signatures were also induced in these cells (Fig. 6g). These results indicate that HCQ\ntriggers a STING-dependent IFN-I response in the lung. Based on the pattern of Sting1\nexpression, these findings suggest that MoMFs initiate STING-dependent IFN-I responses,\nwhich in turn activate the expression of secondary IFN-stimulated genes in other cell types\n(Fig. 6e‒g; Extended Data Fig. 6e, f). This is consistent with our in vitro observations of\nnucleocytosis by macrophages within GM-BMCs (Fig. 2f, g), indicating that MoMFs are\ncandidate inducers of nucleocytosis in vivo. Notably, systemic production of IFNβ was not\nobserved (Extended Data Fig. 5c), indicating a local effect of HCQ in the lung. Considering\nthe different magnitudes of the STING-dependent IFN-I responses across cell types (Fig. 6f,\ng; Extended Data Fig. 6e), such cell type-dependent responses may underlie the localized\nIFN-I response in the lung. In conclusion, these results demonstrate the physiological\nrelevance of HCQ in inducing a STING-dependent local IFN-I response in vivo.\nReviewer #2 (Innate/DC immunity, CAD) (Remarks to the Author):\nComment 1:\nThe article by Negishi et al. entitled \"Phased lysosomal malfunction triggers nucleocytosis to the\ncGAS-IFN-I axis\" is interesting and well written, but some data have to be added/modified to be\nmore convincing (only few cells observed, correlation of calreculin staining but no demonstration,\nor n=3 biological replicates, etc….).\nIndeed, in this article, the authors have demonstrated with the help of 5 figures that:\n1. IFN-beta is induced in vitro by antivirals cationic amphiphilic drugs (CADs) such as\nhydroxychloroquine (HCQ) on mouse BM-DCs and that this production is coming from a limited\nnumber of cells.\n2. This process involves cell death-related events (no pathway identified) and the STING pathway\n(using cGAS and STING Ko BM-DCs).\n3. DNA can be transfer from one DC (or tumor cells) to BM-DC by videomicroscopy\n(nucleocytosis)\n4. Rho/ROCK kinases are involved in the IFN-b production through calreticulin engagement\nResponse 1:\nWe sincerely thank Referee 2 for the positive evaluation of our study. We have addressed all\nthe points you raised. In response to your suggestions, we conducted additional experiments\nand revised the manuscript text accordingly. Our detailed, point-by-point responses are\nprovided below. All additions and revisions are indicated in blue in the response document.\nPlease kindly review our responses.\nComment 2:\nFor Fig 1.\n-As DCs can mature spontaneously, removal and activation with PBS 12h as a real negative\ncontrol has to be done.\nResponse 2:\nThank you for your valuable comment. We apologize for the insufficient explanation. After\ndifferentiation, GMDCs are washed to remove the GM-CSF-containing medium and then\ncultured in medium without GM-CSF. In Fig. 1, the negative control refers to cells treated\nwith medium alone as a comparison to HCQ and cGAMP treatment in the same medium.\nUnder this condition, no IFN production is detected (e.g., Fig. 1c). In response to your\nsuggestion, we performed RNA-seq analysis using medium treatment for 3, 6, or 12 hours as\na negative control. We clearly identified gene sets that remain unchanged under medium\ntreatment but change significantly after HCQ treatment. These results are shown in Extended\nFig. 1a.\nChange: Figure, Extended Fig. 1a.\nAddition:\nComment 3:\n-Gene enrichement analysis has also to be done using for example The Molecular Signatures\nDatabase (MSigDB) in order to better characterize pathways activated by CAD.\nResponse 3:\nThank you for your valuable comment. We agree that pathway analysis is an interesting aspect.\nWe analyzed the trends of genes induced by HCQ and presented the results in Extended Fig.\n1a and 1c (Please refer to our previous response regarding Extended Data Fig. 1a). We\nperformed two types of analyses: one combining cGAMP data and HCQ data, and another\nanalyzing HCQ data alone. As expected, we found interesting and consistent results,\nincluding hits in cytosolic DNA sensing pathways. We have described these findings in the\nResults section accordingly.\nChange: Figure, Extended Data Fig. 1c\nChange: Result, Line 126-128\nBefore:\nFurthermore, HCQ induced the expression of IFN-inducible genes and various genes\nrelated to the immune response (Fig. 1a, b, Extended Data Fig. 1a).\nAfter:\nConsistently, HCQ induced the expression of IFN-inducible genes and various genes\nrelated toPRR pathways and viruses(Fig. 1a, b, Extended Data Fig. 1a-c).\nComment 4:\n-All the data in figure 1 represent n=3 donors which is not enough to perform a t-test.\nResponse 4:\nThank you very much for your valuable comment. We apologize for the inappropriate\nstatistical approach, the insufficient explanation, and any confusion caused by our initial\ndescription. For each ELISA assay, we confirmed reproducibility in three or more independent\nexperimental replicates and present representative data with N = 3 replicates. Here, N = 3\nrefers to three independently cultured 3 replicates after stimulation. Although GM-BMCs\nwere derived from the bone marrow of one mouse, N = 3 dose not means the technical\nreplicates of ELISA measurement itself. We sincerely apologize again for the lack of sufficient\ninformation. We have now corrected all ELISA figure legends accordingly. ʻData are expressed\nas the mean ±s.d. of N = 3 replicates of each in vitro culture condition in one representative\nexperiment (each experiment was repeated three times)ʼ. While this practice may depend on\nthe experimental system, to the best of our knowledge, such representation is widely accepted\nand examples can be found in journals from the Nature group and others (eLife\n2020;9:e53627., Nat. Commun. | (2025) 16:4640 Fig.3e, nature chemical biology\nhttps://doi.org/10.1038/s41589-025-02031-x, Ex. Data Fig. 1, Nat. Commun. | (2025)\n16:3346, Fig. 3, etc.).\nThe cited references and other previous reports indicate that, in many cases, t-tests\nwith N=3 are accepted, even though statistical reliability may be low̶indicating the need for\nrigorous, case-by-case validation. Accordingly, we have addressed this point in our ELISA\nassay. To further ensure the validity of our approach, we have conducted additional\nexperiments and analyses. The statistical concerns you raised primarily relate to experiments\nusing cultured cells from wild-type and gene knockout mice (STING, cGAS, TBK1/TNF).\nThese involve comparisons of cells derived from different individual animals. We agree that\nindividual variability, including cell number, microenvironment, and population differences,\ncan impact IFN responses, as you pointed out regarding plasmacytoid dendritic cells (pDCs).\nHowever, in our study, the cultured and differentiated cells were normalized for cell number\nafter isolation and cultured under identical conditions for several days. Therefore, it is unclear\nhow directly individual variability affects our results. Moreover, such effects likely depend on\nexperimental design and analysis outputs, requiring case-by-case assessment.\nImportantly, the IFNproduction results shown in Fig. 1 exhibit an all-or-none effect between\nwild-type and gene-deficient (STING, cGAS, TBK1/TNF knockout) cells at both protein and\nRNA expression levels. None of these knockout cells showed an IFNβ response to HCQ\ntreatment. This suggests that large sample sizes may not be necessary in our experimental\nsystem to evaluate HCQ-induced type I IFN responses.\nFurthermore, to demonstrate the lack of variability in the responses of knockout\n(KO) cells, we pooled results from several independent experiments using cells deficient in\nSTING, cGAS, and TBK1/TNF. Since these were independent experiments, the data include\nnot only biological variability among individual animals but also experimental variability\nacross different runs and other factors. Nonetheless, the IFN production levels in STING,\ncGAS, and TBK1/TNF knockout cells consistently exhibit an all-or-none pattern compared\nto wild-type cells. Additionally, we have included RNA-seq results from STING knockout\nmice (biological N=3), which also show an all-or-none dependency of Ifnb1 expression on\nSTING at the RNA level\nTaken together, these results support the validity of our experimental design for the\nELISA assay using N=3 replicates of each in vitro culture condition with at least three\nindependent repeats. Meanwhile, we agree that a t-test with N=3 replicates may have limited\nstatistical power when comparing WT and KO groups, although both technical and biological\nN =3 are commonly accepted for the analysis of cytokines (ELISA or qRT-PCR), even in\nrecent studies (eLife 2020;9:e53627., Nat. Commun. | (2025) 16:4640 Fig.3e, nature\nchemical biology https://doi.org/10.1038/s41589-025-02031-x, Ex. Data Fig. 1, Nat.\nCommun. | (2025) 16:3346, Fig. 3, etc.). Therefore, we have removed the statistical analysis\nand now present the blot data directly in the results of ELISA assay. We have also added the\nsummarized data from multiple experiments in Extended Fig. 1 and accurately clarified\nreplicate definitions in the figure legends of all ELISA assays.\nWe believe these responses adequately address your concerns and improve\nunderstanding of our data. Thank you for your helpful comments and consideration.\nChange: Figure, Fig. 1, Extended Data Fig. 1\nBefore: Fig. 1\nAfter: Fig. 1\nAddition: Extended Data Fig. 1\nChange: Legend, Fig. 1\nBefore:\nData in c, e-g, and i represent n = 3 biological replicates plotted as the mean ± s.d. Statistical\nanalysis was performed using Studentʼs t-test. *p < 0.05, **p < 0.01, ***p < 0.001.\nAfter:\nData in c, e-g, and i are expressed as the mean ±s.d. of n = 3 replicates of each in vitro culture\ncondition in one representative experiment (each experiment was repeated three times).\nChange: Legend, Extended Data Fig. 1\nAddition:\nExtended Data Fig. 1. g. IFNβ concentration in the culture supernatant of control or gene-\ndeficient GM-BMCs treated with the 80 uM of HCQ for 16 h. Data is the pool of independent\nexperiments (Tnf-/-/Tbk1-/-; N = 4, Sting1-/-; N = 5, Cgas-/-; N = 4).\nChange: Legend, Similar correction\nFig. 3c, 4h, 4i, 4k, 4m, 5a, 5b, 5k, 6b, Ex Data Fig. 1h, 1i, 1j, 2d, 4k, 5a, 5b, 5d, 5f, 5g, 5h, 5j,\n6a\nRelated response:\nIn relation to the concern about insufficient replicates, we performed additional experiments\nto include new biological replicates in Extended Figure 5c. The results confirmed our original\nconclusions, and no changes were made to the data interpretation or overall findings.\nFurthermore, regarding Extended Figure 6, which was presented as supplementary\ninformation in the Discussion, the number of replicates was limited. We have now cited\npreviously published studies that conducted more appropriate analyses on similar topics, and\nthe Discussion has been revised accordingly as shown below.\nAdditional Reference:\nJ Pharmacol Exp Ther 365:447‒459, June 2018\nPharm Res (2022) 39:57‒73\nBr. J. clin. Pharmac. (1988), 26, 303-313\nChange: Discussion, Line 472-474\nBefore:\nNotably, the intracellular accumulation of HCQ is known to be associated with its\nefficacy15,16,19,39. We also confirmed accumulation in BMDCs and predicted that intracellular\nconcentrations increased approximately 100-fold (Extended Data Fig. 6a). Contrarily, HCQ\nin vivo blood levels rapidly decreased within 24 hours(Extended Data Fig. 6b, c),\nconsistent\nwith HCQ accumulation. Based on these results, we speculate that HCQ dosage control in\nthe local area is challenging, which may be another reason why HCQ did not demonstrate a\nclinical therapeutic effect against SARS-CoV-2\nAfter:\nNotably, the intracellular accumulation of HCQ is known to be associated with its\nefficacy15,16,19,39. Previous studies have reported that in vivo blood levels of HCQ decrease\nrapidly within 24 hours, consistent with its intracellular accumulation (Br. J. Clin. Pharmacol.\n1988;26:303‒313; J. Pharmacol. Exp. Ther. 2018;365:447‒459; Pharm. Res. 2022;39:57‒73).\nBased on these reports,we speculate that HCQ dosage control in the local area is challenging,\nwhich may be another reason why HCQ did not demonstrate a clinical therapeutic effect\nagainst SARS-CoV-2\nChange: Figure, method, legend, related to Extended Data Fig. 6\nDeletion:\nComment 5:\nFig2.\n-The limited number of cells producing type I IFN is a known phenomenon in many cells\n(observed by intracellular FACS staining) and more precisely on pDC which are specialized for\nthis function. It is also well known that the level of IFN type I secretion is very different between\ndonors, itʼs why the use of only n=3 donors here is not enough to conclude. Statistical analysis is\nnot appropriate for example for Fig 2k as a two way ANOVA couldnʼt be done with n=3\nbiological replicate.\nResponse 5:\nWe sincerely apologize for both the inappropriate use of statistical analysis and insufficient\ninformation, similar to the issue pointed out for Fig. 1. The ELISA assays were conducted\nwith n = 3 replicates for each in vitro culture condition across at least three independent\nexperiments, all of which produced consistent results. A representative dataset is shown in the\nfigure. As described above, we consider this analytical method to be reliable. Following the\nsame correction as for Fig. 1, we have removed the statistical analysis and now present the\nblot data directly.\nChange: Figure, Figure: 3c\nBefore:\nAfter:\nComment 6:\n-Line 206, authors have to be more cautious and used « support the notion that maybe … »\nResponse 6:\nThank you for pointing this out. We have revised the sentence accordingly, as shown below.\nChange: Result, Line 218-219\nBefore:\nThese results support the notion that dsDNA transfer occurs from dying cells to living cells\nduring HCQ-induced IFNβ production.\nAfter:\nThese results suggest the possibility that dsDNA transfer may occur from dying cells to living\ncells during HCQ-induced IFNβ production.\nComment 7:\n-in Fig 2j, author may include the % of sytotox green postive cells in non-multiplet cells.\nResponse 7:\nThank you for the comment. We have added the percentage of SYTOX Green‒positive cells\nin non-multiplet cells to Extended Fig. 3a. The following description has been included.\nChange: Figure, Extended Fig. 3a\nAddition:\nChange: Result, Line 214-215\nBefore:\nNotably, HCQ treatment significantly increased the number of SYTOX green-positive\nmultiplets, which included both live cells and dying cells (Fig. 2i, j).\nAfter:\nNotably, HCQ treatment significantly increased the number of SYTOX green-positive cells,\nnot only singlet but also multiplets that included both live cells and dying cells (Fig. 3a, b,\nExtended Data Fig. 3a).\nComment 8:\n-scRNAseq performed on treated DC is not very informative because only few genes are shown.\nIt seems like one or two clusters of cells respond to HCQ. DEG analysis have to be done to\nfurther characterize DCs responding to HCQ. Indeed, a specific cell subsets (or cell state)\nproducing IFN-b in BM-DC is thus not identified.\nDo this HCQ activation is conserved with other DC subsets ? Flt3l generated cDC1 ? pDC ? on\nblood circulating DC and not BM-derived ? monocytes ?\nResponse 8:\nThank you for this valuable comment. We agree that the classification of GM-DCs is an\nimportant point, as GM-DCs are known to represent a heterogeneous population. In response,\nwe performed additional analyses focusing on cell-type characterization and have added the\nresults in Fig. 2e together with a new description in theResultssection. Interestingly, the\nIFN‒positive cells were classified as macrophages, which we believe is an important finding.\nWe appreciate the reviewer for drawing our attention to this aspect.\nBased on this result, we concluded that the term “GM-DC” was not appropriate to\ndescribe the cells used in this study and have therefore replaced it throughout the manuscript\nwith “GM-CSF‒cultured bone marrow cells (GM-BMCs).” In addition, we confirmed that\nperitoneal macrophages did not produce IFN and that splenocytes, which contain\nmacrophages, also showed no response. These findings suggest that nucleocytosis-mediated\nIFN production may occur in specialized cell types, such as pDCs. Consistently, additional\nanalyses of thein vivoscRNA-seq data revealed IFN-responsive signatures in macrophage-\nlineage cells (Fig. 6g). Notably, MoMacs exhibited high STING expression (Fig. 6f),\nsuggesting that they may be responsible for thein vivoSTING-dependent responses.\nWe have added these observations to theResultssection and expanded the\ndiscussion regarding the cell types involved. Your insight led us to an important and\nunexpected finding, for which we are very grateful.\nChange: Figure, Fig. 2e\nAddition:\nChange: Legend, Fig. 2e\nAddition:\nFig. 2. e. UMAP plots showing cell types (left three panels) annotated by the expression of\nkey marker genes (Z-score) (right panel).\nChange: Result, Line 187-190\nAddition:\nInterestingly, Ifnb1 expression was induced by HCQ only in a cell cluster categorized as\nmacrophages, whereas cGAMP induced Ifnb1 in both macrophage and DC clusters (Fig. 2f,\ng), indicating that a macrophage-specific function is required for HCQ-mediated IFN\nproduction.\nChange: Discussion, Line 533-540\nAddition:\nRelated to this issue, clarifying the specific macrophage cell type capable of inducing\nnucleocytosis represents an intriguing future direction. As shown in Fig. 2g, Ifnb1 expression\nwas observed in the macrophage population, whereas DCs, peritoneal macrophages, and\nsplenocytes did not produce IFN upon HCQ treatment (Extended Data Fig. 6a). These\nresults suggest the possible existence of a specialized IFN-I-producing macrophage subset\nacting through nucleocytosis. Identification of such a novel IFN-I-producing macrophage\nsubset would be highly intriguing and remains an important subject for future investigation.\nRelated corrections:\nDC to macrophage: Line 64, 68, 365, 456\nGMDC to GM-BMC : All of terms in the manuscript.\nComment 9:\nFig3.\nFig3a. : IFN-b expression is not visible on pictures !? and the graph on the right is not clear. The\nY axis has to better indicates: “DNA intensity”\nResponse 9:\nWe apologize for the use of colors that may have impaired clarity. In this figure, we have\nchanged the color scheme from that used in Fig. 2. Nucleic acids are now shown in red, and\nIFN is indicated in blue for better visibility. In addition, the labeling of “Sytox” originally\nreferred to the reagent name and did not necessarily match the color in the figure, which may\nhave caused confusion. We have therefore changed the label to “Sytox (DNA)” and clarified\nthat blue represents IFN. Furthermore, the Y-axis of the graph has been updated to indicate\n“DNA intensity”.\nChange: Figure, Fig. 4a\nBefore:\nAfter:\nComment 10:\n-The DNA transfer from one DC to another is based on data in fig 3a and is not very clear (very\ndiffuse) and video microscopy allows the observation of only limited number of cells. This has to\nbe better demonstrated.\nResponse 10:\nTo address your concerns, we conducted additional analyses using Z-stack imaging and\nholographic microscopy. These approaches enabled us to capture Z-slice images illustrating\nmultiple cases of nuclear access and to confirm the transfer of DNA between cells. We believe\nthat these new data clarify the observation of nucleocytosis. Although these analyses are\nqualitative in nature, when combined with complementary quantitative assessments\nperformed using the Discover S8 microscope (Fig. 4b, c), they provide strong support for the\npresence of nucleocytosis from both qualitative and quantitative perspectives.\nThe diffuse appearance of DNA in IFN‒producing cells may reflect either the\ngenuine distribution of nucleic acids within the cytoplasm or limitations of the optical\nresolution. At this stage, the most important point is the occurrence of DNA transfer itself,\nwhile the precise physical state of the transferred nucleic acids remains to be determined in\nfuture studies. As the nature of the transferred DNA may vary depending on its quantity and\ncontext, nucleocytosis is unlikely to exhibit a single morphological pattern. We have\nincorporated this interpretation into the revisedDiscussionsection.\nChange: Figure, Fig. 3d-i (left), Extended Data Fig. 3b, c (right)\nAddition: (Please see the revised figure for details; the following is a summary.)\nFig. 3d-I. Extended Data Fig. 3b, c\nChange: Legend, Fig. 3, Extended Data Fig. 3\nAddition:\nFig. 3. d-h. Microscopic analysis of HCQ-treated GM-BMCs. d. Snapshot analysis of GM-\nBMCs treated with HCQ (80 µM) for indicated time periods. Bright field with DNA staining\nis shown in both MIP and Z-slice images. e. Time-laps analysis of GM-BMCs treated with\nHCQ (80 µM). Bright field with DNA staining is shown in left five panels. DNA intensity is\nsummarised in the middle. Z-slice picture at indicated time point is shown in the right. f.\nHolotomographic analysis of GM-BMCs treated with HCQ (80 µM). Snapshot images in\nindicated time points are shown in both MIP and Z-slice pictures. g, h. Holotomographic\ntime-laps analysis of GM-BMCs treated with HCQ (100 µM) for indicated time periods. DNA\nstaining is shown in red in MIP images. Z-slice images at indicated time point are shown in\nh. i. Concentration of IFN in the culture supernatant of GM-BMCs treated with HCQ (100\nµM) in the presence of indicated concentration of inhibitor.\nExtended Data Fig. 3. b, c. Time-laps analysis of GM-BMCs treated with HCQ (80 µM).\nBright field with DNA staining is shown in left six panels. DNA intensity is summarized in\nthe right. Z-slice picture at indicated time point is shown in c.\nChange: Result, Line 223-242\nAddition:\nFrom above results (Fig. 3a-c), we hypothyzed that, through contact between dead and live\ncells, DNA is transferred to IFNβ-producing cells, thereby activating the STING-cGAS\nresponse. According to the results of LCI-S, within 6 hours after HCQ treatment, at which\ntime IFNβ secretion is observed, nuclear structures of sytox-positive dead cells can be\ndetected (Fig. 2b, d). Given the fact that HCQ induced strong IFNβ production, enough\namount of DNA is efficiently taken up from dead cells. Therefore, we next examined whether\ncontact of live cells with dead cell nuclei and subsequent DNA uptake occurs by microscopic\nanalysis. As a result, although the distance between dead and live cells and the degree of dead\ncell disintegration varied, in all cases both MIP and slice images revealed protrusion-like\nstructures and direct access to the nucleus (Fig. 3d). Remarkably, time-lapse analysis further\ndemonstrated a decrease in DNA intensity in dead cell nuclei accompanied by an increase in\nDNA intensity in live cells (Fig. 3e). Likewise, holographic microscopy confirmed the\npresence of protrusion-like structures, and importantly, DNA signals within the protrusion\nwas also detected (Fig. 3f, g). Cross-sectional image analysis revealed that these protrusion\nextended into the nucleus and that low-density regions was observed inside the nuclei at sites\nof contact (Fig. 3f, g). Consistent with these findings, inhibitors of actin polymerization\nspecifically suppressed HCQ-induced IFNβ production (Fig. 3i). Collectively, these results\nsuggest that live cells directly access the nuclei of dead cells and extract DNA.\nChange: Discussion, Line 448-454\nAddition:\nFurthermore, how nucleic acids are extracted from the nucleus and in what state they exist\nremains to be elucidated. In Fig. 3d and Fig. 4a, DNA appears to diffuse in the cytosol of\nIFN-producing cells, consistent with activation of the cytoplasmic cGAS-STING pathway.\nAlthough it is currently difficult to determine the precise state of these nucleic acids, the most\nimportant point of our findings is that their translocation has been confirmed. Further high-\nresolution analyses, such as electron microscopy, will be required to clarify this issue.\nComment 11:\nFig3b. : the legend is not clear and the data already shown in fig 2.\nNumbers in white (legend ?) : not visible\nDefine P1 and P2 ?\nResponse 11:\nWe apologize for the confusion caused by the unclear labeling. The numbers shown in white\nwere automatically assigned by the imaging system and have no specific meaning; therefore,\nthey have been removed. P1 and P2 correspond to those shown in Fig. 2j. In this figure, we\npresent several representative examples. Although there is some overlap with Fig. 2, we\nbelieve that displaying both figures helps illustrate multiple typical cases more clearly.\nAdditional explanations have been included in the figure legend. We apologize for the\nprevious lack of clarity.\nChange: Figure, Fig. 4b\nBefore:\nAfter:\nChange: Legend, Fig. 4b\nAddition:\nb. Representative images of SYTOX Green‒positive duplets analyzed in Fig. 3b. Six\nrepresentative images from each population are shown. (‒)P2: P2 population without HCQ\ntreatment (Fig. 3b). HCQ P1: P1 population with HCQ treatment (Fig. 3b).\nComment 12:\nFig3d-g :« calreticulin accumulated in the DNA-positive region of HCQ-induced dying cells » is\noverinterpretation as the figure 3g gave us only the proportion of calreticulin in the nucleus\ncompared to the cytosol which is very clear on figure 3d.\nResponse 12:\nThank you for this comment. We have revised the text accordingly, as shown below. The\nnuclear translocation has also been confirmed by nucleoprotein Western blotting, and we\nkindly refer the reviewer to Extended Data Fig. 4f for these results.\nChange: Result,: Line 262-267\nBefore:\nNotably, calreticulin translocated from the cytosol to the nucleus after HCQ treatment and\nfurther accumulated in the DNA-positive region of HCQ-induced dying cells (Fig. 3d-g,\nExtended Data Fig. 3d, e, Supplementary Movie 8).\nAfter:\nNotably, calreticulin was detected in DNA-positive regions after HCQ treatment, indicating\nits translocation from the cytosol to the nucleus (Fig. 4d-g, Extended Data Fig. 4d, e;\nSupplementary Movie 8). To exclude the possibility that this observation was due to HCQ-\ninduced morphological changes, we performed nuclear western blotting and confirmed\ncalreticulin nuclear translocation (Extended Data Fig. 4f).\nComment 13:\nFig3i : Authors have to use the same scale for comparison and specify in the caption that this is\nan intracellular staining.\nResponse 13:\nThank you for the helpful comment. We have adjusted the scale for proper comparison across\npanels and clarified the description in the figure legend.\nChange: Figure, Fig. 4\nBefore: After:\nComment 14:\nFig3j: too much pixelization, not very clear and may be not useful\nResponse 14:\nThank you for the comment. We agree that the image obtained with the Discover S8 is not\nvery clear. This panel was intended not to show detailed cellular morphology, but rather to\nillustrate the presence or absence of the merged (yellow) region. We apologize for not\nproviding sufficient explanation previously and have added a clarification in the figure legend.\nChange: Legend, Fig 4j\nBefore:\n(j) Representative images of each population. (k) Correlation value between calreticulin and\nthe nucleus.\nAfter:\n(j) Representative images of each population. Merged regions are shown in yellow. Based on\nthe corrected images, correlation values between calreticulin and the nucleus were calculated\nand are presented in panel k.\nComment 15:\n-line 266 “inhibition of HCQ-induced IFNβ production (Extended 267 Data Fig. 4b),\nsuggesting the involvement of PPT1 inhibition in IFNβ production. ». This have to be included\nas main result.\nResponse 15:\nThank you for the comment. We agree that this is an important result and have moved it to\nthe main Fig. 5b.\nComment 16:\nFig4.\nLine 300 ‒“our results indicate that both calreticulin accumulation via proton inhibition and cell\n-death via PPT1 inhibition are important for robust IFNβ production (Fig. 4j)”. Authors have to\nbe more cautious here as a PTT1 KO was not evaluated.\nResponse 16:\nThank you for this valuable comment. We apologize for the insufficient explanation and the\noverstatement in our original description. As shown in Fig. 4h and Extended Fig. 1m,\ntreatment with Baf A caused changes in calreticulin localization in live cells but only weakly\ninduced cell death and did not promote IFN production. In contrast, DC661, a\nPPT1-specific inhibitor, induced cell death but showed very limited IFN-inducing activity\n(Fig. 5a). Considering that Baf A combined with DC661 strongly induced IFN production,\nwe infer that both the alteration of calreticulin localization caused by proton inhibition in\nlysosomes and the cell-death induction caused by PPT1 inhibition are required for robust\nIFN induction.\nFurthermore, because other IFN-I inducers were found to bind to the active pocket of PPT1\nand the strength of this binding correlated with IFN induction activity, the importance of\nPPT1 inhibition is further supported. We have revised the text to describe these points with\ngreater caution and clarity in the revised manuscript.\nChange: Result, Line 348-353\nBefore:\nConsidering calreticulin enhancement in live cells by Baf A (Fig. 3h), our results indicate that\nboth calreticulin accumulation via proton inhibition and cell death via PPT1 inhibition are\nimportant for robust IFNβ production (Fig. 4j).\nAfter:\nAs shown in Fig. 4h, Baf A treatment leads to relocalization of calreticulin mainly in living\ncells but induces only weak cell death and fails to trigger IFN production (Extended Data\nFig. 1n). In contrast, DC661 strongly induces cell death but elicits only minimal IFN\nproduction (Fig. 5a). Taken together, these findings indicate that proton inhibition‒induced\ncalreticulin relocalization and PPT1 inhibition-induced cell death both contribute to robust\nIFN induction.\nComment 17:\n-again, a two way anova couldnʼt be done with n=3 biological replicates.\nResponse 17:\nThank you for the comment. As explained in response#4, we have removed the statistical\nanalysis and revised the data presentation accordingly.\nChange: Figure, Fig. 5\nBefore: After:\nComment 18:\nFig5.\n-only one cell in image 5c. Authors should show us a wider field and more cells have to be\nanalyzed.\nResponse 18:\nThank you for the comment. We have added the wide-field results in Extended Fig. 6b and\nincluded the corresponding quantitative data in Fig. 6c.\nChange: Figure, Fig 6, Extended Data Fig. 6\nAddition:\nFig 6c Ex Fig 6b:\nComment 19:\n-Legend on histogram is missing (X axis?)\nResponse 19:\nThank you for the comment. We apologize for the lack of clarity. We have added an\nexplanation for the X-axis in the legend, as shown below.\nChange: Legend, Fig. 6c\nBefore:\nIntensities of calreticulin and DNA staining were calculated at the site of the white lines.\nAfter:\nIntensities of calreticulin and DNA staining were calculated at the site of the white lines shown\nin the images in the left panel. The X-axis indicates the distance from the left edge of the\nwhite lines.\nComment 20:\n-Title Fig5 “Various type…” replace by “Two types of tumor cell…”\nResponse 20:\nThank you for the comment. We agree that the original title was inappropriate. We have\ndeleted “Various type” and revised the title as indicated below, reflecting the content of the\npresented results. In addition, the corresponding description in the Results section has been\nmodified to replace the phrase “various cells.”\nChange: Figure title, Fig.6\nBefore: Various types of dying cells trigger IFNβ production after HCQ treatment.\nAfter:IFN production by HCQ-treated tumor cells and in vivo effect of HCQ.\nChange: Result, Line 372\nBefore:\nConsistently, HCQ-induced nuclear translocation of calreticulin was observed in these cells\n(Fig. 5c, Extended Data Fig. 5b), indicating that nucleocytosis-inducing cell death is induced\nin various cells.\nAfter :\nConsistently, HCQ-induced nuclear translocation of calreticulin was observed in these cells\n(Fig. 5c, Extended Data Fig. 5b), indicating that nucleocytosis-inducing cell death is induced\nin these two types of tumor cells.\nComment 21:\n-Fig5e: Instead of using a single gene to annotate clusters, authors could use other tools such as\nUcell. Again, better analysis of the scRNAseq data could help to understand the full effect of\nHCQ and not just to analyze IFN-related genes, otherwise simple qPCR would be enough.\nThe number of cells analyzed by scRNAseq is certainly not enough to have DC subsets which is\nmissing in regard to the rest of the paper.\n-For example, -what is the expression of STING in the different clusters?\n-Endothelial cells highly respond in vivo to HCQ. Do their express STING? This is not discussed\nor described.\n-scRNAseq data generated in vivo is not well described (see the last paragraph of the Result\nsection) and discussed.\nResponse 21:\nThank you for this comment. We agree that the aim of this analysis was to capture the overall\nresponse induced by HCQ in vivo. The primary objective was to determine whether HCQ\ninduces a STING-dependent response in vivo, rather than solely to identify IFN-producing\ncells. For this reason, we analyzed the entire cell population without enriching for any specific\nsubset. We acknowledge that the lack of a global gene-expression analysis was a shortcoming,\nand we have now addressed this. By examining overall gene-expression trends, we confirmed\nthat macrophages, neutrophils, epithelial cells, and other cell types exhibit STING-dependent\nIFN responses.\nIn addition, based on findings discussed in another comment, we identified\nmacrophage-lineage cells as the main IFN-producing population in vitro. This type of cells\n(MoMF and AMF) were detected in the present analysis and were found to have strong IFN\nresponses in MoMF. This is a particularly interesting result, and we appreciate the reviewerʼs\ninsight, which helped us fulfill the analytical goals of this study. These results and\ninterpretations have been added to the Results sections. We also apologize for the insufficient\nexplanation of cell annotation; this was based on multiple marker genes, and further details\nhave been included in the Methods section.\nRegarding STING expression levels, we found that two macrophage-lineage clusters\n(MoMF and AMF) expressed STING at high levels. Notably, MoMF cells displayed activated\nIFN responses, suggesting they may respond to HCQ in vivo, in agreement with our in vitro\nresults. In contrast, other cell types, including epithelial cells, showed low STING expression,\nindicating the possibility that they respond secondarily to type I IFNs. We have added this\ninterpretation to the description of the scRNA-seq results.\nChange: Figure, Fig. 6, Extended Data Fig. 6\nAddition: Fig. 6\nAddition: Extended Data Fig. 6\nChange: Result, Line 378-398\nBefore:\nWe observed increased expression of IFN-inducible genes in lung cells from HCQ-treated\nmice, all of which were induced in a STING-dependent manner, confirming the potential of\nHCQ to induce an IFN-I response in vivo (Fig. 5f, g). Notably, systemic production of IFNβ\nwas not observed, indicating a local effect of HCQ (Extended Data Fig. 5c). Moreover, the\nmagnitude of STING-dependent IFN-I response by HCQ was cell type-specific (Fig. 5f and\nExtended Data Fig. 5d), indicating local IFN-I response. In conclusion, these results show the\nphysiological relevance of lysosomal dysfunction induced by HCQ in activating a local IFN-I\nresponse in vivo.\nAfter:\nAt first, we classified the cell types detected in the scRNA-seq analysis and found that the\nSting1 gene was expressed in macrophage subsets, including monocyte-derived macrophages\n(MoMFs) and alveolar macrophages (AMFs) (Fig. 6d, e). Interestingly, when we analyzed the\ngene expression patterns across the detected cell types, the IFN-I response emerged as one of\nthe most prominent subsets among both the total gene set and the STING-dependent genes\n(Fig. 6f). Importantly, IFN-I-related genes were expressed in a STING-dependent manner in\nmultiple cell types, particularly MoMFs, epithelial cells, and neutrophils, and IFN-stimulated\ngene signatures were also induced in these cells (Fig. 6g). These results indicate that HCQ\ntriggers a STING-dependent IFN-I response in the lung. Based on the pattern of Sting1\nexpression, these findings suggest that MoMFs initiate STING-dependent IFN-I responses,\nwhich in turn activate the expression of secondary IFN-stimulated genes in other cell types\n(Fig. 6e‒g; Extended Data Fig. 6e, f). This is consistent with our in vitro observations of\nnucleocytosis by macrophages within GM-BMCs (Fig. 2f, g), indicating that MoMFs are\ncandidate inducers of nucleocytosis in vivo. Notably, systemic production of IFNβ was not\nobserved (Extended Data Fig. 5c), indicating a local effect of HCQ in the lung. Considering\nthe different magnitudes of the STING-dependent IFN-I responses across cell types (Fig. 6f,\ng; Extended Data Fig. 6e), such cell type-dependent responses may underlie the localized\nIFN-I response in the lung. In conclusion, these results demonstrate the physiological\nrelevance of HCQ in inducing a STING-dependent local IFN-I response in vivo.\nChange: Method, scRNA-seq\nAddition:\nCell types for each cluster were annotated based on differentially expressed genes identified\nby the FindAllMarkers function and known marker genes.\nComment 22:\nIn conclusion, my opinion is to accept this paper but with major modifications. Indeed, the possible\nacquisition of DNA by nucleocytosis, the direct induction of IFN-b by HCQ during a cell-death\nprocess is very interesting, but\n1/all the paper is made with in-vitro-generated BM-DCs\n2/The pathway involved in CAD mediated cell-death is not identified.\n3/The nucleocytosis is not enough demonstrated and the molecular mechanism not identified\n4/There are many over-interpretations and sometimes correlations more than demonstrations.\n5/many data in the paper concern few cells or are generated with only n=3 biological replicates\nwith sometimes two variables/experiment and thus statistics not suitable.\nResponse 22:\nWe sincerely appreciate the reviewersʼ constructive evaluation of our study. In accordance\nwith the comments, we have extensively revised the manuscript, which we believe has\nsubstantially strengthened both its clarity and impact.\n1. Regarding point 1, through analyses using various cell types, we identified that HCQ\ninduces IFN production specifically in macrophage-lineage cells within GM-BMCs.\nConsistently, in vivo data also demonstrated strong responses in macrophage-lineage\ncells. The finding that nucleocytosis occurs in particular cell types is highly intriguing,\nand thanks to the reviewersʼ suggestions, we were able to uncover new insights into\ncell-type specificity. The results further suggest the existence of a previously\nunrecognized macrophage subset, which may provide opportunities for future\ninvestigation.\n2. Regarding point 2, we confirmed that CADs, like DC661, target PPT1. These shared\ncharacteristics were validated through multiple complementary approaches. In additional\nexperiments, we showed that N-butyl-tert-treated cells exhibited inhibited IFN\nproduction across all CADs tested. Together, these findings consistently demonstrate\nthat CADs induce cell death through PPT1 inhibition. Moreover, as reported in a\nprevious study (Ref. 35, J. Clin. Invest. 133, 2023), PPT1 inhibition can trigger mixed\nmodes of cell death. Our data, supported by inhibitor experiments, are consistent with\nthese findings. Taken together, these results suggest that calreticulin translocation to the\nnucleus may play an important role independent of the specific mode of cell death. We\nhave added additional analyses addressing calreticulin dynamics. We also apologize for\nthe previously insufficient explanation of PPT1, as pointed out by Referee 1, and have\nnow clarified its relevance in the revised text. Overall, our findings emphasize the\nimportance of PPT1 inhibition in cell death.\n3. For point 3, we performed additional analyses, particularly microscopy-based imaging,\nto\nclarify nucleocytosis from multiple perspectives. And further additional experiments also\nreinforced the involvement of Rho kinase and calreticulin with greater clarity.\n4. Regarding point 4, we carefully revised the text according to the reviewerʼs suggestions\nto ensure accuracy and appropriateness.\n5. For point 5 as well, we conducted the necessary additional experiments and revised the\nmanuscript appropriately in line with the reviewerʼs comments.\nThroughout the revision process, we have addressed all of the reviewersʼ comments\nthoroughly and have made the corresponding corrections or additions. This study began with\ncompound screening and the identification of novel type I IFN inducers, proceeded to the\nanalysis of molecular targets and structural mechanisms, clarified related mechanism, and\nultimately led to the discovery of a new phenomenon, nucleocytosis. We believe that the\nrevised manuscript now possesses sufficient novelty, impact, and completeness to merit\npublication. We would be deeply grateful for your further consideration.\nAdditional revisions\nIn addition to the revisions made in response to the reviewersʼ comments, we have also made\nseveral updates summarized below. These include modifications related to the revision\nprocess itself as well as changes necessitated by the updated submission status, as the\nmanuscript is no longer being submitted as a back-to-back paper with the related study.\nMain Text: Line, 203\nConsistently, HCQ induced cell death in a dose-dependent manner, and the dose-\nresponse curve of IFNβ exhibited a bell-shaped pattern (Fig. 2h), indicating that high\nHCQ concentrations induce cell death in IFNβ-producing cells or inhibit the B-DNA-\ncGAS axis through conversion to Z-DNA (Negichi H., Kubota Y., Wada Y. et. al\nsubmitted).\nAddition in authors and author contributions\nDaisuke Muto(Investigation), Yusuke Suenaga(Investigation), Taichi Kojima(Investigation),\nYuzuki Matsuda(Investigation), Irish Sean Road(Investigation),Yoji Nagasaki (Resources)\nAddition in acknowledgement\nSayaka Kobayashi\nAddition of reagents\nSupplementary Data table 1b is updated.\nRevision in Method\nImmunoblot analysis: method for the isolation of nuclear fraction\nscRNA-seq: method for GSEA, the annotation of cell cluster, analysis ISG,\nLCI-S imaging analysis: analysis with wide-field LCI-S module\nAnalysis of HCQ concentration: Delete\nMicroscopic analysis: analysis with BZ-X1000, 3D Cell Explorer microscope, and HT-X1\nNumbering\nNumbers of Figures and References have been revised throughout the text."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have addressed my main concerns and I congratulate them on an improved revised version of the manuscript.", "reviewer_2": "In this revised version, the authors have addressed most of the points that were requested thus my opinion is to accept this paper now."}, "author_response": ""}]

Decision letter