TREM2 Recognition of Candidalysin Orchestrates Mucosal Immunity in Oropharyngeal Candidiasis

TREM2 Recognition of Candidalysin Orchestrates Mucosal Immunity in Oropharyngeal Candidiasis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Biological Sciences - Article TREM2 Recognition of Candidalysin Orchestrates Mucosal Immunity in Oropharyngeal Candidiasis Weiwei Deng, Yishan Chen, Siqi Liu, Kefan Lin, Kai Zhang, Di Wang, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4137807/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The landscape of oral mucosal immunity, particularly in the context of oropharyngeal candidiasis (OPC), remains largely uncharted. By employing single-cell RNA sequencing (scRNA-seq) on murine models of OPC, we have illuminated the immune dynamics within this niche. We discovered a new subpopulation: TREM2-expressing macrophages, intrinsic to the oral mucosa, which infiltrated in response to Candida albicans (C. albicans) infection. However, these macrophages were significantly depleted under cortisone acetate (CA)-induced immunosuppression. This study unveiled the pattern recognition receptor (PRR) characteristics of TREM2 during OPC, where TREM2 demonstrated the ability to directly recognize candidalysin at positions G65, N73, and N91-K92, inducing downstream inflammatory signaling regulation of TNF-α, which orchestrated macrophage and neutrophil responses and influenced Th17 cell differentiation. As a result, the absence of TREM2 increases the susceptibility of mice to OPC. Conversely, administering TREM2 agonists has been shown to facilitate the clearance of OPC induced by CA in mice. Therefore, our findings expand the understanding of TREM2 beyond its known association with neurodegenerative diseases and metabolic disorders, positioning it as a key receptor in bridging the host-fungus immune interface, and providing novel therapeutic insights for glucocorticoid-induced OPC. Biological sciences/Microbiology/Fungi/Fungal host response Health sciences/Diseases/Oral diseases/Oral candidiasis Oropharyngeal candidiasis Mucosal immunity Candida albicans Fungal immunity TREM2 Candidalysin Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction C. albicans relies on its agglutinin-like sequence (ALS) adhesins for adherence to oral epithelial cells [1]. Oral epithelial cells, in turn, recognize pathogen-associated molecular patterns (PAMPs), specifically β-glucan, through their EphA2 [2]. Moreover, these epithelial cells can identify Als3 of C. albicans through EGFR [3], activating downstream PI3K/Akt, NF-κB, and MAPK signaling pathways. This activation results in the transcription of AP-1 transcription factors c-Fos and c-Jun, promoting the secretion of various cytokines, β-defensins, and antimicrobial peptides by epithelial cells. The chemokines secreted in response recruit Th17 cells, Th22 cells, neutrophils, and macrophages. Th17 cells secrete IL-17/IL17F, which, upon binding to the IL-17RA/IL-17RC receptors on epithelial cells, activates downstream signaling pathways, thereby facilitating the transcription of inflammation-related cytokines [4, 5]. In concordance with IL-17R, IL-22RA is predominantly expressed in non-hematopoietic cells, and the IL-22 secreted by Th22 cells is crucial for maintaining the barrier function of oral epithelial cells during OPC [6]. Neutrophils recognize β-glucan through their EphA2, inducing the generation of ROS to eliminate C. albicans [7]. Upon detecting longer hyphae, neutrophils initiate a specific form of cell death, releasing neutrophil extracellular traps (NETs) composed of decondensed chromatin and intracellular granule proteins to capture and kill pathogens [8, 9]. Macrophages contribute to the defense against C. albicans through phagocytosis, killing activity, and ROS production [10, 11]. Despite the crucial role of macrophages in fungal immunity, previous research on OPC has predominantly concentrated on IL-17 signaling, with limited exploration of the specific functions and mechanisms of macrophages in this context. In recent years, the role of TREM2 (Triggering receptor expressed on myeloid cells-2, TREM2) has emerged as a new research focus in various diseases [12]. TREM2, a single-pass transmembrane immunoglobulin superfamily member, is predominantly expressed in microglial cells and macrophages [12]. Functioning as a receptor, TREM2 can bind to a diverse range of ligands, recruiting the adaptor proteins DAP10/12 and activating PI3K and Syk signaling [12-15]. Additionally, TREM2 can be cleaved into a soluble protein by the metalloproteinases ADAM10 and ADAM17 [16, 17]. Studies have demonstrated that the overexpression of Trem2 in mice with Alzheimer's disease effectively improves pathological lesions and cognitive impairments [18]. Furthermore, research has identified that TREM2 + macrophages can phagocytose and clear damaged cells in the liver, thereby suppressing chronic liver inflammation and non-alcoholic fatty liver disease induced by obesity [19]. Initially considered an anti-inflammatory molecule during infections, recent research suggests that TREM2 can promote cellular phagocytosis of bacteria and enhance inflammatory responses [20]. The phagocytic activity dependent on TREM2 necessitates the presence of the full-length TREM2 protein [21]. Moreover, the production of ROS in response to infection is also contingent on TREM2 [22, 23]. Despite the research community has shifted its focus towards recognizing the central role of TREM2 as a key immune signaling hub induced by pathology, its mechanistic involvement in fungal immunity remains unclear. Our research elucidated the pivotal role of TREM2 + macrophages in the defense against oral candidiasis through their regulation of TNF-α, which orchestrates anti-fungal immune response. Crucially, we unveiled TREM2's capacity to directly recognize candidalysin, instigating a DAP12/Syk/NF-κB mediated TNF-α signaling cascade. This discovery paved the way for leveraging the TREM2 activator as a novel therapeutic strategy in glucocorticoid-induced OPC, offering a beacon of hope for enhancing mucosal immunity. Results Induced transcription of TREM2 predominantly situated at the infection sites The single-cell resolution landscape of OPC has not been mapped to date. To address this gap, we utilized scRNA-seq in a murine model (Fig.1A), encompassing normal tongue tissue, tongue tissue post- C. albicans infection, and tongue tissue of mice treated with CA to induce OPC. Following sequencing and subsequent seurat pipeline analysis, a total of 30,810 cells were identified (Fig.1B, C). Predominantly, these cells comprised non-immune cells such as fibroblasts, endothelial cells, and smooth muscle cells (Fig.1B), with immune cells accounting for only 12.19%, aligning with the observed low proportion of immune cells in tongue tissue. Further subsetting of these immune cells (Fig.1D, E) revealed macrophages distinguishing into TREM2 + and TREM2 - subpopulations. Conventionally, macrophage subpopulations with distinct functions are denoted as M1 and M2 macrophages. However, it is crucial to note that the M1 and M2 classification, derived mainly from in vitro polarization assays, is more apt for describing the activation state of macrophages in vitro [24]. Indeed, differentiating macrophage subpopulations in murine tongue tissue using M1 or M2 markers proved challenging (Extended Data Fig.1A). With the increasing application of single-cell studies, macrophage subtyping leans towards utilizing TREM2 for distinction. Within tongue tissue, the confirmed TREM2 + macrophages exhibited an elevated proportion among immune cells post- C. albicans infection, while CA-treated mice showed a significant reduction in the proportion of TREM2 + macrophages (Fig.1F, Supplementary Table 1). To ascertain the presence of TREM2 + macrophages in the human oral mucosa, we conducted an analysis of publicly available scRNA-seq data [25] of the oral mucosa (Extended Data Fig.1B). After subsetting immune cell populations (Extended Data Fig.1C) and subsequent clustering (Extended Data Fig.1E, F), we identified the presence of TREM2 + macrophages in normal human tissue (Extended Data Fig.1D). These findings indicated that these cells may also represent a type of tissue-resident macrophage, akin to microglial cells found in the brain, Kupffer cells in the liver, and alveolar macrophages in lung tissue. To validate this hypothesis, we performed immunofluorescence and flow cytometric analyses, confirming the presence of TREM2 + macrophages in normal murine tongue tissue (Extended Data Fig.1G), predominantly localized within the internal regions of the tongue tissue (Extended Data Fig.1H). Upon C. albicans infection, the proportion of TREM2 + macrophages in murine tongue tissue significantly increased (Extended Data Fig.1G), with these macrophages predominantly situated at the infection sites (Extended Data Fig.1H). Hematopoietic-derived TREM2 is indispensable for protection against OPC Previous studies have suggested an inhibitory role for TREM2 in tumor immunity [26-28]. Findings from the OPC mouse model demonstrate the complete clearance of C. albicans by Day 5 [29]. Intriguingly, during the early stages of OPC (Day 1), we observed an accumulation of TREM2-expressing macrophages (Extended Data Fig.1G, H). To further understand the role of TREM2 in OPC and rule out any inhibitory effects (Considering that Trem2 deficiency leads to rapid recovery in OPC mice), we conducted an assessment of TREM2 impact during Days 1 and 2. The results revealed that Trem2 deficiency increased susceptibility to OPC in mice, manifested by lower body weight and higher fungal burden in Trem2 -/- mice (Fig.2A, B). Pathological findings also demonstrated more severe epithelial fungal invasion in Trem2 -/- mice (Fig.2C). By the fifth day, WT mice exhibited undetectable levels of C. albicans , while Trem2 -/- mice still harbored persistent fungal infections (Extended Data Fig.1I, J). Over the past decade, the classification of Ly6C + and Ly6C - macrophages has become a prevalent tool for studying monocyte-derived macrophages [30]. This classification helps in accurately defining the state of macrophages within complex internal microenvironments [30]. Ly6C + macrophages undergo significant enrichment and display a pro-inflammatory phenotype, actively participating in acute inflammatory responses. Our investigation further unveiled a pronounced infiltration of TREM2 + macrophages at the infection site (Extended Data Fig.1H). We postulated that these TREM2 + macrophages might belong to the Ly6C + subset. To validate this hypothesis, flow cytometric analysis was conducted, revealing differential presence of Ly6C + TREM2 + macrophages before and after infection, while Ly6C - TREM2 + macrophages exhibited no such difference (Fig.2D). Additionally, we observed that TREM2 + macrophages at the infection site were also CX3CR1 + (Extended Data Fig.2A), a marker for infiltrating monocyte-derived macrophages. scRNA-seq data further indicated a high expression of CX3CR1 in both human and murine TREM2 + macrophages (Extended Data Fig.2B, C). Remarkably, the administration of the lymphocyte recirculation inhibitor FTY720 effectively suppressed the infiltration of Ly6C + TREM2 + macrophages, with no impact on Ly6C - TREM2 + macrophage infiltration (Extended Data Fig.2D). This inhibition significantly heightened susceptibility to OPC in mice (Extended Data Fig.2E-H). These findings strongly support a protective role of hematopoietic-origin TREM2 in OPC. To pinpoint the specific source of TREM2 in the anti-fungal effect, we created chimeric mice by replacing the bone marrow (BM) of lethally irradiated wild-type (WT) mice with a reconstituting of WT BM and Trem2 -/- BM. The results demonstrated that chimeric mice exhibited increased susceptibility to OPC (Extended Data Fig.2I, J). Therefore, we can confidently affirm that hematopoietic-origin TREM2 plays a pivotal protective role in OPC. Previous studies have firmly established that Trem2 expression is confined to macrophages within the myeloid cell compartment [19, 31], underscoring that TREM2 primarily exerts its function through macrophages of hematopoietic origin. Recent investigations indicated an elevation in TREM2 expression within macrophages across various liver diseases and relevant mouse models [32-37]. However, whether TREM2 undergoes upregulation during fungal infections remains unexplored. To address this knowledge gap, we stimulated mouse bone marrow-derived macrophages (BMDMs) with C. albicans , revealing an augmentation in TREM2 protein (Extended Data Fig.2K). Intriguingly, IL-17 was also identified as a potential inducer of TREM2 protein upregulation (Extended Data Fig.2K). These findings suggested that, subsequent to macrophage infiltration into the OPC infection site, both C. albicans and IL-17 contributed to TREM2 protein upregulation, thereby facilitating the clearance of C. albicans . Pro-inflammatory role of TREM2 + macrophages in OPC To elucidate the molecular mechanisms through which TREM2 contributes to protection in OPC, we further analyzed scRNA-seq data. We observed that TREM2 + macrophages upregulated inflammatory chemokines ( Cxcl1 , Cxcl16 , Ccl2 , Ccl4 , and Ccl9 ), antigen presentation ( H2-DMb1 , H2-Aa, H2-Eb1 , H2-DMa , and Cd74 ), interferon response ( Ifitm3 ), complement pathway ( C1qa , C1qb , and C1qc ), protein degradation ( Lamp1 , Ctss , Ctsz , and Lgmn ), inflammation markers ( Rgs10 , Mpeg1 , and Tnf ), costimulatory molecules ( Cd86 ), chemokine receptors ( Ccr2 and Ccr5 ), pattern recognition receptors ( Tlr2 ), and surface adhesion receptor ( Cd44 ) (Fig.2E, Supplementary Table 2). In contrast, TREM2 - macrophages primarily upregulated ribosomal proteins ( Rps2 , Rps6 , Rps12 , and Rpsa ), the inflammatory chemokine ( Ccl3 ), and the complement pathway component ( C11bp ) (Fig.2E, Supplementary Table 2). Pathway analysis revealed that TREM2 + macrophages primarily enhanced pathways related to antigen processing and presentation, phagosome formation, chemokine signaling, NF-κB activation, Th17 cell differentiation, cytokine-cytokine receptor interaction, and TNF signaling—all crucial for antifungal immunity (Fig.2E). On the other hand, TREM2 - macrophages upregulated pathways associated with disease states, not involving antifungal immune responses (Fig.2E). Other antifungal immune cells, such as neutrophils, were enriched with pathways like phagosome formation, neutrophil extracellular trap formation, IL-17 signaling, C-type lectin receptor signaling, TNF signaling, cytokine-cytokine receptor interaction, and NF-κB signaling (Fig.2E). T cells exhibited enrichment in pathways vital to their function, including Th1 and Th2 cell differentiation, Th17 cell differentiation, and T cell receptor signaling (Fig.2E), reflecting the reliability of our cell clustering and functional analysis. Further analysis revealed that under normal physiological conditions, TREM2 + macrophages showed gene oncology (GO) functional enrichment in inflammatory response, MAPK signaling, and antigen processing and presentation (Extended Data Fig.3A, Supplementary Table 3). Upon C. albicans infection, TREM2 + macrophages predominantly upregulated GO functions related to the cellular response to interleukin-1, endocytosis, cytokine-mediated signaling, and IL-17 signaling (Extended Data Fig.3B, Supplementary Table 3), indicating a pro-inflammatory role even prior to infection and promoting fungal clearance through activation of IL-17 signaling after C. albicans infection. The upregulation of various chemokines, inflammatory mediators, and receptors in TREM2 + macrophages, coupled with the enhanced cytokine-cytokine receptor interaction pathway (Fig. 2E), suggested extensive interactions with other immune cells. Indeed, strong intercellular interactions were observed between TREM2 + and TREM2 - macrophages, T cells, and neutrophils, with TREM2 + macrophages also engaging in self-regulation (Extended Data Fig.3C). These interactions predominantly involved signals through CCL, APP, CXCL, TNF, GRN, and VISFATIN (Extended Data Fig.3D). Notably, the TNF signaling was exclusively generated by TREM2 + macrophages and impacted neutrophils, T cells, TREM2 + and TREM2 - macrophages (Extended Data Fig.3D). GSEA analysis further identified a significant upregulation of TNF signaling in TREM2 + macrophages compared to other immune cells (Extended Data Fig.3E), with only TREM2 + macrophages showing high expression of Tnf , and the TNF receptor being expressed in neutrophils, T cells, and both TREM2 + and TREM2 - macrophages (Extended Data Fig.3F), aligning with the cell interaction analysis of TNF signaling regulation in these immune cells. Correlation analysis substantiated a significant positive association of TREM2 with TNF expression and TNF signaling pathways in both humans and mice (Extended Data Fig.3G), preliminarily confirming the unique role of TREM2 + macrophages in regulating TNF signaling. Regulatory influence of TREM2 on macrophage TNF-α secretion Our bioinformatics analysis has confirmed TREM2 as a potential regulator of TNF (Extended Data Fig.3G). To determine the relationship between TREM2 and TNF-α, we first examined the co-localization of TREM2 + macrophages with TNF-α. Our findings revealed that TREM2 + macrophages were capable of secreting TNF-α and were localized to the site of infection in OPC (Extended Data Fig.4 A). Flow cytometry analysis also indicated a significant infiltration of TREM2 + TNF-α + macrophages in the infected tongue tissue, whereas the infiltration of TREM2 - TNF-α + macrophages showed no difference (Extended Data Fig.4B). Consistently, Ly6C + TREM2 + macrophages were significantly more prevalent in the infected tongue tissue, with an increase in Ly6C + TREM2 + TNF-α + macrophages at the infection site, while there was no disparity observed with Ly6C - TREM2 + TNF-α + and TREM2 - TNF-α + macrophages (Extended Data Fig.4C, D). Further analysis of TNF-α in tongue tissues revealed that the absence of Trem2 led to a significant decrease in TNF-α in OPC tongue tissues (Extended Data Fig.4E). TNF-α is primarily secreted by macrophages, T cells, and B cells, which also inhabit the immunological microenvironment of the mouse tongue (Fig.1D). To ascertain which cells were affected by the Trem2 deficiency leading to reduced TNF-α in OPC tongue tissues, we analyzed the secretion of TNF-α by these cells before and after Trem2 knockout. The results indicated that the absence of Trem2 mainly affected the secretion of TNF-α by macrophages (Extended Data Fig.4F), significantly reducing the infiltration of TNF-α-secreting macrophages at the infection site (Extended Data Fig.4G), while B cells, CD4 + T cells, and CD8 + T cells showed no difference in TNF-α secretion (Extended Data Fig.5A). To investigate how TREM2 affects the secretion of TNF-α by macrophages, we first studied whether there were differences in macrophage infiltration levels. We found that Trem2 knockout significantly reduced the number of macrophages at the infection site (Extended Data Fig.5B), corresponding with a notable decrease in macrophages at the infection site (Extended Data Fig.4G). Previous research suggests that TREM2 is critical for promoting microglia proliferation and inhibiting apoptosis [12, 38-40]. We hypothesized that the significant reduction in macrophages following Trem2 knockout could be due to inhibited proliferation and activated apoptosis. To test this hypothesis, we examined the impact of TREM2 on macrophage proliferation and apoptosis, finding that Trem2 knockout significantly inhibited macrophage proliferation in OPC (Extended Data Fig.5C) and promoted apoptosis (Extended Data Fig.5D). Immunofluorescence results also showed a propensity for promoted apoptosis and inhibited proliferation in the OPC infection sites lacking Trem2 (Extended Data Fig.5E). In summary, our study has identified that TREM2 influences the proliferation and apoptosis of macrophages in OPC tissues, which significantly reduces the number of TNF-α-secreting macrophages, thereby decreasing the levels of TNF-α within the tissue. Regulation of TNF-α secretion by TREM2 confers protection in OPC TNF-α plays a pivotal role in systemic fungal infections, and studies suggest that deleting Tnf in vivo increases susceptibility to OPC in mice [41]. We administered TNF-α monoclonal antibodies to WT mice, which did not affect their body weight (Extended Data Fig.6A), but resulted in significantly lower body weight on days 1 and 2 post- C. albicans infection (Extended Data Fig.6B), along with increased fungal burden (Extended Data Fig.6C), and more severe epithelial invasion (Extended Data Fig.6D). These findings implied that the decrease in TNF-α levels in tissues due to Trem2 deficiency may be a contributing factor to increased susceptibility to OPC. To test this hypothesis, we restored TNF-α in the Trem2 -deficient OPC model and observed that although this restoration did not significantly reverse the weight loss caused by Trem2 deficiency (Extended Data Fig.6E), it completely reversed the susceptibility to OPC (Extended Data Fig.6F, G). This evidence corroborated that TREM2 exerted a protective role in OPC by modulating the secretion of TNF-α. Modulation of macrophage inflammatory response by TREM2-mediated TNF-α secretion Inflammatory cytokines, chemokines, antimicrobial peptides, and defensins are critical for the clearance of fungi, recruitment of immune cells, and regulation of their functions. TNF-α serves as a potential regulator of inflammatory cytokines, and its deficiency leads to a marked suppression of inflammatory activity. In our in vitro co-culture of BMDMs with C. albicans , we discovered that the absence of Trem2 significantly inhibited the expression of Tnf , Il6 , Il23 , S100a8 , S100a9 , Defb1, Cxcl1 , Cxcl2 , Ccl2 , Ccl7 , and S100a7a (Extended Data Fig.6H and Extended Data Fig.7A). Exogenous supplementation of TNF-α was able to reverse these differences (Extended Data Fig.6H and Extended Data Fig.7A). The expression of these genes is primarily regulated by inflammatory pathways, and we found that Trem2 deficiency notably inhibited the activation of NF-κB's P65 subunit and the degradation of IκBα (Extended Data Fig.7B), as well as the activation of Syk (Extended Data Fig.7B), and suppressed the activity of the MAPK pathway's P38 (Extended Data Fig.7C). The supplementation of exogenous TNF-α reversed these deficiencies. Although PI3k/Akt is a downstream signal of TREM2, in the context of C. albicans infection, TREM2 did not rely on this pathway (Extended Data Fig.7D). In conclusion, we have elucidated that TREM2 is capable of modulating the secretion of TNF-α, thereby amplifying the inflammatory signaling response in the context of C. albicans infection. Regulation of Th17 cell differentiation by TREM2 via TNF-α IL-17 is essential for combating OPC, predominantly produced by Th17 cells, innate lymphoid cells (ILCs), and γδT cells. The absence of Trem2 suppressed the expression of Tnf, Il6, and Il23 , cytokines that induce Th17 differentiation [42-44], leading us to postulate that Trem2 deficiency may also affect Th17 cells in OPC. To verify this hypothesis, we assessed the immune cells secreting IL-17, IL-17F, and IL-22 in the tongues of mice. The results showed that Trem2 deficiency significantly inhibited the proportion of Th17 cells without affecting other IL-17-secreting immune cells (Extended Data Fig.8A), indicating a specific impact of TREM2 on Th17 cells. Trem2 deficiency also significantly reduced the proportions of IL-17F-producing Th17, CD4 - αβT cells, and ILCs (Extended Data Fig.8B), and even the secretion of IL-22 by Th22 and CD4 - αβT cells was notably suppressed (Extended Data Fig.8C). Also, in contrast to WT, Trem2 -/- mice demonstrated a markedly diminished secretion of IL-17 in their lingual supernatant (Extended Data Fig.7E). Interestingly, Trem2 deficiency unexpectedly resulted in increased neutrophil infiltration (Extended Data Fig.8D), possibly due to the increased fungal burden, as systemic infection studies have found that more C. albicans can lead to increased neutrophil infiltration, with neutrophil levels seemingly scaling with fungal load [45, 46]. Trem2 deficiency also significantly suppressed Th1 infiltration (Extended Data Fig.8E), while IFN-γ is not essential in OPC since mice lacking IFN-γ or the IL-12 subunit IL-12p35 do not exhibit increased susceptibility to OPC [47, 48]. Trem2 deficiency did not affect the infiltration of dendritic cells (DCs), eosinophils, or mast cells at the site of infection (Extended Data Fig.8F). Subsequent studies revealed that administration of TNF-α monoclonal antibodies markedly reduced the populations of IL-17-producing Th17 cells (Extended Data Fig.8G), Th17 cells secreting IL-17F (Extended Data Fig.8H), as well as Th22 and CD4 - αβT cells that produce IL-22 in OPC (Extended Data Fig.8I). To conclusively validate that TREM2 influences Th17 cell differentiation through TNF-α, we undertook a co-culture experiment. Naïve CD4 + T cells were incubated with supernatant derived from BMDMs stimulated with C. albicans . We found that Trem2 knockout significantly inhibited Th17 cell differentiation (Extended Data Fig.9A) and the secretion of IL-17F by CD4 + T cells (Extended Data Fig.9B), which could be reversed with exogenous TNF-α. In summary, the data confirmed that TREM2 modulated the secretion of TNF-α, impacting Th17 differentiation to regulate IL-17 signaling. TREM2 regulates macrophage and neutrophil killing abilities through TNF-α Macrophages contribute to the clearance of C. albicans through phagocytosis, killing, and ROS production, while neutrophils also produce NETs to kill fungi. TNF-α regulates these functions of macrophages and neutrophils [49, 50]. The single-cell analysis also indicated that TNF-α secreted by TREM2 + macrophages acted upon both macrophages and neutrophils (Extended Data Fig.3C, D). Indeed, Trem2 deficiency significantly inhibited macrophage phagocytosis (Extended Data Fig.9C), killing ability (Extended Data Fig.9D), and ROS production (Extended Data Fig.9G), with exogenous TNF-α reversing these functional deficits. To clarify if Trem2 deficiency attenuated the killing ability of neutrophils due to decreased TNF-α, we co-cultured neutrophils with supernatant obtained from BMDMs that had been stimulated with C. albicans. Consistent with the regulation of macrophage functions by TNF-α, we found that Trem2 knockout inhibited neutrophil phagocytosis of C. albicans (Extended Data Fig.9E), killing (Extended Data Fig.9F), and ROS production (Extended Data Fig.9G). Trem2 knockout also significantly inhibited NETs at the site of infection (Extended Data Fig.9H), a deficit also observed in tongue tissues treated with TNF-α monoclonal antibodies (Extended Data Fig.9I). The NETs deficiency caused by Trem2 knockout could be reversed by supplementing TNF-α (Extended Data Fig.9J). In the in vitro setting, neutrophils co-cultured with supernatant from BMDMs demonstrated a significant inhibition in the production of NETs following Trem2 knockout. This reduction in NETs production could be counteracted by the addition of exogenous TNF-α (Extended Data Fig.9K). In conclusion, we demonstrated that TREM2 influenced the fungicidal functions of macrophages and neutrophils by regulating TNF-α. TREM2 recognition of candidalysin initiates TNF Signaling TREM2, as a receptor, is capable of recognizing a variety of ligands, including a wide range of anionic molecules that are free, can bind to cell membranes, and include components from both Gram-positive and Gram-negative bacteria (such as Neisseria Gonorrhoeae , Escherichia coli , and Staphylococcus aureus ), DNA, lipoproteins, and phospholipids [12, 51]. Building on our findings, we observed that Trem2 deficiency presented similar impairments to PRR deficiencies, leading to compromised antifungal inflammatory responses, including signal pathway deficiencies (Extended Data Fig.6H and Extended Data Fig.7A-C). This led us to propose that TREM2 might be involved in the recognition of C. albicans . To test this hypothesis, we co-incubated the extracellular segment of TREM2 with both spore and hyphal forms of C. albicans and found that both human and mouse TREM2 recognized only the hyphal form of the fungus, not the yeast form (Fig.3A, B), suggesting the presence of PAMPs on the hyphae recognized by TREM2. To determine the specific PAMPs recognized by TREM2, we incubated its extracellular domain with various PAMPs. Previous research has identified that TREM2 can recognize sphingolipid [52], which are abundantly present on the cell membrane of fungi. Here, we have also purified C. albicans sphingolipid to investigate whether TREM2 is involved in the recognition of fungal surface sphingolipids. Finally, we discovered that human and mouse TREM2 could engage with multiple PAMPs (LPS, a known ligand of TREM2, served as a positive control in the study) but mainly recognized candidalysin (Fig.3C, D), the first acknowledged classical virulence factor of C. albicans [53, 54]. After infection, C. albicans forms hyphae, which induce the expression of the ECE1 gene, coding for Ece1p [55, 56]. Ece1p is then processed by Kex2p to produce immature candidalysin, which is finally secreted by the hyphae after Kex1p removes the terminal R93 to generate mature candidalysin (SIIGIIMGILGNIPQVIQIIMSIVKAFKGNK) [54, 57, 58]. This revealed why TREM2 only recognized the hyphal form of C. albicans and not the yeast form. Immunofluorescence also showed that candidalysin could co-localize with TREM2 on THP-1 cells (Fig.3E), and overexpression of TREM2 in 293T cells with candidalysin confirmed that TREM2 could bind to candidalysin (Fig.3F). In the absence of Trem2 , the recognition of candidalysin by BMDMs was significantly inhibited (Extended Data Fig.10A). These multifaceted results affirmed that TREM2 could directly bind and recognize candidalysin. When PAMPs bind to their receptors, they induce an inflammatory signal response. Does the recognition of candidalysin by TREM2 also trigger such signaling activation? To address this question, we stimulated BMDMs with candidalysin and found that it could induce the activation of P65, but this activation was suppressed in the absence of Trem2 (Extended Data Fig.10B, C), with the regulation of Tnf expression consistent with P65 activity (Extended Data Fig.10D). Other PAMPs, only zymosan had a similar effect (Extended Data Fig.10E), indicating that TREM2 could recognize candidalysin and zymosan to provoke an inflammatory response. Given the significant role of candidalysin and the primary recognition of it by TREM2 (Fig. 3A-D), we investigated the specific binding sites of TREM2 for candidalysin. Employing AlphaFold, DeepMind's AI-powered tool for predicting protein 3D structures from amino acid sequences, we modeled the interaction between the extracellular domain of human TREM2 and the fungal toxin candidalysin. Following this, protein docking with haddock 2.4 identified that the highest scoring interactions (Select the intersection of the top-scoring results from two rounds of molecular docking) showed TREM2 binding to candidalysin's G65, N73, and N91-N92 (located on a loop structure) (Extended Data Fig.10F). To confirm the specificity of TREM2 for these sites, we mutated or deleted them (Extended Data Fig.10G), and found that mutations and deleting the loop site significantly inhibited the recognition of candidalysin by human and mouse TREM2 (Extended Data Fig.10H). The mutations at these amino acid sites do not alter the early activity of the early NF-kB signaling pathway (Extended Data Fig.10I); however, as time progresses, there is a significant suppression of the NF-kB signal (Extended Data Fig.10J), suggesting that these site mutations lead to an inability of TREM2 to form a stable, long-term binding structure with candidalysin. Candidalysin's identified sites correspond to TREM2's D131, R136, and P169 (Extended Data Fig.10F). Mutating these sites in TREM2 and then overexpressing it in 293T cells with candidalysin showed that the mutations in TREM2's D131, R136, and P169 significantly inhibited the recognition of candidalysin by TREM2 (Fig.4A-C). It is noteworthy that mutations at the N73, G65, and N91-N92 residues of candidalysin markedly impaired its interaction with TREM2 (Fig.4A-C). This finding underscores the critical role these residues play in the molecular recognition processes of TREM2. Together these findings ascertain that the residues D131, R136, and P169 of TREM2 are involved in recognizing the candidalysin sites G65, N73, and N91-K92. TREM2 activates NF-κB via the DAP12/Syk axis to regulate the secretion of TNF-α TREM2 recognized its ligand, leading to the recruitment and activation of the adaptor proteins DAP10 and DAP12 [15]. This process activated downstream signaling pathways, notably Syk and PI3k/Akt [15]. Previous research had established that DAP12 primarily activates the Syk pathway, while DAP10 is associated with activating PI3k/Akt [12, 59]. In our study, we found that TREM2's recognition of C. albicans predominantly stimulated the Syk pathway (Extended Data Fig.7B), but not the PI3k/Akt pathway (Extended Data Fig.7D), suggesting an interaction between TREM2 and candidalysin via DAP12. Our experimental findings supported this hypothesis. Upon stimulation with candidalysin, there was a significant aggregation of DAP12 in the vicinity of TREM2, unlike DAP10, which did not show a notable increase (Fig.4D, E). This indicated that TREM2's engagement with candidalysin primarily involved DAP12, leading to downstream signaling activation. Moreover, selectively diminishing Dap12 expression, rather than Dap10 , significantly decreased the Syk activation triggered by candidalysin (Extended Data Fig.11A). Given that Syk acts upstream of NF-κB [60, 61], reducing Dap12 expression or directly inhibiting Syk significantly hindered the activation of the NF-κB subunit P65 (Extended Data Fig.11A, B). NF-κB is known for its critical role in the regulation of inflammatory mediators including TNF-α, IL-6, chemokines, and antimicrobial proteins during infection [62]. The knockdown of Dap12 or the inhibition of Syk both significantly suppressed the expression of Tnf (Extended Data Fig.11C, D). Thus, we concluded that TREM2's recognition of candidalysin prompted an immune response through the DAP12/Syk axis, which then activated the NF-κB signaling pathway. This activation regulated TNF-α secretion, orchestrating an effective inflammatory and immune response in the context of OPC. TREM2 agonist Hsp60 exhibits therapeutic effects in CA-induced OPC CA-induced OPC is commonly seen in clinical settings, and our scRNA-seq data also indicated a significant reduction in the proportion of TREM2 + macrophages in the CA-induced OPC model (Fig.1F), suggesting that CA might suppress TREM2 + macrophages, contributing to OPC susceptibility. Indeed, in the CA-induced OPC model, we observed fewer TREM2 + TNF-α + macrophages at the infection site on day 1 (Extended Data Fig.12A), and by day 3, these cells were completely undetectable (Extended Data Fig.12B). Flow cytometric analysis also showed that CA inhibited Ly6C + TREM2 + macrophages (Extended Data Fig.12C) and Ly6C + TREM2 + TNF-α + macrophages (Extended Data Fig.12D). Hsp60, as a specific TREM2 ligand agonist used to stimulate TREM2 activity [63-65], may have therapeutic potential in OPC. Although CA significantly reduced the number of TREM2 + macrophages (Extended Data Fig.12A-D), a subset of TREM2 + macrophages remained in the lingual tissue (Extended Data Fig.12C, D), providing a basis for using Hsp60 to stimulate TREM2 as a treatment for CA-induced OPC. We explored the therapeutic effects of Hsp60, TNF-α, and soluble TREM2 (sTREM2) in a CA-induced OPC model. The results showed no difference in body weight between the mice on days 1 and 2 of the model (Extended Data Fig.12E), but on day 3, mice treated with Hsp60 had higher body weight compared to controls (Extended Data Fig.12F), suggesting potential phenotypic differences at this time point. On day 3, the Hsp60 and TNF-α treatment groups exhibited lower fungal burdens and milder C. albicans epithelial invasion and damage (Extended Data Fig.12G, H). However, we did not observe a therapeutic effect from sTREM2 (Extended Data Fig.12E-H), and in vitro stimulation of BMDMs with sTREM2 did not reverse the suppression of the NF-kB pathway caused by Trem2 deficiency (Extended Data Fig.13A, B), reflecting that TREM2 mainly exerts its function through receptor-mediated inflammation rather than in a soluble form. To confirm that Hsp60 mediated its therapeutic effects through TREM2, we treated Trem2 -deficient BMDMs with Hsp60 in vitro and found that Hsp60 could enhance the expression of Tnf in WT BMDMs, but this enhancement was ineffective in the absence of Trem2 (Extended Data Fig.13C). Similarly, we found that Hsp60 induced Th17 differentiation (Extended Data Fig.13D) and enhanced macrophage phagocytosis and killing of C. albicans (Extended Data Fig.13E, F) through TREM2. In conclusion, we have determined that the TREM2 agonist Hsp60 can have therapeutic effects in CA-induced OPC by activating TREM2 function. Discussion Different PRRs play a critical role in the recognition of C. albicans during systemic infections, but they are not as pivotal in OPC [66]. For instance, dectin-1 is indispensable for recognizing systemic infections caused by C. albicans [67], yet it is not crucial in OPC [68], and the expression level of CLEC7A may even be reduced in OPC [69]. Recent studies have discovered that epithelial cells can identify C. albicans through EphA2 and EGFR [2, 3]. The EphA2 on epithelial cells and neutrophils can recognize β-glucan, leading neutrophils to produce ROS to kill C. albicans [2]. Meanwhile, EGFR can recognize C. albicans ' Als3 and form a complex with EphA2 [3]. Research has also found that candidalysin can activate EGFR phosphorylation, although EGFR does not directly bind and recognize candidalysin [54, 70]. Indeed, to date, no receptor has been identified that directly recognizes candidalysin. This gap in our understanding highlights a critical area of exploration within the field of fungal immunology. The identification of such a receptor would be a significant advancement, providing new insights into the molecular mechanisms that underpin the immune system's ability to detect and respond to this pathogen. Notably, we have demonstrated that TREM2 recognized candidalysin, initiating a cascade of inflammatory responses essential for protective immunity. This recognition process appeared to be highly specific, involving key residues on TREM2 that interacted with particular sites on candidalysin, thus affirming the precision of innate immune receptors in pathogen detection. Previous research into OPC has been constrained by technological limitations, often focused narrowly on specific cells without a comprehensive exploration of the interplay between immune cells. The advent of scRNA-seq technology has now surmounted these challenges, enabling us to elucidate the intricate interactions between TREM2 and TNF-α signaling pathways that are crucial for both the innate and adaptive immune responses against C. albicans in OPC. Our study had detailed how TREM2, upon recognizing C. albicans , triggered macrophage activation of the Syk kinase, which subsequently activated the P65 subunit to regulate the secretion of TNF-α. TNF-α, in turn, acted in an autocrine manner on macrophages and a paracrine fashion on neutrophils to modulate the fungicidal functions of these innate immune cells. This regulation was vital for the host's first line of defense, coordinating the killing and phagocytic capacities required to counteract fungal pathogens effectively. Additionally, TREM2's role in shaping the differentiation of Th17 cells via TNF-α has been highlighted, suggesting an important connection between innate and adaptive immunity. This cross-talk between immune cells was likely instrumental in orchestrating a full-spectrum immune response, enabling not only the initial clearance of the pathogen but also the development of long-term immunity. Our findings extended the functional repertoire of TREM2 beyond its previously understood roles in neurodegenerative diseases and metabolic disorders [12, 59, 71-76], positioning it as a central player in immune responses against fungal infections. The therapeutic potential of TREM2 agonists like Hsp60 in CA-induced OPC models demonstrated the translational relevance of our discoveries. This agonist may rejuvenate impaired immune responses, thus offering a promising therapeutic avenue for conditions characterized by immune suppression or dysregulation. In conclusion, our research underscored the critical role of TREM2 in the immune response to OPC, providing a foundation for future investigations aimed at harnessing this receptor for clinical benefit. The interplay between TREM2 and TNF-α was a testament to the complexity and elegance of the immune system, and further exploration of this axis may yield significant advancements in our fight against fungal pathogens. Methods Materials availability The present research did not result in the creation of any novel reagents. All antibodies, primers, and reagents have been integrated into a table with corresponding product numbers (Supplementary Table 4). Data availability The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive (Genomics, Proteomics & Bioinformatics 2021) in National Genomics Data Center (Nucleic Acids Res 2022), China National Center for Bioinformation / Beijing Institute of Genomics, Chinese Academy of Sciences (GSA: CRA014588) that are publicly accessible at https://ngdc.cncb.ac.cn/gsa. Additionally, this paper includes an analysis of pre-existing data that is publicly available at the COVID-19 Cell Atlas website (https://www.covid19cellatlas.org/). Code availability This paper does not report original code. Detailed information about software used in this manuscript is provided in the Supplementary Table 4. Any additional information required to reanalyze the data reported in this paper will be made available from the lead contact upon request. OPC model The construction of the mouse OPC model was based on previously reported methods in the literature [6, 29, 47, 77]. Three days before infection, a monoclonal culture of C. albicans (SC5314) was transferred into 10 ml of YPD liquid medium and incubated at 30°C on a shaker. On the second day, 100 μl of the culture was transferred to fresh 10 ml of YPD liquid medium for overnight incubation, a step that was then repeated once more. Both WT and Trem2 -/- (1-4773) mice, sourced from cyagen and of the C57BL/6 background, were used in the experiments. Littermate control mice were matched for sex, age, and weight. One day before infection, mice were weighed and each mouse was injected with 225 mg/kg of cortisone acetate. The cortisone acetate was suspended in saline containing 0.05% Tween 80 and homogenized with vortexing or sonication for one minute (as cortisone acetate is not water-soluble, it was frequently vortexed for homogenization prior to injection). The non-immunosuppressed model did not involve the aforementioned injection. Overnight-cultured C. albicans spores were centrifuged at 1000 g for 5 minutes, the supernatant was discarded, and the spores were washed twice with PBS. Ultimately, the spores were reconstituted in 1 ml of HBSS (Thermo Fisher) medium. To induce OPC, 0.0025g cotton balls, saturated with either 10 7 CFU C. albicans yeast or HBSS (serving as uninfected controls), were administered sublingually for a duration of 75 minutes while the mice were under general anesthesia. Preparation of single-cell suspensions from tongue tissue Single-cell suspensions were generated from whole tongue tissues using an established protocol [78]. In summary, the tongue tissue was finely chopped and incubated in a 10 ml enzymatic digestion mixture. This mixture comprised 385 U/ml collagenase type IV (YEASEN), 2 U/ml dispase II (Gibco), and 50 μg/ml DNase I (Solarbio) in RPMI medium (Gibco). The tissue-digestion mixture was then incubated at 37°C in a shaking water bath for 45 minutes. To halt the digestion process, PBS supplemented with 5 mM EDTA (Quality Biological) was added, and the mixture was subsequently cooled on ice. The resulting cell suspension was filtered through a 70-μm mesh, followed by washing and further filtration through a 40-μm mesh before a final wash. The single-cell suspension was centrifuged at 1000 rpm for 5 minutes, followed by erythrocyte lysis using 1X red blood cell lysis buffer (Thermo Fisher) for 5 minutes. After lysis, the cells were washed and dead cells were removed using dead cell removal magnetic beads (Miltenyi) according to the manufacturer's instructions to further purify the sample. The final single-cell preparation was then used for library construction with the 10X Genomics platform for single-cell sequencing. ScRNA-seq analyses The various datasets were initially assembled into counts data using CellRanger (version 5.0.0) with reference genome data for mouse (mm10) and human (GRch38). Post assembly, the Seurat package (version 4.0.6) with the IntegrateData function was employed to integrate different datasets. As the mouse data was generated by our research group, minimal batch effects were observed, and the IntegrateData function of Seurat was sufficient to correct for these effects. Following the integration, all single-cell data underwent classical Seurat pipeline analysis [79]. Initially, the proportion of mitochondrial genes detected in each cell was calculated. Cells with a high mitochondrial gene ratio and outliers (cells with >100 genes detected, total gene expression >500, and mitochondrial gene proportion <25%) were filtered out using the subset function. Quality control of single-cell data was then followed by normalization using the NormalizeData function in Seurat. The FindVariableFeatures algorithm was utilized to identify highly variable genes, which are indicative of the biological characteristics of each cell group and provide references for cell clustering. This was followed by data scaling using the ScaleData function. PCA clustering analysis was performed using the RunPCA function, and the final cell subgroups were determined using the RunUMAP, FindNeighbors, and FindClusters functions. Cell subgroups were annotated using the FindAllMarkers function, primarily based on the expression of cell markers specific to each cell group in both mouse and human samples. The expression of these cell markers in each cell subgroup was visualized using the pheatmap package (version 1.0.12). Cell communication was analyzed using the cellchat package (version 1.5.0). Pathway analysis between different cell subgroups was conducted using the ClusterGVis package (version 0.1.1). The Rmagic package (version 2.0.3) was employed to impute and fill in missing values for conducting correlation analyses. Determination of fungal burden in tongue tissues Following euthanasia, the mice's tongues and associated oral tissues were excised and weighed. The tissues were then cut using sterile scissors, homogenized in saline, and subsequently diluted with sterile PBS (Thermo Fisher). Homogenates of the tissues at various dilutions were plated on YPD agar plates. These plates were incubated at 37°C in a fungal incubator for 24-48 hours, after which colony counts were conducted to assess fungal burden. Histological analysis of tongues To conduct immunofluorescence staining of mouse tongue tissues, researchers first euthanized the mice and excised the tongue and related oral tissues. They fixed the tissues in 4% paraformaldehyde (Solarbio) for 24 hours at 4°C, then rinsed them in PBS (Thermo Fisher) to remove excess fixative. They proceeded to embed the tissues in paraffin and sectioned them at 5-10 μm thickness. The sections were deparaffinized in xylene, rehydrated through a series of graded alcohols, and antigen retrieval was performed in a citrate buffer (Solarbio). After blocking non-specific binding with a suitable blocking solution, the sections were incubated with primary antibodies specific to the target proteins overnight at 4°C. Following primary antibody incubation, the sections were washed in PBS and incubated with fluorophore-conjugated secondary antibodies for an hour at room temperature in the dark. Optionally, DAPI (Abcam) was applied for nuclear staining, then the sections were mounted with an anti-fade mounting medium. The sections were examined under a fluorescence microscope and images were captured, which were analyzed with image analysis software to quantify fluorescence intensity or colocalization. At predetermined intervals following infection, the tongues of the mice were extracted and immersed in 10% buffered formalin (Solarbio) for overnight fixation. The formalin was then drained and substituted with 70% ethanol. The processes of paraffin embedding, sectioning, and Periodic acid-Schiff staining were executed using a reagent kit (Solarbio) as per the manufacturer's instructions. Murine bone marrow reconstitution experiment Recipient mice, 6 weeks of age, were pre-conditioned with acidified water containing antibiotics (pH 2.5-3, hydrochloric acid (Solarbio), neomycin sulfate (Solarbio) 2 mg/mL) for 5 days prior to the experiment. For irradiation, 6-week-old mice were placed in a sterile container and exposed to 10 Gy radiation, followed by a rest period of 2-3 hours in their cages. Eight-week-old donor mice were euthanized, immersed in 75% alcohol, and then transferred to a biosafety cabinet for sterile processing. Femurs and tibias were isolated, stripped of residual muscle, and rinsed in PBS (Thermo Fisher). Bones were soaked in 75% alcohol in a six-well plate for 5 minutes and then transferred to PBS containing 2% penicillin/streptomycin (Gibco). Both ends of the bones were snipped off, and the bone marrow cavity was flushed with DMEM (Gibco) containing 3% inactivated FBS and 2% penicillin/streptomycin. The bone marrow was then expelled, centrifuged at 1500 rpm for 5 minutes, and the pellet was collected. The pelleted bone marrow cells were resuspended in 3 mL of red blood cell lysis buffer (Thomas Scientific) and subsequently filtered through a mesh. After lysis, the bone marrow cells were centrifuged at 4°C, 4000 rpm for 5 minutes, the supernatant was discarded, and cells were washed twice with 10 mL PBS. Cells were then resuspended in PBS. Recipient mice were intravenously injected with 1×10 7 hematopoietic stem cells from the donor mice via the tail vein. Post-injection, recipient mice continued to be fed acidified water with antibiotics, which was changed twice a week, and the bone marrow reconstitution was allowed to proceed for 2 weeks. Production of BMDMs Bone marrow cells were harvested from the femurs and tibias of male C57BL/6 mice aged 6 to 8 weeks. The process involved flushing out bone marrow cells using sterile DMEM (Gibco), followed by the elimination of red blood cells via Red Blood Cell Lysis Buffer (Thomas Scientific). The cells were then cultured for 7 days in a medium containing 20% L929 conditional medium, supplemented with 10% FBS (Gibco), 100 mg/mL streptomycin, and 100 U/mL penicillin (Gibco), as outlined in previous studies. Post 7 days, the BMDMs were harvested and plated overnight in DMEM. Subsequently, these cells were subjected to various treatments as specified in individual experiments. qPCR detection RNA extraction was performed using NucleoZOL (Macherey Nagel). Subsequently, cDNA synthesis was carried out using the 1st Strand cDNA Synthesis Kit from Takara. Real-time PCR analysis was conducted utilizing the TB Green Premix Ex Taq ROX plus kits (Takara). The resulting data were normalized against Gapdh expression. In experiments designed to evaluate the impact of TNF-α on immune cells, the cells were treated with 20 ng/mL TNF-α (PeproTech) for 6 hours prior to infection with C. albicans . Immunoblot analysis Cells underwent lysis in RIPA buffer (Beyotime), supplemented with both protease and phosphatase inhibitors from Beyotime. Protein quantification was performed utilizing the BCA Kit (Thermo Scientific). Equal amounts of proteins were resolved via SDS-PAGE, followed by their transfer onto PVDF membranes (Millipore). The membranes were then blocked using 5% skim-fat milk (Solarbio) for one hour and subsequently incubated with primary antibodies. This step was followed by the application of HRP-conjugated secondary antibodies and enhancement with ECL reagent (Absin). The chemiluminescent images thus obtained were documented using the ChemiDoc Touch Imaging System provided (Bio-Rad). Detection of immune cell infiltration Mice were euthanized one day after infection, and tongue tissues were collected. Single-cell suspensions were prepared using the aforementioned method. Subsequent experiments were conducted using different strategies. For non-secretory cytokine-producing cells: Fc receptors were blocked followed by staining with various markers for 30 minutes. After one wash, cells were filtered through a 40μm mesh. Live/dead cells were distinguished using LIVE/DEAD markers (Thermo Scientific) in a flow cytometer. Within the live cell population, immune cell subtypes including CD45 + Ly6G + CD11b + (Neutrophils), CD45 + Ly6C + CD11b + Ly6G – MHCII – F4/80 - (Monocytes), CD45 + CD11b + F4/80 + (Macrophages), CD45 + MHCII hi F4/80 – CD11c hi (Dendritic Cells), CD45 + MHCII – F4/80 - Ly6G – SSC hi CD170(Siglec-F + ) (Eosinophils), and CD45 + ckit + FceR1 + (Mast cells) were identified. For secretory cytokine-producing cells: After red blood cell lysis, cells were incubated with a cell stimulation cocktail (Thermo Fisher) at 37°C for 5 hours, followed by Fc receptor blocking and surface marker staining. After washing, cells were fixed and permeabilized using fixation/permeabilization solution (BD Bioscience). Post-permeabilization, cells were stained with cytokine antibodies for 30 minutes, washed, and then filtered through a 40μm mesh. Finally, within the live cell population in the flow cytometer, subtypes including CD45 + CD3 + γδTCR + IL-17A + (γδT cells), CD45 + CD3 + CD4 + γδTCR - IL-17A + (Th17), CD45 + Lineage - CD90.2 + CD127 + IL-17A + (ILCs), and CD45 + CD3 + CD4 + IFN-γ + (Th1) were determined. Assessment of uptake and killing Two six-well plates were prepared, each well seeded with 5×10 5 corresponding cells. The prepared C. albicans spore suspension was added to the cell culture plates at a spore-to-cell ratio of 10:1 and co-incubated at 37°C for 30 minutes. After 30 minutes of incubation, both six-well plates were washed three times with sterile PBS. For one of the plates, cells in each well were lysed with 1 mL of sterile water, using vigorous pipetting to ensure complete cell lysis. A tenfold serial dilution of the lysate was performed, taking 100 μL for plating on YPD agar, and incubated at 37°C for 2 days. The resulting colonies were counted as uptake index and as the baseline fungal burden for the cell killing assay. Simultaneously, to the other six-well plate, 1 mL of complete medium was added, and incubation continued for an additional 2 hours. The supernatant was discarded and the wells were washed three times with PBS (Thermo Fisher). The cells in each well were lysed with 1 mL of sterile water as described above, plated on YPD agar, and incubated at 37°C for 2 days before counting. The bactericidal efficiency was calculated as follows: Killing efficiency = (1 - (CFU at 2 hours / CFU at 30 minutes)) × 100%. Detection of ROS In a 12-well plate, each well was seeded with 1×10 6 macrophages. After allowing sufficient time for the cells to adhere, C. albicans was added to stimulate the cells according to the specific experimental objectives. The cell culture medium was then discarded, and the cells were washed three times with serum-free medium. DCFH-DA (Beyotime) was diluted in serum-free medium at a 1:1000 ratio to achieve a final concentration of 10 μmol/L, and 500 μL of the diluted DCFH-DA solution was added to each well. The cells were incubated at 37°C for 20 minutes. The cells were then washed three times with serum-free medium to thoroughly remove any DCFH-DA that had not entered the cells. The cells were digested and resuspended as single-cell suspensions. Finally, the fluorescence intensity was measured using a spectrophotometer with an excitation wavelength of 488 nm and an emission wavelength of 525 nm. Isolation of neutrophils from bone marrow Neutrophils were isolated according to the instructions provided with the separation kit (Solarbio). Briefly, the cell suspension was layered over the separation solution. Centrifugation was performed at room temperature using a horizontal rotor at 500g for 30 minutes. Post-centrifugation, neutrophils in the lower layer of the centrifuge tube were aspirated, followed by washing the cells with 10 mL PBS (Thermo Fisher) or cell washing solution. The cells were then centrifuged at 250g for 10 minutes, followed by red blood cell lysis and subsequent washing centrifugation. The supernatant was discarded, and the cells were resuspended in 5 mL PBS or cell washing solution, followed by centrifugation at 250g for 10 minutes. The isolated neutrophils were co-cultured with supernatant from BMDMs. The BMDMs were incubated with C. albicans for a 24-hour period, with the experimental conditions including either the administration of 10 ng/mL of TNF-α (PeproTech) or its omission. After co-culture, neutrophils were collected for uptake, killing, and ROS production assays as described above. Co-culturing Naive CD4 + T Cells with the Supernatant from BMDMs Following the euthanasia of the mice, spleens were collected for cell isolation. Single-cell suspensions were prepared by employing a filtration technique. Naive CD4 + T cells were isolated using cell microbeads (Miltenyi) as per the protocol provided by the manufacturer. These cells, at a concentration of 5×10 5 , were co-cultured with the supernatant from BMDMs. The BMDMs were stimulated with C. albicans for 24 hours, accompanied by either the addition or absence of 10 ng/mL of TNF-α (PeproTech). During the co-culture period, the cells were stimulated with 2 μg/mL plate-bound anti-CD3 antibody (Bioxcell), and in the solution, 1 ng/mL TGF-β1 (PeproTech), 1 μg/mL anti-CD28 antibody (Bioxcell), 10 μg/mL anti-IFN-γ antibody (Bioxcell), and 10 μg/mL anti-IL-4 antibody (Bioxcell) were added. IL-6 and IL-23 were not additionally supplemented. Following the incubation period, the medium was aspirated and the cells were centrifuged. The cells were then stimulated with a cell stimulation cocktail (Thermo Fisher) for 5 hours before flow cytometric analysis of Th17 cells. Binding experiment For flow cytometry analysis, the method previously reported was employed [80]. In brief, spore or hyphal forms of C. albicans were incubated in 1–3% bovine serum albumin (BSA) in PBS, to which His-tagged proteins were added until reaching a final concentration of 5 μg/ml. This was followed by a 4-hour incubation at 4 °C. The fungal particles were then washed in fluorescence-activated cell sorting (FACS) buffer (0.5% BSA and 2 mM EDTA in PBS). The bound His-tagged proteins were detected using a PE-conjugated donkey anti-His antibody (BioLegend). The samples were then fixed in 1% formaldehyde (Solarbio) and subjected to analysis. For the ELISA assays [80], cell fractions were coated onto wells overnight at a concentration of 500 μg/ml (50ug/well), followed by blocking with 5% BSA in PBS (100μl/well). His-TREM2 at a concentration of 10μg/ml was then added to the wells and incubated for 2 hours at 37℃. The wells were subsequently washed with PBS containing 0.5% (v/v) Tween-20. His tag antibody (HRP) (Sino Biological) was added and incubated for an additional hour at 37℃. Following additional washing, the binding of His-TREM2 was quantified using an ELISA kit as recommended by the manufacture (Multi sciences). The reaction was terminated with stop solution, and the optical densities were measured at 450 and 630 nm by Varioskan LUX (Thermol scientific). Production of candidalysin mutant peptides All mutant candidalysin peptides were synthesized by Shanghai Chu Peptide Biotechnology. Protein in vivo study Starting from day 0, mice were injected every other day with 100 ng of Hsp60 (MedChemExpress), TNF-α (MedChemExpress), or 1 μg sTREM2 (Novoprotein). Implementing oral candidiasis modeling using the aforementioned immunomodulatory methods. Immunoprecipitation The target gene sequence was cloned into the pCDH-CMV plasmid, which was subsequently transfected into 293T cells using Lipofectamine 3000 (Thermo Fisher) according to the manufacturer's instructions. 48 hours post-transfection, cells were lysed using RIPA buffer (CST) for total protein extraction and then subjected to a 3-hour incubation with 1 mg of the respective antibodies. This was followed by a 6-hour incubation with Protein A/G beads (Santa Cruz Biotechnology) at 4°C. The proteins were then eluted with a protein loading buffer and heated for 10 minutes at 95°C. Subsequently, the samples were processed for immunoblot analysis as described above. Gene knockdown experiment BMDMs were seeded in 6-well plates at a density of 1 × 10 6 cells per well. A mixture of 10 µL siRNA (100 pmol/mL) and 10 µL Advanced DNA RNA transfection reagent (Zeta Life) was prepared and incubated at room temperature for 15 minutes to allow complex formation. This mixture was then added to the wells containing 1 ml of normal DMEM medium (Gibco). 48 hours later, cells were lysed using RIPA buffer (CST), followed by protein extraction. Immunoblot analysis was then conducted as described above. Sphingolipid extraction The extraction of sphingolipids from C. albicans can be described utilizing an established methodology [81]. Initially augment fungal cell extracts or freeze-dried media with appropriate internal standards. Start with a primary extraction using the Mandela extraction buffer comprising a mixture of ethanol, deionized water, diethyl ether, and pyridine, supplemented with ammonium hydroxide in a specific volumetric ratio (ethanol: dH2O: diethylether: pyridine:4.2NNH4OH; 15:15:5:1:0.018; v/v). Follow this with a secondary Bligh and Dyer extraction employing methanol and chloroform. At this juncture, the samples are suitable for analyzing inorganic phosphate content, determining lipid dry weight, or isolating particular sphingolipid constituents via solid phase extraction. For the removal of glycerol backbone-containing lipid impurities, undertake a mild alkaline base hydrolysis using potassium hydroxide in methanol. If working with substantial fungal masses, initial crushing of the sample in the lipid extraction buffer using glass beads or grinding into powder with a pestle and mortar in liquid nitrogen may be necessary before proceeding with extraction. QUANTIFICATION AND STATISTICAL ANALYSIS Statistical methodologies were not utilized for pre-determining the sample size. In the conducted experiments, randomization was applied exclusively to in vivo studies, wherein age-matched mice were randomly allocated to various experimental groups based on genotype. The allocation during experiments and during the evaluation of outcomes was known to the investigators, except in the case of microscopic analyses (such as PAS, IF, and other stainings), where blinding was maintained. Single-cell data analyses were executed using standard procedures in R packages. Fungal load and weight loss metrics were subjected to Mann-Whitney U test analysis. qPCR and flow cytometry assessments were analyzed using unpaired t tests. GraphPad Prism was employed for data analysis, considering a P value of <0.05 as the threshold for statistical significance. Each symbol in the graphical representations corresponds to an individual mouse or sample, with significance levels indicated as *P <0.05, **P <0.01, ***P <0.001, and ****P < 0.0001. Declarations Acknowledgments Not applicable. Funding This work was supported by the key project of the National Natural Science Foundation of China (82030095) and the National Natural Science Foundation of China (81972941). Author contributions W.D., Y.L., R.L., X.W., and K.Z. were responsible for the conceptualization of the study. R.L. and Y.L. secured funding acquisition. R.L., Y.L.and B.Y. also provided supervision for the research. 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Nature, 2018. 555 (7696): p. 382-386. Singh, A. and M. Del Poeta, Sphingolipidomics: an important mechanistic tool for studying fungal pathogens. Frontiers in microbiology, 2016. 7 : p. 501. Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryTable1.csv Supplementary Table 1 SupplementaryTable2.csv Supplementary Table 2 SupplementaryTable3.csv Supplementary Table 3 SupplementaryTable4.docx Supplementary Table 4 ExtendedDataFig.1.tif Extended Data Fig.1 ExtendedDataFig.2.tif Extended Data Fig.2 ExtendedDataFig.3.tif Extended Data Fig.3 ExtendedDataFig.4.tif Extended Data Fig.4 ExtendedDataFig.5.tif Extended Data Fig.5 ExtendedDataFig.6.tif Extended Data Fig.6 ExtendedDataFig.7.tif Extended Data Fig.7 ExtendedDataFig.8.tif Extended Data Fig.8 ExtendedDataFig.9.tif Extended Data Fig.9 ExtendedDataFig.10.tif Extended Data Fig.10 ExtendedDataFig.11.tif Extended Data Fig.11 ExtendedDataFig.12.tif Extended Data Fig.12 ExtendedDataFig.13.tif Extended Data Fig.13 ExtendeddatafiguresandtablesLegends.docx Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4137807","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Biological Sciences - Article","associatedPublications":[],"authors":[{"id":281867088,"identity":"7b8b6b0f-855d-4cfd-adf6-8072f5f40d01","order_by":0,"name":"Weiwei 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14:16:18","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4137807/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4137807/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53834082,"identity":"8b51a810-a2e7-4874-a38a-56ebdda763c9","added_by":"auto","created_at":"2024-04-01 05:43:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":742367,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDissecting the Oral Immune Landscape in OPC Through scRNA-seq Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Schematic representation of the experimental design for analyzing the immune microenvironment in a murine OPC model. Control mice and those treated with CA were infected with \u003cem\u003eC. albicans\u003c/em\u003e, followed by tissue collection for scRNA-seq analysis.\u003c/p\u003e\n\u003cp\u003e(B) UMAP visualization of the diverse cell populations identified in murine tongue tissue.\u003c/p\u003e\n\u003cp\u003e(C) Heatmap displaying gene expression profiles across identified cell clusters. The deeper the yellow coloration, the higher the gene expression level; conversely, the deeper the blue coloration, the lower the gene expression.\u003c/p\u003e\n\u003cp\u003e(D) UMAP plot of immune cell subpopulations.\u003c/p\u003e\n\u003cp\u003e(E) Feature plots illustrating the expression patterns of select genes, including \u003cem\u003eTrem2\u003c/em\u003e, across different cell clusters, emphasizing the distinct biomarkers of immune cells.\u003c/p\u003e\n\u003cp\u003e(F) Bar graph depicting the proportion of immune cells.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/0d12d2c9d3973f2e39bb3add.png"},{"id":53834081,"identity":"b366fa6d-f1aa-4408-8286-190eadd7605e","added_by":"auto","created_at":"2024-04-01 05:43:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1623717,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional Implications of TREM2\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e Macrophages in OPC.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Graphs displaying body weight percentage of WT and \u003cem\u003eTrem2\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/- \u003c/em\u003e\u003c/sup\u003emice on Days 1 (left, n=9) and 2 (right, WT: n=9; \u003cem\u003eTrem2\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e: n=7) post-infection.\u003c/p\u003e\n\u003cp\u003e(B) Quantification of fungal burden in WT and \u003cem\u003eTrem2\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/- \u003c/em\u003e\u003c/sup\u003emice, Left graph for Day 1 (n=9), right graph for Day 2 (WT: n=9; \u003cem\u003eTrem2\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e: n=7).\u003c/p\u003e\n\u003cp\u003e(C) Histological analysis of tongue tissue revealed enhanced epithelial invasion by \u003cem\u003eC. albicans\u003c/em\u003e in \u003cem\u003eTrem2\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e mice compared to WT. Day 1 (n=9); Day 2 (WT: n=9; \u003cem\u003eTrem2\u003c/em\u003e\u003csup\u003e\u003cem\u003e-/-\u003c/em\u003e\u003c/sup\u003e: n=7).\u003c/p\u003e\n\u003cp\u003e(D) Flow cytometry analysis of macrophages infiltration in tongue tissues on Day 1 post-infection. The flow cytometry data represent the findings in LY6C\u003csup\u003e+\u003c/sup\u003e macrophages (Left). The right side represented the statistical results (n=14).\u003c/p\u003e\n\u003cp\u003e(E) Heatmap of gene expression profiles from scRNA-seq data. The left side listed gene symbols; the heatmap reflected gene expression outcomes, and the right side showed the results of top pathway enrichment analysis. Statistical significance for (A) and (B) was assessed using Mann-Whitney U test, and for (D) using unpaired t-test. Experiments were repeated 2-3 times. Data represented mean ± SEM. *P \u0026lt; 0.05, **P \u0026lt; 0.01, and ****P \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/eb230ce074c7e01f7daf3850.png"},{"id":53834797,"identity":"462ec22a-ed6b-4a73-b3e7-2608064356aa","added_by":"auto","created_at":"2024-04-01 05:51:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1095364,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTREM2 Directly Recognizes candidalysin.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-B) Flow cytometry analysis of human (A) and mouse (B) TREM2 recognition of the hyphal form (right) of \u003cem\u003eC. albicans\u003c/em\u003e, not the yeast form (left).\u003c/p\u003e\n\u003cp\u003e(C-D) Elisa binding assays showing human (C) and mouse (D) TREM2 engagement with multiple PAMPs.\u003c/p\u003e\n\u003cp\u003e(E) Immunofluorescence microscopy images displaying co-localization of candidalysin with TREM2 on THP-1 cells.\u003c/p\u003e\n\u003cp\u003e(F) After overexpressing human \u003cem\u003eTREM2\u003c/em\u003e and \u003cem\u003eECE1\u003c/em\u003e(candidalysin) in 293T cells, an immunoprecipitation assay to detect the interaction between TREM2 and candidalysin was conducted. Statistical significance assessed by unpaired t-test across three independent experiments with data represented as mean ± SEM. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ***p\u0026lt;0.0001.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/76df0349be97a135109ab0bf.png"},{"id":53834085,"identity":"bea53ce2-7b4f-45fb-9425-7f2813560a16","added_by":"auto","created_at":"2024-04-01 05:43:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1108413,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKey site validation for TREM2 recognition of Candidalysin, and Recruitment of DAP12 by TREM2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-C) Immunoprecipitation assay was conducted to detect the interactions in 293T: between human TREM2 D131 and candidalysin N73 (A), human TREM2 R136 and candidalysin G65 (B), and human TREM2 P169 with the candidalysin N91-K92 sequence (C).\u003c/p\u003e\n\u003cp\u003e(D) Immunofluorescence detection of THP-1’s DAP10 and DAP12 recruitment following candidalysin stimulation.\u003c/p\u003e\n\u003cp\u003e(E) After overexpressing \u003cem\u003eTREM2\u003c/em\u003e in 293T cells, the cells were stimulated with candidalysin, followed by an immunoprecipitation assay. The IgG group and the experimental group utilized the corresponding input sample.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/c35f054d79d78fa0673f2d42.png"},{"id":54595549,"identity":"9deb2622-ca6b-4e47-91c9-c523dc882aa6","added_by":"auto","created_at":"2024-04-12 18:50:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3849506,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/873ee8bb-4050-4c24-8bc5-ca02e2d06f95.pdf"},{"id":53834091,"identity":"e2e3ecf1-50ce-453d-a130-f2eae5a6095d","added_by":"auto","created_at":"2024-04-01 05:43:04","extension":"csv","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1117,"visible":true,"origin":"","legend":"Supplementary Table 1","description":"","filename":"SupplementaryTable1.csv","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/09e968714af6ecb29dd5db3f.csv"},{"id":53834088,"identity":"7c595a56-a269-4b39-91b2-a6fd7b519d8d","added_by":"auto","created_at":"2024-04-01 05:43:03","extension":"csv","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":110172,"visible":true,"origin":"","legend":"Supplementary Table 2","description":"","filename":"SupplementaryTable2.csv","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/763ba4895ec1167e38e007fd.csv"},{"id":53834084,"identity":"4d5c67aa-28b9-4824-a824-7fb090ebd69e","added_by":"auto","created_at":"2024-04-01 05:43:03","extension":"csv","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":10073,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 3\u003c/p\u003e","description":"","filename":"SupplementaryTable3.csv","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/c71d6ae3f44481a99ba61b50.csv"},{"id":53834841,"identity":"7b5976f5-9121-44d3-b092-999fa543e7de","added_by":"auto","created_at":"2024-04-01 05:51:04","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":26814,"visible":true,"origin":"","legend":"Supplementary Table 4","description":"","filename":"SupplementaryTable4.docx","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/117b42a74b4ab9e5748fdc30.docx"},{"id":53834100,"identity":"0b824e7f-ee95-44d1-91c9-401452af7432","added_by":"auto","created_at":"2024-04-01 05:43:04","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":55625228,"visible":true,"origin":"","legend":"Extended Data 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Fig.11\u003c/p\u003e","description":"","filename":"ExtendedDataFig.11.tif","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/58b230833119295e38da7168.tif"},{"id":53834103,"identity":"80ff2c53-80ec-4e7b-8f99-e6af5c718ed9","added_by":"auto","created_at":"2024-04-01 05:43:07","extension":"tif","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":154151908,"visible":true,"origin":"","legend":"Extended Data Fig.12","description":"","filename":"ExtendedDataFig.12.tif","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/6b88da37c28d4409234ec6cc.tif"},{"id":53834096,"identity":"18b6f9a1-f249-4235-a3fc-8dd226abb107","added_by":"auto","created_at":"2024-04-01 05:43:04","extension":"tif","order_by":17,"title":"","display":"","copyAsset":false,"role":"supplement","size":2292960,"visible":true,"origin":"","legend":"Extended Data Fig.13","description":"","filename":"ExtendedDataFig.13.tif","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/dc28b709c7242bce215d1c7c.tif"},{"id":53834087,"identity":"cdb54812-ebe2-4f40-92c5-146ddde7f83e","added_by":"auto","created_at":"2024-04-01 05:43:03","extension":"docx","order_by":18,"title":"","display":"","copyAsset":false,"role":"supplement","size":19320,"visible":true,"origin":"","legend":"","description":"","filename":"ExtendeddatafiguresandtablesLegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-4137807/v1/0dbfd528c7b8aaa9f4520f71.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"TREM2 Recognition of Candidalysin Orchestrates Mucosal Immunity in Oropharyngeal Candidiasis","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cem\u003eC. albicans\u003c/em\u003e relies on its agglutinin-like sequence (ALS) adhesins for adherence to oral epithelial cells [1]. Oral epithelial cells, in turn, recognize pathogen-associated molecular patterns (PAMPs), specifically \u0026beta;-glucan, through their EphA2 [2]. Moreover, these epithelial cells can identify Als3 of \u003cem\u003eC. albicans\u0026nbsp;\u003c/em\u003ethrough EGFR [3], activating downstream PI3K/Akt, NF-\u0026kappa;B, and MAPK signaling pathways. This activation results in the transcription of AP-1 transcription factors c-Fos and c-Jun, promoting the secretion of various cytokines, \u0026beta;-defensins, and antimicrobial peptides by epithelial cells. The chemokines secreted in response recruit Th17 cells, Th22 cells, neutrophils, and macrophages. Th17 cells secrete IL-17/IL17F, which, upon binding to the IL-17RA/IL-17RC receptors on epithelial cells, activates downstream signaling pathways, thereby facilitating the transcription of inflammation-related cytokines [4, 5]. In concordance with IL-17R, IL-22RA is predominantly expressed in non-hematopoietic cells, and the IL-22 secreted by Th22 cells is crucial for maintaining the barrier function of oral epithelial cells during OPC [6]. Neutrophils recognize \u0026beta;-glucan through their EphA2, inducing the generation of ROS to eliminate \u003cem\u003eC. albicans\u0026nbsp;\u003c/em\u003e[7]. Upon detecting longer hyphae, neutrophils initiate a specific form of cell death, releasing neutrophil extracellular traps (NETs) composed of decondensed chromatin and intracellular granule proteins to capture and kill pathogens [8, 9]. Macrophages contribute to the defense against \u003cem\u003eC. albicans\u003c/em\u003e through phagocytosis, killing activity, and ROS production [10, 11]. Despite the crucial role of macrophages in fungal immunity, previous research on OPC has predominantly concentrated on IL-17 signaling, with limited exploration of the specific functions and mechanisms of macrophages in this context.\u003c/p\u003e\n\u003cp\u003eIn recent years, the role of TREM2 (Triggering receptor expressed on myeloid cells-2, TREM2) has emerged as a new research focus in various diseases [12]. TREM2, a single-pass transmembrane immunoglobulin superfamily member, is predominantly expressed in microglial cells and macrophages [12]. Functioning as a receptor, TREM2 can bind to a diverse range of ligands, recruiting the adaptor proteins DAP10/12 and activating PI3K and Syk signaling [12-15]. Additionally, TREM2 can be cleaved into a soluble protein by the metalloproteinases ADAM10 and ADAM17 [16, 17]. Studies have demonstrated that the overexpression of \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003ein mice with Alzheimer\u0026apos;s disease effectively improves pathological lesions and cognitive impairments [18]. Furthermore, research has identified that TREM2\u003csup\u003e+\u003c/sup\u003e macrophages can phagocytose and clear damaged cells in the liver, thereby suppressing chronic liver inflammation and non-alcoholic fatty liver disease induced by obesity [19]. Initially considered an anti-inflammatory molecule during infections, recent research suggests that TREM2 can promote cellular phagocytosis of bacteria and enhance inflammatory responses [20]. The phagocytic activity dependent on TREM2 necessitates the presence of the full-length TREM2 protein [21]. Moreover, the production of ROS in response to infection is also contingent on TREM2 [22, 23]. Despite the research community has shifted its focus towards recognizing the central role of TREM2 as a key immune signaling hub induced by pathology, its mechanistic involvement in fungal immunity remains unclear.\u003c/p\u003e\n\u003cp\u003eOur research elucidated the pivotal role of TREM2\u003csup\u003e+\u003c/sup\u003e macrophages in the defense against oral candidiasis through their regulation of TNF-\u0026alpha;, which orchestrates anti-fungal immune response. Crucially, we unveiled TREM2\u0026apos;s capacity to directly recognize candidalysin, instigating a DAP12/Syk/NF-\u0026kappa;B mediated TNF-\u0026alpha; signaling cascade. This discovery paved the way for leveraging the TREM2 activator as a novel therapeutic strategy in glucocorticoid-induced OPC, offering a beacon of hope for enhancing mucosal immunity.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eInduced transcription of \u003cem\u003eTREM2\u003c/em\u003e predominantly situated at the infection sites\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe single-cell resolution landscape of OPC has not been mapped to date. To address this gap, we utilized scRNA-seq in a murine model (Fig.1A), encompassing normal tongue tissue, tongue tissue post-\u003cem\u003eC. albicans\u003c/em\u003e infection, and tongue tissue of mice treated with CA to induce OPC. Following sequencing and subsequent seurat pipeline analysis, a total of 30,810 cells were identified (Fig.1B, C). Predominantly, these cells comprised non-immune cells such as fibroblasts, endothelial cells, and smooth muscle cells (Fig.1B), with immune cells accounting for only 12.19%, aligning with the observed low proportion of immune cells in tongue tissue. Further subsetting of these immune cells (Fig.1D, E) revealed macrophages distinguishing into TREM2\u003csup\u003e+\u003c/sup\u003e and TREM2\u003csup\u003e-\u003c/sup\u003e subpopulations. Conventionally, macrophage subpopulations with distinct functions are denoted as M1 and M2 macrophages. However, it is crucial to note that the M1 and M2 classification, derived mainly from \u003cem\u003ein vitro\u003c/em\u003e polarization assays, is more apt for describing the activation state of macrophages \u003cem\u003ein vitro\u0026nbsp;\u003c/em\u003e[24]. Indeed, differentiating macrophage subpopulations in murine tongue tissue using M1 or M2 markers proved challenging (Extended Data Fig.1A). With the increasing application of single-cell studies, macrophage subtyping leans towards utilizing TREM2 for distinction. Within tongue tissue, the confirmed TREM2\u003csup\u003e+\u003c/sup\u003e macrophages exhibited an elevated proportion among immune cells post-\u003cem\u003eC. albicans\u003c/em\u003e infection, while CA-treated mice showed a significant reduction in the proportion of TREM2\u003csup\u003e+\u0026nbsp;\u003c/sup\u003emacrophages (Fig.1F, Supplementary Table 1).\u003c/p\u003e\n\u003cp\u003eTo ascertain the presence of TREM2\u003csup\u003e+\u003c/sup\u003e macrophages in the human oral mucosa, we conducted an analysis of publicly available scRNA-seq data [25] of the oral mucosa (Extended Data Fig.1B). After subsetting immune cell populations (Extended Data Fig.1C) and subsequent clustering (Extended Data Fig.1E, F), we identified the presence of TREM2\u003csup\u003e+\u003c/sup\u003e macrophages in normal human tissue (Extended Data Fig.1D). These findings indicated that these cells may also represent a type of tissue-resident macrophage, akin to microglial cells found in the brain, Kupffer cells in the liver, and alveolar macrophages in lung tissue. To validate this hypothesis, we performed immunofluorescence and flow cytometric analyses, confirming the presence of TREM2\u003csup\u003e+\u003c/sup\u003e macrophages in normal murine tongue tissue (Extended Data Fig.1G), predominantly localized within the internal regions of the tongue tissue (Extended Data Fig.1H). Upon \u003cem\u003eC. albicans\u003c/em\u003e infection, the proportion of TREM2\u003csup\u003e+\u003c/sup\u003e macrophages in murine tongue tissue significantly increased (Extended Data Fig.1G), with these macrophages predominantly situated at the infection sites (Extended Data Fig.1H).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHematopoietic-derived TREM2 is indispensable for protection against OPC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrevious studies have suggested an inhibitory role for TREM2 in tumor immunity [26-28]. Findings from the OPC mouse model demonstrate the complete clearance of \u003cem\u003eC. albicans\u0026nbsp;\u003c/em\u003eby Day 5 [29]. Intriguingly, during the early stages of OPC (Day 1), we observed an accumulation of TREM2-expressing macrophages (Extended Data Fig.1G, H). To further understand the role of TREM2 in OPC and rule out any inhibitory effects (Considering that \u003cem\u003eTrem2\u003c/em\u003e deficiency leads to rapid recovery in OPC mice), we conducted an assessment of TREM2 impact during Days 1 and 2. The results revealed that \u003cem\u003eTrem2\u003c/em\u003e deficiency increased susceptibility to OPC in mice, manifested by lower body weight and higher fungal burden in \u003cem\u003eTrem2\u003csup\u003e-/-\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003emice (Fig.2A, B). Pathological findings also demonstrated more severe epithelial fungal invasion in \u003cem\u003eTrem2\u003csup\u003e-/-\u0026nbsp;\u003c/sup\u003e\u003c/em\u003emice (Fig.2C). By the fifth day, WT mice exhibited undetectable levels of \u003cem\u003eC. albicans\u003c/em\u003e, while \u003cem\u003eTrem2\u003csup\u003e-/-\u003c/sup\u003e\u003c/em\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003emice still harbored persistent fungal infections (Extended Data Fig.1I, J).\u003c/p\u003e\n\u003cp\u003eOver the past decade, the classification of Ly6C\u003csup\u003e+\u003c/sup\u003e and Ly6C\u003csup\u003e-\u003c/sup\u003e macrophages has become a prevalent tool for studying monocyte-derived macrophages [30]. This classification helps in accurately defining the state of macrophages within complex internal microenvironments [30]. Ly6C\u003csup\u003e+\u0026nbsp;\u003c/sup\u003emacrophages undergo significant enrichment and display a pro-inflammatory phenotype, actively participating in acute inflammatory responses. Our investigation further unveiled a pronounced infiltration of TREM2\u003csup\u003e+\u003c/sup\u003e macrophages at the infection site (Extended Data Fig.1H). We postulated that these TREM2\u003csup\u003e+\u003c/sup\u003e macrophages might belong to the Ly6C\u003csup\u003e+\u003c/sup\u003e subset. To validate this hypothesis, flow cytometric analysis was conducted, revealing differential presence of Ly6C\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eTREM2\u003csup\u003e+\u003c/sup\u003e macrophages before and after infection, while Ly6C\u003csup\u003e-\u0026nbsp;\u003c/sup\u003eTREM2\u003csup\u003e+\u003c/sup\u003e macrophages exhibited no such difference (Fig.2D). Additionally, we observed that TREM2\u003csup\u003e+\u003c/sup\u003e macrophages at the infection site were also CX3CR1\u003csup\u003e+\u003c/sup\u003e (Extended Data Fig.2A), a marker for infiltrating monocyte-derived macrophages. scRNA-seq data further indicated a high expression of \u003cem\u003eCX3CR1\u003c/em\u003e in both human and murine TREM2\u003csup\u003e+\u003c/sup\u003e macrophages (Extended Data Fig.2B, C). Remarkably, the administration of the lymphocyte recirculation inhibitor FTY720 effectively suppressed the infiltration of Ly6C\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eTREM2\u003csup\u003e+\u003c/sup\u003e macrophages, with no impact on Ly6C\u003csup\u003e-\u003c/sup\u003eTREM2\u003csup\u003e+\u003c/sup\u003e macrophage infiltration (Extended Data Fig.2D). This inhibition significantly heightened susceptibility to OPC in mice (Extended Data Fig.2E-H). These findings strongly support a protective role of hematopoietic-origin TREM2 in OPC. To pinpoint the specific source of TREM2 in the anti-fungal effect, we created chimeric mice by replacing the bone marrow (BM) of lethally irradiated wild-type (WT) mice with a reconstituting of WT BM and \u003cem\u003eTrem2\u003csup\u003e-/-\u003c/sup\u003e\u0026nbsp;\u003c/em\u003eBM. The results demonstrated that chimeric mice exhibited increased susceptibility to OPC (Extended Data Fig.2I, J). Therefore, we can confidently affirm that hematopoietic-origin TREM2 plays a pivotal protective role in OPC. Previous studies have firmly established that \u003cem\u003eTrem2\u003c/em\u003e expression is confined to macrophages within the myeloid cell compartment [19, 31], underscoring that TREM2 primarily exerts its function through macrophages of hematopoietic origin.\u003c/p\u003e\n\u003cp\u003eRecent investigations indicated an elevation in \u003cem\u003eTREM2\u0026nbsp;\u003c/em\u003eexpression within macrophages across various liver diseases and relevant mouse models [32-37]. However, whether \u003cem\u003eTREM2\u003c/em\u003e undergoes upregulation during fungal infections remains unexplored. To address this knowledge gap, we stimulated mouse bone marrow-derived macrophages (BMDMs) with \u003cem\u003eC. albicans\u003c/em\u003e, revealing an augmentation in TREM2 protein (Extended Data Fig.2K). Intriguingly, IL-17 was also identified as a potential inducer of TREM2 protein upregulation (Extended Data Fig.2K). These findings suggested that, subsequent to macrophage infiltration into the OPC infection site, both \u003cem\u003eC. albicans\u003c/em\u003e and IL-17 contributed to TREM2 protein upregulation, thereby facilitating the clearance of \u003cem\u003eC. albicans\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePro-inflammatory role of TREM2\u003csup\u003e+\u0026nbsp;\u003c/sup\u003emacrophages in OPC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate the molecular mechanisms through which TREM2 contributes to protection in OPC, we further analyzed scRNA-seq data. We observed that TREM2\u003csup\u003e+\u003c/sup\u003e macrophages upregulated inflammatory chemokines (\u003cem\u003eCxcl1\u003c/em\u003e, \u003cem\u003eCxcl16\u003c/em\u003e, \u003cem\u003eCcl2\u003c/em\u003e, \u003cem\u003eCcl4\u003c/em\u003e, and \u003cem\u003eCcl9\u003c/em\u003e), antigen presentation (\u003cem\u003eH2-DMb1\u003c/em\u003e, \u003cem\u003eH2-Aa,\u003c/em\u003e \u003cem\u003eH2-Eb1\u003c/em\u003e, \u003cem\u003eH2-DMa\u003c/em\u003e, and \u003cem\u003eCd74\u003c/em\u003e), interferon response (\u003cem\u003eIfitm3\u003c/em\u003e), complement pathway (\u003cem\u003eC1qa\u003c/em\u003e, \u003cem\u003eC1qb\u003c/em\u003e, and \u003cem\u003eC1qc\u003c/em\u003e), protein degradation (\u003cem\u003eLamp1\u003c/em\u003e, \u003cem\u003eCtss\u003c/em\u003e, \u003cem\u003eCtsz\u003c/em\u003e, and \u003cem\u003eLgmn\u003c/em\u003e), inflammation markers (\u003cem\u003eRgs10\u003c/em\u003e, \u003cem\u003eMpeg1\u003c/em\u003e, and \u003cem\u003eTnf\u003c/em\u003e), costimulatory molecules (\u003cem\u003eCd86\u003c/em\u003e), chemokine receptors (\u003cem\u003eCcr2\u003c/em\u003e and \u003cem\u003eCcr5\u003c/em\u003e), pattern recognition receptors (\u003cem\u003eTlr2\u003c/em\u003e), and surface adhesion receptor (\u003cem\u003eCd44\u003c/em\u003e) (Fig.2E, Supplementary Table 2). In contrast, TREM2\u003csup\u003e-\u0026nbsp;\u003c/sup\u003emacrophages primarily upregulated ribosomal proteins (\u003cem\u003eRps2\u003c/em\u003e, \u003cem\u003eRps6\u003c/em\u003e, \u003cem\u003eRps12\u003c/em\u003e, and \u003cem\u003eRpsa\u003c/em\u003e), the inflammatory chemokine (\u003cem\u003eCcl3\u003c/em\u003e), and the complement pathway component (\u003cem\u003eC11bp\u003c/em\u003e) (Fig.2E, Supplementary Table 2). Pathway analysis revealed that TREM2\u003csup\u003e+\u003c/sup\u003e macrophages primarily enhanced pathways related to antigen processing and presentation, phagosome formation, chemokine signaling, NF-\u0026kappa;B activation, Th17 cell differentiation, cytokine-cytokine receptor interaction, and TNF signaling\u0026mdash;all crucial for antifungal immunity (Fig.2E). On the other hand, TREM2\u003csup\u003e-\u003c/sup\u003e macrophages upregulated pathways associated with disease states, not involving antifungal immune responses (Fig.2E). Other antifungal immune cells, such as neutrophils, were enriched with pathways like phagosome formation, neutrophil extracellular trap formation, IL-17 signaling, C-type lectin receptor signaling, TNF signaling, cytokine-cytokine receptor interaction, and NF-\u0026kappa;B signaling (Fig.2E). T cells exhibited enrichment in pathways vital to their function, including Th1 and Th2 cell differentiation, Th17 cell differentiation, and T cell receptor signaling (Fig.2E), reflecting the reliability of our cell clustering and functional analysis.\u003c/p\u003e\n\u003cp\u003eFurther analysis revealed that under normal physiological conditions, TREM2\u003csup\u003e+\u0026nbsp;\u003c/sup\u003emacrophages showed gene oncology (GO) functional enrichment in inflammatory response, MAPK signaling, and antigen processing and presentation (Extended Data Fig.3A, Supplementary Table 3). Upon \u003cem\u003eC. albicans\u0026nbsp;\u003c/em\u003einfection, TREM2\u003csup\u003e+\u0026nbsp;\u003c/sup\u003emacrophages predominantly upregulated GO functions related to the cellular response to interleukin-1, endocytosis, cytokine-mediated signaling, and IL-17 signaling (Extended Data Fig.3B, Supplementary Table 3), indicating a pro-inflammatory role even prior to infection and promoting fungal clearance through activation of IL-17 signaling after \u003cem\u003eC. albicans\u003c/em\u003e infection.\u003c/p\u003e\n\u003cp\u003eThe upregulation of various chemokines, inflammatory mediators, and receptors in TREM2\u003csup\u003e+\u003c/sup\u003e macrophages, coupled with the enhanced cytokine-cytokine receptor interaction pathway (Fig. 2E), suggested extensive interactions with other immune cells. Indeed, strong intercellular interactions were observed between TREM2\u003csup\u003e+\u003c/sup\u003e and TREM2\u003csup\u003e-\u003c/sup\u003e macrophages, T cells, and neutrophils, with TREM2\u003csup\u003e+\u003c/sup\u003e macrophages also engaging in self-regulation (Extended Data Fig.3C). These interactions predominantly involved signals through CCL, APP, CXCL, TNF, GRN, and VISFATIN (Extended Data Fig.3D). Notably, the TNF signaling was exclusively generated by TREM2\u003csup\u003e+\u003c/sup\u003e macrophages and impacted neutrophils, T cells, TREM2\u003csup\u003e+\u003c/sup\u003e and TREM2\u003csup\u003e-\u003c/sup\u003e macrophages (Extended Data Fig.3D). GSEA analysis further identified a significant upregulation of TNF signaling in TREM2\u003csup\u003e+\u003c/sup\u003e macrophages compared to other immune cells (Extended Data Fig.3E), with only TREM2\u003csup\u003e+\u003c/sup\u003e macrophages showing high expression of \u003cem\u003eTnf\u003c/em\u003e, and the TNF receptor being expressed in neutrophils, T cells, and both TREM2\u003csup\u003e+\u003c/sup\u003e and TREM2\u003csup\u003e-\u003c/sup\u003e macrophages (Extended Data Fig.3F), aligning with the cell interaction analysis of TNF signaling regulation in these immune cells. Correlation analysis substantiated a significant positive association of \u003cem\u003eTREM2\u0026nbsp;\u003c/em\u003ewith \u003cem\u003eTNF\u003c/em\u003e expression and TNF signaling pathways in both humans and mice (Extended Data Fig.3G), preliminarily confirming the unique role of TREM2\u003csup\u003e+\u003c/sup\u003e macrophages in regulating TNF signaling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegulatory influence of TREM2 on macrophage TNF-\u0026alpha; secretion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur bioinformatics analysis has confirmed TREM2 as a potential regulator of \u003cem\u003eTNF\u0026nbsp;\u003c/em\u003e(Extended Data Fig.3G). To determine the relationship between TREM2 and TNF-\u0026alpha;, we first examined the co-localization of TREM2\u003csup\u003e+\u003c/sup\u003e macrophages with TNF-\u0026alpha;. Our findings revealed that TREM2\u003csup\u003e+\u003c/sup\u003e macrophages were capable of secreting TNF-\u0026alpha; and were localized to the site of infection in OPC (Extended Data Fig.4 A). Flow cytometry analysis also indicated a significant infiltration of TREM2\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eTNF-\u0026alpha;\u003csup\u003e+\u003c/sup\u003e macrophages in the infected tongue tissue, whereas the infiltration of TREM2\u003csup\u003e-\u0026nbsp;\u003c/sup\u003eTNF-\u0026alpha;\u003csup\u003e+\u003c/sup\u003e macrophages showed no difference (Extended Data Fig.4B). Consistently, Ly6C\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eTREM2\u003csup\u003e+\u003c/sup\u003e macrophages were significantly more prevalent in the infected tongue tissue, with an increase in Ly6C\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eTREM2\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eTNF-\u0026alpha;\u003csup\u003e+\u003c/sup\u003e macrophages at the infection site, while there was no disparity observed with Ly6C\u003csup\u003e-\u0026nbsp;\u003c/sup\u003eTREM2\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eTNF-\u0026alpha;\u003csup\u003e+\u003c/sup\u003e and TREM2\u003csup\u003e-\u0026nbsp;\u003c/sup\u003eTNF-\u0026alpha;\u003csup\u003e+\u003c/sup\u003e macrophages (Extended Data Fig.4C, D). Further analysis of TNF-\u0026alpha; in tongue tissues revealed that the absence of \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003eled to a significant decrease in TNF-\u0026alpha; in OPC tongue tissues (Extended Data Fig.4E). TNF-\u0026alpha; is primarily secreted by macrophages, T cells, and B cells, which also inhabit the immunological microenvironment of the mouse tongue (Fig.1D). To ascertain which cells were affected by the \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003edeficiency leading to reduced TNF-\u0026alpha; in OPC tongue tissues, we analyzed the secretion of TNF-\u0026alpha; by these cells before and after \u003cem\u003eTrem2\u003c/em\u003e knockout. The results indicated that the absence of \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003emainly affected the secretion of TNF-\u0026alpha; by macrophages (Extended Data Fig.4F), significantly reducing the infiltration of TNF-\u0026alpha;-secreting macrophages at the infection site (Extended Data Fig.4G), while B cells, CD4\u003csup\u003e+\u003c/sup\u003e T cells, and CD8\u003csup\u003e+\u003c/sup\u003e T cells showed no difference in TNF-\u0026alpha; secretion (Extended Data Fig.5A).\u003c/p\u003e\n\u003cp\u003eTo investigate how TREM2 affects the secretion of TNF-\u0026alpha; by macrophages, we first studied whether there were differences in macrophage infiltration levels. We found that \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003eknockout significantly reduced the number of macrophages at the infection site (Extended Data Fig.5B), corresponding with a notable decrease in macrophages at the infection site (Extended Data Fig.4G). Previous research suggests that TREM2 is critical for promoting microglia proliferation and inhibiting apoptosis [12, 38-40]. We hypothesized that the significant reduction in macrophages following \u003cem\u003eTrem2\u003c/em\u003e knockout could be due to inhibited proliferation and activated apoptosis. To test this hypothesis, we examined the impact of TREM2 on macrophage proliferation and apoptosis, finding that \u003cem\u003eTrem2\u003c/em\u003e knockout significantly inhibited macrophage proliferation in OPC (Extended Data Fig.5C) and promoted apoptosis (Extended Data Fig.5D). Immunofluorescence results also showed a propensity for promoted apoptosis and inhibited proliferation in the OPC infection sites lacking \u003cem\u003eTrem2\u003c/em\u003e (Extended Data Fig.5E). In summary, our study has identified that TREM2 influences the proliferation and apoptosis of macrophages in OPC tissues, which significantly reduces the number of TNF-\u0026alpha;-secreting macrophages, thereby decreasing the levels of TNF-\u0026alpha; within the tissue.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegulation of TNF-\u0026alpha; secretion by TREM2 confers protection in OPC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTNF-\u0026alpha; plays a pivotal role in systemic fungal infections, and studies suggest that deleting \u003cem\u003eTnf\u003c/em\u003e \u003cem\u003ein vivo\u003c/em\u003e increases susceptibility to OPC in mice [41]. We administered TNF-\u0026alpha; monoclonal antibodies to WT mice, which did not affect their body weight (Extended Data Fig.6A), but resulted in significantly lower body weight on days 1 and 2 post-\u003cem\u003eC. albicans\u0026nbsp;\u003c/em\u003einfection (Extended Data Fig.6B), along with increased fungal burden (Extended Data Fig.6C), and more severe epithelial invasion (Extended Data Fig.6D). These findings implied that the decrease in TNF-\u0026alpha; levels in tissues due to \u003cem\u003eTrem2\u003c/em\u003e deficiency may be a contributing factor to increased susceptibility to OPC. To test this hypothesis, we restored TNF-\u0026alpha; in the \u003cem\u003eTrem2\u003c/em\u003e-deficient OPC model and observed that although this restoration did not significantly reverse the weight loss caused by\u003cem\u003e\u0026nbsp;Trem2\u003c/em\u003e deficiency (Extended Data Fig.6E), it completely reversed the susceptibility to OPC (Extended Data Fig.6F, G). This evidence corroborated that TREM2 exerted a protective role in OPC by modulating the secretion of TNF-\u0026alpha;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModulation of macrophage inflammatory response by TREM2-mediated TNF-\u0026alpha; secretion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInflammatory cytokines, chemokines, antimicrobial peptides, and defensins are critical for the clearance of fungi, recruitment of immune cells, and regulation of their functions. TNF-\u0026alpha; serves as a potential regulator of inflammatory cytokines, and its deficiency leads to a marked suppression of inflammatory activity. In our \u003cem\u003ein vitro\u003c/em\u003e co-culture of BMDMs with \u003cem\u003eC. albicans\u003c/em\u003e, we discovered that the absence of \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003esignificantly inhibited the expression of \u003cem\u003eTnf\u003c/em\u003e, \u003cem\u003eIl6\u003c/em\u003e, \u003cem\u003eIl23\u003c/em\u003e, \u003cem\u003eS100a8\u003c/em\u003e, \u003cem\u003eS100a9\u003c/em\u003e,\u003cem\u003e\u0026nbsp;Defb1,\u003c/em\u003e \u003cem\u003eCxcl1\u003c/em\u003e, \u003cem\u003eCxcl2\u003c/em\u003e, \u003cem\u003eCcl2\u003c/em\u003e, \u003cem\u003eCcl7\u003c/em\u003e, and \u003cem\u003eS100a7a\u003c/em\u003e (Extended Data Fig.6H and Extended Data Fig.7A). Exogenous supplementation of TNF-\u0026alpha; was able to reverse these differences (Extended Data Fig.6H and Extended Data Fig.7A). The expression of these genes is primarily regulated by inflammatory pathways, and we found that \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003edeficiency notably inhibited the activation of NF-\u0026kappa;B\u0026apos;s P65 subunit and the degradation of I\u0026kappa;B\u0026alpha; (Extended Data Fig.7B), as well as the activation of Syk (Extended Data Fig.7B), and suppressed the activity of the MAPK pathway\u0026apos;s P38 (Extended Data Fig.7C). The supplementation of exogenous TNF-\u0026alpha; reversed these deficiencies. Although PI3k/Akt is a downstream signal of TREM2, in the context of \u003cem\u003eC. albicans\u003c/em\u003e infection, TREM2 did not rely on this pathway (Extended Data Fig.7D). In conclusion, we have elucidated that TREM2 is capable of modulating the secretion of TNF-\u0026alpha;, thereby amplifying the inflammatory signaling response in the context of \u003cem\u003eC. albicans\u003c/em\u003e infection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegulation of Th17 cell differentiation by TREM2 via TNF-\u0026alpha;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIL-17 is essential for combating OPC, predominantly produced by Th17 cells, innate lymphoid cells (ILCs), and \u0026gamma;\u0026delta;T cells. The absence of \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003esuppressed the expression of \u003cem\u003eTnf,\u003c/em\u003e \u003cem\u003eIl6,\u003c/em\u003e and \u003cem\u003eIl23\u003c/em\u003e, cytokines that induce Th17 differentiation [42-44], leading us to postulate that \u003cem\u003eTrem2\u003c/em\u003e deficiency may also affect Th17 cells in OPC. To verify this hypothesis, we assessed the immune cells secreting IL-17, IL-17F, and IL-22 in the tongues of mice. The results showed that \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003edeficiency significantly inhibited the proportion of Th17 cells without affecting other IL-17-secreting immune cells (Extended Data Fig.8A), indicating a specific impact of TREM2 on Th17 cells. \u003cem\u003eTrem2\u003c/em\u003e deficiency also significantly reduced the proportions of IL-17F-producing Th17, CD4\u003csup\u003e-\u0026nbsp;\u003c/sup\u003e\u0026alpha;\u0026beta;T cells, and ILCs (Extended Data Fig.8B), and even the secretion of IL-22 by Th22 and CD4\u003csup\u003e-\u003c/sup\u003e \u0026alpha;\u0026beta;T cells was notably suppressed (Extended Data Fig.8C). Also, in contrast to WT, \u003cem\u003eTrem2\u003csup\u003e-/-\u003c/sup\u003e\u003c/em\u003e mice demonstrated a markedly diminished secretion of IL-17 in their lingual supernatant (Extended Data Fig.7E). Interestingly, \u003cem\u003eTrem2\u003c/em\u003e deficiency unexpectedly resulted in increased neutrophil infiltration (Extended Data Fig.8D), possibly due to the increased fungal burden, as systemic infection studies have found that more\u003cem\u003e\u0026nbsp;C. albicans\u003c/em\u003e can lead to increased neutrophil infiltration, with neutrophil levels seemingly scaling with fungal load [45, 46]. \u003cem\u003eTrem2\u003c/em\u003e deficiency also significantly suppressed Th1 infiltration (Extended Data Fig.8E), while IFN-\u0026gamma; is not essential in OPC since mice lacking IFN-\u0026gamma; or the IL-12 subunit IL-12p35 do not exhibit increased susceptibility to OPC [47, 48]. \u003cem\u003eTrem2\u003c/em\u003e deficiency did not affect the infiltration of dendritic cells (DCs), eosinophils, or mast cells at the site of infection (Extended Data Fig.8F).\u003c/p\u003e\n\u003cp\u003eSubsequent studies revealed that administration of TNF-\u0026alpha; monoclonal antibodies markedly reduced the populations of IL-17-producing Th17 cells (Extended Data Fig.8G), Th17 cells secreting IL-17F (Extended Data Fig.8H), as well as Th22 and CD4\u003csup\u003e-\u0026nbsp;\u003c/sup\u003e\u0026alpha;\u0026beta;T cells that produce IL-22 in OPC (Extended Data Fig.8I). To conclusively validate that TREM2 influences Th17 cell differentiation through TNF-\u0026alpha;, we undertook a co-culture experiment. Na\u0026iuml;ve CD4\u003csup\u003e+\u003c/sup\u003e T cells were incubated with supernatant derived from BMDMs stimulated with \u003cem\u003eC. albicans\u003c/em\u003e. We found that \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003eknockout significantly inhibited Th17 cell differentiation (Extended Data Fig.9A) and the secretion of IL-17F by CD4\u003csup\u003e+\u003c/sup\u003e T cells (Extended Data Fig.9B), which could be reversed with exogenous TNF-\u0026alpha;. In summary, the data confirmed that TREM2 modulated the secretion of TNF-\u0026alpha;, impacting Th17 differentiation to regulate IL-17 signaling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTREM2 regulates macrophage and neutrophil killing abilities through TNF-\u0026alpha;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMacrophages contribute to the clearance of \u003cem\u003eC. albicans\u003c/em\u003e through phagocytosis, killing, and ROS production, while neutrophils also produce NETs to kill fungi. TNF-\u0026alpha; regulates these functions of macrophages and neutrophils [49, 50]. The single-cell analysis also indicated that TNF-\u0026alpha; secreted by TREM2\u003csup\u003e+\u003c/sup\u003e macrophages acted upon both macrophages and neutrophils (Extended Data Fig.3C, D). Indeed, \u003cem\u003eTrem2\u003c/em\u003e deficiency significantly inhibited macrophage phagocytosis (Extended Data Fig.9C), killing ability (Extended Data Fig.9D), and ROS production (Extended Data Fig.9G), with exogenous TNF-\u0026alpha; reversing these functional deficits. To clarify if \u003cem\u003eTrem2\u003c/em\u003e deficiency attenuated the killing ability of neutrophils due to decreased TNF-\u0026alpha;, we co-cultured neutrophils with supernatant obtained from BMDMs that had been stimulated with \u003cem\u003eC. albicans.\u003c/em\u003e Consistent with the regulation of macrophage functions by TNF-\u0026alpha;, we found that \u003cem\u003eTrem2\u003c/em\u003e knockout inhibited neutrophil phagocytosis of \u003cem\u003eC. albicans\u003c/em\u003e (Extended Data Fig.9E), killing (Extended Data Fig.9F), and ROS production (Extended Data Fig.9G). \u003cem\u003eTrem2\u003c/em\u003e knockout also significantly inhibited NETs at the site of infection (Extended Data Fig.9H), a deficit also observed in tongue tissues treated with TNF-\u0026alpha; monoclonal antibodies (Extended Data Fig.9I). The NETs deficiency caused by \u003cem\u003eTrem2\u003c/em\u003e knockout could be reversed by supplementing TNF-\u0026alpha; (Extended Data Fig.9J). In the \u003cem\u003ein vitro\u003c/em\u003e setting, neutrophils co-cultured with supernatant from BMDMs demonstrated a significant inhibition in the production of NETs following \u003cem\u003eTrem2\u003c/em\u003e knockout. This reduction in NETs production could be counteracted by the addition of exogenous TNF-\u0026alpha; (Extended Data Fig.9K). In conclusion, we demonstrated that TREM2 influenced the fungicidal functions of macrophages and neutrophils by regulating TNF-\u0026alpha;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTREM2 recognition of candidalysin initiates TNF Signaling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTREM2, as a receptor, is capable of recognizing a variety of ligands, including a wide range of anionic molecules that are free, can bind to cell membranes, and include components from both Gram-positive and Gram-negative bacteria (such as \u003cem\u003eNeisseria\u003c/em\u003e \u003cem\u003eGonorrhoeae\u003c/em\u003e, \u003cem\u003eEscherichia coli\u003c/em\u003e, and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e), DNA, lipoproteins, and phospholipids [12, 51]. Building on our findings, we observed that \u003cem\u003eTrem2\u003c/em\u003e deficiency presented similar impairments to PRR deficiencies, leading to compromised antifungal inflammatory responses, including signal pathway deficiencies (Extended Data Fig.6H and Extended Data Fig.7A-C). This led us to propose that TREM2 might be involved in the recognition of \u003cem\u003eC. albicans\u003c/em\u003e. To test this hypothesis, we co-incubated the extracellular segment of TREM2 with both spore and hyphal forms of \u003cem\u003eC. albicans\u003c/em\u003e and found that both human and mouse TREM2 recognized only the hyphal form of the fungus, not the yeast form (Fig.3A, B), suggesting the presence of PAMPs on the hyphae recognized by TREM2. To determine the specific PAMPs recognized by TREM2, we incubated its extracellular domain with various PAMPs. Previous research has identified that TREM2 can recognize sphingolipid [52], which are abundantly present on the cell membrane of fungi. Here, we have also purified \u003cem\u003eC. albicans\u003c/em\u003e sphingolipid to investigate whether TREM2 is involved in the recognition of fungal surface sphingolipids. Finally, we discovered that human and mouse TREM2 could engage with multiple PAMPs (LPS, a known ligand of TREM2, served as a positive control in the study) but mainly recognized candidalysin (Fig.3C, D), the first acknowledged classical virulence factor of \u003cem\u003eC. albicans\u003c/em\u003e [53, 54]. After infection, \u003cem\u003eC. albicans\u003c/em\u003e forms hyphae, which induce the expression of the \u003cem\u003eECE1\u003c/em\u003e gene, coding for Ece1p [55, 56]. Ece1p is then processed by Kex2p to produce immature candidalysin, which is finally secreted by the hyphae after Kex1p removes the terminal R93 to generate mature candidalysin (SIIGIIMGILGNIPQVIQIIMSIVKAFKGNK) [54, 57, 58]. This revealed why TREM2 only recognized the hyphal form of \u003cem\u003eC. albicans\u003c/em\u003e and not the yeast form. Immunofluorescence also showed that candidalysin could co-localize with TREM2 on THP-1 cells (Fig.3E), and overexpression of \u003cem\u003eTREM2\u003c/em\u003e in 293T cells with candidalysin confirmed that TREM2 could bind to candidalysin (Fig.3F). In the absence of \u003cem\u003eTrem2\u003c/em\u003e, the recognition of candidalysin by BMDMs was significantly inhibited (Extended Data Fig.10A). These multifaceted results affirmed that TREM2 could directly bind and recognize candidalysin.\u003c/p\u003e\n\u003cp\u003eWhen PAMPs bind to their receptors, they induce an inflammatory signal response. Does the recognition of candidalysin by TREM2 also trigger such signaling activation? To address this question, we stimulated BMDMs with candidalysin and found that it could induce the activation of P65, but this activation was suppressed in the absence of \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003e(Extended Data Fig.10B, C), with the regulation of \u003cem\u003eTnf\u0026nbsp;\u003c/em\u003eexpression consistent with P65 activity (Extended Data Fig.10D). Other PAMPs, only zymosan had a similar effect (Extended Data Fig.10E), indicating that TREM2 could recognize candidalysin and zymosan to provoke an inflammatory response.\u003c/p\u003e\n\u003cp\u003eGiven the significant role of candidalysin and the primary recognition of it by TREM2 (Fig. 3A-D), we investigated the specific binding sites of TREM2 for candidalysin. Employing AlphaFold, DeepMind\u0026apos;s AI-powered tool for predicting protein 3D structures from amino acid sequences, we modeled the interaction between the extracellular domain of human TREM2 and the fungal toxin candidalysin. Following this, protein docking with haddock 2.4 identified that the highest scoring interactions (Select the intersection of the top-scoring results from two rounds of molecular docking) showed TREM2 binding to candidalysin\u0026apos;s G65, N73, and N91-N92 (located on a loop structure) (Extended Data Fig.10F). To confirm the specificity of TREM2 for these sites, we mutated or deleted them (Extended Data Fig.10G), and found that mutations and deleting the loop site significantly inhibited the recognition of candidalysin by human and mouse TREM2 (Extended Data Fig.10H). The mutations at these amino acid sites do not alter the early activity of the early NF-kB signaling pathway (Extended Data Fig.10I); however, as time progresses, there is a significant suppression of the NF-kB signal (Extended Data Fig.10J), suggesting that these site mutations lead to an inability of TREM2 to form a stable, long-term binding structure with candidalysin. Candidalysin\u0026apos;s identified sites correspond to TREM2\u0026apos;s D131, R136, and P169 (Extended Data Fig.10F). Mutating these sites in \u003cem\u003eTREM2\u003c/em\u003e and then overexpressing it in 293T cells with candidalysin showed that the mutations in TREM2\u0026apos;s D131, R136, and P169 significantly inhibited the recognition of candidalysin by TREM2 (Fig.4A-C). It is noteworthy that mutations at the N73, G65, and N91-N92 residues of candidalysin markedly impaired its interaction with TREM2 (Fig.4A-C). This finding underscores the critical role these residues play in the molecular recognition processes of TREM2. Together these findings ascertain that the residues D131, R136, and P169 of TREM2 are involved in recognizing the candidalysin sites G65, N73, and N91-K92.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTREM2 activates NF-\u0026kappa;B via the DAP12/Syk axis to regulate the secretion of TNF-\u0026alpha;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTREM2 recognized its ligand, leading to the recruitment and activation of the adaptor proteins DAP10 and DAP12 [15]. This process activated downstream signaling pathways, notably Syk and PI3k/Akt [15]. Previous research had established that DAP12 primarily activates the Syk pathway, while DAP10 is associated with activating PI3k/Akt [12, 59]. In our study, we found that TREM2\u0026apos;s recognition of \u003cem\u003eC. albicans\u003c/em\u003e predominantly stimulated the Syk pathway (Extended Data Fig.7B), but not the PI3k/Akt pathway (Extended Data Fig.7D), suggesting an interaction between TREM2 and candidalysin via DAP12. Our experimental findings supported this hypothesis. Upon stimulation with candidalysin, there was a significant aggregation of DAP12 in the vicinity of TREM2, unlike DAP10, which did not show a notable increase (Fig.4D, E). This indicated that TREM2\u0026apos;s engagement with candidalysin primarily involved DAP12, leading to downstream signaling activation. Moreover, selectively diminishing \u003cem\u003eDap12\u003c/em\u003e expression, rather than \u003cem\u003eDap10\u003c/em\u003e, significantly decreased the Syk activation triggered by candidalysin (Extended Data Fig.11A). Given that Syk acts upstream of NF-\u0026kappa;B [60, 61], reducing \u003cem\u003eDap12\u003c/em\u003e expression or directly inhibiting Syk significantly hindered the activation of the NF-\u0026kappa;B subunit P65 (Extended Data Fig.11A, B). NF-\u0026kappa;B is known for its critical role in the regulation of inflammatory mediators including TNF-\u0026alpha;, IL-6, chemokines, and antimicrobial proteins during infection [62]. The knockdown of \u003cem\u003eDap12\u003c/em\u003e or the inhibition of Syk both significantly suppressed the expression of \u003cem\u003eTnf\u0026nbsp;\u003c/em\u003e(Extended Data Fig.11C, D). Thus, we concluded that TREM2\u0026apos;s recognition of candidalysin prompted an immune response through the DAP12/Syk axis, which then activated the NF-\u0026kappa;B signaling pathway. This activation regulated TNF-\u0026alpha; secretion, orchestrating an effective inflammatory and immune response in the context of OPC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTREM2 agonist Hsp60 exhibits therapeutic effects in CA-induced OPC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCA-induced OPC is commonly seen in clinical settings, and our scRNA-seq data also indicated a significant reduction in the proportion of TREM2\u003csup\u003e+\u003c/sup\u003e macrophages in the CA-induced OPC model (Fig.1F), suggesting that CA might suppress TREM2\u003csup\u003e+\u003c/sup\u003e macrophages, contributing to OPC susceptibility. Indeed, in the CA-induced OPC model, we observed fewer TREM2\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eTNF-\u0026alpha;\u003csup\u003e+\u003c/sup\u003e macrophages at the infection site on day 1 (Extended Data Fig.12A), and by day 3, these cells were completely undetectable (Extended Data Fig.12B). Flow cytometric analysis also showed that CA inhibited Ly6C\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eTREM2\u003csup\u003e+\u003c/sup\u003e macrophages (Extended Data Fig.12C) and Ly6C\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eTREM2\u003csup\u003e+\u003c/sup\u003e TNF-\u0026alpha;\u003csup\u003e+\u003c/sup\u003e macrophages (Extended Data Fig.12D).\u003c/p\u003e\n\u003cp\u003eHsp60, as a specific TREM2 ligand agonist used to stimulate TREM2 activity [63-65], may have therapeutic potential in OPC. Although CA significantly reduced the number of TREM2\u003csup\u003e+\u003c/sup\u003e macrophages (Extended Data Fig.12A-D), a subset of TREM2\u003csup\u003e+\u0026nbsp;\u003c/sup\u003emacrophages remained in the lingual tissue (Extended Data Fig.12C, D), providing a basis for using Hsp60 to stimulate TREM2 as a treatment for CA-induced OPC. We explored the therapeutic effects of Hsp60, TNF-\u0026alpha;, and soluble TREM2 (sTREM2) in a CA-induced OPC model. The results showed no difference in body weight between the mice on days 1 and 2 of the model (Extended Data Fig.12E), but on day 3, mice treated with Hsp60 had higher body weight compared to controls (Extended Data Fig.12F), suggesting potential phenotypic differences at this time point. On day 3, the Hsp60 and TNF-\u0026alpha; treatment groups exhibited lower fungal burdens and milder \u003cem\u003eC. albicans\u003c/em\u003e epithelial invasion and damage (Extended Data Fig.12G, H). However, we did not observe a therapeutic effect from sTREM2 (Extended Data Fig.12E-H), and \u003cem\u003ein vitro\u003c/em\u003e stimulation of BMDMs with sTREM2 did not reverse the suppression of the NF-kB pathway caused by \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003edeficiency (Extended Data Fig.13A, B), reflecting that TREM2 mainly exerts its function through receptor-mediated inflammation rather than in a soluble form. To confirm that Hsp60 mediated its therapeutic effects through TREM2, we treated \u003cem\u003eTrem2\u003c/em\u003e-deficient BMDMs with Hsp60 \u003cem\u003ein vitro\u003c/em\u003e and found that Hsp60 could enhance the expression of \u003cem\u003eTnf\u0026nbsp;\u003c/em\u003ein WT BMDMs, but this enhancement was ineffective in the absence of \u003cem\u003eTrem2\u0026nbsp;\u003c/em\u003e(Extended Data Fig.13C). Similarly, we found that Hsp60 induced Th17 differentiation (Extended Data Fig.13D) and enhanced macrophage phagocytosis and killing of \u003cem\u003eC. albicans\u003c/em\u003e (Extended Data Fig.13E, F) through TREM2. In conclusion, we have determined that the TREM2 agonist Hsp60 can have therapeutic effects in CA-induced OPC by activating TREM2 function.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDifferent PRRs play a critical role in the recognition of \u003cem\u003eC. albicans\u003c/em\u003e during systemic infections, but they are not as pivotal in OPC [66]. For instance, dectin-1 is indispensable for recognizing systemic infections caused by \u003cem\u003eC. albicans\u003c/em\u003e [67], yet it is not crucial in OPC [68], and the expression level of \u003cem\u003eCLEC7A\u0026nbsp;\u003c/em\u003emay even be reduced in OPC [69]. Recent studies have discovered that epithelial cells can identify\u003cem\u003e\u0026nbsp;C. albicans\u003c/em\u003e through EphA2 and EGFR [2, 3]. The EphA2 on epithelial cells and neutrophils can recognize \u0026beta;-glucan, leading neutrophils to produce ROS to kill \u003cem\u003eC. albicans\u0026nbsp;\u003c/em\u003e[2]. Meanwhile, EGFR can recognize \u003cem\u003eC. albicans\u003c/em\u003e\u0026apos; Als3 and form a complex with EphA2 [3]. Research has also found that candidalysin can activate EGFR phosphorylation, although EGFR does not directly bind and recognize candidalysin [54, 70]. Indeed, to date, no receptor has been identified that directly recognizes candidalysin. This gap in our understanding highlights a critical area of exploration within the field of fungal immunology. The identification of such a receptor would be a significant advancement, providing new insights into the molecular mechanisms that underpin the immune system\u0026apos;s ability to detect and respond to this pathogen. Notably, we have demonstrated that TREM2 recognized candidalysin, initiating a cascade of inflammatory responses essential for protective immunity. This recognition process appeared to be highly specific, involving key residues on TREM2 that interacted with particular sites on candidalysin, thus affirming the precision of innate immune receptors in pathogen detection.\u003c/p\u003e\n\u003cp\u003ePrevious research into OPC has been constrained by technological limitations, often focused narrowly on specific cells without a comprehensive exploration of the interplay between immune cells. The advent of scRNA-seq technology has now surmounted these challenges, enabling us to elucidate the intricate interactions between TREM2 and TNF-\u0026alpha; signaling pathways that are crucial for both the innate and adaptive immune responses against \u003cem\u003eC. albicans\u0026nbsp;\u003c/em\u003ein OPC. Our study had detailed how TREM2, upon recognizing \u003cem\u003eC. albicans\u003c/em\u003e, triggered macrophage activation of the Syk kinase, which subsequently activated the P65 subunit to regulate the secretion of TNF-\u0026alpha;. TNF-\u0026alpha;, in turn, acted in an autocrine manner on macrophages and a paracrine fashion on neutrophils to modulate the fungicidal functions of these innate immune cells. This regulation was vital for the host\u0026apos;s first line of defense, coordinating the killing and phagocytic capacities required to counteract fungal pathogens effectively. Additionally, TREM2\u0026apos;s role in shaping the differentiation of Th17 cells via TNF-\u0026alpha; has been highlighted, suggesting an important connection between innate and adaptive immunity. This cross-talk between immune cells was likely instrumental in orchestrating a full-spectrum immune response, enabling not only the initial clearance of the pathogen but also the development of long-term immunity.\u003c/p\u003e\n\u003cp\u003eOur findings extended the functional repertoire of TREM2 beyond its previously understood roles in neurodegenerative diseases and metabolic disorders [12, 59, 71-76], positioning it as a central player in immune responses against fungal infections. The therapeutic potential of TREM2 agonists like Hsp60 in CA-induced OPC models demonstrated the translational relevance of our discoveries. This agonist may rejuvenate impaired immune responses, thus offering a promising therapeutic avenue for conditions characterized by immune suppression or dysregulation.\u003c/p\u003e\n\u003cp\u003eIn conclusion, our research underscored the critical role of TREM2 in the immune response to OPC, providing a foundation for future investigations aimed at harnessing this receptor for clinical benefit. The interplay between TREM2 and TNF-\u0026alpha; was a testament to the complexity and elegance of the immune system, and further exploration of this axis may yield significant advancements in our fight against fungal pathogens.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eMaterials availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present research did not result in the creation of any novel reagents. All antibodies, primers, and reagents have been integrated into a table with corresponding product numbers (Supplementary Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw sequence data reported in this paper have been deposited in the Genome Sequence Archive (Genomics, Proteomics \u0026amp; Bioinformatics 2021) in National Genomics Data Center (Nucleic Acids Res 2022), China National Center for Bioinformation / Beijing Institute of Genomics, Chinese Academy of Sciences (GSA: CRA014588) that are publicly accessible at https://ngdc.cncb.ac.cn/gsa. Additionally, this paper includes an analysis of pre-existing data that is publicly available at the COVID-19 Cell Atlas website (https://www.covid19cellatlas.org/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis paper does not report original code. Detailed information about software used in this manuscript is provided in the Supplementary Table 4. Any additional information required to reanalyze the data reported in this paper will be made available from the lead contact upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOPC model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe construction of the mouse OPC model was based on previously reported methods in the literature [6, 29, 47, 77]. Three days before infection, a monoclonal culture of \u003cem\u003eC. albicans\u003c/em\u003e (SC5314) was transferred into 10 ml of YPD liquid medium and incubated at 30\u0026deg;C on a shaker. On the second day, 100 \u0026mu;l of the culture was transferred to fresh 10 ml of YPD liquid medium for overnight incubation, a step that was then repeated once more. Both WT and \u003cem\u003eTrem2\u003csup\u003e-/-\u003c/sup\u003e\u003c/em\u003e (1-4773) mice, sourced from cyagen and of the C57BL/6 background, were used in the experiments. Littermate control mice were matched for sex, age, and weight. One day before infection, mice were weighed and each mouse was injected with 225 mg/kg of cortisone acetate. The cortisone acetate was suspended in saline containing 0.05% Tween 80 and homogenized with vortexing or sonication for one minute (as cortisone acetate is not water-soluble, it was frequently vortexed for homogenization prior to injection). The non-immunosuppressed model did not involve the aforementioned injection. Overnight-cultured \u003cem\u003eC. albicans\u003c/em\u003e spores were centrifuged at 1000 g for 5 minutes, the supernatant was discarded, and the spores were washed twice with PBS. Ultimately, the spores were reconstituted in 1 ml of HBSS (Thermo Fisher) medium. To induce OPC, 0.0025g cotton balls, saturated with either 10\u003csup\u003e7\u003c/sup\u003e CFU \u003cem\u003eC. albicans\u003c/em\u003e yeast or HBSS (serving as uninfected controls), were administered sublingually for a duration of 75 minutes while the mice were under general anesthesia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePreparation of single-cell suspensions from tongue tissue\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSingle-cell suspensions were generated from whole tongue tissues using an established protocol [78]. In summary, the tongue tissue was finely chopped and incubated in a 10 ml enzymatic digestion mixture. This mixture comprised 385 U/ml collagenase type IV (YEASEN), 2 U/ml dispase II (Gibco), and 50 \u0026mu;g/ml DNase I (Solarbio) in RPMI medium (Gibco). The tissue-digestion mixture was then incubated at 37\u0026deg;C in a shaking water bath for 45 minutes. To halt the digestion process, PBS supplemented with 5 mM EDTA (Quality Biological) was added, and the mixture was subsequently cooled on ice. The resulting cell suspension was filtered through a 70-\u0026mu;m mesh, followed by washing and further filtration through a 40-\u0026mu;m mesh before a final wash. The single-cell suspension was centrifuged at 1000 rpm for 5 minutes, followed by erythrocyte lysis using 1X red blood cell lysis buffer (Thermo Fisher) for 5 minutes. After lysis, the cells were washed and dead cells were removed using dead cell removal magnetic beads (Miltenyi) according to the manufacturer\u0026apos;s instructions to further purify the sample. The final single-cell preparation was then used for library construction with the 10X Genomics platform for single-cell sequencing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eScRNA-seq analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe various datasets were initially assembled into counts data using CellRanger (version 5.0.0) with reference genome data for mouse (mm10) and human (GRch38). Post assembly, the Seurat package (version 4.0.6) with the IntegrateData function was employed to integrate different datasets. As the mouse data was generated by our research group, minimal batch effects were observed, and the IntegrateData function of Seurat was sufficient to correct for these effects. Following the integration, all single-cell data underwent classical Seurat pipeline analysis [79]. Initially, the proportion of mitochondrial genes detected in each cell was calculated. Cells with a high mitochondrial gene ratio and outliers (cells with \u0026gt;100 genes detected, total gene expression \u0026gt;500, and mitochondrial gene proportion \u0026lt;25%) were filtered out using the subset function. Quality control of single-cell data was then followed by normalization using the NormalizeData function in Seurat. The FindVariableFeatures algorithm was utilized to identify highly variable genes, which are indicative of the biological characteristics of each cell group and provide references for cell clustering. This was followed by data scaling using the ScaleData function. PCA clustering analysis was performed using the RunPCA function, and the final cell subgroups were determined using the RunUMAP, FindNeighbors, and FindClusters functions. Cell subgroups were annotated using the FindAllMarkers function, primarily based on the expression of cell markers specific to each cell group in both mouse and human samples. The expression of these cell markers in each cell subgroup was visualized using the pheatmap package (version 1.0.12).\u003c/p\u003e\n\u003cp\u003eCell communication was analyzed using the cellchat package (version 1.5.0). Pathway analysis between different cell subgroups was conducted using the ClusterGVis package (version 0.1.1). The Rmagic package (version 2.0.3) was employed to impute and fill in missing values for conducting correlation analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetermination of fungal burden in tongue tissues\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing euthanasia, the mice\u0026apos;s tongues and associated oral tissues were excised and weighed. The tissues were then cut using sterile scissors, homogenized in saline, and subsequently diluted with sterile PBS (Thermo Fisher). Homogenates of the tissues at various dilutions were plated on YPD agar plates. These plates were incubated at 37\u0026deg;C in a fungal incubator for 24-48 hours, after which colony counts were conducted to assess fungal burden.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHistological analysis of tongues\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo conduct immunofluorescence staining of mouse tongue tissues, researchers first euthanized the mice and excised the tongue and related oral tissues. They fixed the tissues in 4% paraformaldehyde (Solarbio) for 24 hours at 4\u0026deg;C, then rinsed them in PBS (Thermo Fisher) to remove excess fixative. They proceeded to embed the tissues in paraffin and sectioned them at 5-10 \u0026mu;m thickness. The sections were deparaffinized in xylene, rehydrated through a series of graded alcohols, and antigen retrieval was performed in a citrate buffer (Solarbio). After blocking non-specific binding with a suitable blocking solution, the sections were incubated with primary antibodies specific to the target proteins overnight at 4\u0026deg;C. Following primary antibody incubation, the sections were washed in PBS and incubated with fluorophore-conjugated secondary antibodies for an hour at room temperature in the dark. Optionally, DAPI (Abcam) was applied for nuclear staining, then the sections were mounted with an anti-fade mounting medium. The sections were examined under a fluorescence microscope and images were captured, which were analyzed with image analysis software to quantify fluorescence intensity or colocalization.\u003c/p\u003e\n\u003cp\u003eAt predetermined intervals following infection, the tongues of the mice were extracted and immersed in 10% buffered formalin (Solarbio) for overnight fixation. The formalin was then drained and substituted with 70% ethanol. The processes of paraffin embedding, sectioning, and Periodic acid-Schiff staining were executed using a reagent kit (Solarbio) as per the manufacturer\u0026apos;s instructions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMurine bone marrow reconstitution experiment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRecipient mice, 6 weeks of age, were pre-conditioned with acidified water containing antibiotics (pH 2.5-3, hydrochloric acid (Solarbio), neomycin sulfate (Solarbio) 2 mg/mL) for 5 days prior to the experiment. For irradiation, 6-week-old mice were placed in a sterile container and exposed to 10 Gy radiation, followed by a rest period of 2-3 hours in their cages. Eight-week-old donor mice were euthanized, immersed in 75% alcohol, and then transferred to a biosafety cabinet for sterile processing. Femurs and tibias were isolated, stripped of residual muscle, and rinsed in PBS (Thermo Fisher). Bones were soaked in 75% alcohol in a six-well plate for 5 minutes and then transferred to PBS containing 2% penicillin/streptomycin (Gibco). Both ends of the bones were snipped off, and the bone marrow cavity was flushed with DMEM (Gibco) containing 3% inactivated FBS and 2% penicillin/streptomycin. The bone marrow was then expelled, centrifuged at 1500 rpm for 5 minutes, and the pellet was collected. The pelleted bone marrow cells were resuspended in 3 mL of red blood cell lysis buffer (Thomas Scientific) and subsequently filtered through a mesh. After lysis, the bone marrow cells were centrifuged at 4\u0026deg;C, 4000 rpm for 5 minutes, the supernatant was discarded, and cells were washed twice with 10 mL PBS. Cells were then resuspended in PBS. Recipient mice were intravenously injected with 1\u0026times;10\u003csup\u003e7\u003c/sup\u003e hematopoietic stem cells from the donor mice via the tail vein. Post-injection, recipient mice continued to be fed acidified water with antibiotics, which was changed twice a week, and the bone marrow reconstitution was allowed to proceed for 2 weeks.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProduction of BMDMs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBone marrow cells were harvested from the femurs and tibias of male C57BL/6 mice aged 6 to 8 weeks. The process involved flushing out bone marrow cells using sterile DMEM (Gibco), followed by the elimination of red blood cells via Red Blood Cell Lysis Buffer (Thomas Scientific). The cells were then cultured for 7 days in a medium containing 20% L929 conditional medium, supplemented with 10% FBS (Gibco), 100 mg/mL streptomycin, and 100 U/mL penicillin (Gibco), as outlined in previous studies. Post 7 days, the BMDMs were harvested and plated overnight in DMEM. Subsequently, these cells were subjected to various treatments as specified in individual experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eqPCR detection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA extraction was performed using NucleoZOL (Macherey Nagel). Subsequently, cDNA synthesis was carried out using the 1st Strand cDNA Synthesis Kit from Takara. Real-time PCR analysis was conducted utilizing the TB Green Premix Ex Taq ROX plus kits (Takara). The resulting data were normalized against Gapdh expression. In experiments designed to evaluate the impact of TNF-\u0026alpha; on immune cells, the cells were treated with 20 ng/mL TNF-\u0026alpha; (PeproTech) for 6 hours prior to infection with \u003cem\u003eC. albicans\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunoblot analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells underwent lysis in RIPA buffer (Beyotime), supplemented with both protease and phosphatase inhibitors from Beyotime. Protein quantification was performed utilizing the BCA Kit (Thermo Scientific). Equal amounts of proteins were resolved via SDS-PAGE, followed by their transfer onto PVDF membranes (Millipore). The membranes were then blocked using 5% skim-fat milk (Solarbio) for one hour and subsequently incubated with primary antibodies. This step was followed by the application of HRP-conjugated secondary antibodies and enhancement with ECL reagent (Absin). The chemiluminescent images thus obtained were documented using the ChemiDoc Touch Imaging System provided (Bio-Rad).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetection of immune cell infiltration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMice were euthanized one day after infection, and tongue tissues were collected. Single-cell suspensions were prepared using the aforementioned method. Subsequent experiments were conducted using different strategies. For non-secretory cytokine-producing cells: Fc receptors were blocked followed by staining with various markers for 30 minutes. After one wash, cells were filtered through a 40\u0026mu;m mesh. Live/dead cells were distinguished using LIVE/DEAD markers (Thermo Scientific) in a flow cytometer. Within the live cell population, immune cell subtypes including CD45\u003csup\u003e+\u003c/sup\u003eLy6G\u003csup\u003e+\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003e (Neutrophils), CD45\u003csup\u003e+\u003c/sup\u003eLy6C\u003csup\u003e+\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003eLy6G\u003csup\u003e\u0026ndash;\u003c/sup\u003eMHCII\u003csup\u003e\u0026ndash;\u003c/sup\u003eF4/80\u003csup\u003e-\u003c/sup\u003e (Monocytes), CD45\u003csup\u003e+\u003c/sup\u003eCD11b\u003csup\u003e+\u003c/sup\u003eF4/80\u003csup\u003e+\u003c/sup\u003e (Macrophages), CD45\u003csup\u003e+\u003c/sup\u003eMHCII\u003csup\u003ehi\u003c/sup\u003eF4/80\u003csup\u003e\u0026ndash;\u003c/sup\u003eCD11c\u003csup\u003ehi\u003c/sup\u003e (Dendritic Cells), CD45\u003csup\u003e+\u003c/sup\u003eMHCII\u003csup\u003e\u0026ndash;\u003c/sup\u003eF4/80\u003csup\u003e-\u003c/sup\u003eLy6G\u003csup\u003e\u0026ndash;\u003c/sup\u003eSSC\u003csup\u003ehi\u003c/sup\u003eCD170(Siglec-F\u003csup\u003e+\u003c/sup\u003e) (Eosinophils), and CD45\u003csup\u003e+\u003c/sup\u003eckit\u003csup\u003e+\u003c/sup\u003eFceR1\u003csup\u003e+\u003c/sup\u003e (Mast cells) were identified.\u003c/p\u003e\n\u003cp\u003eFor secretory cytokine-producing cells: After red blood cell lysis, cells were incubated with a cell stimulation cocktail (Thermo Fisher) at 37\u0026deg;C for 5 hours, followed by Fc receptor blocking and surface marker staining. After washing, cells were fixed and permeabilized using fixation/permeabilization solution (BD Bioscience). Post-permeabilization, cells were stained with cytokine antibodies for 30 minutes, washed, and then filtered through a 40\u0026mu;m mesh. Finally, within the live cell population in the flow cytometer, subtypes including CD45\u003csup\u003e+\u003c/sup\u003eCD3\u003csup\u003e+\u003c/sup\u003e\u0026gamma;\u0026delta;TCR\u003csup\u003e+\u003c/sup\u003eIL-17A\u003csup\u003e+\u0026nbsp;\u003c/sup\u003e(\u0026gamma;\u0026delta;T cells), CD45\u003csup\u003e+\u003c/sup\u003eCD3\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003e\u0026gamma;\u0026delta;TCR\u003csup\u003e-\u003c/sup\u003eIL-17A\u003csup\u003e+\u003c/sup\u003e (Th17), CD45\u003csup\u003e+\u003c/sup\u003eLineage\u003csup\u003e-\u003c/sup\u003eCD90.2\u003csup\u003e+\u003c/sup\u003eCD127\u003csup\u003e+\u003c/sup\u003eIL-17A\u003csup\u003e+\u003c/sup\u003e (ILCs), and CD45\u003csup\u003e+\u003c/sup\u003eCD3\u003csup\u003e+\u003c/sup\u003eCD4\u003csup\u003e+\u003c/sup\u003eIFN-\u0026gamma;\u003csup\u003e+\u003c/sup\u003e (Th1) were determined.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of uptake and killing\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo six-well plates were prepared, each well seeded with 5\u0026times;10\u003csup\u003e5\u003c/sup\u003e corresponding cells. The prepared \u003cem\u003eC. albicans\u0026nbsp;\u003c/em\u003espore suspension was added to the cell culture plates at a spore-to-cell ratio of 10:1 and co-incubated at 37\u0026deg;C for 30 minutes. After 30 minutes of incubation, both six-well plates were washed three times with sterile PBS. For one of the plates, cells in each well were lysed with 1 mL of sterile water, using vigorous pipetting to ensure complete cell lysis. A tenfold serial dilution of the lysate was performed, taking 100 \u0026mu;L for plating on YPD agar, and incubated at 37\u0026deg;C for 2 days. The resulting colonies were counted as uptake index and as the baseline fungal burden for the cell killing assay. Simultaneously, to the other six-well plate, 1 mL of complete medium was added, and incubation continued for an additional 2 hours. The supernatant was discarded and the wells were washed three times with PBS (Thermo Fisher). The cells in each well were lysed with 1 mL of sterile water as described above, plated on YPD agar, and incubated at 37\u0026deg;C for 2 days before counting. The bactericidal efficiency was calculated as follows: Killing efficiency = (1 - (CFU at 2 hours / CFU at 30 minutes)) \u0026times; 100%.\u003c/p\u003e\n\u003cp\u003eDetection of ROS\u003c/p\u003e\n\u003cp\u003eIn a 12-well plate, each well was seeded with 1\u0026times;10\u003csup\u003e6\u003c/sup\u003e macrophages. After allowing sufficient time for the cells to adhere, \u003cem\u003eC. albicans\u003c/em\u003e was added to stimulate the cells according to the specific experimental objectives. The cell culture medium was then discarded, and the cells were washed three times with serum-free medium. DCFH-DA (Beyotime) was diluted in serum-free medium at a 1:1000 ratio to achieve a final concentration of 10 \u0026mu;mol/L, and 500 \u0026mu;L of the diluted DCFH-DA solution was added to each well. The cells were incubated at 37\u0026deg;C for 20 minutes. The cells were then washed three times with serum-free medium to thoroughly remove any DCFH-DA that had not entered the cells. The cells were digested and resuspended as single-cell suspensions. Finally, the fluorescence intensity was measured using a spectrophotometer with an excitation wavelength of 488 nm and an emission wavelength of 525 nm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIsolation of neutrophils from bone marrow\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNeutrophils were isolated according to the instructions provided with the separation kit (Solarbio). Briefly, the cell suspension was layered over the separation solution. Centrifugation was performed at room temperature using a horizontal rotor at 500g for 30 minutes. Post-centrifugation, neutrophils in the lower layer of the centrifuge tube were aspirated, followed by washing the cells with 10 mL PBS (Thermo Fisher) or cell washing solution. The cells were then centrifuged at 250g for 10 minutes, followed by red blood cell lysis and subsequent washing centrifugation. The supernatant was discarded, and the cells were resuspended in 5 mL PBS or cell washing solution, followed by centrifugation at 250g for 10 minutes.\u003c/p\u003e\n\u003cp\u003eThe isolated neutrophils were co-cultured with supernatant from BMDMs. The BMDMs were incubated with \u003cem\u003eC. albicans\u003c/em\u003e for a 24-hour period, with the experimental conditions including either the administration of 10 ng/mL of TNF-\u0026alpha; (PeproTech) or its omission. After co-culture, neutrophils were collected for uptake, killing, and ROS production assays as described above.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCo-culturing Naive CD4\u003csup\u003e+\u003c/sup\u003e T Cells with the Supernatant from BMDMs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing the euthanasia of the mice, spleens were collected for cell isolation. Single-cell suspensions were prepared by employing a filtration technique. Naive CD4\u003csup\u003e+\u003c/sup\u003e T cells were isolated using cell microbeads (Miltenyi) as per the protocol provided by the manufacturer. These cells, at a concentration of 5\u0026times;10\u003csup\u003e5\u003c/sup\u003e, were co-cultured with the supernatant from BMDMs. The BMDMs were stimulated with \u003cem\u003eC. albicans\u003c/em\u003e for 24 hours, accompanied by either the addition or absence of 10 ng/mL of TNF-\u0026alpha; (PeproTech). During the co-culture period, the cells were stimulated with 2 \u0026mu;g/mL plate-bound anti-CD3 antibody (Bioxcell), and in the solution, 1 ng/mL TGF-\u0026beta;1 (PeproTech), 1 \u0026mu;g/mL anti-CD28 antibody (Bioxcell), 10 \u0026mu;g/mL anti-IFN-\u0026gamma; antibody (Bioxcell), and 10 \u0026mu;g/mL anti-IL-4 antibody (Bioxcell) were added. IL-6 and IL-23 were not additionally supplemented. Following the incubation period, the medium was aspirated and the cells were centrifuged. The cells were then stimulated with a cell stimulation cocktail (Thermo Fisher) for 5 hours before flow cytometric analysis of Th17 cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBinding experiment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor flow cytometry analysis, the method previously reported was employed [80]. In brief, spore or hyphal forms of \u003cem\u003eC. albicans\u003c/em\u003e were incubated in 1\u0026ndash;3% bovine serum albumin (BSA) in PBS, to which His-tagged proteins were added until reaching a final concentration of 5 \u0026mu;g/ml. This was followed by a 4-hour incubation at 4 \u0026deg;C. The fungal particles were then washed in fluorescence-activated cell sorting (FACS) buffer (0.5% BSA and 2 mM EDTA in PBS). The bound His-tagged proteins were detected using a PE-conjugated donkey anti-His antibody (BioLegend). The samples were then fixed in 1% formaldehyde (Solarbio) and subjected to analysis.\u003c/p\u003e\n\u003cp\u003eFor the ELISA assays [80], cell fractions were coated onto wells overnight at a concentration of 500 \u0026mu;g/ml (50ug/well), followed by blocking with 5% BSA in PBS (100\u0026mu;l/well). His-TREM2 at a concentration of 10\u0026mu;g/ml was then added to the wells and incubated for 2 hours at 37℃. The wells were subsequently washed with PBS containing 0.5% (v/v) Tween-20. His tag antibody (HRP) (Sino Biological) was added and incubated for an additional hour at 37℃. Following additional washing, the binding of His-TREM2 was quantified using an ELISA kit as recommended by the manufacture (Multi sciences). The reaction was terminated with stop solution, and the optical densities were measured at 450 and 630 nm by Varioskan LUX (Thermol scientific).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProduction of candidalysin mutant peptides\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll mutant candidalysin peptides were synthesized by Shanghai Chu Peptide Biotechnology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein \u003cem\u003ein vivo\u003c/em\u003e study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStarting from day 0, mice were injected every other day with 100 ng of Hsp60 (MedChemExpress), TNF-\u0026alpha; (MedChemExpress), or 1 \u0026mu;g sTREM2 (Novoprotein). Implementing oral candidiasis modeling using the aforementioned immunomodulatory methods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunoprecipitation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe target gene sequence was cloned into the pCDH-CMV plasmid, which was subsequently transfected into 293T cells using Lipofectamine 3000 (Thermo Fisher) according to the manufacturer\u0026apos;s instructions. 48 hours post-transfection, cells were lysed using RIPA buffer (CST) for total protein extraction and then subjected to a 3-hour incubation with 1 mg of the respective antibodies. This was followed by a 6-hour incubation with Protein A/G beads (Santa Cruz Biotechnology) at 4\u0026deg;C. The proteins were then eluted with a protein loading buffer and heated for 10 minutes at 95\u0026deg;C. Subsequently, the samples were processed for immunoblot analysis as described above.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGene knockdown experiment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBMDMs were seeded in 6-well plates at a density of 1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells per well. A mixture of 10 \u0026micro;L siRNA (100 pmol/mL) and 10 \u0026micro;L Advanced DNA RNA transfection reagent (Zeta Life) was prepared and incubated at room temperature for 15 minutes to allow complex formation. This mixture was then added to the wells containing 1 ml of normal DMEM medium (Gibco). 48 hours later, cells were lysed using RIPA buffer (CST), followed by protein extraction. Immunoblot analysis was then conducted as described above.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSphingolipid extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe extraction of sphingolipids from \u003cem\u003eC. albicans\u003c/em\u003e can be described utilizing an established methodology [81]. Initially augment fungal cell extracts or freeze-dried media with appropriate internal standards. Start with a primary extraction using the Mandela extraction buffer comprising a mixture of ethanol, deionized water, diethyl ether, and pyridine, supplemented with ammonium hydroxide in a specific volumetric ratio (ethanol: dH2O: diethylether: pyridine:4.2NNH4OH; 15:15:5:1:0.018; v/v). Follow this with a secondary Bligh and Dyer extraction employing methanol and chloroform. At this juncture, the samples are suitable for analyzing inorganic phosphate content, determining lipid dry weight, or isolating particular sphingolipid constituents via solid phase extraction. For the removal of glycerol backbone-containing lipid impurities, undertake a mild alkaline base hydrolysis using potassium hydroxide in methanol. If working with substantial fungal masses, initial crushing of the sample in the lipid extraction buffer using glass beads or grinding into powder with a pestle and mortar in liquid nitrogen may be necessary before proceeding with extraction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQUANTIFICATION AND STATISTICAL ANALYSIS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical methodologies were not utilized for pre-determining the sample size. In the conducted experiments, randomization was applied exclusively to \u003cem\u003ein vivo\u003c/em\u003e studies, wherein age-matched mice were randomly allocated to various experimental groups based on genotype. The allocation during experiments and during the evaluation of outcomes was known to the investigators, except in the case of microscopic analyses (such as PAS, IF, and other stainings), where blinding was maintained. Single-cell data analyses were executed using standard procedures in R packages. Fungal load and weight loss metrics were subjected to Mann-Whitney U test analysis. qPCR and flow cytometry assessments were analyzed using unpaired t tests. GraphPad Prism was employed for data analysis, considering a P value of \u0026lt;0.05 as the threshold for statistical significance. Each symbol in the graphical representations corresponds to an individual mouse or sample, with significance levels indicated as *P \u0026lt;0.05, **P \u0026lt;0.01, ***P \u0026lt;0.001, and ****P \u0026lt; 0.0001.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the key project of the National Natural Science Foundation of China (82030095) and the National Natural Science Foundation of China (81972941).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eW.D., Y.L., R.L., X.W., and K.Z. were responsible for the conceptualization of the study. R.L. and Y.L. secured funding acquisition. R.L., Y.L.and B.Y. also provided supervision for the research. W.D., Y.L., R.L., X.W., Y.X. and K.Z. contributed to the writing, review, and editing of the manuscript. W.D., Y.C., S.L., K.L., D.W., Z.Y., and W.Z. were involved in the investigation and validation aspects of the research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNikou, S.-A., et al., \u003cem\u003eCandida albicans interactions with mucosal surfaces during health and disease.\u003c/em\u003e Pathogens, 2019. \u003cstrong\u003e8\u003c/strong\u003e(2): p. 53.\u003c/li\u003e\n\u003cli\u003eSwidergall, M., et al., \u003cem\u003eEphA2 is an epithelial cell pattern recognition receptor for fungal \u0026beta;-glucans.\u003c/em\u003e Nature microbiology, 2018. \u003cstrong\u003e3\u003c/strong\u003e(1): p. 53-61.\u003c/li\u003e\n\u003cli\u003eSwidergall, M., et al., \u003cem\u003eActivation of EphA2-EGFR signaling in oral epithelial cells by Candida albicans virulence factors.\u003c/em\u003e PLoS pathogens, 2021. \u003cstrong\u003e17\u003c/strong\u003e(1): p. e1009221.\u003c/li\u003e\n\u003cli\u003eGladiator, A., et al., \u003cem\u003eCutting edge: IL-17\u0026ndash;secreting innate lymphoid cells are essential for host defense against fungal infection.\u003c/em\u003e The Journal of Immunology, 2013. \u003cstrong\u003e190\u003c/strong\u003e(2): p. 521-525.\u003c/li\u003e\n\u003cli\u003eConti, H.R., et al., \u003cem\u003eOral-resident natural Th17 cells and \u0026gamma;\u0026delta; T cells control opportunistic Candida albicans infections.\u003c/em\u003e Journal of Experimental Medicine, 2014. \u003cstrong\u003e211\u003c/strong\u003e(10): p. 2075-2084.\u003c/li\u003e\n\u003cli\u003eAggor, F.E., et al., \u003cem\u003eOral epithelial IL-22/STAT3 signaling licenses IL-17\u0026ndash;mediated immunity to oral mucosal candidiasis.\u003c/em\u003e Science immunology, 2020. \u003cstrong\u003e5\u003c/strong\u003e(48): p. eaba0570.\u003c/li\u003e\n\u003cli\u003eSwidergall, M., et al., \u003cem\u003eEphA2 is a neutrophil receptor for Candida albicans that stimulates antifungal activity during oropharyngeal infection.\u003c/em\u003e Cell reports, 2019. \u003cstrong\u003e28\u003c/strong\u003e(2): p. 423-433. e5.\u003c/li\u003e\n\u003cli\u003eBranzk, N., et al., \u003cem\u003eNeutrophils sense microbe size and selectively release neutrophil extracellular traps in response to large pathogens.\u003c/em\u003e Nature immunology, 2014. \u003cstrong\u003e15\u003c/strong\u003e(11): p. 1017-1025.\u003c/li\u003e\n\u003cli\u003eWarnatsch, A., et al., \u003cem\u003eReactive oxygen species localization programs inflammation to clear microbes of different size.\u003c/em\u003e Immunity, 2017. \u003cstrong\u003e46\u003c/strong\u003e(3): p. 421-432.\u003c/li\u003e\n\u003cli\u003eLeonhardt, J., et al., \u003cem\u003eCandida albicans \u0026beta;-glucan differentiates human monocytes into a specific subset of macrophages.\u003c/em\u003e Frontiers in immunology, 2018. \u003cstrong\u003e9\u003c/strong\u003e: p. 2818.\u003c/li\u003e\n\u003cli\u003eCheng, S.-C., et al., \u003cem\u003eInterplay between Candida albicans and the mammalian innate host defense.\u003c/em\u003e Infection and immunity, 2012. \u003cstrong\u003e80\u003c/strong\u003e(4): p. 1304-1313.\u003c/li\u003e\n\u003cli\u003eDeczkowska, A., A. 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Del Poeta, \u003cem\u003eSphingolipidomics: an important mechanistic tool for studying fungal pathogens.\u003c/em\u003e Frontiers in microbiology, 2016. \u003cstrong\u003e7\u003c/strong\u003e: p. 501.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Oropharyngeal candidiasis, Mucosal immunity, Candida albicans, Fungal immunity, TREM2, Candidalysin","lastPublishedDoi":"10.21203/rs.3.rs-4137807/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4137807/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The landscape of oral mucosal immunity, particularly in the context of oropharyngeal candidiasis (OPC), remains largely uncharted. By employing single-cell RNA sequencing (scRNA-seq) on murine models of OPC, we have illuminated the immune dynamics within this niche. We discovered a new subpopulation: TREM2-expressing macrophages, intrinsic to the oral mucosa, which infiltrated in response to Candida albicans (C. albicans) infection. However, these macrophages were significantly depleted under cortisone acetate (CA)-induced immunosuppression. This study unveiled the pattern recognition receptor (PRR) characteristics of TREM2 during OPC, where TREM2 demonstrated the ability to directly recognize candidalysin at positions G65, N73, and N91-K92, inducing downstream inflammatory signaling regulation of TNF-α, which orchestrated macrophage and neutrophil responses and influenced Th17 cell differentiation. As a result, the absence of TREM2 increases the susceptibility of mice to OPC. Conversely, administering TREM2 agonists has been shown to facilitate the clearance of OPC induced by CA in mice. Therefore, our findings expand the understanding of TREM2 beyond its known association with neurodegenerative diseases and metabolic disorders, positioning it as a key receptor in bridging the host-fungus immune interface, and providing novel therapeutic insights for glucocorticoid-induced OPC.","manuscriptTitle":"TREM2 Recognition of Candidalysin Orchestrates Mucosal Immunity in Oropharyngeal Candidiasis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-01 05:42:58","doi":"10.21203/rs.3.rs-4137807/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-microbiology","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"nmicrobiol","sideBox":"Learn more about [Nature Microbiology](http://www.nature.com/nmicrobiol/)","snPcode":"","submissionUrl":"","title":"Nature Microbiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Research","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6da817e6-7de7-4be9-ae4f-678afe995330","owner":[],"postedDate":"April 1st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":29680238,"name":"Biological sciences/Microbiology/Fungi/Fungal host response"},{"id":29680239,"name":"Health sciences/Diseases/Oral diseases/Oral candidiasis"}],"tags":[],"updatedAt":"2024-05-09T10:15:46+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-01 05:42:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4137807","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4137807","identity":"rs-4137807","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}