Tetrandrine-Driven Autophagy Suppresses SARS-CoV-2 Replication by Modulating Cholesterol and IGF Signaling Pathways

Tetrandrine-Driven Autophagy Suppresses SARS-CoV-2 Replication by Modulating Cholesterol and IGF Signaling Pathways | 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 Article Tetrandrine-Driven Autophagy Suppresses SARS-CoV-2 Replication by Modulating Cholesterol and IGF Signaling Pathways Manuela Antonioli, Lais Marchioro, Sofia De Stefanis, Beatriz Araújo, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6958516/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Jan, 2026 Read the published version in Cell Death Discovery → Version 1 posted 7 You are reading this latest preprint version Abstract SARS-CoV-2 exploits multiple host cellular processes, including autophagy—a critical intracellular degradation pathway—to facilitate viral replication and evade immune detection. Tetrandrine, a natural bis-benzylisoquinoline alkaloid derived from Stephania tetrandra , has been reported to modulate autophagy and exhibits potential antiviral properties. In this study, we investigated the effects of Tetrandrine on SARS-CoV-2 infection in human lung epithelial cells (Calu-3), with a particular focus on autophagy-related mechanisms. Our results demonstrate that Tetrandrine modulates autophagic activity in a dose-dependent manner and significantly reduces SARS-CoV-2 replication, particularly when administered prior to infection. Notably, its antiviral effect is retained in autophagy-deficient cells, indicating the involvement of autophagy-independent mechanisms. Proteomic analysis of Calu-3 cells infected with the Omicron BA.5 variant revealed that Tetrandrine regulates several host pathways implicated in viral replication, including autophagy, cholesterol metabolism, and insulin-like growth factor signaling. These findings suggest that Tetrandrine exerts multifaceted antiviral effects by targeting both autophagy-dependent and -independent cellular pathways. Collectively, our data supports the potential of Tetrandrine as a therapeutic candidate against COVID-19 and warns further evaluation in preclinical and clinical models. Data are available via ProteomeXchange with identifier PXD064448. Biological sciences/Cell biology/Autophagy Biological sciences/Drug discovery/Target identification Biological sciences/Microbiology/Antimicrobials/Antiviral agents SARS-CoV-2 Tetrandrine Autophagy Proteomic Analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has profoundly impacted global health, economies, and healthcare systems. Since its emergence in December 2019, SARS-CoV-2 has rapidly spread worldwide, leading the World Health Organization (WHO) to declare it a pandemic in March 2020 ( 1 , 2 ). Despite the development of vaccines and antiviral therapies, SARS-CoV-2 continues to pose a significant threat, particularly to individuals with comorbidities and immunosuppressive conditions. The virus is highly adaptable, with frequent mutations giving rise to variants of concern (VOCs) that can evade immune responses and, in some cases, exhibit increased transmissibility or resistance to existing treatments ( 3 , 4 ). Consequently, there is an ongoing need to identify novel therapeutic strategies that can effectively inhibit viral replication and mitigate disease progression. A defining aspect of SARS-CoV-2 is its ability to exploit host cellular processes for replication and immune evasion. Among these processes, autophagy, an evolutionarily conserved intracellular degradation pathway, plays a crucial role in host-virus interactions ( 5 ). In this context, during viral infections, including SARS-CoV-2, viruses can manipulate autophagy to enhance their replication. SARS-CoV-2 has been shown to reduce autophagy, promoting autophagic vesicles development while inhibiting degradative steps, which are essential for removing viral components ( 6 ). SARS-CoV-2 has been shown to hijack the autophagic machinery to facilitate its replication cycle inducing autophagosome formation but blocking their fusion with lysosomes ( 7 , 8 ). This blockage is mediated by viral proteins such as ORF3a and ORF7a, which inhibit autophagic flux, thereby promoting viral replication. These mechanisms ultimately create a cellular environment that favors viral persistence and immune evasion( 9 – 11 ). Given the dual role of autophagy in SARS-CoV-2 infection - both as a protective mechanism and as a pathway exploited by the virus - it has been described as a double-edged sword in COVID-19 pathogenesis. This paradox presents a major challenge in developing autophagy-targeting therapies. While some pharmacological agents that induce autophagy have been proposed as antiviral strategies, others that inhibit autophagy have also been explored, aiming to disrupt viral replication cycles ( 12 – 15 ). Thus, a deeper understanding of how autophagy modulation influences SARS-CoV-2 infection is essential for developing effective therapeutic approaches. One promising compound that has garnered attention for its autophagy-modulating and antiviral properties is Tetrandrine, a bis-benzylisoquinoline alkaloid derived from Stephania tetrandra . Traditionally used in Chinese medicine for its anti-inflammatory and immunomodulatory effects, Tetrandrine has been extensively studied for its pharmacological activities, including its ability to regulate calcium signaling, apoptosis and autophagy ( 16 ). It has been previously demonstrated that Tetrandrine exhibits antiviral effects against various pathogens, including herpes simplex virus (HSV-1), human immunodeficiency virus (HIV), Ebola virus, and MERS-CoV ( 17 – 20 ). More recently, Tetrandrine has been described as inhibiting SARS-CoV-2 replication in vitro , making it a compelling candidate for further investigation (Liu et al., 2023). Mechanistically, Tetrandrine modulates autophagy in a dose-dependent manner. At lower concentrations, it has been shown to induce autophagy, promoting the clearance of damaged cellular components. However, at higher concentrations, it inhibits autophagic flux, preventing the fusion of autophagosomes with lysosomes by its ability to antagonize calcium channels like Two-Pore Channel type 2 (TPC2), which may disrupt viral replication processes (Li et al., 2022; Liu et al., 2022; Liu et al., 2021). This dual effect suggests that Tetrandrine could either enhance the antiviral properties of autophagy or impair the virus’s ability to exploit autophagic pathways, depending on the treatment conditions. However, the precise molecular mechanisms by which Tetrandrine exerts its antiviral effects against SARS-CoV-2 remain incompletely understood. Furthermore, its anti-inflammatory properties may be beneficial in mitigating the excessive immune responses and cytokine storm associated with severe COVID-19 cases. Despite these promising findings, several questions remain regarding the exact molecular targets of Tetrandrine in the context of SARS-CoV-2 infection. Moreover, while in vitro studies suggest potent antiviral activity, further preclinical and clinical evaluations are required to determine its efficacy and safety in COVID-19 patients ( 25 ). Understanding how Tetrandrine modulates autophagy in SARS-CoV-2-infected cells and whether its antiviral effects are primarily autophagy-dependent or involve additional pathways are essential for its potential therapeutic application. This study aims to investigate the role of Tetrandrine as a therapeutic modulator of autophagy in SARS-CoV-2 infection, focusing on elucidating its molecular mechanisms of action. Specifically, we assess whether Tetrandrine’s antiviral effects are mediated through autophagy regulation or alternative cellular pathways. By combining virological assays, confocal microscopy, and proteomic analyses, we seek to provide a deeper understanding of how Tetrandrine interferes with SARS-CoV-2 replication. Results Tetrandrine modulates autophagy in Calu-3 cells and reduces SARS-CoV-2 infection It has been previously shown that SARS-CoV-2-infected cells initially activate autophagy as a survival mechanism to immediately constrain the infection; however, similarly to other viruses, SARS-CoV-2 suddenly inhibits autophagy during infection ( 26 ). Based on this evidence, we were interested in testing the ability of Tetrandrine to reduce SARS-CoV-2 infection by evaluating autophagy response. To this aim, we initially evaluated whether Tetrandrine modulates autophagy in the human lung cancer cell line Calu-3. Before proceeding, we started assessing cell proliferation and viability using the MTT assay and Trypan Blue exclusion test, respectively, in Calu-3 cells treated with 5 µM and 10 µM Tetrandrine for 24 hours, in which no significant changes in cell proliferation as well as in cell viability were observed following Tetrandrine treatment (Supplementary Fig. 1A, 1B). Therefore, Tetrandrine at these concentrations and time used for this study does not exhibit any toxic effects on our cellular model. We subsequently evaluated the effect of Tetrandrine on the autophagic pathway by treating cells with 5 µM and 10 µM Tetrandrine for 24 hours with and without the addition of the lysosome inhibitor, Bafilomycin A1, and evaluating LC3 lipidation by western blotting (Supplementary Fig. 1C). As shown, autophagy increases with Tetrandrine at the concentration of 5 µM. Meanwhile, the autophagic flux is inhibited by 10 µM of Tetrandrine since no further accumulation of LC3II has been observed following the addition of Bafilomycin A1. Altogether, these results suggest that Tetrandrine differentially modulates autophagy in Calu-3 cells in a dose-dependent manner, with autophagy induction activated at lower concentrations and autophagic flux inhibited at higher ones. Subsequently, we tested the effect of Tetrandrine on cells infected with SARS-CoV-2. To this aim, Calu-3 cells were subjected or not to previous treatment with Tetrandrine at 5 or 10 µM for 2 h. Then, cells were infected with the SARS-CoV-2 Omicron BA.5 variant at 0.2 MOI and Tetrandrine was added for 24 hours post-infection at the concentration of 5 and 10 µM. After 24 h, we performed a real-time qPCR on RNA extracted from the cells and the supernatant, monitoring for RNA encoding viral proteins E (Envelope) and S (Spike) (Fig. 1 A). Not infected cells were used as a negative control. The quantity of SARS-CoV-2 gene S in the cells was significantly reduced following Tetrandrine treatment; as shown, a strong reduction of SARS-CoV-2 genes could be observed at both concentrations, with 10 µM having a more substantial effect (Fig. 1 B). Interestingly, the inhibitory effect on viral infection was even more evident when cells were pre-treated with Tetrandrine compared to post-treated ones. Of note, Fig. 1 C reports the quantity of S gene in the supernatant, giving us a picture of SARS-CoV-2 viral particles released from Calu-3 cells. Similarly, SARS-CoV-2 gene S decreases when Tetrandrine is added. However, the post-treatment with Tetrandrine 5 µM did not show any significant difference from the control. Accordingly, the quantity of SARS-CoV-2, analyzed by evaluating gene E by qPCR, showed a similar result to gene S in both cells and supernatants (Fig. 1 D-E). Altogether, our results suggest Tetrandrine reduces SARS-CoV-2 infection with higher efficacy when administered before the infection. Therefore, we have performed our subsequent analyses by pre-treating Calu-3 cells with Tetrandrine 2 h before SARS-CoV-2 infection. Tetrandrine inhibits Calu-3 infection by blocking SARS-CoV-2 replication Based on our previous results, we focused on characterizing how Tetrandrine inhibits viral infection. To achieve this aim, we pre-treated Calu-3 cells with Tetrandrine for 2 h and then infected in the presence or absence of Tetrandrine with the SARS-CoV-2 BA.5 variant at different time points (3 h, 6 h, 10 h, and 24 h). Following the treatment, cells were fixed in 4% PFA for immunofluorescence analysis, and the supernatant was collected to monitor viral release by qPCR. To check autophagy and viral particles within the cells, we stained cellular LC3 and viral S proteins and analyzed them by immunofluorescence using confocal microscopy. As shown in Figs. 2 A and 2 B, we observed a similar amount of viral S protein 3 h post-infection (P.I.) when comparing Tetrandrine treated and untreated cells, indicating the viral uptake is not inhibited by the treatment. In contrast, while untreated Calu-3 cells showed high levels of cellular S 6 and 10 h P.I. with a subsequent decrease at 24 h P.I., Tetrandrine-treated ones did not, thus indicating that the drug inhibits SARS-CoV-2 replication. Similarly, the release of viral particles, which increased 10 h and 24 h following infection of Calu-3 cells, was strongly inhibited when cells were treated with Tetrandrine (Fig. 2 C). Moreover, to monitor autophagy response during SARS-CoV-2 infection, we quantified the area of autophagic vesicles by measuring the area of LC3 puncta per cell by immunofluorescence. Our results demonstrated that cellular LC3 strongly increases in Tetrandrine treated cells following viral infection, 5 µM being more effective than 10 µM (Fig. 2 D). This result suggests Tetrandrine was able to impact autophagy regulation in infected cells, even though SARS-CoV-2 infection did not seem to substantially impact autophagy in our cellular model when compared to untreated groups. In addition, to evaluate whether viral particles are sequestered into autophagic vesicles, we assessed co-localization of S and LC3 signals using Mander’s coefficient. As reported in Fig. 2 E, while S progressively reduced co-localization with LC3 during infection in untreated cells, the addition of Tetrandrine, which in turn increases LC3 puncta and blocks viral replication, did not show this trend. These results suggest that Tetrandrine could also impact viral particle release through autophagy. To test this hypothesis, we analyzed autophagic flux 24 h post SARS-CoV-2 infection in the presence or absence of Bafilomycin A1 and following Tetrandrine treatment. As reported in Fig. 2 F, the western blotting analysis of the autophagic markers LC3 and the relative densitometric analysis showed that autophagy was activated by 5 and 10 µM of Tetrandrine 24 h after the infection with the BA.5 variant of SARS-CoV-2. Altogether, our results indicate that the addition of Tetrandrine 2 h before SARS-CoV-2 infection induces autophagy and strongly inhibits viral replication. Autophagy and tetrandrine treatment may affect SARS-CoV-2 infection independently of each other To test whether the inhibition of SARS-CoV-2 replication by Tetrandrine is mediated by its ability to stimulate autophagy following infection, we tested both viral replication and release 24 h P.I. in Tetrandrine-treated cells with or without autophagy impairment. As shown in Fig. 3 A, we stably downregulated the abundance of the autophagic protein ATG7 by lentiviral expression of specific shRNA, thus causing a substantial inhibition of autophagy confirmed by LC3 Western blotting following Bafilomycin A1 treatment (Fig. 3 B). Stable ATG7-silenced Calu-3 cells were used to evaluate whether the effect of Tetrandrine on SARS-CoV-2 replication depends or not on autophagy. To this aim, we performed a real-time qPCR on shATG7- and scrambled shRNA (shSCR, neg. ctrl.)-treated Calu-3 cells to analyze the amount of viral gene in the cells and in the supernatant following SARS-CoV-2 infection for 24 h. As demonstrated in Fig. 3 C, we observed a decrease of the S viral gene expression in the cells following 5 and 10 µM Tetrandrine treatments, which was independent of ATG7 downregulation, thus suggesting Tetrandrine inhibits viral replication in an autophagy-independent manner. By contrast, the analysis of S gene in the supernatant (Fig. 3 D) revealed autophagy inhibition impacts viral particles released in Calu-3 cells, a mechanism that appeared uncoupled to the addition of Tetrandrine. Altogether, our results suggest that the suppression of SARS-CoV-2 replication observed by exposing Calu-3 cells to Tetrandrine is only partially assessed by its ability to activate canonical autophagy, suggesting that other pathways are involved. However, autophagy per se seems to play a relevant role in regulating the SARS-CoV-2 cycle since its inhibition affects the release of viral particles. Proteomics analysis of SARS-CoV-2-infected Calu-3 cells To further investigate how Tetrandrine inhibits SARS-CoV-2 replication, Calu-3 cells were submitted to the pre-infection treatment protocol (Fig. 1 A) and, 24 h P.I., protein extracts derived from three independent experiments were analyzed by mass spectrometry (MS)-based expression proteomics (Fig. 4 A). Protein identification was performed using MaxQuant software, and the Principal Component Analysis of the entire dataset was performed using Perseus software. As shown in Fig. 4 B, samples cluster into two main groups represented by infected and not infected cells, thus indicating the presence of SARS-CoV-2 was the main factor influencing protein abundant among the two different populations. Accordingly, the Volcano plot of differentially abundance proteins (DAPs) following SARS-CoV-2 infection (Fig. 4 C) showed viral proteins enriched only in infected cells (red dots), and 1775 cellular proteins (blue dots) are differentially abundant following SARS-CoV-2 infection. As shown, by the Bubble plot reported in Fig. 4 D, Reactome, KEGG, and Wiki pathways analyses indicated a strong modulation of mechanisms involved in SARS-CoV-2 infection, which included RNA metabolism, innate immune response, and autophagy. Therefore, our initial analysis of global proteomics-derived data underlines that the experimental settings used allow the clear discrimination of SARS-CoV-2 infected and non-infected cells, supporting the evaluation of cellular responses and pathways affected by the virus. Tetrandrine modulates the proteome of SARS-CoV-2 infected Calu-3 cells In line with previous results, the unsupervised hierarchical cluster analysis confirmed that SARS-CoV-2 infection distinguishes the two main sample groups (Fig. 5 A). Interestingly, the analysis highlighted three subgroups of Tetrandrine treatments only in SARS-CoV-2 exposed cells, indicating that Tetrandrine did not significantly modulate protein expression in basal condition but mainly following infection (Fig. 5 A). Then, to verify which pathways were altered following SARS-CoV-2 infection in Calu-3 cells, StringApp and the functional enrichment analysis tools specifically developed for Cytoscape were used to highlight cellular mechanisms altered by the infection. Based on the prior premises, we deeply analyzed infected and non-infected groups separately based on Tetrandrine treatment. The principal component analysis reported in Fig. 5 B confirmed that Tetrandrine treatment partially impacts the abundance of proteins in cells not exposed to viral infection; as shown, a slight separation of the untreated population from the Tetrandrine-treated cells could be observed independently from the used Tetrandrine concentration. By contrast, following SARS-CoV-2 infection, the untreated population strongly differs from the Tetrandrine ones, with distinct groups for 5 µM and 10 µM concentrations (Fig. 5 C). To further evaluate how Tetrandrine treatment modulates protein levels following SARS-CoV-2 infection, we extracted from the whole dataset proteins whose abundances were significantly modulated 24 h P.I. The evaluation was performed for untreated, 5 and 10 µM Tetrandrine exposed cells, separately. The Venn diagram in Fig. 5 D showed that 1824 proteins were differentially abundant (DAPs) following infection with SARS-CoV-2 and compared to non-infected cells. Considering the whole number of proteins, 164 were exclusive to the 5 µM group samples, 220 to the 10 µM group samples, and 480 specific to the untreated group. Interestingly, 74 DAPs were found to be shared among the Tetrandrine treated samples independently from concentration. Tetrandrine modulates autophagy, cholesterol and insulin-like growth factor metabolism in SARS-CoV-2-infected Calu-3 cells Since following SARS-CoV-2 infection 5 µM differed from the 10 µM Tetrandrine treatment, we compared single treatments to the untreated cells. Figure 6 A shows the Volcano plot of DAPs from infected cells following 5 µM Tetrandrine treatment. As expected, SARS-CoV-2 proteins were expressed low following Tetrandrine treatment (red dots), supporting that the drug inhibits SARS-CoV-2 replication. Then, the network of all cellular DAPs was analyzed using the application of String-DB specifically developed for Cytoscape. The reported network illustrates protein abundance differences; the color indicates red for up- and blue for down-regulation in Tetrandrine, along with the relative statistical significance as represented by the intensity of the –log(p-value) (Fig. 6 B). A Functional enrichment analysis was performed to identify pathways specifically modulated by 5 µM Tetrandrine treatment following SARS-CoV-2 infection. As shown in Fig. 6 C, 15 pathways among KEGG, Reactome, and Wiki were modulated. In line with previous results, autophagy was altered by 5 µM Tetrandrine following infection. Unexpectedly, the metabolism of cholesterol and the insulin-like growth factor were also affected by Tetrandrine treatment. We have previously shown that both 5 µM and 10 µM Tetrandrine inhibited SARS-CoV-2 replication; therefore, we performed the same pathway analysis for 10 µM Tetrandrine treatment (Fig. 7 ). According to our previous analysis, also 10 µM Tetrandrine reduced the expression of SARS-CoV-2 proteins (Fig. 7 A), further demonstrating Tetrandrine constrains viral replication. In addition, the network and the pathways analysis revealed cell adhesion and Notch3-mediated apoptosis were pathways specifically modulated by 10 µM Tetrandrine (Fig. 7 B). However, both cholesterol metabolism and insulin-like growth factor were equally altered in 5 and 10 µM Tetrandrine exposition (Fig. 7 C). Discussion One of the most impactful global health crises in modern history is represented by the COVID-19 pandemic, caused by the virus SARS-CoV-2, which has profoundly affected public health, economies, and daily life worldwide. One of the key aspects of SARS-CoV-2 pathogenesis resides in its capability to subvert host cellular mechanisms, including several processes of the immune and stress response ( e.g. autophagy). Indeed, in steady-state conditions, autophagy operates at a basal level, continuously preventing the accumulation of toxic cellular components. However, it is rapidly upregulated in response to various stressors, such as nutrient deprivation, hypoxia, and infection ( 27 ). During viral infections, autophagy is known to play a dual role. On the one hand, it serves as a defense mechanism by degrading viral components and presenting viral antigens to the immune system ( 28 ); on the other hand, it acts as a hub for viral replication and survival ( 29 ). In this regard, SARS-CoV-2 has been shown to manipulate autophagy in several ways. For instance, the virus can block the fusion of autophagosomes with lysosomes, thereby preventing the degradation of viral components and creating a favorable environment for viral replication (Silva & Travassos, 2022; Sun et al., 2023). Moreover, SARS-CoV-2 proteins, such as NSP6, have been implicated in these processes, as they promote autophagosome formation while inhibiting their fusion with lysosomes ( 26 ). By impairing the autophagic flux, the virus could evade host defenses and sustain its replication cycle ( 32 ). Overall, the numerous interactions occurring between SARS-CoV-2 and autophagic proteins further highlight the virus's ability to hijack cellular autophagy for its benefit, thus making it a potential target for COVID-19 therapy ( 33 ). In this context, our study explored the molecular mechanisms by which Tetrandrine, a potent Ca 2+ channel inhibitor ( 34 ), hampers SARS-CoV-2, with a particular focus on the role of autophagy in the viral life cycle. Our results showed that Tetrandrine modulates autophagy in a dose-dependent manner in Calu-3 cells, a human lung adenocarcinoma epithelial cell line commonly used in SARS-CoV-2 research. At a lower concentration of 5 µM, Tetrandrine induces autophagy, as evidenced by the increased turnover of LC3-II, a marker of autophagosome formation. By contrast, at a higher concentration of 10 µM, Tetrandrine inhibits the autophagic flux, preventing the fusion of autophagosomes with lysosomes. This dual effect is consistent with previous reports suggesting the capability of Tetrandrine to modulate autophagy in a dose-dependent manner, in which at lower concentrations the drug promotes autophagy by activating autophagy-related genes like ATG7 and through ROS generation and ERK activation in cancer cells model ( 35 , 36 ). At higher concentrations, it has been shown to inhibit autophagy by antagonizing TPC2, thus disrupting viral replication process (Gerndt et al., 2020; Heister & Poston, 2020). In this context, we have shown that Tetrandrine significantly reduces SARS-CoV-2 infection in Calu-3 cells, and the antiviral effect is even more relevant when the cells have been pre-treated with Tetrandrine, thus indicating that the preventive treatment may enhance drug efficacy. Quantitative PCR analysis has revealed a substantial reduction in the levels of viral genes encoding the Spike (S) and Envelope (E) proteins in Tetrandrine-treated cells, with a more marked effect observed at the higher concentrations. Interestingly, the inhibitory effect of Tetrandrine on the SARS-CoV-2 shows similar trends for both cellular and supernatant-contained viral particles, thus suggesting that the viral replication could be more affected than its release. Recently, Liu et al. (2023) have demonstrated that Tetrandrine has more significant antiviral activity, particularly during the early-entry stage of SARS-CoV-2 wild-strain infection, preventing the virus from reaching the endolysosomes in Vero-E6 cells, even if the drug was pre-incubated before infection. The authors also pointed out that, as a Ca 2+ channel blocker, Tetrandrine may hinder the maturation of trafficking-related processes through TPC2 and interfere with SARS-CoV-2 mobility within the cell, reducing viral entry. Our results suggest that the effects of Tetrandrine extend beyond just blocking TPC2 since we observed an increased number of viral particles in cell supernatant treated with Ned-19, a selective inhibitor of NAADP-induced Ca²⁺ release via TPC2 ( 39 , 40 ). In addition, we have observed the anti-viral properties of Tetrandrine both pre- and post-virus incubation against the most circulant strain, i.e. omicron BA.5, which has already been described to infect host cells via endocytosis ( 41 , 42 ). Using this system, we have dissected how Tetrandrine impairs the viral life cycle by evaluating the SARS-CoV-2 amount inside the cells at different time points post-infection by confocal microscopy. At three hours post-infection, the S signal was similar between Tetrandrine-treated and untreated cells, thus suggesting viral particles could access cells independently from the treatment. On the other hand, our results show that Tetrandrine strongly reduced S signal six hours post-infection at both concentrations, thus supporting the fact that viral replication is mainly affected by the drug. In addition, we observed an increased number of autophagic vesicles following Tetrandrine treatment during infection at both concentrations, as revealed by LC3 immunofluorescence. Intriguingly, at ten hours post-infection, viral particle release increases with a corresponding reduction of Spike-LC3 co-localization in untreated cells, thus suggesting a possible link between autophagy modulation and virus shedding. In line, the addition of Tetrandrine to infected cells stably maintained the association of viral particles to the autophagic vesicles, further suggesting that autophagy could play a role in viral release rather than viral entry and replication. In this context, it has been shown that SARS-CoV-2 proteins ( e.g. ORF7) activate LC3II leading to the accumulation of autophagosomes and then promoting the production of progeny virus ( 9 ). Additionally, the disruption of autophagy and the over-accumulation of autophagosomes can impair the viral ability to hijack cellular resources necessary for its replication and lead to cell death ( 43 , 44 ). In line, we have observed that the inhibition of autophagy by ATG7 silencing per se reduces the released viral particles, which was independent of Tetrandrine treatment. Collectively, our results suggest that autophagy contributes to SARS-CoV-2 inhibition mediated by Tetrandrine to a lesser extent. Indeed, the inhibition of autophagy obtained by ATG7 downregulation does not impact on the antiviral effects of Tetrandrine. Together, our results suggest that Tetrandrine may interfere with additional pathways beyond autophagy, thus highlighting its multifaceted nature in antiviral activity. Aimed at evaluating other pathways relevant to the anti-viral activity of Tetrandrine, we assessed the proteome of SARS-CoV-2 infected cells by mass spectrometry following the addition of Tetrandrine at different concentrations. Of note, despite Tetrandrine inhibition of SARS-CoV-2 replication being dose-independent, the two concentrations used in this study diversely impacted protein expression. This consideration prompted us to analyze the 5 µM concentration independently from 10 µM concerning untreated cells following infection. It is important to note that our data confirmed that Tetrandrine treatment strongly reduces the expression of viral proteins in both concentrations. Moreover, the data analysis identified several DEPs in Tetrandrine-treated and SARS-CoV-2-infected, which specifically belong to the cholesterol metabolism and insulin-like growth factor signaling, independently from Tetrandrine concentrations. It has been described that SARS-CoV-2 affects the insulin/IGF signaling pathway in the host cell/tissue modulating the infection ( 45 ). On the other hand, the cholesterol pathway has been involved in SARS-CoV-2 entry and replication ( 46 , 47 ) into the host cells; thereby, the capability of Tetrandrine to limit SARS-CoV-2 infection can reside in its ability to modulate these pathways when added before infection. Given the well-established roles of cholesterol metabolism in viral entry and replication and the involvement of insulin/IGF signaling in the host response to infection, these pathways may represent critical nodes through which Tetrandrine exerts its antiviral effects ( 45 , 47 ). Cholesterol metabolism has been extensively described in promoting viral entry into host cells through clathrin-mediated endocytosis, as well as maintaining the integrity of the endosomal membrane, which is crucial for the fusion and release of viral contents into the cytoplasm (Shi et al., 2016; Wrensch et al., 2014). On the other hand, alterations in cholesterol metabolism may exert significant antiviral effects based on manipulation of intracellular viral trafficking, including SARS-CoV-2 entry ( 51 – 53 ). Also, viral replication, assembly, release and immune evasion have been related to cholesterol-associated pathways( 48 ) of several viruses, SARS-CoV-2 included ( 54 – 56 ). Among cholesterol metabolism, we found that Tetrandrine upregulates Cystatin C (CST3) and SDC2 during infection. Interestingly, these two proteins have been previously described in HIV and HSV replication in the host cells, suggesting that they are possibly conserved cellular targets in many viral infections ( 57 , 58 ). Similarly to cholesterol, we identified insulin-like growth factor signaling modulated by Tetrandrine during SARS-CoV-2 infection. In this regard, it has been recently suggested that insulin could potentially facilitate the entry and replication of SARS-CoV-2 in patients with diabetes (Sun, 2023). At the same time, anti-diabetic drugs were shown to benefit diabetic patients with COVID-19 by suppressing mTOR signaling promoting autophagy and exerting anti-inflammatory effects ( 60 ). Moreover, the cholesterol synthetase DHCR24, which is induced by insulin, has been identified as downregulated in SARS-CoV-2-infected Calu-3 cells ( 61 ). Our proteomic screening identified that DHCR24 protein levels increased upon Tetrandrine treatment, suggesting another possible mechanism for its antiviral properties. These findings underscore the potential of Tetrandrine to target multiple pathways involved in SARS-CoV-2 infection, making it a versatile and promising therapeutic candidate. In summary, our study provides compelling evidence that Tetrandrine has the potential to inhibit SARS-CoV-2 infection through a combination of mechanisms, including the modulation of autophagy and interference with other cellular pathways essential for viral replication. The observed dose-dependent effects of Tetrandrine on autophagy and its ability to impact viral replication, even in the absence of autophagy, highlight the complexity of its antiviral action. Given the multifaceted roles of autophagy in viral infections and the diverse pathways influenced by Tetrandrine, our study contributes to the broader effort of identifying effective treatments for SARS-CoV-2, with Tetrandrine emerging as a promising candidate for therapeutic intervention against this ongoing global health crisis. Overall, while preclinical data are encouraging ( 62 ), comprehensive clinical evaluation is crucial to validate the efficacy and safety of Tetrandrine in COVID-19 patients. The complexity of SARS-CoV-2 pathology and the multifaceted roles of autophagy in viral infections underscore the need for a nuanced understanding of how Tetrandrine modulates these processes. By unravelling the complex interactions between Tetrandrine, autophagy, and viral replication, our research contributes to the broader scientific effort to develop effective treatments for SARS-CoV-2, ultimately aiming to mitigate viral activity and long-term symptoms. Future studies should focus on detailed clinical trials to explore the therapeutic potential of Tetrandrine in patients with COVID-19 and long-COVID. In addition, we found that Tetrandrine is more efficient in blocking SARS-CoV-2 replication when administered before infection, thus opening the possibility of evaluating its efficacy in preventing SARS-CoV-2 infection. This will provide crucial insights into its role as a potential antiviral agent and its application in the broader context of viral therapeutics. Materials and methods Drugs . Tetrandrine was purchased from Cayman Chemical, Ann Arbor, MI, USA and Bafilomycin A1 from St. Louis, Missouri, EUA. Cell culture The human lung cancer cell line, Calu-3, was used as a cellular model for the present study. Cells were cultured in Eagle’s Minimum Essential Medium (MEM; Sigma-Aldrich 51412C) integrated with 10% of Fetal Bovine Serum (FBS), L-glutamine 2µM (Corning 25-005-CI) and 1% of penicillin/streptomycin (Corning 30-001-CI). Cells were maintained in culture in sterile polystyrene plates, at 37°C and 5% of CO 2 in thermostatic incubators. At 80–90% confluence the cells were diluted following this procedure: washed twice with PBS (Dulbecco's Phosphate Buffered Saline; Euroclone ECB 4004L), detached from the plate using trypsin/EDTA (Sigma-Aldrich T3924) and, finally dilute 1:4 to new plates (Corning). SARS-CoV-2 infection SARS-CoV-2, human, Italy, clade GRA, lineage BA.5.1, Omicron (BA.5-like), strain hCoV-19/Italy/LAZ-INMI-3329/2022, former VOC Omicron GRA (B.1.1.529 + BA.*) first detected in Botswana/Hong Kong/South Africa was used to infect Calu-3 cells at a multiplicity of infection (M.O.I.) of 0.2. Viral inoculum or medium only (Not Infected) was added to cells and incubated for 1 h and 30′ at 37°C, 5% CO 2 . The viral inoculum was then removed, and cells were washed twice with PBS. Next, complete MEM was added, and cells were cultured at 37°C, 5% CO 2 . Immediately after inoculum removal (T0) or 24h post-infection, supernatants and cells were collected for the subsequent analysis. Real-time RT-PCR and viral quantification Based on the manufacturer's guidelines, total RNA was isolated from Calu-3 cells with the Direct-zol RNA MicroPrep KIT (Zymo Research Corp). To perform RT-PCR analyses, 1 µg of total RNA was reverse transcribed using AMV-reverse transcriptase (Promega Corporation) to obtain single-stranded cDNA. To analyze the supernatant, RNA was extracted from 140 µL of Calu-3 culture medium using the Qiamp viral RNA kit (Qiagen) and then eluted in 50 µL of elution buffer. To determine viral abundance, the RealStar® SARS-CoV-2 RT-PCR Kit RUO (Altona Diagnostics) was used to amplify the E − and S- SARS-CoV-2 genes by Real-time qPCR using 10 µL of RNA extracted from supernatant, or 40 ng of cellular isolated RNA. ATG7 downregulated Calu-3 cells For stable human ATG7 mRNA interference, a lentiviral ATG7 mRNA–targeting pLKO.1 plasmid was used (TRCN0000007584, Sigma-Aldrich) to produce lentiviral particles as follows: 293T cells were transiently transfected with expression vectors using the calcium phosphate method with 10 mg of lentiviral vectors, 2.5 mg of pCMV-VSV-G, and 7.5 mg of psPAX2 plasmid for 48 hours. Lentiviral particles in the supernatant were pelleted by ultracentrifugation at 19,800 RPM on an SW28 rotor for 2 hours and resuspended with 500 mL PBS every 20 mL of collected medium. 300’000 Calu-3 cells were infected twice by adding 20 mL of viral suspension to complete MEM supplemented with polybrene (4 mg/mL) for 6 and 18 hours, respectively. Following infection, cells were maintained in culture, and ATG7 expression levels were tested by Western blotting. Western blots Cells were lysed in CelLytic reagent (Sigma-Aldrich) completed with specific inhibitors: proteases inhibitor cocktail (PIC, Sigma Aldrich), phosphatases like sodium orthovanadate (Na3VO4) 0,5 µM, sodium molybdate (Na2MoO4) 5 µM, sodium fluoride (NaF) 5 µM, phenylmethanesulfonyl fluoride (PMSF) 0,5 µM and 1,10-phenanthroline (OPT) 2 µM and 2-chloroacetamide (ClCH2CONH2) 50 µM. Protein concentration was quantified using the BCA method (Thermo Fisher), and an equal amount of total protein per sample was mixed with a reducing agent (NuPAGE™ Cat. N. NP0004, Thermo Fisher) and Leamli Sample Buffer (Bio-Rad Cat. N. 1610747) and then loaded in homemade polyacrylamide gels at different concentrations for the SDS-PAGE. Proteins were transferred onto a PVDF membrane (Polyvinylidene Fluoride, Millipore) previously activated with 100% methanol, in semi-dry conditions using Transfer Blot Turbo (Bio-Rad) with a buffer consisting of 0.025 M Tris-base, 0.19 M glycine (TrisGly Bio-Rad, Cat N. 1610734) and 20% methanol. The filter was washed three times with PBS-Tween (0,1%) (T-PBS) and incubated with 5% milk solution in T-PBS for one hour to saturate non-specific sites. Incubation with the primary antibody specific to the protein of interest was performed overnight, at 4°C and stirring. The primary antibodies were diluted in 5% milk in T-PBS as indicated. After incubation, the primary antibody was removed from the filter and washed three times with T-PBS. Subsequently, a second one-hour incubation was performed using a specific peroxidase-conjugated secondary antibody diluted 1:5000 in 5% milk in T-PBS. The secondary antibody was removed, and the filter was washed three times with T-PBS. For protein detection, the PVDF membranes were incubated for three minutes with a commercial solution (ECL plus Millipore WBLUC0500 or WBLUR0500) containing the substrate for the chemiluminescence reaction catalyzed by peroxidase. Finally, the light signal was detected through a CCD camera of the ChemiDoc Touch Imaging System (Bio-Rad) associated with a digital image acquisition system. Image Lab 6.1 software from Bio-Rad was used to visualize and process images. Primary antibodies used were: Rabbit anti-LC3 (1:1000, Cell Signaling Technology 2775), Mouse anti-GADPH (1:500000, Calbiochem CB1001), Mouse anti-HSP90 (1:1000, Santa Cruz Biotechnology, sc-13,119), Goat anti-ATG7 (1:500 Santa Cruz Biotechnology, sc-8668). The secondary antibodies used (Jackson lab) were anti-rabbit (JI 711–036–152), anti-mouse (JI 715–036–150), and anti-goat (JI 705–036–147), all diluted 1:5000. Immunofluorescence For immunofluorescence analysis, Calu-3 cells were grown on glass coverslips, treated with Tetrandrine and infected as described above, and then fixed with 4% paraformaldehyde. After fixing, cells were washed twice with PBS and permeabilized by incubation with 0.5% Triton for 10 minutes at room temperature. Following a double washing with PBS, the non-specific background was reduced by blocking cells with 10% donkey serum in PBS for 30 minutes. Then, cells were incubated with primary antibodies diluted in 1% donkey serum for 1 hour at room temperature, re-washed, and incubated with secondary antibodies for 30 minutes in the dark. Finally, ProLong™ Gold Antifade Mountant (Thermo Fisher, cat. N. P36931) was added to assemble the glass coverslip on a glass slide, which was subsequently sealed. The images were acquired using LSM 900, Airyscan SR Zeiss confocal microscope. At least 30 cells per sample have been acquired and then analyzed using ImageJ Fiji software. In detail, we measured the area of viral Spike or cellular LC3 per cell by using the ‘Analyze Particles’ tool of Image J. To evaluate the Lc3-Spike colocalization, the Jacop ImageJ plug-in has been used to assess the Mander’s coefficient of Spike signal on LC3 one. Primary antibodies: Rabbit Anti-LC3 (1:200, Sigma-Aldrich, L7543), Mouse Anti- SARS-CoV-2 spike (1:200, GeneTex (Irvine, CA, USA). Secondary antibodies: anti-rabbit Alexa Fluor 488-conjugated (Thermo Fischer, A21206), anti-mouse Cy3-conjugated (Jackson ImunoResearch, 715–166 − 150). Sample preparation for mass spectrometry For whole proteome analyses of Calu-3 cells, with and without infection of SARS-CoV-2 and with the different treatments, 10 mg of protein extract per sample were incubated with 1 µM DTT, heated for 10 min at 75°C followed by 5.5 µM IAA incubated for 10 min in dark at RT. Trypsin was added with a 1:100 ratio (Trypsin: protein, w/w), and samples were left for digestion overnight at 37°C. TFA was added drop-wise to completely precipitate sodium deoxycholate and centrifuged at 14000 rpm, 23°C. Supernatants containing the peptides were STAGE tip-purified and dissolved in buffer A (0.1% formic acid in MS grade water) for LC-MS/MS measurements. Mass spectrometry-based proteomic analyses HF-X mass spectrometer in line with an EasyLC 1000 nanoflow-HPLC (Thermo Fisher Scientific) has been used for LC-MS/MS. Purified peptides were separated using a 60 minutes ramp on fused silica HPLC column tips (I.D. 75 µm, New Objective, self-packed with ReproSil-Pur 120 C18-AQ, 1.9 µm [Dr. Maisch] to a length of 20 cm) of a gradient composed by water plus 0.1% formic acid (buffer A) and increasing concentrations of 80% acetonitrile in water plus 0.1% formic acid (buffer B). The mass spectrometer was operated in data-independent mode. Each survey scan was performed with mass range m/z = 350–1,200 and resolution: 120’000, then 28 DIA scans were performed (isolation width of 31.4 m/z), thus covering a total range of precursors from 350-1,200 m/z (AGC target value: 3 x 10 6 , resolution: 30’000, and 27% of normalized collision energy)( 63 ). Protein identification and quantification were performed with Spectronaut software (v15.7, Biognosys) without imputation in direct DIA mode and using full-length Uniprot human (UniProt, 2022), SARS-CoV-2 (Uniprot, Severe acute respiratory syndrome coronavirus 2 (2019-nCoV)), and common contaminants databases. Perseus software (version 1.6.15.0) (Tyanova et al., 2016) has been used to analyze DIA results. Before performing statistical analyses, an obvious batch effect of the data of replicate 3 was removed by using the "remove batch effect" function of the Perseus software with the Limma option as method. Obtained protein quantity values were log2 converted and grouped to compare infected to non-infected cells filtered based on proteins identified in at least one group with a coverage of 90%. Missing values were imputed from normal distribution based on the total matrix (width 0.3 and downshift 1.3). The whole matrix of identifications was used to calculate the Principal Component Analysis (2 components FDR < 0.05). To generate the volcano plots, we set 250 randomizations based on two sides t-test (FDR < 0.05 and S0 = 0.1). Differentially abundant proteins between non-infected and SARS-CoV-2 infected cells were compared based on Tetrandrine treatment, and a quantitative VENN diagram was generated using the open access online software, Venny 2.1 ( https://bioinfogp.cnb.csic.es/tools/venny/ ). Hierarchical clustering of identified proteins was performed after Z-score normalization, and multiple-sample test (ANOVA) and Post hoc Tukey’s HSD test of one-way ANOVA (FDR < 0.05) were calculated for proteins among groups. Euclidean distance was used for the comparison, and clusters were extracted using n = 4 (between columns) and n = 18 (between rows). Proteins identified from SARS-CoV2 infected cells showing significant fold changes following Tetrandrine treatments were considered to analyze cellular modulated pathways. The network analysis and the visualization of cellular proteins significantly modulated were performed using the application of String-DB specifically developed for Cytoscape (v3.8.2) (StringApp) ( 64 ). In the reported networks, the difference in the colour of the nodes represents a differential fold of changes in the expression of Tetrandrine-treated cells versus untreated ones. In addition, the diameter refers to the statistical significance of the identification represented as the negative log of the p-value. The pathways analysis was performed by selecting Rectome, KEGG, and Wiki-Pathways through the Functional Enrichment analysis in Cytoscape. The analysis was performed with DAPs following Tetrandrine treatment of SARS-CoV-2 infected cells (FDR < 0.05, and redundancy = 0.4); the length of the bars represents -log of p-values of reported histograms. When changing pathways were represented through BubblePlot, the diameter of the bubble indicates the number of identified proteins. Statistical analysis Statistical analysis of the data obtained from the Western blot, MTS, Trypan Blue, and Real-Time qPCR was performed using ordinary 1-way or 2-way ANOVA with multiple comparison tests based on variable numbers. Values are shown as the mean ± SEM of at least three independent experiments. Densitometric analysis of Western blotting was performed using Image Lab 5.2.1 (Bio-Rad), with the control ratio arbitrarily defined as 1.00. For immunofluorescence analysis, the normal distribution has been verified, and the statistical analysis was performed using ANOVA 2-way test. All statistical analyses were performed using GraphPad Prism 9.0 software, considering significant P values < 0.05. Declarations Acknowledgements. Dr. Daniele Lapa for the BSL3 laboratory formation of L.O.M. at IRCCS INMI L. Spallanzani. Mohammadreza Bayat and Nesilda Qaja for sustaining M.A. in leading the IRCCS INMI L. Spallanzani laboratory activity and Confocal Images analysis, respectively. Laboratory of Emerging Viruses (LEVE), Department of Genetics, Evolution, Microbiology and Immunology, at Unicamp, specially to Dr. Jose Luiz Proença-Modena and the group of researchers, supporting the discussion of results and BSL3 laboratory formation of L.O.M. in Brazil. Conflict of Interest Statement. The authors declare no competing interests. Author Contributions. L.O.M., S.D.S. G.M., S.S.S., G.M.F., M.P., G.J.S.P., M.A. conceptualization; L.O.M., S.S., B.G.A, I.K.M.W., D.M., G.M., G.J.S.P, M.A. methodology; L.O.M., S.D.S., B.G.A., D.M, M.A. data curation and funding acquisition; G.J.S.P.; M.A.; G.M. supervision and validation; L.O.M., I.K.M.W., S.S.S., F.M., J.D., G.J.S.P., M.A. writing – review & editing; L.O.M.; G.J.S.P.; M.A. writing – original draft. All authors approved the final version of the manuscript. Ethics Statement: Ethics approval was not needed, as this study does not involve patients or animals. Funding. This study received support from Fundação de Amparo à Pesquisa do Estado de São Paulo - FAPESP: 2019/14722-4; 2022/15748-0 (G.J.S.P.); 2019/02821-8 (S.S.S.). This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES and CAPES/PrInt) - Finance Code 001 for scholarship to L.O.M.. The study has also been funded by the University and the Canton of Fribourg as part of the SKINTEGRITY.CH research network to J.D., by the Biology Department of Tor Vergata University of Rome (project acronym, AutoCuRC) to M.A., supported by the Italian Ministry of Health with Ricerca Corrente Linea 1 to IRCCS INMI L. Spallanzani (F.M., and G.M. project n. 1), and Ricerca Finalizzata (GR-2019-12369231) to M.A. The Italian Ministry of University and Research has funded the scholarship for the PhD program in Cellular and Molecular Biology to S.D.S. Data Availability. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Supplemental data. This article contains supplemental data (figures). References Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia. New England Journal of Medicine. 2020 Mar 26;382(13):1199–207. 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Available from: https://pubmed.ncbi.nlm.nih.gov/14597658/ Additional Declarations There is no conflict of interest Supplementary Files SupplFigure1.tif Supplementary Figure 1 SupplFigure2.tif Supplementary Figure 2 SupplementaryWB.tif Supplementary WB Marchioroetal.SupplmaterialSARSCoV2andTetrandrine.docx Supplementary Matherial SuppTable1.xlsx Supplementary Table Cite Share Download PDF Status: Published Journal Publication published 06 Jan, 2026 Read the published version in Cell Death Discovery → Version 1 posted Editorial decision: revise 30 Jul, 2025 Review # 1 received at journal 29 Jul, 2025 Reviewer # 1 agreed at journal 01 Jul, 2025 Reviewers invited by journal 01 Jul, 2025 Submission checks completed at journal 24 Jun, 2025 Editor assigned by journal 23 Jun, 2025 First submitted to journal 23 Jun, 2025 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-6958516","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":478895536,"identity":"ab0dfd94-d2ef-4550-82de-8ba309800104","order_by":0,"name":"Manuela Antonioli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYNCCAhjDgEGGjb2xAcTgwa/FAEQwgxk8bDwHIVrw64FrYQAaLpHAAGVhB7rtZ49JfDCwY+Cf3X/wcUGBDQ+f5OO2RzcKGGTscWgxO5OXJjnDIJlB4s5hZuMZBmk8bNKJ7cY5eBxmdiDHTJrHAOioG8lsQMZhkJY2abxazr8xk/5jUM8gD9cieZCAlhtAWxgMDjMYwLVIMBLS8sbYssfgOI/hjWRjYx6QX3jADpPg4TmAy2E5hjd+VFTLyd1IfPiY54+NnHz78WfSOX9s7NkbcFgDBRiukMCvfhSMglEwCkYBXgAABalFjoxC6K8AAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-7568-4713","institution":"IRCCS L. Spallanzani","correspondingAuthor":true,"prefix":"","firstName":"Manuela","middleName":"","lastName":"Antonioli","suffix":""},{"id":478895537,"identity":"3435a92a-0d15-4632-95b7-be48cc9e24b9","order_by":1,"name":"Lais Marchioro","email":"","orcid":"","institution":"Escola Paulista de Medicina, Universidade Federal de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Lais","middleName":"","lastName":"Marchioro","suffix":""},{"id":478895538,"identity":"ca3a8665-f007-427b-87e9-1a7b8a6f215c","order_by":2,"name":"Sofia De Stefanis","email":"","orcid":"","institution":"Tor Vergata University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Sofia","middleName":"","lastName":"De Stefanis","suffix":""},{"id":478895539,"identity":"9db678e6-9deb-424e-835d-c9c54e880ebc","order_by":3,"name":"Beatriz Araújo","email":"","orcid":"","institution":"Escola Paulista de Medicina, Universidade Federal de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Beatriz","middleName":"","lastName":"Araújo","suffix":""},{"id":478895540,"identity":"e9427e79-b8a7-4fd4-b4ea-d6fc04cc2a40","order_by":4,"name":"Davide Mariotti","email":"","orcid":"","institution":"National Institute for Infectious Diseases \"Lazzaro Spallanzani\"-IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Davide","middleName":"","lastName":"Mariotti","suffix":""},{"id":478895541,"identity":"e902b1a8-b607-4b5c-964b-b2b7ddafdf1f","order_by":5,"name":"Ingrid Watanabe","email":"","orcid":"","institution":"Escola Paulista de Medicina, Universidade Federal de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Ingrid","middleName":"","lastName":"Watanabe","suffix":""},{"id":478895542,"identity":"03a065e4-a7e8-4c2a-8898-9bdec1aa8e83","order_by":6,"name":"Michael Stumpe","email":"","orcid":"","institution":"University of Fribourg","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Stumpe","suffix":""},{"id":478895543,"identity":"449844a1-4eee-4336-a7a3-234423ed59fd","order_by":7,"name":"Giulia Matusali","email":"","orcid":"","institution":"National Institute for Infectious Diseases ‘Lazzaro Spallanzani’, IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Giulia","middleName":"","lastName":"Matusali","suffix":""},{"id":478895544,"identity":"963fb787-c858-4877-a770-4104a83577d4","order_by":8,"name":"Fabrizio Maggi","email":"","orcid":"","institution":"National Institute for Infectious Diseases \"Lazzaro Spallanzani\"-IRCCS","correspondingAuthor":false,"prefix":"","firstName":"Fabrizio","middleName":"","lastName":"Maggi","suffix":""},{"id":478895545,"identity":"1fe2c975-eec3-4d6f-9d1c-e9285b033655","order_by":9,"name":"Soraya Smaili","email":"","orcid":"https://orcid.org/0000-0001-5844-1368","institution":"Universidade Federal de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Soraya","middleName":"","lastName":"Smaili","suffix":""},{"id":478895546,"identity":"771327a5-4327-4949-b96a-440fbafdfd51","order_by":10,"name":"Jörn Dengje","email":"","orcid":"","institution":"University of Fribourg","correspondingAuthor":false,"prefix":"","firstName":"Jörn","middleName":"","lastName":"Dengje","suffix":""},{"id":478895547,"identity":"ae3feec7-d7ef-48b7-952c-bc5fefdf77c2","order_by":11,"name":"Gustavo Pereira","email":"","orcid":"","institution":"Universidade Federal de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Gustavo","middleName":"","lastName":"Pereira","suffix":""}],"badges":[],"createdAt":"2025-06-23 16:09:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6958516/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6958516/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41420-025-02926-7","type":"published","date":"2026-01-06T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85942594,"identity":"84f0957e-e4cf-40a3-8963-242961e73332","added_by":"auto","created_at":"2025-07-03 12:04:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":528174,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalysis of Omicron BA.5 SARS-CoV-2 replication in Calu-3 cells treated with Tetrandrine. \u003c/strong\u003eQuantitative real-time analysis of SARS-CoV-2 BA.5 replication in Calu-3 cells infected and/or pre-treated for two hours with (5 and 10 µM) Tetrandrine. \u003cstrong\u003eA: \u003c/strong\u003eSARS-CoV-2 infection and treatment protocol design; \u003cstrong\u003eB:\u003c/strong\u003e Number of copies/µL of the Spike gene in the intracellular medium after 24 hours of treatment; \u003cstrong\u003eC:\u003c/strong\u003e Number of copies/µL of the S gene in the extracellular medium after 24 hours of treatment; \u003cstrong\u003eD:\u003c/strong\u003e Number of copies of the E gene per µg of RNA extracted from cells after 24 hours with prior treatment; \u003cstrong\u003eE:\u003c/strong\u003e Number of copies of the E gene per µg of RNA extracted from the supernatant after 24 hours with prior treatment. All results are expressed as mean ± SEM and analyzed by one-way ANOVA followed by Tukey’s post hoc test. *p \u0026lt; 0.02; ***p \u0026lt; 0.0004; and ****p \u0026lt; 0.0001 compared to the UNT group.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/fb0426ed3bcf0eab9fd913fc.png"},{"id":85941385,"identity":"a98425e0-3f7f-42e6-b264-7807f23082ef","added_by":"auto","created_at":"2025-07-03 11:48:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1483323,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eViral replication and autophagy dynamics in Calu-3 cells infected with the SARS-CoV-2 BA.5 variant. A:\u003c/strong\u003e Representative immunofluorescence images of cellular LC3 (green) and viral Spike (red) in cells pre-treated with Tetrandrine at 5 or 10 µM at different time points post-infection (P.I.) with SARS-CoV-2 BA.5. Scale: 10 µm; \u003cstrong\u003eB:\u003c/strong\u003e Quantification of Spike-positive area per cell expressed as a percentage of the total cellular area; \u003cstrong\u003eC:\u003c/strong\u003eQuantitative real-time PCR of the S gene in the supernatant at different time points P.I.; \u003cstrong\u003eD:\u003c/strong\u003e Quantification of LC3-positive area per cell expressed as a percentage of the total cellular area; \u003cstrong\u003eE:\u003c/strong\u003e Mander’s coefficient for Spike localization in LC3; \u003cstrong\u003eF:\u003c/strong\u003e Evaluation of autophagic flux 24 hours P.I. in cells pre-treated with Tetrandrine at 5 and 10 µM. Bafilomycin A1 was added 2 hours before the lysis, and LC3 and HSP90 were analyzed by Western blotting using anti-LC3 (14 kDa) and anti-HSP90 (90 kDa) antibodies. The optical density representing the relative expression of each protein was normalized using internal control for the anti-HSP90 (90 kDa) antibody, as shown in the representations.\u003cstrong\u003e \u003c/strong\u003eAll results are expressed as mean ± SEM and analyzed by one-way ANOVA followed by Tukey’s post hoc test. **p \u0026lt; 0.003; ***p \u0026lt; 0.0004; and ****p \u0026lt; 0.0001 compared to the UNT group.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/c321ece41654ee06e7df18c5.png"},{"id":85941389,"identity":"314e694a-05d1-469e-93b5-d6d773d76009","added_by":"auto","created_at":"2025-07-03 11:48:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":295910,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalysis of BA.5 variant viral replication in Calu-3 cells with ATG7 silencing and treated with Tetrandrine. \u003c/strong\u003eCalu-3 cells with stable ATG7 silencing were pre-treated with Tetrandrine at 5 and 10 µM and subsequently infected with SARS-CoV-2 in the presence or absence of Tetrandrine for 24 hours.\u003cstrong\u003e A:\u003c/strong\u003e Western blotting analysis of ATG7 protein levels using the anti-ATG7 (70 kDa) antibody; \u003cstrong\u003eB:\u003c/strong\u003e Western blotting analysis of LC3 protein levels using the anti-LC3 (14 kDa) antibody, with or without lysosomal inhibition by Bafilomycin A1. The optical density representing the relative expression of each protein was normalized using the internal control for the anti-HSP90 (90 kDa) or anti-GAPDH (40 kDa) antibody, as shown in the representations; \u003cstrong\u003eC-D:\u003c/strong\u003e Quantitative real-time PCR analysis of the S gene of the SARS-CoV-2 BA.5 variant in infected cells (\u003cstrong\u003eC\u003c/strong\u003e) or its release in the supernatant (\u003cstrong\u003eD\u003c/strong\u003e). All results are expressed as mean ± SEM and analyzed by one-way ANOVA followed by Tukey’s post hoc test. ****p \u0026lt; 0.0001 compared to the UNT group.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/58bc751344fab93ada37b1c7.png"},{"id":85943568,"identity":"bcb0bd6f-6edd-495f-b068-5a639f2a2ef1","added_by":"auto","created_at":"2025-07-03 12:12:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":701646,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProteomic analysis of Calu-3 cells infected with the SARS-CoV-2 BA.5 variant. \u003c/strong\u003eProtein extracts derived from Calu-3 cells, either infected or uninfected for 24 hours with the SARS-CoV-2 BA.5.1 variant and treated with Tetrandrine, were subjected to proteomic analysis.\u003cstrong\u003e A:\u003c/strong\u003e Experimental workflow of the proteomic analysis; \u003cstrong\u003eB:\u003c/strong\u003e Principal Component Analysis (PCA) showing the clustering of infected and uninfected cells; \u003cstrong\u003eC:\u003c/strong\u003e Volcano plot displaying the 1,775 differentially expressed proteins (DEPs) between SARS-CoV-2-infected cells (right) and uninfected cells (left). Cellular proteins are shown in blue, while viral proteins are shown in red; \u003cstrong\u003eD:\u003c/strong\u003e Pathway enrichment analysis performed using the STRING-App in Cytoscape, selecting WikiPathways, Reactome, and KEGG pathways.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/43eac8613e547109b66a5242.png"},{"id":85941399,"identity":"669967ec-9608-4826-81fe-8d132387e0cf","added_by":"auto","created_at":"2025-07-03 11:48:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":564794,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProteomic analysis of SARS-CoV-2-infected Calu-3 cells based on Tetrandrine treatment.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA: \u003c/strong\u003eHierarchical clustering analysis of non-infected (NI) and infected (SARS-CoV-2) cells under different conditions: Tetrandrine pre-treatment or Non-treatment; \u003cstrong\u003eB:\u003c/strong\u003ePrincipal Component Analysis (PCA) of uninfected cells and; \u003cstrong\u003eC:\u003c/strong\u003eSARS-CoV-2-infected cells, highlighting clustering based on different Tetrandrine treatment conditions; \u003cstrong\u003eD:\u003c/strong\u003e Venn diagram of all differentially expressed proteins (DEPs) identified in SARS-CoV-2-infected cells following Tetrandrine treatment.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/82a39150341b6905f0749766.png"},{"id":85941411,"identity":"53b5c3f7-2e57-4b19-a5c4-0d004574ad84","added_by":"auto","created_at":"2025-07-03 11:48:49","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":982585,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSignaling pathway analysis comparing SARS-CoV-2-infected Calu-3 cells untreated and pre-treated with Tetrandrine at 5 μM. A:\u003c/strong\u003e Volcano plot comparing untreated SARS-CoV-2-infected Calu-3 cells (left) and pre-treated cells with Tetrandrine at 5 µM (right). Cellular differentially expressed proteins (DEPs) are shown in blue, and viral proteins are shown in red; \u003cstrong\u003eB:\u003c/strong\u003e Protein network analysis using STRING; \u003cstrong\u003eC:\u003c/strong\u003e Pathway enrichment analysis performed using the STRING app in Cytoscape, with the WikiPathway, Reactome, and KEGG databases.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/2e329d34c99b6406b3d6d431.png"},{"id":85941403,"identity":"c597b9d9-1559-469c-8e72-1ab05338a248","added_by":"auto","created_at":"2025-07-03 11:48:49","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1178253,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSignaling pathway analysis comparing SARS-CoV-2-infected Calu-3 cells untreated and pre-treated with Tetrandrine at 10 μM. A:\u003c/strong\u003e Volcano plot comparing untreated SARS-CoV-2-infected Calu-3 cells (left) and cells pre-treated with Tetrandrine at 10 μM (right). Cellular differentially expressed proteins (DEPs) are shown in blue, and viral proteins are shown in red; \u003cstrong\u003eB:\u003c/strong\u003e Protein network analysis using STRING; \u003cstrong\u003eC:\u003c/strong\u003e Pathway enrichment analysis performed using the STRING app in Cytoscape, with the WikiPathway, Reactome, and KEGG databases.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/a88ea6c1e76a4b89046532bb.png"},{"id":85942399,"identity":"dd1bc82c-c656-44ff-b386-7b4dba26b13e","added_by":"auto","created_at":"2025-07-03 11:56:48","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":765506,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eViral cycle and potential actions of Tetrandrine on SARS-CoV-2 replication. \u003c/strong\u003eThere are two distinct pathways for SARS-CoV-2 entry (showed in the diagram in blue), in which the virus can either fuse with the cell membrane to release its genetic material or be internalized via the endocytic pathway. Viral structural proteins and genomic RNA are produced at the replication site and then translocated to the Golgi compartment, where new viruses are packaged and budded until they reach the plasma membrane and are released into the extracellular medium.\u003cstrong\u003e \u003c/strong\u003eIn parallel, viral proteins can activate the autophagic mechanism (pink diagram), which leads to viral degradation or exocytosis. However, SARS-CoV-2 possesses viral escape mechanisms that benefit from the autophagic pathway.\u003cstrong\u003e \u003c/strong\u003eTetrandrine, in turn, may interfere with some steps of the viral cycle, leading to a decrease in viral load, through:\u003cstrong\u003e1: \u003c/strong\u003eaction on the cholesterol pathway, preventing viral release and/or the formation of new viruses; \u003cstrong\u003e2: \u003c/strong\u003einduction of autophagy; \u003cstrong\u003e3: \u003c/strong\u003eblockade of the final phase of autophagy, possibly associated with TPC channels; \u003cstrong\u003e4: \u003c/strong\u003emodulation of insulin metabolism, leading to dysregulation, which culminates in mTOR inhibition and consequent activation of autophagy.\u003cstrong\u003e \u003c/strong\u003e(Prepared by the author with Biorender.com, 2025).\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/52215f514da9081fb653bea1.png"},{"id":102095054,"identity":"979cf93d-0914-4296-9fc4-5bb574e0ebce","added_by":"auto","created_at":"2026-02-07 08:14:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7893838,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/4bc4631b-cd57-4370-b3f5-943aa8de6d19.pdf"},{"id":85942392,"identity":"a4ceb523-6256-478e-9fcb-5fa876c24a43","added_by":"auto","created_at":"2025-07-03 11:56:48","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":82040,"visible":true,"origin":"","legend":"Supplementary Figure 1","description":"","filename":"SupplFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/99dfe7a2641b90be9498d719.tif"},{"id":85941387,"identity":"f74deb9e-13f4-4a1d-a373-29210bb4f3bc","added_by":"auto","created_at":"2025-07-03 11:48:48","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":97690,"visible":true,"origin":"","legend":"Supplementary Figure 2","description":"","filename":"SupplFigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/4daa3c8342a5ed356593002a.tif"},{"id":85941396,"identity":"d15b6f44-c6bf-4733-85d7-25c28d873dc6","added_by":"auto","created_at":"2025-07-03 11:48:48","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":296832,"visible":true,"origin":"","legend":"Supplementary WB","description":"","filename":"SupplementaryWB.tif","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/c67a89f9fabec3805bf9cf31.tif"},{"id":85942395,"identity":"6eee43c5-fa0e-4a6b-af18-289c1bdcf4ab","added_by":"auto","created_at":"2025-07-03 11:56:48","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":32226,"visible":true,"origin":"","legend":"Supplementary Matherial","description":"","filename":"Marchioroetal.SupplmaterialSARSCoV2andTetrandrine.docx","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/b3afa91143896304c855b666.docx"},{"id":85942598,"identity":"7284855c-eccd-42a2-898e-df292c9fe359","added_by":"auto","created_at":"2025-07-03 12:04:48","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":766619,"visible":true,"origin":"","legend":"Supplementary Table","description":"","filename":"SuppTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6958516/v1/33a5218860d78e537099e650.xlsx"}],"financialInterests":"There is no conflict of interest","formattedTitle":"Tetrandrine-Driven Autophagy Suppresses SARS-CoV-2 Replication by Modulating Cholesterol and IGF Signaling Pathways","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has profoundly impacted global health, economies, and healthcare systems. Since its emergence in December 2019, SARS-CoV-2 has rapidly spread worldwide, leading the World Health Organization (WHO) to declare it a pandemic in March 2020 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Despite the development of vaccines and antiviral therapies, SARS-CoV-2 continues to pose a significant threat, particularly to individuals with comorbidities and immunosuppressive conditions. The virus is highly adaptable, with frequent mutations giving rise to variants of concern (VOCs) that can evade immune responses and, in some cases, exhibit increased transmissibility or resistance to existing treatments (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Consequently, there is an ongoing need to identify novel therapeutic strategies that can effectively inhibit viral replication and mitigate disease progression.\u003c/p\u003e \u003cp\u003eA defining aspect of SARS-CoV-2 is its ability to exploit host cellular processes for replication and immune evasion. Among these processes, autophagy, an evolutionarily conserved intracellular degradation pathway, plays a crucial role in host-virus interactions (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In this context, during viral infections, including SARS-CoV-2, viruses can manipulate autophagy to enhance their replication. SARS-CoV-2 has been shown to reduce autophagy, promoting autophagic vesicles development while inhibiting degradative steps, which are essential for removing viral components (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSARS-CoV-2 has been shown to hijack the autophagic machinery to facilitate its replication cycle inducing autophagosome formation but blocking their fusion with lysosomes (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). This blockage is mediated by viral proteins such as ORF3a and ORF7a, which inhibit autophagic flux, thereby promoting viral replication. These mechanisms ultimately create a cellular environment that favors viral persistence and immune evasion(\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Given the dual role of autophagy in SARS-CoV-2 infection - both as a protective mechanism and as a pathway exploited by the virus - it has been described as a double-edged sword in COVID-19 pathogenesis. This paradox presents a major challenge in developing autophagy-targeting therapies. While some pharmacological agents that induce autophagy have been proposed as antiviral strategies, others that inhibit autophagy have also been explored, aiming to disrupt viral replication cycles (\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Thus, a deeper understanding of how autophagy modulation influences SARS-CoV-2 infection is essential for developing effective therapeutic approaches.\u003c/p\u003e \u003cp\u003eOne promising compound that has garnered attention for its autophagy-modulating and antiviral properties is Tetrandrine, a bis-benzylisoquinoline alkaloid derived from \u003cem\u003eStephania tetrandra\u003c/em\u003e. Traditionally used in Chinese medicine for its anti-inflammatory and immunomodulatory effects, Tetrandrine has been extensively studied for its pharmacological activities, including its ability to regulate calcium signaling, apoptosis and autophagy (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). It has been previously demonstrated that Tetrandrine exhibits antiviral effects against various pathogens, including herpes simplex virus (HSV-1), human immunodeficiency virus (HIV), Ebola virus, and MERS-CoV (\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). More recently, Tetrandrine has been described as inhibiting SARS-CoV-2 replication \u003cem\u003ein vitro\u003c/em\u003e, making it a compelling candidate for further investigation (Liu et al., 2023).\u003c/p\u003e \u003cp\u003eMechanistically, Tetrandrine modulates autophagy in a dose-dependent manner. At lower concentrations, it has been shown to induce autophagy, promoting the clearance of damaged cellular components. However, at higher concentrations, it inhibits autophagic flux, preventing the fusion of autophagosomes with lysosomes by its ability to antagonize calcium channels like Two-Pore Channel type 2 (TPC2), which may disrupt viral replication processes (Li et al., 2022; Liu et al., 2022; Liu et al., 2021). This dual effect suggests that Tetrandrine could either enhance the antiviral properties of autophagy or impair the virus\u0026rsquo;s ability to exploit autophagic pathways, depending on the treatment conditions. However, the precise molecular mechanisms by which Tetrandrine exerts its antiviral effects against SARS-CoV-2 remain incompletely understood. Furthermore, its anti-inflammatory properties may be beneficial in mitigating the excessive immune responses and cytokine storm associated with severe COVID-19 cases.\u003c/p\u003e \u003cp\u003eDespite these promising findings, several questions remain regarding the exact molecular targets of Tetrandrine in the context of SARS-CoV-2 infection. Moreover, while \u003cem\u003ein vitro\u003c/em\u003e studies suggest potent antiviral activity, further preclinical and clinical evaluations are required to determine its efficacy and safety in COVID-19 patients (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Understanding how Tetrandrine modulates autophagy in SARS-CoV-2-infected cells and whether its antiviral effects are primarily autophagy-dependent or involve additional pathways are essential for its potential therapeutic application.\u003c/p\u003e \u003cp\u003eThis study aims to investigate the role of Tetrandrine as a therapeutic modulator of autophagy in SARS-CoV-2 infection, focusing on elucidating its molecular mechanisms of action. Specifically, we assess whether Tetrandrine\u0026rsquo;s antiviral effects are mediated through autophagy regulation or alternative cellular pathways. By combining virological assays, confocal microscopy, and proteomic analyses, we seek to provide a deeper understanding of how Tetrandrine interferes with SARS-CoV-2 replication.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eTetrandrine modulates autophagy in Calu-3 cells and reduces SARS-CoV-2 infection\u003c/h2\u003e \u003cp\u003eIt has been previously shown that SARS-CoV-2-infected cells initially activate autophagy as a survival mechanism to immediately constrain the infection; however, similarly to other viruses, SARS-CoV-2 suddenly inhibits autophagy during infection (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Based on this evidence, we were interested in testing the ability of Tetrandrine to reduce SARS-CoV-2 infection by evaluating autophagy response. To this aim, we initially evaluated whether Tetrandrine modulates autophagy in the human lung cancer cell line Calu-3. Before proceeding, we started assessing cell proliferation and viability using the MTT assay and Trypan Blue exclusion test, respectively, in Calu-3 cells treated with 5 \u0026micro;M and 10 \u0026micro;M Tetrandrine for 24 hours, in which no significant changes in cell proliferation as well as in cell viability were observed following Tetrandrine treatment (Supplementary Fig.\u0026nbsp;1A, 1B). Therefore, Tetrandrine at these concentrations and time used for this study does not exhibit any toxic effects on our cellular model. We subsequently evaluated the effect of Tetrandrine on the autophagic pathway by treating cells with 5 \u0026micro;M and 10 \u0026micro;M Tetrandrine for 24 hours with and without the addition of the lysosome inhibitor, Bafilomycin A1, and evaluating LC3 lipidation by western blotting (Supplementary Fig.\u0026nbsp;1C). As shown, autophagy increases with Tetrandrine at the concentration of 5 \u0026micro;M. Meanwhile, the autophagic flux is inhibited by 10 \u0026micro;M of Tetrandrine since no further accumulation of LC3II has been observed following the addition of Bafilomycin A1. Altogether, these results suggest that Tetrandrine differentially modulates autophagy in Calu-3 cells in a dose-dependent manner, with autophagy induction activated at lower concentrations and autophagic flux inhibited at higher ones.\u003c/p\u003e \u003cp\u003eSubsequently, we tested the effect of Tetrandrine on cells infected with SARS-CoV-2. To this aim, Calu-3 cells were subjected or not to previous treatment with Tetrandrine at 5 or 10 \u0026micro;M for 2 h. Then, cells were infected with the SARS-CoV-2 Omicron BA.5 variant at 0.2 MOI and Tetrandrine was added for 24 hours post-infection at the concentration of 5 and 10 \u0026micro;M. After 24 h, we performed a real-time qPCR on RNA extracted from the cells and the supernatant, monitoring for RNA encoding viral proteins E (Envelope) and S (Spike) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Not infected cells were used as a negative control. The quantity of SARS-CoV-2 gene S in the cells was significantly reduced following Tetrandrine treatment; as shown, a strong reduction of SARS-CoV-2 genes could be observed at both concentrations, with 10 \u0026micro;M having a more substantial effect (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Interestingly, the inhibitory effect on viral infection was even more evident when cells were pre-treated with Tetrandrine compared to post-treated ones. Of note, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC reports the quantity of S gene in the supernatant, giving us a picture of SARS-CoV-2 viral particles released from Calu-3 cells. Similarly, SARS-CoV-2 gene S decreases when Tetrandrine is added. However, the post-treatment with Tetrandrine 5 \u0026micro;M did not show any significant difference from the control. Accordingly, the quantity of SARS-CoV-2, analyzed by evaluating gene E by qPCR, showed a similar result to gene S in both cells and supernatants (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD-E). Altogether, our results suggest Tetrandrine reduces SARS-CoV-2 infection with higher efficacy when administered before the infection. Therefore, we have performed our subsequent analyses by pre-treating Calu-3 cells with Tetrandrine 2 h before SARS-CoV-2 infection.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTetrandrine inhibits Calu-3 infection by blocking SARS-CoV-2 replication\u003c/h3\u003e\n\u003cp\u003eBased on our previous results, we focused on characterizing how Tetrandrine inhibits viral infection. To achieve this aim, we pre-treated Calu-3 cells with Tetrandrine for 2 h and then infected in the presence or absence of Tetrandrine with the SARS-CoV-2 BA.5 variant at different time points (3 h, 6 h, 10 h, and 24 h). Following the treatment, cells were fixed in 4% PFA for immunofluorescence analysis, and the supernatant was collected to monitor viral release by qPCR. To check autophagy and viral particles within the cells, we stained cellular LC3 and viral S proteins and analyzed them by immunofluorescence using confocal microscopy. As shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, we observed a similar amount of viral S protein 3 h post-infection (P.I.) when comparing Tetrandrine treated and untreated cells, indicating the viral uptake is not inhibited by the treatment. In contrast, while untreated Calu-3 cells showed high levels of cellular S 6 and 10 h P.I. with a subsequent decrease at 24 h P.I., Tetrandrine-treated ones did not, thus indicating that the drug inhibits SARS-CoV-2 replication. Similarly, the release of viral particles, which increased 10 h and 24 h following infection of Calu-3 cells, was strongly inhibited when cells were treated with Tetrandrine (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMoreover, to monitor autophagy response during SARS-CoV-2 infection, we quantified the area of autophagic vesicles by measuring the area of LC3 puncta per cell by immunofluorescence. Our results demonstrated that cellular LC3 strongly increases in Tetrandrine treated cells following viral infection, 5 \u0026micro;M being more effective than 10 \u0026micro;M (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). This result suggests Tetrandrine was able to impact autophagy regulation in infected cells, even though SARS-CoV-2 infection did not seem to substantially impact autophagy in our cellular model when compared to untreated groups.\u003c/p\u003e \u003cp\u003eIn addition, to evaluate whether viral particles are sequestered into autophagic vesicles, we assessed co-localization of S and LC3 signals using Mander\u0026rsquo;s coefficient. As reported in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE, while S progressively reduced co-localization with LC3 during infection in untreated cells, the addition of Tetrandrine, which in turn increases LC3 puncta and blocks viral replication, did not show this trend. These results suggest that Tetrandrine could also impact viral particle release through autophagy. To test this hypothesis, we analyzed autophagic flux 24 h post SARS-CoV-2 infection in the presence or absence of Bafilomycin A1 and following Tetrandrine treatment. As reported in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF, the western blotting analysis of the autophagic markers LC3 and the relative densitometric analysis showed that autophagy was activated by 5 and 10 \u0026micro;M of Tetrandrine 24 h after the infection with the BA.5 variant of SARS-CoV-2. Altogether, our results indicate that the addition of Tetrandrine 2 h before SARS-CoV-2 infection induces autophagy and strongly inhibits viral replication.\u003c/p\u003e\n\u003ch3\u003eAutophagy and tetrandrine treatment may affect SARS-CoV-2 infection independently of each other\u003c/h3\u003e\n\u003cp\u003eTo test whether the inhibition of SARS-CoV-2 replication by Tetrandrine is mediated by its ability to stimulate autophagy following infection, we tested both viral replication and release 24 h P.I. in Tetrandrine-treated cells with or without autophagy impairment. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, we stably downregulated the abundance of the autophagic protein ATG7 by lentiviral expression of specific shRNA, thus causing a substantial inhibition of autophagy confirmed by LC3 Western blotting following Bafilomycin A1 treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Stable ATG7-silenced Calu-3 cells were used to evaluate whether the effect of Tetrandrine on SARS-CoV-2 replication depends or not on autophagy. To this aim, we performed a real-time qPCR on shATG7- and scrambled shRNA (shSCR, neg. ctrl.)-treated Calu-3 cells to analyze the amount of viral gene in the cells and in the supernatant following SARS-CoV-2 infection for 24 h.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs demonstrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, we observed a decrease of the S viral gene expression in the cells following 5 and 10 \u0026micro;M Tetrandrine treatments, which was independent of ATG7 downregulation, thus suggesting Tetrandrine inhibits viral replication in an autophagy-independent manner. By contrast, the analysis of S gene in the supernatant (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD) revealed autophagy inhibition impacts viral particles released in Calu-3 cells, a mechanism that appeared uncoupled to the addition of Tetrandrine. Altogether, our results suggest that the suppression of SARS-CoV-2 replication observed by exposing Calu-3 cells to Tetrandrine is only partially assessed by its ability to activate canonical autophagy, suggesting that other pathways are involved. However, autophagy \u003cem\u003eper se\u003c/em\u003e seems to play a relevant role in regulating the SARS-CoV-2 cycle since its inhibition affects the release of viral particles.\u003c/p\u003e\n\u003ch3\u003eProteomics analysis of SARS-CoV-2-infected Calu-3 cells\u003c/h3\u003e\n\u003cp\u003eTo further investigate how Tetrandrine inhibits SARS-CoV-2 replication, Calu-3 cells were submitted to the pre-infection treatment protocol (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) and, 24 h P.I., protein extracts derived from three independent experiments were analyzed by mass spectrometry (MS)-based expression proteomics (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Protein identification was performed using MaxQuant software, and the Principal Component Analysis of the entire dataset was performed using Perseus software. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, samples cluster into two main groups represented by infected and not infected cells, thus indicating the presence of SARS-CoV-2 was the main factor influencing protein abundant among the two different populations. Accordingly, the Volcano plot of differentially abundance proteins (DAPs) following SARS-CoV-2 infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC) showed viral proteins enriched only in infected cells (red dots), and 1775 cellular proteins (blue dots) are differentially abundant following SARS-CoV-2 infection. As shown, by the Bubble plot reported in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD, Reactome, KEGG, and Wiki pathways analyses indicated a strong modulation of mechanisms involved in SARS-CoV-2 infection, which included RNA metabolism, innate immune response, and autophagy. Therefore, our initial analysis of global proteomics-derived data underlines that the experimental settings used allow the clear discrimination of SARS-CoV-2 infected and non-infected cells, supporting the evaluation of cellular responses and pathways affected by the virus.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTetrandrine modulates the proteome of SARS-CoV-2 infected Calu-3 cells\u003c/h3\u003e\n\u003cp\u003eIn line with previous results, the unsupervised hierarchical cluster analysis confirmed that SARS-CoV-2 infection distinguishes the two main sample groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Interestingly, the analysis highlighted three subgroups of Tetrandrine treatments only in SARS-CoV-2 exposed cells, indicating that Tetrandrine did not significantly modulate protein expression in basal condition but mainly following infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Then, to verify which pathways were altered following SARS-CoV-2 infection in Calu-3 cells, StringApp and the functional enrichment analysis tools specifically developed for Cytoscape were used to highlight cellular mechanisms altered by the infection. Based on the prior premises, we deeply analyzed infected and non-infected groups separately based on Tetrandrine treatment. The principal component analysis reported in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB confirmed that Tetrandrine treatment partially impacts the abundance of proteins in cells not exposed to viral infection; as shown, a slight separation of the untreated population from the Tetrandrine-treated cells could be observed independently from the used Tetrandrine concentration. By contrast, following SARS-CoV-2 infection, the untreated population strongly differs from the Tetrandrine ones, with distinct groups for 5 \u0026micro;M and 10 \u0026micro;M concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). To further evaluate how Tetrandrine treatment modulates protein levels following SARS-CoV-2 infection, we extracted from the whole dataset proteins whose abundances were significantly modulated 24 h P.I. The evaluation was performed for untreated, 5 and 10 \u0026micro;M Tetrandrine exposed cells, separately. The Venn diagram in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD showed that 1824 proteins were differentially abundant (DAPs) following infection with SARS-CoV-2 and compared to non-infected cells. Considering the whole number of proteins, 164 were exclusive to the 5 \u0026micro;M group samples, 220 to the 10 \u0026micro;M group samples, and 480 specific to the untreated group. Interestingly, 74 DAPs were found to be shared among the Tetrandrine treated samples independently from concentration.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTetrandrine modulates autophagy, cholesterol and insulin-like growth factor metabolism in SARS-CoV-2-infected Calu-3 cells\u003c/h2\u003e \u003cp\u003eSince following SARS-CoV-2 infection 5 \u0026micro;M differed from the 10 \u0026micro;M Tetrandrine treatment, we compared single treatments to the untreated cells. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA shows the Volcano plot of DAPs from infected cells following 5 \u0026micro;M Tetrandrine treatment. As expected, SARS-CoV-2 proteins were expressed low following Tetrandrine treatment (red dots), supporting that the drug inhibits SARS-CoV-2 replication. Then, the network of all cellular DAPs was analyzed using the application of String-DB specifically developed for Cytoscape. The reported network illustrates protein abundance differences; the color indicates red for up- and blue for down-regulation in Tetrandrine, along with the relative statistical significance as represented by the intensity of the \u0026ndash;log(p-value) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). A Functional enrichment analysis was performed to identify pathways specifically modulated by 5 \u0026micro;M Tetrandrine treatment following SARS-CoV-2 infection. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC, 15 pathways among KEGG, Reactome, and Wiki were modulated. In line with previous results, autophagy was altered by 5 \u0026micro;M Tetrandrine following infection. Unexpectedly, the metabolism of cholesterol and the insulin-like growth factor were also affected by Tetrandrine treatment.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe have previously shown that both 5 \u0026micro;M and 10 \u0026micro;M Tetrandrine inhibited SARS-CoV-2 replication; therefore, we performed the same pathway analysis for 10 \u0026micro;M Tetrandrine treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). According to our previous analysis, also 10 \u0026micro;M Tetrandrine reduced the expression of SARS-CoV-2 proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA), further demonstrating Tetrandrine constrains viral replication. In addition, the network and the pathways analysis revealed cell adhesion and Notch3-mediated apoptosis were pathways specifically modulated by 10 \u0026micro;M Tetrandrine (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). However, both cholesterol metabolism and insulin-like growth factor were equally altered in 5 and 10 \u0026micro;M Tetrandrine exposition (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOne of the most impactful global health crises in modern history is represented by the COVID-19 pandemic, caused by the virus SARS-CoV-2, which has profoundly affected public health, economies, and daily life worldwide. One of the key aspects of SARS-CoV-2 pathogenesis resides in its capability to subvert host cellular mechanisms, including several processes of the immune and stress response (\u003cem\u003ee.g.\u003c/em\u003e autophagy). Indeed, in steady-state conditions, autophagy operates at a basal level, continuously preventing the accumulation of toxic cellular components. However, it is rapidly upregulated in response to various stressors, such as nutrient deprivation, hypoxia, and infection (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). During viral infections, autophagy is known to play a dual role. On the one hand, it serves as a defense mechanism by degrading viral components and presenting viral antigens to the immune system (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e); on the other hand, it acts as a hub for viral replication and survival (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In this regard, SARS-CoV-2 has been shown to manipulate autophagy in several ways. For instance, the virus can block the fusion of autophagosomes with lysosomes, thereby preventing the degradation of viral components and creating a favorable environment for viral replication (Silva \u0026amp; Travassos, 2022; Sun et al., 2023). Moreover, SARS-CoV-2 proteins, such as NSP6, have been implicated in these processes, as they promote autophagosome formation while inhibiting their fusion with lysosomes (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). By impairing the autophagic flux, the virus could evade host defenses and sustain its replication cycle (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Overall, the numerous interactions occurring between SARS-CoV-2 and autophagic proteins further highlight the virus's ability to hijack cellular autophagy for its benefit, thus making it a potential target for COVID-19 therapy (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). In this context, our study explored the molecular mechanisms by which Tetrandrine, a potent Ca\u003csup\u003e2+\u003c/sup\u003e channel inhibitor (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), hampers SARS-CoV-2, with a particular focus on the role of autophagy in the viral life cycle.\u003c/p\u003e \u003cp\u003eOur results showed that Tetrandrine modulates autophagy in a dose-dependent manner in Calu-3 cells, a human lung adenocarcinoma epithelial cell line commonly used in SARS-CoV-2 research. At a lower concentration of 5 \u0026micro;M, Tetrandrine induces autophagy, as evidenced by the increased turnover of LC3-II, a marker of autophagosome formation. By contrast, at a higher concentration of 10 \u0026micro;M, Tetrandrine inhibits the autophagic flux, preventing the fusion of autophagosomes with lysosomes. This dual effect is consistent with previous reports suggesting the capability of Tetrandrine to modulate autophagy in a dose-dependent manner, in which at lower concentrations the drug promotes autophagy by activating autophagy-related genes like ATG7 and through ROS generation and ERK activation in cancer cells model (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). At higher concentrations, it has been shown to inhibit autophagy by antagonizing TPC2, thus disrupting viral replication process (Gerndt et al., 2020; Heister \u0026amp; Poston, 2020).\u003c/p\u003e \u003cp\u003eIn this context, we have shown that Tetrandrine significantly reduces SARS-CoV-2 infection in Calu-3 cells, and the antiviral effect is even more relevant when the cells have been pre-treated with Tetrandrine, thus indicating that the preventive treatment may enhance drug efficacy. Quantitative PCR analysis has revealed a substantial reduction in the levels of viral genes encoding the Spike (S) and Envelope (E) proteins in Tetrandrine-treated cells, with a more marked effect observed at the higher concentrations. Interestingly, the inhibitory effect of Tetrandrine on the SARS-CoV-2 shows similar trends for both cellular and supernatant-contained viral particles, thus suggesting that the viral replication could be more affected than its release. Recently, Liu et al. (2023) have demonstrated that Tetrandrine has more significant antiviral activity, particularly during the early-entry stage of SARS-CoV-2 wild-strain infection, preventing the virus from reaching the endolysosomes in Vero-E6 cells, even if the drug was pre-incubated before infection. The authors also pointed out that, as a Ca\u003csup\u003e2+\u003c/sup\u003e channel blocker, Tetrandrine may hinder the maturation of trafficking-related processes through TPC2 and interfere with SARS-CoV-2 mobility within the cell, reducing viral entry. Our results suggest that the effects of Tetrandrine extend beyond just blocking TPC2 since we observed an increased number of viral particles in cell supernatant treated with Ned-19, a selective inhibitor of NAADP-induced Ca\u0026sup2;⁺ release via TPC2 (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). In addition, we have observed the anti-viral properties of Tetrandrine both pre- and post-virus incubation against the most circulant strain, i.e. omicron BA.5, which has already been described to infect host cells via endocytosis (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Using this system, we have dissected how Tetrandrine impairs the viral life cycle by evaluating the SARS-CoV-2 amount inside the cells at different time points post-infection by confocal microscopy. At three hours post-infection, the S signal was similar between Tetrandrine-treated and untreated cells, thus suggesting viral particles could access cells independently from the treatment. On the other hand, our results show that Tetrandrine strongly reduced S signal six hours post-infection at both concentrations, thus supporting the fact that viral replication is mainly affected by the drug. In addition, we observed an increased number of autophagic vesicles following Tetrandrine treatment during infection at both concentrations, as revealed by LC3 immunofluorescence. Intriguingly, at ten hours post-infection, viral particle release increases with a corresponding reduction of Spike-LC3 co-localization in untreated cells, thus suggesting a possible link between autophagy modulation and virus shedding. In line, the addition of Tetrandrine to infected cells stably maintained the association of viral particles to the autophagic vesicles, further suggesting that autophagy could play a role in viral release rather than viral entry and replication. In this context, it has been shown that SARS-CoV-2 proteins (\u003cem\u003ee.g.\u003c/em\u003e ORF7) activate LC3II leading to the accumulation of autophagosomes and then promoting the production of progeny virus (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Additionally, the disruption of autophagy and the over-accumulation of autophagosomes can impair the viral ability to hijack cellular resources necessary for its replication and lead to cell death (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). In line, we have observed that the inhibition of autophagy by ATG7 silencing \u003cem\u003eper se\u003c/em\u003e reduces the released viral particles, which was independent of Tetrandrine treatment. Collectively, our results suggest that autophagy contributes to SARS-CoV-2 inhibition mediated by Tetrandrine to a lesser extent. Indeed, the inhibition of autophagy obtained by ATG7 downregulation does not impact on the antiviral effects of Tetrandrine. Together, our results suggest that Tetrandrine may interfere with additional pathways beyond autophagy, thus highlighting its multifaceted nature in antiviral activity.\u003c/p\u003e \u003cp\u003eAimed at evaluating other pathways relevant to the anti-viral activity of Tetrandrine, we assessed the proteome of SARS-CoV-2 infected cells by mass spectrometry following the addition of Tetrandrine at different concentrations. Of note, despite Tetrandrine inhibition of SARS-CoV-2 replication being dose-independent, the two concentrations used in this study diversely impacted protein expression. This consideration prompted us to analyze the 5 \u0026micro;M concentration independently from 10 \u0026micro;M concerning untreated cells following infection. It is important to note that our data confirmed that Tetrandrine treatment strongly reduces the expression of viral proteins in both concentrations. Moreover, the data analysis identified several DEPs in Tetrandrine-treated and SARS-CoV-2-infected, which specifically belong to the cholesterol metabolism and insulin-like growth factor signaling, independently from Tetrandrine concentrations. It has been described that SARS-CoV-2 affects the insulin/IGF signaling pathway in the host cell/tissue modulating the infection (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). On the other hand, the cholesterol pathway has been involved in SARS-CoV-2 entry and replication (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e) into the host cells; thereby, the capability of Tetrandrine to limit SARS-CoV-2 infection can reside in its ability to modulate these pathways when added before infection.\u003c/p\u003e \u003cp\u003eGiven the well-established roles of cholesterol metabolism in viral entry and replication and the involvement of insulin/IGF signaling in the host response to infection, these pathways may represent critical nodes through which Tetrandrine exerts its antiviral effects (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Cholesterol metabolism has been extensively described in promoting viral entry into host cells through clathrin-mediated endocytosis, as well as maintaining the integrity of the endosomal membrane, which is crucial for the fusion and release of viral contents into the cytoplasm (Shi et al., 2016; Wrensch et al., 2014). On the other hand, alterations in cholesterol metabolism may exert significant antiviral effects based on manipulation of intracellular viral trafficking, including SARS-CoV-2 entry (\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). Also, viral replication, assembly, release and immune evasion have been related to cholesterol-associated pathways(\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e) of several viruses, SARS-CoV-2 included (\u003cspan additionalcitationids=\"CR55\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). Among cholesterol metabolism, we found that Tetrandrine upregulates Cystatin C (CST3) and SDC2 during infection. Interestingly, these two proteins have been previously described in HIV and HSV replication in the host cells, suggesting that they are possibly conserved cellular targets in many viral infections (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). Similarly to cholesterol, we identified insulin-like growth factor signaling modulated by Tetrandrine during SARS-CoV-2 infection. In this regard, it has been recently suggested that insulin could potentially facilitate the entry and replication of SARS-CoV-2 in patients with diabetes (Sun, 2023). At the same time, anti-diabetic drugs were shown to benefit diabetic patients with COVID-19 by suppressing mTOR signaling promoting autophagy and exerting anti-inflammatory effects (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). Moreover, the cholesterol synthetase DHCR24, which is induced by insulin, has been identified as downregulated in SARS-CoV-2-infected Calu-3 cells (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e). Our proteomic screening identified that DHCR24 protein levels increased upon Tetrandrine treatment, suggesting another possible mechanism for its antiviral properties. These findings underscore the potential of Tetrandrine to target multiple pathways involved in SARS-CoV-2 infection, making it a versatile and promising therapeutic candidate.\u003c/p\u003e \u003cp\u003eIn summary, our study provides compelling evidence that Tetrandrine has the potential to inhibit SARS-CoV-2 infection through a combination of mechanisms, including the modulation of autophagy and interference with other cellular pathways essential for viral replication. The observed dose-dependent effects of Tetrandrine on autophagy and its ability to impact viral replication, even in the absence of autophagy, highlight the complexity of its antiviral action. Given the multifaceted roles of autophagy in viral infections and the diverse pathways influenced by Tetrandrine, our study contributes to the broader effort of identifying effective treatments for SARS-CoV-2, with Tetrandrine emerging as a promising candidate for therapeutic intervention against this ongoing global health crisis.\u003c/p\u003e \u003cp\u003eOverall, while preclinical data are encouraging (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e), comprehensive clinical evaluation is crucial to validate the efficacy and safety of Tetrandrine in COVID-19 patients. The complexity of SARS-CoV-2 pathology and the multifaceted roles of autophagy in viral infections underscore the need for a nuanced understanding of how Tetrandrine modulates these processes. By unravelling the complex interactions between Tetrandrine, autophagy, and viral replication, our research contributes to the broader scientific effort to develop effective treatments for SARS-CoV-2, ultimately aiming to mitigate viral activity and long-term symptoms. Future studies should focus on detailed clinical trials to explore the therapeutic potential of Tetrandrine in patients with COVID-19 and long-COVID. In addition, we found that Tetrandrine is more efficient in blocking SARS-CoV-2 replication when administered before infection, thus opening the possibility of evaluating its efficacy in preventing SARS-CoV-2 infection. This will provide crucial insights into its role as a potential antiviral agent and its application in the broader context of viral therapeutics.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e \u003cb\u003eDrugs\u003c/b\u003e. Tetrandrine was purchased from Cayman Chemical, Ann Arbor, MI, USA and Bafilomycin A1 from St. Louis, Missouri, EUA.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCell culture\u003c/h2\u003e \u003cp\u003eThe human lung cancer cell line, Calu-3, was used as a cellular model for the present study. Cells were cultured in \u003cem\u003eEagle\u0026rsquo;s Minimum Essential Medium\u003c/em\u003e (MEM; Sigma-Aldrich 51412C) integrated with 10% of Fetal Bovine Serum (FBS), L-glutamine 2\u0026micro;M (Corning 25-005-CI) and 1% of penicillin/streptomycin (Corning 30-001-CI). Cells were maintained in culture in sterile polystyrene plates, at 37\u0026deg;C and 5% of CO\u003csub\u003e2\u003c/sub\u003e in thermostatic incubators. At 80\u0026ndash;90% confluence the cells were diluted following this procedure: washed twice with PBS (Dulbecco's Phosphate Buffered Saline; Euroclone ECB 4004L), detached from the plate using trypsin/EDTA (Sigma-Aldrich T3924) and, finally dilute 1:4 to new plates (Corning).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSARS-CoV-2 infection\u003c/h2\u003e \u003cp\u003eSARS-CoV-2, human, Italy, clade GRA, lineage BA.5.1, Omicron (BA.5-like), strain hCoV-19/Italy/LAZ-INMI-3329/2022, former VOC Omicron GRA (B.1.1.529\u0026thinsp;+\u0026thinsp;BA.*) first detected in Botswana/Hong Kong/South Africa was used to infect Calu-3 cells at a multiplicity of infection (M.O.I.) of 0.2. Viral inoculum or medium only (Not Infected) was added to cells and incubated for 1 h and 30\u0026prime; at 37\u0026deg;C, 5% CO\u003csub\u003e2\u003c/sub\u003e. The viral inoculum was then removed, and cells were washed twice with PBS. Next, complete MEM was added, and cells were cultured at 37\u0026deg;C, 5% CO\u003csub\u003e2\u003c/sub\u003e. Immediately after inoculum removal (T0) or 24h post-infection, supernatants and cells were collected for the subsequent analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eReal-time RT-PCR and viral quantification\u003c/h2\u003e \u003cp\u003eBased on the manufacturer's guidelines, total RNA was isolated from Calu-3 cells with the Direct-zol RNA MicroPrep KIT (Zymo Research Corp). To perform RT-PCR analyses, 1 \u0026micro;g of total RNA was reverse transcribed using AMV-reverse transcriptase (Promega Corporation) to obtain single-stranded cDNA. To analyze the supernatant, RNA was extracted from 140 \u0026micro;L of Calu-3 culture medium using the Qiamp viral RNA kit (Qiagen) and then eluted in 50 \u0026micro;L of elution buffer. To determine viral abundance, the RealStar\u0026reg; SARS-CoV-2 RT-PCR Kit RUO (Altona Diagnostics) was used to amplify the E\u0026thinsp;\u0026minus;\u0026thinsp;and S- SARS-CoV-2 genes by Real-time qPCR using 10 \u0026micro;L of RNA extracted from supernatant, or 40 ng of cellular isolated RNA.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eATG7 downregulated Calu-3 cells\u003c/h2\u003e \u003cp\u003eFor stable human ATG7 mRNA interference, a lentiviral ATG7 mRNA\u0026ndash;targeting pLKO.1 plasmid was used (TRCN0000007584, Sigma-Aldrich) to produce lentiviral particles as follows: 293T cells were transiently transfected with expression vectors using the calcium phosphate method with 10 mg of lentiviral vectors, 2.5 mg of pCMV-VSV-G, and 7.5 mg of psPAX2 plasmid for 48 hours. Lentiviral particles in the supernatant were pelleted by ultracentrifugation at 19,800 RPM on an SW28 rotor for 2 hours and resuspended with 500 mL PBS every 20 mL of collected medium. 300\u0026rsquo;000 Calu-3 cells were infected twice by adding 20 mL of viral suspension to complete MEM supplemented with polybrene (4 mg/mL) for 6 and 18 hours, respectively. Following infection, cells were maintained in culture, and ATG7 expression levels were tested by Western blotting.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eWestern blots\u003c/h2\u003e \u003cp\u003eCells were lysed in CelLytic reagent (Sigma-Aldrich) completed with specific inhibitors: proteases inhibitor cocktail (PIC, Sigma Aldrich), phosphatases like sodium orthovanadate (Na3VO4) 0,5 \u0026micro;M, sodium molybdate (Na2MoO4) 5 \u0026micro;M, sodium fluoride (NaF) 5 \u0026micro;M, phenylmethanesulfonyl fluoride (PMSF) 0,5 \u0026micro;M and 1,10-phenanthroline (OPT) 2 \u0026micro;M and 2-chloroacetamide (ClCH2CONH2) 50 \u0026micro;M. Protein concentration was quantified using the BCA method (Thermo Fisher), and an equal amount of total protein per sample was mixed with a reducing agent (NuPAGE\u0026trade; Cat. N. NP0004, Thermo Fisher) and Leamli Sample Buffer (Bio-Rad Cat. N. 1610747) and then loaded in homemade polyacrylamide gels at different concentrations for the SDS-PAGE. Proteins were transferred onto a PVDF membrane (Polyvinylidene Fluoride, Millipore) previously activated with 100% methanol, in semi-dry conditions using Transfer Blot Turbo (Bio-Rad) with a buffer consisting of 0.025 M Tris-base, 0.19 M glycine (TrisGly Bio-Rad, Cat N. 1610734) and 20% methanol. The filter was washed three times with PBS-Tween (0,1%) (T-PBS) and incubated with 5% milk solution in T-PBS for one hour to saturate non-specific sites. Incubation with the primary antibody specific to the protein of interest was performed overnight, at 4\u0026deg;C and stirring. The primary antibodies were diluted in 5% milk in T-PBS as indicated. After incubation, the primary antibody was removed from the filter and washed three times with T-PBS. Subsequently, a second one-hour incubation was performed using a specific peroxidase-conjugated secondary antibody diluted 1:5000 in 5% milk in T-PBS. The secondary antibody was removed, and the filter was washed three times with T-PBS. For protein detection, the PVDF membranes were incubated for three minutes with a commercial solution (ECL plus Millipore WBLUC0500 or WBLUR0500) containing the substrate for the chemiluminescence reaction catalyzed by peroxidase. Finally, the light signal was detected through a CCD camera of the ChemiDoc Touch Imaging System (Bio-Rad) associated with a digital image acquisition system. Image Lab 6.1 software from Bio-Rad was used to visualize and process images. Primary antibodies used were: Rabbit anti-LC3 (1:1000, Cell Signaling Technology 2775), Mouse anti-GADPH (1:500000, Calbiochem CB1001), Mouse anti-HSP90 (1:1000, Santa Cruz Biotechnology, sc-13,119), Goat anti-ATG7 (1:500 Santa Cruz Biotechnology, sc-8668). The secondary antibodies used (Jackson lab) were anti-rabbit (JI 711\u0026ndash;036\u0026ndash;152), anti-mouse (JI 715\u0026ndash;036\u0026ndash;150), and anti-goat (JI 705\u0026ndash;036\u0026ndash;147), all diluted 1:5000.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence\u003c/h2\u003e \u003cp\u003eFor immunofluorescence analysis, Calu-3 cells were grown on glass coverslips, treated with Tetrandrine and infected as described above, and then fixed with 4% paraformaldehyde. After fixing, cells were washed twice with PBS and permeabilized by incubation with 0.5% Triton for 10 minutes at room temperature. Following a double washing with PBS, the non-specific background was reduced by blocking cells with 10% donkey serum in PBS for 30 minutes. Then, cells were incubated with primary antibodies diluted in 1% donkey serum for 1 hour at room temperature, re-washed, and incubated with secondary antibodies for 30 minutes in the dark. Finally, ProLong\u0026trade; Gold Antifade Mountant (Thermo Fisher, cat. N. P36931) was added to assemble the glass coverslip on a glass slide, which was subsequently sealed. The images were acquired using LSM 900, Airyscan SR Zeiss confocal microscope. At least 30 cells per sample have been acquired and then analyzed using ImageJ Fiji software. In detail, we measured the area of viral Spike or cellular LC3 per cell by using the \u0026lsquo;Analyze Particles\u0026rsquo; tool of Image J. To evaluate the Lc3-Spike colocalization, the Jacop ImageJ plug-in has been used to assess the Mander\u0026rsquo;s coefficient of Spike signal on LC3 one. Primary antibodies: Rabbit Anti-LC3 (1:200, Sigma-Aldrich, L7543), Mouse Anti- SARS-CoV-2 spike (1:200, GeneTex (Irvine, CA, USA). Secondary antibodies: anti-rabbit Alexa Fluor 488-conjugated (Thermo Fischer, A21206), anti-mouse Cy3-conjugated (Jackson ImunoResearch, 715\u0026ndash;166\u0026thinsp;\u0026minus;\u0026thinsp;150).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eSample preparation for mass spectrometry\u003c/h2\u003e \u003cp\u003eFor whole proteome analyses of Calu-3 cells, with and without infection of SARS-CoV-2 and with the different treatments, 10 mg of protein extract per sample were incubated with 1 \u0026micro;M DTT, heated for 10 min at 75\u0026deg;C followed by 5.5 \u0026micro;M IAA incubated for 10 min in dark at RT. Trypsin was added with a 1:100 ratio (Trypsin: protein, w/w), and samples were left for digestion overnight at 37\u0026deg;C. TFA was added drop-wise to completely precipitate sodium deoxycholate and centrifuged at 14000 rpm, 23\u0026deg;C. Supernatants containing the peptides were STAGE tip-purified and dissolved in buffer A (0.1% formic acid in MS grade water) for LC-MS/MS measurements.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eMass spectrometry-based proteomic analyses\u003c/h2\u003e \u003cp\u003eHF-X mass spectrometer in line with an EasyLC 1000 nanoflow-HPLC (Thermo Fisher Scientific) has been used for LC-MS/MS. Purified peptides were separated using a 60 minutes ramp on fused silica HPLC column tips (I.D. 75 \u0026micro;m, New Objective, self-packed with ReproSil-Pur 120 C18-AQ, 1.9 \u0026micro;m [Dr. Maisch] to a length of 20 cm) of a gradient composed by water plus 0.1% formic acid (buffer A) and increasing concentrations of 80% acetonitrile in water plus 0.1% formic acid (buffer B). The mass spectrometer was operated in data-independent mode. Each survey scan was performed with mass range m/z\u0026thinsp;=\u0026thinsp;350\u0026ndash;1,200 and resolution: 120\u0026rsquo;000, then 28 DIA scans were performed (isolation width of 31.4 m/z), thus covering a total range of precursors from 350-1,200 m/z (AGC target value: 3 x 10\u003csup\u003e6\u003c/sup\u003e, resolution: 30\u0026rsquo;000, and 27% of normalized collision energy)(\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e). Protein identification and quantification were performed with Spectronaut software (v15.7, Biognosys) without imputation in direct DIA mode and using full-length Uniprot human (UniProt, 2022), SARS-CoV-2 (Uniprot, Severe acute respiratory syndrome coronavirus 2 (2019-nCoV)), and common contaminants databases. Perseus software (version 1.6.15.0) (Tyanova et al., 2016) has been used to analyze DIA results. Before performing statistical analyses, an obvious batch effect of the data of replicate 3 was removed by using the \"remove batch effect\" function of the Perseus software with the Limma option as method. Obtained protein quantity values were log2 converted and grouped to compare infected to non-infected cells filtered based on proteins identified in at least one group with a coverage of 90%. Missing values were imputed from normal distribution based on the total matrix (width 0.3 and downshift 1.3). The whole matrix of identifications was used to calculate the Principal Component Analysis (2 components FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05). To generate the volcano plots, we set 250 randomizations based on two sides t-test (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and S0\u0026thinsp;=\u0026thinsp;0.1). Differentially abundant proteins between non-infected and SARS-CoV-2 infected cells were compared based on Tetrandrine treatment, and a quantitative VENN diagram was generated using the open access online software, Venny 2.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinfogp.cnb.csic.es/tools/venny/\u003c/span\u003e\u003cspan address=\"https://bioinfogp.cnb.csic.es/tools/venny/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Hierarchical clustering of identified proteins was performed after Z-score normalization, and multiple-sample test (ANOVA) and Post hoc Tukey\u0026rsquo;s HSD test of one-way ANOVA (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were calculated for proteins among groups. Euclidean distance was used for the comparison, and clusters were extracted using n\u0026thinsp;=\u0026thinsp;4 (between columns) and n\u0026thinsp;=\u0026thinsp;18 (between rows). Proteins identified from SARS-CoV2 infected cells showing significant fold changes following Tetrandrine treatments were considered to analyze cellular modulated pathways. The network analysis and the visualization of cellular proteins significantly modulated were performed using the application of String-DB specifically developed for Cytoscape (v3.8.2) (StringApp) (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). In the reported networks, the difference in the colour of the nodes represents a differential fold of changes in the expression of Tetrandrine-treated cells versus untreated ones. In addition, the diameter refers to the statistical significance of the identification represented as the negative log of the p-value. The pathways analysis was performed by selecting Rectome, KEGG, and Wiki-Pathways through the Functional Enrichment analysis in Cytoscape. The analysis was performed with DAPs following Tetrandrine treatment of SARS-CoV-2 infected cells (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and redundancy\u0026thinsp;=\u0026thinsp;0.4); the length of the bars represents -log of p-values of reported histograms. When changing pathways were represented through BubblePlot, the diameter of the bubble indicates the number of identified proteins.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis of the data obtained from the Western blot, MTS, Trypan Blue, and Real-Time qPCR was performed using ordinary 1-way or 2-way ANOVA with multiple comparison tests based on variable numbers. Values are shown as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM of at least three independent experiments. Densitometric analysis of Western blotting was performed using Image Lab 5.2.1 (Bio-Rad), with the control ratio arbitrarily defined as 1.00. For immunofluorescence analysis, the normal distribution has been verified, and the statistical analysis was performed using ANOVA 2-way test. All statistical analyses were performed using GraphPad Prism 9.0 software, considering significant P values\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements.\u003c/strong\u003e Dr. Daniele Lapa for the BSL3 laboratory formation of L.O.M. at IRCCS INMI L. Spallanzani. Mohammadreza Bayat and Nesilda Qaja for sustaining M.A. in leading the IRCCS INMI L. Spallanzani laboratory activity and Confocal Images analysis, respectively. Laboratory of Emerging Viruses (LEVE), Department of Genetics, Evolution, Microbiology and Immunology, at Unicamp, specially to Dr. Jose Luiz Proen\u0026ccedil;a-Modena and the group of researchers, supporting the discussion of results and BSL3 laboratory formation of L.O.M. in Brazil.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement.\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions.\u003c/strong\u003e\u0026nbsp; \u0026nbsp;L.O.M., S.D.S. G.M., S.S.S., G.M.F., M.P., G.J.S.P., M.A. conceptualization; L.O.M., S.S., B.G.A, I.K.M.W., D.M., G.M., G.J.S.P, M.A. methodology; L.O.M., S.D.S., B.G.A., D.M, M.A. data curation and funding acquisition; G.J.S.P.; M.A.; G.M. supervision and validation; L.O.M., I.K.M.W., S.S.S., F.M., J.D., G.J.S.P., M.A. writing \u0026ndash; review \u0026amp; editing; L.O.M.; G.J.S.P.; M.A. writing \u0026ndash; original draft. All authors approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Statement:\u003c/strong\u003e Ethics approval was not needed, as this study does not involve patients or animals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding.\u003c/strong\u003e This study received support from Funda\u0026ccedil;\u0026atilde;o de Amparo \u0026agrave; Pesquisa do Estado de S\u0026atilde;o Paulo - FAPESP: 2019/14722-4; 2022/15748-0 (G.J.S.P.); 2019/02821-8 (S.S.S.). This study was financed in part by the Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior - Brasil (CAPES and CAPES/PrInt) - Finance Code 001 for scholarship to L.O.M.. The study has also been funded by the University and the Canton of Fribourg as part of the SKINTEGRITY.CH research network to J.D., by the Biology Department of Tor Vergata University of Rome (project acronym, AutoCuRC) to M.A., supported by the Italian Ministry of Health with Ricerca Corrente Linea 1 to IRCCS INMI L. Spallanzani (F.M., and G.M. project n. 1), and Ricerca Finalizzata (GR-2019-12369231) to M.A. The Italian Ministry of University and Research has funded the scholarship for the PhD program in Cellular and Molecular Biology to S.D.S.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability.\u003c/strong\u003e The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplemental data.\u0026nbsp;\u003c/strong\u003eThis article contains supplemental data (figures).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLi Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus\u0026ndash;Infected Pneumonia. New England Journal of Medicine. 2020 Mar 26;382(13):1199\u0026ndash;207. \u003c/li\u003e\n\u003cli\u003eZhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. 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Available from: https://pubmed.ncbi.nlm.nih.gov/14597658/\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cell-death-discovery","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddiscovery","sideBox":"Learn more about [Cell Death Discovery](http://www.nature.com/cddiscovery/)","snPcode":"41420","submissionUrl":"https://mts-cddiscovery.nature.com/","title":"Cell Death Discovery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"SARS-CoV-2, Tetrandrine, Autophagy, Proteomic Analysis","lastPublishedDoi":"10.21203/rs.3.rs-6958516/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6958516/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSARS-CoV-2 exploits multiple host cellular processes, including autophagy\u0026mdash;a critical intracellular degradation pathway\u0026mdash;to facilitate viral replication and evade immune detection. Tetrandrine, a natural bis-benzylisoquinoline alkaloid derived from \u003cem\u003eStephania tetrandra\u003c/em\u003e, has been reported to modulate autophagy and exhibits potential antiviral properties. In this study, we investigated the effects of Tetrandrine on SARS-CoV-2 infection in human lung epithelial cells (Calu-3), with a particular focus on autophagy-related mechanisms. Our results demonstrate that Tetrandrine modulates autophagic activity in a dose-dependent manner and significantly reduces SARS-CoV-2 replication, particularly when administered prior to infection. Notably, its antiviral effect is retained in autophagy-deficient cells, indicating the involvement of autophagy-independent mechanisms. Proteomic analysis of Calu-3 cells infected with the Omicron BA.5 variant revealed that Tetrandrine regulates several host pathways implicated in viral replication, including autophagy, cholesterol metabolism, and insulin-like growth factor signaling. These findings suggest that Tetrandrine exerts multifaceted antiviral effects by targeting both autophagy-dependent and -independent cellular pathways. Collectively, our data supports the potential of Tetrandrine as a therapeutic candidate against COVID-19 and warns further evaluation in preclinical and clinical models. Data are available via ProteomeXchange with identifier PXD064448.\u003c/p\u003e","manuscriptTitle":"Tetrandrine-Driven Autophagy Suppresses SARS-CoV-2 Replication by Modulating Cholesterol and IGF Signaling Pathways","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-03 11:48:43","doi":"10.21203/rs.3.rs-6958516/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-07-30T11:27:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-07-30T00:04:16+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-07-01T15:59:23+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-07-01T07:58:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-24T10:46:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-23T16:00:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cell Death Discovery","date":"2025-06-23T16:00:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cell-death-discovery","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddiscovery","sideBox":"Learn more about [Cell Death Discovery](http://www.nature.com/cddiscovery/)","snPcode":"41420","submissionUrl":"https://mts-cddiscovery.nature.com/","title":"Cell Death Discovery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fd06b1df-700f-45fa-8a37-f1392c862bf2","owner":[],"postedDate":"July 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":50845573,"name":"Biological sciences/Cell biology/Autophagy"},{"id":50845574,"name":"Biological sciences/Drug discovery/Target identification"},{"id":50845575,"name":"Biological sciences/Microbiology/Antimicrobials/Antiviral agents"}],"tags":[],"updatedAt":"2026-02-07T08:14:31+00:00","versionOfRecord":{"articleIdentity":"rs-6958516","link":"https://doi.org/10.1038/s41420-025-02926-7","journal":{"identity":"cell-death-discovery","isVorOnly":false,"title":"Cell Death Discovery"},"publishedOn":"2026-01-06 05:00:00","publishedOnDateReadable":"January 6th, 2026"},"versionCreatedAt":"2025-07-03 11:48:43","video":"","vorDoi":"10.1038/s41420-025-02926-7","vorDoiUrl":"https://doi.org/10.1038/s41420-025-02926-7","workflowStages":[]},"version":"v1","identity":"rs-6958516","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6958516","identity":"rs-6958516","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}