Proteomic and Single-Cell insights unveiling therapeutic potential of curcumin against IL- 17A induced acute lung injury in C57BL/6 mice

Proteomic and Single-Cell insights unveiling therapeutic potential of curcumin against IL- 17A induced acute lung injury in C57BL/6 mice | 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 Research Article Proteomic and Single-Cell insights unveiling therapeutic potential of curcumin against IL- 17A induced acute lung injury in C57BL/6 mice Mahesh Manjunath Gouda, Rex Devasahayam Arokia Balaya, Prashant Kumar Modi, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4400688/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Oct, 2024 Read the published version in Inflammation → Version 1 posted 11 You are reading this latest preprint version Abstract Acute lung injury (ALI) is primarily driven by an intense inflammation in the alveolar epithelium. Key to this is the pro-inflammatory cytokine, Interleukin 17 (IL-17), which influences pulmonary immunity and modifies p53 function. The direct role of IL-17A in p53-fibrinolytic system is still unclear, it is important to evaluate this mechanism to regulate the ALI progression to idiopathic pulmonary fibrosis (IPF). C57BL/6 mice, exposed to recombinant IL-17A protein and treated with curcumin, provided insight into IL-17A mechanisms and curcumin's potential for modulating early pulmonary fibrosis stages. A diverse methodology, including proteomics, single-cell RNA sequencing (scRNA-seq) integration, molecular, and Schroedinger approach were utilized. In silico approaches facilitated the potential interactions between curcumin, IL-17A, and apoptosis-related proteins. A notable surge in the expression levels of IL-17A, p53, and fibrinolytic components such as Plasminogen Activator Inhibitor-1 (PAI-I) was discerned upon the IL17A exposure in mouse lungs. Furthermore, the enrichment of pathways and differential expression of proteins underscored the significance of IL-17A in governing downstream regulatory pathways such as inflammation, NF-kappaB signaling, Mitogen-Activated Protein Kinases (MAPK), p53, oxidative phosphorylation, JAK-STAT, and apoptosis. The integration of scRNA-seq data from 20 IPF and 10 control lung specimens emphasized the importance of IL-17A mediated downstream regulation in PF patients. A potent immuno-pharmacotherapeutic agent, curcumin, demonstrated a substantial capacity to modulate the lung pathology and molecular changes induced by IL-17A in mouse lungs. Human IPF single cell data integration confirmed the effects of IL-17A mediated fibrinolytic components in ALI to IPF progression. IL-17A alveolar epithelial cells p53 proteomics scRNA-seq acute lung injury pulmonary fibrosis curcumin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Acute lung injury (ALI) is marked by severe inflammation of the alveolar epithelium, which triggers the release of inflammatory cytokines, accumulation of macrophages, and neutrophil infiltration, culminating in the destruction of the alveolar epithelium [ 1 – 3 ]. Such destruction precipitates an intense inflammatory response [ 4 ]. As part of the defence mechanism, various biomolecules with diverse functions are mobilized, including cytokines, small glycoprotein messengers that play an integral role in immune responses [ 5 ]. This catalyzes acute inflammation, igniting the innate immune response. ALI incidence in the United States is estimated at 22 per 0.1 million population, with a fatality rate of 40–50% [ 6 ]. IL-17, orchestrates pro-inflammatory responses by critically participating in lung immunity regulation. IL-17 is categorized into six subtypes, IL-17A to IL-17F with IL-17A and IL-17F best understood in terms of biological functionality [ 7 ]. IL-17A and IL-17F are heterodimers operating through an IL-17RA and IL-17RC heterodimeric receptor complex [ 8 ]. Th17 cells, pivotal in various adaptive immunities, produce IL-17A and IL-17F [ 9 ]. Current research reveals Th17 cells release TGF-β, IL-6, IL-1β, and TNF-α, which regulate IL-17A. TGF-β and IL-6 can induce Th17 activation and proliferation, as well as IL-17 production [ 10 ]. Thus, IL-17A engenders tissue inflammation and host defense via multiple signal regulation aspects. IL-17A also influences the alteration of p53 expression, leading to pulmonary fibrosis progression [ 11 – 13 ]. IL-17A-driven production of pro-inflammatory cytokines, chemokines, and antimicrobial peptides by diverse airborne cell types is crucial for robust host defence against pathogens [ 14 – 16 ]. Literature suggests that IL-17A plays a role in the accumulation of macrophages in lungs exposed to cigarette smoke, and it targets non-traditional T cell sources of IL-17A[ 17 ]. This may present an alternative strategy to regulate pathogenic macrophages. Concurrent activation of TLR2 and IL-17R in bronchial epithelium leads to the sequestration of MyD88 by Act1/CIKS, thereby neutralizing TLR2 signaling and restoring homeostasis[ 18 , 19 ]. Morphine exerts an inhibitory influence on early IL-17 release and the Act1-MyD88 interaction, causing pathogen clearance reduction and persistent inflammation [ 20 ]. Thymosin-β4 (Tβ4) participates in the modulation of Bleomycin-induced IL-17 expression in the lung. Tβ4 treatment results in decreased IL-17 producing cells and inhibits IL-17 expression in the lung, correlating with its antifibrotic effect [ 21 ]. IL-17A primarily executes its immunoregulatory function by encouraging inflammatory activity, and by recruiting neutrophils and macrophages to inflammation sites. IL-17A receptors are commonly found in non-hematopoietic cells such as fibroblasts and epithelial cells [ 7 ]. In the lung epithelial cell line treated with IL-17A, the upregulation of several cytokines, including chemokines (C-X-C motif) ligand (CXCL1), chemokine (C-C motif) ligand 2 (CCL2), CCL7, CCL20, and matrix metalloproteinases (MMPs) 3 and 13, was observed [ 22 ]. The augmented expression of IL-17A also coincides with the expression of p53 and its cross-linked regulation. Elevated expression of p53 is noted in IL-17A mediated changes during lung injury, leading to increased p53 expression [ 23 ]. Upon lung injury, p53 expression amplifies in type II alveolar epithelial cells (AECs). p53 operates at transcriptional and post-transcriptional levels to regulate gene expression. An enhanced interaction of p53 with the untranslated region (UTR) of urokinase plasminogen activator (uPA), urokinase plasminogen activator receptor (uPAR), and plasminogen activator inhibitor-1 (PAI-1) mRNAs aids in preventing the onset of pulmonary fibrosis [ 23 ]. Recent research indicates that IL-17A neutralization results in substantial downregulation of neutrophil presence in bronchoalveolar lavage fluid (BALF) [ 24 ]. It was found that the tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) leads to a decrease in IL-1β and IL-6. The crucial role of IL-17A in pulmonary fibrosis can be illustrated by the example of neutralized IL-17A triggering late inflammation through the IL-17RA signaling pathway. Literature underscores the inherent presence of the IL-1β-IL-23-IL-17A axis and its direct relevance to early lung inflammation and the progressive march towards fibrosis following injury [ 24 ]. In our preceding studies, we identified IL-17A as a key downstream regulator of several critical pathways such as the p53-fibrinolytic system, MAPK, AKT, JAK/STAT signaling, and alveolar epithelial cell (AEC) apoptosis during ALI in alveolar basal epithelial cells, C57BL/6 mice, and during cigarette smoke-induced COPD (clinical samples) [ 1 , 13 , 23 ]. In this paper, we present corroborative evidence for the pivotal role of IL-17A during IL17A recombinant protein-induced ALI in C57BL/6 mice. Our findings also support the therapeutic potential of curcumin against IL-17A mediated downstream changes during ALI. High-throughput technologies, such as mass spectrometry (MS), facilitate absolute quantification of differentially expressed proteins in mouse lung tissue, determining the biological processes and protein-protein interactions involved in downstream signaling mechanisms. In silico strategies have made it possible to explore the potential interaction between curcumin and inflammatory proteins and apoptosis protein caspase 3. The integration of scRNA-seq data from 20 pulmonary fibrosis (PF) and 10 control lung specimens, encompassing 114,396 cells, has identified 31 unique cell subsets/states emphasized the importance of IL-17A mediated downstream regulation in PF patients. The comprehensive data generated from this study could be instrumental in developing novel therapeutic strategies against ALI and pulmonary fibrosis. Methods and Materials Mouse model Male C57BL/6 mice, aged 7-8 weeks and weighing approximately 25 ± 5 g, were employed for the animal studies. The mice were obtained from the central animal facility of Manipal College of Pharmaceutical Sciences, Manipal, India. The mice were accommodated in sterile polypropylene enclosures, with paddy husks serving as bedding material, and were granted unrestricted access to food and water. The execution of animal experiments received the endorsement of both the Committee for the Control and Supervision of Experiments on Animals (CPCSEA) and the Institutional Animal Ethics Committee (IAEC) of Yenepoya University (approval number: 11a/31/12/2015). IL-17A induced Acute Lung injury in mice In the study, mice were subjected to an intranasal administration of IL-17A recombinant protein (1 µg) to induce ALI. Following a 24-hour period, curcumin was administered intraperitoneally at a dosage of 75 mg/kg mouse body weight. After 72 hours post-IL-17A administration, the animal experiments were concluded (Figure 1a). Following the conclusion of the experiments, lung tissues were harvested from the mice for subsequent analysis. Isolation and quantification of proteins The harvested mouse lung tissue was homogenized utilizing an extraction buffer (sodium EDTA pH 7.9) and then subjected to centrifugation at 10,000 RPM for 15 minutes at 4°C. Subsequently, the supernatant was collected, and the protein concentration within the sample was ascertained via the Bradford method. Western blotting Proteins extracted from mouse lung tissue were first separated using Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE) on 10% gels. Subsequently, they were electroblotted onto a polyvinylidene difluoride (PVDF) membrane which had been previously blocked with 2% Bovine Serum Albumin (BSA) in Tris-Buffered Saline with Tween-20 (TBST). The membrane was then incubated overnight at 4°C with specific primary antibodies, followed by further incubation with secondary antibodies conjugated with horseradish peroxidase (HRP). Protein expression patterns were visualized using the Enhanced Chemiluminescence (ECL) detection method (Pierce ECL Western Blotting Substrate, Thermo Fisher Scientific, USA). qPCR analysis Total RNA was isolated from mouse lung tissue using the Tri reagent (Sigma-Aldrich). Adhering to the manufacturer's guidelines, the concentration of the extracted total RNA was estimated, after which it underwent cDNA synthesis facilitated by the iScript cDNA synthesis kit (BIO-RAD). Quantitative Polymerase Chain Reaction (qPCR) was conducted using the FG power SYBR green PCR master mix (Thermo Fisher Scientific, USA). All utilized gene-specific primers are detailed below. 1) Mouse IL-17A Forward: 5′-ACGTTTCTCAGCAAACTTAC-3′ Reverse: 5′-CCCCTTTACACCTTCTTTTC-3′ 2) Mouse uPA Forward: 5′-AGAGTCTGAAAGTGACTATCTC-3′ Reverse: 5′-CCTTCGATGTTACAGATAAGC-3′ 3) Mouse uPAR Forward: 5′-TCTGGATCTTCAGAGCTTTC-3′ Reverse: 5′-GCCTCTTACGGTATAACTCC-3′ 4) Mouse PAI-I Forward: 5′-AGCAACAAGTTCAACTACAC-3′ Reverse: 5′-CTTCCATTGTCTGATGAGTTC-3′ 5) Mouse β-actin Forward: 5′-TTAATTTCTGAATGGCCCAG-3′ Reverse: 5′-GACCAAAGCCTTCATACATC-3′ Histopathology and Immunofluorescence staining Mouse lung tissue was formalin-fixed and paraffin-embedded (FFPE), then sectioned into 4.5 µm slices. These sections underwent sequential immersions in one to three xylene baths for paraffin removal, followed by rehydration using graded alcohol series. Subsequently, Hematoxylin and Eosin (H&E) staining was performed to identify histopathological changes within the lung tissue. For the detection of specific protein expressions in the tissue sections, immunofluorescence staining was utilized. Proteomics sample preparation Lysates from mouse lung tissue were prepared using a lysis buffer composed of 50 mM Triethylammonium bicarbonate (TEABC). Protein extraction was performed with a lysis buffer containing 4% Sodium Dodecyl Sulfate (SDS) and 50 mM TEABC. The protein concentration in the tissue lysates was subsequently determined using the bicinchoninic acid (BCA) assay. Protein digestion The process of in-solution digestion was undertaken as delineated in previous descriptions. Briefly, protein samples, each containing 50 µg of protein, were reduced using 10 mM dithiothreitol (DTT) and alkylated using 20 mM iodoacetamide (IAA). Following this, the salt concentration was minimized through acetone precipitation. Protein digestion ensued, employing trypsin (in a 1:20 ratio) (modified sequencing grade; Promega, Madison, WI), and was carried out at 37°C for a duration of 16 hours. After digestion, the peptides were lyophilized and desiccated before undergoing desalting via C18 cartridges. The desalted peptides were subjected to vacuum drying and subsequently stored at -80°C in preparation for liquid chromatography-mass spectrometry (LC-MS/MS) analysis. LC-MS/MS analysis Peptide were analyzed using the Thermo Scientific Q Exactive Plus-Orbitrap mass spectrometer (Thermo Fischer Scientific, Bremen, Germany), linked to the Easy-nLC-1200 nanoflow liquid chromatography system (Thermo Scientific). Peptides were reconstituted in 0.1% formic acid, then loaded onto a 2 cm trap column (nanoViper, 3 μm C18 Aq) (Thermo Fisher Scientific). Samples were processed with a 60-minute linear gradient of buffer B (95 percent acetonitrile and 0.1 percent formic acid) at a flow rate of 300 nL/min. Full MS scans were executed within the range of 350-1800 m/z, employing a resolution of 70,000, a target value of 1.00 + E6, and a permitted ion accumulation time of 60 ms. Identification of peptides and proteins Raw mass spectrometry files were processed using the Proteome Discoverer 2.2 software suite (Thermo Fisher Scientific). The Mus musculus RefSeq89 database, which comprises 29,938 protein entries and common contaminants, was sourced from NCBI. MS/MS data were probed with this Protein Database and recognized mass spectrometers, employing the SEQUEST and Mascot algorithms. Search parameters encompassed carbamidomethylation of cysteine as a fixed modification and oxidation of methionine, as well as a minimum peptide length of 7 amino acids, allowing for 1 missed cleavage. The mass tolerance was determined at 10 ppm for MS and 0.05 Da for MS/MS, with the false discovery rate set at 1% for PSM. Proteomics data analysis Gene Ontology enrichment analysis was conducted using the VISEAGO (v 1.6.0) package in R (31406507). We accessed the public database for Biological Process (BP) and Molecular Function (MF) categories from the Gene Ontology (GO) database (http://geneontology.org/). Related gene terms of the identified mouse proteins were obtained from EnterGene and an enrichment analysis was undertaken for the proteins that exhibited differential expression between the treated and the curcumin-supplemented treated groups. All enriched GO terms (p < 0.01) were categorized into functional clusters via hierarchical clustering, considering the semantic similarity between GO terms based on the GO graph topology and using Ward's criterion. Pathway enrichment analysis was executed using the pathfindeR package in R (v1.6.2) (31608109). We utilized the most recent version of the KEGG database with an enrichment threshold of an adjusted p-value of 0.01. Gene sets comprising 5 to 500 genes were considered with an enrichment threshold of 0.01. Graphical representation of the data was accomplished using the ggplot2 package (v 3.5.5). Single cell sequencing data analysis The single-cell RNA sequencing dataset (GSE135893) was incorporated to further elucidate the regulatory pathway molecules mediated by IL-17A in pulmonary fibrosis (PF) patients and control subjects [30]. The dataset, comprising a total of 111,900 cells derived from 20 PF and 10 control lung samples, was scrutinized employing the Scanpy Python module. Stringent quality control measures were enacted by restricting the per-cell gene count to a range of 200-5000 and disregarding genes expressed in less than three cells. Following these measures, the data underwent normalization and subsequent log transformation. Genes exhibiting high variability were segregated based on predefined cut-off criteria. In the next stage, Principal Component Analysis (PCA), powered by the 'arpack' singular value decomposition (SVD) solver, was carried out on the filtered and normalized dataset. This process effectively reduced the dimensionality of the data while accentuating its primary axes of variation. The PCA-derived results were then employed to construct neighborhood graphs. The Louvain method was applied for community detection within these graphs, thus generating distinct, non-overlapping clusters of cells. The spatial distribution of these unique cellular clusters was visualized utilizing the Uniform Manifold Approximation and Projection (UMAP) technique. An array of UMAP plots was produced, each characterized by unique color codes representing parameters such as diagnostic classification, cellular population, and cell type. The expression trends of pivotal genes, specifically IL17A, TP53, SERPINE1 (PAI-1), BLMH, ITGB1, STAT3, VIM, COL1, COL5, FBLN1, FBLN2, MMP2, MMP5, NFKB1, GATA3, JAK1, IL27RA, and IL2RB were mapped on the UMAP and violin plots in their respective subsets. Additionally, the frequency of cell types expressing these target genes was calculated in conjunction with the cell counts across different populations. Exclusion criteria were set to filter out cell types and populations with counts falling below specified values. Data subsets correlating to different diagnostic groups (Control and IPF), immune cells, and epithelial cells (AT1 and AT2 cells) were generated. These subsets were visualized through UMAP and violin plots based on several parameters and gene expression trends. This comprehensive analytical pipeline facilitated a thorough exploration of the scRNA-seq data, unveiling critical insights about the unique cellular populations and the IL-17A mediated gene expression. In silico molecular docking studies Virtual screening based on structural characteristics was carried out using the GLIDE v7.7 (Grid-based Ligand Docking with Energetics) module from the Maestro v11.4 modeling suite, provided by Schroedinger, LLC, New York, NY, 2017-4. The software was installed on an Intel Core i7-4770 processor, utilizing the GNOME™ Linux 2.6 Centos 6.5 kernel. GLIDE aims to identify the most favorable interactions between a ligand and a receptor molecule. The ligand could be a single entity, while the receptor could comprise more than one molecule. GLIDE operates through rigid or flexible docking modes, and the final ranking was based on the GLIDE Score. In cases where GLIDE Score was selected as the scoring function, the emodel score was used to rank the poses of the ligands. In silico docking was performed to elucidate the molecular interactions between curcumin, IL-17A, and cleaved caspase-3 protein molecules. The crystal structures of IL-17A and cleaved caspase-3 were procured from the Protein Data Bank (PDB). Statistical analysis The data is presented as the mean ± standard deviation. For statistical analysis, Student's t-test was employed for comparison between two groups, and one-way analysis of variance (ANOVA) was utilized for comparing multiple groups. All data analyses were carried out using the GraphPad Prism 9. Results IL-17A expression during IL-17A-induced lung inflammation in C57BL/6 mouse Based on the empirical data derived from bleomycin (BLM)-exposed murine lungs [ 1 ], the ensuing inflammatory response was further probed by the introduction of recombinant IL-17A protein into the mice lungs. The findings indicated that IL-17A functions as the primary inflammatory cytokine implicated in the advancement of lung injury (Fig. 1 b). The concentration of IL-17A protein exhibited a significant augmentation upon exposure to IL-17A (Fig. 1 c and d). Complementing these findings, further validation of IL-17A mRNA expression revealed that IL-17A can potentiate the overproduction of IL-17A transcripts in the nucleus, thereby escalating IL-17A mRNA levels. IL-17A mRNA levels were found to be significantly elevated in the IL-17A-exposed mice relative to those treated with saline and curcumin. However, curcumin administration was capable of significantly suppressing IL-17A mRNA levels in the IL-17A-exposed mice (Fig. 1 e). Corroborating this observation, curcumin was again evidenced to exert a protective effect against IL-17A-induced lung injury in mice. A significant reduction of IL-17A was discernible in the curcumin-treated mice, as confirmed by immunofluorescence staining (Fig. 1 c). The specific interaction between curcumin and IL-17A, particularly the binding of curcumin to the IL-17A binding sites, was examined via the Schroedinger in silico methodology. The interaction of curcumin with IL-17A is depicted in Fig. 1 f. The docking simulation generated a docking energy of -3.69 Kcal/mol, indicative of hydrogen bond formation. Specifically, a hydrogen bond was formed between the hydroxyl group of curcumin and the hydrophobic amino acid residue, LEU97 (Fig. 1 f). Proteins associated with IL-17A mediated downstream pathways during IL-17A induced ALI in C57BL/6 mice The proteomic analysis of lung homogenate samples from mice exposed to saline, IL-17A, and IL-17A plus curcumin led to the detection of 1124, 910, and 1465 proteins, respectively. From these, we identified 481 unique proteins across the experimental groups (Fig. 1 g). These data, derived from label-free or quantitative proteomics, were subjected to functional enrichment analysis to characterize each protein's role. Pathway enrichment analysis revealed that IL-17A administration in mice upregulated proteins associated with signaling pathways such as NF-κB, TH17 cell differentiation, JAK-STAT signaling, RNA transport, and oxidative phosphorylation (Fig. 1 i). These pathways are well-established contributors to the pathophysiology of acute lung injury. The study substantiated that IL-17A administration does more than merely instigate inflammation; it also triggers several downstream signaling cascades, which could potentiate acute injury, leading to severe cellular apoptosis and subsequent fibrotic niche development. We investigated the 15 primary enriched signaling pathways elicited by IL-17A and validated the enriched proteins associated with TH17 cell differentiation, oxidative phosphorylation, the p53-plasmin cascade, and apoptosis in IL-17A-induced mouse lung injury models, using molecular approaches (Fig. 2 d and e). Interestingly, a robust interplay was observed between proteins involved in TH17 cell differentiation and various downstream signaling pathways such as NF-κB signaling, RNA transport, the spliceosome, oxidative phosphorylation, and JAK-STAT signaling (Fig. 2 d). Further analysis uncovered that the proteins exhibiting differential regulation between IL-17A treatment and curcumin intervention predominantly belong to the inflammation, MAPK, and apoptosis pathways (Fig. 2 e). Notably, the molecules associated with IL-17A differentiation, such as JAK1, IL27RA, HLA-DPA1, NFATC3, IL2RB, and GATA3, were significantly downregulated in the curcumin-treated mice (Fig. 2 e). p53-fibrinolytic system during IL-17A-induced lung in C57BL/6 mice In the current investigation, we observed a significant upregulation in the expression of phosphorylated p53 (P-p53), p53, and PAI-I proteins following IL-17A administration in mice (Fig. 2 a). However, the intervention with curcumin effectively counteracted the IL-17A-induced expression of P-p53, p53, and PAI-I, highlighting curcumin's restorative role in the IL-17A-mediated impairment of the p53 fibrinolytic system. Immunofluorescence staining was employed to ascertain the expression levels of P-p53, p53, and PAI-I in lung tissues of mice exposed to IL-17A. The IL-17A-exposed mouse lungs exhibited an increased count of P-p53, p53, and PAI-I molecules, reinforcing IL-17A's role in promoting lung injury in mice (Fig. 2 c). Conversely, curcumin-treated mouse lungs presented minimal numbers of P-p53, p53, and PAI-I positive cells. This observation suggests that curcumin effectively modulates the p53-PAI-I expression, restoring it to physiological levels (Fig. 2 c). Analysis of IL-17A-mediated alterations in mRNA expression of fibrinolytic components demonstrated that IL-17A administration was implicated in the induction of PAI-I mRNA expression by suppressing uPA and uPAR mRNA levels in mice lungs (Fig. 2 b). Concretely, PAI-I mRNA levels were significantly elevated, and uPA and uPAR mRNA levels were markedly reduced in the IL-17A-treated mice. In a reciprocal manner, curcumin intervention significantly downregulated PAI-I mRNA and upregulated uPA and uPAR mRNA expression in mice (Fig. 2 b). Caspase-3 activation during IL-17A-induced lung in C57BL/6 mice To confirm the role of IL-17A in alveolar epithelial cells (AECs) apoptosis, we introduced recombinant IL-17A protein in mice via intranasal administration. Upon IL-17A administration, the expression level of the apoptosis marker, cleaved caspase-3 protein, was significantly increased (Fig. 3 a and b). Conversely, intervention with curcumin led to a notable downregulation of cleaved caspase-3 expression, thus confirming curcumin's restorative role during IL-17A-mediated AECs cell death. The expression of cleaved caspase-3 was further validated using immunofluorescent staining (Fig. 3 b). IL-17A-exposed mouse lung tissue sections displayed enhanced staining for cleaved caspase-3 proteins, while curcumin treatment led to a significant decrease in the staining intensity. The molecular interaction of curcumin with the binding sites of cleaved caspase-3 was examined using the Schroedinger in silico approach. The interaction of curcumin with cleaved caspase-3 is depicted in Fig. 3 c, showing robust molecular bonding with the ASP70, TYR67, and ARG66 residues of the cleaved caspase-3 protein (Fig. 3 c). Single cell integration to evaluate the IL-17A mediated pathway genes activities in IPF patient As previously mentioned, a total of 111,900 single cells from 20 pulmonary fibrosis (PF) and 10 control lung specimens were analyzed using the Scanpy Python module, with individual lung specimen single cell data represented in Fig. 3 d. Uniform Manifold Approximation and Projection (UMAP) analysis for diagnosis yielded six subcategories: Control, Interstitial Lung Disease (ILD), Idiopathic Pulmonary Fibrosis (IPF), Nonspecific Interstitial Pneumonia (NSIP), Sarcoidosis, and Chronic Hypersensitivity Pneumonitis (cHP) (Fig. 3 e). Further cellular population clustering resulted in identifiable cell clusters such as endothelial, epithelial, immune, and mesenchymal cells (Fig. 3 e). Subclustering identified 31 different cell type expression patterns. Subsequent evaluation of control and IPF subsets produced 87,248 single cells, with the expression of key genes of interest observed across diagnoses, cell populations, and cell types (Fig. 4 ). The insights gathered from the control and IPF subsets led us to subset the control and IPF individually, thereby visualizing the expression patterns of key genes of interest. The control subset yielded 31,127 single cells with key genes of interest visualized according to cell population and cell types (Fig. 5 a and 5 b). We observed no significant expression of IL-17A, PAI-1, p53, BLMH, NFKB1, GAT3, IL27RA, and IL2Rb in cell population and cell types compared to the IPF subset, comprising 56,121 single cells. In the IPF subset, significant high expression of TP53, PAI-1, BLMH, ITGB1, STAT3, VIM, FBLN1, FBLN2, MMP2, NFKB1, JAK1, and IL27RA were observed (Fig. 6 d). Notably, key genes such as ITGB1, STAT3, FBLN1, FBLN2, and MMP2 were significantly expressed in mesenchymal cells. PAI-1 expression was observed in fibroblasts (Fig. 6 c), and FBLN1, FBLN2, and MMP2 expression in fibroblasts and myofibroblasts, signaling progressive disease (Fig. 6 b). Subsetting immune cells in control and IPF resulted in 44,984 single cells (Fig. 7 a), with 19,398 single cells in control (Fig. 7 d) and 25,586 single cells in IPF immune cells (Fig. 7 e). Macrophages, B cells, NK cells, and T cells were highly expressed in IPF immune cells (Fig. 7 b). A significant difference was observed in the expression of ITGB1, STAT3, and VIM in IPF immune cells compared to control (Fig. 7 d and 7 e). Additionally, NFKB1 expression in IPF mast cells and IL2RB in proliferating macrophages provides further insights into NFKB1 and IL2RB signaling pathways (Fig. 7 d and 7 e). Lastly, an analysis of 8,108 single cells from an epithelial cell subset of AT1 and AT2 cells furnished additional insights into AT1 and AT2 cell behavior in control and IPF single cells (Fig. 8 ). Although no observable expression of IL-17A was found in AT1 and AT2 cells, ITGB1 and STAT3 were highly expressed in both cell types (Fig. 8 c and 8 d). Interestingly, JAK1 expression was significantly higher in control and AT2 cells (Fig. 8 c and 8 d). Discussion The current findings demonstrate the substantial regulatory role of curcumin in modulating acute alveolar epithelial inflammation, as well as the subsequent activation of IL-17A mediated macrophage accumulation and neutrophil infiltration in C57BL/6 mice [ 1 ]. IL-17A has been identified as a central inflammatory cytokine implicated in the progression of lung injury [ 1 ]. This cytokine promotes an overproduction of IL-17A transcripts in the nucleus, potentially augmenting IL-17A mRNA levels. We observed a significant increase in IL-17A mRNA levels in IL-17A exposed mice, compared to those treated with saline and curcumin [ 23 ]. Our findings indicate that curcumin administration notably downregulates IL-17A mRNA levels in IL-17A exposed mice. Previous literature has highlighted the therapeutic potential of curcumin against inflammatory processes, stating that curcumin plays an integral role in mitigating numerous chronic diseases, including neurodegenerative, cardiovascular, pulmonary, metabolic, autoimmune, and neoplastic diseases [ 25 ]. The interaction of p53 with key fibrinolytic system components, such as uPA, uPAR, and PAI-1, has been reported to regulate apoptosis or survival following Acute Lung Injury (ALI) [ 26 ]. Our results show a significant increase in the expression of P-p53, p53, and PAI-I proteins in mice post-IL-17A administration. However, intervention with curcumin was able to reverse IL-17A-induced expressions of P-p53, p53, and PAI-I, implying that curcumin administration exhibits a restorative effect in the context of IL-17A-mediated impairment of the p53 fibrinolytic system. Additionally, the mRNA levels of the fibrinolytic component PAI-I were significantly increased in the mice administered with IL-17A, while uPA and uPAR mRNA levels were notably decreased post-IL-17A administration. Curcumin was shown to effectively modulate the IL-17A-mediated p53 fibrinolytic system during IL-17A-induced Acute Lung Injury (ALI) in vitro [ 27 ]. The administration of curcumin was found to regulate the IL-17A mediated p53-fibrinolytic system. Caspase-3, a crucial executor of apoptosis and an activated death protease catalyzing many vital cellular proteins [ 28 ], was shown to be activated by IL-17A injury, leading to increased expression of cleaved caspase-3 [ 29 ]. IL-17A administration significantly upregulated the expression level of cleaved caspase-3 proteins, whereas curcumin administration counteracted this by downregulating cleaved caspase-3 expression levels. Our study thus confirms curcumin's protective role in attenuating IL-17A mediated cell death of AECs. Further, immunofluorescence staining results corroborated that the expression of cleaved caspase-3 proteins decreased after curcumin treatment in IL-17A-exposed lung tissue sections of mice. Label-free quantitative proteomics bioinformatics analysis revealed that IL-17A administration in mouse lungs instigates ALI and mediates several downstream signaling pathways, including inflammation, oxidative phosphorylation, MAPK, p53, plasminogen cascade, JAK-STAT, and apoptosis. The differentially regulated proteins identified, such as IL-17A, TP53, PAI-1, BLMH, ITGB1, STAT3, VIM, FBLN1, FBLN2, MMP2, NFKB1, JAK1, and IL27RA, were found to be associated with the afore-mentioned metabolic pathways. These protein complexes were significantly decreased following curcumin intervention in IL-17A-exposed mice. An in silico binding analysis demonstrated that during the interaction between curcumin and IL-17A, hydrogen bonds were formed between the hydroxyl group of curcumin and the hydrophobic amino acid LEU97. Similarly, curcumin also participated in bond formation with the chemokine CXCL12. The interaction between the curcumin ring structure and ARG47 was elucidated. The study also investigated the amino group (NH) of curcumin and showed robust binding with GLU15. Additionally, curcumin's carboxyl group (O) was implicated in bond formation with the amino acid residues ARG47 and ASN45 of CXCL12. The nitrogen group (N) of curcumin was found to form bonds with the amino acid residue ALA19 of the afore-mentioned chemokine. The results presented in the analysis provide a comprehensive view of the cellular composition and key gene expression in pulmonary fibrosis (PF) and control lung specimens, enabling us to deepen our understanding of the disease process at the single-cell level. The use of UMAP analysis to categorize diagnoses into six distinct groups underscores the heterogeneity of interstitial lung diseases. The discovery of 31 cell type expression patterns further highlights the complexity of the lung cellular microenvironment and its probable contribution to the disease pathogenesis. Particularly notable is the differential expression of various key genes across both disease and control groups. In the IPF subset, significant upregulation of genes such as TP53, PAI-1, BLMH, ITGB1, STAT3, VIM, FBLN1, FBLN2, MMP2, NFKB1, JAK1, and IL27RA was observed. The increased expression of these genes, notably ITGB1, STAT3, FBLN1, FBLN2, and MMP2 in mesenchymal cells, may point to their crucial role in the fibrotic process. Especially interesting is the marked expression of PAI-1 in fibroblasts and FBLN1, FBLN2, and MMP2 in fibroblasts and myofibroblasts, as these patterns may be indicative of progressive disease. Looking at the immune cell subset, we see a substantial difference in the expression of ITGB1, STAT3, and VIM in IPF immune cells compared to control. The expression of NFKB1 in IPF mast cells and IL2RB in proliferating macrophages might suggest a potential mechanism of disease development and progression via these immune pathways. Finally, the epithelial cell analysis focused on AT1 and AT2 cells reveals differential expression of ITGB1, STAT3, and JAK1, which could potentially impact the epithelial-mesenchymal transition process, a key feature in IPF. The significant overexpression of JAK1 in control and AT2 cells may also indicate its role in protective mechanisms. Overall, these results provide valuable insights into the cellular and genetic landscape of pulmonary fibrosis and associated diseases. They underscore the critical role of various genes in disease pathology and progression and may help pave the way for the development of new therapeutic strategies. However, the exact biological functions and interplay of these genes in disease pathogenesis require further investigation. Conclusion These findings highlight curcumin's potent regulatory role in moderating acute alveolar epithelial inflammation and controlling IL-17A-mediated inflammatory responses in lung injury. Notably, curcumin's capability to counteract IL-17A induced expressions of P-p53, p53, and PAI-I suggests its restorative potential in the p53 fibrinolytic system. The study also demonstrates curcumin's ability to downregulate cleaved caspase-3 expression levels, which confirms its protective role in mitigating cell death. Through label-free quantitative proteomics analysis, it uncovers how curcumin intervention significantly impacts the expression of key proteins involved in inflammatory and metabolic pathways in IL-17A-exposed mice. Furthermore, through single-cell analysis, the study provides valuable insights into the complex interplay between genes and cells, underlining the heterogeneity of interstitial lung diseases. The binding properties of curcumin, as revealed by in silico analysis, suggests its potential for therapeutic applications. Abbreviations Acute Lung Injury (ALI), Interleukin 17A (IL-17A), Transforming Growth Factor beta (TGF-β), Interleukin 6 (IL-6), Interleukin 1 beta (IL-1β), Tumor Necrosis Factor alpha (TNF-α), Interleukin 17F (IL-17F), Interleukin 17 Receptor A (IL-17RA), Interleukin 17 Receptor C (IL-17RC), T helper 17 cells (Th17), Toll-like Receptor 2 (TLR2), Myeloid differentiation primary response 88 (MyD88), Thymosin beta-4 (Tβ4), Chemokine (C-X-C motif) ligand 1 (CXCL1), Chemokine (C-C motif) ligand 2 (CCL2), Chemokine (C-C motif) ligand 7 (CCL7), Chemokine (C-C motif) ligand 20 (CCL20), Matrix Metalloproteinases (MMPs), Untranslated Region (UTR), Urokinase Plasminogen Activator (uPA), Urokinase Plasminogen Activator Receptor (uPAR), Plasminogen Activator Inhibitor-1 (PAI-1), Bronchoalveolar Lavage Fluid (BALF), Tissue Inhibitor of Matrix Metalloproteinase-1 (TIMP-1), Mitogen-Activated Protein Kinase (MAPK), Janus Kinase/Signal Transducers and Activators of Transcription (JAK/STAT), Alveolar Epithelial Cell (AEC), Pulmonary Fibrosis (PF), Mass Spectrometry (MS), Single-cell RNA sequencing (scRNA-seq), Interstitial Lung Disease (ILD), Idiopathic Pulmonary Fibrosis (IPF), Nonspecific Interstitial Pneumonia (NSIP), Sarcoidosis, and Chronic Hypersensitivity Pneumonitis (cHP). Declarations Acknowledgments Authors would like to acknowledge the facility provided by Yenepoya (Deemed to be University) and financial support rendered by ICMR and Seed Grant from Yenepoya (Deemed to be University). D. A. B. Rex is a recipient of the Senior Research Fellowship from the Indian Council of Medical Research (ICMR), Government of India. Conflicts of interest Authors declare that they have no conflict of interest. Ethical approval This in vivo study is ethically approval by the CPCSEA and Institutional animal ethics committee, Yenepoya University. Author contributions Conceived the idea and designed the experiments: YPB and MMG. MMG, PM and YPB designed the proteomic experiments. PM processed the samples for the mass spectrometry analysis. Performing experiments: MMG. Proteomics and single cell data analysis and visualization: MMG. Proteomics data analysis: RDAB, and SK. Schroedinger in silico analysis: JC. Funding Sources This work was supported by the ICMR Grant (59/12/2015/online/BMS/TRM- 2015-1235). Data Availability Data Availability Statement: single-cell RNA sequencing dataset is available on GEO (GSE135893) and contact the corresponding author for the proteomics data. References Gouda, M.M., and Bhandary, Y.P. 2018. Curcumin down-regulates IL-17A mediated p53-fibrinolytic system in bleomycin induced acute lung injury in vivo . Journal of Cellular Biochemistry 119:7285–7299. Grommes, J., and Soehnlein, O. 2011. Contribution of neutrophils to acute lung injury. Molecular Medicine 17:293–307. Johnson, E.R., and Matthay, M.A. 2010. Acute lung injury: epidemiology, pathogenesis, and treatment. Journal of Aerosol Medicine and Pulmonary Drug Delivery 23:243–52. Robb, C.T., et al. 2016. Key mechanisms governing resolution of lung inflammation. Seminars in Immunopathology 38:425–48. Holdsworth, S.R., and Gan, P.Y. 2015. Cytokines: Names and Numbers You Should Care About. Clinical Journal of the American Society of Nephrology 10:2243–54. Goss, C.H., et al. 2003. Incidence of acute lung injury in the United States. Critical Care Medicine 31:1607–11. Jin, W., and Dong, C. 2013. IL-17 cytokines in immunity and inflammation. Emerging Microbes & Infections 2:e60. Goepfert, A., et al. 2017. The human IL-17A/F heterodimer: a two-faced cytokine with unique receptor recognition properties. Scientific Reports 7:8906. Brembilla, N.C., Senra, L., and Boehncke, W.H. 2018. The IL-17 Family of Cytokines in Psoriasis: IL-17A and Beyond. Frontiers in Immunology 9:1682. Ghoreschi, K., et al. 2010. Generation of pathogenic T(H)17 cells in the absence of TGF-beta signalling. Nature 467:967–71. Wu, Q., et al. 2020. p53: A Key Protein That Regulates Pulmonary Fibrosis. Oxidative Medicine and Cellular Longevity 2020:6635794. Nagaraja, M.R., et al. 2018. p53 Expression in Lung Fibroblasts Is Linked to Mitigation of Fibrotic Lung Remodeling. The American Journal of Pathology 188:2207–2222. Gouda, M.M., et al. 2018. Changes in the expression level of IL-17A and p53-fibrinolytic system in smokers with or without COPD. Molecular Biology Reports 45:2835–2841. Kuwabara, T., et al. (2017) The Role of IL-17 and Related Cytokines in Inflammatory Autoimmune Diseases. Mediators of Inflammation 3908061. Archer, N.K., et al. 2016. Interleukin-17A (IL-17A) and IL-17F Are Critical for Antimicrobial Peptide Production and Clearance of Staphylococcus aureus Nasal Colonization. Infection and Immunity 84:3575–3583. Onishi, R.M., and Gaffen, S.L. 2010. Interleukin-17 and its target genes: mechanisms of interleukin-17 function in disease. Immunology 129:311–21. Bozinovski, S., et al. 2015. Innate cellular sources of interleukin-17A regulate macrophage accumulation in cigarette- smoke-induced lung inflammation in mice. Clinical Science 129:785–96. Gu, C., Wu, L., and Li, X. 2016. IL-17 family: cytokines, receptors and signaling. Cytokine 64:477–85. Wu, L.J., Zepp, L. X. 2012. Function of Act1 in IL-17 family signaling and autoimmunity. Advances in Experimental Medicine and Biology 946:223–35. Banerjee, S., et al. 2015. Morphine compromises bronchial epithelial TLR2/IL17R signaling crosstalk, necessary for lung IL17 homeostasis. Scientific Reports 5:11384. Conte, E., et al. 2014. Thymosin beta4 reduces IL-17-producing cells and IL-17 expression, and protects lungs from damage in bleomycin-treated mice. Immunobiology 219:425–31. Luo, J., et al. 2019. Epigenetic Regulation of IL-17-Induced Chemokines in Lung Epithelial Cells. Mediators of Inflammation 9050965. Gouda, M.M., et al. 2020. Proteomics Analysis Revealed the Importance of Inflammation-Mediated Downstream Pathways and the Protective Role of Curcumin in Bleomycin-Induced Pulmonary Fibrosis in C57BL/6 Mice. Journal Proteome Research 19:2950–2963. Ding, W., et al. 2015. Interleukin-17A promotes the formation of inflammation in the lung tissues of rats with pulmonary fibrosis. Experimental and Therapeutic Medicine 10:491–497. Aggarwal, B.B., and Harikumar, K.B. 2009. Potential therapeutic effects of curcumin, the anti-inflammatory agent, against neurodegenerative, cardiovascular, pulmonary, metabolic, autoimmune and neoplastic diseases. The International Journal of Biochemistry & Cell Biology 41:40–59. Bhandary, Y.P., et al. 2015. Role of p53-fibrinolytic system cross-talk in the regulation of quartz-induced lung injury. Toxicology and Applied Pharmacology 283:92–8. Gouda, M.M., Prabhu, A., and Bhandary, Y.P. 2018. Curcumin alleviates IL-17A-mediated p53-PAI-1 expression in bleomycin-induced alveolar basal epithelial cells. Journal of Cellular Biochemistry 19:2222–2230. Porter, A.G., and Janicke, R.U. 1999. Emerging roles of caspase-3 in apoptosis. Cell Death Differentiation 6:99–104. Bockerstett, K.A., et al. 2018. Interleukin-17A Promotes Parietal Cell Atrophy by Inducing Apoptosis. Cellular and Molecular Gastroenterology and Hepatology 5:678–690. Habermann, A.C., et al. 2020. Single-cell RNA sequencing reveals profibrotic roles of distinct epithelial and mesenchymal lineages in pulmonary fibrosis. Science Advances 6(28):eaba1972. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 19 Oct, 2024 Read the published version in Inflammation → Version 1 posted Editorial decision: Revision requested 17 Jun, 2024 Reviews received at journal 17 Jun, 2024 Reviews received at journal 01 Jun, 2024 Reviewers agreed at journal 31 May, 2024 Reviewers agreed at journal 12 May, 2024 Reviewers agreed at journal 12 May, 2024 Reviewers agreed at journal 10 May, 2024 Reviewers invited by journal 10 May, 2024 Editor assigned by journal 10 May, 2024 Submission checks completed at journal 10 May, 2024 First submitted to journal 10 May, 2024 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-4400688","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":301602768,"identity":"e43f55d7-5141-4ea5-aa2a-254af2130fc3","order_by":0,"name":"Mahesh Manjunath Gouda","email":"","orcid":"","institution":"University of Bonn","correspondingAuthor":false,"prefix":"","firstName":"Mahesh","middleName":"Manjunath","lastName":"Gouda","suffix":""},{"id":301602769,"identity":"958e49ae-0521-410b-bf8b-5907d8daa074","order_by":1,"name":"Rex Devasahayam Arokia Balaya","email":"","orcid":"","institution":"Yenepoya Research Centre, Yenepoya (Deemed to be University)","correspondingAuthor":false,"prefix":"","firstName":"Rex","middleName":"Devasahayam Arokia","lastName":"Balaya","suffix":""},{"id":301602770,"identity":"8fd81fec-4e5b-475c-ba15-610be94fcf37","order_by":2,"name":"Prashant Kumar Modi","email":"","orcid":"","institution":"Yenepoya Research Centre, Yenepoya (Deemed to be University)","correspondingAuthor":false,"prefix":"","firstName":"Prashant","middleName":"Kumar","lastName":"Modi","suffix":""},{"id":301602771,"identity":"4691ec84-ba24-44ac-9e6d-8add2ed2c462","order_by":3,"name":"Safouane Kadri","email":"","orcid":"","institution":"Helmholtz-Zentrum München","correspondingAuthor":false,"prefix":"","firstName":"Safouane","middleName":"","lastName":"Kadri","suffix":""},{"id":301602772,"identity":"6dbe50a2-6b21-46c7-b5c7-ea9737b9d259","order_by":4,"name":"Jaikanth Chanderasekaran","email":"","orcid":"","institution":"Sri Ramachandra Institute of Higher education and Research (Deemed to be University","correspondingAuthor":false,"prefix":"","firstName":"Jaikanth","middleName":"","lastName":"Chanderasekaran","suffix":""},{"id":301602773,"identity":"c7103e40-e131-497f-bceb-755e9adc8499","order_by":5,"name":"Yashodhar Prabhakar Bhandary","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIiWNgGAWjYHACNoYPFQcSgAwDILYBYsbGA4S0MM44A9eSBtLSQFALM28bXMthsBBeLQbHjz97wHPmTh7/7OaNnyvbztutbT8MtKXGJhqnljM55gYSFc+KJe4cK5Y823Y7eduZRKCWY2m5Dbi0HMhhkzA4czix4UaOgWQjUIvZAaAWxobDuLWcf/5MIrHtcOL8GznGPxvbziWbnX9IQMuNBDOJg0AtG27kmAFtOWBndoOALZI33phJNpx5lrjxRlqZZcO55ASzG0BbEvD4he98+jPpPxV3EufdSN58s6HMzt7sfPrDBx9qbHBqUTiAzGNkY0gEq0zAoRwE5FHN+sNgj0fxKBgFo2AUjFAAAFcQdNhNkgTsAAAAAElFTkSuQmCC","orcid":"","institution":"Yenepoya Research Centre, Yenepoya (Deemed to be University)","correspondingAuthor":true,"prefix":"","firstName":"Yashodhar","middleName":"Prabhakar","lastName":"Bhandary","suffix":""}],"badges":[],"createdAt":"2024-05-10 12:32:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4400688/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4400688/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10753-024-02167-3","type":"published","date":"2024-10-19T15:57:41+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57290218,"identity":"868e271e-55d9-468b-a20e-62fd31373d6c","added_by":"auto","created_at":"2024-05-28 17:55:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":708891,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIL-17A induced lung injury in C57BL/6 mice. \u003c/strong\u003e(a) Schematic representation of IL-17A recombinant protein induced lung injury and curcumin intervention in mice followed by proteomics analysis. (b) Effect of curcumin on IL-17A altered lung histology. Mice were exposed to\u003cstrong\u003e \u003c/strong\u003eIL-17A (1 µg) followed by curcumin (75 mg/kg body weight of mouse) intervention. Mice were sacrificed after 72 h and lung histology was photographed. Representative photographs are shown. (c) Immunofluorescent staining to locate IL-17A expression. Mice lung tissue sections were subjected to immunofluorescent staining using IL-17A antibody. Representative microscopic images are shown. Image quantifications were shown compared to saline (*p\u0026lt;0.05); compared to IL-17A treatment (#p\u0026lt;0.05) (Mean±SD, n=3). (d) Effect of curcumin on IL-17A protein expression. IL-17A levels were analyzed using western blotting and normalized with β-actin; representative blots are shown. Quantitative values for each treatment were obtained by densitometric analysis. *p\u0026lt;0.05 compared to saline; #p\u0026lt;0.05 compared to IL-17A treatment (Mean±SD, n=3). (e) Effect of curcumin on IL-17A mRNA expression. Total RNA was isolated from mice lung tissues and RT-PCR was performed using IL-17A gene specific primers. Relative expression of IL-17A mRNA was compared with β-actin; the relative fold changes are shown. *p\u0026lt;0.05 compared to saline; #p\u0026lt;0.05 compared to IL-17A treatment (Mean±SD, n=3). (f) \u003cem\u003eIn silico\u003c/em\u003e molecular docking to validate the molecular interaction of curcumin with the binding site of IL-17A protein. (g) Venn diagram for the identified genes. (h) Comparison of the number of genes involved in the Molecular function (MF), Cellular component (CC), and biological process (BP) based on the PANTHER gene ontology. (i)\u003cstrong\u003e \u003c/strong\u003eRepresentation of top 15 enriched pathways between IL-17A vs IL-17A + curcumin based on the fold enrichment.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4400688/v1/c5b83fbb4c86cc93bf50993d.png"},{"id":57290224,"identity":"087597da-7a14-43f4-b682-6e4dfcf2e9ae","added_by":"auto","created_at":"2024-05-28 17:55:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":979023,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIL-17A mediated p53 fibrinolytic system in C57BL/6 mice. \u003c/strong\u003e(a)\u003cstrong\u003e \u003c/strong\u003eEffect of curcumin on P-p53, p53, and PAI-I expression. Mice were exposed to\u003cstrong\u003e \u003c/strong\u003eIL-17A followed by curcumin intervention. After 72 h, expression levels of P-p53, p53, and PAI-I was analyzed using western blotting and normalized with β-actin; representative blots are shown. Quantitative values for each treatment were obtained by densitometric analysis. *p\u0026lt;0.05 compared to saline; #p\u0026lt;0.05 compared to IL-17A treatment (Mean±SD, n=3). (b) Effect of curcumin on uPA, uPAR, and PAI-I mRNA expression. Total RNA was isolated from mice lung tissues and analyzed for RT-PCR using uPA, uPAR, and PAI-I gene specific primers. Relative expressions were compared with β-actin and fold changes are shown.*p\u0026lt;0.05 compared to saline; #p\u0026lt;0.05 compared to IL-17A treatment (Mean±SD, n=3). (c) Immunofluorescent staining to locate P-p53, p53, and PAI-I expression. Mice lung tissue sections were subjected to immunofluorescent staining using P-p53, p53, and PAI-I antibodies. Representative microscopic images are shown. Image quantifications were shown compared to saline (*p\u0026lt;0.05); compared to IL-17A treatment (#p\u0026lt;0.05) (Mean±SD, n=3). (d) Protein to protein interaction heatmap of top 10 enriched pathways proteins between IL-17A vs IL-17A + curcumin. (e) Differentially regulated proteins of the IL-17A mediated inflammatory pathways were listed and compared with curcumin intervention. Heatmaps and plots are represented based on the fold changes of the specific proteins.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4400688/v1/2e97707484f82ab7c5be56d5.png"},{"id":57290221,"identity":"22230fac-8299-4eb7-be88-d2728ad3fe8b","added_by":"auto","created_at":"2024-05-28 17:55:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":885314,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIL-17A induced alveolar epithelial cell apoptosis in C57BL/6 mice and integration of control and IPF single cells. \u003c/strong\u003e(a) Effect of curcumin on cleaved caspase-3 expression. Cleaved caspase-3 expression levels were analyzed using western blotting and normalized with β-actin; representative blots are shown. Quantitative values for each treatment were obtained by densitometric analysis. *p\u0026lt;0.05 compared to saline; #p\u0026lt;0.05 compared to IL-17A treatment (Mean±SD, n=3). (b) Immunofluorescent staining to locate cleaved caspase-3 expression. Mice lung tissue sections were subjected to immunofluorescent staining using cleaved caspase-3 antibody. Representative microscopic images are shown. Image quantifications were shown compared to saline (*p\u0026lt;0.05); compared to IL-17A treatment (#p\u0026lt;0.05) (Mean±SD, n=3). (c) \u003cem\u003eIn silico\u003c/em\u003e molecular docking to validate the molecular interaction of curcumin with the binding site of cleaved caspase-3 protein. (d) UMAP representation of 111,900 cells from control and IPF specimens. (e) UMAP embedding of diagnosis categories namely control, ILD, IPF, NSIP, sarcoidosis, and cHP. UMAP representation of cell population namely endothelial, epithelial, immune, and mesenchymal. (f) UMAP embedding of resulted 31 cell types.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4400688/v1/950d0b74045c4f2e76b7cbfd.png"},{"id":57290222,"identity":"ea2f23cf-12d8-47ef-9765-2b33ee0391f1","added_by":"auto","created_at":"2024-05-28 17:55:33","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1583942,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKey genes expression in control and IPF single cells. \u003c/strong\u003e(a) UMAP embedding of\u003cstrong\u003e \u003c/strong\u003e87,248 control and IPF single cells. (b) Key genes median expression in cell population. (c) Key genes median expression in diagnosis categories. (d) Key genes median expression in cell types. (e) UMAP embedding of key genes expression in control and IPF single cells.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4400688/v1/3e663fd3e5ef156bd9ccdc4c.png"},{"id":57290227,"identity":"74b6b049-f469-4a5c-b9da-8079d448c288","added_by":"auto","created_at":"2024-05-28 17:55:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1481311,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvaluation of control cells. \u003c/strong\u003e(a) UMAP embedding of\u003cstrong\u003e \u003c/strong\u003e31,127 control single cells. (b) Key genes median expression in cell types. (c) Key genes median expression in cell population. (d) UMAP embedding of key genes expression in control single cells.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4400688/v1/00f9489181923b48129091e7.png"},{"id":57292363,"identity":"67c3397d-4a3c-4546-8c77-d667a31bd0d9","added_by":"auto","created_at":"2024-05-28 18:03:34","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1550220,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvaluation of IPF cells. \u003c/strong\u003e(a) UMAP embedding of\u003cstrong\u003e \u003c/strong\u003e56,121 IPF single cells. (b) Key genes median expression in cell types. (c) Key genes median expression in cell population. (d) UMAP embedding of key genes expression in IPF single cells.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4400688/v1/5d1c1f003b2633caf98c940c.png"},{"id":57290219,"identity":"4d8c6b5f-df3f-4773-a9a6-4bf316bda51e","added_by":"auto","created_at":"2024-05-28 17:55:33","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":634341,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvaluation of control and IPF immune cells. \u003c/strong\u003e(a) UMAP embedding of\u003cstrong\u003e \u003c/strong\u003e44,984 control and IPF immune cells. (b) UMAP embedding of immune cell types in control and IPF immune cells. (c) Key genes median expression in control and IPF immune cells. (d) UMAP representation of 19,398 control immune cells and key genes median expression in immune cell types. (e) UMAP representation of 25,586 IPF immune cells and key genes median expression in immune cell types.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4400688/v1/b671d80354199ffc641e2320.png"},{"id":57290223,"identity":"b675192c-9c7d-4c66-ac72-b1e0db460f90","added_by":"auto","created_at":"2024-05-28 17:55:33","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":666851,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvaluation of control and IPF epithelial cells. \u003c/strong\u003e(a) UMAP embedding of\u003cstrong\u003e \u003c/strong\u003e8,108 control and IPF cells. (b) UMAP representation of AT1 and AT2 epithelial cells. (c) Key genes median expression in control and IPF epithelial cells. (d) Key genes median expression in AT1 and AT2 epithelial cells. (e) UMAP embedding of key genes expression in AT1 and AT2 epithelial cells.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-4400688/v1/1eaac971eaa8a527afb90e05.png"},{"id":67149007,"identity":"1081ea79-f48a-44fb-a02a-7ebf86c908ed","added_by":"auto","created_at":"2024-10-21 16:10:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9148347,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4400688/v1/43db8dea-e070-4a88-9fe1-42a2d58a5335.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Proteomic and Single-Cell insights unveiling therapeutic potential of curcumin against IL- 17A induced acute lung injury in C57BL/6 mice","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAcute lung injury (ALI) is marked by severe inflammation of the alveolar epithelium, which triggers the release of inflammatory cytokines, accumulation of macrophages, and neutrophil infiltration, culminating in the destruction of the alveolar epithelium [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Such destruction precipitates an intense inflammatory response [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. As part of the defence mechanism, various biomolecules with diverse functions are mobilized, including cytokines, small glycoprotein messengers that play an integral role in immune responses [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This catalyzes acute inflammation, igniting the innate immune response. ALI incidence in the United States is estimated at 22 per 0.1\u0026nbsp;million population, with a fatality rate of 40\u0026ndash;50% [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. IL-17, orchestrates pro-inflammatory responses by critically participating in lung immunity regulation. IL-17 is categorized into six subtypes, IL-17A to IL-17F with IL-17A and IL-17F best understood in terms of biological functionality [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. IL-17A and IL-17F are heterodimers operating through an IL-17RA and IL-17RC heterodimeric receptor complex [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Th17 cells, pivotal in various adaptive immunities, produce IL-17A and IL-17F [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Current research reveals Th17 cells release TGF-β, IL-6, IL-1β, and TNF-α, which regulate IL-17A. TGF-β and IL-6 can induce Th17 activation and proliferation, as well as IL-17 production [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Thus, IL-17A engenders tissue inflammation and host defense via multiple signal regulation aspects. IL-17A also influences the alteration of p53 expression, leading to pulmonary fibrosis progression [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. IL-17A-driven production of pro-inflammatory cytokines, chemokines, and antimicrobial peptides by diverse airborne cell types is crucial for robust host defence against pathogens [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLiterature suggests that IL-17A plays a role in the accumulation of macrophages in lungs exposed to cigarette smoke, and it targets non-traditional T cell sources of IL-17A[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This may present an alternative strategy to regulate pathogenic macrophages. Concurrent activation of TLR2 and IL-17R in bronchial epithelium leads to the sequestration of MyD88 by Act1/CIKS, thereby neutralizing TLR2 signaling and restoring homeostasis[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Morphine exerts an inhibitory influence on early IL-17 release and the Act1-MyD88 interaction, causing pathogen clearance reduction and persistent inflammation [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThymosin-β4 (Tβ4) participates in the modulation of Bleomycin-induced IL-17 expression in the lung. Tβ4 treatment results in decreased IL-17 producing cells and inhibits IL-17 expression in the lung, correlating with its antifibrotic effect [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. IL-17A primarily executes its immunoregulatory function by encouraging inflammatory activity, and by recruiting neutrophils and macrophages to inflammation sites. IL-17A receptors are commonly found in non-hematopoietic cells such as fibroblasts and epithelial cells [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the lung epithelial cell line treated with IL-17A, the upregulation of several cytokines, including chemokines (C-X-C motif) ligand (CXCL1), chemokine (C-C motif) ligand 2 (CCL2), CCL7, CCL20, and matrix metalloproteinases (MMPs) 3 and 13, was observed [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The augmented expression of IL-17A also coincides with the expression of p53 and its cross-linked regulation. Elevated expression of p53 is noted in IL-17A mediated changes during lung injury, leading to increased p53 expression [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Upon lung injury, p53 expression amplifies in type II alveolar epithelial cells (AECs). p53 operates at transcriptional and post-transcriptional levels to regulate gene expression. An enhanced interaction of p53 with the untranslated region (UTR) of urokinase plasminogen activator (uPA), urokinase plasminogen activator receptor (uPAR), and plasminogen activator inhibitor-1 (PAI-1) mRNAs aids in preventing the onset of pulmonary fibrosis [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent research indicates that IL-17A neutralization results in substantial downregulation of neutrophil presence in bronchoalveolar lavage fluid (BALF) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. It was found that the tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) leads to a decrease in IL-1β and IL-6. The crucial role of IL-17A in pulmonary fibrosis can be illustrated by the example of neutralized IL-17A triggering late inflammation through the IL-17RA signaling pathway. Literature underscores the inherent presence of the IL-1β-IL-23-IL-17A axis and its direct relevance to early lung inflammation and the progressive march towards fibrosis following injury [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our preceding studies, we identified IL-17A as a key downstream regulator of several critical pathways such as the p53-fibrinolytic system, MAPK, AKT, JAK/STAT signaling, and alveolar epithelial cell (AEC) apoptosis during ALI in alveolar basal epithelial cells, C57BL/6 mice, and during cigarette smoke-induced COPD (clinical samples) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In this paper, we present corroborative evidence for the pivotal role of IL-17A during IL17A recombinant protein-induced ALI in C57BL/6 mice. Our findings also support the therapeutic potential of curcumin against IL-17A mediated downstream changes during ALI.\u003c/p\u003e \u003cp\u003eHigh-throughput technologies, such as mass spectrometry (MS), facilitate absolute quantification of differentially expressed proteins in mouse lung tissue, determining the biological processes and protein-protein interactions involved in downstream signaling mechanisms. In silico strategies have made it possible to explore the potential interaction between curcumin and inflammatory proteins and apoptosis protein caspase 3. The integration of scRNA-seq data from 20 pulmonary fibrosis (PF) and 10 control lung specimens, encompassing 114,396 cells, has identified 31 unique cell subsets/states emphasized the importance of IL-17A mediated downstream regulation in PF patients. The comprehensive data generated from this study could be instrumental in developing novel therapeutic strategies against ALI and pulmonary fibrosis.\u003c/p\u003e"},{"header":"Methods and Materials","content":"\u003cp\u003e\u003cstrong\u003eMouse model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMale C57BL/6 mice, aged 7-8 weeks and weighing approximately 25 \u0026plusmn; 5 g, were employed for the animal studies. The mice were obtained from the central animal facility of Manipal College of Pharmaceutical Sciences, Manipal, India. The mice were accommodated in sterile polypropylene enclosures, with paddy husks serving as bedding material, and were granted unrestricted access to food and water. The execution of animal experiments received the endorsement of both the Committee for the Control and Supervision of Experiments on Animals (CPCSEA) and the Institutional Animal Ethics Committee (IAEC) of Yenepoya University (approval number: 11a/31/12/2015).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIL-17A induced Acute Lung injury in mice\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the study, mice were subjected to an intranasal administration of IL-17A recombinant protein (1 \u0026micro;g) to induce ALI. Following a 24-hour period, curcumin was administered intraperitoneally at a dosage of 75 mg/kg mouse body weight. After 72 hours post-IL-17A administration, the animal experiments were concluded (Figure 1a). Following the conclusion of the experiments, lung tissues were harvested from the mice for subsequent analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIsolation and quantification of proteins\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe harvested mouse lung tissue was homogenized utilizing an extraction buffer (sodium EDTA pH 7.9) and then subjected to centrifugation at 10,000 RPM for 15 minutes at 4\u0026deg;C. Subsequently, the supernatant was collected, and the protein concentration within the sample was ascertained via the Bradford method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWestern blotting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProteins extracted from mouse lung tissue were first separated using Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE) on 10% gels. Subsequently, they were electroblotted onto a polyvinylidene difluoride (PVDF) membrane which had been previously blocked with 2% Bovine Serum Albumin (BSA) in Tris-Buffered Saline with Tween-20 (TBST). The membrane was then incubated overnight at 4\u0026deg;C with specific primary antibodies, followed by further incubation with secondary antibodies conjugated with horseradish peroxidase (HRP). Protein expression patterns were visualized using the Enhanced Chemiluminescence (ECL) detection method (Pierce ECL Western Blotting Substrate, Thermo Fisher Scientific, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eqPCR analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was isolated from mouse lung tissue using the Tri reagent (Sigma-Aldrich). Adhering to the manufacturer\u0026apos;s guidelines, the concentration of the extracted total RNA was estimated, after which it underwent cDNA synthesis facilitated by the iScript cDNA synthesis kit (BIO-RAD). Quantitative Polymerase Chain Reaction (qPCR) was conducted using the FG power SYBR green PCR master mix (Thermo Fisher Scientific, USA). All utilized gene-specific primers are detailed below.\u003c/p\u003e\n\u003cp\u003e1) \u0026nbsp; Mouse IL-17A\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eForward: 5\u0026prime;-ACGTTTCTCAGCAAACTTAC-3\u0026prime;\u003c/p\u003e\n\u003cp\u003eReverse:\u0026nbsp;5\u0026prime;-CCCCTTTACACCTTCTTTTC-3\u0026prime;\u003c/p\u003e\n\u003cp\u003e2) \u0026nbsp; Mouse uPA\u003c/p\u003e\n\u003cp\u003eForward: 5\u0026prime;-AGAGTCTGAAAGTGACTATCTC-3\u0026prime;\u003c/p\u003e\n\u003cp\u003eReverse: 5\u0026prime;-CCTTCGATGTTACAGATAAGC-3\u0026prime;\u003c/p\u003e\n\u003cp\u003e3) \u0026nbsp; Mouse uPAR\u003c/p\u003e\n\u003cp\u003eForward: 5\u0026prime;-TCTGGATCTTCAGAGCTTTC-3\u0026prime;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Reverse: 5\u0026prime;-GCCTCTTACGGTATAACTCC-3\u0026prime;\u003c/p\u003e\n\u003cp\u003e4) \u0026nbsp; Mouse PAI-I\u003c/p\u003e\n\u003cp\u003eForward: 5\u0026prime;-AGCAACAAGTTCAACTACAC-3\u0026prime;\u003c/p\u003e\n\u003cp\u003eReverse: 5\u0026prime;-CTTCCATTGTCTGATGAGTTC-3\u0026prime;\u003c/p\u003e\n\u003cp\u003e5) \u0026nbsp; Mouse \u0026beta;-actin\u003c/p\u003e\n\u003cp\u003eForward: 5\u0026prime;-TTAATTTCTGAATGGCCCAG-3\u0026prime;\u003c/p\u003e\n\u003cp\u003eReverse: 5\u0026prime;-GACCAAAGCCTTCATACATC-3\u0026prime;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHistopathology and Immunofluorescence staining\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMouse lung tissue was formalin-fixed and paraffin-embedded (FFPE), then sectioned into 4.5 \u0026micro;m slices. These sections underwent sequential immersions in one to three xylene baths for paraffin removal, followed by rehydration using graded alcohol series. Subsequently, Hematoxylin and Eosin (H\u0026amp;E) staining was performed to identify histopathological changes within the lung tissue. For the detection of specific protein expressions in the tissue sections, immunofluorescence staining was utilized.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProteomics sample preparation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLysates from mouse lung tissue were prepared using a lysis buffer composed of 50 mM Triethylammonium bicarbonate (TEABC). Protein extraction was performed with a lysis buffer containing 4% Sodium Dodecyl Sulfate (SDS) and 50 mM TEABC. The protein concentration in the tissue lysates was subsequently determined using the bicinchoninic acid (BCA) assay.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein digestion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe process of in-solution digestion was undertaken as delineated in previous descriptions. Briefly, protein samples, each containing 50 \u0026micro;g of protein, were reduced using 10 mM dithiothreitol (DTT) and alkylated using 20 mM iodoacetamide (IAA). Following this, the salt concentration was minimized through acetone precipitation. Protein digestion ensued, employing trypsin (in a 1:20 ratio) (modified sequencing grade; Promega, Madison, WI), and was carried out at 37\u0026deg;C for a duration of 16 hours. After digestion, the peptides were lyophilized and desiccated before undergoing desalting via C18 cartridges. The desalted peptides were subjected to vacuum drying and subsequently stored at -80\u0026deg;C in preparation for liquid chromatography-mass spectrometry (LC-MS/MS) analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLC-MS/MS analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeptide were analyzed using the Thermo Scientific Q Exactive Plus-Orbitrap mass spectrometer (Thermo Fischer Scientific, Bremen, Germany), linked to the Easy-nLC-1200 nanoflow liquid chromatography system (Thermo Scientific). Peptides were reconstituted in 0.1% formic acid, then loaded onto a 2 cm trap column (nanoViper, 3 \u0026mu;m C18 Aq) (Thermo Fisher Scientific). Samples were processed with a 60-minute linear gradient of buffer B (95 percent acetonitrile and 0.1 percent formic acid) at a flow rate of 300 nL/min. Full MS scans were executed within the range of 350-1800 m/z, employing a resolution of 70,000, a target value of 1.00 + E6, and a permitted ion accumulation time of 60 ms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentification of peptides and proteins\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw mass spectrometry files were processed using the Proteome Discoverer 2.2 software suite (Thermo Fisher Scientific). The Mus musculus RefSeq89 database, which comprises 29,938 protein entries and common contaminants, was sourced from NCBI. MS/MS data were probed with this Protein Database and recognized mass spectrometers, employing the SEQUEST and Mascot algorithms. Search parameters encompassed carbamidomethylation of cysteine as a fixed modification and oxidation of methionine, as well as a minimum peptide length of 7 amino acids, allowing for 1 missed cleavage. The mass tolerance was determined at 10 ppm for MS and 0.05 Da for MS/MS, with the false discovery rate set at 1% for PSM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProteomics data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGene Ontology enrichment analysis was conducted using the VISEAGO (v 1.6.0) package in R (31406507). We accessed the public database for Biological Process (BP) and Molecular Function (MF) categories from the Gene Ontology (GO) database (http://geneontology.org/). Related gene terms of the identified mouse proteins were obtained from EnterGene and an enrichment analysis was undertaken for the proteins that exhibited differential expression between the treated and the curcumin-supplemented treated groups. All enriched GO terms (p \u0026lt; 0.01) were categorized into functional clusters via hierarchical clustering, considering the semantic similarity between GO terms based on the GO graph topology and using Ward\u0026apos;s criterion. Pathway enrichment analysis was executed using the pathfindeR package in R (v1.6.2) (31608109). We utilized the most recent version of the KEGG database with an enrichment threshold of an adjusted p-value of 0.01. Gene sets comprising 5 to 500 genes were considered with an enrichment threshold of 0.01. Graphical representation of the data was accomplished using the ggplot2 package (v 3.5.5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle cell sequencing data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe single-cell RNA sequencing dataset (GSE135893) was incorporated to further elucidate the regulatory pathway molecules mediated by IL-17A in pulmonary fibrosis (PF) patients and control subjects [30]. The dataset, comprising a total of 111,900 cells derived from 20 PF and 10 control lung samples, was scrutinized employing the Scanpy Python module. Stringent quality control measures were enacted by restricting the per-cell gene count to a range of 200-5000 and disregarding genes expressed in less than three cells. Following these measures, the data underwent normalization and subsequent log transformation. Genes exhibiting high variability were segregated based on predefined cut-off criteria.\u003c/p\u003e\n\u003cp\u003eIn the next stage, Principal Component Analysis (PCA), powered by the \u0026apos;arpack\u0026apos; singular value decomposition (SVD) solver, was carried out on the filtered and normalized dataset. This process effectively reduced the dimensionality of the data while accentuating its primary axes of variation. The PCA-derived results were then employed to construct neighborhood graphs. The Louvain method was applied for community detection within these graphs, thus generating distinct, non-overlapping clusters of cells. The spatial distribution of these unique cellular clusters was visualized utilizing the Uniform Manifold Approximation and Projection (UMAP) technique.\u003c/p\u003e\n\u003cp\u003eAn array of UMAP plots was produced, each characterized by unique color codes representing parameters such as diagnostic classification, cellular population, and cell type. The expression trends of pivotal genes, specifically IL17A, TP53, SERPINE1 (PAI-1), BLMH, ITGB1, STAT3, VIM, COL1, COL5, FBLN1, FBLN2, MMP2, MMP5, NFKB1, GATA3, JAK1, IL27RA, and IL2RB were mapped on the UMAP and violin plots in their respective subsets. Additionally, the frequency of cell types expressing these target genes was calculated in conjunction with the cell counts across different populations. Exclusion criteria were set to filter out cell types and populations with counts falling below specified values.\u003c/p\u003e\n\u003cp\u003eData subsets correlating to different diagnostic groups (Control and IPF), immune cells, and epithelial cells (AT1 and AT2 cells) were generated. These subsets were visualized through UMAP and violin plots based on several parameters and gene expression trends. This comprehensive analytical pipeline facilitated a thorough exploration of the scRNA-seq data, unveiling critical insights about the unique cellular populations and the IL-17A mediated gene expression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIn silico\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;molecular docking studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVirtual screening based on structural characteristics was carried out using the GLIDE v7.7 (Grid-based Ligand Docking with Energetics) module from the Maestro v11.4 modeling suite, provided by Schroedinger, LLC, New York, NY, 2017-4. The software was installed on an Intel Core i7-4770 processor, utilizing the GNOME\u0026trade; Linux 2.6 Centos 6.5 kernel. GLIDE aims to identify the most favorable interactions between a ligand and a receptor molecule. The ligand could be a single entity, while the receptor could comprise more than one molecule. GLIDE operates through rigid or flexible docking modes, and the final ranking was based on the GLIDE Score. In cases where GLIDE Score was selected as the scoring function, the emodel score was used to rank the poses of the ligands. In silico docking was performed to elucidate the molecular interactions between curcumin, IL-17A, and cleaved caspase-3 protein molecules. The crystal structures of IL-17A and cleaved caspase-3 were procured from the Protein Data Bank (PDB).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data is presented as the mean \u0026plusmn; standard deviation. For statistical analysis, Student\u0026apos;s t-test was employed for comparison between two groups, and one-way analysis of variance (ANOVA) was utilized for comparing multiple groups. All data analyses were carried out using the GraphPad Prism 9.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eIL-17A expression during IL-17A-induced lung inflammation in C57BL/6 mouse\u003c/h2\u003e \u003cp\u003eBased on the empirical data derived from bleomycin (BLM)-exposed murine lungs [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], the ensuing inflammatory response was further probed by the introduction of recombinant IL-17A protein into the mice lungs. The findings indicated that IL-17A functions as the primary inflammatory cytokine implicated in the advancement of lung injury (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The concentration of IL-17A protein exhibited a significant augmentation upon exposure to IL-17A (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec and d). Complementing these findings, further validation of IL-17A mRNA expression revealed that IL-17A can potentiate the overproduction of IL-17A transcripts in the nucleus, thereby escalating IL-17A mRNA levels. IL-17A mRNA levels were found to be significantly elevated in the IL-17A-exposed mice relative to those treated with saline and curcumin. However, curcumin administration was capable of significantly suppressing IL-17A mRNA levels in the IL-17A-exposed mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). Corroborating this observation, curcumin was again evidenced to exert a protective effect against IL-17A-induced lung injury in mice. A significant reduction of IL-17A was discernible in the curcumin-treated mice, as confirmed by immunofluorescence staining (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eThe specific interaction between curcumin and IL-17A, particularly the binding of curcumin to the IL-17A binding sites, was examined via the Schroedinger in silico methodology. The interaction of curcumin with IL-17A is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef. The docking simulation generated a docking energy of -3.69 Kcal/mol, indicative of hydrogen bond formation. Specifically, a hydrogen bond was formed between the hydroxyl group of curcumin and the hydrophobic amino acid residue, LEU97 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eProteins associated with IL-17A mediated downstream pathways during IL-17A induced ALI in C57BL/6 mice\u003c/h2\u003e \u003cp\u003eThe proteomic analysis of lung homogenate samples from mice exposed to saline, IL-17A, and IL-17A plus curcumin led to the detection of 1124, 910, and 1465 proteins, respectively. From these, we identified 481 unique proteins across the experimental groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg). These data, derived from label-free or quantitative proteomics, were subjected to functional enrichment analysis to characterize each protein's role. Pathway enrichment analysis revealed that IL-17A administration in mice upregulated proteins associated with signaling pathways such as NF-κB, TH17 cell differentiation, JAK-STAT signaling, RNA transport, and oxidative phosphorylation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ei). These pathways are well-established contributors to the pathophysiology of acute lung injury. The study substantiated that IL-17A administration does more than merely instigate inflammation; it also triggers several downstream signaling cascades, which could potentiate acute injury, leading to severe cellular apoptosis and subsequent fibrotic niche development.\u003c/p\u003e \u003cp\u003eWe investigated the 15 primary enriched signaling pathways elicited by IL-17A and validated the enriched proteins associated with TH17 cell differentiation, oxidative phosphorylation, the p53-plasmin cascade, and apoptosis in IL-17A-induced mouse lung injury models, using molecular approaches (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed and e). Interestingly, a robust interplay was observed between proteins involved in TH17 cell differentiation and various downstream signaling pathways such as NF-κB signaling, RNA transport, the spliceosome, oxidative phosphorylation, and JAK-STAT signaling (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurther analysis uncovered that the proteins exhibiting differential regulation between IL-17A treatment and curcumin intervention predominantly belong to the inflammation, MAPK, and apoptosis pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). Notably, the molecules associated with IL-17A differentiation, such as JAK1, IL27RA, HLA-DPA1, NFATC3, IL2RB, and GATA3, were significantly downregulated in the curcumin-treated mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003ep53-fibrinolytic system during IL-17A-induced lung in C57BL/6 mice\u003c/h2\u003e \u003cp\u003eIn the current investigation, we observed a significant upregulation in the expression of phosphorylated p53 (P-p53), p53, and PAI-I proteins following IL-17A administration in mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). However, the intervention with curcumin effectively counteracted the IL-17A-induced expression of P-p53, p53, and PAI-I, highlighting curcumin's restorative role in the IL-17A-mediated impairment of the p53 fibrinolytic system.\u003c/p\u003e \u003cp\u003eImmunofluorescence staining was employed to ascertain the expression levels of P-p53, p53, and PAI-I in lung tissues of mice exposed to IL-17A. The IL-17A-exposed mouse lungs exhibited an increased count of P-p53, p53, and PAI-I molecules, reinforcing IL-17A's role in promoting lung injury in mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Conversely, curcumin-treated mouse lungs presented minimal numbers of P-p53, p53, and PAI-I positive cells. This observation suggests that curcumin effectively modulates the p53-PAI-I expression, restoring it to physiological levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eAnalysis of IL-17A-mediated alterations in mRNA expression of fibrinolytic components demonstrated that IL-17A administration was implicated in the induction of PAI-I mRNA expression by suppressing uPA and uPAR mRNA levels in mice lungs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Concretely, PAI-I mRNA levels were significantly elevated, and uPA and uPAR mRNA levels were markedly reduced in the IL-17A-treated mice. In a reciprocal manner, curcumin intervention significantly downregulated PAI-I mRNA and upregulated uPA and uPAR mRNA expression in mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eCaspase-3 activation during IL-17A-induced lung in C57BL/6 mice\u003c/h2\u003e \u003cp\u003eTo confirm the role of IL-17A in alveolar epithelial cells (AECs) apoptosis, we introduced recombinant IL-17A protein in mice via intranasal administration. Upon IL-17A administration, the expression level of the apoptosis marker, cleaved caspase-3 protein, was significantly increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea and b). Conversely, intervention with curcumin led to a notable downregulation of cleaved caspase-3 expression, thus confirming curcumin's restorative role during IL-17A-mediated AECs cell death.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe expression of cleaved caspase-3 was further validated using immunofluorescent staining (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). IL-17A-exposed mouse lung tissue sections displayed enhanced staining for cleaved caspase-3 proteins, while curcumin treatment led to a significant decrease in the staining intensity. The molecular interaction of curcumin with the binding sites of cleaved caspase-3 was examined using the Schroedinger in silico approach. The interaction of curcumin with cleaved caspase-3 is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, showing robust molecular bonding with the ASP70, TYR67, and ARG66 residues of the cleaved caspase-3 protein (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eSingle cell integration to evaluate the IL-17A mediated pathway genes activities in IPF patient\u003c/h2\u003e \u003cp\u003eAs previously mentioned, a total of 111,900 single cells from 20 pulmonary fibrosis (PF) and 10 control lung specimens were analyzed using the Scanpy Python module, with individual lung specimen single cell data represented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed. Uniform Manifold Approximation and Projection (UMAP) analysis for diagnosis yielded six subcategories: Control, Interstitial Lung Disease (ILD), Idiopathic Pulmonary Fibrosis (IPF), Nonspecific Interstitial Pneumonia (NSIP), Sarcoidosis, and Chronic Hypersensitivity Pneumonitis (cHP) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). Further cellular population clustering resulted in identifiable cell clusters such as endothelial, epithelial, immune, and mesenchymal cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). Subclustering identified 31 different cell type expression patterns.\u003c/p\u003e \u003cp\u003eSubsequent evaluation of control and IPF subsets produced 87,248 single cells, with the expression of key genes of interest observed across diagnoses, cell populations, and cell types (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The insights gathered from the control and IPF subsets led us to subset the control and IPF individually, thereby visualizing the expression patterns of key genes of interest. The control subset yielded 31,127 single cells with key genes of interest visualized according to cell population and cell types (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). We observed no significant expression of IL-17A, PAI-1, p53, BLMH, NFKB1, GAT3, IL27RA, and IL2Rb in cell population and cell types compared to the IPF subset, comprising 56,121 single cells. In the IPF subset, significant high expression of TP53, PAI-1, BLMH, ITGB1, STAT3, VIM, FBLN1, FBLN2, MMP2, NFKB1, JAK1, and IL27RA were observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed). Notably, key genes such as ITGB1, STAT3, FBLN1, FBLN2, and MMP2 were significantly expressed in mesenchymal cells. PAI-1 expression was observed in fibroblasts (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec), and FBLN1, FBLN2, and MMP2 expression in fibroblasts and myofibroblasts, signaling progressive disease (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eSubsetting immune cells in control and IPF resulted in 44,984 single cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea), with 19,398 single cells in control (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed) and 25,586 single cells in IPF immune cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ee). Macrophages, B cells, NK cells, and T cells were highly expressed in IPF immune cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). A significant difference was observed in the expression of ITGB1, STAT3, and VIM in IPF immune cells compared to control (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ee). Additionally, NFKB1 expression in IPF mast cells and IL2RB in proliferating macrophages provides further insights into NFKB1 and IL2RB signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ee).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLastly, an analysis of 8,108 single cells from an epithelial cell subset of AT1 and AT2 cells furnished additional insights into AT1 and AT2 cell behavior in control and IPF single cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Although no observable expression of IL-17A was found in AT1 and AT2 cells, ITGB1 and STAT3 were highly expressed in both cell types (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ec and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ed). Interestingly, JAK1 expression was significantly higher in control and AT2 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ec and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current findings demonstrate the substantial regulatory role of curcumin in modulating acute alveolar epithelial inflammation, as well as the subsequent activation of IL-17A mediated macrophage accumulation and neutrophil infiltration in C57BL/6 mice [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. IL-17A has been identified as a central inflammatory cytokine implicated in the progression of lung injury [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This cytokine promotes an overproduction of IL-17A transcripts in the nucleus, potentially augmenting IL-17A mRNA levels. We observed a significant increase in IL-17A mRNA levels in IL-17A exposed mice, compared to those treated with saline and curcumin [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Our findings indicate that curcumin administration notably downregulates IL-17A mRNA levels in IL-17A exposed mice. Previous literature has highlighted the therapeutic potential of curcumin against inflammatory processes, stating that curcumin plays an integral role in mitigating numerous chronic diseases, including neurodegenerative, cardiovascular, pulmonary, metabolic, autoimmune, and neoplastic diseases [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The interaction of p53 with key fibrinolytic system components, such as uPA, uPAR, and PAI-1, has been reported to regulate apoptosis or survival following Acute Lung Injury (ALI) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Our results show a significant increase in the expression of P-p53, p53, and PAI-I proteins in mice post-IL-17A administration. However, intervention with curcumin was able to reverse IL-17A-induced expressions of P-p53, p53, and PAI-I, implying that curcumin administration exhibits a restorative effect in the context of IL-17A-mediated impairment of the p53 fibrinolytic system. Additionally, the mRNA levels of the fibrinolytic component PAI-I were significantly increased in the mice administered with IL-17A, while uPA and uPAR mRNA levels were notably decreased post-IL-17A administration.\u003c/p\u003e \u003cp\u003eCurcumin was shown to effectively modulate the IL-17A-mediated p53 fibrinolytic system during IL-17A-induced Acute Lung Injury (ALI) in vitro [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The administration of curcumin was found to regulate the IL-17A mediated p53-fibrinolytic system. Caspase-3, a crucial executor of apoptosis and an activated death protease catalyzing many vital cellular proteins [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], was shown to be activated by IL-17A injury, leading to increased expression of cleaved caspase-3 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. IL-17A administration significantly upregulated the expression level of cleaved caspase-3 proteins, whereas curcumin administration counteracted this by downregulating cleaved caspase-3 expression levels. Our study thus confirms curcumin's protective role in attenuating IL-17A mediated cell death of AECs. Further, immunofluorescence staining results corroborated that the expression of cleaved caspase-3 proteins decreased after curcumin treatment in IL-17A-exposed lung tissue sections of mice. Label-free quantitative proteomics bioinformatics analysis revealed that IL-17A administration in mouse lungs instigates ALI and mediates several downstream signaling pathways, including inflammation, oxidative phosphorylation, MAPK, p53, plasminogen cascade, JAK-STAT, and apoptosis. The differentially regulated proteins identified, such as IL-17A, TP53, PAI-1, BLMH, ITGB1, STAT3, VIM, FBLN1, FBLN2, MMP2, NFKB1, JAK1, and IL27RA, were found to be associated with the afore-mentioned metabolic pathways. These protein complexes were significantly decreased following curcumin intervention in IL-17A-exposed mice.\u003c/p\u003e \u003cp\u003eAn \u003cem\u003ein silico\u003c/em\u003e binding analysis demonstrated that during the interaction between curcumin and IL-17A, hydrogen bonds were formed between the hydroxyl group of curcumin and the hydrophobic amino acid LEU97. Similarly, curcumin also participated in bond formation with the chemokine CXCL12. The interaction between the curcumin ring structure and ARG47 was elucidated. The study also investigated the amino group (NH) of curcumin and showed robust binding with GLU15. Additionally, curcumin's carboxyl group (O) was implicated in bond formation with the amino acid residues ARG47 and ASN45 of CXCL12. The nitrogen group (N) of curcumin was found to form bonds with the amino acid residue ALA19 of the afore-mentioned chemokine.\u003c/p\u003e \u003cp\u003eThe results presented in the analysis provide a comprehensive view of the cellular composition and key gene expression in pulmonary fibrosis (PF) and control lung specimens, enabling us to deepen our understanding of the disease process at the single-cell level. The use of UMAP analysis to categorize diagnoses into six distinct groups underscores the heterogeneity of interstitial lung diseases. The discovery of 31 cell type expression patterns further highlights the complexity of the lung cellular microenvironment and its probable contribution to the disease pathogenesis. Particularly notable is the differential expression of various key genes across both disease and control groups. In the IPF subset, significant upregulation of genes such as TP53, PAI-1, BLMH, ITGB1, STAT3, VIM, FBLN1, FBLN2, MMP2, NFKB1, JAK1, and IL27RA was observed. The increased expression of these genes, notably ITGB1, STAT3, FBLN1, FBLN2, and MMP2 in mesenchymal cells, may point to their crucial role in the fibrotic process. Especially interesting is the marked expression of PAI-1 in fibroblasts and FBLN1, FBLN2, and MMP2 in fibroblasts and myofibroblasts, as these patterns may be indicative of progressive disease. Looking at the immune cell subset, we see a substantial difference in the expression of ITGB1, STAT3, and VIM in IPF immune cells compared to control. The expression of NFKB1 in IPF mast cells and IL2RB in proliferating macrophages might suggest a potential mechanism of disease development and progression via these immune pathways.\u003c/p\u003e \u003cp\u003eFinally, the epithelial cell analysis focused on AT1 and AT2 cells reveals differential expression of ITGB1, STAT3, and JAK1, which could potentially impact the epithelial-mesenchymal transition process, a key feature in IPF. The significant overexpression of JAK1 in control and AT2 cells may also indicate its role in protective mechanisms.\u003c/p\u003e \u003cp\u003eOverall, these results provide valuable insights into the cellular and genetic landscape of pulmonary fibrosis and associated diseases. They underscore the critical role of various genes in disease pathology and progression and may help pave the way for the development of new therapeutic strategies. However, the exact biological functions and interplay of these genes in disease pathogenesis require further investigation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThese findings highlight curcumin's potent regulatory role in moderating acute alveolar epithelial inflammation and controlling IL-17A-mediated inflammatory responses in lung injury. Notably, curcumin's capability to counteract IL-17A induced expressions of P-p53, p53, and PAI-I suggests its restorative potential in the p53 fibrinolytic system. The study also demonstrates curcumin's ability to downregulate cleaved caspase-3 expression levels, which confirms its protective role in mitigating cell death. Through label-free quantitative proteomics analysis, it uncovers how curcumin intervention significantly impacts the expression of key proteins involved in inflammatory and metabolic pathways in IL-17A-exposed mice. Furthermore, through single-cell analysis, the study provides valuable insights into the complex interplay between genes and cells, underlining the heterogeneity of interstitial lung diseases. The binding properties of curcumin, as revealed by in silico analysis, suggests its potential for therapeutic applications.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAcute Lung Injury (ALI), \u0026nbsp;Interleukin 17A (IL-17A), Transforming Growth Factor beta (TGF-\u0026beta;), Interleukin 6 (IL-6), Interleukin 1 beta (IL-1\u0026beta;), Tumor Necrosis Factor alpha (TNF-\u0026alpha;), Interleukin 17F (IL-17F), Interleukin 17 Receptor A (IL-17RA), Interleukin 17 Receptor C (IL-17RC), T helper 17 cells (Th17), Toll-like Receptor 2 (TLR2), Myeloid differentiation primary response 88 (MyD88), Thymosin beta-4 (T\u0026beta;4), Chemokine (C-X-C motif) ligand 1 (CXCL1), Chemokine (C-C motif) ligand 2 (CCL2), Chemokine (C-C motif) ligand 7 (CCL7), Chemokine (C-C motif) ligand 20 (CCL20), Matrix Metalloproteinases (MMPs), Untranslated Region (UTR), Urokinase Plasminogen Activator (uPA), Urokinase Plasminogen Activator Receptor (uPAR), Plasminogen Activator Inhibitor-1 (PAI-1), Bronchoalveolar Lavage Fluid (BALF), Tissue Inhibitor of Matrix Metalloproteinase-1 (TIMP-1), Mitogen-Activated Protein Kinase (MAPK), Janus Kinase/Signal Transducers and Activators of Transcription (JAK/STAT), Alveolar Epithelial Cell (AEC), Pulmonary Fibrosis (PF), Mass Spectrometry (MS), Single-cell RNA sequencing (scRNA-seq), Interstitial Lung Disease (ILD), Idiopathic Pulmonary Fibrosis (IPF), Nonspecific Interstitial Pneumonia (NSIP), Sarcoidosis, and Chronic Hypersensitivity Pneumonitis (cHP).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors would like to acknowledge the facility provided by Yenepoya (Deemed to be University) and financial support rendered by ICMR and Seed Grant from Yenepoya (Deemed to be University). D. A. B. Rex is a recipient of the Senior Research Fellowship from the Indian Council of Medical Research (ICMR), Government of India.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis \u003cem\u003ein vivo\u0026nbsp;\u003c/em\u003estudy is ethically\u0026nbsp;approval by the CPCSEA and Institutional animal ethics committee, Yenepoya University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceived the idea and designed the experiments: YPB and MMG. MMG, PM and YPB designed the proteomic experiments. PM processed the samples for the mass spectrometry analysis. \u0026nbsp;Performing experiments: MMG. Proteomics and single cell data analysis and visualization: MMG. \u0026nbsp;Proteomics data analysis: RDAB, and SK.\u0026nbsp;Schroedinger in silico analysis: JC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the ICMR Grant (59/12/2015/online/BMS/TRM- 2015-1235).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData Availability Statement: single-cell RNA sequencing dataset is available on GEO (GSE135893) and contact the corresponding author for the proteomics data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGouda, M.M., and Bhandary, Y.P. 2018. Curcumin down-regulates IL-17A mediated p53-fibrinolytic system in bleomycin induced acute lung injury \u003cem\u003ein vivo\u003c/em\u003e. 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Cellular and Molecular Gastroenterology and Hepatology 5:678\u0026ndash;690.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHabermann, A.C., et al. 2020. Single-cell RNA sequencing reveals profibrotic roles of distinct epithelial and mesenchymal lineages in pulmonary fibrosis. Science Advances 6(28):eaba1972.\u003c/span\u003e\u003c/li\u003e\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":"inflammation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ifla","sideBox":"Learn more about [Inflammation](https://www.springer.com/journal/10753)","snPcode":"10753","submissionUrl":"https://submission.nature.com/new-submission/10753/3","title":"Inflammation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"IL-17A, alveolar epithelial cells, p53, proteomics, scRNA-seq, acute lung injury, pulmonary fibrosis, curcumin","lastPublishedDoi":"10.21203/rs.3.rs-4400688/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4400688/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAcute lung injury (ALI) is primarily driven by an intense inflammation in the alveolar epithelium. Key to this is the pro-inflammatory cytokine, Interleukin 17 (IL-17), which influences pulmonary immunity and modifies p53 function. The direct role of IL-17A in p53-fibrinolytic system is still unclear, it is important to evaluate this mechanism to regulate the ALI progression to idiopathic pulmonary fibrosis (IPF). C57BL/6 mice, exposed to recombinant IL-17A protein and treated with curcumin, provided insight into IL-17A mechanisms and curcumin's potential for modulating early pulmonary fibrosis stages. A diverse methodology, including proteomics, single-cell RNA sequencing (scRNA-seq) integration, molecular, and Schroedinger approach were utilized. In silico approaches facilitated the potential interactions between curcumin, IL-17A, and apoptosis-related proteins. A notable surge in the expression levels of IL-17A, p53, and fibrinolytic components such as Plasminogen Activator Inhibitor-1 (PAI-I) was discerned upon the IL17A exposure in mouse lungs. Furthermore, the enrichment of pathways and differential expression of proteins underscored the significance of IL-17A in governing downstream regulatory pathways such as inflammation, NF-kappaB signaling, Mitogen-Activated Protein Kinases (MAPK), p53, oxidative phosphorylation, JAK-STAT, and apoptosis. The integration of scRNA-seq data from 20 IPF and 10 control lung specimens emphasized the importance of IL-17A mediated downstream regulation in PF patients. A potent immuno-pharmacotherapeutic agent, curcumin, demonstrated a substantial capacity to modulate the lung pathology and molecular changes induced by IL-17A in mouse lungs. Human IPF single cell data integration confirmed the effects of IL-17A mediated fibrinolytic components in ALI to IPF progression.\u003c/p\u003e","manuscriptTitle":"Proteomic and Single-Cell insights unveiling therapeutic potential of curcumin against IL- 17A induced acute lung injury in C57BL/6 mice","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-28 17:55:24","doi":"10.21203/rs.3.rs-4400688/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-17T12:57:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-17T06:15:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-02T01:33:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"92143223093298045794811285506023982814","date":"2024-05-31T08:35:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"219351189228130773340368879957834887008","date":"2024-05-12T20:11:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8470889756879929353086402879352918122","date":"2024-05-12T14:49:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81610268550820764177432505421479004473","date":"2024-05-10T15:19:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-10T14:06:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-10T13:19:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-10T13:19:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Inflammation","date":"2024-05-10T12:31:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"inflammation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ifla","sideBox":"Learn more about [Inflammation](https://www.springer.com/journal/10753)","snPcode":"10753","submissionUrl":"https://submission.nature.com/new-submission/10753/3","title":"Inflammation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a2155c6d-966f-4aff-ab3b-dafba06c833a","owner":[],"postedDate":"May 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-21T16:02:43+00:00","versionOfRecord":{"articleIdentity":"rs-4400688","link":"https://doi.org/10.1007/s10753-024-02167-3","journal":{"identity":"inflammation","isVorOnly":false,"title":"Inflammation"},"publishedOn":"2024-10-19 15:57:41","publishedOnDateReadable":"October 19th, 2024"},"versionCreatedAt":"2024-05-28 17:55:24","video":"","vorDoi":"10.1007/s10753-024-02167-3","vorDoiUrl":"https://doi.org/10.1007/s10753-024-02167-3","workflowStages":[]},"version":"v1","identity":"rs-4400688","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4400688","identity":"rs-4400688","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}