Exosome‐like nanoparticles from Mulberry bark prevent DSS‐induced colitis via the AhR/COPS8 pathway
2022; Springer Nature; Volume: 23; Issue: 3 Linguagem: Inglês
10.15252/embr.202153365
ISSN1469-3178
AutoresMukesh K. Sriwastva, Zhongbin Deng, Bomei Wang, Yun Teng, Anil Kumar, Kumaran Sundaram, Jingyao Mu, Chao Lei, Gerald W. Dryden, Fangyi Xu, Lifeng Zhang, Jun Yan, Xiang Zhang, Juw Won Park, Michael L. Merchant, Nejat K. Egilmez, Huang‐Ge Zhang,
Tópico(s)Extracellular vesicles in disease
ResumoArticle7 January 2022free access Source DataTransparent process Exosome-like nanoparticles from Mulberry bark prevent DSS-induced colitis via the AhR/COPS8 pathway Mukesh K Sriwastva Mukesh K Sriwastva orcid.org/0000-0003-4370-4625 Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Data curation, Formal analysis, Validation, Investigation, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Zhong-Bin Deng Zhong-Bin Deng Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Data curation, Formal analysis, Investigation, Methodology Search for more papers by this author Bomei Wang Bomei Wang Department of Translational Oncology, Genentech, San Francisco, California, USA Contribution: Investigation, Methodology Search for more papers by this author Yun Teng Yun Teng Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Conceptualization, Resources, Software, Validation Search for more papers by this author Anil Kumar Anil Kumar Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Formal analysis, Investigation Search for more papers by this author Kumaran Sundaram Kumaran Sundaram Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Formal analysis, Investigation Search for more papers by this author Jingyao Mu Jingyao Mu Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Data curation, Formal analysis, Investigation, Methodology Search for more papers by this author Chao Lei Chao Lei Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Formal analysis, Investigation, Methodology Search for more papers by this author Gerald W Dryden Gerald W Dryden Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Robley Rex Veterans Affairs Medical Center, Louisville, KY, USA Department of Pharmacology and Toxicology, University of Louisville, Louisville, KY, USA Contribution: Resources, Funding acquisition, Project administration Search for more papers by this author Fangyi Xu Fangyi Xu Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Investigation, Methodology Search for more papers by this author Lifeng Zhang Lifeng Zhang Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Resources, Data curation, Funding acquisition, Project administration Search for more papers by this author Jun Yan Jun Yan Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Resources, Data curation, Software Search for more papers by this author Xiang Zhang Xiang Zhang KBRIN Bioinformatics Core, University of Louisville, Louisville, KY, USA Contribution: Data curation, Software Search for more papers by this author Juw Won Park Juw Won Park orcid.org/0000-0002-4610-6893 KBRIN Bioinformatics Core, University of Louisville, Louisville, KY, USA Department of Computer Engineering and Computer Science, University of Louisville, Louisville, KY, USA Contribution: Software, Formal analysis Search for more papers by this author Michael L Merchant Michael L Merchant Kidney Disease Program and Clinical Proteomics Center, University of Louisville, Louisville, KY, USA Contribution: Data curation, Formal analysis Search for more papers by this author Nejat K Egilmez Nejat K Egilmez Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Data curation, Funding acquisition, Project administration Search for more papers by this author Huang-Ge Zhang Corresponding Author Huang-Ge Zhang [email protected] orcid.org/0000-0001-9665-9202 Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Robley Rex Veterans Affairs Medical Center, Louisville, KY, USA Contribution: Conceptualization, Supervision, Funding acquisition, Validation, Investigation, Writing - original draft, Project administration, Writing - review & editing Search for more papers by this author Mukesh K Sriwastva Mukesh K Sriwastva orcid.org/0000-0003-4370-4625 Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Data curation, Formal analysis, Validation, Investigation, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Zhong-Bin Deng Zhong-Bin Deng Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Data curation, Formal analysis, Investigation, Methodology Search for more papers by this author Bomei Wang Bomei Wang Department of Translational Oncology, Genentech, San Francisco, California, USA Contribution: Investigation, Methodology Search for more papers by this author Yun Teng Yun Teng Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Conceptualization, Resources, Software, Validation Search for more papers by this author Anil Kumar Anil Kumar Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Formal analysis, Investigation Search for more papers by this author Kumaran Sundaram Kumaran Sundaram Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Formal analysis, Investigation Search for more papers by this author Jingyao Mu Jingyao Mu Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Data curation, Formal analysis, Investigation, Methodology Search for more papers by this author Chao Lei Chao Lei Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Formal analysis, Investigation, Methodology Search for more papers by this author Gerald W Dryden Gerald W Dryden Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Robley Rex Veterans Affairs Medical Center, Louisville, KY, USA Department of Pharmacology and Toxicology, University of Louisville, Louisville, KY, USA Contribution: Resources, Funding acquisition, Project administration Search for more papers by this author Fangyi Xu Fangyi Xu Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Investigation, Methodology Search for more papers by this author Lifeng Zhang Lifeng Zhang Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Resources, Data curation, Funding acquisition, Project administration Search for more papers by this author Jun Yan Jun Yan Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Resources, Data curation, Software Search for more papers by this author Xiang Zhang Xiang Zhang KBRIN Bioinformatics Core, University of Louisville, Louisville, KY, USA Contribution: Data curation, Software Search for more papers by this author Juw Won Park Juw Won Park orcid.org/0000-0002-4610-6893 KBRIN Bioinformatics Core, University of Louisville, Louisville, KY, USA Department of Computer Engineering and Computer Science, University of Louisville, Louisville, KY, USA Contribution: Software, Formal analysis Search for more papers by this author Michael L Merchant Michael L Merchant Kidney Disease Program and Clinical Proteomics Center, University of Louisville, Louisville, KY, USA Contribution: Data curation, Formal analysis Search for more papers by this author Nejat K Egilmez Nejat K Egilmez Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Contribution: Data curation, Funding acquisition, Project administration Search for more papers by this author Huang-Ge Zhang Corresponding Author Huang-Ge Zhang [email protected] orcid.org/0000-0001-9665-9202 Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA Robley Rex Veterans Affairs Medical Center, Louisville, KY, USA Contribution: Conceptualization, Supervision, Funding acquisition, Validation, Investigation, Writing - original draft, Project administration, Writing - review & editing Search for more papers by this author Author Information Mukesh K Sriwastva1,†, Zhong-Bin Deng1,†, Bomei Wang2, Yun Teng1, Anil Kumar1, Kumaran Sundaram1, Jingyao Mu1, Chao Lei1, Gerald W Dryden1,3,4, Fangyi Xu1, Lifeng Zhang1, Jun Yan1, Xiang Zhang5, Juw Won Park5,6, Michael L Merchant7, Nejat K Egilmez1 and Huang-Ge Zhang *,1,3 1Department of Microbiology & Immunology, Brown Cancer Center, University of Louisville, Louisville, KY, USA 2Department of Translational Oncology, Genentech, San Francisco, California, USA 3Robley Rex Veterans Affairs Medical Center, Louisville, KY, USA 4Department of Pharmacology and Toxicology, University of Louisville, Louisville, KY, USA 5KBRIN Bioinformatics Core, University of Louisville, Louisville, KY, USA 6Department of Computer Engineering and Computer Science, University of Louisville, Louisville, KY, USA 7Kidney Disease Program and Clinical Proteomics Center, University of Louisville, Louisville, KY, USA † These authors contributed equally to this work *Corresponding author. Tel: +1 502 852 8623; E-mail: [email protected] EMBO Reports (2022)23:e53365https://doi.org/10.15252/embr.202153365 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Bark protects the tree against environmental insults. Here, we analyzed whether this defensive strategy could be utilized to broadly enhance protection against colitis. As a proof of concept, we show that exosome-like nanoparticles (MBELNs) derived from edible mulberry bark confer protection against colitis in a mouse model by promoting heat shock protein family A (Hsp70) member 8 (HSPA8)-mediated activation of the AhR signaling pathway. Activation of this pathway in intestinal epithelial cells leads to the induction of COP9 Constitutive Photomorphogenic Homolog Subunit 8 (COPS8). Utilizing a gut epithelium-specific knockout of COPS8, we demonstrate that COPS8 acts downstream of the AhR pathway and is required for the protective effect of MBELNs by inducing an array of anti-microbial peptides. Our results indicate that MBELNs represent an undescribed mode of inter-kingdom communication in the mammalian intestine through an AhR-COPS8-mediated anti-inflammatory pathway. These data suggest that inflammatory pathways in a microbiota-enriched intestinal environment are regulated by COPS8 and that edible plant-derived ELNs may hold the potential as new agents for the prevention and treatment of gut-related inflammatory disease. Synopsis Mulberry bark derived exosome-like nanoparticles (MBELNs) prevent gut inflammation via plant heat shock protein HSPA8-mediated activation of AhR/COPS8 pathways. Treatment with MBELNs promotes the restoration of gut microbiome homeostasis, ameliorating intestinal inflammatory pathologies. Mulberry bark derived exosome-like nanoparticles (MBELNs) prevent mouse colitis via the AhR/COPS8 pathway. Binding of MBELN-derived heat shock protein HSPA8 to AhR leads to the activation of AhR signaling. Activation of AhR leads to the induction of an array of anti-microbial peptides (AMPs) via COP9/COPS8. AhR/COPS8-dependent induction of AMPs inhibits intestinal inflammation and alters fecal gut microbiota composition. Introduction Developing a variety of avenues to deal with or to adapt to stresses such as changing environment, climate, lifestyle, or social structure is central to maintaining human health. Deficiency in or loss of strategies to deal with new or previous unmet changes or stresses can result in disease. For plants to remain healthy, they must develop more comprehensive strategies to deal with a higher frequency of changes and a more diversified variety of stresses in order to survive. Plant bark is considered an accumulation of several different outer layers of a woody plant and constitutes 10–20% of the weight of most woody plants (Loub et al, 1975; Vane et al, 2006) that protects the plant against numerous insults coming from desiccation, agents causing disease, and extreme temperatures. Whether these features can be utilized for improving human healthy has not been studied in detail. Recently, we (Mu et al, 2014) and others (Xiao et al, 2018) have identified exosome-like nanoparticles (ELNs) from tissues of edible plants. ELNs are naturally released, and they are taken up by host cells and subsequently communicate with ELN recipient cells, which is a biological hallmark of mammalian cell-derived exosomes. Unlike animal exosomes which are difficult to produce in large quantities, ELNs can easily be isolated and purified in large quantities. Therefore, in this study, we sought to identify the therapeutic factor(s) in ELNs, which may provide ELN recipient cells a strategy to deal with stress analogous to plant cells. Mulberry, a deciduous plant from the genus Morus (family Moraceae) that includes several species (most commonly Morus notabillis, Morus alba, and Morus rubra) is grown for several beneficial roles including fruit production, leaf production for silkworm feeding (Sanchez, 1999), its clinical efficacy in glucose metabolism (Asai et al, 2011), against untreated type 2 diabetes (Nakamura et al, 2011), and mild dyslipidemia (Aramwit et al, 2013), to yield bark for paper production and because of its multiple usage in traditional medicines (Asano et al, 1994; Kim et al, 1999; Chan et al, 2016). We selected the plant Morus notabillis for this study because of its widespread presence, therapeutic application, and the availability of the complete genome sequence (He et al, 2013). The aryl hydrocarbon receptor (AhR)-mediated signaling pathway plays a role in response to stress and a number of chemicals isolated from plants (Rothhammer & Quintana, 2019). There are a number of natural ligands from plant sources that have been shown to be effective in neurological disease, inhibiting tumor growth, lowering cholesterol, and having positive effects in other chronic illnesses (Hirano et al, 1995; Diplock et al, 1998; Datla et al, 2001; Kurowska & Manthey, 2004). These AhR agonists exert their function by AhR-mediated CYP1A1 activation, downregulation of nuclear factor kappa B (NF-kB)-mediated inflammatory signaling, and activation of inflammatory molecules (Singh et al, 2007; Sarkar et al, 2008; Choi et al, 2010; Potapovich et al, 2011). Whether edible plant bark-derived factors have an effect on AhR signaling is not known. Further, the molecular mediators and mechanisms governing the association between molecules from plants and the AhR signaling pathway in mammalian cells in general are still elusive. The purpose of this study was to determine whether edible plant bark-derived ELNs could be utilized to protect against colitis in a mouse model that results in numerous insults to the gut microbiome and the resulting metabolites. We thus tested whether a plant defensive strategy could be used to enhance protection against colitis in a mammalian model. We used mulberry bark-derived exosome-like nanoparticles (MBELNs) as a proof of concept to study the effect of MBELNs on gut epithelial AhR-mediated signaling in mice. MBELN-fed mice showed enhanced mucus barrier function. Moreover, we found that MBELN-derived HSPA8 is required for MBELN-mediated induction of the expression of AhR as well as activation of AhR. Further, activation of the AhR signaling pathway leads to induction of the expression of COP9/COPS8. The role of induced COPS8 was further demonstrated using intestinal specific COPS8 knockout (KO) mice, showing that MBELN-mediated protection of mice from dextran sulfate sodium (DSS)-induced colitis was abolished in COPS8 KO mice. Mechanistically, we show that MBELN treatment results in deneddylation of cullin 1 (CUL1). The COP9 signalosome inhibits the E3 ubiquitin ligase activity of Cullin-RING ubiquitin ligases (CRLs) by promoting the cleavage of neural precursor cell expressed developmentally downregulated protein 8 (NEDD8)-CUL1 conjugates (also conceptualized as deneddylation) (Lyapina et al, 2001). Our findings thus link plant communication with the mammalian kingdom via plant-derived exosome-like nanoparticle-mediated regulation of CUL1 deneddylation and the mammalian proteasome degradation machinery. Results MBELNs enhance the expression and activate the aryl hydrocarbon receptor (AhR)-mediated pathway We isolated exosome-like nanoparticles from mulberry bark (MBELNs) by differential centrifugation (Appendix Fig S1A). The sucrose-purified MBELNs had an average diameter of 151.3 ± 45.4 nm (Appendix Fig S1B and C) and showed exosome-like characteristics based on a bilayer structure and size revealed by electron microscopy (Appendix Fig S1D). Like other liposomes, the presence of a number of explicit lipid molecules (Appendix Fig S1E and F) and proteins (Appendix Fig S1G and Dataset EV1) was demonstrated by mass spectrometry (MS) analysis. The presence of RNA was confirmed by agarose gel electrophoresis with and without digestion by RNase. Isolated RNA was further analyzed using mRNA sequencing that confirmed the presence of several peculiar RNAs with critical roles in metabolic and anti-pathogenicity as well (Appendix Fig S1H and I and Dataset EV2). To evaluate the potential efficacy and use of MBELNs as an agent to improve gut healthiness, the toxicity and tropism were evaluated. MBELNs were orally administered to C57BL/6J mice (once daily for 15 days) at two different doses (2 × 109 and 1 × 1010 MBELNs/100 µl/dose/mouse/day) and mice rested for the next 15 days (no treatment) and were then humanely sacrificed on day 30. Mice showed no adverse effects including no significant changes in body weight (Appendix Fig S2A), skin rash, or abnormal fecal discharge during MBELN administration or follow-up. However, at the dose of 1 × 1010 MBELNs/mouse, mice had a slightly reduced body weight that was not significant; this group of mice did not show any other adverse changes. Mice did not show any abnormal effects regarding morphology of internal organs, gut tissue microscopic structure, blood cholesterol, triglycerides, or liver enzyme alanine transaminase (ALT), while liver enzyme aspartate transaminase (AST) was lower in the MBELN group, but still in a normal range (Appendix Fig S2B–D). The in vivo bio-distribution and trafficking of DiR-labeled MBELNs after oral administration was evaluated in mice using an Odyssey imaging system. Three hours (h) after a single oral administration of DiR-labeled MBELNs (10 × 109 particles/mouse), DiR fluorescent signals were predominantly detected in the duodenum–ileum of the small intestine, colon, and cecum. A small fraction of fluorescent signal was also observed in spleen, liver, lung, kidney, heart, and blood. The presence and intensity of the imaging signal indicated that DiR-labeled MBELNs were detectable up to 6 h after a single dose in blood, heart, liver, lung, kidney, and brain, while in the small intestine and colon tissue, it was detectable up to 12 h later. The signal was reduced over time and was not detectable at 24 h (Appendix Fig S2E and F). Confocal microscopy analysis demonstrated that 3 h after orally administering MBELNs, it was predominantly taken up by gut epithelial cells, Paneth cells (yellow arrow), and colon tissue. Additionally, in the spleen and liver, the MBELNs were predominantly present in F4/80+ macrophages (Appendix Fig S2G). Next, the effect of MBELNs on the genes expressed in colon tissue was further determined. MBELNs were orally administered to wild-type C57BL/6J mice for seven days and the expression of genes was profiled using cDNA array analysis. The results suggested that MBELN treatment has an effect on the genes expressed in colon tissue (Fig 1A). We noticed that the expression of AhR was increased due to MBELN treatment. Our recent work indicated that edible plant-derived exosomes regulate AhR-mediated signaling pathways in the intestinal epithelium (Teng et al, 2018). AhR is an important ligand-activated receptor molecule responding to endogenous or exogenous ligands, including plant-derived ligands, and plays a significant role in the host defense mechanism (Moura-Alves et al, 2014, 2019). To determine whether MBELNs can activate the AhR-mediated pathway, mouse Hepa1.1 cells, stably harboring an AhR responsive luciferase reporter construct, were incubated with vehicle, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD; 1 nM) as a positive control, or increasing concentrations of MBELNs (2.5 × 109, 5 × 109, 7.5 × 109, 10 × 109 particles/ml). Exposure to MBELNs resulted in a dose-dependent increase in luciferase expression. A significant 2-fold induction over vehicle treatment was observed at the lowest concentration of 2.5 × 109 particles/ml and a maximal 27-fold expression increase at 10 × 109 particles/ml. The data indicate that MBELNs are a more potent activator of the AhR pathway than the prototypical AhR agonist TCDD (Fig 1B). Intestinal epithelial cells are one of the major cell types targeted by MBELNs. Therefore, we further explored whether MBELNs affect activation of the AhR-mediated pathway in intestinal epithelial cells. C57BL/6 murine colon MC38 cells and human colon Caco2 cells were exposed to vehicle or MBELNs for 3 h. First, we found that MBELN treatment (5 × 109 particles/ml) increases levels of phosphorylated-AhR as well as total AhR in both mouse MC38 cells and human intestinal epithelial Caco2 cells (Fig 1C and Appendix Fig S2H). The induction of AhR expression was further demonstrated in colon epithelial tissue of C57BL/6J mice following 3 h of a single dose of oral administration of MBELNs (10 × 109 particles/mouse) (Fig 1D). Induction of AhR target genes, including Cytochrome P450, family 1, subfamily A, polypeptide 1 (CYP1A1), and Indoleamine 2,3-dioxygenase (IDO1), and corresponding proteins, was also observed in MBELN-treated MC38 cells, Caco2 cells and in C57BL/6J mouse colon epithelial tissue in vivo (Appendix Fig S2I and J). Figure 1. MBELNs activate AhR signaling A. Mice were orally administered with mulberry bark-derived exosome-like nanoparticles (MBELNs) (10 × 109 particles/100 µl/mouse) or phosphate-buffered saline (PBS) for 7 days. Heat map showing influence of MBELNs on colonic gene expression from three biological replicates. B. In vitro assessment of MBELN-dependent induction of aryl hydrocarbon receptor (AhR) promoter using HEPA1.1 cells (contain AhR responsive luciferase reporter construct). Data are mean ± SEM from three biological replicates. **P < 0.01, ***P < 0.001 using one-way ANOVA. C. Representative images showing expression of pAhR in MC38 cells and Caco2 cells treated with MBELNs from three biological replicates. Scale bar 20 μm. D. Western blot (top) and graphical representation of fold changes (bottom) for AhR in MC38 cells, Caco2 cells, and colon epithelial cells after treatment with MBELNs. Data are mean ± SEM of three biological replicates. *P < 0.05 using Student’s t-test. E. Fecal microbiota were analyzed following administration of MBELNs (10 × 109 particle/100 µl/dose/day/mouse) for 7 days to C57BL/6 mice. Alpha diversity (Shannon index) was calculated at the family level and is displayed as a bar-and-whiskers plot for each individual combination of control and MBELN treatment. The center line represents the median and the box encloses the 1st and 3rd quartiles (“hinges”). The upper and lower whiskers represent the furthermost points from the respective hinges, which are no more than 1.5 interquartile ranges from the hinge. The individual points are overlaid. Data are presented from five mice or biological replicates. F. Beta diversity analysis, biplots samples (points), and bacterial taxa at family level (axes) are simultaneously projected on the two-dimensional canonical axes (CA1 and CA2). Data are presented from five mice or biological replicates. G. Pictorial representation of dextran sulfate sodium (DSS; 2%)-induced colitis development in mice. H. Graph showing loss of weight following DSS-induced colitis with and without MBELN treatment. Data are mean ± SEM of seven biological replicates, **P < 0.01 using Mann–Whitney test. I. Representative image showing changes in colon morphology and length following DSS-induced colitis with concurrent treatment with MBELNs. J. Column graph showing changes in colon length. Data are mean ± SEM from seven biological replicates, **P < 0.01 using one-way ANOVA. K, L. Hematoxylin and eosin (HE) staining to show histological changes in colon tissue (left) and a graph showing severity score (right) based on histological data. Scale bar 200 μm. Data are mean ± SEM of seven biological replicates, **P < 0.01 using Student’s t-test. M. Enzyme-linked immunosorbent assay (ELISA) for interleukin (IL)-6 and IL-1β from colon tissue. Data are mean ± SEM from seven biological replicates, **P < 0.01 using one-way ANOVA. Source data are available online for this figure. Source Data for Figure 1 [embr202153365-sup-0003-SDataFig1.pdf] Download figure Download PowerPoint Diet can alter the composition of gut microbiota. Analysis of MBELN-related alterations in microbial community composition following a 7-day treatment at a family level showed an increase in bacterial species richness in the feces (Fig 1E). Beta diversity analysis demonstrated significant dissimilarities between microbiota populations (Fig 1F). MBELN treatment enhanced the bacterial communities of Firmicutes (Dehalobacteriaceae, Lachnospiraceae, Ruminococcaceae, Erysipelotrichaceae, and Mogibacteriaceae), Porphyromonadaceae, Prevotellaceae, Rikenellaceae, Paraprevotellaceae from Bacteroidetes, Proteobacteria (Pseudomonadaceae, Desulfovibrionaceae), and Verrucomicrobia (Verrucomicrobiaceae), while it reduced the community richness for Actinobacteria (Corynebacterium), Bacteroidetes (Bacteroidaceae, S24.7 and Odoribacteraceae), Firmicutes (Lactobacillaceae, Turicibacteraceae, and Clostridiaceae), Proteobacteria (Alcaligenaceae and Helicobacteraceae) and Tenericutes (Mycoplasmataceae) (Appendix Fig S3A). Next, we tested whether MBELNs could inhibit species-specific growth of bacteria. We found that MBELNs had species-specific growth inhibitory effects on virulent Listeria (L.) monocytogenes-EGD (Lis-EGD), while they did not affect the growth of Escherichia coli (E. coli), Porphyromonas gingivalis (PG), Streptococcus gordonii (SG), and non-virulent Listeria monocytogenes (Lis) (Appendix Fig S3B and C). We also noticed that MBELNs were able to inhibit the expression of bacterial mRNAs (Appendix Fig S3D; Dataset EV3) that are crucial for the pathogenesis of virulence and growth (Chatterjee et al, 2006; Toledo-Arana et al, 2009; Hamon et al, 2012). Next, we determined whether the protein complexes formed by a virulent strain of L. monocytogenes-EGD with MBELNs are different from the non-virulent strain of L. monocytogenes. We identified a unique protein profile of virulent L. monocytogenes-EGD that interacted with biotin-labeled MBELNs when compared to non-virulent L. monocytogenes (Appendix Fig S3E and F; Dataset EV4). The interacting proteins may contribute to the efficiency in uptake of virulent versus non-virulent strains (12.6 vs. 30.8% in non-virulent vs. virulent L. monocytogenes; Appendix Fig S3G). The phenotypes, including AhR activation and bacterial species-specific growth inhibition, were reproduced with MBELNs from different lots of mulberry bark harvested at different time points (summer, fall, winter, and spring). In addition, there was no difference on AhR induction in MC38 cells, suggesting that the therapeutic factors from MBELNs are not affected by seasonal variation or another factor (Fig EV1A). Click here to expand this figure. Figure EV1. MBELN-induced induction of AhR To test the reproducibility of mulberry bark-derived exosome-like nanoparticles (MBELN) collected during different seasons of the year, MBELNs were extracted in spring, summer, fall, and winter and used to treat MC38 cells to evaluate AhR expression. Data are mean ± SEM from three biological replicates per group. **P < 0.01 using one-way ANOVA. Heat map showing gene influences in crypts of villi in C57BL/6J mice. Data shown are from three technical replicates. Western blot for COP9/COP9 Constitutive Photomorphogenic Homolog Subunit 8 (COPS8) in MC38 cells following MBELN treatment. Data shown are from three biological replicates. mRNA expression of COPS8 in MC38 and after MBELN administration and C57BL/6J colon epithelial cells following MBELN administration for 7 days. Data are mean ± SEM from three biological replicates per group. **P < 0.01
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