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. 2025 Feb 28;34(1):20–33. doi: 10.5607/en25001

Sphingomonas Paucimobilis-derived Extracellular Vesicles Reverse Aβ-induced Dysregulation of Neurotrophic Factors, Mitochondrial Function, and Inflammatory Factors through MeCP2-mediated Mechanism

Eun-Hwa Lee 1,†, Hyejin Kwon 1,†, So-Young Park 1, Jin-Young Park 1, Jin-Hwan Hong 1, Jae-Won Paeng 2, Yoon-Keun Kim 2,*, Pyung-Lim Han 1,*
PMCID: PMC11919641  PMID: 40091636

Abstract

Recent studies have shown an increased abundance of Sphingomonas paucimobilis, an aerobic, Gram-negative bacterium with a distinctive cell envelope rich in glycosphingolipids, within the gut microbiome of individuals with Alzheimer Disease (AD). However, the fact that S. paucimobilis is a well-known pathogen associated with nosocomial infections presents a significant challenge in investigating whether its presence in the gut microbiome is detrimental or beneficial, particularly in the context of AD. This study examines the impact of S. paucimobilis-derived extracellular vesicles (Spa-EV) on Aβ-induced pathology in cellular and animal models of AD. Microarray analysis reveals that Spa-EV treatment modulates Aβ42-induced alterations in gene expression in both HT22 neuronal cells and BV2 microglia cells. Among the genes significantly affected by Spa-EV, notable examples include Bdnf, Nt3/4, and Trkb, which are key players of neurotrophic signaling; Pgc1α, an upstream regulator of mitochondrial biogenesis; Mecp2 and Sirt1, epigenetic factors that regulate numerous gene expressions; and Il1β, Tnfα, and Nfκb-p65, which are associated with neuroinflammation. Remarkably, Spa-EV effectively reverses Aβ42-induced alteration in the expression of these genes through the upregulation of Mecp2. Furthermore, administration of Spa-EV in Tg-APP/PS1 mice restores the reduced expression of neurotrophic factors, Pgc1α, MeCP2, and Sirt1, while suppressing the increased expression of proinflammatory genes in the brain. Our results indicate that Spa-EV has the potential to reverse Aβ-induced dysregulation of gene expression in neuronal and microglial cells. These alterations encompass those essential for neurotrophic signaling and neuronal plasticity, mitochondrial function, and the regulation of inflammatory processes.

Keywords: Sphingomonas, Aβ, MeCP2, PGC1α, NF-kB, Microglia

INTRODUCTION

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of Aβ plaque and neurofibrillary tangle in the brain, leading to a gradual decline in cognitive function and memory loss [1]. AD is caused by a complex interplay of genetic and non-genetic factors. AD accounts for 60% to 70% of all dementia cases [2], which is a significant burden for individuals with ageing [3]. Given the diverse causes and symptoms of AD, developing effective and varied strategies for prevention and treatment is crucial to address the growing disease burden associated with various factors in the aging population.

Recent studies have demonstrated profound changes in the gut microbiota composition of individuals with AD patients [4, 5]. Sphingomonas paucimobilis was elevated in the gut microflora of individuals with AD [6] and Parkinson disease [7], but decreased in those with autism spectrum disorder [8]. S. paucimobilis is an aerobic Gram-negative bacterium typically found in soil and plant roots [9, 10]. S. paucimobilis is a relatively uncommon but globally distributed pathogen that can cause nosocomial infections [10-13]. Gram-negative bacteria often cause serious infections and release lipopolysaccharides (endotoxins), triggering systemic inflammation and aggravating infection symptoms. The outer membrane of S. paucimobilis is composed of glycosphingolipids instead of lipopolysaccharides [14, 15]. While S. paucimobilis is found in the human gut microbiome, the impact of altered S. paucimobilis levels on the pathogenesis of AD or other brain diseases remains uncertain. Additionally, the potential for S. paucimobilis to cause nosocomial infections presents a challenge in investigating its potential benefits for brain health, especially in the context of AD.

Bacterial extracellular vesicle (EV) serves as key messengers in inter-kingdom communication and long-distance signaling [16, 17]. Bacterial EV exerts diverse effects, including mediating antibiotic resistance between microbial populations, and modulating immune responses in host cells [18-20]. Recently, it was reported that EV derived from the gram-positive probiotics Lactobacillus plantarum and Bacillus subtilis or EV from the gram-negative probiotic Akkermansia muciniphila counteract glucocorticoid-induced reductions in neurotrophic factor expression in an MeCP2- or Sirt1-dependent manner in HT22 cells and also reverse stress-induced decreases in neurotrophic factor expression in hippocampal neurons of adult mice [21, 22]. Moreover, Lactobacillus paracasei-derived EV reverse Aβ-induced transcriptional changes in neurotrophic factors and Aβ-induced pathogenesis in the brains of Tg-APP/PS1 mice [23]. These findings highlight the potential of EVs from probiotics may offer certain advantages beyond those provided by the probiotics themselves. It was recently reported that S. paucimobili derived EV reduces Ab plaque deposition and improves cognitive deficits Tg-APP/PS1 mice [24]. However, It remains unclear whether S. paucimobilis-derived EV exerts beneficial effects on the brain without inducing adverse consequences. In this study, we investigated how S. paucimobilis-derived EV induces molecular changes that may modulate Aβ-induced pathology in cellular and animal models of AD.

MATERIALS AND METHODS

Animals

Tg-APPswe/PS1dE9 mice (Tg-APP/PS1) were crossed with C57BL6×C3H hybrid mice as described previously [25, 26]. Mice were housed 3~4 animals per standard clear plastic cage in a temperature (23°C~24°C)- and humidity (50%~60%)-controlled environment under a 12 h light/dark cycle (lights on at 07:00~19:00 h). The animals had ad libitum access to water and food.

Genotyping of Tg-APP/PS1 mice was carried out using PCR of genomic DNA with the following primers: 5’-CTAGGCCACAGAATTGAAAGATCT-3’ and 5’-GTAGGTGGAAATTCTAGCATCATCC-3’ for WT (324 bp), 5’-AATAGAGAACGGCAGGAGCA-3’ and 5’-GCCATGAGGGCACTAATCAT-3’ for the PS1 gene (324/608 bp), and 5’-AGGACTGACCACTCGACCAG-3’ and 5’-CGGGGGTCTAGTTCTGCAT-3’ for the APP gene (324/350 bp).

Animals were handled in accordance with the animal care guidelines of Ewha Womans University. The experimental procedures involving EV treatment in Tg-APP/PS1 mice were approved by the Ewha Womans University Animal Care and Use Committee (IACUC 16-019).

Aβ42 treatment in cultured cells

HT22 hippocampal neuronal cells and BV2 microglia cells were cultured as described previously [26, 27]. HT22 cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM; LM001-05, Welgene Inc, Gyeongan-si, Republic of Korea) supplemented with 10% fetal bovine serum (FBS; FB02-500, Serum Source International, Charlotte, NC, USA) and 1% penicillin (20 units/ml)/streptomycin (20 mg/ml) (LS202-02, Welgene Inc.) in a humidified 37°C incubator supplied with 5% CO2. BV2 cells were maintained in DMEM supplemented with 5% FBS and 1% penicillin (20 units/ml)/streptomycin (20 mg/ml).

Aβ42 peptide (03112; Invitrogen, Camarillo, CA, USA) was dissolved in 5% DMSO to produce a 400 μM solution, which was divided into 10 μl aliquots and stored at -80°C until use. Each Aβ42 aliquot in DMSO was diluted to 10 μM in 400 ul of 1X PBS (137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, and 1.8 mM KH2PO4), which was then incubated at 4°C for 24 h with gentle rocking.

For treatment with Aβ42 or EVs, HT22 cells were seeded to 0.5×105 cells/well in a 24-well plate (SPL Life Science, Pocheon-si, Republic of Kora) for 24 h in DMEM containing 10% FBS and penicillin (20 units/ml)/streptomycin (20 mg/ml). BV2 cells were seeded to 1.0×105 cells/well in a 24-well plate for 24 h in DMEM containing 5% FBS and 1% penicillin/streptomycin. After washing, cells were exposed to Aβ42 (1 μM, final) or Aβ42 plus EVs (10 μg/ml, final) in DMEM containing 1% FBS, and no penicillin/streptomycin for 24 h and harvested for analyses.

siRNA transfection into cultured cells

siRNA transfection into HT22 cells was carried out as described previously [23, 28]. Briefly, HT22 cells plated to a density of 1.0×105 cells/well in a 6-well plate were grown in DMEM containing 10% FBS and 1% penicillin/streptomycin for 24 h. After washing with 1X PBS, siRNA transfection was carried out using Lipofectaime-2000 (13778-075; Invitrogen). Lipofectaime-2000 (9 μl) and 20 μM siRNA (3 μl) were separately diluted in 150 μl of Opti-MEM® Medium (31985070, Gibco, Thermo Fisher Scientific, Paisley, Scotland, UK), and mixed at a 1:1 ratio. After incubating for 5 min, 250 μl of the siRNA-Lipofectaime-2000 complex was gently dripped onto HT22 cells in 6-well plates, and the cells were incubated for 24 h. BV2 cells were seeded at a density of 2.0×105 cells per well in a 24-well plate and cultured in DMEM supplemented with 5% FBS and 1% penicillin/streptomycin for 24 hours. Lipofectaime-2000 (2.1 μl) and 20 μM siRNA (0.7 μl) were separately diluted in 35 μl of Opti-MEM® Medium (31985070, Gibco, Thermo Fisher Scientific, Paisley, Scotland, UK), and mixed at a 1:1 ratio. After incubating for 5 min, 62.5 μl of the siRNA-Lipofectaime-2000 complex was gently dripped onto BV2 cells in a 24-well plate, and the cells were incubated for 24 h. The final treatment dose was 20 μg of siRNA per well (or final concentration, 50 pM of siRNA). The siRNAs were resolved to 50 ng/μl in siRNA dilution buffer (B-002000-UB-100, Dharmacon, Lafayette, CO, USA).

Control siRNA (siCON, SN-1012), MeCP2-siRNA (#1385135; NM_001081979.2), Sirt1-siRNA (#93759; NM_001159589.2), Pgc-1α-siRNA (#19017; NM_008904.2), Nfκb p65-siRNA (#19697-1; NM_009045.4), and Nfκb p50-siRNA (#18033-1; NM_008689.2) were purchased from Bioneer Co. (Daejeon, Republic of Korea).

Preparation of EVs from bacterial cultures

Bacterial culture and EV preparation were carried out as described previously [23, 29]. In brief, Sphingomonas paucimobilis (NCTC 11030) was cultured in MRS broth (MBcell, KisanBio., Seoul, Republic of Korea) for 18 h at 37°C with gentle shaking (150 rpm). When the optical density of the culture reached 1.0 at 600 nm, the bacteria were pelleted by centrifugation at 10,000×g for 20 min, and the resulting supernatant was collected and passed through a 0.22-μm bottle-top filter (Corning, NY, USA) to remove remaining cells and cell debris.

The filtrate was concentrated with a MasterFlex pump system (Cole-Parmer, IL, USA) using a 100-kDa Pellicon 2 Cassette filter membrane (Merck Millipore, MA, USA) and subsequently passed through a 0.22-μm bottle-top filter. The resulting filtrate was centrifugated at 150,000×g for 3 h at 4°C; and EV pellets were obtained, washed, and resuspended in PBS (137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 1.8 mM KH2PO4). Protein concentrations were measured in the resuspended EV fractions using a BCA protein assay kit (Thermo Fisher Scientific, MA, USA). Collected EV were stored at -80°C until use.

Administration of Spa-EV to mice

Spa-EV were orally administered to Tg-APP/PS1 mice, similar to that described previously [21, 23]. Spa-EV were diluted in drinking water to a concentration of 15 μg/ml and was administered to mice at a dose of 2.27 mg/Kg/day (or 1.753×10^12 particles/Kg/day) on the indicated days. Spa-EV-containing bottles were freshly prepared every other day.

Quantitative real-time PCR

Quantitative real-time PCR (qPCR) was carried out as described previously [23, 28]. Briefly, HT22 cells were cultured in a 6-well plate and total RNA was isolated using TRI-zol solution (15596-018, Invitrogen). Hippocampal tissues were homogenized in TRI-zol solution using pellet pestles, and total RNA was isolated. Two μg of total RNA was converted to cDNA using a reverse transcriptase system (Promega, Madison, WI, USA).

The PCR was carried out using the CFX 96 Real-Time PCR System Detector (Bio-Rad Laboratories) in a 20 μl volume containing 4 μl of 1/8 diluted cDNA, 10 μl of 2X iQTM SYBR Green Supermix (Bio-Rad Laboratories, Foster City, CA, USA), and 1 μl each of 5 pmol/μl forward and reverse primers. Transcript levels were normalized relative to Gapdh and L32 levels.

The primers used in this study were: tBdnf (total form), forward 5’-TGGCTGACACTTTTGAGCAC-3’ and reverse 5’-GTTTGCGGCATCCAGGTAAT-3’; Creb1, forward 5’-TGGACAGCAGATTCTAGTG-3’ and reverse 5’-GGAGGACGCCATAACAAC-3’; G9a, forward 5’-CGCAACATCACCCATCTG-3’ and reverse 5’-TCATACCAGCATCGGATACT-3’; Hdac2, forward 5’- GGGACAGGCTTGGTTGTTTC-3’ and reverse 5’-GAGCATCAGCAATGGCAAGT-3’; Hif1a, forward 5’- TGAGCTTGCTCATCAGTTGC-3’ and reverse 5’- GCACCATCACAAAGCCATCT-3’; Kdm4a, forward 5’-GTCTGGCCTCTTCACTCAGT-3’ and reverse 5’- TACCATTCACGTCTGCTCCA-3’; MeCP2, forward 5’-ACAGCGGCGCTCCATTATC-3’ and reverse 5’-CCCAGTTACCGTGAAGTCAAAA-3’; Nqo, forward 5’-TGAAGGAGGCTGCTGTAGAG-3’ and reverse 5’-GTTCGGCCACAATATCTGGG-3’; Nrf1, forward 5’-CGTTACAGGGCGGTGAAATG-3’ and reverse 5’-ACTCCAGTAAGTGCTCCGAC-3’; Nrf2, forward 5’-GTTGCCCACATTCCCAAACA-3’ and reverse 5’-CTGATGAGGGGCAGTGAAGA-3’; Nt3, forward 5’-TACTACGGCAACAGAGACG-3’ and reverse 5’-GTTGCCCACATAATCCTCC-3’; Nt4/5, forward 5’-AGCGTTGCCTAGGAATACAGC-3’ and reverse 5’-GGTCATGTTGGATGGGAGGTATC-3’; Pgc1a, forward 5’-CCTCTTTGCCCAGATCTTCCT-3’ and reverse 5’-GTGAGAACCGCTAGCAAGTT-3’; Setdb1, forward 5’-GGTGGTTGAAGAGCTGGGTA-3’ and reverse 5’-TCACTTCCCTGGATGCATCA-3’; Sirt1, forward 5’-GATCCTTCAGTGTCATGGTTC-3’ and reverse 5’-ATGGCAAGTGGCTCATCA-3’; Sirt5, forward 5’-ATCGCAAGGCTGGCACCAAGAA-3’ and reverse 5’-CTAAAGCTGGGC AGATCGGACT-3’; Sirt7, forward 5’-CTGGAGATTCCTGTCTACAACCG-3’ and reverse 5’- AGTGACTTCCTACTGTGGCTGC-3’; Suv39h1, forward 5’-TGGTTAAGTGGCGTGGGTAT-3’ and reverse 5’- TTGTTCCCAACGCTGAAGTG-3’; Tfam, forward 5’-GCATCCCCTCGTCTATCAGT-3’ and reverse 5’- CACAGGGCTGCAATTTTCCT-3’; TrkB, forward 5’-AAGGACTTTCATCGGGAAGCTG-3’ and reverse 5’-TCGCCCTCCACACAGACAC-3’; Vdac, forward 5’- AGTGACCCAGAGCAACTTCGCA-3’ and reverse 5’-CAGGCGAGATTGACAGCAGTCT-3’; Vegfa, forward 5’- GCAGGCTGCTGTAACGATGAA-3’ and reverse 5’- TTTGATCCGCATGATCTGCAT-3’; Nfκb_p50, forward 5’-GGGAAGCTGTCTTTGCTGAG-3’ and reverse 5’- GTAGCAGCATTAGCGGGAAG-3’; Nfκb_p65, 5’-TCAATGGCTACACAGGACCA-3’ and reverse 5’-GGCAGAGGTCAGCCTCATAG-3’; Tnfα, forward 5’- TGTACGGTTGTTGGTCTGGA-3’ and reverse 5’-TGGCCTGTTTTTGGAGTAGG-3’; IL1β, 5’-CAGGCAGGCAGTATCACTCA-3’ and reverse 5’- TGTCCTCATCCTGGAAGGTC-3’; iNos, 5’-TCAGGTGCCCTCTAGCACTT-3’ and reverse 5’-CTGAGGCGACAGAAGGTAGG-3’; Gapdh, forward 5’-AGAAGGTGGTGAAGCAGGCATC-3’ and reverse 5’-CGAAGGTGGAAGA GTGGGAGTTG-3’; and L32, forward 5’-GCTGCCATCTGTTTTACGG-3’ and reverse 5’-TGACTGGTGCCTGATGAACT-3’.

Microarray analysis

Microarray analysis was carried out as described previously [23, 30]. HT22 or BV2 cells were plated at a density of 1.0×105 cells/well in a 6-well plate. After 24 h, the cells were treated with Aβ42 (1 μM, final) or Aβ42 plus EV (10 μg/ml, final) and incubated for an additional 24 h. Total RNA was isolated using the RNeasy Mini Kit (Qiagen, Hilden, Germany). Macrogen Inc. (Seoul, South Korea) was requested to carry out GeneChip hybridization and collect raw data, including signaling reading of the internal quality control probes and extraction of the scanned raw data, as described below. Briefly, the purified RNAs were quantified using an Agilent Bioanalyzer 2100 Expert (Agilent Technologies, Palo Alto, CA, USA). Purified total RNA (400 ng) with high-quality 28S/18S rRNA (1.8~2.0) and A260/280 (1.8~1.9) ratios was converted to first- and second-strand cRNA, and then to biotin-labeled cRNA. The biotin-labeled cRNAs (7.5 µg) were fragmented by heating to 94°C for 35 min. Each of the fragmented biotin-labeled cRNA samples (6.0 µg) was hybridized to a GeneChipTM Mouse Gene 2.0 ST Array, representing 33,793 mouse gene transcripts. The hybridized array signals were amplified with Amersham Fluorolink streptavidin-Cy3 (GE Healthcare Bio-Sciences, Little Chalfont, UK) and were scanned using GeneChip® HT Scanner and AGCC software (Affymetrix GeneChip® Command Console, Version 3.2.2). Microarray signals were converted into log2 scale values and normalized using a robust multi-array average (RMA) method implemented in Affymetrix® Power Tools (APT). The false discovery rate (FDR) was controlled by adjusting the p value using the Benjamini-Hochberg algorithm. The log2 values of microarray data were used to account for the differences in the expression levels.

Gene Ontology enrichment analyses

Microarray signals were analyzed to identify differentially expressed genes between comparison groups using the limma package in R [31] (https://www.bioconductor.org/packages/release/bioc/html/limma.html) Volcano plots were generated using 33,793 microarray signal values to visualize differential expression, with log2 fold-change for the x-axis and -log10 (p-value) for the y-axis, comparing the two experimental groups. Microarray signal values were also analyzed using a Rank-Rank Hypergeometric Overlap (RRHO) geographic tool (http://systems.crump.ucla.edu/rankrank/). A RRHO map was constructed using the -log10 (p-value), as described previously [23, 32]. Genes that were up- or downregulated by Aβ and whose expression was reversed by Spa-EV were then selected based on the STRING database [33] (http://string-db.org) followed by selecting top 30% ranked genes based on their log2 fold-change values.

Identified genes were grouped into functional clusters by serial k-means clustering and determined whether each cluster contained genes for biological process, molecular function or cellular components using STRING database (http://string-db.org) and the ShinyGO [34] (http://bioinformatics.sdstate.edu/go/) tools.

Statistical analysis

Two-sample comparisons were carried out using Student’s t-test, and multiple comparisons were performed using one-way ANOVA followed by the Newman-Keuls post hoc test or using two-way ANOVA or two-way repeated measures ANOVA followed by the Bonferroni post hoc test. All data are presented as mean±SEM, and statistical significance was accepted at the 5% level.

RESULTS

Spa-EV counteracted Aβ42-induced altered expression of genes in HT22 cells

Microarray analysis revealed that Aβ42 induced substantial changes in gene expression in HT22 cells, with 45.0% of the 33,793 total transcripts being up- or downregulated by more than 1.1-fold. Notably, Spa-EV reversed the expression of 49.7% of Aβ42-downregulated genes and 57.5% of Aβ42-upregulated genes by more than 1.1-fold (Fig. 1A). An independent approach using Rank-Rank Hypergeometric Overlap (RRHO) analysis further corroborated Spa-EV's ability to reverse Aβ42-induced gene expression changes. Among the total of 27,580 independent transcript signals, 38.5% (10,632 transcripts; Quadrant A) were upregulated and 31.6% (8,707 transcripts; Quadrant D) were downregulated by Aβ42, and their altered expressions were reversed by Spa-EV. Conversely, 16.3% (4,495 transcripts; Quadrant C) and 13.6% (3,746 transcripts; Quadrant B) were, respectively, up- and downregulated by Aβ42, with their altered expressions were further changed by Spa-EV in the same direction as Aβ42 (Fig. 1B~D).

Fig. 1.

Fig. 1

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Microarray analysis revealed Spa-EV's ability to reverse Aβ42-induced alterations in gene expression in HT22 cells. (A) Volcano plots of differentially expressed transcripts between comparison groups, with log2 fold-change on the x-axis and –log10(p-value) on the y-axis. (B~D) Gene expression patterns induced by Aβ42 and Spa-EV (B). RRHO map with Aβ42-induced gene expression changes (CON vs. Aβ42) on the x-axis and Spa-EV effects on Aβ42-induced changes (Aβ42 vs. Aβ42+Spa-EV) on the y-axis (C). The numbers of transcript signals (%) in each quadrant (D). (E~H) Procedure for selecting top-30% ranked genes in each quadrant (E), and heatmaps of their expression patterns (F). Functional clustering and distribution of the selected genes in each quadrant (G) and the selected clusters with distinct biological processes (H). (I, J) Cluster #6 of Quadrant D, enriched in genes related to transcription, biosynthetic pathways, and other cellular functions (I). The interaction network (J) illustrating the relationships among genes within the biological processes (highlighted in red). (K, L) The expression patterns of 106 genes classified as “regulation of transcription” within Cluster 6 (K). GO annotation of these genes based on Molecular Function identified 30 genes involved in “signaling receptor binding” (highlighted in red). Volcano plotting of 30 selected genes by log2 fold-change and –log10(p-value) (L).

We selected the top 30% ranked genes within each quadrant: 1,853 in Quadrant A, 1,946 in Quadrant D, 877 in Quadrant C, and 668 in Quadrant B. Heatmaps visualized the Aβ42- and Spa-EV-induced gene expression changes of selected genes (Fig. 1E, F). Serial k-means clustering of the top 30% ranked genes in each quadrant identified distinct biological functional groups, as summarized in Fig. 1G, H. Further analysis focused on genes in Quadrants A and D.

Quadrant D, which included genes downregulated by Aβ42 but upregulated by Spa-EV, could be grouped into 10 distinct clusters (Fig. 1H), including nervous system development and neurogenesis, RNA processing and ribosome biogenesis, vesicle-mediated transport, and tissue morphogenesis and cell migration. Remarkably, cluster #6 (190 genes) contained genes for transcription/epigenetic regulation (Mecp2, Sirt1, Sirt6, Hdac4, Hdac7, and kdm4a) and mitochondrial function (Pgc1α Nqo1, and Vdac) (Fig. 1H~L). Cluster #10 (106 genes) was enriched in genes regulating “tissue morphogenesis and cell migration”, including Bdnf, Ngfr, Vegf, Nrg1, Epha2, and Rhoa (Supplemental Fig. S1A~D).

Quadrant A, which included genes upregulated by Aβ42 but downregulated by Spa-EV, could be grouped into 8 functional clusters (Fig. 1H), including RNA processing and ribosome biogenesis, peptide signaling and cell surface receptor signaling, and transmembrane transport, Cluster #8 (180 genes) demonstrated genes involved in immune response to external biotic stimulus, including those for cytokines (Il1b, Hmgb1, and Tgfb) and chemokines (Cxcl1, Cxcl13, Ccl1, and Ccl4) (Supplemental Fig. S1E~H).

Mecp2 is a key player mediating Spa-EV's restoring effects on Aβ42-induced gene expression changes in HT22 cells

To validate the microarray data, we conducted further in vitro and in vivo studies on Spa-EV’s effects on Aβ42-induced changes. HT22 cells treated with Aβ42 (1 μM) exhibited a marked decrease in the expression of Brain derived neurotrophic factor (Bdnf), Neurotrophin 3 (Nt3), Neurotrophin 4/5 (Nt4/5), and Trkb. Conversely, Spa-EV (10 μg/ml) treatment effectively reversed the Aβ42-induced downregulation of Bdnf, Nt4/5, and Trkb, but not Nt3 (Fig. 2A). Aβ42 treatment also increased the expression of the histone deacetylase (HDAC) Hdac2, while reducing Sirt1. Conversely, Spa-EV treatment reversed the altered expression of these genes (Fig. 2B).

Fig. 2.

Fig. 2

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Spa-EV reversed Aβ42-indcued altered expression of neurotrophic factors, Trkb, and epigenetic factors in HT22 cells. (A~D) Expression levels of total Bdnf (tBdnf), Nt3, Nt4/5, and TrkB (A, C); Hdac2, Sirt1, and Mecp2 (B, D) in HT22 cells treated with Aβ42, Aβ42 plus Spa-EV, and Aβ42 plus Spa-EV and siRNA-Mecp2 (A, B) or siRNA-Sirt1 (C, D). siRNA-mediated knockdown Mecp2 (A, left panel) of Sirt1 (C, left panel). Con, siRNA-control. Aβ42, 1 μM; Spa-EV, 10 μg/ml. (E) Expression levels of Hif1α, Pgc1α, Nrf1, Nrf2, and Vdac in HT22 cells (CON), HT22 cells treated with Aβ42 (Aβ), Aβ42 plus Spa-EV (Aβ+Spa-EV), and Aβ42 plus Spa-EV and siRNA-Mecp2 (Aβ+Spa-EV+si-Mecp2) or siRNA-Sirt1 (Aβ+Spa-EV+si-Sirt1). siRNA-mediated knockdown of Mecp2 and Sirt1 (left panel). Data are presented as mean±SEM (n=8 each). *p<0.05; **p<0.01 (Student t-test; One-way ANOVA or Two-way ANOVA followed by post hoc test).

We then investigated the role of the epigenetic factors MeCP2 and Sirt1 in Spa-EV’s restoring effects. siRNA-mediated Mecp2 knockdown blocked the Spa-EV-induced upregulation of Bdnf, Nt4/5, and Trkb in Aβ42-treated HT22 cells. Mecp2 knockdown also abolished the Spa-EV-induced upregulation of Sirt1, while reversing the Spa-EV-induced downregulation of Hdac2 (Fig. 2A, B). Similarly, Sirt1 knockdown blocked the Spa-EV-induced upregulation of Bdnf, Nt4/5, and Trkb in Aβ42-treated HT22 cells. Sirt1 knockdown also inhibited the Spa-EV-induced upregulation of Mecp2 and downregulation of Hdac2 (Fig. 2C, D). These results suggest that Spa-EV counteracts Aβ42-induced alterations in expression of neurotrophic factors and Trkb, primarily through MeCP2 and Sirt1.

Regarding the microarray data on genes regulating mitochondria and related function (Fig. 1H~L), we examined Spa-EV effects genes regulating mitochondria and related function. RT-PCR analysis indicated that Aβ42 treatment upregulated Hif1α and downregulated Pgc1α, Nrf1, Nrf2, and Vdac in HT22 cells. Conversely, Spa-EV treatment counteracted the Aβ42-induced upregulation of Hif1α and the downregulation of Pgc1α, Nrf1, Nrf2, and Vdac (Fig. 2E). siRNA-mediated Mecp2 knockdown completely abolished the Spa-EV effects on Aβ42-induced changes in the expression of Hif1α, Pgc1α, Nrf1, and Vdac. Sirt1 knockdown partially abrogated Spa-EV effects on Hif1α, Pgc1α, Nrf1, Nrf2, and Vdac (Fig. 2N, O). These results suggest that MeCP2, primarily, and Sirt1, to some extent, mediate Spa-EV’s effects on the expression of these genes.

Spa-EV treatment restored the decreased expression of neurotrophic factors, Trkb, and Pgc1a, and Mecp2 in the hippocampus of Tg-APP/PS1 mice

Tg-APP/PS1 mice exhibited decreased levels of Bdnf, Nt3, Nt4/5, Vegfa, and Trkb in the hippocampus compared to wildtype mice. In contrast, Tg-APP/PS1 mice treated with Spa-EV showed increased levels of Bdnf, Nt3, Nt4/5, Vegfa, and Trkb compared to untreated Tg-APP/PS1 mice (Fig. 3A, B).

Fig. 3.

Fig. 3

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Spa-EV treatment reversed the downregulation of neurotrophic factors and the epigenetic factors MeCP2 and Sirt1 in the hippocampus of Tg-APP/PS1 mice. (A) Experimental design. Tg-APP/PS1 mice were administered Spa-EV (2.27 mg/Kg/day) daily for 4 weeks, beginning at 6.5 months of age. WT, wildtype mice; Tg, Tg-APP/PS1 mice; Tg+Spa-EV, Tg-APP/PS1 mice treated with Spa-EV. Arrow, tissue preparation. (B~E) Expression levels of tBdnf, Nt3, Nt4/5, Vegfa, and Trkb (B); Hdac2, Sirt1, Sirt5, Sirt7, Kdm4a, G9a, Setdb1, and Suv39h1 (C); and Mecp2 and Creb1 (D), and Hif1α, Pgc1α, Nrf1, Nrf2, Tfam, and Nqo1 (E) in the hippocampus of WT, Tg, and Tg+Spa-EV. n=8 animals per group. (F, K) Photomicrographs showing MeCP2 (F) and Sirt1 (G) expression in CA1 and CA3 pyramidal neurons. Quantification of MeCP2 (H, I) and Sirt1 (J, K) expression levels in WT, Tg, and Tg+Spa-EV. n=7~8 animals. Scale bars, 100 µm. Data are presented as mean±SEM. *p<0.05; **p<0.01 (One-way ANOVA followed by Newman-Keuls post hoc test).

Tg-APP/PS1 mice showed increased expression of Hdac2, G9a, and Suv39h1, and decreased expression of Sirt1, Sirt5, Sirt7, KDM4a, Mecp2, and Creb1 compared to wildtype controls. In contrast, Tg-APP/PS1 mice treated with Spa-EV displayed reduced expression of Hdac2 and G9a, and enhanced expression of Sirt1, Sirt5, Sirt7, Suv39h1, Mecp2, and Creb1 compared to Tg-APP/PS1 mice (Fig. 3C, D).

Tg-APP/PS1 mice exhibited also increased expression of Hif1α, and decreased expression of Pgc1α, Nrf1, Nrf2, and Vdac in the hippocampus compared to wildtype mice. Conversely, Tg-APP/PS1 mice treated with Spa-EV showed reduced expression of Hif1α and increased expression of Pgc1α, Nrf1, Nrf2, and Vdac compared to Tg-APP/PS1 mice (Fig. 3E).

Immunohistochemical analysis revealed that Tg-APP/PS1 mice had decreased expression of MeCP2 and Sirt1 in the pyramidal neurons in CA1 and CA3 regions compared to wildtype mice. Conversely, Tg-APP/PS1 mice treated with Spa-EV showed increased expression of MeCP2 and Sirt1 compared to untreated Tg-APP/PS1 mice (Fig. 3F~K). Collectively, these results suggest that Spa-EV can restore the expression of genes regulating neurotrophic function and mitochondrial function, both in vitro and in vivo.

Spa-EV treatment suppressed Aβ42-induced upregulation of proinflammatory genes in BV2 cells and in the hippocampus of Tg-APP/PS1 mice

Next, we investigated whether “bacteria-derived Spa-EV” has pro-inflammatory or anti-inflammatory effects in microglial cells. Microarray analysis showed that Spa-EV reversed Aβ42-induced gene expression changes in BV2 cells, similar to its effects in HT22 cells. Spa-EV upregulated the expression of 42.3% of Aβ42-downregulated genes and downregulated the expression of 56.4% of Aβ42-upregulated genes by more than 1.1-fold (Fig. 4A). An independent approach using RRHO mapping further supported Spa-EV’s ability to counteract the Aβ42-induced alterations. Among the total 27,728 transcript signals identified as independent ones, 25.6% (7,106 transcripts; Quadrant A) were upregulated and 35.1% (9,727 transcripts; Quadrant D) were downregulated by Aβ42, and their altered expressions were reversed by Spa-EV. Conversely, 19.8% (5,479 transcripts; Quadrant C) and 19.5% (5,416 transcripts; Quadrant B) were, respectively, up- and downregulated by Aβ42, while Spa-EV potentiated their altered expression in the same direction (Fig. 4B~D).

Fig. 4.

Fig. 4

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Microarray data showing notable reversal of Aβ42-induced gene expression changes by Spa-EV in BV2 cells. (A) Volcano plots of differentially expressed transcripts between comparison groups, with log2fold-change on the x-axis and –log10(p-value) on the y-axis. (B~D) Gene expression patterns induced by Aβ42 and Spa-EV (B). Aβ42-induced gene expression changes (CON vs. Aβ42) and Spa-EV effects on Aβ42-induced changes (Aβ42 vs. Aβ42+Spa-EV) (C). The numbers of transcript signals (%) in each quadrant (D). (E~H) Procedure for selecting top-30% ranked genes in each quadrant (E), and heatmaps of their expression patterns (F). Functional clustering and distribution of the selected genes in each quadrant (G) and the selected clusters with distinct biological processes (H). (I, J) Cluster #2 of Quadrant A, encompassing genes involved in ‘immune cell response and neuroinflammation’ (I). The interaction network (J) among genes within the biological processes marked in blue. (K, L) Heatmaps illustrating the expression of 148 genes classified as 'immune system response’ in cluster #2 (K). GO analysis of these genes based on Molecular Function identified 35 genes with high interaction (marked in blue). Volcano plots showing the distribution of 35 selected genes by log2fold-change and –log10(p-value) (L).

For further analysis, we selected the top-30% ranked genes within each quadrant: 1,244 in Quadrant A, 1,974 in Quadrant D, 1,018 in Quadrant C, and 1,218 in Quadrant B. Heatmaps of these genes illustrated the dramatic reversal of Aβ42-induced gene expression changes by Spa-EV (Fig. 4E, F). Serial k-means clustering revealed distinct biological functional groups among the top-30% ranked genes in each quadrant, which were summarized in Fig. 4G, H. Further analysis was focused on the genes in Quadrants A and D.

Quadrant A, which included genes upregulated by Aβ42 but downregulated by Spa-EV, could be grouped into 5 functional clusters, including protein targeting and sorting, regulation of immune system process, and vesicle-mediated transport and cell-cell signaling. Clusters #2 (263 genes) contained genes involved in microglia response to external stimuli and neuroinflammation, such as IL-1β, Tnfα, Nos2 (iNos), Nfkb1(Nfkb, p50), Rela(Nfkb, p65), CD40, Cxcl10, Mmp14, Fas, Nedd4, Stat3, and cMyc (Fig. 4I~L).

Quadrant D, which included genes downregulated by Aβ42 but upregulated by Spa-EV, were categorized into 10 functional clusters, including cell projection organization and morphogenesis, cell surface receptor signaling and immune response, and none coding RNA and RNA processing (Fig. 4H, I). Notably, clusters #4 (224 genes) contained genes for epigenetic and transcription factors, including Hdac2, Hdac4, Stat5, Runx2, Dnmt3a, Cebpa, Nfatc1, Rb1, Carm1, Trim24, and Nr4a1. Clusters #5 (213 genes) contained genes for chromatin organization and cell cycle process, including Stag3, Msh2, Tada2a, Cbx1, Hmgn5, H1f2, Smarcad1, Suv39h2, Macroh2a1, L3mbtl3, and Scmh1 (Fig. 4H, I, Supplemental Fig. S2).

To validate the microarray data on immune response and neuroinflammation, we conducted further in vitro and in vivo studies. Real-time PCR analysis confirmed that Spa-EV treatment in BV2 cells reversed Aβ42-induced changes of Nfkb_p50, Nfkb_p65, Tnfα, IL-1β, Nos2(iNos), and Mecp2 expression (Fig. 5A). siRNA-mediated Mecp2 downregulation increased the expression of Nfkb_p50, Nfkb_p65, Tnfα, and IL-1β (Fig. 5B). siRNA-mediated Nfkb_p50 downregulation blocked Aβ42-induced changes of Nfkb_p65 and Mecp2, but not Tnfα and IL-1β (Fig. 5C). In contrast, Nfkb_p65 downregulation did not block Aβ42-induced upregulation of Nfkb_p50 and Tnfα and IL-1β, although it suppressed Aβ42-induced downregulation of Mecp2 (Fig. 5D). These results suggest that Mecp2 is a key player in regulating Spa-EV effects on Aβ42-induced proinflammatory responses in microglia.

Fig. 5.

Fig. 5

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Spa-EV treatment reduced the expression of proinflammatory factors in the brain of Tg-APP/PS1 mice. (A) Expression levels of Nfkb_p50, Nfkb_p65, Tnfa, IL-1b, iNos, and Mecp2 in BV2 cells treated with Aβ42 (1 μM, final) or Aβ42 plus Spa-EV (10 μg/ml, final). (B) Expression levels of Nfkb_p50, Nfkb_p65, Tnfa, and IL-1b in BV2 cells transfected with siRNA-Mecp2. siRNA-mediated Mecp2 knockdown (left panel). siMecp2, siRNA-Mecp2. Con, siRNA-control. (C) Expression levels of Nfkb_p65, Tnfa, IL-1b, and Mecp2 in BV2 cells treated with Aβ42 (1 μM, final) or Aβ42 (1 μM, final) plus siRNA-Nfkb_p50. siRNA-mediated Nfkb_p50 knockdown (left panel). siNfkb_p50, siRNA- Nfkb_p50. Con, siRNA-control. (D) Expression levels of Nfkb_p50, Tnfa, IL-1b, and Mecp2 in BV2 cells treated with Aβ42 (1 μM, final) or Aβ42 (1 μM, final) plus siRNA-Nfkb_p65. siRNA-mediated Nfkb_p65 knockdown (left panel). siNfkb_p65, siRNA- Nfkb_p65. Con, siRNA-control. (E~H) Photomicrographs showing the anti-Iba1-stained parietal cortex (pacx), hippocampus (hp), and piriform cortex (piricx) (E) of Tg-APP/PS1 (Tg) and Tg-APP/PS1 mice treated with Spa-EV (Tg+Spa-EV). Higher magnification of the parietal cortex (E, low panels) of the indicated groups. Quantification of total fluorescent intensity (F), total area (G), and number (H) of Iba1 positive cells with threshold intensity cut-off in the parietal cortex, hippocampus, and piriform cortex of the indicated groups. Data are presented as mean±SEM (n=6~9). *p<0.05; **p<0.01 (One-way ANOVA followed by Newman-Keuls post hoc test, and two-way ANOVA followed by Bonferroni post hoc test)

Immunohistochemical analysis revealed significantly increased levels of Iba-1 staining in the parietal cortex, hippocampus, and piriform cortex of Tg-APP/PS1 mice compared to wild-type controls. Notably, Spa-EV treatment in Tg-APP/PS1 mice significantly, but modestly, reduced Iba-1 staining levels compared to untreated Tg-APP/PS1 mice (Fig. 5E~H). Overall, these results suggest that Spa-EV can reverse Aβ42-induced upregulation of pro-inflammatory genes both in vitro and in vivo.

DISCUSSION

Spa-EV treatment restored the reduced expression of neurotrophic factors, Pgc1α, MeCP2, and Sirt1, and suppresses the increased expression of proinflammatory genes in cultured neural cells (Fig. 1, 2, 4, Supplementary Fig. S1, S2), and also in the brain of Tg-APP/PS1 mice (Fig. 3, 5). These in vitro and in vivo findings raise following interacted issues regarding the therapeutic effects of Spa-EV on Aβ pathology.

First, Spa-EV exerts profound effects on gene expression in both HT22 neuronal cells and BV2 microglia, as demonstrated by in vitro studies using microarray and RT-PCR analysis (Fig. 1, 2, 4, Supplementary Fig. S1, S2). Thus, Spa-EV has an ability to directly influence cellular function by modulating the transcriptional system.

Second, microarray data indicated that among over 27,500 independent transcript signals, Spa-EV reversed the expression of approximately 50% of Aβ42-induced upregulated or down-regulated genes by more than 1.1-fold in both HT22 and BV2 cells (Fig. 1, 4, Supplementary Fig. S1, S2). Thus, Spa-EV exerted antagonistic activity, preventing Aβ42-driven gene expression alterations. We demonstrated that Spa-EV’s effects are, at least in part, mediated by upregulation of Mecp2 and Sirt1 expression, although further research is needed to fully elucidate the underlying mechanisms by which Spa-EV regulates Mecp2 and Sirt1 expression, and which components in Spa-EV produce such effects.

Third, the in vitro cell data on Spa-EV effects, including RT-PCR and microarray analyses, are remarkably consistent with the in vivo data observed after Spa-EV administration in Tg-APP/PS1 mice. As demonstrated, Spa-EV upregulated the expression of neurotrophic factors (e.g., Bdnf and Nt4/5) and TrkB, along with key genes regulating mitochondrial function like Pgc1α and Vdac in HT22 cells (Fig. 1~3, Supplementary Fig. S1). Similar, but not identical, transcriptional effects were also observed in HT22 cells treated with EVs from Lactobacillus paracasei, Lactobacillus plantarum, and Akkermansia muciniphila [21-23]. Furthermore, fluorescent-labeled Spa-EV was detected in the brain after 24 hours [24]. These results suggest that administered Spa-EV likely reaches the brain and directly acts on brain cells, although further research is warranted to confirm this possibility.

Forth, “bacteria-derived Spa-EV” suppressed the enhanced expression of neuroinflammatory regulatory factors such as IL-1β, TNF-α, NF-κB p50, and NF-κB p65 in BV2 cells and in the brain of Tg-APP/PS1 mice (Fig. 4, 5, Supplementary Fig. S2). These results indicate that although Spa-EV is derived from a gut bacterium potentially pathogenic at a certain condition, Spa-derived EV is anti-inflammatory, rather than not proinflammatory.

Fifth, Spa-EV reversed the altered expression of genes regulating mitochondrial function, including Pgc1α, Nrf1, Nrf2, Hif1α, and Vdac in Aβ42-treated HT22 cells and in the brains of Tg-APP/PS1 mice (Fig. 2, 3). Pgc1α, Nrf1, Nrf2, and Hif1α are transcriptional factors that regulate energy metabolism and mitochondrial biogenesis [35-37]. Spa-EV-induced alterations in Nrf1, Nrf2, and Vdac were mediated by the upregulation of Mecp2 and Sirt1 in HT22 cells (Fig. 2, 3). These results suggest that Spa-EV has an impact on the energy metabolism and biosynthetic pathways in brain cells by restoring the altered expression of genes regulating mitochondrial function in the brain of Tg-APP/PS1 mice.

Microglia play a critical role in regulating Aβ pathology in AD brains. Moderately activated microglia can exert phagocytic clearance of Aβ. Under pathological conditions such as excessive Aβ accumulation, microglia are overactivated and release high levels of reactive oxygen species, nitric oxide, and proinflammatory cytokines, which are cytotoxic to or impair normal function of neural cells [38, 39]. Spa-EV-induced transcriptional changes (Fig. 4, 5, Supplementary Fig. S2) may help microglia mitigate Aβ pathology in Tg-APP/PS1 mice. This study demonstrates Spa-EV has an ability to counteract Aβ-induced transcriptional changes in the express of genes associated with normal neuronal function, microglial cell’s activity, and Aβ-induced pathology in Tg-APP/PS1 mice. While the exact composition of neuroactive components in Spa-EV remains to be determined, further research is necessary to comprehensively evaluate the utility of the S. paucimobilis bacterium itself compared to Spa-EV for AD treatment.

Supplemental Materials

en-34-1-20-supple.pdf (15.2MB, pdf)

ACKNOWLEDGEMENTS

This study was supported partly by a grant (RS-2022-NR067846) for PLH, a grant (RS-2022-NR075314) for EHL from the Ministry of Science, ICT and Future Planning, Republic of Korea, a grant for PLH from MD Healthcare Inc., and a grant (RS-2022-NR072430) for JYP from the Ministry of Education, Republic of Korea.

References

  • 1.Breijyeh Z, Karaman R. Comprehensive review on Alzheimer's disease: causes and treatment. Molecules. 2020;25:5789. doi: 10.3390/molecules25245789. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Scheltens P, De Strooper B, Kivipelto M, Holstege H, Chételat G, Teunissen CE, Cummings J, van der Flier WM. Alzheimer's disease. Lancet. 2021;397:1577–1590. doi: 10.1016/S0140-6736(20)32205-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Prince MJ, Wu F, Guo Y, Gutierrez Robledo LM, O'Donnell M, Sullivan R, Yusuf S. The burden of disease in older people and implications for health policy and practice. Lancet. 2015;385:549–562. doi: 10.1016/S0140-6736(14)61347-7. [DOI] [PubMed] [Google Scholar]
  • 4.Vogt NM, Kerby RL, Dill-McFarland KA, Harding SJ, Merluzzi AP, Johnson SC, Carlsson CM, Asthana S, Zetterberg H, Blennow K, Bendlin BB, Rey FE. Gut microbiome alterations in Alzheimer's disease. Sci Rep. 2017;7:13537. doi: 10.1038/s41598-017-13601-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Zhuang ZQ, Shen LL, Li WW, Fu X, Zeng F, Gui L, Lü Y, Cai M, Zhu C, Tan YL, Zheng P, Li HY, Zhu J, Zhou HD, Bu XL, Wang YJ. Gut microbiota is altered in patients with Alzheimer's disease. J Alzheimers Dis. 2018;63:1337–1346. doi: 10.3233/JAD-180176. [DOI] [PubMed] [Google Scholar]
  • 6.Zhou Y, Wang Y, Quan M, Zhao H, Jia J. Gut microbiota changes and their correlation with cognitive and neuropsychiatric symptoms in Alzheimer's disease. J Alzheimers Dis. 2021;81:583–595. doi: 10.3233/JAD-201497. [DOI] [PubMed] [Google Scholar]
  • 7.Qian Y, Yang X, Xu S, Wu C, Song Y, Qin N, Chen SD, Xiao Q. Alteration of the fecal microbiota in Chinese patients with Parkinson's disease. Brain Behav Immun. 2018;70:194–202. doi: 10.1016/j.bbi.2018.02.016. [DOI] [PubMed] [Google Scholar]
  • 8.Lee Y, Park JY, Lee EH, Yang J, Jeong BR, Kim YK, Seoh JY, Lee S, Han PL, Kim EJ. Rapid assessment of microbiota changes in individuals with autism spectrum disorder using bacteria-derived membrane vesicles in urine. Exp Neurobiol. 2017;26:307–317. doi: 10.5607/en.2017.26.5.307. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.White DC, Sutton SD, Ringelberg DB. The genus Sphingomonas: physiology and ecology. Curr Opin Biotechnol. 1996;7:301–306. doi: 10.1016/S0958-1669(96)80034-6. [DOI] [PubMed] [Google Scholar]
  • 10.Ionescu MI, Neagoe DȘ, Crăciun AM, Moldovan OT. The gram-negative bacilli Isolated from caves-Sphingomonas paucimobilis and Hafnia alvei and a review of their involvement in human infections. Int J Environ Res Public Health. 2022;19:2324. doi: 10.3390/ijerph19042324. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Göker T, Aşık RZ, Yılmaz MB, Çelik I, Tekiner A. Sphingomonas paucimobilis: a rare infectious agent found in cerebrospinal fluid. J Korean Neurosurg Soc. 2017;60:481–483. doi: 10.3340/jkns.2014.0102.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Laupland KB, Paterson DL, Stewart AG, Edwards F, Harris PNA. Sphingomonas paucimobilis bloodstream infection is a predominantly community-onset disease with significant lethality. Int J Infect Dis. 2022;119:172–177. doi: 10.1016/j.ijid.2022.03.060. [DOI] [PubMed] [Google Scholar]
  • 13.Ryan MP, Adley CC. Sphingomonas paucimobilis: a persistent Gram-negative nosocomial infectious organism. J Hosp Infect. 2010;75:153–157. doi: 10.1016/j.jhin.2010.03.007. [DOI] [PubMed] [Google Scholar]
  • 14.Raetz CR, Whitfield C. Lipopolysaccharide endotoxins. Annu Rev Biochem. 2002;71:635–700. doi: 10.1146/annurev.biochem.71.110601.135414. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Ramachandran G. Gram-positive and Gram-negative bacterial toxins in sepsis: a brief review. Virulence. 2014;5:213–218. doi: 10.4161/viru.27024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Kim JH, Lee J, Park J, Gho YS. Gram-negative and Gram-positive bacterial extracellular vesicles. Semin Cell Dev Biol. 2015;40:97–104. doi: 10.1016/j.semcdb.2015.02.006. [DOI] [PubMed] [Google Scholar]
  • 17.Liu Y, Defourny KAY, Smid EJ, Abee T. Gram-positive bacterial extracellular vesicles and their impact on health and disease. Front Microbiol. 2018;9:1502. doi: 10.3389/fmicb.2018.01502. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Brown L, Wolf JM, Prados-Rosales R, Casadevall A. Through the wall: extracellular vesicles in Gram-positive bacteria, mycobacteria and fungi. Nat Rev Microbiol. 2015;13:620–630. doi: 10.1038/nrmicro3480. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Liao YT, Kuo SC, Chiang MH, Lee YT, Sung WC, Chen YH, Chen TL, Fung CP. Acinetobacter baumannii Extracellular OXA-58 is primarily and selectively released via outer membrane vesicles after sec-dependent periplasmic translocation. Antimicrob Agents Chemother. 2015;59:7346–7354. doi: 10.1128/AAC.01343-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Choi JW, Kim SC, Hong SH, Lee HJ. Secretable small RNAs via outer membrane vesicles in periodontal pathogens. J Dent Res. 2017;96:458–466. doi: 10.1177/0022034516685071. [DOI] [PubMed] [Google Scholar]
  • 21.Choi J, Kim YK, Han PL. Extracellular vesicles derived from Lactobacillus plantarum increase BDNF expression in cultured hippocampal neurons and produce antidepressant-like effects in mice. Exp Neurobiol. 2019;28:158–171. doi: 10.5607/en.2019.28.2.158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Choi J, Kwon H, Kim YK, Han PL. Extracellular vesicles from Gram-positive and Gram-negative probiotics remediate stress-induced depressive behavior in mice. Mol Neurobiol. 2022;59:2715–2728. doi: 10.1007/s12035-021-02655-9. [DOI] [PubMed] [Google Scholar]
  • 23.Kwon H, Lee EH, Park SY, Park JY, Hong JH, Kim EK, Shin TS, Kim YK, Han PL. Lactobacillus-derived extracellular vesicles counteract Aβ42-induced abnormal transcriptional changes through the upregulation of MeCP2 and Sirt1 and improve Aβ pathology in Tg-APP/PS1 mice. Exp Mol Med. 2023;55:2067–2082. doi: 10.1038/s12276-023-01084-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Kim YK. Sphingomonas-derived nanovesicles and use thereof. Patent KR 10-2022-0081273 2022
  • 25.Jankowsky JL, Slunt HH, Ratovitski T, Jenkins NA, Copeland NG, Borchelt DR. Co-expression of multiple transgenes in mouse CNS: a comparison of strategies. Biomol Eng. 2001;17:157–165. doi: 10.1016/S1389-0344(01)00067-3. [DOI] [PubMed] [Google Scholar]
  • 26.Choi J, Kwon HJ, Lee JE, Lee Y, Seoh JY, Han PL. Hyperoxygenation revitalizes Alzheimer's disease pathology through the upregulation of neurotrophic factors. Aging Cell. 2019;18:e12888. doi: 10.1111/acel.12888. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Seol SI, Davaanyam D, Oh SA, Lee EH, Han PL, Kim SW, Lee JK. Age-dependent and Aβ-induced dynamic changes in the subcellular localization of HMGB1 in neurons and microglia in the brains of an animal model of Alzheimer's disease. Cells. 2024;13:189. doi: 10.3390/cells13020189. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Lee JE, Kwon HJ, Choi J, Seo JS, Han PL. Aging increases vulnerability to stress-induced depression via upregulation of NADPH oxidase in mice. Commun Biol. 2020;3:292. doi: 10.1038/s42003-020-1010-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Choi JH, Moon CM, Shin TS, Kim EK, McDowell A, Jo MK, Joo YH, Kim SE, Jung HK, Shim KN, Jung SA, Kim YK. Lactobacillus paracasei-derived extracellular vesicles attenuate the intestinal inflammatory response by augmenting the endoplasmic reticulum stress pathway. Exp Mol Med. 2020;52:423–437. doi: 10.1038/s12276-019-0359-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Kim TK, Lee JE, Kim JE, Park JY, Choi J, Kim H, Lee EH, Han PL. G9a-mediated regulation of OXT and AVP expression in the basolateral amygdala mediates stress-induced lasting behavioral depression and its reversal by exercise. Mol Neurobiol. 2016;53:2843–2856. doi: 10.1007/s12035-015-9160-z. [DOI] [PubMed] [Google Scholar]
  • 31.Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43:e47. doi: 10.1093/nar/gkv007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Plaisier SB, Taschereau R, Wong JA, Graeber TG. Rank-rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures. Nucleic Acids Res. 2010;38:e169. doi: 10.1093/nar/gkq636. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Szklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, Gable AL, Fang T, Doncheva NT, Pyysalo S, Bork P, Jensen LJ, von Mering C. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 2023;51:D638–D646. doi: 10.1093/nar/gkac1000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Ge SX, Jung D, Yao R. ShinyGO: a graphical gene-set enrichment tool for animals and plants. Bioinformatics. 2020;36:2628–2629. doi: 10.1093/bioinformatics/btz931. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.LeBleu VS, O'Connell JT, Gonzalez Herrera KN, Wikman H, Pantel K, Haigis MC, de Carvalho FM, Damascena A, Domingos Chinen LT, Rocha RM, Asara JM, Kalluri R. PGC-1α mediates mitochondrial biogenesis and oxidative phosphorylation in cancer cells to promote metastasis. Nat Cell Biol. 2014;16:992–1003. doi: 10.1038/ncb3039. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Gureev AP, Shaforostova EA, Popov VN. Regulation of mitochondrial biogenesis as a way for active longevity: interaction between the Nrf2 and PGC-1α signaling pathways. Front Genet. 2019;10:435. doi: 10.3389/fgene.2019.00435. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Guarino F, Zinghirino F, Mela L, Pappalardo XG, Ichas F, De Pinto V, Messina A. NRF-1 and HIF-1α contribute to modulation of human VDAC1 gene promoter during starvation and hypoxia in HeLa cells. Biochim Biophys Acta Bioenerg. 2020;1861:148289. doi: 10.1016/j.bbabio.2020.148289. [DOI] [PubMed] [Google Scholar]
  • 38.Sung PS, Lin PY, Liu CH, Su HC, Tsai KJ. Neuroinflammation and neurogenesis in Alzheimer's disease and potential therapeutic approaches. Int J Mol Sci. 2020;21:701. doi: 10.3390/ijms21030701. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Leng F, Edison P. Neuroinflammation and microglial activation in Alzheimer disease: where do we go from here? Nat Rev Neurol. 2021;17:157–172. doi: 10.1038/s41582-020-00435-y. [DOI] [PubMed] [Google Scholar]

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Supplementary Materials

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