Activation of RAW264.7 macrophages by active fraction of Albizia julibrissin saponin via Ca2+–ERK1/2–CREB–lncRNA pathways

Chenying Wanga, Jing Dua, Xiangfeng Chena, Yongliang Zhub, Hongxiang Suna,⁎
a Key Laboratory of Animal Virology of Ministry of Agriculture, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
b Cancer Institute and Education Ministry Key Laboratory of Cancer Prevention and Intervention, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310009, China

⁎ Corresponding author at: College of Animal Sciences, Zhejiang University, Yuhangtang Road 866, Hangzhou 310058, China.
E-mail address: [email protected] (H. Sun).
Received 11 June 2019; Received in revised form 7 September 2019; Accepted 30 September 2019



The saponin active fraction from the stem bark of Albizia julibrissin (AJSAF) is an ideal vaccine adjuvant, but its mechanism of action remains unclear. The recent evidences indicate that long noncoding RNAs (lncRNAs) play essential roles in regulating the activation and function of macrophages. The current experiments were designed to investigate the effects of AJSAF on the activation of RAW264.7 macrophages and to explore its intracellular molecular mechanisms using a global gene expression microarray. AJSAF could significantly enhance phagocytic activity, induce reactive oXygen species (ROS), promote surface molecule expression, and up-regulate the mRNA and protein expression of cytokines and chemokines in RAW264.7 cells. AJSAF induced the differential ex- pression of 223 mRNAs and 103 lncRNAs in RAW264.7 cells. Bioinformatics were used to predict the potential target mRNAs and function of up-regulated lncRNA A_30_P01018532 in RAW264.7 cells induced by AJSAF. The total 99 co-expressed mRNAs were classified as putative target genes of A_30_P01018532. A_30_P01018532 was associated with the inflammatory and immune response. AJSAF significantly increased the intracellular free Ca2+ levels and induced the phosphorylation of ERK1/2 and CREB in RAW264.7 cells. Moreover, Ca2+ chelator
BAPTA-AM, ERK1/2 inhibitor PD98059 and CREB inhibitor KG-501 significantly inhibited the up-regulation of TNF-α, CCL2, CXCL2, CCL22, and A_30_P01018532 in RAW264.7 cells induced by AJSAF. These results sug- gested that AJSAF could activate RAW264.7 cells via Ca2+–ERK1/2–CREB pathways and that A_30_P01018532 might be an important regulator of mRNA expression in AJSAF-activated macrophage. This study may provide insights into the molecular mechanisms of action of AJSAF.

Albizia julibrissin Saponin Macrophage
Long noncoding RNA (lncRNA)
Microarray ERK signaling

1. Introduction

Purified recombinant antigens generally elicit weak immune re- sponses unless they are co-formulated with adjuvants. Adjuvants sti- mulate the innate immune response and shape cellular and humoral responses that eventually confer protection against pathogens [1]. Adjuvants are essential components of new generation vaccines, but still their mechanism of action is poorly understood. The innate im- mune cells are activated through pattern recognition receptors (PRRs). However, it could hardly explain immune responses to some adjuvants that remarkably activate the immune system but have been identified no PRRs yet. The ‘danger’ model suggests that immunity might be guided by danger-associated molecular patterns (DAMPs) released from the damaged and dying cells [2,3]. Aluminum compound (Alum) has been shown to have cytotoXic effects resulting in the release of host DNA into the cytoplasm and then influence its adjuvanticity through triggering STING (stimulator of IFN gene)-dependent DNA sensing mechanisms [4,5]. QS-21, a highly characterized adjuvant-active sa- ponin compound isolated from the bark of the Quillaja saponoria Mo- lina, induced macrophage and dendritic cell death in a caspase-1-, ASC-, and NLRP3-independent manner at higher concentrations, which might contribute to release of DAMPs resulting in priming a signal and im- pacting its adjuvant effects [6]. Although the mechanism of action of saponin-based adjuvants is being intensively studied [7–9], it is still not fully elucidated [10].
Long non-coding RNAs (lncRNAs), greater than 200 nucleotides in length, can regulate the mRNA expression in diverse biological contexts [11,12]. Recent evidences indicate that lncRNAs play important roles in directing the development and controlling the activation of macro- phages [13]. A series of lncRNAs such as PACER [14], THRIL [15], and lnc-13 [16] in human, as well as lincRNA-CoX2 [17], lincRNA-EPS [18], lncRNA-ACOD1 [19], and lncRNA Mirt2 [20] in mice have been found to regulate the activation and function of macrophages. The discovery and identification of lncRNAs in the immune cells has provided a new perspective on the gene regulation [21]. Therefore, the study on lncRNAs is likely to reveal the novel mechanism of action of saponin adjuvants.
In our previous studies, the active fraction of saponin from the stem bark of Albizia julibrissin Durazz. (AJSAF) has been proved to improve antigen-specific both cellular and humoral immune responses, and si- multaneously elicit a Th1/Th2 response in mice to recombinant fowl poX virus vector-based H5 avian influenza vaccine (rFPV) [22] and porcine reproductive and respiratory syndrome virus (PRRSV) vaccine [23], and be a promising adjuvant candidate for vaccine. Many vaccine adjuvants have been reported to act through activating antigen-pre- senting cells (APCs) such as dendritic cells [24]. Macrophages exert an important role in the immune system as an interface between innate and adaptive immunity [25]. RAW264.7 cells are commonly accepted as a tool to investigate the molecular mechanisms of macrophages in- volved in regulating immunity [26] and the most suitable model cell lines for dendritic cell [27]. The current experiments were designed to investigate the activation of AJSAF on RAW264.7 macrophages and to explore its intracellular molecular mechanisms, especially the regula- tion role of lncRNAs using gene expression microarray.

2. Materials and methods

2.1. Reagents
3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), polymyxin B (PMB), fluorescein isothiocyanate-conjugated dextran (FITC-dextran) and KG-501 (CREB inhibitor) were purchased from Sigma Chemical Co., Saint Louis, MO, USA; fetal bovine serum (FBS) was from Gibco, Grand Island, NY, USA; DMEM medium was from Corning, Cellgro, NY, USA; mouse cytokine and chemokine de- tecting ELISA kits were from Wuhan Boster Biological Technology Co. Ltd., Hubei, China. TRIzol reagent was purchased from Ambion Inc., Carlsbad, CA, USA; revert Aid™ M-MuLV reverse transcriptase was from Fermentas, Amherst, NY, USA; diethylpyrocarbonate (DEPC), ribonu- clease inhibitor and oligo(dT)18 were from Sangon Biotech (Shanghai) Co., Ltd., China; FastStart universal SYBR Green Master (ROX) was from Roche Diagnostics, Indianapolis, IN, USA. Phycoerythrin (PE)-con- jugated anti-mouse CD40 (Clone: 1C10), CD80 (Clone: 16-10A1), CD86 (Clone: PO3.1), MHC-I (H-2 Kb, Clone: AF6-88-5.5.3), and MHC-II (I-
Ab, Clone: AF6-120.1) monoclonal antibodies (mAbs) were purchased from eBioscience Inc., San Diego, CA, USA; Fluo-3 AM was from Dojindo Laboratory, Kumamoto, Japan; reactive oXygen species (ROS) assay kit, horseradish peroXidase (HRP)-conjugated goat anti-rabbit and anti-mouse IgG (H + L), enhanced chemiluminescence (ECL) kit and RIPA lysis buffer were from Beyotime Biotech, Jiangsu, China; phos- phatase inhibitor cocktail and protease inhibitor cocktail were from Bimake, Houston, TX, USA; anti-mouse actin, IL-1β (D4T2D), anti- rabbit ERK, p-ERK1/2 (Thr202/Tyr204), CREB and p-CREB (Ser133) mAbs were from Cell Signaling Technology, Beverly, MA, USA; Ca2+ chelator BAPTA-AM and ERK1/2 inhibitor PD98059 were from Selleck, Houston, TX, USA. SurePrint G3 8 × 60 K mouse gene expression mi- croarray was provided from Agilent Technologies. Santa Clara, CA, USA.

2.2. Preparation and characterization of AJSAF
AJSAF was prepared and characterized as previously described [23]. A total of 29 saponins including 10 new compounds in AJSAF were identified and characterized by high-performance liquid chro- matography coupled with quadrupole time-of-flight mass spectrometry based on accurate mass database [28].

2.3. Cell culture
RAW264.7 cells were purchased from the cell bank of the Shanghai Branch of the Chinese Academy of Sciences (Shanghai, China), and maintained in a 5% CO2 atmosphere in DMEM medium supplemented with 10% FBS, 100 μg/ml streptomycin, and 100 U/ml penicillin.

2.4. Cell viability assay
RAW264.7 cells were seeded at 2 × 104 cell/well in a 96-well plate and incubated at 37 °C in a humidified atmosphere with 5% CO2. After 24 h, the various concentrations of AJSAF were added into each well and these cells were incubated at 37 °C. 4 h before the end, the cell prolifera- tion was detected using MTT assay as previously described [29].

2.5. Enzyme-linked immunosorbent assay (ELISA)
RAW264.7 cells were incubated with AJSAF (200 μg/ml) for up to 16 h or AJSAF (100, 200, and 250 μg/ml) for 16 h, and the culture supernatant was collected for the detection of TNF-α, CCL2, CXCL2, and CCL22 levels using commercial ELISA kits [29].

2.6. Determination of phagocytic uptake
RAW264.7 cells were treated with AJSAF for 24 h. The cells were harvested and then resuspended in 100 μl FITC-dextran solution (1 mg/ml). After incubation at 37 °C for 30 min, the phagocytic activity was measured using BD FACSVerse System (BD Biosciences, San Jose, CA, USA) [29].

2.7. Surface molecule expression analysis
The surface molecule expression on RAW264.7 cells was determined by flow cytometry [30]. RAW264.7 cells treated with AJSAF for 24 h were harvested and washed with ice-cold PBS containing 2% FCS. Cells were blocked with purified anti-mouse CD16/CD32 antibody (FcR block) for 10 min, and then stained with optimal concentrations of PE-conjugated anti-mouse CD40, CD80, CD86, MHC-I, and MHC-II antibodies for an ad- ditional 30 min. The stained cells were analyzed on BD FACSVerse System.

2.8. ROS detection
The intracellular ROS levels were detected using assay kit. After treatment of AJSAF for 2 h, RAW264.7 cells were incubated with 20 μM of 2′,7′-dichlorofluorescin diacetate (DCFH-DA) at 37 °C for 20 min, and then washed with DMEM three times. The mean fluorescence intensity (MFI) was determined by flow cytometry with BD FACSVerse system.

2.9. Intracellular free calcium detection
The intracellular free Ca2+ levels were measured by flow cytometry using a fluorescent dye Fluo-3 AM. After exposed to AJSAF at 200 μg/ ml for different time, RAW264.7 cells were incubated with 5 μM of Fluo-3 AM at 37 °C for 30 min away from light. The harvested cells were washed twice with HBSS, and then detected for the MFI using flow cytometer at the excitation wave length of 488 nm [31].

2.10. Quantitative real-time PCR (qRT-PCR)
After incubation with or without AJSAF, RAW264.7 cells were subjected to TRIzol reagent. The total RNA was isolated and reverse transcription was performed as previously [32]. The PCR was per- formed on an ABI 7500 PCR system using FastStart Universal SYBR Green Master (RoX). The PCR cycling was performed as follows: initial denaturation at 95 °C for 10 min followed by 40 cycles of denaturation at 95 °C for 10 s, and annealing at 60 °C for 1 min. The specific primers for qRT-PCR were synthesized by Sangon Biotech (Shanghai) Co., Ltd. (China) and the sequences were listed in Supplementary Table 1. Primer amplification efficiency and specificity were verified for each set of primers. GAPDH was used as an endogenous control. The mRNA expression levels of the tested genes relative to GAPDH were de- termined using the 2−ΔΔCt method and shown as fold induction.

2.11. Microarray analysis
Total RNA from RAW264.7 cells was further purified with RNeasy® Mini kit (Qiagen). Fluorescent complementary RNA (cRNA) was gen- erated by Agilent’s Low Input Quick Amp Labeling Kit and purified with RNeasy® Mini kit. The integrity of the input template RNA and labeled cRNA was determined using the NanoDrop UV-VIS spectrophotometer and the Agilent 2100 bioanalyzer using RNA 6000 Nano LabChip kit. RNA labelling and hybridization were performed according to the manufacture’s protocol. Hybridized microarrays were scanned with Agilent C scanner using Agilent’s Scan Control software, version
A.8.4.1. The features were extracted with the Feature EXtraction soft- ware. Data pre-processing and differential expression analysis were done in R software. The data were normalized using the quantile method (GENESPRING12.0). Normalized expression data were sub- jected to log2 transformation. P-value < 0.05 and fold change threshold (absolute ratio) > 2 were considered as significant difference [33].

2.12. Functional analysis of differentially expressed mRNAs
Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for the functions and pathways of differentially expressed mRNAs (DEGs) using DAVID Bioinformatics Resources (version 6.8,[34]. The significance was determined using the Fisher’s exact test and χ2 test, and the threshold of significance was defined by P-value and false discovery rate (FDR). The common and unique ones of KEGG category- associated genes were analyzed by Venn diagram. Ingenuity Pathways Analysis (IPA) software (Ingenuity Systems, Redwood City, CA) was used for network analysis and upstream analysis of DEGs to show crucial effectors and regulatory factors [35].

2.13. Annotation and functional analysis of differentially expressed lncRNAs
Differentially expressed lncRNAs were annotated through the da- tabase of Refseq, Ensembl, fRNAdb, and NONCODE [36,37]. The coding potential of each lncRNA was evaluated by using the Coding Potential Calculator ( [38]. The interaction between transcription factors and lncRNA promoter regions was predicted by omiXcore ( [39]. RNAfold web server ( RNAWebSuite/RNAfold.cgi) was applied for predicting secondary structures of lncRNA sequences. The co-expressed mRNAs of lncRNAs were identified by Pearson’s correlation coefficients between each lncRNA/mRNA pair [40]. The significance was determined using the following cutoff: a Pearson’s correlation coefficient > 0.8 or < –0.8 and P < 0.01. Next, cis and trans regulation predictions were performed. In cis-acting analysis, the positions of lncRNAs were searched within 100 kb of their co-expressed mRNAs using the RefSeq and UCSC Known Genes databases (mm10) [41]. Three prediction principles including RNA-RNA, RNA-DNA and RNA-protein interactions were used for the trans-acting analysis. LncRNATargets ( lrt/) was used to predict the RNA-RNA and RNA-DNA interaction based on nucleic acid thermodynamics [42]. The interaction of lncRNA and RNA-binding protein (RBP) was predicted using RBPDB (The database of RNA-binding protein specificities) [43] and the RBP-binding mRNAs in GO terms were considered as the possible targets of lncRNAs. The interaction networks of lncRNA and its target mRNAs were constructed using Cytoscape [44]. The function of lncRNA was predicted using GO and KEGG analysis based on its target mRNAs. Fig. 1. Effects of AJSAF on the growth of RAW264.7 cells. RAW264.7 cells were treated with AJSAF at the various concentrations for 6, 12 and 24 h, and then cell proliferation was detected using MTT assay. The values are presented as mean ± SD (n = 4). Significant differences with control cells (0 μg/ml) were designated as **P < 0.01 and ***P < 0.001. 2.14. Fractionation of nuclear and cytosolic RNA Fractionation of nuclear and cytosolic RNA was performed as pre- viously described [45]. Briefly, RAW264.7 cells (5 × 106) were har- vested and resuspended in 200 µl ice-cold lysis buffer (0.1% NP-40 in PBS) with protease inhibitor cocktail (Bimake) and ribonucleoside va- nadyl complex (10 mM) (New England BioLabs) for 2 min on ice. The samples were centrifuged at 12,000 rpm for 5 min at 4 °C. The super- natants containing the cytosolic fraction were miXed with 5 volumes of TRIzol reagent. Pellets were washed twice with ice-cold lysis buffer, and nuclei were lysed with 1 ml TRIzol reagent. RNA was extracted according to the user’s manual. 2.15. Western blotting After treated with AJSAF for various time, RAW264.7 cells were washed twice with cold PBS and lysed with RIPA lysis buffer. The contents of protein were measured with the BCA protein assay kit using bovine serum albumin as a standard. The denatured proteins were se- parated on 10%–12% SDS-PAGE and transferred to PVDF membrane. After blocking the membrane with 5% skim milk in Tris buffered saline containing 0.1% Tween-20 (TTBS) for 1 h at 37 °C, the blot was in- cubated with anti-mouse actin, IL-1β, anti-rabbit ERK1/2, p-ERK1/2, CREB, or p-CREB mAbs overnight at 4 °C. Subsequently, the membranes were washed with TTBS and incubated with HRP-conjugated goat anti- mouse or anti-rabbit IgG (H + L) for 1 h. After washing the membrane with TTBS three times, the signal was visualized with ECL on the LiCor C-DiGit Blot scanner (LiCor, Lincoln, NE) [33]. 2.16. Inhibition assay After incubation with BAPTA-AM (25 μM), PD98059 (15 μM) for 0.5 h, or KG-501 (10 μM) for 1 h, RAW264.7 cells were stimulated with AJSAF (200 μg/ml) for 2, 4, or 24 h. The cells and supernatants were collected for detecting the gene expression and protein levels of TNF-α, CCL2, CXCL2, CCL22, and A_30_P01018532 by qRT-PCR and ELISA, respectively. 2.17. Statistical analysis Data were expressed as mean ± SD and examined for their statis- tical significance of difference with ANOVA and a Tukey post-hoc test. P-value less than 0.05 was considered to be statistically significant. Fig. 2. Effects of AJSAF on the phagocytic activity (A), surface molecule expression (B), and secretion of cytokines and chemokines (C) of RAW264.7 cells. RAW264.7 cells were incubated with AJSAF for 24 h (A and B) or 16 h (C), and then cells and the culture supernatant were collected to measure phagocytic activity, surface molecule expression levels and the contents of TNF-α, CCL2, CXCL2, and CCL22 using flow cytometry and ELISA, respectively. The values are presented as mean ± SD (n = 3). Significant differences with 0 μg/ml were designated as **P < 0.01 and ***P < 0.001. 3. Results 3.1. Effects of AJSAF on the growth of RAW264.7 cells The effects of AJSAF on the growth of RAW264.7 cells were de- tected using MTT assay, and the results were shown in Fig. 1. AJSAF is not cytotoXic to RAW264.7 cells up to the concentration of 150 μg/ml (P > 0.05). However, AJSAF significantly inhibited the proliferation of RAW264.7 cells at the concentration of 200–350 μg/ml in a concentration-dependent manner (P < 0.001). 3.2. AJSAF induces the activation of RAW264.7 cells The effect of AJSAF on phagocytic uptake of FITC-dextran in RAW264.7 cells was examined, and the results were shown in Fig. 2A. AJSAF markedly concentration-dependently promote the phagocytic ca- pacities of macrophages. The expression levels of the accessory and costi- mulatory molecules on RAW264.7 cells treated with AJSAF for 24 h were also measured. AJSAF significantly enhanced the expression levels of sur- face molecules CD40, CD80, CD86, MHC I, and MHC II (P < 0.01 and P < 0.001, Fig. 2B). The effects of AJSAF on the production of the cytokines and che- mokines from RAW264.7 cells were further detected. As shown in Fig. 2C, AJSAF remarkably concentration-dependently induced the se- cretion of TNF-α, CCL2, CXCL2, and CCL22 from RAW264.7 cells (P < 0.001). AJSAF also significantly concentration-dependently pro- moted the protein expression of IL-1β (Supplementary Fig. 1) and time- dependently induced the production of TNF-α, CCL2, CXCL2, and CCL22 from RAW264.7 cells (Supplementary Fig. 2). The mRNA expression levels of cytokines and chemokines in RAW264.7 cells treated with AJSAF at the various concentrations for different times were detected by qRT-PCR. AJSAF remarkably up- regulated the mRNA expression levels of IL-1β, TNF-α, CCL2, CXCL2, and CCL22 in RAW264.7 cells in time- and concentration-dependent manner (Fig. 3). 3.3. Differentially expressed mRNAs and lncRNAs To clarify the molecular mechanisms of activation of RAW264.7 cell, the cells stimulated with AJSAF (200 μg/ml) for 2 h were subjected to SurePrint G3 8 × 60 K mouse gene expression microarray representing 39,430 mRNA probes and 16,251 lncRNA probes. The work flow of the microarray analysis was shown in Fig. 4. The microarray analysis revealed 394 differentially expressed probes including 270 mRNAs and 124 lncRNAs with FC > 2 and P value ≤ 0.05 compared to untreated sam- ples. Among the differentially expressed probes, 191 mRNA and 47 lncRNA probes were up-regulated, corresponding to 164 and 41 genes, while down-regulated 79 mRNA and 77 lncRNA probes corresponded to 61 and 62 genes, respectively. To confirm the validity of the microarray results, qRT-PCR was undertaken for 12 up-regulated genes (CSF1, CSF3, MARCKS, PTGER2, FLRT3, NLRP3, NOD2, A_30_P01033086, A_30_P01032527, A_30_P01019478, A_30_P01021097, and A_30_P01018532) and 4 down-regulated genes (CASK, MSH4,
Fig. 3. Effects of the AJSAF on the mRNA expression of cytokines and chemokines in RAW264.7 cells. RAW264.7 were incubated with medium or AJSAF (100, 200, or 250 μg/ml) for up to 8 h, the mRNA expression levels of IL-1β, TNF-α, CCL2, CXCL2, and CCL22 were measured using qRT-PCR. The values are presented as mean ± SD (n = 3). Significant differences with control cells (0 μg/ml) were designated as **P < 0.01 and ***P < 0.001. A_30_P01033073, and A_30_P01029853). AJSAF-induced expression levels of selected genes by qRT-PCR were consistent with microarray analysis data (Supplementary Fig. 3). Among DEGs, 38 genes (IL-1α, IL-1β, TNF-α, CXCL2, CCL4, SOCS3, TNFRSF1B, ZC3H12A, INHBA, SAA3, CCRL2, ICOSL, MTMR7, TNFAIP3, NFKBIZ, STX11, KDM6B, ADORA2A, CDC42EP2, ARG2, GPR84, DUSP2, TNFSF9, GADD45B, PPFIA3, FAS, 1200009I06Rik, NIACR1, CLEC4E, JAG1, BCL3, GCH1, JUNB, NFKBIA, A130040M12Rik, ICAM1, CENPP, and CD84) were defined as distinct M1 markers, 20 genes (IL-10, CCL7, CCL24, CD83, CISH, FLRT3, CSF1, HBEGF, AHR, MMP9, IRF4, PTPRE, 4833422F24Rik, SPHK1, MYC, ZBTB46, ERRFI1, REL, 5330406M23Rik, and IFIT2) were as distinct M2 markers, while 20 (PTGER2, OLR1, PDE4B, CCL22, PIM1, IER3, IRG1, CD40, PHLDA1, NFKBIE, MALT1, PTGS2, 3930401B19Rik, TRAF1, SRC, ST3GAL1, JDP2, TCF4, FGD4, and KLHL6) were common to both M1 and M2 macrophages (Supplementary Table 2) based on GSE69607database [46]. 3.4. GO and KEGG analysis of differentially expressed mRNAs All 223 DEGs have been subjected to GO functional analysis, and the results were shown in Fig. 5A. The molecular function included ‘cytokine activity’ (P = 7.73 × 10−15), ‘chemokine activity’ (P = 7.59 × 10−5), ‘CCR chemokine receptor binding’ (P = 1.18 × 10−4), ‘protein binding’ (P = 6.10 × 10−4), ‘TNF receptor binding’ (P = 3.09 × 10−3), and ‘cal- modulin binding’ (P = 2.63 × 10−2). The biological process were con- nected to ‘inflammatory response’ (P = 1.94 × 10−20), ‘immune response’ (P = 1.33 × 10−10),’ ‘cellular response to IL-1′ (P = 4.58 × 10−9), ‘reg- ulation of ERK1 and ERK2 cascade’ (P = 2.66 × 10−7), ‘regulation of NF- κB activity’ (P = 1.02 × 10−6), and ‘neutrophil chemotaxis’ (P = 4.26 × 10−6). KEGG analysis was used to identify the immune-related pathway of the DEGs. The most significant pathways were ‘TNF pathway’ (P = 2.79 × 10−16), ‘cytokine-cytokine receptor interaction’ (P = 4.13 × 10−10), ‘NF-κB pathway’ (P = 1.89 × 10−7), ‘Jak-STAT pathway’ (P = 5.24 × 10−5), ‘NOD-like receptor (NLR) pathway’ (P = 5.10 × 10−4), and ‘MAPK pathway’ (P = 0.003) (Fig. 5B). The Venn diagram was generated for clarifying the relationship among the enriched KEGG pathways. There were two ‘focus’ genes IL-1β and TNF in the terms of ‘TNF signaling pathway’, ‘NF-κB pathway’, ‘NLR pathway’, and ‘MAPK pathway’ (Fig. 5C). Several gene expressions were unique for each pathway, with BCL3, SOCS3, CSF1, IL15, JUNB, LIF, MMP9, CXCL2, CX3CL1, and TNFRSF1B for ‘TNF signaling pathway’, LTB, CCL4, CD40, and MALTL for ‘NF-κB pathway’, NLRP3 for ‘NLR pathway’, and IL-1α, PDGFB, DUSP2, DUSP5, GADD45A, GADD45B, and MYC for ‘MAPK pathway’, respectively. 3.5. Core genes and core regulators of differentially expressed mRNAs To clarify the core genes of DEGs, a ‘focus gene’ network was gen- erated using IPA software. TNF-α and IL-1β were identified to be two focus genes in the network consisting of 108 genes (Fig. 5D). The up- stream analysis revealed that TNF (z = 4.113, P = 8.81 × 10−26), IL- 1β (z = 4.344, P = 3.73 × 10−18), and ERK1/2 (z = 3.236, P = 2.32 × 10−14) were the core regulators involved in the immune response of RAW264.7 cells to AJSAF (Fig. 5E). IPA pathway analysis showed that Ca2+ pathway activated ERK cascade and its downstream transcription factor CREB in AJSAF-treated RAW264.7 cells (Fig. 5F). 3.6. Annotation and functional prediction of A_30_P01018532 To unveil potential associations between lncRNAs and mRNAs, TOP 10 up-regulated lncRNA probes were subjected to bioinformatic ana- lyses (Supplementary Table 3). A_30_P01027990 and A_30_P01033086 were predicted to possess coding abilities. A_30_P01025400, A_30_P01023376, and A_30_P01017981 were found to have no sig- nificant difference between their probe signal and the background. Among the other 5 lncRNA probes (A_30_P01018532, A_30_P01032527, A_30_P01025874, A_30_P01019478, and A_30_P01021097) detected in both control and AJSAF-treated RAW264.7 cells based on microarray analysis, A_30_P01018532 (coding potential score −0.994) was the most up-regulated lncRNA in RAW64.7 cells induced by AJSAF, and selected for annotation and functional analysis. The prediction of target mRNAs might provide a foundation to analyze the function of lncRNAs. The co-expressed mRNAs were clas- sified as the potential target genes of lncRNA. Firstly, the correlation analysis of A_30_P01018532 and 124 differentially expressed immune- related mRNAs was conducted to afford 104 co-expressed mRNAs. Secondly, two independent algorithms (cis and trans) were used to predict the potential targets of A_30_P01018532. For the cis-acting analysis, the mRNAs in the same chromosome 100 kb upstream and downstream of A_30_P01018532 were searched, and no target mRNAs were found. Meanwhile, two platforms lncRNA Targets and RBPDB were used to predict the trans-target genes of A_30_P01018532. By analyzing the interaction of A_30_P01018532 with mRNA (lncRNA–RNA) and promoter sequence (lncRNA–DNA) of its co-ex- pressed mRNAs, 20 (Fig. 6A) and 24 (Fig. 6B) mRNAs were predicted to be putative target genes. Through 32 RBPs probably interacting with A_30_P01018532, 90 co-expressed mRNAs were predicted to be puta- tive trans-target genes (Fig. 6C). Collectively, 99 putative target mRNAs of the A_30_P01018532 were obtained after excluding duplicate genes. The GO function analysis of A_30_P01018532 target mRNAs was conducted and the results were shown in Fig. 6D. The main enriched bio- logical processes were the ‘inflammatory response’ (P = 1.12 × 10−21), ‘immune response’ (P = 5.16 × 10−15), ‘cellular response to IL-1′ (P = 4.27 × 10−10), ‘regulation of ERK1 and ERK2 cascade’ (P = 5.23 × 10−9), ‘regulation of NF-κB activity’ (P = 6.91 × 10−9), and ‘regulation of apoptotic process’ (P = 9.48 × 10−9). The enriched molecular functions mainly included the ‘cytokine activity’ (P = 2.68 × 10−18), ‘protein binding’ (P = 3.41 × 10−9), ‘chemokine activity’ (P = 5.52 × 10−6), ‘growth factor activity’ Fig. 5. GO, KEGG and IPA analysis of differentially expressed mRNAs (DEGs) in RAW264.7 cells treated with AJSAF (200 μg/ml) for 2 h. (A) GO function. (B) KEGG immune-related pathways. (C) Venn diagram showing shared and unique DEGs in four pathways. The network analysis (D), upstream analysis (E) and pathway analysis (F) of DEGs using IPA software. (P = 1.24 × 10−5), ‘TNF-activated receptor activity’ (P = 1.57 × 10−4), and ‘CCR chemokine receptor binding’ (P = 4.36 × 10−4). KEGG analysis indicated that A_30_P01018532 could be involved in ‘TNF signaling pathway’ (P = 2.39 × 10−19), ‘cytokine-cytokine receptor interaction’ (P = 7.04 × 10−12), ‘NF-κB pathway’ (P = 5.30 × 10−9), ‘Jak-STAT pathway’ (P = 2.32 × 10−5), ‘NLR pathway’ (P = 9.22 × 10−5), and ‘MAPK signaling pathway’ (P = 0.001) (Fig. 6E). The orientation and 307 nt sequence of A_30_P01018532 were confirm using RT-PCR. A_30_P01018532 was proved to locate in the nucleus using fractionation of nuclear and cytosolic RNA and PCR (Fig. 6F). A_30_P01018532 was encoded by the opposite strand of the MRLN on chromosome 10 (Fig. 6G). The second structure of A_30_P01018532 possessed RNA binding domain and several RBP binding motifs, including the sequence that could combine with MRLN’s third exon (Fig. 6H). 3.7. Ca2+–ERK1/2–CREB pathway was essential for activation of RAW264.7 cells by AJSAF The effects of AJSAF on intracellular ROS generation in RAW264.7 cells were determined. As shown in Fig. 7A, AJSAF significantly con- centration-dependently induced production of ROS from RAW264.7 cells (P < 0.001). AJSAF also increased intracellular free calcium le- vels in a time- and concentration-dependent manner (Fig. 7B). More- over, Ca2+ chelator BAPTA-AM remarkably suppressed the up-regu- lated expression levels of TNF-α, CCL2, CXCL2, CCL22, and A_30_P01018532 (Fig. 7C) as well as the secretion of TNF-α, CCL2, CXCL2, and CCL22 in RAW264.7 cells induced by AJSAF (Fig. 7D). These results revealed that Ca2+ signaling was involved in AJSAF- mediated RAW264.7 cell activation. IPA analysis suggested ERK as one of the possible upstream mole- cules involved in the activation of RAW264.7 cells induced by AJSAF (Fig. 5E). Meanwhile, omiXcore predicted that the downstream tran- scription factor CERB of ERK1/2 could bind to the promoter region A_30_P01018532 with the score 0.97 (Supplementary Fig. 4). To in- vestigate whether AJSAF activated RAW264.7 cells via this pathway, the phosphorylation of ERK1/2 and CERB in RAW264.7 cells were detected by western blotting. AJSAF significantly induced the phos- phorylation of ERK1/2 and CREB from 15 min to 120 min (Fig. 7E). Pretreatment with ERK1/2 inhibitor PD98059 and CREB inhibitor KG- 501 significantly inhibited the up-regulated expression levels of TNF-α, CCL2, CXCL2, CCL22, and A_30_P01018532 in RAW264.7 cells induced by AJSAF (Fig. 7F–G). Collectively, these results confirmed the in- volvement of ERK1/2-CREB in the activation of RAW264.7 cells in- duced by AJSAF. 4. Discussion AJSAF has been previously reported to exert the immunological adjuvant effects on rFPV [22] and PRRSV vaccine [23] by inducing cytokine and chemokine immunostimulatory environment at the site of injection. However, its further mechanism of action is to be addressed. Many vaccine adjuvants were proved to act through activating mac- rophages [24]. In the present study, AJSAF was investigated for the potential to activate RAW264.7 macrophages and its intracellular mo- lecular mechanisms. AJSAF significantly promoted the phagocytic capacity and the ex- pression of the surface molecules CD40, CD80, CD86, MHC I, and MHC II. AJSAF could markedly time- and concentration-dependently not only induced the release of cytokines (IL-1β and TNF-α) and chemo- kines (CCL2, CXCL2 and CCL22) from RAW264.7 cells, but up-regu- lated the mRNA expression levels of IL-1β, TNF-α, CCL2, CXCL2, and CCL22 in RAW264.7 cells. Damaged and dead cells produce and release small endogenous DAMPs, which activate innate immune cells and in- itiate adaptive immune response [2]. The role of DAMPs, such as uric acid [47], DNA [3,5], and ATP [48] in adjuvant effects of Alum and MF59 has been confirmed. In view of that AJSAF was cytotoXic to RAW264.7 at the concentration > 150 μg/ml, the activation of macro- phages induced by AJSAF might contribute to its limited cytotoXicity resulting in release of DAMPs.
To investigate the molecular mechanisms associated with AJSAF- induced macrophage activation, the gene expression microarray was performed for AJSAF-treated RAW264.7 cells. AJSAF induced the dif- ferential expression of 223 annotated mRNAs and 103 non-redundant lncRNAs in RAW264.7 cells. Among the DEGs, the mRNA expression levels of 38 distinct M1, 20 typical M2, and 20 markers common to both M1 and M2 in RAW264.7 cells were up-regulated by AJSAF, suggesting that AJSAF elicited both M1 and M2 polarization of macrophages. These results further confirmed that AJSAF could induce the activation
Fig. 6. Annotation and functional prediction of A_30_P01018532. The potential target mRNAs of A_30_P01018532 by predicting the interaction with mRNA (A), DNA (B), and RBP (C). GO (D) and KEGG (E) analysis of A_30_P01018532 potential target mRNAs. (F) Location of A_30_P01018532 in RAW264.7 cells. (G) Annotation of A_30_P01018532. (H) Centroid secondary structure of A_30_P01018532 with the RNA binding domain and RBP binding motif.
of macrophage and were consistent with that AJSAF elicited a balanced Th1/Th2 response to rFPV [22] and PRRSV vaccine [23].
Using KEGG analysis, ‘TNF signaling pathway’, ‘NF-κB pathway’, ‘NLR pathway’, and ‘MAPK pathway’ were identified as the main im- mune-related pathways of the DEGs in RAW264.7 cells induced by AJSAF. All four pathways contained 2 common genes IL-1β and TNF. Furthermore, IL-1β and TNF were also identified as the core genes in the network of immune-related DEGs in AJSAF-activated RAW264.7 cells. TNF-α was reported to be a key mediator of the interaction be- tween macrophages and epithelial cells necessary for induction of cy- tokine responses [49]. The upstream analysis identified TNF, IL-1β and ERK1/2 as core regulators in AJSAF-activated RAW264.7 cells. IPA pathway analysis revealed that AJSAF activated ERK cascade and its downstream CREB in RAW264.7 cells via Ca2+ pathway.
LncRNAs are important regulators of mRNA expression and achieve regulatory specificity through interacting with RNA, DNA, and RBPs [50–52]. In this study, the microarray analysis revealed that AJSAF induced 103 differentially expressed lncRNAs in RAW264.7 cells. Based on the protein-coding potential, evolutionary conservation, and qRT- PCR verification, A_30_P01018532 was selected for further annotation and functional prediction. Three putative regulatory models such as RNA–RNA, RNA–DNA, and RNA–protein interactions were employed to predict the target gene of A_30_P01018532. Among 104 co-expressed mRNAs, 99 were identified as potential target genes of A_30_P01018532. GO analysis of these putative target mRNAs revealed that A_30_P01018532 involved in ‘inflammatory response’, ‘immune response’, ‘cellular response to IL-1’, ‘regulation of ERK1 and ERK2 cascade’, ‘regulation of NF-κB activity’, and ‘regulation of apoptotic process’. The KEGG pathway analysis indicated that ‘TNF signaling pathway’, ‘cytokine-cytokine receptor interaction’, ‘NF-κB pathway’, and ‘Jak-STAT pathway’ involved in activation of RAW264.7 cells in- duced by AJSAF. These results were consistent with functional char- acterization of AJSAF-activated macrophages, suggesting the core reg- ulatory roles of A_30_P01018532 in macrophage activation by AJSAF. Because of its location in the nucleus, A_30_P01018532 could reg- ulate the transcription of target mRNAs via base-pair interactions. MRLN (2310015B20Rik) exon 3 could bind with A_30_P01018532.

MRLN was reported to involve in the regulation of Ca2+ uptake into the sarcoplasmic reticulum [53]. RNA–DNA interaction analysis revealed that A_30_P01018532 could form duplex base-pairing interactions with the promoter of 24 DEGs such as TNF, CLEC2D, calcium/calmodulin- dependent serine protein kinase (CASK), and myristoylated alanine rich protein C substrate-like 1 (MARCKSL1). It was reported that CASK in- teracted with Ca2+ pump 4b/CI [54] and MARCKSL1 had a very strong affinity for calcium-bound calmodulin [55,56]. Therefore, it was speculated that A_30_P01018532 might be a regulator in AJSAF-in- duced Ca2+ signaling. We also performed RNA–protein interaction prediction to figure out 32 RBPs, which involved in the transcription of 90 target genes. A_30_P01018532 contained the motifs bound to ZFP36, KHSRP, EIF4B, MBNAL, and FUS, which formed a stable long stem of the secondary structure. ZFP36 and KHSRP were at the center of A_30_P01018532–RBP–mRNA networks. ZFP36 was reported to reg- ulate CREB activity [57] and bind to the A+U-rich element in the TNF- α 3′-untranslated region which promoted deadenylation and destabili- zation of the TNF-α mRNA [58]. KHSRP is an important regulator of pro-inflammatory genes TNF-α, IL-8, and iNOS [59]. Therefore, A_30_P01018532 could mediate AJSAF-induced activation of RAW264.7 cells through interacting with ZFP36 and KHSRP.
AJSAF induced the generation of ROS in RAW264.7 cells. ROS exert positive or negative modulation on the activity of different calcium channels. GO molecular function analysis of DEGs in RAW264.7 cells induced by AJSAF identified MARCKS, MYH3, SPHK1, MARCKSL1, and MYLK2 enriched in ‘calmodulin binding’. In this study, AJSAF induced a sustained intracellular Ca2+ rise in RAW264.7 cells. Moreover, Ca2+ chelator BAPTA-AM significantly reduced AJSAF-induced expression of TNF-α, CCL2, CXCL2, CCL22, and A_30_P01018532. These results suggested that Ca2+ pathway was involved in AJSAF-mediated mac- rophage activation.
Ca2+ signal induced the phosphorylation of ERK1/2 and CREB [60,61]. GO biological process and KEGG analysis of the DEGs in RAW264.7 cells induced by AJSAF revealed that ERK1/2 cascade was involved in AJSAF-mediated molecular mechanism. The upstream analysis also identified ERK1/2 as a core upstream regulator in AJSAF- activated RAW264.7 cells, regulating DEGs such as SOCS3, MYC, IL-1β, CXCL2, TNF, CCL2, MMP9, CCL4, and SAA3. Minutes after AJSAF
treatment, the expression levels of ERK1/2 and CREB phosphorylation were up-regulated. AJSAF-induced TNF-α, CCL2, CXCL2, CCL22, and A_30_P01018532 expression levels in RAW264.7 cells were also sig- nificantly suppressed by ERK1/2 inhibitor (PD98059) and CREB in- hibitor (KG-501). Thus, AJSAF-induced intracellular Ca2+ could pro- mote the phosphorylation of ERK1/2 and CREB resulting in the activation of macrophages.
Fig. 7. Roles of Ca2+–ERK1/2–CREB pathway in activation of RAW264.7 cells by AJSAF. (A and B) RAW264.7 cells were incubated with medium or AJSAF (150, 200, or 250 μg/ml), and then collected to detect the levels of ROS (A, 2 h) and intracellular free calcium (B, 1–8 h). (C and D) After pre-incubation with or without BAPTA-AM (25 μM) for 30 min, RAW264.7 cells were treated with AJSAF (200 μg/ml) for 2 or 24 h, and then the gene expression levels (C, 2 h) and the contents in the culture supernatants (D, 24 h) of TNF-α, CCL22, CXCL2, CCL22, and A_30_P01018532 were detected by qRT-PCR and ELISA, respectively. (E) RAW264.7 cells were treated with AJSAF (200 μg/ml) for 0, 15, 30, 60, and 120 min, the protein levels were detected by Western blotting. The figure shown is representative of three independent experiments. (F–H) After pre-incubation with or without PD98059 for 30 min or KG-501 for 1 h, RAW264.7 cells were treated with medium or AJSAF (200 μg/ml) for 2 or 24 h, and then the gene expression levels (F and G, 2 h) and the contents in the culture supernatants (H, 24 h) of TNF-α, CCL2, CXCL2, CCL22, and A_30_P01018532 were detected by qRT-PCR and ELISA, respectively. The values are presented as mean ± SD (n = 3). Significant differences with control cells (0 μg/ml) were designated as *P < 0.05, **P < 0.01 and ***P < 0.001. Fig. 8. Possible mechanisms in activation of RAW264.7 cells induced by AJSAF and action mode of A_30_P01018532. AJSAF activates RAW264.7 cells via Ca2+–ERK1/2–CREB pathway resulting in up-regulation of the mRNA expression of cytokine and chemokines. A_30_P01018532 might participate in Ca2+–ERK1/ 2–CREB pathway by regulating its target gene through interaction with DNA (A), mRNA (B), or RBP (C). In conclusion, we first investigated the expression profile of mRNAs and lncRNAs in RAW264.7 cells activated by AJSAF. Secondly, our experimental data revealed AJSAF could activate RAW264.7 cells via Ca2+–ERK1/2–CREB signaling. Furthermore, A_30_P01018532 was predicted to participate in Ca2+–ERK1/2–CREB pathway by regulating its target mRNAs through interaction with DNA, mRNA like MRLN or RBP like KHSRP (Fig. 8). This study might provide insights into the molecular mechanisms of action of AJSAF. Further studies are still re- quired to elucidate the biological functions of A_30_P01018532 and its mechanisms. Acknowledgments This work was supported by Grant-in-Aid from the National Key R& D Program of China (2017YFD0501505), the National Natural Science Foundation of China (Nos. 31272597, 31472229, and 31772783), the Zhejiang Provincial Natural Science Foundation of China (No. LZ13C180001), and the Dabeinong Funds for Discipline Development and Talent Training in Zhejiang University. 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