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Transcriptomic analysis reveals the effect of the exopolysaccharide of Psychrobacter sp. B-3 on gene expression in RAW264.7 macrophage cells
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Pingping ZHANG1, Jiang LI2, *, Leiye YU3, 4, Jingfang WEI1, Tong XU1, Guojie SUN1, *
Acta Oceanologica Sinica | 2018, 37(8) : 46 - 53
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Acta Oceanologica Sinica | 2018, 37(8): 46-53
• Marine Biology •
Transcriptomic analysis reveals the effect of the exopolysaccharide of Psychrobacter sp. B-3 on gene expression in RAW264.7 macrophage cells
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Pingping ZHANG1, Jiang LI2, *, Leiye YU3, 4, Jingfang WEI1, Tong XU1, Guojie SUN1, *
Affiliations
  • 1 College of Biological Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
  • 2 Key Laboratory of Marine Bioactive Substances, the First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China
  • 3 Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
  • 4 University of Chinese Academy of Sciences, Beijing 100049, China
Published: 2018-08-25 doi: 10.1007/s13131-018-1227-z
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B-3 exopolysaccharide is extracted from the Antarctic psychrophilic bacterium Psychrobacter sp. B-3. We have previously shown that it activates macrophages and affects their immunoregulatory activities. To determine what genes are affected during this process, we detected the genes differentially expressed in cells of RAW264.7 macrophages treated with B-3 exopolysaccharide by transcriptomic analysis. B-3 exopolysaccharide treatment caused differential expression of 420 genes, of which 178 were up-regulated and 242 were down-regulated. These genes were shown to be involved in many aspects of cell function, mainly metabolism and immunity. Genes were enriched in multiple immune-related pathways, and the most significantly enriched genes were involved in antigen processing and presentation pathways. The pathway in which differentially expressed genes were the most significantly enriched was the metabolic pathway; specifically, the expression of many metabolic enzyme genes was altered by B-3 exopolysaccharide treatment. Additionally, the genes involved in metabolisms of amino acids, carbohydrates, lipids and nucleotides, varied to certain degrees. B-3 exopolysaccharide, therefore, appears to directly affect the immune function of RAW264.7 macrophages as an immunostimulant, or to indirectly change intracellular metabolism. This is the first study to determine the effect of an Antarctic psychrophilic bacterial exopolysaccharide on RAW264.7 macrophages. Our findings provide an important reference for research into the regulation of macrophage immune function by different polysaccharides.

Psychrobacter sp. B-3  /  B-3 exopolysaccharide  /  RAW264.7 macrophage  /  differentially expressed genes  /  immunological pathway  /  metabolic pathway
Pingping ZHANG, Jiang LI, Leiye YU, Jingfang WEI, Tong XU, Guojie SUN. Transcriptomic analysis reveals the effect of the exopolysaccharide of Psychrobacter sp. B-3 on gene expression in RAW264.7 macrophage cells[J]. Acta Oceanologica Sinica, 2018 , 37 (8) : 46 -53 . DOI: 10.1007/s13131-018-1227-z
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1 Introduction
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Polysaccharides from fungi, plants, bacteria, and animals have been shown to exhibit a variety of biological activities, including antitumor (Wasser, 2002; Lemieszek and Rzeski, 2012), immunoregulatory (Wakabayashi et al., 1997; Wasser, 2002; Schepetkin and Quinn, 2006; Won et al., 2011), and antiviral functions (Arena et al., 2009; Wang et al., 2012). The immunoregulatory activity of polysaccharides, such as β-glucans from fungi and higher plants, has been an important topic for research, both in vitro and in vivo. Studies have shown that polysaccharides affect the production of cytokines and other molecules, thereby activating different immune cells, such as macrophages (Stier et al., 2014) and T cells (Inatsuka et al., 2013; Stier et al., 2014).
Many in vitro studies have determined the effects of polysaccharides on macrophage activation (Schepetkin and Quinn, 2006; Tseng et al., 2012; Li et al., 2017), and RAW264.7 macrophages have been widely used as a model system. Most in vitro studies regarding macrophage regulation (Leung et al., 2006; Li et al., 2007; Won et al., 2011; Reiber et al., 2017; Lee et al., 2018) have tested the following effects: secretion of cytokines and small molecules, phagocytic ability, differentiation state, and activation of signaling pathways and polysaccharide receptors on cell membranes. However, it is not clear whether polysaccharides solely affect the expression of specific immune-related molecules and signaling pathways in macrophages, or whether other genes are affected. A comprehensive understanding of polysaccharide-induced gene expression changes in activated macrophages would thus contribute to a better understanding of the underlying molecular mechanisms.
In recent years, high-throughput sequencing technology has been used to study the entire genome (Zhu et al., 2014; Han et al., 2011). As a form of deep sequencing technology, RNA sequencing has been widely applied to research at the transcriptional level (Wang et al., 2009; Landolt et al., 2016). For example, transcriptomic analysis has been used for research into quantitative gene expression regarding the biological processes of cells and tissues.
B-3 exopolysaccharide was extracted from an Antarctic psychrophilic bacterium, Psychrobacter sp. B-3, which was isolated from ice samples collected at the Uruguay Station (62°11'50.52"S, 58°55'50.4"W) during the 24th Chinese National Antarctic Research Expedition. We previously showed that B-3 exopolysaccharide is composed of two monosaccharides, including mannose and glucose, and has a molecular weight of 5 400 Da. An immunomodulation assay showed that B-3 exopolysaccharide activates RAW264.7 macrophages and affects their immunomodulatory activity, for example, by increasing the production of tumor necrosis factor-α and nitric oxide (NO) (Yu et al., 2016). Based on our previous work, the present study used transcriptomic analysis to analyze the effects of B-3 exopolysaccharide on the gene expression of RAW264.7 cells. This is the first time that the effect of an exopolysaccharide from an Antarctic bacterium on RAW264.7 macrophage global gene expression has been determined. These results will provide an important reference for in-depth and comprehensive studies regarding activated macrophages and the changes to their immunomodulatory activity that are induced by polysaccharides from various sources.
2 Materials and methods
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2.1 Sample handling
RAW264.7 cells were purchased from KeyGEN BioTECH (Nanjing, China), and cultured in DMEM medium (Gibco, Waltham, MA, USA) containing 10% heat-inactivated fetal bovine serum and 1% penicillin-streptomycin at 37°C in a humidified incubator with 5% CO2. Cells were seeded into six-well plates at a density of 2×106 cell/mL in 1 mL medium per well. Next, 3.3 μL of 3 mg/mL Polymyxin B (20 μg) was added to each well and incubated for 30 min. Then, 1 mL of diluted B-3 exopolysaccharide was added to two wells at a final concentration of 2 μg/mL, while 1 mL of complete medium was added to each of two other wells as the control group. The plates were incubated for 24 h because we previously showed that 0.02–20 μg/mL B-3 exopolysaccharide enhanced cell proliferation, phagocytosis, and NO production after stimulation for 24 h or 48 h (Yu et al., 2016).
2.2 RNA extraction and quality determination
Total RNA of four samples was extracted using an ultrapure RNA extraction kit (Kangwei Shiji Biological Technology Co., Ltd., Beijing, China) and stored at –80°C for later use. Before freezing, a sample was separated via 1% agarose gel electrophoresis at 180 V for 16 min. Concentration was measured by a NanoDrop spectrophotometer; integrity and purity were tested using the Agilent 2100 bioanalyzer and NanoDrop spectrophotometer, respectively.
2.3 cDNA library construction and sequencing
Oligo (dT) magnetic beads were used for mRNA enrichment. mRNA was broken into short pieces and used as a template. First-strand cDNA was synthesized from this using random hexamer primers; other components of PCR amplification were added for second-strand cDNA synthesis. Double-stranded cDNA was purified by AMPure XP beads, then ends were repaired, a poly-A tail was added, and sequencing joints were connected. AMPure XP beads were used to select the correct fragment sizes, and PCR was performed to enrich the cDNA library.
The Qubit2.0 fluorometer, Agilent 2100 bioanalyzer, and quantitative PCR were used respectively for initial quantitative detection, insert size detection, and accurate concentration quantification (effective concentration of the library >2 nmol/L). The SE50 strategy was used for sequencing. Sequencing and subsequent data analysis were performed by Novogene (Beijing, China).
2.4 Data analysis
The Illumina HiSeqTM2500 sequencing platform was used for high-throughput sequencing. The original raw image data file was converted by base calling into sequenced reads, using CASAVA base recognition. Clean reads were obtained by removing belt joints and low-quality reads, and then used for subsequent analysis. Filtered clean sequences were aligned with the reference sequence using TopHat software for genome positioning analysis. The positioning number (total mapped reads) and clean reads percentage were obtained. Reads per kilobase of transcript per million mapped reads (RPKM), which considers both the depth and length of the gene sequence, was used to estimate the gene expression level (Mortazavi et al., 2008).
We adopted DESeq (Anders and Huber, 2010) for the analysis of differentially expressed genes. The screening standard for differentially expressed genes was padj<0.05. Gene Ontology (GO) and Kyoko Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed for differentially expressed genes.
2.5 Gene function annotation
The following databases were used for gene function annotation: Ensembl (http://www.asia.ensembl.org), GO (http://www.geneontology.org), and KEGG (http://www. genome.jp/kegg/pathway.html).
2.6 Real-time PCR
RAW264.7 cells were stimulated by 2 μg/mL B-3 exopolysaccharide for 24 h. A total of 3 μg RNA per sample was reverse transcribed into cDNA using Invitrogen MMLV retrovirus kits, following manufacturer’s instructions. Quantitative PCR was performed using the IQ5 real-time multiple fluorescent quantitative PCR system (Bio-Rad, Hercules, CA, USA). Primer sequences are listed in Table A1. Reaction mixtures (15 μL) contained 4.5 μL double-distilled water, 7.5 μL 2X QuantiFast SYBR Green PCR Master Mix (Qiagen, Beijing, China), 1 μL upstream and downstream primers (6 μmol/L), and 1 μL cDNA. PCR conditions were as follows: 95°C for 5 min, followed by 40 cycles of 95°C for 10 s, and 60°C for 30 s. Each experiment was performed in triplicate. GAPDH was chosen as a reference gene. The 2–△△Ct method was used for relative quantitation.
2.7 Statistical analysis
SPSS17.0 software was used for statistical analysis, and significant differences between means were analyzed using Student’s t-test. Values of p<0.05 were regarded as statistically significant.
3 Results and discussion
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3.1 Evaluation and analysis of sequencing data
To study the effect of B-3 exopolysaccharide on RAW264.7 cell gene expression, cells were treated for 24 h with 2 μg/mL B-3 exopolysaccharide. Sequencing results are summarized in Table 1. The original data received from the control and experimental groups were 11564799, 12618276 and 13197215, 11969746, respectively, including clean sequences of 11558830, 12611092 and 13189345, 12611092, respectively. Each accounted for 99.9% of the original data, and the sequencing error rate was only 0.01%. The percentages of total sequence positioning to the genome for MRCN2, MRCN3, MRCP2, and MRCP3 were 94.35%, 94.22%, 93.68%, and 94.35%, respectively, while sequences with the sole position comprised 81.22%, 81.22% and 80.8%, 80.96%, respectively. Only a small number of sequences were found in multiple alignments. Comparing the distribution of reads with the genome, most sequences matched to exons, followed by introns and intergenic regions. Clean reads were used for subsequent GO and KEGG analyses of gene expression.
3.2 Quantitative analysis of gene expression and differentially expressed genes
RPKM was used to evaluate gene expression levels (Mortazavi et al., 2008) via the standard RPKM>1. HTSeq software was used to analyze gene expression levels of various samples via the union model. A Venn diagram of gene expression was drawn to depict the quantitative results of gene expression, as shown in Fig. 1. A total of 209 genes were only expressed in the B-3 exopolysaccharide-treated group (MRCP), while 214 were only expressed in the control group (MRCN); 10 567 genes were expressed in both groups. Differentially expressed genes were screened using the standard of genetic variations, padj<0.05, as a filter. A total of 420 genes were differentially expressed between MRCP and MRCN, of which 178 were up-regulated while 242 were down-regulated, as shown in Fig. 2. These genes were involved in diverse functions within the cell.
3.3 Real-time quantitative PCR validation
To verify our preliminary results that B-3 polysaccharide treatment changed the expression of an extensive proportion of RAW264.7 macrophage genes involved in different biochemical pathways, we selected four differentially expressed genes that are representative of different biochemical pathways for quantitative PCR analysis: Acy1 (encoding aminoacylase 1), Nos2, Pgm5 (encoding phosphoglucomutase 5), and Pik3c2b (encoding phosphoinositide-3-kinase, class 2, beta polypeptide). Acy1 and Pgm5 are mainly involved in substance metabolism, while Nos2 and Pik3c2b have roles in immune-related pathways. Our quantitative PCR results were consistent with differential expression findings. Nos2 and Acy1 were upregulated, while Pgm5 and Pik3c2b were downregulated after treatment with B-3 exopolysaccharide, as shown in Fig. 3.
3.4 GO enrichment analysis
GO is the international standard classification system of gene function that is mainly divided into the three categories of Cellular Component, Molecular Function, and Biological Process. GO enrichment analysis of differentially expressed genes identified in the present study was performed via GOseq software (Young et al., 2010), which annotated 319 differentially expressed genes. We selected the 30 most significantly enriched GO terms, as shown in Fig. 4. Among them, the immune response (GO: 0006955) and immune system process (GO: 0002376) were the most significantly enriched within the Biological Process category. Eleven genes in these two GO terms were differentially expressed, of which six were up-regulated and five were down-regulated. Dephosphorylation (GO: 0016311) was another significantly enriched GO term within Biological Process, while catalytic activity (GO: 0003824) was the most enriched GO term within Molecular Function. A total of 154 genes in this GO term were differentially expressed, of which 60 were up-regulated and 94 were down-regulated. Enzyme activities (GO: 0030234) was another significantly enriched GO term within Molecular Function, which revealed 16 GO differentially expressed genes (seven up-regulated and nine down-regulated), as well as GTP combination (GO: 0005525), which showed 16 GO differentially expressed genes (six up-regulated and 10 down-regulated), and amidine base nucleotide (GO: 0032561), which revealed 16 GO differentially expressed genes (six up-regulated and 10 down-regulated). Cell migration regulation, cell adhesion regulation, phosphatase activity, nicotinamide adenine dinucleotide (NAD) layer synthesis, metabolism, protein complex, and tumor necrosis factor receptor were also significantly enriched GO terms.
To determine which catalytic activities of enzymes were involved in the GO term catalytic activity (0003824), this term was further characterized. The differentially expressed gene enrichment numbers of this GO term are listed in Table 2. The three most enriched categories were hydrolase activity, transferase activity, and oxidoreductase activity. As examples, Nos2 encodes an oxidoreductase, Acy1 encodes a hydrolase, and Pik3c2b encodes a hydrolase/transferase. Genes with enzyme catalytic activity involved in this GO term participated in the synthesis, processing, and metabolism of a variety of cellular substances. This suggests that B-3 exopolysaccharide greatly changed the metabolism of RAW264.7 cells. This may be because B-3 exopolysaccharide was regarded as an immunostimulant or source of energy, so its ingestion by the cells induced downstream signaling. However, further studies are needed to confirm this.
3.5 KEGG enrichment analysis
KEGG mainly analyzes signaling pathways of differentially expressed genes (Kanehisa et al., 2008). In this study, the differentially expressed genes were enriched in 224 KEGG pathways, of which the most significantly enriched was the antigen processing and presentation pathway (mmu04612). Several genes were up-regulated in this pathway, including H2-D1 (encoding histocompatibility 2, D region locus 1), H2-T24 (encoding histocompatibility 2, T region locus 24), H2-T23 (encoding histocompatibility 2, T region locus 23), li (encoding CD74), Tapbp (encoding TAP binding protein), B2m (encoding beta-2 microglobulin), and Calr (encoding calreticulin). These are critical genes of major histocompatibility complex (MHC) Class I or Class II pathways (Vyas et al., 2008; Blum et al., 2013). This indicates that stimulation by B-3 exopolysaccharide enhanced the antigen processing and presentation abilities of macrophages through the MHC Class I and Class II pathways. Other immune-related pathways were also enriched (Table 3), which play an important role in initial and adaptive immunity. This shows that B-3 exopolysaccharide enhanced the immune reactivity of RAW264.7 cells. Moreover, several infection pathways were also significantly enriched, such as those involving hepatitis C (mmu05160) and measles (mmu05162).
Among the 224 enriched KEGG pathways, the most enriched was the metabolic pathway (mmu01100), involving 43 differentially expressed genes. This was consistent with the most enriched GO term of catalytic activity (0003824) in the GO results, as enzymes with various catalytic activities are keys to cell metabolism. These metabolic pathways involve a variety of substances, including amino acids, carbohydrates, lipids, vitamins, and nucleotides. Other enriched pathways included signaling pathways, cellular adhesion and migration, material synthesis, and transport. Differentially expressed genes induced by B-3 exopolysaccharide stimulation are therefore involved in multiple functions, including immunity, metabolism, disease, and signaling. The 20 most significantly enriched pathway entries are shown in Fig. 5.
KEGG enrichment analysis indicated that B-3 exopolysaccharide affected multiple immune-related pathways of macrophages, such as antigen processing and presentation, the Toll-like receptor signaling pathway, and leukocyte transendothelial migration. The Jak-STAT signaling pathway and NF-kappa B signaling pathway were also significantly enriched by B-3 stimulation. These two pathways affect macrophage proliferation, differentiation, and immune regulation (Rawlings et al., 2004; Hayden and Ghosh, 2011).
Among all differentially expressed genes, 154 were involved in the catalytic activity (0003824) GO term, and 43 were involved in metabolic pathways (mmu01100) of the KEGG analysis. This indicated that B-3 exopolysaccharide has a significant effect on RAW264.7 cell metabolism. Macrophage metabolism is known to be closely associated with immune function (Ghesquière et al., 2014; Kelly and O’Neill, 2015). For example, metabolites and metabolic enzymes regulate immune cell plasticity by affecting gene transcription, signaling pathways, or epigenetics (Ghesquière et al., 2014). Nos2 is a type of oxidoreductase and inducible NO synthase that catalyzes substrates to generate NO, while Acy1 is a hydrolase that catalyzes the hydrolysis of acylated L-amino acids into L-amino acids and an acyl group (https://en. wikipedia.org/wiki/ACY1). Acy1 also participates in the synthesis of L-arginine, which, together with NADPH, is a precursor molecule of NO (Aktan, 2004). NO and Nos2 play complex roles in innate and adaptive immunity (Bogdan, 2015), and immune cell metabolic activity is known to be closely linked to its immune function.
Our sequencing and quantitative PCR results showed that B-3 exopolysaccharide stimulation upregulated Nos2 and Acy1 in RAW264.7 cells. The resulting increased NO synthesis would further adjust the immune reactivity of RAW264.7 cells.
4 Conclusions
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B-3 exopolysaccharide stimulation was found to alter the expression of a large array of genes in RAW264.7 macrophages. It also dramatically changed the metabolism of various substances and affected multiple signaling pathways, especially immune-related pathways. These results reveal that changes in metabolic activity caused by B-3 exopolysaccharide are closely linked with its immune function. This study provides a reference for research into the regulation of macrophage immune function by polysaccharides.
Funding
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  • The Important National Science & Technology Specific Projects under contract No. 2011ZX8001-003; the National Natural Science Fundation of China under contract No. 40706053; Chinese Polar Environment Comprehensive Investigation & Assessment Programs under contract No. CHINARE2017-01-05.
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Appendix
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Year 2018 volume 37 Issue 8
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Article Info
doi: 10.1007/s13131-018-1227-z
  • Receive Date：2017-12-01
  • Online Date：2026-04-14
  • Published：2018-08-25
Article Data
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History
  • Received：2017-12-01
  • Accepted：2018-04-12
Funding
The Important National Science & Technology Specific Projects under contract No. 2011ZX8001-003; the National Natural Science Fundation of China under contract No. 40706053; Chinese Polar Environment Comprehensive Investigation & Assessment Programs under contract No. CHINARE2017-01-05.
Affiliations
    1 College of Biological Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
    2 Key Laboratory of Marine Bioactive Substances, the First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China
    3 Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
    4 University of Chinese Academy of Sciences, Beijing 100049, China

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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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