A total of 20 BALB/c male mice (6–8 weeks old, 25–30 g) were obtained from the Experimental Animal Center of Qinglongshan (Nanjing, China), and were housed in pathogen-free mouse colonies with a 12-h light, 12-h dark cycle. Mice received standard chow diet, with free access to drinking water between 25 and 26°C. Relative humidity was maintained between 60 and 70%, and padding was changed twice/week. All animal experiments were performed according to the guidelines for the Care and Use of Laboratory Animals (Ministry of Health, China, 1998). All experimental protocols were approved by the Animal Ethics Committee of Yijishan Hospital (Wuhu, Anhui, China).

Bone marrow-derived macrophages (BMDMs) were isolated from BALB/c mice by flushing the femurs with Dulbecco's modified Eagle's medium (DMEM; HyClone; GE Healthcare, Chicago, IL, USA) according to our previous studies (6,25). Ethical approval was provided by the Animal Ethical Committee of Yijishan Hospital. Macrophages plated on six-well plates (1×10⁶ cells/well) were maintained in DMEM supplemented with 20% fetal bovine serum (FBS; Gibco; Thermo Fisher Scientific, Inc., Waltham, MA, USA) and 20% L929 supernatant at 37°C and 5% CO₂ (26). Following 7 days in culture, the medium was removed, and the cells were cultured in RPMI-1640 (HyClone; GE Healthcare) supplemented with 10% FBS for an additional 24 h. Macrophages were then stimulated for 48 h in DMEM/10% FBS containing either 100 ng/ml LPS and 20 ng/ml IFN-γ (for M1 polarization) or 20 ng/ml IL-4 (for M2 polarization), as described previously (6,25).

BMDMs were collected following 48 h culture with polarization stimuli, and total RNA was extracted using TRIzol (Invitrogen; Thermo Fisher Scientific, Inc.), according to the manufacturer's instructions. RNA quantity and quality were measured using a NanoDrop 2000 (Thermo Fisher Scientific, Inc.), and RNA integrity was assessed using an Agilent Bioanalyzer 2100 (Agilent Technologies, Inc., Santa Clara, CA, USA) and denaturing agarose gel electrophoresis. Total RNA was further purified using an RNeasy Mini kit and RNase-Free DNase set (both from Qiagen GmbH, Hilden, Germany).

Total RNA from each sample was amplified and labeled by using a Low Input Quick Amp WT Labeling kit (Agilent Technologies), following the manufacturer's instructions. Labeled cRNA was purified using an RNeasy Mini kit (Qiagen GmbH). The concentration and specific activity of the labeled cRNAs (pmol Cy3/µg cRNA) were measured using a NanoDrop 2000. Each microarray slide (catalog no. p/n G2534-60011/G2534-60014; Agilent Technologies Inc.) was hybridized with 1.65 µg Cy3-labeled cRNA using a gene expression hybridization kit (catalog no. p/n 5188–5242; Agilent Technologies, Inc.) in a hybridization oven (catalog no. p/n G2545A; Agilent Technologies, Inc.), according to the manufacturer's protocol. Following 17 h of hybridization, the slides were washed in staining dishes (Thermo Fisher Scientific, Inc.) with a gene expression wash buffer kit (catalog no. p/n 5188–5327; Agilent Technologies, Inc.), following the manufacturer's protocol. Next, the slides were scanned using an Agilent Microarray Scanner G2565C (Agilent Technologies, Inc.) with the following settings: Dye channel green, scan resolution 3 µm, PMT 100% and 20-bit scanning. The Agilent Feature Extraction software (version 10.7; Agilent Technologies, Inc.) was used to analyze the acquired array images. Quantile normalization and subsequent data processing were performed using GeneSpring software version 11.0 (Agilent Technologies, Inc.). DEGs were identified through fold change (>2-fold) filtering. Microarray analysis was performed by Shanghai Biotechnology Corporation (Shanghai, China). Array data were deposited at the Gene Expression Omnibus database of the National Center for Biotechnology Information (accession no. GSE81922).

To further understand the biological relevance and associated pathways of DEGs, functional enrichment analysis was performed using the Biological Network Gene Ontology (BiNGO; v3.0.3) and CluePedia (v1.0.4) web-based tools (27,28). BiNGO (http://www.psb.ugent.be/cbd/papers/BiNGO) is a tool that identifies Gene Ontology (GO) terms that are significantly overrepresented in a set of genes or a subgraph of a biological network. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy and takes advantage of Cytoscape's versatile visualization environment to produce an intuitive molecular interaction network. The CluePediaCytoscape plugin (v3.0.1; www.ici.upmc.fr/cluepedia) is a search tool for new markers that are potentially associated to pathways. A pathway-like visualization can be created using the Cerebral plugin (v2.8.2) layout (29). The threshold of hypergeometric distribution of functional annotation was 0.05.

Since genes act by interacting with other genes to accomplish their functions; the interaction networks of the candidate genes identified were further explored by bioinformatics analysis. In the present study, 18 macrophage polarization-associated genes identified by gene expression profiling (listed in Table I) were examined for gene interaction networks using the Search for the Retrieval of Interacting Genes/Proteins (STRING; v9.0) database (string-db.org) (30). This database provides information on both experimental and predicted interactions from varied sources, including computational prediction, literature mining and knowledge transfer between organisms and information aggregated from other primary databases. An extended network was constructed by setting the required confidence score to 0.400.

The threshold set for significant up- and downregulated DEGs in microarray data was >2-fold change and P<0.05. Data were expressed as the mean ± standard error of the mean. Statistical analysis was performed using a Student's t-test by using Graphpad Prism v5.0 (GraphPad Software, Inc., La Jolla, CA, USA) for comparison between two groups. P<0.05 was considered to indicate a statistically significant difference.

A box-plot was used to visualize the distributions of the intensities from all samples, and principal component analysis (PCA) was employed to perform an unsupervised examination of differences in the signals between M1 macrophages and M2 macrophages. As demonstrated in Fig. 1A, the distribution of the log2-ratio of the microarray intensity values in the six samples (three repeats for M1 and three repeats for M2 macrophages) was very similar following quantile normalization. The M1 macrophage samples were distinctly separated from the M2 macrophage samples in the PCA plots (Fig. 1B), suggesting a differential gene expression between M1 and M2 macrophages.

Based on a threshold set at >2-fold change and P<0.05 for the microarray data, a total of 1,253 differentially-expressed mRNAs were identified in M1 compared with M2 macrophage samples, of which 696 mRNAs were upregulated and 557 mRNAs were downregulated. A volcano plot illustrated the expression variance in the number of DEGs at different P-values and fold changes (Fig. 1C). Independent hierarchical clustering, visualized by a heat map (Fig. 1D), further confirmed that the identified DEGs were significantly distinct between the M1 and M2 groups.

To generate insights into the potential biological functions of DEGs, functional enrichment analysis was performed using GO and KEGG pathway terms and mapped in functional networks using the Cytoscape plug-ins, BiNGO and CluePedia. GO identified three categories: biological process, cellular component, and molecular function. Through GO analysis, 34 and 40 GO terms were significantly enriched for up- and downregulated DEGs, respectively, based on the setting threshold of P<0.05 and false discovery rate (FDR) <0.05 (Table II). The main GO categories were: Protein binding, regulation of biological process, response to stimulus, metabolic process and cell differentiation (Fig. 2). Moreover, 15 and four pathways were significantly enriched for up and downregulated DEGs, respectively, which could be categorized into 15 and four groups, respectively. The groups were classified according to their different functions and the function details are presented in Table III (left column). Some of the groups shared similar genes. The main pathways identified by KEGG were the HIF1 signaling pathway, TNF signaling pathway, innate immune system, apoptosis and cytokine-cytokine receptor interaction (Fig. 3).

An interaction network was constructed using STRING and then visualized using Cytoscape based on the macrophage polarization-associated genes identified in the present study. The network comprised 18 genes and 38 interactions (Fig. 4). The main type of gene associations was co-occurrence. Among these, IL6, TNF, IL1β, nitric oxide synthase 2 (NOS2) and SOCS3 were the key nodes, displaying the highest connectivity within the network (Fig. 4).