Transcriptional profiling of host cell responses to encephalomyocarditis virus (EMCV)

To depict the global picture of host transcriptomic response to EMCV infection, and to identify host factors involved in the infection course, we performed RNA-seq on Illumina platform using cDNA libraries of EMCV infected and mock infected BHK-21 cells. EMCV infected cells were harvested at 12, 24, and 30 hpi. An average of 115 million reads were generated from each sample, and an average of 114 million reads passed the quality control. 72.6% of clean reads were mapped to the hamster genome in the mock infected group. In 24 hpi group, 65.3% and 7.2% of clean reads were aligned to hamster genome and EMCV genome respectively, indicating viral RNA replication before 24 hpi. In 30 hpi group, 41.5% of clean reads were mapped to EMCV genome, indicating active replication of the viral RNA (Table 1). The amounts of EMCV copies were quantified by real-time PCR, and EMCV infection was also validated. The viral RNA levels increased rapidly during infection (Fig. 1).

The number of DEGs (≥1.5fold, with P value < 0.05) at each time point was shown in Table 2. 237, 241, and 207 genes were found differentially expressed at 12, 24, and 30 hpi respectively (Additional file 1: Figure S1, Table 2). There was little difference between the total number of DEGs at each time point, however, the percentage of down regulated genes reduced drastically as the infection time grew. At 30 hpi, only 7.7% DEGs were down regulated. Even at 12 hpi, majority of the DEGs were up regulated. Moreover, DEGs with a fold change of larger than 2 at 30 hpi were much more than that at other time points (12 hpi and 24 hpi) (Table 2).

DEG data were further subjected to Gene Ontology (GO) and KEGG pathway analysis. GO terms classified the functions of all differentially expressed transcripts, producing 41 functional types at 30 hpi, including immune system process, metabolic process, response to stimulus, and signaling (Fig. 2). We designated three functional categories of interest based on GO functional classification and KEGG pathway enrichment (Figs. 2 and 3): host defense, signaling and metabolism. Representative DEGs involved in host defense at the three time points, as well as the KEGG pathways which the DEGs belong to, were listed in Table 3. We identified several innate immunity pathways responsive to EMCV infection, including RIG-I-like receptor signaling pathway, TGF-beta signaling pathway, and NF-kappa B signaling pathway (Fig. 3, Table 3).

LGP2, which is demonstrated to coordinate with MDA5 [23], showed a fold decrease at 12 h after EMCV infection. Genomic RNA of EMCV is considered to recognized by cellular RLR receptor MDA5, not RIG-I [24]. Mx dynamin-like GTPases have been shown to have antiviral activity in type I and type III interferon systems. Recent data revealed that human MX2 served as a restriction factor for HIV-1 and other primate lentiviruses [25]. Here we showed that MX2 was down-regulated in EMCV infected BHK-21 cells at 12 hpi. The above results indicated a quick restriction of host antiviral activity by EMCV. On the other hand, antiviral genes, TAK1 and complement C3, were found up-regulated in this study at 24 hpi and 30 hpi, suggesting host defense responses. Tumor necrosis factor receptor superfamily, member 25 (TNFRSF25) transcript was discovered decreased remarkably at 30 hpi. The same TNFRSF25 was also found down-regulated in Japanese encephalitis virus infected mouse spleens [26]. Recent data indicated that knockdown of TNFRSF25 led to an increased anti-apoptotic potential [27]. EMCV is a lytic virus causing necrotic cell death, which counteracts host cell antiviral immunity by inhibiting apoptosis. Down-regulation of TNFRSF25 might contribute to this inhibition. TNFAIP3 (A20) transcript expression was found increased at 24 hpi and 30 hpi, which functions in negative regulation of NF-kappa B signaling (Table 3). A20 was demonstrated to inhibit TNF induced apoptosis [28]. Furthermore, a recent study showed that deficiency of A20 in myeloid cells improved the resistance against influenza infection, by an enhanced innate response [29]. Thus, overexpression of A20 probably counteracted the innate immune responses induced by EMCV infection, however, still needs further investigation. These findings indicated that EMCV also restricted host defense at later infection time points.

Representative DEGs involved in signaling and the KEGG pathways which the DEGs belong to, were listed in Additional file 2: Table S1. Representative DEGs involved in metabolism as well as the KEGG pathways which the DEGs belong to, were listed in Additional file 3: Table S2. Several signaling pathways, including MAPK signaling pathway, PPAR signaling pathway, mTOR signaling pathway, were widely affected subsequent to EMCV infection (Additional file 2: Table S1, Fig. 3). The differential analysis also showed that multiple metabolism pathways, especially lipid metabolism were responsive to EMCV, including Terpenoid backbone biosynthesis, Steroid biosynthesis, Biosynthesis of unsaturated fatty acids, and Glycerophospholipid metabolism (Additional file 3: Table S2, Fig. 3). Replication of EMCV RNA needs to modulate host cell lipid landscape [17]. Following the deep analysis of DEGs, we saw that the transcriptional level of host lipid metabolism were changed by EMCV.

To analyze dynamic gene expression at series time points (0, 12, 24, and 30 hpi) during EMCV infection with RNA-seq DEG data, we performed pattern analysis using STEM (Short Time-series Expression Miner) software (mock infection was designated as 0 hpi). STEM is used to analyze short time series gene expression data. The results revealed four significant expression patterns (P < 0.05): 1. decreasing at 12 hpi and then increasing (red, including IL18, LGP2, A20 and TAK1); 2. increasing at 12 hpi and then decreasing (green, including WNT5A); 3. gradually increasing, part of the genes decreasing at 12 hpi, and then increasing gradually at later time points after infection (blue, including PLA2G2A, TXNIP, C3, TRAF2, PTGS2, CLK1, and ZFP36); 4. decreasing at 12 hpi and then increasing, but back to expression level at 0 hpi (yellow, including MRGPRG) (Additional file 4: Table S3, Fig. 4). The STEM analysis was also supported by real-time PCR later. Several antiviral genes, including LGP2, TAK1, ZFP36 and C3 decreased at 12 hpi, then increased, of which C3 increased gradually at later time after 12 hpi. These results suggested that 12 hpi was an important time point for expression pattern change, probably indicating antagonism between virus and host. EMCV might immediately reduce host antiviral gene expression to restrict antiviral activity, however, the host cells were able to make a response later to counteract with or defeat the restriction activity induced by EMCV, although were not capable of inhibiting the replication of the virus.

Eighteen genes from the three functional categories were selected for validation of our RNA-seq DEG data by Real-time RT-qPCR (Additional file 5: Table S4). Gene expression profiles of Real-time RT-qPCR were compared with those of RNA-seq. Among the 18 genes, 16 genes exhibited similar expression patterns as compared with RNA-seq data. The other two genes (DDX3X and HES2) didn't have obvious expression changes based on RT-qPCR results. Fourteen of the verified differential expression genes were up regulated, and only two genes, TNFRSF25 and WNT9A down regulated. ZFP36, a RNA binding protein, which targets HIV RNA for degradation [30], showed the most significant changes in differential expression (Fig. 5). Nevertheless, the specific role of ZFP36 in EMCV infection is unclear. Moreover, short time series gene expression pattern was also verified by real-time PCR (Additional file 6: Figure S2).