1 Introduction
Porcine deltacoronavirus (PDCoV) is a novel porcine enteropathogenic coronavirus that has been shown to be transmissible between species and can cause intestinal damage in pigs, chickens, and mice (Li et al., 2020a,b). More recently, PDCoV was detected and isolated from three children in Haiti who presented with acute febrile illness (Lednicky et al., 2021), highlighting the serious threat of PDCoV to human health. Some broad-spectrum antivirals, such as lithium chloride, diammonium glycyrrhizinate and remdesivir, are being investigated for their potential to treat PDCoV in vitro (Zhai et al., 2019; Brown et al., 2019). It has also been found that remdesivir has a relatively high therapeutic effect on PDCoV in vitro (Brown et al., 2019). There is no best choice for the prevention and treatment of PDCoV in animal models.
Selenium (Se) is an important micronutrient. It has many biological functions, including antioxidant, antiviral and immunomodulatory effects (Roman et al., 2014). There is increasing evidence that Se plays a chemopreventive role in cancer risk and incidence (Roman et al., 2014; Wallenberg et al., 2014) and viral diseases (Sepúlveda et al., 2002; Li et al., 2023; Sartori et al., 2016; Wang et al., 2020). It may play a chemopreventive role against cancer by scavenging reactive oxygen species (ROS), thereby preventing DNA damage and the onset of mutations (Selenius et al., 2010). Studies have shown that selenomethionine (SeMet) can inhibit PDCoV replication in LLC-PK cells in a dose-dependent manner (Ren et al., 2022). Our previous experiment showed that SeMet could alleviate the intestinal injury induced by PDCoV-infected piglets or mice (Li, 2021; Li et al., 2025). However, the possible mechanisms remain poorly understood.
In recent years, accumulating evidence has supported the idea that the gut microbiota plays an important role in the pathogenesis of PDCoV (Li et al., 2020a,b; Zhang et al., 2025; Zhang Y. et al., 2024). PDCoV infection induces an imbalance in the gut microbiota, reducing bacterial diversity (Li et al., 2020a), altering metabolites, and inducing inflammatory responses (Li et al., 2020b). Thus, gut barrier damage induced by PDCoV-infected piglets can be attenuated by modulating the gut microbiota (Zhang et al., 2025). Our previous studies have shown that FMT can alleviate the clinical signs of PDCoV infection in piglets by modulating the intestinal flora and the composition of the intestinal barrier, thereby reducing the inflammatory response (Zhang et al., 2025). In addition, host Se levels can also influence the composition of the intestinal microbiota and the colonization of the gastrointestinal tract, thereby affecting selenium status (Kasaikina et al., 2011; Ferreira et al., 2021). Feeding Se-enriched supplements to mice can regulate the gut microbiota and host metabolism and reduce intestinal inflammation in mice (Wang H. et al., 2024). However, the potential effect of SeMet on the gut microbiota and its metabolites in PDCoV-infected mice has not been investigated.
The current study used C57BL/6 (C57) mice as a model of PDCoV infection to explore the effect of SeMet on intestinal microbiota and its metabolites in mice infected with PDCoV.
2 Materials and methods
2.1 Virus and animals
The virulent PDCoV HNZK-02-P5 strain was provided by Professor Zhanyong Wei in Henan Agricultural University.
Four-week-old C57 mice (female, approximately 16 g) were randomly divided into 3 groups (10 mice per group), namely Control group, PDCoV group, and SeMet+PDCoV group. These mice were supplemented with SeMet and subjected to viral infection experiments as previously described (Li et al., 2025). The mice in the SeMet + PDCoV group were fed with a SeMet-treated diet (0.3 mg/kg Se) daily from day 1 until the end of the experiment. On day 23, the mice in the PDCoV group and the SeMet+PDCoV group were inoculated intragastrically with 300 μL per mouse of PDCoV HNZK-02-P5 strain (1 × 106 TCID50), and the mice in the Control group were inoculated with the same volume of Dulbecco's modified Eagle's medium (DMEM). On day 28, all mice in the experimental groups were necropsied. The intestinal tissues were collected to measure viral load and conduct histopathological analysis. The colonic contents were collected and stored at −80 °C until high-throughput sequencing (Illumina MiSeq) of the 16S rRNA gene and LC-MS/MS metabolomics were assessed. All operations were approved by the Medical Ethics Committee of Yan'an University Affiliated Hospital (Yan'an, China).
2.2 DNA extraction from the colonic content and 16S rRNA sequencing
To analyse the composition of the microbial community, 16S rRNA sequencing was performed on samples of the mouse colon. The FastDNA®SPIN Kit (MP Bio, United States) was used to extract microbial DNA according to the manufacturer's instructions. DNA concentration was assessed using a NanoDrop 2,000 UV-vis spectrophotometer (Thermo Scientific, Wilmington, USA). The integrity of genomic DNA was assessed by 1.0% agarose gel electrophoresis. All DNA was stored at −20 °C until further analysis.
For 16S rRNA sequencing, the hypervariable regions V3-V4 of the 16S rRNA gene were amplified using universal primers 338F and 806R (Mori et al., 2013). The products were sequenced on the Illumina MiSeq (Illumina, San Diego) and the sequences were analyzed using standard protocols provided by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China).
2.3 Metabolomic signatures
UHPLC-Q Exactive HF-X technology was used to analyse the metabolic profiles of the control, PDCoV, and SeMet groups. A thawed sample (50 mg) was accurately weighed and immediately ground to powder.
The sample was homogenized in 1 mL of pre-cooled methanol/ddH2O solvent (4:1, v/v). The mixture was treated with cryogenic ultrasound at 5 °C for 30 min, placed at −20 °C for 30 min and then centrifuged at 4 °C and 13,000 g for 15 min. The supernatant was extracted and lyophilised using a vacuum lyophiliser, and the dried sample was redissolved in 100 μL acetonitrile/ddH2O solvent (1:1, v/v) for homogenisation. After centrifugation at 4 °C and 14,000 rpm for 15 min, the supernatant was collected for subsequent analyses. Additional quality control (QC) samples were prepared to monitor instrument stability and repeatability.
The UHPLC-Q Exactive HF-X system was analyzed for LC-MS/MS using the following LC conditions: Mobile phase A, 0.1% formic acid in water: acetonitrile (95:5, v/v), mobile phase B, 0.1% formic acid in acetonitrile: isopropanol: water (47.5:47.5, v/v), flow rate, 0.4 mL/min. MS conditions were set as follows: Positive and negative ion scan mode is used to collect the sample quality spectrum signal, and the quality scan range is m/z: 70–1,050. The floating ion spray voltage was 3,500 V and 2,800 V for positive and negative modes. The sheath gas, auxiliary heating gas, and ion source heating temperature were 40 psi, 10 psi, and 400 °C respectively. The cyclic collision energy, MS1 resolution and MS2 resolution were 20-40-60 V, 70,000 and 17,500 respectively.
2.4 Combined different species and metabolome analyses
A comprehensive analysis was conducted to examine both different species and differentially accumulated metabolites. Pearson's correlation analysis was performed for different species and metabolites detected in the Control, PDCoV, and SeMet + PDCoV groups by Euclidean distance.
2.5 Bioinformatic analysis of the sequencing data
Bioinformatics, statistical, and visual analyses were performed using QIIME and the R package (v3.1.1). Sequences were clustered into operational taxonomic units (OTUs) using UPARSE (version 3.3.1) with a 97% similarity cut-off and used for further analysis of rarefaction curves, Venn diagrams, and alpha diversity indices (Shannon, Simpson, ACE, Chao, and Good's coverage) using Mothur software v1.30.1. Beta diversity was based on weighted UniFrac distance analysis. At the phylum, family, and genus levels, community bar plots were used to show the structural composition of communities in different subgroups.
Metabolite data processing was performed using Progenesis QI software (Waters Corporation, Milford, USA). Simultaneously, metabolites were identified by database searches, the main databases being HMDB, Metlin, and MajorBio Database. Based on the variable importance in projection (VIP) obtained by the OPLS-DA model, the metabolites with VIP > 1 and P < 0.05 were determined as significantly different metabolites, with the p-value generated by Student's t-test. Differential metabolites were mapped to their biochemical pathways using pathway and enrichment analysis based on the KEGG database (http://www.genome.jp/kegg/). Spearman correlation analysis was performed on the different species and metabolites obtained by difference analysis.
2.6 Statistical analysis
One-way analysis of variance (ANOVA) was performed to analyse the significance between groups, and the Tukey post hoc test was used for multiple comparisons. GraphPad Prism 6.0 was used for statistical tests and graphs. Results are presented as mean ± standard deviation (SD). Statistical details are provided in the figure legends. P < 0.05 was considered statistically significant, *, P < 0.05; **, P < 0.01.
4 Discussion
As a devastating enteropathogenic animal coronavirus, PDCoV could cause intestinal damage in pigs, chickens, and mice, severely affecting their survival (Liang et al., 2019; Li et al., 2020a; Hu et al., 2016; Zhang H. et al., 2022). This leads to significant losses in the livestock industry and economy, as well as posing a serious threat to global public health. Consequently, the search for effective antiviral strategies has become a focal point of public interest. Se, as an important trace element, has attracted attention in recent years for its remarkable antiviral properties. SeMet could alleviate PDCoV-induced intestine injury in piglets and mice, mainly by improving histopathological parameters (Li, 2021; Li et al., 2025). Intestinal health is influenced by lifestyle, diet, and the structure of intestinal microbiota (Moco et al., 2012). Se can interact with gut microbiota, affecting the host's health (Kasaikina et al., 2011; Qiao et al., 2022; Zhang et al., 2021; Zhang H. et al., 2024). In addition, gut microbiota may contribute to the pathogenesis of PDCoV (Zhang J. et al., 2022; Zhang Y. et al., 2024), and the clinical symptoms of PDCoV infection in piglets can be alleviated by regulating intestinal flora (Zhang et al., 2025). In order to explore whether the effects of SeMet improving intestine injury are related to the intestinal microbiota and metabolites, the gut microbiota's diversity and metabolomics in the colon of mice were evaluated. The results showed that SeMet could regulate the intestinal microbiota and metabolites in mice infected with PDCoV. The analysis also revealed a significant correlation between bacterial genera and metabolites.
The intestine is the habitat of a variety of dynamic microbial ecosystems. The diversity of intestinal microbiota is one of the most important elements in resisting the colonization of invading pathogens (Keesing et al., 2010). Studies have shown that PDCoV could significantly reduce the richness and diversity of intestinal microbiota in piglets (Li et al., 2020a). Interestingly, a significant increase in diversity was shown in the PDCoV-infected SPF chickens at 5 dpi (Li et al., 2020b). In this study, there were no significant differences in microbiota diversity among the Control group, the PDCoV group, and the SeMet + PDCoV group. The conflicting results from different studies may be due to differences in species susceptibility to PDCoV. In addition, the microbiota dysbiosis index was higher after PDCoV infection and significantly improved after SeMet supplementation, suggesting that PDCoV infection disrupts the structure of the intestinal flora and that SeMet alleviates PDCoV-induced intestinal dysbiosis.
The normal gut symbionts form a stable community that resists the invasion of pathogens or non-native bacteria and ensures colonization resistance (Freter, 1955; Bohnhoff et al., 1954; Stecher and Hardt, 2008). In terms of species composition (Phylum, Family, and Genus), PDCoV changed the structure of the gut microbiota. Interestingly, the SeMet treatment restored the changes in gut microbiota closer to the control group. At the Phylum level, the main core of the gut microbiota is composed of Bacteroidetes and Firmicutes (Beheshti-Maal et al., 2021). The change of the Firmicutes/Bacteroidetes ratio may be an important indicator of intestinal ecological disorder (Li et al., 2020a,b), which is usually associated with disease susceptibility (Ley et al., 2006). The results of this study were similar to those of previous research. Interestingly, at the family level, we found that the relative abundance of probiotics (Lachnospiraceae, Muribaculaceae, and Akkermansiaceae) in the PDCoV group had increased, accompanied by a decrease in probiotics (Lactobacillaceae, Bifidobacteriaceae, and norank_o_Clostridia UCG-014). The Lachnospiraceae, as an important member of Firmicutes, exists widely in the human gut and is considered to be potentially beneficial. However, Lachnospiraceae abundance also increases in the intestinal lumen of subjects with different diseases, although the taxa of this family have repeatedly demonstrated their ability to produce beneficial metabolites for their host (Vacca et al., 2020). The Muribaculaceae family is a group of bacteria belonging to the Bacteroidetes order. This family is attached to the mucous layer and shows a strong correlation with inflammatory bowel disease (Lee et al., 2019). Clostridia UCG-014 belongs to the Firmicutes phylum, and its increased abundance helps to restore the gut microbiome's homeostasis, thereby regulating metabolism and alleviating hyperlipidaemia (Duan et al., 2024).
In addition, at the Genus level, there appear to be complex interactions between viral strains and resident bacteria. Lactobacillus and Bifidobacterium, as the main probiotic genera, were significantly decreased in the PDCoV group. Previous research indicated that piglets infected with PDCoV HNZK-P5 showed a substantial reduction in lactobacillus (Zhang J. et al., 2022; Zhang Y. et al., 2024). Probiotics are an important part of the intestinal mucosal barrier, which can effectively resist the penetration of pathogenic microorganisms (Cai et al., 2020), regulate intestinal flora (Cai et al., 2020), produce antiviral metabolites (Al Kassaa et al., 2014), and inhibit the production of pro-inflammatory cytokines (Ghadimi et al., 2012; Hedin et al., 2007). Notably, the abundance of certain probiotics, including Lachnospiraceae_NK4A136_group and Akkermansia, increased significantly in the PDCoV group. We hypothesize that this may be related to competition between microorganisms. In conclusion, SeMet was found to effectively modulate PDCoV-induced changes in the gut microbiota.
Metabolites are often considered as a bridge between genotype and phenotype, and changes in metabolite levels can directly reveal the function of genes, thus revealing biochemical and molecular mechanisms more effectively (Shen et al., 2023). Changes in metabolic status are caused by gut microbial imbalances in piglets infected with PDCoV (Shi et al., 2024). We hypothesized that the effect of SeMet on the intestinal microbiota in PDCoV-infected mice could extend to impact the intestinal metabolic profile. Metabolic profiling analysis showed that PDCoV infection resulted in metabolic disorders, whereas SeMet treatment significantly mitigated PDCoV-induced metabolic alterations. Amino acids have a variety of important functions in living organisms. They play a role in the synthesis of proteins and other important biomolecules, as well as providing intermediate metabolites for the tricarboxylic acid cycle and gluconeogenesis. Amino acids are involved in the process of viral infection and innate immunity, which is a complex process that involves many different factors (Tomé, 2021). PDCoV infection resulted in changes in the expression patterns of a variety of amino acids (Wang G. et al., 2024). In the present study, we found that the levels of both dipeptides were decreased in the PDCoV group, including Phe-Pro and Tyr-Pro. Research has shown that Phe-Pro is the only in vivo active cholesterol-lowering dipeptide among 400 kinds of dipeptides (Banno et al., 2019). PDCoV infection could cause a disturbance in cholesterol metabolism, and further promote its own replication (Zhang J. et al., 2022; Barrantes, 2022). Interestingly, PDCoV infection increased Tyr, Trp and Glu metabolites. This may be to regulate the tricarboxylic acid cycle within the host cell in order to provide amino acids and energy for viral replication (Wang G. et al., 2024). In addition, we also noted an increase in the level of Octadecanamide during PDCoV infection. Fatty amides are well-known mediators of immune response (Lowin et al., 2019; Servettaz et al., 2010). We speculated that the increase in octadecanamide levels was correlated with altered immunity during PDCoV infection.
Pathway enrichment analysis revealed that SeMet supplementation altered the dysregulation of metabolic pathways triggered by PDCoV, including inflammatory mediator regulation of TRP channels, Fc epsilon Rl signaling pathway, and Tropane, piperidine and pyridine alkaloid biosynthesis. The activity of TRPA1 channels and Fc ε [var epsilon] RI signaling has been shown to mediate proinflammatory cytokine responses (Lee et al., 2016; Wu et al., 2021; Péterfy et al., 2008; Li et al., 2021). Supplementation of SeMet down-regulated the inflammatory mediator regulation of TRP channels and Fc epsilon Rl signaling pathways, which may be a cascade reaction of SeMet's inhibition of inflammatory responses. Additionally, SeMet supplementation also up-regulated in Tropane, piperidine and pyridine alkaloid biosynthesis, the content of which had a significant positive correlation with antioxidant activity (Luo et al., 2023). This is consistent with the antioxidant effect of SeMet. Furthermore, this study revealed distinct associations between metabolites and gut microbiota, indicating that perturbations in the gut microbiota are closely related to alterations in the metabolic phenotype.