Porcine reproductive and respiratory syndrome virus (PRRSV) causes significant economic losses in the global swine industry due to its high genetic diversity and different virulence levels, which complicate disease management and vaccine development. This study evaluated longitudinal changes in the immune cell composition of bronchoalveolar lavage fluid and the clinical outcomes across PRRSV strains with varying virulence, using techniques including single-cell transcriptomics. In highly virulent infection, faster viral replication results in an earlier peak lung-damage time point, marked by significant interstitial pneumonia, a significant decrease in macrophages, and an influx of lymphocytes. Viral tracking reveals less than 5% of macrophages are directly infected, and further analysis indicates bystander cell death, likely regulated by exosomal microRNAs as a significant factor. In contrast, the peak intermediate infection shows a delayed lung-damage time point with fewer cell population modifications. Furthermore, anti-inflammatory M2-like macrophages (SPP1-CXCL14high) are identified and their counts increase during the peak lung-damage time point, likely contributing to local defense and lung recovery, which is not observed in high virulent infection. These findings provide a comprehensive description of the immune cellular landscape and differential PRRSV virulence mechanisms, which will help build new hypotheses to understand PRRSV pathogenesis and other respiratory infections.

Porcine reproductive and respiratory syndrome (PRRS) causes significant economic losses in the swine industry. However, the molecular mechanisms behind the common and cell type-specific systemic responses during PRRS virus (PRRSV) infection are not well understood. In this study, we collected viremia data, antibody levels, and whole-blood RNA-seq data obtained from eight PRRSV-infected piglets. We utilised a cell deconvolution approach to calculate cell type enrichment, constructed a time-serial gene co-expression network with differentially expressed genes, and conducted functional annotations. Three significant modules were identified within the network. The changes associated with viremia revealed an upregulated expression of genes related to antiviral activity. In the T-cell- and NK-cell-specific modules, infection led to an increased T-cell population and upregulation of genes related to T-cell defence responses. Conversely, in the monocyte- and neutrophil-specific module, genes involved in inflammatory responses were downregulated due to a decrease in monocyte proportion. This study highlights the time-series antiviral activities associated with viremia and the transcriptomic changes associated with immune responses in specific cell types. The findings provide comprehensive insights into host responses to PRRSV infection, including diagnostic biomarkers.

Cervical cancer, which is mainly caused by oncogenic human papillomavirus subtypes, remains a significant global health challenge. Recent studies have indicated a connection between cervical cancer and the uterine microbiome, underscoring its importance. This study explored the potential of liquid-based cytology (LBC) samples, which are typically used for cytological analysis, in investigating the cervical microbiome. Thirty women participated in the study and provided clinical information. Three samples were obtained from each participant: one for clinical purposes using LBC, another for microbiome sampling using LBC, and a third using the SWAB Microbiome kit. The LBC and traditional swab (SWAB) samples were subjected to high-throughput 16S rRNA gene sequencing for microbiome analysis. The results revealed a consistent dominance of key taxa, particularly Lactobacillus spp. The analysis of differential abundance highlighted variations in microbial abundance among individuals, which were more prominent than those resulting from the sampling methods. Functional analysis identified arachidonic acid and alpha-linolenic acid metabolism, along with a cautionary note regarding the low mean proportion values. The network analysis revealed positive correlations between indicators of structure among the networks, highlighting the robustness of microbiome similarities despite the diversity of sampling methods. Supervised machine learning has revealed challenges in distinguishing LBC and SWAB samples based on their microbiome features. Weighted co-expression network analysis revealed that the correlation between microbial clusters and the sampling method with clinical data was not significant. This study emphasizes the similarity in microbial communities observed using the LBC and SWAB methods, highlighting the potential of using dual diagnostic approaches. Additionally, the use of residual LBC samples in large-scale microbiological studies can provide comprehensive insights into cervical health and disease.

Despite the significant threat of heat stress to livestock animals, only a few studies have considered the potential relationship between broiler chickens and their microbiota. Therefore, this study examined microbial modifications, transcriptional changes and host-microbiome interactions using a predicted metabolome data-based approach to understand the impact of heat stress on poultry. After the analysis, the host functional enrichment analysis revealed that pathways related to lipid and protein metabolism were elevated under heat stress conditions. In contrast, pathways related to the cell cycle were suppressed under normal environmental temperatures. In line with the transcriptome analysis, the microbial analysis results indicate that taxonomic changes affect lipid degradation. Heat stress engendered statistically significant difference in the abundance of 11 microorganisms, including Bacteroides and Peptostreptococcacea. Together, integrative approach analysis suggests that microbiota-induced metabolites affect host fatty acid peroxidation metabolism, which is correlated with the gene families of Acyl-CoA dehydrogenase long chain (ACADL), Acyl-CoA Oxidase (ACOX) and Acetyl-CoA Acyltransferase (ACAA). This integrated approach provides novel insights into heat stress problems and identifies potential biomarkers associated with heat stress.

Background Porcine reproductive and respiratory syndrome respiratory sickness in weaned and growing pigs, as well as sow reproductive failure, and its infection is regarded as one of the most serious swine illnesses worldwide. Given the current lack of an effective treatment, in this study, we identified natural compounds capable of inhibiting non-structural protein 4 (Nsp4) of the virus, which is involved in their replication and pathogenesis. Results We screened natural compounds ( n = 97,999) obtained from the ZINC database against Nsp4 and selected the top 10 compounds for analysing protein–ligand interactions and physicochemical properties. The five compounds demonstrating strong binding affinity were then subjected to molecular dynamics simulations (100 ns) and binding free energy calculations. Based on analysis, we identified four possible lead compounds that represent potentially effective drug-like inhibitors. Conclusions These methods identified that these natural compounds are capable of inhibiting Nsp4 and possibly effective as antiviral therapeutics against PRRSV.

Recently, interest in the function of pig backfat (BF) has increased in the field of livestock animals, and many transcriptome-based studies using commercial pig breeds have been conducted. However, there is a lack of comprehensive studies regarding the biological mechanisms of Korean native pigs (KNPs) and Yorkshire pig crossbreeds. In this study, therefore, BF samples of F1 crossbreeds of KNPs and Yorkshire pigs were investigated to identify differentially expressed genes (DEGs) and their related terms using RNA-sequencing analysis. DEG analysis identified 611 DEGs, of which 182 were up-regulated and 429 were down-regulated. Lipid metabolism was identified in the up-regulated genes, whereas growth and maturation-related terminologies were identified in the down-regulated genes. LEP and ACTC1 were identified as highly connected core genes during functional gene network analysis. Fat tissue was observed to affect lipid metabolism and organ development due to hormonal changes driven by transcriptional alteration. This study provides a comprehensive understanding of BF contribution to crossbreeds of KNPs and Yorkshire pigs during growth periods.