LAP3 contributes to IFN-γ-induced arginine depletion and malignant transformation of bovine mammary epithelial cells

Study of Plasma Biochemistry and Plasma Metabolomics Differences in Montbéliard and Holstein Backcross and Holstein Heifers

Holstein cattle are the main breed of dairy cattle in China. However, given the high degree of purebred selection of Holstein cattle, Chinese dairy cattle are increasingly being characterized by poor disease resistance, poor quality, and declining fertility. In this study, using Montbéliard × Holstein cattle as females and Montbéliard bulls as males for backcross breeding, we sought to provide a reference for improving the quality and performance of Holstein cattle and enhancing the efficiency of dairy farming. On the basis of similar physiological status and age, we selected 24 Montbéliard and Holstein backcross heifers and 11 Holstein heifers fed the same formula for comparative analyses. Plasma samples collected for plasma biochemical index analyses revealed that the content of ALB and BUN in the Montbéliard and Holstein backcross heifers was 20.83% (31.62 g/L to 26.17 g/L) and 42.36% (6.89 mmol/L to 4.84 mmol/L) higher than in the Holsteins (p < 0.01). The ALB/GLB (0.90 to 0.60, p < 0.05) was significantly higher in Montbéliard and Holstein backcross heifers than in Holstein heifers. Similarly, the activity of CAT in the backcross heifers was 61.28% (4.29 U/mL to 2.66 U/mL) higher than that in the Holstein heifers (p < 0.05). Although the activity of GSH-Px in the backcross heifers also showed an increasing trend, the difference did not reach the level of statistical significance (p = 0.052). Compared with Holstein heifers, the concentrations of IgA, IgG, and IL-4 were elevated by 32.52% (24.90 μg/mL to 18.79 μg/mL, p < 0.01), 13.46% (234.32 μg/mL to 206.53 μg/mL, p < 0.01), and 14.59% (306.27 pg/mL to 267.28 pg/mL, p < 0.05), and the contents of IL-6 and TNF-α were decreased by 15.92% (215.71 pg/mL to 256.55 pg/mL, p < 0.01) and 32.17% (7.17 ng/mL to 10.57 ng/mL, p < 0.01) in the plasma of Montbéliard and Holstein backcross heifers. Among the experimental heifers, five animals from each of the two groups were selected for plasma metabolomic analysis based on untargeted liquid chromatography-mass spectrometry. A comparison of the differential metabolites between the two heifer breeds revealed an up-regulation of d-glucuronic acid, s-glutathionyl-l-cysteine, and oleic acid levels in the backcross cattle compared with those in the Holstein heifers. We speculate that changes in the levels of these metabolites may be associated with an enhancement of the anti-inflammatory, antioxidant, and immune systems in these backcross heifers. Collectively, our findings in this study indicate that compared with 12-month-old purebred Holstein heifers, Montbéliard and Holstein backcross heifers of the same age are characterized by higher antioxidant capacity and immunity.

Mitochondrial-related hub genes in dermatomyositis: muscle and skin datasets-based identification and in vivo validation

Background: Mitochondrial dysfunction has been implicated in the pathogenesis of dermatomyositis (DM), a rare autoimmune disease affecting the skin and muscles. However, the genetic basis underlying dysfunctional mitochondria and the development of DM remains incomplete. Methods: The datasets of DM muscle and skin tissues were retrieved from the Gene Expression Omnibus database. The mitochondrial related genes (MRGs) were retrieved from MitoCarta. DM-related modules in muscle and skin tissues were identified with the analysis of weighted gene co-expression network (WGCNA), and then compared with the MRGs to obtain the overlapping mitochondrial related module genes (mito-MGs). Subsequently, differential expression genes (DEGs) obtained from muscle and skin datasets were overlapped with MRGs to identify mitochondrial related DEGs (mito-DEGs). Next, functional enrichment analysis was applied to analyze possible relevant biological pathways. We used the Jvenn online tool to intersect mito-MGs with mito-DEGs to identify hub genes and validate them using reverse transcription quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry staining. In addition, we evaluated immune infiltration in muscle and skin tissues of DM patients using the one-sample gene set enrichment analysis (ssGSEA) algorithm and predicted potential transcription factor (TF) -gene network by NetworkAnalyst. Results: The WGCNA analysis revealed 105 mito-MGs, while the DEG analysis identified 3 mito-DEGs. These genes showed functional enrichment for amino acid metabolism, energy metabolism and oxidative phosphorylation. Through the intersection analysis of the mito-MGs from the WGCNA analysis and the mito-DEGs from the DEG set, three DM mito-hub genes (IFI27, CMPK2, and LAP3) were identified and validated by RT-qPCR and immunohistochemistry analysis. Additionally, positive correlations were observed between hub genes and immune cell abundance. The TF-hub gene regulatory network revealed significant interactions involving ERG, VDR, and ZFX with CMPK2 and LAP3, as well as SOX2 with LAP3 and IFI27, and AR with IFI27 and CMPK2. Conclusion: The mito-hub genes (IFI27, CMPK2, and LAP3) are identified in both muscles and skin tissues from DM patients. These genes may be associated with immune infiltration in DM, providing a new entry point for the pathogenesis of DM.

Identification and verification of an exosome-related gene risk model to predict prognosis and evaluate immune infiltration for colorectal cancer

Colorectal cancer (CRC) is a common malignant tumor that severely endangers human health. Exosomes show great potential in tumor immunotherapy. Increasingly studies have shown that exosome-related genes are effective prognostic biomarkers. Clinical information and gene expression data of CRC patients were obtained from gene expression omnibus and the cancer genome atlas. The data were then classified into training and independent validation sets. In the training set, exosome-related genes with a prognostic value were selected by univariate Cox analysis, least absolute shrinkage and selection operator Cox regression model, and stepwise Cox regression analysis. Risk scores were calculated based on the selected genes to stratify patients. The selected exosome-related genes were applied to establish a risk model. Based on 11 exosome-related genes, a prognostic risk model, which could stratify the risk both in the training and validation sets, was established. According to the survival curves, the prognoses of the high- and low-risk groups were significantly different. The AUCs of the risk model for prognostic prediction were 0.735 and 0.784 in the training and validation sets, respectively. A nomogram was constructed to predict the survival of CRC patients. Single-sample gene set enrichment analysis and ESTIMATE algorithms revealed that the risk model was related to immune cell infiltration. The value of the risk model in predicting immunotherapeutic outcomes was also confirmed. An exosome-related gene risk model was constructed to predict prognosis, evaluate microenvironment immune cell infiltration levels and bring a new perspective to CRC patient treatment.

Untargeted metabolomics reveals alternations in metabolism of bovine mammary epithelial cells upon IFN-γ treatment

BACKGROUND

IFN-γ is a pleiotropic cytokine that has been shown to affect multiple cellular functions of bovine mammary epithelial cells (BMECs) including impaired milk fat synthesis and induction of malignant transformation via depletion of arginine, one of host conditionally essential amino acids. But the molecular mechanisms of these IFN-γ induced phenotypes are still unknown.

METHODS

BMECs were treated with IFN-γ for 6 h, 12 h, and 24 h. The metabolomic profiling in BMECs upon IFN-γ induction were assessed using untargeted ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) metabolomic analysis. Key differentially expressed metabolites (DEMs) were quantified by targeted metabolomics.

RESULTS

IFN-γ induction resulted in significant differences in the contents of metabolites. Untargeted analysis identified 221 significantly DEMs, most of which are lipids and lipid-like molecules, organic acids and derivatives, organ heterocyclic compounds and benzenoids. According to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, DEMs were enriched in fructose and mannose metabolism, phosphotransferase system (PTS), β-alanine metabolism, arginine and proline metabolism, methane metabolism, phenylalanine metabolism, and glycolysis/gluconeogenesis. Quantification of selected key DEMs by targeted metabolomics showed significantly decreased levels of D-(-)-mannitol, argininosuccinate, and phenylacetylglycine (PAG), while increased levels in S-hydroxymethylglutathione (S-HMG) and 2,3-bisphospho-D-glyceric acid (2,3-BPG).

CONCLUSIONS

These results provide insights into the metabolic alterations in BMECs upon IFN-γ induction and indicate potential theoretical basis for clarifying IFN-γ-induced diseases in mammary gland.