Phospholipase D regulates ferroptosis signal transduction in mouse spleen hypoxia response.

High-altitude hypoxia exposure can lead to phospholipase D-mediated lipid metabolism disorder in spleen tissues and induce ferroptosis. Nonetheless, the key genes underlying hypoxia-induced splenic phospholipase D and the ferroptosis pathway remain unclear. This study aimed to establish a hypoxia animal model. Combined transcriptomic and proteomic analyses showed that 95 predicted target genes (proteins) were significantly differentially expressed under hypoxic conditions. Key genes in phospholipase D and ferroptosis pathways under hypoxic exposure were identified by combining Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis techniques. Gene set enrichment analysis (GSEA) showed that the differential gene sets of the phospholipase D and ferroptosis signaling pathways were upregulated in the high-altitude hypoxia group. The genes in the phospholipase D signalling pathway were verified, and the expression levels of KIT and DGKG were upregulated in spleen tissues under hypoxic exposure. Subsequently, the mRNA and protein expression levels of genes from the exogenous pathway such as TFRC, SLC40A1, SLC7A11, TRP53, and FTH1 and those from the endogenous pathway such as GPX4, HMOX1, and ALOX15 differentials in the ferroptosis signalling pathway were verified, and the results indicated significant differential expression. In summary, exposure to high-altitude hypoxia mediated phospholipid metabolism disturbance through the phospholipase D signalling pathway and further induced ferroptosis, leading to splenic injury.

Investigating the Impact of Gut Microbiota on Gout Through Mendelian Randomization.

Background: The relationship between gout and gut microbiota has attracted significant attention in current research. However, due to the diverse range of gut microbiota, the specific causal effect on gout remains unclear. This study utilizes Mendelian randomization (MR) to investigate the causal relationship between gut microbiota and gout, aiming to elucidate the underlying mechanism of microbiome-mediated gout and provide valuable guidance for clinical prevention and treatment. Materials and Methods: The largest genome-wide association study meta-analysis conducted by the MiBioGen Consortium (n=18,340) was utilized to perform a two-sample Mendelian randomization investigation on aggregate statistics of intestinal microbiota. Summary statistics for gout were utilized from the data released by EBI. Various methods, including inverse variance weighted, weighted median, weighted model, MR-Egger, and Simple-mode, were employed to assess the causal relationship between gut microbiota and gout. Reverse Mendelian randomization analysis revealed a causal association between bacteria and gout in forward Mendelian randomization analysis. Cochran's Q statistic was used to quantify instrumental variable heterogeneity. Results: The inverse variance weighted estimation revealed that Rikenellaceae exhibited a slight protective effect on gout, while the presence of Ruminococcaceae UCG_011 is associated with a marginal increase in the risk of gout. According to the reverse Mendelian Randomization results, no significant causal relationship between gout and gut microbiota was observed. No significant heterogeneity of instrumental variables or level pleiotropy was detected. Conclusion: Our MR analysis revealed a potential causal relationship between the development of gout and specific gut microbiota; however, the causal effect was not robust, and further research is warranted to elucidate its underlying mechanism in gout development. Considering the significant association between diet, gut microbiota, and gout, these findings undoubtedly shed light on the mechanisms of microbiota-mediated gout and provide new insights for translational research on managing and standardizing treatment for this condition.

Transcriptomics and metabolomics study in mouse kidney of the molecular mechanism underlying energy metabolism response to hypoxic stress in highland areas.

Exposure to hypoxia disrupts energy metabolism and induces inflammation. However, the pathways and mechanisms underlying energy metabolism disorders caused by hypoxic conditions remain unclear. In the present study, a hypoxic animal model was created and transcriptomic and non-targeted metabolomics techniques were applied to further investigate the pathways and mechanisms of hypoxia exposure that disrupt energy metabolism. Transcriptome results showed that 3,007 genes were significantly differentially expressed under hypoxic exposure, and Gene Ontology annotation analysis and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analysis showed that the differentially expressed genes (DEGs) were mainly involved in energy metabolism and were significantly enriched in the tricarboxylic acid (TCA) cycle and oxidative phosphorylation (OXPHOS) pathway. The DEGs IDH3A, SUCLA2, and MDH2 in the TCA cycle and the DEGs NDUFA3, NDUFS7, UQCRC1, CYC1 and UQCRFS1 in the OXPHOS pathway were validated using mRNA and protein expression, and the results showed downregulation. The results of non-targeted metabolomics showed that 365 significant differential metabolites were identified under plateau hypoxia stress. KEGG enrichment analysis showed that the differential metabolites were mainly enriched in metabolic processes, such as energy, nucleotide and amino acid metabolism. Hypoxia exposure disrupted the TCA cycle and reduced the synthesis of amino acids and nucleotides by decreasing the concentration of cis-aconitate, α-ketoglutarate, NADH, NADPH and that of most amino acids, purines, and pyrimidines. Bioinformatics analysis was used to identify inflammatory genes related to hypoxia exposure and some of them were selected for verification. It was shown that the mRNA and protein expression levels of IL1B, IL12B, S100A8 and S100A9 in kidney tissues were upregulated under hypoxic exposure. The results suggest that hypoxia exposure inhibits the TCA cycle and the OXPHOS signalling pathway by inhibiting IDH3A, SUCLA2, MDH2, NDUFFA3, NDUFS7, UQCRC1, CYC1 and UQCRFS1, thereby suppressing energy metabolism, inducing amino acid and nucleotide deficiency and promoting inflammation, ultimately leading to kidney damage.

Phospholipase D regulates ferroptosis signal transduction in mouse spleen hypoxia response

High-altitude hypoxia exposure can lead to phospholipase D-mediated lipid metabolism disorder in spleen tissues and induce ferroptosis. Nonetheless, the key genes underlying hypoxia-induced splenic phospholipase D and the ferroptosis pathway remain unclear. This study aimed to establish a hypoxia animal model. Combined transcriptomic and proteomic analyses showed that 95 predicted target genes (proteins) were significantly differentially expressed under hypoxic conditions. Key genes in phospholipase D and ferroptosis pathways under hypoxic exposure were identified by combining Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis techniques. Gene set enrichment analysis (GSEA) showed that the differential gene sets of the phospholipase D and ferroptosis signaling pathways were upregulated in the high-altitude hypoxia group. The genes in the phospholipase D signalling pathway were verified, and the expression levels of KIT and DGKG were upregulated in spleen tissues under hypoxic exposure. Subsequently, the mRNA and protein expression levels of genes from the exogenous pathway such as TFRC, SLC40A1, SLC7A11, TRP53, and FTH1 and those from the endogenous pathway such as GPX4, HMOX1, and ALOX15 differentials in the ferroptosis signalling pathway were verified, and the results indicated significant differential expression. In summary, exposure to high-altitude hypoxia mediated phospholipid metabolism disturbance through the phospholipase D signalling pathway and further induced ferroptosis, leading to splenic injury.