Identification of sepsis-associated mitochondrial genes through RNA and single-cell sequencing approaches

Abstract

Background Sepsis ranks among the most formidable clinical challenges, characterized by exorbitant treatment costs and substantial demands on healthcare resources. Mitochondrial dysfunction emerges as a pivotal risk factor in the pathogenesis of sepsis, underscoring the imperative to identify mitochondrial-related biomarkers. Such biomarkers are crucial for enhancing the accuracy of sepsis diagnostics and prognostication. Methods In this study, adhering to the SEPSIS 3.0 criteria, we collected peripheral blood within 24 h of admission from 20 sepsis patients at the ICU of the Southwest Medical University Affiliated Hospital and 10 healthy volunteers as a control group for RNA-seq. The RNA-seq data were utilized to identify differentially expressed RNAs. Concurrently, mitochondrial-associated genes (MiAGs) were retrieved from the MitoCarta3.0 database. The differentially expressed genes were intersected with MiAGs. The intersected genes were then subjected to GO (Gene Ontology), and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses and core genes were filtered using the PPI (Protein-Protein Interaction) network. Subsequently, relevant sepsis datasets (GSE65682, GSE28750, GSE54514, GSE67652, GSE69528, GSE95233) were downloaded from the GEO (Gene Expression Omnibus) database to perform bioinformatic validation of these core genes. Survival analysis was conducted to assess the prognostic value of the core genes, while ROC (Receiver Operating Characteristic) curves determined their diagnostic value, and a meta-analysis confirmed the accuracy of the RNA-seq data. Finally, we collected 5 blood samples (2 normal controls (NC); 2 sepsis; 1 SIRS (Systemic Inflammatory Response Syndrome), and used single-cell sequencing to assess the expression levels of the core genes in the different blood cell types. Results Integrating high-throughput sequencing with bioinformatics, this study identified two mitochondrial genes (COX7B, NDUFA4) closely linked with sepsis prognosis. Survival analysis demonstrated that patients with lower expression levels of COX7B and NDUFA4 exhibited a higher day survival rate over 28 days, inversely correlating with sepsis mortality. ROC curves highlighted the significant sensitivity and specificity of both genes, with AUC values of 0.985 for COX7B and 0.988 for NDUFA4, respectively. Meta-analysis indicated significant overexpression of COX7B and NDUFA4 in the sepsis group in contrast to the normal group (P < 0.01). Additionally, single-cell RNA sequencing revealed predominant expression of these core genes in monocytes-macrophages, T cells, and B cells. Conclusion The mitochondrial-associated genes (MiAGs) COX7B and NDUFA4 are intimately linked with the prognosis of sepsis, offering potential guidance for research into the mechanisms underlying sepsis.