A new molecular method for rapid etiological diagnosis of sepsis with improved performance

Comparison of microbiological and molecular diagnosis for identification of respiratory secondary infections in COVID-19 patients and their antimicrobial resistance patterns

We report the use of a new multiplex Real-Time PCR platform to simultaneously identify 24 pathogens and 3 antimicrobial-resistance genes directly from respiratory samples of COVID-19 patients. Results were compared to culture-based diagnosis. Secondary infections were detected in 60% of COVID-19 patients by molecular analysis and 73% by microbiological assays, with no significant differences in accuracy, indicating Gram-negative bacteria as the predominant species. Among fungal superinfections, Aspergillus spp. were detected by both methods in more than 7% of COVID-19 patients. Oxacillin-resistant S. aureus and carbapenem-resistant K. pneumoniae were highlighted by both methods. Secondary microbial infections in SARS-CoV-2 patients are associated with poor outcomes and an increased risk of death. Since PCR-based tests significantly reduce the turnaround time to 4 hours and 30 minutes (compared to 48 hours for microbial culture), we strongly support the routine use of molecular techniques, in conjunction with microbiological analysis, to identify co/secondary infections.

Identification of Immune-Related Key Genes as Potential Diagnostic Biomarkers of Sepsis in Children

Objective

The pathogenesis of sepsis is still unclear due to its complexity, especially in children. This study aimed to analyse the immune microenvironment and regulatory networks related to sepsis in children at the molecular level and to identify key immune-related genes to provide a new basis for the early diagnosis of sepsis.

Methods

The GSE145227 and GSE26440 datasets were downloaded from the Gene Expression Omnibus. The analyses included differentially expressed genes (DEGs), functional enrichment, immune cell infiltration, the competing endogenous RNA (ceRNA) interaction network, weighted gene coexpression network analysis (WGCNA), protein–protein interaction (PPI) network, key gene screening, correlation of sepsis molecular subtypes/immune infiltration with key gene expression, the diagnostic capabilities of key genes, and networks describing the interaction of key genes with transcription factors and small-molecule compounds. Finally, real-time quantitative PCR (RT–qPCR) was performed to verify the expression of key genes.

Results

A total of 236 immune-related DEGs, most of which were enriched in immune-related biological functions, were found. Further analysis of immune cell infiltration showed that M0 macrophages and neutrophils infiltrated more in the sepsis group, while fewer activated memory CD4⁺ T cells, resting memory CD4⁺ T cells, and CD8⁺ T cells did. The interaction network of ceRNA was successfully constructed. Six key genes (FYN, FBL, ATM, WDR75, FOXO1 and ITK) were identified by WGCNA and PPI analysis. We found strong associations between key genes and constructed septic molecular subtypes or immune cell infiltration. Receiver operating characteristic analysis showed that the area under the curve values of the key genes for diagnosis were all greater than 0.84. Subsequently, we successfully constructed an interaction network of key genes and transcription factors/small-molecule compounds. Finally, the key genes in the samples were verified by RT–qPCR.

Conclusion

Our results offer new insights into the pathogenesis of sepsis in children and provide new potential diagnostic biomarkers for the disease.