Nasal microbiota - a potential diagnostic biomarker of sepsis

Nasal microbiota of intensive care unit (ICU) patients effectively distinguishes sepsis from nonseptic cases and outperforms gut microbiota analysis in predicting sepsis, according to a new study published in Microbiology Spectrum .

"These results have implications for the development of diagnostic strategies and progress in the treatment of critical illnesses," said the study's corresponding author, Professor Jiaolong He, MD, PhD, of the Microbiome Medical Center, Department of Laboratory Medicine, Rujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.

"In the past, we have paid more attention to the gut microbiota of patients with sepsis, but it is also worth paying attention to the respiratory microbiota."

Sepsis is a severe disease with a high mortality rate ranging from 29.9% to 57.5%. Despite the establishment of the third international consensus definition of sepsis and septic shock (Sepsis-3) in 2016, many aspects of sepsis still require further study to improve its diagnosis.

The evolution of diagnostic criteria from Sepsis-1 to Sepsis-3 shows the need for continued research. In addition, diagnostic criteria for sepsis have shifted from focusing solely on the inflammatory response to also including organ failure caused by infection.

Although significant progress has been made in the diagnosis of sepsis, biological indicators with high sensitivity and specificity have not been identified. In addition, low culture positivity rates and the presence of few culturable organisms limit the diagnosis of clinical sepsis. Therefore, identifying a new, effective and reliable biomarker for sepsis was the goal of the researchers.

In the new study, the researchers recruited 157 subjects (89 with sepsis) of both sexes at the Affiliated Hospital of Southern Medical University. They collected nasal swabs and fecal samples from septic and non-septic patients in the ICU and the respiratory and critical care unit.

The researchers extracted and sequenced DNA using Illumina technology. Bioinformatics analysis, statistical processing and machine learning methods were used to distinguish between septic and non-septic patients.

He and colleagues found that the nasal microbiota of septic patients had significantly lower overall community richness (P=0.002) and different composition (P=0.001) compared with non-septic patients. Corynebacteria, Staphylococcus, Acinetobacter, and Pseudomonas were identified as enriched genera in the nasal microbiota of septic patients.

"Going forward, we suggest the potential for further studies, perhaps using animal models or larger patient cohorts, to further our understanding of the role of the microbiota in sepsis beyond the antibiotic effect," He said.