Utility of sTREM-1 biomarker and hcp Gene for Identification of Acinetobacter baumannii Colonization and Infection in Lung

Abstract

Objective Respiratory infections or colonization of Acinetobacter baumannii (Ab) are common in clinical practice but are treated differently. Early identification of Ab infection and colonization reduces the risk of antibiotic mismatch but objective laboratory indicators to distinguish between bacterial infections and colonization are lacking. To distinguish infection and colonization of Ab, we tested the role of two biomarkers, triggering receptor expressed on myeloid cells-1 (TREM-1) and Hemolysin co-regulated protein (Hcp). Methods A total of 96 inpatients with Ab were divided into infection and colonization groups. Blood samples were collected on day 1, 2, 3, 5, 8 and 10 and daily maximum body temperature (T) was recorded.PCR and RT-PCR were used to detect the presence and expression levels of the hcp gene in Ab clinical isolates. Results sTREM-1 and PCT levels on days 1-10 and neutrophil classification (N%) on days 1-3 were different (P < 0.05) in the infection group and colonization group.ROC curves showed significant differences in N% and sTREM-1 on days 2 and 3(P < 0.01).sTREM-1 had the highest AUCROC on days 1, 2 and 3 of all the markers. On day 1, the ROC curve of "WBC&N%&PCT&sTREM-1"was statistically different from individual indices (WBC count, N% and PCT; P < 0.05) and was equal to the ROC curve of sTREM-1 (P > 0.05). 35 of 96 patients were classified as infection group and 61 as colonization group with hcp gene detection rates of 71.43% (25/35) and 31.15% (19/61), respectively. No differences in hcp gene presence and transcript levels were found between two groups (P > 0.05). Conclusion Dynamic monitoring of sTREM-1 and PCT are valuable in identifying Ab infection and colonization. sTREM-1, can be improved by combination with multiple biomarkers in the early stage for identification of infection and colonization. The hcp gene was more likely to be present in the infection cohort.

sTREM-1 as a Predictive Biomarker for Disease Severity and Prognosis in COVID-19 Patients

“…23,24 Research has shown that TREM-1 expression can be induced by various viral infections, including influenza A virus and hepatitis C virus, as well as bacterial infections like Staphylococcus aureus and Pseudomonas aeruginosa. [25][26][27] Soluble TREM-1 (sTREM-1) is a 27 kDa peptide composed of the extracellular domain of TREM-1, which can be shed into the bloodstream. 28,29 Multiple studies have investigated the use of sTREM-1 for predicting mortality in sepsis patients.…”