Bloodstream infections remain one of the major challenges in intensive care units, leading to sepsis or even septic shock in many cases. Due to the lack of timely diagnostic approaches with sufficient sensitivity, mortality rates of sepsis are still unacceptably high. However a prompt diagnosis of the causative microorganism is critical to significantly improve outcome of bloodstream infections. Although various targeted molecular tests for blood samples are available, time-consuming blood culture-based approaches still represent the standard of care for the identification of bacteria. Here we describe the establishment of a complete diagnostic workflow for the identification of infectious microorganisms from seven septic patients based on unbiased sequence analyses of free circulating DNA from plasma by next-generation sequencing. We found significant levels of DNA fragments derived from pathogenic bacteria in samples from septic patients. Quantitative evaluation of normalized read counts and introduction of a sepsis indicating quantifier (SIQ) score allowed for an unambiguous identification of Gram-positive as well as Gram-negative bacteria that exactly matched with blood cultures from corresponding patient samples. In addition, we also identified species from samples where blood cultures were negative. Reads of non-human origin also comprised fragments derived from antimicrobial resistance genes, showing that, in principle, prediction of specific types of resistance might be possible. The complete workflow from sample preparation to species identification report could be accomplished in roughly 30 h, thus making this approach a promising diagnostic platform for critically ill patients suffering from bloodstream infections.

The increasing incidence of bloodstream infections including sepsis is a major challenge in intensive care units worldwide. However, current diagnostics for pathogen identification mainly depend on culture- and molecular-based approaches, which are not satisfactory regarding specificity, sensitivity, and time to diagnosis. Herein, we established a complete diagnostic workflow for real-time high-throughput sequencing of cell-free DNA from plasma based on nanopore sequencing for the detection of the causative agents, which was applied to the analyses of eight samples from four septic patients and three healthy controls, and subsequently validated against standard next-generation sequencing results. By optimization of library preparation protocols for short fragments with low input amounts, a 3.5-fold increase in sequencing throughput could be achieved. With tailored bioinformatics workflows, all eight septic patient samples were found to be positive for relevant pathogens. When considering time to diagnosis, pathogens were identified within minutes after start of sequencing. Moreover, an extrapolation of real-time sequencing performance on a cohort of 239 septic patient samples revealed that more than 90% of pathogen hits would have also been detected using the optimized MinION workflow. Reliable identification of pathogens based on circulating cell-free DNA sequencing using optimized workflows and real-time nanopore-based sequencing can be accomplished within 5 to 6 hours following blood draw. Therefore, this approach might provide therapy-relevant results in a clinically critical timeframe.

Fungi are of increasing importance in sepsis. However, culture-based diagnostic procedures are associated with relevant weaknesses. Therefore, culture- and next-generation sequencing (NGS)-based fungal findings as well as corresponding plasma levels of β-d-glucan, interferon gamma (INF-γ), tumor necrosis factor alpha (TNF-α), interleukin (IL)-2, -4, -6, -10, -17A, and mid-regional proadrenomedullin (MR-proADM) were evaluated in 50 septic patients at six consecutive time points within 28 days after sepsis onset. Furthermore, immune-response patterns during infections with Candida spp. were studied in a reconstituted human epithelium model. In total, 22% (n = 11) of patients suffered from a fungal infection. An NGS-based diagnostic approach appeared to be suitable for the identification of fungal pathogens in patients suffering from fungemia as well as in patients with negative blood cultures. Moreover, MR-proADM and IL-17A in plasma proved suitable for the identification of patients with a fungal infection. Using RNA-seq., adrenomedullin (ADM) was shown to be a target gene which is upregulated early after an epithelial infection with Candida spp. In summary, an NGS-based diagnostic approach was able to close the diagnostic gap of routinely used culture-based diagnostic procedures, which can be further facilitated by plasmatic measurements of MR-proADM and IL-17A. In addition, ADM was identified as an early target gene in response to epithelial infections with Candida spp.

Early sepsis identification is of paramount importance for an effective therapy and the patient outcome; however, a suitable prognostic biomarker is lacking. Anti-inflammatory nonneuronal cholinergic signaling modulates the magnitude of an immune response. Serum cholinesterase (BChE), an enzyme that hydrolyzes acetylcholine, plays an important role during inflammatory response and serves as an accurate index of cholinergic activity. BChE activity was measured in septic patients using a point-of-care system, and levels of conventional inflammatory markers and the disease severity scores were obtained. We observed a strong, sustained reduction in BChE activity in patients who died within a 90-day observation period, as compared to survivors. Reduced BChE activity when measured at the ICU admission effectively differentiated between the 90-day survivor and the nonsurvivor patient groups. We estimated a critical BChE level of 1.661 kU/L (CI 0.5–0.8, 94% sensitivity, 48% specificity, AUC 0.7) to best predict patient outcome providing a benchmark criterion for early detection of potentially fatal sepsis measured at the admission. This finding suggests that the BChE activity, used in combination with the laboratory tests, clinical examination, and the disease severity scoring, could serve to identify high-risk patients at the ICU admission, the most critical time point in the sepsis treatment.

Despite limited sensitivity and specificity, blood cultures (BCs) still represent the gold standard of diagnostic care in septic patients. We aimed to overcome current diagnostic limitations by unbiased next-generation sequencing (NGS) of circulating microbial cell-free DNA (mcfDNA) in plasma samples. We performed a prospective, observational, non-interventional, multicenter study (Next GeneSiS-Trial) to compare positivity rates for NGS-based identification of causative pathogens with BCs in patients suffering from sepsis or septic shock. An independent expert panel (n=3) retrospectively evaluated the plausibility of NGS-based findings and the potential for anti-infective treatment adaptations based on NGS results. The positivity rate of NGS-based diagnostics (NGS+) for 491 septic patients was 70.5% compared to positive BCs (BC+) with 19.4% within the first three days after sepsis onset. NGS+ results were evaluated as plausible in 98.6% of cases by the expert panel. Based on the experts´ recommendations, additional knowledge of NGS-based pathogen findings would have resulted in anti-infective treatment adaptations in 32.6% of all patients. Potentially inadequately treated NGS+/blood culture negative (BC-) patients showed worse outcomes. The integration of NGS-based pathogen diagnostics in sepsis has the potential to improve patients´ outcomes as compared to a treatment strategy based on standard-of-care microbiological diagnostics alone.