Sepsis, a life-threatening organ dysfunction caused by a dysregulated host response to infection, remains a major challenge in clinical practice due to its high mortality and morbidity rates. Traditional diagnostic methods often fall short in providing timely and accurate identification of sepsis, leading to delays in appropriate treatment. Next-generation sequencing (NGS) technologies, with their ability to analyze genetic material rapidly and comprehensively, offer promising solutions for overcoming these diagnostic challenges. By leveraging NGS and other advanced molecular techniques, there is potential to significantly enhance the precision and speed of sepsis diagnosis, ultimately paving the way for more effective personalized medicine approaches.

The primary aim of this Research Topic is to explore and address the diagnostic challenges of sepsis through the application of next-generation sequencing (NGS) and related advanced molecular techniques. This research seeks to improve the early and accurate detection of sepsis, distinguish it from other inflammatory conditions, and identify the specific pathogens involved. By fostering interdisciplinary collaboration, the topic will focus on the development of novel diagnostic biomarkers, gene signatures, and classifiers that can differentiate between bacterial and viral infections. Additionally, it will explore the potential of personalized medicine to tailor treatments based on the genetic and transcriptional profiles of individual patients. Achieving these goals will enhance clinical outcomes by enabling targeted and timely therapeutic interventions.

We invite the submission of original research articles, reviews and mini reviews that address various aspects of sepsis diagnosis through next-generation sequencing and personalized medicine. Submissions on (but not limited to) the following topics are welcome.

• Development and validation of transcriptional diagnostics and gene signatures for sepsis

• Application of metagenomics and NGS in identifying pathogens in sepsis patients

• Approaches to differentiate sepsis from sterile inflammation using molecular techniques

• Classifiers for distinguishing bacterial and viral infections in sepsis

• Utilization of comprehensive datasets to address the heterogeneity of sepsis

• Personalized treatment strategies based on patient-specific genetic and transcriptional data

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Frontiers in Cellular and Infection Microbiology

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