A fight against time
novel methods for the rapid diagnosis of sepsis
Time: Fri 2026-03-06 13.00
Location: Q2, Malvinas Väg 10
Video link: https://kth-se.zoom.us/j/68282646509
Language: English
Subject area: Electrical Engineering
Doctoral student: María Henar Marino Miguélez , Mikro- och nanosystemteknik
Opponent: Senior lecturer Pelle Ohlsson, Division for Biomedical Engineering, Lund University, Lund, Sweden
Supervisor: Professor Wouter van der Wijngaart, Mikro- och nanosystemteknik; Professor Johan Elf, Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
QC 20260206
Abstract
Sepsis is a life-threatening condition affecting an estimated 49 million people annually and causing approximately 20% of the deaths worldwide. Survival in septic shock decreases by about 8% per hour of delayed or inappropriate treatment, making rapid diagnosis critical. Consequently, patient outcomes strongly depend on the rapid initiation of appropriate antimicrobial therapy, making sepsis diagnosis a fight against time. However, current blood culture-based workflows typically require several days to deliver actionable results, largely due to the extremely low bacterial concentrations in blood (1-100 CFU/mL) that necessitate time-consuming culture steps. There is therefore a pressing need for diagnostic protocols capable of rapidly isolating and characterizing bacteria directly from blood.
In this work, we address a key limitation in current diagnostic pipelines by developing and evaluating culture-free approaches for the rapid isolation, detection, species identification, and antimicrobial susceptibility testing (AST) of bacteria directly from blood, starting at clinically relevant concentrations. Two centrifugation-based sample preparation strategies were developed: one compatible with samples drawn into blood culture bottles and one designed for whole blood. Using the first approach, we demonstrated the isolation and identification of five common sepsis-causing bacteria within 12 hours. This approach relies solely on standard laboratory equipment, which facilitates direct translation to clinical laboratories. The whole-blood approach combines centrifugation and selective blood cell lysis with microfluidic trapping and deep learning-based automated detection, and enables culture-free detection of bacteria from blood within 2 h. Building on this foundation, the workflow was further extended to integrate real-time automated detection, single-cell phenotypic AST, and species identification by fluorescence in situ hybridization (FISH), directly from uncultured blood in under 7 h.
The sample preparation steps of these protocols rely heavily on manual processing. Therefore, subsequent work focused on the development of a one-step centrifuge device that automates bacterial isolation and up-concentration while maintaining compatibility with downstream processes, such as subculturing, mass spectrometry-based identification, and microfluidic single-cell analysis. All approaches were evaluated using healthy human blood samples spiked with common sepsis-causing bacteria, and serve as proof-of-concept of rapid, culture-free bacterial characterization directly from blood.
Together, the results presented in this thesis demonstrate the potential of combining centrifugation-based sample preparation, microfluidics, and automated image analysis to substantially shorten diagnostic turnaround times for sepsis and bloodstream infections. Although further validation with clinical samples and increased automation are required, this work provides experimental and methodological advances toward faster sepsis diagnostics.