Sepsis is a frequent and severe consequence of bloodstream infection (BSI) and remains a leading cause of global mortality and morbidity. Diagnosis of BSI is challenging because circulating pathogen concentrations are often extremely low and conventional diagnosis depends on blood culture, which is slow. This delay forces empiric antimicrobial therapy that can worsen patient outcomes and contribute to antimicrobial resistance. The study introduces STREAM — sedimentation-assisted tandem rocking and enrichment for analysis and monitoring — as a platform designed to isolate and enrich pathogens directly from whole blood while preserving growth conditions near the organisms’ natural doubling times.
STREAM is described as an enrichment workflow that combines sedimentation and a controlled rocking motion to concentrate microbes from whole blood. The technique is intended to recover pathogens without requiring prolonged culture amplification, maintaining conditions that allow organisms to remain close to their native growth dynamics. The abstract reports the platform as an approach to efficiently isolate pathogens for downstream single-cell molecular and phenotypic assays directly from whole-blood specimens.
A central feature of the platform is the integration of STREAM with single-cell analysis methods. By operating at the single-cell level, the combined system aims to deliver both rapid identification of the causative organism(s) and phenotypic antimicrobial susceptibility results from enriched whole-blood samples. According to the abstract, this integrated approach enabled a rapid and robust diagnostic workflow for bloodstream infections.
For organism identification the authors applied molecularly barcoded sequential fluorescence in situ hybridization (FISH). This approach uses sequential rounds of hybridization with molecular barcodes to identify pathogens at the single-cell level. In the cohort of 104 positive blood culture samples reported in the abstract, identification by this method showed 96.15% concordance with results obtained by the clinical laboratory, indicating close agreement between the STREAM–single-cell identification method and conventional clinical reference testing.
Phenotypic susceptibility was assessed using a gel-based single-cell AST protocol. This format measures antimicrobial effect at the single-cell level within a gel matrix, enabling determination of susceptibility for individual cells recovered from blood. The gel-based single-cell AST results were compared with reference susceptibility determinations across multiple drug–dose combinations to quantify agreement metrics.
Key performance metrics reported in the abstract include:
These figures indicate high overall agreement with clinical laboratory standards for both identification and susceptibility readouts as summarized in the source abstract.
The integrated STREAM workflow achieved a reported analytical detection limit in whole blood as low as 0.1 to 1 CFU/ml, demonstrating sensitivity that addresses the low pathogen loads typical of bloodstream infections. The full diagnostic workflow — combining enrichment, single-cell identification, and phenotypic AST — produced complete results within 6.75 to 17 hours, substantially faster than traditional blood-culture-dependent methods.
According to the abstract, STREAM coupled with single-cell analysis provides a rapid, robust route to comprehensive BSI diagnosis directly from whole blood, offering both identification and phenotypic antimicrobial susceptibility information with high concordance and agreement metrics. The faster time-to-result and low detection limit suggest potential to reduce empiric antimicrobial use and improve sepsis management.
The source material for this summary is restricted to the abstract-level content provided. Additional experimental details, pathogen-specific performance, clinical validation cohorts, implementation requirements, and potential limitations beyond those summarized in the abstract were not reported in the source text and therefore are not included here.