Rapid Antimicrobial Susceptibility Testing on Clinical Urine Samples by Video-Based Object Scattering Intensity Detection

Fenni Zhang, Jiapei Jiang, Michelle McBride, Xinyu Zhou, Yunze Yang, Manni Mo, Joseph Peterman, Thomas Grys, Shelley E. Haydel, Nongjian Tao, Shaopeng Wang

Research output: Contribution to journalArticlepeer-review

Abstract

To combat the ongoing public health threat of antibiotic-resistant infections, a technology that can quickly identify infecting bacterial pathogens and concurrently perform antimicrobial susceptibility testing (AST) in point-of-care settings is needed. Here, we develop a technology for point-of-care AST with a low-magnification solution scattering imaging system and a real-time video-based object scattering intensity detection method. The low magnification (1-2×) optics provides sufficient volume for direct imaging of bacteria in urine samples, avoiding the time-consuming process of culture-based bacterial isolation and enrichment. Scattering intensity from moving bacteria and particles in the sample is obtained by subtracting both spatial and temporal background from a short video. The time profile of scattering intensity is correlated with the bacterial growth rate and bacterial response to antibiotic exposure. Compared to the image-based bacterial tracking and counting method we previously developed, this simple image processing algorithm accommodates a wider range of bacterial concentrations, simplifies sample preparation, and greatly reduces the computational cost of signal processing. Furthermore, development of this simplified processing algorithm eases implementation of multiplexed detection and allows real-time signal readout, which are essential for point-of-care AST applications. To establish the method, 130 clinical urine samples were tested, and the results demonstrated an accuracy of ∼92% within 60-90 min for UTI diagnosis. Rapid AST of 55 positive clinical samples revealed 98% categorical agreement with both the clinical culture results and the on-site parallel AST validation results. This technology provides opportunities for prompt infection diagnosis and accurate antibiotic prescriptions in point-of-care settings.

Original languageEnglish (US)
Pages (from-to)7011-7021
Number of pages11
JournalAnalytical Chemistry
Volume93
Issue number18
DOIs
StatePublished - May 11 2021
Externally publishedYes

ASJC Scopus subject areas

  • Analytical Chemistry

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