journal article·2023-11Open access

Accurate Prediction of Antimicrobial Susceptibility for Point‐of‐Care Testing of Urine in Less than 90 Minutes via iPRISM Cassettes

Xin Jiang, Talya Borkum, Sagi Shprits, Joseph Boen, Sofia Arshavsky‐Graham, Baruch Rofman, Merav Strauss, Raul Colodner, Jeremias Sulam, Sarel Halachmi, Heidi Leonard, Ester Segal

Advanced Science· Volume 10· Issue 31

Abstract

Abstract The extensive and improper use of antibiotics has led to a dramatic increase in the frequency of antibiotic resistance among human pathogens, complicating infectious disease treatments. In this work, a method for rapid antimicrobial susceptibility testing (AST) is presented using microstructured silicon diffraction gratings integrated into prototype devices, which enhance bacteria‐surface interactions and promote bacterial colonization. The silicon microstructures act also as optical sensors for monitoring bacterial growth upon exposure to antibiotics in a real‐time and label‐free manner via intensity‐based phase‐shift reflectometric interference spectroscopic measurements (iPRISM). Rapid AST using clinical isolates of Escherichia coli (E. coli) from urine is established and the assay is applied directly on unprocessed urine samples from urinary tract infection patients. When coupled with a machine learning algorithm trained on clinical samples, the iPRISM AST is able to predict the resistance or susceptibility of a new clinical sample with an Area Under the Receiver Operating Characteristic curve (AUC) of ∼ 0.85 in 1 h, and AUC > 0.9 in 90 min, when compared to state‐of‐the‐art automated AST methods used in the clinic while being an order of magnitude faster.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Bacterial Identification and Susceptibility Testing · Biosensors and Analytical Detection · Spectroscopy Techniques in Biomedical and Chemical Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Biotechnology and Food Engineering Technion – Israel Institute of Technology Haifa 3200003 Israel

Department of Urology Bnai Zion Medical Center Haifa 3104800 Israel

Department of Biomedical Engineering Johns Hopkins University Clark 320B, 3400 N Charles St Baltimore MD 21218 USA

Department of Mechanical Engineering Technion – Israel Institute of Technology Haifa 3200003 Israel

Laboratory of Clinical Microbiology Emek Medical Center Afula 1834111 Israel

The Rappaport Faculty of Medicine Technion – Israel Institute of Technology Haifa 3200003 Israel

Funding

Israel Science Foundation

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