Portable Prussian Blue-Based Sensor for Bacterial Detection in Urine

Author:

Psotta Carolin,Chaturvedi Vivek,Gonzalez-Martinez Juan F.ORCID,Sotres Javier,Falk Magnus

Abstract

Bacterial infections can affect the skin, lungs, blood, and brain, and are among the leading causes of mortality globally. Early infection detection is critical in diagnosis and treatment but is a time- and work-consuming process taking several days, creating a hitherto unmet need to develop simple, rapid, and accurate methods for bacterial detection at the point of care. The most frequent type of bacterial infection is infection of the urinary tract. Here, we present a wireless-enabled, portable, potentiometric sensor for E. coli. E. coli was chosen as a model bacterium since it is the most common cause of urinary tract infections. The sensing principle is based on reduction of Prussian blue by the metabolic activity of the bacteria, detected by monitoring the potential of the sensor, transferring the sensor signal via Bluetooth, and recording the output on a laptop or a mobile phone. In sensing of bacteria in an artificial urine medium, E. coli was detected in ~4 h (237 ± 19 min; n = 4) and in less than 0.5 h (21 ± 7 min, n = 3) using initial E. coli concentrations of ~103 and 105 cells mL−1, respectively, which is under or on the limit for classification of a urinary tract infection. Detection of E. coli was also demonstrated in authentic urine samples with bacteria concentration as low as 104 cells mL−1, with a similar response recorded between urine samples collected from different volunteers as well as from morning and afternoon urine samples.

Funder

European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie MSCA-ITN “ImplantSens”

Knowledge Foundation and Mats Paulsson’s Foundation for Research, Innovation, and Development of Society

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference47 articles.

1. Biosensors for Whole-Cell Bacterial Detection;Ahmed;Clin. Microbiol. Rev.,2014

2. Laboratory Diagnosis of Urinary Tract Infections in Adult Patients;Wilson;Med. Microbiol.,2004

3. Guidelines on Urological Infections;Grabe;Eur. Assoc. Urol.,2015

4. Urinary tract infections: Epidemiology, mechanisms of infection and treatment options;Walker;Nat. Rev. Microbiol.,2015

5. The Basics of Bacteriuria: Strategies of Microbes for Persistence in Urine;Ipe;Front. Cell. Infect. Microbiol.,2016

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