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Portable Prussian Blue-Based Sensor for Bacterial Detection in Urine

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,...

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Autores principales: Psotta, Carolin, Chaturvedi, Vivek, Gonzalez-Martinez, Juan F., Sotres, Javier, Falk, Magnus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823789/
https://www.ncbi.nlm.nih.gov/pubmed/36616986
http://dx.doi.org/10.3390/s23010388
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author Psotta, Carolin
Chaturvedi, Vivek
Gonzalez-Martinez, Juan F.
Sotres, Javier
Falk, Magnus
author_facet Psotta, Carolin
Chaturvedi, Vivek
Gonzalez-Martinez, Juan F.
Sotres, Javier
Falk, Magnus
author_sort Psotta, Carolin
collection PubMed
description 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 ~10(3) and 10(5) 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 10(4) cells mL(−1), with a similar response recorded between urine samples collected from different volunteers as well as from morning and afternoon urine samples.
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spelling pubmed-98237892023-01-08 Portable Prussian Blue-Based Sensor for Bacterial Detection in Urine Psotta, Carolin Chaturvedi, Vivek Gonzalez-Martinez, Juan F. Sotres, Javier Falk, Magnus Sensors (Basel) Article 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 ~10(3) and 10(5) 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 10(4) cells mL(−1), with a similar response recorded between urine samples collected from different volunteers as well as from morning and afternoon urine samples. MDPI 2022-12-30 /pmc/articles/PMC9823789/ /pubmed/36616986 http://dx.doi.org/10.3390/s23010388 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Psotta, Carolin
Chaturvedi, Vivek
Gonzalez-Martinez, Juan F.
Sotres, Javier
Falk, Magnus
Portable Prussian Blue-Based Sensor for Bacterial Detection in Urine
title Portable Prussian Blue-Based Sensor for Bacterial Detection in Urine
title_full Portable Prussian Blue-Based Sensor for Bacterial Detection in Urine
title_fullStr Portable Prussian Blue-Based Sensor for Bacterial Detection in Urine
title_full_unstemmed Portable Prussian Blue-Based Sensor for Bacterial Detection in Urine
title_short Portable Prussian Blue-Based Sensor for Bacterial Detection in Urine
title_sort portable prussian blue-based sensor for bacterial detection in urine
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823789/
https://www.ncbi.nlm.nih.gov/pubmed/36616986
http://dx.doi.org/10.3390/s23010388
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