Photonic sensor based on surface imprinted polymers for enhanced point-of-care diagnosis of bacterial urinary tract infections

Effective bacterial detection is crucial for health diagnostics, particularly for the detection of pathogenic species like Escherichia coli (E. coli), which is responsible for up to 90% of urinary tract infections (UTIs), is especially crucial. Current detection methods are time-consuming, often delaying diagnosis and treatment. This study introduces an innovative approach for rapid E. coli detection using porous silicon (PSi) substrates combined with Surface Imprinted Polymers (SIPs) for photoluminescence-based (PL-based) E. coli detection. The PSi/SIP substrates offer high sensitivity, selectivity, and a low limit of detection (LOD) without the need for natural recognition elements. These substrates, fabricated via metal-assisted chemical etching (MACE) and PDMS-based E. coli imprinting, demonstrate reliable repeatability and a fast detection. Real-time detection experiments in phosphate-buffered saline (PBS) and urine showed consistent stair-like quenching of the PL signal with increasing E. coli concentrations, achieving theoretical LODs of approximately 13 ± 2 CFU/mL in PBS and 17 ± 3 CFU/mL in urine. The substrates exhibited excellent selectivity, differentiating E. coli from other species such as Cronobacter sakazakii (C. sakazakii) and Listeria monocytogenes. The high sensitivity and reproducibility of PSi/SIP substrates, along with the ease of use and rapid detection capabilities of the resulting sensor, highlight the potential of this novel platform for point-of-care (PoC) applications in clinical diagnostics.

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Publication Details

Journal
Biosensors and Bioelectronics
Published
2024-11-05
DOI
https://doi.org/10.1016/j.bios.2024.116916
Citations
7
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
1.29

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article

Photonic sensor based on surface imprinted polymers for enhanced point-of-care diagnosis of bacterial urinary tract infections

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7 citations
Biosensors and Bioelectronics
Biosensors and Analytical Detection
1.29
article

Photonic sensor based on surface imprinted polymers for enhanced point-of-care diagnosis of bacterial urinary tract infections

Valerii Myndrul, Rocio Arreguin Campos, Kasper Eersels, Igor Iatsunskyi, Bart van Grinsven, Flavia Di Scala
article en
7 citations

Abstract

Effective bacterial detection is crucial for health diagnostics, particularly for the detection of pathogenic species like Escherichia coli (E. coli), which is responsible for up to 90% of urinary tract infections (UTIs), is especially crucial. Current detection methods are time-consuming, often delaying diagnosis and treatment. This study introduces an innovative approach for rapid E. coli detection using porous silicon (PSi) substrates combined with Surface Imprinted Polymers (SIPs) for photoluminescence-based (PL-based) E. coli detection. The PSi/SIP substrates offer high sensitivity, selectivity, and a low limit of detection (LOD) without the need for natural recognition elements. These substrates, fabricated via metal-assisted chemical etching (MACE) and PDMS-based E. coli imprinting, demonstrate reliable repeatability and a fast detection. Real-time detection experiments in phosphate-buffered saline (PBS) and urine showed consistent stair-like quenching of the PL signal with increasing E. coli concentrations, achieving theoretical LODs of approximately 13 ± 2 CFU/mL in PBS and 17 ± 3 CFU/mL in urine. The substrates exhibited excellent selectivity, differentiating E. coli from other species such as Cronobacter sakazakii (C. sakazakii) and Listeria monocytogenes. The high sensitivity and reproducibility of PSi/SIP substrates, along with the ease of use and rapid detection capabilities of the resulting sensor, highlight the potential of this novel platform for point-of-care (PoC) applications in clinical diagnostics.

Biosensors and BioelectronicsVol. 268
Maastricht University (NL), Adam Mickiewicz University in Poznań (PL)
Narodowe Centrum Nauki
Openalex Percentile: Top 21%
Biosensors and Analytical Detection
1.29
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