Discriminating macromolecular interactions based on an impedimetric fingerprint supported by multivariate data analysis for rapid and label-free Escherichia coli recognition in human urine

Adrian Koterwa; Mattia Pierpaoli; Bożena Nejman-Faleńczyk; Sylwia Bloch; Artur Zieliński; Wioletta Adamus-Białek; Zofia Jeleniewska; Bartosz Trzaskowski; Robert Bogdanowicz; Grzegorz Węgrzyn; Paweł Niedziałkowski; Jacek Ryl

doi:10.1016/j.bios.2023.115561

Discriminating macromolecular interactions based on an impedimetric fingerprint supported by multivariate data analysis for rapid and label-free Escherichia coli recognition in human urine

Abstract

This manuscript presents a novel approach to address the challenges of electrode fouling and highly complex electrode nanoarchitecture, which are primary concerns for biosensors operating in real environments. The proposed approach utilizes multiparametric impedance discriminant analysis (MIDA) to obtain a fingerprint of the macromolecular interactions on flat glassy carbon surfaces, achieved through self-organized, drop-cast, receptor-functionalized Au nanocube (AuNC) patterns. Real-time monitoring is combined with singular value decomposition and partial least squares discriminant analysis, which enables selective identification of the analyte from raw impedance data, without the use of electric equivalent circuits. As a proof-of-concept, the authors demonstrate the ability to detect Escherichia coli in real human urine using an aptamer-based biosensor that targets RNA polymerase. This is significant, as uropathogenic E. coli is a difficult-to-treat pathogen that is responsible for the majority of hospital-acquired urinary tract infection cases. The proposed approach offers a limit of detection of 11.3 CFU/mL for the uropathogenic E. coli strain No. 57, an analytical range in all studied concentrations (up to 105 CFU/mL), without the use of antifouling strategies, yet not being specific vs other E.coli strain studied (BL21(DE3)). The MIDA approach allowed to identify negative overpotentials (−0.35 to −0.10 V vs Ag/AgCl) as most suitable for the analysis, offering over 80% sensitivity and accuracy, and the measurement was carried out in just 2 min. Moreover, this approach is scalable and can be applied to other biosensor platforms.

Citations

2

CrossRef
0

Web of Science
1

Scopus

Authors (12)

Adrian Koterwa
- Uniwersytet Gdański
Mattia Pierpaoli dr
Bożena Nejman-Faleńczyk
- Uniwersytet Gdański
Sylwia Bloch
- Uniwersytet Gdański
Artur Zieliński dr hab. inż.
Wioletta Adamus-Białek
- Uniwersytet Jana Kochanowskiego w Kielcach
Zofia Jeleniewska
Bartosz Trzaskowski
- Uniwersytet Warszawski
Robert Bogdanowicz dr hab. inż.
Grzegorz Węgrzyn Profesor
- Uniwersytet Gdański
Paweł Niedziałkowski Dr
- Uniwersytet Gdański
Jacek Ryl dr hab. inż.

Cite as

Full text

download paper

downloaded 28 times

Publication version: Accepted or Published Version
DOI:: Digital Object Identifier (open in new tab) 10.1016/j.bios.2023.115561
License: open in new tab

full content of the article see on external site open in new tab

Keywords

Details

Category:

Articles

Type:

artykuły w czasopismach

Published in:

BIOSENSORS & BIOELECTRONICS no. 238,
ISSN: 0956-5663

Language:

English

Publication year:

2023

Bibliographic description:

Koterwa A., Pierpaoli M., Nejman-Faleńczyk B., Bloch S., Zieliński A., Adamus-Białek W., Jeleniewska Z., Trzaskowski B., Bogdanowicz R., Węgrzyn G., Niedziałkowski P., Ryl J.: Discriminating macromolecular interactions based on an impedimetric fingerprint supported by multivariate data analysis for rapid and label-free Escherichia coli recognition in human urine// BIOSENSORS & BIOELECTRONICS -,iss. 238 (2023), s.115561-

DOI: