Browsing by Subject "Bacteria detection"

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Open Access
Disintegration and machine-learning-assisted identification of bacteria on antimicrobial and plasmonic Ag–CuxO nanostructures
(American Chemical Society, 2023-03-08) Şahin, F.; Çamdal, A.; Şahin, G. D.; Ceylan, A.; Ruzi, M.; Önses, Mustafa Serdar
Bacteria cause many common infections and are the culprit of many outbreaks throughout history that have led to the loss of millions of lives. Contamination of inanimate surfaces in clinics, the food chain, and the environment poses a significant threat to humanity, with the increase in antimicrobial resistance exacerbating the issue. Two key strategies to address this issue are antibacterial coatings and effective detection of bacterial contamination. In this study, we present the formation of antimicrobial and plasmonic surfaces based on Ag–CuxO nanostructures using green synthesis methods and low-cost paper substrates. The fabricated nanostructured surfaces exhibit excellent bactericidal efficiency and high surface-enhanced Raman scattering (SERS) activity. The CuxO ensures outstanding and rapid antibacterial activity within 30 min, with a rate of >99.99% against typical Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus bacteria. The plasmonic Ag nanoparticles facilitate the electromagnetic enhancement of Raman scattering and enables rapid, label-free, and sensitive identification of bacteria at a concentration as low as 103 cfu/mL. The detection of different strains at this low concentration is attributed to the leaching of the intracellular components of the bacteria caused by the nanostructures. Additionally, SERS is coupled with machine learning algorithms for the automated identification of bacteria with an accuracy that exceeds 96%. The proposed strategy achieves effective prevention of bacterial contamination and accurate identification of the bacteria on the same material platform by using sustainable and low-cost materials.
Open Access
Performance comparison of aptamer- and antibody-based biosensors for bacteria detection on glass surfaces
(Taylor & Francis Inc., 2025) Balcı, O.; Kürekçi, A.; Özalp, V. C.; Barbaros, Çetin
Antibodies are the most common ligands in commercial and research assay systems for detecting whole pathogen cells. On the other hand, aptamers are superior ligands with many advantages over antibodies in sensitive and robust assay development. Extensive comparisons between aptamer-based biosensors and immune sensors are limited to protein analytes. Here, we report a comparison of ligands (four antibodies and one aptamer for each bacteria) to be used as a biosensor for Escherichia coli and Staphylococcus aureus on glass surfaces through systematic experiments. We have demon-strated that anti-E. coli antibody and mouse monoclonal to S. aureus have the best performance among the compared ligands. Hence, the ligands with the best performance were further investigated within the scope of linear range, analytical sensitivity, and reproducibility of the results. We have demonstrated that anti-E. coli antibody with a capture efficiency of 89.1% and mouse monoclonal to S. aureus with a capture efficiency of 88.2% have the best performance among the compared ligands. The results suggest that antibody ligands function with higher efficiency than aptamer ligands but aptamers have strong potential as an analytical tool.