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Development of lateral flow analysis system for the determination of Escherichia coli and Salmonella enteritidis

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2019
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Abstract (EN)

In recent years, rapid and accurate detection of pathogenic bacteria has been a current research area in terms of public health and food safety. One of the effective methods for this purpose is Surface-enhanced Raman scattering (SERS), its sensitivity, signal amplification capability, portability, and paper-based horizontal flow immunoassay (LFIA) system; Due to their high analysis rate and low cost, they stand out as a powerful and effective technique for the detection of pathogenic microorganisms. In the first step of this study, E. coli and S. enteritidis strains selected and known common pathogenicity were used to generate the SERS-based LFIA system using the raman tag DTNB; 5,5 ́-Dithiobis(2-Nitrobenzoic acid). Quantitative analysis and rapid detection of selected bacteria was performed after pre-enrichment with Fe3O4/Au-PEI nanoparticles. For this purpose, 20 nm gold nanoparticle (AuNP) and 15 nm Fe3O4/Au-PEI were synthesized. In the next stage, optimized conditions for detection of selected microorganisms were investigated by using rennet enzyme cleaving casein. In the second stage of our study, Fe3O4/Au-PEI nanoparticles coated selected bacterial antibody were interacted with E. coli concentrations of 101-107 cfu/mL with used of enzyme based magnetic extraction LFIA system. Then, when the casein was hydrolyzed with the help of rennet, E. coli bound to Fe3O4/Au-PEI nanoparticles was separated by magnetic field. Free bacteria were carried out on nitrocellulose membrane with DTNB raman label bound to AuNPs on conjugation pad (AuNP DTNB antibody complex), and the paper-based LFIA system was then allowed to be detected bacteria concentration on the test line of the nitrocellulose membrane. Tracking the SERS signals of DTNB molecule, LOD: 0,52 cfu/mL and R2: 0,98 values were determined from a linear calibration curve against the increasing concentration of bacteria. These values have been shown to work exclusively for E. coli against different bacterial species such as B. subtilis, M. luteus, S. enteritidis strains. In the third stage of our study, synthetic urine, reference blood and commercial milk samples were used as biological samples. With the developed system, the efficiency of binding of selected E. coli was determined as 86% or more. In the last stage of our study, the effectiveness of E. coli was investigated in synthetic urine, reference blood and commercial milk known as biological samples. Here, this study showed that the synthetic urine, reference blood and milk, valuable nutrients especially indicator E. coli tested as biological samples confirmed the idea that we will detect other pathogen bacteria. In this study, an alternative method was considered due to the expensive antibody used in the determination of pathogen microorganisms. In accordance with this purpose, instead of the antibody used in LFIA system, it is aimed to use bacteriophages as an alternative method because of their natural affinity and high specificity of host selectivity. For this reason, the P22 phage selecting S. enteritidis as the host, and its antibody were used to compare. As a result of bacteriophage study, S. enteritidis (101-107 cfu/mL) was determined from SERS calibration curve as LOD: 7 cfu/mL and R2: 0,98 whereas LOD: 6 cfu/mL and R2: 0,98 were found in our antibody study. These results showed that bacteriophage would be an alternative and inexpensive method compared to antibody in the detection of pathogenic microorganisms. In our in vivo study, egg and chicken samples infected with S. enteritidis were found to bind and separate 90% or more bacteria when using our P22-bacteriophage-based LFIA system. As a result, it was found that our LFIA system works effectively and also bacteriophages can be an alternative method.

Author

Hasan İlhan

How to Cite

Hasan İlhan (Doctorate thesis). Development of lateral flow analysis system for the determination of Escherichia coli and Salmonella enteritidis, 2019, Hacettepe University.

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