Electrochemical Immunosensor in Combination with an Artificial Neural Network Study for Pathogenic Bacteria Detection using a Modified Glassy Carbon Electrode

IF 1 4区 生物学 Q4 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Applied Biochemistry and Microbiology Pub Date : 2023-12-10 DOI:10.1134/S0003683823060261
S. Panhwar, H. A. Keerio, A. Ali, N. H. Khokhar, M. Muqeet, G. S. Solangi
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Abstract

We report here the results of studies related to the fabrication of an electrochemical immunosensor for the detection of Escherichia coli ATCC 25922 using AuNPs-GCE-avidin-Ab-E. coli based on complex compound. In the presence of targeted bacteria, the specific antibody was coated on the surface with gold nanoparticles (AuNPs). The detailed morphology of synthesized AuNPs was confirmed using analytical techniques. The proposed immunosensor revealed a high electrocatalytic activity and linear response at the peak potential value over a wide concentration of E. coli ATCC 25922 from 101 to 105 CFU/mL. The results were correlated with the linear equation of (R2 = 0.991). The recorded results were responded in the presence of targeted E. coli ATCC 25922 with other bacterial strains such as Salmonella typhi, Klebsiella aerogenes, and E. coli O57:H7 indicating a high selectivity of electrochemical immunosensor. A combined artificial neural network (ANN) approach serves as a powerful model to understand and analyze the intelligent data of the digital transformation output. The determined regression method of the fabricated sensor was selected for evaluation of the ANN-based technique that initiated to be a superior known method. The applied technique confirmed a great practical approach to targeted bacteria in spiked samples of the sandwich complex. Therefore, the satisfactory result demonstrates the feature of simulation data attainment and analysis is highly reliable and attractive. Moreover, the constructed immunosensor may be used to screen contaminated water and prevents an epidemic of life-threatening infectious disease.

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利用改性玻璃碳电极检测病原菌的电化学免疫传感器与人工神经网络结合研究
我们在此报告利用基于复合物的 AuNPs-GCE-avidin-Ab-E. coli 制作检测大肠杆菌 ATCC 25922 的电化学免疫传感器的相关研究结果。在目标细菌存在的情况下,特异性抗体被包覆在金纳米粒子(AuNPs)表面。利用分析技术确认了合成 AuNPs 的详细形态。所提出的免疫传感器具有很高的电催化活性,在大肠杆菌 ATCC 25922 从 101 CFU/mL 到 105 CFU/mL 的广泛浓度范围内,其峰值电位具有线性响应。结果与线性方程(R2 = 0.991)相关。在目标大肠杆菌 ATCC 25922 和其他细菌菌株(如伤寒沙门氏菌、产气克雷伯氏菌和大肠杆菌 O57:H7)存在的情况下,记录的结果都能得到响应,这表明电化学免疫传感器具有很高的选择性。人工神经网络(ANN)组合方法是理解和分析数字转换输出智能数据的强大模型。在对基于 ANN 的技术进行评估时,选择了已确定的已制造传感器的回归方法。所应用的技术证实了针对夹心复合物加标样品中细菌的一种非常实用的方法。因此,令人满意的结果表明,模拟数据的获取和分析具有高度可靠性和吸引力。此外,所构建的免疫传感器可用于筛查受污染的水源,防止威胁生命的传染病流行。
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来源期刊
Applied Biochemistry and Microbiology
Applied Biochemistry and Microbiology 生物-生物工程与应用微生物
CiteScore
1.70
自引率
12.50%
发文量
75
审稿时长
6-12 weeks
期刊介绍: Applied Biochemistry and Microbiology is an international peer reviewed journal that publishes original articles on biochemistry and microbiology that have or may have practical applications. The studies include: enzymes and mechanisms of enzymatic reactions, biosynthesis of low and high molecular physiologically active compounds; the studies of their structure and properties; biogenesis and pathways of their regulation; metabolism of producers of biologically active compounds, biocatalysis in organic synthesis, applied genetics of microorganisms, applied enzymology; protein and metabolic engineering, biochemical bases of phytoimmunity, applied aspects of biochemical and immunochemical analysis; biodegradation of xenobiotics; biosensors; biomedical research (without clinical studies). Along with experimental works, the journal publishes descriptions of novel research techniques and reviews on selected topics.
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