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Electrochemical Biosensors for Pathogenic Bacteria

  • Author(s): Saucedo, Nuvia Maria
  • Advisor(s): Mulchandani, Ashok
  • et al.
Abstract

ABSTRACT OF THE DISSERTATION

Electrochemical Biosensors for Pathogenic Bacteria

by

Nuvia Maria Saucedo

Doctor of Philosophy, Graduate Program in Chemistry

University of California, Riverside, August 2015

Professor Ashok Mulchandani, Chairperson

Microbial diseases due to infections from bacteria and viruses constitute a major cause of death. Though recent technological advances have allowed for sensitive and selective detection of pathogenic bacteria, these methods are multi-step, have long assay times and require skilled lab technicians. Owing to the lack of point-of-care detection methods, clinical infections are often misdiagnosed as they rely on patient symptoms instead of empirical tests. This leads to prescription of inappropriate medication and prolonged suffering from infection. The use of antibiotics for viral infections and prescribing of ineffective antibiotics for bacterial infections has contributed to the rise of a new threat, the emergence of antibiotic-resistant bacteria. Thus, there is an urgent need for development of detection platforms which are sensitive, selective, point-of-care and allow for determination of the pathogen.

To address this need, electrochemical biosensors were fabricated utilizing different transduction materials, including carbon nanotubes (CNTs), conductive polymer 4-(3-pyrrolyl) butyric acid, graphene and reduced graphene oxide (rGO). Owing to their high sensitivity, robustness, and ease of device integration, these materials are ideal candidates for the development of next generation biosensors. For selective capture of bacteria, the transducer surface was functionalized with lectins which serve as the bioreceptor element. The lectin-carbohydrate interactions, which are known to be highly specific, were exploited to result in unique binding profiles allowing for the distinction between bacterial and viral pathogens as well as between different bacterial strains. Further, the biosensors were capable of probing the viability of bacteria by detecting changes in pH caused by the excretion of metabolites from healthy bacterial cells. The proposed detection scheme thus allowed for screening of antibiotics and ranking of antibiotic efficacy against different bacterial strains. This work demonstrates the performance of these biosensors as quick screens for distinguishing bacterial from viral infections, a novel concept, and determining antibiotic efficacy prior to prescription thus addressing antibiotic misuse and the emergence of antibiotic resistant-bacteria.

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