Date of Award
12-2010
Document Type
Thesis
Degree Name
Master of Science (MS)
Legacy Department
Microbiology
Committee Chair/Advisor
Tzeng, Tzuen-Rong J
Committee Member
McNealy , Tamara
Committee Member
Jalili , Nader
Abstract
The increasing number of disease outbreaks results in a demand for novel pathogen detectors. Carbohydrates serving as receptors for pathogen lectins have become the focus of such research. Two primary sugars, ‡-D-mannose and ‡-L-fucose, as receptors for Escherichia coli and Pseudomonas aeruginosa, respectively, are of great interest to researchers due to their high affinity. These interactions can be studied using carbohydrate microarrays, which are also suitable platforms for detecting bacterial pathogens. In addition, carbohydrates have the potential to act as sensing molecules in microcantilever-based biosensors. The goal of this research was to design a carbohydrate microarray system to study the interactions between bacteria and their carbohydrate receptors, and to apply these results to development of a microcantilever-based biosensor.
First, a carbohydrate microarray system was developed and evaluated utilizing the recognition specificity between ‡-D-mannose and type-1 fimbriae of E. coli ORN178. Chemically synthesized polysaccharides were immobilized non-covalently onto nitrocellulose membrane-coated glass slides using a contact printer. This microarray system was used to establish the optimized conditions of bacterial cultivation and hybridization for the expression of lectins. It specifically detects E. coli ORN178 with a detection limit of 104-105 cells/membrane. This binding interaction is absent when using E. coli ORN208 (a mutant of ORN178 strain expressing abnormal type-1 fimbriae), or E. coli O157:H7 as the targets. In addition, this binding interaction is abolished when pre-exposing E. coli ORN178 to free mannose. Then, the feasibility of utilizing this carbohydrate microarray system for profiling of bacteria by their carbohydrate binding specificity was investigated using eight carbohydrates and six bacterial strains. Each bacterial strain was cultivated and allowed to hybridize to the carbohydrate microarray under its optimal conditions for cell growth and lectin expression.
Second, a gold-coated microcantilever-based biosensor was covalently functionalized with carbohydrates, which served as the sensing molecules, followed by hybridization with 106cells/mL or 109cells/mL E. coli strains expressing green fluorescent proteins. Fluorescence emitted from E. coli ORN178/pGREEN or E. coli ORN208/pGREEN cells of both concentrations was observed under an epi-fluorescent microscope. Statistical analysis of the resonance frequencies, measured using Polytec Micro System Analyzer (MSA)-400, of both uncoated microcantilevers and microcantilevers functionalized with carbohydrates indicated that carbohydrate molecules were uniformly coated on the surface of functionalized microcantilevers. However, there was no statistically significant evidence to conclude that these two bacterial strains bound specifically to these fabricated microcantilever surfaces, a result different from our expectation, probably due to the non-uniform binding of bacterial cells.
This research represents the first step into the development of a carbohydrate microarray system for the evaluation of bacterial binding specificity to host cell surface carbohydrates and a microcantilever biosensor based on the interactions between bacterial adhesins and host cell receptors. By exploring the use of adhesin-carbohydrate binding specificities for bacteria classification, identification, and detection, this research opens the door for more investigations in the bacteria-carbohydrate interactions and in the development of diagnostic tools and biosensors that are more stable, easier to fabricate, and ones that do not require sample pre-enrichment, cell lysis, or cell staining typically required for current antibody- or nucleic acid-based bioassays.
Recommended Citation
Cheng, Yunyan, "DEVELOPMENT OF A CARBOHYDRATE MICROARRAY SYSTEM AND A MICROCANTILEVER-BASED BIOSENSOR FOR DETECTION OF TARGET BACTERIA" (2010). All Theses. 1027.
https://tigerprints.clemson.edu/all_theses/1027