Abstract Time-consuming diagnosis of bacterial blood stream infections and inappropriate antibiotic therapy have critical implications for patient outcome – with mortality figures rising for every hour of delayed treatment. The development of diagnostic methods that are capable of selective and rapid bacteria detection, and do not rely on preliminary blood culturing and Gram-staining procedures, is imperative in providing effective therapy and preventing multi-resistance. The aim of this dissertation was to develop a quantum dot based and Gram-specific bacteria labelling protocol. Focused on the detection of Gram-negative species, a two-step conjugation protocol was produced to functionalise quantum dots with anti-lipid A antibodies. Ionic adsorption and EDC chemistry were used to obtain oriented and covalent conjugation of antibodies to the quantum dot surface. In order to reduce non-specific binding of unreacted carboxylic groups on the conjugates to the bacterial membrane, and optimise the accuracy of detection, blocking experiments were conducted with molecules that could provide a neutral surface charge and sterically block open sites. To access lipid A on E. coli cells, three different antigen retrieval methods were tested. As a result, the developed quantum dot-anti lipid A conjugates were able to detect and specifically label Gram-negative E. coli cells after treatment with 0.6mM EDTA or acetic acid pH 3.58 at 42.5°C. 1% BSA reduced non-specific binding to untreated E. coli cells. Furthermore, in comparison to experiments performed with Tris as a blocking agent, the protein reduced non-specific binding to Gram-positive cells. The results obtained in this project are a step further in the development of a new method to rapidly detect bacteria Gram-specifically.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-182047 |
| Date | January 2016 |
| Creators | Jahnsen, Ann-Lena |
| Publisher | KTH, Skolan för teknik och hälsa (STH) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | TRITA-STH ; 2016:7 |
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