Title of article :
Characterization of self-assembled monolayers (SAMs) on silicon substrate comparative with polymer substrate for Escherichia coli O157:H7 detection Review Article
Carmen Moldovan، نويسنده , , Carmen Mihailescu، نويسنده , , Dana Stan، نويسنده , , Lavinia Ruta، نويسنده , , Rodica Iosub، نويسنده , , Raluca Gavrila، نويسنده , , Munizer Purica، نويسنده , , Schiopu Vasilica، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
This article presents the characterization of two substrates, silicon and polymer coated with gold, that are functionalized by mixed self-assembled monolayers (SAMs) in order to efficiently immobilize the anti-Escherichia coli O157:H7 polyclonal purified antibody.
A biosurface functionalized by SAMs (self-assembled monolayers) technique has been developed. Immobilization of goat anti-E. coli O157:H7 antibody was performed by covalently bonding of thiolate mixed self-assembled monolayers (SAMs) realized on two substrates: polymer coated with gold and silicon coated with gold. The F(ab′)2 fragments of the antibodies have been used for eliminating nonspecific bindings between the Fc portions of antibodies and the Fc receptor on cells. The properties of the monolayers and the biofilm formatted with attached antibody molecules were analyzed at each step using infrared spectroscopy (FTIR-ATR), atomic force microscopy (AFM), scanning electron microscopy (SEM) and cyclic voltammetry (CV). In our study the gold-coated silicon substrates approach yielded the best results.
These experimental results revealed the necessity to investigate each stage of the immobilization process taking into account in the same time the factors that influence the chemistry of the surface and the further interactions as well and also provide a solid basis for further studies aiming at elaborating sensitive and specific immunosensor or a microarray for the detection of E. coli O157:H7.
Mixed self-assembled monolayers , Escherichia coli O157:H7 gold , Immunosensor , FTIR-ATR
Journal title :
Applied Surface Science