Interactions between bacterial surface and nanoparticles govern the performance of "chemical nose" biosensors

Abstract

Rapid and portable diagnosis of pathogenic bacteria can save lives lost from infectious diseases. Biosensors based on a "chemical nose" approach are attracting interest because they are versatile but the governing interactions between bacteria and the biosensors are poorly understood. Here, we use a "chemical nose" biosensor based on gold nanoparticles to explore the role of extracellular polymeric substances in bacteria-nanoparticle interactions. We employ simulations using Maxwell-Garnett theory to show how the type and extent of aggregation of nanoparticles influence their colorimetric response to bacteria. Using eight different species of Gram-positive and Gram-negative bacteria, we demonstrate that this "chemical nose" can detect and identify bacteria over two orders of magnitude of concentration (89% accuracy). Additionally, the "chemical nose" differentiates between binary and tertiary mixtures of the three most common hospital-isolated pathogens: Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa (100% accuracy). We demonstrate that the complex interactions between nanoparticles and bacterial surface determine the colorimetric response of gold nanoparticles and thus, govern the performance of "chemical nose" biosensors.

Keywords: Colorimetric; Extracellular polymeric substances; Gold nanoparticles; Lipid blots; Modeling; Pathogens.