Differential sensing of hydrophobic analytes with serum albumins

Abstract

In the last decade, there has been a growing interest in the use of differential sensing for molecular recognition. Inspired by the mammalian olfactory system, differential sensing employs an array of non-selective receptors, which through cross-reactive interactions, create a distinct pattern for each analyte tested. The unique fingerprints obtained for each analyte with differential sensing are studied with statistical analysis techniques, such as principal component analysis and linear discriminant analysis. It was postulated that serum albumin proteins would be applicable to differential sensing schemes due to significant differences in sequence identity between different serum albumin species, and due to the wide range of hydrophobic molecules which are known to bind to these proteins. Consequently, cross-reactive serum albumin arrays were developed, utilizing hydrophobic fluorescent indicators to detect hydrophobic molecules. As such, serum albumin cross-reactive arrays were employed to discriminate subtly different hydrophobic analytes, and mixtures of these analytes, in the form of terpenes and perfumes, plasticizers and plastic explosive mixtures, and glycerides and adipocyte extracts. In this doctoral work, a detailed review of the field of differential sensing, and a thorough study of principal component analysis and linear discriminant analysis in various differential sensing scenarios, are given. These introductory chapters aid in better understanding the methods and techniques applied in later experimental chapters. In chapter 3, serum albumins, a PRODAN indicator, and an additive are shown to discriminate five terpene analytes and terpene doped perfumes. Chapter 4 describes an array with serum albumins, two dansyl fluorophores, and an additive which successfully differentiate the plasticizers found within the plastic explosives C4 and Semtex and simulated C4 and Semtex mixtures. Discrimination of these simulated mixtures was also achieved with this array in the presence of soil contaminants, demonstrating the potential real-world applicability of this sensing ensemble. Finally, chapter 5 details an array consisting of serum albumins, several fluorescent indicators, and a Grubb's olefin metathesis reaction, to differentiate saturated and unsaturated triglycerides, diglycerides, and monoglycerides. Mixtures of glycerides in adipocyte extracts taken from rats with different health states were then successfully discriminated, showing promise for clinical applications in differentiating adipoctyes from pre-diabetic, type 2 diabetic, and non-diabetic individuals.