Analysis of Biopolymers and Synthetic Polymers Using Structurally Selective Analytical Techniques in Combination with Mass Spectrometry
Harris, Rachel Ann
The development of novel analytical methods and instrumentation has enabled the characterization of increasingly complex samples. In particular, mass spectrometry (MS) is a technique that has found broad application in the analysis of biological extracts and other complex samples due to its speed, sensitivity, and specificity. However, mass spectrometry as an analytical technique is fundamentally limited by its inability to distinguish the presence of isomers, compounds that have the same mass-to-charge (m/z), which are common in both lipid extracts and synthetic polymer samples. In both cases, the inability to elucidate structural isomerism constitutes a critical loss of information that may result in negative experimental outcomes. For example, the position of the double bond in a lipid signaling molecule has been shown to modulate its binding affinity to Cytochrome c Oxidase, but current mass spectrometry-based lipidomics workflows are unable to elucidate double bond position in identified lipids. These challenges motivate the current work, which seeks to develop analytical tools and methodologies that can be utilized in conjunction with mass spectrometry to address the isomer problem and improve the structural characterization of lipid and synthetic polymer samples. Several experimental approaches have been explored for distinguishing isomers in this work, including the utilization of ion mobility (IM) as an orthogonal dimension of separation to mass analysis, and novel fragmentation approaches such as ozonolysis (Oz) and surface induced dissociation (SID), but a unifying theme emerges that a combination of multiple structurally-selective analytical techniques are necessary for delineating all the forms of isomerism that may be present in a sample. The methods developed in this work will increase the field’s capacity for reducing isomerism, characterizing complex samples, and enable important discoveries in applications research such as lipidomics.