Mass Spectrometric Deconvolution of Libraries of Natural Peptide Toxins

Abstract

This thesis deals with the analysis of natural peptide libraries using mass spectrometry. In the course of the study, both ribosomal and non-ribosomal classes of peptides have been investigated. Microheterogeneity, post-translational modifications (PTM), isobaric amino acids and disulfide crosslinks present critical challenges in routine mass spectral structure determination of natural peptides. These problems form the core of this thesis. Chapter 2 describes an approach where chemical derivatization, in unison with high resolution LC-MSn experiments, resulted in deconvolution of a microheterogenous peptide library of B. subtilis K1. Chapter 3 describes an approach for distinction between isobaric amino acids (Leu/Ile/Hyp), by the use of combined ETD-CID fragmentation, through characteristic side chain losses. Chapters 4-6 address a long standing problem in structure elucidation of peptide toxins; the determination of disulfide connectivity. Through the use of direct mass spectral CID fragmentation, a methodology has been proposed for determination of the S-S pairing schemes in polypeptides. Further, an algorithm DisConnect has been developed for a rapid and robust solution to the problem. This general approach is applicable to both peptides and proteins, irrespective of the size and the number of disulfide bonds present. The method has been successfully applied to a large number of peptide toxins from marine cone snails, conotoxins, synthetic foldamers and proteins. Chapter 7 describes an attempt to integrate next generation sequencing (NGS) data with mass spectrometric analysis of the crude venom. This approach couples rapidly generated cDNA sequences, with high-throughput LC-ESI-MS/MS analysis, which provides mass spectral fragmentation information. An algorithm has been developed that allows the construction of a putative conus peptide database from the NGS data, followed by a protocol that permits rapid annotation of tandem MS data. The approach is exemplified by an analysis of the peptide components present in the venom of Conus amadis, yielding 225 chemically unique sequences, with identification of more than 150 sites of PTMs. In summary, this thesis presents different methodologies that address the existing limitations of de novo mass spectral structure determination of natural peptides and presents new methodologies that permit for rapid and efficient analysis of complex mixtures.