Mason, Christopher J.

Abstract Motivation: Using stable isotopes in global proteome scans, labeled molecules from one sample are pooled with unlabeled molecules from another sample and subsequently subjected to mass-spectral analysis. Stable-isotope methodologies make use of the fact that identical molecules of different stable-isotope compositions are differentiated in a mass spectrometer and are represented in a mass spectrum as distinct isotopic clusters with a known mass shift. We describe two multivariable linear regression models for 16O/18O stable-isotope labeled data that jointly model pairs of resolved isotopic clusters from the same peptide and quantify the abundance present in each of the two biological samples while concurrently accounting for peptide-specific incorporation rates of the heavy isotope. The abundance measure for each peptide from the two biological samples is then used in down-stream statistical analyses, e.g. differential expression analysis. Because the multivariable regression models are able to correct for the abundance of the labeled peptide that appear as an unlabeled peptide due to the inability to exchange the natural C-terminal oxygen for the heavy isotope, they are particularly advantageous for a two-step digestion/labeling procedure. We discuss how estimates from the regression model are used to quantify the variability of the estimated abundance measures for the paired samples. Although discussed in the context of 16O/18O stable-isotope labeled data, the multivariable regression models are generalizable to other stable-isotope labeled technologies. Contact: eckel@mayo.edu

AbstractBackground: One of the numerous proteins causing amyloidosis is transthyretin (TTR), a protein usually responsible for the transport of thyroxine and retinol-binding protein. Variants within TTR cause it to aggregate and form insoluble fibers that accumulate in tissue, leading to organ dysfunction.Methods: TTR was immunoprecipitated from serum by use of a polyclonal antibody and subsequently reduced with tris(2-carboxyethyl)phosphine. The purified TTR was then analyzed by fast-gradient liquid chromatography–dual-electrospray ionization Fourier-transform ion-cyclotron-resonance (FT-ICR) mass spectrometry. DNA sequencing was performed on all samples used in this study.Results: Because of the inherent limitations in achieving high mass measurement accuracy based on the most abundant isotopic mass, we applied a fitting procedure that allowed determination of monoisotopic mass. Wild-type TTR (mean molecular mass, 13 761 Da) and its associated variant forms could be distinguished because of the high molecular mass accuracy afforded by FT-ICR (≤3 ppm) except for instances involving isobaric species or when isotopic distributions overlapped significantly. The [M + 11 H+]11+ charge state for all samples was used to determine the mass accuracies for both wild-type and variant forms of the protein. We correctly assigned seven of seven TTR variants. Moreover, using a combination of proteomic and genomic technologies, we discovered and characterized a previously unreported cis double mutation with a mass only 2 Da different from wild-type TTR. Furthermore, DNA sequencing of the TTR gene for all individuals in this study completely agreed with the intact protein measurements.Conclusions: FT-ICR mass spectrometry has sufficient mass accuracy to identify genetic variants of immunoaffinity-purified TTR. We believe that 91% of known TTR variants could be detected by this technique.