Showing papers by "Jimmy K. Eng published in 2012"

Accurate peptide fragment mass analysis: multiplexed peptide identification and quantification.

Abstract: Fourier transform-all reaction monitoring (FT-ARM) is a novel approach for the identification and quantification of peptides that relies upon the selectivity of high mass accuracy data and the specificity of peptide fragmentation patterns. An FT-ARM experiment involves continuous, data-independent, high mass accuracy MS/MS acquisition spanning a defined m/z range. Custom software was developed to search peptides against the multiplexed fragmentation spectra by comparing theoretical or empirical fragment ions against every fragmentation spectrum across the entire acquisition. A dot product score is calculated against each spectrum to generate a score chromatogram used for both identification and quantification. Chromatographic elution profile characteristics are not used to cluster precursor peptide signals to their respective fragment ions. FT-ARM identifications are demonstrated to be complementary to conventional data-dependent shotgun analysis, especially in cases where the data-dependent method fails because of fragmenting multiple overlapping precursors. The sensitivity, robustness, and specificity of FT-ARM quantification are shown to be analogous to selected reaction monitoring-based peptide quantification with the added benefit of minimal assay development. Thus, FT-ARM is demonstrated to be a novel and complementary data acquisition, identification, and quantification method for the large scale analysis of peptides.

Cross-linking measurements of the Potato leafroll virus reveal protein interaction topologies required for virion stability, aphid transmission, and virus-plant interactions.

Abstract: Protein interactions are critical determinants of insect transmission for viruses in the family Luteoviridae. Two luteovirid structural proteins, the capsid protein (CP) and the readthrough protein (RTP), contain multiple functional domains that regulate virus transmission. There is no structural information available for these economically important viruses. We used Protein Interaction Reporter (PIR) technology, a strategy that uses chemical cross-linking and high resolution mass spectrometry, to discover topological features of the Potato leafroll virus (PLRV) CP and RTP that are required for the diverse biological functions of PLRV virions. Four cross-linked sites were repeatedly detected, one linking CP monomers, two within the RTP, and one linking the RTP and CP. Virus mutants with triple amino acid deletions immediately adjacent to or encompassing the cross-linked sites were defective in virion stability, RTP incorporation into the capsid, and aphid transmission. Plants infected with a new, infectio...

Sites of ubiquitin attachment in Saccharomyces cerevisiae.

Abstract: Sites of ubiquitin modification have been identified by mass spectrometry based on the increase in molecular mass of a tryptic peptide carrying two additional glycine residues from the ubiquitin moiety. However, such peptides with GG shifts have been difficult to discover. We identify 870 unique sites of ubiquitin attachment on 438 different proteins of the yeast Saccharomyces cerevisiae.

In vivo application of photocleavable protein interaction reporter technology.

Abstract: In vivo protein structures and protein–protein interactions are critical to the function of proteins in biological systems. As a complementary approach to traditional protein interaction identification methods, cross-linking strategies are beginning to provide additional data on protein and protein complex topological features. Previously, photocleavable protein interaction reporter (pcPIR) technology was demonstrated by cross-linking pure proteins and protein complexes and the use of ultraviolet light to cleave or release cross-linked peptides to enable identification. In the present report, the pcPIR strategy is applied to Escherichia coli cells, and in vivo protein interactions and topologies are measured. More than 1600 labeled peptides from E. coli were identified, indicating that many protein sites react with pcPIR in vivo. From those labeled sites, 53 in vivo intercross-linked peptide pairs were identified and manually validated. Approximately half of the interactions have been reported using other...

A likelihood-based scoring method for peptide identification using mass spectrometry

Abstract: Mass spectrometry provides a high-throughput approach to identify proteins in biological samples. A key step in the analysis of mass spectrometry data is to identify the peptide sequence that, most probably, gave rise to each observed spectrum. This is often tackled using a database search: each observed spectrum is compared against a large number of theoretical “expected” spectra predicted from candidate peptide sequences in a database, and the best match is identified using some heuristic scoring criterion. Here we provide a more principled, likelihood-based, scoring criterion for this problem. Specifically, we introduce a probabilistic model that allows one to assess, for each theoretical spectrum, the probability that it would produce the observed spectrum. This probabilistic model takes account of peak locations and intensities, in both observed and theoretical spectra, which enables incorporation of detailed knowledge of chemical plausibility in peptide identification. Besides placing peptide scoring on a sounder theoretical footing, the likelihood-based score also has important practical benefits: it provides natural measures for assessing the uncertainty of each identification, and in comparisons on benchmark data it produced more accurate peptide identifications than other methods, including SEQUEST. Although we focus here on peptide identification, our scoring rule could easily be integrated into any downstream analyses that require peptide-spectrum match scores.