Conference Program - ABRF 2011 - Association of Biomolecular ...

(W2) Spectral and Sequence DatabaseSearching in ProteomicsL. MartensGhent University, Ghent, BelgiumThis session will present an overview of more advanced methods tomatch acquired MS/MS spectra to peptides, including strategies todetect (unexpected) protein modifications, and the use of spectrallibraries for peptide identification by spectrum-to-spectrum matching.Introduced by some of the world’s foremost experts in these proteomicsinformatics challenges, this session is meant to provide a pragmaticintroduction to the topics for interested researchers, thus making thesemethods directly adoptable in the lab.(W2-1) ETD Performance and Complementarityto Other Fragmentation Methods for ProteomicAnalysisR. ChalkleyUniversity of California San Francisco, San Francisco, CA,United StatesRadical-driven fragmentation approaches present an alternative to thewell-established collisional cleavage approaches that have dominatedproteomic research up until now. With the recent availability ofelectron transfer dissociation (ETD) in commercial quadrupole iontrap and hybrid instruments, this technology is now accessible to manyresearchers. It has been described as a complementary approachto CID, and decision tree approaches have been employed where achoice between CID or ETD is made depending on the precursor m/zand charge. In this presentation I will discuss the performance of ETD forpeptide identification, drawing heavily on data acquired as part of the2011 iPRG study ‘Identification of Electron Transfer Dissocation (ETD)Mass Spectra’. Results will be compared to analyses of the same sampleusing CID and HCD, decision tree approaches and the differencein measuring data in the ion trap versus in the orbitrap detector. Acomparison of search engine performance will be presented andmethods for improving database search engine analysis of ETD datawill also be discussed.(W2-2) Discovery, Identification and Localization ofPost-Translational ModificationsN. BandeiraCenter for Computational Mass Spectrometry, Departmentof Computer Science and Engineering Skaggs School ofPharmacy and Pharmaceutical Sciences University ofCalifornia, San Diego, CA, United StatesMass spectrometry based analysis of post-translational modificationscommonly report thousands of modified-peptide identificationsaccompanied by both precisely and ambiguously localizedmodification sites. Since these identifications often motivate extensivefollow up studies, the confident identification of the peptide andaccurate localization of the modification site(s) remains one of themajor challenges in computational proteomics. As revealed by the2010 iPRG study on identification of phosphopeptides and localizationof phosphorylation sites, participants only attempted to call themodification sites for less than 2 out of every 3 identified spectraand actually disagreed on over 20% of all cases where at least twoparticipants called a modification site. In this talk we will cover currentand novel methods for identification of post-translationally modifiedpeptides and automated determination of site localization confidencescores and false discovery rates.(W2-3) Building and Using MS/MS Spectral Librariesfor Peptide Identifications in ProteomicsH. LamThe Hong Kong University of Science and Technology, ClearWater Bay, Hong Kong, ChinaSpectral library searching is an emerging approach in peptideidentifications from tandem mass spectra, a critical step in proteomicdata analysis. In this approach, a spectral library is first meticulouslycompiled from a large collection of previously observed and identifiedpeptide MS/MS spectra. An unknown spectrum is then identified bycomparing it to all the candidates in the spectral library for the mostsimilar match. Thanks to the reduction of search space to only thepreviously discovered peptides, and the use of real, experimentallyobserved reference spectra for more precise spectral matching, thisapproach is considerably faster and more sensitive than the popularalternative of sequence searching. This talk will explain the basicprinciples of spectral library building and searching, describe itsadvantages and limitations, and provide a starting point for researchersinterested in adopting this new approach in their data analysis. It willalso discuss the future outlook on the evolution and utility of spectrallibraries in the field of proteomics.(W3) Quantifying Protein Turnover by In VivoMetabolic Labeling(W3-1) Stable Isotope Tracers Applied to MeasuringRates of Protein Synthesis and Breakdown in Muscle:Principles and ApplicationsR.R. WolfeUniversity of Arkansas for Medical Sciences, Little Rock, AR,United StatesMuscle is in a constant state of turnover, meaning that it is continuouslysynthesized and broken down. The balance between the rates ofsynthesis and breakdown determines if an individual is gaining orloosing muscle mass. It is therefore of interest in a variety of physiologicalcircumstances to quantify the rates of muscle protein synthesis andbreakdown. Tracer methodology using both radioactive and stableisotopes has been used in a wide variety of kinetic studies, includingmeasurement of synthetic and breakdown rates of various compounds.Stable isotopes are particularly suited for the study of muscle proteinmetabolism, as multiple amino acid tracers can be used simultaneously,and multiple labels can be used with any individual amino acid,including labeling the nitrogen with 15N. Two basic approaches canbe used to measure muscle protein synthesis. The direct incorporationof a labeled amino acid is the most conventional. This techniqueinvolves infusion or injection of tracer and measurement of subsequentincorporation into muscle protein over time. The measurement of theprecursor enrichment, which is usually taken to be the free intracellularpool of the tracer amino acid, is necessary to calculate the actual rateof synthesis. Alternatively, the rate of muscle protein synthesis can bederived from the rate of uptake of an amino acid from blood. In thisWorkshop SessionAbstractsABRF 2011 — Technologies to Enable Personalized Medicine • 45