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dc.contributor.authorMuller, Stephan A.
dc.contributor.authorKohajda, Tibor
dc.contributor.authorFindeiß, Sven
dc.contributor.authorStadler, Peter F.
dc.contributor.authorMag Washietl, Stefan
dc.contributor.authorKellis, Manolis
dc.contributor.authorBergen, Martin von
dc.contributor.authorKalkhof, Stefan
dc.date.accessioned2011-04-28T18:43:35Z
dc.date.available2011-04-28T18:43:35Z
dc.date.issued2010-08
dc.date.submitted2010-07
dc.identifier.issn1618-2642
dc.identifier.issn1618-2650
dc.identifier.urihttp://hdl.handle.net/1721.1/62552
dc.description.abstractProteins with molecular weights of <25 kDa are involved in major biological processes such as ribosome formation, stress adaption (e.g., temperature reduction) and cell cycle control. Despite their importance, the coverage of smaller proteins in standard proteome studies is rather sparse. Here we investigated biochemical and mass spectrometric parameters that influence coverage and validity of identification. The underrepresentation of low molecular weight (LMW) proteins may be attributed to the low numbers of proteolytic peptides formed by tryptic digestion as well as their tendency to be lost in protein separation and concentration/desalting procedures. In a systematic investigation of the LMW proteome of Escherichia coli, a total of 455 LMW proteins (27% of the 1672 listed in the SwissProt protein database) were identified, corresponding to a coverage of 62% of the known cytosolic LMW proteins. Of these proteins, 93 had not yet been functionally classified, and five had not previously been confirmed at the protein level. In this study, the influences of protein extraction (either urea or TFA), proteolytic digestion (solely, and the combined usage of trypsin and AspN as endoproteases) and protein separation (gel- or non-gel-based) were investigated. Compared to the standard procedure based solely on the use of urea lysis buffer, in-gel separation and tryptic digestion, the complementary use of TFA for extraction or endoprotease AspN for proteolysis permits the identification of an extra 72 (32%) and 51 proteins (23%), respectively. Regarding mass spectrometry analysis with an LTQ Orbitrap mass spectrometer, collision-induced fragmentation (CID and HCD) and electron transfer dissociation using the linear ion trap (IT) or the Orbitrap as the analyzer were compared. IT-CID was found to yield the best identification rate, whereas IT-ETD provided almost comparable results in terms of LMW proteome coverage. The high overlap between the proteins identified with IT-CID and IT-ETD allowed the validation of 75% of the identified proteins using this orthogonal fragmentation technique. Furthermore, a new approach to evaluating and improving the completeness of protein databases that utilizes the program RNAcode was introduced and examined.en_US
dc.description.sponsorshipHelmholtz Alliance on Systems Biologyen_US
dc.description.sponsorshipEuropean Cooperation in the Field of Scientific and Technical Research (Organization) (COST Action "Systems Chemistry" CM0703)en_US
dc.description.sponsorshipDeutsche Forschungsgemeinschaft (DFG) (Grant no. STA 850/7-1)en_US
dc.description.sponsorshipErwin Schrodinger Fellowshipen_US
dc.language.isoen_US
dc.publisherSpringeren_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s00216-010-4093-xen_US
dc.rightsCreative Commons Attribution-Noncommercialen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc/2.5en_US
dc.sourceMIT web domainen_US
dc.titleOptimization of parameters for coverage of low molecular weight proteinsen_US
dc.typeArticleen_US
dc.identifier.citationMüller, Stephan A. et al. “Optimization of Parameters for Coverage of Low Molecular Weight Proteins.” Analytical and Bioanalytical Chemistry 398.7-8 (2010) : 2867-2881. Copyright © 2010, The Author(s)en_US
dc.contributor.departmentBroad Institute of MIT and Harvarden_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.approverKellis, Manolis
dc.contributor.mitauthorMag Washietl, Stefan
dc.contributor.mitauthorKellis, Manolis
dc.relation.journalAnalytical and Bioanalytical chemistryen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsMüller, Stephan A.; Kohajda, Tibor; Findeiß, Sven; Stadler, Peter F.; Washietl, Stefan; Kellis, Manolis; Bergen, Martin; Kalkhof, Stefanen
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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