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Membrane protein shaving with thermolysin can be used to evaluate topology predictors
Stockholm University, Science for Life Laboratory (SciLifeLab). Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Science for Life Laboratory (SciLifeLab). Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Science for Life Laboratory (SciLifeLab). Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Science for Life Laboratory (SciLifeLab). Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
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2013 (English)In: Proteomics, ISSN 1615-9853, E-ISSN 1615-9861, Vol. 13, no 9, 1467-1480 p.Article in journal (Refereed) Published
Abstract [en]

Topology analysis of membrane proteins can be obtained by enzymatic shaving in combination with MS identification of peptides. Ideally, such analysis could provide quite detailed information about the membrane spanning regions. Here, we examine the ability of some shaving enzymes to provide large-scale analysis of membrane proteome topologies. To compare different shaving enzymes, we first analyzed the detected peptides from two over-expressed proteins. Second, we analyzed the peptides from non-over-expressed Escherichia coli membrane proteins with known structure to evaluate the shaving methods. Finally, the identified peptides were used to test the accuracy of a number of topology predictors. At the end we suggest that the usage of thermolysin, an enzyme working at the natural pH of the cell for membrane shaving, is superior because: (i) we detect a similar number of peptides and proteins using thermolysin and trypsin; (ii) thermolysin shaving can be run at a natural pH and (iii) the incubation time is quite short. (iv) Fewer detected peptides from thermolysin shaving originate from the transmembrane regions. Using thermolysin shaving we can also provide a clear separation between the best and the less accurate topology predictors, indicating that using data from shaving can provide valuable information when developing new topology predictors.

Place, publisher, year, edition, pages
2013. Vol. 13, no 9, 1467-1480 p.
Keyword [en]
Bioinformatics, Digestion on-membrane, Mass spectra, Membrane proteins
National Category
Biochemistry and Molecular Biology
Identifiers
URN: urn:nbn:se:su:diva-90357DOI: 10.1002/pmic.201200517ISI: 000318049800011OAI: oai:DiVA.org:su-90357DiVA: diva2:631262
Funder
Swedish Research Council, VR-NT 2009-5072Swedish Research Council, VR-M 2007-3065Swedish Research Council, VR-NT 2008-3454Swedish Research Council, 2009-698
Note

AuthorCount:7;

Available from: 2013-06-20 Created: 2013-06-03 Last updated: 2017-12-06Bibliographically approved

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Skwark, MarcinNilsson, DanielGranholm, ViktorElofsson, Arne
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