Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
13
pubmed:dateCreated
2008-7-17
pubmed:abstractText
The analytical performance of MALDI-MS is highly influenced by sample preparation and the choice of matrix. Here we present an improved MALDI-MS sample preparation method for peptide mass mapping and peptide analysis, based on the use of the 2,5-dihydroxybenzoic acid matrix and prestructured sample supports, termed: matrix layer (ML). This sample preparation is easy to use and results in a rapid automated MALDI-MS and MS/MS with high quality spectra acquisition. The between-spot variation was investigated using standard peptides and statistical treatment of data confirmed the improvement gained with the ML method. Furthermore, the sample preparation method proved to be highly sensitive, in the lower-attomole range for peptides, and we improved the performance of MALDI-MS/MS for characterization of phosphopeptides as well. The method is versatile for the routine analysis of in-gel tryptic digests thereby allowing for an improved protein sequence coverage. Furthermore, reliable protein identification can be achieved without the need of desalting sample preparation. We demonstrate the performance and the robustness of our method using commercially available reference proteins and automated MS and MS/MS analyses of in-gel digests from lung tissue lysate proteins separated by 2-DE.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1615-9861
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
8
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2583-95
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Matrix layer sample preparation: an improved MALDI-MS peptide analysis method for proteomic studies.
pubmed:affiliation
Department of Drug Research and Medical Biotechnology, Fraunhofer Institute of Toxicology and Experimental Medicine, Hannover, Germany.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't