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Proc Natl Acad Sci U S A. 2003 Mar 4;100(5):2795-800. Epub 2003 Feb 18.

Detection of secreted peptides by using hypothesis-driven multistage mass spectrometry.

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Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, The Rockefeller University, 1230 York Avenue, New York, NY 10021 USA.


A method is presented for the rapid detection and characterization of trace amounts of peptides secreted from microorganisms, including pheromones, virulence factors, and quorum-sensing peptides. The procedure, based on targeted multistage MS, uses a novel matrix-assisted laser desorptionionization-ion trap mass spectrometer to overcome limitations of current MS methods (limited dynamic range, signal suppression effects, and chemical noise) that impair observation of low abundance peptides from complex biological matrixes. Here, secreted peptides that are hypothesized to be present in the supernatant, but that may not be sufficiently abundant to be observed in single-stage mass spectra, are subjected to multistage MS. Highly specific fragmentation signatures enable unambiguous identification of the peptides of interest and differentiation of the signals from the background. As examples, we demonstrate the rapid (<1 min) determination of the mating type of cells in colonies of Saccharomyces cerevisiae and the elucidation of autoinducing peptides (AIPs) from supernatants of pathogenic Staphylococci. We confirm the primary structures of the agrD encoded cyclic AIPs of Staphylococcus aureus for groups I, II, and IV and provide direct evidence that the native group-III AIP is a heptapeptide (INCDFLL). We also show that the homologous peptide from Staphylococcus intermedius is a nonapeptide (RIPTSTGFF) with a lactone ring formed through condensation of the serine side chain with the C terminus of the peptide. This is the first demonstration of cyclization in a staphylococcal AIP that occurs via lactone formation. These examples demonstrate the analytical power of the present procedure for characterizing secreted peptides and its potential utility for identifying microorganisms.

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