Current non-gel techniques for analyzing proteomes rely heavily on mass spectrometric analysis of enzymatically digested protein mixtures. Prior to analysis, a highly complex peptide mixture is either separated on a multidimensional chromatographic system or it is first reduced in complexity by isolating sets of representative peptides. Recently, we developed a peptide isolation procedure based on diagonal electrophoresis and diagonal chromatography. We call it combined fractional diagonal chromatography (COFRADIC). In previous experiments, we used COFRADIC to identify more than 800 Escherichia coli proteins by tandem mass spectrometric (MS/MS) analysis of isolated methionine-containing peptides. Here, we describe a diagonal method to isolate N-terminal peptides. This reduces the complexity of the peptide sample, because each protein has one N terminus and is thus represented by only one peptide. In this new procedure, free amino groups in proteins are first blocked by acetylation and then digested with trypsin. After reverse-phase (RP) chromatographic fractionation of the generated peptide mixture, internal peptides are blocked using 2,4,6-trinitrobenzenesulfonic acid (TNBS); they display a strong hydrophobic shift and therefore segregate from the unaltered N-terminal peptides during a second identical separation step. N-terminal peptides can thereby be specifically collected for further liquid chromatography (LC)-MS/MS analysis. Omitting the acetylation step results in the isolation of non-lysine-containing N-terminal peptides from in vivo blocked proteins.

A novel gel-free proteomic technology was used to identify more than 800 proteins from 50 million Escherichia coli K12 cells in a single analysis. A peptide mixture is first obtained from a total unfractionated cell lysate, and only the methionine-containing peptides are isolated and identified by mass spectrometry and database searching. The sorting procedure is based on the concept of diagonal chromatography but adapted for highly complex mixtures. Statistical analysis predicts that we have identified more than 40% of the expressed proteome, including soluble and membrane-bound proteins. Next to highly abundant proteins, we also detected low copy number components such as the E. coli lactose operon repressor, illustrating the high dynamic range. The method is about 100 times more sensitive than two-dimensional gel-based methods and is fully automated. The strongest point, however, is the flexibility in the peptide sorting chemistry, which may target the technique toward quantitative proteomics of virtually every class of peptides containing modifiable amino acids, such as phosphopeptides, amino-terminal peptides, etc

Several studies have been published in which holistic approaches were used to characterise the proteome and transcriptome of human platelets. The key intent being that a deeper understanding of the normal and aberrant physiological functions of platelets can only be achieved if most biomolecular building blocks are mapped. Here we present the application of recently developed novel technologies that overcome some of the shortcomings of gel-based proteomics. Central in our approach is the so-called combined fractional diagonal chromatography (COFRADIC)-technology in which sets of representative peptides are sorted in a diagonal RP chromatographic system through a specific modification of their side chain. In this study we combined three different COFRADIC sorting techniques to analyse the proteome of human platelets. Methionyl, cysteinyl and amino terminal peptides were isolated and analysed by MS/MS. Merging the peptide identifications obtained after database searching resulted in a core set of 641 platelet proteins, which comprises the largest set identified today. In comparison to previously published platelet proteomes, we identified 404 novel platelet proteins containing a high number of hydrophobic membrane proteins and hypothetical proteins. Furthermore we discuss the observed characteristics and potential benefits of each of the different COFRADIC technologies for proteome analysis and highlight important issues that need to be considered when searching sequence databases using data obtained in peptide-centric, non-gel proteomics studies.