Chemical probes and tandem mass spectrometry: a strategy for the quantitative analysis of proteomes and subproteomes

Functional clustering algorithm for high-dimensional proteomics data

Clustering proteomics data is a challenging problem for any traditional clustering algorithm. Usually, the number of samples is largely smaller than the number of protein peaks. The use of a clustering algorithm which does not take into consideration the number of features of variables (here the number of peaks) is needed. An innovative hierarchical clustering algorithm may be a good approach. We propose here a new dissimilarity measure for the hierarchical clustering combined with a functional data analysis. We present a specific application of functional data analysis (FDA) to a high-throughput proteomics study. The high performance of the proposed algorithm is compared to two popular dissimilarity measures in the clustering of normal and human T-cell leukemia virus type 1 (HTLV-1)-infected patients samples.

Functional proteomics for the discovery of carbohydrate-related enzyme activities

Carbohydrate metabolism is central to the growth and development of organisms. Thousands of genes that are believed to code for proteins that build and remodel saccharides have been uncovered by genome sequencing projects, thereby necessitating higher-throughput methods to delineate the chemical and biological functions of all these proteins. Recent methods discussed in this review have begun to address this problem by the design of new activity-based probes and mass-differentiated carbohydrate libraries. In addition, a comparative view of carbohydrate-related enzymes from all three branches of life has led to the discovery of unusual enzymes to simplify the synthesis of carbohydrates such as the sugar nucleotides required by glycosyltransferases.

Protein sequence tags: A novel solution for comparative proteomics

Comparative proteome profiling using stable isotope peptide labelling and mass spectrometry has emerged as a promising strategy. Here, we show the broad potential of our proprietary protein sequence tag (PST) technology. A special feature of PST is its ability to detect a wide variety of proteins including the pharmaceutically relevant membrane and nuclear proteins. This procedure addresses a similar number of proteins, compared to the multidimensional protein identification technology approach, but offers additionally a quantitative analysis with its recently developed quantitative PST version.

On-line counting of cysteine residues in peptides during electrospray ionization by electrogenerated tags and their application to protein identification

The electrochemically induced mass spectrometric tagging of cysteines by substituted hydroquinones was studied for peptides in a classical electrospray solvent (i.e., MeOH/H2O/AcOH 50/49/1). The tagging efficiency was tested with different hydroquinone compounds on an undecapeptide containing one cysteine residue. 2-carboxymethylhydroquinone was the most reactive probe and revealed to be suitable for cysteine quantification in peptides containing up to three cysteine residues, even in the case of two consecutive cysteines in the sequence. We demonstrate the compatibility of the on-line electrochemical tagging method for the cysteine content analysis of peptides coming from gel-free protein digestion procedures. The identification of bovine serum albumin and human alpha-lactalbumin digest samples in a peptide mapping strategy was greatly improved by the application of the electrotagging technique as post-column treatment. Indeed, the determination of cysteine content in the tryptic peptides provided powerful information in order to enhance the identification score as well as the discrimination against other protein candidates. The tagging method was then applied to the determination of four proteins in a model mixture.

Mass spectrometry-based methods for biomarker detection and analysis

The use of modern mass spectroscopy methods has made proteomics a promising new tool for the clinical diagnosis of cancer and other diseases. Because body fluids like plasma, serum or liquor can be analyzed, proteomics should be easily integrated into large clinical trials. However, before proteomics can be implemented, rigorous quality control is urgently needed. One of the major topics of proteomics is the search for specific biomarkers which can be used for the qualitative and quantitative judgment of a disease.:

High throughput quantitative analysis of serum proteins using glycopeptide capture and liquid chromatography mass spectrometry

It is expected that the composition of the serum proteome can provide valuable information about the state of the human body in health and disease and that this information can be extracted via quantitative proteomic measurements. Suitable proteomic techniques need to be sensitive, reproducible, and robust to detect potential biomarkers below the level of highly expressed proteins, generate data sets that are comparable between experiments and laboratories, and have high throughput to support statistical studies. Here we report a method for high throughput quantitative analysis of serum proteins. It consists of the selective isolation of peptides that are N-linked glycosylated in the intact protein, the analysis of these now deglycosylated peptides by liquid chromatography electrospray ionization mass spectrometry, and the comparative analysis of the resulting patterns. By focusing selectively on a few formerly N-linked glycopeptides per serum protein, the complexity of the analyte sample is significantly reduced and the sensitivity and throughput of serum proteome analysis are increased compared with the analysis of total tryptic peptides from unfractionated samples. We provide data that document the performance of the method and show that sera from untreated normal mice and genetically identical mice with carcinogen-induced skin cancer can be unambiguously discriminated using unsupervised clustering of the resulting peptide patterns. We further identify, by tandem mass spectrometry, some of the peptides that were consistently elevated in cancer mice compared with their control littermates.

Proteomics/genomics and signaling in lymphocytes

Recent technological advances in genomics, proteomics and bioinformatics have offered new insights into the molecular mechanisms that underlie lymphocyte signaling and function, and the development of new tools in these areas has opened up new avenues for biological investigation. By adding a quantitative dimension to lymphocyte proteome profiling, molecular machines and spatiotemporal regulatory processes can now be analyzed using such discovery-driven approaches. Biologists employing genomic and proteomic tools are gathering data at increasing speed and their struggle to extract maximal biological information is helped by new software tools that enable the detailed comparison of multiple datasets.