The assembly of signaling molecules surrounding the integrin family of adhesion receptors remains poorly understood. Recently, the membrane protein caveolin was found in complexes with β1 integrins. Caveolin binds cholesterol and several signaling molecules potentially linked to integrin function, e.g., Src family kinases, although caveolin has not been directly implicated in integrin-dependent adhesion. Here we report that depletion of caveolin by antisense methodology in kidney 293 cells disrupts the association of Src kinases with β1 integrins resulting in loss of focal adhesion sites, ligand-induced focal adhesion kinase (FAK) phosphorylation, and adhesion. The nonintegrin urokinase receptor (uPAR) associates with and stabilizes β1 integrin/caveolin complexes. Depletion of caveolin in uPAR-expressing 293 cells also disrupts uPAR/integrin complexes and uPAR-dependent adhesion. Further, β1 integrin/caveolin complexes could be disassociated by uPAR-binding peptides in both uPAR-transfected 293 cells and human vascular smooth muscle cells. Disruption of complexes by peptides in intact smooth muscle cells blocks the association of Src family kinases with β1 integrins and markedly impairs their migration on fibronectin. We conclude that ligand-induced signaling necessary for normal β1 integrin function requires caveolin and is regulated by uPAR. Caveolin and uPAR may operate within adhesion sites to organize kinase-rich lipid domains in proximity to integrins, promoting efficient signal transduction.

The proposed model is based on the measurement of the retention times of 346 tryptic peptides in the 560-to 4,000-Da mass range, derived from a mixture of 17 protein digests. These peptides were measured in HPLC-MALDI MS runs, with peptide identities confirmed by MS/MS. The model relies on summation of the retention coefficients of the individual amino acids, as in previous approaches, but additional terms are introduced that depend on the retention coefficients for amino acids at the N-terminal of the peptide. In the 17-protein mixture, optimization of two sets of coefficients, along with additional compensation for peptide length and hydrophobicity, yielded a linear dependence of retention time on hydrophobicity, with an R 2 value about 0.94. The predictive capability of the model was used to distinguish peptides with close m/z values and for detailed peptide mapping of selected proteins. Its applicability was tested on columns of different sizes, from nano-to narrow-bore, and for direct sample injection, or injection via a pre-column. It can be used for accurate prediction of retention times for tryptic peptides on reversed-phase (300-Å pore size) columns of different sizes with a linear water-ACN gradient and with TFA as the ion-pairing modifier. Molecular & Cellular Proteomics 3:908 -919, 2004.The application of MS to biomolecular analysis has revolutionized protein research within the past decade (1). This can be mostly attributed to the development of ionization techniques that are compatible with biomolecules, i.e. MALDI (2, 3) and ESI (4), as well as improved instrumentation. However, although modern mass spectrometers provide high mass accuracy and sensitivity, the protein complexity and concentration range usually found in biological samples still present a challenge. The problem has been traditionally attacked by separation of complex protein mixtures by two-dimensional gel electrophoresis, with subsequent protein in-gel digestion, followed by ESI or MALDI MS. This remains one of the most popular sample preparation procedures, especially suitable for protein identification and quantitation. However, the method is best suited for higher abundance proteins with masses greater than 12-14 kDa, and some categories of molecules, such as membrane proteins (1) or species with extremes in isoelectric points, are handled poorly. There are also difficulties in adapting the method to high-throughput applications.Alternative analytical approaches are based on pre-fractionation of protein mixtures or cell lysates before the final MS steps of analysis (5-9). This often involves proteolytic digestion, followed by one-or multi-dimensional chromatographic separation of the resulting peptides, with subsequent detection by MS/MS. Such a method may yield considerable simplification of the problem, because the fractions from on-or off-line HPLC separations have reduced complexity compared with the original sample. Indeed, the combination of HPLC-ESI (MS or MS/MS) has proved to be a "work horse" for large-scale high-throug...

SELDI-TOF-MS offers a unique platform for high throughput urine protein profiling; however, standardization of analysis conditions is critical, and both extrinsic and intrinsic factors must be taken into account for accurate data interpretation.

Because they are obligate intracellular parasites, all viruses are exclusively and intimately dependent upon host cells for replication. Viruses, in turn, induce profound changes within cells, including apoptosis, morphological changes, and activation of signaling pathways. Many of these alterations have been analyzed by gene arrays, which measure the cellular "transcriptome." Until recently, it has not been possible to extend comparable types of studies to globally examine all the host cellular proteins, which are the actual effector molecules. We have used stable isotope labeling by amino acids in cell culture (SILAC), combined with high-throughput two-dimensional (2-D) high-performance liquid chromatography (HPLC)/mass spectrometry, to determine quantitative differences in host proteins after infection of human lung A549 cells with human influenza virus A/PR/8/34 (H1N1) for 24 h. Of the 4,689 identified and measured cytosolic protein pairs, 127 were significantly upregulated at >95% confidence, 153 were significantly downregulated at >95% confidence, and a total of 87 proteins were upregulated or downregulated more than 5-fold at >99% confidence. Gene ontology and pathway analyses indicated differentially regulated proteins and included those involved in host cell immunity and antigen presentation, cell adhesion, metabolism, protein function, signal transduction, and transcription pathways.