A Functional Proteomic Method for Biomarker Discovery

The sequencing of the human genome holds out the hope for personalized medicine, but it is clear that analysis of DNA or RNA content alone is not sufficient to understand most disease processes. Proteomic strategies that allow unbiased identification of proteins and their post-transcriptional and -translation modifications are an essential complement to genomic strategies. However, the enormity of the proteome and limitations in proteomic methods make it difficult to determine the targets that are particularly relevant to human disease. Methods are therefore needed that allow rational identification of targets based on function and relevance to disease. Screening methodologies such as phage display, SELEX, and small-molecule combinatorial chemistry have been widely used to discover specific ligands for cells or tissues of interest, such as tumors. Those ligands can be used in turn as affinity probes to identify their cognate molecular targets when they are not known in advance. Here we report an easy, robust and generally applicable approach in which phage particles bearing cell- or tissue-specific peptides serve directly as the affinity probes for their molecular targets. For proof of principle, the method successfully identified molecular binding partners, three of them novel, for 15 peptides specific for pancreatic cancer

A Role for the Juxtamembrane Cytoplasm in the Molecular Dynamics of Focal Adhesions

Focal adhesions (FAs) are specialized membrane-associated multi-protein complexes that link the cell to the extracellular matrix and play crucial roles in cell-matrix sensing. Considerable information is available on the complex molecular composition of these sites, yet the regulation of FA dynamics is largely unknown. Based on a combination of FRAP studies in live cells, with in silico simulations and mathematical modeling, we show that the FA plaque proteins paxillin and vinculin exist in four dynamic states: an immobile FA-bound fraction, an FA-associated fraction undergoing exchange, a juxtamembrane fraction experiencing attenuated diffusion, and a fast-diffusing cytoplasmic pool. The juxtamembrane region surrounding FAs displays a gradient of FA plaque proteins with respect to both concentration and dynamics. Based on these findings, we propose a new model for the regulation of FA dynamics in which this juxtamembrane domain acts as an intermediary layer, enabling an efficient regulation of FA formation and reorganization

FHA-Mediated Cell-Substrate and Cell-Cell Adhesions Are Critical for Bordetella pertussis Biofilm Formation on Abiotic Surfaces and in the Mouse Nose and the Trachea

Bordetella spp. form biofilms in the mouse nasopharynx, thereby providing a potential mechanism for establishing chronic infections in humans and animals. Filamentous hemagglutinin (FHA) is a major virulence factor of B. pertussis, the causative agent of the highly transmissible and infectious disease, pertussis. In this study, we dissected the role of FHA in the distinct biofilm developmental stages of B. pertussis on abiotic substrates and in the respiratory tract by employing a murine model of respiratory biofilms. Our results show that the lack of FHA reduced attachment and decreased accumulation of biofilm biomass on artificial surfaces. FHA contributes to biofilm development by promoting the formation of microcolonies. Absence of FHA from B. pertussis or antibody-mediated blockade of surface-associated FHA impaired the attachment of bacteria to the biofilm community. Exogenous addition of FHA resulted in a dose-dependent inhibitory effect on bacterial association with the biofilms. Furthermore, we show that FHA is important for the structural integrity of biofilms formed on the mouse nose and trachea. Together, these results strongly support the hypothesis that FHA promotes the formation and maintenance of biofilms by mediating cell-substrate and inter-bacterial adhesions. These discoveries highlight FHA as a key factor in establishing structured biofilm communities in the respiratory tract

Parameter estimate of signal transduction pathways

BACKGROUND: The "inverse" problem is related to the determination of unknown causes on the bases of the observation of their effects. This is the opposite of the corresponding "direct" problem, which relates to the prediction of the effects generated by a complete description of some agencies. The solution of an inverse problem entails the construction of a mathematical model and takes the moves from a number of experimental data. In this respect, inverse problems are often ill-conditioned as the amount of experimental conditions available are often insufficient to unambiguously solve the mathematical model. Several approaches to solving inverse problems are possible, both computational and experimental, some of which are mentioned in this article. In this work, we will describe in details the attempt to solve an inverse problem which arose in the study of an intracellular signaling pathway. RESULTS: Using the Genetic Algorithm to find the sub-optimal solution to the optimization problem, we have estimated a set of unknown parameters describing a kinetic model of a signaling pathway in the neuronal cell. The model is composed of mass action ordinary differential equations, where the kinetic parameters describe protein-protein interactions, protein synthesis and degradation. The algorithm has been implemented on a parallel platform. Several potential solutions of the problem have been computed, each solution being a set of model parameters. A sub-set of parameters has been selected on the basis on their small coefficient of variation across the ensemble of solutions. CONCLUSION: Despite the lack of sufficiently reliable and homogeneous experimental data, the genetic algorithm approach has allowed to estimate the approximate value of a number of model parameters in a kinetic model of a signaling pathway: these parameters have been assessed to be relevant for the reproduction of the available experimental data

Systems microscopy approaches to understand cancer cell migration and metastasis

Cell migration is essential in a number of processes, including wound healing, angiogenesis and cancer metastasis. Especially, invasion of cancer cells in the surrounding tissue is a crucial step that requires increased cell motility. Cell migration is a well-orchestrated process that involves the continuous formation and disassembly of matrix adhesions. Those structural anchor points interact with the extra-cellular matrix and also participate in adhesion-dependent signalling. Although these processes are essential for cancer metastasis, little is known about the molecular mechanisms that regulate adhesion dynamics during tumour cell migration. In this review, we provide an overview of recent advanced imaging strategies together with quantitative image analysis that can be implemented to understand the dynamics of matrix adhesions and its molecular components in relation to tumour cell migration. This dynamic cell imaging together with multiparametric image analysis will help in understanding the molecular mechanisms that define cancer cell migration