Purinergic P2Y2 receptors modulate endothelial sprouting

Purinergic P2 receptors are critical regulators of several functions within the vascular system, including platelet aggregation, vascular inflammation, and vascular tone. However, a role for ATP release and P2Y receptor signalling in angiogenesis remains poorly defined. Here, we demonstrate that blood vessel growth is controlled by P2Y₂ receptors. Endothelial sprouting and vascular tube formation were significantly dependent on P2Y₂ expression and inhibition of P2Y₂ using a selective antagonist blocked microvascular network generation. Mechanistically, overexpression of P2Y₂ in endothelial cells induced the expression of the proangiogenic molecules CXCR4, CD34, and angiopoietin-2, while expression of VEGFR-2 was decreased. Interestingly, elevated P2Y₂ expression caused constitutive phosphorylation of ERK1/2 and VEGFR-2. However, stimulation of cells with the P2Y₂ agonist UTP did not influence sprouting unless P2Y₂ was constitutively expressed. Finally, inhibition of VEGFR-2 impaired spontaneous vascular network formation induced by P2Y₂ overexpression. Our data suggest that P2Y₂ receptors have an essential function in angiogenesis, and that P2Y₂ receptors present a therapeutic target to regulate blood vessel growth.

Stress responses and conditioning effects in mesothelial cells exposed to peritoneal dialysis fluid

Renal replacement therapy by peritoneal dialysis is frequently complicated by technical failure. Peritoneal dialysis fluids (PDF) cause injury to the peritoneal mesothelial cell layer due to their cytotoxicity. As only isolated elements of the involved cellular processes have been studied before, we aimed at a global assessment of the mesothelial stress response to PDF. Following single or repeated exposure to PDF or control medium, proteomics and bioinformatics techniques were combined to study effects in mesothelial cells (MeT-5A). Protein expression was assessed by two-dimensional gel electrophoresis, and significantly altered spots were identified by MALDI-TOF MS and MS2 techniques. The lists of experimentally derived candidate proteins were expanded by a next neighbor approach and analyzed for significantly enriched biological processes. To address the problem of an unknown portion of false positive spots in 2DGE, only proteins showing significant p-values on both levels were further interpreted. Single PDF exposure resulted in reduction of biological processes in favor of reparative responses, including protein metabolism, modification and folding, with chaperones as a major subgroup. The observed biological processes triggered by this acute PDF exposure mainly contained functionally interwoven multitasking proteins contributing as well to cytoskeletal reorganization and defense mechanisms. Repeated PDF exposure resulted in attenuated protein regulation, reflecting inhibition of stress responses by high levels of preinduced chaperones. The identified proteins were less attributable to acute cellular injury but rather to specialized functions with a reduced number of involved multitasking proteins. This finding agrees well with the concept of conditioning effects and cytoprotection. In conclusion, this study describes the reprogrammed proteome of mesothelial cells during recovery from PDF exposure and adaption to repetitive stress. A broad stress response with a number of highly overlapping processes and multitasking proteins shifts toward a more specific response of only few less overlapping processes.

Linking the ovarian cancer transcriptome and immunome

Background

Autoantigens have been reported in a variety of tumors, providing insight into the interplay between malignancies and the immune response, and also giving rise to novel diagnostic and therapeutic concepts. Why certain tumor-associated proteins induce an immune response remains largely elusive.

Results

This paper analyzes the proposed link between increased abundance of a protein in cancerous tissue and the increased potential of the protein for induction of a humoral immune response, using ovarian cancer as an example. Public domain data sources on differential gene expression and on autoantigens associated with this malignancy were extracted and compared, using bioinformatics analysis, on the levels of individual genes and proteins, transcriptional coregulation, joint functional pathways, and shared protein-protein interaction networks. Finally, a selected list of ovarian cancer-associated, differentially regulated proteins was tested experimentally for reactivity with antibodies prevalent in sera of ovarian cancer patients.

Genes reported as showing differential expression in ovarian cancer exhibited only minor overlap with the public domain list of ovarian cancer autoantigens. However, experimental screening for antibodies directed against antigenic determinants from ovarian cancer-associated proteins yielded clear reactions with sera.

Conclusion

A link between tumor protein abundance and the likelihood of induction of a humoral immune response in ovarian cancer appears evident.

Transforming omics data into context: Bioinformatics on genomics and proteomics raw data

Differential gene expression analysis and proteomics have exerted significant impact on the elucidation of concerted cellular processes, as simultaneous measurement of hundreds to thousands of individual objects on the level of RNA and protein ensembles became technically feasible. The availability of such data sets has promised a profound understanding of phenomena on an aggregate level, expressed as the phenotypic response (observables) of cells, e.g., in the presence of drugs, or characterization of cells and tissue displaying distinct patho-physiological states. However, the step of transforming these data into context, i.e., linking distinct expression or abundance patterns with phenotypic observables - and furthermore enabling a sound biological interpretation on the level of reaction networks and concerted pathways, is still a major shortcoming. This finding is certainly based on the enormous complexity embedded in cellular reaction networks, but a variety of computational approaches have been developed over the last few years to overcome these issues. This review provides an overview on computational procedures for analysis of genomic and proteomic data introducing a sequential analysis workflow: Explorative statistics for deriving a first, from the purely statistical viewpoint, relevant candidate gene/protein list, followed by co-regulation and network analysis to biologically expand this core list toward functional networks and pathways. The review on these procedures is complemented by example applications tailored at identification of disease-associated proteins. Optimization of computational procedures involved, in conjunction with the continuous increase in additional biological data, clearly has the potential of boosting our understanding of processes on a cell-wide level.

Discrete simulation of regulatory homo- and heterodimerization in the apoptosis effector phase

MOTIVATION

Quantitative simulation of molecular reaction networks is among the most promising approaches towards an understanding of complex biochemical pathways. Numerous qualitative as well as quantitative data from diverse experimental settings, in particular from genomics and proteomics, have to be contextually linked to convert static data into dynamic functionality.

RESULTS

This paper presents the Lattice Molecular Automaton, a Cellular Automaton-based simulation tool, capable of representing complex molecular dynamics at different levels of granularity. A data structure concept represents molecular units, whose dynamics, embedded on a 2D grid, is defined via detailed intermolecular interaction profiles. The data structures hold diverse information as molecular type, potential, as well as kinetic energy states, which allows a precise representation of intracellular reaction networks. The molecular dynamics is performed via local computation of individual molecular states on the lattice, which, in conjunction with discretized space and time, enables excellent scalability of this simulation concept. This paper finally gives Lattice Molecular Automaton simulation results on key elements of apoptosis, the cell death cascade, in particular focusing on the regulatory function of homo- and heterodimerization of members of the Bcl-2 protein family in the apoptosis effector phase. The regulatory proteins Bcl2, Bax, and Bak constitute a diffusion-driven molecular switch with inherent damping of apoptosis induction, thereby controlling the apoptosis reaction cascade under noisy, external apoptosis inducing conditions.