Protein interaction networks in medicine and disease.

The physical interaction of proteins is subject to intense investigation that has revealed that proteins are assembled into large densely connected networks. In this review, we will examine how signaling pathways can be combined to form higher order protein interaction networks. By using network graph theory, these interaction networks can be further analyzed for global organization, which has revealed unique aspects of the relationships between protein networks and complex biological phenotypes. Moreover, several studies have shown that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer progression. These relationships suggest a novel paradigm for treatment of complex multigenic disease where the protein interaction network is the target of therapy more so than individual molecules within the network.

Dynamic modularity in protein interaction networks predicts breast cancer outcome.

Changes in the biochemical wiring of oncogenic cells drives phenotypic transformations that directly affect disease outcome. Here we examine the dynamic structure of the human protein interaction network (interactome) to determine whether changes in the organization of the interactome can be used to predict patient outcome. An analysis of hub proteins identified intermodular hub proteins that are co-expressed with their interacting partners in a tissue-restricted manner and intramodular hub proteins that are co-expressed with their interacting partners in all or most tissues. Substantial differences in biochemical structure were observed between the two types of hubs. Signaling domains were found more often in intermodular hub proteins, which were also more frequently associated with oncogenesis. Analysis of two breast cancer patient cohorts revealed that altered modularity of the human interactome may be useful as an indicator of breast cancer prognosis.

Human non-synonymous single nucleotide polymorphisms can influence ubiquitin-mediated protein degradation.

Ubiquitin-mediated proteolysis plays a critical role in the degradation of proteins important in the cellular processes, such as cell cycle/division, differentiation and development, DNA repair, transcriptional regulation, and signaling. It is carried out by a complex cascade of enzymes that contain a high degree of specificity to motifs found in many proteins with rapid turnover. For example, the PEST motifs are hydrophilic stretches of amino acids that serve as signals for proteolytic degradation. In this study, we propose that amino acid altering non-synonymous single nucleotide polymorphisms (nsSNP) result in the abolishment or creation of putative PEST motifs, and thus lead to abnormal stabilization or degradation of the proteins. Using a web-based algorithm, PESTFind, we analyzed a total of 253 nsSNPs from proteins involved in cell cycle (n = 24), DNA repair (n = 128), and TGFbeta signaling pathway (n = 101). Fifteen nsSNPs were located within putative PEST sequences, and 9/15 (60%) either created or abolished these PEST motifs. PEST motifs were abolished in the presence of nsSNPs in CCND3, PMS2, POLE4, SITPEC, and PPARG and putative PEST motifs were created in NEIL2, BIRC4, MLL2, and PPP1R15A. Although experimental analyses are required to confirm these results, they suggest that nsSNPs can induce changes in ubiquitin-mediated protein degradation.

A comparison of high cell density fed-batch fermentations involving both induced and non-induced recombinant Escherichia coli under well-mixed small-scale and simulated poorly mixed large-scale conditions.

In this work, multi-parameter flow cytometric techniques, coupled with dual colour fluorescent staining, have been used to study the metabolic consequences of inclusion body formation in high cell density fed-batch cultures of the recombinant E. coli strain MSD3735, producing the IPTG inducible model mammalian protein, AP50. Further, we report on the development of the scale-down, two compartment (STR + PFR) experimental simulation model to study, for the first time, the effect of a changing microenvironment with respect to three of the major spatial heterogeneities that may be associated with large-scale bioprocessing (pH, glucose and dissolved oxygen concentration) on a recombinant bacterial system. Using various time points for induction and various scale-down configurations, it has been shown that inclusion body formation is followed immediately by a detrimental progressive change in individual cell physiological state with respect to both cytoplasmic membrane polarisation and permeability, resulting in a lower final biomass yield. However, the extent of this change was found to be dependent on whether the AP50 protein was induced or not, on the time of induction and on which combination of heterogeneities was being simulated. From this and previous work, it is clear that the scale-down two-compartment model can be used to study the impact of genetically modifying an organism to produce inclusion bodies and any range and combination of potential heterogeneities known to exist at the large scale.

Functional nonsynonymous single nucleotide polymorphisms from the TGF-beta protein interaction network.

Protein complexes mediated by protein-protein interactions are essential for many cellular functions. Transforming growth factor (TGF)-beta signaling involves a cascade of protein-protein interactions and malfunctioning of this pathway has been implicated in human diseases. Using an in silico approach, we analyzed the naturally occurring human genetic variations from the proteins involved in the TGF-beta signaling (10 TGF-beta proteins and 242 other proteins interacting with them) to identify the ones that have potential biological consequences. All proteins were searched in the dbSNP database for the presence of nonsynonymous single nucleotide polymorphisms (nsSNPs). A total of 118 validated nsSNPs from 63 proteins were retrieved and analyzed in terms of 1) evolutionary conservation status, 2) being located in a functional protein domain or motif, and 3) altering putative protein motif or phosphorylation sites. Our results indicated the presence of 31 nsSNPs that occurred at evolutionarily conserved residues, 37 nsSNPs were located in protein domains, motifs, or repeats, and 46 nsSNPs were predicted to either create or abolish putative protein motifs or phosphorylation sites. We undertook this study to analyze the human genetic variations that can affect the protein function and the TGF-beta signaling. The nsSNPs reported in here can be characterized by experimental approaches to elucidate their exact biological roles and whether they are related to human disease.

High-throughput mapping of a dynamic signaling network in mammalian cells.

Signaling pathways transmit information through protein interaction networks that are dynamically regulated by complex extracellular cues. We developed LUMIER (for luminescence-based mammalian interactome mapping), an automated high-throughput technology, to map protein-protein interaction networks systematically in mammalian cells and applied it to the transforming growth factor-beta (TGFbeta) pathway. Analysis using self-organizing maps and k-means clustering identified links of the TGFbeta pathway to the p21-activated kinase (PAK) network, to the polarity complex, and to Occludin, a structural component of tight junctions. We show that Occludin regulates TGFbeta type I receptor localization for efficient TGFbeta-dependent dissolution of tight junctions during epithelial-to-mesenchymal transitions.

The application of multi-parameter flow cytometry to the study of recombinant Escherichia coli batch fermentation processes.

Multi-parameter flow cytometric techniques coupled with dual colour fluorescent staining were used to study the physical and metabolic consequences of inclusion body formation in batch cultures of the recombinant Escherichia coli strain MSD3735. This strain contains a plasmid coding for the isopropylthiogalactopyranoside-inducible model eukaryotic protein AP50. It is known that the synthesis of foreign proteins at high concentrations can exert a severe metabolic stress on the host cell and that morphological changes can occur. In this work, using various points of induction, it was shown that inclusion body formation is followed immediately by measurable changes in the characteristic intrinsic light scatter patterns for the individual cell (forward scatter, 90 degrees side scatter) and a concomitant progressive change in the individual cell physiological state with respect to both cytoplasmic membrane polarisation and permeability. This work establishes flow cytometry as a potentially valuable tool for monitoring recombinant fermentation processes, providing important information for scale-up. Further, we discuss the possibility of optimising inclusion body formation by manipulating the fermentation conditions based on these rapid "real-time" measurements.

Identification of in vitro folding conditions for procathepsin S and cathepsin S using fractional factorial screens.

Human procathepsin S and cathepsin S were expressed as inclusion bodies in Escherichia coli. Following solubilization of the inclusion body proteins, fractional factorial protein folding screens were used to identify folding conditions for procathepsin S and cathepsin S. A primary folding screen, including eight factors each at two levels, identified pH and arginine as the main factors affecting procathepsin S folding. In a second simple screen, the yields were further improved. The in vitro folding of mature cathepsin S has never been reported previously. In this study we used a series of fractional factorial screens to identify conditions that enabled the active enzyme to be generated without the prodomain although the yields were much lower than achieved with procathepsin S. Our data show the power of fractional factorial screens to rapidly identify folding conditions even for a protein that does not easily fold into its active conformation.