An ensemble framework for clustering protein-protein interaction networks

MOTIVATION: Protein-Protein Interaction (PPI) networks are believed to be important sources of information related to biological processes and complex metabolic functions of the cell. The presence of biologically relevant functional modules in these networks has been theorized by many researchers. However, the application of traditional clustering algorithms for extracting these modules has not been successful, largely due to the presence of noisy false positive interactions as well as specific topological challenges in the network. RESULTS: In this article, we propose an ensemble clustering framework to address this problem. For base clustering, we introduce two topology-based distance metrics to counteract the effects of noise. We develop a PCA-based consensus clustering technique, designed to reduce the dimensionality of the consensus problem and yield informative clusters. We also develop a soft consensus clustering variant to assign multifaceted proteins to multiple functional groups. We conduct an empirical evaluation of different consensus techniques using topology-based, information theoretic and domain-specific validation metrics and show that our approaches can provide significant benefits over other state-of-the-art approaches. Our analysis of the consensus clusters obtained demonstrates that ensemble clustering can (a) produce improved biologically significant functional groupings; and (b) facilitate soft clustering by discovering multiple functional associations for proteins. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Effects of yeast, fermentation time, and preservation methods on tarhana

The physicochemical properties of tarhana soup produced with different dough treatments, fermentation times, and preservation methods were examined. Tarhana doughs were prepared with yogurt (control) or baker's yeast (Saccharomyces cerevisiae) and fermented for 3 days. Samples were taken at 24, 48, and 72 hr. Samples were then preserved via one of four methods: sun dried, dried in the shade, vacumn dried, and frozen. Frozen samples produced lower organic acid levels after 72 hr of fermentation in both control (0.68 g/100 g) and yeast (0.61 g/100 g) applications than samples that were dried (0.94 g/100 g control samples; 0.81 g/100 g samples with yeast). Increasing fermentation time resulted in a significant effect on the formation of organic acid in the tarhana (p < .01). At 72 hr of fermentation, total acidity increased 11%, 17%, and 23% for tarhana samples vacumn-dried, sun-dried, and dried in the shade, respectively. Preservation methods also affected the moisture, ash, crude protein, total acidity, pH, salt, fat, reducing sugar levels, and the sensory assestment of tarhana soup (p < .01). Sensory characteristics were not significantly affected by baker's yeast in any of the preservation methods used (p > .01). However, sensory scores for tarhana prepared from the samples dried in a sheltered area showed a reduction in color desireablilty as the fermentation time increased. The soup prepared from frozen tarhana (72 hr fermentation, with yeast) had the highest scores with respect to color, mouth feel, flavor, and overall acceptability. Vacuum-dried samples' scores in these areas were also high in comparison to the two other drying methods.     

Integration of Metabolic Modeling and Phenotypic Data in Evaluation and Improvement of Ethanol Production Using Respiration-Deficient Mutants of Saccharomyces cerevisiae

Flux balance analysis and phenotypic data were used to provide clues to the relationships between the activities of gene products and the phenotypes resulting from the deletion of genes involved in respiratory function in Saccharomyces cerevisiae. The effect of partial or complete respiratory deficiency on the ethanol production and growth characteristics of hap4Δ/hap4Δ, mig1Δ/mig1Δ, qdr3Δ/qdr3Δ, pdr3Δ/pdr3Δ, qcr7Δ/qcr7Δ, cyt1Δ/cyt1Δ, and rip1Δ/rip1Δ mutants grown in microaerated chemostats was investigated. The study provided additional evidence for the importance of the selection of a physiologically relevant objective function, and it may improve quantitative predictions of exchange fluxes, as well as qualitative estimations of changes in intracellular fluxes. Ethanol production was successfully predicted by flux balance analysis in the case of the qdr3Δ/qdr3Δ mutant, with maximization of ethanol production as the objective function, suggesting an additional role for Qdr3p in respiration. The absence of similar changes in estimated intracellular fluxes in the qcr7Δ/qcr7Δ mutant compared to the rip1Δ/rip1Δ and cyt1Δ/cyt1Δ mutants indicated that the effect of the deletion of this subunit of complex III was somehow compensated for. Analysis of predicted flux distributions indicated self-organization of intracellular fluxes to avoid NAD⁺/NADH imbalance in rip1Δ/rip1Δ and cyt1Δ/cyt1Δ mutants, but not the qcr7Δ/qcr7Δ mutant. The flux through the glycerol efflux channel, Fps1p, was estimated to be zero in all strains under the investigated conditions. This indicates that previous strategies for improving ethanol production, such as the overexpression of the glutamate synthase gene GLT1 in a GDH1 deletion background or deletion of the glycerol efflux channel gene FPS1 and overexpression of GLT1, are unnecessary in a respiration-deficient background.     

UPEC kidney infection triggers neuro-immune communication leading to modulation of local renal inflammation by splenic IFNγ

Bacterial infection results in a veritable cascade of host responses, both local and systemic. To study the initial stages of host-pathogen interaction in living tissue we use spatially-temporally controlled in vivo models. Using this approach, we show here that within 4 h of a uropathogenic Escherichia coli (UPEC) infection in the kidney, an IFNγ response is triggered in the spleen. This rapid infection-mediated inter-organ communication was found to be transmitted via nerve signalling. Bacterial expression of the toxin α-hemolysin directly and indirectly activated sensory neurons, which were identified in the basement membrane of renal tubules. Nerve activation was transmitted via the splenic nerve, inducing upregulation of IFNγ in the marginal zones of the spleen that led to increasing concentrations of IFNγ in the circulation. We found that IFNγ modulated the inflammatory signalling generated by renal epithelia cells in response to UPEC infection. This demonstrates a new concept in the host response to kidney infection; the role of nerves in sensing infection and rapidly triggering a systemic response which can modulate inflammation at the site of infection. The interplay between the nervous and immune systems is an exciting, developing field with the appealing prospect of non-pharmaceutical interventions. Our study identifies an important role for systemic neuro-immune communication in modulating inflammation during the very first hours of a local bacterial infection in vivo.     

Flux balance analysis of a genome-scale yeast model constrained by exometabolomic data allows metabolic system identification of genetically different strains

A systems approach to biology requires a principled approach to pathway identification. In this study, the two nuclear petite yeast mutants K1Deltapet191a and K1Deltapet191ab and their parental industrial strain K1 were cultured in glucose-containing microaerobic chemostats. Exometabolomic profiles were used to infer the differences in the fermentation characteristics and respiration capacity of the strains. The ability of the metabolite measurement information to describe genetically different strains was investigated using a genome-scale yeast model. Flux balance analysis (FBA) of the model reveals that the objective function of minimal oxygen consumption enables the identification of the effect of genotypic differences when combined with the knowledge of the extracellular state of metabolism. The predicted decrease in oxygen consumption flux of K1Deltapet191a and K1Deltapet191ab strains with respect to the parental strain is about 80% and 100%, respectively, which coincides with the respiratory deficiencies of the strains. The expected increase in ethanol production rates in response to the decrease in the respiratory capacity was also predicted to be very close to the experimental values. This study shows the predictive power of the integrated analysis of genome-scale models with exometabolomic profiles, since accurate predictions could be made without any information about the respiration capacity of the strains. The FBA approach thereby enables identification of responsive pathways and so permits the elucidation of the genetic characteristics of strains in terms of expressed metabolite profiles.     

Protein kinase C Inhibitors selectively modulate dynamics of cell adhesion molecules and cell death in human colon cancer cells

During development of colon cancer, Protein Kinase Cs (PKCs) are involved in regulation of many genes controlling several cellular mechanisms. Here, we examined the changes in cell adhesion molecules and PKCs for colorectal cancer progression. We identified that PKCs affected expression of EpCAM, claudins, tetraspanins. Treatment with low concentrations of PKC inhibitors resulted in decreased cell viability. In addition, immunoblotting and qRT-PCR analysis showed that apoptosis was inhibited while autophagy was induced by PKC inhibition in colon cancer cells. Furthermore, we observed decreased levels of intracellular Reactive Oxygen Species (ROS), lipid peroxidation and protein carbonyl, confirming the ROS-induced apoptosis. Taken together, our results reveal that PKC signalling modulates not only cell adhesion dynamics but also cell death-related mechanisms.

Abbreviations: PKC: Protein Kinase C; EpCAM: Epithelial cell adhesion molecule; FBS: fetal bovine serum; MTT: 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide); CAM: cell adhesion molecule; ROS: reactive oxygen species