vProtein: Identifying Optimal Amino Acid Complements from Plant-Based Foods

Background: Indispensible amino acids (IAAs) are used by the body in different proportions. Most animal-based foods provide these IAAs in roughly the needed proportions, but many plant-based foods provide different proportions of IAAs. To explore how these plant-based foods can be better used in human nutrition, we have created the computational tool vProtein to identify optimal food complements to satisfy human protein needs. Methods: vProtein uses 1251 plant-based foods listed in the United States Department of Agriculture standard release 22 database to determine the quantity of each food or pair of foods required to satisfy human IAA needs as determined by the 2005 daily recommended intake. The quantity of food in a pair is found using a linear programming approach that minimizes total calories, total excess IAAs, or the total weight of the combination. Results: For single foods, vProtein identifies foods with particularly balanced IAA patterns such as wheat germ, quinoa, and cauliflower. vProtein also identifies foods with particularly unbalanced IAA patterns such as macadamia nuts, degermed corn products, and wakame seaweed. Although less useful alone, some unbalanced foods provide unusually good complements, such as Brazil nuts to legumes. Interestingly, vProtein finds no statistically significant bias toward grain/ legume pairings for protein complementation. These analyses suggest that pairings of plant-based foods should be based on the individual foods themselves instead of based on broader food group-food group pairings. Overall, the most efficien

The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods

Regulation of mTORC1 Signaling by pH

BACKGROUND: Acidification of the cytoplasm and the extracellular environment is associated with many physiological and pathological conditions, such as intense exercise, hypoxia and tumourigenesis. Acidification affects important cellular functions including protein synthesis, growth, and proliferation. Many of these vital functions are controlled by mTORC1, a master regulator protein kinase that is activated by various growth-stimulating signals and inactivated by starvation conditions. Whether mTORC1 can also respond to changes in extracellular or cytoplasmic pH and play a role in limiting anabolic processes in acidic conditions is not known. METHODOLOGY/FINDINGS: We examined the effects of acidifying the extracellular medium from pH 7.4 to 6.4 on human breast carcinoma MCF-7 cells and immortalized mouse embryo fibroblasts. Decreasing the extracellular pH caused intracellular acidification and rapid, graded and reversible inhibition of mTORC1, assessed by measuring the phosphorylation of the mTORC1 substrate S6K. Fibroblasts deleted of the tuberous sclerosis complex TSC2 gene, a major negative regulator of mTORC1, were unable to inhibit mTORC1 in acidic extracellular conditions, showing that the TSC1-TSC2 complex is required for this response. Examination of the major upstream pathways converging on the TSC1-TSC2 complex showed that Akt signaling was unaffected by pH but that the Raf/MEK/ERK pathway was inhibited. Inhibition of MEK with drugs caused only modest mTORC1 inhibition, implying that other unidentified pathways also play major roles. CONCLUSIONS: This study reveals a novel role for the TSC1/TSC2 complex and mTORC1 in sensing variations in ambient pH. As a common feature of low tissue perfusion, low glucose availability and high energy expenditure, acidic pH may serve as a signal for mTORC1 to downregulate energy-consuming anabolic processes such as protein synthesis as an adaptive response to metabolically stressful conditions

Translational Up-Regulation and High-Level Protein Expression from Plasmid Vectors by mTOR Activation via Different Pathways in PC3 and 293T Cells

BACKGROUND: Though 293T cells are widely used for expression of proteins from transfected plasmid vectors, the molecular basis for the high-level expression is yet to be understood. We recently identified the prostate carcinoma cell line PC3 to be as efficient as 293T in protein expression. This study was undertaken to decipher the molecular basis of high-level expression in these two cell lines. METHODOLOGY/PRINCIPAL FINDINGS: In a survey of different cell lines for efficient expression of platelet-derived growth factor-B (PDGF-B), β-galactosidase (β-gal) and green fluorescent protein (GFP) from plasmid vectors, PC3 was found to express at 5-50-fold higher levels compared to the bone metastatic prostate carcinoma cell line PC3BM and many other cell lines. Further, the efficiency of transfection and level of expression of the reporters in PC3 were comparable to that in 293T. Comparative analyses revealed that the high level expression of the reporters in the two cell lines was due to increased translational efficiency. While phosphatidic acid (PA)-mediated activation of mTOR, as revealed by drastic reduction in reporter expression by n-butanol, primarily contributed to the high level expression in PC3, multiple pathways involving PA, PI3K/Akt and ERK1/2 appear to contribute to the abundant reporter expression in 293T. Thus the extent of translational up-regulation attained through the concerted activation of mTOR by multiple pathways in 293T could be achieved through its activation primarily by the PA pathway in PC3. CONCLUSIONS/SIGNIFICANCE: Our studies reveal that the high-level expression of proteins from plasmid vectors is effected by translational up-regulation through mTOR activation via different signaling pathways in the two cell lines and that PC3 is as efficient as 293T for recombinant protein expression. Further, PC3 offers an advantage in that the level of expression of the protein can be regulated by simple addition of n-butanol to the culture medium

Evolution of the TOR Pathway

The TOR kinase is a major regulator of growth in eukaryotes. Many components of the TOR pathway are implicated in cancer and metabolic diseases in humans. Analysis of the evolution of TOR and its pathway may provide fundamental insight into the evolution of growth regulation in eukaryotes and provide a practical framework on which experimental evidence can be compared between species. Here we performed phylogenetic analyses on the components of the TOR pathway and determined their point of invention. We find that the two TOR complexes and a large part of the TOR pathway originated before the Last Eukaryotic Common Ancestor and form a core to which new inputs have been added during animal evolution. In addition, we provide insight into how duplications and sub-functionalization of the S6K, RSK, SGK and PKB kinases shaped the complexity of the TOR pathway. In yeast we identify novel AGC kinases that are orthologous to the S6 kinase. These results demonstrate how a vital signaling pathway can be both highly conserved and flexible in eukaryotes

Tracking of an electron beam through the solar corona with LOFAR

© ESO 2018. The Sun's activity leads to bursts of radio emission, among other phenomena. An example is type-III radio bursts. They occur frequently and appear as short-lived structures rapidly drifting from high to low frequencies in dynamic radio spectra. They are usually interpreted as signatures of beams of energetic electrons propagating along coronal magnetic field lines. Here we present novel interferometric LOFAR (LOw Frequency ARray) observations of three solar type-III radio bursts and their reverse bursts with high spectral, spatial, and temporal resolution. They are consistent with a propagation of the radio sources along the coronal magnetic field lines with nonuniform speed. Hence, the type-III radio bursts cannot be generated by a monoenergetic electron beam, but by an ensemble of energetic electrons with a spread distribution in velocity and energy. Additionally, the density profile along the propagation path is derived in the corona. It agrees well with three-fold coronal density model by (1961, ApJ, 133, 983)

Computational Prediction and Experimental Verification of New MAP Kinase Docking Sites and Substrates Including Gli Transcription Factors

In order to fully understand protein kinase networks, new methods are needed to identify regulators and substrates of kinases, especially for weakly expressed proteins. Here we have developed a hybrid computational search algorithm that combines machine learning and expert knowledge to identify kinase docking sites, and used this algorithm to search the human genome for novel MAP kinase substrates and regulators focused on the JNK family of MAP kinases. Predictions were tested by peptide array followed by rigorous biochemical verification with in vitro binding and kinase assays on wild-type and mutant proteins. Using this procedure, we found new ‘D-site’ class docking sites in previously known JNK substrates (hnRNP-K, PPM1J/PP2Czeta), as well as new JNK-interacting proteins (MLL4, NEIL1). Finally, we identified new D-site-dependent MAPK substrates, including the hedgehog-regulated transcription factors Gli1 and Gli3, suggesting that a direct connection between MAP kinase and hedgehog signaling may occur at the level of these key regulators. These results demonstrate that a genome-wide search for MAP kinase docking sites can be used to find new docking sites and substrates