CD36 signals to the actin cytoskeleton and regulates microglial migration via a p130Cas complex

The pattern recognition receptor CD36 initiates a signaling cascade that promotes microglial activation and recruitment to beta-amyloid deposits in the brain. In the present study we identify the focal adhesion-associated proteins p130Cas, Pyk2, and paxillin as novel members of the tyrosine kinase signaling pathway downstream of CD36 and show that assembly of this complex is essential for microglial migration. In primary microglia and macrophages exposed to beta-amyloid, the scaffolding protein p130Cas is rapidly tyrosine-phosphorylated and co-localizes with CD36 to membrane ruffles contemporaneous with F-actin polymerization. These beta-amyloid-stimulated events are not detected in CD36 null cells and are dependent on CD36 activation of Src family tyrosine kinases. Fyn, a Src kinase known to interact with CD36, co-precipitates with p130Cas and is an essential upstream intermediate in the signaling pathways leading to phosphorylation of the p130Cas substrate domain. Furthermore, the p130Cas-interacting kinase Pyk2 and the cytoskeletal adapter protein paxillin also demonstrate CD36-dependent phosphorylation, identifying these focal adhesion molecules as additional members of this beta-amyloid signaling cascade. Disruption of this p130Cas complex by small interfering RNA silencing inhibits p44/42 mitogen-activated protein kinase phosphorylation and microglial migration, illustrating the importance of this pathway in microglial activation and recruitment. Together, these data are the first to identify the signaling cascade that directly links CD36 to the actin cytoskeleton and, thus, implicates it in diverse processes such as cellular migration, adhesion, and phagocytosis.     

Rotational-echo double-resonance NMR-restrained model of the ternary complex of 5-enolpyruvylshikimate-3-phosphate synthase

The 46-kD enzyme 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase catalyzes the condensation of shikimate-3-phosphate (S3P) and phosphoenolpyruvate to form EPSP. The reaction is inhibited by N-(phosphonomethyl)-glycine (Glp), which, in the presence of S3P, binds to EPSP synthase to form a stable ternary complex. We have used solid-state NMR and molecular modeling to characterize the EPSP synthase-S3P-Glp ternary complex. Modeling began with the crystal coordinates of the unliganded protein, published distance restraints, and information from the chemical modification and mutagenesis literature on EPSP synthase. New inter-ligand and ligand-protein distances were obtained. These measurements utilized the native (31)P in S3P and Glp, biosynthetically (13)C-labeled S3P, specifically (13)C and (15)N labeled Glp, and a variety of protein-(15)N labels. Several models were investigated and tested for accuracy using the results of both new and previously published rotational-echo double resonance (REDOR) NMR experiments. The REDOR model is compared with the recently published X-ray crystal structure of the ternary complex, PDB code 1G6S. There is general agreement between the REDOR model and the crystal structure with respect to the global folding of the two domains of EPSP synthase and the relative positioning of S3P and Glp in the binding pocket. However, some of the REDOR data are in disagreement with predictions based on the coordinates of 1G6S, particularly those of the five arginines lining the binding site. We attribute these discrepancies to substantive differences in sample preparation for REDOR and X-ray crystallography. We applied the REDOR restraints to the 1G6S coordinates and created a REDOR-refined xray structure that agrees with the NMR results.     

Encoding microbial metabolic logic: predicting biodegradation

Prediction of microbial metabolism is important for annotating genome sequences and for understanding the fate of chemicals in the environment. A metabolic pathway prediction system (PPS) has been developed that is freely available on the world wide web (), recognizes the organic functional groups found in a compound, and predicts transformations based on metabolic rules. These rules are designed largely by examining reactions catalogued in the University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD) and are generalized based on metabolic logic. The predictive accuracy of the PPS was tested: (1) using a 113-member set of compounds found in the database, (2) against a set of compounds whose metabolism was predicted by human experts, and (3) for consistency with experimental microbial growth studies. First, the system correctly predicted known metabolism for 111 of the 113 compounds containing C and H, O, N, S, P and/or halides that initiate existing pathways in the database, and also correctly predicted 410 of the 569 known pathway branches for these compounds. Second, computer predictions were compared to predictions by human experts for biodegradation of six compounds whose metabolism was not described in the literature. Third, the system predicted reactions liberating ammonia from three organonitrogen compounds, consistent with laboratory experiments showing that each compound served as the sole nitrogen source supporting microbial growth. The rule-based nature of the PPS makes it transparent, expandable, and adaptable.     

Investigating the independent evolution of the size of floral organs via G-matrix estimation and artificial selection

The attractiveness of a plant to pollinators is dependent on both the number of flowers produced and the size of the petals. However, limiting resources often result in a size/number trade-off, whereby the plant can make either more flowers or larger flowers, but not both. If developmental genes underlying sepal and petal identity (some of which overlap) also influence size, then this shared genetic basis could constrain the independent evolution of floral size and attractiveness. Here, we determined whether the size of sepals and petals in the dioecious perennial, Silene latifolia, are developmentally independent by performing two experiments: a genetic variance-covariance experiment to estimate genetic correlations between calyx width, petal-limb length, flower mass, and number and a four-bout artificial-selection experiment to alter calyx width and estimate the correlated response in petal-limb length. In addition, we determined whether variation in petal-limb length is the result of cell expansion or cell proliferation. The first experiment revealed that petal-limb length is not genetically correlated with calyx width, and the second experiment confirmed this; selection on calyx width did not result in a predictable or significant change in petal-limb length. Flower number was negatively correlated with all the floral traits measured, indicating a flower size/number trade-off. Cell number, but not size, explained a significant amount of the variation in petal-limb length. We conclude that the size of the two outer floral organs can evolve independently. This species can therefore increase the number of flowers produced by decreasing investment in the calyx without simultaneously decreasing petal size and the attractiveness of each individual flower to pollinators.     

The University of Minnesota Biocatalysis/Biodegradation Database: post-genomic data mining

The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://umbbd.ahc.umn.edu/) provides curated information on microbial catabolism and related biotransformations, primarily for environmental pollutants. Currently, it contains information on over 130 metabolic pathways, 800 reactions, 750 compounds and 500 enzymes. In the past two years, it has increased its breath to include more examples of microbial metabolism of metals and metalloids; and expanded the types of information it includes to contain microbial biotransformations of, and binding interactions with many chemical elements. It has also increased the ways in which this data can be accessed (mined). Structure-based searching was added, for exact matches, similarity, or substructures. Analysis of UM-BBD reactions has lead to a prototype, guided, pathway prediction system. Guided prediction means that the user is shown all possible biotransformations at each step and guides the process to its conclusion. Mining the UM-BBD's data provides a unique view into how the microbial world recycles organic functional groups. UM-BBD users are encouraged to comment on all aspects of the database, including the information it contains and the tools by which it can be mined. The database and prediction system develop under the direction of the scientific community.     

SubViral RNA: a database of the smallest known auto-replicable RNA species

We describe here the establishment of an online database containing a large number of sequences and related data on viroids, viroid-like RNAs and human hepatitis delta virus (vHDV) in a customizable and user-friendly format. This database is available on the World Wide Web at http://penelope.med.usherb.ca/subviral.