Crystal structure of a novel mid-gut procarboxypeptidase from the cotton pest Helicoverpa armigera.

The cotton bollworm Helicoverpa armigera (Hubner) (Lepidoptera: Noctuidae) is one of the most serious insect pests in Australia, India and China. The larva causes substantial economical losses to legume, fibre, cereal oilseed and vegetable crops. This pest has proven to be difficult to control by conventional means, mainly due to the development of pesticide resistance. We present here the 2.5 A crystal structure from the novel procarboxypeptidase (PCPAHa) found in the gut extracts from H. armigera larvae, the first one reported for an insect. This metalloprotease is synthesized as a zymogen of 46.6 kDa which, upon in vitro activation with Lys-C endoproteinase, yields a pro-segment of 91 residues and an active carboxypeptidase moiety of 318 residues. Both regions show a three-dimensional structure quite similar to the corresponding structures in mammalian digestive carboxypeptidases, the most relevant structural differences being located in the loops between conserved secondary structure elements, including the primary activation site. This activation site contains the motif (Ala)(5)Lys at the C terminus of the helix connecting the pro- and the carboxypeptidase domains. A remarkable feature of PCPAHa is the occurrence of the same (Ala)(6)Lys near the C terminus of the active enzyme. The presence of Ser255 in PCPAHa instead of Ile and Asp found in the pancreatic A and B forms, respectively, enlarges the S1' specificity pocket and influences the substrate preferences of the enzyme. The C-terminal tail of the leech carboxypeptidase inhibitor has been modelled into the PCPAHa active site to explore the substrate preferences and the enzymatic mechanism of this enzyme.     

Characterization of the atypical Ppz/Hal3 phosphatase system from the pathogenic fungus Cryptococcus neoformans

Ppz Ser/Thr protein phosphatases (PPases) are found only in fungi and have been proposed as potential antifungal targets. In Saccharomyces cerevisiae Ppz1 (ScPpz1) is involved in regulation of monovalent cation homeostasis. ScPpz1 is inhibited by two regulatory proteins, Hal3 and Vhs3, which have moonlighting properties, contributing to the formation of an unusual heterotrimeric PPC decarboxylase (PPCDC) complex crucial for CoA biosynthesis. Here we report the functional characterization of CnPpz1 (CNAG_03673) and two possible Hal3‐like proteins, CnHal3a (CNAG_00909) and CnHal3b (CNAG_07348) from the pathogenic fungus Cryptococcus neoformans. Deletion of CnPpz1 or CnHal3b led to phenotypes unrelated to those observed in the equivalent S. cerevisiae mutants, and the CnHal3b‐deficient strain was less virulent. CnPpz1 is a functional PPase and partially replaced endogenous ScPpz1. Both CnHal3a and CnHal3b interact with ScPpz1 and CnPpz1 in vitro but do not inhibit their phosphatase activity. Consistently, when expressed in S. cerevisiae, they poorly reproduced the Ppz1‐regulatory properties of ScHal3. In contrast, both proteins were functional monogenic PPCDCs. The CnHal3b isoform was crystallized and, for the first time, the 3D‐structure of a fungal PPCDC elucidated. Therefore, our work provides the foundations for understanding the regulation and functional role of the Ppz1‐Hal3 system in this important pathogenic fungus.     

A validated whole-genome association study of efficient food conversion in cattle

The genetic factors that contribute to efficient food conversion are largely unknown. Several physiological systems are likely to be important, including basal metabolic rate, the generation of ATP, the regulation of growth and development, and the homeostatic control of body mass. Using whole-genome association, we found that DNA variants in or near proteins contributing to the background use of energy of the cell were 10 times as common as those affecting appetite and body-mass homeostasis. In addition, there was a genic contribution from the extracellular matrix and tissue structure, suggesting a trade-off between efficiency and tissue construction. Nevertheless, the largest group consisted of those involved in gene regulation or control of the phenotype. We found that the distribution of micro-RNA motifs was significantly different for the genetic variants associated with residual feed intake than for the genetic variants in total, although the distribution of promoter sequence motifs was not different. This suggests that certain subsets of micro-RNA are more important for the regulation of this trait. Successful validation depended on the sign of the allelic association in different populations rather than on the strength of the initial association or its size of effect.     

Mining gene expression profiles: an integrated implementation of kernel principal component analysis and singular value decomposition

The detection of genes that show similar profiles under different experimental conditions is often an initial step in inferring the biological significance of such genes. Visualization tools are used to identify genes with similar profiles in microarray studies. Given the large number of genes recorded in microarray experiments, gene expression data are generally displayed on a low dimensional plot, based on linear methods. However, microarray data show nonlinearity, due to high-order terms of interaction between genes, so alternative approaches, such as kernel methods, may be more appropriate. We introduce a technique that combines kernel principal component analysis (KPCA) and Biplot to visualize gene expression profiles. Our approach relies on the singular value decomposition of the input matrix and incorporates an additional step that involves KPCA. The main properties of our method are the extraction of nonlinear features and the preservation of the input variables (genes) in the output display. We apply this algorithm to colon tumor, leukemia and lymphoma datasets. Our approach reveals the underlying structure of the gene expression profiles and provides a more intuitive understanding of the gene and sample association.     

Gene expression studies of developing bovine <Emphasis Type="Italic">longissimus</Emphasis>muscle from two different beef cattle breeds

Background  

The muscle fiber number and fiber composition of muscle is largely determined during prenatal development. In order to discover genes that are involved in determining adult muscle phenotypes, we studied the gene expression profile of developing fetal bovine longissimus muscle from animals with two different genetic backgrounds using a bovine cDNA microarray. Fetal longissimus muscle was sampled at 4 stages of myogenesis and muscle maturation: primary myogenesis (d 60), secondary myogenesis (d 135), as well as beginning (d 195) and final stages (birth) of functional differentiation of muscle fibers. All fetuses and newborns (total n = 24) were from Hereford dams and crossed with either Wagyu (high intramuscular fat) or Piedmontese (GDF8 mutant) sires, genotypes that vary markedly in muscle and compositional characteristics later in postnatal life.     

Structural basis for SENP2 protease interactions with SUMO precursors and conjugated substrates

SUMO processing and deconjugation are essential proteolytic activities for nuclear metabolism and cell-cycle progression in yeast and higher eukaryotes. To elucidate the mechanisms used during substrate lysine deconjugation, SUMO isoform processing and SUMO isoform interactions, X-ray structures were determined for a catalytically inert SENP2 protease domain in complex with conjugated RanGAP1-SUMO-1 or RanGAP1-SUMO-2, or in complex with SUMO-2 or SUMO-3 precursors. Common features within the active site include a 90 degrees kink proximal to the scissile bond that forces C-terminal amino acid residues or the lysine side chain toward a protease surface that appears optimized for lysine deconjugation. Analysis of this surface reveals SENP2 residues, particularly Met497, that mediate, and in some instances reverse, in vitro substrate specificity. Mutational analysis and biochemistry provide a mechanism for SENP2 substrate preferences that explains why SENP2 catalyzes SUMO deconjugation more efficiently than processing.