Glycoside hydrolases (GHs, also called glycosidases) catalyze the hydrolysis of glycosidic bonds in polysaccharides. Numerous GH genes have been identified from various organisms and are classified into 188 families, abbreviated GH1 to GH188. Enzymes in the GH32 family hydrolyze fructans, which are present in approximately 15% of flowering plants and are widespread across microorganisms.
View Article and Find Full Text PDFAnimals are thought to use only glucose polymers (glycogen) as energy reserve, whereas both glucose (starch) and fructose polymers (fructans) are used by microbes and plants. Here, it is reported that the gall midge Mayetiola destructor, and likely other herbivorous animal species, gained the ability to utilize dietary fructans directly as storage polysaccharides by a single horizontal gene transfer (HGT) of bacterial levanase/inulinase gene followed by gene expansion and differentiation. Multiple genes encoding levanases/inulinases have their origin in a single HGT event from a bacterium and they show high expression levels and enzymatic activities in different tissues of the gall midge, including nondigestive fat bodies and eggs, both of which contained significant amounts of fructans.
View Article and Find Full Text PDFGut microbes are known to play various roles in insects such as digestion of inaccessible nutrients, synthesis of deficient amino acids, and interaction with ecological environments, including host plants. Here, we analyzed the gut microbiome in Hessian fly, a serious pest of wheat. A total of 3,654 high quality sequences of the V3 hypervariable region of the 16S rRNA gene were obtained through 454-pyrosequencing.
View Article and Find Full Text PDFVariation in environmental and physical factors within food processing facilities can influence both the distribution of stored-product pests and trapping efficiency. Data from a long-term Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae) monitoring program was used to evaluate spatial variation in captures among trap locations and to determine relationships with environmental and physical variables. From the complete monitoring data set, different subsets were created for the cool and warm seasons, and period of time when environmental and physical factors were measured (2009-2010), with all data sets showing significant differences among trap locations in terms of beetle captures and proportion of time that traps exceeded 2.
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