Identification and characterization of proteins from Bacillus thuringiensis with high toxic activity against the sheep blowfly, Lucilia cuprina.

Current control of the sheep blowfly (Lucilia cuprina) relies on chemical insecticides, however, with the development of resistance and increasing concerns about human health and environmental residues, alternative strategies to control this economically important pest are required. In this study, we have identified several isolates of Bacillus thuringiensis (Bt), collected from various Australian soil samples, that produce crystals containing 130 and 28 kDa proteins. These isolates were highly toxic to feeding larvae in both in vitro bioassays and in vivo on sheep. By N-terminal amino acid sequencing, we identified the smaller crystal band (28 kDa) as a cytological (Cyt) protein. Upon solubilization and proteolytic processing by trypsin, the 130 kDa crystal protein yielded among others, a truncated 55-60 kDa toxin moiety which exhibited larvicidal activity against sheep blowfly. The amino-terminal sequence of the trypsin-resistant protein band revealed that this Bt endotoxin was encoded by a new cry gene. The novel cry protein was present in all the strains that were highly toxic in the larval assay. We have also identified from one of the isolates, a novel secretory toxin with larvicidal activity.

Diet influences the ecology of lactic acid bacteria and Escherichia coli along the digestive tract of cattle: neural networks and 16S rDNA.

In this manuscript, the authors have sought to gain a better understanding of the interactions between Escherichia coli and lactic acid bacteria (LAB) isolated from Rogossa MRS agar along the digestive tract of grain- and forage-fed cattle. E. coli from cattle receiving a high-grain diet were more numerous (P<0.05) than from the high-forage diet and the highest numbers were in the faeces. Isolates on Rogossa MRS agar were always greater in the high-grain diet (P<0.05) and contained a significant number of LAB. A random set of Rogossa MRS agar colonies was selected and artificial neural networks were used to develop a relationship between colony description and species which was validated using sequence analysis (16S rDNA). The neural networks correctly predicted species in more than 80 % of cases and was composed, primarily, of Lactobacillus vitulinus, Lactobacillus ruminis, Selenomonas ruminantium, Streptococcus bovis, Acidaminococcus fermentans and Megasphaera elsdenii. In conjunction with statistical diversity indices, it was demonstrated that diversity in the high-fibre diet was always lower and was a consequence of the dominance of Str. bovis. In contrast, the diversity in the high-grain diet was greater (P<0.05) and was a consequence of the decline in Str. bovis. These data demonstrate that there is a positive relationship between coliform and LAB isolates throughout the digestive tract of cattle, and diet is the major factor regulating bacterial composition.