The decrease in susceptibility to Cry1Ab was expected, but the specific contributions to this resistance by MON 810 maize cannot be distinguished from cross-resistance to Cry1Ab caused by exposure to Cry1F maize. Technologies combining multiple novel insecticidal traits with no cross-resistance to the current Cry1 proteins and high activity against the same target pests should be pursued in Brazil and similar environments. © 2015 Society of Chemical Industry.
Background: Cases of western corn rootworm (WCR) field-evolved resistance toCry3Bb1 and other corn rootworm (CRW) control traits have been reported. Pyramid products expressing multiple CRW traits can delay resistance compared to single trait products. We used field studies to assess the pyramid CRW corn products, SmartStax (expressing Cry3Bb1 and Cry34Ab1/Cry35Ab1) and SmartStax PRO (expressing Cry3Bb1, Cry34Ab1/Cry35Ab1 and DvSnf7), at locations with high WCR densities and possible Cry3Bb1 resistance, and to assess the reduction in adult emergence attributable to DvSnf7 and other traits. Insect resistance models were used to assess durability of SmartStax and SmartStax PRO to WCR resistance. Results: SmartStax significantly reduced root injury compared to non-CRW-trait controls at all but one location with measurable WCR pressure, while SmartStax PRO significantly reduced root injury at all locations, despite evidence of Cry3Bb1 resistance at some locations. The advantage of SmartStax PRO over SmartStax in reducing root damage was positively correlated with root damage on non-CRW-trait controls. DvSnf7 was estimated to reduce WCR emergence by approximately 80-95%, which modeling indicated will improve durability of Cry3Bb1 and Cry34Ab1/Cry35Ab1 compared to SmartStax. Conclusion: The addition of DvSnf7 in SmartStax PRO can reduce root damage under high WCR densities and prolong Cry3Bb1 and Cry34Ab1/Cry35Ab1 durability.
To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.
Genes of the major histocompatibility complex (MHC) influence the urinary odors of mice. Behavioral studies have shown (1) that mice differing only at MHC have distinct urinary odors, suggesting an MHC odor phenotype or odortype; (2) that the MHC odortype can be recognized across different background strains; and (3) that the MHC odortype is not an additive trait. Very little is known about the odorants underlying this behavioral phenotype. We compared urinary volatile profiles of two MHC haplotypes (H2(b) and H2(k)) and their heterozygous cross (H2(b) x H2(k)) for two different background strains (C57BL/6J and BALB/c) using solid phase micro-extraction (SPME) headspace analysis and gas chromatography/mass spectrometry (GC/MS). Both MHC and background genes substantially influence the volatile profile. Of 148 compounds screened, 108 of them significantly differ between the six genotypes. Surprisingly, for numerous compounds, their MHC associations are moderated by background genes (i.e., there is a significant MHC x background interaction effect in the statistical model relating genotype to relative compound concentration). These interactions account for nearly 30% of the total genetic effect on the volatile profile. MHC heterozygosity further extends the odortype diversity. For many compounds, the volatile expression for the heterozygote is more extreme than the expression for either homozygote, suggesting a heterozygous-specific odortype. The remarkable breadth of effects of MHC variation on concentrations of metabolites and the interaction between MHC and other genetic variation implies the existence of as yet unknown processes by which variation in MHC genes gives rise to variation in volatile molecules in body fluids.
This paper examines the application of gas chromatography/mass spectrometry (GC/MS) in a comparative experiment to identify volatile compounds from urine that differ in concentration between two groups of inbred mice. A complex mixture might comprise several hundred or even thousands of volatile compounds. Because their number and location in a chromatogram are generally unknown, and because components overlap in populous chromatograms, the statistical problems offer significant challenges beyond traditional two-group screening procedures. We describe a statistical procedure to compare two-dimensional GC/MS profiles between groups, which entails (1) signal processing, baseline correction, and peak detection in single ion chromatograms; (2) aligning chromatograms in time; (3) normalizing differences in overall signal intensities; and (4) detecting chromatographic regions that differ between groups. In an application to chemosignaling, we detect differences in GC/MS chromatograms of ether-extracted urine collected from two inbred groups of mice that differ only in genes of the major histocompatibility complex (MHC). Several dozen MHC-regulated compounds are found, including two known mouse pheromones, 2,5-dimethylpyrazine and 2-sec-butyl-4,5-dihydrothiazole.
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