Regulatory considerations surrounding the deployment of Bt-expressing cowpea in Africa: report of the deliberations of an expert panel.

Cowpea (Vigna unguiculata spp unguiculata) is adapted to the drier agro-ecological zones of West Africa where it is a major source of dietary protein and widely used as a fodder crop. Improving the productivity of cowpea can enhance food availability and security in West Africa. Insect predation--predominately from the legume pod borer (Maruca vitrata), flower thrips (Megalurothrips sjostedti) and a complex of pod-sucking bugs (e.g., Clavigralla spp)--is a major yield-limiting factor in West African cowpea production. Dramatic increases in yield are shown when M. vitrata is controlled with insecticides. However, availability, costs, and safety considerations limit pesticides as a viable option for boosting cowpea production. Development of Bt-cowpea through genetic modification (GM) to control the legume pod borer is a promising approach to cowpea improvement. Cowpea expressing the lepidopteran-active Cry1Ab protein from Bacillus thuringiensis is being developed as a first generation Bt-cowpea crop for West Africa. Appropriate stewardship of Bt-cowpea to assure its sustainability under West African conditions is critical to its successful development. A first step in this process is an environmental risk assessment to determine the likelihood and magnitude of adverse effects of the Cry1Ab protein on key environmental protection goals in West Africa. Here we describe the results of an expert panel convened in 2009 to develop the problem formulation phase for Bt-cowpea and to address specific issues around gene flow, non-target arthropods, and insect resistance management.

Characterization of Cry34/Cry35 binary insecticidal proteins from diverse Bacillus thuringiensis strain collections.

Bacillus thuringiensis crystal proteins of the Cry34 and Cry35 classes function as binary toxins showing activity on the western corn rootworm, Diabrotica virgifera virgifera LeConte. We surveyed 6,499 B. thuringiensis isolates by hybridization for sequences related to cry35A genes, identifying 78 strains. Proteins of the appropriate molecular mass (ca. 44 kDa) for Cry35 were observed in 42 of the strains. Full-length, or nearly full-length, sequences of 34 cry34 genes and 16 cry35 genes were also obtained from cloning, PCR analysis, and DNA sequencing. These included representatives of all known Cry34A, Cry34B, Cry35A, and Cry35B classes, as well as a novel Cry34A/Cry35A-like pair. Bioassay analysis indicated that cry35-hybridizing strains not producing a ca. 14-kDa protein, indicative of Cry34, were not active on corn rootworms, and that the previously identified Cry34A/Cry35A pairs were more active than the Cry34B/Cry35B pairs. The cry35-hybridizing B. thuringiensis strains were found in locales and materials typical for other B. thuringiensis strains. Comparison of the sequences with the geographic origins of the strains showed that identical, or nearly identical, sequences were found in strains from both Australasia and the Americas. Sequence similarity searches revealed that Cry34 proteins are similar to predicted proteins in Photorhabdus luminescens and Dictyostelium discoidium, and that Cry35Ab1 contains a segment similar to beta-trefoil domains that may be a binding motif. The binary Cry34/Cry35 B. thuringiensis crystal proteins thus appear closely related to each other, are environmentally ubiquitous, and share sequence similarities consistent with activity through membrane disruption in target organisms.

Sensitivity analysis for validating expert opinion as to ideal data set criteria for transport modeling.

Environmental fate modeling results are often used in risk assessment without adequately considering uncertainty in exposure predictions. Sensitivity analysis is fundamental to model validation and error prediction since sensitive model input parameters account for the largest variance in model prediction. Once identified, sensitive model input parameters can be used to propagate parametric uncertainty in numerical predictions. Output sensitivity to variation in input code sequences was investigated for the pesticide root zone model (PRZM 3) using Plackett-Burman analysis for six runoff and leaching data sets. The analysis utilized an incomplete block factorial design with even parameter weighting and uniform proportional input perturbation. Timing and duration of key period rainfall were assumed a priori to be dominant sensitive inputs. Thus, meteorological data were fixed, allowing identification of additional input components contributing to model sensitivity. Results validated expert modeler assumptions concerning parameters most critical for model validation. For leaching data sets, the application rate, soil bulk density (an indicator of available water-holding capacity), chemical partition coefficient, and pesticide degradation rates were commonly the most sensitive inputs. For runoff data sets, the in-crop runoff curve number was the most significant input governing pesticide loss in runoff and erosion flux. The chemical partition coefficient, soil and foliar decay rates, and soil bulk density were also common sensitive components for runoff predictions. These commonly observed sensitive components for runoff and leaching prediction need to be carefully considered in the design and conduct of relevant field studies, modeling assessment of such studies, and future improvements in algorithms for environmental transport modeling.