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A General Approach to Test for Interaction Among Mixtures of Insecticidal Proteins Which Target Different Orders of Insect Pests.

ABSTRACT: A shift toward transgenic crops which produce combinations of insecticidal proteins has increased the interest (Syngenta Seeds, Inc., Minnetonka, MN) in studying the potential for interactions amongst those proteins. We present a general testing method which accommodates proteins with nonoverlapping spectrums of activity. Our sequential testing approach first investigates groups of the proteins with overlapping activity; e.g., proteins active against Lepidoptera or Coleoptera, respectively. The Colby method is used to test for interactions within each respective group. Subsequently, the mixture of proteins within each group is regarded as a single entity and tests for interactions between the groups (when combined) is conducted using analysis of variance. We illustrate the method using Cry1Ab, Vip3Aa20, and Cry1F (a mixture of proteins active against Lepidoptera), and mCry3A and eCry3.1Ab (a mixture of proteins active against Coleoptera). These insecticidal proteins are produced by Bt11 × MIR162 × TC1507 × MIR604 × 5307 maize. We detected no interactions between Cry1Ab, Vip3Aa20, and Cry1F in tests using larvae of two different lepidopteran species, and possible slight antagonism between mCry3A and eCry3.1Ab with a coleopteran test species. We detected no effect of (eCry3.1Ab + mCry3A) on the potency of (Cry1Ab + Vip3Aa20 + Cry1F) to lepidopteran larvae, and no effect of (Cry1Ab + Vip3Aa20 + Cry1F) on the potency of (mCry3A + eCry3.1Ab) to coleopteran larvae. We discuss implications of these results for characterization of Bt11 × MIR162 × TC1507 × MIR604 × 5307 maize, and the value of the method for characterizing other transgenic crops that produce several insecticidal proteins.

SUBMITTER: Graser G

PROVIDER: S-EPMC5416900 | biostudies-other | 2017 Jan

REPOSITORIES: biostudies-other

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A General Approach to Test for Interaction Among Mixtures of Insecticidal Proteins Which Target Different Orders of Insect Pests.

Graser Gerson G Walters Frederick S FS Burns Andrea A Sauve Alaina A Raybould Alan A

Journal of insect science (Online) 20170101 2

A shift toward transgenic crops which produce combinations of insecticidal proteins has increased the interest (Syngenta Seeds, Inc., Minnetonka, MN) in studying the potential for interactions amongst those proteins. We present a general testing method which accommodates proteins with nonoverlapping spectrums of activity. Our sequential testing approach first investigates groups of the proteins with overlapping activity; e.g., proteins active against Lepidoptera or Coleoptera, respectively. The ...[more]

PMID: 28355479

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Project description:Brazil and South Africa, countries with economies in transition, are characterized by a dual agrarian structure co-occurring, sometimes, alongside in the same region. Large-scale commercial farming produces crops for export to global markets on the one hand, and small-scale farming, on the other hand, provides for subsistence and local markets. In both systems, maize (Zea mays) is a key crop for these two countries. For the commercial system, maize is a commodity crop while for the small-scale system it is the prime staple crop. In commercial systems, farmers predominantly grow genetically modified (GM) hybrid maize. In small-scale systems, farmers rely on open pollinated varieties (OPVs) and/or landraces and are largely dependent on seed saving systems. The aim of this study was to understand the relationship between transgene expression rates, the resulting concentrations of the transgene product (Bt protein) and its bioactivity in insect pests following transgene flow from GM hybrid maize into non-genetically modified, non-GM near-isogenic maize hybrid (ISO) and OPVs. We modeled segregation patterns and measured cry1Ab transgene expression (mRNA quantification), Cry1Ab protein concentration and pest survival. Two groups of F1, F2 crosses and backcrosses with GM, ISO and OPV maize varieties from Brazil and South Africa were used. Bioassays with the larvae of two lepidopteran maize pest species, Helicoverpa armigera and Spodoptera littoralis, were carried out. Overall, the cry1Ab transgene outcrossed effectively into the genetic backgrounds tested. The cry1Ab transgene was stably expressed in both ISO and OPV genetic backgrounds. Transgene introgression led to consistent, though highly variable, concentrations of Cry1Ab toxins that were similar to those observed in GM parental maize. Most crosses, but not all, suggested the expected Mendelian segregation pattern. Transgene expression rates were significantly higher than expected from purely Mendelian segregation in the South African crosses. In South African materials, ISO and OPV crosses produced significantly lower Cry1Ab concentrations compared to the GM parental maize. The Cry1Ab toxins from crosses were bioactive and induced mortality rates of ≥92.19% in H. armigera and ≥40.63% in S. littoralis after a period of only 4 days. However, no correlations were observed between the quantitation of mRNA for cry1Ab and the corresponding Cry1Ab protein concentrations, nor between the Cry1Ab concentrations and insect mortality rates across different genetic backgrounds. We therefore suggest that while transcription of the cry1Ab transgene reliably determines the presence of Cry1Ab protein, mRNA levels do not reflect, by themselves, the end Cry1Ab protein concentrations found in the plant. Because predictably high Cry1Ab concentrations are a key prerequisite for effective insect resistance management (IRM) programs, this observation raises questions about the effectiveness of such programs in scenarios with complex crop genetic backgrounds. On the other hand, confirmed bioactivity in all crosses should be expected to impact small farmer's selection behavior, unknowingly favoring the insecticidal trait. This may lead to a fixation of the trait in the wider population, and may influence the genetic diversity of varieties maintained by small-scale farmers.

Project description:BACKGROUND: Previous studies on insect DNA barcoding provide contradictory results and suggest not consistent performances across orders. This work aims at providing a general evaluation of insect DNA barcoding and "mini-barcoding" by performing simulations on a large database of 15,948 DNA barcodes. We compared the proportions of correctly identified queries across a) six insect orders (Coleoptera, Diptera, Hemiptera, Hymenoptera, Lepidoptera and Orthoptera), b) four identification criteria (Best Match: BM; Best Close Match: BCM; All Species Barcodes: ASB; tree-based identification: NJT), and c) reference databases with different taxon coverage (100, 500, 1,000, 1,500 and 1,995 insect species). RESULTS: Analysis of variance revealed highly significant differences among ID criteria and insect orders. A posteriori comparisons of means showed that NJT had always a significantly lower identification success (NJT = 0.656, S.D. = 0.118) compared to both BM and BCM (BM = 0.948, S.D. = 0.026; BCM = 0.946, S.D. = 0.031). NJT showed significant variations among orders, with the highest proportion of correctly identified queries in Hymenoptera and Orthoptera and the lowest in Diptera. Conversely, the proportions of correct matches of BM and BCM were consistent across orders but a progressive increase in false identification was observed when larger reference databases were used. CONCLUSIONS: Regardless the relatively low proportion of Type I errors (misidentification of queries which are represented in the reference database) of BM and BCM, the lack of reference DNA barcodes for 98% of the known insect species implies that insect DNA barcoding is heavily biased by Type II errors (misidentification of queries without conspecifics in the database). The detrimental effects of Type II errors could be circumvented if insect DNA barcoding is used to verify the lack of correspondence between a query and a list of properly referenced target species (e.g. insect pests). This "negative identification" would only be subjected to Type I errors and could be profitably adopted in insect quarantine procedures.

Dataset Information

A General Approach to Test for Interaction Among Mixtures of Insecticidal Proteins Which Target Different Orders of Insect Pests.

Publications

A General Approach to Test for Interaction Among Mixtures of Insecticidal Proteins Which Target Different Orders of Insect Pests.

Similar Datasets

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