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      An ABC Transporter Mutation Is Correlated with Insect Resistance to Bacillus thuringiensis Cry1Ac Toxin

      1 , 2 , 2 , 2 , *

      PLoS Genetics

      Public Library of Science

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          Abstract

          Transgenic crops producing insecticidal toxins from Bacillus thuringiensis (Bt) are commercially successful in reducing pest damage, yet knowledge of resistance mechanisms that threaten their sustainability is incomplete. Insect resistance to the pore-forming Cry1Ac toxin is correlated with the loss of high-affinity, irreversible binding to the mid-gut membrane, but the genetic factors responsible for this change have been elusive. Mutations in a 12-cadherin-domain protein confer some Cry1Ac resistance but do not block this toxin binding in in vitro assays. We sought to identify mutations in other genes that might be responsible for the loss of binding. We employed a map-based cloning approach using a series of backcrosses with 1,060 progeny to identify a resistance gene in the cotton pest Heliothis virescens that segregated independently from the cadherin mutation. We found an inactivating mutation of the ABC transporter ABCC2 that is genetically linked to Cry1Ac resistance and is correlated with loss of Cry1Ac binding to membrane vesicles. ABC proteins are integral membrane proteins with many functions, including export of toxic molecules from the cell, but have not been implicated in the mode of action of Bt toxins before. The reduction in toxin binding due to the inactivating mutation suggests that ABCC2 is involved in membrane integration of the toxin pore. Our findings suggest that ABC proteins may play a key role in the mode of action of Bt toxins and that ABC protein mutations can confer high levels of resistance that could threaten the continued utilization of Bt–expressing crops. However, such mutations may impose a physiological cost on resistant insects, by reducing export of other toxins such as plant secondary compounds from the cell. This weakness could be exploited to manage this mechanism of Bt resistance in the field.

          Author Summary

          Crystal toxin proteins from Bacillus thuringiensis (Bt) make ideal bioinsecticides because of their high potency against certain insects and lack of activity against most other species. Transgenic cotton and maize expressing pore-forming Cry1A Bt-toxins are now widely used in agriculture, enabling substantial reductions in the use of chemical insecticides. However this has greatly increased the selection pressure in pest populations for toxin resistance. Preventing or delaying the development of this resistance is a high priority, to avoid a replay of the onset of insecticide resistance brought on by dependency on chemical pesticides. Because the molecular details of Bt mode of action are still not fully understood, insect strains collected from the field and selected to high levels of resistance in the laboratory are useful in discovering the obstacles the toxin must overcome before it finally forms the pore and kills the insect. We used a genetic approach to explore a poorly understood step in the toxin mode of action, which is blocked in an extremely resistant strain of an important cotton pest. As well as providing the tools to diagnose this type of resistance when it appears in the field, this discovery suggests factors that may counteract its eventual spread.

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          Most cited references 72

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          MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations.

          With the advent of RFLPs, genetic linkage maps are now being assembled for a number of organisms including both inbred experimental populations such as maize and outbred natural populations such as humans. Accurate construction of such genetic maps requires multipoint linkage analysis of particular types of pedigrees. We describe here a computer package, called MAPMAKER, designed specifically for this purpose. The program uses an efficient algorithm that allows simultaneous multipoint analysis of any number of loci. MAPMAKER also includes an interactive command language that makes it easy for a geneticist to explore linkage data. MAPMAKER has been applied to the construction of linkage maps in a number of organisms, including the human and several plants, and we outline the mapping strategies that have been used.
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            A combined transmembrane topology and signal peptide prediction method.

            An inherent problem in transmembrane protein topology prediction and signal peptide prediction is the high similarity between the hydrophobic regions of a transmembrane helix and that of a signal peptide, leading to cross-reaction between the two types of predictions. To improve predictions further, it is therefore important to make a predictor that aims to discriminate between the two classes. In addition, topology information can be gained when successfully predicting a signal peptide leading a transmembrane protein since it dictates that the N terminus of the mature protein must be on the non-cytoplasmic side of the membrane. Here, we present Phobius, a combined transmembrane protein topology and signal peptide predictor. The predictor is based on a hidden Markov model (HMM) that models the different sequence regions of a signal peptide and the different regions of a transmembrane protein in a series of interconnected states. Training was done on a newly assembled and curated dataset. Compared to TMHMM and SignalP, errors coming from cross-prediction between transmembrane segments and signal peptides were reduced substantially by Phobius. False classifications of signal peptides were reduced from 26.1% to 3.9% and false classifications of transmembrane helices were reduced from 19.0% to 7.7%. Phobius was applied to the proteomes of Homo sapiens and Escherichia coli. Here we also noted a drastic reduction of false classifications compared to TMHMM/SignalP, suggesting that Phobius is well suited for whole-genome annotation of signal peptides and transmembrane regions. The method is available at as well as at
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              Advantages of combined transmembrane topology and signal peptide prediction—the Phobius web server

              When using conventional transmembrane topology and signal peptide predictors, such as TMHMM and SignalP, there is a substantial overlap between these two types of predictions. Applying these methods to five complete proteomes, we found that 30–65% of all predicted signal peptides and 25–35% of all predicted transmembrane topologies overlap. This impairs predictions of 5–10% of the proteome, hence this is an important issue in protein annotation. To address this problem, we previously designed a hidden Markov model, Phobius, that combines transmembrane topology and signal peptide predictions. The method makes an optimal choice between transmembrane segments and signal peptides, and also allows constrained and homology-enriched predictions. We here present a web interface (http://phobius.cgb.ki.se and http://phobius.binf.ku.dk) to access Phobius.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                December 2010
                December 2010
                16 December 2010
                : 6
                : 12
                Affiliations
                [1 ]Department of Biological Sciences, Clemson University, Clemson, South Carolina, United States of America
                [2 ]Department of Entomology, Max Planck Institute for Chemical Ecology, Jena, Germany
                University of Georgia, United States of America
                Author notes

                Conceived and designed the experiments: LJG YP DGH. Performed the experiments: LJG YP. Analyzed the data: LJG YP DGH. Contributed reagents/materials/analysis tools: HV. Wrote the paper: LJG DGH.

                Article
                10-PLGE-RA-4143R2
                10.1371/journal.pgen.1001248
                3002984
                21187898
                Gahan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 11
                Categories
                Research Article
                Biochemistry/Biomacromolecule-Ligand Interactions
                Biotechnology/Plant Biotechnology
                Cell Biology/Cellular Death and Stress Responses
                Genetics and Genomics/Animal Genetics

                Genetics

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