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      Comparative Genomics of Bacillus thuringiensis Reveals a Path to Specialized Exploitation of Multiple Invertebrate Hosts

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          ABSTRACT

          Understanding the genetic basis of host shifts is a key genomic question for pathogen and parasite biology. The Bacillus cereus group, which encompasses Bacillus thuringiensis and Bacillus anthracis, contains pathogens that can infect insects, nematodes, and vertebrates. Since the target range of the essential virulence factors (Cry toxins) and many isolates is well known, this group presents a powerful system for investigating how pathogens can diversify and adapt to phylogenetically distant hosts. Specialization to exploit insects occurs at the level of the major clade and is associated with substantial changes in the core genome, and host switching between insect orders has occurred repeatedly within subclades. The transfer of plasmids with linked cry genes may account for much of the adaptation to particular insect orders, and network analysis implies that host specialization has produced strong associations between key toxin genes with similar targets. Analysis of the distribution of plasmid minireplicons shows that plasmids with orf156 and orf157, which carry genes encoding toxins against Lepidoptera or Diptera, were contained only by B. thuringiensis in the specialized insect clade (clade 2), indicating that tight genome/plasmid associations have been important in adaptation to invertebrate hosts. Moreover, the accumulation of multiple virulence factors on transposable elements suggests that cotransfer of diverse virulence factors is advantageous in terms of expanding the insecticidal spectrum, overcoming insect resistance, or through gains in pathogenicity via synergistic interactions between toxins.

          IMPORTANCE

          Population genomics have provided many new insights into the formation, evolution, and dynamics of bacterial pathogens of humans and other higher animals, but these pathogens usually have very narrow host ranges. As a pathogen of insects and nematodes, Bacillus thuringiensis, which produces toxins showing toxicity to many orders of insects and other invertebrates, can be used as a model to study the evolution of pathogens with wide host ranges. Phylogenomic analysis revealed that host specialization and switching occur at the level of the major clade and subclade, respectively. A toxin gene co-occurrence network indicates that multiple toxins with similar targets were accumulated by the same cell in the whole species. This accumulation may be one of the strategies that B. thuringiensis has used to fight against host resistance. This kind of formation and evolution of pathogens represents a different path used against multiple invertebrate hosts from that used against higher animals.

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          Most cited references53

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          Bacillus thuringiensis and its pesticidal crystal proteins.

          During the past decade the pesticidal bacterium Bacillus thuringiensis has been the subject of intensive research. These efforts have yielded considerable data about the complex relationships between the structure, mechanism of action, and genetics of the organism's pesticidal crystal proteins, and a coherent picture of these relationships is beginning to emerge. Other studies have focused on the ecological role of the B. thuringiensis crystal proteins, their performance in agricultural and other natural settings, and the evolution of resistance mechanisms in target pests. Armed with this knowledge base and with the tools of modern biotechnology, researchers are now reporting promising results in engineering more-useful toxins and formulations, in creating transgenic plants that express pesticidal activity, and in constructing integrated management strategies to insure that these products are utilized with maximum efficiency and benefit.
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            Hierarchical and Spatially Explicit Clustering of DNA Sequences with BAPS Software

            Phylogeographical analyses have become commonplace for a myriad of organisms with the advent of cheap DNA sequencing technologies. Bayesian model-based clustering is a powerful tool for detecting important patterns in such data and can be used to decipher even quite subtle signals of systematic differences in molecular variation. Here, we introduce two upgrades to the Bayesian Analysis of Population Structure (BAPS) software, which enable 1) spatially explicit modeling of variation in DNA sequences and 2) hierarchical clustering of DNA sequence data to reveal nested genetic population structures. We provide a direct interface to map the results from spatial clustering with Google Maps using the portal http://www.spatialepidemiology.net/ and illustrate this approach using sequence data from Borrelia burgdorferi. The usefulness of hierarchical clustering is demonstrated through an analysis of the metapopulation structure within a bacterial population experiencing a high level of local horizontal gene transfer. The tools that are introduced are freely available at http://www.helsinki.fi/bsg/software/BAPS/.
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              Quake: quality-aware detection and correction of sequencing errors

              We introduce Quake, a program to detect and correct errors in DNA sequencing reads. Using a maximum likelihood approach incorporating quality values and nucleotide specific miscall rates, Quake achieves the highest accuracy on realistically simulated reads. We further demonstrate substantial improvements in de novo assembly and SNP detection after using Quake. Quake can be used for any size project, including more than one billion human reads, and is freely available as open source software from http://www.cbcb.umd.edu/software/quake.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                mBio
                MBio
                mbio
                mbio
                mBio
                mBio
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2150-7511
                8 August 2017
                Jul-Aug 2017
                : 8
                : 4
                : e00822-17
                Affiliations
                [a ]State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
                [b ]College of Informatics, Huazhong Agricultural University, Wuhan, China
                [c ]College of Life and Environmental Science, University of Exeter, Penryn, United Kingdom
                The Sanger Institute
                Author notes
                Address correspondence to Ming Sun, m98sun@ 123456mail.hzau.edu.cn .
                Article
                mBio00822-17
                10.1128/mBio.00822-17
                5550751
                28790205
                6d0985a4-d96b-4c4c-ad3f-ec3acb9d7a25
                Copyright © 2017 Zheng et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 17 May 2017
                : 26 June 2017
                Page count
                supplementary-material: 7, Figures: 6, Tables: 0, Equations: 0, References: 76, Pages: 14, Words: 9252
                Funding
                Funded by: Chinese Fundamental Research Funds for the Central Universities
                Award ID: 2662015PY123
                Award ID: 2662017PY094
                Award Recipient : Ming Sun
                Funded by: National Key Research and Development Program of China
                Award ID: 2017YFD0201201
                Award Recipient : Ming Sun
                Funded by: China 948 Program of Ministry of Agriculture
                Award ID: 2016-X21
                Award Recipient : Ming Sun
                Funded by: Chinese Fundametal Research Funds for the Central Universities
                Award ID: 2662016QD039
                Award Recipient : Jinshui Zheng
                Funded by: National Natural Science Foundation of China (NSFC) https://doi.org/10.13039/501100001809
                Award ID: 31500003
                Award Recipient : Jinshui Zheng
                Funded by: National Natural Science Foundation of China (NSFC) https://doi.org/10.13039/501100001809
                Award ID: 31670085
                Award Recipient : Ming Sun
                Funded by: China Postdoctoral Science Foundation https://doi.org/10.13039/501100002858
                Award ID: 2015M580649
                Award ID: 2016T90700
                Award Recipient : Jinshui Zheng
                Categories
                Research Article
                Custom metadata
                July/August 2017

                Life sciences
                bacillus thuringiensis,host specialization,invertebrate pathogen,population genomics

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