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      Comprehensive genome analysis of a pangolin-associated Paraburkholderia fungorum provides new insights into its secretion systems and virulence

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          Abstract

          Background

          Paraburkholderia fungorum (P. fungorum) is a Gram-negative environmental species that has been commonly used as a beneficial microorganism in agriculture as an agent for biocontrol and bioremediation. Its use in agriculture is controversial as many people believe that it could harm human health; however, there is no clear evidence to support.

          Methodology

          The pangolin P. fungorum (pangolin Pf) genome has a genomic size of approximately 7.7 Mbps with N50 of 69,666 bps. Our study showed that pangolin Pf is a Paraburkholderia fungorum supported by evidence from the core genome SNP-based phylogenetic analysis and the ANI analysis. Functional analysis has shown that the presence of a considerably large number of genes related to stress response, virulence, disease, and defence. Interestingly, we identified different types of secretion systems in the genome of pangolin Pf, which are highly specialized and responsible for a bacterium’s response to its environment and in physiological processes such as survival, adhesion, and adaptation. The pangolin Pf also shared some common virulence genes with the known pathogenic member of the Burkholderiales. These genes play important roles in adhesion, motility, and invasion.

          Conclusion

          This study may provide better insights into the functions, secretion systems and virulence of this pangolin-associated bacterial strain. The addition of this genome sequence is also important for future comparative analysis and functional work of P. fungorum.

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          Most cited references72

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          IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets

          Abstract IslandViewer (http://www.pathogenomics.sfu.ca/islandviewer/) is a widely-used webserver for the prediction and interactive visualization of genomic islands (GIs, regions of probable horizontal origin) in bacterial and archaeal genomes. GIs disproportionately encode factors that enhance the adaptability and competitiveness of the microbe within a niche, including virulence factors and other medically or environmentally important adaptations. We report here the release of IslandViewer 4, with novel features to accommodate the needs of larger-scale microbial genomics analysis, while expanding GI predictions and improving its flexible visualization interface. A user management web interface as well as an HTTP API for batch analyses are now provided with a secured authentication to facilitate the submission of larger numbers of genomes and the retrieval of results. In addition, IslandViewer's integrated GI predictions from multiple methods have been improved and expanded by integrating the precise Islander method for pre-computed genomes, as well as an updated IslandPath-DIMOB for both pre-computed and user-supplied custom genome analysis. Finally, pre-computed predictions including virulence factors and antimicrobial resistance are now available for 6193 complete bacterial and archaeal strains publicly available in RefSeq. IslandViewer 4 provides key enhancements to facilitate the analysis of GIs and better understand their role in the evolution of successful environmental microbes and pathogens.
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            VFDB: a reference database for bacterial virulence factors

            Bacterial pathogens continue to impose a major threat to public health worldwide in the 21st century. Intensified studies on bacterial pathogenesis have greatly expanded our knowledge about the mechanisms of the disease processes at the molecular level over the last decades. To facilitate future research, it becomes necessary to form a database collectively presenting the virulence factors (VFs) of various medical significant bacterial pathogens. The aim of virulence factor database (VFDB) (http://www.mgc.ac.cn/VFs/) is to provide such a source for scientists to rapidly access to current knowledge about VFs from various bacterial pathogens. VFDB is comprehensive and user-friendly. One can search VFDB by browsing each genus or by typing keywords. Furthermore, a BLAST search tool against all known VF-related genes is also available. VFDB provides a unified gateway to store, search, retrieve and update information about VFs from various bacterial pathogens.
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              IslandViewer: an integrated interface for computational identification and visualization of genomic islands

              Summary: Genomic islands (clusters of genes of probable horizontal origin; GIs) play a critical role in medically important adaptations of bacteria. Recently, several computational methods have been developed to predict GIs that utilize either sequence composition bias or comparative genomics approaches. IslandViewer is a web accessible application that provides the first user-friendly interface for obtaining precomputed GI predictions, or predictions from user-inputted sequence, using the most accurate methods for genomic island prediction: IslandPick, IslandPath-DIMOB and SIGI-HMM. The graphical interface allows easy viewing and downloading of island data in multiple formats, at both the chromosome and gene level, for method-specific, or overlapping, GI predictions. Availability: The IslandViewer web service is available at http://www.pathogenomics.sfu.ca/islandviewer and the source code is freely available under the GNU GPL license. Contact: brinkman@sfu.ca
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                3 September 2020
                2020
                : 8
                : e9733
                Affiliations
                [1 ]Institute of Biological Sciences, Faculty of Science, Universiti Malaya , Kuala Lumpur, Malaysia
                [2 ]Genome Informatics Research Laboratory, Centre for Research in Biotechnology for Agriculture (CEBAR), High Impact Research Building, Universiti Malaya , Kuala Lumpur, Malaysia
                [3 ]Centre for Research in Biotechnology for Agriculture (CEBAR), Level 3, Research Management & Innovation Complex, Universiti Malaya , Copenhagen, Kuala Lumpur, Malaysia
                [4 ]College of Science and Technology, Wenzhou-Kean University , Wenzhou, Zhejiang Province, China
                [5 ]Current affiliation: The Novo Nordisk Foundation Center for Basic Metabolic Research, Human Genomics and Metagenomics in Metabolism, Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen, Denmark
                [6 ]Current affiliation: Cancer Science Institute of Singapore, National University of Singapore , Singapore
                Article
                9733
                10.7717/peerj.9733
                7474880
                32953261
                8d8fada4-dc4a-4084-9a6f-9947505204a3
                ©2020 Tan et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 7 April 2020
                : 25 July 2020
                Funding
                Funded by: Wenzhou-Kean University
                Award ID: The high-level talent recruitment programme for academic and research platform construction (Reference Number: 5000105)
                Funded by: UM High Impact Research (HIR)
                Award ID: UM.C/625/HIR/MOHE/CHAN-08
                Funded by: The Ministry of Higher Education of Malaysia
                Funded by: The Centre for Research in Biotechnology for Agriculture (CEBAR)
                Award ID: IRU-MRUN (RU023-2015)
                This work was funded by the high-level talent recruitment programme for academic and research platform construction (Reference Number: 5000105) from Wenzhou-Kean University and the UM High Impact Research (HIR) grant (Grant Number: UM.C/625/HIR/MOHE/CHAN-08) from the Ministry of Higher Education of Malaysia. Ka Yun Tan was partially supported by the Centre for Research in Biotechnology for Agriculture (CEBAR) grant IRU-MRUN (RU023-2015). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Bioinformatics
                Taxonomy

                secretion system,taxonomy,burkholderia,rast
                secretion system, taxonomy, burkholderia, rast

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