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Genome-Wide Analysis of Type VI System Clusters and Effectors in Burkholderia Species

Overview of attention for article published in Plant Pathology Journal, February 2018
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Title
Genome-Wide Analysis of Type VI System Clusters and Effectors in <italic>Burkholderia</italic> Species
Published in
Plant Pathology Journal, February 2018
DOI 10.5423/ppj.ft.11.2017.0231
Pubmed ID
Authors

Thao Thi Nguyen, Hyun-Hee Lee, Inmyoung Park, Young-Su Seo

Abstract

Type VI secretion system (T6SS) has been discovered in a variety of gram-negative bacteria as a versatile weapon to stimulate the killing of eukaryotic cells or prokaryotic competitors. Type VI secretion effectors (T6SEs) are well known as key virulence factors for important pathogenic bacteria. In many Burkholderia species, T6SS has evolved as the most complicated secretion pathway with distinguished types to translocate diverse T6SEs, suggesting their essential roles in this genus. Here we attempted to detect and characterize T6SSs and potential T6SEs in target genomes of plant-associated and environmental Burkholderia species based on computational analyses. In total, 66 potential functional T6SS clusters were found in 30 target Burkholderia bacterial genomes, of which 33% possess three or four clusters. The core proteins in each cluster were specified and phylogenetic trees of three components (i.e., TssC, TssD, TssL) were constructed to elucidate the relationship among the identified T6SS clusters. Next, we identified 322 potential T6SEs in the target genomes based on homology searches and explored the important domains conserved in effector candidates. In addition, using the screening approach based on the profile hidden Markov model (pHMM) of T6SEs that possess markers for type VI effectors (MIX motif) (MIX T6SEs), 57 revealed proteins that were not included in training datasets were recognized as novel MIX T6SE candidates from the Burkholderia species. This approach could be useful to identify potential T6SEs from other bacterial genomes.

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The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 24%
Student > Bachelor 7 14%
Student > Master 6 12%
Student > Doctoral Student 3 6%
Professor > Associate Professor 2 4%
Other 3 6%
Unknown 17 34%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 26%
Biochemistry, Genetics and Molecular Biology 11 22%
Immunology and Microbiology 3 6%
Psychology 2 4%
Nursing and Health Professions 1 2%
Other 1 2%
Unknown 19 38%