Viral metagenomics analysis and eight novel viral genomes identified from the Dushanzi mud volcanic soil in Xinjiang, China
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Viruses are the most abundant biological entities and play significant biological roles in marine system. However, little is known about their biodiversity in mud volcanic soil, which is salty and covered with emitting sludge. In this study, we report metagenomic analysis results of viral community composition and function from the Dushanzi mud volcanic soil (named NHS) in Xinjiang, China, and provide a comparative analysis with other environmental types.
Materials and methods
We utilized metagenomes to obtain the virus data and carried out viral automatic phylogenetic and functional analyses by the metagenomics analysis server. After assembling by metaSPAdes, scaffolds were rapidly identified and annotated with the PHAge Search Tool in order to identify new phage genomes.
Results and discussion
For the ssDNA viral group, Microviridae were the most abundant viral family, which were above 95%. Other plant viruses (Geminiviridae, Nanoviridae) and animal viruses (Circoviridae, Parvoviridae) were also detected. The majority of viral significant hits belonged to Siphoviridae (80.36%). Phages, which infect bacteria, were widely distributed in the soil sample. There were eight novel viral genomes identified in the NHS virome. The two longest scaffolds were annotated to Pseudomonas aeruginosa phage YMC11 and Acinetobacter baumannii phage LZ35, respectively. Other six new viral genomes were identified as Microviridae. Comparisons of NHS virome with other published viromes revealed that the type of ecosystem mainly drove the viral community structure.
This work provided detailed viral community composition and function information, which supplemented microbial community research on mud volcanoes. Importantly, we also identified eight complete viral genomes in the NHS virome which were obviously different from known viruses.
KeywordsMud volcanoes Soil Taxonomic compositions Virome
We would like to thank Associate Professor Phillip Michael Chalk (The University of Melbourne) for improving English expression.
This work was supported by the National Science Foundation of China (Grant Nos. 41571248 and 41771289).
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