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Obtaining Genome Sequences of Mutualistic Bacteria in Single Microcystis Colonies.

Jing Tu | Liang Chen | Shen Gao | Junyi Zhang | Changwei Bi | Yuhan Tao | Na Lu | Zuhong Lu
International journal of molecular sciences | 2019

Cells of Microcystis are associated with heterotrophic bacteria and organized in colonies in natural environment, which are basic elements in the mass occurrence of cyanobacterial species. Analyzing these colonies by using metagenomics is helpful to understand species composition and relationship. Meanwhile, the difference in population abundance among Microcystis colonies could be used to recover genome bins from metagenome assemblies. Herein, we designed a pipeline to obtain high-quality genomes of mutualistic bacteria from single natural Microcystis colonies. Single colonies were lysed, and then amplified by using multiple displacement amplification to overcome the DNA quantity limit. A two-step assembly was performed after sequencing and scaffolds were grouped into putative bins based on their differential-coverage among species. We analyzed six natural colonies of three prevailing Microcystis species from Lake Taihu. Clustering results proved that colonies of the same species were similar in the microbial community composition. Eight putative population genome bins with wide bacterial diversity and different GC content were identified based on coverage difference among colonies. At the phylum level, proteobacteria was the most abundant besides cyanobacteria. Six of the population bins were further refined into nearly complete genomes (completeness > 90%).

Pubmed ID: 31614621

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RefSeq (tool)

RRID:SCR_003496

Collection of curated, non-redundant genomic DNA, transcript RNA, and protein sequences produced by NCBI. Provides a reference for genome annotation, gene identification and characterization, mutation and polymorphism analysis, expression studies, and comparative analyses. Accessed through the Nucleotide and Protein databases.

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Hmmer (tool)

RRID:SCR_005305

Tool for searching sequence databases for homologs of protein sequences, and for making protein sequence alignments. It implements methods using probabilistic models called profile hidden Markov models (profile HMMs). Compared to BLAST, FASTA, and other sequence alignment and database search tools based on older scoring methodology, HMMER aims to be significantly more accurate and more able to detect remote homologs because of the strength of its underlying mathematical models. In the past, this strength came at significant computational expense, but in the new HMMER3 project, HMMER is now essentially as fast as BLAST.

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QIAGEN (tool)

RRID:SCR_008539

A commercial organization which provides assay technologies to isolate DNA, RNA, and proteins from any biological sample. Assay technologies are then used to make specific target biomolecules, such as the DNA of a specific virus, visible for subsequent analysis.

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Prodigal (tool)

RRID:SCR_011936

Software tool for protein coding gene prediction for prokaryotic genomes.

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