Literature DB >> 29198031

Metatranscriptomics analysis of cyanobacterial aggregates during cyanobacterial bloom period in Lake Taihu, China.

Zhenzhu Chen1,2, Junyi Zhang1,3, Rui Li1, Fei Tian1, Yanting Shen1, Xueying Xie1, Qinyu Ge4, Zuhong Lu1.   

Abstract

Molecular mechanism of interaction between the bloom-forming cyanobacterial species and attached microbios within cyanobacterial aggregates has not been elucidated yet and understanding of which would help to unravel the cyanobacteria bloom-forming mechanism. In this study, we profiled the metabolically active community by high-throughput metatranscriptome sequencing from cyanobacterial aggregates during cyanobacterial bloom period in Lake Taihu, China. A total of 308 million sequences were obtained using the HiSeq 2500 sequencing platform, which provided a great sequence coverage to carry out the in-depth taxonomic classification, functional classification, and metabolic pathway analysis of the cyanobacterial aggregates. The results show that bacteria dominated in cyanobacterial aggregates, accounting for more than 96.66% of total sequences. Microcystis was the most abundant genus, accounted for 26.80% of total assigned sequences at the genus level in cyanobacterial aggregates community; however, Proteobacteria (46.20%) was found to be as the most abundant active bacterial populations at the phylum level. More importantly, nitrogen, phosphonate, and phosphinate metabolism which associated with eutrophication were found in this study. Especially, the enzymes and organisms relating to denitrification and anammox of nitrogen metabolism, which reduced nitrogen concentration by reducing nitrate to nitrogen to inhibit the eutrophication, were first discovered in Lake Taihu during cyanobacterial bloom period. The present study provides a snapshot of metatranscriptome for cyanobacterial aggregates in Lake Taihu and demonstrates that cyanobacterial aggregates could play a key role in the nitrogen cycle in eutrophic water.

Entities:  

Keywords:  Cyanobacterial aggregates; Lake Taihu; Metatranscriptome; Microcystis; Next generation sequencing

Mesh:

Year:  2017        PMID: 29198031     DOI: 10.1007/s11356-017-0733-4

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


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