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Microbiol Res. 2018 Dec;217:1-13. doi: 10.1016/j.micres.2018.08.015. Epub 2018 Aug 30.

Profiles of quorum sensing (QS)-related sequences in phycospheric microorganisms during a marine dinoflagellate bloom, as determined by a metagenomic approach.

Author information

1
Shenzhen Public Platform for Screening and Application of Marine Microbial Resources, The Graduate School at Shenzhen, Tsinghua University, Guangdong Province, Shenzhen, China.
2
The Division of Environment and Energy, Graduate School at Shenzhen, Peking University, Guangdong Province, Shenzhen, China.
3
Shenzhen Public Platform for Screening and Application of Marine Microbial Resources, The Graduate School at Shenzhen, Tsinghua University, Guangdong Province, Shenzhen, China. Electronic address: zhou.jin@sz.tsinghua.edu.cn.

Abstract

The complicated relationships among environmental microorganisms are regulated by quorum sensing (QS). Understanding QS-based signals could shed light on the interactions between microbial communities in certain environments. Although QS characteristics have been widely discussed, few studies have been conducted on the role of QS in phycospheric microorganisms. Here, we used metagenomics to examine the profile of AI-1 (AinS, HdtS, LuxI) and AI-2 (LuxS) autoinducers from a deeply sequenced microbial database, obtained from a complete dinoflagellate bloom. A total of 3001 putative AI-1 homologs and 130 AI-2 homologs were identified. The predominant member among the AI groups was HdtS. The abundance of HdtS, AinS, and LuxS increased as the bloom developed, whereas the abundance of LuxI showed the opposite trend. Phylogenetic analysis suggested that HdtS and LuxI synthase originated mainly from alpha-, beta-, and gamma-Proteobacteria, whereas AinS synthase originated solely from Vibrionales. In comparison to AI-1, the sequences related to AI-2 (LuxS) demonstrated a much wider taxonomic coverage. Some significant correlations were found between dominant species and QS signals. In addition to the QS, we also performed parallel analysis of the quorum quenching (QQ) sequences. In comparison to QS, the relative abundance of QQ signals was lower; however, an obvious frequency correlation was observed. These results suggested that QS and QQ signals co-participate in regulating microbial communities during an algal bloom. These data helped to reveal the characteristic behavior of algal symbiotic bacteria, and facilitated a better understanding of microbial dynamics during an algal bloom event from a chemical ecological perspective.

KEYWORDS:

Dinoflagellate bloom; Metagenomic; Microbial dynamic; Profile; Quorum sensing

PMID:
30384903
DOI:
10.1016/j.micres.2018.08.015
[Indexed for MEDLINE]

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