Identifying drivers of microbial community composition associated with aquatic primary producers: metagenomic analysis of cyanobacterial cultures. Issue 7 (10th July 2020)

• Record Type: Journal Article
• Authors: Green, David; Rad-Menendez, Cecilia; De Boever, Frederik
• Is Part Of: Access microbiology. Volume 2:Issue 7A(2020)
• Publication Date: 2020-07-10
• Subjects: Microbiology -- Periodicals; 579
• DOI: 10.1099/acmi.ac2020.po0815
• Languages: English
• ISSNs: 2516-8290

Abstract

Abstract : The energy derived from aquatic primary production is fundamental to driving Earth's life support systems – but they don't achieve all this by themselves. Heterotrophic bacteria found in the photic zones of aquatic environments have a fundamental role in this too. Our group's interest is in understanding how heterotrophs help autotrophs: who in these communities are important, and how and why they are important. Answering this is important in both natural and manmade environments so we can model these environments, and as appropriate, manipulate them, such as applying designer microbiomes to aid industrialisation of algal cultivation. Metagenomic analysis of 31 marine and freshwater cyanobacterial cultures from the Culture Collection of Algae & Protozoa resulted in assembly of >400 bacterial metagenomes (MAGs) with ca. 14 unique MAGs per culture. Community composition was clearly partitioned by salinity as a driver but collectively niche accounted for most community taxonomic variation. No universal core microbiome was identified, but taxonomic composition of marine cultures bore notable similarities to marine eukaryotic algal communities and to a natural cyanobacterial mat community found next to a northern Chilean geyser. Stable taxonomic associations imply that these taxa may have functional importance to their algal host. Functional analysis of the MAGs is underway and we will test whether the relative taxonomic variability contrasts with low functional variation between communities. If true, this implies that primary producers drive community assembly in a functionally predictable way, and that function, not taxonomy, is the more important parameter to understand.