Identification of archaea in a mixed microbial community

The fundamental biological differences between archaea and bacteria domains have led to a consistent overlooked archaeal assessment in environmental microbial communities approaches. This is mainly because primers targeting the archaeal 16S rRNA genes also bind to bacterial 16S rRNA gene sequences, especially when bacterial relative abundance is greater than archaeal. Moreover, the quantification of archaeal diversity and community remains limited as the sequence coverage of archaea is usually low owing to the inability of available prokaryotic primers to amplify archaeal genes.
In this study, by selectively addressing sequencing marker genes for archaeal amplification and by developing our own mock community, the type and relative abundance of microorganisms can be identified. The objective is to have a synthetic microbial community which will provide us an internal reference for sequencing optimization for archaeal identification and for archaeal DNA extraction optimization.
To improve the identification and quantification of archaea, a selection of primer pair combinations that amplify 16S rRNA efficiently was carried out. This primer set targets the from V1-V3, to V4-V5 and V5-V6 regions of the 16S rRNA gene, to allow simultaneous sequencing of PCR products from the domains. Furthermore, in this MOCK there are species with different archaeal cell surface envelope, methanogenic archaea and co-existing, sequencing controversial and thick-walled bacteria, which will conform a suitable pool for the optimization of a methodological set-up for 16S rRNA amplicon sequencing approach of microbial communities.
The development of this newly designed MOCK will not only give us further insights for archaeal sequencing analysis in environmental samples. Moreover, this study will also give us an important knowledge for an historical overlooked archaeal diversity study providing a new instrument, currently not available, that can be used in every scientific archaeal research.