Phylometagenomics of cycad coralloid roots reveals shared symbiotic signals.

Cycads are known to host symbiotic cyanobacteria, including Nostocales species, as well as other sympatric bacterial taxa within their specialized coralloid roots. Yet, it is unknown if these bacteria share a phylogenetic origin and/or common genomic functions that allow them to engage in facultative symbiosis with cycad roots. To address this, we obtained metagenomic sequences from 39 coralloid roots sampled from diverse cycad species and origins in Australia and Mexico. Culture-independent shotgun metagenomic sequencing was used to validate sub-community co-cultures as an efficient approach for functional and taxonomic analysis. Our metanalysis shows a host-independent microbiome core consisting of seven bacterial orders with high species diversity within the identified taxa. Moreover, we recovered 43 cyanobacterial metagenome-assembled genomes, and in addition to Nostoc spp., symbiotic cyanobacteria of the genus Aulosira were identified for the first time. Using this robust dataset, we used phylometagenomic analysis to reveal three monophyletic cyanobiont clades, two host-generalist and one cycad-specific that includes Aulosira spp. Although the symbiotic clades have independently arisen, they are enriched in certain functional genes, such as those related to secondary metabolism. Furthermore, the taxonomic composition of associated sympatric bacterial taxa remained constant. Our research quadruples the number of cycad cyanobiont genomes and provides a robust framework to decipher cyanobacterial symbioses, with the potential of improving our understanding of symbiotic communities. This study lays a solid foundation to harness cyanobionts for agriculture and bioprospection, and assist in conservation of critically endangered cycads.

Metagenomics Bioinformatic Pipeline.

Microbial communities' taxonomic and functional diversity has been broadly studied since sequencing technologies enabled faster and cheaper data obtainment. Nevertheless, the programming skills needed and the amount of software available may be overwhelming to someone trying to analyze these data. Here, we present a comprehensive and straightforward pipeline that takes shotgun metagenomics data through the needed steps to obtain valuable results. The raw data goes through a quality control process, metagenomic assembly, binning (the obtention of single genomes from a metagenome), taxonomic assignment, and taxonomic diversity analysis and visualization.