Species-level profiling of <i>Landoltia punctata</i> (duckweed) microbiome under nutrient stress using full-length 16S rRNA sequencing

Duckweed is a rapidly-growing aquatic plant utilized as food/feed and for wastewater remediation. It coexists with complex microbial communities that play crucial roles in its growth and capability for phytoremediation. In a previous study, microbiomes associated with four duckweed species (<i>Spirodela polyrhiza</i>, <i>Landoltia punctata</i>, <i>Lemna aequinoctialis</i>, and <i>Wolffia globosa</i>) grown under natural and nutrient-deficient conditions, were investigated using V3V4 16S rRNA sequencing. However, species-level classification was not achieved due to the partial 16S rRNA sequences obtained, restricting the selection of potential microbial species for further application. In this study, <i>L. punctata</i> samples from the previous work were investigated further by employing full-length 16S rRNA sequencing. A total of 31 predominant microbial species were identified. Under stress, the proportion of Proteobacteria increased significantly, along with potentially beneficial bacteria such as <i>Roseateles depolymerans</i>, <i>Pelomonas saccharophila</i>, <i>Acidovorax temperans</i>, <i>Ensifer adhaerens</i> and <i>Rhizobium straminoryzae</i>. Functional metagenomic predictions suggest that associated microbes adapt to stressors and may confer benefits to duckweed, including pathways related to host adhesion, biofilm formation, microbial growth modulation, and co-factors and vitamin biosynthesis. Furthermore, the study demonstrates both the advantages and limitations of full-length 16S rRNA amplicon sequencing. The findings provide more insight into <i>L. punctata</i> microbiomes at species-level, facilitating establishment of stable, beneficial microbial communities for duckweed applications. Ongoing investigations aim to isolate key microbial species from <i>L. punctata</i> and validate their roles through co-cultivation, along with establishing potential synthetic microbial communities based on the metagenomic findings.