Distribution and diversity of eukaryotic microalgae in Kuwait waters assessed using 18S rRNA gene sequencing.

Abstract

The microbial communities play a crucial role in ecosystem functioning through interactions among individuals and taxonomic groups in a highly dynamic marine ecosystem. The structure and functioning of the microbial communities are often influenced by the changes in the surrounding environment. Monitoring the microbial diversity of the marine ecosystem helps to understand spatial patterns of microbial community and changes due to season, climate, and various drivers of biological diversity. Kuwait is characterized by an arid environment with a high degree of temperature variation during summer and winter. Our understanding of spatial distribution patterns of microbial communities, their diversity, and the influence of human activities on the degree of changes in the diversity of the microbial community in Kuwait territorial waters remain unclear. In this study, we employed 18S rRNA sequencing to explore marine microalgal community composition and dynamics in seawater samples collected from Kuwait waters over two seasonal cycles across six locations. A total of 448,184 sequences across 36 replicates corresponding to 12 samples from six stations were obtained. The quality-filtered sequences were clustered into 1,293 representative sequences, which were then classified into different eukaryotic taxa. This study reveals that the phytoplankton community in Kuwait waters is diverse and shows significant variations among different taxa during summer and winter. Dinoflagellates and diatoms were the most abundant season-dependent microalgae taxa in Kuwait waters. Alexandrium and Pyrophacus were abundant in summer, whereas Gonyaulax was abundant during the winter. The abundance of Coscinodiscus and Navicula, of the diatom genera, were also dependent upon both seasonal and possible anthropogenic factors. Our results demonstrate the effectiveness of a sequencing-based approach, which could be used to improve the accuracy of quantitative eukaryotic microbial community profiles.