Temporal Variability of Virioplankton during a Gymnodinium catenatum Algal Bloom

Abstract

Viruses are key biogeochemical engines in the regulation of the dynamics of phytoplankton. However, there has been little research on viral communities in relation to algal blooms. Using the virMine tool, we analyzed viral information from metagenomic data of field dinoflagellate (Gymnodinium catenatum) blooms at different stages. Species identification indicated that phages were the main species. Unifrac analysis showed clear temporal patterns in virioplankton dynamics. The viral community was dominated by Siphoviridae, Podoviridae, and Myoviridae throughout the whole bloom cycle. However, some changes were observed at different phases of the bloom; the relatively abundant Siphoviridae and Myoviridae dominated at pre-bloom and peak bloom stages, while at the post-bloom stage, the members of Phycodnaviridae and Microviridae were more abundant. Temperature and nutrients were the main contributors to the dynamic structure of the viral community. Some obvious correlations were found between dominant viral species and host biomass. Functional analysis indicated some functional genes had dramatic response in algal-associated viral assemblages, especially the CAZyme encoding genes. This work expands the existing knowledge of algal-associated viruses by characterizing viral composition and function across a complete algal bloom cycle. Our data provide supporting evidence that viruses participate in dinoflagellate bloom dynamics under natural conditions.

Prophage Genomics and Ecology in the Family Rhodobacteraceae

“…To test if the putative prophages identified were also observed in association with phytoplankton, we mapped metagenome reads from a dinoflagellate bloom against the 44 high- and medium-quality prophages identified here. The metagenomes were obtained from a previous study of a Gymnodinium catenatum dinoflagellate bloom in Shenzhen, China [ 78 , 79 ]. Metagenomes were generated by filtering water samples through a 10 μm filter followed by flocculation, 0.22 μm filtration, DNA extraction of the filters, and sequencing on an Illumina HiSeq 2000 (San Diego, CA, USA) [ 78 ].…”

“…The metagenomes were obtained from a previous study of a Gymnodinium catenatum dinoflagellate bloom in Shenzhen, China [ 78 , 79 ]. Metagenomes were generated by filtering water samples through a 10 μm filter followed by flocculation, 0.22 μm filtration, DNA extraction of the filters, and sequencing on an Illumina HiSeq 2000 (San Diego, CA, USA) [ 78 ]. Raw metagenome reads in FASTQ format were retrieved from the NCBI Sequence Read Archive (SRA) using the SRA toolkit (Accessed 16 December 2020).…”

“…Raw metagenome reads in FASTQ format were retrieved from the NCBI Sequence Read Archive (SRA) using the SRA toolkit (Accessed 16 December 2020). These viromes are YT1, YT3 (pre-bloom), YT4, YT5, YT6 (bloom), and YT8, YT19, and YT11 (post-bloom) [ 78 ]. The metagenomes were filtered in BBDuk, BBTools version 38.86 using quality trimming of both right and left sides (qtrim = rl), (trimq = 30), adapter trimming of both sides with a k-mer size of 23 (ktrim = l, ktrim = r, k = 23, mink = 11), a hamming distance of one (hdist = 1), and tpe and tpo parameters.…”

“…The circular genomes are represented linearly, with the direction of the arrow representing the direction of transcription. Figure S3: The abundance of high and medium quality prophages mapped at 80 % identity to eight G. catenatum algal bloom metagenomes from Du et al, and Huang et al [ 78 , 79 ]. Phages with greater than ten reads mapped in a metagenome are represented here.…”

Herbicide control of the invasive Amur honeysuckle (Lonicera maackii) does not alter soil microbial communities or activity

“…Both of these scenarios result in direct herbicide application onto soils (but see Frank, Nakatsu, et al., 2018). Of these studies, there are varied soil responses, including reduced microbial diversity and abundance of ammonia oxidation genes when exposed to mesotrione (Du et al., 2020), reduction of dehydrogenase activity with glufosinate exposure (Pampulha et al., 2007) and broad reduction in organic carbon for several herbicide classes (Lupwayi et al., 2004). However, a general consensus is that glyphosate formulations do little to impact soil microbial communities or functionality (Guijarro et al., 2018; Kepler et al., 2020; Weaver et al., 2007).…”