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. 2024 Jul 27;22(8):342.
doi: 10.3390/md22080342.

Long-Read Sequencing Unlocks New Insights into the Amphidinium carterae Microbiome

Miranda Judd  1 , Jens Wira  1 , Allen R Place  1 , Tsvetan Bachvaroff  1
Affiliations

Long-Read Sequencing Unlocks New Insights into the Amphidinium carterae Microbiome

Miranda Judd et al. Mar Drugs. .

Abstract

Dinoflagellates are one of the largest groups of marine microalgae and exhibit diverse trophic strategies. Some dinoflagellates can produce secondary metabolites that are known to be toxic, which can lead to ecologically harmful blooms. Amphidinium carterae is one species of dinoflagellate that produces toxic compounds and is used as a model for dinoflagellate studies. The impact of the microbiome on A. carterae growth and metabolite synthesis is not yet fully understood, nor is the impact of bacterial data on sequencing and assembly. An antibiotic cocktail was previously shown to eliminate 16S amplification from the dinoflagellate culture. Even with drastically reduced bacterial numbers during antibiotic treatment, bacterial sequences were still present. In this experiment, we used novel Nanopore long-read sequencing techniques on A. carterae cultures to assemble 15 full bacterial genomes ranging from 2.9 to 6.0 Mb and found that the use of antibiotics decreased the percentage of reads mapping back to bacteria. We also identified shifts in the microbiome composition and identified a potentially deleterious bacterial species arising in the absence of the antibiotic treatment. Multiple antibiotic resistance genes were identified, as well as evidence that the bacterial population does not contribute to toxic secondary metabolite synthesis.

Keywords: dinoflagellate; long-read sequencing; microbiome; secondary metabolites.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 3
Figure 3
Functional traits identified via CARD based on the KEGG database [34]. Specific pathway names for each row are listed in Supplemental Table S3.
Figure 1
Figure 1
Amphidinium carterae growth with and without antibiotics. (a) Growth curves of A. carterae cultures; (b) image of lysed A. carterae (red arrow) taken at 100×, and the presence of rod-shaped bacteria (blue arrow).
Figure 2
Figure 2
Bacterial populations with and without antibiotics. (a) Percent of reads and bases mapping back to bacterial genomes from both the antibiotic-free and antibiotic-treated cultures, aligned using minimap2. (b) Bacterial abundance based on read mapping in the antibiotic-free and antibiotic-treated cultures.
Figure 4
Figure 4
Secondary metabolites present in the bacterial genomes, identified by antiSMASH [35].
Figure 5
Figure 5
Antimicrobial resistance in assembled microbiome. (a) Antimicrobial resistance genes within each assembled bacterial genome (b) Specialty genes identified from the CARD database [36].
Figure 6
Figure 6
Antibiotic resistance genes’ protein structure predictions created by AlphaFold, unique to the assembled Roseovarius mucosus genome [37,38]. Confidence in structure ranged based on per-residue model confidence score (pLDDT) from dark blue (pLDDT > 90), light blue (90 > pLDDT > 70), yellow (70 > pLDDT > 50), to orange (pLDDT < 50).
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Grants and funding

This research was funded by the Vetlesen foundation and the IMET Angel Investor Program.

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