Microorganisms attached to particles have been shown to be different from free-living microbes and to display diverse metabolic activities. However, little is known about the ecotypes associated with particles and their substrate preference in anoxic marine waters. Here, we investigate the microbial community colonizing particles in the anoxic and sulfide-rich waters of the Black Sea. We incubated beads coated with different substrates in situ at 1000 and 2000 m depth. After 6 h, the particleattached microbes were dominated by Gamma-and Alpha-proteobacteria, and groups related to the phyla Latescibacteria, Bacteroidetes, Planctomycetes and Firmicutes, with substantial variation across the bead types, indicating that the attaching communities were selected by the substrate. Further laboratory incubations for 7 days suggested the presence of a community of highly specialized taxa. After incubation for 35 days, the microbial composition across all beads and depths was similar and primarily composed of putative sulfur cycling microbes. In addition to the major shared microbial groups, subdominant taxa on chitin and proteincoated beads were detected pointing to specialized microbial degraders. These results highlight the role of particles as sites for attachment and biofilm formation, while the composition of organic matter defined a secondary part of the microbial community.
To monitor the effect of nature restoration projects in North Sea ecosystems, accurate and intensive biodiversity assessments are vital. DNA based techniques and especially environmental DNA (eDNA) metabarcoding from seawater is becoming a powerful monitoring tool. However, current approaches are based on genetic target regions of <500 nucleotides, which offer limited taxonomic resolution. This study aims to develop and validate a long read nanopore sequencing method for eDNA that enables improved identification of fish species.We designed a universal primer pair targeting a 2kb region covering the 12S and 16S rRNA genes of fish mitochondria. eDNA was amplified and sequenced using the Oxford Nanopore MiniON. Sequence data was processed using the new pipeline Decona, and accurate consensus identities of above 99.9% were retrieved. The primer set efficiency was tested with eDNA from a 3.000.000 L zoo aquarium with 31 species of bony fish and elasmobranchs. Over 55% of the species present were identified on species level and over 75% on genus level. Next, our long read eDNA metabarcoding approach was applied to North Sea eDNA field samples collected at ship wreck sites, the Gemini Offshore Wind Farm, the Borkum Reef Grounds and a bare sand bottom. Here, location specific fish and vertebrate communities were obtained. Incomplete reference databases still form a major bottleneck in further developing high resolution long read metabarcoding. Yet, the method has great potential for rapid and accurate fish species monitoring in marine field studies.
Sequencing of long amplicons is one of the major benefits of Nanopore technologies, as it allows for reads much longer than Illumina. One of the major challenges for the analysis of these long Nanopore reads is the relatively high error rate. Sequencing errors are generally corrected by consensus generation and polishing. This is still a challenge for mixed samples such as metabarcoding environmental DNA, bulk DNA, mixed amplicon PCR’s and contaminated samples because sequence data would have to be clustered before consensus generation. To this end, we developed Decona (https://github.com/Saskia-Oosterbroek/decona), a command line tool that creates consensus sequences from mixed (metabarcoding) samples using a single command. Decona uses the CD-hit algorithm to cluster reads after demultiplexing (qcat) and filtering (NanoFilt). The sequences in each cluster are subsequently aligned (Minimap2), consensus sequences are generated (Racon) and finally polished (Medaka). Variant calling of the clusters (Medaka) is optional. With the integration of the BLAST+ application Decona does not only generate consensus sequences but also produces BLAST output if desired. The program can be used on a laptop computer making it suitable for use under field conditions. Amplicon data ranging from 300-7500 nucleotides was successfully processed by Decona, creating consensus sequences reaching over 99,9% read identity. This included fish datasets (environmental DNA from filtered water) from a curated aquarium, vertebrate datasets that were contaminated with human sequences and separating sponge sequences from their countless microbial symbionts. Decona considerably simplifies and speeds up post sequencing processes, providing consensus sequences and BLAST output through a single command. Classifying consensus sequences instead of raw sequences improves classification accuracy and drastically decreases the amount of sequences that need to be classified. Overall it is a user friendly option for researchers with limited knowledge of script based data processing.
To monitor the effect of nature restoration projects in North Sea ecosystems, accurate and intensive biodiversity assessments are vital. DNA based techniques and especially environmental DNA (eDNA) metabarcoding from seawater is becoming a powerful monitoring tool. However, current approaches are based on genetic target regions of <500 nucleotides, which offer limited taxonomic resolution. This study aims to develop and validate a long read nanopore sequencing method for eDNA that enables improved identification of fish species. We designed a universal primer pair targeting a 2kb region covering the 12S and 16S rRNA genes of fish mitochondria. eDNA was amplified and sequenced using the Oxford Nanopore MiniON. Sequence data was processed using the new pipeline Decona, and accurate consensus identities of above 99.9% were retrieved. The primer set efficiency was tested with eDNA from a 3.000.000 L zoo aquarium with 31 species of bony fish and elasmobranchs. Over 55% of the species present were identified on species level and over 75% on genus level. Next, our long read eDNA metabarcoding approach was applied to North Sea eDNA field samples collected at ship wreck sites, the Gemini Offshore Wind Farm, the Borkum Reef Grounds and a bare sand bottom. Here, location specific fish and vertebrate communities were obtained. Incomplete reference databases still form a major bottleneck in further developing high resolution long read metabarcoding. Yet, the method has great potential for rapid and accurate fish species monitoring in marine field studies.
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