Research Article |
Corresponding author: Danwei Huang ( huangdanwei@nus.edu.sg ) Academic editor: Thorsten Stoeck
© 2018 Yue Sze, Lilibeth N. Miranda, Tsai Min Sin, Danwei Huang.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Sze Y, Miranda LN, Sin TM, Huang D (2018) Characterising planktonic dinoflagellate diversity in Singapore using DNA metabarcoding. Metabarcoding and Metagenomics 2: e25136. https://doi.org/10.3897/mbmg.2.25136
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Dinoflagellates are traditionally identified morphologically using microscopy, which is a time-consuming and labour-intensive process. Hence, we explored DNA metabarcoding using high-throughput sequencing as a more efficient way to study planktonic dinoflagellate diversity in Singapore’s waters. From 29 minimally pre-sorted water samples collected at four locations in western Singapore, DNA was extracted, amplified and sequenced for a 313-bp fragment of the V4–V5 region in the 18S ribosomal RNA gene. Two sequencing runs generated 2,847,170 assembled paired-end reads, corresponding to 573,176 unique sequences. Sequences were clustered at 97% similarity and analysed with stringent thresholds (≥150 bp, ≥20 reads, ≥95% match to dinoflagellates), recovering 28 dinoflagellate taxa. Dinoflagellate diversity captured includes parasitic and symbiotic groups which are difficult to identify morphologically. Richness is similar between the inner and outer West Johor Strait, but variations in community structure are apparent, likely driven by environmental differences. None of the taxa detected in a recent phytoplankton bloom along the West Johor Strait have been recovered in our samples, suggesting that background communities are distinct from bloom communities. The voluminous data obtained in this study contribute baseline information for Singapore’s phytoplankton communities and prompt future research and monitoring to adopt the approach established here.
high-throughput sequencing, Johor Strait, molecular operational taxonomic unit, phytoplankton, Singapore Strait
Dinoflagellates (Alveolata: Dinophyceae) are a diverse and abundant group of unicellular protists found in both marine and freshwater environments. With more than 2,000 living species described (
In the marine environment, there are more than 1,500 species including both photosynthetic and non-photosynthetic types (
The most common and earliest method of observing phytoplankton is through light microscopy, which is time consuming, labour intensive and demands a high level of taxonomic expertise (
Molecular techniques exploit the genetic distinction between species to identify and quantify species and have played an integral role in our understanding of the systematic positions and evolutionary relationships amongst organisms (
Improved technologies for performing high-throughput sequencing have enabled multiplexed amplification products to be sequenced from numerous samples or from an environmental sample, in a method generally known as DNA metabarcoding, which is meeting the needs of many ecologists for rapid taxon identification (
In the marine environment, metabarcoding has been useful for studying both benthic and planktonic eukaryotic diversity (
The earliest studies of Singapore’s marine phytoplankton communities were carried out in the mid-1900s, focusing on the Singapore Strait (
There have been more than 20 positively identified species of dinoflagellates reported from Singapore’s waters, but those which are known in detail have been studied mainly because they are associated with harmful algal blooms (
While more techniques are being explored, high-throughput sequencing has yet to enter the mainstream of Singapore’s phytoplankton research, especially for the non-bloom baseline phytoplankton communities. Hence, the aim of this study is to take a metabarcoding approach to characterise the dinoflagellate communities at four sites along the western coast of Singapore (Fig.
A total of 29 plankton samples were collected between September and December 2015 at four sites in western Singapore (Fig.
Collections were carried out using a 15-μm-mesh plankton net hauled vertically from 5 m depth to the water surface. From each haul, the volume of water collected was standardised using a 50-ml measuring cylinder and temporarily transferred to a plastic bottle. Each sample was filtered through an 8-µm cellulose filter paper (Whatman, Sigma-Aldrich), which was immediately wrapped in sterilised aluminium foil, snap frozen in liquid nitrogen and stored at -30 °C prior to DNA extraction.
Each filter paper was cut into two and placed in separate 1.5-ml tubes for DNA extraction using the standard CTAB (cetyltrimethylammonium bromide) and phenol-chloroform protocol (
A 313-bp, V4-V5 region of the 18S rRNA locus was amplified using newly-designed forward primer, REL18S1F (5’– GTT GCG GTT AAA AAG CTC GTA GTT GGA–3’) and reverse primer, REL18S1R (5’–AAC AAA TCC AAG AAT TTC ACC TCT GAC–3’), which is the reverse complement of the published Dino18SF3 designed specifically for dinoflagellates (
Three PCR replicates were carried out for each sample with a 25-μl reaction mixture containing 2.5 μl 10× reaction buffer, 2.0 μl dNTPs, 1.0 μl of 10μM forward and reverse primers, 0.2 μl Bioready rTaq (Bulldog Bio), 2 μl DNA diluted 5× or 10× and 16.3 μl water. For each unique primer combination, a negative control (without DNA) was also prepared. In other words, every PCR for an actual sample was accompanied by a negative control using the same pair of barcoded primers. During the analyses, MOTUs appearing in the negative controls post-filtering would be removed from their corresponding samples. The PCR protocol comprised 1 min of initial denaturation at 94 °C, followed by 35 cycles of 45 s at 94 °C, 45 s at 53 °C and 1 min at 72 °C, ending with 3 min at 72 °C. Amplified products were quantified using the Qubit dsDNA BR Assay Kit on a Qubit 3 Fluorometer (Thermo Fisher Scientific) in order to pool approximately equal amount of PCR product for each tagged amplicon. Purification of the mixed products was performed using SureClean Plus (Bioline) following the manufacturer’s protocol.
The pooled PCR products, including all negative controls, were split into two for Illumina DNA library preparation and paired-end sequencing with the Illumina MiSeq System. Approximately half of a sequencing run was targeted for each library—the first run generated read lengths of 2× 250 bp (MiSeq Reagent Kit v2), while the second 2× 300 bp (MiSeq Reagent Kit v3).
Assembly of paired-end reads was performed using Paired-End reAd mergeR (PEAR) version 0.9.6 (
The assembled reads were analysed in OBITools version 1.2.0 (
Sequences with at least 20 reads were clustered into molecular operational taxonomic units (MOTUs) with USEARCH version 8.1.1861 (
We compared dinoflagellate MOTU identities across the PCR triplicates and only retained those that met the above criteria in at least two replicates. MOTUs appearing in the negative controls were to be removed from their corresponding sample set if they met the same criteria. Retained sequences were combined first according to their sample and then site, noting their respective number of reads for each MOTU. Sequences from all samples were combined to determine the total number of unique dinoflagellate MOTUs amongst all samples.
Phylogenetic analyses were carried out to determine relationships amongst the MOTUs and previously sequenced taxa. Rhodophytes Rhodella violacea (Kornmann) Wehrmeyer (GenBank accession AF168624) and Bangia atropurpurea (Mertens ex Roth) C.Agardh (AF169339) were selected as outgroups. Taxa analysed in
The two Illumina MiSeq sequencing runs produced 2,847,170 assembled paired-end reads corresponding to 573,176 unique sequences. Further error pruning, sequence filtering and chimera removal further reduced the number of unique sequences to 268. After clustering the sequences using a 97% similarity threshold, 133 MOTUs were recovered. Filtering based on ≥95% sequence similarity to GenBank dinoflagellate sequences resulted in 28 unique MOTUs remaining (Table
The phylogenetic analyses revealed deep relationships that were generally inconsistent amongst NJ, ML and Bayesian reconstructions, but these were poorly supported across all analyses. There were no topological conflicts that were supported by any of the analyses, so we discuss the well-supported nodes using the NJ tree (Fig.
OTU10, OTU37 and OTU61 showed no sequence similarity to any known species but exhibited high similarity to a limited set of ‘uncultured dinoflagellates’ (Table
Neighbour-joining (NJ) tree showing 18S rRNA sequence relationships amongst dinoflagellates in Singapore (bold) and from GenBank. The 28 molecular operational taxonomic units detected in this study are denoted by prefix ‘OTU’. Dinoflagellate orders are represented by coloured branches. Bootstrap supports based on NJ and maximum likelihood (ML) methods (≥50), as well as Bayesian posterior probabilities (≥0.8) are shown as circles at the nodes.
Some MOTUs could be placed in a likely taxon, such as OTU20 in Gymnodinium and OTU129 in Prorocentrum, as they had high sequence similarity with and were nested within known taxa. There were also MOTUs exhibiting exact sequence matches to specific dinoflagellate species, an indication that such species were already known. These were represented by zero branch length difference between the MOTU and the known species, such as OTU23 with Amphidinium klebsii, OTU73 with Alexandrium cohorticula and OTU81 with Gyrodinium instriatum.
None of the samples recovered bloom-forming dinoflagellates such as Karlodinium and Takayama, which were detected in abundance during a recent phytoplankton bloom along the WJS id="ABBRID0ENRTY" in February 2014 (
The two most widespread MOTUs were OTU1 (identical sequence with G. fusiforme) and OTU20 (uncultured dinoflagellate). The former was present at both WJS sites and Jurong Island, while the latter was detected at both WJS sites and St John’s Island (Table
Nearly half of the MOTUs (13 of 28) were detected at inner and outer WJS each. There was an overlap of four MOTUs, including the abundant OTU1 (G. fusiforme), between the two WJS sites. Fewer MOTUs were found at Jurong Island (6 of 28) and St John’s Island (8 of 28). Two-thirds of the former’s MOTUs were unique to Jurong Island, while most of St John’s Island’s MOTUs (6 of 8) were found at WJS. Jurong Island and St John’s Island were sampled only at one time point, so results ought to be viewed with caution. At WJS, the highest MOTU richness was observed during October 2015 (Fig.
Number of dinoflagellate molecular operational taxonomic units (MOTUs) recovered at each of four sites, inner West Johor Strait (Inner WJS, red), outer West Johor Strait (Outer WJS, orange), Jurong Island (JI, green) and St John’s Island (SJI, blue), as well as the month of sampling in 2015.
Molecular operational taxonomic units of dinoflagellates recovered from four sites along the western coast of Singapore, with information about their closest GenBank matches and sequencing read counts at each site and sampling month in 2015.
MOTU | GenBank accession number | GenBank closest match | Identity | Inner West Johor Strait | Outer West Johor Strait | Jurong Island | St John’s Island | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Sep | Oct | Nov | Dec | Sep | Oct | Nov | Dec | ||||||
OTU1 | MH234223 |
AB120002 Gyrodinium fusiforme ( |
100.0 | 367351 | 167408 | 357281 | 226843 | 147 | 4302 | 688 | 185 | 96020 | |
OTU10 | MH234224 |
GU819712 Uncultured dinoflagellate ( |
100.0 | 1036 | 476 | 6114 | 320 | 1268 | |||||
OTU11 | MH234225 |
AB827556 Uncultured dinoflagellate ( |
97.7 | 526 | 1315 | ||||||||
OTU12 | MH234226 |
KC488405 Uncultured dinoflagellate ( |
98.5 | 141 | 4347 | 99 | |||||||
OTU16 | MH234227 |
AJ968729 Paulsenella vonstoschii ( |
100.0 | 4435 | |||||||||
OTU20 | MH234228 | FJ914425 Uncultured dinoflagellate | 100.0 | 395 | 4362 | 139 | 502 | ||||||
OTU23 | MH234229 | EU046335 Amphidinium klebsii | 100.0 | 691 | 1968 | ||||||||
OTU31 | MH234230 | FR865625 Gonyaulax spinifera | 100.0 | 1415 | |||||||||
OTU37 | MH234231 |
GU819660 Uncultured dinoflagellate ( |
100.0 | 813 | |||||||||
OTU38 | MH234232 |
AB181899 Protoperidinium pallidum ( |
95.4 | 561 | |||||||||
OTU45 | MH234233 |
EU780628 Uncultured eukaryote ( |
99.6 | 257 | 113 | ||||||||
OTU48 | MH234234 | FJ914426 Uncultured dinoflagellate | 98.5 | 619 | |||||||||
OTU51 | MH234235 |
FJ467492 Warnowia sp. ( |
100.0 | 32 | |||||||||
OTU58 | MH234236 |
AB694525 Uncultured dinoflagellate ( |
99.2 | 147 | 77 | ||||||||
OTU61 | MH234237 |
GU820302 Uncultured dinoflagellate ( |
100.0 | 162 | 23 | ||||||||
OTU64 | MH234238 |
AB120002 Gyrodinium fusiforme ( |
95.9 | 503 | |||||||||
OTU72 | MH234239 | AJ276699 Ceratium furca | 99.6 | 145 | 48 | ||||||||
OTU73 | MH234240 |
AF113935 Alexandrium cohorticula ( |
100.0 | 130 | |||||||||
OTU81 | MH234241 | AY721981 Gyrodinium instriatum | 100.0 | 36 | |||||||||
OTU96 | MH234242 |
FN598427 Uncultured dinoflagellate ( |
100.0 | 21 | |||||||||
OTU97 | MH234243 |
GU819784 Uncultured dinoflagellate ( |
99.6 | 21 | 21 | ||||||||
OTU98 | MH234244 |
FJ823465 Uncultured Symbiodinium ( |
100.0 | 41 | |||||||||
OTU102 | MH234245 |
AB827518 Uncultured dinoflagellate ( |
97.7 | 22 | |||||||||
OTU107 | MH234246 |
FJ467492 Warnowia sp. ( |
98.1 | 466 | |||||||||
OTU110 | MH234247 |
AB120002 Gyrodinium fusiforme ( |
98.8 | 21 | |||||||||
OTU123 | MH234248 |
AB120002 Gyrodinium fusiforme ( |
96.5 | 380 | |||||||||
OTU127 | MH234249 |
AB120002 Gyrodinium fusiforme ( |
98.0 | 34 | 62 | ||||||||
OTU129 | MH234250 |
EF492510 Prorocentrum mexicanum ( |
100.0 | 147 |
The two Illumina MiSeq sequencing runs generated a large number of reads that likely represent the majority of dinoflagellate individuals captured on the sample filters. Overall, the use of DNA metabarcoding on minimally sorted water samples has recovered a greater diversity of dinoflagellates in Singapore than a previous study that sequenced clone isolates amplified from water samples at comparable sites (
After retaining sequences with ≥95% similarity to GenBank dinoflagellate sequences, only 28 dinoflagellate MOTUs have been detected. It is worth noting that the extent of how well represented 18S rRNA dinoflagellate sequences are in GenBank varies amongst genera. Sequences from the genus Alexandrium are most abundant on GenBank, with approximately 500 available. This is followed by Prorocentrum with 97 sequences retrieved; all other genera are represented by fewer sequences, with some having only one sequence available. Despite having the largest collection of published 18S rRNA sequences available, sequencing effort for dinoflagellates is highly skewed amongst genera. The majority of MOTUs, not assigned to dinoflagellates, indicate that the primers which have been designed for dinoflagellates also capture other organisms. Our database searches have indeed recovered several diatoms amongst other eukaryotes. The 18S region amplified falls within the V4–V5 region that is commonly used to broadly amplify eukaryotic 18S rDNA using universal primers (
As with the previous study in Singapore by
A symbiotic dinoflagellate of the genus Symbiodinium (OTU98) has been detected at inner WJS in December 2015. That this taxon is not more widespread and even absent in samples from the reef environment of St John’s Island is surprising because of its ubiquity and importance as endosymbionts of scleractinian corals (zooxanthellae;
By far, the most read-abundant MOTU is OTU1, which has a sequence identical to Gyrodinium fusiforme. While taxon assignments based on the 18S rRNA gene may not be precise, this species is known to be widespread and has been recorded in Indonesia and the Malacca Strait (
Contrary to the hypothesis that mixing between the inner and outer WJS homogenises the communities along the Strait, considerable differences have been found between the two sampling stations (Fig.
The primary goal of all high-throughput sequencing of amplified markers is to recover accurate MOTU sequences and richness estimates from the voluminous sequence data (
The 18S rRNA is a commonly-used and well-characterised genetic marker with a highly conserved function across all living cells. It comprises nine hypervariable regions (V1–V9) (Ki 2012;
Downstream of the amplification and sequencing steps, we have attempted to account for possible errors associated with high-throughput sequencing and DNA metabarcoding. These measures include the omission of sequences <150 bp represented by fewer than 20 reads or those not matching at least 95% to published dinoflagellate sequences. Consequently, despite high read recovery, there was low read usability, with only 268 unique sequences that were eventually used for analysis. We also retained unique sequences only if they were detected in two of three PCR replicates and would potentially remove signals appearing in the negative controls. While high-throughput sequencing studies such as this are efficient in producing large amounts of sequence data, it is important to note that there are known issues concerning Illumina-based DNA metabarcoding, including primer tag jumps, contamination and false positive detections (
Despite the stringent thresholds, we have recovered a higher diversity of planktonic dinoflagellates—28 MOTUs—than previously reported for Singapore waters (
We thank staff and crew of the Ecological Monitoring, Informatics and Dynamics Research Group (Tropical Marine Science Institute) and R/V Galaxea (St John’s Island National Marine Lab), for assisting with field research; members of the Reef Ecology Laboratory for support and assistance, especially Ywee Chieh Tay for advice on data analyses; and Céline Mercier, for providing assistance regarding usage of OBITools. This study was funded by the National Research Foundation, Prime Minister’s Office, Singapore under its Marine Science R&D Programme (MSRDP-P03).