Received: 11 June 2023

Accepted: 4 October 2023

DOI: 10.1111/1462-2920.16524

BRIEF REPORTDNA metabarcoding focused on difficult-to-culture protists:
An effective approach to clarify biological interactions
Yasuhide Nakamura 1,2
Atsushi Yamaguchi 5 |1Estuary Research Center, Shimane
University, Matsue, Japan2

Department of Botany, National Museum of
Nature and Science, Tsukuba, Japan3
Department of Biological Science, Graduate
School of Science, The University of Tokyo,
Tokyo, Japan
4
Manazuru Marine Center for Environmental
Research and Education, Yokohama National
University, Manazuru, Japan
5
Faculty of Fisheries Sciences, Hokkaido
University, Hakodate, Japan
6
Fisheries Resources Institute, Fisheries
Research and Education Agency, Yokohama,Japan
7Center for Molecular Biodiversity Research,
National Museum of Nature and Science,
Tsukuba, Japan
Correspondence
Yasuhide Nakamura, Estuary ResearchCenter, Shimane University, 1060
Nishikawatsu-cho, Matsue 690-8504, Japan.
Email: jasnakamura@gmail.com
Funding information
Fisheries Research and Education Agency ofJapan; Japan Society for the Promotion of
Science, Grant/Award Number: JP20K15589| Hiryori Itagaki 3 | Akihiro Tuji 2 | Shinji Shimode 4 |Kiyotaka Hidaka 6 | Eri Ogiso-Tanaka 7

Abstract
DNA metabarcoding on a single organism is a promising approach to clarify
the biological interactions (e.g., predator–prey relationships and symbiosis,
including parasitism) of difficult-to-culture protists. To evaluate the effectiveness of this method, Radiolaria and Phaeodaria, which are ecologicallyimportant protistan groups, were chosen as target taxa. DNA metabarcoding on a single organism focused on the V9 region of the 18S rRNA generevealed potential symbionts, parasites and food sources of Radiolaria andPhaeodaria. Previously reported hosts and symbionts (parasites) weredetected, and newly recognized combinations were also identified. The contained organisms largely differed between Radiolaria and Phaeodaria. In
Radiolaria, members of the same order tended to contain similar organisms,
and the taxonomic composition of possible symbionts, parasites, and foodsources was fixed at the species level. Members of the same phaeodarianfamily, however, did not contain similar organisms, and body part (i.e., thecentral capsule or the phaeodium) was the most important factor that
divided the taxonomic composition of detected organisms, implying that the
selection of appropriate body part is important when trying to ascertain contained organisms, even for unicellular zooplankton. Our results show that
DNA metabarcoding on a single organism is effective in revealing the biological interactions of difficult-to-culture protists.

INTRODUCTION
The biological interactions (e.g., competition, predator–
prey relationships and symbiosis, including parasitism)of protists have been widely studied, mainly focusingon ‘culturable’ species in the domain of microbiology or
protistology. However, many protists in natural environments cannot be successfully cultured under artificial
conditions, and these ‘difficult-to-culture’ protists arereported to play important roles in natural environments(Biard et al., 2016; Ikenoue et al., 2019; Sogawa
et al., 2022).
DNA metabarcoding is an effective approach toclarify biological interactions of aquatic organisms, andthe taxonomic composition (species diversity) ofenvironmental samples can be thoroughly clarified byusing this technique. For example, DNA metabarcoding
has been used to clarify the food sources of crustaceans (Cleary et al., 2012, 2015). However, because
multicellular organisms contain numerous cells, a
blocking polymerase chain reaction (PCR) with Peptide
Nucleic Acid (PNA) must also be performed to reducethe detection of host’s DNA (Nakamura, Tuji,et al., 2020), which creates a bottleneck when trying toanalyse numerous species at the same time. Symbionts, parasites and food sources, however, are moreeasily detected by DNA metabarcoding focused on unicellular eukaryotes (i.e., protists) because they have arelatively small amount of DNA. The DNA sequence ofdifficult-to-culture protists has generally been difficult to© 2023 Applied Microbiology International and John Wiley & Sons Ltd.
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clarify because of their small amount of DNA and thehigh risk of contamination. However, a single-cell DNA
analysis method for protists was established, and the
DNA sequences of numerous protistan groups havebeen revealed during the last decade (Decelle, Suzuki,
et al., 2012; Nakamura et al., 2021; Nakamura, Sandin,
et al., 2020; Pawlowski et al., 2013; Sandin et al., 2019,2021). For these reasons, the combination of single-cell
DNA analysis and DNA metabarcoding should be aneffective means to clarify the biological interactions ofdifficult-to-culture protists and other organisms.
Radiolaria and Phaeodaria are difficult-to-culture
but ecologically important protists. Radiolaria contain6 orders and more than 1100 species (Nakamura
et al., 2021; Suzuki & Aita, 2011), while Phaeodaria
currently includes 18 families and about 300 species(Nakamura et al., 2015; Nakamura & Suzuki, 2015).
These two groups are heterotrophic or mixotrophic unicellular zooplankton, most of which have siliceous skeletons. They are thought to be key groups inecosystems and material cycles in the world ocean
because their high abundance and large contribution tomaterial cycles have often been reported in the past
decade (Biard & Ohman, 2020; Nakamura et al., 2013;
Sogawa et al., 2022). The symbiosis between these
two groups and other eukaryotic organisms has also
attracted attention recently. Radiolaria and Phaeodaria
are reported to have a symbiotic relationship with crustaceans, which is called the ‘Rhizarian rider’ phenomenon (Nakamura, Minemizu, & Saito, 2019; Saito
et al., 2022). Radiolaria are also known for their symbiosis with algae, and their symbiotic algae have been
analysed with different approaches, such as microscopic observation (Anderson, 1983), DNA barcoding(Decelle, Siano, et al., 2012) and fluorescence pattern(Zhang et al., 2018). Their symbiosis is thought to becomplicated because some Radiolaria can have morethan two symbiotic algae (Decelle, Siano, et al., 2012).
Closely related species have also been reported tohave symbiotic algae of totally different origins. For
example, Dictyocoryne profunda (Radiolaria) has acyanobacterium (symbiotic alga) (Yuasa et al., 2012),
whereas D. truncata (Radiolaria) possesses a haptophyte (symbiotic alga) (Yuasa et al., 2019). Although agreat deal of knowledge has been accumulated during
the past 150 years (Table S1), the taxonomic composition of radiolarian symbiotic algae has never been thoroughly clarified. Compared with the case of Radiolaria,
knowledge about the symbiosis of Phaeodaria is limited, with less than 10 reports currently available(Table S1).
Radiolaria and Phaeodaria have similar cell size,
body structure and ecological niches. This study therefore focused on these two groups as the target organisms and to show the first big picture, attempted to
explore the interactions between Radiolaria/Phaeodaria
and other eukaryotic organisms. DNA metabarcoding

on a single organism was applied to detect potential
symbionts, parasites and food sources, to show a comprehensive big picture of the biological interactions ofthese difficult-to-culture protists.

EXPERIMENTAL PROCEDURES
Field sampling, microscopy and treatment
Plankton sampling was conducted in 2012–2019 at
22 stations located in seven marine areas of the Northern Hemisphere (Figure 1). Radiolaria and Phaeodaria
were manually isolated from the bulk plankton samples
under a stereomicroscope or inverted microscope(e.g., TMS, Nikon, Japan). The isolated individuals
were then photographed with a digital camera(e.g., Nikon 1 V3, Nikon, Japan) attached to the microscopes, and individuals were identified based on theirmorphological characteristics. The identified specimens
were then carefully observed to confirm that no otherorganisms were attached to their surface. After theobservation, the specimens were individually preservedin tubes filled with approximately 2.0 mL of 99.9% ethanol and stored at 4 C. Among these ethanol-preserved
specimens, Orodaria and solitary Collodaria were dissected with a sterilized scalpel under a stereomicroscope, and the central area containing nuclei was
isolated. Large Phaeodaria (larger than ca. 400 μm in
diameter) were also dissected, and their ‘central capsule’ (the protoplasmic body, including the nuclei) and‘phaeodium’ (mass of aggregated brown or yellowish
particles) were isolated to separately perform further
analyses.
After the DNA extraction (described later), some ofthe specimens, which have solid siliceous skeletons,
were observed with a scanning electron microscope(SEM, JSM-6390LV with LaB6 gun, JEOL, Japan). The
conditions and parameters were the same as thosedescribed in Nakamura et al. (2016).

DNA metabarcoding and cluster analysis
Each isolated specimen (whole cell, central capsule, or
phaeodium) was individually put into 100 μL of
guanidine-containing extraction buffer (GITC buffer)(Decelle, Suzuki, et al., 2012), and the DNA wasextracted according to the method described in Nakamura et al. (2015). Three tubes filled with ethanol werealso analysed as negative controls in the subsequent
experiment. The DNA extraction was conducted in a
specialized and sterilized laboratory.
Hitherto reported symbionts, parasites and preyorganisms of Radiolaria and Phaeodaria were mainly
eukaryotes (Table S1), and to compare with these previous studies, the eukaryote-specific primers were14622920, 2023, 12, Downloaded from https://ami-journals.onlinelibrary.wiley.com/doi/10.1111/1462-2920.16524 by Hokkaido University, Wiley Online Library on [19/12/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License

DNA METABARCODING FOCUSED ON DIFFICULT-TO-CULTURE PROTISTS

NAKAMURA ET AL.

F I G U R E 1 Location of the plankton sampling stations in 2012–2019. Pink dots indicate the sampling stations. The detailed information oneach station is shown in Table S2.

chosen in this study. The V9 hypervariable region of
approximately 315 base pairs in the 18S rRNA gene
was amplified by PCR following the procedure in Toju
(2016). The first fusion primers were designed by combining P5 or P7 adapters, a series of ‘N’ andV9-specific sequences for eukaryotes: 1389F (50 TTGTACACACCGCCC-30 ) and 1510R (50 -CCTTCYGCAGGTTCACCTAC-30 ) (Amaral-Zettler et al., 2009).
The structure of primers (for the first and second PCR),
the contents of the reaction mixture and the thermal
cycling conditions were the same as in Nakamura, Tuji,et al. (2020). Three negative controls were also contained in the PCR to check that there was no contamination of eukaryotes. After the second PCR, all of the
PCR products were mixed and purified with AMPure
XP (Beckman Coulter, USA). The purified mixture wasadjusted to 4 pM before amplicon sequencing using
MiSeq (Illumina, USA). One run of sequencing was performed with MiSeq Reagent kit v3 (600 cycles)(Illumina, USA), following the recommended protocol
and default settings.
The obtained data were analysed with Claident ver.
0.2.2019.05.10 software (Tanabe & Toju, 2013) according to the Claident manual (Tanabe, 2018). Low-quality
sequences, with average quality scores less than
30 were removed, and chimera sequences were also
excluded. The sequences were then clustered into
OTUs using a minimum identification score of 0.97.
The OTU compositions of each specimen are summarized in a matrix, which lists sequences longer than
200 mer with at least 200 reads. After the treatment
mentioned above, 0.01%–10.31% of the original
sequence reads were removed in each sample. The

OTUs were taxonomically identified until the genus or
species level by the Basic Local Alignment Search Tool
(BLASTN) from the U.S. National Center of Biotechnology Information (https://www.ncbi.nlm.nih.gov/) using
the nr database, excluding environmental sample
sequences. The taxonomic name of the registeredsequence with at least 98% match was assigned toeach OTU in most cases. However, some sequencesdifficult to identify by BLASTN were (1) further identified
by SILVA (Quast et al., 2013) and/or (2) assigned taxonomic names by creating phylogenetic trees containing
sequences of related organisms. The classification ofphylum- or class-level taxa is referred to by Adl et al.
(2019) and Nakamura, Matsuoka, et al. (2019). The relative abundance (%) was derived from the ratio of thetotal sequence read and the sequence read of eachhigher taxon.
Cluster analyses were based on the taxonomic
composition of the detected organisms in each specimen. The read numbers of detected OTUs were collapsed into binary data (0 or 1), and the Euclidean
distances within the resulting dataset were calculatedby the statistical software College Analysis ver. 6.6(Fukui & Hosokawa, 2004). We constructed dendrograms based on the higher taxon and habitat by Ward’s
method (Ward, 1963) to visualize the differencesamong the layers.

RESULTSA total of 22 plankton samples were collected over
8 years (Figure 1). From these samples, 28 Radiolaria

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and 56 Phaeodaria, belonging to almost all orders,were analysed by the DNA metabarcoding (Figures 2
and S1, Table S2). In the DNA metabarcoding analyses, the sequences of the hosts (Radiolaria andPhaeodaria) were often detected in most of the specimens (Figure 3, Table S3). Multiple eukaryotic organisms were detected in most of the radiolarianspecimens, except for specimens Tax4, Kn10b, St2,
oth5b, GS14 and Or9, in which only radiolariansequences were detected. The same taxa tended to be
detected in the same Radiolaria, such as Kinetoplastea, Pelagomonas and Scrippsiella in Acanthoplegma
krohni (specimens Ae6 and Ae7), and Prymnesium in
Acanthometron pellucidum (specimens Ae9 and Ae10).
Photosynthetic organisms (e.g., Haptophyta, Pelagophyceae and Dinoflagellata) were frequently detectedin the radiolarian orders Acantharia, Taxopodia, Spumellaria and Collodaria, whereas they were neverfound in the order Orodaria, in which nonphotosynthetic Dinoflagellata and animals (Cnidaria
and Chaetognatha) were detected.

Host sequences were also mainly detected in
Phaeodaria, followed by other eukaryotic organisms(Figure 4). However, no or very few hosts of Phaeodaria were detected in the family Astracantha and thespecimens from the phaeodium (specimens with ‘phd’in their names). Similar to Radiolaria, the same taxa
tended to be found in the same Phaeodaria, for example, Cephaloidophora/Thiriotia in the family Castanellidae and Dermocystidium in the family Astracantha.
Other eukaryotic organisms were more frequently
detected in specimens from the phaeodium than in
specimens from the central capsules.
The cluster analysis based on the detected organisms revealed that all specimens could be categorized
into two large groups: cluster A including only Phaeodaria and cluster B containing Radiolaria andPhaeodaria (Figure S2). In cluster B, Phaeodaria
appeared in several limited subclusters.
Further analysis of Radiolaria clarified that they
could be clustered into three large groups, and this categorization corresponded to radiolarian order-level

F I G U R E 2 Some specimens of Radiolaria and Phaeodaria collected in this study. (A) Dictyocoryne truncata, (B) Diplosphaera hexagonalis,(C) Myelastrum trinibrachium, (D) Sticholonche zanclea, (E) Sphaerozoum punctatum, (F) Acanthoplegma sp., (G) Castanidium longispinum,(H) Aulosphaera sp., (I) Challengeron channeri, (J) Challengeria naresii, (K) Atlanticella sp., (L) Tuscarora tubulosa.

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DNA METABARCODING FOCUSED ON DIFFICULT-TO-CULTURE PROTISTS

NAKAMURA ET AL.

F I G U R E 3 Proportion in total sequence reads (%) of Radiolaria (host) and other detected organisms (possible symbionts, parasites andfood sources). The first, second and third highest values for each specimen are shown in red, orange and yellow, respectively. Taxa with green
circles are photosynthetic autotrophs, which have the potential to be symbiotic algae. *18S rRNA sequences are not registered in the NCBI
database. **The proportion of the host.

taxonomy (Figure S3): cluster C, which contained theorders Acantharia and Taxopodia; cluster D, which
included only the order Spumellaria; and cluster E,
which is mainly composed of the order Collodaria,
although three specimens belonging to other orders
were also present.
Unlike Radiolaria, phaeodarian clusters did not correspond to the order- or family-level taxonomy(Figure S4). Rather, the difference between body parts(central capsule vs. phaeodium) was highlighted. As aresult, Phaeodaria were categorized into two large clusters: cluster F, which chiefly contained the specimensfrom the phaeodium; and cluster G, which mainly
included specimens isolated from the central capsule.

DISCUSSIONRadiolaria
The cluster analysis based on the taxonomic composition of organisms detected in the Radiolaria and Phaeodaria specimens suggests that the organisms
contained in them largely differ between these twogroups (Figure S2). The high detection of algae (phytoplankton) presumably reflects their symbiosis judging
from previous reports concerning the symbiosis of protists (Bjorbækmo et al., 2020; Nowack &Melkonian, 2010). The taxonomic composition of potential symbionts, parasites and food sources seems to be
fixed at the species level, considering that the same
species of Radiolaria contained similar organisms(Figure 3). The cluster analysis focused on Radiolaria
also shows that members of the same radiolarian ordertend to contain similar other organisms (Figure S3),
suggesting that their biological interactions largely differ
among the orders.
The following algae detected in this study havesome kind of biological interaction with Radiolaria: Haptophyta, Pelagophyceae and Dinoflagellata (Figure 3).
The following combinations were recognized for the
first time by this study: Gyrodinium in Litholophus
sp. (Acantharia); Pelagomonas, Scrippsiella and Karlodinium in Acanthoplegma krohni (Acantharia); Pelagomonas, Scrippsiella and Zooxanthella in Sticholonche
zanclea (Taxopodia); and Haptophyta in Myelastrum trinibrachium (Spumellaria). The detected organisms may
be symbiotic algae judging from the data of previous
studies (Table S1), but other analyses, such as observations of substance transportation, are necessary tofurther clarify details on their symbiosis. The following
combinations may be symbiosis with more than twoalgae, as suggested by (Decelle, Siano, et al., 2012):
Pelagomonas and Scrippsiella in Acanthoplegma
krohni (Acantharia) and Sticholonche zanclea(Taxopodia) (Figure 3). Future studies applying DNA

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F I G U R E 4 Proportion in total sequence reads (%) of Phaeodaria (host) and other detected organisms (possible symbionts, parasites andfood sources). The first, second and third highest values for each specimen are shown in red, orange and yellow, respectively. Taxa with green
circles are photosynthetic autotrophs, which have the potential to be symbiotic algae. *18S rRNA sequences are not registered in the NCBI
database. **The proportion of the host.

metabarcoding on single organism would further reveal
the symbiosis with multiple algae.
Kinetoplastea (Euglenozoa), Apicomplexa and Massisteria (Cercozoa), which were detected in the Radiolaria specimens (Figure 3), are known to be parasitic tosome marine organisms (Gull, 2001; Mylnikov
et al., 2015; Seeber & Steinfelder, 2016), and thesetaxa could be parasites of Radiolaria. This is the firstreport of parasitism of these three taxa to Radiolaria.
The detection of multicellular organisms (Cnidaria,
Chaetognatha, Crustacea and Chordata, including
fishes) should be interpreted carefully because theseanimals have a large number of cells, and they can bedetected more easily than unicellular hosts. It is possible that is that some Radiolaria feed on the carcassesof multicellular animals contained in detritus or marine
snow (Ikenoue et al., 2019; Nakamura et al., 2017).
Another possibility is that some parts of the body ofthese multicellular animals were contained inside thespecimens. Certain large Radiolaria have beenreported to be eaten by gelatinous zooplankton, suchas Cnidaria and salps (Nakamura et al., 2021), but theirfragile bodies are easily damaged during the process offield sampling. They thereby become unrecognizable,
but a small amount of their bodies remain inside theradiolarian specimens. This is especially the case in
the order Orodaria (Or1 and Or3), which are often fed
on by gelatinous zooplankton.

Phaeodaria
The cluster analysis focused on Phaeodaria suggested
that, unlike the case with Radiolaria, members of thesame phaeodarian family do not tend to contain similarorganisms (Figure S4). The body part (i.e., the central
capsule or the phaeodium) could be the most importantfactor dividing the taxonomic composition of detectedorganisms (Figure S4), implying that the selection of an
appropriate body part is important when determining

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DNA METABARCODING FOCUSED ON DIFFICULT-TO-CULTURE PROTISTS

contained organisms, even for unicellular zooplankton.
Previous researchers have suggested that the phaeodium contains undigested prey (Gowing, 1986, 1989),
and this idea is partly supported by the results of thisstudy, which revealed that the phaeodium contains
numerous small organisms (i.e., possible foodsources).
There was a paucity of information about the biological interactions of Phaeodaria (Table S1). Some previous studies thoroughly reviewed the symbiosis ofprotists and the biological interactions were well documented for the other culturable cercozoans (Bjorbækmo
et al., 2020; Nowack & Melkonian, 2010). Very little
information was, however, available for Phaeodaria,
which also belong to Cercozoa. This study succeededin adding to and updating knowledge on thesebiological interactions. Previous studies reported that
Dinoflagellata are parasitic on Phaeodaria (CachonEnjumet, 1961), and this was confirmed by our results.
In addition, we found that Apicomplexa, Massisteria(Cercozoa) and Dermocystidium (Mesomycetozoea)
may also be parasites of some Phaeodaria since thesetaxa are known as parasites of diverse marine organisms (Gull, 2001; Mylnikov et al., 2015; Seeber &Steinfelder, 2016).
Symbiotic algae have not previously been reported
in Phaeodaria, and therefore, the detection of photosymbiotic organisms should be interpreted carefully.
Most of these algae may be food sources, but it is also
possible that some of them function as symbiotic algae
because some host Phaeodaria were collected ineuphotic zones (e.g., Aulosphaera sp.1, Coelanthemum auloceroides and Aulacantha scolymantha). In
addition, the algae detected in these Phaeodaria(e.g., Haptophyta and some autotrophic species of
Dinoflagellata) are symbionts of other marine organisms (Bjorbækmo et al., 2020; Lee et al., 2022; Takagi
et al., 2019). Considering the Radiolarian results(Figure 3), Pelagophyceae may also be symbiotic algaeof Phaeodaria.
Similar to the case of Radiolaria, multicellular organisms (Chaetognatha, Mollusca, Crustacea and Chordata, including fishes) were detected in Phaeodaria.
These taxa are food sources or possibly contaminantsin the plankton sampling process. It is noteworthy that
Copepoda were more frequently detected in Phaeodaria than in Radiolaria. This crustacean taxon is oneof the most abundant zooplankton in the world ocean,and consequently, contamination with their body parts
during the sampling process is possible. However,some specimens of Phaeodaria and Radiolaria werecollected in the same stations (Stas. 101, 102,
103, 104, KJ1 and Ses1) (Table S2), and Copepoda
were rarely detected in Radiolaria (Figure 3). The highdetection of Copepoda, therefore, presumably reflects
an ecological characteristic of Phaeodaria. It has been

NAKAMURA ET AL.

suggested that Phaeodaria feed on detritus or marine
snow (Gowing, 1989), and the carcasses of Copepoda
and other multicellular organisms are often contained inthese substances. Copepoda may thus be eaten indirectly by Phaeodaria and presumably be an importantfood source.

DNA metabarcoding of difficult-to-culture
protists
The presence of multiple symbionts and parasites isgenerally difficult to detect, and simultaneous analysis
of numerous specimens requires a great deal of timeand effort with ordinary methods. However, by using a
combination of single-cell DNA analysis and DNA
metabarcoding, we were able to overcome these obstacles. This study succeeded in shedding light on the biological interactions of two groups of difficult-to-culture
protists, Radiolaria and Phaeodaria. Moreover, theapproach was shown to be effective enough to reveal
the ecological relationships of these difficult-to-culture
protists.
Future studies should focus on other difficultto-culture but ecologically important protists such as
Ciliophora, Choanoflagellata and especially Foraminifera. The last group is known as an environmental proxybecause of their wide distribution, importance as microfossils and function as primary producers of symbiotic
algae (Takagi et al., 2019). The symbionts of Foraminifera could be clarified more easily than those of Radiolaria and Phaeodaria because the 18S ribosomal RNA
sequence of this group is largely different from othereukaryotes, and therefore, the host would not be
detected. Indeed, Foraminifera are rarely detected by
DNA metabarcoding using eukaryote-specific primers(Sogawa et al., 2022). In addition, more specimens ofRadiolaria and Phaeodaria should be examined to further confirm the pattern and specificity of their symbionts, parasites and food sources.
AU THOR CONT RI BU TION S
Yasuhide Nakamura: Conceptualization (lead); data
curation (lead); formal analysis (lead); funding acquisition (lead); investigation (lead); methodology (lead);project administration (lead); resources (lead); visualization (lead); writing – original draft (lead);writing – review and editing (lead). Hiryori Itagaki:
Investigation (supporting); resources (supporting). Akihiro Tuji: Methodology (supporting). Shinji Shimode:
Investigation (supporting); resources (supporting).
Atsushi Yamaguchi: Investigation (supporting);
resources (supporting). Kiyotaka Hidaka: Investigation(supporting); resources (supporting). Eri OgisoTanaka: Formal analysis (supporting); methodology(supporting); software (supporting).

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A CK NO W L E DG E M E NT S
We sincerely thank Dr. Tsuyoshi Hosoya (NMNS),
Dr. Noritoshi Suzuki (Tohoku Univ.), Dr. Fabrice Not(CNRS, Roscoff) and Dr. Haruka Takagi (Chiba Univ.)
for their kind advice and support. We also thankDr. John Dolan (Laboratoire d’Océanographie deVillefranche-sur-Mer), Dr. Rie S. Hori (Ehime Univ.),
Dr. Susumu Ohtsuka (Hiroshima Univ.), Dr. Rei Somiya(JERA) and the members of the Plankton Laboratory(Hokkaido Univ.) for their help in plankton sampling.
We are grateful to the captains and crew of T/SOshoro-maru (Hokkaido Univ.), T/S Toyoshio-maru(Hiroshima Univ.) and R/V Soyo-maru (Fisheries
Research and Education Agency). The cruise of Soyomaru was conducted as part of the marine fisheries
stock assessment and evaluation for Japanese waters
conducted by the Fisheries Research and Education
Agency of Japan. This work was financially supported
by JSPS KAKENHI Grant Number JP20K15589(Y. Nakamura).

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C ON F L I CT OF I NT E R E S T S T A T E M E NT
The authors declare that they have no conflict ofinterest.
D AT A AV AI L AB IL IT Y S T A T E ME NT
All data used are present in the paper and the Supplementary Material. Amplicon sequences generated inthis study are available via the NCBI and DDBJ databases with the accession number DRA017142
https://ddbj.nig.ac.jp/(BioProject
PRJDB16648):
resource/bioproject/PRJDB16648.
ORCID
Yasuhide Nakamura
1632-2883

https://orcid.org/0000-0003-

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S UP P O RT IN G I NF O R M AT IO N
Additional supporting information can be found online
in the Supporting Information section at the end of thisarticle.
How to cite this article: Nakamura, Y., Itagaki,
H., Tuji, A., Shimode, S., Yamaguchi, A., Hidaka,
K. et al. (2023) DNA metabarcoding focused on
difficult-to-culture protists: An effective approach
to clarify biological interactions. Environmental
Microbiology, 25(12), 3630–3638. Available from:https://doi.org/10.1111/1462-2920.16524

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