Science, Faculty of
Botany, Department of
Earth, Ocean and Atmospheric Sciences, Department of
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Microbiome. 2021 Nov 26;9(1):230
The Author(s)
Zhong, Kevin Xu
Cho, Anna
Deeg, Christoph M.
Chan, Amy M.
Suttle, Curtis Arnold, 1955-
Background The microbiome affects the health of plants and animals, including humans, and has many biological, ecological, and evolutionary consequences. Microbiome studies typically rely on sequencing ribosomal 16S RNA gene fragments, which serve as taxonomic markers for prokaryotic communities; however, for eukaryotic microbes this approach is compromised, because 18S rRNA gene sequences from microbial eukaryotes are swamped by contaminating host rRNA gene sequences. Results To overcome this problem, we developed CRISPR-Cas Selective Amplicon Sequencing (CCSAS), a high-resolution and efficient approach for characterizing eukaryotic microbiomes. CCSAS uses taxon-specific single-guide RNA (sgRNA) to direct Cas9 to cut 18S rRNA gene sequences of the host, while leaving protistan and fungal sequences intact. We validated the specificity of the sgRNA on ten model organisms and an artificially constructed (mock) community of nine protistan and fungal pathogens. The results showed that > 96.5% of host rRNA gene amplicons were cleaved, while 18S rRNA gene sequences from protists and fungi were unaffected. When used to assess the eukaryotic microbiome of oyster spat from a hatchery, CCSAS revealed a diverse community of eukaryotic microbes, typically with much less contamination from oyster 18S rRNA gene sequences than other methods using non-metazoan or blocking primers. However, each method revealed taxonomic groups that were not detected using the other methods, showing that a single approach is unlikely to uncover the entire eukaryotic microbiome in complex communities. To facilitate the application of CCSAS, we designed taxon-specific sgRNA for ~16,000 metazoan and plant taxa, making CCSAS widely available for characterizing eukaryotic microbiomes that have largely been neglected. Conclusion CCSAS provides a high-through-put and cost-effective approach for resolving the eukaryotic microbiome of metazoa and plants with minimal contamination from host 18S rRNA gene sequences. Video Abstract
METHODOLOGY Open AccessRevealing the composition of theeukaryotic microbiome of oyster spat byCRISPR-Cas Selective Amplicon Sequencing(CCSAS)Kevin Xu Zhong1*, Anna Cho2, Christoph M. Deeg2, Amy M. Chan1 and Curtis A. Suttle1,2,3,4*AbstractBackground: The microbiome affects the health of plants and animals, including humans, and has many biological,ecological, and evolutionary consequences. Microbiome studies typically rely on sequencing ribosomal 16S RNAgene fragments, which serve as taxonomic markers for prokaryotic communities; however, for eukaryotic microbesthis approach is compromised, because 18S rRNA gene sequences from microbial eukaryotes are swamped bycontaminating host rRNA gene sequences.Results: To overcome this problem, we developed CRISPR-Cas Selective Amplicon Sequencing (CCSAS), a high-resolution and efficient approach for characterizing eukaryotic microbiomes. CCSAS uses taxon-specific single-guideRNA (sgRNA) to direct Cas9 to cut 18S rRNA gene sequences of the host, while leaving protistan and fungalsequences intact. We validated the specificity of the sgRNA on ten model organisms and an artificially constructed(mock) community of nine protistan and fungal pathogens. The results showed that > 96.5% of host rRNA geneamplicons were cleaved, while 18S rRNA gene sequences from protists and fungi were unaffected. When used toassess the eukaryotic microbiome of oyster spat from a hatchery, CCSAS revealed a diverse community ofeukaryotic microbes, typically with much less contamination from oyster 18S rRNA gene sequences than othermethods using non-metazoan or blocking primers. However, each method revealed taxonomic groups that werenot detected using the other methods, showing that a single approach is unlikely to uncover the entire eukaryoticmicrobiome in complex communities. To facilitate the application of CCSAS, we designed taxon-specific sgRNA for~16,000 metazoan and plant taxa, making CCSAS widely available for characterizing eukaryotic microbiomes thathave largely been neglected.Conclusion: CCSAS provides a high-through-put and cost-effective approach for resolving the eukaryotic microbiomeof metazoa and plants with minimal contamination from host 18S rRNA gene sequences.Keywords: Eukaryotic microbiome, 18S rRNA gene, Microeukaryote, CRISPR-Cas, Taxon-specific single-guide RNA, gRNAtarget site, CasOligo, CCSAS© The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you giveappropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate ifchanges were made. The images or other third party material in this article are included in the article's Creative Commonslicence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commonslicence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtainpermission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to thedata made available in this article, unless otherwise stated in a credit line to the data.* Correspondence: xzhong@eoas.ubc.ca; suttle@science.ubc.ca1Department of Earth, Ocean, and Atmospheric Sciences, The University ofBritish Columbia, Vancouver, British Columbia, CanadaFull list of author information is available at the end of the articleZhong et al. Microbiome (2021) 9:230 https://doi.org/10.1186/s40168-021-01180-0BackgroundThere is a growing interest in understanding how thecomposition of the microbiome affects the health of plants[1, 2] and animals [3–7], including humans [8, 9]. For ex-ample, in humans the gut microbiome is associated withboth positive and adverse health effects, and changes inthe microbiome have been linked to a number of diseases[10–13], such as obesity [14, 15], diabetes [16, 17], inflam-matory bowel disease [18–21], cancer [22–25], cadiovas-cular disease [26, 27], and even mental illness [28–30]. Aswell, a wide span of biological, ecological, and evolutionaryquestions have been addressed through microbiome stud-ies [3, 6–9, 31, 32]. Microbes have been shown to affecthost metabolism [33], host immunity [34, 35], and humandevelopment [8, 36] including the brain [37, 38], and mayeven influence the evolution of animals and plantsthrough microbe-host interactions [3, 7, 32, 39–45].Microbiome studies have largely been facilitatedthrough deep sequencing of ribosomal RNA gene frag-ments [46–49]; yet, our knowledge of the eukaryoticcomponent of the microbiome, particularly protists, isrelatively limited compared to that of prokaryotes [6,49–53]. This is largely due to the challenge of profilinghost-associated eukaryotic microbes, as the standard“universal” primers [54] used to amplify 18S rRNA genesequences from eukaryotic microbes also amplify host18S rRNA gene sequences, which will dominate the se-quencing library [46, 52, 55].A number of approaches have been used to minimizecontamination by host 18S rRNA gene sequences. Forexample, primers can be designed that will not amplifyhost 18S rRNA sequences, but will amplify sequencesfrom microeukaryotes (e.g., reference 56–58); alterna-tively, other marker genes can be targeted such as theITS region of fungi [59]. However, designing primers toamplify ribosomal RNA gene sequences from a broadrange of microeukaryotes, but not the host, can bechallenging.Another approach is to use primers to block ampli-fication of host 18S rRNA sequences to study theeukaryotic microbiome [60]. Such “blocking primers”typically use a short blocking-oligonucleotide with amodified 3′ end that binds to the 18S rRNA gene ofthe host, and prevents “universal” 18S primers fromamplifying host sequences [60]. Such an approach hasbeen successfully applied to krill [60], fish [61, 62],coral [63], primates [64], shrimp [65, 66], flying squid[67], mosquitos [68, 69] and Pacific oysters [57], al-though a large proportion of the sequences can stillbe host-derived (e.g., up to 92% in coral, 42% in krill,and 45% in fish) [57, 63, 71]. This approach alsorequires designing and optimizing the blockingprimers for each animal host, which remains achallenge [70, 71].Recently, a method involving the usage of non-metazoan (UNonMet) primers [58] was developed [70,71] and was shown to be effective in coral and humans[70, 72]. This “non-metazoan primers” method employsa nested-PCR approach which involves a two-step PCRprocedure. The first-PCR step uses UNonMet primers[58] to generate ~600-bp fragments of 18S rRNA genethat are specific to microeukaryotes but not to meta-zoans; the products from the first PCR are reamplifiedusing the “universal” 18S primers to produce a shorter18S rRNA gene fragment [70]. This method has the ad-vantage of not requiring host-specific primer design, butbased on in silico analysis cannot be used for spongesand ctenophores [70].Here, we describe CRISPR-Cas Selective Amplicon Se-quencing (CCSAS), an alternative approach to resolvethe eukaryotic microbiome of metazoa and plants. Clus-tered regularly interspaced short palindromic repeats(CRISPR) and the CRISPR-associated protein 9 (Cas9)system provides bacteria and archaea adaptive immunityagainst viruses and plasmids by cleaving invadingdouble-stranded (ds) DNA [73]. The sequence-specificcleavage is performed by Cas9 endonuclease in the pres-ence of guide RNA (gRNA). This gRNA is a duplexcomprising a trans-activating RNA (tracrRNA) that is ascaffold for binding the Cas9 protein, and an approxi-mately 20 nucleotide (nt) crispr RNA (crRNA) guide se-quence that is complementary to the DNA target site[74–77]. Cas9 can be programmed to target any DNAsequence by modifying the 20-nt guide sequence [77,78]. Due to its precision in DNA cutting, the simplicityin programming and the ability to artificially fuse thegRNA duplex (tracrRNA-crRNA) into a single-guideRNA (sgRNA) [77], CRISPR-Cas9 has emerged as apowerful tool in a wide variety of applications [78, 79].CCSAS leverages this tool by using a custom sgRNA todirect Cas9 to specifically cut host 18S rRNA gene se-quences in the region flanked by “universal” primers.The cleaved host 18S fragments contain only a 3′ or 5′primer-binding region, resulting in short single-stranded(ss) DNA products produced by PCR, which are re-moved during the preparation of the sequencing library.This results in a library highly enriched in 18S ampli-cons from microeukaryotes, allowing for high-resolutionsurveys of the taxonomic composition of eukaryoticmicrobes associated with any eukaryotic host.ResultsDesign of the taxon-specific sgRNAThe key to CCSAS is the 20-nt guide sequence of gRNAthat directs Cas9 to selectively cut the 18S rRNA genesequences of the host, but not those of the associatedmicroeukaryotes. We developed CasOligo (https://github.com/kevinzhongxu/CasOligo), an R package thatZhong et al. Microbiome (2021) 9:230 Page 2 of 17contains the algorithm Cas9.gRNA.oligo1(), which iden-tifies 20-nt sequences in the 18S rRNA gene regionspanned by “universal” primers that can serve as target-sites for gRNA, and which are complementary to thesgRNA’s guide sequence. The selected gRNA andsgRNA duplex thus dictates the specificity of thesgRNA-CRISPR-Cas complex, allowing a user to easilysynthesize a taxon-specific sgRNA.To validate the target-specificity of sgRNA, taxon-specific sgRNAs were designed and tested for 18S rRNAsequences from each of the following ten model organ-isms: human (Homo sapiens), salmon (Salmo salar),shrimp (Solenocera crassicornis), chicken (Gallus gallusdomesticus), cow (Bos taurus), mouse (Mus musculus),fruit fly (Drosophila melanogaster), rock cress (Arabi-dopsis thaliana), oyster (Crassostrea gigas), and thenematode (Caenorhabditis elegans), as well as beingtested against an artificially constructed (mock) commu-nity composed of nine protists and fungi (Table S1 andS2). The results showed that the CRISPR-Cas9 treatmenteffectively cleaved the host 18S amplicons, while ampli-cons from the mock community of protists and fungiremained intact (Fig. 1). Comparisons using qPCR withand without CRISPR-Cas9 treatment showed that only0.6% to 3.5% of the intact 18S amplicons remained afterCRISPR-Cas9 cutting (Fig. S1). Thus, the sgRNAs effect-ively targeted host sequences, while leaving sequencesfrom microeukaryotes intact.Using CCSAS to reveal host-associated microeukaryoticpopulationsThe next step was to evaluate the effectiveness of Cas9when complexed with the host-specific sgRNA. AfterCRISPR-Cas9 treatment, about 0.6% to 3.5% of theremaining 18S amplicons were still host-derived, but inmost cases still dominated the sequencing library (datanot shown). Hence, to further reduce the host-derived 18SrRNA gene sequences, we introduced a two-step CRISPR-Cas9 procedure (Fig. 2). First, Cas9 with a taxon-specificsgRNA that is complementary to the host 18S rRNA genesequence at the 20-nt target-site is used to cut the hostgenomic 18S rRNA gene and then the remaining uncut18S sequences are amplified using PCR. Any amplificationof the cut fragments yields short pieces of ssDNA that areremoved during size-selection clean-up step using SPRImagnetic beads. Second, following the first size selection,another Cas9 cut, PCR amplification, and size selectionare conducted (Fig. 2), resulting in almost the completeremoval of host 18S amplicons, while leaving the protistanand fungal amplicons intact. This allows for high-resolution characterization of the composition of themicroeukaryotic community with a fraction of the sequen-cing effort typically used.We applied two-step CCSAS to examine theeukaryotic microbiome from eight different samples ofoyster spat (C. gigas) collected from a hatchery that wasexperiencing mortality events. The results showed thatusing CCSAS in conjunction with “universal” 18Sprimers resulted in almost the complete removal of oys-ter 18S amplicons, while leaving the protistan and fungalamplicons intact and highly enriched for sequencing(Fig. S2; Fig. 3a). With CCSAS, the percentage of se-quences from metazoa (mostly assigned to oysters, al-though some were from nematodes in the orderMonhysterida; Fig. S2) was at most 7.4%, while in threeout of eight samples, sequences from metazoa were un-detectable (Fig. 3a). In contrast, with non-metazoan andblocking primers, up to 48.5% and 62.9% of sequences,respectively, were still from metazoa (Fig. 3a), primarilyoysters (Fig. S2). When compared to non-metazoan andblocking primers, CCSAS revealed all the majoreukaryotic microbial groups including members of theOchrophyta, Labyrinthulomycetes, and Ciliophora (Fig.3a-b). Nevertheless, given that there are differences inFig. 1 Agilent Bioanalyzer gel images of 18S amplicons from ten model organisms (a and b) and an artificial community of protists and fungi (c)to which Cas9 with the taxon-specific sgRNA (as shown in Table S2) was either added (+) or not (−). Gel bands show the amplicon length inbase pairs (bp) relative to a DNA ladder. The labels on the X-axes of panel c indicate the ID of the taxon-specific sgRNAs and its correspondinghost to targetZhong et al. Microbiome (2021) 9:230 Page 3 of 17primer design among the three methods, as well as dif-ferences in PCR conditions (Table S3) [54, 57, 63, 70,102], it is not surprising that there were differencesamong the taxa detected (Fig. 3b). For example, CCSASdetected the genus Telonema, peronosporomycetes inthe Stramenopiles, and Picomonadida in the Picozoa,while non-metazoan and blocking primers did not. Yet,CCSAS did not detect the MAST4-group of strameno-philes or hyphochytriomyctes, while non-metazoanprimers did, and prymnesiophytes, cryptophytes, andfungi in the phylum Cryptomycota and the division Chy-tridiomycota were only revealed by the blocking primers.As well, members of the genus Mantamonas and thefamily Acanthocystidae were detected by the non-metazoan and blocking primers, but not by CCSAS (Fig.3b). Additionally, using CCSAS, the relative abundancesof cercozoans and dinoflagellates were less than with theother methods (Fig. 3a). Thus, amplification with “uni-versal” 18S primers combined with CCSAS had less con-tamination by host sequences and revealed someadditional taxa compared to non-metazoan and blockingprimers; however, there were also some taxa that wereabsent using CCSAS. Nonetheless, the composition ofthe eukaryotic microbiome detected by the threemethods was quite similar (ANOSIM: r2 = 0.131, p value= 0.032, n = 8; PERMANOVA: r2 = 0.145, p value =0.175, n = 8), and taxa that were not detected by one ormore methods were always a minor component of theoverall community.Moreover, the community structure was quite similaramong the three methods for four of eight oyster sam-ples (i.e., Oyster 2, 6, 7, and 8; Fig. 3c), although thegenus-level relative abundances were variable acrossmicroeukaryotic genera between oysters and methods(Fig. 4a). Differences in genera detected among methods(Fig. 4b) included a dinoflagellate (Gyrodinium) andlabyrinthulomycete (Labyrinthula) that occurred in rela-tively higher abundance using CCSAS. In contrast, com-pared to CCSAS, the blocking primers resulted inrelatively higher abundance of several genera including aFig. 2 Workflow for two-step CRISPR-Cas Selective Amplicon Sequencing (CCSAS) to study the composition of the host-associated eukaryotic microbiomeZhong et al. Microbiome (2021) 9:230 Page 4 of 17dinoflagellate (Islandinium), ochrophytes (Stauroneis,Nitzschia, and Paraphysomonase), a ciliophoran (Para-nophrys), a cercozoan (Thaumatomasix), and a bicosoe-cid (Pseudobodo). Finally, compared to CCSAS, usingthe non-metazoan primers resulted in higher relativeabundances of other genera belonging to ciliophora(Philaster and Miamiensis), a unicellular opisthokont(Salpingoeca), and ochrophytes (Navicula, Phaeodacty-lum, and Thalassiosira). Nonetheless, despite the differ-ences among methods, the composition of themicroeukaryotic communities was quite similar amongmethods.Fig. 3 Panel a shows the relative abundances of eukaryotic groups in eight oyster samples revealed using deep-sequencing of 18S amplicons of rRNAgenes. The methods are based on using non-metazoan primers (NM), blocking primers (BP), and CCSAS that combines 18S “universal” primers andcleavage using CRISPR-Cas9. Panel b shows the comparison of the number of 18S rRNA gene OTUs summed for the eight oyster samples for eachmicroeukaryotic group. Panel c shows the Principal Coordinate Analyses (PCoA) of the community structure of the microeukaryotic 18S rRNA genesequences in oyster spat. The PCoA ordinates the weighted Unifrac matrix that are based on the presence/absence and the relative abundance ofmicroeukaryotic OTUs. Symbol colors represent the oyster samples, and the shapes indicate different methods (CCSAS, NM, BP)Zhong et al. Microbiome (2021) 9:230 Page 5 of 17Fig. 4 Heatmap (a) showing the relative abundance of 18S rRNA genes in microeukaryotic genera in oyster spat using the three methods. Inpanel b, linear discriminant analysis effect size (LEfSe) reveals differentially detected microeukaryotic genera in oysters among the three methods.The histogram shows LDA scores calculated for differences in genus-level abundances among microeukaryotic 18S rRNA genes for the threemethods, and the dot plot shows the p values that determines the LDA significanceZhong et al. Microbiome (2021) 9:230 Page 6 of 17Database of gRNA target sites for metazoa and plantsTo enable CCSAS to be easily applied for characterizingeukaryotic microbiomes in a wide range of metazoa andplants, we used CasOligo to identify gRNA target sitesfor 99.6% of the 15907 metazoa and plant taxa (meta-phyta of Embryophyta group) in the SILVA SSU data-base [80] (version 119, released on 24 July 2014) (Fig. 5).For each taxon, we identified between 3 and 217 (aver-age 33) gRNA target sites that are compatible with theCRISPR-Cas9 system (Fig. S3); of these, between 1 and214 targeted the putative host 18S sequence, but notprotistan or fungal sequences. Thus, the database pro-vides a wide selection of gRNA-target-site sequencesfrom which to design taxon-specific sgRNAs.Although it is not possible to design a “universal”sgRNA that targets all metazoa and plants, but notmicroeukaryotes, some sgRNAs target broad taxonomicgroups (Fig. S4). For example, based on in silico analysis,sgRNA_058534 targets 3099 species from 22 classes andfamilies of Animalia, primarily 72.7% of the 4014 Insectaspecies in SILVA (Fig. S4). CasOligo can also be used toretrieve gRNA-target-site sequences for specific taxa byentering the species name of the host using the function,search.db.byname(). Nonetheless, it is best to identify thetaxon-specific gRNA target site based on the 18S rRNAgene sequence of the host, because the action ofCRISPR-Cas9 is sequence-specific and the gRNA-target-site database does not cover all sequence variants for aspecific taxon.DiscussionCCSAS provides a new way to obtain high-resolutiontaxonomic data for the eukaryotic microbiomes ofplants, animals, and other metazoa. By employingCRISPR-Cas9 with taxon-specific gRNAs, the back-ground of host 18S sequences is greatly reduced or elim-inated; thus, CCSAS requires much less sequencing thanother methods to obtain high-resolution taxonomic datafor the eukaryotic microbiome. Moreover, the creationof a database of gRNA target sites, and the primarygRNA-target-site oligonucleotide design functions of theCasOligo package, makes it easy to profile the eukaryoticmicrobiome of metazoa and plants. We identified taxon-specific gRNA target sites for 99.6% of the taxa in theSILVA database, with an average of 33 taxon-specificgRNA target sites per taxon, showing that CCSAS canbe applied to nearly all metazoa and plants. Additionally,the CasOligo package provides an oligonucleotide designFig. 5 Illustration showing the number and taxonomic distribution of gRNA target sites for metazoa and plants that are available for 18S rRNAsequences in the SILVA SSU database v119 [80]. These gRNA-target-site oligonucleotide sequences are used for designing and synthesizing thetaxon-specific and the CRISPR-Cas9-compatible sgRNAs that are used to guide CRISPR-Cas9 to cut the 18S rRNA genes of metazoan or planthosts, but not those of microeukaryotes (protists and fungi). The node size indicates the number of species at each corresponding taxonomiclevel, while the size of the edge presents the number of gRNA target sites. Nodes and edges with the highest values are purple, while thesmallest ones are gray. Only taxa with more than 50 gRNA target sites per taxon are shownZhong et al. Microbiome (2021) 9:230 Page 7 of 17function, Cas9.oligo.search2(), that can be used to designcustom sgRNAs for any gene for which the sequence isknown, and for which there is a reference database forcomparison, so that the specificity of the sgRNA can beascertained. This includes genes encoding other regionsof rRNA, such as the 16S and 23S rRNA genes, or meta-bolic genes (e.g., COX1). Thus, CCSAS makes it possibleto study the genetic diversity of any gene in complexsystems, including genes that are rare, by removing anysequence that would otherwise dominate the data. Thesequence-specific removal of any amplicon has a widerange of applications, including pathogen diagnosis, andstudies of symbiosis and microbiome therapy.There are a few considerations in applying CCSAS tomicrobiome studies. First, gRNA can recognize the wrongtarget [81–83], which might lead Cas9 to cut some pro-tistan and fungal sequences, or incompletely cleave hostsequences. This problem can be minimized by careful de-sign of the gRNA, and in silico analysis against the mostcomprehensive databases of 18S gene sequences. Second,efficient sequencing requires effective removal of the cuthost amplicons. This can be accomplished by optimizingthe size selection of SPRI magnetic beads or may reducesequencing efficiency, or adapting other methods for sizeselecting DNA fragments. Third, there are inherent ampli-fication biases associated with PCR [84]; thus, the accuracyof differences in the relative abundances of specific se-quences using CCSAS, or any other PCR-based approachis unknown. Fourth, the design of host-specific gRNA tar-get sites is only as good as the available 18S rRNA genereferences for microeukaryotes. However, the design ofgRNA target sites will continue to improve as SSU se-quence databases continue to expand. Despite these ca-veats, CCSAS can be used to obtain high-resolution dataon the composition of eukaryotic microbiomes with rela-tively low-sequencing effort. Moreover, it has broad appli-cation because gRNA target sites can be identified forthousands of host species.Our study revealed that most micro-eukaryotes infarmed Pacific oyster spat from British Columbia, Canada,were diatoms in the genera Skeletonema, Thalassiosira,and Cyclotella, ciliates in the subclass Scuticociliatia, andlabyrinthulomycetes in the genus Aplanochytrium (Fig. 3a;Fig. 4a). In another study of the eukaryotic microbiome infarmed adult Pacific oysters in France [57], diatoms, dino-flagellates, and ciliophorans in the genus Trichodina (sub-class Peritrichia) were abundant. As oysters filter-feed onprotists and bacteria [85], it is not surprising that diatomsand dinoflagellates are enriched in the oyster microeukar-yotic microbiome. Notably, in oyster spat in BC, ciliatesfrom the subclass Scuticociliatia accounted for up to~78.2% of the 18S rRNA using CCSAS, and up to ~40%using the other two methods (Fig. S5). The scuticociliateswere from diverse genera including Cohnilembus,Entodiscus, Homalogastra, Metanophrys, Miamiensis,Paranophrys, Parauronema, Philaster, Porpostoma, Pseu-docohnilembus, and Uronema (Fig. S5; Fig. 4a). Membersfrom some of these genera can be opportunistic pathogensthat cause disease (e.g., Scuticociliatosis, Brown-band dis-ease) in a broad range of marine animals such as crusta-ceans, mollusks, corals, and fish including seahorses andsharks [86–95]. Scuticociliates from the genera Para-nophrys and Uronema have been reported to cause diseasein oysters in the USA [96] and Australia [97, 98], respect-ively. Members of the genera Paranophrys and Uronemawere not detected or were in low abundance in all eightoyster samples from BC (Fig. S5; Fig. 4a). Another putativepathogen, the ciliate Miamiensis avidus, was in relativelyhigh abundance across all oyster samples (Fig. S5).Although there were differences in the taxonomic pro-files of microeukaryotes generated using the threemethods, it is important to stress that the relative abun-dances of most taxa were quite similar using the differentapproaches. The most striking difference among methodswas the much lower relative abundance of sequences frommetazoa that was detected using CCSAS, indicating lesscontamination from host-derived sequences. As well, eachof the methods resolved some taxa of microeukaryotesthat the other methods did not; however, the taxa thatwere selectively detected were present in relatively lowabundance. These differences are not surprising given thateach primer set differs in its mismatches among taxa [99,100]. Consequently, relative abundance data must beinterpreted cautiously. Nonetheless, our data show theutility of using CCSAS to investigate the eukaryotic micro-biome of animals in a complex environment, and that oys-ter spat harbor potential pathogens including thescuticociliates Miamiensis avidus, Paranophrys sp., andUronema sp.ConclusionsCCSAS is a powerful tool with which to investigate thecomposition of the eukaryotic microbiome for a vastarray of host organisms. Relative to approaches usingnon-metazoan or blocking primers, CCSAS providessimilar resolution of the eukaryotic microbial commu-nity, but with much less contamination by sequencesfrom host 18S rRNA genes. Moreover, the ease withwhich specific sgRNA can be designed allows CCSAS tobe used to explore the eukaryotic microbiome of almostany host organism. Thus, CCSAS can facilitate signifi-cant advances for investigations of the eukaryotic micro-biome across a wide diversity of hosts.MethodsOrganisms and samplesTen model organisms, human (Homo sapiens), salmon(Salmo salar), shrimp (Solenocera crassicornis), chickenZhong et al. Microbiome (2021) 9:230 Page 8 of 17(Gallus gallus domesticus), cow (Bos taurus), mouse(Mus musculus), fruit fly (Drosophila melanogaster), rockcress (Arabidopsis thaliana), oyster (Crassostrea gigas),and nematode (Caenorhabditis elegans), as well as ninespecies of protists and fungi were obtained from eithercommercial markets or laboratories at The University ofBritish Columbia (Table S1). As well, eight samples ofseven- to 28-day-old oyster spat, with sizes ranging be-tween 0.4 and 1.0 mm, were obtained from a hatcherythat was experiencing mortality events. The oyster spatwere immediately frozen using liquid nitrogen followingcollection, and stored at −80 °C until analysis.Genomic DNA extractionDNA from the model organisms, protists, fungi, and oys-ter spat were extracted using the DNeasy Blood & Tis-sue Kit (Qiagen) following the manufacturer’s directions,and quantified using the Qubit™ DNA HS Assay Kit(Invitrogen).An artificial community of microeukaryotes was madeby pooling equal amounts (~50 ng) of genomic DNAfrom each protist and fungus (Table S1).Design and synthesis of taxon-specific sgRNAThe specificity of CRISPR-Cas9 is determined by a 20-ntguide sequence within the sgRNA, which directs Cas9 tocut a target DNA at the 20-nt target site that is comple-mentary to this guide sequence. Thus, the design of ataxon-specific sgRNA requires identifying a 20-ntgRNA-target-site oligonucleotide sequence in the host18S rRNA gene, which is, absent in microeukaryotes.This taxon-specific 20-nt gRNA-target-site oligonucleo-tide sequence, reverse-complement to the sgRNA’s guidesequence, determines the specificity of the sgRNA andthereby the CRISPR-Cas action that is to cut 18S rRNAgene from the host but not from microeukaryotes. Thistaxon-specific 20-nt gRNA-target-site oligonucleotidesequence is used to synthesize the taxon-specific sgRNAusing an EnGen™ sgRNA Synthesis Kit from New Eng-land Biolabs (NEB).Obtaining the host 18S rRNA gene sequencesPrior to the design of the sgRNA, we obtained the 18SrRNA gene sequences of the host organisms for identify-ing gRNA target sites, and employed the following clon-ing and sequencing approaches:For each host, 18S rRNA gene fragments were PCRamplified using the “universal” primers TAReuk454FWD1and TAReukREV3 [54] to produce 380-450 bp ampliconsthat were sequenced to facilitate the design of gRNA-target-site oligos targeting each host. We selected theseprimers as they are among the most widely used to exam-ine the diversity of microeukaryotic communities [99,100]. Briefly, PCR was conducted in four separatereactions run at annealing temperatures of 45, 47, 48, or49 °C, to ensure amplification of a 380-450 bp fragmentfrom the V4 region of the 18S rRNA gene. Each 25 μL re-action mix was made with 1X PCR buffer (NEB), 4 mMMgCl2, 20 μg of Bovine Serum Albumin (NEB), 200 nMof each dNTP (Invitrogen), 0.4 μM of each primer, 0.5 Uof Q5® high fidelity polymerase (NEB) and ~10 ng of gen-omic DNA template. As previously described [54], the ini-tial denaturation and activation was at 95 °C for 5 min,followed by 10 cycles consisting of 95 °C for 30 s, 57 °Cfor 45 s, and 72 °C for 1 min, followed by 25 cycles of de-naturation at 95 °C for 30 s, annealing at 45, 47, 48, or 49°C for 45 s, elongation at 72 °C for 60 s, and a final elong-ation for 10 min at 72 °C. The PCR products from the fourreactions were then pooled, and the 18S amplicons puri-fied using Agencourt SPRI magnetic beads (BeckmanCoulter) at a 1:1 (vol:vol) ratio of beads:DNA to removefragments < 200 bp.These purified amplicons were then cloned into pCR2-TOPO vectors (Invitrogen) using the TOPO TA CloningKit (Invitrogen). Four 18S rRNA gene clones from eachmodel organism were sent for Sanger sequencing at theNAPS Unit sequencing facility at The University of Brit-ish Columbia. These DNA sequences were then used todesign the taxon-specific 20-nt gRNA-target-site se-quences, which were used to synthesize the taxon-specific sgRNAs that guide Cas9 to cleave the host 18Ssequences, as outlined below.Design of the taxon-specific gRNA-target-siteoligonucleotide sequencesWe developed the R package CasOligo (https://github.com/kevinzhongxu/CasOligo) to design taxon-specific20-nt gRNA-target-site oligonucleotide sequences, whichallows sgRNA to recognize 18S sequences from specifictaxa. Taxon-specific gRNA-target-site oligonucleotidesequences were designed for each model organism usingthe Cas9.gRNA.oligo1() function in CasOligo by provid-ing a fasta file of the V4 region of the 18S rRNA genefrom each organism that is amplified by the “universal”18S primers, TAReuk454FWD1 and TAReukREV3 [54].The same approach can be used to design taxon-specificgRNA-target-site oligonucleotide sequences for any hostorganism. First, Cas9.gRNA.oligo1() searches the for-ward and reverse strands of the 18S rRNA gene for 20-nt gRNA-target-site oligonucleotide sequences that arecompatible with Cas9 nuclease; compatibility requiresthat the protospacer-adjacent-motif (PAM), NGG, is im-mediately adjacent to the 3′ downstream region of the20-nt target-site sequence. Each of these 20-nt gRNA-target-site sequences is potentially a target for the com-bined actions of sgRNA and Cas9. Next, each potentialgRNA-target-site sequence is searched against theSILVA SSU database for the V4 region of 18S rRNAZhong et al. Microbiome (2021) 9:230 Page 9 of 17genes, in order to determine if the sequence is absent inprotistan and fungal microeukaryotes. If so, this gRNA-target-site sequence can be used to synthesize a sgRNAthat will guide Cas9 to specifically cut the host 18SrRNA gene. The gRNA-target-site oligonucleotide se-quences designed in this study are shown in Table S2.Synthesis of sgRNA-template oligonucleotidesOnce suitable taxon-specific 20-nt gRNA-target-siteoligonucleotide sequences were identified, the sgRNA-template oligonucleotide sequences were obtained usingthe EnGen™ sgRNA Template Oligo Designer (https://nebiocalculator.neb.com/#!/sgrna), which adds a T7 pro-moter sequence at the 5′ end, and a 14-nt overlap se-quence at the 3′ end of the 20-nt gRNA-target-sitesequence. For our studies, this sgRNA-template oligo-nucleotide was synthesized by Integrated DNA Tech-nologies (IDT), and diluted to 1 μM with moleculargrade ultrapure water (Invitrogen).Synthesis of sgRNAThe 1 μM sgRNA-template oligonucleotide was used asa DNA template to synthesize the sgRNA using theEnGen™ sgRNA synthesis kit, S. pyogenes (NEB) by fol-lowing the manufacturer’s instructions. The resultingsgRNA was treated with amplification grade DNase I(Invitrogen) at room temperature for 15 min to removeany remaining DNA and then purified using a RNAClean & Concentrator-25 Kit (Zymo Research) by fol-lowing the manufacturer’s instructions. Finally, the frag-ment size of the sgRNA was assessed using an AgilentRNA 6000 Pico Kit (Agilent) and its concentration mea-sured using a Qubit™ RNA HS Assay Kit (Invitrogen).Validation of the design of taxon-specific sgRNATo validate the design of gRNA for taxon-specific cleav-age, we first generated 18S amplicons for each model or-ganism and the mock community of protists and fungi.Then, these 18S amplicons were used to ascertain theeffect of CRISPR-Cas9, in conjunction with taxon-specificsgRNA, on cleavage of the amplicons. The results werevisualized on a gel using a Bioanalyzer (Agilent) andassessed using quantitative PCR (qPCR) as detailed below.Preparation of the host 18S ampliconsFor each of the ten host organisms and the mock com-munity of protists and fungi, 18S rRNA gene fragmentswere obtained using PCR with the “universal” primersTAReuk454FWD1 and TAReukREV3 [54] following theconditions detailed above. The 18S amplicons were puri-fied using Agencourt SPRI magnetic beads (BeckmanCoulter) at a 1:1 (vol:vol) ratio of beads:DNA.DNA cleavage using CRISPR-Cas9For each of the ten host organisms and the mock com-munity of protists and fungi, the purified 18S ampliconswere cut using Cas9 Nuclease, S. pyogenes (NEB) in thepresence of a sgRNA, following the manufacturer’s di-rections. Briefly, the 10 μL reaction contained approxi-mately 0.1 pmol of dsDNA, 1 pmol of sgRNA, and 1pmol of Cas9, as well as 1x Cas9 reaction buffer to keepthe molar ratio of Cas9:sgRNA:template DNA at 10:10:1.The reaction was incubated at 37 °C for 4 h in a thermo-cycler, followed by 70 °C for 10 min to deactivate theCRISPR-Cas9. For each sample, in parallel with theCRISPR-Cas9 treatment, we also prepared the reactionwithout CRISPR-Cas9 treatment, in which Cas9 nucleaseand sgRNA were replaced with molecular grade ultra-pure water (Invitrogen). Thus, each reaction of bothtreatments contained the same amount of templatedsDNA (18S amplicons at 0.1 pmol) and was subjectedto the same incubation conditions.Visualization using gel electrophoresisThe size of the 18S rRNA gene fragments with and with-out CRISPR-Cas9 treatment was visualized by gel elec-trophoresis using a Bioanalyser (Agilent). Prior toloading into the gel, the Cas9-cut products (5 μL out of10 μL) were treated with 1 mg/mL (final) Proteinase K(Invitrogen) at room temperature for 15 min to digestthe Cas9 nuclease. Then, 1 to 2 μL of this proteinase-K-treated product was added into a well of an Agilent HighSensitive DNA Chip in a Bioanalyzer (Agilent) tovisualize and verify cutting by CRISPR-Cas9.Quantitative PCRTo determine the efficiency of CRISPR-Cas9 for eliminat-ing host-derived 18S sequences, we used quantitative PCR(qPCR) and the primers TAReuk454FWD1 and TAReuk-REV3 (Table S3) that targets a 380-450 bp fragment of theV4 region of the 18S rRNA gene, to assess the proportionof 18S amplicons cut by Cas9. The 10 μL qPCR reactionscontained 1 X SsoFast™ EvaGreen® Supermix (Bio-Rad),0.5 μM of each primer, and a 1 μL 1/10000 dilution ofDNA template consisting of amplified products, eitherwith or without the addition of Cas9. Thermal cycling wasdone in a CFX96 real-time PCR detection system (Bio-Rad) with the following program: 3 min denaturation at95 °C, followed by 40 cycles of denaturation at 95 °C for30 s, and annealing and extension at 49 °C for 30 s. Nine,tenfold serially diluted standards (ranging from 5 × 100 to5 × 109 molecules per mL) were run in duplicate alongwith two no-template control reactions containing 1 μL ofnuclease-free water. The amplicon standards were madefrom a cloned 18S rRNA gene fragment amplified from aculture of the prasinophyte microalga, Micromonaspusilla, using the primer set TAReuk454FWD1/Zhong et al. Microbiome (2021) 9:230 Page 10 of 17TAReukREV3 [54]. The amplicons were purified using aMiniElute® PCR Purification Kit (Qiagen), and quantifiedusing a Qubit® dsDNA High Sensitivity Assay Kit (Invitro-gen). The size of the amplicon was checked using gel-electrophoresis, and the qPCR melting curves were usedto confirm that the fluorescence signal corresponded to asingle-sized DNA fragment. The qPCR amplification effi-ciency was between 0.95 and 1.05 for the cloned ampli-cons (with r > 0.98, n = 9).Sequencing library preparation using CRISPR-CasSelective Amplicon Sequencing (CCSAS)To profile host-associated eukaryotic microbiomes, wedeveloped CRISPR-Cas Selective Amplicon Sequencing(CCSAS), which combines the use of CRISPR-Cas9 anduniversal 18S primers to prepare a sequencing librarythat is compatible with Illumina sequencing platforms.The method uses a taxon-specific sgRNA to guide Cas9nuclease to selectively cleave 18S rRNA gene sequencesfrom metazoa and plants, which then can be removed bysize selection with SPRI beads; sequences from microeu-karyotes are left intact, and can be amplified by PCR.Therefore, CCSAS allows high-resolution profiling ofhost-associated eukaryotic microbiomes with relativelylow sequencing effort. In this study, we present CCSAS(Fig. 2); the two-step CRISPR-Cas procedure first usesCas9 to cut the host gene encoding 18S rRNA gene,followed by a second cut of any host-derived 18S ampli-cons. Details of the method are provided below.Cas9 cutting of host genomic DNAGenomic DNA of the host was cut using Cas9 Nuclease,S. pyogenes (NEB) following the manufacturer’s direc-tions. Briefly, a 10-μL reaction mix containing approxi-mately 0.1 pmol of genomic DNA, 1 pmol of sgRNAand 1 pmol of Cas9, as well as 1x Cas9 reaction bufferto keep the molar ratio of Cas9:sgRNA:template DNA at10:10:1 was incubated at 37 °C for 4 h in a thermocycler.The first PCR and size selectionThe Cas9-cleaved genomic DNA was used as a templatein the first PCR to generate 380-450 bp amplicons fromthe V4 region of the 18S rRNA gene that are depleted inhost sequences. To ensure representative amplification of18S sequences from microeukaryotes, four parallel PCRreactions were run at different annealing temperatures(45, 47, 48, or 49 °C), using the “universal” 18S primersTAReuk454FWD1-Nxt and TAReukREV3-Nxt (TableS3). Compared to TAReuk454FWD1 and TAReukREV3[54], this modified primer set contained overhang adaptersequences (Table S3), which are compatible with Illuminaindexes and sequencing adapters. These adapters allowedfor a second PCR to append Illumina Nextera XT indexesto each side of the amplicons as forward and reverseprimers, thus creating a dual-indexed library. This dual-indexed library preparation approach is adapted from Illu-mina [101].Details on the first PCR reactions are as follows.Briefly, each 25 μL reaction mix contained 1X PCR buf-fer (NEB), 4 mM MgCl2, 20 μg of Bovine Serum Albu-min (NEB), 200 nM of each dNTP (Invitrogen), 0.4 μMof each primer, 0.5 U of Q5® high fidelity polymerase(NEB), and 5 μL of the Cas9-cleaved genomic DNA. Be-cause the reverse primer is 2 bp shorter than the for-ward primer and has a lower annealing temperature, weused the two-step PCR approach of Stoeck et al. [54], inwhich there is an initial ten PCR cycles at an annealingtemperature where only the forward primer will bindand amplify, followed by 25 cycles at one of four lowerannealing temperatures (45, 47, 48, or 49 °C) where bothforward and reverse primers amplify. The program hasan initial denaturation and activation at 95 °C for 5 min,followed by ten, three-step cycles consisting of 94 °C for30 s, 57 °C for 45 s, and 72 °C for 1 min, followed by 25cycles of denaturation at 94 °C for 30 s, annealing at ei-ther 45, 47, 48, or 49 °C for 45 s and elongation at 72 °Cfor 60 s, with a final elongation for 10 min at 72 °C. Atthe end, the PCR product of the four reactions waspooled together. Then, amplicons were size-selected andpurified using magnetic Agencourt SPRI beads (Beck-man Coulter) at an 0.8:1 (vol:vol) ratio of beads:DNA toremove fragment < 300bp.Cas9 cutting of the 18S ampliconsTo further remove 18S host amplicons, the size-selectedamplicons described above were cut again using Cas9Nuclease, S. pyogenes (NEB). Briefly, the 10 μL reactioncontained approximately 0.1 pmol of DNA amplicons, 1pmol of sgRNA, 1 pmol of Cas9, 1x Cas9 reaction bufferto keep the molar ratio of Cas9:sgRNA:template DNA at10:10:1. The reaction was incubated at 37 °C for 4 h in athermocycler.The 2nd PCR and size selectionThe product of the second Cas9-cut was used as thetemplate for a second PCR (index PCR) to generate theindexed amplicons libraries. The 50-μL reaction mix ofthe second PCR comprised 1X PCR buffer (NEB), 4 mMMgCl2, 200 nM of each dNTP (Invitrogen), 5 μL of eachindex primer (N7XX and S5XX of Nextera® XT IndexKit, Illumina), 1 U of Q5® high fidelity polymerase(NEB), and 5 μL of the product of the second Cas9 cut.The second PCR (index PCR) consisted of an initial de-naturation and activation at 95 °C for 3 min, followed by29 three-step cycles consisting of 95 °C for 30 s, 55 °Cfor 30 s, and 72 °C for 30 s, and a final elongation for 10min at 72 °C. The indexed amplicons generated by thesecond PCR were size-selected and purified usingZhong et al. Microbiome (2021) 9:230 Page 11 of 17magnetic Agencourt SPRI beads (Beckman Coulter) at aratio of 0.8:1 (vol:vol) for beads:DNA to remove frag-ments < 300 bp.During size selection with SPRI magnetic beads, thebead:DNA ratio depends on the size of the fragmentsthat need to be separated. As the size of the fragmentsgenerated by cutting the ~424-bp metazoan 18S rRNAgene sequences will vary depending on the cut site, thebeads:DNA ratio of a specific sgRNA may need to be op-timized to remove all of the cleaved fragments. It is im-portant to remove sequence fragments generated byamplification of the cleaved host 18S rRNA genes, asthese can reduce sequencing efficiency.Sequencing library preparation for amplicons generatedusing universal 18S primersSequencing libraries for 18S amplicons generated using the“universal” 18S primers, and not cut using CRISPR-Cas9,were prepared using protocols adapted from Illumina [101].Briefly, two successive runs of PCR were performed as fol-lows: For the first PCR, 29 cycles of amplification using themodified primers TAReuk454FWD1-Nxt and TAReukREV3-Nxt (Table S3) were used to generate 380 to 450 bp ampli-cons of the V4 region of the 18S rRNA genes. The reactionconditions for the first PCR were as detailed above for thefirst CCSAS PCR, except that there was about 5 ng of gen-omic DNA in the sample. The amplicons were purified usingmagnetic Agencourt SPRI beads (Beckman Coulter) at a ratioof 1:1 (vol:vol) for beads:DNA to remove fragments < 200 bp.Five microliters of the purified amplicons from thefirst PCR were used as templates for the second PCR(index PCR). The PCR reactions and conditions for theindex PCR were the same as above the second CCSASPCR, except here the PCR amplification cycle was re-duced to be 16 cycles. The amplicon libraries generatedwere purified using magnetic Agencourt SPRI beads(Beckman Coulter) at a ratio of 1:1 (vol:vol) for beads:DNA to remove fragments < 200 bp.Sequencing library preparation for amplicons generatedusing the blocking primersPreparation of the sequencing library for the 18S ampli-cons obtained using blocking primers was similar to thatdescribed above, except that the first PCR used the primerset 18SV4-F-Nxt/18SV4-R-Nxt and the oyster-blockingprimer 18SV4-Block-oyster (Table S3), which was adaptedfrom Clerissi et al. [57], to amplify a ~377 bp fragment of18S rRNA gene that is specific to microeukaryotes but notPacific oysters. This 30-nt oyster-blocking primer wasmodified at the 3′ end with theSpacer C3 CPG (3 hydro-carbons) and contained a 10-bp overlap with the reverseprimer 18SV4-R-Nxt, which prevents the amplification ofthe 18S rRNA gene from Pacific oysters, and thus enrichesthe proportion of amplicons from microeukaryotes [57].In the first PCR, the 25-μL reaction mix comprised 1XPCR buffer (NEB), 4 mM MgCl2, 20 μg of Bovine SerumAlbumin (NEB), 200 nM of each dNTP (Invitrogen), 0.4μM of primer 18SV4-F-Nxt, 0.4 μM of primer 18SV4-R-Nxt, 1.2 μM of the oyster-blocking primer 18SV4-Block-oyster, 0.5 U of Q5® high-fidelity polymerase (NEB), andapproximately 5 ng of genomic DNA. The PCR cyclingwas as per Clerissi et al. [57], which included an initial in-cubation of 15 min at 96 °C followed by 35 cycles of de-naturation at 96 °C for 30 s, annealing at 52 °C for 30 sand elongation at 72 °C for 60 s, and a final elongation for10 min at 72 °C. The first PCR product was purified usingmagnetic Agencourt SPRI beads (Beckman Coulter) at aratio of 1:1 (vol:vol) for beads:DNA to remove fragments< 200 bp (e.g., dimers). The amplicon libraries were com-pleted as described above, with a 16-cycle index PCR toadd a Nextera® XT index (Illumina) to each 3′ and 5′ endof the amplicons.Sequencing library preparation for amplicons generatedusing non-metazoan primersThe non-metazoan primers, UNonMet primers [58], anda two-step nested-PCR were used to generate 18S ampli-cons from non-metazoan eukaryotes following delCampo et al. [70]. The first step of the nested-PCR usesthe primers 18s-EUK581-F and 18s-EUK1134-R [58](Table S3) to generate ~600-bp 18S rRNA gene frag-ments from microeukaryotes. Then, these fragments areused in a second PCR with the universal V4 primer setE572F-Nxt/E1009R-Nxt [102] (Table S3) to amplify a~440-bp 18S rRNA gene fragment to which overhangingadapter sequences (Table S3) are added that are compat-ible with the Illumina indexes and sequencing adapters.Finally, a third PCR is used to add a Nextera® XT index(Illumina) to each 3′ and 5′ end of the amplicons.In the first PCR, the 25 μL reaction mix comprised 1XPCR buffer (NEB), 4 mM MgCl2, 20 μg of Bovine SerumAlbumin (NEB), 200 nM of each dNTP (Invitrogen), 0.4μM of each primer, 0.5 U of Q5® high-fidelity polymer-ase (NEB), and approximately 5 ng of genomic DNA.The initial denaturation of 2 min at 98 °C was followedby 25 cycles of denaturation at 98 °C for 30 s, annealingat 51.5 °C for 30 s and elongation at 72 °C for 60 s, anda final elongation for 10 min at 72 °C. The first PCRproduct was purified using magnetic Agencourt SPRIbeads (Beckman Coulter) at a ratio of 1:1 (vol:vol) forbeads:DNA to remove fragments < 200bp (e.g., dimers).In the second PCR, adapted from Comeau et al. [102],the 25 μL reaction mix comprised 1X PCR buffer (NEB),4 mM MgCl2, 20 μg of Bovine Serum Albumin (NEB),200 nM of each dNTP (Invitrogen), 0.4 μM of each pri-mer, 0.5 U of Q5® high-fidelity polymerase (NEB), andapproximately 5 ng of the purified 1st PCR amplicons.There initial denaturation of 2 min at 98 °C was followedZhong et al. Microbiome (2021) 9:230 Page 12 of 17by 20 cycles of denaturation at 98 °C for 10 s, annealingat 55 °C for 30 s and elongation at 72 °C for 30 s, and afinal elongation for 10 min at 72 °C. The PCR productwas purified using magnetic Agencourt SPRI beads(Beckman Coulter) at a ratio of 1:1 (vol:vol) for beads:DNA to remove fragments < 200 bp (e.g., dimers).Last, the amplicon libraries were completed as de-scribed above, with a 16-cycles of PCR to add the Nex-tera® XT index (Illumina) to the 3′ and 5′ ends of theamplicons.Next-generation sequencing and data analysisThe DNA concentrations of the 18S amplicon sequen-cing libraries that were prepared using “universal” 18Sprimers, non-metazoan primers, blocking primers, orthe CCSAS method were measured using the Qubit®dsDNA High Sensibility Assay Kit (Invitrogen). Thefragment size for each type of library was determinedusing an Agilent bioanalyzer with the High SensitiveDNA Chip (Agilent). Equimolar amounts of these bar-coded and purified amplicon sequencing libraries werepooled and sequenced at the BRC Sequencing Core atThe University of British Columbia using MiSeq Illu-mina 2 × 300bp chemistry.Sequences were processed and analyzed using QIIMEversion 1.9 [103]. Briefly, sequences were de-multiplexedby their forward and reverse indexes, and the paired-endreads merged using PEAR version 1.10.4 [104]. Then, se-quences from different samples were pooled, and Uclust[105] was used for OTU picking with 99% nucleotide se-quence similarity. Taxonomy was assigned for represen-tative OTU sequences using the Uclust consensustaxonomy assigner and the SILVA SSU database [80](version v132, released on 13 December 2017) at a 90%confidence cutoff. The samples were normalized by ana-lyzing the relative abundance for each OTU or taxon asthe proportion of all sequences within a sample. Thedownstream analysis was conducted in R v3.5.3 [106]using packages such as Phyloseq version 1.26.1 [107]and the figures were generated using ggplot2 version3.3.0 [108] and metacoder [109].To compare microeukaryotic community structuresbetween samples and methods, the principal coordinateanalyses (PCoA) were performed on the ordination ofthe weighted Unifrac metrics [110] that were based onthe presence/absence and relative abundance of OTUs.The dissimilarity of the microeukaryotic communitycomposition between methods was examined using PER-MANOVA analysis [111] with the adonis function andBray-Curtis method in R package Vegan v.2.5 [112] andMicrobiome version 1.13.12 [113]. The similarity of themicroeukaryotic community composition betweenmethods was examined using ANOSIM analysis [114]with the anosim function and Jaccard method in R pack-age Vegan v.2.5 [112].Linear discriminant analysis effect size (LEfSe) [115]was conducted to identify oyster associated micro-eukaryotic taxa that were differentially abundant be-tween three methods, and was calculated with defaultsetting using the Galaxy modules provided by the Hut-tenhower lab. Briefly, LEfSe used the two-tailed non-parametric Kruskal-Wallis test to evaluate thesignificance of differences in taxonomic abundance be-tween three methods. Then, a set of pairwise testsamong three methods was performed using the unpairedWilcoxon test. In the end, the linear discriminant ana-lysis (LDA) was conducted to estimate the effect size ofeach differentially abundant taxa [115].AbbreviationsCRISPR: Clustered regularly interspaced short palindromic repeats;Cas: CRISPR-associated protein; CCSAS: CRISPR-Cas Selective AmpliconSequencing; gRNA: Guide RNA; sgRNA: Single-guide RNA; dsDNA: Double-stranded DNA; ssDNA: Single-stranded DNA; nt: Nucleotide; crRNA: CrisprRNA; tracrRNA: Trans-activating RNA; V4 region of the 18S rRNAgene: Variable region 4 of the 18S rRNA gene; PCR: Polymerase chainreaction; OTU: Operational taxonomic unit; SSU: Small subunit;dNTP: Deoxyribonucleotide triphosphate; bp: Base pairsSupplementary InformationThe online version contains supplementary material available at https://doi.org/10.1186/s40168-021-01180-0.Additional file 1: Table S1. List of organisms used in this study.Additional file 2: Table S2. List of the 20-nt sgRNA-target-site oligo-nucleotide sequences designed for cutting V4 region of 18S rRNA genesof ten model organisms using CRISPR-Cas9.Additional file 3: Table S3. List of primers used in this study.Additional file 4: Figure S1. Percentage of intact 18S ampliconsremaining from the model organisms after cutting with one-step CRISPR-Cas9. The concentration of intact 18S amplicons was measured using Quan-titative PCR for samples both with and without CRISPR-Cas9 treatment. Theportion of remaining intact 18S amplicons was determined by dividing theconcentration 18S amplicons in sample with CRISPR-Cas9 treatment by thatof without CRISPR-Cas9 treatment. The labels on the X-axes indicate the IDof the taxon-specific sgRNA and its corresponding host.Additional file 5: Figure S2. Eukaryotic taxa representing >1% of thesequences revealed by deep-sequencing of the 18S rRNA amplicons for oys-ter spat samples, using "universal" 18S primers (Table S3), non-metazoanprimers (Table S3), blocking primers (Table S3), or CRISPR-Cas SelectiveAmplicon Sequencing (CCSAS) combining "universal" 18S primers andCRISPR-Cas9 with pacific-oyster-specific sgRNA m258 (Table S2).Additional file 6: Figure S3. Distribution of the number of gRNA-target-sites of each metazoan and plant species from the SILVA SSU data-base v119 [80]. These gRNA-target-site oligonucleotide sequences wereidentified, using the Cas9.gRNA.oligo1() algorithm, from the V4 region ofthe 18S rRNA gene that is flanked by the 18S "universal" primer set TAR-euk454FWD1 / TAReukREV3 [54], and are used for designing and synthe-sizing the CRISPR-Cas9-compatible sgRNA. The taxon-specific gRNA-target-sites allows the design of the sgRNA to taxon-specifically cut the18S rRNA gene sequence of a metazoan or plant host but not microeu-karyotes (protists and fungi) using CRISPR-Cas9.Additional file 7: Figure S4. Summary of the number of eukaryoticspecies at each D7 taxonomic level that the sgRNA can cut at the V4region of the 18S rRNA genes that are flanked by the 18S "universal"primer set TAReuk454FWD1 / TAReukREV3 [54]. These nine sgRNAs,Zhong et al. Microbiome (2021) 9:230 Page 13 of 17which are among 205242 unique taxon-specific sgRNA designed fromthe SILVA SSU database (version 119) [80] using CasOligo, are selected toshow that some sgRNAs can target more than 1000 species and broadtaxonomic groups based on an in-silico analysis (i.e. 100% match to the18S rRNA gene sequences of the metazoan host at the gRNA-target-site,but no match for protists and fungi). Taxon names on the left side of thepanel are shown as SILVA taxonomic hierarchy with levels ranging fromD0 (kingdom) to D7. The D7 taxonomic level comprises eukaryotic classesand families.Additional file 8: Figure S5. Relative abundances of ciliates from thesubclass Scuticociliatia in eight oyster samples revealed using deep-sequencing of 18S amplicons of rRNA genes using non-metazoan primers(NM), blocking primers (BP) and CRISPR-Cas Selective Amplicon Sequen-cing (CCSAS). The relative abundances of scuticociliates are presented asa barplot (a), and as a heatmap showing the genus-level relative abun-dances of scuticociliates (b).AcknowledgementsWe gratefully acknowledge V. Au, M.L. Berbee, J. Caleta, M. Edgley, G. Hu, J.Kronstad, D.G. Moerman, G. Xiang, C. Yang, and Y. Zhang of the University ofBritish Columbia, R. Saunders of RKS Laboratories Ltd., and K.M. Miller fromFisheries and Oceans, Canada, for providing biological materials for testing(Table S1).Authors’ contributionsDuring a stimulating discussion to profile the eukaryotic microbiotaassociated with Pacific oysters, C.M.D. proposed the idea of using CRISPR-Cas9 technology to reduce the background of 18S rRNA genes and con-ducted a pilot trial. K.X.Z. conceived, developed, and implemented the CCSAS method, the CasOligo package, and the database of gRNA target sites. A.C.contributed to the optimization of the CCSAS method. C.A.S and A.M.C. wereinvolved in discussions of experimental design and interpretation of the data.K.X.Z and C.A.S. wrote the manuscript with input from all authors. The au-thors read and approved the final manuscript.Authors’ informationCurrent address of A.C. is Department of Botany, The University of BritishColumbia, Vancouver, British Columbia, Canada. C.M.D. is currently at theDepartment of Forest and Conservation Sciences, The University of BritishColumbia, Vancouver, British Columbia, Canada.FundingThis work was supported by the Gordon and Betty Moore Foundation (grant:GBMF#5600), the Natural Sciences and Engineering Research Council ofCanada (grants: RGPIN-2015-05896, RGPIN-2020-06519) and an infrastructureaward from the Canada Foundation for Innovation and British ColumbiaKnowledge Development Fund to C.A.S. A.C. was supported by an awardfrom the Pacific Research Board (grant: NPRB GSRA#1335).Availability of data and materialsAll next-generation sequencing data generated in this study have been de-posited in the NCBI Sequence Read Archive (SRA) under the accession num-bers SRR13658714 to SRR13658745. The Sanger cloning-sequencing datawere deposited in GenBank under the accession numbers MT328571 toMT328580 for 18S rRNA gene sequences of ten model organisms. All relatedscripts, functions, and algorithms for designing gRNA-target-site oligonucleo-tide sequences are included in the custom R package: CasOligo (https://github.com/kevinzhongxu/CasOligo). The gRNA-target-sites database was in-cluded in the CasOligo package, as well. The authors declare that all otherdata supporting the findings of this study are available within the paperand/or the associated supplementary files.DeclarationsEthics approval and consent to participateNot applicable.Consent for publicationNot applicable.Competing interestsThe authors declare that they have no competing interests.Author details1Department of Earth, Ocean, and Atmospheric Sciences, The University ofBritish Columbia, Vancouver, British Columbia, Canada. 2Department ofMicrobiology and Immunology, The University of British Columbia,Vancouver, British Columbia, Canada. 3Department of Botany, The Universityof British Columbia, Vancouver, British Columbia, Canada. 4Institute for theOceans and Fisheries, The University of British Columbia, Vancouver, BritishColumbia, Canada.Received: 17 February 2021 Accepted: 20 October 2021References1. Philippot L, Raaijmakers JM, Lemanceau P, van der Putten WH. Goingback to the roots: the microbial ecology of the rhizosphere. 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Eukaryotic microbiome
18S rRNA gene
Microeukaryote
CRISPR-Cas
Taxon-specific single-guide RNA
gRNA target site
CasOligo
CCSAS
Revealing the composition of the eukaryotic microbiome of oyster spat by CRISPR-Cas Selective Amplicon Sequencing (CCSAS)
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