We report 11 bacterial draft genome sequences and 38 metagenome-assembled genomes (MAGs) from marine phytoplankton exometabolite enrichments. The genomes and MAGs represent marine bacteria adapted to the metabolite environment of phycospheres, organic matter-rich regions surrounding phytoplankton cells, and are useful for exploring functional and taxonomic attributes of phytoplankton-associated bacterial communities.
ABSTRACT
We report 11 bacterial draft genome sequences and 38 metagenome-assembled genomes (MAGs) from marine phytoplankton exometabolite enrichments. The genomes and MAGs represent marine bacteria adapted to the metabolite environment of phycospheres, organic matter-rich regions surrounding phytoplankton cells, and are useful for exploring functional and taxonomic attributes of phytoplankton-associated bacterial communities.
ANNOUNCEMENT
Bacteria associated with marine phytoplankton play essential roles in global carbon and nutrient cycles (1, 2). In the nutrient-rich phycosphere surrounding phytoplankton cells, the interactions among cooccurring bacteria and between bacteria and their hosts determine community composition. The phycosphere therefore represents a unique microcosm in which ecological principles of microbial community assembly can be examined (3, 4). A high-throughput synthetic phycosphere system was established (5) in which a natural coastal seawater bacterial assemblage was passaged through 8 serial transfers in a 96-well format culture system containing different mixtures of metabolites known to be released preferentially by diatoms (6, 7) or dinoflagellates (7). Here, we report the genomes and metagenome-assembled genomes (MAGs) enriched in those synthetic phycospheres, providing a resource for understanding the functional potentials of, and ecological interactions occurring in, ocean microbial communities.
The 11 bacterial strains were isolated from 2 microbial communities, 1 supplied with a mixture of 5 diatom exometabolites (xylose, glutamate, glycolate, ectoine, and dihydroxypropanesulfonate) and the other with 5 dinoflagellate exometabolites (ribose, spermidine, trimethylamine, isethionate, and dimethylsulfoniopropionate) (5). Enrichments were serially diluted, plated onto solid marine basal medium containing each of the individual metabolites, and grown at 24°C in the dark for 1 week. Single colonies were isolated to uniform morphology on half-strength yeast extract-tryptone sea salt medium. DNA extraction was carried out using the ZymoBIOMICS DNA miniprep kit, and libraries were prepared using the KAPA Hyper prep kit (Kapa Biosystems, Wilmington, MA). Illumina MiSeq (2 × 150 bp) reads were trimmed using Trimmomatic v0.38 (8), quality was assessed using QUAST (9), and de novo assembly was performed using SPAdes v3.12.0 (10). The 16S rRNA genes were amplified using the 27F and 1492R primers (11). Sanger sequencing performed at Genewiz (South Plainfield, NJ) confirmed the purity of the amplicons.
Metagenome sequencing (Illumina NextSeq; 1 × 150 bp) was carried out on enrichment cultures representing six diatom and six dinoflagellate exometabolite treatments. As described previously (5), reads from the six diatom or the six dinoflagellate exometabolite treatments were separately coassembled using MEGAHIT v1.1.3 (12, 13). Default parameters were used for all software unless otherwise specified. Reads were mapped to the assembly with Bowtie v2.2.9 (14) and binned into MAGs using Anvi’o v4 (15, 16) and CONCOCT (17) following published protocols (18) (http://merenlab.org/data/tara-oceans-mags/). The completeness and redundancy of bins were assessed using CheckM v1.0.12 (19). Only bins with >80% completeness and <10% redundancy are reported here (Table 1). The taxonomic classifications of the MAGs were inferred using the Microbial Genome Atlas (MiGA) (http://microbial-genomes.org/) using the TypeMat database (20).
TABLE 1.
Characteristics of 11 isolate genomes and 38 MAGs obtained from serial enrichments of a coastal bacterial assemblage with metabolites from marine diatoms or dinoflagellates
| Isolate or MAG | Taxonomic classificationa | Size (Mb) | G+C content (%) | No. of reads | Coverage (×) | No. of contigs | N50 (bp) | Compl (%)/cont (%)b | SRA accession no. | GenBank accession no. | Closest genome (GenBank accession no.)c | ANI or AAI (%) | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Isolates | ||||||||||||||||||
| HF1 | Marivivens donghaensis | 3.34 | 60.8 | 317,066 | 14.2 | 24 | 292,199 | 99.7/0.8 | SRR11481811 | JAATOP000000000 | Marivivens sp. JLT3646 NZ (CP018572) | 66.7f | ||||||
| HF2 | Thalassospira lucentensis | 4.50 | 53.2 | 477,674 | 15.9 | 13 | 758,710 | 100.0/0.0 | SRR11481803 | JAATOV000000000 | Thalassospira lucentensis MCCC 1A00383 | 84.4g | ||||||
| HF7 | Pseudooceanicola sp. | 4.27 | 64.9 | 312,562 | 11.0 | 74 | 103,803 | 98.5/0.8 | SRR11481802 | JAATOW000000000 | Pseudooceanicola antarcticus (GCA_002786285) | 67.7f | ||||||
| HF9A | Phaeobacter sp. | 4.27 | 62.2 | 256,104 | 9.0 | 262 | 30,359 | 99.3/1.5 | SRR11481810 | JAATOX000000000 | Epibacterium scottomollicae (GCA_003003215) | 79.9f | ||||||
| HF9B | Vibrio diazotrophicus | 4.39 | 43.3 | 256,880 | 8.8 | 193 | 47,679 | 99.8/2.6 | SRR11481807 | JAATOR000000000 | Vibrio diazotrophicus NBRC 103148 | 91.0g | ||||||
| HF15 | Thalassospira sp. | 4.29 | 54.5 | 412,760 | 14.4 | 25 | 551,637 | 100.0/0.0 | SRR11481809 | JAAVKI000000000 | Thalassospira indica NZ (CP031555) | 88.0g | ||||||
| HF17 | Vibrio campbellii | 5.66 | 45.5 | 273,858 | 7.3 | 459 | 21,883 | 99.7/1.2 | SRR11481808 | JAATOQ000000000 | Vibrio campbellii NZ (CP019293) | 97.8g | ||||||
| HF18 | Salipiger thiooxidans | 5.26 | 67.5 | 272,102 | 7.8 | 1,007 | 9,637 | 95.4/2.8 | SRR11481806 | JAATOS000000000 | Salipiger thiooxidans (GCA_900102075) | 97.8g | ||||||
| HF31 | Celeribacter sp. | 3.60 | 59.9 | 605,892 | 25.2 | 13 | 522,533 | 99.2/0.5 | SRR11481805 | JAATOT000000000 | Celeribacter ethanolicus NZ (CP022196) | 84.5g | ||||||
| HF66 | Pseudoalteromonas sp. | 4.39 | 40.7 | 692,080 | 23.6 | 48 | 210,054 | 100.0/0.4 | SRR11481804 | JAATOU000000000 | Pseudoalteromonas shioyasakiensis (GCA_001550135) | 91.6g | ||||||
| HF70 | Vibrio hepatarius | 4.71 | 45.9 | 382,864 | 12.2 | 74 | 168,419 | 100.0/0.9 | SRR11481812 | JAATOO000000000 | Vibrio hepatarius (GCA_001274785) | 92.6g | ||||||
| MAGsd | ||||||||||||||||||
| HF-Dia02 | Oceanospirillaceae | 4.47 | 42.0 | 423,160 | 14.2 | 283 | 24,277 | 86.5/3.0 | SRR11451986 | JABXIF000000000 | Marinomonas polaris DSM 16579 | 81.6g | ||||||
| HF-Dia03 | Rhodobacterales | 3.64 | 53.4 | 1,038,613 | 42.8 | 201 | 31,207 | 95.0/0.8 | SRR11451960 | JABXHV000000000 | Labrenzia suaedae (GCA_900142725) | 64.5f | ||||||
| HF-Dia04 | Cryomorphaceae | 3.29 | 45.4 | 302,680 | 13.8 | 182 | 29,213 | 97.9/9.7 | SRR11451963 | JABXHS000000000 | Phaeocystidibacter luteus (GCA_008933115) | 82.4g | ||||||
| HF-Dia05 | Flavobacteriales | 2.53 | 40.3 | 1,017,060 | 60.3 | 97 | 147,211 | 93.1/2.7 | SRR11451996 | JABXHN000000000 | Arenibacter aquaticus (GCA_003957295) | 59.6f | ||||||
| HF-Dia07 | Alteromonadaceae | 5.10 | 47.9 | 16,809,600 | 494.4 | 123 | 84,748 | 99.9/2.8 | SRR11451997 | JABXHM000000000 | Alteromonas alba (GCA_002993365) | 77.4f | ||||||
| HF-Dia11 | Flavobacteriales | 2.94 | 32.3 | 429,240 | 21.9 | 98 | 76,707 | 98.3/1.1 | SRR11451994 | JABXHX000000000 | Tenacibaculum sp. DSM 106434 | 65.1f | ||||||
| HF-Dia12 | Gammaproteobacteria | 3.42 | 40.8 | 517,560 | 22.7 | 285 | 17,653 | 93.4/2.2 | SRR11451988 | JABXID000000000 | Psychrosphaera saromensis (GCA_002954545) | 64.2f | ||||||
| HF-Dia14 | Gammaproteobacteria | 3.64 | 51.8 | 485,333 | 20.0 | 287 | 19,154 | 95.1/4.9 | SRR11451964 | JABXHR000000000 | Thiohalobacter thiocyanaticus NZ (AP018052) | 46.4f | ||||||
| HF-Dia15 | Rhizobiales | 3.97 | 45.9 | 304,367 | 11.5 | 295 | 19,983 | 91.4/3.0 | SRR11451989 | JABXIC000000000 | Terasakiella pusilla DSM 6293 (GCA_000688235) | 68.8f | ||||||
| HF-Dia17 | Oceanospirillales | 3.38 | 51.2 | 22,932,173 | 1,017.7 | 418 | 10,263 | 91.2/3.3 | SRR11451974 | JABXHP000000000 | Marinobacterium mangrovicola (GCA_004339595) | 62.1f | ||||||
| HF-Dia18 | Rhodobacteraceae | 4.51 | 63.1 | 24,212,687 | 805.3 | 409 | 15,672 | 93.0/5.3 | SRR11451991 | JABXIA000000000 | Leisingera daeponensis DSM 23529 | 86.7g | ||||||
| HF-Dia21 | Oceanospirillales | 4.53 | 40.5 | 1,265,380 | 41.9 | 96 | 99,744 | 99.2/0.4 | SRR11451993 | JABXHY000000000 | Pleionea mediterranea (GCA_003148745) | 62.4f | ||||||
| HF-Dia22 | Flavobacteriia | 4.70 | 40.8 | 463,733 | 14.8 | 179 | 42,273 | 98.6/1.4 | SRR11451985 | JABXHO000000000 | “Candidatus Fluviicola riflensis” (CP022585) | 56.2f | ||||||
| HF-Dia23 | Tenacibaculum sp. | 3.20 | 31.7 | 424,533 | 19.9 | 86 | 70,967 | 98.5/0.8 | SRR11451962 | JABXHT000000000 | Tenacibaculum discolor (GCA_003664185) | 97.8g | ||||||
| HF-Dia27 | Oceanospirillales | 3.64 | 45.2 | 2,817,360 | 116.1 | 196 | 31,979 | 98.3/2.6 | SRR11451965 | JABXHQ000000000 | Pleionea mediterranea (GCA_003148745) | 64.1f | ||||||
| HF-Dia28e | Ruegeria pomeroyi | 4.51 | 64.0 | 60,900,033 | 2,025.5 | 200 | 33,165 | 97.6/2.2 | SRR9668573 | JABXIZ000000000 | Ruegeria pomeroyi DSS-3 | 100.0g | ||||||
| HF-Dia32 | Flavobacteriales | 3.09 | 45.8 | 861,080 | 41.8 | 76 | 69,153 | 97.7/0.5 | SRR11451995 | JABXHW000000000 | Phaeocystidibacter luteus (GCA_008933115) | 67.2f | ||||||
| HF-Dia38 | Cyclobacteriaceae | 3.39 | 40.8 | 2,743,640 | 121.4 | 460 | 8,688 | 86.7/4.1 | SRR11451992 | JABXHZ000000000 | Algoriphagus kandeliae (GCA_004571135) | 82.1g | ||||||
| HF-Dia39 | Marivivens sp. | 2.49 | 56.7 | 7,811,960 | 470.6 | 142 | 23,748 | 95.1/1.0 | SRR11451961 | JABXHU000000000 | Marivivens sp. JLT3646 NZ (CP018572) | 97.2g | ||||||
| HF-Dia40 | Vibrionaceae | 4.24 | 46.3 | 7,453,920 | 263.7 | 357 | 16,672 | 96.6/2.1 | SRR11451990 | JABXIB000000000 | Vibrio hepatarius (GCA_001274785) | 92.6g | ||||||
| HF-Din01 | Salipiger sp. | 4.40 | 68.0 | 10,301,867 | 351.2 | 701 | 7,265 | 86.8/2.7 | SRR11451976 | JABXIO000000000 | Salipiger thiooxidans (GCA_900102075) | 98.0g | ||||||
| HF-Din02 | Methylocystaceae | 4.09 | 48.4 | 13,224,333 | 485.0 | 69 | 276,225 | 100.0/1.0 | SRR11451984 | JABXIG000000000 | Terasakiella pusilla DSM 6293 | 79.0f | ||||||
| HF-Din03e | Ruegeria pomeroyi | 4.54 | 64.0 | 36,062,733 | 1,191.5 | 78 | 105,484 | 98.7/0.7 | SRR9668574 | JABXIY000000000 | Ruegeria pomeroyi DSS-3 | 100.0g | ||||||
| HF-Din05 | Gammaproteobacteria | 3.45 | 45.4 | 425,500 | 18.5 | 223 | 24,639 | 93.7/2.2 | SRR11451969 | JABXIU000000000 | Pseudoalteromonas phenolica O-BC30 GCA 004103265 | 48.7f | ||||||
| HF-Din08 | Oceanospirillaceae | 5.78 | 58.6 | 3,787,827 | 98.3 | 249 | 42,217 | 98.1/2.0 | SRR11451978 | JABXIM000000000 | Marinobacterium rhizophilum DSM 18822 | 68.5g | ||||||
| HF-Din09 | Flammeovirgaceae | 4.04 | 42.1 | 2,308,187 | 85.7 | 543 | 9,559 | 92.8/2.7 | SRR11451975 | JABXIP000000000 | Roseivirga spongicola (GCA_004103265) | 81.4f | ||||||
| HF-Din10 | Alphaproteobacteria | 3.00 | 54.3 | 1,760,000 | 88.0 | 309 | 14,274 | 81.9/1.7 | SRR11451968 | JABXIV000000000 | Hankyongella ginsenosidimutans W1-2-3 (CP039704) | 50.2f | ||||||
| HF-Din11 | Vibrio campbellii | 5.63 | 45.3 | 36,542,453 | 973.6 | 92 | 123,020 | 100.0/0.1 | SRR11451983 | JABXIH000000000 | Vibrio campbellii NZ (CP019293) | 97.9g | ||||||
| HF-Din12 | Oceanospirillales | 2.58 | 41.6 | 1,683,880 | 97.9 | 62 | 69,368 | 98.1/4.1 | SRR11451973 | JABXIQ000000000 | Kangiella profundi NZ (CP025120) | 63.5f | ||||||
| HF-Din13 | Campylobacteraceae | 2.76 | 28.4 | 1,264,080 | 68.7 | 38 | 142,008 | 99.2/1.2 | SRR11451982 | JABXII000000000 | Halarcobacter bivalviorum strain LMG 26154 (CP031217) | 85.2g | ||||||
| HF-Din14 | Rhodobacteraceae | 3.53 | 59.9 | 13,734,053 | 583.6 | 64 | 109,963 | 98.9/0.5 | SRR11451979 | JABXIL000000000 | Celeribacter halophilus (GCA_003254175) | 82.0g | ||||||
| HF-Din16 | Flavobacteriia | 1.81 | 37.0 | 97,740 | 8.1 | 234 | 9,657 | 83.0/2.3 | SRR11451970 | JABXIT000000000 | Maribacter cobaltidurans NZ (CP022957) | 57.8f | ||||||
| HF-Din17 | Gammaproteobacteria | 4.03 | 44.2 | 354,640 | 13.2 | 487 | 12,701 | 85.8/4.3 | SRR11451967 | JABXIW000000000 | Pleionea mediterranea (GCA_003148745) | 49.3f | ||||||
| HF-Din19 | Flavobacteriales | 2.37 | 29.8 | 260,700 | 16.5 | 69 | 52,100 | 97.9/1.4 | SRR11451981 | JABXIJ000000000 | Polaribacter porphyrae (GCA_002954685) | 68.7f | ||||||
| HF-Din21 | Kordiimonadaceae | 3.62 | 53.6 | 1,908,947 | 79.1 | 96 | 81,569 | 97.1/1.8 | SRR11451971 | JABXIS000000000 | Kordiimonas lipolytica (GCA_001550065) | 76.8f | ||||||
| HF-Din22 | Cyclobacteriaceae | 3.65 | 40.7 | 1,498,933 | 61.6 | 38 | 178,308 | 99.6/0.6 | SRR11451977 | JABXIN000000000 | Algoriphagus kandeliae (GCA_004571135) | 81.1g | ||||||
| HF-Din24 | Gammaproteobacteria | 3.50 | 44.0 | 22,920,333 | 982.3 | 151 | 35,787 | 98.5/2.3 | SRR11451980 | JABXIK000000000 | Oceanobacter kriegii DSM 6294 (GCA_000422845) | 54.6f | ||||||
| HF-Din29 | Gammaproteobacteria | 2.11 | 49.9 | 753,973 | 53.6 | 305 | 8,218 | 82.8/2.9 | SRR11451972 | JABXIR000000000 | Spongiibacter marinus DSM 19753 (GCA_000422345) | 51.2f | ||||||
Taxonomic classification of isolates is based on >98% similarity of 16S rRNA genes or >98% similarity of hsp60 genes (Vibrio only). Taxonomic classification of metagenome-assembled genomes (MAGs) is based on the lowest taxonomic level with a P value of ≤0.015 as calculated in MiGA using the TypeMat database, in which average nucleotide identity (ANI) is generally reported for similarities of ≥85%, and average amino acid identity (AAI) is reported if the ANI is <85%.
Compl, completeness level; cont, contamination level.
Closest genome was determined by MiGA analysis using the TypeMat database.
MAGs that start with HF-Dia are assembled from the six diatom metagenomes, while MAGs that start with HF-Din are assembled from the six dinoflagellate metagenomes.
Previously published (5).
AAI.
ANI.
Data availability.
All data are deposited under GenBank BioProject number PRJNA553557. The raw reads of the genomic data for the isolates are deposited under SRA accession numbers SRR11481802 to SRR11481812. The original raw reads of the metagenomic data used for MAG assembly are deposited under SRA accession numbers SRR11434620 to SRR11434631. The assemblies for isolates and MAGs are deposited under the GenBank accession numbers listed in Table 1; the versions described in this paper are the first versions.
ACKNOWLEDGMENTS
We thank Julian Damashek for bioinformatic advice.
This work was supported by Simons Foundation grant 542391 to M.A.M. within the Principles of Microbial Ecosystems Collaborative. Sequencing was carried out at the Georgia Genomics and Bioinformatics Core (GGBC) (Athens, GA).
We declare no competing interests.
REFERENCES
- 1.Amin SA, Parker MS, Armbrust EV. 2012. Interactions between diatoms and bacteria. Microbiol Mol Biol Rev 76:667–684. doi: 10.1128/MMBR.00007-12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Azam F, Fenchel T, Field JG, Gray JS, Meyer-Reil LA, Thingstad F. 1983. The ecological role of water-column microbes in the sea. Mar Ecol Prog Ser 10:257–263. doi: 10.3354/meps010257. [DOI] [Google Scholar]
- 3.Azam F, Malfatti F. 2007. Microbial structuring of marine ecosystems. Nat Rev Microbiol 5:782–791. doi: 10.1038/nrmicro1747. [DOI] [PubMed] [Google Scholar]
- 4.Seymour JR, Amin SA, Raina J-B, Stocker R. 2017. Zooming in on the phycosphere: the ecological interface for phytoplankton–bacteria relationships. Nat Microbiol 2:17065. doi: 10.1038/nmicrobiol.2017.65. [DOI] [PubMed] [Google Scholar]
- 5.Fu H, Uchimiya M, Gore J, Moran MA. 2020. Ecological drivers of bacterial community assembly in synthetic phycospheres. Proc Natl Acad Sci U S A 117:3656–3662. doi: 10.1073/pnas.1917265117. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Amin SA, Hmelo LR, van Tol HM, Durham BP, Carlson LT, Heal KR, Morales RL, Berthiaume CT, Parker MS, Djunaedi B, Ingalls AE, Parsek MR, Moran MA, Armbrust EV. 2015. Interaction and signalling between a cosmopolitan phytoplankton and associated bacteria. Nature 522:98–101. doi: 10.1038/nature14488. [DOI] [PubMed] [Google Scholar]
- 7.Landa M, Burns AS, Roth SJ, Moran MA. 2017. Bacterial transcriptome remodeling during sequential co-culture with a marine dinoflagellate and diatom. ISME J 11:2677–2690. doi: 10.1038/ismej.2017.117. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Bolger AM, Lohse M, Usadel B. 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120. doi: 10.1093/bioinformatics/btu170. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Gurevich A, Saveliev V, Vyahhi N, Tesler G. 2013. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29:1072–1075. doi: 10.1093/bioinformatics/btt086. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA. 2012. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 19:455–477. doi: 10.1089/cmb.2012.0021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Frank JA, Reich CI, Sharma S, Weisbaum JS, Wilson BA, Olsen GJ. 2008. Critical evaluation of two primers commonly used for amplification of bacterial 16S rRNA genes. Appl Environ Microbiol 74:2461–2470. doi: 10.1128/AEM.02272-07. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Li D, Liu CM, Luo R, Sadakane K, Lam TW. 2015. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31:1674–1676. doi: 10.1093/bioinformatics/btv033. [DOI] [PubMed] [Google Scholar]
- 13.Li D, Luo R, Liu CM, Leung CM, Ting HF, Sadakane K, Yamashita H, Lam TW. 2016. MEGAHIT v1.0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods 102:3–11. doi: 10.1016/j.ymeth.2016.02.020. [DOI] [PubMed] [Google Scholar]
- 14.Langmead B, Salzberg S. 2012. Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357–359. doi: 10.1038/nmeth.1923. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Eren AM, Esen ÖC, Quince C, Vineis JH, Morrison HG, Sogin ML, Delmont TO. 2015. Anvi’o: an advanced analysis and visualization platform for ’omics data. PeerJ 3:e1319. doi: 10.7717/peerj.1319. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Delmont TO, Eren AM. 2016. Identifying contamination with advanced visualization and analysis practices: metagenomic approaches for eukaryotic genome assemblies. PeerJ 4:e1839. doi: 10.7717/peerj.1839. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Alneberg J, Bjarnason BS, De Bruijn I, Schirmer M, Quick J, Ijaz UZ, Lahti L, Loman NJ, Andersson AF, Quince C. 2014. Binning metagenomic contigs by coverage and composition. Nat Methods 11:1144–1146. doi: 10.1038/nmeth.3103. [DOI] [PubMed] [Google Scholar]
- 18.Delmont TO, Quince C, Shaiber A, Esen ÖC, Lee ST, Rappé MS, McLellan SL, Lücker S, Eren AM. 2018. Nitrogen-fixing populations of Planctomycetes and Proteobacteria are abundant in surface ocean metagenomes. Nat Microbiol 3:804–813. doi: 10.1038/s41564-018-0176-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. 2015. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res 25:1043–1055. doi: 10.1101/gr.186072.114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Rodriguez-R LM, Gunturu S, Harvey WT, Rosselló-Mora R, Tiedje JM, Cole JR, Konstantinidis KT. 2018. The Microbial Genomes Atlas (MiGA) webserver: taxonomic and gene diversity analysis of Archaea and Bacteria at the whole genome level. Nucleic Acids Res 46:W282–W288. doi: 10.1093/nar/gky467. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All data are deposited under GenBank BioProject number PRJNA553557. The raw reads of the genomic data for the isolates are deposited under SRA accession numbers SRR11481802 to SRR11481812. The original raw reads of the metagenomic data used for MAG assembly are deposited under SRA accession numbers SRR11434620 to SRR11434631. The assemblies for isolates and MAGs are deposited under the GenBank accession numbers listed in Table 1; the versions described in this paper are the first versions.
