Here, we report results from PCR and sequencing of bacterial 16S rRNA genes from leaf and root surfaces from nine submerged aquatic vegetation (SAV) samples comprising five species. Samples were from four sites along the Potomac River

Alexiev, Alexandra

Eisen, Jonathan A

Lang, Jenna M

Vann, Laura E

English

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UC DavisUC Davis Previously Published WorksTitleBacterial Community Sequences of Submerged Aquatic Vegetation in the Potomac RiverPermalinkhttps://escholarship.org/uc/item/9kk096hnJournalMicrobiology Resource Announcements, 9(1)ISSN2576-098XAuthorsAlexiev, AlexandraVann, Laura ELang, Jenna Met al.Publication Date2020-01-02DOI10.1128/mra.01175-19 Peer reviewedeScholarship.org Powered by the California Digital LibraryUniversity of CaliforniaBacterial Community Sequences of Submerged AquaticVegetation in the Potomac RiverAlexandra Alexiev,a,b,c,d Laura E. Vann,b,c,d,e Jenna M. Lang,b,c,d Jonathan A. Eisenb,c,daDepartment of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado, USAbDepartment of Evolution and Ecology, University of California, Davis, California, USAcDepartment of Medical Microbiology and Immunology, University of California, Davis, California, USAdGenome Center, University of California, Davis, California, USAeGenomics and Bioinformatics Department, Novozymes, Davis, California, USAABSTRACT Here, we report results from PCR and sequencing of bacterial 16S rRNAgenes from leaf and root surfaces from nine submerged aquatic vegetation (SAV)samples comprising five species. Samples were from four sites along the PotomacRiver.Submerged aquatic vegetation (SAV) comprises plants that grow fully submerged inmarine or freshwater most of the time and are often restricted to shallow water (1).They are globally distributed, provide habitat and food for coastal fauna, absorb waveenergy and nutrients, produce oxygen, and stabilize coastal sediment (2). Humanactivities have heavily affected coastal regions via pollution and reduced suitable SAVhabitat, particularly in the Chesapeake Bay (3). The presence of SAV is also known toinfluence the structure, density, and metabolic activity of sediment and rhizospheremicrobial communities (4–8). Furthermore, there is evidence that different SAV speciestake up different amounts of nitrogen and phosphorus, which can, in turn, affect theabundance of denitrifying bacteria on their roots (8). This paper reports the results of16S rRNA gene PCR and sequencing of samples from roots and leaves of five SAVspecies at four sites along the Potomac River, which feeds into the Chesapeake Bay(Table 1).Triplicate leaf and root samples were taken from an individual of each visuallydistinct species of SAV identified at each site and stored in a sterile tube of Xpeditionlysis/stabilization solution (Zymo Research, Irvine, CA) at room temperature until DNAextraction. Sites were named P1 to P4, with P1 being the most freshwater site (0.18 ppt)and P4 being the most marine (8.08 ppt) and closest to the Chesapeake Bay. Briefly, weprocessed the samples as follows. DNA was extracted using the PowerSoil DNAisolation kit (MoBio Laboratories, Carlsbad, CA). PCR amplification of the V4 region ofthe 16S rRNA gene was conducted with the bacterial/archaeal primers 515F/806R (9)and custom barcodes (Invitrogen, Carlsbad, CA) (10). Samples were sequenced on aMiSeq instrument (Illumina, San Diego, CA) at the University of California (UC) DavisGenome Center Sequencing Core, using the MiSeq 500-cycle v2 kit for 250-bp paired-end sequencing. This yielded 1,070,385 reads for 56 samples, ranging from 6 reads persample to 100,126 reads per sample.Sequence processing was done on a lab server (Linux 3.2.0-29-generic number46-Ubuntu, 16 central processing units [CPUs] and 48 GB of RAM). Demultiplexing useda custom script which automates quality assessment and trimming (https://github.com/gjospin/scripts/blob/master/Demul_trim_prep.pl). The script trims bases from the rightside of the reads that are below Q20 and then discards reads less than 35 bp long. Oncesequences are trimmed, they are merged. Open-reference operational taxonomic unitsCitation Alexiev A, Vann LE, Lang JM, Eisen JA.2020. Bacterial community sequences ofsubmerged aquatic vegetation in the PotomacRiver. Microbiol Resour Announc 9:e01175-19.https://doi.org/10.1128/MRA.01175-19.Editor Frank J. Stewart, Georgia Institute ofTechnologyCopyright © 2020 Alexiev et al. This is anopen-access article distributed under the termsof the Creative Commons Attribution 4.0International license.Address correspondence to Jonathan A. Eisen,jaeisen@ucdavis.edu.Received 30 September 2019Accepted 20 November 2019Published 2 January 2020AMPLICON SEQUENCE COLLECTIONScrossmVolume 9 Issue 1 e01175-19 mra.asm.org 1(OTUs) were picked at a 97% cutoff with QIIME version 1.9.0 (11) and the Greengenesdatabase (12). Reads identified as being from chloroplasts or mitochondria, flagged aschimeric, or not assigned a taxonomy were removed from further processing. Detailedprotocols and workflow documentation are available online (https://doi.org/10.6084/m9.figshare.5860926.v3).There were 1,070,385 reads total for 56 samples after the above sequence-TABLE 1 Sample collection listSample descriptionNo. of readsper sample Raw count in bpTrimmed count inbp (% of raw count)Merged count inbp (% of raw count)Kit.control 25 140 87 (62.14) 54 (38.57)Kit.control 22 67 48 (71.64) 31 (46.27)Site.P1.UnkSps.Leaf 11 64 46 (71.88) 28 (43.75)Site.P1.UnkSps.Leaf 2,815 3,466 3,293 (95.01) 2,991 (86.3)Site.P1.UnkSps.Leaf 9,023 12,438 11,785 (94.75) 10,174 (81.8)Site.P1.UnkSps.Root 84,120 102,951 97,670 (94.87) 91,468 (88.85)Site.P1.UnkSps.Root 100,126 130,084 120,239 (92.43) 110,333 (84.82)Site.P1.UnkSps.Root 90,173 112,716 106,847 (94.79) 99,397 (88.18)Site.P1.Vallisneria_sps_unk.Leaf 104 437 366 (83.75) 261 (59.73)Site.P1.Vallisneria_sps_unk.Leaf 6,982 13,335 12,735 (95.5) 12,145 (91.08)Site.P1.Vallisneria_sps_unk.Leaf 16,302 24,985 23,611 (94.5) 22,038 (88.2)Site.P1.Vallisneria_sps_unk.Root 22,369 32,515 31,401 (96.57) 30,335 (93.3)Site.P1.Vallisneria_sps_unk.Root 14,430 25,714 24,428 (95) 22,771 (88.55)Site.P1.Vallisneria_sps_unk.Root 46,096 67,889 64,803 (95.45) 61,161 (90.09)Site.P1.Ruppia_maritima.Leaf 1,237 4,174 4,045 (96.91) 3,813 (91.35)Site.P1.Ruppia_maritima.Leaf 34 263 230 (87.45) 147 (55.89)Site.P1.Ruppia_maritima.Leaf 280 882 811 (91.95) 714 (80.95)Site.P1.Ceratophyllum_demersum.Leaf 4,041 10,431 10,180 (97.59) 9,805 (94)Site.P1.Ceratophyllum_demersum.Leaf 2,037 4,099 3,908 (95.34) 3,627 (88.48)Site.P1.Ceratophyllum_demersum.Leaf 6,237 21,693 21,296 (98.17) 20,790 (95.84)Site.P2.Potamogeton_perfoliatus.Leaf 20,481 50,697 49,585 (97.81) 48,095 (94.87)Site.P2.Potamogeton_perfoliatus.Leaf 13,513 37,567 36,566 (97.34) 35,302 (93.97)Site.P2.Potamogeton_perfoliatus.Leaf 16,021 38,842 37,440 (96.39) 35,605 (91.67)Site.P2.Potamogeton_perfoliatus.Root 39,788 46,487 45,037 (96.88) 42,876 (92.23)Site.P2.Potamogeton_perfoliatus.Root 11,998 14,095 13,611 (96.57) 12,944 (91.83)Site.P2.Potamogeton_perfoliatus.Root 31,799 35,214 34,276 (97.34) 32,998 (93.71)Site.P2.Vallisneria_sps_unk.Leaf1 16,774 60,180 59,031 (98.09) 57,467 (95.49)Site.P2.Vallisneria_sps_unk.Leaf1 14,042 44,402 43,358 (97.65) 41,775 (94.08)Site.P2.Vallisneria_sps_unk.Leaf1 20,938 84,103 81,431 (96.82) 77,746 (92.44)Site.P2.Vallisneria_sps_unk.Root 98,013 128,459 120,010 (93.42) 112,773 (87.79)Site.P2.Vallisneria_sps_unk.Root 22,709 33,065 30,031 (90.82) 27,348 (82.71)Site.P2.Vallisneria_sps_unk.Root 26,191 40,148 37,109 (92.43) 34,564 (86.09)Site.P2.Vallisneria_sps_unk.Leaf2 11,863 37,872 36,591 (96.62) 34,886 (92.12)Site.P2.Vallisneria_sps_unk.Leaf2 172 720 663 (92.08) 550 (76.39)Site.P2.Vallisneria_sps_unk.Leaf2 5,914 20,316 19,772 (97.32) 19,030 (93.67)Site.P2.Myriophyllum_spicatum.Leaf 33,577 119,521 117,639 (98.43) 115,176 (96.36)Site.P2.Myriophyllum_spicatum.Leaf 32,088 106,020 103,336 (97.47) 98,959 (93.34)Site.P2.Myriophyllum_spicatum.Leaf 38,571 113,778 110,832 (97.41) 106,517 (93.62)Site.P3.Myriophyllum_spicatum.Leaf 8,767 26,684 26,169 (98.07) 25,325 (94.91)Site.P3.Myriophyllum_spicatum.Leaf 4,555 10,840 10,498 (96.85) 10,095 (93.13)Site.P3.Myriophyllum_spicatum.Leaf 452 1,534 1,466 (95.57) 1,336 (87.09)Site.P3.Myriophyllum_spicatum.Root 18,799 23,568 22,105 (93.79) 20,838 (88.42)Site.P3.Myriophyllum_spicatum.Root 42,702 51,778 47,966 (92.64) 45,262 (87.42)Site.P3.Myriophyllum_spicatum.Root 16,185 18,642 17,771 (95.33) 17,138 (91.93)Site.P3.Vallisneria_sps_unk.Leaf 1,692 3,746 3,657 (97.62) 3,563 (95.11)Site.P3.Vallisneria_sps_unk.Leaf 53 259 165 (63.71) 107 (41.31)Site.P3.Vallisneria_sps_unk.Leaf 12,516 20,122 19,408 (96.45) 18,394 (91.41)Site.P3.Vallisneria_sps_unk.Root 41,072 49,833 47,140 (94.6) 44,681 (89.66)Site.P3.Vallisneria_sps_unk.Root 34,861 41,769 40,052 (95.89) 37,960 (90.88)Site.P3.Vallisneria_sps_unk.Root 7,965 9,528 8,991 (94.36) 8,594 (90.2)Site.P4.Myriophyllum_spicatum.Leaf 7,395 10,019 9,588 (95.7) 9,240 (92.22)Site.P4.Myriophyllum_spicatum.Leaf 6 29 25 (86.21) 12 (41.38)Site.P4.Myriophyllum_spicatum.Leaf 4,404 6,691 5,855 (87.51) 5,498 (82.17)Site.P4.Myriophyllum_spicatum.Root 2,935 4,721 4,510 (95.53) 4,254 (90.11)Site.P4.Myriophyllum_spicatum.Root 4,988 9,583 9,088 (94.83) 8,510 (88.8)Site.P4.Myriophyllum_spicatum.Root 122 411 314 (76.4) 221 (53.77)Alexiev et al.Volume 9 Issue 1 e01175-19 mra.asm.org 2processing steps. The average number of reads per sample was 19,114 and ranged from6 to 100,126. Sample-specific metrics are listed in Table 1. We identified 6,634 microbialOTUs total from our samples (n  40). OTUs assigned to the genera Methylotenera (2.2%of all sequences), Sulfurimonas (1.4%), and Sulfuricurvum (2.9%) and the family Rhodo-cyclaceae (1.4%) are the most common among all the samples. Leaf samples weredominated by Methylotenera mobilis (3.5% of leaf-associated sequences) and the genusPlanctomyces (2.2%), whereas root samples were dominated by Sulfuricurvum kujiense(6.8% of root-associated sequences), the genus Sulfurimonas (6.0%), and the familyRhodocyclaceae (5.7%).Data availability. Sequences from this data set are available through NCBI underthe accession number PRJNA305164. Detailed protocols and workflow documentationare available on FigShare (https://doi.org/10.6084/m9.figshare.5860926.v3).ACKNOWLEDGMENTSThis work was supported by a grant from the Gordon and Betty Moore Foundation(GBMF333), “Investigating the co-evolutionary relationships between seagrasses andtheir microbial symbionts.”We also thank Greg Meyer and Andrew Whitehead for coordinating travel to thesites.REFERENCES1. Les DH, Cleland MA, Waycott M. 1997. Phylogenetic studies in Alisma-tidae, II: evolution of marine angiosperms (seagrasses) and hydrophily.Syst Bot 22:443– 463. https://doi.org/10.2307/2419820.2. Williams SL, Heck KL, Jr. 2001. Seagrass community ecology, p 317–337.In Bertness MD, Gaines SD, Hay ME (ed), Marine community ecology.Sinauer Associates, Sunderland, MA.3. Kahn JR, Kemp WM. 1985. Economic losses associated with the degra-dation of an ecosystem: the case of submerged aquatic vegetation inChesapeake Bay. 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Bacterial Community Sequences of Submerged Aquatic Vegetation in the Potomac River

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Bacterial Community Sequences of Submerged Aquatic Vegetation in the Potomac River.

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