Sediment and groundwater metagenomes from subsurface microbial communities from the Oak Ridge National Laboratory Oak Ridge Reservation, Oak Ridge, Tennessee, USA
Lauren M. Lui, Torben N. Nielsen, Heidi J. Smith, John-Marc Chandonia, Jennifer V. Kuehl, Fangchao Song, Andrew Sczesnak, Andrew Hendrickson, Terry C. Hazen, Matthew W. Fields, Adam P. Arkin

TL;DR
This paper presents metagenomic data from sediment and groundwater samples collected at Oak Ridge, TN, to study subsurface microbial communities and their response to contamination.
Contribution
The study provides new metagenomic datasets from subsurface environments to explore microbial metabolism and community differences.
Findings
Metagenomes were collected from 26 sediment and 9 groundwater samples at Oak Ridge.
Samples were analyzed to study microbial metabolism and contamination effects on communities.
The dataset includes comparisons between groundwater and sediment microbial communities.
Abstract
We report 26 subsurface sediment and 9 groundwater metagenomes from the Oak Ridge Reservation at Oak Ridge, TN, USA. Samples were collected from various depths and phases (attached vs planktonic) to study subsurface microbial metabolism, the effect of contamination on microbial communities, and differences across groundwater and sediment microbial communities.
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
| Sample origin | Sample description | SRA accession(s) | NCBI BioSample accession for co-assembly |
|---|---|---|---|
| GW271 groundwater well | 0.1 μm filter, filtered onsite at ORNL |
| |
| GW271 groundwater well | 0.2 μm filter, filtered at LBNL |
| |
| GW271 groundwater well | 0.2 μm filter, filtered onsite at ORNL |
| |
| FW106 groundwater well | 0.1 μm filter, filtered onsite at ORNL |
| |
| FW106 groundwater well | 0.2 μm filter, filtered at LBNL |
| |
| FW106 groundwater well | 0.2 μm filter, filtered onsite at ORNL |
| |
| FW115-24 groundwater well | 0.1 μm filter, filtered onsite at ORNL |
| Same as SRA accession |
| FW115-24 groundwater well | 0.2 μm filter, filtered at LBNL |
| |
| FW115-24 groundwater well | 0.2 μm filter, filtered onsite at ORNL |
| |
| Groundwater extraction negative control | Control |
| No co-assembly attempted |
| Groundwater reagent water extraction negative control | Control |
| No co-assembly attempted |
| EB271-02-01 sediment core | Vadose zone, 91.44–128.85 cm bgs |
| |
| EB271-02-02 sediment core | Vadose zone, 128.85–166.25 cm bgs |
| |
| EB271-02-03 sediment core | Vadose zone, 166.25–182.88 cm bgs |
| |
| EB271-03-01 sediment core | Vadose zone, 182.88–211 cm bgs |
| |
| EB271-03-02 sediment core | Vadose zone, 211.26–239.64 cm bgs |
| |
| EB271-03-03 sediment core | Vadose zone, 239.64–274.32 cm bgs |
| |
| EB271-04-01 sediment core | Variably saturated zone, 274.32–297.83 cm bgs |
| |
| EB271-04-02 sediment core | Variably saturated zone, 297.83–321.35 cm bgs |
| |
| EB271-04-03 sediment core | Variably saturated zone, 321.35–344.86 cm bgs |
| |
| EB271-04-04 sediment core | Variably saturated zone, 344.86–365.76 cm bgs |
| |
| EB271-05-01 sediment core | Saturated zone, 365.76–383.27 cm bgs |
| |
| EB271-05-02 sediment core | Saturated zone, 383.27–400.78 cm bgs |
| |
| EB271-05-03 sediment core | Saturated zone, 400.78–418.29 cm bgs |
| |
| EB271-05-04 sediment core | Saturated zone, 418.29–438.72 cm bgs |
| Same as SRA accession |
| EB106-02-01 sediment core | Vadose zone, 91.44–127.22 cm bgs |
| |
| EB106-02-02 sediment core | Vadose zone, 127.22–163.00 cm bgs |
| |
| EB106-02-03 sediment core | Vadose zone, 163.00–182.88 cm bgs |
| |
| EB106-03-01 sediment core | Vadose zone, 182.88–197.58 cm bgs |
| |
| EB106-03-02 sediment core | Vadose zone, 197.58–212.27 cm bgs |
| |
| EB106-03-03 sediment core | Vadose zone, 212.27–226.97 cm bgs |
| Same as SRA accession |
| EB106-03-04 sediment core | Vadose zone, 226.97–241.66 cm bgs |
| Same as SRA accession |
| EB106-03-05 sediment core | Vadose zone, 241.66–256.36 cm bgs |
| Same as SRA accession |
| EB106-04-01 sediment core | Vadose zone, 274.32–291.47 cm bgs |
| Same as SRA accession |
| EB106-04-04 sediment core | Variably saturated zone, 325.76–342.90 cm bgs |
| Same as SRA accession |
| EB106-05-04 sediment core | Saturated zone, 410.65–425.61 cm bgs |
| Same as SRA accession |
| EB106-05-06 sediment core | Saturated zone 440.57–457.20 cm bgs |
| Same as SRA accession |
| Sediment extraction negative control | Control |
| No co-assembly attempted |
| Sediment extraction negative control | Control |
| No co-assembly attempted |
- —U.S. Department of Energyhttp://dx.doi.org/10.13039/100000015
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Taxonomy
TopicsMicrobial Community Ecology and Physiology · Methane Hydrates and Related Phenomena · Genomics and Phylogenetic Studies
ANNOUNCEMENT
The terrestrial subsurface is a critical biome for the Earth’s biogeochemical cycling and sources of consumable freshwater; however, we still know little about the microbial communities that drive the biogeochemical processes and how they are impacted by environmental conditions (1). Environmental sequencing has provided the best avenue for studying these microbial communities, especially since many species have unknown conditions for lab culturing (2). In this study, we generated metagenomes to study the subsurface microbiome from the centimeter scale to the field scale (3) and to study the relationship between the sediment and water communities at the Oak Ridge Reservation, a site that has been impacted by heavy metal, nitrate, and radionuclide contamination due to leaching from waste disposal ponds (4, 5). We generated shotgun metagenomics data from 77 sediment samples and 33 groundwater samples.
Sediment samples were taken from the boreholes EB106 and EB271, whose drilling, geology, location, and biogeochemistry are described in reference 6. Each borehole was cut into approximately 22.86 cm cores. From each core, we took 5 g replicates for DNA extraction using a modified protocol of the Qiagen PowerMax Soil kit to reduce bead-beating (and thus DNA fragmentation) as described in reference 7 and documented on Protocols.io (dx.doi.org/10.17504/protocols.io.kqdg3kepqv25/v1). For EB271, cores had 1–3 replicates. For EB106, for 12 cores, we were able to obtain enough DNA for metagenomics sequencing. The first five cores had three replicates. The other cores only have one replicate, either due to poor DNA yield or failed metagenomics library prep, and some required ~20 g of sediment to obtain enough DNA for sequencing, as indicated in Table 1.
Water samples were collected from adjacent groundwater wells (FW106, FW115-24, GW271) to the boreholes 1 week after drilling. Well construction, location, and biogeochemistry are described in reference 6. On the day of sampling, 5 L of water was filtered sequentially in an anaerobic chamber through 0.2 and 0.1 um PES filters. Water was also shipped to Lawrence Berkeley Lab overnight, and biomass from 2 L of water was collected on 0.2 um PES filters. DNA was extracted from filters using the same method as the sediment.
Metagenomics sequencing libraries were prepared using the Illumina Nextera Flex Kit (now called Illumina DNA Prep Kit), according to the manufacturer’s instructions. Library concentration was measured using a Qubit 3 Fluorometer. Samples were sequenced by QB3 Genomics, UC Berkeley, Berkeley, CA (RRID:SCR_022170) using 2 × 150 bp on an Illumina HiSeq4000.
Illumina reads were filtered for phiX174 and trimmed to remove any residual adapter sequences using BBTools Version 38.86 (8) using parameters “bf1 ktrim=r k=23 mink=11” along with a database of Illumina adapters and phiX174 spike-in. The resulting read set was assembled using SPAdes Version 3.15.4 (9, 10) with parameters “—memory 1024 —only-assembler —meta -k 21,33,55,77,99,127.” The SPAdes built-in error correction was disabled as it isn’t generally necessary and requires more computer memory than we had available. Metagenomes from the same sample were co-assembled, resulting in 26 sediment metagenomes and nine groundwater metagenomes. Co-assemblies improved assembly metrics, generally increasing N50 to 1.7-2X the individual assembly N50s.
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1Smith HJ, Zelaya AJ, De León KB, Chakraborty R, Elias DA, Hazen TC, Arkin AP, Cunningham AB, Fields MW. 2018. Impact of hydrologic boundaries on microbial planktonic and biofilm communities in shallow terrestrial subsurface environments. FEMS Microbiol Ecol 94:fiy 191. doi:10.1093/femsec/fiy 19130265315 PMC 6192502 · doi ↗ · pubmed ↗
- 2Anantharaman K, Brown CT, Hug LA, Sharon I, Castelle CJ, Probst AJ, Thomas BC, Singh A, Wilkins MJ, Karaoz U, Brodie EL, Williams KH, Hubbard SS, Banfield JF. 2016. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat Commun 7:13219. doi:10.1038/ncomms 1321927774985 PMC 5079060 · doi ↗ · pubmed ↗
- 3Lui LM, Majumder EL-W, Smith HJ, Carlson HK, von Netzer F, Fields MW, Stahl DA, Zhou J, Hazen TC, Baliga NS, Adams PD, Arkin AP. 2021. Mechanism across scales: a holistic modeling framework integrating laboratory and field studies for microbial ecology. Front Microbiol 12:642422. doi:10.3389/fmicb.2021.64242233841364 PMC 8024649 · doi ↗ · pubmed ↗
- 4Smith MB, Rocha AM, Smillie CS, Olesen SW, Paradis C, Wu L, Campbell JH, Fortney JL, Mehlhorn TL, Lowe KA, et al.. 2015. Natural bacterial communities serve as quantitative geochemical biosensors. M Bio 6:e 00326-15. doi:10.1128/m Bio.00326-1525968645 PMC 4436078 · doi ↗ · pubmed ↗
- 5Green SJ, Prakash O, Jasrotia P, Overholt WA, Cardenas E, Hubbard D, Tiedje JM, Watson DB, Schadt CW, Brooks SC, Kostka JE. 2012. Denitrifying bacteria from the genus Rhodanobacter dominate bacterial communities in the highly contaminated subsurface of a nuclear legacy waste site. Appl Environ Microbiol 78:1039–1047. doi:10.1128/AEM.06435-1122179233 PMC 3273022 · doi ↗ · pubmed ↗
- 6Moon J-W, Paradis CJ, Joyner DC, von Netzer F, Majumder EL, Dixon ER, Podar M, Ge X, Walian PJ, Smith HJ, et al.. 2020. Characterization of subsurface media from locations up- and down-gradient of a uranium-contaminated aquifer. Chemosphere 255:126951. doi:10.1016/j.chemosphere.2020.12695132417512 · doi ↗ · pubmed ↗
- 7Wu X, Gushgari-Doyle S, Lui LM, Hendrickson AJ, Liu Y, Jagadamma S, Nielsen TN, Justice NB, Simmons T, Hess NJ, Joyner DC, Hazen TC, Arkin AP, Chakraborty R. 2023. Distinct depth-discrete profiles of microbial communities and geochemical insights in the subsurface critical zone. Appl Environ Microbiol 89:e 0050023. doi:10.1128/aem.00500-2337272792 PMC 10304653 · doi ↗ · pubmed ↗
- 8BB Tools. 2016. DOE Joint Genome Institute. Available from: https://jgi.doe.gov/data-and-tools/software-tools/bbtools. Retrieved 25 Jul 2023.
