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Microbial production and consumption of hydrocarbons in the global ocean

Nature Microbiology volume 6, pages 489–498 (2021)Cite this article

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Abstract

Seeps, spills and other oil pollution introduce hydrocarbons into the ocean. Marine cyanobacteria also produce hydrocarbons from fatty acids, but little is known about the size and turnover of this cyanobacterial hydrocarbon cycle. We report that cyanobacteria in an oligotrophic gyre mainly produce n-pentadecane and that microbial hydrocarbon production exhibits stratification and diel cycling in the sunlit surface ocean. Using chemical and isotopic tracing we find that pentadecane production mainly occurs in the lower euphotic zone. Using a multifaceted approach, we estimate that the global flux of cyanobacteria-produced pentadecane exceeds total oil input in the ocean by 100- to 500-fold. We show that rapid pentadecane consumption sustains a population of pentadecane-degrading bacteria, and possibly archaea. Our findings characterize a microbial hydrocarbon cycle in the open ocean that dwarfs oil input. We hypothesize that cyanobacterial hydrocarbon production selectively primes the ocean’s microbiome with long-chain alkanes whereas degradation of other petroleum hydrocarbons is controlled by factors including proximity to petroleum seepage.

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Fig. 1: Pentadecane maps onto trends in ocean fluorescence and cyanobacteria abundance.
Fig. 2: Most pentadecane production in lower euphotic zone.
Fig. 3: Pentadecane rapidly consumed by specialists in waters underlying the oligotrophic ocean.

Data availability

All oceanographic, chemical and cell count data are available at the Biological and Chemical Oceanography Data Management Office website under project code NSF OCE-1635562 (https://doi.org/10.26008/1912/bco-dmo.826878.1). Metagenomes are available through the NCBI in BioProject PRJNA657625. Databases accessed were the Genome Taxonomy Database (https://data.ace.uq.edu.au/public/gtdb/data/releases/release89/89.0/, v.r89), the Pfam database (ftp://ftp.ebi.ac.uk/pub/databases/Pfam/releases/Pfam31.0, v.31.0) and the Ocean Microbial Reference Gene Catalogue (http://ocean-microbiome.embl.de/companion.html). Source data are provided with this paper.

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Acknowledgements

We thank G. Paradis for analytical support; the R/V Neil Armstrong captain and crew for support at sea; the Hawai’ian Oceanographic Time Series programme and the crew of the R/V Kilo Moana for enabling a preliminary study; J. Hayes and P. Chisholm for their advice on the study; J. Ossolinski, H. Fredricks, B. Jenkins and R. Swarthout for assistance on the R/V Armstrong cruise; T. McKinnon for assistance in dissolved inorganic carbon isotope measurements; A. Ebling for total particulate phosphate measurements; N. Poulton for flow cytometry analysis; and K. Krogslund for nutrient analysis. For bioinformatic analysis, this work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation (NSF) grant no. ACI-1548562. Specifically, it used the Bridges system, which is supported by NSF award no. ACI-1445606, at the Pittsburgh Supercomputing Center. This project was supported by NSF grant nos. OCE-1635562, OCE-1536346, OCE-1756254 and OCE-1634478.

Author information

Author notes

  1. These authors contributed equally: Connor R. Love, Eleanor C. Arrington.

Authors and Affiliations

  1. Interdepartmental Graduate Program for Marine Science, University of California—Santa Barbara, Santa Barbara, CA, USA

    Connor R. Love, Eleanor C. Arrington & Kelsey M. Gosselin

  2. Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA

    Christopher M. Reddy, Benjamin A. S. Van Mooy & Robert K. Nelson

  3. Department of Earth Science and Marine Science Institute, University of California—Santa Barbara, Santa Barbara, CA, USA

    David L. Valentine

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Contributions

C.R.L. carried out the organization of field experiments and measurements of pentadecane production and concentration, and corresponding data analysis. E.C.A. carried out the biodegradation experiments and bioinformatic work. B.A.S.V.M. contributed nutrient data, cell count data and sediment trap particles for experimentation. K.M.G. carried out the pentadecane concentration measurements. C.M.R. built the methodology for pentadecane quantification. R.K.N. carried out the two-dimensional gas chromatography quality checks. D.L.V. contributed towards experimental design and data interpretation.

Corresponding author

Correspondence to David L. Valentine.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Microbiology thanks Alexandra Turchyn and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Pentadecane extraction data quality check.

a, Histogram of percent recovery of the internal standard (DDTP). b, Histogram of standard deviation of replicates of pentadecane concentration measurements; only a few replicates have a standard deviation > 15 ng L−1. c, Pentadecane concentration data vs. percent recovery of DDTP; there is no coherent trend of greater recovery with higher concentration. d, Cyanobacterial cell abundance (Pro. + Syn.) vs. standard deviation of pentadecane concentration between replicates; points with high standard deviation and low cyanobacterial cell abundance were further investigated (see Supplementary Note).

Source data

Extended Data Fig. 2 Pentadecane concentration changes during light incubations.

Concentration of pentadecane at beginning and end of 30-hour light incubations (time = 0 and 30 hours) at three light penetration depths for stations 3, 4, 5, 7, 8, 9 (indicated by number at right of each panel). Water was incubated at the light level from which it was collected (see Methods). Data are plotted as black open circles and represent biologically independent measurements; bar indicates mean of replicates at that light depth, error bars indicate standard deviation of n = 3 replication.

Source data

Extended Data Fig. 3 Pentadecane concentration changes during dark control incubations.

Concentration of pentadecane at beginning and end of 30-hour dark control incubations (time = 0 and 30 hours) at three light penetration depths for stations 3, 4, 5, 7, 8 (indicated by number at right of each panel). Data are plotted as black open circles and represent biologically independent measurements; bar indicates mean of replicates at that light depth, error bars indicate standard deviation of n = 3 replication.

Source data

Extended Data Fig. 4 Station 6 diel patterns across different light depths.

Light depths kept constant through Lagrangian sampling framework whereas the DCM is a depth variable feature throughout the diel cycle (see Methods). The x-axis represents time of day in hours, with gray shading representing night. Diel patterns of a pentadecane, b Prochlorococcus, c Synechococcus, d fluorescence (averaged with 1-meter resolution data with 2 data points above and 2 data points below to smooth signal, n = 5) and e-g selected ratios (see Supplementary Note). a, e, Data are plotted as open circles with n = 2 biologically independent pentadecane measurements, solid circles indicate mean.

Source data

Extended Data Fig. 5 Water mass proxies show consistent diel sampling for lower euphotic zone.

Seawater density plotted against pentadecane concentration colored by light penetration depth and feature (DCM). In this plot, seawater density acts as a proxy for water mass identity in diel sampling. The closer the vertical spread of points of the same color means that samples are more likely to have originated from the same water mass, whereas the further spread means that samples may have originated from different water masses. The horizontal spread of points of the same color represents different concentrations of pentadecane found in the diel cycle. 3% PAR, 1% PAR and particularly the DCM, have pronounced changes in pentadecane over the diel cycle with minimal shifts in seawater density. We conclude this to mean that pentadecane patterns at these depths can be attributed to biological origin, rather than sampling of different water masses. Further information on sampling and data in Methods and Supplementary Note.

Source data

Extended Data Fig. 6 Community composition and diversity in pentadecane incubations.

a-b, Microbial community composition within pentadecane incubations informed via the V4 region of the 16 S rRNA gene for initial samples and those harvested at 27 days (station 3) and 29 days (station 6). Labels on x axis are sample IDs of biologically independent DNA samples with the following abbreviations (T0: time point 0, T0part: initial sediment trap particle community, T0SW (a and b): initial seawater community, T0sw + part (a, b, and c): initial seawater community immediately after particles added, #: pentadecane enrichment). Nucleotide variants are grouped by genus and are listed under associated family and genus; if genus is unclassified than it is listed as NA. All taxa less than 5% are aggregated and shaded gray. c, Shannon diversity index (see Supplementary Note) for each biologically independent DNA sample. Shannon indices for pentadecane (n = 2 at station 3, n = 3 at station 6) and pentadecane + particles (n = 4 at station 3, n = 3 at station 6).

Source data

Extended Data Fig. 7 AlkB diversity underlying the North Atlantic subtropical gyre.

Phylogenetic analysis of genes closely related to alkB from Tara Ocean dataset reveal bacterial and archaeal clades distinct from xylene monooxygenase and fatty acid desaturases. a, Protein domain architecture across select representatives of xylene monooxygenase, alkane-1 monooxygenase, fatty acid desaturase, and related proteins from the Tara Oceans dataset which share a core fatty acid desaturase-like region (blue) expanded on in panel b. b, Abbreviated protein alignment for phylogenetic analyses (for details see Methods). Each column of alignment figure represents a sliding window of 5 bp with the following identity to consensus sequence coloration: green (100%), mustard (80-99% similar), yellow (60-79% similar), gray (<60% similar). The black box represents the region containing the eight histidine residues considered catalytically essential which were used for phylogenetic analyses in panels c-d. c, Maximum-likelihood phylogenetic tree with scale bar of substitutions per site. For clarity, bootstrap values are not shown for the full tree. Δ-X indicates activity X carbons from the carboxylic end of the fatty acid and ω-X indicates activity X carbons from the methyl end of the fatty acid. d, Expanded subtree of membrane monooxygenases and delta-9 fatty acid desaturases (outgroup). Clade coloration in panel d is according to position in panel c. NCBI accession codes are given for functional representatives in the subtree (accession_ORF#).

Source data

Extended Data Fig. 8 Putative archaeal alkB consistently abundant at surface and DCM stations.

a, Maximum-likelihood phylogenetic analysis for each station with scale bar of substitutions per site. Clade designations as follows: green (alkane-1-monoxygenase representatives and related Tara hits), blue (xylene monooxygenase representative and related Tara hits), yellow (putative Marine Group II/III archaeal monooxygenase). See Supplementary Data 2 for homology search results for putative MG II/III monooxygenase hits. Trees <27 unknown Tara sequences are out-grouped with delta-9 fatty acid desaturases, whereas trees with >27 unknown Tara sequences are left unrooted. b, Meta-data for each Tara station and abundance of unique hits derived from read-mapping. % Coverage indicates the fraction of reads that map to genes within each clade (xylene monooxygenase, alkB, or archaeal monooxygenase) over the total reads mapped to all alkB-like, xylene-like, and archaeal monooxygenases found at each station.

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Extended Data Fig. 9 Phylogenetic confirmation of AlkB presence in MAGs from pentadecane incubations.

a, Maximum likelihood tree of alkB hits within metagenomes compared to fatty acid desaturase, xylene monooxygenase, and alkB functionally expressed/characterized representatives (See Supplementary Note for identification details). Δ-X indicates activity X carbons from the carboxylic end of the fatty acid and ω-X indicates activity X carbons from the methyl end of the fatty acid. b, Expanded view of the alkane-1-monooxygenase, xylene monooxygenase, and related hits from metagenomes. Coloration in panel b is according to position in panel a. Gene copies for alkB in MAGS (in green) used in Fig. 3h.

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Extended Data Fig. 10 Proportional prokaryote contribution to phytoplankton community compared across time-series stations.

Depth profiles of ~20 years of data from the Bermuda Atlantic Time-series (BATS, at top, data obtained from Bermuda Atlantic Time-series Study http://bats.bios.edu/bats-data/), the Hawaii Ocean Time-series (HOT, in middle, data obtained from Hawaii Ocean Time-series HOT-DOGS application; University of Hawai’i at Mānoa, National Science Foundation Award #1756517), and this study (at bottom). Data points are colored on a gradient by the proportional contribution to the phytoplankton community by Prochlorococcus and Synechococcus (total phytoplankton community is calculated as Pro. + Syn. + pico- + nano-Eukaryotes for BATS and this study, and Pro. + Syn. + pico-Eukaryotes for HOT). BATS and HOT data are each from a single station measured nearly monthly for ~20 years whereas measurements from this study incorporate spatial variability (see Fig. 1) with minimal temporal variability (all measurements taken in May 2017). The proportional contribution of Prochlorococcus and Synechococcus is >90 % of the phytoplankton community at BATS 84% of the time. At HOT, Pro. + Syn. is > 90 % of phytoplankton community ~100% of the time. For this study, Pro. + Syn. is >90% of the phytoplankton community (Pro. + Syn. + pico + nano-Eukaryotes) for 80% of the measurements, with most cases of lower proportional prokaryote abundance due to an anomalous nutrient pulse observed at station 9 (a Synechococcus bloom) or at low absolute abundance of Pro. + Syn.

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Supplementary information

Supplementary Information

Supplementary Tables 1–4 and Supplementary Note.

Reporting Summary

Supplementary Data 1

Tara Oceans hydrocarbon gene abundance.

Supplementary Data 2

Blast results for Tara Oceans alkB-related hits.

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16S rRNA community analysis of pentadecane incubations.

Source Data Extended Data Fig. 7

Protein alignment of Tara Oceans alkB-like hits across all North Atlantic subtropical gyre stations, in fasta format.

Source Data Extended Data Fig. 8

Zip file of 8 protein alignments for each individual Tara Ocean station analysed in this study, in fasta format.

Source Data Extended Data Fig. 9

Protein alignment of alkB hits within MAGs, in fasta format.

Source Data Extended Data Fig. 10

Statistical source data.

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Love, C.R., Arrington, E.C., Gosselin, K.M. et al. Microbial production and consumption of hydrocarbons in the global ocean. Nat Microbiol 6, 489–498 (2021). https://doi.org/10.1038/s41564-020-00859-8

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