| Contributors | Affiliation | Role |
|---|---|---|
| Giovannoni, Stephen | Oregon State University (OSU) | Principal Investigator |
| Copley, Nancy | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
This dataset is a log of samples collected on AE1516 at the Bermuda Atlantic Time-series study site (BAT) Hydrostation S. The samples were analyzed for microbial diversity, dissolved organic carbon (DOC), total DOC, single celled genomics, and an osmolyte inculation experiment.
Methodology References:
Tangential flow filtration methods are described in Giovannoni, et al (1990).
Methods for DOM oxidation measurements are described in Sun, et al (2011).
Methods for rRNA gene diversity analysis are described in Vergin, et al (2013).
Methods for DOM analysis are described in Carini, et al (2014).
| File |
|---|
sample_log_AE1516.csv (Comma Separated Values (.csv), 4.49 KB) MD5:80944ab03045916340b24031cc6b50a9 Primary data file for dataset ID 616269 |
| Parameter | Description | Units |
| cruise_id | cruise identification | unitless |
| sample_descrip | samples taken for this purpose | unitless |
| date | date in yyyy-mm-dd format. | unitless |
| time | time; UTC or local? | hh:mm |
| person | person who handles the sample | unitless |
| depth | sample collection depth | meters |
| sample_id | sample identification (date and depth); taken with PPL cartridge | unitless |
| filtrand_id | filtrand identification (date and depth); from Sterivex filter | unitless |
| TOC_id | total organic carbon sample id (date_time_depth); given to Craig Carlson for analysis | unitless |
| sample_volume | sample volume filtered | milliliters |
| filter_size | filter pore size and membrane type | unitless |
| preservation | preservative/buffer used | unitless |
| incubation | incubation period | hours |
| temp_stored | temperature at which samples were stored | degrees Celsius |
| Website | |
| Platform | R/V Atlantic Explorer |
| Report | |
| Start Date | 2015-07-01 |
| End Date | 2015-07-03 |
| Description | Objectives:
1. TFF surface water samples to collect cells for two metabolite oxidation experiments: A) osmolytes, B) 14C-dimethylarsenate. 80 L surface sample to 600 ml, expecting ~10^7 cells ml. This collection plan executed --- times over two days (late afternoon and morning, each day; (Giovannoni/Halsey experiments; Landry, Giovannoni on TFF).
2. TFF surface water samples to collect cells single cell genomics by FACS at JGI. After concentration by TFF cells will be filtered through 0.45 um Nuclepore filters, and cryopreserved in SCGC glycine betaine cryopreservation buffer.
3. TFF 100 m water samples to collect cells for Ib, IIa, IIIa, IV or Vb ecotypes, TFF cell concentrates from will be filtered through 0.45 um Nuclepore filters, and cryopreserved in SCGC glycerol cryopreservation buffer.
4. DOM and nucleic acid water profile for chemistry and amplicon sequencing. Surface to 300 m (surface, 40, 80, 120, 160, 200, 250, 300 m), all samples that will be first filtered through 0.2 µm Sterivex cartridges and then A) 300 ml will frozen at -80 (or -20, in a pinch) in polypropylene or teflon bottles; for chemistry, or B) 3.7 liter will be concentrated with PPL cartridges and stored at -20 in the bound state (sealed and store PPLs). Add SLP to Sterivex cartridges and freeze at -80 C. DOC samples, collected in ashed EPA vials, will be collected for every DOM sample.
Cruise information and original data are available from the NSF R2R data catalog. |
SAR11 (Pelagibacterales) are the most abundant group of bacterioplankton in the oceans. Globally, they are estimated to oxidize to carbon dioxide (CO2) between 5 and 22% of all the organic carbon produced by photosynthesis each day. The activities of bacterioplankton such as SAR11 determine the residence times of different forms of organic carbon, and ultimately shape the composition of dissolved organic pools in the oceans, which rival atmospheric CO2 in mass. Accurate and detailed information about the oceanic carbon cycle is used in models that are valued for their potential to predict and understand future changes in ocean ecosystems. This grant supports analyses of genomic data that predict the carbon oxidation functions of SAR11 cells, and supports experiments with cells in culture, where high-resolution mass spectrometry technology is applied to discover new organic carbon oxidation biochemistry. To assess the importance of SAR11 carbon oxidation functions in ocean ecosystems, this project includes four short oceanographic cruises to the Bermuda Atlantic Time-series Study (BATS) site, in the western Sargasso Sea. On these cruises the concentrations and oxidation rates of organic compounds will be measured, and linked to variation in planktonic SAR11 populations.
It is a paradox that SAR11 cells are the most abundant in the oceans, but also have among the smallest genomes known. The central goal of this proposal is to understand what types of dissolved organic matter (DOM) are oxidized to CO2 by SAR11. Implicit to this approach is the perspective that some abundant chemoheterotrophic bacterioplankton taxa, particularly those with small genomes, have evolved specialist strategies for oxidizing organic matter. Understanding these strategies can lead to a more detailed and accurate understanding of the biological processes that recycle biological production to CO2. Major project aims are: 1) investigate SAR11 genomes and assay cells in culture with high-resolution mass spectrometry approaches and isotopic labeling to identify the range of compounds these cells can oxidize to CO2; 2) at BATS, measure biological oxidation rates of DOM compounds used by SAR11; 3) link spatiotemporal SAR11 genome variation to patterns of DOM oxidation in the ocean surface layer (0-300 m). This projects includes four short cruises to BATS that target the four microbial plankton community types at this site: upper euphotic zone, deep chlorophyll maximum, spring bloom and upper mesopelagic. Products of this activity will include new information about variation in labile DOM oxidation across the surface layer, and specific links to genome features that will improve the accuracy of interpretation of global ocean metagenomic data.
| Funding Source | Award |
|---|---|
| NSF Division of Ocean Sciences (NSF OCE) |