Contributors | Affiliation | Role |
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Orellana, Monica V. | University of Washington Friday Harbor Laboratories (FHL) | Principal Investigator |
Lausted, Christopher | Institute for Systems Biology (ISB) | Co-Principal Investigator |
Huang, Sui | Institute for Systems Biology (ISB) | Scientist |
York, Amber D. | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Cultures: Axenic Thalassiosira pseudonana (CCMP 1335, National Center for Marine Algae and Microbiota, Maine, USA; LSID urn:lsid:marinespecies.org:taxname:148934) batch cultures were grown in enriched artificial seawater (ESAW) medium modified with reduced levels of nitrate (170 μM) to characterize starvation. Before the experiment, the diatoms were acclimated to a constant 20 °C temperature and under a 12: 12 h dark: light diurnal cycle at 300 μmol photons·m−2·s−1 using cool fluorescent lights. The cultures were continuously equilibrated at ambient (420 ppm CO2 by bubbling mixed gasses (air and CO2 at 0.4 L/min) regulated using mass-flow controllers (GFC17, Aalborg) and monitored with a CO2 analyzer (model Q-S151; Qubit Systems) into a 1.5-L glass bioreactor system. The bioreactors were inoculated with 150,000 cells/ml of acclimated, axenic T. pseudonana and grown for 5 days on a 12: 12 h dark: light cycle. The pH was monitored spectrophotometrically (Dickson et al. 2007); the photochemical yield of photosystem II (variable fluorescence/maximum fluorescence Fv/Fm) was measured with an AquaPen AP100; and total dissolved nitrogen was measure using the Nitrite/Nitrate, Colorimetric Test Roche # 11746081001) kit after syringe-filtering (0.2μm) the samples. Samples were taken twice a day, in the middle of dark-time, and the middle of the light-time representing different growth conditions regulating the metabolism based on light and nitrogen on days one and two (Ashworth et al. 2013). On days three and four, samples were only taken during the light time for experiment b. This experiment was repeated to evaluate the recovery of the cells from starvation by amending NO3 (170 uM+/- 5uM) on day 5, after 70 hrs of starvation for T. pseudonana and sampled at T1: 0h, T2: 1h and T3: 3 hr, and T4: 6 hr after adding the supplemental nitrogen. Samples T1, T2, T3, were set on ice in the dark before analysis at when T4 was sampled.
Experiment Metadata (physiology, gene and cell information):
* Sheet 1 of file "EAGER 10x Physiological metadata and measurements.xlsx" was imported into the BCO-DMO data system up to Excel row 15 (following rows containing metadata describing the columns was not imported as part of the data table, it was added to the "Parameters" section of the dataset metadata.
* DateTime (UTC) added in ISO 8601 format using provided dates and times (PST/PSD) .
* Column names adjusted to conform to BCO-DMO naming conventions designed to support broad re-use by a variety of research tools and scripting languages. [Only numbers, letters, and underscores. Can not start with a number]
* Three columns for replicates of F/cell flow were removed from table at submitter's request.
File |
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918841_v1_physiological-data.csv (Comma Separated Values (.csv), 2.70 KB) MD5:0dcc34596f03a7c84762c09bfe228ea8 Primary data file for dataset ID 918841, version 1 |
Parameter | Description | Units |
Species | Thaps = Thalassiosira pseudonana (LSID urn:lsid:marinespecies.org:taxname:148934) | unitless |
Identification | identification "1" | unitless |
Date | Date sampled (mm-dd-yy) | unitless |
Time | Time sampled (HH:MM), 24hr | unitless |
ISO_DateTime_UTC | DateTime with timezone sampled, ISO 8601 format | unitless |
Hours | Hours since innoculation | unitless |
Diel | Diel Cycle (Day/ Night) | unitless |
PPM_CO2_analyzer | CO2 (CO2 Analyzer) | parts per million (ppm) |
cell_counts_q1 | Cell counts q1 (quadrant 1) | cells |
cell_counts_q2 | Cell counts q2 (quadrant 2) | cells |
cell_counts_q3 | Cell counts q3 (quadrant 3) | cells |
cell_counts_q4 | Cell counts q4 (quadrant 4) | cells |
dF | Dilution factor | unitless |
cells_mL_avgerage | cell concentration | cells per ml (cells/ml) |
Quantum_yield_1 | Quantum Yield replicate 1 | unitless |
Quantum_yield_2 | Quantum Yield replicate 2 | unitless |
Quantum_Yield_3 | Quantum Yield replicate 3 | unitless |
QY_AVG | Quantum Yield Average | unitless |
FT1 | Fluorescence replicate 1 | unitless |
FT2 | Fluorescence replicate 2 | unitless |
FT3 | Fluorescence replicate 3 | unitless |
FT_AVG | Fluorescence Average | unitless |
pH | pH (potential for Hydrogen) | unitless |
Sample_for_RNA | Sample for RNA (Yes/No) | unitless |
Cell_Pellet | Cell pellet (Yes/No) | unitless |
CF_Media | Cell free media for nutrient profiling | unitless |
uM_Nitrate1 | Nitrate replicate 1 | micromolar (uM) |
uM_Nitrate2 | Nitrate replicate 2 | micromolar (uM) |
uM_Nitrate3 | Nitrate replicate 3 | micromolar (uM) |
uM_Nitrate_AVG | Nitrate average | micromolar (uM) |
Dataset-specific Instrument Name | CO2 analyzer (model Q-S151; Qubit Systems) |
Generic Instrument Name | CO2 Analyzer |
Generic Instrument Description | Measures atmospheric carbon dioxide (CO2) concentration. |
Dataset-specific Instrument Name | AquaPen AP100, Photon Systems Instruments (Drásov, Czechia) |
Generic Instrument Name | Fluorometer |
Generic Instrument Description | A fluorometer or fluorimeter is a device used to measure parameters of fluorescence: its intensity and wavelength distribution of emission spectrum after excitation by a certain spectrum of light. The instrument is designed to measure the amount of stimulated electromagnetic radiation produced by pulses of electromagnetic radiation emitted into a water sample or in situ. |
NSF Award Abstract:
Diatoms are important primary producers in sunlit oceans and lakes across the globe. They are key players in spring phytoplankton blooms, which in turn support food webs that include productive fisheries. In addition, these photosynthetic diatom cells are known to capture enormous amounts of carbon, which are exported to depth as blooms die off. In oceanic systems, this process effectively removes carbon from the atmosphere for thousands of years. However, the biological mechanisms that lead to carbon sequestration, the transfer of carbon from the atmosphere into the deep ocean, are not well understood. As diatom populations reach the end of the bloom cycle, individual cells start to deteriorate and undergo cell death. The collapse of diatom populations is regarded as a critical point (or tipping point), which can be predicted by understanding the genetic activity of the population. This project seeks to elucidate how environmental change influences diatom cell-death processes. A mechanistic understanding of these cellular processes will elucidate how climate change could alter carbon-removal from the atmosphere and affect ocean productivity. The knowledge and methods developed during this study are applicable across organisms from all domains of life. The broader impacts of this project are focused on high school education and new ideas and approaches for three-dimensional learning opportunities in support of Next Generation Science Standards (NGSS). Specifically, researchers are working with high school educators and partners to teach concepts of systems approaches, tipping points, and carbon sequestration in the marine environment through educational modules.
The goal is to determine the structure of diatom populations during the transition of actively growing cells towards population collapse by identifying the point of commitment (tipping point) at the level of individual cells. The model system is the diatom, Thalassiosira pseudonana, which is widespread and a common bloom-forming species. The random decision process of individual diatom cells is being characterized by establishing a genome-wide gene expression space through the physical and biochemical characterization of the cells. Implementation of the project is focused on measuring the phenotypic responses in the diatom to environmental factors including severe stress. Transcriptomic analyses during the transition of cell proliferation towards culture collapse include bulk (RNA-Seq) and single-cell (scRNA-Seq) high-throughput sequencing. Using a systems biology approach, the genetic information obtained from the samples is incorporated into predictive models to identify genetic transitions that occur prior to population collapse. The systems approach can detect changes in transcriptomic state that precede a critical point in the cell death process leading to predictions of how diatoms respond to environmental change. This work opens new vistas for the elucidation of mechanistic pathways of diatom cell populations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
The Ocean Carbon and Biogeochemistry (OCB) program focuses on the ocean's role as a component of the global Earth system, bringing together research in geochemistry, ocean physics, and ecology that inform on and advance our understanding of ocean biogeochemistry. The overall program goals are to promote, plan, and coordinate collaborative, multidisciplinary research opportunities within the U.S. research community and with international partners. Important OCB-related activities currently include: the Ocean Carbon and Climate Change (OCCC) and the North American Carbon Program (NACP); U.S. contributions to IMBER, SOLAS, CARBOOCEAN; and numerous U.S. single-investigator and medium-size research projects funded by U.S. federal agencies including NASA, NOAA, and NSF.
The scientific mission of OCB is to study the evolving role of the ocean in the global carbon cycle, in the face of environmental variability and change through studies of marine biogeochemical cycles and associated ecosystems.
The overarching OCB science themes include improved understanding and prediction of: 1) oceanic uptake and release of atmospheric CO2 and other greenhouse gases and 2) environmental sensitivities of biogeochemical cycles, marine ecosystems, and interactions between the two.
The OCB Research Priorities (updated January 2012) include: ocean acidification; terrestrial/coastal carbon fluxes and exchanges; climate sensitivities of and change in ecosystem structure and associated impacts on biogeochemical cycles; mesopelagic ecological and biogeochemical interactions; benthic-pelagic feedbacks on biogeochemical cycles; ocean carbon uptake and storage; and expanding low-oxygen conditions in the coastal and open oceans.
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) |