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  • 1
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    Massachusetts Institute of Technology and Woods Hole Oceanographic Institution
    Publication Date: 2022-05-25
    Description: Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2001
    Description: Processes that enable marine phytoplankton to acquire trace metals are fundamental to our understanding of primary productivity and global carbon cycling. This thesis explored the biogeochemistry of cobalt using analytical chemistry and physiological experiments with the dominant phytoplankton species, Prochlorococcus. A high sensitivity method for Co speciation was developed using hanging mercury drop cathodic stripping voltammetry. Dissolved Co at the Bermuda Atlantic Time Series station (BATS) in the Sargasso Sea was bound by strong organic complexes with a conditional stability constant of logK=16.3l0.9. A depth profile of Co at BATS revealed a nutrient-like profile. Biweekly time series measurements of total cobalt near Bermuda from the MITESS sampler were 0-47pM throughout 1999, and averaged 20±10pM in 1999. A transect of total cobalt from BATS to American coastal waters ranged from 19- 133pM and correlated negatively with salinity (r2=0.93), suggestive of coastal waters as an input source. Prochlorococcus strains MED4-Ax and SS120 showed an absolute requirement for Co, despite replete Zn. 57Co uptake rates and growth rates were enhanced by additions of filtered low Co cultures, suggesting that a ligand is present that facilitates Co uptake. Bottle incubations from a Synechococcus bloom in the Pacific showed production of 425pM strong cobalt ligand. These and other lines of evidence support the hypothesis that a cobalt ligand, or cobalophore, is involved in cobalt uptake. Co-limited Prochlorococcus cultures exhibited an increase in the fraction of cells in G2 relative to other cell cycle stages during exponential growth, and the durations of this stage increased with decreasing cobalt concentrations. This effect was not observed with Fe, N, or P-limited cultures, suggestive of a specific biochemical function of cobalt that would interfere with the late stages of the cell cycle. The ligand Teta was explored as a means to induce cobalt limitation. The CoTeta complex was not bioavailable to the Sargasso Sea microbial assemblage in short-term experiments. Bottle incubations with Teta did not induce cobalt limitation of Prochlorococcus. These results are consistent with the lower conditional stability constant for CoTeta (logK=11.2l0.1) relative to natural cobalt ligands in seawater, and with culture studies that suggest uptake of cobalt via strong organic ligands.
    Description: The work in this thesis was supported by a grant from the National Science Foundation (#OCE-9618729) for cyanobacteria metal interactions in the Sargasso Sea. I have been funded through WHOI on an NSF coastal traineeship (#DGE-9454129) for my first year, followed by an EP A STAR Graduate Fellowship for the subsequent years. Additional funding was supplied by the WHOI Educational Endowment Funds and by the WHOI Ditty Bag fund for part of the DNA/cell cycle work.
    Keywords: Biogeochemistry ; Cobalt ; Marine phytoplankton ; Cyanobacteria ; Oceanus (Ship : 1975-) Cruise OC349
    Repository Name: Woods Hole Open Access Server
    Type: Thesis
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  • 2
    Publication Date: 2022-05-25
    Description: Presented at AGU Fall Meeting, American Geophysical Union, Washington, D.C., 10 – 14 Dec 2018
    Description: Data repositories often transform submissions to improve understanding and reuse of data by researchers other than the original submitter. However, scientific workflows built by the data submitters often depend on the original data format. In some cases, this makes the repository’s final data product less useful to the submitter. As a result, these two workable but different versions of the data provide value to two disparate, non-interoperable research communities around what should be a single dataset. Data repositories could bridge these two communities by exposing provenance explaining the transform from original submission to final product. A subsequent benefit of this provenance would be the transparent value-add of domain repository data curation. To improve its data management process efficiency, the Biological and Chemical Oceanography Data Management Office (BCO-DMO, https://www.bco-dmo.org) has been adopting the data containerization specification defined by the Frictionless Data project (https://frictionlessdata.io). Recently, BCO-DMO has been using the Frictionless Data Package Pipelines Python library (https://github.com/frictionlessdata/datapackage-pipelines) to capture the data curation processing steps that transform original submissions to final data products. Because these processing steps are stored using a declarative language they can be converted to a structured provenance record using the Provenance Ontology (PROV-O, https://www.w3.org/TR/prov-o/). PROV-O abstracts the Frictionless Data elements of BCO-DMO’s workflow for capturing necessary curation provenance and enables interoperability with other external provenance sources and tools. Users who are familiar with PROV-O or the Frictionless Data Pipelines can use either record to reproduce the final data product in a machine-actionable way. While there may still be some curation steps that cannot be easily automated, this process is a step towards end-to-end reproducible transforms throughout the data curation process. In this presentation, BCO-DMO will demonstrate how Frictionless Data Package Pipelines can be used to capture data curation provenance from original submission to final data product exposing the concrete value-add of domain-specific repositories.
    Description: NSF #1435578
    Keywords: Provenance ; Frictionless Data ; Data management
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 3
    Publication Date: 2022-05-26
    Description: Presented at Data Curation Network, May 15, 2020
    Description: At domain-specific data repositories, curation that strives for FAIR principles often entails transforming data submissions to improve understanding and reuse. The Biological and Chemical Oceanography Data Management Office (BCO-DMO, https://www.bco-dmo.org) has been adopting the data containerization specification of the Frictionless Data project (https://frictionlessdata.io) in an effort to improve its data curation process efficiency. In doing so, BCO-DMO has been using the Frictionless Data Package Pipelines library (https://github.com/frictionlessdata/datapackage-pipelines) to define the processing steps that transform original submissions to final data products. Because these pipelines are defined using a declarative language they can be serialized into formal provenance data structures using the Provenance Ontology (PROV-O, https://www.w3.org/TR/prov-o/). While there may still be some curation steps that cannot be easily automated, this method is a step towards reproducible transforms that bridge the original data submission to its published state in machine-actionable ways that benefit the research community through transparency in the data curation process. BCO-DMO has built a user interface on top of these modular tools for making it easer for data managers to process submission, reuse existing workflows, and make transparent the added value of domain-specific data curation.
    Description: NSF #1924618
    Keywords: Data Curation ; Provenance ; Workflows ; Frictionless Data ; Data management ; Data repository
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 4
    Publication Date: 2022-05-26
    Description: Presented at USGS Data Management Working Group, 9, November 2020
    Description: At domain-specific data repositories, curation that strives for FAIR principles often entails transforming data submissions to improve understanding and reuse. The Biological and Chemical Oceanography Data Management Office (BCO-DMO, https://www.bco-dmo.org) has been adopting the data containerization specification of the Frictionless Data project (https://frictionlessdata.io) in an effort to improve its data curation process efficiency. In doing so, BCO-DMO has been using the Frictionless Data Package Pipelines library (https://github.com/frictionlessdata/datapackage-pipelines) to define the processing steps that transform original submissions to final data products. Because these pipelines are defined using a declarative language they can be serialized into formal provenance data structures using the Provenance Ontology (PROV-O, https://www.w3.org/TR/prov-o/). While there may still be some curation steps that cannot be easily automated, this method is a step towards reproducible transforms that bridge the original data submission to its published state in machine-actionable ways that benefit the research community through transparency in the data curation process. BCO-DMO has built a user interface on top of these modular tools for making it easier for data managers to process submission, reuse existing workflows, and make transparent the added value of domain-specific data curation.
    Description: NSF #1924618
    Keywords: Data Curation ; Provenance ; Workflows ; Frictionless Data ; Data management ; Data repository
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 5
    Publication Date: 2022-05-26
    Description: Presented at AGU Ocean Sciences, 11 - 16 February 2018, Portland, OR
    Description: At the Biological and Chemical Oceanography Data Management Office (BCO-DMO) Big Data challenges have been steadily increasing. The sizes of data submissions have grown as instrumentation improves. Complex data types can sometimes be stored across different repositories . This signals a paradigm shift where data and information that is meant to be tightly-coupled and has traditionally been stored under the same roof is now distributed across repositories and data stores. For domain-specific repositories like BCO-DMO, a new mechanism for assembling data, metadata and supporting documentation is needed. Traditionally, data repositories have relied on a human's involvement throughout discovery and access workflows. This human could assess fitness for purpose by reading loosely coupled, unstructured information from web pages and documentation. Distributed storage was something that could be communicated in text that a human could read and understand. However, as machines play larger roles in the process of discovery and access of data, distributed resources must be described and packaged in ways that fit into machine automated workflows of discovery and access for assessing fitness for purpose by the end-user. Once machines have recommended a data resource as relevant to an investigator's needs, the data should be easy to integrate into that investigator's toolkits for analysis and visualization. BCO-DMO is exploring the idea of data containerization, or packaging data and related information for easier transport, interpretation, and use. Data containerization reduces not only the friction data repositories experience trying to describe complex data resources, but also for end-users trying to access data with their own toolkits. In researching the landscape of data containerization, the Frictionlessdata Data Package (http://frictionlessdata.io/) provides a number of valuable advantages over similar solutions. This presentation will focus on these advantages and how the Frictionlessdata Data Package addresses a number of real-world use cases faced for data discovery, access, analysis and visualization in the age of Big Data.
    Description: NSF #1435578, NSF #1639714
    Keywords: Frictionless Data ; Data management ; Data exchange ; Data Transport ; Distributed data ; Data tools ; Big data
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 6
    Publication Date: 2022-05-26
    Description: Presented at the Fall AGU Meeting, New Orleans, LA, 11-15 December 2017
    Description: As cross-disciplinary geoscience research increasingly relies on machines to discover and access data, one of the critical questions facing data repositories is how data and supporting materials should be packaged for consumption. Traditionally, data repositories have relied on a human's involvement throughout discovery and access workflows. This human could assess fitness for purpose by reading loosely coupled, unstructured information from web pages and documentation. In attempts to shorten the time to science and access data resources across may disciplines, expectations for machines to mediate the process of discovery and access is challenging data repository infrastructure. This challenge is to find ways to deliver data and information in ways that enable machines to make better decisions by enabling them to understand the data and metadata of many data types. Additionally, once machines have recommended a data resource as relevant to an investigator's needs, the data resource should be easy to integrate into that investigator's toolkits for analysis and visualization. The Biological and Chemical Oceanography Data Management Office (BCO-DMO) supports NSF-funded OCE and PLR investigators with their project's data management needs. These needs involve a number of varying data types some of which require multiple files with differing formats. Presently, BCO-DMO has described these data types and the important relationships between the type's data files through human-readable documentation on web pages. For machines directly accessing data files from BCO-DMO, this documentation could be overlooked and lead to misinterpreting the data. Instead, BCO-DMO is exploring the idea of data containerization, or packaging data and related information for easier transport, interpretation, and use. In researching the landscape of data containerization, the Frictionlessdata Data Package (http://frictionlessdata.io/) provides a number of valuable advantages over similar solutions. This presentation will focus on these advantages and how the Frictionlessdata Data Package addresses a number of real-world use cases faced for data discovery, access, analysis and visualization.
    Description: National Science Foundation Award #1435578, Award #1639714
    Keywords: Frictionless Data ; Data management ; Data workflows ; Data transport
    Repository Name: Woods Hole Open Access Server
    Type: Presentation
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  • 7
    Publication Date: 2022-05-26
    Description: © The Author(s), 2011. This is an open-access article subject to a non-exclusive license between the authors and Frontiers Media SA, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited. The definitive version was published in Frontiers in Microbiology 2 (2011): 215, doi:10.3389/fmicb.2011.00215.
    Description: Improvements in temporal and spatial sampling frequency have the potential to open new windows into the understanding of marine microbial dynamics. In recent years, efforts have been made to allow automated samplers to collect microbial biomass for DNA/RNA analyses from moored observatories and autonomous underwater vehicles. Measurements of microbial proteins are also of significant interest given their biogeochemical importance as enzymes that catalyze reactions and transporters that interface with the environment. We examined the influence of five preservatives solutions (SDS-extraction buffer, ethanol, trichloroacetic acid, B-PER, and RNAlater) on the proteome integrity of the marine cyanobacterium Synechococcus WH8102 after 4 weeks of storage at room temperature. Four approaches were used to assess degradation: total protein recovery, band integrity on an SDS detergent polyacrylamide electrophoresis (SDS-PAGE) gel, and number of protein identifications and relative abundances by 1-dimensional LC–MS/MS proteomic analyses. Total protein recoveries from the preserved samples were lower than the frozen control due to processing losses, which could be corrected for with internal standardization. The trichloroacetic acid preserved sample showed significant loss of protein band integrity on the SDS-PAGE gel. The RNAlater preserved sample showed the highest number of protein identifications (103% relative to the control; 520 ± 31 identifications in RNAlater versus 504 ± 4 in the control), equivalent to the frozen control. Relative abundances of individual proteins in the RNAlater treatment were quite similar to that of the frozen control (average ratio of 1.01 ± 0.27 for the 50 most abundant proteins), while the SDS-extraction buffer, ethanol, and B-PER all showed significant decreases in both number of identifications and relative abundances of individual proteins. Based on these findings, RNAlater was an effective proteome preservative, although further study is warranted on additional marine microbes.
    Description: This work was funded by the National Science Foundation Chemical and Biological Oceanography, Center for Microbial Oceanography Research and Education (C-MORE), and the Gordon and Betty Moore Foundation.
    Keywords: Proteome ; Preservation ; Autonomous sampling ; Cyanobacteria ; Alkaline phosphatase ; Proteomics ; Synechococcus WH8102
    Repository Name: Woods Hole Open Access Server
    Type: Article
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