Single colony metaproteomes of Trichodesmium from samples collected in North Atlantic surface waters during the R/V Atlantis cruise AT39-05 in March of 2018

Dataset: Trichodesmium field metaproteomes - single colony metaproteomesSingle colony metaproteomes of Trichodesmium from samples collected in North Atlantic surface waters during the R/V Atlantis cruise AT39-05 in March of 2018. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/786694Gordon and Betty Moore Foundation (GBMF) GBMF3934, Gordon and Betty Moore Foundation: Marine Microbiology Initiative (MMI) GBMF3782, NSF Division of Ocean Sciences (NSF OCE) OCE-1657766, NSF Division of Ocean Sciences (NSF OCE) OCE-185071

The biogeochemistry of cobalt in the Sargasso Sea

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 2001Processes 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.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

Seeing many-body effects in single- and few-layer graphene: Observation of two-dimensional saddle-point excitons

Significant excitonic effects were observed in graphene by measuring its optical conductivity in a broad spectral range including the two-dimensional {\pi}-band saddle-point singularities in the electronic structure. The strong electron-hole interactions manifest themselves in an asymmetric resonance peaked at 4.62 eV, which is red-shifted by nearly 600 meV from the value predicted by ab-initio GW calculations for the band-to-band transitions. The observed excitonic resonance is explained within a phenomenological model as a Fano interference of a strongly coupled excitonic state and a band continuum. Our experiment also showed a weak dependence of the excitonic resonance in few-layer graphene on layer thickness. This result reflects the effective cancellation of the increasingly screened repulsive electron-electron (e-e) and attractive electron-hole (e-h) interactions.Comment: 9 pages, 3 figures, In PR

Production of cobalt binding ligands in a Synechococcus feature at the Costa Rica upwelling dome

Author Posting. © American Society of Limnology and Oceanography, 2005. This is the author's version of the work. It is posted here by permission of American Society of Limnology and Oceanography for personal use, not for redistribution. The definitive version was published in Limnology and Oceanography 50 (2005): 279-290.The Costa Rica upwelling dome (CRD; ~8.67ºN and 90.6ºW) was characterized chemically for cobalt and nickel abundances and speciation, and biologically using cyanobacterial abundances and phylogeny. Total dissolved cobalt was 93 pmol L-1at 90 m depth and decreased in surface waters to 45 pmol L-1 at 10 m. Cobalt was 40% labile at 90 m, but was completely complexed by strong ligands at 10 m. A surface transect out of the dome showed decreasing total dissolved cobalt from 57 pmol L-1 to 12 pmol L-1. Detection window studies showed that natural cobalt ligand complexes have conditional stability constants greater than 1016.8, and that competition with nickel did not release cobalt bound to organic complexes, consistent with natural cobalt ligands being Co(III)-complexes. Synechococcus cell densities at the CRD are among the highest reported in nature, varying between 1.2 x 106 to 3.7 x 106 cells ml-1. Phylogenetic analysis using the 16S-23S rDNA internally transcribed spacer showed the majority of clones were related to Synechococcus strain MIT S9220, while the remaining subset form a novel group within the marine Synechococcus lineage. In a bottle incubation experiment chlorophyll increased with cobalt and iron additions relative to each element alone and the unamended control treatment. Cobalt speciation analysis of incubation experiments revealed large quantities of strong cobalt ligand complexes in the cobalt addition treatments (401 pmol L-1), whereas cobalt added to a 0.2 mm filtered control remained predominantly labile (387 pmol L-1), demonstrating that the Synechococcus-dominated community is a source of strong cobalt ligands.This research was funded by NSF OCE-9618729, OCE-0327225, and OCE-0220826

FASTA file of sequences in Trichodesmium field metaproteomes mapped to a Trichodesmium metagenome plus cyanoGEBA species genomes from samples collected in the Atlantic and Pacific Ocean between 2000 and 2018

Dataset: Trichodesmium field metaproteomes - sequence fastaFASTA file of sequences in Trichodesmium field metaproteomes analyzed by 2D LC-MS/MS mapped to a Trichodesmium metagenome (IMG ID 2821474806) plus cyanoGEBA species genomes (Shih et al, 2013). Samples were collected in North Atlantic surface waters, at station BATS (Bermuda Atlantic Time-series Study), and station ALOHA (A Long-Term Oligotrophic Habitat Assessment) between 2000 and 2018. Related datasets: Trichodesmium field metaproteomes - peptide spectral counts: https://www.bco-dmo.org/dataset/787168 Trichodesmium field metaproteomes - protein spectral counts: https://www.bco-dmo.org/dataset/787147 Trichodesmium sample provenance: https://www.bco-dmo.org/dataset/787093 - Sample provenance file, which includes sample locations, filter sizes For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/787181Gordon and Betty Moore Foundation (GBMF) GBMF3934, Gordon and Betty Moore Foundation: Marine Microbiology Initiative (MMI) GBMF3782, NSF Division of Ocean Sciences (NSF OCE) OCE-1657766, NSF Division of Ocean Sciences (NSF OCE) OCE-185071

Net tow metaproteoome of Trichodesmium species mapped to a Trichodesmium metagenome plus cyanoGEBA species genomes in units of normalized peptide spectral counts from samples collected in the Atlantic and Pacific Ocean between 2000 and 2018

Dataset: Trichodesmium field metaproteomes - peptide spectral countsNet tow metaproteoome of Trichodesmium species mapped to a Trichodesmium metagenome plus cyanoGEBA species genomes, analyzed by 2D LC-MS/MS in units of normalized peptide spectral counts. Samples were collected in North Atlantic surface waters, at station BATS (Bermuda Atlantic Time-series Study), and station ALOHA (A Long-Term Oligotrophic Habitat Assessment) between 2000 and 2018. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/787168Gordon and Betty Moore Foundation (GBMF) GBMF3934, Gordon and Betty Moore Foundation: Marine Microbiology Initiative (MMI) GBMF3782, NSF Division of Ocean Sciences (NSF OCE) OCE-1657766, NSF Division of Ocean Sciences (NSF OCE) OCE-185071

Stochastic Cutoff Method for Long-Range Interacting Systems

A new Monte-Carlo method for long-range interacting systems is presented. This method consists of eliminating interactions stochastically with the detailed balance condition satisfied. When a pairwise interaction $V_{ij}$ of a $N$-particle system decreases with the distance as $r_{ij}^{-\alpha}$, computational time per one Monte Carlo step is ${\cal O}(N)$ for $\alpha \ge d$ and ${\cal O}(N^{2-\alpha/d})$ for $\alpha < d$, where $d$ is the spatial dimension. We apply the method to a two-dimensional magnetic dipolar system. The method enables us to treat a huge system of $256^2$ spins with reasonable computational time, and reproduces a circular order originated from long-range dipolar interactions.Comment: 18 pages, 9 figures, 1 figure and 1 reference are adde

The Frictionless Data Package : data containerization for addressing big data challenges [poster]

Presented at AGU Ocean Sciences, 11 - 16 February 2018, Portland, ORAt 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.NSF #1435578, NSF #163971

The Frictionless Data Package : data containerization for automated scientific workflows [poster]

Presented at the Fall AGU Meeting, New Orleans, LA, 11-15 December 2017As 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.National Science Foundation Award #1435578, Award #163971