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Dataset Title:  Isolation, culturing, and sequencing of bacteria and viruses collected in
Canoe Cove, Nahant, MA during 2010 (Marine Bacterial Viruses project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_658497)
Range: longitude = -70.906 to -70.906°E, latitude = 42.419 to 42.419°N
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Data Access Form | Files
 
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  bioproject_accession {
    String bcodmo_name "accession number";
    String description "The accession number of the BioProject(s) to which the BioSample belongs";
    String long_name "Bioproject Accession";
    String units "unitless";
  }
  env_biome {
    String bcodmo_name "site";
    String description "Descriptor of the broad ecological context of a sample.";
    String long_name "Env Biome";
    String units "unitless";
  }
  geo_loc_name {
    String bcodmo_name "site";
    String description "Geographical origin of the sample.";
    String long_name "Geo Loc Name";
    String units "unitless";
  }
  organism_type {
    String bcodmo_name "sample";
    String description "Type of organism described";
    String long_name "Organism Type";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  collection_date {
    String bcodmo_name "date";
    String description "Date of sampling; mm/dd/yy";
    String long_name "Collection Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  isolation_source {
    String bcodmo_name "site_descrip";
    String description "Describes the physical, environmental and/or local geographical source of the biological sample from which the sample was derived.";
    String long_name "Isolation Source";
    String units "unitless";
  }
  sample_name {
    String bcodmo_name "sample";
    String description "Sample name in source database";
    String long_name "Sample Name";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  organism {
    String bcodmo_name "species";
    String description "Organism associated with sample. Identitified to species when possible.";
    String long_name "Organism";
    String units "unitless";
  }
  strain {
    String bcodmo_name "sample";
    String description "Microbial or eukaryotic strain name";
    String long_name "Strain";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  isolate {
    String bcodmo_name "sample";
    String description "Identification or description of the specific individual from which this sample was obtained";
    String long_name "Isolate";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  host {
    String bcodmo_name "sample";
    String description "The natural (as opposed to laboratory) host to the organism from which the sample was obtained.";
    String long_name "Host";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  lab_host {
    String bcodmo_name "sample";
    String description "Scientific name and description of the laboratory host used to propagate the source organism or material from which the sample was obtained.";
    String long_name "Lab Host";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  sample_type {
    String bcodmo_name "sample_type";
    String description "Sample type, such as cell culture, mixed culture, tissue sample, whole organism, single cell, metagenomic assembly";
    String long_name "Sample Type";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 42.419, 42.419;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -70.906, -70.906;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  }
  temp {
    Float32 _FillValue NaN;
    Float32 actual_range 13.8, 16.3;
    String bcodmo_name "temperature";
    String description "Temperature of the sample at time of sampling.";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "degrees celsius";
  }
  ordinal_day_of_isolation {
    Int16 _FillValue 32767;
    Int16 actual_range 222, 286;
    String bcodmo_name "julian_day_yr0";
    String description "Day of year sample was isolated.";
    String long_name "Ordinal Day Of Isolation";
    String units "unitless";
  }
  description {
    String bcodmo_name "brief_desc";
    String description "Description of the sample.";
    String long_name "Description";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Bacteria and viruses were collected from the littoral marine zone at Canoe
Cove, Nahant, MA, USA, on August 22 [ordinal day 222], September 18 [261], and
October 13 [286], 2010.
 
Bacteria were collected using a previously described size-fractionation
method[1]. Bacterial strain naming convention is described using the example
of 10N.286.54.E5: the first position (here \\u201c10N\\u201d) indicates the year
(2010) and location (Nahant) of isolation, the second position (here
\\u201c286\\u201d) indicates the ordinal day of isolation, the third position
(here \\u201c54\\u201d) is a code representing the size-fraction of origin
(0.2um: 45,46,47; 1um: 48,49,50; 5um: 51,52,53; 63um: 54,55,56), and the
fourth position is the storage plate well identifier. Multiple codes within
the size-fraction identifier reflect independent water samples for the 63um
fraction, and independent water sample fractionation series for the other size
classes (water sample A: 45,51,54; sample B: 46, 52, 55; sample C: 47, 53,
56).
 
Bacterial genome libraries were prepared for sequencing using a tagmentation-
based approach and 1-2ng input DNA per isolate, as previously described[2].
Genomes were sequenced in multiplexed pools of 50-60 samples per Illumina
HiSeq lane. Accession numbers for all bacterial genomes associated with this
study are provided in Supplementary Table S1.
 
Bacterial phylogenetic relationships were determined by extracting ribosomal
proteins from 278 genomes with hmmsearch[3] and aligning with MAFFT[4] as
described in Hehemann et al. (2016)[5]. These strains were added to the
Vibrionaceae ribosomal phylogeny used in Hehemann et al., 2016 and taxonomy
was assigned using manual inspection. Full-length hsp60 sequences were also
extracted from these genomes using hmmsearch with default parameters and the
Cpn60 hmm (PF00118) from Pfam[6]. The hsp60 sequences were aligned using the
mafft-fftnsi algorithm. Sanger-sequenced hsp60 fragments from 40 strains
lacking genome sequences were added to this alignment using the mafft-fftnsi
algorithm with the --addfragments option. The hsp60 alignment was concatenated
to the ribosomal protein alignment and used to create a phylogeny using RAxML
under a partitioned general time reversible (GTR) model (options: \\u2013q, -m
GTRGAMMAX)[7]. SH-like supports were calculated using RAxML.
 
Viruses were collected using a previously described iron flocculation
approach[8], using 4L sample volumes, 0.2um pre-filtration to remove bacteria,
0.2um filters for floc-capture, and oxalate solution for resuspension to
maintain virus viability. Isolation of viruses was performed as follows. Iron-
oxalate concentrate volumes equivalent to 15mL of seawater were mixed into
agar overlays of 1,334 potential host Vibrio. The agar overlays were performed
by combining 150uL overnight host culture and virus concentrate directly on a
bottom agar (1% agar, 5% glycerol, 125mL/L of chitin supplement [40g/L
coarsely ground chitin, autoclaved, 0.2um filtered] in 2216MB), directly
pipetting 2mL of molten top agar (52 degrees C, 0.4% agar, 5% glycerol, in
2216MB) onto the bottom agar, and rapidly swirling to mix.\\u00a0 Plates were
incubated for 2 weeks, and plaques were archived for later purification.
Sequencing and genome analysis of viruses is described briefly, as follows.
High titer lysates of serially purified viruses were concentrated using 30kD
centrifugal filter units (Millipore, Amicon Ultra Centrifugal Filters,
Ultracel 30K, UFC903024) and washed with 1:100 Marine Broth 2216 to reduce
salts for nuclease treatment. Concentrates were brought to approximately 500uL
using 1:100 diluted 2216MB and then treated with DNase I and RNase A for 65
min at 37 degrees C to digest unencapsidated nucleic acids. Nuclease treated
viral lysates were extracted by addition of 1:10 final volume of SDS mix
(0.25M EDTA, 0.5M Tris-HCl (pH9.0), 2.5% sodium dodecyl sulfate), 30 min
incubation at 65C; addition of 0.125 volumes 8M potassium acetate, 60 min
incubation on ice; addition of 0.5 volumes phenol-chloroform; recovery of
nucleic acids from aqueous phase by isopropanol and ethanol precipitation.
Genomes were sequenced in multiplexed pools using Illumina MiSeq and HiSeq
technologies, assembled using CLC assembly cell, and manually curated to
standardize genome start positions for the Caudovirales.
 
Viral strain naming convention is described using the example of
1.008.O._10N.286.54.E5, with specific identifiers separated by a period. The
first position (here \\u201c1\\u201d) represents a unique identifier for each
independent plaque isolated from a given host from the initial exposure of a
given host to an environmental virus concentrate. The second position (here
\\u201c008\\u201d) represents a unique working ID for a host strain. The third
position (here \\u201cO\\u201d) indicates a unique sublineage generated from a
single plaque during viral serial purification, for example due to the
emergence of multiple plaque morphologies. Following the underscore is the
full strain ID of the host of isolation, as described above.
 
Accession numbers for all viral genomes associated with this study are
included under NCBI BioProject PRJNA328102.";
    String awards_0_award_nid "564675";
    String awards_0_award_number "OCE-1435868";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1435868";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"BioSample Submission Data for NCBI 
  L. Kelly and M. Polz, PIs 
  Version 8 September 2016";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String date_created "2016-09-09T19:11:48Z";
    String date_modified "2020-01-27T16:38:54Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.658497.1";
    Float64 Easternmost_Easting -70.906;
    Float64 geospatial_lat_max 42.419;
    Float64 geospatial_lat_min 42.419;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -70.906;
    Float64 geospatial_lon_min -70.906;
    String geospatial_lon_units "degrees_east";
    String history 
"2022-08-20T05:39:22Z (local files)
2022-08-20T05:39:22Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_658497.das";
    String infoUrl "https://www.bco-dmo.org/dataset/658497";
    String institution "BCO-DMO";
    String keywords "accession, bco, bco-dmo, biological, biome, bioproject, bioproject_accession, chemical, collection, collection_date, data, dataset, date, day, description, dmo, env, env_biome, erddap, geo, geo_loc_name, host, isolate, isolation, isolation_source, lab, lab_host, latitude, loc, longitude, management, name, oceanography, office, ordinal, ordinal_day_of_isolation, organism, organism_type, preliminary, sample, sample_name, sample_type, source, strain, temperature, type";
    String license "https://www.bco-dmo.org/dataset/658497/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/658497";
    Float64 Northernmost_Northing 42.419;
    String param_mapping "{'658497': {'lat': 'master - latitude', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/658497/parameters";
    String people_0_affiliation "Yeshiva University";
    String people_0_person_name "Dr Libusha Kelly";
    String people_0_person_nid "564679";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Massachusetts Institute of Technology";
    String people_1_affiliation_acronym "MIT";
    String people_1_person_name "Dr Martin Polz";
    String people_1_person_nid "564684";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Hannah Ake";
    String people_2_person_nid "650173";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Marine Bacterial Viruses";
    String projects_0_acronym "Marine Bacterial Viruses";
    String projects_0_description 
"Description from NSF award abstract:
Microbes make up the majority of the biomass in the ocean and viral mortality is one of the main ecological factors determining the diversity, abundance and turnover of microbial taxa. Yet, in spite of the known overall importance of viruses, the dynamics of their interactions with their specific microbial hosts remain poorly understood. This project will characterize viral strategies for survival and interaction with their hosts in the ocean, with the goal of enabling a better understanding of the conditions under which viruses can effectively control bacterial populations. The work will generate and integrate diverse data types, ranging from quantification of specific interactions, environmental dynamics of microbial hosts and their viruses, and comparative genome analysis. While the project focuses on the coastal ocean of New England, the approaches and findings will be applicable to the larger field of marine microbial ecology, to other virus/host systems in nature and to engineered systems. This project will fill a gap in current microbial ecology curricula by creating a bioinformatics module to provide training in large-scale sequence data collection and analysis. The module will be refined through testing during an annual course in Nicaragua and will be broadly accessible in the US and internationally. The close collaboration, throughout this project and its associated outreach, between two laboratories with complementary research strengths will provide highly interdisciplinary training for undergraduate students as well for two graduate students.
Viruses and their microbial hosts have co-evolved over billions of year and shape the ecology of the ocean in many ways. Broadly, understanding the mechanisms and emergent properties of virus-host interactions will allow for better understanding and modeling of biogeochemical cycles and the diversity of microbes at the population and genomic level. The guiding hypothesis of this project is that the prevalence of each of different viral strategies is probabilistic and linked to host availability, environmental parameters, and frequency-dependent competition with other virus strains for available hosts. This research will address four aims that characterize how viruses interact with their hosts in the dilute ocean environment by:
(1) quantification of ecological tradeoffs between specialist and generalist viral strategies,
(2) estimation of the prevalence of dual lytic/lysogenic strategy in marine viruses,
(3) identification of host surface receptors of particular viruses and examination of genetic signatures of distinct viral strategies in virus and host genomes, and
(4) identification of genetic and metabolic interactions between virus and host genomes.
This study takes advantage of a model system with the largest available collection of viruses and hosts for which host range and genome sequences have been determined. This work will provide fine-scale analysis of host and phage genomic diversity and abundance in this model system, while at the same time estimating host-range and co-infection, all of which represent important, poorly constrained parameters in virus-host interactions. Finally, this project complements the large number of studies that have looked at single host-virus interactions, metagenome sequencing, and assessment of viral impact on microbial production.";
    String projects_0_end_date "2017-08";
    String projects_0_geolocation "Coastal waters off Nahant, MA";
    String projects_0_name "How can bacterial viruses succeed in the marine environment?";
    String projects_0_project_nid "564676";
    String projects_0_start_date "2014-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 42.419;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "bioproject_accession,env_biome,geo_loc_name";
    String summary "Isolation, culturing, and sequencing of bacteria and viruses collected in Canoe Cove, Nahant, MA during 2010 (Marine Bacterial Viruses project)";
    String title "Isolation, culturing, and sequencing of bacteria and viruses collected in Canoe Cove, Nahant, MA during 2010 (Marine Bacterial Viruses project)";
    String version "1";
    Float64 Westernmost_Easting -70.906;
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.


 
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