Microbial and Mineralogical Characterizations of Soils Collected from the Deep Biosphere of the Former Homestake Gold Mine, South Dakota View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2010-10

AUTHORS

Gurdeep Rastogi, Shariff Osman, Ravi Kukkadapu, Mark Engelhard, Parag A. Vaishampayan, Gary L. Andersen, Rajesh K. Sani

ABSTRACT

A microbial census on deep biosphere (1.34 km depth) microbial communities was performed in two soil samples collected from the Ross and number 6 Winze sites of the former Homestake gold mine, Lead, South Dakota using high-density 16S microarrays (PhyloChip). Soil mineralogical characterization was carried out using X-ray diffraction, X-ray photoelectron, and Mössbauer spectroscopic techniques which demonstrated silicates and iron minerals (phyllosilicates and clays) in both samples. Microarray data revealed extensive bacterial diversity in soils and detected the largest number of taxa in Proteobacteria phylum followed by Firmicutes and Actinobacteria. The archael communities in the deep gold mine environments were less diverse and belonged to phyla Euryarchaeota and Crenarchaeota. Both the samples showed remarkable similarities in microbial communities (1,360 common OTUs) despite distinct geochemical characteristics. Fifty-seven phylotypes could not be classified even at phylum level representing a hitherto unidentified diversity in deep biosphere. PhyloChip data also suggested considerable metabolic diversity by capturing several physiological groups such as sulfur-oxidizer, ammonia-oxidizers, iron-oxidizers, methane-oxidizers, and sulfate-reducers in both samples. High-density microarrays revealed the greatest prokaryotic diversity ever reported from deep subsurface habitat of gold mines. More... »

PAGES

539-550

References to SciGraph publications

  • 2005-04. Bacterial community shift along a subsurface geothermal water stream in a Japanese gold mine in EXTREMOPHILES
  • 2009-07. Molecular Studies on the Microbial Diversity Associated with Mining-Impacted Coeur d’Alene River Sediments in MICROBIAL ECOLOGY
  • 2007-04. High-Density Universal 16S rRNA Microarray Analysis Reveals Broader Diversity than Typical Clone Library When Sampling the Environment in MICROBIAL ECOLOGY
  • 2009-11. Extracting nucleic acids from activated sludge which reflect community population diversity in ANTONIE VAN LEEUWENHOEK
  • 2003-08. Distribution and phylogenetic diversity of the subsurface microbial community in a Japanese epithermal gold mine in EXTREMOPHILES
  • 1997-08. Crystal Structure Refinement and Mössbauer Spectroscopy of an Ordered, Triclinic Clinochlore in CLAYS AND CLAY MINERALS
  • 2008-08. Towards environmental systems biology of Shewanella in NATURE REVIEWS MICROBIOLOGY
  • 2009-04. Isolation and characterization of cellulose-degrading bacteria from the deep subsurface of the Homestake gold mine, Lead, South Dakota, USA in JOURNAL OF INDUSTRIAL MICROBIOLOGY & BIOTECHNOLOGY
  • 2010-01. Microbial Diversity in Uranium Mining-Impacted Soils as Revealed by High-Density 16S Microarray and Clone Library in MICROBIAL ECOLOGY
  • 2004. Mössbauer Spectroscopy of Environmental Materials and Their Industrial Utilization in NONE
  • 2009-11. Microbial Communities in Subpermafrost Saline Fracture Water at the Lupin Au Mine, Nunavut, Canada in MICROBIAL ECOLOGY
  • 2009-08. Molecular analysis of prokaryotic diversity in the deep subsurface of the former Homestake gold mine, South Dakota, USA in JOURNAL OF MICROBIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00248-010-9657-y

    DOI

    http://dx.doi.org/10.1007/s00248-010-9657-y

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1037258980

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/20386898


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0503", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Soil Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/05", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Environmental Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Archaea", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Bacteria", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "DNA, Archaeal", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "DNA, Bacterial", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gold", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Mining", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Oligonucleotide Array Sequence Analysis", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Phylogeny", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "RNA, Ribosomal, 16S", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Sequence Analysis, DNA", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Soil Microbiology", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "South Dakota", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "University of California, Davis", 
              "id": "https://www.grid.ac/institutes/grid.27860.3b", 
              "name": [
                "Department of Chemical and Biological Engineering, South Dakota School of Mines and Technology, 57701, Rapid City, SD, USA", 
                "Department of Plant Pathology, University of California, 95616, Davis, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Rastogi", 
            "givenName": "Gurdeep", 
            "id": "sg:person.015167530421.43", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015167530421.43"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Lawrence Berkeley National Laboratory", 
              "id": "https://www.grid.ac/institutes/grid.184769.5", 
              "name": [
                "Ecology Department, Earth Sciences Division, Lawrence Berkeley National Laboratory, 94720, Berkeley, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Osman", 
            "givenName": "Shariff", 
            "id": "sg:person.01136037347.84", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136037347.84"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Pacific Northwest National Laboratory", 
              "id": "https://www.grid.ac/institutes/grid.451303.0", 
              "name": [
                "WR Wiley Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 99352, Richland, WA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kukkadapu", 
            "givenName": "Ravi", 
            "id": "sg:person.013242462472.75", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013242462472.75"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Pacific Northwest National Laboratory", 
              "id": "https://www.grid.ac/institutes/grid.451303.0", 
              "name": [
                "WR Wiley Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 99352, Richland, WA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Engelhard", 
            "givenName": "Mark", 
            "id": "sg:person.0635174077.43", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0635174077.43"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Jet Propulsion Lab", 
              "id": "https://www.grid.ac/institutes/grid.211367.0", 
              "name": [
                "California Institute of Technology, Jet Propulsion Laboratory, 91109, Pasadena, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Vaishampayan", 
            "givenName": "Parag A.", 
            "id": "sg:person.01154547436.35", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01154547436.35"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Lawrence Berkeley National Laboratory", 
              "id": "https://www.grid.ac/institutes/grid.184769.5", 
              "name": [
                "Ecology Department, Earth Sciences Division, Lawrence Berkeley National Laboratory, 94720, Berkeley, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Andersen", 
            "givenName": "Gary L.", 
            "id": "sg:person.01160741113.38", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01160741113.38"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "South Dakota School of Mines and Technology", 
              "id": "https://www.grid.ac/institutes/grid.263790.9", 
              "name": [
                "Department of Chemical and Biological Engineering, South Dakota School of Mines and Technology, 57701, Rapid City, SD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sani", 
            "givenName": "Rajesh K.", 
            "id": "sg:person.0711152065.74", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0711152065.74"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1111/j.1462-2920.2005.00881.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002130744"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1462-2920.2005.00881.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002130744"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00248-008-9445-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002461464", 
              "https://doi.org/10.1007/s00248-008-9445-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00248-008-9445-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002461464", 
              "https://doi.org/10.1007/s00248-008-9445-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1128/aem.67.21.5750-5760.2001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003795525"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/jobm.200900239", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006216787"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/jobm.200900239", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006216787"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1046/j.1462-2920.2003.00408.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006594392"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/713851170", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008284662"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1574-6976.1997.tb00351.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008492579"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1128/aem.67.5.2354-2359.2001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010648941"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1128/aem.68.5.2535-2541.2002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012300785"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00248-006-9134-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012794989", 
              "https://doi.org/10.1007/s00248-006-9134-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00248-006-9134-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012794989", 
              "https://doi.org/10.1007/s00248-006-9134-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00248-009-9598-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016375090", 
              "https://doi.org/10.1007/s00248-009-9598-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00248-009-9598-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016375090", 
              "https://doi.org/10.1007/s00248-009-9598-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00248-009-9598-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016375090", 
              "https://doi.org/10.1007/s00248-009-9598-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1046/j.1462-2920.2003.00512.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017818685"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00792-003-0324-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021815682", 
              "https://doi.org/10.1007/s00792-003-0324-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1574-6941.2006.00203.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023575408"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0168-583x(91)95681-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025757344"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0168-583x(91)95681-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025757344"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00248-009-9553-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025920987", 
              "https://doi.org/10.1007/s00248-009-9553-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00248-009-9553-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025920987", 
              "https://doi.org/10.1007/s00248-009-9553-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00248-009-9553-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025920987", 
              "https://doi.org/10.1007/s00248-009-9553-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.gca.2004.01.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026782524"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1139/m96-080", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027341816"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1128/aem.00120-09", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031507754"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0608255104", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032060705"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1037603589", 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4419-9040-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037603589", 
              "https://doi.org/10.1007/978-1-4419-9040-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4419-9040-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037603589", 
              "https://doi.org/10.1007/978-1-4419-9040-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrmicro1947", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038422319", 
              "https://doi.org/10.1038/nrmicro1947"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10482-009-9374-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040880856", 
              "https://doi.org/10.1007/s10482-009-9374-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10482-009-9374-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040880856", 
              "https://doi.org/10.1007/s10482-009-9374-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10482-009-9374-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040880856", 
              "https://doi.org/10.1007/s10482-009-9374-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/01490450600875696", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042591539"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12275-008-0249-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043449465", 
              "https://doi.org/10.1007/s12275-008-0249-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12275-008-0249-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043449465", 
              "https://doi.org/10.1007/s12275-008-0249-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1128/aem.72.3.1719-1728.2006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044410665"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1128/aem.00246-06", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048894991"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10295-009-0528-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050496871", 
              "https://doi.org/10.1007/s10295-009-0528-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10295-009-0528-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050496871", 
              "https://doi.org/10.1007/s10295-009-0528-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00792-005-0433-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050857413", 
              "https://doi.org/10.1007/s00792-005-0433-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00792-005-0433-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050857413", 
              "https://doi.org/10.1007/s00792-005-0433-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1099/ijs.0.64173-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060387104"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1116/1.1247873", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062163853"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1127376", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062453777"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1155495", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062457579"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1346/ccmn.1997.0450406", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1065020342"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1346/ccmn.1997.0450406", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1065020342", 
              "https://doi.org/10.1346/ccmn.1997.0450406"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1077158779", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1082873120", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1083211592", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2010-10", 
        "datePublishedReg": "2010-10-01", 
        "description": "A microbial census on deep biosphere (1.34\u00a0km depth) microbial communities was performed in two soil samples collected from the Ross and number 6 Winze sites of the former Homestake gold mine, Lead, South Dakota using high-density 16S microarrays (PhyloChip). Soil mineralogical characterization was carried out using X-ray diffraction, X-ray photoelectron, and M\u00f6ssbauer spectroscopic techniques which demonstrated silicates and iron minerals (phyllosilicates and clays) in both samples. Microarray data revealed extensive bacterial diversity in soils and detected the largest number of taxa in Proteobacteria phylum followed by Firmicutes and Actinobacteria. The archael communities in the deep gold mine environments were less diverse and belonged to phyla Euryarchaeota and Crenarchaeota. Both the samples showed remarkable similarities in microbial communities (1,360 common OTUs) despite distinct geochemical characteristics. Fifty-seven phylotypes could not be classified even at phylum level representing a hitherto unidentified diversity in deep biosphere. PhyloChip data also suggested considerable metabolic diversity by capturing several physiological groups such as sulfur-oxidizer, ammonia-oxidizers, iron-oxidizers, methane-oxidizers, and sulfate-reducers in both samples. High-density microarrays revealed the greatest prokaryotic diversity ever reported from deep subsurface habitat of gold mines.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s00248-010-9657-y", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1081458", 
            "issn": [
              "0095-3628", 
              "1432-184X"
            ], 
            "name": "Microbial Ecology", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "3", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "60"
          }
        ], 
        "name": "Microbial and Mineralogical Characterizations of Soils Collected from the Deep Biosphere of the Former Homestake Gold Mine, South Dakota", 
        "pagination": "539-550", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "b17d1a14e6498e0365755a2f18111d738e6dbd529419e70a0e7b51ac5bc74a97"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "20386898"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "7500663"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s00248-010-9657-y"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1037258980"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s00248-010-9657-y", 
          "https://app.dimensions.ai/details/publication/pub.1037258980"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T10:18", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000348_0000000348/records_54316_00000000.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007/s00248-010-9657-y"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00248-010-9657-y'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00248-010-9657-y'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00248-010-9657-y'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00248-010-9657-y'


     

    This table displays all metadata directly associated to this object as RDF triples.

    297 TRIPLES      21 PREDICATES      80 URIs      33 LITERALS      21 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s00248-010-9657-y schema:about N050df2e101314f208cd432273cd10285
    2 N479e5f6fe9cc4263a4fc03a461b94989
    3 N78554ca6022743758e1d9d5381abff7e
    4 N83271da5dd8f4c91bda5717518eb3778
    5 N8850503e946546ca96d7cd122e4f0511
    6 N8b6d702c5159482f9409c74b096cc861
    7 N8bdf640ba7e140e693ea507e5eba261e
    8 Nba15091fcb834f4088e7b6b6ffc18f34
    9 Nbcb79aea14a7457b8af012b622c0d165
    10 Nc325eedf31014614880cbd2b36535bcb
    11 Nd6a55ea9a9f5438e81f6dc02ba9f10f5
    12 Nee87d0cfa87b4a8ab388937d8c2ee5f8
    13 anzsrc-for:05
    14 anzsrc-for:0503
    15 schema:author N473db7f5d5134bb7b1082840cbb7c131
    16 schema:citation sg:pub.10.1007/978-1-4419-9040-2
    17 sg:pub.10.1007/s00248-006-9134-9
    18 sg:pub.10.1007/s00248-008-9445-0
    19 sg:pub.10.1007/s00248-009-9553-5
    20 sg:pub.10.1007/s00248-009-9598-5
    21 sg:pub.10.1007/s00792-003-0324-9
    22 sg:pub.10.1007/s00792-005-0433-8
    23 sg:pub.10.1007/s10295-009-0528-9
    24 sg:pub.10.1007/s10482-009-9374-z
    25 sg:pub.10.1007/s12275-008-0249-1
    26 sg:pub.10.1038/nrmicro1947
    27 sg:pub.10.1346/ccmn.1997.0450406
    28 https://app.dimensions.ai/details/publication/pub.1037603589
    29 https://app.dimensions.ai/details/publication/pub.1077158779
    30 https://app.dimensions.ai/details/publication/pub.1082873120
    31 https://app.dimensions.ai/details/publication/pub.1083211592
    32 https://doi.org/10.1002/jobm.200900239
    33 https://doi.org/10.1016/0168-583x(91)95681-3
    34 https://doi.org/10.1016/j.gca.2004.01.005
    35 https://doi.org/10.1046/j.1462-2920.2003.00408.x
    36 https://doi.org/10.1046/j.1462-2920.2003.00512.x
    37 https://doi.org/10.1073/pnas.0608255104
    38 https://doi.org/10.1080/01490450600875696
    39 https://doi.org/10.1080/713851170
    40 https://doi.org/10.1099/ijs.0.64173-0
    41 https://doi.org/10.1111/j.1462-2920.2005.00881.x
    42 https://doi.org/10.1111/j.1574-6941.2006.00203.x
    43 https://doi.org/10.1111/j.1574-6976.1997.tb00351.x
    44 https://doi.org/10.1116/1.1247873
    45 https://doi.org/10.1126/science.1127376
    46 https://doi.org/10.1126/science.1155495
    47 https://doi.org/10.1128/aem.00120-09
    48 https://doi.org/10.1128/aem.00246-06
    49 https://doi.org/10.1128/aem.67.21.5750-5760.2001
    50 https://doi.org/10.1128/aem.67.5.2354-2359.2001
    51 https://doi.org/10.1128/aem.68.5.2535-2541.2002
    52 https://doi.org/10.1128/aem.72.3.1719-1728.2006
    53 https://doi.org/10.1139/m96-080
    54 https://doi.org/10.1346/ccmn.1997.0450406
    55 schema:datePublished 2010-10
    56 schema:datePublishedReg 2010-10-01
    57 schema:description A microbial census on deep biosphere (1.34 km depth) microbial communities was performed in two soil samples collected from the Ross and number 6 Winze sites of the former Homestake gold mine, Lead, South Dakota using high-density 16S microarrays (PhyloChip). Soil mineralogical characterization was carried out using X-ray diffraction, X-ray photoelectron, and Mössbauer spectroscopic techniques which demonstrated silicates and iron minerals (phyllosilicates and clays) in both samples. Microarray data revealed extensive bacterial diversity in soils and detected the largest number of taxa in Proteobacteria phylum followed by Firmicutes and Actinobacteria. The archael communities in the deep gold mine environments were less diverse and belonged to phyla Euryarchaeota and Crenarchaeota. Both the samples showed remarkable similarities in microbial communities (1,360 common OTUs) despite distinct geochemical characteristics. Fifty-seven phylotypes could not be classified even at phylum level representing a hitherto unidentified diversity in deep biosphere. PhyloChip data also suggested considerable metabolic diversity by capturing several physiological groups such as sulfur-oxidizer, ammonia-oxidizers, iron-oxidizers, methane-oxidizers, and sulfate-reducers in both samples. High-density microarrays revealed the greatest prokaryotic diversity ever reported from deep subsurface habitat of gold mines.
    58 schema:genre research_article
    59 schema:inLanguage en
    60 schema:isAccessibleForFree false
    61 schema:isPartOf N42ed6f4c74d74cd88cc5d4b5a6ed46fe
    62 Nda63a52ade3f4afea7f244d8fc02744e
    63 sg:journal.1081458
    64 schema:name Microbial and Mineralogical Characterizations of Soils Collected from the Deep Biosphere of the Former Homestake Gold Mine, South Dakota
    65 schema:pagination 539-550
    66 schema:productId N49375a8d6f66462f929f1df5323e3b0a
    67 N4968dacecd054c0e935b1929460c3d54
    68 N4e33f634ae994179a6e451fefcf0f44f
    69 N8c295cc296e7485188050ac7ccc10488
    70 Nf9d4c0a66d5e4556bc0af47cc815c909
    71 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037258980
    72 https://doi.org/10.1007/s00248-010-9657-y
    73 schema:sdDatePublished 2019-04-11T10:18
    74 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    75 schema:sdPublisher N55a649c1598040e7abfe6fecef8e03f9
    76 schema:url http://link.springer.com/10.1007/s00248-010-9657-y
    77 sgo:license sg:explorer/license/
    78 sgo:sdDataset articles
    79 rdf:type schema:ScholarlyArticle
    80 N034421cc5c3544b19025997bfb2b0f50 rdf:first sg:person.01160741113.38
    81 rdf:rest Neb599eb78eff40918dfaf217be2067fb
    82 N050df2e101314f208cd432273cd10285 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    83 schema:name South Dakota
    84 rdf:type schema:DefinedTerm
    85 N24371d36efc64f299164980779b1217d rdf:first sg:person.013242462472.75
    86 rdf:rest N5007ad2a1d79436f860224156673323b
    87 N2f8864c2e9234410803bcf5dbe9592d7 rdf:first sg:person.01154547436.35
    88 rdf:rest N034421cc5c3544b19025997bfb2b0f50
    89 N42ed6f4c74d74cd88cc5d4b5a6ed46fe schema:volumeNumber 60
    90 rdf:type schema:PublicationVolume
    91 N473db7f5d5134bb7b1082840cbb7c131 rdf:first sg:person.015167530421.43
    92 rdf:rest N81fa85f98a9348cbba9a48959747c0de
    93 N479e5f6fe9cc4263a4fc03a461b94989 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    94 schema:name RNA, Ribosomal, 16S
    95 rdf:type schema:DefinedTerm
    96 N49375a8d6f66462f929f1df5323e3b0a schema:name dimensions_id
    97 schema:value pub.1037258980
    98 rdf:type schema:PropertyValue
    99 N4968dacecd054c0e935b1929460c3d54 schema:name pubmed_id
    100 schema:value 20386898
    101 rdf:type schema:PropertyValue
    102 N4e33f634ae994179a6e451fefcf0f44f schema:name nlm_unique_id
    103 schema:value 7500663
    104 rdf:type schema:PropertyValue
    105 N5007ad2a1d79436f860224156673323b rdf:first sg:person.0635174077.43
    106 rdf:rest N2f8864c2e9234410803bcf5dbe9592d7
    107 N55a649c1598040e7abfe6fecef8e03f9 schema:name Springer Nature - SN SciGraph project
    108 rdf:type schema:Organization
    109 N78554ca6022743758e1d9d5381abff7e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    110 schema:name Gold
    111 rdf:type schema:DefinedTerm
    112 N81fa85f98a9348cbba9a48959747c0de rdf:first sg:person.01136037347.84
    113 rdf:rest N24371d36efc64f299164980779b1217d
    114 N83271da5dd8f4c91bda5717518eb3778 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    115 schema:name DNA, Archaeal
    116 rdf:type schema:DefinedTerm
    117 N8850503e946546ca96d7cd122e4f0511 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    118 schema:name DNA, Bacterial
    119 rdf:type schema:DefinedTerm
    120 N8b6d702c5159482f9409c74b096cc861 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    121 schema:name Bacteria
    122 rdf:type schema:DefinedTerm
    123 N8bdf640ba7e140e693ea507e5eba261e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    124 schema:name Phylogeny
    125 rdf:type schema:DefinedTerm
    126 N8c295cc296e7485188050ac7ccc10488 schema:name readcube_id
    127 schema:value b17d1a14e6498e0365755a2f18111d738e6dbd529419e70a0e7b51ac5bc74a97
    128 rdf:type schema:PropertyValue
    129 Nba15091fcb834f4088e7b6b6ffc18f34 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    130 schema:name Archaea
    131 rdf:type schema:DefinedTerm
    132 Nbcb79aea14a7457b8af012b622c0d165 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    133 schema:name Oligonucleotide Array Sequence Analysis
    134 rdf:type schema:DefinedTerm
    135 Nc325eedf31014614880cbd2b36535bcb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    136 schema:name Sequence Analysis, DNA
    137 rdf:type schema:DefinedTerm
    138 Nd6a55ea9a9f5438e81f6dc02ba9f10f5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    139 schema:name Mining
    140 rdf:type schema:DefinedTerm
    141 Nda63a52ade3f4afea7f244d8fc02744e schema:issueNumber 3
    142 rdf:type schema:PublicationIssue
    143 Neb599eb78eff40918dfaf217be2067fb rdf:first sg:person.0711152065.74
    144 rdf:rest rdf:nil
    145 Nee87d0cfa87b4a8ab388937d8c2ee5f8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    146 schema:name Soil Microbiology
    147 rdf:type schema:DefinedTerm
    148 Nf9d4c0a66d5e4556bc0af47cc815c909 schema:name doi
    149 schema:value 10.1007/s00248-010-9657-y
    150 rdf:type schema:PropertyValue
    151 anzsrc-for:05 schema:inDefinedTermSet anzsrc-for:
    152 schema:name Environmental Sciences
    153 rdf:type schema:DefinedTerm
    154 anzsrc-for:0503 schema:inDefinedTermSet anzsrc-for:
    155 schema:name Soil Sciences
    156 rdf:type schema:DefinedTerm
    157 sg:journal.1081458 schema:issn 0095-3628
    158 1432-184X
    159 schema:name Microbial Ecology
    160 rdf:type schema:Periodical
    161 sg:person.01136037347.84 schema:affiliation https://www.grid.ac/institutes/grid.184769.5
    162 schema:familyName Osman
    163 schema:givenName Shariff
    164 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136037347.84
    165 rdf:type schema:Person
    166 sg:person.01154547436.35 schema:affiliation https://www.grid.ac/institutes/grid.211367.0
    167 schema:familyName Vaishampayan
    168 schema:givenName Parag A.
    169 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01154547436.35
    170 rdf:type schema:Person
    171 sg:person.01160741113.38 schema:affiliation https://www.grid.ac/institutes/grid.184769.5
    172 schema:familyName Andersen
    173 schema:givenName Gary L.
    174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01160741113.38
    175 rdf:type schema:Person
    176 sg:person.013242462472.75 schema:affiliation https://www.grid.ac/institutes/grid.451303.0
    177 schema:familyName Kukkadapu
    178 schema:givenName Ravi
    179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013242462472.75
    180 rdf:type schema:Person
    181 sg:person.015167530421.43 schema:affiliation https://www.grid.ac/institutes/grid.27860.3b
    182 schema:familyName Rastogi
    183 schema:givenName Gurdeep
    184 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015167530421.43
    185 rdf:type schema:Person
    186 sg:person.0635174077.43 schema:affiliation https://www.grid.ac/institutes/grid.451303.0
    187 schema:familyName Engelhard
    188 schema:givenName Mark
    189 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0635174077.43
    190 rdf:type schema:Person
    191 sg:person.0711152065.74 schema:affiliation https://www.grid.ac/institutes/grid.263790.9
    192 schema:familyName Sani
    193 schema:givenName Rajesh K.
    194 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0711152065.74
    195 rdf:type schema:Person
    196 sg:pub.10.1007/978-1-4419-9040-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037603589
    197 https://doi.org/10.1007/978-1-4419-9040-2
    198 rdf:type schema:CreativeWork
    199 sg:pub.10.1007/s00248-006-9134-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012794989
    200 https://doi.org/10.1007/s00248-006-9134-9
    201 rdf:type schema:CreativeWork
    202 sg:pub.10.1007/s00248-008-9445-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002461464
    203 https://doi.org/10.1007/s00248-008-9445-0
    204 rdf:type schema:CreativeWork
    205 sg:pub.10.1007/s00248-009-9553-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025920987
    206 https://doi.org/10.1007/s00248-009-9553-5
    207 rdf:type schema:CreativeWork
    208 sg:pub.10.1007/s00248-009-9598-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016375090
    209 https://doi.org/10.1007/s00248-009-9598-5
    210 rdf:type schema:CreativeWork
    211 sg:pub.10.1007/s00792-003-0324-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021815682
    212 https://doi.org/10.1007/s00792-003-0324-9
    213 rdf:type schema:CreativeWork
    214 sg:pub.10.1007/s00792-005-0433-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050857413
    215 https://doi.org/10.1007/s00792-005-0433-8
    216 rdf:type schema:CreativeWork
    217 sg:pub.10.1007/s10295-009-0528-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050496871
    218 https://doi.org/10.1007/s10295-009-0528-9
    219 rdf:type schema:CreativeWork
    220 sg:pub.10.1007/s10482-009-9374-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1040880856
    221 https://doi.org/10.1007/s10482-009-9374-z
    222 rdf:type schema:CreativeWork
    223 sg:pub.10.1007/s12275-008-0249-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043449465
    224 https://doi.org/10.1007/s12275-008-0249-1
    225 rdf:type schema:CreativeWork
    226 sg:pub.10.1038/nrmicro1947 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038422319
    227 https://doi.org/10.1038/nrmicro1947
    228 rdf:type schema:CreativeWork
    229 sg:pub.10.1346/ccmn.1997.0450406 schema:sameAs https://app.dimensions.ai/details/publication/pub.1065020342
    230 https://doi.org/10.1346/ccmn.1997.0450406
    231 rdf:type schema:CreativeWork
    232 https://app.dimensions.ai/details/publication/pub.1037603589 schema:CreativeWork
    233 https://app.dimensions.ai/details/publication/pub.1077158779 schema:CreativeWork
    234 https://app.dimensions.ai/details/publication/pub.1082873120 schema:CreativeWork
    235 https://app.dimensions.ai/details/publication/pub.1083211592 schema:CreativeWork
    236 https://doi.org/10.1002/jobm.200900239 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006216787
    237 rdf:type schema:CreativeWork
    238 https://doi.org/10.1016/0168-583x(91)95681-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025757344
    239 rdf:type schema:CreativeWork
    240 https://doi.org/10.1016/j.gca.2004.01.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026782524
    241 rdf:type schema:CreativeWork
    242 https://doi.org/10.1046/j.1462-2920.2003.00408.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1006594392
    243 rdf:type schema:CreativeWork
    244 https://doi.org/10.1046/j.1462-2920.2003.00512.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1017818685
    245 rdf:type schema:CreativeWork
    246 https://doi.org/10.1073/pnas.0608255104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032060705
    247 rdf:type schema:CreativeWork
    248 https://doi.org/10.1080/01490450600875696 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042591539
    249 rdf:type schema:CreativeWork
    250 https://doi.org/10.1080/713851170 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008284662
    251 rdf:type schema:CreativeWork
    252 https://doi.org/10.1099/ijs.0.64173-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060387104
    253 rdf:type schema:CreativeWork
    254 https://doi.org/10.1111/j.1462-2920.2005.00881.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1002130744
    255 rdf:type schema:CreativeWork
    256 https://doi.org/10.1111/j.1574-6941.2006.00203.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1023575408
    257 rdf:type schema:CreativeWork
    258 https://doi.org/10.1111/j.1574-6976.1997.tb00351.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1008492579
    259 rdf:type schema:CreativeWork
    260 https://doi.org/10.1116/1.1247873 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062163853
    261 rdf:type schema:CreativeWork
    262 https://doi.org/10.1126/science.1127376 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062453777
    263 rdf:type schema:CreativeWork
    264 https://doi.org/10.1126/science.1155495 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062457579
    265 rdf:type schema:CreativeWork
    266 https://doi.org/10.1128/aem.00120-09 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031507754
    267 rdf:type schema:CreativeWork
    268 https://doi.org/10.1128/aem.00246-06 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048894991
    269 rdf:type schema:CreativeWork
    270 https://doi.org/10.1128/aem.67.21.5750-5760.2001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003795525
    271 rdf:type schema:CreativeWork
    272 https://doi.org/10.1128/aem.67.5.2354-2359.2001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010648941
    273 rdf:type schema:CreativeWork
    274 https://doi.org/10.1128/aem.68.5.2535-2541.2002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012300785
    275 rdf:type schema:CreativeWork
    276 https://doi.org/10.1128/aem.72.3.1719-1728.2006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044410665
    277 rdf:type schema:CreativeWork
    278 https://doi.org/10.1139/m96-080 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027341816
    279 rdf:type schema:CreativeWork
    280 https://doi.org/10.1346/ccmn.1997.0450406 schema:sameAs https://app.dimensions.ai/details/publication/pub.1065020342
    281 rdf:type schema:CreativeWork
    282 https://www.grid.ac/institutes/grid.184769.5 schema:alternateName Lawrence Berkeley National Laboratory
    283 schema:name Ecology Department, Earth Sciences Division, Lawrence Berkeley National Laboratory, 94720, Berkeley, CA, USA
    284 rdf:type schema:Organization
    285 https://www.grid.ac/institutes/grid.211367.0 schema:alternateName Jet Propulsion Lab
    286 schema:name California Institute of Technology, Jet Propulsion Laboratory, 91109, Pasadena, CA, USA
    287 rdf:type schema:Organization
    288 https://www.grid.ac/institutes/grid.263790.9 schema:alternateName South Dakota School of Mines and Technology
    289 schema:name Department of Chemical and Biological Engineering, South Dakota School of Mines and Technology, 57701, Rapid City, SD, USA
    290 rdf:type schema:Organization
    291 https://www.grid.ac/institutes/grid.27860.3b schema:alternateName University of California, Davis
    292 schema:name Department of Chemical and Biological Engineering, South Dakota School of Mines and Technology, 57701, Rapid City, SD, USA
    293 Department of Plant Pathology, University of California, 95616, Davis, USA
    294 rdf:type schema:Organization
    295 https://www.grid.ac/institutes/grid.451303.0 schema:alternateName Pacific Northwest National Laboratory
    296 schema:name WR Wiley Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 99352, Richland, WA, USA
    297 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...