Candidate probiotic Lactiplantibacillus plantarum HNU082 rapidly and convergently evolves within human, mice, and zebrafish gut but differentially influences the resident ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2021-06-30

AUTHORS

Shi Huang, Shuaiming Jiang, Dongxue Huo, Celeste Allaband, Mehrbod Estaki, Victor Cantu, Pedro Belda-Ferre, Yoshiki Vázquez-Baeza, Qiyun Zhu, Chenchen Ma, Congfa Li, Amir Zarrinpar, Yang-Yu Liu, Rob Knight, Jiachao Zhang

ABSTRACT

BackgroundImproving probiotic engraftment in the human gut requires a thorough understanding of the in vivo adaptive strategies of probiotics in diverse contexts. However, for most probiotic strains, these in vivo genetic processes are still poorly characterized. Here, we investigated the effects of gut selection pressures from human, mice, and zebrafish on the genetic stability of a candidate probiotic Lactiplantibacillus plantarum HNU082 (Lp082) as well as its ecological and evolutionary impacts on the indigenous gut microbiota using shotgun metagenomic sequencing in combination with isolate resequencing methods.ResultsWe combined both metagenomics and isolate whole genome sequencing approaches to systematically study the gut-adaptive evolution of probiotic L. plantarum and the ecological and evolutionary changes of resident gut microbiomes in response to probiotic ingestion in multiple host species. Independent of host model, Lp082 colonized and adapted to the gut by acquiring highly consistent single-nucleotide mutations, which primarily modulated carbohydrate utilization and acid tolerance. We cultivated the probiotic mutants and validated that these gut-adapted mutations were genetically stable for at least 3 months and improved their fitness in vitro. In turn, resident gut microbial strains, especially competing strains with Lp082 (e.g., Bacteroides spp. and Bifidobacterium spp.), actively responded to Lp082 engraftment by accumulating 10–70 times more evolutionary changes than usual. Human gut microbiota exhibited a higher ecological and genetic stability than that of mice.ConclusionsCollectively, our results suggest a highly convergent adaptation strategy of Lp082 across three different host environments. In contrast, the evolutionary changes within the resident gut microbes in response to Lp082 were more divergent and host-specific; however, these changes were not associated with any adverse outcomes. This work lays a theoretical foundation for leveraging animal models for ex vivo engineering of probiotics to improve engraftment outcomes in humans.1TYRt-mQpEqyYou2DA7bqRVideo abstract More... »

PAGES

151

References to SciGraph publications

  • 2014-06-10. The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic in NATURE REVIEWS GASTROENTEROLOGY & HEPATOLOGY
  • 2018-10-30. Species-level functional profiling of metagenomes and metatranscriptomes in NATURE METHODS
  • 2016-02-12. AdapterRemoval v2: rapid adapter trimming, identification, and read merging in BMC RESEARCH NOTES
  • 2012-11-18. Fucose sensing regulates bacterial intestinal colonization in NATURE
  • 2019-06-20. Establishing microbial composition measurement standards with reference frames in NATURE COMMUNICATIONS
  • 2017-06-14. Expert consensus document: The International Scientific Association for Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of prebiotics in NATURE REVIEWS GASTROENTEROLOGY & HEPATOLOGY
  • 2012-12-27. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler in GIGASCIENCE
  • 2014-12-03. Temporal variability is a personalized feature of the human microbiome in GENOME BIOLOGY
  • 2019-11-28. Improved metagenomic analysis with Kraken 2 in GENOME BIOLOGY
  • 2016-08-31. Metagenomic approach reveals microbial diversity and predictive microbial metabolic pathways in Yucha, a traditional Li fermented food in SCIENTIFIC REPORTS
  • 2018-02-28. Environment dominates over host genetics in shaping human gut microbiota in NATURE
  • 2010-05-27. Convergence in probiotic Lactobacillus gut-adaptive responses in humans and mice in THE ISME JOURNAL: MULTIDISCIPLINARY JOURNAL OF MICROBIAL ECOLOGY
  • 2019-11-07. Genomic and epidemiological evidence of bacterial transmission from probiotic capsule to blood in ICU patients in NATURE MEDICINE
  • 2012-03-04. Fast gapped-read alignment with Bowtie 2 in NATURE METHODS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s40168-021-01102-0

    DOI

    http://dx.doi.org/10.1186/s40168-021-01102-0

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1139274963

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/34193290


    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/2008/06", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Biological Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Genetics", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Animals", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Bifidobacterium", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gastrointestinal Microbiome", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Humans", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Mice", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Microbiota", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Probiotics", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Zebrafish", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "School of Food Science and Engineering, Hainan University, Haikou, China", 
                "UCSD Health Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
                "Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Huang", 
            "givenName": "Shi", 
            "id": "sg:person.01074626724.22", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01074626724.22"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "School of Food Science and Engineering, Hainan University, Haikou, China", 
              "id": "http://www.grid.ac/institutes/grid.428986.9", 
              "name": [
                "School of Food Science and Engineering, Hainan University, Haikou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Jiang", 
            "givenName": "Shuaiming", 
            "id": "sg:person.015734664417.36", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015734664417.36"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "School of Food Science and Engineering, Hainan University, Haikou, China", 
              "id": "http://www.grid.ac/institutes/grid.428986.9", 
              "name": [
                "School of Food Science and Engineering, Hainan University, Haikou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Huo", 
            "givenName": "Dongxue", 
            "id": "sg:person.0620460120.04", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0620460120.04"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Biomedical Sciences Graduate Program, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "Biomedical Sciences Graduate Program, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Allaband", 
            "givenName": "Celeste", 
            "id": "sg:person.0625665663.23", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0625665663.23"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "UCSD Health Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "UCSD Health Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Estaki", 
            "givenName": "Mehrbod", 
            "id": "sg:person.0715356340.58", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715356340.58"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Cantu", 
            "givenName": "Victor", 
            "id": "sg:person.016507333101.73", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016507333101.73"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "UCSD Health Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
                "Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Belda-Ferre", 
            "givenName": "Pedro", 
            "id": "sg:person.01255245123.96", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01255245123.96"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "UCSD Health Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
                "Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "V\u00e1zquez-Baeza", 
            "givenName": "Yoshiki", 
            "id": "sg:person.01113460501.49", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01113460501.49"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "UCSD Health Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
                "Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Zhu", 
            "givenName": "Qiyun", 
            "id": "sg:person.011522220701.89", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011522220701.89"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "School of Food Science and Engineering, Hainan University, Haikou, China", 
              "id": "http://www.grid.ac/institutes/grid.428986.9", 
              "name": [
                "School of Food Science and Engineering, Hainan University, Haikou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ma", 
            "givenName": "Chenchen", 
            "id": "sg:person.012566567664.88", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012566567664.88"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Key Laboratory of Food Nutrition and Functional Food of Hainan Province, 570228, Haikou, China", 
              "id": "http://www.grid.ac/institutes/None", 
              "name": [
                "School of Food Science and Engineering, Hainan University, Haikou, China", 
                "Key Laboratory of Food Nutrition and Functional Food of Hainan Province, 570228, Haikou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Li", 
            "givenName": "Congfa", 
            "id": "sg:person.0660713743.85", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0660713743.85"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "VA San Diego Healthcare, 3350 La Jolla Village Dr, 92161, San Diego, CA, USA", 
              "id": "http://www.grid.ac/institutes/None", 
              "name": [
                "Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
                "UCSD Division of Gastroenterology, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
                "VA San Diego Healthcare, 3350 La Jolla Village Dr, 92161, San Diego, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Zarrinpar", 
            "givenName": "Amir", 
            "id": "sg:person.010546227027.19", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010546227027.19"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Channing Division of Network Medicine, Department of Medicine, Brigham and Women\u2019s Hospital and Harvard Medical School, 02115, Boston, MA, USA", 
              "id": "http://www.grid.ac/institutes/grid.38142.3c", 
              "name": [
                "Channing Division of Network Medicine, Department of Medicine, Brigham and Women\u2019s Hospital and Harvard Medical School, 02115, Boston, MA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Liu", 
            "givenName": "Yang-Yu", 
            "id": "sg:person.01013373644.11", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01013373644.11"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "UCSD Health Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
                "Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
                "Biomedical Sciences Graduate Program, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
                "Department of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Knight", 
            "givenName": "Rob", 
            "id": "sg:person.016311745377.96", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016311745377.96"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Key Laboratory of Food Nutrition and Functional Food of Hainan Province, 570228, Haikou, China", 
              "id": "http://www.grid.ac/institutes/None", 
              "name": [
                "School of Food Science and Engineering, Hainan University, Haikou, China", 
                "UCSD Health Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA", 
                "Key Laboratory of Food Nutrition and Functional Food of Hainan Province, 570228, Haikou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Zhang", 
            "givenName": "Jiachao", 
            "id": "sg:person.011346604554.69", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011346604554.69"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1186/s13059-014-0531-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034675947", 
              "https://doi.org/10.1186/s13059-014-0531-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13104-016-1900-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040653018", 
              "https://doi.org/10.1186/s13104-016-1900-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrgastro.2017.75", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1086020795", 
              "https://doi.org/10.1038/nrgastro.2017.75"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1923", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006541515", 
              "https://doi.org/10.1038/nmeth.1923"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep32524", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003566262", 
              "https://doi.org/10.1038/srep32524"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41467-019-10656-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1117296456", 
              "https://doi.org/10.1038/s41467-019-10656-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41592-018-0176-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1107804224", 
              "https://doi.org/10.1038/s41592-018-0176-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ismej.2010.61", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037681660", 
              "https://doi.org/10.1038/ismej.2010.61"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41591-019-0626-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1122362111", 
              "https://doi.org/10.1038/s41591-019-0626-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrgastro.2014.66", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012609471", 
              "https://doi.org/10.1038/nrgastro.2014.66"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/2047-217x-1-18", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016521225", 
              "https://doi.org/10.1186/2047-217x-1-18"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature25973", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101264718", 
              "https://doi.org/10.1038/nature25973"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature11623", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044708958", 
              "https://doi.org/10.1038/nature11623"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-019-1891-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1122989517", 
              "https://doi.org/10.1186/s13059-019-1891-0"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2021-06-30", 
        "datePublishedReg": "2021-06-30", 
        "description": "BackgroundImproving probiotic engraftment in the human gut requires a thorough understanding of the in vivo adaptive strategies of probiotics in diverse contexts. However, for most probiotic strains, these in vivo genetic processes are still poorly characterized. Here, we investigated the effects of gut selection pressures from human, mice, and zebrafish on the genetic stability of a candidate probiotic Lactiplantibacillus plantarum HNU082 (Lp082) as well as its ecological and evolutionary impacts on the indigenous gut microbiota using shotgun metagenomic sequencing in combination with isolate resequencing methods.ResultsWe combined both metagenomics and isolate whole genome sequencing approaches to systematically study the gut-adaptive evolution of probiotic L. plantarum and the ecological and evolutionary changes of resident gut microbiomes in response to probiotic ingestion in multiple host species. Independent of host model, Lp082 colonized and adapted to the gut by acquiring highly consistent single-nucleotide mutations, which primarily modulated carbohydrate utilization and acid tolerance. We cultivated the probiotic mutants and validated that these gut-adapted mutations were genetically stable for at least 3 months and improved their fitness in vitro. In turn, resident gut microbial strains, especially competing strains with Lp082 (e.g., Bacteroides spp. and Bifidobacterium spp.), actively responded to Lp082 engraftment by accumulating 10\u201370 times more evolutionary changes than usual. Human gut microbiota exhibited a higher ecological and genetic stability than that of mice.ConclusionsCollectively, our results suggest a highly convergent adaptation strategy of Lp082 across three different host environments. In contrast, the evolutionary changes within the resident gut microbes in response to Lp082 were more divergent and host-specific; however, these changes were not associated with any adverse outcomes. This work lays a theoretical foundation for leveraging animal models for ex vivo engineering of probiotics to improve engraftment outcomes in humans.1TYRt-mQpEqyYou2DA7bqRVideo abstract", 
        "genre": "article", 
        "id": "sg:pub.10.1186/s40168-021-01102-0", 
        "inLanguage": "en", 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.7028139", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.8556184", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.8744733", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.8554837", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.4242003", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.7752854", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.7614455", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.4455483", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.8557027", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.3537236", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.7614321", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.8199846", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.9413418", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.2439028", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1048878", 
            "issn": [
              "2049-2618"
            ], 
            "name": "Microbiome", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "9"
          }
        ], 
        "keywords": [
          "evolutionary change", 
          "genetic stability", 
          "multiple host species", 
          "whole genome sequencing approach", 
          "genome sequencing approach", 
          "resident gut microbes", 
          "single nucleotide mutations", 
          "different host environments", 
          "shotgun metagenomic sequencing", 
          "resident gut microbiome", 
          "evolutionary impact", 
          "human gut microbiota", 
          "zebrafish gut", 
          "indigenous gut microbiota", 
          "host species", 
          "selection pressure", 
          "sequencing approach", 
          "gut microbiota", 
          "genetic processes", 
          "metagenomic sequencing", 
          "acid tolerance", 
          "host environment", 
          "gut microbes", 
          "human gut", 
          "resident microbiome", 
          "ex vivo engineering", 
          "carbohydrate utilization", 
          "gut microbiome", 
          "microbiome", 
          "mutations", 
          "adaptive strategies", 
          "host model", 
          "vivo engineering", 
          "probiotic L. plantarum", 
          "L. plantarum", 
          "gut", 
          "microbiota", 
          "metagenomics", 
          "mutants", 
          "microbes", 
          "humans", 
          "species", 
          "sequencing", 
          "strains", 
          "mice", 
          "fitness", 
          "adaptation strategies", 
          "probiotic strains", 
          "thorough understanding", 
          "isolates", 
          "engraftment outcomes", 
          "animal models", 
          "tolerance", 
          "plantarum", 
          "probiotics", 
          "response", 
          "changes", 
          "evolution", 
          "engraftment", 
          "understanding", 
          "most probiotic strains", 
          "contrast", 
          "strategies", 
          "probiotic ingestion", 
          "environment", 
          "engineering", 
          "turn", 
          "stability", 
          "ResultsWe", 
          "evolves", 
          "combination", 
          "process", 
          "ingestion", 
          "effect", 
          "utilization", 
          "impact", 
          "results", 
          "diverse contexts", 
          "model", 
          "foundation", 
          "approach", 
          "context", 
          "work", 
          "method", 
          "theoretical foundation", 
          "pressure", 
          "outcomes", 
          "months", 
          "adverse outcomes"
        ], 
        "name": "Candidate probiotic Lactiplantibacillus plantarum HNU082 rapidly and convergently evolves within human, mice, and zebrafish gut but differentially influences the resident microbiome", 
        "pagination": "151", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1139274963"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/s40168-021-01102-0"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "34193290"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/s40168-021-01102-0", 
          "https://app.dimensions.ai/details/publication/pub.1139274963"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-06-01T22:24", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20220601/entities/gbq_results/article/article_880.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1186/s40168-021-01102-0"
      }
    ]
     

    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.10.1186/s40168-021-01102-0'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s40168-021-01102-0'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s40168-021-01102-0'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s40168-021-01102-0'


     

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

    388 TRIPLES      22 PREDICATES      137 URIs      115 LITERALS      15 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/s40168-021-01102-0 schema:about N689ff0920f9a4712af64de3cc6a0e4a6
    2 N6ee0ec794da54de288b6379b1d030c9d
    3 N714d672a8fc6498d8d74c677c5bc8272
    4 N991d736e3f4043b785d6877d86a5a832
    5 N9f02b48ef556443bb2d004e9fb2cc53f
    6 Na01a6202fb784185a8e34becae9fd622
    7 Nb8d0b261f1764234a5119d2b162aa1b0
    8 Ne92930f491ea46b781cf875456325d90
    9 anzsrc-for:06
    10 anzsrc-for:0604
    11 schema:author N200b6c15f30942e9ab9286594c116294
    12 schema:citation sg:pub.10.1038/ismej.2010.61
    13 sg:pub.10.1038/nature11623
    14 sg:pub.10.1038/nature25973
    15 sg:pub.10.1038/nmeth.1923
    16 sg:pub.10.1038/nrgastro.2014.66
    17 sg:pub.10.1038/nrgastro.2017.75
    18 sg:pub.10.1038/s41467-019-10656-5
    19 sg:pub.10.1038/s41591-019-0626-9
    20 sg:pub.10.1038/s41592-018-0176-y
    21 sg:pub.10.1038/srep32524
    22 sg:pub.10.1186/2047-217x-1-18
    23 sg:pub.10.1186/s13059-014-0531-y
    24 sg:pub.10.1186/s13059-019-1891-0
    25 sg:pub.10.1186/s13104-016-1900-2
    26 schema:datePublished 2021-06-30
    27 schema:datePublishedReg 2021-06-30
    28 schema:description BackgroundImproving probiotic engraftment in the human gut requires a thorough understanding of the in vivo adaptive strategies of probiotics in diverse contexts. However, for most probiotic strains, these in vivo genetic processes are still poorly characterized. Here, we investigated the effects of gut selection pressures from human, mice, and zebrafish on the genetic stability of a candidate probiotic Lactiplantibacillus plantarum HNU082 (Lp082) as well as its ecological and evolutionary impacts on the indigenous gut microbiota using shotgun metagenomic sequencing in combination with isolate resequencing methods.ResultsWe combined both metagenomics and isolate whole genome sequencing approaches to systematically study the gut-adaptive evolution of probiotic L. plantarum and the ecological and evolutionary changes of resident gut microbiomes in response to probiotic ingestion in multiple host species. Independent of host model, Lp082 colonized and adapted to the gut by acquiring highly consistent single-nucleotide mutations, which primarily modulated carbohydrate utilization and acid tolerance. We cultivated the probiotic mutants and validated that these gut-adapted mutations were genetically stable for at least 3 months and improved their fitness in vitro. In turn, resident gut microbial strains, especially competing strains with Lp082 (e.g., Bacteroides spp. and Bifidobacterium spp.), actively responded to Lp082 engraftment by accumulating 10–70 times more evolutionary changes than usual. Human gut microbiota exhibited a higher ecological and genetic stability than that of mice.ConclusionsCollectively, our results suggest a highly convergent adaptation strategy of Lp082 across three different host environments. In contrast, the evolutionary changes within the resident gut microbes in response to Lp082 were more divergent and host-specific; however, these changes were not associated with any adverse outcomes. This work lays a theoretical foundation for leveraging animal models for ex vivo engineering of probiotics to improve engraftment outcomes in humans.1TYRt-mQpEqyYou2DA7bqRVideo abstract
    29 schema:genre article
    30 schema:inLanguage en
    31 schema:isAccessibleForFree true
    32 schema:isPartOf N81d533b2c64c442aa8ec51575f15793d
    33 Nba3b9f6180a746f4a73e8c7b43d81fcb
    34 sg:journal.1048878
    35 schema:keywords L. plantarum
    36 ResultsWe
    37 acid tolerance
    38 adaptation strategies
    39 adaptive strategies
    40 adverse outcomes
    41 animal models
    42 approach
    43 carbohydrate utilization
    44 changes
    45 combination
    46 context
    47 contrast
    48 different host environments
    49 diverse contexts
    50 effect
    51 engineering
    52 engraftment
    53 engraftment outcomes
    54 environment
    55 evolution
    56 evolutionary change
    57 evolutionary impact
    58 evolves
    59 ex vivo engineering
    60 fitness
    61 foundation
    62 genetic processes
    63 genetic stability
    64 genome sequencing approach
    65 gut
    66 gut microbes
    67 gut microbiome
    68 gut microbiota
    69 host environment
    70 host model
    71 host species
    72 human gut
    73 human gut microbiota
    74 humans
    75 impact
    76 indigenous gut microbiota
    77 ingestion
    78 isolates
    79 metagenomic sequencing
    80 metagenomics
    81 method
    82 mice
    83 microbes
    84 microbiome
    85 microbiota
    86 model
    87 months
    88 most probiotic strains
    89 multiple host species
    90 mutants
    91 mutations
    92 outcomes
    93 plantarum
    94 pressure
    95 probiotic L. plantarum
    96 probiotic ingestion
    97 probiotic strains
    98 probiotics
    99 process
    100 resident gut microbes
    101 resident gut microbiome
    102 resident microbiome
    103 response
    104 results
    105 selection pressure
    106 sequencing
    107 sequencing approach
    108 shotgun metagenomic sequencing
    109 single nucleotide mutations
    110 species
    111 stability
    112 strains
    113 strategies
    114 theoretical foundation
    115 thorough understanding
    116 tolerance
    117 turn
    118 understanding
    119 utilization
    120 vivo engineering
    121 whole genome sequencing approach
    122 work
    123 zebrafish gut
    124 schema:name Candidate probiotic Lactiplantibacillus plantarum HNU082 rapidly and convergently evolves within human, mice, and zebrafish gut but differentially influences the resident microbiome
    125 schema:pagination 151
    126 schema:productId N76b87b984f084396b6ac4832c89a9074
    127 Nbc432a916947402da1049267a3a458ff
    128 Nd83f1d478af044988f6c1bc6b848e9b5
    129 schema:sameAs https://app.dimensions.ai/details/publication/pub.1139274963
    130 https://doi.org/10.1186/s40168-021-01102-0
    131 schema:sdDatePublished 2022-06-01T22:24
    132 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    133 schema:sdPublisher N2f3b392674c547448091e3c9325b2723
    134 schema:url https://doi.org/10.1186/s40168-021-01102-0
    135 sgo:license sg:explorer/license/
    136 sgo:sdDataset articles
    137 rdf:type schema:ScholarlyArticle
    138 N13812f7af66c40b69872fe96ed0d5ed7 rdf:first sg:person.011522220701.89
    139 rdf:rest Nb7dcb3cccbeb4c49be062234362c9283
    140 N200b6c15f30942e9ab9286594c116294 rdf:first sg:person.01074626724.22
    141 rdf:rest N58616eb2752944f6ab15ca48db74fc9c
    142 N2f3b392674c547448091e3c9325b2723 schema:name Springer Nature - SN SciGraph project
    143 rdf:type schema:Organization
    144 N45e4f89d13d542d0bd1d24ae2375e244 rdf:first sg:person.016507333101.73
    145 rdf:rest Nd6c83ed2d3554fcd82ee97b3ab62fe5b
    146 N4c73508c208b40ca910247a880919012 rdf:first sg:person.010546227027.19
    147 rdf:rest N7b4b58e1458f459998edb8029edd9fe1
    148 N58616eb2752944f6ab15ca48db74fc9c rdf:first sg:person.015734664417.36
    149 rdf:rest N6d59dddd4a2b45c58f169d76408b9506
    150 N689ff0920f9a4712af64de3cc6a0e4a6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    151 schema:name Humans
    152 rdf:type schema:DefinedTerm
    153 N68ef45840f0a49249bf876108cde642c rdf:first sg:person.016311745377.96
    154 rdf:rest Na45a3c16bd57412c9fb05d59b16780b1
    155 N6d59dddd4a2b45c58f169d76408b9506 rdf:first sg:person.0620460120.04
    156 rdf:rest Nb60e7e0a98ed44d68a9a0b352fd9abe7
    157 N6ee0ec794da54de288b6379b1d030c9d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    158 schema:name Bifidobacterium
    159 rdf:type schema:DefinedTerm
    160 N714d672a8fc6498d8d74c677c5bc8272 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    161 schema:name Microbiota
    162 rdf:type schema:DefinedTerm
    163 N73b6c02ff8c8497c8aa1cd21af6d4078 rdf:first sg:person.0715356340.58
    164 rdf:rest N45e4f89d13d542d0bd1d24ae2375e244
    165 N76b87b984f084396b6ac4832c89a9074 schema:name dimensions_id
    166 schema:value pub.1139274963
    167 rdf:type schema:PropertyValue
    168 N7b4b58e1458f459998edb8029edd9fe1 rdf:first sg:person.01013373644.11
    169 rdf:rest N68ef45840f0a49249bf876108cde642c
    170 N8114f3b14aa4488d8501bf2d6b69aa6c rdf:first sg:person.0660713743.85
    171 rdf:rest N4c73508c208b40ca910247a880919012
    172 N81d533b2c64c442aa8ec51575f15793d schema:issueNumber 1
    173 rdf:type schema:PublicationIssue
    174 N991d736e3f4043b785d6877d86a5a832 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    175 schema:name Animals
    176 rdf:type schema:DefinedTerm
    177 N9f02b48ef556443bb2d004e9fb2cc53f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    178 schema:name Probiotics
    179 rdf:type schema:DefinedTerm
    180 Na01a6202fb784185a8e34becae9fd622 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    181 schema:name Mice
    182 rdf:type schema:DefinedTerm
    183 Na217bdd417714b379797466ab932616f rdf:first sg:person.01113460501.49
    184 rdf:rest N13812f7af66c40b69872fe96ed0d5ed7
    185 Na45a3c16bd57412c9fb05d59b16780b1 rdf:first sg:person.011346604554.69
    186 rdf:rest rdf:nil
    187 Nb60e7e0a98ed44d68a9a0b352fd9abe7 rdf:first sg:person.0625665663.23
    188 rdf:rest N73b6c02ff8c8497c8aa1cd21af6d4078
    189 Nb7dcb3cccbeb4c49be062234362c9283 rdf:first sg:person.012566567664.88
    190 rdf:rest N8114f3b14aa4488d8501bf2d6b69aa6c
    191 Nb8d0b261f1764234a5119d2b162aa1b0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    192 schema:name Zebrafish
    193 rdf:type schema:DefinedTerm
    194 Nba3b9f6180a746f4a73e8c7b43d81fcb schema:volumeNumber 9
    195 rdf:type schema:PublicationVolume
    196 Nbc432a916947402da1049267a3a458ff schema:name pubmed_id
    197 schema:value 34193290
    198 rdf:type schema:PropertyValue
    199 Nd6c83ed2d3554fcd82ee97b3ab62fe5b rdf:first sg:person.01255245123.96
    200 rdf:rest Na217bdd417714b379797466ab932616f
    201 Nd83f1d478af044988f6c1bc6b848e9b5 schema:name doi
    202 schema:value 10.1186/s40168-021-01102-0
    203 rdf:type schema:PropertyValue
    204 Ne92930f491ea46b781cf875456325d90 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    205 schema:name Gastrointestinal Microbiome
    206 rdf:type schema:DefinedTerm
    207 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    208 schema:name Biological Sciences
    209 rdf:type schema:DefinedTerm
    210 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    211 schema:name Genetics
    212 rdf:type schema:DefinedTerm
    213 sg:grant.2439028 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    214 rdf:type schema:MonetaryGrant
    215 sg:grant.3537236 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    216 rdf:type schema:MonetaryGrant
    217 sg:grant.4242003 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    218 rdf:type schema:MonetaryGrant
    219 sg:grant.4455483 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    220 rdf:type schema:MonetaryGrant
    221 sg:grant.7028139 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    222 rdf:type schema:MonetaryGrant
    223 sg:grant.7614321 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    224 rdf:type schema:MonetaryGrant
    225 sg:grant.7614455 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    226 rdf:type schema:MonetaryGrant
    227 sg:grant.7752854 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    228 rdf:type schema:MonetaryGrant
    229 sg:grant.8199846 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    230 rdf:type schema:MonetaryGrant
    231 sg:grant.8554837 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    232 rdf:type schema:MonetaryGrant
    233 sg:grant.8556184 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    234 rdf:type schema:MonetaryGrant
    235 sg:grant.8557027 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    236 rdf:type schema:MonetaryGrant
    237 sg:grant.8744733 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    238 rdf:type schema:MonetaryGrant
    239 sg:grant.9413418 http://pending.schema.org/fundedItem sg:pub.10.1186/s40168-021-01102-0
    240 rdf:type schema:MonetaryGrant
    241 sg:journal.1048878 schema:issn 2049-2618
    242 schema:name Microbiome
    243 schema:publisher Springer Nature
    244 rdf:type schema:Periodical
    245 sg:person.01013373644.11 schema:affiliation grid-institutes:grid.38142.3c
    246 schema:familyName Liu
    247 schema:givenName Yang-Yu
    248 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01013373644.11
    249 rdf:type schema:Person
    250 sg:person.010546227027.19 schema:affiliation grid-institutes:None
    251 schema:familyName Zarrinpar
    252 schema:givenName Amir
    253 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010546227027.19
    254 rdf:type schema:Person
    255 sg:person.01074626724.22 schema:affiliation grid-institutes:grid.266100.3
    256 schema:familyName Huang
    257 schema:givenName Shi
    258 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01074626724.22
    259 rdf:type schema:Person
    260 sg:person.01113460501.49 schema:affiliation grid-institutes:grid.266100.3
    261 schema:familyName Vázquez-Baeza
    262 schema:givenName Yoshiki
    263 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01113460501.49
    264 rdf:type schema:Person
    265 sg:person.011346604554.69 schema:affiliation grid-institutes:None
    266 schema:familyName Zhang
    267 schema:givenName Jiachao
    268 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011346604554.69
    269 rdf:type schema:Person
    270 sg:person.011522220701.89 schema:affiliation grid-institutes:grid.266100.3
    271 schema:familyName Zhu
    272 schema:givenName Qiyun
    273 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011522220701.89
    274 rdf:type schema:Person
    275 sg:person.01255245123.96 schema:affiliation grid-institutes:grid.266100.3
    276 schema:familyName Belda-Ferre
    277 schema:givenName Pedro
    278 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01255245123.96
    279 rdf:type schema:Person
    280 sg:person.012566567664.88 schema:affiliation grid-institutes:grid.428986.9
    281 schema:familyName Ma
    282 schema:givenName Chenchen
    283 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012566567664.88
    284 rdf:type schema:Person
    285 sg:person.015734664417.36 schema:affiliation grid-institutes:grid.428986.9
    286 schema:familyName Jiang
    287 schema:givenName Shuaiming
    288 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015734664417.36
    289 rdf:type schema:Person
    290 sg:person.016311745377.96 schema:affiliation grid-institutes:grid.266100.3
    291 schema:familyName Knight
    292 schema:givenName Rob
    293 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016311745377.96
    294 rdf:type schema:Person
    295 sg:person.016507333101.73 schema:affiliation grid-institutes:grid.266100.3
    296 schema:familyName Cantu
    297 schema:givenName Victor
    298 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016507333101.73
    299 rdf:type schema:Person
    300 sg:person.0620460120.04 schema:affiliation grid-institutes:grid.428986.9
    301 schema:familyName Huo
    302 schema:givenName Dongxue
    303 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0620460120.04
    304 rdf:type schema:Person
    305 sg:person.0625665663.23 schema:affiliation grid-institutes:grid.266100.3
    306 schema:familyName Allaband
    307 schema:givenName Celeste
    308 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0625665663.23
    309 rdf:type schema:Person
    310 sg:person.0660713743.85 schema:affiliation grid-institutes:None
    311 schema:familyName Li
    312 schema:givenName Congfa
    313 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0660713743.85
    314 rdf:type schema:Person
    315 sg:person.0715356340.58 schema:affiliation grid-institutes:grid.266100.3
    316 schema:familyName Estaki
    317 schema:givenName Mehrbod
    318 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715356340.58
    319 rdf:type schema:Person
    320 sg:pub.10.1038/ismej.2010.61 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037681660
    321 https://doi.org/10.1038/ismej.2010.61
    322 rdf:type schema:CreativeWork
    323 sg:pub.10.1038/nature11623 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044708958
    324 https://doi.org/10.1038/nature11623
    325 rdf:type schema:CreativeWork
    326 sg:pub.10.1038/nature25973 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101264718
    327 https://doi.org/10.1038/nature25973
    328 rdf:type schema:CreativeWork
    329 sg:pub.10.1038/nmeth.1923 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006541515
    330 https://doi.org/10.1038/nmeth.1923
    331 rdf:type schema:CreativeWork
    332 sg:pub.10.1038/nrgastro.2014.66 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012609471
    333 https://doi.org/10.1038/nrgastro.2014.66
    334 rdf:type schema:CreativeWork
    335 sg:pub.10.1038/nrgastro.2017.75 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086020795
    336 https://doi.org/10.1038/nrgastro.2017.75
    337 rdf:type schema:CreativeWork
    338 sg:pub.10.1038/s41467-019-10656-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1117296456
    339 https://doi.org/10.1038/s41467-019-10656-5
    340 rdf:type schema:CreativeWork
    341 sg:pub.10.1038/s41591-019-0626-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1122362111
    342 https://doi.org/10.1038/s41591-019-0626-9
    343 rdf:type schema:CreativeWork
    344 sg:pub.10.1038/s41592-018-0176-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1107804224
    345 https://doi.org/10.1038/s41592-018-0176-y
    346 rdf:type schema:CreativeWork
    347 sg:pub.10.1038/srep32524 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003566262
    348 https://doi.org/10.1038/srep32524
    349 rdf:type schema:CreativeWork
    350 sg:pub.10.1186/2047-217x-1-18 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016521225
    351 https://doi.org/10.1186/2047-217x-1-18
    352 rdf:type schema:CreativeWork
    353 sg:pub.10.1186/s13059-014-0531-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1034675947
    354 https://doi.org/10.1186/s13059-014-0531-y
    355 rdf:type schema:CreativeWork
    356 sg:pub.10.1186/s13059-019-1891-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1122989517
    357 https://doi.org/10.1186/s13059-019-1891-0
    358 rdf:type schema:CreativeWork
    359 sg:pub.10.1186/s13104-016-1900-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040653018
    360 https://doi.org/10.1186/s13104-016-1900-2
    361 rdf:type schema:CreativeWork
    362 grid-institutes:None schema:alternateName Key Laboratory of Food Nutrition and Functional Food of Hainan Province, 570228, Haikou, China
    363 VA San Diego Healthcare, 3350 La Jolla Village Dr, 92161, San Diego, CA, USA
    364 schema:name Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    365 Key Laboratory of Food Nutrition and Functional Food of Hainan Province, 570228, Haikou, China
    366 School of Food Science and Engineering, Hainan University, Haikou, China
    367 UCSD Division of Gastroenterology, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    368 UCSD Health Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    369 VA San Diego Healthcare, 3350 La Jolla Village Dr, 92161, San Diego, CA, USA
    370 rdf:type schema:Organization
    371 grid-institutes:grid.266100.3 schema:alternateName Biomedical Sciences Graduate Program, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    372 Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    373 Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    374 Department of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    375 UCSD Health Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    376 schema:name Biomedical Sciences Graduate Program, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    377 Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    378 Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    379 Department of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    380 School of Food Science and Engineering, Hainan University, Haikou, China
    381 UCSD Health Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA
    382 rdf:type schema:Organization
    383 grid-institutes:grid.38142.3c schema:alternateName Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, 02115, Boston, MA, USA
    384 schema:name Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, 02115, Boston, MA, USA
    385 rdf:type schema:Organization
    386 grid-institutes:grid.428986.9 schema:alternateName School of Food Science and Engineering, Hainan University, Haikou, China
    387 schema:name School of Food Science and Engineering, Hainan University, Haikou, China
    388 rdf:type schema:Organization
     




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


    ...