Meta-Analysis Reveals Reproducible Gut Microbiome Alterations in Response to a High-Fat Diet
Multiple research groups have shown that diet impacts the gut microbiome; however, variability in experimental design and quantitative assessment have made it challenging to assess the degree to which similar diets have reproducible effects across studies. Through an unbiased subject-level meta-anal...
Saved in:
Published in | Cell host & microbe Vol. 26; no. 2; pp. 265 - 272.e4 |
---|---|
Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
14.08.2019
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Multiple research groups have shown that diet impacts the gut microbiome; however, variability in experimental design and quantitative assessment have made it challenging to assess the degree to which similar diets have reproducible effects across studies. Through an unbiased subject-level meta-analysis framework, we re-analyzed 27 dietary studies including 1,101 samples from rodents and humans. We demonstrate that a high-fat diet (HFD) reproducibly changes gut microbial community structure. Finer taxonomic analysis revealed that the most reproducible signals of a HFD are Lactococcus species, which we experimentally demonstrate to be common dietary contaminants. Additionally, a machine-learning approach defined a signature that predicts the dietary intake of mice and demonstrated that phylogenetic and gene-centric transformations of this model can be translated to humans. Together, these results demonstrate the utility of microbiome meta-analyses in identifying robust and reproducible features for mechanistic studies in preclinical models.
[Display omitted]
•A generalizable approach is presented for meta-analysis of microbiome datasets•High-fat diets induce reproducible shifts in the mouse gut microbiome•Nonviable Lactococcus contamination is widespread in experimental diets•Phylogenetic and gene signatures translate to human microbiomes
Bisanz and Upadhyay et al. execute a meta-analysis of previous studies evaluating the effect of a high-fat diet on the gut microbiome. They define reproducible features across studies for mechanistic experimentation and uncover that residual DNA contamination in experimental diets should be measured and accounted for in study design. |
---|---|
AbstractList | Multiple research groups have shown that diet impacts the gut microbiome; however, variability in experimental design and quantitative assessment have made it challenging to assess the degree to which similar diets have reproducible effects across studies. Through an unbiased subject-level meta-analysis framework, we re-analyzed 27 dietary studies including 1,101 samples from rodents and humans. We demonstrate that a high-fat diet (HFD) reproducibly changes gut microbial community structure. Finer taxonomic analysis revealed that the most reproducible signals of a HFD are Lactococcus species, which we experimentally demonstrate to be common dietary contaminants. Additionally, a machine-learning approach defined a signature that predicts the dietary intake of mice and demonstrated that phylogenetic and gene-centric transformations of this model can be translated to humans. Together, these results demonstrate the utility of microbiome meta-analyses in identifying robust and reproducible features for mechanistic studies in preclinical models.
[Display omitted]
•A generalizable approach is presented for meta-analysis of microbiome datasets•High-fat diets induce reproducible shifts in the mouse gut microbiome•Nonviable Lactococcus contamination is widespread in experimental diets•Phylogenetic and gene signatures translate to human microbiomes
Bisanz and Upadhyay et al. execute a meta-analysis of previous studies evaluating the effect of a high-fat diet on the gut microbiome. They define reproducible features across studies for mechanistic experimentation and uncover that residual DNA contamination in experimental diets should be measured and accounted for in study design. Multiple research groups have shown that diet impacts the gut microbiome; however, variability in experimental design and quantitative assessment have made it challenging to assess the degree to which similar diets have reproducible effects across studies. Through an unbiased subject-level meta-analysis framework, we re-analyzed 27 dietary studies including 1,101 samples from rodents and humans. We demonstrate that a high-fat diet (HFD) reproducibly changes gut microbial community structure. Finer taxonomic analysis revealed that the most reproducible signals of a HFD are Lactococcus species, which we experimentally demonstrate to be common dietary contaminants. Additionally, a machine-learning approach defined a signature that predicts the dietary intake of mice and demonstrated that phylogenetic and gene-centric transformations of this model can be translated to humans. Together, these results demonstrate the utility of microbiome meta-analyses in identifying robust and reproducible features for mechanistic studies in preclinical models.Multiple research groups have shown that diet impacts the gut microbiome; however, variability in experimental design and quantitative assessment have made it challenging to assess the degree to which similar diets have reproducible effects across studies. Through an unbiased subject-level meta-analysis framework, we re-analyzed 27 dietary studies including 1,101 samples from rodents and humans. We demonstrate that a high-fat diet (HFD) reproducibly changes gut microbial community structure. Finer taxonomic analysis revealed that the most reproducible signals of a HFD are Lactococcus species, which we experimentally demonstrate to be common dietary contaminants. Additionally, a machine-learning approach defined a signature that predicts the dietary intake of mice and demonstrated that phylogenetic and gene-centric transformations of this model can be translated to humans. Together, these results demonstrate the utility of microbiome meta-analyses in identifying robust and reproducible features for mechanistic studies in preclinical models. Multiple research groups have shown that diet impacts the gut microbiome; however, variability in experimental design and quantitative assessment have made it challenging to assess the degree to which similar diets have reproducible effects across studies. Through an unbiased subject-level meta-analysis framework, we re-analyzed 27 dietary studies including 1101 samples from rodents and humans. We demonstrate that a high-fat diet (HFD) reproducibly changes gut microbial community structure. Finer taxonomic analysis revealed that the most reproducible signal of a HFD are Lactococcus species, which we experimentally demonstrate are common dietary contaminants. Additionally, a machine learning approach defined a signature that predicts the dietary intake of mice and demonstrated that phylogenetic and gene-centric transformations of this model can be translated to humans. Together, these results demonstrate the utility of microbiome meta-analyses in identifying robust and reproducible features for mechanistic studies in preclinical models. Multiple research groups have shown that diet impacts the gut microbiome; however, variability in experimental design and quantitative assessment have made it challenging to assess the degree to which similar diets have reproducible effects across studies. Through an unbiased subject-level meta-analysis framework, we re-analyzed 27 dietary studies including 1,101 samples from rodents and humans. We demonstrate that a high-fat diet (HFD) reproducibly changes gut microbial community structure. Finer taxonomic analysis revealed that the most reproducible signals of a HFD are Lactococcus species, which we experimentally demonstrate to be common dietary contaminants. Additionally, a machine-learning approach defined a signature that predicts the dietary intake of mice and demonstrated that phylogenetic and gene-centric transformations of this model can be translated to humans. Together, these results demonstrate the utility of microbiome meta-analyses in identifying robust and reproducible features for mechanistic studies in preclinical models. |
Author | Ly, Kimberly Bisanz, Jordan E. Turnbaugh, Jessie A. Upadhyay, Vaibhav Turnbaugh, Peter J. |
AuthorAffiliation | 1 Department of Microbiology and Immunology, University of California San Francisco, CA 94143, USA 4 Lead Contact 3 Chan Zuckerberg Biohub, San Francisco, CA 94158, USA 2 Department of Internal Medicine, University of California San Francisco, CA 94143, USA |
AuthorAffiliation_xml | – name: 4 Lead Contact – name: 3 Chan Zuckerberg Biohub, San Francisco, CA 94158, USA – name: 2 Department of Internal Medicine, University of California San Francisco, CA 94143, USA – name: 1 Department of Microbiology and Immunology, University of California San Francisco, CA 94143, USA |
Author_xml | – sequence: 1 givenname: Jordan E. surname: Bisanz fullname: Bisanz, Jordan E. organization: Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA – sequence: 2 givenname: Vaibhav surname: Upadhyay fullname: Upadhyay, Vaibhav organization: Department of Internal Medicine, University of California San Francisco, San Francisco, CA 94143, USA – sequence: 3 givenname: Jessie A. surname: Turnbaugh fullname: Turnbaugh, Jessie A. organization: Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA – sequence: 4 givenname: Kimberly surname: Ly fullname: Ly, Kimberly organization: Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA – sequence: 5 givenname: Peter J. surname: Turnbaugh fullname: Turnbaugh, Peter J. email: peter.turnbaugh@ucsf.edu organization: Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31324413$$D View this record in MEDLINE/PubMed |
BookMark | eNp9Uctq3DAUFSWlebQ_0EXRshu7eliSDaUwJM0DEgql3RWELF1nNNjWVJIH8ve1Z9LQdJHVvXDP43LOKToawwgIvaekpITKT5vSrsNQMkKbksiSUP4KndCGV4Uksjna77TglNXH6DSlDSFCEEXfoGNOOasqyk_QrzvIpliNpn9IPuHvsAPTL3Mbg5usb3vAV1PGd97G0PowAF71GaLJPowJ-3GGpu28As4BG3zt79fFpcn4wkN-i153sxq8e5xn6Ofl1x_n18Xtt6ub89VtYSshciGNahpnFamYEo1kTsoWGmWVkyAM6ZgTXHTQWN52bStsQ2xbV7UTgrq67hg_Q18OutupHcBZGHM0vd5GP5j4oIPx-vll9Gt9H3ZaKlIzVc8CHx8FYvg9Qcp68MlC35sRwpQ0Y1Komki1eH341-vJ5G-kM4AdAHNgKUXoniCU6KU3vdFLb3rpTROpyZ5U_0eyPu8znv_1_cvUzwcqzAnvPESdrIfRgvMRbNYu-JfofwDiK7R3 |
CitedBy_id | crossref_primary_10_1016_j_celrep_2022_111332 crossref_primary_10_1039_D4FO02199A crossref_primary_10_12677_ACM_2023_1371488 crossref_primary_10_1016_j_isci_2023_106313 crossref_primary_10_1021_acsnano_4c07885 crossref_primary_10_1128_msystems_00303_20 crossref_primary_10_1016_j_clnu_2023_03_017 crossref_primary_10_1038_s41579_022_00805_x crossref_primary_10_1038_s41467_021_21408_9 crossref_primary_10_1007_s11894_022_00859_0 crossref_primary_10_3390_biomedicines11123144 crossref_primary_10_1016_j_celrep_2022_111461 crossref_primary_10_1016_j_foodchem_2025_143391 crossref_primary_10_1016_j_biochi_2020_09_007 crossref_primary_10_1128_spectrum_01799_24 crossref_primary_10_1186_s12866_024_03195_7 crossref_primary_10_3389_fimmu_2024_1321395 crossref_primary_10_1038_s41579_024_01068_4 crossref_primary_10_1080_20002297_2022_2051336 crossref_primary_10_3389_frmbi_2024_1394719 crossref_primary_10_1038_s41598_023_38895_z crossref_primary_10_3390_pathogens13080702 crossref_primary_10_3389_fphar_2022_870407 crossref_primary_10_1007_s11916_020_00871_x crossref_primary_10_3389_frmbi_2024_1412468 crossref_primary_10_3390_molecules27196156 crossref_primary_10_1016_j_tjnut_2022_12_019 crossref_primary_10_1111_vde_13250 crossref_primary_10_1007_s43657_023_00095_0 crossref_primary_10_1128_mBio_01723_20 crossref_primary_10_3390_molecules29050976 crossref_primary_10_1080_19490976_2023_2205386 crossref_primary_10_1002_ajp_70004 crossref_primary_10_1038_s41598_024_59603_5 crossref_primary_10_3390_ijms22115981 crossref_primary_10_1016_j_cell_2020_04_027 crossref_primary_10_1007_s11427_022_2283_4 crossref_primary_10_1165_rcmb_2020_0288TR crossref_primary_10_1016_j_jid_2021_01_003 crossref_primary_10_3390_foods11010098 crossref_primary_10_1016_j_molmet_2021_101427 crossref_primary_10_1016_j_jff_2023_105917 crossref_primary_10_3390_nu15245056 crossref_primary_10_1016_j_csbj_2020_08_028 crossref_primary_10_1016_j_smim_2023_101724 crossref_primary_10_1038_s41531_021_00156_z crossref_primary_10_3390_genes12101505 crossref_primary_10_3390_nu15081966 crossref_primary_10_1016_j_celrep_2022_111008 crossref_primary_10_1152_physiolgenomics_00066_2023 crossref_primary_10_3390_nu15081841 crossref_primary_10_1038_s41598_024_78527_8 crossref_primary_10_1016_j_phrs_2024_107321 crossref_primary_10_1016_j_ejim_2023_10_002 crossref_primary_10_3390_pathogens12091087 crossref_primary_10_1038_s41564_021_00948_2 crossref_primary_10_1038_s41598_024_69685_w crossref_primary_10_1016_j_biopha_2023_114985 crossref_primary_10_3390_microorganisms12122417 crossref_primary_10_1016_j_chom_2020_06_012 crossref_primary_10_1016_j_tjnut_2024_07_014 crossref_primary_10_1016_j_chom_2021_04_004 crossref_primary_10_1038_s41564_023_01484_x crossref_primary_10_1007_s10123_024_00518_6 crossref_primary_10_1111_acel_13599 crossref_primary_10_1039_D1FO03952K crossref_primary_10_7717_peerj_10372 crossref_primary_10_1128_spectrum_01722_23 crossref_primary_10_3389_fnut_2023_1291853 crossref_primary_10_1038_s41522_023_00472_7 crossref_primary_10_1128_mSphere_00558_19 crossref_primary_10_1128_spectrum_02352_24 crossref_primary_10_3390_nu13041302 crossref_primary_10_3390_biology11050633 crossref_primary_10_1016_j_trsl_2021_01_009 crossref_primary_10_1038_s41598_020_74122_9 crossref_primary_10_3389_fmed_2021_646710 crossref_primary_10_1093_femsec_fiad096 crossref_primary_10_1016_j_isci_2024_110447 crossref_primary_10_3389_fnut_2022_1040744 crossref_primary_10_3389_fcimb_2024_1393108 crossref_primary_10_1038_s41598_021_03670_5 crossref_primary_10_3390_biomedicines10010083 crossref_primary_10_1016_j_foodres_2023_113761 crossref_primary_10_1093_database_baac033 crossref_primary_10_1002_fsn3_4420 crossref_primary_10_1097_MCO_0000000000000763 crossref_primary_10_1016_j_physbeh_2022_113987 crossref_primary_10_3390_ijms22147613 crossref_primary_10_1038_s41598_021_98248_6 crossref_primary_10_3390_ijms23115935 crossref_primary_10_3390_ijms21165850 crossref_primary_10_1007_s10123_023_00380_y crossref_primary_10_1038_s41522_024_00536_2 crossref_primary_10_1093_gastro_goac010 crossref_primary_10_1128_aem_01552_24 crossref_primary_10_53365_nrfhh_192940 crossref_primary_10_1186_s40168_021_01149_z crossref_primary_10_3389_fnut_2023_1244692 crossref_primary_10_7554_eLife_70349 crossref_primary_10_1002_jgh3_12709 crossref_primary_10_3390_nu14163407 crossref_primary_10_1038_s41467_024_45359_z crossref_primary_10_3390_nu13114146 crossref_primary_10_1051_ocl_2020070 crossref_primary_10_1038_s43705_021_00053_9 crossref_primary_10_3389_fncel_2023_895017 crossref_primary_10_1038_s41467_024_46135_9 crossref_primary_10_3390_ijms24065631 crossref_primary_10_1093_advances_nmaa181 crossref_primary_10_1051_npvelsa_2023018 crossref_primary_10_1038_s41598_023_28764_0 crossref_primary_10_3389_fnut_2023_1285516 crossref_primary_10_1007_s40618_022_01902_7 crossref_primary_10_3390_jpm14010008 crossref_primary_10_3389_fnut_2022_819882 crossref_primary_10_1371_journal_pone_0240996 crossref_primary_10_1038_s43705_022_00131_6 crossref_primary_10_3390_microorganisms11030777 crossref_primary_10_3390_nu14193985 crossref_primary_10_1016_j_cmet_2022_12_013 crossref_primary_10_1016_j_meatsci_2024_109642 crossref_primary_10_1128_msystems_01322_23 crossref_primary_10_1128_mSystems_00116_21 crossref_primary_10_1016_j_celrep_2021_110113 crossref_primary_10_3390_children10020241 crossref_primary_10_1128_msystems_01247_24 crossref_primary_10_1080_19490976_2022_2139978 crossref_primary_10_3390_nu13113992 crossref_primary_10_1002_imt2_270 crossref_primary_10_1002_mnfr_201901315 crossref_primary_10_1128_mSphere_00731_20 crossref_primary_10_3390_nu17040737 crossref_primary_10_1038_s41579_023_00888_0 crossref_primary_10_3389_fnut_2022_941969 crossref_primary_10_3390_nu14194050 crossref_primary_10_1002_adbi_202300100 crossref_primary_10_1016_j_chom_2019_07_012 crossref_primary_10_1016_j_cell_2024_07_039 crossref_primary_10_1016_j_clnu_2021_01_031 crossref_primary_10_3390_nu15010217 crossref_primary_10_1016_j_xcrm_2023_101235 crossref_primary_10_1016_j_jff_2021_104853 crossref_primary_10_1111_omi_12382 crossref_primary_10_1111_1462_2920_16537 crossref_primary_10_1111_1462_2920_15441 crossref_primary_10_1128_spectrum_00567_23 crossref_primary_10_3390_nu13082795 crossref_primary_10_1016_j_coviro_2021_09_016 crossref_primary_10_3390_jcm10215074 crossref_primary_10_1186_s13098_024_01561_z crossref_primary_10_1538_expanim_21_0182 crossref_primary_10_1016_j_micres_2023_127346 crossref_primary_10_1016_j_immuni_2023_12_009 crossref_primary_10_1016_j_ebiom_2025_105630 crossref_primary_10_1186_s12931_020_01361_9 crossref_primary_10_1186_s12970_020_00353_w crossref_primary_10_1016_j_celrep_2022_111641 crossref_primary_10_1007_s10695_022_01105_0 crossref_primary_10_3390_ijms24043084 crossref_primary_10_1042_BSR20203850 crossref_primary_10_1002_mbo3_1404 crossref_primary_10_1186_s12887_023_03939_w crossref_primary_10_1016_j_bpsgos_2023_02_011 crossref_primary_10_1016_j_lfs_2021_119675 crossref_primary_10_1038_s41368_024_00301_3 crossref_primary_10_3233_NHA_220198 crossref_primary_10_1111_obr_13701 crossref_primary_10_1016_j_cell_2024_10_022 crossref_primary_10_1038_s41385_022_00547_2 crossref_primary_10_1016_j_foodres_2022_112179 crossref_primary_10_37586_2949_4745_3_2024_154_160 crossref_primary_10_1186_s40795_024_00971_6 crossref_primary_10_3390_molecules27227830 crossref_primary_10_3390_nu12082347 crossref_primary_10_1186_s12263_021_00703_6 crossref_primary_10_1038_s41590_023_01587_x crossref_primary_10_3390_antibiotics11060793 crossref_primary_10_1038_s41598_024_79339_6 crossref_primary_10_1111_apm_13272 crossref_primary_10_1016_j_biopha_2022_113810 crossref_primary_10_1002_pmic_202400149 crossref_primary_10_1128_mSystems_00317_20 crossref_primary_10_1128_mSystems_00665_20 crossref_primary_10_1038_s42255_024_01064_1 crossref_primary_10_1111_jnc_16156 crossref_primary_10_1111_acel_13760 crossref_primary_10_1016_j_jff_2024_106555 crossref_primary_10_1371_journal_pbio_3001758 crossref_primary_10_1371_journal_pone_0260591 crossref_primary_10_1038_s42255_021_00439_y crossref_primary_10_1111_apm_13386 crossref_primary_10_2147_CCID_S450227 crossref_primary_10_1134_S207905702560003X crossref_primary_10_1038_s41467_024_49963_x crossref_primary_10_1136_gutjnl_2021_325753 crossref_primary_10_1007_s40726_023_00273_8 crossref_primary_10_1016_j_csbj_2020_07_020 crossref_primary_10_3389_fcimb_2024_1407051 crossref_primary_10_2147_DMSO_S346007 crossref_primary_10_1016_j_phrs_2020_104952 crossref_primary_10_3389_fpsyt_2024_1295766 crossref_primary_10_1152_ajpendo_00071_2021 crossref_primary_10_1038_s42255_021_00426_3 crossref_primary_10_3390_ijms25179366 crossref_primary_10_1080_19490976_2022_2050635 crossref_primary_10_3389_fcell_2022_849985 crossref_primary_10_3389_fnut_2024_1429242 crossref_primary_10_1002_mnfr_202300141 crossref_primary_10_1080_19490976_2023_2197835 crossref_primary_10_1128_msystems_00108_24 crossref_primary_10_1039_D4FO02390K crossref_primary_10_3389_fmicb_2025_1559521 crossref_primary_10_1007_s12325_020_01272_7 crossref_primary_10_1128_Spectrum_00074_21 crossref_primary_10_37349_en_2024_00038 crossref_primary_10_3390_nu15061534 crossref_primary_10_1111_obr_13493 |
Cites_doi | 10.1186/s40168-017-0258-6 10.1038/ismej.2017.119 10.1016/j.celrep.2017.10.056 10.1126/scitranslmed.3000322 10.1371/journal.pone.0084689 10.1371/journal.pone.0097500 10.1016/j.chom.2014.11.010 10.1371/journal.pone.0092193 10.1016/j.cell.2014.05.052 10.1177/1471082X14535524 10.1371/journal.pone.0071806 10.1093/bioinformatics/btq166 10.1038/nbt.2676 10.1016/j.cmet.2016.05.001 10.3389/fmicb.2017.02224 10.1016/j.jnutbio.2016.05.015 10.1038/ismej.2014.45 10.1093/bioinformatics/btq461 10.1371/journal.pone.0126976 10.1038/nmicrobiol.2016.220 10.3389/fmicb.2017.00905 10.1186/s12866-016-0883-4 10.1038/nature25753 10.1038/ni.2403 10.1038/ismej.2015.183 10.3945/jn.116.242859 10.1038/nature12820 10.7717/peerj.3889 10.1136/gutjnl-2014-307142 10.1073/pnas.0504978102 10.1371/journal.pone.0030087 10.7554/eLife.21887 10.1073/pnas.1501897112 10.1038/nbt.3981 10.1007/s00253-015-6753-4 10.1038/nature18309 10.1038/533452a 10.1126/science.1208344 10.1128/mBio.01018-16 10.1016/j.cmet.2015.07.007 10.1111/j.1654-1103.2003.tb02228.x 10.1073/pnas.1102938108 10.1093/bioinformatics/btg412 10.1093/bioinformatics/bts611 10.1038/4441022a 10.1371/journal.pcbi.1004977 10.1128/mSystems.00191-16 10.1128/AEM.03006-05 10.1371/journal.pone.0059470 10.1038/nbt.3353 10.7717/peerj.2584 10.1038/nmicrobiol.2016.131 10.1016/j.chom.2017.02.021 10.1371/journal.pone.0061217 10.2337/db14-1916 10.1186/s12986-016-0116-8 10.1016/j.chom.2008.02.015 10.1023/A:1010933404324 |
ContentType | Journal Article |
Copyright | 2019 Elsevier Inc. Copyright © 2019 Elsevier Inc. All rights reserved. |
Copyright_xml | – notice: 2019 Elsevier Inc. – notice: Copyright © 2019 Elsevier Inc. All rights reserved. |
DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 7X8 5PM |
DOI | 10.1016/j.chom.2019.06.013 |
DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic PubMed Central (Full Participant titles) |
DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic |
DatabaseTitleList | MEDLINE - Academic MEDLINE |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Biology |
EISSN | 1934-6069 |
EndPage | 272.e4 |
ExternalDocumentID | PMC6708278 31324413 10_1016_j_chom_2019_06_013 S1931312819303026 |
Genre | Meta-Analysis Research Support, Non-U.S. Gov't Journal Article Research Support, N.I.H., Extramural |
GrantInformation_xml | – fundername: NCI NIH HHS grantid: R21 CA227232 – fundername: NHLBI NIH HHS grantid: R01 HL122593 |
GroupedDBID | --- --K 0R~ 1~5 29B 2WC 4.4 457 4G. 53G 5GY 62- 6I. 6J9 7-5 AACTN AAEDW AAFTH AAIAV AAKRW AALRI AAUCE AAVLU AAXUO ABJNI ABMAC ABMWF ABVKL ACGFO ACGFS ADBBV ADEZE ADJPV AEFWE AENEX AEXQZ AFTJW AGKMS AITUG ALKID ALMA_UNASSIGNED_HOLDINGS AMRAJ ASPBG AVWKF AZFZN BAWUL CS3 DIK DU5 E3Z EBS EJD F5P FCP FDB FEDTE HVGLF IHE IXB JIG K97 M41 O-L O9- OK1 P2P RCE RIG ROL RPZ SES SSZ TR2 UNMZH WQ6 ZA5 AAEDT AAIKJ AAMRU AAYWO AAYXX ABDGV ACVFH ADCNI ADVLN AEUPX AFPUW AGCQF AGHFR AIGII AKAPO AKBMS AKRWK AKYEP APXCP CITATION HZ~ OZT ZBA 0SF CGR CUY CVF ECM EIF NPM 7X8 5PM EFKBS |
ID | FETCH-LOGICAL-c455t-6a799dc704275962d66be97c7d6e5a0f2d535fe9c3bfbb5c90cb848d551d88f23 |
IEDL.DBID | IXB |
ISSN | 1931-3128 1934-6069 |
IngestDate | Thu Aug 21 14:04:33 EDT 2025 Thu Jul 10 18:00:57 EDT 2025 Wed Feb 19 02:31:55 EST 2025 Tue Jul 01 02:44:21 EDT 2025 Thu Apr 24 23:03:54 EDT 2025 Fri Feb 23 02:31:03 EST 2024 |
IsDoiOpenAccess | false |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 2 |
Keywords | murine meta-analysis machine learning Lactococcus microbiome high-fat diet |
Language | English |
License | Copyright © 2019 Elsevier Inc. All rights reserved. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c455t-6a799dc704275962d66be97c7d6e5a0f2d535fe9c3bfbb5c90cb848d551d88f23 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Conceptualization, JEB, VU, and PJT; Methodology, JEB, JAT; Investigation, JEB, VU, KL, JAT, and PJT; Writing – Original Draft, VU and JEB; Writing - Review and Editing, JEB, VU, and PJT; Funding Acquisition, PJT; Supervision, PJT. Author Contributions These authors contributed equally to this manuscript. |
OpenAccessLink | http://www.cell.com/article/S1931312819303026/pdf |
PMID | 31324413 |
PQID | 2265780672 |
PQPubID | 23479 |
ParticipantIDs | pubmedcentral_primary_oai_pubmedcentral_nih_gov_6708278 proquest_miscellaneous_2265780672 pubmed_primary_31324413 crossref_primary_10_1016_j_chom_2019_06_013 crossref_citationtrail_10_1016_j_chom_2019_06_013 elsevier_sciencedirect_doi_10_1016_j_chom_2019_06_013 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2019-08-14 |
PublicationDateYYYYMMDD | 2019-08-14 |
PublicationDate_xml | – month: 08 year: 2019 text: 2019-08-14 day: 14 |
PublicationDecade | 2010 |
PublicationPlace | United States |
PublicationPlace_xml | – name: United States |
PublicationTitle | Cell host & microbe |
PublicationTitleAlternate | Cell Host Microbe |
PublicationYear | 2019 |
Publisher | Elsevier Inc |
Publisher_xml | – name: Elsevier Inc |
References | David, Maurice, Carmody, Gootenberg, Button, Wolfe, Ling, Devlin, Varma, Fischbach (bib8) 2014; 505 Dollive, Chen, Grunberg, Bittinger, Hoffmann, Vandivier, Cuff, Lewis, Wu, Bushman (bib11) 2013; 8 Ballal, Veiga, Fenn, Michaud, Kim, Gallini, Glickman, Quéré, Garault, Béal (bib3) 2015; 112 Goodman, Kallstrom, Faith, Reyes, Moore, Dantas, Gordon (bib42) 2011; 108 Voigt, Forsyth, Green, Mutlu, Engen, Vitaterna, Turek, Keshavarzian (bib53) 2014; 9 Turnbaugh, Ridaura, Faith, Rey, Knight, Gordon (bib51) 2009; 1 Lagkouvardos, Pukall, Abt, Foesel, Meier-Kolthoff, Kumar, Bresciani, Martínez, Just, Ziegler (bib21) 2016; 1 Volynets, Louis, Pretz, Lang, Ostaff, Wehkamp, Bischoff (bib54) 2017; 147 Kembel, Cowan, Helmus, Cornwell, Morlon, Ackerly, Blomberg, Webb (bib18) 2010; 26 Finucane, Sharpton, Laurent, Pollard (bib15) 2014; 9 Park, Ahn, Park, Huh, Yoo, Yu, Sung, McGregor, Choi (bib60) 2013; 8 Dalby, Ross, Walker, Morgan (bib7) 2017; 21 Turnbaugh (bib34) 2017; 21 Xiao, Sonne, Feng, Chen, Xia, Li, Fang, Zhang, Fjære, Midtbø (bib57) 2017; 5 Anhê, Roy, Pilon, Dudonné, Matamoros, Varin, Garofalo, Moine, Desjardins, Levy, Marette (bib37) 2015; 64 Lu, Sun, Li, Zhang, Zhou, Su (bib46) 2017; 8 Roopchand, Carmody, Kuhn, Moskal, Rojas-Silva, Turnbaugh, Raskin (bib49) 2015; 64 Ley, Turnbaugh, Klein, Gordon (bib24) 2006; 444 Wu, Chen, Hoffmann, Bittinger, Chen, Keilbaugh, Bewtra, Knights, Walters, Knight (bib55) 2011; 334 Breiman (bib4) 2001; 45 Everard, Lazarevic, Gaïa, Johansson, Ståhlman, Bäckhed, Delzenne, Schrenzel, François, Cani (bib41) 2014; 8 Ruan, Statt, Huang, Tsai, Kuo, Chan, Liao, Tan, Kao (bib50) 2016; 2 Baker (bib2) 2016; 533 Hu, Wang, Liang, Li, Wu, Jin (bib44) 2015; 99 Amir, McDonald, Navas-Molina, Kopylova, Morton, Zech Xu, Kightley, Thompson, Hyde, Gonzalez, Knight (bib1) 2017; 2 Martín-Fernández, Hron, Templ, Filzmoser, Palarea-Albaladejo (bib26) 2015; 15 Cox, Yamanishi, Sohn, Alekseyenko, Leung, Cho, Kim, Li, Gao, Mahana (bib39) 2014; 158 Carmody, Gerber, Luevano, Gatti, Somes, Svenson, Turnbaugh (bib6) 2015; 17 Kopylova, Noé, Touzet (bib19) 2012; 28 Xiao, Feng, Liang, Sonne, Xia, Qiu, Li, Long, Zhang, Zhang (bib56) 2015; 33 DeSantis, Hugenholtz, Larsen, Rojas, Brodie, Keller, Huber, Dalevi, Hu, Andersen (bib9) 2006; 72 Upadhyay, Poroyko, Kim, Devkota, Fu, Liu, Tumanov, Koroleva, Deng, Nagler (bib36) 2012; 13 Sinha, Abu-Ali, Vogtmann, Fodor, Ren, Amir, Schwager, Crabtree, Ma, Abnet (bib32) 2017; 35 Kulecka, Paziewska, Zeber-Lubecka, Ambrozkiewicz, Kopczynski, Kuklinska, Pysniak, Gajewska, Mikula, Ostrowski (bib45) 2016; 13 Paradis, Claude, Strimmer (bib28) 2004; 20 Pasolli, Truong, Malik, Waldron, Segata (bib29) 2016; 12 Rognes, Flouri, Nichols, Quince, Mahé (bib30) 2016; 4 Edgar (bib14) 2017; 5 Moya-Pérez, Neef, Sanz (bib47) 2015; 10 Langille, Zaneveld, Caporaso, McDonald, Knights, Reyes, Clemente, Burkepile, Vega Thurber, Knight (bib22) 2013; 31 Ziętak, Kovatcheva-Datchary, Markiewicz, Ståhlman, Kozak, Bäckhed (bib59) 2016; 23 Silverman, Washburne, Mukherjee, David (bib31) 2017; 6 Turnbaugh, Bäckhed, Fulton, Gordon (bib35) 2008; 3 Kuznetsova, Brockhoff, Christensen (bib20) 2017; 82 Howe, Ringus, Williams, Choo, Greenwald, Owens, Coleman, Meyer, Chang (bib43) 2016; 10 Luo, Tsementzi, Kyrpides, Read, Konstantinidis (bib25) 2012; 7 Edgar (bib12) 2010; 26 Callahan, McMurdie, Holmes (bib5) 2017; 11 Chan, Brar, Kirjavainen, Chen, Peng, Li, Leung, El-Nezami (bib38) 2016; 16 Gurevitch, Koricheva, Nakagawa, Stewart (bib17) 2018; 555 Edgar (bib13) 2016 Ley, Bäckhed, Turnbaugh, Lozupone, Knight, Gordon (bib23) 2005; 102 Sze, Schloss (bib33) 2016; 7 Zeng, Ishaq, Zhao, Wright (bib58) 2016; 35 Dixon (bib10) 2003; 14 Evans, LePard, Kwak, Stancukas, Laskowski, Dougherty, Moulton, Glawe, Wang, Leone (bib40) 2014; 9 Gloor, Macklaim, Pawlowsky-Glahn, Egozcue (bib16) 2017; 8 McMurdie, Holmes (bib27) 2013; 8 Perry, Peng, Barry, Cline, Zhang, Cardone, Petersen, Kibbey, Goodman, Shulman (bib48) 2016; 534 Ussar, Griffin, Bezy, Fujisaka, Vienberg, Softic, Deng, Bry, Gordon, Kahn (bib52) 2015; 22 Chan (10.1016/j.chom.2019.06.013_bib38) 2016; 16 Amir (10.1016/j.chom.2019.06.013_bib1) 2017; 2 Anhê (10.1016/j.chom.2019.06.013_bib37) 2015; 64 McMurdie (10.1016/j.chom.2019.06.013_bib27) 2013; 8 Sze (10.1016/j.chom.2019.06.013_bib33) 2016; 7 Pasolli (10.1016/j.chom.2019.06.013_bib29) 2016; 12 Wu (10.1016/j.chom.2019.06.013_bib55) 2011; 334 Volynets (10.1016/j.chom.2019.06.013_bib54) 2017; 147 Zeng (10.1016/j.chom.2019.06.013_bib58) 2016; 35 Ballal (10.1016/j.chom.2019.06.013_bib3) 2015; 112 Upadhyay (10.1016/j.chom.2019.06.013_bib36) 2012; 13 Edgar (10.1016/j.chom.2019.06.013_bib12) 2010; 26 Ley (10.1016/j.chom.2019.06.013_bib24) 2006; 444 Kuznetsova (10.1016/j.chom.2019.06.013_bib20) 2017; 82 Martín-Fernández (10.1016/j.chom.2019.06.013_bib26) 2015; 15 Park (10.1016/j.chom.2019.06.013_bib60) 2013; 8 Voigt (10.1016/j.chom.2019.06.013_bib53) 2014; 9 Breiman (10.1016/j.chom.2019.06.013_bib4) 2001; 45 Dalby (10.1016/j.chom.2019.06.013_bib7) 2017; 21 Sinha (10.1016/j.chom.2019.06.013_bib32) 2017; 35 Luo (10.1016/j.chom.2019.06.013_bib25) 2012; 7 Goodman (10.1016/j.chom.2019.06.013_bib42) 2011; 108 Turnbaugh (10.1016/j.chom.2019.06.013_bib34) 2017; 21 Kopylova (10.1016/j.chom.2019.06.013_bib19) 2012; 28 Edgar (10.1016/j.chom.2019.06.013_bib13) 2016 Howe (10.1016/j.chom.2019.06.013_bib43) 2016; 10 DeSantis (10.1016/j.chom.2019.06.013_bib9) 2006; 72 Paradis (10.1016/j.chom.2019.06.013_bib28) 2004; 20 Perry (10.1016/j.chom.2019.06.013_bib48) 2016; 534 Ziętak (10.1016/j.chom.2019.06.013_bib59) 2016; 23 Langille (10.1016/j.chom.2019.06.013_bib22) 2013; 31 Finucane (10.1016/j.chom.2019.06.013_bib15) 2014; 9 Xiao (10.1016/j.chom.2019.06.013_bib56) 2015; 33 Ruan (10.1016/j.chom.2019.06.013_bib50) 2016; 2 Carmody (10.1016/j.chom.2019.06.013_bib6) 2015; 17 Evans (10.1016/j.chom.2019.06.013_bib40) 2014; 9 Xiao (10.1016/j.chom.2019.06.013_bib57) 2017; 5 Callahan (10.1016/j.chom.2019.06.013_bib5) 2017; 11 Dixon (10.1016/j.chom.2019.06.013_bib10) 2003; 14 Gurevitch (10.1016/j.chom.2019.06.013_bib17) 2018; 555 Silverman (10.1016/j.chom.2019.06.013_bib31) 2017; 6 Cox (10.1016/j.chom.2019.06.013_bib39) 2014; 158 Roopchand (10.1016/j.chom.2019.06.013_bib49) 2015; 64 Ley (10.1016/j.chom.2019.06.013_bib23) 2005; 102 Rognes (10.1016/j.chom.2019.06.013_bib30) 2016; 4 Dollive (10.1016/j.chom.2019.06.013_bib11) 2013; 8 Kulecka (10.1016/j.chom.2019.06.013_bib45) 2016; 13 Edgar (10.1016/j.chom.2019.06.013_bib14) 2017; 5 Everard (10.1016/j.chom.2019.06.013_bib41) 2014; 8 Lu (10.1016/j.chom.2019.06.013_bib46) 2017; 8 Moya-Pérez (10.1016/j.chom.2019.06.013_bib47) 2015; 10 Kembel (10.1016/j.chom.2019.06.013_bib18) 2010; 26 Baker (10.1016/j.chom.2019.06.013_bib2) 2016; 533 Hu (10.1016/j.chom.2019.06.013_bib44) 2015; 99 Turnbaugh (10.1016/j.chom.2019.06.013_bib51) 2009; 1 David (10.1016/j.chom.2019.06.013_bib8) 2014; 505 Ussar (10.1016/j.chom.2019.06.013_bib52) 2015; 22 Gloor (10.1016/j.chom.2019.06.013_bib16) 2017; 8 Lagkouvardos (10.1016/j.chom.2019.06.013_bib21) 2016; 1 Turnbaugh (10.1016/j.chom.2019.06.013_bib35) 2008; 3 31415747 - Cell Host Microbe. 2019 Aug 14;26(2):158-159 |
References_xml | – volume: 7 start-page: e30087 year: 2012 ident: bib25 article-title: Direct comparisons of Illumina vs. Roche 454 sequencing technologies on the same microbial community DNA sample publication-title: PLoS One – volume: 8 start-page: 2224 year: 2017 ident: bib16 article-title: Microbiome datasets are compositional: and this is not optional publication-title: Front. Microbiol. – volume: 33 start-page: 1103 year: 2015 end-page: 1108 ident: bib56 article-title: A catalog of the mouse gut metagenome publication-title: Nat. Biotechnol. – volume: 8 start-page: e59470 year: 2013 ident: bib60 article-title: Supplementation of publication-title: PLoS One – volume: 21 start-page: 1521 year: 2017 end-page: 1533 ident: bib7 article-title: Dietary uncoupling of gut microbiota and energy harvesting from obesity and glucose tolerance in mice publication-title: Cell Rep. – volume: 2 start-page: 759 year: 2017 ident: bib1 article-title: Deblur rapidly resolves single-nucleotide community sequence patterns publication-title: mSystems – volume: 5 start-page: e3889 year: 2017 ident: bib14 article-title: Accuracy of microbial community diversity estimated by closed- and open-reference OTUs publication-title: PeerJ – volume: 35 start-page: 30 year: 2016 end-page: 36 ident: bib58 article-title: Colonic inflammation accompanies an increase of β-catenin signaling and publication-title: J. Nutr. Biochem. – volume: 533 start-page: 452 year: 2016 end-page: 454 ident: bib2 article-title: 1,500 scientists lift the lid on reproducibility publication-title: Nature – volume: 11 start-page: 2639 year: 2017 end-page: 2643 ident: bib5 article-title: Exact sequence variants should replace operational taxonomic units in marker-gene data analysis publication-title: ISME J. – volume: 15 start-page: 134 year: 2015 end-page: 158 ident: bib26 article-title: Bayesian-multiplicative treatment of count zeros in compositional data sets publication-title: Stat. Model. – volume: 22 start-page: 516 year: 2015 end-page: 530 ident: bib52 article-title: Interactions between gut microbiota, host genetics and diet modulate the predisposition to obesity and metabolic syndrome publication-title: Cell Metab. – volume: 64 start-page: 872 year: 2015 end-page: 883 ident: bib37 article-title: A polyphenol-rich cranberry extract protects from diet-induced obesity, insulin resistance and intestinal inflammation in association with increased publication-title: Gut – volume: 5 start-page: 43 year: 2017 ident: bib57 article-title: High-fat feeding rather than obesity drives taxonomical and functional changes in the gut microbiota in mice publication-title: Microbiome – volume: 23 start-page: 1216 year: 2016 end-page: 1223 ident: bib59 article-title: Altered microbiota contributes to reduced diet-induced obesity upon cold exposure publication-title: Cell Metab. – volume: 2 start-page: 16220 year: 2016 ident: bib50 article-title: Dual-specificity phosphatase 6 deficiency regulates gut microbiome and transcriptome response against diet-induced obesity in mice publication-title: Nat. Microbiol. – volume: 108 start-page: 6252 year: 2011 end-page: 6257 ident: bib42 article-title: Extensive personal human gut microbiota culture collections characterized and manipulated in gnotobiotic mice publication-title: Proc. Natl. Acad. Sci. USA – volume: 112 start-page: 7803 year: 2015 end-page: 7808 ident: bib3 article-title: Host lysozyme-mediated lysis of publication-title: Proc. Natl. Acad. Sci. USA – volume: 8 start-page: e61217 year: 2013 ident: bib27 article-title: phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data publication-title: PLoS One – volume: 158 start-page: 705 year: 2014 end-page: 721 ident: bib39 article-title: Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences publication-title: Cell – start-page: 081257 year: 2016 ident: bib13 article-title: UNOISE2: improved error-correction for Illumina 16S and ITS amplicon sequencing publication-title: bioRxiv – volume: 10 start-page: 1217 year: 2016 end-page: 1227 ident: bib43 article-title: Divergent responses of viral and bacterial communities in the gut microbiome to dietary disturbances in mice publication-title: ISME J. – volume: 4 start-page: e2584 year: 2016 ident: bib30 article-title: VSEARCH: a versatile open source tool for metagenomics publication-title: PeerJ – volume: 8 start-page: 905 year: 2017 ident: bib46 article-title: Modulation of the gut microbiota by krill oil in mice fed a high-sugar high-fat diet publication-title: Front. Microbiol. – volume: 45 start-page: 5 year: 2001 end-page: 32 ident: bib4 article-title: Random forests publication-title: Mach. Learn. – volume: 3 start-page: 213 year: 2008 end-page: 223 ident: bib35 article-title: Diet-induced obesity is linked to marked but reversible alterations in the mouse distal gut microbiome publication-title: Cell Host Microbe – volume: 1 start-page: 6ra14 year: 2009 ident: bib51 article-title: The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice publication-title: Sci. Transl. Med. – volume: 6 start-page: e21887 year: 2017 ident: bib31 article-title: A phylogenetic transform enhances analysis of compositional microbiota data publication-title: eLife – volume: 102 start-page: 11070 year: 2005 end-page: 11075 ident: bib23 article-title: Obesity alters gut microbial ecology publication-title: Proc. Natl. Acad. Sci. USA – volume: 20 start-page: 289 year: 2004 end-page: 290 ident: bib28 article-title: APE: analyses of phylogenetics and evolution in R language publication-title: Bioinformatics – volume: 9 start-page: e97500 year: 2014 ident: bib53 article-title: Circadian disorganization alters intestinal microbiota publication-title: PLoS One – volume: 9 start-page: e92193 year: 2014 ident: bib40 article-title: Exercise prevents weight gain and alters the gut microbiota in a mouse model of high fat diet-induced obesity publication-title: PLoS One – volume: 99 start-page: 9111 year: 2015 end-page: 9122 ident: bib44 article-title: Antibiotic-induced imbalances in gut microbiota aggravates cholesterol accumulation and liver injuries in rats fed a high-cholesterol diet publication-title: Appl. Microbiol. Biotechnol. – volume: 7 start-page: e01018-e16 year: 2016 ident: bib33 article-title: Looking for a signal in the noise: revisiting obesity and the microbiome publication-title: MBio – volume: 64 start-page: 2847 year: 2015 end-page: 2858 ident: bib49 article-title: Dietary polyphenols promote growth of the gut bacterium publication-title: Diabetes – volume: 28 start-page: 3211 year: 2012 end-page: 3217 ident: bib19 article-title: SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data publication-title: Bioinformatics – volume: 444 start-page: 1022 year: 2006 end-page: 1023 ident: bib24 article-title: Microbial ecology: human gut microbes associated with obesity publication-title: Nature – volume: 31 start-page: 814 year: 2013 end-page: 821 ident: bib22 article-title: Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences publication-title: Nat. Biotechnol. – volume: 8 start-page: 2116 year: 2014 end-page: 2130 ident: bib41 article-title: Microbiome of prebiotic-treated mice reveals novel targets involved in host response during obesity publication-title: ISME J. – volume: 9 start-page: e84689 year: 2014 ident: bib15 article-title: A taxonomic signature of obesity in the microbiome? Getting to the guts of the matter publication-title: PLoS One – volume: 72 start-page: 5069 year: 2006 end-page: 5072 ident: bib9 article-title: Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB publication-title: Appl. Environ. Microbiol. – volume: 534 start-page: 213 year: 2016 end-page: 217 ident: bib48 article-title: Acetate mediates a microbiome-brain-β-cell axis to promote metabolic syndrome publication-title: Nature – volume: 82 year: 2017 ident: bib20 article-title: LmerTest package: tests in linear mixed effects models publication-title: J. Stat. Softw. – volume: 26 start-page: 1463 year: 2010 end-page: 1464 ident: bib18 article-title: Picante: R tools for integrating phylogenies and ecology publication-title: Bioinformatics – volume: 334 start-page: 105 year: 2011 end-page: 108 ident: bib55 article-title: Linking long-term dietary patterns with gut microbial enterotypes publication-title: Science – volume: 555 start-page: 175 year: 2018 end-page: 182 ident: bib17 article-title: Meta-analysis and the science of research synthesis publication-title: Nature – volume: 26 start-page: 2460 year: 2010 end-page: 2461 ident: bib12 article-title: Search and clustering orders of magnitude faster than BLAST publication-title: Bioinformatics – volume: 14 start-page: 927 year: 2003 end-page: 930 ident: bib10 article-title: VEGAN, a package of R functions for community ecology publication-title: J. Veg. Sci. – volume: 13 start-page: 57 year: 2016 ident: bib45 article-title: Prolonged transfer of feces from the lean mice modulates gut microbiota in obese mice publication-title: Nutr. Metab. – volume: 12 start-page: e1004977 year: 2016 ident: bib29 article-title: Machine learning meta-analysis of large metagenomic datasets: tools and biological insights publication-title: PLoS Comput. Biol. – volume: 35 start-page: 1077 year: 2017 end-page: 1086 ident: bib32 article-title: Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium publication-title: Nat. Biotechnol. – volume: 16 start-page: 264 year: 2016 ident: bib38 article-title: High fat diet induced atherosclerosis is accompanied with low colonic bacterial diversity and altered abundances that correlates with plaque size, plasma A-FABP and cholesterol: a pilot study of high fat diet and its intervention with publication-title: BMC Microbiol. – volume: 17 start-page: 72 year: 2015 end-page: 84 ident: bib6 article-title: Diet dominates host genotype in shaping the murine gut microbiota publication-title: Cell Host Microbe – volume: 505 start-page: 559 year: 2014 end-page: 563 ident: bib8 article-title: Diet rapidly and reproducibly alters the human gut microbiome publication-title: Nature – volume: 147 start-page: 770 year: 2017 end-page: 780 ident: bib54 article-title: Intestinal barrier function and the gut microbiome are differentially affected in mice fed a western-style diet or drinking water supplemented with fructose publication-title: J. Nutr. – volume: 21 start-page: 278 year: 2017 end-page: 281 ident: bib34 article-title: Microbes and diet-induced obesity: fast, cheap, and out of control publication-title: Cell Host Microbe – volume: 8 start-page: e71806 year: 2013 ident: bib11 article-title: Fungi of the murine gut: episodic variation and proliferation during antibiotic treatment publication-title: PLoS One – volume: 10 start-page: e0126976 year: 2015 ident: bib47 article-title: CECT 7765 Reduces Obesity-Associated Inflammation by Restoring the Lymphocyte-Macrophage Balance and Gut Microbiota Structure in High-Fat Diet-Fed Mice publication-title: PLoS One – volume: 1 start-page: 16131 year: 2016 ident: bib21 article-title: The Mouse Intestinal Bacterial Collection (miBC) provides host-specific insight into cultured diversity and functional potential of the gut microbiota publication-title: Nat. Microbiol. – volume: 13 start-page: 947 year: 2012 end-page: 953 ident: bib36 article-title: Lymphotoxin regulates commensal responses to enable diet-induced obesity publication-title: Nat. Immunol. – volume: 5 start-page: 43 year: 2017 ident: 10.1016/j.chom.2019.06.013_bib57 article-title: High-fat feeding rather than obesity drives taxonomical and functional changes in the gut microbiota in mice publication-title: Microbiome doi: 10.1186/s40168-017-0258-6 – volume: 11 start-page: 2639 year: 2017 ident: 10.1016/j.chom.2019.06.013_bib5 article-title: Exact sequence variants should replace operational taxonomic units in marker-gene data analysis publication-title: ISME J. doi: 10.1038/ismej.2017.119 – volume: 21 start-page: 1521 year: 2017 ident: 10.1016/j.chom.2019.06.013_bib7 article-title: Dietary uncoupling of gut microbiota and energy harvesting from obesity and glucose tolerance in mice publication-title: Cell Rep. doi: 10.1016/j.celrep.2017.10.056 – volume: 1 start-page: 6ra14 year: 2009 ident: 10.1016/j.chom.2019.06.013_bib51 article-title: The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice publication-title: Sci. Transl. Med. doi: 10.1126/scitranslmed.3000322 – volume: 9 start-page: e84689 year: 2014 ident: 10.1016/j.chom.2019.06.013_bib15 article-title: A taxonomic signature of obesity in the microbiome? Getting to the guts of the matter publication-title: PLoS One doi: 10.1371/journal.pone.0084689 – volume: 9 start-page: e97500 year: 2014 ident: 10.1016/j.chom.2019.06.013_bib53 article-title: Circadian disorganization alters intestinal microbiota publication-title: PLoS One doi: 10.1371/journal.pone.0097500 – volume: 17 start-page: 72 year: 2015 ident: 10.1016/j.chom.2019.06.013_bib6 article-title: Diet dominates host genotype in shaping the murine gut microbiota publication-title: Cell Host Microbe doi: 10.1016/j.chom.2014.11.010 – volume: 9 start-page: e92193 year: 2014 ident: 10.1016/j.chom.2019.06.013_bib40 article-title: Exercise prevents weight gain and alters the gut microbiota in a mouse model of high fat diet-induced obesity publication-title: PLoS One doi: 10.1371/journal.pone.0092193 – volume: 158 start-page: 705 year: 2014 ident: 10.1016/j.chom.2019.06.013_bib39 article-title: Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences publication-title: Cell doi: 10.1016/j.cell.2014.05.052 – volume: 15 start-page: 134 year: 2015 ident: 10.1016/j.chom.2019.06.013_bib26 article-title: Bayesian-multiplicative treatment of count zeros in compositional data sets publication-title: Stat. Model. doi: 10.1177/1471082X14535524 – volume: 8 start-page: e71806 year: 2013 ident: 10.1016/j.chom.2019.06.013_bib11 article-title: Fungi of the murine gut: episodic variation and proliferation during antibiotic treatment publication-title: PLoS One doi: 10.1371/journal.pone.0071806 – volume: 26 start-page: 1463 year: 2010 ident: 10.1016/j.chom.2019.06.013_bib18 article-title: Picante: R tools for integrating phylogenies and ecology publication-title: Bioinformatics doi: 10.1093/bioinformatics/btq166 – volume: 31 start-page: 814 year: 2013 ident: 10.1016/j.chom.2019.06.013_bib22 article-title: Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences publication-title: Nat. Biotechnol. doi: 10.1038/nbt.2676 – volume: 23 start-page: 1216 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib59 article-title: Altered microbiota contributes to reduced diet-induced obesity upon cold exposure publication-title: Cell Metab. doi: 10.1016/j.cmet.2016.05.001 – volume: 8 start-page: 2224 year: 2017 ident: 10.1016/j.chom.2019.06.013_bib16 article-title: Microbiome datasets are compositional: and this is not optional publication-title: Front. Microbiol. doi: 10.3389/fmicb.2017.02224 – volume: 35 start-page: 30 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib58 article-title: Colonic inflammation accompanies an increase of β-catenin signaling and Lachnospiraceae/Streptococcaceae bacteria in the hind gut of high-fat diet-fed mice publication-title: J. Nutr. Biochem. doi: 10.1016/j.jnutbio.2016.05.015 – volume: 8 start-page: 2116 year: 2014 ident: 10.1016/j.chom.2019.06.013_bib41 article-title: Microbiome of prebiotic-treated mice reveals novel targets involved in host response during obesity publication-title: ISME J. doi: 10.1038/ismej.2014.45 – volume: 26 start-page: 2460 year: 2010 ident: 10.1016/j.chom.2019.06.013_bib12 article-title: Search and clustering orders of magnitude faster than BLAST publication-title: Bioinformatics doi: 10.1093/bioinformatics/btq461 – volume: 10 start-page: e0126976 year: 2015 ident: 10.1016/j.chom.2019.06.013_bib47 article-title: Bifidobacterium pseudocatenulatum CECT 7765 Reduces Obesity-Associated Inflammation by Restoring the Lymphocyte-Macrophage Balance and Gut Microbiota Structure in High-Fat Diet-Fed Mice publication-title: PLoS One doi: 10.1371/journal.pone.0126976 – volume: 2 start-page: 16220 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib50 article-title: Dual-specificity phosphatase 6 deficiency regulates gut microbiome and transcriptome response against diet-induced obesity in mice publication-title: Nat. Microbiol. doi: 10.1038/nmicrobiol.2016.220 – volume: 8 start-page: 905 year: 2017 ident: 10.1016/j.chom.2019.06.013_bib46 article-title: Modulation of the gut microbiota by krill oil in mice fed a high-sugar high-fat diet publication-title: Front. Microbiol. doi: 10.3389/fmicb.2017.00905 – volume: 16 start-page: 264 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib38 publication-title: BMC Microbiol. doi: 10.1186/s12866-016-0883-4 – volume: 555 start-page: 175 year: 2018 ident: 10.1016/j.chom.2019.06.013_bib17 article-title: Meta-analysis and the science of research synthesis publication-title: Nature doi: 10.1038/nature25753 – start-page: 081257 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib13 article-title: UNOISE2: improved error-correction for Illumina 16S and ITS amplicon sequencing publication-title: bioRxiv – volume: 13 start-page: 947 year: 2012 ident: 10.1016/j.chom.2019.06.013_bib36 article-title: Lymphotoxin regulates commensal responses to enable diet-induced obesity publication-title: Nat. Immunol. doi: 10.1038/ni.2403 – volume: 10 start-page: 1217 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib43 article-title: Divergent responses of viral and bacterial communities in the gut microbiome to dietary disturbances in mice publication-title: ISME J. doi: 10.1038/ismej.2015.183 – volume: 147 start-page: 770 year: 2017 ident: 10.1016/j.chom.2019.06.013_bib54 article-title: Intestinal barrier function and the gut microbiome are differentially affected in mice fed a western-style diet or drinking water supplemented with fructose publication-title: J. Nutr. doi: 10.3945/jn.116.242859 – volume: 505 start-page: 559 year: 2014 ident: 10.1016/j.chom.2019.06.013_bib8 article-title: Diet rapidly and reproducibly alters the human gut microbiome publication-title: Nature doi: 10.1038/nature12820 – volume: 5 start-page: e3889 year: 2017 ident: 10.1016/j.chom.2019.06.013_bib14 article-title: Accuracy of microbial community diversity estimated by closed- and open-reference OTUs publication-title: PeerJ doi: 10.7717/peerj.3889 – volume: 64 start-page: 872 year: 2015 ident: 10.1016/j.chom.2019.06.013_bib37 article-title: A polyphenol-rich cranberry extract protects from diet-induced obesity, insulin resistance and intestinal inflammation in association with increased Akkermansia spp. population in the gut microbiota of mice publication-title: Gut doi: 10.1136/gutjnl-2014-307142 – volume: 102 start-page: 11070 year: 2005 ident: 10.1016/j.chom.2019.06.013_bib23 article-title: Obesity alters gut microbial ecology publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.0504978102 – volume: 7 start-page: e30087 year: 2012 ident: 10.1016/j.chom.2019.06.013_bib25 article-title: Direct comparisons of Illumina vs. Roche 454 sequencing technologies on the same microbial community DNA sample publication-title: PLoS One doi: 10.1371/journal.pone.0030087 – volume: 6 start-page: e21887 year: 2017 ident: 10.1016/j.chom.2019.06.013_bib31 article-title: A phylogenetic transform enhances analysis of compositional microbiota data publication-title: eLife doi: 10.7554/eLife.21887 – volume: 112 start-page: 7803 year: 2015 ident: 10.1016/j.chom.2019.06.013_bib3 article-title: Host lysozyme-mediated lysis of Lactococcus lactis facilitates delivery of colitis-attenuating superoxide dismutase to inflamed colons publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.1501897112 – volume: 35 start-page: 1077 year: 2017 ident: 10.1016/j.chom.2019.06.013_bib32 article-title: Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium publication-title: Nat. Biotechnol. doi: 10.1038/nbt.3981 – volume: 99 start-page: 9111 year: 2015 ident: 10.1016/j.chom.2019.06.013_bib44 article-title: Antibiotic-induced imbalances in gut microbiota aggravates cholesterol accumulation and liver injuries in rats fed a high-cholesterol diet publication-title: Appl. Microbiol. Biotechnol. doi: 10.1007/s00253-015-6753-4 – volume: 534 start-page: 213 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib48 article-title: Acetate mediates a microbiome-brain-β-cell axis to promote metabolic syndrome publication-title: Nature doi: 10.1038/nature18309 – volume: 533 start-page: 452 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib2 article-title: 1,500 scientists lift the lid on reproducibility publication-title: Nature doi: 10.1038/533452a – volume: 334 start-page: 105 year: 2011 ident: 10.1016/j.chom.2019.06.013_bib55 article-title: Linking long-term dietary patterns with gut microbial enterotypes publication-title: Science doi: 10.1126/science.1208344 – volume: 7 start-page: e01018-e16 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib33 article-title: Looking for a signal in the noise: revisiting obesity and the microbiome publication-title: MBio doi: 10.1128/mBio.01018-16 – volume: 22 start-page: 516 year: 2015 ident: 10.1016/j.chom.2019.06.013_bib52 article-title: Interactions between gut microbiota, host genetics and diet modulate the predisposition to obesity and metabolic syndrome publication-title: Cell Metab. doi: 10.1016/j.cmet.2015.07.007 – volume: 14 start-page: 927 year: 2003 ident: 10.1016/j.chom.2019.06.013_bib10 article-title: VEGAN, a package of R functions for community ecology publication-title: J. Veg. Sci. doi: 10.1111/j.1654-1103.2003.tb02228.x – volume: 108 start-page: 6252 year: 2011 ident: 10.1016/j.chom.2019.06.013_bib42 article-title: Extensive personal human gut microbiota culture collections characterized and manipulated in gnotobiotic mice publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.1102938108 – volume: 20 start-page: 289 year: 2004 ident: 10.1016/j.chom.2019.06.013_bib28 article-title: APE: analyses of phylogenetics and evolution in R language publication-title: Bioinformatics doi: 10.1093/bioinformatics/btg412 – volume: 28 start-page: 3211 year: 2012 ident: 10.1016/j.chom.2019.06.013_bib19 article-title: SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts611 – volume: 444 start-page: 1022 year: 2006 ident: 10.1016/j.chom.2019.06.013_bib24 article-title: Microbial ecology: human gut microbes associated with obesity publication-title: Nature doi: 10.1038/4441022a – volume: 12 start-page: e1004977 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib29 article-title: Machine learning meta-analysis of large metagenomic datasets: tools and biological insights publication-title: PLoS Comput. Biol. doi: 10.1371/journal.pcbi.1004977 – volume: 82 year: 2017 ident: 10.1016/j.chom.2019.06.013_bib20 article-title: LmerTest package: tests in linear mixed effects models publication-title: J. Stat. Softw. – volume: 2 start-page: 759 year: 2017 ident: 10.1016/j.chom.2019.06.013_bib1 article-title: Deblur rapidly resolves single-nucleotide community sequence patterns publication-title: mSystems doi: 10.1128/mSystems.00191-16 – volume: 72 start-page: 5069 year: 2006 ident: 10.1016/j.chom.2019.06.013_bib9 article-title: Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB publication-title: Appl. Environ. Microbiol. doi: 10.1128/AEM.03006-05 – volume: 8 start-page: e59470 year: 2013 ident: 10.1016/j.chom.2019.06.013_bib60 article-title: Supplementation of Lactobacillus curvatus HY7601 and Lactobacillus plantarum KY1032 in diet-induced obese mice is associated with gut microbial changes and reduction in obesity publication-title: PLoS One doi: 10.1371/journal.pone.0059470 – volume: 33 start-page: 1103 year: 2015 ident: 10.1016/j.chom.2019.06.013_bib56 article-title: A catalog of the mouse gut metagenome publication-title: Nat. Biotechnol. doi: 10.1038/nbt.3353 – volume: 4 start-page: e2584 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib30 article-title: VSEARCH: a versatile open source tool for metagenomics publication-title: PeerJ doi: 10.7717/peerj.2584 – volume: 1 start-page: 16131 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib21 article-title: The Mouse Intestinal Bacterial Collection (miBC) provides host-specific insight into cultured diversity and functional potential of the gut microbiota publication-title: Nat. Microbiol. doi: 10.1038/nmicrobiol.2016.131 – volume: 21 start-page: 278 year: 2017 ident: 10.1016/j.chom.2019.06.013_bib34 article-title: Microbes and diet-induced obesity: fast, cheap, and out of control publication-title: Cell Host Microbe doi: 10.1016/j.chom.2017.02.021 – volume: 8 start-page: e61217 year: 2013 ident: 10.1016/j.chom.2019.06.013_bib27 article-title: phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data publication-title: PLoS One doi: 10.1371/journal.pone.0061217 – volume: 64 start-page: 2847 year: 2015 ident: 10.1016/j.chom.2019.06.013_bib49 article-title: Dietary polyphenols promote growth of the gut bacterium Akkermansia muciniphila and attenuate high-fat diet–induced metabolic syndrome publication-title: Diabetes doi: 10.2337/db14-1916 – volume: 13 start-page: 57 year: 2016 ident: 10.1016/j.chom.2019.06.013_bib45 article-title: Prolonged transfer of feces from the lean mice modulates gut microbiota in obese mice publication-title: Nutr. Metab. doi: 10.1186/s12986-016-0116-8 – volume: 3 start-page: 213 year: 2008 ident: 10.1016/j.chom.2019.06.013_bib35 article-title: Diet-induced obesity is linked to marked but reversible alterations in the mouse distal gut microbiome publication-title: Cell Host Microbe doi: 10.1016/j.chom.2008.02.015 – volume: 45 start-page: 5 year: 2001 ident: 10.1016/j.chom.2019.06.013_bib4 article-title: Random forests publication-title: Mach. Learn. doi: 10.1023/A:1010933404324 – reference: 31415747 - Cell Host Microbe. 2019 Aug 14;26(2):158-159 |
SSID | ssj0055071 |
Score | 2.642975 |
SecondaryResourceType | review_article |
Snippet | Multiple research groups have shown that diet impacts the gut microbiome; however, variability in experimental design and quantitative assessment have made it... |
SourceID | pubmedcentral proquest pubmed crossref elsevier |
SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
StartPage | 265 |
SubjectTerms | Animals Bacteria - classification Bacteria - genetics Databases, Factual Diet Diet, High-Fat Gastrointestinal Microbiome - genetics Gastrointestinal Microbiome - physiology high-fat diet Humans Lactococcus Lactococcus - classification Lactococcus - genetics Machine Learning meta-analysis Mice microbiome murine Phylogeny |
Title | Meta-Analysis Reveals Reproducible Gut Microbiome Alterations in Response to a High-Fat Diet |
URI | https://dx.doi.org/10.1016/j.chom.2019.06.013 https://www.ncbi.nlm.nih.gov/pubmed/31324413 https://www.proquest.com/docview/2265780672 https://pubmed.ncbi.nlm.nih.gov/PMC6708278 |
Volume | 26 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1La9wwEBYhEOiltEkf20dQobciNrIeto9pkm0opIe0gT0UhJ7UZetdWm8g_74zsr1kU5pDTsb2CIRGGn32fPqGkPe-qGUMyTKe6sBkVJG5IjkGa1xxF2sZQibIftHnV_LzXM13yMl4FgZplUPs72N6jtbDk-kwmtNV00y_AvTgIieCIAzDpwTEYSGrfIhv_nGMxijXxfvMMmdoPRyc6TleWI8E6V111vDk4n-b07_g8y6H8tamNHtCHg9okh73HX5KdmK7T_b6-pI3B-T7RewsG3VH6GW8BliI11XWeW3cItJP645eNL0c069IjxdZZhknI21aMM0U2ki7JbUUSSFsZjt62sTuGbmanX07OWdDOQXmpVId07as6-BLrK6BNXeC1uCM0pdBR2WPUhGUQOqZFy45p3x95F0lqwCYKlRVKsRzstsu2_iSUGF1USsXpPRJCl9YYYXWNqWysghIJoSP42j8oDWOJS8WZiSV_TQ49gbH3iCzjosJ-bBps-qVNu61VqN7zNZ8MbAV3Nvu3ehLAwsJsyO2jcv1HwM4FKIXZqYn5EXv200_UN8ScCO0Lre8vjFAke7tN23zI4t16xJAVlm9emB_X5NHeId_sbl8Q3a73-v4FmBQ5w7zPP8LDukHog |
linkProvider | Elsevier |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwEB6VIgQXVF5loYCRuCFr69jO41gKyxa6PUAr7QHJ8lMELdkVZJH67-txkhULogdOkWJbsmbG4y_x528AXtmsEt4FTVmoHBVeemqyYGhc45IZXwnnEkH2LJ9eiA9zOd-B4-EuDNIq-9zf5fSUrfs3496a41Vdjz9H6MF4OgiKaTh-StyAmxENFFi_4WT-ZkjHqNfFuqNlRrF7f3OmI3lhQRLkd1VJxJPxf-1Of6PPP0mUv-1Kkz2428NJctTN-B7s-OY-3OoKTF4-gC8z32o6CI-QT_5XxIX4XCWh19osPHm_bsms7vSYvntytEg6yxiNpG5i18Sh9aRdEk2QFUInuiVva98-hIvJu_PjKe3rKVArpGxprouqcrbA8hpYdMflefRGYQuXe6kPQ-YkR-6Z5SYYI211aE0pShdBlSvLkPFHsNssG_8YCNd5VknjhLBBcJtprnme6xCKUiMiGQEb7KhsLzaONS8WamCVfVNoe4W2V0itY3wErzdjVp3UxrW95eAetRUwKu4F1457OfhSxZWExyO68cv1TxWBaExfeDQ9gv3Ot5t5oMBlBI5xdLHl9U0HVOnebmnqr0mtO0ZkmRXlk_-c7wu4PT2fnarTk7OPT-EOtuAvbSYOYLf9sfbPIiZqzfMU81dN9ArB |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Meta-Analysis+Reveals+Reproducible+Gut+Microbiome+Alterations+in+Response+to+a+High-Fat+Diet&rft.jtitle=Cell+host+%26+microbe&rft.au=Bisanz%2C+Jordan+E&rft.au=Upadhyay%2C+Vaibhav&rft.au=Turnbaugh%2C+Jessie+A&rft.au=Ly%2C+Kimberly&rft.date=2019-08-14&rft.eissn=1934-6069&rft.volume=26&rft.issue=2&rft.spage=265&rft_id=info:doi/10.1016%2Fj.chom.2019.06.013&rft_id=info%3Apmid%2F31324413&rft.externalDocID=31324413 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1931-3128&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1931-3128&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1931-3128&client=summon |