Mammalian gut metabolomes mirror microbiome composition and host phylogeny.
Journal
The ISME journal
ISSN: 1751-7370
Titre abrégé: ISME J
Pays: England
ID NLM: 101301086
Informations de publication
Date de publication:
05 2022
05 2022
Historique:
received:
27
01
2021
accepted:
09
11
2021
revised:
18
10
2021
pubmed:
15
12
2021
medline:
28
4
2022
entrez:
14
12
2021
Statut:
ppublish
Résumé
In the past decade, studies on the mammalian gut microbiome have revealed that different animal species have distinct gut microbial compositions. The functional ramifications of this variation in microbial composition remain unclear: do these taxonomic differences indicate microbial adaptations to host-specific functionality, or are these diverse microbial communities essentially functionally redundant, as has been indicated by previous metagenomics studies? Here, we examine the metabolic content of mammalian gut microbiomes as a direct window into ecosystem function, using an untargeted metabolomics platform to analyze 101 fecal samples from a range of 25 exotic mammalian species in collaboration with a zoological center. We find that mammalian metabolomes are chemically diverse and strongly linked to microbiome composition, and that metabolome composition is further correlated to the phylogeny of the mammalian host. Specific metabolites enriched in different animal species included modified and degraded host and dietary compounds such as bile acids and triterpenoids, as well as fermentation products such as lactate and short-chain fatty acids. Our results suggest that differences in microbial taxonomic composition are indeed translated to host-specific metabolism, indicating that taxonomically distant microbiomes are more functionally diverse than redundant.
Identifiants
pubmed: 34903850
doi: 10.1038/s41396-021-01152-0
pii: 10.1038/s41396-021-01152-0
pmc: PMC9038745
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1262-1274Subventions
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : 240356
Organisme : Israel Science Foundation (ISF)
ID : 1947/19
Organisme : U.S. Department of Health & Human Services | National Institutes of Health (NIH)
ID : GMS10RR029121
Organisme : Israel Science Foundation (ISF)
ID : 1667/15
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : 640384
Informations de copyright
© 2021. The Author(s).
Références
Ley RE, Hamady M, Lozupone C, Turnbaugh PJ, Ramey RR, Bircher JS, et al. Evolution of mammals and their gut microbes. Science. 2008;320:1647–51.
pubmed: 18497261
pmcid: 2649005
doi: 10.1126/science.1155725
Song SJ, Sanders JG, Delsuc F, Metcalf J, Amato K, Taylor MW, et al. Comparative analyses of vertebrate gut microbiomes reveal convergence between birds and bats. mBio. 2020;11:e02901–19.
pubmed: 31911491
pmcid: 6946802
doi: 10.1128/mBio.02901-19
Godon J-J, Arulazhagan P, Steyer J-P, Hamelin J. Vertebrate bacterial gut diversity: size also matters. BMC Ecol. 2016;16:12.
pubmed: 27008566
pmcid: 4804487
doi: 10.1186/s12898-016-0071-2
Lutz HL, Jackson EW, Webala PW, Babyesiza WS, Kerbis Peterhans JC, Demos TC, et al. Ecology and host identity outweigh evolutionary history in shaping the bat microbiome. mSystems. 2019;4:e00511–19.
pubmed: 31719140
pmcid: 7407897
Nishida AH, Ochman H. Rates of gut microbiome divergence in mammals. Mol Ecol. 2018;27:1884–97.
pubmed: 29290090
pmcid: 5935551
doi: 10.1111/mec.14473
Groussin M, Mazel F, Sanders JG, Smillie CS, Lavergne S, Thuiller W, et al. Unraveling the processes shaping mammalian gut microbiomes over evolutionary time. Nat Commun. 2017;8:14319.
pubmed: 28230052
pmcid: 5331214
doi: 10.1038/ncomms14319
Lim SJ, Bordenstein SR. An introduction to phylosymbiosis. Proc Biol Sci. 2020;287:20192900.
pubmed: 32126958
pmcid: 7126058
Ross AA, Müller KM, Weese JS, Neufeld JD. Comprehensive skin microbiome analysis reveals the uniqueness of human skin and evidence for phylosymbiosis within the class Mammalia. Proc Natl Acad Sci USA. 2018;115:E5786–E5795.
pubmed: 29871947
pmcid: 6016819
doi: 10.1073/pnas.1800367115
Ochman H, Worobey M, Kuo C-H, Ndjango J-BN, Peeters M, Hahn BH, et al. Evolutionary relationships of wild hominids recapitulated by gut microbial communities. PLoS Biol. 2010;8:e1000546.
pubmed: 21103409
pmcid: 2982803
doi: 10.1371/journal.pbio.1000546
Amato KR, G Sanders J, Song SJ, Nute M, Metcalf JL, Thompson LR, et al. Evolutionary trends in host physiology outweigh dietary niche in structuring primate gut microbiomes. ISME J. 2018;13:576–87.
pubmed: 29995839
pmcid: 6461848
doi: 10.1038/s41396-018-0175-0
Moeller AH, Caro-Quintero A, Mjungu D, Georgiev AV, Lonsdorf EV, Muller MN, et al. Cospeciation of gut microbiota with hominids. Science. 2016;353:380–2.
pubmed: 27463672
pmcid: 4995445
doi: 10.1126/science.aaf3951
Brooks AW, Kohl KD, Brucker RM, van Opstal EJ, Bordenstein SR. Phylosymbiosis: relationships and functional effects of microbial communities across host evolutionary history. PLoS Biol. 2016;14:e2000225.
pubmed: 27861590
pmcid: 5115861
doi: 10.1371/journal.pbio.2000225
Delsuc F, Metcalf JL, Wegener Parfrey L, Song SJ, González A, Knight R. Convergence of gut microbiomes in myrmecophagous mammals. Mol Ecol. 2014;23:1301–17.
pubmed: 24118574
doi: 10.1111/mec.12501
Muegge BD, Kuczynski J, Knights D, Clemente JC, González A, Fontana L, et al. Diet drives convergence in gut microbiome functions across mammalian phylogeny and within humans. Science. 2011;332:970–4.
pubmed: 21596990
pmcid: 3303602
doi: 10.1126/science.1198719
Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, et al. A core gut microbiome in obese and lean twins. Nature. 2009;457:480–4.
pubmed: 19043404
doi: 10.1038/nature07540
Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature. 2012;486:207–14.
doi: 10.1038/nature11234
Weimer PJ. Redundancy, resilience, and host specificity of the ruminal microbiota: implications for engineering improved ruminal fermentations. Front Microbiol. 2015;6:296.
pubmed: 25914693
pmcid: 4392294
doi: 10.3389/fmicb.2015.00296
Louca S, Parfrey LW, Doebeli M. Decoupling function and taxonomy in the global ocean microbiome. Science. 2016;353:1272–7.
pubmed: 27634532
doi: 10.1126/science.aaf4507
Nelson MB, Martiny AC, Martiny JBH. Global biogeography of microbial nitrogen-cycling traits in soil. Proc Natl Acad Sci USA. 2016;113:8033–40.
pubmed: 27432978
pmcid: 4961168
doi: 10.1073/pnas.1601070113
Louca S, Polz MF, Mazel F, Albright MBN, Huber JA, O’Connor MI, et al. Function and functional redundancy in microbial systems. Nat Ecol Evol. 2018;2:936–43.
pubmed: 29662222
doi: 10.1038/s41559-018-0519-1
Inkpen SA, Andrew Inkpen S, Douglas GM, Brunet TDP, Leuschen K, Ford Doolittle W, et al. The coupling of taxonomy and function in microbiomes. Biol Philos. 2017;32:1225–43.
doi: 10.1007/s10539-017-9602-2
Krautkramer KA, Fan J, Bäckhed F. Gut microbial metabolites as multi-kingdom intermediates. Nat Rev Microbiol. 2021;19:77–94.
pubmed: 32968241
doi: 10.1038/s41579-020-0438-4
Turnbaugh PJ, Gordon JI. An invitation to the marriage of metagenomics and metabolomics. Cell. 2008;134:708–13.
pubmed: 18775300
doi: 10.1016/j.cell.2008.08.025
Moya A, Ferrer M. Functional redundancy-induced stability of gut microbiota subjected to disturbance. Trends Microbiol. 2016;24:402–13.
pubmed: 26996765
doi: 10.1016/j.tim.2016.02.002
Wang M, Carver JJ, Phelan VV, Sanchez LM, Garg N, Peng Y, et al. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nat Biotechnol. 2016;34:828–37.
pubmed: 27504778
pmcid: 5321674
doi: 10.1038/nbt.3597
Wilson DE, Reeder DM Mammal species of the world: a taxonomic and geographic reference. 2005. JHU Press.
Jami E, Israel A, Kotser A, Mizrahi I. Exploring the bovine rumen bacterial community from birth to adulthood. ISME J. 2013;7:1069–79.
pubmed: 23426008
pmcid: 3660679
doi: 10.1038/ismej.2013.2
Stevenson DM, Weimer PJ. Dominance of Prevotella and low abundance of classical ruminal bacterial species in the bovine rumen revealed by relative quantification real-time PCR. Appl Microbiol Biotechnol. 2007;75:165–74.
pubmed: 17235560
doi: 10.1007/s00253-006-0802-y
Caporaso JG, Gregory Caporaso J, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012;6:1621–4.
pubmed: 22402401
pmcid: 3400413
doi: 10.1038/ismej.2012.8
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.
pubmed: 27214047
pmcid: 4927377
doi: 10.1038/nmeth.3869
Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590–6.
pubmed: 23193283
doi: 10.1093/nar/gks1219
Douglas GM, Maffei VJ, Zaneveld JR, Yurgel SN, Brown JR, Taylor CM, et al. PICRUSt2 for prediction of metagenome functions. Nat Biotechnol. 2020;38:685–8.
pubmed: 32483366
pmcid: 7365738
doi: 10.1038/s41587-020-0548-6
Gawlik-Dziki U, Dziki D, Baraniak B, Lin R. The effect of simulated digestion in vitro on bioactivity of wheat bread with Tartary buckwheat flavones addition. LWT. 2009;42:137–43.
doi: 10.1016/j.lwt.2008.06.009
Melnik AV, da Silva RR, Hyde ER, Aksenov AA, Vargas F, Bouslimani A, et al. Coupling targeted and untargeted mass spectrometry for metabolome-microbiome-wide association studies of human fecal samples. Anal Chem. 2017;89:7549–59.
pubmed: 28628333
doi: 10.1021/acs.analchem.7b01381
Giavalisco P, Li Y, Matthes A, Eckhardt A, Hubberten H-M, Hesse H, et al. Elemental formula annotation of polar and lipophilic metabolites using
pubmed: 21699588
doi: 10.1111/j.1365-313X.2011.04682.x
Lisec J, Schauer N, Kopka J, Willmitzer L, Fernie AR. Gas chromatography mass spectrometry–based metabolite profiling in plants. Nat Protoc. 2006;1:387–96.
pubmed: 17406261
doi: 10.1038/nprot.2006.59
Hochberg U, Degu A, Toubiana D, Gendler T, Nikoloski Z, Rachmilevitch S, et al. Metabolite profiling and network analysis reveal coordinated changes in grapevine water stress response. BMC Plant Biol. 2013;13:184.
pubmed: 24256338
pmcid: 4225576
doi: 10.1186/1471-2229-13-184
Shabat SKB, Sasson G, Doron-Faigenboim A, Durman T, Yaacoby S, Berg Miller ME, et al. Specific microbiome-dependent mechanisms underlie the energy harvest efficiency of ruminants. ISME J. 2016;10:2958–72.
pubmed: 27152936
pmcid: 5148187
doi: 10.1038/ismej.2016.62
Pluskal T, Castillo S, Villar-Briones A, Orešič M MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinformatics. 2010;11;1–11.
Nothias L-F, Petras D, Schmid R, Dührkop K, Rainer J, Sarvepalli A, et al. Feature-based molecular networking in the GNPS analysis environment. Nat Methods. 2020;17:905–8.
pubmed: 32839597
pmcid: 7885687
doi: 10.1038/s41592-020-0933-6
da Silva RR, Wang M, Nothias L-F, van der Hooft JJJ, Caraballo-Rodríguez AM, Fox E, et al. Propagating annotations of molecular networks using in silico fragmentation. PLoS Comput Biol. 2018;14:e1006089.
pubmed: 29668671
pmcid: 5927460
doi: 10.1371/journal.pcbi.1006089
Ernst M, Kang KB, Caraballo-Rodríguez AM, Nothias L-F, Wandy J, Chen C, et al. MolNetEnhancer: enhanced molecular networks by integrating metabolome mining and annotation tools. Metabolites. 2019;9:144.
pmcid: 6680503
doi: 10.3390/metabo9070144
Djoumbou Feunang Y, Eisner R, Knox C, Chepelev L, Hastings J, Owen G, et al. ClassyFire: automated chemical classification with a comprehensive, computable taxonomy. J Cheminform. 2016;8:61.
pubmed: 27867422
pmcid: 5096306
doi: 10.1186/s13321-016-0174-y
Chambers MC, Maclean B, Burke R, Amodei D, Ruderman DL, Neumann S, et al. A cross-platform toolkit for mass spectrometry and proteomics. Nat Biotechnol. 2012;30:918–20.
pubmed: 23051804
pmcid: 3471674
doi: 10.1038/nbt.2377
Kessner D, Chambers M, Burke R, Agus D, Mallick P. ProteoWizard: open source software for rapid proteomics tools development. Bioinformatics. 2008;24:2534–6.
pubmed: 18606607
pmcid: 2732273
doi: 10.1093/bioinformatics/btn323
Aksenov AA, Laponogov I, Zhang Z, Doran SLF, Belluomo I, Veselkov D, et al. Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data. Nat Biotechnol. 2021;39:169–73.
pubmed: 33169034
doi: 10.1038/s41587-020-0700-3
Kiela PR, Ghishan FK. Physiology of intestinal absorption and secretion. Best Pr Res Clin Gastroenterol. 2016;30:145–59.
doi: 10.1016/j.bpg.2016.02.007
Karasov WH, Diamond JM. Interplay between physiology and ecology in digestion. Bioscience. 1988;38:602–11.
doi: 10.2307/1310825
McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE. 2013;8:e61217.
pubmed: 23630581
pmcid: 3632530
doi: 10.1371/journal.pone.0061217
Dixon P. VEGAN, a package of R functions for community ecology. J Veg Sci. 2003;14:927–30.
doi: 10.1111/j.1654-1103.2003.tb02228.x
Wickham H, ggplot2: elegant graphics for data analysis. Springer; 2016.
Hulsen T, de Vlieg J, Alkema W. BioVenn—a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams. BMC Genomics. 2008;9:488.
pubmed: 18925949
pmcid: 2584113
doi: 10.1186/1471-2164-9-488
Anderson MJ. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 2001;26:32–46.
Anderson MJ, Walsh DCI. PERMANOVA, ANOSIM, and the Mantel test in the face of heterogeneous dispersions: what null hypothesis are you testing? Ecol Monogr. 2013;83:557–74.
doi: 10.1890/12-2010.1
Galili T. dendextend: an R package for visualizing, adjusting and comparing trees of hierarchical clustering. Bioinformatics. 2015;31:3718–20.
pubmed: 26209431
pmcid: 4817050
doi: 10.1093/bioinformatics/btv428
Paradis E, Schliep K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics. 2019;35:526–8.
pubmed: 30016406
doi: 10.1093/bioinformatics/bty633
Hedges SB, Dudley J, Kumar S. TimeTree: a public knowledge-base of divergence times among organisms. Bioinformatics. 2006;22:2971–2.
pubmed: 17021158
doi: 10.1093/bioinformatics/btl505
Kumar S, Stecher G, Suleski M, Hedges SB. TimeTree: a resource for timelines, timetrees, and divergence times. Mol Biol Evol. 2017;34:1812–9.
pubmed: 28387841
doi: 10.1093/molbev/msx116
Baker FB. Stability of two hierarchical grouping techniques case I: sensitivity to data errors. J Am Stat Assoc. 1974;69:440–5.
De Cáceres M, Legendre P. Associations between species and groups of sites: indices and statistical inference. Ecology. 2009;90:3566–74.
pubmed: 20120823
doi: 10.1890/08-1823.1
Sumner LW, Amberg A, Barrett D, Beale MH, Beger R, Daykin CA, et al. Proposed minimum reporting standards for chemical analysis chemical analysis working group (CAWG) metabolomics standards initiative (MSI). Metabolomics. 2007;3:211–21.
pubmed: 24039616
pmcid: 3772505
doi: 10.1007/s11306-007-0082-2
Jarmusch AK, Wang M, Aceves CM, Advani RS, Aguirre S, Aksenov AA, et al. ReDU: a framework to find and reanalyze public mass spectrometry data. Nat Methods. 2020;17:901–4.
pubmed: 32807955
pmcid: 7968862
doi: 10.1038/s41592-020-0916-7
Ridlon JM, Kang D-J, Hylemon PB. Bile salt biotransformations by human intestinal bacteria. J Lipid Res. 2006;47:241–59.
pubmed: 16299351
doi: 10.1194/jlr.R500013-JLR200
Winston JA, Theriot CM. Diversification of host bile acids by members of the gut microbiota. Gut Microbes. 2019;11:1–14.
Quinn RA, Melnik AV, Vrbanac A, Fu T, Patras KA, Christy MP, et al. Global chemical effects of the microbiome include new bile-acid conjugations. Nature. 2020;579:123–9.
pubmed: 32103176
pmcid: 7252668
doi: 10.1038/s41586-020-2047-9
Haslewood GA. Bile salt evolution. J Lipid Res. 1967;8:535–50.
pubmed: 4862128
doi: 10.1016/S0022-2275(20)38873-8
Hofmann AF, Hagey LR, Krasowski MD. Bile salts of vertebrates: structural variation and possible evolutionary significance. J Lipid Res. 2010;51:226–46.
pubmed: 19638645
pmcid: 2803226
doi: 10.1194/jlr.R000042
Hofmann AF. Bile acids: the good, the bad, and the ugly. N. Physiol Sci. 1999;14:24–29.
Bergman EN. Energy contributions of volatile fatty acids from the gastrointestinal tract in various species. Physiol Rev. 1990;70:567–90.
pubmed: 2181501
doi: 10.1152/physrev.1990.70.2.567
Engelhardt W von, Rechkemmer G. The physiological effects of short-chain fatty acids in the hind gut. Fibre in human and animal nutrition. 1983. The Royal Society of New Zealand, Palmerston North, New Zealand, pp 149-55.
Reichardt N, Duncan SH, Young P, Belenguer A, McWilliam Leitch C, Scott KP, et al. Phylogenetic distribution of three pathways for propionate production within the human gut microbiota. ISME J. 2014;8:1323–35.
pubmed: 24553467
pmcid: 4030238
doi: 10.1038/ismej.2014.14
Clemens ET, Stevens CE. Sites of organic acid production and patterns of digesta movement in the gastro-intestinal tract of the raccoon. J Nutr. 1979;109:1110–6.
pubmed: 448450
doi: 10.1093/jn/109.6.1110
Schwab C, Cristescu B, Boyce MS, Stenhouse GB, Gänzle M. Bacterial populations and metabolites in the feces of free roaming and captive grizzly bears. Can J Microbiol. 2009;55:1335–46.
pubmed: 20029525
doi: 10.1139/W09-083
Schwab C, Gänzle M. Comparative analysis of fecal microbiota and intestinal microbial metabolic activity in captive polar bears. Can J Microbiol. 2011;57:177–85.
pubmed: 21358758
doi: 10.1139/W10-113
Kanehisa M. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28:27–30.
pubmed: 10592173
pmcid: 102409
doi: 10.1093/nar/28.1.27
Tofalo R, Cocchi S, Suzzi G. Polyamines and gut microbiota. Front Nutr. 2019;6:16.
pubmed: 30859104
pmcid: 6397830
doi: 10.3389/fnut.2019.00016
Matsumoto M, Kibe R, Ooga T, Aiba Y, Kurihara S, Sawaki E, et al. Impact of intestinal microbiota on intestinal luminal metabolome. Sci Rep. 2012;2:233.
pubmed: 22724057
pmcid: 3380406
doi: 10.1038/srep00233
Pugin B, Barcik W, Westermann P, Heider A, Wawrzyniak M, Hellings P, et al. A wide diversity of bacteria from the human gut produces and degrades biogenic amines. Micro Ecol Health Dis. 2017;28:1353881.
Nakamura A, Ooga T, Matsumoto M. Intestinal luminal putrescine is produced by collective biosynthetic pathways of the commensal microbiome. Gut Microbes. 2019;10:159–71.
pubmed: 30183487
doi: 10.1080/19490976.2018.1494466
Aura A-M, O’Leary KA, Williamson G, Ojala M, Bailey M, Puupponen-Pimiä R, et al. Quercetin derivatives are deconjugated and converted to hydroxyphenylacetic acids but not methylated by human fecal flora in vitro. J Agric Food Chem. 2002;50:1725–30.
pubmed: 11879065
doi: 10.1021/jf0108056
Booth AN, Deeds F, Jones FT, Murray CW. The metabolic fate of rutin and quercetin in the animal body. J Biol Chem. 1956;223:251–7.
pubmed: 13376593
doi: 10.1016/S0021-9258(18)65133-6
Jaganath IB, Mullen W, Edwards CA, Crozier A. The relative contribution of the small and large intestine to the absorption and metabolism of rutin in man. Free Radic Res. 2006;40:1035–46.
pubmed: 17015248
doi: 10.1080/10715760600771400
Mena P, Calani L, Bruni R, Del Rio D. Bioactivation of high-molecular-weight polyphenols by the gut microbiome. Diet-Microbe Interactions in the Gut. Academic Press; 2015. pp 73–101.
Serra A, Macià A, Romero M-P, Reguant J, Ortega N, Motilva M-J. Metabolic pathways of the colonic metabolism of flavonoids (flavonols, flavones and flavanones) and phenolic acids. Food Chem. 2012;130:383–93.
doi: 10.1016/j.foodchem.2011.07.055
Peng X, Zhang Z, Zhang N, Liu L, Li S, Wei H. In vitro catabolism of quercetin by human fecal bacteria and the antioxidant capacity of its catabolites. Food Nutr Res. 2014;58:23406.
Feng X, Li Y, Brobbey Oppong M, Qiu F. Insights into the intestinal bacterial metabolism of flavonoids and the bioactivities of their microbe-derived ring cleavage metabolites. Drug Metab Rev. 2018;50:343–56.
pubmed: 30010437
doi: 10.1080/03602532.2018.1485691
Maini Rekdal V, Bess EN, Bisanz JE, Turnbaugh PJ, Balskus EP. Discovery and inhibition of an interspecies gut bacterial pathway for Levodopa metabolism. Science. 2019;364:1055.
doi: 10.1126/science.aau6323
Maini Rekdal V, Nol Bernadino P, Luescher MU, Kiamehr S, Le C, Bisanz JE, et al. A widely distributed metalloenzyme class enables gut microbial metabolism of host- and diet-derived catechols. Elife. 2020;9:e50845.
pubmed: 32067637
pmcid: 7028382
doi: 10.7554/eLife.50845
Davenport ER, Sanders JG, Song SJ, Amato KR, Clark AG, Knight R. The human microbiome in evolution. BMC Biol. 2017;15:127.
pubmed: 29282061
pmcid: 5744394
doi: 10.1186/s12915-017-0454-7
Steiner CC, Ryder OA. Molecular phylogeny and evolution of the Perissodactyla. Zool J Linn Soc. 2011;163:1289–303.
doi: 10.1111/j.1096-3642.2011.00752.x
McKenzie VJ, Song SJ, Delsuc F, Prest TL, Oliverio AM, Korpita TM, et al. The effects of captivity on the mammalian gut microbiome. Integr Comp Biol. 2017;57:690–704.
pubmed: 28985326
pmcid: 5978021
doi: 10.1093/icb/icx090
Frankel JS, Mallott EK, Hopper LM, Ross SR, Amato KR. The effect of captivity on the primate gut microbiome varies with host dietary niche. Am J Primatol. 2019;81:e23061.
pubmed: 31713260
doi: 10.1002/ajp.23061
Dührkop K, Nothias L-F, Fleischauer M, Reher R, Ludwig M, Hoffmann MA, et al. Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra. Nat Biotechnol. 2021;39:462–71.
pubmed: 33230292
doi: 10.1038/s41587-020-0740-8
Tripathi A, Vázquez-Baeza Y, Gauglitz JM, Wang M, Dührkop K, Nothias-Esposito M, et al. Chemically informed analyses of metabolomics mass spectrometry data with Qemistree. Nat Chem Biol. 2021;17:146–51.
pubmed: 33199911
doi: 10.1038/s41589-020-00677-3
Hehemann J-H, Correc G, Barbeyron T, Helbert W, Czjzek M, Michel G. Transfer of carbohydrate-active enzymes from marine bacteria to Japanese gut microbiota. Nature. 2010;464:908–12.
pubmed: 20376150
doi: 10.1038/nature08937
Pudlo NA, Pereira GV, Parnami J, Cid M, Markert S, Tingley JP, et al. Extensive transfer of genes for edible seaweed digestion from marine to human gut bacteria. bioRxiv. 2020. https://doi.org/10.1101/2020.06.09.142968 .
Scheline RR Metabolism of higher terpenoids. CRC Handbook of Mammalian Metabolism of Plant Compounds. CRC Press; 1991. pp 197–241.
Saha JR, Butler VP Jr, Neu HC, Lindenbaum J. Digoxin-inactivating bacteria: identification in human gut flora. Science. 1983;220:325–7.
pubmed: 6836275
doi: 10.1126/science.6836275
Koppel N, Bisanz JE, Pandelia M-E, Turnbaugh PJ, Balskus EP. Discovery and characterization of a prevalent human gut bacterial enzyme sufficient for the inactivation of a family of plant toxins. Elife. 2018;7:e33953.
pubmed: 29761785
pmcid: 5953540
doi: 10.7554/eLife.33953
Louis P, Flint HJ. Formation of propionate and butyrate by the human colonic microbiota. Environ Microbiol. 2017;19:29–41.
pubmed: 27928878
doi: 10.1111/1462-2920.13589
Ridlon JM, Kang DJ, Hylemon PB, Bajaj JS. Bile acids and the gut microbiome. Curr Opin Gastroenterol. 2014;30:332–8.
pubmed: 24625896
pmcid: 4215539
doi: 10.1097/MOG.0000000000000057
Begley M, Gahan CGM, Hill C. The interaction between bacteria and bile. FEMS Microbiol Rev. 2005;29:625–51.
pubmed: 16102595
doi: 10.1016/j.femsre.2004.09.003
Lee M-T, Le HH, Johnson EL. Dietary sphinganine is selectively assimilated by members of the mammalian gut microbiome. J Lipid Res. 2021;62:100034.
pubmed: 32646940
pmcid: 7910519
doi: 10.1194/jlr.RA120000950
Johnson EL, Heaver SL, Waters JL, Kim BI, Bretin A, Goodman AL, et al. Sphingolipids produced by gut bacteria enter host metabolic pathways impacting ceramide levels. Nat Commun. 2020;11:2471.
pubmed: 32424203
pmcid: 7235224
doi: 10.1038/s41467-020-16274-w