Turroni F, van Sinderen D, Ventura M. Genomics and ecological overview of the genus Bifidobacterium. Int J Food Microbiol. 2011;149:37–44.
Google Scholar
O’Callaghan A, van Sinderen D. Bifidobacteria and their role as members of the human gut microbiota. Front Microbiol. 2016;7:925.
Google Scholar
Ferrario C, Milani C, Mancabelli L, Lugli GA, Duranti S, Mangifesta M, et al. Modulation of the eps-ome transcription of bifidobacteria through simulation of human intestinal environment. FEMS Microbiol Ecol. 2016;92:fiw056.
Google Scholar
Sayers EW, Beck J, Brister JR, Bolton EE, Canese K, Comeau DC, et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2020;48:D9–D16.
Google Scholar
Bottacini F, Medini D, Pavesi A, Turroni F, Foroni E, Riley D, et al. Comparative genomics of the genus Bifidobacterium. Microbiology. 2010;156:3243–54.
Google Scholar
Turroni F, Duranti S, Bottacini F, Guglielmetti S, Van Sinderen D, Ventura M. Bifidobacterium bifidum as an example of a specialized human gut commensal. Front Microbiol. 2014;5:437.
Google Scholar
Bottacini F, Motherway MO, Kuczynski J, O’Connell KJ, Serafini F, Duranti S, et al. Comparative genomics of the Bifidobacterium breve taxon. BMC Genomics. 2014;15:170.
Google Scholar
Milani C, Lugli GA, Duranti S, Turroni F, Bottacini F, Mangifesta M, et al. Genomic encyclopedia of type strains of the genus Bifidobacterium. Appl Environ Microbiol. 2014;80:6290–302.
Google Scholar
Milani C, Lugli GA, Duranti S, Turroni F, Mancabelli L, Ferrario C, et al. Bifidobacteria exhibit social behavior through carbohydrate resource sharing in the gut. Sci Rep. 2015;5:15782.
Google Scholar
Milani C, Turroni F, Duranti S, Lugli GA, Mancabelli L, Ferrario C, et al. Genomics of the genus Bifidobacterium reveals species-specific adaptation to the glycan-rich gut environment. Appl Environ Microbiol. 2016;82:980–91.
Google Scholar
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.
Google Scholar
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.
Google Scholar
Gaulke CA, Arnold HK, Humphreys IR, Kembel SW, O’Dwyer JP, Sharpton TJ. Ecophylogenetics clarifies the evolutionary association between mammals and their gut microbiota. mBio. 2018;9:e01348–18.
Google Scholar
Youngblut ND, Reischer GH, Walters W, Schuster N, Walzer C, Stalder G, et al. Host diet and evolutionary history explain different aspects of gut microbiome diversity among vertebrate clades. Nat Commun. 2019;10:2200.
Google Scholar
Lozupone CA, Hamady M, Cantarel BL, Coutinho PM, Henrissat B, Gordon JI, et al. The convergence of carbohydrate active gene repertoires in human gut microbes. Proc Natl Acad Sci USA. 2008;105:15076–81.
Google Scholar
Makarova K, Slesarev A, Wolf Y, Sorokin A, Mirkin B, Koonin E, et al. Comparative genomics of the lactic acid bacteria. Proc Natl Acad Sci USA. 2006;103:15611–6.
Google Scholar
Moeller AH, Suzuki TA, Phifer-Rixey M, Nachman MW. Transmission modes of the mammalian gut microbiota. Science. 2018;362:453–7.
Google Scholar
Browne HP, Almeida A, Kumar N, Vervier K, Adoum AT, Viciani E, et al. Host adaptation in gut Firmicutes is associated with sporulation loss and altered colonisation patterns. 2020. https://www.biorxiv.org/content/10.1101/2020.09.09.289504v1.
Muegge BD, Kuczynski J, Knights D, Clemente JC, Gonzalez A, Fontana L, et al. Diet drives convergence in gut microbiome functions across mammalian phylogeny and within humans. Science. 2011;332:970–4.
Google Scholar
Suzuki TA. Links between natural variation in the microbiome and host fitness in wild mammals. Integr Comp Biol. 2017;57:756–69.
Google Scholar
McFall-Ngai M, Hadfield MG, Bosch TC, Carey HV, Domazet-Loso T, Douglas AE, et al. Animals in a bacterial world, a new imperative for the life sciences. Proc Natl Acad Sci USA. 2013;110:3229–36.
Google Scholar
Lugli GA, Alessandri G, Milani C, Mancabelli L, Ruiz L, Fontana F, et al. Evolutionary development and co-phylogeny of primate-associated bifidobacteria. Environ Microbiol. 2020;22:3375–93.
Google Scholar
Lugli GA, Mancino W, Milani C, Duranti S, Mancabelli L, Napoli S, et al. Dissecting the evolutionary development of the species Bifidobacterium animalis through comparative genomics analyses. Appl Environ Microbiol. 2019;85:e02806–18.
Google Scholar
Lugli GA, Duranti S, Albert K, Mancabelli L, Napoli S, Viappiani A, et al. Unveiling genomic diversity among members of the species Bifidobacterium pseudolongum, a widely distributed gut commensal of the animal kingdom. Appl Environ Microbiol. 2019;85:e03065–18.
Google Scholar
Milani C, Mangifesta M, Mancabelli L, Lugli GA, James K, Duranti S, et al. Unveiling bifidobacterial biogeography across the mammalian branch of the tree of life. ISME J. 2017;11:2834–47.
Google Scholar
Foster KR, Schluter J, Coyte KZ, Rakoff-Nahoum S. The evolution of the host microbiome as an ecosystem on a leash. Nature. 2017;548:43–51.
Google Scholar
van Vliet S, Doebeli M. The role of multilevel selection in host microbiome evolution. Proc Natl Acad Sci USA. 2019;116:20591–7.
Google Scholar
Groussin M, Mazel F, Alm EJ. Co-evolution and co-speciation of host-gut bacteria systems. Cell Host Microbe. 2020;28:12–22.
Google Scholar
Olm MR, Brown CT, Brooks B, Firek B, Baker R, Burstein D, et al. Identical bacterial populations colonize premature infant gut, skin, and oral microbiomes and exhibit different in situ growth rates. Genome Res. 2017;27:601–12.
Google Scholar
Duranti S, Lugli GA, Napoli S, Anzalone R, Milani C, Mancabelli L, et al. Characterization of the phylogenetic diversity of five novel species belonging to the genus Bifidobacterium: Bifidobacterium castoris sp. nov., Bifidobacterium callimiconis sp. nov., Bifidobacterium goeldii sp. nov., Bifidobacterium samirii sp. nov. and Bifidobacterium dolichotidis sp. nov. Int J Syst Evol Microbiol. 2019;69:1288–98.
Google Scholar
Lugli GA, Milani C, Duranti S, Mancabelli L, Mangifesta M, Turroni F, et al. Tracking the taxonomy of the genus Bifidobacterium based on a phylogenomic approach. Appl Environ Microbiol. 2017;84:e02249–17.
Snel B, Bork P, Huynen MA. Genome phylogeny based on gene content. Nat Genet. 1999;21:108–10.
Google Scholar
Dutilh BE, Huynen MA, Bruno WJ, Snel B. The consistent phylogenetic signal in genome trees revealed by reducing the impact of noise. J Mol Evol. 2004;58:527–39.
Google Scholar
Legendre P, Desdevises Y, Bazin E. A statistical test for host-parasite coevolution. Syst Biol. 2002;51:217–34.
Google Scholar
Michaux JR, Chevret P, Filippucci MG, Macholan M. Phylogeny of the genus Apodemus with a special emphasis on the subgenus Sylvaemus using the nuclear IRBP gene and two mitochondrial markers: cytochrome b and 12S rRNA. Mol Phylogenet Evol. 2002;23:123–36.
Google Scholar
Lawson MAE, O’Neill IJ, Kujawska M, Gowrinadh Javvadi S, Wijeyesekera A, Flegg Z, et al. Breast milk-derived human milk oligosaccharides promote Bifidobacterium interactions within a single ecosystem. ISME J. 2020;14:635–48.
Google Scholar
Van Den Broek LAM, Voragen AGJ. Bifidobacterium glycoside hydrolases and (potential) prebiotics. Innov Food Sci Emerg Technol 2008;9:401–7.
Pokusaeva K, Fitzgerald GF, van Sinderen D. Carbohydrate metabolism in Bifidobacteria. Genes Nutr. 2011;6:285–306.
Google Scholar
Rodriguez CI, Martiny JBH. Evolutionary relationships among bifidobacteria and their hosts and environments. BMC Genomics. 2020;21:26.
Google Scholar
Henrissat B, Davies GJ. Glycoside hydrolases and glycosyltransferases. Families, modules, and implications for genomics. Plant Physiol. 2000;124:1515–9.
Google Scholar
Stam MR, Danchin EG, Rancurel C, Coutinho PM, Henrissat B. Dividing the large glycoside hydrolase family 13 into subfamilies: towards improved functional annotations of alpha-amylase-related proteins. Protein Eng Des Sel. 2006;19:555–62.
Google Scholar
Miyazaki T, Ishizaki Y, Ichikawa M, Nishikawa A, Tonozuka T. Structural and biochemical characterization of novel bacterial alpha-galactosidases belonging to glycoside hydrolase family 31. Biochem J. 2015;469:145–58.
Google Scholar
Hachem MA, Fredslund F, Andersen JM, Jonsgaard Larsen R, Majumder A, Ejby M, et al. Raffinose family oligosaccharide utilisation by probiotic bacteria: insight into substrate recognition, molecular architecture and diversity of GH36 α-galactosidases. Biocatal Biotransform. 2012;30:316–25.
Google Scholar
Kujawska M, La Rosa SL, Roger LC, Pope PB, Hoyles L, McCartney AL, et al. Succession of Bifidobacterium longum strains in response to a changing early life nutritional environment reveals dietary substrate adaptations. iScience. 2020;23:101368.
Google Scholar
Liu H, Ren W, Ly M, Li H, Wang S. Characterization of an alkaline GH49 dextranase from marine bacterium Arthrobacter oxydans KQ11 and its application in the preparation of isomalto-oligosaccharide. Mar Drugs. 2019;17:479.
Google Scholar
Michlmayr H, Hell J, Lorenz C, Bohmdorfer S, Rosenau T, Kneifel W. Arabinoxylan oligosaccharide hydrolysis by family 43 and 51 glycosidases from Lactobacillus brevis DSM 20054. Appl Environ Microbiol. 2013;79:6747–54.
Google Scholar
Fujita K, Takashi Y, Obuchi E, Kitahara K, Suganuma T. Characterization of a novel beta-l-arabinofuranosidase in Bifidobacterium longum: functional elucidation of a DUF1680 protein family member. J Biol Chem. 2014;289:5240–9.
Google Scholar
Viens P, Lacombe-Harvey ME, Brzezinski R. Chitosanases from Family 46 of glycoside hydrolases: from proteins to phenotypes. Mar Drugs. 2015;13:6566–87.
Google Scholar
Sela DA, Garrido D, Lerno L, Wu S, Tan K, Eom HJ, et al. Bifidobacterium longum subsp. infantis ATCC 15697 alpha-fucosidases are active on fucosylated human milk oligosaccharides. Appl Environ Microbiol. 2012;78:795–803.
Google Scholar
Garrido D, Ruiz-Moyano S, Kirmiz N, Davis JC, Totten SM, Lemay DG, et al. A novel gene cluster allows preferential utilization of fucosylated milk oligosaccharides in Bifidobacterium longum subsp longum SC596. Sci Rep-Uk. 2016;6:35045.
Google Scholar
Kitaoka M. Bifidobacterial enzymes involved in the metabolism of human milk oligosaccharides. Adv Nutr. 2012;3:422S–9S.
Google Scholar
Kiyohara M, Tanigawa K, Chaiwangsri T, Katayama T, Ashida H, Yamamoto K. An exo-alpha-sialidase from bifidobacteria involved in the degradation of sialyloligosaccharides in human milk and intestinal glycoconjugates. Glycobiology. 2011;21:437–47.
Google Scholar
Breton C, Snajdrova L, Jeanneau C, Koca J, Imberty A. Structures and mechanisms of glycosyltransferases. Glycobiology. 2006;16:29R–37R.
Google Scholar
Hidalgo-Cantabrana C, Sanchez B, Milani C, Ventura M, Margolles A, Ruas-Madiedo P. Genomic overview and biological functions of exopolysaccharide biosynthesis in Bifidobacterium spp. Appl Environ Microbiol. 2014;80:9–18.
Google Scholar
Cantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V, Henrissat B. The carbohydrate-active EnZymes database (CAZy): an expert resource for Glycogenomics. Nucleic Acids Res. 2009;37:D233–8.
Google Scholar
Lavrinienko A, Tukalenko E, Mousseau TA, Thompson LR, Knight R, Mappes T, et al. Two hundred and fifty-four metagenome-assembled bacterial genomes from the bank vole gut microbiota. Sci Data. 2020;7:312.
Google Scholar
Baumler A, Fang FC. Host specificity of bacterial pathogens. Cold Spring Harb Perspect Med. 2013;3:a010041.
Google Scholar
Glazko GV, Nei M. Estimation of divergence times for major lineages of primate species. Mol Biol Evol. 2003;20:424–34.
Google Scholar
Milton K. The critical role played by animal source foods in human (Homo) evolution. J Nutr. 2003;133:3886S–92S.
Google Scholar
Renaud S, Michaux J, Schmidt DN, Aguilar JP, Mein P, Auffray JC. Morphological evolution, ecological diversification and climate change in rodents. Proc Biol Sci. 2005;272:609–17.
Google Scholar
Michaux JR, Libois R, Filipucci M-G. So close and so different: comparative phylogeography of two small mammal species, the Yellow-necked fieldmouse (Apodemus flavicollis) and the Woodmouse (Apodemus sylvaticus) in the Western Palearctic region. Heredity. 2005;94:52–63.
Google Scholar
Ge D, Feijó A, Cheng J, Lu L, Liu R, Abramov AV, et al. Evolutionary history of field mice (Murinae: Apodemus), with emphasis on morphological variation among species in China and description of a new species. Zool J Linn Soc. 2019;187:5188–534.
Moeller AH, Peeters M, Ndjango JB, Li Y, Hahn BH, Ochman H. Sympatric chimpanzees and gorillas harbor convergent gut microbial communities. Genome Res. 2013;23:1715–20.
Google Scholar
Knowles SCL, Eccles RM, Baltrunaite L. Species identity dominates over environment in shaping the microbiota of small mammals. Ecol Lett. 2019;22:826–37.
Google Scholar
Watts CHS. The foods eaten by wood mice (Apodemus sylvaticus) and bank voles (Clethrionomys glareolus) in Wytham Woods, Berkshire. J Anim Ecol. 1968;37:25–41.
Abt KF, Bock WF. Seasonal variations of diet composition in farmland field mice Apodemus spp. and bank voles Clethrionomys glareolus. Acta Theriol. 1998;43:379–89.
Rogers LM, Gorman ML. The diet of the wood mouse Apodemus sylvaticus on set‐aside land. J Zool. 1995;235:77–83.
Van Laere KM, Beldman G, Voragen AG. A new arabinofuranohydrolase from Bifidobacterium adolescentis able to remove arabinosyl residues from double-substituted xylose units in arabinoxylan. Appl Microbiol Biotechnol. 1997;47:231–5.
Google Scholar
Margolles A, de los Reyes-Gavilan CG. Purification and functional characterization of a novel alpha-L-arabinofuranosidase from Bifidobacterium longum B667. Appl Environ Microbiol. 2003;69:5096–103.
Google Scholar
Lagaert S, Pollet A, Delcour JA, Lavigne R, Courtin CM, Volckaert G. Substrate specificity of three recombinant alpha-L-arabinofuranosidases from Bifidobacterium adolescentis and their divergent action on arabinoxylan and arabinoxylan oligosaccharides. Biochem Biophys Res Commun. 2010;402:644–50.
Google Scholar
Ito T, Saikawa K, Kim S, Fujita K, Ishiwata A, Kaeothip S, et al. Crystal structure of glycoside hydrolase family 127 beta-l-arabinofuranosidase from Bifidobacterium longum. Biochem Biophys Res Commun. 2014;447:32–7.
Google Scholar
Kataržytė M, Kutorga E. Small mammal mycophagy in hemiboreal forest communities of Lithuania. Central Eur J Biol. 2011;6:446–56.
Lee HW, Park YS, Jung JS, Shin WS. Chitosan oligosaccharides, dp 2-8, have prebiotic effect on the Bifidobacterium bifidium and Lactobacillus sp. Anaerobe. 2002;8:319–24.
Google Scholar
Vernazza CL, Gibson GR, Rastall RA. In vitro fermentation of chitosan derivatives by mixed cultures of human faecal bacteria. Carbohyd Polym. 2005;60:539–45.
Google Scholar
Yang CM, Ferket PR, Hong QH, Zhou J, Cao GT, Zhou L, et al. Effect of chito-oligosaccharide on growth performance, intestinal barrier function, intestinal morphology and cecal microflora in weaned pigs. J Anim Sci. 2012;90:2671–6.
Google Scholar
Zhang C, Jiao S, Wang ZA, Du Y. Exploring effects of chitosan oligosaccharides on mice gut microbiota in in vitro fermentation and animal model. Front Microbiol. 2018;9:2388.
Google Scholar
Wu J, Zhang L. Dissolution behavior and conformation change of chitosan in concentrated chitosan hydrochloric acid solution and comparison with dilute and semidilute solutions. Int J Biol Macromol. 2019;121:1101–8.
Google Scholar
Costa CN, Teixeira VG, Delpech MC, Souza JV, Costa MA. Viscometric study of chitosan solutions in acetic acid/sodium acetate and acetic acid/sodium chloride. Carbohydr Polym. 2015;133:245–50.
Google Scholar
Kiu R, Treveil A, Harnisch LC, Caim S, Leclaire C, van Sinderen D, et al. Bifidobacterium breve UCC2003 induces a distinct global transcriptomic program in neonatal murine intestinal epithelial cells. iScience. 2020;23:101336.
Google Scholar
Hughes KR, Harnisch LC, Alcon-Giner C, Mitra S, Wright CJ, Ketskemety J, et al. Bifidobacterium breve reduces apoptotic epithelial cell shedding in an exopolysaccharide and MyD88-dependent manner. Open Biol. 2017;7:160155.
Fanning S, Hall LJ, Cronin M, Zomer A, MacSharry J, Goulding D, et al. Bifidobacterial surface-exopolysaccharide facilitates commensal-host interaction through immune modulation and pathogen protection. Proc Natl Acad Sci USA. 2012;109:2108–13.
Google Scholar
Roca C, Alves VD, Freitas F, Reis MA. Exopolysaccharides enriched in rare sugars: bacterial sources, production, and applications. Front Microbiol. 2015;6:288.
Google Scholar
Balzaretti S, Taverniti V, Guglielmetti S, Fiore W, Minuzzo M, Ngo HN, et al. A novel rhamnose-rich hetero-exopolysaccharide isolated from Lactobacillus paracasei DG activates THP-1 human monocytic cells. Appl Environ Microbiol. 2017;83:e02702–16.
Google Scholar
Stradiotto A, Cagnacci F, Delahay R, Tioli S, Nieder L, Rizzoli A. Spatial organization of the yellow-necked mouse: effects of density and resource availability. J Mammal. 2009;90:704–14.
Wood DE, Salzberg SL. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol. 2014;15:R46.
Google Scholar
Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34:i884–i90.
Google Scholar
Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19:455–77.
Google Scholar
Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068–9.
Google Scholar
Eren AM, Esen OC, Quince C, Vineis JH, Morrison HG, Sogin ML, et al. Anvi’o: an advanced analysis and visualization platform for ‘omics data. PeerJ. 2015;3:e1319.
Google Scholar
Capella-Gutierrez S, Silla-Martinez JM, Gabaldon T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics. 2009;25:1972–3.
Google Scholar
Nguyen LT, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32:268–74.
Google Scholar
Whelan S, Goldman N. A general empirical model of protein evolution derived from multiple protein families using a maximum-likelihood approach. Mol Biol Evol. 2001;18:691–9.
Google Scholar
Paradis E, Schliep K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics. 2019;35:526–8.
Google Scholar
Pritchard L, Glover RH, Humphris S, Elphinstone JG, Toth IK. Genomics and taxonomy in diagnostics for food security: soft-rotting enterobacterial plant pathogens. Anal Methods. 2016;8:12–24.
Chun J, Oren A, Ventosa A, Christensen H, Arahal DR, da Costa MS, et al. Proposed minimal standards for the use of genome data for the taxonomy of prokaryotes. Int J Syst Evol Microbiol. 2018;68:461–6.
Google Scholar
Huerta-Cepas J, Forslund K, Coelho LP, Szklarczyk D, Jensen LJ, von Mering C, et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Mol Biol Evol. 2017;34:2115–22.
Google Scholar
Zhang H, Yohe T, Huang L, Entwistle S, Wu P, Yang Z, et al. dbCAN2: a meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 2018;46:W95–W101.
Google Scholar
Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGillin D, et al. vegan: community ecology package. R package version 25-6. 2019. https://CRAN.R-project.org/package=vegan.
De Caceres M, Legendre P, Moretti M. Improving indicator species analysis by combining groups of sites. Oikos. 2010;119:1674–84.
Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: architecture and applications. BMC Bioinformatics. 2009;10:421.
Google Scholar
Waack S, Keller O, Asper R, Brodag T, Damm C, Fricke WF, et al. Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models. BMC Bioinformatics. 2006;7:142.
Google Scholar
Bertelli C, Laird MR, Williams KP, Lau BY, Hoad G, Winsor GL, et al. IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets. Nucleic Acids Res. 2017;45:W30–W5.
Google Scholar
Source: Ecology - nature.com