Polysaccharide source altered ecological network, functional profile, and short-chain fatty acid production in a porcine gut microbiota
äºBeneficial MicrobesSearch for other papers by C. Long in
Current site
Google Scholar
Search for other papers by S. de Vries in
Current site
Google Scholar
Search for other papers by K. Venema in
Current site
Google Scholar
Several validated dynamic in vitro models of the colon have been developed for humans, but there is no dynamic in vitro fermentation model for pigs. This study was conducted to modify the human, dynamic, computer-controlled TNO in vitro model of the colon (TIM-2) for pigs and investigate effects of different starch sources and polysaccharides on swine microbiota structure, ecological network, predictive functional profile, and short-chain fatty acids production. Our study showed that three different types of starch or two polysaccharides greatly impacted microbiota composition. Co-occurrence network analysis indicated that microbiota fed with different sources of starch changed the network topological properties. Functional profiles were predicted to vary significantly among the three starch treatments, and the original pig faecal inoculum was more similar to maize starch treatment. On the other hand, compared with maize starch and arabinoxylans (AX), the microbial composition of the original inoculum was more similar when AX-XG (arabinoxylans and xyloglucan) were added, and the functional profile of the original inoculum also clustered with AX-XG. The cumulative production of acetic, propionic, and butyric acid on maize starch were significantly higher than those on potato starch and wheat starch, while only the amount of acetic acid was significant higher on AX-XG than that on AX. In conclusion, supplementation of maize starch as the starch source together with AX and XG, leads to the bacteria being more stable in the in vitro model and closer to the original inoculum and microbial function compared to potato starch, wheat starch and AX. A maize basal diet may improve energy absorption in the large intestine in growing pigs.
-
Adami, A. and Cavazzoni, V., 1999. Occurrence of selected bacterial groups in the faeces of piglets fed with Bacillus coagulans as probiotic. Journal of Basic Microbiology 39: 3-9.
'Occurrence of selected bacterial groups in the faeces of piglets fed with Bacillus coagulans as probiotic ' () 39 Journal of Basic Microbiology : 3 -9.
-
Aguirre, M., de Souza, C.B. and Venema, K., 2016. The gut microbiota from lean and obese subjects contribute differently to the fermentation of arabinogalactan and inulin. PLoS ONE 11: e0159236.
'The gut microbiota from lean and obese subjects contribute differently to the fermentation of arabinogalactan and inulin ' () 11 PLoS ONE : e0159236.
-
Aguirre, M., Jonkers, D.M., Troost, F.J., Roeselers, G. and Venema, K., 2014. In vitro characterization of the impact of different substrates on metabolite production, energy extraction and composition of gut microbiota from lean and obese subjects. PLoS ONE 9: e113864. https://doi.org/10.1371/journal.pone.0113864
-
Anderson, M.J., 2001. A new method for non-parametric multivariate analysis of variance. Austral Ecology 26: 32-46.
'A new method for non-parametric multivariate analysis of variance ' () 26 Austral Ecology : 32 -46.
-
Assenov, Y., RamÃrez, F., Schelhorn, S.-E., Lengauer, T. and Albrecht, M., 2007. Computing topological parameters of biological networks. Bioinformatics 24: 282-284.
'Computing topological parameters of biological networks ' () 24 Bioinformatics : 282 -284.
-
Bader, G.D. and Hogue, C.W., 2003. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics 4: 2.
'An automated method for finding molecular complexes in large protein interaction networks ' () 4 BMC Bioinformatics : 2.
-
Barroso, E., Cueva, C., Peláez, C. and Carmen, M., 2015a. The computer-controlled multicompartmental dynamic model of the gastrointestinal system SIMGI. In: Verhoeckx, K. Cotter, P., López-Expósito, I., Kleiveland, C., Lea, T. and Mackie, A. (eds.) The impact of food bioactives on health â in vitro and ex vivo models. Springer, Heidelberg, Germany, pp. 319-327.
'The computer-controlled multicompartmental dynamic model of the gastrointestinal system SIMGI ', () 319 -327.
-
Barroso, E., Cueva, C., Peláez, C., MartÃnez-Cuesta, M.C. and Requena, T., 2015b. Development of human colonic microbiota in the computer-controlled dynamic SIMulator of the GastroIntestinal tract SIMGI. LWT â Food Science and Technology 61: 283-289.
'Development of human colonic microbiota in the computer-controlled dynamic SIMulator of the GastroIntestinal tract SIMGI ' () 61 LWT â Food Science and Technology : 283 -289.
-
Barry, J., Hoebler, C., Macfarlane, G., MacFarlane, S., Mathers, J., Reed, K., Mortensen, P., Nordgaard, I., Rowland, I. and Rumney, C., 1995. Estimation of the fermentability of dietary fibre in vitro: a European interlaboratory study. British Journal of Nutrition 74: 303-322.
'Estimation of the fermentability of dietary fibre in vitro: a European interlaboratory study ' () 74 British Journal of Nutrition : 303 -322.
-
Belobrajdic, D.P., Bird, A.R., Conlon, M.A., Williams, B.A., Kang, S., McSweeney, C.S., Zhang, D., Bryden, W.L., Gidley, M.J. and Topping, D.L., 2012. An arabinoxylan-rich fraction from wheat enhances caecal fermentation and protects colonocyte DNA against diet-induced damage in pigs. British Journal of Nutrition 107: 1274-1282.
'An arabinoxylan-rich fraction from wheat enhances caecal fermentation and protects colonocyte DNA against diet-induced damage in pigs ' () 107 British Journal of Nutrition : 1274 -1282.
-
Bokulich, N.A., Kaehler, B.D., Rideout, J.R., Dillon, M., Bolyen, E., Knight, R., Huttley, G.A. and Gregory Caporaso, J., 2018. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2âs q2-feature-classifier plugin. Microbiome 6: 90. https://doi.org/10.1186/s40168-018-0470-z
-
Brouns, F., Arrigoni, E., Langkilde, A.M., Verkooijen, I., Fässler, C., Andersson, H., Kettlitz, B., van Nieuwenhoven, M., Philipsson, H. and Amadò, R., 2007. Physiological and metabolic properties of a digestion-resistant maltodextrin, classified as type 3 retrograded resistant starch. Journal of Agricultural and Food Chemistry 55: 1574-1581. https://doi.org/10.1021/jf062057w
-
Callahan, B.J., McMurdie, P.J., Rosen, M.J., Han, A.W., Johnson, A.J.A. and Holmes, S.P., 2016. DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods 13: 581. https://doi.org/10.1038/nmeth.3869
-
Cantu-Jungles, T.M., do Nascimento, G.E., Zhang, X., Iacomini, M., Cordeiro, L.M. and Hamaker, B.R., 2019. Soluble xyloglucan generates bigger bacterial community shifts than pectic polymers during in vitro fecal fermentation. Carbohydrate Polymers 206: 389-395.
'Soluble xyloglucan generates bigger bacterial community shifts than pectic polymers during in vitro fecal fermentation ' () 206 Carbohydrate Polymers : 389 -395.
-
Cohen, R. and Havlin, S., 2010. Complex networks: structure, robustness and function. Cambridge university press.
'Complex networks: structure, robustness and function', ().
-
Costa, M.O., Chaban, B., Harding, J.C.S. and Hill, J.E., 2014. Characterization of the fecal microbiota of pigs before and after inoculation with âBrachyspira hampsoniiâ. PLoS One 9: e106399.
'Characterization of the fecal microbiota of pigs before and after inoculation with âBrachyspira hampsoniiâ ' () 9 PLoS One : e106399.
-
David, L.A., Maurice, C.F., Carmody, R.N., Gootenberg, D.B., Button, J.E., Wolfe, B.E., Ling, A.V., Devlin, A.S., Varma, Y., Fischbach, M.A., Biddinger, S.B., Dutton, R.J. and Turnbaugh, P.J., 2014. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505: 559-563. https://doi.org/10.1038/nature12820
-
De Menezes, A.B., Lewis, E., OâDonovan, M., OâNeill, B.F., Clipson, N. and Doyle, E.M., 2011. Microbiome analysis of dairy cows fed pasture or total mixed ration diets. FEMS Microbiology Ecology 78: 256-265.
'Microbiome analysis of dairy cows fed pasture or total mixed ration diets ' () 78 FEMS Microbiology Ecology : 256 -265.
-
De Souza, C.B., Roeselers, G., Troost, F., Jonkers, D., Koenen, M. and Venema, K., 2014. Prebiotic effects of cassava bagasse in TNOâs in vitro model of the colon in lean versus obese microbiota. Journal of Functional Foods 11: 210-220.
'Prebiotic effects of cassava bagasse in TNOâs in vitro model of the colon in lean versus obese microbiota ' () 11 Journal of Functional Foods : 210 -220.
-
Duncan, S.H., Belenguer, A., Holtrop, G., Johnstone, A.M., Flint, H.J. and Lobley, G.E., 2007. Reduced dietary intake of carbohydrates by obese subjects results in decreased concentrations of butyrate and butyrate-producing bacteria in feces. Applied Environmental Microbiology 73: 1073-1078. https://doi.org/10.1128/AEM.02340-06
-
Emerson, E.L. and Weimer, P.J., 2017. Fermentation of model hemicelluloses by Prevotella strains and Butyrivibrio fibrisolvens in pure culture and in ruminal enrichment cultures. Applied Microbiology and Biotechnology 101: 4269-4278.
'Fermentation of model hemicelluloses by Prevotella strains and Butyrivibrio fibrisolvens in pure culture and in ruminal enrichment cultures ' () 101 Applied Microbiology and Biotechnology : 4269 -4278.
-
Faust, K. and Raes, J., 2012. Microbial interactions: from networks to models. Nature Reviews Microbiology 10: 538. https://doi.org/10.1038/nrmicro2832
-
Faust, K., Sathirapongsasuti, J.F., Izard, J., Segata, N., Gevers, D., Raes, J. and Huttenhower, C., 2012. Microbial co-occurrence relationships in the human microbiome. PLoS Computational Biology 8: e1002606.
'Microbial co-occurrence relationships in the human microbiome ' () 8 PLoS Computational Biology : e1002606.
-
Gaenzle, M.G., 2015. Lactic metabolism revisited: metabolism of lactic acid bacteria in food fermentations and food spoilage. Current Opinion in Food Science 2: 106-117.
'Lactic metabolism revisited: metabolism of lactic acid bacteria in food fermentations and food spoilage ' () 2 Current Opinion in Food Science : 106 -117.
-
Gao, K., Xu, A., Krul, C., Venema, K., Liu, Y., Niu, Y., Lu, J., Bensoussan, L., Seeram, N.P. and Heber, D., 2006. Of the major phenolic acids formed during human microbial fermentation of tea, citrus, and soy flavonoid supplements, only 3, 4-dihydroxyphenylacetic acid has antiproliferative activity. Journal of Nutrition 136: 52-57.
'Of the major phenolic acids formed during human microbial fermentation of tea, citrus, and soy flavonoid supplements, only 3, 4-dihydroxyphenylacetic acid has antiproliferative activity ' () 136 Journal of Nutrition : 52 -57.
-
Gibson, G.R., Cummings, J.H. and Macfarlane, G.T., 1988. Use of a three-stage continuous culture system to study the effect of mucin on dissimilatory sulfate reduction and methanogenesis by mixed populations of human gut bacteria. Applied and Environmental Microbiology 54: 2750-2755.
'Use of a three-stage continuous culture system to study the effect of mucin on dissimilatory sulfate reduction and methanogenesis by mixed populations of human gut bacteria ' () 54 Applied and Environmental Microbiology : 2750 -2755.
-
Gomez, K.A. and Gomez, A.A., 1984. Statistical procedures for agricultural research. John Wiley & Sons, Hoboken, NJ, USA.
'Statistical procedures for agricultural research', ().
-
Hopkins, M.J., Englyst, H.N., Macfarlane, S., Furrie, E., Macfarlane, G.T. and McBain, A.J., 2003. Degradation of cross-linked and non-cross-linked arabinoxylans by the intestinal microbiota in children. Applied and Environmental Microbiology 69: 6354-6360.
'Degradation of cross-linked and non-cross-linked arabinoxylans by the intestinal microbiota in children ' () 69 Applied and Environmental Microbiology : 6354 -6360.
-
Jackson, P.G. and Cockcroft, P.D., 2007. Handbook of pig medicine. Elsevier Health Sciences.
'Handbook of pig medicine', ().
-
Jami, E. and Mizrahi, I., 2012. Composition and similarity of bovine rumen microbiota across individual animals. PLoS ONE 7: e33306.
'Composition and similarity of bovine rumen microbiota across individual animals ' () 7 PLoS ONE : e33306.
-
Klindworth, A., Pruesse, E., Schweer, T., Peplies, J., Quast, C., Horn, M. and Glöckner, F.O., 2013. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Research 41: e1. https://doi.org/10.1093/nar/gks808
-
Kovatcheva-Datchary, P., Egert, M., Maathuis, A., RajiliÄ-StojanoviÄ, M., De Graaf, A.A., Smidt, H., De Vos, W.M. and Venema, K., 2009. Linking phylogenetic identities of bacteria to starch fermentation in an in vitro model of the large intestine by RNA-based stable isotope probing. Environmental Microbiology 11: 914-926.
'Linking phylogenetic identities of bacteria to starch fermentation in an in vitro model of the large intestine by RNA-based stable isotope probing ' () 11 Environmental Microbiology : 914 -926.
-
Kraler, M., Ghanbari, M., Domig, K.J., Schedle, K. and Kneifel, W., 2016. The intestinal microbiota of piglets fed with wheat bran variants as characterised by 16S rRNA next-generation amplicon sequencing. Archives of Animal Nutrition 70: 173-189.
'The intestinal microbiota of piglets fed with wheat bran variants as characterised by 16S rRNA next-generation amplicon sequencing ' () 70 Archives of Animal Nutrition : 173 -189.
-
Langille, M.G., Zaneveld, J., Caporaso, J.G., McDonald, D., Knights, D., Reyes, J.A., Clemente, J.C., Burkepile, D.E., Thurber, R.L.V. and Knight, R., 2013. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature Biotechnology 31: 814.
'Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences ' () 31 Nature Biotechnology : 814.
-
Larsbrink, J., Rogers, T.E., Hemsworth, G.R., McKee, L.S., Tauzin, A.S., Spadiut, O., Klinter, S., Pudlo, N.A., Urs, K. and Koropatkin, N.M., 2014. A discrete genetic locus confers xyloglucan metabolism in select human gut Bacteroidetes. Nature 506: 498.
'A discrete genetic locus confers xyloglucan metabolism in select human gut Bacteroidetes ' () 506 Nature : 498.
-
Louca, S., Jacques, S.M., Pires, A.P., Leal, J.S., Srivastava, D.S., Parfrey, L.W., Farjalla, V.F. and Doebeli, M., 2017. High taxonomic variability despite stable functional structure across microbial communities. Nature Ecology and Evolution 1: 0015.
'High taxonomic variability despite stable functional structure across microbial communities ' () 1 Nature Ecology and Evolution : 0015.
-
Lozupone, C.A., Hamady, M., Kelley, S.T. and Knight, R., 2007. Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities. Applied Environmental Microbiology 73: 1576-1585. https://doi.org/10.1128/AEM.01996-06
-
Lozupone, C.A., Stombaugh, J.I., Gordon, J.I., Jansson, J.K. and Knight, R., 2012. Diversity, stability and resilience of the human gut microbiota. Nature 489: 220.
'Diversity, stability and resilience of the human gut microbiota ' () 489 Nature : 220.
-
Maathuis, A., Hoffman, A., Evans, A., Sanders, L. and Venema, K., 2009. The effect of the undigested fraction of maize products on the activity and composition of the microbiota determined in a dynamic in vitro model of the human proximal large intestine. Journal of the American College of Nutrition 28: 657-666.
'The effect of the undigested fraction of maize products on the activity and composition of the microbiota determined in a dynamic in vitro model of the human proximal large intestine ' () 28 Journal of the American College of Nutrition : 657 -666.
-
Macfarlane, G., Cummings, J., Macfarlane, S. and Gibson, G., 1989. Influence of retention time on degradation of pancreatic enzymes by human colonic bacteria grown in a 3-stage continuous culture system. Journal of Applied Bacteriology 67: 521-527.
'Influence of retention time on degradation of pancreatic enzymes by human colonic bacteria grown in a 3-stage continuous culture system ' () 67 Journal of Applied Bacteriology : 521 -527.
-
Martinez, R.C., Cardarelli, H.R., Borst, W., Albrecht, S., Schols, H., Gutiérrez, O.P., Maathuis, A.J., de Melo Franco, B.D., De Martinis, E.C. and Zoetendal, E.G. 2013. Effect of galactooligosaccharides and Bifidobacterium animalis Bb-12 on growth of Lactobacillus amylovorus DSM 16698, microbial community structure, and metabolite production in an in vitro colonic model set up with human or pig microbiota. FEMS Microbiology Ecology 84: 110-123.
'Effect of galactooligosaccharides and Bifidobacterium animalis Bb-12 on growth of Lactobacillus amylovorus DSM 16698, microbial community structure, and metabolite production in an in vitro colonic model set up with human or pig microbiota ' () 84 FEMS Microbiology Ecology : 110 -123.
-
Minekus, M., Marteau, P., Havenaar, R. and, Huis inât Veld, J., 1995. A multicompartmental dynamic computer-controlled model simulating the stomach and small intestine. Alternatives to Laboratory Animals 23: 197-209.
'A multicompartmental dynamic computer-controlled model simulating the stomach and small intestine ' () 23 Alternatives to Laboratory Animals : 197 -209.
-
Minekus, M., Smeets-Peeters, M., Bernalier, A., Marol-Bonnin, S., Havenaar, R., Marteau, P., Alric, M., Fonty, G. and Huis inât Veld, J., 1999. A computer-controlled system to simulate conditions of the large intestine with peristaltic mixing, water absorption and absorption of fermentation products. Applied Microbiology and Biotechnology 53: 108-114. https://doi.org/10.1007/s002530051622
-
Molly, K., Woestyne, M.V. and Verstraete, W., 1993. Development of a 5-step multi-chamber reactor as a simulation of the human intestinal microbial ecosystem. Applied Microbiology and Biotechnology 39: 254-258.
'Development of a 5-step multi-chamber reactor as a simulation of the human intestinal microbial ecosystem ' () 39 Applied Microbiology and Biotechnology : 254 -258.
-
Neyrinck, A.M., Possemiers, S., Druart, C., Van de Wiele, T., De Backer, F., Cani, P.D., Larondelle, Y. and Delzenne, N.M., 2011. Prebiotic effects of wheat arabinoxylan related to the increase in Bifidobacteria, Roseburia and Bacteroides/Prevotella in diet-induced obese mice. PLoS ONE 6: e20944.
'Prebiotic effects of wheat arabinoxylan related to the increase in Bifidobacteria, Roseburia and Bacteroides/Prevotella in diet-induced obese mice ' () 6 PLoS ONE : e20944.
-
Niu, Q., Li, P., Hao, S., Zhang, Y., Kim, S.W., Li, H., Ma, X., Gao, S., He, L. and Wu, W., 2015. Dynamic distribution of the gut microbiota and the relationship with apparent crude fiber digestibility and growth stages in pigs. Scientific Reports 5: 9938.
'Dynamic distribution of the gut microbiota and the relationship with apparent crude fiber digestibility and growth stages in pigs ' () 5 Scientific Reports : 9938.
-
Ormerod, K.L., Wood, D.L.A., Lachner, N., Gellatly, S.L., Daly, J.N., Parsons, J.D., DalâMolin, C.G.O., Palfreyman, R.W., Nielsen, L.K., Cooper, M.A., Morrison, M., Hansbro, P.M. and Hugenholtz, P., 2016. Genomic characterization of the uncultured Bacteroidales family S24-7 inhabiting the guts of homeothermic animals. Microbiome 4: 36. https://doi.org/10.1186/s40168-016-0181-2
-
Parks, D.H., Tyson, G.W., Hugenholtz, P. and Beiko, R.G., 2014. STAMP: statistical analysis of taxonomic and functional profiles. Bioinformatics 30: 3123-3124.
'STAMP: statistical analysis of taxonomic and functional profiles ' () 30 Bioinformatics : 3123 -3124.
-
Pluske, J. and Hampson, D., 2005. Rice-based diets in pigs: for protection against intestinal bacterial infections: a report for the rural industries research and development corporation. RIRDC Publication No 05/143. Rural Industries Research and Development Corporation, Kingston, Australia. Available at: https://tinyurl.com/y924xxop.
-
Ramayo-Caldas, Y., Mach, N., Lepage, P., Levenez, F., Denis, C., Lemonnier, G., Leplat, J.-J., Billon, Y., Berri, M. and Doré, J., 2016. Phylogenetic network analysis applied to pig gut microbiota identifies an ecosystem structure linked with growth traits. ISME journal 10: 2973.
'Phylogenetic network analysis applied to pig gut microbiota identifies an ecosystem structure linked with growth traits ' () 10 ISME journal : 2973.
-
Rehman, A., Heinsen, F.A., Koenen, M.E., Venema, K., Knecht, H., Hellmig, S., Schreiber, S. and Ott, S.J., 2012. Effects of probiotics and antibiotics on the intestinal homeostasis in a computer controlled model of the large intestine. BMC Microbiology 12: 47. https://doi.org/10.1186/1471-2180-12-47
-
Rose, D.J., Venema, K., Keshavarzian, A. and Hamaker, B.R., 2010. Starch-entrapped microspheres show a beneficial fermentation profile and decrease in potentially harmful bacteria during in vitro fermentation in faecal microbiota obtained from patients with inflammatory bowel disease. British Journal of Nutrition 103: 1514-1524.
'Starch-entrapped microspheres show a beneficial fermentation profile and decrease in potentially harmful bacteria during in vitro fermentation in faecal microbiota obtained from patients with inflammatory bowel disease ' () 103 British Journal of Nutrition : 1514 -1524.
-
Scheller, H.V. and Ulvskov, P., 2010. Hemicelluloses. Annual Review of Plant Biology 61: 263-289. https://doi.org/10.1146/annurev-arplant-042809-112315
-
Seedorf, H., Griffin, N.W., Ridaura, V.K., Reyes, A., Cheng, J., Rey, F.E., Smith, M.I., Simon, G.M., Scheffrahn, R.H. and Woebken, D., 2014. Bacteria from diverse habitats colonize and compete in the mouse gut. Cell 159: 253-266.
'Bacteria from diverse habitats colonize and compete in the mouse gut ' () 159 Cell : 253 -266.
-
Segata, N., Izard, J., Waldron, L., Gevers, D., Miropolsky, L., Garrett, W.S. and Huttenhower, C., 2011. Metagenomic biomarker discovery and explanation. Genome biology 12: R60.
'Metagenomic biomarker discovery and explanation ' () 12 Genome biology : R60.
-
Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B. and Ideker, T., 2003. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome research 13: 2498-2504.
'Cytoscape: a software environment for integrated models of biomolecular interaction networks ' () 13 Genome research : 2498 -2504.
-
Spinosa, M.R., Braccini, T., Ricca, E., De Felice, M., Morelli, L., Pozzi, G. and Oggioni, M.R., 2000. On the fate of ingested Bacillus spores. Research in Microbiology 151: 361-368.
'On the fate of ingested Bacillus spores ' () 151 Research in Microbiology : 361 -368.
-
Stevenson, D.M. and Weimer, P.J., 2007. Dominance of Prevotella and low abundance of classical ruminal bacterial species in the bovine rumen revealed by relative quantification real-time PCR. Applied Microbiology and Biotechnology 75: 165-174.
'Dominance of Prevotella and low abundance of classical ruminal bacterial species in the bovine rumen revealed by relative quantification real-time PCR ' () 75 Applied Microbiology and Biotechnology : 165 -174.
-
Svartström, O., Alneberg, J., Terrapon, N., Lombard, V., de Bruijn, I., Malmsten, J., Dalin, A.-M., Muller, E.E., Shah, P. and Wilmes, P., 2017. Ninety-nine de novo assembled genomes from the moose (Alces alces) rumen microbiome provide new insights into microbial plant biomass degradation. ISME journal 11: 2538.
'Ninety-nine de novo assembled genomes from the moose (Alces alces) rumen microbiome provide new insights into microbial plant biomass degradation ' () 11 ISME journal : 2538.
-
Tian, D., Xu, X., Peng, Q., Wen, Z., Zhang, Y., Wei, C., Qiao, Y. and Shi, B., 2019. In vitro fermentation of arabinoxylan from oat (Avena sativa L.) by Pekin duck intestinal microbiota. 3 Biotech 9: 54.
'In vitro fermentation of arabinoxylan from oat (Avena sativa L.) by Pekin duck intestinal microbiota ' () 9 3 Biotech : 54.
-
Turnbull, P. and Kramer, J., 1985. Intestinal carriage of Bacillus cereus: faecal isolation studies in three population groups. Epidemiology and Infection 95: 629-638.
'Intestinal carriage of Bacillus cereus: faecal isolation studies in three population groups ' () 95 Epidemiology and Infection : 629 -638.
-
Umu, O.C., Frank, J.A., Fangel, J.U., Oostindjer, M., da Silva, C.S., Bolhuis, E.J., Bosch, G., Willats, W.G., Pope, P.B. and Diep, D.B., 2015. Resistant starch diet induces change in the swine microbiome and a predominance of beneficial bacterial populations. Microbiome 3: 16. https://doi.org/10.1186/s40168-015-0078-5
-
Venema, K., Van Nuenen, M., Smeets-Peeters, M., Minekus, M. and Havenaar, R., 2000. TNOâs in vitro large intestinal model: an excellent screening tool for functional food and pharmaceutical research. Ernährung 24: 558-564.
'TNOâs in vitro large intestinal model: an excellent screening tool for functional food and pharmaceutical research ' () 24 Ernährung : 558 -564.
-
Venema, K. and Van den Abbeele, P., 2013. Experimental models of the gut microbiome. Best Practice and Research Clinical Gastroenterology 27: 115-126.
'Experimental models of the gut microbiome ' () 27 Best Practice and Research Clinical Gastroenterology : 115 -126.
-
Verhoeckx, K., Cotter, P., López-Expósito, I., Kleiveland, C., Lea, T., Mackie, A., Requena, T., Swiatecka, D. and Wichers, H., 2015. The impact of food bioactives on health: in vitro and ex vivo models. Springer, Heidelberg, Germany.
'The impact of food bioactives on health: in vitro and ex vivo models', ().
Supplementary Materials
| å ¨é¨æé´ | è¿å»ä¸å¹´ | è¿å»30天 | |
|---|---|---|---|
| æè¦æµè§æ¬¡æ° | 0 | 0 | 0 |
| å ¨ææµè§æ¬¡æ° | 274 | 98 | 8 |
| PDFä¸è½½æ¬¡æ° | 252 | 93 | 4 |
Polysaccharide source altered ecological network, functional profile, and short-chain fatty acid production in a porcine gut microbiota
äºBeneficial MicrobesSearch for other papers by C. Long in
Current site
Google Scholar
PubMed
Search for other papers by S. de Vries in
Current site
Google Scholar
PubMed
Search for other papers by K. Venema in
Current site
Google Scholar
PubMed
Several validated dynamic in vitro models of the colon have been developed for humans, but there is no dynamic in vitro fermentation model for pigs. This study was conducted to modify the human, dynamic, computer-controlled TNO in vitro model of the colon (TIM-2) for pigs and investigate effects of different starch sources and polysaccharides on swine microbiota structure, ecological network, predictive functional profile, and short-chain fatty acids production. Our study showed that three different types of starch or two polysaccharides greatly impacted microbiota composition. Co-occurrence network analysis indicated that microbiota fed with different sources of starch changed the network topological properties. Functional profiles were predicted to vary significantly among the three starch treatments, and the original pig faecal inoculum was more similar to maize starch treatment. On the other hand, compared with maize starch and arabinoxylans (AX), the microbial composition of the original inoculum was more similar when AX-XG (arabinoxylans and xyloglucan) were added, and the functional profile of the original inoculum also clustered with AX-XG. The cumulative production of acetic, propionic, and butyric acid on maize starch were significantly higher than those on potato starch and wheat starch, while only the amount of acetic acid was significant higher on AX-XG than that on AX. In conclusion, supplementation of maize starch as the starch source together with AX and XG, leads to the bacteria being more stable in the in vitro model and closer to the original inoculum and microbial function compared to potato starch, wheat starch and AX. A maize basal diet may improve energy absorption in the large intestine in growing pigs.
| å ¨é¨æé´ | è¿å»ä¸å¹´ | è¿å»30天 | |
|---|---|---|---|
| æè¦æµè§æ¬¡æ° | 0 | 0 | 0 |
| å ¨ææµè§æ¬¡æ° | 274 | 98 | 8 |
| PDFä¸è½½æ¬¡æ° | 252 | 93 | 4 |
