Abstract
Purpose
To investigate the effects of two cereal soluble dietary fibres (SDF), wheat arabinoxylan (AX) and oat-mixed linkage glucans (MLG), on fermentative end-products and bacterial community profiles of the porcine caecum (Cae) and distal colon (DC). We hypothesised that feeding pigs these SDF would stimulate Cae and DC carbohydrate fermentation, resulting in a modification of the resident bacterial communities.
Methods
Five groups of six pigs were each fed one diet based on wheat starch (WS) only, or treatment diets in which some WS was replaced by 10 % AX, or 10 % MLG, a combination of 5 % AX:5 % MLG (AXMLG), or completely replaced with ground whole wheat. Post-euthanasia, Cae and DC digesta were collected for analysis of fermentative end-products, and bacterial community profiles were determined by 16S rRNA gene amplicon 454 pyrosequencing.
Results
Across all the SDF-containing diets, predominantly in the proximal region of the large intestine, Prevotella, Lactobacillus, Mitsuokella and Streptococcus were most significantly influenced (P < 0.05), while notable changes were observed for the Ruminococcaceae and Lachnospiraceae families in the Cae and DC. The addition of MLG or AXMLG had the greatest effect of influencing bacterial profiles, reducing sequence proportions assigned to the genus Clostridium, considered detrimental to gut health, with associated increases in short-chain fatty acid and reduced ammonia concentrations.
Conclusions
This study demonstrated how the cereal SDF AX and MLG altered the large intestinal bacterial community composition, particularly proximally, further giving insights into how diets rich in specific complex carbohydrates shift the bacterial population, by increasing abundance and promoting greater diversity of those bacteria considered beneficial to gut health.
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References
Ferlay J, Soerjomataram I, Ervik M, Dikshit R, Eser S, Mathers C, Rebelo M, Parkin DM, Forman D, Bray, F (2013) GLOBOCAN 2012 v1.0, Cancer incidence and mortality worldwide: IARC CancerBase No. 11. International Agency for Research on Cancer, Lyon, France. http://globocan.iarc.fr
Fung TT, Hu FB, Wu K, Chiuve SE, Fuchs CS, Giovannucci E (2010) The mediterranean and dietary approaches to stop hypertension (DASH) diets and colorectal cancer. Am J Clin Nutr 92:1429–1435
Huang T, Xu M, Lee A, Cho S, Qi L (2015) Consumption of whole grains and cereal fiber and total and cause-specific mortality: prospective analysis of 367,442 individuals. BMC Med 13:59. doi:10.1186/s12916-015-0294-7
Aune D, Chan DS, Lau R, Vieira R, Greenwood DC, Kampman E, Norat T (2011) Dietary fibre, whole grains, and risk of colorectal cancer: systematic review and dose-response meta-analysis of prospective studies. BMJ 343:d6617. doi:10.1136/bmj.d6617
Hou N, Huo D, Dignam JJ (2013) Prevention of colorectal cancer and dietary management. Chin Clin Oncol 2:13. doi:10.3978/j.issn.2304-3865.2013.04.03
Burkitt DP (1971) Epidemiology of cancer of the colon and rectum. Cancer 28:3–13
Saulnier L, Guillon F, Chateigner-Boutin A-L (2012) Cell wall deposition and metabolism in wheat grain. J Cereal Sci 56:91–108
Lazaridou A, Biliaderis CG (2007) Molecular aspects of cereal β-glucan functionality: physical properties, technological applications and physiological effects. J Cereal Sci 46:101–118
Williams BA, Mikkelsen D, le Paih L, Gidley MJ (2011) In vitro fermentation kinetics and end-products of cereal arabinoxylans and (1,3;1,4)-beta-glucans by porcine faeces. J Cereal Sci 53:53–58
Hughes SA, Shewry PR, Gibson GR, McCleary BV, Rastall RA (2008) In vitro fermentation of oat and barley derived beta-glucans by human faecal microbiota. FEMS Microbiol Ecol 64:482–493
Hughes SA, Shewry PR, Li L, Gibson GR, Sanz ML, Rastall RA (2007) In vitro fermentation by human fecal microflora of wheat arabinoxylans. J Agric Food Chem 55:4589–4595
Ziemer CJ (2013) Broad diversity and newly cultured bacterial isolates from enrichment of pig feces on complex polysaccharides. Microb Ecol 66:448–461
Knudsen KEB, Hansen I (1991) Gastrointestinal implications in pigs of wheat and oat fractions 1. Digestibility and bulking properties of polysaccharides and other major constituents. Br J Nutr 65:217–232
Knudsen KEB, Canibe N (2000) Breakdown of plant carbohydrates in the digestive tract of pigs fed on wheat- or oat-based rolls. J Sci Food Agr 80:1253–1261
Williams BA, Zhang D, Lisle AT, Mikkelsen D, McSweeney CS, Kang S, Bryden WL, Gidley MJ (2016) Soluble arabinoxylan enhances large intestinal microbial health biomarkers in pigs fed a red-meat containing diet. Nutrition 32:491–497
Louis P, Flint H (2009) Diversity, metabolism and microbial ecology of butyrate-producing bacteria from the human large intestine. FEMS Microbiol Lett 294:1–8
Chang PV, Hao L, Offermanns S, Medzhitov R (2013) The microbial metabolite butyrate regulates intestinal macrophage function via histone deacetylase inhibition. Proc Natl Acad Sci USA 111:2247–2252
Tremaroli V, Bäckhed F (2012) Functional interactions between the gut microbiota and host metabolism. Nature 489:242–249
Leng SL, Leeding KS, Gibson PR, Bach LA (2001) Insulin-like growth factor-II renders LIM 2405 human colon cancer cells resistant to butyrate-induced apoptosis: a potential mechanism for colon cancer cell survival in vivo. Carcinogenesis 22:1625–1631
Hughes R, Magee EA, Bingham S (2000) Protein degradation in the large intestine: relevance to colorectal cancer. Curr Issues in Intest Microbiol 1:51–58
Sokol H, Pigneur B, Watterlot L, Lakhdari O, Bermudez-Humaran LG, Gratadoux J-J, Blugeon S, Bridonneau C, Furet JP, Corthier G, Grangette C, Vasquez N, Pochart P, Trugnan G, Thomas G, Blottière HM, Doré J, Marteau P, Seksik P, Langella P (2008) Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. Proc Natl Acad Sci USA 105:16731–16736
Miquel S, Leclerc M, Martin R, Chain F, Lenoir M, Raguideau S, Hudault S, Bridonneau C, Northen T, Bowen B, Bermúdez-Humarán LG, Sokol H, Thomas M, Langella P (2015) Identification of metabolic signatures linked to anti-inflammatory effects of Faecalibacterium prausnitzii. mBio. ASM 6:1–15. doi:10.1128/mBio.00300-15
Cummings J (1993) The effect of dietary fiber on fecal weight and composition. In: Spiller GA (ed) CRC Handbook of dietary fiber in human nutrition. CRC Press, Boca Raton, pp 263–315
Jenkins DJA, Vuksan V, Kendall CWC, Wursch P, Jeffcoat R, Waring S, Mehling CC, Vidgen E, Augustin LS, Wong E (1998) Physiological effects of resistant starches on fecal bulk, short chain fatty acids, blood lipids and glycemic index. J Am Coll Nutr 17:609–616
Young GP (2000) Colorectal disorders: a dietary management perspective. Asia Pac J Clin Nut 9:S76–S82
Guilloteau P, Zabielski R, Hammon HM, Metges CC (2010) Nutritional programming of gastrointestinal tract development. Is the pig a good model for man? Nutr Res Rev 23:4–22
Heinritz SN, Mosenthin R, Weiss E (2013) Use of pigs as a potential model for research into dietary modulation of the human gut microbiota. Nutr Res Rev 26:191–209
Zhang D, Williams BA, Mikkelsen D, Li X, Keates HL, Lisle AT, Collins HM, Fincher GB, Bird AR, Topping DL, Gidley MJ, Bryden WL (2015) Soluble arabinoxylan alters digesta flow and protein digestion of red meat-containing diets in pigs. Nutrition 31:1141–1147. doi:10.1016/j.nut.2015.03.006
Vreman HJ, Dowling JA, Raubach RA, Weiner MW (1978) Determination of acetate in biological material by vacuum microdistillation and gas chromatography. Anal Chem 50:1138–1141
Bolleter WT, Bushman CJ, Tidwell PW (1961) Spectrophotometric determination of ammonia as indophenol. Anal Chem 33:592–594
ISO 6496:1999 International organization for standardization. Case postale 56, CH-1211 Genève 20, Switzerland
Lane DJ, Pace B, Olsen GJ, Stahl DA, Sogin ML, Pace NR (1985) Rapid determination of 16S ribosomal RNA sequences for phylogenetic analyses. Proc Natl Acad Sci USA 82:6955–6959
Lane DJ (1991) 16S/23S rRNA sequencing. In: Stackebrant E, Goodfellow M (eds) Nucleic acid techniques in bacterial systematics. Wiley, London, pp 115–175
Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Peña AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336
Bragg L, Stone G, Imelfort M, Hugenholtz P, Tyson GW (2012) Fast, accurate error-correction of amplicon pyrosequences using Acacia. Nat Methods 9:425–426
De Santis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL (2006) Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72:5069–5072
Caporaso JG, Bittinger K, Bushman FD, DeSantis TZ, Andersen GL, Knight R (2010) PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 26:266–267
Cole JR, Wang Q, Cardenas E, Fish J, Chai B, Farris RJ, Kulam-Syed-Mohideen AS, McGarrell DM, Marsh T, Garrity GM, Tiedje JM (2009) The ribosomal database project: improved alignments and new tools for rRNA analysis. Nucleic Acids Res 37:D141–D145
Hass BJ, Gevers D, Earl AM, Feldgarden M, Ward DV, Giannoukos G, Ciulla D, Tabbaa D, Highlander SK, Sodergren E, Methé B, DeSantis TZ (2011) Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Res 21:494–504
Price MN, Dehal PS, Arkin AP (2009) FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol Biol Evol 26:1641–1650
McMurdie PJ, Holmes S (2013) Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLOSONE 8:e61217. doi:10.1371/journal.pone.0061217
Chessel D, Dufour A-B, Thioulouse J (2004) The ade4 package—I: one-table methods. R News 4:5–10
Culhane AC, Perrière G, Considine EC, Cotter TG, Higgins DG (2002) Between-group analysis of microarray data. Bioinformatics 18:1600–1608
R Core Team (2014) R: a language and environment for statistical computing. R foundation for statistical C\computing, Vienna, Austria. http://www.R-project.org/
Ter Braak CJF (1986) Canonical correspondence analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology 67:1167–1179
De Vos P, Garrity GM, Jones D, Krieg NR, Ludwig W, Rainey FA, Schleifer K-H, Whitman WB (eds) (2009) Bergey’s manual of systematic bacteriology. The Firmicutes, vol 3, 2nd edn. Springer, New York
Dai Z-L, Wu G, Zhu W-Y (2011) Amino acid metabolism in intestinal bacteria: links between gut ecology and host health. Front Biosci 16:1768–1786
Cummings JH, Macfarlane GT (1991) The control and consequences of bacterial fermentation in the human colon. J Appl Bacteriol 70:443–459
Arumugam M, Raes J, Pelletier E, Le Paslier D, Yamada T, Mende DR, Fernandes GR, Tap J, Bruls T, Batto JM, Bertalan M, Borruel N, Casellas F, Fernandez L, Gautier L, Hansen T, Hattori M, Hayashi T, Kleerebezem M, Kurokawa K, Leclerc M, Levenez F, Manichanh C, Nielsen HB, Nielsen T, Pons N, Poulain J, Qin J, Sicheritz-Ponten T, Tims S, Torrents D, Ugarte E, Zoetendal EG, Wang J, Guarner F, Pedersen O, de Vos WM, Brunak S, Doré J, MetaHIT Consortium, Antolín M, Artiguenave F, Blottiere HM, Almeida M, Brechot C, Cara C, Chervaux C, Cultrone A, Delorme C, Denariaz G, Dervyn R, Foerstner KU, Friss C, van de Guchte M, Guedon E, Haimet F, Huber W, van Hylckama-Vlieg J, Jamet A, Juste C, Kaci G, Knol J, Lakhdari O, Layec S, Le Roux K, Maguin E, Mérieux A, Melo Minardi R, M’rini C, Muller J, Oozeer R, Parkhill J, Renault P, Rescigno M, Sanchez N, Sunagawa S, Torrejon A, Turner K, Vandemeulebrouck G, Varela E, Winogradsky Y, Zeller G, Weissenbach J, Ehrlich SD, Bork P (2011) Enterotypes of the human gut microbiome. Nature 473:174–180
Slifierz MJ, Friendship RM, Weese JS (2015) Longitudinal study of the early-life fecal and nasal microbiotas of the domestic pig. BMC Microbiol 15:184. doi:10.1186/s12866-015-0512-7
De Filippo C, Cavalieri D, Di Paola M, Ramazzotti M, Poullet JB, Massart S, Collini S, Pieraccini G, Lionetti P (2010) Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci USA 107:14691–14696
Wu GD, Chen J, Hoffmann C, Bittinger K, Chen YY, Keilbaugh SA, Bewtra M, Knights D, Walters WA, Knight R, Sinha R, Gilroy E, Gupta K, Baldassano R, Nessel L, Li H, Bushman FD, Lewis JD (2011) Linking long-term dietary patterns with gut microbial enterotypes. Science 334:105–108
Avgustin G, Wallace RJ, Flint HJ (1997) Phenotypic diversity among rumen isolates of Prevotella ruminicola: proposal for redefinition of Prevotella ruminicola and the creation of Prevotella brevis sp. nov., Prevotella bryantii sp. nov. and Prevotella albensis sp. nov. Int J Syst Bacteriol 47:284–288
Ramsak A, Peterka M, Tajima K, Martin JC, Wood J, Johnston ME, Aminov RI, Avgustin G (2000) Unravelling the genetic diversity of rum`inal bacteria belonging to the CFB phylum. FEMS Microbiol Ecol 33:69–79
Fields MW, Russell JB, Wilson DB (1998) The role of ruminal carboxymethylcellulases in the degradation of β-glucans from cereal grain. FEMS Microbiol Ecol 27:261–268
Gasparic A, Marinsek-Logar R, Martin J, Wallace RJ, Nekrep FV, Flint HJ (1995) Isolation of genes encoding beta-d-xylanase, beta-d-xylosidase and alpha-l-arabinofuranosidase activities from the rumen bacterium Prevotella ruminicola B14. FEMS Microbiol Lett 125:135–141
Krieg NR, Staley, JT, Brown DR, Hedlund BP, Paster BJ, Ward NL, Ludwig W, Whitman WB (eds) (2009) Bergey’s manual of systematic bacteriology, 2nd edn, vol. 4, The Bacteroidetes, Spirochaetes, Tenericutes (Mollicutes), Acidobacteria, Fibrobacteres, Fusobacteria, Dictyoglomi, Gemmatimonadetes, Lentisphaerae, Verrucomicrobia, Chlamydiae, and Planctomycetes, Springer, New York
Payne AN, Chassard C, Zimmermann M, Müller P, Stinca S, Lacroix C (2011) The metabolic activity of gut microbiota in obese children is increased compared with normal-weight children and exhibits more exhaustive substrate utilization. Nutr Diabetes 1:e12. doi:10.1038/nutd.2011.8
Roos S, Karner F, Axelsson L, Jonsson H (2000) Lactobacillus mucosae sp. nov., a new species with in vitro mucus-binding activity isolated from pig intestine. Int J Syst Evol Microbiol 5:251–258
Belenguer A, Duncan SH, Calder AG, Holtrop G, Louis P, Lobley GE, Flint HJ (2006) Two routes of metabolic cross-feeding between Bifidobacterium adolescentis and butyrate-producing anaerobes from the human gut. Appl Environ Microbiol 72:3593–3599
Luo YH, Yang C, Wright AG, He J, Chen DW (2015) Responses in ileal and cecal bacteria to low and high amylose/amylopectin ratio diets in growing pigs. Appl Microbiol Biotechnol 99:10627–10638. doi:10.1007/s00253-015-6917-2
Liu H, Ivarsson E, Dicksved J, Lundh T, Lindberg JE (2012) Inclusion of chicory (Cichorium intybus L.) in pigs’ diets affects the intestinal microenvironment and the gut microbiota. Appl Environ Microbiol 78:4102–4109
Robinson IM, Whipp SC, Bucklin JA, Allison MJ (1984) Characterization of predominant bacteria from the colons of normal and dysenteric pigs. Appl Environ Microbiol 48:964–969
Levesque CL, Hooda S, Swanson KS, de Lange K (2014) Alterations in ileal mucosa bacteria related to diet complexity and growth performance in young pigs. PLoS ONE 9:e108472. doi:10.1371/journal.pone.0108472
Mølbak L, Thomsen LE, Jensen TK, Bach Knudsen KE, Boye M (2007) Increased amount of Bifidobacterium thermacidophilum and Megasphaera elsdenii in the colonic microbiota of pigs fed a swine dysentery preventive diet containing chicory roots and sweet lupine. J Appl Microbiol 103:1853–1867
Haenen D, da Silva CS, Zhang J, Koopmans SJ, Bosch G, Vervoort J, Gerrits WJ, Kemp B, Smidt H, Müller M, Hooiveld GJ (2014) Resistant starch induces catabolic but suppresses immune and cell division pathways and changes the microbiome in the proximal colon of male pigs. J Nutr 143:1889–1898
Frese SA, Parker K, Calvert CC, Mills DA (2015) Diet shapes the gut microbiome of pigs during nursing and weaning. Microbiome 3:28. doi:10.1186/s40168-015-0091-8
Bearson SMD, Allen HK, Bearson BL, Looft T, Brunelle BW, Kich JD, Tuggle CK, Bayles DO, Alt D, Levine UY, Stanton TB (2013) Profiling the gastrointestinal microbiota in response to Salmonella: low versus high Salmonella shedding in the natural porcine host. Infect Genet Evol 16:330–340
Salonen A, Lahti L, Salojärvi J, Holtrop G, Korpela K, Duncan SH, Date P, Farquharson F, Johnstone AM, Lobley GE, Louis P, Flint HJ, de Vos WM (2014) Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men. ISME J 8:2218–2230. doi:10.1038/ismej.2014.63
Sun Y, Zhou L, Fang L, Su Y, Zhu W (2015) Responses in colonic microbial community and gene expression of pigs to a long-term high resistant starch diet. Front Microbiol 6:877. doi:10.3389/fmicb.2015.00877
Walker AW, Ince J, Duncan SH, Webster LM, Holtrop G, Ze X, Brown D, Stares MD, Scott P, Bergerat A, Louis P, McIntosh F, Johnstone AM, Lobley GE, Parkhill J, Flint HJ (2011) Dominant and diet-responsive groups of bacteria within the human colonic microbiota. ISME J 5:220–230. doi:10.1038/ismej.2010.118
Chumpitazi BP, Cope JL, Hollister EB, Tsai CM, McMeans AR, Luna RA, Versalovic J, Shulman RJ (2015) Randomised clinical trial: gut microbiome biomarkers are associated with clinical response to a low FODMAP diet in children with the irritable bowel syndrome. Aliment Pharmacol Ther 42:418–427
Goyette-Desjardins G, Auger J-P, Xu J, Segura M, Gottschalk M (2014) Streptococcus suis, an important pig pathogen and emerging zoonotic agent—an update on the worldwide distribution based on serotyping and sequence typing. Emerg Microbes Infect 3:e45. doi:10.1038/emi.2014.45
Umu ÖCO, Frank JA, Fangel JU, Oostindjer M, da Silva CS, Bolhuis EJ, Bosch G, Willats WG, Pope PB, Diep DB (2015) Resistant starch diet induces change in the swine microbiome and a predominance of beneficial bacterial populations. Microbiome 3:16. doi:10.1186/s40168-015-0078-5
Candela M, Turroni S, Biagi E, Carbonero F, Rampelli S, Fiorentini C, Brigidi P (2014) Inflammation and colorectal cancer, when microbiota-host mutualism breaks. World J Gastroenterol 20:908–922
Simpson HL, Campbell BJ (2015) Review article: dietary fibre—microbiota interactions. Aliment Pharmacol Ther 42:158–179
Schnorr SL, Candela M, Rampelli S, Centanni M, Consolandi C, Basaglia G, Turroni S, Biagi E, Peano C, Severgnini M, Fiori J, Gotti R, De Bellis G, Luiselli D, Brigidi P, Mabulla A, Marlowe F, Henry AG, Crittenden AN (2014) Gut microbiome of the Hadza hunter-gatherers. Nat Commun 5:3654. doi:10.1038/ncomms4654
Acknowledgments
This study was supported by a grant from the CSIRO Flagship Collaboration Fund to the High Fibre Grains Cluster via the Food Futures Flagship. John Gorham was awarded a PhD Scholarship from the Australian Research Council Centre for Excellence in Plant Cell Walls. The authors acknowledge QASP staff, Dr Dagong Zhang and John McVeigh for animal husbandry; Prof Helen Keates for pig anaesthesia; Dr Walter Gerrits, Barbara Gorham, Anton Plushke, Henri Rochegon and Pauline Vasseur for digesta sampling; and Ian Brock and Brian Burren of the Animal Research Institute at Yeerongpilly for SCFA and NH3 analyses.
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All experimental procedures involving pigs were approved by the Animal Ethics Committees of the University of Queensland and CSIRO Food and Nutritional Sciences (Approval Number CNAFS/179/11/CSIRO).
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John B. Gorham and Seungha Kang have contributed equally to this work and joint first authors.
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Fig. S1
Fig. S.1 Plot of the diet vs SCFA concentrations in the Cae digesta (P values refer to significant differences per SCFA type across the five diets) (TIFF 32 kb)
Fig. S2
Fig. S2 Plot of the diet vs SCFA concentrations in the DC (P values refer to significant differences per SCFA type across the five diets) (TIFF 36 kb)
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Gorham, J.B., Kang, S., Williams, B.A. et al. Addition of arabinoxylan and mixed linkage glucans in porcine diets affects the large intestinal bacterial populations. Eur J Nutr 56, 2193–2206 (2017). https://doi.org/10.1007/s00394-016-1263-4
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DOI: https://doi.org/10.1007/s00394-016-1263-4
Keywords
- 16S rRNA gene
- Arabinoxylan
- Mixed linkage glucans
- Pig model
- Pyrosequencing
- Soluble dietary fibre