This study investigated gut microbiota composition along with food, host, and microbial derived metabolites in the colon and systemic circulation of healthy mice following dietary rice bran and fermented rice bran intake. Adult male BALB/c mice were fed a control diet or one of two experimental diets containing 10% w/w rice bran fermented by Bifidobacterium longum or 10% w/w non-fermented rice bran for 15 weeks. Metabolomics was performed on the study diets (food), the murine colon and whole blood. These were analysed in concert with 16S rRNA amplicon sequencing of faeces, caecum, and colon microbiomes. Principal components analysis of murine microbiota composition displayed marked separation between control and experimental diets, and between faecal and tissue (caecum and colon) microbiomes. Colon and caecal microbiomes in both experimental diet groups showed enrichment of Roseburia, Lachnospiraceae, and Clostridiales related amplicon sequence variants compared to control. Bacterial composition was largely similar between experimental diets. Metabolite profiling revealed 530 small molecules comprising of 39% amino acids and 21% lipids that had differential abundances across food, colon, and blood matrices, and statistically significant between the control, rice bran, and fermented rice bran groups. The amino acid metabolite, N-delta-acetylornithine, was notably increased by B. longum rice bran fermentation when compared to non-fermented rice bran in food, colon, and blood. These findings support that dietary intake of rice bran fermented with B. longum modulates multiple metabolic pathways important to the gut and overall health.
Bazanella, M., Maier, T.V., Clavel, T., Lagkouvardos, I., Lucio, M., Maldonado-Gomez, M.X., Autran, C., Walter, J., Bode, L., Schmitt-Kopplin, P. and Haller, D., 2017. Randomized controlled trial on the impact of early-life intervention with bifidobacteria on the healthy infant fecal microbiota and metabolome. American Journal of Clinical Nutrition 106: 1274-1286. https://doi.org/10.3945/ajcn.117.157529
Benjamini, Y. and Hochberg, Y., 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B 57: 289-300.
'Controlling the false discovery rate: a practical and powerful approach to multiple testing ' () 57 Journal of the Royal Statistical Society Series B : 289 -300.
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 2’s q2-feature-classifier plugin. Microbiome 6: 90. https://doi.org/10.1186/s40168-018-0470-z
Brown, D.G., Borresen, E.C., Brown, R.J. and Ryan, E.P., 2017. Heat-stabilised rice bran consumption by colorectal cancer survivors modulates stool metabolite profiles and metabolic networks: a randomised controlled trial. British Journal of Nutrition 117: 1244-1256. https://doi.org/10.1017/s0007114517001106
Bunesova, V., Lacroix, C. and Schwab, C., 2016. Fucosyllactose and L-fucose utilization of infant Bifidobacterium longum and Bifidobacterium kashiwanohense. BMC Microbiology 16: 248-248. https://doi.org/10.1186/s12866-016-0867-4
Callahan, B.J., McMurdie, P.J., Rosen, M.J., Han, A.W., Johnson, A.J. and Holmes, S.P., 2016. DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods 13: 581-583. https://doi.org/10.1038/nmeth.3869
Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K., Fierer, N., Peña, A.G., Goodrich, J.K., Gordon, J.I., Huttley, G.A., Kelley, S.T., Knights, D., Koenig, J.E., Ley, R.E., Lozupone, C.A., McDonald, D., Muegge, B.D., Pirrung, M., Reeder, J., Sevinsky, J.R., Turnbaugh, P.J., Walters, W.A., Widmann, J., Yatsunenko, T., Zaneveld, J. and Knight, R., 2010. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7: 335-336. https://doi.org/10.1038/nmeth.f.303
Caporaso, J.G., Lauber, C.L., Walters, W.A., Berg-Lyons, D., Huntley, J., Fierer, N., Owens, S.M., Betley, J., Fraser, L., Bauer, M., Gormley, N., Gilbert, J.A., Smith, G. and Knight, R., 2012. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME Journal 6: 1621. https://doi.org/10.1038/ismej.2012.8
Caporaso, J.G., Lauber, C.L., Walters, W.A., Berg-Lyons, D., Lozupone, C.A., Turnbaugh, P.J., Fierer, N. and Knight, R., 2011. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proceedings of the National Academy of Sciences of the USA 108: 4516. https://doi.org/10.1073/pnas.1000080107
Celiberto, L.S., Bedani, R., Dejani, N.N., Ivo de Medeiros, A., Sampaio Zuanon, J.A., Spolidorio, L.C., Tallarico Adorno, M.A., Amancio Varesche, M.B., Carrilho Galvao, F., Valentini, S.R., Font de Valdez, G., Rossi, E.A. and Cavallini, D.C.U., 2017. Effect of a probiotic beverage consumption (Enterococcus faecium CRL 183 and Bifidobacterium longum ATCC 15707) in rats with chemically induced colitis. PLoS ONE 12: e0175935. https://doi.org/10.1371/journal.pone.0175935
Chen, C.L., Wu, D.C., Liu, M.Y., Lin, M.W., Huang, H.T., Huang, Y.B., Chen, L.C., Chen, Y.Y., Chen, J.J., Yang, P.H., Kao, Y.C. and Chen, P.Y., 2017a. Cholest-4-en-3-one attenuates TGF-beta responsiveness by inducing TGF-beta receptors degradation in Mv1Lu cells and colorectal adenocarcinoma cells. Journal of Receptor and Signal Transduction Research 37: 189-199. https://doi.org/10.1080/10799893.2016.1203944
Chen, J., Pitmon, E. and Wang, K., 2017b. Microbiome, inflammation and colorectal cancer. Seminars in Immunology 32: 43-53. https://doi.org/10.1016/j.smim.2017.09.006
Cowan, T.E., Palmnas, M.S., Yang, J., Bomhof, M.R., Ardell, K.L., Reimer, R.A., Vogel, H.J. and Shearer, J., 2014. Chronic coffee consumption in the diet-induced obese rat: impact on gut microbiota and serum metabolomics. Journal of Nutritional Biochemistry 25: 489-495. https://doi.org/10.1016/j.jnutbio.2013.12.009
Derkach, A., Sampson, J., Joseph, J., Playdon, M.C. and Stolzenberg-Solomon, R.Z., 2017. Effects of dietary sodium on metabolites: the Dietary Approaches to Stop Hypertension (DASH)-Sodium Feeding Study. American Journal of Clinical Nutrition 106: 1131-1141. https://doi.org/10.3945/ajcn.116.150136
DeSantis, T.Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E.L., Keller, K., Huber, T., Dalevi, D., Hu, P. and Andersen, G.L., 2006. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Applied and Environmental Microbiology 72: 5069-5072. https://doi.org/10.1128/aem.03006-05
Emerson, J.B., Adams, R.I., Roman, C.M.B., Brooks, B., Coil, D.A., Dahlhausen, K., Ganz, H.H., Hartmann, E.M., Hsu, T., Justice, N.B., Paulino-Lima, I.G., Luongo, J.C., Lymperopoulou, D.S., Gomez-Silvan, C., Rothschild-Mancinelli, B., Balk, M., Huttenhower, C., Nocker, A., Vaishampayan, P. and Rothschild, L.J., 2017. Schrodinger’s microbes: tools for distinguishing the living from the dead in microbial ecosystems. Microbiome 5: 86. https://doi.org/10.1186/s40168-017-0285-3
Fabian, C. and Ju, Y.H., 2011. A review on rice bran protein: its properties and extraction methods. Critical Reviews in Food Science and Nutrition 51: 816-827. https://doi.org/10.1080/10408398.2010.482678
Fernandes, A.D., Macklaim, J.M., Linn, T.G., Reid, G. and Gloor, G.B., 2013. ANOVA-like differential expression (ALDEx) analysis for mixed population RNA-Seq. PLoS ONE 8: e67019-e67019. https://doi.org/10.1371/journal.pone.0067019
Fernandes, A.D., Reid, J.N., Macklaim, J.M., McMurrough, T.A., Edgell, D.R. and Gloor, G.B., 2014. Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis. Microbiome 2: 15. https://doi.org/10.1186/2049-2618-2-15
Food and Drug Administration (FDA), 2018. Irradiation in the production, processing, and handling of animal feed and pet food: subpart B – radiation and radiation sources. Code of Federal Regulations Title 21. Food and Drug Administration, Silver Spring, Maryland, USA.
Forster, G.M., Raina, K., Kumar, A., Kumar, S., Agarwal, R., Chen, M.H., Bauer, J.E., McClung, A.M. and Ryan, E.P., 2013. Rice varietal differences in bioactive bran components for inhibition of colorectal cancer cell growth. Food Chemistry 141: 1545-1552. https://doi.org/10.1016/j.foodchem.2013.04.020
Gagnon, M., Savard, P., Rivière, A., LaPointe, G. and Roy, D., 2015. Bioaccessible antioxidants in milk fermented by Bifidobacterium longum subsp. longum strains. BioMed Research International 2015: 169381-169381. https://doi.org/10.1155/2015/169381
Gentleman, R.C., Carey, V.J., Bates, D.M., Bolstad, B., Dettling, M., Dudoit, S., Ellis, B., Gautier, L., Ge, Y., Gentry, J., Hornik, K., Hothorn, T., Huber, W., Iacus, S., Irizarry, R., Leisch, F., Li, C., Maechler, M., Rossini, A.J., Sawitzki, G., Smith, C., Smyth, G., Tierney, L., Yang, J.Y. and Zhang, J., 2004. Bioconductor: open software development for computational biology and bioinformatics. Genome Biology 5: R80. https://doi.org/10.1186/gb-2004-5-10-r80
Glockner, F.O., Yilmaz, P., Quast, C., Gerken, J., Beccati, A., Ciuprina, A., Bruns, G., Yarza, P., Peplies, J., Westram, R. and Ludwig, W., 2017. 25 years of serving the community with ribosomal RNA gene reference databases and tools. Journal of Biotechnology 261: 169-176. https://doi.org/10.1016/j.jbiotec.2017.06.1198
Gloor, G.B., Macklaim, J.M., Pawlowsky-Glahn, V. and Egozcue, J.J., 2017. Microbiome datasets are compositional: and this is not optional. Frontiers in Microbiology 8: 2224. https://doi.org/10.3389/fmicb.2017.02224
Gómez de Cedrón, M., Acín Pérez, R., Sánchez-Martínez, R., Molina, S., Herranz, J., Feliu, J., Reglero, G., Enríquez, J.A. and Ramírez de Molina, A., 2017. MicroRNA-661 modulates redox and metabolic homeostasis in colon cancer. Molecular Oncology 11: 1768-1787. https://doi.org/10.1002/1878-0261.12142
Harrower, M. and Brewer, C., 2003. ColorBrewer.org: an online tool for selecting colour schemes for maps. Cartographic Journal 40: 27-37. https://doi.org/10.1179/000870403235002042
Henderson, A.J., Kumar, A., Barnett, B., Dow, S.W. and Ryan, E.P., 2012a. Consumption of rice bran increases mucosal immunoglobulin A concentrations and numbers of intestinal Lactobacillus spp. Journal of Medicinal Food 15: 469-475. https://doi.org/10.1089/jmf.2011.0213
Henderson, A.J., Ollila, C.A., Kumar, A., Borresen, E.C., Raina, K., Agarwal, R. and Ryan, E.P., 2012b. Chemopreventive properties of dietary rice bran: current status and future prospects. Advanced Nutrition 3: 643-653. https://doi.org/10.3945/an.112.002303
Hernandez-Alonso, P., Canueto, D., Giardina, S., Salas-Salvado, J., Canellas, N., Correig, X. and Bullo, M., 2017. Effect of pistachio consumption on the modulation of urinary gut microbiota-related metabolites in prediabetic subjects. Journal of Nutritional Biochemistry 45: 48-53. https://doi.org/10.1016/j.jnutbio.2017.04.002
Huber, W., Carey, V.J., Gentleman, R., Anders, S., Carlson, M., Carvalho, B.S., Bravo, H.C., Davis, S., Gatto, L., Girke, T., Gottardo, R., Hahne, F., Hansen, K.D., Irizarry, R.A., Lawrence, M., Love, M.I., MacDonald, J., Obenchain, V., Oles, A.K., Pages, H., Reyes, A., Shannon, P., Smyth, G.K., Tenenbaum, D., Waldron, L. and Morgan, M., 2015. Orchestrating high-throughput genomic analysis with bioconductor. Nature Methods 12: 115-121. https://doi.org/10.1038/nmeth.3252
Kassambara, A., 2018. ggpubr: ‘ggplot2’ based publication ready plots. Available at: https://rpkgs.datanovia.com/ggpubr/
Kim, J.M., Ku, S., Kim, Y.S., Lee, H.H., Jin, H., Kang, S., Li, R., Johnston, V.T., Park, S.M. and Ji, E.G. 2018. Safety evaluations of Bifidobacterium bifidum BGN4 and Bifidobacterium longum BORI. International Journal of Molecular Sciences 19: 1422. https://doi.org/10.3390/ijms19051422
Kumar, A., Henderson, A., Forster, G.M., Goodyear, A.W., Weir, T.L., Leach, J.E., Dow, S.W. and Ryan, E.P., 2012. Dietary rice bran promotes resistance to Salmonella enterica serovar Typhimurium colonization in mice. BMC Microbiology 12: 71. https://doi.org/10.1186/1471-2180-12-71
Law, B.M.H., Waye, M.M.Y., So, W.K.W. and Chair, S.Y., 2017. Hypotheses on the potential of rice bran intake to prevent gastrointestinal cancer through the modulation of oxidative stress. International Journal of Molecular Sciences 18: 1352. https://doi.org/10.3390/ijms18071352
Lee, T., Clavel, T., Smirnov, K., Schmidt, A., Lagkouvardos, I., Walker, A., Lucio, M., Michalke, B., Schmitt-Kopplin, P., Fedorak, R. and Haller, D., 2017. Oral versus intravenous iron replacement therapy distinctly alters the gut microbiota and metabolome in patients with IBD. Gut 66: 863-871. https://doi.org/10.1136/gutjnl-2015-309940
Lei, S., Ramesh, A., Twitchell, E., Wen, K., Bui, T., Weiss, M., Yang, X., Kocher, J., Li, G., Giri-Rachman, E., Trang, N.V., Jiang, X., Ryan, E.P. and Yuan, L., 2016. High protective efficacy of probiotics and rice bran against human norovirus infection and diarrhea in gnotobiotic pigs. Frontiers in Microbiology 7: 1699. https://doi.org/10.3389/fmicb.2016.01699
Mann, H.B. and Whitney, D.R., 1947. On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics 18: 50-60. https://doi.org/10.1214/aoms/1177730491
McDonald, D., Price, M.N., Goodrich, J., Nawrocki, E.P., DeSantis, T.Z., Probst, A., Andersen, G.L., Knight, R. and Hugenholtz, P., 2012. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME Journal 6: 610-618. https://doi.org/10.1038/ismej.2011.139
McIntosh, K., Reed, D.E., Schneider, T., Dang, F., Keshteli, A.H., De Palma, G., Madsen, K., Bercik, P. and Vanner, S., 2017. FODMAPs alter symptoms and the metabolome of patients with IBS: a randomised controlled trial. Gut 66: 1241-1251. https://doi.org/10.1136/gutjnl-2015-311339
Merker, R.I., 2018. Bacteriological analytical manual. Nutrition. Food and Drug Administration, Silver Spring, MD, USA.
'Bacteriological analytical manual', ().
Morgan, M., 2018. BiocManager: access the Bioconductor project package repository. R package version 3.9.0. https://doi.org/doi:10.18129/B9.bioc.BiocVersion
Morgan, M., Obenchain, V., Lang, M., Thompson, R. and Turaga, N., 2019. BiocParallel: Bioconductor facilities for parallel evaluation. https://doi.org/doi:10.18129/B9.bioc.BiocParallel
Nealon, N.J., Worcester, C.R. and Ryan, E.P., 2017. Lactobacillus paracasei metabolism of rice bran reveals metabolome associated with Salmonella Typhimurium growth reduction. Journal of Applied Microbiology 122: 1639-1656. https://doi.org/10.1111/jam.13459
Palarea-Albaladejo, J. and Martín-Fernández, J., 2015. zCompositions – R package for multivariate imputation of left-censored data under a compositional approach. Chemometrics and Intelligent Laboratory Systems 143: 85-96. https://doi.org/10.1016/j.chemolab.2015.02.019
Parada, A.E., Needham, D.M. and Fuhrman, J.A., 2016. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environmental Microbiology 18: 1403-1414. https://doi.org/10.1111/1462-2920.13023
Pessione, E. and Cirrincione, S., 2016. Bioactive molecules released in food by lactic acid bacteria: encrypted peptides and biogenic amines. Frontiers in Microbiology 9(7): 876. https://doi.org/10.3389/fmicb.2016.00876
Phoem, A.N., Chanthachum, S. and Voravuthikunchai, S.P., 2015. Applications of microencapsulated Bifidobacterium longum with Eleutherine americana in fresh milk tofu and pineapple juice. Nutrients 7: 2469-2484. https://doi.org/10.3390/nu7042469
Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J. and Glockner, F.O., 2013. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research 41: D590-596. https://doi.org/10.1093/nar/gks1219
R-Core-Team, 2018. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
'R: a language and environment for statistical computing', ().
Rezasoltani, S., Asadzadeh Aghdaei, H., Dabiri, H., Akhavan Sepahi, A., Modarressi, M.H. and Nazemalhosseini Mojarad, E., 2018. The association between fecal microbiota and different types of colorectal polyp as precursors of colorectal cancer. Microbial Pathogenesis 124: 244-249. https://doi.org/10.1016/j.micpath.2018.08.035
Sheflin, A.M., Borresen, E.C., Kirkwood, J.S., Boot, C.M., Whitney, A.K., Lu, S., Brown, R.J., Broeckling, C.D., Ryan, E.P. and Weir, T.L., 2017. Dietary supplementation with rice bran or navy bean alters gut bacterial metabolism in colorectal cancer survivors. Molecular Nutrition and Food Research 61: 1500905. https://doi.org/10.1002/mnfr.201500905
Sheflin, A.M., Borresen, E.C., Wdowik, M.J., Rao, S., Brown, R.J., Heuberger, A.L., Broeckling, C.D., Weir, T.L. and Ryan, E.P., 2015. Pilot dietary intervention with heat-stabilized rice bran modulates stool microbiota and metabolites in healthy adults. Nutrients 7: 1282-1300. https://doi.org/10.3390/nu7021282
Si, X., Shang, W., Zhou, Z., Shui, G., Lam, S.M., Blanchard, C. and Strappe, P., 2018. Gamma-aminobutyric acid enriched rice bran diet attenuates insulin resistance and balances energy expenditure via modification of gut microbiota and short-chain fatty acids. Journal of Agricultural and Food Chemistry 66: 881-890. https://doi.org/10.1021/acs.jafc.7b04994
So, W.K.W., Law, B.M.H., Law, P.T.W., Chan, C.W.H. and Chair, S.Y., 2016. Current hypothesis for the relationship between dietary rice bran intake, the intestinal microbiota and colorectal cancer prevention. Nutrients 8: 569. https://doi.org/10.3390/nu8090569
Sohail, M., Rakha, A., Butt, M.S., Iqbal, M.J. and Rashid, S., 2017. Rice bran nutraceutics: a comprehensive review. Critical Reviews in Food Science and Nutrition 57: 3771-3780. https://doi.org/10.1080/10408398.2016.1164120
Tamanai-Shacoori, Z., Smida, I., Bousarghin, L., Loreal, O., Meuric, V., Fong, S.B., Bonnaure-Mallet, M. and Jolivet-Gougeon, A., 2017. Roseburia spp.: a marker of health? Future Microbiology 12: 157-170. https://doi.org/10.2217/fmb-2016-0130
Tovar, J., De Mello, V.D., Nilsson, A., Johansson, M., Paananen, J., Lehtonen, M., Hanhineva, K. and Bjorck, I., 2017. Reduction in cardiometabolic risk factors by a multifunctional diet is mediated via several branches of metabolism as evidenced by nontargeted metabolite profiling approach. Molecular Nutrition and Food Research 61: 1600552. https://doi.org/10.1002/mnfr.201600552
Tuncil, Y.E., Thakkar, R.D., Arioglu-Tuncil, S., Hamaker, B.R. and Lindemann, S.R., 2018. Fecal microbiota responses to bran particles are specific to cereal type and in vitro digestion methods that mimic upper gastrointestinal tract passage. Journal of Agricultural and Food Chemistry 66: 12580-12593. https://doi.org/10.1021/acs.jafc.8b03469
Vandeputte, D., Falony, G., Vieira-Silva, S., Wang, J., Sailer, M., Theis, S., Verbeke, K. and Raes, J., 2017. Prebiotic inulin-type fructans induce specific changes in the human gut microbiota. Gut 66: 1968-1974. https://doi.org/10.1136/gutjnl-2016-313271
Vu, V.Q., 2011. ggbiplot: A ggplot2 based biplot. Available at: http://github.com/vqv/ggbiplot
Walters, W., Hyde, E.R., Berg-Lyons, D., Ackermann, G., Humphrey, G., Parada, A., Gilbert, J.A., Jansson, J.K., Caporaso, J.G., Fuhrman, J.A., Apprill, A. and Knight, R., 2016. Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems 1. https://doi.org/10.1128/mSystems.00009-15
Watson, J.A., Fang, M. and Lowenstein, J.M., 1969. Tricarballylate and hydroxycitrate: substrate and inhibitor of ATP: citrate oxaloacetate lyase. Archives of Biochemistry and Biophysics 135: 209-217. https://doi.org/10.1016/0003-9861(69)90532-3
Wickham, H., 2007. Reshaping data with the reshape package. Journal of Statistical Software 21: 1-20.
'Reshaping data with the reshape package ' () 21 Journal of Statistical Software : 1 -20.
Wickham, H., 2016. ggplot2: elegant graphics for data analysis. Springer-Verlag, New York, NY, USA. https://doi.org/10.1007/978-0-387-98141-3
Wickham, H., François, R., Henry, L. and Müller, K., 2018. dplyr: A grammar of data manipulation. Available at: https://cran.r-project.org/web/packages/dplyr/index.html
Wilcoxon, F., 1945. individual comparisons by ranking methods. Biometrics Bulletin 1: 80-83. https://doi.org/10.2307/3001968
Wolffram, S., Badertscher, M. and Scharrer, E., 1994. Carrier-mediated transport is involved in mucosal succinate uptake by rat large intestine. Experimental Physiology 79: 215-226.
'Carrier-mediated transport is involved in mucosal succinate uptake by rat large intestine ' () 79 Experimental Physiology : 215 -226.
Wu, K., Li, W., Song, J. and Li, T., 2015. Production, purification, and identification of Cholest-4-en-3-one produced by cholesterol oxidase from Rhodococcus sp. in aqueous/organic biphasic system. Biochemistry Insights 8: 1-8. https://doi.org/10.4137/BCI.S21580
Yang, X., Twitchell, E., Li, G., Wen, K., Weiss, M., Kocher, J., Lei, S., Ramesh, A., Ryan, E.P. and Yuan, L., 2015. High protective efficacy of rice bran against human rotavirus diarrhea via enhancing probiotic growth, gut barrier function, and innate immunity. Scientific Reports 5: 15004. https://doi.org/10.1038/srep15004
Yilmaz, P., Parfrey, L.W., Yarza, P., Gerken, J., Pruesse, E., Quast, C., Schweer, T., Peplies, J., Ludwig, W. and Glockner, F.O., 2014. The SILVA and ‘All-species Living Tree Project (LTP)’ taxonomic frameworks. Nucleic Acids Research 42: D643-648. https://doi.org/10.1093/nar/gkt1209
Zarei, I., Brown, D.G., Nealon, N.J. and Ryan, E.P., 2017. Rice bran metabolome contains amino acids, vitamins & cofactors, and phytochemicals with medicinal and nutritional properties. Rice 10: 24. https://doi.org/10.1186/s12284-017-0157-2
Zheng, H., Yde, C.C., Clausen, M.R., Kristensen, M., Lorenzen, J., Astrup, A. and Bertram, H.C., 2015. Metabolomics investigation to shed light on cheese as a possible piece in the French paradox puzzle. Journal of Agricultural and Food Chemistry 63: 2830-2839. https://doi.org/10.1021/jf505878a
Zhou, Y., Tozzi, F., Chen, J., Fan, F., Xia, L., Wang, J., Gao, G., Zhang, A., Xia, X., Brasher, H., Widger, W., Ellis, L.M. and Weihua, Z., 2012. Intracellular ATP levels are a pivotal determinant of chemoresistance in colon cancer cells. Cancer Research 72: 304. https://doi.org/10.1158/0008-5472.CAN-11-1674
| All Time | Past 365 days | Past 30 Days | |
|---|---|---|---|
| Abstract Views | 0 | 0 | 0 |
| Full Text Views | 326 | 255 | 38 |
| PDF Views & Downloads | 261 | 192 | 35 |
This study investigated gut microbiota composition along with food, host, and microbial derived metabolites in the colon and systemic circulation of healthy mice following dietary rice bran and fermented rice bran intake. Adult male BALB/c mice were fed a control diet or one of two experimental diets containing 10% w/w rice bran fermented by Bifidobacterium longum or 10% w/w non-fermented rice bran for 15 weeks. Metabolomics was performed on the study diets (food), the murine colon and whole blood. These were analysed in concert with 16S rRNA amplicon sequencing of faeces, caecum, and colon microbiomes. Principal components analysis of murine microbiota composition displayed marked separation between control and experimental diets, and between faecal and tissue (caecum and colon) microbiomes. Colon and caecal microbiomes in both experimental diet groups showed enrichment of Roseburia, Lachnospiraceae, and Clostridiales related amplicon sequence variants compared to control. Bacterial composition was largely similar between experimental diets. Metabolite profiling revealed 530 small molecules comprising of 39% amino acids and 21% lipids that had differential abundances across food, colon, and blood matrices, and statistically significant between the control, rice bran, and fermented rice bran groups. The amino acid metabolite, N-delta-acetylornithine, was notably increased by B. longum rice bran fermentation when compared to non-fermented rice bran in food, colon, and blood. These findings support that dietary intake of rice bran fermented with B. longum modulates multiple metabolic pathways important to the gut and overall health.
| All Time | Past 365 days | Past 30 Days | |
|---|---|---|---|
| Abstract Views | 0 | 0 | 0 |
| Full Text Views | 326 | 255 | 38 |
| PDF Views & Downloads | 261 | 192 | 35 |