The Journal of Nutrition
Nutrient Physiology, Metabolism, and Nutrient-Nutrient Interactions
454 Pyrosequencing Reveals a Shift in Fecal
Microbiota of Healthy Adult Men Consuming
Polydextrose or Soluble Corn Fiber1–3
Seema Hooda,4Brittany M. Vester Boler,4Mariana C. Rossoni Serao,4Jennifer M. Brulc,5
Michael A. Staeger,5Thomas W. Boileau,5Scot E. Dowd,6George C. Fahey Jr,4and Kelly S. Swanson4*
4University of Illinois, Department of Animal Sciences, Urbana, IL;5General Mills, Inc., Bell Institute of Health and Nutrition,
Minneapolis, MN; and6MR DNA Molecular Research LP, Shallowater, TX
The relative contribution of novel fibers such as polydextrose and soluble corn fiber (SCF) to the human gut microbiome
and its association with host physiology has not been well studied. This study was conducted to test the impact of
polydextrose and SCF on the composition of the human gut microbiota using 454 pyrosequencing and to identify
associations among fecal microbiota and fermentative end-products. Healthy adult men (n = 20) with a mean dietary fiber
(DF) intake of 14 g/d were enrolled in a randomized, double-blind, placebo-controlled crossover study. Participants
consumed 3 treatment snack bars/d during each 21-d period that contained no supplemental fiber (NFC), polydextrose
(PDX; 21 g/d), or SCF (21 g/d) for 21 d. There were no washout periods. Fecal samples were collected on d 16–21 of each
period; DNA was extracted, followed by amplification of the V4-V6 region of the 16S rRNA gene using barcoded primers.
PDX and SCF significantly affected the relative abundance of bacteria at the class, genus, and species level. The
consumption of PDX and SCF led to greater fecal Clostridiaceae and Veillonellaceae and lower Eubacteriaceae compared
with a NFC. The abundance of Faecalibacterium, Phascolarctobacterium, and Dialister was greater (P , 0.05) in response
to PDX and SCF intake, whereas Lactobacillus was greater (P , 0.05) only after SCF intake. Faecalibacterium prausnitzii,
well known for its antiinflammatory properties, was greater (P , 0.05) after fiber consumption. Principal component
analysis clearly indicated a distinct clustering of individuals consuming supplemental fibers. Our data demonstrate a
beneficial shift in the gut microbiome of adults consuming PDX and SCF, with potential application as prebiotics.J. Nutr.
142: 1259–1265, 2012.
The gastrointestinal microbiome plays a crucial role in human
gastrointestinal and host health, because it affects the metabolism
and development of the immune system and provides protection
against pathogens while modulating gastrointestinal development
(1). Despite its benefits, the gut microbiome has been associated
with complex diseases such as obesity (2,3), diabetes (4), colon
cancer (5), and inflammatory bowel disease (IBD)7(6). The
diversity and composition of the gut microbiota have been
reported to be influenced by age (7), genetics (8), and, most
importantly, diet (9). Dietary components resistant to host
enzymatic digestion are most likely to affect the gut microbiome
(10). The functional importance of the microbiota on human
physiology and disease suggests that the manipulation of these
communities through dietary intervention has therapeutic poten-
tial (11). The RDA for dietary fiber (DF) is 25–38 g/d, but a
majority of Americans consume only 12–18 g/d (12). The effects
of DF, resistant starch, and oligosaccharides on the gut micro-
as it pertains to gut microbiome shifts when novel soluble DF,
has been added to foods for many years, but its effects on the gut
microbiome have also been poorly studied.
PDX is a highly branched, randomly linked polysaccharide
made up of glucose units, with a degree of polymerization
between 3 and 10 and consists of different combinations of
a- and b-linked 1/2, 1/3, 1/4, and 1/6 glycosidic
linkages (17). SCF is made from corn starch and contains
oligosaccharides with random glycosyl bonds. Our previous
tolerance and utilization study data indicated that PDX and SCF
1Supported in part by General Mills, Inc., Minneapolis, MN.
2Author disclosures: J. M. Brulc, M. A. Staeger, and T. W. Boileau work for
General Mills Inc., which provided funding for the study. S. Hooda, B. M. Vester
Boler, M. C. R. Serao, S. E. Dowd, G. C. Fahey Jr, and K. S. Swanson, no conflicts
3Supplemental Table 1 is available from the “Online Supporting Material” link in
the online posting of the article and from the same link in the online table of
contents at http://jn.nutrition.org.
7Abbreviations used: BCFA, branched-chain fatty acids; DF, dietary fiber; IBD,
inflammatory bowel disease; NFC, no-fiber control; OTU, operational taxonomic
unit; PDX, polydextrose; PCA, principal component analysis; RO, resistant
oligosaccharide; SCF, soluble corn fiber.
* To whom correspondence should be addressed. E-mail: ksswanso@illinois.
ã 2012 American Society for Nutrition.
Manuscript received January 24, 2012. Initial review completed February 18, 2012. Revision accepted April 18, 2012.
First published online May 30, 2012; doi:10.3945/jn.112.158766.
by guest on December 26, 2015
Supplemental Material can be found at:
20. Ravussin Y, Koren O, Spor A, Leduc C, Gutman R, Stombaugh J,
Knight R, Ley RE, Leibel RL. Responses of gut microbiota to diet
composition and weight loss in lean and obese mice. Obesity (Silver
22. AACC. Approved methods. 8th ed. St. Paul: American Association of
Cereal Chemists; 1983.
23. Chaney AL, Marbach EP. Modified reagents for determination of urea
and ammonia. Clin Chem. 1962;8:130–2.
24. Yu Z, Morrison M. Improved extraction of PCR-quality community
DNA from digesta and fecal samples. Biotechniques. 2004;36:808–12.
25. Dowd SE, Sun Y, Wolcott RD, Domingo A, Carroll JA. Bacterial tag-
encoded FLX amplicon pyrosequencing (bTEFAP) for microbiome
studies: Bacterial diversity in the ileum of newly weaned salmonella-
infected pigs. Foodborne Pathog Dis. 2008;5:459–72.
26. Gontcharova V, Youn E, Wolcott RD, Hollister EB, Gentry TJ, Dowd
SE. Black Box Chimera Check (B2C2): a Windows-based software for
batch depletion of chimeras from bacterial 16S rRNA gene datasets.
Open Microbiol J. 2010;4:47–52.
27. Edgar RC. MUSCLE: a multiple sequence alignment method with reduced
time and space complexity. BMC Bioinformatics. 2004;5:113.
28. Felsenstein J. PHYLIP (Phylogeny Inference Package) version 3.6.
Department of Genome Sciences, University of Washington, Seattle;
2005 [cited January 2011]. Available from: http://evolution.genetics.
29. Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG. The
CLUSTAL_X windows interface: flexible strategies for multiple se-
quence alignment aided by quality analysis tools. Nucleic Acids Res.
30. Suchodolski JS, Xenoulis PG, Paddock CG, Steiner JM, Jergens AE.
Molecular analysis of the bacterial microbiota in duodenal biopsies
from dogs with idiopathic inflammatory bowel disease. Vet Microbiol.
White J, Kumar S, Dowd SE. Evaluation of the bacterial diversity of pressure
ulcers using bTEFAP pyrosequencing. BMC Med Genomics. 2010;3:41.
32. Jumpertz R, Le DS, Turnbaugh PJ, Trinidad C, Bogardus C, Gordon JI,
Krakoff J. Energy-balance studies reveal associations between gut
microbes, caloric load, and nutrient absorption in humans. Am J Clin
33. Momozawa Y, Deffontaine V, Louis E, Medrano JF. Characterization of
bacteria in biopsies of colon and stools by high throughput sequencing of the
34. Wu GD, Lewis JD, Hoffmann C, Chen YY, Knight R, Bittinger K, Hwang
J, Chen J, Berkowsky R, Nessel L, et al. Sampling and pyrosequencing
methods for characterizing bacterial communities in the human gut using
16S sequence tags. BMC Microbiol. 2010;10:206.
35. Dethlefsen L, Huse S, Sogin ML, Relman DA. The pervasive effects of
an antibiotic on the human gut microbiota, as revealed by deep 16S
rRNA sequencing. PLoS Biol. 2008;6:e280.
36. Ritchie LE, Steiner JM, Suchodolski JS. Assessment of microbial
diversity along the feline intestinal tract using 16S rRNA gene analysis.
FEMS Microbiol Ecol. 2008;66:590–8.
37. Louis P, Flint HJ. Diversity, metabolism and microbial ecology of
butyrate-producing bacteria from the human large intestine. FEMS
Microbiol Lett. 2009;294:1–8.
38. Hamer HM, Jonkers D, Venema K, Vanhoutvin S, Troost FJ, Brummer
RJ. Review article: the role of butyrate on colonic function. Aliment
Pharmacol Ther. 2008;27:104–19.
39. Ramirez-Farias C, Slezak K, Fuller Z, Duncan A, Holtrop G, Louis P.
Effect of inulin on the human gut microbiota: stimulation of Bifido-
bacterium adolescentis and Faecalibacterium prausnitzii. Br J Nutr.
40. Sokol H, Seksik P, Furet JP, Firmesse O, Nion-Larmurier I, Beaugerie L,
Cosnes J, Corthier G, Marteau P, Dore J. Low counts of Faecalibacte-
rium prausnitzii in colitis microbiota. Inflamm Bowel Dis. 2009;15:
41. Sokol H, Pigneur B, Watterlot L, Lakhdari O, Bermu ´dez-Humara ´n LG,
Gratadoux JJ, Blugeon S, Bridonneau C, Furet JP, Corthier G, et al.
Faecalibacterium prausnitzii is an anti-inflammatory commensal bacte-
rium identified by gut microbiota analysis of Crohn disease patients.
Proc Natl Acad Sci USA. 2008;105:16731–6.
42. Bassaganya-Riera J, DiGuardo M, Viladomiu M, de Horna A, Sanchez
S, Einerhand AW, Sanders L, Hontecillas R. Soluble fibers and resistant
starch ameliorate disease activity in interleukin-10-deficient mice with
inflammatory bowel disease. J Nutr. 2011;141:1318–25.
43. Devillard E, McIntosh FM, Duncan SH, Wallace RJ. Metabolism of
linoleic acid by human gut bacteria: different routes for biosynthesis of
conjugated linoleic acid. J Bacteriol. 2007;189:2566–70.
44. Claus SP, Ellero SL, Berger B, Krause L, Bruttin A, Molina J, Paris A,
Want EJ, de Waziers I, Cloarec O, et al. Colonization-induced host-gut
microbial metabolic interaction. MBio. 2011;2:e00271–10.
45. Martı ´nez I, Wallace G, Zhang C, Legge R, Benson AK, Carr TP,
Moriyama EN, Walter J. Diet-induced metabolic improvements in a
hamster model of hypercholesterolemia are strongly linked to alter-
ations of the gut microbiota. Appl Environ Microbiol. 2009;75:
46. Ridlon JM, Kang DJ, Hylemon PB. Bile salt biotransformations by
human intestinal bacteria. J Lipid Res. 2006;47:241–59.
47. Endo K, Kumemura M, Nakamura K, Fujisawa T, Suzuki K, Benno Y,
Mitsuoka T. Effect of high cholesterol diet and polydextrose supple-
mentation on the microflora bacterial enzyme activity, putrefactive
products, volatile fatty acids (VFA) profile, weight and pH of the feces.
Bifidobact Microflora. 1991;10:53–64.
48. Jie Z, Bang-yao L, Ming-Jie X, Hai-wei L, Zu-kang Z, Ting-song W,
Craig SAS. Studies on the effects of polydextrose intake on physiologic
functions in Chinese people. Am J Clin Nutr. 2000;72:1503–9.
49. Maathuis A, Hoffman A, Evans A, Sanders L, Venema K. The effect of
the indigested fraction of maize products on the activity and compo-
sition of the microbiota determined in a dynamic in vitro model of the
human proximal large intestine. J Am Coll Nutr. 2009;28:657–66.
50. Louis P, Duncan SH, McCrae SI, Millar J, Jackson MS, Flint HJ.
Restricted distribution of the butyrate kinase pathway among buty-
rate-producing bacteria from the human colon. J Bacteriol. 2004;186:
51. Duncan SH, Holtrop G, Lobley GE, Calder AG, Stewart CS, Flint HJ.
Contribution of acetate to butyrate formation by human faecal bacteria.
Br J Nutr. 2004;91:915–23.
52. Russell WR, Gratz SW, Duncan SH, Holtrop G, Ince J, Scobbie L,
Duncan G, Johnstone AM, Lobley GE, Wallace RJ, et al. High-protein,
reduced-carbohydrate weight-loss diets promote metabolite profiles
likely to be detrimental to colonic health. Am J Clin Nutr. 2011;93:
Novel fibers affect the human gut microbiome1265
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