454 Pyrosequencing Reveals a Shift in Fecal Microbiota of Healthy Adult Men Consuming Polydextrose or Soluble Corn Fiber

Article (PDF Available)inJournal of Nutrition 142(7):1259-65 · May 2012with38 Reads
DOI: 10.3945/jn.112.158766 · Source: PubMed
Abstract
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.

Figures

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 Fiber
1–3
Seema Hooda,
4
Brittany M. Vester Boler,
4
Mariana C. Rossoni Serao ,
4
Jennifer M. Brulc,
5
Michael A. Staeger,
5
Thomas W. Boileau,
5
Scot E. Dowd,
6
George C. Fahey Jr,
4
and Kelly S. Swanson
4
*
4
University of Illinois, Department of Animal Sciences, Urbana, IL;
5
General Mills, Inc., Bell Institute of Health and Nutrition,
Minneapolis, MN; and
6
MR DNA Molecular Research LP, Shallowater, TX
Abstract
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.
Introduction
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 associat ed
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-
biome have been well established (13–16). However, less is known
as it pertains to gut microbiome shifts when novel soluble DF,
such as soluble corn fiber (SCF), is consumed. Polydextrose (PDX)
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 consis ts of different comb inations 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
1
Supported in part by General Mills, Inc., Minneapolis, MN.
2
Author 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
of interest.
3
Supplemental 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.
* To whom correspondence should be addressed. E-mail: ksswanso@illinois.
edu.
7
Abbreviations 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.
ã 2012 American Society for Nutrition.
Manuscript received January 24, 2012. Initial review completed February 18, 2012. Revision accepted April 18, 2012.
1259
First published online May 30, 2012; doi:10.3945/jn.112.158766.
by guest on December 26, 2015jn.nutrition.orgDownloaded from
6.DC1.html
http://jn.nutrition.org/content/suppl/2012/06/22/jn.112.15876
Supplemental Material can be found at:
were fermentable fibers that, when consumed, led to a reduction
in fecal putrefactive compounds, increased stool bulk, and
increased fecal bifidobacteria concentrations with only slight
intestinal discomfort in a healthy adult human population (18).
Recently, development of high-throughput sequencing tech-
niques has accelerated our understanding of gut microbiome
diversity (19). Pyrosequencing allows a determination of the
entire phylogenetic spectrum, the taxonomic characterization,
and the flexibility to analyze populations at different taxonomic
levels. Thus, 16S rRNA gene-based barcoded pyrosequencing
has been extensively used for characterization of gut microbial
communities in healthy and diseased participants, including
morbidities such as obesity, type II diabetes, and IBD. These
methods also have been used to study the effects of dietary
intervention on the gut microbiome (2,3,14,20).
The objectives of the present study were to test the impact of
the fibers PDX and SCF on the composition of the human fecal
microbiota using 16S rRNA gene pyrosequencing and to identify
associations between microbiota and host physiological param-
eters. We hypothesized that the consumption of PDX or SCF
would beneficially alter gut microbial populations and fecal
metabolites compared with a NFC in a healthy adult human
population.
Participants and Methods
Participants. Healthy adult men (n = 25) were recruited via an e-mail
list from the C ollege of Agricultural, Consumer and Environmental
Sciences at the University of Illinois. Volunteers were assessed for
demographics and vital signs to ensure general health. Inclusion
criteria for the experime nt were as fol lows: 1) to be between 20 and 40
y of age; 2) to be free of know n metabolic and gastroint estinal diseases,
with no history of metabolic or gastroin testinal diseases; 3) t o avoid
taking medications that would impact gut function; 4)torefrainfrom
consuming pre- or probiotic supple ments during the entire duration of
the study; 5) to limit alcohol consumption to 2 ser vings/d; 6) to agree to
avoid any changes in chronic medications until the e nd of the stu dy; 7)
to agree to maintain t he same dosage of any mineral and vitamin
supplements consumed unti l completion of the study; 8)tomaintain
current level of exercise and physical act ivity; 9) to be wil ling t o
complete all necessary stud y questionnaires and to donate stool
specimens as require d; 10) to consume a moderate-fiber diet; and 11)
to voluntarily sign a written informed consent form before partici pa-
tion in the study.
Experimental design and treatments. The study protocol and
informed consent form were approved by the University of Illinois
Institutional Review Board prior to recruitment. This study was designed
as a randomized, double-blind, placebo-controlled crossover study and is
part of the tolerance and utilization study conducted by Vester Boler
et al. (18). Participants were randomly assigned to 1 of 3 treatments: 1)
no supplemental fiber control (NFC); 2) polydextrose (PDX; Litesse II,
Danisco); and 3) soluble corn fiber (SCF; PROMITOR, Tate and Lyle
Ingredients). There was no washout time between periods. Fibers were
incorporated into snack bars formulated to contain 7 g of supplemental
fiber each or no supplemented fiber and made of rice crisps and
manufactured by General Mills. The participants consumed 3 treatment
bars/d (one with each meal) for a total of ~0 g (NFC) or 21 g (PDX or
SCF) supplemental fiber per day. Macronutrient intake was assessed by
daily diet records and the ESHA Food Processor SQL computer software
program version 10.7.0 (ESHA Research). Each experimental period
consisted of 21 d, with a 16-d adaptation phase followed by 5 d of fecal
collection. Participants provided 3 fresh fecal samples (within 15 min of
defecation) on any day during the last 5 d of each treatment period.
Samples were collected using Commode Specimen Collection Systems
(Sage Products). Fresh samples were homogenized and immediately
stored at 2808C for DNA extraction.
The test bars were analyzed for moisture (AOAC 925.09), total fat
(AOAC 968.06), protein (AOAC 968.06; AACC 46.30.01), insoluble
DF (AOAC 2001.03 and 991.43), and total DF (AOAC 2001.03 and
991.43) (21,22). Resistant oligosaccharides (RO; AOAC 2001.03 and
991.43) and RO from fructans (AOAC 997.08) were determined
according to AOAC methods (21). Fecal acetate, propionate, butyrate,
isobutyrate, isovalerate, and valerate concentrations were determined
using a Hewlett-Packard 5890A Series II gas chromatograph (Palo Alto,
CA) and a glass column (180-cm 3 4-mm i.d.) packed with 10% SP-
1200–1%H
3
PO
4
on 80/100 + mesh Chromosorb WAW (Supelco). Fecal
ammonia concentrations were determined using spectrophotometry
according to the methods of Chaney and Marbach (23). Individual
concentrations of indoles and phenols were determined using a Hewlett-
Packard 5890A series II gas chromatograph and a Nukol fused-silica
capillary column (60-m 3 0.32-mm i.d.).
Fecal DNA extraction, pyrosequencing, and bioinformatics. Fecal
DNA extraction was done using a QIAamp DNA stool mini kit (Qiagen)
using the repeated bead beating plus column method (24). Fecal DNA
was quantified using a NanoDrop ND-1000 spectrophotometer (Nano-
Drop Technologies). Extracted DNA from the 3 fresh samples of each
participant per collection period were pooled in equimolar concentra-
tions (resulting in one sample per person per period), diluted to 20 ng in
1 mL, and genomic DNA quality assessed by electrophoresis using
precast E-Gel EX Gel 1% (Invitrogen). Amplification of a 600-bp
sequence in the variable region V4-V6 of the 16S rRNA gene was done
using barcoded primers as previously described (25). PCR of 25 mL were
performed for each sample using a barcoded forward primer (10 mmol/
L), barcoded reverse primer (10 mmol/L), dNTP mix (10 mmol/L),
FastStart 103 buffer with 18 mmol/L of MgCl
2
, FastStart HiFi
Polymerase (5 U in 1 mL), and 5 mL of genomic DNA. dNTP mix,
FastStart 103 buffer with MgCl
2
, and FastStart HiFi Polymerase were
included in the FastStart High Fidelity PCR System, dNTP Pack (Roche
Applied Science). The PCR conditions were: 948C for 3 min; 32 cycles of
948C for 15 s, 628C for 45 s, and 728C for a 1-min extension; followed by
728C for 8 min. After PCR, amplicons were further purified using
AMPure XP beads (Beckman-Coulter) to remove smaller fragments.
Further DNA concentration and quality were measured using a
NanoDrop ND-1000 spectrophotometer and electrophoresis, respec-
tively. Finally, the PCR amplicons were combined in equimolar ratios to
create a DNA pool (20 ng in 1 mL) that was used for pyrosequencing.
The quality of DNA was assessed before pyrosequencing using a 2100
Bioanalyzer (Agilent). Pyrosequencing of the PCR amplicons was
performed at the W. M. Keck Center for Biotechnology at the University
of Illinois using a 454 Genome Sequencer and FLX titanium reagents
(Roche Applied Science). After sequencing was completed, all reads were
scored for quality and any poor quality reads and primer dimers were
removed.
The sequences were selected to estimate total bacterial diversity of
DNA samples in a comparable manner and were trimmed to remove
barcodes, primers, chimeras, plastid, mitochondrial, any non-16S
bacterial reads, and sequences ,350 bp. Chimeras also were deleted
using Black Box Chimera Check (B2C2) (26). A total of 4500 6 100
rarified sequences from each sample were selected based on the highest
mean quality score, sequences were trimmed to 250 bp and aligned with
MUSCLE (27), the distance matrix was then calculated from the
alignment with PHYLIP (28). Operational taxonomic units (OTU) were
assigned by MOTHUR using the read.otu command (29). The maximum
observed rarefaction OTU values and rarefaction curves were created
using MOTHUR output (rarefaction.single command) as previously
described (30).
The bacterial ID community structure was evaluated using Phred25
quality reads, trimmed to remove tags and primer sequence collections,
then depleted of chimera, plastid and mitochondrial sequences with
ambiguous base calls, sequences with .6 bp homopolymer runs, and any
non-16S reads (,70% identity to any known high-quality 16S
sequence), and sequences ,250 bp. The final sequence data (500,588
total sequences; 8630 for each participant) were evaluated using Kraken
(www.krakenblast.com) against a 01–22–11 version database curated
from NCBI to include .350,000 high-quality 16S bacteria and archaeal
1260 Hooda et al.
by guest on December 26, 2015jn.nutrition.orgDownloaded from
sequences as well as quality control screening sequences for mitochon-
dria, plastid, and chloroplast screening sequences. Blast output based on
top hit designations were compiled to generate percentage files at each
taxonomic level as previously described (26,31).
Statistical analyses. Data presented as percentage of sequences at each
taxonomic level were analyzed using the Mixed Models procedure of
SAS (version 9.2; SAS Institute) using each subject as an experimental
unit. Data were tested for normality using the UNIVARIATE procedure
of SAS. The statistical model included the fixed effec t of treatment,
and period and subject as random effects. Means we re separated
for treatments using a Fisher-protected least significant difference with
Tukey adjustment. Results were reported as least square means with
SEM P , 0.05 defined as significant. Principal component analysis
(PCA) of abundance of important bacterial families, macronutrient
intake, and fecal fermentative end-products, including ammonia, phe-
nol, indole, SCFA, and branched-chain fatty acids (BCFA) was done
using JMP software of SAS, with score and loading plots generated.
Results
The total number of fecal samples analyzed for fermentative
end-products per period was reduced to 21, because 2 partic-
ipants moved away, one participant started medication re-
stricted by this study, and one participant had aberrant fecal
patterns (.3 watery stools/d). Twenty fecal samples were used
for microbiome analyses, because one sample had low fecal
DNA quality. The complete detailed description of the partic-
ipants (age = 27.5 6 4.33 y old; body weight = 86.2 6 13.48 kg;
BMI = 27 6 4.02) and their macronutrient intakes for each
treatment group has been described by Vester Boler et al. (18). In
brief, macronutrient intakes including protein (;90 g/d; 19% of
energy), fat (;75 g/d; 35% of energy), carbohydrate (;230 g/d;
19% of energy), and DF (;14.7 g/d) did not differ among
treatments (P . 0.05). The test bars were very similar in
chemical composition, except that the PDX and SCF bars
contained RO (PDX = 7.6 g/bar; SCF = 7.2 g/bar) (18). Ingested
PDX and SCF led to lower (P , 0.05) fecal protein-based
fermentative end-products, including ammonia, phenol, indole,
and total BCFA (18) (Supplemental Table 1). Fecal acetate,
propionate, and butyrate concentrations were lower (P , 0.05)
when participants consumed PDX compared with those who
consumed SCF (18) (Supplemental Table 1). Fecal pH was lower
(P , 0.05) when participants consumed SCF (6.2) compared
with NFC (6.4) (18). SCF intake led to greater (P , 0.05) fecal
Bifidobacterium spp. concentrations (8.2 log CFU/g dry matter
feces) compared with NFC (6.9 log CFU/g dry matter feces)
using qPCR (18). Given those outcomes, we were interested in
using high-throughput sequencing to evaluate the effects on the
entire fecal microbiota population.
Human gut microbiota. Pyrosequencing of 16S rRNA gene
barcoded amplicons resulted in a total of 500,588 high-quality
sequences, wi th a mean of 8630 sequences (range = 5739–
8899) per sample. The OTU, abundance-based coverage
estimation, and bias-corrected Chao 1 richness estimate indi-
cations of diversity did not differ among treatments (Supple-
mental Table 2). Similarly, the tested fibers did not have a
significant effect on the Shannon Index, which indicates that
the consumption of PDX and SCF did not alter overall fecal
bacterial diversity.
Firmicutes was the most abundant bacterial phyla (;93%) in
all participants, with no differences among treatments (Table 1).
Other predominant bacterial phyla detected were Actinobac-
teria, Proteobacteria, Verrucomicrobia, and Bacterioidetes. The
abundance of Actinobacteria was lower when men consumed
PDX and SCF than when they consumed NFC (P , 0.05). In
contrast, SCF intake resulted in a greater (P , 0.05) proportion
of fecal Proteobacteria than NFC and PDX. Fecal Verrucomi-
crobia abundance was greater when participants consumed PDX
than when they consumed SCF (P , 0.05), but neither was
different from NFC.
Among the Firmicutes, the Clostridia class constituted ;90%
of sequences, being dominated by the Ruminococcaceae,
Clostridiaceae, Lachnospiraceae, and Eubacteriaceae families
(Table 1). Ruminococcaceae was the most abundant family
during all treatments, whereas Clostridiaceae and Veillonella-
ceae were greater ( P , 0.05) when the participants consumed
PDX or SCF than when they consumed NFC. In contrast,
Lachnospiraceae
was lower (P , 0.05) when participants
consumed PDX than when they consumed NFC or SCF. Fecal
Eubacteriaceae was lower (P , 0.05) when participants
consumed PDX or SCF than when they consumed NFC.
Interestingly, the abundance of Lactobacillaceae, which consti-
tutes a well-known probiotic species, was higher (P , 0.05) in
participants when they consumed SCF than when they had PDX
or NFC. Within the phylum Actinobacteria, the proportion of
the Bifidobacteriaceae and Coriobacteriaceae families were
lower (P , 0.05) in participants when they consumed PDX or
SCF compared with when they consumed NFC. Furthermore,
PDX intake resulted in lower (P , 0.05) fecal Hyphomicrobia-
ceae, a family of Proteobacteria, compared with NFC. The abun-
dance of fecal Alcaligenaceae, another family within Proteobacteria,
TABLE 1 Bacterial phyla and families in feces of healthy adult
men who consume NFC, PDX, or SCF, each for 21 d,
as determined by 16S rRNA gene pyrosequencing
1
Treatment
Item NFC PDX SCF Pooled SEM
% of sequences
Firmicutes 93.2 92.7 94.5 1.35
Ruminococcaceae 40.7 40.1 38.5 1.70
Clostridiaceae 10.1
a
14.9
b
16.2
b
1.19
Clostridiales
2
11.9 11.6 10.9 1.26
Lachnospiraceae 13.0
b
10.9
a
13.1
b
1.02
Eubacteriaceae 11.5
b
7.24
a
6.34
a
1.20
Veillonellaceae 2.68
a
5.17
b
6.15
b
0.69
Erysipelotrichaceae 2.01 1.78 1.71 0.68
Oscillospiraceae 0.39 0.44 0.34 0.12
Lactobacillales
3
0.22
b
0.10
a
0.08
a
0.04
Lactobacillaceae 0.31
a
0.28
a
0.48
b
0.11
Actinobacteria 3.45
b
1.55
a
1.86
a
0.62
Bifidobacteriaceae 2.55
b
1.25
a
1.61
a
0.58
Coriobacteriaceae 0.91
b
0.31
a
0.26
a
0.14
Proteobacteria 1.74
a
1.75
a
2.82
b
0.30
Enterobacteriaceae 0.19 0.04 0.27 0.11
Hyphomicrobiaceae 0.89
b
0.61
a
0.68
ab
0.17
Alcaligenaceae 0.42
a
0.81
a
1.44
b
0.29
Verrucomicrobia 1.08
ab
3.54
b
0.41
a
1.20
Verrucomicrobiaceae 1.08
ab
3.54
b
0.41
a
1.21
Bacteroidetes 0.45 0.34 0.43 0.10
Bacteroidaceae 0.19 0.23 0.23 0.03
1
Values are least square means and pooled SEM, n = 20. Means in a row with
superscripts without a common letter differ, P , 0.05. NFC, nonfiber control; PDX,
polydextrose; SCF, soluble corn fiber.
2
Unknown family within order Clostridales.
3
Unknown family within order Lactobacillales.
Novel fibers affect the human gut microbiome 1261
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was greater (P , 0.05) in participants when they consumed SCF
compared with when they consumed NFC or PDX. In contrast,
the abundance of fecal Verrucomicrobiaceae was greater (P ,
0.05) in participants when they consumed PDX compared with
SCF.
Among the well-characterized genera within the phyla
Firmicutes, Faecalibacterium, Ruminococcus, Eubacterium,
Clostridium, Roseburia, Subdoligranulum, Oscillospira, Phas-
colarctobacterium, Akkermansia, Dorea, Dialister, Coprococcus,
and Lactobacillus were predominant during all 3 treatments
(Table 2). The proportion of fecal Faecalibacterium, unknown
genera within Clostridiaceae, Phascolar ctobacterium, and
Dialister were greater (P , 0.05) in participants when they
consumed PDX or SCF compared with when they consumed
NFC. Fecal Clostridium and Akkermansia were greater (P ,
0.05) after PDX intake than after the NFC or SCF treatment.
Fecal Lactobacillus was greater ( P , 0.05) after SCF intake
compared with NFC and PDX intakes. In contrast, PDX and
SCFconsumptionledtolower(P , 0.05) Ruminococcus,
Eubacterium, Dorea, and Coprococcus abundance compared
with NFC. Fecal Oscillospira abundance was lower (P ,
0.05) in participants when they consumed SCF than when
they consumed NFC or PDX. Fecal Bifidobacterium and
Coriobacterium abundance was lower (P , 0.05) in partic-
ipants after consumption of PDX or SCF compared with NFC
Fecal Faecalibacterium prausnitzii, well known for its anti-
inflammatory properties, was greater (P , 0.05) in participants
when they consumed PDX or SCF than when they consumed
NFC (Table 3). In contrast, fecal Ruminococcus spp., Eubacte-
rium rectale, Eubacterium halii,andBifidobacterium spp. propor-
tions were lower (P , 0.05) in participants when they consumed
PDX or SCF compared with when they consumed NFC. Fecal
Clostridium leptum was greater (P , 0.05) in participants after
intake of PDX than with SCF or NFC intake. Fecal
Roseburia
spp.
abundance was greater (P , 0.05) only when participants
consumed SCF than when they consumed PDX.
PCA. The PCA of macronutrient intake; fecal fermentative end-
products, including ammonia, phenol, indole, SCFA, and BCFA;
and the proportion of the primary bacterial families present in
feces are shown as score and loading plots in Figure 1. The PC1
and PC2 explained 21.2 and 15.2% of variation, respectively.
The score plot clearly indicated a distinct separation or
clustering of participants consuming PDX or SCF compared
with those consuming NFC. Although individual differences
were noted and the overall microbiome was relatively stable
over time, dietary effects were observed in all participants
studied. The loading plot indicated 3 main clusters. The first
cluster, which included total and individual macronutrient
intake (protein, fat, carbohydrate) and fecal Clostridiaceae,
Clostridales, Bacteroidaceae, and Alcaligenaceae, was positively
affected by PC2 and negatively affected by PC1. The second
cluster, which consisted of fecal acetate, propionate, butyrate,
total SCFA, Lachnospiraceae, Ruminococcaceae, Eubacteria-
ceae, and Lactobacillaceae, was positively affected by PC1 and
negatively by PC2. A third cluster that included fecal BCFA,
ammonia, phenol, indoles, Hyphomicrobiaceae, and Coriobac-
teriaceae was positively affected by both PC1 and PC2 and
negatively correlated with the second cluster.
Discussion
This study was conducted to determine the impact of 2 novel
fibers, PDX and SCF, on fecal microbial community composition
using high-throughput sequencing. This technique allows the
TABLE 2 Bacterial genera in feces of healthy adult men who
consumed NFC, PDX, or SCF, each for 21 d, as
determined by 16S rRNA gene pyrosequencing
1
Treatment
Item NFC PDX SCF Pooled SEM
% of sequences
Firmicutes
Faecalibacterium 20.7
a
24.1
b
25.5
b
2.60
Ruminococcus 13.1
b
9.22
a
7.68
a
0.92
Eubacterium 11.8
b
7.55
a
6.87
a
1.27
Clostridiaceae
2
1.96
a
5.32
b
8.02
b
0.99
Clostridium 8.11
a
9.50
b
8.26
a
0.73
Roseburia 8.77
ab
7.42
a
9.78
b
0.98
Subdoligranulum 4.42 4.18 3.84 0.66
Oscillospira 2.19
b
2.28
b
1.44
a
0.57
Phascolarctobacterium 1.51
a
2.30
b
2.80
b
0.50
Akkermansia 1.08
a
3.54
b
0.41
a
1.21
Dorea 1.40
b
0.69
a
0.72
a
0.20
Dialister 0.97
a
2.35
b
2.87
b
0.79
Coprococcus 0.58
b
0.42
a
0.36
a
0.09
Lactobacillus 0.30
a
0.27
a
0.47
b
0.11
Actinobacteria
Bifidobacterium 2.54
b
1.25
a
1.60
a
0.57
Coriobacterium 0.76
b
0.23
a
0.22
a
0.14
Bacteroidetes
Bacteroides 0.19 0.23 0.23 0.03
1
Values are least square means and pooled SEM, n = 20. Means in a row with
superscripts without a common letter differ, P , 0.05. NFC, nonfiber control; PDX,
polydextrose; SCF, soluble corn fiber.
2
Unknown genera within family Clostridiaceae.
TABLE 3 Bacterial species in feces of healthy adult men who
consumed NFX, PDX, or SCF, each for 21 d, as
determined by 16S rRNA gene pyrosequencing
1
Treatment
Item NFC PDX SCF Pooled SEM
% of sequences
Faecalibacterium spp.
2
12.2 12.7 13.5 1.56
Faecalibacterium prausnitzii 8.57
a
11.4
b
12.1
b
1.52
Clostridiales spp. 11.0 10.9 10.1 1.27
Clostridiaceae spp. 1.96
a
5.32
b
8.02
b
0.99
Clostridium spp. 5.57 6.87 5.57 0.72
Clostridium leptum 0.32
a
0.82
b
0.66
a
0.12
Ruminococcus spp. 9.83
b
6.61
a
5.52
a
0.74
Ruminococcus bromii 1.17 1.14 0.99 0.32
Eubacterium rectale 8.78
b
4.81
a
4.42
a
1.27
Eubacterium hallii 0.55
b
0.39
a
0.30
a
0.08
Roseburia spp. 4.68
a
4.26
a
6.45
b
0.50
Roseburia intestinalis 2.49 2.00 2.01 0.63
Roseburia faecis 1.27 0.91 0.95 0.27
Subdoligranulum spp. 3.28 3.20 0.99 0.67
Bifidobacterium spp. 1.90
b
0.91
a
1.12
a
0.42
1
Values are least square means and pooled SEM, n = 20. Means in a row with
superscripts without a common letter differ, P , 0.05. NFC, nonfiber control; PDX,
polydextrose; SCF, soluble corn fiber.
2
Proportion of bacteria denoted with ‘‘spp.’’ do not include the known members.
1262 Hooda et al.
by guest on December 26, 2015jn.nutrition.orgDownloaded from
comparison of changes at various taxonomic levels and reveals
bacterial shifts as a result of novel fiber consumption. To our
knowledge, this is the first study to exploit 16S rRNA gene-
based pyrosequencing to test the impact of PDX and SCF on the
fecal microbiome of healthy adult human participants.
The predominant bacterial phylum present in all human fecal
samples was Firmicutes (;93%), followed by Actinobacteria
and Bacteroidetes. The relative abundance of Firmicutes was
greater than that reported in recent human experiments pertaining
to gut health (14,32,33). These differences may be attributed to
many variables, including differences in fecal sampling methods,
DNA extraction and PCR amplification methods, and the variable
regions of 16S rRNA gene analyzed among experiments (34).
Moreover, the differences in age, ethnicity, genetics, and living
environments of individuals across studies also may contribute
to the development of the gut microbiota and cannot be ignored.
Differences in Firmicutes abundance may also have been due to
the different DNA extraction techniques used (24). In contrast,
the abundance of Bacteroidetes and Actinobacteria (and thus
Bifidobacterium) appeared to be underestimated using our 16S
rRNA gene-based approach, which was previously reported in
humans and animals (35,36). Thus, it is not appropriate to
compare the absolute results among studies and make strong
conclusions about less abundant groups.
Among the Firmicutes, the families Ruminococcaceae,
Lachnospiraceae, and Eubacteriaceae contain members that
are important to DF degradation and are producers of SCFA
(15,37). The SCFA not only serve as energy for the colonic
epithelium but also as nutrients systemically. Butyrate is a major
source of energy to colonocytes and an important link to gut
health via stimulation of cell proliferation, promotion of apopto-
sis, and prevention of colon cancer (38). Decreased abundance
of fecal Lachnospiraceae and Eubacteriaceae after consumption
of PDX may explain the lower fecal butyrate concentrations
observed in our study (18).
An interesting result of this study was that genus Faecali-
bacterium, and specifically Faecalibacterium prausnitzii, a well-
known butyrate producer with strong antiinflammatory prop-
erties (10), was greater in participants consuming PDX and SCF.
Increased F. prausnitzii also has been reported in human
volunteers following the ingestion of inulin (39). Fecal butyrate
concentrations did not necessarily correlate with F. prausnitzii
abundance in our participants. Because the majority of SCFA are
rapidly absorbed by the colonic epithelia, however, fecal SCFA
concentrations are not a strong indicator of production in the
colon. Moreover, because F. prausnitzii has been reported to
influence gut inflammation via butyrate-independent antiinflam-
matory effects (40), the focus on butyrate may not be appro-
priate. F. prausnitzii has gained considerable attention in recent
years, because it has been related with active IBD, with IBD
patients having lower fecal concentrations than healthy controls
(40). Similar reports of low F. prausnitzii abundance have been
reported in Crohn’s disease patients that exhibited endoscopic
recurrence 6 mo after surgery (41). Given these results, if
dysbiosis can be corrected, F. prausnitzii may be a promising
probiotic agent in IBD prevention. The benefits of SCF intake
were previously demonstrated, with suppressed gut inflamma-
tion reported in SCF-fed compared with control mice with IBD
(42). Although, the beneficial response to SCF was proposed to
be through its antiinflammatory effects on gut mucosa, the
changes mediated via the gut microbiota, especially Faecalibac-
terium, were not measured (42).
A higher prevalence of another major butyrate producer,
Roseburia spp., with SCF was observed. Roseburia spp. also
have a high capacity to form conjugated linoleic acid from
linoleic acid, which exhibits known health benefits in humans
(43).
The family Coriobacteriaceae has been strongly linked with
increased hepatic TG, glycogen, and glucose in mice (44). A
study performed on hamsters reported a strong positive corre-
lation between unidentified bacteria of the Coriobacteriaceae
family and non-HDL plasma cholesterol and cholesterol ab-
sorption (45). This metabolic link has been proposed to be
related to the capability of Coriobacteriaceae to transform bile
acids and thus affect cholesterol metabolism (46). Interestingly,
FIGURE 1 PCA score plot (A) and loading plot (B) of the primary
fecal bacterial families and metabolites of interest in 20 healthy adult
men consuming NFC or 21 g/d of PDX or SCF. The score and loading
plots indicate relationships among observations and variables, respec-
tively. 1, Clostridiaceae; 2, Clostridiales; 3, Bacteroidaceae; 4, Veillo-
nellaceae; 5, Ruminococcaceae; 6, Bifidobacteriaceae; 7,
Lachnospiraceae; 8, Eubacteriaceae; 9, Coriobacteriaceae; 10, Alcali-
genaceae; 11, Hyphomicrobiaceae; 12, Lactobacillaceae; 13, total
dietary fiber; 14, total food intake; 15, total energy intake; 16, protein
intake; 17, carbohydrate intake; 18, total fat intake; 19, saturated fat
intake; 20, fecal ammonia; 21, fecal phenol; 22, fecal indole; 23, fecal
acetate; 24, fecal propionate; 25, fecal isobutyrate; 26, fecal butyrate;
27, fecal isovalerate; 28, fecal valerate; 29, fecal total SCFA; 30, fecal
total BCFA. BCFA, branched-chain fatty acids; NFC, no-fiber control;
PCA, principal component analysis; PDX, polydextrose; SCF, soluble
corn fiber.
Novel fibers affect the human gut microbiome 1263
by guest on December 26, 2015jn.nutrition.orgDownloaded from
Coriobacteriaceae were present at ,1% of all bacteria in our
study, highlighting the importance of groups present in low
proportions on host metabolism. It is noteworthy that in our
study, Coriobacteriaceae were lower in participants consuming
PDX and SCF compared with NFC.
The greater abundance of the Lactobacillus genus in partic-
ipants consuming SCF also was noteworthy, because strains
of this group are often used as a probiotic and are associated
with beneficial effects on the gut in both healthy and diseased
populations. Our results on Lactobacillus, Bifidobacterium,
Bacteroides, and Ruminococcus bromii are in contrast with
previous literature. For example, other researchers have dem-
onstrated that the intake of PDX decreases Bacteroides species
and lecithinase-negative clostridia and increases Lactobacillus
and Bifidobacterium species compared with a control group
(47,48). Similarly, others have demonstrated that SCF stimulates
the growth of bifidobacteria and reduces species of the Bacte-
roides and Ruminococcus bromii when using an in vitro model
of the human proximal large intestine (49).
The significant microbial shift in the gut microbial commu-
nities may due to oligosaccharide fermentation by microbes per
se and, thus, substrate preference or metabolic cross-feeding.
The decrease in Eubacterium rectale with PDX and SCF may be
linked to substrate preference and this species has been linked to
degradation of resistant starch (14). Acetate is the predominant
product of fiber fermentation but also may be converted to
butyrate by several bacterial species (50). The conversion of
acetate to butyrate by Roseburia spp. and F. prausnitzii with the
enzyme butyryl-CoA : acetate-CoA transferase has been demon-
strated in pure culture (51) and highlights the role of metabolic
cross-feeding. A recent in vitro study suggested that gut microbes
prefer branched, especially single-branched, 1/6 linked PDX
molecules (17). However, the detailed mechanism of fermenta-
tion of PDX and SCF is unknown.
The PCA score plot supports the hypothesis that the overall
composition of the gut microbial communities and fermentative
metabolites in human participants consuming novel fibers were
distinctly different from those of NFC. The loading plot showed
distinct separation of total SCFA, products primarily derived
from carbohydrate fermentation, and metabolites of protein
fermentation. This negative correlation further supports the
hypothesis that intake of DF can counteract the adverse effects
of protein fermentation (52). Furthermore, the strong correla-
tion between total fecal SCFA and Lachnospiraceae suggests that
this family was one of the major producers of SCFA in our
human participants (15,37).
The numbers of participants (n = 20), use of double-blinded
crossover design, rather deep 16S rRNA gene pyrosequencing,
and measurement of digestive physiological outcomes highlight
the strengths of this study. However, the authors acknowledge
the potential limitations of the study, including the lack of blood
measurements such as glucose, cholesterol, and TG and the lack
of washout periods between treatments.
In conclusion, this study analyzed bacterial 16S rRNA gene
and clearly demonstrated a significant impact of PDX and SCF
on the composition of the gut bacterial microbiome. Our data
suggest PDX and SCF consumption at physiological dietary
concentrations led to beneficial shifts in fecal microbiota,
primarily in the Firmicutes phyla. The health-promoting effects
resulting from changes in fecal Veillonellaceae, Coriobacteria-
ceae, and F. prausnitzii from novel fiber consumption could be
used to correct or prevent dysbiosis in certain diseases and thus
supports the potential application of these novel fibers as
prebiotics in human nutrition.
Acknowledgments
S.H., B.M.V.B., J.M.B., M.A.S., T.W.B., G.C.F., and K.S.S.
designed research; S.H., B.M.V.B., and M.C.R.S. conducted
research; J.M.B., M.A.S., and T.W.B. provided essential materials
for research; S.H. and S.E.D. analyzed data; S.H. and K.S.S.
wrote the paper; and K.S.S. had primary responsibility for final
content. All authors read and approved the final manuscript.
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    • "The Lactobacillaceae family comprises well-known probiotic bacteria that are generally recognized as safe and are highly adapted to the GI environment (Etzold et al., 2014), which improve overall GI integrity and functionality. This family is described as the energy-generating machinery in humans and animals by increasing the levels of short-chain fatty acids, particularly acetate, propionate and butyrate, in the gut (Hooda et al., 2012; Guerra-Ordaz et al., 2014 ). In a previous study, the synbiotic mixture of L. plantarum and lactulose produced different effects on the microbial populations in pigs (Guerra-Ordaz et al., 2014 ). "
    [Show abstract] [Hide abstract] ABSTRACT: Demand for the development of non-antibiotic growth promoters in animal production has increased in recent years. This report compared the faecal microbiota of weaned piglets under the administration of a basal diet (CON) or that containing prebiotic lactulose (LAC), probiotic Enterococcus faecium NCIMB 11181 (PRO) or their synbiotic combination (SYN). At the phylum level, the Firmicutes to Bacteroidetes ratio increased in the treatment groups compared with the CON group, and the lowest proportion of Proteobacteria was observed in the LAC group. At the family level, Enterobacteriaceae decreased in all treatments; more than a 10-fold reduction was observed in the LAC (0.99%) group compared with the CON group. At the genus level, the highest Oscillibacter proportion was detected in PRO, the highest Clostridium in LAC and the highest Lactobacillus in SYN; the abundance of Escherichia was lowest in the LAC group. Clustering in the discriminant analysis of principal components revealed distinct separation of the feeding groups (CON, LAC, PRO and SYN), showing different microbial compositions according to different feed additives or their combination. These results suggest that individual materials and their combination have unique actions and independent mechanisms for changes in the distal gut microbiota.
    Full-text · Article · Jun 2016
    • "Reproducibility of extraction can also be an issue, particularly in livestock faecal samples, which can have a high degree of heterogeneity due to the faecal matrix, particularly where diet is varied. The development of next-generation sequencing (NGS) provides a powerful tool to increase depth and resolution of community analysis [7] and NGS has been applied for microbial profiling of faecal sample from humans141516 or animals such as swine [5], white rhinoceros [17] and horses [18] . Due to its enhanced depth and resolution, NGS techniques can be more influenced or likely to detect artefacts due to DNA extraction methods, and hence analysis of the impacts of extraction is an important consideration. "
    [Show abstract] [Hide abstract] ABSTRACT: Recovery of high quality PCR-amplifiable DNA has been the general minimal requirement for DNA extraction methods for bulk molecular analysis. However, modern high through-put community profiling technologies are more sensitive to representativeness and reproducibility of DNA extraction method. Here, we assess the impact of three DNA extraction methods (with different levels of extraction harshness) for assessing hindgut microbiomes from pigs fed with different diets (with different physical properties). DNA extraction from each sample was performed in three technical replicates for each extraction method and sequenced by 16S rRNA amplicon sequencing. Host was the primary driver of molecular sequencing outcomes, particularly on samples analysed by wheat based diets, but higher variability, with one failed extraction occurred on samples from a barley fed pig. Based on these results, an effective method will enable reproducible and quality outcomes on a range of samples, whereas an ineffective method will fail to generate extract, but host (rather than extraction method) remains the primary factor.
    Full-text · Article · Nov 2015
    • "Abnormally low levels of Veillonellaceae and Dialister have been described in autistic children (Kang et al., 2013) and patients of Crohn's disease (Joossens et al., 2011). Dietary whole grain intervention (Martinez et al., 2013) and corn fiber (Hooda et al., 2012) increased the Dialister and Veillonellaceae abundance. The genus Oscillospira has been associated with lean BMI (Tims et al., 2013). "
    [Show abstract] [Hide abstract] ABSTRACT: It has been suggested that gut microbiota is altered in Type 2 Diabetes Mellitus (T2DM) patients. This study was to evaluate the effect of the prebiotic xylooligosaccharide (XOS) on the gut microbiota in both healthy and prediabetic (Pre-DM) subjects, as well as impaired glucose tolerance (IGT) in Pre-DM. Pre-DM (n = 13) or healthy (n = 16) subjects were randomized to receive 2 g/day XOS or placebo for 8-weeks. In Pre-DM subjects, body composition and oral glucose tolerance test (OGTT) was done at baseline and week 8. Stool from Pre-DM and healthy subjects at baseline and week 8 was analyzed for gut microbiota characterization using Illumina MiSeq sequencing. We identified 40 Pre-DM associated bacterial taxa. Among them, the abundance of the genera Enterorhabdus, Howardella, and Slackia was higher in Pre-DM. XOS significantly decreased or reversed the increase in abundance of Howardella, Enterorhabdus, and Slackia observed in healthy or Pre-DM subjects. Abundance of the species Blautia hydrogenotrophica was lower in pre-DM subjects, while XOS increased its abundance. In Pre-DM, XOS showed a tendency to reduce OGTT 2-h insulin levels (P = 0.13), but had no effect on body composition, HOMA-IR, serum glucose, triglyceride, satiety hormones, and TNFα. This is the first clinical observation of modifications of the gut microbiota by XOS in both healthy and Pre-DM subjects in a pilot study. Prebiotic XOS may be beneficial in reversing changes in the gut microbiota during the development of diabetes. NCT01944904 (https://clinicaltrials.gov/ct2/show/NCT01944904).
    Full-text · Article · Sep 2015
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