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Resistant starch reduces large intestinal pH and promotes fecal
lactobacilli and bifidobacteria in pigs
B. U. Metzler-Zebeli
1†
, N. Canibe
2
, L. Montagne
3
, J. Freire
4
, P. Bosi
5
, J. A. M. Prates
6
,
S. Tanghe
7
and P. Trevisi
5
1
Institute of Animal Nutrition and Functional Plant Compounds, Department for Farm Animals and Veterinary Public Health, Vetmeduni Vienna, 1210 Vienna,
Austria;
2
Department of Animal Science, Aarhus University, 8830 Tjele, Denmark;
3
PEGASE, Agrocampus Ouest, INRA, 35590, Saint-Gilles, France;
4
LEAF, Instituto
Superior de Agronomia, University of Lisbon, Tapada da Ajuda, 1349-017 Lisbon, Portugal;
5
Department of Agricultural and Food Science (DISTAL), University of
Bologna, 40127 Bologna, Italy;
6
CIISA, Faculty of Veterinary Medicine, University of Lisbon, Avenida da Universidade Técnica, Alto da Ajuda, 1300-477 Lisbon,
Portugal;
7
Nutritional Solutions Divisions, Nutrition Sciences N.V., 9031 Ghent, Belgium
(Received 5 October 2017; Accepted 26 March 2018; First published online 10 May 2018)
Dietary resistant starch (RS) may have prebiotic properties but its effects on fermentation and the microbial population are
inconsistent. This meta-analysis aimed to quantify the relationship between RS type 2 (RS2) and intestinal short-chain fatty acids
(SCFA) and pH as well as certain key bacterial taxa for intestinal health in pigs. From the 24 included articles with sufficient
information about the animal, and dietary and physiological measurements published between 2000 and 2017, individual sub-data
sets for fermentation metabolites, pH, bacterial abundances and apparent total tract digestibility were built and used to
parameterize prediction models on the effect of RS2, accounting for inter- and intra-study variability. In addition, the effect of pig’s
BW at the start of the experiment and duration of the experimental period on response variables were also evaluated using
backward elimination analysis. Dietary RS levels ranged from 0% to 78.0% RS, with median and mean RS levels of 28.8% and
23.0%, respectively. Negative relationships could be established between dietary RS and pH in the large intestine (
P
<0.05), with a
stronger effect in the mid and distal colon, and feces (
R
2
=0.64 to 0.81;
P
<0.001). A dietary level of 15% RS would lower the
pH in the proximal, mid-, distal colon and feces by 0.2, 0.6, 0.4 and 0.6 units, respectively. Increasing RS levels, however, did not
affect SCFA concentrations in the hindgut, but enhanced the molar proportion of propionate in mid-colon and reduced those of
acetate in mid-colon and of butyrate in mid- and distal colon (
R
2
=0.46 to 0.52;
P
<0.05). Backward elimination indicated an
age-related decrease in mid-colonic propionate proportion and increase in mid- and distal colonic butyrate proportion (
P
<0.05),
thereby modulating RS2 effects. In feces, increasing RS levels promoted fecal lactobacilli (
R
2
=0.46;
P
<0.01) and bifidobacteria
(
R
2
=0.57;
P
<0.01), whereby the slope showed the need for a minimal RS level of 10% for a 0.5 log unit-increase in their
abundance. Best-fit equations further supported that a longer experimental period increased fecal lactobacilli but decreased fecal
bifidobacteria (
P
<0.05). In conclusion, dietary RS2 seems to effectively decrease digesta pH throughout the large intestine and
increase lactic acid-producing bacteria in feces of pigs which may limit the growth of opportunistic pathogens in the hindgut. To
achieve these physiologically relevant changes, dietary RS should surpass 10% to 15%.
Keywords: resistant starch type 2, gastrointestinal tract, meta-analysis, lactic acid-producing bacteria, short-chain fatty acids
Implications
Dietary resistant starch (RS) can negatively impact the
energetic efficiency in pigs. By contrast, RS forms a type of
dietary fiber that may affect the host beneficially by stimu-
lating intestinal fermentation. The present meta-regressions
support the capacity of RS type 2 to decrease hindgut pH,
shift the fermentation profile to more propionate in the
mid-colon and to support growth of lactic acid-producing
bacteria in the distal hindgut. Increasing the RS level in pig’s
diet may be used to stabilize the intestinal homeostasis
especially post-weaning and in the early growing period.
Introduction
Starchy feedstuffs represent the largest fraction of pig diets.
However, dietary starches from different sources are digested
at different rates and to different extents depending on the
†
E-mail: barbara.metzler@vetmeduni.ac.at
Animal
(2019), 13:1,pp64–73 © The Animal Consortium 2018
doi:10.1017/S1751731118001003
animal
64
source of starch, feed processing and animal related factors
(Giuberti et al., 2015). The rate, extent and gastrointestinal
site where the starch is degraded will cause different
physiological effects related to nutrient absorption, meta-
bolic response and pig performance (Regmi et al., 2011;
Haenen et al., 2013; Metzler-Zebeli et al., 2015a and 2015b).
The starch digestibility in feedstuffs ranges from rapidly
digestible to resistant to
α
-amylase digestion in the small
intestine. The RS fraction is regarded as a type of dietary fiber
and has received substantial attention in human (Birt et al.,
2013) and pig nutrition (Giuberti et al., 2015). As it escapes
digestion in the small intestine, RS serves as substrate for
fermentation in the hindgut and has been associated with
increased digesta mass, short-chain fatty acids (SCFA)
production and stimulation of amylolytic and butyrogenic
bacteria (Birt et al., 2013). Despite potential health benefits
mediated via the action of SCFA (especially butyrate) such as
ameliorated intestinal integrity and immunity, the dietary RS
fraction has a controversial status in pig nutrition due to its
potential negative impact on energetic efficiency and hence
animal growth (Giuberti et al., 2015). Like other types of
dietary fiber, RS may exert prebiotic effects and may be
considered a functional dietary ingredient rather than an
energy feedstuff (Bird et al., 2009; Nielsen et al., 2014). As
such, RS may contribute to an improved intestinal homeo-
stasis and disease resistance, thereby supporting growth
performance in weaned and growing pigs. Yet, reported
effects of RS on fermentation metabolites, such as SCFA, in
pigs are inconsistent (Bird et al., 2009; Regmi et al., 2011;
Nielsen et al., 2014) which may be associated with factors
like source and inclusion level of RS, feed composition and
the age of the animal. Currently, five different types of RS
have been described (Birt et al., 2013), whereby physically
inaccessible starch (RS1; e.g. intact cereal and seed grains),
resistant granules (RS2; e.g. raw potatoes, high-amylose
cereals (maize, barley)), and retrograded starch (RS3) are the
most relevant RS types in pig diets (Giuberti et al., 2015). RS1
and RS2 are mainly found in unprocessed cereal grains,
legumes and tubers, whereas RS3 forms in heat-processed
feedstuffs (Giuberti et al., 2015).
Collectively, more research evidence is available for RS2
effects on gut microbial metabolites and bacteria in pigs than
for the other RS types from the literature. Therefore, the
primary objective of the present meta-analysis was to
quantify the effect of dietary RS2 on intestinal fermentation
metabolites, pH and certain key bacterial taxa for intestinal
health in weaned, growing and finishing pigs. We used a
meta-analytical approach, because, opposite to qualitative
reviews, meta-analyses can consider changes in the direct
(type and dose) and indirect factors (e.g. age of the animal)
influencing starch digestion, fermentation metabolites and
pH in pig’s gastrointestinal tract which can cause varying
results across research studies (Sales, 2014). In that way,
the overall treatment effect across studies is generalized
(Charbonneau et al., 2006). Effects of RS2 on apparent total
tract digestibility (ATTD) were further examined for the
selected research articles from which gut microbial data were
extracted. Moreover, this meta-analysis aimed to derive
recommendations for dietary RS levels from RS2 sources
leading to physiological effects in pigs.
Material and methods
Literature search
The public search generators PubMed, Google Scholar, Web
of Science (Core collections), and Scopus were used to search
for literature. Research articles which investigated the effect
of RS2 from purified or natural sources on the bacterial
abundance and intestinal fermentation and were published
in scientific journals between the years 2000 and February
2017 were considered for data extraction. Adequate articles
were identified by applying the following search terms in
different combinations: RS, high-amylose starch, slowly
digestible starch, pig, piglet, swine, gastrointestinal tract and
individual segments, gut/intestine, fermentation, microbial
metabolites, total and individual SCFA (or volatile fatty
acids), lactic acid, neutral and anionic forms of fermentation
acids, bacteria, microbiota, microflora and microbiome.
Construction of database
The construction of the database was similar to that
previously described (Metzler-Zebeli et al., 2017). Of the
35 identified articles, 24 were eligible for the present meta-
analysis by meeting a sufficient number of quality criteria
(Supplementary Material Table S1). Quality assessment
criteria included information about dietary composition, RS
level and source (purified concentrate or natural source),
details on pig (breed, age, BW, age, sex, production stage),
housing condition, number of pigs within treatment groups,
duration of the experimental period, experimental design
including randomization of treatment groups, description of
statistical analysis, and intra-study error (if standard devia-
tion was provided, it was converted into standard error), as
well as bacterial abundances, microbial metabolites (i.e. SCFA
and lactate) and pH values in digesta of stomach, ileum,
cecum, proximal, mid and distal colon and feces (rectum). In
addition, average daily feed intake (ADFI), average daily weight
gain (ADG) and ATTD data were extracted. Only
in vivo
studies
were included in the present meta-analysis. The main infor-
mation extracted from each research article is presented in
Table 1. When the dietary concentration of RS was not pro-
vided, the RS amount in the diet was estimated using published
values for similar RS2 sources. In general, different analytical
methodologies, including different
in vitro α
-amylase digestion
approaches (e.g. Champ, 1992; Morales
et al
., 1997) or total
starch and RS assay kits (e.g. Megazyme assay kits), the official
AOAC method (2002), and the determination of RS according
to Englyst and Cummings (1984), were applied to determine
the dietary RS concentration. Or the dietary RS content was
calculated by using the manufacturer’sspecifications in the
various research studies.
In order to consider maturational changes from weaned to
finisher pigs, pig’s BW at the beginning of the experiment (start
BW) was used as an additional predictor variable. Likewise, the
Resistant starch and intestinal fermentation
65
length of the experimental period was considered as additional
predictor variable because the microbial response to a dietary
treatment may change over time.
From the original dataset including all studies, sub-data sets
for the individual dependent variable categories were compiled,
that is, one sub-dataset each for bacterial abundances, pH
values, microbial metabolites including SCFA and lactate,
as well as for performance-related variables such as ADG,
ADFI and ATTD. Data for individual SCFA were analyzed as
concentrations and molar proportions of total SCFA.
Three studies were set as minimum requirement to quan-
tify the combined effect size (Lipsey and Wilson, 2001),
together with a minimum of 10 single observations (treat-
ment means) per dependent variable as well as the respec-
tive SEM of each variable. Only dependent variables which
met these minimum requirements will be presented.
Absolute bacterial abundances were extracted from
studies using quantitative PCR(
n
=7), terminal-fragment-
length polymorphism (
n
=1) and culturing (
n
=2). Although
being different methods of quantification, log
10
colony
forming units (CFU) were previously shown to highly corre-
late (0.979 to 0.998) to log
10
gene copy numbers per gram of
sample (Hein et al., 2001). In applying this correlation, we
expressed the available bacteria data from PCR-based and
culturing-based approaches in log
10
gene copies per gram
intestinal digesta or feces. Nevertheless, it needs to be kept
in mind that CFU and quantitative PCR-based amplification
of short sequences of the 16S rRNA gene, are different
analytical approaches. Therefore, present regression results
should be regarded as an approximation. If provided on DM
basis, microbial metabolites and bacterial abundances were
converted to fresh matter basis.
Data analysis
Descriptive statistics on predictor (i.e. dietary RS level, start
BW and duration of the experimental period) and dependent
variables (i.e. bacteria, microbial metabolites, pH, perfor-
mance and digestibility) was performed using the MEANS
procedure of SAS (SAS Institute Inc., version 9.4) similar to
Metzler-Zebeli et al. (2017). Mixed modeling of each
dependent variable was performed using the MIXED proce-
dure as previously described (Metzler-Zebeli et al., 2017).
The slope and intercept by study, start BW, duration of
experiment and dietary RS content were included as random
effects and an unstructured variance-covariance matrix
(type =UN) was used to avoid a positive correlation between
intercepts and slopes (St-Pierre, 2001). Breed and sex were
initially included in the model but omitted in the final model
as non-influential. By weighing the dependent variable by
the inverse of its squared SEM (SEM of treatment means from
single studies), the unequal variance among studies was
taken into account. In order to test quadratic relationships
between the dietary RS level and dependent variables, its
squared term was included in the model using variance
components (TYPE =VC) as variance-covariance matrix.
However, quadratic relationships were not detectable. Data
were visualized using the GPLOT procedure. Estimates, RMSE
and
R
2
were computed and used to evaluate the goodness of
fit. Significance was declared at
P
<0.05 and trends at
0.05 <
P
<0.10.
Backward elimination analysis (Metzler-Zebeli et al., 2017)
wasusedtoobtainamoreprecisepredictionofinfluencing
factors on dependent variables that were influenced by the
dietary RS level. This allowed for the simultaneous evaluation
of the predictor variables dietary RS level, squared dietary RS
level, start BW and length of the experimental period on the
response variables. Model overparameterization was limited by
allowing for a variance inflation factor of <10 (which assumes
no significant multicollinearity among predictor variables
tested) for every continuous independent variable tested.
Results
Database description
The RS2 originated mainly from corn, potato, pea, barley and
tapioca (Supplementary Material Table S1). In the majority of
studies included, diets were semi-purified with the test starch
as the principal starchy component. The results of the
descriptive statistics for the predictor and dependent vari-
ables are presented in Table 1. The mean and median dietary
RS levels amounted to 28.8% and 23.0% of the diet (DM
basis), respectively, with dietary inclusion levels ranging from
0% to 78% RS (Table 1). The BW of pigs at the beginning of
the experimental period ranged between 4.6 and 105 kg with
a mean and median BW of 23.7 and 30.4 kg, respectively.
Pigs were fed the test diets between 7 and 100 days with a
mean and median duration of the experimental period of
28.7 and 21 days, respectively. Pigs were often restrictively
fed; therefore, the impact of RS2 on ADFI and ADG was not
further assessed. The ranges of the predictor variables
(dietary RS content, BW of the pigs at the start of the
experimental period and the duration of the experimental
period) in the sub-data sets for nutrient digestibility,
gastrointestinal pH, microbial metabolites and bacterial
counts are provided in Supplementary Material Table S2.
Resistant starch type 2 effect on intestinal and fecal pH
Established relationships between dietary RS level and
intestinal and fecal pH showed that the lowering effect of RS
on luminal pH became stronger from the ileum to the distal
segments of the large intestine and feces. In fact, increasing
RS levels tended to decrease the ileal pH (
R
2
=0.16;
P
<0.10) and decreased the pH of digesta in cecum
(
R
2
=0.19;
P
<0.05), proximal, mid and distal colon, and
feces (
R
2
=0.37 to 0.81;
P
<0.001; Figure 1). According to
the present equations, the diet would need to comprise 30%
and 20% RS to decrease the ileal and cecal pH by 0.2 units,
respectively, whereas a dietary amount of 15% would lower
the pH in the proximal, mid and distal colon, and feces by
0.2, 0.6, 0.4 and 0.6 units, respectively.
Resistant starch type 2 effect on intestinal and fecal microbial
metabolite concentrations
Sufficient information was available for SCFA, whereas the
available information for lactate did not meet the minimum
Metzler-Zebeli, Canibe, Montagne, Freire, Bosi, Prates, Tanghe and Trevisi
66
requirement to quantify the combined effect size. According
to the present regressions, increasing the dietary level of RS
did not affect total and individual SCFA concentrations in
ileal, cecal and colonic digesta and feces (Supplementary
Material Table S3). When comparing the molar proportions
of the main SCFAs acetate, propionate and butyrate,
Table 1
Descriptive statistics for predictor and response variables for resistant starch (RS) type 2 effects in pigs
1
Variable
n
studies
n
treat
Mean SEM Median Minimum Maximum
Predictor variables
Dietary RS (%) 24 67 28.8 3.13 23.0 0 78.0
Start BW (kg) 24 67 30.4 3.16 23.7 4.6 105.0
Experimental period (days) 24 67 28.7 2.98 21.0 7 100
Response variables
Ileum
pH 5 18 7.1 0.10 7.1 6.6 8.1
Total SCFA (µmol/g) 5 16 19.2 3.09 15.0 4.2 50.2
Cecum
pH 8 30 6.1 0.09 6.2 5.2 6.8
Total SCFA (µmol/g) 7 28 84.3 6.95 90.2 27 160
Acetate (µmol/g) 7 25 45.4 4.03 42.9 12 86.4
Propionate (µmol/g) 7 25 23.5 2.62 20.4 9. 48.0
Butyrate (µmol/g) 7 25 9.5 1.30 8.8 2.0 20.8
Iso-butyrate (µmol/g) 3 13 0.37 0.11 0.14 0 1.03
Valerate (µmol/g) 3 13 1.7 0.20 1.4 0.8 3
Iso-valerate (µmol/g) 3 13 0.45 0.11 0.32 0 1.10
Proximal colon
pH 10 30 6.0 0.09 6.1 5.2 6.8
Total SCFA (µmol/g) 9 28 81.6 8.2 82.0 29.5 170.0
Acetate (µmol/g) 7 21 37.9 4.38 44.8 7.0 61.4
Propionate (µmol/g) 7 21 14.9 2.3 15.5 4 36.4
Butyrate (µmol/g) 7 21 8.3 1.17 8.8 0.3 16.3
Mid-colon
pH 4 15 6.5 0.17 6.7 5.4 7.2
Total SCFA (µmol/g) 3 10 62.1 16.89 59.4 3.0 175
Acetate (µmol/g) 3 10 33.3 8.62 33.8 2.0 84
Propionate (µmol/g) 3 10 17.4 4.54 15.9 1.0 50.75
Butyrate (µmol/g) 3 10 9.2 3.05 8.0 0.5 31.5
Total bacteria (log
10
gene copies/g) 3 10 8.8 0.37 9.1 6.7 10.5
Distal colon
pH 5 17 6.3 0.13 6.4 5.3 7.0
Total SCFA (µmol/g) 5 17 62.0 8.32 77.2 2.0 114.0
Acetate (µmol/g) 3 10 23.5 5.32 28.2 1.0 45.6
Propionate (µmol/g) 3 10 10.9 2.29 12.3 1.0 21.6
Butyrate (µmol/g) 3 10 5. 1.18 6.5 0.3 10
Feces
pH 5 17 6.3 0.20 6.3 5.1 7.5
Total SCFA (µmol/g) 7 18 65.7 14.45 43.5 35.8 164.7
Acetate (µmol/g) 6 16 25.4 6.23 16.7 19.7 226.0
Propionate (µmol/g) 6 16 25.8 8.19 9.8 6.6 90.0
Butyrate (µmol/g) 6 18 9.7 1.11 8.2 4.7 136.0
Lactobacilli (log
10
gene copies/g) 4 12 6.8 0.35 6.2 5.6 8.6
Bifidobacteria (log
10
gene copies/g) 4 12 6.6 0.40 6.2 5.1 9.0
Enterobacteriaceae
(log
10
gene copies/g) 3 10 8.3 0.33 8.1 6.9 10.3
Performance and digestibility
ADFI (g) 9 36 961 118.7 489 141 2748
ADG (g) 10 36 415 42.1 311 55 762
ATTD of DM (%) 5 16 86.1 2.52 90.0 73.2 97.6
ATTD of CP (%) 7 19 80.3 2.21 78.4 59.0 94.0
ATTD of starch (%) 6 16 99.0 0.43 99.9 93.7 100.0
ADFI =average daily feed intake; ADG =average daily weight gain; ATTD =apparent total tract digestibility; CI =confidence interval;
n
treat
=number of treatment means included; SCFA =short-chain fatty acids.
1
Separate data sets for response variables pH, short-chain fatty acids, bacteria and performance/digestibility were built.
Resistant starch and intestinal fermentation
67
relationships between the dietary RS level and the SCFA
profiles became apparent. As such, regressions showed that
increasing dietary RS levels decreased the molar proportion
of acetate and butyrate but increased that of propionate in
mid-colonic digesta (
R
2
=0.44 to 0.57;
P
<0.05; Table 2). In
distal colonic digesta, only the molar proportion of butyrate
was negatively related to increasing dietary RS levels
(
R
2
=0.50;
P
=0.022). A minimum of 20% of dietary RS
would be needed to elevate the molar propionate proportion
by 5% in mid-colonic digesta.
Resistant starch type 2 effect on bacterial abundances
Sufficient information was available for total bacteria in
colonic digesta and for lactobacilli, bifidobacteria and
Enterobacteriaceae
in feces (Table 3). According to the
present regressions, increasing the RS level did not affect
the total bacterial number in colonic digesta, whereas it
promoted the presence of lactobacilli (
R
2
=0.46,
P
<0.001)
and bifidobacteria (
R
2
=0.52,
P
<0.001) in feces. To achieve
a physiological relevant increase in fecal lactobacilli and
bifidobacteria, a minimum of 10% RS in the diet may be
required.
Resistant starch type 2 effect on apparent total tract
digestibility
The ATTD of DM, CP and starch was not modified by
increasing dietary RS levels (Table 4).
Figure 1 Linear relationships between dietary resistant starch type 2 (RS2) level and intestinal pH in pigs. Best-fit linear model of luminal pH (Y) in
response to dietary RS2 level (X) (a) ileum; (b) cecum; (c) proximal colon; (d) mid-colon; (e) distal colon; and (f) feces.
Metzler-Zebeli, Canibe, Montagne, Freire, Bosi, Prates, Tanghe and Trevisi
68
Backward elimination analysis
Backward elimination analysis showed that the starting BW
of pigs and length of the experimental period influenced
the effect of dietary RS2 on the response variables (Table 5).
The response variables cecal pH, distal colonic pH and
mid-colonic acetate proportion were mainly affected by the
increasing dietary RS level (
R
2
=0.19 to 0.65;
P
<0.05).
According to the squared effect of the RS level, the response
Table 2
Prediction of molar proportions of individual short-chain fatty acids (SCFA mol/100 mol) in cecal and colonic digesta
and feces as affected by dietary resistant starch content (%) in pigs
Parameter estimates Model statistics
Response variable (
Y
) Intercept SEM
Intercept
Slope SEM
Slope
RMSE
R
2
P
value
Cecum
Acetate 57.69 1.96 −0.068 0.068 5.886 0.05 0.327
Propionate 28.50 1.77 −0.005 0.061 5.318 0.00 0.931
Butyrate 11.74 1.00 −0.033 0.034 2.984 0.04 0.340
Proximal colon
Acetate 59.01 4.29 −0.314 0.189 13.945 0.13 0.114
Propionate 21.41 3.29 0.048 0.145 10.689 0.01 0.742
Butyrate 10.98 1.18 0.036 0.052 3.846 0.02 0.502
Mid-colon
Acetate 59.29 2.14 −0.356 0.109 4.789 0.57 0.012
Propionate 26.68 1.47 0.241 0.075 3.288 0.56 0.012
Butyrate 15.36 1.22 −0.157 0.062 2.723 0.44 0.035
Distal colon
Acetate 57.09 2.66 −0.150 0.132 5.660 0.14 0.286
Propionate 29.96 4.00 −0.025 0.197 8.492 0.00 0.901
Butyrate 13.76 1.10 −0.154 0.054 2.335 0.50 0.022
Feces
Acetate 47.24 6.58 0.115 0.267 19.061 0.01 0.674
Propionate 22.20 7.23 0.070 0.293 20.932 0.00 0.814
Butyrate 9.12 1.40 0.021 0.057 4.063 0.01 0.721
Table 3
Prediction of absolute bacterial abundance (log
10
gene copies/g) in colonic digesta and feces as affected by dietary
resistant starch content (%) in pigs
Parameter estimates Model statistics
Response variable (
Y
) Intercept SEM
Intercept
Slope SEM
Slope
RMSE
R
2
P
value
Mid-colon
Total bacteria 8.36 0.60 0.015 0.019 1.106 0.08 0.427
Feces
Lactobacilli 5.81 0.46 0.047 0.015 0.926 0.46 0.008
Bifidobacteria 5.52 0.42 0.046 0.014 0.950 0.52 0.008
Enterobacteriaceae
8.46 0.71 0.005 0.021 1.208 0.01 0.824
Table 4
Prediction of apparent total tract digestibility of nutrients as affected by dietary resistant starch content (%) in pigs
Parameter estimates Model statistics
Response variable (
Y
) Intercept SEM
Intercept
Slope SEM
Slope
RMSE
R
2
P
value
ATTD of DM (%) 84.0 3.28 0.109 0.106 10.03 0.07 0.322
ATTD of CP (%) 82.8 2.56 −0.185 0.109 9.11 0.14 0.109
ATTD of starch (%) 98.8 0.63 0.017 0.029 1.82 0.03 0.558
ATTD =coefficient of total tract apparent digestibility.
Resistant starch and intestinal fermentation
69
variables fecal lactobacilli and bifidobacteria, ileal pH and
distal colonic butyrate proportion followed an asymptotic
approximation with increasing RS levels (
P
<0.05). More-
over, backward elimination showed that, besides the positive
relationship with dietary RS, the duration of the experimental
period increased the fecal numbers of lactobacilli (
R
2
=0.88;
P
<0.05) but decreased those of bifidobacteria (
R
2
=0.78;
P
<0.05). The duration of the experiment also potentiated
the negative relationship between dietary RS level and
proximal colonic pH (
R
2
=0.46;
P
<0.05), whereas it coun-
teracted the decline in mid-colonic pH with increasing dietary
RS level (
R
2
=0.83;
P
<0.05). Moreover, BW at the start of
the experiment influenced mid-colonic propionate (
P
<0.05)
and mid- (
P
<0.10) and distal colonic butyrate proportions
(
P
<0.05) in opposite directions.
Discussion
The present study aimed to systematically and statistically
evaluate the capability of dietary RS2 to modulate intestinal
bacterial abundances and fermentation. In particular, meta-
regressions demonstrated that, with a minimum amount of
10% to 15% actual RS in the diet, RS2 can effectively
decrease the luminal pH in the hindgut of pigs and promote
lactic acid-producing bacteria in pig’s feces. Although the
extracted data covered a wide range of experimental condi-
tions, it should be considered for the interpretation of the
present regressions that most information was available for
luminal pH in the cecum and proximal colon with 21 to 30
treatment comparisons. For the other response variables,
often only low numbers of treatment comparisons could be
extracted. Also, as indicated by the mean and median BW of
pigs, present relationships are more applicable to smaller pigs.
Due to its low digestibility in the small intestine, it is
generally assumed that RS2 promotes fermentation
especially in the proximal regions of the large intestine
(Bach Knudsen et al., 2012; Giuberti et al., 2015). As a
consequence, most research data on RS2 effects on SCFA
were available for the cecum, colon and feces. Fermentation
data for stomach, duodenum and jejunum from research
articles between the years 2000 and 2017 were scarce and
only response variables in ileal digesta met our minimum
requirements for inclusion in this meta-analysis. This was
despite the fact that the pig harbors a highly diverse and
numerous microbial community in the stomach where
fermentation of carbohydrates already commences
(Metzler-Zebeli et al., 2013; Motta et al., 2017).
Due to the fermentation occurring prececally, the dietary
concentration of RS is one of the critical factors for the
effectiveness of RS2 to modify SCFA concentrations in the
hindgut of pigs. Moreover, endogenous RS levels in low-
amylose cereal grains and legumes, depending on the
variety, range from 1% to 20% (Birt et al., 2013; Giuberti
et al., 2015) and may have masked potential RS effects if
dietary levels were too low. There was only one study in
which RS2 was supplemented at very low levels of 0.5%
and 1% RS in powder form or as a capsule (Heo et al.,
2014). In all other studies, higher RS (amylose) contents
were examined, which should have been sufficient to
produce detectable effects of the respective RS2 source on
Table 5
Best-fit equations showing the coefficients of microbial response variables and average daily weight gain in relation to increasing dietary
resistant starch (RS) content, pig’s starting BW and length of the experimental period using backward elimination
Parameter estimates Model statistics
Response variable (
Y
) Factor (
X
) Intercept SEM
Intercept
Slope SEM
Slope
RMSE
R
2
VIF
P
value
Fecal lactobacilli (log
10
gene copies/g) Experimental period (days) 5.43 0.22 0.024 0.004 0.452 0.88 1.03 <0.001
Squared RS content (%) 0.001 0.0001 1.03 0.001
Fecal bifidobacteria (log
10
gene copies/g) Experimental period (days) 7.32 0.75 −0.094 0.040 0.689 0.78 1.00 0.044
Squared RS content (%) 0.001 0.0002 1.00 <0.001
Ileal pH Squared RS content (%) 7.21 0.09 −0.0001 0.0001 0.331 0.22 1.00 0.048
Cecal pH RS content (%) 6.21 0.12 −0.012 0.005 0.406 0.19 1.00 0.028
Proximal colonic pH Experimental period (days) 6.38 0.11 −0.004 0.002 0.337 0.46 1.00 0.039
RS content (%) −0.018 0.004 1.00 <0.001
Mid-colonic pH Experimental period (days) 5.35 0.61 0.064 0.025 0.277 0.83 1.29 0.024
RS content (%) −0.033 0.006 1.29 <0.001
Distal colonic pH RS content (%) 6.57 0.09 −0.027 0.005 0.272 0.65 1.00 <0.001
Fecal pH RS content (%) 6.94 0.17 −0.082 0.026 0.461 0.69 12.89 0.006
Squared RS content (%) 0.001 0.0007 12.89 0.084
Mid-colonic acetate proportion (%) RS content (%) 59.35 1.99 −0.362 0.102 4.457 0.61 1.00 0.007
Mid-colonic propionate proportion (%) Start BW (kg) 59.29 11.12 −1.279 0.447 1.944 0.85 1.08 0.024
RS content (%) 0.005 0.001 1.08 0.002
Mid-colonic butyrate proportion (%) Start BW (kg) −3.43 8.52 0.767 0.341 1.495 0.83 1.06 0.059
RS content (%) −0.165 0.035 1.06 0.002
Distal colonic butyrate proportion (%) RS content (%) 16.00 0.62 −0.509 0.075 1.132 0.92 8.04 <0.001
Squared RS content (%) 0.007 0.002 8.04 0.0042
VIF =variance inflation factor.
Metzler-Zebeli, Canibe, Montagne, Freire, Bosi, Prates, Tanghe and Trevisi
70
intestinal parameters. Many studies utilized semi-purified
diets, thereby greatly circumventing that effects may have
been masked by other fermentable dietary ingredients. Using
semi-purified diets though may reduce the transferability of
results to whole-grain cereal and legume meal diets due to
interactions among ingredients of more complex diets. It is
very probable that other dietary carbohydrates (e.g. pectins,
arabinoxylans,
β
-glucans, cellulose) modified the RS2-
induced effects on intestinal SCFA, bacterial abundances
and digestibility of starch in the research studies. However,
those carbohydrate fractions could not be incorporated in the
present meta-analysis as the chemical composition of
experimental diets was poorly reported in more than half of
the included research articles. Moreover, different analytical
methodologies or the specification of the manufacturer that
provided the starch were used to estimate the dietary RS
content which may have added a certain variability with
respect to the interpretation of the RS2 effects among the
included research articles. With RS2 effects detectable for
certain parameters (i.e. luminal pH along large intestinal
segments, bacteria in feces and SCFA profiles in mid and
distal colon), the slopes of the regression equations indicated
that minimal dietary amounts between 10% and 20% RS are
necessary to cause measurable physiological effects along
the large intestine.
The intestinal pH is indicative of microbial activity and
has been used as measure for intestinal health in pigs by
suppressing the growth of opportunistic pathogens (Heo
et al., 2014). The pH in the large intestine is largely affected
by the amount of dietary fermentable carbohydrates entering
the large intestine, thereby stimulating microbial activity and
generation of SCFA which consequently acidify the digesta
(Wang et al., 2004; Heo et al., 2014). Present meta-
regressions supported this principle for RS2, showing greater
acidification of digesta in the large intestine with increasing
dietary RS levels. Notably, relationships between the dietary
RS content and digesta pH became stronger in the distal
segments of the large intestine. Due to the high degradability
of RS2 sources, for example, raw potato starch and high-
amylose cornstarch, fermentation intensity has been often
assumed to be highest in cecum and proximal colon (Haenen
et al., 2013; Sun et al., 2015). Therefore, it seems plausible
that the steeper slopes for the pH decline in the mid and
distal colon and feces can be partly associated with an
accumulation of protons in digesta. Within a luminal pH
range of 6 to 7 (Bergman, 1990), lactate and SCFA are
ionized and require monocarboxylate transporters for uptake
(Sepponen et al., 2007), whereas protons remain in the
intestinal lumen, thereby increasing digesta acidity. In addi-
tion, proton exchangers reduce the intracellular proton load
after uptake of the acid form of lactate and SCFA into
enterocytes, thereby further acidifying the intestinal lumen
(Collins et al., 1993; Thwaites and Anderson, 2007). Back-
ward elimination results of luminal pH indicated that an
adaptation of the microbiota may increase the production of
SCFA and hence acidification in the proximal colonic digesta
when pigs are fed the RS2 for a longer time period, leading to
a stronger pH decline. Increased microbial degradation of RS
in the proximal large intestine and a reduced substrate flow
to the mid-colon may subsequently explain the positive
relationship between mid-colonic pH and a longer experi-
mental period.
There are several possible explanations for the missing
relationship between dietary RS and SCFA along the large
intestine and feces. As data for SCFA were provided as
concentrations, they do not fully represent the total amount
of SCFA produced on a daily basis (Regmi et al., 2011).
Fermentable fiber increases the digesta bulk in the hindgut
(Bach Knudsen et al., 1993; Pluske et al., 2007); therefore,
daily production of SCFA may be still increased by the
present RS2 sources but not reproducible from the data
available from the individual research studies. Second,
increased synthesis of SCFA stimulates their mucosal uptake
which may have lowered concentrations measured in digesta
(Cummings and Macfarlane, 1991). Nevertheless, meta-
regressions support that dietary RS levels can decrease the
molar proportion of acetate and increase that of propionate
in the mid-colon, thereby supporting results from individual
studies (e.g. Martinez-Puig et al., 2003). Changes in the
Lachnospiraceae
,
Clostridiaceae
and
Bacteroidaceae
families, which comprise propionate-producing bacteria
(Reichardt et al., 2014), have been reported in pigs fed RS2
(Sun et al., 2015 and 2016). Enhanced generation of
propionate may have an important impact on host physiol-
ogy by regulating gene expression and as signaling molecule
(Louis and Flint, 2017). Propionate exerts anti-inflammatory
properties at the intestinal mucosa and, after absorption,
contributes to gluconeogenesis in the liver and can promote
satiety (Morrison and Preston, 2016). Although some studies
reported a stimulating effect of RS2 on butyrate fermentation
(Mentschel and Claus, 2003), our findings of negative
relationships between the butyrate proportion and dietary RS
level in the mid and distal colon were rather unexpected.
Maturational processes within the intestinal microbiota may
have influenced the outcome of the various individual
studies as indicated by the best-fit equations with decreasing
propionate and increasing butyrate proportion with increas-
ing starting BW. Also, the aforementioned discrepancy
between SCFA produced on a daily basis and those measured
per gram digesta should be considered in this context.
Overall, the three dominant phyla of the porcine
microbiota,
Firmicutes
,
Bacteroidetes
and
Actinobacteria
,
comprise important starch-degrading bacterial species
(Haenen et al., 2013; Sun et al., 2015 and 2016). Amylase
and pullulanase activities have been reported, among others,
for lactobacilli, bifidobacteria,
Microbacterium
,
Turicibacter
,
Blautia
,
Ruminococcus
, especially
Ruminococcus bromii-
phylotypes, and
Bacteroides
(Louis et al., 2007; Sun et al.,
2015 and 2016; Louis and Flint, 2017). Other bacteria,
such as
Faecalibacterium
,
Coprococcus, Megasphaera
and
Mitsuokella
, were shown to prosper on RS2-containing
diets (Sun et al., 2015 and 2016), probably via cross-feeding
of fermentation metabolites. Particularly, cross-feeding of
lactate and succinate to propionate-producing bacteria
Resistant starch and intestinal fermentation
71
(Louis and Flint, 2017) may explain the relationships of
dietary RS level with colonic SCFA profiles. The extractable
data from the research articles that met the eligibility criteria
and the minimum requirement to quantify the combined
effect size, however, only allowed for assessing relationships
between dietary RS levels and total bacterial numbers in
colonic digesta and the three best investigated bacterial
groups lactobacilli, bifidobacteria and
Enterobacteriaceae
in
feces. The missing relationship between RS level and total
bacteria in the colon may confirm that RS2-associated
alterations in the overall bacterial community structure and
diversity may be expected rather than changes in their total
numbers as reported in some individual studies (Sun et al.,
2015). Current meta-regressions further support the promo-
tion of fecal lactobacilli and bifidobacteria by dietary RS2
sources in pigs. High intestinal abundance of lactobacilli and
bifidobacteria has been generally associated with intestinal
health, as these genera can contribute to suppress the
growth of opportunistic pathogens (Schmidt et al., 2010;
O’Shea
et al.
, 2012; Yang et al., 2015; Wang et al., 2016) and
exert immunomodulatory effects (Kandasamy et al., 2014;
Kamiya et al., 2016). Although these relationships were
obtained for feces, they likely reflect the conditions in the
distal hindgut. Although belonging to pig’s commensal
microbiota,
Enterobacteriaceae
were mostly investigated
because they comprise opportunistic pathogens, such as
Salmonella
or enterotoxigenic
Escherichia coli
(Fairbrother
et al., 2005). As pH-sensible bacteria,
Enterobacteriaceae
abundance may have been decreased by the RS-related
decrease in luminal pH in the distal large intestine, which
was not confirmed by the present regression analysis. The RS
concentration in digesta consecutively decreases along the
large intestine, which may lead to different effects in the
modulation of microbial taxa from the proximal to distal
large intestine (Haenen et al., 2013). Therefore, relationships
obtained for the distal segments in the current meta-analysis
should not be used to predict relationships in the cecum or
proximal colon. Moreover, data from culturing and PCR-
approaches were combined which should be considered
when interpreting the present relationships for colonic
digesta and feces. By showing a squared effect of dietary RS
level, backward elimination confirmed that a minimum
dietary RS amount is necessary to enhance lactobacilli and
bifidobacterial numbers. Best-fit equations also suggested
short-term and long-term effects of RS2, which were
opposite for lactobacilli and bifidobacteria. As both genera
comprise starch-degraders, the decrease in bifidobacteria
over time may be related to a competition with other
starch-degrading bacteria, such as amylolytic lactobacilli,
and to age-related changes in the bacterial community post-
weaning (Yang et al., 2015; Bian et al., 2016).
Evidence exists that high dietary RS levels negatively
impact ileal DM and energy digestibility (Giuberti et al.,
2015). As the focus of the present meta-analysis was on
intestinal bacterial action and not on nutrient digestibility,
data for apparent ileal digestibility of DM, energy and
nutrients that could be extracted were limited and very likely
not representative. Results support that the ATTD of starch is
almost complete which can be clearly explained by the high
fermentability of the various RS2 sources. However, less
energy can be gained from intestinal fermentation than from
host enzymatic starch digestion (Bach Knudsen et al., 1993),
leading to the often reported depression in growth perfor-
mance with increasing dietary RS intake (Giuberti et al.,
2015).
Conclusion
According to the present meta-regressions, dietary RS2
sources can effectively decrease the luminal pH in the large
intestine, especially in the more distal regions, of pigs, which
may be helpful to suppress the growth of opportunistic
pathogens. Moreover, relationships supported that lactic
acid-producing bacteria such as lactobacilli and bifido-
bacteria in feces and SCFA generation, especially propionate
in the mid-colon, can be promoted by increasing dietary RS
levels. However, present estimations indicated that, in order
to achieve physiologically relevant changes, the actual diet-
ary RS concentration should surpass 10% to 15%. Moreover,
it needs to be considered that for many response variables,
only low numbers of treatment comparisons were available
and no differentiation between different RS2 sources could
be made.
Acknowledgments
This article is based upon work from COST Action FA1401
PiGutNet, supported by COST (European Cooperation in Science
and Technology).
Declaration of interest
The authors declare no potential conflict of interest.
Ethics statement
The present meta-analyses used statistical regression methods
to analyze previously recorded data and did not require ethical
approval.
Software and data repository resources
Data were not deposited in an official repository.
Supplementary material
To view supplementary material for this article, please visit
https://doi.org/10.1017/S1751731118001003
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