Caroline Montelius1, Nadia Osman1, Björn Weström2, Siv Ahrné3, Göran Molin3, Per-Åke Albertsson4, Charlotte Erlanson-Albertsson1. 1. Department of Experimental Medical Science , Lund University , Lund , Sweden. 2. Department of Biology , Lund University , Lund , Sweden. 3. Department of Food Technology, Engineering and Nutrition , Lund University , Lund , Sweden. 4. Department of Biochemistry and Structural Biology , Lund University , Lund , Sweden.
Abstract
Thylakoid membranes derived from green leaf chloroplasts affect appetite-regulating hormones, suppress food intake, reduce blood lipids and lead to a decreased body weight in animals and human subjects. Thylakoids also decrease the intestinal in vitro uptake of methyl-glucose in the rat. The aim of this study was to investigate the effect of dietary thylakoids on the gut microbiota composition, mainly the taxa of lactobacilli and bifidobacteria, in rats fed either a thylakoid-enriched diet or a control diet for 10 d. At the same time, a glucose-tolerance test in the same rats was also performed. Food intake was significantly decreased in the thylakoid-fed rats compared with the control-fed rats over the 10-d study. An oral glucose tolerance test after 10 d of thylakoid- or control-food intake resulted in significantly reduced plasma insulin levels in the thylakoid-fed rats compared with the control-fed rats, while no difference was observed for blood glucose levels. Analysis of gut bacteria showed a significant increase of lactobacilli on the ileal mucosa, specifically Lactobacillus reuteri, in the rats fed the thylakoid diet compared with rats fed the control diet, while faecal lactobacilli decreased. No difference in bifidobacteria between the thylakoid and control groups was found. Analyses with terminal restriction fragment length polymorphism and principal component analysis of faeces demonstrated different microbial populations in the thylakoid- and control-fed animals. These findings indicate that thylakoids modulate the gut microbial composition, which might be important for the regulation of body weight and energy metabolism.
Thylakoid membranes derived from green leaf chloroplasts affect appetite-regulating hormones, suppress food intake, reduce blood lipids and lead to a decreased body weight in animals and human subjects. Thylakoids also decrease the intestinal in vitro uptake of methyl-glucose in the rat. The aim of this study was to investigate the effect of dietary thylakoids on the gut microbiota composition, mainly the taxa of lactobacilli and bifidobacteria, in rats fed either a thylakoid-enriched diet or a control diet for 10 d. At the same time, a glucose-tolerance test in the same rats was also performed. Food intake was significantly decreased in the thylakoid-fed rats compared with the control-fed rats over the 10-d study. An oral glucose tolerance test after 10 d of thylakoid- or control-food intake resulted in significantly reduced plasma insulin levels in the thylakoid-fed rats compared with the control-fed rats, while no difference was observed for blood glucose levels. Analysis of gut bacteria showed a significant increase of lactobacilli on the ileal mucosa, specifically Lactobacillus reuteri, in the rats fed the thylakoid diet compared with rats fed the control diet, while faecal lactobacilli decreased. No difference in bifidobacteria between the thylakoid and control groups was found. Analyses with terminal restriction fragment length polymorphism and principal component analysis of faeces demonstrated different microbial populations in the thylakoid- and control-fed animals. These findings indicate that thylakoids modulate the gut microbial composition, which might be important for the regulation of body weight and energy metabolism.
Entities:
Keywords:
Colon; Lactobacilli; MW, modified Wilkins–Chalgren; OGTT, oral glucose tolerance test; Obesity; PCA, principal component analysis; Quantitative PCR; Small intestine; T-RFLP, terminal restriction fragment length polymorphism; qPCR, quantitative PCR
Today, over one billion adults are overweight with BMI between 25 and 30 kg/m2,
and more than 300 million are obese, with BMI >30 kg/m2,
worldwide(
). Overweight and obesity are strongly associated with type 2 diabetes,
hyperlipidaemia, atherosclerosis and CVD(
,
). The increased availability of palatable food, i.e. foods rich in fat and
sucrose, in Western society is hypothesised to play a significant role in this global increase
of body weight and metabolic disease.Recent data demonstrate that the gut microbiota may affect lipid metabolism and might
therefore be important for the development of obesity and related diseases(
,
). The microbiota can be viewed as a metabolic ‘organ’ exquisitely attuned
to the host's physiology. One function of the microbiota is the ability to process otherwise
indigestible components of the diet, such as plant polysaccharides, as well as taking part in
nutrient acquisition and energy regulation(
). In recent years, it has been proposed that the composition of the gut
microbiota differs between normal-weight, overweight and obesepersons(
). Compositional changes of the microbiota have also been demonstrated to be
associated with the development of diabetes(
), and for the regulation of fat storage via different gene
expressions(
). In recent years, some studies have reported that lactobacilli and
bifidobacteria may be important for body-weight regulation by acting as an anti-obesity
factor(
,
,
,
). Understanding changes in the microbiota, as well as their signalling
pathways, provides an opportunity to identify new therapeutic targets for promoting health.Thylakoids, isolated from the chloroplast membrane of green leaves, contain proteins, lipids
and pigments (e.g. chlorophyll and carotenoids). They have been found to increase satiety,
decrease hunger signals and promote weight loss in a number of studies, both in human subjects
and in animals(
–
). The satiety-promoting effects induced by thylakoids were explained by
their interaction with dietary lipids, prolonging the digestion of dietary
fat(
). Thylakoids have also been found to create a physical ‘barrier’ on the
mucosal surface of the intestine in vitro, causing a decreased uptake of
methyl-glucose and macronutrients over the intestinal wall(
).Since thylakoids interact with dietary products in the intestine, it is of interest to
investigate whether thylakoids might affect the composition of microbiota that confers
benefits upon host well-being and health in a prebiotic way of action. In the present study
thylakoids from spinach leaves were given to rats for 10 d and the intestinal microbiota were
investigated, mainly with respect to bacteria such as lactobacilli and bifidobacteria, as well
as harmful bacteria such as Enterobacteriaceae and
Bacteroides. The influence of thylakoids on food intake was recorded, and the
effect on metabolism was investigated through an oral glucose tolerance test (OGTT). The
long-term effects of thylakoid intake on insulin and glucose levels were also investigated.
Experimental methods
Animals and experimental procedures
The study was performed on rats (Rattus norvegicus) of the
Sprague–Dawley strain (Mol: SPRD Han; Taconic M & B A/S), bred under specific
pathogen-free conditions with a controlled environment (20 ± 1°C, 50 ± 10 % relative
humidity, 12 h light–12 h dark cycle) and using an open cage system. After 7 d of
acclimatisation, sixteen rats were kept individually and fed either a control diet (eight
rats) or a thylakoid-enriched diet (eight rats) of 15 g to finish during the night for
10 d. Besides the experimental diet, all rats were given 25 g of standard rat chow, for
free eating during the day. The experimental diet was composed of standard rat chow (R 36;
Lantmännen) enriched with either only rapeseed oil (control diet) or a thylakoid–oil
suspension (thylakoid diet). Thylakoid membranes were extracted and purified from fresh
baby-spinach leaves as described before(
,
). The thylakoid diet was prepared by mixing 4 g thylakoid powder
(corresponding to 132 mg chlorophyll), 5 g rapeseed oil and 10 g water by using an
Ultraturax mixer. The amount of thylakoids supplemented was calculated by the addition of
6 mg chlorophyll per g of normal food intake (22 g food/rat per d). Both thylakoid and
control diets were isoenergetic, and had the energy (E) distribution of 25E %
carbohydrates, 60E % fat and 15E % proteins.Normal rat chow was administered between 08.00 and 09.00 hours for free eating during the
day. In the afternoon, between 16.00 and 18.00 hours, the remaining chow was removed and
the consumption was recorded. The experimental diet of 15 g per rat was then administered,
and in the next morning, any leftovers of the experimental diet were recorded. Body weight
was measured every day during the 10-d experimental time. On the first and last days,
faecal samples were collected under clean conditions in the morning and the consistency of
the faecal samples appeared to be similar for both groups. An OGTT was performed on the
last day; a 15 % glucose solution in a volume of 10 % of the body weight was given as a
bolus dose by gastric tube feeding. Blood for analysing the glucose concentration was
collected by puncturing the tail vein at time points 0, 15, 30, 45, 60, 90 and 120 min.
The rat was then anaesthetised with isoflouran (Schering-Plogh a/s) and a laparotomy was
performed. Tissue samples from the ileum, caecum and colon were collected, rinsed from
loose materials with a cotton-compress and immediately placed in sterile tubes containing
3 ml freezing media and frozen at −80°C. Blood for analysing the insulin concentration was
obtained by a cardiac puncture, before the rat was killed, into tubes prepared with EDTA
and Aprotinin (Trasylol; Bayer AG), centrifuged at 3000 (Multifuge 1 Sorvall and Heraeus, Kendro Laboratory Products International Sales)
for 15 min at 4°C before the plasma was collected and immediately frozen at −80°C. The
study was approved by the Lund University Ethical Review Committee for Animal Experiments
and was conducted according to the European Community's regulations concerning the
protection of experimental animals.
Analysis of blood glucose and plasma insulin
Glucose levels were directly determined in the vein blood by using a Bayer's
BREEZE® blood glucose meter (Bayer, Diabetes Care). Insulin was analysed with a
sandwich immunoassay technique using double monoclonal antibodies directed at different
sites on an insulin molecule (Mercodia).
Analysis of faecal fat
The faecal samples were kept in closed glass tubes and left to dry at room temperature in
a fume cupboard for 1 month. The dry material was then weighed, placed in a mortar and
homogenised together with chloroform (AnalaR Normapur®; VWR International AB)
for 5 min. The homogenised solution was transferred into a pre-weighed glass filter, and
100 ml of chloroform was slowly washed through the glass filter for 10 min. The glass
filter, now containing the purified faecal components without fat, was dried overnight.
The remaining material was weighed and the lost mass corresponds to the amount of fat that
was present in the original faecal sample. The difference of fat content between day 0 and
10 was compared.
Analysis of bacterial counts
Conventional dilution procedures were used for the viable count of lactobacilli,
bifidobacteria and Enterobactericeae in the mucosal samples from the
ileum, caecum and colon, and in the faecal samples. Samples from appropriate dilutions
were plated on Rogosa agar, modified Wilkins–Chalgren (MW) agar(
,
) and violet red bile glucoseagar (Oxoid). The Rogosa and MW agars were
incubated at 37°C for 72 h anaerobically and the glucoseagar was incubated at 37°C for
24 h aerobically, before the colony-forming units per g of tissue or faeces were
calculated.
16S rDNA sequencing
To confirm the results on the viable count of lactobacilli and bifidobacteria, 16S rDNA
sequencing was performed from isolates picked from MW agar and Rogosa plates. In total,
169 isolates (four to six from each rat) from colon and ileum samples were randomly picked
(fifty-two colon isolates from MW agar plates, fifty-three colon isolates and sixty-four
ileum isolates from Rogosa plates). As a template for the PCR, crude cell extracts were
used as described by Quednau et al.(
). 16S rRNA genes were amplified by using the forward primer ENV1 and
the reverse primer ENV2 (Table 1; Applied
Biosystems). The PCR reaction mixture of total volume 25 μl contained
0·4 μm-ENV1, 0·2 μm-ENV2, 2·5 μl 10 × PCR reaction buffer
(500 mm-Tris-HCl, 100 mm-KCl,
50 mm-(NH4)2SO4,
20 mm-MgCl2, pH 8·3), 0·2 μm-deoxyribonucleotide
triphosphate, 2·5 units of FastStart Taq DNA polymerase (Roche Diagnostics) and 2 μl of
template DNA. PCR was performed in an Eppendorf Mastercycler® 5333 using the
following programme: 95°C for 3 min, 94°C for 3 min, thirty cycles of 94°C for 1 min, 50°C
for 45 s and 72°C for 2 min, followed by an additional extension of 72°C for 7 min. PCRs
containing only reagents without sample DNA were run in parallel as negative PCR controls.
PCR products (2 μl) were verified on 1·5 % agarose gel, and the amplification products
were placed in ninety-six-well plates for sequencing at MWG-Biotech. The generated
sequences, with a read length of 500–526 bases, were compared with the GenBank database
(National Center for Biotechnology Information). The sequence similarity was between 98
and 100 %.
Table 1.
Primers used in constructing standards of bacterial groups for quantitative PCR and
for the amplification of 16S rRNA genes
Target group
Sequence (5′–3′)
Amplicon size (bp)
Reference
Lactobacillus
Lact-16S-F: GGAATCTTCCACAATGGACG
216
20
Lact-16S-R: CGCTTTACGCCCAATAAATCCGG
Bifidobacterium
Bifido-F: TCGCGTCYGGTGTGAAAG
243
21
Bifido-R: CCACATCCAGCRTCCAC
Enterobacteriaceae
Eco1457-F: CATTGACGTTACCCGCAGAAGAAGC
195
22
Eco1652-R: CTCTACGAGACTCAAGCTTGC
Bacteroides prevotella
qBacPre-F: TTTATTGGGTTTAAAGGGAGCGTA
166
23
qBacPre-R: CAATCGGAGTTCTTCGTGATATCTA
16S rRNA genes (ENV1, ENV2)
E-coli 8–27-F: AGA GTT TGA TII TGG CTC AG
24
E-coli 1511–1492-R: CGG ITA CCT TGT TAC GAC TT
F, forward; R, reverse.
Primers used in constructing standards of bacterial groups for quantitative PCR and
for the amplification of 16S rRNA genesF, forward; R, reverse.
DNA extraction of faeces and intestinal biopsies
Faecal and intestinal segments of ileum and colon were thawed and placed in an ultrasonic
bath (Millipore) for 5 min, vortexed for 2 min and centrifuged at 12851 (Eppendorf 5804R) for 10 min. The supernatant was discarded and 190 μl buffer G2
and 15 μl Proteinase K from the DNA Tissue Kit (Qiagen) were added to the intestinal
samples. PBS (500 μl/ 50 mg) was added to the faecal samples before all samples were
incubated at 56°C overnight in a shaking water bath. After centrifugation at 12851 (Eppendorf 5804R) for 8 min, the solution was transferred to a Qiagen sample tube.
Total DNA was extracted and eluted in 200 μl buffer using Biorobot EZ1 (Qiagen) according
to the manufacturer's instructions.
Quantitative PCR analysis
Bacterial groups were estimated using separate quantitative PCR (qPCR) assays. Each assay
reaction contained 10 μl QuantiTect®SYBR Green PCR Master Mix (Qiagen),
0·5 μm of each primer (Table 1), 2 μl
of template DNA and RNase-free water to reach a final volume of 20 μl. Samples, standards
and non-template controls were run as duplicates. Thermal cycling was carried out in
Rotor-Gene Q (Qiagen) with a programme of 95°C for 15 min, followed by forty cycles with
denaturation at 95°C for 15 s, annealing at 56–60°C for 30 s and elongation at 72°C for
30 s. The fluorescent products were detected at the last step of each cycle. Melting curve
analysis was done to ensure specific amplification. Absolute abundance of 16S rRNA genes
was calculated based on standard curves using Rotor-Gene Q series (Software 1.7; Qiagen).
The detection limit was 102 copies per reaction for all assays. To construct
standard curves, cloned products from Lactobacillus plantarum DSM9843,
Bifidobacterium infantis DSM15159, Escherichia coliCCUG29300 and Bacteroides prevotella were used. One loop of the cell
suspension (cloned products) was transferred to 10 ml of lysogeny broth medium with
ampicillin and incubated overnight at 37°C. DNA extraction was performed by using
QIAprep® (Miniprep kit; Qiagen). The concentration of DNA (ng/μl) was finally
measured with Nanodrop ND-1000 (Saveen Werner AB), and used for copy number calculation.
Tenfold dilution series of the DNA products were made in TE buffer (10 mm-Tris;
1 mm-EDTA; pH 8·0). The numbers of bacteria were expressed as the numbers of
amplicon copies per g wet weight of faeces or tissue.
Terminal restriction fragment length polymorphism analysis
16S rRNA genes were amplified as described above with the exception that the forward
primer ENV1 was fluorescently labelled with a fluorescent dye, FAM, at the 5′ end.
Reactions were carried out in triplicate for each sample and a negative control was
included in all PCR runs. PCR products were verified on 1·5 % agarose gel. PCR products of
each sample were pooled and further purified by using the MinElute PCR purification Kit
(Qiagen). DNA was finally eluted in 15 μl of washing buffer and DNA concentrations were
measured with Nanodrop ND-1000 (Saveen Werner AB).Aliquots (200 ng) of purified PCR products were digested at 37°C
(Mastercycler® 5333; Eppendorf) with either the restriction endonuclease enzyme
MspI for 5 h or AluI for 2 h (Fermentas). Inactivation
was made by heating at 65°C for 20 min. After digestion, aliquots of the products were
diluted four times with sterile water in a ninety-six-well plate. Samples were then sent
to the DNA-lab (Skåne University Hospital, Malmö, Sweden) for terminal restriction
fragment length polymorphism (T-RFLP) analysis in a capillary electrophoresis system. The
data from the electrophoresis were analysed with GeneMapper® (version 4.0;
Applied Biosystems) and the fragment sizes and peak areas were estimated using the
Southern method (GeneMapper®). The size range was set from 30 to 600 bp. The
peak amplitude threshold was set to fifty relative fluorescence units for samples and ten
relative fluorescence units for the internal standard. The total peak area for each sample
was calculated by summarising the area for all peaks in a sample. The individual relative
peak area was expressed as percentage of the total area.
Calculations
The Shannon–Wiener index (H′) was calculated using relative peak area
expressed as percentage of the total area for a sample by using the equation: where pi is the relative area expressed as percentage and
ln is the natural logarithm(
). Multivariate data analysis with principal component analysis (PCA)
was performed in SIMCA-P+ (version 12.0.1; Umetrics) to reveal the possible differences in
microbial population between the groups.
Statistics
Values are presented as means with their standard errors or as medians, ranges and 25th
and 75th percentiles. The differences in glucose, insulin and counts of bacteria between
the two experimental groups were assessed by a Mann–Whitney rank sum test using GraphPad
Prism 4.0 (GraphPad Inc.). The difference in food intake, over the entire
experimental period, was assessed by a two-way ANOVA analysis (GraphPad Prism 4.0). The
incidences of different lactobacilli, bifidobacteria and other Gram-positive bacteria were
evaluated by the Fisher exact test (Quick-Stat version 2.6). For all analyses,
P ≤ 0·05 was considered significant.
Results
Food intake, body weight, faecal fat, blood glucose and plasma insulin
All rats finished the experimental diets during the night. The intake of standard rat
chow, i.e. the free eating of standard chow after finishing 15 g of experimental diet, was
significantly decreased in the thylakoid-fed rats compared with the control-fed rats
(P = 0·003; Fig. 1). No
difference in body weight between the groups was observed. The content of faecal fat was
unchanged in either the thylakoid or the control group from day 0 to day 10. Plasma
insulin concentration at 120 min after the OGTT was significantly lower
(P = 0·008) for the thylakoid group compared with the control group
(Fig. 2). No significant difference was found
for blood glucose concentrations after the OGTT at any time point (Fig. 3).
Fig. 1.
Intake of standard rat chow during the 10 d experiment by animals fed a
thylakoid-enriched diet (– –▵– –) or a control diet (––•––). Values are means, with
standard errors represented by vertical bars. Intake was significantly reduced in
the thylakoid-fed animals compared with control animals
(P = 0·003).
Fig. 2.
Plasma concentration of insulin at 120 min after an oral glucose tolerance test in
animals fed a thylakoid-enriched diet or a control diet for 10 d. Values are
medians, with ranges represented by vertical bars, and 25th and 75th percentiles
represented by the box. ** Median value was significantly lower than that of the
control group (P = 0·0082).
Fig. 3.
Blood glucose levels at 0, 15, 30, 45, 60, 90 and 120 min after an oral glucose
tolerance test in animals fed a thylakoid-enriched diet (– –▵– –) or a control diet
(––•––) for 10 d. Values are means, with standard errors represented by vertical
bars. Mean values of the control and thylakoid groups were not significantly
different at any time.
Intake of standard rat chow during the 10 d experiment by animals fed a
thylakoid-enriched diet (– –▵– –) or a control diet (––•––). Values are means, with
standard errors represented by vertical bars. Intake was significantly reduced in
the thylakoid-fed animals compared with control animals
(P = 0·003).Plasma concentration of insulin at 120 min after an oral glucose tolerance test in
animals fed a thylakoid-enriched diet or a control diet for 10 d. Values are
medians, with ranges represented by vertical bars, and 25th and 75th percentiles
represented by the box. ** Median value was significantly lower than that of the
control group (P = 0·0082).Blood glucose levels at 0, 15, 30, 45, 60, 90 and 120 min after an oral glucose
tolerance test in animals fed a thylakoid-enriched diet (– –▵– –) or a control diet
(––•––) for 10 d. Values are means, with standard errors represented by vertical
bars. Mean values of the control and thylakoid groups were not significantly
different at any time.
Bacterial quantification and identification
Lactobacilli were significantly increased in the ileal mucosa in the thylakoid group
compared with the control group, as demonstrated both by viable count
(P = 0·007; Fig. 4) and by qPCR
(P = 0·032; Fig. 5). No
difference was observed on the caecum or colonic mucosa. Moreover, a significant decrease
of lactobacilli in the faecal samples of the thylakoid group was found with qPCR
(P = 0·007; Fig. 5).
Fig. 4.
Viable count (colony-forming units (CFU)/g tissue) of lactobacilli on the mucosa of
the ileum, caecum and colon and in the faeces of animals fed a thylakoid-enriched
diet (■) or a control diet (□) for 10 d. Values are medians, with ranges represented
by vertical bars, and 25th and 75th percentiles represented by the box. ** Median
value was significantly higher compared with that of the control group
(P = 0·007). No differences were seen in the caecum, colon and
faeces.
Fig. 5.
Quantitative PCR analyses of lactobacilli on the ileum, colon mucosa and in the
faeces (log number of amplicon copies/g wet weight) of animals fed a
thylakoid-enriched diet (■) or a control diet (□) for 10 d. Values are means, with
standard errors represented by vertical bars. * Mean value was significantly higher
than that of the control group (P = 0·032). ** Mean value was
significantly lower than that of the control group (P = 0·007). No
difference was observed in the colon.
Viable count (colony-forming units (CFU)/g tissue) of lactobacilli on the mucosa of
the ileum, caecum and colon and in the faeces of animals fed a thylakoid-enriched
diet (■) or a control diet (□) for 10 d. Values are medians, with ranges represented
by vertical bars, and 25th and 75th percentiles represented by the box. ** Median
value was significantly higher compared with that of the control group
(P = 0·007). No differences were seen in the caecum, colon and
faeces.Quantitative PCR analyses of lactobacilli on the ileum, colon mucosa and in the
faeces (log number of amplicon copies/g wet weight) of animals fed a
thylakoid-enriched diet (■) or a control diet (□) for 10 d. Values are means, with
standard errors represented by vertical bars. * Mean value was significantly higher
than that of the control group (P = 0·032). ** Mean value was
significantly lower than that of the control group (P = 0·007). No
difference was observed in the colon.A significantly higher incidence of Lactobacillus reuteri
(P = 0·03) and a lower incidence of Lactobacillus
johnsonii (P = 0·003) were found on the ileal mucosa for the
thylakoid group compared with the control group by 16S rDNA sequencing of isolates picked
randomly from Rogosa agar plates (Table 2). In
the colon mucosa, a significantly lower incidence of Lactobacillus
johnsonii (P = 0·01) as well as a tendency for higher incidence
of Lactobacillus reuteri (P = 0·09) were found for the
thylakoid group compared with the control group (Table
2).
Table 2.
Incidence of different Lactobacillus spp. found by 16S rDNA
sequencing of isolates picked randomly from Rogosa agar plates of ileal and colonic
mucosal samples
Control group
Thylakoid group
Counts
%
Counts
%
P
Ileum
Lactobacillus reuteri
11/29
37·9
28/31
90
0·03
Lactobacillus johnsonii
17/29
58·6
3/31
10
0·003
Lactobacillus gasseri
1/29
3·4
0/31
0
NS
Lactobacillus ruminis
0/29
0
0/31
0
NS
Colon
Lactobacillus reuteri
10/25
40
21/25
84
0·09
Lactobacillus johnsonii
13/25
52
2/25
8
0·01
Lactobacillus gasseri
0/25
0
1/25
4
NS
Lactobacillus ruminis
2/25
8
1/25
4
NS
Incidence of different Lactobacillus spp. found by 16S rDNA
sequencing of isolates picked randomly from Rogosa agar plates of ileal and colonic
mucosal samplesAnalyses of bifidobacteria, on the mucosa of the ileum and colon and in the faeces by
qPCR, showed similar results for both groups (data not shown). In the thylakoid group, a
significantly decreased viable count on MW agar (claimed to be selective for
bifidobacteria) was found in the faeces (P = 0·0006), on the caecum
(P = 0·010) and on the colon mucosa (P = 0·021),
compared with the control group (Fig. 6). However,
by 16S rDNA sequencing of isolates picked randomly from MW agar plates of both groups, it
was shown that the bifidobacteria represented less than 25 % of these bacterial isolates.
Due to insufficient selectivity of the traditional plating methods, the randomly picked
bacteria from these plates were identified as Staphylococcus,
Kocuria and Bacillus simplex (data not shown). Data
from qPCR, sequencing and viable count indicate that bacteria that were decreased by
thylakoids did not include bifidobacteria. Analyses of Enterobacteriaceae
and Bacteroides resulted in no significant difference between the
thylakoid and control groups.
Fig. 6.
Viable count (colony-forming units (CFU)/g tissue) of bacteria on modified
Wikins–Chalgren (MW) media (claimed to be selective for bifidobacteria) on the
mucosa of the ileum, caecum and colon and in the faeces of animals fed a
thylakoid-enriched diet (■) or a control diet (□) for 10 d. Values are medians, with
ranges represented by vertical bars, and 25th and 75th percentiles represented by
the box. * Median value was significantly lower in the caecum
(P = 0·0104) and colon (P = 0·0207) than that of
the control group. *** Median value was significantly lower in the faeces
(P = 0·0006) than that of the control group. No difference was
observed in the ileum.
Viable count (colony-forming units (CFU)/g tissue) of bacteria on modified
Wikins–Chalgren (MW) media (claimed to be selective for bifidobacteria) on the
mucosa of the ileum, caecum and colon and in the faeces of animals fed a
thylakoid-enriched diet (■) or a control diet (□) for 10 d. Values are medians, with
ranges represented by vertical bars, and 25th and 75th percentiles represented by
the box. * Median value was significantly lower in the caecum
(P = 0·0104) and colon (P = 0·0207) than that of
the control group. *** Median value was significantly lower in the faeces
(P = 0·0006) than that of the control group. No difference was
observed in the ileum.Analyses of the microbiota with T-RFLP and PCA on the ileal and colon mucosa with both
MspI and AluI for DNA digestion did not show any
difference between the thylakoid and control groups (data not shown). In the faecal
sample, however, different microbial compositions were observed in the two groups with
PCA, as well as a more homogeneous microbiota in the thylakoid group compared with the
control group (Fig. 7(a) and (b)). No significant differences between the thylakoid and control
groups were found for bacterial diversity after calculations by the Shannon–Wiener
diversity index (data not shown).
Fig. 7.
Principal component analysis (PCA) of terminal restriction fragment length
polymorphism (T-RFLP) data from (a) MspI and (b)
AluI digestion of bacterial DNA of faecal samples in the control
animal (▵) and thylakoid animal (•) groups. The microbiota in the faecal samples
from the control and thylakoid animal groups are completely different from each
other. (□), T-RFLP peaks (bacterial groups).
Principal component analysis (PCA) of terminal restriction fragment length
polymorphism (T-RFLP) data from (a) MspI and (b)
AluI digestion of bacterial DNA of faecal samples in the control
animal (▵) and thylakoid animal (•) groups. The microbiota in the faecal samples
from the control and thylakoid animal groups are completely different from each
other. (□), T-RFLP peaks (bacterial groups).No significant differences between day 0 and day 10 were found in the faecal samples in
either the thylakoid-fed or control-fed rats regarding Enterobacteriaceae
and bifidobacteria.
Discussion
Addition of thylakoids to the diet for 10 d in the experimental rat model resulted in three
main findings: the gut microbiota of the rat was modulated as lactobacilli were increased
and supposedly harmful bacteria were reduced, the intake of food was decreased, and the
insulin response after an OGTT was changed.In the thylakoid group, an increased amount of ileal lactobacilli and a decreased amount of
faecal lactobacilli were found, suggesting that thylakoids cause an increased ileal mucosal
colonisation of lactobacilli. In fact, several studies have shown that specific strains of
lactobacilli have the ability to colonise the intestinal mucosa in high
numbers(
,
). The identification of the lactobacilli by 16S rDNA sequencing showed
that Lactobacillus reuteri was more pronounced in the ileal mucosa and, to
a lesser extent, in colonic mucosa in the thylakoid group. Lactobacillus
johnsonii was less pronounced in both ileal and colonic mucosa in the thylakoid
group compared with the control group.These novel findings demonstrate that small-intestinal mucosal microbiota can be affected
by dietary supplementation, and specifically by the ingestion of thylakoid membranes. Recent
studies have shown that Lactobacillus reuteri has health-promoting effects
by restricting the growth of harmful bacteria(
–
). Therefore, it is of interest that thylakoids were found to decrease
Gram-positive bacteria such as Staphylococcus spp.,
Kocuria and Bacillus simplex.The mechanism behind the beneficial effect of thylakoids in relation to microbiota is not
known and needs to be further studied. There are two possible explanations. One is that the
thylakoids themselves influence the growth of the bacteria in the intestine directly at the
molecular level. The other explanation is an indirect effect of thylakoids, whereby a
reduction in appetite and food intake may affect bacterial composition in the intestine.Lactobacilli have been regarded as anti-obesity factors(
,
,
,
). Elimination of Gram-positive bacteria from the gut appears to be
important for achieving energy balance, e.g. overweight children have an increased growth of
Gram-positive bacteria such as Stapholycoccus aureus compared with
normal-weight subjects(
,
). Moreover, the lactobacilli species Lactobacillus
rhamnosus GG and Lactobacillus gasseri have been found to reduce
adiposity and inflammation associated with obesity(
,
).The anti-obesity effect of thylakoids can now be described both as an effect on appetite
and energy metabolism and from now onwards, in addition, as a potential modulator of the gut
microbiota.The second main finding of this study was that thylakoid supplementation to the diet for
10 d decreased the intake of standard rat chow. This supports earlier findings of a
long-term study with mice given free access to thylakoid-incorporated mouse chow, which
resulted in decreased food intake, body weight and percentage of body fat, compared with
control-fed mice(
). The present decreased intake of standard rat chow in the thylakoid
group indicates an increased satiety after supplementation of thylakoids. It can be
speculated that these results are due to the deviated microbiota, since several studies in
both animals and human subjects have shown interactions between the microbiota and body
weight(
–
). Prebiotics, i.e. non-bacterial components that beneficially affect the
host by stimulating growth and/or activity of the microbiota, have been found to affect food
intake and several gut hormones regulating satiety and hunger(
–
). Since the supplementation of thylakoids has been found to give similar
effects(
–
,
), they could be viewed as a prebiotic agent.The third finding was a decreased insulin response after an OGTT at day 10 in the thylakoid
group, while no difference in blood glucose levels was observed between the groups. Similar
findings were reported in a short-term single-meal study in human subjects, where a reduced
insulin response was found, although blood glucose levels were unchanged(
). The long-term effects of thylakoids decreasing insulin levels,
presented here, have, however, never been shown before. A decreased passage of glucose
during the experimental period of 10 d would theoretically result in a lower secretion of
insulin, resulting in higher insulin sensitivity. It has previously been reported that
thylakoids, in a dose-dependent way, decrease the in vitro uptake of
methyl-glucose over the rat intestinal wall(
). The reason for this decrease could be either an indirect cause of a
steric hindrance formed by thylakoids binding to the mucosa of the intestine, or less
likely, a direct cause of thylakoids binding to glucose molecules(
). Also, the barrier of the intestine has been proposed to be important
for preventing diabetes, where an increased permeability of the intestine might lead to
insulin resistance(
). The formation of an intestinal steric hindrance by thylakoids could
thereby reinforce the intestinal wall. However, since the glucose uptake was the same in
thylakoid-fed and control-fed animals, this explanation seems less likely.Another explanation for the decreased insulin response could be the observed modulation of
the microbiota. Recent studies have proposed that the microbiota modulate lipid and glucose
homeostasis, by affecting the metabolism in the liver and adipose tissue(
). Furthermore, the compositions of the microbiota have been found to
affect the down- or up-regulation of gene expression, which may promote
adiposity(
) or decrease insulin and blood glucose concentrations(
). Moreover, several strains of lactobacilli and bifidobacteria have been
reported to have anti-diabetic effects, by preventing elevation of blood glucose and
reducing insulin responses(
–
). The explanation for these effects, however, is mainly prevention of
immune-mediated destruction of pancreatic β-cells. Thylakoids have, in a previous mouse
experiment, been found to reduce insulin levels and adiposity(
). This could hypothetically be a result of a changed microbiota, through
interaction with the adipose tissue.To conclude, the addition of thylakoids to the diet for 10 d affects the intestinal
composition of the microbiota by increasing the ileal colonisation of lactobacilli. At the
same time thylakoids were found to reduce food intake as well as insulin levels after an
OGTT, without affecting glucose levels. The reduced insulin levels may be a consequence of
the changed intestinal composition of the microbiota. More studies of the interaction of
thylakoids with the microbiota, and the question whether thylakoids can be regarded as a
prebiotic agent, remain to be investigated further.
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Authors: Y Kadooka; M Sato; K Imaizumi; A Ogawa; K Ikuyama; Y Akai; M Okano; M Kagoshima; T Tsuchida Journal: Eur J Clin Nutr Date: 2010-03-10 Impact factor: 4.016
Authors: Fredrik Bäckhed; Hao Ding; Ting Wang; Lora V Hooper; Gou Young Koh; Andras Nagy; Clay F Semenkovich; Jeffrey I Gordon Journal: Proc Natl Acad Sci U S A Date: 2004-10-25 Impact factor: 11.205
Authors: Ruth E Ley; Fredrik Bäckhed; Peter Turnbaugh; Catherine A Lozupone; Robin D Knight; Jeffrey I Gordon Journal: Proc Natl Acad Sci U S A Date: 2005-07-20 Impact factor: 11.205
Authors: Hyang Mi An; Shin Young Park; Do Kyung Lee; Jung Rae Kim; Min Kyeong Cha; Si Won Lee; Hyung Taeck Lim; Kyung Jae Kim; Nam Joo Ha Journal: Lipids Health Dis Date: 2011-07-12 Impact factor: 3.876