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The Effect of Lactulose on the Composition of the
Intestinal Microbiota and Short-chain Fatty Acid
Production in Human Volunteers and a Computercontrolled Model of the Proximal Large Intestine
Koen Venema, Marleen H.M.C. van Nuenen, Ellen G. van den Heuvel1, Wietske Pool2 and
Jos M.B.M. van der Vossen
From the TNO Nutrition and Food Research, Department of Nutritional Physiology, PO Box 360, 3700 AJ Zeist, The
Correspondence to: Dr K. Venema, TNO Nutrition and Food Research, Department of Nutritional Physiology, PO Box
360, NL-3700 AJ Zeist, The Netherlands. Tel.: /31 306944703; Fax: /31 306944928; E-mail:
Microbial Ecology in Health and Disease 2003; 15: 94/105
The objective of this study was to compare the in vivo effect of lactulose on faecal parameters with the effect in a dynamic, computercontrolled in vitro model of the proximal large intestine (TIM-2). Faecal samples from 10 human volunteers collected before (non-adapted)
and after 1 week of treatment (10 g/day) with lactulose (lactulose-adapted) were investigated. Parameters were compared immediately in the
faecal samples, and after incubation in the in vitro model of the large intestine. After an adaptation period of the faecal microbiota in the in
vitro model of the proximal colon, lactulose (10 g/day) was fed to the microbiota over a 48-h period. Samples taken from the model were
investigated for microbiota composition and metabolite production (short-chain fatty acids (SCFAs) and lactate). No changes in the faecal
parameters pH, dry weight or SCFA ratio were observed in the in vivo samples. However, the results show a major change in the ratio of
SCFAs produced in the in vitro model, with a drastic reduction of butyrate production on lactulose. This was clear in the non-adapted
microbiota by the observed arrest in butyrate production 24 h after the start of lactulose feeding. However, in the adapted microbiota
butyrate production was already low from the start of the experiment. In fact, only the microbiota of one of the 10 individuals still produced
significant amounts of butyrate after lactulose adaptation, the concentration in the other samples was extremely low. Similarly, in the in vitro
model lactate production of the non-adapted microbiota started after approximately 24 h, whereas the adapted microbiota produced lactate
from the start. In faecal (in vivo ) samples no changes in microbiota composition were obvious, except for a significant increase in
Bifidobacterium counts after lactulose feeding. With classic plating techniques, the in vitro samples showed an increase in Lactobacillus and
Enterococcus species. With denaturing gradient gel electrophoresis, a clear change in banding pattern was observed, indicating a shift in
microbiota composition. When the major bands that appeared after lactulose feeding in the in vitro model were excised and sequenced, the
sequences showed homology to Lactobacillus and Enterococcus species. This is in agreement with the classic plating technique as well as with
the observed increase in lactate production. Sampling in vivo at ‘the site where it all happens’ (the proximal colon) is difficult and
inconvenient. We conclude that the in vitro model for the proximal colon reflects much better the fermentation of lactulose, in both
metabolite production and changes in microbiota composition, than do faecal samples from an in vivo experiment. Therefore, the in vitro
model is an excellent tool with which to study bioconversion of functional food components and/or drugs. Key words: Lactulose, in vitro
large intestinal model, in vivo study, SCFA, microbiota, DGGE, FISH.
Lactulose is a synthetic disaccharide (4-O-b-D-galactosylD-fructose, molecular weight 342.3) which does not exist in
nature. It is produced in small amounts during heat
treatment of milk. Lactulose can be made on a large scale
from lactose by alkaline isomerization in which galactose is
linked to fructose as a b-1-4-glycoside. Lactulose is thought
to have many potential health applications, ranging from
stimulation of beneficial bacteria in the intestinal microbiota to the treatment of severely ill, chronic hepatic
encephalitic patients (1). Lactulose is neither digested in
nor absorbed from the stomach and small intestine.
Lactulose has been shown to increase Ca2 absorption in
postmenopausal women (2) and to affect the composition
of the intestinal microbiota and short-chain fatty acid
(SCFA) production in vivo (3, 4). In the caecum and
proximal colon lactulose is anaerobically fermented by the
indigenous microbiota. This is evidenced by the production
of hydrogen and/or methane (5/7) and by the production of
lactic acid (4, 8) and SCFAs (9), especially after adaptation
to lactulose (4). In vitro studies with individual strains have
1 Present address: Friesland Coberco Dairy Foods, PO Box 87,
7400 AB Deventer, The Netherlands.
2 Present address: RijksUniversiteit Groningen, Kerklaan 30,
9751 NN Haren, The Netherlands.
# Taylor & Francis 2003. ISSN 0891-060X Microbial Ecology in Health and Disease
DOI: 10.1080/08910600310019895
shown that lactulose can act as a substrate for many lactic
acid bacteria, including gastrointestinal genera and can
support their growth. In healthy adults the intake of 3 g of
lactulose per day for 2 weeks resulted in a significant
increase in the number of Bifidobacterium in faecal samples.
The numbers of (lecithinase-positive) clostridia and Bacteroidaceae decreased significantly (10, 11). In cirrhotic
patients treatment with lactulose for 10 days resulted in a
higher number of faecal lactobacilli (12). The production of
lactic acid and SCFAs resulted in a lower colonic and faecal
pH, the latter depending on the dose, ranging from pH 6 (20
g/day) (4) to pH 5 (/100 g/day) (3). The ultimate function
of SCFAs in the large intestine, such as stimulation of
mucosal proliferation and the suggested inhibitory effect of
butyrate on cancer, is not completely understood. However,
the possible health-promoting effects of butyrate in particular (13) have resulted in an increased interest in SCFA
production in the large intestine and the effect of certain
food or pharmaceutical compounds on the production of
However, one drawback of analysing faecal samples is the
fact that they do not necessarily represent quantitatively
what happens in the different parts of the colon. SCFAs are
predominantly produced in the proximal part of the colon,
where most of the carbohydrate fermentation takes place.
But they will be absorbed for a considerable amount by the
colonic epithelium during subsequent transport of the
chyme to the distal colon. Thus, amount and ratio of
SCFAs recovered in the faeces is not representative of those
produced in the proximal colon. So, the human being is a
‘model’ with various drawbacks. The most important ones
are ethical constraints, high costs and limitations in
sampling from ‘the site where it really happens’. Laboratory
models which simulate the successive kinetic conditions in
the gastrointestinal tract, including an active microbiota of
human origin, can be an alternative. Several computercontrolled models have been developed for this purpose (14,
15). Also TNO has developed dynamic, computer-controlled in vitro gastrointestinal models, in which the
successive conditions in the lumen of the gastric and small
intestinal compartments (16) and in the large intestine (17)
can be simulated in an accurate and reproducible manner.
This offers the opportunity to compare different ingested
products under identical and standardized conditions.
These models are unique tools with which to study the
stability, release, digestibility, absorption and bioconversion
of nutrients, chemicals and pharmaceuticals in the gastrointestinal tract (18). The model simulating the (proximal)
large intestine (TIM-2) has recently been shown to be a
valuable tool in investigating the mechanistic effects behind
the mode of action of prebiotics, such as inulin (19). This
model has been developed and validated using data from
sudden death individuals (17). In the model comprising the
large intestine (TIM-2) the following standardized conditions are simulated: body temperature, pH in the lumen,
delivery of a pre-digested substrate from the ‘ileum’, mixing
and transport of the intestinal contents, absorption of
water, and the presence of a complex, high density,
metabolically active, anaerobic microbiota of human origin.
To prevent growth inhibition of the microbiota by the
microbially produced metabolites (primarily SCFAs and
lactate), these metabolic products are absorbed from the
system via a semi-permeable membrane inside the lumen of
the model (17). In this way, a human microbiota could be
maintained stably in TIM-2 for up to 3 weeks, without
changes in composition or activity.
The objective of this study was to compare the composition of the microbiota and production of SCFAs in faecal
samples derived from human volunteers with those in
samples obtained from a dynamic, computer-controlled in
vitro model of the proximal large intestine (TIM-2)
inoculated with the faecal microbiota of the human
volunteers, using lactulose as a test compound. We show
here that the use of a validated model containing a complex
microbiota of human origin allows a better exploration of
the effect of lactulose ‘at the site where it all happens’ (the
proximal colon) than analyses of faecal matter.
Study substance
The study substance for the in vivo trial consisted of 10 g
lactulose (Solvay Pharmaceuticals, Weesp, The Netherlands) per day, dissolved in 100 ml water with 100 mg
benzoic acid. The pH of all solutions was between 3.0 and
3.2. The solutions were prepared by a pharmacy and packed
in bottles in individual daily portions and stored in the
refrigerator (B/88C) until use. The study substance was
consumed at breakfast for 7 days, starting at day 10.
For the experiments in the in vitro model of the large
intestine (TIM-2; described below), 10 g lactulose per day
were added to a pre-digested food (slightly modified from
ref. 14) and introduced gradually into the model. The predigested food contained (per litre): 2.5 g K2HPO4.3H2O, 4.5
g NaCl, 0.005 g FeSO4.7H2O, 0.5 g MgSO4.7H2O, 0.45 g
CaCl2.2H2O, 0.4 g ox bile, 0.4 g cysteine-HCl, 4.7 g pectin,
4.7 g xylan, 4.7 g arabinogalactan, 4.7 g amylopectin, 23.5 g
casein, 39.2 g starch, 17 g Tween 80, 23.5 g bactopeptone,
plus 1 ml of a vitamin mixture containing (per litre): 1 mg
menadione, 2 mg D-biotin, 0.5 mg vitamin B12, 10 mg
pantothenate, 5 mg nicotinamide, 5 mg p-aminobenzoic
acid and 4 mg thiamine.
Study subjects
Ten apparently healthy postmenopausal women aged between 55 and 64 years (average 60.69/2.5) with body mass
index between 22.4 and 30.0 kg/m2 (average 25.29/2.8)
participated in this study. Exclusion criteria, apart from
Effect of lactulose on SCFA production 95
general health parameters, included lactose intolerance,
known hypersensitivity to lactulose or its components,
known allergy to benzoic acid, smoking, alcohol consumption above three glasses per day, vegetarian, vegan or
macrobiotic diet, and any medication that might influence
the outcome of the study. All participants signed an
informed consent before the start of the study. The study
was approved by the Medical Ethics Committee of TNO
under study-code 99/34.
Design of the human study.
The in vivo study period lasted 17 days during which the
subjects were given a list of liquid, fermented dairy products
and foods containing non-digestible carbohydrates and
dietary fibre for exclusion from their diet during the total
in vivo study period. For the rest, diet was not controlled.
From day 10 to 17 lactulose was consumed during breakfast
(Fig. 1). On day 8, 2 days before the start of the lactulose
treatment, and on day 17, after 7 days of lactulose
treatment, fresh faecal samples were collected and analysed
for microbial composition and SCFA concentrations. In
addition, these samples (hereafter called non-adapted
microbiota (NAM) and adapted microbiota (AM) for the
microbiota collected on day 8 and day 17, respectively) were
used as inoculum for the in vitro experiments with lactulose
in the TIM-2 in vitro system (described below). Body weight
was measured before and after lactulose treatment.
On day 8 and on day 17 all subjects brought a faecal
sample to the institute within 2 h after defecation. Handling
of the fresh faecal samples took place in an anaerobic glove
box. For bacterial enumeration 2/3 g of fresh faeces were
taken from the centre of the bolus, transferred into
transport media and homogenized with an ultraturrax.
Three cryotubes containing glycerol (final concentration
20%) were filled with the faecal suspension and stored in
liquid nitrogen (/1968C) until microbiological analysis.
After measuring faecal pH, five samples were taken from
the fresh faeces and stored at /208C for analysis of dry
matter content and SCFAs. The dry matter content was
determined in all samples by drying about 1 g of a sample in
a pre-weighed tube in an oven at 1608C until no loss of
weight could be detected. Another 30-g portion of the fresh
faecal sample was used to carry out the in vitro experiments
in the TIM-2 system.
Dynamic in vitro model of the large intestine (TIM-2)
TNO’s in vitro model of the proximal large intestine (TIM2) simulates the average conditions in the lumen of the
human proximal colon (17). The model consisted of a
number of linked glass units with flexible walls inside (Fig.
2). Body temperature and peristaltic movements were
achieved by pumping water at 378C into the space between
the glass jacket and the flexible wall at regular intervals. The
computer controlled the sequential squeezing of the walls,
causing the chyme to be mixed and transported through the
system. The model was equipped with hollow-fibre semipermeable membranes inside the lumen of the model to
remove water and fermentation products, such as SCFAs. In
addition, they maintained physiological concentrations of
small molecules, such as electrolytes, and prevented product
inhibition of enzymes due to accumulation of microbial
metabolites. A constant volume of the luminal content was
maintained by water absorption controlled by a level sensor.
The environment in the model was kept strictly anaerobic
by flushing with gaseous nitrogen, to allow for the growth
of a dense, complex microbiota, comparable to that found
in humans in the first part of the colon (caecum/proximal
colon). The pH of 5.8 in the proximal colon was controlled
via the computer by using a pH sensor in combination with
NaOH secretion.
Fig. 1. Study design.
96 K. Venema et al.
Study design of in vitro experiments
In four successive runs, two with NAM and two with AM,
five TIM-2 systems were inoculated in parallel within 5/6 h
after defecation by the human volunteers. The inoculum
was a mixture of 30 g of faeces and 80 ml of pre-digested
food. After stabilization of the microbiota for 16 h on the
pre-digested food, 10 g of lactulose per 24 h were added to
this medium and gradually introduced into the system. In
the experiments with the microbiota adapted to lactulose
(collected on day 17 of the in vivo study), the overnight
stabilization was directly on the standard medium supplemented with 10 g of lactulose per 24 h (Fig. 1). Besides
luminal addition of lactulose, the study substance was also
added to the dialysis fluid (1 g/L) to prevent loss of
lactulose during the dialysis process. During each experimental run, metabolites and microbiota composition were
measured in all models after overnight stabilization (t0) and
after 8, 24, 32 and 48 h of lactulose feeding.
SCFAs and lactate analyses
SCFAs (acetic, propionic, butyric, valeric, iso-valeric and
iso-butyric acid) were analysed in fresh faeces collected
from the human volunteers on days 8 and 17, and in both
lumen and dialysis samples taken from the in vitro model.
Analysis was performed on a gas chromatograph (GC;
Chrompack CP9001, Varian, Bergen op Zoom, The Netherlands) according to the method described by Jouany (20).
After centrifugation of the faecal and TIM-2 samples, the
supernate was diluted (7% by volume) with a mixture of
methanol, internal standard (2 mg/ml 2-ethyl butyric acid)
and formic acid (20%). Of this mixture 0.5 ml was loaded
onto a ‘wide-bore’ GC column (Stabilwax-DA; length 15 m;
ID 0.53 mm; film thickness 0.1 mm; Restek, Bad Homburg,
Germany) using a Chrompack CP9050 automatic sampler
(Varian). L-Lactate and D-lactate were analysed enzymatically in the supernatant of the samples from the large
intestinal model (not in the human faecal samples). The
assay (Roche Biochemicals, Mannheim, Germany) was
automated on a Cobas Mira Plus autoanalyser (Roche)
and is based on the principle of conversion of NAD into
Microbiological methods
All samples were serially diluted 10-fold in peptone
physiological salt solution (Oxoid, Haarlem, The Netherlands). Anaerobic bacterial groups were enumerated on prereduced media in a Bactron IV anaerobic glove box (IKS,
Leerdam, The Netherlands). Total anaerobic bacteria,
Bifidobacterium and Bacteroidaceae were counted on Reinforced Clostridium Blood-China Blue Agar (Oxoid), and
(sulphite-reducing) Clostridium on Perfringens Agar Base
Fig. 2. Schematic representation of the
in vitro model of the proximal colon
(TIM-2) (17). a, peristaltic compartments; b, pH electrode; c, pH control
by secretion of NaOH; d, hollow-fibre
semi-permeable membranes; e, level sensor; f, N2 gas inlet; g, inlet and outlet
valves; h, sampling-port; i, gas collection bag; j, ‘pre-digested food’ container.
Effect of lactulose on SCFA production 97
with a B. cereus selective supplement (Oxoid). These plates
were incubated at 378C under anaerobic conditions. The
facultative anaerobic bacteria were plated and incubated
under aerobic conditions, with the exception of lactobacilli
which were incubated anaerobically after aerobic plating.
Lactobacillus were counted on LAMVAB Agar (21),
Enterobacteriaceae on Violet Red Bile Glucose Agar
(Oxoid), and Enterococcus on Slanetz and Bartley Agar
During the in vitro experiments samples were taken from
the lumen of the TIM-2 system to determine the composition of the microbiota. These samples were immediately
frozen in liquid nitrogen after addition of glycerol (20%)
and stored at /1968C before analysis. LAMVAB selects for
vancomycin-resistant lactobacilli. Although this resistance
is common among lactobacilli isolated from the human
microbiota, plating on LAMVAB may lead to an underestimation of their numbers.
Denaturing gradient gel electrophoresis
For denaturing gradient gel electrophoresis (DGGE) both
RNA and DNA were isolated from the faecal and TIM-2
samples. One gram (faeces) or 1 ml (TIM-2 samples) were
centrifuged and the cells were resuspended in 1 ml of
TN150-buffer (10 mM Tris-HCl pH 8.0, 150 mM NaCl).
Subsequently, 0.3 g zirconium beads and 150 ml acidified
phenol were added and the cells were disrupted with a miniBeadbeater 8
(Merlin Diagnostic Systems, Rotterdam,
The Netherlands). After mixing with 150 ml of a mixture of
chloroform and iso-amylalcohol (24:1; v/v) it was centrifuged and the supernatant was used for isolation of RNA
and DNA. For isolation of RNA the supernatant was
further extracted with phenol/chloroform/iso-amylalcohol.
The nucleic acids were precipitated with sodium acetate and
ethanol. The precipitated nucleic acids were treated with 5
U DNAse in TNMC-buffer (20 mM Tris-HCl, pH 8.0, 10
mM NaCl, 6 mM MgCl2) for 30 min at 378C. After
additional phenol/chloroform/isoamylalcohol extractions,
the RNA was precipitated and resuspended in 100 ml of
10 mM Tris-HCl, pH 8.0. For DNA isolation, a similar
protocol was used, except that RNAse (100 mg/ml final
concentration) was used in TE-buffer (10 mM Tris-HCl, pH
8.0, 1 mM EDTA). The DNA was resuspended in 100 ml
TE-buffer. RT-PCR and PCR were performed using established protocols. The enzymes used were rTth polymerase
(Applied Biosystems, Foster City, CA, USA) and Taq
polymerase (Roche), respectively. The primers used were
U968-GC and L1401 (22). PCR amplification was carried
out in the thermal cycler Hybaid Omnigene (Biozym,
Landgraaf, The Netherlands). The reaction mixture (50
ml) contained approximately 25 pmol of each primer, 0.2
mM of each deoxyribonucleotide triphosphate (Roche), 1 ml
PCR buffer with MgCl2 (Roche), 100 pmol of the target
DNA and 2.5 U of Taq DNA Polymerase (Roche). DNA
fragments were amplified as follows: initial denaturation at
948C for 5 min, followed by 30 cycles consisting of
denaturation at 948C for 10 s, annealing at 568C for 20 s,
extension at 688C for 40 s and a 7-min final extension step
at 688C. The products were stored at /208C until analysis.
The PCR products were separated on a Bio-Rad Dcode
Universal Mutation Detection System (Bio-Rad Laboratories, Veenendaal, The Netherlands), using a urea gradient
from 50% to 60%. Electrophoresis was performed at 40 V
for 24 h at 608C. Silver staining of the separated PCR
products was performed on a Hoefer Automated Gelstainer
as described by the supplier (Amersham Biosciences,
Roosendaal, The Netherlands).
Sequencing and sequence analysis
DNA from bands cut from the DGGE gel was isolated
using the QIAquick PCR purification kit (Westburg,
Leusden, The Netherlands) according to the manufacturer’s
instructions. This DNA was used for re-amplification by
PCR as described above, and the PCR product was
sequenced directly with the ABI PRISM Big Dye Terminator Cycle Sequencing Ready Reaction Kit (Applied
Biosystems) using the supplier’s protocol. The sequence
products were analysed on an ABI PRISM 310 Genetic
Analyzer (Applied Biosystems). The sequences (between
254 and 340 nucleotides long depending on the fragment)
were compared to sequences deposited at the NCBI
database by using the online BLAST service.
Fluorescent in situ hybridization
Fluorescent in situ hybridization (FISH) was performed
according to the protocol described by Langendijk et al.
(22) with minor modifications. In short, after homogenization, 0.5 g of the samples was suspended in 4.5 ml of filtered
PBS, vortex mixed and centrifuged at low speed (700 g) to
remove large particles. Then 1 ml of the supernatant was
mixed with 3 ml of fresh 4% paraformaldehyde solution and
incubated overnight to fix the cells. Dilutions of the fixed
cells in PBS were spread over the surface of a gelatin-coated
slide. Hybridizations with fluorescein isothiocyanatecoupled probes were done overnight at 508C in the presence
of 0.9 M NaCl and 0.1% SDS. After hybridization, slides
were washed at the same temperature for 30 min, rinsed in
milli-Q water and air-dried. At this step DAPI (4?-6?diamidino-2-phenylindole) was added at a final concentration of 1.25 ng/ml for 5 min at 208C to stain all cells. The
slides were washed again, dried and mounted with 6 ml of

(Vector Laboratories, Peterborough, UK) on
each well. Images were recorded on a Zeiss fluorescent
microscope (Zeiss, Weesp, The Netherlands). Depending on
the amount of fluorescent cells, 10/20 microscopic fields
were counted. Fluorescein isothiocyanate probes (Isogen
Bioscience, Maarssen, The Netherlands) used were Eub338,
Bac303, Bif164, Chis150, Clit135, Ec1531, Ato291,
98 K. Venema et al.
Rbro730, Rfla729 and Rec482 (22/29). FISH was done
only with in vivo faecal samples.
Statistical analysis
Statistical analysis was carried out with an SAS statistical
package, version 8.2. The data were compared using the
paired Student’s t-test. Differences between treatments with
p values B/0.05 were considered to be significant. Data are
expressed as mean (SD).
Body weight, faecal pH and dry matter content
The intake of 10 g of lactulose per day had no significant
effect on body weight (72.69/8.3 before lactulose treatment;
72.29/8.3 after lactulose treatment; p/0.92), faecal pH
(6.99/0.8 before and 7.19/0.4 after lactulose treatment; p/
0.60) or dry matter content (25.99/4.4 before and 24.69/3.5
after lactulose treatment; p/0.45). An effect on softening
of the stool was not observed.
SCFAs and lactate
In vivo. Average molar ratios of SCFAs, as measured in
fresh faecal samples, showed no significant differences
between the faecal samples obtained from subjects before
and after the intake of lactulose (Table I). Lactate was not
analysed in fresh faecal samples.
In vitro. Results from the studies in the dynamic in vitro
model of the large intestine were rather different from the
above-described in vivo results. The cumulative total SCFA
production in vitro in time was the same for both the NAM
(Fig. 3A) and the AM (Fig. 3B). However, a statistically
significant lower amount of propionate was found for the
NAM (7.0 mmol 9/3.4 vs 12.0 mmol 9/6.6 for NAM and
AM, respectively; p/0.049), and a statistically significant
lower amount of butyrate for AM (21.2 mmol 9/16.4 vs 3.1
mmol 9/5.1 for NAM and AM, respectively; p/0.005). A
clear effect on molar ratios of SCFAs produced by the
different microbiotas was observed (Table I) with a decrease
in the butyrate ratio for AM compared with NAM as the
major difference. During the first 24 h the NAM produced
almost linear amounts of all three SCFAs. Thereafter,
acetate was still increasing, but the production of propionate and butyrate was arrested. During fermentation of
lactulose by the NAM the production of lactate was
observed only after 24 h (Fig. 3A). D-Lactate production
was higher than L-lactate production (data not shown). For
the AM butyrate production was low during the whole
experiment (Fig. 3B). In fact, a significant amount of
butyrate production could be detected in the microbiota of
Table I
SCFA ratios in fresh faecal samples from humans and in samples from the in vitro large intestinal model at t/48 h (average 9/SD; n/10)
Sample Acetate Propionate n-Butyrate Lactate
Fresh faecal samples NAM 62.4 (9/6.5) 20.4 (9/4.2) 17.2 (9/3.5) nd
AM 63.8 (9/5.5) 20.8 (9/4.6) 15.4 (9/2.8) nd
In vitro samples* NAM 68.7a (9/7.6) 8.2b (9/3.6) 23.0c (9/8.3) /
AM 79.9a (9/11.6) 16.8b (9/9.3) 3.2c (9/4.0) /
In vitro samples$ NAM 47.0 (9/17.5) 5.8 (9/3.0) 17.4d (9/11.5) 29.8 (9/29.5)
AM 41.9 (9/20.1) 7.7 (9/3.3) 1.5d (9/2.1) 48.9 (9/21.8)
NAM, non-adapted microbiota; AM, adapted microbiota; nd, not determined.
*Excluding lactate;
$including lactate.
aDifference between NAM and AM; p/0.02.
bDifference between NAM and AM; p/0.01.
cDifference between NAM and AM; p B/0.00001.
dDifference between NAM and AM; p/0.0008.
Fig. 3. Average SCFA (acetate, propionate and n -butyrate) and
lactate production during 48 h of 10 in vitro experiments of the
non-adapted microbiota (A) and lactulose adapted microbiota (B)
in the large intestinal model.
Effect of lactulose on SCFA production 99
only one of the 10 individuals. In all other nine microbiotas
production was very low or below the limit of detection. As
with the NAM, in the AM propionate production was
arrested after 24 h. The AM was able to produce lactate
from the start of the experimental period, immediately after
lactulose feeding (Fig. 3B). L-Lactate was produced in
higher quantities than D-lactate, which contrasted with the
NAM (data not shown).
In vivo microbiological composition
Bacterial counts in fresh faecal samples reached between
1010 and 1011 cfu/g (wet weight) for both the samples taken
at day 8 and day 17 (Table II). In comparing the average
composition (Table II) of the NAM with the AM an
increase in absolute numbers for Bifidobacterium (p B/
0.00001 both for FISH and the classic plating technique)
and (sulphite-reducing) Clostridium (NS) was found after
lactulose treatment. In addition, the numbers of Bifidobacterium and Bacteroides were similar for the classic plating
technique in comparison to the FISH technique. FISH was
also used for some additional groups of microorganisms for
three randomly selected faecal samples. Using the selective
probes an increase in Clostridium (p B/0.01) and Escherichia
coli (p/ 0.04) was detected in these samples after lactulose
treatment. The Atopobia /Collinsella and the Eubacterium /
Clostridium /Ruminococcus groups stayed at similar levels.
When evaluated separately, the Ruminococcus group decreased slightly in these samples after lactulose treatment
(p/0.04). It should be kept in mind that these analyses
were performed on only 3 of the 10 samples, and therefore,
at the moment it is not known how representative these
findings are. With the probes used, only approximately 65%
of the total microorganisms present were detected (Table
II). Other probes will be needed to study changes in
composition of the other bacterial groups.
In vitro microbiological composition
Table III shows the changes in microbiota composition
(absolute and in percentages) during the experiments in the
large intestinal model based on classic plating of the
microorganisms on (s)elective plates. FISH was not performed on these samples. For the NAM, a relative increase
of Bifidobacterium and decrease of Bacteroides occurred
after lactulose treatment (Table III). The AM showed a
relative decrease in Bifidobacterium (possibly caused by the
increase in other groups, see below), whereas the Bacteriodes population stayed proportionally similar. Especially in
the AM, but also detectable in the NAM, the Lactobacillus
and Enterococcus ratio increased. Also, numerically an
increase of lactobacilli and enterococci was observed after
lactulose feeding (Fig. 4). This occurred, irrespective of
previous lactulose feeding, for both the NAM and the AM
(p/0.009 and p/0.006 for Lactobacillus for NAM and
AM, respectively, and p/0.007 and p/0.006 for Enterococcus for NAM and AM, respectively). The effect was
similar in both cases (Table III).
Using DGGE of PCR fragments obtained from the 16S
rRNA gene region 968/1401 (E. coli numbering; containing the variable regions V6/V8) the changes in dominant
microbiota from one of the individuals in the TIM-2
samples were investigated (Fig. 5). Fig. 5 shows that after
Table II
Composition of the fresh faecal microbiota from humans determined by FISH and classic plating (average 9/SD; n/10)
Microorganism Probe NAM AM
FISH Plating FISH Plating
log10 (cfu/g) ratio (%) (log10 cfu/g) log10 (cfu/g) ratio (%) (log10 cfu/g)
Total bacteria Eub338 10.6 (9/0.2) 100 / 10.6 (9/0.2) 100 /
Bifidobacterium Bif164 8.6a (9/0.4) 1.4 8.8b (9/0.16) 9.5a (9/0.2) 9.5 9.6b (9/0.2)
Bacteroides Bac303 9.4 (9/0.7) 14.0 9.2 (9/0.41) 9.6 (9/0.5) 17.0 9.3 (9/0.4)
Clostridium* Chis150/ Clit135 B/7.35$c B/0.05 / 8.0c (9/0.4) 0.3 /
Atopobium/Collinsella* Ato291 9.1 (9/0.9) 6.5 / 9.3 (9/0.4) 5.1 /
E. coli* Ec1531 B/7.35d B/0.05 / 8.0d (9/0.6) 1.3 /
Ruminococcus* Rfla729/ Rbro730 9.3e (9/0.5) 6.2 / 9.1e (9/0.1) 2.7 /
Eubacterium/Clostridium/Ruminococcus* Rec482 10.0 (9/0.4) 31.0 / 10.1 (9/0.2) 27.1 /
Sulphite-reducing Clostridium / / / 5.0f (9/1.3) / / 5.9f (9/1.0)
Lactobacillus / / / 4.7 (9/1.6) / / 5.0 (9/2.0)
Enterococcus / / / 5.9 (9/1.0) / / 5.81 (9/1.3)
Enterobacteriaceae / / / 6.4 (9/1.4) / / 6.7 (9/1.5)
*Average of three randomly selected faecal samples.
$Detection limit for FISH is log10 7.35 cfu/g.
a, b, c, d, e, f: statistically significant difference between NAM and AM; p B/0.05.
100 K. Venema et al.
lactulose feeding a major shift occurred in the dominant
microbiota. Several new bands appeared (in PCR reactions
from DNA samples as well as from RNA samples) after
lactulose feeding, whereas other bands disappeared. Similar
shifts were seen in the microbiotas from the other individuals, although the exact positions of the bands that
appeared were not always identical (data not shown).
Several of the bands (circled in Fig. 5) were excised from
the gel and the nucleotide sequences were determined and
compared to sequences in the database (Table IV). From
this comparison it is clear that the bands corresponded to
Lactobacillus and Enterococcus species. It therefore appears
that, as was determined with plating on (s)elective plates,
numbers of lactobacilli and enterococci were higher after
lactulose feeding. Since DGGE shows patterns for the
dominant microbiota, it is also clear that no other
unculturable microorganisms were stimulated by lactulose
in this system in such a manner that they became part of the
dominant microbiota. However, it cannot be ruled out that
species present in very small amounts are also stimulated by
lactulose, but still remain below the level of detection for
We show here that addition of lactulose results in a
profound reduction of butyrate production. In the microbiota not adapted to lactulose (NAM) butyrate production
was arrested after 24 h; the microbiota adapted to lactulose
(AM) produced low amounts of butyrate right from the
start of the experiment. Propionate production was also
affected, although to a lesser extent than butyrate and only
markedly detectable in the NAM. It apparently takes
between 8 and 24 h (no samples were taken in between)
to change the metabolic activity of the NAM microbiota.
This is also reflected in the onset of production of lactate by
the NAM after 24 h. Lactate is immediately produced by
the AM. This, and the immediate low butyrate production,
shows that the AM was indeed adapted to lactulose. The
only significant difference in composition of the faecal
microbiota before and after lactulose treatment in humans
was an increase in Bifidobacterium , with a trend of an
increase in (sulphite-reducing) Clostridium . From the results in TIM-2 using both classic plating and DGGE, it is
clear that Lactobacillus and Enterococcus are largely
Table III
Average (n/10) bacterial composition in TIM-2 samples (absolute in cfu/ml and in percentages), inoculated with NAM and with AM, before
(t0) and after 2 days of lactulose intake (t48)
Microorganism NAM (log10 cfu/ml) NAM (%) AM (log10 cfu/ml) AM (%)
t0 t48 t0 t48 t0 t48 t0 t48
Total bacteria 8.7 (9/0.2) 8.9 (9/0.2) 100 100 9.1 (9/0.2) 9.2 (9/0.2) 100 100
Bifidobacterium 8.4 (9/0.5) 8.6 (9/0.8) 48.3 54.3 8.9 (9/0.1) 9.0 (9/0.5) 62.9 37.5
Bacteroides 8.4 (9/0.5) 8.5 (9/0.5) 51.1 38.7 8.6 (9/0.3) 8.8 (9/1.2) 36.2 36.7
Lactobacillus 5.5 (9/0.7) 7.1 (9/1.0) 0.08 1.86 5.7 (9/1.1) 7.1 (9/0.9) 0.31 13.1
Enterobacteriaceae 5.8 (9/1.1) 6.7 (9/0.3) 0.13 0.06 7.0 (9/0.8) 7.3 (9/0.7) 0.07 3.53
Enterococcus 6.6 (9/1.1) 7.9 (9/0.5) 0.34 4.44 6.0 (9/0.7) 7.5 (9/1.1) 0.48 9.25
Fig. 4. Average (9/SD) changes in
microbiota composition in the large
intestinal model. Data from all runs
(n/20) were taken. There were no
significant differences between nonadapted and lactulose-adapted microbiotas.
Effect of lactulose on SCFA production 101
stimulated by addition of lactulose (over 1.5 log increase for
both genera).
SCFAs (primarily acetate, propionate and butyrate) and
D- and L-lactate are the major metabolic products due to
microbial degradation of organic substrates (31, 32). Both
total acid production and SCFA ratios are used in in vivo
studies for the description of bacterial metabolic activities
of a typical microbiota. A drawback of analysing faecal
samples is the fact that they do not represent quantitatively
what happens in the proximal part of the colon where most
fermentation, including that of lactulose, takes place.
SCFAs are predominantly produced in this part of the
colon and will be absorbed by the body to a considerable
extent during subsequent transit of the chyme to the distal
colon and rectum. Consequently, the amount and ratio of
SCFAs recovered in the faeces will not reflect those resulting
from fermentation of lactulose in the proximal colon.
Indeed, our results from the human study show no
difference in faecal SCFA ratios between the control and
lactulose period (Table I). Even if in vivo samples from the
lumen of the proximal colon and the portal blood vein
could be taken, not all the SCFAs produced would be
measured (32). This is because butyrate in particular is used
as a substrate by colonocytes and therefore only low
amounts of this microbial metabolite are found in the
bloodstream (32). In the in vitro model of the proximal
colon used in the present study, these disadvantages are
absent. All SCFAs are detected, either in the lumen of the
model, or in the collected dialysis fluid. This makes it
possible to study mechanistically the effects of lactulose or
any other food compound or drug on microbial metabolite
production. Similar to what we found, the data available in
the literature show no effect of lactulose on butyrate in
faecal samples at the same dosage as that used in the present
study. At higher dosages (up to 160 g of lactulose per day),
the ratio of acetate and lactate increased (13). This is
consistent with the decrease in butyrate and propionate that
we found in the TIM-2 experiments. In batch incubations,
where metabolites accumulate, either a slight increase or a
decrease in butyrate ratios is measured on lactulose.
However, this is most likely caused by interconversion of
lactate into butyrate, a process which is more likely to take
place in a batch incubation in which the metabolites are not
removed, than in vivo , where the metabolites produced are
quickly taken up by the epithelium and do not accumulate
to the same degree. Incubation times in batch cultures are
usually long, allowing time for this interconversion to take
The TNO in vitro model has been developed and
validated using data from sudden death individuals (17).
Both with respect to composition and with respect to
metabolic activity, a faecal inoculum in the model has
been shown to simulate the data from these sudden death
individuals very well. In addition, we have performed
experiments in the model using different microbiotas from
dogs. The microbiotas originated from the caecum and from
faecal material (a microbiota from the terminal ileum was
studied as well). The microbiotas maintained in TIM-2 that
Fig. 5. DGGE analysis of samples from the large intestinal model
from one of the individuals. DGGE analysis was done on both
DNA samples (lanes 1/4) and RNA samples (lanes 5/8). Samples
from the start of the experiment in the in vitro model of the large
intestine (t0: lanes 1, 3, 5 and 7) were compared to samples taken at
the end of the experiment (t48: lanes 2, 4, 6 and 8). Both NAM
(lanes 1, 2, 5 and 6) and AM (lanes 3, 4, 7 and 8) samples were
analysed. The numbered arrows correspond with the PCR products
that were sequenced and of which the homology to database
sequences is shown in Table IV.
Table IV
Comparison of the excised DNA bands from the DGGE gel with
database sequences
E-value Homology (%)
PCR product 1
Lb. sp. oral clone CX036 0 100
Lb. vaginalis ATCC49540 0 99.7
Lb. reuteri DSM 20016 e128 B/97
PCR product 2
Uncultured bacterium S24-8 e149 98.6
Lb. reuteri DSM 20016 e144 97.6
PCR product 3
Lb. sp. oral clone CX036 e148 97.9
Lb. vaginalis KC19 e148 97.9
Uncultured bacterium S24-8 e148 97.9
PCR product 4
E. faecalis VRE no 1492 e128 99.2
For identical species, a sequence identity of /99.7% is taken (30).
102 K. Venema et al.
originated from either the caecum or faeces were shown to
have the same composition and microbial activity as those
of the microbiota when freshly obtained from the caecum,
supporting the hypothesis that the microbiota in TIM-2
does develop to resemble that of the caecum (unpublished
data). We hypothesize that this is also the case for a human
microbiota. A human microbiota could be maintained
stably in TIM-2 for up to 3 weeks on the standard predigested food, without changes in microbial composition or
activity (17).
The increase in bifidobacteria and clostridia in the
human trial is in agreement with data reported in the
literature (33, 34). However, as in the case for SCFA and
lactate production, changes in the faecal microbiota do not
reflect which microorganisms are responsible for fermentation of lactulose in the proximal colon. In fact, it is unlikely
that the stimulation of Clostridium is a direct effect of
lactulose, since Clostridium is known to produce butyrate,
whereas we have found that butyrate production in particular was very low after lactulose addition. In the in vitro
system, lactobacilli and enterococci were increased. This is
in agreement with the observed reduction of production of
butyrate and propionate, and the increase in lactate
production. However, the observed effect in vitro seems to
be in contrast to the effect found in the faecal samples. Since
TIM-2 simulates the proximal colon, we postulate that the
results in TIM-2 are a better reflection of the events taking
place in this part of the colon than are the results from the
faecal samples. In addition, the length of the experiments in
TIM-2 (48 h) was different to those of the in vivo trial (7
days). Perhaps additional microbiological shift would have
been found if the in vitro experiments had been carried out
for a longer period.
The AM was different in metabolic activity immediately
from the start of the experiment in TIM-2. Assuming that
this difference is not caused by the minor increase in
Bifidobacterium , which is corroborated by the fact that
lactobacilli and enterococci are primarily stimulated, we
concluded that the AM is metabolically adapted to lactulose, rather than compositionally adapted. This is a
phenomenon we have seen before. Microbiotas from healthy
individuals that do not seem to differ in composition (at
least based on tools available to us at the moment), differ
with respect to metabolic activity, and hence metabolite
production (data not shown). If the composition was hardly
or not changed, this must mean that the microbiotas were
metabolically predisposed or adapted to lactulose. Alternatively, different strains of the various genera present in
the complex faecal mixture are present with different
enzymatic activities (e.g. saccharolytic versus proteolytic).
The tools available are not sufficiently accurate and
discriminative to detect these differences at the strain level.
The results from the classic plating and FISH, for those
microorganisms for which the comparison can be made, are
in perfect agreement (Table II). Another set of probes was
used on a limited number of faecal samples. It would be
worthwhile to increase the number of group-, genera- or
species-specific probes to see if other changes in the
composition of the microbiota can be identified. From the
DGGE analyses it can be concluded that, apart from the
bands that were excised and sequenced, some additional
bands appear after lactulose addition. We are in the process
of investigating which microorganisms these PCR fragments originate from. The results from classic plating and
DGGE also seem to correlate well, since both show an
increase in lactobacilli and enterococci; however, there is a
discrepancy. The DGGE technique only investigates the
dominant microbiota. Based on this, we would expect an
even larger number of cfu/ml for lactobacilli and enterococci in the TIM-2 samples than is found with classic
plating, even when taking into account the fact that DGGE
is only semi-quantitative. We hypothesize that the (s)elective
media used in classic plating may be too selective to allow
for growth of all of the Lactobacillus and Enterococcus
species in the complex large intestinal microbiota. The
correlation between plating and DGGE is only accidental.
If lactulose would have also stimulated an unculturable
microorganism, there would be no correlation whatsoever
between plating and DGGE. Therefore, the state-of-the-art
molecular tools reveal changes in composition much better
than classical plating.
In conclusion, we postulate that TIM-2 is a valuable tool for
investigating, at a mechanistic level, the effect of food
components on the composition and activity of the large
intestinal microbiota and vice versa (results of present study
and ref. 35). In contrast to analysis of faecal samples, in
TIM-2 all metabolites that are actually produced can be
measured at ‘the site where it all happens’. In combination
with molecular tools to investigate the composition of the
microbiota it is even possible to determine which microorganisms are responsible for a certain effect. The present
example shows that lactulose results in a reduction of
butyrate production in the proximal colon in the in vitro
experiments. Our planned experiments using stable isotopes
in in vivo experiments should corroborate these findings in
the in vivo situation. We hypothesize that lactulose is the
preferred substrate, compared with the complex carbohydrates, for fermentation in the proximal part of the colon.
Whether or not this means that the other carbohydrates
present in the food are fermented to a lesser degree in the
proximal colon and therefore may end up further in the
colon to be fermented there is unknown at present.
However, it is worthwhile investigating this further, since
fermentation of carbohydrates in the transverse and distal
colon is hypothesized to reduce proteolytic fermentation,
with its concomitant production of various toxic metaboEffect of lactulose on SCFA production 103
lites, such as ammonia, phenol and p -cresol. We are
currently adapting TIM-2 to investigate this aspect.
We thank Hakim Rahaoui for technical assistance, Rob Leer for
sequencing the PCR fragments, and Robert Havenaar and Mans
Minekus for helpful discussions. This research was sponsored by
the Dutch Ministry of Economic Affairs, under grant no. and by Solvay Pharmaceuticals.
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Effect of lactulose on SCFA production 105

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