In vitro fermentation of carbohydrates by porcine faecal inocula and their influence on Salmonella Typhimurium growth in batch culture systems


  • Editor: Julian Marchesi

Correspondence: Adele Costabile, Food Microbial Sciences Unit, School of Chemistry, Food Biosciences and Pharmacy, University of Reading, PO Box 226, Reading RG6 6AP, UK. Tel.: +44 0 118 378 6218; fax: +44 0 118 931 0080; e-mail:


The aim of this study was to evaluate in vitro the influence of fermentable carbohydrates on the activity of porcine microbiota and survival of Salmonella Typhimurium in a batch culture system simulating the porcine hindgut. The carbohydrates tested were xylooligosaccharides, a mixture of fructooligosaccharides/inulin (FIN), fructooligosaccharides (FOS), gentiooligosaccharides (GEO) and lactulose (LAC). These ingredients stimulated the growth of selected Bifidobacterium and Lactobacillus species in pure cultures. In batch cultures, the carbohydrates influenced some fermentation parameters. For example, GEO and FIN significantly increased lactic acids compared with the control (no added carbohydrate). With the exception of LAC, the test carbohydrates increased the production of short-chain fatty acid (SCFA) and modified SCFA profiles. Quantitative analysis of bacterial populations by FISH revealed increased counts of the Bifidobacterium group compared with control and, with exception of FOS, increased Lactobacillus, Leuconostoc and Weissella spp. counts. Salmonella numbers were the lowest during the fermentation of LAC. This work has looked at carbohydrate metabolism by porcine microbiota in a pH-controlled batch fermentation system. It provides an initial model to analyse interactions with pathogens.


Salmonella infections in porcines damage both health and productivity. Intestinal infection results in the destruction or turnover of the intestinal mucosa, inducing inflammatory diarrhoea (Haraga et al., 2008). Furthermore, antibiotic resistance in Salmonella species found in farm animals can lead to increased morbidity and mortality, due to reduced efficacy of therapeutic antibiotics. Economic losses associated with Salmonella are not only due to infection in farm animals (Sockett & Roberts, 1991; Roberts et al., 2003; de Jong & Ekdahl, 2006) but also through entry into the human food chain, where they can cause zoonotic infections in humans.

Salmonella infection of farm animals is from multiple sources and also has the capacity to cause asymptomatic infections, thereby increasing dissemination. Recent research indicates that feeding management strategies are capable of exerting some control on Salmonella infection (Hansen, 2004; Fayol-Messaoudi et al., 2005; Kamphues et al., 2005). Colonization of the gastrointestinal tract (GIT) by pathogenic microorganisms is linked to environmental factors of the digesta and therefore, the composition and amount of ingested feed can influence colonization. The challenge is to learn how to manage the animal's feeding in order to modulate the gastrointestinal environmental conditions to suppress colonization by pathogens without causing negative effects to the animal's health and productivity.

Fermentation occurring in the monogastric GIT is recognized as having an important influence on health, both of the GIT itself and also of the host animal through stimulation of gut motility, improvement of energy yield, production of vitamins and the stimulation of gut immunity (Ewing & Cole, 1994). Furthermore, changes originating in the microbial ecosystem due to the fermentation processes are thought to interfere with the development of intestinal pathogens such as Salmonella Typhimurium. Although any dietary material that enters the large intestine (including resistant starch, dietary fibres, proteins and lipids) is able to be fermented by the microbiota, there are specific nondigestible carbohydrates that can induce fermentation by benign or potentially health-promoting indigenous bacteria, for example, lactic acid-producing microorganisms (Collins & Gibson, 1999; Shim et al., 2005; Loh et al., 2006), and may suppress or have no stimulatory effect on undesirable bacteria such as Salmonella (Gibson & Roberfroid, 1995; Oyarzabal & Conner, 1995). These nondigestible carbohydrates are called prebiotics and, in practice, are confined to oligosaccharides (Gibson et al., 2000). Apart from lactic acid, fermentation of prebiotics by these potentially health-promoting, indigenous bacteria would generate products from saccharolytic fermentation as has been observed in porcines (Mountzouris et al., 2006). Furthermore, in addition to the generation of lactic acid and short-chain fatty acids (SCFA) as antibacterial compounds, these bacteria often produce specific antimicrobials (De Vuyst & Leroy, 2007). Changes in the fermentation, together with the limitation of the nutrient sources for pathogenic bacteria, and the possible generation of inhibitory substances would be detrimental for the development of intestinal pathogens such as Salmonella. For example, Gantois et al. (2006) demonstrated that butyrate inhibited the invasion of tissue by Salmonella, specifically by downregulating the SPI1 of Salmonella Typhimurium.

Studies investigating the effect of the inclusion of prebiotics in the feed of porcines on Salmonella are scarce. Correa-Matos et al. (2003) fed 2-day-old piglets with a sow's milk replacer formula with or without a fructooligosaccharides (FOS) supplement (7.5 g L−1 at a rate of 15 mL kg−1 h−1) for 14 days and observed that inclusion of FOS reduced the severity of Salmonella Typhimurium infection-associated symptoms. Letellier et al. (1999) studied the effect of the inclusion of FOS (1%) in the water or feed of 12-day-old pigs for 28 days and observed a reduction of Salmonella shedding when the FOS was included in drinking water. However, other authors have not found a reduction of Salmonella shedding with the use of prebiotics (Burkey et al., 2004).

The beneficial effects of prebiotics (Krueger et al., 2002; Shim et al., 2005) could make them a valuable candidate for their inclusion in porcine feed in order to control Salmonella. However, their effectiveness may depend on the type of prebiotic and studies are needed to ensure their efficacy. Therefore, the objective of this study was to investigate in vitro the influence of different carbohydrates (as candidate prebiotics) on the fermentative activity of porcine microbiota and how this affects the survival of Salmonella Typhimurium. The results obtained could indicate which carbohydrate(s) may be included in the feed in order to reduce the incidence of Salmonella in pigs.

Materials and methods

Stock culture collection

In order to carry out a first screening of the prebiotic potential of the carbohydrates selected for the study, the growth rates of the eight bacterial strains listed below and Salmonella Typhimurium SL1344 in pure cultures were determined in the presence of individual carbohydrates. The bacterial strains were the following: Lactobacillus acidophilus NCIMB 30179 (PXN23), Lactobacillus rhamnosus NCIMB 30188 (PXN54), Lactobacillus casei NCIMB 30185 (PXN37), Lactobacillus plantarum NCIMB 30187 (PXN47), Bifidobacterium bifidum NCIMB 30179 (PXN23), Bifidobacterium longum NCIMB 30182 (PXN30), Bifidobacterium breve NCIMB 30180 (PXN25) and Bifidobacterium infantis NCIMB 30181 (PXN27). All bacterial species except L. plantarum (vegetable origin), were of human origin. Strains were kindly provided by Probiotics International Ltd (Protexin) (Somerset, UK). Strains were maintained at −70 °C in 15% (w/w) glycerol. Utilization of the carbohydrates by Salmonella Typhimurium was tested using a fully virulent nalidixic-acid-resistant derivative of the wild-type strain SL1344, a kind gift from David O'Connor (Southampton University).


The substrates used were commercial xylo-Oligo95P [xylooligosaccharides (XOS); Xylβ1−4[Xyl]n, where n=2–7; 95% oligosaccharides, Suntory Limited, Osaka, Japan], Beneo Synergy1 (FIN, a mixture of fructooligosaccharides/inulin 92% oligosaccharides; Orafti, Tienen, Belgium), gentiooligosaccharides (GEO, a mixture of β1–6 d-glucose oligomers; 95% oligosaccharides; Wako Pure Chemicals, Japan), Beneo GR (FOS, 95% oligosaccharide, β(2–1)-fructan; 60% glucose-fructose, 40% fructose (DP, degree of polymerization, 3–10) and lactulose (LAC; 4-O-β-d-galactopyranosyl-d-fructose, 100% lactulose; Solvay Pharmaceuticals, Southampton, UK).

Growth curves

Growth rates of the eight bacterial strains listed above and Salmonella Typhimurium SL1344 in pure cultures were compared in the presence of individual carbohydrates. Plates of de Man–Rogosa–Sharpe (MRS) agar (Oxoid Ltd, Basingstoke, Hampshire, UK) (for the eight bacterial strains) or brilliant green agar (BGA; Oxoid) containing nalidixic acid (15 μg mL−1) (for Salmonella) were inoculated from the stock culture collection and incubated for 24 h at 37 °C under anaerobic conditions in a Don Whitley anaerobic cabinet (10 : 10 : 80%; H2 : CO2 : N2). Hungate tubes were then inoculated with one colony from each plate. For the Lactobacillus and Bifidobacterium strains, the Hungate tubes contained MRS broth (10 mL) (Oxoid); for Salmonella, the tubes contained 10 mL of Luria–Bertani broth (Difco Laboratories, Detroit, MI). Hungate tubes were incubated overnight in a shaking incubator at 37 °C.

After the overnight incubation, 0.1 mL of each bacterial cell suspension (107 CFU mL−1) was inoculated into Hungate tubes containing 9 mL glucose-free MRS medium (Oxoid) and 1 mL of each carbohydrate separately (1%, w/w). Tubes were then incubated for 24 h at 37 °C in a shaking incubator. The OD660 nm of each culture was determined at hourly intervals for up to 24 h. Subsequently, the exponential-phase growth rate (ΔOD U h−1) of the bacterial strains in each carbohydrate-containing medium was calculated. This experiment was performed in triplicate.

Batch culture fermentations

Two experiments were performed. In the first, batch culture fermentations were performed in order to characterize the fermentation pattern of the carbohydrates. The second was performed in order to evaluate the effect of fermentation (changes in bacterial populations and fermentation products) on Salmonella. For both experiments, sterile stirred batch culture fermentation vessels (100 mL working volume) were prepared and aseptically filled with 45 mL of sterile basal nutrient medium. This medium comprised peptone water (2 g L−1), yeast extract (2 g L−1), NaCl (0.1 g L−1), KH2PO4 (0.04 g L−1), K2HPO4 (0.04 g L−1), MgSO4·7H2O (0.01 g L−1), CaCl2·6H2O (0.01 g L−1), NaHCO3 (2 g L−1), Tween 80 (2 mL L−1), haemin (0.05 g L−1), vitamin K (10 μL L−1), l-cysteine hydrochloride (0.5 g L−1) and bile salts (sodium glycocholate and sodium taurocholate) (0.5 g L−1). The medium was adjusted to pH 7.0, and 4 mL of 0.025% (w/v) resazurin solution was added before autoclaving. All media and chemicals were purchased from Oxoid and Sigma, respectively.

Once in the fermentation vessels, the sterile medium was sparged with O2-free N2 (15 mL min−1) overnight to maintain anaerobic conditions. The following day, a faecal slurry was prepared by collecting and combining fresh faeces from eight pigs fed a commercial standard diet (body weight 25–30 kg, proven free of Salmonella infection by enrichment in selenite broth at 37 °C for 16 h and plating on BGA) and mixing them with prereduced sterile phosphate-buffered saline (PBS) (to yield a 10%, w/v, faecal slurry). Faecal samples were collected directly from the pig rectum with a gloved finger, and immediately placed in an anaerobic jar (AnaeroJarTM 2.5 L, Oxoid Ltd) including a gas-generating kit (AnaeroGenTM, Oxoid) in order to reproduce the anaerobic conditions inside the chamber. Afterwards, the samples were immediately transported from the farm to the laboratory and were diluted with prereduced PBS within 2 h after collection. The faecal matter used was assumed to have a microbial population representative of the large intestinal microbial communities of pigs (Coates et al., 1988; Williams et al., 1998; Bauer et al., 2004). Each vessel was inoculated with 5 mL of the freshly prepared faecal slurry. Each carbohydrate was immediately added at a concentration of 1% (w/v) to one of the five vessels. This amount would correspond to 4% (w/w) of carbohydrate in the pig's feed. An extra vessel with no added carbohydrate source (referred to here as CTR) was also included as a control. In the second experiment, each vessel was infected with 107 CFU mL−1 of an overnight Salmonella culture. The temperature of the fermentation vessels was held at 37 °C using a circulating water bath, pH values were held between 6.4 and 6.6 (average 6.5) by the addition of 0.5 M NaOH or HCl to the vessels, pH was controlled via pH meter controllers (Electrolab260, UK) and anaerobic conditions were maintained by sparging the vessels with O2-free N2 (15 mL min−1).

Batch culture fermentations were run for 24 h, which is the typical incubation time for batch systems when simulating the large intestine of monogastric animals (as reviewed by Coles et al., 2005). In the first experiment, 1 mL of sample was taken at 0, 5, 10 and 24 h for analysis of lactic acid and SCFA using HLPC. In the second experiment, samples (5 mL) were taken at 0, 5, 10 and 24 h for analysis of bacterial populations by FISH and for analyses of lactic acid and SCFA using HPLC.

The first experiment was performed in triplicate and the second in duplicate.

Lactic acid and SCFA analysis

Samples taken from the batch culture vessels were centrifuged at 13 000 g for 5 min to remove all particulate matter. Supernatants were then filtered using 0.2 μm polycarbonate syringe filters (Whatman, UK) and injected (20 μL) into an HPLC system (Merck, NJ) equipped with RI detection. The column used was an ion-exclusion REZEX-ROA organic acid column (Phenomenex Inc.) maintained at 85 °C. Sulphuric acid in HPLC-grade H2O (0.0025 mmol L−1) was used as the eluent, and the flow rate was maintained at 0.5 mL min−1. Quantification of the samples was obtained through calibration curves of lactic, acetic, propionic, butyric and valeric acids and branched-chain fatty acids in concentrations ranging between 12.5 and 100 mM.

Enumeration of bacterial populations by FISH

FISH was performed essentially as described by Daims et al. (2005). Briefly, aliquots (500 μL) of batch culture samples were fixed in three volumes of ice-cold 4% (w/v) paraformaldehyde for 4 h at 4 °C. They were then centrifuged at 13 000 g for 5 min and washed twice in 1 mL of sterile PBS. The cells were pelleted by centrifugation and resuspended in 150 μL of sterile PBS, to which 150 μL of ethanol was added. The samples were then vortexed and stored at −20 °C until used in hybridizations.

For the hybridizations, 20 μL of each sample was pipetted onto Teflon- and poly-l-lysine-coated, six-well (10 mm diameter each) slides (Tekdon Inc., Myakka City, FL). The samples were dried onto the slides at 46 °C for 15 min and afterwards dehydrated in an alcohol series (50%, 80% and 96%, 3 min each). The ethanol was allowed to evaporate from the slides before the probes were applied to the samples. To permeabilize the cells for use with probes Lab158 and Rfla729/Rbro730, samples were treated with 50 μL of lysozyme (1 mg mL−1 in 100 mM Tris-HCl, pH 8.0) at 37 °C for 15 min before being washed briefly (2–3 s) in water and afterwards dehydrated in the ethanol series. A probe/hybridization buffer mixture (5 μL of a 50 ng μL−1 stock of probe plus 45 μL of hybridization buffer) was applied to the surface of each well. Hybridizations were performed for 4 h in an ISO20 oven (Grant Boekel). For the washing step, slides were placed in 50 mL of wash buffer containing 20 μL of 4′,6-diamidino-2-phenylindole dihydrochloride (DAPI; 50 ng μL−1; Sigma) for 15 min. They were then briefly washed (2–3 s) in ice-cold water and dried under a stream of compressed air. Five microlitres of antifade reagent (polyvinyl alcohol mounting medium with DABCO antifading; Sigma) was added to each well and a coverslip was applied. Slides were stored in the dark at 4 °C (for a maximum of 3 days) until cells were counted under a Nikon E400 Eclipse microscope. DAPI slides were visualized with the aid of a DM 400 filter and probe slides with the aid of a DM 575 filter. Numbers of specific bacteria and DAPI-stained entities (used to count total bacteria) were determined using the following equation:


where DF is the dilution factor (300/500=0.6), ACC is the average cell count of 15 fields of view and DFsample refers to the dilution of sample used with a particular probe or stain (e.g. 50 × for Bif164 counts). The figure 6732.42 refers to the area of the well divided by the area of the field of view and the factor 50 takes the cell count back to per millilitre of sample.

All probes were Cy3-labelled and synthesized by Sigma Aldrich. Table 1 gives the details of the probes used in this study.

Table 1.   Probes used for FISH analysis of bacterial populations in samples from batch culture systems
Accession no.*Full nameTarget speciesTemperature (°C)Sequence (5′ to 3′)Reference
  • *

    ND, No information relating to these probes has been deposited in probeBase (

  • Probe designation according to Alm et al. (1996). This information was retrieved from probeBase.

  • These probes were used together in equimolar concentrations (both at 50 ng μL−1). Formamide (20%) was included in the hybridization buffer.

Sal303NDL-S-Sal-1713-a-A-18Different serovars of Salmonella spp.3737AATCACTTCACCTACGTGNordentoft et al. (1997)
Bif164pB-00037S-G-Bif-0164-a-A-18Most Bifidobacterium spp. and Parascardovia denticolens5050CATCCGGCATTACCACCCLangendijk et al. (1995)
Lab158NDS-G-Lab-0158-a-A-20Most Lactobacillus, Leuconostoc and Weissella spp.; Lactococcus lactis; all Vagococcus, Enterococcus, Melisococcus, Tetragenococcus, Catellicoccus, Pediococcus and Paralactobacillus spp.5050GGTATTAGCAYCTGTTTCCAHarmsen et al. (1999)
Bac303pB-00031S-*-Bacto-0303-a-A-17Most Bacteroides sensu stricto and Prevotella spp.; all Parabacteroides; Barnesiella viscericola and Odoribacter splanchnicus4648CCAATGTGGGGGACCTTManz et al. (1996)
Most members of Clostridium cluster I; all members of Clostridium cluster II; Clostridium tyrobutyricum; Adhaeribacter aquaticus and Flexibacter canadensis (family Flexibacteriaceae); [Eubacterium] combesii (family Propionibacteriaceae)5050TTATGCGGTATTAATCTYCCTTTFranks et al. (1998)
Rbro730pB-00558S-*-Rbro-730-a-A-18Ruminococcus bromii-like; Clostridium sporosphaeroides and Clostridium leptum5050TAAAGCCCAGYAGGCCGCHarmsen et al. (2002)
Rfla729pB-00557S-*-Rfla-729-a-A-18Ruminococcus albus and Ruminococcus flavefaciens5050AAAGCCCAGTAAGCCGCCHarmsen et al. (2002)
Atopobium, Colinsella, Olsenella and Eggerthella spp.; Cryptobacterium curtum; Mycoplasma equigenitalium and Mycoplasma elephantis5050GGTCGGTCTCTCAACCCHarmsen et al. (2000)
Most members of Clostridium cluster XIVa; Syntrophococcus sucromutans, [Bacteroides] galacturonicus and [Bacteroides] xylanolyticus, Lachnospira pectinschiza and Clostridium saccharolyticum5050GCTTCTTAGTCARGTACCGFranks et al. (1998)
Prop853NDNDClostridium cluster IX5050ATTGCGTTAACTCCGGCACWalker et al. (2005)

Statistical analysis

All data were analysed by anova with the GLM procedure of SAS (v. 9.1.; SAS Institute Incorporated, Cary, NC).

Growth rates from pure cultures were analysed according to the following model:


where Yi is the dependent variable, μ is the overall mean, αi is the effect of the carbohydrate and ɛN (0,σɛ2) represents the unexplained random error.

Batch culture data were analysed according to the following model:


where Yij is the dependent variable, μ is the overall mean, αi is the effect of the carobohydrate, βj is the effect of the time, (αβ)ij is the interaction between carobohydrate and time and ɛN(0, σɛ2) represents the unexplained random error. Data were analysed initially including the effect of the inoculum and its interactions in the model. However, because no significant effect was found, they were finally excluded.

For analysis of SCFA (mM and %) and lactic acid, differences between means were assessed by time point including the effect of the inoculum.

The differences between means were assessed using the PDIFF option of SAS adjusted by Tukey–Kramer. Statistical significance was accepted at P<0.05, and differences among means with 0.05<P<0.10 were accepted as representing tendencies towards differences.


Influence of carbohydrates on Bifidobacterium spp. and Lactobacillus spp. strains and on Salmonella Typhimurium

Table 2 summarizes bacterial growth rates following incubation of pure cultures with different substrates. Among the carbohydrates tested, the highest growth rates for all the Lactobacillus strains, B. infantis and B. longum occurred in the presence of LAC. The growth rate of B. breve was the highest on FOS, FIN and LAC. The growth rate of Salmonella was the lowest on LAC and FOS. Cell densities after 24 h were the highest in the presence of LAC for B. infantis, B. longum, L. casei, L. plantarum and L. rhamnosus. Low values of cell density for Salmonella after 24 h growth were found in the presence of LAC and XOS.

Table 2.   Rate of exponential-phase growth (ΔOD units h−1) and OD units after 24 h of incubation with carbohydrates of bacterial strains grown in pure cultures
BacteriaRateOD 24 h
  1. a,b,cDifferent superscripts within a row for the same parameter (either Rate or OD 24 h) indicate significant differences within the values (P<0.05).

  2. Values are given as means and residual standard deviations (RSD) (n=3).

B. bifidum0.059ab0.022bc0.080a0.019bc0.002c0.074a0.02680.0170.713b0.393c0.477bc0.203cd0.043d1.183a0.1690.0001
B. breve0.053d0.168b0.104c0.196b0.181b0.247a0.0217<0.00010.740d1.843b1.320c1.9371.820b1.193a0.036<0.0001
B. infantis0.059bc0.067b0.053c0.053c0.086a0.053d0.00740.00090.713b0.780b0.660b0.683b1.293a0.187b0.0970.0001
B. longum0.046cd0.030d0.057c0.035d0.081b0.112a0.0099<0.00010.393d0.460cd1.030b0.677c1.483a1.460a0.123<0.0001
L. acidophilus0.050d0.064de0.155c0.059d0.221a0.184b0.0129<0.00010.373d0.477c1.677a0.263e1.307b1.700a0.044<0.0001
L. casei0.068e0.101de0.132cd0.163bc0.214a0.195ab0.0216<0.00010.670c1.277b1.377b1.507ab1.723a1.763a0.1700.0001
L. plantarum0.107d0.118d0.183c0.083e0.211b0.237a0.0070<0.00010.600e1.357d1.513c0.380f1.723b1.913a0.063<0.0001
L. rhammosus0.036d0.028d0.093c0.028d0.161b0.197a0.0079<0.00010.527c0.543c1.420b0.477c1.563ab1.790a0.155<0.0001
S. Typhimurium0.043ab0.038bc0.044a0.034cd0.029d0.014e0.0045<0.00010.303b0.427a0.450a0.450a0.327b0.240c0.017<0.001

Fermentation parameters in in vitro batch culture fermentations

Table 3 illustrates the production of lactic acid in the absence and presence of Salmonella Typhimurium. In the absence of Salmonella, comparing the averages of the four sampling time points (0, 5, 10 and 24 h), fermentation of FOS (P=0.003) and especially FIN (P<0.0001) and GEO (P<0.0001) generated higher amounts of lactic acid than CTR. The differences were significant after 10 h, with fermentations of GEO (P<0.0001) and FIN (P=0.008) generating more lactic acid than CTR. At 24 h, a marked decrease in the amount of lactic acid generated from the fermentation of GEO was observed and only FIN showed higher concentrations of lactic acid compared with CTR (P=0.012). Of the mean values calculated from all four time points (0, 5, 10 and 24 h) in the presence of Salmonella, only FIN and GEO showed a significant increase in lactic acid compared with CTR (P=0.027 and P=0.002, respectively). Differences during the course of the fermentation occurred after 5 and 10 h. At 5 h, XOS, FIN and GEO showed higher SCFA values than CTR (P=0.007, P=0.006 and P=0.005, respectively). After 10 h, only FIN and GEO showed higher values than CTR (P=0.009 and P=0.004, respectively).

Table 3.   Lactic acid (mM) along the 24 h fermentation of the different carbohydrates in batch cultures in absence or presence of Salmonella
CarbohydrateLactic acid without SalmonellaLactic acid with Salmonella
Incubation time (h)MeanIncubation time (h)Mean
  1. a,b,cDifferent superscripts within a column indicate either significant differences within the values (P<0.05) or a tendency to significance (P<0.10).

  2. Values are given as Lsmeans and residual standard deviations (RSD) (batch without Salmonella, n=3, nMean=12; batch with Salmonella, n=2, nMean=10).


Table 4 illustrates the accumulated generation of total SCFA during the 24 h of fermentation in the batch cultures in the absence and presence of Salmonella. Without Salmonella, SCFA increased over time for all carbohydrates compared with CTR (SEM=0.975; P<0.0001), and the amounts generated, calculated as the mean of the four sampling time points, were higher than CTR. Significant differences were observed after 10 h of fermentation with all additions, except for LAC, showing higher concentrations of SCFA than CTR (P=0.0002, P=0.050, P=0.006 and P=0.016 for XOS, FIN, GEO and FOS, respectively). After 24 h, all carbohydrates except FOS generated higher concentrations of SCFA than CTR, especially LAC and GEO (P=0.025, P=0.011, P=0.003 and P=0.003 for XOS, FIN, GEO and LAC, respectively). In the presence of Salmonella, SCFA increased over time for all the treatments except LAC compared with CTR (SEM=1.168; P<0.0001). With the exception of LAC, all carbohydrates generated higher concentrations of SCFA in the presence of Salmonella than CTR on comparing the average values of the four sampling time points (0, 5, 10 and 24 h). Differences were found at 10 h, with XOS, FIN and GEO giving rise to higher concentrations of total SCFA than CTR (P=0.013, P=0.008 and P=0.018, respectively).

Table 4.   Total SCFA (mM) (sum of acetic, propionic and butyric acids, and BCFA) along the 24 h fermentation of the different carbohydrates in batch cultures in absence or presence of Salmonella
CarbohydrateSCFA without SalmonellaSCFA with Salmonella
Incubation time (h)MeanIncubation time (h)Mean
  1. a,b,cDifferent superscripts within a column indicate either significant differences within the values (P<0.05) or a tendency to significance (P<0.10).

  2. Values are given as Lsmeans and residual standard deviations (RSD) (batch without Salmonella, n=3, nMEAN=12; batch with Salmonella, n=2, nMEAN=10).


Table 5 shows the profiles for the SCFA found in the batch cultures at 24 h of fermentation without and with Salmonella. In the absence of Salmonella, inclusion of carbohydrates modified the percentages of acetic, propionic and butyric acids compared with CTR. XOS and FOS generated higher percentages of acetic acid than CTR. FIN, GEO and LAC showed higher percentages of butyric acid than CTR. All carbohydrates generated lower percentages of propionic acid than CTR. In the presence of Salmonella, none of the carbohydrate additions generated higher percentages of acetic, propionic or butyric acids than CTR.

Table 5.   Proportions of acetic, propionic and butyric acids and BCFA, and concentrations of total SCFA (mM) at 24 h of fermentation of different carbohydrates without and with inoculation of Salmonella Typhimurium into batch cultures
CarbohydrateSCFA at 24 h without SalmonellaSCFA at 24 h with Salmonella
  • *

    Sum of acetic, propionic and butyric acids and BCFA.

  • a,b,cDifferent superscripts within a column indicate either significant differences within the values (P<0.05) or a tendency to significance (P<0.10)

  • Values are given as Lsmeans and residual standard deviations (RSD) (batch without Salmonella, n=3; batch with Salmonella, n=2).


Modulation of bacteria populations in in vitro batch culture fermentations

Population levels of the dominant members of the porcine faecal microbiota determined by FISH are shown in Table 6. Numbers of total bacteria were not affected by the carbohydrate fermented. All carbohydrates induced the growth of bacteria detected by Sal 303 when compared with CTR, although this increase was the lowest for LAC. Those bacteria detected by Bif164 increased with all the carbohydrates. With the exception of FOS and FIN, the carbohydrates induced increased bacteria detected by Lab158 counts. Counts of bacteria detected by Bac303 decreased in the presence of FOS and LAC compared with CTR (P=0.015 and P=0.046, respectively). Also, for bacteria detected by Bac303, the effect of each carbohydrate was different and these differences were dependent on time (data not shown, P interaction <0.05). After 5 h, none of the carbohydrates generated higher counts of bacteria detected by Bac303 than CTR, whereas LAC and generated lower counts than CTR (5.85, 5.55 and 6.49 log10 (cells mL−1) for LAC, FOS and CTR, respectively). However, after 24 h with GEO and FIN, higher counts of bacteria detected by Bac303 were counted compared with CTR (7.20, 7.08 and 6.46 log10 cells mL−1 for GEO, FIN and CTR, respectively). Chis150 counts increased only with FIN compared with CTR (P=0.011). Counts of bacteria detected by Rfla729/Rbro730 increased for all the carbohydrates compared with CTR.

Table 6.   Bacterial populations analyzed by FISH along 24 h of fermentation of different carbohydrates in the batch culture systems inoculated with Salmonella Typhimurium
CarbohydrateMean (log10 cells mL−1)
  • *

    Effect of interaction (P interaction <0.05).

  • a,b,cDifferent superscripts within a column indicate either significant differences within the values (P<0.05) or a tendency to significance (P<0.10).

  • Values are given as Lsmeans and residual standard deviation (RSD) (n-treatment=8, n-time=12, n-interaction=2).


All carbohydrates induced the growth of bacteria detected by Lab158 from 0 to 24 h: XOS, from 5.36 to 6.88 (P=0.0001); FIN from 5.75 to 6.55 (P=0.009); GEO from 5.92 to 6.92 (P=0.002); FOS from 5.65 to 6.27 (P=0.031); and LAC from 5.62 to 6.73 (P=0.001); data not shown).


The aim of this work was to assess potential prebiotics for inclusion in porcine feed in order to reduce the incidence of Salmonella in porcines. The selection of a possible feed additive would be based on evidence from the studies described in this work that showed their influence on the fermentative activity of the hindgut microbiota and on the survival of Salmonella Typhimurium. First, the effect on growth of potentially beneficial bacteria and on inhibition of Salmonella Typhimurium was assessed in pure cultures. In these studies, LAC was the most promising carbohydrate with regard to both effects. To further investigate these initial results, batch culture fermentations were performed because such mixed culture work is essential to assess the possible prebiotic selectivity of a substrate (Gibson & Roberfroid, 1995). In vivo studies in pigs showed that supplementation with a 4% (w/w) prebiotic in a pig's standard diet significantly increased bifidobacteria and lactobacilli (Tzortzis et al., 2005; Tako et al., 2008) while lower concentrations failed to stimulate a significant increase in these bacteria groups (Böhmer et al., 2005; Mountzouris et al., 2006). Digestibility of 60% of a standard diet in pigs leads to an enrichment of nondigestible substrates in around 20% of the dry matter content of the caecum. However, it is known that, compared with humans, fermentation of prebiotic oligosaccharides in pigs already occurs in the ileum (Böhmer et al., 2005; van Loo, 2007). Therefore, to take into account probable digestion in the proximal gut in vivo, we estimated that 4% (w/w) of prebiotic in the pig's feed would equal approximately a concentration of 1% (w/v) in the hindgut. Thus, 1% (w/v) of different potential prebiotics was fermented using a porcine faecal inoculum with and without the addition of 107 CFU Salmonella Typhimurum in a batch culture system at a controlled pH, which reflected the condition in the porcine hindgut to assess fermentation activity. In a first set of fermentations, metabolism was characterized in terms of lactic acid and SCFA production. In a second set of fermentations, changes in bacterial populations and fermentation products (lactic acid and SCFA) and Salmonella survival were investigated.

Prebiotics are thought to be utilized preferentially by Lactobacillus and Bifidobacterium species (Bailey et al., 1991; Kaplan & Hutkins, 2000), and may suppress or have no stimulatory effect on undesirable bacteria such as Salmonella (Gibson & Roberfroid, 1995; Oyarzabal & Conner, 1995). In this way, Lactobacillus and Bifidobacterium species could have a competitive advantage, limiting the nutrient sources for pathogenic bacteria. Thus, Tzortzis et al. (2005) observed in porcines how a novel prebiotic GOS mixture, when added to a commercial diet (4%), increased the density of bifidobacteria and acetate and decreased the pH compared with the control diet supplemented with inulin. Apanavicius et al. (2007) observed an increase in Lactobacillus in puppies fed 1% inulin, together with an increase in acetate and total SCFA compared with those fed with 1% FOS and the control. In the present study, all the carbohydrates were fermented by porcine microbiota, as evidenced by an increase in the production of SCFA compared with CTR in the fermentations without Salmonella. That fermentation took place was also supported by the modulation observed in the bacterial populations detected by Bif164, Bac303, Lab158 and Rbro/Rfla. Carbohydrates in the batch cultures increased bacteria detected by Lab158 from 0 to 24 h. However, inclusion of the carbohydrates in the batch culture systems did not decrease Salmonella growth compared with CTR. While the control did not contain an added carbohydrate and thus was unable to facilitate the growth of Salmonella, Salmonella was able to grow in the presence of the carbohydrates, especially XOS, FIN, FOS and GEO. That Salmonella may have utilized the carbohydrates [except LAC, which Salmonella is not able to metabolize (Liao et al., 1994)] was also supported by the results of the pure culture experiments. Similar results have been reported showing that FOS can stimulate the growth of enterobacteria (Oli et al., 1998; Sakai et al., 2001). It is likely that Salmonella competes with other bacteria from the porcine inoculum for carbohydrates as a carbon source. The carbon source is limiting for the number of carbon atoms converted into SCFA by fermentation. Therefore, with Salmonella fermenting the carbohydrates and generating mainly acetic acid (molar ratios of acetic/propionic/butyric: 96–98/0.7–2.2/0.9–1.2 obtained by incubation of Salmonella in pure cultures in the presence of the carbohydrates tested), an increase in total SCFA compared with fermentation without Salmonella would not be expected as the sum of carbon atoms in the system remains constant or decreases, considering that a part escapes as CO2. This was supported by the similar results of total SCFA with and without Salmonella. However, the fermentation of carbohydrates by Salmonella would lead to a change in the SCFA profiles due to the different end products of fermentation by different bacterial groups. Indeed, while in the absence of Salmonella FIN, GEO and LAC showed higher percentages of butyric acid than CTR, this was not the case in the presence of Salmonella. In addition to this competition for the carbohydrates as a carbon source, Salmonella may have consumed the products of their breakdown as it is known that members of the family Enterobacteriaceae are saccharolytic (mostly C6 carbohydrates such as glucose, mannose, fructose and hexitols) via the phosphoenolpyruvate-dependent phosphotransferase system (PTS) (Postma et al., 1986). While, for example, Horswill & Escalante-Semerena (1999) observed how Salmonella enterica serovar Typhimurium LT2 was able to catabolize propionate through the 2-methylcitric acid cycle, it is unlikely that Salmonella in our experiments utilized SCFA as a carbon source as the concentrations of SCFA, except for LAC, did not differ in the presence or absence of Salmonella.

It has been reported that the production of lactic acid and SCFA could affect the survival of Salmonella. SCFAs are known to reduce populations of the Enterobacteriaceae family and specifically Salmonella (McHan & Shotts, 1993; Lawhon et al., 2002), which are sensitive to low pH values (Smith & Jones, 1963; Ewing & Cole, 1994) compared with other groups of bacteria such as lactobacilli, which are relatively acid-tolerant (Fuller, 1977). The main production site of organic acids in porcines is the hindgut, with concentrations of organic acids ranging from 170 to 230 mM under normal conditions (Clemens & Stevens, 1974). It is believed that high levels of SCFA in the pig's hindgut are inhibitory for Salmonella growth (Meynell, 1963; Bohnhoff et al., 1964; Prohászka et al., 1990). However, despite the increased SCFA generation observed in the fermentation of the carbohydrates, the growth of Salmonella was not inhibited. It may be that the amounts of SCFA generated were not high enough to exert any inhibitory effect on Salmonella. However, while SCFA had no direct effect in vitro, changes in the fermentation profile could influence Salmonella invasion in vivo. It is known that alterations in the gene expression of virulence factors can be promoted by different fermentation products. For example, whereas SCFA such as butyrate and propionate specifically have been able to downregulate Salmonella expression of invasion genes and the invasion of intestinal cells (Lawhon et al., 2002; Van Immerseel et al., 2003), acetate has shown to be able to increase the expression of some of these genes at pH 6 (Durant et al., 2000). Carbohydrates that generate a low molar ratio of acetic acid and a high one for butyric acid may lead to a decrease in the virulence of the pathogen, with GEO and LAC as potential candidates to be tested further.

Lactic acid bacteria display numerous antimicrobial activities. These are mainly due to their production of organic acids but also of other compounds, such as bacteriocins (De Vuyst & Leroy, 2007). All the carbohydrates fermented in the batch cultures increased the counts of those bacteria detected by Bif164, and all of them except FOS increased Lab158 counts compared with CTR. However, the relative amounts of Lab158 and Bif164 dectectable species from the faeces introduced into the batch culture systems were lower than that of Salmonella (107 viable cells, in order to simulate a Salmonella gut infection), and so their increase may not have been sufficient to exert any inhibitory effect on Salmonella. In order to observe an inhibitory effect, the addition of higher amounts of lactic acid bacteria than that naturally present in the GIT may be needed. Thus, the addition of probiotic species in the feed has been demonstrated to be effective against Salmonella Typhimurium infection in both murine and porcine models (Hudault et al., 1997; Silva et al., 1999; Casey et al., 2007; Chiu et al., 2008).


The fermentation of the carbohydrates XOS, GEO, FOS, FIN and LAC by porcine faecal bacteria in batch culture systems modifies the hindgut fermentation. However, to definitively classify them as prebiotics would require an in vivo study. The changes observed in our in vitro conditions did not exert any inhibitory effect on the growth of Salmonella Typhimurium in batch culture systems. Indeed, Salmonella was able to utilize the test carbohydrates itself, competing with saccharolytic bacteria within the porcine inoculum. This competition might have had an antagonistic effect on bifidobacteria and lactobacilli compared with the infection dose of Salmonella. This might explain why our in vitro model used in the present work does not confirm the protective effects against Salmonella described by other authors. Additional mechanisms such as interference with the adhesion of Salmonella to the intestinal epithelium or the enhancement of the immune defence response might influence the efficacy in vivo.


The Universitat Autònoma de Barcelona was financially supported by a Ministerio de Ciencia y Tecnología project (AGL2003-08370-C02-01) through a grant received by S.M.-P. The authors thank Miss Lesley Hoyles for her help with FISH analysis.