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Predominant genera of fecal microbiota in children with atopic dermatitis are not altered by intake of probiotic bacteria Lactobacillus acidophilus NCFM and Bifidobacterium animalis subsp. lactis Bi-07

Nadja Larsen, Finn K. Vogensen, Rikke Gøbel, Kim F. Michaelsen, Waleed Abu Al-Soud, Søren J. Sørensen, Lars H. Hansen, Mogens Jakobsen
DOI: http://dx.doi.org/10.1111/j.1574-6941.2010.01024.x 482-496 First published online: 1 March 2011


The effect of probiotic bacteria Lactobacillus acidophilus NCFM and Bifidobacterium lactis Bi-07 on the composition of the Lactobacillus group, Bifidobacterium and the total bacterial population in feces from young children with atopic dermatitis was investigated. The study included 50 children randomized to intake of one of the probiotic strain or placebo. Microbial composition was characterized by denaturing gradient gel electrophoresis, quantitative PCR and, in a subset of subjects, by pyrosequencing of the 16S rRNA gene. The core population of the Lactobacillus group was identified as Lactobacillus gasseri, Lactobacillus fermentum, Lactobacillus oris, Leuconostoc mesenteroides, while the bifidobacterial community included Bifidobacterium adolescentis, Bifidobacterium bifidum, Bifidobacterium longum and Bifidobacterium catenulatum. The fecal numbers of L. acidophilus and B. lactis increased significantly after intervention, indicating survival of the ingested bacteria. The levels of Bifidobacterium correlated positively (P=0.03), while the levels of the Lactobacillus group negatively (P=0.01) with improvement of atopic eczema evaluated by the Severity Scoring of Atopic Dermatitis index. This correlation was observed across the whole study cohort and not attributed to the probiotic intake. The main conclusion of the study is that administration of L. acidophilus NCFM and B. lactis Bi-07 does not affect the composition and diversity of the main bacterial populations in feces.

  • fecal microbiota
  • probiotic bacteria
  • Lactobacillus
  • Bifidobacterium


There is strong evidence that intestinal microbiota of allergic children differs from nonallergic counterparts (Ouwehand et al., 2001; Isolauri & Salminen, 2008; Shreiner et al., 2008). It was recently demonstrated that allergic children have less bifidobacteria and more clostridia than nonallergic children (Bjorksten et al., 2001; Kalliomaki et al., 2001; Murray et al., 2005; Sepp et al., 2005; Mah et al., 2006). The composition of Bifidobacterium species was found to be different between allergic infants and healthy controls: allergic children had higher levels of Bifidobacterium adolescentis and lower levels of Bifidobacterium bifidum and Bifidobacterium catenulatum (He et al., 2001; Stsepetove et al., 2007). These data support the hypothesis that modulation of the gut microbial community may prevent or even treat allergy (Ozdemir, 2010). A novel approach to alleviate atopic eczema in infants and adults includes diet supplementation with probiotic bacteria, belonging to the genera Lactobacillus and Bifidobacterium (Rosenfeldt et al., 2003; Rijkers et al., 2010). Significant reduction of SCORing Atopic Dermatitis (SCORAD) index after treatment with probiotic Bifidobacterium lactis Bb-12, Lactobacillus rhamnosus GG and Lactobacillus fermentum VRI 003 PCC was demonstrated in several trials enrolling young children (Isolauri et al., 2000; Kirjavainen et al., 2002; Weston et al., 2005). However, the other published reports provided no evidence of SCORAD improvement by probiotic intake (Brouwer et al., 2006; Folster-Holst et al., 2006; Gruber et al., 2007; Roessler et al., 2008).

The relationship between probiotic microorganisms and commensal intestinal bacteria remains uncertain as well. A few studies proved the ability of probiotic strains to affect the main genera of the intestinal microbiota such as Bacteroides, Clostridium and bifidobacteria (Kirjavainen et al., 2002; Garcia-Albiach et al., 2008; He et al., 2008; Lahtinen et al., 2009); while the other studies did not reveal major changes in the microbial composition (Nobaek et al., 2000; Larsen et al., 2006; Nielsen et al., 2007). Thus, further investigations are required to elucidate the link between probiotic interventions, atopic dermatitis (AD) and the gut microbiota.

Previously, we reported the effect of the probiotic strains Lactobacillus acidophilus NCFM and Bifidobacterium animalis subsp. lactis (B. lactis) Bi-07 on clinical severity of AD and inflammatory factors in a double-blind placebo-controlled intervention study with young children with AD (Gøbel et al., 2010). It was demonstrated that the ingested probiotic strains had no overall beneficial effect on the degree of AD measured by SCORAD index, neither on the levels of total and specific IgE, eosinophil cationic protein (ECP) and selected immune regulatory cytokines (IL-10, IFN-γ and IL-31). However, a post hoc analysis showed significant improvement of SCORAD index in the B. lactis Bi-07 group concomitantly with the decrease in IFN-γ and IL-10, suggesting that Bi-07 have a potential for treatment of AD. The main objectives of this study were to investigate the effect of the probiotic strains L. acidophilus NCFM and B. lactis Bi-07 on the composition of the main groups of fecal microbiota in children with AD and to determine whether the clinical effects are related to the changes in bacterial populations. The study was focused on the Lactobacillus group, including Lactobacillus, Leuconostoc, Pediococcus and Weissella, the genus Bifidobacterium and the total bacterial population.

Materials and methods

Probiotic bacteria

Probiotic strains L. acidophilus NCFM (ATCC 700396), B. lactis Bi-07 (ATCC SD5220) and placebo were provided by Danisco Inc. in freeze-dried capsulated form and stored at 5 °C. Capsules with placebo contained a mixture of lactose and silicium dioxide (ratio of 1 : 1) in the amount of 0.5 g equal to the support material in the capsules with probiotic bacteria. Capsules with probiotic bacteria were undergoing continuous quality control of cell counts for the duration of the trial by plating the serial dilution on de Man, Rogosa and Sharpe (MRS) agar (Merck, Darmstadt, Germany) and incubating in an anaerobic jar with AnaeroGen (Oxoid Ltd, UK) at 37 °C for 48 h. There was found no drop in CFU in capsules for the duration of the trial.

Intervention study and collection of fecal samples

The study was a double-blind, randomized placebo-controlled intervention, which included 50 children between the ages of 7 and 24 months diagnosed with AD by their family practitioner. The participants maintained their lifestyle except that products, containing probiotic cultures, were excluded from their diet. The study was approved by The Scientific Ethical Committees of Copenhagen and Frederiksberg (KF 01 271345 and KF 11 315804) and registered at ClinicalTrials.gov (NCT 1007331). The subjects were randomized into three groups: Group A consuming L. acidophilus NCFM (N=17), Group B consuming B. lactis Bi-07 (N=17) and placebo Group C (N=16). Probiotic cultures were ingested in the dosage of approximately 1010 CFU daily during a period of 8 weeks. Fecal samples were collected from each person before the intervention and at the last day of the intervention period. Immediately after defecation samples were kept at 5 °C and brought to the laboratory within 24 h where they were stored at −80 °C until analysis. The severity of AD was assessed using the standardized SCORing Atopic Dermatitis (SCORAD) index by evaluation of the patient's inflammatory lesions (Stalder et al., 1993). Children had an average SCORAD score of 21, indicating a mild severity of AD. Subjects characteristics, SCORAD index and the inflammatory markers were described previously (Gøbel et al., 2010).

Bacterial strains and growth conditions

The following type strains from DSM collection (Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH, Germany), The American Type Culture Collection (ATCC, Virginia,), Nestec Ltd (Switzerland) and other human bacterial isolates (University of Copenhagen, Denmark) of the genera Lactobacillus, Leuconostoc and Bifidobacterium were used: Lactobacillus gasseri ATCC 33323, Lactobacillus casei DSM 20011, Lactobacillus sakei DSM 20014, Lactobacillus gallinarum DSM 10532, Lactobacillus jensenii DSM 20557, Lactobacillus amylovorus DSM 20531, Lactobacillus brevis DSM 20054, Lactobacillus helveticus DSM 20075, Lactobacillus crispatus DSM 20584, Lactobacillus johnsonii NCC 533, Lactobacillus reuteri DSM 20016, Lactobacillus plantarum ATCC 14917, Lactobacillus paraplantarum DSM 10667, Lactobacillus ruminis DSM 20403, Lactobacillus salivarius BS101, Lactobacillus pentosus DSM 20199, Lactobacillus delbrueckii DSM 20081, L. fermentum DSM 20052, Leuconostoc mesenteroides DSM 20343, Leuconostoc pseudomesenteroides DSM 20193, B. adolescentis DSM 20083, Bifidobacterium angulatum DSM 20098, B. bifidum DSM 20082, Bifidobacterium breve DSM 20213, B. catenulatum DSM 16992, Bifidobacterium pseudocatenulatum DSM 20438, Bifidobacterium gallicum DSM 20093 and Bifidobacterium longum Z8. The strains were maintained in 15% glycerol at −80 °C. Before use, the cultures were plated on MRS agar (Merck) and incubated in an anaerobic jar with AnaeroGen (Oxoid Ltd) at 37 °C for 48 h. Additionally, chromosomal DNA isolated from fecal anaerobic bacteria Roseburia intestinalis DSM14610, Prevotella copri DSM18205, Clostridium leptum DSM 753, Clostridium coccoides DSM935, Clostridium nexile DSM1787 and Bacteroides thetaiotaomicron DSM 2079 was used as negative controls in quantitative PCR (qPCR).

Extraction of DNA from fecal samples and bacteria

Bacterial chromosomal DNA was extracted from fecal samples using the QIAamp DNA Stool Mini kit (Qiagen GmbH, Germany) according to the manufacturer's protocol with slight modifications (Nielsen et al., 2003). Modifications included bead beating (glass beads <106 μm, Sigma-Aldrich, Germany) of the samples in FastPrep® FP120 instrument (Bio101 Savant Instruments Inc., Holbrook, NY) at the settings of 6.0 m s−1 for 30 s before extraction and lysis of bacteria cells for 10 min at 95 °C instead of 70 °C. For purification of DNA from bacteria, the strains were grown from a single colony in 10 mL of MRS broth (Merck) at 37 °C for 24 h. The cultures were centrifuged (10 000 g, 3 min) and the pellet was washed in 1 mL sterile solution of 0.9% NaCl. Genomic DNA was extracted with the use of GenElute Bacterial Genomic DNA Kit (Sigma-Aldrich) according to the manufacturer's instructions. DNA concentration and quality in the extracts was determined with a NanoDrop 1000 spectrophotometer Thermo Scientific (Saveen Werner ApS, Denmark).

PCR amplification for denaturing gradient gel electrophoresis (DGGE)

Amplifications were carried out using a Biometra Thermoblock, model TRIO48 (Biotron, Göttingen, Germany). The PCR reaction mixture in a volume of 50 μL contained 5 μL 10 × PCR buffer, 0.2 μM of each primer (Table 1), 0.2 mM of each dNTP, 3.0 mM magnesium chloride (MgCl2), 2.5 U Taq polymerase (Invitrogen A/S, Taastrup, Denmark), and appropriately diluted template DNA (10–50 ng). For amplification of fecal DNA, 10 μg of bovine serum albumin (New England Biolabs, Beverly) was added in the PCR mixture. Amplification with the use of Lactobacillus group-specific and Bifidobacterium genus-specific primers included initial denaturation at 95 °C for 5 min followed by 40 cycles of denaturation at 95 °C for 30 s, annealing at 60 and 64 °C, respectively, for 40 s, extension at 72 °C for 1 min and a final extension at 72 °C for 7 min. The cycling program for PCR with the use of universal primers consisted of denaturation at 95 °C for 5 min, 40 cycles of 95 °C for 30 s, 60 °C for 30 s and 72 °C for 40 s, followed by extension at 72 °C for 7 min. The size and amount of the PCR products were estimated by agarose gel electrophoresis [2% w/v agarose in Tris-acetate-EDTA (TAE) buffer] and staining in ethidium bromide.

View this table:

Primers used in this study for DGGE and real-time qPCR and size of PCR products

Target organismPrimerSequence (5′–3′)PCR product (bp)Reference
Primers for DGGE
Lactobacillus groupLac1FAGCAGTAGGGAATCTTCCA380Walter (2001)
BifidobacteriumBifidFCTCCTGGAAACGGGTGG596Langendijk (1995)
All bacteriaP338FGC clamp– CTCCTACGGGAGGCAGCAG236Muyzer (1993)
Primers for qPCR
L. acidophilusLbAcFCTGCTGTTTCTTCAGCATCT121This study
B. lactisBlacFTACCGGATGCTCCGCT106This study
Lactobacillus gasseri groupLbGasFCCTTTATTTGACGGTAATTACT195This study
Leuconostoc groupLeucFGACAACCTGCCTCAAGGCT177This study
Lactobacillus groupLacFAGCAGTAGGGAATCTTCCA341Rinttila (2004)
BifidobacteriumBifFGCGTGCTTAACACATGCAAGTC126Penders (2005)
All bacteriaUnivFTCCTACGGGAGGCAGCAGT466Nadkarni (2002)
  • * Primers LbAcF and LbAcR targeted cpn60 gene; other primers targeted 16S rRNA gene sequence. F (forward) and R (reverse) indicate the orientation of the primers.

  • The Lactobacillus group comprises genera Lactobacillus, Leuconostoc, Pediococcus and Weisella.

  • GC indicates a 40-bp GC-rich sequence attached to the 5′-end of the primer CGCCCGGGGCGCGCCCCGGGCGGCCCGGGGGCACCGGGGG (Walter et al., 2001).

  • § The Lactobacillus gasseri group includes L. gasseri and Lactobacillus johnsonii.

  • The Leuconostoc group includes Leuconostoc mesenteroides, Leuconostoc pseudomesenteroides, Leuconostoc garlicum, Leuconostoc citreum, Leuconostoc kimchii and Leuconostoc carnosum.

DGGE analysis and gel processing

PCR products were analyzed by DGGE using the DCode System (Bio-Rad, Hercules) essentially according to the Bio-Rad tutorials. Briefly, polyacrylamide gels [8% (v/v) acrylamide-bisacrylamide (37.5 : 1)] in 1 × TAE buffer were used with a linear gradient of the denaturants formamide and urea of 35–50% for the Lactobacillus group, 40–55% for bifidobacteria and 35–60% for all bacteria [100% denaturant corresponded to 7 M urea and 40% (v/v) formamide]. Electrophoresis was performed in a 1 × TAE buffer for 16 h at a constant voltage of 70 V at 60 °C. A marker containing amplified DNA from Lactobacillus species or Bifidobacterium species was run together with the PCR products from fecal samples for normalization of the DGGE profiles. After electrophoresis, gels were stained with SYBR-GOLD (Molecular Probes, Eugene) and photographed using Kodak EDAS 290 System (Eastman Kodak, New Haven, CT). DGGE profiles were analyzed using the bionumerics software, version 4.5 (Applied Maths, St.-Martens-Latem, Belgium). Cluster analysis of DGGE profiles was performed using the unweighted-pair group method with arithmetic averages based on the Pearson correlation coefficient with position tolerance of 1%.

Identification of bacterial species from DGGE profiles

To ensure that DNA fragments with the same running distances matched to the same species, the DNA bands were excised from the DGGE gels, placed in 40 μL sterile water and left overnight at 4 °C for diffusion. The eluted DNA was reamplified with the use of the same primers and amplification conditions as for DGGE analysis. TOPO TA Cloning® Kit (Invitrogen A/S) was used to ligate the PCR amplicons into the pCR®2.1-TOPO vector and transform the recombinant vector into the Escherichia coli TOP10F′ chemically competent cells according to the manufacturer's instructions. Ten colonies from each cloning reaction were randomly picked from selective plates and cultured in Luria–Bertani medium (Merck) overnight at 37 °C with shaking at 200 r.p.m. Plasmid DNA was purified from bacteria suspensions using the E.Z.N.A Miniprep Kit I (Omega Bio-Tek Inc.) and reamplified with the use of the same primers as above. PCR products were analyzed by DGGE for purity and electrophoretic mobility. DNA fragments with the identical migration position as the original DNA band were sequenced (Macrogen Inc., Seoul, Korea). Sequences were aligned to 16S rRNA gene sequences using the basic local alignment search tool (blast) at the National Centre for Biotechnology Information database (http://www.ncbi.nlm.nih.gov/BLAST).

Design of species-specific primers for real-time qPCR

Primer sets for amplification of B. lactis, the L. gasseri group (L. gasseri and L. johnsonii) and L. mesenteroides group (L. mesenteroides, L. pseudomesenteroides, Leuconostoc garlicum, Leuconostoc citreum, Leuconostoc kimchii and Leuconostoc carnosum) shown in Table 1, were designed using 16S rRNA gene sequences from the Ribosomal Database Project release 10 (RDP 10; http://rdp.cme.msu.edu). Lactobacillus acidophilus species-specific primers were constructed using less conserved sequences of Lactobacillus cpn60 genes, retrieved from the Chaperonin Database (http://cpndb.cbr.nrc.ca/; Hill et al., 2004). Sequences were aligned by clustalw software provided by the European Bioinformatics Institute (http://www.ebi.ac.uk/Tools/clustalw2/index.html). The potential target-specific primer sites were assessed by ‘oligoprimer analysis software version 6.71 (Molecular Biology Insights Inc.). Primers were synthesized by TAG Copenhagen A/S (Denmark). Specificity of the primers was evaluated in silico using the nucleotide blast, blastn algorithm (http://blast.ncbi.nlm.nih.gov/Blast.cgi). Specific amplification was further confirmed experimentally by conventional end-point PCR with genomic DNA from bacterial strains listed above followed by gel electrophoresis and by the analysis of qPCR melting curves. The PCR conditions were as follows: 95 °C for 5 min of initial denaturation, followed by 30 cycles of amplification with 95 °C denaturation for 30 s, annealing at 58 °C for 30 s, extension at 72 °C for 40 s and a final extension at 72 °C for 5 min. PCR amplicons were separated by electrophoresis in 2% (w/v) agarose and visualized by ethidium bromide. PCR amplifications were positive for the target species and yielded PCR products of correct sizes. No cross-reactions were observed for the tested nontarget species of the genera Lactobacillus, Leuconostoc, Bifidobacterium, Roseburia, Prevotella, Clostridium and Bacteroides (data not shown).

Real-time qPCR

Quantification of bacteria in fecal samples by qPCR was carried out using the 7500 Fast Real-Time PCR System (Applied Biosystems, CA) as described previously (Larsen et al., 2010). Briefly, the reaction mixture (20 μL) was composed of 0.3 μM of each universal primer or 0.5 μM of each specific primer (Table 1), 10 μL Power SYBR Green PCR Master Mix (Applied Biosystems) and 4 μL total bacterial DNA from fecal samples added in 10-fold serial dilutions starting from 100-fold dilution to diminish the effect of inhibitors. The amplification program consisted of one cycle of 95 °C for 10 min, followed by 40 cycles of 95 °C for 15 s and 60 °C for 1 min. Standard curves were constructed using 10-fold serial dilutions of bacterial genomic DNA, starting from 1 ng DNA in qPCR reaction mixture which corresponded to approximately 2 × 105 cells. DNA isolated from L. acidophilus NCFM was applied as standard for quantification of the total bacterial load and the Lactobacillus group. DNA extracted from B. lactis Bi-07, L. gasseri ATCC 33323 and L. mesenteroides DSM20343 was used for enumeration of the corresponding bacterial species. Cell numbers of bacteria in fecal samples were calculated from the averaged threshold cycle values (Ct) and expressed as Log10 cells g−1 stool sample. The efficiencies (E) of real-time qPCR assays were calculated by the formula E=[10(−1/slope)−1]. The detection limit of SYBR Green qPCR species-specific assays was determined by spiking stool samples, negative for the target species, with known amount of L. acidophilus NCFM and B. lactis Bi-07. Nonspiked samples served as negative controls. Afterwards, the total bacterial DNA was extracted from the spiked and nonspiked samples and subjected to qPCR with the use of species-specific primers. The qPCR analyses of each fecal bacterial DNA were performed in duplicates and the mean values were used. The fold changes of the Lactobacillus group and Bifidobacterium after intervention were determined as ratios (after/before intervention) of bacterial numbers in each DNA sample, normalized to the total bacterial numbers.


Tag-encoded amplicon 454 GS FLX pyrosequencing of fecal bacterial DNA was conducted for six participants from the Group A (L. acidophilus NCFM intake, three subjects) and Group B (B. lactis Bi-07 intake, three subjects) in the samples before and at the end of intervention. Children were all boys, who showed the largest reduction in the Severity Scoring of Atopic Dermatitis (SCORAD) index (between 10 and 19) after intervention period (Gøbel et al., 2010). 454 GS FLX pyrosequencing was carried out as described before (Larsen et al., 2010). Briefly, bacterial primers 530F-mod and 1061R flanking the V4, V5 and V6 regions of the 16S rRNA gene have been used to survey the V4 hypervariable region of the gene (Supporting Information, Table S1). PCR amplification (in a volume of 40 μL) was performed using 1 × Phusion HF buffer, 2.5 mM MgCl2, 0.2 mM dNTP mixture, 0.8 U Phusion Hot Start DNA Polymerase (Finnzymes Oy, Espoo, Finland), 0.5 μM of each primer (TAG Copenhagen A/S) and 1 μL diluted DNA sample at the following conditions: an initial denaturation at 98 °C for 30 s, followed by 30 cycles of denaturation at 98 °C for 5 s, annealing at 53 °C for 20 s, elongation at 72 °C for 20 s and then a final elongation step at 72 °C for 5 min. The PCR products were purified using the QIAEX II Gel Extraction Kit (Qiagen GmbH). Second round of PCR was performed as described above, except that the custom primers with adapter A and 12 tags were used (Table S1) and the number of cycles was reduced to 10 and the annealing temperature was increased to 56 °C. A two-region 454 sequencing run was performed on a GS FLX Standard PicoTiterPlate (70 × 75) according to the manufacturer's instructions (Roche).

Analysis of sequencing data was conducted using Pyrosequencing Pipeline tools at RDP 10 (http://pyro.cme.msu.edu/index.jsp). The RDP Classifier was used to assign 16S rRNA gene sequences to taxonomical hierarchy with confidence threshold of 80%. Bacterial diversity was determined by sampling-based analysis of operational taxonomic units (OTUs) and showed by rarefaction curves. Comparison of bacterial richness across the samples was performed by Chao1 estimate at the distance of 3%, usually applied to characterize richness at species level (Schloss & Handelsman, 2004; Zhang et al., 2009). Phylogenetic assignment was generated using metagenome rapid annotation subsystem technology (mg-rast) metagenomics seed viewer (version 2.0; http://metagenomics.nmpdr.org/).

Statistical analysis

Statistical analysis of the Pearson similarity coefficients, the qPCR and pyrosequencing results was performed using the two independent sample two-tailed t-test [Statistics Online Computational Resource (SOCR), http://www.socr.ucla.edu/SOCR.html]. Correlation between the variables was computed by the Spearman rank correlation provided by free statistics software (version 1.1.23-r4, Office for Research Development and Education, http://www.wessa.net/). The qPCR results were graphically presented by box and whisker charts (Microsoft excel, 2007) and expressed as medians with quartile ranges (QR).


Characterization of the fecal microbiota by DGGE

The DGGE PCR profiles of the Lactobacillus group included 12–15 bands per lane as shown for 15 children in Fig. 1. The DNA fingerprints from the other fecal samples were of poor quality containing a few fuzzy bands, apparently, due to a low content of lactobacilli (data not shown). All the sequenced DNA fragments could be assigned to the genera Lactobacillus and Leuconostoc, exhibiting more than 98% similarity to their nearest relatives (Fig. 1 and Table 2). Sequence matches to genera L. gasseri, L. fermentum, L. acidophilus, Lactobacillus oris, L. mesenteroides and L. pseudomesenteroides were most frequently found. In addition, L. sakei, L. salivarius and L. citreum were identified in some lanes. Emergence of a strong DNA band related to L. acidophilus was commonly observed in the Group A after intake of L. acidophilus NCFM (as shown for subjects A1–A5, Fig. 1). Concurrently, the other predominant DNA bands, including L. gasseri and L. mesenteroides (pseudomesenteroides), were weakened or diminished, suggesting shifts in composition of the Lactobacillus group or a PCR bias (Fig. 1, fragments c, e, g and h).


Lactobacillus group-specific DGGE profiles of the fecal bacterial DNA amplified by PCR with the use of Lactobacillus group-specific primers Lac1F/Lac2R (Table 1). Profiles obtained in the intervention studies for the subjects: A1–A5 (intake of Lactobacillus acidophilus NCFM), B1–B5 (intake of Bifidobacterium lactis Bi-07) and C1–C5 (placebo intake). Numbers 1 and 2 denote the samples collected before and after intervention, respectively. The arrowheads with letters from ‘a’ to ‘j’ indicate the DNA fragments as shown in Table 2. White arrows (d) designate the DNA bands related to L. acidophilus. The DGGE DNA standard (DNA std.) is shown by italic numbers: 1, Lactobacillus pentosus DSM20199; 2, Lactobacillus sakei DSM20014; 3, Lactobacillus gasseri ATCC 33323; 4, L. acidophilus ATCC 700396; 5, Lactobacillus helveticus DSM20075; 6, Lactobacillus ruminis DSM20403.

View this table:

Identification of the Lactobacillus group and Bifidobacterium species in fecal samples by sequence analysis of DGGE bands

DNA bandsClosest relativesGenBank accession numberIdentity (%)
Lactobacillus group
aL. sakeiEF555204.199
bL. salivariusEU099039.199
c, eL. gasseriCP000413.198
dL. acidophilusCP000033.3100
fL. fermentumEF113966.199
gL. mesenteroidesEU306160.198
hL. pseudomesenteroidesAF515228.198
iL. citreumEF121354.199
jL. orisX94229.199
L. antriAY253659.199
Bifidobacterium species
aB. bifidumEF370998.197
bB. adolescentisAP009256.199
cB. longumEF370991.1100
dB. pseudocatenulatumAB186300.299
B. catenulatumAF432082.199
eB. animalis subsp. lactisFJ169944.199
  • * The letters indicate the excised and identified DNA bands are shown in Fig. 1 for the Lactobacillus group and Fig. 2 for Bifidobacterium species.

  • The accession number and identities are given to the closest hit in the GenBank database (NCBI/blast) that matched the query sequence (http://www.ncbi.nlm.nih.gov/blast/Blast.cgi).

Bifidobacterial DGGE fingerprints were generally of low diversity, containing from two to eight DNA bands per lane (Figs 2 and S1). Amplicons from B. lactis were visualized at different intensities in the DGGE profiles from seven participants in the Group B after Bi-07 intake (Fig. 2). The DNA fragments matched to B. longum and to B. pseudocatenulatum/catenulatum were identified in majority of the lanes; while the other predominant species belonged to B. adolescentis and B. bifidum (Table 2). Similarity indices of bifidobacterial DGGE profiles in the Group B were in the range of 75±25% (mean values±SD). These values were somewhat though not significantly lower (P=0.07), compared with those of the Groups A and C, with similarity indices of 85±15% and 88±12%, respectively.


Cluster analysis of Bifidobacterium genus-specific DGGE profiles from the Group B (N=17, intake of Bifidobacterium lactis Bi-07) performed with the use of the Pearson similarity coefficient and presented as unweighted-pair group method with arithmetic averages dendogram. DGGE profiles were produced from fecal bacterial DNA amplified by PCR with the use of genus-specific primers BifidF/BifidR (Table 1). Numbers 1 and 2 after the dash denote the samples collected before and after intervention, respectively. The letters (a, b, c, d and e) indicate position of the DNA fragments as shown in Table 2. White arrows (e) designate the DNA bands related to B. lactis. The DGGE DNA standard (DNA std.) is shown by italic numbers: 1, Bifidobacterium adolescentis DSM20083; 2, Bifidobacterium bifidum DSM20082; 3, Bifidobacterium angulatum DSM20098; 4, Bifidobacterium longum Z8; 5, Bifidobacterium catenulatum DSM16992; 6, B. lactis ATCC SD5220.

The DGGE profiles of all bacteria, generated with the use of universal primers, were composed of 15–50 bands per lane (Fig. S2). Generally, lanes from the same participant formed a separate cluster. Similarity coefficients were not significantly different between the groups, comprising 93±5% (mean±SD) in the Group A, 94±5% in the Group B and 92±7% in the control group. Cluster analysis of the total bacterial DGGE profiles as well as Bifidobacterium-specific profiles showed no grouping according to the administered probiotic strain (Figs S1 and S2).

Species-specific quantification by qPCR

Efficiencies of the species-specific qPCR assays were in the range of 90–99%. The primer concentration of 500 mM in the qPCR mixtures was found to be optimal, based on the analysis of melting curves. No signals from primer-dimers or nonspecific amplification products were detected under optimal conditions. The detection limit of L. acidophilus NCFM and B. lactis Bi-07 was about 104 (or 4.0 Log10) cells g−1 fecal sample, comparable with the other relevant qPCR assays (Bartosch et al., 2004; Gueimonde et al., 2004; Matsuki et al., 2004).

The median numbers of L. acidophilus in the Group A increased significantly from undetectable levels to 7.4 (QR 6.4–7.8) Log10 cells g−1 stool after intervention which corresponded to 10–97% of the Lactobacillus group counts (Fig. 3). Similarly, the estimates of B. lactis in the Group B at the end of intervention increased to 7.6 (QR 7.2–8.1) Log10 cells g−1 stool comprising 0.02–32% of bifidobacterial numbers.


Levels of the total bacteria, the Lactobacillus group, Bifidobacterium, Lactobacillus acidophilus and Bifidobacterium lactis determined by SYBR Green qPCR assay and expressed as Log10 cells g−1 stool. Bacterial groups were quantified in fecal samples collected in the intervention study before (number 1) and after (number 2) intervention. (a) Group A (N=17), intake of L. acidophilus NCFM; (b) Group B (N=17), intake of B. lactis Bi-07; (c) control group (N=16), placebo intake. The median counts are presented by numbers. Asterisks indicate the values after intervention significantly different (P<0.05) from the values before intervention. Boxes show the medians, the upper (75%) and the lower (25%) percentiles of the data. Whiskers indicate the highest and the smallest values.

Quantification of the L. mesenteroides (pseudomesenteroides) group and L. gasseri group was performed in order to validate the DGGE results, indicating alterations in the composition of the Lactobacillus group in feces after NCFM intake (Fig. 1, lanes A1–A5). The baseline levels of L. mesenteroides were between 4.6 and 6.3 Log10 cells g−1 feces and not significantly affected by intervention. Likewise, the numbers of L. gasseri were unchanged after intervention varying from 4.1 to 5.4 Log10 cells g−1 feces.

Quantification of the Lactobacillus group and bifidobacteria by qPCR

The qPCR results of the Lactobacillus group are shown for a part of the study cohort (NCFM Group A, N=16; Bi-07 Group B, N=16 and placebo group, N=7); the remaining estimates were uncertain due to the low concentration of lactobacilli and not included. The baseline levels of lactobacilli were not different between the intervention groups with median values of 6.9 (QR 6.8–7.3) and 6.7 (QR 6.4–7.0) Log10 cells g−1 stool in the Groups A and B, respectively, and 6.4 (QR 6.1–6.7) in the Group C (Fig. 3). After intake of L. acidophilus NCFM the numbers of Lactobacillus group were significantly increased (P<0.01) to 7.9 (QR 7.6–8.4) Log10 cells g−1 stool (Fig. 3a). The baseline levels of bifidobacteria varied from 9.5 to 10.6 (QR) Log10 cells g−1 stool across the study cohort, corresponding to 0.1–27% of the total bacterial numbers and were not significantly affected by intervention. The estimates of all bacteria were between 10.7 and 11.4 (QR) Log10 cells g−1 stool and remained stable across the intervention period.

The fold changes of lactobacilli and bifidobacteria were plotted against the changes of SCORAD index (Fig. 4), previously determined in the clinical studies (Gøbel et al., 2010). Bifidobacterial numbers showed a tendency to increase at the end of the study with improvement of atopic eczema (negative SCORAD index) in all the intervention groups. The opposite relationship, namely, a decrease with SCORAD improvement, was observed for lactobacilli. The correlations between SCORAD index and the fold changes of bifidobacteria (R=−0.31, P=0.03) and the Lactobacillus group (R=0.42, P=0.01) were significant across the whole study cohort.


Correlation between the changes in SCORAD index and the fold change of Bifidobacterium and the Lactobacillus group in children with AD after intake of Bifidobacterium lactis Bi-07 (Bi-07 group), Lactobacillus acidophilus NCFM (NCFM group) or placebo (control group). Bacterial levels were assessed by SYBR Green qPCR assay. The sample size (N), Spearman rank probability (P) and correlation (R) are shown in the graphs.

Characterization of gut microbiota by tag-encoded amplicon pyrosequencing

The total number of sequences was 236 000 with an average read length of 221 bp. After the sequences were sorted and trimmed using the RDP Pyrosequencing Pipelines, the number of sequences (>150 bp) was reduced to 140 125 with an average length of 230 bp. The number of sequences obtained from each of the 12 samples ranged from approximately 8000 to 18 000 (Table 3).

View this table:

The number of sequences, OTUs and richness estimates (Chao1) within fecal bacterial DNA from children with AD as determined by pyrosequencing of the V4 region of 16S rRNA gene

Library IDSample IDNo. of sequencesOTUs at 0.03 differenceChao1 at 0.03 differenceConfidence interval (95%)
A11-113 797100715251409–1675
A17-111 669601856783–960
LibNCFM_2A10-214 899462663601–755
A11-217 942107517731622–1964
B14-112 21790513581251–1499
LibBi07_2B8-212 082312507438–613
B14-212 51176512411118–1406
  • * Libraries of pyrosequencing tags, obtained from six children in the intervention studies with Lactobacillus acidophilus NCFM (N=3) and Bifidobacterium lactis Bi-07 (N=3) before intervention (LibNCFM_1 and LibBi07_1) and after intervention (LibNCFM_2 and LibBi07_2).

  • Fecal samples from intervention studies: Group A (sample ID A10, A11, A17) intake of L. acidophilus NCFM, Group B (sample ID B8, B9, B14) intake of B. lactis Bi-07. Samples denoted with number 1 and 2 after the dash were collected before and after intervention, respectively.

In total, five bacterial phyla were identified in pooled libraries before intervention (Fig. S3). Most of the reads were assigned to Firmicutes (56%), Bacteroidetes (30%) and Actinobacteria (10%), while the rest was distributed among Proteobacteria (2%) and Verrucomicrobia (1%). Phylum Firmicutes was mostly diverse, comprising genera Lachnospiraceae (14%), Roseburia (14%), Faecalibacterium (11%) and unclassified Lachnospiraceae (41%). Genera Veillonella, Erysipelotrichaceae IS, Ruminococcus and Peptostreptococcaceae IS ranged from 1% to 3% of Firmicutes. Rare genera (<1%) included Anaerostipes, Streptococcus, Catenibacterium, Dorea, Subdoligranulum, Dialister, Lactobacillus and Clostridium. The second largest phylum Bacteroidetes was presented by three genera, Bacteroides (94%), Parabacteroides (4%) and Alistipes (1%). Phylum Actinobacteria was primarily composed of Bifidobacterium (96%) and fewer OTUs of Eggerthella, Rothia and Actinomyces. Phylum Proteobacteria harbored diverse genera, including Sutterella, Actinobacillus and Bilophila. Phylum Verrucomicrobia was exclusively presented by genus Akkermansia.

The same bacterial classes tended to be predominant or rare before and after intervention, though differently distributed across the participants (Fig. 5). Class Actinobacteria (Phylum Actinobacteria) was highly variable between the subjects from 0.5% to 26% and slightly but insignificantly increased from on average 10% (the range 0.5–19%) to 13% (the range 1–26%) after intervention in the samples from five out of six subjects analyzed. The relative abundance of class Erysipelotrici within phylum Firmicutes was increased by on average fourfold (P=0.06) after intake of B. lactis Bi-07. Overall abundances of bacterial classes were not significantly altered after administration of the probiotic bacteria.


Relative abundances of bacterial classes determined by 454 GS FLX pyrosequencing of the V4 region of 16S rRNA gene in fecal bacterial DNA from six children of Group A (A10, A11, A17; intake of Lactobacillus acidophilus NCFM) and Group B (B8, B9, B14; intake of Bifidobacterium lactis Bi-07) before (1) and after (2) intervention.

Comparison of the abundances of predominant bacterial genera before and after intervention showed no significant alterations related to the intake of L. acidophilus NCFM and B. lactis Bi-07, though several trends were observed (Table 4). Thus, genus Faecalibacterium within phylum Firmicutes, presented exclusively by Faecalibacterium prausnitzii, was enriched after intervention in all six persons analyzed to the values close to significant (P=0.08). Proportion of bifidobacteria was on average 1.6-fold higher (range 1.2–1.9) after intervention in five of the subjects (P=0.06). Phylogenetic profiling of the sequence library from Group B before intervention showed that genus Bifidobacterium (890 sequences) was represented by B. longum or B. breve (43% of Bifidobacterium), B. bifidum (33%), B. catenulatum (18%) and B. adolescentis (4%). The same species, though in different proportions, were identified in the library from Group B after probiotic intake. Sequence matches to B. lactis were found in the Group B at the end of intervention, comprising 0.5% of bifidobacterial hits. These data are in agreement with sequencing of the DGGE fragments where the same species of bifidobacteria were identified (Table 2). Sequence matches to the genus Lactobacillus increased in total from 4 to 507 in the library of Group A after intervention, most probably due to accumulation of L. acidophilus. However, the exact assignment of Lactobacillus species was not possible to perform, as the sequences, besides L. acidophilus, were highly homologous to L. helveticus, L. crispatus and L. gallinarum.

View this table:

Proportions of the abundant bacterial genera identified by 454 GS FLX pyrosequencing of the V4 region of 16S rRNA gene from six children of the Group A (A10, A11 and A17; intake of Lactobacillus acidophilus NCFM) and Group B (B8, B9 and B14; intake of Bifidobacterium lactis Bi-07) before and after intervention

Proportions of bacterial genera, before/after intervention (%)
Class Bacteroidetes
Class Bacilli
Class Erysipelotrichi
Erysipelotrichaceae IS2.8/2.30.3/0.011.8/1.70.3/3.04.4/1.00.07/0.04
Class Clostridia
Lachnospiraceae IS6.7/8.04.7/3.813.9/10.62.4/5.417.0/7.33.1/3.8
Peptostreptococcaceae IS1.8/0.70.3/0.70.8/0.60.5/0.10.9/0.40.1/0.1
Class Actinobacteria
Class Gammaproteobacteria
Class Verrucomicrobiae
  • * Genera Alistipes, Streptococcus, Anaerostipes, Ruminococcus, Clostridium and Sutterella were found in low proportions and not included.

  • ND, not determined.

Richness and diversity of bacterial populations expressed by rarefaction curves (Fig. S4) and Chao1 estimates (Table 3) showed a large inter- and intraindividual variation (Chao1 in the range of 507–1773). Comparison of the libraries before and after intervention did not reveal any significant shifts in bacterial diversity associated with probiotic intake. The rarefaction curves were far from reaching plateau, indicating the need of additional sequence sampling if the true microbiological diversity should be determined.


The effect of the intake of probiotic bacteria L. acidophilus NCFM and B. lactis Bi-07 on the composition of fecal microbiota in children with AD was investigated in this study using culture-independent methods DGGE PCR, qPCR and 454 GS FLX pyrosequencing. For this purpose, the specific primers were developed and used in qPCR SYBR Green assay for quantification of L. acidophilus, B. lactis, the L. mesenteroides group and the L. gasseri group. The primers showed to be applicable to differentiate the target species from the other related species in a complex population of fecal bacteria by efficient and reliable qPCR assays.

The DGGE analysis signified that each of the children harbored rather diverse population of lactobacilli. The predominant DNA bands, identified as L. gasseri, L. fermentum, L. oris (Lactobacillus antri), L. citreum, L. mesenteroides and L. pseudomesenteroides, were consistent across the subjects, which indicated core community of the Lactobacillus group. The species of Lactobacillus group, identified in this study, are commonly detected in fecal samples of healthy adults (Sui et al., 2002; Nielsen et al., 2003; Dal Bello & Hertel, 2006).

The diversity and composition of fecal lactobacilli in the Groups B (Bi-07 intake) and C (placebo) was stable during the intervention period because there were no major shifts in the DGGE profiles. Stability of the Lactobacillus community was also reported in trials with allergic infants treated with B. lactis Bb-12 (Kirjavainen et al., 2002). The reduction in diversity of the Lactobacillus-specific DGGE profiles from the Group A after intake of L. acidophilus NCFM, raised an assumption that the composition of lactobacilli might be altered by ingested probiotic, also supported by other published data (Sui et al., 2002). However, that assumption was not confirmed by qPCR results, showing no decrease in the levels of L. mesenteroides and L. gasseri. Consequently, we concluded that the shifts in DGGE profiles, at least in respect to the quantified bacteria, were due to the PCR bias caused by prevalence and preferential amplification of L. acidophilus DNA. The baseline numbers of the Lactobacillus group (QR 6.1–7.3 Log10 cells g−1 stool) were consistent with the numbers previously estimated in human feces, suggesting that we assessed a major part of lactobacilli (Goossens et al., 2003; Bartosch et al., 2005).

The predominant species of bifidobacteria in this study, B. adolescentis, B. bifidum, B. longum and B. catenulatum/pseudocatenulatum, are commonly found both in allergic and healthy children (He et al., 2001; Ouwehand et al., 2001; Murray et al., 2005; Stsepetove et al., 2007). Furthermore, it was recently demonstrated that consumption of probiotic bifidobacteria by healthy adults resulted in higher levels of bifidobacteria in stool samples (Shimakawa et al., 2003; Bartosch et al., 2005; Lahtinen et al., 2009). Conversely, we did not find significant changes in bifidobacteria in the Group B at the end of B. lactis Bi-07 administration. The lack of an effect is probably due to the insufficient contribution of the strain, as B. lactis after intake still accounted for a minor part of the bifidobacterial community in most of the samples. It was reported earlier that the prevalence of bifidobacteria in fecal microbiota decreases from about 90% in infants to <10% in young children and adults (Murray et al., 2005; Firmesse et al., 2008). Accordingly, we observed considerable interindividual variation in the proportion of fecal bifidobacteria (0.1–27% of all bacteria) which is, probably, associated with instability of the bifidobacterial community at the early ages of the participants in this study (7–24 months).

Notably, significant correlation between the fold changes of the fecal bacteria and the SCORAD index was determined: improvement of atopic eczema at the end of intervention was related to the increase of bifidobacteria and the decrease of the Lactobacillus group. This relationship seems not to be attributed to the probiotic consumption, as it was found in the whole study cohort. The inverse shifts of bifidobacteria and lactobacilli might be due to the differences in their immune modulatory properties which are known to be strain specific (Foligne et al., 2007; Zeuthen et al., 2008; Ji, 2009; deRoock et al., 2010). These observations are supported by other research, showing negative association of fecal bifidobacteria with atopic eczema (Kalliomaki et al., 2001; Murray et al., 2005; Foekel et al., 2009). Recently, Bifidobacterium was found in significantly higher abundances among cesarean-delivered infants without eczema than in infants with eczema (Hong et al., 2010). There is some evidence as well that intestinal colonization by lactobacilli is linked to allergen sensitization and to the development of allergy in infants (Taylor et al., 2007; Sjogren et al., 2009). However, the assumption that the shifts in bifidobacteria and lactobacilli are connected to their immune activities is poorly supported by the results of the clinical analyses in this trial (Gøbel et al., 2010). As reported before, the inflammatory markers (IgE, ECP and selected immune regulatory cytokines IL-10, IFN-γ and IL-31) were generally not affected by intervention with exception of IFN-γ and IL-10 which were decreased after intake of B. lactis Bi-07. The discrepancy between the results highlights the complexity of the situation and might be explained by a small number of individuals surveyed in the study.

Detection of L. acidophilus and B. lactis in stool samples by DGGE and qPCR indicated survival of the ingested probiotic strains during transit through the intestine. Though assessment of the ingested bacteria was conducted with the use of species-specific rather than strain-specific primers, it is nevertheless most probable that the increase in bacterial counts was a measure of ingested probiotic strains, as it was only observed in Groups A and B after intervention. Furthermore, the elevated numbers of lactobacilli were obviously due to accumulation of L. acidophilus NCFM in feces. These results are supported by other published data which demonstrated significant increase of L. acidophilus and the total population of lactobacilli in feces of healthy adults after NCFM intake (Varcoe et al., 2002; Ouwehand et al., 2009).

As expected, the total microbiota of each child was unique and generally conserved during the intervention period as revealed by the cluster analysis of DGGE profiles. The total bacterial levels in this study (on average 11 Log10 cells g−1 stool), were in accordance with the numbers estimated in human feces using qPCR assays (Kirjavainen et al., 2002; Firmesse et al., 2008). Likewise in case of bifidobacteria, we did not observe clustering of the total bacterial DGGE profiles by the treatment, suggesting that the intake of probiotics did not affect the composition of the main groups of fecal microbiota. Similar conclusions were drawn from earlier human intervention studies with probiotic lactobacilli and bifidobacterial species (Goossens et al., 2003; Kendler et al., 2006; He et al., 2008).

As far as we know this is the first study that used pyrosequencing to characterize the fecal microbiota in association with probiotic consumption in young children with AD. The discriminating power of our approach, evaluated by the number of OTUs and Chao1 indices, was in agreement with recent studies on the fecal microbiota using 454 GS FLX pyrosequencing platform (Andersson et al., 2008; Zhang et al., 2009). The main bacterial taxa found by pyrosequencing in this study were also detected in feces of healthy children and infants with eczema (Roesch et al., 2009; Hong et al., 2010). The proportions of bacterial populations determined by pyrosequencing were not significantly affected by the intake of L. acidophilus NCFM and B. lactis Bi-07 in accordance with the DGGE and qPCR results. Slight increase in bifidobacteria after intervention is in consistent with the qPCR results. Another interesting trend was the elevated proportion of F. prausnitzii in the DNA samples after intervention which might be related to the reduction in eczema, because this bacterium is known to exhibit anti-inflammatory effects in the gut (Dethlefsen et al., 2008; Sokol et al., 2008; Biagi et al., 2010). However, more data are required to confirm this assumption.

In summary, the hypothesis that probiotic bacteria L. acidophilus NCFM and B. lactis Bi-07 affect intestinal microbiota was not confirmed in this study. However, certain limitations of this research, such as a small number of bacterial groups assessed by qPCR and a small group of participants, might explain the lack of an effect. Another reason might be pitfalls connected with the use of fecal samples for characterization of the gut microbial community, because the composition of fecal microbiota is known to be different from bacterial populations adherent to intestinal mucosa (Eckburg et al., 2005; Mentula et al., 2005). Noteworthy, this study indicates that there is a link between development of atopic eczema and the levels of lactobacilli and bifidobacteria in the gut which is not attributed to probiotic intake. Considering the comprehensive knowledge of host specificity and stability of the intestinal bacterial community, also demonstrated in this research, as well as genetic predisposition and differences in lifestyle, it might be expected that children react differently to probiotic intake. In this connection extensive metagenomic studies and larger interventions will be needed to discover significant shifts in the intestinal microbiota imposed by probiotic interventions.

Supporting Information

Fig. S1. Cluster analysis of Bifidobacterium genus-specific DGGE profiles from children with AD performed with the use of the Pearson similarity coefficient and presented as unweighted-pair group method with arithmetic averages dendogram.

Fig. S2. Cluster analysis of DGGE profiles of the total fecal microbiota performed with the use of the Pearson similarity coefficient and presented as unweighted-pair group method with arithmetic averages dendogram.

Fig. S3. Bacterial phyla determined by 454 GS FLX pyrosequencing of the V4 region of 16S rRNA gene in fecal samples from six children with AD.

Fig. S4. Rarefaction analysis of the libraries of V4 pyrosequencing tags of the 16S rRNA gene.

Table S1. Primers, adaptor and sample-specific barcodes used for tag-encoded amplicon pyrosequencing of the V4 region of 16S rRNA gene.

Please note: Wiley-Blackwell is not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.


This research was financially supported by (1) the Danish Agricultural and Veterinary Research Council and the Danish Dairy Research Foundation and (2) by European Commission through the Six Framework Programme for Research and Development, the project FOOD-CT-2005-007081 (PathogenCombat).


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