Original Article

International Journal of Obesity (2012) 36, 817–825; doi:10.1038/ijo.2011.153; published online 9 August 2011

Obesity-associated gut microbiota is enriched in Lactobacillus reuteri and depleted in Bifidobacterium animalis and Methanobrevibacter smithii

M Million1, M Maraninchi2, M Henry1, F Armougom1, H Richet1, P Carrieri3,4,5, R Valero2, D Raccah6, B Vialettes2 and D Raoult1

  1. 1URMITE -CNRS UMR 6236 IRD 198, IFR 48, Faculté de Médecine, Université de la Méditerranée, Marseille, France
  2. 2Service de Nutrition, Maladies Métaboliques et Endocrinologie, UMR-INRA U1260, CHU de la Timone, Marseille, France
  3. 3INSERM, U912(SE4S), Marseille, France
  4. 4Université Aix Marseille, IRD, UMR-S912, Marseille, France
  5. 5ORS PACA, Observatoire Régional de la Santé Provence Alpes Côte d’Azur, Marseille, France
  6. 6Service de Nutrition et Diabétologie, CHU Sainte Marguerite, Marseille, France

Correspondence: Professor D Raoult, Unité des Rickettsies, URMITE -CNRS UMR 6236 IRD 198, IFR 48, Faculté de Médecine, Université de la Méditerranée, 27 Bd Jean Moulin, Marseille, 13005 France. E-mail: Didier.raoult@gmail.com

Received 24 November 2010; Revised 27 June 2011; Accepted 2 July 2011
Advance online publication 9 August 2011





Obesity is associated with increased health risk and has been associated with alterations in bacterial gut microbiota, with mainly a reduction in Bacteroidetes, but few data exist at the genus and species level. It has been reported that the Lactobacillus and Bifidobacterium genus representatives may have a critical role in weight regulation as an anti-obesity effect in experimental models and humans, or as a growth-promoter effect in agriculture depending on the strains.

Objectives and methods:


To confirm reported gut alterations and test whether Lactobacillus or Bifidobacterium species found in the human gut are associated with obesity or lean status, we analyzed the stools of 68 obese and 47 controls targeting Firmicutes, Bacteroidetes, Methanobrevibacter smithii, Lactococcus lactis, Bifidobacterium animalis and seven species of Lactobacillus by quantitative PCR (qPCR) and culture on a Lactobacillus-selective medium.



In qPCR, B. animalis (odds ratio (OR)=0.63; 95% confidence interval (CI) 0.39–1.01; P=0.056) and M. smithii (OR=0.76; 95% CI 0.59–0.97; P=0.03) were associated with normal weight whereas Lactobacillus reuteri (OR=1.79; 95% CI 1.03–3.10; P=0.04) was associated with obesity.



The gut microbiota associated with human obesity is depleted in M. smithii. Some Bifidobacterium or Lactobacillus species were associated with normal weight (B. animalis) while others (L. reuteri) were associated with obesity. Therefore, gut microbiota composition at the species level is related to body weight and obesity, which might be of relevance for further studies and the management of obesity. These results must be considered cautiously because it is the first study to date that links specific species of Lactobacillus with obesity in humans.


gut microbiota; Methanobrevibacter smithii; Lactobacillus reuteri; Bifidobacterium animalis



Obesity, defined as a body mass index (BMI) over 30kgm−2(ref. 1) and a massive expansion of fat, is related to a significantly increased mortality and is a risk factor for many diseases, including diabetes mellitus, hypertension, respiratory disorders, ischemic heart disease, stroke and cancer.2, 3 Obesity can be considered as a transmissible disease because maternal obesity predisposes children to adulthood obesity.4 Its prevalence is increasing steadily among adults, adolescents and children, and has doubled since 1960; and obesity is now considered a worldwide epidemic as, for example, over 30% of the population of North America is obese. The WHO data indicate that obesity currently affects at least 400 million people worldwide and 1.6 billion are overweight. The WHO further projects that by 2015, ~2.3 billion adults will be overweight and more than 700 million will be obese.5 The causes behind the obesity epidemic appear to be complex and involve environmental, genetic, neural and endocrine origins.6

More recently, obesity has been associated with a specific profile of the bacterial gut microbiota, including a decrease in the Bacteroidetes/Firmicutes ratio7, 8, 9, 10 and a decrease in Methanobrevibacter smithii, the leading representative of the gut microbiota archaea.11 Since these pioneering studies, significant associations were found between the increase of some bacterial groups and obesity (Lactobacillus,12 Staphylococcus aureus,13, 14, 15 Escherichia coli,15 Faecalibacterium prausnitzii16). Conversely, other groups have been associated with lean status, mainly belonging to the Bifidobacterium genus.11, 13, 14, 15, 16 To date, controversial studies make it clear that the connection between the microbiome and excess weight is complex.17

As many probiotic strains of Lactobacillus and Bifidobacterium are marketed in products for human consumption, altering the intestinal flora18 and stimulating indigenous lactobacilli and bifidobacteria strains,19 we hypothesized that widespread ingestion of probiotics may promote obesity by altering the intestinal flora.20, 21, 22 However, this remains controversial.23, 24 In a first step to elucidate the interactions between probiotics for human consumption and obesity, only a few studies have compared the obese and lean subjects by focusing on the Lactobacillus and Bifidobacterium genera at the species level13, 16 and they have not been able to demonstrate significant differences probably because of a too small sample size. As a result, by increasing the sample size, we analyze the composition of the digestive microbiota for Firmicutes, Bacteroidetes, the archaea M. smithii, Lactobacillus genus, L. lactis, and explore the relationships between seven selected species of Lactobacillus and one species of Bifidobacterium, used elsewhere in marketed probiotics for human consumption and obesity.


Materials and methods

Ethics, participants and samples

All aspects of the study were approved by the local ethics committee ‘Comité d’éthique de l’IFR 48, Service de Médecine Légale’ (Faculté de Médecine, Marseille, France) under the accession number 10–002, 2010. Only verbal consent was necessary from patients for this study. This is according to the French bioethics decree Number 2007–1220, published in the official journal of the French Republic. Obese patients, as defined by a BMI>30kgm−2 (BMI: weight over height squared (kgm−2)), were selected from two endocrinology units (Hopital La Timone and Hopital Sainte Marguerite, Marseilles, France) from a group of patients attending the clinic for excessive body weight. BMI provides the most useful population-level measure of overweight and obese, as it is the same for both sexes and for all ages of adults.5 However, it may not correspond to the same degree of fatness in different individuals (The Y-Y paradox).25 Control subjects were healthy volunteers over 18 years of age with BMIs between 19 and 25kgm−2. Only a few patients had participated in the previous study conducted by our laboratory.12 The control subjects were predominantly Caucasian and were approached in different geographical locations using a snowball approach. This approach was helpful in making the period of recruitment of cases and controls comparable. The exclusion criteria included the following: non-assessable BMI value, BMI<19kgm−2, BMI>25kgm−2 and <30kgm−2, gastric bypass, history of colon cancer, bowel inflammatory diseases, acute or chronic diarrhea in the previous 4 weeks and antibiotic administration <1 month before stool collection. Clinical data (gender, date of birth, clinical history, weight, height and antibiotic use) were recorded using a standardized questionnaire. The samples, collected using sterile plastic containers, were transported as soon as possible to the laboratory and frozen immediately at −80°C for later analysis. For Firmicutes, Bacteroidetes, M. smithii and Lactobacillus species, analyses were first performed on the whole population and then after exclusion of common subjects with our previous study.12

Analysis of gut microbiota

Culture on specific Lactobacillus medium (LAMVAB medium)

After thawing at room temperature, 100mg of stool was suspended in 900μl of cysteine–peptone–water solution26 and homogenized. A serial dilution was undertaken in phosphate buffered saline. Samples diluted to 1/10 and 1/1000 were inoculated using a 10μl inoculation loop on LAMVAB medium.27 After a 72-hour incubation in jars (AnaeroPack, Mitsubishi Gas Chemical America, Inc., New York, NY, USA) in an anaerobic atmosphere (GasPak EZ Anaerobe, Becton Dickinson, Heidelberg, Germany) at 37°C, the number of morphotypes were identified and 1–4 colonies per morphotype were placed on four spots of an MTP 384 Target plate made of polished steel (Bruker Daltonics GmbH, Bremen, Germany) and stored in trypticase cases in soy culture medium (AES, Bruz, France).

Lactobacillus strain collection and MALDI-TOF spectra database

The Lactobacillus strain collection of our laboratory has been completed by the strains from the Pasteur and DSMZ collections, and reference spectra have been created from those missing in the Bruker database. Bacterial identification was undertaken with an Autoflex II mass spectrometer (Bruker Daltonik GmbH). Data were automatically acquired using Flex control 3.0 and Maldi Biotyper Automation Control 2.0. (Bruker Daltonics GmbH). Raw spectra, obtained for each isolate, were analyzed by standard pattern matching (with default parameter settings) against the spectra of species used as a reference database. An isolate was regarded as correctly identified at the species level when at least one spectrum had a score greater than or equal to1.9, and one spectrum had a score greater than or equal to1.7.28 The reproducibility of the method was evaluated by the duplicate analysis of 10 samples.

Quantitative real-time PCR for M. smithii, Bacteroidetes, Firmicutes and Lactobacillus genus

DNA was isolated from stools as described in Dridi et al.29 The purified DNA samples were eluted to a final volume of 100μl and stored at −80°C until analysis. Real-time PCR was performed on a Stratagene MX3000 system (Agilent, Santa Clara, CA, USA) using QuantiTect PCR mix (Qiagen, Courtaboeuf, France) as described previously.12

Quantitative real-time PCR specific for Lactococcus lactis, Bifidobacterium animalis and seven Lactobacillus species

The primer and probe sequences were located on the Tuf (elongation factor Tu) gene. The Tuf gene from the Lactobacillus strains, reported in Supplementary Table 1, were sequenced and compared, where possible, to the sequence reported in Genbank as described in Supplementary Text 1. All of these sequences were compared by ClustalX (1.8; http://www.clustal.org) using global-multiple sequence alignment by the progressive method. A distance is calculated between every pair of sequences and these are used to construct the phylogenetic tree, which guides the final multiple alignment. The scores are calculated from separate pairwise alignments using the dynamic programming method. A consensus sequence was obtained and compared with the Tuf sequences of Lactobacillus acidophilus, Lactobacillus casei-paracasei, Lactobacillus plantarum, Lactobacillus reuteri, Lactobacillus gasseri, Lactobacillus fermentum and Lactobacillus rhamnosus, Bifidobacterium animalis and Lactococcus lactis, and sequences of primers and probes of highly specific real-time PCR were established. The primer and probe sequences are reported in Supplementary Table 2. The Lactobacillus strain-specific detection proceeded in duplex real-time PCR: L. acidophilus (FAM) and L. casei/paracasei (VIC), L. plantarum (FAM) and L. reuteri (VIC), L. gasseri (FAM) and fermentum (VIC), and L. rhamnosus (FAM). B. animalis (VIC) and Lactococcus lactis (FAM) detection utilized simplex real-time PCR. The duplex real-time PCR was executed as described above and in Armougom et al.12 The specificity was tested on the DNA of the reference strains reported in Supplementary table 1. The stool-purified DNA was analyzed in samples that were pure, diluted at 1/10, and diluted at 1/100 to confirm the absence of inhibitors. Negative controls were included on each plate. The different lactobacilli, B. animalis and Lactococcus lactis were quantified using a plasmid standard curve from 107–10 copies per assay.

Statistical Analysis

First, the results of Lactobacillus-specific culture and quantitative PCR (qPCR) were compared in the two groups (obese and control group) using the Fisher's exact test when comparing proportions, and the Mann–Whitney test when comparing bacterial concentrations. A difference was considered statistically significant when P<0.05. In order to identify which qPCR bacterial groups (Bacteroidetes, B. animalis, Lactococcus lactis, L. acidophilus, L. casei/paracasei, L. fermentum, L. gasseri, L. plantarum, L. reuteri, L. rhamnosus) was most associated with the likelihood of being obese while taking into account possible confounders like age or gender, a logistic regression model was used. Variables with a liberal P<0.20 in the univariate logistic regression analysis were considered eligible for the multiple logistic regression analyses.30 A secondary analysis based on logistic regression analysis was used to identify which culture variables (Lactobacillus species concentration) where associated with obesity. Data analyses were conducted using SPSS v.9.0 (SPSS Inc., Chicago, IL, USA).




In total, 115 subjects (68 obese patients and 47 controls) were included. Thirteen obese subjects and nine controls were part of the previous study conducted in our laboratory.12 The two populations were homogeneous in sex and height, but not in age (Table 1).


In total, 68 obese and 44 controls samples were analyzed. The number of positive samples was greater among the controls vs obese (32/44 vs 30/68, Fisher's exact test, P=0.002). For positive samples, the concentration was not significantly different between obese subjects and controls, respectively (median 4.15 (interquartile range 4–6) vs 5.2 (4–6) log10 CFUml−1, Mann–Whitney test, P=0.93). The proportion (Table 2) and non-parametric quantitative comparison of the concentration of Lactobacillus species between obese subjects and controls has been achieved for the species present in at least six individuals. L. paracasei was found more frequently in controls (17/44 vs 10/68, Fisher's exact test, P=0.004). L. reuteri was found more frequently in obese patients (6/68 vs 1/44, Fisher's exact test, P=0.15), although this was not significant. L. plantarum was found only in controls (8/44 vs 0/68, Fisher's exact test, P=0.0004). Quantitative comparison found higher levels of L. paracasei and L. plantarum in controls (Mann–Whitney test, P=0.005 and P=0.0004, respectively), while L. reuteri was higher in the obese subjects; however, this was not significant (Mann–Whitney test, P=0.14) (Figure 1). Variables eligible for the final logistic regression model were L. paracasei, L. reuteri, L. plantarum, L. brevis, L. fermentum and age. The final multiple logistic regression model showed that after adjustment for age, only L. paracasei was significantly associated with lean status (odds ratio=0.79; 95% confidence interval 0.64–0.97; P=0.03).

Figure 1.
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Quantification of L. paracasei, L. plantarum and L. reuteri in culture (LAMVAB medium) −log (colony forming units per ml of feces)—Mann–Whitney test.

Full figure and legend (38K)

Firmicutes, Bacteroidetes, M. smithii and Lactobacillus species-specific qPCR

M. smithii was found more frequently in controls (40/45(89%) vs 50/67(75%), Fisher's exact test, P=0.05). The analysis did find a lower concentration of M. smithii in obese subjects (Mann–Whitney test, P=0.002; Table 3) and a higher concentration of Lactobacillus (Mann–Whitney test, P=0.04). Bacteroidetes was found in lower concentration in obese, but this result was not significant (Mann–Whitney test, P=0.25) (Figure 2). The same results were found after the exclusion of the common subjects from our previous study (Mann–Whitney test; higher level of Lactobacillus genus in obese people, P=0.026; lower level of M. smithii, P=0.008 and lower level of Bacteroidetes, P=0.09).

Figure 2.
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Quantification of Bacteroidetes, Firmicutes, M. smithii and Lactobacillus genus by qPCR—Mann–Whitney test.

Full figure and legend (97K)

BifidobacteriumLactococcusLactobacillus species-specific qPCR

The different Bifidobacterium–Lactococcus–Lactobacillus species-specific real-time PCRs were tested for their specificity against purified DNA of the strains reported in Supplementary Table 1. The different real-time PCR systems were tested for their sensitivity and we obtained a cycle threshold of about 35 for 10 copies of DNA per 5μl of sample. All of these real-time PCRs have good sensitivity and specificity (Supplementary Table 3). In total, 64 obese samples and 43 control samples were analyzed. The presence of B. animalis was associated with normal weight (Table 4, Fisher's exact test, P=0.007), and L. reuteri was associated with obesity (Fisher's exact test, P=0.03). Comparison using non-parametric statistics found that levels of B. animalis were lower (Mann–Whitney test, P=0.004) and that of L. reuteri were higher in obese people (Mann–Whitney test, P=0.02) (Figure 3). By comparing the culture and the Lactobacillus species-specific PCR, the sensitivity was higher for all seven tested species by PCR vs culture except for L. acidophilus, which was not found by culture or species-specific PCR. Overall, results of culture and PCR were consistent for the presence of L. casei/paracasei (Fisher's exact test, P=0,017), L. plantarum (Fisher's exact test, P=0,05) and L. reuteri (Fisher's exact test, P=0,00001).

Figure 3.
Figure 3 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

Quantification of B. animalis, L. casei/paracasei, L. plantarum and L. reuteri by qPCR—Mann–Whitney test.

Full figure and legend (83K)

Logistic regression analysis

The results of the logistic regression analysis on the qPCR results are presented in Table 5. Variables eligible for the final model were L. casei/paracasei, L. reuteri, L. gasseri, B. animalis, M. smithii and age. The final multiple logistic regression model showed that after adjustment for age, L. reuteri, B. animalis and M. smithii were significantly associated with obesity. L. reuteri was the only one which showed higher levels in obese individuals while B. animalis and M. smithii were found at greater levels in non-obese subjects.



To our knowledge, we report the largest case–control study comparing human obese gut microbiota to controls focusing on Archaea, Bacteroidetes, Firmicutes, Lactobacillus genus, Lactococcus lactis and B. animalis and, for the first time, we used a culture-dependent and culture-independent method to compare the Lactobacillus population at the species level between obese and normal-weighted humans. Our results confirm global alteration in obese gut microbiota with a lower level of M. smithii as already reported in the literature,11 and newly report lower levels of B. animalis, L. paracasei, L. plantarum and higher levels of L. reuteri in obese gut microbiota.

The qPCR system used in this study to detect and quantify Bacteroidetes, Firmicutes, Lactobacillus genus and M. smithii in human feces has already been evaluated and validated.12, 29 LAMVAB-selective media has also been used successfully to identify and enumerate lactobacilli from human feces.27 As in our previous study,12 we found an increase in Lactobacillus in obese patients using the same Lactobacillus genus-specific PCR system. However, we found that its sensitivity profile was heterogeneous among the Lactobacillus species found in human feces by culture (data not shown). We subsequently developed a novel Lactobacillus species-specific qPCR system targeting species associated with obesity or normal weight in our preliminary culture study, and targeting other species present in marketed probiotics products as Lactococcus lactis and B. animalis. Species-specific Lactobacillus PCR based on the Tuf gene and designed for this new study showed good reproducibility, sensitivity and specificity. However, we found significant discrepancies between culture and Lactobacillus species-specific PCR species. First, L. gasseri and L. acidophilus could not be identified in culture due to the presence of vancomycin in the LAMVAB medium. Conversely, although qPCR was much more sensitive than culture to detect selected species of Lactobacillus, we showed that the two methods were consistent for L. casei/paracasei, L. plantarum and L. reuteri. For these three Lactobacillus species, both techniques resulted in the same effect direction with human obesity gut microbiota enriched in L. reuteri, and depleted in L. casei/paracasei and L. plantarum.

The decrease of Bacteroidetes was historically the first alteration significantly associated with obesity as reported by Ley and Turnbaugh,8 in mice and in North American individuals,7, 9 and by Santacruz et al.,15 who observed overweight pregnant women in Spain. We found the same correlation in our previous study,12 and the same effect direction in the present study with the same PCR system on the whole population and after the exclusion of common subjects. Schwiertz et al.11 reported opposite results, but the methodology was objectionable because the Bacteroidetes proportion was obtained by summing Bacteroides and Prevotella genera. Other studies found no interaction between the relative or absolute abundance of Bacteroidetes and obesity.31, 32, 33

In our previous study,12 abundance of M. smithii was significantly higher in patients with anorexia but not in lean controls. In this new study, we found that M. smithii was less frequent and significantly less abundant in obese patients on the whole population and after the exclusion of common subjects. Schwiertz et al.11 using a specific qPCR for Methanobrevibacter species, found similar results in a German population. These results are in contradiction to those of Zhang et al.33 who found that Methanobacteriales was present only in obese individuals using a qPCR but only three obese vs three controls were compared.

In this study, we report an association between lower levels of B. animalis and obesity for the first time. Five studies reported a decreased number of Bifidobacterium representatives in the feces of obese subjects at the genus level.11, 13, 14, 15, 16 At the species level, Kalliomaki et al.13 using a Bifidobacterium species-specific PCR, found that Bifidobacterium longum and Bifidobacterium breve were higher in normal weight controls, but this result was not significant probably because of a small sample size. Experimental data report that administration of a B. breve strain to mice with high-fat diet-induced obesity led to a significant weight decrease.34 Administering four different Bifidobacterium strains to high-fat diet induced obese rats, Yin et al.35 reported that one strain increased body weight gain, another induced a decrease and the two other strains lead to no significant change in body weight but species were not mentioned in this study. In this way, Cani et al.36 reported that high-fat feeding was associated with higher endotoxaemia and lower Bifidobacterium species cecal content in mice. The selective increase of bifidobacteria by oligofructose, improving mucosal barrier function, significantly and positively correlated with improved glucose tolerance, glucose-induced insulin secretion and decreased endotoxaemia.

L. plantarum and L. paracasei were associated with normal weight in culture, consistent with experimental models in the literature reporting an anti-obesity effect of L. plantarum in mice.37 Other Lactobacillus strains have shown an anti-obesity effect in animals and humans similar to the L. gasseri SBT2055 (LG2055) strain in lean Zucker rats38 and in humans.39 This anti-obesity effect may be linked to the production of specific molecules that can interfere with host metabolism, such as conjugated linoleic acid (CLA) for L. plantarum or L. rhamnosus.37, 40 In vivo and in vitro analyses of physiological modifications imparted by CLA on protein and gene expression suggest that CLA exerts its delipidating effects by modulating energy expenditure, apoptosis, fatty acid oxidation, lipolysis, stromal vascular cell differentiation and lipogenesis.37 Authors who have investigated the mechanisms linking conjugated linoleic acid and anti-obesity effects have reported the upregulated expression of genes encoding uncoupling proteins (UCP-2), which could be a primary mechanism through which CLA increases energy expenditure and produces an anti-obesity effect.40

L. reuteri has been associated here with obesity. L. reuteri has been one of the most studied probiotic species especially for its ability to inhibit the growth of other potentially pathogenic microorganisms by secreting antibiotic substances such as reuterin.41 When introduced in pigs, turkeys and rats, L. reuteri led to a significant weight gain and was isolated in higher concentrations from feces after probiotic administration.42, 43, 44 The mechanism by which L. reuteri is able to support the healthy growth of these animals is not entirely understood. It is possible that L. reuteri simply serves to protect livestock against illness caused by Salmonella typhimurium and other pathogens. However, other studies have revealed that L. reuteri can also help when the growth depression is caused entirely by a lack of dietary protein and not by contagious disease.45 This raises the possibility that L. reuteri somehow improves the intestines’ ability to absorb and process nutrients, and increase food conversion.46

As a theoretical basis for the causal link between the gut microbiota alterations and obesity, several mechanisms have been suggested. First, the gut microbiota could interact with weight regulation by hydrolysis of indigestible polysaccharides to monosaccharides easily absorbable activating lipoprotein lipase. Consequently, glucose is rapidly absorbed producing substantial elevations in serum glucose and insulin, both factors that trigger lipogenesis and fatty acids excessively stored with de novo synthesis of triglycerides derived from liver, these two phenomena causing weight gain.47 Second, the composition of gut microbiota has been shown to selectively suppress the angiopoietin-like protein 4/fasting-induced adipose factor in the intestinal epithelium, known as a circulating lipoprotein lipase inhibitor and regulator of peripheral lipid and glucose metabolism.48 Third, it has been suggested that bacterial isolates of gut microbiota may have pro- or anti-inflammatory properties, impacting weight as obesity, having been associated with a low-grade systemic inflammation corresponding to higher plasma endotoxin lipopolysaccharide concentrations defined as metabolic endotoxaemia.49, 50, 51, 52 Fourth, extracting crude fat in feed and excreta, Nahashon et al.53 reported that feeding laying Leghorn with Lactobacillus improved significantly retention of fat with increased cellularity of the Peyer's patches of the ileum, which indicated ileal immune response. Conversely, Bifidobacterium and Lactobacillus species have been cited to deconjugate bile acids, which may decrease fat absorption.54

Finally, specific strains of Lactobacillus and Bifidobacterium fed to farm animals have been shown to increase daily weight gain,55 and this fact has been used for decades in agriculture to increase feed conversion. In this context, one cannot exclude that the ‘growth promoter’ effect in animals associated with oral administration of specific probiotics strains is similar to the mechanisms involved in human obesity. For instance, Abdulrahim et al.56 reported that L. acidophilus significantly increased abdominal fat deposition in female chickens when administered alone and up to 31% when it was associated with zinc bacitracin. Further studies are therefore mandatory in exploring the interactions between probiotics and weight regulation.



In conclusion, reduced levels of M. smithii has been confirmed as being associated with obesity. In addition, higher levels of B. animalis, L. paracasei or L. plantarum were associated with a normal weight whereas higher levels of L. reuteri were associated with obesity, suggesting a possible interrelationship between certain probiotic species, marketed elsewhere for human consumption, and obesity. These results must be considered cautiously because it is the first study to date that links specific species of Lactobacillus with obesity in humans. This issue will be of critical importance in the management of the twenty-first century worldwide epidemic that is obesity and especially considering the booming market of probiotics.




The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript


Conflict of interest

The authors declare no conflict of interest.



  1. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004; 363: 157–163. | Article | PubMed | ISI |
  2. Whitlock G, Lewington S, Sherliker P, Clarke R, Emberson J, Halsey J et al. Body-mass index and cause-specific mortality in 900000 adults: collaborative analyses of 57 prospective studies. Lancet 2009; 373: 1083–1096. | Article | PubMed | ISI |
  3. Yanovski SZ, Yanovski JA. Obesity. N Engl J Med 2002; 346: 591–602. | Article | PubMed | ISI | CAS |
  4. Lawlor DA, Smith GD, O’Callaghan M, Alati R, Mamun AA, Williams GM et al. Epidemiologic evidence for the fetal overnutrition hypothesis: findings from the mater-university study of pregnancy and its outcomes. Am J Epidemiol 2007; 165: 418–424. | Article | PubMed | ISI |
  5. World health organization. Obesity and overweight. Fact sheet N°311. 2011.
  6. Tilg H, Moschen AR, Kaser A. Obesity and the microbiota. Gastroenterology 2009; 136: 1476–1483. | Article | PubMed | ISI |
  7. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE et al. A core gut microbiome in obese and lean twins. Nature 2009; 457: 480–484. | Article | PubMed | ISI | CAS |
  8. Ley RE, Backhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut microbial ecology. Proc Natl Acad Sci USA 2005; 102: 11070–11075. | Article | PubMed | CAS |
  9. Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature 2006; 444: 1022–1023. | Article | PubMed | ISI | CAS |
  10. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006; 444: 1027–1031. | Article | PubMed | ISI |
  11. Schwiertz A, Taras D, Schafer K, Beijer S, Bos NA, Donus C et al. Microbiota and SCFA in lean and overweight healthy subjects. Obesity (Silver Spring) 2010; 18: 190–195. | Article | PubMed |
  12. Armougom F, Henry M, Vialettes B, Raccah D, Raoult D. Monitoring bacterial community of human gut microbiota reveals an increase in Lactobacillus in obese patients and Methanogens in anorexic patients. PLoS One 2009; 4: e7125. | Article | PubMed | CAS |
  13. Kalliomaki M, Collado MC, Salminen S, Isolauri E. Early differences in fecal microbiota composition in children may predict overweight. Am J Clin Nutr 2008; 87: 534–538. | PubMed | ISI | CAS |
  14. Collado MC, Isolauri E, Laitinen K, Salminen S. Distinct composition of gut microbiota during pregnancy in overweight and normal-weight women. Am J Clin Nutr 2008; 88: 894–899. | PubMed | ISI | CAS |
  15. Santacruz A, Collado MC, Garcia-Valdes L, Segura MT, Martin-Lagos JA, Anjos T et al. Gut microbiota composition is associated with body weight, weight gain and biochemical parameters in pregnant women. Br J Nutr 2010; 104: 83–92. | Article | PubMed | ISI | CAS |
  16. Balamurugan R, George G, Kabeerdoss J, Hepsiba J, Chandragunasekaran AM, Ramakrishna BS. Quantitative differences in intestinal Faecalibacterium prausnitzii in obese Indian children. Br J Nutr 2010; 103: 335–338. | Article | PubMed | ISI |
  17. Pennisi E. Microbiology. girth and the gut (bacteria). Science 2011; 332: 32–33. | Article | PubMed | ISI |
  18. Fujimoto J, Matsuki T, Sasamoto M, Tomii Y, Watanabe K. Identification and quantification of Lactobacillus casei strain Shirota in human feces with strain-specific primers derived from randomly amplified polymorphic DNA. Int J Food Microbiol 2008; 126: 210–215. | Article | PubMed | ISI |
  19. Ohashi Y, Inoue R, Tanaka K, Matsuki T, Umesaki Y, Ushida K. Lactobacillus casei strain Shirota-fermented milk stimulates indigenous lactobacilli in the pig intestine. J Nutr Sci Vitaminol (Tokyo) 2001; 47: 172–176. | Article | PubMed |
  20. Raoult D. Obesity pandemics and the modification of digestive bacterial flora. Eur J Clin Microbiol Infect Dis 2008; 27: 631–634. | Article | PubMed | ISI | CAS |
  21. Raoult D. Human microbiome: take-home lesson on growth promoters? Nature 2008; 454: 690–691. | Article | PubMed | ISI | CAS |
  22. Raoult D. Probiotics and obesity: a link? Nat Rev Microbiol 2009; 7: 616. | Article | PubMed | ISI |
  23. Delzenne N, Reid G. No causal link between obesity and probiotics. Nat Rev Microbiol 2009; 7: 901. | Article | PubMed | CAS |
  24. Ehrlich SD. Probiotics—little evidence for a link to obesity. Nat Rev Microbiol 2009; 7: 901. | Article | PubMed | CAS |
  25. Yajnik CS, Yudkin JS. The Y-Y paradox. Lancet 2004; 363: 163. | Article | PubMed | ISI |
  26. Jackson MS, Bird AR, McOrist AL. Comparison of two selective media for the detection and enumeration of lactobacilli in human faeces. J Microbiol Methods 2002; 51: 313–321. | Article | PubMed | ISI |
  27. Hartemink R, Domenech VR, Rombouts FM. LAMVAB-A new selective medium for the isolation of lactobacilli from faeces. J Microbiol Methods 1997; 29: 77–84. | Article | ISI | CAS |
  28. Seng P, Drancourt M, Gouriet F, La Scola B, Fournier PE, Rolain JM et al. Ongoing revolution in bacteriology: routine identification of bacteria by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Clin Infect Dis 2009; 49: 543–551. | Article | PubMed | ISI |
  29. Dridi B, Henry M, El Khechine A, Raoult D, Drancourt M. High prevalence of Methanobrevibacter smithii and Methanosphaera stadtmanae detected in the human gut using an improved DNA detection protocol. PLoS One 2009; 4: e7063. | Article | PubMed |
  30. Hosmer DW, Lemeshow S. Applied Logistic Regression 2nd edn. Wiley: New York, 2000.
  31. Mai V, McCrary QM, Sinha R, Glei M. Associations between dietary habits and body mass index with gut microbiota composition and fecal water genotoxicity: an observational study in African American and Caucasian American volunteers. Nutr J 2009; 8: 49. | Article | PubMed |
  32. Duncan SH, Lobley GE, Holtrop G, Ince J, Johnstone AM, Louis P et al. Human colonic microbiota associated with diet, obesity and weight loss. Int J Obes (Lond) 2008; 32: 1720–1724. | Article | PubMed | CAS |
  33. Zhang H, DiBaise JK, Zuccolo A, Kudrna D, Braidotti M, Yu Y et al. Human gut microbiota in obesity and after gastric bypass. Proc Natl Acad Sci USA 2009; 106: 2365–2370. | Article | PubMed |
  34. Kondo S, Xiao JZ, Satoh T, Odamaki T, Takahashi S, Sugahara H et al. Antiobesity effects of Bifidobacterium breve strain B-3 supplementation in a mouse model with high-fat diet-induced obesity. Biosci Biotechnol Biochem 2010; 74: 1656–1661. | Article | PubMed | ISI |
  35. Yin YN, Yu QF, Fu N, Liu XW, Lu FG. Effects of four bifidobacteria on obesity in high-fat diet induced rats. World J Gastroenterol 2010; 16: 3394–3401. | Article | PubMed | ISI |
  36. Cani PD, Neyrinck AM, Fava F, Knauf C, Burcelin RG, Tuohy KM et al. Selective increases of bifidobacteria in gut microflora improve high-fat-diet-induced diabetes in mice through a mechanism associated with endotoxaemia. Diabetologia 2007; 50: 2374–2383. | Article | PubMed | ISI | CAS |
  37. Lee K, Paek K, Lee HY, Park JH, Lee Y. Antiobesity effect of trans-10, cis-12-conjugated linoleic acid-producing Lactobacillus plantarum PL62 on diet-induced obese mice. J Appl Microbiol 2007; 103: 1140–1146. | Article | PubMed | ISI |
  38. Hamad EM, Sato M, Uzu K, Yoshida T, Higashi S, Kawakami H et al. Milk fermented by Lactobacillus gasseri SBT2055 influences adipocyte size via inhibition of dietary fat absorption in Zucker rats. Br J Nutr 2009; 101: 1–9. | Article |
  39. Kadooka Y, Sato M, Imaizumi K, Ogawa A, Ikuyama K, Akai Y et al. Regulation of abdominal adiposity by probiotics (Lactobacillus gasseri SBT2055) in adults with obese tendencies in a randomized controlled trial. Eur J Clin Nutr 2010; 64: 636–643. | Article | PubMed | ISI | CAS |
  40. Lee HY, Park JH, Seok SH, Baek MW, Kim DJ, Lee KE et al. Human originated bacteria, Lactobacillus rhamnosus PL60, produce conjugated linoleic acid and show anti-obesity effects in diet-induced obese mice. Biochim Biophys Acta 2006; 1761: 736–744. | PubMed | CAS |
  41. Talarico TL, Casas IA, Chung TC, Dobrogosz WJ. Production and isolation of reuterin, a growth inhibitor produced by Lactobacillus reuteri. Antimicrob Agents Chemother 1988; 32: 1854–1858. | PubMed | ISI | CAS |
  42. Chang YH, Kim JK, Kim HJ, Kim WY, Kim YB, Park YH. Selection of a potential probiotic Lactobacillus strain and subsequent in vivo studies. Antonie Van Leeuwenhoek 2001; 80: 193–199. | Article | PubMed | ISI |
  43. Lu YC, Yin LT, Chang WT, Huang JS. Effect of Lactobacillus reuteri GMNL-263 treatment on renal fibrosis in diabetic rats. J Biosci Bioeng 2010; 110: 709–715. | Article | PubMed | ISI |
  44. England JA, Watkins SE, Saleh E, Waldroup PW. Effects of Lactobacillus reuteri on live performance and intestinal development of male turkeys. J Appl Poultry Sci 1996; 5: 311–324.
  45. Dunham HJ, Casas IA, Edens FW, Parkhurst CR, Garlich JD, Dobrogosz WJ. Avian growth depression in chickens induced by environmental, microbiological, or nutritional stress is moderated by probiotic administrations of Lactobacillus reuteri. Biosc Microflor 1998; 17: 133–139.
  46. Casas IA, Dobrogosz WJ. Validation of the probiotic concept: Lactobacillus reuteri confers broad-spectrum protection against disease in humans and animals. Microb Ecol Health Dis 2000; 12: 247–285.
  47. Backhed F, Manchester JK, Semenkovich CF, Gordon JI. Mechanisms underlying the resistance to diet-induced obesity in germ-free mice. Proc Natl Acad Sci USA 2007; 104: 979–984. | Article | PubMed | CAS |
  48. Backhed F, Ding H, Wang T, Hooper LV, Koh GY, Nagy A et al. The gut microbiota as an environmental factor that regulates fat storage. Proc Natl Acad Sci USA 2004; 101: 15718–15723. | Article | PubMed | CAS |
  49. Bastard JP, Maachi M, Lagathu C, Kim MJ, Caron M, Vidal H et al. Recent advances in the relationship between obesity, inflammation, and insulin resistance. Eur Cytokine Netw 2006; 17: 4–12. | PubMed | ISI | CAS |
  50. Hotamisligil GS. Inflammation and metabolic disorders. Nature 2006; 444: 860–867. | Article | PubMed | ISI | CAS |
  51. Sbarbati A, Osculati F, Silvagni D, Benati D, Galie M, Camoglio FS et al. Obesity and inflammation: evidence for an elementary lesion. Pediatrics 2006; 117: 220–223. | Article | PubMed | ISI |
  52. Fogarty AW, Glancy C, Jones S, Lewis SA, McKeever TM, Britton JR. A prospective study of weight change and systemic inflammation over 9 y. Am J Clin Nutr 2008; 87: 30–35. | PubMed | ISI | CAS |
  53. Nahashon SN, Nakaue HS, Snyder SP, Mirosh LW. Performance of single comb White Leghorn layers fed corn-soybean meal and barley-corn-soybean meal diets supplemented with a direct-fed microbial. Poult Sci 1994; 73: 1712–1723. | Article | PubMed | ISI |
  54. Shimada K, Bricknell KS, Finegold SM. Deconjugation of bile acids by intestinal bacteria: review of literature and additional studies. J Infect Dis 1969; 119: 73–81. | Article |
  55. Fuller R. Probiotics in man and animals. J Appl Bacteriol 1989; 66: 365–378. | Article | PubMed | ISI | CAS |
  56. Abdulrahim SM, Haddadin MS, Odetallah NH, Robinson RK. Effect of Lactobacillus acidophilus and zinc bacitracin as dietary additives for broiler chickens. Br Poult Sci 1999; 40: 91–94. | Article | PubMed | ISI |


We thank all the volunteers without whom this study would not have been possible.

Author contributions

Conceived and designed the experiments: DR. Performed the clinical study: MM, MM, RV, BV and DR. Performed the experiments: MM and MH. Analyzed the data: FA, HR and PC. Wrote the paper: MM, MH, HR and DR.

Supplementary Information accompanies the paper on International Journal of Obesity website

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivative Works 3.0 Unported License.
To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/

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