Impact of supplementation with a food-derived microbial community on obesity-associated inflammation and gut microbiota composition
Obesity is a complex pathology associated with dysbiosis, metabolic alterations, and low-grade chronic inflammation promoted by immune cells, infiltrating and populating the adipose tissue. Probiotic supplementation was suggested to be capable of counteracting obesity-associated immune and microbial alterations, based on its proven immunomodulatory activity and positive effect on gut microbial balance. Traditional fermented foods represent a natural source of live microbes, including environmental strains with probiotic features, which could transiently colonise the gut. The aim of our work was to evaluate the impact of supplementation with a complex foodborne bacterial consortium on obesity-associated inflammation and gut microbiota composition in a mouse model.
C57BL/6J mice fed a 45% high fat diet (HFD) for 90 days were supplemented with a mixture of foodborne lactic acid bacteria derived from the traditional fermented dairy product “Mozzarella di Bufala Campana” (MBC) or with the commercial probiotic GG strain of Lactobacillus rhamnosus (LGG). Inflammation was assessed in epididymal white adipose tissue (WAT) following HFD. Faecal microbiota composition was studied by next-generation sequencing.
Significant reduction of epididymal WAT weight was observed in MBC-treated, as compared to LGG and control, animals. Serum metabolic profiling showed correspondingly reduced levels of triglycerides and higher levels of HDL cholesterol, as well as a trend toward reduction of LDL-cholesterol levels. Analysis of the principal leucocyte subpopulations in epididymal WAT revealed increased regulatory T cells and CD4+ cells in MBC microbiota-supplemented mice, as well as decreased macrophage and CD8+ cell numbers, suggesting anti-inflammatory effects. These results were associated with lower levels of pro-inflammatory cytokines and chemokines in WAT explants. Faecal bacterial profiling demonstrated increased Firmicutes/Bacteroidetes ratio in all mice groups following HFD.
Taken together, these results indicate a protective effect of MBC microbiota supplementation toward HFD-induced fat accumulation and triglyceride and cholesterol levels, as well as inflammation, suggesting a stronger effect of a mixed microbial consortium vs single-strain probiotic supplementation. The immunomodulatory activity exerted by the MBC microbiota could be due to synergistic interactions within the microbial consortium, highlighting the important role of dietary microbes with yet uncharacterised probiotic effect.
KeywordsChronic inflammation Fermented dairy Foodborne microbiota White adipose tissue High fat diet
Granulocyte macrophage-colony stimulating factor
High fat diet
Interferon gamma-induced protein
Lactic acid bacteria
L. rhamnosus GG
Mozzarella di Bufala Campana
De Man Rogosa Sharpe medium
Operational taxonomic units
Principal component analysis
Principal Coordinates Analysis
Regulated on Activation-Normal T cell Expressed and Secreted
Tumour necrosis factor
Regulatory T cells
White adipose tissue
Obesity is a chronic, multifactorial disorder reaching epidemic proportions globally, affecting persons of virtually all ages in both developed and developing countries [1, 2]. Promoted by a combination of genetic predisposition, nutritional excess, and sedentary lifestyle, obesity is primarily characterised by increased fat mass, accompanied by development of related disorders [3, 4, 5]. Expansion of the adipose organ, mainly affecting white adipose tissue (WAT), results in adipocyte dysfunction. WAT has been increasingly considered not only a metabolic organ, but also an active endocrine tissue, as it secretes a large number of peptide hormones called adipokines, such as leptin and adiponectin, that operate in a complex network and actively communicate with other organs [6, 7]. Secretion by the adipose organ is disturbed in obesity, as adipokine release is dysregulated and associated with production of several inflammation mediators. For this reason, the adipose tissue is considered to be a major contributor to obesity-linked low-grade chronic inflammation . The inflammatory process involves impairment of both the innate and adaptive immune system and is triggered by local secretion of inflammatory cytokines and chemokines such as tumour necrosis factor-α (TNF-α), interleukin-6 (IL-6), monocyte chemoattractant protein (MCP)-1, and Regulated on Activation Normal T cell Expressed and Secreted (RANTES). These mediators recruit immune cells from blood vessels, such as lymphocytes and macrophages, which in turn massively infiltrate the adipose tissue . Indeed, high levels of inflammatory cells such as T CD8+ lymphocytes and activated M1 macrophages are found in obese WAT, accompanied by decreased levels of CD4+CD25+Foxp3+ regulatory T (Treg) cells, a key population in maintaining immunological tolerance and immune homeostasis [10, 11, 12]. This inflammatory status, arising locally and then becoming systemic, triggers the onset of other diseases frequently associated with obesity such as the metabolic syndrome, characterised by visceral obesity, high blood pressure, insulin resistance, high circulating triglyceride levels, and low HDL cholesterol, leading in turn to increased risk of cardiovascular diseases [13, 14, 15, 16].
The gut microbiota has recently attracted much attention as a crucial factor associated with obesity . Alterations of intestinal microbial composition, in terms of bacterial phyla and classes associated with improved energy extraction from the undigested dietary carbohydrate component, were identified in obese human subjects and animal obesity models, with consequent impact on host metabolism and energy storage . Both diet- and genetically induced obesity were shown to associate with imbalance in the relative proportion of Gram-negative Bacteroidetes and Gram-positive Firmicutes, the two major phyla of gut bacteria, with the latter prevailing in obese subjects . However, imbalance in these two bacterial phyla is not sufficient by itself to determine the obesity phenotype. Other factors, such as diet, pre- and probiotic supplementation, antibiotics, surgery, and faecal transplantation, can impact the overall metabolic capacity of the gut microbiome . Within this context, dietary interventions aimed at promoting selection of beneficial intestinal microbes could represent a powerful strategy to counteract obesity-associated intestinal dysbiosis. There is growing evidence that probiotic and/or prebiotic supplementation can positively modulate gut microbiota, thus representing important assets in the management of obesity . The probiotic component of the gut microbiota can confer health benefits to the host mainly acting on immunomodulation and positively influencing intestinal microbial balance . Probiotic supplementation was therefore suggested to be able to counteract obesity-associated immune alterations and microbial imbalance [23, 24, 25]. As an alternative to commercially available probiotic strains, a natural source of live bacteria is represented by fermented foods, which also confer the advantage of providing the host with a complex microbiota containing several environmental strains with potential probiotic features, such as the capability to transiently colonise animal and human gut and interact with the resident gut microbiota, mainly at a trophic level . Increasing scientific interest in fermented foods was also recently boosted by their possible use as models for more complex microbiota such as the gut . The most relevant foodborne lactic acid bacteria (LAB) belong to the Lactobacillus, Lactococcus, Streptococcus, Pediococcus, and Leuconostoc genera. Several LAB species are also highly represented within the resident gut microbiota of healthy humans. Lactobacillus species, in particular, are abundant both in food and in the gut .
The aim of our work was to evaluate the impact of supplementation with a complex foodborne bacterial community on obesity-associated inflammation, as well as on gut microbiota composition. For this purpose, we used a mouse model of high fat diet (HFD)-induced obesity, comparing the effect of supplementation with a mixture of natural LAB strains derived from the traditional fermented dairy product “Mozzarella di Bufala Campana” (MBC)  and with the well-characterised probiotic GG strain of Lactobacillus rhamnosus (LGG). The MBC bacterial consortium was dominated by Lactobacillus delbrueckii, Lactobacillus fermentum, and Leuconostoc lactis . LGG was used as probiotic control on the basis of its proven beneficial effects in the prevention of obesity [31, 32].
Experimental design, animals, and diets
MBC is a traditional Italian fermented cheese with PDO designation (Product of Designated Origin, EEC Regulation no. 1107). It is consumed fresh, within 2 weeks from production, and it contains high titres of live bacteria . To prepare the MBC microbiota, 10 g of cheese samples were diluted in 90 ml sodium citrate solution (2% w/v) and homogenised in a BagMixer400 (Interscience, France), as previously described . To standardise the bacterial inoculum to be administered to mice, the MBC homogenate was entirely used as a single inoculum in 2 l of De Man Rogosa Sharpe (MRS) medium (Oxoid Ltd., England) and incubated at 37 °C for 48 h under anaerobic conditions (Anaerocult A, Merck, Germany) to obtain a final bacterial titre of about 1.5 × 109 CFU/ml. The resulting bacterial suspension was divided in aliquots containing 1 × 109 CFU each, stored at − 80 °C in 20% (v/v) glycerol, and thawed daily for oral administration to mice, following washing, resuspension in 1× PBS, and mixing with small amounts of minced feed.
The LGG strain ATCC53103 was grown, prepared, and orally given to mice as described above for MBC microbiota.
Serum metabolic measurements
The following plasma parameters were analysed: glucose (Glucose Liquid kit, Sentinel Diagnostics, Milan, Italy), HDL and LDL cholesterol (Max Discovery HDL and LDL Cholesterol Assay Kits, Bioo Scientific, Austin, TX), and triglycerides (Triglycerides Liquid kit, Sentinel Diagnostics). The adiponectin was quantified by ELISA (Biorbyt, Cambridge, UK). Analyses were conducted on a subset of five samples for each treatment, due to technical issues related to serum withdrawal or hemolysis.
Immune cell isolation and staining
Macrophages and lymphocytes were isolated from the epididymal WAT stromal vascular fraction (SVF), according to , as several populations of immune cells are well known to reside in the SVF. The following monoclonal antibodies, purchased from eBioscience (San Diego, CA), were used in this study: FITC anti-CD3 (clone 500A2), PE anti-CD8 (clone 53-6.7), PE-Cy5 anti-CD4 (clone RM4-5), FITC anti-CD11b (clone M1/70), PE anti-F4/80 (clone BM8), PerCP-Cy5.5 anti-CD45 (clone 30-F11), and anti-CD16/CD32 (clone 93). Briefly, 1 × 106 cells, resuspended in FACS labelling buffer (PBS with 2 mM EDTA and 1% foetal calf serum), were pre-incubated for 20 min with anti-CD16/CD32 to avoid non-specific binding, then washed and labelled with the appropriate mixture of antibodies for 30 min, centrifuged, and resuspended in FACS labelling buffer. Flow cytometry analysis was performed using a FACSCalibur flow cytometer (BD Biosciences, Milan, Italy). To exclude dead/dying cells that could non-specifically bind antibodies, leukocytes were gated according to forward and side scatter. The percentage of T helper and cytotoxic cells was calculated on lymphocyte gate (CD3+), whereas the CD11b+ and F4/80+ cell subsets were calculated on the leukocyte gate (CD45+). Treg cell (CD4+CD25+Foxp3+) analysis was performed with a specific kit (eBioscience, San Diego, CA) staining CD4 (FITC), CD25 (PE) and transcription factor Foxp3 (PE-Cy5), according to the manufacturer’s instructions. The percentage of CD25+Foxp3+ cells was calculated on lymphocyte CD4+ gate. For all analyses, at least 10.000 events were acquired and analysed using the CellQuest software (BD Biosciences, Milan, Italy).
Cytokine and chemokine secretion in WAT explants
WAT explant cultures were established essentially as described by . Briefly, epididymal WAT was dissected, weighed, minced, and placed into 12-well tissue culture plates (Corning, Milan, Italy) at 120 mg/well, with either 1 ml T cell activation medium (complete DMEM containing 3.7 g/l NaHCO3, 10% heat-inactivated foetal calf serum, 4 mM glutamine, 1% non-essential amino acids, 105 U/l penicillin and 100 mg/l streptomycin, 5 ng/ml phorbol 12-myristate 13-acetate (PMA), and 1 ng/ml ionomycin) or control medium (complete DMEM without ionomycin and PMA). All reagents were from Euroclone (Milan, Italy), except for ionomycin and PMA, which were from Sigma (Milan, Italy). Conditioned media were collected after 24 h of culture at 37 °C in an atmosphere of 5% CO2/95% air at 90% relative humidity and stored at − 80 °C until further analysis. The levels of cytokines and chemokines were analysed using Bio-plex/Luminex technology (mouse magnetic Luminex screening assay, Labospace, Milan) or ELISA assays (Affymetrix, eBioscience, San Diego, CA). The following cytokines and chemokines were simultaneously detected by Luminex technology in 50 μl undiluted samples: interferon gamma-induced protein (IP)-10, granulocyte macrophage-colony stimulating factor (GM-CSF), Regulated on Activation-Normal T cell Expressed and Secreted (RANTES), interleukin (IL)-23, IL-4, and IL-10. The following cytokines were analysed by ELISA (100 μl samples): tumour necrosis factor (TNF)-α, interferon (IFN)-γ, IL-17A, and IL-6. For these latter two cytokines, samples were diluted 1:500, as the readings by Luminex assays for IL-17A and IL-6 were out of range.
DNA extraction from faecal samples
Total DNA was extracted from 80 mg faecal samples with QIAamp DNA Stool Mini Kit (Qiagen, Hilden, Germany) according to manufacturer’s instructions. Qiagen DNA extraction method used in this work was chosen as it was listed among the most reproducible kits, ensuring minimal influence on next-generation sequencing (NGS) data analysis .
NGS was performed on faecal DNA samples from four animals for each of the three experimental groups, at the three time points indicated in Fig. 1, namely t0, t15, and t105 (total number of samples = 36). Partial 16S rRNA gene sequences were amplified using primer pair Probio_Uni and /Probio_Rev, which targets the V3 region of the gene and sequenced at the DNA sequencing facility of GenProbio srl (www.genprobio.com) using a MiSeq (Illumina). Primers and protocols, including amplicon checks, were as described in . Individual sequence reads were filtered with the Illumina software to remove low quality and polyclonal sequences. All Illumina quality-approved, trimmed, and filtered data were exported as .fastq files and processed using a custom script based on the QIIME software suite . Quality control retained sequences 140–400 bp long, with mean sequence quality score > 20, and truncation at first base if a low quality rolling 10-bp window was found. Presence of homopolymers > 7 bp and sequences with mismatched primers were omitted. To calculate downstream diversity (alpha and beta diversity indices, UniFrac analysis), 16S rRNA operational taxonomic units (OTUs) were defined at ≥ 97% sequence homology using uclust . All reads were classified to the lowest possible taxonomic rank using QIIME and a reference dataset from the SILVA database . Similarities between samples were calculated by unweighted UniFrac . The range of similarities is calculated between the values 0 and 1. Principal Coordinate Analysis (PCoA) was applied using the UniFrac program.
Statistical univariate analysis
Values in graphs and tables represent means ± SD. Prior to analysis, normal distribution and homogeneity of variance of all variables were assumed with Shapiro-Wilk’s and Levene’s tests, respectively. Statistical significance was evaluated by one-way ANOVA or by ANCOVA, followed by post hoc Tukey honestly significant difference (HSD) test. Differences with P values < 0.05 were considered significant. Statistical univariate analysis was performed with the “Statistica” software package (version 5.0; Stat Soft Inc., Tulsa, OK).
Statistical multivariate analysis
Non-supervised principal component analysis (PCA) of WAT immunological profiles (leukocyte subpopulations and cytokine/chemokine secretion) was performed with Past software, version 2.17c . Data were collected in a matrix of 27 rows (number of animals) and 15 columns (number of variables) and were auto-scaled by mean-centring and normalised by standard deviation. Pearson’s correlation coefficients between variables and principal components, as well as statistical significance of the correlation, were also calculated.
Bacterial supplementation affects epididymal WAT weight and metabolic parameters
Body weight, epididymal WAT weight, and food and energy intake from HFD of MBC, LGG, or CTRL mice
Body weight (g)
19.19 ± 1.44
19.41 ± 1.79
18.80 ± 0.89
31.75 ± 1.97
31.88 ± 2.13
30.63 ± 3.35
11.61 ± 1.94
12.47 ± 2.55
12.36 ± 2.63
WAT weight (g)
1.35*# ± 0.31
1.78 ± 0.30
1.89 ± 0.49
Food intake (g/day)
2.40 ± 0.66
2.54 ± 0.62
2.48 ± 0.63
Energy intake from HFD (Kcal/day)
10.80 ± 0.60
11.39 ± 0.69
11.26 ± 1.05
Serum metabolic measurements in MBC, LGG, or CTRL mice
107.42 ± 47.74
72.97 ± 7.64
86.91 ± 11.43
147.12* ± 65.91
163.21# ± 69.23
316.98 ± 142.39
HDL cholesterol (mg/dl)
155.91** ± 16.13
137.29* ± 25.21
108.86 ± 12.91
LDL cholesterol (mg/dl)
92.75# ± 19.06
105.77 ± 48.03
132.83 ± 15.09
16.25 ± 3.39
17.46 ± 4.87
19.23 ± 5.53
WAT immunological profiles highlight the anti-inflammatory effect of MBC microbiota supplementation
PCA loadings relative to the first two principal components from WAT immunological profiles of MBC, LGG, and CTRL mice
Impact of bacterial supplementation on gut microbiota profiles
In this work, we investigated the effects of a complex foodborne bacterial community (MBC microbiota) on obesity-associated inflammation and gut microbiota composition in a HFD-induced obese mouse model. The cultivable LAB component of MBC microbiota, selected by growth in MRS medium, was extracted from a fermented unripened cheese especially rich in live titres of LAB species  dominated by L. fermentum, L. delbrueckii, and Leuc. lactis  whose strains have often been associated with probiotic features . The rationale for supplementing mice with the microbial consortium was based on the highly biodiverse nature of foodborne strains in fermented dairies, including several LAB strains of environmental origin with beneficial, although yet uncharacterised, features . Their combined metabolic functions and metabolites have been suggested to exert positive effects on host physiology through synergistic mechanisms, more efficiently than single strain supplementation . However, the probiotic capacity of mixed foodborne microbial consortia has been gaining consideration only recently [44, 45, 46]. Moreover, most published work report supplementation with single bacterial strains, and only few studies compared multi-strain probiotic mixtures to investigate possible synergistic interactions . We chose to run a parallel group of mice for comparison, supplemented with the single probiotic strain GG of Lactobacillus rhamnosus that was shown to exert positive effects on obesity-related inflammation in mice and humans .
The obese phenotype was induced in C57BL/6J mice by feeding a 45% HFD for 3 months, resulting in weight gain in all experimental groups irrespective of bacterial supplementation type. Many other studies report decreased body weight gain following probiotic supplementation [31, 48]. Although we detected constant weight gain in all mice groups, decreased epididymal WAT weight was evident following oral administration of MBC microbiota as compared to the other mice groups, as well as a more pronounced anti-inflammatory effect than LGG supplementation. Decreased inflammation and amelioration of obesity-related metabolic and immunological dysfunctions were previously observed with bacterial supplementation of HFD-fed mice [49, 50], but they were not accompanied by WAT weight reduction. WAT is considered the main contributor to development of the obesity-associated low-grade chronic systemic inflammatory state, which is characterised by an imbalanced cytokine network with increased production of several pro-inflammatory mediators. Epididymal WAT, like other intra-abdominal WAT depots, is now recognised to have a more negative impact on health than subcutaneous WAT , and its decreased weight following MBC supplementation further highlights a higher efficacy of this complex microbial community in supporting healthy metabolism. The specific anti-inflammatory effects observed in our study involved decreased levels of the pro-inflammatory cytokines IL-6 and IFN-γ and of the chemokines IP-10 and RANTES in cultured WAT explants of LGG-supplemented mice, while MBC-treated animals displayed stronger decrease in the expression of a broader panel of pro-inflammatory cytokines and chemokines, namely IL-6, TNF-α, IL-17A, IFN-γ, IP-10, GM-CSF, and RANTES. Other studies using single probiotic strains or multi-strain mixtures observed decreased expression of some of these markers [48, 50, 52]. IL-6 and TNF-α are the main cytokines produced by pro-inflammatory macrophages in obese adipose tissue, whereas RANTES and IP-10 are important lymphocyte and macrophage chemo-attractants . IFN-γ is secreted by infiltrating CD8+ T cells, thus contributing to the critical events driving adipose tissue inflammation . Regarding IL-17, it was suggested that obesity predisposes to selective expansion of the Th17 subclass of T lymphocytes, producing high levels of IL-17 in an IL-6-dependent process . The cytokine GM-CSF, although not frequently measured in studies addressing probiotic-dependent immunomodulation in obesity, was reported to increase in the serum of obese mice .
The positive effects exerted by MBC supplementation on the overall profile of WAT inflammatory cytokines and chemokines were also associated to improved balance between the major sub-populations of immune cells, as revealed by reduced percentage of pro-inflammatory CD8+ T lymphocytes, activated leukocytes and macrophages, and increased CD4+ T lymphocytes and CD25+Foxp3+ Treg cells. Similar findings were reported in other tissues following Bifidobacterium pseudocatenulatum supplementation , in the adipose tissue after Lactobacillus gasseri supplementation , or using a probiotic mixture of L. rhamnosus and Bifidobacterium animalis subsp. lactis . Treg cells are highly represented in the WAT of lean mice, and they are essential for the maintenance of an anti-inflammatory environment in the absence of obesity. Treg cell number has been shown to decrease in the WAT of obese mice, contributing to worsen the inflammatory state [10, 11]. The increased Treg cell number that we observe after MBC supplementation is a result of particular relevance, considering that selective modulation of this population was shown to be tightly related to the level of obesity-associated inflammation .
The anti-inflammatory effects occurring with MBC supplementation were even more evident following PCA analysis of the datasets, which clearly discriminated MBC samples from LGG and CTRL samples along the first principal component axis. This confirms the key role of the immune cell subpopulations, as well as of the cytokines GM-CSF, IL-6, and TNF-α, as the most important variables contributing to the discrimination. Separation of the LGG and CTRL samples into two distinct clusters was highlighted only as a trend. These effects were accompanied by positive changes in the expression of lipid metabolism biomarkers in the MBC-supplemented group, with decreased circulating levels of triglycerides, increased HDL-cholesterol levels, and a trend toward decreasing LDL cholesterol. Higher levels of circulating HDL cholesterol were also observed in the LGG mice group, in line with previous reports on supplementation with single probiotics or mixtures [31, 48, 50].
Interaction with the host metagenome is considered an important aspect in probiotic-mediated immune stimulation [22, 57]. We analysed faecal microbiota biodiversity in treated mice by NGS of 16S rDNA. Our results confirmed that gut microbiota composition was indeed affected by HFD, leading to the establishment of an increased Firmicutes/Bacteroidetes ratio typical of the obesity pattern . Bacterial supplementation was not able to overcome HFD-induced effects on gut microbial profile, as no substantial modifications in faecal microbiota composition could be observed over time by NGS. The overriding effect of HFD on microbial biodiversity was also confirmed by advanced multivariate statistical analysis, namely Principal Coordinates Analysis (PCoA), revealing no specific clustering of bacterial species according to supplementation type, while highlighting a clear variation of microbial composition at the end of the experimental period in all mice groups. Other studies reported different extent of alterations in resident gut microbiota profile following probiotic treatment of HFD-fed mice [48, 50, 59, 60], but the studies are not always comparable due to different experimental designs (duration of treatment, percent dietary fat, etc.) and experimental approaches employed for microbial profiling (i.e. NGS, qPCR). In our study, the high sensitivity of NGS allowed to detect two of the three predominant species characterising the MBC-derived microbiota, namely L. delbrueckii and Leuc. lactis, although with low relative abundance in the faecal microbiome of supplemented mice. These two species may thus be able to colonise the gut of supplemented mice more efficiently. Gut colonisation capacity of some components of MBC-derived microbiota was also shown in the simple model organism Caenorhabditis elegans . On the other hand, the L. rhamnosus species that includes the LGG strain was undetectable in faecal microbiomes of LGG-treated mice. Conflicting results concerning LGG colonisation capacity have been reported in the literature. Park et al. recently observed decreased Lactobacillus relative abundances in the murine gut, including the LGG strain, following LAB supplementation , while in another report of orally administered LGG to knockout (ApoE−/−) mice fed HFD, L. rhamnosus could be recovered by faecal dilution and plating . Nevertheless, several reports indicate that oral administration of specific bacteria can exert beneficial effects on the host even in the absence of colonisation [59, 62, 63, 64].
Taken together, our results suggest that supplementation with a biodiverse foodborne bacterial consortium can exert beneficial effects on obesity-associated inflammation and health-related parameters more effectively than single probiotic strain supplementation. A recent report by Sonnenburg et al. clearly shows that dietary perturbations can lead to permanent loss of specific gut bacterial taxa, due to negative selection of metabolic activities that become unnecessary under imbalanced dietary regimens . These results point at limitations in microbiota resilience occurring under extreme conditions, such as HFD-induced obesity, where the alterations cannot be reversed by simple dietary intervention if not accompanied by specific bacterial supplementation aimed at restoring the lost taxa. Foodborne bacteria could play a key role in this respect, and to the best of our knowledge, this is among the very few reports evaluating the impact of a complex microbial consortium naturally occurring in a traditional fermented food on host physiology.
Our results demonstrate a stronger effect of a mixed microbial consortium vs single-strain probiotic supplementation in ameliorating HFD-induced inflammation in the WAT of obese mice. The present study highlights the importance of considering complex foodborne microbial consortia naturally occurring in fermented products for human consumption as potential probiotic vectors. It also points at the importance of coupling multivariate to univariate statistical analysis for better understanding of the key factors responsible for probiotic effects. The observed immunomodulatory activity exerted by the MBC-derived microbiota suggests synergistic interactions of microbial strains of environmental origin, present within the foodborne consortium. More studies are needed to further investigate the role of dietary microbes with yet uncharacterised probiotic effect, aimed also at identifying novel, under-represented strains which could be unique to the foodborne microbiota.
The Authors wish to thank Kariklia Pascucci for her kind support in daily lab work, Dr. Andrea Ciolfi for his valuable assistance in managing the NGS data, and Dr. Fausta Natella and Dr. Gianni Pastore for their helpful suggestions on the statistical analysis.
This work was funded in part by the Italian Ministry of Agriculture, Food & Forestry Policies (MiPAAF), with grant “MEDITO” (DM 12487/7303/11) and with national support to the JPI-HDHL “ENPADASI” project.
Availability of data and materials
Raw NGS data are available at the EMBL-EBI European Nucleotide Archive (ENA) , under the study accession number PRJEB20801.
MR, GP, and CD conceived and designed the experiments. MR, PZ, BG, AF, and CD performed the experiments. MR and CD analysed the data and supervised all data analyses. GP contributed reagents/materials/analysis tools. MR, GP, and CD wrote the paper. RR did the animal experiments/treatments. MR and AF performed the immunological analysis. PZ, BG, and CD performed the microbiological analysis. CD analysed the microbiota sequencing data. All authors read and approved the final manuscript.
All experimental procedures involving animals complied with the European Guidelines for the Care and Use of Animals for Research Purposes (Directive 2010/63/EU), and protocols were approved by the Ethical Committee of the Food and Nutrition Research Center and by the National Health Ministry, General Direction of Animal Health and Veterinary Drugs (agreement no 201/2015-PR).
Consent for publication
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
- 1.World Health Organization. Obesity and overweight fact sheet N 311-updated March 2011 2011, http://www.who.int/mediacentre/factsheets/fs311/en/index.html.
- 2.Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, Mullany EC, Biryukov S, Abbafati C, Abera SF, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384:766–81.CrossRefPubMedPubMedCentralGoogle Scholar
- 7.Khan M, Joseph F. Adipose tissue and adipokines: the association with and application of adipokines in obesity. Scientifica (Cairo). 2014;2014:328592.Google Scholar
- 22.Sanchez B, Delgado S, Blanco-Miguez A, Lourenco A, Gueimonde M, Margolles A. Probiotics, gut microbiota, and their influence on host health and disease. Mol Nutr Food Res. 2017;61Google Scholar
- 33.Orr JS, Kennedy AJ, Hasty AH. Isolation of adipose tissue immune cells. J Vis Exp. 2013:e50707.Google Scholar
- 41.Hammer Ø, Harper DAT, Ryan PD. PAST: paleontological statistics software package for education and data analysis. Palaeontol Electron. 2001;4:9pp.Google Scholar
- 44.Rosa DD, Dias MM, Grzeskowiak LM, Reis SA, Conceicao LL, Peluzio MD. Milk kefir: nutritional, microbiological and health benefits. Nutr Res Rev. 2017:1–15.Google Scholar
- 45.Kim DH, Kim H, Jeong D, Kang IB, Chon JW, Kim HS, Song KY, Seo KH. Kefir alleviates obesity and hepatic steatosis in high-fat diet-fed mice by modulation of gut microbiota and mycobiota: targeted and untargeted community analysis with correlation of biomarkers. J Nutr Biochem. 2017;44:35–43.CrossRefPubMedGoogle Scholar
- 48.Alard J, Lehrter V, Rhimi M, Mangin I, Peucelle V, Abraham AL, Mariadassou M, Maguin E, Waligora-Dupriet AJ, Pot B, et al. Beneficial metabolic effects of selected probiotics on diet-induced obesity and insulin resistance in mice are associated with improvement of dysbiotic gut microbiota. Environ Microbiol. 2016;18:1484–97.CrossRefPubMedGoogle Scholar
- 61.Chan YK, Brar MS, Kirjavainen PV, Chen Y, Peng J, Li D, Leung FC, El-Nezami H. High fat diet induced atherosclerosis is accompanied with low colonic bacterial diversity and altered abundances that correlates with plaque size, plasma A-FABP and cholesterol: a pilot study of high fat diet and its intervention with Lactobacillus rhamnosus GG (LGG) or telmisartan in ApoE−/− mice. BMC Microbiol. 2016;16:264.CrossRefPubMedPubMedCentralGoogle Scholar
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.