Microbiota and Related Metabolome in Omnivore, Vegetarian or Vegan Diets

Microorganisms in Foods and in Humans: Study of the Microbiota and the Related Metabolome as Affected by Omnivore, Vegetarian or Vegan Diets

The human body houses a huge microbial ecosystem, including the intestinal and oral microbiota. Both these ecosystems, and, in particular, the intestinal one, are responsible for maintaining human health. The response of the organism to the diet and the relative alteration of the susceptibility to disease are worth of investigation to comprehend the role of the microbiota to maintain the state of well being in humans. This concept, which is the overall scientific basis of the entire project, perfectly fits with the declared scopes of Horizon 2020. Understanding the impact of omnivore, vegetarian and vegan diets on human intestinal microbiota is aligned to the Grand Societal Challenge of the Horizon 2020 scheme, which is addressing the human nutritional needs and the impact of food on human physiological functions. In particular, studying the link between dietary habits and the intestinal microbiota activity will be pivotal to improve the food-based promotion of health and well being. The project aims at studying how the omnivore, vegetarian and vegan diets may affect the oral intake of microorganims, and the composition of the oral and fecal microbiota. With the aim to build up a permanent European platform for such type of studies, ten Research Units (RUs) are involved in the proposal, with the partnership of 16 National and, especially, foreign Institutions, covering 12 different countries. About 50 omnivore, vegetarian and vegan volunteers, for a total of 150 subjects will be recruited. Volunteers will be asked to fill in diaries, describing their dietary habits, and to collect biological samples (saliva, feces and urine), once a week for three weeks. For obvious ethical constraints, biopsies will be not available in this study. RUs will share their tasks, mainly depending on the nature of the samples to be studied, namely foods and biological samples. Based on the different dietary habits, the presumptive intake of microorganims will be estimated using literature data and, especially, culture-dependent methods. Typing and antibiotic resistance of some food related microbial communities or foods will be also investigated. The microbial diversity of foods, whose microbiota has never been studied in depth, will be characterized by PCR-DGGE and deep sequencing. The metabolome characterization will complete the overview on foods. After collecting and preparing biological samples from the three diet groups, the oral and fecal microbiota will be studied. The viable cell number of several microbial groups will be estimated in fecal samples, before freezing. Preliminarily, the microbial diversity of saliva and fecal ecosystems will be analyzed through PCR-DGGE. PCR assessment of genetic basis of antibiotic resistance will be also carried out. Selected numbers of biological samples will be further subjected to next generation sequencing, aiming at determining representative individuals/samples of the three types of diet. Only for feces, representative samples (e.g., 4/5 for each diet) will be subjected to meta-omics analyses based on meta-genomic, meta-transcriptomic and meta-proteomic approaches. An integrated and iterative workflow will be also developed, by assembling an in house synthetic meta-genome. The functionality of fecal samples and/or of isolates from feces will be characterized based on fecal genotoxic and anti-genotoxic activities, and modulation of the immune response. In agreement with an holistic approach, the metabolome analysis of saliva, feces and urine will complete the characterization of biological samples. All data available from the different RUs will merge into a common database, whose structure will be developed during the project. Based on the literature data (ISI Web of Knowledge), this is the first study that aims at correlating the effect of the main dietary habits on the oral and fecal microbiota through integrated meta-omics analyses.

The overall objective of this project is to find the relationship between diet and saliva and fecal microbiota, through high-throughput and integrated meta-omics (genomic, transcriptomic, proteomic and metabolomic) analyses. Several questions are still debated within this context. For instance, what is the daily intake of microbes and their role on the balance of the intestinal microbiota? How is the intestinal microbiota affected by the main types of diet (omnivore, vegetarian and vegan)? Which are the prevailing microbial groups at intestinal level, depending on the type of diet? What is the presumptive contribution of each microbial group in maintaining the host health? The quantitative and qualitative determination of the main microbial groups harboured in foods, depending on dietary habits, responds to an earlier question and coincides with one of the objectives of this project. The estimation of the diversity (genomics), functional activity (transcriptomics and proteomics) and metabolites (metabolomics) of, especially, the fecal microbiota coincide with the holistic approach of this project and responds to several of the earlier questions. Considering the close correlation between the balance of different microbial populations in various niches of the human body and the onset of metabolic pathologies, this project shall furnish novel knowledge that may highlight possible relationships between diet and dismetabolisms. Diet has to be considered as the most appropriate and inexpensive tool to determine a stable and favourable oral and intestinal microbiota, which prevents diseases and guarantees human longevity. These overall objectives of the project shall be reached on the basis of specific targets, such as: (i) the identification of biological, molecular and metabolic markers specific to the type of diet; (ii) the estimation of the differences in the microbiota and metabolome of saliva and feces, both among individuals and between types of diet; (iii) the estimation of the qualitative and quantitative differences on the microbial intake connected to the type of diet; and (iv) the identification of the functional features of fecal samples related to the type of diet, which can be regarded as indicators of disease susceptibility.

With the aim to reach the overall objective of this project, ten Research Units (RUs; RU1-10) are involved in the proposal, with the partnership of 16 National and, especially, foreign Institutions, covering 12 different countries. The leaders of each RU are reported below:

• RU1. Marco Gobbetti is the Principal Investigator of the proposal and leader of RU1. As reported by ISI Web of Science, he is author of 188 publications which were cited 4,075 times, with an average of citations per publication of 21.68 and an h index of 39. He has been recently listed in the Top Italian Scientists by VIA Academy (yearly evaluation for scientists having a value of h-index higher than 30). The RU1 has gained a good experience on the study of the intestinal microbiota of celiacs, and on the proteomics applied to lactic acid bacteria and foods. RU1 will play the role of the coordinator of the project. Within this project, RU1 is involved in: recruitment of volunteers; administration of diaries; handling and preparation of biological samples; determination of the main microbial groups in the fecal samples by culture-dependent methods; meta-proteomics characterization of selected fecal samples from individuals having different dietary habits; and statistical elaboration of the results. Within this project, the RU1 will collaborate with the Instituto de Investigacìon en Ciencias de la Alimentacìon, CIAL (CSIC - UAM), Madrid, Spain, for the specific attribution of functional activities and/or metabolic pathways to identified proteins and with the Department of Microbiology of the University College Cork, Ireland, for the bioinformatic approach to proteome studies.
• RU2. Gianluigi Cardinali is the leader of RU2. As reported by ISI Web of Science, he is author of 38 publications with an h index of 11. The RU2 operates since approximately twenty years in the field of biodiversity and taxonomy of yeasts, which are analysed through microbiological and molecular techniques. Within this project, RU2 is involved in: characterization of the diversity of the food micobiota through PCR-DGGE approach; characterization of the micobiota of fecal samples through PCR-DGGE approach; and, as leader, in the management of the statistical elaboration of the results from all the RUs, providing a common database. The RU2 will collaborate with the Centraalbureau voor Schimmelcultures (CBS), Utrecht, The Netherlands, for the bioinformatic elaboration of the data.
• RU3. Danilo Ercolini is the leader of RU3. As reported by ISI Web of Science, he is author of 58 publications, with a total number of citations of 1,354 and an h index of 21. The RU3 has been involved for years now in studies of microbial ecology of complex ecosystems, mainly food ecosystems. The food microbiota has been always studied by advanced molecular approaches and by culture-independent methods that do not require culturing of microorganisms on synthetic media. Within this project, RU3 is involved in: characterization of the diversity of the microbiota in saliva samples; deep sequencing of selected food samples; deep sequencing of selected fecal and saliva samples; meta-genomics characterization of selected fecal samples from individuals having different dietary habits; and statistical elaboration of the results. Within this project, the RU3 will collaborate with the Earth Microbiome Project (EMP, www.earthmicrobiome.org) that is run in the Argonne National Laboratory, Lemont, United States, to create data sets describing microorganisms from a broad range of ecosystems.
• RU4. Erasmo Neviani is the leader of RU4. As reported by ISI Web of Science, he is author of 111 publications, with a total number of citations of 1,508 and an h index of 22. The RU4 has gained good experience in food microbial ecology for a comprehensive and integrated evaluation of the microbial populations, dynamics and physiological status of cells at various stages of food manufacture. Within this project, RU4 is involved in: preparation of diaries; recruitment of volunteers; administration of diaries; handling and preparation of biological samples; determination of the main microbial groups in the fecal samples through culture-dependent methods; elaboration of the results from diaries; determination of the main microbial groups in foods through culture-dependent and -independent methods; and statistical elaboration of the results. Within this project, the RU4 will collaborate with the Department of Food Science and Technology of the Agricultural University of Athens, Greece, for the microbial determination in foods and, especially, in dairy products, with the Epidemiology Unit of the Fondazione IRCCS Istituto Nazionale dei Tumori of Milan, Italy, for the assistance on the dietary habit recording, and with the National Institute for Food and Nutrition Research of Rome, Italy, for monitoring the putative deficiencies related to restrictive dietary regimes.
• RU5. Aldo Corsetti is the leader of RU5. As reported by ISI Web of Science, he is author of 81 publications with a total number of citations of 2,084 and an h index of 28. RU5 has gained good experience in the field of microbial ecology of food and beverages as well as in that of strains characterization for biotechnological and functional aspects, in order to select starter cultures for different applications. Within this project, RU5 is involved in: determination of the main microbial groups in foods through culture-dependent methods; identification and typing of microbial isolated from foods; characterization of the genotoxicity of fecal samples; characterization of the anti-genotoxigenic activity of microbial isolates from foods; and statistical elaboration of the results. Within this project, the RU5 will collaborate with the Department of Agricultural, Food and Nutritional Science, University of Alberta, Canada, for molecular typing of food-isolated microorganisms by a multi-locus type sequencing.
• RU6. Patrizia Brigidi is the leader of RU6. As reported by ISI Web of Science, she is author of 102 publications that were cited 3,158 times, with an average of citations per publication of 32.41 and an h index of 26. RU6 has a consolidated and wide competence in the field of identification and molecular quantification of bacteria from complex ecosystems (feces and intestinal biopsies) and in the field of molecular mechanisms responsible for health benefits of bacteria. Within this project, RU6 is involved in: recruitment of volunteers; administration of diaries; handling and preparation of biological samples; determination of the main microbial groups in the fecal samples through culture-dependent methods; meta-transcriptomics characterization of selected fecal samples from individuals having different dietary habits; and statistical elaboration of the results. Within this project, the RU6 will collaborate with the Food Microbial Science Unit, University of Reading, United Kingdom, for the development of the metatranscriptomic platform and in the bioinformatic analysis of the obtained sequences for their assignment to KEGG and COG cluster of functional activities.
• RU7. Francesca Clementi is the leader of RU7. As reported by ISI Web of Science, she is author of 59 publications that were cited 504 times, with an average of citations per publication of 11.25 and an h index of 15. The RU7 has a trustworthy expertise concerning the role, monitoring and control of foodborne microorganisms, especially lactic acid bacteria. Within this project, RU7 is involved in: characterization of the diversity of the food microbiota by PCR-DGGE; determination of the antibiotic resistance in fecal and saliva samples; isolation and identification of antibiotic resistant lactic acid bacteria from fecal and saliva samples; characterization of the genes involved in the microbial antibiotic resistance; study of the mechanisms for transferring antibiotic resistance between bacteria; and statistical elaboration of the results. Within this project, the RU7 will collaborate with the Greek Democritus University of Thrace, Greece, and with the Rowett Institute for Nutrition and Health of the University of Aberdeen, Scotland, on the investigation of transferable antibiotic resistance genes in foods and lactic acid bacteria isolated from saliva and fecal samples.
• RU8. Luca Simone Cocolin is the leader of RU8. As reported by Scopus, he is author 131 publications that were cited 2,036 times, resulting in an h index of 25. The RU 8 has an extensive experience in the application of culture-independent methods for the study of microbial biodiversity and vitality in fermented foods. It has also knowledge of quantitative PCR (qPCR) for the quantification of specific microorganisms from complex ecosystems. Within this project, RU8 is involved in: recruitment of volunteers; administration of diaries; handling and preparation of biological samples; determination of the main microbial groups in the fecal samples through culture-dependent methods; profiling of the fecal microbiota by DGGE approaches applied both at DNA and RNA level; meta-genomic characterization of selected fecal samples from individuals having different dietary habits; and statistical elaboration of the results. Within this project, RU8 will collaborate with the University of Maribor (UM), Slovenia, and the Democritus University of Thrace (DUT), Alexandroupolis, Greece, for aspects, dealing with the interaction of pathogens-host cells and for possible modifications of the diet of the different diet groups, that may best exploit the known beneficial role of certain microbial groups associated with specific foods, respectively.
• RU9. Mauro Rossi is the leader of RU9. As reported by ISI Web of Science, he is author of 41 publications, with a total number of citations of 1087 and an h index of 19. The RU9 has a long-standing experience (>25 years) and strong collaborations in the field of the biochemistry and immunology of the small intestine. Within this project, RU9 is involved in: isolation of lactobacilli and bifidobacteria from fecal samples; characterization of the in vitro immune response of fecal isolates using Caco-2 cell; characterization of the in vitro immune response of fecal isolates using dendritic cells; measurement of cytokine secretion in Caco-2 and dendritic cells; and statistical elaboration of the results. Within this project, RU9 will collaborate with the Ecofisiología Microbiana y Nutriciòn, Instituto de Agroquímica y Tecnología de Alimentos (CSIC), Valencia, Spain (attachment in Model B), to establish whether peculiarities in fecal microbiota could play a role in the onset of intestinal immune dysfunctions.
• RU10. Lucia Vannini is the leader of RU10. As reported by ISI Web of Science, she is the author of 27 publications with a total number of citations of 322 and an h index of 9. The RU10 has gained a good experience both in the food microbiology area and in the use of instrumental techniques, and particularly nuclear magnetic resonance, for metabolome analysis of biological samples. Within this project, RU10 is involved in: metabolome characterization of selected foods; metabolome characterization of saliva samples; metabolome characterization of fecal and urine samples, and statistical elaboration of the results. Within this project, R10 will collaborate with the Swedish Institute for Food and Biotechnology, Sweden, and the Institute of Chemical Technology, Department of Research and Development, Prague, Czech Republic, for aspects, respectively, concerning the metabolomic characterization of some selected foods and biological samples. The cascade approach used will make each research activity and each RU indispensable to achieve the main objectives of the project.

This study will composed by different activity (AI-VI) described below:

• ACTIVITY I. Recruitment of individuals, administration of diaries, handling, preparation and storage of biological samples, and microbiological analyses of fecal samples.
• AI.1. Recruitment of individuals and administration of diaries (RU1, 4, 6, 8) About 50 omnivore, vegetarian and vegan volunteers, for a total of 150 subjects will be recruited.Vegetarian and vegan individuals will be recruited with the cooperation of the Italian Scientific Society of Vegetarian Nutrition. Omnivore individuals will be recruited through advertisements published at the Universities. About 50 healthy volunteers will be recruited including an approximately equal number of omnivores, vegetarians and vegans (age 18-59 years, male/female ratio ca. 1:1). Recruited volunteers will be asked to sign a consensus document, to record their dietary habits. The diaries will be elaborate to get detailed information on food characteristics, allowing an easy identification of the products on the market and an estimation of the presumptive microbial load ingested. The Ethics Committee of the Universities will be informed before the project will start.
• AI.2. Handling, preparation and storage of biological samples (RU1, 4, 6, 8). Each individual will supply samples of saliva, feces and urine weekly, for a time span of three weeks. Triplicate samples will be pooled before analyses in order to limit the intra-individual variability. Handling will be carried out differently depending on the type of biological samples (saliva, feces, urine) and subsequent analyses (e.g., DNA, RNA, proteome). Simultaneously with the recruitment of individuals and collection of biological samples, most of the RUs will be involved in setting up the techniques/methods.
• AI.3. Microbiological analyses of fecal samples (RU1, 4, 6, 8). In the first time the viable counts will be performed by plating fresh fecal material on different selective culture media, to enumerate the most common fecal microbial groups.
• AI.4. Set up of techniques/methods (RU1, 2, 3, 5, 6, 7, 8, 9, 10). Simultaneously with the recruitment of individuals and collection of biological samples, most of the RUs will be involved in setting up the techniques/methods. In order to establish an independent and competitive platform for meta-omics analyses, RU3 will purchase equipment for high throughput sequencing, which is a main economic investment in this project.
• ACTIVITY II. Food microbiota and metabolome. Based on the information from dietary diaries, the most representative foods of the 3 diets will be split in 3 categories: (i) low (TBC, 10^3 cfu/g); (ii) intermediate (TBC 10^3 - 10^6 cfu/g); and (iii) high (TBC ³ 10^6 cfu/g) microbial load. For foods of group (i) the microbial number will be estimated based on literature data. For foods of groups (ii) and (iii) the microbial number will be determined based on literature data in the case of well known products with low market differentiation (e.g., Parmigiano Reggiano cheese), whereas appropriate analyses will be done in the case of products with large market variability (e.g., Mozzarella cheese). In the latter case, the analyses will involve a large number of products available in the market. The microbial diversity of foods will be studied more in depth first by PCR-DGGE (Polymerase Chain Reaction-Denaturing Gradient Gel electrophoresis) and when needed by deep sequencing on the basis of level of complexity and current knowledge of the microbiota of the specific foods.
• AII.1 Quantitative determination of microorganisms in foods (RU 4, 5; 7). The analysis of foods will be shared between RU4 and 5, and some samples will be analysed by both RU to reciprocally validate the results. Subsequently, RU4 will characterize selected foods by LH-PCR (Length Heterogeneity Polymerase Chain Reaction) analysis, and the results will be compared with those obtained by RU7 using PCR-DGGE. RU5 will identify a large collection of isolates from foods, aiming at finding possible relationships with a reduced anti-genotoxic activity of the fecal waters and presence of specific microorgansims in the ingested foods.
• AII.2 Microbial diversity in foods (RU 2, 3). First, this activity will consider poorly characterized foods that are specifically eaten by veregetarians and vegans based on records from diaries. Both micro- and mico-biota will be investigated. PCR-DGGE analyses for yeasts and filamentous fungi will be based on the amplification of parts of the D1/D2 domain encoding for the subunit LSU or 26S of the rRNA, and the ITS (Internal transcribed spacer) regions. The V3 region of the 16S rRNA gene will be targeted to detect bacteria. After DGGE analysis, the resulting gels will be digitalised and analysed by the software Bionumerics. Dendrograms will be subjected to cluster analysis to exclude from the further sequencing those samples having a coefficient of similarity 85%; such selection will save costs of the next generation sequencing, and will assure to get a manageable quantity of data to be analyzed via bio-informatics. RU3 will perform the deep sequencing using libraries of amplicons of variable genes of taxonomic interest and using specific procedures according to the type of sequencing platform that will be purchased. The sequencing results will be elaborated on a bioinformatic basis by the RU2.
• AII.3 Food metabolome (RU 10). Based on the information on dietary habits, the fermented foods most represented in the three diets, will be analysed to find a possible relationship between chemical compounds ingested (e.g., salycilic acid) and presumptively recovered in biological samples. The metabolome analyses will be carried out by GC-MS/SPME (Gas Chromatography-mass Spectrometry /solid-phase microextraction) and FTIR (Fourier Transform Infrared) spectroscopy.
• ACTIVITY III. The microbiota of feces and saliva. Preliminarily, all saliva and fecal samples from all the ca. 150 volunteers will be subjected to PCR-DGGE analyses to get an overview of the microbial diversity. RT-PCR-DGGE (Real Time- Polymerase Chain Reaction- Denaturing gradient gel electrophoresis) will be also considered to estimate viable populations in feces. Based on these analyses, representative samples of each dietary habit will be subjected to next generation sequencing. The output of all these results should allow, step by step, the selection of 4/5 fecal samples for each of the three diets to be subjected to meta-omics analyses.
• ACTIVITY III.1. Study of the biodiversity.
• AIII.1.1. PCR-DGGE Profiling (RU 2, 3, 8) PCR-DGGE analyses for yeasts and filamentous fungi will target 26S rRNA and ITS regions, while V3 and/or V6-V8 regions of the 16S rRNA will be studied for bacteria. Both DNA and RNA (after RT-PCR) will be used as target to investigate total and viable populations, respectively. Under the same experimental conditions, RU3 will characterize the bacterial diversity of saliva samples. After DGGE, image and cluster analyses from DNA and RNA samples it will be possible to define a difference between the global and viable population. The dendrograms of similarity will be used to exclude from the further sequencing activity those samples having a coefficient of similarity ³ 85%; such selection will save costs of the next generation sequencing analyses, and will assure to get a manageable quantity of data to be analyzed via bio-informatics.
• AIII.1.2. Next Generation Sequencing (RU 3, 8) Deep sequencing on selected saliva and fecal samples will be done using libraries of amplicons of variable genes of taxonomic interest. All sequencing results obtained both for bacteria and fungi will be elaborated on a bioinformatic basis by the RU2.
• AIII.1.3. Antibiotic resistance (RU 7) DNA extracted directly from saliva and fecals samples will be screened for the occurrence of genes encoding for resistances to several antibiotics using PCR assays. Samples, resulted to be positive for antibiotic resistance (AR) genes, will be used to isolate antibiotic-resistant lactobacilli, lactococci and enterococci. After identification, isolates showing values of minimum inhibitory concentration (MIC) higher than the corresponding breakpoints will be confirmed by PCR amplification of the corresponding AR genes. The possibility of transferring AR genes localized on genetic mobile elements from isolates to bacteria of clinical interest will be evaluated by conjugation trials.
• AIII.2. Meta-omics analyses of selected fecal samples According to the cascade approach, the results from the study of the microbial diversity of fecal samples will select 4/5 individuals representative of each of the 3 types of diet (4/5 x 3 = 12/15) to be subjected to meta-omics analyses. The meta-omics approaches will provide an in house database, consisting of the DNA and RNA sequences from the fecal microbiomes of the 12/15 individuals, which will allow a complete view of the synthesized proteins.
• AIII.2.1. Meta-genomics (RU3, 8) Fecal DNA will be quantified and a shotgun sequencing protocol will be applied for meta-genomic analysis. This task should be performed by the RU3, depending on performance and availability of the sequencing platform, which will be engaged full time in the analysis of DNA and cDNA amplicons of feces and saliva. Alternatively, specialized companies will carry out this task as a service.
• AIII.2.2. Meta-transcriptomics (RU 6) The overall microbial gene expression profile will be characterized using an innovative Illumina-based Metatranscriptomic approach and the protocol set up during first months of the project. cDNA will be sinthetised from RNA according to optimized procedures. Random amplification of the cDNA will be performed and the cDNA will be sequenced by using the Illumina HiSeq platform. The sequenced meta-transcriptomes will be assembled together using Velvet/MetaVelvet or SOAPdenovo packages to achieve the largest possible consensus sequence. The transcripts sequences will be annotated using well-established pipelines and transcripts will be searched using RPS-BLAST (Reversed Position Specific- Basic Local Alignment Search Tool) against KEGG (Kyoto Encyclopedia of Genes and Genomes), COG (Clusters of Orthologous Groups) and the Genbank databases. Bacteria-like reads identified by nr BLASTX will be further searched against the COG database. The functional roles of the sequences will be assigned based on the KEGG and COG searches.
• AIII.2.3. Meta-proteomics (RU1) Based on the workflow designed within the first months of activity, proteins will be extracted from each fecal sample and analysed by gel-free and/or gel-based proteomics. The identification of peptides will be performed using the mass spectrometer Finnigan LCQ Deca XP MAX. Differential proteomic analysis will be carried out. For peptide identification, the Open Mass Spectra Search Algorithm will be used to search MS/MS spectra against the available databases. To retrieve further functional information, the proteins based on COG classification will be annotated. The identified COGs will be mapped on KEGG metabolic pathways database and visualized by the online application of iPath. After FDR correction, all identified peptides will be searched against UniProtKB and then mapped. To address the highest functional level of all the identified proteins, the identified COGs onto KEGG pathways will be mapped. Besides the common microbial core, inter-individual and inter-diet differences will be determined in terms of metabolic function.
• ACTIVITY IV. Functional characterization. The characterization of some functional features of fecal samples and of microbial isolates from fecal samples will strengthen the link between diet and intestinal microbiota.
• AIV.1 Fecal genotoxic and anti-genotoxic activities (RU 5) Samples of fecal water (FW) will be prepared and the genotoxicity will be determined by Comet assay. The HT29 enterocytes (10^6 cells/assay) co-exposed to FW and incorporated into LMA slide will be subjected to Single-Cell Gel-Electrophoresis (SCGE) and analysed by epifluorescence. Several microbial isolates from foods will be investigated for the inhibitory activity towards genotoxic and mutagenic compounds, which are potentially present in the intestine. The effect of the microorganism-genotoxin co-incubation will be assayed through the evaluation of the residual genotoxic activity of the compounds using the SOS-Chromotest (target Escherichia coli PQ37 sfiA:lacZ) and, in parallel, the Comet assay (target enterocytes HT29).
• AIV.2. Fecal microorganisms and modulation of the immune response (RU 9) The conditions for growth and differentiation of dendritic cells (DC) and Caco-2 cells will be set up within the first months of activity. Lactobacilli and bifidobacteria will be isolated from all fecal samples and used as irradiated bacteria to detect the expression of immune mediators in enterocytes. Transcript and cognate protein secretion levels of IL-8 and tolerogenic TGF-beta (Transforming growth factor beta) and TSLP (Thymic Stromal Lymphopoietin) will be determined. Irradiated bacteria will be also used to stimulate surface markers in DC cells. Total RNA will be extracted from the Caco-2 and DC cells, and cDNA will be prepared to look at the relative gene expression of IL-8, TGF-beta, TSLP, TNF-alpha, IL-12p40 and IL-10; the concentration of the corresponding gene products will be determined by ELISA (Enzyme-Linked ImmunoSorbent Assay).
• ATTIVITY V. Saliva, fecal and urine metabolome (RU10). To complete the "omics" approach, the metabolome of samples of feces, urine and saliva will be analysed with three techniques (GC-MS/SPME, FTIR/ATR (Fourier Transform Infrared/Attenuated Total Reflectance) and NMR (Nuclear Magnetic Resonance) according to the protocols previously set up. Chemical compounds will be identified using mass spectra databases as well as mass spectra data in the literature and/or data from pure chemical compounds. Upon thawing of urine and saliva samples, the NMR analysis will be performed within 2 h. Fecal samples will be prepared giving the maximum importance to the complete recovery of water-soluble molecules. The NMR spectra will be prepared for statistical analysis by correcting the little peaks misalignments through iCoshift algorithm.
• ATTIVITY VI. Statistical elaboration of the results (all RUs). During project development, RU2 will take care of the maintenance of the website in collaboration with the partner CBS (Centraalbureau voor Schimmelcultures, Utrecht, NL), the site will collect all the results from the different research activities. This database will be used for analysis in "R mode" to assess the impact of various descriptors in determining the diversity of the three diets, and in "Q mode" to determine difference between the three diets. During the same time, the most relevant results will be disseminated through scientific publications into peer-reviewed journals.

Taking into account the topic to be studied, this project has undoubtedly applied potential aspects. For instance, the knowledge of the effect of diet on human microbiota could result in the preparation of appropriate guidelines to be distributed in campaigns of integrated care promotion. Consumer preferences, attitudes, needs, behaviour, lifestyle and education will be taken care of, and communication between consumers and the food chain research community will be enhanced in order to improve informed choice and its impact on quality of life. Empowering individuals to improve and manage their health through correct dietary habits will result in cost savings to healthcare systems.

Inclusion Criteria:

• Age (18 - 59 years).
• BMI (18.5-24.9 kg/m2).
• No usual intake of drugs and dietary supplements / pharmacological pre-and probiotics.
• No taking antibiotics in the last three months.
• Absence of intestinal (Crohn's disease, ulcerative colitis, bacterial contamination syndrome, constipation, celiac disease, irritable bowel disease) and metabolic (diabetes type 1 and type 2, cardiovascular and neurovascular diseases, cancer, neurodegenerative diseases, rheumatoid arthritis, allergies) diseases.
• No pregnancy and breast-feeding.

Exclusion Criteria:

• Inability to give the informed consent.