Because of the high number of RUs participating to this project, details on specific activities and description of collaborations with foreign partners are deferred to Models B. A planning of the tasks is 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; 1-6 months). Vegetarian and vegan individuals will be recruited with the cooperation of the Italian Scientific Society of Vegetarian Nutrition (http://www.scienzavegetariana.it/). Omnivore individuals will be recruited through advertisements published at the Universities. Exclusion criteria will be fixed by RU4. About 50 healthy volunteers will be recruited by each of the 4 RUs, including an approximately equal number of omnivores, vegetarians and vegans (age 30-50 years, male/female ratio ca. 1:1). Recruited volunteers will be asked to sign a consensus document, to record their dietary habits and to collect biological samples (saliva, feces and urine). RU4 will be responsible to draft the diaries, which shall permit to get detailed information on consolidated dietary habits and on food characteristics, allowing an easy identification of the products on the market and an estimation of the presumptive microbial load ingested. RU4 will elaborate the diaries at the end of period foreseen for the project. The Ethics Committee of the Universities will be informed before the project will start. Based on the possible withdrawal of individuals, the total number of volunteers recruited by the 4 RUs should be ca. 150 (50 omnivores + 50 vegetarians + 50 vegans). The statistical significance of 50 volunteers per each type of diet has been previously validated through Power Analysis.
AI.2. HANDLING, PREPARATION AND STORAGE OF BIOLOGICAL SAMPLES (RU1, 4, 6, 8; 1-6 months). 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). Details are shown in the Models B of RU1, 4, 6 and 8.
AI.3. MICROBIOLOGICAL ANALYSES OF FECAL SAMPLES (RU1, 4, 6, 8; 1-6 months). The viable counts will be performed by plating fresh fecal material on different selective culture media, to enumerate the most common fecal microbial groups (39, 40).
AI.4. SET UP OF TECHNIQUES/METHODS (RU1, 2, 3, 5, 6, 7, 8, 9, 10; 1-6 months or more). Simultaneously with the recruitment of individuals and collection of biological samples, most of the RUs will be involved in setting up the techniques/methods. These activities will vary depending on the specific tasks (see Models B). 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 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; 7-18 months). 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. The quantification of the microbial groups commonly occurring in foods will be completed within 18 months.
Subsequently, RU4 will characterize selected foods by LH-PCR analysis (41), 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 and 7; 7-30 months). 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 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 ³ 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; 7-9 months). 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 and FTIR 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 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; 7-24 months). 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; 10-30 months). Deep sequencing on selected saliva and fecal samples will be done using libraries of amplicons of variable genes of taxonomic interest as above described. Results for selection of fecal samples for -omics analyeses will be completed within 12-24 months, but deep sequencing will continue further to optimise the results from the screening. 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; 13-30 months). 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; 13-30 months). 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; 13-30 months). 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 against KEGG, COG 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; 13-30 months). 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 (42). 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; 7-30 months). Samples of fecal water (FW) will be prepared (43) and the genotoxicity will be determined by Comet assay (44). 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) (43).
AIV.2. FECAL MICROORGANISMS AND MODULATION OF THE IMMUNE RESPONSE (RU 9; 7-30 months). 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 and TSLP 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.
ATTIVITY V. SALIVA, FECAL AND URINE METABOLOME (RU10; 7-30 months)
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 and NMR) 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 (45).
ATTIVITY VI. STATISTICAL ELABORATION OF THE RESULTS (all RUs; 31-36 months)
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.Research activities.