Gastrointestinal Simulation Model TWIN-SHIME Shows Differences

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The Gastrointestinal Simulation Model TWIN-SHIME® Shows Differences Between Human Urolithin-Metabotypes in Gut Microbiota Composition, Pomegranate Polyphenol Metabolism, and Transport Along the Intestinal Tract Rocio Garcia-Villalba, Hanne Vissenaekens, Judit Pitart, Maria Romo-Vaquero, Juan Carlos Espín, Charlotte Grootaert, María V. Selma, Katleen Raes, Guy Smagghe, Sam Possemiers, John Van Camp, and Francisco A. Tomas-Barberan J. Agric. Food Chem., Just Accepted Manuscript • Publication Date (Web): 15 Jun 2017 Downloaded from http://pubs.acs.org on June 16, 2017

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Journal of Agricultural and Food Chemistry

The Gastrointestinal Simulation Model TWIN-SHIME® Shows Differences Between Human Urolithin-Metabotypes in Gut Microbiota Composition, Pomegranate Polyphenol Metabolism, and Transport Along the Intestinal Tract

Rocío García-Villalba,†* Hanne Vissenaekens, δde* Judit Pitart,‡ María Romo-Vaquero,† Juan C. Espín,† Charlotte Grootaert,δ María V. Selma,† Katleen Raes,d Guy Smagghe,e Sam Possemiers,‡ John Van Camp,δ Francisco A. Tomas-Barberan†# †

Research Group on Quality, Safety, and Bioactivity of Plant Foods, Laboratory of Food &

Health; Dep. Food Science and Technology, CEBAS-CSIC, 30100 Campus de Espinardo, Murcia, Spain. E-mail: [email protected]; Phone: +34-968396200. ‡

δ

ProDigest BVBA, Ghent, Belgium

Department of Food Safety and Food Quality, Faculty of Bioscience Engineering, Ghent

University, Ghent, Belgium d

Department of Industrial Biological Sciences, Faculty of Bioscience Engineering, Ghent

University, Kortrijk, Belgium e

Department of Crop Protection, Ghent University, Faculty of Bioscience Engineering, Ghent,

Belgium *Contributed equally #Corresponding author 1 2

Title running header: Urolithin metabotypes and gastrointestinal simulation.

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®

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ABSTRACT: A TWIN-SHIME

system was used to compare the metabolism of pomegranate

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polyphenols by the gut microbiota from two individuals with different urolithin metabotypes.

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Gut microbiota, ellagitannin metabolism, short-chain fatty acids (SCFA), transport of

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metabolites and phase II metabolism using Caco-2 cells were explored. The simulation

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reproduced the in vivo metabolic profiles for each metabotype. The study shows for the first

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time that microbial composition, metabolism of ellagitannins and SCFA differ between

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metabotypes and along the large intestine. The assay also showed that pomegranate phenolics

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preserved intestinal cell integrity. Pomegranate polyphenols enhanced urolithin and propionate

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production, as well as Akkermansia and Gordonibacter prevalence with the highest effect in the

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descending colon. The system provides an insight into the mechanisms of pomegranate

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polyphenol gut microbiota metabolism and absorption through intestinal cells. The results

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obtained by the combined SHIME®/Caco-2 cell system are consistent with previous human and

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animal studies and show that, although urolithin metabolites are present along the

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gastrointestinal tract due to enterohepatic circulation, they are predominantly produced in the

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distal colon region.

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KEYWORDS: ellagic acid, urolithin, phenotypes, gut microbiota, intestinal cells

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INTRODUCTION

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Dietary ellagitannins (ETs) and ellagic acid (EA) have been associated with important

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health effects and benefits in diseases including cardiovascular disease.1,2 They are

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present in dietary sources in larger amounts than previously estimated.3 In humans, ETs

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are not absorbed as such, and the absorption of EA is rather low.4 Both ETs and EA are

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catabolized by the gut microbiota leading to urolithin metabolites.5 The final metabolites

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in this catabolic conversion are urolithin A (Uro-A), urolithin B (Uro-B), and

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isourolithin A (Isouro-A) (Figure 1). Not all individuals have the appropriate gut

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microbiota to produce the final urolithin metabolites and three different urolithin

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metabotypes (UMs), UM-A, UM-B, and UM-0, have been reported.6 Species of the

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genus Gordonibacter have been identified as gut microbiota constituents that are

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involved in the conversion of EA into intermediary urolithins. 7,8 Fecal Gordonibacter

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concentrations correlate positively with urolithin-A content in feces and urine,9 although

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other unknown bacterial species are needed to produce the final urolithin metabolites.

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Urolithins reach in human plasma concentrations within the µM range,10,11 and these

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bioavailable metabolites, trigger different molecular and cell responses that may

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account, at least partially, for the antioxidant, anti-inflammatory, anticancer, cardio-

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metabolic, and neuroprotective effects attributed to ETs and (or) to ET-containing

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foods.2,

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identification of the specific regions of the intestine where they are formed, and the gut

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microbiota involved are of special interest. After pomegranate polyphenols intake,

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several urolithins have been detected in human feces, urine and also in biopsies taken

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from prostate and different regions of the colon in cancer patients.14,

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production of urolithins from EA by human fecal microbiota from both metabotype A

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and B has also been described.16 However, the gastrointestinal tract site for urolithin

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Therefore, the study of the mechanisms for urolithin production, the

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In vitro

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production, the stability and absorption of the metabolites in the gut are still unknown.

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To date, Gordonibacter levels have only been quantified in human fecal samples, but its

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distribution throughout the digestive tract and its role in urolithin production are still

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unknown. Fecal Gordonibacter levels are higher in urolithin metabotype A (UM-A)

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individuals than in those with urolithin metabotype B (UM-B) and urolithin metabotype

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0 (UM-0).17 Modulation of some human fecal bacteria by consumption of ET- rich food

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such as pomegranate has recently been described,18,19 and the increase of fecal

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Gordonibacter levels was highlighted.19 However, modulation of Gordonibacter and

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other bacterial groups by ET-rich foods along the digestive tract as well as their

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differences between metabotypes have not been explored and require further research.

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In the present study, a simulator of the human intestinal microbial ecosystem (TWIN-

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SHIME®) was used to shed light on ET gut microbiota metabolism in the different

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regions of the intestine. A pomegranate extract (PE) supplement was subjected to a

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stomach and small intestine (SI) digestion to estimate the bioavailability of native

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polyphenols and their catabolism in the upper part of the gastrointestinal tract. Long-

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term microbial colon fermentation was also investigated in the TWIN-SHIME®, thus

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determining the gut microbiota metabolism of ETs in the colon, the urolithin production

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pathway, the sites of transformation and the metabolite profile of (poly)phenolics which

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have potential to be absorbed . The production of specific SCFA was also evaluated, as

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well as the modulation of gut microbiota. The intestinal transport and cell metabolism of

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the (poly)phenolics were also evaluated through direct addition of diluted phenolics-

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containing SHIME® matrix to Caco-2-cells. Overall, our results are of interest to

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validate this system when comparing with the results previously obtained in vivo.

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MATERIALS AND METHODS

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Pomegranate Extract (PE) and Chemicals. A characterized PE was provided by

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Laboratorios Admira S.L. (Alcantarilla, Murcia, Spain).19 EA, punicalagin and 6,7-

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dihydroxycoumarin (DHC) were from Sigma-Aldrich (St. Louis, MO, USA). Urolithins

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were obtained as previously described.3 Purity was higher than 95% for all tested

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compounds. Organic solvents such as methanol, acetone, and acetonitrile were from

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Merck (Darmstadt, Germany). All chemicals and reagents were of analytical grade.

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Volunteer stratification and characterization. To select the fecal donors for UM-A

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and UM-B, 13 individuals consumed 30 g walnuts/day for three days, and urine samples

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were collected on the third day. Urolithin production and metabolic profiles were

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evaluated using HPLC-DAD-MS,20 and eight individuals were stratified as UM-A, four

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as UM-B and one as UM-0. This distribution is consistent with normal values as

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previously reported.20,6 Representatives of UM-A and UM-B were selected as fecal

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donors for the assay of ET metabolism in the gastrointestinal simulator.

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Metabolism of the ETs in the TWIN-SHIME® and sampling. A SHIME® setup

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(registered name from Ghent University and ProDigest), simulating the entire human

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gastrointestinal tract, was used as previously reported.21-23 To investigate two different

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metabotypes (UM-A and UM-B) at the same time, a TWIN-SHIME® setup23 was used

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by operating two systems in parallel. The first two reactors are of the fill-and-draw

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principle to simulate different steps in food uptake and digestion, with peristaltic pumps

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adding a defined amount of SHIME® nutritional medium (140 mL 3x/day) and

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pancreatic and bile liquid (60 mL 3x/day), respectively, to the stomach and small

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intestine (SI) compartments and emptying the respective reactors after specified

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intervals. The last three compartments simulate the ascending (AC), transverse (TC) and

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descending (DC) colon. Inoculum preparation, retention time, pH, temperature settings

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and reactor feed composition were previously described.23 After inoculating the colon

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reactors of the TWIN-SHIME® system with fresh fecal samples from UM-A and UM-B,

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a two-week stabilization period allowed the microbial community to differentiate in the

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reactors. After the stabilization period, the standard SHIME® nutrient matrix was further

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dosed to the model for two weeks. Analysis of samples in this control period allowed to

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determine the baseline microbial community composition and activity in the different

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reactors, which were used as a control to compare with the results from the treatment

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period where the basic diet was supplemented with 1.8 g/day of PE during three weeks.

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TWIN-SHIME® samples obtained from the different reactors (SI, AC, TC, and DC)

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were analyzed . Samples were taken for chemical (ET derived metabolites and SCFA

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profile) and microbial (denaturing gradient gel electrophoresis (DGGE) and quantitative

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PCR (qPCR)) analyses.

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EA and urolithins LC-MS analysis. Samples (2 mL) from the different vessels of the

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TWIN-SHIME® were extracted with 2 mL of ethyl acetate acidified with 1.5% formic

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acid. The mixture was vortexed for 2 min and centrifuged at 3500g for 10 min. The

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organic phase was separated and evaporated under reduced pressure to dryness. The dry

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samples were then redissolved in 400 µL of methanol and filtered through a 0.22 µm

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PVDF filter. Then 5 µL of 10 µg/mL of internal standard (6,7-dihydroxycoumarin) was

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added to 50 µL of the sample before the injection onto a column for HPLC-DAD-single

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Q analysis. Several samples were also analyzed after 1:10 dilution in methanol to

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quantify compounds present at very high concentrations (saturated compounds).

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Samples (0.5 mL) from the Caco-2 transport experiment were extracted with 0.5 mL

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acetonitrile: formic acid (2%). After vortexing the samples for 2 minutes they were

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centrifuged for 15 min at 14,000 g. The supernatants were collected, dried using

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nitrogen and stored at -80 ºC until HPLC-MS analyses. Samples were analyzed as

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described previously,3,20 using HPLC-DAD-MS with a reversed-phase column. All

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metabolites were quantified with their standards at 305 nm, except for EA, punicalagin,

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and Uro-M7 at 360 nm. These were quantified with EA calibration curve at 360 nm.

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The method validation previously reported,3,20 was adapted regarding recovery and

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limits of detection and quantification using this matrix (SHIME®

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(Supplementary Table 1).

medium)

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SCFA analysis. TWIN-SHIME® samples were analyzed as previously described.24

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Briefly, SCFA were extracted from the samples with diethyl ether, after the addition of

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2-methyl hexanoic acid as an internal standard. Extracts were analyzed using a GC-

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2014 gas chromatograph (Shimadzu, Hertogenbosch, The Netherlands), equipped with a

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capillary fatty acid-free EC-1000 Econo-Cap column (dimensions: 25mm0.53 mm, film

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thickness 1.2 mM; Alltech, Laarne, Belgium), a flame ionization detector and a split

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injector. The injection volume was 1 mL, and the temperature profile was set from 110

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to 160 °C, with a temperature increase of 6 °C/min. The carrier gas was nitrogen, and

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the temperature of the injector and detector were 100 and 220 °C, respectively.

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DNA extraction and microbial analysis. Powerfecal® DNA isolation kit (Mo-Bio

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Laboratories, Carlsbad, CA, USA) was used to isolate total DNA from different

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SHIME® samples. An additional step was done consisting on vigorous shake using a

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FastPrep® Instrument and 2mL tubes containing special beads (MP Biomedicals, LLC,

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Ohio, USA). After DNA extraction, DGGE was used to monitor the most prominent

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shifts within the overall microbial community together with group-specific shifts within

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the total bacteria25 and Clostridium cluster XIVa.26 After DNA extraction and PCR with

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general or group-specific primers, DGGE was performed to separate PCR products.25, 26

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Gels had a denaturizing gradient from 45% to 60% and were run using a DCodeTM

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Universal Mutation Detection System (Bio-Rad). Data analysis was carried out using

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GelCompar version 6.6 (Applied Maths, Sint-Martens-Latem, Belgium). Pearson

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correlation and UPGMA (Unweighted Pair Group Method using Arithmetic Mean)

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clustering were used to calculate dendrograms of DGGE profiles.

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qPCR for total bacteria, Firmicutes, Bacteroidetes, Bacteroides spp., Bifidobacterium

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spp., Lactobacillus spp., Akkermansia spp and Gordonibacter spp. was performed as

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previously reported.17,19 Real-time qPCR was run on the ABI 7500 system (Applied

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Biosystems, ABI, Madrid, Spain) following manufacturer’s conditions.

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Maintenance of intestinal cell culture. The human colon adenocarcinoma cell line

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Caco-2 (HTB37™) was obtained and cultured as reported previously.27 Cells were

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maintained in an incubator with a water saturated atmosphere of 10% CO2 at 37 ºC

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(Memmert CO2 incubator, Memmert GmbH & Co., Nurnberg, Germany). The cell

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culture medium was replaced 3 times a week, and when Caco-2 cells reached 80-90%

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confluence, the cells were sub-cultured using 0.25% (v/v) trypsin-EDTA solution

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(Sigma-Aldrich).

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Cytotoxicity measurements. Using MTT and SRB assays, the cytotoxicity of (i) PE-

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free intestinal matrix, (ii) digested PE and (iii) undigested PE on the intestinal Caco-2

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cellswas investigated.27,28 Intestinal Caco-2 cells were maintained 21 days to obtain

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confluent monolayers of differentiated intestinal cells as previously reported.27,28 21

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Days post-seeding, the Caco-2 monolayers were loaded for 4 h with 1/5 (v/v) dilutions

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of the intestinal matrix and the (un)digested PE in HBSS.29 Subsequently the MTT and

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SRB assays were performed to monitor mitochondrial activity and protein content,

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respectively.27,28

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Intestinal transport. Caco-2 cells were seeded on the apical side of the Transwell®

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filters of 6-well Transwell® plates (0.4 µm pore diameter, 24 mm insert, Corning Costar

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Co., Elscolab, Kruibeke, Belgium) and after 21 days, a 100% confluent monolayer was

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reported.27,28 To ensure that the intestinal Caco-2 cell monolayer (i) is intact during the

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transport assays and (ii) is not permanently damaged by the treatment, the

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transepithelial electrical resistance (TEER) of the monolayer was measured before,

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immediately after, and 24 h after the transport assays. The paracellular transport was

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also assessed 24 h after the transport assays using the fluorescent paracellular transport

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marker Lucifer Yellow. Based on in-house experience,27,28 Hank’s balanced salt

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solution (HBSS) (Gibco Life Technologies) was selected as a transport medium. Cells

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were washed and pre-incubated with the transport medium (HBSS) for 1 h. Next, cells

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were treated with dilutions of (i) PE-free intestinal matrix, (ii) digested PE and (iii)

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undigested PE dissolved in HBSS (2mL, pH 6.5), while fresh HBSS (2.5 mL, pH 7.5)

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was loaded in the basal compartment, and incubated for 4 h (37 °C and 10% CO2).

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Samples (0.5 mL) from the apical and basal compartments were obtained after 2 and 4 h

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of treatment.

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Statistical analysis. All samples were analyzed in triplicate. All data are expressed as

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mean value ± SD. Statistical analyses were performed using SPSS V.23 for Windows

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(SPSS, Chicago, IL, USA). Two-way ANOVA was performed to evaluate differences

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between groups. Bonferroni posthoc test was used to investigate differences between

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stages. Statistical significance was accepted at P