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Adherence to a Mediterranean diet influences the fecal metabolic profile of microbial-derived phenolics in a Spanish cohort of middle-age and older people Isabel Gutiérrez-Díaz, Tania Fernández-Navarro, Nuria Salazar, Begoña Bartolome, Maria Victoria Moreno-Arribas, Enrique Juan de Andres-Galiana, Juan Luis FernándezMartínez, Clara G. de los Reyes-Gavilan, Miguel Gueimonde, and Sonia Gonzalez-Solares J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.6b04408 • Publication Date (Web): 28 Dec 2016 Downloaded from http://pubs.acs.org on January 2, 2017

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Journal of Agricultural and Food Chemistry

TITLE: Adherence to a Mediterranean diet influences the fecal metabolic profile of microbial-derived phenolics in a Spanish cohort of middle-age and older people. Isabel Gutiérrez-Díaz1,2, Tania Fernández-Navarro1,2, Nuria Salazar2, Begoña Bartolomé3, M. Victoria Moreno-Arribas3, Enrique Juan de Andres-Galiana4, Juan Luis Fernández-Martínez4, Clara G. de los Reyes-Gavilán2, Miguel Gueimonde2 and Sonia González-Solares1*. 1

Department of Functional Biology, University of Oviedo, C/Julián Clavería s/n

Oviedo, 33006 Asturias, Spain. 2

Department of Microbiology and Biochemistry of Dairy Products, Instituto de

Productos Lácteos de Asturias - Consejo Superior de Investigaciones Científicas (IPLACSIC), Paseo Río Linares s/n Villaviciosa, 33300 Asturias, Spain. 3

Institute of Food Science Research (CIAL), CSIC-UAM, CEI UAM-CSIC, C/ Nicolás

Cabrera 9, 28049 Madrid, Spain. 4

Department of Applied Mathematics. University of Oviedo C/ Calvo Sotelo. 33007

Asturias, Spain. *Sonia González Solares. (Tel: +(34)985104209; Fax: +(34)985103534; E-mail: [email protected])

1 ACS Paragon Plus Environment


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ABSTRACT

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Despite the evidence regarding the influence of certain polyphenol food sources on the

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metabolic profile in feces, the association between the different phenolics provided by

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the diet and the fecal phenolic profile has not been elucidated. In this study, the

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composition of phenolic metabolites in fecal solutions was analyzed by UPLC-ESI-

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MS/MS in 74 volunteers. This fecal phenolic profile showed a high interindividual

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variation of the different compounds analyzed, phenylacetic and phenylpropionic acids

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being the major classes of phenolic metabolites excreted in feces. Subjects with higher

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adherence to a Mediterranean dietary pattern presented greater fecal concentrations of

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benzoic and 3-hydroxyphenylacetic acids, positively correlated with the intake of the

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principal classes and subclasses of polyphenols and fibers, and higher levels of

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Clostridium cluster XVIa and Faecalibacterium prausnitzii. These results provide a link

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among the Mediterranean dietary pattern, the bioactive compounds of the diet and the

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fecal metabolic phenolic profile.

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KEYWORDS

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Mediterranean dietary pattern, phenolic compounds, fiber, fecal metabolites excretion,

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physical activity.


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INTRODUCTION

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Scientific evidence has associated the intake of polyphenol-rich foods and beverages

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with the prevention of several pathologies.1-3 The antioxidant, anti-inflammatory or

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anti-carcinogenic potential of these compounds may contribute to these benefits.4-8

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However, an important question that remains unsolved is whether specific effects can be

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attributed to each class and/or individual compound of these polyphenols or to their

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combined effect as a part of a whole diet. On the other hand, most studies available have

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focused on the antioxidant effect of plasmatic polyphenols absorbed from dietary

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components at the small intestine.9 However, the vast majority of polyphenols reach the

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colon, where they are metabolized by the colonic microbiota, in some cases rendering

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metabolites which may have greater biological activity than their dietary precursors.10, 11

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Analysis of the fecal composition not only provides valuable information regarding

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microbial produced metabolites and unabsorbed dietary components, but also provides

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insight on whether the functionality of the gut ecosystem could undergo modifications

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after dietary interventions.12 There are some research regarding the influence of certain

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polyphenol rich-foods on the phenolic profile produced by the colonic microbiota.13-16

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Nevertheless, the association between the phenolics provided by a regular diet and their

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fecal excretion products has not been elucidated yet. While one of the most

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representative components of a Mediterranean dietary pattern, red wine, has been

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associated with an increase in the fecal excretion of 3,5-dihydroxybenzoic,

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protocatechuic, 3-O-methylgallic, vanillic, syringic, phenylpropionic, 4-hydroxy-5-

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(phenyl)valeric and p-coumaric acids,17 raspberry dietary supplementation does not

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appear to have significant impact on fecal phenolic profile.18 The high interindividual

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variation in the gut microbial composition and the different metabolic pathways

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potentially involved in the metabolism of the wide variety of phenolic compounds 3 ACS Paragon Plus Environment


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ingested with diet,17, 19-21 hinder the evaluation of the results obtained. It is also probable

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that the different diets among countries might impact differently on the amount and the

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type of biocompounds consumed by their inhabitants and the composition and

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metabolism of the intestinal microbiota involved in the metabolic transformation of

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polyphenols.22-25 Thus, it is necessary to establish whether the fecal phenolic profile can

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be related with the regular dietary pattern, taking into consideration that physical and

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lifestyle factors also show a high correlation with dietary intake. Therefore, the aim of

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this study was to investigate whether a regular Mediterranean dietary pattern could be

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associated with the microbial-derived phenolic metabolites profile in fecal samples and,

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if so, what are the dietary components related to them.


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MATERIALS AND METHODS

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This cross-sectional study comprised 74 health mature volunteers from Asturias region

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(North of Spain), 54 women and 20 men (71.3±11.2 years old). Participants were

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recruited between 2009 and 2012 from subjects attending to a Program of the University

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of Oviedo for people older than 50 years and from Institutions for elderly people in

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Asturias. In a preliminary interview, volunteers were informed of the objectives of the

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study. When they agreed to participate, a personal appointment was made to collect

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dietary information. Exclusion criteria were previous diagnosis of cancer, autoimmune

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or digestive diseases, and consumption of probiotics/prebiotics or antibiotics during the

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previous month. Participants were mentally and physically able to participate in the

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study and gave their written informed consent. Ethical approval was obtained from the

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Regional Ethics Committee for Clinical Research (Servicio de Salud del Principado de

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Asturias), in compliance with the Declaration of Helsinki.

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Nutritional assessment

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Dietary intake of the previous year was registered with a food frequency questionnaire

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(FFQ) of 160 food items, designed a priori for this project and validated with a 24-h

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dietary for the intake of dietary biocompounds .26 Experts noted down detailed

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information about menu preparation and other information relevant to the study on fiber

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intake, for example the consumption of fruit peeled or with skin. In the time of

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interview, volunteers were enquired about the frequency and amount they ate each food.

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They could choose between 7 servings from 3 standardized photographs. To record the

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consumption of alcoholic beverages, each volunteer was asked if they evenly consumed

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wine, beer, cider and/or liquors, as well as, the type and amount, using household

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measures (a glass, a bottle, etc.). Methodological issues concerning dietary assessment

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have been detailed elsewhere.26 Food intake was analyzed for energy, macronutrients 5 ACS Paragon Plus Environment


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and total dietary fiber content by using the nutrient Food Composition Tables developed

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by the Centro de Enseñanza Superior de Nutrición Humana y Dietética (CESNID).27

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Also, the following fiber components were ascertained using Marlett et al.28 food

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composition tables: soluble fiber, soluble pectin, soluble hemicellulose, insoluble fiber,

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insoluble pectin, insoluble hemicellulose, Klason lignin and cellulose (Table 4), based

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on the enzymatic-chemical method developed by Theander et al.29 by which pectin

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content is determined using calorimetric assay, cellulose and hemicellulose are

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determined by high-performance liquid chromatography (HPLC), and Klason lignin is

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estimated as the insoluble material after a Saeman acid hydrolysis.30 The phenolic

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compound content in foods was completed using the Phenol Explorer database. It

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contains more than 35,000 content values for 500 different polyphenols in over 400

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foods and are classified into polyphenols classes such as flavonoids (anthocyanins,

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dihydrochalcones, dihydroflavonols, flavanols, flavanones, flavones and flavonols),

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phenolic acids (hydroxycinnamic and hydroxybenzoic acids), lignans, stilbenes, and

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others (alkylphenols and tyrosols) (Table 4). For recipes, polyphenol content was

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calculated on the basis of the contents of the ingredient and its polyphenol composition.

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All of this information was mainly determined by HPLC, gas chromatography (GC),

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and capillary electrophoresis (CE) and was obtained from more than 1,300

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publications.31

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Mediterranean diet score

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A Mediterranean Diet Score (MDS) was created using previous reports.32,33 Median

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daily intake of the 8 components of the MDS was adjusted for sex and add up one point

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to the total punctuation: high intake of cereals and potatoes, legumes, vegetables fruit,

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and ethanol, high ratio of monounsaturated / saturated lipids and low intake of meat and

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processed meat and milk and dairy products. Therefore, the possible range of


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punctuation was 0-8 points, using 4 points as cutoff, associated with greater adherence

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to MDS and also with health-promoting effects.33,34

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Anthropometric evaluation

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Height was measured using a stadiometer with ±1 mm of error (Año-Sayol, Barcelona,

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Spain). andweight on a scale with an accuracy of ±100 g (Seca, Hamburg, Germany).

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Body mass index (BMI) was calculated by: weight (kg) / height (m2) and stratified

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according to Sociedad Española para el Estudio De la Obesidad (SEEDO) criteria: lean-

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normal (≤25 Kg/m2), over-weight (25.1 to 29.99 kg/m2), and obese (≥30.0 kg/m2). 35

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Fecal specimen collection

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Each subject was asked to provide a fecal sample just after the nutritional interview,

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which was collected in sterile containers and frozen at -20 °C until further analyses,

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within a maximum of 2 h from deposition.

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Microbiological analyses

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The DNA was isolated form one gram of fecal sample by using the QIAamp DNA stool

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mini kit (Qiagen, Hilden, Germany) as previously described.36 PCR amplification and

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detection of the 16 rRNA gene for the quantification of different bacterial groups

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(Akkermansia, Bacteroides–Prevotella–Porphiromonas, Bifidobacterium, Clostridium

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cluster XVIa, Lactobacillus group and Faecalibacterium prausnitzii) in feces was

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performed with a 7,500 Fast Real-Time PCR System (Applied Biosystems, Foster City,

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CA, USA) using SYBR Green PCR Master Mix (Applied Biosystems) as previously

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described.37

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Phenolic metabolites assessment



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For sample preparation, frozen fecal samples were thawed, and one gram was taken,

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diluted 1/10 in sterile phosphate-buffered saline solution (PBS; 0.01 M phosphate

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buffer, 0.0027 M potassium chloride, 0.137 M sodium chloride, pH 7.4, prepared from

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tablets from Sigma-Aldrich) and homogenized in a LabBlender 400 stomacher (Seward

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Medical, London, UK) at full-speed for 4 min. Supernatants were then obtained by

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centrifugation (10,000g, 30 min, 4 ºC) and filtration through 0.2 µm and stored at -20 ºC

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until analysis.

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For the analysis of phenolic metabolites in the fecal solutions, a previously reported

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UPLC-ESI-MS/MS method was followed,17, 20 with some modifications. LOD (limit of

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detection) of phenolic acids by this UPLC-TQMS equipment is up to 0.001 µg/mL.38

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The liquid chromatographic system was a Waters Acquity UPLC (Milford, MA)

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equipped with a binary pump, an autosampler thermostatted at 10 ºC and a heated

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column compartment (40 ºC). The column employed was a BEH-C18, 2.1x100 mm and

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1.7 µm particle size, from Waters (Milford, MA, USA). The mobile phases were 0.1%

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(v/v) formic acid in water (A) and 0.1% (v/v) formic acid in acetonitrile (B). The

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gradient programme was as follows: 0 min, 0.1% B; 1.5 min, 0.1% B; 11.17 min, 16.3%

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B; 11.5 min, 18.4% B; 14 min, 18.4% B; 14.1 min, 99.9% B; 15.5 min, 99.9% B; 15.6

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min, 0.1% B. Equilibrium time was 2.4 min resulting in a total run-time of 18 min. The

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flow rate was set constant at 0.5 mL/min and the injection volume was 2 µL. The LC

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effluent was pumped to an Acquity TQD tandem quadrupole mass spectrometer

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equipped with a Z-spray electrospray ionization (ESI) source operated in negative

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polarity mode. The ESI parameters were set as follows: capillary voltage, 3 kV; source

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temperature, 130 ºC; desolvation temperature, 400 ºC; desolvation gas (N2) flow rate,

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750 L/h; cone gas (N2) flow rate, 60 L/h. For quantification purposes, data were

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collected in the multiple reaction monitoring (MRM) mode, tracking the transition of 8 ACS Paragon Plus Environment

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parent and product ions specific to each compound. The MS/MS parameters (cone

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voltage, collision energy and MRM transition) of the 62 phenolic compounds targeted

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in the present study (mandelic acids, benzoic acids, phenols, hippuric acids,

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phenylacetic acids, phenylpropionic acids, cinnamic acids, 4-hydroxyvaleric acids and

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valerolactones) were previously reported.17 The ESI was operated in negative ionization

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mode, except for γ-valerolactone (positive mode). All metabolites were quantified using

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the calibration curves of their corresponding standards, commercially-available from

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different

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Vestenbergsgreuth, Germany; and Extrasynthese, Genay, France. Only 4-hydroxy-5-

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(4´-hydroxy-phenyl)-valeric and 4-hydroxy-5-(3´,4´-dihydroxy-phenyl)-valeric acids,

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which were quantified using the calibration curve of 3-(4´-hydroxyphenyl)-propionic

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and 3-(3´,4´-dihydroxyphenyl)-propionic acids, respectively. Data acquisition and

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processing was realized with MassLynx 4.1 software. Results were expressed as the

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amount (µg) of phenolic metabolites in 1 mL of decimal fecal dilutions.

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Statistical analyses

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IBM-SPSS version 22.0 (SPSS-Inc., Chicago) was used as statistical software for data

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analyses. Goodness of fit to normal distribution was analyzed with the Kolmogorov-

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Smirnov test. When the distribution of variables was skewed, the natural logarithm of

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each value was used in the statistical test. For data of fecal phenolic compounds, only

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those fecal compounds with concentrations >0.2 µg/mL and detectable in at least 5

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samples were considered. A Student’s t-test was used to evaluate the differences in the

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means of continuous variables according to the categorical variables as gender, age (50-

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65 and ≥65 years), BMI (

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