**Contents**


Reprinted from: *Nutrients* **2020**, *12*, 3471, doi:10.3390/nu12113471 .................. **135**


### *Editorial* **Diet and Microbiome in Health and Aging**

**Silvia Arboleya 1,2,\*, Sonia González 2,3,\* and Nuria Salazar 1,2,\***


After several years of research, sufficient evidence has been found supporting that diet is one of the main factors able to modulate both composition and activity of the intestinal microbiota, thus positioning it as a cornerstone in the host-microbiota interface. The gut microbiota plays a crucial role in the maintenance of normal host physiology. The rapid development of next-generation sequencing methods for nucleic acids, in the last decade, has facilitated in-depth studies of gut microbiome composition and function.

The articles collected in this Special Issue of Nutrients journal are intended to contribute to the progress of knowledge in the field as well as the basis for putative dietary interventions aimed at counteracting microbiota dysbiosis. These novel papers deal with the study of the relationship of diet on the intestinal microbiota from the early stages of life, deepening in certain pathologies, particularly relevant in this period of life, such as allergies, autism or overweight, up to adulthood and senescence. In addition, comprehensive review papers on hot topics such as the gut-brain axis, or the potential benefits of probiotics and prebiotics in the diet for allergy modulation were included. By providing updated and contrasted data, the authors propose several hypotheses that will be addressed in future research, which will undoubtedly arouse the interest of Nutrients journal readers.

The correct establishment of the gut microbiota at early life is known to be a milestone process for the later health of humans. Exponential studies during the last years have correlated aberrant gut microbiota colonization at the beginning of life with impairment on the intestinal, immune or nervous systems development [1]. Overweight, allergic diseases or neurodevelopmental disorders, like autism spectrum disorder (ASD), have been associated with gut microbiota alterations. Therefore, studying the composition of the gut microbiota at early life to be used as a predictor or to be target for modulation, is of great interest to prevent possible future diseases. In this context, Gonzalez et al. [2] evaluated the link between gut microbes and infant weight gain in the course of the first year of life in a cohort of full-term one-month aged neonates. They found significant associations between specific microbial groups and higher weight at 6 and 12 months, albeit being differently in vaginally and C-section delivered babies. Those gut microbes could be considered as potential microbial predictors for later weight gain.

The study of the connection between gut microbes, their metabolites and brain is currently favorable. Recent studies provide a close correlation of gut microbiota with different behavioral and cognitive traits, becoming a key stimulus during the first stages of neurodevelopment [3]. The exhaustive review by Johnson et al. [4] summarized the putative mechanisms implicated in the microbiome-brain interaction in the context of ASD. Genetic, environmental and epigenetic factors take part in an etiology puzzle that is not yet fully understood, in which the gut microbiome but also the mother's vaginal and oral microbiomes are playing a role. The authors highlighted diet and probiotics as gut microbiome modulators promising breakthrough interventions in the direction to get

**Citation:** Arboleya, S.; González, S.; Salazar, N. Diet and Microbiome in Health and Aging. *Nutrients* **2022**, *14*, 3250. https://doi.org/10.3390/ nu14163250

Received: 26 July 2022 Accepted: 2 August 2022 Published: 9 August 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

more individualized treatment approaches with lower side effects to guarantee the best clinical outcomes. Atopic diseases like asthma and allergic rhinitis often begin in early childhood when intestinal microbiota is underdeveloped. Evidence clearly supports a role for gut colonization in promoting and maintaining a balanced immune response in early life, thus this period could be considered as a window of opportunity [5]. Meirlaen et al. [6] aimed in their review to investigate if prevention and/or treatment of those atopic diseases could be accomplished by targeting gut microbiome. They performed an up to date search including both animal and clinical studies where probiotics, prebiotics or synbiotics were administered for the prevention or treatment of asthma and allergic rhinitis. The authors concluded that the current evidence is not enough to make recommendations of the use in children mainly due to the large heterogeneities derived from clinical study designs, but highlighted the benefits arisen from controlled pre-clinical studies. In concordance, they pointed out the need of well-designed and standardized studies to further clarify the action of those compounds on atopic diseases.

Diet has been identified as one of the main factors influencing gut microbiota modulation from early life, with breastfeeding as the greatest influencer at this time. In adulthood, solid evidence supports that long-term diets modulate the composition of the major microbial communities inhabiting the colon [7]. However, nowadays no reliable tool for calculating the healthiest dietary pattern in terms of microbiota has been identified for different diseases or adult life stages. We have a broad understanding of the impact of diet on the gut microbiota but formulating meaningful targeted dietary strategies remains a key challenge. In this sense, the work reported by Ruiz-Saavedra et al. [8] compared people over 50 years of age in different dietary indices, widely used in the literature, evaluating their potential for predicting the composition of the intestinal microbiota together with several other indicators of inflammatory state and oxidative stress, which are of special relevance in the aging process. On the other hand, some dietary components as well as isolated foods, have also demonstrated the capacity to modulate the intestinal microbiota at different levels. In this direction, the consumption of coffee in the regular diet, in a sample of healthy people aged between 19 and 95 years, has been associated with intestinal microbiota composition by González et al. [9]. In this descriptive and observational work, novel hypotheses have been proposed for the modulation of the *Bacteroides-Prevotella-Porphyromonas* group, associated in several studies with improved metabolic health, through coffee or the polyphenols contained in this beverage.

The impact of functional foods including probiotics, prebiotics and other bioactive compounds in the gut microbiota and host health has been evaluated in this Special issue through two *in vivo* murine models and a clinical trial. Massot-Cladera et al. [10] demonstrated that multivitamin and mineral supplementation together with prebiotic fibers (inulin and acacia gum) for 4 weeks differentially modulated gut microbiota composition, mineral absorption, and some immune and metabolic biomarkers in Wistar adult rats. Intestinal immune enhancement was reported in inulin-enriched supplement whereas acacia fiber supplement had stronger prebiotic activity, which may favor increasing mineral absorption. In another preclinical trial employing also diabetic type 2 Wistar rats, Toejing et al. [11] assessed the potential antidiabetic properties of the strain *Lactobacillus paracasei* HII01 isolated from the fermentation of northern Thai pickle. The strain was tested alone or in combination with the first-line drug antidiabetic drug metformin during a 12 weeks' period and potential beneficial effects were observed. The authors demonstrated that *L. paracasei* HII01 enhanced glycemic parameters including improvement in glucose intolerance, insulin, leptin and lipids levels, insulin-signaling proteins including from skeletal muscle that are involved in insulin-stimulated glucose uptake. This strain in diabetic rats also modulated the rat's gut microbiota reducing the plasma endotoxemia and systemic inflammation and increased caecum short chain fatty acids levels. The results suggested that there were no synergistic effects of metformin and probiotic *L. paracasei* HII01 but the data pointed out that this strain could be considered as a complementary supplement dietary strategy for type 2 diabetic patients.

The importance of the correct vaginal microbiota composition in vaginal health and success in pregnancy was also assessed by Fernández et al. [12]. The authors reported differences in vaginal parameters (pH, Nugent score, microbiota composition and soluble immune factor levels) between women with reproductive failure and fertile women. The lowest vaginal pH values and Nugent scores were associated with vaginal communities dominated by lactobacilli, while those with the highest pH values and Nugent scores were associated with a depletion of lactobacilli. Moreover, for the first time an antibioticassociated depletion of vaginal lactobacilli was associated with long-term health, infertility and lower pregnancy success rates. The administration of the strain *Ligilactobacillus salivarius* CECT5713 for 6 months was also tested by the first time to women with reproductive failure and resulted in improved reproductive success by the modulation of the gut microbiota and it also induced several changes in biochemical and immunological parameters in women who got pregnant. These results demonstrated that the assessment of the microbial profiles in the reproductive tract should be evaluated in cases of reproductive failure of unknown cause or origin and the administration of *L. salivarus* CECT5713 is a novel and promising strategy to modulate the reproductive tract microbiome in order to increase the success of pregnancy. Moles et al. [13] in a comprehensive review, also assessed the dietary changes across human history and the evolution of the gut microbiota as result to these changes. They disclose the power of diet over one-off treatments, such as probiotics or prebiotics, on the gut microbiota modulation and highlighted the need to unravel the diet-host-microbiota interaction to achieve a preventive and personalized medicine.

Demographic aging is a global challenge. Through its impact on various levels such as the immune system, digestive tract or cognitive impairment, the intestinal microbiota is a potential target for enhancing life quality throughout old age. With this aim, van Soest et al. [14] have studied the effect of the administration of a Mediterranean diet, rich in fresh fruits and vegetables, on inflammatory status and cognitive decline in European individuals over 65 years of age belonging to the NU-AGE cohort. While confirming a positive association between the consumption of a pro-inflammatory diet rich in animal products with a more pro-inflammatory microbiota, no impact on the cognitive decline of the participants was observed. Undoubtedly, slowing down cognitive decline along with the prevention of conditions such as Alzheimer's disease is one of the major challenges of the nutrition field in the elderly in the last decade. The comprehensive review by Megur et al. [15] analyzed clinical and experimental studies highlighting the key role of gut microbiota dysbiosis in the development of Alzheimer's disease. Several mechanisms of action are proposed through which the microbiota could act as a communicator between the gut and the brain.

In another study, the supplementation of isolated polyphenol rich fractions from blueberry (BB) employing in vitro fecal batch fermentations demonstrated the differential effects of the blueberry ingredients on the fecal microbiota composition in the artificial colon model [16]. Moreover, the same authors in a pilot clinical study reported that freeze-dried whole BB consumption by healthy female volunteers in two age groups (young and older) for 6 weeks changed the gut microbiota composition. The BB consumption produced higher effects in microbiota diversity in older women and its modulation was associated with antioxidant activity in healthy adults. These results support the idea that BB consumption is related with beneficial effects by both the polyphenolic and fiber content of this fruit and could be potentially used for a healthy ageing.

Some recent research has also suggested that physical activity, independent of diet, may impact positively on the composition of the microbiome, however this is not yet elucidated at the extremes of life. On the basis of evidence indicating that physically active seniors had better gastrointestinal health [17]. Fart et al. [18] explored gut microbiota composition and diversity in elderly people, according to their physical activity. Results showed significant reductions in the proportion of some microorganisms such as *Parasutterella excrementihominis* and *Bilophila wadsworthia* associated with a beneficial effect on gastrointestinal health.

The collection of articles included in this Special Issue evidenced some of the current progress on the knowledge about the effects of diet on host health through the gut microbiota modulation. Understanding the complex and dynamic interaction between dietary exposures and gut microbiota throughout lifespan can help to elucidate their potential role in different pathologies and to guide future strategies for the prevention and treatment of diseases.

**Author Contributions:** Conceptualization, S.A., S.G., N.S.; writing—original draft preparation S.A., S.G., N.S.; writing—review and editing, S.A., S.G., N.S. All authors have read and agreed to the published version of the manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


## *Article* **Long-Term Co**ff**ee Consumption is Associated with Fecal Microbial Composition in Humans**

**Sonia González 1,2, Nuria Salazar 2,3, Sergio Ruiz-Saavedra 2,3, María Gómez-Martín 1,2, Clara G. de los Reyes-Gavilán 2,3 and Miguel Gueimonde 2,3,\***


Received: 14 April 2020; Accepted: 28 April 2020; Published: 1 May 2020

**Abstract:** Coffee consumption has been related to a preventive effect against several non-transmissible pathologies. Due to the content of this beverage in phytochemicals and minerals, it has been proposed that its impact on health may partly depend on gut microbiota modulation. Our aim was to explore the interaction among gut microbiota, fecal short chain fatty acids, and health-related parameters in 147 healthy subjects classified according to coffee consumption, to deepen the association of the role of the (poly)phenol and alkaloid content of this beverage. Food daily intake was assessed by an annual food frequency questionnaire (FFQ). Coffee consumption was categorized into three groups: non-coffee-consumers (0–3 mL/day), moderate consumers (3–45 mL/day) and high-coffee consumers (45–500 mL/day). Some relevant groups of the gut microbiota were determined by qPCR, and concentration of fecal short chain fatty acids by gas chromatography. Serum health related biomarkers were determined by standardized methods. Interestingly, a higher level of *Bacteroides–Prevotella–Porphyromonas* was observed in the high consumers of coffee, who also had lower levels of lipoperoxidation. Two groups of coffee-derived (poly)phenol, methoxyphenols and alkylphenols, and caffeine, among alkaloids, were directly associated with *Bacteroides* group levels. Thus, regular consumption of coffee appears to be associated with changes in some intestinal microbiota groups in which dietary (poly)phenol and caffeine may play a role.

**Keywords:** coffee; (poly)phenol; gut microbiota; *Bacteroides*

#### **1. Introduction**

Coffee is one of the most consumed non-alcoholic beverages worldwide and it may exert different effects at a physiological level [1]. Although it has traditionally been considered as a beverage with very low nutritional value, epidemiological evidence suggests that moderate coffee consumption may reduce the risk of chronic diseases such as metabolic syndrome, obesity, type 2 diabetes [2], cardiovascular diseases [3], or some types of cancer [4–6]. Coffee may impact directly on the host gastrointestinal physiology by increasing intestinal motility and reducing intestinal transit time [7,8]. Some of these widely described benefits of coffee have been attributed to its high content in non-nutritional compounds such as phenolic compounds, fibers, minerals, and caffeine [9], which may also influence host metabolic pathways related to health maintenance. From these compounds, caffeine, (poly)phenols, and fibers are able to reach and exert some of their effects in the large intestine, being fermented by the gut microbiota [10]. Thus, given the pivotal role that microbiota plays on human nutrition and

health [11], it is possible that some of the beneficial effects of the coffee components may be related with the participation of the gut microbiota in the metabolism of such compounds. Interventional studies analyzing the impact of a moderate coffee intake during three weeks in a healthy population have reported an increase of *Bifidobacterium* [9], sometimes also linked to a decrease of *Clostridium* and *Escherichia coli* [9,12–14]. Regarding other bacterial groups, such as *Bacteroides*, the results in the literature remain controversial [9,13,15,16]. Among the possible mechanisms to explain these associations, data from in vitro studies pointed to a direct relationship between chlorogenic acids and selective changes on the *Blautia coccoides–Eubacterium rectale* group [10] and between caffeine and the abundance of the *Lactobacillus* species [17]. Based on previous evidences indicating that theobromine, an alkaloid present in coffee, can enhance (poly)phenol absorption in the intestine [18], a synergistic effect for phenolic compounds and alkaloids on the intestinal microbiota at this location may be plausible. To date, most of the studies analyzing the impact of coffee on the composition of the intestinal microbiota come from in vitro, animal, or intervention studies. However, to the best of our knowledge, no observational studies are currently available analyzing the impact of regular coffee consumption on fecal microbiota, taking into consideration the influence that the content of this beverage in caffeine and phenolic compounds may exert on the microbiota. This information would contribute to expand the existing knowledge about the impact of coffee on gastrointestinal physiology and therefore, on health maintenance.

#### **2. Subjects and Methods**

The study included 147 participants, with ages ranging from 19 to 95 years and body mass index (BMI) scores between 19.0 and 39.0 kg/m2 who were recruited in Asturias (Atlantic coast of Spain). Volunteers were cited individually, informed about the study, and gave informed written consent before enrolment. Inclusion criteria were the absence of diagnosed immune or digestive related pathologies as well as non-consumption of corticoids, immunosuppressive drugs, monoclonal antibodies, antibiotics, or immunotherapy, and not having consumed probiotics or prebiotics as dietary supplements during the previous month.

The study was approved by the Bioethics Committee of CSIC (Consejo Superior de Investigaciones Científicas) and the Regional Ethics Committee for Clinical Research (Servicio de Salud del Principado de Asturias n 13/2010).

#### *2.1. Nutritional Assessment*

Participants were instructed to maintain their usual dietary pattern before the study. Regular food intake was assessed by trained personnel in a personal interview of approximately 1 h duration, using an annual semi-quantitative food frequency questionnaire (FFQ), previously validated [19,20]. Methodological issues about dietary assessment were published elsewhere [18]. Food consumption was transformed into energy and macronutrients intake using the food composition tables of CESNID (Centro de Enseñanza Superior de Nutrición Humana y Dietética) [21]. Caffeine intake was estimated from the United States Department of Agriculture (USDA) food composition database [22]. The polyphenols content in foods was completed using the Phenol Explorer database that compiled detailed information from over 400 foods and beverages, including coffee [23] and fiber components, and were ascertained using the Marlett et al. food composition tables [24].

At the time of carrying out the blood extraction, height and weight were taken by standardized protocols previously described [25] in order to calculate the BMI by the formula: weight (kg)/height (m2).

#### *2.2. Blood Biochemical Analyses*

Fasting blood samples were drawn by venipuncture and centrifuged (1000× g, 15 min). Plasma and serum aliquots were kept at −20 ◦C until analyses. Plasma glucose, cholesterol, and triglycerides were determined by standard methods. Serum C-reactive protein (CRP) levels were determined by ELISA (CRP Human Instant ELISA, Ebioscience, San Diego, CA, USA), and malondialdehyde (MDA) by using the Byoxytech LPO-586 assay (Oxis International S.A., Paris, France) [26]. Serum leptin was determined by using the Human Leptin ELISA Development Kit 900-K90 (PeproTech Inc., Rocky Hill, NJ, USA) according to the manufacturer's instructions.

#### *2.3. Fecal Collection and Microbial Analysis*

Participants were provided with a sterile container for fecal sample collection; after deposition samples were immediately frozen at −20 ◦C and transported to the laboratory. For analyses, samples were melted at room temperature (24 ± 2 ◦C), weighed, diluted 1/10 in sterile PBS, and homogenized (LabBlender 400 Stomacher, Seward Medical, London, UK) for 4 min; the DNA was extracted using the QIAamp DNA stool mini kit (Qiagen, Hilden, Germany) as described elsewhere [27]. Quantification of different bacterial populations, covering the major bacterial groups present in the human gut, was achieved in a 7500 Fast Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) using SYBR Green PCR Master Mix (Applied Biosystems) [27] (Table 1). One microliter of template fecal DNA (~5 ng) and 0.2 μM of each primer were added to the 25 μL reaction mixture. PCR cycling consisted of an initial cycle of 95 ◦C 10 min, followed by 40 cycles of 95 ◦C 15 s, and 1 min at the appropriate primer−pair temperature. The number of cells was determined by comparing the Ct values obtained from a standard curve as previously described [27]. Fecal DNA extracts were analyzed and the mean quantity per gram of fecal wet weight was calculated for each bacterial group.

Major short chain fatty acid (SCFA), acetate, propionate, and butyrate were analyzed by gas chromatography from the supernatants of 1 mL of the homogenized feces as previously indicated [28]. A chromatograph 6890N (Agilent Technologies Inc., Palo Alto, CA, USA) connected to a mass spectrometry detector (MS) 5973N (Agilent Technologies) and a flame ionization detector (FID) was used for identification and quantification of SCFA, respectively, as described previously [29].


**Table 1.** Primers and annealing temperatures used for the quantification of intestinal microbial groups by qPCR.

Adapted from Reference [28].

#### *2.4. Statistical Analyses*

Statistical analysis was performed using the IBM SPSS program version 24.0 (IBM SPSS, Inc., Chicago, IL, USA). Goodness of fit to the normal distribution was analyzed by means of the Kolmogorov−Smirnov test. When the distribution of variables was skewed, the natural logarithm of each value was used in the statistical test. For descriptive purposes, mean values are presented on untransformed variables. Differences in general and anthropometric characteristics, blood parameters, gut microbial groups, and fecal SCFA were assessed in accordance to tertiles of coffee intake through multivariate analyses adjusted by age, gender, BMI, and energy, based on the strong evidences linking these factors with human microbial composition. Pearson correlation was conducted to elucidate the interplay between caffeine and polyphenols from coffee and intestinal microbiota. The conventional probability value (0.05) for significance was used in the interpretation of results. Results obtained from

the sample analysis were plotted using Microsoft Excel Software version 2016 (Microsoft Corporation, Redmon, Washington, USA). Data resulting from the Pearson correlation tests were plotted using GraphPad Prism version 8 for Windows (GraphPad Software, San Diego, CA, USA).

#### **3. Results**

The general characteristics of the sample are described in Table 2 according to the coffee tertiles. No statistically significant differences were found based on coffee consumption for any of the variables evaluated, with the exception of age, which was lower in subjects with the highest consumption of coffee (tertile 3).


**Table 2.** General characteristics of the study sample according to coffee consumption tertiles.

All values are shown as mean ± standard deviation (SD). Values in the same row showing a different subscript present a statistically significant difference (*p* ≤ 0.05). Tobacco user refers people with smoking-habit at the time of the study.

The possible existence of a dietary pattern linked to coffee consumption was explored, as shown in Figure 1.

**Figure 1.** A radar plot representing differences in dietary patterns according to coffee consumption (mL/day) tertiles. \* *p* ≤ 0.05.

From the 19 items analyzed, only a moderate increase in the consumption of greens and vegetables was found across coffee tertiles, this being higher in tertile 3. As expected, since coffee is usually consumed with sugar, significant differences were also observed in the intake of non-alcoholic beverages and sugar products. In spite of this, the scarce differences found do not allow for a differential dietary pattern in the high-consumers group to be defined. When the average counts of the major gut microbial groups were analyzed, based on coffee consumption tertiles (Table 3), the sole difference observed was a significantly higher level of *Bacteroides-Prevotella-Porphyromonas* in tertile 3. Nevertheless, no differences were detected in fecal levels of SCFA according to coffee consumption, neither in the studied serum biomarkers, with the exception of MDA, an indirect biomarker of lipid peroxidation, whose concentration was lower in tertile 3.


**Table 3.** Differences in gut microbiota composition, fecal short chain fatty acids concentration (SCFA), and serum markers according to coffee consumption tertiles.

\* Results obtained from multivariate analyses adjusted by age, gender, BMI, and energy. Values in the same row showing different subscripts present a statistically significant difference; (*p* ≤ 0.05). MDA, malondialdehyde; LDL, low density lipoprotein; HDL, high density lipoprotein.

Coffee is a dietary source of various bioactive compounds including (poly)phenols and alkaloids (Figure 2). At the compound level, the major phenolic compounds provided by coffee were caffeoylquinic and feruloylquinic acids among hydroxycinnamics, and guaiacol from methoxyphenols (Figure 2A). As shown in Figure 2B, coffee was the major contributor to the intake of caffeine in the sample, explaining more than 90% of its consumption.

**Figure 2.** Representation of (**A**) the contribution of each coffee phenolic compound in the sample and (**B**) the dietary caffeine sources in the sample.

Furthermore, the linear relationships between coffee derived dietary components and the microbiota was estimated through Pearson's correlation test and are presented graphically in the heatmap of Figure 3. From the different phenolic compounds analyzed, those derived from coffee have shown the highest correlation with intestinal microbial groups together with caffeine. While metoxyphenols and alkylmethoxyphenols were correlated with the levels of the *Bacteroides– Prevotella–Porphyromonas* group with a *r* = 0.177 and 0.182, respectively, caffeine intake was directly associated with fecal *Bacteroides* levels (*r* = 0.200).

**Figure 3.** A heatmap showing Pearson correlations among intestinal microbial groups (Log n cells/gram feces), fecal short chain fatty acids (mM), polyphenol groups (mg/day), and alkaloids (mg/day), from coffee and other dietary sources. Columns correspond to major intestinal microbial groups and fecal SCFA; rows correspond to dietary polyphenols and alkaloids. Blue and red colors denote negative and positive association, respectively. The intensity of the colors represents the degree of association between variables. Asterisks indicate significant associations: \* *p* ≤ 0.05; \*\* *p* ≤ 0.01.

#### **4. Discussion**

Our results represent a first step in broadening the knowledge of the association between the regular intake of coffee and fecal microbiota in an apparently healthy human population, suggesting a possible implication of coffee phenolic compounds and caffeine in this relationship.

The mean consumption of coffee is highly variable in the study sample, ranging between 0 and 500 mL/day, in a similar way to that observed in other European countries with a Mediterranean-type dietary pattern, such as Italy or Greece [30]. Given the absence of a reference value to establish coffee consumption levels, tertiles have been used to categorize the sample. The defined cut-off points are coherent from a methodological point of view, since they group non-coffee-consumers (0–3 mL/day) in tertile 1, moderate consumers (3–45 mL/day) in tertile 2, which could correspond to those subjects consuming a little cup of coffee per day of the so-called Italian coffee, and the tertile 3 of high consumers. Still, it must be taken into account that this tertile 3 has a lower mean intake of coffee than what has been reported in other countries, such as Germany [30]; therefore, our data may not be directly extrapolated to other countries with different trends in coffee consumption. It is also important to note that important differences in the coffee preparation procedures exist among different consumers and different countries. In our case, the mean coffee intake in tertile 3 is slightly lower than the range of 400–600 mL [9], associated with a protective effect against various pathologies [3,31]. Interestingly, in some studies the long-term consumption of seven cups of coffee per day has been associated with a reduction in the risk of metabolic syndrome, obesity, and type 2 diabetes [32,33]. However, since the coffee cup volume could vary from 150 mL to 300 mL among the studies included in the meta-analysis of Grosso et al. [32] indicated just before, extrapolations to our results are limited.

In some impaired health conditions, alterations in the intestinal microbiota have been described, mainly a decrease in the abundance of *Bacteroides* and/or an increase in the Firmicutes/ Bacteroidetes ratio [34–36]. In line with this, we have found higher fecal levels of the *Bacteroides-Prevotella-Porphyromonas* group in the high coffee consumers, supporting previous evidences in humans and animal models having higher fecal levels of these microorganisms in groups of better metabolic status [34–36]. It is tempting to speculate about this potential association; however, given the descriptive nature of this cross-sectional study, we cannot establish cause–effect relationships or directionality. Members of the phylum Bacteroidetes have been hypothesized to reduce intracellular oxygen levels, thus favoring the growing of anaerobic species which could promote the maintenance of intestinal balance, and they are identified as key glycan degrading bacteria [37,38] being more able to metabolize polyphenols than other groups such as Firmicutes. In this sense, coffee polyphenols explained a 20% of total polyphenol intake in the subjects with the highest consumption (tertile 3). Therefore, we hypothesized that at an equivalent total intake of polyphenols, the physiological effect of these compounds may differ among subjects depending on their dietary origin. It has been demonstrated that coffee-derived polyphenols were able to interact with intestinal bacteria in a bidirectional way: polyphenols may modify the gut environment [39], and/or they can be catabolized by intestinal bacteria converting them into a large variety of compounds with greater antioxidant activity than the compound of origin [40]. Despite some coffee-derived phenolic compounds, such as chlorogenic acid, having been associated in in vitro studies with important antioxidant and anti-inflammatory effects [41–44], we did not find differences in serum antioxidant capacity or in C-reactive protein, depending on the coffee consumption levels. Several factors may explain these results. Firstly, it is possible that the amount of coffee consumed in this sample was insufficient to observe a differential effect among tertiles, and secondly, subjects with low coffee consumption received polyphenols through other foodstuffs, thus ultimately achieving a similar polyphenol intake to the high coffee consumers (mean intake of 1604.4 and 1487.7 mg/day in T2 and T3 respectively, *p* = 0.533). Considering the high impact of phenolic compounds on gut microbial modulation, future human intervention studies analyzing the impact of coffee on fecal microbiota [9] should evaluate the intake of dietary and specific coffee polyphenols.

Moreover, there is evidence from animal research showing that caffeine administration counteracts shifts in the ratio, Firmicutes/Bacteroides, resulting from a western diet [45]. Although we cannot attribute the observed differences in fecal microbial composition to a single compound, caffeine has been positively correlated in this work with most of the gut microbial groups analyzed. In turn, evidences of lower MDA concentrations in high coffee consumers may be in consonance with data in the literature describing the down-regulation effect of caffeine on lipid binding proteins and consequently in lipogenesis [46–49].

At the time of interpreting these results, the limited sample size should be considered. Nonetheless, we have found associations whose consistency and strength justify further research. Human experimentation in healthy subjects is limited by the logistical problems associated with carrying out direct measurements. Fecal SCFA accounts for only 5% to 10% of SCFA production that is not absorbed in the colon [50]. The FFQ is one of the most valid dietary tools in order to describe subjects' regular dietary intake. However, to accurately quantify the coffee derived polyphenols, it would be advisable to register more detailed information about coffee such as the variety, the amount of powder used, ground grain size, and the final volume obtained [30]. Since we did not have individuals with daily intakes greater than 500 mL, it would be desirable in the future to be able to expand this group to deepen the association between this beverage and intestinal microbiota and oxidative stress, and to determine whether this would be dose dependent.

#### **5. Conclusions**

The interaction between coffee consumption, a modifiable factor, and intestinal bacteria may be useful for the development of dietary strategies in humans focused on diverse pathologies where the concentration of the *Bacteroides* group was altered.

**Author Contributions:** The authors' responsibilities were as follows: S.G. and M.G. designed the experimental work. S.R.-S. and M.G.-M. carried out the nutritional and anthropometric determinations. S.G., N.S., C.G.d.l.R.-G., and M.G. obtained the biological samples. N.S., C.G.d.l.R.-G., and M.G. were involved in microbiota and SCFA analysis, meanwhile S.R.-S. and M.G.-M. performed the statistical analysis. S.G. wrote the original draft. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Plan Estatal de I+D+I through projects AGL2017-83653-R (AEI/FEDER, UE) and RTI2018-098288-B-I00 (MCIU/AEI/FEDER, UE), and by contracts with Biopolis SL (Valencia, Spain), CAUCE Foundation (Oviedo, Spain) and Alimerka Foundation (Llanera, Spain). N.S. was granted a postdoctoral contract awarded by the Fundación para la Investigación Biosanitaria de Asturias (FINBA); M.G-M. was supported by a FPU (FPU18/03393) predoctoral grant from the Spanish Ministry of Science, Innovation and Universities; and S.R.-S. is the recipient of a Research Training contract awarded under project RTI2018-098288-B-I00.

**Acknowledgments:** We show our greatest gratitude to all the volunteers participating in the study.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Review*
