Compliance with Nutritional Recommendations and Gut Microbiota Profile in Galician Overweight/Obese and Normal-Weight Individuals

Citation: Sinisterra-Loaiza, L.; Alonso-Lovera, P.; Cardelle-Cobas, A.; Miranda, J.M.; Vázquez, B.I.; Cepeda, A. Compliance with Nutritional Recommendations and Gut Microbiota Profile in Galician Overweight/Obese and Normal-Weight Individuals. Nutrients 2023,15, 3418. https:// doi.org/10.3390/nu15153418 Academic Editor: Yoshitaka Hashimoto Received: 30 June 2023 Revised: 28 July 2023 Accepted: 28 July 2023 Published: 1 August 2023 Copyright: © 2023 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/). nutrients Article Compliance with Nutritional Recommendations and Gut Microbiota Profile in Galician Overweight/Obese and Normal-Weight Individuals Laura Sinisterra-Loaiza, Patricia Alonso-Lovera, Alejandra Cardelle-Cobas * , Jose Manuel Miranda , Beatriz I. Vázquez and Alberto Cepeda Laboratorio de Higiene, Inspección y Control de Alimentos, Departamento de Química Analítica, Nutrición y Bromatología, Campus Terra, Universidade da Santiago de Compostela, 27002 Lugo, Spain; [email protected] (L.S.-L.); [email protected] (P.A.-L.); [email protected] (J.M.M.); [email protected] (B.I.V.); [email protected] (A.C.) *Correspondence: alejandra.car[email protected] Abstract: Different research studies have identified specific groups or certain dietary compounds as the onset and progression of obesity and suggested that gut microbiota is a mediator between these compounds and the inflammation associated with pathology. In this study, the objective was to evaluate the dietary intake of 108 overweight (OW), obese (OB), and normal-weight (NW) individuals and to analyze their gut microbiota profile to determine changes and associations with Body Mass Index (BMI) and diet. When individuals were compared by BMI, significant differences in fiber and monounsaturated fatty acids (MUFAs) intake were observed, showing higher adequacy for the NW group. The analysis of gut microbiota showed statistical differences for 18 ASVs; Anaerostipes and Faecalibacterium decreased in the OW/OB group, whereas the genus Oscillospira increased; the genus was also found in the LEFSe analysis as a biomarker for OW/OB. Roseburia faecis was found in a significantly higher proportion of NW individuals and identified as a biomarker for the NW group. Correlation analysis showed that adequation to nutritional recommendation for fiber indicated a higher abundance of Prevotella copri, linearly correlated with F. prausnitzii,Bacteroides caccae, and R. faecis. The same correlation was found for the adequation for MUFAs, with these bacteria being more abundant when the intake was adjusted to or below the recommendations. Keywords: gut microbiota; obesity; fiber; monounsaturated fatty acids; BMI 1. Introduction Western societies have undergone a process that involves major qualitative and quantitative changes in dietary habits. Thus, traditional diets have been replaced by diets characterized by a higher energy load and a decrease in fiber and complex carbohydrates. These changes, in addition to behavioral changes such as less physical activity, have resulted in an increase in worldwide overweight and obesity rates [ 1 ]. Obesity is the abnormal or excessive accumulation of fat that can be detrimental to health. It is of multifactorial origin, resulting from pathological processes and deriving from an interrelation between numerous factors [2,3]. According to the European Health Survey in Spain 2020, about 16% of the Spanish population suffers from obesity, while 37.60% of the population is overweight [ 4 ]. Other recent monitoring work revealed that Galicia is one of the regions of Spain in which there are higher rates of obesity in adults, reaching 26.7% [ 5 ]. Additionally, a study reported that during the COVID-19 confinement, 44% of participants indicated an increase in their body weight, with an average increase of 2.8 kg [ 6 ]. Thus, it is probably true that the current overweight rate of Galician people could now be higher than those in the cited reports [ 4 , 5 ]. Nutrients 2023,15, 3418. https://doi.org/10.3390/nu15153418 https://www.mdpi.com/journal/nutrients Nutrients 2023,15, 3418 2 of 19 Several authors have pointed out that the dietary habits of Galician people do not follow the same patterns as in the rest of Spain. However, together with the north of Portugal, they are included in the dietary model known as the Atlantic Diet [ 7 , 8 ]. Knowledge of the dietary patterns of the population is essential to understanding the potential impact of the strategies implemented to prevent the increase in obesity rates [9]. One approach to treating obesity in recent years involves the study of the gut microbiota, the results of which in both mice and humans describe remarkable differences between the gut microbiota of obese (OB) and normal-weight (NW) subjects. When there is an excess of body fat, colonic concentrations of Firmicutes increase by more than 50%, while those of Bacteroides decrease correlatively compared to NW subjects [ 10 ]. The composition of the gut microbiota of obese individuals is characterized by a decrease in genera such as Akkermansia,Alistipes,Faecalibacterium, and Oscillibacter [ 11 , 12 ] and an increase in Staphylococcus and Clostridium [13–16]. In addition, dietary patterns are considered modulators of the gut microbiota; for example, excessive fat consumption induces an imbalance in the gut microbiota, leading to gut barrier dysfunction, increased host body weight, and low-grade inflammation of adipose tissue [ 17 ]. A high-protein diet, on the other hand, increases the growth of bile-tolerant bacterial species (Alistipes,Bilophila, and Bacteroides) and decreases bacteria that hydrolyze disaccharides or polysaccharides into simple carbohydrates (Roseburia, Eubacterium rectale, and Ruminococcus bromii) [18]. Although there is available evidence about the differences in gut microbiota composition in both overweight or obese and normal-weight individuals, there is scarce information about potential biomarkers associated with certain dietary compounds. Thus, the hypothesis of the present study is that dietary intake, especially specific dietary components, is associated with different gut microbiota compositions in both overweight or obese and normal-weight subjects. Therefore, the aim of this study was to differentiate the gut microbiota of overweight (OW) and OB subjects from that of NW subjects, in a sample of Galician people, compare the results with previous studies to establish potential biomarkers and determine its association with dietary components potentially diminished or increased in each group under study. 2. Materials and Methods 2.1. Population and Sample Size This cross-sectional study is part of an international project about the search for novel biomarkers in diabetes and obesity in Iberian-America (CyTED project 918PTE0540). The study population for the present analysis included 108 individuals, ranging in age from 40 to 70 years , with habitual residence in Galicia (a northwest region of Spain). The sample size was estimated based on previous studies [ 19 – 21 ]. The participants were informed of the objectives of the study, and informed consent was obtained from each volunteer to participate in the study, and all data obtained were handled according to Spanish Law 3/2018 on personal data protection. This consent detailed the conditions of the research, highlighting the voluntary nature of participation, the possibility of withdrawing from the study even with the acceptance of the consent, and the anonymous treatment of the data for research purposes only. The following inclusion criteria were used: age between 40 and 70 years; absence of diagnosed pathologies, not having undergone medical treatment with hormones, corticoids, or having recently consumed any of the following substances: proton pump inhibitors, amphetamines, alpha-adrenergic drugs, alpha-blockers, beta-blockers, opiates, calciumantagonists, neuroleptics, tricyclic antidepressants, phenothiazines, central nervous system stimulants (cocaine, etc.); not having consumed any supplement containing probiotics or prebiotics during the previous 2 months; in the case of women, not being pregnant Ethical approval for this study was obtained from The Regional Ethics Committee for Clinical Research (Galician Health Service, SERGAS, n ◦ 2018/270) in compliance with the Nutrients 2023,15, 3418 3 of 19 Declaration of Helsinki of 1964 regarding privacy, confidentiality, and informed consent. All experiments were carried out in accordance with approved guidelines and regulations. 2.2. Anthropometric Measures Anthropometric measurements were obtained. Weight was determined using an InBody 127 digital scale (InBody, Tokyo, Japan). Height was measured with a portable stadiometer (ADE MZ10042; Hamburg, Germany), with the subject upright and in balance, without bending the knees. Subsequently, the Body Mass Index (BMI) was calculated using the Quetelet formula: BMI = weight (kg)/[height (m)] 2 . According to the classification ranges proposed by the Spanish Obesity Society [ 22 ], three volunteers were grouped in groups according to their BMI: 18–24.9 kg/m 2 for NW, 25–29.9 kg/m 2 for OW, and ≥ 30 OB kg/m 2 . 2.3. Dietary Information A 72 h dietary record was completed by the volunteers for 3 days (2 workdays and 1 weekend day). The volunteers were given instructions on how to record their dietary intake. They were also asked to provide information on the portions of food consumed, the ingredients and techniques used in cooking, and the type and quantity of beverages consumed. The mean daily energy and nutrient intake of each volunteer were calculated using the open software “diet calculator”, available on the website of the Endocrinology and Clinical Nutrition Research Centre [ 23 ], which is based on Spanish foods. Data obtained from the software were compared to the nutritional objectives for the Spanish adult population published by the Spanish Society of Community Nutrition (SENC, 24) to determine their nutritional adequacy. The data obtained were compared by sex and by BMI of volunteers. Data about micronutrient (minerals and vitamins) intake were compared to Reference Dietary Intakes (RDI) established by the Spanish Federation of Nutrition, Food and Dietetics Societies [24]. The data obtained were compared by sex and BMI of the volunteers. 2.4. Fecal Sample Collection and DNA Extraction Volunteers received detailed instructions to collect fecal samples and were provided with a sterile container that should deliver to the laboratory along with the 72 h dietary record. Samples should have been delivered within two hours after defecation or, in the case of not being able to do it, they should have been immediately frozen at − 20 ◦ C after deposition and delivery to the laboratory where they were conserved frozen until treated for analysis. DNA from fecal samples was extracted using the Dneasy Powersoil kit (Qiagen ® , Hilden, Germany) following the manufacturer’s instructions. Extracted DNA was then quantified using a Qubit ™ 4 fluorometer (Invitrogen, Thermo Fisher Scientific, Carlsbad, CA, USA) and the Qubit kit 1X dsDNA High Sensitivity (Thermo Fisher Scientific, Inc., Karlsruhe, Germany). After quantification, DNA samples were frozen and stored at − 20 ◦C until further analysis. 2.5. 16S rRNA Amplicon Sequencing For 16S rRNA amplicon sequencing, 2 µ L of DNA extracted from each sample was used to construct the libraries, and the Ion GeneStudio TM S5 System (Life Technologies, Carlsbad, CA, USA) was used. For this purpose, the 16S hypervariable regions were amplified with two sets of primers, v2–4–8 and v3–6, 7–9, and the libraries were prepared by using the Ion 16S TM Metagenomics Kit (Life Technologies) and the Ion Xpress TM Plus Fragment Library Kit (Life Technologies). Libraries containing equal amounts of PCR products pooled with a barcode were prepared by using the Ion Xpress TM Barcode Adapters Kit (Life Technologies). Then, these libraries were quantified by using the Ion Universal Library Quantitation Kit (Life Technologies). Next, 10 pM of each library was pooled and loaded on an Ion One- Touch ™ 2 System (Life Technologies), which automatically performs template preparation and enrichment. Template-positive ion sphere particles were enriched with Dynabeads ™ MyOne ™ Streptavidin C1 magnetic beads (Invitrogen, Carlsbad, CA, USA) by using an Ion Nutrients 2023,15, 3418 4 of 19 One Touch ES instrument. Finally, an Ion 520 TM chip (Life Technologies) was loaded with the samples on an Ion GeneStudioTM S5 System sequencer using the Ion 520™ & Ion 530™ Loading Reagents supplied in the OT2-Kit (Life Technologies). 2.6. Statistical and Bioinformatic Analysis Student’s t-test for independent samples was used to compare qualitative variables between different groups (sex or BMI). The X2 test with Yates’s correction was used to compare frequencies. In all cases, the obtained differences were considered statistically significant if the pvalue was less than 0.05. A two-way ANOVA was used to determine significative differences for time and substrates as the two covariates in the general linear model using Tukey’s analysis. For significant differences (p< 0.05) a one-way ANOVA was conducted for each substrate comparing 0, 5, 10, and 24 h. Similarly, each substrate was compared using two-way ANOVA; results were significant when p< 0.05. The software SPSS ® v.27 for Windows (SPSS Inc., Chicago, IL, USA) was used for these analyses. For the analysis of 16S rRNA amplicon sequencing, the raw sequencing reads were obtained from the Torrent Suite software (v. 5.12.2.) as fastq files. The fastq files were processed with QIIME 2 software v. 2022.11 [ 25 ]. To produce amplicon sequence variants (ASVs), the DADA2 method was used for quality filtration (Q score ≥ 30), trimming, denoising, and dereplication. Samples with features (taxa) with a total abundance (summed across all samples) of <10 were removed. Taxonomy was assigned to ASVs by using the q2-feature-classifier classify-sklearn naïve Bayes taxonomy classifier, which was compared to the Greengenes 13_8 99% operational taxonomic unit (OTU) reference sequences. STAMP software (v 2.1.3) for the “Statistical Analysis of Taxonomic and Functional Profiles” [ 26 ] was used to determine statistical differences in the obtained ASVs at the species level. Kruskal–Wallis H test with post hoc Tukey–Kramer test was employed. The OTUs with taxonomic information, obtained in QIIME2, were used together with a metadata file, in text format, for their analyses in the free platform Microbiome Analyst, “a comprehensive statistical, functional and integrative analysis of microbiome data” [ 27 ]. alpha- and betadiversity, correlation, and LEfSe analysis were carried out. 3. Results 3.1. Nutritional Analysis and Adequation to the Objectives and the Recommended Daily Intakes for the Spanish Population A total of 108 subjects completed a 72 h dietary recall, and their anthropometric measurements were obtained. Of these, 67 (62%) were women and 41 (38%) were men. The average age of the subjects was 51.0 ± 8.0 years, and the average kilocalorie intake was 2344.0 ± 556.9 kcal/day. Comparing this energy intake by sex, a significantly higher intake (p= 0.04) was observed for men (2502.6 ± 538.3) than for women (2247.0 ± 537.0). Data obtained for macronutrients and other parameters are shown in Table 1. As it can be observed, the average total carbohydrate intake in terms of % of energy is deficient, 88.1% of the individuals do not achieve the recommendations. The same occurs for fiber intake (84.3% of individuals are in deficit). Regarding the lipid profile, 89.6% of the participants are above the objectives, which indicates a diet rich in fat, especially in saturated fat since 88% of the volunteers showed to possess a consumption above the recommendations. For protein, it is necessary to indicate that this macronutrient does not appear in the recommendations for the Spanish population, since its determination is depending on the other two macronutrients. The percent for protein usually recommended is 10–15% of total energy. The data obtained for the participants of this study indicated an adequation of 38.9% and an excess of 61.1%. For simple sugar, only 13 individuals showed to have a consumption below a 10%, being an average intake of 18.1 ± 7.4%. Regarding fruit and vegetable consumption, the average intake of fruit and vegetables was 1.8 ± 1.5 servings, which is <50% of the recommended five daily servings; only 4.6% of the population surveyed had the recommended Nutrients 2023,15, 3418 5 of 19 intake, while 94.4% did not meet the recommendations. Regarding other parameters such as alcohol consumption, most of the volunteers showed to be below the recommendation of 1 and 2 Standard Drink Units (SDUs) of alcoholic beverages, for women and men, respectively. Regarding water consumption, 45.4% of the participants did not reach the recommendations for water consumption. Table 1. Participants’ diet quality in terms of a caloric lipid profile: adequacy to nutritional objectives for the Spanish population (n= 108). Results are expressed as the average ± standard deviation. Diet adequacy is expressed as the number of individuals meeting the nutritional goals and in brackets is expressed as percent. DIET ADEQUACY CALORIC PROFILE NUTRITIONAL OBJECTIVES VALUES OF PARTICIPANTS’ DIET DÉFICIT ADEQUATE EXCESS Carbohydrates (% Energy) 50–55 38.9 ±7.8 96 (88.1%) 11 (10.1%) 1 (0.9%) Fiber (g/1000 kcal) >14 11.7 ±7.7 91 (84.3%) 15 (13.9%) 2 (1.9%) Lipids (% Energy) 30–35 41.8 ±8.0 7 (6.4%) 15 (13.9%) 86 (79.6%) LIPID PROFILE SFA (% Energy) ≤7–8 12.0 ±3.2 - 13 (0.0%) 95 (88%) MUFA (% Energy) 20 20.8 ±16.1 36 (33.3%) 45 (41.7%) 27 (25.0%) PUFA (% Energy) 5 5.9 ±3.6 39 (38.0%) 23 (21.2%) 62 (57.4%) Cholesterol (mg) <300 347.0 ±138.6 0 (0.0%) 46 (42.6%) 62 (57.4%) OTHERS Water (mL) 2000 2063.3 ±627.9 49 (45.4%) 59 (54.6%) 0 (0.0%) Fruits and vegetables 5 portions 1.8 ±1.5 102 (94.4%) 5 (4.6%) 1 (0.9%) Sugar (% Energy) 6–10 18.1 ±7.4 - 13 (12.0%) 95 (88.0%) Alcohol (g) ≤1 SDU women ≤2 SDU men 10.84 ±44.43 - 100 (92.6%) 8 (7.4%) SFA: Saturated Fatty Acids; MFA: Monounsaturated Fatty Acids; PUFA: Polyunsaturated Fatty Acids; SDU: Standard Drink Unit. When the data obtained were compared by sex (Table S1), there were some significant differences in dietary patterns between men and women. Thus, in general, women accomplish more nutritional objectives than men. On average, men have a higher intake of protein, a lower consumption of carbohydrates, and a higher consumption of fat than women. Regarding the lipid profile, statistical differences were found for SFA, where women, once again, showed to better accomplish the nutritional objectives for the Spanish population. Comparing intake data according to BMI (Table 2), no statistical differences were found among NW, OW, and OB subjects for all parameters investigated with the exception of total energy, fiber, and MUFAs, for which statistical differences were found. In the case of fiber, a better adequation (32.5%) was observed for NW individuals than for OW/OB (15.2 and 14.3, respectively). For MUFAs, only 14.3% of the OB volunteers accomplish the objectives, whereas for the OW and NW groups, the accomplishment was higher, 36.4 and 25%, respectively. For total energy, 2284.0 ± 658.6 kcal/day were obtained for the NW group, whereas for the OW and OB group, the total energy obtained was 2221.3 ± 497.2 and 2498.4 ± 459.1 kcal/day, respectively. A significantly higher caloric intake was obtained for the OB group (p= 0.0356). Regarding water, fruit, vegetables, and sugar, no statistical differences were observed according to BMI. However, in general, the NW and the OW groups showed higher adequacy for water and alcohol consumption. For sugar consumption, the worst adequacy was obtained for the NW group, but these values included all the simple sugar consumed, including that provided for fruits and not only the added simple sugar, and this is the group consuming more fruits and vegetables. Nutrients 2023,15, 3418 6 of 19 Table 2. Macronutrient intake for normal weight (NW), overweight (OW), or obese (OB) subjects, and its adequation to the nutritional objectives for the Spanish population (n= 108). Caloric profile, lipidic profile, and others are shown. Results are expressed with mean ± standard deviation. Diet adequacy is expressed as the number of individuals meeting the nutritional goals and in brackets is expressed as percent. NW (n= 40) OW (n= 35) OB (n= 33) CALORIC PROFILE Nutritional Objectives Mean ±SD Intake Adequacy: n(%) Mean ±SD Intake Adequacy: n(%) Mean ±SD Intake Adequacy: n(%) pValue Carbohydrates (% Energy) 50–55% 40.3 ±7.1 5 (12.5%) 37.4 ±7.7 1 (3.0%) 38.8 ±8.6 4(11.4%) 0.274 Lipids (% Energy) 30–35% 40.6 ±6.3 6 (15.0%) 43.6 ±9.6 5 (15.2%) 41.9 ±7.5 5 (14.3%) 0.280 Fiber (g/1000 Kcal) >14 14.2 ±9.5 13 (32.5%) 12.5 ±10.14 4 (12.0%) 9.1 ±2.9 5 (14.3%) 0.038 LIPID PROFILE SFA (% Energy) ≤7–8 11.8 ±2.8 3 (7.5%) 11.9 ±3.0 4 (12.1%) 15.5 ±8.1 0 (0.0%) 0.559 MUFA (% Energy) 20 20.3 ±5.7 10 (25.0%) 19.4 ±5.7 12 (36.4%) 6.5 ±5.3 5 (14.3%) <0.001 PUFA (% Energy) 5 5.8 ±2.1 12 (30.0%) 6.5 ±5.3 19 (57.6%) 5.4 ±2.7 6 (17.4%) 0.874 Cholesterol (mg) <300 mg 340.3 ±137.7 19 (47.5%) 348.0 ±129.8 11 (33.0%) 354.1 ±152.1 10 (28.6%) 0.915 OTHERS Water (mL) 2000 mL 2305.36 ±487.6 23 (57.5%) 2128.0 ±682.2 20 (57.4%) 2098.1 ±736.4 16 (48.5%) 0.751 Fruits and vegetables 5 portions 1.9 ±1.5 3 (7.5%) 1.3 ±1.4 1 (2.8%) 2.2 ±1.5 1 (3.0%) 0.785 Sugar 6–10 20.0 ±9.0 1 (2.5%) 19.0 ±7.1 5 (14.3%) 16.0 ±5.1 7 (21.2%) 0.632 Alcohol (g) ≤1 SDU women ≤2 SDU men 3.8 ±9.8 39 (97.5%) 4.0 ±8.7 32 (97.0%) 3.9 ±8.8 31 (88.6%) 0.298 SFA: Saturated Fatty Acids; MFA: Monounsaturated Fatty Acids; PUFA: Polyunsaturated Fatty Acids; SDU: Standard Drink Unit. Regarding the intake of micronutrients, a comparison between women and men can be seen in Table S2. Significant differences were found between sexes for the intake of thiamine, riboflavin, niacin, vitamin B6, vitamin E, phosphorus, and iron, with the average daily intake being higher in men than in women for all the micronutrients. Regarding adequacy, however, women possess a major percentage of adequacy than men. When comparing micronutrient intake by BMI (Table 3), it was found that NW subjects consumed higher amounts of some micronutrients such as iron, iodine, and ascorbic acid than OW and OB patients, whereas tocopherol intake was significantly higher for OW subjects and OB patients, and a higher intake of calciferol with respect to both NW and OW subjects was observed. Compliance with intake with current recommendations was higher in NW subjects than in OW subjects for calcium, iron, iodine, zinc, ascorbic acid, and calciferol. Only in the case of magnesium were the highest compliance rates found in OB subjects with respect to NW and OW patients. Table 3. Micronutrient intake for normal weight (NW), overweight (OW), or obese (OB) subjects, and its adequation to the Dietary Reference Intakes (DRI) for the Spanish population (n= 108). Diet adequacy is expressed as the number of individuals meeting the DRI and in brackets is expressed as percent. NW (n= 40) OW (n= 35) OB (n= 33) Vitamins Average ±SD Intake Adequacy n(%) Average ±SD Intake Adequacy n(%) Average ±SD Intake Adequacy n(%) pValue Thiamine (mg) 1.5 ±0.8 32 (80.0%) 1.9 ±0.9 31 (88.6%) 1.4 ±0.3 29 (87.9%) 0.009 Riboflavin (mg) 1.7 ±0.5 30 (75.0%) 2.1 ±0.6 31 (88.6%) 1.7 ±0.4 27 (81.9%) 0.007 Nutrients 2023,15, 3418 7 of 19 Table 3. Cont. NW (n= 40) OW (n= 35) OB (n= 33) Vitamins Average ±SD Intake Adequacy n(%) Average ±SD Intake Adequacy n(%) Average ±SD Intake Adequacy n(%) pValue Niacin (mg) 30.5 ±10.7 30 (75.0%) 40.4 ±14.5 16 (45.7%) 31.6 ±7.7 25 (75.8%) 0.0005 Vitamin B6(µg) 2.0 ±0.8 35 (87.5%) 2.3 ±1.1 33 (94.3%) 2.0 ±0.6 30 (90.9%) 0.159 Folic acid (µg) 281.3 ±126.3 13 (32.5%) 278.3 ±105.2 10 (28.6%) 255.3 ±74.6 8 (24.2%) 0.537 Vitamin B12 (µg) 6.1 ±6.0 40 (100%) 6.4 ±2.5 35 (100%) 5.6 ±2.8 33 (100%) 0.697 Vitamin C (mg) 151.2 ±87.7 35 (87.5%) 166.2 ±79.6 33 (94.3%) 160.7 ±68.5 33 (100%) 0.738 Vitamin A (µg) 798.4 ±603.1 24 (60.0%) 750.5 ±452.7 19 (54.3%) 745.0 ±406.8 17 (51.5%) 0.868 Vitamin D (µg) 2.9 ±3.2 8 (20.0%) 4.6 ±6.0 11 (31.4%) 4.5 ±6.5 11 (33.3%) 0.321 Vitamin E (mg) 8.3 ±8.1 5 (12.5%) 7.8 ±9.9 4 (11.4%) 5.9 ±5.6 2 (6.1%) 0.416 Minerals Calcium (mg) 719.8 ±297.1 7 (17.5%) 841.2 ±415.0 12 (34.3%) 792.9 ±348.4 10 (30.3%) 0.331 Magnesium (mg) 325.7 ±134.9 23 (57.5%) 368.9 ±95.8 23 (65.7%) 308.8 ±81.0 15 (45.5%) 0.063 Potassium (mg) 3086.7 ±904.1 22 (55.0%) 4044.5 ± 1135.9 26 (74.3%) 3511.8 ±745.6 24 (72.7%) 0.0001 Phosporus (mg) 1415.5 ±500.5 38 (95.0%) 1716.9 ±472.9 34 (97.1%) 1436.8 ±380.6 32 (97.0%) 0.009 Iron (mg) 16.7 ±9.0 23 (57.5%) 18.3 ±5.8 29 (82.9%) 14.0 ±2.8 21 (63.6%) 0.035 Iodine (µg) 184.4 ±150.3 16 (40.0%) 347.5 ±197.4 25 (71.4%) 292.5 ±153.6 25 (75.8%) 0.0002 Zinc (mg) 24.4 ±78.7 29 (72.5%) 14.1 ±3.5 34 (97.1%) 10.8 ±2.9 27 (81.8%) 0.0445 Sodium (mg) 2610.9 ±677.5 6 (15.0%) 5609.5 ± 1219.7 0 (0.0%) 3877.1 ±346.0 0 (0.0%) <0.0001 3.2. Analysis of the Gut Microbiota Composition 3.2.1. Alpha- and Beta-Diversity A total of 95 fecal samples were collected from the volunteers. A first analysis between groups (NW, OW, and OB) was carried out; however, no differences were obtained between the OW and OB groups. Therefore, a second analysis conducted by grouping OW and OB was developed. Although the BMI is the most extended method, in clinical practice, to classify overweight and obesity in adults, it is not the most adequate to determine the amount of body fat. In addition, the nutritional analysis has shown that, in terms of adequacy, the individuals included in the NW group accomplish in higher proportion the nutritional objectives and the DRI for the Spanish population than the OW and OB groups (for example, the % of adequacy for the group of OW and OB is 0, whereas 15% of the individuals in the NW group meet the RDI) To investigate alpha-diversity, the Chao1 richness and Shannon diversity (richness and abundance) indices were determined. No statistical differences were found between the NW and OW/OB groups for Chao1 (ANOVA, p= 0.1953) nor for Shannon (p= 0.711). For beta-diversity, calculated by Bray-Curtis, no statistical differences were found between groups (F-value: 0.7111; R-squared: 0.0079266; p-value: 0.768) either. See Figure 1. 3.2.2. Relative Abundance of Bacteria The relative frequency (Figure 2) at the phylum level (a) showed an increase in the Bacteroidetes phlylum in the OW/OB (35.5%) group in comparison with the NW group (33.2%), whereas the Firmicutes phylum decreased in the OW/OB group (53.3% vs. 56.3%) as well as Actinobacteria (3.54 vs. 3.90%). At the genus level (Figure 1b), the main identified bacteria were Bacteroides and Prevotella, contributing to the Bacteroidetes phylum, while Blautia and Ruminoccocus formed the Firmicutes phylum, and Bifidobacterium contributes to Actinobacteria phylum; in the Proteobacteria phylum, the main genus was Sutterella and Succinivibrio. Finally, at the species level, 50 species were identified, with the main identified ones being Prevotella copri,Bacteroides uniformis,Bifidobacterium adolescentis, and Bifidobacterium longum, among others. Nutrients 2023,15, 3418 8 of 19 Nutrients 2023, 15, x FOR PEER REVIEW 8 of 21 (for example, the % of adequacy for the group of OW and OB is 0, whereas 15% of the individuals in the NW group meet the RDI) To investigate alpha-diversity, the Chao1 richness and Shannon diversity (richness and abundance) indices were determined. No statistical differences were found between the NW and OW/OB groups for Chao1 (ANOVA, p = 0.1953) nor for Shannon (p = 0.711). For beta-diversity, calculated by Bray-Curtis, no statistical differences were found between groups (F-value: 0.7111; R-squared: 0.0079266; p-value: 0.768) either. See Figure 1. Figure 1. (a) Shannon index and (b) Chao1 index (alpha-diversity), in red for normal-weight individuals (NW) and, in blue for overweight/obese (OW/OB); (c) beta-diversity determined by principal coordinates analysis (PCoA) based on the Bray-Curtis dissimilarity index; red NW group and blue OW/OB group. 3.2.2. Relative Abundance of Bacteria The relative frequency (Figure 2) at the phylum level (a) showed an increase in the Bacteroidetes phlylum in the OW/OB (35.5%) group in comparison with the NW group (33.2%), whereas the Firmicutes phylum decreased in the OW/OB group (53.3% vs. 56.3%) as well as Actinobacteria (3.54 vs. 3.90%). At the genus level (Figure 1b), the main identified bacteria were Bacteroides and Prevotella, contributing to the Bacteroidetes phylum, while Blautia and Ruminoccocus formed the Firmicutes phylum, and Bifidobacterium contributes to Actinobacteria phylum; in the Proteobacteria phylum, the main genus was Sutterella and Succinivibrio. Finally, at the species level, 50 species were identified, with the main identified ones being Prevotella copri, Bacteroides uniformis, Bifidobacterium adolescentis, and Bifidobacterium longum, among others. Regarding the statistical differences, the analysis using the software STAMP showed statistical differences for 18 ASVs (see table in Supplementary Material). In Figure 3, it is possible to see the box plots for three identified bacterial genera and 1 other species. In the graphics, it can be observed as the genera Anaerostipes and Faecalibacterium decreased in Figure 1. ( a ) Shannon index and ( b ) Chao1 index (alpha-diversity), in red for normal-weight individuals (NW) and, in blue for overweight/obese (OW/OB); ( c ) beta-diversity determined by principal coordinates analysis (PCoA) based on the Bray-Curtis dissimilarity index; red NW group and blue OW/OB group. Nutrients 2023, 15, x FOR PEER REVIEW 9 of 21 the OW/OB group whereas the genus Oscillospira increased. For the species, R. faecis, the proportion of sequence obtained was statistically higher in NW individuals than in OW/OB. (a) (b) Figure 2. Relative abundance of different bacterial phyla and genera. Bacterial composition (relative abundance, %) was determined using 16S rRNA amplicon sequencing at the phylum (a) and genus (b) levels. The x-axis shows the different groups evaluated (NW vs. OW/OB). Due to the large number of reported bacteria, only the top 19 most abundant genera were included in the legend. NW: normal weight; OW/OB, overweight/obese individuals. Figure 2. Relative abundance of different bacterial phyla and genera . Bacterial composition (relative abundance, %) was determined using 16S rRNA amplicon sequencing at the phylum ( a ) and genus ( b ) levels. The x-axis shows the different groups evaluated (NW vs. OW/OB). Due to the large number of reported bacteria, only the top 19 most abundant genera were included in the legend. NW: normal weight; OW/OB, overweight/obese individuals. Nutrients 2023,15, 3418 9 of 19 Regarding the statistical differences, the analysis using the software STAMP showed statistical differences for 18 ASVs (see table in Supplementary Material). In Figure 3, it is possible to see the box plots for three identified bacterial genera and 1 other species. In the graphics, it can be observed as the genera Anaerostipes and Faecalibacterium decreased in the OW/OB group whereas the genus Oscillospira increased. For the species, R. faecis, the proportion of sequence obtained was statistically higher in NW individuals than in OW/OB. Nutrients 2023, 15, x FOR PEER REVIEW 10 of 21 Figure 3. Box plots obtained in the statistical analysis with STAMP for the genera Anaerostipes, Faecalibacterium, Oscillospira, and the species R. faecis. Blue represents the NW group, and orange is the OW/OB group. 3.2.3. Correlation Analysis: Microbiota-Fiber, Microbiota-MUFAs Since statistical differences were found for fiber and MUFAs intake in the nutritional analysis, a correlation analysis was carried out with these two factors to establish a linear relationship among the identified species. Individuals were, in this case, classified depending on their adequation to the recommended intake, reaching or not reaching the recommendation standards for an adequate, lower, or high consumption in the case of MUFAs. Figure 4a,b show the obtained results. As can be seen in Figure 4a, P. copri was more abundant in individuals achieving recommendations for fiber, and this species was positively correlated with F. prausnizii, B. ovatus, B. caccae, B. uniformis, and R. faecis. A negative correlation was found for B. adolescentis, Collinsella aerofaciens, Dorea formicigenerans, Parabacteroides distasonis, Ruminococcus bromii, and B. longum. The bacteria positively correlated with fiber were those more abundant in NW individuals (see Supplementary Material Figure S1). Regarding MUFAs (Figure 4b), P. copri was more abundant in those individuals with adequate consumption to recommendations, followed by individuals with low consumption, and the lowest abundance was observed for those individuals with high consumption. For this species, a positive correlation was observed with B. caccae, F. prausnitzii, R. faecis, and B. ovatus. Figure 3. Box plots obtained in the statistical analysis with STAMP for the genera Anaerostipes, Faecalibacterium,Oscillospira, and the species R. faecis. Blue represents the NW group, and orange is the OW/OB group. 3.2.3. Correlation Analysis: Microbiota-Fiber, Microbiota-MUFAs Since statistical differences were found for fiber and MUFAs intake in the nutritional analysis, a correlation analysis was carried out with these two factors to establish a linear relationship among the identified species. Individuals were, in this case, classified depending on their adequation to the recommended intake, reaching or not reaching the recommendation standards for an adequate, lower, or high consumption in the case of MUFAs. Figure 4a,b show the obtained results. As can be seen in Figure 4a, P. copri was more abundant in individuals achieving recommendations for fiber, and this species was positively correlated with F. prausnizii,B. ovatus,B. caccae,B. uniformis, and R. faecis. A negative correlation was found for B. adolescentis,Collinsella aerofaciens,Dorea formicigenerans,Parabacteroides distasonis, Ruminococcus bromii, and B. longum. The bacteria positively correlated with fiber were those more abundant in NW individuals (see Supplementary Material Figure S1). Regarding MUFAs (Figure 4b), P. copri was more abundant in those individuals with adequate consumption to recommendations, followed by individuals with low consumption, and the lowest abundance was observed for those individuals with high consumption. For this species, a positive correlation was observed with B. caccae,F. prausnitzii,R. faecis, and B. ovatus. Nutrients 2023,15, 3418 16 of 19 Supplementary Materials: The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/nu15153418/s1, Figure S1: Correlation analysis. Figures show the obtained results for the correlation analysis between identified bacterial species and BMI of individual (NW in red and OW/OB in green, groups) Red lines showed a positive correlation among bacterial species whereas blue lines showed a negative correlation; Table S1: Participants’ diet quality by sex, in terms of caloric profile and lipid quality: adequacy to nutritional objectives for the Spanish population.; Table S2: Micronutrient intake and adequation to the Dietary Reference Intakes (DRI) for the Spanish population in women and men. Author Contributions: Conceptualization, A.C. and A.C.-C.; methodology, L.S.-L. and P.A.-L.; software, A.C.-C.; validation, A.C.-C.; formal analysis, J.M.M.; writing—original draft preparation, L.S.-L. and B.I.V.; writing—review and editing, A.C.-C., J.M.M. and A.C.; supervision, A.C.; funding acquisition, A.C. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Ministry of Economy and Competitiveness through the State Program of I+D+I Oriented to the Challenges of Society 2017–2020 (International Joint Pro-gramming 2018). Project PCI2018-093245. Institutional Review Board Statement: Ethical approval for this study was obtained from The Regional Ethics Committee for Clinical Research (Galician Health Service, SERGAS, n ◦ 2018/270) in compliance with the Declaration of Helsinki of 1964 regarding privacy, confidentiality, and informed consent. All experiments were carried out in accordance with approved guidelines and regulations. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: The data presented in this study are available on request from the corresponding author. Acknowledgments: The authors thank the CyTED and each National Organism for Science and Technology for funding the IBEROBDIA project (918PTE0540). 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