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Background and aim Fecal microbiome disturbances are linked to different human diseases. In the case of obesity, gut microbiota seems to play a role in the development of low-grade inflammation. The purpose of the present study was to identify specific bacterial families and genera associated with an increased obesity-related inflammatory status, which would allow to build a regression model for the prediction of the inflammatory status of obese and overweight subjects based on fecal microorganisms. Methods A total of 361 volunteers from the Obekit trial (65 normal-weight, 110 overweight, and 186 obese) were classified according to four variables: waist/hip ratio (≥0.86 for women and ≥1.00 for men), leptin/adiponectin ratio (LAR, ≥3.0 for women and ≥1.4 for men), and plasma C-reactive protein (≥2 mg/L) and TNF levels (≥0.85 pg/mL). An inflammation score was designed to classify individuals in low (those subjects who did exceed the threshold value in 0 or 1 variable) or high inflammatory index (those subjects who did exceed the threshold value in 2 or more variables). Fecal 16 S rRNA sequencing was performed for all participants, and differential abundance analyses for family and genera were performed using the MicrobiomeAnalyst web-based platform. Results Methanobacteriaceae, Christensenellaceae, Coriobacteriaceae, Bifidobacteriaceae, Catabacteriaceae, and Dehalobacteriaceae families, and Methanobrevibacter, Eggerthella, Gemmiger, Anaerostipes, and Collinsella genera were significantly overrepresented in subjects with low inflammatory index. Conversely, Carnobacteriaceae, Veillonellaceae, Pasteurellaceae, Prevotellaceae and Enterobacteriaceae families, and Granulicatella, Veillonella, Haemophilus, Dialister Parabacteroides, Prevotella, Shigella, and Allisonella genera were more abundant in subjects with a high inflammatory index. A regression model adjusted by BMI, sex, and age and including the families Coriobacteriaceae and Prevotellaceae and the genus Veillonella was developed. Conclusion A microbiota-based regression model was able to predict the obesity-related inflammatory status (area under the ROC curve = 0.8570 ± 0.0092 Harrell's optimism-correction) and could be useful in the precision management of inflammobesity.

Ultra-processed foods (UPFs) consumption could affect gut microbiota diversity and profile. We aimed to evaluate the effects of UPFs on microbiota, considering the role of sex. The consumption of UPFs (using NOVA criteria) was assessed with a validated 137-item food-frequency questionnaire. Participants (n = 359) were classified into less than three servings per day (n = 96) of UPFs and more than five (n = 90). Women and men were subclassified following the same criteria. 16S rRNA sequencing was performed from DNA fecal samples, and differences in microbiota were analyzed using EdgeR. The relationship between UPFs and bacteria was assessed by Spearman correlation and comparison of tertiles of consumption. Women who consumed more than five servings/day of UPFs presented an increase in Acidaminococcus, Butyrivibrio, Gemmiger, Shigella, Anaerofilum, Parabacteroides, Bifidobacterium, Enterobacteriales, Bifidobacteriales and Actinobacteria and a decrease in Melainabacter and Lachnospira. Bifidobacterium, Bifidobacteriales and Actinobacteria was positively associated with pizza and Actinobacteria with industrially processed dairy in women. Men who consumed more than five servings/day presented an increase of Granulicatella, Blautia, Carnobacteriaceae, Bacteroidaceae, Peptostreptococcaceae, Bacteroidia and Bacteroidetes and a decrease of Anaerostipes and Clostridiaceae. Bacteroidia and Bacteroidetes correlated positively with industrially processed meat. This study suggests that UPFs may affect microbiota composition differently in women and men.

The MD (Mediterranean diet) is recognized as one of the healthiest diets worldwide and is associated with the prevention of cardiovascular and metabolic diseases. Dietary habits are considered one of the strongest modulators of gut microbiota, which seem to play a significant role in health status of the host. The purpose of the present study was to evaluate interactive associations between gut microbiota composition and habitual dietary intake in 360 Spanish adults from the Obekit cohort (normal weight, overweight, and obese participants). Dietary intake and adherence to the MD tests were administered and fecal samples were collected from each participant. Fecal 16S rRNA (ribosomal Ribonucleic Acid) gene sequencing was performed and checked against the dietary habits. MetagenomeSeq was the statistical tool applied to analyze data at the species taxonomic level. Results from this study identified several beneficial bacteria that were more abundant in the individuals with higher adherence to the MD. Bifidobacterium animalis was the species with the strongest association with the MD. Some SCFA (Short Chain Fatty Acids) -producing bacteria were also associated with MD. In conclusion, this study showed that MD, fiber, legumes, vegetable, fruit, and nut intake are associated with an increase in butyrate-producing taxa such as Roseburia faecis, Ruminococcus bromii, and Oscillospira (Flavonifractor) plautii.

Obesity has been related to intestinal dysbiosis and the modification of gut microbiota composition by dietary strategies becomes a promising strategy to help manage obesity. The aim of the current study was to evaluate the effect of two weight-loss diets on the composition and functional profile of gut microbiota. 55 men and 124 women with BMI > 25 kg/m2 were randomly assigned to moderately high-protein (MHP) or low-fat (LF) diet. Differences in fecal bacteria abundance (based on 16 s rRNA sequencing) between before and after 4 months of calorie restriction was analyzed using EdgeR tool in MicrobiomeAnalyst platform. Bacterial functional profile was predicted using Tax4Fun and metagenomeSeq analysis. Significant KEGG Orthology (KO) terms were selected for the metabolomic study using chromatography. After the intervention, MHP-men showed a significant decrease in Negativicutes, Selenomonadales, Dielma and Dielma fastidiosa. LF-men showed a significant increase in Bacilli, Lactobacillales, Christensenellaceae, Peptococcaceae, and Streptococcaceae, Peptococcus, Streptococcus and Christensenella, Duncaniella dubosii_CP039396_93.49%, Roseburia sp_AB744234_98.96% and Alistipes inops_KJ572413_99.57%. MHP-women increased Pasteurellales, Phascolarctobacterium succinatutens, Ruthenibacterium lactatiformans_LR215981_99.55% and decreased in Phascolarctobacterium succinatutens_NR112902_99.56%. Finally, LF-women presented a significant decrease in Bacteroides clarus and Erysipelothrix inopinata_CP060715_84.4%. Surprisingly, no matching bacterial changes were found between these four groups. A total of 42 KO, 10 metabolic pathways and 107 related metabolites related were found implicated in these bacterial changes. Seven metabolites were confirmed in plasma. Weight-loss-related-changes in gut microbiome composition and the functional profile occur in a sex- and diet-related manner, showing that women and men could differentially benefit from the consumption of MHP and LF diets. NCT02737267, 10th March 2016 retrospectively registered.

Background: Unbalances in microRNAs (miRNA) and gut microbiota patterns have been proposed as putative factors concerning onset and development of obesity and other metabolic diseases. However, the determinants that mediate the interactions between miRNAs and the gut microbiome impacting on obesity are scarcely understood. Thus, the aim of this article was to investigate possible interactions between circulating miRNAs and gut microbiota composition in obesity. Method: The analyzed sample comprised 78 subjects with obesity [cases, body mass index (BMI): 30 – 40 kg/m2] and 25 eutrophic individuals (controls, BMI £ 25 kg/m2). The expression of 96 miRNAs was investigated in plasma of all individuals using miRCURY LNA miRNA Custom PCR Panels (Exiqon). Bacterial DNA sequencing was performed following the Illumina 16S protocol. The FDR (Benjamini-Hochberg test, q-value) correction was used for multiple comparison analyses.Results: A total of 26 circulating miRNAs and 12 bacterial species were found differentially expressed between cases and controls. Interestingly, an interaction among three miRNAs (miR-130b-3p, miR-185-5p, and miR-21-5p) with Bacteroides eggerthi, and BMI levels was evidenced (r2= 0.148, P= 0.004). Those miRNAs that correlated with obesity-associated gut bacteria abundance are known to regulate target genes that participate in metabolism-related pathways, such as fatty acid degradation, carbohydrate digestion and absorption, insulin signaling, and glycerolipid metabolism. Conclusion: This study characterized an interaction between the abundance of 4 bacterial species and 14 circulating miRNAs in relation to body adiposity. Moreover, the current study also suggests that miRNAs may serve as a communication mechanism between the gut microbiome and human hosts. Clinical trial registration: clinicaltrials.gov (reg. no. NCT02737267).

The gut microbiome has been recognized as a tool for understanding adiposity accumulation and for providing personalized nutrition advice for the management of obesity and accompanying metabolic complications. The genetic background is also involved in human energy homeostasis. In order to increase the value of nutrigenetic dietary advice, the interplay between genetics and microbiota must be investigated. The purpose of the present study was to evaluate interactive associations between gut microbiota composition and 95 obesity-related single nucleotide polymorphisms (SNPs) searched in the literature. Oral mucosa and fecal samples from 360 normal weight, overweight and obese subjects were collected. Next generation genotyping of these 95 SNPs and fecal 16S rRNA sequencing were performed. A genetic risk score (GRS) was constructed with 10 SNPs statistically or marginally associated with body mass index (BMI). Several microbiome statistical analyses at family taxonomic level were applied (LEfSe, Canonical Correspondence Analysis, MetagenomeSeq and Random Forest), and Prevotellaceae family was found in all of them as one of the most important bacterial families associated with BMI and GRS. Thus, in this family it was further analyzed the interactive association between BMI and GRS with linear regression models. Interestingly, women with higher abundance of Prevotellaceae and higher GRS were more obese, compared to women with higher GRS and lower abundance of Prevotellaceae. These findings suggest relevant interrelationships between Prevotellaceae and the genetic background that may determine interindividual BMI differences in women, which opens the way to new precision nutrition-based treatments for obesity.

Background: The determinants that mediate the interactions between microRNAs and the gut microbiome impacting on obesity are scarcely understood. Thus, the aim of this study was to investigate possible interactions between circulating microRNAs and gut microbiota composition in obesity. Method: The sample comprised 78 subjects with obesity (cases, body mass index (BMI): 30&ndash, 40 kg/m2) and 25 eutrophic individuals (controls, BMI &le, 25 kg/m2). The expression of 96 microRNAs was investigated in plasma of all individuals using miRCURY LNA miRNA Custom PCR Panels. Bacterial DNA sequencing was performed following the Illumina 16S protocol. The FDR correction was used for multiple comparison analyses. Results: A total of 26 circulating microRNAs and 12 bacterial species were found differentially expressed between cases and controls. Interestingly, an interaction among three miRNAs (miR-130b-3p, miR-185-5p and miR-21-5p) with Bacteroides eggerthi and BMI levels was evidenced (r2 = 0.148, p = 0.004). Moreover, these microRNAs regulate genes that participate in metabolism-related pathways, including fatty acid degradation, insulin signaling and glycerolipid metabolism. Conclusions: This study characterized an interaction between the abundance of 4 bacterial species and 14 circulating microRNAs in relation to obesity. Moreover, the current study also suggests that miRNAs may serve as a communication mechanism between the gut microbiome and human hosts.

Diverse evidence suggests that the gut microbiota is involved in the development of obesity and associated comorbidities. It has been reported that the composition of the gut microbiota differs in obese and lean subjects, suggesting that microbiota dysbiosis can contribute to changes in body weight. However, the mechanisms by which the gut microbiota participates in energy homeostasis are unclear. Gut microbiota can be modulated positively or negatively by different lifestyle and dietary factors. Interestingly, complex interactions between genetic background, gut microbiota, and diet have also been reported concerning the risk of developing obesity and metabolic syndrome features. Moreover, microbial metabolites can induce epigenetic modifications (i.e., changes in DNA methylation and micro-RNA expression), with potential implications for health status and susceptibility to obesity. Also, microbial products, such as short-chain fatty acids or membrane proteins, may affect host metabolism by regulating appetite, lipogenesis, gluconeogenesis, inflammation, and other functions. Metabolomic approaches are being used to identify new postbiotics with biological activity in the host, allowing discovery of new targets and tools for incorporation into personalized therapies. This review summarizes the current understanding of the relations between the human gut microbiota and the onset and development of obesity. These scientific insights are paving the way to understanding the complex relation between obesity and microbiota. Among novel approaches, prebiotics, probiotics, postbiotics, and fecal microbiome transplantation could be useful to restore gut dysbiosis.