Consumption of golden berries (Physalis peruviana L.) might reduce biomarkers of oxidative stress and alter gut permeability in men without changing inflammation status or the gut microbiota.

Golden berry (Physalis peruviana) is a tropical fruit rich in antioxidants that has been proposed to be able to control the lipid profile in hypercholesterolemic patients. Dyslipidemia is an independent risk factor for cardiometabolic diseases. The gut microbiota is strongly associated with cardiometabolic risk and is involved in redox balance, intestinal permeability, and inflammation. However, the impacts of golden berry on some of these factors, including the human gut microbiota, have never been tested, and there are no tools for compliance monitoring or dietary intake assessment regarding nutritional interventions with this fruit. In the pre-post quasi-experimental nutritional intervention presented here, 18 adult men (27-49 years old) consumed golden berries (Dorada variety) for three weeks. We evaluated putative biomarkers of exposure through an untargeted metabolomics approach (liquid chromatography-mass spectrometry LC-MS), quantified the biomarkers of oxidative stress, gut permeability, and inflammation in plasma, and assessed the effects of fruit intake on the gut microbiota through 16S rRNA gene sequencing of feces (Illumina MiSeq V2). First, syringic acid and kaempferol were identified as putative biomarkers of golden berry consumption. Intervention with this fruit promoted physiological changes in the participants after three weeks, reducing the level of the oxidative stress marker 8-isoprostane (-148 pg/ml; 36.1 %; p = 0.057) and slightly altering gut permeability by increasing the plasma levels of LBP (2.91 µg/ml; 54.6 %; p = 0.0005) and I-FABP (0.15, 14.7 %, p = 0.04) without inducing significant inflammation; i.e., the levels of IL-1ß, TNF-α and IL-8 changed by 0.7 (2.0 %), -4.0 (-9.6 %) and -0.4 (-1.8 %) pg/ml, respectively. Notably, the consumption of golden berries did not affect the gut microbiota of the individuals consistently but instead shifted it in a personalized manner. The compositions of the gut microbiota of a given individual at the end of intervention and one month after the end of intervention were statistically more similar to their own baseline than to a corresponding sample from a different individual. This intervention identified putative biomarkers of golden berry intake along with potential benefits of its consumption relevant to cardiometabolic disease risk reduction. Golden berries are likely to positively modulate redox balance, although this effect must be proven in a future controlled clinical trial.

Variants in genes of innate immunity, appetite control and energy metabolism are associated with host cardiometabolic health and gut microbiota composition.

Identifying the genetic and non-genetic determinants of obesity and related cardiometabolic dysfunctions is cornerstone for their prevention, treatment, and control. While genetic variants contribute to the cardiometabolic syndrome (CMS), non-genetic factors, such as the gut microbiota, also play key roles. Gut microbiota is intimately associated with CMS and its composition is heritable. However, associations between this microbial community and host genetics are understudied. We contribute filling this gap by genotyping 60 variants in 39 genes of three modules involved in CMS risk, measuring cardiometabolic risk factors, and characterizing gut microbiota in a cohort of 441 Colombians. We hypothesized that CMS risk variants were correlated with detrimental levels of clinical parameters and with the abundance of disease-associated microbes. We found several polymorphisms in genes of innate immunity, appetite control, and energy metabolism that were associated with metabolic dysregulation and microbiota composition; the associations between host genetics and cardiometabolic health were independent of the participants' gut microbiota, and those between polymorphisms and gut microbes were independent of the CMS risk. Associations were also independent of the host genetic ancestry, diet and lifestyle. Most microbes explaining genetic-microbiota associations belonged to the families Lachnospiraceae and Ruminococcaceae. Multiple CMS risk alleles were correlated with increased abundance of beneficial microbiota, suggesting that the phenotypic outcome of the evaluated variants might depend upon the genetic background of the studied population and its environmental context. Our results provide additional evidence that the gut microbiota is under the host genetic control and present pathways of host-microbe interactions.

Gut microbiota composition explains more variance in the host cardiometabolic risk than genetic ancestry.

Cardiometabolic affections greatly contribute to the global burden of disease. The susceptibility to obesity, cardiovascular disease, and type-2 diabetes, conditions that add to the cardiometabolic syndrome (CMS), was associated with the ancestral genetic composition and gut microbiota. Studies explicitly testing associations between genetic ancestry and gut microbes are growing. We here examined whether the host genetic ancestry was associated with gut microbiota composition, and distinguished the effects of genetic ancestry and non-genetic factors on human cardiometabolic health. We performed a cross-sectional study with 441 community-dwelling Colombian mestizos from five cities spanning the Andes, Pacific, and Caribbean coasts. We characterized the host genetic ancestry by genotyping 40 ancestry informative markers; characterized gut microbiota through 16S rRNA gene sequencing; assessed diet intake, physical activity, cigarette, and medicament consumption; and measured cardiometabolic outcomes that allowed calculating a CMS risk scale. On average, each individual of our cohort was 67 ± 6% European, 21 ± 5% Native American and 12 ± 5% African. Multivariable-adjusted generalized linear models showed that individuals with higher Native American and African ancestries had increased fasting insulin, body mass index and CMS risk, as assessed by the CMS risk scale. Furthermore, we identified 21 OTUs associated to the host genetic ancestry and 20 to cardiometabolic health. While we highlight novel associations between genetic ancestry and gut microbiota, we found that the effect of intestinal microbes was more likely to explain the variance in CMS risk scale than the contributions of European, Native American and African genetic backgrounds.

Green Coffee Extract Improves Cardiometabolic Parameters and Modulates Gut Microbiota in High-Fat-Diet-Fed ApoE-/- Mice.

Chlorogenic acids (CGA) are the most abundant phenolic compounds in green coffee beans and in the human diet and have been suggested to mitigate several cardiometabolic risk factors. Here, we aimed to evaluate the effect of a water-based standardized green coffee extract (GCE) on cardiometabolic parameters in ApoE-/- mice and to explore the potential underlying mechanisms. Mice were fed an atherogenic diet without (vehicle) or with GCE by gavage (equivalent to 220 mg/kg of CGA) for 14 weeks. We assessed several metabolic, pathological, and inflammatory parameters and inferred gut microbiota composition, diversity, and functional potential. Although GCE did not reduce atherosclerotic lesion progression or plasma lipid levels, it induced important favorable changes. Specifically, improved metabolic parameters, including fasting glucose, insulin resistance, serum leptin, urinary catecholamines, and liver triglycerides, were observed. These changes were accompanied by reduced weight gain, decreased adiposity, lower inflammatory infiltrate in adipose tissue, and protection against liver damage. Interestingly, GCE also modulated hepatic IL-6 and total serum IgM and induced shifts in gut microbiota. Altogether, our results reveal the cooccurrence of these beneficial cardiometabolic effects in response to GCE in the same experimental model and suggest potential mediators and pathways involved.

Higher Fecal Short-Chain Fatty Acid Levels Are Associated with Gut Microbiome Dysbiosis, Obesity, Hypertension and Cardiometabolic Disease Risk Factors.

Fiber fermentation by gut microbiota yields short-chain fatty acids (SCFAs) that are either absorbed by the gut or excreted in feces. Studies are conflicting as to whether SCFAs are beneficial or detrimental to cardiometabolic health, and how gut microbiota associated with SCFAs is unclear. In this study of 441 community-dwelling adults, we examined associations of fecal SCFAs, gut microbiota diversity and composition, gut permeability, and cardiometabolic outcomes, including obesity and hypertension. We assessed fecal microbiota by 16S rRNA gene sequencing, and SCFA concentrations by gas chromatography/mass spectrometry. Fecal SCFA concentrations were inversely associated with microbiota diversity, and 70 unique microbial taxa were differentially associated with at least one SCFA (acetate, butyrate or propionate). Higher SCFA concentrations were associated with a measure of gut permeability, markers of metabolic dysregulation, obesity and hypertension. Microbial diversity showed association with these outcomes in the opposite direction. Associations were significant after adjusting for measured confounders. In conclusion, higher SCFA excretion was associated with evidence of gut dysbiosis, gut permeability, excess adiposity, and cardiometabolic risk factors. Studies assessing both fecal and circulating SCFAs are needed to test the hypothesis that the association of higher fecal SCFAs with obesity and cardiometabolic dysregulation is due to less efficient SCFA absorption.

Gut microbiota is associated with obesity and cardiometabolic disease in a population in the midst of Westernization.

Westernization and its accompanying epidemiological transitions are associated with changes in gut microbiota. While the extremes of this lifestyle spectrum have been compared (hunter-gatherers, industrialized countries), populations undergoing such shifts have received little attention. To fill the gap of knowledge about the microbiome evolution following broad lifestyle changes and the emergence of disease-associated dysbiosis, we performed a cross-sectional study in which we characterized the microbiota of 441 Colombian adults through 16S rRNA gene sequencing and determined its relationship with demographic, health-related and dietary parameters. We showed that in the gut microbiota of this cohort thrive taxa proper of both hunter-gatherers (Prevotella, Treponema) and citizens of industrialized countries (Bacteroides, Bifidobacterium, Barnesiella); the relative abundances of these taxa differed from those in Western and non-Western populations. We also showed that the Colombian gut microbiota is composed of five consortia of co-abundant microorganisms that are differentially associated with lifestyle, obesity and cardiometabolic disease, and highlighted metabolic pathways that might explain associations between microbiota and host health. Our results give insights into the evolution of the gut microbiota, and underscore the importance of this community to human health. Promoting the growth of specific microbial consortia could help ameliorating physiological conditions associated with Western lifestyles.

Impact of DNA extraction, sample dilution, and reagent contamination on 16S rRNA gene sequencing of human feces.

Culture-independent methods have granted the possibility to study microbial diversity in great detail, but technical issues pose a threat to the accuracy of new findings. Biases introduced during DNA extraction can result in erroneous representations of the microbial community, particularly in samples with low microbial biomass. We evaluated the DNA extraction method, initial sample biomass, and reagent contamination on the assessment of the human gut microbiota. Fecal samples of 200 mg were subjected to 1:10 serial dilutions; total DNA was obtained using two commercial kits and the microbiota assessed by 16S ribosomal RNA (rRNA) gene sequencing. In addition, we sequenced multiple technical controls. The two kits were efficient in extracting DNA from samples with as low as 2 mg of feces. However, in instances of lower biomass, only one kit performed well. The number of reads from negative controls was negligible. Both DNA extraction kits allowed inferring microbial consortia with similar membership but different abundances. Furthermore, we found differences in the taxonomic profile of the microbial community. Unexpectedly, the effect of sample dilution was moderate and did not introduce severe bias into the microbial inference. Indeed, the microbiota inferred from fecal samples was distinguishable from that of negative controls. In most cases, samples as low as 2 mg did not result in a dissimilar representation of the microbial community compared with the undiluted sample. Our results indicate that the gut microbiota inference is not much affected by contamination with laboratory reagents but largely impacted by the protocol to extract DNA.

Metformin Is Associated With Higher Relative Abundance of Mucin-Degrading Akkermansia muciniphila and Several Short-Chain Fatty Acid-Producing Microbiota in the Gut.

OBJECTIVE: Recent studies suggest the beneficial effects of metformin on glucose metabolism may be microbially mediated. We examined the association of type 2 diabetes, metformin, and gut microbiota in community-dwelling Colombian adults. On the basis of previous research, we hypothesized that metformin is associated with higher levels of short-chain fatty acid (SCFA)-producing and mucin-degrading microbiota. RESEARCH DESIGN AND METHODS: Participants were selected from a larger cohort of 459 participants. The present analyses focus on the 28 participants diagnosed with diabetes-14 taking metformin- and the 84 participants without diabetes who were matched (3-to-1) to participants with diabetes by sex, age, and BMI. We measured demographic information, anthropometry, and blood biochemical parameters and collected fecal samples from which we performed 16S rRNA gene sequencing to analyze the composition and structure of the gut microbiota. RESULTS: We found an association between diabetes and gut microbiota that was modified by metformin use. Compared with participants without diabetes, participants with diabetes taking metformin had higher relative abundance of Akkermansia muciniphila, a microbiota known for mucin degradation, and several gut microbiota known for production of SCFAs, including Butyrivibrio, Bifidobacterium bifidum, Megasphaera, and an operational taxonomic unit of Prevotella. In contrast, compared with participants without diabetes, participants with diabetes not taking metformin had higher relative abundance of Clostridiaceae 02d06 and a distinct operational taxonomic unit of Prevotella and a lower abundance of Enterococcus casseliflavus. CONCLUSIONS: Our results support the hypothesis that metformin shifts gut microbiota composition through the enrichment of mucin-degrading A. muciniphila as well as several SCFA-producing microbiota. Future studies are needed to determine if these shifts mediate metformin's glycemic and anti-inflammatory properties.