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Fiber and gut microbiome

Fiber and gut microbiome

Flaxseed for digestive health cell walls: Mocrobiome on nutrient bioaccessibility and Fiber and gut microbiome. In multivariate models for CRP, higher CRP Fiber and gut microbiome associated with enrichment of Fibed. Over-representation of genes in the qnd module was characterized based on gene ontology biological process and KEGG pathways using clusterProfiler [ ]. As previously described [ 23 ], we used Illumina HiSeq sequencing paired-end 2 × nucleotides shotgun sequencing platform. In their study, the gut microbiota of 49 healthy volunteers was tracked before and during inulin intervention for more than two weeks.

Fiber and gut microbiome -

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Medical News Today. Health Conditions Health Products Discover Tools Connect. Short-term increase in fiber alters gut microbiome. By Timothy Huzar on April 3, — Fact checked by Catherine Carver, BA, MPH, MBChB. Share on Pinterest An increase in fiber can change the microbiome within 2 weeks.

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We found that dietary fiber from fruit sources in particular e. The Health Professionals Follow-Up Study HPFS is an ongoing prospective cohort study of 51, US male health professionals aged 40 to 75 years at enrollment in [ 22 ].

From to , we recruited men in the MLVS and collected longitudinal stool samples [ 23 ]. Participants were asked to provide stool samples from two consecutive bowel movements 24—72 h apart, followed approximately 6 months later by collection of a second, similar paired samples. Participants placed each bowel movement into a container with RNAlater and completed a questionnaire detailing the date and time of evacuation, Bristol stool scale, and other relevant information.

As previously described [ 23 ], we used Illumina HiSeq sequencing paired-end 2 × nucleotides shotgun sequencing platform. DNA was extracted from samples, in addition to RNA from a subset of samples from 96 participants who provided stool samples during both sampling periods and did not report the use of antibiotics within the past year.

In the HPFS, dietary intake was assessed every 4 years since enrollment in with a validated, semi-quantitative Food Frequency Questionnaire FFQ [ 26 ].

Participants were asked how often they typically consumed each food of a standard portion size e. Daily intake of each nutrient was calculated by multiplying the reported frequency of each food item by its nutrient content and summing across foods, followed by curator quality control.

Fiber intake was calculated using the Associations of Official Analytical Chemists method accepted by the US FDA and the World Health Organization for nutrition labeling purposes [ 27 ].

We adjusted fiber intake for total caloric intake using the nutrient residual method [ 28 ]. FFQs have demonstrated good reproducibility and validity for assessing habitual intake; the correlation coefficient comparing dietary fiber assessment from FFQ with multiple 7-day dietary records is 0. To represent long-term intake, we calculated the cumulative average of dietary fiber intake based on seven FFQs prior to the stool collection from through Participants in the MLVS were also administered 7-day dietary records recording recent diet contemporaneously with stool sample collections.

Participants measured and reported gram weights for foods using a Primo Multifunction Kitchen Scale and ruler before and after eating, provided recipes of home-prepared foods, and returned labels of store-brand products.

The Nutrition Data System for Research was used to derive over nutrients and dietary constituents including dietary fiber intake [ 29 ]. Sequencing reads were passed through the KneadData 0. Taxonomic profiling was performed using MetaPhIAn 2. Metagenomes and metatranscriptomes were functionally profiled using HUMAnN 2.

Briefly, for each sample, taxonomic profiling is used to identify detectable organisms. Reads are recruited to sample-specific pangenomes including all gene families in any detected microorganisms using Bowtie2 [ 33 ].

Unmapped reads are aligned against UniRef90 [ 34 ] using DIAMOND translated search [ 35 ]. Hits are counted per gene family and normalized for length and alignment quality. For calculating abundances from reads that map to more than one reference sequence, search hits are weighted by significance alignment quality, gene length, and gene coverage.

UniRef90 abundances from both the nucleotide and protein levels were then 1 mapped to level 4 enzyme commission EC nomenclature, 2 combined into structured pathways from MetaCyc [ 36 ], and 3 regrouped to carbohydrate-active enzymes CAZy [ 37 ].

More details about functional profiling in the MLVS have been described previously [ 23 , 25 ]. Owing to the compositionality of RNA and DNA measurements, the resulting ratio is relative to the mean transcript abundance of the entire microbial community. Thus, a ratio of 1 implies that the pathway is transcribed at the mean transcription abundance of all pathways in the microbial community.

The MLVS collected two fasting blood samples in blood tubes with liquid sodium heparin during the same period as fecal sample collection. Plasma levels of high-sensitivity CRP were measured at the Franke lab at University of Hawaii using a Cobas MiraPlus clinical chemistry analyzer Roche Diagnostics, Indianapolis, IN and a latex particle enhanced immunoturbidimetry-based kit from Pointe Scientific Lincoln Park, MI.

We paired longitudinal stool microbiome with concurrent blood measurements and dietary intake, resulting in samples for taxonomic and metagenomic analyses and samples for metatranscriptomic analyses.

We performed omnibus testing with permutational multivariate analysis of variance PERMANOVA of Bray-Curtis dissimilarities permutations to quantify the percentage of variance explained by age, lifestyle, diet, and clinical biomarkers.

We identified microbial species and functions associated with dietary fiber intake and CRP using multivariate linear mixed model in MaAsLin 2 0. We additionally adjusted for body mass index BMI in the model for CRP to delineate microbial species associated with chronic inflammation independent of adiposity.

To examine an interaction between fiber intake and gut microbiome composition, we applied an equivalent multivariate linear mixed model that included a product term of fiber and presence of P.

copri fiber: P. copri in addition to their main effects and evaluated the statistical significance of the product term:. Overall type I error was controlled using the Benjamini-Hochberg false discovery rate FDR.

We assessed diet-microbiome-inflammation interactions using existing data from the MLVS, a cohort of generally healthy men nested in the HPFS Fig. The mean age of MLVS participants was At the first collection, participants had a mean intake of dietary fiber of The majority of participants were physically active, did not smoke, and had normal stool consistency as represented by Bristol score; interestingly, these characteristics did not differ by overall fiber intake Table 1.

Linking the gut microbiome, dietary fiber, and systemic inflammation in a cohort of adult males. A participants nested within the Health Professionals Follow-Up Study [ 23 , 25 ] provided up to four stool samples with concurrent blood samples over a 6-month study period, generating metagenomes from all participants and metatranscriptomes from a subset of 96 selected because they provided stool at both sampling periods and did not report antibiotic use during the past year.

B Overall recent dietary fiber intake and C-reactive protein as a biomarker of systemic inflammation levels were distributed representatively across this population. D Major food sources of fiber intake included cereals, vegetables, and fruits. E Principal coordinate analysis based on species-level Bray-Curtis dissimilarity decorated by quartiles of C-reactive protein and continuous fruit fiber intake suggested that fiber intake and CRP levels were not the overall largest sources of microbial community variability other fiber subsets in Additional file 1 : Figure S1.

We included metagenomes and metatranscriptomes in our analyses [ 23 ]. A total of microbial species were retained after quality control from MetaPhlAn 2 [ 31 ] and gene, transcript, and pathway functional profiles from DNA and RNA using HUMAnN 2 [ 32 ].

We first tested for associations between overall microbiome structure and our main variables of interest fiber subsets and CRP and covariates Fig. Thus, neither fiber intake nor CRP levels alone were the main drivers of overall microbiome configurations, which were instead dominated by baseline inter-individual differences [ 25 ].

We examined the possibility that the relationship between recent dietary fiber intake and CRP levels was not uniform across the population.

Consistent with other findings [ 39 ], We tested this interaction quantitatively and found that the inverse association between dietary fiber and CRP was significantly stronger among participants who did not have P.

copri , compared to those with P. We tested the 10 most abundant species and found that P. copri was the only species whose abundance modified the association between fiber intake and CRP.

We also found similar modulation effects of P. copri at each timepoint separately. Prevotella copri carriage abrogates the protective effects of recent dietary fiber intake on C-reactive protein. Multivariate linear mixed models of log-transformed CRP were fit including recent fiber intake and P.

copri carriage binary , their interaction, accounting for participant membership as a random effect, and adjusting for age, recent antibiotic use, and total calorie intake. We excluded samples with CRP values below or above the detection limits, and thus, samples from participants were included in this analysis.

The relationship between dietary fiber and plasma CRP was significantly stronger among participants who did not carry P. copri 0 abundance. These results support that microbiome structure, primarily via P.

copri carriage, likely modifies the effects of fiber intake in alleviating chronic inflammation. Relatedly, P. copri has previously shown both positive and negative influences on human health.

Some studies have linked P. copri to improved glucose tolerance and insulin responses in fiber-rich diets [ 40 , 41 ]. Others, in contrast, associated P.

copri with insulin resistance and glucose intolerance as well as inflammatory diseases [ 42 , 43 , 44 ]. In combination with recent evidence that Westernization leads to reduced prevalence and genetic diversity of P.

copri [ 39 ] and the much greater amount and diversity of plant-based dietary fiber sources in global diets, our results provide compelling novel evidence for chronic, systemic health consequences of gut microbial metabolism of dietary compounds.

In the absence of overall microbiome shifts with fiber intake or CRP, we next identified individual microbial species associated with these variables using multivariate linear mixed model in MaAsLin 2 [ 38 ] Fig.

Consistent with previous studies [ 46 ], both recent and long-term higher dietary fiber were associated with shifts in Clostridiales, the major butyrate producers, including increases of Eubacterium eligens , Faecalibacterium prausnitzii , and genus Roseburia , but also decreases in Clostridium , Lachnospiraceae , and Ruminococcus spp.

Increased fiber intake was also associated with increased relative abundances of Haemophilus parainfluenzae and Bacteroides cellulosilyticus. These associations remained robust despite additional adjustment for Bristol score and other lifestyle factors including alcohol intake and physical activity.

Species abundances significantly associated with C-reactive protein and dietary fiber intake. We included metagenomic samples from participants in this analysis.

Comparisons used log-transformed CRP and fiber assessed as recent intake using both 7-day dietary records and long-term cumulative averages from Food Frequency Questionnaires over Models were adjusted for age, recent antibiotics, and total calorie intake; models for CRP were additionally adjusted for body mass index.

B Raw non-residualized abundances for the species associated with recent dietary fiber intake and C CRP. Both recent and long-term higher dietary fibers were associated with shifts in individual microbial species such as Clostridiales.

Greater microbial differences were observed in association with intake of pectin and fiber from fruits and, to a lesser extent, cereals, compared to vegetable fiber. Higher CRP levels corresponded with a generally inflammation-associated gut microbial configuration [ 45 ].

For example, the findings mentioned above including positive associations with E. eligens and F. prausnitzii and inverse associations with Lachnospiraceae and Ruminococcus were largely driven by pectin and fruit fiber. The distinct chemical structures of dietary fibers lead to substantial variations in solubility and fermentability and subsequent effects on the microbial composition and functions [ 9 , 10 ].

Pectin is a soluble dietary fiber rich in apples, pears, plums, and citrus fruits. It comprises a highly complex set of plant cell wall polysaccharides including homo-polygalacturonan, rhamnogalacturonan I, and rhamnogalacturonan II [ 47 ]. Our results were in line with reports from in vitro and animal studies that pectin induced influences on the gut microbiota composition, including increases of Clostridiales such as F.

prausnitzii and a highly selective promotion of E. eligens as well as depletion of Bacteroidetes [ 48 , 49 , 50 ]. Associations of soluble and insoluble fiber with microbial species were similar Additional file 1 : Figure S3, Additional file 2 : Table S2 , possibly due to the challenge of differentiating the soluble vs.

insoluble subtypes through available diet instruments [ 51 ]. In multivariate models for CRP, higher CRP was associated with enrichment of B. uniformis , B.

salyersale , Barnesiella intestinihominis , and Parabacteroides independent of adiposity. In a previous analysis of older adult subjects, CRP was positively associated with a metagenomically assembled Bacteroides co-abundance group [ 52 ].

However, unlike the positive association observed here with P. distasonis and P. johnsonii , the former was shown to alleviate obesity and metabolic dysfunctions via production of succinate and secondary bile acids in mice [ 53 ].

Higher CRP levels were also associated with depletion of Lachnospiraceae bacterium 3 1 46FAA , E. eligens , and Bifidobacterium bifidum , consistent with their anti-inflammatory effects as shown in experimental studies [ 50 , 54 , 55 ].

Dietary fiber intake in particular recent intake from pectin was also significantly associated with a large number of metagenomic functional pathways Additional file 1 : Figure S4, Additional file 2 : Table S3 and features Additional file 1 : Figure S5, Additional file 2 : Table S4 involved in the metabolism of carbohydrates and amino acids.

A greater total fiber intake was associated with significant enrichment of PWY β- 1,4 -mannan degradation, P Bifidobacterium shunt, PWY L-isoleucine biosynthesis IV, and PWY putrescine biosynthesis, whereas the rest of pathways were generally depleted.

A higher intake of total fiber and pectin was also associated with significantly enriched expression of EC 3. To specifically investigate fiber intake in relation to functional capacity and activity relating to carbohydrate utilization, we further mapped gene families into carbohydrate-active enzymes CAZy [ 37 ].

CAZy covers enzymes catalyzing the breakdown, biosynthesis, or modification of carbohydrates and glycoconjugates including glycoside hydrolases GHs , glucosylTransferases GTs , polysaccharide lyases PLs , carbohydrate esterases CEs , auxiliary activities AAs , and non-catalytic carbohydrate-binding modules CBMs.

We identified a total of 84 CAZys metagenomically associated with dietary fiber—again, particularly pectin and fruit fiber—using multivariate linear testing Fig. Concordant with the chemical structure of pectin consisting of repeated units of α - -linked d -galacturonic acid, and the fermentation requirement of pectinase, we detected an enrichment of PL9 strongly positively correlated with pectin intake.

PL9 covers enzymes including pectate lyase EC 4. In our samples, expression of PL9 was primarily contributed by E. eligens , followed by B. thetaiotaomicron , F. prausnitzii , and B. An increase of GH25, carried by diverse species of Eubacterium , Bacteroides , and Faecalibacterium , was also strongly associated with fiber and pectin intake.

Meanwhile, fiber and pectin also showed inverse associations with some features, such as GH29, contributed largely by Bacteroides species and involved in degradation of other glycan targets. Finally, some other enzyme families that were contributed mostly by Clostridiales, such as CBM13, were also associated with a greater intake of fiber and pectin.

CAZy and dietary fiber intake. Comparisons used fiber assessed as recent intake using both 7-day dietary records and long-term cumulative averages from Food Frequency Questionnaires over — Models were adjusted for age, recent antibiotics, and total calorie intake.

B Abundances of metagenomes and metatranscriptomes of polysaccharide lyase family 9 PL9 , glycoside hydrolase family 29 GH29 , and carbohydrate-binding module family 13 CBM13 by contributing species and samples, with species ranked by mean relative abundance, and samples ranked by pectin intake.

We included metagenomes and metatranscriptomes in this analysis. A total of 84 CAZys metagenomically associated with dietary fiber in particular pectin and fruit fiber. We additionally evaluated the associations of recent dietary fiber and pectin with copy-number normalized transcript levels of CAZys, i.

Interestingly, this recapitulated the positive association between PL9 and dietary fiber. There was also a trend towards positive correlation between pectin intake and PL9, although not achieving statistical significance.

Here, we have demonstrated one of the first explicit interaction relationships by which a specific component of the gut microbiome P. copri modifies a dietary exposure fiber intake with a well-established marker of systemic inflammation plasma C-reactive protein levels.

In addition to this interaction effect, direct effects of dietary fiber intake on the gut microbiome generally increased Clostridiales, which also play a pivotal role in regulating localized and systemic inflammation [ 56 ].

These microbial alterations also varied among specific fiber sources, with the greatest effects deriving from pectin and fruit fiber.

For instance, abundances of E. prausnitzii as well as their functions in the degradation of polysaccharides were enriched in participants with greater dietary fiber and, especially, pectin intake.

We also linked individual microbial signatures to chronic systemic inflammation. These findings collectively offer novel human evidence supporting a variety of fiber-gut-microbiome interactions relevant to chronic systemic inflammation.

Specifically, in our population, P. copri carriage eliminated the strongly protective effects of increased fiber intake on systemic inflammation, with P. copri carriers distributed across a range of generally modest CRP levels and non-carriers varying between higher and lower extremes according to fiber intake.

The impact of P. copri on human health overall is still controversial, as conflicting results have been reported among different populations and phenotypes. As a fiber-degrader, Prevotella was positively associated with production of SCFAs e.

Conversely, P. copri has been associated with chronic inflammatory conditions such as rheumatoid arthritis [ 42 , 43 ] and insulin resistance and glucose intolerance [ 44 ].

Strain-level heterogeneity and distinct clades of the P. copri complex may contribute to its functional diversity and some of these apparent phenotypic contradictions [ 59 , 60 ].

For instance, genetically diverse P. copri isolates utilize distinct sets of polysaccharides from dietary plant sources [ 59 ]. The combination of P. copri diversity, fiber type and amount diversity, and the gradual, multi-generational loss of P.

copri clades from Westernized populations could account for the complexity of this interaction [ 39 ]. Our findings suggest that P. copri could in principle have both direct effects on systemic inflammation, as well as opposing, indirect effects caused by reduced bioavailability of fermentable fibers or other fermentation products to other microbes.

Additional investigation is thus needed to functionally characterize the influence of P. copri on modulating dietary effects on inflammation, health, and host-microbe coevolution. An additional intriguing result from this study was the specificity of many fiber-microbiome influences to fruit fibers and pectin.

As a major soluble fiber component in the plant cell wall, particularly in fruits and vegetables, pectin serves as the nutritional niche for some groups of bacteria, such as B. thetaiotaomicron [ 61 ], F. prausnitzii [ 49 ], and E.

eligens [ 8 ]. It is likely that the chemical complexity of pectin relative to other fiber sources facilitates its capacity to nourish diverse microbial communities [ 62 ].

Polysaccharide utilization loci that orchestrate the detection, sequestration, enzymatic digestion, and transport of complex carbohydrates have been identified in most gut-resident species, especially among the Bacteroidetes [ 63 ].

However, knowledge of the impact of pectin in particular on the gut microbial communities is still limited and has been restricted to in vitro and animal studies. To our knowledge, we for the first time identified pectin-induced alterations in gut microbiota composition and functional capabilities and subsequent impact in inflammation in a human population study.

These results suggest that pectin intake may exert a selection pressure on the gut microbiota leading to the predominance of organisms that degrade pectic polysaccharides and an enhancement of functional activities specifically based on their utilization.

This supports the notion that gut microbial strains are highly specialized, particularly with respect to carbon source utilization and products, and can evolve and adapt over the course of an adult lifetime to utilize a unique subset of complex polysaccharides in a personalized, individual-specific manner [ 61 ].

At least one additional recent study, using a distinct population and methodology, found potentially similar between-subject variation in fiber sources with respect to the microbiome. There, significant agreement between microbiome composition and fiber-source diversity was observed for fruits and grains, but not for vegetables or legumes [ 64 ].

Such heterogeneity according to fiber sources might be explained not only by the distinct chemical structures of fibers in each type of food [ 10 ], but also by other fruit-specific bioactive compounds such as polyphenols flavonoids, phenolic acids, and carotenoids [ 65 ] and even cooking raw vs.

cooked plant foods [ 66 ]. Our population-based investigation does not distinguish between these potential mechanisms, for which in vitro studies and randomized controlled trials of specific fibers are better suited although these cannot, conversely, assess the long-term effects of dietary fiber.

Likewise, as an observational study, we cannot be definitive about causality and although the fiber-microbiome-inflammation association was robust despite adjustment for many variables, we cannot rule out the potential for residual confounding.

Finally, since our study only included older adult men in the US, we are cautious about generalizability to other populations, especially, younger and non-Western populations in whom relevant dietary or microbial components may be quite distinct. Thus, we plan to validate these findings in additional cohorts with information on diet, the gut microbiome, and health outcomes.

As one of the only sustainable long-term influences on the gut microbiome and chronic health, dietary interactions and interventions are a key strategy to mitigate chronic inflammation. Our findings will benefit from further investigation of the specific mechanisms by which P.

copri mediates dietary biochemistry and host inflammation, as well as the specific routes by which pectin directly influences other gut microbiome members. An understanding of these distinct effects of dietary fibers, pectin, and how they are transformed and utilized by microbial communities would pave the way forward for development of personalized fiber-based interventions for the prevention of chronic inflammatory diseases.

All the metadata from the Health Professionals Follow-Up Study are available through a request for external collaboration and upon approvals of a letter of intent and a research proposal.

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Human gut microbiota has gtu fundamental role in human Organic Guarana Powder, and diet is one of the most Fiher factors modulating the Fibe microbial ecosystem. Fiber, fat, proteins, and micronutrients Fiber and gut microbiome shape Sports supplements activity anx structure. Much information is available Fiber and gut microbiome the role of defined prebiotic fibers on Fiebr microbiota, but ,icrobiome known are the effects of intact dietary fiber sources on healthy gut ecosystems. This research investigated in vitro the short-term effect of 22 commercially available food sources of dietary fiber on gut microbiota activity [pH, gas, short-chain fatty acids SCFAbranched fatty acids BCFAlactate] and specific composition of Firmicutes, Bacteroidetes, bifidobacteria, and lactobacilli populations. In general, all the whole grain cereals had a similar effect on gut microbiota modulation, inducing acetate and butyrate production and increasing bifidobacteria levels. Dietary fiber is composed of carbohydrate polymers with three or more monomeric units, which are not digested or absorbed in the human small intestine 1 — 3.


Gut Health Expert on How Fiber Optimizes Your Microbiome - Dr. Will Bulsiewicz on Health Theory Jump gu What is the microbiome? Future areas tut research. Fibeg a bustling Peppermint candy cookies on a weekday morning, Fiber and gut microbiome sidewalks flooded microiome people rushing to get to work or to appointments. Now Fbier this Fiber and gut microbiome a microscopic level and you have an idea of what the microbiome looks like inside our bodies, consisting of trillions of microorganisms also called microbiota or microbes of thousands of different species. The microbiome is even labeled a supporting organ because it plays so many key roles in promoting the smooth daily operations of the human body. The microbiome consists of microbes that are both helpful and potentially harmful. Fiber and gut microbiome

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