scholarly journals Effect of fructans, prebiotics and fibres on the human gut microbiome assessed by 16S rRNA-based approaches: a review

2020 ◽  
Vol 11 (2) ◽  
pp. 101-129 ◽  
Author(s):  
K.S. Swanson ◽  
W.M. de Vos ◽  
E.C. Martens ◽  
J.A. Gilbert ◽  
R.S. Menon ◽  
...  
Keyword(s):  
16S Rrna ◽  
Gut Microbiota ◽  
Relative Abundance ◽  
Gut Microbiome ◽  
Human Gut ◽  
Beta Glucan ◽  
Dietary Fibres ◽  
Sequencing Studies ◽  
Resistant Starches ◽  
The Impact

The inherent and diverse capacity of dietary fibres, nondigestible oligosaccharides (NDOs) and prebiotics to modify the gut microbiota and markedly influence health status of the host has attracted rising interest. Research and collective initiatives to determine the composition and diversity of the human gut microbiota have increased over the past decade due to great advances in high-throughput technologies, particularly the 16S ribosomal RNA (rRNA) sequencing. Here we reviewed the application of 16S rRNA-based molecular technologies, both community wide (sequencing and phylogenetic microarrays) and targeted methodologies (quantitative PCR, fluorescent in situ hybridisation) to study the effect of chicory inulin-type fructans, NDOs and specific added fibres, such as resistant starches, on the human intestinal microbiota. Overall, such technologies facilitated the monitoring of microbiota shifts due to prebiotic/fibre consumption, though there are limited community-wide sequencing studies so far. Molecular studies confirmed the selective bifidogenic effect of fructans and galactooligosaccharides (GOS) in human intervention studies. Fructans only occasionally decreased relative abundance of Bacteroidetes or stimulated other groups. The sequencing studies for various resistant starches, polydextrose and beta-glucan showed broader effects with more and different types of gut microbial species being enhanced, often including phylotypes of Ruminococcaceae. There was substantial variation in terms of magnitude of response and in individual responses to a specific fibre or NDO which may be due to numerous factors, such as initial presence and relative abundance of a microbial type, diet, genetics of the host, and intervention parameters, such as intervention duration and fibre dose. The field will clearly benefit from a more systematic approach that will support defining the impact of prebiotics and fibres on the gut microbiome, identify biomarkers that link gut microbes to health, and address the personalised response of an individual’s microbiota to prebiotics and dietary fibres.

scholarly journals Identification and Removal of Potential Contaminants in 16S rRNA Gene Sequence Datasets from Low Microbial Biomass Samples: An Example from the Mosquito Gut

2020 ◽  
Author(s):  
Sebastián Diaz ◽  
Juan Sebastián Escobar ◽  
Frank William Avila
Keyword(s):  
Microbial Biomass ◽  
16S Rrna ◽  
Gut Microbiota ◽  
Relative Abundance ◽  
Vector Competence ◽  
Negative Control ◽  
Rrna Gene ◽  
Physiological Processes ◽  
Physiological Relevance ◽  
The Impact

Abstract Background: The bacterial gut microbiota of the female mosquito influences numerous physiological processes, including vector competence. As a low-microbial-biomass ecosystem, mosquito gut tissue is prone to contamination from the laboratory environment and from reagents commonly used to dissect and/or isolate DNA from gut tissue. In this report, we analyze five 16S rRNA datasets, including new data obtained by us, to gain insight into the impact of potential contaminating sequences on the composition, diversity, and structure of the mosquito gut microbial community. Results: We present a clustering-free approach that, based on the relative abundance of amplicon sequence variants (ASVs) in gut and negative control samples , allowed for the identification of candidate contaminating sequences. Some of these sequences belong to bacterial taxa previously identified as common contaminants in metagenomic studies; they have also been identified as part of the mosquito core gut microbiota, with putative physiological relevance for the host. By using different relative abundance cutoffs, we show that contaminating sequences have a significant impact on gut microbiota diversity and structure.Conclusions: The approach presented here allows the identification and removal of purported contaminating sequences in datasets obtained from low-microbial biomass samples. While it was exemplified with the analysis of gut microbiota from mosquitos, it can easily extend to other datasets dealing with similar technical artifacts.

scholarly journals DETERMINING RELATIVE IMPORTANCE OF HUMAN GUT MICROBIOTA, AGE, GENDER AND LIFESTYLE PATTERN AS A PREDICTOR FOR BMI USING LOGMPIE DATA

2021 ◽  
Vol 21 (2) ◽  
Author(s):  
Komal Jani ◽  
Shelly Gupta
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Random Forest ◽  
Gut Microbiota ◽  
Relative Abundance ◽  
Gut Microbiome ◽  
Relative Importance ◽  
Human Gut ◽  
Human Gut Microbiota ◽  
Lifestyle Pattern

We use the ‘Relative Abundance Table’ and ‘LogMPIE Study Metadata’ from the “Landscape of Gut Microbiome - Pan-India Exploration”, or LogMPIE dataset to find out the relative importance of human gut microbiota abundance (specifically genus), age, gender, and lifestyle pattern as a predictor for BMI (Body Mass Index). The LogMPIE data is taken from 1004 subjects and 993 unique microorganisms are reported along with BMI, age, and physical activity. We use Random Forest Regressor to find out the relative importance of the above-mentioned features (microorganism genus abundance, age, gender, and lifestyle pattern) in predicting the BMI of a subject. The objective here is not the prediction of BMI using the features but to find out the relative importance of these features as much as these affect the BMI.

scholarly journals Monosodium Glutamate Induces Changes in Hepatic and Renal Metabolic Profiles and Gut Microbiome of Wistar Rats

Nutrients ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1865
Author(s):  
Kanokwan Nahok ◽  
Jutarop Phetcharaburanin ◽  
Jia V. Li ◽  
Atit Silsirivanit ◽  
Raynoo Thanan ◽  
...  
Keyword(s):  
16S Rrna ◽  
Gut Microbiota ◽  
16S Rrna Gene ◽  
Gut Microbiome ◽  
Wistar Rats ◽  
Monosodium Glutamate ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Male Wistar Rats ◽  
The Impact

The short- and long-term consumption of monosodium glutamate (MSG) increases urinary pH but the effects on the metabolic pathways in the liver, kidney and the gut microbiota remain unknown. To address this issue, we investigated adult male Wistar rats allocated to receive drinking water with or without 1 g% MSG for 2 weeks (n = 10, each). We performed a Nuclear Magnetic Resonance (NMR) spectroscopy-based metabolomic study of the jejunum, liver, and kidneys, while faecal samples were collected for bacterial DNA extraction to investigate the gut microbiota using 16S rRNA gene sequencing. We observed significant changes in the liver of MSG-treated rats compared to controls in the levels of glucose, pyridoxine, leucine, isoleucine, valine, alanine, kynurenate, and nicotinamide. Among kidney metabolites, the level of trimethylamine (TMA) was increased, and pyridoxine was decreased after MSG-treatment. Sequencing of the 16S rRNA gene revealed that MSG-treated rats had increased Firmicutes, the gut bacteria associated with TMA metabolism, along with decreased Bifidobacterium species. Our data support the impact of MSG consumption on liver and kidney metabolism. Based on the gut microbiome changes, we speculate that TMA and its metabolites such as trimethylamine-N-oxide (TMAO) may be mediators of the effects of MSG on the kidney health.

scholarly journals Different analysis strategies of 16S rRNA gene data from rodent studies generate contrasting views of gut bacterial communities associated with diet, health and obesity

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10372
Author(s):  
Jose F. Garcia-Mazcorro ◽  
Jorge R. Kawas ◽  
Cuauhtemoc Licona Cassani ◽  
Susanne Mertens-Talcott ◽  
Giuliana Noratto
Keyword(s):  
16S Rrna ◽  
Gut Microbiota ◽  
16S Rrna Gene ◽  
Relative Abundance ◽  
Bacterial Communities ◽  
Future Research ◽  
Rrna Gene ◽  
Microbial Composition ◽  
Analysis Strategies ◽  
The Impact

Background One of the main functions of diet is to nurture the gut microbiota and this relationship affects the health of the host. However, different analysis strategies can generate different views on the relative abundance of each microbial taxon, which can affect our conclusions about the significance of diet to gut health in lean and obese subjects. Here we explored the impact of using different analysis strategies to study the gut microbiota in a context of diet, health and obesity. Methods Over 15 million 16S rRNA gene sequences from published studies involving dietary interventions in obese laboratory rodents were analyzed. Three strategies were used to assign the 16S sequences to Operational Taxonomic Units (OTUs) based on the GreenGenes reference OTU sequence files clustered at 97% and 99% similarity. Results Different strategies to select OTUs influenced the relative abundance of all bacterial taxa, but the magnitude of this phenomenon showed a strong study effect. Different taxa showed up to 20% difference in relative abundance within the same study, depending on the analysis strategy. Very few OTUs were shared among the samples. ANOSIM test on unweighted UniFrac distances showed that study, sequencing technique, animal model, and dietary treatment (in that order) were the most important factors explaining the differences in bacterial communities. Except for obesity status, the contribution of diet and other factors to explain the variability in bacterial communities was lower when using weighted UniFrac distances. Predicted functional profile and high-level phenotypes of the microbiota showed that each study was associated with unique features and patterns. Conclusions The results confirm previous findings showing a strong study effect on gut microbial composition and raise concerns about the impact of analysis strategies on the membership and composition of the gut microbiota. This study may be helpful to guide future research aiming to investigate the relationship between diet, health, and the gut microbiota.

scholarly journals Recipe for a Healthy Gut: Intake of Unpasteurised Milk Is Associated with Increased Lactobacillus Abundance in the Human Gut Microbiome

Nutrients ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1468
Author(s):  
Mary I. Butler ◽  
Thomaz F. S. Bastiaanssen ◽  
Caitriona Long-Smith ◽  
Kirsten Berding ◽  
Sabrina Morkl ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Gut Microbiome ◽  
Dairy Products ◽  
Human Gut ◽  
Microbiome Composition ◽  
Organic Farm ◽  
Functional Richness ◽  
Genus Lactobacillus ◽  
The Impact ◽  
Milk And Dairy Products

Introduction: The gut microbiota plays a role in gut–brain communication and can influence psychological functioning. Diet is one of the major determinants of gut microbiota composition. The impact of unpasteurised dairy products on the microbiota is unknown. In this observational study, we investigated the effect of a dietary change involving intake of unpasteurised dairy on gut microbiome composition and psychological status in participants undertaking a residential 12-week cookery course on an organic farm. Methods: Twenty-four participants completed the study. The majority of food consumed during their stay originated from the organic farm itself and included unpasteurised milk and dairy products. At the beginning and end of the course, participants provided faecal samples and completed self-report questionnaires on a variety of parameters including mood, anxiety and sleep. Nutrient intake was monitored with a food frequency questionnaire. Gut microbiota analysis was performed with 16S rRNA gene sequencing. Additionally, faecal short chain fatty acids (SCFAs) were measured. Results: Relative abundance of the genus Lactobacillus increased significantly between pre- and post-course time points. This increase was associated with participants intake of unpasteurised milk and dairy products. An increase in the faecal SCFA, valerate, was observed along with an increase in the functional richness of the microbiome profile, as determined by measuring the predictive neuroactive potential using a gut–brain module approach. Conclusions: While concerns in relation to safety need to be considered, intake of unpasteurised milk and dairy products appear to be associated with the growth of the probiotic bacterial genus, Lactobacillus, in the human gut. More research is needed on the effect of dietary changes on gut microbiome composition, in particular in relation to the promotion of bacterial genera, such as Lactobacillus, which are recognised as being beneficial for a range of physical and mental health outcomes.

scholarly journals Antidepressants fluoxetine and amitriptyline induce alterations in intestinal microbiota and gut microbiome function in rats exposed to chronic unpredictable mild stress

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Weijie Zhang ◽  
Wan Qu ◽  
Hua Wang ◽  
He Yan
Keyword(s):  
Gut Microbiota ◽  
Oral Administration ◽  
Relative Abundance ◽  
Gut Microbiome ◽  
Antidepressant Treatment ◽  
Species Abundance ◽  
Tricyclic Antidepressant ◽  
Mild Stress ◽  
Chronic Unpredictable Mild Stress ◽  
The Impact

AbstractAntidepressant medications are known to modulate the central nervous system, and gut microbiota can play a role in depression via microbiota–gut–brain axis. But the impact of antidepressants on gut microbiota function and composition remains poorly understood. Thus this study assessed the effect of serotonin reuptake inhibitor antidepressant fluoxetine (Flu) and tricyclic antidepressant amitriptyline (Ami) administration on gut microbiota composition, diversity, and species abundance, along with microbial function in a chronic unpredictable mild stress (CUMS)-induced depression rat model. Oral administration of Ami and Flu significantly altered the overall gut microbiota profile of CUMS-induced rats, as assessed using the permutational multivariate analysis of variance test. At the phylum level, 6-week of antidepressant treatment led to a decreased Firmicutes/Bacteroidetes ratio due to an enhanced Bacteroidetes and reduced Firmicutes relative abundance. Flu was more potent than Ami at altering the Firmicutes and Bacteroidetes levels in the CUMS rats. At the family level, both antidepressants significantly increased the abundance of Porphyromonadaceae. However, an increased Bacteroidaceae level was significantly associated with Ami, not Flu treatment. Furthermore, at the genus level, an increase in the relative abundance of Parabacteroides, Butyricimonas, and Alistipes was observed following Ami and Flu treatment. Subsequent metagenomics and bioinformatics analysis further indicated that Ami and Flu likely also modulated metabolic pathways, such as those involved in carbohydrate metabolism, membrane transport, and signal transduction. Additionally, both antidepressants affected antibiotic resistome, such as for aminoglycoside (aph3iiiA), multidrug (mdtK, mdtP, mdtH, mdtG, acrA), and tetracycline (tetM) resistance in CUMS rats. These data clearly illustrated the direct impact of oral administration of Flu and Ami on the gut microbiome, thus set up the foundation to reveal more insights on the therapeutic function of the antidepressants and their overall contribution to host health.

scholarly journals Comprehensive mouse gut metagenome catalog reveals major difference to the human counterpart

2021 ◽  
Author(s):  
Silas Kieser ◽  
Evgeny M. Zdobnov ◽  
Mirko Trajkovski
Keyword(s):  
Gut Microbiota ◽  
Gut Microbiome ◽  
New Order ◽  
Human Gut ◽  
Rarefaction Analysis ◽  
Human Counterpart ◽  
The Impact ◽  
Human And Mouse ◽  
Gut Metagenome ◽  
Mouse Gut Microbiota

AbstractMouse is the most used model for studying the impact of microbiota on its host, but the repertoire of species from the mouse gut microbiome remains largely unknown. Here, we construct a Comprehensive Mouse Gut Metagenome (CMGM) catalog by assembling all currently available mouse gut metagenomes and combining them with published reference and metagenome-assembled genomes. The 50’011 genomes cluster into 1’699 species, of which 78.1% are uncultured, and we discovered 226 new genera, 7 new families, and 1 new order. Rarefaction analysis indicates comprehensive sampling of the species from the mouse gut. CMGM enables an unprecedented coverage of the mouse gut microbiome exceeding 90%. Comparing CMGM to the human gut microbiota shows an overlap 64% at the genus, but only 16% at the species level, demonstrating that human and mouse gut microbiota are largely distinct.

scholarly journals The Impact of Anthelmintic Treatment on Human Gut Microbiota Based on Cross-Sectional and Pre- and Postdeworming Comparisons in Western Kenya

mBio ◽  
2019 ◽  
Vol 10 (2) ◽  
Author(s):  
Alice V. Easton ◽  
Mariam Quiñones ◽  
Ivan Vujkovic-Cvijin ◽  
Rita G. Oliveira ◽  
Stella Kepha ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Gut Microbiome ◽  
Intestinal Parasites ◽  
Fold Change ◽  
Rrna Gene ◽  
Human Gut ◽  
Microbial Composition ◽  
Content Type ◽  
Average Fold Change ◽  
The Impact

ABSTRACT Murine studies suggest that the presence of some species of intestinal helminths is associated with changes in host microbiota composition and diversity. However, studies in humans have produced varied conclusions, and the impact appears to vary widely depending on the helminth species present. To demonstrate how molecular approaches to the human gut microbiome can provide insights into the complex interplay among disparate organisms, DNA was extracted from cryopreserved stools collected from residents of 5 rural Kenyan villages prior to and 3 weeks and 3 months following albendazole (ALB) therapy. Samples were analyzed by quantitative PCR (qPCR) for the presence of 8 species of intestinal parasites and by MiSeq 16S rRNA gene sequencing. Based on pretreatment results, the presence of neither Ascaris lumbricoides nor Necator americanus infection significantly altered the overall diversity of the microbiota in comparison with age-matched controls. Following ALB therapy and clearance of soil-transmitted helminths (STH), there were significant increases in the proportion of the microbiota made up by Clostridiales (P = 0.0002; average fold change, 0.57) and reductions in the proportion made up by Enterobacteriales (P = 0.0004; average fold change, −0.58). There was a significant posttreatment decrease in Chao1 richness, even among individuals who were uninfected pretreatment, suggesting that antimicrobial effects must be considered in any posttreatment setting. Nevertheless, the helminth-associated changes in Clostridiales and Enterobacteriales suggest that clearance of STH, and of N. americanus in particular, alters the gut microbiota. IMPORTANCE The gut microbiome is an important factor in human health. It is affected by what we eat, what medicines we take, and what infections we acquire. In turn, it affects the way we absorb nutrients and whether we have excessive intestinal inflammation. Intestinal worms may have an important impact on the composition of the gut microbiome. Without a complete understanding of the impact of mass deworming programs on the microbiome, it is impossible to accurately calculate the cost-effectiveness of such public health interventions and to guard against any possible deleterious side effects. Our research examines this question in a “real-world” setting, using a longitudinal cohort, in which individuals with and without worm infections are treated with deworming medication and followed up at both three weeks and three months posttreatment. We quantify the impact of roundworms and hookworms on gut microbial composition, suggesting that the impact is small, but that treatment of hookworm infection results in significant changes. This work points to the need for follow-up studies to further examine the impact of hookworm on the gut microbiota and determine the health consequences of the observed changes.

scholarly journals Assessment of Bidirectional Relationships Between 98 Genera of the Human Gut Microbiota and Amyotrophic Lateral Sclerosis: A 2-Sample Mendelian Randomization Study

2021 ◽  
Author(s):  
Linjing Zhang ◽  
Zhenhuang Zhuang ◽  
Gan Zhang ◽  
Tao Huang ◽  
Dongsheng Fan
Keyword(s):  
Gut Microbiota ◽  
Relative Abundance ◽  
Gut Microbiome ◽  
Human Gut ◽  
Standard Deviation Increase ◽  
Inverse Variance ◽  
Bidirectional Relationship ◽  
Weighted Median ◽  
Log Odds ◽  
Lateral Sclerosis

Abstract BackgroundGrowing evidence suggests a mutual interaction between gut microbiome alterations and ALS pathogenesis. However, previous studies were susceptible to potential confounding factors and reverse causation bias, likely leading to inconsistent and biased results. Therefore, to decipher the potentially mutual relationship between gut microbiota and ALS, we used a bidirectional two-sample MR approach to examine the associations between the gut microbiome and ALS. Effects of potential metabolites on ALS were also estimated in MR design.ResultsUsing the inverse variance-weighted method, OTU10032 unclassified Enterobacteriaceae species-level OTU and unclassified Acidaminococcaceae were associated with a higher risk of ALS (per relative abundance: OR, 1.04; 95% CI, 1.01–1.07; P = 0.011 and OR, 1.02; 95% CI, 1.01–1.04; P = 0.009, respectively). Importantly, Gamma-Glu-Phe was showed potential deleterious effects on the risk of ALS (genetically predicted per a 1-standard deviation increase in the level of Gamma-Glu-Phe: OR, 1.96; 95% CI, 1.50–2.55; P = 0.012). Sensitivity analysis of the two candidate genera and metabolites using the MR-Egger and weighted-median methods produced similar estimates, and no horizontal pleiotropy or outliers were observed. Intriguingly, genetically predicted ALS was associated with an increase in the relative abundance of OTU4607_Sutterella (per 1-unit higher log odds: β, 2.23; 95% CI, 1.27–3.18; P = 0.020) and Lactobacillales_ORDER (per 1-unit higher log odds: β, 0.51; 95% CI, 0.09–0.94; P = 0.019).ConclusionsOur findings provide novel evidence supporting the bidirectional relationship between the gut microbiota and ALS and highlight that a transsynaptic, glutaminergic, excitotoxic mechanism could provide a pathogenic basis for ALS. These results may contribute to designing microbiome- and microbiome-dependent metabolite interventions in future ALS clinical trials.

scholarly journals Assessment of bidirectional relationships between 98 genera of the human gut microbiota and amyotrophic lateral sclerosis: a 2-sample Mendelian randomization study

BMC Neurology ◽  
2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Linjing Zhang ◽  
Zhenhuang Zhuang ◽  
Gan Zhang ◽  
Tao Huang ◽  
Dongsheng Fan
Keyword(s):  
Gut Microbiota ◽  
Relative Abundance ◽  
Gut Microbiome ◽  
Human Gut ◽  
Standard Deviation Increase ◽  
Inverse Variance ◽  
Bidirectional Relationship ◽  
Weighted Median ◽  
Log Odds ◽  
Lateral Sclerosis

Abstract Background Growing evidence suggests a mutual interaction between gut microbiome alterations and ALS pathogenesis. However, previous studies were susceptible to potential confounding factors and reverse causation bias, likely leading to inconsistent and biased results. Objectives To decipher the potentially mutual relationship between gut microbiota and ALS, we used a bidirectional two-sample MR approach to examine the associations between the gut microbiome and ALS. Results Using the inverse variance-weighted method, OTU10032 unclassified Enterobacteriaceae species-level OTU and unclassified Acidaminococcaceae were associated with a higher risk of ALS (per relative abundance: OR, 1.04; 95% CI, 1.01–1.07; P = 0.011 and OR, 1.02; 95% CI, 1.01–1.04; P = 0.009, respectively). Importantly, Gamma-Glu-Phe was showed potential deleterious effects on the risk of ALS (genetically predicted per a 1-standard deviation increase in the level of Gamma-Glu-Phe: OR, 1.96; 95% CI, 1.50–2.55; P = 0.012). Sensitivity analysis of the two candidate genera and metabolites using the MR-Egger and weighted-median methods produced similar estimates, and no horizontal pleiotropy or outliers were observed. Intriguingly, genetically predicted ALS was associated with an increase in the relative abundance of OTU4607_Sutterella (per 1-unit higher log odds: β, 2.23; 95% CI, 1.27–3.18; P = 0.020) and Lactobacillales_ORDER (per 1-unit higher log odds: β, 0.51; 95% CI, 0.09–0.94; P = 0.019). Conclusions Our findings provide novel evidence supporting the bidirectional relationship between the gut microbiota and ALS. These results may contribute to designing microbiome- and microbiome-dependent metabolite interventions in future ALS clinical trials.

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