scholarly journals The Adult Phenylketonuria (PKU) Gut Microbiome

2021 ◽  
Vol 9 (3) ◽  
pp. 530
Author(s):  
Viviana J. Mancilla ◽  
Allison E. Mann ◽  
Yan Zhang ◽  
Michael S. Allen
Keyword(s):  
Gut Microbiome ◽  
Community Diversity ◽  
Rrna Gene ◽  
Dietary Interventions ◽  
Dietary Restrictions ◽  
Stool Samples ◽  
Phenylalanine Metabolism ◽  
Restrictive Diet ◽  
And Control ◽  
Amino Acid Formula

Phenylketonuria (PKU) is an inborn error of phenylalanine metabolism primarily treated through a phenylalanine-restrictive diet that is frequently supplemented with an amino acid formula to maintain proper nutrition. Little is known of the effects of these dietary interventions on the gut microbiome of PKU patients, particularly in adults. In this study, we sequenced the V4 region of the 16S rRNA gene from stool samples collected from adults with PKU (n = 11) and non-PKU controls (n = 21). Gut bacterial communities were characterized through measurements of diversity and taxa abundance. Additionally, metabolic imputation was performed based on detected bacteria. Gut community diversity was lower in PKU individuals, though this effect was only statistically suggestive. A total of 65 genera across 5 phyla were statistically differentially abundant between PKU and control samples (p < 0.001). Additionally, we identified six metabolic pathways that differed between groups (p < 0.05), with four enriched in PKU samples and two in controls. While the child PKU gut microbiome has been previously investigated, this is the first study to explore the gut microbiome of adult PKU patients. We find that microbial diversity in PKU children differs from PKU adults and highlights the need for further studies to understand the effects of dietary restrictions.

scholarly journals Comparative Analysis of Fecal Microbiota Composition Between Rheumatoid Arthritis and Osteoarthritis Patients

Genes ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 748 ◽  
Author(s):  
Jin-Young Lee ◽  
Mohamed Mannaa ◽  
Yunkyung Kim ◽  
Jehun Kim ◽  
Geun-Tae Kim ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gut Microbiota ◽  
Gut Microbiome ◽  
Bacterial Species ◽  
Amplicon Sequencing ◽  
Fecal Microbiota ◽  
Rrna Gene ◽  
Microbiota Composition ◽  
Stool Samples ◽  
Gut Microbiota Composition

The aim of this study was to investigate differences between the gut microbiota composition in patients with rheumatoid arthritis (RA) and those with osteoarthritis (OA). Stool samples from nine RA patients and nine OA patients were collected, and DNA was extracted. The gut microbiome was assessed using 16S rRNA gene amplicon sequencing. The structures and differences in the gut microbiome between RA and OA were analyzed. The analysis of diversity revealed no differences in the complexity of samples. The RA group had a lower Bacteroidetes: Firmicutes ratio than did the OA group. Lactobacilli and Prevotella, particularly Prevotella copri, were more abundant in the RA than in the OA group, although these differences were not statistically significant. The relative abundance of Bacteroides and Bifidobacterium was lower in the RA group. At the species level, the abundance of certain bacterial species was significantly lower in the RA group, such as Fusicatenibacter saccharivorans, Dialister invisus, Clostridium leptum, Ruthenibacterium lactatiformans, Anaerotruncus colihominis, Bacteroides faecichinchillae, Harryflintia acetispora, Bacteroides acidifaciens, and Christensenella minuta. The microbial properties of the gut differed between RA and OA patients, and the RA dysbiosis revealed results similar to those of other autoimmune diseases, suggesting that a specific gut microbiota pattern is related to autoimmunity.

scholarly journals The Microbiota Diversity Following Antibiotic Treatment of Clostridium Difficile Infection

2020 ◽  
Author(s):  
Dana Binyamin ◽  
Orna Nitzan ◽  
Maya Azrad ◽  
Zohar Hamo ◽  
Omry Koren ◽  
...  
Keyword(s):  
Clostridium Difficile ◽  
Gut Microbiota ◽  
Antibiotic Treatment ◽  
Gut Microbiome ◽  
Diarrheal Disease ◽  
Medical Center ◽  
Disease Onset ◽  
Intestinal Microbiome ◽  
Rrna Gene ◽  
Stool Samples

Abstract Background: Clostridium difficile (C. difficile) is a major nosocomial pathogen that infects the human gut and can cause diarrheal disease. A dominant risk factor is antibiotic treatment that disrupts the normal gut microbiota. The aim of the study was to examine the correlation between antibiotic treatment received prior to C. difficile infection (CDI) onset and patient gut microbiota.Methods: Stool samples were collected from patients with CDI, presenting at the Baruch Padeh Medical Center Poriya, Israel. Demographic and clinical information, including previous antibiotic treatments, was collected from patient charts, and CDI severity score was calculated. Bacteria were isolated from stool samples, and gut microbiome was analyzed by sequencing the 16S rRNA gene using the Illumina MiSeq platform and QIIME2.Results: In total, 84 patients with C. difficile infection were enrolled in the study; all had received antibiotics prior to disease onset. Due to comorbidities, 46 patients (55%) had received more than one class of antibiotics. The most common class of antibiotics used was cephalosporins (n=44 cases). The intestinal microbiota of the patients was not uniform. Differences in intestinal microbiome were influenced by the different combinations of antibiotics that the patients had received (p = 0.022)Conclusions: The number of different antibiotics administered has a major impact on the CDI patients gut microbiome, mainly on bacterial richness.

scholarly journals Microbiota diversity following antibiotic treatment of Clostridium difficile infection

2020 ◽  
Author(s):  
Dana Binyamin ◽  
Orna Nitzan ◽  
Maya Azrad ◽  
Zohar Hamo ◽  
Omry Koren ◽  
...  
Keyword(s):  
Clostridium Difficile ◽  
Gut Microbiota ◽  
Antibiotic Treatment ◽  
Gut Microbiome ◽  
Diarrheal Disease ◽  
Medical Center ◽  
Disease Onset ◽  
Intestinal Microbiome ◽  
Rrna Gene ◽  
Stool Samples

Abstract Background: Clostridium difficile (C. difficile) is a major nosocomial pathogen that infects the human gut and can cause C. difficile infection (CDI), a diarrheal disease. A dominant risk factor is antibiotic treatment, which disrupts the normal gut microbiota. The aim of the study was to examine the correlation between antibiotic treatment received prior to CDI onset and patient gut microbiota during the infection.Methods: Stool samples were collected from patients with CDI, presenting at the Baruch Padeh Medical Center Poriya, Israel. Demographic and clinical information, including previous antibiotic treatments, was collected from patient charts, and CDI severity score was calculated. Bacteria were isolated from stool samples, and gut microbiome was analyzed by sequencing the 16S rRNA gene, using the Illumina MiSeq platform and QIIME2.Results: In total, 84 patients with CDI were enrolled in the study; all had received antibiotics prior to disease onset. Due to comorbidities, 46 patients (55%) received more than one class of antibiotics. The most common class of antibiotics used was cephalosporins (n=44 cases). The intestinal microbiota of the patients was not uniform. Differences in intestinal microbiome were influenced by the different numbers of antibiotics families that the patients received (p = 0.022)Conclusions: The number of different antibiotics amount has a major impact on the gut microbiome of CDI patients, particularly on its bacterial richness.

scholarly journals Dead or Alive? Molecular life-dead distinction in human stool samples reveals significantly different composition of the microbial community

2018 ◽  
Author(s):  
Alexandra Perras ◽  
Kaisa Koskinen ◽  
Maximilian Mora ◽  
Michael Beck ◽  
Lisa Wink ◽  
...  
Keyword(s):  
Microbial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Microbial Communities ◽  
Human Health ◽  
Gene Targeting ◽  
Gut Microbiome ◽  
Rrna Gene ◽  
Stool Samples ◽  
Human Stool

AbstractThe gut microbiome is strongly interwoven with human health. Conventional gut microbiome analysis generally involves 16S rRNA gene targeting next generation sequencing (NGS) of stool microbial communities, and correlation of results with clinical parameters. However, some microorganisms may not be alive at the time of sampling, and thus their impact on the human health is potentially less significant. As conventional NGS methods do not differentiate between viable and dead microbial components, retrieved results provide only limited information.Propidium monoazide (PMA) is frequently used in food safety monitoring and other disciplines to discriminate living from dead cells. PMA binds to free DNA and masks it for subsequent procedures. In this article we show the impact of PMA on the results of 16S rRNA gene-targeting NGS from human stool samples and validate the optimal applicable concentration to achieve a reliable detection of the living microbial communities.Fresh stool samples were treated with a concentration series of zero to 300 μM PMA, and were subsequently subjected to amplicon-based NGS. The results indicate that a substantial proportion of the human microbial community is not intact at the time of sampling. PMA treatment significantly reduced the diversity and richness of the sample depending on the concentration and impacted the relative abundance of certain important microorganisms (e.g. Akkermansia, Bacteroides). Overall, we found that a concentration of 100 μM PMA was sufficient to quench signals from disrupted microbial cells.The optimized protocol proposed here can be easily implemented in classical microbiome analyses, and helps to retrieve an improved and less blurry picture of the microbial community composition by excluding signals from background DNA.

scholarly journals Gut Microbiota-Targeted Diets Modulate Human Immune Status

2020 ◽  
Author(s):  
Hannah C. Wastyk ◽  
Gabriela K Fragiadakis ◽  
Dalia Perelman ◽  
Dylan Dahan ◽  
Bryan D Merrill ◽  
...  
Keyword(s):  
Immune System ◽  
Gut Microbiota ◽  
Gut Microbiome ◽  
Fermented Food ◽  
Community Diversity ◽  
Fermented Foods ◽  
Dietary Interventions ◽  
High Fiber ◽  
Prospective Study Design ◽  
Microbiota Diversity

AbstractDiet modulates the gut microbiome, and gut microbes, in turn, can impact the immune system. Here, we used two gut microbiota-targeted dietary interventions, plant-based fiber or fermented foods, to determine how each influences the human microbiome and immune system in healthy adults. Using a 17-week randomized, prospective study design combined with -omics measurements of microbiome and host, including extensive immune profiling, we found distinct effects of each diet. High-fiber consumers showed increased gut microbiome-encoded glycan-degrading CAZymes despite stable community diversity. Three distinct immunological trajectories in high fiber-consumers corresponded to baseline microbiota diversity. Alternatively, the high-fermented food diet steadily increased microbiota diversity and decreased inflammatory markers. The data highlight how coupling dietary interventions to deep and longitudinal immune and microbiome profiling can provide individualized and population-wide insight. Our results indicate that fermented foods may be valuable in countering the decreased microbiome diversity and increased inflammation pervasive in the industrialized society.

scholarly journals Sewage Reflects the Microbiomes of Human Populations

mBio ◽  
2015 ◽  
Vol 6 (2) ◽  
Author(s):  
Ryan J. Newton ◽  
Sandra L. McLellan ◽  
Deborah K. Dila ◽  
Joseph H. Vineis ◽  
Hilary G. Morrison ◽  
...  
Keyword(s):  
Microbial Community ◽  
Gut Microbiome ◽  
Marker Gene ◽  
Population Variation ◽  
Human Populations ◽  
Rrna Gene ◽  
Community Structures ◽  
Data Set ◽  
Stool Samples ◽  
Number Of Individuals

ABSTRACT Molecular characterizations of the gut microbiome from individual human stool samples have identified community patterns that correlate with age, disease, diet, and other human characteristics, but resources for marker gene studies that consider microbiome trends among human populations scale with the number of individuals sampled from each population. As an alternative strategy for sampling populations, we examined whether sewage accurately reflects the microbial community of a mixture of stool samples. We used oligotyping of high-throughput 16S rRNA gene sequence data to compare the bacterial distribution in a stool data set to a sewage influent data set from 71 U.S. cities. On average, only 15% of sewage sample sequence reads were attributed to human fecal origin, but sewage recaptured most (97%) human fecal oligotypes. The most common oligotypes in stool matched the most common and abundant in sewage. After informatically separating sequences of human fecal origin, sewage samples exhibited ~3× greater diversity than stool samples. Comparisons among municipal sewage communities revealed the ubiquitous and abundant occurrence of 27 human fecal oligotypes, representing an apparent core set of organisms in U.S. populations. The fecal community variability among U.S. populations was significantly lower than among individuals. It clustered into three primary community structures distinguished by oligotypes from either: Bacteroidaceae, Prevotellaceae, or Lachnospiraceae/Ruminococcaceae. These distribution patterns reflected human population variation and predicted whether samples represented lean or obese populations with 81 to 89% accuracy. Our findings demonstrate that sewage represents the fecal microbial community of human populations and captures population-level traits of the human microbiome. IMPORTANCE The gut microbiota serves important functions in healthy humans. Numerous projects aim to define a healthy gut microbiome and its association with health states. However, financial considerations and privacy concerns limit the number of individuals who can be screened. By analyzing sewage from 71 cities, we demonstrate that geographically distributed U.S. populations share a small set of bacteria whose members represent various common community states within U.S. adults. Cities were differentiated by their sewage bacterial communities, and the community structures were good predictors of a city's estimated level of obesity. Our approach demonstrates the use of sewage as a means to sample the fecal microbiota from millions of people and its potential to elucidate microbiome patterns associated with human demographics.

scholarly journals The effect of toxic pyridine-alkaloid secondary metabolites on the sunbird gut microbiome

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Mohanraj Gunasekaran ◽  
Maya Lalzar ◽  
Yehonatan Sharaby ◽  
Ido Izhaki ◽  
Malka Halpern
Keyword(s):  
Secondary Metabolites ◽  
Gut Microbiota ◽  
Gut Microbiome ◽  
Amplicon Sequencing ◽  
Control Group ◽  
Rrna Gene ◽  
Microbiota Composition ◽  
Degrading Bacteria ◽  
And Control ◽  
Gut Microbiota Composition

AbstractSunbirds feed on tobacco tree nectar which contains toxic nicotine and anabasine secondary metabolites. Our aim was to understand the effect of nicotine and anabasine on the gut microbiota composition of sunbirds. Sixteen captive sunbirds were randomly assigned to two diets: artificial nectar either with (treatment) or without (control) added nicotine and anabasine. Excreta were collected at 0, 2, 4 and 7 weeks of treatment and samples were processed for bacterial culture and high-throughput amplicon sequencing of the 16S rRNA gene. The gut microbiome diversity of the treated and control birds changed differently along the seven-week experiment. While the diversity decreased in the control group along the first three samplings (0, 2 and 4 weeks), it increased in the treatment group. The microbiota composition analyses demonstrated that a diet with nicotine and anabasine, significantly changed the birds’ gut microbiota composition compared to the control birds. The abundance of nicotine- and anabasine- degrading bacteria in the excreta of the treated birds, was significantly higher after four and seven weeks compared to the control group. Furthermore, analysis of culturable isolates, including Lactococcus, showed that sunbirds’ gut-associated bacteria were capable of degrading nicotine and anabasine, consistent with their hypothesised role as detoxifying and nutritional symbionts.

scholarly journals 680 Automated Ion torrent based solution enables accurate gut microbiome quantification of bacterial species relevant to research in cancer and its response to immunotherapy

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A719-A719
Author(s):  
Shrutii Sarda ◽  
David Merrill ◽  
Heesun Shin ◽  
Anna McGeachy ◽  
Birgit Drews ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Small Cell Lung Carcinoma ◽  
Phenotypic Variability ◽  
Bacterial Species ◽  
Human Microbiome ◽  
Species Level ◽  
Rrna Gene ◽  
List Type ◽  
Cell Lung Carcinoma ◽  
Stool Samples

BackgroundA low-cost targeted solution to profiling gut microbial diversity is sequencing of the 16S rRNA gene; however, it is often insufficient to gain species level resolution due to high homology across different bacteria. Therefore, we developed a first-of-its-kind targeted sequencing solution that supplements 16S gene targets, with highly species-specific primers for a cohort of 73 bacteria associated with research in diabetes, cancer and its response to immunotherapy, gastrointestinal and auto-immune disorders. This assay performs at 100% sensitivity and specificity for the species-level detection (Ion AmpliSeq Microbiome Health Research Kit: www.thermofisher.com/ngsmicrobiome) of these bacteria and is hence better suited for gut microbiome profiling in the context of the above phenotypes, as compared to other existing solutions.MethodsTo assess the utility of the panel in cancer immunotherapy research, we sequenced DNA from 15 stool samples from subjects with Non-Small Cell Lung Carcinoma (NSCLC) undergoing immunotherapy, and compared their microbiome profiles to 26 healthy stool samples collected internally. With our post-sequencing workflow on Ion Reporter™, we automatically generate a report with taxonomic classifications, sample diversity metrics through QIIME2 integration, and relative abundance visualizations for bacteria across multiple samples.ResultsWe identified significant microbiome composition differences between the healthy samples and cancer/treated samples, as evidenced by (i) a clear separation between the two cohorts based on a beta diversity principal coordinate analysis (PCoA) plot, driven by large abundance changes in Clostridium, Lachnoclostridium, Subdolinigranulum and Oscillibacter (P < 0.05), (ii) grouping into distinct classes based on overall microbiome profiles (Analysis-of-Similarities ANOSIM P = 0.003), and (iii) differences in abundances of specific bacteria with anti-tumor effects1 such as F. prausnitzii (P = 0.02).ConclusionsWe have created a highly multiplexed, sensitive and specific assay for robust characterization of gut microbiota, with compatibility on both (i) the Ion GeneStudio S5™ with a 48-hr sample-to-result turnaround, and (ii) the new Ion Genexus™ System, a fully integrated platform featuring a hands-off, automated sample-to-report workflow that delivers results in a single day. It enables an efficient and affordable means for conducting extensive analyses of the human microbiome having applications in the study of phenotypic variability, and the potential relationship to disease.For research use only. Not for use in diagnostic procedures.ReferenceMa J, Sun L, Liu Y. et al. Alter between gut bacteria and blood metabolites and the anti-tumor effects of Faecalibacterium prausnitzii in breast cancer. BMC Microbiol 2020; 20:1–19.

scholarly journals Characterization of gut microbiome and metabolome in Helicobacter pylori patients in an underprivileged community in the United States

2021 ◽  
Author(s):  
Brian White ◽  
John Sterrett ◽  
Zoya Grigoryan ◽  
Lauren Lally ◽  
Jared Heinze ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Helicobacter Pylori ◽  
Fatty Acid ◽  
Gut Microbiome ◽  
Rrna Gene ◽  
Fecal Microbiome ◽  
Control Subjects ◽  
Stool Samples ◽  
H Pylori

Background: Helicobacter pylori, a bacterium that infects approximately half of the world population, is associated with various gastrointestinal diseases, including peptic ulcers, non-ulcer dyspepsia, gastric adenocarcinoma, and gastric lymphoma. To combat the increasing antibiotic resistance of H. pylori, the need for new therapeutic strategies has become more pressing. Characterization of the interactions between H. pylori and the fecal microbiome, as well as the mechanisms underlying these interactions, may offer new therapeutic approaches. Exploration of changes in fatty acid metabolism associated with H. pylori-mediated alterations of the fecal microbiome may also reveal strategies to help prevent progression to neoplasia. Aim: To characterize the gut microbiome and metabolome in H. pylori patients in a socioeconomically challenged and underprivileged inner-city community. Methods: Stool samples from 19 H. pylori patients and 16 control subjects were analyzed. 16S rRNA gene sequencing was performed on normalized pooled amplicons using the Illumina MiSeq System using a MiSeq reagent kit v2. Alpha and beta diversity analyses were performed in QIIME 2. Non-targeted fatty acid analysis of the samples was carried out using gas chromatography-mass spectrometry (GC-MS), which measures the total content of 30 fatty acids in stool after conversion into their corresponding fatty acid methyl esters. Multi-dimensional scaling (MDS) was performed on Bray-Curtis distance matrices created from both the metabolomics and microbiome datasets and a Procrustes test was performed on the metabolomics and microbiome MDS coordinates. Results: Fecal microbiome analysis showed that alpha diversity was lowest in H. pylori patients over 40 years of age compared to control subjects of similar age group. Beta diversity analysis of the samples revealed significant differences in microbial community structure between H. pylori patients and control subjects. Thirty-eight and six taxa had lower and higher relative abundance in H. pylori patients, respectively. Taxa that were enriched in H. pylori patients included Atopobium, Gemellaceae, Micrococcaceae, Gemellales and Rothia (R. mucilaginosa). Notably, relative abundance of the phylum Verrucomicrobia was decreased in H. pylori patients compared to control subjects, suggesting disruption of the gut mucosal environment by H. pylori. Procrustes analysis showed a significant relationship between the microbiome and metabolome datasets. Stool samples from H. pylori patients showed increases in several fatty acids including the polyunsaturated fatty acids (PUFAs) 22:4n6, 22:5n3, 20:3n6 and 22:2n6, while decreases were noted in other fatty acids including the PUFA 18:3n6. The pattern of changes in fatty acid concentration correlated to the Bacteroidetes:Firmicutes ratio determined by 16S rRNA gene analysis. Conclusion: An individualized understanding of gut microbiome features among H. pylori patients will pave the way for improved community impact, reduced healthcare burdens of repeated treatment, and decreased mounting resistance.

scholarly journals The microbiota diversity following antibiotic treatment in Clostridium difficile infection

2020 ◽  
Author(s):  
Dana Binyamin ◽  
Orna Nitzan ◽  
Maya Azrad ◽  
Zohar Hamo ◽  
Omry Koren ◽  
...  
Keyword(s):  
Clostridium Difficile ◽  
Gut Microbiota ◽  
Antibiotic Treatment ◽  
Gut Microbiome ◽  
Diarrheal Disease ◽  
Medical Center ◽  
Disease Onset ◽  
Intestinal Microbiome ◽  
Rrna Gene ◽  
Stool Samples

Abstract Background Clostridium difficile ( C. difficile ) is a major nosocomial pathogen that infect the human gut and can cause C. difficile infection (CDI), a diarrheal disease. A dominant risk factor is antibiotic treatment that disrupts the normal gut microbiota. The aim of the study is to examine the correlation between antibiotic treatment received prior to C. difficile infection (CDI) onset and patient gut microbiota Methods Stool samples were collected from patients with CDI, presenting at the Baruch Padeh Medical Center Poriya, Israel. Demographic and clinical information, including previous antibiotic treatments, was collected from patient charts, and CDI severity score was calculated. Bacteria were isolated from stool samples, and gut microbiome was analyzed by sequencing the 16S rRNA gene using the Illumina MiSeq platform and QIIME2. Results In total, 84 patients with C. difficile infection were enrolled in the study; all had received antibiotics prior to disease onset. Due to comorbidities, 46 patients (55%) received more than one class of antibiotics. The most common class of antibiotics used was cephalosporins (n=44 cases). The intestinal microbiota of the patients was not uniform. Differences in intestinal microbiome were influenced by the different combinations of antibiotics that the patients received ( p = 0.022) Conclusions The number of different antibiotics combinations has a major impact on the CDI patients gut microbiome, mainly on bacterial richness.

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