Accumulating evidence shows that Helicobacter pylori protects against some metabolic and immunological diseases in which the development of these diseases coincide with temporal or permanent dysbiosis. The aim of this study was to assess the effect of H. pylori eradication on the human gut microbiome.
As part of the currently on-going ESSAY (Eradication Study in Stable Adults/Youths) study, we collected stool samples from 17 H. pylori-positive young adult (18–30 years-old) volunteers. The same cohort was followed up 6, 12 and 18 months-post H. pylori eradication. The impact of H. pylori on the human gut microbiome pre- and post-eradication was investigated using high throughput 16S rRNA gene (V3-V4 region) sequencing using the Illumina Miseq followed by data analysis using Qiime pipeline.
We compared the composition and diversity of bacterial communities in the fecal microbiome of the H. pylori-positive volunteers, before and after H. pylori eradication therapy. The 16S rRNA gene was sequenced at an average of 150,000–170,000 reads/sample. The microbial diversity were similar pre- and post-H. pylori eradication with no significant differences in richness and evenness of bacterial species. Despite that the general profile of the gut microbiome was similar pre- and post-eradication, some changes in the bacterial communities at the phylum and genus levels were notable, particularly the decrease in relative abundance of Bacterioidetes and corresponding increase in Firmicutes after H. pylori eradication. The significant increase of short-chain fatty acids (SCFA)-producing bacteria genera could also be associated with increased risk of metabolic disorders.
Our preliminary stool metagenomics study shows that eradication of H. pylori caused perturbation of the gut microbiome and may indirectly affect the health of human. Clinicians should be aware of the effect of broad spectrum antibiotics used in H. pylori eradication regimen and be cautious in the clinical management of H. pylori infection, particularly in immunocompromised patients.
Citation: Yap TW-C, Gan H-M, Lee Y-P, Leow AH-R, Azmi AN, Francois F, et al. (2016) Helicobacter pylori Eradication Causes Perturbation of the Human Gut Microbiome in Young Adults. PLoS ONE 11(3): e0151893. https://doi.org/10.1371/journal.pone.0151893
Editor: Jonathan H. Badger, National Cancer Institute, UNITED STATES
Received: December 23, 2015; Accepted: March 4, 2016; Published: March 18, 2016
Copyright: © 2016 Yap et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files. All metagenome sequence files are available in the MG-RAST server. The accession numbers were included in the paper.
Funding: This study was supported by the University of Malaya-Ministry of Education (UM-MOE) High Impact Research (HIR) Grant UM.C/HIR/MOE/13/4 (HIR Account No: H-50001-00-A000029), by the Diane Belfer Program for Human Microbial Ecology, the C and D fund (anonymous donors), and the Knapp Family Fund.
Competing interests: The authors have declared that no competing interests exist.
The human body routinely harbors approximately 100 trillion bacteria which outnumber our human cells by 10 to 1 . This bacterial population constitutes the microbiota and the majority of them living in the lower part of gastrointestinal tract. The human gut microbiota is an intricate and dynamic ecosystem that has coevolved with human for millions of years . It has been regarded as a metabolically active “organ” located within the human gastrointestinal tract [3, 4] as it has developed metabolic traits that complement host’s metabolism [5–8]. A healthy gastrointestinal system relies on a balanced commensal biota to regulate processes such as energy metabolism [9–12], elimination of pathogens [13–15] and influences the signaling pathways that range from modulation of the mucosal immune response  to development of metabolic diseases [9–11, 17, 18]. Accumulating evidence suggests that dysbiosis, or an abnormal microbiota, has been associated with an increasingly long list of diseases, including inflammatory bowel disease, obesity, and atopic diseases such as eczema and asthma [13, 19].
Helicobacter pylori is a Gram-negative, spiral-shaped, microaerophilic bacterium that colonizes the gastric mucosa of humans and non-human primates naturally. More than half of the world’s population is infected with H. pylori and its prevalence is as high as 80% in some populations . In a minority of those infected, H. pylori can cause peptic ulcers (10%), gastric cancer (1–2%), and rarely mucosa-associated lymphoid tissue (MALT) lymphoma . H. pylori is believed to colonize the stomach of humans at least since the initial migration of our ancestors from East Africa approximately 60,000 years ago . It has been postulated that H. pylori may be part of the human indigenous microbiome. However, due to socioeconomic development, modern hygienic practices and the advent of the antibiotics, the human gut microbiota is changing and H. pylori is gradually disappearing. There is an increasing number of epidemiological and experimental evidence for the protective effect of H. pylori infection on the development of obesity [23–25], childhood asthma , allergies , inflammatory bowel diseases , in which the development of these diseases coincide with either temporal or permanent dysbiosis.
Thus, in this study, we hypothesize that the eradication of H. pylori may cause perturbation of the GI microbiome, which can indirectly affect the health of human host. We investigated the effect of H. pylori eradication on the human gut microbiome using 16S rRNA gene amplicon metagenomics sequencing up to 18 months post-eradication.
Materials and Methods
Our study is part of the currently on-going ESSAY (Eradication Study in Stable Adults/Youths) study in Malaysia, New York and an European Center. In Malaysia, it was conducted at the University of Malaya Medical Centre (UMMC) between June 2012 and May 2014. Healthy young adults between the ages of 18–30 years old were first screened to assess study eligibility. The exclusion criteria for the study were diabetes, hyper or hypothyroidism, prior gastric or bariatric surgery, prior documented treatment of H. pylori, antibiotic use within 4 weeks of enrollment, steroid or other immunomodulating drugs use within 4 weeks of enrollment, recent vaccination and Charlson weighed comorbidity index <2. The study protocol was reviewed and approved by Medical Ethics Committee at UMMC (Ref No. 877.1). Written informed consent was obtained from qualified volunteers prior to study participation. H. pylori’s status of the qualified candidates was determined as previously described .
As we reported earlier, 57 (9.9%) of the 573 volunteers screened in the ESSAY study were tested positive for H. pylori using both non-radioactive 13C Urea Breath Test (UBT) and detection of anti-H. pylori antibodies and were considered as H. pylori-positive. However, only 32 agreed and consented to participate in the study . Of these 32 H. pylori positive volunteers, we only managed to collect stool samples from 17 of them. Treatment with a 7-day twice daily regimen and a proton pump inhibitor as current standard of care (amoxicillin 1000 mg, clarithromycin 500 mg, and pantoprazole 40 mg) was given to the volunteers and approximately 6 weeks after completing the treatment protocol, H. pylori eradication were ascertained using UBT. The volunteers were subsequently followed up at 6, 12, and 18 months post-H. pylori eradication. Stool samples were collected during each visit and frozen immediately at -80°C until DNA extraction.
Nucleic Acid Extraction from Stool Samples
Nucleic acid extraction was done using MoBio PowerSoil DNA Isolation Kit (Mo Bio Laboratories, Carlsbad, CA). The DNA extraction protocol was adopted from Section 7.9 Specimen Processing For Extraction of Bacterial Genomic DNA taken from Manual of Procedures for Human Microbiome Project: Core Microbiome Sampling Protocol A (HMP Protocol #07–001), Version 12.0 (http://www.hmpdacc.org/tools_protocols/tools_protocols.php) with slight modification . Instead of pre-processing the stool specimen with MoBio lysis buffer, approximately 100–200 mg of stool sample was added directly into PowerBead Tubes and vortexed to dispense the sample. The subsequent steps in the manufacturer’s protocol were followed accordingly.
16S rRNA Gene Amplification and Sequencing
The V3-V4 region of the bacterial 16S rRNA gene sequences were amplified using the primer pair 338F* (5′-NNNNCCTACGGGAGGCAGCAG-3′) and 1061R (5′-GACTACHVGGGTATCTAATCC-3′) containing the complete Illumina adapter [31, 32].
Briefly, each 50 μL of polymerase chain reaction (PCR) reaction contains 10 ng of fecal genomic DNA as template, 25 μL NEBNext High-Fidelity 2x PCR Master Mix (New England Biolabs, Ipswich, MA) and 1 μL of 10 μM of each primer. PCR reactions were carried out using the following protocol: (1) for the stool samples, an initial denaturation step performed at 98°C for 30 sec followed by 30 cycles of denaturation (98°C, 10 s), annealing (60°C, 10 s) and extension (72°C, 30 sec), and a final elongation of 1 min at 72°C. PCR products ~600 bases in size were gel-excised and purified using QIAquick Gel Extraction Kit (QIAGEN, Hilden, Germany). The libraries were quantified using KAPA library quantification kit (KAPA Biosystems, Capetown, South Africa), normalized, pooled and sequenced (2 x 250 bp paired-end read setting) on the MiSeq (Illumina, San Diego, CA) located at the Monash University Malaysia Genomics Facility.
Sequence pre-processing and quality filtering.
Demultiplexing and generation of raw fastq files for each individual library was performed on-board by the MiSeq Reporter Software. The forward and reverse 16S primer sequence located at the 5’ end of the forward and reverse reads, respectively, were trimmed using FASTX-Toolkit . The trimmed paired-end reads were subsequently overlapped using PEAR: Illumina Paired-End reAd mergeR (default setting) .
Analysis of quality filtered reads using Qiime.
The merged paired-end reads were analyzed using the Quantitative Insights into Microbial Ecology (Qiime)  pipeline. To perform detection and clustering of 16S rRNAs, an open-reference Operational Taxonomic Units (OTUs) picking approach was used. pick_open_reference_otus.py is the primary interface for open-reference OTU picking in QIIME, and includes taxonomy assignment, sequence alignment, and tree-building steps. In this open-reference OTU picking process, reads were firstly clustered against a Greengenes 13_8 reference sequence collection  (available at http://qiime.org/home_static/dataFiles.html) through closed-reference OTUs picking. Subsequently, 0.1% of the reads which failed to hit the reference sequence collection were randomly subsampled and clustered de novo using UCLUST , with an OTU cluster defined at a sequence similarity of 97%. Each cluster centroid was then chosen as a “new reference sequence” for another round of closed-reference OTU picking. OTU assignments for read that failed to hit the reference database were picked by an additional round of de novo clustering. The PyNAST alignment algorithm  was used to align the OTU representative sequences against the Greengenes core reference alignment  with a minimum identity of 75%, and then a phylogenetic tree was built using FastTree . Finally we generated a OTU table (biom summarize-table) for downstream diversity analysis by excluding the sequences that had failed to align by PyNAST. We also used the generated OTU table to summarize microbiome communities by taxonomic levels (by default: phylum, class, order, family, genus) based on different time-points (summarize_taxa_through_plots.py).
The raw data of the taxonomy summary results (.txt file) were exported to SPSS software version 20.0 (SPSS Inc., Chicago, IL) for statistical analysis. The mean abundance in percentage (%) and the 95% confidence interval (95% CI) for the phyla of stool microbiome at different time-points were calculated. Parametric paired-samples t-test was performed to compare the genera of the stool microbiome between Baseline vs. 6 months, Baseline vs. 12 months, and Baseline vs. 18 months post-H. pylori eradication; a two-tailed p-value of < 0.05 was considered significant. Pearson’s Correlation Coefficient was also performed to investigate the relationship between the phylum Bacteroidetes-to-Firmicutes ratio and the Body Mass Index (BMI) of the subjects across different time-points; a two-tailed p-value of < 0.05 was considered significant.
We evaluated samples for alpha diversity (microbial diversity within samples) and beta diversity (community diversity between samples) analysis using Qiime. Alpha diversity analysis (alpha_rarefaction.py) involves rarefaction analysis by subsampling OTU table on the basis of a minimum rarefaction depth value that is chosen depending on the minimum number of sequences/sample obtained. For our study, the rarefaction depth value for the comparison of Baseline and 6 months post-eradication was set as 82,536, the rarefaction depth value for the comparison of Baseline and 12 months post-eradication was set as 84,177, whereas the rarefaction depth value for the comparison of Baseline and 18 months post-eradication was set as 84,333. The alpha diversity was then calculated using both “non-phylogeny-based” (observed species, chao1, Shannon index) and “phlogeny-based” (PD whole tree) matrices for each rarefied OTU table. We compared the alpha diversity between different groups (time-points) of the samples by non-parametric two-sample t-test (compare_alpha_diversity.py).
Beta diversity between our samples was calculated using the default beta diversity metrics of weighted and unweighted UniFrac  (beta_diversity_through_plots.py) on even subsampled OTU table. The resulting UniFrac distance matrices were used to perform Principal Coordinate Analysis (PCoA) to determine the similarity between groups of samples/time-points. The PCoA plots in three dimensions were visualized using the Emperor tool . Non-parametric statistical analysis ANOSIM was performed via QIIME (compare_categories.py—method anosim) to test the statistical significance between different time-points (Baseline vs. 6 months post-eradication and Baseline vs. 12 months eradication).
Demographics of the Study Cohort
Stool samples from 17 H. pylori-positive healthy young Malaysian with a mean age of 25 years were collected. The volunteers were followed up after they were given H. pylori eradication therapy. Only 17, 10, and 6 stool samples were successfully collected at 6, 12, and 18 months post-eradication, respectively. All the 16S rRNA sequences were deposited in MetaGenome Rapid Annotation using Subsystem Technology (MG-RAST) under the accession numbers as shown in Table 1.
Characterization of Stool Microbiome
A total of 5,834,726 quality-filtered reads were obtained from Baseline vs. 6 months post-eradication group with an average of 171,610 ± 58,372 (standard deviation, SD) reads per sample, whilst, a total of 3,077,037 quality-filtered reads were obtained from Baseline vs. 12 months post-eradication group with an average of 153,852 ± 32,306 reads per sample. For Baseline vs. 18 months post-eradication group, a total of 2,000,505 quality-filtered reads with an average of 166,709 ± 69, 793 reads per sample were obtained. These reads were clustered into 45,875 unique OTUs at 97% sequence similarity in Baseline vs. 6 months post-eradication group with an average of 1349 OTUs per sample. In Baseline vs. 12 months post-eradication group, these reads were clustered into 31,351 unique OTUs at 97% sequence similarity with an average of 1568 OTUs per sample. In Baseline vs. 18 months post-eradication group, they were clustered into 28,157 unique OTUs at 97% sequence similarity with an average of 2346 OTUs per sample.
For the comparison of microbial biodiversity within Baseline and 6 months post-eradication stool samples, alpha diversity analysis was performed after rarefaction to 82,536 sequences/sample (minimum sampling depth). For the comparison of microbial diversity within Baseline and 12 months post-eradication stool samples, alpha diversity analysis was performed after rarefaction to 84,177 sequences/sample. Whereas, for comparison of microbial diversity within Baseline and 18 months post-eradication stool samples, alpha diversity analysis was performed after rarefaction to 84,333 sequences/sample. We used several “phylogeny-based” and “non-phylogeny-based” matrices to calculate alpha diversity, including PD whole tree, chao1, observed species for microbial richness and the Shannon index for microbial evenness. When Baseline samples was compared with 6 months post-eradication samples, the rarefaction curves generated for all four matrices showed that the stool microbiome in 6 months-post eradication samples demonstrated greater diversity than Baseline samples (Fig 1). However, non-parametric two-sample t-test performed on the four matrices showed that there was no significant difference of the microbial diversity within baseline and 6 months post-eradication stool samples (p>0.05). Similarly, when Baseline samples was compared with 12 or 18 months post-eradication samples, the rarefaction curves generated for all four matrices showed that the stool microbiome in 12 and 18 months-post eradication samples demonstrated greater diversity than Baseline samples (Figs 2 and 3). However, non-parametric two-sample t-test performed on the four matrices showed that the microbial biodiversity within baseline and 12 months post-eradication as well as within baseline and 18 months post-eradication stool samples also did not differ significantly (p>0.05).
pylori eradication. Rarefraction curve for A. chao1, B. observed species, C. PD whole tree, and D. the Shannon index generated from alpha diversity analysis.
Rarefraction curve for A. chao1, B. observed species, C. PD whole tree, and D. the Shannon index generated from alpha diversity analysis.
Rarefraction curve for A. chao1, B. observed species, C. PD whole tree, and D. the Shannon index generated from alpha diversity analysis.
The PCoA plots generated from both weighted and unweighted UniFrac distance metrics in beta diversity analysis for Baseline vs. 6 months post-eradication, Baseline vs. 12 months post-eradication and Baseline vs. 18 months post-eradication did not show distinct clustering between the time-points (S1 & S2 Figs). Non-parametric statistical test analysis of similarity (ANOSIM) also showed that the differences in bacterial communities between the time-points were not significant (p>0.05).
The taxonomy summary of the phyla and genera of stool microbiome in healthy young Malaysian adults pre- and post-eradication of H. pylori were summarized in Fig 4 and Fig 5. Before the eradication H. pylori, the most abundant phyla were Bacteroidetes (52.09%; 95% CI, 44.85%-60.07%), Firmicutes (32.91%; 95% CI, 26.67%-39.06%), Actinobacteria (6.68%; 95% CI, 4.03%-9.68%), and Proteobacteria (5.77%; 95% CI, 3.94%-8.03%) (Fig 1A). At 6 months post-H. pylori eradication, the relative abundance of Bacteroidetes decreased to 47.82% (95% CI, 42.24%-52.94%) and Firmicutes increased to 37.82% (95% CI, 32.19%-43.71%), as compared to Baseline. In addition, the relative abundance of both phyla Actinobacteria (4.86%; 95% CI, 2.65%-7.27%), and Proteobacteria (3.69%; 95% CI, 2.58%-4.92%) also reduced 6 months post-eradication. Interestingly, we also observed that the relative abundance of Verrucomicrobia increased markedly, from 0.07% (95% CI, 0.01%-0.17%) at Baseline to 3.30% (95% CI, 0.08%-9.53%) 6 months post-eradication (Fig 1B). At 12 months post-H. pylori eradication, Firmicutes (43.53%; 95% CI, 31.66%-54.29%) replaced Bacteroidetes (36.84%; 95% CI, 26.45%-49.26%), as the most abundant phylum in the stool microbiome. Similar patterns were observed in Actinobacteria (8.14%; 95% CI, 3.34%-14.48%), Proteobacteria (6.75%; 95% CI, 2.93%-12.39%), and Fusobacteria (0.36%; 95% CI, 0%-1.07%) in which their relative abundances higher than Baseline. The relative abundance of Verrucromicrobia (0.97%; 95% CI, 0.2%-2.1%), on the other hand, seems to be restoring to the Baseline level though its abundance was still higher than that of Baseline (Fig 1C). At 18 months-post H. pylori eradication, both Bacteroidetes and Firmicutes had the highest relative abundance which was approximately 38% for both phyla. Enrichment of the relative abundance of Proteobacteria (8.40%; 95% CI, 3.77%-13.03%) and Actinobacteria (7.96%; 95% CI, 3.11%-14.57%) were observed where their relative abundance increased to higher than Baseline, 6 months, and also 12 months post-eradication. The relative abundance of Verrucomicrobia (1.29%; 95% CI, 0%-3%) at 18 months-post eradication was still higher than Baseline whereas the relative abundance of Fusobacteria (0.11%; 95% CI, 0%-0.32%) had been restored to Baseline level (Fig 1D) (Table 2). The Bacteroidetes-to-Firmicutes ratio at Baseline, 6 months, 12 months, and 18 months were 8:5, 13:10, 5:6, and 1:1, respectively. Despite the observed trend in Bacteroidetes-to-Firmicutes ratio, these changes across time were not statistically significant (Paired-samples t-test, p≥0.05). The Bacteroidetes-to-Firmicutes ratio were also not significantly correlated with BMI of the volunteers across different time-points (Person’s correlation, p≥0.05).
Relative abundance of phyla at A. Baseline, B. 6 months-post eradication, C. 12 months-post eradication, and D. 18 months-post eradication.
Comparison of the relative abundance of genera between A. Baseline vs. 6 months-post eradication, B. Baseline vs. 12 months-post eradication, and C. Baseline vs. 18 months-post eradication.
When the genera of stool microbiome between Baseline and 6 months post-H. pylori eradication group were compared, the relative abundance of Anaerofustis, Phascolarctobacterium, and Ruminococcus (Family: Lachnospiraceae) in the stool microbiome were found to have increased significantly whereas the relative abundance of an unnamed genus under Candidate Division TM7 phylum (Order & Family: unnamed)decreased significantly (Paired-samples t-test, p<0.05) (Table 3). The relative abundance of three genera in the stool microbiome changed significantly (p<0.05) when baseline was compared with 12 months post-eradication groups. The relative abundance of Dialister (p = 0.033) and Helicobacter (p = 0.041) increased while the relative abundance of Agrobacterium (p = 0.031) decreased 12 months post-H. pylori eradication (Table 4). Agrobacterium was detected in Baseline and 6 months post-eradication samples but disappeared in 12 and 18 months post-eradication samples. When the genera of stool microbiome between Baseline and 18 months post-H. pylori eradication group were compared, genus Helicobacter (p = 0.033) and another unnamed genus under Candidate Division TM7 phylum (Family: Rs-045) was found to have increased significantly (Table 5).
To examine for the presence of enterohepatic Helicobacter species (EHS), we used the generated OTU table to further summarize microbiome communities up to species level. The generated 16S rRNA data showed that the only Helicobacter species detected was H. pylori (Table 4, Table 5 and S1 File)
To our knowledge, the effect of H. pylori eradication on the gut microbiome has yet to be investigated in H. pylori-positive healthy young Malaysian adult. H. pylori-positive volunteers were given eradication therapy and the same cohort of volunteers was subsequently followed up for 6, 12, and 18 months post-eradication. We performed diversity analysis to study the effect of H. pylori eradication on the gut microbial communities. The lack of significance within each time-point group as well as between the different time-point groups demonstrated that the microbial diversity of the gut microbiome of the volunteers was equally rich and proportional. In addition, following the eradication of H. pylori, the bacterial communities were not affected. The bacterial communities were similar pre- and post-H. pylori eradication. Therefore, these results suggested that eradication of H. pylori may not remarkably interrupt the composition and structure of the gut microbiome.
Irrespective of the H. pylori eradication status, the general profile of the gut microbiome of the volunteers in our ESSAY study was in accordance with previous findings. As reported elsewhere, most bacterial species in the human and mouse gut was dominated by phyla Bacteroidetes and Firmicutes . Less abundant bacteria phyla such as Actinobacteria, Proteobacteria, Verrucromicrobia, and as well as Euryarcheaota (mainly methanogenic archae Methaobrevibacter smithii) were also present [44, 45]. It has been reported that the general profile of the bacteria community of an individual at different body habitats seems to be reasonably stable over time .
Despite that the general profile of the gut microbiome was similar pre- and post-H. pylori eradication, our metagenomics study revealed some changes in the bacterial communities at the phylum and genus levels that are notable. Twelve months post-H. pylori eradication, the relative abundance of Bacteroidetes in the stool microbiome of the volunteers decreased 15% with relative increase in Firmicutes, as compared to stool microbiome at Baseline. There are growing evidences that indicated the inverse relationship between H. pylori prevalence and rate of overweight/obesity. Hence, the gradual decrease of the H. pylori colonization that has been observed in recent decades could be causally related to the human epidemic obesity . Studies in human and mice have shown that obesity is associated with changes in the composition of the gut microbiome. An early study reported that genetically obese ob/ob mice had a 50% reduction in the abundance of Bacteroidetes and proportional increase in Firmicutes . Study in human also demonstrated enrichment in Firmicutes and a corresponding reduction in Bacteroidetes levels in the microbiota of obese individuals; after weight loss, the Bacteroidetes-to-Firmicutes ratio normalized to the level observed in lean individuals .Bacteroidetes and Firmicutes have been associated with the regulation of lipid and bile acid metabolism as well as energy homeostasis in host [49, 50]. Essentially, it has been demonstrated that perturbations of bile acid-mediated signaling pathway influence risk of metabolic complications such as obesity and diabetes . Eighteen months post-eradication, however, the relative abundance of Bacteroidetes and Firmicutes seems to be restoring to the Baseline levels with the enrichment of Proteobacteria.
In a recent study that investigated the short- and long-term effects of clarithromycin and metronidazole treatment, a dramatic decline in Actinobacteria in both throat and feces was reported immediately after H. pylori eradication therapy. Although the diversity of the microbiome subsequently recovered to resemble the pre-treatment states, the microbiota remained perturbed in some cases for up to four years post-treatment . Correspondingly, in our study, the relative abundance of phylum Actinobacteria decreased 6 months-post eradication, and at 12 and 18 months post-eradication, it had increased to resemble to or higher than the Baseline level. This result indicated that broad-spectrum antibiotics used in H. pylori eradication treatment are also capable of inhibiting a range of Gram-positive and Gram-negative bacteria as well as other bacteria besides eradicating H. pylori [53, 54]. It was reported that high-level colonization of the human gut by Verrucomicrobia following broad-spectrum antibiotic treatment . Thus, the increase of phylum Verrucomicrobia 6 months post-eradication could be also attributed to the broad-spectrum antibiotic treatment used in H. pylori eradication therapy. However, at 12 and 18 months post-eradication, it seems to be restoring to the Baseline level.
Another interesting finding was observed for phylum Proteobacteria. The relative abundance of Proteobacteria decreased 6 months post-H. pylori eradication but then it increased to even higher than the Baseline state at 12 and 18 months post-eradication. This finding may correlate with our observation at the genus level of the gut microbiome where Helicobacter was found 12 and 18 months post-eradication but not during Baseline and 6 months post-eradication. It has been reported that besides H. pylori, EHS can also colonize the mucosal surfaces of the intestinal tract and/or the liver of humans, mammals and birds . Our study showed that the Helicobacter species detected in the stool samples at 12 and 18 months post-eradication was not EHS but H. pylori. The sole identification of H. pylori is not due to the lack of taxonomic representation for Helicobacter species in Greengenes database . A study published recently showed that 16S rRNA gene can be used to differentiate between gastric Helicobacter and EHS although it is not sufficient to distinguish between different EHS .
Before the H. pylori-positive volunteers were given the eradication regimen, H. pylori was still attached to the gastric mucosa of the stomach and therefore, it may be the reason why it was not detected in their stool samples. Although H. pylori is generally viewed as a non-invasive pathogen, some in vivo and in vitro studies have demonstrated otherwise. H. pylori was found to reside in the vacuole in the cytoplasm, replicate on the cell membrane to form a microcolony, multiply in macrophages and bone marrow-derived dendritic cells, replicate in epithelial cells, and repopulate the extracellular space after the extracellular bacterial population has been killed by gentamicin for up to 3 days [58–63]. Chu et al. also reported that some coccoid forms of H. pylori were present on the plasma membrane of epithelial cells 18 hours post-H. pylori infection . All of these studies showed that H. pylori may be a facultative intracellular organism [64, 65]. When the H. pylori-positive volunteers were given H. pylori eradication therapy, most of the H. pylori colonized on the gastric mucosa may be killed, but some of them may have invaded the gastric epithelial cells and/or antigen-presenting cells and turned into non-culturable but viable, metabolizing coccoid forms under the stress of antibiotics. The dormant coccoid form is resistant to antibiotic and can spread to infect other cells in the absence of an effective concentration of antibiotic . In addition, Tan et al. recently published a report suggesting that even at low to moderate multiplicity of infection (MOI 10), H. pylori may impede the proliferation of macrophages by disrupting the cell cycle-associated genes and such disruption may be an immunoevasive strategy utilized by H. pylori . It is likely that H. pylori utilizes the advantage of ecological niche to replicate intracellularly and survive the antibacterial therapy. This may explain the transient disappearance of H. pylori immediately following H. pylori eradication therapy but reappeared at 12–18 months later.
To further strengthen our findings, we performed proteomics analysis on these stool samples using LC-MS approach. Consistent with the detection of H. pylori 16S rRNA in these stool samples, H. pylori proteins were also detected (S1 Table) confirming the presence of the bacterium and their viability. In addition, we also managed to call back the volunteers (whom stool samples were detected with Helicobacter 16S rRNA) for UBT at 18 months post-H.pylori eradication. However, all of them were found to be negative for H. pylori by UBT (data not shown). Negative UBT results at 18 months post-H. pylori eradication ruled out the possibility of recrudescence or reinfection of H. pylori in the volunteers. A previous report showed that coccoid forms of H. pylori may give false negative result for UBT  as they produced low level of urease as compared to spiral forms [68, 69]. These may explain the negative UBT results of these volunteers despite detection of H. pylori DNA and proteins in their stool samples. Our finding has also shown that there is a possibility of H. pylori can be shed through feces and supported the notion that H. pylori may be transmitted through fecal-oral route via contaminated water or food .
The genus Anaerofustis was proposed and classified as A. stercorihominis sp. nov. under phylum Firmicutes and class Clostridia to accommodate a phylogenetically distinct Gram-positive, strictly anaerobic, catalase-negative, rod-shaped organism isolated from human feces. It was found to produce acetate and butyrate as end products of glucose fermentation . The significant increment of the relative abundance of Anaerofustis 6 months-post eradication could be attributed to the anti-inflammatory and antimicrobial properties possessed by butyrate-producing bacteria  that may play a role in restoring the delicate balance between human host and the perturbed gut microbiome. Butyrate producing bacteria produce SCFA such as acetate, butyrate, and propionate  through fermentation; the presence of SCFA is believed to be associated with reduced inflammation  and has an important effect on colonic health [74, 75]. At 12- & 18 months-post eradication, the relative abundance of Anaerofustis was returned to Baseline level after human gut microbiome was restored.
Interestingly, the relative abundance of another SCFA-producing bacteria genus, Phascolarctobacterium, also showed significant increment 6 months-post eradication. Phascolarctobacterium is also a genus of Firmicutes bacteria classified within the class of Clostridia. P. succinatutens sp. nov. isolated by Watanabe and co-workers recently from human feces. P. succinatutens sp. nov. is distributed broadly in the gut as subdominant members that may adapt to the intestinal environment by specializing to utilize the succinate generated by other bacterial species to produce propionate , which may also act as a health-promoting microbial metabolite in the human gut  post-H. pylori eradication to aid in the restoration of the perturbed microbiome. On the side note, SCFA was also reported to stimulate the release of hormone PYY and GLP-1 from rodent enteroendocrine L cells via activation of the G-protein-coupled free fatty acid receptor (FFAR) 2 [78–80]. Of the SCFA produced by colonic fermentation of dietary fibre, propionate has the highest affinity for FFAR 2 [81, 82]. Recently, the first-in-human study also demonstrated that direct delivery of propionate to the colon acutely increases the release of PYY and GLP-1 . In a study reported recently by our group has also shown that H. pylori eradication was associated with long term elevation of active amylin, PYY, and GLP-1 in the serum . By this mechanism of SCFA-linked G-protein-coupled receptor activation, the gut microbiota may contribute markedly to increased nutrient uptake and deposition, contributing to the development of metabolic disorders . Hence, there is a possibility that eradication of H. pylori may cause dybiosis which in turn influence the human energy metabolism and lead to the development of obesity.
The genus Ruminococcus belongs to phylum Firmicutes and corresponds to 5–15% of the total bacterial population in the colon [85, 86]. Currently, the genus Ruminococcus is divided into two phylogenetically separate groups which are categorized under two separate families Ruminococcaceae  and Lachnospiraceae  with numerous misclassified Ruminococcus species . Thus, although the relative abundance of this genus was found to have increased significantly 6 months-post eradication, we could not decipher the effect of H. pylori eradication on this bacteria genus. Similarly, genus TM7 is a recently described candidate division of the domain Bacteria, which is currently known only from environmental 16S ribosomal DNA sequence data . Candidate division TM7 is found in a diverse range of environment habitats [90–93] and human body sites [93–97]. These microorganisms have been suggested to play an important role in the early stages of inflammatory mucosal processes, probably by modifying growth conditions for competing bacterial populations [93, 94]. However, we could not elucidate the effect of H. pylori eradication on these organisms in relation to health diseases because they have been uncultivable, with no pure-culture representatives.
In addition to Helicobacter, genera Dialister and Agrobacterium were also found to have changed significantly 12 months post-H. pylori eradication. Although the clinical significance of Dialister spp. and Agrobacterium associated with any disease or infection following H. pylori eradication remains unknown for the time being, it is noteworthy that the significant changes of the relative abundance of these genera 12 months-post eradication.
Our preliminary stool metagenomics study has shown that the eradication of H. pylori caused perturbation of the gut microbiome and may indirectly affect the health of human. Clinicians should be aware of the effect of broad spectrum antibiotics used in H.pylori eradication regime and be more cautious in the clinical management of H. pylori infection, particularly patients from the immunocompromised group. Nonetheless, high throughput experimental approaches such as whole genome shotgun sequencing and metatranscriptomics with bigger sample size is required to verify the observation of this study and also to reveal the complex gene repertoire of the gut microbiome and consequences of H. pylori eradication in modulating human health.
S1 Fig. Unweighted Principal Coordinate Analysis (PCoA) plots.
Unweighted PCoA plots generated in beta diversity analysis for A. Baseline vs. 6 months-post eradication, B. Baseline vs. 12 months-post eradication, and C. Baseline vs. 18 months-post eradication.
S2 Fig. Weighted Principal Coordinate Analysis (PCoA) plots.
Weighted PCoA plots generated in beta diversity analysis for A. Baseline vs. 6 months-post eradication, B. Baseline vs. 12 months-post eradication, and C. Baseline vs. 18 months-post eradication.
S1 File. Relative abundance of species of the gut microbiome at Baseline, 6, 12 and 18 Months-Post H. pylori eradication.
We extend our gratitude to the nurses and clinical staff of the Endoscopy Unit, UMMC and researchers of the Helicobacter Research Laboratory at High Impact Research (HIR) Building, UM.
Conceived and designed the experiments: FF GPP. Performed the experiments: TWCY HMG YPL. Analyzed the data: TWCY. Contributed reagents/materials/analysis tools: JV. Wrote the paper: TWCY HMG FF GPP MFL KLG JV. Carried out the recruitment of volunteers: TWCY AHRL ANA. Carried out the clinical analysis: AHRL KLG. Helped to supervise the laboratory works: MFL JV.
- 1. Savage DC. Microbial ecology of the gastrointestinal tract. Annu Rev Microbiol. 1977;31:107–133. pmid:334036
- 2. Ley RE, Hamady M, Lozupone C, Turnbaugh PJ, Ramey RR, Bircher JS, et al. Evolution of mammals and their gut microbes. Science. 2008;320(5883):1647–1651. pmid:18497261
- 3. Hooper LV, Midtvedt T, Gordon JI. How host-microbial interactions shape the nutrient environment of the mammalian intestine. Annu Rev Nutr. 2002;22:283–307. pmid:12055347
- 4. O'Hara AM, Shanahan F. The gut flora as a forgotten organ. EMBO Rep. 2006;7(7):688–693. pmid:16819463
- 5. Hooper LV, Wong MH, Thelin A, Hansson L, Falk PG, Gordon JI. Molecular analysis of commensal host-microbial relationships in the intestine. Science. 2001;291(5505):881–884. pmid:11157169
- 6. Rawls JF, Mahowald MA, Ley RE, Gordon JI. Reciprocal gut microbiota transplants from zebrafish and mice to germ-free recipients reveal host habitat selection. Cell. 2006;127(2):423–433. pmid:17055441
- 7. Li M, Wang B, Zhang M, Rantalainen M, Wang S, Zhou H, et al. Symbiotic gut microbes modulate human metabolic phenotypes. Proc Natl Acad Sci U S A. 2008;105(6):2117–2122. pmid:18252821
- 8. Cantarel BL, Lombard V, Henrissat B. Complex carbohydrate utilization by the healthy human microbiome. PLoS One. 2012;7(6):e28742. pmid:22719820
- 9. Cani PD, Delzenne NM. The role of the gut microbiota in energy metabolism and metabolic disease. Curr Pharm Des. 2009;15(13):1546–1558. pmid:19442172
- 10. Harris K, Kassis A, Major G, Chou CJ. Is the gut microbiota a new factor contributing to obesity and its metabolic disorders? J Obes. 2012;2012:14.
- 11. Tilg H, Kaser A. Gut microbiome, obesity, and metabolic dysfunction. J Clinc Invest. 2011;121(6):2126–2132.
- 12. Cani PD, Delzenne NM. Gut microflora as a target for energy and metabolic homeostasis. Curr Opin Clin Nutr Metab Care. 2007;10(6):729–734. pmid:18089955
- 13. Sekirov I, Russell SL, Antunes LCM, Finlay BB. Gut microbiota in health and disease. Physiol Rev. 2010;90(3):859–904. pmid:20664075
- 14. Endt K, Stecher B, Chaffron S, Slack E, Tchitchek N, Benecke A, et al. The microbiota mediates pathogen clearance from the gut lumen after non-typhoidal Salmonella diarrhea. PLoS Pathog. 2010;6(9):e1001097. pmid:20844578
- 15. Buffie CG, Pamer EG. Microbiota-mediated colonization resistance against intestinal pathogens. Nat Rev Immunol. 2013;13(11):790–801. pmid:24096337
- 16. Kelly D, Conway S, Aminov R. Commensal gut bacteria: mechanisms of immune modulation. Trends Immunol. 2005;26(6):326–333. pmid:15922949
- 17. DiBaise JK, Frank DN, Mathur R. Impact of the gut microbiota on the development of obesity: current concepts. Am J Gastroenterol Suppl. 2012;1(1):22–27.
- 18. Tremaroli V, Backhed F. Functional interactions between the gut microbiota and host metabolism. Nature. 2012;489(7415):242–249. pmid:22972297
- 19. Sun J, Chang EB. Exploring gut microbes in human health and disease: Pushing the envelope. Genes Dis. 2014;1(2):132–139. pmid:25642449
- 20. Clyne M, Dolan B, Reeves EP. Bacterial factors that mediate colonization of the stomach and virulence of Helicobacter pylori. FEMS Microbiol Lett. 2007;268(2):135–143. pmid:17313591
- 21. Kusters JG, van Vliet AH, Kuipers EJ. Pathogenesis of Helicobacter pylori infection. Clin Microbiol Rev. 2006;19(3):449–490. pmid:16847081
- 22. Linz B, Balloux F, Moodley Y, Manica A, Liu H, Roumagnac P, et al. An African origin for the intimate association between humans and Helicobacter pylori. Nature. 2007;445(7130):915–918. pmid:17287725
- 23. Francois F, Roper J, Joseph N, Pei Z, Chhada A, Shak JR, et al. The effect of H. pylori eradication on meal-associated changes in plasma ghrelin and leptin. BMC Gastroenterol. 2011;11:37. doi: 1471-230X-11-37 [pii] pmid:21489301
- 24. Nwokolo CU, Freshwater DA, O'Hare P, Randeva HS. Plasma ghrelin following cure of Helicobacter pylori. Gut. 2003;52(5):637–640. pmid:12692045
- 25. Osawa H. Ghrelin and Helicobacter pylori infection. World J Gastroenterol. 2008;14(41):6327–6333. pmid:19009647
- 26. Chen Y, Blaser MJ. Helicobacter pylori colonization is inversely associated with childhood asthma. J Infect Dis. 2008;198(4):553–560. pmid:18598192
- 27. Amberbir A, Medhin G, Erku W, Alem A, Simms R, Robinson K, et al. Effects of Helicobacter pylori, geohelminth infection and selected commensal bacteria on the risk of allergic disease and sensitization in 3-year-old Ethiopian children. Clin Exp Allergy. 2011;41(10):1422–1430. pmid:21831135
- 28. Amnon S, Robert MG. Helicobacter pylori is a risk factor for colonic neoplasms. Am J Gastroenterol. 2012;108(2):208–215. pmid:23208272
- 29. Yap TW-C, Leow AH- R, Azmi AN, Francois F, Perez-Perez GI, Blaser MJ, et al. Changes in metabolic hormones in Malaysian young adults following Helicobacter pylori eradication. PLoS One. 2015;10(8):e0135771. pmid:26291794
- 30. Peterson J, Garges S, Giovanni M, McInnes P, Wang L, Schloss JA, et al. The NIH Human Microbiome Project. Genome Res. 2009;19(12):2317–2323. pmid:19819907
- 31. Klindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 2013;41(1):e1. pmid:22933715
- 32. Bartram AK, Lynch MD, Stearns JC, Moreno-Hagelsieb G, Neufeld JD. Generation of multimillion-sequence 16S rRNA gene libraries from complex microbial communities by assembling paired-end illumina reads. Appl Environ Microbiol2011;77(11):3846–3852.
- 33. Available: http://hannonlab.cshl.edu/fastx_toolkit/.
- 34. Zhang J, Kobert K, Flouri T, Stamatakis A. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics. 2014;30(5):614–620. pmid:24142950
- 35. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nature Methods. 2010;7(5):335–336. pmid:20383131
- 36. McDonald D, Price MN, Goodrich J, Nawrocki EP, DeSantis TZ, Probst A, et al. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J. 2012;6(3):610–618. pmid:22134646
- 37. Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 2010;26(19):2460–2461. pmid:20709691
- 38. Caporaso JG, Bittinger K, Bushman FD, DeSantis TZ, Andersen GL, Knight R. PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics. 2010;26(2):266–267. pmid:19914921
- 39. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol. 2006;72(7):5069–5072. pmid:16820507
- 40. Price MN, Dehal PS, Arkin AP. FastTree 2—approximately maximum-likelihood trees for large alignments. PLoS One. 2010;5(3):e9490. pmid:20224823
- 41. Lozupone C, Knight R. UniFrac: a New Phylogenetic method for comparing microbial communities. Appl Environ Microbiol. 2005;71(12):8228–8235. pmid:16332807
- 42. Vazquez-Baeza Y, Pirrung M, Gonzalez A, Knight R. EMPeror: a tool for visualizing high-throughput microbial community data. GigaScience. 2013;2(1):16. pmid:24280061
- 43. Ley RE, Bäckhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut microbial ecology. Proc Natl Acad Sci U S A. 2005;102(31):11070–11075. pmid:16033867
- 44. Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L, Sargent M, et al. Diversity of the human intestinal microbial flora. Science. 2005;308(5728):1635–1638. pmid:15831718
- 45. Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, Manichanh C, et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature. 2010;464(7285):59–65. pmid:20203603
- 46. Costello EK, Lauber CL, Hamady M, Fierer N, Gordon JI, Knight R. Bacterial community variation in human body habitats across space and time. Science. 2009;326(5960):1694–1697. pmid:19892944
- 47. Lender N, Talley NJ, Enck P, Haag S, Zipfel S, Morrison M, et al. Associations between Helicobacter pylori and obesity—an ecological study. Aliment Pharmacol Ther. 2014;40(1):24–31. pmid:24832176
- 48. Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature. 2006;444(7122):1022–1023. pmid:17183309
- 49. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006;444(7122):1027–1131. pmid:17183312
- 50. Van Eldere J, Celis P, De Pauw G, Lesaffre E, Eyssen H. Tauroconjugation of cholic acid stimulates 7 alpha-dehydroxylation by fecal bacteria. Appl Environ Microbiol. 1996;62(2):656–661. pmid:8593067
- 51. Martin FP, Dumas ME, Wang Y, Legido-Quigley C, Yap IK, Tang H, et al. A top-down systems biology view of microbiome-mammalian metabolic interactions in a mouse model. Mol Syst Biol. 2007;3:112. pmid:17515922
- 52. Jakobsson HE, Jernberg C, Andersson AF, Sjolund-Karlsson M, Jansson JK, Engstrand L. Short-term antibiotic treatment has differing long-term impacts on the human throat and gut microbiome. PLoS One. 2010;5(3):e9836. pmid:20352091
- 53. Peters DH, Clissold SP. Clarithromycin. A review of its antimicrobial activity, pharmacokinetic properties and therapeutic potential. Drugs. 1992;44(1):117–164. pmid:1379907
- 54. Elliott TSJ, Stone JW. Review article: metronidazole and the anaerobic gut flora. Aliment Pharmacol Ther. 1990;4(3):227–238. pmid:2104087
- 55. Dubourg G, Lagier JC, Armougom F, Robert C, Audoly G, Papazian L, et al. High-level colonisation of the human gut by Verrucomicrobia following broad-spectrum antibiotic treatment. Int J Antimicrob Agents. 2013;41(2):149–155. pmid:23294932
- 56. Schauer DB. Enterohepatic Helicobacter Species. In: Mobley HLT, Mendz GL, Hazell SL, editors. Helicobacter pylori: Physiology and Genetics. Washington DC: ASM Press; 2001.
- 57. Ménard A, Buissonnière A, Prouzet-Mauléon V, Sifré E, Mégraud F. The GyrA encoded gene: a pertinent marker for the phylogenetic revision of Helicobacter genus. Syst Appl Microbiol. 2016.
- 58. Kwok T, Backert S, Schwarz H, Berger J, Meyer TF. Specific entry of Helicobacter pylori into cultured gastric epithelial cells via a zipper-like mechanism. Infect Immun. 2002;70(4):2108–2120. pmid:11895977
- 59. Amieva MR, Salama NR, Tompkins LS, Falkow S. Helicobacter pylori enter and survive within multivesicular vacuoles of epithelial cells. Cell Microbiol. 2002;4(10):677–690. pmid:12366404
- 60. Wang YH, Wu JJ, Lei HY. The autophagic induction in Helicobacter pylori-infected macrophage. Exp Biol Med (Maywood). 2009;234(2):171–180.
- 61. Tan S, Tompkins LS, Amieva MR. Helicobacter pylori usurps cell polarity to turn the cell surface into a replicative niche. PLoS Pathog. 2009;5(5):e1000407. pmid:19412339
- 62. Wang YH, Gorvel JP, Chu YT, Wu JJ, Lei HY. Helicobacter pylori impairs murine dendritic cell responses to infection. PLoS One. 2010;5(5):e10844. pmid:20523725
- 63. Chu YT, Wang YH, Wu JJ, Lei HY. Invasion and multiplication of Helicobacter pylori in gastric epithelial cells and implications for antibiotic resistance. Infect Immun. 2010;78(10):4157–4165. pmid:20696835
- 64. Dubois A, Boren T. Helicobacter pylori is invasive and it may be a facultative intracellular organism. Cell Microbiol. 2007;9(5):1108–1116. pmid:17388791
- 65. Petersen AM, Krogfelt KA. Helicobacter pylori: an invading microorganism? A review. FEMS Immunol Med Microbiol. 2003;36(3):117–126. pmid:12738380
- 66. Tan GMY, Looi CY, Fernandez KC, Vadivelu J, Loke MF, Wong WF. Suppression of cell division-associated genes by Helicobacter pylori attenuates proliferation of RAW264.7 monocytic macrophage cells. Sci Rep. 2015;5.
- 67. Weingart V, Rüssmann H, Koletzko S, Weingart J, Höchter W, Sackmann M. Sensitivity of a novel stool antigen test for detection of Helicobacter pylori in adult outpatients before and after eradication therapy. J Clin Microbiol. 2004;42(3):1319–1321. pmid:15004108
- 68. Nilius M, Strohle A, Bode G, Malfertheiner P. Coccoid like forms (CLF) of Helicobacter pylori. Enzyme activity and antigenicity. Zentralbl Bakteriol. 1993;280(1–2):259–272. pmid:8280950
- 69. Hua J, Ho B. Is the coccoid form of Helicobacter pylori viable? Microbios. 1996;87(351):103–12. pmid:9032959
- 70. Malaty HM. Epidemiology of Helicobacter pylori infection. In: Sutton P, Mitchell HM, editors. Helicobacter pylori in the 21st century. Wallingford: CABI; 2010. pp. 1–12.
- 71. Finegold SM, Lawson PA, Vaisanen ML, Molitoris DR, Song Y, Liu C, et al. Anaerofustis stercorihominis gen. nov., sp. nov., from human feces. Anaerobe. 2004;10(1):41–45. pmid:16701499
- 72. Hamer HM, Jonkers D, Venema K, Vanhoutvin S, Troost FJ, Brummer RJ. The role of butyrate on colonic function. Aliment Pharmacol Ther. 2008;27(2):104–119. pmid:17973645
- 73. Karlsson F, Tremaroli V, Nielsen J, Backhed F. Assessing the human gut microbiota in metabolic diseases. Diabetes. 2013;62(10):3341–3349. pmid:24065795
- 74. Szylit O, Andrieux C. Physiological and pathophysiological effects of carbohydrate fermentation. World Rev Nutr Diet. 1993;74:88–122. pmid:8212731
- 75. Cummings JH, Macfarlane GT. Colonic microflora: nutrition and health. Nutrition. 1997;13(5):476–478. pmid:9225346
- 76. Watanabe Y, Nagai F, Morotomi M. Characterization of Phascolarctobacterium succinatutens sp. nov., an asaccharolytic, succinate-utilizing bacterium isolated from human feces. Appl Environ Microbiol. 2012;78(2):511–518. pmid:22081579
- 77. Hosseini E, Grootaert C, Verstraete W, Van de Wiele T. Propionate as a health-promoting microbial metabolite in the human gut. Nutr Rev. 2011;69(5):245–258. pmid:21521227
- 78. Tolhurst G, Heffron H, Lam YS, Parker HE, Habib AM, Diakogiannaki E, et al. Short-chain fatty acids stimulate glucagon-like peptide-1 secretion via the G-Protein–coupled receptor FFAR2. Diabetes. 2012;61(2):364–371. pmid:22190648
- 79. Cherbut C, Ferrier L, Rozé C, Anini Y, Blottière H, Lecannu G, et al. Short-chain fatty acids modify colonic motility through nerves and polypeptide YY release in the rat. Am J Physiol. 1998;275(6 Pt 1):G1415–22. pmid:9843779
- 80. Anini Y, Fu-Cheng X, Cuber JC, Kervran A, Chariot J, Rozé C. Comparison of the postprandial release of peptide YY and proglucagon-derived peptides in the rat. Pflügers Arch. 1999;438(3):299–306. pmid:10398859
- 81. Brown AJ, Goldsworthy SM, Barnes AA, Eilert MM, Tcheang L, Daniels D, et al. The orphan G Protein-coupled receptors GPR41 and GPR43 are activated by propionate and other short chain carboxylic acids. J Biol Chem. 2003;278(13):11312–11319. pmid:12496283
- 82. Le Poul E, Loison C, Struyf S, Springael J-Y, Lannoy V, Decobecq M-E, et al. Functional characterization of human receptors for short chain fatty acids and their role in polymorphonuclear cell activation. J Biol Chem. 2003;278(28):25481–25489. pmid:12711604
- 83. Chambers ES, Viardot A, Psichas A, Morrison DJ, Murphy KG, Zac-Varghese SEK, et al. Effects of targeted delivery of propionate to the human colon on appetite regulation, body weight maintenance and adiposity in overweight adults. Gut. 2014.
- 84. Erejuwa OO, Sulaiman SA, Ab Wahab MS. Modulation of gut microbiota in the management of metabolic disorders: the prospects and challenges. Int J Mol Sci. 2014;15(3):4158–4188. pmid:24608927
- 85. Chassard C, Scott KP, Marquet P, Martin JC, Del'homme C, Dapoigny M, et al. Assessment of metabolic diversity within the intestinal microbiota from healthy humans using combined molecular and cultural approaches. FEMS Microbiol Ecol. 2008;66(3):496–504. pmid:18811647
- 86. Ramirez-Farias C, Slezak K, Fuller Z, Duncan A, Holtrop G, Louis P. Effect of inulin on the human gut microbiota: stimulation of Bifidobacterium adolescentis and Faecalibacterium prausnitzii. British J Nutr. 2009;101(04):541–550.
- 87. Rainey FA. Family VIII. Ruminococcaceae fam. nov. Bergey’s Manual of Systematic Bacteriology. 2009;3:1016–1043.
- 88. Rainey FA. Family V. Lachnospiraceae fam. nov. Bergey's Manual of Systematic Bacteriology. 2009;3:921.
- 89. Liu C, Finegold SM, Song Y, Lawson PA. Reclassification of Clostridium coccoides, Ruminococcus hansenii, Ruminococcus hydrogenotrophicus, Ruminococcus luti, Ruminococcus productus and Ruminococcus schinkii as Blautia coccoides gen. nov., comb. nov., Blautia hansenii comb. nov., Blautia hydrogenotrophica comb. nov., Blautia luti comb. nov., Blautia producta comb. nov., Blautia schinkii comb. nov. and description of Blautia wexlerae sp. nov., isolated from human faeces. Int J Syst Evol Microbiol. 2008;58(8):1896–1902.
- 90. Hugenholtz P, Tyson GW, Webb RI, Wagner AM, Blackall LL. Investigation of candidate division TM7, a recently recognized major lineage of the domain bacteria with no known pure-culture representatives. Appl Environ Microbiol. 2001;67(1):411–419. pmid:11133473
- 91. Ouverney CC, Armitage GC, Relman DA. Single-cell enumeration of an uncultivated TM7 cubgroup in the human subgingival crevice. Appl Environ Microbiol. 2003;69(10):6294–6298. pmid:14532094
- 92. Kumar PS, Griffen AL, Barton JA, Paster BJ, Moeschberger ML, Leys EJ. New bacterial species associated with chronic periodontitis.J Dent Res. 2003;82(5):338–344. pmid:12709498
- 93. Brinig MM, Lepp PW, Ouverney CC, Armitage GC, Relman DA. Prevalence of bacteria of division TM7 in human subgingival plaque and their association with disease. Appl Environ Microbiol. 2003;69(3):1687–1694. pmid:12620860
- 94. Kuehbacher T, Rehman A, Lepage P, Hellmig S, Fölsch UR, Schreiber S, et al. Intestinal TM7 bacterial phylogenies in active inflammatory bowel disease. J Med Microbiol. 2008;57(12):1569–1576.
- 95. Dinis JM, Barton DE, Ghadiri J, Surendar D, Reddy K, Velasquez F, et al. In search of an uncultured human-associated TM7 bacterium in the environment. PLoS One. 2011;6(6):1–8.
- 96. Pei Z, Bini EJ, Yang L, Zhou M, Francois F, Blaser MJ. Bacterial biota in the human distal esophagus. Proc Natl Acad Sci U S A. 2004;101(12):4250–4255. pmid:15016918
- 97. Dewhirst FE, Chen T, Izard J, Paster BJ, Tanner ACR, Yu W-H, et al. The human oral microbiome. J Bacteriol. 2010;192(19):5002–5017. pmid:20656903