Associations of gut microbiome with endogenous estrogen levels in healthy postmenopausal women.

PURPOSE: The gut microbiome is a potentially important contributor to endogenous estrogen levels after menopause. In healthy postmenopausal women, we examined associations of fecal microbiome composition with levels of urinary estrogens, their metabolites, and relevant metabolic pathway ratios implicated in breast cancer risk. METHODS: Eligible postmenopausal women (n = 164) had a body mass index (BMI) ≤ 35 kg/m2 and no history of hormone use (previous 6 months) or cancer/metabolic disorders. Estrogens were quantified in spot urine samples with liquid chromatography-high resolution mass spectrometry (corrected for creatinine). Bacterial DNA was isolated from fecal samples and the V1-V2 hypervariable regions of 16S rRNA were sequenced on the Illumina MiSeq platform. We examined associations of gut microbiome's indices of within-sample (alpha) diversity (i.e., Shannon, Chao1, and Inverse Simpson), phylogenetic diversity, and the ratio of the two main phyla (Firmicutes and Bacteroidetes; F/B ratio) with individual estrogens and metabolic ratios, adjusted for age and BMI. RESULTS: In this sample of 164 healthy postmenopausal women, the mean age was 62.9 years (range 47.0-86.0). We found significant inverse associations of observed species with 4-pathway:total estrogens (p = 0.04) and 4-pathway:2-pathway (p = 0.01). Shannon index was positively associated with 2-catechols: methylated 2-catechols (p = 0.04). Chao1 was inversely associated with E1:total estrogens (p = 0.04), and 4-pathway:2-pathway (p = 0.02) and positively associated with 2-pathway:parent estrogens (p = 0.01). Phylogenetic diversity was inversely associated with 4-pathway:total estrogens (p = 0.02), 4-pathway:parent estrogens (p = 0.03), 4-pathway:2-pathway (p = 0.01), and 4-pathway:16-pathway (p = 0.03) and positively associated with 2-pathway:parent estrogens (p = 0.01). F/B ratio was not associated with any of the estrogen measures. CONCLUSION: Microbial diversity was associated with several estrogen metabolism ratios implicated in breast cancer risk. Further studies are warranted to confirm these findings in a larger and more representative sample of postmenopausal women, particularly with enrichment of minority participants.

Gut microbiome, body weight, and mammographic breast density in healthy postmenopausal women.

PURPOSE: We examined gut microbiome (GM) profiles in relation to mammographic breast density (BD) and body mass index (BMI) in healthy postmenopausal women. METHODS: Eligible women were postmenopausal, had a BMI ≤ 35 kg/m2, and had not recently taken oral/IV antibiotics. All women provided a fecal sample and information on breast cancer risk factors. Mammographic BD was classified with the American College of Radiology's BI-RADS BD classification system. Bacterial DNA was isolated from fecal samples and the V1-V2 hypervariable regions of 16S rRNA were sequenced on the Illumina MiSeq platform. We examined associations of GM with indices of within-sample (alpha) diversity and the ratio of the two main phyla (Firmicutes and Bacteroidetes; F/B ratio) with BD and BMI. RESULTS: Among 69 women with BD data, 39 had low BD (BI-RADS I/II) and 30 had high BD (BI-RADS III/IV). BMI was inversely associated with BD (mean BMI = 23.8 and 28.0 in women with high and low BD, respectively, p = 1.07 × 10-5). Similar levels of GM diversity were found across weight groups according to Shannon (p = 0.83); Inverse Simpson (p = 0.97); and Chao1 (p = 0.31) indices. F/B ratio and microbiota diversity were suggestively greater in women with high vs. low BD (p = 0.35, 0.14, 0.15, and 0.17 for F/B ratio, Shannon, Inverse Simpson and Chao1, respectively). CONCLUSION: Suggestive differences observed in women with high and low BD with respect to GM alpha diversity and prevalence of specific GM taxa need to be confirmed in larger studies.

Microbiota composition in bilateral healthy breast tissue and breast tumors.

PURPOSE: Previous reports suggest that a complex microbiome exists within the female human breast that might contribute to breast cancer etiology. The purpose of this pilot study was to assess the variation in microbiota composition by breast side (left versus right) within individual women and compare the microbiota of normal and breast tumor tissue between women. We aimed to determine whether microbiota composition differs between these groups and whether certain bacterial taxa may be associated with breast tumors. METHODS: Bilateral normal breast tissue samples (n = 36) were collected from ten women who received routine mammoplasty procedures. Archived breast tumor samples (n = 10) were obtained from a biorepository. DNA was extracted, amplified, and sequenced. Microbiota data were analyzed using QIIME and RStudio. RESULTS: The most abundant phyla in both tumor and normal tissues were Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria. There were statistically significant differences in the relative abundance of various bacterial taxa between groups. Alpha diversity (Simpson's index) was significantly higher in normal compared to tumor samples (0.968 vs. 0.957, p = 0.022). Based on unweighted UniFrac measures, breast tumor samples clustered distinctly from normal samples (R2 = 0.130; p = 0.01). Microbiota composition in normal samples clustered within women (R2 = 0.394; p = 0.01) and by breast side (left or right) within a woman (R2 = 0.189; p = 0.03). CONCLUSION: Significant differences in diversity between tumor and normal tissue and in composition between women and between breasts of the same woman were identified. These results warrant further research to investigate the relationship between microbiota and breast cancer.

Dietary raisin intake has limited effect on gut microbiota composition in adult volunteers.

BACKGROUND: Dried fruits, such as raisins, contain phytochemicals and dietary fibers that contribute to maintaining health, potentially at least partially through modification in gut microbiota composition and activities. However, the effects of raisin consumption on gut microbiota have not previously been thoroughly investigated in humans. Therefore, the objective of this study was to determine how adding three servings of sun dried raisin/day to the diet of healthy volunteers affects gut microbiota composition. METHODS: A 14-day exploratory feeding study was conducted with thirteen healthy individuals between the ages of 18 and 59 years. Participants consumed three servings (28.3 g each) of sun dried raisins daily. Fecal samples were collected prior to raisin consumption (baseline) and after the addition of raisins to the diet (on days 7 and 14). To determine the effects of raisin intake, fecal microbiota composition before and after raisin consumption was characterized for each participant by 16S rRNA gene sequencing. RESULTS: Overall microbiota diversity was not significantly affected by adding raisins to the diet. However, upon addition of raisins to the diet specific OTUs matching Faecalibacterium prausnitzii, Bacteroidetes sp. and Ruminococcus sp. increased in prevalence while OTUs closest to Klebsiella sp., Prevotella sp. and Bifidobacterium spp. decreased. CONCLUSION: Our findings suggest that adding raisins to the diet can affect the prevalence of specific bacterial taxa. Potential health benefits of the observed microbiota changes should be determined in future studies in populations for which specific health outcomes can be targeted. TRIAL REGISTRATION: http://www.clinicaltrials.gov ; Identifier: NCT02713165 .

The vaginal microbial communities of healthy expectant Brazilian mothers and its correlation with the newborn's gut colonization.

The female lower genital tract harbors a complex microbial community essential for homeostasis and health. During pregnancy, the female body undergoes unique hormonal changes that contribute to weight gain as well as modulations in immune function that can affect microbiota composition. Several studies have described the vaginal microbiota of pregnant women from the USA, Europe and Mexico. Here we expand our knowledge about the vaginal microbial communities during the third trimester to healthy expectant Brazilian mothers. Vaginal samples were collected from patients delivering at the Hospital de Clínicas de Porto Alegre, Brazil. Microbial DNA was isolated from samples and the V4 region of the 16S rRNA gene was amplified and sequenced using the PGM Ion Torrent. Brazilian pregnant women presented three distinct types of microbial community at the time of labor. Two microbial communities, Cluster 1 and Cluster 3, presented an overall dominance of Lactobacillus while Cluster 2 tended to present higher diversity and richness, with the presence of Pseudomonas, Prevotella and other vaginosis related bacteria. About half of the Brazilian mothers sampled here had dominance of L. iners. The proportion of mothers without dominance of any Lactobacillus was higher in Brazil (22%) compared to UK (2.4%) and USA, where this community type was not detected. The vaginal microbiota showed significant correlation with the composition of the babies' gut microbiota (p-value = 0.002 with a R2 of 15.8%). Mothers presenting different vaginal microbiota shared different microorganisms with their newborns, which would reflect on initial colonizers of the developing newborns' gut.

Interactions of coffee consumption and postmenopausal hormone use in relation to breast cancer risk in UK Biobank.

PURPOSE: We investigated the association of coffee consumption with postmenopausal breast cancer risk, overall and by the status of postmenopausal hormone therapy (PMH). METHODS: This study included 126,182 postmenopausal women (2,636 with breast cancer and 123,546 without) from UK Biobank. Cancer diagnoses were ascertained through the linkage to the UK National Health Service Central Registers. Information on breast cancer risk factors and coffee consumption was collected at baseline and updated during follow-up. We used Cox proportional hazards regression to evaluate associations between coffee consumption and breast cancer, overall and in stratified analyses by woman's PMH status (none, past, current). RESULTS: In the overall analysis, coffee consumption was not associated with breast cancer risk (Hazard Ratio [HR] 1.00, 95% CI 0.91-1.11 for 2-3 cups/day, and HR 0.98, 95% CI 0.87-1.10 for ≥ 4 cups/day, p-trend = 0.69). Women with no PMH history who consumed ≥ 4 cups/day had a 16% reduced risk of breast cancer as compared to women who consumed < 7 cups/week (HR 0.84, 95% CI 0.71-1.00). Among women with past PMH, those consuming ≥ 4 cups/day had a 22% greater risk of breast cancer than women consuming < 7 cups/week (HR 1.22, 95% CI 1.01-1.47). No association was found among current PMH users. We found no significant interaction between PMH and coffee consumption (p = 0.24). CONCLUSIONS: Coffee consumption might be associated with increased breast cancer risk in women who used hormones in the past. Further studies are warranted to confirm these findings and elucidate potential biological mechanisms underlying the observed associations.

ESPRIT-Forest: Parallel clustering of massive amplicon sequence data in subquadratic time.

The rapid development of sequencing technology has led to an explosive accumulation of genomic sequence data. Clustering is often the first step to perform in sequence analysis, and hierarchical clustering is one of the most commonly used approaches for this purpose. However, it is currently computationally expensive to perform hierarchical clustering of extremely large sequence datasets due to its quadratic time and space complexities. In this paper we developed a new algorithm called ESPRIT-Forest for parallel hierarchical clustering of sequences. The algorithm achieves subquadratic time and space complexity and maintains a high clustering accuracy comparable to the standard method. The basic idea is to organize sequences into a pseudo-metric based partitioning tree for sub-linear time searching of nearest neighbors, and then use a new multiple-pair merging criterion to construct clusters in parallel using multiple threads. The new algorithm was tested on the human microbiome project (HMP) dataset, currently one of the largest published microbial 16S rRNA sequence dataset. Our experiment demonstrated that with the power of parallel computing it is now compu- tationally feasible to perform hierarchical clustering analysis of tens of millions of sequences. The software is available at http://www.acsu.buffalo.edu/∼yijunsun/lab/ESPRIT-Forest.html.

Novel encapsulation improves recovery of probiotic strains in fecal samples of human volunteers.

Probiotic supplements can contribute to maintaining health and ameliorating various disease symptoms. Probiotics can be delivered in many forms with crucial differences in their survival during gastrointestinal (GI) passage. Previously, a novel encapsulation, Probiotic Pearls™ Acidophilus, Integrative Therapeutics, LLC, USA (Pearls), was shown to increase survival in vitro after exposure to gastric conditions. Here, we compare fecal recovery in human volunteers consuming Pearls or a conventional hard-shelled gelatin capsule. We performed a randomized double-blinded, two-armed trial, with six healthy subjects in each 12-day study arm. In fecal samples collected at baseline, twice during the intervention period, and after washout, we compared colony counts between the two encapsulation methods. The identity of the colonies was confirmed by colony morphology, strain-specific PCR, and 16S rRNA gene sequencing. We further performed a comprehensive 16S rRNA gene sequencing-based analysis to identify differential effects on overall microbiota composition. We detected an average log increase in bifidobacteria of 0.152 cfu/g with gelatin and 0.651 cfu/g with Pearls capsules (p > 0.05). Total lactobacilli counts increased in both groups with no difference between the groups. However, the supplemented Lactobacillus acidophilus NCFM decreased to baseline levels within 7 days after end of supplementation with gelatin capsules while 3.11 log cfu/g higher counts compared to baseline (p = 0.05) remained for Pearls. Targeted qPCR largely confirmed the trends observed by viable plate counts. Protecting the probiotic strains by Pearls encapsulation results in higher recovery rates of the supplemented lactobacilli and bifidobacteria in fecal samples and increased persistence, suggesting an improved survival and viability that might increase efficacy towards achieving desired health benefits.

Lactobacillus gasseri KS-13, Bifidobacterium bifidum G9-1, and Bifidobacterium longum MM-2 Ingestion Induces a Less Inflammatory Cytokine Profile and a Potentially Beneficial Shift in Gut Microbiota in Older Adults: A Randomized, Double-Blind, Placebo-Controlled, Crossover Study.

OBJECTIVE: This study determined whether older adults who consumed a probiotic mixture would have a greater proportion of circulating CD4+ lymphocytes, altered cytokine production, and a shift in intestinal microbiota toward a healthier microbial community. METHODS: Participants (70 ± 1 years [mean ± SEM]; n = 32) consumed a probiotic (Lactobacillus gasseri KS-13, Bifidobacterium bifidum G9-1, and Bifidobacterium longum MM2) or a placebo twice daily for 3 weeks with a 5-week washout period between intervention periods. Blood and stools were collected before and after each intervention. The percentage of circulating CD4+ lymphocytes and ex vivo mitogen-stimulated cell cytokine production were measured. In stools, specific bacterial targets were quantified via quantitative polymerase chain reaction (qPCR) and community composition was determined via pyrosequencing. RESULTS: During the first period of the crossover the percentage of CD4+ cells decreased with the placebo (48% ± 3% to 31% ± 3%, p < 0.01) but did not change with the probiotic (44% ± 3% to 42% ± 3%) and log-transformed concentrations of interleukin-10 increased with the probiotic (1.7 ± 0.2 to 3.4 ± 0.2, p < 0.0001) but not the placebo (1.7 ± 0.2 to 2.1 ± 0.2). With the probiotic versus the placebo a higher percentage of participants had an increase in fecal bifidobacteria (48% versus 30%, p < 0.05) and lactic acid bacteria (55% versus 43%, p < 0.05) and a decrease in Escherichia coli (52% versus 27%, p < 0.05). Several bacterial groups matching Faeacalibactierium prausnitzii were more prevalent in stool samples with the probiotic versus placebo. CONCLUSIONS: The probiotic maintained CD4+ lymphocytes and produced a less inflammatory cytokine profile possibly due to the changes in the microbial communities, which more closely resembled those reported in healthy younger populations.

Halogenated Phenazines that Potently Eradicate Biofilms, MRSA Persister Cells in Non-Biofilm Cultures, and Mycobacterium tuberculosis.

Conventional antibiotics are ineffective against non-replicating bacteria (for example, bacteria within biofilms). We report a series of halogenated phenazines (HP), inspired by marine antibiotic 1, that targets persistent bacteria. HP 14 demonstrated the most potent biofilm eradication activities to date against MRSA, MRSE, and VRE biofilms (MBEC = 0.2-12.5 µM), as well as the effective killing of MRSA persister cells in non-biofilm cultures. Frontline MRSA treatments, vancomycin and daptomycin, were unable to eradicate MRSA biofilms or non-biofilm persisters alongside 14. HP 13 displayed potent antibacterial activity against slow-growing M. tuberculosis (MIC = 3.13 µM), the leading cause of death by bacterial infection around the world. HP analogues effectively target persistent bacteria through a mechanism that is non-toxic to mammalian cells and could have a significant impact on treatments for chronic bacterial infections.

A large-scale benchmark study of existing algorithms for taxonomy-independent microbial community analysis.

Recent advances in massively parallel sequencing technology have created new opportunities to probe the hidden world of microbes. Taxonomy-independent clustering of the 16S rRNA gene is usually the first step in analyzing microbial communities. Dozens of algorithms have been developed in the last decade, but a comprehensive benchmark study is lacking. Here, we survey algorithms currently used by microbiologists, and compare seven representative methods in a large-scale benchmark study that addresses several issues of concern. A new experimental protocol was developed that allows different algorithms to be compared using the same platform, and several criteria were introduced to facilitate a quantitative evaluation of the clustering performance of each algorithm. We found that existing methods vary widely in their outputs, and that inappropriate use of distance levels for taxonomic assignments likely resulted in substantial overestimates of biodiversity in many studies. The benchmark study identified our recently developed ESPRIT-Tree, a fast implementation of the average linkage-based hierarchical clustering algorithm, as one of the best algorithms available in terms of computational efficiency and clustering accuracy.

The metabolizable energy of dietary resistant maltodextrin is variable and alters fecal microbiota composition in adult men.

Resistant maltodextrin (RM) is a novel soluble, nonviscous dietary fiber. Its metabolizable energy (ME) and net energy (NE) values derived from nutrient balance studies are unknown, as is the effect of RM on fecal microbiota. A randomized, placebo-controlled, double-blind crossover study was conducted (n = 14 men) to determine the ME and NE of RM and its influence on fecal excretion of macronutrients and microbiota. Participants were assigned to a sequence consisting of 3 treatment periods [24 d each: 0 g/d RM + 50 g/d maltodextrin and 2 amounts of dietary RM (25 g/d RM + 25 g of maltodextrin/d and 50 g/d RM + 0 g/d maltodextrin)] and were provided all the foods they were to consume to maintain their body weight. After an adaptation period, excreta were collected during a 7-d period. After the collection period, 24-h energy expenditure was measured. Fluorescence in situ hybridization, quantitative polymerase chain reaction, and 454 titanium technology-based 16S rRNA sequencing were used to analyze fecal microbiota composition. Fecal amounts of energy (544, 662, 737 kJ/d), nitrogen (1.5, 1.8, 2.1 g/d), RM (0.3, 0.6, 1.2 g/d), and total carbohydrate (11.1, 14.2, 16.2 g/d) increased with increasing dose (0, 25, 50 g) of RM (P < 0.0001). Fat excretion did not differ among treatments. The ME value of RM was 8.2 and 10.4 kJ/g, and the NE value of RM was -8.2 and 2.0 kJ/g for the 25 and 50 g/d RM doses, respectively. Both doses of RM increased fecal wet weight (118, 148, 161 g/d; P < 0.0001) and fecal dry weight (26.5, 32.0, 35.8 g/d; P < 0.0001) compared with the maltodextrin placebo. Total counts of fecal bacteria increased by 12% for the 25 g/d RM dose (P = 0.17) and 18% for the 50 g/d RM dose (P = 0.019). RM intake was associated with statistically significant increases (P < 0.001) in various operational taxonomic units matching closest to ruminococcus, eubacterium, lachnospiraceae, bacteroides, holdemania, and faecalibacterium, implicating RM in their growth in the gut. Our findings provide empirical data important for food labeling regulations related to the energy value of RM and suggest that RM increases fecal bulk by enhancing the excretion of nitrogen and carbohydrate and the growth of specific microbial populations.

Effects of almond and pistachio consumption on gut microbiota composition in a randomised cross-over human feeding study.

The modification of microbiota composition to a 'beneficial' one is a promising approach for improving intestinal as well as overall health. Natural fibres and phytochemicals that reach the proximal colon, such as those present in various nuts, provide substrates for the maintenance of healthy and diverse microbiota. The effects of increased consumption of specific nuts, which are rich in fibre as well as various phytonutrients, on human gut microbiota composition have not been investigated to date. The objective of the present study was to determine the effects of almond and pistachio consumption on human gut microbiota composition. We characterised microbiota in faecal samples collected from volunteers in two separate randomised, controlled, cross-over feeding studies (n 18 for the almond feeding study and n 16 for the pistachio feeding study) with 0, 1·5 or 3 servings/d of the respective nuts for 18 d. Gut microbiota composition was analysed using a 16S rRNA-based approach for bacteria and an internal transcribed spacer region sequencing approach for fungi. The 16S rRNA sequence analysis of 528 028 sequence reads, retained after removing low-quality and short-length reads, revealed various operational taxonomic units that appeared to be affected by nut consumption. The effect of pistachio consumption on gut microbiota composition was much stronger than that of almond consumption and included an increase in the number of potentially beneficial butyrate-producing bacteria. Although the numbers of bifidobacteria were not affected by the consumption of either nut, pistachio consumption appeared to decrease the number of lactic acid bacteria (P< 0·05). Increasing the consumption of almonds or pistachios appears to be an effective means of modifying gut microbiota composition.

The intersection of social determinants of health, the microbiome, and health outcomes in immigrants: A scoping review.

In the present scoping review, we explore whether existing evidence supports the premise that social determinants of health (SDoH) affect immigrant health outcomes through their effects on the microbiome. We adapt the National Institute on Minority Health and Health Disparities' research framework to propose a conceptual model that considers the intersection of SDoH, the microbiome, and health outcomes in immigrants. We use this conceptual model as a lens through which to explore recent research about SDoH, biological factors associated with changes to immigrants' microbiomes, and long-term health outcomes. In the 17 articles reviewed, dietary acculturation, physical activity, ethnicity, birthplace, age at migration and length of time in the host country, socioeconomic status, and social/linguistic acculturation were important determinants of postmigration microbiome-related transformations. These factors are associated with progressive shifts in microbiome profile with time in host country, increasing the risks for cardiometabolic, mental, immune, and inflammatory disorders and antibiotic resistance. The evidence thus supports the premise that SDoH influence immigrants' health postmigration, at least in part, through their effects on the microbiome. Omission of important postmigration social-ecological variables (e.g., stress, racism, social/family relationships, and environment), limited research among minoritized subgroups of immigrants, complexity and inter- and intra-individual differences in the microbiome, and limited interdisciplinary and biosocial collaboration restrict our understanding of this area of study. To identify potential microbiome-based interventions and promote immigrants' well-being, more research is necessary to understand the intersections of immigrant health with factors from the biological, behavioral/psychosocial, physical/built environment, and sociocultural environment domains at all social-ecological levels.

M-pick, a modularity-based method for OTU picking of 16S rRNA sequences.

BACKGROUND: Binning 16S rRNA sequences into operational taxonomic units (OTUs) is an initial crucial step in analyzing large sequence datasets generated to determine microbial community compositions in various environments including that of the human gut. Various methods have been developed, but most suffer from either inaccuracies or from being unable to handle millions of sequences generated in current studies. Furthermore, existing binning methods usually require a priori decisions regarding binning parameters such as a distance level for defining an OTU. RESULTS: We present a novel modularity-based approach (M-pick) to address the aforementioned problems. The new method utilizes ideas from community detection in graphs, where sequences are viewed as vertices on a weighted graph, each pair of sequences is connected by an imaginary edge, and the similarity of a pair of sequences represents the weight of the edge. M-pick first generates a graph based on pairwise sequence distances and then applies a modularity-based community detection technique on the graph to generate OTUs to capture the community structures in sequence data. To compare the performance of M-pick with that of existing methods, specifically CROP and ESPRIT-Tree, sequence data from different hypervariable regions of 16S rRNA were used and binning results were compared. CONCLUSIONS: A new modularity-based clustering method for OTU picking of 16S rRNA sequences is developed in this study. The algorithm does not require a predetermined cut-off level, and our simulation studies suggest that it is superior to existing methods that require specified distance levels to define OTUs. The source code is available at http://plaza.ufl.edu/xywang/Mpick.htm.

Intestinal dysbiosis and depletion of butyrogenic bacteria in Clostridium difficile infection and nosocomial diarrhea.

Clostridium difficile infection (CDI) causes nearly half a million cases of diarrhea and colitis in the United States each year. Although the importance of the gut microbiota in C. difficile pathogenesis is well recognized, components of the human gut flora critical for colonization resistance are not known. Culture-independent high-density Roche 454 pyrosequencing was used to survey the distal gut microbiota for 39 individuals with CDI, 36 subjects with C. difficile-negative nosocomial diarrhea (CDN), and 40 healthy control subjects. A total of 526,071 partial 16S rRNA sequence reads of the V1 to V3 regions were aligned with 16S databases, identifying 3,531 bacterial phylotypes from 115 fecal samples. Genomic analysis revealed significant alterations of organism lineages in both the CDI and CDN groups, which were accompanied by marked decreases in microbial diversity and species richness driven primarily by a paucity of phylotypes within the Firmicutes phylum. Normally abundant gut commensal organisms, including the Ruminococcaceae and Lachnospiraceae families and butyrate-producing C2 to C4 anaerobic fermenters, were significantly depleted in the CDI and CDN groups. These data demonstrate associations between the depletion of Ruminococcaceae, Lachnospiraceae, and butyrogenic bacteria in the gut microbiota and nosocomial diarrhea, including C. difficile infection. Mechanistic studies focusing on the functional roles of these organisms in diarrheal diseases and resistance against C. difficile colonization are warranted.

Survey of culture, goldengate assay, universal biosensor assay, and 16S rRNA Gene sequencing as alternative methods of bacterial pathogen detection.

Cultivation-based assays combined with PCR or enzyme-linked immunosorbent assay (ELISA)-based methods for finding virulence factors are standard methods for detecting bacterial pathogens in stools; however, with emerging molecular technologies, new methods have become available. The aim of this study was to compare four distinct detection technologies for the identification of pathogens in stools from children under 5 years of age in The Gambia, Mali, Kenya, and Bangladesh. The children were identified, using currently accepted clinical protocols, as either controls or cases with moderate to severe diarrhea. A total of 3,610 stool samples were tested by established clinical culture techniques: 3,179 DNA samples by the Universal Biosensor assay (Ibis Biosciences, Inc.), 1,466 DNA samples by the GoldenGate assay (Illumina), and 1,006 DNA samples by sequencing of 16S rRNA genes. Each method detected different proportions of samples testing positive for each of seven enteric pathogens, enteroaggregative Escherichia coli (EAEC), enterotoxigenic E. coli (ETEC), enteropathogenic E. coli (EPEC), Shigella spp., Campylobacter jejuni, Salmonella enterica, and Aeromonas spp. The comparisons among detection methods included the frequency of positive stool samples and kappa values for making pairwise comparisons. Overall, the standard culture methods detected Shigella spp., EPEC, ETEC, and EAEC in smaller proportions of the samples than either of the methods based on detection of the virulence genes from DNA in whole stools. The GoldenGate method revealed the greatest agreement with the other methods. The agreement among methods was higher in cases than in controls. The new molecular technologies have a high potential for highly sensitive identification of bacterial diarrheal pathogens.

16S rRNA gene sequencing of stool samples collected from patients with latent tuberculosis infection before, during, and two months after treatment with 3HP or 4R.

OBJECTIVE: We present 16s rRNA gene sequencing (V1-V2 region) and sample data from a pilot observational cohort study to describe the gut microbiota dynamics of subjects with latent tuberculosis infection (LTBI) treated with daily 600 mg rifampicin for four months (4R) or a weekly dose of 900 mg combination of rifapentine and isoniazid for three months (3HP). Our objectives were to (1) document changes to the gut microbiota immediately following exposure to the rifamycins and (2) document recovery to baseline two months after treatment completion. DATA DESCRIPTION: We enrolled six subjects with subjects with LTBI and prospectively followed them for 5-6 months. Each subject provided stool samples before, during, and two months after treatment. Six healthy controls were sampled in parallel with the patients with LTBIs. We report amplicon sequence variants (ASVs) and taxonomic assignments for 60 stool samples. Additionally, we provide access to the raw amplicon sequences, and subject responses to questionnaires about their diet, medication, and lifestyle changes over the study follow-up period. Furthermore, we provide the concentration of the parent and partially active rifamycin metabolite concentrations measured validated LC-MS-MS assays of phosphate buffer washes of the stool samples collected from the LTBI participants. This comprehensive dataset is a valuable resource for future systematic reviews and meta-analyses of the impact of LTBI therapy on the gut microbiota.

Therapies for Parkinson's disease and the gut microbiome: evidence for bidirectional connection.

The gut brain axis (GBA), a bidirectional communication pathway has often been linked to health and disease, and gut microbiota (GM), a key component of this pathway shown to be altered in Parkinson's disease (PD), are suggested to contribute to the pathogenesis of PD. There are few studies that report the impact of oral medication therapy on GM, however, there are even fewer studies that discuss the impact of other treatments such as device assisted therapies (DAT) including deep brain stimulation (DBS), levodopa-carbidopa intestinal gel infusion (LCIG) and photobiomodulation (PBM) and how these might impact GM. Here, we review the literature and summarize findings of the potential contributions of GM to the heterogenous clinical response to pharmaceutical therapies among individuals with PD. We also discuss the potential interactions between the GM and DATs such as DBS and LCIG and present evidence for alterations in GM in response to DATs. Given the complexity and highly individual nature of the GM of patients with PD and the potential influence that other external factors such as diet, lifestyle, medications, stage of the disease and other comorbidities, further investigations into the response of GM to therapies are worthy of future study in prospective, controlled trials as well as medication naïve individuals. Such detailed studies will help us further comprehend the relationship between GM in PD patients, and will help investigate the potential of targeting GM associated changes as a treatment avenue for PD.