scholarly journals Gut microbiota composition related with Clostridium difficile-positive diarrhea and C. difficile type (A+B+, A-B+, and A-B-) in ICU hospitalized patients

2017 ◽  
Author(s):  
Anhua Wu ◽  
Juping Duan ◽  
Sidi Liu ◽  
Xiujuan Meng ◽  
Pengcheng Zhou ◽  
...  
Keyword(s):  
Clostridium Difficile ◽  
Gut Microbiota ◽  
16S Rdna ◽  
Gene Annotation ◽  
Control Group ◽  
Analysis Tool ◽  
Microbiota Composition ◽  
Icu Patients ◽  
Α Diversity ◽  
Gut Microbiota Composition

AbstractBackgroundGut microbiota composition of intensive care unit (ICU) patients suffering from Clostridium difficile-positive diarrhea (CDpD) is still poorly understood. This study aims to use 16S rDNA (and metagenome) sequencing to compare the microbiota composition of 58 (and 5) ICU patients with CDpD (CDpD group), 33 (and 4) ICU patients with C. difficile negative diarrhea (CDnD group), and 21 (and 5) healthy control subjects (control group), as well as CDpD patients in A+B+ (N=34; A/B: C. difficile TcdA/B), A-B+ (N=7), and A-B- (N=17) subgroups. For 16S rDNA data, OTU clustering (tool: UPARSE), taxonomic assignment (tool: RDP classifier), α-diversity and β-diversity analyses (tool: QIIME) were conducted. For metagenome data, metagenome assembly (tool: SOAP), gene calling (tools: MetaGeneMark, CD-HIT, and SoapAligner), unigene alignment (tool: DIAMOND), taxon difference analysis (tool: Metastats), and gene annotation (tool: DIAMOND) were performed.ResultsThe microbial diversity of CDpD group was lower than that of CDnD and control groups. The abundances of 10 taxa (e.g. Deferribacteres, Cryptomycota, Acetothermia) in CDpD group were significantly higher than that in CDnD group. The abundances of Saccharomycetes and Clostridia were significantly lower in CDpD in comparison with control. A+B+, A-B+ and A-B- subgroups couldn’t be separated in principal component analysis, while some taxa are significantly different between A+B+ and A-B- subgroups.ConclusionCDpD might relate to the decrease of beneficial taxa (i.e. Saccharomycetes and Clostridia) and the increase of harmful taxa (e.g. Deferribacteres, Cryptomycota, Acetothermia) in gut microbiota in ICU patients. C. difficile type might be slightly associated with gut microbiota composition.

scholarly journals Anti-predation Defense Traits of Daphnia are Associated With the Gut Microbiota Composition Shaped by Fish Kairomone

2021 ◽  
Author(s):  
Qi Liu ◽  
Siddiq Akbar ◽  
Zihao Ding ◽  
Qiming Zhou ◽  
Lei Gu ◽  
...  
Keyword(s):  
Life History ◽  
Gut Microbiota ◽  
Relative Abundance ◽  
Life History Traits ◽  
Induced Defense ◽  
Control Group ◽  
Microbiota Composition ◽  
Fish Kairomone ◽  
Α Diversity ◽  
Gut Microbiota Composition

Abstract Background: Gut microbiota plays an important role in host physiology and fitness. The gut microbiota can promote host health by influencing life history traits, especially in arthropods. However, it is not clear whether the performance of host defense traits in response to predator pressure in natural food webs is related to their gut microbiota composition. In this study, we used Daphnia magna as a model organism to investigate the relationship of D. magna life history traits and gut microbiota alterations under predator kairomone based on 16S rRNA amplicon sequencing.Result: We showed that the microbiota composition of D. magna was significantly affected by their predator risk and development stage. The relative abundance of Comamonadaceae (mainly Limnohabitans sp.) significantly decreased in the presence of predator kairomone. Furthermore, the presence of predator kairomone significantly reduced the α diversity of gut microbiota in D. magna with the increase of instar. Among them, the OTUs belonged to Epsilonbacteraeota and Firmicutes in the presence of predator kairomone were significantly higher than those in the control group. The results of functional predictions showed that predation pressure promote the metabolic function of gut microbiota, such as metabolism of energy, cofactors, and vitamins. By analyzing the correlation between the induced defense traits of D. magna and the relative abundance of bacteria, we found that the increased abundance of Comamonadaceae, Moraxellaceae, and Flavobacteriaceae were linearly correlated with the partial defense traits of D. magna. Specifically speaking, body size was positively correlated with an increased abundance of Comamonadaceae, whereas spine length was negatively correlated with an increased abundance of Comamonadaceae but was positively correlated with increased Flavobacteriaceae abundance. Conclusions: Our results suggested that predation risk can affect the composition of the gut microbiota in D. magna, which may indirectly induce the production of defensive traits in D. magna. The results of this study revealed an important role of gut microbiota in the development of defensive traits of Daphnia in response to fish predators. The correlation between microbial abundance and defense traits is of great significance for further understanding the effect of host-microbiota interaction on individual anti-predation defense.

scholarly journals Antibiotics at birth and later antibiotic courses: effects on gut microbiota

2021 ◽  
Author(s):  
Sofia Ainonen ◽  
Mysore V Tejesvi ◽  
Md. Rayhan Mahmud ◽  
Niko Paalanne ◽  
Tytti Pokka ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Control Group ◽  
List Type ◽  
Antibiotic Exposure ◽  
Microbiota Composition ◽  
Long Term Effects ◽  
The Impact ◽  
Antibiotic Courses ◽  
Gut Microbiota Composition

Abstract Background Intrapartum antibiotic prophylaxis (IAP) is widely used, but the evidence of the long-term effects on the gut microbiota and subsequent health of children is limited. Here, we compared the impacts of perinatal antibiotic exposure and later courses of antibiotic courses on gut microbiota. Methods This was a prospective, controlled cohort study among 100 vaginally delivered infants with different perinatal antibiotic exposures: control (27), IAP (27), postnatal antibiotics (24), and IAP and postnatal antibiotics (22). At 1 year of age, we performed next-generation sequencing of the bacterial 16S ribosomal RNA gene of fecal samples. Results Exposure to the perinatal antibiotics had a clear impact on the gut microbiota. The abundance of the Bacteroidetes phylum was significantly higher in the control group, whereas the relative abundance of Escherichia coli was significantly lower in the control group. The impact of the perinatal antibiotics on the gut microbiota composition was greater than exposure to later courses of antibiotics (28% of participants). Conclusions Perinatal antibiotic exposure had a marked impact on the gut microbiota at the age of 1 year. The timing of the antibiotic exposure appears to be the critical factor for the changes observed in the gut microbiota. Impact Infants are commonly exposed to IAP and postnatal antibiotics, and later to courses of antibiotics during the first year of life. Perinatal antibiotics have been associated with an altered gut microbiota during the first months of life, whereas the evidence regarding the long-term impact is more limited. Perinatal antibiotic exposure had a marked impact on the infant’s gut microbiota at 1 year of age. Impact of the perinatal antibiotics on the gut microbiota composition was greater than that of the later courses of antibiotics at the age of 1 year.

MO598COMPARISON OF GUT MICROBIOTA COMPOSITION BETWEEN PERITONEAL DIALYSIS PATIENTS AND HEALTHY HOUSEHOLD CONTACTS

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Renata Rodrigues Teixeira ◽  
Laila S. Andrade ◽  
Natalia Barros Ferreira Pereira ◽  
Christian Hoffmann ◽  
Lilian Cuppari
Keyword(s):  
Peritoneal Dialysis ◽  
Gut Microbiota ◽  
Diet Quality ◽  
Quality Index ◽  
Control Group ◽  
Microbiota Composition ◽  
Household Contacts ◽  
Diet Quality Index ◽  
Feces Sample ◽  
Gut Microbiota Composition

Abstract Background and Aims According to some studies, it seems that advanced chronic kidney disease (CKD) has the potential to cause alterations in the composition of patients gut microbiota. Most of these data have been provided by comparing the microbiota profile between patients and healthy individuals. However, well-known factors that influence the microbiota composition such as age, environment and diet were not considered in the majority of these comparative studies. In the present study, we aimed to compare the gut microbiota composition between patients on peritoneal dialysis (PD) and age-paired healthy household contacts. Method This is a cross-sectional study. Patients undergoing automated PD for at least 3 months, aged 18 to 75 years and clinically stable were enrolled. Those who were using prebiotics, probiotics, symbiotics and antibiotics within a period of 30 days before the study, were not included. A healthy control group was composed by individuals living in the same home and with similar age of the patients. Participants received sterile materials to collect the feces sample and were instructed to keep it refrigerated and bring to the clinic within a period of 12h. To evaluate the microbial profile, 16S ribosomal DNA was PCR-amplified and sequenced on an IlluminaMiSeq platform. Diet was evaluated using a 3-day food record and the diet quality was analyzed by a Brazilian Diet Quality Index. Rome IV questionnaire was applied to diagnose constipation. Nutritional status was assessed by 7-point subjective global assessment (SGA) and body mass index (BMI). Fasting blood samples were collected and clinical data were obtained from interviewing the participants and from the patient’s charts. Data are presented in percentage, mean ± standard deviation or median (interquartile range). Results Twenty patients (PD group) and 20 healthy household contacts (control group) were studied. In PD group: 70% were men, 53.5 (48.2 - 66) years old, 50% had diabetes, BMI 25.9 ± 4.8 kg/m², 95% well-nourished, 40% constipated, 14 (5.2 – 43.5) months on dialysis and 80% had residual diuresis. In control group: 30% were men, 51.5 (46.2 - 59.7) years old, BMI 28.7 ± 3.5 kg/m² and 20% constipated. Except of sex (p = 0.01) and BMI (p = 0.04), there were no other differences between groups. Comparing dietary intake between groups, no difference was found in daily energy [PD: 20.8 ± 5.4 kcal/kg/d vs. control: 22.0 ± 5.6 kcal/kg/d, p = 0.51], protein (PD: 0.8 ± 0.2 g/kg/d vs. control: 0.9 ± 0.2 g/kg/d, p = 0.23) and fiber [PD: 14.1 (10.7 – 21.1) g/d vs. 13.7 (10.4 – 18.0) g/d, p = 0.85]. In addition, the Diet Quality Index was also not different between groups (PD: 52.3 ± 15.6 vs. control: 54.5 ± 14.8, p = 0.65). Regarding microbiota composition, no difference was found between groups in alfa diversity (Figure 1), beta diversity (p>0.05), and genera differential abundance (Figure 2). Conclusion In the present study, no difference in the gut microbiota composition was found between patients on PD and healthy household contacts sharing a similar environment and diet. This result suggests that CKD and PD seem not to alter significantly gut microbiota composition.

scholarly journals The microbiota of farmed mink (Neovison vison) follows a successional development and is affected by early life antibiotic exposure

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Martin Iain Bahl ◽  
Anabelle Legarth Honoré ◽  
Sanne Tygesen Skønager ◽  
Oliver Legarth Honoré ◽  
Tove Clausen ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Early Life ◽  
Intramuscular Administration ◽  
Control Group ◽  
Rrna Gene ◽  
Antibiotic Administration ◽  
Lactation Period ◽  
Microbiota Composition ◽  
Gut Microbiota Composition ◽  
Successional Development

AbstractOn many mink farms, antibiotics are used extensively during the lactation period to reduce the prevalence and severity of pre-weaning diarrhoea (PWD) in mink kits (also referred to as greasy kit syndrome). Concerns have been raised, that routine treatment of PWD with antibiotics could affect the natural successional development of the gut microbiota, which may have long lasting consequences. Here we investigated the effects of early life antibiotic treatment administered for 1 week (postnatal days 13–20). Two routes of antibiotic administration were compared to a non-treated control group (CTR, n = 24). Routes of administration included indirect treatment, through the milk from dams receiving antibiotics by intramuscular administration (ABX_D, n = 24) and direct treatment by intramuscular administration to the kits (ABX_K, n = 24). A tendency for slightly increased weight at termination (Day 205) was observed in the ABX_K group. The gut microbiota composition was profiled by 16S rRNA gene sequencing at eight time points between Day 7 and Day 205. A clear successional development of the gut microbiota composition was observed and both treatment regimens caused detectable changes in the gut microbiota until at least eight days after treatment ceased. At termination, a significant positive correlation was identified between microbial diversity and animal weight.

scholarly journals Microbial signature in IgE-mediated food allergies

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Michael R. Goldberg ◽  
Hadar Mor ◽  
Dafna Magid Neriya ◽  
Faiga Magzal ◽  
Efrat Muller ◽  
...  
Keyword(s):  
Food Allergy ◽  
Gut Microbiota ◽  
Learning Algorithm ◽  
Area Under The Curve ◽  
Food Allergies ◽  
Rrna Gene ◽  
Microbiota Composition ◽  
Α Diversity ◽  
Ige Mediated ◽  
Gut Microbiota Composition

Abstract Background Multiple studies suggest a key role for gut microbiota in IgE-mediated food allergy (FA) development, but to date, none has studied it in the persistent state. Methods To characterize the gut microbiota composition and short-chain fatty acid (SCFAs) profiles associated with major food allergy groups, we recruited 233 patients with FA including milk (N = 66), sesame (N = 38), peanut (N = 71), and tree nuts (N = 58), and non-allergic controls (N = 58). DNA was isolated from fecal samples, and 16S rRNA gene sequences were analyzed. SCFAs in stool were analyzed from patients with a single allergy (N = 84) and controls (N = 31). Results The gut microbiota composition of allergic patients was significantly different compared to age-matched controls both in α-diversity and β-diversity. Distinct microbial signatures were noted for FA to different foods. Prevotella copri (P. copri) was the most overrepresented species in non-allergic controls. SCFAs levels were significantly higher in the non-allergic compared to the FA groups, whereas P. copri significantly correlated with all three SCFAs. We used these microbial differences to distinguish between FA patients and non-allergic healthy controls with an area under the curve of 0.90, and for the classification of FA patients according to their FA types using a supervised learning algorithm. Bacteroides and P. copri were identified as taxa potentially contributing to KEGG acetate-related pathways enriched in non-allergic compared to FA. In addition, overall pathway dissimilarities were found among different FAs. Conclusions Our results demonstrate a link between IgE-mediated FA and the composition and metabolic activity of the gut microbiota.

scholarly journals Peanut Intake Enriches Butyrate Producing Bacteria and Expression of a Gene Associated With Butyrate Production in Adults With Elevated Fasting Glucose: An RCT

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 1178-1178
Author(s):  
Philip Sapp ◽  
Regina Lamendella ◽  
Penny Kris-Etherton ◽  
Kristina Petersen
Keyword(s):  
Gut Microbiota ◽  
Fasting Glucose ◽  
Gene Annotation ◽  
Small Subunit ◽  
Functional Gene ◽  
Sequence Variant ◽  
Microbiota Composition ◽  
Fatty Acid Production ◽  
Butyrate Production ◽  
Gut Microbiota Composition

Abstract Objectives To assess the effect of consuming 28 g/d of peanuts for 6-weeks, compared to an isocaloric lower fat, higher carbohydrate (LFHC) snack, on gut microbiota composition in adults with elevated fasting glucose. Further, to identify functional and compositional differences in responders using metatranscriptomics. Methods In a randomized, crossover trial, 50 adults (52% male; 42 ± 15 y; BMI 28.3 ± 5.6 kg/m2; glucose 100 ± 8 mg/dL) consumed 28g/d of dry roasted, unsalted, peanuts (160 kcal) or a LFHC snack for 6-wk with a 4-wk washout period. Fecal samples were collected at the baseline and endpoint of each period. Gut microbiota composition was measured using 16 rRNA sequencing and QIIME2 for amplicon sequence variant assignment. Metatranscriptomic sequencing was conducted on baseline and endpoint samples from subjects with the greatest reduction in glucose following the peanut condition (n = 24), to measure gene expression related to microbial metabolic pathways. The NUGEN library preparation method was used to generate cDNA. MetaPhlan2 and HUMAnN2 were used for taxonomic and functional gene annotation, and iPATH3 and Pathview were used for mapping to functional gene pathways. Results No between-condition difference in α or β microbiota diversity was observed. Following peanut intake, roseburia and ruminococcaceae were significantly enriched (LDA > 2; P < 0.05). Metatranscriptomics showed enrichment of the K03518 (aerobic carbon-monoxide dehydrogenase small subunit) gene following peanut intake (P < 0.05). Conclusions Enrichment of roseburia was observed following consumption of 28 g/d of peanuts in adults with elevated fasting glucose. Metatranscriptomics revealed enrichment of the K03518 gene, which is associated with short chain fatty acid production and degradation of β-mannans. These results suggest peanut intake enriches a known butyrate producer and the increased expression of a gene implicated in butyrate production adds further support for peanut-induced gut microbiome modulation. Funding Sources The Peanut Institute and the National Center for Advancing Translational Sciences, National Institutes of Health (1UL1TR002014-01).

scholarly journals Analyzing Type 2 Diabetes Associations with the Gut Microbiome in Individuals from Two Ethnic Backgrounds Living in the Same Geographic Area

Nutrients ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 3289
Author(s):  
Manon Balvers ◽  
Mélanie Deschasaux ◽  
Bert-Jan van den Born ◽  
Koos Zwinderman ◽  
Max Nieuwdorp ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Gut Microbiota ◽  
South Asian ◽  
Gut Microbiome ◽  
Geographical Area ◽  
Microbiota Composition ◽  
Α Diversity ◽  
Functional Pathways ◽  
Gut Microbiota Composition

It is currently unknown whether associations between gut microbiota composition and type 2 diabetes (T2D) differ according to the ethnic background of individuals. Thus, we studied these associations in participants from two ethnicities characterized by a high T2D prevalence and living in the same geographical area, using the Healthy Life In Urban Settings (HELIUS) study. We included 111 and 128 T2D participants on metformin (Met-T2D), 78 and 49 treatment-naïve T2D (TN-T2D) participants, as well as a 1:1 matched group of healthy controls from, respectively, African Surinamese and South-Asian Surinamese descent. Fecal microbiome profiles were obtained through 16S rRNA gene sequencing. Univariate and machine learning analyses were used to explore the associations between T2D and the composition and function of the gut microbiome in both ethnicities, comparing Met-T2D and TN-T2D participants to their respective healthy control. We found a lower α-diversity for South-Asian Surinamese TN-T2D participants but no significant associations between TN-T2D status and the abundance of bacterial taxa or functional pathways. In African Surinamese participants, we did not find any association between TN-T2D status and the gut microbiome. With respect to Met-T2D participants, we identified several bacterial taxa and functional pathways with a significantly altered abundance in both ethnicities. More alterations were observed in South-Asian Surinamese. Some altered taxa and pathways observed in both ethnicities were previously related to metformin use. This included a strong negative association between the abundance of Romboutsia and Met-T2D status. Other bacterial taxa were consistent with previous observations in T2D, including reduced butyrate producers such as Anaerostipes hadrus. Hence, our results highlighted both shared and unique gut microbial biomarkers of Met-T2D in individuals from different ethnicities but living in the same geographical area. Future research using higher-resolution shotgun sequencing is needed to clarify the role of ethnicity in the association between T2D and gut microbiota composition.

Dysbiosis of Fecal Microbiota in Allergic Rhinitis Patients

2020 ◽  
Vol 34 (5) ◽  
pp. 650-660 ◽  
Author(s):  
Xiang Liu ◽  
Jing Tao ◽  
Jing Li ◽  
Xiaolin Cao ◽  
Yong Li ◽  
...  
Keyword(s):  
Allergic Rhinitis ◽  
Statistical Analysis ◽  
Gut Microbiota ◽  
Study Groups ◽  
Fecal Microbiota ◽  
Rrna Gene ◽  
Microbiota Composition ◽  
Linear Discriminant ◽  
Α Diversity ◽  
Gut Microbiota Composition

Background The gut microbiota plays an important role in shaping the immune system and may be closely connected to the development of allergic diseases. Objective This study aimed to determine the gut microbiota composition in Chinese allergic rhinitis (AR) patients as compared with healthy controls (HCs). Methods We collected stool samples from 93 AR patients and 72 age- and sex-matched HCs. Gut microbiota composition was analyzed using QIIME targeting the 16S rRNA gene. Functional pathways were predicted using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States. Statistical analysis was performed using the R program, linear discriminant analysis effect size (LefSe), analysis of QIIME, and statistical analysis of metagenomic profiles, among other tests. Results Compared with HCs, AR patients had significantly lower gut-microbiota α-diversity ( P < .001). The gut microbiota composition significantly differed between the 2 study groups. At the phylum level, the relative abundance of Bacteroidetes was higher while those of Actinobacteria and Proteobacteria were lower in the AR group than in the HC group ( P < .001, q < 0.001). At the genus level, Escherichia-Shigella, Prevotella, and Parabacteroides ( P < .001, q < 0.001) had significantly higher relative abundances in the AR group than in the HC group. LefSe analysis indicated that Escherichia-Shigella, Lachnoclostridium, Parabacteroides, and Dialister were potential biomarkers for AR. In addition, predictive metagenome functional analysis showed that pyruvate, porphyrin, chlorophyll, purine metabolism, and peptidoglycan biosynthesis significantly differed between the AR and HC groups. Conclusion A comparison of the gut microbiota of AR patients and HCs suggested that dysbiosis of the fecal microbiota is involved in the development of AR. The present results may reveal key differences and identify targets for preventive or therapeutic intervention.

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