Explore the vast range of titles available.

We have investigated the diversity and composition of gut microbiotas isolated from AD (Alzheimer's disease) patients (n = 41) and healthy seniors (n = 43) from Nur-Sultan city (Kazakhstan). The composition of the gut microbiota was characterized by 16S ribosomal RNA sequencing. Our results demonstrated significant differences in bacterial abundance at phylum, class, order, and genus levels in AD patients compared to healthy aged individuals. Relative abundance analysis has revealed increased amount of taxa belonging to Acidobacteriota, Verrucomicrobiota, Planctomycetota and Synergistota phyla in AD patients. Among bacterial genera, microbiotas of AD participants were characterized by a decreased amount of Bifidobacterium, Clostridia bacterium, Castellaniella, Erysipelotrichaceae UCG-003, Roseburia, Tuzzerella, Lactobacillaceae and Monoglobus. Differential abundance analysis determined enriched genera of Christensenellaceae R-7 group, Prevotella, Alloprevotella, Eubacterium coprostanoligenes group, Ruminococcus, Flavobacterium, Ohtaekwangia, Akkermansia, Bacteroides sp. Marseille-P3166 in AD patients, whereas Levilactobacillus, Lactiplantibacillus, Tyzzerella, Eubacterium siraeum group, Monoglobus, Bacteroides, Erysipelotrichaceae UCG-003, Veillonella, Faecalibacterium, Roseburia, Haemophilus were depleted. We have also found correlations between some bacteria taxa and blood serum biochemical parameters. Adiponectin was correlated with Acidimicrobiia , Faecalibacterium , Actinobacteria , Oscillospiraceae , Prevotella and Christensenellaceae R-7 . The Christensenellaceae R-7 group and Acidobacteriota were correlated with total bilirubin, while Firmicutes, Acidobacteriales bacterium, Castellaniella alcaligenes, Lachnospiraceae , Christensenellaceae and Klebsiella pneumoniae were correlated with the level of CRP in the blood of AD patients. In addition, we report the correlations found between disease severity and certain fecal bacteria. This is the first reported study demonstrating gut microbiota alterations in AD in the Central Asian region.

Across human populations, 16S rRNA gene-based surveys of gut microbiomes have revealed that the bacterial family Christensenellaceae and the archaeal family Methanobacteriaceae cooccur and are enriched in individuals with a lean, compared to an obese, body mass index (BMI). Whether these association patterns reflect interactions between metabolic partners, as well as whether these associations play a role in the lean host phenotype with which they associate, remains to be ascertained. Here, we validated previously reported cooccurrence patterns of the two families and their association with a lean BMI with a meta-analysis of 1,821 metagenomes derived from 10 independent studies. Furthermore, we report positive associations at the genus and species levels between Christensenella spp. and Methanobrevibacter smithii, the most abundant methanogen of the human gut. By coculturing three Christensenella spp. with M. smithii, we show that Christensenella spp. efficiently support the metabolism of M. smithii via H2 production far better than Bacteroides thetaiotaomicron does. Christensenella minuta forms flocs colonized by M. smithii even when H2 is in excess. In culture with C. minuta, H2 consumption by M. smithii shifts the metabolic output of C. minuta’s fermentation toward acetate rather than butyrate. Together, these results indicate that the widespread cooccurrence of these microorganisms is underpinned by both physical and metabolic interactions. Their combined metabolic activity may provide insights into their association with a lean host BMI.IMPORTANCE The human gut microbiome is made of trillions of microbial cells, most of which are Bacteria, with a subset of Archaea. The bacterial family Christensenellaceae and the archaeal family Methanobacteriaceae are widespread in human guts. They correlate with each other and with a lean body type. Whether species of these two families interact and how they affect the body type are unanswered questions. Here, we show that species within these families correlate with each other across people. We also demonstrate that particular species of these two families grow together in dense flocs, wherein the bacteria provide hydrogen gas to the archaea, which then make methane. When the archaea are present, the ratio of bacterial products (which are nutrients for humans) is changed. These observations indicate that when these species grow together, their products have the potential to affect the physiology of their human host.

Background There is mounting evidence that individuals with kidney disease and kidney stones have an abnormal gut microbiota composition. No studies to date have summarised the evidence to categorise how the gut microbiota profile of these individuals may differ from controls. Synthesis of this evidence is essential to inform future clinical trials. This systematic review aims to characterise differences of the gut microbial community in adults with kidney disease and kidney stones, as well as to describe the functional capacity of the gut microbiota and reporting of diet as a confounder in these studies. Methods Included studies were those that investigated the gut microbial community in adults with kidney disease or kidney stones and compared this to the profile of controls. Six scientific databases (CINHAL, Medline, PubMed, Scopus, Web of Science and Cochrane Library), as well as selected grey literature sources, were searched. Quality assessment was undertaken independently by three authors. The system of evidence level criteria was employed to quantitatively evaluate the alteration of microbiota by strictly considering the number, methodological quality and consistency of the findings. Additional findings relating to altered functions of the gut microbiota, dietary intakes and dietary methodologies used were qualitatively summarised. Results Twenty-five articles met the eligibility criteria and included data from a total of 892 adults with kidney disease or kidney stones and 1400 controls. Compared to controls, adults with kidney disease had increased abundances of several microbes including Enterobacteriaceae, Streptococcaceae, Streptococcus and decreased abundances of Prevotellaceae, Prevotella, Prevotella 9 and Roseburia among other taxa. Adults with kidney stones also had an altered microbial composition with variations to Bacteroides, Lachnospiraceae NK4A136 group, Ruminiclostridium 5 group , Dorea, Enterobacter, Christensenellaceae and its genus Christensenellaceae R7 group . Differences in the functional potential of the microbial community between controls and adults with kidney disease or kidney stones were also identified. Only three of the 25 articles presented dietary data, and of these studies, only two used a valid dietary assessment method. Conclusions The gut microbiota profile of adults with kidney disease and kidney stones differs from controls. Future study designs should include adequate reporting of important confounders such as dietary intake to assist with interpretation of findings.

Abstract Context Sleep disruption is associated with worse glucose metabolic control and altered gut microbiota in animal models. Objective We aimed to evaluate the possible links among rapid eye movement (REM) sleep duration, continuous glucose levels, and gut microbiota composition. Methods This observational, prospective, real-life, cross-sectional case-control study included 118 (60 with obesity), middle-aged (39.1-54.8 years) healthy volunteers recruited at a tertiary hospital. Glucose variability and REM sleep duration were assessed by 10-day continuous glucose monitoring (CGM) (Dexcom G6) and wrist actigraphy (Fitbit Charge 3), respectively. The coefficient of variation (CV), interquartile range (IQR), and SD of glucose variability was assessed and the percentage of time in range (% TIR), at 126-139 mg/dL (TIR2), and 140-199 mg/dL (TIR3) were calculated. Shotgun metagenomics sequencing was applied to study gut microbiota taxonomy and functionality. Results Increased glycemic variability (SD, CV, and IQR) was observed among subjects with obesity in parallel to increased % TIR2 and % TIR3. REM sleep duration was independently associated with % TIR3 (β = −.339; P < .001) and glucose variability (SD, β = −.350; P < .001). Microbial taxa from the Christensenellaceae family (Firmicutes phylum) were positively associated with REM sleep and negatively with CGM levels, while bacteria from Enterobacteriacea family and bacterial functions involved in iron metabolism showed opposite associations. Conclusion Decreased REM sleep duration was independently associated with a worse glucose profile. The associations of species from Christensenellaceae and Enterobacteriaceae families with REM sleep duration and continuous glucose values suggest an integrated picture of metabolic health.

BackgroundHigh-throughput sequencing has been widely used in characterizing microbial communities and revealing microbial-host interactions. However, the abundance produced by this technique is semi-quantitative, leading researchers to focus on the relative abundance of microbes and ignore the total microbial load. Moreover, changes in relative abundance do not accurately reflect the actual shifts in microbial load, which may hinder further microbiological research.MethodsIn this study, a bacterial absolute abundance quantitative method based on high-throughput 16S rRNA gene V4 sequencing was developed and used to reveal the changes in the gut microbiota of patients with ulcerative colitis (UC) who underwent fecal microbiota transplantation (FMT) (IDDF2023-ABS-0089 Figure 1 (a) Design and workflow of spike-in bacterium DNA). Samples were collected and analyzed before FMT (W0) and at 1 (W1), 4(W4) and 12 (W12) weeks after FMT.ResultsThe spike-in bacterium Bacillus baekryungensis 700Cs for absolute abundance analysis was well distinguishable from the gut bacteria and did not affect the bacterial composition of fecal samples. The overall bacterial communities changed significantly (P<0.01) after FMT (IDDF2023-ABS-0089 Figure 1 (b) The absolute abundance of Donor, FMT (W0) and at 1 (W1), 4(W4) and 12 (W12) weeks after FMT), characterized by enrichment of 14 genera (eg Prevotella_9, Megamonas) and depletion of 29 genera (eg Veillonella, Escherichia-Shigella). Furthermore, gut bacterial communities of patients who achieved clinical remission (Rm) were shifted toward donors at W1, much earlier than these are not achieving clinical remission (NRm). The load of Ruminococcaceae_UCG-002, Ruminococcaceae_UCG-003 and Ruminococcaceae_UCG-005 were significantly (P<0.05) increased in Rm. The abundances of Eubacterium_coprostanoligenes_group, Coprococcus_3 and Holdemanella were significantly (P<0.05) increased for two consecutive timepoints post-FMT in Rm group, and that Christensenellaceae_R-7_group in the W1 was significantly (P<0.05) greater than that of W0 (IDDF2023-ABS-0089 Figure 1 (c) The significantly different taxa between W0 and W4 in patients with UC achieving clinical remission after FMT). Meanwhile, the abundances of un_f_Enterobacteriaceae, Haemophilus and Actinomyces were significantly decreased for 2 or 3 consecutive timepoints post-FMT in the Rm group.Abstract IDDF2023-ABS-0089 Figure 1ConclusionsAdopting this method, we identified significant shifts in gut bacteria of patients with UC after FMT, especially in the clinical remission group, including the increase of Ruminococcaceae_UCG-002, Coprococcus_3, Christensenellaceae_R-7 and decrease of Veillonella and Haemophilus. Their results show that FMT is a feasible therapeutic option in the treatment of UC and identified microbes that may contribute to the therapeutic efficacy.

The community of microbes in the gastrointestinal tract of mammals, known as the gut microbiome (GMB), plays a critical role in host ecology and evolution. GMB variation is modulated by both host physiology and environmental conditions experienced by the host. Here we characterized the GMBs of 11 free-ranging large herbivore species inhabiting Etosha National Park, Namibia. We examined how intrinsic (i.e., sex, gut morphology, feeding guild) and extrinsic (i.e., geographic zone, waterhole site) factors influenced GMB diversity and community structure within and across herbivore species. We extracted DNA from herbivore fecal samples (n = 312) and amplified the 16s rRNA gene region to identify bacterial taxa. We defined core bacterial taxa as those present at ≥1% relative abundance in ≥50% of the samples from each species. Within bovid species, the core phylum Verrucomicrobiota and the core genera RF39 , Alistipes , Christensenellaceae_R-7 group , and NK4A214 were significantly different in abundance across geographic zones. Microbial richness was significantly greater in female than male eland, and we detected sex-specific differences in Christensenellaceae_R-7 group across all herbivores and P-251-O5 within gemsbok. Mean Bulla evenness was higher in ruminants than nonruminants and differed significantly between giraffes and impala. Elephants also showed a significant correlation between unweighted UniFrac distance and geographic distance between sample locations. By identifying baseline core microbial abundance and occurrence data for this herbivore community, wildlife managers can incorporate long-term GMB monitoring to track microbial shifts in host species over time.

Constipation is a widespread problem in paediatric practice, affecting almost 30% of children. One of the key causal factors of constipation may be disturbances in the homeostasis of the gastrointestinal microbiome. The aim of the study was to determine whether the oral and fecal microbiomes differ between children with and without constipation. A total of 91 children over three years of age were included in the study. Of these, 57 were qualified to a group with constipation, and 34 to a group without. The saliva and stool microbiomes were evaluated using 16S rRNA gene amplicon sequencing. Functional constipation was associated with characteristic bacterial taxa in the fecal microbiota. Statistically significant differences were found at the family level: Burkholderiaceae (q = 0.047), Christensenellaceae (q = 0.047), Chlostridiaceae (q = 0.047) were significantly less abundant in the constipation group, while the Tannerellaceae (q = 0.007) were more abundant. At the genus level, the significant differences were observed for rare genera, including Christensenellaceae r-7 (q = 2.88 × 10 −2 ), Fusicatenibacter (q = 2.88 × 10 −2 ), Parabacteroides (q = 1.63 × 10 −2 ), Romboutsia (q = 3.19 × 10 −2 ) and Subdoligranulum (q = 1.17 × 10 −2 ). All of them were less abundant in children with constipation. With the exception of significant taxonomic changes affecting only feces, no differences were found in the alpha and beta diversity of feces and saliva. Children with functional constipation demonstrated significant differences in the abundance of specific bacteria in the stool microbiome compared to healthy children. It is possible that the rare genera identified in our study which were less abundant in the constipated patients ( Christensellaceae r-7, Fusicatenibacter, Parabacteroides, Romboutsia and Subdoligranulum ) may play a role in protection against constipation. No significant differences were observed between the two groups with regard to the saliva microbiome.

Background:Patients with primary dry syndrome have a disturbed gut microbiota with metabolic dysfunction. The impact of gut microbiota on disease progression in patients with pSS is not yet fully understood, despite a growing body of research suggesting that a healthy gut microbiota is essential for patients with pSS.Objectives:The aim of this study was to investigate the combined effects of gut microbial disorders on disease activity and immune function in patients with pSS and to screen possible biomarkers as potential biomarkers for predicting disease progression.Methods:This study recruited 49 patients with pSS between November 2018 and September 2020 All pSS patients met the 2016 American College of Rheumatology (ACR)/European Alliance of Associations for Rheumatology (EULAR) joint revised classification and diagnostic criteria. All included cases were not taking systemic antibiotics and probiotics one month before each sample collection. Patients with severe infections, malignant tumors and other autoimmune diseases were excluded. Baseline clinical data and fresh fecal specimens were collected from all subjects, and the subjects’ gut microbiome was assessed using 16S rRNA gene sequencing. Multiple machine learning screens for potential biomarkers.Results:We grouped pSS patients according to the ESSDAI Score and found that patients with pSS in the active group (n=30) had more severe immune imbalances and gut microbiome dysbiosis than patients with pSS in the inactive group (n=19). Moreover, there was a decrease in butyric acid-producing bacteria along with an increase in pro-inflammatory mediator-producing flora in the active pSS patients. Results of correlation analyses showed that butyric acid-producing bacteria (e.g., Prevotella, [Eubacterium]_ruminantium_group, Christensenellaceae_R-7_group, and Butyricoccaceae;_) were negatively correlated with the ESSDAI Score. In particular, Collinsella was positively correlated with the levels of cytokines (e.g., IL-17, IL-2, TNF-a) in peripheral blood, and [Eubacterium]_ruminantium_group and Christensenellaceae_R-7_group were positively correlated with the absolute number of Th17 cells and NK cells, respectively. Next, we screened three significant genera (AUC up to 0.863) as potential biomarkers for assessing disease activity using the machine learning method of Lasso combined logistic regression, which were Prevotella (AUC=0.709), Subdoligranulum (AUC=0.693), Collinsella (AUC=0.6).Conclusion:Dysregulation of the gut microbiome is present in patients with pSS and is particularly significant in patients with active disease. A dysregulated gut microbiome may be involved in immune dysfunction in pSS patients, which in turn promotes disease progression. Therefore, a healthy gut microbiome is essential for patients with pSS, and attention to gut health may help to slow the progression of pSS disease.Figure 1.Microbial communities with significant differences at the genus level in the active group compared to the inactive group.Figure 2.Correlation analysis and potential biomarkers: (A) Correlation between important differential bacterial genera and conventional laboratory indicators; (B) The correlation between important differential bacterial genera and immunological indicators; (C) And (D)Diagnostic efficacy of biomarkers screened by Lasso and logistic regression.REFERENCES:NIL.Acknowledgements:NIL.Disclosure of Interests:None declared.

Background:Patients with Primary Sjogren’s syndrome (pSS) have a disturbed gut microbiota with metabolic dysfunction. The impact of gut microbiota on disease progression in patients with pSS is not yet fully understood, despite a growing body of research suggesting that a healthy gut microbiota is essential for patients with pSS.Objectives:The aim of this study was to investigate the combined effects of gut microbial disorders on disease activity and immune function in patients with pSS and to screen possible biomarkers as potential biomarkers for predicting disease progression.Methods:This study recruited 49 patients with pSS between November 2018 and September 2020 All pSS patients met the 2016 American College of Rheumatology (ACR)/European Alliance of Associations for Rheumatology (EULAR) joint revised classification and diagnostic criteria. All included cases were not taking systemic antibiotics and probiotics one month before each sample collection. Patients with severe infections, malignant tumors and other autoimmune diseases were excluded. Baseline clinical data and fresh fecal specimens were collected from all subjects, and the subjects’ gut microbiome was assessed using 16S rRNA gene sequencing. Multiple machine learning screens for potential biomarkers.Results:We grouped pSS patients according to the ESSDAI Score and found that patients with pSS in the active group (n=30) had more severe immune imbalances and gut microbiome dysbiosis than patients with pSS in the inactive group (n=19). Moreover, there was a decrease in butyric acid-producing bacteria along with an increase in pro-inflammatory mediator-producing flora in the active pSS patients. Results of correlation analyses showed that butyric acid-producing bacteria (e.g., Prevotella, [Eubacterium]_ruminantium_group, Christensenellaceae_R-7_group, and Butyricoccaceae;_) were negatively correlated with the ESSDAI Score. In particular, Collinsella was positively correlated with the levels of cytokines (e.g., IL-17, IL-2, TNF-a) in peripheral blood, and [Eubacterium]_ruminantium_group and Christensenellaceae_R-7_group were positively correlated with the absolute number of Th17 cells and NK cells, respectively. Next, we screened three significant genera (AUC up to 0.863) as potential biomarkers for assessing disease activity using the machine learning method of Lasso combined logistic regression, which were Prevotella (AUC=0.709), Subdoligranulum (AUC=0.693), Collinsella (AUC=0.6).Conclusion:Dysregulation of the gut microbiome is present in patients with pSS and is particularly significant in patients with active disease. A dysregulated gut microbiome may be involved in immune dysfunction in pSS patients, which in turn promotes disease progression. Therefore, a healthy gut microbiome is essential for patients with pSS, and attention to gut health may help to slow the progression of pSS disease.REFERENCES:NIL.Figure 1.Microbial communities with significant differences at the genus level in the active group compared to the inactive group.Figure 2.Correlation analysis and potential biomarkers: (A) Correlation between important differential bacterial genera and conventional laboratory indicators; (B) The correlation between important differential bacterial genera and immunological indicators; (C) And (D)Diagnostic efficacy of biomarkers screened by Lasso and logistic regression.Acknowledgements:NIL.Disclosure of Interests:None declared.

Background Improving feed efficiency is the most important goal for modern animal production. The regulatory mechanisms of controlling feed efficiency traits are extremely complex and include the functions related to host genetics and gut microbiota. Short-chain fatty acids (SCFAs), as significant metabolites of microbiota, could be used to refine the combined effect of host genetics and gut microbiota. However, the association of SCFAs with the gut microbiota and host genetics for regulating feed efficiency is far from understood. Results In this study, 464 broilers were housed for RFI measuring and examining the host genome sequence. And 300 broilers were examined for cecal microbial data and SCFA concentration. Genome-wide association studies (GWAS) showed that four out of seven SCFAs had significant associations with genome variants. One locus (chr4: 29414391–29417189), located near or inside the genes MAML3 , SETD7 , and MGST2 , was significantly associated with propionate and had a modest effect on feed efficiency traits and the microbiota. The genetic effect of the top SNP explained 8.43% variance of propionate. Individuals with genotype AA had significantly different propionate concentrations (0.074 vs. 0.131 μg/mg), feed efficiency (FCR: 1.658 vs. 1.685), and relative abundance of 14 taxa compared to those with the GG genotype. Christensenellaceae and Christensenellaceae_R-7_group were associated with feed efficiency, propionate concentration, the top SNP genotypes, and lipid metabolism. Individuals with a higher cecal abundance of these taxa showed better feed efficiency and lower concentrations of caecal SCFAs. Conclusion Our study provides strong evidence of the pathway that host genome variants affect the cecal SCFA by influencing caecal microbiota and then regulating feed efficiency. The cecal taxa Christensenellaceae and Christensenellaceae_R-7_group were identified as representative taxa contributing to the combined effect of host genetics and SCFAs on chicken feed efficiency. These findings provided strong evidence of the combined effect of host genetics and gut microbial SCFAs in regulating feed efficiency traits. 6SQoLRD3ZqDatjTJpeYTJE Video Abstract