Characteristics Of Gut Microbiome Research Articles

Predicting superagers: a machine learning approach utilizing gut microbiome features

ObjectiveCognitive decline is often considered an inevitable aspect of aging; however, recent research has identified a subset of older adults known as “superagers” who maintain cognitive abilities comparable to those of younger individuals. Investigating the neurobiological characteristics associated with superior cognitive function in superagers is essential for understanding “successful aging.” Evidence suggests that the gut microbiome plays a key role in brain function, forming a bidirectional communication network known as the microbiome-gut-brain axis. Alterations in the gut microbiome have been linked to cognitive aging markers such as oxidative stress and inflammation. This study aims to investigate the unique patterns of the gut microbiome in superagers and to develop machine learning-based predictive models to differentiate superagers from typical agers.MethodsWe recruited 161 cognitively unimpaired, community-dwelling volunteers aged 60 years or from dementia prevention centers in Seoul, South Korea. After applying inclusion and exclusion criteria, 115 participants were included in the study. Following the removal of microbiome data outliers, 102 participants, comprising 57 superagers and 45 typical agers, were finally analyzed. Superagers were defined based on memory performance at or above average normative values of middle-aged adults. Gut microbiome data were collected from stool samples, and microbial DNA was extracted and sequenced. Relative abundances of bacterial genera were used as features for model development. We employed the LightGBM algorithm to build predictive models and utilized SHAP analysis for feature importance and interpretability.ResultsThe predictive model achieved an AUC of 0.832 and accuracy of 0.764 in the training dataset, and an AUC of 0.861 and accuracy of 0.762 in the test dataset. Significant microbiome features for distinguishing superagers included Alistipes, PAC001137_g, PAC001138_g, Leuconostoc, and PAC001115_g. SHAP analysis revealed that higher abundances of certain genera, such as PAC001138_g and PAC001115_g, positively influenced the likelihood of being classified as superagers.ConclusionOur findings demonstrate the machine learning-based predictive models using gut-microbiome features can differentiate superagers from typical agers with a reasonable performance.

Gut Microbiome Compositional and Functional Features Associate with Alzheimer's Disease Pathology.

The gut microbiome is a potentially modifiable factor in Alzheimer's disease (AD); however, understanding of its composition and function regarding AD pathology is limited. Shallow-shotgun metagenomic data was used to analyze fecal microbiome from participants enrolled in the Wisconsin Microbiome in Alzheimer's Risk Study, leveraging clinical data and cerebrospinal fluid (CSF) biomarkers. Differential abundance and ordinary least squares regression analyses were performed to find differentially abundant gut microbiome features and their associations with CSF biomarkers of AD and related pathologies. Gut microbiome composition and function differed between people with AD and cognitively unimpaired individuals. The compositional difference was replicated in an independent cohort. Differentially abundant gut microbiome features were associated with CSF biomarkers of AD and related pathologies. These findings enhance our understanding of alterations in gut microbial composition and function in AD, and suggest that gut microbes and their pathways are linked to AD pathology.

Comparative analysis of the gut microbiome of ungulate species from Qinghai-Xizang plateau.

Several studies have investigated the gut bacterial composition of wild ungulates in the Qinghai-Xizang Plateau. However, the relationship between their gut microbiome dendrograms and their phylogenetic tree remains unclear. In this study, we analyzed 45 amplicons (V3-V4 region of the 16S rRNA gene) from five wild ungulates-Pseudois nayaur, Pantholops hodgsonii, Gazella subgutturosa, Bos grunniens, and Equus kiang-from the Qinghai-Xizang Plateau to clarify the relationship between their phylogenies and gut microbiome dendrograms. The unweighted pair group method with arithmetic mean analysis and hierarchical clustering analysis indicated that G. subgutturosa is closely related to P. nayaur; however, these results were inconsistent with their phylogenetic trees. Additionally, the indicator genera in the microbiome of each wild ungulate showed strong associations with the diets and habitats of their host. Thus, diet and space niche differentiation may primarily account for the differences between the gut microbiome characteristics of these wild ungulates and their phylogeny. In summary, our research provides insights into the evolutionary factors influencing the gut microbiome of wild ungulates in the Qinghai-Xizang Plateau.

Intestinal microbiology and urinary tract infection associated risk in long-term aged care residents

BackgroundUrinary tract infections (UTI) are the most frequently diagnosed infection in residents of long-term care and are a major risk factor for urosepsis, hospitalisation, and death. Translocation of gut pathobionts into the urinary tract is the presumed cause of most UTIs. While specific gut microbiota characteristics have been linked to UTI risk in younger adults, their relevance in aged care residents remains uncertain.MethodsThe faecal microbiome was assessed in 54 long-term aged care residents with a history of UTIs and 69 residents without a UTI history. Further comparisons were made to microbiome characteristics in 20 younger adults without UTIs. Microbiome characteristics were examined in relation to prior and subsequent UTIs, as well as antibiotic therapy.ResultsIn long-term aged care residents, prior UTI history and exposure to UTI-exclusive antibiotics do not significantly affect microbiome composition or functional capacity. However, exposure to antibiotics unrelated to UTI treatment is associated with distinct microbiota compositional traits. Adjustment for dementia, incontinence, diabetes, and prior antibiotic use finds no microbiota characteristic linked to UTI development. However, prior UTI is identified as a predictor of future UTIs. Comparison with younger adults identifies greater within-participant dispersion in aged care residents, as well as lower microbiota diversity and altered microbiome functional potential.ConclusionsNo association between the gut microbiome and UTI incidence, as has been reported in younger individuals, is evident in long-term aged care residents. Considerable variability in gut microbiome characteristics, relating to high antibiotic exposure and age-related physiological and immunological factors, could mask such a relationship. However, it cannot be discounted that increased UTI risk in the elderly is independent of microbiome-mediated mechanisms.

Prenatal ozone exposure and variations of the gut microbiome: Evidence from a Chinese mother-infant cohort

BackgroundThe gut microbiome is central to human health, but the potential impact of ozone (O3) exposure on its establishment in early life has not been thoroughly examined. Therefore, this study aimed to investigate the relationship between prenatal O3 exposure and the variations of the human gut microbiome during the first two years of life. DesignA cohort study design was used. Pregnant women in the third trimester were recruited from an obstetric clinic, and long-term follow-ups were conducted after delivery. The gut microbiome was analyzed using the 16 S rRNA V3-V4 gene regions. Functional pathway analyses of gut microbial communities in neonates were performed using Tax4fun. The average concentrations of ambient O3 and other air pollutants from pregnancy to delivery were calculated using the China High Air Pollutants (CHAP) dataset, based on the permanent residential addresses of participants. Multiple linear regression and mixed linear models were utilized to investigate the associations between prenatal O3 exposure and gut microbiome features. ResultsPrenatal O3 exposure did not significantly affect the gut microbial alpha diversity of mothers and neonates. However, it was found to be positively associated with the gut microbial alpha diversity in 24-month-old infants. Prenatal O3 exposure explained 13.1 % of the variation in neonatal gut microbial composition. After controlling for potential covariates, prenatal O3 exposure was associated with neonatal-specific gut microbial taxa and functional pathways. Furthermore, the mixed linear models showed that prenatal O3 exposure was negatively associated with variations of Streptococcus (p-value = 0.001, q-value = 0.005), Enterococcus (p-value = 0.001, q-value = 0.005), Escherichia-Shigella (p-value = 0.010, q-value = 0.025), and Bifidobacterium (p-value = 0.003, q-value = 0.010). ConclusionsThis study is the first to examine the effects of prenatal O3 exposure on gut microbial homeostasis and variations. It demonstrates that prenatal O3 exposure is associated with variations in certain aspects of the gut microbiome. These findings provide novel insights into the dynamics and establishment of the human microbiome during the first two years of life.

Role of blood metabolites in mediating the effect of gut microbiome on the mutated-RAS/BRAF metastatic colorectal cancer-specific survival

BackgroundRecent studies have linked alterations in the gut microbiome and metabolic disruptions to the invasive behavior and metastasis of colorectal cancer (CRC), thus affecting patient prognosis. However, the specific relationship among gut microbiome, metabolite profiles, and mutated-RAS/BRAF metastatic colorectal cancer (M-mCRC) remains unclear. Furthermore, the potential mechanisms and prognostic implications of metabolic changes induced by gut microbiome alterations in patients with M-mCRC still need to be better understood.MethodsWe conducted Mendelian randomization (MR) to evaluate the causal relationship of genetically predicted 196 gut microbiome features and 1400 plasma metabolites/metabolite ratios on M-mCRC-specific survival. Additionally, we identified significant gut microbiome-metabolites/metabolite ratio associations based on M-mCRC. Metabolite information was annotated, and functional annotation and pathway enrichment analyses were performed on shared proteins corresponding to significant metabolite ratios, aiming to reveal potential mechanisms by which gut microbiome influences M-mCRC prognosis via modulation of human metabolism.ResultsWe identified 11 gut microbiome features and 49 known metabolites/metabolite ratios correlated with M-mCRC-specific survival. Furthermore, we identified 17 gut microbiome-metabolite/metabolite ratio associations specific to M-mCRC, involving eight lipid metabolites and three bilirubin degradation products. The shared proteins corresponding to significant metabolite ratios were predominantly localized within the integral component of the membrane and exhibited enzymatic activities such as glucuronosyltransferase and UDP-glucuronosyltransferase, crucial in processes such as glucuronidation, bile secretion, and lipid metabolism. Moreover, these proteins were significantly enriched in pathways related to ascorbate and aldarate metabolism, pentose and glucuronate interconversions, steroid hormone biosynthesis, and bile secretion.ConclusionOur study offers novel insights into the potential mechanisms underlying the impact of the gut microbiome on the prognosis of M-mCRC. These findings serve as a meaningful reference for exploring potential therapeutic targets and strategies in the future.

Metagenomic analysis demonstrates distinct changes in the gut microbiome of Kawasaki diseases children.

Kawasaki disease (KD) has been considered as the most common required pediatric cardiovascular diseases among the world. However, the molecular mechanisms of KD were not fully underlined, leading to a confused situation in disease management and providing precious prognosis prediction. The disorders of gut microbiome had been identified among several cardiovascular diseases and inflammation conditions. Therefore, it is urgent to elucidate the characteristics of gut microbiome in KD and demonstrate its potential role in regulating intravenous immunoglobulin (IVIG) resistance and coronary artery injuries. A total of 96 KD children and 62 controls were enrolled in the study. One hundred forty fecal samples had been harvested from KD patients, including individuals before or after IVIG treatment, with or without early coronary artery lesions and IVIG resistance. Fecal samples had been collected before and after IVIG administration and stored at -80°C. Then, metagenomic analysis had been done using Illumina NovaSeq 6000 platform. After that, the different strains and functional differences among comparisons were identified. First, significant changes had been observed between KD and their controls. We found that the decrease of Akkermansia muciniphila, Faecalibacterium prausnitzii, Bacteroides uniformis, and Bacteroides ovatus and the increase of pathogenic bacteria Finegoldia magna, Abiotrophia defectiva, and Anaerococcus prevotii perhaps closely related to the incidence of KD. Then, metagenomic and responding functional analysis demonstrated that short-chain fatty acid pathways and related strains were associated with different outcomes of therapeutic efficacies. Among them, the reduction of Bacteroides thetaiotaomicron, the enrichment of Enterococcus faecalis and antibiotic resistance genes had been found to be involved in IVIG resistance of KD. Moreover, our data also revealed several potential pathogenetic microbiome of that KD patients with coronary artery lesions. These results strongly proved that distinct changes in the gut microbiome of KD and the dysfunction of gut microbiomes should be responsible for the pathogenesis of KD and significantly impact the prognosis of KD.

Multiple-trait genomic prediction for swine meat quality traits using gut microbiome features as a correlated trait.

Traits such as meat quality and composition are becoming valuable in modern pork production; however, they are difficult to include in genetic evaluations because of the high phenotyping costs. Combining genomic information with multiple-trait indirect selection with cheaper indicator traits is an alternative for continued cost-effective genetic improvement. Additionally, gut microbiome information is becoming more affordable to measure using targeted rRNA sequencing, and its applications in animal breeding are becoming relevant. In this paper, we investigated the usefulness of microbial information as a correlated trait in selecting meat quality in swine. This study incorporated phenotypic data encompassing marbling, colour, tenderness, loin muscle and backfat depth, along with the characterization of gut (rectal) microbiota through 16S rRNA sequencing at three distinct time points of the animal's growth curve. Genetic progress estimation and cross-validation were employed to evaluate the utility of utilizing host genomic and gut microbiota information for selecting expensive-to-record traits in crossbred individuals. Initial steps involved variance components estimation using multiple-trait models on a training dataset, where the top 25 associated operational taxonomic units (OTU) for each meat quality trait and time point were included. The second step compared the predictive ability of multiple-trait models incorporating different numbers of OTU with single-trait models in a validation set. Results demonstrated the advantage of including genomic information for some traits, while in some instances, gut microbial information proved advantageous, namely, for marbling and pH. The study suggests further investigation into the shared genetic architecture between microbial features and traits, considering microbial data's compositional and high-dimensional nature. This research proposes a straightforward method to enhance swine breeding programs for improving costly-to-record traits like meat quality by incorporating gut microbiome information.

The gut-brain axis in individuals with alcohol use disorder: Anexploratory study of associations among clinical symptoms, brain morphometry, and the gut microbiome.

Alcohol use disorder (AUD) is commonly associated with distressing psychological symptoms. Pathologic changes associated with AUD have been described in both the gut microbiome and brain, but the mechanisms underlying gut-brain signaling in individuals with AUD are unknown. This study examined associations among the gut microbiome, brain morphometry, and clinical symptoms in treatment-seeking individuals with AUD. We performed a secondary analysis of data collected during inpatient treatment for AUD in subjects who provided gut microbiome samples and had structural brain magnetic resonance imaging (MRI; n = 16). Shotgun metagenomics sequencing was performed, and the morphometry of brain regions of interest was calculated. Clinical symptom severity was quantified using validated instruments. Gut-brain modules (GBMs) used to infer neuroactive signaling potential from the gut microbiome were generated in addition to microbiome features (e.g., alpha diversity and bacterial taxa abundance). Bivariate correlations were performed between MRI and clinical features, microbiome and clinical features, and MRI and microbiome features. Amygdala volume was significantly associated with alpha diversity and the abundance of several bacteria including taxa classified to Blautia, Ruminococcus, Bacteroides, and Phocaeicola. There were moderate associations between amygdala volume and GBMs, including butyrate synthesis I, glutamate synthesis I, and GABA synthesis I & II, but these relationships were not significant after false discovery rate (FDR) correction. Other bacterial taxa with shared associations to MRI features and clinical symptoms included Escherichia coli and Prevotella copri. We identified gut microbiome features associated with MRI morphometry and AUD-associated symptom severity. Given the small sample size and bivariate associations performed, these results require confirmation in larger samples and controls to provide meaningful clinical inferences. Nevertheless, these results will inform targeted future research on the role of the gut microbiome in gut-brain communication and how signaling may be altered in patients with AUD.

Research progress on the characteristics of gut microbiome in early life and its influence on atopic march

Allergic diseases are affected by both genetic background and environmental factors.In recent years, many studies have shown that allergic diseases are closely related to the gut microbiome.This article will elaborate on the composition of gut microbiome in early life and its relationship with allergies, the mechanism of action, and the influence of gut microbiome colonization on the atopic march, in order to improve the understanding of the relationship between allergy prevention or treatment and gut microbiome in children, and provide new ideas for the early prevention of allergic diseases and the early intervention of allergic processes.

Novel screening approach for cancer cachexia using metagenomic gut microbiome profiling in patients with advanced non-small cell lung cancer.

12090 Background: Cancer cachexia (CC) is a multifactorial syndrome involving immune-metabolic crosstalk across multiple organs and has been associated with a negative clinical impact in patients with non-small cell lung cancer (NSCLC) amenable to immune checkpoint inhibitors (ICIs). In parallel, the gut microbiome (GM) has emerged as a key contributor to ICI response. In this study, we aimed to evaluate the association between CC and GM composition and its metabolic potentials. Methods: We collected fecal samples from 139 patients with advanced NSCLC treated with ICI. In addition to 16S rRNA sequencing for all patients, shotgun metagenomic microbiome profiling was performed for 69 patients to estimate the species-level composition and functional capacity of the GM. Cancer cachexia was diagnosed according to the international consensus based on the body weight changes over the previous six months. Survival time was calculated using the Kaplan-Meier method. GM diversity indices, differential abundance, and functional profiles based on the MetaCyc database were compared between the patients with and without CC. Results: Median progression-free survival (PFS) and overall survival (OS) were significantly shorter in the cachexia group compared to the non-cachexia group [4.5 vs. 11.5 months (p < 0.001) and 10.8 vs. 44.9 months (p < 0.01), respectively]. Both GM profiling techniques revealed a significant difference in beta diversity between both groups (p < 0.01). In addition, metagenomic analyses revealed the distinct characteristics of GM at the species level between the groups. The CC group showed an overrepresentation of the commensal bacteria, such as Escherichia coli, Ruthenibacterium lactatiformans, Hungatella hathewayi,and Eggerthella lenta, whereas the non-CC group showed an enrichment of Parabacteroides distasonis, Eubacterium rectale,and Roseburia inulinivorans. Moreover, functional analysis revealed the significantly different metabolic potentials of GM in the CC group. The CC group showed an enrichment of pathways, such as D-arabinose degradation II, L-lysine degradation, and octan oxidation. Finally, the clustering of patients based on significant metabolic pathways or gene reactions provided a high predictive ability to discriminate between patients with and without CC. Conclusions: The shotgun metagenomic approach allowed for the characterization of the altered gut microbes and their metabolic potentials in patients with CC. Stratification based on the GM profiles may be useful as a novel screening method for CC, which is progressive and may involve more multistage pathology than identified by the conventional approach.

Postoperative Delirium and the Older Adult: Untangling the Confusion.

Postoperative delirium is one of the most prevalent postoperative complications, affecting mostly older adults. Its incidence is expected to rise because of surgical advances, shifting demographics, and increased life expectancy. Although an acute alteration in brain function, postoperative delirium is associated with adverse outcomes, including progressive cognitive decline and dementia, that place significant burdens on patients' lives and healthcare systems. This has prompted efforts to understand the mechanisms of postoperative delirium to provide effective prevention and treatment. There are multiple mechanisms involved in the etiology of postoperative delirium that share similarities with the physiological changes associated with the aging brain. In addition, older patients often have multiple comorbidities including increased cognitive impairment that is also implicated in the genesis of delirium. These tangled connections pinpointed a shift toward creation of a holistic model of the pathophysiology of postoperative delirium. Scientific advancements integrating clinical risk factors, possible postoperative delirium biomarkers, genetic features, digital platforms, and other biotechnical and information technological innovations, will become available in the near future. Advances in artificial intelligence, for example, will aggregate cognitive testing platforms with patient-specific postoperative delirium risk stratification studies, panels of serum and cerebrospinal fluid molecules, electroencephalogram signatures, and gut microbiome features, along with the integration of novel polygenetic variants of sleep and cognition. These advances will allow for the enrollment of high-risk patients into prevention programs and help uncover new pharmacologic targets.

Identifying Gut Microbiome Features that Predict Responsiveness Toward a Prebiotic Capable of Increasing Calcium Absorption: A Pilot Study.

Previously, we demonstrated that prebiotics may provide a complementary strategy for increasing calcium (Ca) absorption in adolescents which may improve long-term bone health. However, not all children responded to prebiotic intervention. We determine if certain baseline characteristics of gut microbiome composition predict prebiotic responsiveness. In this secondary analysis, we compared differences in relative microbiota taxa abundance between responders (greater than or equal to 3% increase in Ca absorption) and non-responders (less than 3% increase). Dual stable isotope methodologies were used to assess fractional Ca absorption at the end of crossover treatments with placebo, 10, and 20g/day of soluble corn fiber (SCF). Microbial DNA was obtained from stool samples collected before and after each intervention. Sequencing of the 16S rRNA gene was used to taxonomically characterize the gut microbiome. Machine learning techniques were used to build a predictive model for identifying responders based on baseline relative taxa abundances. Model output was used to infer which features contributed most to prediction accuracy. We identified 19 microbial features out of the 221 observed that predicted responsiveness with 96.0% average accuracy. The results suggest a simplified prescreening can be performed to determine if a subject's bone health may benefit from a prebiotic. Additionally, the findings provide insight and prompt further investigation into the metabolic and genetic underpinnings affecting calcium absorption during pubertal bone development.

Gut microbiome features and metabolites in non-alcoholic fatty liver disease among community-dwelling middle-aged and older adults

BackgroundThe specific microbiota and associated metabolites linked to non-alcoholic fatty liver disease (NAFLD) are still controversial. Thus, we aimed to understand how the core gut microbiota and metabolites impact NAFLD.MethodsThe data for the discovery cohort were collected from the Guangzhou Nutrition and Health Study (GNHS) follow-up conducted between 2014 and 2018. We collected 272 metadata points from 1546 individuals. The metadata were input into four interpretable machine learning models to identify important gut microbiota associated with NAFLD. These models were subsequently applied to two validation cohorts [the internal validation cohort (n = 377), and the prospective validation cohort (n = 749)] to assess generalizability. We constructed an individual microbiome risk score (MRS) based on the identified gut microbiota and conducted animal faecal microbiome transplantation experiment using faecal samples from individuals with different levels of MRS to determine the relationship between MRS and NAFLD. Additionally, we conducted targeted metabolomic sequencing of faecal samples to analyse potential metabolites.ResultsAmong the four machine learning models used, the lightGBM algorithm achieved the best performance. A total of 12 taxa-related features of the microbiota were selected by the lightGBM algorithm and further used to calculate the MRS. Increased MRS was positively associated with the presence of NAFLD, with odds ratio (OR) of 1.86 (1.72, 2.02) per 1-unit increase in MRS. An elevated abundance of the faecal microbiota (f__veillonellaceae) was associated with increased NAFLD risk, whereas f__rikenellaceae, f__barnesiellaceae, and s__adolescentis were associated with a decreased presence of NAFLD. Higher levels of specific gut microbiota-derived metabolites of bile acids (taurocholic acid) might be positively associated with both a higher MRS and NAFLD risk. FMT in mice further confirmed a causal association between a higher MRS and the development of NAFLD.ConclusionsWe confirmed that an alteration in the composition of the core gut microbiota might be biologically relevant to NAFLD development. Our work demonstrated the role of the microbiota in the development of NAFLD.

Education as Risk Factor of Mild Cognitive Impairment: The Link to the Gut Microbiome

BackgroundWith differences apparent in the gut microbiome in mild cognitive impairment (MCI) and dementia, and risk factors of dementia linked to alterations of the gut microbiome, the question remains if gut microbiome characteristics may mediate associations of education with MCI.ObjectivesWe sought to examine potential mediation of the association of education and MCI by gut microbiome diversity or composition.DesignCross-sectional study.SettingLuxembourg, the Greater Region (surrounding areas in Belgium, France, Germany).ParticipantsControl participants of the Luxembourg Parkinson’s Study.MeasurementsGut microbiome composition, ascertained with 16S rRNA gene amplicon sequencing. Differential abundance, assessed across education groups (0–10, 11–16, 16+ years of education). Alpha diversity (Chao1, Shannon and inverse Simpson indices). Mediation analysis with effect decomposition was conducted with education as exposure, MCI as outcome and gut microbiome metrics as mediators.ResultsAfter exclusion of participants below 50, or with missing data, n=258 participants (n=58 MCI) were included (M [SD] Age=64.6 [8.3] years). Higher education (16+ years) was associated with MCI (Odds ratio natural direct effect=0.35 [95% CI 0.15–0.81]. Streptococcus and Lachnospiraceae-UCG-001 genera were more abundant in higher education.ConclusionsEducation is associated with gut microbiome composition and MCI risk without clear evidence for mediation. However, our results suggest signatures of the gut microbiome that have been identified previously in AD and MCI to be reflected in lower education and suggest education as important covariate in microbiome studies.

Associations Between Gut Microbial Features and Sickness Symptoms in Kidney Transplant Recipients.

The study investigated the relationship of gut microbiome features and sickness symptoms in kidney transplant recipients. Employing a prospective, longitudinal design, we collected data from 19 participants who had undergone living-donor kidney transplant at three timepoints (pre-transplant and 1week and 3months post-transplant). Sickness symptom data and fecal specimens were collected at each timepoint. Participants were grouped either as high or low sickness symptom severity at baseline. Shotgun metagenomics sequencing characterized gut microbial structure and functional gene content. Fecal microbial features, including alpha (evenness and richness within samples) and beta (dissimilarities between samples) diversity and relative abundances, were analyzed using R statistical packages. Cross-sectional and longitudinal analyses examined relationships between gut microbial features and sickness symptoms. Although our exploratory findings revealed no significant differences in alpha and beta diversity between groups, the high-severity group showed lower microbial richness and evenness than the low-severity group. The high-severity group had enriched relative abundance of bacteria from the genera Citrobacter and Enterobacter and reduced relative abundance of bacteria from the genus Akkermansia across timepoints. No functional genes differed significantly between groups or timepoints. Kidney transplant recipients with high symptom burden displayed increased putative proinflammatory bacteria and decreased beneficial bacteria. This study provides an effect size that future large cohort studies can employ to confirm associations between gut microbial features and sickness symptom experiences in the kidney transplant population. The study findings also have implications for future interventional studies aiming to alleviate the sickness symptom burden in this population.

Integrated omics analysis reveals the alteration of gut microbiota and fecal metabolites in Cervus elaphus kansuensis

The gut microbiota is the largest and most complex microecosystem in animals. It is influenced by the host’s dietary habits and living environment, and its composition and diversity play irreplaceable roles in animal nutrient metabolism, immunity, and adaptation to the environment. Although the gut microbiota of red deer has been studied, the composition and function of the gut microbiota in Gansu red deer (Cervus elaphus kansuensis), an endemic subspecies of red deer in China, has not been reported. In this study, the composition and diversity of the gut microbiome and fecal metabolomics of C. elaphus kansuensis were identified and compared for the first time by using 16S rDNA sequencing, metagenomic sequencing, and LC-MS/MS. There were significant differences in gut microbiota structure and diversity between wild and farmed C. elaphus kansuensis. The 16S rDNA sequencing results showed that the genus UCRD-005 was dominant in both captive red deer (CRD) and wild red deer (WRD). Metagenomic sequencing showed similar results to those of 16S rDNA sequencing for gut microbiota in CRD and WRD at the phylum and genus levels. 16S rDNA and metagenomics sequencing data suggested that Bacteroides and Bacillus might serve as marker genera for CRD and WRD, respectively. Fecal metabolomics results showed that 520 metabolites with significant differences were detected between CRD and WRD and most differential metabolites were involved in lipid metabolism. The results suggested that large differences in gut microbiota composition and fecal metabolites between CRD and WRD, indicating that different dietary habits and living environments over time have led to the development of stable gut microbiome characteristics for CRD and WRD to meet their respective survival and reproduction needs.Key points• Environment and food affected the gut microbiota and fecal metabolites in red deer• Genera Bacteroides and Bacillus may play important roles in CRD and WRD, respectively• Flavonoids and ascorbic acid in fecal metabolites may influence health of red deer

Characteristics of gut microbiome in patients with pediatric solid tumor.

Pediatric solid tumors are a common malignant disease in children, and more and more studies have proved that there is an inseparable relationship between adult tumors and intestinal microbiome, but the changes in the intestinal microbiota of pediatric solid tumor (PST) patients have been scarcely examined. This study aims to examine the differences in the intestinal microbiota features between patients diagnosed with PST and healthy controls (HCs). To elucidate the unique characteristics of the gut microbiota in pediatric patients with solid tumors, we recruited 23 PST patients and 20 HCs. A total of 43 stool samples were gathered, and then 16S rRNA sequencing was performed. We noticed a noticeable pattern of elevated diversity in the gut microbiota within the PST groups. The differences in microbial communities among two groups were remarkable, regarding the analysis at the class level, the abundance of Bacilli was markedly increased in PST patients compared to HCs (P < 0.05), regarding the analysis at the genus level, The presence of Enterococcus was significantly higher in PST cases compared to HCs (P < 0.01), while Lachnospiraceae unclassified, Lachnospira, Haemophilus and Colidextribacter in PST cases, the abundance was significantly reduced. (P < 0.05), 6 genera, including Bacilli, Lactobacillales, Enterococcaceae and Morganella, showed a significant enrichment compared to healthy controls, while 10 genera, including Bilophila, Colidextribacter, Pasteurellales, Haemophilus, Lachnospiraceae unclassified, Lachnospira and Fusobacteriales, were significant reduction in the PST groups. Our research conducted the characterization analysis of the gut microbiota in PST patients for the first time. More importantly, there are some notable differences in the gut microbiota between PST patients and healthy controls, which we believe is an interesting finding.

Gut microbiome characteristics of women with hypothyroidism during early pregnancy detected by 16S rRNA amplicon sequencing and shotgun metagenomic.

This study aimed to explore the correlation between microbiota dysbiosis and hypothyroidism in early pregnancy by 16S rRNA amplicon sequencing combined with metagenomic sequencing. Sixty pregnant women (30 with hypothyroidism and 30 normal controls) were recruited for 16S rRNA amplicon sequencing, and 6 patients from each group were randomly selected for metagenomic sequencing to assess the gut microbiome profile. The 16S rRNA results showed that beta-diversity in the hypothyroidism group was decreased. The relative abundances of the Prevotella and Paraprevotella genera increased in the hypothyroidism group, and Blautia predominated in the controls. The metagenomics results revealed that Prevotella_stercorea_CAG_629, Prevotella_hominis, Prevotella_sp_AM34_19LB, etc. were enriched in the hypothyroidism group at the species level. Functional analysis revealed that the pyridoxal 5'-phosphate synthase pdxT subunit module was decreased, and the short-chain fatty acid (SCFA) transporter and phospholipase/carboxylesterase modules were strongly enriched in the hypothyroidism group. Hypothyroidism patients had increased C-reactive protein (CRP), interleukin-2 (IL-2), IL-4, IL-10, and tumor necrosis factor (TNF)-α levels. The pyridoxal 5'-phosphate synthase pdxT subunit, the SCFA transporter, and the phospholipase/carboxylesterase module were associated with different Prevotella species. In early pregnancy, women with hypothyroidism exhibit microbiota dysbiosis, and Prevotella may affect the metabolism of glutamate, SCFA, and phospholipases, which could be involved in the development of hypothyroidism during pregnancy.

Gut microbiome characteristics of horses with history of cribbing behavior: An observational study

Gut microbiome characteristics of horses with history of cribbing behavior: An observational study