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Microbiology Spectrum Aug 2023Many studies have suggested that gut microbiota dysbiosis may be one of the pathogenesis factors of diabetes mellitus (DM), while it is not clear whether it is involved...
Many studies have suggested that gut microbiota dysbiosis may be one of the pathogenesis factors of diabetes mellitus (DM), while it is not clear whether it is involved in the development of diabetic kidney diseases (DKD). The objective of this study was to determine bacterial taxa biomarkers during the progression of DKD by investigating bacterial compositional changes in early and late DKD. 16S rRNA gene sequencing was performed on fecal samples, including the diabetes mellitus (DM), DNa (early DKD), and DNb (late DKD) groups. Taxonomic annotation of microbial composition was performed. Samples were sequenced on the Illumina NovaSeq platform. At the genus level, we found counts of , , and were significantly elevated both in the DNa group (0.0001, 0.0007, and 0.0174, respectively) and the DNb group (0.0001, 0.0012, and 0.0003, respectively) compared with those in the DM group. Only the level of was significantly decreased in the DNa group than the DM group and in the DNb group than the DNa group. Counts of , were significantly decreased in the DNa group compared with those in the DM group (0.001 and 0.006, respectively) and in the DNb group compared with those in the DM group (0.0001 and 0.003, respectively). Levels of , and were positively correlated with an estimated glomerular filtration rate (eGFR), but negatively correlated with microalbuminuria (MAU), 24 h urinary protein quantity (24hUP), and serum creatinine (Scr). Moreover, the areas under the curve (AUCs) of and were 83.33% and 80.77%, respectively, for the DM and DNa cohorts, respectively. Notably, the largest AUC for DNa and DNb cohorts was also that of at 83.60%. Gut microbiota dysbiosis was found in the early and late stages of DKD, especially in the early stage. may be the most promising intestinal bacteria biomarker that can help distinguish different stages of DKD. It is not clear as to whether gut microbiota dysbiosis is involved in the progression of DKD. This study may be the first to explore gut microbiota compositional changes in diabetes, early-DKD, and late DKD. We identify different gut microbial characteristics during different stages of DKD. Gut microbiota dysbiosis is found in the early and late stages of DKD. may be the most promising intestinal bacteria biomarker that can help distinguish different stages of DKD, although further studies are warranted to illustrate these mechanisms.
Topics: Diabetic Nephropathies; Humans; Male; Female; Middle Aged; Gastrointestinal Microbiome; Clostridiales; Biomarkers; Diabetes Mellitus; Bacteria; Feces; Kidney Failure, Chronic
PubMed: 37341590
DOI: 10.1128/spectrum.00382-23 -
International Microbiology : the... Nov 2023The gut microbiota is closely related to the development of sepsis. The aim of this study was to explore changes in the gut microbiota and gut metabolism, as well as...
The gut microbiota is closely related to the development of sepsis. The aim of this study was to explore changes in the gut microbiota and gut metabolism, as well as potential relationships between the gut microbiota and environmental factors in the early stages of sepsis. Fecal samples were collected from 10 septic patients on the first and third days following diagnosis in this study. The results showed that in the early stages of sepsis, the gut microbiota is dominated by microorganisms that are tightly associated with inflammation, such as Escherichia-Shigella, Enterococcus, Enterobacteriaceae, and Streptococcus. On sepsis day 3 compared to day 1, there was a significant decrease in Lactobacillus and Bacteroides and a significant increase in Enterobacteriaceae, Streptococcus, and Parabacteroides. Culturomica_massiliensis, Prevotella_7 spp., Prevotellaceae, and Pediococcus showed significant differences in abundance on sepsis day 1, but not on sepsis day 3. Additionally, 2-keto-isovaleric acid 1 and 4-hydroxy-6-methyl-2-pyrone metabolites significantly increased on sepsis day 3 compared to day 1. Prevotella_7 spp. was positively correlated with phosphate and negatively correlated with 2-keto-isovaleric acid 1 and 3-hydroxypropionic acid 1, while Prevotella_9 spp. was positively correlated with sequential organ failure assessment score, procalcitonin and intensive care unit stay time. In conclusion, the gut microbiota and metabolites are altered during sepsis, with some beneficial microorganisms decreasing and some pathogenic microorganisms increasing. Furthermore, Prevotellaceae members may play different roles in the intestinal tract, with Prevotella_7 spp. potentially possessing beneficial health properties and Prevotella_9 spp. potentially playing a promoting role in sepsis.
Topics: Humans; Feces; Gastrointestinal Microbiome; Enterobacteriaceae; Sepsis; RNA, Ribosomal, 16S
PubMed: 37145385
DOI: 10.1007/s10123-023-00363-z -
Gut Sep 2023
Topics: Humans; Colitis; Bacteroidetes; Probiotics
PubMed: 36788013
DOI: 10.1136/gutjnl-2022-329386 -
Journal of Agricultural and Food... Jul 2023Aflatoxin B (AFB), a potent food-borne hepatocarcinogen, is the most toxic aflatoxin that induces liver injury in humans and animals. Species-specific sensitivities of...
Aflatoxin B (AFB), a potent food-borne hepatocarcinogen, is the most toxic aflatoxin that induces liver injury in humans and animals. Species-specific sensitivities of aflatoxins cannot be fully explained by differences in the metabolism of AFB between animal species. The gut microbiota are critical in inflammatory liver injury, but it remains to reveal the role of gut microbiota in AFB-induced liver injury. Here, mice were gavaged with AFB for 28 days. Then, the modulation of gut microbiota, colonic barrier, and liver pyroptosis and inflammation were analyzed. To further verify the direct role of gut microbiota in AFB-induced liver injury, mice were treated with antibiotic mixtures (ABXs) to deplete the microbiota, and fecal microbiota transplantation (FMT) was conducted. The treatment of AFB in mice altered gut microbiota composition, such as increasing the relative abundance of , , and , inducing colonic barrier dysfunction and promoting liver pyroptosis. In ABX-treated mice, AFB had little effect on the colonic barrier and liver pyroptosis. Notably, after FMT, in which the mice were colonized with gut microbiota from AFB-treated mice, colonic barrier dysfunction, and liver pyroptosis and inflammation were obliviously identified. We proposed that the gut microbiota directly participated in AFB-induced liver pyroptosis and inflammation. These results provide new insights into the mechanisms of AFB hepatotoxicity and pave a window for new targeted interventions to prevent or reduce AFB hepatotoxicity.
Topics: Mice; Humans; Animals; Aflatoxin B1; Gastrointestinal Microbiome; Chemical and Drug Induced Liver Injury, Chronic; Liver; Aflatoxins; Inflammation
PubMed: 37406338
DOI: 10.1021/acs.jafc.3c02617 -
Frontiers in Endocrinology 2023This study was designed to explore the composition of the intestinal microbiota and its longitudinal variation between the second trimester (T2) and the third trimester... (Observational Study)
Observational Study
Composition of the intestinal microbiota and its variations between the second and third trimesters in women with gestational diabetes mellitus and without gestational diabetes mellitus.
OBJECTIVE
This study was designed to explore the composition of the intestinal microbiota and its longitudinal variation between the second trimester (T2) and the third trimester (T3) in women with gestational diabetes mellitus (GDM) and pregnant women with normal glucose tolerance.
METHODS
This observational study was conducted at Peking Union Medical College Hospital (PUMCH). Women with GDM and pregnant women with normal glucose tolerance were enrolled in the study, and fecal samples were collected during T2 (weeks 24~28) and T3 (weeks 34~38). Fecal samples were analyzed from 49 women with GDM and 42 pregnant women with normal glucose tolerance. The 16S rRNA gene amplicon libraries were sequenced to analyze the microbiota and QIIME2 was used to analyze microbiome bioinformatics.
RESULTS
The four dominant phyla that , , and which accomplish about 99% of the total relative abundance did not significantly change between the T2 and T3 in the GDM and healthy groups. At the genus level, the relative abundance of (0 vs. 0.25%, P = 0.041) and (0 vs. 0.29%, P = 0.041) increased significantly in the control group, but not in the GDM group. At the phylum level, the relative abundance of and was significantly different between women with GDM and pregnant women with normal glucose tolerance in both T2 and T3. In T2 and T3, the relative abundances of , , and were significantly higher in the GDM group than in the control group (P<0.05). The relative abundance of in the GDM group was lower than in the control group in both T2 and T3.
CONCLUSIONS
The intestinal microbiota composition was stable from T2 to T3 in the GDM and control groups; however, the intestinal microbiota composition was different between the two groups.
Topics: Pregnancy; Female; Humans; Diabetes, Gestational; Pregnancy Trimester, Third; Gastrointestinal Microbiome; RNA, Ribosomal, 16S; Blood Glucose; Glucose; Bacteria; Actinobacteria
PubMed: 37522117
DOI: 10.3389/fendo.2023.1126572 -
Nutrients Nov 2023The objective of this study was to examine the correlation between gut microbiota and both age-related macular degeneration (AMD) and glaucoma. Mendelian randomization...
The objective of this study was to examine the correlation between gut microbiota and both age-related macular degeneration (AMD) and glaucoma. Mendelian randomization studies were conducted utilizing the data sourced from the genome-wide association study (GWAS) database for the gut microbiome, AMD, and glaucoma. Single nucleotide polymorphism (SNP) estimates were summarized through five Mendelian randomization (MR) methods. We utilized Cochran's Q statistic to evaluate the heterogeneity of the instrumental variables (IVs). Additionally, we employed a "leave-one-out" approach to verify the stability of our findings. Inverse variance weighted (IVW) suggests that Eubacterium (oxidoreducens group) and Parabacteroides had a protective effect on AMD. Both weighted median and IVW suggest that Lachnospiraceae (NK4A136 group) and Ruminococcaceae (UCG009) had a protective effect on AMD. However, both weighted median and IVW suggest that Dorea had a risk effect on AMD. Similarly, The IVW of Eubacterium (ventriosum group) showed a risk effect on AMD. The weighted median of Eubacterium (nodatum group), Lachnospiraceae (NC2004 group), and Roseburia had a risk effect on glaucoma. IVW suggested that Ruminococcaceae (UCG004) had a risk effect on glaucoma. Reverse MR analysis found a causal link between Eubacterium (nodatum group) and glaucoma. No causal relationships were found between AMD or glaucoma and the other mentioned bacterial groups. No significant heterogeneity or evidence of horizontal pleiotropy was detected. This study found that certain gut bacteria had protective effects on AMD, while others may be risk factors for AMD or glaucoma. Likewise, reverse MR found that glaucoma led to an increased abundance of certain gut bacteria. Further trials are needed to clarify the specific mechanisms involved.
Topics: Humans; Gastrointestinal Microbiome; Genome-Wide Association Study; Mendelian Randomization Analysis; Glaucoma; Macular Degeneration; Clostridiales; Lactobacillales
PubMed: 37960299
DOI: 10.3390/nu15214646 -
Frontiers in Sports and Active Living 2023The gut microbiome plays a fundamental role in host homeostasis through regulating immune functions, enzyme activity, and hormone secretion. Exercise is associated with...
INTRODUCTION
The gut microbiome plays a fundamental role in host homeostasis through regulating immune functions, enzyme activity, and hormone secretion. Exercise is associated with changes in gut microbiome composition and function. However, few studies have investigated the gut microbiome during training periodization. The present study aimed to investigate the relationship between training periodization and the gut microbiome in elite athletes.
METHODS
In total, 84 elite athletes participated in the cross-sectional study; and gut microbiome was determined during their transition or preparation season period. Further, 10 short-track speed skate athletes participated in the longitudinal study, which assessed the gut microbiome and physical fitness such as aerobic capacity and anaerobic power in the general and specific preparation phase of training periodization. The gut microbiome was analyzed using 16S rRNA sequencing.
RESULTS
The cross-sectional study revealed significant differences in and genera and in enterotype distribution between transition and preparation season phase periodization. In the longitudinal study, training phase periodization altered the level of , , and in the microbiome. Such changes in the microbiome were significantly correlated with alternations in aerobic capacity and tended to correlate with the anaerobic power.
DISCUSSION
These findings suggest that periodization alters the gut microbiome abundance related to energy metabolism and trainability of physical fitness. Athlete's condition may thus be mediated to some extent by the microbiota in the intestinal environment.
PubMed: 37521099
DOI: 10.3389/fspor.2023.1219345 -
FEBS Open Bio Aug 2023Ulcerative colitis (UC) is a recurrent inflammatory disease related to gut microbiota disorder. Metabolites and their sensors play an important role in the communication...
Ulcerative colitis (UC) is a recurrent inflammatory disease related to gut microbiota disorder. Metabolites and their sensors play an important role in the communication between gut microbes and their host. Our previous study revealed that G protein-coupled receptor 35 (GPR35) is a key guardian of kynurenic acid (KA) and a core element of the defense responses against gut damage. However, the mechanism remains unknown. In this study, a DSS-induced rat colitis model was established and 16S rRNA sequencing was applied to explore the influence of GPR35-mediated KA sensing on gut microbiota homeostasis. Our results demonstrated that GPR35-mediated KA sensing is a necessary component in maintaining gut barrier integrity against DSS-induced damage. Furthermore, we provide compelling evidence suggesting that GPR35-mediated KA sensing plays a crucial role in maintaining gut microbiota homeostasis, which contributes to alleviation of DSS-induced colitis. In addition, five classes (Actinobacteria, Beta-/Gamma-proteobacteria, Erysipelotrichi, and Coriobacteriia) and six genera (Corynebacterium, Allobaculum, Parabacteroides, Sutterella, Shigella, and Xenorhabdus) were identified as the marked bacterial taxa that characterized the progression and outcome of colitis and are regulated by GPR35-mediated KA sensing. Our findings highlight that GPR35-mediated KA sensing is an essential defense mechanism against disorder of gut microbiota in UC. The results provide insights into the key role of specific metabolites and their monitor in maintaining gut homeostasis.
Topics: Rats; Animals; Colitis, Ulcerative; Gastrointestinal Microbiome; Kynurenic Acid; RNA, Ribosomal, 16S; Colitis; Receptors, G-Protein-Coupled; Bacteria
PubMed: 37423235
DOI: 10.1002/2211-5463.13673 -
European Journal of Pediatrics Oct 2023Idiopathic short stature (ISS) accounts for more than 70% of childhood short stature cases, with an undefined etiology and pathogenesis, leading to limited treatment....
UNLABELLED
Idiopathic short stature (ISS) accounts for more than 70% of childhood short stature cases, with an undefined etiology and pathogenesis, leading to limited treatment. However, recent studies have shown that intestinal microbiota may be associated with ISS. This study aimed to characterize the intestinal microbiota in children with ISS, effect of treatment with growth hormones, and association between specific bacterial species and ISS. This study enrolled 55 children, comprising 40 diagnosed with ISS at Jinhua Hospital, Zhejiang University, and 15 healthy controls. The subjects with ISS were divided into the untreated ISS group (UISS group, 22 children who had not been treated with recombinant human growth hormone [rhGH]), treated ISS group (TISS group, 18 children treated with rhGH for 1 year), and control group (NC group, 15 healthy children). High-throughput sequencing was used to determine the intestinal microbiota characteristics. Higher abundances of Bacteroides, Prevotella, Alistipes, Parabacteroides, Agathobacter and Roseburia were found in the UISS and TISS groups than in the control group, whereas Bifidobacterium, Subdoligranulum, and Romboutsia were less abundant. The composition of intestinal microbiota in the UISS and TISS groups was almost identical, except for Prevotella. The TISS group had significantly lower levels of Prevotella than did the UISS group, which were closer to those of the NC group. Receiver operating characteristic curve analysis revealed that the abundances of Prevotella, Bifidobacterium, Bacteroides, and Subdoligranulum were effective in differentiating between the UISS and NC groups.
CONCLUSION
Alterations in intestinal microbiota may be associated with ISS. Specific bacterial species, such as Prevotella, may be potential diagnostic markers for ISS.
WHAT IS KNOWN
• ISS is associated with the GH-IGF-1 axis. • Recent studies indicated an association between the GH-IGF-1 axis and intestinal microbiota.
WHAT IS NEW
• Children with ISS showed alterations in intestinal microbiota, with a relative increase in the abundance of gut inflammation-related bacteria. • The relative abundances of Prevotella, Bacteroides, Bifidobacterium, and Subdoligranulum may serve as potential diagnostic markers.
Topics: Humans; Child; Insulin-Like Growth Factor I; Cross-Sectional Studies; Gastrointestinal Microbiome; Human Growth Hormone; Growth Hormone; Bacteria; Growth Disorders; Body Height
PubMed: 37522979
DOI: 10.1007/s00431-023-05132-8 -
Atherosclerosis May 2024Metabolic associated fatty liver disease (MAFLD) is a novel concept proposed in 2020, which is more practical for identifying patients with fatty liver disease with high...
BACKGROUND
Metabolic associated fatty liver disease (MAFLD) is a novel concept proposed in 2020, which is more practical for identifying patients with fatty liver disease with high risk of disease progression. Fatty liver is a driver for extrahepatic complications, particularly cardiovascular diseases (CVD). Although the risk of CVD in MAFLD could be predicted by carotid ultrasound test, a very early stage prediction method before the formation of pathological damage is still lacking.
METHODS
Stool microbiomes and plasma metabolites were compared across 196 well-characterized participants encompassing normal controls, simple MAFLD patients, MAFLD patients with carotid artery pathological changes, and MAFLD patients with diagnosed coronary artery disease (CAD). 16S rDNA sequencing data and untargeted metabolomic profiles were interrogatively analyzed using differential abundance analysis and random forest (RF) machine learning algorithm to identify discriminatory gut microbiomes and metabolomic.
RESULTS
Characteristic microbial changes in MAFLD patients with CVD risk were represented by the increase of Clostridia and Firmicutes-to-Bacteroidetes ratios. Faecalibacterium was negatively correlated with mean-intima-media thickness (IMT), TC, and TG. Megamonas, Bacteroides, Parabacteroides, and Escherichia were positively correlated with the exacerbation of pathological indexes. MAFLD patients with CVD risk were characterized by the decrease of lithocholic acid taurine conjugate, and the increase of ethylvanillin propylene glycol acetal, both of which had close relationship with Ruminococcus and Gemmiger. Biotin l-sulfoxide had positive correlation with mean-IMT, TG, and weight. The general auxin pesticide beta-naphthoxyacetic acid and the food additive glucosyl steviol were both positively correlated with the increase of mean-IMT. The model combining the metabolite signatures with 9 clinical parameters accurately distinguished MAFLD with CVD risk in the proband and validation cohort. It was found that citral was the most important discriminative metabolite marker, which was validated by both in vitro and in vivo experiments.
CONCLUSIONS
Simple MAFLD patients and MAFLD patients with CVD risk had divergent gut microbes and plasma metabolites. The predictive model based on metabolites and 9 clinical parameters could effectively discriminate MAFLD patients with CVD risk at a very early stage.
Topics: Humans; Gastrointestinal Microbiome; Male; Female; Middle Aged; Feces; Metabolomics; Cardiovascular Diseases; Biomarkers; Risk Assessment; Case-Control Studies; Aged; Predictive Value of Tests; Bacteria; Heart Disease Risk Factors; Adult; Non-alcoholic Fatty Liver Disease; Machine Learning; Carotid Intima-Media Thickness
PubMed: 38581738
DOI: 10.1016/j.atherosclerosis.2024.117526