Effects of Tiaopi Xiezhuo decoction on constipation and gut dysbiosis in patients with peritoneal dialysis

Jian Gan powder ameliorates immunological liver injury in mice by modulating the gut microbiota and metabolic profiles

BACKGROUND

Immunological liver injury (ILI) is a common liver disease associated with the microbiota-gut-liver axis. Jian Gan powder (JGP) exhibits both protective and therapeutic effects on hepatitis virus-induced ILI in the clinic. However, the underlying mechanisms remain elusive. The aim of this study is to investigate the hepatoprotective effects and associated mechanisms of JGP in the context of gut microbiota, utilizing a mouse model of ILI.

METHODS

The mouse model was established employing Bacillus Calmette-Guérin (BCG) plus lipopolysaccharide (LPS). Following treatment with JGP (7.5, 15, or 30 g/kg), serum, liver, and fresh fecal samples were analyzed. 16S rRNA gene sequencing and untargeted metabolomics profiling were performed to assess the role of JGP on the gut microbiota and its metabolites.

RESULTS

JGP treatment markedly reduced serum IFN-γ, IL-6, IL-22, and hepatic p-STAT3 (phosphorylated transducer and activator of transcription-3) expression. In contrast, JGP increased the percentage of proliferating cell nuclear antigen-positive liver cells in treated mice. Fecal 16S rRNA gene sequencing revealed that JGP treatment restored the levels of Alloprevotella, Burkholderia-Caballeronia-Paraburkholderia, Muribaculum, Streptococcus, and Stenotrophomonas. Additionally, metabolomics analysis of fecal samples showed that JGP restored the levels of allylestrenol, eplerenone, phosphatidylethanolamine (PE) (P-20:0/0:0), sphingomyelin (SM) d27:1, soyasapogenol C, chrysin, and soyasaponin I.

CONCLUSIONS

JGP intervention improves ILI by restoring gut microbiota and modifying its metabolic profiles. These results provide a novel insight into the mechanism of JGP in treating ILI and the scientific basis to support its clinical application.

Prenatal Lead Exposure Is Associated with Reduced Abundance of Beneficial Gut Microbial Cliques in Late Childhood: An Investigation Using Microbial Co-Occurrence Analysis (MiCA)

Many analytical methods used in gut microbiome research focus on either single bacterial taxa or the whole microbiome, ignoring multibacteria relationships (microbial cliques). We present a novel analytical approach to identify microbial cliques within the gut microbiome of children at 9-11 years associated with prenatal lead (Pb) exposure. Data came from a subset of participants (n = 123) in the Programming Research in Obesity, Growth, Environment and Social Stressors cohort. Pb concentrations were measured in maternal whole blood from the second and third trimesters of pregnancy. Stool samples collected at 9-11 years old underwent metagenomic sequencing to assess the gut microbiome. Using a novel analytical approach, Microbial Co-occurrence Analysis (MiCA), we paired a machine learning algorithm with randomization-based inference to first identify microbial cliques that were predictive of prenatal Pb exposure and then estimate the association between prenatal Pb exposure and microbial clique abundance. With second-trimester Pb exposure, we identified a two-taxa microbial clique that included Bifidobacterium adolescentis and Ruminococcus callidus and a three-taxa clique that also included Prevotella clara. Increasing second-trimester Pb exposure was associated with significantly increased odds of having the two-taxa microbial clique below the median relative abundance (odds ratio (OR) = 1.03, 95% confidence interval (CI) [1.01-1.05]). Using a novel combination of machine learning and causal inference, MiCA identified a significant association between second-trimester Pb exposure and the reduced abundance of a probiotic microbial clique within the gut microbiome in late childhood.

Effects of Lactiplantibacillus plantarum GUANKE on Diphenoxylate-Induced Slow Transit Constipation and Gut Microbiota in Mice

Slow transit constipation (STC) is a prevalent gastrointestinal condition with slow transit, and some probiotics can effectively relieve constipation, but the exact mechanisms have not been fully understood. In this study, we evaluate the impact of Lactiplantibacillus plantarum GUANKE (GUANKE) on diphenoxylate-induced slow transit constipation and speculate on the underlying mechanisms in a mouse model. Administration of L. plantarum GUANKE alleviated constipation indexes, including defecation time, fecal output and water content, and gastrointestinal transit ratio. In addition, GUANKE restored the protein expression of constipation-related intestinal factors (aquaporins (AQPs) and interstitial Cajal cells (ICCs)) in colon tissues measured using immunofluorescence staining; regulated the neurotransmitters and hormones, such as increased levels of 5-hydroxytryptamine, substance P, and motilin; and decreased levels of vasoactive intestinal peptide and nitric oxide in serum, as measured by an ELISA. 16S rRNA and correlation analysis of feces indicated that GUANKE administration effectively reduced constipation-induced Prevotella enrichment and suggested a potential contribution of Prevotella to diphenoxylate-induced STC in mice. GUANKE had no effect on short-chain fatty acids (SCFAs) in cecum content. This study revealed that GUANKE may alleviate constipation in mice through regulating intestinal neurotransmitter and hormone release and altering specific bacterial taxa, rather than by affecting SCFAs and the diversity of microbiota in the gut. Further research is needed to confirm if the findings observed in this study will be consistent in other animal studies or clinical trials.

Prenatal Pb exposure is associated with reduced abundance of beneficial gut microbial cliques in late childhood: an investigation using Microbial Co-occurrence Analysis (MiCA)

Background

Many analytical methods used in gut microbiome research focus on either single bacterial taxa or the whole microbiome, ignoring multi-bacteria relationships (microbial cliques). We present a novel analytical approach to identify multiple bacterial taxa within the gut microbiome of children at 9-11 years associated with prenatal Pb exposure.

Methods

Data came from a subset of participants (n=123) in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) cohort. Pb concentrations were measured in maternal whole blood from the second and third trimesters of pregnancy. Stool samples collected at 9-11 years old underwent metagenomic sequencing to assess the gut microbiome. Using a novel analytical approach, Microbial Co-occurrence Analysis (MiCA), we paired a machine-learning algorithm with randomization-based inference to first identify microbial cliques that were predictive of prenatal Pb exposure and then estimate the association between prenatal Pb exposure and microbial clique abundance.

Results

With second-trimester Pb exposure, we identified a 2-taxa microbial clique that included Bifidobacterium adolescentis and Ruminococcus callidus, and a 3-taxa clique that added Prevotella clara. Increasing second-trimester Pb exposure was associated with significantly increased odds of having the 2-taxa microbial clique below the 50th percentile relative abundance (OR=1.03,95%CI[1.01-1.05]). In an analysis of Pb concentration at or above vs. below the United States and Mexico guidelines for child Pb exposure, odds of the 2-taxa clique in low abundance were 3.36(95%CI[1.32-8.51]) and 6.11(95%CI[1.87-19.93]), respectively. Trends were similar with the 3-taxa clique but not statistically significant.

Discussion

Using a novel combination of machine-learning and causal-inference, MiCA identified a significant association between second-trimester Pb exposure and reduced abundance of a probiotic microbial clique within the gut microbiome in late childhood. Pb exposure levels at the guidelines for child Pb poisoning in the United States, and Mexico are not sufficient to protect against the potential loss of probiotic benefits.