Lean nonalcoholic steatohepatitis (NASH) poses a serious threat to public health worldwide. Herbs of the genus Gentiana have been used for centuries to treat hepatic disease or have been consumed for ...hepatic protection efficiency. Gentiopicroside (GPS), the main bioactive component of Gentiana herbs, has been shown to be beneficial for protecting the liver, improving intestinal disorders, modulating bile acid profiles, ameliorating alcoholic hepatosteatosis, and so on. It is plausible to speculate that GPS may hold potential as a therapeutic strategy for lean NASH. However, no related studies have been conducted thus far.
The present work aimed to investigate the benefit of GPS on NASH in a lean mouse model.
NASH in a lean mouse model was successfully established via a published method. GPS of 50 and 100 mg/kg were orally administered to verify the effect. Untargeted metabolomics, 16S rDNA sequencing and bile acid (BA) profiling, as well as qPCR and Western blotting analysis were employed to investigate the mechanism underlying the alleviating effect.
GPS significantly reduced the increase in serum biochemicals and liver index, and attenuated the accumulation of fat in the livers of lean mice with NASH. Forty-two potential biomarkers were identified by metabolomics analysis, leading to abnormal metabolic pathways of primary bile acid biosynthesis and fatty acid biosynthesis, which were subsequently rebalanced by GPS. A decreased Firmicutes/Bacteroidetes (F/B) ratio and disturbed BA related GM profiles were revealed in lean mice with NASH but were partially recovered by GPS. Furthermore, serum profiling of 23 BAs confirmed that serum BA levels were elevated in the lean model but downregulated by GPS treatment. Pearson correlation analysis validated associations between BA profiles, serum biochemical indices and related GM. qPCR and Western blotting analysis further elucidated the regulation of genes associated with liver lipid synthesis and bile acid metabolism.
GPS may ameliorate steatosis in lean mice with NASH, regulating the metabolomic profile, BA metabolism, fatty acid biosynthesis, and BA-related GM. All these factors may contribute to its beneficial effect.
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•Gentiopicroside has been verified of alleviating NASH in lean mice.•Metabolomics, 16S rRNA sequencing and bile acid profiling were integrated to reveal the mechanism.•The alleviation was associated with regulations of BA metabolism and BA related gut microbiota.
In this study, we sought to determine the effects of intestinal flora on the feed efficiency of meat ducks by evaluating the correlation between intestinal flora and residual feed intake. The F2 ...generation of Cherry Valley ducks × Runzhou Crested White ducks was used as the study subjects, and feed consumption being recorded from d 21 to 42. RFI was calculated based on growth performance, and 20 low RFI and 20 high RFI ducks were randomly selected to characterize the effect of RFI on growth performance. To analyze the intestinal flora affecting RFI, 16s rDNA sequencing was performed on the contents of 5 intestinal segments from the HR and LR groups, and macrogenomic sequencing was performed on the cecal contents. Feed intake, average daily feed intake, feed conversion ratio, and residual feed intake were lower in low RFI. Analysis of the intestinal flora revealed the cecum to be more highly enriched in the carbohydrate metabolism pathway and less enriched with potentially pathogenic taxa than the other assessed intestinal regions. Further analysis of the cecal microbiota identified nine significantly differentially enriched intestinal flora. In this study, we accordingly identified a basis for the mechanisms underlying the effects of the intestinal flora on meat duck feed efficiency.
The development of next generation sequencing (NGS) techniques has enabled researchers to study and understand the world of microorganisms from broader and deeper perspectives. The contemporary ...advances in DNA sequencing technologies have not only enabled finer characterization of bacterial genomes but also provided deeper taxonomic identification of complex microbiomes which in its genomic essence is the combined genetic material of the microorganisms inhabiting an environment, whether the environment be a particular body econiche (e.g., human intestinal contents) or a food manufacturing facility econiche (e.g., floor drain). To date, 16S rDNA sequencing, metagenomics and metatranscriptomics are the three basic sequencing strategies used in the taxonomic identification and characterization of food-related microbiomes. These sequencing strategies have used different NGS platforms for DNA and RNA sequence identification. Traditionally, 16S rDNA sequencing has played a key role in understanding the taxonomic composition of a food-related microbiome. Recently, metagenomic approaches have resulted in improved understanding of a microbiome by providing a species-level/strain-level characterization. Further, metatranscriptomic approaches have contributed to the functional characterization of the complex interactions between different microbial communities within a single microbiome. Many studies have highlighted the use of NGS techniques in investigating the microbiome of fermented foods. However, the utilization of NGS techniques in studying the microbiome of non-fermented foods are limited. This review provides a brief overview of the advances in DNA sequencing chemistries as the technology progressed from first, next and third generations and highlights how NGS provided a deeper understanding of food-related microbiomes with special focus on non-fermented foods.
Green manure rotation is commonly used to increase soil fertility and improve crop yield. However, the effects of this management practice on the underground microbial ecosystem and the indirect ...impact on the aboveground crop growth have not been systematically analysed. In this study, we investigated the rice rhizosphere and bulk soil microbial community in a 31-year-old field experimental site treated with different green manures and rice rotations using both 16S rDNA high-throughput sequencing and quantitative PCR approaches. Four treatments have been setup in this experimental site since 1982, including a rice-rice-winter fallow treatment as a control and three green manure rotation treatments: rice-rice-Chinese milk vetch, rice-rice-rape and rice-rice-ryegrass. The qPCR results showed that the bacterial abundances in the rice rhizosphere of the green manure rotation treatments were all significantly higher than in the winter fallow (p < 0.05), but no significant differences were found among those three green manure rotation treatments. Moreover, α-diversity analysis revealed that green manure rotations decreased the microbial diversity (Shannon and Simpson indexes) and richness (Chao value) in the rice rhizosphere. Permutational Multivariate Analysis of Variance based on β-diversity revealed the microbial community was significantly switched in rice rhizosphere after long-term green manure rotation (p < 0.01). Additionally, the soil and plant characteristics contributed almost equally to the rhizosphere bacterial community based on a partial CCA-based variation partitioning analysis. At the genus level, the well-known plant-growth-promoting rhizobacteria Acinetobacter (31%–41%) and Pseudomonas (14%–28%) were the preponderant groups in green manure rotation treatments but accounted for only 4.4% and 2.5% in the winter fallow treatment. Overall, long-term rice-rice-green manure rotation shaped the microbial community in the rice rhizosphere; in particular, some beneficial bacteria, Acinetobacter and Pseudomonas, accumulated in the rhizosphere of green manure treatments.
•Long-term green manure increased the bacterial abundance in bulk soil and rhizosphere.•The microbial community in rhizosphere was altered by both soil and plant changes.•Acinetobacter and Pseudomonas accumulated in rhizosphere of green manure treatments.
Pigs are one of the most important economic livestock. Gut microbiota is not only critical to the health but also the production efficiency of pigs. Manipulating gut microbiota relies on the full ...view of gut microbiome and the understanding of drive forces shaping microbial communities. 16s rDNA sequencing was used to profile microbiota along the longitudinal and radical axes to obtain the topographical map of microbiome in different intestinal compartments in young pigs. Alpha and beta-diversities revealed distinct differences in microbial compositions between the distal ileum and cecum and colon, as well as between the lumen and mucosa.
and
dominated in the ileum, constituting 95 and 80% of the luminal and mucosa-attached microbiome. Transitioning from the small intestine to the large intestine, luminal
increased from 1.69 to 45.98% in the cecum and 40.09% in the colon, while mucosal
raised from 9 to 35.36% and 27.96%. Concurrently, luminal
and
and mucosal-attached
remarkably decreased. By co-occurrence network analyses,
and
were recognized as the central nodes of luminal microbial network, and
and
were identified as mucosal central nodes. Co-abundance was uncovered among
, and
in the luminal and mucosal microbiome, while opportunistic pathogens from γ-
in the mucosa. Strong co-exclusion was shown between
with
-centered microbial groups in the lumen. Redundancy analysis found bile acids and short chain fatty acids explained 37.1 and 41% of variations in the luminal microbial composition, respectively. Primary bile acid, taurine- and glycine- conjugated bile acids were positively correlated with
, whereas secondary bile acids, acetate, propionate, butyrate, and valerate were positively correlated with
. Functional analyses demonstrated that
, and
were positively correlated with gene functions related to amino acids, energy, cofactors and vitamins metabolism, which are indispensable for the hosts. These results suggested site specific colonization and co-occurrence of swine gut microbiome closely relate to the microenvironment in each niche. Interactions of core gut microbiome greatly contributed to metabolism and/or immunity in the swine intestine.
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•The microbial genes changed during composting with different AgNPs concentrations.•The contributions of environmental variables to the microbial genes were different.•28.8% of the ...variations in 16S rDNA gene were significantly explained by NO3−-N.•pH significantly explained 61.8% of the variations in nitrifying genes.•NO3−-N and TN explained 34.2% and 9.2% of denitrifying genes changes, respectively.
This study evaluated the contributions of environmental variables to the variations in bacterial 16S rDNA, nitrifying and denitrifying genes abundances during composting in the presence of polyvinylpyrrolidone coated silver nanoparticles (PVP-AgNPs). Manual forward selection in redundancy analysis (RDA) indicated that the variation in 16S rDNA was significantly explained by NO3−-N, while nitrifying genes were significantly related with pH, and denitrifying genes were driven by NO3−-N and TN. Partial RDA further revealed that NO3−-N solely explained 28.8% of the variation in 16S rDNA abundance, and pH accounted for 61.8% of the variation in nitrifying genes. NO3−-N and TN accounted for 34.2% and 9.2% of denitrifying genes variation, respectively. The RDA triplots showed that different genes shared different relationships with environmental parameters. Based on these findings, a composting with high efficiency and quality may be conducted in the future work by adjusting the significant environmental variables.
The link between microbiota and gastric cancer (GC) has attracted widespread attention. However, the phylogenetic profiles of niche-specific microbiota in the tumor microenvironment is still unclear. ...Here, mucosa-associated microorganisms from 62 pairs of matched GC tissues and adjacent non-cancerous tissues were characterized by 16S rRNA gene sequencing. Functional profiles of the microbiota were predicted using PICRUSt, and a co-occurrence network was constructed to analyze interactions among gastric microbiota. Results demonstrated that mucosa-associated microbiota from cancerous and non-cancerous tissues established micro-ecological systems that differed in composition, structure, interaction networks, and functions. Microbial richness and diversity were increased in cancerous tissues, with the co-occurrence network exhibiting greater complexity compared with that in non-cancerous tissue. The bacterial taxa enriched in the cancer samples were predominantly represented by oral bacteria (such as
,
, and
), while lactic acid-producing bacteria (such as
and
) were more abundant in adjacent non-tumor tissues. Colonization by
, which is a GC risk factor, also impacted the structure of the microbiota. Enhanced bacterial purine metabolism, carbohydrate metabolism and denitrification functions were predicted in the cancer associated microbial communities, which was consistent with the increased energy metabolism and concentration of nitrogen-containing compounds in the tumor microenvironment. Furthermore, the microbial co-occurrence networks in cancerous and non-cancerous tissues of GC patients were described for the first time. And differential taxa and functions between the two groups were identified. Changes in the abundance of certain bacterial taxa, especially oral microbiota, may play a role in the maintenance of the local microenvironment, which is associated with the development or progression of GC.
Depression has become the leading cause of disability worldwide and a growing public health problem in China. In addition, intestinal flora may be associated with depression. This study investigated ...the effect of the decoction Xiaoyaosan (XYS) against depressive behavior through the regulation of intestinal flora. Fifty-two healthy male Sprague-Dawley rats were randomly divided into four groups (i.e., control, model, XYS, and fluoxetine). The latter three groups were subjected to 21 days of chronic restraint stress to produce the stress depression model. Rats in the XYS and fluoxetine groups received intragastric administration of XYS and fluoxetine, respectively. The behavioral changes of the rats were observed after 21 days. Stool specimens were sequenced using the 16S rDNA high-throughput method to detect the structure and changes in intestinal flora. There was no difference observed in alpha diversity among the groups. At the phylum level, XYS regulated the abundance of Bacteroidetes, Proteobacteria, Firmicutes, Chloroflexi, and Planctomycetes. At the genus level, XYS reduced the abundance of the Prevotellaceae_Ga6A1_group, Prevotellaceae_UCG-001, and Desulfovibrio. On the contrary, it increased the abundance of the Ruminococcaceae family to improve depression-like behavior. The mechanism involved in this process may be related to short-chain fatty acids, lipopolysaccharides, and intestinal inflammation.
Emerging evidence indicates that gut dysbiosis may play a regulatory role in the onset and progression of Huntington's disease (HD). However, any alterations in the fecal microbiome of HD patients ...and its relation to the host cytokine response remain unknown. The present study investigated alterations and host cytokine responses in patients with HD. We enrolled 33 HD patients and 33 sex- and age- matched healthy controls. Fecal microbiota communities were determined through 16S ribosomal DNA gene sequencing, from which we analyzed fecal microbial richness, evenness, structure, and differential abundance of individual taxa between HD patients and healthy controls. HD patients were evaluated for their clinical characteristics, and the relationships of fecal microbiota with these clinical characteristics were analyzed. Plasma concentrations of interferon gamma (IFN-γ), interleukin 1 beta (IL-1β), IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, and tumor necrosis factor alpha were measured by Meso Scale Discovery (MSD) assays, and relationships between microbiota and cytokine levels were analyzed in the HD group. HD patients showed increased α-diversity (richness), β-diversity (structure), and altered relative abundances of several taxa compared to those in healthy controls. HD-associated clinical characteristics correlated with the abundances of components of fecal microbiota at the genus level. Genus
was correlated with total functional capacity scores and IL-4 levels. Our present study also revealed that genus
were negatively correlated with proinflammatory IL-6 levels. Taken together, our present study represents the first to demonstrate alterations in fecal microbiota and inflammatory cytokine responses in HD patients. Further elucidation of interactions between microbial and host immune responses may help to better understand the pathogenesis of HD.
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