OBJECTIVE: To investigate the prevalence of Echinococcus infections in wild carnivores in Serthar County, Sichuan Province, so as to provide insights into echinococcosis control in local areas. METHODS: Stool samples were collected from wild carnivores in Serthar County, Sichuan Province in May 2021, and the host sources of stool samples and Echinococcus infections were identified using PCR assays. The prevalence of E. multilocularis, E. granulosus and E. shiquicus infections was estimated in different hosts. RESULTS: A total of 583 stool samples were collected from wild carnivores, including 147 stool samples from fox, 154 from wolf, 227 from wild dogs and 11 from lynx. The overall prevalence of E. multilocularis, E. granulosus and E. shiquicus infections was 5.68%, 0.19% and 14.20% in canine stool samples, and no E. granulosus infection was detected in fox stool samples, while the prevalence of E. multilocularis and E. shiquicus infections was 0.68% and 47.62% in fox stool samples (χ² = 88.41, P < 0.001). No E. granulosus or E. shiquicus infection was detected in wolf stool samples, and the prevalence of E. multilocularis infection was 10.39% in wolf stool samples. The prevalence of E. multilocularis, E. granulosus and E. shiquicus infections was 5.73%, 0.44% and 2.20% in canine stool samples (χ² = 12.13, P < 0.01). In addition, the prevalence of E. multilocularis infections was significantly higher in wolf stool samples than in canine and fox stool samples (χ² = 13.23, P < 0.01), and the prevalence of E. shiquicus infections was significantly higher in fox stool samples than in canine and wolf stool samples (χ² = 187.01, P < 0.001). No Echinococcus infection was identified in 11 lynx stool samples. CONCLUSIONS The prevalence of Echinococcus infections is high in wild canines in Serthar County, Sichuan Province. Wolf, wild dog and fox all participate in the wild life cycle of E. multilocularis in Serthar County, and wolf and wild dogs may play a more important role.
Animals ; Dogs/microbiology* ; China/epidemiology* ; DNA, Helminth/genetics* ; Echinococcosis/veterinary* ; Feces ; Foxes/microbiology* ; Lynx/microbiology* ; Prevalence ; Wolves/microbiology* ; Carnivora/microbiology*

Objective: To analyze the short-term effect of individual atmospheric PM_2.5 exposure on the diversity, enterotype, and community structure of gut microbiome in healthy elderly people in Jinan, Shandong province. Methods: The present panel study recruited 76 healthy elderly people aged 60-69 years old in Dianliu Street, Lixia District, Jinan, Shandong Province, and followed them up five times from September 2018 to January 2019. The relevant information was collected by questionnaire, physical examination, precise monitoring of individual PM_2.5 exposure, fecal sample collection and gut microbiome 16S rDNA sequencing. The Dirichlet multinomial mixtures (DMM) model was used to analyze the enterotype. Linear mixed effect model and generalized linear mixed effect model were used to analyze the effect of PM_2.5 exposure on gut microbiome α diversity indices (Shannon, Simpson, Chao1, and ACE indices), enterotype and abundance of core species. Results: Each of the 76 subjects participated in at least two follow-up visits, resulting in a total of 352 person-visits. The age of 76 subjects was (65.0±2.8) years old with BMI (25.0±2.4) kg/m². There were 38 males accounting for 50% of the subjects. People with an educational level of primary school or below accounted for 10.5% of the 76 subjects, and those with secondary school and junior college or above accounting for 71.1% and 18.4%. The individual PM_2.5 exposure concentration of 76 subjects during the study period was (58.7±53.7) μg/m³. DMM model showed that the subjects could be divided into four enterotypes, which were mainly driven by Bacteroides, Faecalibacterium, Lachnospiraceae, Prevotellaceae, and Ruminococcaceae. Linear mixed effects model showed that different lag periods of PM_2.5 exposure were significantly associated with a lower gut α diversity index (FDR<0.05 after correction). Further analysis showed that PM_2.5 exposure was significantly associated with changes in the abundances of Firmicutes (Megamonas, Blautia, Streptococcus, etc.) and Bacteroidetes (Alistipes) (FDR<0.05 after correction). Conclusion: Short-term PM_2.5 exposure is significantly associated with a decrease in gut microbiome diversity and changes in the abundance of several species of Firmicutes and Bacteroidetes in the elderly. It is necessary to further explore the underlying mechanisms between PM_2.5 exposure and the gut microbiome, so as to provide a scientific basis for promoting the intestinal health of the elderly.
Aged ; Humans ; Male ; Middle Aged ; Feces/microbiology* ; Gastrointestinal Microbiome ; Particulate Matter ; RNA, Ribosomal, 16S/genetics* ; Female

Many natural products can be bio-converted by the gut microbiota to influence pertinent efficiency. Ginsenoside compound K (GCK) is a potential anti-type 2 diabetes (T2D) saponin, which is mainly bio-transformed into protopanaxadiol (PPD) by the gut microbiota. Studies have shown that the gut microbiota between diabetic patients and healthy subjects are significantly different. Herein, we aimed to characterize the biotransformation of GCK mediated by the gut microbiota from diabetic patients and healthy subjects. Based on 16S rRNA gene sequencing, the results indicated the bacterial profiles were considerably different between the two groups, especially Alistipes and Parabacteroides that increased in healthy subjects. The quantitative analysis of GCK and PPD showed that gut microbiota from the diabetic patients metabolized GCK slower than healthy subjects through liquid chromatography tandem mass spectrometry (LC-MS/MS). The selected strain A. finegoldii and P. merdae exhibited a different metabolic capability of GCK. In conclusion, the different biotransformation capacity for GCK may impact its anti-diabetic potency.
Humans ; Gastrointestinal Microbiome/genetics* ; Chromatography, Liquid/methods* ; Healthy Volunteers ; RNA, Ribosomal, 16S ; Feces/microbiology* ; Tandem Mass Spectrometry ; Biotransformation ; Diabetes Mellitus, Type 2/drug therapy*

BACKGROUND: Type 2 diabetes mellitus (T2DM) is an independent risk factor for colorectal cancer (CRC), and the patients with CRC and T2DM have worse survival. The human gut microbiota (GM) is linked to the development of CRC and T2DM, respectively. However, the GM characteristics in patients with CRC and T2DM remain unclear. METHODS: We performed fecal metagenomic and targeted metabolomics studies on 36 samples from CRC patients with T2DM (DCRC group, n = 12), CRC patients without diabetes (CRC group, n = 12), and healthy controls (Health group, n = 12). We analyzed the fecal microbiomes, characterized the composition and function based on the metagenomics of DCRC patients, and detected the short-chain fatty acids (SCFAs) and bile acids (BAs) levels in all fecal samples. Finally, we performed a correlation analysis of the differential bacteria and metabolites between different groups. RESULTS: Compared with the CRC group, LefSe analysis showed that there is a specific GM community in DCRC group, including an increased abundance of Eggerthella , Hungatella , Peptostreptococcus , and Parvimonas , and decreased Butyricicoccus , Lactobacillus , and Paraprevotella . The metabolomics analysis results revealed that the butyric acid level was lower but the deoxycholic acid and 12-keto-lithocholic acid levels were higher in the DCRC group than other groups ( P < 0.05). The correlation analysis showed that the dominant bacterial abundance in the DCRC group ( Parvimonas , Desulfurispora , Sebaldella , and Veillonellales , among others) was negatively correlated with butyric acid, hyodeoxycholic acid, ursodeoxycholic acid, glycochenodeoxycholic acid, chenodeoxycholic acid, cholic acid and glycocholate. However, the abundance of mostly inferior bacteria was positively correlated with these metabolic acid levels, including Faecalibacterium , Thermococci , and Cellulophaga . CONCLUSIONS Unique fecal microbiome signatures exist in CRC patients with T2DM compared to those with non-diabetic CRC. Alterations in GM composition and SCFAs and secondary BAs levels may promote CRC development.
Humans ; Gastrointestinal Microbiome/genetics* ; Diabetes Mellitus, Type 2 ; Microbiota ; Bacteria/genetics* ; Fatty Acids, Volatile ; Colorectal Neoplasms/metabolism* ; Butyrates ; Feces/microbiology*

To explore the composition and diversity of the intestinal microflora of Leopoldamys edwardsi in Hainan Island. In November 2019, DNA was extracted from fecal samples of 25 adult Leopoldamys edwardsi (14 males and 11 females) in Hainan Island at the Joint Laboratory of tropical infectious diseases of Hainan Medical College and Hong Kong University. Based on the IonS5TMXL sequencing platform, single-end sequencing (Single-End) was used to construct a small fragment library for single-end sequencing. Based on Reads shear filtration and OTUs clustering. The species annotation and abundance analysis of OTUs were carried out by using mothur method and SSUrRNA database, and further conducted α diversity and β diversity analysis. A total of 1481842 high quality sequences, belonging to 14 Phyla, 85 families and 186 Genera, were obtained from 25 intestinal excrement samples of Leopoldamys edwardsi. At the level of phyla classification, the main core biota of the Leopoldamys edwardsi contained Firmicutes (46.04%),Bacteroidetes (25.34%), Proteobacteria (17.09%), Tenericutes (7.38%) and Actinobacteria (1.67%), these five phyla account for 97.52% of all phyla. The ratio of Helicobacter which occupied the largest proportion at the genus level was 12.44%, followed by Lactobacillus (11.39%), Clostridium (6.19%),Mycoplasma (4.23%) and Flavonifractor (3.52%). High throughput sequencing analysis showed that the intestinal flora of Leopoldamys edwardsi in Hainan Island was complex and diverse, which had the significance of further research.
Adult ; Animals ; Bacteria/genetics* ; Feces/microbiology* ; Female ; Gastrointestinal Microbiome/genetics* ; High-Throughput Nucleotide Sequencing ; Humans ; Intestines ; Male ; Murinae/genetics*

OBJECTIVES: To examine the changes of intestinal flora in children newly diagnosed with acute lymphoblastic leukemia (ALL) and the influence of chemotherapy on intestinal flora. METHODS: Fecal samples were collected from 40 children newly diagnosed with ALL before chemotherapy and at 2 weeks, 1 month, and 2 months after chemotherapy. Ten healthy children served as the control group. 16S rDNA sequencing and analysis were performed to compare the differences in intestinal flora between the ALL and control groups and children with ALL before and after chemotherapy. RESULTS: The ALL group had a significant reduction in the abundance of intestinal flora at 1 and 2 months after chemotherapy, with a significant reduction compared with the control group (P<0.05). Compared with the control group, the ALL group had a significant reduction in the diversity of intestinal flora before and after chemotherapy (P<0.05). At the phylum level, compared with the control group, the ALL group had a significant reduction in the relative abundance of Actinobacteria at 2 weeks, 1 month, and 2 months after chemotherapy (P<0.05) and a significant increase in the relative abundance of Proteobacteria at 1 and 2 months after chemotherapy (P<0.05). At the genus level, compared with the control group, the ALL group had a significant reduction in the relative abundance of Bifidobacterium at 2 weeks, 1 month, and 2 months after chemotherapy (P<0.05); the relative abundance of Klebsiella in the ALL group was significantly higher than that in the control group at 1 and 2 months after chemotherapy and showed a significant increase at 1 month after chemotherapy (P<0.05); the relative abundance of Faecalibacterium in the ALL group was significantly lower than that in the control group before and after chemotherapy and showed a significant reduction at 2 weeks and 1 month after chemotherapy (P<0.05). The relative abundance of Enterococcus increased significantly at 1 and 2 months after chemotherapy in the ALL group (P<0.05), and was significantly higher than that in the control group (P<0.05). CONCLUSIONS The diversity of intestinal flora in children with ALL is significantly lower than that in healthy children. Chemotherapy significantly reduces the abundance of intestinal flora and can reduce the abundance of some probiotic bacteria (Bifidobacterium and Faecalibacterium) and increase the abundance of pathogenic bacteria (Klebsiella and Enterococcus) in children with ALL.
Bacteria/genetics* ; Bifidobacterium ; Child ; Feces/microbiology* ; Gastrointestinal Microbiome ; Humans ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/drug therapy*

Ma-Mu-Ran Antidiarrheal Capsules (MMRAC) is traditional Chinese medicine that has been used to treat diarrhea caused by acute enteritis (AE) and bacillary dysentery in Xinjiang (China) for many years. However, the potential therapeutic mechanism of MMRAC for AE and its regulatory mechanism on host metabolism is unclear. This study used fecal metabolomics profiling with GC/MS and 16S rRNA gene sequencing analysis to explore the potential regulatory mechanisms of MMRAC on a dextran sulfate sodium salt (DSS)-induced mouse model of AE. Fecal metabolomics-based analyses were performed to detect the differentially expressed metabolites and metabolic pathways. The 16S rRNA gene sequencing analysis was used to assess the altered gut microbes at the genus level and for functional prediction. Moreover, Pearson correlation analysis was used to integrate differentially expressed metabolites and altered bacterial genera. The results revealed that six intestinal bacteria and seven metabolites mediated metabolic disorders (i.e., metabolism of amino acid, carbohydrate, cofactors and vitamins, and lipid) in AE mice. Besides, ten altered microbes mediated the differential expression of eight metabolites and regulated these metabolisms after MMRAC administration. Overall, these findings demonstrate that AE is associated with metabolic disorders and microbial dysbiosis. Further, we present that MMRAC exerts protective effects against AE by improving host metabolism through the intestinal flora.
Animals ; Antidiarrheals/pharmacology* ; Capsules ; Enteritis/genetics* ; Feces/microbiology* ; Genes, rRNA ; Metabolomics ; Mice ; RNA, Ribosomal, 16S/genetics*

BACKGROUND: Anorexia nervosa (AN) is a psychological disorder, which is characterized by the misunderstanding of body image, food restriction, and low body weight. An increasing number of studies have reported that the pathophysiological mechanism of AN might be associated with the dysbiosis of gut microbiota. The purpose of our study was to explore the features of gut microbiota in patients with AN, hoping to provide valuable information on its pathogenesis and treatment. METHODS: In this cross-sectional study, from August 2020 to June 2021, patients with AN who were admitted into Peking University Third Hospital and Peking University Sixth Hospital ( n   =  30) were recruited as the AN group, and healthy controls (HC) were recruited from a middle school and a university in Beijing ( n   =  30). Demographic data, Hamilton Depression Scale (HAMD) scores of the two groups, and length of stay of the AN group were recorded. Microbial diversity analysis of gut microbiota in stool samples from the two groups was analyzed by 16S ribosomal RNA (rRNA) gene sequencing. RESULTS: The weight (AN vs. HC, [39.31 ± 7.90] kg vs. [56.47 ± 8.88] kg, P  < 0.001) and body mass index (BMI, AN vs. HC, [14.92 ± 2.54] kg/m 2vs. [20.89 ± 2.14] kg/m 2 , P  < 0.001) of patients with AN were statistically significantly lower than those of HC, and HAMD scores in AN group were statistically significantly higher than those of HC. For alpha diversity, there were no statistically significant differences between the two groups; for beta diversity, the two groups differed obviously regarding community composition. Compared to HC, the proportion of Lachnospiraceae in patients with AN was statistically significantly higher (AN vs. HC, 40.50% vs. 31.21%, Z  = -1.981, P  = 0.048), while that of Ruminococcaceae was lower (AN vs. HC, 12.17% vs. 19.15%, Z  = -2.728, P  = 0.007); the proportion of Faecalibacterium (AN vs. HC, 3.97% vs. 9.40%, Z  = -3.638, P  < 0.001) and Subdoligranulum (AN vs. HC, 4.60% vs. 7.02%, Z  = -2.369, P  = 0.018) were statistically significantly lower, while that of Eubacterium_hallii_group was significantly higher (AN vs. HC, 7.63% vs. 3.43%, Z  = -2.115, P  = 0.035). Linear discriminant effect (LEfSe) analysis (LDA score >3.5) showed that o_Lachnospirales, f_Lachnospiraceae, and g_Eubacterium_hallii_group (o, f and g represents order, family and genus respectively) were enriched in patients with AN. Microbial function of nutrient transport and metabolism in AN group were more abundant ( P  > 0.05). In AN group, weight and BMI were significantly negatively correlated with the abundance of Bacteroidota and Bacteroides , while positively correlated with Subdoligranulum . BMI was significantly positively correlated with Firmicutes; HAMD scores were significantly negatively correlated with Faecalibacterium. CONCLUSIONS The composition of gut microbiota in patients with AN was different from that of healthy people. Clinical indicators have correlations with the abundance of gut microbiota in patients with AN.
Humans ; Gastrointestinal Microbiome/physiology* ; Anorexia Nervosa ; Cross-Sectional Studies ; Dysbiosis/microbiology* ; Body Mass Index ; RNA, Ribosomal, 16S/genetics* ; Feces/microbiology*

The community structure and diversity of the gut microbiota are associated with human diseases. However, the analysis of different community structure might be influenced by experimental approaches such as the quality of DNA extraction. Therefore, evaluating the efficiency of different DNA extraction methods for specific intestinal species is a guideline for obtaining a comprehensive human gut microbial profile, which may assist the in-depth investigation into the structure of the gut microbial community. The aim of this study was to perform a comparative analysis of five different DNA extraction methods. With the aid of qPCR, the efficiency of five DNA extraction kits was evaluated in terms of the purity of the extracted DNA, the DNA concentration, and the abundance of genomic DNA extracted from specific intestinal species. The results showed that the kit Q gave the best extraction results, especially for Gram-positive bacteria such as Lactobacillus and Bifidobacterium. The average DNA concentration of the N kit was lower than that of the Q kit, but there was no significant difference between the two in terms of the purity. Compared to the other three commercial kits (M, PSP, TG), the efficiency of the N kit in extracting the genomic DNA of the specified microorganisms were the least different from those of the Q kit. In contrast, the DNA extracted by the M kit was of higher quality but of lower concentration, and was not very efficient for Gram-positive bacteria. The DNA extracted by the TG and PSP kits was inferior to the other validated kits in terms of the concentration, quality and bacterial abundance. These results provide a basis for the selection of genomic DNA extraction methods in microecological research experiments.
DNA/genetics* ; DNA, Bacterial/genetics* ; Feces/microbiology* ; Humans ; Microbiota/genetics* ; RNA, Ribosomal, 16S/genetics*

Fecal microbiota transplantation (FMT) refers to using the intestinal microorganisms present in the feces or processed feces from healthy people for treating various types of diseases, such as digestive and metabolic diseases. The rapid development of metagenomic and culturomic technologies in gut microbiome analysis provides powerful tools for the FMT research and its clinical applications. Metagenomics technologies comprehensively revealed the diversity and functions of gut microbiota under health and disease conditions, while culturomics technologies helped isolation and identification of "unculturable" bacteria in the human gut under conventional culture conditions. The combination of these two technologies not only enabled us better understand the FMT regularities of cause and effect in clinical practices, but also effectively promoted its applications. Considering the above advantages, this article summarized the applications of metagenomics and culturomics technologies in FMT and prospected its future development trend.
Humans ; Fecal Microbiota Transplantation ; Metagenomics ; Feces/microbiology* ; Gastrointestinal Microbiome ; Bacteria