Gut Microbiome-Based Diagnostic Model to Predict Diabetes Mellitus

The influence of simulated weightlessness on the composition and function of gut microbiota and bile acid metabolism products

The aim of this study was to investigate the effects of simulated weightlessness on gut microbiota, bile acid metabolism, and inflammatory cytokines compared to the control group. The study compared the changes in gut microbiota at the phylum and genus levels in the feces of control and weightlessness rats after 1 and 8 weeks using fecal 16S rRNA sequencing. In the weightlessness group, there was an increase in the proportion of anaerobic bacteria and biofilm-forming bacteria, and a decrease in the proportion of aerobic and Gram-negative bacteria. Further investigations explored the impact of weightlessness on bile acid metabolism products. The levels of glycine ursodeoxycholic acid, glycine chenodeoxycholic acid, glycine deoxycholic acid and glycine cholic acid levels were lower in rats undergoing weightlessness for 1 week compared to the control group.Moreover, the study examined the relationship between gut microbiota and bile acid metabolism products.It was observed that, unlike the control group, there were significant positive correlations between Planctomycetes, Proteobacteria, Synergistetes, and GUDCA levels in rats after 1 week of weightlessness. Finally, ELISA results indicated significant differences in the levels of MDA, GSH, NLRP3, and SIgA inflammatory cytokines between rats undergoing weightlessness for 1 week and the control group rats. Our research confirmed that the simulated weightlessness environment significantly affects the gut microbiota and bile acid metabolism in rats, potentially leading to changes in inflammatory cytokines and causing intestinal tissue inflammation. Further exploring the relationship between gut microbiota and bile acid metabolism under weightless conditions will be crucial for understanding the functional changes in the intestines caused by weightlessness.

Investigation of the hypoglycemic mechanism of the ShenQi compound formula through metabonomics and 16S rRNA sequencing

Introduction: Herbal formulations are renowned for their complex biological activities, acting on multiple targets and pathways, as evidenced by in vitro studies. However, the hypoglycemic effect and underlying mechanisms of Shenqi Compound (SQ), a traditional Chinese herbal formula, remain elusive. This study aimed to elucidate the hypoglycemic effects of SQ and explore its mechanisms of action, focusing on intestinal flora and metabolomics. Methods: A Type 2 diabetes mellitus (T2DM) rat model was established through a high-fat diet, followed by variable glucose and insulin injections to mimic the fluctuating glycemic conditions seen in diabetes. Results: An eight-week regimen of SQ significantly mitigated hyperglycemia, inflammation, and insulin resistance in these rats. Notably, SQ beneficially modulated the gut microbiota by increasing populations of beneficial bacteria, such as Lachnospiraceae_NK4A136_group and Akkermansia, while reducing and inhibiting harmful strains such as Ruminococcus and Phascolarctobacterium. Metabolomics analyses revealed that SQ intervention corrected disturbances in Testosterone enanthate and Glycerophospholipid metabolism. Discussion: Our findings highlight the hypoglycemic potential of SQ and its mechanisms via modulation of the gut microbiota and metabolic pathways, offering a theoretical foundation for the use of herbal medicine in diabetes management.

Enhanced protein-metabolite correlation analysis: To investigate the association between Staphylococcus aureus mastitis and metabolic immune pathways

Mastitis is a disease characterized by congestion, swelling, and inflammation of the mammary gland and usually caused by infection with pathogenic microorganisms. Furthermore, the development of mastitis is closely linked to the exogenous pathway of the gastrointestinal tract. However, the regulatory mechanisms governing the gut-metabolism-mammary axis remain incompletely understood. The present study revealed alterations in the gut microbiota of mastitis rats characterized by an increased abundance of the Proteobacteria phylum. Plasma analysis revealed significantly higher levels of L-isoleucine and cholic acid along with 7-ketodeoxycholic acid. Mammary tissue showed elevated levels of arachidonic acid metabolites and norlithocholic acid. Proteomic analysis showed increased levels of IFIH1, Tnfaip8l2, IRGM, and IRF5 in mastitis rats, which suggests that mastitis triggers an inflammatory response and immune stress. Follistatin (Fst) and progesterone receptor (Pgr) were significantly downregulated, raising the risk of breast cancer. Extracellular matrix (ECM) receptors and focal adhesion signaling pathways were downregulated, while blood-milk barrier integrity was disrupted. Analysis of protein-metabolic network regulation revealed that necroptosis, protein digestion and absorption, and arachidonic acid metabolism were the principal regulatory pathways involved in the development of mastitis. In short, the onset of mastitis leads to changes in the microbiota and alterations in the metabolic profiles of various biological samples, including colonic contents, plasma, and mammary tissue. Key manifestations include disturbances in bile acid metabolism, amino acid metabolism, and arachidonic acid metabolism. At the same time, the integrity of the blood-milk barrier is compromised while inflammation is promoted, thereby reducing cell adhesion in the mammary glands. These findings contribute to a more comprehensive understanding of the metabolic status of mastitis and provide new insights into its impact on the immune system.

Efficacy of fecal microbiota transplantation in type 2 diabetes mellitus: a systematic review and meta-analysis

OBJECTIVE

Type 2 diabetes mellitus (T2DM) is one of the common metabolic diseases worldwide, and studies have found significant differences in the composition and ratio of intestinal flora between patients with T2DM and normal glucose tolerance, and fecal microbiota transplantation (FMT) may modulate the composition of the intestinal microbiota thereby alleviating the hyperglycemic state. We conducted a meta-analysis and systematic review of existing randomized controlled trials (RCTs) to assess the efficacy of FMT in T2DM.

METHODS

We conducted a computer search of PubMed, Embase, The Cochrane Library, and Web of Science to screen randomized controlled trials studies on FMT treatment for T2DM and extracted data from studies that met inclusion criteria. RevMan 5.4 software and Stata 11 software was used for meta-analysis. The indexes of Hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), postprandial blood glucose (PBG), homeostasis model assessment of insulin resistance (HOMA-IR), triglycerides (TG), cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), body mass index (BMI), Aspartate Aminotransferase (AST), Alanine Transaminase (ALT), Systolic blood pressure (SBP) and Diastolic blood pressure (DBP) were mainly evaluated after FMT treatment of T2DM patients, and the changes of intestinal flora were evaluated.

RESULTS

Four RCTs met the inclusion criteria and were included in the meta-analysis. Results of the meta-analysis showed that compared with the non-FMT group, FMT combined treatment could significantly reduce the PBG level in patients with type 2 diabetes (MD = -0.51, 95% CI: -1.42-0.40, P = 0.27). Compared with single FMT treatment, FMT combined treatment could reduce TG levels in patients with type 2 diabetes (MD = -0.60, 95% CI: -1.12~-0.07, P = 0.03). The levels of TG (MD = -0.26, 95% CI: -0.51~-0.02, P = 0.03), HOMA-IR (MD = -2.73, 95% CI: -4.71~0.75, P = 0.007) and HDL (MD = -0.06,95% CI: -0.10~-0.02, P = 0.003) were significantly decreased after treatment in the single FMT group. The level of TC (MD = -0.65, 95% CI: -1.00~-0.31, P = 0.0002) was significantly decreased after FMT combined treatment. Compared with before treatment, ALT (MD = -2.52, 95% CI: -3.86~-1.17, P = 0.0002) and DBP (MD = -2, 95% CI: -3.32~0.68, P = 0.003) levels decreased after treatment in the single FMT group and the FMT combined group. FPG (MD = -0.94, 95% CI: -1.86~-0.02, P = 0.04), TG (MD = -0.73, 95% CI: -1.42~-0.04, P = 0.04) and TC (MD = -0.94, 95% CI: -1.45~-0.43, P = 0.0003) were significantly decreased after combined drug and diet therapy. Secondly, FMT can promote the colonization and growth of donor-related flora in patients with type 2 diabetes.

CONCLUSION

In patients with type 2 diabetes mellitus, FMT treatment can reduce the levels of PBG, TG, HOMA-IR, TC, ALT, and DBP, especially in the combined treatment regimen. In addition, FMT can reshape the intestinal flora and establish the balance of dominant flora.

Predicting the role of the human gut microbiome in type 1 diabetes using machine-learning methods

Gut microbes is a crucial factor in the pathogenesis of type 1 diabetes (T1D). However, it is still unclear which gut microbiota are the key factors affecting T1D and their influence on the development and progression of the disease. To fill these knowledge gaps, we constructed a model to find biomarker from gut microbiota in patients with T1D. We first identified microbial markers using Linear discriminant analysis Effect Size (LEfSe) and random forest (RF) methods. Furthermore, by constructing co-occurrence networks for gut microbes in T1D, we aimed to reveal all gut microbial interactions as well as major beneficial and pathogenic bacteria in healthy populations and type 1 diabetic patients. Finally, PICRUST2 was used to predict Kyoto Encyclopedia of Genes and Genomes (KEGG) functional pathways and KO gene levels of microbial markers to investigate the biological role. Our study revealed that 21 identified microbial genera are important biomarker for T1D. Their AUC values are 0.962 and 0.745 on discovery set and validation set. Functional analysis showed that 10 microbial genera were significantly positively associated with D-arginine and D-ornithine metabolism, spliceosome in transcription, steroid hormone biosynthesis and glycosaminoglycan degradation. These genera were significantly negatively correlated with steroid biosynthesis, cyanoamino acid metabolism and drug metabolism. The other 11 genera displayed an inverse correlation. In summary, our research identified a comprehensive set of T1D gut biomarkers with universal applicability and have revealed the biological consequences of alterations in gut microbiota and their interplay. These findings offer significant prospects for individualized management and treatment of T1D.

Bifidobacteria in disease: from head to toe

Bifidobacteria as a strictly anaerobic gram-positive bacteria, is widely distributed in the intestine, vagina and oral cavity, and is one of the first gut flora to colonize the early stages of life. Intestinal flora is closely related to health, and dysbiosis of intestinal flora, especially Bifidobacteria, has been found in a variety of diseases. Numerous studies have shown that in addition to maintaining intestinal homeostasis, Bifidobacteria may be involved in diseases covering all parts of the body, including the nervous system, respiratory system, genitourinary system and so on. This review collects evidence for the variation of Bifidobacteria in typical diseases among various systems, provides mild and effective therapeutic options for those diseases that are difficult to cure, and moves Bifidobacteria from basic research to further clinical applications.

Faecalibacterium prausnitzii as a potential Antiatherosclerotic microbe

BACKGROUND

The gut microbiota plays a crucial role in coronary artery disease (CAD) development, but limited attention has been given to the role of the microbiota in preventing this disease. This study aimed to identify key biomarkers using metagenomics and untargeted metabolomics and verify their associations with atherosclerosis.

METHODS

A total of 371 participants, including individuals with various CAD types and CAD-free controls, were enrolled. Subsequently, significant markers were identified in the stool samples through gut metagenomic sequencing and untargeted metabolomics. In vivo and in vitro experiments were performed to investigate the mechanisms underlying the association between these markers and atherosclerosis.

RESULTS

Faecal omics sequencing revealed that individuals with a substantial presence of Faecalibacterium prausnitzii had the lowest incidence of CAD across diverse CAD groups and control subjects. A random forest model confirmed the significant relationship between F. prausnitzii and CAD incidence. Notably, F. prausnitzii emerged as a robust, independent CAD predictor. Furthermore, our findings indicated the potential of the gut microbiota and gut metabolites to predict CAD occurrence and progression, potentially impacting amino acid and vitamin metabolism. F. prausnitzii mitigated inflammation and exhibited an antiatherosclerotic effect on ApoE-/- mice after gavage. This effect was attributed to reduced intestinal LPS synthesis and reinforced mechanical and mucosal barriers, leading to decreased plasma LPS levels and an antiatherosclerotic outcome.

CONCLUSIONS

Sequencing of the samples revealed a previously unknown link between specific gut microbiota and atherosclerosis. Treatment with F. prausnitzii may help prevent CAD by inhibiting atherosclerosis.

Bioinformatics analysis of the diversity of gut microbiota and different microbiota on insulin resistance in diabetes mellitus patients

It aimed to explore the diversity of gut microbiota (GM) and the effect of different microbiota on insulin resistance in diabetes mellitus (DM) patients through bioinformatics analysis.

MATERIAL AND METHOD

Microarray data were obtained from GEO database. GM samples from DM patients and healthy controls were collected, and 16S rRNA gene sequencing was carried out adopting high-throughput sequencing technology. The differential expression genes were screened using the Qlucore Omics Explorer 3.0 software. Subsequently, online tools such as STRING and DAVID were utilized for bioinformatics analysis of the differential expression genes. The differences in bacterial diversity between DM patients and healthy controls were evaluated by analyzing the diversity indicators of the microbiota, such as Shannon and Chao1 indexes. Differential abundance and functional prediction analysis were adopted to explore the different microbiota and its possible metabolic pathways between DM patients and controls. And differences in insulin resistance in specific bacterial taxa were analyzed.

RESULT

GM diversity between DM patients and controls had significant differences. GM diversity was lower in DM patients compared with controls, as indicated by a decrease in Shannon and Chao1 indexes. The differential abundance analysis showed that there were multiple different bacterial communities between DM patients and controls, including some bacterial communities at the genus-level. Functional prediction analysis also revealed potential metabolic pathways related to GM and insulin resistance in DM patients. HEXB, ZC3H12A, CCR, CXCR3, GBR10, CDK9, TXN, IGFBP3, PDHA1, and NDUFB3 genes may be potential targets for treatment.

CONCLUSION

There are differences in GM diversity between DM patients and healthy controls, and the different microbiota may be related to the occurrence and development of insulin resistance.

Alterations of the intestinal microbiome and metabolome in women with rheumatoid arthritis

Rheumatoid arthritis (RA) is more common in women, and many reports of sex differences have been reported in various aspects of RA. However, there has been a lack of specific research on women's gut flora. To assess the association between the gut flora and RA patients, this study combined the microbiome with metabolomics. Fecal samples from RA patients and healthy controls were collected for 16S rRNA sequencing. Nontargeted liquid chromatography-mass spectrometry was used to detect metabolites in fecal samples. We comprehensively used various analytical methods to reveal changes in intestinal flora and metabolites in female patients. The gut flora of RA patients was significantly different from that of healthy women. The abundance of Bacteroides, Megamonas and Oscillospira was higher in RA patients, while the abundance of Prevotella, Gemmiger and Roseburia was lower than that of healthy women. Gemmiger, Bilophila and Odoribacter represented large differences in microflora between RA and healthy women and could be used as potential microorganisms in the diagnosis. Fatty acid biosynthesis was significantly different between RA patients and healthy women in terms of metabolic pathways. There were different degrees of correlation between the gut flora and metabolites. Lys-Phe-Lys and heptadecasphin-4-enine can be used as potential markers for RA diagnosis. There was an extremely significant positive correlation between Megamonas, Dialister and rheumatoid factors, which was found for the first time. These findings indicated that alterations of these gut microbiome and metabolome may contribute to the diagnosis and treatment of RA patients.

Immune-mediated hematological disease in dogs is associated with alterations of the fecal microbiota: a pilot study

BACKGROUND

The dog is the most popular companion animal and is a valuable large animal model for several human diseases. Canine immune-mediated hematological diseases, including immune-mediated hemolytic anemia (IMHA) and immune thrombocytopenia (ITP), share many features in common with autoimmune hematological diseases of humans. The gut microbiome has been linked to systemic illness, but few studies have evaluated its association with immune-mediated hematological disease. To address this knowledge gap, 16S rRNA gene sequencing was used to profile the fecal microbiota of dogs with spontaneous IMHA and ITP at presentation and following successful treatment. In total, 21 affected and 13 healthy control dogs were included in the study.

RESULTS

IMHA/ITP is associated with remodeling of fecal microbiota, marked by decreased relative abundance of the spirochete Treponema spp., increased relative abundance of the pathobionts Clostridium septicum and Escherichia coli, and increased overall microbial diversity. Logistic regression analysis demonstrated that Treponema spp. were associated with decreased risk of IMHA/ITP (odds ratio [OR] 0.24-0.34), while Ruminococcaceae UCG-009 and Christensenellaceae R-7 group were associated with increased risk of disease (OR = 6.84 [95% CI 2-32.74] and 8.36 [95% CI 1.85-71.88] respectively).

CONCLUSIONS

This study demonstrates an association of immune-mediated hematological diseases in dogs with fecal dysbiosis, and points to specific bacterial genera as biomarkers of disease. Microbes identified as positive or negative risk factors for IMHA/ITP represent an area for future research as potential targets for new diagnostic assays and/or therapeutic applications.

Impact of dietary interventions on pre-diabetic oral and gut microbiome, metabolites and cytokines

Diabetes and associated comorbidities are a global health threat on the rise. We conducted a six-month dietary intervention in pre-diabetic individuals (NCT03222791), to mitigate the hyperglycemia and enhance metabolic health. The current work explores early diabetes markers in the 200 individuals who completed the trial. We find 166 of 2,803 measured features, including oral and gut microbial species and pathways, serum metabolites and cytokines, show significant change in response to a personalized postprandial glucose-targeting diet or the standard of care Mediterranean diet. These changes include established markers of hyperglycemia as well as novel features that can now be investigated as potential therapeutic targets. Our results indicate the microbiome mediates the effect of diet on glycemic, metabolic and immune measurements, with gut microbiome compositional change explaining 12.25% of serum metabolites variance. Although the gut microbiome displays greater compositional changes compared to the oral microbiome, the oral microbiome demonstrates more changes at the genetic level, with trends dependent on environmental richness and species prevalence in the population. In conclusion, our study shows dietary interventions can affect the microbiome, cardiometabolic profile and immune response of the host, and that these factors are well associated with each other, and can be harnessed for new therapeutic modalities.

Effects of dietary supplementation of Anoectochilus roxburghii extract (ARE) on growth performance, abdominal fat deposition, meat quality, and gut microbiota in broilers

The broiler industry frequently encounters 2 common problems: excessive deposition of abdominal fat and poor quality of meat. However, there are limited nutritional manipulation strategies to address these issues. While Anoectochilus roxburghii (Wall.) Lindl., a traditional Chinese herb, has been shown to have multiple beneficial effects in humans, its potential roles in broiler chickens remain unexplored. In this study, the effects of dietary supplementation with Anoectochilus roxburghii extract (ARE) on growth performance, abdominal fat deposition, meat quality, blood indices, and gut microbiota were investigated in yellow-feather broiler chickens. A total of 90 twenty-one-day-old yellow-feather broilers were randomly divided into 3 treatments, and each treatment included 5 replicates with 6 birds per replicate. Birds were fed a basal diet supplemented with 0, 0.15, or 0.30% ARE for 6 wk. The results showed that the inclusion of ARE in the diet did not have any significant effect on meat yield (P > 0.05). However, it did lead to a reduction in abdominal fat deposition and an improvement in meat quality (P < 0.05). Mechanistically, the addition of ARE inhibited lipid biosynthesis and enhanced lipid breakdown in both the liver and adipose tissue of the broilers. Furthermore, ARE supplementation increased the antioxidase activities in the muscle and serum of the broilers (P < 0.05). In addition, the supplementation of ARE optimized the diversity and composition of the cecal microbiota, particularly by lowering the ratio of Firmicutes to Bacteroidetes (P < 0.05). Moreover, the abundance of some bacteria that were positively correlated with abdominal fat deposition was reduced by ARE, and vice versa (P < 0.05). Collectively, the results suggest that ARE is a promising candidate as a feed additive for reducing abdominal fat deposition and improving meat quality in the broiler industry.

Gut microbiota: The key to the treatment of metabolic syndrome in traditional Chinese medicine - a case study of diabetes and nonalcoholic fatty liver disease

Metabolic syndrome mainly includes obesity, type 2 diabetes (T2DM), alcoholic fatty liver (NAFLD) and cardiovascular diseases. According to the ancient experience philosophy of Yin-Yang, monarch-minister compatibility of traditional Chinese medicine, prescription is given to treat diseases, which has the advantages of small toxic and side effects and quick effect. However, due to the diversity of traditional Chinese medicine ingredients and doubts about the treatment theory of traditional Chinese medicine, the mechanism of traditional Chinese medicine is still in doubt. Gastrointestinal tract is an important part of human environment, and participates in the occurrence and development of diseases. In recent years, more and more TCM researches have made intestinal microbiome a new frontier for understanding and treating diseases. Clinically, nonalcoholic fatty liver disease (NAFLD) and diabetes mellitus (DM) often co-occur. Our aim is to explain the mechanism of interaction between gastrointestinal microbiome and traditional Chinese medicine (TCM) or traditional Chinese medicine formula to treat DM and NAFLD. Traditional Chinese medicine may treat these two diseases by influencing the composition of intestinal microorganisms, regulating the metabolism of intestinal microorganisms and transforming Chinese medicinal compounds.

Gut-microbiome-based predictive model for ST-elevation myocardial infarction in young male patients

BACKGROUND

ST-segment elevation myocardial infarction (STEMI) in young male patients accounts for a significant proportion of total heart attack events. Therefore, clinical awareness and screening for acute myocardial infarction (AMI) in asymptomatic patients at a young age is required. The gut microbiome is potentially involved in the pathogenesis of STEMI. The aim of the current study is to develop an early risk prediction model based on the gut microbiome and clinical parameters for this population.

METHODS

A total of 81 young males (age < 44 years) were enrolled in this study. Forty-one young males with STEMI were included in the case group, and the control group included 40 young non-coronary artery disease (CAD) males. To identify the differences in gut microbiome markers between these two groups, 16S rRNA-based gut microbiome sequencing was performed using the Illumina MiSeq platform. Further, a nomogram and corresponding web page were constructed. The diagnostic efficacy and practicability of the model were analyzed using K-fold cross-validation, calibration curves, and decision curve analysis (DCA).

RESULTS

Compared to the control group, a significant decrease in tendency regarding α and β diversity was observed in patients in the case group and identified as a significantly altered gut microbiome represented by Streptococcus and Prevotella. Regarding clinical parameters, compared to the control group, the patients in the case group had a higher body mass index (BMI), systolic blood pressure (SBP), triglyceride (TG), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) and low blood urea nitrogen (BUN). Additionally, BMI and SBP were significantly (p<0.05) positively correlated with Streptococcus and [Ruminococcus]. Further, BMI and SBP were significantly (p<0.05) negatively correlated with Prevotella and Megasphaera. A significant negative correlation was only observed between Prevotella and AST (p < 0.05). Finally, an early predictive nomogram and corresponding web page were constructed based on the gut microbiome and clinical parameters with an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.877 and a C-index of 0.911. For the internal validation, the stratified K-fold cross-validation (K = 3) was as follows: AUC value of 0.934. The calibration curves of the model showed good consistency between the actual and predicted probabilities. The DCA results showed that the model had a high net clinical benefit for use in the clinical setting.

CONCLUSION

In this study, we combined the gut microbiome and common clinical parameters to construct a prediction model. Our analysis shows that the constructed model is a non-invasive tool with potential clinical application in predicting STEMI in the young males.