The Alteration in Composition and Function of Gut Microbiome in Patients with Type 2 Diabetes

The effect of the administration form of antibiotic therapy on the gut microbiome in patients with infected diabetic foot ulcers - DFIATIM trial

BACKGROUND

Diabetic foot infections (DFIs) contribute to the global disability burden. Beta-lactams are the most commonly used antibiotics for treating DFIs. However, the use of antibiotics may lead to disruption of the healthy balance of the gut microbiota, causing dysbiosis.

METHODS

Patients with infected diabetic foot ulcers (iDFUs) were treated with two kinds of beta-lactams (amoxicillin/clavulanic acid or ceftazidime) according to microbial sensitivity of causative agents via bolus or continuous administration modes. Changes in the gut microbiome of patients were analyzed. Diabetic patients without iDFUs were used as a control group. 16 S ribosomal RNA gene amplicon sequencing was performed on stool samples collected from participants.

RESULTS

Alpha diversity and beta diversity of gut microbiota of treated patients did not show significant differences between bolus and continuous modes. However, significant differences were observed between gut microbiota diversity of treated patients and control group. PCoA plots showed individualized responses of the patient's gut microbiota to antibiotics at different times using both administration forms associated with the pre-treatment state of microbiota composition. Enterococcus, Sellimonas, and Lachnoclostridium were the common bacterial markers differentially abundant in the gut microbiota of antibiotic-treated patients with iDFUs while Roseburia, Dorea, and Monoglobus were mainly abundant in the gut microbiota of patients without iDFUs. Predicted pathways like "Transporters", "ABC transporters" and "Phosphotranspherase system (PTS)" were upregulated in the gut microbiome of patients treated with bolus regime which may lead to increased intestinal barrier permeability.

CONCLUSION

The present study reported alterations in gut microbiota composition and functionality and provided the bacterial markers as well as potential metabolic signatures associated with each administration mode in patients with iDFUs, which may be used as a reference set for future studies of the effect of antibiotics administration on the gut microbiome of patients with iDFUs. This study shed light on the importance of understanding the effect of antibiotic administration form on gut microbiome in patients with iDFUs.

TRIAL REGISTRATION

The DFIATIM Clinical Trial (Full title: "Rationalisation of ATB therapy in diabetic foot infection and its impact on the intestinal microbiota") is submitted to the European Union Clinical Trials Database under the EudraCT Number: 2019-001997-27. The date of registration is July 17th, 2020.

A systematic review on gut microbiota in type 2 diabetes mellitus

Aims/hypothesis

The gut microbiota play crucial roles in the digestion and degradation of nutrients, synthesis of biological agents, development of the immune system, and maintenance of gastrointestinal integrity. Gut dysbiosis is thought to be associated with type 2 diabetes mellitus (T2DM), one of the world's fastest growing diseases. The aim of this systematic review is to identify differences in the composition and diversity of the gut microbiota in individuals with T2DM.

Methods

A systematic search was conducted to identify studies reporting on the difference in gut microbiota composition between individuals with T2DM and healthy controls. Relevant studies were evaluated, and their characteristics and results were extracted using a standardized data extraction form. The studies were assessed for risk of bias and their findings were reported narratively.

Results

58 observational studies published between 2010 and 2024 were included. Beta diversity was commonly reported to be different between individuals with T2DM and healthy individuals. Genera Lactobacillus, Escherichia-Shigella, Enterococcus, Subdoligranulum and Fusobacteria were found to be positively associated; while Akkermansia, Bifidobacterium, Bacteroides, Roseburia, Faecalibacteirum and Prevotella were found to be negatively associated with T2DM.

Conclusions

This systematic review demonstrates a strong association between T2DM and gut dysbiosis, as evidenced by differential microbial abundances and altered diversity indices. Among these taxa, Escherichia-Shigella is consistently associated with T2DM, whereas Faecalibacterium prausnitzii appears to offer a protective effect against T2DM. However, the heterogeneity and observational nature of these studies preclude the establishment of causative relationships. Future research should incorporate age, diet and medication-matched controls, and include functional analysis of these gut microbes.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42023459937.

The influence of alterations in the composition of intestinal microbiota on neurovascular coupling and cognitive dysfunction in individuals afflicted with CSVD

INTRODUCTION

An expanding body of research has explored the crucial role of gut microbiota in cerebral small vessel disease (CSVD). The objective of this study is to investigate alterations in the gut microbiota structure among CSVD patients, to explore the correlation between differential taxonomic levels and the neurovascular coupling index as well as cognitive function and to elucidate the imaging and biomarkers of mild cognitive impairment (MCI) in CSVD.

METHODS

We enrolled 104 patients with CSVD and 40 healthy controls (HC). Based on cognitive test scores, CSVD patients were categorized into a cognitively normal group (CSVD-NCI, n=61) and a mild cognitive impairment group (CSVD-MCI, n=43). Performing magnetic resonance imaging (MRI) scans, gut microbiota analysis, as well as clinical and neuropsychological assessments for all participants. Based on arterial spin labeling (ASL) and blood oxygen level-dependent (BOLD) imaging data, cerebral blood flow (CBF) and neural activity indices are computed. The coupling indices of CBF/mReHo, CBF/mfALFF, CBF/mALFF, and CBF/mDC are calculated to assess the whole-brain neurovascular coupling changes in patients with CSVD.

RESULTS

Species annotation revealed differences in the composition at the phylum and genus levels among the HC, CSVD-NCI, and CSVD-MCI groups. Additionally, differential analysis using the Kruskal-Wallis test demonstrated specific dominant microbial communities in all three groups. The relative abundance of certain dominant microbial communities in CSVD patients exhibited correlations with neurovascular coupling and cognitive function. The combined assessment of Bacteroides genus and CBF/mDC proved effective in distinguishing between CSVD-NCI and CSVD-MCI, providing a novel non-invasive approach for the diagnosis of MCI in CSVD.

Intestinal flora composition and fecal metabolic phenotype in elderly patients with sleep disorders combined with type 2 diabetes

Objectives

This study aimed to determine whether type 2 diabetes (T2D) is an independent risk factor for sleep disorders in the elderly and explore the possible intestinal flora factors of sleep disorders combined with T2D in this population.

Methods

All hospitalized patients with sleep disorders aged ≥65 years between June and November 2023 were retrospectively analyzed, and they were divided into a sleep disorder group (n = 134) and a control group (n = 109). The logistic regression method was utilized to clarify the causal relationship between T2D and sleep disorders. For stool analyses, 42 patients were randomly extracted, which included the control group (n = 14), diabetes group (n = 14), and elderly patients with sleep disorders combined with the T2D group (ESdD) (n = 14). The composition feature of intestinal flora and metabolomics in the ESdD group was described through high-throughput 16S rDNA sequencing and nontargeted analysis based on liquid chromatography-mass spectrometry.

Results

Gender, body mass index (BMI), T2D, intestinal discomfort, and anxiety depression were independent risk factors for sleep disorders in the elderly. Notably, older individuals with T2D were 3.3 times more likely to experience sleep disorders than normal individuals. Compared with the control group, the ESdD group had decreased relative abundance of Barnesiella and Marvinbryantia, with 47 metabolites upregulated and 53 metabolites downregulated. The ESdD group showed a decrease in Lachnospiraceae_UCG_010, with 62 metabolites upregulated and 43 metabolites downregulated, compared with the diabetes group.

Conclusions

Diabetes is an independent risk factor for sleep disorders in the elderly patients. Variations in intestinal flora and metabolism significantly influence the onset and progression of the ESdD group.

Identification of circulating microbial DNA and its association with kidney function in patients with diabetic kidney disease

AIM

Recently, substantial studies have been accumulated to indicate the important role of gut microbiota in diabetic kidney disease (DKD). The abnormal change of bacterial-derived products could imply specific injuries or play beneficial or harmful roles in DKD progression. In this study, we examined the presence and contribution of the Klebsiella oxytoca gene in the circulation of patients with DKD.

METHOD

We enrolled a total of 16 healthy participants, 17 patients with DKD, 5 patients with DKD requiring haemodialysis (HD), and 7 patients with CKD without diabetes. Bacterial-derived DNA (16S rDNA and a specific K. oxytoca gene) in the blood was detected using droplet digital PCR, then investigated the relationship with clinical characteristics.

RESULTS

We identified an increase in K. oxytoca genes in the blood of DKD patients. Interestingly, blood K. oxytoca copies and K. oxytoca/ 16S DNA ratio correlated with higher blood creatinine and BUN levels together with lower eGFR in DKD patients. K. oxytoca levels were also associated with higher neutrophil percentage, lower lymphocyte frequency, and increased neutrophil-to-lymphocyte ratio.

CONCLUSION

Collectively, the presence of the K. oxytoca gene in the circulation could serve as a biomarker reflecting reduced renal function in DKD patients.

Alterations in the Gut Microbiota Composition in Obesity with and without Type 2 Diabetes: A Pilot Study

Purpose

Obesity has become a major public health concern worldwide, increasing the risk of T2DM. Growing evidence indicates gut microbiota dysbiosis is related to metabolic disorders. We aimed to firstly investigate the compositional and functional features of the gut microbiome between obesity with and without T2DM in the Chinese population.

Methods

A total of 32 obese individuals accompanied with T2DM and 18 age and gender-matched obesity with normal glucose tolerance (NGT) were enrolled. Fecal samples were collected, and the gut microbiota profile was determined using the Illumina MiSeq platform based on V3-V4 bacterial 16S rRNA gene.

Results

Compared with obesity- NGT, obesity-T2DM showed a significantly higher alpha diversity. Principal coordinates analysis based on both Bray-Curtis distance and weighted Unifrac revealed that the global microbial composition was significantly different between the two groups (P = 0.007 and P = 0.005, respectively). At the phylum level, Obesity-T2DM patients exhibited a significant decrease in Bacteroidetes, and a pronounced increase in Firmicutes. Regarding the genus level, Bacteroides and Escherichia-Shigella were found to increase considerably, while Prevotella_9 and Sutterella had an evident decrease in Obesity-T2DM. Furthermore, Spearman correlation analysis revealed that Prevotella_9 and Sutterella were negatively associated with HbA1c and fasting blood glucose.

Conclusion

We found clear differences in the gut microbiota composition in obesity-T2DM compared with obesity-NGT. Obesity accompanied with T2DM may aggravate the obesity-associated gut microbiota, and gut microbiota is expected to be a promising novel intervention target for obese management. However, larger sample size and more in-depth taxonomic identification studies are warranted.

Gut microbiome related to metabolic diseases after moderate-to-vigorous intensity exercise

Background objectives

The purpose of this study is to investigate changes in gut microbiota related to metabolic diseases after moderate and high-intensity exercise. A total of 24 participants were divided into three groups: Non-Exercise Group (NEG, n = 8, 28.6 ± 5.3 years, 176.0 ± 7.8 cm, 81.3 ± 14.6 kg), Moderate Intensity Exercise Group (MIEG, n = 8, 26.5 ± 3.3 years, 176.9 ± 5.0 cm, 75.4 ± 9.5 kg), and Vigorous Intensity Exercise Group (VIEG, n = 8, 30.6 ± 5.9 years, 174.2 ± 3.5 cm, 77.8 ± 12.2 kg).

Methods

The participants were selected by assessing physical activity, gut health status, presence of diseases, recent disease diagnoses, and dietary disorders. Those who reported any presence disease or recent disease diagnosis were excluded from the current study. Stool samples were collected after a 10-h fast for gut microbiome analysis. MIEG participants trained at 40-59 % heart rate reserve (HRR) for at least 150 min per week, while VIEG participants trained at ≥ 60 % HRR for at least 90 min per week. After 4 weeks, all participants provided stool samples for gut microbiome analysis.Data analysis was conducted using the Wilcoxon test, with statistical significance set at ≤ 0.05.

Results

The results indicated an increase in Prevotella in MIEG, while Veillonella, Dorea_formicigenerans, and Dorea_longicatena exhibited a decrease (p < 0.05). In VIEG, there was an increase in Bacteroides, Butyricimonas, Odoribacter, and Alistipes (p < 0.05).

Conclusion

These modified microbial groups were associated with factors related to metabolic diseases, including inflammatory bowel disease, obesity, colorectal cancer, diabetes, hypertension, metabolic liver diseases, and ischemic heart diseases. Additional research is essential to delve into the relationship between exercise and these alterations in the microbiome.

Study on the mechanism of modified Gegen Qinlian decoction in regulating the intestinal flora-bile acid-TGR5 axis for the treatment of type 2 diabetes mellitus based on macro genome sequencing and targeted metabonomics integration

BACKGROUND

Currently, there are many drugs available for the treatment of type 2 diabetes mellitus (T2DM), but most of them cause various side effects due to the need for long-term use. As a traditional Chinese medicine, Gegen Qinlian Decoction (GQD) has shown good efficacy and low side effects in the treatment of T2DM in both clinical and basic research. Based on relevant traditional Chinese medicine theories, dried ginger is innovatively added the formula of traditional GQD to create a modified GQD. This modification reduces the side effects of traditional GQD while exerting its therapeutic effect on T2DM. Previous studies have found that the modified GQD can regulate endoplasmic reticulum stress in the liver, inhibit hepatic gluconeogenesis, protect pancreatic islet β cells, and control blood sugar levels by inhibiting the FXR/neuronal ceramide signaling pathway. GQD can also regulate the intestinal microbiota to achieve therapeutic and protective effects in various gastrointestinal diseases. However, there is no research exploring whether the modified GQD achieves its therapeutic mechanism for T2DM by regulating the intestinal microbiota.

PURPOSE

To explore the mechanism of modified GQD in the treatment of T2DM based on multi-omics, focusing on its effect on the "intestinal flora bile acid TGR5'' axis.

METHODS

The T2DM model was established using db/db mice, which were randomly divided into a model group, metformin group, high-dose GQD group, medium-dose GQD group, low-dose GQD group, while m/m mice were used as blank control. The drug intervention lasted for 12 weeks, during which the general conditions, oral glucose tolerance (OGT), blood glucose, and lipid-related indexes were recorded. Additionally, the fasting insulin (FINS), c-peptide, GLP-1 in serum, and cAMP in the ileum were measured by ELISA assay. Furthermore, the composition, abundance, and function of the intestinal microbiota were determined by macro genome sequencing, while bile acid was detected by targeted metabonomics. For histological evaluation, HE staining was used to observe the pathological changes of the ileum and pancreas, and the ultrastructure of the ileum and pancreas was observed by transmission electron microscopy. Apoptosis in the ileum tissue was detected by Tunel staining. Moreover, the mRNA and protein expressions of TGR5, PKA, CREB, PC1/3, GLP-1, and their phosphorylation levels in the ileum were detected by qPCR, immunohistochemistry, and Western blot; The expression of INS in the pancreas was also evaluated using immunohistochemistry. Finally, double immunofluorescence staining was used to detect the co-localization expression of TGR5 and GLP-1, NeuroD1, and GLP-1 in the ileum.

RESULTS

The modified GQD was found to significantly reduce blood glucose, improve oral glucose tolerance, and blood lipid levels, as well as alleviate the injury of the ileum and pancreas in T2DM mice. Furthermore, modified GQD was found to effectively regulate intestinal flora, improve bile acid metabolism, activate the TRG5/cAMP/PKA/CREB signal pathway, and stimulate GLP-1 secretion.

CONCLUSION

GQD can regulate the "intestinal flora-bile acid-TGR5" axis and has a therapeutic effect on T2DM in mice.

Comparison of Glucose Metabolizing Properties of Enterobacterial Probiotic Strains In Vitro

Before the absorption in the intestine, glucose encounters gut bacteria, which may serve as a barrier against hyperglycemia by metabolizing glucose. In the present study, we compared the capacity of enterobacterial strains to lower glucose levels in an in vitro model of nutrient-induced bacterial growth. Two probiotic strains, Hafnia alvei HA4597 (H. alvei) and Escherichia coli (E. coli) Nissle 1917, as well as E. coli K12, were studied. To mimic bacterial growth in the gut, a planktonic culture was supplemented twice daily by the Luria Bertani milieu with or without 0.5% glucose. Repeated nutrient provision resulted in the incremental growth of bacteria. However, in the presence of glucose, the maximal growth of both strains of E. coli but not of H. alvei was inhibited. When glucose was added to the culture medium, a continuous decrease in its concentration was observed during each feeding phase. At its highest density, H. alvei displayed more efficient glucose consumption accompanied by a more pronounced downregulation of glucose transporters' expression than E. coli K12. Thus, the study reveals that the probiotic strain H. alvei HA4597 is more resilient to maintain its growth than E. coli in the presence of 0.5% glucose accompanied by more efficient glucose consumption. This experimental approach offers a new strategy for the identification of probiotics with increased glucose metabolizing capacities potentially useful for the prevention and co-treatment of type 2 diabetes.

Exploring the interplay between antiretroviral therapy and the gut-oral microbiome axis in people living with HIV

The gut and oral microbiome is altered in people living with HIV (PLWH). While antiretroviral treatment (ART) is pivotal in restoring immune function in PLWH, several studies have identified an association between specific antiretrovirals, particularly integrase inhibitors (INSTI), and weight gain. In our study, we explored the differences in the oral and gut microbiota of PLWH under different ART regimens, and its correlation to Body Mass Index (BMI). Fecal and salivary samples were collected from PLWH (n = 69) and healthy controls (HC, n = 80). We performed taxonomy analysis to determine the microbial composition and relationship between microbial abundance and ART regimens, BMI, CD4+T-cell count, CD4/CD8 ratio, and ART duration. PLWH showed significantly lower richness compared to HC in both the oral and gut environment. The gut microbiome composition of INSTI-treated individuals was enriched with Faecalibacterium and Bifidobacterium, whereas non-nucleotide reverse transcriptase inhibitor (NNRTI)-treated individuals were enriched with Gordonibacter, Megasphaera, and Staphylococcus. In the oral microenvironment, Veillonella was significantly more abundant in INSTI-treated individuals and Fusobacterium and Alloprevotella in the NNRTI-treated individuals. Furthermore, Bifidobacterium and Dorea were enriched in gut milieu of PLWH with high BMI. Collectively, our findings identify distinct microbial profiles, which are associated with different ART regimens and BMI in PLWH on successful ART, thereby highlighting significant effects of specific antiretrovirals on the microbiome.

Prevotella copri alleviates hyperglycemia and regulates gut microbiota and metabolic profiles in mice

Prevotella copri is the dominant species of the Prevotella genus in the gut, which is genomically heterogeneous and difficult to isolate; hence, scarce research was carried out for this species. This study aimed to investigate the effect of P. copri on hyperglycemia. Thirty-nine strains were isolated from healthy individuals, and three strains (HF2123, HF1478, and HF2130) that had the highest glucose consumption were selected to evaluate the effects of P. copri supplementation on hyperglycemia. Microbiomics and non-target metabolomics were used to uncover the underlying mechanisms. Oral administration of P. copri in diabetic db/db mice increased the expression and secretion of glucagon-like peptide-1 (GLP-1), significantly improved hyperglycemia, insulin resistance, and lipid accumulation, and alleviated the pathological morphology in the pancreas, liver, and colon. P. copri changed the composition of the gut microbiota of diabetic db/db mice, which was characterized by increasing the ratio of Bacteroidetes to Firmicutes and increasing the relative abundance of genera Bacteroides, Akkermansia, and Faecalibacterium. After intervention with P. copri, fecal metabolic profiling showed that fumaric acid and homocysteine contents decreased, and glutamine contents increased. Furthermore, amino acid metabolism and cAMP/PKA signaling pathways were enriched. Our findings indicate that P. copri improved glucose metabolism abnormalities in diabetic db/db mice. Especially, one of the P. copri strains, HF2130, has shown superior performance in improving hyperglycemia, which may have the potential as a probiotic against hyperglycemia.

IMPORTANCE

As a core member of the human intestinal ecosystem, Prevotelal copri has been associated with glucose metabolic homeostasis in previous studies. However, these results have often been derived from metagenomic studies, and the experimental studies have been based solely on the type of strain DSM 18205T. Therefore, more experimental evidence from additional isolates is needed to validate the results according to their high genomic heterogeneity. In this study, we isolated different branches of strains and demonstrated that P. copri could improve the metabolic profile of hyperglycemic mice by modulating microbial activity. This finding supports the causal contribution of P. copri in host glucose metabolism.

Investigating the causal association between gut microbiota and type 2 diabetes: a meta-analysis and Mendelian randomization

Background

Studies have shown that gut dysbiosis contributes to the pathophysiology of type 2 diabetes mellitus (T2DM). Identifying specific gut microbiota dysbiosis may provide insight into the pathogenesis of T2DM.

Purpose

This study investigated the causal relationship between gut microbiota and T2DM using meta-analysis and Mendelian randomization (MR).

Methods

In the first part, we searched for literature on gut microbiota and T2DM, and conducted a meta-analysis. We observed differences in glycosylated hemoglobin and fasting blood glucose levels in both groups. Second, we obtained GWAS data from genome-wide association study database 19 (GWAS). We used two-sample MR analysis to verify the forward and reverse causal associations between gut microbiota and T2DM. Additionally, we selected the European GWAS data from the European Bioinformatics Institute (EBI) as a validation set for external validation of the MR analysis. In the third part, we aimed to clarify which gut microbiota contribute to the degree of causal association between group disorders and T2DM through multivariate MR analysis and Bayesian model averaging (MR-BMA).

Results

1. According to the meta-analysis results, the glycated hemoglobin concentration in the gut probiotic intervention group was significantly lower than in the control group. Following treatment, fasting blood glucose levels in the intervention group were significantly lower than those in the control group. 2. The results of two samples MR analysis revealed that there were causal relationships between six gut microbiota and T2DM. Genus Haemophilus and order Pasteurellaceae were negatively correlated with T2DM. Genus Actinomycetes, class Melanobacteria and genus Lactobacillus were positively correlated. Reverse MR analysis demonstrated that T2DM and gut microbiota did not have any reverse causal relationship. The external validation data set showed a causal relationship between gut microbiota and T2DM. 3. Multivariate MR analysis and MR-BMA results showed that the independent genus Haemophilus collection had the largest PP.

Conclusion

Our research results suggest that gut microbiota is closely related to T2DM pathogenesis. The results of further MR research and an analysis of the prediction model indicate that a variety of gut microbiota disorders, including genus Haemophilus, are causally related to the development of T2DM. The findings of this study may provide some insight into the diagnosis and treatment of T2DM.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO.

Quercetin Alleviates Insulin Resistance and Repairs Intestinal Barrier in db/db Mice by Modulating Gut Microbiota

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease which seriously affects public health. Gut microbiota remains a dynamic balance state in healthy individuals, and its disorder may affect health status and even results in metabolic diseases. Quercetin, a natural flavonoid, has been shown to have biological activities that can be used in the prevention and treatment of metabolic diseases. This study aimed to explore the mechanism of quercetin in alleviating T2DM based on gut microbiota. db/db mice were adopted as the model for T2DM in this study. After 10 weeks of administration, quercetin could significantly decrease the levels of body weight, fasting blood glucose (FBG), serum insulin (INS), the homeostasis model assessment of insulin resistance (HOMA-IR), monocyte chemoattractant protein-1 (MCP-1), D-lactic acid (D-LA), and lipopolysaccharide (LPS) in db/db mice. 16S rRNA gene sequencing and untargeted metabolomics analysis were performed to compare the differences of gut microbiota and metabolites among the groups. The results demonstrated that quercetin decreased the abundance of Proteobacteria, Bacteroides, Escherichia-Shigella and Escherichia_coli. Moreover, metabolomics analysis showed that the levels of L-Dopa and S-Adenosyl-L-methionine (SAM) were significantly increased, but 3-Methoxytyramine (3-MET), L-Aspartic acid, L-Glutamic acid, and Androstenedione were significantly decreased under quercetin intervention. Taken together, quercetin could exert its hypoglycemic effect, alleviate insulin resistance, repair the intestinal barrier, remodel the intestinal microbiota, and alter the metabolites of db/db mice.

Enteric neuropathy in diabetes: Implications for gastrointestinal function

Diabetes, commonly known for its metabolic effects, also critically affects the enteric nervous system (ENS), which is essential in regulating gastrointestinal (GI) motility, secretion, and absorption. The development of diabetes-induced enteric neuropathy can lead to various GI dysfunctions, such as gastroparesis and irregular bowel habits, primarily due to disruptions in the function of neuronal and glial cells within the ENS, as well as oxidative stress and inflammation. This editorial explores the pathophysiological mechanisms underlying the development of enteric neuropathy in diabetic patients. Additionally, it discusses the latest advances in diagnostic approaches, emphasizing the need for early detection and intervention to mitigate GI complications in diabetic individuals. The editorial also reviews current and emerging therapeutic strategies, focusing on pharmacological treatments, dietary management, and potential neuromodulatory interventions. Ultimately, this editorial highlights the necessity of a multidisciplinary approach in managing enteric neuropathy in diabetes, aiming to enhance patient quality of life and address a frequently overlooked complication of this widespread disease.

Causal relationship between T2DM microvascular complications and gut microbiota: a Mendelian randomization study

Background

Gowing number of studies have demonstrated the association between gut microbiome and T2DM microvascular complications, however the causal relationship remains unclear. Therefore, we using the Mendelian randomization (MR) approach to investigate this causal relation.

Methods

Using gut microbiome data from the International MiBioGen Consortium genome-wide association study (GWAS) and T2DM microvascular complications data from the FinnGen Consortium GWAS to perform MR analyses. Single nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs), the inverse variance weighting (IVW) method was used as the primary analysis method, and the results were tested for heterogeneity and horizontal pleiotropy.

Results

Our research identified that there are 5 known microbial species and 2 unknown microbial species in the gut microbiome that were causally related to T2DM retinopathy. Besides, three and seven known microbial species causal relationships between the gut microbiome and T2DM neuropathy and T2DM nephropathy, respectively.

Conclusions

Using MR methods, we demonstrated the causal relationship between gut microbiome and microvascular complications in T2DM, providing a new strategy for the prevention and treatment of it.

Phyllostachys nigra (Lodd. ex Lindl.) derived polysaccharide with enhanced glycolipid metabolism regulation and mice gut microbiome

This study focuses on the characterization and regulation of glycolipid metabolism of polysaccharides derived from biomass of Phyllostachys nigra (Lodd. ex Lindl.) root (PNr). The extracts from dilute hydrochloric acid, hot water, and 2 % sodium hydroxide solution were characterized through molecular weight, gel permeation chromatography, monosaccharides, Fourier transform infrared, and nuclear magnetic resonance spectroscopy analyses. Polysaccharide from alkali extraction and molecular sieve purification (named as: PNS2A) exhibited optimal inhibitory of 3T3-L1 cellular differentiation and lowered insulin resistance. The PNS2A is made of a hemicellulose-like main chain of →4)-β-D-Xylp-(1→ that was connected by branches of 4-O-Me-α-GlcAp-(1→, T-α-D-Galp-(1→, T-α-L-Araf-(1→, →2)-α-L-Araf-(1→, as well as β-D-Glcp-(1→4-β-D-Glcp-(1→ fragments. Oral delivery of PNS2A in diabetes mice brought down blood glucose and cholesterol levels and regulated glucose and lipid metabolism. PNS2A alleviated diabetes symptoms and body weight and protected liver and kidney function in model animals by altering the gut microbiome. Polysaccharides can be a new approach to develop bamboo resources.

Effects of in vitro fermentation of Atractylodes chinensis (DC.) Koidz. polysaccharide on fecal microbiota and metabolites in patients with type 2 diabetes mellitus

Atractylodes chinensis (DC.) Koidz. polysaccharide (AKP) has been shown to have hypoglycemic activity. In this study, the effects of AKP on fecal microbiota and metabolites in healthy subjects and patients with type 2 diabetes mellitus (T2DM) were investigated using an in vitro simulated digestive fermentation model. AKP were isolated and purified from Atractylodes chinensis (DC.) Koidz. Its main component AKP1 (AKP-0 M, about 78 % of AKP) has an average molecular weight of 3.25 kDa with monosaccharide composition of rhamnose, arabinose, and galactosamine in a molar ratio of 1: 1.25: 2.88. Notably, AKP fermentation might improve the intestinal microbiota of T2DM patients by the enrichment of some specific bacteria rather than the increase of microbial diversity. The addition of AKP specifically enriched Bifidobacteriaceae and weakened the proportion of Escherichia-Shigella. Moreover, AKP also increased the levels of short-chain fatty acids without affecting total gut gas production, suggesting that AKP could have beneficial effects while avoiding flatulence. Metabolomic analysis revealed that ARP fermentation caused changes in some metabolites, which were mainly related to energy metabolism and amino acid metabolism. Importantly, ARP fermentation significantly increased the level of myo-inositol, an insulin sensitizer. In addition, a significant correlation was observed between specific microbiota and differential metabolites. This study has laid a theoretical foundation for AKP application in functional foods.

Camel milk peptides alleviate hyperglycemia by regulating gut microbiota and metabolites in type 2 diabetic mice

This study aimed to investigate the hypoglycemic effect of Camel milk peptides (CMPs) on Type 2 diabetes mellitus (T2DM) mice and reveal its related mechanism from the aspect of gut microbiota and metabolites. The administering CMPs significantly alleviated the weight loss, polydipsia and polyphagia, reduced fasting blood glucose (FBG), improved insulin resistance and sensitivity, and restored the level of serum hormones, lipopolysaccharide (LPS), lipid metabolic and tissue damage. Furthermore, CMPs intervention remarkably reversed gut microbiota dysbiosis in T2DM mice by reducing the relative abundance of Proteobacteria, Allobaculum, Clostridium, Shigella and the Firmicutes/Bacteroidetes ratio, while increasing the relative abundance of Bacteroidetes and Blautia. Metabolomic analysis identified 84 different metabolites between T2DM and CMPs-treated groups, participating in three pathways of Pantothenate and CoA biosynthesis, Phenylalanine metabolism and Linoleic acid metabolism. Ureidopropionic acid, pantothenic acid, hippuric acid, hydrocinnamic acid and linoleic acid were identified as key acidic metabolites closely related to hypoglycemic effect. Correlation analysis indicated that CMPs might have a hypoglycemic effect through their impact on gut microbiota, leading to variations in short-chain fatty acids (SCFAs), acidic metabolites and metabolic pathways. These findings suggest that CMPs could be a beneficial nutritional supplement for intervention T2DM.

Angelica polysaccharides relieve blood glucose levels in diabetic KKAy mice possibly by modulating gut microbiota: an integrated gut microbiota and metabolism analysis

BACKGROUND

Angelica polysaccharides (AP) have numerous benefits in relieving type 2 diabetes (T2D). However, the underlying mechanisms have yet to be fully understood. Recent many reports have suggested that altering gut microbiota can have adverse effects on the host metabolism and contribute to the development of T2D. Here, we successfully established the T2D model using the male KKAy mice with high-fat and high-sugar feed. Meanwhile, the male C57BL/6 mice were fed with a normal feed. T2D KKAy mice were fed either with or without AP supplementation. In each group, we measured the mice's fasting blood glucose, weight, and fasting serum insulin levels. We collected the cecum content of mice, the gut microbiota was analyzed by targeted full-length 16S rRNA metagenomic sequencing and metabolites were analyzed by untargeted-metabolomics.

RESULTS

We found AP effectively alleviated glycemic disorders of T2D KKAy mice, with the changes in gut microbiota composition and function. Many bacteria species and metabolites were markedly changed in T2D KKAy mice and reversed by AP. Additionally, 16 altered metabolic pathways affected by AP were figured out by combining metagenomic pathway enrichment analysis and metabolic pathway enrichment analysis. The key metabolites in 16 metabolic pathways were significantly associated with the gut microbial alteration. Together, our findings showed that AP supplementation could attenuate the diabetic phenotype. Significant gut microbiota and gut metabolite changes were observed in the T2D KKAy mice and AP intervention.

CONCLUSIONS

Administration of AP has been shown to improve the composition of intestinal microbiota in T2D KKAy mice, thus providing further evidence for the potential therapeutic application of AP in the treatment of T2D.

From-Toilet-to-Freezer: A Review on Requirements for an Automatic Protocol to Collect and Store Human Fecal Samples for Research Purposes

The composition, viability and metabolic functionality of intestinal microbiota play an important role in human health and disease. Studies on intestinal microbiota are often based on fecal samples, because these can be sampled in a non-invasive way, although procedures for sampling, processing and storage vary. This review presents factors to consider when developing an automated protocol for sampling, processing and storing fecal samples: donor inclusion criteria, urine-feces separation in smart toilets, homogenization, aliquoting, usage or type of buffer to dissolve and store fecal material, temperature and time for processing and storage and quality control. The lack of standardization and low-throughput of state-of-the-art fecal collection procedures promote a more automated protocol. Based on this review, an automated protocol is proposed. Fecal samples should be collected and immediately processed under anaerobic conditions at either room temperature (RT) for a maximum of 4 h or at 4 °C for no more than 24 h. Upon homogenization, preferably in the absence of added solvent to allow addition of a buffer of choice at a later stage, aliquots obtained should be stored at either -20 °C for up to a few months or -80 °C for a longer period-up to 2 years. Protocols for quality control should characterize microbial composition and viability as well as metabolic functionality.

Causal relationship between kidney stones and gut microbiota contributes to the gut-kidney axis: a two-sample Mendelian randomization study

Background

Gut microbiota, particularly Oxalobacter formigenes, has been previously reported to be associated with kidney stones. However, the conflicting results from both observational and intervention studies have created substantial uncertainty regarding the contribution of Oxalobacter formigenes to the formation of kidney stone.

Methods

We employed a two-sample MR analysis to investigate the causal relationship between gut microbiota and kidney stones using GWASs summary statistics obtained from the MiBioGen and FinnGen consortia. Moreover, we conducted a reserve MR analysis to assess the direction of the causal associations between gut microbiota and kidney stones. The inverse variance weighted (IVW) approach represents the primary method of Mendelian Randomization (MR) analysis.

Results

Our analyses do not yield supportive evidence for a causal link between the genus Oxalobacter (OR = 0.99, 95% CI: 0.90-1.09, p = 0.811) and the formation of kidney stones. The order Actinomycetales (OR = 0.79, 95% CI: 0.65-0.96, p = 0.020), family Actinomycetaceae (OR = 0.79, 95% CI: 0.65-0.96, p = 0.019), family Clostridiaceae 1 (OR = 0.80, 95% CI: 0.67-0.96, p = 0.015), genus Clostridiumsensustricto 1 (OR = 0.81, 95% CI: 0.67-0.98, p = 0.030) and genus Hungatella (OR = 0.86, 95% CI: 0.74-0.99, p = 0.040) had protective effects on kidney stones, and the genus Haemophilus (OR = 1.16, 95% CI: 1.01-1.33, p = 0.032), genus Ruminococcaceae (UCG010) (OR = 1.38, 95% CI: 1.04-1.84, p = 0.028), genus Subdoligranulum (OR = 1.27, 95% CI: 1.06-1.52, p = 0.009) were risk factors for kidney stones. Differential abundance analysis provide no evidence of a association between Oxalobacter formigenes and kidney stones, and showed genus Subdoligranulum were risk factors for kidney stones. Reverse MR analysis did not indicate any causal association of kidney stones on gut microbiota. No considerable heterogeneity of instrumental variables or horizontal pleiotropy was observed.

Conclusion

Our two-sample MR study did not find any causal relationship between genus Oxalobacter and kidney stones. The association between gut microbiota and kidney stones does not solely depend on the presence of genus Oxalobacter/Oxalobacter formigenes. A more integrated approach using multiple omics platforms is needed to better understand the pathogenesis of kidney stones in the context of complex gene-environment interactions over time.

Damp-heat constitution influences gut microbiota and urine metabolism of Chinese infants

Background

As an increasingly popular complementary and alternative approach for early detection and treatment of disease, traditional Chinese medicine constitution (TCMC) divides human beings into those with balanced constitution (BC) and unbalanced constitution, where damp-heat constitution (DHC) is one of the most unbalanced constitutions. Many studies have been carried out on the microscopic mechanism of constitution classification; however, most of these studies were conducted in adults and rarely in infants. Many diseases are closely related to intestinal microbiota, and metabolites produced by the interaction between microbiota and the body may impact constitution classification. Herein, we investigated the overall constitution distribution in Chinese infants, and analyzed the profiles of gut microbiota and urine metabolites of DHC to further promote the understanding of infants constitution classification.

Methods

General information was collected and TCMC was evaluated by Constitutional Medicine Questionnaires. 1315 questionnaires were received in a cross-sectional study to investigate the constitution composition in Chinese infants. A total of 56 infants, including 30 DHC and 26 BC, were randomly selected to analyze gut microbiota by 16S rRNA sequencing and urine metabolites by UPLC-Q-TOF/MS method.

Results

BC was the most common constitution in Chinese infants, DHC was the second common constitution. The gut microbiota and urine metabolites in the DHC group showed different composition compared to the BC group. Four differential genera and twenty differential metabolites were identified. In addition, the combined marker composed of four metabolites may have the high potential to discriminate DHC from BC with an AUC of 0.765.

Conclusions

The study revealed the systematic differences in the gut microbiota and urine metabolites between infants with DHC and BC. Moreover, the differential microbiota and metabolites may offer objective evidences for constitution classification.

Gut microbiome in PCOS associates to serum metabolomics: a cross-sectional study

The association between gut microbiome and chronic metabolic disease including polycystic ovary syndrome (PCOS), is well documented, however, the relationship between the gut microbiota and serum metabolites remains unknown. In this study, untargeted metabolomics together with a 16S rRNA gene sequencing tool was used to detect small molecule serum metabolites and the gut microbiome. We identified 15 differential metabolites between PCOS patients and the healthy control. Lysophosphatidylcholine (LPC) (18:2, 20:3, 18:1, P-16:0, 17:0, 15:0, 18:3, 20:4), phosphatidylcholine(PC), ganglioside GA2 (d18:1/16:0) and 1-linoleoylglycerophosphocholine were increased in the PCOS group, and the concentrations of phosphoniodidous acid, bilirubin, nicotinate beta-D-ribonucleotide and citric acid were decreased in the PCOS group, suggesting a lipid metabolism and energy metabolism disorder in the PCOS patients. The diversity of gut microbiota in PCOS group was lower than that in healthy controls. Escherichia/Shigella, Alistipes and an unnamed strain 0319_6G20 belonging to Proteobacteria were important distinguishing genera (LDA > 3.5) in PCOS. Prevotella_9 was positively correlated with phosphoniodidous acid, nicotinate beta-D-ribonucleotide and citric acid concentrations, and negatively correlated with the concentration of LPC (20:3) and 1-linoleoylglycerophosphocholine; Roseburia was negatively correlated with LPC concentration (20:4), while the characteristic genus 0319_6G20 of PCOS was positively correlated with LPC concentration (20:3) (COR > 0.45). SF-36 in the PCOS group was significantly lower than that in the healthy control (HC) group, which was associated with the presence of Escherichia-Shigella and Alistipes. Our finding demonstrated the correlation between the gut microbiota and serum metabolites in PCOS, and therefore characteristic gut microbiota and metabolites may play an important role in the insulin resistance and the mood changes of PCOS patients.

The harmful intestinal microbial community accumulates during DKD exacerbation and microbiome-metabolome combined validation in a mouse model

OBJECTIVE

Diabetic kidney disease (DKD) is one of the most prevalent complications of diabetes mellitus (DM) and is associated with gut microbial dysbiosis. We aim to build a diagnostic model to aid clinical practice and uncover a crucial harmful microbial community that contributes to DKD pathogenesis and exacerbation.

DESIGN

A total of 528 fecal samples from 180 DKD patients and 348 non-DKD populations (138 DM and 210 healthy volunteers) from the First Affiliated Hospital of Zhengzhou University were recruited and randomly divided into a discovery phase and a validation phase. The gut microbial composition was compared using 16S rRNA sequencing. Then, the 180 DKD patients were stratified into four groups based on clinical stages and underwent gut microbiota analysis. We established DKD mouse models and a healthy fecal microbiota transplantation (FMT) model to validate the effects of gut microbiota on DKD and select the potential harmful microbial community. Untargeted metabolome-microbiome combined analysis of mouse models helps decipher the pathogenetic mechanism from a metabolic perspective.

RESULTS

The diversity of the gut microbiome was significantly decreased in DKD patients when compared with that of the non-DKD population and was increased in the patients with more advanced DKD stages. The DKD severity in mice was relieved after healthy gut microbiota reconstruction. The common harmful microbial community was accumulated in the subjects with more severe DKD phenotypes (i.e., DKD and DKD5 patients and DKD mice). The harmful microbial community was positively associated with the serum injurious metabolites (e.g., cholic acid and hippuric acid).

CONCLUSION

The fecal microbial community was altered markedly in DKD. Combining the fecal analysis of both human and animal models selected the accumulated harmful pathogens. Partially recovering healthy gut microbiota can relieve DKD phenotypes via influencing pathogens' effect on DKD mice's metabolism.

Characterization and diagnostic value of the gut microbial composition in patients with minimal change disease

Background: Minimal change disease (MCD) is one of the most common causes of primary nephrotic syndrome with high morbidity. This study aimed to explore the typical alterations of gut microbiota in MCD and establish a non-invasive classifier using key gut microbiome. We also aimed to evaluate the therapeutic efficiency of gut microbiota intervention in MCD through animal experiments. Methods: A total of 222 stool samples were collected from MCD patients and healthy controls at the First Affiliated Hospital of Zhengzhou University and Shandong Provincial Hospital for 16S rRNA sequencing. Optimum operational taxonomic units (OTUs) were obtained for constructing a diagnostic model. MCD rat models were established using doxorubicin hydrochloride for exploring the therapeutic efficiency of gut microbial intervention through fecal microbiota transplantation (FMT). Results: The α-diversity of gut microbiota decreased in MCD patients when compared with healthy controls. The relative abundance of bacterial species also changed significantly. We constructed a diagnostic model based on eight optimal OTUs and it achieved efficiency of 97.81% in discovery cohort. The high efficiency of diagnostic model was also validated in the patients with different disease states and cross-regional cohorts. The treatment partially recovered the gut microbial dysbiosis in patients with MCD. In animal experiments, likewise, the gut microbiota changed sharply in MCD rats. However, gut microbial interventions did not reduce urinary protein or pathological kidney damage. Conclusion: Gut Microbiota shifts sharply in both patients and rats with MCD. Typical microbial changes can be used as biomarkers for MCD diagnosis. The gut microbiota compositions in patients with MCD tended to normalize after treatment. However, the intervention of gut microbiota seems to have no therapeutic effect on MCD.

The human microbiome in disease and pathology

This narrative review seeks to examine the relationships between bacterial microbiomes and infectious disease. This is achieved by detailing how different human host microbiomes develop and function, from the earliest infant acquisitions of maternal and environmental species through to the full development of microbiomes by adulthood. Communication between bacterial species or communities of species within and outside of the microbiome is a factor in both maintenance of homeostasis and management of threats from the external environment. Dysbiosis of this homeostasis is key to understanding the development of disease states. Several microbiomes and the microbiota within are used as prime examples of how changes in species composition, particularly at the phylum level, leads to such diverse conditions as inflammatory bowel disease (IBD), type 2 diabetes, psoriasis, Parkinson's disease, reflux oesophagitis and others. The review examines spatial relationships between microbiomes to understand how dysbiosis in the gut microbiome in particular can influence diseases in distant host sites via routes such as the gut-lung, gut-skin and gut-brain axes. Microbiome interaction with host processes such as adaptive immunity is increasingly identified as critical to developing the capacity of the immune system to react to pathogens. Dysbiosis of essential bacteria involved in modification of host substrates such as bile acid components can result in development of Crohn's disease, small intestine bacterial overgrowth, hepatic cancer and obesity. Interactions between microbiomes in distantly located sites are being increasingly being identified, resulting in a 'whole of body' effect by the combined host microbiome.

Gut Microbiome Analysis Can Be Used as a Noninvasive Diagnostic Tool and Plays an Essential Role in the Onset of Membranous Nephropathy

Membranous nephropathy (MN) is a common cause of nephrotic syndrome. The aim is to establish a non-invasive diagnostic model of MN using differential gut microbiome analysis, and to explore the relationship between the gut microbiome and MN pathogenesis in vivo. 825 fecal samples from MN patients and healthy participants are collected from multiple medical centers across China. Key operational taxonomic units (OTUs) obtained through 16S rRNA sequencing are used to establish a diagnostic model. A rat model of MN is developed to explore the relationship between the gut microbiome and the pathogenesis of MN. The diversity and richness of the gut microbiome are significantly lower in patients with MN than in healthy individuals. The diagnostic model based on seven OTUs achieves an excellent efficiency of 98.36% in the training group and also achieves high efficiency in cross-regional cohorts. In MN rat model, gut microbiome elimination prevents model establishment, but fecal microbiome transplantation restores the phenotype of protein urine. Gut microbiome analysis can be used as a non-invasive tool for MN diagnosis. The onset of MN depends on the presence of naturally colonized microbiome. Early intervention in the gut microbiome may help reduce urinary protein level in MN.

The Biotics Family: Current Knowledge and Future Perspectives in Metabolic Diseases

Globally, metabolic diseases such as obesity, type 2 diabetes mellitus and non-alcoholic fatty liver disease pose a major public health threat. Many studies have confirmed the causal relationship between risk factors and the etiopathogenesis of these diseases. Despite this, traditional therapeutic management methods such as physical education and diet have proven insufficient. Recently, researchers have focused on other potential pathways for explaining the pathophysiological variability of metabolic diseases, such as the involvement of the intestinal microbiota. An understanding of the relationship between the microbiome and metabolic diseases is a first step towards developing future therapeutic strategies. Currently, much attention is given to the use of biotics family members such as prebiotics (lactolose, soy oligosaccharides, galactooligosaccharides, xylooligosaccharides or inulin) and probiotics (genera Lactobacillus, Bifidobacterium, Lactococcus, Streptococcus or Enterococcus). They can be used both separately and together as synbiotics. Due to their direct influence on the composition of the intestinal microbiota, they have shown favorable results in the evolution of metabolic diseases. The expansion of the research area in the biotics family has led to the discovery of new members, like postbiotics. In the age of personalized medicine, their use as therapeutic options is of great interest to our study.

Insights of Host Physiological Parameters and Gut Microbiome of Indian Type 2 Diabetic Patients Visualized via Metagenomics and Machine Learning Approaches

Type 2 diabetes (T2D) is a serious public health issue and may also contribute to modification in the structure of the intestinal microbiota, implying a link between T2D and microbial inhabitants in the digestive tract. This work aimed to develop efficient models for identifying essential physiological markers for improved T2D classification using machine learning algorithms. Using amplicon metagenomic approaches, an effort has also been made to understand the alterations in core gut microbial members in Indian T2D patients with respect to their control normal glucose tolerance (NGT). Our data indicate the level of fasting blood glucose (FBG) and glycated hemoglobin (HbA1c) were the most useful physiological indicators while random forest and support vector machine with RBF Kernel were effective predictions models for identifications of T2D. The dominating gut microbial members Allopreotella, Rikenellaceae RC9 gut group, Haemophilus, Ruminococcus torques group, etc. in Indian T2D patients showed a strong association with both FBG and HbA1c. These members have been reported to have a crucial role in gut barrier breakdown, blood glucose, and lipopolysaccharide level escalation, or as biomarkers. While the dominant NGT microbiota (Akkermansia, Ligilactobacillus, Enterobacter, etc.) in the colon has been shown to influence inflammatory immune responses by acting as an anti-inflammatory agent and maintaining the gut barrier. The topology study of co-occurrence network analysis indicates that changes in network complexity in T2D lead to variations in the different gut microbial members compared to NGT. These studies provide a better understanding of the gut microbial diversity in Indian T2D patients and show the way for the development of valuable diagnostics strategies to improve the prediction and modulation of the T2D along with already established methods.

The Specific Alteration of Gut Microbiota in Diabetic Kidney Diseases—A Systematic Review and Meta-Analysis

Background

Emerging evidence indicates that gut dysbiosis is involved in the occurrence and development of diabetic kidney diseases (DKD). However, the key microbial taxa closely related to DKD have not been determined.

Methods

PubMed, Web of Science, Cochrane, Chinese Biomedical Databases, China National Knowledge Internet, and Embase were searched for case-control or cross-sectional studies comparing the gut microbiota of patients with DKD and healthy controls (HC) from inception to February 8, 2022, and random/fixed-effects meta-analysis on the standardized mean difference (SMD) were performed for alpha diversity indexes between DKD and HC, and beta diversity indexes and the relative abundance of gut microbiota were extracted and summarized qualitatively.

Results

A total of 16 studies (578 patients with DKD and 444 HC) were included. Compared to HC, the bacterial richness of patients with DKD was significantly decreased, and the diversity indexes were decreased but not statistically, companying with a distinct beta diversity. The relative abundance of phylum Proteobacteria, Actinobacteria, and Bacteroidetes, family Coriobacteriaceae, Enterobacteriaceae, and Veillonellaceae, genus Enterococcus, Citrobacter, Escherichia, Klebsiella, Akkermansia, Sutterella, and Acinetobacter, and species E. coli were enriched while that of phylum Firmicutes, family Lachnospiraceae, genus Roseburia, Prevotella, and Bifidobacterium were depleted in patients with DKD.

Conclusions

The gut microbiota of patients with DKD may possess specific features characterized by expansion of genus Escherichia, Citrobacter, and Klebsiella, and depletion of Roseburia, which may contribute most to the alterations of their corresponding family and phylum taxa, as well as the bacterial diversity and composition. These microbial taxa may be closely related to DKD and serve as promising targets for the management of DKD.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42021289863.

Application of machine learning tools: Potential and useful approach for the prediction of type 2 diabetes mellitus based on the gut microbiome profile

The gut microbiota plays an important role in the regulation of the immune system and the metabolism of the host. The aim of the present study was to characterize the gut microbiota of patients with type 2 diabetes mellitus (T2DM). A total of 118 participants with newly diagnosed T2DM and 89 control subjects were recruited in the present study; six clinical parameters were collected and the quantity of 10 different types of bacteria was assessed in the fecal samples using quantitative PCR. Taking into consideration the six clinical variables and the quantity of the 10 different bacteria, 3 predictive models were established in the training set and test set, and evaluated using a confusion matrix, area under the receiver operating characteristic curve (AUC) values, sensitivity (recall), specificity, accuracy, positive predictive value and negative predictive value (npv). The abundance of Bacteroides, Eubacterium rectale and Roseburia inulinivorans was significantly lower in the T2DM group compared with the control group. However, the abundance of Enterococcus was significantly higher in the T2DM group compared with the control group. In addition, Faecalibacterium prausnitzii, Enterococcus and Roseburia inulinivorans were significantly associated with sex status while Bacteroides, Bifidobacterium, Enterococcus and Roseburia inulinivorans were significantly associated with older age. In the training set, among the three models, support vector machine (SVM) and XGboost models obtained AUC values of 0.72 and 0.70, respectively. In the test set, only SVM obtained an AUC value of 0.77, and the precision and specificity were both above 0.77, whereas the accuracy, recall and npv were above 0.60. Furthermore, Bifidobacterium, age and Roseburia inulinivorans played pivotal roles in the model. In conclusion, the SVM model exhibited the highest overall predictive power, thus the combined use of machine learning tools with gut microbiome profiling may be a promising approach for improving early prediction of T2DM in the near feature.

Pharmacomicrobiomics in Western Medicine and Traditional Chinese Medicine in Type 2 Diabetes

Pharmacomicrobiomics refers to the interactions between foreign compounds and the gut microbiome resulting in heterogeneous efficacy, side effects, and toxicity of the compound concerned. Glucose lowering drugs reduce blood glucose by modulating insulin secretion and its actions as well as redistributing energy disposal. Apart from genetic, ecological, and lifestyle factors, maintaining an equilibrium of the whole gut microbiome has been shown to improve human health. Microbial fingerprinting using faecal samples indicated an 'invisible phenotype' due to different compositions of microbiota which might orchestrate the interactions between patients' phenotypes and their responses to glucose-lowering drugs. In this article, we summarize the current evidence on differences in composition of gut microbiota between individuals with type 2 diabetes (T2D) and healthy individuals, the disruption of the balance of beneficial and pathogenic microbiota was shown in patients with T2D and how Western Medicine (WM) and Traditional Chinese Medicine (TCM) might re-shape the gut microbiota with benefits to the host immunity and metabolic health. We particularly highlighted the effects of both WM and TCM increase the relative abundance of health promoting bacteria, such as, Akkermansia muciniphila, Blautia, and Bifidobacterium adolescentis, and which have been implicated in type 2 diabetes (T2D). Several lines of evidence suggested that TCM might complement the efficacy of WM through alteration of microbiota which warrants further investigation in our pursuit of prevention and control of T2D.

White common bean extract remodels the gut microbiota and ameliorates type 2 diabetes and its complications: A randomized double-blinded placebo-controlled trial

OBJECTIVE

Excessive carbohydrate intake is a high risk factor for increased morbidity of type 2 diabetes (T2D). A novel regimen for the dietary care of diabetes that consists of a highly active α-amylase inhibitor derived from white common bean extract (WCBE) and sufficient carbohydrates intake was applied to attenuate T2D and its complications. Furthermore, the role of gut microbiota in this remission was also investigated.

METHODS

We conducted a 4-month randomized double-blinded placebo-controlled trial. During the intense intervention period, ninety subjects were randomly assigned to the control group (Group C) and WCBE group (Group W). Subjects in Group C were supplemented with 1.5 g of maltodextrin as a placebo. Subjects in Group W took 1.5 g of WCBE half an hour before a meal. Fifty-five participants continued the maintenance intervention receiving the previous dietary intervention whereas less frequent follow-up. The variation in biochemical, vasculopathy and neuropathy indicators and the structure of the fecal microbiota during the intervention was analyzed.

RESULT

Glucose metabolism and diabetic complications showed superior remission in Group W with a 0.721 ± 0.742% decline of glycosylated hemoglobin after 4 months. The proportion of patients with diabetic peripheral neuropathy (Toronto Clinical Scoring System, TCSS ≥ 6) was significantly lower in Group W than in Group C. Both the left and right sural sensory nerve conduction velocity (SNCV-left sural and SNCV-right sural) slightly decreased in Group C and slightly increased in Group W. Additionally, the abundances of Bifidobacterium, Faecalibacterium and Anaerostipes were higher in Group W, and the abundances of Weissella, Klebsiella, Cronobacter and Enterobacteriaceae_unclassified were lower than those in Group C at month 2. At the end of month 4, Bifidobacterium remained more abundant in Group W.

CONCLUSION

To our knowledge, this is the first report of improvement to diabetes complications by using a dietary supplement in such a short-term period. The enrichment of SCFA-producing bacteria might be responsible for the attenuation of T2D and its complications.

CLINICAL TRIAL REGISTRATION NUMBER

http://www.chictr.org.cn/edit.aspx?pid=23309&htm=4, identifier ChiCTR-IOR-17013656.

Gut Microbiota and Mycobiota Evolution Is Linked to Memory Improvement after Bariatric Surgery in Obese Patients: A Pilot Study

Patients with obesity are known to exhibit gut microbiota dysbiosis and memory deficits. Bariatric surgery (BS) is currently the most efficient anti-obesity treatment and may improve both gut dysbiosis and cognition. However, no study has investigated association between changes of gut microbiota and cognitive function after BS. We prospectively evaluated 13 obese patients on anthropometric data, memory functions, and gut microbiota-mycobiota before and six months after BS. The Rey Auditory Verbal Learning Test (AVLT) and the symbol span (SS) of the Weschler Memory Scale were used to assess verbal and working memory, respectively. Fecal microbiota and mycobiota were longitudinally analyzed by 16S and ITS2 rRNA sequencing respectively. AVLT and SS scores were significantly improved after BS (AVLT scores: 9.7 ± 1.7 vs. 11.2 ± 1.9, p = 0.02, and SS scores: 9.7 ± 23.0 vs. 11.6 ± 2.9, p = 0.05). An increase in bacterial alpha-diversity, and Ruminococcaceae, Prevotella, Agaricus, Rhodotorula, Dipodascus, Malassezia, and Mucor were significantly associated with AVLT score improvement after BS, while an increase in Prevotella and a decrease in Clostridium, Akkermansia,&nbsp;Dipodascus and Candida were linked to SS scores improvement. We identified several changes in the microbial communities that differ according to the improvement of either the verbal or working memories, suggesting a complex gut-brain-axis that evolves after BS.

Gut Microbiota Composition and Fecal Metabolic Profiling in Patients With Diabetic Retinopathy

Recent evidence suggests there is a link between metabolic diseases and gut microbiota. To investigate the gut microbiota composition and fecal metabolic phenotype in diabetic retinopathy (DR) patients. DNA was extracted from 50 fecal samples (21 individuals with type 2 diabetes mellitus-associated retinopathy (DR), 14 with type 2 diabetes mellitus but without retinopathy (DM) and 15 sex- and age-matched healthy controls) and then sequenced by high-throughput 16S rDNA analysis. Liquid chromatography mass spectrometry (LC-MS)-based metabolomics was simultaneously performed on the samples. A significant difference in the gut microbiota composition was observed between the DR and healthy groups and between the DR and DM groups. At the genus level, Faecalibacterium, Roseburia, Lachnospira and Romboutsia were enriched in DR patients compared to healthy individuals, while Akkermansia was depleted. Compared to those in the DM patient group, five genera, including Prevotella, were enriched, and Bacillus, Veillonella, and Pantoea were depleted in DR patients. Fecal metabolites in DR patients significantly differed from those in the healthy population and DM patients. The levels of carnosine, succinate, nicotinic acid and niacinamide were significantly lower in DR patients than in healthy controls. Compared to those in DM patients, nine metabolites were enriched, and six were depleted in DR patients. KEGG annotation revealed 17 pathways with differentially abundant metabolites between DR patients and healthy controls, and only two pathways with differentially abundant metabolites were identified between DR and DM patients, namely, the arginine-proline and α-linolenic acid metabolic pathways. In a correlation analysis, armillaramide was found to be negatively associated with Prevotella and Subdoligranulum and positively associated with Bacillus. Traumatic acid was negatively correlated with Bacillus. Our study identified differential gut microbiota compositions and characteristic fecal metabolic phenotypes in DR patients compared with those in the healthy population and DM patients. Additionally, the gut microbiota composition and fecal metabolic phenotype were relevant. We speculated that the gut microbiota in DR patients may cause alterations in fecal metabolites, which may contribute to disease progression, providing a new direction for understanding DR.