Metagenomics and Faecal Metabolomics Integrative Analysis towards the Impaired Glucose Regulation and Type 2 Diabetes in Uyghur-Related Omics

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.

Metabolomic analysis of the Puerarin hypoglycemic activity via AMPK-mTOR and PPARγ-NF-κB signaling pathways

BACKGROUND

Diabetes mellitus (DM) is a chronic metabolic disease characterized by hyperglycemia, and its increasing prevalence is a global concern. Early diagnostic markers and therapeutic targets are essential for DM prevention and treatment. Pueraria, derived from kudzu root, is used clinically for various symptoms, and its active compound, Puerarin, shows promise in improving insulin resistance and reducing inflammation.

PURPOSE

This study aims to evaluate the protective effects of metformin and Puerarin at different doses in an STZ-induced DM mouse model. The intricate metabolites within the serum of STZ-induced diabetic mice were subjected to thorough investigation, thus elucidating the intricate mechanism through which Puerarin demonstrates notable efficacy in the treatment of diabetes.

METHODS

An STZ-induced DM mouse model is established. Mice are treated with metformin and puerarin at varying doses. Physiological, biochemical, and histomorphological assessments are performed. Metabolomics analysis is carried out on serum samples from control, DM, metformin, and medium-dose Puerarin groups. Western blot and qRT-PCR technologies are used to validate the mechanisms.

RESULTS

The DM mouse model replicates abnormal blood glucose, insulin levels, physiological, biochemical irregularities, as well as liver and pancreas damage. Treatment with metformin and Puerarin restores these abnormalities, reduces organ injury, and modulates AMPK, PPARγ, mTOR, and NF-κB protein and mRNA expression. Puerarin activates the AMPK-mTOR and PPARγ-NF-κB signaling pathways, regulating insulin signaling, glucolipid metabolism, and mitigating inflammatory damage.

CONCLUSION

This study demonstrates that Puerarin has the potential to treat diabetes by modulating key signaling pathways. The focus was on the finding that Puerarin has been shown to improve insulin signaling, glucolipid metabolism and attenuate inflammatory damage through the modulation of the AMPK-mTOR and PPARγ-NF-κB pathways. The discovery of Puerarin's favorable protective effect and extremely complex mechanism highlights its prospect in the treatment of diabetes and provides theoretical support for its comprehensive development and utilization.

Comprehensive analysis of the microbiome and metabolome in pus from pyogenic liver abscess patients with and without diabetes mellitus

Introduction

Pyogenic liver abscess (PLA) patients combined with diabetes mellitus (DM) tend to have more severe clinical manifestations than without DM. The mechanism responsible for this phenomenon is not entirely clear. The current study therefore aimed to comprehensively analyze the microbiome composition and metabolome in pus from PLA patients with and without DM, to determine the potential reasons for these differences.

Methods

Clinical data from 290 PLA patients were collected retrospectively. We analyzed the pus microbiota using 16S rDNA sequencing in 62 PLA patients. In addition, the pus metabolomes of 38 pus samples were characterized by untargeted metabolomics analysis. Correlation analyses of microbiota, metabolites and laboratory findings were performed to identify significant associations.

Results

PLA patients with DM had more severe clinical manifestations than PLA patients without DM. There were 17 discriminating genera between the two groups at the genus level, among which Klebsiella was the most discriminating taxa. The ABC transporters was the most significant differential metabolic pathway predicted by PICRUSt2. Untargeted metabolomics analysis showed that concentrations of various metabolites were significantly different between the two groups and seven metabolites were enriched in the ABC transporters pathway. Phosphoric acid, taurine, and orthophosphate in the ABC transporters pathway were negatively correlated with the relative abundance of Klebsiella and the blood glucose level.

Discussion

The results showed that the relative abundance of Klebsiella in the pus cavity of PLA patients with DM was higher than those without DM, accompanied by changes of various metabolites and metabolic pathways, which may be associated with more severe clinical manifestations.

Key Stratification of Microbiota Taxa and Metabolites in the Host Metabolic Health-Disease Balance

Human gut microbiota seems to drive the interaction with host metabolism through microbial metabolites, enzymes, and bioactive compounds. These components determine the host health-disease balance. Recent metabolomics and combined metabolome-microbiome studies have helped to elucidate how these substances could differentially affect the individual host pathophysiology according to several factors and cumulative exposures, such as obesogenic xenobiotics. The present work aims to investigate and interpret newly compiled data from metabolomics and microbiota composition studies, comparing controls with patients suffering from metabolic-related diseases (diabetes, obesity, metabolic syndrome, liver and cardiovascular diseases, etc.). The results showed, first, a differential composition of the most represented genera in healthy individuals compared to patients with metabolic diseases. Second, the analysis of the metabolite counts exhibited a differential composition of bacterial genera in disease compared to health status. Third, qualitative metabolite analysis revealed relevant information about the chemical nature of metabolites related to disease and/or health status. Key microbial genera were commonly considered overrepresented in healthy individuals together with specific metabolites, e.g., Faecalibacterium and phosphatidylethanolamine; and the opposite, Escherichia and Phosphatidic Acid, which is converted into the intermediate Cytidine Diphosphate Diacylglycerol-diacylglycerol (CDP-DAG), were overrepresented in metabolic-related disease patients. However, it was not possible to associate most specific microbiota taxa and metabolites according to their increased and decreased profiles analyzed with health or disease. Interestingly, positive association of essential amino acids with the genera Bacteroides were observed in a cluster related to health, and conversely, benzene derivatives and lipidic metabolites were related to the genera Clostridium, Roseburia, Blautia, and Oscillibacter in a disease cluster. More studies are needed to elucidate the microbiota species and their corresponding metabolites that are key in promoting health or disease status. Moreover, we propose that greater attention should be paid to biliary acids and to microbiota-liver cometabolites and its detoxification enzymes and pathways.

Microbiome analysis revealing microbial interactions and secondary bacterial infections in COVID-19 patients comorbidly affected by Type 2 diabetes

The mortality of coronavirus disease 2019 (COVID-19) disease is very high among the elderly or individuals having comorbidities such as obesity, cardiovascular diseases, lung infections, hypertension, and/or diabetes. Our study characterizes the metagenomic features in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-infected patients with or without type 2 diabetes, to identify the microbial interactions associated with its fatal consequences.This study compared the baseline nasopharyngeal microbiome of SARS-CoV-2-infected diabetic and nondiabetic patients with controls adjusted for age and gender. The metagenomics based on next-generation sequencing was performed using Ion GeneStudio S5 Series and the data were analyzed by the Vegan-package in R. All three groups possessed significant bacterial diversity and dissimilarity indexes (p < 0.05). Spearman's correlation coefficient network analysis illustrated 183 significant positive correlations and 13 negative correlations of pathogenic bacteria (r = 0.6-1.0, p < 0.05), and 109 positive correlations between normal flora and probiotic bacteria (r > 0.6, p < 0.05). The SARS-CoV-2 diabetic group exhibited a significant increase in pathogens and secondary infection-causing bacteria (p < 0.05) with a simultaneous decrease of normal flora (p < 0.05). The dysbiosis of the bacterial community might be linked with severe consequences of COVID-19-infected diabetic patients, although a few probiotic strains inhibited numerous pathogens in the same pathological niches. This study suggested that the promotion of normal flora and probiotics through dietary supplementation and excessive inflammation reduction by preventing secondary infections might lead to a better outcome for those comorbid patients.

Rumen-protected glucose supplementation alters fecal microbiota and its metabolic profiles in early lactation dairy cows

INTRODUCTION

Negative energy balance (NEB) is the pathological basis of metabolic disorders in early lactation dairy cows. Rumen-protected glucose (RPG) is a feed additive to relieve NEB of cows in early lactation. The aims of the current study were to evaluate the impact of different doses of RPG supply on fecal microbiota and metabolome in early lactation dairy cows, and their correlation with each other.

METHODS

A total of 24 multiparous Holstein dairy cows in early lactation were randomly assigned to one of four treatments for the first 35 days of the early lactation period, as follows: control group, a basal diet without RPG (CON); low RPG, a basal diet plus 200 g/d RPG (LRPG); medium RPG, a basal diet plus 350 g/d RPG (MRPG); or HRPG, high RPG, a basal diet plus 500 g/d RPG (HRPG). After 35 days, fecal samples were obtained from cows in all groups individually and using 16S rRNA gene sequencing to evaluate their microbiotas, while their metabolites were evaluated through metabolomics.

RESULTS

As expected, Firmicutes and Bacteroidetes were the core bacteria phyla. After RPG supplementation, there were an increase in Firmicutes and a decrease in Bacteroidetes. MRPG increased the relative abundance of cellulolytic bacteria, including Ruminococcaceae_UCG-005, Lachnospiraceae_UCG-008, Lachnospiraceae_FCS020_group, and Ruminiclostridium_9, while it decreased the relative abundance of Alistipes, Prevotellaceae_UCG-003, and Dorea. RPG supplementation could regulate the carbohydrate metabolism and amino acid metabolism pathway significantly and relieve lipolysis in dairy cows. Correlation analysis of fecal microbiome and metabolome showed that some major differential bacteria were the crucial contributors to differential metabolites.

CONCLUSION

In conclusion, RPG supplementation can affect the fecal microbial components and microbial metabolism, and 350 g RPG might be the ideal dose as a daily supplement.

Fecal microbiota and metabolomics revealed the effect of long-term consumption of gallic acid on canine lipid metabolism and gut health

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Long-term consumption of 0.02%∼0.08% GA had no negative effect on canine body condition.

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GA intervention improved anti-oxidative and anti-inflammatory capacities.

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0.08% GA regulated lipid metabolism in serum.

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0.08% GA increased the relative abundance of SCFAs-producing bacteria.

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0.08% GA regulated carbohydrate metabolism in fece.

Gallic acid (GA) is a natural polyphenolic compound with many health benefits. To assess the potential risk of long-term consumption of GA to gut health, healthy dogs were fed a basal diet supplemented with GA (0%, 0.02%, 0.04%, and 0.08%) for 45 d, and fecal microbiota and metabolomics were evaluated. This study demonstrated that GA supplementation regulated serum lipid metabolism by reducing serum triglyceride, fat digestibility, and Bacteroidetes/Firmicutes ratio. In addition, the relative abundance of Parasutterella was significantly lower, and the SCFAs-producing bacteria were increased along with fecal acetate and total SCFAs contents accumulation in the 0.08% GA group. Metabolomics data further elucidated that 0.08% GA significantly affected carbohydrate metabolism by downregulating succinic acid in fece, thereby alleviating inflammation and oxidative stress. Overall, this study confirmed the beneficial effects of long-term consumption of GA on lipid metabolism and gut health, and the optimal level of GA supplementation was 0.08%.

Lower abundance of Bacteroides and metabolic dysfunction are highly associated with the post-weaning diarrhea in piglets

Growing evidences show a direct link between diarrhea and disorders of gut microbiota in pigs. However, whether there are microbial markers associated with post-weaning diarrhea remains unknown. In the current study, we compared the microbial community, functions and metabolites between healthy weaned piglets (group H, n=7) and piglets with post-weaning diarrhea (group D, n=7), in order to find out diarrhea associated microbial markers. Each of 7 fecal samples was collected from H and D piglets (weaned at 21 d and sampled at 26 d). The metagenomic and untargeted metabolomic analysis revealed that the microbial composition, function and metabolic profile in D pigs was considerably reshaped, including the reduced abundance and number of Bacteroides, which significantly correlated with the diarrhea status of host. The carbohydrate metabolism, biosynthesis and metabolism, lipid metabolism, amino acid metabolism, and the activity of glycan and carbohydrates digestion related enzymes showed extensively down-regulated in D pigs compared with H pigs. Diarrhea significantly changed the metabolic profiles of fecal microbiota, and most of the altered metabolites were negatively or positively correlated with the change in the abundance of Bacteroides. In conclusion, the lower abundance of Bacteroides and its associated metabolic dysfunction may be regarded as microbial markers of physiological post-weaning diarrhea in piglets.

Composition and diversity of gut microbiota in diabetic retinopathy

Objective

Diabetic retinopathy (DR) is one of the most common complications of type 2 diabetes mellitus. The current study investigates the composition, structure, and function of gut microbiota in DR patients and explores the correlation between gut microbiota and clinical characteristics of DR.

Methods

A total of 50 stool samples were collected from 50 participants, including 25 DR patients and 25 healthy controls (HCs). 16S ribosomal RNA gene sequencing was used to analyze the gut microbial composition in these two groups. DNA was extracted from the fecal samples using the MiSeq platform.

Results

The microbial structure and composition of DR patients were different from that of HCs. The microbial richness of gut microbiota in DR was higher than that of normal individuals. The alterations of microbiome of DR patients were associated with disrupted Firmicutes, Bacteroidetes, Synergistota, and Desulfobacterota phyla. In addition, increased levels of Bacteroides, Megamonas, Ruminococcus_torques_group, Lachnoclostridium, and Alistipes, and decreased levels of Blautia, Eubacterium_ hallii_group, Collinsella, Dorea, Romboutsia, Anaerostipes, and Fusicatenibacter genera were observed in the DR groups. Additionally, a stochastic forest model was developed to identify a set of biomarkers with seven bacterial genera that can differentiate patients with DR from those HC. The microbial communities exhibited varied functions in these two groups because of the alterations of the above-mentioned bacterial genera.

Conclusion

The altered composition and function of gut microbiota in DR patients indicated that gut microbiome could be used as non-invasive biomarkers, improve clinical diagnostic methods, and identify putative therapeutic targets for DR.

Gallnut Tannic Acid Exerts Anti-stress Effects on Stress-Induced Inflammatory Response, Dysbiotic Gut Microbiota, and Alterations of Serum Metabolic Profile in Beagle Dogs

Stress exposure is a potential threat to humans who live or work in extreme environments, often leading to oxidative stress, inflammatory response, intestinal dysbiosis, and metabolic disorders. Gallnut tannic acid (TA), a naturally occurring polyphenolic compound, has become a compelling source due to its favorable anti-diarrheal, anti-oxidative, anti-inflammatory, and anti-microbial activities. Thus, this study aimed to evaluate the anti-stress effects of gallnut TA on the stress-induced inflammatory response, dysbiotic gut microbiota, and alterations of serum metabolic profile using beagle models. A total of 13 beagle dogs were randomly divided into the stress (ST) and ST + TA groups. Dietary supplementation with TA at 2.5 g/kg was individually fed to each dog in the ST + TA group for 14 consecutive days. On day 7, all dogs were transported for 3 h from a stressful environment (days 1–7) to a livable site (days 8–14). In our results, TA relieved environmental stress-induced diarrheal symptoms in dogs and were shown to protect from myocardial injury and help improve immunity by serum biochemistry and hematology analysis. Also, TA inhibited the secretion of serum hormones [cortisol (COR), glucocorticoid (GC), and adrenocorticotropic hormone (ACTH)] and the expression of heat shock protein (HSP) 70 to protect dogs from stress-induced injury, thereby relieving oxidative stress and inflammatory response. Fecal 16S rRNA gene sequencing revealed that TA stimulated the growth of beneficial bacteria (Allobaculum, Dubosiella, Coriobacteriaceae_UCG-002, and Faecalibaculum) and suppressed the growth of pathogenic bacteria (Escherichia-Shigella and Streptococcus), thereby increasing fecal butyrate levels. Serum metabolomics further showed that phytosphingosine, indoleacetic acid, arachidonic acid, and biotin, related to the metabolism of sphingolipid, tryptophan, arachidonic acid, and biotin, respectively, could serve as potential biomarkers of stress exposure. Furthermore, Spearman’s correlation analysis showed strong relationships between the four potential serum biomarkers and differential bacteria. Overall, gallnut TA may be a potential prebiotic for the prevention and treatment of stress-induced metabolic disorders by targeting intestinal microbiota.

Feature Selection Pipelines with Classification for Non-targeted Metabolomics Combining the Neural Network and Genetic Algorithm

Non-targeted metabolomics via high-resolution mass spectrometry methods, such as direct infusion Fourier transform-ion cyclotron resonance mass spectrometry (DI-FT-ICR MS), produces data sets with thousands of features. By contrast, the number of samples is in general substantially lower. This disparity presents challenges when analyzing non-targeted metabolomics data sets and often requires custom methods to uncover information not always accessible via classical statistical techniques. In this work, we present a pipeline that combines a convolutional neural network with traditional statistical approaches and an adaptation of a genetic algorithm. The developed method was applied to a lifestyle intervention cohort data set, where subjects at risk of type 2 diabetes underwent an oral glucose tolerance test. Feature selection is the final result of the pipeline, achieved through classification of the data set via a neural network, with a precision-recall score of over 0.9 on the test set. The features most relevant for the described classification were then chosen via a genetic algorithm. The output of the developed pipeline encompasses approximately 200 features with high predictive scores, providing a fingerprint of the metabolic changes in the prediabetic class on the data set. Our framework presents a new approach which allows to apply complex modeling based on convolutional neural networks for the analysis of high-resolution mass spectrometric data.

Gallic Acid Alleviates Gut Dysfunction and Boosts Immune and Antioxidant Activities in Puppies Under Environmental Stress Based on Microbiome-Metabolomics Analysis

Early-life exposure to environmental stress disrupts the gut barrier and leads to inflammatory responses and changes in gut microbiota composition. Gallic acid (GA), a natural plant polyphenol, has received significant interest for its antioxidant, anti-inflammatory, and antimicrobial properties that support the maintenance of intestinal health. To assess whether dietary supplementation of GA alleviates environmental stress, a total of 19 puppies were randomly allocated to the following three dietary treatments for 2 weeks: 1) basal diet (control (CON)); 2) basal diet + transportation (TS); and 3) basal diet with the addition of 500 mg/kg of GA + transportation (TS+GA). After a 1-week supplementation period, puppies in the TS and TS+GA groups were transported from a stressful environment to another livable location, and puppies in the CON group were then left in the stressful environment. Results indicated that GA markedly reduced the diarrhea rate in puppies throughout the trial period and caused a moderate decline of serum cortisol and HSP-70 levels after transportation. Also, GA alleviated the oxidative stress and inflammatory response caused by multiple environmental stressors. Meanwhile, puppies fed GA had a higher abundance of fecal Firmicutes and Lactobacillus and lower Proteobacteria, Escherichia–Shigella, and Clostridium_sensu_stricto_1 after transportation. As a result, the TS+GA group had the highest total short-chain fatty acids and acetic acid. Also, the fecal and serum metabolomics analyses revealed that GA markedly reversed the abnormalities of amino acid metabolism, lipid metabolism, carbohydrate metabolism, and nucleotide metabolism caused by stresses. Finally, Spearman’s correlation analysis was carried out to explore the comprehensive microbiota and metabolite relationships. Overall, dietary supplementation of GA alleviates oxidative stress and inflammatory response in stressed puppies by causing beneficial shifts on gut microbiota and metabolites that may support gut and host health.

Morus alba L. water extract changes gut microbiota and fecal metabolome in mice induced by high-fat and high-sucrose diet plus low-dose streptozotocin

Gut microbiota plays a key role in the pathophysiology of type 2 diabetes mellitus (T2D). Mulberry leaf has a hypoglycemic effect, but the potential mechanism is not fully understood. This study aimed to explore the influences and potential mechanisms of mulberry leaf water extract (MLWE) intervention on mice with T2D induced through a high-fat and high-sucrose diet combined with streptozotocin by the combination of fecal metabolomics and gut microbiota analysis. Results showed that MLWE could decrease fasting blood glucose and body weight while ameliorating lipid profiles, insulin resistance, liver inflammation, and the accumulation of lipid droplets in T2D mice. MLWE could reverse the abundances of the phyla Actinobacteria and Bacteroidetes and the ratio of Firmicutes/Bacteroidetes, and increase the abundances of the phyla Cyanobacteria and Epsilonbacteraeota in the feces of T2D mice. The abundances of genera Alloprevotella, Parabacteroides, Muribaculaceae, and Romboutsia in the feces of T2D mice could be reversed, while Oscillatoriales_cyanobacterium and Gastranaerophilales could be reinforced by MLWE supplementation. The levels of nine metabolites in the feces of T2D mice were improved, among which glycine, Phe-Pro, urocanic acid, phylloquinone, and lactate were correlated with Romboutsia and Gastranaerophilales. Taken together, we conclude that MLWE can effectively alleviate T2D by mediating the host-microbial metabolic axis.

Gut Microbiota in Bone Health and Diabetes

PURPOSE OF REVIEW

Patients with diabetes mellitus (DM) are at increased risk of developing osteopathogenesis and skeletal fragility. The role of the gut microbiota in both DM and osteopathy is not fully explored and may be involved in the pathology of both diseases.

RECENT FINDINGS

Gut microbiota alterations have been observed in DM and osteopathogenic disorders as compared with healthy controls, such as significantly lower abundance of Prevotella and higher abundance of Lactobacillus, with a diminished bacterial diversity. Other overlapping gastro-intestinal features include the loss of intestinal barrier function with translocation of bacterial metabolites to the blood stream, induction of immunological deficits and changes in hormonal and endocrinal signalling, which may lead to the development of diabetic osteopathy. Signalling pathways involved in both DM and osteopathy are affected by gut bacteria and their metabolites. Future studies should focus on gut microbiota involvement in both diseases.

Deregulation of lncRNA HIST1H2AG-6 and AIM1-3 in peripheral blood mononuclear cells is associated with newly diagnosed type 2 diabetes

BACKGROUND

Type 2 diabetes mellitus (T2DM) is mainly affected by genetic and environmental factors; however, the correlation of long noncoding RNAs (lncRNAs) with T2DM remains largely unknown.

METHODS

Microarray analysis was performed to identify the differentially expressed lncRNAs and messenger RNAs (mRNAs) in patients with T2DM and healthy controls, and the expression of two candidate lncRNAs (lnc-HIST1H2AG-6 and lnc-AIM1-3) were further validated using quantitative real-time polymerase chain reaction (qRT-PCR). Spearman's rank correlation coefficient was used to measure the degree of association between the two candidate lncRNAs and differentially expressed mRNAs. Furthermore, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and GO (Gene Ontology) enrichment analysis were used to reveal the biological functions of the two candidate lncRNAs. Additionally, multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed.

RESULTS

The microarray analysis revealed that there were 55 lncRNAs and 36 mRNAs differentially expressed in patients with T2DM compared with healthy controls. Notably, lnc-HIST1H2AG-6 was significantly upregulated and lnc-AIM1-3 was significantly downregulated in patients with T2DM, which was validated in a large-scale qRT-PCR examination (90 controls and 100 patients with T2DM). Spearman's rank correlation coefficient revealed that both lncRNAs were correlated with 36 differentially expressed mRNAs. Furthermore, functional enrichment (KEGG and GO) analysis demonstrated that the two lncRNA-related mRNAs might be involved in multiple biological functions, including cell programmed death, negative regulation of insulin receptor signal, and starch and sucrose metabolism. Multivariate logistic regression analysis revealed that lnc-HIST1H2AG-6 and lnc-AIM1-3 were significantly correlated with T2DM (OR = 5.791 and 0.071, respectively, both P = 0.000). Furthermore, the ROC curve showed that the expression of lnc-HIST1H2AG-6 and lnc-AIM1-3 might be used to differentiate patients with T2DM from healthy controls (area under the ROC curve = 0.664 and 0.769, respectively).

CONCLUSION

The profiles of lncRNA and mRNA were significantly changed in patients with T2DM. The expression levels of lnc-HIST1H2AG-6 and lnc-AIM1-3 genes were significantly correlated with some features of T2DM, which may be used to distinguish patients with T2DM from healthy controls and may serve as potential novel biomarkers for diagnosis in the future.

Dysbiosis and Implication of the Gut Microbiota in Diabetic Retinopathy

The pathogenesis of type 2 diabetes mellitus (T2DM) is commonly associated with altered gut bacteria. However, whether the microbial dysbiosis that exists in human diabetic patients with or without retinopathy is different remains largely unknown. Here, we collected clinical information and fecal samples from 75 participants, including 25 diabetic patients without retinopathy (DM), 25 diabetic patients with retinopathy (DR), and 25 healthy controls (HC). The gut microbial composition in the three groups was analyzed using 16S ribosomal RNA (rRNA) gene sequencing. Microbial structure and composition differed in the three groups. The α and β diversities in both the DM and DR groups were reduced compared with those in the HC group. Blautia was the most abundant genus, especially in the DM group. In addition, increased levels of Bifidobacterium and Lactobacillus and decreased levels of Escherichia-Shigella, Faecalibacterium, Eubacterium_hallii_group and Clostridium genera were observed in the DM and DR groups compared with the HC group. Furthermore, a biomarker set of 25 bacterial families, which could distinguish patients in the DR group from those in the DM and HC groups was identified, with the area under the curve values ranging from 0.69 to 0.85. Of note, Pasteurellaceae, which was increased in DM and decreased in DR compared with HC, generated a high AUC (0.74) as an individual predictive biomarker. Moreover, 14 family biomarkers were associated with fasting blood glucose levels or diabetes, with most of them being negatively correlated. In summary, our study establishes compositional alterations of gut microbiota in DM and DR, suggesting the potential use of gut microbiota as a non-invasive biomarker for clinical and differential diagnosis, as well as identifying potential therapeutic targets of diabetic retinopathy.

Dysbiosis in the Development of Type I Diabetes and Associated Complications: From Mechanisms to Targeted Gut Microbes Manipulation Therapies

Globally, we are facing a worrying increase in type 1 diabetes mellitus (T1DM) incidence, with onset at younger age shedding light on the need to better understand the mechanisms of disease and step-up prevention. Given its implication in immune system development and regulation of metabolism, there is no surprise that the gut microbiota is a possible culprit behind T1DM pathogenesis. Additionally, microbiota manipulation by probiotics, prebiotics, dietary factors and microbiota transplantation can all modulate early host-microbiota interactions by enabling beneficial microbes with protective potential for individuals with T1DM or at high risk of developing T1DM. In this review, we discuss the challenges and perspectives of translating microbiome data into clinical practice. Nevertheless, this progress will only be possible if we focus our interest on developing numerous longitudinal, multicenter, interventional and double-blind randomized clinical trials to confirm their efficacy and safety of these therapeutic approaches.

Gut microbiota and aging

Aging is characterized by the functional decline of tissues and organs and increased risk of aging-associated disorders, which pose major societal challenges and are a public health priority. Despite extensive human genetics studies, limited progress has been made linking genetics with aging. There is a growing realization that the altered assembly, structure and dynamics of the gut microbiota actively participate in the aging process. Age-related microbial dysbiosis is involved in reshaping immune responses during aging, which manifest as immunosenescence (insufficiency) and inflammaging (over-reaction) that accompany many age-associated enteric and extraenteric diseases. The gut microbiota can be regulated, suggesting a potential target for aging interventions. This review summarizes recent findings on the physiological succession of gut microbiota across the life-cycle, the roles and mechanisms of gut microbiota in healthy aging, alterations of gut microbiota and aging-associated diseases, and the gut microbiota-targeted anti-aging strategies.