The Fecal Microbiota Is Already Altered in Normoglycemic Individuals Who Go on to Have Type 2 Diabetes

The Role of Fecal Microbiota Transplantation (FMT) in the Management of Metabolic Diseases in Humans: A Narrative Review

The gut microbiota represents a complex ecosystem of trillions of microorganisms residing in the human gastrointestinal tract, which is known to interact with the host physiology and regulate multiple functions. Alterations in gut microbial composition, diversity, and function are referred to as dysbiosis. Dysbiosis has been associated with a variety of chronic diseases, including Clostridioides difficile infections, but also cardiometabolic diseases, including obesity, metabolic syndrome, and type 2 diabetes mellitus (T2DM). The implication of gut microbiota dysbiosis in the pathogenesis of both obesity and T2DM has paved the way to implementing novel therapeutic approaches for metabolic diseases through gut microbial reconfiguration. These interventions include probiotics, prebiotics, and synbiotics, while a more innovative approach has been fecal microbiota transplantation (FMT). FMT is a procedure that delivers healthy human donor stool to another individual through the gastrointestinal tract, aiming to restore gut microbiota balance. Several studies have investigated this approach as a potential tool to mitigate the adverse metabolic effects of gut microbiota aberrations associated with obesity and T2DM. The aim of the present review was to critically summarize the existing evidence regarding the clinical applications of FMT in the management of obesity and T2DM and provide an update on the potential of this method to remodel the entire host microbiota, leading thus to weight loss and sustained metabolic benefits. Safety issues, long-term efficacy, limitations, and pitfalls associated with FMT studies are further discussed, emphasizing the need for further research and standardization in certain methodological aspects in order to optimize metabolic outcomes.

Gut Microbiota in the Progression of Type 2 Diabetes and the Potential Role of Exercise: A Critical Review

Type 2 diabetes (T2D) is the predominant metabolic epidemic posing a major threat to global health. Growing evidence indicates that gut microbiota (GM) may critically influence the progression from normal glucose tolerance, to pre-diabetes, to T2D. On the other hand, regular exercise contributes to the prevention and/or treatment of the disease, and evidence suggests that a possible way regular exercise favorably affects T2D is by altering GM composition toward health-promoting bacteria. However, research regarding this potential effect of exercise-induced changes of GM on T2D and the associated mechanisms through which these effects are accomplished is limited. This review presents current data regarding the association of GM composition and T2D and the possible critical GM differentiation in the progression from normal glucose, to pre-diabetes, to T2D. Additionally, potential mechanisms through which GM may affect T2D are presented. The effect of exercise on GM composition and function on T2D progression is also discussed.

Effect of time-restricted eating regimen on weight loss is mediated by gut microbiome

Time-restricted eating (TRE) is a promising obesity management strategy, but weight-loss efficacy varies among participants, and the underlying mechanism is unclear. The study aimed to investigate the role of gut microbiota in weight-loss response during long-term TRE intervention. We analyzed data from 51 obese adults in a 12-month TRE program, categorizing them into distinct weight loss groups (DG) and moderate weight loss groups (MG) based on their TRE responses. Shotgun metagenomic sequencing analysis revealed a significant increase in species closely associated with weight loss effectiveness and metabolic parameter changes in the DG group. Pathways related to fatty acid biosynthesis, glycogen biosynthesis, and nucleotide metabolism were reduced in the DG group and enhanced in the MG group. Next, we identified nine specific species at baseline that contributed better responses to TRE intervention and significant weight loss. Collectively, gut microbiota contributes to responsiveness heterogeneity in TRE and can predict weight-loss effectiveness.

Effect of Akkermansia muciniphila on pancreatic islet β-cell function in rats with prediabetes mellitus induced by a high-fat diet

Prediabetes is an important stage in the development of diabetes. It is necessary to find a safe, effective and sustainable way to delay and reverse the progression of prediabetes. Akkermansia muciniphila (A. muciniphila) is one of the key bacteria associated with glucose metabolism. Recent studies mainly focus on the effect of A. muciniphila on obesity and insulin resistance, but there is no research on the effect of A. muciniphila on pancreatic β-cell function and its mechanism in prediabetes. In this study, we investigated the effects of A. muciniphila on β-cell function, apoptosis and differentiation, as well as its effects on the gut microbiome, intestinal barrier, metaflammation and the expression of Toll-like receptors (TLRs) in a high-fat diet (HFD)-induced prediabetic rat model. The effect of A. muciniphila was compared with dietary intervention. The results showed both A. muciniphila treatment and dietary intervention can reduce metaflammation by repairing the intestinal barrier in rats with prediabetes induced by an HFD and improve β-cell secretory function, apoptosis and differentiation through signaling pathways mediated by TLR2 and TLR4. Additionally, A. muciniphila can further elevate β-cell secretion, attenuate apoptosis and improve differentiation and the TLR signaling pathway on the basis of diet.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

mbDecoda: a debiased approach to compositional data analysis for microbiome surveys

Potentially pathogenic or probiotic microbes can be identified by comparing their abundance levels between healthy and diseased populations, or more broadly, by linking microbiome composition with clinical phenotypes or environmental factors. However, in microbiome studies, feature tables provide relative rather than absolute abundance of each feature in each sample, as the microbial loads of the samples and the ratios of sequencing depth to microbial load are both unknown and subject to considerable variation. Moreover, microbiome abundance data are count-valued, often over-dispersed and contain a substantial proportion of zeros. To carry out differential abundance analysis while addressing these challenges, we introduce mbDecoda, a model-based approach for debiased analysis of sparse compositions of microbiomes. mbDecoda employs a zero-inflated negative binomial model, linking mean abundance to the variable of interest through a log link function, and it accommodates the adjustment for confounding factors. To efficiently obtain maximum likelihood estimates of model parameters, an Expectation Maximization algorithm is developed. A minimum coverage interval approach is then proposed to rectify compositional bias, enabling accurate and reliable absolute abundance analysis. Through extensive simulation studies and analysis of real-world microbiome datasets, we demonstrate that mbDecoda compares favorably with state-of-the-art methods in terms of effectiveness, robustness and reproducibility.

Glucose-lowering effects of a synbiotic combination containing Pediococcus acidilactici in C. elegans and mice

AIMS/HYPOTHESIS

Modulation of gut microbiota has emerged as a promising strategy to treat or prevent the development of different metabolic diseases, including type 2 diabetes and obesity. Previous data from our group suggest that the strain Pediococcus acidilactici CECT9879 (pA1c) could be an effective probiotic for regulating glucose metabolism. Hence, the objectives of this study were to verify the effectiveness of pA1c on glycaemic regulation in diet-induced obese mice and to evaluate whether the combination of pA1c with other normoglycaemic ingredients, such as chromium picolinate (PC) and oat β-glucans (BGC), could increase the efficacy of this probiotic on the regulation of glucose and lipid metabolism.

METHODS

Caenorhabditis elegans was used as a screening model to describe the potential synbiotic activities, together with the underlying mechanisms of action. In addition, 4-week-old male C57BL/6J mice were fed with a high-fat/high-sucrose diet (HFS) for 6 weeks to induce hyperglycaemia and obesity. Mice were then divided into eight groups (n=12 mice/group) according to dietary supplementation: control-diet group; HFS group; pA1c group (1010 colony-forming units/day); PC; BGC; pA1c+PC+BGC; pA1c+PC; and pA1c+BGC. Supplementations were maintained for 10 weeks. Fasting blood glucose was determined and an IPGTT was performed prior to euthanasia. Fat depots, liver and other organs were weighed, and serum biochemical variables were analysed. Gene expression analyses were conducted by real-time quantitative PCR. Sequencing of the V3-V4 region of the 16S rRNA gene from faecal samples of each group was performed, and differential abundance for family, genera and species was analysed by ALDEx2R package.

RESULTS

Supplementation with the synbiotic (pA1c+PC+BGC) counteracted the effect of the high glucose by modulating the insulin-IGF-1 signalling pathway in C. elegans, through the reversal of the glucose nuclear localisation of daf-16. In diet-induced obese mice, all groups supplemented with the probiotic significantly ameliorated glucose tolerance after an IPGTT, demonstrating the glycaemia-regulating effect of pA1c. Further, mice supplemented with pA1c+PC+BGC exhibited lower fasting blood glucose, a reduced proportion of visceral adiposity and a higher proportion of muscle tissue, together with an improvement in the brown adipose tissue in comparison with the HFS group. Besides, the effect of the HFS diet on steatosis and liver damage was normalised by the synbiotic. Gene expression analyses demonstrated that the synbiotic activity was mediated not only by modulation of the insulin-IGF-1 signalling pathway, through the overexpression of GLUT-1 and GLUT-4 mediators, but also by a decreased expression of proinflammatory cytokines such as monocyte chemotactic protein-1. 16S metagenomics demonstrated that the synbiotic combinations allowed an increase in the concentration of P. acidilactici, together with improvements in the intestinal microbiota such as a reduction in Prevotella and an increase in Akkermansia muciniphila.

CONCLUSIONS/INTERPRETATION

Our data suggest that the combination of pA1c with PC and BGC could be a potential synbiotic for blood glucose regulation and may help to fight insulin resistance, diabetes and obesity.

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.

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

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

Gut microbiota composition and function in pregnancy as determinants of prediabetes at two-year postpartum

AIMS

Deep metagenomics offers an advanced tool for examining the relationship between gut microbiota composition and function and the onset of disease; in this case, does the composition and function of gut microbiota during pregnancy differ in women who develop prediabetes and those who do not at two-year postpartum, and whether the gut microbiota composition associates with glycemic traits.

METHODS

In total, 439 women were recruited in early pregnancy. Gut microbiota was assessed by metagenomics analysis in early (13.9 ± 2.0 gestational weeks) and late pregnancy (35.1 ± 1.0 gestational weeks). Prediabetes was determined using American Diabetes Association criteria as fasting plasma glucose 5.6-6.9 mmol/l analyzed by an enzymatic hexokinase method. Of the women, 39 (22.1%) developed prediabetes by two-year postpartum.

RESULTS

The relative abundances of Escherichia unclassified (FDR < 0.05), Clostridiales bacterium 1_7_ 47FAA (FDR < 0.25) and Parabacteroides (FDR < 0.25) were higher, and those of Ruminococcaceae bacterium D16 (FDR < 0.25), Anaerotruncus unclassified (FDR < 0.25) and Ruminococcaceae noname (FDR < 0.25) were lower in early pregnancy in those women who later developed prediabetes. In late pregnancy, Porphyromonas was higher and Ruminococcus sp 5_1_39BFAA was lower in prediabetes (FDR < 0.25). Furthermore, fasting glucose concentrations associated inversely with Anaerotruncus unclassified in early pregnancy and directly with Ruminococcus sp 5_1_39BFAA in late pregnancy (FDR < 0.25). α-Diversity or β-diversity did not differ significantly between the groups. Predictions of community function during pregnancy were not associated with prediabetes.

CONCLUSIONS

Our study shows that some bacterial species during pregnancy contributed to the onset of prediabetes within two-year postpartum. These were attributable primarily to a lower abundance of short-chain fatty acids-producing bacteria.

Alterations in the Gut Microbiota in Pregnant Women with Pregestational Type 2 Diabetes Mellitus

Human gut dysbiosis is associated with type 2 diabetes mellitus (T2DM); however, the gut microbiome in pregnant women with pregestational type 2 diabetes mellitus (PGDM) remains unexplored. We investigated the alterations in the gut microbiota composition in pregnant women with or without PGDM. The gut microbiota was examined using 16S rRNA sequencing data of 234 maternal fecal samples that were collected during the first (T1), second (T2), and third (T3) trimesters. The PGDM group presented a reduction in the number of gut bacteria taxonomies as the pregnancies progressed. Linear discriminant analyses revealed that Megamonas, Bacteroides, and Roseburia intestinalis were enriched in the PGDM group, whereas Bacteroides vulgatus, Faecalibacterium prausnitzii, Eubacterium rectale, Bacteroides uniformis, Eubacterium eligens, Subdoligranulum, Bacteroides fragilis, Dialister, Lachnospiraceae, Christensenellaceae R-7, Roseburia inulinivorans, Streptococcus oralis, Prevotella melaninogenica, Neisseria perflava, Bacteroides ovatus, Bacteroides caccae, Veillonella dispar, and Haemophilus parainfluenzae were overrepresented in the control group. Correlation analyses showed that the PGDM-enriched taxa were correlated with higher blood glucose levels during pregnancy, whereas the taxonomic biomarkers of normoglycemic pregnancies exhibited negative correlations with glycemic traits. The microbial networks in the PGDM group comprised weaker microbial interactions than those in the control group. Our study reveals the distinct characteristics of the gut microbiota composition based on gestational ages between normoglycemic and PGDM pregnancies. Further longitudinal research involving women with T2DM at preconception stages and investigations using shotgun metagenomic sequencing should be performed to elucidate the relationships between specific bacterial functions and PGDM metabolic statuses during pregnancy and to identify potential therapeutic targets. IMPORTANCE The incidence of pregestational type 2 diabetes mellitus (PGDM) is increasing, with high rates of serious adverse maternal and neonatal outcomes that are strongly correlated with hyperglycemia. Recent studies have shown that type 2 diabetes mellitus is associated with gut microbial dysbiosis; however, the gut microbiome composition and its associations with the metabolic features of patients with PGDM remain largely unknown. In this study, we investigated the changes in the gut microbiota composition in pregnant women with and without PGDM. We identified differential taxa that may be correlated with maternal metabolic statuses during pregnancy. Additionally, we observed that the number of taxonomic and microbial networks of gut bacteria were distinctly reduced in women with hyperglycemia as their pregnancies progressed. These results extend our understanding of the associations between the gut microbial composition, PGDM-related metabolic changes, and pregnancy outcomes.

Multi-omics signatures in new-onset diabetes predict metabolic response to dietary inulin: findings from an observational study followed by an interventional trial

AIM

The metabolic performance of the gut microbiota contributes to the onset of type 2 diabetes. However, targeted dietary interventions are limited by the highly variable inter-individual response. We hypothesized (1) that the composition of the complex gut microbiome and metabolome (MIME) differ across metabolic spectra (lean-obese-diabetes); (2) that specific MIME patterns could explain the differential responses to dietary inulin; and (3) that the response can be predicted based on baseline MIME signature and clinical characteristics.

METHOD

Forty-nine patients with newly diagnosed pre/diabetes (DM), 66 metabolically healthy overweight/obese (OB), and 32 healthy lean (LH) volunteers were compared in a cross-sectional case-control study integrating clinical variables, dietary intake, gut microbiome, and fecal/serum metabolomes (16 S rRNA sequencing, metabolomics profiling). Subsequently, 27 DM were recruited for a predictive study: 3 months of dietary inulin (10 g/day) intervention.

RESULTS

MIME composition was different between groups. While the DM and LH groups represented opposite poles of the abundance spectrum, OB was closer to DM. Inulin supplementation was associated with an overall improvement in glycemic indices, though the response was very variable, with a shift in microbiome composition toward a more favorable profile and increased serum butyric and propionic acid concentrations. The improved glycemic outcomes of inulin treatment were dependent on better baseline glycemic status and variables related to the gut microbiota, including the abundance of certain bacterial taxa (i.e., Blautia, Eubacterium halii group, Lachnoclostridium, Ruminiclostridium, Dialister, or Phascolarctobacterium), serum concentrations of branched-chain amino acid derivatives and asparagine, and fecal concentrations of indole and several other volatile organic compounds.

CONCLUSION

We demonstrated that obesity is a stronger determinant of different MIME patterns than impaired glucose metabolism. The large inter-individual variability in the metabolic effects of dietary inulin was explained by differences in baseline glycemic status and MIME signatures. These could be further validated to personalize nutritional interventions in patients with newly diagnosed diabetes.

Differences in gut microbiota and its metabolic function among different fasting plasma glucose groups in Mongolian population of China

BACKGROUND

Many studies reported the association between gut microbiota and type 2 diabetes mellitus (T2D), but it is still unclear which bacterial genus plays a key role and how the metabolic function of gut microbiota changes in the occurrence and development of T2D. Besides, there is a high diabetic prevalence in Mongolian population, which may be partly affected by their high calorie diet. This study identified the main bacterial genus influencing T2D in Mongolian population, and analyzed the changes of metabolic function of gut microbiome. The association between dietary factors and the relative abundance of main bacterial genus and its metabolic function was also studied.

METHODS

Dietary surveys and gut microbiota test were performed on 24 Mongolian volunteers that were divided into T2D (6 cases), PRET2D (6 cases) and Control group (12 cases) according to fasting plasma glucose (FPG) values. The relative abundance and metabolic function of gut microbiome from their fecal samples were measured by metagenomic analysis. Statistic method was used to evaluate the association between dietary factors and the relative abundance of the main bacterial genus or its metabolic function.

RESULTS

This study found that the Clostridium genus may be one of the key bacterial genera affecting the process of T2D. First, the relative abundance of Clostridium genus was significantly different among the three groups. Second, there was a higher relative abundance of metabolic enzymes of gut bacteria in PRET2D and T2D group than that in Control group. Third, a strong correlation between Clostridium genus and many metabolic enzymes was uncovered, many of which may be produced by the Clostridium. Last, carotene intake daily was negatively correlated with the Clostridium but positively correlated with tagaturonate reductase catalyzing interconversions of pentose and glucuronate.

CONCLUSIONS

The gut Clostridium genus may play an important role in the development of T2D and it could be a potential biomarker for T2D in Mongolian population. Meanwhile, the metabolic function of gut bacteria has changed during the early stage of T2D and the changes in carbohydrate, amino acid, lipid or energy metabolism of Clostridium genus may play a critical role. In addition, the carotene intake may affect reproduction and metabolic function of Clostridium genus.

The Commensal Anaerobe Veillonella dispar Reprograms Its Lactate Metabolism and Short-Chain Fatty Acid Production during the Stationary Phase

Veillonella spp. are obligate, anaerobic, Gram-negative bacteria found in the human oral cavity and gut. Recent studies have indicated that gut Veillonella promote human homeostasis by producing beneficial metabolites, specifically short-chain fatty acids (SCFAs), by lactate fermentation. The gut lumen is a dynamic environment with fluctuating nutrient levels, so the microbes present shifting growth rates and significant variations of gene expression. The current knowledge of lactate metabolism by Veillonella has focused on log phase growth. However, the gut microbes are mainly in the stationary phase. In this study, we investigated the transcriptomes and major metabolites of Veillonella dispar ATCC 17748T during growth from log to stationary phases with lactate as the main carbon source. Our results revealed that V. dispar reprogrammed its lactate metabolism during the stationary phase. Lactate catabolic activity and propionate production were significantly decreased during the early stationary phase but were partially restored during the stationary phase. The propionate/acetate production ratio was lowered from 1.5 during the log phase to 0.9 during the stationary phase. Pyruvate secretion was also greatly decreased during the stationary phase. Furthermore, we have demonstrated that the gene expression of V. dispar is reprogrammed during growth, as evidenced by the distinct transcriptomes present during the log, early stationary, and stationary phases. In particular, propionate metabolism (the propanediol pathway) was downregulated during the early stationary phase, which explains the decrease in propionate production during the stationary phase. The fluctuations in lactate fermentation during the stationary phase and the associated gene regulation expand our understanding of the metabolism of commensal anaerobes in changing environments. IMPORTANCE Short-chain fatty acids produced by gut commensal bacteria play an important role in human physiology. Gut Veillonella and the metabolites acetate and propionate, produced by lactate fermentation, are associated with human health. Most gut bacteria in humans are in the stationary phase. Lactate metabolism by Veillonella spp. during the stationary phase is poorly understood and was therefore the focus of the study. To this end, we used a commensal anaerobic bacterium and explored its short-chain fatty acid production and gene regulation in order to provide a better understanding of lactate metabolism dynamics during nutrient limitation.

Biofilm-based delivery approaches and specific enrichment strategies of probiotics in the human gut

The use of probiotics has been one of the effective strategies to restructure perturbed human gut microbiota following a disease or metabolic disorder. One of the biggest challenges associated with the use of probiotic-based gut modulation strategies is to keep the probiotic cells viable and stable during the gastrointestinal transit. Biofilm-based probiotics delivery approaches have emerged as fascinating modes of probiotic delivery in which probiotics show significantly greater tolerance and biotherapeutic potential, and interestingly probiotic biofilms can be developed on food-grade surfaces too, which is ideal for the growth and proliferation of bacterial cells for incorporation into food matrices. In addition, biofilms can be further encapsulated with food-grade materials or with bacterial self-produced biofilms. This review presents a newly emerging and unprecedently discussed techniques for the safe delivery of probiotics based on biofilms and further discusses newly emerging prebiotic materials which target specific gut microbiota groups for growth and proliferation.

Metagenomic analysis reveals crosstalk between gut microbiota and glucose-lowering drugs targeting the gastrointestinal tract in Chinese patients with type 2 diabetes: a 6 month, two-arm randomised trial

AIMS/HYPOTHESIS

The use of oral glucose-lowering drugs, particularly those designed to target the gut ecosystem, is often observed in association with altered gut microbial composition or functional capacity in individuals with type 2 diabetes. The gut microbiota, in turn, plays crucial roles in the modulation of drug efficacy. We aimed to assess the impacts of acarbose and vildagliptin on human gut microbiota and the relationships between pre-treatment gut microbiota and therapeutic responses.

METHODS

This was a randomised, open-labelled, two-arm trial in treatment-naive type 2 diabetes patients conducted in Beijing between December 2016 and December 2017. One hundred participants with overweight/obesity and newly diagnosed type 2 diabetes were recruited from the Pinggu Hospital and randomly assigned to the acarbose (n=50) or vildagliptin (n=50) group using sealed envelopes. The treatment period was 6 months. Blood, faecal samples and visceral fat data from computed tomography images were collected before and after treatments to measure therapeutic outcomes and gut microbiota. Metagenomic datasets from a previous type 2 diabetes cohort receiving acarbose or glipizide for 3 months were downloaded and processed. Statistical analyses were applied to identify the treatment-related changes in clinical variables, gut microbiota and associations.

RESULTS

Ninety-two participants were analysed. After 6 months of acarbose (n=44) or vildagliptin (n=48) monotherapy, both groups achieved significant reductions in HbA_1c (from 60 to 46 mmol/mol [from 7.65% to 6.40%] in the acarbose group and from 59 to 44 mmol/mol [from 7.55% to 6.20%] in the vildagliptin group) and visceral fat areas (all adjusted p values for pre-post comparisons <0.05). Both arms showed drug-specific and shared changes in relative abundances of multiple gut microbial species and pathways, especially the common reductions in Bacteroidetes species. Three months and 6 months of acarbose-induced changes in microbial composition were highly similar in type 2 diabetes patients from the two independent studies. Vildagliptin treatment significantly enhanced fasting active glucagon-like peptide-1 (GLP-1) levels. Baseline gut microbiota, rather than baseline GLP-1 levels, were strongly associated with GLP-1 response to vildagliptin, and to a lesser extent with GLP-1 response to acarbose.

CONCLUSIONS/INTERPRETATION

This study reveals common microbial responses in type 2 diabetes patients treated with two glucose-lowering drugs targeting the gut differently and acceptable performance of baseline gut microbiota in classifying individuals with different GLP-1 responses to vildagliptin. Our findings highlight bidirectional interactions between gut microbiota and glucose-lowering drugs.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02999841 FUNDING: National Key Research and Development Project: 2016YFC1304901.

The human gut microbiota and glucose metabolism: a scoping review of key bacteria and the potential role of SCFAs

The gut microbiota plays a fundamental role in human nutrition and metabolism and may have direct implications for type 2 diabetes and associated preconditions. An improved understanding of relations between human gut microbiota and glucose metabolism could lead to novel opportunities for type 2 diabetes prevention, but human observational studies reporting on such findings have not been extensively reviewed. Here, we review the literature on associations between gut microbiota and markers and stages of glucose dysregulation and insulin resistance in healthy adults and in adults with metabolic disease and risk factors. We present the current evidence for identified key bacteria and their potential roles in glucose metabolism independent of overweight, obesity, and metabolic drugs. We provide support for SCFAs mediating such effects and discuss the role of diet, as well as metabolites derived from diet and gut microbiota interactions. From 5983 initially identified PubMed records, 45 original studies were eligible and reviewed. α Diversity and 45 bacterial taxa were associated with selected outcomes. Six taxa were most frequently associated with glucose metabolism: Akkermansia muciniphila, Bifidobacterium longum, Clostridium leptum group, Faecalibacterium prausnitzii, and Faecalibacterium (inversely associated) and Dorea (directly associated). For Dorea and A. muciniphila, associations were independent of metabolic drugs and body measures. For A. muciniphila and F. prausnitzii, limited evidence supported SCFA mediation of potential effects on glucose metabolism. We conclude that observational studies applying metagenomics sequencing to identify species-level relations are warranted, as are studies accounting for confounding factors and investigating SCFA and postprandial glucose metabolism. Such advances in the field will, together with mechanistic and prospective studies and investigations into diet-gut microbiota interactions, have the potential to bring critical insight into roles of gut microbiota and microbial metabolites in human glucose metabolism and to contribute toward the development of novel prevention strategies for type 2 diabetes, including precision nutrition.

Gut Microbiota Composition in Prediabetes and Newly Diagnosed Type 2 Diabetes: A Systematic Review of Observational Studies

Evidence of gut microbiota involvement in regulating glucose metabolism and type 2 diabetes mellitus (T2DM) progression is accumulating. The understanding of microbial dysbiosis and specific alterations of gut microbiota composition that occur during the early stages of glucose intolerance, unperturbed by anti-diabetic medications, is especially essential. Hence, this systematic review was conducted to summarise the existing evidence related to microbiota composition and diversity in individuals with prediabetes (preDM) and individuals newly diagnosed with T2DM (newDM) in comparison to individuals with normal glucose tolerance (nonDM). A systematic search of the PubMed, MEDLINE and CINAHL databases were conducted from inception to February 2021 supplemented with manual searches of the list of references. The primary keywords of “type 2 diabetes”, “prediabetes”, “newly-diagnosed” and “gut microbiota” were used. Observational studies that conducted analysis of the gut microbiota of respondents with preDM and newDM were included. The quality of the studies was assessed using the modified Newcastle-Ottawa scale by independent reviewers. A total of 18 studies (5,489 participants) were included. Low gut microbial diversity was generally observed in preDM and newDM when compared to nonDM. Differences in gut microbiota composition between the disease groups and nonDM were inconsistent across the included studies. Four out of the 18 studies found increased abundance of phylum Firmicutes along with decreased abundance of Bacteroidetes in newDM. At the genus/species levels, decreased abundance of Faecalibacterium prausnitzii, Roseburia, Dialister, Flavonifractor, Alistipes, Haemophilus and Akkermansia muciniphila and increased abundance of Lactobacillus, Streptococcus, Escherichia, Veillonella and Collinsella were observed in the disease groups in at least two studies. Lactobacillus was also found to positively correlate with fasting plasma glucose (FPG), HbA1c and/or homeostatic assessment of insulin resistance (HOMA-IR) in four studies. This renders a need for further investigations on the species/strain-specific role of endogenously present Lactobacillus in glucose regulation mechanism and T2DM disease progression. Differences in dietary intake caused significant variation in specific bacterial abundances. More studies are needed to establish more consistent associations, between clinical biomarkers or dietary intake and specific gut bacterial composition in prediabetes and early T2DM.

Alterations of the Gut Microbiota in Patients with Diabetic Nephropathy

Diabetic nephropathy (DN) is the primary cause of end-stage renal disease. Accumulating studies have implied a critical role for the gut microbiota in diabetes mellitus (DM) and DN. However, the precise roles and regulatory mechanisms of the gut microbiota in the pathogenesis of DN remain largely unclear. In this study, metagenomics sequencing was performed using fecal samples from healthy controls (CON) and type 2 diabetes mellitus (T2DM) patients with or without DN. Fresh fecal samples from 15 T2DM patients without DN, 15 DN patients, and 15 age-, gender-, and body mass index (BMI)-matched healthy controls were collected. The compositions and potential functions of the gut microbiota were estimated. Although no difference of gut microbiota α and β diversity was observed between the CON, T2DM, and DN groups, the relative abundances of butyrate-producing bacteria (Clostridium, Eubacterium, and Roseburia intestinalis) and potential probiotics (Lachnospira and Intestinibacter) were significantly reduced in T2DM and DN patients. Besides, Bacteroides stercoris was significantly enriched in fecal samples from patients with DN. Moreover, Clostridium sp. 26_22 was negatively associated with serum creatinine (P < 0.05). DN patients could be accurately distinguished from CON by Clostridium sp. CAG_768 (area under the curve [AUC] = 0.941), Bacteroides propionicifaciens (AUC = 0.905), and Clostridium sp. CAG_715 (AUC = 0.908). DN patients could be accurately distinguished from T2DM patients by Pseudomonadales, Fusobacterium varium, and Prevotella sp. MSX73 (AUC = 0.889). Regarding the potential bacterial functions of the gut microbiota, the citrate cycle, base excision repair, histidine metabolism, lipoic acid metabolism, and bile acid biosynthesis were enriched in DN patients, while selenium metabolism and branched-chain amino acid biosynthesis were decreased in DN patients.

IMPORTANCE Gut microbiota imbalance is found in fecal samples from DN patients, in which Roseburia intestinalis is significantly decreased, while Bacteroides stercoris is increased. There is a significant correlation between gut microbiota imbalance and clinical indexes related to lipid metabolism, glucose metabolism, and renal function. The gut microbiota may be predictive factors for the development and progression of DN, although further studies are warranted to illustrate their regulatory mechanisms.

Modulation of Gut Microbiota and Metabolites by Berberine in Treating Mice With Disturbances in Glucose and Lipid Metabolism

Introduction: Glucose and lipid metabolism disturbances has become the third major disease after cancer and cardio-cerebrovascular diseases. Emerging evidence shows that berberine can effectively intervene glucose and lipid metabolism disturbances, but the underlying mechanisms of this remain unclear. To investigate this issue, we performed metagenomic and metabolomic analysis in a group of normal mice (the NC group), mice with disturbances in glucose and lipid metabolism (the MC group) and mice with disturbances in glucose and lipid metabolism after berberine intervention (the BER group).

Result: Firstly, analysis of the clinical indicators revealed that berberine significantly improved the blood glucose and blood lipid of the host. The fasting blood glucose level decreased by approximately 30% in the BER group after 8 weeks and the oral glucose tolerance test showed that the blood glucose level of the BER group was lower than that of the MC group at any time. Besides, berberine significantly reduced body weight, total plasma cholesterol and triglyceride. Secondly, compared to the NC group, we found dramatically decreased microbial richness and diversity in the MC group and BER group. Thirdly, LDA effect size suggested that berberine significantly altered the overall gut microbiota structure and enriched many bacteria, including Akkermansia (p < 0.01), Eubacterium (p < 0.01) and Ruminococcus (p < 0.01). Fourthly, the metabolomic analysis suggested that there were significant differences in the metabolomics signature of each group. For example, isoleucine (p < 0.01), phenylalanine (p < 0.05), and arbutin (p < 0.05) significantly increased in the MC group, and berberine intervention significantly reduced them. The arbutin content in the BER group was even lower than that in the NC group. Fifthly, by combined analysis of metagenomics and metabolomics, we observed that there were significantly negative correlations between the reduced faecal metabolites (e.g., arbutin) in the BER group and the enriched gut microbiota (e.g., Eubacterium and Ruminococcus) (p < 0.05). Finally, the correlation analysis between gut microbiota and clinical indices indicated that the bacteria (e.g., Eubacterium) enriched in the BER group were negatively associated with the above-mentioned clinical indices (p < 0.05).

Conclusion: Overall, our results describe that the changes of gut microbiota and metabolites are associated with berberine improving glucose and lipid metabolism disturbances.

Dietary regulations for microbiota dysbiosis among post-menopausal women with type 2 diabetes

Type 2 diabetes (T2D) and T2D-associated comorbidities, such as obesity, are serious universally prevalent health issues among post-menopausal women. Menopause is an unavoidable condition characterized by the depletion of estrogen, a gonadotropic hormone responsible for secondary sexual characteristics in women. In addition to sexual dimorphism, estrogen also participates in glucose-lipid homeostasis, and estrogen depletion is associated with insulin resistance in the female body. Estrogen level in the gut also regulates the microbiota composition, and even conjugated estrogen is actively metabolized by the estrobolome to maintain insulin levels. Moreover, post-menopausal gut microbiota is different from the pre-menopausal gut microbiota, as it is less diverse and lacks the mucolytic Akkermansia and short-chain fatty acid (SCFA) producers such as Faecalibacterium and Roseburia. Through various metabolites (SCFAs, secondary bile acid, and serotonin), the gut microbiota plays a significant role in regulating glucose homeostasis, oxidative stress, and T2D-associated pro-inflammatory cytokines (IL-1, IL-6). While gut dysbiosis is common among post-menopausal women, dietary interventions such as probiotics, prebiotics, and synbiotics can ease post-menopausal gut dysbiosis. The objective of this review is to understand the relationship between post-menopausal gut dysbiosis and T2D-associated factors. Additionally, the study also provided dietary recommendations to avoid T2D progression among post-menopausal women.

Antidiabetic Effects of Pediococcus acidilactici pA1c on HFD-Induced Mice

Prediabetes (PreD), which is associated with impaired glucose tolerance and fasting blood glucose, is a potential risk factor for type 2 diabetes mellitus (T2D). Growing evidence suggests the role of the gastrointestinal microbiota in both PreD and T2D, which opens the possibility for a novel nutritional approach, based on probiotics, for improving glucose regulation and delaying disease progression of PreD to T2D. In this light, the present study aimed to assess the antidiabetic properties of Pediococcus acidilactici (pA1c) in a murine model of high-fat diet (HFD)-induced T2D. For that purpose, C57BL/6 mice were given HFD enriched with either probiotic (1 × 10¹⁰ CFU/day) or placebo for 12 weeks. We determined body weight, fasting blood glucose, glucose tolerance, HOMA-IR and HOMA-β index, C-peptide, GLP-1, leptin, and lipid profile. We also measured hepatic gene expression (G6P, PEPCK, GCK, IL-1β, and IL-6) and examined pancreatic and intestinal histology (% of GLP-1⁺ cells, % of goblet cells and villus length). We found that pA1c supplementation significantly attenuated body weight gain, mitigated glucose dysregulation by reducing fasting blood glucose levels, glucose tolerance test, leptin levels, and insulin resistance, increased C-peptide and GLP-1 levels, enhanced pancreatic function, and improved intestinal histology. These findings indicate that pA1c improved HFD-induced T2D derived insulin resistance and intestinal histology, as well as protected from body weight increase. Together, our study proposes that pA1c may be a promising new dietary management strategy to improve metabolic disorders in PreD and T2D.

Characteristics of the Intestinal Microorganisms in Middle-Aged and Elderly Patients: Effects of Smoking

Introduction: Smoking affects the occurrence and development of many diseases. We attempt to study the structure of intestinal flora in the middle-aged and elderly population as well as how smoking affects the intestinal flora. Methods: We collected population information, biochemical indicators, and patient feces from 188 middle-aged and elderly male patients, and their feces were tested for the 16S rRNA gene of intestinal flora. Results: We performed a cluster analysis on the intestinal structure of the included population and found that there was a significant difference in the number of smokers between each group (p = 0.011). Subsequently, the microbiological diversity analysis of current smokers and nonsmokers was carried out. The results indicated that there was a significant difference in species composition between the two groups (p = 0.029). Through the analysis on LEfSe differential bacteria, it was found that in current smoking patients, the abundances of the genus Bifidobacterium and the genus Coprobacillus were less, while the abundances of the genera Shigella, Paraprevotella, Burkholderia, Sutterella, Megamonas, and p-75-a5 under the family level of Erysipelotrichaceae were slightly high. We analyzed the correlation between the abundances of these eight different bacteria and clinical indicators. The results revealed the following: the abundance of the genus Bifidobacterium was negatively correlated with fasting blood glucose (r = -0.198, p = 0.006) and positively correlated with uric acid (r = 0.207, p = 0.004) and total bilirubin (r = 0.175, p = 0.017); Shigella bacteria were positively correlated with fasting blood glucose (r = 0.160, p = 0.028) and uric acid (r = 0.153, p = 0.036) levels; the genus Paraprevotella and BMI (r = -0.172, p = 0.018) are negatively correlated; the abundance of the genus Burkholderia was positively correlated with γ-glutamyltransferase (r = 0.146, p = 0.045) levels; Sutterella was correlated with fasting blood glucose (r = 0.143, p = 0.05) and creatinine level (r = -0.16, p = 0.027), which was positively correlated with fasting blood glucose and negatively correlated with creatinine. Conclusions: In middle-aged and elderly patients with cardiovascular disease, smoking can reduce the abundance of Bifidobacterium, while the abundances of some negative bacteria such as Burkholderia, Sutterella, and Megamonas increase.

Gut Microbiome-Based Diagnostic Model to Predict Diabetes Mellitus

The aim of this study was to determine the diversity of intestinal microflora and its correlation with clinical parameters in diabetic patients and healthy subjects and to assess the importance of intestinal flora in patients with diabetes. Forty-four patients with diabetes were included. The control group included 47 healthy people. Their data, biochemical indicators and results from 16S rRNA sequencing of their fecal samples were collected. Compared with the healthy population, the intestinal flora of the diabetic patients was obviously abnormal. Within the diabetes group, the abundances of the genera Faecalibacterium, Prevotella, and Roseburia were higher, and the abundances of the genera Shigella and Bifidobacterium were lower. In the correlation analysis between bacteria and clinical indicators, it was found that the genera Veillonella and unclassified_Enterobacteriaceae were negatively related to blood glucose, while the genera Phascolarctobacterium, unidentified_Bacteroidales and Prevotella were significantly positively correlated with fasting blood glucose. Twelve microbial markers were detected in the random forest model, and the area under the curve (AUC) was 84.1%. This index was greater than the diagnostic effect of fasting blood glucose. This was also supported by the joint diagnostic model of microorganisms and clinical indicators. In addition, the intestinal flora significantly improved the diagnosis of diabetes. In conclusion, it can be concluded from these results that intestinal flora is essential for the occurrence and development of diabetes, which seems to be as important as blood glucose itself.

Abbreviations: PCoA: principal coordinate analysis; NMDS: non econometric multidimensional scaling analysis; LEfSe: linear discriminant analysis effect size; LDA: linear discriminant analysis; POD: probability of disease; BMI: body mass index; DCA: decision curve analysis