Distinct gut metagenomics and metaproteomics signatures in prediabetics and treatment-naïve type 2 diabetics

The central role of the gut microbiota in the pathophysiology and management of type 2 diabetes

The inhabitants of our intestines, collectively called the gut microbiome, comprise fungi, viruses, and bacterial strains. These microorganisms are involved in the fermentation of dietary compounds and the regulation of our adaptive and innate immune systems. Less known is the reciprocal interaction between the gut microbiota and type 2 diabetes mellitus (T2DM), as well as their role in modifying therapies to reduce associated morbidity and mortality. In this review, we aim to discuss the existing literature on gut microbial strains and their diet-derived metabolites involved in T2DM. We also explore the potential diagnostics and therapeutic avenues the gut microbiota presents for targeted T2DM management. Personalized treatment plans, driven by diet and medication based on the patient's microbiome and clinical markers, could optimize therapy.

Quantification and Correlation Analysis of Bacteroides Species with Diabetes-Related Amino Acids in Individuals with Prediabetes and Type 2 Diabetes Mellitus

Background: The relationship between gut microbiota and diabetes-related amino acids significantly impacts insulin resistance and obesity. We aimed to quantify two Bacteroidetes species and their correlation with branched-chain amino acids, aromatic amino acids, and glutamate in prediabetes (preDM) and type 2 diabetes mellitus (T2DM). Methods: Fecal samples were collected from 68 participants, including 21 with T2DM, 23 with preDM, and 24 with normal glycemic tolerance (NGT). The abundance of Bacteroides vulgatus and Bacteroides thetaiotaomicron was determined by quantitative real-time polymerase chain reaction. Plasma amino acid measurements were performed using liquid chromatography coupled with tandem mass spectrometry. Results: The quantities of B. vulgatus and B. thetaiotaomicron were reduced in preDM and T2DM than in NGT subjects, but it was not statistically significant. The concentrations of leucine, valine, and tyrosine were significantly higher in preDM and T2DM than in NGT subjects (P < 0.05). A negative correlation was observed between B. thetaiotaomicron abundance and two aromatic amino acids (tyrosine, r = -0.28, P = 0.04; phenylalanine, r = -0.26, P = 0.05). Conclusions: These findings imply that, since gut microbiota varies throughout ethnic groups, further research with many participants will be required to determine the abundance of B. vulgatus and B. thetaiotaomicron in preDM and T2DM and their association with diabetes-related amino acids.

Strain-specific gut microbial signatures in type 2 diabetes identified in a cross-cohort analysis of 8,117 metagenomes

The association of gut microbial features with type 2 diabetes (T2D) has been inconsistent due in part to the complexity of this disease and variation in study design. Even in cases in which individual microbial species have been associated with T2D, mechanisms have been unable to be attributed to these associations based on specific microbial strains. We conducted a comprehensive study of the T2D microbiome, analyzing 8,117 shotgun metagenomes from 10 cohorts of individuals with T2D, prediabetes, and normoglycemic status in the United States, Europe, Israel and China. Dysbiosis in 19 phylogenetically diverse species was associated with T2D (false discovery rate < 0.10), for example, enriched Clostridium bolteae and depleted Butyrivibrio crossotus. These microorganisms also contributed to community-level functional changes potentially underlying T2D pathogenesis, for example, perturbations in glucose metabolism. Our study identifies within-species phylogenetic diversity for strains of 27 species that explain inter-individual differences in T2D risk, such as Eubacterium rectale. In some cases, these were explained by strain-specific gene carriage, including loci involved in various mechanisms of horizontal gene transfer and novel biological processes underlying metabolic risk, for example, quorum sensing. In summary, our study provides robust cross-cohort microbial signatures in a strain-resolved manner and offers new mechanistic insights into T2D.

Benchmarking low- and high-throughput protein cleanup and digestion methods for human fecal metaproteomics

The application of fecal metaproteomics to large-scale studies of the gut microbiota requires high-throughput analysis and standardized experimental protocols. Although high-throughput protein cleanup and digestion methods are increasingly used in shotgun proteomics, no studies have yet critically compared such protocols using human fecal samples. In this study, human fecal protein extracts were processed using several different protocols based on three main approaches: filter-aided sample preparation (FASP), solid-phase-enhanced sample preparation (SP3), and suspension trapping (S-Trap). These protocols were applied in both low-throughput (i.e., microtube-based) and high-throughput (i.e., microplate-based) formats, and the final peptide mixtures were analyzed by liquid chromatography coupled to high-resolution tandem mass spectrometry. The FASP-based methods and the combination of SP3 with in-StageTips (iST) yielded the best results in terms of the number of peptides identified through a database search against gut microbiome and human sequences. The efficiency of protein digestion, the ability to preserve hydrophobic peptides and high molecular weight proteins, and the reproducibility of the methods were also evaluated for the different protocols. Other relevant variables, including interindividual variability of stool, duration of protocols, and total costs, were considered and discussed. In conclusion, the data presented here can significantly contribute to the optimization and standardization of sample preparation protocols in human fecal metaproteomics. Furthermore, the promising results obtained with the high-throughput methods are expected to encourage the development of automated workflows and their application to large-scale gut microbiome studies.IMPORTANCEFecal metaproteomics is an experimental approach that allows the investigation of gut microbial functions, which are involved in many different physiological and pathological processes. Standardization and automation of sample preparation protocols in fecal metaproteomics are essential for its application in large-scale studies. Here, we comparatively evaluated different methods, available also in a high-throughput format, enabling two key steps of the metaproteomics analytical workflow (namely, protein cleanup and digestion). The results of our study provide critical information that may be useful for the optimization of metaproteomics experimental pipelines and their implementation in laboratory automation systems.

Association between gut microbiota and diabetic nephropathy: a two-sample Mendelian randomization study

Background

To clarify the causal relationship between gut microbiota and diabetic nephropathy (DN), we employed Mendelian randomization (MR). Despite a strong correlation observed, establishing causality is still unclear. By utilizing MR, we aimed to investigate this relationship further and shed light on the potential causal effect of gut microbiota on DN.

Methods

Genetic instrumental variables for gut microbiota were obtained from a GWAS with 18340 participants. DN summary statistics (1032 cases, 451248 controls) were sourced from a separate GWAS. The primary analysis used the inverse-variance weighted (IVW) method. Reverse MR analysis was conducted to explore reverse causation. Rigorous sensitivity analyses were performed to ensure the resilience and reliability of the study's findings.

Results

We found two bacterial traits associated with an increased risk of DN: genus LachnospiraceaeUCG008 (OR: 1.4210; 95% CI: 1.0450, 1.9322; p = 0.0250) and genus Terrisporobacter (OR: 1.9716; 95% CI: 1.2040, 3.2285; p = 0.0070). Additionally, phylum Proteobacteria (OR: 0.4394; 95% CI: 0.2721, 0.7096; p = 0.0008) and genus Dialister (OR: 0.4841; 95% CI: 0.3171, 0.7390; p = 0.0008) were protective against DN. Sensitivity analyses consistently supported these results. In the reverse MR analysis, no statistically significant associations were observed between DN and these four bacterial traits.

Conclusions

Our analyses confirmed a potential causal relationship between certain gut microbiota taxa and the risk of DN. However, additional studies are required to elucidate the underlying mechanisms through which gut microbiota influences the development of DN.

Bacterial Growth Modulatory Effects of Two Branched-Chain Hydroxy Acids and Their Production Level by Gut Microbiota

Branched-chain hydroxy acids (BCHAs), produced by lactic acid bacteria, have recently been suggested as bioactive compounds contributing to the systemic metabolism and modulation of the gut microbiome. However, the relationship between BCHAs and gut microbiome remains unclear. In this study, we investigated the effects of BCHAs on the growth of seven different families in the gut microbiota. Based on in vitro screening, both 2-hydroxyisovaleric acid (HIVA) and 2-hydroxyisocaproic acid (HICA) stimulated the growth of Lactobacillaceae and Bifidobacteriaceae, with HIVA showing a significant growth promotion. Additionally, we observed not only the growth promotion of probiotic Lactobacillaceae strains but also growth inhibition of pathogenic B. fragilis in a dosedependent manner. The production of HIVA and HICA varied depending on the family of the gut microbiota and was relatively high in case of Lactobacillaceae and Lachnosporaceae. Furthermore, HIVA and HICA production by each strain positively correlated with their growth variation. These results demonstrated gut microbiota-derived BCHAs as active metabolites that have bacterial growth modulatory effects. We suggest that BCHAs can be utilized as active metabolites, potentially contributing to the treatment of diseases associated with gut dysbiosis.

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.

A genomic compendium of cultivated human gut fungi characterizes the gut mycobiome and its relevance to common diseases

The gut fungal community represents an essential element of human health, yet its functional and metabolic potential remains insufficiently elucidated, largely due to the limited availability of reference genomes. To address this gap, we presented the cultivated gut fungi (CGF) catalog, encompassing 760 fungal genomes derived from the feces of healthy individuals. This catalog comprises 206 species spanning 48 families, including 69 species previously unidentified. We explored the functional and metabolic attributes of the CGF species and utilized this catalog to construct a phylogenetic representation of the gut mycobiome by analyzing over 11,000 fecal metagenomes from Chinese and non-Chinese populations. Moreover, we identified significant common disease-related variations in gut mycobiome composition and corroborated the associations between fungal signatures and inflammatory bowel disease (IBD) through animal experimentation. These resources and findings substantially enrich our understanding of the biological diversity and disease relevance of the human gut mycobiome.

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.

Divergent age-associated and metabolism-associated gut microbiome signatures modulate cardiovascular disease risk

Insight into associations between the gut microbiome with metabolism and aging is crucial for tailoring interventions to promote healthy longevity. In a discovery cohort of 10,207 individuals aged 40-93 years, we used 21 metabolic parameters to classify individuals into five clusters, termed metabolic multimorbidity clusters (MCs), that represent different metabolic subphenotypes. Compared to the cluster classified as metabolically healthy (MC1), clusters classified as 'obesity-related mixed' (MC4) and 'hyperglycemia' (MC5) exhibited an increased 11.1-year cardiovascular disease (CVD) risk by 75% (multivariable-adjusted hazard ratio (HR): 1.75, 95% confidence interval (CI): 1.43-2.14) and by 117% (2.17, 1.72-2.74), respectively. These associations were replicated in a second cohort of 9,061 individuals with a 10.0-year follow-up. Based on analysis of 4,491 shotgun fecal metagenomes from the discovery cohort, we found that gut microbial composition was associated with both MCs and age. Next, using 55 age-specific microbial species to capture biological age, we developed a gut microbial age (MA) metric, which was validated in four external cohorts comprising 4,425 metagenomic samples. Among individuals aged 60 years or older, the increased CVD risk associated with MC4 or MC5, as compared to MC1, MC2 or MC3, was exacerbated in individuals with high MA but diminished in individuals with low MA, independent of age, sex and other lifestyle and dietary factors. This pattern, in which younger MA appears to counteract the CVD risk attributable to metabolic dysfunction, implies a modulating role of MA in cardiovascular health for metabolically unhealthy older people.

Blap-6, a Novel Antifungal Peptide from the Chinese Medicinal Beetle Blaps rhynchopetera against Cryptococcus neoformans

Cryptococcus neoformans (C. neoformans) is a pathogenic fungus that can cause life-threatening meningitis, particularly in individuals with compromised immune systems. The current standard treatment involves the combination of amphotericin B and azole drugs, but this regimen often leads to inevitable toxicity in patients. Therefore, there is an urgent need to develop new antifungal drugs with improved safety profiles. We screened antimicrobial peptides from the hemolymph transcriptome of Blaps rhynchopetera (B. rhynchopetera), a folk Chinese medicine. We found an antimicrobial peptide named blap-6 that exhibited potent activity against bacteria and fungi. Blap-6 is composed of 17 amino acids (KRCRFRIYRWGFPRRRF), and it has excellent antifungal activity against C. neoformans, with a minimum inhibitory concentration (MIC) of 0.81 μM. Blap-6 exhibits strong antifungal kinetic characteristics. Mechanistic studies revealed that blap-6 exerts its antifungal activity by penetrating and disrupting the integrity of the fungal cell membrane. In addition to its direct antifungal effect, blap-6 showed strong biofilm inhibition and scavenging activity. Notably, the peptide exhibited low hemolytic and cytotoxicity to human cells and may be a potential candidate antimicrobial drug for fungal infection caused by C. neoformans.

Metabolic and inflammatory perturbation of diabetes associated gut dysbiosis in people living with and without HIV infection

BACKGROUND

Gut dysbiosis has been linked with both HIV infection and diabetes, but its interplay with metabolic and inflammatory responses in diabetes, particularly in the context of HIV infection, remains unclear.

METHODS

We first conducted a cross-sectional association analysis to characterize the gut microbial, circulating metabolite, and immune/inflammatory protein features associated with diabetes in up to 493 women (~ 146 with prevalent diabetes with 69.9% HIV +) of the Women's Interagency HIV Study. Prospective analyses were then conducted to determine associations of identified metabolites with incident diabetes over 12 years of follow-up in 694 participants (391 women from WIHS and 303 men from the Multicenter AIDS Cohort Study; 166 incident cases were recorded) with and without HIV infection. Mediation analyses were conducted to explore whether gut bacteria-diabetes associations are explained by altered metabolites and proteins.

RESULTS

Seven gut bacterial genera were identified to be associated with diabetes (FDR-q <  0.1), with positive associations for Shigella, Escherichia, Megasphaera, and Lactobacillus, and inverse associations for Adlercreutzia, Ruminococcus, and Intestinibacter. Importantly, the associations of most species, especially Adlercreutzia and Ruminococcus, were largely independent of antidiabetic medications use. Meanwhile, 18 proteins and 76 metabolites, including 3 microbially derived metabolites (trimethylamine N-oxide, phenylacetylglutamine (PAGln), imidazolepropionic acid (IMP)), 50 lipids (e.g., diradylglycerols (DGs) and triradylglycerols (TGs)) and 23 non-lipid metabolites, were associated with diabetes (FDR-q <  0.1), with the majority showing positive associations and more than half of them (59/76) associated with incident diabetes. In mediation analyses, several proteins, especially interleukin-18 receptor 1 and osteoprotegerin, IMP and PAGln partially mediate the observed bacterial genera-diabetes associations, particularly for those of Adlercreutzia and Escherichia. Many diabetes-associated metabolites and proteins were altered in HIV, but no effect modification on their associations with diabetes was observed by HIV.

CONCLUSION

Among individuals with and without HIV, multiple gut bacterial genera, blood metabolites, and proinflammatory proteins were associated with diabetes. The observed mediated effects by metabolites and proteins in genera-diabetes associations highlighted the potential involvement of inflammatory and metabolic perturbations in the link between gut dysbiosis and diabetes in the context of HIV infection.

RapidAIM 2.0: a high-throughput assay to study functional response of human gut microbiome to xenobiotics

Aim: Our gut microbiome has its own functionalities which can be modulated by various xenobiotic and biotic components. The development and application of a high-throughput functional screening approach of individual gut microbiomes accelerates drug discovery and our understanding of microbiome-drug interactions. We previously developed the rapid assay of individual microbiome (RapidAIM), which combined an optimized culturing model with metaproteomics to study gut microbiome responses to xenobiotics. In this study, we aim to incorporate automation and multiplexing techniques into RapidAIM to develop a high-throughput protocol. Methods: To develop a 2.0 version of RapidAIM, we automated the protein analysis protocol, and introduced a tandem mass tag (TMT) multiplexing technique. To demonstrate the typical outcome of the protocol, we used RapidAIM 2.0 to evaluate the effect of prebiotic kestose on ex vivo individual human gut microbiomes biobanked with five different workflows. Results: We describe the protocol of RapidAIM 2.0 with extensive details on stool sample collection, biobanking, in vitro culturing and stimulation, sample processing, metaproteomics measurement, and data analysis. The analysis depth of 5,014 ± 142 protein groups per multiplexed sample was achieved. A test on five biobanking methods using RapidAIM 2.0 showed the minimal effect of sample processing on live microbiota functional responses to kestose. Conclusions: Depth and reproducibility of RapidAIM 2.0 are comparable to previous manual label-free metaproteomic analyses. In the meantime, the protocol realizes culturing and sample preparation of 320 samples in six days, opening the door to extensively understanding the effects of xenobiotic and biotic factors on our internal ecology.

Signs of aging in midlife: physical function and sex differences in microbiota

Microbiota composition has been linked to physical activity, health measures, and biological age, but a shared profile has yet to be shown. The aim of this study was to examine the associations between microbiota composition and measures of function, such as a composite measure of physical capacity, and biological age in midlife, prior to onset of age-related diseases. Seventy healthy midlife individuals (age 44.58 ± 0.18) were examined cross-sectionally, and their gut-microbiota profile was characterized from stool samples using 16SrRNA gene sequencing. Biological age was measured using the Klemera-Doubal method and a composition of blood and physiological biomarkers. Physical capacity was calculated based on sex-standardized functional tests. We demonstrate that the women had significantly richer microbiota, p = 0.025; however, microbiota diversity was not linked with chronological age, biological age, or physical capacity for either women or men. Men had slightly greater β-diversity; however, β-diversity was positively associated with biological age and with physical capacity for women only (p = 0.01 and p = 0.04; respectively). For women, an increase in abundance of Roseburia faecis and Collinsella aerofaciens, as well as genus Ruminococcus and Dorea, was significantly associated with higher biological age and lower physical capacity; an increase in abundance of Akkermansia muciniphila and genera Bacteroides and Alistipes was associated with younger biological age and increased physical capacity. Differentially abundant taxa were also associated with non-communicable diseases. These findings suggest that microbiota composition is a potential mechanism linking physical capacity and health status; personalized probiotics may serve as a new means to support health-promoting interventions in midlife. Investigating additional factors underlying this link may facilitate the development of a more accurate method to estimate the rate of aging.

Integrative metagenomic and metabolomic analyses reveal the potential of gut microbiota to exacerbate acute pancreatitis

Early dysbiosis in the gut microbiota may contribute to the severity of acute pancreatitis (AP), however, a comprehensive understanding of the gut microbiome, potential pathobionts, and host metabolome in individuals with AP remains elusive. Hence, we employed fecal whole-metagenome shotgun sequencing in 82 AP patients and 115 matched healthy controls, complemented by untargeted serum metabolome and lipidome profiling in a subset of participants. Analyses of the gut microbiome in AP patients revealed reduced diversity, disrupted microbial functions, and altered abundance of 77 species, influenced by both etiology and severity. AP-enriched species, mostly potential pathobionts, correlated positively with host liver function and serum lipid indicators. Conversely, many AP-depleted species were short-chain fatty acid producers. Gut microflora changes were accompanied by shifts in the serum metabolome and lipidome. Specifically, certain gut species, like enriched Bilophila wadsworthia and depleted Bifidobacterium spp., appeared to contribute to elevated triglyceride levels in biliary or hyperlipidemic AP patients. Through culturing and whole-genome sequencing of bacterial isolates, we identified virulence factors and clinically relevant antibiotic resistance in patient-derived strains, suggesting a predisposition to opportunistic infections. Finally, our study demonstrated that gavage of specific pathobionts could exacerbate pancreatitis in a caerulein-treated mouse model. In conclusion, our comprehensive analysis sheds light on the gut microbiome and serum metabolome in AP, elucidating the role of pathobionts in disease progression. These insights offer valuable perspectives for etiologic diagnosis, prevention, and intervention in AP and related conditions.

High-throughput screening of the effects of 90 xenobiotics on the simplified human gut microbiota model (SIHUMIx): a metaproteomic and metabolomic study

The human gut microbiota is a complex microbial community with critical functions for the host, including the transformation of various chemicals. While effects on microorganisms has been evaluated using single-species models, their functional effects within more complex microbial communities remain unclear. In this study, we investigated the response of a simplified human gut microbiota model (SIHUMIx) cultivated in an in vitro bioreactor system in combination with 96 deep-well plates after exposure to 90 different xenobiotics, comprising 54 plant protection products and 36 food additives and dyes, at environmentally relevant concentrations. We employed metaproteomics and metabolomics to evaluate changes in bacterial abundances, the production of Short Chain Fatty Acids (SCFAs), and the regulation of metabolic pathways. Our findings unveiled significant changes induced by 23 out of 54 plant protection products and 28 out of 36 food additives across all three categories assessed. Notable highlights include azoxystrobin, fluroxypyr, and ethoxyquin causing a substantial reduction (log2FC < -0.5) in the concentrations of the primary SCFAs: acetate, butyrate, and propionate. Several food additives had significant effects on the relative abundances of bacterial species; for example, acid orange 7 and saccharin led to a 75% decrease in Clostridium butyricum, with saccharin causing an additional 2.5-fold increase in E. coli compared to the control. Furthermore, both groups exhibited up- and down-regulation of various pathways, including those related to the metabolism of amino acids such as histidine, valine, leucine, and isoleucine, as well as bacterial secretion systems and energy pathways like starch, sucrose, butanoate, and pyruvate metabolism. This research introduces an efficient in vitro technique that enables high-throughput screening of the structure and function of a simplified and well-defined human gut microbiota model against 90 chemicals using metaproteomics and metabolomics. We believe this approach will be instrumental in characterizing chemical-microbiota interactions especially important for regulatory chemical risk assessments.

Insoluble/soluble fraction ratio determines effects of dietary fiber on gut microbiota and serum metabolites in healthy mice

Both soluble dietary fiber (SDF) and insoluble dietary fiber (IDF) play pivotal roles in maintaining gut microbiota homeostasis; whether the effects of the different ratios of IDF and SDF are consistent remains unclear. Consequently, we selected SDFs and IDFs from six representative foods (apple, celery, kale, black fungus, oats, and soybeans) and formulated nine dietary fiber recipes composed of IDF and SDF with a ratio from 1 : 9 to 9 : 1 (NDFR) to compare their impact on microbial effects with healthy mice. We discovered that NDFR treatment decreased the abundance of Proteobacteria and the ratio of Firmicutes/Bacteroidetes at the phylum level. The α diversity and relative richness of Parabacteroides and Prevotella at the genus level showed an upward trend along with the ratio of IDF increasing, while the relative abundance of Akkermansia at the genus level and the production of acetic acid and propionic acid exhibited an increased trend along with the ratio of SDF increasing. The relative abundance of Parabacteroides and Prevotella in the I9S1DF group (the ratio of IDF and SDF was 9 : 1) was 1.72 times and 5.92 times higher than that in the I1S9DF group (the ratio of IDF and SDF was 1 : 9), respectively. The relative abundance of Akkermansia in the I1S9DF group was 17.18 times higher than that in the I9S1DF group. Moreover, a high ratio of SDF (SDF reaches 60% or more) enriched the glycerophospholipid metabolism pathway; however, a high ratio of IDF (IDF reaches 80% or more) regulated the tricarboxylic acid cycle. These findings are helpful in the development of dietary fiber supplements based on gut microbiota and metabolites.

Microbiome and metabolome dysbiosis analysis in impaired glucose tolerance for the prediction of progression to diabetes mellitus

Gut microbiota and circulating metabolite dysbiosis predate important pathological changes in glucose metabolic disorders; however, comprehensive studies on impaired glucose tolerance (IGT), a diabetes mellitus (DM) precursor, are lacking. Here, we perform metagenomic sequencing and metabolomics on 47 pairs of individuals with IGT and newly diagnosed DM and 46 controls with normal glucose tolerance (NGT); patients with IGT are followed up after 4 years for progression to DM. Analysis of baseline data reveals significant differences in gut microbiota and serum metabolites among the IGT, DM, and NGT groups. In addition, 13 types of gut microbiota and 17 types of circulating metabolites showed significant differences at baseline before IGT progressed to DM, including higher levels of Eggerthella unclassified, Coprobacillus unclassified, Clostridium ramosum, L-valine, L-norleucine, and L-isoleucine, and lower levels of Eubacterium eligens, Bacteroides faecis, Lachnospiraceae bacterium 3_1_46FAA, Alistipes senegalensis, Megaspaera elsdenii, Clostridium perfringens, α-linolenic acid, 10E,12Z-octadecadienoic acid, and dodecanoic acid. A random forest model based on differential intestinal microbiota and circulating metabolites can predict the progression from IGT to DM (AUC = 0.87). These results suggest that microbiome and metabolome dysbiosis occur in individuals with IGT and have important predictive values and potential for intervention in preventing IGT from progressing to DM.

Altered Gut Microbiota as a Potential Risk Factor for Coronary Artery Disease in Diabetes: A Two-Sample Bi-Directional Mendelian Randomization Study

The current body of research points to a notable correlation between an imbalance in gut microbiota and the development of type 2 diabetes mellitus (T2D) as well as its consequential ailment, coronary artery disease (CAD). The complexities underlying the association, especially in the context of diabetic coronary artery disease (DCAD), are not yet fully understood, and the causal links require further clarification. In this study, a bidirectional Mendelian randomization (MR) methodology was utilized to explore the causal relationships between gut microbiota, T2D, and CAD. By analyzing data from the DIAGRAM, GERA, UKB, FHS, and mibioGen cohorts and examining GWAS databases, we sought to uncover genetic variants linked to T2D, CAD, and variations in gut microbiota and metabolites, aiming to shed light on the potential mechanisms connecting gut microbiota with DCAD. Our investigation uncovered a marked causal link between the presence of Oxalobacter formigenes and an increased incidence of both T2D and CAD. Specifically, a ten-unit genetic predisposition towards T2D was found to be associated with a 6.1% higher probability of an increase in the Oxalobacteraceae family's presence (β = 0.061, 95% CI = 0.002-0.119). In a parallel finding, an augmented presence of Oxalobacter was related to an 8.2% heightened genetic likelihood of CAD (β = 0.082, 95% CI = 0.026-0.137). This evidence indicates a critical pathway by which T2D can potentially raise the risk of CAD via alterations in gut microbiota. Additionally, our analyses reveal a connection between CAD risk and Methanobacteria, thus providing fresh perspectives on the roles of TMAO and carnitine in the etiology of CAD. The data also suggest a direct causal relationship between increased levels of certain metabolites - proline, lysophosphatidylcholine, asparagine, and salicylurate - and the prevalence of both T2D and CAD. Sensitivity assessments reinforce the notion that changes in Oxalobacter formigenes could pose a risk for DCAD. There is also evidence to suggest that DCAD may, in turn, affect the gut microbiota's makeup. Notably, a surge in serum TMAO levels in individuals with CAD, coinciding with a reduced presence of methanogens, has been identified as a potentially significant factor for future examination.

A Narrative Review on Strategies for the Reversion of Prediabetes to Normoglycemia: Food Pyramid, Physical Activity, and Self-Monitoring Innovative Glucose Devices

In 2019, "Nutrition Therapy for Adults with Diabetes or Prediabetes: A Consensus Report" was published. This consensus report, however, did not provide an easy way to illustrate to subjects with prediabetes (SwPs) how to follow a correct dietary approach. The purpose of this review is to evaluate current evidence on optimum dietary treatment of SwPs and to provide a food pyramid for this population. The pyramid built shows that everyday consumption should consist of: whole-grain bread or potatoes eaten with their skins (for fiber and magnesium) and low glycemic index carbohydrates (GI < 55%) (three portions); fruit and vegetables (5 portions), in particular, green leafy vegetables (for fiber, magnesium, and polyphenols); EVO oil (almost 8 g); nuts (30 g, in particular, pistachios and almonds); three portions of dairy products (milk/yogurt: 300-400 g/day); mineral water (almost 1, 5 L/day for calcium intake); one glass of wine (125 mL); and three cups of coffee. Weekly portions should include fish (four portions), white meat (two portions), protein plant-based food (four portions), eggs (egg portions), and red/processed meats (once/week). At the top of the pyramid, there are two pennants: a green one means that SwPs need some personalized supplementation (if daily requirements cannot be satisfied through diet, vitamin D, omega-3, and vitamin B supplements), and a red one means there are some foods and factors that are banned (simple sugar, refined carbohydrates, and a sedentary lifestyle). Three to four times a week of aerobic and resistance exercises must be performed for 30-40 min. Finally, self-monitoring innovative salivary glucose devices could contribute to the reversion of prediabetes to normoglycemia.

Unveiling the potential pleiotropic effects of metformin in treating COVID-19: a comprehensive review

This review article explores the potential of metformin, a medication commonly used for type 2 diabetes, as an antiviral and anti-inflammatory agent in the context of coronavirus disease 2019 (COVID-19). Metformin has demonstrated inhibitory effects on the growth of SARS-CoV-2 in cell culture models and has shown promising results in reducing viral load and achieving undetectable viral levels in clinical trials. Additionally, metformin exhibits anti-inflammatory properties by reducing the production of pro-inflammatory cytokines and modulating immune cell function, which may help prevent cytokine storms associated with severe COVID-19. The drug's ability to regulate the balance between pro-inflammatory Th17 cells and anti-inflammatory Treg cells suggests its potential in mitigating inflammation and restoring T cell functionality. Furthermore, metformin's modulation of the gut microbiota, particularly changes in bacterial taxa and the production of short-chain fatty acids, may contribute to its therapeutic effects. The interplay between metformin, bile acids, the gut microbiome, glucagon-like peptide-1 secretion, and glycemic control has implications for the management of diabetes and potential interventions in COVID-19. By refreshing the current evidence, this review highlights the potential of metformin as a therapeutic option in the management of COVID-19, while also exploring its effects on the gut microbiome and immunometabolism.

Tracing the evolving dynamics and research hotspots of microbiota and immune microenvironment from the past to the new era

Gut microbiota can regulate many physiological processes within gastrointestinal tract and other distal sites. Dysbiosis may not only influence chronic diseases like the inflammatory bowel disease (IBD), metabolic disease, tumor and its therapeutic efficacy, but also deteriorate acute injuries. This article aims to review the documents in this field and summarize the research hotspots as well as developing processes. Gut microbiota and immune microenvironment-related documents from 1976 to 2022 were obtained from the Web of Science Core Collection database. Bibliometrics was used to assess the core authors and journals, most contributive countries and affiliations together with hotspots in this field and keyword co-occurrence analysis. Data were visualized to help comprehension. Nine hundred and twelve documents about gut microbiota and immune microenvironment were retrieved, and the annual publications increased gradually. The most productive author, country, and affiliation were "Zitvogel L," USA and "UNIV TEXAS MD ANDERSON CANC CTR," respectively. FRONTIERS IN IMMUNOLOGY, CANCERS, and INTERNATIONAL JOURNAL OF MOLECULAR SCIENCE were the periodicals with most publications. Keyword co-occurrence analysis identified three clusters, including gut microbiota, inflammation, and IBD. Combined with the visualized analysis of documents and keyword co-occurrence as well as literature reading, we recognized three key topics of gut microbiota: cancer and therapy; immunity, inflammation and IBD; acute injuries and metabolic diseases. This article revealed researches on gut microbiota and immune microenvironment were growing. More attention should be given to the latest hotspots like gut microbiota, inflammation, IBD, cancer and immunotherapy, acute traumas, and metabolic diseases.IMPORTANCEGut microbiota can regulate many physiological processes within gastrointestinal tract and other distal sites. Dysbiosis may not only influence chronic diseases like inflammatory bowel disease (IBD), metabolic disease, tumor and its therapeutic efficacy, but also deteriorate acute injuries. While the application of bibliometrics in the field of gut microbiota and immune microenvironment still remains blank, which focused more on the regulation of the gut microbiota on the immune microenvironment of different kinds of diseases. Here, we intended to review and summarize the presented documents in gut microbiota and immune microenvironment field by bibliometrics. And we revealed researches on gut microbiota and immune microenvironment were growing. More attention should be given to the latest hotspots like gut microbiota, inflammation, IBD, cancer and immunotherapy, acute traumas, and metabolic diseases.

Data-driven decision-making for precision diagnosis of digestive diseases

Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented opportunities for individualized precision medicine. However, traditional statistical methods cannot effectively process and utilize such big data. To meet this new challenge, machine learning algorithms have been developed and applied rapidly in recent years, which are capable of reducing dimensionality, extracting features, organizing data and forming automatable data-driven clinical decision systems. Data-driven clinical decision-making have promising applications in precision medicine and has been studied in digestive diseases, including early diagnosis and screening, molecular typing, staging and stratification of digestive malignancies, as well as precise diagnosis of Crohn's disease, auxiliary diagnosis of imaging and endoscopy, differential diagnosis of cystic lesions, etiology discrimination of acute abdominal pain, stratification of upper gastrointestinal bleeding (UGIB), and real-time diagnosis of esophageal motility function, showing good application prospects. Herein, we reviewed the recent progress of data-driven clinical decision making in precision diagnosis of digestive diseases and discussed the limitations of data-driven decision making after a brief introduction of methods for data-driven decision making.

Metabolic engineering of human gut microbiome: Recent developments and future perspectives

Many studies have demonstrated that the gut microbiota is associated with human health and disease. Manipulation of the gut microbiota, e.g. supplementation of probiotics, has been suggested to be feasible, but subject to limited therapeutic efficacy. To develop efficient microbiota-targeted diagnostic and therapeutic strategies, metabolic engineering has been applied to construct genetically modified probiotics and synthetic microbial consortia. This review mainly discusses commonly adopted strategies for metabolic engineering in the human gut microbiome, including the use of in silico, in vitro, or in vivo approaches for iterative design and construction of engineered probiotics or microbial consortia. Especially, we highlight how genome-scale metabolic models can be applied to advance our understanding of the gut microbiota. Also, we review the recent applications of metabolic engineering in gut microbiome studies as well as discuss important challenges and opportunities.

Investigating causal associations among gut microbiota, gut microbiota-derived metabolites, and gestational diabetes mellitus: a bidirectional Mendelian randomization study

BACKGROUND

Previous studies have shown that gut microbiota (GM) and gut microbiota-derived metabolites are associated with gestational diabetes mellitus (GDM). However, the causal associations need to be treated with caution due to confounding factors and reverse causation.

METHODS

This study obtained genetic variants from genome-wide association study including GM (N = 18,340), GM-derived metabolites (N = 7,824), and GDM (5,687 cases and 117,89 controls). To examine the causal association, several methods were utilized, including inverse variance weighted, maximum likelihood, weighted median, MR-Egger, and MR.RAPS. Additionally, reverse Mendelian Randomization (MR) analysis and multivariable MR were conducted to confirm the causal direction and account for potential confounders, respectively. Furthermore, sensitivity analyses were performed to identify any potential heterogeneity and horizontal pleiotropy.

RESULTS

Greater abundance of Collinsella was detected to increase the risk of GDM. Our study also found suggestive associations among Coprobacter, Olsenella, Lachnoclostridium, Prevotella9, Ruminococcus2, Oscillibacte, and Methanobrevibacter with GDM. Besides, eight GM-derived metabolites were found to be causally associated with GDM. For the phenylalanine metabolism pathway, phenylacetic acid was found to be related to the risk of GDM.

CONCLUSIONS

The study first used the MR approach to explore the causal associations among GM, GM-derived metabolites, and GDM. Our findings may contribute to the prevention and treatment strategies for GDM by targeting GM and metabolites, and offer novel insights into the underlying mechanism of the disease.

Expanding germ-organ theory: Understanding non-communicable diseases through enterobacterial translocation

Diverse microbial communities colonize different habitats of the human body, including gut, oral cavity, nasal cavity and tissues. These microbial communities are known as human microbiome, plays a vital role in maintaining the health. However, changes in the composition and functions of human microbiome can result in chronic low-grade inflammation, which can damage the epithelial cells and allows pathogens and their toxic metabolites to translocate into other organs such as the liver, heart, and kidneys, causing metabolic inflammation. This dysbiosis of human microbiome has been directly linked to the onset of several non-communicable diseases. Recent metabolomics studies have revealed that pathogens produce several uraemic toxins. These metabolites can serve as inter-kingdom signals, entering the circulatory system and altering host metabolism, thereby aggravating a variety of diseases. Interestingly, Enterobacteriaceae, a critical member of Proteobacteria, has been commonly associated with several non-communicable diseases, and the abundance of this family has been positively correlated with uraemic toxin production. Hence, this review provides a comprehensive overview of Enterobacterial translocation and their metabolites role in non-communicable diseases. This understanding may lead to the identification of novel biomarkers for each metabolic disease as well as the development of novel therapeutic drugs.

A bibliometric analysis of the global impact of metaproteomics research

Background

Metaproteomics is a subfield in meta-omics that is used to characterize the proteome of a microbial community. Despite its importance and the plethora of publications in different research area, scientists struggle to fully comprehend its functional impact on the study of microbiomes. In this study, bibliometric analyses are used to evaluate the current state of metaproteomic research globally as well as evaluate the specific contribution of Africa to this burgeoning research area. In this study, we use bibliometric analyses to evaluate the current state of metaproteomic research globally, identify research frontiers and hotspots, and further predict future trends in metaproteomics. The specific contribution of Africa to this research area was evaluated.

Methods

Relevant documents from 2004 to 2022 were extracted from the Scopus database. The documents were subjected to bibliometric analyses and visualization using VOS viewer and Biblioshiny package in R. Factors such as the trends in publication, country and institutional cooperation networks, leading scientific journals, author's productivity, and keywords analyses were conducted. The African publications were ranked using Field-Weighted Citation Impact (FWCI) scores.

Results

A total of 1,138 documents were included and the number of publications increased drastically from 2004 to 2022 with more publications (170) reported in 2021. In terms of publishers, Frontiers in Microbiology had the highest number of total publications (62). The United States of America (USA), Germany, China, and Canada, together with other European countries were the most productive. Institution-wise, the Helmholtz Zentrum für Umweltforschung, Germany had more publications while Max Plank Institute had the highest total collaborative link strength. Jehmlich N. was the most productive author whereas Hettich RL had the highest h-index of 63. Regarding Africa, only 2.2% of the overall publications were from the continent with more publication outputs from South Africa. More than half of the publications from the continent had an FWCI score ≥ 1.

Conclusion

The scientific outputs of metaproteomics are rapidly evolving with developed countries leading the way. Although Africa showed prospects for future progress, this could only be accelerated by providing funding, increased collaborations, and mentorship programs.

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.

The Implication of the Gut Microbiome in Heart Failure

Heart failure is a worldwide health problem with important consequences for the overall wellbeing of affected individuals as well as for the healthcare system. Over recent decades, numerous pieces of evidence have demonstrated that the associated gut microbiota represent an important component of human physiology and metabolic homeostasis, and can affect one's state of health or disease directly, or through their derived metabolites. The recent advances in human microbiome studies shed light on the relationship between the gut microbiota and the cardiovascular system, revealing its contribution to the development of heart failure-associated dysbiosis. HF has been linked to gut dysbiosis, low bacterial diversity, intestinal overgrowth of potentially pathogenic bacteria and a decrease in short chain fatty acids-producing bacteria. An increased intestinal permeability allowing microbial translocation and the passage of bacterial-derived metabolites into the bloodstream is associated with HF progression. A more insightful understanding of the interactions between the human gut microbiome, HF and the associated risk factors is mandatory for optimizing therapeutic strategies based on microbiota modulation and offering individualized treatment. The purpose of this review is to summarize the available data regarding the influence of gut bacterial communities and their derived metabolites on HF, in order to obtain a better understanding of this multi-layered complex relationship.

Evaluation of mulberry leaves’ hypoglycemic properties and hypoglycemic mechanisms

The effectiveness of herbal medicine in treating diabetes has grown in recent years, but the precise mechanism by which it does so is still unclear to both medical professionals and diabetics. In traditional Chinese medicine, mulberry leaf is used to treat inflammation, colds, and antiviral illnesses. Mulberry leaves are one of the herbs with many medicinal applications, and as mulberry leaf study grows, there is mounting evidence that these leaves also have potent anti-diabetic properties. The direct role of mulberry leaf as a natural remedy in the treatment of diabetes has been proven in several studies and clinical trials. However, because mulberry leaf is a more potent remedy for diabetes, a deeper understanding of how it works is required. The bioactive compounds flavonoids, alkaloids, polysaccharides, polyphenols, volatile oils, sterols, amino acids, and a variety of inorganic trace elements and vitamins, among others, have been found to be abundant in mulberry leaves. Among these compounds, flavonoids, alkaloids, polysaccharides, and polyphenols have a stronger link to diabetes. Of course, trace minerals and vitamins also contribute to blood sugar regulation. Inhibiting alpha glucosidase activity in the intestine, regulating lipid metabolism in the body, protecting pancreatic -cells, lowering insulin resistance, accelerating glucose uptake by target tissues, and improving oxidative stress levels in the body are some of the main therapeutic properties mentioned above. These mechanisms can effectively regulate blood glucose levels. The therapeutic effects of the bioactive compounds found in mulberry leaves on diabetes mellitus and their associated molecular mechanisms are the main topics of this paper’s overview of the state of the art in mulberry leaf research for the treatment of diabetes mellitus.

Targeting Lung-Gut Axis for Regulating Pollution Particle-Mediated Inflammation and Metabolic Disorders

Cigarette smoking (CS) or ambient particulate matter (PM) exposure is a risk factor for metabolic disorders, such as insulin resistance (IR), increased plasma triglycerides, hyperglycemia, and diabetes mellitus (DM); it can also cause gut microbiota dysbiosis. In smokers with metabolic disorders, CS cessation decreases the risks of serious pulmonary events, inflammation, and metabolic disorder. This review included recent studies examining the mechanisms underlying the effects of CS and PM on gut microbiota dysbiosis and metabolic disorder development; one of the potential mechanisms is the disruption of the lung-gut axis, leading to gut microbiota dysbiosis, intestinal dysfunction, systemic inflammation, and metabolic disease. Short-chain fatty acids (SCFAs) are the primary metabolites of gut bacteria, which are derived from the fermentation of dietary fibers. They activate G-protein-coupled receptor (GPCR) signaling, suppress histone deacetylase (HDAC) activity, and inhibit inflammation, facilitating the maintenance of gut health and biofunction. The aforementioned gut microbiota dysbiosis reduces SCFA levels. Treatment targeting SCFA/GPCR signaling may alleviate air pollution-associated inflammation and metabolic disorders, which involve lung-gut axis disruption.

High-Resolution Taxonomic Characterization Reveals Novel Human Microbial Strains with Potential as Risk Factors and Probiotics for Prediabetes and Type 2 Diabetes

Alterations in the composition of the gut microbiota is thought to play a key role in causing type 2 diabetes, yet is not fully understood, especially at the strain level. Here, we used long-read DNA sequencing technology of 16S-ITS-23S rRNA genes for high-resolution characterization of gut microbiota in the development of type 2 diabetes. Gut microbiota composition was characterized from fecal DNA from 47 participants divided into 4 cohorts based on glycemic control: normal glycemic control (healthy; n = 21), reversed prediabetes (prediabetes/healthy; n = 8), prediabetes (n = 8), or type 2 diabetes (n = 10). A total of 46 taxa were found to be possibly related to progression from healthy state to type 2 diabetes. Bacteroides coprophilus DSM 18228, Bifidobacterium pseudocatenulatum DSM 20438, and Bifidobacterium adolescentis ATCC 15703 could confer resistance to glucose intolerance. On the other hand, Odoribacter laneus YIT 12061 may be pathogenic as it was found to be more abundant in type 2 diabetes participants than other cohorts. This research increases our understanding of the structural modulation of gut microbiota in the pathogenesis of type 2 diabetes and highlights gut microbiota strains, with the potential for targeted opportunistic pathogen control or consideration for probiotic prophylaxis and treatment.

Adjunctive Probio-X Treatment Enhances the Therapeutic Effect of a Conventional Drug in Managing Type 2 Diabetes Mellitus by Promoting Short-Chain Fatty Acid-Producing Bacteria and Bile Acid Pathways

Metformin is a common drug for the management of type 2 diabetes mellitus; however, it causes various adverse gastrointestinal effects, especially after prolonged treatment. It is thus of interest to identify an adjuvant treatment that synergizes with the efficacy of metformin while mitigating its adverse effects. Since previous evidence supports that the gut microbiota is a target of metformin, this study investigated the beneficial effect and mechanism of the coadministration of probiotics with metformin in the management of type 2 diabetes mellitus by conducting a 3-month randomized, double-blind, placebo-controlled clinical trial (n = 27 and 21 in the probiotic and placebo groups, respectively, who completed the trial). Clinical results showed that the coadministration of probiotics with metformin significantly reduced glycated hemoglobin compared with metformin taken alone (P < 0.05). Metagenomic and metabolomic analyses showed that the coadministration of probiotics increased the abundance of gut short-chain fatty acid (SCFA)-producing bacteria and bile acids. Significantly or marginally more bile acids and related metabolites were detected in the probiotic group than in the placebo group postintervention. Taken together, the results of our study showed that the coadministration of probiotics with metformin synergized with the hypoglycemic effect in patients with type 2 diabetes mellitus, which was likely through modulating the gut microbiome and, subsequently, SCFA and bile acid metabolism. Our findings support that cotreatment with probiotics and metformin is beneficial to patients with type 2 diabetes mellitus. IMPORTANCE Metformin causes variable adverse gastrointestinal effects, especially after prolonged treatment. We found that cotreatment with Probio-X and metformin for the management of type 2 diabetes mellitus may promote gut SCFA-producing bacteria and the levels of specific bile acids, thus increasing the secretion of related gastrointestinal hormones and ultimately improving glucose homeostasis.

Microbiome epidemiology and association studies in human health

Studies of the human microbiome share both technical and conceptual similarities with genome-wide association studies and genetic epidemiology. However, the microbiome has many features that differ from genomes, such as its temporal and spatial variability, highly distinct genetic architecture and person-to-person variation. Moreover, there are various potential mechanisms by which distinct aspects of the human microbiome can relate to health outcomes. Recent advances, including next-generation sequencing and the proliferation of multi-omic data types, have enabled the exploration of the mechanisms that connect microbial communities to human health. Here, we review the ways in which features of the microbiome at various body sites can influence health outcomes, and we describe emerging opportunities and future directions for advanced microbiome epidemiology.

Dynamic network modeling of gut microbiota during Alzheimer's disease progression in mice

The intimate association between the gut microbiota (GM) and the central nervous system points to potential intervention strategies for neurological diseases. Nevertheless, there is currently no theoretical framework for selecting the window period and target bacteria for GM interventions owing to the complexity of the gut microecosystem. In this study, we constructed a complex network-based modeling approach to evaluate the topological features of the GM and infer the window period and bacterial candidates for GM interventions. We used Alzheimer's disease (AD) as an example and traced the GM dynamic changes in AD and wild-type mice at one, two, three, six, and nine months of age. The results revealed alterations of the topological features of the GM from a scale-free network into a random network during AD progression, indicating severe GM disequilibrium at the late stage of AD. Through stability and vulnerability assessments of the GM networks, we identified the third month after birth as the optimal window period for GM interventions in AD mice. Further computational simulations and robustness evaluations determined that the hub bacteria were potential candidates for GM interventions. Moreover, our GM functional analysis suggested that Lachnospiraceae UCG-001 - the hub and enriched bacterium in AD mice - was the keystone bacterium for GM interventions owing to its contributions to quinolinic acid synthesis. In conclusion, this study established a complex network-based modeling approach as a practical strategy for disease interventions from the perspective of the gut microecosystem.

Machine learning for data integration in human gut microbiome

Recent studies have demonstrated that gut microbiota plays critical roles in various human diseases. High-throughput technology has been widely applied to characterize the microbial ecosystems, which led to an explosion of different types of molecular profiling data, such as metagenomics, metatranscriptomics and metabolomics. For analysis of such data, machine learning algorithms have shown to be useful for identifying key molecular signatures, discovering potential patient stratifications, and particularly for generating models that can accurately predict phenotypes. In this review, we first discuss how dysbiosis of the intestinal microbiota is linked to human disease development and how potential modulation strategies of the gut microbial ecosystem can be used for disease treatment. In addition, we introduce categories and workflows of different machine learning approaches, and how they can be used to perform integrative analysis of multi-omics data. Finally, we review advances of machine learning in gut microbiome applications and discuss related challenges. Based on this we conclude that machine learning is very well suited for analysis of gut microbiome and that these approaches can be useful for development of gut microbe-targeted therapies, which ultimately can help in achieving personalized and precision medicine.

Potential of gut microbiota for lipopolysaccharide biosynthesis in European women with type 2 diabetes based on metagenome

The abnormal accumulation of lipopolysaccharide (LPS) plays a crucial role in promoting type 2 diabetes (T2D). However, the capability of the gut microbiota to produce LPS in patients with T2D is still unclear, and evidence characterizing the patterns of gut microbiota with LPS productivity remains rare. This study aimed to uncover the profiles of LPS-biosynthesis-related enzymes and pathways, and explore the potential of LPS-producing gut microbiota in T2D. The gut metagenomic sequencing data from a European female cohort with normal glucose tolerance or untreated T2D were analyzed in this study. The sequence search revealed that the relative abundance of the critical enzymes responsible for LPS biosynthesis was significantly high in patients with T2D, especially for N-acetylglucosamine deacetylase, 3-deoxy-D-manno-octulosonic-acid transferase, and lauroyl-Kdo2-lipid IVA myristoyltransferase. The functional analysis indicated that a majority of pathways involved in LPS biosynthesis were augmented in patients with T2D. A total of 1,173 species from 335 genera containing the gene sequences of LPS enzymes, including LpxA/B/C/D/H/K/L/M and/or WaaA, coexisted in controls and patients with T2D. Critical taxonomies with discriminative fecal abundance between groups were revealed, which exhibited different associations with enzymes. Moreover, the identified gut microbial markers had correlations with LPS enzymes and were subsequently associated with microbial pathways. The present findings delineated the potential capability of gut microbiota toward LPS biosynthesis in European women and highlighted a gut microbiota−based mechanistic link between the disturbance in LPS biosynthesis and T2D. The restoration of LPS levels through gut microbiota manipulation might offer potential approaches for preventing and treating T2D.

The role of the gut microbiota in health and cardiovascular diseases

The gut microbiota is critical to human health, such as digesting nutrients, forming the intestinal epithelial barrier, regulating immune function, producing vitamins and hormones, and producing metabolites to interact with the host. Meanwhile, increasing evidence indicates that the gut microbiota has a strong correlation with the occurrence, progression and treatment of cardiovascular diseases (CVDs). In patients with CVDs and corresponding risk factors, the composition and ratio of gut microbiota have significant differences compared with their healthy counterparts. Therefore, gut microbiota dysbiosis, gut microbiota-generated metabolites, and the related signaling pathway may serve as explanations for some of the mechanisms about the occurrence and development of CVDs. Several studies have also demonstrated that many traditional and latest therapeutic treatments of CVDs are associated with the gut microbiota and its generated metabolites and related signaling pathways. Given that information, we summarized the latest advances in the current research regarding the effect of gut microbiota on health, the main cardiovascular risk factors, and CVDs, highlighted the roles and mechanisms of several metabolites, and introduced corresponding promising treatments for CVDs regarding the gut microbiota. Therefore, this review mainly focuses on exploring the role of gut microbiota related metabolites and their therapeutic potential in CVDs, which may eventually provide better solutions in the development of therapeutic treatment as well as the prevention of CVDs.

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.

The role of intestinal stem cell within gut homeostasis: Focusing on its interplay with gut microbiota and the regulating pathways

Intestinal stem cells (ISCs) play an important role in maintaining intestinal homeostasis via promoting a healthy gut barrier. Within the stem cell niche, gut microbiota linking the crosstalk of dietary influence and host response has been identified as a key regulator of ISCs. Emerging insights from recent research reveal that ISC and gut microbiota interplay regulates epithelial self-renewal. This article reviews the recent knowledge on the key role of ISC in their local environment (stem cell niche) associating with gut microbiota and their metabolites as well as the signaling pathways. The current progress of intestinal organoid culture is further summarized. Subsequently, the key challenges and future directions are discussed.

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.

A maternal higher-complex carbohydrate diet increases bifidobacteria and alters early life acquisition of the infant microbiome in women with gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is associated with considerable imbalances in intestinal microbiota that may underlie pathological conditions in both mothers and infants. To more definitively identify these alterations, we evaluated the maternal and infant gut microbiota through the shotgun metagenomic analysis of a subset of stool specimens collected from a randomized, controlled trial in diet-controlled women with GDM. The women were fed either a CHOICE diet (60% complex carbohydrate/25% fat/15% protein, n=18) or a conventional diet (CONV, 40% complex carbohydrate/45% fat/15% protein, n=16) from 30 weeks' gestation through delivery. In contrast to other published studies, we designed the study to minimize the influence of other dietary sources by providing all meals, which were eucaloric and similar in fiber content. At 30 and 37 weeks' gestation, we collected maternal stool samples; performed the fasting measurements of glucose, glycerol, insulin, free fatty acids, and triglycerides; and administered an oral glucose tolerance test (OGTT) to measure glucose clearance and insulin response. Infant stool samples were collected at 2 weeks, 2 months, and 4-5 months of age. Maternal glucose was controlled to conventional targets in both diets, with no differences in Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). No differences in maternal alpha or beta diversity between the two diets from baseline to 37 weeks' gestation were observed. However, women on CHOICE diet had higher levels of Bifidobacteriaceae, specifically Bifidobacterium adolescentis, compared with women on CONV. Species-level taxa varied significantly with fasting glycerol, fasting glucose, and glucose AUC after the OGTT challenge. Maternal diet significantly impacted the patterns of infant colonization over the first 4 months of life, with CHOICE infants showing increased microbiome alpha diversity (richness), greater Clostridiaceae, and decreased Enterococcaceae over time. Overall, these results suggest that an isocaloric GDM diet containing greater complex carbohydrates with reduced fat leads to an ostensibly beneficial effect on the maternal microbiome, improved infant gut microbiome diversity, and reduced opportunistic pathogens capable of playing a role in obesity and immune system development. These results highlight the critical role a maternal diet has in shaping the maternal and infant microbiome in women with GDM.

Effects of Resveratrol Administration in Liver Injury Prevention as Induced by an Obesogenic Diet: Role of Ruminococcaceae

Gut microbiota dysbiosis has been described in several metabolic disruptions, such as non-alcoholic fatty liver disease (NAFLD). Administration of resveratrol has been claimed to elicit benefits against NAFLD along with modulating gut microbiota composition. This investigation aims to study the putative mediating role of gut microbiota in the potential hepato-protective effects of resveratrol in a diet-induced NAFLD rat model. The involvement of bacteria from the Ruminococcaceae family in such effects was also addressed. Resveratrol administration resulted in lowered liver weight and serum total and non-HDL cholesterol concentrations, as well as in increased serum HDL cholesterol levels. The administration of this polyphenol also prevented obesogenic diet-induced serum transaminase increases. In addition, histopathological analysis revealed that resveratrol administration ameliorated the dietary-induced liver steatosis and hepatic inflammation. Gut microbiota sequencing showed an inverse relationship between some bacteria from the Ruminococcaceae family and the screened hepatic markers, whereas in other cases the opposite relationship was also found. Interestingly, an interaction was found between UBA-1819 abundance and resveratrol induced liver weight decrease, suggesting that for this marker resveratrol induced effects were greater when the abundance of this bacteria was high, while no actions were found when UBA-1819 abundance was low.

Enterobacterial LPS-inducible LINC00152 is regulated by histone lactylation and promotes cancer cells invasion and migration

Gut microbes participate in pathogenesis by interacting with the host genome through epigenetic mechanisms, such as long non-coding RNAs. However, the mechanisms by which the microbiota induce expression alteration of long non-coding RNAs remains unclear. Here, we quantified the transcriptome alteration of human colon cell lines after being infected by a common enteric pathogen Salmonella typhimurium SL1344. We observed a widespread lncRNAs expression alteration. Among them, the elevated expression of LINC00152 was verified and proved to be induced by enteric bacteria-derived lipopolysaccharide (LPS). The inducible LINC00152 were found to inhibit Salmonella invasion and inflammation response. LINC00152 was overexpressed in tumors of the clinical CRC samples compared with adjacent normal tissues. Accordingly, we also demonstrated that overexpression of LINC00152 promoted the migration and invasion of colorectal cancer cells. Consistently, we observed an increased abundance of gram-negative bacteria and LPS in tumors tissue. Taken together, the above data implicated that enriched gram-negative bacteria in tumor tissue might promote tumor growth through modulating the expression of LINC00152. Furthermore, we demonstrated that LPS upregulated the expression of LINC00152 by introducing histone lactylation on its promoter and decreasing the binding efficiency of the repressor, YY1, to it. Our results provide new insights into how enterobacteria affect host epigenetics in human disease.

Metaomics in Clinical Laboratory: Potential Driving Force for Innovative Disease Diagnosis

Currently, more and more studies suggested that reductionism was lack of holistic and integrative view of biological processes, leading to limited understanding of complex systems like microbiota and the associated diseases. In fact, microbes are rarely present in individuals but normally live in complex multispecies communities. With the recent development of a variety of metaomics techniques, microbes could be dissected dynamically in both temporal and spatial scales. Therefore, in-depth understanding of human microbiome from different aspects such as genomes, transcriptomes, proteomes, and metabolomes could provide novel insights into their functional roles, which also holds the potential in making them diagnostic biomarkers in many human diseases, though there is still a huge gap to fill for the purpose. In this mini-review, we went through the frontlines of the metaomics techniques and explored their potential applications in clinical diagnoses of human diseases, e.g., infectious diseases, through which we concluded that novel diagnostic methods based on human microbiomes shall be achieved in the near future, while the limitations of these techniques such as standard procedures and computational challenges for rapid and accurate analysis of metaomics data in clinical settings were also examined.

Red Raspberry and Fructo-Oligosaccharide Supplementation, Metabolic Biomarkers, and the Gut Microbiota in Adults with Prediabetes: A Randomized Crossover Clinical Trial

BACKGROUND

Evidence suggests that the gut microbiota and cardiometabolic status are associated, suggesting dietary interventions that alter the microbiota may affect metabolic health.

OBJECTIVES

We investigated whether supplementation with (poly)phenol-dense red raspberries (RRB), alone or with a fructo-oligosaccharide (FOS) prebiotic, would improve biomarkers of cardiometabolic risk in individuals with prediabetes (PreDM) and insulin resistance (IR) and whether the effects are related to modulation of the gut microbiota.

METHODS

Adults with PreDM-IR (n = 26; mean ± SEM age, 35 ± 2 years; fasting glucose, 5.7 ± 0.1 mmol/L; HOMA-IR, 3.3 ± 0.3) or who were metabolically healthy (reference group; n = 10; age, 31 ± 3 years; fasting glucose, 5.1 ± 0.2 mmol/L; HOMA-IR, 1.1 ± 0.1) participated in a randomized crossover trial with two 4-week supplementation periods, in which they consumed either RRB (125 g fresh equivalents) daily or RRB + 8g FOS daily, separated by a 4-week washout. The primary outcome variable was the change in the gut microbiota composition, assessed by shotgun sequencing before (baseline) and at the end of each supplementation period. Secondary outcomes were changes in glucoregulation, lipid metabolism, anti-inflammatory status, and anthropometry. The trial is registered at ClinicalTrials.gov, NCT03049631.

RESULTS

In PreDM-IR, RRB supplementation reduced hepatic-IR (-30.1% ± 14.6%; P = 0.04) and reduced plasma total and LDL cholesterol [-4.9% ± 1.8% (P = 0.04) and -7.2% ± 2.3% (P = 0.003), respectively] from baseline. Adding FOS (RRB + FOS) improved β-cell function [insulin secretion rate, +70.2% ± 32.8% (P = 0.02); Disposition Index, +94.4% ± 50.2% (P = 0.04)], but had no significant effect on plasma cholesterol compared to baseline. RRB increased Eubacterium eligens (2-fold) and decreased Ruminococcus gnavus (-60% ± 34%), whereas RRB + FOS increased Bifidobacterium spp. (4-fold) and decreased Blautia wexlerae (-23% ± 12%) from baseline (all P values ≤ 0.05). R. gnavus was positively correlated with hepatic-IR, and E. eligens and Bifidobacterium catenulatum were negatively correlated with cholesterol concentrations (P ≤ 0.05).

CONCLUSIONS

Increased Bifidobacterium spp., concurrently with reduced R. gnavus, was associated with metabolic improvements in adults with PreDM-IR, warranting further research on the mechanisms involved in (poly)phenol/FOS-microbial interactions with host metabolism.

Host-microbial interactions in metabolic diseases: from diet to immunity

Growing evidence suggests that the gut microbiome is an important contributor to metabolic diseases. Alterations in microbial communities are associated with changes in lipid metabolism, glucose homeostasis, intestinal barrier functions, and chronic inflammation, all of which can lead to metabolic disorders. Therefore, the gut microbiome may represent a novel therapeutic target for obesity, type 2 diabetes, and nonalcoholic fatty liver disease. This review discusses how gut microbes and their products affect metabolic diseases and outlines potential treatment approaches via manipulation of the gut microbiome. Increasing our understanding of the interactions between the gut microbiome and host metabolism may help restore the healthy symbiotic relationship between them.