The Gut Microbiota Profile According to Glycemic Control in Type 1 Diabetes Patients Treated with Personal Insulin Pumps.Microorganisms. 2021;9. [PMID: 33445500 DOI: 10.3390/microorganisms9010155]

Effects of four food hydrocolloids on colitis and their regulatory effect on gut microbiota

Hydrocolloids are important food additives and have potential regulatory effects on gut microbiota. The development of colitis is closely related to changes in gut microbiota. The effect of food hydrocolloids on the structure of the gut microbiota and their impact on colitis has not been well investigated. Therefore, this study investigated the effects of four hydrocolloids (carrageenan, guar gum, xanthan gum, and pectin) on colitis, and explored their regulatory effects on gut microbiota. The results indicated that pectin and guar effectively alleviated body weight loss and disease activity index, reduced inflammatory cytokine levels, and promoted short-chain fatty acids (SCFAs) production. They increased the abundance of Akkermansia muciniphila, Oscillospira, and Lactobacillus, and Akkermansia abundance had a negative correlation with the severity of colitis. In contrast, carrageenan and xanthan gum did not significantly improve colitis, and carrageenan reduced the production of SCFAs. Both carrageenan and xanthan gum increased the abundance of Ruminococcus gnavus, and Ruminococcus abundance was positively correlated with the severity of colitis. These findings suggest that food additives have an impact on host health and provide guidance for the diet of patients with colitis.

EVOO supplement prevents type 1 diabetes by modulating gut microbiota and serum metabolites in NOD mice

AIMS

Extra virgin olive oil (EVOO) is the highest quality olive oil available and has been shown to regulate postprandial blood glucose in patients with type 1 diabetes (T1D). However, it remains uncertain whether EVOO can prevent the onset of T1D. In this study, we investigated the potential preventive effect of orally administered EVOO on T1D in non-obese diabetic (NOD) mice.

MAIN METHODS

We analyzed changes in fecal microbes using 16 s rDNA sequencing and serum metabolites using Ultra High-Performance Liquid Chromatography and Quadrupole Time-of-Flight Mass Spectrometry (Q-TOF-MS).

KEY FINDINGS

Our findings showed that EVOO supplementation in NOD mice slowed gastric emptying, reduced insulitis, and delayed T1D onset. Moreover, EVOO altered the composition of fecal microbes, increasing the Bacteroidetes/Firmicutes ratio, and promoting the growth of short-chain fatty acids (SCFAs)-producing bacteria, such as Lachnoclostridium and Ruminococcaceae_UCG-005. Moreover, it also increased beneficial serum metabolites, including unsaturated fatty acid and triterpenoid, which positively correlated with the increased SCFA-producing bacteria and negatively correlated with the disease indicators. Conversely, most decreased serum lipid metabolites, such as Oleamide, showed the opposite trend.

SIGNIFICANCE

Our study demonstrates that EVOO may ameliorate pancreas inflammation and prevent T1D onset in NOD mice by modulating gut microbiota and serum metabolites.

Machine learning approach reveals microbiome, metabolome, and lipidome profiles in type 1 diabetes

INTRODUCTION

Type 1 diabetes (T1D) is a complex disorder influenced by genetic and environmental factors. The gut microbiome, the serum metabolome, and the serum lipidome have been identified as key environmental factors contributing to the pathophysiological mechanisms of T1D.

OBJECTIVES

We aimed to explore the gut microbiota, serum metabolite, and serum lipid signatures in T1D patients by machine learning.

METHODS

We evaluated 137 individuals in a cross-sectional cohort involving 38 T1D patients, 38 healthy controls, and 61 T1D patients for validation. We characterized gut microbiome, serum metabolite, and serum lipid profiles with machine learning approaches (logistic regression, support vector machine, Gaussian naive Bayes, and random forest).

RESULTS

The machine learning approaches using the microbiota composition did not accurately diagnose T1D (model accuracy = 0.7555), while the accuracy of the model using the metabolite composition was 0.9333. Based on the metabolite composition, 3-hydroxybutyric acid and 9-oxo-ode (area under curve = 0.70 and 0.67, respectively, both increased in T1D) were meaningful overlap metabolites screened by multiple bioinformatics methods. We confirmed the biological relevance of the microbiome, metabolome, and lipidome features in the validation group.

CONCLUSION

By using machine learning algorithms and multi-omics, we demonstrated that T1D patients are associated with altered microbiota, metabolite, and lipidomic signatures or functions.

Beneficial Effects of Dietary Flaxseed Oil through Inflammation Pathways and Gut Microbiota in Streptozotocin-Induced Diabetic Mice

Flaxseed oil (FO) has displayed potential anti-diabetes properties by providing a high content of α-linolenic acid. However, the effects and mechanisms of FO on type 1 diabetes are still unclear. The present study aims to explore the effects of different doses of FO feeding on hepatic inflammation and gut microbiota in streptozotocin-induced diabetic mice. Forty-eight six-week-old C57BL/6J male mice were divided into a control group (CON), a diabetic group (MOD), a diabetes with 7.0% w/w FO feeding group (FO-L), and a diabetes with 10.5% w/w FO feeding group (FO-H) for six weeks. The 7.0% w/w and 10.5% w/w FO feeding groups exhibited potential recovery of the number and size of pancreas tissues. The fasting blood glucose level was significantly decreased only after 4 weeks of feeding with 10.5% w/w FO in diabetic mice. The 10.5% w/w FO feeding group significantly decreased the postprandial blood glucose level of mice in the OGTT test. Hepatic glycogen levels were dramatically upregulated in the mice fed with both 7.0% w/w and 10.5% w/w FO. FO feeding significantly attenuated hepatic LPS, TNF-α, and IL-1β levels. In addition, we observed that 7.0% w/w and 10.5% w/w FO feedings notably downregulated hepatic gene and protein expressions of TLR4, MyD88, and P65. Furthermore, only 10.5% FO regulated fecal microbiota by increasing the relative abundance of the Bacteroidetes phylum, Lactococcus family, and Muribaculaceae and Streptococcaceae family and genus in streptozotocin-induced diabetic mice. Therefore, we conclude that FO feeding plays a role in anti-inflammation via the regulation of hepatic LPS/TLR4/MyD88 pathways and gut microbiota. In addition, different doses of FO supplementation may exhibit varying mechanisms in streptozotocin-induced mice.

Oral Microbiota-One Habitat or Diverse Niches? A Pilot Study of Sampling and Identification of Oral Bacterial and Fungal Biota in Patients with Type I Diabetes Mellitus Treated with Insulin Pump

OBJECTIVE

The oral microbiota is a very complex and dynamic microbial ecosystem. Alterations of its balance can result in oral and systemic diseases. We aimed to characterize the microbiota in particular niches of the oral cavity in adult type 1 diabetes patients treated with continuous infusion of insulin with insulin pump (IP). In addition, we aimed to determine optimal sites of oral microbiota sampling in studies of large research groups of patients with DM I.

DESIGN

In this pilot study, we sampled the buccal and soft palate mucosa, tongue, palatal and buccal dental surfaces and gingival pockets of adult DM I patients treated with IP.

RESULTS

In total, 23 patients were recruited. The oral microbiota was dominated by Streptococus and Neisseria, with a low incidence of cariogenic S. mutans and Lactobacillus, as well as periodontal pathogens such as Prevotella. There were significant differences in overall CFU counts of all strains, Gram-positive, Staphylococci, Streptococci and S. oralis strains between mucosal and dental surface sites. The overall CFU counts of all strains and Gram-positive strains were higher in dental sites vs. mucosal sites (both p < 0.001). CFU counts of S. oralis were significantly higher in dental sites vs. gingival pocket sites (p = 0.013). Candida species were rare. The mucosal sites on the buccae presented lower diversity and bacterial counts.

CONCLUSIONS

In the study group of adult DM I patients treated with IP, the microbiota in particular niches of the oral cavity was significantly different. Three distinct and optimally appropriate sampling sites for oral microflora were identified: buccal and palatal mucosa, dental surface and gingival pockets. The results of this study may be the basis for further studies of large groups of patients with DM I.

Gut microbiota, behavior, and nutrition after type 1 diabetes diagnosis: A longitudinal study for supporting data in the metabolic control

Introduction

Type 1 diabetes (T1D) risk involves genetic susceptibility but also epigenetics, environment, and behaviors. Appropriate metabolic control, especially quickly after the diagnosis, is crucial for the patient quality of life.

Methods

This study aimed to produce a quantitative comparison of the behavior, nutrition habits, and gut microbiota composition between the onset and the 1-year follow-up in 35 children with T1D.

Results and discussion

At follow-up, with the metabolic control, many parameters improved significantly, with respect to the onset, such as glycated hemoglobin (-19%), body mass index (BMI), and also nutritional behaviors, such as normal calorie intake (+6%), carbohydrate intake (-12%), extra portion request (-4%), and meals distribution during the day. Moreover, glycated hemoglobin decrement correlated with both total and rapid absorption carbohydrate intake (Spearman's rho = 0.288, 95% CI 0.066-0.510, p = 0.013), showing as the nutritional behavior supported the insulin therapy efficiency. The next-generation sequencing (NGS) analysis of microbiota revealed abundance differences for Ruminococcus bromii and Prevotella copri (higher at onset, p < 0.001) and the genera Succinivibrio and Faecalibacterium (lower at onset, p < 0.001), as a consequence of nutritional behavior, but it was not the only changing driver. The qRT-PCR analysis showed significant variations, in particular for Bacteroidetes and Bifidobacterium spp. (+1.56 log gene copies/g stool at follow-up, p < 0.001). During the year, in 11% of the patients, severe clinical episodes occurred (hypoglycemic or ketoacidosis). The likelihood of a severe hypoglycemic episode was modulated when the Methanobrevibacter smithii amount increased (odds ratio 3.7, 95% CI 1.2-11.4, p = 0.026). Integrated evaluation, including nutritional behavior and microbiota composition, could be considered predictive of the metabolic control management for children cohort with a recent diagnosis of T1D.

Bacillus coagulans Alleviates Intestinal Damage Induced by TiO2 Nanoparticles in Mice on a High-Fat Diet

Titanium dioxide nanoparticles (TiO₂ NPs) are generally added in considerable amounts to food as a food additive. Oral exposure to TiO₂ NPs could induce intestinal damage, especially in obese individuals with a high-fat diet. The probiotic Bacillus coagulans (B. coagulans) exhibits good resistance in the gastrointestinal system and is beneficial to intestinal health. In this study, B. coagulans was used to treat intestinal damage caused by TiO₂ NPs in high-fat-diet mice via two intervention methods: administration of TiO₂ NPs and B. coagulans simultaneously and administration of TiO₂ NPs followed by that of B. coagulans. The intervention with B. coagulans was found to reduce the inflammatory response and oxidative stress. A 16S rDNA sequencing analysis revealed that B. coagulans had increased the diversity of gut microbiota and optimized the composition of gut microbiota. Fecal metabolomics analysis indicated that B. coagulans had restored the homeostasis of sphingolipids and amino acid metabolism. The intervention strategy of administering TiO₂ NPs followed by B. coagulans was found to be more effective. In conclusion, B. coagulans could alleviate intestinal damage induced by TiO₂ NPs in high-fat-diet mice TiO₂B. coagulans. Our results suggest a new avenue for interventions against intestinal damage induced by TiO₂ NPs.

Gut Microbiota Functional Traits, Blood pH, and Anti-GAD Antibodies Concur in the Clinical Characterization of T1D at Onset

Alterations of gut microbiota have been identified before clinical manifestation of type 1 diabetes (T1D). To identify the associations amongst gut microbiome profile, metabolism and disease markers, the 16S rRNA-based microbiota profiling and ¹H-NMR metabolomic analysis were performed on stool samples of 52 T1D patients at onset, 17 T1D siblings and 57 healthy subjects (CTRL). Univariate, multivariate analyses and classification models were applied to clinical and -omic integrated datasets. In T1D patients and their siblings, Clostridiales and Dorea were increased and Dialister and Akkermansia were decreased compared to CTRL, while in T1D, Lachnospiraceae were higher and Collinsella was lower, compared to siblings and CTRL. Higher levels of isobutyrate, malonate, Clostridium, Enterobacteriaceae, Clostridiales, Bacteroidales, were associated to T1D compared to CTRL. Patients with higher anti-GAD levels showed low abundances of Roseburia, Faecalibacterium and Alistipes and those with normal blood pH and low serum HbA_1c levels showed high levels of purine and pyrimidine intermediates. We detected specific gut microbiota profiles linked to both T1D at the onset and to diabetes familiarity. The presence of specific microbial and metabolic profiles in gut linked to anti-GAD levels and to blood acidosis can be considered as predictive biomarker associated progression and severity of T1D.

The Effect of Whole-Grain Diet on the Gut Microbiota of the Elderly Individuals

A whole-grain (WG) diet affects human health in multiple ways. However, the effect of WG on the gut microbiota of the elderly individuals is still largely unknown. In this study, WG did not affect the microbial α-diversity but had a profound impact on the microbes' abundance in the elderly individuals. WG increased the abundance of Verrucomicrobia and decreased the abundance of Firmicutes. The prediction of microbial function showed that glucose metabolism and lipid metabolism were inhibited. In addition, the effects of WG on the gut microbiota of normal-weight (NW) and overweight (OW) individuals were different. WG increased Verrucomicrobia in the NW group and decreased Firmicutes in the OW group. Meanwhile, the effect of WG on gut microbiota showed gender characteristics, Firmicutes/Bacteroidetes ratio was decreased in women, while Verrucomicrobia abundance was increased in men. The use of WG could improve the microbial composition and promote the growth of beneficial microbes, which may be beneficial to the health of the elderly individuals.

The Effect of Polyphenol Extract from Rosa Roxburghii Fruit on Plasma Metabolome and Gut Microbiota in Type 2 Diabetic Mice

Rosa roxburghii fruit is an underutilized functional food abundant in polyphenols. Polyphenols have been proved to have antidiabetic effects. This study investigates the effects of Rosa roxburghii fruit polyphenols extract (RPE) on plasma metabolites and gut microbiota composition in streptozotocin (STZ)- and high-fat diet- induced type 2 diabetes using metabolomics and 16S rRNA gene sequencing. The induced diabetic mice were fed with 400 mg/kg body weight RPE for 8 weeks. RPE demonstrated hypoglycemic, hypolipidemic, and anti-inflammatory effects. Colonic oxidative stress biomarkers were also lowered by RPE. Besides, RPE decreased plasma ceramides and tyrosine levels and increased carnitine and phosphatidylinositols levels, indicating improved insulin resistance, lipid metabolism, and immune response. Furthermore, RPE decreased abundances of Lachnospiraceae and Rikenellaceae and increased abundances of Erysipelotrichaceae and Faecalibaculum. Metabolic function prediction of the gut microbiota by PICRUSt demonstrated that RPE downregulated the phosphotransferase system. Taken together, these findings demonstrated that RPE has the potential to prevent type 2 diabetes by regulating the plasma metabolites and gut microbes.

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

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

A systematic review and meta-analysis of gut microbiota in diabetic kidney disease: Comparisons with diabetes mellitus, non-diabetic kidney disease, and healthy individuals

BACKGROUND

Gut microbiota has been reported to play an important role in diabetic kidney disease (DKD), however, the alterations of gut bacteria have not been determined.

METHODS

Studies comparing the differences of gut microbiome between patients with DKD and non-DKD individuals using high-throughput sequencing technology, were systematically searched and reviewed. Outcomes were set as gut bacterial diversity, microbial composition, and correlation with clinical parameters of DKD. Qualitative data were summarized and compared through a funnel R script, and quantitative data were estimated by meta-analysis.

RESULTS

A total of 15 studies and 1640 participants were included, the comparisons were conducted between DKD, diabetes mellitus (DM), non-diabetic kidney disease (NDKD), and healthy controls. There were no significant differences of α-diversity between DKD and DM, and between DKD and NDKD, however, significant lower microbial richness was found in DKD compared to healthy controls. Different bacterial compositions were found between DKD and non-DKD subjects. The phylum Actinobacteria were found to be enriched in DKD compared to healthy controls. At the genus level, we found the enrichment of Hungatella, Bilophila, and Escherichia in DKD compared to DM, patients with DKD showed lower abundances of Faecalibacterium compared to those with NDKD. The genera Butyricicoccus, Faecalibacterium, and Lachnospira were depleted in DKD compared to healthy controls, whereas Hungatella, Escherichia, and lactobacillus were significantly enriched. The genus Ruminococcus torques group was demonstrated to be inversely correlated with estimated glomerular filtration rate of DKD.

CONCLUSIONS

Gut bacterial alterations was demonstrated in DKD, characterized by the enrichment of the genera Hungatella and Escherichia, and the depletion of butyrate-producing bacteria, which might be associated with the occurrence and development of DKD. Further studies are still needed to validate these findings, due to substantial heterogeneity.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/, identifier CRD42022340870.

A new paradigm for a new simple chemical: butyrate & immune regulation

Short-chain fatty acids (SCFAs) play an important role in the host system. Among SCFAs, butyrate has received particular attention for its large effect on host immunity, particularly in supplying energy to enterocytes and producing immune cells. Butyrate enters the cells through the Solute Carrier Family 5 Member 8 (SLC5A8) transporters, then works as a histone deacetylase inhibitor (HDAC) that inhibits the activation of Nuclear factor-κB (NF-κB), which down-regulates the expression of IL-1β, IL-6, TNF-α. Meanwhile, butyrate acts as a ligand to activate G protein-coupled receptors GPR41, GPR43, and GPR109, promoting the expression of anti-inflammatory factors. Besides, it inhibits the proinflammatory factors. Further, it can also suppress the expression of chemokines and reduce inflammation to maintain host homeostasis. This paper reviews the research progress highlighting the potential function of butyrate as a factor impacting intestinal health, obesity and brain disorders.

Holistic perspective of the role of gut microbes in diabetes mellitus and its management

The gut microbiota (GM) plays a role in the development and progression of type 1 and type 2 diabetes mellitus (DM) and its complications. Gut dysbiosis contributes to the pathogenesis of DM. The GM has been shown to influence the efficacy of different antidiabetic medications. Intake of gut biotics, like prebiotics, probiotics and synbiotics, can improve the glucose control as well as the metabolic profile associated with DM. There is some preliminary evidence that it might even help with the cardiovascular, ophthalmic, nervous, and renal complications of DM and even contribute to the prevention of DM. More large-scale research studies are needed before wide spread use of gut biotics in clinical practice as an adjuvant therapy to the current management of DM.

Preterm Birth Is Correlated With Increased Oral Originated Microbiome in the Gut

Background

Preterm birth is one of the leading causes of perinatal morbidity and mortality. Gut microbiome dysbiosis is closely related to adverse pregnancy outcomes. However, the role of the gut microbiome in the pathogenesis of preterm birth remains poorly studied.

Method

We collected fecal samples from 41 women (cases presenting with threatened preterm labor =19, 11 of which delivered preterm; gestational age-matched no-labor controls, all of which delivered at term = 22) were recruited for the study. We performed 16S rRNA amplicon sequencing to compare the composition of the gut microbiome in threatened preterm labor cases and controls and among women who delivered preterm and at term. By annotating taxonomic biomarkers with the Human Oral Microbiome Database, we observed an increased abundance of potential oral-to-gut bacteria in preterm patients.

Results

Patients with preterm birth showed a distinct gut microbiome dysbiosis compared with those who delivered at term. Opportunistic pathogens, particularly Porphyromonas, Streptococcus, Fusobacterium, and Veillonella, were enriched, whereas Coprococcus and Gemmiger were markedly depleted in the preterm group. Most of the enriched bacteria were annotated oral bacteria using the Human Oral Microbiome Database. These potential oral-to-gut bacteria were correlated with clinical parameters that reflected maternal and fetal status.

Conclusions

This study suggests that patients who deliver preterm demonstrate altered gut microbiome that may contain higher common oral bacteria.