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The association between body composition and gut microbiota in type 2 diabetes mellitus (DM) remains unknown. To elucidate the correlation of body composition and gut microbiota, we conducted a clinical study to enroll 179 patients with type 2 DM. Body composition of lean tissue index (LTI) and fat tissue index was measured by Body Composition Monitor. Eight pairs of 16S rRNA gene primers specific to Firmicutes, Bacteroidetes, the Clostridium leptum group, Bacteroides, Bifidobacterium, Akkermansia muciniphila, Escherichia coli, and Faecalibacterium prausnitzii were used to measure their abundance by quantitative polymerase chain reaction. The results showed that type 2 DM with higher abundance of phylum Firmicutes and a higher ratio of phyla Firmicutes to Bacteroidetes (phyla F/B ratio) had higher LTI. This significant correlation between phyla F/B ratio and LTI was especially evident in type 2 DM with high body mass index, and independent of glycemic control or dipeptidyl peptidase-4 inhibitor usage. In conclusion, our study demonstrated the positive association of LTI with the abundance of phylum Firmicutes and the phyla F/B ratio in type 2 DM.

Metabolic syndrome (MS) has been an important health issue in the world, and insulin resistance (IR) is one of the characteristics of MS, increasing the risk for the onset and poor prognosis of type 2 diabetes mellitus (T2D). However, the interactional effect of obesity or abnormal body composition on the correlation between gut microbiota and IR in T2D patients is not well-explored. This cross-sectional study used a body composition monitor to evaluate lean tissue mass and fat tissue mass. IR was calculated using homeostatic model assessment-insulin resistance (HOMA-IR). Eight pairs of 16S rRNA gene primers specific to Firmicutes, Bacteroidetes, Clostridium leptum group, Faecalibacteriumprausnitzii, B acteroides, Bifidobacterium, Akkermansia muciniphila, and Escherichia coli were utilized to measure their abundance by qPCR. One hundred and fifty-four T2D patients were enrolled and stratified by the median HOMA-IR (2.5) and body mass index (BMI) of 25 kg/m2. A lower abundance of A. muciniphila was found in T2D patients with high HOMA-IR and BMI respectively. HOMA-IR and BMI had a synergistic effect on the reduction of the abundance of A. muciniphila. After adjusting metabolic factors, the low abundance of A. muciniphila significantly increased the risk for greater severity of IR. Furthermore, the negative correlation between A. muciniphila and IR was only found in T2D patients with high lean tissue. In conclusion, decreased abundance of fecal A. muciniphila enhanced the severity of IR in Asians with T2D, especially those having lean mass, and this significant relationship was independent of obesity.

Type 2 diabetes (T2D) is associated with an increased risk of cardiovascular disease (CVD). The gut microbiota may contribute to the onset and progression of T2D and CVD. The aim of this study was to evaluate the relationship between the gut microbiota and subclinical CVD in T2D patients. This cross-sectional study used echocardiographic data to evaluate the cardiac structure and function in T2D patients. We used a quantitative polymerase chain reaction to measure the abundances of targeted fecal bacterial species that have been associated with T2D, including Bacteroidetes, Firmicutes, Clostridium leptum group, Faecalibacterium prausnitzii, Bacteroides, Bifidobacterium, Akkermansia muciniphila, and Escherichia coli. A total of 155 subjects were enrolled (mean age 62.9 ± 10.1 years, 57.4% male and 42.6% female). Phyla Bacteroidetes and Firmicutes and genera Bacteroides were positively correlated with the left ventricular ejection fraction. Low levels of phylum Firmicutes were associated with an increased risk of left ventricular hypertrophy. High levels of both phylum Bacteroidetes and genera Bacteroides were negatively associated with diastolic dysfunction. A high phylum Firmicutes/Bacteroidetes (F/B) ratio and low level of genera Bacteroides were correlated with an increased left atrial diameter. Phyla Firmicutes and Bacteroidetes, the F/B ratio, and the genera Bacteroides were associated with variations in the cardiac structure and systolic and diastolic dysfunction in T2D patients. These findings suggest that changes in the gut microbiome may be the potential marker of the development of subclinical CVD in T2D patients.

Introduction: Non-alcoholic fatty liver disease (NAFLD) remains an important health issue worldwide. The increasing prevalence of NAFLD is linked to type 2 diabetes (T2D). The gut microbiota is associated with the development of NAFLD and T2D. However, the relationship between gut microbiota and NAFLD severity has remained unclear in T2D patients. The aim of this study was to evaluate the relationship of gut microbiota with the severity of NAFLD in T2D patients. Methods: This cross-sectional study used transient elastography (FibroScan) to evaluate the severity of hepatic steatosis. We utilized qPCR to measure the abundance of Bacteroidetes, Firmicutes, Faecalibacterium prausnitzii, Clostridium leptum group, Bacteroides, Bifidobacterium, Akkermansia muciniphila, and Escherichia coli. Results: Of 163 T2D patients, 83 with moderate to severe NAFLD had higher abundance of bacteria of the phylum Firmicutes with respect to 80 patients without NAFLD or with mild NAFLD. High abundance of the phylum Firmicutes increased the severity of NAFLD in T2D patients. A positive correlation between NAFLD severity and the phylum Firmicutes was found in T2D male patients with body mass index ≥24 kg/m2 and glycated hemoglobin &lt, 7.5%. Conclusion: Enrichment of the fecal microbiota with the phylum Firmicutes is significantly and positively associated with NAFLD severity in T2D patients. The gut microbiota is a potential predictor of NAFLD severity in T2D patients.

Objectives To explore the mechanisms mediating the different levels of gentamicin resistance in enterococci. Methods Susceptibility testing with gentamicin and PCR of resistance determinants were performed in 149 enterococcal isolates. Genetic relatedness was characterized by MLST and PFGE analysis. Sequences of the aac(6′)-Ie-aph(2′′)-Ia gene and its surrounding environment were determined by Illumina sequencing. Stability assays of gentamicin resistance were carried out to evaluate the probability of loss of the high-level gentamicin resistance (HLGR) phenotype. Results A total of 17 (11.4%) aac(6′)-Ie-aph(2′′)-Ia-positive enterococcal isolates (2 Enterococcus faecalis and 15 Enterococcus faecium) with non-HLGR phenotype were found. MLST analysis revealed that the 2 E. faecalis belonged to ST116 and ST618, while all the 15 E. faecium belonged to clonal complex 17. Sequence analysis demonstrated that IS1216V was inserted into the 5′-end of aac(6′)-Ie-aph(2′′)-Ia, leading to loss of HLGR phenotype. Three IS1216V insertion types were found, and type II and III were frequently found in E. faecium. Interestingly, a total of 38 aac(6′)-Ie-aph(2′′)-Ia-positive E. faecium with HLGR phenotype also had type II or type III IS1216V insertion. Sequencing of the aac(6′)-Ie-aph(2′′)-Ia-positive HLGR E. faecium E37 revealed that an intact aac(6′)-Ie-aph(2′′)-Ia was located adjacent to IS1216V-disrupted aac(6′)-Ie-aph(2′′)-Ia. In a non-antibiotic environment, E37 tended to lose HLGR phenotype with a probability of 1.57 × 10−4, which was largely attributed to homologous recombination between the intact and disrupted aac(6′)-Ie-aph(2′′)-Ia. Conclusions This is first study to elucidate that the E. faecium is capable of changing its HLGR phenotype, which may contribute to adaptation to hospital environments with decreased usage of gentamicin.

This work proposes a novel dynamic resource adjustment architecture that includes a routing planning mechanism and a bandwidth resource planning mechanism for a virtual tenant network (VTN) with software-defined networking (SDN). The routing planning mechanism helps to assign the routing paths in a physical network to solve the problem of their uneven distribution, with the ultimate goal of improving the utilization of the network routing. The bandwidth resource planning mechanism helps to manage the tenant demand for bandwidth resources to solve the problem of an excessive bandwidth requirement and thereby to improve the utilization of network bandwidth resources. The proposed architecture helps not only to plan routing paths in a physical network to satisfy a VTN user request but also to guarantee bandwidth usage based on overall network conditions. Analytical results indicate that the proposed routing planning mechanism increases the efficiency of routing assignment and that the proposed bandwidth resource scheduling increases bandwidth utilization by 10.92%.