Erratum: Differential Analysis of Hypertension-Associated Intestinal Microbiota.

[This corrects the article DOI: 10.7150/ijms.29322.].

Spatial-resolved metabolomics reveals tissue-specific metabolic reprogramming in diabetic nephropathy by using mass spectrometry imaging

Detailed knowledge on tissue-specific metabolic reprogramming in diabetic nephropathy (DN) is vital for more accurate understanding the molecular pathological signature and developing novel therapeutic strategies. In the present study, a spatial-resolved metabolomics approach based on air flow-assisted desorption electrospray ionization (AFADESI) and matrix-assisted laser desorption ionization (MALDI) integrated mass spectrometry imaging (MSI) was proposed to investigate tissue-specific metabolic alterations in the kidneys of high-fat diet-fed and streptozotocin (STZ)-treated DN rats and the therapeutic effect of astragaloside IV, a potential anti-diabetic drug, against DN. As a result, a wide range of functional metabolites including sugars, amino acids, nucleotides and their derivatives, fatty acids, phospholipids, sphingolipids, glycerides, carnitine and its derivatives, vitamins, peptides, and metal ions associated with DN were identified and their unique distribution patterns in the rat kidney were visualized with high chemical specificity and high spatial resolution. These region-specific metabolic disturbances were ameliorated by repeated oral administration of astragaloside IV (100 mg/kg) for 12 weeks. This study provided more comprehensive and detailed information about the tissue-specific metabolic reprogramming and molecular pathological signature in the kidney of diabetic rats. These findings highlighted the promising potential of AFADESI and MALDI integrated MSI based metabolomics approach for application in metabolic kidney diseases.

Differential Analysis of Hypertension-Associated Intestinal Microbiota.

Hypertension is the main risk factor for cerebral stroke and death resulting from cerebral stroke. Current association studies on hypertension and intestinal microbiota focus on patients with hypertension (HTN); however, no investigations involving patients with isolated diastolic hypertension (IDH) or systolic hypertension (SH) have been conducted to date. In this study, fecal samples from 62 cases with normal blood pressure (BP) and 67 cases with high BP were used for 16S amplicon sequencing. Sixty-one cases of HTN and 61 corresponding cases with normal BP were obtained by propensity score matching (PSM), and differential analysis was conducted using the DEseq2 package. PSM was also used to match six IDH patients with six controls and to match 35 cases of SH with 35 controls. There were 54 differential genera between the HTN and normal BP groups, and there were five differential genera between the IDH and normal BP groups. There were 38 differential genera between the SH and normal BP groups, including Christensenella. Bayesian network analysis showed that variations in BP influenced microbial abundance. Pearson's correlation analysis showed that bacterial abundance is correlated with BP. Significant differences between the intestinal microbiota of high and normal BP groups were observed. Gut microbiota dysbiosis differed among HTN, IDH, and SH patients. In particular, diastolic blood pressure (DBP) and systolic blood pressure (SBP) were related to different intestinal microbiota.

Age-stratified comparative analysis of the differences of gut microbiota associated with blood glucose level.

BACKGROUND: Gut bacteria are an important component of the microbiota ecosystem in humans and other animals, and they play important roles in human health. The aim of this study was to investigate the relationship between gut microbiota and multiple demographical-, behavioral-, or biochemical-related factors in subjects with chronic disease. Subjects with a very wide age range who participated in community-based chronic disease prevention and screening programs in China were enrolled. We analyzed the intestinal microbiota composition using 16S rRNA-based high-throughput sequencing of fecal samples, analyzed the association between gut microbiota structure and multiple demographical, behavioral, and biochemical factors, and compared the differences in microbiota composition in age-stratified groups with different blood glucose levels. RESULTS: Our results showed that both age and blood glucose levels had a significant impact on the gut microbiota structure. We also identified several taxa showed distinct abundance in groups with different glucose levels. Lactobacillus and Bifidobacterium at genus level and their related taxa were more abundant in the GLU high group comparing with GLU normal group and in NGR group comparing with DM group. Further analysis using the age-stratified data showed that blood glucose levels had a more significant impact on the gut microbiota in the ≥76 y age group than in the ≤75 y age group, which indicated that it is necessary to take age into account when conducting such studies. Moreover, we identified several taxa that were highly associated with blood glucose levels in the ≥76 y age group but not in the ≤75 y age group. Within the ≥76 y age group, Lachnospiraceae incertae sedis and Bacteroides were more abundant in the GLU normal group, whereas Lactobacillus and Bifidobacterium at genus level were more abundant in the GLU high group. CONCLUSIONS: This result suggested that taxa that are capable of differentiating blood glucose levels might differ significantly in different age groups.