Table_2_A multi-omics approach to investigate characteristics of gut microbiota and metabolites in hypertension and diabetic nephropathy SPF rat models.DOCX

BackgroundImbalance in intestinal microbiota caused by microbial species and proportions or metabolites derived from microbes are associated with hypertension, as well as diabetic nephropathy. However, the involvement of the intestinal microbiota and metabolites in hypertension and diabetic nephropathy comorbidities (HDN) remains to be elucidated.MethodsWe investigated the effects of intestinal microbiota on HDN in a rat model and determined the abundance of the intestinal microbiota using 16S rRNA sequencing. Changes in fecal and serum metabolites were analyzed using ultra-high-performance liquid chromatography-mass spectrometry.ResultsThe results showed abundance of Proteobacteria and Verrucomicrobia was substantially higher, whereas that of Bacteroidetes was significant lower in the HDN group than in the sham group. Akkermansia, Bacteroides, Blautia, Turicibacter, Lactobacillus, Romboutsia, and Fusicatenibacter were the most abundant, and Prevotella, Lachnospiraceae_NK4A136_group, and Prevotella_9 were the least abundant in the HDN group. Further analysis with bile acid metabolites in serum showed that Blautia was negatively correlated with taurochenodeoxycholic acid, taurocholic acid, positively correlated with cholic acid and glycocholic acid in serum.ConclusionsThese findings suggest that the gut microbiota and metabolites in feces and serum substantially differed between the HDN and sham groups. The F/B ratio was higher in the HDN group than in the sham group. Blautia is potentially associated with HDN that correlated with differentially expressed bile acid metabolites, which might regulate the pathogenesis of HDN via the microorganism–gut–metabolite axis.</p

Data_Sheet_1_A multi-omics approach to investigate characteristics of gut microbiota and metabolites in hypertension and diabetic nephropathy SPF rat models.PDF

BackgroundImbalance in intestinal microbiota caused by microbial species and proportions or metabolites derived from microbes are associated with hypertension, as well as diabetic nephropathy. However, the involvement of the intestinal microbiota and metabolites in hypertension and diabetic nephropathy comorbidities (HDN) remains to be elucidated.MethodsWe investigated the effects of intestinal microbiota on HDN in a rat model and determined the abundance of the intestinal microbiota using 16S rRNA sequencing. Changes in fecal and serum metabolites were analyzed using ultra-high-performance liquid chromatography-mass spectrometry.ResultsThe results showed abundance of Proteobacteria and Verrucomicrobia was substantially higher, whereas that of Bacteroidetes was significant lower in the HDN group than in the sham group. Akkermansia, Bacteroides, Blautia, Turicibacter, Lactobacillus, Romboutsia, and Fusicatenibacter were the most abundant, and Prevotella, Lachnospiraceae_NK4A136_group, and Prevotella_9 were the least abundant in the HDN group. Further analysis with bile acid metabolites in serum showed that Blautia was negatively correlated with taurochenodeoxycholic acid, taurocholic acid, positively correlated with cholic acid and glycocholic acid in serum.ConclusionsThese findings suggest that the gut microbiota and metabolites in feces and serum substantially differed between the HDN and sham groups. The F/B ratio was higher in the HDN group than in the sham group. Blautia is potentially associated with HDN that correlated with differentially expressed bile acid metabolites, which might regulate the pathogenesis of HDN via the microorganism–gut–metabolite axis.</p

Table_1_A multi-omics approach to investigate characteristics of gut microbiota and metabolites in hypertension and diabetic nephropathy SPF rat models.DOCX

BackgroundImbalance in intestinal microbiota caused by microbial species and proportions or metabolites derived from microbes are associated with hypertension, as well as diabetic nephropathy. However, the involvement of the intestinal microbiota and metabolites in hypertension and diabetic nephropathy comorbidities (HDN) remains to be elucidated.MethodsWe investigated the effects of intestinal microbiota on HDN in a rat model and determined the abundance of the intestinal microbiota using 16S rRNA sequencing. Changes in fecal and serum metabolites were analyzed using ultra-high-performance liquid chromatography-mass spectrometry.ResultsThe results showed abundance of Proteobacteria and Verrucomicrobia was substantially higher, whereas that of Bacteroidetes was significant lower in the HDN group than in the sham group. Akkermansia, Bacteroides, Blautia, Turicibacter, Lactobacillus, Romboutsia, and Fusicatenibacter were the most abundant, and Prevotella, Lachnospiraceae_NK4A136_group, and Prevotella_9 were the least abundant in the HDN group. Further analysis with bile acid metabolites in serum showed that Blautia was negatively correlated with taurochenodeoxycholic acid, taurocholic acid, positively correlated with cholic acid and glycocholic acid in serum.ConclusionsThese findings suggest that the gut microbiota and metabolites in feces and serum substantially differed between the HDN and sham groups. The F/B ratio was higher in the HDN group than in the sham group. Blautia is potentially associated with HDN that correlated with differentially expressed bile acid metabolites, which might regulate the pathogenesis of HDN via the microorganism–gut–metabolite axis.</p

Image_2_A multi-omics approach to investigate characteristics of gut microbiota and metabolites in hypertension and diabetic nephropathy SPF rat models.TIF

BackgroundImbalance in intestinal microbiota caused by microbial species and proportions or metabolites derived from microbes are associated with hypertension, as well as diabetic nephropathy. However, the involvement of the intestinal microbiota and metabolites in hypertension and diabetic nephropathy comorbidities (HDN) remains to be elucidated.MethodsWe investigated the effects of intestinal microbiota on HDN in a rat model and determined the abundance of the intestinal microbiota using 16S rRNA sequencing. Changes in fecal and serum metabolites were analyzed using ultra-high-performance liquid chromatography-mass spectrometry.ResultsThe results showed abundance of Proteobacteria and Verrucomicrobia was substantially higher, whereas that of Bacteroidetes was significant lower in the HDN group than in the sham group. Akkermansia, Bacteroides, Blautia, Turicibacter, Lactobacillus, Romboutsia, and Fusicatenibacter were the most abundant, and Prevotella, Lachnospiraceae_NK4A136_group, and Prevotella_9 were the least abundant in the HDN group. Further analysis with bile acid metabolites in serum showed that Blautia was negatively correlated with taurochenodeoxycholic acid, taurocholic acid, positively correlated with cholic acid and glycocholic acid in serum.ConclusionsThese findings suggest that the gut microbiota and metabolites in feces and serum substantially differed between the HDN and sham groups. The F/B ratio was higher in the HDN group than in the sham group. Blautia is potentially associated with HDN that correlated with differentially expressed bile acid metabolites, which might regulate the pathogenesis of HDN via the microorganism–gut–metabolite axis.</p

Table_3_A multi-omics approach to investigate characteristics of gut microbiota and metabolites in hypertension and diabetic nephropathy SPF rat models.XLSX

BackgroundImbalance in intestinal microbiota caused by microbial species and proportions or metabolites derived from microbes are associated with hypertension, as well as diabetic nephropathy. However, the involvement of the intestinal microbiota and metabolites in hypertension and diabetic nephropathy comorbidities (HDN) remains to be elucidated.MethodsWe investigated the effects of intestinal microbiota on HDN in a rat model and determined the abundance of the intestinal microbiota using 16S rRNA sequencing. Changes in fecal and serum metabolites were analyzed using ultra-high-performance liquid chromatography-mass spectrometry.ResultsThe results showed abundance of Proteobacteria and Verrucomicrobia was substantially higher, whereas that of Bacteroidetes was significant lower in the HDN group than in the sham group. Akkermansia, Bacteroides, Blautia, Turicibacter, Lactobacillus, Romboutsia, and Fusicatenibacter were the most abundant, and Prevotella, Lachnospiraceae_NK4A136_group, and Prevotella_9 were the least abundant in the HDN group. Further analysis with bile acid metabolites in serum showed that Blautia was negatively correlated with taurochenodeoxycholic acid, taurocholic acid, positively correlated with cholic acid and glycocholic acid in serum.ConclusionsThese findings suggest that the gut microbiota and metabolites in feces and serum substantially differed between the HDN and sham groups. The F/B ratio was higher in the HDN group than in the sham group. Blautia is potentially associated with HDN that correlated with differentially expressed bile acid metabolites, which might regulate the pathogenesis of HDN via the microorganism–gut–metabolite axis.</p

Image_1_A multi-omics approach to investigate characteristics of gut microbiota and metabolites in hypertension and diabetic nephropathy SPF rat models.TIF

BackgroundImbalance in intestinal microbiota caused by microbial species and proportions or metabolites derived from microbes are associated with hypertension, as well as diabetic nephropathy. However, the involvement of the intestinal microbiota and metabolites in hypertension and diabetic nephropathy comorbidities (HDN) remains to be elucidated.MethodsWe investigated the effects of intestinal microbiota on HDN in a rat model and determined the abundance of the intestinal microbiota using 16S rRNA sequencing. Changes in fecal and serum metabolites were analyzed using ultra-high-performance liquid chromatography-mass spectrometry.ResultsThe results showed abundance of Proteobacteria and Verrucomicrobia was substantially higher, whereas that of Bacteroidetes was significant lower in the HDN group than in the sham group. Akkermansia, Bacteroides, Blautia, Turicibacter, Lactobacillus, Romboutsia, and Fusicatenibacter were the most abundant, and Prevotella, Lachnospiraceae_NK4A136_group, and Prevotella_9 were the least abundant in the HDN group. Further analysis with bile acid metabolites in serum showed that Blautia was negatively correlated with taurochenodeoxycholic acid, taurocholic acid, positively correlated with cholic acid and glycocholic acid in serum.ConclusionsThese findings suggest that the gut microbiota and metabolites in feces and serum substantially differed between the HDN and sham groups. The F/B ratio was higher in the HDN group than in the sham group. Blautia is potentially associated with HDN that correlated with differentially expressed bile acid metabolites, which might regulate the pathogenesis of HDN via the microorganism–gut–metabolite axis.</p

Cellobiose and xylobiose uptake of ST transporters <i>in vivo</i>.

<p><b>A)</b> Cellobiose (G2), <b>B</b>) xylobiose (X2) and <b>C</b>) xylotriose (X3) uptake from D452-2 cells expressing ST transporters. Cells were incubated in buffer containing 200 μM sugar. Polysaccharide concentrations were measured at t = 0 min and t = 30 min. The concentration of sugar consumed was normalized to 1 OD unit of cells. Measurements represent the mean sugar uptake along with corresponding standard error from biological triplicates.</p

Competition between xylobiose and cellobiose uptake.

<p>Xylobiose uptake in the presence of increasing concentrations of cellobiose in cells expressing ST transporters. Cells were incubated in buffer containing 200 μM X2 along with increasing stoichiometric ratios of G2: 0X, 1X, and 10X the concentration of X2. Measurements represent mean X2 consumed after 30 min incubation from biological triplicates for each ratio indicated, along with standard error bars.</p

Chromosomal expression of transporter ST16 relative to plasmid-based expression slows aerobic growth.

<p><b>A</b>). Aerobic growth profiles of yeast SR8A strains with plasmid expressing CDT-2, ST16 or empty control were compared with ST16 transporter expressed from a chromosomal copy at the <i>LEU2</i> locus. Error bars represent standard deviations of biological triplicates. <b>B</b>). GFP fluorescence emission spectroscopy analysis of ST16-GFP fusion expression. ST16, cells lacking the GFP fusion to establish baseline fluorescence.</p

Aerobic growth profile of ST transporters on xylodextrin.

<p><b>A</b>). Growth curve of SR8A strain expressing CDT-2 from a plasmid up to 96 hours, with the area under the curve (AUC) shaded. A representative experiment is shown with xylodextrin as the sole carbon source under aerobic conditions. <b>B</b>). AUCs for SR8A strains with plasmids expressing different ST transporters. AUCs are plotted as the log₂ of the ratio of ST over CDT-2 AUCs. All experiments were conducted in biological triplicate, with error bars representing standard deviations.</p