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AimsHypertension (HTN) can lead to heart and kidney damage. The gut microbiota has been linked to HTN, although it is difficult to estimate its significance due to the variety of other features known to influence HTN. In the present study, we used germ-free (GF) and colonized (COL) littermate mice to quantify the impact of microbial colonization on organ damage in HTN.Methods and resultsFour-week-old male GF C57BL/6J littermates were randomized to remain GF or receive microbial colonization. HTN was induced by subcutaneous infusion with angiotensin (Ang) II (1.44mg/kg/d) and 1% NaCl in the drinking water; sham-treated mice served as control. Renal damage was exacerbated in GF mice, whereas cardiac damage was more comparable between COL and GF, suggesting that the kidney is more sensitive to microbial influence. Multivariate analysis revealed a larger effect of HTN in GF mice. Serum metabolomics demonstrated that the colonization status influences circulating metabolites relevant to HTN. Importantly, GF mice were deficient in anti-inflammatory fecal short-chain fatty acids (SCFA). Flow cytometry showed that the microbiome has an impact on the induction of anti-hypertensive myeloid-derived suppressor cells and pro-inflammatory Th17 cells in HTN. In vitro inducibility of Th17 cells was significantly higher for cells isolated from GF than conventionally raised mice.ConclusionsMicrobial colonization status of mice had potent effects on their phenotypic response to a hypertensive stimulus, and the kidney is a highly microbiota-susceptible target organ in HTN. The magnitude of the pathogenic response in GF mice underscores the role of the microbiome in mediating inflammation in HTN.Translation PerspectiveTo assess the potential of microbiota-targeted interventions to prevent organ damage in hypertension, an accurate quantification of microbial influence is necessary. We provide evidence that the development of hypertensive organ damage is dependent on colonization status and suggest that a healthy microbiota provides anti-hypertensive immune and metabolic signals to the host. In the absence of normal symbiotic host-microbiome interactions, hypertensive damage to the kidney in particular is exacerbated. We suggest that hypertensive patients experiencing perturbations to the microbiota, which are common in CVD, may be at a greater risk for target-organ damage than those with a healthy microbiome.

Introduction: The gut microbiota is suspected to play a role in hypertension and hypertensive end organ damage. In the present study, we used germ-free mice to demonstrate that microbial colonization modulates the response to a hypertensive stimulus. Methods: Four-week-old male germ-free C57BL6/J littermates were randomized to remain germ-free (GF) or to receive microbiota transfer from SPF donor mice to achieve full colonization status (COL). At 12 weeks, Angiotensin (Ang) II was infused s.c. for 14 days (1.44mg/kg/d, osmotic minipumps) and 1% NaCl added to the drinking water; sham-treated mice served as control. After 14 days of AngII we assessed inflammation and organ damage. Results: Fecal bacterial load in COL mice was similar to SPF donor mice (qPCR). Shotgun metagenomic sequencing of fecal samples revealed hypertension-induced alterations in microbiome composition confirming previous reports. Serum metabolome analysis ( Biocrates MxP Quant 500) confirmed the absence of microbiota-dependent metabolites in GF. Interestingly, microbiota-dependent metabolites relevant for cardiovascular risk (TMAO, indoxyl sulfate) were elevated in hypertensive COL mice compared to sham-treated. Hypertensive kidney damage was aggravated in GF mice. However, marker genes for tubular damage ( Lcn2 ), inflammation ( Ccl2 ), and fibrosis ( Col1a3 ) showed a stronger increase in GF mice (fold changes [fc] COL vs. GF: 7.5 vs 11.0, 1.2 vs 3.3, 1.3 vs 2.2, respectively). Albuminuria (fc 2 vs 25) and histology for kidney fibrosis (fc 1.1 vs 1.4) confirmed the aggravated kidney damage in GF mice. Similarly, we observed an aggravated cardiac damage in GF mice. Flow cytometry of splenic lymphocytes showed that the adaptive immune response to AngII + 1% NaCl, as evidenced by Th17 (fc 1.4 vs 2) and CD8+ central memory cells, was intensified in GF mice. In vitro , naïve T cells isolated from GF mice more readily polarized into Th17 (26 ± 5%) compared to T cells from SPF mice (19 ± 1%). Conclusion: The bacterial colonization status has potent effects on the phenotypic response to a hypertensive stimulus, evident to varying degrees in hearts and kidneys. The inflammatory response and the end organ damage in GF compared to COL mice demonstrates the importance of the gut microbiota in hypertension.

Aims Recent technical developments have allowed the study of the human microbiome to accelerate at an unprecedented pace. Methodological differences may have considerable impact on the results obtained. Thus, we investigated how different storage, isolation, and DNA extraction methods can influence the characterization of the intestinal microbiome, compared to the impact of true biological signals such as intraindividual variability, nutrition, health, and demographics. Methods and results An observative cohort study in 27 healthy subjects was performed. Participants were instructed to collect stool samples twice spaced by a week, using six different methods (naive and Zymo DNA/RNA Shield on dry ice, OMNIgene GUT, RNALater, 95% ethanol, Zymo DNA/RNA Shield at room temperature). DNA extraction from all samples was performed comparatively using QIAamp Power Fecal and ZymoBIOMICS DNA Kits. 16S rRNA sequencing of the gut microbiota as well as qPCRs were performed on the isolated DNA. Metrics included alpha diversity as well as multivariate and univariate comparisons of samples, controlling for covariate patterns computationally. Interindividual differences explained 7.4% of overall microbiome variability, whereas the choice of DNA extraction method explained a further 5.7%. At phylum level, the tested kits differed in their recovery of Gram-positive bacteria, which is reflected in a significantly skewed enterotype distribution. Conclusion DNA extraction methods had the highest impact on observed microbiome variability, and were comparable to interindividual differences, thus may spuriously mimic the microbiome signatures of various health and nutrition factors. Conversely, collection methods had a relatively small influence on microbiome composition. The present study provides necessary insight into the technical variables which can lead to divergent results from seemingly similar study designs. We anticipate that these results will contribute to future efforts towards standardization of microbiome quantification procedures in clinical research.