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Diurnal Timing Dependent Alterations in Gut Microbial Composition Are Synchronously Linked to Salt-Sensitive Hypertension and Renal Damage

Originally publishedhttps://doi.org/10.1161/HYPERTENSIONAHA.120.14830Hypertension. 2020;76:59–72

Abstract

Alterations of diurnal rhythms of blood pressure (BP) and reshaping of gut microbiota are both independently associated with hypertension. However, the relationships between biorhythms of BP and gut microbial composition are unknown. We hypothesized that diurnal timing-associated alterations of microbial compositions are synchronous with diurnal rhythmicity, dip in BP, and renal function. To test this hypothesis, Dahl salt-sensitive (S) rats on low- and high-salt diets were examined for time of day effects on gut microbiota, BP, and indicators of renal damage. Major shifts in night and day patterns of specific groups of microbiota were observed between the dark (active) and light (rest) phases, which correlated with diurnal rhythmicity of BP. The diurnal abundance of Firmicutes, Bacteroidetes, and Actinobacteria were independently associated with BP. Discrete bacterial taxa were observed to correlate independently or interactively with one or more of the following 3 factors: (1) BP rhythm, (2) dietary salt, and (3) dip in BP. Phylogenetic Investigation of Communities revealed diurnal timing effects on microbial pathways, characterized by upregulated biosynthetic processes during the active phase of host, and upregulated degradation pathways of metabolites in the resting phase. Additional metagenomics functional pathways with rhythm variations were noted for aromatic amino acid metabolism and taurine metabolism. These diurnal timing dependent changes in microbiota, their functional pathways, and BP dip were associated with concerted effects of the levels of renal lipocalin 2 and kidney injury molecule-1 expression. These data provide evidence for a firm and concerted diurnal timing effects of BP, renal damage, and select microbial communities.

Introduction

Circadian, diurnal rhythm is a vital physiological feature of life forms, which enables holobionts to adapt to the day and night cycles of planet Earth. Evidence suggests that both factions of the holobiont, that is, the host and its microbiota demonstrate physiological circadian rhythms. Blood pressure (BP) is a good example of a host physiological feature with a well-defined diurnal rhythm. In a healthy human, BP rises to its peak during awakening morning hours and declines to the lowest level during night, which is 10% to 20% lower compared with the daytime mean.1 This diurnal rhythm of BP of the host is primarily influenced by both intrinsic genetic factors2,3 and extrinsic environmental factors.3,4 Recent research suggests that intestinal microbiota also exhibit similar diurnal rhythms. Studies in mice have shown that both compositional and functional profiles of gut microbiota show circadian oscillations.5,6 Diurnal rhythms of the intestinal gut microbiota are primarily modulated by diet, time of feeding, and its communication with the host.7 Thaiss et al8 reported that food intake mainly in the dark (active) phase of rodents leads to a shift of gut microbial functional pathways towards energy metabolism, DNA repair, and cell growth. Conversely, chemotaxis and adherence of bacteria to epithelial mucus are enriched in the light resting phase.8 Such cyclical patterns in gut microbiota and its metabolic activity also affect host physiology. For example, bile acids and their metabolism involve both host and microbiota activities.9 Circadian peaks of primary and secondary bile acids in serum were also demonstrated.10 Thus, the interplay of the gut microbiota with host metabolism in response to external cues such as diet and circadian disruption appears to have far-reaching health consequences on the holobiont.11–18

In recent years, there has been a greater appreciation of links between hypertension and gut microbiota.19–50 We and others have shown that consumption of a high-salt diet alters gut microbial composition and causes a shift in the energy metabolism of the host.51–53 Due to the links between energy metabolism and microbial rhythms as well as the primary nature of BP following natural diurnal rhythms, we hypothesized that diurnal timing alterations in gut microbial compositions are associated with characteristic features of salt-sensitive hypertension. To test this hypothesis, we used the inbred Dahl salt-sensitive (S) rat. This is a well-established model of hypertension, originally housed at the University of Toledo since the 1980s.54 The S rats have been extensively investigated for genetic factors contributing to hypertension and more recently for understanding the microbial and metabolic contributions to BP regulation.21–23,36,37,39,51,55 Previous works have demonstrated that a high-salt diet alters circadian BP rhythm of the S rats.56–60 Thus, we used this strain to study the relationship between gut microbiota, dietary salt, and diurnal timing effects on the BP hemodynamics of the host.

Methods

Data, analytic methods, and study materials will be made available to other researchers upon request.

Animal Study

The study design was approved by the University of Toledo Institutional Animal Care and Use Committee. All the animals were male Dahl salt-sensitive (S) rats maintained on a low-salt (0.3% NaCl, Harlan Teklad, 7034) diet until weaning. The rats were on a normal 12:12 light: dark cycle. Concomitantly raised pups were weaned at 4 weeks of age, assigned to various experimental groups, and maintained either on a low-salt or a high-salt (2% NaCl, Harlan Teklad, TD94217) diet. Rats were euthanized at ≈3 months of age. Groups of rats were euthanized during the dark phase (2:00 am–4:00 am) and light phases (3:00 pm–5:00 pm), and tissues were harvested. Blood was collected at these 2 distinct periods. The fecal samples were collected freshly just moments before euthanization of the animals for harvesting tissues at the 2-time points. Serum was separated and frozen at −80°C until further use. All the tissue samples were snap-frozen in liquid nitrogen and saved at −80°C.

Measurement of BP and Activity

Experimental groups of rats were implanted with radio-telemetry transmitters as described previously.21 Postsurgical care was provided for 48 hours. BP and activity were recorded using the DSI software and equipment (https://www.datasci.com/). Dataquest A.R.T 4.2 Software was used to analyze the systolic, diastolic, mean arterial pressure, and activity collected at 5-minute intervals to get average value in each hour.

16S rRNA Gene Analysis

QIAampPower Fecal_DNA kit (QIAGEN) was used to extract DNA from the fecal pellet (≈0.2 g) collected at two separate time windows as described later under the results section. Fifty milliliters of low Tris-Ethylenediaminetetraacetic acid buffer (0.1 mmol/L Ethylenediaminetetraacetic acid, Tris-HCl buffer, 10 mmol/L, pH8.5) was used for the elution of DNA instead of the AE buffer provided in the kit. DNA concentration was determined using the NanoDrop and further diluted using a low Tris-Ethylenediaminetetraacetic acid buffer to a final concentration of 5ng/mL. For 16S library preparation and processing, the Illumina User Guide for 16S Metagenomic Sequencing Library Preparation section ‘Preparing 16S Ribosomal RNA Gene Amplicons for the Illumina MiSeq System (Part No. 15044223 Rev. B) for 16S library preparation, clean-up, normalization, and pooling’ was followed. Ilumina primers used for amplification of the 16S rRNA gene-targeted the V3-V4 region. The primer sequences were as follows:

TCGTCGGC AGCGTCAGATGTGT ATAAGAGACAGC CTACGGGNGG CWGCAG and GTCTCGT GGGCTCGGA GATGTGTATAAGAGA CAGGGACTACHV GGGTWTCTAAT. Raw 16S sequencing data were processed and analyzed using a bioinformatics pipeline comprising of multiple software using methods described earlier.51

Quality Filtering, Operational Taxonomic Units Picking, and Data Analysis

Raw 16S sequencing data were processed and analyzed using a bioinformatics pipeline of multiple software including USEARCH,61 Quantitative Insights Into microbial Ecology software package (version 1.9.1),62 linear discriminant analysis effect size,63 phylogenetic investigation of communities by reconstruction of unobserved states,64 and HMP unified metabolic analysis network.65

Raw paired-end reads were merged to create consensus sequences and then quality filtered using USEARCH (version 9). Chimeric sequences were identified and filtered using Quantitative Insights Into Microbial Ecology combined with the USEARCH (version 6) algorithm. Open reference operational taxonomic units were subsequently picked using Quantitative Insights Into microbial Ecology combined with the USEARCH (version 6) algorithm, and taxonomy assignment was performed using Greengenes66 as the reference database. Using a series of Quantitative Insights Into microbial Ecology pipelines, α- and β-diversity analyses were performed using a BIOM formatted operational taxonomic unit table. Taxonomic features with difference abundance were further summarized using linear discriminant analysis effect size (https://huttenhower.sph.harvard.edu/galaxy/) for group comparisons and predictive metagenome functional analysis was performed using phylogenetic investigation of communities by reconstruction of unobserved states and HMP unified metabolic analysis network.

RNA Isolation and Real Time-Polymerase Chain Reaction

RNA was extracted from kidney and distal colon samples from low salt and high salt fed animals (at the same 2 aforementioned timepoints for fecal collections) using the TRIzol method as described earlier.51 RNA concentration was measured using a NanoDrop and reverse transcription-polymerase chain reaction was performed to prepare cDNA using the SuperScript III kit (Invitrogen) using random hexamer primers. The resultant cDNA was diluted, and real-time polymerase chain reaction mixtures were set up using the SYBR Green master mix (Applied Biosystems). Following polymerase chain reaction amplification, mRNA levels of Lcn2, Kim1, Mcp1, Il18, and Tnfa was determined using the 2ΔΔCt method.51

Measurement of β-Hydroxybutyrate

β-Hydroxybutyrate level was measured in the serum obtained from low salt, high salt, or high salt with 1,3-butanediol groups by using a colorimetric assay kit (Cayman Chemicals, catalog No. 700190). Briefly, serum was diluted to 1:6 with assay buffer provided in the kit. Standard was prepared as per manufacturer’s protocol. The standards and samples were added into respective wells, and reaction was triggered by adding the developer solution. After 30 minutes of incubation at 25°C in dark, optical density was recorded at 450 nm using SpectraMax M3 microplate reader from Molecular Devices (Sunnyvale, CA).

Data Analysis and Visualization

Graph Pad Prism version 8.1.1 were used for statistical analysis and data presentation, respectively. Nonparametric Mann-Whitney test was used to compare 2 groups, whereas 1-way ANOVA with Bonferroni post hoc test was used for studies with >2 groups. For 2 groups with 2 factors (ie, salt, rhythms), 2-way ANOVA was applied followed by Tukey multiple comparisons. Statistically significant values were represented as P≤0.05 (*), P≤0.01 (**), and P≤0.001 (***). All the figures with scattered dots are expressed as Mean±SEM. Information on replicates for each experiment are provided in the figures/figure legends. To summarize the direction of time of day responsive alteration of microbiota, we took the relative abundance of each microbiota in each sample, combined the relative abundance of all samples of each bacterium separately. Next, we divided each sample microbiota abundance with the combined abundance and multiply by 100 to determine percent normalized abundance and plotted it with Graph Pad Prism. Clustered correlation heatmap (Figure S2 and S5 in the Data Supplement) was created using R v3.5.2, heatmap3 function and Ward clustering method. In Figure 5, only relevant metagenomic pathways (Time of day-responsive, salt-responsive, and BP dip-responsive) were used to generate the heatmap. Un-clustered correlation heatmap was also created using Graph Pad Prism Version 8.1.1.

Results

Correlation of Gut Microbial and BP Diurnal Rhythms in Salt-Induced Hypertensive S Rats

Groups of Dahl S rats on low- and high-salt diets were monitored for BP by telemetry during their active and resting phases. In both low- and high-salt fed groups, systolic BP demonstrated a diurnal rhythm with increased BP during the dark (active) phase and decreased BP during the light (rest) phase (Figure 1A and 1B). Further, the systolic BP difference between dark and light phases over 48 hours was significantly higher in the high-salt fed S rats than that of the low-salt fed rats (Figure 1C). To determine if there were concerted time of day correlation of gut microbiota with systolic BP, fecal samples collected at the peak and trough time points of BP were examined by 16S sequencing (Table S1). Beta diversity biplot indicated that microbial compositions of rats on a low-salt diet clustered together whereas, microbial composition of rats on a high-salt diet clustered differentially depending on the time of day when their fecal samples were collected (Figure S1). Bacteroidetes and Firmicutes, the 2 major phyla constituting almost 90% of the total gut microbiota, were significantly different between the dark and light phases in the high-salt fed rats, but only trending in the low-salt fed group (Figure 1D and 1E). Specifically, in the light (rest) phase when BP was lower, there was a marked increase in Firmicutes compared with that in the dark (active) phase (Figure 1D). Conversely, Bacteroidetes were significantly lower in the light (rest) phase than that in the dark (active) phase (Figure 1E). Further, a 2-way ANOVA conducted to differentiate between salt and diurnal timing effects on microbiota demonstrated a significant impact of only timing, but not salt, as an independent factor correlating with the abundance of both Firmicutes and Bacteroidetes and only salt, but not timing, as an independent factor affecting the abundance of Actinobacteria (Figure 1D through 1F). The diurnal timing effect on both Firmicutes and Bacteroidetes resulted in a prominent inverse correlation of the ratio of Firmicutes to Bacteroidetes (F/B) with BP in the high-salt fed group (Figure 1B). However, this difference in the F/B ratio was trending, but not statistically significant in the low-salt fed S rats (Figure 1A and 1B).

Figure 1.

Figure 1. Synchronous diurnal rhythms of blood pressure (BP) and gut microbial the ratio of Firmicutes/Bacteroidetes abundance (F/B) ratio in S rats. Systolic BP was consecutively measured by radio telemetry for 48 h on (A) low (0.3%) NaCl and (B) high (2%) NaCl diets. C, Blood pressure Dip (BP Dip), the difference in mean systolic BP between the dark and light cycles, is significantly higher in S rats on a high-salt diet than those on a low-salt diet. D–F, The relative abundance of bacterial phyla in the dark and light phases were evaluated by 16S rRNA gene sequencing. All values are mean±SEM, N=5 per group. B, **P<0.01 by 2-way ANOVA followed by Tukey post hoc test. C, **P<0.01 in nonparametric Mann-Whitney test. D–F, *P<0.05 and ** P<0.01 by 2-way ANOVA analysis followed by Tukey post hoc test.

To further identify groups of bacterial taxa that were synchronous with diurnal rhythms in both the low- and high-salt fed groups of rats, an unsupervised hierarchical clustering analysis was conducted, whereby bacterial taxa clustered based on their similarity in abundance levels between the low- and high-salt fed rats at the 2-time points (ie, dark (active) and light (rest) phases (Figure S2). Among these, statistically significant taxa are shown in Figure 2. The major groups of bacterial taxa representing timing-responsive, salt-responsive, and BP dip-responsive microbiota are presented in Figure S2. Among these, the most significantly timing-responsive microbiota were f_Streptococcaceae, f_Veillonellaceae, f_Clostridiaceae, f_Helicobacteriaceae; other, g_Lactobacillus, g_Sutterella, f_Erysipelotrichaceae (Figure 2A through 2G). However, g_Prevotella was only trending towards significance (Figure 2H).

Figure 2.

Figure 2. The effects of diurnal timing, salt, and their interaction on the abundance of bacterial taxa. The relative abundance of bacteria taxa responsive to diurnal timing, salt, and blood pressure (BP) dip were presented in bar graph. A–H, Abundance of time of day-responsive microbiota in low- and high-salt fed rats. F–N, Abundance of salt-responsive microbiota in dark and light phases. E, F, and O, Taxa demonstrating an interactive effect between salt and time of day. F, G, and O, Dashed arrows in these plots depict taxa that are responsive to BP dip. Each data point represents relative abundance value in percentage obtained from a single animal. N=5 per group. All data analyzed by 2-way ANOVA followed by Tukey post hoc test, *P<0.05, **P<0.01, and ***P<0.001.

Similar to the timing-responsive microbiota, we found several taxa to be independently associated with salt (Figure S2). Among these, the most significant salt-responsive taxa were f_Lachnospiraceae; other, f_Ruminococcaceae, g_Paraprevotella, g_Turicibacter, g_Allobaculum, g_Sutterella, f_Erysipelotrichaceae, g_Prevotella, and g_Anaerostipes (Figure 2F though 2N).

Besides rhythm and salt, the magnitude of BP was independently associated with specific microbiota. We categorized these as BP dip-responsive microbiota (Figure S2). Among these, the most significant BP dip-responsive taxa were represented by g_Sutterella, f_Erysipelotrichaceae, and o_Clostridiales (Figure 2F, 2G, and 2O).

Next, we queried for interactive effects between diurnal timing and salt by conducting a 2-way ANOVA. Accordingly, g_Lactobacillus, g_Sutterella, and o_Clostridiales were identified as taxa that were responsive to an interactive effect between time of day and salt (Figure 2E, 2F, and 2O). Since the current work was focused on the diurnal timing effect, we summarized the timing-responsive bacteria with respect to their direction of change between the dark and light cycles. Figure S3A shows the composite directionality of bacteria that are collectively either up or down in abundance between the dark and light cycles. A similar composite for salt-responsive taxa is provided in Figure S3B. However, no bacteria were found to be correlated with a P<0.05 with the activity of the host (Figure S4, activity was recorded from BP telemeters).

Diurnal Timing, Salt and BP Dip-Responsive Microbiota Correlate With Systolic BP

Having noted these discrete alterations in bacterial taxa responsive to either timing or salt, we asked which of these alterations correlated with systolic BP. Figure 3A is the correlation plot of diurnal timing-responsive taxa occurring in a high-salt fed condition. There were 5 groups significantly correlating with systolic BP. These were f_Clostridiace, g_Sutterella, g_Prevotella, o_Clostridiales, and F/B ratio. While abundances in g_Sutterella and g_Prevotella directly correlated with systolic BP, abundances in f_Clostridiaceae, o_Clostridiales, and F/B ratio were inversely correlated with systolic BP (Figure 3A). These correlations were specific to a high-salt condition as none were significant in the timing-responsive taxa under a low-salt condition (Figure 3B).

Figure 3.

Figure 3. Heatmap of microbiota with systolic blood pressure (SBP) for diurnal timing effect in high-salt fed rats and diurnal timing effect in low-salt fed rats. A) Rhythmicity in high salt and B) rhythmicity in low salt. The bottom of (A) are expanded views of significantly correlated taxa with SBP (n=9 per group) wherein plots shown in gray represent inverse correlations. Plots shown in pink represent direct correlations. *P<0.05, **P<0.01, and ***P<0.001 as determined by Spearman correlation analysis. F/B indicates Firmicutes/Bacteroidetes.

Next, we examined salt-sensitivity in the dark and light phases by querying for bacterial taxa which corresponded with the BP dip of systolic BP. Figure 4A indicates that systolic BP is directly correlated with f_Lachnospiraceae; other, whereas BP is inversely correlated with g_Prevotella, g_Anaerostipes, o_Clostridiales in dark phase. Similarly, P_Actinobacteria and f_Lachnospiraceae were directly correlated and g_Lactobacillus and g_Anaerostipes were inversely correlated with systolic BP in the light phase (Figure 4B).

Figure 4.

Figure 4. Heatmap of microbiota with systolic blood pressure (SBP) for salt-sensitivity in the dark (active) phase and salt-sensitivity in the light (rest) phase. A) salt-sensitivity in the dark phase and B) salt-sensitivity in the light phase. The bottom of (A; n=10 per group) and (B; n=8 per group) are expanded views of significantly correlated taxa with SBP. Plots shown in grey represent inverse correlations. Plots shown in pink represent direct correlations. *P<0.05, **P<0.01, and ***P<0.001 as determined by Spearman correlation analysis. F/B indicates Firmicutes/Bacteroidetes.

There were additional taxa in Figures 3 and 4 that were respectively associated with either timing and salt-sensitivity but were not correlated with systolic BP. These taxa were perhaps quorum-sensing bacteria expanding or contracting in their abundances based on the ones that were correlating with systolic BP.

Distinct Clusters of Diurnal Timing- and Salt-Responsive Functional Pathways

Next, we sought to understand the metagenomic functional pathways altered as a result of the dynamic diurnal alterations in bacterial taxa (Table II in the Data Supplement). There was a clear difference in metagenomic functional pathways between dark (active) and light (rest) phases (Figure 5). The timing-responsive pathways upregulated in the dark (active) phase were mostly biosynthetic processes of steroid hormones, steroids, aromatic amino acids, N.Glycan, polyketide sugar, signaling pathways such as p53, Peroxisome proliferator-activated receptor (Ppar), Nucleotide-binding and oligomerization domain (NOD)-like receptor and epithelial cell signaling pathways (Figure 5). In contrast, the time of day-responsive pathways upregulated in the light (rest) phase were largely degradation and metabolic pathways of a variety of biochemicals including ketone bodies, short-chain fatty acids (propanoate, butanoate), aromatic amino acids (cysteine, methionine, and tyrosine), and aromatic molecules (Dichloro Diphenyl Trichloroethane, dioxin, xylene, benzoate, styrene, bisphenol, naphthalene). In addition, both gluconeogenesis and the phosphotransferase system were upregulated in the light (rest) phase, whereas oxidative phosphorylation was upregulated in the dark (active) phase. Besides these, unique pathways independently responsive to dietary salt were noted. These included the metabolic pathways enriched in the rat on high salt (ie, metabolism of starch and sucrose, arginine and proline, nitrogen and methane), whereas other metabolic pathways such as metabolism of taurine and hypotaurine, pyrimidine, glutathione, arachidonic acid, alpha-linolenic acid, Inositol phosphate which were enriched in low salt-consuming rats (Figure 5). In addition, degradation pathways of valine, leucine, and isoleucine were enriched in the low-salt group compared with the high-salt group.

Figure 5.

Figure 5. Unbiased clustering of predicted metagenomic functional pathways in S rats on low- and high-salt diets during light and dark phases. Relevant metagenomic functional pathways data predicted based on the16s rDNA gene sequencing analysis were subjected to unbiased hierarchical clustering to generate the heatmap. Data was auto-scaled based on the column, and the Ward clustering method was used. Blue color on the scale indicates lower abundance in predicted bacterial function while red color is for higher prevalence of predicted bacterial function. Purple rectangles highlight the diurnal timing responsive bacterial function. Blue rectangles are for salt-responsive bacterial function. Red rectangles are for interaction (BP dip)-responsive bacterial function. HS indicates high salt and LS, low salt.

Distinct Clusters of BP Dip-Responsive Functional Pathways

Next, we asked if there were functional pathways associated with the reshaping of microbiota representing an interaction between diurnal timing and salt. These pathways marked as, BP dip, in Figure 5 were overrepresented exclusively in the animals on a high-salt diet during their active phase. These upregulated pathways were noted as biotin and riboflavin metabolism, penicillin and cephalosporin biosynthesis, beta-lactam resistance and photosynthesis. Similarly, the functional pathways downregulated with the BP dip of BP in the active phase of the high-salt fed group, compared with all the other groups, were ascorbate, aldarate and flagellar assembly and caprolactam degradation (Figure 5).

In all these analyses, it is important to note that the phylogenetic investigation of communities by reconstruction of unobserved states method was used which has the obvious limitation of being a predictive tool.

Synchronous Diurnal Variation in Renal Damage Markers

In addition to gut microbial reshaping,21 renal damage is another feature of the pathology exhibited by the salt-sensitive hypertensive S rats.51,67–74 Given the observed diurnal variation in gut microbiota and BP in the S rats, we evaluated the diurnal expression of lipocalin 2 (Lcn2), kidney injury marker 1 (Kim1), monocyte chemoattractant protein 1 (Mcp1), interleukin 18 (Il18) and tumor necrosis factor α (Tnfα). Expression of Mcp1, Il18, and Tnfa were influenced by dietary salt. The renal expression of Lcn2 was markedly influenced by both the factors, diurnal timing as well as salt (Figure 6A). The diurnal timing effect was prominent in the S rats on high salt, wherein Lcn2 was significantly upregulated during the dark (active) phase compared with the light (rest) phase (Figure 6A). However, this timing effect was blunted in the low-salt groups (Figure 6A), suggesting an interactive effect between timing and salt on Lcn2. Indeed, the interactive effect between the 2 factors on Lcn2 expression was statistically significant (Figure 6A). Similar results were also found with the kidney injury marker 1 (Kim1; Figure 6B). In accordance with the dip of BP differences found in the dark phase between high and low salt groups, Mcp1, Il18 showed significantly higher expression in high salt compared with low-salt group in the dark phase (Figure 6C and 6D). These results demonstrated a strong correlation between the biorhythmicity of BP, gut microbiota, and renal damage markers operating either independently or interactively with dietary salt.

Figure 6.

Figure 6. Renal damage markers and ketone body level in S rats on low- and high-salt diets in the dark and light phases. The relative fold change of renal (A) Lipocalin 2 (Lcn2), (B) kidney injury marker 1 (Kim1), (C) monocyte chemoattractant protein 1 (Mcp1), (D) interleukin 18 (Il18), (E) tumor necrosis factor α (Tnfα), and the circulating level of (F) β-hydroxybutyrate was measured by a colorimetric assay as described in the methods section. The significance of diurnal timing, salt and interaction effectors were evaluated by 2-way ANOVA. The difference between groups was determined by 2-way ANOVA analysis followed by the Tukey post hoc test; *P<0.05 and **P<0.01.

Lack of Synchronous Diurnal Variation in Salt-Responsive Ketone Metabolism

We have previously shown that β-hydroxybutyrate, a ketone body inhibited by high salt, attenuates hypertension in the S rats on a high-salt diet.51 Therefore, we examined the circulating levels of β-hydroxybutyrate to investigate its diurnal association with gut microbiota, renal damage, and BP. The circulating level of β-hydroxybutyrate was decreased in the S rats on a hig-salt diet in the dark (active) phase, compared with those on a low-salt diet (Figure 6F). This difference in circulating levels of β-hydroxybutyrate between low- and high-salt groups subsided in the light phase when the animals were resting. Therefore, there was a significant salt effect on the levels of β-hydroxybutyrate. Despite the strong salt effect on this metabolite, a 2-way ANOVA indicated that the circulating levels of β-hydroxybutyrate were not affected by rhythm either as an independent or as an interactive factor. These data suggest that the metabolic effects of salt on ketone body production are not synchronously aligned with the diurnal timing of gut microbiota and BP.

Discussion

This study investigated the correlation between diurnal rhythms of salt-sensitive BP and diurnal timing variation in gut microbial composition and function. Significant correlations were observed between the biorhythms of both BP and gut microbial composition. Interestingly, renal damage markers were also observed to follow a concerted diurnal variation. Both independent and interactive effects were detected for rhythm and dietary salt as factors associated with microbiota. Further, distinct metagenomic functional pathways were found to be associated with the rhythmicity of BP. To our knowledge, this study is the first to illustrate that the diurnal variation of the host hemodynamic function and composition of gut microbiota are associated and operate synchronously in a high-salt diet-induced hypertensive state.

Intrinsic circadian rhythms of physiological processes evolved to adapt to the 24-hour dark-light cycle.75 While circadian rhythms in BP regulation are well known,76–79 recent evidence suggests that such rhythms are also exhibited by gut microbial composition.12–18,80–86 Deletion of Bmal1, a master circadian gene, abolished diurnal oscillation of the relative and absolute abundances of Bacteroides and Lactobacillus spp.6 These together indicate that the entire holobiont is closely influenced by circadian rhythms. Considering the role of gut microbiota in BP regulation, we posed a fundamental question of whether there are any relationships or lack thereof between gut microbiota and BP in the diurnal cycle. The basis for our question stemmed from previous observations mentioned below: (1) Habitual intake of salt has long been recognized as a major risk for elevated BP.85 (2) Hashimoto et al58 reported that a high-salt diet alters its circadian BP rhythm, exemplified by a greater BP dip of circadian rhythm for mean arterial BP. (3) Our group demonstrated that a high-salt diet significantly induces alterations in the gut microbial composition and serum metabolites of hypertensive S rats.51 Therefore, we speculated that the relationship between gut microbial compositions and BP in the diurnal cycle exists and that such a relationship could be further modulated in the salt-sensitive hypertensive state. In this study, we used the S rats on low- and high-salt diets to monitor the changes in host and gut microbiota in response to 3 factors, diurnal rhythm of BP, dietary salt intake, and BP dip. It is important to note that our study was not designed to and, therefore, does not particularly address the cause-or-effect relationship between bacterial groups and their respective responsive factors. Instead, it is the first report of a firm association between the two. Our data provide the first evidence for such a diurnal pattern to exist as inferred by the prominent time of day alteration in the compositions of the two major phyla of gut microbiota, Firmicutes and Bacteroidetes. The F/B ratio was also markedly lower in the dark (active) phase when the BP was highest during the 24-hour cycles. In an unbiased clustering heatmap analysis, distinct patterns of specific bacterial taxa were observed to be synchronous with diurnal rhythm, salt and BP dip in S rats.

Salt is already reported in the literature to influence microbial communities,22–24,52,87–92 but what is novel in our study is that it further illustrates that salt imparts a time-of-day rearrangement of certain specific gut microbial communities occurring in response to salt, which is different between the dark and light cycles. For example, prior research identified g_Lactobacillus as a key salt-responsive taxon regulating BP.24,52,88 Furthermore, in our study, g_Lactobacillus was associated with salt-sensitive hypertension more prominently in the light phase. In contrast to g_Lactobacillus which was only associated in the light phase, lower abundance of Anaerostipes was correlated with systolic BP in both the dark as well as in the light phases. Bier et al23 previously reported g_Anaerostipes as a taxon with lowered abundance in response to a high-salt diet. Our study, therefore, corroborates this observation and extends it to indicate that an inverse correlation of g_Anaerostipes with systolic BP occurs independent of diurnal timing.

g_Sutterella, a BP dip-responsive taxon, belongs to the class β-proteobacteria. While nothing specific was previously known about the rhythmicity of g_Sutterella, this taxon is known to be associated with pathologies of the gut and brain.93 Thus, it is possible that g_Sutterella adversely impact the gut-brain axis in a salt- and rhythm-responsive manner.

To further understand why microbiota are expanding and contracting in certain populations, we reasoned that these are probably adaptive mechanisms for coping with the availability of food, which is different between the dark and light cycles. If so, the functional pathways of the microbiota would reveal the pathways by which they adapt. Interestingly, in the diurnal timing-responsive bacteria, biosynthetic and signaling processes were mainly upregulated during the active phase of the host, while degradation and metabolic pathways were predominant during the resting phase of the host.

These data are well aligned with the food consumption pattern of the host, wherein during the dark phase when the host consumes food, microbiota are demonstrating biosynthetic pathways. Similarly, during the light phase when the host is resting, microbiota follow degradation and metabolic pathways. The synchronous overlap of these observations with BP is an interesting association. However, due to the fact that feeding patterns overlap with BP, it is admittedly difficult to uncouple the reshaping of microbiota with metabolism of the host from BP of the host. What is clear, however, is that the synchronized nature of the holobiont with its host hemodynamic process occurs in concert with diurnal reshaping of microbial physiology.

Such a correlation between microbiota and BP was not observed with microbiota and activity (Figure S4). While this enhances the specificity of the correlation of microbiota to the time of day BP readings, it does not entirely dismiss the possibility that BP rhythms secondary to a number of other biological rhythms independent of microbial influences could be operating in our studies. Further experiments are warranted to rule out such possibilities.

Microbial compositions are known to affect host energy metabolism. However, whether microbial energy metabolism is also impacted by microbial composition is not clear. Our observation that BP rhythm-responsive microbiota shift from oxidative phosphorylation in the dark (active) phase to gluconeogenesis and pentose phosphate pathway in the light (rest) phase suggests that microbial communities also display diurnal rhythmicity of energy metabolism, presumably in response to availability of food. How this affects BP requires further work. However, the observation that host circulating levels of the biofuel β-hydroxybutyrate were not affected by rhythm suggests that the rhythmicity of energy metabolism of the microbiota, rather than that of the host is linked to BP.

There were some notable diurnal variations of microbial metabolomic pathways, which point to functions in addition to energy metabolism. For example, we observed a significant difference in aromatic amino acid metabolism of the microbiota between the dark and light cycles. While biosynthesis of aromatic amino acids is upregulated in the dark phase when BP is higher, degradation of aromatic amino acids is enhanced in the light phase when BP is lower. This observation is in line with recent evidence from 3 independent human studies suggesting that aromatic amino acids increase the risk for hypertension.94–96

Besides diurnal timing-responsive pathways, our study has also uncovered salt-responsive functional pathways of microbiota. These include the NOD, Ppar, and p53 pathways, all of which are reported to be upregulated with salt and associated with high BP.51,67,97–107 Also, functional pathways encompassing taurine and hypotaurine metabolism were downregulated with salt, whereby, it is possible that the metabolism of these bile acid substrates by microbiota lower BP. In support, taurine supplementation was cardioprotective and renoprotective in the high-salt fed stroke-prone spontaneously hypertensive rat.108 Similarly, several other animal and human studies report similar beneficial effects of dietary taurine on salt-sensitive BP.109 A more recent double-blinded human study also suggests that taurine supplementation significantly decreased the 24-hour ambulatory BP, especially in those with high-normal BP.110

Collectively, our data demonstrate that microbial communities are rapidly scaled up or down synchronously with time-of-day variation in BP. While the purpose for this reshaping could be driven by the natural selection of the fittest group of bacteria depending on their ability to survive under the conditions of differential availability of food during the dark and light cycles, we also provide evidence to support the idea that such a reshaping of microbiota causes alterations in functional pathways of the microbiota, which in turn may impact BP of the host.

If such synchronous features are occurring daily within the holobiont, we questioned whether host responses such as renal damage markers would also demonstrate a synchronous daily diurnal rhythm. In support, our data collected with lipocalin 2 and kidney injury marker 1 suggests that renal damage markers is also synchronous with the time of day oscillations of microbial compositions and BP, whereas MCP-1, IL-18, and TNFα were regulated in a salt-dependent manner.

One significant limitation of our study is that we have only sampled at 2 timepoints, which fails to capture the rhythmicity of bacteria during the entire day. Also, our study has admittedly not addressed sex effects because we wanted to avoid the reported inconsistencies between strains of rats in females.111,112

Perspectives

Overall, our study is the first to demonstrate a correlative link between biorhythmicity of BP, renal damage, and microbial communities. We propose that these potential links are synchronized via the observed alterations in various metagenomic pathways impacting the entire holobiont. We acknowledge though that our study does not test cause-or-effect relationships. Even so, given the large, independent, and interdependent effects of rhythm, salt and BP dip documented, our study provides the necessary basis for consideration of timing of imparting medication and or microbial-targeted strategies to optimize outcomes of hypertension management.

Acknowledgments

We acknowledge Roy Schneider, Manager, Medical Illustration, University of Toledo College of Medicine and Life Sciences for technical support for the creation of the graphical abstract.

Footnotes

*These authors contributed equally to this work.

The Data Supplement is available with this article at https://www.ahajournals.org/doi/suppl/10.1161/HYPERTENSIONAHA.120.14830.

Correspondence to Bina Joe, Department of Physiology and Pharmacology Center for Hypertension and Personalized Medicine, University of Toledo College of Medicine and Life Sciences, 3000 Arlington Ave, Toledo, OH 43614. Email

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Novelty and Significance

What Is New?

  • Diurnal rhythmic pattern of blood pressure is known to correlate with host factors. Here we report for the first time that it is additionally correlated with gut microbial compositions.

  • Specific communities of bacteria were identified to correlate either independently or interactively with dietary salt, time of day or dip in blood pressure.

What Is Relevant?

  • By examining the resting and active phases, we report a significant correlation between gut microbial composition and diurnal variation of blood pressure.

  • Our observations suggest that time-of-day reshaping of gut microbiota could be targeted as a new factor for clinical management of hypertension and renal disease.

Summary

Diurnal timing dependent modulation in gut microbiota was associated with systolic blood pressure and renal damage markers.

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