Potential role for age as a modulator of oral nitrate reductase activity
Reduction of salivary nitrate to nitrite by oral nitrate reductase (NR) expressing bacteria has emerged as an integral pathway in regulating nitric oxide (NO) homeostasis and signaling. The oral microbiome is critical for this pathway. Variations in this pathway may underlie variable responses in the magnitude by which dietary or therapeutic nitrate modulates NO-signaling. The relationships between oral microbes and NR activity, and the factors that affect this relationship remain unclear however. Using a cross-sectional study design, the objective of this study was to determine the relationships between oral microbes and oral NR activity using a protocol that directly measures initial NR activity. Tongue swabs were collected from 28 subjects ranging in age from 21-73y. Initial NR activity showed a bell-shaped dependence with age, with activity peaking at ~40-50y and being lower but similar between younger (20-30y) and older (51-73) individuals. Microbiome relative abundance and diversity analyses, using 16s sequencing, demonstrated differences across age and identified both NR expressing and non-expressing bacteria in modulating initial NR activity. Finally, initial NR activity was measured in 3mo and 13mo old C57BL/6J mice. No differences in bacterial number were observed. However initial NR activity was significantly (80%) lower in 13mo old mice. Collectively, these data suggest that age is a variable in NR activity and may modulate responsiveness to dietary nitrate.
Introduction<!>Subject recruitment:<!>NR activity:<!>Bacterial counts:<!>Bacterial DNA extraction and amplification:<!>Next Generation Sequencing and bioinformatics analysis:<!>Mice:<!>Nitrite and Nitrate Measurement:<!>Statistics:<!>Oral NR activity increase up to mid age and then fall during old age.<!>Analyses of oral microbial communities.<!>Relationship between oral microbial communities and NR activity.<!>Oral NR activity is age-dependent in mice:<!>Discussion<!>
<p>Nitric oxide (NO) is a biological mediator with a broad range of functions in health and disease. Production of NO is controlled by three nitric oxide synthases (NOS) and also by non NOS-dependent sources that involve nitrate reduction to nitrite in the oral cavity, and then further reduction of nitrite to NO in the circulation and systemic tissues [1; 2]. In this model, endogenous or dietary derived nitrate is concentrated in the saliva where nitrate-reductase (NR) expressing bacteria, residing on the distal tongue, reduce nitrate to nitrite [1; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15]. Saliva nitrite is swallowed, where it elicits NO-signaling in the acidic stomach, but also in all other major organs and tissues by various pH and hypoxia dependent mechanisms [4; 5; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27]. The importance of this enterosalivary nitrate to nitrite pathway is indicated by nitrate ingestion leading to a lowering of blood pressure, improvement of bioenergetics, vascular and cognitive function, exercise performance and inhibition of platelet aggregation and inflammation, and reversal of these responses if oral bacteria are depleted by antibacterial mouthwash [3; 5; 12; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39]. Furthermore, retrospective analyses show frequency of mouthwash use may be linked to an increased risk for metabolic disease and hypertension [40; 41].</p><p>Systematic varying of substrate nitrate via the diet, coupled with measurement of NO-responsive end-points (e.g. blood pressure lowering) and time dependent changes in plasma / salivary nitrite and nitrate are the predominant experimental approaches used to delineate the functionality of the enterosalivary nitrate to nitrite pathway. Notable is the variance in the magnitude of effects, with some studies not observing any appreciable effect of nitrate at all. For example, a single dose of nitrate containing beet juice failed to decrease blood pressure in diabetics [42] and a systematic review of twelve studies designed to test the effects of dietary nitrate in older individuals showed that nitrate improved exercise-related end points in ~80% of studies, but lowered blood pressure in only ~50% of studies. Moreover, the magnitude of increases in plasma nitrite after dietary nitrate varied 3-fold (168 – 503%) [43].</p><p>The oral microbiome regulating nitrate-reduction is likely to be one variable that affects the magnitude of functional outcomes discussed above. However, few studies have directly assessed how varied is oral NR activity and related this to microbial composition and diversity. This is an important consideration as oral dysbiosis in different physiologic or pathologic conditions may limit the therapeutic efficacy of dietary nitrate, and in turn probiotic strategies that improve oral nitrate-reduction may be a therapeutic consideration to improve NO-homeostasis [2; 6]. Using a cross-sectional study design, the objective of this study was to determine the relationships between oral microbes and oral NR activity using a protocol that directly measures initial NR activity.</p><!><p>Subjects were recruited from University of Alabama at Birmingham (UAB) according to UAB Institutional Review Board approved protocols and after receiving consent and demographic information collected. Subjects that are current smokers, used antibiotics or mouthwash over the previous week, or were hospitalized in the last 6 months were excluded.</p><!><p>Tongue scrapes were collected as described [44]. Briefly, scrapings from the posterior tongue were collected using the narrow end of a sterile disposable lab spatula. Five gentle scrapes were performed in one direction left to right, followed by a further 5 scrapes in the other direction. Scrape volumes of approximately 30μl were collected. 70μl of normal saline was used to rinse the spatula and total volume (100μl) collected into Eppendorf tubes. 500 μl BHI broth was then added, final volume was 600μl. Two aliquots each of 100μl were incubated at 37°C for 10min. Water (vehicle control) was then added to one aliquot, and sodium nitrate (1mM) added to the other, and both incubated at 37°C. At indicated times, samples were vortex mixed (~5sec) to ensure homogenous sampling and 10μl collected, frozen in liquid nitrogen and stored at −80°C. Samples were thawed on ice and in the dark and nitrite measured by triiodide based reduction coupled with ozone chemiluminescence as previously described using a Sievers 280i Nitric Oxide analyzer (GE analytical instruments, Boulder, CO) [45]. Nitrite levels were determined by comparison with standard curves measured daily. Initial NR activity was measured by calculating the initial rates of nitrite formation as described previously [44].</p><!><p>Bacterial colony forming unit (CFU) were determined using TSBA agar by the drop plate method as described previously [44]. For each sample, 10 μl BHI containing tongues scrapes were serially diluted in sterile normal saline until 10−6 dilutions then plated on TSBA agar medium. A minimum of 3 drops (10μl each) of each dilution were plated and incubated overnight at 37°C under aerobic conditions. CFU were then counted and averaged for the 3 drops, for each dilution.</p><!><p>Fecal DNA Isolation Kit (Zymo Research, D6010) was used to prepare DNA from tongue scrapes. Extracted DNA was used as a template for PCR (LongAmp Taq PCR kit (NEB, cat. no. E5200S) using unique barcoded primers to V4 region of the 16S rRNA gene to generate an amplicon library for individual samples. The PCR products from the individual samples were then electrophoresed on an agarose gel, excised from the gel and purified using a Qiagen QIAquick Gel Extraction Kit[46].</p><!><p>Sample preparation for loading onto the Illumina MiSeq and data analysis was performed as described [46]. 16S sequence processing and analysis was performed using QWRAP (QIIME wrapper) package generated by UAB microbiome core[46]. QWRAP acts as a QIIME software wrapper, guiding the user through use of publically available tools such as FASTQC and FASTX for quality checking and quality-filtering, followed by QIIME tools to perform microbiome analysis. The data analysis workflow was A. Chimera Filtering using program "Usearch". B. Operational taxonomic unit (OUT) Clustering at 97% sequence similarity using program "uclust". C. Picking representative of OTUs based on abundance. D. Assigning taxonomy to OTUs using RDP classifier (threshold 0.8) using Greengenes database. E. Sorting OTU table based on file "sample_order.txt". F. Summarizing OTUs into taxonomic groups. G. Creating Normalized OTU table i.e. converting raw numbers from OTU table into proportion and also merging the taxa information in a single file. H. A filtered list of top 10, top 25 and top 100 OTUs and taxa are generated. To assess relationships between NR activity and bacterial abundance, we also performed text mining analysis for the presence or absence of 'NR' or 'nitrite reductase' genes using the bacterial ensemble database (https://bacteria.ensembl.org/index.html).</p><!><p>Male C57BL/6J mice (2 months or 12 month of age) were purchased from Jackson Labs (Bar Harbor, ME, USA) and NR activity, and bacterial number (colony forming units) determined as described [44]. Briefly, distal tongue swabs were collected and cultured in BHI broth at 21% oxygen, for 18h, 37°C. Nitrate reductase activity was assessed by measuring kinetics of nitrite formation after addition of nitrate (1mM) and secondly, by measurement of plasma nitrite after administration of nitrate. For the latter, mice were administered nitrate (1g/L) via the drinking water for 3 weeks. Water was replaced every 3 days. Mice were sacrificed at 3 and 13 months of age by intraperitoneal injection of xylazine and ketamine (2.5 and 17.5 mg/kg body weight respectively) followed by cervical dislocation. Blood was collected using citrate (anticoagulant), RBCs pelleted (2000 x g, 2min, 4°C). Plasma was collected and snap frozen in liquid nitrogen and stored at −80°C for later determination of nitrite and nitrate concentration. All experiments were performed using UAB IACUC approved protocol #20939.</p><!><p>After thawing plasma on ice, nitrite and nitrate were extracted using 1 part plasma and 2 parts methanol. Nitrate and nitrite concentrations were measured using HPLC-coupled to the Griess reaction using ENO-30 apparatus (Eicom, Japan) and by comparison to standard curve generated daily using sodium nitrate and sodium nitrite.</p><!><p>Data were first analyzed for normality using D'Agostino and Pearson Normality test to determine subsequent tests using parametric or non-parametric methods. Data were analyzed by 1-way ANOVA with post-test to determine significance between individual groups. Correlations were performed using Spearman analyses. The significance was set at p<0.05. All analyses were performed using Graph Pad Prism software (V7.04), San Diego, CA.</p><!><p>We enrolled a total of 34 participants with ages ranging from 21-73y; 6 samples were excluded due to problems in sample processing, including viscous saliva that precluded assessment of NR activity. Of the 28 participants included in the analyses, 19 were male and 9 female, with distribution by race being white (21), black (1), Asian (4) and Hispanic (2). Posterior tongue swabs were collected and initial rates for NR activity, and bacterial burden (measured by colony forming unit assays) determined as outlined in methods. Initial analyses showed no correlation between the top 50 most abundant bacterial species and initial NR activity across all subjects (not shown); however when initial nitrate-reduction rates were plotted versus subject age a Gaussian non-linear (R2 = 0.29) relationship was observed (Fig 1A). For comparison, linear regression analysis showed no relationship (R2 = 0.005, not shown). A significant positive and linear correlation between NR activity and CFU was observed (Fig 1B) supporting bacterial abundance being a determinant of NR activity. To further evaluate relationships between bacteria, NR-activity and age, we divided the subjects in three age categories, 20-30y, 31-50y, and 51-73y. Fig 1C shows that NR activity was significantly lower in the 20-30y and 51-73y groups compared to 31-50y group.</p><!><p>We next performed 16s ribosomal RNA gene sequencing of the V4 region[46]. Fig 2A shows the principal component analysis of both unweighted Unifrac and Bray Curtis indices, and demonstrate that the beta diversity was significantly different between three age groups. Alpha diversity (PD Whole tree) significantly (p < 0.05) correlated inversely with age (Fig 2B). Shannon, Simpson and Chao values did not correlate with age (data not shown). Eleven phylum were detected among the three age groups with five, Actinobacteria, Bacteriodetes, Firmicutes, Fusobacteria and Proteobacteria comprising >99% of these (Fig 2C). The relative abundance of Proteobacteria trended to be lower in 51-73y age group compared to 20-30y group (~2-fold, p = 0.06) and 31-50y group (~ 2.6 fold, p= 0.12). Spirochetes also trended to be lower (~4 fold) in 51-73 age group compared to 31-50y group (p=0.09). TM7 had a significant reduction (~2.5 fold) in 31-50y group compared to 20-30y group (p< 0.05). Forty-one of the top 50 OTU's based on relative abundance were detectable to the genus level. The different OTUs that resolved to unique genus/species were labeled in numerical order (such as Prevotella sp. 1, Prevotella sp. 2 etc). Fig 2D shows bacterial diversity based on abundance within each age group.</p><!><p>To gain insights into how bacterial abundance relates to NR activity, a spearman correlation analysis was performed for all data regardless of the age group. No significant correlation was found between initial NR activity and relative abundance of any bacteria (Supplementary Fig 1). However, correlation analyses within each age category revealed significant positive and negative associations. Fig 3 presents these including correlations which were close to significance (p < 0.1). In the 20-30y age group (Fig 3A), abundance of Actinomyces sp. and the undefined species Unknown 2 of the family Veillonellacea positively associated with rate of nitrate reduction. In the 31-50y age group (Fig 3B), initial NR activity positively correlated with Oribacterium sp and inversely correlated with Veillonella sp. (2), Tannerella sp, with trends noted for Prevotella sp. (2). In the 51-73y age group (Fig 3C), initial NR activity was inversely correlated with Veillonella dispar with trends noted for Streptococcus sp. (1) and Tannerella sp, the latter being a positive association. To gain insights into potential mechanisms by which these bacteria modulate NR activity, we performed text mining analysis for the presence or absence of 'NR' or 'nitrite reductase' genes using the bacterial ensemble database for every genus / species revealed in microbiome analyses. Table 1 lists whether bacteria shown in Fig 3 contain nitrate or nitrite reductase genes.</p><p>Notably, Table 1 shows that of the three bacteria that positively correlated with NR activity, only Actinomyces contains the NR gene. The other two species Oribacterium and Tannerella do not, but may express nitrite reductase genes. Further, bacteria that negatively correlate with NR activity all may express both nitrate and nitrite-reductase genes. Finally, to better understand how NR activity associated bacteria may influence each other's abundance, correlation analyses between relative abundance of each bacterium shown in Fig 3 was performed; Fig 4 shows relationships where correlations were significant. Only Actinomyces and unknown (2) were not associated with any other bacterium.</p><!><p>Oral NR activity was measured in 3 mo or 13 mo male C57BL/6J mice. Due to the low yield of bacteria present on mouse tongue swabs, bacteria were first cultured (and amplified) for 18h prior to assessing rate of nitrate reduction[44]. Fig 5A shows NR activity was ~80% lower in older mice, however no differences in bacterial numbers were observed (Fig 5B). Furthermore, plasma nitrite levels were 4-5-fold higher in younger versus older mice after dietary nitrate exposure (Fig 5C).</p><!><p>How nitrate is metabolized in the oral cavity has emerged as an important question for understanding physiologic mechanisms regulating systemic NO-signaling, as well as development of therapeutics to increase NO-bioavailability. The presence of NR expressing bacteria on the tongue is key. Recent studies show that this microbiome is dynamic and modifiable by mouthwash, tongue scraping and diet [12; 47; 48; 49]. Several studies have identified bacteria that regulate NR activity, information that could lead to probiotic-based approaches to increase nitrate-dependent NO-generation. Other parameters to consider include the potentially competing reaction of nitrite reduction to NO or ammonia in the oral cavity, and presence of non-NR expressing bacteria that regulate growth and survival of NR expressing bacteria [47; 48; 50; 51]. Using 16s RNA sequencing, several studies have identified bacteria that positively or negatively associate with dietary nitrate-dependent increases in salivary or plasma nitrite, or biological activity end points (e.g. changes in blood pressure, coagulation or bioenergetics) [12; 47; 48; 49; 50; 51; 52; 53]. While clearly important to assess clinical or therapeutic impact, these end points are not only dependent on nitrate-reduction but also on the balance with nitrite reduction and multiple subsequent steps that control nitrite-dependent mediation of NO-signaling.</p><p>With an objective to delineate relationships between the oral microbiome and NR activity we opted to use tongue scrapes and assess NR activity directly ex vivo. This assay is responsive to interventions that decrease bacterial number [44; 54] although one potential limitation is inability to sample bacteria residing in deeper areas of the tongue crypts. Notwithstanding, using this approach we did not observe any correlations between the top 50 most abundant bacterial species and initial NR activity across all subjects. However, when separated by age, significant positive or negative associations were observed (Table 1). Of these bacteria, Actinomyces sp, Prevotella sp., Veillonella dispar., Veillonella sp. and Streptococcus sp. have been shown previously to positively associate with NR activity [8; 10; 12; 48; 49; 53]. In our data, only Actinomyces sp showed positive association with initial NR activity with the other bacteria displaying inverse associations. Notably, recent studies have shown negative associations between plasma nitrite / nitrate and Veillonella and Prevotella also [49]. Thus, not all NR expressing bacteria may positively modulate nitrate-dependent stimulation of NO-signaling. Moreover, all the aforementioned bacteria also express nitrite reductase based on text mining of Ensemble data base. Whether NR and nitrite reductase activities are balanced, whether one dominates over the other remains unclear. As discussed by others, this an area that needs to be investigated further in the context of variance in individual responses to dietary nitrate.</p><p>We also identified Oribacterium and Tannarella as possible modulators of NR activity, but neither were found to express NR genes by text mining of the Ensemble database. Tannarella does express nitrite reductase genes that may account for negative association with NR activity. In contrast, its abundance was positively correlated with Prevotella and Veillonella abundance, both known to possess NR activity. Interestingly, Oribacteria expresses neither NR nor nitrite reductase genes. However, its abundance positively correlated with NR activity suggesting this bacterium may regulate the abundance of and/or activity of NR in other bacteria. A limitation of the text mining approach is its reliance on a database that contains information only for genes that have been sequenced to date. Absence of a gene does not preclude its absence in the respective bacterial genome therefore. Indeed, we note that Tannerella may express NR genes; for example Tannerella oral taxon 286 (BU063) has been reported to express reductase genes that may be involved in metabolism of nitrate as a respiratory substrate [55]. Nevertheless, our data add to the growing list of studies that underscore the need to better understand bacterial diversity and interplay between different bacteria in the oral cavity, and in turn how these are integrated to modulate nitrate dependent stimulation of NO-signaling. We also noticed that the changes in NR were proportional to the number of bacteria across all ages. While the majority of studies to date have focused on microbiota and microbiome diversity, whether the number of bacteria differ between individuals, independent of mouthwash use, warrants further assessment also.</p><p>Oral nitrate reductase activity is extremely low at birth rising over the first year of life [54; 56], but if and how activity changes further with age remains less clear. Nitrate supplementation significantly increases salivary / plasma nitrite and stimulates NO-responsive physiologic end points in older individuals, and in some cases effects being of a greater magnitude compared to younger adults [43; 49; 57; 58]. Our results are consistent in that NR activity was similar between younger and older adults. However, a bell-shaped dependence of NR activity with age was observed with activity peaking at ~40-50y. While our study was not designed to test age-associations across pre-defined age groups, presented data do raise an intriguing hypothesis that middle aged adults may be more responsive to nitrate therapy compared to younger or older individuals, a hypothesis that requires testing via prospective studies.</p><p>Further supporting age as a modifier of oral NR activity, we found this activity was dramatically lower in older mice. Many variables (e.g. housing, chow) affect microbiome diversity and function in mice, with most of this data derived from studies on the gut microbiome. Relatively little is known regarding mechanisms regulating the oral microbiome. While all mice were housed under identical conditions, we recognize not all variables were likely accounted for, and further studies to confirm our results are needed. Interestingly, age associated loss of NO-bioavailability, secondary to diminished endothelial nitric oxide synthase activity is an established concept in mechanisms thought to underlie vascular dysfunction in older individuals [59]. Our data suggest oral NR-derived NO may also be lower representing a novel therapeutic target to improve NO-bioavailability. Further studies are needed to determine mechanisms underpinning these associations. Finally, we acknowledge the limitation that our study did not relate changes in NR activity with changes in NR activity in vivo nor nitrate dependent stimulation of NO-responsive functional end points. To what extent increases or decreases in NR activity measured ex vivo, as we have conducted in this study, leads to changes in nitrate-dependent functional effects is not known. To date, most studies have evaluated effects of interventions (oral mouthwash or antiseptics) that are likely to dramatically alter the number of bacteria. Whether smaller changes in bacterial number and/or diversity lead to changes in nitrate-dependent NO-signaling is a question that requires additional investigation. We speculate that age is as a modulator of oral NR activity and underscore the need for larger prospective studies that assess NR activity and nitrate-dependent changes in NO bioavailability across (young, middle and older) age spectrum.</p><!><p>Supplementary Figure 1: Heat map showing Spearman Correlation coefficients between bacterial abundance and nitrate reductase activity in different age groups. Top row; Correlation within all subjects (regardless of age grouping). 2nd row; Correlation within 20-30 yrs age group, 3rd row; Correlation within 31-50 y age group, Bottom row; Correlation within 51-73 yrs age group.</p>