The redox cofactor nicotinamide adenine dinucleotide (NAD) plays a central role in metabolism and is a substrate for signaling enzymes including poly-ADP-ribose-polymerases (PARPs) and sirtuins. NAD concentration falls during aging, which has triggered intense interest in strategies to boost NAD levels. A limitation in understanding NAD metabolism has been reliance on concentration measurements. Here, we present isotope-tracer methods for NAD flux quantitation. In cell lines, NAD was made from nicotinamide and consumed largely by PARPs and sirtuins. In vivo, NAD was made from tryptophan selectively in the liver, which then excreted nicotinamide. NAD fluxes varied widely across tissues, with high flux in the small intestine and spleen and low flux in the skeletal muscle. Intravenous administration of nicotinamide riboside or mononucleotide delivered intact molecules to multiple tissues, but the same agents given orally were metabolized to nicotinamide in the liver. Thus, flux analysis can reveal tissue-specific NAD metabolism.

Here, we establish methods for measurement of NAD synthesis and breakdown fluxes in cell lines and mouse tissues using stable isotope tracers combined with mathematical modeling. We find that NAM is the main NAD source in both cell lines and most murine tissues. Liver actively makes NAD de novo from tryptophan, releasing NAM into the blood, which supports NAD biosynthesis in the rest of the body. Mouse tissues vary markedly in NAD fluxes and turnover rates, with the liver, lung, spleen, and small intestine having a faster turnover half-time than any of the tested cultured cell lines, and the skeletal muscle slower. Unlike in cell culture, where NR and NMN are readily incorporated into NAD (), oral administration fails to deliver NR or NMN to tissues without breaking the nicotinamide-ribose bond. Assimilation after intravenous (i.v.) administration varies between tissues, with NR being used preferentially over NMN in the muscle. Future pharmacological and nutraceutical efforts to boost NAD will need to take into account the minimal oral bioavailability of NR and NMN and the tissue-specific features of NAD metabolism.

To date, analysis of NAD metabolism and related drug perturbations has largely relied on measurement of the concentration of NAD, and occasionally of related metabolites, and on how these levels change in response to drug perturbation, disease, and aging. In addition, enzyme activities in lysates have been measured (). Estimating NAD synthesis and breakdown rates based on concentrations or biochemical assays is insufficient: an increased concentration may reflect increased production or decreased consumption, while enzyme activities in lysates may not reflect cellular regulatory mechanisms. Accordingly, there is an unmet need to measure NAD production and consumption rates in cells and tissues (fluxes). Flux measurement holds the potential to illuminate the main pathways responsible for NAD production and consumption, and how they differ across cell types, tissues, and disease states. AlthoughC tracing to estimate NAD turnover was reported more than 40 years ago (), mass spectrometry now allows similar experiments to be conducted using stable isotopes, with quantitative measurement of both unlabeled and labeled forms of different NAD-related metabolites ().

Consistent with the medical importance of NAD metabolism, there has been great interest in its pharmacological modulation. Small-molecule PARP inhibitors promote cell death in certain cancers by blocking DNA damage repair (), but also spare NAD, which can be beneficial in other settings (). Hyperactivation of PARPs promotes cell death through multiple mechanisms, including NAD depletion and signaling through PAR-dependent pathways (). Inhibitors of the enzyme NAMPT, which is required for NAD biosynthesis from NAM, are in clinical trials for cancer treatment, based on their potential to deplete NAD and thereby block cancer growth (). Certain cancers cannot make NAD from NA, which led to the concept of rescuing normal cells, but not vulnerable cancer cells, from NAMPT inhibition using NA (). NAMPT activators are under investigation for treating neurodegeneration by raising NAD (). Activators of NAD-consuming SIRTs, whose activities are suspected to deleteriously drop when NAD levels are low in aging and degenerative disease, have also been proposed as therapeutics (). CD38 deletion is effective in reducing diet-induced obesity and metabolic syndrome in mouse models, and is thought to act in part by increasing tissue NAD levels (). Finally, there is extensive interest in NR and NMN, which can be converted into NAD without passing through the gating enzyme for NAM assimilation, NAMPT, as nutraceuticals to boost NAD levels and prevent the effects of aging ().

Measuring NAD metabolism is of great interest due to NAD's fundamental biological importance, and ties to human disease and normal aging. NAD is gradually depleted during aging in multiple tissues and has been proposed as a master regulator of age-dependent pathology (). Its depletion induces mitochondrial dysfunction and nuclear DNA damage by mechanisms that are currently under intense investigation (). Acute NAD depletion has been proposed to promote neurodegeneration, to drive cardiomyocyte damage during heart attacks, and to potentiate the killing of cancer cells by chemotherapy ().

The redox cofactor NAD (nicotinamide adenine dinucleotide) plays a central role in cellular energy generation, carrying high-energy electrons and driving oxidative phosphorylation (). NAD is regenerated from NADH by oxidation, with rapid cycling between the oxidized and reduced forms. The total pool size of NAD(H) depends on the relative rates of synthesis and degradation. In mammals, NAD is made de novo from tryptophan, via the Preiss-Handler pathway from nicotinic acid (NA), via the salvage pathway from nicotinamide (NAM, the redox-active ring alone, without ADP-ribose), or via the nicotinamide ribose kinase pathway from nicotinamide riboside (NR) (). NAD is consumed by NAD kinase, which makes the anabolic and redox defense cofactor NADP(H), as well as multiple families of signaling enzymes. Sirtuins (SIRTs) remove acyl marks (most commonly acetylation) on proteins using NAD, generating O-acyl-ADP-ribose and NAM (). ADP-ribosyl-transferases, most famously poly-ADP-ribose-polymerases (PARPs), which play an important role in DNA damage repair, use NAD to modify proteins with ADP-ribosyl groups (). Cyclic ADP-ribose hydrolases (CD38/CD157) consume NAD to make the calcium-releasing second messengers, cyclic ADP-ribose and NAADP (). Puzzlingly, the catalytic domain of CD38 faces the extracellular space under normal conditions, raising questions of how it accesses NAD (). Thus, NAD metabolism is complex, with multiple production routes and a myriad of consuming enzymes, many of which primarily function in signaling, rather than metabolism.

Nuclear ADP-ribosylation reactions in mammalian cells: where are we today and where are we going?.

In the brain, we detected only M+1 NAD, indicating a reliance on circulating NAM and suggesting that intact NR and NMN may not cross the blood-brain barrier ( Figure 7 E). This was also true after i.v. administration of a very high dose of NR or NMN (500 mg/kg; Figure S7 B). Interestingly, NR but not NMN was efficiently assimilated intact into NAD in the muscle ( Figure 7 E). This preference of muscle for NR held true also at 500 mg/kg i.v. ( Figure S7 B). To our knowledge, this is the first clear example of a differential metabolic effect between these two compounds in vivo. Tissue-specific utilization of different precursors should be considered in the design of future NAD-boosting drugs.

Examination of tissue NAD labeling indicated some direct assimilation of oral NR and NMN into liver NAD, based on M+2 labeling, which made up a minority of the signal, but was nonetheless readily detectable. The active formation of liver NAD from NR and NMN is consistent with both compounds being subject to substantial hepatic first-pass metabolism. In contrast, extrahepatic tissues displayed minimal M+2 NAD ( Figure 7 E), suggesting that orally delivered NR and NMN are converted into NAM before reaching the systemic circulation. Intravenous injection of NR or NMN, on the other hand, resulted in substantial M+2 NAD in both the liver and kidney. To explore whether higher oral doses of NR were also cleared by the liver, we examined the dynamics of tissue NAD labeling from 200 mg/kg i.v. or oral doubly labeled NR. Similar to the 50 mg/kg dose, the 200 mg/kg dose resulted in M+2 NAD in the liver but not the muscle or kidney after oral administration ( Figure S7 A). Thus, even very high doses of oral NR do not reach tissues intact.

While tryptophan, NA, and NAM are the physiological circulating NAD precursors, NR and NMN have garnered much attention as potential alternative precursors for use as nutraceuticals to elevate NAD. These precursors can be incorporated into NAD without breaking the nicotinamide-ribose linkage, allowing them to bypass the gating NAMPT reaction, which is subject to feedback inhibition by NAD (). NR and NMN boost NAD levels in vitro and in vivo, and have shown promise in a number of rodent disease models (). To probe their metabolism, we employed versions of NR and NMN that are isotopically labeled on both the nicotinamide and ribose moieties. This allowed us to distinguish NAD made directly from NR or NMN (M+2) versus NAD made from NAM-derived NR or NMN (M+1) ( Figure 7 A). While reasonably stable in tissue culture medium (t∼ 12 hr) ( Figure S4 G), both NR and NMN were quickly degraded to NAM in whole blood (t3 min) ( Figures 7 B, 7C, and S4 H). Accordingly, we flash-froze blood specimens and then later extracted them with −80°C methanol (80:20). NR and NMN were administered by i.v. bolus or oral gavage at 50 mg/kg, which is equivalent to 290 mg in a 70-kg human on a body surface area basis, in the range of common nutraceuticals. The limits of detection for measurement of NR and NMN were 0.1 and 0.2 nM, respectively. Readily detectable concentrations of intact NR were observed in the blood following i.v., but not after oral, administration, indicating nearly complete first-pass metabolism ( Figures 7 D and S7 ). NMN was barely detectable even after i.v. administration; its i.v. dosing did, however, result in a rise in circulating NR. Irrespective of the route of delivery, the main circulating product of the administered NR or NMN was NAM, which increased by ∼20× within 5 min of i.v. NR or NMN; oral NR or NMN administration led to a more modest rise in circulating NAM ( Figure 7 C).

(C) Circulating NAM from tail bleeds at the indicated times after a 50-mg/kg bolus of [ 2 H, 13 C]NR or [ 2 H, 13 C]NMN by oral gavage or by i.v. injection.

(A) Schematic of [ 2 H, 13 C]NR and [ 2 H, 13 C]NMN metabolism in vivo. NAD made directly from NR or NMN is M+2 labeled. NAD made from NAM-derived NR or NMN is M+1 labeled. Previously made NAD, or NAD made from unlabeled NAM, is unlabeled (M+0).

This quantitative analysis confirmed that the liver is the main producer of circulating NAM from tryptophan, with the kidney also net excreting NAM made from both tryptophan and NA ( Figure 6 A). Tissue fluxes are reported in units of molarity per time, i.e., are normalized to tissue volumes. Correcting for the larger volume of the liver relative to the kidney, the fraction of total NAM production by the liver is >95%. The other examined tissues differed dramatically in their rates of NAD turnover, with the small intestine and spleen having a flux more than 40-fold greater than muscle or fat ( Figures 6 A and 6B). There was a trend toward higher expression of NAD-consuming enzymes in the tissues with faster NAD turnover flux, but no strong correlation with any particular NAD-consuming enzyme ( Figure 6 B). In contrast to cell lines, where flux through NAD correlated more strongly with NAD concentration than turnover half-time, in vivo the reverse was true ( Figures 6 C and 6D). This indicates large tissue-specific differences in NAD consumption pathway activities. Notably, while standard tissue culture cell lines showed similar NAD turnover half-times irrespective of their tissue of origin, half-times varied by 50-fold across tissues in vivo, with the half-time for NAD turnover in the small intestine more than 10-fold faster than in any tested cultured cell line ( Figure 6 E). Based on the striking differences between cultured cell lines and tissues in vivo, we examined fluxes in freshly isolated primary hepatocytes. Like liver, and in contrast to HepG2 cells, the freshly isolated hepatocytes produced NAD from tryptophan and manifested a fast NAD turnover time of ∼2 hr ( Figure 6 F). Thus, mammalian NAD metabolism involves extensive tissue-specific pathway regulation, which is not replicated in standard cell lines.

To gain a more complete picture of tissue-specific NAD metabolism, we used the NAM-, tryptophan-, and NA-tracing data to quantitate NAD fluxes in each tissue (f, f, f, fin Figure 5 B; Table S5 ). The flux model assumes both spatial homogeneity (i.e., each tissue as a single well-mixed pool) and metabolic (but not isotopic) steady state. NAM is eliminated from cells by excretion of it or one of its metabolic products such as N-methylnicotinamide ( Figure S5 ). For half of the tissues, the model was able to fit the experimental data well, i.e., without significant systematic error; for the other half of the tissues, some systematic misfit was observed ( Figure S6 Table S5 ). The misfitting mainly reflected a discrepancy in NAM labeling rate over time, e.g., in the lung, NAM labeling at 1 hr was too great relative to 5 hr to be accounted for given the assumption that the tissue is a single well-mixed pool. Thus, in half of tissues, we obtained evidence for compartmentation, either between cells within the tissue or within the individual cells. Alternatively, it is possible that another unmodeled factor impacted the labeling. Despite these complications, the resulting optimized flux set ( Figure 6 A; Table S5 ) accurately accounted for labeling patterns after co-infusion of [U-C]Trp and [2,4,5,6-H]NAM (20:1 ratio, equal to their physiological ratio in serum) and co-infusion of [U-C]NA and [2,4,5,6-H]NAM (1:10 ratio, equal to their ratio in serum) ( Tables S6 and S7 ).

(A) Quantitative NAD fluxes in tissues, based on metabolic flux analysis informed by liquid chromatography-mass spectrometry measurement of metabolite labeling in serum and tissues after separate infusions of [C]Trp, [C]NA, and [H]NAM. Values shown are fluxes (μM/hr) from the best fit flux sets for network in (B). For complete flux sets, see Table S5 . Fluxes shown for tryptophan and NA reflect net assimilation into NAD. For NAM, there is significant net export from the liver and kidney. For these two tissues, we show separately the uptake and excretion fluxes of NAM, as determined by modeling of the tissue-labeling data. For all other tissues, NAM uptake and excretion are balanced, and we show only a single value corresponding to the exchange rate between the tissue and circulation.

The extent of recycling of assimilated NAM M+4 into NAM M+3 varied by organ, being greatest in the spleen and small intestine and least in the skeletal muscle, suggesting rapid NAD turnover in the spleen and small intestine and slow turnover in the muscle ( Figure 5 E). Next, we measured NAM, NAD, and NADPH tissue labeling at multiple time points (for tissue-specific NAM, NAD, and NADPH concentrations, see Table S4 ). NADP(H) labeled detectably more slowly than NAD(H), and the relative labeling ( Figure 5 F) allowed us to calculate NAD kinase forward flux and NADP(H) turnover. Particularly slow NADPH labeling was observed in the lung. As in cell culture, the NAD kinase forward flux is a modest NAD consumer, accounting for ∼25% of total net cellular NAD production (the sum of f+f+fin Figure 5 B). The skeletal muscle showed the greatest lag between NAM and NAD labeling, and the slowest NAD labeling overall, confirming slow NAD turnover, whereas the spleen and small intestine showed the fastest NAD labeling ( Figure 5 H).

We then investigated flux from circulating NAM to tissue NAD. Infusion of [2,4,5,6-H]NAM at a consistent rate of 0.2 nmol/g/min resulted in approximately 50% serum NAM labeling, with a rapid increase in NAM M+4 and slow accumulation of NAM M+3, which is formed by assimilation of NAM M+4 into NAD, loss of the redox-active hydrogen, and subsequent cleavage of NAD to NAM ( Figure 5 D). Tissue NAM was less labeled than serum NAM, with the extent of labeled NAM assimilation variable across organs ( Figure 5 E). Thus, in contrast to cell lines where NAM exchange with the medium is fast, in vivo, exchange between the blood stream and tissues is slow and thus potentially an important site of regulation.

Infusion of [U-C]Trp (M+11) at a consistent rate of 5 nmol per g mouse body weight per min rapidly resulted in approximately 60% serum tryptophan labeling, with accumulation over ∼24 hr of serum NAM M+6 (six carbon atoms from tryptophan are retained in NAD and NAM) ( Figure S5 A). Tissue sampling at 5 hr revealed preferential NAM labeling in the liver. Liver NAM was labeled in excess of circulating NAM, whereas NAM in all other tissues was labeled less than circulating NAM ( Figure 5 C). A straightforward interpretation is that, like cell lines, most tissues do not make NAD by de novo synthesis, and instead rely on NAM synthesized and released from liver. Infusion of [U-C]NA (M+6) at a consistent rate of 0.02 nmol per g per min resulted in 85% serum NA labeling. This high extent of labeling, despite the low infusion rate, indicates that endogenous NA circulatory turnover flux is small, i.e., there is little flux from circulating NA into tissues, or vice versa (). Thus, circulating NA seems to be a minor contributor to endogenous NAD production in most tissues. Consistent with this, even though the labeled NA infusion had increased the circulating NA level several-fold, the contribution of NA to serum NAM was low (1% after 5 hr, compared with 5% after 5 hr from tryptophan infusion; Figure 5 C). Quantitative analysis, which takes into account the extent of circulating precursor labeling, indicates that the flux from circulating tryptophan to serum NAM exceeds the flux from NA to NAM (even after the elevation of circulating NA by the labeled infusion) by roughly an order of magnitude.

We next employed isotope tracing to probe whole-organism NAD metabolic fluxes. In mammalian plasma, tryptophan, NAM, and NA are the only NAD precursors with concentrations >0.1 μM ( Figure 5 A). We accordingly selected [U-C]Trp, [2,4,5,6-H]NAM, and [U-C]NA for in vivo tracing studies ( Figure 5 B; for their effects in vitro, see Figures S3 and S4 ). Infusions were performed on 12- to 14-week-old C57BL/6 mice pre-catheterized on the right jugular vein, aiming to quantify in a tissue-specific manner (1) biosynthetic flux from tryptophan and NA to NAD, (2) salvage flux from tissue NAM to NAD, (3) exchange flux between tissue NAM and serum NAM, and (4) NAD kinase flux.

(H) Labeled fractions of NAM, NAD, and NADPH in tissues after 1, 2, and 5 hr of [H]NAM infusion. For (E)–(H), data are mean ± SD, n = 3. For related cell culture experiments, see also Figures S3, S4, and S5 and Tables S1 and S4

(B) Schematic of tryptophan (Trp) and NAM tracer metabolism. [ 13 C]Trp was infused via the jugular vein at 5 nmol/g/min and [ 2 H]NAM at 0.3 nmol/g/min; tryptophan to NAD flux (f 1 ), NA to NAD flux (f 2 ), NAM uptake from circulation (f 3 ), and NAMPT flux (f 4 ).

To measure NAD consumption and its dependence on NAD concentration in more cell types, we measured NAD dynamics in response to FK866 across 12 cell lines (3 other breast cancer cell lines, 4 gastrointestinal cancer cell lines, 2 melanoma cell lines, and differentiated myocytes and adipocytes). Across these cell lines, the tfor NAD depletion by FK866 was nearly identical to NAD labeling tin the absence of drug (R= 0.92, slope = 1.03, p < 0.005) ( Figure 4 D; Table S3 ). Different cell lines varied in NAD demand for growth ( Figure 3 K), NAD concentration (from 1 to 7 nmol per million cells) and labeling half-time (5–14 hr). Together, [NAD] and labeling tdetermine NAD synthesis flux (f= ln2[NAD]/labeling t). Interestingly, [NAD] was more variable than tand thus exerted greater influence over f. Indeed, we found a strong correlation between NAD concentration and synthesis flux (R= 0.81, p < 0.005), but no correlation between tand flux ( Figures 4 E and 4F). These data are consistent with high production flux leading to a large NAD pool size, with the consumption rate in cell lines proportional to [NAD]. One practical implication of this finding is that NAD flux can be estimated in tissue culture by the kinetics of NAD loss after blocking NAMPT, without the need for isotope tracer methods.

The rate of enzymatic reactions depends on substrate concentration, so we expect an effect of concentrations on fluxes. To test whether such a relationship exists for NAD consumption, we first treated cells with FK866, an NAMPT inhibitor in clinical trials (), simultaneously with switching into [H]NAM. As expected, FK866 almost completely blocked NAD labeling. We then assessed whether the resulting drop in NAD concentration altered NAD consumption kinetics. The decline in NAD concentration following addition of FK866 approximated a single-exponential decay ( Figure 4 A), which implies that NAD consumption depends linearly on its concentration: f= k [NAD]. To further test the relationship between [NAD] and f, we reduced the medium NAM to 0.1× or 0.01× of its normal concentration in DMEM (i.e., to roughly 1.5× and 0.15× normal circulating levels) or added NR at 5× the normal media NAM concentration, resulting in a 20% decrease, 70% decrease, or 60% increase in [NAD], respectively ( Figure 4 B). We then switched to isotopic NAM or NR at the same concentration and observed that fwas roughly proportional to [NAD] ( Figures 4 B and 4C). Because PARP1/2 and SIRT1/2 are major consumption enzymes, these data suggest that, at least in in T47D cells, their cellular activities are substantially determined by NAD concentration.

(D) Correlation between tfor NAD labeling by [H]NAM and tfor NAD depletion upon adding FK866 (100 nM) across 12 cell lines. Each dot represents one cell line. For data by cell line, see Table S3

(B) NAD concentration before and after labeling for 5 hr. T47D cells were pre-treated with 1× NAM (standard DMEM condition), 0.1× NAM, or 0.01× NAM, for 1 week and labeled with the same concentration of [ 2 H]NAM, or were pre-treated with 5× NR for 4 days and labeled with the same concentration of [ 2 H, 13 C]NR. Data are mean ± SD, n = 4.

(A) NAD concentration and labeling in T47D cells treated with FK866 (100 nM, NAMPT inhibitor). FK866 was added simultaneously with switching cells into [ 2 H]NAM. Symbols, experimental data (mean ± SD, n = 3); line, fit to equations corresponding to the illustrated kinetic scheme, which assumes that NAMPT fully blocks NAD synthesis and NAD consumption is proportional to its concentration (“first-order kinetics”).

NAD+ depletion by APO866 in combination with radiation in a prostate cancer model, results from an in vitro and in vivo study.

We then examined two additional cell lines, the transformed but non-tumorigenic breast cell MCF7 and differentiated C2C12 myotubes ( Figures S2 E–S2I). Comparison of NAD labeling with cellular growth rate revealed that most NAD in the MCF7 cells was passed along to their daughter cells, whereas in the differentiated C2C12 cells, essentially all NAD was consumed, as expected based on their post-mitotic status ( Figure 3 K). Similarly, among different proliferating cell lines, growth rate and NAD usage for growth were correlated (R= 0.48, p = 0.01; Figure S2 K). In both MCF7 cells and C2C12 myotubes, based on NAM-tracer experiments with olaparib and sirtinol, the relative contributions of PARP1/2 and SIRT1/2 were similar. Thus, across several cell lines, NAD consumption by PARP1/2 is similar to that by SIRT1/2 ( Figures 3 K and 3L).

To evaluate contributions from other pathways, we monitored the increase in NAD pool size and labeling pattern in T47D cells treated with sirtinol (a SIRT1/2 inhibitor) and EX527 (a SIRT1 inhibitor) ( Figures 3 H, S2 C, and S2D). We observed a significant decrease in f. Quantitatively SIRT1/2 consume about one-third of NAD under basal conditions (32 pmol per million cells per hr, CI: 24–41), similar to consumption by PARP1/2. The effect of dual PARP1/2 and SIRT1/2 inhibition was roughly additive. The flux measurements lack the precision to assess whether PARP inhibition is activating sirtuins, or vice versa, but the data do confirm that PARP1/2 and SIRT1/2 collectively account for the majority of NAD consumption ( Figures 3 I and 3J).

To investigate the effects of acute DNA damage, we treated T47D cells with zeocin to trigger DNA double-strand breaks at the same time as switching into [H]NAM and analyzed total andH-NAD after 8 hr. Zeocin reduced total NAD to ∼60% of control, mainly by accelerating the loss of unlabeled NAD, and this effect was blocked by olaparib ( Figure 3 F). Quantitative analysis revealing ∼2× increase in fthat was reversed by co-treatment with PARP inhibitor ( Figure 3 G). Thus, PARP consumes about one-third of NAD under basal conditions and becomes the dominant consumer in the presence of overt DNA damage. These observations capture the quantitative change in flux during DNA damage, although harsher damage might lead to a yet more dramatic change ().

One potential explanation is that PARP activity is determined mainly by cellular factors, such as DNA damage, which may not be reliably captured in lysates. Constitutive DNA damage due to genetic defects in DNA repair has been reported to decrease NAD pools (). We investigated cells with dysfunction in the DNA repair protein xeroderma pigmentosum group A (XPA) and a matched control line that was rescued by XPA transfection (). Compared with XPA-restored cells, XPA-deficient cells suffer from chronic DNA damage, and exhibit lower steady-state NAD concentration () (confirmed in Figure S2 A). We observed faster NAD labeling ( Figure S2 B) and an associated larger total NAD consumption flux in the XPA-deficient cells ( Figure 3 E). Moreover, the PARP contribution (as measured by adding olaparib together with labeled NAM) was larger. Thus, while we do not observe a relationship between basal lysate PARylation activities and NAD flux, we capture the known link between compromised DNA repair, PARP, and NAD consumption.

PARP is thought to be the major NAD consumer in cells with DNA damage (). In the absence of DNA damage, basal PARP activity, as measured by the accumulation of protein poly-ADP-ribosylation in cell lysates with poly(ADP-ribose) glycohydrolase inhibitor added, was recently reported to vary markedly across cancer cell lines (). We compared PARP-mediated NAD flux in five human breast cancer cell lines with basal lysate PARylation activities (). We found that the two cell lines with relatively high accumulation of PARylation in lysates (KPL1 and MCF7) did not exhibit lower NAD concentration or higher PARP-mediated NAD consumption than the three cell lines with relatively low PARylation (AU565, SKBR3, and T47D) ( Figure 3 D; Table S2 ). This suggests that cellular PARP1/2 flux is determined by factors distinct from PARP activity as captured by lysate assays.

To measure NAD consumption by PARP1/2, the major DNA damage responsive PARPs, we switched exponentially growing cells simultaneously into [H]NAM and olaparib (AZD2281), an FDA-approved PARP1/2 inhibitor drug (). Compared with untreated cells, olaparib-treated cells accumulated an indistinguishable amount of labeled NAD at early time points ( Figure 3 A, blue lines), indicating that NAD synthesis from NAM is unaltered. The decay of unlabeled NAD was, however, slower, resulting in an approximately 10% increase in NAD concentration over 15 hr. Thus, PARP inhibition increased the NAD pool by decreasing its consumption (). Based on the slower rate of unlabeled NAD decline, we determined the value of fupon inhibitor treatment ( Figures 3 B and 3C) to be 79 pmol per million cells per hr (versus 118 in the absence of PARP inhibition), with the difference being the PARP contribution of 39 pmol per million cells per hr (CI: 28–43). A caveat is that this calculation assumes constant NAD consumption by other pathways, whereas the rise in total NAD concentration after inhibitor treatment could be driving compensatory increases in other components of f. Due to the small change in NAD pool and flux determination based on data taken at early time points after PARP inhibition, the impact of such errors should be small. Thus, in T47D cells, approximately one-third of NAD consumption is due to basal PARP1/2 activity.

(L) Pie graphs indicating NAD fates in differentiated myocytes (C2C12 cells) and proliferating T47D and MCF7 cells. Consumption routes in C2C12 cells and MCF7 cells were determined as for T47D cells (see Figure S2 for data in C2C12 cells and MCF7 cells).

(K) Fraction of NAD directed toward supporting growth in different cell lines cell lines, as determined by experimental measurements of growth rate relative to NAD isotope labeling rate (mean with 95% confidence interval).

(J) Decrease in NAD consumption, calculated based on first 4 hr after drug exposure in T47D cells, for olaparib (10 μM, PARP1/2 inhibitor), sirtinol (25 μM, Sirtuin 1/2 inhibitor), EX527(10 μM, Sirtuin 1/2 inhibitor), and co-treatment of olaparib (10 μM) and sirtinol (25 μM) (mean with 95% confidence interval).

(F) NAD concentration and labeling in T47D cells incubated simultaneously with [ 2 H]NAM and zeocin (250 μg/mL, to induce DNA double-strand break), with or without olaparib, for 8 hr. Data are mean ± SD, n = 3.

(E) Total NAD consumption fluxes in XPA-deficient or XPA-restored cells treated with DMSO or olaparib, calculated from [ 2 H]NAM labeling in the first 8 hr of drug treatment. Results are normalized to untransfected XPA-deficient cells; data are mean ± SD, n = 3; ∗ p < 0.05, paired t test.

(D) PARylation activity and PARP-mediated NAD consumption as measured by isotope tracing in the presence and absence of 10 μM olaparib are not correlated across five breast cell lines. Lysate and MagPlex beads were incubated together overnight to measure PARylation activity (). Data are mean ± SD, n = 3.

(C) Fitted NAD efflux based on NAD concentration, cell growth rate, and isotope labeling in the presence or absence of 10 μM olaparib, as shown in (A). Horizontal line within box, best fit; box, interquartile range; whisker, 95% confidence intervals.

(A) NAD concentration and labeling in T47D cells treated with olaparib (10 μM, PARP1/2 inhibitor). Olaparib was added simultaneously with switching cells into [H]NAM. Symbols, experimental data (mean ± SD, n = 3); lines, fit to equations corresponding to model in (B) ( STAR Methods ).

NAD is the substrate for essential metabolic processes including NADP synthesis by NAD kinase and important protein covalent modification reactions (e.g., deacetylation and ADP-ribosylation). We sought to separately quantify the major NAD-consuming pathways ( Figure 2 A). To investigate the contribution of NAD kinase, we measured the dynamics of NADP labeling. Like NAD/NADH, NADP/NADPH are coupled by rapid oxidation-reduction and label equally ( Figure S1 D). Compared with NAD, NADP labeled detectably more slowly ( Figure 2 B). The slower labeling does not reflect a slower intrinsic turnover rate of NADP(H) relative to NAD(H), but rather the NADP being downstream of NAD, with the time lag in labeling used to calculate the NAD kinase forward flux (f) () ( STAR Methods ). Based on the labeling kinetics, the intrinsic turnover half-time of NADP is about 2-fold shorter than for NAD. However, due to the 20-fold smaller total pool size of NADP(H) relative to NAD(H) ( Figure S1 G), the NAD kinase flux is only ∼10% of total NAD consumption, 12 pmol per million cells per hr (CI: 11–14), compared with total NAD consumption of 118 pmol per million cells per hr.

[NAD] is the constant total intracellular concentration of NAD(H) (i.e., the sum of the oxidized and reduced cofactor concentrations, which is 1,880 pmol per million cells, with [NAD] > [NADH]; note that the volume of 1 million cells is about 3 μL, so this equates to about 0.6 mM NAD). Based on the experimental data for isotope incorporation ( Figures 1 B and 1C), fis 144 pmol per million cells per hr, with a 95% confidence interval (CI) of 121–169 (determined by bootstrapping). The NAD synthesis flux fmust balance with (1) all NAD consumption (i.e., due to PARPs, SIRTs, CD38, NAD kinase, and other NAD-consumers, the sum of which is f) and (2) expansion of the NAD pool due to cell growth (f). Cell growth was measured separately to determine the growth rate constant (g) with f= g [NAD]. In T47D cells, faccounts for ∼20% of f. Therefore, with the NAD concentration of about 0.6 mM, and a turnover tof 9 hr, T47D cells break down a majority of newly made NAD.

We next developed a quantitative analysis of the fluxes underlying the observed labeling dynamics. After being taken up by cells, NAM forms NAD with flux f. In the presence of labeled NAM, the unlabeled fraction of NAD (NAD) ( Figure 1 B) accordingly decreases:

In addition to NAD M+4 and M+3, we also observed a minor NAD M+2 fraction ( Figure 1 D). The M+2 species could, in theory, arise from interconversion between NAD and quinolinic acid, or spontaneous hydrogen-deuterium exchange. RNAi knockdown of quinolinate phosphoribosyl transferase did not inhibit formation of the M+2 species, suggesting it is generated by spontaneous exchange () ( Figures S1 E and S1F).

Switching to labeled NAM did not alter the NAD concentration ( Figure S1 C). Although the NAM was M+4, most labeled NAD was M+3, as expected due to rapid turnover of the redox-active hydrogen at the 4 position ( Figure 1 C). The observed rate of NAD M+3 production may be slowed by the deuterium kinetic isotope effect at the redox-active hydrogen position. Nevertheless, the oxidation-reduction cycle between NAD and NADH is sufficiently rapid so as to result in the indistinguishable labeling kinetics for NAD and NADH ( Figure S1 D). Thus, we approximate NAD(H) as a single well-mixed pool for the purposes of the NAD-tracing studies reported here. Neither the deuterium at the 4 position nor the other deuterium-labeled sites are involved in the NAD synthesis and consumption reactions that we study, and thus are not expected to impact the fluxes that we measure.

To quantify NAD metabolism in tissue culture, we substituted [2,4,5,6-H]NAM into the media of T47D breast cancer cells. DMEM with 10% dialyzed serum was prepared from scratch with solely isotopic NAM (32 μM, the standard DMEM concentration, which is 15× normal circulating levels in mice; Table S1 ) ( Figure 1 A). Feeding-labeled NAM resulted, at steady state, in nearly complete NAD labeling. Feeding [U-C]Trp did not result in detectable NAD labeling, even after 4 days in NAM-free medium ( Figures S1 A and S1B), consistent with lack of the relevant enzyme expression in T47D cells (). There is no NA or NR in standard cell culture medium. Thus, in these typical cell culture conditions, essentially all NAD is synthesized from NAM.

Discussion

NAD plays a central role in epigenetics and energy metabolism. It is accordingly important to measure NAD production and consumption pathways, and how they differ across cell types, tissues, physiological states, and diseases. In addition, it is important to understand the impact of drugs and nutraceuticals on NAD metabolism. Here we present an isotopic-tracing approach to quantify NAD synthesis and consumption fluxes: introduction of labeled NAM or other NAD precursors followed by measurement of NAD labeling. Both NAM and NAD are sufficiently abundant and stable for facile measurement of their quantitative labeling by liquid chromatography-mass spectrometry, rendering the methods well suited for broad application.

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Sassone-Corsi P. Altered behavioral and metabolic circadian rhythms in mice with disrupted NAD+ oscillation. Chiang et al., 2015 Chiang S.H.

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et al. Genetic ablation of CD38 protects against Western diet-induced exercise intolerance and metabolic inflexibility. In steadily growing cell lines, NAD labeling follows single-exponential kinetics ( Figure 1 B). The disappearance rate of unlabeled NAD in the presence of labeled NAM reflects the total activity of all consumption pathways. By tracing label incorporation into NADP(H) we showed that NAD kinase accounts for 10% of NAD consumption ( Figure 2 ). By combining this isotope tracer measurement with pharmacological modulation of PARP1/2 and SIRT1/2, we were able to assign each enzyme class a substantial (∼1/3) role in NAD consumption under basal conditions ( Figure 3 J). As expected, cells defective in DNA repair or suffering acute DNA damage had faster PARP-mediated NAD consumption, which validated our method and quantified the effect of DNA damage on flux through the PARPs. In contrast, neither PARP expression levels nor activity in lysate was predictive of the basal PARP-mediated NAD consumption flux in cell lines. We did not observe substantial NAD consumption by CD38 in cell culture (based on inhibition with quercetin and apigenin; Figure S2 H), although genetic evidence suggests that CD38 plays a substantial role in NAD consumption in vivo ().

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Wannemacher Jr., R.W. Evidence for a linear correlation between the level of dietary tryptophan and hepatic NAD concentration and for a systematic variation in tissue NAD concentration in the mouse and the rat. Typical cell culture medium contains only two potential NAD precursors, NAM and tryptophan (). In our hands, primary hepatocytes were the only cell type capable of using tryptophan for NAD synthesis, indicating that the vast majority of cells depend entirely on NAM. In animals, gene data indicate expression of the enzymes required for de novo synthesis of NAD from tryptophan in the liver and kidney ( Figure S5 D), and the concentration of tryptophan in the diet has been reported to affect the liver NAD levels (). Consistent with this, quantitative analysis of in vivo tracing data with labeled NAM and tryptophan indicated de novo NAD synthesis from tryptophan in the kidney and, to a much greater extent, the liver. Other tissues, in contrast, relied almost exclusively on circulating NAM made by the liver. Liver synthesis of NAD and excretion of NAM occurred even when serum NAM was elevated by co-infusion of tryptophan and NAM; thus, liver constitutively produces NAM to support NAD synthesis throughout the rest of the body ( Figure 6 A).

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Pascal J.M. The Zn3 domain of human poly(ADP-ribose) polymerase-1 (PARP-1) functions in both DNA-dependent poly(ADP-ribose) synthesis activity and chromatin compaction. Beneke et al., 2000 Beneke S.

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Bürkle A. Comparative characterisation of poly(ADP-ribose) polymerase-1 from two mammalian species with different life span. m values (0.01–0.6 mM). While these biochemical data suggest that PARPs and sirtuins should be substantially saturated at 0.6 mM NAD, physiological K m values are often higher than those measured in a test tube, due to active site competition from other metabolites in the cellular milieu ( Yuan et al., 2009 Yuan J.

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Ziegler M. Pathways and subcellular compartmentation of NAD biosynthesis in human cells from entry of extracellular precursors to mitochondrial NAD generation. To explore the relationship between NAD concentration and fluxes, we changed medium levels of NAM and NR, as well as added FK866, thereby manipulating the intracellular NAD concentration in cultured cells across an ∼10-fold range. NAD consumption flux correlated strongly with NAD concentration; this correlation results in NAD turnover time being relatively consistent (∼8 hr, substantially longer than the 1–2 hr half-life previously estimated for DH98/AH2 cells, which were not included in the present study;). The simplest explanation for the correlation between NAD concentration and flux is that consumption flux is a linear function of the concentration of NAD, the enzymes' substrate. According to Michaelis-Menten kinetics, such a linear relationship is expected only when substrate is subsaturating. We observed an average whole-cell concentration of NAD ranging from 0.1 to 2 mM, with the T47D cells in which we conducted the nutrient perturbation experiments having 0.6 mM. While this is similar to or below the Kof NAD kinase (0.6–1 mM) (), it exceeds the reported NAD Kof PARP1 (0.1–0.2 mM) () and most of the (quite variable) literature estimates of sirtuin Kvalues (0.01–0.6 mM). While these biochemical data suggest that PARPs and sirtuins should be substantially saturated at 0.6 mM NAD, physiological Kvalues are often higher than those measured in a test tube, due to active site competition from other metabolites in the cellular milieu (). In addition, NAD and NADH are often protein bound, and the free NAD concentrations within cytosol and/or mitochondria may be considerably less than the whole-cell averages or the Kvalues for consuming enzymes (). Thus, the simplest biochemical explanation for the correlation between NAD concentrations and fluxes is a roughly linear dependence of PARP and sirtuin activity on NAD concentration.

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et al. Genetic ablation of CD38 protects against Western diet-induced exercise intolerance and metabolic inflexibility. Camacho-Pereira et al., 2016 Camacho-Pereira J.

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Lee H.C. Determinants of the membrane orientation of a calcium signaling enzyme CD38. In contrast to the relatively consistent NAD turnover half-time in cell culture of 6–12 hr, NAD turnover rates varied dramatically across tissues ( Figure 6 E). In several tissues, NAD turnover was substantially faster than in any of the cultured cell lines that we examined. On the flip side, in the skeletal muscle, it was substantially slower. This variation in NAD turnover rate between tissues in vivo highlights the importance of understanding the mechanisms controlling NAD fluxes. Across tissues, we did not observe a strong correlation between flux and NAD concentration or the protein levels of known NAD consumers or biosynthetic enzymes ( Figures 6 B and 6C) (). This may reflect regulation of these enzymes by other means, such as partner proteins or subcellular localization, or that other major NAD consumption pathways may remain to be discovered. For example, one open question is CD38 orientation and regulation. CD38 is thought to be a major sink for NAD in tissues, especially in older mice, as inferred from the effects of genetic ablation on NAD levels (). However, in its standard ectoenzyme orientation, where the active site is not exposed to the cytoplasm, CD38 may not be active. Under some conditions, or in some tissues, it may be expressed in an inverted orientation or on an intracellular membrane, making it much more active (). This kind of topological regulation would not be captured in gene expression or lysate biochemical data. Clearly, much remains to be learned concerning NAD metabolism in tissues, distinct from tissue culture. We note, for example, that the hepatocellular carcinoma cell line HepG2 exhibits no NAD production from tryptophan and much slower NAD flux than mouse liver or isolated hepatocytes. This kind of differential would be masked if only steady-state NAD concentration were measured, emphasizing the importance of flux assays.

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et al. NRK1 controls nicotinamide mononucleotide and nicotinamide riboside metabolism in mammalian cells. Nikiforov et al., 2011 Nikiforov A.

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Ziegler M. Pathways and subcellular compartmentation of NAD biosynthesis in human cells from entry of extracellular precursors to mitochondrial NAD generation. We also explored the metabolism of two NAD precursors that have recently received attention for their ability to elevate tissue NAD levels, NR and NMN. Interestingly, we found that neither compound was able to enter the circulation intact in substantial quantities when delivered orally. While the dose that we used (50 mg/kg) was modest in order to avoid severe metabolic perturbation, our result is consistent with our previous finding that 200 mg/kg oral NR contributes directly to NAD synthesis in the liver, but not the skeletal muscle (). Similarly, in the present experiment, lack of direct tissue assimilation of orally administered NR or NMN is evident in the labeling pattern of tissue NAD. Direct assimilation of M+2 NR or NMN would yield M+2 NAD. Turnover of M+2 NAD within a tissue could in principle produce M+1 NAD after direct NR or NMN assimilation, but our independent measurements of tissue NAD turnover ( Figure 5 ) revealed that these fluxes are too slow to account for the lack of M+2 tissue NAD. Another hypothetical possibility is base exchange (). Without formally ruling out such a possibility, we observed that i.v. administration of either compound results in its detection within the circulation (albeit to a much greater extent for NR) and a robust M+2 peak in the kidney, proving that the route of delivery has a profound effect on the ability of these precursors to reach target tissues. Surprisingly, i.v. NR was much more effective than NMN for labeling the NAD pool in the skeletal muscle. This is consistent with the proposal that at least some tissues are incapable of taking up NMN directly (). On the other hand, direct transport of NMN would allow its utilization even in tissues that lack NRK or NAMPT activity. Thus, it will be extremely important to consider tissue-specific enzyme and transporter expression when using NAD precursors therapeutically.

Overall, by developing broadly applicable NAD-tracing methods, we have been able to gather a substantial body of foundational data regarding NAD metabolism and its potential modulation with nutraceuticals. In some cases, such as liver being the main site of NAD de novo synthesis, we are able to validate hypotheses based on expression data. In other cases, such as NAD consumption by PARP in culture, we find that biochemical data do not predict metabolic fluxes. Perhaps most importantly, we identify many distinguishing features of the in vivo context. These include high variability in NAD turnover across tissues and nearly complete first-pass metabolism of oral NR and NMN, which likely result in these compounds having systemic effects similar to or indistinguishable from oral NAM. We also identify tissue-specific preferences in NAD precursor uptake, with the muscle highly responsive to NR, but not NMN or NAM. Use of isotope tracing to understanding these fundamental features of in vivo NAD metabolism will open the door to more selective and effective interventions against aging and disease.