NAD⁺ depletion links metabolic stress to drive innate immune priming and selectively control PANoptosis

Abstract

The innate immune system can detect infection, tissue damage, and other homeostatic disruptions to initiate an immune response, drive inflammation, and promote programmed cell death. While these responses can be beneficial in host defense, aberrant activation of inflammatory, lytic cell death pathways can be pathogenic. Emerging evidence suggests that cellular metabolic disruption can promote inflammatory cell death, but the mechanistic connections between these processes are not well understood, limiting our ability to identify regulatory nodes that can be therapeutically targeted. Here, we found that intracellular levels of the metabolic cofactor nicotinamide adenine dinucleotide (NAD⁺) were depleted in response to cell death triggers that drive pyroptosis, necroptosis, PANoptosis, and ferroptosis. However, restoring NAD⁺ inhibited PANoptosis but not the other forms of cell death. Mechanistically, NAD⁺ restoration reduced the expression of PANoptotic sensors or regulators, including the transcription factor IRF1, a critical factor for innate immune sensor priming in PANoptosis. Our findings thereby suggest that NAD⁺ depletion is an early cell death signaling event and that restoring NAD⁺ levels specifically blocks PANoptosis by suppressing priming. Hence, targeting NAD⁺ metabolism represents a potential therapeutic strategy for infectious and inflammatory diseases associated with dysregulated PANoptosis.

Introduction

Pathogens, inflammation, and homeostatic alterations initiate innate immune responses through recognition of pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) by pattern recognition receptors. Pattern recognition receptor activation then drives inflammatory signaling, programmed cell death, and amplification of the immune response. Several programmed cell death pathways have been characterized to date, including nonlytic apoptosis and lytic pyroptosis, necroptosis, PANoptosis, and ferroptosis.^1–3 Cell death through these lytic pathways can be beneficial for host defense, but their dysregulation can lead to inflammatory disease and cancer.^1,4–6

Innate immunity, inflammatory signaling, and cell death are also associated with disruptions in metabolism,^7–15 and metabolic signals are increasingly recognized as innate immune modulators.^16–18 For example, perturbations in nicotinamide adenine dinucleotide (NAD⁺), which functions as a pivotal redox cofactor and as a substrate for metabolic enzymes,¹⁹ can accompany cellular stress that can induce reactive oxygen species²⁰ and subsequent cell death.^19,21–25 For example, the bacterial PAMP lipopolysaccharide (LPS) decreases the NAD⁺/NADH ratio and activates the NLRP3 inflammasome.¹²Mycobacterium tuberculosis infection depletes NAD⁺ and thereby promotes macrophage cell death via activation of RIPK3 and MLKL.²⁶ Additionally, depletion of intracellular NAD⁺ can initiate PANoptosis,^27–29 an innate immune, lytic cell death pathway initiated by innate immune sensors and driven by caspases and RIPKs through PANoptosomes.³⁰ Despite these observed associations among metabolism, innate immunity, and inflammatory cell death, it is unknown whether NAD⁺ metabolism is a general regulator of innate immune activation and cell death, and the molecular mechanisms connecting NAD⁺ metabolism with inflammatory cell death remain unclear.

Here, we observed NAD⁺ depletion to be a general feature of innate immune activation and cell death across several triggers. However, restoration of NAD⁺ levels prevented cell death only in PANoptosis, and not pyroptosis, necroptosis, or ferroptosis. Mechanistically, the restoration of NAD⁺ levels blocked the priming, or signal 1, needed to induce the expression of critical regulators or sensors for PANoptosis. These findings position NAD⁺ as a conserved metabolic regulator of PANoptosis across multiple innate immune sensors, linking cellular metabolism directly to inflammatory cell death and identifying the modulation of NAD⁺ as a potential therapeutic strategy to limit pathological inflammation driven by PANoptosis.

Methods

Mice

Wild-type (WT) C57BL/6, Aim2^–/–,³¹Nlrp3^–/–,³²Nlrc4^–/–,³³Mlkl^–/–,³⁴Nlrc5^–/–Nlrp12^–/–,²⁷Irf1^–/–,³⁵Zbp1^–/–,³⁶ and Casp8^–/–Ripk3^–/–37 mice used in the study have been described previously. All mice were generated on or extensively backcrossed to the C57BL/6 background. Mice were bred at the Animal Resources Center at St. Jude Children’s Research Hospital and maintained under specific pathogen–free conditions. Male and female 6- to 12-wk-old mice were used for all the in vitro experiments in this study. Mice were maintained with a 12 h light/dark cycle and were fed standard chow. Animal studies were conducted under protocols approved by the St. Jude Children’s Research Hospital Committee on the Use and Care of Animals.

Mouse bone marrow–derived macrophages

Primary mouse bone marrow–derived macrophages (BMDMs) were cultured for 6 d in Iscove’s modified Dulbecco’s medium (12440-053; Thermo Fisher Scientific) supplemented with 10% heat-inactivated fetal bovine serum (HI-FBS) (S1620; Biowest), 30% L929-conditioned medium, 1% nonessential amino acids (11140-050; Thermo Fisher Scientific), and 1% penicillin and streptomycin (15070-063; Thermo Fisher Scientific). The BMDMs were counted and seeded onto 12-well plates at a density of 1 × 10⁶ cells/well or 24-well plates at a density of 0.5 × 10⁶ cells/well and incubated overnight before use. For stimulations involving RSL3, 0.5 × 10⁶ and 0.25 × 10⁶ cells/well were seeded onto 12- and 24-well plates, respectively.

Reagents and cell stimulation

BMDMs were treated in Dulbecco’s Modified Eagle Medium (DMEM) (11995-065; Gibco) containing 10% HI-FBS and 1% penicillin and streptomycin with the following DAMPs, PAMPs, cytokines, and inhibitors alone or in combinations where indicated: 50 μM hemin (heme; H9039; Sigma-Aldrich), 25 ng/mL ultrapure LPS from Escherichia coli (0111: B4) (tlrl-3pelps; InvivoGen), 500 ng/mL Pam3CSK4 (Pam3; tlrl-pms; InvivoGen), 25 ng/mL TNF (315-01A; PeproTech), 25 μM Z-VAD(OMe)-FMK (zVAD; 14463; Cayman Chemical), 10 μM (1S,3R)-RSL3 (RSL3, 19288; Cayman Chemical), 50 ng/mL IFN-γ (315-05; PeproTech), 20 μM Ferrostatin-1 (Fer-1; 17729; Cayman Chemical), 400 nM (5Z)-7-oxozeanol (TAK1 inhibitor [TAK1i], 17459; Cayman Chemical), and 10 mM nicotinamide (NAM) (N3376; Sigma-Aldrich). Hemin (100 mM stock) was prepared by dissolving in filter-sterilized 0.1 M NaOH, as previously described.³⁸ Stocks were freshly prepared before each experiment. For LPS plus ATP stimulation, BMDMs were primed for 4 h with 25 ng/mL ultrapure LPS and then stimulated with 5 mM ATP (101275310001; Roche); LPS alone was used to examine induction of protein expression by immunoblotting analysis. For DNA transfection, each reaction consisted of 2 μg per million cells poly(dA:dT) (tlrl-patn; InvivoGen) resuspended in phosphate-buffered saline (PBS) and mixed with 0.6 μL Xfect polymer in Xfect reaction buffer (631318; Clontech Laboratories). After 10 min, DNA complexes were added to BMDMs in Opti-MEM (31985–070; Thermo Fisher Scientific).

Virus and bacteria culture

Influenza A virus (IAV) (A/Puerto Rico/8/34, H1N1 [PR8]) was prepared as previously described³⁹ and propagated from 11-d-old embryonated chicken eggs by allantoic inoculation. The IAV titer was measured by plaque assay in Madin-Darby canine kidney cells (CCL-34; ATCC). Salmonella enterica serovar Typhimurium (S. Tm) strain SL1344 was inoculated into LB media (3002–031; MP Biomedicals) and incubated overnight under aerobic conditions at 37 °C. S. Tm SL1344 was subcultured (1:10) into fresh LB media for 3 h at 37 °C to generate log phase grown bacteria. Francisella novicida strain U112 was prepared as previously described⁴⁰ and was grown in BBL Trypticase Soy Broth (211768; BD) supplemented with 0.2% L-cysteine (C7880; Sigma-Aldrich) overnight under aerobic conditions at 37 °C. F. novicida was subcultured (1:10) in fresh Trypticase Soy Broth supplemented with 0.2% L-cysteine for 3 h and resuspended in PBS.

For virus infection, BMDMs were infected with IAV (multiplicity of infection [MOI] 20) in DMEM plain media (D6171; Sigma-Aldrich). At 1 h after infection, 10% HI-FBS was added to the cells. For bacterial infection, S. Tm (MOI 0.1) and F. novicida (MOI 50) were used. Four hours after infection, F. novicida–infected cells were washed 2 times with PBS, and complete DMEM media containing 50 μg/mL gentamicin (15750-060; Thermo Fisher Scientific) was added to kill extracellular bacteria.

Real-time cell death analysis

The kinetics of cell death were monitored using the IncuCyte S3 or SX5 (Sartorius) live-cell analysis systems. BMDMs were seeded in 24-well tissue culture plates and treated with the indicated stimuli. Cell death was measured by propidium iodide (P3566; Life Technologies) incorporation following the manufacturer’s protocol. The plate was scanned for the indicated time durations, with fluorescent and phase-contrast images acquired in real time every 20 min, 1 h, or 2 h. Propidium iodide–positive dead cells were marked with a red mask and quantified using the software package supplied with the IncuCyte imager. A minimum of 4 images per well were captured for the analysis of each time point.

Intracellular NAD⁺ measurement

BMDMs were seeded a day before stimulation in 12-well plates. After stimulation, the adherent cells in the plate were washed once with 1× Dulbecco’s PBS (14190-250; Thermo Fisher Scientific), and then the cells were collected in PBS and pelleted. These cell pellets were used to measure NAD⁺ levels using EnzyChrom NAD/NADH Assay Kit (E2ND-100; BioAssay Systems) following the manufacturer’s instructions with slight modifications. Briefly, the cell pellet was resuspended in 50 μL NAD buffer, and the cells were incubated at 60 °C for 10 min. The cell extracts were then neutralized with 10 μL assay buffer and 50 μL NADH buffer. The mixture was vortexed briefly and centrifuged at 14,000 rpm for 10 min. Then, 20 μL of supernatant or standards was transferred into a clear, flat-bottom 96-well half-area microplate (CLS3695; Corning), and 40 μL of freshly prepared working reagent was added. The mixture was mixed by tapping the plate briefly. The plate was then read immediately for optical density (OD) at 565 nm at time zero (OD₀, defined as the initial OD measurement) and after 15 min incubation at RT (OD₁₅). NAD⁺ content was then calculated from ΔOD (OD₁₅-OD₀) using the standard curve. NAD⁺ content was normalized to total protein, which was quantified using the Pierce BCA Protein Assay Kit (23227; Thermo Fisher Scientific). Time points for NAD⁺ measurements were selected based on the kinetics of cell death with a given trigger, with samples collected at the initiation of cell death for each trigger. In some cases, a single set of untreated control wells was used to compare against multiple triggers stimulated at the same time in the same experiment. The data are plotted separately in the figures for optimal visualization; therefore, the same untreated control data appear between Figures 1A and 2C, and among Figure S1A, C, and G.

Figure 1.

Intracellular NAD⁺ levels are depleted following treatment with many, but not all, cell death triggers. NAD⁺ levels (left) and cell death kinetics (right) in mouse BMDMs treated with the indicated cell death triggers. Data represent mean ± SEM. Data are representative of at least 3 independent experiments. Statistical analyses were performed using unpaired t test (left) and 2-way analysis of variance (right). **P < 0.01; ****P < 0.0001. NS, not significant.

Figure 2.

NAD⁺ levels are depleted in PANoptosis. NAD⁺ levels (left) and cell death kinetics (right) in mouse bone marrow–derived macrophages (BMDMs) treated with the indicated PANoptotic triggers. Data represent mean ± SEM. Data are representative of at least 3 independent experiments. Statistical analyses were performed using unpaired t test (left) and 2-way analysis of variance (right). *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Immunoblotting analysis

For the immunoblotting analysis, BMDMs were seeded overnight before stimulation at a density of 1 × 10⁶ cells/well in 12-well plates. After appropriate treatments, the adherent cells in the plate were washed once with 1× Dulbecco’s PBS and lysed with RIPA buffer supplemented with protease inhibitors (A32965; Thermo Fisher Scientific) and phosphoStop (PHOSS-RO; Roche), according to the manufacturer’s instructions. These lysates were then combined with the sample loading buffer. All samples were boiled at 100 °C for 10 min prior to loading onto gels and separated using sodium dodecyl sulfate–polyacrylamide gel electrophoresis, followed by transfer onto Amersham Hybond P polyvinylidene difluoride membranes (10600023; GE HealthCare Life Sciences). After blocking nonspecific binding with 5% skim milk, membranes were incubated overnight with the following antibodies, as indicated: anti-IRF1 (#8478; Cell Signaling Technology; 1:1,000), anti-NLRC5 (clone E1E9Y; #72379; Cell Signaling Technology; 1:2,000), anti-iNOS (#13120; Cell Signaling Technology; 1:1,000), anti–phospho-RIPK1 (p-RIPK1; #31122; Cell Signaling Technology; 1:1,000), anti-total RIPK1 (t-RIPK1; #3493; Cell Signaling Technology; 1:1,000), anti-ZBP1 (AG-20B-0010; AdipoGen; 1:1,000), anti-AIM2 (ab119791; Abcam; 1:1,000), anti-NLRP3 (#AG-20B-0014; AdipoGen; 1:1,000), anti-phospho-IκBα (p-IκBα; #2859; Cell Signaling Technology; 1:1,000), anti-phospho-NF-κB p65 (p-NF-κB p65; #3033; Cell Signaling Technology; 1:1,000), and anti–β-actin (sc-47778 horseradish peroxidase [HRP]; Santa Cruz; 1:10,000). Membranes were then washed and probed with the appropriate HRP-conjugated secondary antibodies (anti-mouse [315-035-047] or anti-rabbit [111-035-047], 1:5,000; Jackson ImmunoResearch Laboratories). Immunoblot images were acquired on an Amersham Imager using Immobilon Forte Western HRP Substrate (WBLUF0500, Millipore) or SuperSignal West Femto Maximum Sensitivity Substrate (34096; Thermo Fisher Scientific). Using ImageJ software (version 1.54p; National Institutes of Health), brightness and contrast were adjusted uniformly for individual images.

Statistical analysis

GraphPad Prism version 10 (GraphPad Software) was used for statistical analysis. Data are shown as mean ± SEM. Statistical significance was determined by using unpaired Welch’s t test to compare two groups and 1- or 2-way analysis of variance analysis (with Dunnett’s or Tukey’s multiple comparisons tests) for 3 or more groups. The number of experimental replicates is indicated in the corresponding figure legends. Statistical significance is represented as *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Results

NAD⁺ is depleted in response to most lytic cell death triggers

Innate immune activation and inflammatory cell death signaling are associated with metabolic disruption, including depletion of intracellular NAD⁺ levels.^{19,21–25,29} However, it remains unclear whether NAD⁺ loss is a general feature of inflammatory cell death pathways or if it is specific to certain pathways. To address this, we stimulated mouse BMDMs with various cell death triggers and measured intracellular NAD⁺ levels at a time point corresponding to the initiation of cell death for each trigger. Induction of necroptosis with TNF plus z-VAD⁴¹ resulted in a significant decrease in intracellular NAD⁺ levels (Fig. 1A). Similarly, stimulation of BMDMs with RSL3 to trigger ferroptosis⁴² led to significant NAD⁺ depletion (Fig. 1B). Additionally, BMDMs transfected with poly(dA:dT) to activate the AIM2 inflammasome and drive pyroptosis⁴³ had reduced NAD⁺ levels (Fig. 1C). In contrast, cells infected with S. Tm to engage the NLRC4 inflammasome⁴⁴ underwent robust cell death, but did not have a significant reduction in NAD⁺ levels (Fig. 1D).

We next examined NAD⁺ dynamics in response to physiological triggers of PANoptosis. We observed significant reductions in intracellular NAD⁺ levels with all 6 tested triggers: heme plus Pam3CSK4 (Pam3) to induce NLRC5/NLRP12-dependent PANoptosis (Fig. 2A),^27,45 TNF plus IFN-γ to induce cytokine-mediated PANoptosis (Fig. 2B),⁴⁶ TAK1 inhibition to induce RIPK1-dependent PANoptosis (Fig. 2C),⁴⁷ IAV infection to induce ZBP1-dependent PANoptosis (Fig. 2D),⁴⁸F. novicida infection to induce AIM2-dependent PANoptosis (Fig. 2E),⁴⁹ and LPS plus ATP to induce NLRP3-dependent PANoptosis (Fig. 2F).⁵⁰ Collectively, these results identify NAD⁺ depletion as a consistent metabolic feature across diverse physiological PANoptotic stimuli and show that reductions in NAD⁺ levels are common to most, but not all, lytic cell death pathways.

Restoration of NAD⁺ levels selectively protects against PANoptosis

As we found that NAD⁺ depletion accompanies most inflammatory cell death pathways, we examined whether restoration of intracellular NAD⁺ levels regulates the cell death. To test this, mouse BMDMs were supplemented with NAM, a precursor in the NAD⁺ salvage pathway, together with cell death triggers. NAM supplementation restored NAD⁺ levels across all the tested triggers (Fig. S1), but this did not protect against cell death with the necroptotic (Fig. 3A), ferroptotic (Fig. 3B), or inflammasome-inducing (Fig. 3C, D) triggers. In contrast, NAM supplementation significantly inhibited cell death for all the tested PANoptotic triggers (Fig. 4A–F). Together, these results suggest a specific requirement for NAD⁺ depletion in the regulation of PANoptosis.

Figure 3.

NAD⁺ restoration does not protect from necroptosis, ferroptosis, or pyroptosis and inflammasome-induced cell death. Quantification of cell death in BMDMs treated with the indicated cell death triggers with and without nicotinamide (NAM) at the indicated time points (left), with corresponding representative cell death images (right). Genetic knockouts (A, C, D) or inhibitor treatment (B) are included as negative controls. Data represent mean ± SEM. Scale bar = 50 µm. Data are representative of at least 3 independent experiments. Statistical analyses were performed using 1-way analysis of variance. NS, not significant; PI, propidium iodide.

Figure 4.

Restoration of NAD⁺ levels selectively protects against PANoptosis. Quantification of cell death in BMDMs treated with the indicated triggers with and without nicotinamide (NAM) at the indicated time points (left), with corresponding representative cell death images (right). Genetic knockouts are included as negative controls. Data represent mean ± SEM. Scale bar = 50 µm. Data are representative of at least 3 independent experiments. Statistical analyses were performed using 1-way analysis of variance. *P < 0.05; ****P < 0.0001. PI, propidium iodide.

NAD⁺ depletion regulates expression of PANoptotic mediators

Given the selective protective effect of NAD⁺ restoration on PANoptotic cell death, we next investigated whether NAD⁺ restoration affects the expression of innate immune sensors and their upstream transcriptional regulators in PANoptosis. Interferon regulatory factor 1 (IRF1) is known to upregulate most PANoptotic sensors,^45,46,51 and we observed that IRF1 expression was robustly induced in BMDMs in response to all PANoptotic stimuli examined (Fig. 5A–F). However, its expression was reduced or delayed by NAM treatment in response to heme plus Pam3 stimulation (Fig. 5A), TAK1 inhibition (Fig. 5C), IAV infection (Fig. 5D), F. novicida infection (Fig. 5E), and LPS treatment (Fig. 5F). In the context of NLRP3, nuclear factor κB signaling is also known to be a transcriptional regulator,^52,53 and we found that NAM treatment delayed phosphorylation of IκBα and nuclear factor κB p65 (Fig. 5F).

Figure 5.

NAD⁺ depletion regulates PANoptosis priming. Immunoblot analysis of IRF1, PANoptosis sensors, and PANoptosis regulator protein expression or phosphorylation at the indicated time points following treatment with the indicated PANoptotic triggers with or without nicotinamide (NAM). Data are representative of at least 3 independent experiments.

We also assessed the expression of the PANoptotic sensors downstream of these transcriptional regulators. NAM supplementation suppressed NLRC5 expression (Fig. 5A) and RIPK1 phosphorylation (Fig. 5C), and it delayed the expression of ZBP1 (Fig. 5D) and NLRP3 (Fig. 5F), although no effect was observed on AIM2 expression (Fig. 5E). In the context of cytokine-mediated PANoptosis, in which the specific sensor remains unknown, NAM supplementation reduced the expression of the regulator iNOS (Fig. 5B), which is known to be activated downstream of IRF1.⁴⁶ Collectively, these results indicate that NAD⁺ restoration blocks the priming needed to induce the expression of critical regulators or sensors for PANoptosis.

Discussion

Innate immune activation and inflammation are accompanied by metabolic changes, notably NAD⁺ depletion^{13,19,21–23,27,29,54}; yet, how these changes functionally contribute to inflammatory cell death has remained unclear. Here, we found that NAD⁺ depletion was generally observed in lytic cell death. The exception was NLRC4-mediated cell death in response to S. Tm. S. Tm infection can increase the gene and protein expression of NAM phosphoribosyltransferase,^55,56 which produces NAD⁺ in the salvage pathway. Moreover, inflammatory cell death signaling is protective to the host in Salmonella infection.^57,58 This suggests that Salmonella may use NAM phosphoribosyltransferase stimulation to avoid NAD⁺ depletion and reduce inflammatory cell death as a form of immune evasion.

While NAD⁺ depletion was generally a common feature in lytic cell death, counteracting this depletion selectively inhibited PANoptosis, and not pyroptosis, necroptosis, or ferroptosis. The selective role of NAD⁺ dynamics in the regulation of PANoptosis demonstrates specificity in the immunometabolic regulation of inflammatory cell death. Mechanistically, NAD⁺ restoration was generally associated with attenuation of early IRF1 expression and selective modulation of downstream PANoptosis-associated innate immune sensors and regulators, suggesting that NAD⁺ availability influences the transcriptional licensing of PANoptotic signaling. This is similar to the priming concept that has been observed for inflammasomes, in which an initial triggering event (signal 1) is critical to upregulate the expression of transcription factors, sensors, and other molecules that are necessary for the subsequent activation event. Furthermore, the relationship between IRF1 suppression and sensor regulation was stimulus dependent, wherein NAD⁺ restoration affected both IRF1 and sensor expression in response to most PANoptotic stimuli, with two exceptions. NAD⁺ restoration only affected IRF1 in AIM2-mediated PANoptosis, perhaps due to the basal expression of AIM2 allowing it to act as a direct sensor of nucleic acids without upregulation. It also only affected iNOS expression in the context of cytokine-mediated PANoptosis. How NAD⁺ levels impact other downstream steps in PANoptosis, such as caspase activation, requires future study.

We consistently observed that simultaneous treatment with NAM and cell death triggers achieved NAD⁺ levels comparable to those of untreated cells. However, NAM is also known to act as an inhibitor of NAD⁺-consuming enzymes such as PARPs and sirtuins.^59–61 Therefore, the reduction in cell death we observed with NAM treatment may have also been impacted by these alternative mechanisms in addition to NAD⁺ levels.

Collectively, our findings establish NAD⁺ level as a selective signal that mechanistically links cellular metabolic state to PANoptosis. The ability to restrain PANoptosis through NAD⁺ restoration represents a potential immunometabolic strategy to limit pathological inflammation in PANoptosis-associated disease while preserving other essential immune responses.

Author contributions

R.S. (Conceptualization [Equal], Formal analysis [Lead], Investigation [Lead], Writing—original draft [Equal]), N.P. (Formal analysis [Supporting], Validation [Equal], Writing—review & editing [Supporting]), B.S. (Formal analysis [Supporting], Validation [Equal], Writing—review & editing [Supporting]), B.R.S. (Formal analysis [Supporting], Validation [Supporting], Writing—review & editing [Supporting]), P.A.G. (Formal analysis [Supporting], Writing—original draft [Equal], Writing—review & editing [Supporting]), R.E.T. (Conceptualization [Supporting], Formal analysis [Supporting], Writing—review & editing [Lead]), and T.-D.K. (Conceptualization [Equal], Funding acquisition [Lead], Supervision [Lead], Writing—review & editing [Supporting])

Supplementary material

Supplementary material is available at The Journal of Immunology online.

Funding

Work from our laboratory is supported by the National Institutes of Health (AI101935, AI124346, AI160179, and CA253095 to T.-D.K.) and the American Lebanese Syrian Associated Charities (to T.-D.K.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funding agencies had no role in the design and conduct of the study, the data interpretation, or the manuscript preparation.

Conflicts of interest

The authors declare no conflicts of interest.

Data availability

All data are present within the manuscript and included within the figures and supplemental files. Any additional information is available from the lead contact upon reasonable request.