In recent years, T cells metabolic characteristic in relation to their activation stage, differentiation and function have been more closely studied. In CD8 T cells, there are clear differences between the metabolic pathways used between naïve, memory and effector cells (**Table 1**). In addition, between the three identified memory T cell subsets, TEM, TCM, and TRM cells, there are communalities and differences affecting cell development, maintenance and function. How the development of these memory subsets are fine-tuned, with initial differences between TRM cell development compared to TEM and TCM cells reported, remains incompletely understood. CD8 TRM cells have characteristics of effector T cells, with increased expression of transcripts for proteins involved in metabolism and effector proteins such as granzymes, active cellular migration, as well as uptake of FFA and storage in lipid droplets, but without active proliferation or secretion of effector molecules such as IFN-γ. The positioning of TRM cells in diverse tissues would suggest that tissue-specific adaptations might be required for their long-term maintenance and specific function. Yet, the transcriptional make up of CD8 TRM cells in different tissues is largely similar (90, 91). Lipids are recognized to be an important substrate and FAO as important source of energy for CD8 TRM cells, but the signals resulting the bioavailability of FFA stored in lipid droplets remain to be discovered. Upon activation, CD8 TRM cells appear to use similar metabolic pathways compared with effector CD8 T cells, using OXPHOS and glycolysis. However, maintenance of T cells sets CD8 TRM cell apart, with the high levels of P2RX7 increasing susceptibility to cell death, the expression of AhR critical for survival and the altered cardiolipin composition and mitochondria activity of those CD8 T cells residing at the top layers of the skin and intestine.

The biochemical analysis of TRM cells has been hampered due to the difficulties in harvesting sufficient cell numbers and the inability to culture these cells, requiring constant interactions with tissue cells. Their important role in providing immediate protection against microbial invasion as well as tissue homeostasis and their role in systemic metabolism and pathological conditions, combined with technological advances enabling more sensitive cellular and biochemical analysis, will contribute important new discoveries in the coming years.

### REFERENCES

### AUTHOR CONTRIBUTIONS

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

### FUNDING

This work was supported by the European Union H2020 ERA project (No 667824 – EXCELLtoINNOV) for work in the Veldhoen laboratory.

### ACKNOWLEDGMENTS

The authors like to acknowledge Tania Gilot Mendes Carvalho, iMM histology department, who kindly provided the immunohistochemistry pictures used in **Figure 1**. We also acknowledge publishing support, UID/BIM/50005/2019, project funded by Fundação para a Ciência e a Tecnologia (FCT)/Ministério da Ciência, Tecnologia e Ensino Superior (MCTES) through Fundos do Orçamento de Estado.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Konjar and Veldhoen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Ataxin-3 Links NOD2 and TLR2 Mediated Innate Immune Sensing and Metabolism in Myeloid Cells

Thomas P. Chapman1†, Daniele Corridoni 1†, Seiji Shiraishi 1 , Sumeet Pandey 2 , Anna Aulicino1 , Simon Wigfield3 , Maria do Carmo Costa4 , Marie-Laëtitia Thézénas 5 , Henry Paulson4 , Roman Fischer 5 , Benedikt M. Kessler 5 and Alison Simmons 1 \*

1 MRC Human Immunology Unit, MRC Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom, 2 Translational Gastroenterology Unit, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom, 3 Department of Oncology, University of Oxford, Oxford, United Kingdom, 4 Department of Neurology, University of Michigan, Ann Arbor, MI, United States, 5 Nuffield Department of Medicine, Target Discovery Institute, University of Oxford, Oxford, United Kingdom

#### Edited by:

Hannes Stockinger, Medical University of Vienna, Austria

### Reviewed by:

Jaya Talreja, Wayne State University, United States Guntram A. Grassl, Hannover Medical School, Germany

#### \*Correspondence:

Alison Simmons<EMAIL_ADDRESS>
†These authors have contributed equally to this work

#### Specialty section:

This article was submitted to Molecular Innate Immunity, a section of the journal Frontiers in Immunology

Received: 02 April 2019 Accepted: 14 June 2019 Published: 19 July 2019

#### Citation:

Chapman TP, Corridoni D, Shiraishi S, Pandey S, Aulicino A, Wigfield S, do Carmo Costa M, Thézénas M-L, Paulson H, Fischer R, Kessler BM and Simmons A (2019) Ataxin-3 Links NOD2 and TLR2 Mediated Innate Immune Sensing and Metabolism in Myeloid Cells. Front. Immunol. 10:1495. doi: 10.3389/fimmu.2019.01495 The interplay between NOD2 and TLR2 following recognition of components of the bacterial cell wall peptidoglycan is well-established, however their role in redirecting metabolic pathways in myeloid cells to degrade pathogens and mount antigen presentation remains unclear. We show NOD2 and TLR2 mediate phosphorylation of the deubiquitinase ataxin-3 via RIPK2 and TBK1. In myeloid cells ataxin-3 associates with the mitochondrial cristae protein MIC60, and is required for oxidative phosphorylation. Depletion of ataxin-3 leads to impaired induction of mitochondrial reactive oxygen species (mROS) and defective bacterial killing. A mass spectrometry analysis of NOD2/TLR2 triggered ataxin-3 deubiquitination targets revealed immunometabolic regulators, including HIF-1α and LAMTOR1 that may contribute to these effects. Thus, we define how ataxin-3 plays an essential role in NOD2 and TLR2 sensing and effector functions in myeloid cells.

Keywords: Nod2, TLR2, metabolism, innate immnuity, ataxin 3

### INTRODUCTION

Pattern recognition receptors (PRRs) recognize foreign antigen to direct innate and adaptive immune responses against invading pathogens (1). Polymorphisms in the PRR nucleotidebinding oligomerization domain-containing protein 2 (NOD2) represent the strongest genetic risk factor for the inflammatory bowel disease Crohn's (CD), and thus this bacterial sensor is the focus of particular research interest (2–4). NOD2 recognizes muramyl dipeptide (MDP), the largest fraction of peptidoglycan, that is present in the cell walls of all bacteria (5). Subsequent activation of NF-κB and MAPK pathways via interaction with receptor-interacting protein kinase 2 (RIPK2) results in an array of immune responses, such as production and regulation of pro-inflammatory cytokines (6), and modulation of T-cell function (7–9). NOD2 also directs autophagy, which is important both for bacterial clearance and MHC class II antigen presentation (10). Importantly, NOD2 signaling is intimately linked with that of toll like receptor TLR2, with both responding to ligands derived from the same bacterial component, peptidoglycan. Although the precise mechanisms of cross-regulation are not well-understood, both NOD2 and TLR2 activate separate upstream signaling cascades to recruit the same NFκB and MAPK pathways, and are typically thought to act in a synergistic fashion (11). CD patients harboring NOD2 polymorphisms display loss-of-function for induction of NOD2 and NOD2/TLR2 effector signaling factors (12, 13). In contrast, gain-of-function mutations of NOD2 have been associated with other inflammatory disease, such as Blau syndrome and earlyonset-sarcoidosis (EOS).

In recent years it has become clear that cross-talk between metabolic and immune pathways is central to the regulation of host defense (14). Immune cells undergo significant metabolic reprogramming during the immune response, both as a result of changes in the metabolic microenvironment induced by inflammation, and in response to immune triggering. This interplay appears of particular importance to dendritic cells and macrophages and controls core processes including differentiation (15). However, while the importance of PRR activation in directing metabolic pathways that impact on immune effector function is now well-established, how NOD2 and TLR2 influence myeloid metabolism is unclear. Here, following a phosphoproteomic screen of NOD2 and TLR signaling we identify a deubiquitinase essential for metabolic reprogramming and innate effector function in myeloid cells.

### RESULTS

### NOD2 and TLR2 Stimulation Leads to Ataxin-3 Phosphorylation Mediated by RIPK2 and TBK1

We identified ataxin-3 as one of the most differentially phosphorylated proteins on NOD2/TLR2 stimulation through a quantitative phosphoproteomic screen in monocyte derived dendritic cells (moDCs) from healthy human donors (**Supplementary Table 1**). Ataxin-3 is a deubiquitinase (DUB) (16) that is required for non-selective autophagy and that is linked to neurodegenerative disease (17–19).

We first validated this result by immunoblotting phosphoenriched samples for ataxin-3 (**Figure 1A**). Both NOD2 and TLR2 stimulation alone led to ataxin-3 phosphorylation; this effect was enhanced on dual stimulation of NOD2 and TLR2. It was also observed to a lesser extent following stimulation of TLR4, TLR7, and TLR8 (**Figure 1A**). NOD2 mediated phosphorylation of ataxin-3 was examined in greater detail. A time course experiment demonstrated that ataxin-3 phosphorylation was maximal 30 min after MDP stimulation (**Figure 1B**). While NOD2 is the only known receptor for MDP, the absolute requirement for NOD2 in the MDP stimulated phosphorylation of ataxin-3 was investigated. We downregulated expression of NOD2 in THP-1 cells using short hairpin RNAs (shRNA) targeting NOD2 (**Figure 1C**). Reduction of ataxin-3 phosphorylation on MDP exposure was observed in NOD2 knockdown cells (**Figure 1D**). Next, given the central importance of RIPK2 in NOD2 signaling (20, 21), the requirement of RIPK2 for phosphorylation of ataxin-3 by NOD2 was investigated. NOD2-RIPK2 inflammatory signaling can be potently and selectively inhibited by the clinically relevant kinase inhibitor Ponatinib, that functions by blocking RIPK2 autophosphorylation and ubiquitination (22). moDCs were treated with Ponatinib prior to stimulation with MDP or PAM3CSK4 or both, with phosphorylation of p38 used as a positive control for the inhibitor. As expected, inhibition of RIPK2 blocked NOD2 induced phosphorylation of p38, but had no effect on induction by TLR2, which signals to p38 via a MyD88 pathway which is independent of RIPK2 (23). Inhibition of RIPK2 led to complete inhibition of NOD2 induced phosphorylation of ataxin-3, and significant abrogation of the synergistic NOD2/TLR2 signal in both cell types (**Figure 1E**). Recent evidence suggests that tank binding kinase 1 (TBK1) may represent a novel but important kinase in the NOD2/RIPK2 signaling cascade (24, 25) and MDP stimulation of the NOD2 receptor has been shown to induce TBK1 phosphorylation at S172 (24). Consequently, the requirement for TBK1 in NOD2/RIPK2 dependent phosphorylation of ataxin-3 was examined. We downregulated expression of TBK1 in THP-1 cells using short hairpin RNAs (shRNA) targeting TBK1 (**Figure 1F**). Reduction of ataxin-3 phosphorylation on MDP exposure was observed in TBK1 knockdown cells (**Figure 1G**). The possibility that TBK1 might directly phosphorylate ataxin-3, as has been described for a number of other proteins including optineurin (26) and p62 (27), was explored using an in vitro kinase assay (**Figure 1H**). The expected autophosphorylation of TBK1 was demonstrated by a marginally higher molecular weight of the TBK1 band in samples containing both TBK1 and ATP. Importantly, a significant proportion of the ataxin-3 band was noted at a higher molecular weight in samples containing ataxin-3, TBK1 and ATP, consistent with ataxin-3 phosphorylation (**Figure 1H**). Notably, no change in migration of the ataxin-3 band was seen in samples containing ataxin-3 and TBK1 but not ATP, confirming the ATP dependency of this shift, consistent with phosphorylation. Finally, the phosphorylation site of ataxin-3 was sought, using liquid chromatography mass spectrometry analysis of endogenous ataxin-3 immunoprecipitated from THP-1 cells. A significant shift in mass/charge ratio, consistent with phosphorylation, was detected at a single peptide in the MDP/PAM3CSK4 stimulated sample only, corresponding to phosphorylation at serine 265 (**Figure 1I**). This residue has been described as a phosphorylation site in 12 separate large scale mass spectrometry (MS) screens of human primary cells and cell lines (28), and is highly conserved in placental bearing mammals (29), but there is no existing knowledge of its functional relevance. It is located in close proximity to the second ubiquitin interacting motif (UIM), suggesting that phosphorylation could affect specificity of DUB target, as has been described for neighboring serine residues 256/260/261 (30) (**Figure 1J**).

Taken together, this data shows that activation of NOD2/TLR2 signaling pathway induces phosphorylation of the DUB ataxin-3. TBK1 is required for the direct phosphorylation of ataxin-3 at serine 265 following NOD2/TLR2 activation.

### Ataxin-3 Localizes With the Mitochondrial Cristae Protein MIC60 and Regulates the Expression of the Oxphos Machinery Components

To identify novel interacting partners of ataxin-3 in innate immune cells, endogenous ataxin-3 was immunoprecipitated in moDCs from healthy human donors, and subjected to mass

FIGURE 1 | NOD2/TLR2-mediated phosphorylation of ataxin-3. Immunoblot using antibodies against ataxin-3 and β-actin of whole cell lysates (WCL) and phosphoprotein enriched lysates (PE) from moDCs either (A) unstimulated or stimulated with the NOD2 ligand MDP 10µg/ml, or the TLR2 ligand PAM3CSK4 1µg/ml, or both, or the TLR4 ligand LPS 100 ng/ml or the TLR7/8 ligand R848 (Resiquimod) 1µg/ml for 30 min or (B) unstimulated or stimulated with the NOD2 ligand MDP for 15, 30, or 60 min. (C) THP-1 cells were transduced with control or NOD2-targeting lentiviral shRNAs and analyzed for NOD2 expression by qPCR analysis. (D) Immunoblot using antibodies against ataxin-3, p38, and β-actin of WCL and PE lysates from THP-1 cells expressing control or NOD2 shRNA and either unstimulated or stimulated with the NOD2 ligand MDP or the TLR ligand PAM3CSK4, or both, for 60 min. (E) Immunoblot using antibodies against ataxin-3, p38 and β-actin of WCL and PE lysates from THP1 cells which were pre-treated with the RIPK2 inhibitor Ponatinib 50 nM for 60 min and then left unstimulated or stimulated with the NOD2 ligand MDP or the TLR2 ligand PAM3CSK4 or both. (F) THP-1 cells were transduced with control or TBK1-targeting lentiviral shRNAs and immunoblotted to detect TBK1 expression (G) Immunoblot using antibodies against ataxin-3, p38 and b-actin of WCL and PE lysates from THP-1 cells expressing control or TBK1 shRNA left unstimulated or stimulated with the NOD2 ligand MDP or the TLR2 ligand PAM3CSK4 or both for 60 min. (H) Immunoblot using antibodies against TBK1 and ataxin-3 following an in vitro kinase assay of GST-TBK1 protein or His-ataxin-3 protein with ATP, or both GST-TBK1 and His-ataxin-3 with or without ATP which were incubated for 60 min at 30◦C. (I,J) Identification of the phosphorylated serine residue (s265) in ataxin-3 with a characteristic increase in mass/charge ratio in the stimulated sample. All immunoblots are representative of at least two independent experiments.

spectrometry analysis. One of the most abundant proteins identified in the pull down was the mitochondrial cristae protein MIC60 (**Figures 2A,B**). The association between ataxin-3 and MIC60 was validated through immunoblot of immunoprecipitated ataxin-3 (**Figure 2C**). There appeared to be no change in abundance of MIC60 when moDCs were stimulated with MDP + PAM3CSK4 prior to immunoprecipitation of ataxin-3, suggesting that NOD2/TLR2 stimulation does not

affect binding. To further confirm the association, MIC60 was pulled down, and an immunoblot for ataxin-3 performed (**Figure 2D**). Here, ataxin-3 appeared at two molecular weights, suggesting that either two separate isoforms bind to MIC60, or it is post-translationally modified. Finally, super-resolution assessment using stimulated emission depletion (STED) microscopy confirmed that ataxin-3 was situated in close proximity to MIC60 (**Figure 2E**).

MIC60 is the largest protein in the mitochondrial contact site (MICOS) complex, which is embedded in the mitochondrial inner membrane and acts as a key regulator of cristae junction formation and assembly of respiratory chain complexes which are required for oxidative phosphorylation (31). Additional specific roles for MIC60 include the import of proteins (32, 33) and regulation of mitochondrial DNA (mtDNA) transcription (34, 35). Consequently, we examined the effect of ataxin-3 knockdown in moDCS on expression of mtDNA genes that encode components of the oxphos machinery. moDCS from healthy human donors were found to express either a single or double isoform of ataxin-3 with approximately equal frequency, but all detectable isoforms could be efficiently knocked down (**Figure 2F**). Ataxin-3 depletion led to a 2 fold upregulation of NADH-ubiquinone oxidoreductase 1 (MT-ND1), with a statistically significant upregulation observed for mRNA expression of two other genes from Complex I, MT-ND3 and MT-ND4L (**Figure 2G**). In comparison, genes encoding components of Complex III, IV and V were broadly unaffected. It is noteworthy that mtDNA transcription is tightly regulated due to its close links to oxphos, and thus 1.5- to 2-fold changes in mRNA expression level represent a potentially functionally significant alteration (36). The effect of NOD2/TLR2 stimulation was examined on MT-ND1, the most significantly affected gene. Stimulation led to a significant upregulation in mRNA expression in both the control and ataxin-3 depleted cells, but there was significantly greater ND1 in the ataxin-3 depleted cells following stimulation (**Figure 2H**). Finally, to understand if these effects on Complex I genes correlate with modulation of cytokine responses, we have assessed the expression of IL8, IL1β, TNF, IL12B, and IL23A in response to TLR/NOD2 signaling in human moDCS and found that ataxin-3 depletion using siRNA did not affect the levels of these cytokines (data not shown).

These results indicate a novel association between ataxin-3 and MIC60, a component of the MICOS complex involved in the regulation of mtDNA. We demonstrated that ataxin-3 regulates mtDNA by downregulating the expression of Complex I genes, an effect increased on NOD2/TLR2 sensing.

### Ataxin-3 Is Important for Optimal Mitochondrial Respiration Following NOD2 and TLR2 Stimulation

We next investigated the functional relevance of the observed changes in the expression of Complex I genes. Using short hairpin RNAs (shRNA) targeting the ataxin-3 gene (ATXN3), we downregulated ataxin-3 protein expression in THP-1 cells (**Figure 3A**). We next performed a real time analysis of oxidative phosphorylation to address the function of ataxin-3. We found that ataxin-3 depletion led to a significant reduction in all the key parameters of mitochondrial respiration assessed (**Figures 3B–F**).

We next determined whether NOD2/TLR2-mediated ataxin-3 phosphorylation stimulation affects mitochondrial respiration. Prolonged triggering of these PRRs led to an expected metabolic shift (37) with downregulation of oxidative phosphorylation. In the ataxin-3 depleted cells the level of oxphos remained significantly lower than in the control cells following stimulation (**Figures 3G–J**). Importantly, no significant difference in mtDNA copy number was found between the control and ataxin-3 depleted THP-1 cell line (**Supplementary Figure 1**), suggesting that there are no differences in mitochondrial mass or turnover through mitophagy to explain the observed changes.

Taken together, this data shows that in innate immune cells, ataxin-3 is required for optimal mitochondrial respiration and this effect is enhanced following its phosphorylation on NOD2/TLR2 stimulation.

### Ataxin-3 Is Required for Mitochondrial ROS Production, and Is Necessary for Optimal Bacterial Killing

A key function of mitochondrial respiration in immune cells is the generation of mROS. This results from leakage of electrons, predominantly from Complex I and to a lesser extent from Complex III, which partially reduce oxygen to form superoxide (38). The effect of ataxin-3 depletion on mROS and total cellular ROS was therefore examined. Ataxin-3 depletion led to a significant reduction in mROS (**Figure 4A**). As expected, there was a corresponding decrease in total cellular ROS, to which mROS makes a significant contribution (**Figure 4B**). The ability of immune cells to upregulate mROS production on pathogen challenge is crucial to the immune response (39); importantly, ataxin-3 depleted cells also produced less mROS on NOD2/TLR2 stimulation (**Figure 4C**). mROS forms an important component of antibacterial responses, and is important for bacterial killing (39). To test the functional significance of the observed impairment of mitochondrial oxphos and mROS generation on NOD2/TLR2 triggering, we assessed the response of ataxin-3 depleted macrophages to Salmonella Typhimurium, a Gram-negative intracellular bacterium that is sensitive to ROS-dependent killing (39, 40). A gentamicin survival assay was undertaken. While bacterial invasion was unchanged, as evidenced by similar bacterial counts at 1 h postinfection, there was subsequently significantly greater bacterial survival in the ataxin-3 depleted cells that was maximal at 6 h (**Figure 4D**). There were no significant differences in cell viability between the two groups at any of the infection time points (**Supplementary Figure 2**), excluding differences in cell survival as a contributing factor in the bacterial killing deficit.

Taken together, this data shows that in macrophages ataxin-3 is required for mROS generation and this contributes to effective intracellular bacterial killing.

### An Unbiased Ubiquitome Screen Reveals Novel DUB Targets of Ataxin-3 Following NOD2 and TLR2 Activation

To further define the role of ataxin-3 in NOD2/TLR2 signaling, we sought to define downstream DUB targets. Classically the ubiquitinated proteome, also termed the ubiquitome, was first enriched using His6-tagged ubiquitinated conjugates under denaturing conditions. However, concerns exist over the impact of overexpressed modified His6, which competes with

endogenous ubiquitin, on the ubiquitome (41). An alternative method of enrichment, using high affinity ubiquitin traps has therefore been developed. These tandem ubiquitin binding entities (TUBEs) specifically recognize, bind to, and stabilize polyubiquitinated proteins, protecting them from degradation by DUBs or the proteasome. The enriched ubiquitinated proteins can then be analyzed by MS (41–43). The ability of TUBEs to preferentially recognize either K48 or K63 linked polyubiquitin provides a further advantage. Consequently, the use of a K63- TUBEs1 system which shows a 10-fold higher affinity for K63 linked chains, allows the selective enrichment of the K63 linked ubiquitome. This provides a specific means of purifying the K63 chains favored by ataxin-3 (44), and thus was employed as a strategy for defining novel DUB targets of ataxin-3 in immune cells.

The TUBEs2 system was used to enrich ubiquitinated proteins in ataxin-3 depleted and control THP-1 cells, either left unstimulated or stimulated for 1 h with MDP + PAM3CSK4. Samples from three biological replicates were then subjected to mass spectrometry analysis (**Figure 5A**). As a quality control prior to MS analysis, immunoblotting with an antibody against K63-linkage specific polyubiquitin demonstrated a marked increase in the levels of K63 ubiquitinated proteins in the ataxin-3 depleted cells, most notably at higher molecular weights, with NOD2/TLR2 stimulation leading to a separate shift in staining pattern (**Figure 5B**).

Mass spectrometry analysis identified 291 proteins as changing significantly between any condition when averaged across the three biological replicates. As ataxin-3 acts as a DUB, ataxin-3 depletion would classically lead to an accumulation of ubiquitinated targets and thus particular attention was paid to those proteins that showed an increase in abundance in the ataxin-3 depleted samples (**Supplementary Table 2**). However, as deubiquitination can also regulate protein stability, it is likely that a number of the proteins found to decrease in abundance on ataxin-3 depletion are also direct DUB targets of ataxin-3. Most notably, the immunometabolic regulator HIF1α (45) was found to be more abundant in the ataxin-3 depleted cells, suggesting that ataxin-3 may deubiquitinate HIF1α (**Figure 5C**). To specifically interrogate the importance of NOD2/TLR2 phosphorylation of ataxin-3 on DUB activity, the abundance of proteins in the ataxin-3 depleted cells was compared to the control cells following stimulation with MDP + PAM3CSK4 (**Supplementary Table 3**). Strikingly, a cluster of proteins related to metabolism were noted in the ataxin-3 depleted cells (marked in red on **Figure 5D**).

\*\*p < 0.01.

## Ataxin-3 Deubiquitinates HIF, PLD3, and LAMTOR1 Upon NOD2 and TLR2 Activation

A number of the proteins from the mass spectrometry analysis were selected for further validation. HIF1α was of particular interest given its central role in immunometabolism. Although classically described as part of the family of hypoxia-inducible factor regulators, mediating the cellular response to hypoxia (46), more recent work has demonstrated a broader role in regulation of the immune system. It is important for both the survival and function of cells of the innate immune system,

through regulation of metabolic activation (47–49). HIF1αwas validated as a DUB target of ataxin-3 through immunoblot, with a significant increase in ubiquitinated HIF1α in the ataxin-3 depleted cells (**Figure 6A**). HIF1α was detected in the whole cell lysates of both control and ataxin-3 depleted cells in normoxia, as the proteasome inhibitor MG132 which reduces the degradation of all ubiquitinated proteins was added to the cell suspension 30 min before the end of all TUBEs experiments.

Phospholipase D3 (PLD3) was also intriguing as it has recently been shown to regulate inflammatory cytokine responses in response to TLR9 signaling by acting as an endonuclease (50). In humans, mutations confer an increased risk for the neurodegenerative diseases Alzheimer's (51) and spinocerebellar ataxia (52), with increasing evidence of the role of innate immune dysfunction in neurodegeneration (53). Importantly, polyglutamine repeat mutations in ataxin-3 are themselves associated with the spinocerebellar ataxia Machado-Joseph disease (18). Ragulator complex protein LAMTOR1 forms part of the Ragulator complex essential for amino acid sensing and activation of mTORC1 (54), but has also been linked to independent roles in lysosomal maturation (55) and M2 macrophage differentiation (56). PLD3 and LAMTOR1 were both validated by immunoblot (**Figures 6B,C**). Ataxin-3 depletion led to accumulation of ubiquitinated forms of both PLD3 and LAMTOR1. Notably, NOD2/TLR2 stimulation increased LAMTOR1 ubiquitination in the control cells, but there was markedly more LAMTOR1 ubiquitination in the stimulated ataxin-3 depleted cells (**Figure 6C**). This suggests that ataxin-3 modulates the ubiquitination of LAMTOR1 induced by NOD2/TLR2 stimulation.

To further study the interaction between LAMTOR1 and ataxin-3, an overexpression system was employed in the human cell line HEK293. HA-ataxin-3 and GFP-LAMTOR1 was overexpressed, together with a GFP-control and then IP of HAataxin-3 performed using an antibody against the HA tag. Ataxin-3 was found to bind directly to LAMTOR1 (**Figure 6D**). Next,

FIGURE 6 | (C) LAMTOR1 in whole cell lysates (input) and TUBEs1 enriched fractions from control shRNA and ataxin-3 shRNA THP-1 cells left unstimulated or stimulated for 60 min with MDP + PAM3CSK4. (D) Immunoblot using antibodies against GFP, HA, and β-actin in input and HA-immunoprecipitated lysates, in HEK293 cells where GFP and/or GFP-LAMTOR1 and/or HA-ataxin-3 were overexpressed. (E) Immunoblot using antibodies against ubiquitin, GFP, ataxin-3, and β-actin in input and isotype control (iso) or GFP immunoprecipitated lysates where ubiquitin and GFP-LAMTOR1 were overexpressed with or without HA-ataxin-3. All immunoblots are representative of at least two independent experiments.

the finding that LAMTOR1 is a direct DUB target of ataxin-3 was confirmed. Ubiquitin, GFP-LAMTOR1 and HA-ataxin-3 were overexpressed in HEK293 cells and IP of GFP-LAMTOR1 performed using an antibody against the GFP tag. The level of ubiquitinated GFP-LAMTOR1 was found to be significantly less in cells where HA-ataxin-3 was co-expressed (**Figure 6E**).

Taken together, these results show that ataxin-3 modulates the ubiquitination of previously unidentified targets related to metabolism. This effect is enhanced on following phosphorylation of ataxin-3 on NOD2/TLR2 triggering.

### DISCUSSION

In this study we demonstrate that NOD2 and TLR2 phosphorylates the deubiquitinase ataxin-3 at serine 265 through a signaling cascade involving RIPK2 and TBK1. Immunoprecipitation and MS analysis of interacting partners established an association with a core component of the mitochondrial MICOS complex MIC60. Ataxin-3 was subsequently shown to be necessary for optimal mitochondrial respiration and mitochondrial ROS generation in macrophages, an effect enhanced by its phosphorylation on NOD2/TLR2 triggering. In line with this, we found that ataxin-3 is required for optimal intracellular bacterial killing of Salmonella Typhimurium. Finally, we dissected the specific DUB role of ataxin-3 in an immune context through an unbiased MS screen of the ubiquitome. A preponderance of metabolism related proteins were discovered including HIF1α, phospholipase D3 and LAMTOR1, underlining a central role of ataxin-3 in immunometabolism.

Deubiquitinating enzymes (DUBs) represent specialized proteases which modify ubiquitin chains by cleaving the isopeptide bonds linking the ubiquitin C-terminus to a lysine side chain on the target protein. Modification of ubiquitination may alter cellular responses through regulation of target protein stability, or mediate signal transduction through non-degradative pathways including mediation of protein-protein interactions (57). Ataxin-3 is a small protein, consisting of 364 amino acids, that is ubiquitously expressed (58). At the N-terminus there is a catalytic Josephin domain, which acts as a protease that hydrolyses ubiquitin linkages and allows ataxin-3 to function as a DUB (59). A flexible C-terminal tail contains either two or three ubiquitin-interacting motifs (UIMs), according to the isoform (60). The UIMs mediate selective binding to ubiquitin chains, determining the type of chain that can be cleaved by the Josephin domain. Ataxin-3 shows a preference for cleavage of K63-Ub chains, although it is able to bind both K63 and K48 chains (44).

Ataxin-3 has been linked to neurodegenerative disease after unstable CAG repeat expansions in the ATXN3 gene were identified as the cause of spinocerebellar ataxia Type 3 (SCA3), also known as Machado-Joseph Disease, the most common autosomal dominant ataxia (18). Importantly, the expanded polyglutamine stretch results in more complex sequelae than a simple loss of protein function, and likely leads to a toxic gain of function through altered binding properties, aggregation and subcellular localization (61). Accumulating evidence suggests that ataxin-3 performs diverse cellular roles, including DNA repair (62, 63) and transcriptional regulation (64), regulation of protein quality through endoplasmic reticulum (ER) associated degradation (65) and aggresome formation (66), and beclin-1 dependent autophagy (17). A recent study provided a first link to immune regulation, demonstrating that ataxin-3 regulates Type 1 interferon antiviral responses through interaction with histone deacetylase 3 (HDAC 3) (67). The present study is the first to link ataxin-3 to PRR signaling and demonstrate its importance in mitochondrial respiration in macrophages, following the discovery that ataxin-3 associates with the mitochondrial protein MIC60.

MIC60 forms a core part of the MICOS complex, which is embedded in the mitochondrial inner membrane. It acts as a key regulator of mitochondrial inner membrane shape and organization. This is essential for cristae junction formation and assembly of respiratory chain complexes which are required for oxidative phosphorylation (31). MIC60 also appears to act independently of the MICOS complex, and has recently been implicated in regulation of mtDNA transcription (35). The mitochondrial genome encodes just 13 proteins, all essential components of oxphos complexes I, III and IV. In keeping with this known function of MIC60, we found that depletion of ataxin-3 led to specific upregulation of mtDNA transcripts encoding proteins required for Complex I, and this was further upregulated by NOD2/TLR2 stimulation. In addition, specific interrogation of mitochondrial oxidative phosphorylation through use of the Seahorse platform demonstrated that ataxin-3 depletion led to a particularly striking impairment in maximal respiration and spare respiratory capacity (SRC). SRC represents the extra mitochondrial capacity available within a cell to produce energy under conditions of increased work or stress and is important for cellular function and survival (68–70). Macrophages increase their SRC in response to bacterial infection to drive anti-microbial responses, and this is coordinated in part by modulation of the ETC Complexes I and II (71). In M2 macrophages, SRC is critical for their activation and prolonged survival, and clearance of the parasitic helminth (72). We found that ataxin-3 depletion impaired mROS production at both baseline and in response to NOD2/TLR2 stimulation, demonstrating the functional relevance of the observed mitochondrial respiratory impairment. Finally, we demonstrated the importance of ataxin-3 in intracellular killing of the pathogen Salmonella Typhimurium, with PRR mediated mROS generation well-established as critical for destruction of this bacterium (39).

Fewer than 100 DUBs are thought to be responsible for regulating the ubiquitination of tens of thousands of proteins in a tightly regulated and sophisticated manner (57, 73). Hence defining the wide-ranging DUB targets of ataxin-3 is essential to decipher its functions. Ubiquitin signaling represents an indispensable mechanism of regulating both the innate and adaptive immune response, and is central to the NOD2 cascade (74). For the first time, this study undertook an unbiased screen of the ubiquitome in ataxin-3 depleted cells. Notably, a significant number of metabolism related proteins were found, further reinforcing the potential importance of ataxin-3 in cellular immunometabolism.

The discovery that HIF1α is a DUB target of ataxin-3 in macrophages is noteworthy, given the emergency of HIF1α as a key immunometabolic regulator. Work in a conditional HIF1 α knockout mouse, targeting the myeloid lineage, demonstrated the critical requirement of HIF1 α for inflammatory responses (75). This correlated with defects in glycolysis and metabolic activation, which is tightly regulated by HIF1 α The endolysosomal protein PLD3 was also validated as a further novel DUB target of ataxin-3. Although PLD3 contains two phosphodiesterase domains, and hence is classed as a member of the phospholipase diesterase (PLD) family which act to hydrolyse phospholipids, the phospholipase activity of PLD3 has not been definitively established. The importance of PLDS in immunity was recently demonstrated, with the discovery that it acts as a single-stranded acid exonuclease that breaks down ligands for the PRR TLR9, hence regulating TLR9 mediated inflammatory responses in collaboration with PLD4 (50).

The discovery in the present study that NOD2/TLR2 triggering leads to deubiquitination of LAMTOR1 by ataxin-3 is of particular interest. LAMTOR1, also known as p18, is a late endosome/lysosome membrane adapter protein that localizes to the lipid rafts of these organelles (76, 77). LAMTOR1 plays an essential role in the activation of the mTORC kinase complex in response to amino acid levels (54). Through a mechanism involving the lysosomal v-ATPase in the presence of amino acid sufficiency, LAMTOR1 forms a scaffold at the lysosomal membrane with LAMTOR2,3,4 and 5 (the pentameric Ragulator complex) for the Rag GTPase complex (RagAB/CD) (54, 78, 79). This leads to the recruitment and activation of mTORC1 which inhibits autophagy. The lysosomal v-ATPAse-Ragulator complex also activates another critical metabolic sensor, AMP-activated protein kinase (AMPK), which responds to falling energy levels by driving cellular catabolism programmes and downregulating anabolic pathways (80). Thus, this complex is able to respond to both energy/nutrient sufficiency and deficiency. Strikingly, of all cells, macrophages express the highest levels of the five Ragulator components, suggesting their importance in the immune response (81). Indeed, LAMTOR1 was recently found to be essential for the polarization of M2 macrophages both in vitro and in vivo in a knockout mouse model, by coupling metabolism to immunity (56).

The physiological importance of NOD2 and TLR2 in both the innate and adaptive immune response is well-established. The interplay between NOD2 and TLR2 has been well-characterized given the fact that they both respond to adjacent components of PGN found in the bacterial cell walls. The NOD2 signaling pathway amplifies TLR2 activation and both receptors synergize in the induction of cytokine production. NOD2 variants confer the greatest single genetic risk factor for Crohn's disease disease (2, 3), yet significant gaps remain in our knowledge of how this receptor exerts its effects (82). Notably, despite the recent explosion of interest in the field of immunometabolism, almost nothing is known about how the synergistic effects of NOD2 and TLR2 signaling might intersect with metabolic pathways to modulate the immune response. Here, we defined the molecular and functional basis by which NOD2/TLR2 sensing links to ataxin-3 and, consequently, other immunometabolic factors. Future studies are required to provide novel prospects for modulating these pathways as new therapeutic strategies for inflammatory disorders.

### MATERIALS AND METHODS

### Cells

Human monocytes were purified from healthy donor peripheral blood mononuclear cells (PBMCs) by positive immunoselection with anti-CD14-conjugated MACS beads (Miltenyi Biotec). moDCs were obtained by culturing monocytes for 5 days with IL-4 and GM-CSF (Peprotech). Immature moDCs were harvested on day 5 of culture. The human THP-1 cell line was purchased from ATCC. Prior to use, THP-1 were differentiated by treatment with 25 ng/ml phorbol 12-myristate 13-acetate (PMA) (Sigma) for 16 h.

### Reagents and Antibodies

The following stains were used: MItosox Red M36008 (Invitrogen) and DHR 123 D23806 (Invitrogen).  The secondary antibodies included: anti-rabbit HRP conjugate #7074 (Cell Signaling), anti-mouse HRP conjugate #7076 (Cell Signaling), goat anti-rabbit Alexa fluor 488 A-11034 (Invitrogen), goat anti-rabbit Alexa fluor 488 A-11029 (Invitrogen), goat antimouse Alexa fluor 568 A-11036 (Invitrogen), goat anti-rabbit Alexa fluor 568 A-11004 (Invitrogen). Beta actin HRP conjugate #5125 (Cell Signaling). For qPCR, the following Taqman primers were used (all ThermoFisher): NOD2 (Hs01550753\_m1), RPLP0 (Hs99999902\_m1), MT-ND1 Hs02596873\_s1, MT-ND2, Hs02596874\_g1, MT-ND3 Hs02596875\_s1, MT-ND4L Hs02596877\_g1, MT-CYB Hs02596867\_s1, MT-CO1 Hs02596864\_g1, ATP6, Hs02596862\_g1. For overexpression experiments, GFP-LAMTOR1 and HA-ataxin-3 were obtained from the University of Dundee.

### Cell Stimulation

moDCs and THP-1 cells were left unstimulated or stimulated with 10µg/ml MDP or 1µg/ml PAM3CSK4 (Invivogen) or both at the indicated time points. In some experiments, other PRR ligands were used including LPS 100 ng/ml, and R848 1µg/ml (Invivogen) or cells were treated with the small molecule inhibitor Ponatinib (50 nM) for 1 h.

### Phosphoprotein Purification

Cells were harvested on ice and washed once with ice cold modified Hanks Buffered Saline (HBS) (20 mM HEPES pH 7.4, 150 mM NaCl in ddH20). Cell pellets were lysed in Qiagen "Phosphoprotein lysis buffer" containing 0.25% (v/v) CHAPS with 1% (v/v) phosphatase inhibitor cocktail 3 (Sigma), protease inhibitor tablet (Qiagen) and the nuclease 0.0002% (v/v) Benzonase (Qiagen) at 4◦C for 40 min, with vortexing every 10 min. Cell debris was removed by centrifugation of the lysate at 13,300 rpm for 30 min at 4◦C. The clarified supernatant was then transferred to fresh pre-cooled tubes and protein concentration determined by BCA assay. The samples were then diluted in Qiagen "wash buffer" containing 0.25% (v/v) CHAPS to a concentration of 0.1 mg/ml. Aliquots of whole cell lysate and diluted whole cell lysate were kept for subsequent immunoblot. The phosphoenrichment columns were washed with 6 ml "wash buffer," before the diluted samples were loaded onto the columns. Following two further washes of the columns with 6 ml "wash buffer," the phosphoenriched fraction was eluted from the columns using Qiagen "elution buffer" containing 0.25% (v/v) CHAPS. Following concentration of the eluted fraction to a volume of 200–300 µl using 9 k molecular weight cut-off concentrator columns (Thermo Fisher) with centrifugation 13,000 rpm 30 min, protein concentration was measured by BCA. For mass spectrometry (MS) experiments, phosphoenriched lysates were stored at −80◦C. Otherwise, whole cell lysate, diluted whole cell lysate and phosphoenriched lysates were processed for SDS-PAGE with NuPage LDS Sample buffer (Life Technologies) and 100 mM dithriothreitol (Sigma), followed by heating at 70◦C for 5 min. Samples were then frozen at −80◦C until immunoblotting was performed.

### Immunoprecipitation

Samples were washed twice in ice cold HBS and then lysed in 1,000 µl lysis buffer for 30 min at 4◦C with end over end mixing [Cell Signaling Lysis Buffer 20 mM Tris-HCL pH7.5, 1 mM Na2EDTA, 1 mM EGTA, 1% Triton, 2.5 mM sodium pyrophosphate, 1 mM beta-glycerophosphate, 1 mM Na3O4, 1µg/ml leupeptin supplemented with 1% (v/v) HALT protease inhibitor cocktail (Thermo Fisher) and 1% (v/v) Phosphatase inhibitor cocktail 2 and 3 (Sigma) and 1 mM PMSF (Cell Signaling)]. Lysates were clarified by centrifugation at 14,000 g for 15 min at 4◦C, and the supernatant transferred to fresh Eppendorfs. Protein concentrations were calculated by BCA. Fifty µl of input lysate was heated with LDS/DTT and stored at −80◦C for later immunoblot. Next, concentrations were adjusted to 1 mg/ml and 7.5 mg of protein was taken forward for IP for each condition. The appropriate antibody or isotype control antibody was added to the lysates followed by incubation with gentle end over end mixing at 4◦C overnight.

The next morning, Protein G Dynabeads (Thermo Fisher) were washed once in lysis buffer, using a DynaMag2 magnet (Invitrogen) to separate the beads from solution, and 5 µl of beads per 1 µg of antibody was added to each sample. Samples were incubated with the beads with gentle end over end mixing for 2 h at 4◦C. Following this, the supernatant was removed using a magnet to separate the beads, with 50 µl of the supernatant heated with LDS/DTT and stored at −80◦C later immunoblot. The beads were washed 4 times in total with lysis buffer containing all protease and phosphatase inhibitors, with gentle end over end mixing for 5 min at 4◦C for each wash. Elution of the beads was then performed by incubating the beads with pH 2.8 elution buffer (Pierce) with gentle end over end mixing for 30 min at 4◦C. The eluate was collected and neutralized immediately with 1/10 volume of 1 M Tris-HCL pH 9. Elution and neutralization was performed a further two times to ensure complete elution. The eluate was stored at −80◦C until used for downstream processing.

### Tandem Ubiquitin Binding Entities (TUBEs) Ubiquitin Immunoprecipitation

Typically 2.5 × 107 THP-1 cells were used per condition. Thirty min before the end of the experimental conditions, samples were incubated with 10µM MG132 (Sigma) for 30 min at 37◦C before harvesting, washing once in ice cold PBS and lysing in 1 ml Ub-IP lysis buffer (50 mM Tris-HCL (pH 8.0), 150 mM NaCl, 5 mM EDTA, 1% NP-40, 0.5% Deoxycholate, 0.1% SDS, protease inhibitor cocktail (Roche), 1% (v/v) phosphatase inhibitor cocktail 3 (Sigma), 20µM MG132, 50µM PR619 and 100 mM N-ethylmaleimide (Sigma). Cells were lysed for 30 min at 4◦C with gentle end over end mixing. The lysate was clarified by centrifugation at 13,000 rpm for 20 min at 4◦C, and the supernatant transferred to fresh Eppendorfs. Protein concentration was calculated by the Bradford assay and protein concentrations normalized to 2 mg/ml. Typically 2 mg of protein was taken forward for TUBEs IP. Fifty ul of input fraction was heated with LDS/DTT and stored at −80◦C for later immunoblot. Samples were incubated with 40 µl TUBE1 agarose beads (LifeSensors), or control agarose beads (LifeSensors) for 4 h at 4◦C with gentle end over end mixing. The beads were then centrifuged at 3,000 g for 3 min and washed with lysis buffer containing all inhibitors three times (each wash was performed for 5 min at 4◦C with gentle end over end mixing), followed by two final washes with lysis buffer without SDS and Deoxycholate. Elution was then performed with 50 ul of pH 2.8 elution buffer (Pierce) for 30 min with gentle end over end mixing at 4◦C, followed by immediate neutralization with 1/10 volume 1 M Tris-HCL pH 9. Elution and neutralization was performed three times in total. Samples prepared for later MS analysis were frozen at −80◦C until further processing (100 of 150 µl total eluate). The remaining 50 µl, and all eluate from other experiments were heated with 2 × LDS/DTT at 70◦C for 10 min and stored at −80◦C until immunoblot.

### Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS)

100 µl of lysate was adjusted to 175 µl with ddH20. All samples were then successively reduced and alkylated for 30 min with 5 mM dithiothreitol and 20 mM iodoacetamide, respectively. The proteins were then precipitated using chloroform-methanol precipitation and the pellet were solubilized in 6 M urea, 0.1 M Tris pH 7.8. The sample were diluted to 1 M Urea. The digestion was performed overnight at 37◦C by adding 500 ng of trypsin. The peptides were desalted using a C18 cartridge (Waters). Briefly, the samples were conditioned with buffer A (1% (v/v) acetonitrile, 0.1% (v/v) trifluoroacetic acid (TFA) in water) prior to equilibration with buffer B (65% (v/v) acetonitrile, 0.1% (v/v) TFA in water). The acidified peptides were loaded onto the column, washed with buffer A and eluted with buffer B. The solution containing the peptides was dried with a speedvac and solubilised in 1% (v/v) acetonitrile, 0.1% (v/v) TFA in water for mass spectrometry analysis.

Peptides were analyzed with nano ultra-high performance liquid chromatography tandem mass spectrometry (nano-UPLC-MS/MS) using a Dionex Ultimate 3000 nanoUPLC, coupled to an Orbitrap Fusion Lumos mass spectrometer (Thermo Scientific). MS analysis was performed essentially as described previously (83). In brief, the data were acquired with a resolution of 120,000 full-width half maximum at mass/charge 200 with EASY-IC using the reagent ion source (202 m/z) for internal calibration enabled, Top speed precursor ion selection, Dynamic Exclusion of 60 s and fragmentation performed in Collision Induced dissociation (CID) mode with Collision Energy of 35.

### Analysis of Mass Spectrometry Data Label-Free Quantitative Analysis

The raw MS data was analyzed using Progenesis QI (Waters) and searched using Mascot 2.5 (Matrix Science). The search settings were as follows: trypsin with 1 miscleavage allowed, oxidation (M) and Deamidation (N, Q) were set as variable modifications and carbamidomethylation (C) as fixed modification. The data was searched against human protein sequences using the UPR\_homoSapiens\_20141015 (85,889 sequences; 33,866,397 residues) allowing a peptide mass tolerance of 10 ppm and a fragment mass tolerance of 0.05 Da.

### Peaks Search for Phosphorylation

The raw MS data was analyzed in PEAKS Studio 7.5 (Bioinformatics Solutions Inc). The settings were the following: The database used was the swissprot human database was used for the proteins identification. The enzyme used for the search was trypsin allowing a maximum of 2 miscleavages. Fixed modifications: Carbamidomethyl (C); Variable modifications: Deamidated (N), Deamidated (Q), Oxidation (M), Phospho (STY). Ten ppm mass tolerance were allowed for the precursor ions and 0.05 Da was allowed for the fragment ions.

### Mascot Search for Phosphorylation

The raw MS data was searched using Mascot with following settings. Enzyme: Trypsin; Fixed modifications: Carbamidomethyl (C); Variable modifications: Deamidated (N), Deamidated (Q), Oxidation (M), Phospho (ST), Phospho (Y); Peptide mass tolerance: ± 10 ppm (# 13C = 1); Fragment mass tolerance: ± 0.5 Da; Max missed cleavages: 1.

### shRNA Lentiviral Transduction and siRNA Transfection

Short hairpin RNA lentiviral particles were produced and transduced following the RNAi Consortium (TRC) protocols. ShRNA containing pLKO.1 vectors targeting NOD2 (SHCLND-NM\_022162), ataxin-3 (SHCLND-NM\_004993), TBK1 (SHCLND-NM\_013254) or non-Target shRNA Control Plasmid DNA were all obtained from Sigma (MISSION shRNA Plasmid DNA). In brief, HEK293T packaging cells growing in 6 cm well plate were transfected with a mix of 1 µg packaging vector (psPAX2), 0.4 µg envelope vector (pMD2.G) and 1.6 µg hairpin-pLKO.1 vector (SHC016 control or gene specific shRNA. Fugene-6 (Promega) was used as transfection reagent. Cell culture medium containing lentiviral particles (LVP) was collected 48 h later and passed through a 0.45µm filter (Sartorius). Virus preparations were then concentrated by centrifugation at 30,000 rpm for 90 min. Viral particles were added to cultured THP-1 cells in R10 [Roswell Park Memorial Institute medium (RPMI-1640) (Sigma) supplemented with 10% (v/v) heat-inactivated fetal calf serum (FCS) (Sigma), 2 mM (1% v/v) L-glutamine (Sigma)] together with 8µg/ml Polybrene (Sigma) to improve transfection efficiency. Following incubation for 3 h at 37◦C, the cells were harvested, washed, and resuspended at 1 × 106 cells/ml in R10 media with antibiotics including puromycin (as selective antibiotic). After 10 days of continuous selection with puromycin, knockdown efficiency was assessed by immunoblot. Transfection of human dendritic cells was performed by electroporation of SMARTpool ONTARGETplus human ataxin-3 (ATXN3) or non-targeting siRNAs (Dharmacon). Cells were resuspended in the solution provided with the kit (Invitrogen) followed by electroporation with Neon System kit (Invitrogen) using the following parameters: 1,475 V, 20 ms, 2 pulses. After 48 h, cells were harvested for use in experiments and to check knockdown by immunoblot.

### Adherent Cell Transfection

Human HEK293/NOD2 Cells were seeded 24 h prior to transfection in media without antibiotics. Transfection mixes were made, comprising Fugene (Promega) at a ratio of 3:1 to amount of DNA plasmid to be transfected, in the appropriate volume of Opti-MEM (Gibco, Thermo Fisher) (10% of volume of media in wells to be transfected). The transfection mixes were incubated at room temperature for 20 min and then added dropwise to the wells to be transfected. Cells were either cultured for a further 24 or 48 h before being used for downstream applications.

### RNA Isolation

Typically 2–5 × 106 cells per condition were harvested and washed once with cold PBS. Pellets were resuspended in 350 µl RLT buffer (Qiagen) containing 1% (v/v) Mercaptoethanol (Sigma) and stored at −80◦C. Samples were thawed on ice and homogenized by adding to Qiashredder columns (Qiagen) and centrifuged 2 min 13,000 rpm. RNA isolation was then peformed using RNeasy kits (Qiagen) according to manufacturer's instructions. The isolated RNA was eluted by added 25 µl nuclease free water (Ambion) to the RNeasy column membrane for 5 min, followed by centrifugation into fresh Eppendorfs 8,000 g 1 min. RNA concentration and purity were obtained using a Nanodrop 1000 spectrophotometer (Thermo Fisher) and samples were stored at −20◦C until further analysis.

### Reverse Transcription

RNA was reverse transcribed using a high capacity RNA to cDNA kit (Applied Biosystems). Five hundred ng to 2 µg of RNA was normalized to the same concentration for each sample using nuclease free water (Ambion) in polypropylene PCR tubes (Starlab). Then an RT mix containing 2 µl 10× RT buffer, 0.8 µl 25× dNTP mix, 2 µl RT random primers, 1 µl multiscribe RT, 1 µl RNase inhibitor (Applied Biosystems) and 3.2 µl nuclease free water was added to each PCR tube (10 µl total RT mix) (Starlab) for a total volume of RNA sample and RT mix of 20 µl. This was reverse transcribed using a Thermo Cycler (Applied Biosystems) with the program: 25◦C 10 min, 37◦C 120 min, 85◦C 5 min. The cDNA was stored at −20◦C.

### Quantitative Real Time Polymerase Chain Reaction (qPCR)

qPCR was performed using TaqMan chemistry (Applied Biosystems). cDNA was diluted 10-fold with nuclease free water. 4.5 µl of diluted cDNA was added in triplicate for each sample to wells of a white 0.2 ml 96 well PCR microplate (Starlab). 0.5 µl of TaqMan FAM-MGB labeled primer (Applied Biosystems) and 5 µl TaqMan Universal PCR Mastermix (Applied Biosystems) was added to each well, resulting in a 10 µl total reaction mix. The plate was covered with a polyolefin optical film (Starlab) and centrifuged at 400 g for 1 min. qPCR was then performed using the Bio-Rad C1000 Thermal cycler CFX Realtime system (Bio-Rad) using the manufacturer's recommended program: 50◦C 2 min, 95◦C 10 min, then 40 cycles of 95◦C 15 s, 60◦C 1 min. Mean cycle threshold (Ct) number was calculated from the triplicate values. Relative gene expression was calculated in comparison to the housekeeping RPLP0 control. The difference in gene expression between conditions was calculated using the 2 −11Ct. This is derived from:

1CT = CT(targetgene) − CT(control gene)

11CT = 1CT(targetcondition) − CT(control condition).

### Flow Cytometry

Typically 0.5 × 106 THP-1 cells per condition were plated in 1 ml of media in 12 well plates and differentiated for 16 h with 25 ng/ml PMA (Sigma). Following differentiation, the indicated treatments were applied. Cells were then harvested with gentle scraping and transferred to a FACS tube. The following staining protocols were then followed. Cytofluorometric evaluation was by the LSRII flow cytometer (BD Biosciences) with analysis of the data by FLOWJo.

### MitoSOX Red Staining

The cells were pelleted by centrifugation and resuspended in room temperature HBSS (Thermo Fisher) to wash, then centrifuged. The cells were resuspended in 200 µl MitoSOX red solution (final concentration 5µM MitoSOX red (Invitrogen) in HBSS) and incubated for 15 min in the 37◦C cell culture incubator. Two hundred µl of HBSS was added, and the tube centrifuged. The cells were resuspended in 250 µl HBSS and cytofluorometric evaluation performed.

### Dihydrorhodamine 123 (DHR) Staining

The cells were pelleted by centrifugation and resuspended in room temperature PBS to wash, then centrifuged. The cells were resuspended in 50 µl DHR solution (final concentration 2.5µg/ml DHR 123 (Invitrogen) in PBS) and incubated for 30 min at 37◦C in a water bath. As a positive control, 50 µl of PMA (final concentration 100 ng/ml (Sigma) in PBS) was added to control samples for the final 15 min. The cells were centrifuged and then washed once with PBS, before resuspension in 200 µl FACS staining buffer. Cells were fixed with the addition of 200 µl 1% PFA and cytofluorometric evaluation performed.

### Seahorse Mitochondrial Stress Assay

The Seahorse XFe96 Extracellular Flux Analyser was used to measure mitochondrial respiration and glycolysis (Seahorse Bioscience). Seahorse 96 well assay plates (Seahorse Bioscience) were coated with Cell-Tak suspension (Corning). THP-1 cells were seeded at 1.5 × 105 cells/well. Next, the optimal working concentrations of the compounds used for the mitochondrial stress test (oligomycin, FCCP and antimycin/rotenone) and the glycolysis stress test (oligomycin and 2-DG) were determined for THP-1 cells. The aim was to maximize the response to each compound with the lowest concentration possible. An XFe96 sensor cartridge (Seahorse) was hydrated overnight prior to Seahorse assays by adding 200 µl of XF calibrant solution to each well and incubating in a CO2 free incubator at 37◦C. The sensor cartridge (Seahorse) was loaded with the test drug compounds immediately prior to the assay and loaded on the Seahorse Analyser. Twenty-four h before the assay was run, cells were harvested, counted and resuspended at 1.88 × 106 cells/ml. Two ml of cell suspension was plated in 6 well plates for each condition, with or without the appropriate ligand stimulation for the required duration. On the day of the assay, 1 ml of cell suspension from each condition was harvested into 1.5 ml Eppendorf tubes. For the mito stress test, cells were resuspended in mito stress test media with or without ligand(s) (XF base media (Seahorse Bioscience) supplemented with 1 mM sodium pyruvate (Sigma), 5 mM glucose (Life Technologies) and 2% FCS (Sigma) adjusted to pH 7.4 at 37◦C and sterile filtered). Eighty µl of cell suspension (1.5 × 105 cells) was then seeded in quadruplicate for each condition and the plate was centrifuged at 200 g for 1 min. Following 30 min in a CO2 free incubator at 37◦C, 95 ul of fresh mito stress test media was added to each well, and after a further 15 min in a CO2 free incubator the assay was run. Final concentrations of injected drugs were 1µM oligomycin, 1µM FCCP, 0.3µM rotenone and 0.3 µM antimycin.

### STED Immunofluorescence Microscopy

Cells were plated in 8-well detachable tissue culture chambers on a PCA slide (Sarstedt) coated with 0.01% poly-l-lysine (Sigma) cells were at a density of 1–2 × 105 cell per well in 250 ul of appropriate media. At the end of the experiment, cells were washed twice with PBS, fixed with 4% paraformaldehyde (Sigma) for 15 min and permeabilized with 0.5% (v/v) Triton X-100 (Sigma). Cells were blocked overnight at 4◦C with 150 µl blocking solution per well (5% (v/v) human serum (Sigma), 5% (v/v) goat serum (Sigma), 5% (v/v) FCS (Sigma). The following day, cells were incubated with primary antibody diluted in 140 µl blocking solution at a pre-optimized or manufacturer recommended concentration for 1 h at room temperature. Following three washes with PBS (250 µl per well, 5 min gentle shaking), cells were incubated with the species appropriate fluorescently labeled secondary antibody for 1 h at room temperature. Cells were washed three further times with PBS, and the detached slide was then mounted with Vectashield mounting media containing DAPI (Vector Laboratories). Alternatively, cells were incubated with 200 µl PBS containing 1:100 DAPI (Thermo Fisher) for 15 min at room temperature and the detached slide was mounted with Vectashield mounting media without DAPI (Vector Laboratories). A Leica SP8 STED system was used for imaging. ImageJ was used for image processing and analysis.

### Bacterial Killing Assay

1 × 106 THP-1 cells were seeded per condition in 1 ml R10 without antibiotics in a 24 well plate, and differentiated overnight with 25 ng/ml PMA. After 16 h, the media was changed for 500 µl fresh R10 media without antibiotics. Two h later, Salmonella enterica serovar Typhimurium strain LT2 (ATCC 700220) was added at a multiplicity of infection (MOI) of 20:1. Thirty min post-infection, wells were washed twice with PBS and 500 µl fresh R10 supplemented with Gentamicin 100µg/ml was added. After a further thirty min, wells were washed once with PBS and 500 µl fresh R10 supplemented with Gentamicin 30µg/ml was added. At the end of the designated post-infection period, the medium was removed (and stored at −80◦C until later analysis by ELISA) and 500 µl of PBS with 1% (v/v) saponin was added to the wells, followed by incubation for 5 min at 37◦C. Five hundred µl of PBS was added and serial dilutions plated on LB/agar plates, incubated overnight at 37◦C, and colonies then counted.

### REFERENCES

Alternatively, when cell viability post-infection was assessed, cells were detached by incubating with 500 µl of trypsin per well for 5 min at 37◦C, then viability assessed by trypan blue staining (Invitrogen) and counting of live/dead cells.

### Statistical Analysis

Prism (GraphPad) was used to determine the statistical significance. When making multiple comparisons on a data set, analysis was by one-way ANOVA with post-hoc Bonferroni analysis. For experiments with two sample groups (one condition, one control) and a single comparison, analysis was by paired, two-tailed Student's t-test. Error bars represent Standard Error of the Mean (SEM).

### DATA AVAILABILITY

The MS proteomics data is available upon request from the authors.

### ETHICS STATEMENT

Ethical approval for the study was obtained from National Research Ethics Service (NRES) Sheffield Research Ethics Committee (REC reference: 16/YH/0247) and from West Midlands - The Black Country Research Ethics Committee (REC reference: 09/H1204/30).

### AUTHOR CONTRIBUTIONS

TC, DC, and AS designed experimental studies, interpreted the data, and wrote the manuscript. TC, DC, SS, SP, AA, SW, MdC, M-LT, RF, and BK performed experiments, acquired, and analyzed data. HP and BK provided critical reagents, helped interpret data. AS supervised and obtained funding.

### FUNDING

This work was supported by the UK MRC and by a Wellcome Investigator Award to AS, an NIHR Research Professorship to AS, and a Wellcome Clinical Training fellowship to TC. TC was also supported by the NIHR Biomedical Research Center, based at Oxford University Hospitals Trust, Oxford.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu. 2019.01495/full#supplementary-material

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Chapman, Corridoni, Shiraishi, Pandey, Aulicino, Wigfield, do Carmo Costa, Thézénas, Paulson, Fischer, Kessler and Simmons. This is an openaccess article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# NAD-Biosynthetic and Consuming Enzymes as Central Players of Metabolic Regulation of Innate and Adaptive Immune Responses in Cancer

Valentina Audrito1,2 \*, Antonella Managò1,2, Federica Gaudino1,2, Leonardo Sorci 3 , Vincenzo Gianluca Messana1,2, Nadia Raffaelli 4 and Silvia Deaglio1,2 \*

1 Department of Medical Sciences, University of Turin, Turin, Italy, 2 Italian Institute for Genomic Medicine, Turin, Italy, 3 Division of Bioinformatics and Biochemistry, Department of Materials, Environmental Sciences and Urban Planning, Polytechnic University of Marche, Ancona, Italy, 4 Department of Agricultural, Food and Environmental Sciences, Polytechnic University of Marche, Ancona, Italy

#### Edited by:

Anna Ohradanova-Repic, Medical University of Vienna, Austria

#### Reviewed by:

Armando A. Genazzani, University of Eastern Piedmont, Italy Antje Garten, Leipzig University, Germany

#### \*Correspondence:

Valentina Audrito<EMAIL_ADDRESS>Silvia Deaglio<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Cancer Immunity and Immunotherapy, a section of the journal Frontiers in Immunology

> Received: 25 April 2019 Accepted: 09 July 2019 Published: 25 July 2019

#### Citation:

Audrito V, Managò A, Gaudino F, Sorci L, Messana VG, Raffaelli N and Deaglio S (2019) NAD-Biosynthetic and Consuming Enzymes as Central Players of Metabolic Regulation of Innate and Adaptive Immune Responses in Cancer. Front. Immunol. 10:1720. doi: 10.3389/fimmu.2019.01720 Cancer cells, particularly in solid tumors, are surrounded by non-neoplastic elements, including endothelial and stromal cells, as well as cells of immune origin, which can support tumor growth by providing the right conditions. On the other hand, local hypoxia, and lack of nutrients induce tumor cells to reprogram their metabolism in order to survive, proliferate, and disseminate: the same conditions are also responsible for building a tumor-suppressive microenvironment. In addition to tumor cells, it is now well-recognized that metabolic rewiring occurs in all cellular components of the tumor microenvironment, affecting epigenetic regulation of gene expression and influencing differentiation/proliferation decisions of these cells. Nicotinamide adenine dinucleotide (NAD) is an essential co-factor for energy transduction in metabolic processes. It is also a key component of signaling pathways, through the regulation of NAD-consuming enzymes, including sirtuins and PARPs, which can affect DNA plasticity and accessibility. In addition, both NAD-biosynthetic and NAD-consuming enzymes can be present in the extracellular environment, adding a new layer of complexity to the system. In this review we will discuss the role of the "NADome" in the metabolic cross-talk between cancer and infiltrating immune cells, contributing to cancer growth and immune evasion, with an eye to therapeutic implications.

Keywords: immunometabolism, metabolic reprogramming, immune cell regulation, NAD, tumor microenvironment

### COMPOSITION OF THE TUMOR MICROENVIRONMENT: SUPPORTIVE AND IMMUNOREGULATORY CELLS

The solid tumor microenvironment (TME), as well as the lymphoid niche, is a dynamic and multicellular ecosystem with complex interactions (1, 2). Intercellular crosstalk within this niche is driven by multiple receptor-ligand systems, as well as by locally synthesized soluble proteins, including chemokines/cytokines, interleukins, interferons, growth, and angiogenic factors (3, 4). This unique environment is essential for tumor growth, metastatic dissemination, and drug-resistance. Furthermore, the cellular and soluble components of the TME have an important role in shaping metabolic reprogramming of cancer cells, an established hallmark of cancer, and in creating an immunosuppressive environment (5–8), as showed in **Figure 1**.

The formation of the TME and the regulation of immune responses are orchestrated by different types of host cells, including endothelial cells (ECs), mesenchymal stem/stromal cells [MSCs, including cancer-associated fibroblasts (CAFs) and tumor-associated MSCs (TA-MSCs)], and tumor-infiltrating immune cells [i.e., tumor-infiltrating lymphocytes (TILs), tumorassociated macrophages (TAMs), myeloid-derived suppressor cells (MDSCs), and tumor-associated neutrophils (TANs)]. Their concerted action promotes tumor growth and spreading (1, 2, 9, 10) (**Figure 1**).

### Endothelial Cells (ECs)

ECs support blood supply, nutrient transport, metabolic homeostasis, and immune cell trafficking, and are involved in inflammatory response (11).

To provide nutrients to the growing tumor, ECs form tumorassociated (angiogenic) vessels originating from locally preexisting vessels or recruiting bone marrow-derived endothelial progenitors. They also represent the first interface between circulating blood cells, tumor cells, and the extracellular matrix, thereby playing a central role in regulating leukocyte recruitment, tumor cell features, and metastasis dissemination (12). Tumorassociated EC are dysfunctional, partly as a consequence of local hypoxia, which induces the production of soluble factors promoting neo-angiogenesis and contributing to tumor dissemination and chemoresistance (13, 14). Among these factors, vascular endothelial growth factor A (VEGF-A) can also play a critical role in the control of immune tolerance, linking immune suppression with angiogenesis (15).

### Mesenchymal Stem/Stromal Cells (MSCs)

MSCs strongly affect the development and progression of various cancers (16). Stromal cells represent the main cell component with both supportive and immunoregulatory functions; they derived from multipotent cells of mesodermal origin which virtually reside in all tissues with an important role in tissue regeneration (16). MSCs have been found to migrate to tumors and to evolve into TA-MSCs and CAFs with an active role in tumor survival, proliferation, migration and drug resistance, and therefore, recently emerged as attractive targets or tools for anticancer approaches (17, 18).

CAFs are the most abundant resident cells of the TME. Numerous studies have demonstrated that CAFs have prominent roles in cancer pathogenesis (19, 20). Mechanistically, CAFs shape the extracellular matrix (ECM) structure, which supports the tumor cells (i) to invade and interact with stromal cells through the secretion of growth factors, cytokines and chemokines including interleukin-6 (IL-6), transforming growth factor-β (TGF-β) and CC-chemokine ligand 2 (CCL2); (ii) to amplify immune evasion recruiting immune cells, especially immunosuppressive cells into the tumor stroma; (iii) to promote the establishment of an intratumoral vascular network through proinflammatory and proangiogenic mediators (21). CAFs also activate epithelial-mesenchymal transition (EMT) in cancer cells, conferring their pro-invasive and stem-like features (22). In addition, CAFs are plastic cells that co-evolve with cancer cells and acquire a pro-tumor phenotype, contributing to tumor evolution (23). Due to the pro-tumor role of CAFs in support cancer development they become promising therapeutic targets for cancer therapy (21).

### Tumor-Infiltrating Lymphocytes (TILs)

TILs are additional immune components, crucial in driving immune responses within the TME, adding more complexity in the composition of the TME (3). TILs are white blood cells, including T and B cells, that have left the bloodstream and migrated toward a tumor or tissue resident (1, 24). Their abundance varies according to tumor type and stage and in some cases relates to disease prognosis, tumor progression, and response to anticancer therapy (1, 25, 26). T cell differentiation status, survival, activation or "stemness properties" are determining factors of antitumor potency (27) and functions of TILs dynamically change within the TME (28). Sometimes TILs, specifically cytotoxic CD8+ memory T cells and CD4+ T helper 1 (Th1), which are normally antigen "experienced," kill tumor cells (29), and the presence of lymphocytes in tumors is often associated with a better prognosis during immunotherapy treatment, including the adoptive transfer of naturally- TIL or genetically-engineered T cells and the use of immune-checkpoint inhibitors (26, 30). However, very often, during cancer progression and chronic inflammation, T cells become exhausted due to the persistent antigen exposure. T cell exhaustion is a state of T cell dysfunction defined by poor effector function, sustained expression of inhibitory receptors, such as programmed cell death protein 1 (PD1) and cytotoxic T lymphocyte antigen 4 (CTLA4), and transcriptional programs altered compared with functional effector or memory T cells (31).

Regulatory T (Treg) cells are another TME cell type that has immunosuppressive functions in cancer, inhibiting recognition, and clearance of tumor cells by the immune system (30, 32, 33). Tregs are characterized by the expression of CD4, CD25, and forkhead box P3 (FOXP3) as their master regulator. Foxp3þ Treg can originate in the thymus (naturally occurring Treg) or can be induced (iTreg) in the periphery by soluble cytokines and cell-cell contact (34) and are essential for maintaining peripheral tolerance and limiting auto-immune diseases. However, the proportions of Tregs are much higher in the circulation of patients with solid and hematologic malignancies and accumulation of Tregs in the tumor microenvironment is associated with disease progression and reduced survival (35, 36). From a functional point of view, Tregs inhibit both cellular and humoral immune responses by suppressing expansion and activation of conventional CD4+ and cytotoxic CD8+ T cells, and natural killer cells, mainly through the secretion of suppressive cytokines, such as TGF-β and IL-10. The development of agents that specifically inhibit Treg functions or remove them from the TME will permit new approaches for anticancer immunotherapy (37).

FIGURE 1 | The tumor microenvironment. A schematic view of the tumor microenvironment components. Established cancers are usually surrounded by a wide array of stromal cells and infiltrating immune cells of both innate and acquired immunity, such as MDSCs, macrophages, dendritic cells, neutrophils, NK cells, and lymphocytes. They form a complex regulatory network that supports tumor growth by creating a tolerogenic environment that enables cancers to evade immune surveillance and destruction. TAN, tumor-associated neutrophils; TAM, tumor-associated macrophages; MDSC, myeloid-derived suppressive cells; CAF, cancer-associated fibroblasts. Figure arrange using BioRender software https://biorender.com/.

### Tumor-Associated Macrophages (TAMs)

TAMs are important mediators of tumorigenesis, resident in the tissue or deriving from peripheral reservoirs such as the bone marrow (BM) and spleen (2). Macrophages are functionally plastic and can be polarized into the immune stimulating and antitumor M1 subtype, or into "alternatively activated" M2 macrophages producing type II cytokines, promoting antiinflammatory responses, and having pro-tumorigenic functions (38, 39). Macrophage polarization is finely tuned in response to different microenvironmental stimuli (40). For example, hypoxia may mediate this transition from tumor suppressing to tumor promoting macrophages (41). Furthermore, it has been shown a reciprocal regulation between CAFs and M2 macrophages: CAFs promote monocyte recruitment and polarization toward the M2 phenotype, leading to the enhancement of proangiogenic features, in parallel M2 macrophages are able to induce fibroblast activation (42). It is well-known that TAMs have a clear role in supporting multiple aspects of tumor progression (43). For example, TAMs promote tumor cell invasion through a paracrine loop that involves tumor-derived colony-stimulating factor 1 (CSF-1) and macrophage-derived epidermal growth factor (EGF) (43, 44). Moreover, TAMs induce immune suppression [reviewed in (45)] mediated by (i) expression of inhibitory receptors, including human leukocyte antigens (HLA)-E and HLA-G and T cell immune checkpoint ligands, such as PDL1, PDL2, CD80 and CD86, which directly inhibit T cell functions and NK cells; (ii) release of several cytokines, such as IL-10 and transforming growth factor-β (TGFβ), that contribute to feed a strong immunosuppressive microenvironment by inhibiting CD4+ (Th1 and Th2 cells) and CD8+ T cells and inducing Treg cell expansion and recruitment through CCL2, CCL3, and CCL20. Lastly, they induce depletion of essential amminoacids for cytotoxic activity of T cells including l-arginine and tryptophan, or production of kynurenine by indoleamine 2,3-dioxygenase (IDO) that inhibits T cell cytotoxicity.

Reversion of TAMs back to an M1 phenotype has also been reported (46), highlighting a potential therapeutic opportunity in which re-education of TME-resident macrophages might have beneficial anti-tumorigenic effects (45).

### Myeloid-Derived Suppressor Cells (MDSCs)

Along with TAMs, MDSCs are considered major promoters of tumor immune evasion (47). This population of myeloid cells, functionally defined as immunosuppressive, arises as a consequence of aberrant myelopoiesis typical of cancer (48). During tumorigenesis, MDSCs are mobilized from BM, via CXCR4/CXCL12 axis (49) and infiltrate tumors, where they promote tumor neoangiogenesis, producing endothelial growth factors [e.g., VEGF, basic fibroblast growth factor (bFGF)] (47). At the same time, they disrupt the major mechanisms of immunosurveillance, including antigen presentation by dendritic cells (DCs), T cell activation, M1 macrophage polarization and NK cell cytotoxicity, as reviewed in Safari et al. (50) and Wang et al. (51). Pharmacological inhibitors of CXCR4, are now under clinical investigation for the mobilization of immune and hematopoietic stem cells (52). Noteworthy, depletion of MDSCs by chemotherapeutic agents (e.g., gemcitabine, cyclophosphamide) can efficiently contribute to their anticancer action (48, 50, 53).

### Tumor-Associated Neutrophils (TANs)

More recently, a population of neutrophils, known as TANs, has been identified as tumor supporter promoting growth, invasion, and angiogenesis of cancer cells, although they have been classically considered to exhibit a defensive response against tumor cells. Like all other leukocytes, they migrate into tissues under the effect of specific chemokines, cytokines and cell adhesion molecules for example TGF-β and IL-8 induce the formation of a pro-tumorigenic (N2) phenotype capable of supporting tumor growth and suppressing the antitumor immune responses (54, 55). Accordingly, TGF-β blocking results in the recruitment and activation of TAN with an anti-tumor phenotype (54). The main tumor-promoting mechanisms of TANs include secretion of chemokines and/or cytokines, reactive oxygen species (ROS), and matrix-degrading proteinases, among others, conditioning tumor immune surveillance, metastasis, invasion, angiogenesis, and cellular proliferation (55, 56).

### TUMOR-STROMA METABOLIC CROSS-TALK IN TME

It has been shown that the environment surrounding tumor cells is characterized by low oxygen tension (i.e., hypoxia) due to the abnormal blood vessel formation, defective blood perfusion, and unlimited cancer cell proliferation (14). The progression of hypoxia over time is a consequence of increased oxygen consumption and high glycolytic rate of aberrantly proliferating cancer cells (aerobic glycolysis or Warburg metabolism), leading to lactate dehydrogenase (LDH) activity, lactate excretion and TME acidosis, which alters the tumor-stroma "metabolic cross-talk" (**Figure 1**). Vice versa, hypoxia rapidly fosters energy production in tumor cells via glycolysis through hypoxia-inducible factor 1-alpha (HIF-1α) mediated transcriptional control (57, 58). In addition, a hypoxic environment also modulates tumor-associated immune and stromal cells metabolism and fate. The rapid consumption of extracellular glucose and glutamine by tumor cells, especially in hypoxic conditions, leads to the accumulation of extracellular lactate, which was shown to affect several cell types within the TME (59). Increased lactate levels promote the insurance of an immune-permissive microenvironment by attenuating DCs and T cell activation, monocyte migration, and polarization of resident macrophages to TAMs (60–63). Furthermore, lactate accumulation promotes angiogenesis, stabilizes HIF-1α and activates NF-kB and PI-3 kinase signaling in endothelial cells, as well as inducing secretion of the proangiogenic factor VEGF from tumor-associated stromal cells (64–66). The secretion of lactate via the monocarboxylate transporter (MCT3) is coupled to the cotransport of H+, which supports acidification of the cellular microenvironment (59). The surplus of CO2 generated in mitochondrial decarboxylation reactions contributes to extracellular acidification as well (67). Then, a class of extracellular carbonic anhydrases (CA) can convert CO2 to H+ and HCO3−. Accordingly, expression of CAIX isoforms is elevated during hypoxia and can be considered a proxy for HIF-1α signaling (68). A consequence of increased extracellular acidification is the stimulation of the proteolytic activity of MMPs that promotes the degradation of the extracellular matrix components enhancing tumor invasion (69).

Lactate in TME can be also recycled, as occurs in the Cori cycle in the liver. In this reciprocal metabolite changes between cancer cells and immune/stromal cells, lactate produced under hypoxic conditions by glycolytic cells can be re-uptaken by aerobic cells, via MCT1, and utilized for mitochondrial tricarboxylic acid (TCA) cycle and oxidative phosphorylation (OXPHOS) (70, 71). This well characterized mechanism is known as the "reverse Warburg effect" (70, 72). In a model of epithelial cancer, tumor cells instruct the normal stroma to transform into a wound-healing stroma, providing the necessary energy-rich microenvironment for facilitating tumor growth and angiogenesis (72, 73). This metabolic cross-talk is evident in breast, prostate and ovarian cancer (74–76).

Both innate and adaptive immune cells increase their metabolic capacity upon stimulation, promoting energy generation, and biosynthesis supporting proliferation, effector molecule production, and differentiation (77). The impact of such altered metabolic state and levels of metabolites in TME on immune cell function is emerging. For example, a competition between tumor cells and T cells for the glucose pool in the aerobic microenvironment is linked to suppressed effector T-cell functions. In fact, activated T cells rely on glucose metabolism, up-regulating GLUT1 transporter via T cell receptor (TCR) and CD28-induced Akt activation (78, 79). Critical concentrations and/or lack of two amino acids, glutamine and arginine, necessary for T-cell activation, differentiation and proliferation, are therefore inhibitory to T cell functions (79).

The TME shows high levels of immunosuppressive metabolic byproducts, including a turnover in the TME release of adenosine triphosphate (ATP) and nicotinamide dinucleotide (NAD) which are metabolized by the ectoenzymes CD39, CD73, and the NADase CD38 to adenosine (80, 81). Adenosine binds to the T-cell adenosine A2R receptor inhibiting effector T-cell functions and stimulating Treg cells (82, 83). Furthermore, the adenosinergic axis is over-functional in hypoxic conditions, connecting adenosine-mediated immunesuppression to low oxygen tension (84, 85).

Overall, a better understanding of the critical players within the TME and their specific roles in immune regulation will help design of metabolism-targeted therapeutic strategies for improving immunotherapy regimens in cancer.

Recently, NAD pathway enzymes and metabolites were shown to affect immune-cell functions and fate and alter the cancer cell-TME crosstalk. The following paragraphs are focused on describing these molecular circuits and their therapeutic implications.

### NAD HOMEOSTASIS: AN OVERVIEW

NAD is a vital molecule governing many metabolic processes. It is used as a redox coenzyme by several dehydrogenases, and as a co-substrate by various NAD-consuming enzymes (86, 87). Among them are (i) mono- or poly-ADP ribosyltransferases (including ARTs and PARPs), which transfer the ADP ribose moiety to acceptor proteins resulting in their modification and function regulation, (ii) sirtuins, which catalyze the NADdependent deacetylation of metabolic enzymes and transcription factors, thus controlling their activity; (iii) NAD glycohydrolase that generates different NAD metabolites, including ADP ribose (ADPR), cyclic ADP ribose (cADPR) and nicotinic acid adenine dinucleotide phosphate (NAADP), with calcium (Ca+2 ) mobilizing activity. These enzymes are involved in the control of a wide range of biological processes, including transcription, DNA repair, cell adaptation to stress signals, and immune response (88). By catalyzing their reactions, they render NAD continuous re-synthesis an indispensable process. Various NAD biosynthetic routes guarantee the coenzyme regeneration, in different combination and with different efficiency depending on the cell-type and metabolic status (89, 90). A schematic overview of NAD homeostasis is shown in **Figure 2** and reviewed in Sharif et al. (87), Magni et al. (91), and Houtkooper et al. (92).

The route which recycles nicotinamide (Nam), produced by the breakage of the N-glyosidic bond in the various NADconsuming reactions, back to NAD that is considered the major pathway ensuring NAD homeostasis. It involves the phosphoribosylation of Nam to nicotinamide mononucleotide (NMN) by the enzyme Nam phosphoribosyltransferase (NAMPT) and the subsequent adenylation of NMN to NAD by NMN adenylyltransferase (NMNATs). This same route also salvages extracellular Nam that can be of dietary origin or can be formed in the extracellular space by the NAD glycohydrolase activity of the CD38 ectoenzyme acting on extracellular NAD and/or NMN. NAD can also be synthetized from exogenous nicotinamide riboside (NR) and nicotinic acid (NA) through distinct routes that are initiated by NR kinase (NRK) and NA phosphoribosyltransferase (NAPRT), respectively. The former enzyme phosphorylates NR to NMN, whereas the latter enzyme phosphoribosylates NA to nicotinate mononucleotide (NAMN). NMNATs convert NMN to NAD, and NAMN to nicotinate adenine dinucleotide (NAAD). NAAD is finally amidated to NAD by the enzyme NAD synthetase. A de novo biosynthetic route, which starts from tryptophan and enters the amidated route from NA, is also operative in several tissues and cell-types. The first and rate- limiting step in this pathway is the conversion of tryptophan to N-formylkynurenine by either IDO or tryptophan 2,3 -dioxygenase (TDO). Four reactions are then required to transform N-formylkynurenine to an unstable intermediate, α-amino-β-carboxymuconate-εsemialdehyde (ACMS), which undergoes either decarboxylation, directed toward oxidation, or spontaneous cyclization to quinolinic acid (QA) directed toward NAD formation. Indeed, QA is phosphoribosylated to NAMN by the enzyme QA phosphoribosyltransferase (QAPRT), and the formed NAMN enters the NA salvage pathway. Among the enzymes involved in NAD homeostasis, NAMPT, CD38, sirtuins, and IDO are overexpressed in different types of cancer (93) and have been shown to play a role in cancer immune tolerance (94, 95). In the following sections, we will review what is known about their expression and function in the TME.

### NAMPT IN METABOLIC REGULATION AND ACTIVATION OF MYELOID CELLS

As the first and rate-limiting enzyme, NAMPT plays a pivotal role in the biosynthesis pathway of NAD from its nicotinamide precursor. It converts Nam and 5-phosphoribosyl-1-pyrophosphate (PRPP) into NMN in a complex reaction that can be significantly improved by a non-stoichiometric ATP hydrolysis (96). NAMPT is found both intracellularly and extracellularly (97, 98). Intracellular NAMPT (iNAMPT) is primarily located in the nucleus and cytosol. Previous studies reported NAMPT in mitochondria as well (99), but this remains a controversial finding (100, 101). As one of the main regulators of NAD intracellular level, NAMPT plays a crucial role in cellular metabolism (102). Conversely, the extracellular form of NAMPT (eNAMPT) has emerged as an important mediator of inflammatory programs (103). eNAMPT has been found in plasma and other extracellular fluids, including the supernatants of numerous cell types (103); however, while the mechanisms behind eNAMPT secretion remain unknown, they do not seem to rely on the classic pathway (104). Notably, the cytokine-like functions appear independent of the protein catalytic activity (105). In keeping with this view, NAMPT's substrates PRPP and ATP are apparently unavailable in the extracellular space to sustain the enzymatic activity (106).

eNAMPT was originally found to be secreted by activated lymphocytes and bone marrow stromal cells by Samal et al. (107) and called pre-B-cell colony enhancing factor [PBEF (107). In 2005, Fukuhara (108) identified eNAMPT

as an adipokine and called it visfatin. These different names reflect its role in immune system and adipose tissue regulation.

Independent studies have conclusively shown that NAMPT expression and secretion can be induced by inflammatory signals in immune cells, in particular neutrophils, monocytes and macrophages (109). Both pathogen-derived lipopolysaccharide (LPS) and host-derived inflammatory stimuli, including tumor necrosis factor-α (TNF-α), IL-1β, IL-6, and leptin, can upregulate NAMPT transcription in macrophages and other several types of cells (110–113). Several studies showed stimulation of cytokine release after exposure of cells to exogenous NAMPT, highlighting a role of eNAMPT as an inflammatory mediator as reviewed in Garten et al. (103). Following NAMPT treatment, IL-1β, IL-6, TNF-α, and IL-10 are up-regulated in peripheral blood mononuclear cells (PBMCs) and CD14+ monocytes (114). Co-stimulatory molecules such as CD54, CD40, and CD80 are also up-regulated in response to NAMPT treatment, an effect mediated through PI3-kinase and MAPKs p38, MEK1, and JNK (114). Furthermore, in macrophages NAMPT increases MMPs expression and activity (115). In vitro, eNAMPT promotes cell survival in macrophages subjected to endoplasmic reticulum (ER) stress, a frequent event in obesity and obesity-associated diseases. eNAMPT induces IL-6 secretion, followed by IL-6 mediated autocrine/paracrine activation of the prosurvival signal transducer STAT3, with a mechanism that is independent of the enzymatic activity (112).

Emerging evidence supports a role of NAMPT in regulating the differentiation program and the metabolic adaptation of myeloid cells. As described previously, activated macrophages can be divided in two subgroups in vitro: those with proinflammatory activity (M1) involved in first line of defense against bacterial infection, and those with anti-inflammatory activity (M2) that regulate tissue repair and wound healing (116), even if this is an oversimplification of the functional diversity occurring in vivo. Metabolic reprogramming of immune cells is required for both pro- and anti-inflammatory responses and a vast spectrum of metabolic statuses accompanies the complexity of phenotypes [reviewed in (117, 118)]. In general, an increase in glycolysis and in glucose uptake is typically associated to an M1 phenotype (119), while M2 macrophages rely on intact TCA cycle and OXPHOS as major source of ATP via electron transport chain and ATP synthase (120, 121). However, in addition to an augmented mitochondrial metabolism, alternatively activated macrophages can also use glycolysis when OXPHOS is disrupted (122). Another important pathway is the pentose phosphate pathway (PPP), which generates pentoses, 5-ribose phosphate and nicotinamide adenine dinucleotide phosphate (NADPH). NADPH is essential in activated M1 macrophages because it fuels ROS production by NADPH oxidase (123), even if

other groups demonstrated that NADPH and NADPH oxidase play a role even in M2 differentiation (124). Concerning lipid metabolism, fatty acid synthesis is coupled to pro-inflammatory activity of macrophages, while beta-oxidation is typical of antiinflammatory macrophages (117).

The increase of glycolysis associated with M1 activation of macrophages is orchestrated by the transcription factor HIF-1α. When cells experience low oxygen levels HIF-1α is stabilized and, upon binding of the HIF-1β subunit, initiates the transcription of genes such as glucose transporter and glycolytic enzymes (125, 126). NF-kB is required for transcriptional activation of HIF-1α (127); whereas, in M2 macrophages, genes involved in metabolic reprogramming are largely controlled by STAT6 and peroxisome proliferator-activated receptor gamma coactivator-1 beta (PGC-1β) (128).

Both iNAMPT and eNAMPT influence fundamental monocyte/macrophages processes such as differentiation, polarization and migration, even if the exact role of iNAMPT/eNAMPT in the process of myelopoiesis is incompletely elucidated so far (129–131) as summarized in **Figure 3**. For example, NAMPT has a role in the induction of an immunosuppressive and tumor-promoting microenvironment in chronic lymphocytic leukemia, where eNAMPT is important for the differentiation of monocytes toward tumor-supporting immunosuppresive M2 macrophage, promoting their differentiation, and polarization in tumor-supportive cells including TAMs (130). Recently, it was demonstrated that iNAMPT acts also on MDSCs, where NAMPT inhibits CXCR4 transcription, via NAD/SIRT1/HIF-1α axis, and this, in turn, leads to a mobilization of MDSCs and enhances their production of suppressive nitric oxide (132).

Changes in NAD levels characterize different stage of macrophage polarization: in general, higher levels of NAD are typical of classically activated pro-inflammatory macrophages (M1), while NAD levels are lower in alternatively activated antiinflammatory macrophages (M2). The NAMPT/NAD/SIRT1 axis seems to play a relevant role in myeloid cell functions as shown by the fact that efficient activation of M1 macrophages needs an increase of both NAMPT expression and cytosolic NAD (133). NAMPT-dependent generation of NAD is also crucial in the metabolic switch characterizing the transition from the early initiation phase of acute inflammation, which is anabolic and primarily requires glycolysis, to the later adaptation phase which is catabolic and relies on fatty acid oxidation (FAO) for energy (134). During these processes, also NAD-consuming deacetylases enzymes SIRT1 and SIRT6 have a role in regulating metabolism, increasing fatty oxidation and reducing glycolysis, respectively, coupling metabolic polarity with the inflammatory response, as described with more details later (135, 136). These data support the notion that NAD homeostasis has a crucial role in connecting bioenergetics and inflammation (134). A further feedback loop that links NAD to polarization of myeloid component has been suggested in monocytes, where NAMPT expression is induced by TNF-α via HIF-1α. In turn, NAMPT signaling involving NF-kB pathway activates activating protein 1 (AP1), inducing IL6 and TNFA transcription modulating myeloid cell activation (137).

In congenital neutropenia, a disorder in which patients display accumulation of granulocytic progenitors and no mature neutrophils in bone marrow, it has been shown that granulocyte colony-stimulating factor (G-CSF) is effective as it up-regulates NAMPT, which in turn triggers NAD/SIRT1 dependent granulopoiesis via CCAAT/enhancer-binding protein α/β (C/EBPα/β) up-regulation (129). On the contrary, GM-CSF is not effective in congenital neutropenia because it is unable to activate iNAMPT upregulation and NAD/SIRT1 axis (138). Following the induction of myeloid differentiation with G-CSF, the NAD-consuming enzyme SIRT1 deacetylase C/EBPα at position Lys 161 (129, 138). NAMPT inhibition with FK866 led to the dramatic elevation of acetylated C/EBPα levels and reduced amounts of total C/EBPα protein, accompanied by diminished mRNA expression of C/EBPα target genes (G-CSF, G-CSFR, and ELANE). Moreover, treatment of acute myeloid leukemia cell line HL-60 with recombinant NAMPT or transduction of HL-60 cells with NAMPT-expressing lentiviral construct induced myeloid differentiation of these cells per sé (138).

An open question is whether the cytokine-like actions that eNAMPT exerts on myeloid cells are related to its enzymatic activity or are mediated by the binding to a cell surface receptor. The fact that treatment with low concentrations of recombinant eNAMPT is sufficient to activate specific intracellular signaling pathways suggests that eNAMPT has cytokine-like properties and binds to and activates a cell surface receptor. In 2015, Camp et al. identified eNAMPT as a new ligand of the Toll-like receptor 4 (TLR4) (105). The authors demonstrated that in human lung endothelial cells, eNAMPT activates an inflammatory response via activation of NF-kB signaling pathway by binding TLR4-MD2 (105). However, the fact that recombinant eNAMPT is often produced in E. Coli strains renders the interpretation of these results controversial for the possible contamination of LPS, the natural ligand of TLR4, and activator of inflammatory programs. New studies have to confirm the TLR4 engagement by eNAMPT and correlate this with myeloid differentiation and plasticity.

The evidence linking myeloid cell fate and NAD/NAMPT could open the way to pharmacological inhibition of either iNAMPT and/or eNAMPT for re-education of myeloid cells. This could be useful in the context of acute inflammation, but also in cancer to force a reversion of immunosuppressive microenvironment, in combination with immunotherapy, as summarized in **Figure 3**.

For iNAMPT specific small molecules inhibitors exist, most known FK866 (also known as APO866) and GMX1778 (also known as CHS-828), among others (**Table 1**) (139–143, 159– 161). However, most of the data on these drugs describe their effect on the tumor itself, and not on cells of the microenvironment (141, 161). Whether these inhibitors could also affect also eNAMPT activity is unknown, even if, as mentioned before, the enzymatic activity of eNAMPT is controversial. On the other hand, for eNAMPT, the group of Garcia, in order to block only the cytokine-like activity of eNAMPT, has devised a polyclonal eNAMPT neutralizing antibody (130, 144), that could be useful in those condition in which only the extracellular form of eNAMPT is detrimental and intracellular enzymatic activity needs to be preserved.

myeloid-derived suppressive cells.

### CD38 IN METABOLIC DYNAMICS OF T CELLS ACTIVATION

Cluster of differentiation (CD) protein CD38, first identified as a lymphocyte antigen, is a cell surface glycohydrolase that cleaves a glycosidic bond within NAD to yield Nam, ADPribose (ADPR), and cyclic ADPR (cADPR), and converts NAD phosphate (NADP) to NAADP, all calcium (Ca2+) mobilizing molecules (162, 163). These molecules bind specific receptors, like the ryanodine receptor on endoplasmic reticulum, the lysosomal two-pore channel and the plasma membrane calcium channel transient receptor (TRPM2), activating calcium signaling, which in turn affects gene expression, cell cycle control, cell survival, energy metabolism, leukocyte trafficking, and inflammation (87).

CD38 is a transmembrane protein with four different forms, according to the cellular localization (164). The most common form of CD38 has a type II membrane orientation, i.e., with the catalytic domain facing the extracellular space. By contrast, the less abundant type III transmembrane form has its catalytic site facing the inside. Intriguingly, soluble intracellular and extracellular forms of CD38 have also been ascribed (165, 166). CD38 is widely expressed both in immune cell types (bone marrow progenitors, natural killer cells, monocytes, and activated T- and B-lymphocytes) and in non-hematopoietic cells (167).

TABLE 1 | Pharmacologic tools currently undergoing pre- or clinical evaluation to block NADome enzymes.

I, inhibitor; T, solid and/or hematological tumors; IC, inflammatory conditions; MM, multiple myeloma; ALL, acute lymphoblastic leukemia; MD, metabolic diseases; ND, neurodegenerative diseases.

CD38 is also an unquestionable contributor to intracellular NAD homeostasis (168, 169) and this apparent "paradox" has been in part reconciled by recent reports demonstrating that CD38 can also degrade circulating NAD precursors such as NMN and NR, thus preventing their fueling of NAD biosynthesis (170, 171). Notably, CD38 enzymatic activity mediates many roles which include metabolism regulation and pathogenesis of heart disease, obesity, aging and inflammation, among the others. Nevertheless, it is well-established that CD38 overexpression is correlated to different hematological malignances including myelomas and leukemias (172). In this contest, a broad immune regulatory role for NAD and CD38 on T cell behavior has been reported (87, 145, 173) and summarized in **Figure 4**. In order to elucidate the impact of CD38 modulation of NAD homeostasis in T cell, a brief synthesis of T cell metabolism is necessary, as metabolism drives T cell life (36, 174, 175). One of the main challenges of the field in a translational perspective is to manipulate T cell metabolism in order to improve their immune response capacity. Defined metabolic pathways orchestrate T cell development, differentiation, function and persistence (176). TCA/OXPHOS-mediated ATP production is instrumental for the maturation of Naïve T (TN) lymphocytes, a population of quiescent non-proliferative cells, in primary lymphoid organs (177). T cell activation is initiated after antigen recognition and TCR ligation. This step, requiring major histocompatibility complex, and co-stimulatory molecules, activates T lymphocytes inducing both a rapid proliferation rate and a differentiation program toward effector functions (176). To sustain both clonal expansion and active immune response, T cells shift to an anabolic metabolism which provides faster ATP production and nutrients supply. While cytolytic CD8+ T (Tc) cells dominantly shift metabolism to glycolysis, activated CD4+ T helper (Th) cells increase both glycolysis and FAO (178). FAO also supports metabolism of iTreg and long living memory T-cell (Tm) (178). All these T cell subsets, to achieve their metabolic profile, require a coordinated transcriptional program together with a specific system of nutrient uptake. T cells depend on the import of substrates such as glucose, amino-acids (especially glutamine), and glycerol. In TN and Tm cells, increased expression of glucose and glutamine transporters is controlled by the transcription factor c-Myc (36) and regulated by a specific cytokine, IL-7 (175). AKT-mTOR and TLR signaling, as well as the transcription factors HIF-1α, c-Myc and FoxP3, have been shown to directly regulate Treg metabolic programming and development, while HIF-1α and mTOR control the glycolytic phenotype and activation (IFN-γ production) of effector T-cells, Th1, Th2, and Th17 lineages (36). Metabolism underpins T cell cycle through quiescence and activation states and T-cells failure to engage specific metabolic programs is a biological

of NAMPT available for continuous NAD regeneration. These reactions occur also in immune cells modifying NAD concentrations and affecting sirtuins activities. The NAD/CD38/SIRTUINS axis regulates T cell immune cell fate, metabolism, and gene transcription. Evidence of high CD38 expressing immune suppressive cells have been reported in several tumors. CD38 inhibition was sufficient to re-establish T cell proliferation, antitumor cytokine secretion, and killing capability. ADPR, ADP-ribose; cADPR, cyclic ADPR; NADP, NAD phosphate; NAADP, nicotinic acid adenine dinucleotide phosphate; Ca2+, calcium; NR, nicotinamide riboside; NMN, nicotinamide mononucleotide; Nam, nicotinamide; MDSC, myeloid-derived suppressive cells; PD-1, programmed cell death protein 1; PD-L1, PD-1 ligand.

phenomenon accompanying tumor aggressiveness and T cell exhaustions (176). The crosstalk between cancer cell and tumor TILs is played at different levels. As already mentioned, it has been shown that the establishments of nutrients competition between tumor cells and TILs has a primary role in influencing T cell fate and dysfunctions (34, 179–181). Malignant cells push their metabolism toward a Warburg phenotype. The consequent induction of a hypoxic and nutrient-deprived environment (low glucose, glutamine, glycine, and serine) shapes a tumor sustaining microenvironment and immune tolerance (179). Indeed, T cells migrating to tumors sites must adapt to both (i) nutrient-depleted environments (182) and contemporarily to (ii) the presence of hypoxic tumor-derived metabolites including lactate, adenosine, cyclic adenosine monophosphate (cAMP), IDO/kynurenine.

In this context, CD38-mediated Ca2+ mobilization can directly affect T cell metabolism. In the physiology of a T lymphocyte, Ca2+ controls T cell gene expression and consequently differentiation, development and cytotoxicity (183). Alteration of Ca2+ signaling affects immune deregulation and consequently tumor initiation and progression (183–186). A second level of T cell metabolic reprogramming control by the CD38/NAD axis also involves sirtuins (173). Indeed, a lot of literature has been produced on the role of SIRT1, as a key modulator of immune cell functions, as described in a dedicated section of this review (166, 187, 188). In this case, the inverse correlation between expression of CD38 and intracellular NAD contents, act on SIRT1-mediated post-transcriptional control of key genes involved in T cell functions (173). Furthermore, it was recently shown that CD38 is highly expressed by specific subsets of immunosuppressive TILs (i.e., Treg and Th17) (34, 36, 173, 189) and by MDSC, another key immunosuppressive cellular component of tumor milieu represented (190). Both, CD38highMDSC cells-mediated suppression of activated T-cells and the concomitant expression of CD38 with exhaustion markers on T cells, for example PD1, pointed to an active role of CD38 in modulating T cell metabolism and fate toward the generation of an immune tolerant landscape in tumor (173). Evidence of high CD38 expressing Treg have been reported for multiple myeloma and acute lymphoblastic leukemia, where the use of mAbs against CD38 (daratumumab, isatuximab, and MOR202, **Table 1**) is more than a promising therapeutic option to reestablish a functional immune surveillance (145– 147, 189, 191, 192). In these tumor models, suppression of CD38+ cancer cells associate with an increase in T-helper and cytotoxic T lymphocytes, T-cell functional response and TCR clonality (191, 192). A functional relationship between CD38 and Th17 has also been highlighted (173). Th17 is a CD4+ T cell subpopulation secreting IL17, which gained interest in the field of immunotherapy due to their self-renewal, plasticity and hematopoietic stem-like phenotype (173, 193). Adoptive T cell transfer (ACT) therapy is a powerful strategy developed for controlling cancer (194, 195). The emerged staminal potential of Th17, together with their ability to persist for long times at tumor sites, made of this T cell subset an ideal candidate to improve ACT efficacy (173, 196, 197). Chatterjee et al. recently demonstrated that, SIRT1-dependent deacetylation of the transcription factor forkhead box O1 (FOXO1) drives the functional homing in different organs of a hybrid Th1/Th17 population 24 h after ACT. Most importantly, they reported that, the decrease of CD38 expression on Th17 cells leads to the increase of intracellular NAD concentration, reinforcing the SIRT1-dependent immune efficacy of this T cell population (173). For these reasons, the inhibition of CD38 has been proposed not only to specifically target CD38high immune suppressive cell populations (MDSCs, Treg), but also to improve tumor control via ACT therapy or using immunomodulatory drugs (173, 191, 192).

Lastly, very recently CD38 was considered as major acquired mechanism of resistance to PD-1/PD-L1 blockade, causing CD8+ T cell suppression. Co-targeting of CD38 and PD-L1 improves anti-tumor immune response. CD38 manipulation was sufficient to regulate CD8+ T cell proliferation, antitumor cytokine secretion, and killing capability (198).

### SIRTUINS AND EPIGENETIC REGULATION OF IMMUNE RESPONSE

Sirtuins, initially described as transcriptional silencers in yeast (199), represent a class of NAD-dependent enzymes with deacetylase activity. So far, seven isoforms (SIRT1-7) constitute the family of mammalian sirtuins, which differ in subcellular compartmentation, enzymatic activity, and in vivo substrate selectivity (200). As a primary cellular location, SIRT1, SIRT6, and SIRT7 are found in the nucleus, SIRT2 in the cytoplasm, and SIRT3-SIRT5 in mitochondria (201). However, recent reports have shown that sirtuins are not anchored to precise subcellular compartments, and may shuttle between them, depending on cell type or physio-pathological conditions (202–205). The canonical reaction catalyzed by sirtuins is the transfer of an acetyl group from protein lysine residues to the ADPR moiety of NAD. As a result, the reaction produces Nam, first released, the deacetylated lysine, and 2'-O-acetyl-ADP ribose (206). Although lysine deacetylation is the primary activity of sirtuins, recent studies have shown that these enzymes can remove a variety of other acyl-lysine groups (207). Some sirtuins act as ADPribosyltransferases, although the biological relevance of such activity is incompletely understood. Mammalian sirtuins target different proteins in an isoform-specific fashion (207, 208), allowing their regulation of multiple processes like energy metabolism, epigenetic regulation of gene expression, DNA repair, inflammation, cellular stress resistance, healthy aging, tumorigenesis, autophagy, and apoptosis as reviewed in Haigis and Sinclair (208), Finkel et al. (209), and Houtkooper et al. (210).

Emerging evidence demonstrated that sirtuins are key regulators of inflammatory stress response in immune and non-immune cells (95, 211–213). Sirtuins are involved in epigenetic regulation, through deacetylation of histones and/or non-histone proteins, of metabolic, phenotypic, and bioenergetics reprogramming of immune cells (immuno-metabolism) (210, 212–214).

SIRT1 is the most extensively studied sirtuins, especially for its role in aging (210, 214). In addition, SIRT1 is involved in controlling stem cell development, cell differentiation and autophagy, metabolic reprogramming and inflammation (209, 215). SIRT1 is also the most studied among sirtuins involved in immune regulation and here we summarized some SIRT1 activities in epigenetic regulation of metabolism and immune response (**Figure 5**).

Epigenetic mechanisms are essential to the development and differentiation of the immune system, as well as in related pathologies (216–218). Epigenetic mechanisms include multilevel intracellular events that influence chromatin structure and gene expression such as histone methylation and acetylation, as well as DNA methylation, non-coding RNAs and chromatin remodeling (219). Further, numerous signals (i.e., TCR, TLRs, inhibitory receptors, and cytokines) drive changes in the epigenome that result in downstream modulation of immune responses (77). TLR signaling in macrophages regulates differentiation/polarization and activation in response to pathogens affecting gene expression and metabolic reprogramming (220, 221). In particular, TLR4 engagement by LPS in macrophages drives a shift toward a glycolytic metabolism impairing mitochondrial respiration (222), resulting in a marked shifts in NAD/NADH ratios, which influence the activities of SIRT1, potentially altering deacetylation of histone and non-histone substrates (134, 223). Liu et al. found in TLR4-stimulated THP-1 promonocytes that SIRT1 support a switch from increased glycolysis to increased FAO as early inflammation converts to late inflammation (134). The shift to late acute inflammation and elevated FAO required

block tumor progression. TLR4, Toll-like receptor 4; AMPK, AMP-activated protein kinase; HIF, Hypoxia-inducible factor; PD-1, programmed cell death protein 1;

CTLA-4, Cytotoxic T-Lymphocyte Antigen 4; TAM, tumor-associated macrophages; MDSC, myeloid-derived suppressive cells.

peroxisome proliferator-activated receptor gamma coactivator (PGC-1α),a known target of SIRT1 (187, 224–227). A circuit of AMP-activated protein kinase [(AMPK)/SIRT1/PGC-1α] results in the deacetylation and modulation of the activity of downstream SIRT1 targets that include the PGC-1α and the FOXO1 and FOXO3a transcription factors. The AMPK-induced SIRT1-mediated deacetylation of these targets explains many of the convergent biological effects of these two energy sensors, AMPK and SIRT1, on cellular metabolism (225, 226).

Recent studies have showed that the regulation of innate immunity and energy metabolism are connected through antagonistic crosstalk between NF-κB and SIRT1 signaling pathways (228). NF-κB signaling has a major role in innate immunity defense, while SIRT1 regulates the oxidative respiration and cellular survival (229). However, NF-κB activation can stimulate glycolysis during acute inflammation, whereas SIRT1 activation inhibits NF-κB signaling and enhances oxidative metabolism and the resolution of inflammation. SIRT1 inhibits NF-κB signaling directly by deacetylating the p65 subunit of NF-κB complex (230). SIRT1 stimulates oxidative energy production via the activation of AMPK, peroxisome proliferator activated receptor (PPARα) and PGC-1α and simultaneously, these factors inhibit NF-κB pathway and suppress inflammation (225, 226, 231). Using a myeloid cellspecific SIRT1 knockout (Mac-SIRT1 KO) mouse model, Schug et al. show that ablation of SIRT1 in macrophages renders NF-κB hyperacetylated, resulting in increased transcription of proinflammatory target genes. Consistent with increased proinflammatory gene expression, Mac-SIRT1 KO mice challenged with a high-fat diet display high levels of activated macrophages in liver and adipose tissue, predisposing the animals to development of systemic insulin resistance and metabolic derangement (232). In some cases, the effects of SIRT1 in regulating metabolism of immune cells are mediated by HIF-1α (233). SIRT1 can bind and deacetylate HIF-1α resulting in a stabilization or in an inhibition of the protein, depending on the cells and context (234, 235). The SIRT1-HIF-1α axis bridges the innate immune signal to an adaptive immune response by directing affecting metabolism, cytokines production, and differentiation of immune cells (236). For example, (i) SIRT1 can limit the function and differentiation of MDSCs through HIF-1α-induced glycolytic metabolic reprogramming (237), (ii) SIRT1 can regulate T helper 9 (Th9) cell differentiation through the mTOR/HIF-1α-dependent glycolytic pathway (238). The interplay between HIFs and sirtuins may also extend to stress settings such as hypoxic tumors, in which cellular redox balance is perturbed (64, 239).

For adaptive immune cells, SIRT1 has a key role in mediating the differentiation of T cell subsets in a NAD-dependent manner. T cells exhibit remarkable phenotypic and functional plasticity during immune responses (240). SIRT1 is involved in (i) Th and Treg cell differentiation (238, 241); (ii) SIRT1 signals in DCs can repress PPARγ activity and promote T helper 2 (Th2) cell responses in airway allergy through metabolismindependent manners (242); (iii) SIRT1 interacts with c- Jun and inhibits CD4 T cells to mediate T cell tolerance (243); (iv) SIRT1 regulates CD8 T-cell differentiation interacting with basic leucine zipper transcription factor ATF-like (BATF) and regulating both epigenetic remodeling and energy metabolism of T cells (244). Furthermore, (v) SIRT1/FOXO1 axis regulates metabolic reprogramming of terminally differentiated memory T cells, as previously described (188).

Finally, SIRT1 has been shown to play also important roles in physiological processes affecting organismal longevity as well as stem cell function and self-renewal (245, 246). In macrophages, SIRT1 is emerging as critical positive modulator of self-renewal, regulating G1/S transition, cell cycle progression and a network of self-renewal genes (247).

Similar functions in regulating inflammation and metabolism are exerted also by SIRT2 and SIRT6 (134, 213, 248).

Interactions of cellular metabolic and epigenetic pathways and how these two key biological processes interplay to feedback modulate immune cell function is attracting in cancer therapy. Sirtuins/NAD axis has proven to be a crucial link between epigenetics and metabolism, and hence, it is an important area of study for therapeutic implications (215). While there are only specific activators or inhibitors for SIRT1 exist, drugs that affect NAD levels or NAD precursors offer the possibility to regulate all seven sirtuins coordinately (239). These compounds can be used alone or in combination with existing cancer therapies. The effects of SIRT1 inhibitors (e.g., cambinol, sirtinol, tenovins, Ex-527, **Table 1**) are currently studied mainly in the context of cancer (239). Very recent data show the impact of SIRT1 inhibition or genetic deletion on T cell responses, particularly on Treg differentiation. Genetic deletion or pharmacologic inhibition of SIRT1 through EX-527 improves Foxp3+ Treg number and function through increased Foxp3 transcription its acetylation, leading to decreased Foxp3 turnover from ubiquitination and poly(ADP)ribosylation. As a result, targeting SIRT1 increases both central and inducible Foxp3+ Tregs and promotes their suppressive functions, as summarized in Chadha et al. (249). SIRT1 inhibition is therefore useful in the context of graft-vs. host disease (GVHD), to extend allograft survival (249–251). However, there are a number of studies in which SIRT1 deletion or inhibition led to proinflammatory conditions, indicating that regulation of the system is still incompletely understood (249, 252). Interestingly, the Nam generated in deacetylase reactions by SIRTs acts as a negative feedback regulator of SIRT activity (253, 254). This Nam is converted back to NAD by the action of NAMPT and NMNATs. Hence, NAD-biosynthetic enzymes, in particular NAMPT, also regulate sirtuins signaling (255) providing the rational to use NAMPT inhibitors to interfere with Sirtuins functions.

Overall these results indicate that sirtuins broadly coordinate innate and adaptive immune reprogramming and represent druggable immunometabolic enhancement targets, useful also to repolarize immune cells in TME.

### IMMUNOSUPPRESSION VIA TRYPTOPHAN CATABOLISM: THE ROLE OF KYNURENINE PATHWAY ENZYMES

Amino acid catabolism is a key effector in driving immune tolerance. IDO is a cytosolic, heme-dependent enzyme responsible for the rate-limiting step of de novo NAD synthesis from tryptophan in extrahepatic tissues. The catalyzed-reaction yields N-formylkynurenine and commits the aminoacid toward its conversion to QA through the kynurenine pathway (90), which accounts for >90% of tryptophan catabolism (256). Tryptophan is an essential amino acid in protein metabolism, a precursor for the synthesis of the neurotransmitter serotonin and tryptamine, as well as for the synthesis of NAD and the hormone melatonin (257, 258).

In recent years, IDO has drawn enormous attention due to its immune regulatory functions (259–261) and summarized in **Figure 6**. IDO is not constitutively expressed in immune cells. Rather, various stimuli, and signaling pathways induce transcription and translation of metabolically-active IDO enzyme protein. Among them, TLRs, tumor necrosis factor superfamily members (TNFRs), interferon beta receptor (IFNBR), the interferon gamma receptor (IFNGR), transforming growth factor beta receptors (TGFBRs) and the aryl hydrocarbon receptor (AhR) all can activate signaling mechanisms that either induce or maintain IDO expression. NF-KB activation is a central downstream signal of these pathways regulating IDO expression (262).

By catalyzing the initial and rate-limiting step of tryptophan degradation, IDO reduces the local tryptophan concentration and produces immune modulatory tryptophan metabolites (263). In particular, cells expressing IDO and TDO produce the tryptophan catabolite kynurenine that, by interacting with the aryl hydrocarbon receptor expressed by T cells, Tregs and DCs, regulates immunity (264). Additionally, inhibition of CD8+ Tcell-mediated cytotoxic function was found to be an important mechanism behind IDO's immune-modulating property (264). Due to the role in regulating T cell response and fate, IDO function is critical in organ and tissue graft survival, in viral infection, in tissue-specific autoimmunity and the promotion of cancer cell survival (265). The biologic function of the IDO pathway was originally described as both counter-regulatory

(controlling inflammation) and tolerogenic (creating acquired antigen-specific tolerance in T cells) (257).

T-Lymphocyte Antigen 4; Foxp3, forkhead box P3; TAM, tumor-associated macrophages; MDSC, myeloid-derived suppressive cells.

Escape from the immune response is essential for cancer progression, however, mechanisms underlying this process remain unclear. Kynurenine in the tumor microenvironment was recently shown to favor immunosuppression (265, 266). Tryptophan catabolism was shown to create an immunosuppressive milieu in tumors and in tumor-draining lymph nodes through accumulation and secretion of immunosuppressive tryptophan catabolites that bind and activate AhR (267), leading to induction of T-cell anergy, apoptosis, increased conversion of naïve CD4+ T cells into Tregs and polarization of DCs and macrophages toward an immunosuppressive phenotype (190, 261, 265, 268).

 In most studies, the ratio of kynurenine to tryptophan was measured in patient plasma as a measure of IDO and TDO activity (156, 267). Moreover, not only tumor can express IDO, but also immune cells including both TAM and MDSC express high levels of IDO, in response to inflammatory cytokines, of which IFN-γ is the most potent inducer, amplifying the circuit of immunosuppression (190, 271, 272).

According to the role of IDO in driving immunosuppression, in the last years IDO became a valid target in cancer therapy (273, 274). Competitive inhibitors of IDO are currently being tested in clinical trials in patients with solid cancer, with the aim of enhancing the efficacy of conventional chemotherapy, vaccine or checkpoint inhibitors (275). Agents currently account for the majority of the trials: indoximod (1-methyl-D-tryptophan), an inhibitor of the IDO pathway (155, 276), epacadostat (INCB024360) (156) and BMS-986205 (158) (**Table 1**), with encouraging results. Importantly, the use of IDO inhibitors can be also overcome the resistance to immunotherapies targeting immune checkpoints, strongly supporting the combination therapies with IDO inhibitors irrespective of IDO expression by the tumor cells (277). Additional IDO inhibitors are in the development pipeline, as well as agents that may target TDO, or a second isoform of IDO (IDO2) (275).

### CONCLUDING REMARKS

Anticancer strategies targeting simultaneously oncogenic and metabolic pathways, de-regulated in cancer cells, seem to be ideal and have shown some promising results. Interestingly, local conditions in the tumor microenvironment affect also metabolic responses of immune cells, favoring immunetolerance, and immune-escape mechanisms. One of the goals of immunotherapy could be to re-educate the immune system to kill tumors, by reprogramming their metabolism. The network

### REFERENCES

of immunosuppressive mechanisms in the TME is complex, multifactorial, and mutually reinforcing. A better knowledge of the main players of this cross-talk can help in designing more effective combination therapies. In this picture, NADmetabolizing enzymes are receiving increasing attention to due to their role in conditioning several aspects of immune cell fate and functions. It is foreseeable that modulators/inhibitors of the NADome (summarized in **Table 1**) will become useful alone or in combination with current anti-cancer therapeutic strategies to regulate both tumor growth and immune populations of TME.

### AUTHOR CONTRIBUTIONS

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

### FUNDING

This work was supported by the Italian Institute for Genomic Medicine Institutional funds, by Gilead Fellowship program 2018, by the Ministry of Education University and Research-MIUR, PRIN Project 2017CBNCYT and Progetto strategico di Eccellenza Dipartimentale #D15D18000410001 (the latter awarded to the Dept. of Medical Sciences, University of Turin) and ITN INTEGRATA program (grant agreeement 813284).

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Audrito, Managò, Gaudino, Sorci, Messana, Raffaelli and Deaglio. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Macrophage Rewiring by Nutrient Associated PI3K Dependent Pathways

#### Omar Sharif 1,2 \*, Julia Stefanie Brunner 1,2, Andrea Vogel 1,2 and Gernot Schabbauer 1,2 \*