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Macrophages preserve systemic self-tolerance and promote inflammation resolution and tissue repair through efferocytosis (Poon et al., 2014). In addition to the recognition and engulfment of dying cells, efferocytosis triggers the production of anti-inflammatory and tissue-reparative cytokines (Fadok et al., 1998) as well as inflammation-resolving bioactive lipids (Serhan and Savill, 2005). While these host-protective responses act in part through lipid-activated nuclear receptortranscription factors (A-Gonzalez et al., 2009), the signal transduction role of metabolites during efferocytic reprogramming is largely untested. This is likely important during syndromes of metabolite imbalance, where the anti-inflammatory potential of macrophages is often depressed and contributes to disease progression(Tabas and Glass, 2013).
It is now well appreciated that intracellular metabolism is integrated with the balance of cell activation. In macrophages, glycolysis is required for both pro-inflammatory polarization and the mobilizing of biosynthetic precursors to combat bacterial infection (Palsson-McDermott et al., 2015). Elevated glucose utilization is also necessary for alternative macrophage activation, the latter initiated by the cytokine interleukin-4 (IL-4) and further accompanied by increased oxidative phosphorylation (Huang et al., 2016). In the case of efferocytosis, biosynthetic precursors are in abundant supply within the phagocytic body, raising the prospect that apoptotic cell catabolism could provide substrates for macrophage reprogramming. Early studies of efferocytosis implicate cellular metabolism for the energetic currency that is necessary for actin-mediated engulfment of external bodies (Oren et al., 1963). Separately, mitochondrial uncoupling proteins (Park et al., 2011) and components of mitochondrial fission machinery (Wang et al., 2017) are necessary for multiple rounds of efferocytosis; this is of particular importance during tissue injury, which is characterized by heightened cell turnover. Taken together, these examples emphasize a conserved interplay between efferocytosis and cellular and mitochondrial metabolism; however, what is left unsolved is whether the catabolism of dying cells is integrated to the signature macrophage anti-inflammatory response.
To comprehend relationships between cellular metabolism, inflammation, and tissue repair, we report the metabolome of macrophages during efferocytosis. We implemented unbiased global metabolic pathway analyses to reveal a unique association between fatty acid oxidation (FAO), mitochondrial respiration, and inflammation during the catabolism of apoptotic cells. From our investigation, we discovered that efferocytosis significantly elevated long-chain fatty acid content in macrophages, activated the respiratory chain, and was required to stimulate a macrophage anti-inflammatory response through the generation of metabolic signaling intermediates, particularly NAD+. This non-canonical mitochondrial response was found to also be important during tissue injury, supporting its significance to the broad pathophysiology of wound healing.
Clearance of dying cells (efferocytosis) during tissue injury associates the metabolism of apoptotic cells by macrophages with gene expression of anti-inflammatory cytokines (Serhan and Savill, 2005). Surprisingly, the underlying metabolic relationships of efferocytosis to basic mechanisms of gene expression remain mysterious. To address potential connections, we first searched for in vivoevidence of metabolic polarization in tissue injury macrophages that were both anti-inflammatory and efferocytic. We employed myocardial infarction (MI) as a clinically relevant model of injury in which defects in efferocytosis lead to heart failure (Wan et al., 2013). To isolate efferocytes, we induced MI in transgenic MHC-Cre mCherry reporter mice. Using this previously validated approach (DeBerge et al., 2017), we could distinguish CD11b+Ly6c−Ly6g−F4/80+CD64+ macrophages that accumulated either high (HI) or low (LO) mCherry signal, consistent with efferocytosis of high versus low levels of injured cardiac cells, respectively. CD64+ mCherry-HI cardiac macrophages expressed heightened levels of the canonical anti-inflammatory cytokine Il-10 (Figure 1A), relative to their mCherry-LO counterparts. We further queried for unique signs of metabolic activation. Relative to tissue-sorted monocytes and neutrophils, Mɸs consumed more oxygen, and in particular, mCherry-HI (efferocytic) Mɸs (which also expressed Il-10) exhibited the highest oxygen consumption rate (OCR) (Figure 1B). This heightened OCR was not incompatible with the hypoxic stress that occurs during MI. For instance, we injected PIMOnidazole (Varia et al., 1998), which labels free sulfhydryls of hypoxic cells, and could identify both hypoxic (PIMO+) and non-hypoxic (PIMO−) cardiac Mɸs (Figure 1C), the majority of which were, interestingly, PIMO negative at 12 hr post MI. To test associations between hypoxia and efferocytic IL-10, we sorted PIMO+mCherry−, PIMO+mCherry+, PIMO−mCherry−, and PIMO−mCherry+ cardiac macrophages (Figure S1) and measured IL-10 gene expression by qPCR. PIMO−mCherry+ (non-hypoxic efferocytic) macrophages registered the highest IL-10 mRNA levels (Figure 1C), consistent with the notion that cardiac macrophages in areas of oxygen availability have the highest capacity to secrete IL-10. Thus, in a model where efferocytosis is necessary for both inflammation resolution and organ function (Howangyin et al., 2016, Wan et al., 2013), the anti-inflammatory polarization of efferocytic Mɸs directly coincided with heightened oxidative respiration.
To dig deeper into the cell-intrinsic relationships between efferocytic cellular metabolism and cytokine production, we modeled these events in culture. We elicited activated primary peritoneal macrophages. For apoptotic cells we chose human Jurkat T cells, which are standardized targets for macrophage co-cultivation(Fadok et al., 1998); this also permitted us to distinguish the gene expression response in a species-specific manner after RNA sequencing (see also STAR Methods). In culture, we began with a non-biased screen of secreted chemokinesand cytokines. This approach confirmed that apoptotic cells (Annexin V+, PI−) specifically and reproducibly induced macrophages to produce the canonical anti-inflammatory cytokine IL-10 (Fadok et al., 1998) (Figures 1D and 1E). This response was also validated with primary autologous apoptotic thymocytes and primary splenocytes (Figure 1F). Pro-reparative TGF-β was additionally induced after efferocytosis, as previously reported (Xiao et al., 2008) (Figure S2A), while pro-inflammatory TNF-α was suppressed (Figure S2B). Also induced was GM-CSF, which was recently shown to regulate leukocyte accumulation in heart (Anzai et al., 2017). The specificity of the efferocytic cytokine phenotype was underscored by cytokines that were not affected (Figure S2C). Unexpectedly, IL-9 (Figure S2A) and Eotaxin (Figure S2B), the former linked to T-regulatory cell function (Eller et al., 2011) and the latter to eosinophil responses, were also regulated by efferocytosis (Jose et al., 1994).
Consistent with our in vivo data, basal OCR was significantly elevated in Mɸs that were fed apoptotic cells (Figure 1G). This was in contrast to Mɸs co-cultivated with either live cells or inert polystyrene beads (Figure 1H). Remarkably, efferocytes exhibited heightened mitochondrial spare respiratory capacity, consistent with an elevated bioenergetics reserve, potentially provided by the introduction of exogenous metabolic substrates. Glycolytic extracellular acidification rate (ECAR) also trended higher during efferocytosis (Figure 1G); however, the ratio of OCR to ECAR was higher during apoptotic cell engulfment relative to non-efferocytes, consistent with a mitochondrial bias during efferocytosis.
A mitochondrial bias suggested a role for fatty acid utilization. To directly probe metabolic remodeling during efferocytosis, we performed unbiased liquid chromatography-tandem mass spectrometry (LC-MS/MS). Over 255 total biochemicals were altered with a p < 0.05, with 181 induced and 74 downregulated (Table S1). Unbiased analysis of the LC-MS/MS readings identified reproducible global changes in metabolites (Figure 2A and Table S1). Metabolite set enrichment analysis highlighted noteworthy escalations in long-chain free fatty acids as well as fatty acid metabolism (Figure 2B). Random forest analysis (Lunetta et al., 2004) revealed that lipid metabolites such as 3-hydroxybutyrylcarnitine, behenoylcarnitine, and arachidoylcarnitine were top enriched metabolites in efferocytes (Figure S3A). We further examined lipid metabolites that are involved in FAO. Long-chain fatty acids hexadecanedioate, myristoylglycerol, and linoleoylcarnitine were also increased in efferocytes. Furthermore, CPT substrate palmitoylcarnitine was also elevated (Figure 2C).
In separate experiments, in which we screened transcriptomic responses to efferocytosis, gene ontology enrichment analysis of canonical pathways from our mRNA-seq analysis revealed the most significantly mobilized pathways; these included mitochondrial electron transport (Figure 2D). Sequencing reads were aligned to murine gene annotation files to distinguish from human sequence (Alvey et al., 2017). Consistent with the metabolomics profile, we also validated that apoptotic cell stimulation of primary macrophages induced expression of genes involved in FAO, the electron transport chain, and oxidative phosphorylationpathways (Figure 2E). In line with these data, qPCR validation did not show contamination from apoptotic cell mRNAs, as control experiments in which apoptotic cells were co-cultivated with macrophages at 4°C did not phenocopy the efferocytosis gene signature. At first approximation, these parallel analyses of principal cytokine, transcriptional, and metabolic modules revealed an efferocytic signature that coupled anti-inflammatory cytokine production to fatty acid breakdown and mitochondrial metabolism.
Given the emphasis on fatty acids and the mitochondrion from our functional respiration and metabolite analyses, and given that apoptotic cells are a significant source of external lipid substrate, we hypothesized that apoptotic cells cultured with heightened fatty acids may additively fuel IL-10 production during their catabolismin phagocytes. To this point, we cultivated apoptotic cells with increasing concentrations of fatty acid-supplemented media to elevate fatty acid content(Spector et al., 1979), subsequently induced apoptosis, and overlaid normalized ratios of apoptotic cells to macrophages. Figure 3A demonstrates that levels of IL-10 secretion directly correlated with increasing doses of fatty acid supplementation; this was specific to IL-10, as TNF-α was not affected, as might be suspected under lipotoxicity. Evidence for fatty acid induction of IL-10 in T cells per se was not found (Figure S4A). To address if FAO is required for IL-10 generation in efferocytes, we initially added etomoxir (ETO) to target CPT1 enzymes involved in FAO (Carroll et al., 1978). We found that ETO reduced OCR in macrophages after efferocytosis (Figure 3B), as well as IL-10, but this was independent of TGF-β production (Figure 3C). However, recent findings indicate that ETO disrupts coenzyme A homeostasis (Divakaruni et al., 2018), and so we specifically targeted Cpt1 and Cpt2gene expression with siRNAs (Figure S6) and then found similar results (Figure 3D). Separately, previous reports elegantly described IL-4-induced macrophage polarization that required glucose utilization (Huang et al., 2016). Efferocytosis was distinctly characterized by the inability of glycolysis inhibitors to blunt IL-10 production (Figures 3E and 3F).
Consistent with a significant role of the mitochondrion during efferocytic IL-10 regulation, we interestingly documented evidence for spatial localization of mitochondria proximal to phagocytic cups (Figure S4B). Furthermore, elevations in oxygen consumption were consistent with heightened mitochondrial electron transport and mitochondrial oxidative phosphorylation, and the electron transport chain is coupled to mitochondrial FAO (Schönfeld et al., 2010, Wang et al., 2010). Electron transport is catalyzed in part by Rieske iron-sulfur protein, or RISP (Hartl et al., 1986). RISP has been newly implicated in activities beyond electron transport (Ansó et al., 2017); however, such a non-canonical role in macrophages is unclear and of unique significance to inflammation. To test the hypothesis that electron transport contributes to efferocytic anti-inflammatory polarization, we crossed Rispfl/fl mice (Waypa et al., 2013) with a myeloid and macrophage recombinase, LysMcre. Rispfl/fl LysMcre mice developed and matured to both normal body size and dietary intake and did not present with any significant sign of immuno-compromise. In primary macrophages, immunoblots confirmed reduction of RISP protein (Figure 4A). RISP is encoded by nuclear gene ubiquinol-cytochrome c reductase(Uqcrfs1), and the failure of RISP to be imported into the mitochondrial inner membrane did not overtly compromise macrophage mitochondrial morphology (Figure 4B). Risp-deficient macrophages also exhibited reduced oxygen consumption at baseline and a compensatory increase in glycolysis, as indicated by moderately elevated extracellular acidification (Figure 4C). Importantly, Risp-deficient macrophages were proficient at phagocytosis (Figure 4D). To test if Risp was required for anti-inflammatory efferocytic polarization, we measured IL-10 production. Supernatants from Risp-deficient macrophages exhibited clear reductions in IL-10 that were specific to efferocytosis (Figure 4E). This was not a generalized defect, as mutant macrophages were competent at producing pro-inflammatory cytokine TNF-α in response to LPS. To address potential off-target effects during cellular differentiation in germline Rispfl/fl LysMcre mice, we reproduced our findings after RNA silencing in mature macrophages (Figure 4F). We next targeted signaling that was downstream of apoptotic cell binding and added Antimycin A after apoptotic cell engulfment, which inhibits complex III activity (Rich, 1983). Figure 4G depicts that Antimycin A also led to IL-10 suppression. We independently corroborated these findings with a structurally dissimilar complex III inhibitor, myxothiazol (Figure 4H) (Ikeda et al., 1965). Although ATP in Risp-deficient macrophages was acutely reduced during efferocytosis, these levels quickly recovered (Figures S5A and S5B). Moreover, efferocytic IL-10 was not inhibited by interfering with mitochondrial membrane potential (Figure S5C). Separately, complex III and RISP are significant sources of mitochondrial reactive oxygen species (mROS) (Chandel et al., 2000). Efferocytic IL-10 was also not blocked with inhibitors of mROS, interestingly, in contrast to TGF-β (Figure S5D).
Metabolic rewiring alters the availability of functional metabolites that regulate macrophage function (Jha et al., 2015). Our nonbiased analysis of Risp deficiency during efferocyotsis revealed specific reductions in nicotinate and nicotinamidemetabolism. This included changes in NAD+ metabolites MNA and adenosine 5′-diphosphoribose (ADP-ribose) (Figure 5A), as well as aspartate, which is dependent on a suitable NAD+/NADH ratio within the malate-aspartate shuttle. Nicotinamide and quinolinate were not changed (Figure S3B). Focused pathway analyses corroborated an increased ratio of oxidized coenzyme nicotinamide adenine dinucleotide NAD+ to NADH in efferocytes, which was further reduced with Rispdeficiency (Figures 5B and 5C). Thus, aside from its role in metabolic redox reactions, we considered a novel role for NAD+ during efferocytic anti-inflammatory reprogramming. To test this, we added NAD+ precursor NMN to Rispfl/fl LysMcremacrophages during efferocytosis and found that NMN was sufficient to rescue IL-10 production (Figure 5D). Remarkably, NAD-dependent IL-10 was specific to efferocytosis, as NAD+ supplementation alone, in the absence of apoptotic cell feeding, did not lead to elevated IL-10.
Elevated NAD+/NADH ratios support the activity of sirtuin deacetylases (Tanner et al., 2000). We first investigated a role for SIRT2 given previous links to macrophage polarization and bacterial phagocytosis (Ciarlo et al., 2017); however, Sirt2-deficient phagocytes remained relatively competent at generating IL-10 after efferocytosis (Figure 6A). This was in contrast to Sirt1, which displayed elevated protein levels after efferocytosis (Figure 6B) and was also required relatively more than Sirt2 for IL-10 generation (Figure 6C). SIRT1 protein activity (Chatterjee et al., 2018) was reduced during efferocytosis under Risp deficiency (Figure 6D). Further, and as predicted from a temporal sequence in which NAD+ is upstream of SIRT1 protein activity, Sirt1-deficient macrophages were refractory to IL-10 rescue after supplementation with NAD+ precursor NMN (Figure 6E). To address mechanistic links to IL-10 gene regulation, we explored the role of the transcription factor Pbx-1, or pre-B cell leukemia transcription factor-1 (Pbx-1), which is required for IL-10 expression (Chung et al., 2007). To determine if the SIRT1-IL-10 axis involved Pbx-1, we performed chromatin immunoprecipitation (ChIP) for PBX-1 protein, during efferocytosis and also after knocking down Sirt1. Consistent with our hypothesis, Sirt1 deficiency reduced PBX-1 binding to the apoptotic cell response element of the IL-10 promoter (Figure 6F). Furthermore, in Risp-deficient macrophages, PBX1binding to the IL-10 promoter was reduced and partially rescued by NMN (Figure 6G). Pbx1-knockdown also abrogated efferocytic IL-10 (Figure 6H), as predicted (Chung et al., 2007). These data support the contention that efferocytic accumulations in NAD+ in turn signal through SIRT1 and PBX1 protein to induce IL-10 gene expression.
To address the in vivo significance of our findings, we examined Risp-dependent IL-10 in the aforementioned model of tissue injury requiring efferocytosis (Wan et al., 2013) and macrophage IL-10 polarization (Shiraishi et al., 2016) during MI. To isolate myocardial macrophages that were participating in efferocytosis, we induced MI in transgenic mCherry mice, described above, that specifically express red cardiomyocytes (Zhang et al., 2015). Double-positive CD64+ (macrophage) mCherry+ efferocytes exhibited heightened Risp-dependent OCR and expression of genes involved in oxidative phosphorylation (Figures 7A and 7B). In myeloid Risp-deficient mice, MI also led to acute mortality, with more than half of subjects succumbing to death between 4 and 7 days post MI (Figure 7C). Necropsy revealed increased myocardial rupture of the left ventricular free wall and evidence of hemothorax(Figure 7C). Importantly, increases in ventricular rupture were independent of macrophage accumulation, as cardiac flow cytometry revealed similar macrophage levels in the injured myocardium, preceding ventricular rupture (Figure 7D). Within cardiac extracts, IL-10 and TGF-β mRNA were greatly reduced (Figure 7E).
Phagocytosis has evolved beyond nutritional uptake to couple with the active synthesis of anti-inflammatory cytokines. An integration of immunity with nutrient sensing would permit efficient energy utilization during anabolic demand. Now, as cellular metabolism is appreciated to contribute to diverse cell functions beyond biosynthetic demand, less appreciated are the fundamental mechanisms to explain how metabolic intermediates participate in non-energetic signal transduction. Mitochondria facilitate immunologic function (Buck et al., 2017) and also act as platforms for superoxide signaling (Chandel et al., 2000, Tait and Green, 2012) and the generation of metabolites that regulate the epigenetic landscape (Jha et al., 2015). A unique aspect of efferocytic catabolism is the potential of metabolic substrates, derived from the apoptotic cell, to directly influence macrophage polarization. In this context, cellular imbalances of lipids and proteins during disease could particularly compromise the integrated metabolic response of macrophages to promote tissue repair.
Early in inflammation, acute-phase monocytes and macrophages are highly glycolytic, particularly under limiting oxygen tensions. Glycolytic remodeling is important for macrophage polarization (Haschemi et al., 2012). For example, macrophages that are in contact with Th2-derived cytokines such as IL-4 partially utilize glucose for alternative macrophage polarization (Huang et al., 2016). In our hands, the generation of anti-inflammatory IL-10 was not blocked by inhibitors of glycolysis (Figure 3), although extracellular acidification did trend higher during efferocytosis. One likely explanation is the abundant substrate supply provided by the apoptotic cell, which could preclude needs to mobilize metabolites that are pre-stored in the phagocyte. Relative to modest effects on glycolysis, OCR was significantly elevated during apoptotic cell metabolism, in comparison to that reported for IL-4, where macrophages may use internal lipid stores to fuel mitochondrial metabolism (Huang et al., 2014). IL-4 and apoptotic cells may work together to cooperatively program macrophages for tissue repair (Bosurgi et al., 2017), and it will be informative to examine if IL-4 modulates efferocytic mitochondrial activation.
Changes in macrophage metabolites from our nonbiased metabolomics during efferocytosis were both intuitive and less self-evident. For example, we are intrigued by efferocytic-associated escalations in sedoheptulose-7-phosphate (Table S1), which has separately been linked to macrophage polarization in connection with the pentose phosphate pathway/PPP (Haschemi et al., 2012). Studies that directly interfere (Köhler et al., 1970) with rate-limiting enzymes of this pathway during efferocytosis would be interesting to validate potential causal relationships of the PPP to cytokine signaling. Furthermore, consistent with increased lipid metabolism, efferocytosis led to accumulations of the monoacylglycerol 1-palmitoleoyl glycerol, which may be formed by lipases during the breakdown of triglycerides or diglycerides (Chandak et al., 2010). Efferocytes also accumulated dephosphocoenzyme A, a direct precursor of coenzyme A. In line with increased gene expression of TCA enzymes, TCA metabolites pyruvate, citrate, and α-ketoglutarate were reduced after apoptotic cell engulfment. Efferocytosis induced itaconate, which can inhibit the accumulation of proinflammatory succinate during endotoxin challenge (Lampropoulou et al., 2016). Levels of succinate trended lower in efferocytes (Table S1) but were not statistically different. Efferocytosis may also suppress the macrophage response to lipopolysaccharide/LPS (Fadok et al., 1998). It remains to be determined if efferocytic metabolites contribute to this suppression. Though the above changes represent just a snapshot of the dynamic flux occurring during efferocytosis, our global analysis provides a foundation from which to test other specific metabolic pathways.
In functional mitochondria, electron transport recycles mitochondrial NADH to NAD+. This occurs together with a secondary oxidation of cytosolic NADH alongside mitochondrial shuttles that transport reducing agents across mitochondrial membranes (Titov et al., 2016). Thus, mitochondrial NAD+ is coupled to NAD+/NADH balance in the cytosol. In macrophages, the synthesis of NAD+ by nicotinamide phosphoribosyl-transferase (NAMPT) promotes cytoskeletal activation during cellular adhesion (Venter et al., 2014). NAD+ accumulation in efferocytes required Risp, and additional reductions in nicotinate and nicotinamide are consistent with efferocytic regulation of the NAD+ pool. Decreases in NAD+/NADH ratio can also lead to increased 2-hydroxyglutarate (2-HG), and this imbalance can impair hematopoietic stem cell differentiation (Ansó et al., 2017). 2-HG, as well as α-ketoglutarate, are further linked to altered epigenetic methylation on key immunoregulatory genes (Liu et al., 2017). Though our preliminary analyses do not reveal significant Risp-dependent changes in 2-HG in the setting of efferocytosis, this does not discount the possibility that other mitochondrial-dependent epigenetic alterations may be functioning, and this is an interesting focus for future studies.
The integration of NAD+ with sirtuin histone deacetylases (Tanner et al., 2000) supports the concept of gene regulation by metabolic signaling. The seven sirtuin isoforms differ in both subcellular localization and function, and SIRT3, SIRT4, and SIRT5 localize to mitochondria (Kim et al., 2010). Given that SIRT1 is cytosolic in its localization, this suggests that alterations in the mitochondrial pool of NAD+ during efferocytosis also affect the cytosolic pool. SIRT1 has also been linked to LXR (Li et al., 2007), and LXR is known to regulate efferocytosis (A-Gonzalez et al., 2009). In skeletal cells, SIRT1 controls the transcription of peroxisome proliferator-activated receptor-gamma co-activator-1α (PGC-1α) (Amat et al., 2009), which separately has been linked to IL-10 induction (Morari et al., 2010) and oxidative metabolism in macrophages (Vats et al., 2006). Elevated oxygen consumption, in conjunction with requirements for SIRT1, also hints that increased mitochondrial biogenesis could in principle be a component of the efferocytic IL-10 response.
Our findings in heart support the physiologic relevance of our cellular working model (Figure S7, Working Model). Within the myocardium, efferocytosis is required to preserve ventricular systolic function after MI (Wan et al., 2013, Dehn and Thorp, 2017). Although MI creates an acutely ischemic microenvironment that dampens oxidative respiration, the resolving phase of inflammation accumulates non-hypoxic macrophages, some of which may generate IL-10 in the myocardium. The significance of Risp-dependent reductions in IL-10 or NAD in vivo may be tested by restoring IL-10 or NMN (Yamamoto et al., 2014) specifically in macrophages with mitochondria dysfunction and during tissue injury. IL-10 is a key protective factor in heart (Krishnamurthy et al., 2009), and its secretion is necessary for wound closure through activation of epithelial proliferation (Quiros et al., 2017). Risp was also required for efferocytic TGF-β, which contributes to early replacement fibrosis. Furthermore, it will be interesting to determine how pattern recognition receptor ligands released from necrotic cells during tissue injury could potentially rewire phagocyte metabolic bias (Krawczyk et al., 2010).
A caveat to our findings in heart is that LysMcre may be expressed in certain non-macrophage cells, such as the neutrophil. Neutrophil lipolysis and FAO were recently linked to cellular autophagy, differentiation, and inflammation (Riffelmacher et al., 2017). However, in our hands, LysMcre deletion of Risp did not alter cardiac neutrophil accumulation (Figure 7). Additional aspects of our working model warrant future study. For example, potential signaling axes between apoptotic cell receptors and the mitochondria remain to be fully elucidated. In this context, receptor-mediated signal transduction could cooperatively amplify the mitochondrial response during efferocytosis. In addition, the electron transport chain may function during other core macrophage functions. This includes phagocyte recruitment, phagocyte proliferation and survival, and antigen presentation. In the setting of disease, it will be important to elucidate just how varied metabolite composition contributes to macrophage function and NAD+generation, such as during cardiometabolic pathophysiology. For example, atherosclerotic progression is characterized by the turnover and pro-inflammatory phagocytosis of cholesterol-laden foam cells and cholesterol crystals (Hansson et al., 2015). Carbon tracing during metabolite flux from apoptotic foam cells to phagocyte has the potential to implicate additional unique immunometabolic cues that may fuel these nonresolving inflammatory disorders. These molecular pathways may also be relevant to pathologies where natural somatic mitochondrial mutations contribute to mitochondrial dysfunction.
REAGENT or RESOURCE | SOURCE | IDENTIFIER |
---|---|---|
Antibodies | ||
Pbx-1 | Thermo Fisher | Cat# PA5-17223, RRID:AB_10980993 |
Risp | Abcam | Cat# Ab14746, RRID:AB_301445 |
Sirt1 | Abcam | Cat# Ab110304, RRID:AB_10864359 |
Cpt1 | Abcam | Cat# Ab234111 |
Cpt2 | Thermo Fisher | Cat# PA5-19222, RRID:AB_10984377 |
APC anti-mouse Ly-6C | BioLegend | Cat# 128015, RRID:AB_1732087 |
PerCP anti-mouse Ly-6G | BioLegend | Cat# 127653, RRID:AB_2616998 |
PE/Cy7 anti-mouse F4/80 | BioLegend | Cat# 123113, RRID:AB_893490 |
APC/Cy7 anti-mouse/human CD11b | BioLegend | Cat# 101225, RRID:AB_830641 |
Brilliant Violet 421 anti-mouse CD64 | BioLegend | Cat# 139309, RRID:AB_2562694 |
Chemicals, Peptides, and Recombinant Proteins | ||
Etomoxir | Sigma-Aldrich | Cat# E1905, CAS: 828934-41-4 |
Oligomycin | Sigma-Aldrich | Cat# 75351-5MG, CAS: 1404-19-9 |
Rotenone | Sigma-Aldrich | Cat# R8875, CAS: 83-79-4 |
Antimycin A | Sigma-Aldrich | Cat# A8674, CAS: 1397-94-0 |
FCCP | Sigma-Aldrich | Cat# C2920-10MG, CAS: 370-86-5 |
UK5099 | Sigma-Aldrich | Cat#PZ0160, CAS: 56396-35-1 |
Fatty acid supplement | Sigma-Aldrich | Cat# F7050-5ML |
Beta-nicotinamide mononucleotide | Sigma-Aldrich | Cat# N3501-100MG, CAS: 1094-61-7 |
Brewer thioglycollate medium | Sigma-Aldrich | Cat# B2551-500 g |
Critical Commercial Assays | ||
Mouse IL-10 ELISA Set | BD Biosciences | 555252 |
Mouse TNF ELISA Set | BD Biosciences | 555268 |
NAD/NADH Assay Kit | Abcam | Ab65348 |
SIRT activity assay kit | Abcam | Ab156065 |
Hypoxyprobe Plus Kit | Hypoxyprobe Inc | HP2-100Kit |
Chromatin Immunoprecipitation Assay | Millipore Sigma | 17-295 |
ATP Assay Kit | Abcam | Ab83355 |
TruSeq Stranded mRNA LT sample prep Kit | Illumina | RS-122-2101 |
Bio-Plex Pro Mouseu Cytokine 23-plex | Bio Rad | M60009RDPD |
Deposited Data | ||
RNA-seq | This paper | GEO: GSE121681 |
Experimental Models: Cell Lines | ||
Jurkat cells | ATCC | Cat# CRL-8131, RRID:CVCL_U323 |
Experimental Models: Organisms/Strains | ||
Rispflox/flox mice | Dr. Schumacker | PMID: 23328522 |
C57BL/6J mice | The Jackson Lab | RRID: IMSR_JAX:000664 |
LysmCre mice | The Jackson Lab | Stock No: 004781 |
Myh6-mCherry mice | The Jackson Lab | Stock No: 021577 |
Oligonucleotides | ||
Acadm-F GGATGACGGAGCAGCCAATG Acadm-R ATACTCGTCACCCTTCTTCT | This paper | N/A |
Acadvl-F TATCTCTGCCCAGCGACTTT Acadvl-R TGGGTATGGGAACACCTGAT | This paper | N/A |
β-actin-F TCCATCATGAAGTGTGACGT β-actin-R TACTCCTGCTTGCTGATCCAC | This paper | N/A |
CD36-F GAGGCATTCTCATGCCAGT CD36-R ACGTCATCTGGGTTTTGCAC | This paper | N/A |
CPT1a-F TGCTTTACAGGCGCAAACTG CPT1a-R GCAGATGTGTCAGGACCGAGT | This paper | N/A |
Dlat-F TCCTGCAGGTGTCTTCACAG Dlat-R GACGGAGATTTTCCCTTTCC | This paper | N/A |
FABP4-F GGATTTGGTCACCATCCGGT FABP4-R TTCCATCCCACTTCTGCACC | This paper | N/A |
FH1-F AGCAATGCATATTGCTGCTG FH1-R CGCATACTGGACTTGCTGAA | This paper | N/A |
IDH3b-F GTTTTTGAGACGGGTGCTCG IDH3b-R TCCCATGTCTCGAGTCCGTA | This paper | N/A |
IL1b-F TACGGACCCCAAAAGATGA IL1b-R TGCTGCTGCGAGATTTGAAG | This paper | N/A |
IL6-F TAGTCCTTCCTACCCCAATTTCC IL6-R TTGGTCCTTAGCCACTCCTTC | This paper | N/A |
IL-10-F ATAACTGCACCCACTTCCCA IL-10-R GGGCATCACTTCTACCAGGT | This paper | N/A |
MDH1-F GAAGCCCTGAAAGACGACAG MDH1-R TCGACACGAACTCTCCCTCT | This paper | N/A |
Mmp9-F CAAGTGGGACCATCATAACATCA Mmp9-R GATCATGTCTCGCGGCAAGT | This paper | N/A |
PDHB-F TCGAAGCCATAGAAGCCAGT PDHB-R AGGCATAGGGACATCAGCAC | This paper | N/A |
Tnfa-F ACGGCATGGATCTCAAAGAC Tnfa-R AGATAGCAAATCGGCTGACG | This paper | N/A |
CHIP pbx binding region-F TTTTCTACCAGCAGCAAGCA CHIP pbx binding region-R ATGCTAGCTGGGTCTTGAGC | This paper | N/A |
CHIP CTRL-F TTCCCTAGGATCAGGGAGGT CHIP CTRL-R AATGGGCCTCTCTTTCCAGT | This paper | N/A |
Recombinant DNA | ||
FlexiTube siRNA risp | QIAGEN | Cat No: GS66694 |
FlexiTube siRNA SIRT1 | QIAGEN | Cat No: GS93759 |
FlexiTube siRNA Pbx1 | QIAGEN | Cat No: GS18514 |
FlexiTube siRNA Cpt1a | QIAGEN | Cat No: GS12894 |
FlexiTube siRNA Cpt2 | QIAGEN | Cat No: GS12896 |
Software and Algorithms | ||
FlowJo X 10.0.7r2 | FlowJo | https://www.flowjo.com/ |
Prism 7 | GraphPad | https://www.graphpad.com/ |
Further information and requests for resources and reagents should be directed to and will be fulfilled by the first author Shuang Zhang, shuangzhang2017@u.northwestern.edu.
C57BL/6J mice were bred in our facility and our colonies are refreshed yearly with mice purchased from the Jackson Laboratory. LysmCre mice were purchased from the Jackson Laboratory and bred in house. Uqcrfs1; RISPfl/fl mice were provided by Dr. Paul Schumacker and was generated as described (Waypa et al., 2013). αMHC-mCherry mice were obtained from the Jackson Laboratory. Ten- to sixteen-week-old mice were used for experiments. Investigators were not blinded to the group allocation for some studies. Mice were housed in temperature- and humidity-controlled environments and kept on a 12:12h day/night cycle with access to standard mouse chow and water ad libitum. All studies were approved and reviewed by the Institutional Animal Care and Use Committee at Northwestern University (Chicago, Illinois), protocol #IS00000375.
For experimental MI: Surgeries were performed on mice 12-16 weeks of age and as described (Wan et al., 2013). Surgeries were performed by an individual blinded to the genotype. Mice were anesthetized with Avertin and secured in a supine positionand endotracheal-intubated and ventilated with an Inspira Advanced Safety Single Animal Pressure/Volume Controlled Ventilator (Harvard Apparatus, Holliston, MA) with room air supplemented with oxygen to maintain blood gases within normal physiological limits. The chest wall was shaved and left thoracotomy was performed. With the aid of a dissecting microscope, the left ventricle was visualized and left coronary artery on the anterior wall was permanently ligated with monofilament nylon 8-0 sutures (Ethicon, Somerville, NJ) 2mm distal to the site of its emergence from under the left atrium. Blanching/pale discoloration and hypokinesis of the anterior wall verified LAD ligation. The chest wall was closed with 7-0 nylon sutures and the skin and subcutaneous tissue was closed. Sham operations were performed on animals by passing the suture beneath the LAD without ligating the vessel.
Peritoneal macrophages were elicited in mice with thioglycollate broth (Sigma-Aldrich) and harvested after lavage. Adherent macrophages were co-cultivated with apoptotic Jurkat T cells. Tcells were induced to apoptosis after ultravioliet irradiation and early apoptotic cells (ACs) were identified as annexin V positive, propidium iodide negative, and overlaid at a ratio of 5 ACs to 1 phagocyte. Non-engulfed Tcells were removed from adherent phagocytes, 1 hr post co-cultivation. Engulfment was confirmed by microscopic and flow cytometric analysis with fluorescently labeled apoptotic cells.
Cell culture supernatant was collected 5 hr post co-cultivation. Chemokines and cytokines were analyzed with a Bio-Plex Pro Mouse cytokine 23-plex from Bio Rad using a Luminex 200 multiplex instrument (Luminex, Austin, TX) and MAGPIX analysis. Additional cytokines, including IL-10, were validated by independent ELISA. For IL-1β measurements, 5mM ATP was added 3 hr after LPS stimulation.
Adherent peritoneal macrophages were stimulated with apoptotic thymocytes for 6 hr, versus control. RNA was isolated from cells with Trizol and RNA quality assessed at the Northwestern Genomics core with RNA integrity values of 10 for a minimum of 100 ng per sample. Library construction was performed in lab and sequencing was performed at the Genomics Core facility at the University of Chicago and Northwestern University. Sequencing libraries were constructed using an Illumina TruSeq Stranded mRNA prep kit LT for mRNA sequencing and constructs sequenced on NextSeq 500 instrument and HiSeq 2500 System from Illumina. For RNaseq, the quality of DNA reads, in FASTQ format, was evaluated using FastQC. Adapters were trimmed and reads were aligned to the Mus musculusgenome (mm10) using STAR (Dobin et al., 2013). Read counts for each gene were calculated using HTSeq-count in conjunction with a gene annotation file for mm10 obtained from University of California Santa Cruz at genome.ucsc.edu. Normalization and differential expression were determined using DESeq2. The cutoff for determining significantly differentially expressed genes was an FDR-adjusted p value less than 0.05. Transcriptome analysis was performed at the bioinformatics core at Northwestern University with assistance from Matthew Schipma, PhD.
Metabolomics analyses were carried out in with Metabolon (Durham, NC) as previously described (Evans et al., 2009, Masri et al., 2014) and with the University of Michigan Metabolomics Core. Briefly, control and Risp-deficient peritoneal macrophages were treated as indicated. Cell lysates were harvested, methanol extracted, and analyzed by ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS; positive mode), UPLC-MS/MS (negative mode) and gas chromatography–mass spectrometry (GC-MS). Metabolites were identified by automated comparison of the ion features in the experimental samples to a reference library of chemical standard entries that included retention time, molecular weight (m/z), preferred adducts, and in-source fragments as well as associated MS spectra, and curated by visual inspection for quality control. These data are listed in Table S1.
To measure the extracellular acidification rate (ECAR) and OCR, apoptotic cell-treated primary macrophages were plated on an XF24 cell culture microplates coated with CellTak. Experiments were conducted in XF assay medium containing 25 mM glucose, 2 mM L-glutamine, and 1 mM Na pyruvate, and analyzed using a Seahorse XF24 extracellular flux analyzer (Agilent Technologies). Where indicated, the following were injected: ATP-synthesis inhibitor oligomycin (1.5 μM), carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone (FCCP; 1.5 μM) to uncouple ATP synthesis, rotenone (100 nM) to block complex I, and antimycin A (1 μM) (Sigma) to block complex III. Basal ECAR, OCR, and spare respiratory capacity were generated by Wave Desktop software (Agilent Technologies).
Macrophages were cultured on sterilized Thermanox plastic coverslips and cultivated with apoptotic cells. Subsequently, coverslip were fixed with 0.1 M sodium cacodylate buffer (pH 7.3) containing 2% paraformaldehyde and 2.5% glutaraldehyde for 30 min at room temperature and were kept at 4°C and then processed for TEM. Coverslips were flat-embedded in resin and cured in a 60°C oven. Samples were sectioned on a Leica Ultracut UC6 ultramicrotome into 70nm sections and collected on 200 mesh copper grids. Samples were processed and imaged on an FEI Tecnai Spirit G2 TEM at the Advantaged Imaging Center at Feinberg School of Medicine with assistance from Lennell Reynolds Jr.
Whole cell extract was isolated from macrophages treated with or without apoptotic cells. Pbx-1 binding to chromatin was pulled down via chromatin immunoprecipitation. In brief, chromatin was sonicated into 200-1000 bp following crosslinking. After overnight incubation with isotype IgG or PBX-1 antibody, 100ul of protein A beads was added into the solution and incubated for 1hr at 4C. The protein-bound beads were collected, DNA was eluted and reverse cross-linked. DNA was recovered by phenol/chloroform extraction and ethanol precipitation.
Cells were lysed in RIPA buffer, resolved on 10% polyacrylamide gels and transferred to nitrocellulose membranes. Membranes were blocked using 5% milk and then incubated in the primary antibody overnight. Antibodies were anti-RISP, anti-SIRT1, anti-CPT1A, anti-CPT2, and anti-α-tubulin. Membranes were rinsed 3 times with tween solution and then incubated with secondary antibody. Secondary antibodies utilized were anti-mouse IgG, HRP-linked and anti-rabbit IgG, HRP-linked.
Chromatin for chromatin immunoprecipitation (ChIP) was prepared and proteins cross-linked to DNA. Chromatin was incubated overnight with antibodies against PBX-1 or isotype control. PCR primers were designed to amplify the IL-10 apoptotic cell response element (Chung et al., 2007) and were performed in primary macrophages after siRNA knockdown of indicated genes. SIRT1 activity was measured with the Sirt1 Activity Assay Kit from Abcam, Cambridge, MA and as described (Chatterjee et al., 2018).
Infarcted mice were anesthetized with isoflurane and peripheral blood drawn into citrate anticoagulant solution. Hearts were harvested, perfused with saline to remove peripheral cells, minced with fine scissors, and incubated in a cocktail of collagenase and DNase. Cells were filtered through a 70mm strainer and pelleted at 500xg. Total cell numbers were counted by Trypan blue staining and cell suspensions were rinsed with Hank’s Balanced Salt Solution supplemented with 0.2% (wt/vol) bovine serum albumin and 1% wt/vol fetal calf serum.
Statistical analyses were performed with GraphPad Prism (GraphPad Software, La Jolla, CA). Comparisons between two groups were performed using two-tailed, unpaired t test with 95% confidence interval. For comparisons of more than two variables, 1-way ANOVA was utilized with 95% confidence interval. Data are presented as mean ± SEM. For qPCR and murine model of myocardial infarction, power and sample size were estimated based on our previous work. The statistical parameters and criteria for significance can be found in the figure legends.
The RNaseq datasets generated during and/or analyzed during the current study are available at GEO: GSE121681 (WT = Wild-Type, AC = Apoptotic Cell. LPS = lipopolysaccharide).
Funding support from NHLBI F32HL127958 (M.D.) and HL122309 and HL139812(E.B.T.), Chicago Biomedical Consortium, AHA predoctoral fellowship to S.Z., NU presidential fellowship to S.Z., and Sidney Bess Memorial Fund. Special thanks to Lennell Reynolds, Jr. at the NU imaging facility. D.R.G. is supported by 2R01CA152601-A1, 1R01CA152799-01A1, 1R01CA168292-01A1, 1R01CA214025-01, the Avon Foundation for Breast Cancer Research, the Lynn Sage Cancer Research Foundation, the Zell Family Foundation, and the Chicago Biomedical Consortium as well the Searle Funds at The Chicago Community Trust.
Conceptualization, S.Z., S.W., and E.B.T.; Methodology, S.Z., S.W., and M.D.; Formal Analysis, A.G., M.S., and J.M.K.; Investigation, S.Z., M.D., N.S.C., P.T.S., and E.B.T.; Resources, S.W., I.B.-S., D.R.G., N.S.C., L.Y.-C., and P.T.S.; Writing-Original Draft, S.Z.; Writing-Review & Editing, S.Z. and E.B.T.; Funding Acquisition, S.Z. and E.B.T.
Jason Kinchen is an employee of Metabolon.
Document S1. Figures S1–S7.