SUMMARY
Apoptotic cell clearance by macrophages (efferocytosis) promotes resolution signaling pathways, which can be triggered by molecules derived from the phagolysosomal degradation of apoptotic cells. We show here that nucleotides derived from the hydrolysis of apoptotic cell DNA by phagolysosomal Dnase2a activates a DNA–PKcs–mTORC2/Rictor pathway that increases Myc to promote non-inflammatory macrophage proliferation. Efferocytosis-induced proliferation expands the pool of resolving macrophages in vitro and in mice, including zymosan-induced peritonitis, dexamethasone-induced thymocyte apoptosis, and atherosclerosis regression. In the dexamethasone-thymus model, hematopoietic Rictor deletion blocked efferocytosing macrophage proliferation, apoptotic cell clearance, and tissue resolution. In atherosclerosis regression, silencing macrophage Rictor or Dnase2a blocked efferocyte proliferation, apoptotic cell clearance, and plaque stabilization. In view of previous work showing that other types of apoptotic cell cargo can promote resolution in individual efferocytosing macrophages, the findings here suggest that signaling triggered apoptotic cell-derived nucleotides can amplify this benefit by increasing the number of these macrophages.
Graphical Abstract
ETOC Blurb
Apoptotic cell (AC) clearance by macrophages (efferocytosis) promotes tissue resolution, and its failure contributes to inflammatory diseases. Gerlach at al. show that AC-nucleotides trigger efferocytosing macrophages to proliferate, which is essential for resolution in vivo, including in atherosclerosis regression. These findings may suggest new ways to treat non-resolving inflammatory diseases.
INTRODUCTION
Macrophages play critical roles in tissue remodeling in normal physiology and in resolution of inflammation and tissue injury (Wynn et al., 2013). A critical process in resolution is the clearance of apoptotic cells (ACs), or efferocytosis (Boada-Romero et al., 2020; Dalli and Serhan, 2017; Doran et al., 2020; Henson, 2017; Morioka et al., 2019). Efferocytosis prevents tissue necrosis and inflammation by preventing necrosis, and ACs activate receptor-mediated signaling pathways in macrophage that suppress inflammation and promote resolution and repair (Boada-Romero et al., 2020; Bosurgi et al., 2017; Cai et al., 2016; Camenisch et al., 1999; Dalli and Serhan, 2017; Doran et al., 2020; Henson, 2017; Lemke and Rothlin, 2008; McDonald et al., 1999; Morioka et al., 2019; Tibrewal et al., 2008). Macrophages are capable of high-capacity efferocytosis, which plays a critical role in the resolution process. For example, in hypercholesterolemic humans and mice with established atherosclerosis, marked lowering of plasma cholesterol triggers a burst of efferocytosis that mediates resolution and plaque stabilization, which in humans lowers the risk of coronary artery disease (Fisher, 2016; Sharma et al., 2020; Sipahi et al., 2006; Yurdagul et al., 2020). Conversely, efferocytosis becomes defective in many chronic inflammatory diseases, including progressing atherosclerosis, leading to tissue damage and chronic inflammation (Boada-Romero et al., 2020; Dalli and Serhan, 2017; Doran et al., 2020; Henson, 2017; Morioka et al., 2019). The pro-resolving/repair function of macrophages is influenced by specific intracellular metabolic pathways (O’Neill and Pearce, 2016). Some of these pro-resolving pathways are triggered by metabolites, e.g., amino acids and lipids, obtained from the phagolysosomal degradation of ACs during efferocytosis (A-Gonzalez et al., 2009; Morioka et al., 2018; Yurdagul et al., 2020; Zhang et al., 2018).
In this study we explored another class of AC-derived molecules, namely, nucleic acids. We found that nucleotides derived from the phagolysosomal hydrolysis of AC-DNA during efferocytosis triggers a signaling pathway that promotes the proliferation of pro-resolving macrophages. In resolving settings in vivo, e.g., sterile peritonitis, dexamethasone-induced thymocyte apoptosis, and atherosclerosis regression, efferocytic macrophages proliferate, and when the AC-oligonucleotide signaling pathway is inhibited, efferocytic macrophage proliferation is blocked and resolution is impaired.
RESULTS
Efferocytosing Macrophages Undergo Proliferation
To study differences between efferocytosing and basal macrophages, we incubated bone marrow-derived macrophages (BMDMs) with Vybrant® DiD-labeled apoptotic Jurkat cells for 45 minutes. The unengulfed ACs were then removed by rinsing, and the macrophages were either fixed immediately or incubated for an additional 24 hours and then fixed. We use DiD-fluorescence to distinguish AC+ from AC− macrophages. At the 24-hour timepoint, the number of AC+ macrophages increased, whereas the number of AC− macrophages did not change (Figure 1A). Further, ~30% of the AC+ macrophage subpopulation, but not the AC− subpopulation, displayed an increase in the percentage of macrophages expressing the proliferation marker Ki67+ as well as the total number of macrophages (Figure 1B). We also used flow cytometry to analyze macrophages pre-incubated with EdU (5-ethynyl-2’-deoxyuridine), a thymidine analog that is incorporated into newly synthesized DNA. Consistent with the above data, the percent of EdU+ macrophages and total number of macrophages were higher in the AC+ versus AC− macrophage subpopulation at the 24-hour timepoint (Figure 1C). As with Ki67, ~30% of AC+ macrophages showed an increase in EdU positivity. As a final test, macrophages were pre-labeled with the cytoplasmic dye carboxyfluorescein diacetate succinimidyl ester (CFSE), a dye that is diluted in proliferating cells. Flow cytometric analysis showed a substantially higher level of CFSE dilution in AC+ versus AC− macrophages at the 24-hour timepoint (Figure 1D), indicating that AC+ macrophages undergo cell division. Similar results were obtained when we used apoptotic BMDMs (Figures S1A and S1B); when we gated on macrophages in which ACs were documented to be in phagolysosomes, i.e., by using ACs labeled with pHrodo™ dye, which requires an acidic environment for fluorescence emission (Figure S1C); or when we used human monocyte-derived macrophages (HMDMs) (Figure 1E and 1F).
Figure 1. Efferocytosis Induces Macrophage Proliferation.
Bone marrow-derived macrophages (BMDMs) were incubated with DiD-labeled apoptotic Jurkat cells (ACs) for 45 minutes (45 min), followed by rinsing to remove unengulfed ACs and then harvesting immediately or after an addition 24-hour incubation in the absence of ACs (24 hr) unless otherwise specified.
(A) BMDMs from both timepoints were stained with DAPI, and cell number/field of view was assessed by counting DAPI-stained DiD− (AC−) and DiD+ (AC+) macrophages (n = 11 biological replicates).
(B) Left, Fluorescence microscopic images of BMDMs harvested after 45 minutes (top) or 24 hours (bottom). Yellow arrows identify DiD+ (AC+) Ki67+ macrophages. Scale bar, 50 μm. Middle, percentage of Ki67+ macrophages within the AC− and AC+ macrophage subpopulations. Right, AC− and AC+ macrophage numbers/field of view. For both analyses, n = 10 biological replicates.
(C) BMDMs were pre-labeled with EdU and then assayed by flow cytometry at the 24-hour timepoint for the percentage of EdU+ macrophages within the AC− and AC+ macrophages (left and middle) and for AC− and AC+ macrophage numbers (right) (n = 5-6 biological replicates).
(D) BMDMs were pre-labeled with CFSE for 15 minutes and then assayed by flow cytometry at the 24-hour timepoint for the percentage of macrophages in each group that doubled, calculated from the decrease in CSFE fluorescence (n = 3 biological replicates).
(E) Human monocyte-derived macrophages (HMDMs) were used instead of BMDMs and assayed by flow cytometry at the 24-hour timepoint for the percentage of Ki67+ cells within AC− and AC+ macrophages (left) and for AC− and AC+ macrophage numbers (right) (n = 3 biological replicates).
(F) HMDMs were incubated for 45 minutes ± ACs and assayed for the number of cells/well; dotted line indicates cell number at the beginning of the experiment (n = 3 biological replicates).
(G) BMDMs transfected with siRbcn or scrambled RNA control and labeled with EdU were harvested after the 24-hour timepoint or at 48 hours after removal of the labeled ACs and then assayed for the percentage of EdU+ macrophages (n = 3 biological replicates).
(H) BMDMs transfected with siRbcn or scrambled RNA were incubated ± unlabeled ACs and quantified for cell number/well; dotted line indicates cell number at the beginning of the experiment (n = 3 biological replicates).
(I) Groups 1-4, BMDMs pre-treated with bafilomycin and labeled with EdU were harvested 18 hours after labeled-AC removal and assayed for the percentage of EdU+ macrophages. Groups 5-8, BMDMs were incubated with CSF1 or Gas6 for 18 hours instead of ACs and assayed as above (n = 3 biological replicates).
(J) BMDMs from Mertkfl/fl or Mertkfl/fl Lyz2Cre+/− mice were labeled with EdU were harvested at 24- or 48-hour timepoints and assayed for the percentage of EdU+ macrophages.
(K) BMDMs from Mertkfl/fl or Mertkfl/fl Lyz2Cre+/− mice were pre-treated with bafilomycin and labeled with EdU were harvested at 24- or 48-hour timepoints and assayed for the percentage of EdU+ macrophages (n = 3 biological replicates).
All values are means ± SEM; letters that are different indicate statistical significance at p<0.05.
The above experiments used BMDMs differentiated from monocytes in media containing L-cell conditioned media, but with no other treatment (basal macrophages). Another type of macrophage proliferation can be triggered by Th2 immunity, which can be modeled in vitro by treatment of basal macrophages with interleukin-4 (IL-4) (Bosurgi et al., 2017; Jarjour et al., 2019; Jenkins et al., 2011). We therefore questioned whether efferocytosis and IL-4 treatment might have additive effects on macrophage proliferation. As expected, each treatment alone increased macrophage proliferation, and we found that the combination of AC uptake and IL-4 treatment increased macrophage proliferation above that seen with either treatment alone (Figures S1D). In contrast, proliferation was very low in inflammatory macrophages generated by treatment with lipopolysaccharide (LPS) and interferon-γ (IFN-γ), and there was no response to efferocytosis (Figures S1E and S1F). In summary, efferocytosis triggers the proliferation of basal and resolving mouse and human macrophages, but not inflammatory macrophages. We call this process efferocytosis-induced macrophage proliferation (EIMP).
Proliferation of Efferocytosing Macrophages Requires Phagolysosomal Degradation of ACs, with an Additional Stimulus from MerTK
To determine if phagolysosomal AC degradation was necessary for EIMP, we silenced Rubicon (Figure S2A), a scaffold protein that is needed for a critical process in phagolysosomal function during efferocytosis called LC3-associated phagocytosis (Martinez et al., 2015). Scrambled RNA- and siRbcn-treated BMDMs were pulsed with EdU and incubated with DiD-labeled ACs for 45 minutes and assayed for the percentage of EdU+ macrophages at 24 or 48 hours after AC removal, as above. Rubicon silencing, despite not blocking of the initial uptake of ACs (Figure S2B, left), resulted in a marked decrease in the percent EdU-positivity in AC+ macrophages at both time points (Figure 1G). Moreover, the increment in cell number after incubation with ACs was suppressed by Rubicon silencing (Figure 1H). Bafilomycin, which inhibits phagolysosomal acidification and degradation of internalized ACs (Bagaitkar et al., 2018; Yurdagul et al., 2020), also blocked the percent EdU-positivity in AC+ macrophages (Figure 1I, bars 1-4) despite no effect on initial AC uptake (Figure S2B, right). As an important control, we showed that CSF1-induced macrophage proliferation, which should not involve phagolysosomes, was not blocked by bafilomycin (Figure 1I, bars 5-6).
Although blocking phagolysosomal degradation of ACs markedly suppressed EIMP, there was a residual AC-induced proliferative response (Figure 1I, bars 3-4). To explain this finding, we hypothesized that the initial activation of a signaling receptor by ACs may contribute partially to EIMP, focusing on the efferocytosis receptor MerTK (Lemke and Rothlin, 2008). BMDMs derived from MerTKfl/fl (control) or MerTKfl/flLyz2Cre+/− (myeloid-MerTK-deleted) mice (Cai et al., 2020; Fourgeaud et al., 2016) were exposed to DiD-labeled ACs and then assayed for the percent of EdU+ macrophages at 24 and 48 hours. Note that although efferocytosis is ~50% inhibited in macrophages lacking MerTK (Figure S2C), the analysis focused on the subset of macrophages that internalized DiD-ACs despite the absence of MerTK. We found that the percent of EdU+ cells was lower in AC+ macrophages lacking MerTK compared with control AC+ macrophages (Figure 1J). Further, the increase in macrophage number induced by ACs was also lower in macrophages lacking MerTK (Figure S2D). In contrast, macrophages lacking Axl, which have a smaller defect in efferocytosis than Mertk−/− macrophages (Subramanian et al., 2016) showed no defect in the percent of EdU+ cells in AC+ macrophages or in the increase in cell number induced by ACs (Figures S2E and S2F, bars 7-8). Likewise, silencing the efferocytosis receptor CD36 (Xiong et al., 2013) had no effect on EIMP (Figure S2G). We also showed that macrophage proliferation induced by CSF1 was not decreased by MerTK deletion (or by Axl knockout) (Figures S2E and S2F, bars 9-11), which further distinguishes EIMP from CSF1-induced macrophage proliferation.
To further distinguish the MerTK and phagolysosomal pathways in EIMP, we showed that the MerTK ligand Gas6 promoted a modest level of macrophage proliferation, and, as predicted, it was not significantly blocked by bafilomycin (Figure 1I, bars 7-8). Further, we found that the combination of bafilomycin treatment and MerTK absence markedly abrogated the percent increase in EdU-positivity in AC+ macrophages compared with either perturbation alone (Figure 1K). Thus, two separate pathways contribute to EIMP: a pathway requiring degradation of ACs in phagolysosomes and a pathway downstream of MerTK, which likely becomes activated by AC-bound Gas6 prior to AC engulfment.
EIMP Requires the Phagolysosomal Release of AC-Derived Oligonucleotides, which Activate mTORC2 through DNA-PKcs
Given that cell cycling is the biological endpoint of EIMP, we considered that nucleotides derived from the hydrolysis of AC-DNA might be the key trigger of the phagolysosomal branch of EIMP. As an initial test of this idea, we incubated macrophages with DiD-labeled IgG-coated red blood cells (IgG-RBCs), which lack DNA, vs. ACs or DiD-labeled IgG-coated ACs (IgG-ACs). Consistent with our previous results, macrophages that had ingested DiD-labeled ACs were enriched for EdU labeling, which was also observed in macrophages that had ingested DiD-labeled IgG-ACs (Figure 2A, left, bars 1-3). However, the macrophages that ingested IgG-RBCs did not show this response even though the uptake was similar to that of ACs (Figures 2A, left, bar 4, and S3A). To correct for differences in AC vs. IgG-RBC internalization into phagolysosomes, we used pHrodo™-labeled ACs and RBCs and gated on macrophages with similar fluorescence, which confirmed that macrophages with internalized RBCs do not undergo proliferation (Figure 2A, right graph). These findings are consistent with the notion that AC-DNA is important for the EIMP response.
Figure 2. Degradation of AC-derived Oligonucleotides Activate DNA-PKcs and mTORC2 Activity to Promote EIMP.
The standard conditions are as in Figure 1 unless noted otherwise.
(A) BMDMs were incubated for 45 minutes with DiD-labeled (left) or pHrodo-labeled (right) ACs, IgG-coated ACs, or IgG-coated RBCs. At the 24-hour timepoint, the macrophages were quantified by flow cytometry for the percentage of EdU+ macrophages (n = 3 biological replicates).
(B) Groups 1-4, BMDMs transfected with siDnase2a or scrambled RNA and labeled with EdU were assayed at the 24-hour timepoint for the percentage of EdU+ macrophages. Groups 5-6, BMDMs were incubated with CSF1 for 24 hours instead of ACs and assayed as above (n = 3 biological replicates).
(C) BMDMs transfected with siDnase2a or scrambled RNA and labeled with EdU were incubated with IgG-RBCs or IgG-RBCs containing salmon sperm DNA and assayed at the 24-hour timepoint for the percentage of EdU+ macrophages (n = 3 biological replicates).
(D) BMDMs transfected with siPrkdc or scrambled RNA and labeled with EdU were assayed at the 24-hour timepoint for the percentage of EdU+ macrophages (n = 3 biological replicates).
(E) BMDMs transfected with siDnase2a or scrambled RNA were incubated for 1 hour ± ACs. Lysates were immunoblotted for phospho-Thr2609-DNA-PKcs and total DNA-PKc; the graph shows the phospho:total DNA-PKcs densitometric ratio, expressed relative to No ACs/Scramble control (n = 3 biological replicates).
(F) Pair groups 1-2, BMDMs transfected with siRictor or scrambled RNA and labeled with EdU were incubated assayed at the 24-hour timepoint for the percentage of EdU+ macrophages. Pair group 3, BMDMs were incubated with CSF1 for 24 hours instead of ACs and assayed as above (n = 3 biological replicates).
(G) BMDMs transfected with scrambled RNA or siDnase2a were incubated for 1 hour ± ACs. Lysates were immunoblotted for phospho-Ser473-Akt and total Akt, with quantification (n = 3 biological replicates).
(H) BMDMs transfected with scrambled RNA or siPrkdc were incubated for 1 hour ± ACs. Lysates were immunoblotted for phospho-Ser473-Akt and total Akt, with quantification (n = 3 biological replicates).
(I) BMDMs treated with vehicle or the Akt inhibitor MK-2206 for 2h and then labeled with EdU were assayed at the 24-hour timepoint for the percentage of EdU+ macrophages (n = 3 biological replicates).
All values are means ± SEM; letters that are different indicate statistical significance at p<0.05.
To test causation, we assayed EIMP in macrophages with silenced Dnase2a (Figure S3B), the phagolysosomal enzyme that digests AC-DNA into oligonucleotides (Minchew and Didenko, 2011). Silencing Dnase2a resulted in decreased EdU incorporation into AC+ macrophages and less AC-induced increase in cell number compared with macrophages transfected with scrambled RNA (Figures 2B, bars 1-4, and S3C). Note that siDnase2a did not block the initial uptake of ACs (Figure S3D) and did not trigger autophagy (Lan et al., 2014) based on the lack of an increase in punctate LC3-II staining (Figure S3E). Moreover, exogenous addition of nucleotide triphosphates (NTPs) did not rescue the proliferation defect observed in Dnase2a-silenced macrophages (Figure S3F). As with siRbcn and bafilomycin, Dnase2a silencing had no effect on CSF1-induced EdU incorporation (Figure 2B, bars 5-6). Moreover, neither silencing of Dnase1 (Figure S3G, left), a cytosolic enzyme that degrades DNA into nucleotides, nor silencing of glucose-6-phosphate-dehydrogenase (G6pdx) (Figure S3G, right), a rate-limiting enzyme involved in the pentose phosphate pathway that produces de novo nucleotides, blocked EIMP (Figures S3H). Finally, we revisited the IgG-coated RBC system, this time electroporating salmon sperm DNA into the RBCs. The DNA-loaded IgG-RBCs were able to stimulate macrophage EdU incorporation compared with unloaded IgG-RBCs, and this proliferative response was blunted in macrophages treated with siDnase2a (Figure 2C). Together, these results show that AC-derived oligonucleotides generated by phagolysosomal Dnase2a is necessary for EIMP.
To uncover the mechanistic link between Dnase2a-derived oligonucleotides and EIMP, we searched for enzymes that are capable of binding DNA oligonucleotides and associated with proliferation and considered DNA-dependent protein kinase (DNA-PK). DNA-PK, which consists of a catalytic subunit called DNA-PKcs (gene name Prkdc) and a nucleotide-binding domain (Dynan and Yoo, 1998), can promote cell proliferation by activating mTORC2 (Zheng et al., 2016). To test the involvement of DNA-PKcs in EIMP, we treated BMDMs with siPrkdc or scrambled RNA (Figure S3I) and conducted an EdU-incorporation assay. We found that siPrkdc. which had no effect on initial AC uptake (Figure S3J), markedly inhibited the percent of EdU+ macrophages within the AC+ subpopulation (Figure 2D). Further, phosphorylation of DNA-PKcs, which is a marker of its activation, was increased in AC+ versus AC− macrophages, and this increase was completely abrogated by siDnase2a (Figure 2E). Thus, phagolysosomal degradation of AC-DNA activates DNA-PKcs, which is necessary for EIMP.
We questioned whether AC-derived nucleotides, in addition to activating DNA-PKcs, might also be incorporated into the nuclei of macrophages undergoing EIMP. We first incubated Jurkat cells with EdU for 2 hours such that a portion of the cells, i.e., those undergoing DNA synthesis during this period, would have their DNA labeled. The Jurkat cells were then rendered apoptotic, labeled with DiD, and added to control (scrambled RNA-treated), siDnase2a-treated, and bafilomycin-treated macrophages for 45 mins. The non-internalized ACs were then rinsed away, and the macrophages were incubated for an additional 18 hours. We found that ~40% of the nuclei of control macrophages showed EdU staining that could not be explained by EdU in residual DiD+ AC material (Figure S3K). With siDnase2a treatment, most of the EdU label was associated with residual DiD+ AC material, with much less incorporated into macrophage nuclei. As expected, bafilomycin-treated macrophages showed the presence of undegraded DiD+ EdU+ ACs, with very little EdU label in macrophage nuclei. These data are consistent with the idea that macrophages undergoing EIMP use nucleotides derived from hydrolysis of AC-DNA to synthesize DNA.
We next further explored the DNA-PKcs-mediated signaling role of AC nucleotides in EIMP. In view of the aforementioned mTORC2 link (Zheng et al., 2016) and previous data showing that platelet-derived growth factor-induced macrophage proliferation is impaired in macrophages lacking the key mTORC2 protein Rictor (Babaev et al., 2018), we tested the role of mTORC2 in EIMP by silencing Rictor. Treatment of macrophages with siRictor (Figure S3L), which did not block initial AC uptake (Figure S3M), decreased the percent of EdU+ macrophages within the AC+ subpopulation but had no effect on CSF1-induced EdU incorporation (Figure 2F). Further, ACs induced phosphorylation of Akt at serine-473 (Figures 2G and 2H), which is an mTORC2-mediated process necessary for proliferation in another setting (Zheng et al., 2016), and this was prevented by both siDnase2a and siPrkdc. Additionally, inhibiting Akt with the pan-Akt inhibitor MK-2206 (Yoshida et al., 2015) inhibited EIMP (Figure 2I). These combined data support a role for the following pathway in EIMP: Dnase2a-hydrolyzed AC-DNA → DNA-PKcs → mTORC2 → phospho-Akt → proliferation.
Increased Myc Expression Downstream of Both mTORC2 and MerTK-ERK1/2 Signaling is Necessary for EIMP
In this section, we present evidence that both the MerTK and phagolysosomal-nucleotide pathways converge on the pro-proliferative transcription factor Myc (Carroll et al., 2018) to promote EIMP. To begin, we found that AC+ macrophages had a higher level of Myc than AC− macrophages and that this increase was blunted by siRbcn and in Mertk−/− macrophages (Figures 3A and 3B, S3N). Most importantly, the percentage of EdU+ cells within both AC+ macrophages and Gas6-treated macrophages was suppressed by silencing Myc (Figures 3C and S3O) despite no change in initial AC uptake (Figure S3P). Thus, both the phagolysosomal degradation of ACs and the engagement of MerTK increases Myc expression to stimulate EIMP.
Figure 3. Mertk-Erk1/2 and mTORC2 are Both Necessary for Full Myc Expression during EIMP.
The standard conditions are as in Figure 1 unless noted otherwise.
(A) BMDMs transfected with scrambled RNA or siRbcn were harvested 3 hours after removal of the labeled ACs, immunostained for intracellular Myc, and assayed for Myc MFI, gating on AC− and AC+ macrophages (n = 3 biological replicates).
(B) BMDMs from Mertkfl/fl or Mertkfl/fl Lyz2Cre+/− mice were harvested 3 hours after removal of the labeled ACs, immunostained for intracellular Myc, and assayed for Myc MFI, gating on AC− and AC+ macrophages (n = 3 biological replicates).
(C) Groups 1-4, BMDMs transfected with siMyc or scrambled RNA and labeled with EdU were assayed at the 24-hour timepoint for the percentage of EdU+ macrophages. Groups 5-6, BMDMs were incubated with Gas6 for 24 hours instead of ACs and assayed as above (n = 3 biological replicates).
(D) BMDMs transfected with scrambled RNA, siDnase2a, siPrkdc, or siRictor were incubated ± ACs for 45 minutes and harvested 3 hours later. Lysates were immunoblotted for Myc and β-actin; the graph shows the Myc:β-actin densitometric ratio, expressed relative to No ACs/Scramble control (n = 3 biological replicates).
(G) BMDMs transfected with scrambled RNA, siDnase2a, siPrkdc, or siRictor were incubated ± ACs for 45 minutes, harvested 3 hours later, and assayed for Myc mRNA (n = 3 biological replicates).
(H) Groups 1-4, BMDMs treated ± U0126 were harvested at the 3-hour timepoint and assayed for Myc in AC− and AC+ macrophages by flow cytometry. Groups 5-6, BMDMs were incubated with Gas6 instead of ACs and assayed as above (n = 3 biological replicates).
(I) Groups 1-4, BMDMs treated ± U0126 and labeled with EdU were harvested at the 24-hour timepoint and assayed for the percentage of EdU+ macrophages. Groups 5-6, BMDMs were incubated with Gas6 instead of ACs and assayed as above (n = 3 biological replicates).
(J) BMDMs transfected with scrambled RNA or siRictor were treated ± U0126 and then incubated ± ACs for 45 minutes, harvested at the 3-hour timepoint, and immunoblotted for Myc and β-actin.
All values are means ± SEM; letters that are different indicate statistical significance at p<0.05.
With regard to the phagolysosomal pathway, we asked whether the aforementioned Dnase2a—DNA-PKcs—mTORC2 pathway might contribute to increased Myc. Indeed, the silencing of Dnase2a, DNA-PKcs, or Rictor led to decreases in both Myc protein and Myc mRNA (Figures 3D–3G). With regard to MerTK, we postulated that activation of ERK1/2 might be involved, as MerTK engagement leads to ERK1/2 activation, including in macrophages (Cai et al., 2018; Nishi et al., 2019; Schlegel et al., 2013), and ERK1/2 has been linked to increased Myc expression in other cell types (Sears et al., 1999). As expected, AC+ macrophages had increased phospho-ERK1/2, a measure of ERK1/2 activation, compared with AC− macrophages, and phospho-ERK1/2 was decreased in AC+ macrophages lacking MerTK (Figure S3Q). To test causation in EIMP, macrophages were pre-treated with U0126, a MEK inhibitor that prevents Erk1/2 phosphorylation (Favata et al., 1998), and then incubated with EdU and either DiD-labeled ACs or Gas6. The ERK inhibitor suppressed Myc expression (Figures 3H and S3R) and decreased the percentage of EdU+ cells within both AC+ macrophages and Gas6-treated macrophages (Figures 3I). Finally, when both the mTORC2 and ERK pathways were inhibited by siRictor and U0126, AC-induced Myc was almost completely suppressed (Figure 3J). Thus, the phagolysosomal and MerTK pathways, via mTORC2 and ERK1/2, respectively, combine to increase Myc in efferocytosing macrophages, which is necessary for EIMP.
Myc Drives EIMP by Upregulating Bhlhe40 and Downregulating c-Maf
In a different setting of macrophage proliferation, the Myc target Bhlhe40 was shown to increase macrophage proliferation by downregulating the anti-proliferative protein c-Maf (gene name Maf) (Jarjour et al., 2019; Rauschmeier et al., 2019). We therefore asked whether Myc might drive EIMP by increasing the expression of Bhlhe40. Incubating macrophages with ACs increased Bhlhe40 mRNA and Bhlhe40 protein, and Myc silencing blunted these increases (Figure 4A). Further, incubating macrophages with ACs decreased Maf mRNA and c-Maf protein, and Myc silencing prevented these decreases (Figures 4B and S4A). We established a link between Bhlhe40 and c-Maf by showing that silencing Bhlhe40 (Figure S4B) prevented the AC-induced decrease in Maf mRNA and c-Maf protein (Figures 4C and 4D), without blocking initial AC uptake (Figure S4C). Further, silencing either Dnase2a or Rictor prevented the AC-induced increase in Bhlhe40 and decrease in c-Maf (Figures 4E, 4F, and S4D). Most importantly, silencing Bhlhe40 completely prevented the increase in EdU incorporation in AC+ macrophages and the increase in cell number in macrophages incubated with ACs, which was not seen with CSF1-induced proliferation (Figures 4G and 4H). Finally, transfection of macrophages with c-Maf (Figure S4E) blocked the increase in EdU incorporation into AC+ macrophages (Figure 4I). In summary, AC-mediated activation of MerTK-ERK signaling together with activation of DNA-PKcs—mTORC2 signaling by Dnase2a-derived AC-oligonucleotides induces Myc to a high enough level where it induces Bhlhe40. Bhlhe40 then represses the cell-cycling-inhibitor c-Maf to drive proliferation (Figure 4J).
Figure 4. Myc Drives EIMP by Upregulating Bhlhe40 and Downregulating c-Maf.
The standard conditions and n number are as in Figure 1 unless noted otherwise.
(A) BMDMs transfected with scrambled RNA or siMyc were incubated ± ACs for 45 minutes, harvested 6 hours later, and assayed for Bhlhe40 mRNA (left) or Bhlhe40 protein by immunoblot (right), The graph shows the Bhlhe40:μ-actin densitometric ratio, expressed relative to No ACs/Scramble control (n = 3 biological replicates).
(B) BMDMs transfected with scrambled RNA or siMyc were incubated ± ACs for 45 minutes, harvested 6 hours later, and assayed for Maf mRNA (left) or c-Maf protein by immunoblot, with quantification (right) (n = 3 biological replicates).
(C) BMDMs transfected with scrambled RNA or siBhlhe40 were incubated ± ACs for 45 minutes, harvested 6 hours later, and assayed for Maf mRNA (n = 3 biological replicates).
(D) BMDMs transfected with scrambled RNA or siBhlhe40 were harvested at the 6-hour timepoint and assayed for c-Maf in AC− and AC+ macrophages by flow cytometry (n = 3 biological replicates).
(E-F) BMDMs transfected with scrambled RNA, siDnase2a, or siRictor and incubated ± ACs were assayed at the 6-hour timepoint for Bhlhe40 and Maf mRNA (n = 3 biological replicates).
(G) Groups 1-4, BMDMs transfected with scrambled RNA or siBhlhe40 and then labeled with EdU were harvested at the 24-hour timepoint and assayed for the percentage of EdU+ macrophages. Groups 5-6, BMDMs were incubated for 24 hours with CSF1 instead of ACs and assayed as above (n = 3 biological replicates).
(H) Groups 1-4, BMDMs transfected with scrambled RNA or siBhlhe40 were incubated ± EdU and assayed at the 24-hour timepoint for cell number/well. Groups 5-6, BMDMs were incubated for 24 hours with CSF1 instead of ACs and assayed as above (n = 3 biological replicates).
(I) BMDMs transfected with empty plasmid or Maf-encoding plasmid and then labeled with EdU were harvested at the 24-hour timepoint and assayed for the percentage of EdU+ macrophages (n = 3 biological replicates).
(J) Schematic summary of the EIMP pathway. AC-mediated activation of MerTK-ERK signaling and activation of DNA-PKcs—mTORC2 signaling by Dnase2a-derived AC-oligonucleotides converge to induce Myc, which then induces Bhlhe40. Bhlhe40 represses the cell-cycling-inhibitor c-Maf to drive macrophage proliferation.
All values are means ± SEM; letters that are different indicate statistical significance at p<0.05.
Macrophages Undergoing EIMP are Competent Efferocytes and Producers of TGFβ and IL-10 in Vitro
We reasoned that EIMP would expand the pool of macrophages capable of clearing ACs and producing pro-resolving molecules. We therefore tested whether macrophages that had undergone EIMP were adequate at carrying out efferocytosis and producing two efferocytosis-induced resolving/repair proteins, transforming growth factor-β (TGFβ) and interleukin-10 (IL-10) (Fadok et al., 1998; Voll et al., 1997). We generated AC-induced proliferating macrophages by incubating BMDMs with unlabeled ACs for 45 minutes, followed by a 24-hour incubation. Proliferating macrophages were identified by Ki67-positivity, and a majority of these KI67+ macrophages were undergoing efferocytosis, i.e., had internalized an AC. We then compared these “EIMP macrophages” with control non-EIMP macrophages, i.e., Ki67− macrophages that did not undergo an initial incubation with unlabeled ACs, for their relative abilities to carry out efferocytosis and post-efferocytic TGFβ and IL-10 production.
For efferocytosis, we assayed both single AC uptake as well as the key resolving process of continual efferocytosis (Park et al., 2011; Wang et al., 2017; Yurdagul et al., 2020). To assay single-AC efferocytosis, the two groups of macrophages were incubated with PKH67-labeled ACs for 45 minutes, followed by AC removal and quantification of PKH67 uptake. For continual efferocytosis, control and EIMP macrophages were first incubated as above with PKH67-labeled ACs, followed by rinsing and a 2-hour incubation in medium alone. The macrophages were then incubated for 45 minutes with PKH26-labeled ACs and quantified for PKH67 and PKH26 double-positivity among all PKH67+ macrophages (Yurdagul et al., 2020). The data show that EIMP macrophages ingested single PKH67-labeled ACs to the same extent as control macrophages, and they showed an even greater ability to engulf a second AC (Figures 5A and 5B).
Figure 5. Macrophages Undergoing EIMP are Competent Efferocytes and Producers of TGFβ and IL-10 in Vitro, and Evidence of EIMP in Vivo.
(A) Macrophages not previously exposed to ACs and shown to be Ki67− (control Mϕs) or Ki67+ macrophages after 24-hour incubation with unlabeled ACs (AC-induced proliferating macrophages, termed “EIMP Mϕs”) were incubated with PKH67-labeled ACs for 45 minutes. The percentage of PKH67+ macrophages of total macrophages was assayed as a measure of single-cell efferocytosis (n = 5 biological replicates).
(B) Control and Ki67+ EIMP macrophages were incubated first with PKH67-labeled ACs and then, after 2 hours, with PKH26-labeled ACs. The percentage of PKH67+ PKH26+ macrophages of PKH67+ macrophages for each group was assayed as a measure of double-cell efferocytosis (n = 5 biological replicates). Right, representative fluorescence microscopic images for this experiment. Yellow arrows indicate PKH67+ PKH26+ Ki67+ macrophages. Scale bar, 50 μm.
(C-D) EdU-labeled macrophages were incubated with DiD-labeled ACs for 45 minutes, rinsed, and incubated an additional 18 hours. The cells were detached, immunostained for intracellular TGFβ and IL-10, and subjected to flow cytometric analysis to assess TGFβ and IL-10 mean fluorescence intensity (n = 3 biological replicates). Golgi-stop was added to the cells at the beginning of the 18-hour incubation to enable quantification of intracellular TGFβ and IL-10.
(E) Mice were injected with EdU (200 μg/mouse i.p.) 24 hours prior to injection with PBS or 1 mg of zymosan A. After 24 or 48 hours, peritoneal cells were immunostained for F4/80 and intracellular Gr1 and subjected to flow cytometric analysis. Left, Flow cytometry plot showing that macrophage permeabilization is needed to detect Gr1, indicating that the Gr1 is intracellular, i.e., a marker of macrophage engulfment of neutrophils. Right, Flow plots and quantification of the percentage of EdU+ cells within F4/80+ macrophages that were either negative (AC−) or positive (AC+) for intracellular Gr1 (n = 5 mice per group).
(F) Ki67, Mac2, and TUNEL staining of thymic sections from mice 18 hours after injection with PBS or dexamethasone (Dex). The percentage of Ki67+ macrophages among AC+ and AC− thymic macrophages was quantified by immunofluorescence microscopy (IFM) (n = 7 mice per group). Scale bar, 50 μm.
To assess TGFβ and IL-10 production, macrophages were pre-incubated with EdU and then incubated with DiD-labeled ACs for 45 minutes and then, after removal of unengulfed ACs, cultured for an additional 18 hours. Golgi-stop was added to the cells at the beginning of the 18-hour incubation to enable quantification of intracellular TGFβ and IL-10. AC+ and AC− macrophages were then assayed for intracellular TGFβ and IL-10 by flow cytometry. As expected (Fadok et al., 1998; Voll et al., 1997), TGFβ and IL-10 were higher in AC+ versus AC− macrophages in the non-EIMP (EdU−) control cohort. Most importantly, the AC-induced increments in TGFβ and IL-10 were also seen in EIMP (EdU+) macrophages (Figures 5C, 5D, S4F, and S4G). In summary, macrophages undergoing EIMP are highly competent at both efferocytosis and in efferocytosis-induced production of two key pro-resolving cytokines.
EIMP Occurs in Vivo in Acute Models of High-Burden Efferocytosis
As an initial inquiry into the presence of EIMP in vivo, we examined a model of sterile peritoneal inflammation in which the yeast cell wall component zymosan A is injected into the peritoneal cavity of mice. In this model, the inflammatory stimulus of zymosan leads to neutrophil recruitment, which peaks at 12 hours, followed by neutrophil apoptosis and apoptotic neutrophil clearance by intraperitoneal resolving-type macrophages (Pashover-Schallinger et al., 2012; Proto et al., 2018). To assess macrophage proliferation, the mice were injected i.p. with EdU 24 hours prior to the injection of vehicle or zymosan. At 24 and 48 hours after zymosan injection, peritoneal cells were harvested and immunostained for the cell-surface marker F4/80 to identify macrophages and for intracellular Gr1, a marker of neutrophils (Figure S4H). Flow cytometric analysis was then conducted to quantify the percent of EdU+ macrophages within the Gr1+ (AC+) and Gr1− (AC−) macrophage subpopulations. At both 24 and 48 hour time points, the percentage of EdU+ cells was higher in AC+ versus AC− macrophages (Figure 5E), consistent with EIMP in this setting.
We next turned to a well-characterized model of high-burden efferocytosis in which mice are injected with dexamethasone to induce robust thymocyte apoptosis (dex-mice). High-capacity, continual efferocytosis by thymic macrophages limits the accumulation of dead thymocytes, which protects against tissue necrosis and inflammation (Park et al., 2011; Yurdagul et al., 2020). Efferocytic macrophages are identified by staining thymic sections with anti-Mac2 to identify macrophages and with TUNEL reagent to mark engulfed dead thymocytes, i.e., macrophages with cytoplasmic TUNEL staining (Park et al., 2011; Yurdagul et al., 2020). Note that thymocytes with nuclear TUNEL (dead cells) are very rare in this model (Figure S5A). We assayed Ki67-staining to determine whether efferocytosing (AC+) macrophages were more proliferative than non-efferocytosing (AC−) macrophages in dex-mice versus PBS-treated control mice. As expected, efferocytosing macrophages were uncommon in the thymi of PBS-treated control mice owing to the paucity of apoptotic thymocytes (Figure 5F, top), and the small AC+ macrophage subpopulation was not significantly enriched in Ki67+ macrophages compared with the AC− macrophage subpopulation (Figure 5F, bars 1-2). As expected, AC+ macrophages were readily observed in the dex-mice thymi (Figure 5F, bottom), and, most importantly, there was a higher percentage Ki67+ cells AC+ vs. AC− macrophages (Figure 5F, bars 3-4).
To determine the role of Rictor, we examined the dex-thymus model in mice transplanted with Rictorfl/fl bone marrow cells that were first incubated in vitro with vehicle (control) or with TAT-Cre to delete Rictor prior to transplantation. As designed, bone marrow cells subsequently harvested from the mice transplanted with Rictorfl/fl TAT-Cre cells had undetectable Rictor, as did the macrophages in the thymi of these mice (Figure S5B). We found that the percent of Ki67+ cells within the AC+ macrophage subpopulation and the total number of macrophages was much lower in the thymi of the Rictorfl/fl TAT-Cre mice versus control mice (Figure 6A and 6B), without a change in thymic macrophage death (Figure S5C).
Figure 6. Rictor-Dependent EIMP and Resolution in Dexamethasone-Induced Thymocyte Apoptosis.
Mice were transplanted with Rictorfl/fl and Rictorfl/fl TAT-Cre bone marrow. After 4 weeks, the mice were injected i.p. with PBS or dexamethasone (Dex) and then the thymi were harvested 18 hours later and assayed as follows:
(A) Ki67, Mac2, and TUNEL staining , with yellow arrows indicating Mac2+ Ki67+ AC+ macrophages. Scale bar, 50 μm. The graph shows quantification of percentage of Ki67+ cells within AC+ and AC− macrophages (n = 5 mice per group). Scale bar, 50 μm.
(B) Quantification of F4/80+ macrophages by flow cytometry (n = 5 mice per group).
(C) Quantification by IFM of Myc, Bhlehe40, and c-Maf MFI in AC+ and AC− macrophages (n = 5 mice per group).
(D) Annexin-V+ (apoptotic) cells by flow cytometry and cell counting, and thymic weights (n = 5 mice per group).
(E) As a measure of efferocytosis, ratio of Mac2+ macrophage-associated:free TUNEL+ ACs by IFM (n = 5 mice per group).
(F) Quantification of percent area of necrosis (anuclear area) of total area in H&E-stained sections; yellow arrows indicate area of necrosis(n = 5 mice per group). Scale bar, 200 μm.
(G) Immunostaining and quantification of IL-6 MFI in Mac2+ areas (n = 5 mice per group). All values are means ± SEM; letters that are different indicate statistical significance at p<0.05.
As further evidence for EIMP in the dex-thymus model, we found that AC+ thymic macrophages expressed a higher level of Myc compared with AC− macrophages in control Rictorfl/fl-transplanted dex-mice, but this increase was much less in dex-mice whose macrophages lacked Rictor (Figures 6C, left, and S5D, top). Moreover, as predicted by the EIMP pathway, Bhlhe40 expression in thymic macrophages was increased in AC+ macrophages of control dex-mice but not dex-mice whose macrophages lacked Rictor (Figures 6C, middle, and S5D, middle). Further, although c-Maf expression showed only a slight trend toward lower expression AC+ versus AC− thymic macrophages in control dex-mice mice, its expression was markedly increased in AC+ thymic macrophages in Rictor-deficient dex-mice (Figures 6C, right, and S5D, bottom). Thus, suppression of EIMP in thymic macrophages by targeting Rictor is associated with suppression of the unique molecular signature of EIMP elucidated in vitro. These combined data indicate that EIMP occurs in high-AC setting in vivo.
EIMP Contributes to AC Clearance and Tissue Protection in Vivo
We first examined the resolution-related consequences of myeloid-Rictor deletion in the above dex-thymus model. As predicted by our hypothesis on the role of EIMP in continual efferocytosis, the thymi of Rictor-deficient dex-mice had an increase number of ACs compared with control dex-mice, and this was accompanied by increased overall cellularity and thymus weight (Figure 6D), which are features of thymi in which clearance of dead thymocytes is impaired (Park et al., 2011; Yurdagul et al., 2020). More directly, efferocytosis itself was impaired in the thymi of Rictor-deficient mice (Figure 6E), which suggests a defect in continual efferocytosis in view of finding in Figure S3K that Rictor silencing in macrophages does not lower initial AC uptake. Most importantly, the impairments in EIMP and efferocytosis in Rictor-deficient mice was associated with increased thymic necrosis and increased expression of the inflammatory cytokine IL-6, indicating impaired tissue resolution (Figures 6F, 6G, and S5E).
We next turned to a pre-clinical model of an important pro-resolving process in humans, atherosclerosis regression. In humans with established high-risk atherosclerosis, marked lowering of plasma cholesterol promotes features of plaque stabilization, notably decreases in plaque necrosis and thickening of a protective fibrous cap that overlies necrotic lesions, which is associated with lower risk of coronary artery disease (Sipahi et al., 2006). Hypercholesterolemic mice in which plasma cholesterol is markedly lowered provide a model of this plaque resolution process (Fisher, 2016). Moreover, efferocytosis by lesional macrophages is increased during plaque regression and is a key process in the plaque remodeling/resolution response (Sharma et al., 2020; Yurdagul et al., 2020). For the regression model, Ldlr−/− mice are fed a Western-type diet for 16 weeks, which causes advanced atherosclerotic lesions at the aortic root. One cohort is harvested at this time (baseline), while others are injected with a helper-dependent adenovirus containing the human LDLR gene (HDAd-LDLR), which is non-integrating and restores LDL receptor expression in hepatocytes to clear plasma LDL, and then switched to a chow diet for 5 additional weeks (Willecke et al., 2015; Yurdagul et al., 2020).
To test the role of the AC-nucleotide—mTORC2 signaling pathway in atherosclerotic lesional macrophages at the time of regression, we took advantage of an approach that uses siRNA-containing nanoparticles (NPs) to silence genes in these cells (Tao et al., 2020). The NPs are conjugated with a peptide called S2P, which recognizes the macrophage receptor stabilin-2 and facilitates macrophage targeting, and they penetrate atherosclerotic lesions (Tao et al., 2020). The size and zeta potential of these NPs (Figures S6A and S6B) were similar to those in our previous report (Tao et al., 2020). The mice were injected at the onset of regression with S2P-NPs containing control scrambled RNA or siRNA targeting either of two mRNAs critical for the AC-nucleotide/mTORC2 signaling pathway, Rictor and Dnase2a.
Beginning with siRictor NPs, the regression protocol successfully lowered plasma cholesterol in both cohorts (scrambled RNA and siRictor) compared with the baseline 16-week cohort (Figure S6C). Other systemic parameters in the regression cohorts were not affected significantly by siRictor NP administration (Figures S6D–S6H). As designed, siRictor NPs markedly lowered Rictor expression in regressing lesional macrophages (Mac2+) but not in non-macrophage (Mac2−) cells (Figure S6I). We found that efferocytosing (AC+) macrophages in regressing lesions had a marked increase in Ki67-staining compared with either AC− macrophages in these lesions or all macrophages in the baseline cohort (Figures 7A, first 4 groups, and S6J, first two columns of images). Most importantly, this increase in Ki67 among AC+ macrophages in regressing lesions was markedly abrogated in the siRictor cohort (Figures 7A, groups 5-6, and S6J, third column of images). As expected, the overall number of lesional macrophages was decreased by regression, but there was a selective increase in the subpopulation of macrophages carrying out efferocytosis (AC+), which was abrogated by treatment with siRictor NPs (Figures 7B). We also found that Myc expression was increased in regressing lesional macrophages compared with baseline lesional macrophages, and the fold-increase was greater in AC+ versus AC− macrophages, and this finding was also abrogated by siRictor treatment (Figures 7C).
Figure 7. Rictor- and Dnase2a-Dependent EIMP and Resolution in Atherosclerosis Regression.
Ldlr−/− mice were fed the Western diet for 16 weeks and then either harvested (Baseline) or subjected to the atherosclerosis-regression protocol for 5 weeks. The regression mice were administered S2P-NPs containing siRictor (A-E) or siDnase2a (F-J) (or scrambled-RNA NPs as control), throughout the regression period.
(A and F) Lesions were immunostained for Ki67, Mac2, and TUNEL. Overlap of cytoplasmic TUNEL staining with Mac2+ macrophages indicates efferocytosing (AC+) macrophages. The percent Ki67+ macrophages within AC+ and AC− lesional macrophages was quantified by IFM (n = 7-10 mice per group).
(B and G) The percent of efferocytosing (AC+) macrophages among total macrophages and the total number of Mac2+ cells per lesion section were quantified in the 3 groups of mice.
(C and H) Lesions were immunostained for Myc, Mac2, and TUNEL. Myc MFI within AC+ and AC− lesional macrophages was quantified by IFM and expressed relative to the MFI of Myc in AC− macrophages in the baseline cohort (n = 7-10 mice per group).
(D and I) Left, Quantification of the ratio of macrophage-associated ACs:free ACs, expressed relative to the baseline cohort. Right, the mean number of apoptotic (nuclear TUNEL+) cells per aortic root lesion section.
(E and J) Quantification of the lesions for necrotic area and fibrous cap thickness. The top row of images are H&E-stained; necrotic areas are outlined with dashed lines. The bottom row of images are Sirius red-stained and show where fibrous cap thickness was measured. Scale bar, 200 μm. Collagen cap thickness was measured at the lesional midpoint and both shoulder regions and then averaged and quantified as the ratio of collagen cap thickness to lesion area; data are presented relative to the baseline cohort average.
All values are means ± SEM; letters that are different indicate statistical significance at p<0.05.
As noted above, efferocytosis increases in plaque regression (Sharma et al., 2020; Yurdagul et al., 2020), and we predicted that EIMP, by expanding the pool of efferocytes, would enhance continual efferocytosis and the clearance of ACs in this setting. Compared with baseline lesions, the ratio of macrophage-associated ACs:free ACs was increased in the control regression cohort but not in the siRictor cohort, and this was associated with lowering of ACs in the control cohort but not in the siRictor cohort, without a change in total ACs (Figures 7D and S6L). Most importantly, the decrease in plaque necrosis and increase in fibrous cap thickness observed in the control regressing lesions were abrogated by siRictor-NP treatment (Figures 7E and S6M).
In addition to blocking EIMP, two other effects of siRictor might have contributed to these plaque changes. First, in IL-4-treated macrophages in vitro and in worm-infected mice, deletion of Rictor lowers interferon regulatory factor 4 (IRF4), which, by suppressing oxidative phosphorylation, blocks macrophage alternative activation (Huang et al., 2016). Second, in the context that siRictor lowers Myc, Myc induces a set of specific genes in IL4-treated macrophages in vitro, notably Alox15 and Scarb1 (encoding SR-BI) that are associated with alternative activation (Pello et al., 2012). However, a recent study showed that IL-4 is not increased in regressing versus progressing lesions (Weinstock et al., 2021), and, most importantly, we found that treatment with siRictor NPs did not decrease arginase 1 (Arg1), which is a marker of alternatively-activated macrophages, or IRF4, ALOX15, or SR-BI in regressing lesional macrophages (Figure S6N).
To provide further evidence for the nucleotide-EIMP pathway in plaque regression, we tested the effect of S2P-NPs containing siDnase2a. siDNase2a NPs did not have a significant effect on cholesterol or other systemic endpoints during regression (Figures S7A–S7F), and they successfully lowered Dnase2a expression in regressing lesional macrophages but not in non-macrophage cells (Figure S7G). Compared with scrambled RNA-NP treatment, siDnase2a-NP treatment lowered Ki67-positivity in efferocytosing (AC+) macrophages in regressing lesions; abrogated the expansion of efferocytosing macrophages in regression; and lowered Myc expression to a greater degree in AC+ versus AC− macrophages (Figures 7F–7H and S7H). These changes were associated with impairments in regression-induced efferocytosis and AC clearance; regression-induced decreases in plaque necrosis and lesion area; and regression-induced fibrous cap thickening (Figures 7I–7J and S7H–S7J). As with siRictor, the expression of Arg1, IRF4, ALOX15, and SR-BI in regressing lesional macrophages was not affected by siDnase2a (Figure S7K). Finally, the impairments in resolution in the siDnase2a cohort could, in theory, be caused by activation of a stimulator-of-interferon-genes (STING) response in macrophages. However, we found that the expression of the STING-response chemokine CXCL10, a marker of the STING response in vivo (Okabe et al., 2005), was very low in regressing lesional macrophages and not affected by siDnase2a-NP treatment (Figure S7L). Further, Cxcl10 mRNA was actually decreased in AC-incubated BMDMs 4 hours after AC removal and not affected by siDnase2a despite the fact that EIMP occurs in this time frame and is suppressed by siDnase2a (Figure S7M). While siDnase2a did increase Cxcl10 24 hours after an initial AC exposure, silencing STING did not rescue the inhibitory effect of siDnase2a on EIMP despite successfully lowering Cxcl10 (Figures S7N and S7O). These combined data show that the inhibition of EIMP by siDnase2a is not a secondary effect of a STING-mediated type 1 interferon response. In summary, proliferation is observed in efferocytosing macrophages in regressing atherosclerotic lesions, and silencing two different molecules in the nucleotide-mTORC2-EIMP pathway in macrophages blocks this proliferative response and abrogates key regression-induced resolution processes important in plaque stabilization.
DISCUSSION
Based on the findings here and in previous reports (A-Gonzalez et al., 2009; Morioka et al., 2018; Yurdagul et al., 2020; Zhang et al., 2018), we propose an integrated resolution concept related to AC-cargo pathways in efferocytosing macrophages: while most pathways, e.g., those stimulated by AC-derived amino acids and lipids, promote resolution in individual macrophages, EIMP triggered by AC-derived nucleotides amplifies this affect by expanding the pool of these resolving macrophages. As continuing efferocytosis is a key pro-resolving function in these pathways, a positive-feedback cycle is established to handle high-AC burdens and prevent tissue injury. As a consequence, when any step in this cycle is interrupted in a disease setting, a pathogenic negative-feedback cycle of impaired resolution and efferocytosis ensues (Dalli and Serhan, 2017; Doran et al., 2020; Morioka et al., 2019).
Two key lines of evidence suggest that EIMP is a key contributing factor to the beneficial resolution-efferocytosis cycle. First, the expanded pool of macrophages resulting from EIMP are highly competent at both continual efferocytosis and post-efferocytic production of TGFβ and IL-10. Second, interruption of the EIMP signaling pathway in vivo causes a decrease in efferocytic (AC+) macrophage proliferation and, most importantly, this is associated with impaired resolution and AC clearance. A key point when we conducted this experiment in atherosclerosis regression was that almost identical results were obtained when we silenced either of two distinct molecules in the pathway, Rictor or Dnase2a, which have not previously been linked together in other cellular pathways. Of note, a previous study reported that overall macrophage proliferation is reduced during plaque regression (Härdtner et al., 2020), and we, as others (Sharma et al., 2020), found a net overall decrease in the total number of macrophages in regressing vs. baseline plaques. The key point revealed here, however, is that proliferation is increased in a subpopulation of macrophages in these lesions, i.e., efferocytosing macrophages, suggesting that the combination of these processes is to increase the resolving:inflammatory macrophage ratio in regression to promote plaque stabilization.
Future studies will determine if interruption of additional processes contribute to impaired resolution when the AC-nucleotide-mTORC2 pathway is silenced in macrophages in vivo. One theoretical possibility was that activation of Rictor and/or Myc in the pathway could promote the alternative activation of macrophages, which is seen in high-IL-4 settings in vitro and in vivo (Huang et al., 2016; Pello et al., 2012). However, resolving plaques do not have higher levels of IL-4 or the related cytokine IL-13 than progressing plaques (Weinstock et al., 2021), and we did not detect evidence of these pathways in regressing lesional macrophages. Thus, context is key, which is further highlighted by the anti-atherogenic effect of myeloid Rictor deletion in the very different setting of progressing atherosclerosis (Babaev et al., 2018). In particular, progressing lesions are populated with inflammatory macrophages (Rahman et al., 2017), which we showed do not respond to efferocytosis with proliferation.
Elegant prior reports have demonstrated macrophage proliferation in other settings, but in these setting proliferation was not linked to AC engulfment or shown to be a mechanism to increase AC-clearance capacity. For example, tissue-resident macrophages established during embryogenesis are able to self-renew to restore tissue homeostasis (Alliot et al., 1999; Davies et al., 2011; Hashimoto et al., 2013). One mediator of macrophage self-renewal is CSF1 (Fejer et al., 2015), which we showed triggers proliferation by a pathway that is distinct from the EIMP pathway. A previous in vitro study reported that ACs can support the survival of growth factor-starved macrophages while actually inhibiting CSF1-induced macrophage proliferation (Reddy et al., 2002), but whether these phenomena are relevant in vivo, particularly in settings of high-burden apoptosis, remains unknown. Other important studies have shown that macrophage proliferation occurs in settings of Th2 immunity, such as in response to IL-4 in vitro or helminth infection in vivo (Bosurgi et al., 2017; Jarjour et al., 2019; Jenkins et al., 2011). In one of these studies, combined deletion of MerTK and Axl was shown to suppress macrophage proliferation in worm-infected mice (Bosurgi et al., 2017), but the proliferative response was not linked to AC engulfment or metabolism, ERK1/2-Myc signaling, or AC clearance in vivo. While it is possible that the findings in this previous study may have relevance to the MerTK arm of EIMP, Th2-induced macrophage proliferation requires IL-4 (Bosurgi et al., 2017), whereas EIMP does not. Finally, in a completely different scenario, inflammation can be a stimulus for pathogenic macrophage proliferation, including in progressing atherosclerosis (Davies et al., 2013; Du et al., 2020; Morita et al., 2020; Robbins et al., 2013; Sinha et al., 2020). We found that IFNγ/LPS-treated macrophages were unable to execute EIMP, which may be related to the finding that LPS suppresses Myc expression in macrophages (Liu et al., 2016). Moreover, the proliferation of inflammatory macrophages in progressing lesions is induced by CSF1 (Sinha et al., 2020), which, as mentioned, is distinct from EIMP.
In chronic, non-resolving diseases, efferocytosis is impaired, which based on our findings would block the efferocytosis-resolution-EIMP positive-feedback cycle and amplify disease progression. Progressing atherosclerosis is a prime example in which this cycle is likely to be broken by processes known to block lesional macrophage efferocytosis, such as MerTK cleavage or SIRPα activation (Cai et al., 2017; Kojima et al., 2016). Moreover, these lesions are populated mostly by inflammatory macrophages, which are incapable of EIMP. However, these lesions do contain a small population of non-inflammatory, efferocytic macrophages, and so, based on the mechanisms identified herein, it may be possible to therapeutically promote the specific expansion of this population of macrophages to restore the pro-resolving positive-feedback cycle.
Limitations of Study
In addition to blocking EIMP, siDnase2a and siRictor could have affected our in vivo endpoints by one or more additional mechanisms. In our analysis of the atherosclerosis regression model, we presented data suggesting that certain key possible confounders, e.g., changes in macrophage polarization or IRF4 for siRictor or a type-1 IFN response for siDnase2a, were not triggered by the siRNAs. Moreover, the fact that almost identical results were observed for both siRNAs further suggests the effects seen were due primarily to interruption of EIMP. Nonetheless, a future study looking at the effects of these interventions on lesional cell populations and gene expression, e.g., via single-cell sequencing, could add further insight into this issue. Further, it would, in theory, be helpful to test an intervention that directly blocked macrophage cell cycling, i.e., without blocking an upstream signaling pathway, as long as that intervention did not have its own confounding issues, e.g., blocking monocyte generation in the bone marrow, blocking inflammatory macrophage proliferation, or triggering cell senescence. The most impactful test of our central hypothesis on the pro-resolving role of EIMP was in a mouse model of atherosclerosis regression. While this model phenocopies certain plaque stabilization features in humans after marked lowering of plasma LDL, the results of our study do not address whether the pathway plays a role in atherosclerosis regression in humans or contribute to the lowering of CAD risk in this setting. Future studies comparing stable with unstable regions of human atheroma for the biochemical signature of the pathway, viewed in the context of our data showing that the pathway is present in human monocyte-derived macrophages, may add increased human relevance to these findings.
STAR METHODS
RESOURCE AVAILABILITY
Lead Contact
Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Dr. Ira Tabas (iat1@cumc.columbia.edu).
Materials Availability
This study did not generate new unique reagents.
Data And Code Availability
All data reported in this paper will be shared by the lead contact upon request.
This paper does not report original code.
Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request
EXPERIMENTAL MODEL AND SUBJECT DETAILS
Cell Lines
Jurkat (human T lymphocytes) and L-929 (mouse fibroblasts) cells were obtained from ATCC and cultured in DMEM (GIBCO) supplemented with 10% (vol/vol) heat-inactivated fetal bovine serum (HI-FBS; GIBCO), 10 U/mL penicillin, and 100 mg/mL streptomycin (Corning). Cells were cultured in 5% CO2 incubator at 37°C.
Primary Cell Culture
To culture bone marrow-derived macrophages (BMDMs), bone marrow was isolated from 8-12 week old mice (male) and cultured for 7-10 days in DMEM supplemented with 10% heat-inactivated fetal bovine serum (HI-FBS), 10 U/mL penicillin, 100 mg/mL streptomycin and 20% L-929 fibroblast-conditioned media (L-cell conditioned media). To elicit a pro-resolving macrophage phenotype, BMDMs were incubated with 10 ng/mL recombinant mouse IL-4 (Sigma-Aldrich) for 24 hours. To elicit a pro-inflammatory macrophage phenotype, BMDMs were incubated with 50 ng/mL LPS + 25 ng/mL IFNγ (Peprotech) for 24 hours. Cells were cultured in 5% CO2 incubator at 37°C
Human samples
Human macrophages were derived from peripheral human blood monocytes that were isolated from buffy coats, purchased from the New York Blood Center, of anonymous, de-identified healthy adult volunteers, with informed consent. University Institutional Review Board and Health Insurance Portability and Accountability Act guidelines were followed. Monocytes were isolated in a discontinuous gradient of Histopaque solution. After 4 hours of adhesion on 24-well plates, cells were rinsed, and medium was changed to RPMI-1640 (GIBCO) containing 10% HI-FBS, 10 U/mL penicillin and 100 mg/mL streptomycin, and 10 ng/mL of M-CSF (Peprotech). These cells were then used for experiments after 7-10 days when they were more than 75% confluent. Cells were cultured in 5% CO2 incubator at 37°C.
Mouse studies
Animal protocols were approved by Columbia University’s institutional animal care and use committee. All mice were cared for according to the NIH guidelines for the care and use of laboratory animals, and were in good general health based on appearance and activity. The mice were housed in standard cages at 22°C under a 12-12 hour light-dark cycle in a barrier facility with ad libitum access to water and food. Mertkfl/fl Lyz2cre male mice on the C57BL/6J background were generated as previously described (Cai et al., 2020; Fourgeaud et al., 2016). Male wild-type C57BL/6J and Rictorfl/fl mice (8-10 weeks/old) were obtained from Jackson Laboratory (Bar Harbor, ME) and were allowed to adapt to housing conditions in animal facility for 1 week before commencement of experiments. Littermate control mice were randomly assigned to experimental groups by investigators. Investigators were blinded for the atherosclerosis studies but were not blinded for the zymosan-induced sterile peritonitis or the dexamethasone-induced thymus injury experiments.
METHOD DETAILS
Induction of Apoptosis and Fluorescent Labeling of Jurkat Cells
Jurkat cells were irradiated with 254-nm UV lamp for 15 minutes, followed by incubation at 37°C 5% CO2 for 2-3 hours. This method typically generates 85% annexin-V+ cells. The apoptotic cells (ACs) were resuspended in 1x PBS at a concentration of 2 X107 cells/mL with 5 μL of Vybrant® DiD cell-labeling solution (Invitrogen) for 10 minutes. For efferocytosis assays involving the sequential uptake of differentially labeled ACs added at 2 different times, ACs were suspended at the same concentration, but in Diluent C (Sigma-Aldrich), and incubated for 5 minutes with 4 mL of Diluent C containing concentrated PKH67 or PKH26 membrane-intercalating dyes (Sigma-Aldrich). Cells were rinsed twice with 1x PBS and resuspended at a concentration 4 X 106 cells/mL in DMEM containing 10% heat-inactivated FBS, and then used for experiments.
siRNA-mediated Gene Silencing
Scrambled RNA control and oligo-targeted siRNAs were transfected into macrophages in 24-well plates using Lipofectamine RNAiMAX (Life Technologies) using 50 nM of siRNA per well. After 18 hours, the media were changed to DMEM/10% FBS, and the cells were incubated for an additional 30 hours.
Efferocytosis-Induced Macrophage Proliferation Assay and Flow Cytometry
BMDMs were incubated with 20 μM of EdU solution (Abeam) for 1 hour prior to the addition of DiD-labeled apoptotic Jurkat cells for 45min. After 45 minutes, the macrophages were rinsed with PBS to remove unbound ACs and incubated for 24 hours in DMEM containing 10% heat-inactivated FBS. After 24 hours, the macrophages were detached using Cell Stripper (Invitrogen), pelleted by centrifugation at 3000 x g for 3 minutes, resuspended in FACS-staining buffer (PBS containing 2% FBS and 1 mM EDTA) at a density of 1 X 106 in 200 μL, and incubated on ice with Fc Receptor Blocking Solution (anti-mouse CD16/32; Biolegend) for 30 minutes. The macrophages were then pelleted by centrifugation and resuspended in 4% paraformaldehyde. After 15 minutes, the cells were rinsed, suspended in permeabilization buffer containing 0.1% saponin, and immunostained with fluorescent-labeled antibodies for 60 minutes on ice. The macrophages were then washed with permeabilization buffer, and EdU staining was carried out using the Abeam EdU Proliferation Kit (iFluor 488) at room temperature. The macrophages were then suspended in flow tubes and analyzed on a BD FACS Canto II flow cytometer. Data analysis was carried out using FlowJo software. For other flow cytometric experiments, non-permeabilized and saponin-permeabilized macrophages were incubated with fluorescent antibodies for 60 min on ice to label cell-surface and intracellular proteins, respectively, in other experiments, the macrophages were first incubated with unlabeled primary antibodies for 2 hours, rinsed three times with FACS buffer containing 0.1% saponin, and incubated with fluorescently-conjugated secondary antibodies for an additional 2 hours. The cells were then subjected to flow cytometric analysis as above.
Cell Number Counting
Bone marrow-derived macrophages were incubated in the presence or absence of unlabeled ACs for 45 minutes at a 5:1 AC:macrophage ratio. The wells were then rinsed with PBS to remove unengulfed ACs, and the macrophages were incubated for an additional 24 hours, after which they were detached using Cell Stripper (Invitrogen) and counted using the Countess II Automated Cell Counter (Invitrogen).
CFSE Proliferation Assay
Macrophages were incubated with 5(6)-Carboxyfluorescein diacetate N-hydroxysuccinimidyl ester (CFSE) for 15 minutes, then washed with DMEM to remove non-incorporated dye. The cells were then incubated with DiD-labeled ACs for 45 min, followed by rinsing and incubation for an additional 24 hours. The macrophages were then removed from the dish, fixed with 4% PFA, resuspended in FACS buffer, and subjected to assay of CFSE fluorescence by flow cytometry. Data analysis was carried out using FlowJo software.
Assay of Single-AC and Sequential Double-AC Uptake by Control Macrophages and EIMP-Induced Proliferative Macrophages
For EIMP-induced proliferative macrophages, BMDMs were plated in 24-well plates at a density of 1.8 X 105 cells per well and incubated with unlabeled ACs for 45 minutes at a 5:1 AC:macrophage ratio. The wells were rinsed with PBS to remove unengulfed ACs, and the macrophages were incubated in culture medium for 24 hours. The cells were then incubated with PKH67-labeled ACs for 45 minutes at a 5:1 AC:macrophage ratio, followed by rinsing with PBS. One cohort was harvested for analysis (single-AC efferocytosis), while a second cohort was incubated for another 2 hours in normal cell culture media, followed by the addition of PKH27-labeled ACs (double-AC efferocytosis). After 45 minutes, the monolayers were rinsed with PBS, and then the macrophages were fixed with 4% paraformaldehyde for 15 minutes, rinsed with PBS, permeabilized with Triton X-100, and immunostained using anti-Ki67. For control macrophages, the initial 24-hour incubation with unlabeled ACs was omitted. The macrophages were imaged on a Leica epifluorescence microscope (DMI6000B), and the images were analyzed using Imaris 9.5 quantification software for Ki67− and Ki67+ macrophages containing PKH67 alone or both PKH67 and PKH27.
Nuclear EdU Incorporation Assay
Live Jurkat cells were incubated with 20 μM EdU (Abeam) for 2 hours, washed three times with PBS, labeled with DiD cell membrane-labeling solution, and then rendered apoptotic as above. Macrophages were then incubated with the EdU-labeled ACs for 45mins, followed by washing twice with PBS and then incubation for 18 hours. The cells were then fixed with 4% PFA, macrophage nuclei were counterstained with DAPI, and images were taken on a Leica epifluorescence microscope (DMI6000B). Image analysis was conducted using Imaris 9.5 quantification software to quantify the percentage of macrophages with nuclear EdU staining not associated with DiD+ AC material.
Assay of TGFβ and IL-10 by EIMP-Induced Proliferative Macrophages
BMDMs were plated in 24-well plates at a density of 1.8 X 105 cells per well and incubated with EdU for 1 hour prior to the addition of DiD-labeled ACs at a 5:1 AC:macrophage ratio. After 45 minutes, the macrophages were rinsed with PBS and incubated overnight in DMEM containing 10% FBS and 2 μL/mL Protein Transport Inhibitor Cocktail (eBioscience; Invitrogen) to prevent exosomal release of secreted proteins. The macrophages were then rinsed, detached, pelleted by centrifugation, resuspended in FACS buffer containing Fc receptor blocker, and incubated for 30 minutes. Cells were then pelleted and resuspended in 4% paraformaldehyde for 15 minutes, followed by permeabilization with 0.1% saponin. Intracellular staining was carried out with fluorescent antibodies against TGFβ and IL-10 for 60 minutes on ice. The cells were then rinsed with permeabilization buffer, stained at room temperature with EdU using the Abeam EdU Proliferation Kit (iFluor 488), resuspended in FACS buffer, and analyzed on a BD FACS Canto II flow cytometer. Data analysis was carried out using FlowJo software.
Zymosan-Induced Peritonitis and Peritoneal Uptake of Labeled ACs
EdU (200 μg/mouse) was injected i.p., and 24 hours later sterile peritonitis was induced by a single 500-μL i.p. injection of 1 mg zymosan A (Sigma-Aldrich). After 24 or 48 hours, the mice were euthanized, and peritoneal lavage fluid was collected with using 3 mL of PBS. The lavage fluid was passed through a 40-μm strainer and the cells were pelleted by centrifugation and resuspended in FACS buffer containing Fc receptor blocker. After 30 minutes incubation on ice, the cells were incubated for 2 hours with fluorescently conjugated anti-F4/80 antibody (BioLegend). The cells were washed with then FACs buffer three times and suspended in permeabilization buffer containing anti-Ly-6G/Ly-6C (Gr-1) (Biolegend) to stain engulfed apoptotic neutrophils. After incubation overnight. To distinguish between external and internalized neutrophils in the macrophages, cell-surface staining with anti-F4/80 and anti-Gr-1 of non-permeabilized cells was used. After an overnight incubation, the cells were stained at room temperature for EdU using the Abeam EdU Proliferation Kit (iFluor 488). The cells were then washed twice and resuspended in FACs buffer and placed into flow tubes for analysis on a BD FACs Cantos II flow cytometer. Data analysis was carried out using FlowJo software.
Bone Marrow Transplant
Eight-week old male C57BL/6J mice were irradiated using 1,000 rads from a 137 Cesium GammaCell source. The same day, bone marrow cells were harvested from a Rictorfl/fl mouse and incubated with 5 μM of TAT-CRE Recombinase (Millipore) for 30 minutes to delete the floxed Rictor gene or vehicle control. The Rictor-deleted control bone marrow cells were then rinsed twice with PBS, resuspended at 2.5 X 106 cells, and injected via tail vein into the irradiated C57BL/6J recipient mice. Recipient mice were given acidic water containing 10 mg/mL neomycin for 3 weeks following the bone marrow transplant. After 4 weeks, the thymus efferocytosis assay described below was conducted.
Thymus Assays
Mice transplanted with control or Rictor-deleted bone marrow were injected i.p. with 250 μL PBS containing 250 μg dexamethasone (Sigma-Aldrich) dissolved in DMSO. Eighteen hours after injection, the mice were euthanized, and thymi were harvested and weighed. One lobe of the thymus was mechanically dissociated, and cells were counted to determine total cell number. Cells were then stained with annexin-V and anti-F4/80, followed by flow cytometry to determine the number of thymic ACs and macrophages. The other lobe of the thymus was fixed in 4% paraformaldehyde, paraffin-embedded, and sectioned, followed by staining of 5-μm sections with TUNEL reagent (Roche), anti-Mac2 (Cedarlane), anti-Ki67 (Abeam), and anti-c-Myc (ThermoFisher), anti-Bhlhe40 (ThermoFisher), and anti-c-Maf (ThermoFisher). Fluorescence microscopic imaging was use to quantify Mac2+ Ki67+ macrophages with cytoplasmic TUNEL (cTUN+), indicative of proliferation in efferocytic macrophages. Also, efferocytosis was assessed by quantifying the ratio cTUN+ cells associated with Mac2+ macrophages to non-macrophage-associated (“free’) cTUN+ cells.
siRictor and siDnase2a S2P-Nanoparticles
50:50 PLGA, with inherent viscosity range of 0.55 to 0.75 dl/g and size of 43.4 kDa, was purchased from LACTEL Absorbable Polymers by DURECT Corporation (catalog # B6013-2). DSPE-PEG (3 kDa) was obtained from Avanti Polar Lipids (catalog # 880320), and DSPE-PEG-Mal (PEG molecular weight 3.4 kDa) was purchased from Nanocs Inc. (catalog # PG2-DSML-3k). CRTLTVRKC peptide was from GLS Biochem Systems Inc (catalog # 652358). The cationic lipid G0-C14 and targeted lipid-PEG (DSPE-PEG-S2P) were synthesized according to our previous reports (Kamaly et al., 2013; Tao et al., 2020). Using siRictor and siDnase2a, the targeted siRNA-loaded S2P50 NPs were then prepared using an optimized nano-precipitation method modified from our previous report (Tao et al., 2020). Specifically, the interaction time between G0-C14 and siRNAs was increased from 10 seconds to 30 seconds, together with gentle, repeated mixing with a pipette, to enhance more effective complexation; and the magnetic stirring rpm was increased from 1000 to 1200, and the preparation time was increased from 1 hour to 1.5 hours, to enable more effective volatilization of organic solvent. All procedures were conducted under aseptic conditions to avoid contamination.
Tissue Collection and Lesion Analysis
Ten-week-old male Ldlr−/− mice were placed on Western diet (Envigo, TD 88137) for a total of 16 weeks. One cohort was harvested at that time (baseline), and other cohorts (regression) were injected with a helper-dependent adenovirus containing the human Ldlr gene (HDAd-LDLR) and simultaneously placed a chow diet for an additional five weeks. This virus is a non-integrating vector that primarily targets the liver and restores expression of the Ldlr in hepatocytes to levels sufficient to markedly reduce circulating cholesterol in Ldlr−/− mice. For the regression cohorts, the mice were administered S2P-nanoparticles containing control scrambled RNA (Scr), siRictor, or siDnase2a at the start of the regression period. The nanoparticles were administered twice a week during the five-week regression period. Upon sacrifice, mice were perfused with PBS through left ventricular cardiac puncture, and aortic roots were collected and processed for histology. Sections were stained with hematoxylin and eosin for morphometric lesion analysis. Atherosclerotic lesion area, defined as the space from the internal elastic lamina to the lumen, was quantified by taking the average of 6 sections spaced 30-μm apart, beginning at the base of the aortic root. Boundary lines were drawn around these regions, and the area measurements were obtained by image analysis software. A 3,000-μm2 threshold cut-off was applied to acellular regions to calculate areas of necrosis. Thickness of the collagen-rich fibrous cap was assessed in picrosirius red-stained sections, with the width of the cap measured at the lesional midpoint and both shoulder regions and then averaged and quantified as the ratio of mean collagen cap thickness to lesion area. Fasting blood glucose levels were measured using ONETOUCH Ultra after food was withdrawn for 18h. Total plasma cholesterol was measured using a WAKO Diagnostics kit. Complete blood cell counts, including leukocyte differential, were obtained using a FORCYTE Hematology Analyzer (Oxford Science).
Tissue Immunohistochemistry and Immunofluorescence Microscopy
Paraffin-embedded specimens were sectioned, de-paraffinized with xylene, and rehydrated in decreasing concentrations of ethanol. Antigen retrieval and unmasking were achieved by incubation with citrate buffer (1:100 dilution), followed by pressure cooking for 10 minutes. After cooling, the sections were incubated with TUNEL reagent for 60 minutes at 37°C and washed 3 times with PBS. The sections were then incubated for 60 minutes with blocking solution, consisting of PBS containing 2% bovine serum albumin (BSA). The sections were then incubated overnight at 4°C with anti-Mac2 (1:10,000), anti-Ki67 (1:200), anti-Myc (1:200), anti-Bhlhe40 (1:200), anti-c-Maf (1:200), anti-Rictor (1:100), anti-MerTK (1:200), anti-Arg1 (1:200), anti-IL-6 (1:100), anti-CXCL10 (1:100), anti-IRF4 (1:200), anti-ALOX15 (1:200), and anti-SR-BI (1:200) antibodies. On the following day, the sections were washed in PBS and incubated with fluorescently-labeled secondary antibodies for 2 hours, washed, dried, and counterstained with DAPI. Images were taken using a Leica epifluorescence microscope (DMI6000B) or, for spinning disk confocal microscopy, a Nikon Ti Eclipse inverted microscope. Image analysis was completed using Imaris 9.5 quantification software.
Immunoblotting
BMDMs were lysed in 2X Laemmli lysis buffer (Bio-Rad) containing 50 mM β-mercaptoethanol. The cell lysates were heated at 95°C for 10-15 minutes, separated on 4%-20% SDS-PAGE gradient gels (Invitrogen) at 150 V for 1.5 hours, and electro-transferred to nitrocellulose membranes at 100V for 2-3 hours. For larger proteins, such as Rictor (250kDa), electro-transfer to nitrocellulose membranes was carried out overnight at 23V. The membranes were incubated with 5% milk for 1 hour followed by rinsing in Tri-buffered saline containing Tween-20 (TBST) and incubation overnight at 4°C with primary antibodies in PBS containing 1% BSA. Primary antibodies were detected with using HRP-conjugated secondary antibodies (Pierce). Densitometry was performed using ImageJ software.
Quantitative Real Time PCR
RNA was extracted from BMDMs using the PureLink RNA Mini kit (Thermo Fisher Scientific). The quality and concentration of RNA was determined by absorbance at 260 and 280nm using a NanoDrop spectrophotometer (Thermo Fisher Scientific). Complementary DNA was synthesized from 0.5-1 μg of RNA, which had a 260/280 ratio of >1.8, using oligo (dT) and Superscript II (Applied Biosystems). Quantitative RT-PCR was performed using a 7500 Real-Time PCR system (Applied Biosystems) and SYBR Green Master Mix reagents (Applied Biosystems).
Electroporation of Overexpression Plasmids
Macrophages were transfected with Maf1 plasmid via electroporation (Invitrogen). Maf1 plasmid DNA at (0.75 μg) was added directly to 5 X 105 pelleted macrophages. Cells and DNA were resuspended in 150 μL of R-buffer (Invitrogen) and subjected to electroporation at 1550 mV with 10 ms intervals for 2 pulses. The macrophages were then plated directly into 24-well plates and experiments were conducted two days later.
QUANTIFICATION AND STATISTICAL ANALYSIS
Data were tested for normality using either the D’Agostino-Pearson or Shapiro-Wilk test, and statistical significance was determined using GraphPad Prism software. P-values for normally distributed data were calculated using either the Student’s t test for two groups or one-way ANOVA with Fisher’s Least Significant Difference (LSD) post-hoc analysis when there were three or more groups. P-values for non-normally distributed data were calculated using the Mann-Whitney rank sum test or the uncorrected Dunn’s test. Data are shown as mean values ± SEM. Graphical representation of differences that are statistically significant at p ≤ 0.05 are signified by different letters. Data marked by the same letter are not statistically significant.
Supplementary Material
KEY RESOURCES TABLE
| REAGENT or RESOURCE | SOURCE | IDENTIFIER |
|---|---|---|
| Antibodies | ||
| Rabbit anti-p-Akt (S473) | Cell Signaling Technology | Cat# 4060S; RRID: AB_2315049 (1:2000 dilution) |
| Rabbit anti-Akt | Cell Signaling Technology | Cat# 4691S; RRID: AB_915783 (1:2000 dilution) |
| Rabbit anti-Rictor | Cell Signaling Technology | Cat# 2114S; RRID: AB_2179963 (1:2000 dilution) |
| Rat anti-Mac2 | Cedarlane | Cat# CL8942AP; RRID:AB_10060357 (1:10,000 dilution) |
| Rabbit anti-c-Myc | Proteintech | Cat# 10828-1-AP; RRID: AB_2148585 (1:200 dilution) |
| Rabbit anti-β-actin-HRP | Cell Signaling Technology | Cat# 5125S; RRID: AB_1903890 (1:5000 dilution) |
| Mouse anti-c-Myc | Invitrogen | Cat# MA1-980; RRID: AB_558470 (1:200 dilution) |
| Rabbit anti-c-Myc | Cell Signaling Technology | Cat# 18583S; (1:2500 dilution) |
| Rabbit anti-DNA-PKcs | Invitrogen | Cat# MA5-32192; RRID: AB_2809479 (1:200 dilution) |
| Rabbit anti-Bhlhe40 | Invitrogen | Cat# PA1-16546; RRID: AB_2065348 (1:200 dilution) |
| Rabbit anti-cMaf | Invitrogen | Cat# PA5-23179 RRID: AB_2540705 (1:200 dilution) |
| Rabbit anti-Ki67 | Abcam | Cat# ab16667; RRID: AB_302459 (1:200 dilution) |
| Sheep anti-Ki67 | R&D Systems | Cat# AF7649; RRID: AB_2687500 (1:200 dilution) |
| Rabbit anti-Irf4 | Invitrogen | Cat# 11247-2-AP; RRID: AB_2264940 (1:200 dilution) |
| Rabbit anti-Alox15 | Bioss | Cat# bs-6505R; RRID: AB_11051537 (1:200 dilution) |
| Rabbit anti-Phospho-p44/42 MAPK (Erk1/2) (Thr202/Tyr204) | Cell Signaling Technology | Cat# 4370S; RRID: AB_2315112 (1:200 dilution) |
| Rat anti-mouse F4/80 (PE/Cy7) | Biolegend | Cat# 123113; RRID:AB_893490 (1:100 dilution) |
| Rat anti-mouse IL-10 (PE) | Invitrogen | Cat# 12-7101-41 RRID: AB_10669561 (1:100 dilution) |
| Rabbit anti-Cxcl10/IP-10 | Thermo Fisher Scientific | Cat# MA5-32674 RRID:AB_2809951 (1:100 dilution) |
| Goat anti-IL-6 | R&D Systems | Cat# AF-406-NA RRID:AB_354478 (1:200 dilution) |
| Rabbit anti-phospho-DNA-PKcs (Thr 2609) | Invitrogen | Cat# PA5-105749 RRID:AB_2817148 (1:200 dilution) |
| Rabbit anti-Rictor | Novus | Cat# NB100-612 RRID:AB_10000886 |
| APC anti-mouse LAP (TGF-β1) | Biolegend | Cat# 141406 RRID: AB_10898159 (1:100 dilution) |
| APC anti-mouse Ly-6G/Ly-6C (Gr-1) | Biolegend | Cat# 108412 RRID: AB_313377 (1:100 dilution) |
| Rabbit IgG | Sigma-Aldrich | Cat# PP64B; RRID:AB_97852 |
| Goat anti-mouse (HRP) | Invitrogen | Cat# 32230 (1:2000 dilution) |
| Goat anti-rabbit (HRP) | Invitrogen | Cat# 32260 (1:2000 dilution) |
| Goat anti-mouse (AF488) | Invitrogen | Cat# A11001; RRID:AB_2534069 (1:200 dilution) |
| Goat anti-mouse (AF555) | Invitrogen | Cat# A28180; RRID:AB_2536164 (1:200 dilution) |
| Goat anti-rat (AF488) | Invitrogen | Cat# A11006; RRID:AB_141373 (1:200 dilution) |
| Goat anti-rabbit (AF488) | Invitrogen | Cat# A11034 (1:200 dilution) |
| Goat anti-rabbit (AF555) | Invitrogen | Cat# A21428; RRID:AB_141784 (1:200 dilution) |
| Chicken anti-rabbit (AF647) | Invitrogen | Cat# A-21443 RRID: AB_2535861 (1:200 dilution) |
| Goat anti-Rat (AF647) | Invitrogen | Cat# A21247; RRID:AB_141778 (1:200 dilution) |
| Pacific Blue anti-F4/80 | Biolegend | Cat# 123123; RRID:AB_893487 (1:100 dilution) |
| Chemicals, Peptides, and Recombinant Proteins | ||
| Dulbecco’s Modified Eagle Media (DMEM) | Corning | Cat# 10-013-CV |
| Roswell Park Memorial Institute (RPMI) 1640 Media | Corning | Cat# 10-040-CV |
| Opti-MEM | GIBCO | Cat# 31985-070 |
| 1X HBSS | Corning | Cat# 21-022-CV |
| 1X PBS | Corning | Cat# 21-040-CV |
| CellStripper | Corning | Cat# 25-056-CI |
| Heat-Inactivated Fetal Bovine Serum | GIBCO | Cat# 10438-026 |
| Penicillin/Streptomycin | Corning | Cat# 30-002-CI |
| Human Macrophage Colony Stimulating Factor (M-CSF) | Peprotech | Cat# 300-25 |
| HISTOPAQUE-1077 | Sigma-Aldrich | Cat# 10771-100ML |
| 2-Well Glass Slides | Thermo Scientific | Cat# 155380 |
| 4-Well Glass Slides | Thermo Scientific | Cat# 155383 |
| 8-Well Glass Slides | Thermo Scientific | Cat# 155411 |
| Novex 4-20% Tris-Glycine Mini Gels, 15-well | Invitrogen | Cat# XP04205BOX |
| 2X Laemmli Buffer | Bio-Rad | Cat# 1610747 |
| PKH67 Fluorescent Cell Linker | Sigma-Aldrich | Cat# PKH67GL-1KT |
| PKH26 Fluorescent Cell Linker | Sigma-Aldrich | Cat# PKH26GL-1KT |
| Cell-Vue Claret Fluorescent Cell Linker | Sigma-Aldrich | Cat# MINCLARET-1KT |
| Diluent C | Sigma-Aldrich | Cat# CGLDIL |
| Interleukin-4 | Sigma-Aldrich | Cat# SRP3211 |
| Interferon-γ (IFN-γ) | Peprotech | Cat# 315-05 |
| Cytochalasin D | Sigma-Aldrich | Cat# C8273 |
| U0126 | Tocris Bio-Techne | Cat# 1144 |
| DMSO | Sigma-Aldrich | Cat# D2650 |
| β-mercaptoethanol | Bio-Rad | Cat# 1610710 |
| Citrate-dextrose solution | Sigma-Aldrich | Cat# C3821 |
| Recombinant mouse Gas6 protein | R&D Systems | Cat# 986-GS |
| pHrodo Green | Thermo Scientific | Cat# P35373 |
| pHrodo Red | Thermo Scientific | Cat# P35372 |
| CMLD-2 | Sigma-Aldrich | Cat# 538339 |
| Recombinant HuR | Novus Biologicals | Cat# H00001994-P01 |
| Bafilomycin A1 | Sigma-Aldrich | Cat# B1793 |
| Dexamethasone | Calbiochem | Cat# 265005 |
| Actinomycin D | Sigma-Aldrich | Cat# A1410 |
| Annexin V (FITC) | BD Biosciences | Cat# 560931 |
| Zymosan A | Sigma-Aldrich | Cat# Z4250 |
| Lipofectamine RNAiMax | Life Technologies | Cat# 13778-150 |
| Neomycin | Sigma-Aldrich | Cat# N1142 |
| Polymyxin B | Sigma-Aldrich | Cat# P4932 |
| 40 μm Nylon Cell Strainers | BD Falcon | Cat# 352340 |
| Power SYBR Green PCR Master Mix | Applied Biosystems | Cat# 4367659 |
| EdU Proliferation Assay Kit | Abcam | Cat# ab219801 |
| AFDye 488 Azide | Click Chemistry Tools | Cat# 1275-1 |
| AFDye 555 Azide | Click Chemistry Tools | Cat# 1287-1 |
| Copper (II) Sulfate Solution | Sigma-Aldrich | Cat# C2284-25ML |
| (+)-Sodium L-Ascorbate | Sigma-Aldrich | Cat# A4034-100G |
| BD BD GolgiStop | Thermo Scientific | Cat# BDB554724 |
| 50:50 PLGA (inherent viscosity range of 0.55 to 0.75 dl/g, 43.4 kDa) | LACTEL Absorbable Polymers by DURECT Corporation | Cat# B6013-2 |
| DSPE-PEG (MW, 3 kDa) | Avanti Polar Lipids | Cat# 880320 |
| DSPE-PEG-Mal (PEG molecular weight, 3.4 kDa) | Nanocs Inc. | Cat# PG2-DSML-3k |
| S2P peptide (CRTLTVRKC) | GLS Biochem Systems Inc | Cat# 652358 |
| ethylenediamine core-poly (amidoamine) (PAMAM) generation 0 dendrimer | Sigma-Aldrich | Cat# 412368 |
| 1,2-epoxytetradecane | Sigma-Aldrich | Cat# 260266 |
| REAGENT or RESOURCE | ||
| 0.45-mm nitrocellulose membranes | Bio-Rad | Cat# 1620115 |
| Hoechst 33342 | Thermo Scientific | Cat# 62249 |
| Lipofectamine RNAiMax | Life Technologies | Cat# 13778-150 |
| Perm buffer II | BD Biosciences | Cat# 558052 |
| Critical Commercial Assays | ||
| PureLink RNA Mini Kit | Thermo Fisher Scientific | Cat# 12183025 |
| TUNEL Kit | Roche | Cat# 12156792910 |
| Supersignal West Pico Chemiluminescence Kit | Thermo Fisher Scientific | Cat# 34080 |
| Total Cholesterol Kit | Wako Diagnostics | Cat# 999-02601 |
| Experimental Models: Cell Lines | ||
| Human: Jurkat cells | ATCC | ATCC TIB-152 |
| Mouse: L-929 Fibroblast cells | ATCC | ATCC CCL-1 |
| Mouse: Bone Marrow-Derived Macrophage cells | This paper | N/A |
| Mouse: Elicited Peritoneal Macrophage cells | This paper | N/A |
| Human: Peripheral Blood Monocyte-Derived Macrophage cells | This paper | N/A |
| Sheep Red Blood Cells 10% washed pooled cells | Rockland Immunochemicals, Inc. | R405-0050 |
| Experimental Models: Organisms/Strains | ||
| Mouse: C57BL/6J | The Jackson Laboratory | JAX: 000664 |
| Mouse: Ldlr−/−: C57BL/6J | The Jackson Laboratory | JAX: 002207 |
| Mouse: Rictorfl/fl:C57BL/6J | The Jackson Laboratory | JAX: 020649 |
| Mouse: Lyz2cre: C57BL/6J | Clausen et al., 1999 | N/A |
| Mouse: MerTKfl/fl: C57BL/6J | Fourgeaud et al., 2016 | N/A |
| Oligonucleotides | ||
| ON-TARGETplus non-targeting pool | GE Healthcare Dharmacon | D-001810-10-05 |
| Mouse: ON-TARGETplus Rubicon siRNA | GE Healthcare Dharmacon | L-172564-00-0005 |
| Mouse: IDT Dnase2a DsiRNA | Integrated DNA Technologies | mm.Ri.Dnase2a.13.1 |
| Mouse: IDT Rictor DsiRNA | Integrated DNA Technologies | mm.Ri.Rictor.13.1 |
| Mouse: IDT PRKDC DsiRNA | Integrated DNA Technologies | mm.Ri.Prkdc.13.1 |
| Mouse: IDT Bhlhe40 DsiRNA | Integrated DNA Technologies | mm.Ri.Bhlhe40.13.1 |
| siScramble sense: 5′-CUUACGCUGAGUACUUCGATT-3′, antisense: 5′-UCGAAGUACUCAGCGUAAGTT-3′ | Horizon Discovery Ltd. | N/A |
| Mouse: cMyc siRNA | Sigma-Aldrich | SASI_Mm01_00157474 |
| Mouse: Dnase2a Forward AAGCCCTGAGCTGCTATGG |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Dnase2a Reverse ATACGTCAGTCCCTTTGGAGTA |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Hprt Forward TCAGTCAACGGGGGACATAAA |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Hprt Reverse GGGGCTGTACTGCTTAACCAG |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Rictor Forward ACAGTTGGAAAAGTGGCACAA |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Rictor Reverse GCGACGAACGTAGTTATCACCA |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Prkdc Forward AAACCTGTTCCGAGCTTTTCTG |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Prkdc Reverse TCTCAATCTGAGGACGAATTGC |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Rbcn Forward CAGGGTGTAGTGCATGGTTCT |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Rbcn Reverse CCGCCAAGATCCATTCCCG |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Bhlhe40 Forward ACGGAGACCTGTCAGGGATG |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Bhlhe40 Reverse GGCAGTTTGTAAGTTTCCTTGC |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Maf Forward GGAGACCGACCGCATCATC |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Maf Reverse TCATCCAGTAGTAGTCTTCCAGG |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Myc Forward TGACCTAACTCGAGGAGGAGCTGGAA |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Myc Reverse AAGTTTGAGGCAGTTAAAATTATGGCT |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: G6pdx Forward CACAGTGGACGACATCCGAAA |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: G6pdx Reverse AGCTACATAGGAATTACGGGCAA |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Dnase1 Forward CTCAATCGGTGGGTGACAGTA |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Mouse: Dnase1 Reverse TGTCCCTGGATAAAGGAAACCA |
PrimerBank | www.pga.mgh.harvard.edu/primerbank |
| Recombinant DNA | ||
| cMaf Rat tagged ORF cDNA expression plasmid | Origene | Cat# RR209464 |
| HDAd-LDLR | Baylor College of Medicine | Willecke et. al., 2015 |
| Software and Algorithms | ||
| NIS-Elements | Nikon | Advanced Research |
| Leica Application Suite | Leica | Advanced Fluorescence |
| Imaris 9.5.0 | Oxford Systems | |
| ImageJ | NIH | www.imagej.nih.gov/ij |
| FIJI | Schindelin et al., 2012 | www.fiji.sc |
| PRISM | GraphPad Software | Version 6 |
| FlowJo | FlowJo, LLC | Version 10 |
| Other | ||
| Genotyping Service | Genetyper | www.genetyper.com |
| Salmon Sperm DNA Ready-to-Use Solution | Rockland Immunochemicals, Inc. | MB-103-0025 |
| Mouse Diet: High-Fat Western Diet | Envigo | Cat# TD.88137 |
| Helper-Dependent Adenovirus Cloning and Packaging Services | Baylor College of Medicine | N/A |
Apoptotic cell degradation after macrophage efferocytosis induces proliferation
Apoptotic cell derived nucleotides trigger a DNA-PK—mTorc2—Myc proliferation pathway
Proliferating efferocytic macrophages are pro-resolving in vitro and in vivo
Genetic silencing of the proliferation pathway hinders atherosclerosis regression
ACKNOWLEDGMENTS
We thank Dr. Carla Rothlin for providing Mertkfl/fl mice and Drs. Theresa Swayne and Laura Munteanu for assistance with confocal imaging. The confocal microscopy work in this study was conducted in the Confocal and Specialized Microscopy Shared Resource of the Herbert Irving Comprehensive Cancer Center at Columbia University, supported by NIH grants P30CA013696 and S10RR025686. Flow cytometry was conducted in the Columbia Center for Translational Immunology Core Facility, funded by NIH grants P30CA013696 and S10OD020056 and S10RR027050. Co-authors were supported by the following NIH grants: T32 5T32HL007343-42 (to B.D.G.); K99 HL145131 (to A.Y. Jr.); P20 GM121307 (to C.G.K.); R01 HL127464 (to I.T. and J.S.); and R01 HL087123, and R35 HL145228 (to I.T.). This work was also supported by an American Heart Association post-doctoral fellowship grant (20POST35210962 to C.K.), Harvard Medical School (HMS)/Brigham and Women’s Hospital (BWH) Khoury Innovation award (122829 to W.T.), and an Assistant Professor start-up package from HMS/BWH Department of Anesthesiology, Perioperative and Pain Medicine (to W.T.).
Footnotes
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DECLARATION OF INTERESTS
The authors declare no competing interests.
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