Time-Series Transcriptome Analysis Reveals the miR-27a-5p-Ppm1l Axis as a New Pathway Regulating Macrophage Alternative Polarization After Myocardial Infarction

Abstract

Background: Timely differentiation of monocytes into M2-like macrophages is important in the cardiac healing process after myocardial infarction (MI), but molecular mechanisms governing M2-like macrophage differentiation at the transcriptional level after MI have not been fully understood.

Methods and Results: A time-series microarray analysis of mRNAs and microRNAs in macrophages isolated from the infarcted myocardium was performed to identify the microRNAs involved in regulating the process of differentiation to M2-like macrophages. Correlation analysis revealed 7 microRNAs showing negative correlations with the progression of polarity changes towards M2-like subsets. Next, correlation coefficients for the changes in expression of mRNAs and miRNAs over time were calculated for all combinations. As a result, miR-27a-5p was extracted as a possible regulator of the largest number of genes in the pathway for the M2-like polarization. By selecting mouse mRNAs and human mRNAs possessing target sequences of miR-27a-5p and showing expression patterns inversely correlated with that of miR-27a-5p, 8 potential targets of miR-27a-5p were identified, including Ppm1l. Using the mouse bone marrow-derived macrophages undergoing differentiation into M2-like subsets by interleukin 4 stimulation, we confirmed that miR-27a-5p suppressed M2-related genes by negatively regulating Ppm1l expression.

Conclusions: Ppm1l and miR-27a-5p may be the key molecules regulating M2-like polarization, with miR-27a-5p inhibiting the M2-like polarization through downregulation of Ppm1l expression.

Cardiovascular diseases, including myocardial infarction (MI), have been associated with high levels of mortality and morbidity worldwide.^1,2 Adult cardiomyocytes lack the regenerative capacity, so prolonged ischemia causes death of the affected myocardium leading to a subsequent maladaptive cardiac remodeling. Although recent advances in revascularization techniques have led to a steady improvement of the post-MI mortality rates, post-infarction heart failure imposes a growing socioeconomic burden as patients survive with progressive left ventricular dysfunction due to cumulative ischemic myocardial damage, highlighting the need for better understanding of the pathophysiology of MI.

Cardiac healing after MI is a complex process involving a wide variety of immune-mediated molecular and cellular cascades, which result in the replacement of the necrotic myocardium by the granulation tissue that is transformed to a collagen-based scar tissue.^3–10 Among the immune cells accumulating at the site of infarction, macrophages make a decisive contribution to the healing process. There are at least two subsets of macrophages with distinct functions and patterns of accumulation after a tissue injury. M1-like macrophages are inflammatory and show early accumulation after a tissue injury, whereas alternatively activated M2-like macrophages support tissue repair at a later stage.^3,11 Recent experimental studies have shown that an excessive accumulation of inflammatory macrophages leads to an irreversible cardiac damage,^12–14 whereas an expansion of the M2-like macrophages leads to an improved cardiac function and survival following MI.^15–18 Thus, elucidation of the molecular pathways involved in promoting the accumulation of reparative M2-like macrophages at sites of myocardial ischemia may lead to the identification of novel targets for therapeutic intervention after MI.

Recently, the role of non-coding RNAs, including micro RNAs (miRNAs), in regulation of multiple important pathways has attracted considerable attention. The miRNAs are highly conserved short non-coding RNAs.¹⁹ In eukaryotic cells, the miRNAs constitute a major regulatory gene family,^20,21 and are involved in numerous biological processes by modifying the expression of target genes at the post-transcriptional level.²² Some miRNAs have been reported to play a role in regulating the polarization of macrophages,^19,23 but the influence of a large number of these RNAs on this biological process remains unknown.

Accordingly, we performed a time-series transcriptome analysis of the cardiac macrophages, which revealed that the inhibition of the release of miRNA 27a-5p (miR-27a-5p) was required for the macrophage polarization towards an M2-like phenotype in the infarcted myocardium.

Methods

Ethics Approval

This study conformed to the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health (publication No. 85-23, revised 1996), and was approved by the Institutional Animal Care and Use Committee at the Keio University School of Medicine (12094).

Macrophage Preparation for Transcriptome Analysis

The detailed methods for macrophage preparation have been previously reported.¹ Briefly, after a 70–37% Percoll gradient centrifugation, the CD45⁺ leukocytes were enriched either within the 37%/70% interface or the 70% Percoll solution. Single-cell suspensions from the freshly obtained leukocyte-enriched fractions were analyzed for CD11b and CD45 expressions using flow cytometry. The CD45⁺CD11b⁺ myeloid cells were divided into the F4/80⁺ macrophages and the Ly-6G⁺ neutrophils, with the F4/80⁺ macrophages further divided based on M1-like (classically activated macrophages, CD206^low) and M2-like (alternatively activated macrophages, CD206^high) polarity. The M1-like macrophages were the predominant macrophages in the early stages of the post-MI healing. M2 macrophages were the predominant cell type in the sham-operated heart and increased in number at the later stage of the post-MI healing. Although the microarray analysis was conducted with only one plate (n=1, number of plates scanned per time-points for mRNA and miRNA) due to limited resources available, macrophages were collected from multiple mice (sham: n=11; MI day 1: n=5; MI day 3: n=3; MI day 7: n=2; MI day 14: n=2).

Mouse Bone Marrow-Derived Macrophages (BMDM) Culture

Mouse BMDM were harvested by using a previously published method,²⁴ and were cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% FBS and 10 ng/mL M-CSF. For the M2-like polarization experiment, BMDM were kept serum-free for 12 h and were stimulated with 15 ng/mL interleukin 4 (IL4) for 24 h. An M2-like polarization with this method was confirmed by flow cytometry and quantitative polymerase chain reaction (qPCR). Both IL4 and M-CSF were purchased from PeproTech (NJ, USA, #315 for M-CSF and #214 for IL4).

Overexpression and Knock-Down of Micro RNA

The transfection was performed with a final concentration of 100 nmol/L of either Pre-miR, miR inhibitor or its control according to the manufacturer’s instructions. BMDM was kept serum-free for 12 h after transfection was completed and was stimulated with 15ng/mL IL4 for 24 h before harvesting RNA for measurement.

Knock-Down Analysis of Ppm1l

Transfection was conducted with a final concentration of 30 nmol/L according to the manufacturer’s instructions. BMDM was kept serum-free for 12 h after transfection was completed and was stimulated with 15 ng/mL IL4 for 24 h before harvesting RNA for measurement.

Co-Expression of miRNA and Ppm1l

The construct of the Ppm1l-expressing plasmid is shown in Supplementary Figure 1 and the sequence of Ppm1l in the plasmid is shown in the Supplementary File. BMDM were transfected with the miR-27a-5p precursor and the Ppm1l-expressing plasmid at the same time. The final concentrations were 100 nmol/L and 15 nmol/L respectively. BMDM were kept serum-free for 12 h after transfection was completed and were stimulated with 15 ng/mL IL4 for 24 h before harvesting RNA for measurement.

Statistical Analysis

For wet-lab experiments, values are presented as the mean±SEM. Comparisons between groups were conducted using the analysis of variance (ANOVA) followed by a pairwise-t-test with the Benjamini and Hochberg correction²⁵ for multiple testing for multigroup comparison and a paired-t-test for 2 group comparison. A 2-tailed P<0.05 indicated statistical significance. Statistical analysis was performed with the R version 3.5.1.

Results

Identification of the miRNAs Regulating the M2-Like Polarization of the Macrophages

In order to identify the miRNAs involved in regulating the M2-like polarization of the macrophages that infiltrate the mouse myocardium, we performed a transcriptomic analysis using a RNA microarray on macrophages harvested from the infarct region of the heart at various time points after MI. The detailed methods for macrophage preparation have been previously reported and are explained in the Supplementary File.³ We determined the Pearson’s correlations coefficient of the changes in the miRNA expression with changes in the numbers of the M1-like and the M2-like macrophages over time (Figure 1A). The miRNAs potentially regulating the M2-like polarization of the macrophages were selected as those showing either a positive correlation or an inverse correlation (≥0.8 or ≤−0.8) with the percentage of M2-like macrophages over time and an opposite correlation coefficient value with the change in the percentage of M1-like macrophages. This analysis revealed 7 miRNAs showing a negative correlation with the percentage of the M2-like macrophages (Figure 1A inset). For example, the expression of miR-27a-5p showed a strong inverse correlation with the change in the percentage of the M2-like macrophages over time (r=−0.8), but little correlation to the change in the percentage of the M1-like macrophages (r=0.075). None of the miRNAs had a positive correlation with the percentage of the M2-like macrophages and a negative correlation coefficient value with the percentage of the M1-like macrophages.

Figure 1.

Extraction of micro RNAs (miRNAs) potentially regulating M2-like polarization from transcriptome analysis. (A) Correlation analysis of miRNA expressions and the relative numbers of M2-like macrophages and M1-like macrophages. The inset shows an enlargement of the area displaying a strong negative correlation with M2-like macrophages (r>0.8) and positive correlation coefficient value for M1-like macrophages. (B) Plot of the number of mRNAs with high correlation coefficient with the miRNAs vs. fold changes of miRNA expression. The blue area indicates miRNAs showing a high number of mRNA correlating with the miRNAs (>7,500 mRNAs) and a marked change of expression (>1.5-fold). (C) Relative expression of candidate miRNA. (D) Scatter plot showing miR-27a-5p expression vs. the number of M2-like macrophages relative to the total number of macrophages. Note that the point indicated with a black triangle is overlapping 2 points.

Next, Pearson’s correlation coefficients were calculated for all combinations of the changes in expressions of these 7 miRNAs and the mRNAs in the microarray. We assumed that the mRNAs in the pathway that was regulated by the miRNA should correlate with it. Therefore, miRNA correlating with large numbers of mRNA may be involved in important pathways of the macrophage polarization. Thus, we calculated the numbers of mRNA with a strong correlation for each miRNA by counting the numbers of mRNAs with a correlation of r≥0.8 or r≤−0.8 to assess the potential effect of the miRNA on the M2-like polarization. The results were plotted against the magnitude of expression changes during the 14 days after an MI (Figure 1B). To narrow down the candidate miRNAs as regulators of the M2-like macrophage differentiation, those showing little change of expression (<1.5-fold) after MI were excluded. As a result, miR-27a-5p was extracted as the miRNA that appeared to potentially regulate the largest number of genes in the M2-like polarization pathway.

Figure 1C displays the time course of expression of the 7 miRNAs after an MI. Figure 1D shows the relationship between the expression of miR-27a-5p and the proportion of the M2-like subset to the entire macrophage population. As the points of Day 7 and Day 14 overlapped, only 3 dots were visible, but in fact, 4 dots have been included. It can be concluded that miR-27a-5p expression decreases as the macrophage polarization progresses towards the M2-like phenotype.

miR-27a-5p Negatively Regulates Expression of M2-Like Marker Genes

In order to test if miR-27a-5p was a negative regulator of the M2-like polarization pathway, we used a system that stimulated the BMDM with IL4 to differentiate them into M2-like macrophages. The M2-like polarization was confirmed with flow cytometry analysis (Supplementary Figure 2). Quantitative PCR (qPCR) analysis revealed that the M2 marker genes (Arg1, Relmα, Mrc1, and Il10) were induced after 24 h of stimulation with IL4 (Figure 2A). Contrary to the upregulation of these M2 marker genes, the expression of miR-27a-5p was decreased (Figure 2B). To further confirm that miR-27a-5p inhibited the macrophage polarization towards an M2-like phenotype, BMDM were transfected with either miR-27a-5p precursor or with miR-27a-5p inhibitor, and then stimulated with IL4. The efficiency of miR-27a-5p precursor and the miR-27a-5p inhibitor transfection were confirmed by RT-qPCR (Figure 2C, Supplementary Figure 3). Overexpression of miR-27a-5p attenuated the expression of the M2 marker genes (Figure 2D), whereas overexpression of the miR-27a-5p inhibitor increased the expression of these M2 marker genes (Figure 2E). These results suggested that miR-27a-5p may have negatively regulated the macrophage polarization towards an M2-like phenotype in the IL4-stimulated BMDM.

Figure 2.

In-vitro analysis confirming that miR-27a-5p is located upstream and inhibits M2-like polarization. (A) Quantitative polymerase chain reaction (qPCR) for the M2 markers in the bone marrow-derived macrophages (BMDM) stimulated with interleukin 4 (IL4). cont: n=6; IL4: n=6. (B) qPCR for miR-27a-5p in the BMDM stimulated with IL4. cont: n=6; Il4: n=6. (C) qPCR for miR-27a-5p and (D) for the M2 markers in the BMDM after transfection with the miR-27a-5p precursor and stimulation with IL4. Cont: n=6; miR: n=6. (E) qPCR for the M2 markers in the BMDM after transfection with the miR-27a-5p inhibitor and stimulation with IL4. Cont: n=6; miR-inhibitor: n=6. The horizontal black bar indicates the mean. *Indicates statistical significance. Cont, control; miR, transfected with the miR-27a-5p precursor; miR-inhibitor, transfected with the miR-27a-5p inhibitor.

Identification of Potential Targets of miR-27a-5p in Macrophages

To search for the targets of miR-27a-5p regulating the M2-like polarization, mRNAs that had a target sequence of miR-27a-5p in both mice and humans were selected using the TargetScan software.²⁶ It is likely that changes in the expression of mRNAs that is directly regulated by miR-27a-5p, show a strong inverse correlation with the expression of miR-27a-5p. Thus, mRNAs with a correlation coefficient of ≤–0.8 for miR-27a-5p expression were selected. Because it was likely that mRNAs with small changes of expression over time have little influence on the M2-like polarization, we selected mRNAs showing a change of more than 4-fold in expression within 2 weeks after MI (Figure 3A). This analysis identified 8 mRNAs as potential targets of miR-27a-5p (Figure 3B). Figure 3C shows the time course of expressions of the 8 mRNAs after MI. Note that the expression of day 0 (sham mice) was 1 for all the miRNAs because the expression was normalized with the sham data in the microarray analysis, as explained in the Supplementary File (Methods).

Figure 3.

Screening for the target of miR-27a-5p in regulation of M2-like polarization. (A) Fold change vs. correlation with miR-27a-5p plots of mRNAs containing the target site for miR-27a-5p. (B) List of mRNAs showing a strong negative correlation and marked changes of expression. (C) Plot of fold change vs. time after MI (days) of the potential target mRNA.

To determine whether any of these mRNAs were actual targets of miR-27a-5p, we examined the effect of the forced miR-27a-5p expression on these mRNAs in the IL4-stimulated BMDM. As a result, expressions of 4 mRNAs (Apbb2, Zbtb20, Ppm1l, and Zdhhc14) were significantly suppressed by the forced miR-27a-5p expression (Figure 4).

Figure 4.

Overexpression analysis of miR-27a-5p to evaluate potential target mRNA. Quantitative polymerase chain reaction (qPCR) for the potential target mRNA in bone marrow-derived macrophages (BMDM) transfected with the miR-27a-5p precursor or the control and stimulated with interleukin 4. Cont: n=6; miR: n=6. The horizontal black bar indicates the mean. *Indicates statistical significance. Cont, control; miR, transfected with the miR-27a-5p precursor.

Evaluation of miRNA Targets by the Luciferase Reporter Gene Assay

Among the potential target mRNAs of miR-27a-5p, Ppm1l was identified as a possible target that may be involved in the macrophage polarization towards the M2-like phenotype based on information from the literature (the details of the literature are in the discussion section). Western blot analysis revealed that transfection with miR-27a-5p decreased the Ppm1l protein level, further supporting our hypothesis (Supplementary Figure 4). The 3’UTR of mouse and human Ppm1l mRNA possesses target sites for miR-27a-5p (Figure 5A).

Figure 5.

Luciferase analysis of the 3’UTR of Ppm1l. (A) Target site of miR-27a-5p in the 3’UTR of mouse and human Ppm1l. (B) Schematic drawing and (C) the construction map of the luciferase expression vector, including the 3’UTR of the Ppm1l mRNA. (D) Luciferase assay of bone marrow-derived macrophages (BMDM) co-transfected with a plasmid expressing the luciferases and the miR-27a-5p precursor. Cont: n=6; miR: n=6. The horizontal black bar indicates the mean. *Iindicates statistical significance. Cont, control; miR, transfected with miR-27a-5p precursor.

To examine the effect of miR-27a-5p-mediated posttranscriptional regulation, a dual-luciferase miRNA target expression vector was created by cloning the putative miR-27a-5p target sequence in the 3’UTR of Ppm1l mRNA into the 3’ of the firefly luciferase gene (Figure 5B). The complete map of the plasmid used for this luciferase reporter assay is shown in Figure 5C and the sequence of the 3’UTR region of Ppm1l used in this analysis is shown in the Supplementary File. Renilla luciferase was used as a control reporter for normalization. BMDM were co-transfected with a plasmid containing Renilla and firefly luciferase with the 3’UTR of Ppm1l, and a precursor of miR-27a-5p. Renilla and firefly luciferase activities were measured at 24 h after transfection. Firefly luciferase activity (normalized to the Renilla luciferase activity) was reduced by transfection of miR-27a-5p, indicating that this miRNA bound to its cloned putative target sequence (Figure 5D). We confirmed that miR-27a-5p inhibitor increased expression of Ppm1l in BMDM under IL4-stimulated conditions (Supplementary Figure 3).

Ppm1l Acts Upstream of the M2-Like Polarization and Is the Target of miR-27a-5p

Ppm1l expression displayed a marginally significant increase (P=0.053) when BMDM was stimulated with IL4 (Figure 6A). Then, we examined whether Ppm1l was involved in the macrophage polarization toward M2-like phenotype as a downstream target of miR-27a-5p. BMDM were transfected with siRNAs for Ppm1l and stimulated with IL4. Two different Ppm1l siRNAs effectively reduced the Ppm1l expression. As hypothesized, both Ppm1l siRNAs significantly suppressed the expression of the M2 marker genes such as Arg1, Relmα, Mrc1 (Figure 6B). Ppm1l siRNAs tended to reduce the expression of Il10 but this did not reach statistical significance.

Figure 6.

miR-27a-5p Ppm1l pathway regulating M2-like polarization. (A) Quantitative polymerase chain reaction (qPCR) analysis of Ppm1l on bone marrow-derived macrophages (BMDM) with and without stimulation with interleukin 4 (IL4). Cont: n=6; IL4: n=6. (B) qPCR analysis of the BMDM transfected with siRNA for Ppm1l and stimulated with IL4. Cont: n=10; siPpm1l_1: n=10; siPpm1l_2: n=10. (C) qPCR confirming co-transfection of BMDM with the miR-27a-5p precursor and Ppm1l. Cont: n=4; miR: n=4; miR+Ppm1l: n=4. (D) qPCR analysis of the M2 markers in BMDM after co-transfection with the miR-27a-5p precursor and Ppm1l. Cont: n=4; miR: n=4; miR+Ppm1l: n=4. The horizontal black bar indicates the mean. *Indicates statistical significance. Cont, control; miR, transfected with the miR-27a-5p precursor; miR+Ppm1l, transfected with both the miR-27a-5p precursor and Ppm1l-expressing plasmid. siPpm1l_1 and siPpm1l_2 were 2 different siRNAs targeting Ppm1l.

Next, we examined whether the suppression of macrophage polarization towards an M2-like phenotype by miR-27a-5p could be overridden by an overexpression of Ppm1l. The transfection efficacy was confirmed by qPCR (Figure 6C). Ppm11 expression restored Arg1, IL10, and Mrc1 expression in the IL4-stimulated BMDM overexpressing miR-27a-5p, but this had no effect on Relmα expression (Figure 6D).

Discussion

We have previously reported that the polarization of macrophages changes over time from an M1-like to an M2-like predominance after MI,³ but the key molecular mechanism regulating this process was unknown.

In the present study, we used time-series correlation analysis of the RNA microarray data to identify that the change in the expression of miR-27a-5p was associated with the macrophage polarization toward an M2-like phenotype after MI. Using the in vitro system of differentiation of BMDM into an M2-like macrophage induced by IL4, we showed that Ppm1l was involved in the M2 marker genes expression as one of the miR-27a-5p target genes (Figure 7).

Figure 7.

Graphic summary of the pathway. (A) The miRNA-27a-5p reduce the expression of mRNA of Ppm1l resulting in reduced expression of the protein. (B) Decreased PPM1L by miRNA-27a-5p reduces the polarization toward M2-like and overexpressing PPM1L rescues the M2-like polarization. (C) Collectively, a decrease in miRNA-27a-5p results in increased M2-like polarization.

It has been reported that miR-27a-5p is associated with multiple biological processes, including ischemia-reperfusion injury of the liver,²⁷ fat deposition,²⁸ and tumor suppression.²⁹ There is a study showing that miR-27a-5p downregulates in LPS-treated RAW267.4 cells and focuses on MCP1P1 as one of the targets of miR-27a-5p.²³ This study does not address the function of miR-27a-5p in regulating macrophage polarity. Thus, our study is the first to identify a role for miR-27a-5p in macrophage polarity changes, and that PPM1L was profoundly involved in differentiation to M2-like. Whether miR-27a-5p actively promotes differentiation into M1-like macrophages was not examined in our study. What we found is that the expression of miR-27a-5p in myocardial macrophages is elevated on days 1–3 of infarction, and reduced expression of PPM1L would have inhibited differentiation into M2-like.

Ppm1l (formerly called PP2Cε) was originally identified as a negative regulator of the stress-activated protein kinase signaling pathway,³⁰ and later found to be an endoplasmic reticulum (ER)-resident transmembrane protein involved in the regulation of ceramide trafficking.³¹ It has been also known to be associated with metabolic syndromes in humans.³² Its gene product is a phosphatase involved in the dephosphorylation of IRE1,³³ an important regulator of the endoplasmic reticulum stress. It has been reported that dephosphorylation of IRE1 inhibits its splicing activity and leads to a reduced splicing of Xbp-1,³³ whereas an M2-like polarization of the macrophages is suppressed by an increase in the spliced form of Xbp-1.³⁴ Taken together, these reports suggest that dephosphorylation of IRE1 may promote an M2-like polarization of the macrophages. This is in good agreement with our findings that the downregulation of Ppm1l inhibits the expression of the M2 marker genes in an in vitro system of differentiation of the BMDM into an M2-like macrophage induced by IL4.

Several limitations of this study should be noted. First, our transcriptome analysis only assessed 1 plate per time point and statistical testing could not be performed. Therefore, discovery-by-chance cannot be excluded. Also, the estimation of potential importance of miRNA on the macrophage polarization based on numbers of correlation with mRNA needs further validation and cannot detect definitive interactions between miRNA and mRNA. These results should be interpreted as only hypothesis-generating. Second, we could only analyze expression based on fold changes and correlations, limiting the depth of our study to detect small meaningful changes of expression patterns. Thus, analysis of a large number of samples may have revealed more pathways relevant to the M2-like polarization. Third, we only tested Ppm1l as a target of miR-27a-5p due to limited resources. We did not confirm that the pathway involving PPM1L is the only one that is regulated by miR-27a-5p. Therefore, there could be a possibility that other pathways are also involved in the regulation of M2-like polarization. This should be addressed in future research. Fourth, we have not been able to examine whether miR-27a-5p upregulation actively promotes the differentiation into M1-like. The role of miR-27a-5p in regulating the balance between M1-like and M2-like macrophages is of interest, but is out of the scope of the current study that focused mainly on understanding the mechanism of M2-like differentiation to promote wound healing after MI. This should be an interesting subject for future research.

In conclusion, our results suggested that miR-27a-5p and Ppm1l may be key molecules in the regulation of M2-like polarization, with miR-27a-5p inhibiting the M2-like polarization by downregulation of Ppm1l expression.

Sources of Funding

This work was supported by a grant from Vehicle Racing Commemorative Foundation.

Disclosures

K.F. is a member of Circulation Journal’s Editorial Team.

Data Availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Supplementary Files

Please find supplementary file(s);

http://dx.doi.org/10.1253/circj.CJ-20-0783

References

• 1.   Amsterdam EA, Wenger NK, Brindis RG, Casey DE Jr, Ganiats TG, Holmes DR Jr, et al. 2014 AHA/ACC guideline for the management of patients with non-ST-elevation acute coronary syndromes: A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2014; 64: e139–e228.
• 2.   Hamm CW, Bassand JP, Agewall S, Bax J, Boersma E, Bueno H, et al. ESC guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: The Task Force for the management of acute coronary syndromes (ACS) in patients presenting without persistent ST-segment elevation of the European Society of Cardiology (ESC). Eur Heart J 2011; 32: 2999–3054.
• 3.   Yan X, Anzai A, Katsumata Y, Matsuhashi T, Ito K, Endo J, et al. Temporal dynamics of cardiac immune cell accumulation following acute myocardial infarction. J Mol Cell Cardiol 2013; 62: 24–35.
• 4.   van den Borne SW, Diez J, Blankesteijn WM, Verjans J, Hofstra L, Narula J. Myocardial remodeling after infarction: The role of myofibroblasts. Nat Rev Cardiol 2010; 7: 30–37.
• 5.   Shinde AV, Frangogiannis NG. Fibroblasts in myocardial infarction: A role in inflammation and repair. J Mol Cell Cardiol 2014; 70: 74–82.
• 6.   Frantz S, Ertl G. Healing after myocardial infarction. Cardiovasc Res 2005; 66: 22–32.
• 7.   Nahrendorf M, Swirski FK, Aikawa E, Stangenberg L, Wurdinger T, Figueiredo JL, et al. The healing myocardium sequentially mobilizes two monocyte subsets with divergent and complementary functions. J Exp Med 2007; 204: 3037–3047.
• 8.   Liehn EA, Postea O, Curaj A, Marx N. Repair after myocardial infarction, between fantasy and reality: The role of chemokines. J Am Coll Cardiol 2011; 58: 2357–2362.
• 9.   Frangogiannis NG. The inflammatory response in myocardial injury, repair, and remodelling. Nat Rev Cardiol 2014; 11: 255–265.
• 10.   Prabhu SD, Frangogiannis NG. The biological basis for cardiac repair after myocardial infarction: From inflammation to fibrosis. Circ Res 2016; 119: 91–112.
• 11.   Nahrendorf M, Swirski FK. Monocyte and macrophage heterogeneity in the heart. Circ Res 2013; 112: 1624–1633.
• 12.   Anzai A, Anzai T, Nagai S, Maekawa Y, Naito K, Kaneko H, et al. Regulatory role of dendritic cells in postinfarction healing and left ventricular remodeling. Circulation 2012; 125: 1234–1245.
• 13.   Anzai A, Choi JL, He S, Fenn AM, Nairz M, Rattik S, et al. The infarcted myocardium solicits GM-CSF for the detrimental oversupply of inflammatory leukocytes. J Exp Med 2017; 214: 3293–3310.
• 14.   Nahrendorf M. Myeloid cell contributions to cardiovascular health and disease. Nat Med 2018; 24: 711–720.
• 15.   Shiraishi M, Shintani Y, Shintani Y, Ishida H, Saba R, Yamaguchi A, et al. Alternatively activated macrophages determine repair of the infarcted adult murine heart. J Clin Invest 2016; 126: 2151–2166.
• 16.   Gordon S, Martinez FO. Alternative activation of macrophages: Mechanism and functions. Immunity 2010; 32: 593–604.
• 17.   Lörchner H, Pöling J, Gajawada P, Hou Y, Polyakova V, Kostin S, et al. Myocardial healing requires Reg3β-dependent accumulation of macrophages in the ischemic heart [Article]. Nat Med 2015; 21: 353–362.
• 18.   Jung M, Ma Y, Iyer RP, DeLeon-Pennell KY, Yabluchanskiy A, Garrett MR, et al. IL-10 improves cardiac remodeling after myocardial infarction by stimulating M2 macrophage polarization and fibroblast activation. Basic Res Cardiol 2017; 112: 33.
• 19.   Chen T, Huang Z, Wang L, Wang Y, Wu F, Meng S, et al. MicroRNA-125a-5p partly regulates the inflammatory response, lipid uptake, and ORP9 expression in oxLDL-stimulated monocyte/macrophages. Cardiovasc Res 2009; 83: 131–139.
• 20.   Zhang B, Wang Q, Pan X. MicroRNAs and their regulatory roles in animals and plants. J Cell Physiol 2007; 210: 279–289.
• 21.   Bartel DP. MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell 2004; 116: 281–297.
• 22.   Lim LP, Lau NC, Garrett-Engele P, Grimson A, Schelter JM, Castle J, et al. Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature 2005; 433: 769–773.
• 23.   Cheng Y, Du L, Jiao H, Zhu H, Xu K, Guo S, et al. Mmu-miR-27a-5p-dependent upregulation of MCPIP1 inhibits the inflammatory response in LPS-induced RAW264.7 macrophage cells. Biomed Res Int 2015; 2015: 607692.
• 24.   Ying W, Cheruku PS, Bazer FW, Safe SH, Zhou B. Investigation of macrophage polarization using bone marrow derived macrophages. J Vis Exp 2013; 76: 50323.
• 25.   Benjamini Y, Hochberg Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B (Methodological) 1995; 57: 289–300.
• 26.   Agarwal V, Bell GW, Nam JW, Bartel DP. Predicting effective microRNA target sites in mammalian mRNAs. eLife 2015; 4: e05005.
• 27.   Xing Y, Li J, Li SP, Xi J, Ma N, Liu L, et al. MiR-27a-5p regulates apoptosis of liver ischemia-reperfusion injury in mice by targeting Bach1. J Cell Biochem 2018; 119: 10376–10383.
• 28.   Yang W, Tang K, Wang Y, Zan L. MiR-27a-5p increases steer fat deposition partly by targeting calcium-sensing receptor (CASR). Sci Rep 2018; 8: 3012.
• 29.   Mizuno K, Mataki H, Arai T, Okato A, Kamikawaji K, Kumamoto T, et al. The microRNA expression signature of small cell lung cancer: Tumor suppressors of miR-27a-5p and miR-34b-3p and their targeted oncogenes. J Hum Genet 2017; 62: 671–678.
• 30.   Li MG, Katsura K, Nomiyama H, Komaki K, Ninomiya-Tsuji J, Matsumoto K, et al. Regulation of the interleukin-1-induced signaling pathways by a novel member of the protein phosphatase 2C family (PP2Cepsilon). J Biol Chem 2003; 278: 12013–12021.
• 31.   Saito S, Matsui H, Kawano M, Kumagai K, Tomishige N, Hanada K, et al. Protein phosphatase 2Cepsilon is an endoplasmic reticulum integral membrane protein that dephosphorylates the ceramide transport protein CERT to enhance its association with organelle membranes. J Biol Chem 2008; 283: 6584–6593.
• 32.   Chen Y, Zhu J, Lum PY, Yang X, Pinto S, MacNeil DJ, et al. Variations in DNA elucidate molecular networks that cause disease. Nature 2008; 452: 429–435.
• 33.   Lu G, Ota A, Ren S, Franklin S, Rau CD, Ping P, et al. PPM1l encodes an inositol requiring-protein 1 (IRE1) specific phosphatase that regulates the functional outcome of the ER stress response. Mol Metab 2013; 2: 405–416.
• 34.   Shan B, Wang X, Wu Y, Xu C, Xia Z, Dai J, et al. The metabolic ER stress sensor IRE1alpha suppresses alternative activation of macrophages and impairs energy expenditure in obesity. Nat Immunol 2017; 18: 519–529.