Early Age Efferocytosis Directs Macrophage Arachidonic Acid Metabolism for Tissue Regeneration

In response to organ injury in adults, macrophages often promote scarring, yet during early life are required for tissue regeneration. To elucidate mechanisms underlying age-associated regeneration, we compared the macrophage injury response in newborns versus adult hearts. Single cell analysis revealed an accumulation of tissue-resident macrophages in neonates that were selectively polarized for apoptotic cell recognition and uptake (efferocytosis). Ablation of the apoptotic cell recognition receptor Mertk in newborns prevented cardiac regeneration. These findings could be attributed to reprogramming of macrophage gene expression that was required for biosynthesis of the eicosanoid Thromboxane A2, which unexpectedly activated parenchymal cell proliferation. Markers of Thromboxane A2 production were suppressed in adult macrophages after efferocytosis. Moreover, macrophage-neighboring neonatal cardiomyocytes expressed the Thromboxane A2 receptor, whose activation induced a metabolic shift supporting cellular proliferation. Our data reveal a fundamental age-defined macrophage response in which lipid mitogens produced during efferocytosis support receptor-mediated tissue regeneration. Overall design: Single cell mRNA sequencing. Single cell suspensions were isolated as described in the method section “Flow Cytometry” by Collagenase Type II and DNase digestion of hearts. After RBC lysis, samples underwent dead cell removal (StemCell Technologies) by Annexin V staining. Next, samples underwent a CD45-positive selection (StemCell Technologies) to enrich cardiac leukocytes. Enriched cells and flow-through cells were both counted and recombined at a ratio of 2 CD45+ cells for every 1 non-CD45+ cell. Combined single cell suspensions were diluted to target a recovery of 5,000 cells per sample. The single cell RNA-sequencing libraries were prepared using the 10X Genomics Single Cell 3' Gene Expression (v3 or v3.1 chemistry) pipeline. The prepared libraries were run on an Agilent Bioanalyzer High Sensitivity Chip and Kapa Biosystems Library Quantification Kit for Illumina platforms for quality control before sequencing. All libraries were sequenced on the Illumina NovaSeq 6000 platform with the following parameters: Read 1—26 cycles; i7 Index—8 cycles; Read 2—98 cycles. Processing and analysis of scRNA-seq data. Raw Sequencing Data Processing (Alignment, Barcode Assignment, and UMI Counting). The raw FASTQ files were first aligned to the murine transcriptome (GRCm38; mm10) using CellRanger (10X Genomics, v4.0.0). Aligned reads were then filtered for valid barcodes and UMIs to generate gene-cell matrices used for downstream analysis.