Time-resolved single-cell transcriptomics uncovers dynamics of cardiac neutrophil diversity in murine myocardial infarction

Abstract

Objective-After myocardial infarction, neutrophils rapidly and massively infiltrate the heart, where they can promote both tissue healing and damage. Here, we investigated the dynamics of cardiac neutrophil heterogeneity after infarction.Methods and results-We employed single-cell transcriptomics (scRNA-seq) to investigate temporal neutrophil heterogeneity in the heart after murine myocardial infarction. At day 1, 3, and 5 after infarction, neutrophils could be delineated into six distinct clusters with specific time-dependent patterning and proportions. While the majority of neutrophils at day 1 were characterized by high expression of chemokines (e.g. Cxcl3, Ccl6), and putative activity of transcriptional regulators involved in hypoxic response (Hif1a) and emergency granulopoiesis (Cebpb), two major subsets of Siglecf hi (enriched for e.g. Icam1 and Tnf) and Siglecf low (Slpi, Ifitm1) neutrophils were found at 3 and 5 days. Flow cytometry analysis confirmed the presence of LY6G + SIGLECF hi and LY6G + SIGLECF low neutrophils in the heart from 3 days after infarction onwards. LY6G + SIGLECF hi neutrophils were absent from the bone marrow, blood and spleen, suggesting local acquisition of surface SIGLECF. Acquisition of the SIGLECF hi state was paralleled by features of neutrophil ageing and activation (ICAM1 hi CXCR4 hi CD49d hi CD62L low ). scRNA-seq of atherosclerotic aortas revealed two neutrophil subsets with gene expression patterns reminiscent of the major Siglecf hi and Siglecf low cardiac neutrophil subpopulations, revealing that these populations may be present across distinct contexts of cardiovascular inflammation.Conclusion-Altogether, our data provide a time-resolved census of neutrophil diversity and gene expression dynamics in the mouse ischemic heart at the single-cell level, and suggests that temporal neutrophil heterogeneity is in part driven by local transition to a SIGLECF hi state.

Anti-Ly6G binding and trafficking mediate positive neutrophil selection to unleash the anti-tumor efficacy of radiation therapy

“… 38 For instance, upon infection or inflammation, old CXCR4 pos neutrophils home faster 39 to the injury site to mitigate threats, while after myocardial lesion, local neutrophil aging results in SiglecF neutrophil differentiation prone to remodeling based on transcriptomic signatures. 40 In the present study, we show for the first time that both paradigms are relevant to the physiology of neutrophils after RT.…”

“…In cancer studies, partial or transient neutrophil depletion complicates the interpretation of results, as cancer models require several weeks of antibody-treatment and follow-up. 9 The biological significance of residual and anti-Ly6G bound neutrophils has not been investigated. However, clinical pathologies, such as transfusion-related acute lung injury, 10 and granulomatosis polyangiitis ; 11 where antibodies targeting the membrane of neutrophils and anti-neutrophil cytoplasmic antibodies (ANCAs) are, respectively, found; suggest that antibody-targeted neutrophils can be harmful, especially to lung tissues.…”

Meta-Analysis of Leukocyte Diversity in Atherosclerotic Mouse Aortas

“…Regardless of such intrinsic obstacles, neutrophils have been detected in healthy and atherosclerotic arteries by scRNAseq 130 , and in this meta-analysis. In atherosclerosis, these neutrophils have recently been proposed to segregate into Siglecf hi and Siglecf low neutrophil subsets, similar to the neutrophil subpopulations infiltrating the heart after myocardial infarction 178 . In this meta-analysis we report Siglecf hi neutrophils in atherosclerotic but not healthy aortas, a new discovery.…”

Single-cell transcriptomic profiling maps monocyte/macrophage transitions after myocardial infarction in mice

“…Monocytes, macrophages and neutrophils were extracted and examined in a new clustering analysis (Figure 1 and S1C). Time-dependent neutrophil clusters (cluster 9, 10 and 13, Figure 1A-C) are described in detail in (16). Here, we focused our analysis on monocytes and macrophages (2,562 cells) and their heterogeneity over the post-MI time continuum ( Figure 1A-C, Table S1).…”