Cell Rep.: co-auth.: I.Xenarios

 2018 Apr 10;23(2):622-636. doi: 10.1016/j.celrep.2018.03.029.

Deciphering the Dynamic Transcriptional and Post-transcriptional Networks of Macrophages in the Healthy Heart and after Myocardial Injury.

Author information

1
Myocardial Pathophysiology Area, Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), 28029 Madrid, Spain.
2
Vital-IT, SIB Swiss Institute of Bioinformatics, University of Lausanne, 1015 Lausanne, Switzerland.
3
Vascular Pathophysiology Area, Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), 28029 Madrid, Spain.
4
Bioinformatics Unit, Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), 28029 Madrid, Spain. Electronic address: fscabo@cnic.es.
5
Myocardial Pathophysiology Area, Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), 28029 Madrid, Spain. Electronic address: mricote@cnic.es.

Abstract

Macrophage plasticity has been studied in vitro, but transcriptional regulation upon injury is poorly understood. We generated a valuable dataset that captures transcriptional changes in the healthy heart and after myocardial injury, revealing a dynamic transcriptional landscape of macrophage activation. Partial deconvolution suggested that post-injury macrophages exhibit overlapping activation of pro-inflammatory and anti-inflammatory programs rather than aligning to canonical M1/M2 programs. Furthermore, simulated dynamics and experimental validation of a regulatory core of the underlying gene-regulatory network revealed a negative-feedback loop that limits initial inflammation via hypoxia-mediated upregulation of Il10. Our results also highlight the prominence of post-transcriptional regulation (miRNAs, mRNA decay, and lincRNAs) in attenuating the myocardial injury-induced inflammatory response. We also identified a cardiac-macrophage-specific gene signature (e.g., Egfr and Lifr) and time-specific markers for macrophage populations (e.g., Lyve1, Cd40, and Mrc1). Altogether, these data provide a core resource for deciphering the transcriptional network in cardiac macrophages in vivo.

KEYWORDS:

Boolean dynamical model; IL-10; heart; lincRNAs; miRnome; myocardial injury; partial deconvolution; transcriptome analysis

PMID: 29642017