FocusFIBROSIS

Lifting the veil on macrophage diversity in tissue regeneration and fibrosis

See allHide authors and affiliations

Science Immunology  11 Oct 2019:
Vol. 4, Issue 40, eaaz0749
DOI: 10.1126/sciimmunol.aaz0749

Abstract

Sommerfeld et al. have used single-cell RNA sequencing to unravel the role of macrophages in driving tissue repair and fibrosis.

Macrophages are key mediators of host defense and critical players in a range of physiological process, including homeostasis, tissue repair, and regeneration (1). However, certain pathological conditions, such as those associated with chronic inflammation, propel macrophages to respond with specific profibrotic signals that lead to tissue fibrosis. Engineered biological scaffolds have been explored as environmental guides of tissue regeneration. Biomaterial composition can influence macrophage phenotype and function, although the resulting macrophage identity has not been well described. Typically, macrophages have been thought to exist over a canonical spectrum of anti-inflammatory/protissue repair (M2) to proinflammatory/profibrotic (M1); however, the heterogeneity of macrophage populations, their abundance of functions, and the nuances of their phenotypes in vivo are being more deeply understood as a result of recent technological advances, such as single-cell RNA sequencing (scRNAseq). In this issue of Science Immunology, Sommerfeld et al. use single-cell technology and functional evaluations as a platform to describe how macrophages respond to distinct microenvironments and show that manipulating these macrophage populations can dictate the fate of the tissue during fibrosis (2).

What is the best way to identify macrophages released from tissues? Using in vivo murine models of repair and fibrosis, Sommerfeld et al. show that computational analysis of scRNAseq data can help to predict surface markers that can be used to identify macrophage clusters in tissues. scRNAseq analysis revealed that Cd301b, Cd9, and Cd74 [invariant polypeptide associated to the major histocompatibility complex II (MHCII)] gene expression could discriminate the regenerative and fibrotic terminal clusters. The corresponding surface antibodies anti-CD9, anti-CD301b, and anti-MHCII were then used to distinguish the new phenotypic profiles by flow cytometry. The authors also validated protein expression in tissues in the absence of cell isolation using immunofluorescent microscopy. Notably, the traditional macrophage surface markers CD86 and CD206 that are predominantly expressed on fibrotic and regenerative clusters, respectively, failed to completely differentiate phenotypic macrophage subsets identified by Sommerfeld et al. Together, these results challenge the applicability of the traditional M1/M2 classification in vivo and provide a revised alternative.

In their approach, the authors used scRNA-seq on sorted differentiated macrophages (CD45+CD64+F4/80hi) followed by unbiased clustering to directly examine macrophage transcriptional signatures, phenotype, and function in cells enzymatically released from both proregenerative and profibrotic environments. The regenerative condition was marked by the presence of two clusters of macrophages, R1 (CD9+CD301b+MHCIIhi) and R2 (CD9CD301b+CD206+), whereas cells released from the profibrotic microenvironment were characterized by the presence of the two terminal clusters F1 (CD9CD301bMHCIIhi) and F2 (CD9hiCD301bMHCIIIL36g+) (Fig. 1). Analysis of precursor-progeny relationships observed in the different microenvironments allowed the reconstruction of macrophage differentiation trajectories. The profibrotic terminal clusters, F1 and F2, originated from a common precursor, whereas the proregenerative terminal clusters, R1 and R2, arose from three precursor clusters.

Fig. 1 The cross-talk between macrophages and the microenviroment controls tissue regeneration.

scRNAseq enables the identification of key surface markers of macrophages in both proregenerative and profibrotic environments, allowing subsequent characterization of their frequency and function over time. Microenvironmental cues favor macrophage polarization into the regenerative clusters R1 (CD9+CD301b+MHCIIhi) and R2 (CD9CD301b+CD206+) or into the fibrotic clusters F1 (CD9 CD301bMHCIIhi) and F2 (CD9hiCD301bMHCIIIL36γ+). Although both R1 and F1 are marked by proinflammatory responses, their magnitude and composition differ and lead to opposing outcomes. R1 and R2 assist tissue repair by actively engaging and coordinating immune cells in a coinciding effort toward regeneration. R1 mobilizes and instructs cells through chemokine expression and antigen presentation, and R2 coordinates a type 2 response through Il-4 and Ccl24 expression and exhibits phagocytic activity. Conversely, F1 and F2 drive FBR. F1 directs the exacerbated expression of interferon-related cytokines, and F2 favors fibrosis by feeding and thriving in a microenvironment marked by type 17 immune responses. ECM, extracellular matrix; PCL, polycaprolactone.

CREDIT: A. KITTERMAN/SCIENCE IMMUNOLOGY

To further detail the newly described subsets, the authors performed gene set enrichment and gene network analyses and sorted the subpopulations by flow cytometry over a 6-week time course of tissue injury. As summarized in Fig. 1, up-regulation of genes associated with antigen presentation (H2 genes and Cd74) and inflammatory activity/leukocyte activation (Cxcl1, Ccr2, Ccl5, Tnfa, and Il1b) was a hallmark for R1 macrophages. Flow cytometric analysis revealed that this population expanded during the first 3 weeks after injury under the proregenerative condition and seemed critical to coordinate the local immune response. Conversely, R2 macrophages up-regulated genes associated with anti-inflammatory responses (Chil3, Cd163, and Mrc1), eosinophil recruitment (Ccl24), type 2 responses (Il4ra), and endocytic gene modules (Cltc, Clta, and Ap2a2). Interleukin-4 (IL-4) has been shown critical for muscle repair (3), and R2 showed the highest Il4ra expression among the macrophage’s subsets. The presence of the R2 subset was sustained in the regenerative condition (weeks 1 to 6 after injury), and their phagocytic activity, a key function for clearance of cell debris, was confirmed by flow cytometry (Fig. 1). The terminal fibrotic associated clusters, F1 and F2, were marked by unique inflammatory properties. Genes commonly associated with inflammation and interferon responses (Stat1, Myd88, Irf7, Il18, Tlr2, Ccl4, Ccl7, and Cxcl10) were up-regulated in the F1 cluster, whereas the inflammatory markers (Slpi, Hdc, Tlr2, and Il1b) and genes associated with autoimmunity (Il36γ, Trem1, Asprv1, and Il17ra) were elevated in the F2 macrophage subset. The authors also showed that IL-36γ serves as a marker for the identification of the F2 subset at the tissue level using immunofluorescence staining. The longitudinal characterization of the fibrosis-associated clusters in the wound under profibrotic conditions showed significant reduction in the F1 subset within the first 3 weeks. In contrast, the F2 subset frequency was maintained elevated over time, supporting its participation in tissue fibrosis.

What is the link between profibrotic macrophages (F2) and IL-17 in the fibrotic response? The authors elegantly tested the relevance of IL-36g and IL-17RA signaling for F2 polarization and fibrosis by recreating the muscle wound model in the presence of a profibrotic environment in both Il17 and Il17ra knockout mice. The authors demonstrated that fibrosis was reduced in IL17−/− and IL17ra−/− mice and that F2 macrophages were absent in the latter. Importantly, the authors clearly demonstrated a link between IL-36γ signaling, T helper 17 responses, and fibrosis, with IL-36γ expression increasing over time under the profibrotic condition and helping to fuel the local IL-17 response. This is in agreement with data showing that IL-17 is a key mediator of foreign body response (FBR) to synthetic implants (4). Although macrophages, including the F2 population, do not directly produce IL-17, they respond to an IL-17–enriched environment by up-regulating IL-17 receptor and increasing IL-36γ expression. They propose that IL-36γ contributes to sustained IL-17 and IL-36γ itself by establishing a feedback loop within the tissue environment.

In terms of the physiological relevance, the regenerative-associated R2 profile was shown to transcriptionally overlap with macrophages found in healthy human liver (5), an organ known for its regenerative capacity and for holding the largest portion of resident macrophages in the body. In addition, in the absence of a regenerative biological scaffold, the authors showed that the R2 population only appears at later time points, suggesting that environmental cues driving macrophage differentiation toward R2 may be exploited to promote tissue repair. With respect to fibrosis-associated clusters, the F2 subset was shown by immunofluorescence histology to be present in the context of human fibrotic (breast implant tissue capsules) and autoimmune conditions (histiocytosis).

This study provides new information regarding muscle regeneration and tissue fibrosis, and it also provides an elegant framework to further advance our understanding of macrophage biology, their transition phenotypes, and key signals involved in their polarization at multiple sites. Macrophages are known to instruct tissue repair processes across the body, including muscle, liver, nervous system, heart, lung, and intestine. The fact that macrophages isolated from different locations are unique with regard to their phenotype and transcriptional program (6, 7) speaks to the influence of local microenvironment (8), with the type and site of injury helping define macrophage phenotype and function (9).

Tissue regeneration features a dynamic and highly complex biological process taking place in a very fragile environment. The ability to examine organ systems and cellular networks within their natural niche with single-cell resolution helps unveil the universe that surrounds cell communication, interaction, and function (10). The work of Sommerfeld et al. contributes to the regenerative medicine field by using a new lens to describe how macrophage polarization can switch gears toward regeneration or fibrosis and how the local environment shapes macrophage identity. This approach will be particularly relevant as efforts are made to identify populations of tissue-resident immune cells found in diseased tissues that may not conform to typical legacy flow cytometry panels. Parallel studies in injured tissues from different sites, which also incorporate spatial analysis and interaction with other cells in the vicinity, will help determine the heterogeneity of proregenerative and profibrotic macrophages across the body.

REFERENCES

View Abstract

Navigate This Article