Title

Single cell transcriptomics based-MacSpectrum reveals novel macrophage activation signatures in diseases.

Document Type

Article

Publication Date

4-16-2019

Keywords

JGM

JAX Source

JCI Insight 2019; 4(10):e126453

PMID

30990466

DOI

https://doi.org/10.1172/jci.insight.126453

Abstract

Adipose tissue macrophages (ATM) are crucial for maintaining adipose tissue homeostasis and mediating obesity-induced metabolic abnormalities, including prediabetic conditions and type 2 diabetes mellitus. Despite their key functions in regulating adipose tissue metabolic and immunologic homeostasis under normal and obese conditions, a high-resolution transcriptome annotation system that can capture ATM multifaceted activation profiles has not yet been developed. This is primarily attributed to the complexity of their differentiation/activation process in adipose tissue and their diverse activation profiles in response to microenvironmental cues. Although the concept of multifaceted macrophage action is well-accepted, no current model precisely depicts their dynamically regulated in vivo features. To address this knowledge gap, we generated single-cell transcriptome data from primary bone marrow-derived macrophages under polarizing and non-polarizing conditions to develop new high-resolution algorithms. The outcome was creation of a two-index platform, MacSpectrum (https://macspectrum.uconn.edu), that enables comprehensive high-resolution mapping of macrophage activation states from diverse mixed cell populations. MacSpectrum captured dynamic transitions of macrophage subpopulations under both in vitro and in vivo conditions. Importantly, MacSpectrum revealed unique "signature" gene sets in ATMs and circulating monocytes that displayed significant correlation with BMI and homeostasis model assessment of insulin resistance (HOMA-IR) in obese human patients. Thus, MacSpectrum provides unprecedented resolution to decode macrophage heterogeneity and will open new areas of clinical translation.

Comments

The authors are grateful for the services of the JAX-UConn Single Cell Genomics Center for scRNA-seq library preparation and sequencing. We thank Z. Huang from the University of Connecticut Department of Immunology for assisting with ATM isolation, E. Jellison from the UConn Health Flow Cytometry Core for performing fluorescence-activated cell sorting, P. Robson from the Jackson Laboratory for Genomic Medicine Single Cell Biology Laboratory for conducting fluorescence-activated cell sorting and single-cell transcriptome generation, and M. Bolisetty from the Jackson Laboratory for Genomic Medicine Single Cell Biology Laboratory for scRNA-seq read alignments and UMI matrices generation.

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