Single-cell transcriptomics-based MacSpectrum reveals macrophage activation signatures in diseases
| Autor: | Beiyan Zhou, Christopher P. Bonin, Chuan Li, Anthony T. Vella, Cullen Farragher, Antoine Ménoret, Paul Holvoet, Zhengqing Ouyang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Male
0301 basic medicine EXPRESSION POLARIZATION Adipose tissue macrophages Mice Obese Adipose tissue BETA Inflammation Biology Research & Experimental Medicine DENDRITIC CELLS Transcriptome Mice 03 medical and health sciences 0302 clinical medicine Insulin resistance INFLAMMATION ADIPOSE-TISSUE MACROPHAGES medicine NOMENCLATURE Animals Homeostasis Humans Macrophage Obesity Science & Technology Macrophages Cell Differentiation Translation (biology) General Medicine Macrophage Activation medicine.disease Cell biology Mice Inbred C57BL 030104 developmental biology DIFFERENTIATION Adipose Tissue Diabetes Mellitus Type 2 Medicine Research & Experimental MONOCYTES 030220 oncology & carcinogenesis OBESITY medicine.symptom Life Sciences & Biomedicine Research Article |
| Popis: | 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. ispartof: JCI INSIGHT vol:4 issue:10 ispartof: location:United States status: published |
| Databáze: | OpenAIRE |
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