Transcriptomic characterization of CD206- and CD206+ macrophages in human pancreatic islets and exocrine tissue
Macrophages reside in all organs and participate in homeostatic- and immune regulative processes. Little is known about pancreatic macrophage gene expression. CD206 is an endocytic receptor with prior use in subclassifying macrophages. In the present study, global gene expression was characterized in human pancreatic macrophage subpopulations. Flow cytometry was used to sort CD206-    and CD206+ macrophages separately from pancreatic islets and exocrine tissue to high purity. RNA-seq generated transcriptomic profiles were then analyzed. Comparing CD206- with CD206+ macrophages, CD206- showed enrichment in proliferation and nucleic acid processing, glycolysis, pro-inflammatory and SPP1-associated gene sets while CD206+ showed enrichment in complement-, IL-10 and IL-2RA immune regulation, as well as scavenging-related gene sets. Two sets involved in immune regulation were enriched in islet CD206-, while various sets including some proinflammatory sets were enriched in exocrine CD206- macrophages. Fewer differences were found between CD206+ macrophages, with enrichment in two IL2-RA related gene sets in islets and eight gene sets in exocrine samples. Comparing macrophages between individuals with normoglycemia, elevated HbA1c or type 2 diabetes, only a few diverse differentially expressed genes were identified. This work characterizes global gene expression and identifies differences between CD206- and CD206+ macrophage populations within the human pancreas. Overall design: To investigate pancreatic macrophages, fresh pancreases from donors without diabetes(ND), Type 1 Diabetes(T1D), Type 2 Diabetes(T2D) and Intermediade glycemic status(IGM) were dispersed and sorted into exocrine and pancreatic fraction.  Flow cytometry was used to sort macrophages from other cell types; Macrophages were then sorted into  CD206-    and CD206+ macrophages separately from pancreatic islets and exocrine tissue to high purity. RNA-seq generated transcriptomic profiles were then analyzed