Immunophenotyping monocytes, macrophages and granulocytes in the Pteropodid bat Eonycteris spelaea.
Akshamal M GamageFeng ZhuMatae AhnRandy Jee Hiang FooYing Ying HeyDolyce H W LowIan H MendenhallCharles-Antoine DutertreLin-Fa WangPublished in: Scientific reports (2020)
Bats are asymptomatic reservoir hosts for several highly pathogenic viruses. Understanding this enigmatic relationship between bats and emerging zoonotic viruses requires tools and approaches which enable the comparative study of bat immune cell populations and their functions. We show that bat genomes have a conservation of immune marker genes which delineate phagocyte populations in humans, while lacking key mouse surface markers such as Ly6C and Ly6G. Cross-reactive antibodies against CD44, CD11b, CD14, MHC II, and CD206 were multiplexed to characterize circulating monocytes, granulocytes, bone-marrow derived macrophages (BMDMs) and lung alveolar macrophages (AMs) in the cave nectar bat Eonycteris spelaea. Transcriptional profiling of bat monocytes and BMDMs identified additional markers - including MARCO, CD68, CD163, CD172α, and CD88 - which can be used to further characterize bat myeloid populations. Bat cells often resembled their human counterparts when comparing immune parameters that are divergent between humans and mice, such as the expression patterns of certain immune cell markers. A genome-wide comparison of immune-related genes also revealed a much closer phylogenetic relationship between bats and humans compared to rodents. Taken together, this study provides a set of tools and a comparative framework which will be important for unravelling viral disease tolerance mechanisms in bats.
Keyphrases
- genome wide
- dendritic cells
- single cell
- genetic diversity
- endothelial cells
- peripheral blood
- type diabetes
- sars cov
- dna methylation
- poor prognosis
- gene expression
- bone marrow
- transcription factor
- signaling pathway
- metabolic syndrome
- cell cycle arrest
- long non coding rna
- cell death
- genome wide identification
- bioinformatics analysis