Single-cell RNA-seq ties macrophage polarization to growth rate of intracellular Salmonella

Nat Microbiol. 2016 Nov 14:2:16206. doi: 10.1038/nmicrobiol.2016.206.

Abstract

Intracellular bacterial pathogens can exhibit large heterogeneity in growth rate inside host cells, with major consequences for the infection outcome. If and how the host responds to this heterogeneity remains poorly understood. Here, we combined a fluorescent reporter of bacterial cell division with single-cell RNA-sequencing analysis to study the macrophage response to different intracellular states of the model pathogen Salmonella enterica serovar Typhimurium. The transcriptomes of individual infected macrophages revealed a spectrum of functional host response states to growing and non-growing bacteria. Intriguingly, macrophages harbouring non-growing Salmonella display hallmarks of the proinflammatory M1 polarization state and differ little from bystander cells, suggesting that non-growing bacteria evade recognition by intracellular immune receptors. By contrast, macrophages containing growing bacteria have turned into an anti-inflammatory, M2-like state, as if fast-growing intracellular Salmonella overcome host defence by reprogramming macrophage polarization. Additionally, our clustering approach reveals intermediate host functional states between these extremes. Altogether, our data suggest that gene expression variability in infected host cells shapes different cellular environments, some of which may favour a growth arrest of Salmonella facilitating immune evasion and the establishment of a long-term niche, while others allow Salmonella to escape intracellular antimicrobial activity and proliferate.

MeSH terms

  • Animals
  • Biological Variation, Population
  • Cell Differentiation*
  • Cells, Cultured
  • Gene Expression Profiling*
  • Host-Pathogen Interactions
  • Macrophages / microbiology*
  • Macrophages / physiology*
  • Mice, Inbred C57BL
  • Salmonella typhimurium / growth & development*
  • Sequence Analysis, RNA
  • Single-Cell Analysis