bioRxivMolecular BiologyPreprint
Salmonella injectisome penetration of macrophages triggers rapid translation of transcription factors and protection against cell death
George WoodiD, Rebecca JohnsoniD, Jessica Powell, Owain J. BryantiD, Filip LastovkaiD, Matthew P. Brember, Pani Tourlomousis, John P. CarriD, Clare Elizabeth BryantiD, Betty ChungiD
Abstract
During bacterial infection both the host cell and its invader must divert intracellular resources to synthesise specific proteins in a timely manner. For the host, these factors may be needed for innate immune responses, including programmed cell death, and in the bacteria newly synthesized proteins may be survival factors needed to counteract host responses. Salmonella is an important food-borne bacterial pathogen that invades and multiplies within host cells. It is well established that invasion of epithelial cells is dependent upon the SPI-1 Type III injectisome, a biological needle that penetrates and secretes effectors into host cells to promote internalization. However, the importance of the SPI-1 injectisome in infection of professional phagocytes such as macrophages, which are the predominant host cell type during systemic infection, is less clear. Through time resolved parallel transcriptomic and translatomic studies of macrophage infection, we revealed that SPI-1 injectisome-dependent infection of macrophages triggers rapid translation of transcription factor mRNAs, including Early Growth Response 1 (Egr1). Despite the short half-life of EGR1 protein, its swift synthesis within the initial hour of infection is sufficient to inhibit transcription of pro-inflammatory genes and thereby restrain inflammatory responses and programmed cell death within the first hour of during early infection. This transient period of inflammatory suppression in macrophages is exploited by Salmonella to establish infection and sheds new insight on the importance of translational activation in host-pathogen dynamics during Salmonella infection.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 6
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