Salmonella enterica serovar Typhimurium inhibits the innate immune response and promotes apoptosis in a ribosomal/TRP53-dependent manner in swine neutrophils

Abstract

Neutrophils are the first barriers for resisting the invasion, proliferation, and damage caused by Salmonella Typhimurium. However, the mechanisms that control this resistance are not completely understood. In this study, we established an in vitro Salmonella infection model in porcine neutrophils, and analyzed the cellular transcriptome by deep sequencing and flow cytometry. The results showed that ribosomal gene transcription was inhibited, and two of these genes, RPL39 and RPL9, were related to TRP53 activation. Furthermore, several important innate immunity genes were also inhibited. Knock-down of RPL39 and RPL9 by siRNA caused an approximate fourfold up-regulation of TRP53. Knock-down of RPL39 and RPL9 also resulted in a significant down-regulation of IFNG and TNF, indicating an inhibition of the innate immune response. Silencing of RPL39 and RPL9 also resulted in the up-regulation of FAS, RB1, CASP6, and GADD45A, which play roles in cell cycle arrest and apoptosis. Neutrophils were either first treated with RPL39 siRNA, RPL9 siRNA, TRP53 activator, or TRP53 inhibitor, and then infected with Salmonella. Knock-down of RPL39 and RPL9, or treatment with TRP53 activator, can increase the intracellular proliferation of Salmonella in neutrophils. We speculate that much of the Salmonella virulence can be attributed to the enhancement of cell cycle arrest and the inhibition of the innate immune response, which allows the bacteria to successfully proliferate intracellularly.

Keywords: RPL39; RPL9; Salmonella; TRP53; deep-sequencing; neutrophils; porcine.

Figure 1

Reducing RPL39 and RPL9 expression through siRNA knock-down up-regulates TRP53 expression in neutrophils. Flow cytometry plots for rested and stimulated neutrophils following antibody staining for TRP53 (FITC-A) and CD14 (PE-A). Neutrophils were either untreated at zero hours (column T0), treated for four hours (column T4), or treated for eight hours (column T8) with RPL39 siRNA (row A), RPL9 siRNA (row B), TRP53 inhibitor (row C), or TRP53 activator (row D).

Figure 2

Modulation of the ribosomal/TRP53 pathway increases evidence of apoptosis and immune system arrest. The transcription level of four apoptosis genes and two innate immunity genes were measured via RT-PCR following pre-treatment with TRL39 siRNA, RPL9 siRNA, TRP53 inhibitor, or TRP53 activator and infection with Salmonella. Gene expression was normalized to GAPDH transcription level $2^{\mathrm{\Delta }40-\mathrm{ct}}$ for A FAS, B RB1, C CASP6, D GADD45A, E NFKB, and F INFG. Error bars represent mean ± SD. * = P < 0.05 (ANOVA test, number of replicates = 3).

Figure 3

Modulation of neutrophil ribosomal/TRP53 pathway impacts the ability of Salmonella to infect and proliferate intracellularly. Flow cytometry for neutrophils left untreated at zero hours (column T0) or pre-treated for four (column T4) or eight hours (column T8) with RPL39 siRNA (row A), RPL9 siRNA (row B), TRP53 inhibitor (row C), and TRP53 activator (row D) and then infected with GFP fluorescent labeled Salmonella. Fluorescence intensity represents bacterial replication. Line graphs show the overlay of three replicate experiments.

Figure 4

Ribosomal/TRP53 pathway pattern mediated by Salmonella infection. Following the intracellular invasion of Salmonella, the bacterium secretes proteins that inhibit the transcription of RPL39 and RPL9, and then increases the accumulation of TRP53. TRP53 acts on the FAS/CASP6 sub-pathway and promotes apoptosis. TRP53 can also modulate the GADD45A sub-network and causes cell cycle arrest. Besides RPL39 and RPL9, three genes (ABL1, F2, and PTEN) which promote TRP53 activity, and four genes (AKT1, SDCBP, PSEN1, and TNFRSF8) which inhibit TRP53 activity were differentially expressed in neutrophils infected with Salmonella. The regulatoryrelationships shown in this figure were either discovered in this study or curated from gene expression regulation relationships deposited in GEREDB database [18].