Salmonella enterica serovar Typhimurium inhibits the innate immune response and promotes apoptosis in a ribosomal/TRP53-dependent manner in swine neutrophils
Veterinary Research volume 51, Article number: 105 (2020)
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.
Salmonella enterica serovar Typhimurium is a Gram-negative facultative intracellular bacterium that colonizes both animals and humans . Pigs carrying Salmonella can shed bacteria on a farm, which may subsequently lead to the bacterial contamination of pig carcasses in a slaughterhouse, thereby posing a serious threat to the swine industry . A Salmonella infection is a dynamic process that involves the interaction between various immune cells and the bacteria. Burton et al. demonstrated through single cell analysis and computer modeling that Salmonella bacteria can survive inside macrophages but are partially killed when engulfed by neutrophils and inflammatory monocytes . The main mechanisms by which bacteria are effectively killed are through the production of a lethal concentration of reactive oxygen species (ROS) and hypochloric acid in phagocytes . When Salmonella is engulfed by macrophages, the bacteria release a series of virulence factors through the type III secretion system, which modulates lysosome and vesicle maturation. This may reduce the pre-mature macrophage antibacterial response and may provide an ecological niche for Salmonella replication . In the peripheral blood, neutrophils are the most abundant type of leukocytes. Recent studies have shown that the killing activity of neutrophils infected with Salmonella was found to decrease significantly after 2 h, but the overall bacterial proliferation was not significantly different from Salmonella in primary macrophages [6,7,8].
In the early stages of infection (24 to 48 h), Salmonella interacts with most phagocytic and non-phagocytic immune cells, including B-lymphocytes, T-lymphocytes, neutrophils, monocytes, and dendritic cells, however, Salmonella bacteria have never been detected in mature macrophages . In the cells containing Salmonella, neutrophils represent the largest and most active population of cells that may contain Salmonella . Similar to the behavior within macrophages, Salmonella mainly interacts with neutrophils through the type III secretion system and weakens the bactericidal activity, allowing Salmonella to survive and proliferate within neutrophils .
Ribosomes translate genetic information stored in mRNA into peptides in several steps, including initiation, extension, termination, and circulation. Previous studies have reported Salmonella-induced transcriptional inhibition of ribosomal genes in the peripheral blood of piglets infected with Salmonella enterica serovar Typhimurium . This has been confirmed by high-throughput sequencing experiments . Following infection with Salmonella, peripheral blood collected from piglets demonstrated a significant down-regulation of 55 ribosomal protein genes . This involved 6 translation-related signaling pathways, which suggests that Salmonella infection modulates multiple key steps in the gene translation process. While it has been shown that peripheral blood collected from piglets infected with Salmonella contains many different types of hemocytes, the specific cells that are responsible for the gene expression responses remain unknown. In this study, the transcriptome of neutrophils infected with Salmonella was determined through deep sequencing, and we proposed a mechanism for Salmonella modulation of the host transcriptome and intracellular survival.
Materials and methods
Neutrophil isolation and infection
Peripheral blood samples were collected from 20 healthy crossbreed (Duroc × Landrace × Yorkshire) piglets obtained from a commercial swine farm in Jingzhou, China without sacrificing the animals (ten males and ten females, four weeks old). Piglets were randomly selected from ten litters (2 animals for each litter) and then co-housed together in climate-controlled facilities. Prior to blood collection, the feces were tested negative for Salmonella three times. Salmonella was quantified from feces by direct counting using bacteriological methods, as described by Uthe et al. . The sample collection was approved by the Animal Care and Use Committee of Hubei Province (China, YZU-2018–0031). Neutrophils were isolated by density gradient centrifugation using Ficoll-Paque™ media (GE Healthcare Life Sciences, Shanghai, China), as per the manufacturer’s instructions. Luria broth and M9 minimal medium were used to culture Salmonella bacteria. The neutrophils were treated with 106 colony forming units (cfu) of Salmonella enterica serovar Typhimurium (ATCC® 14,028™) as previously described (multiplicity of infection = 100:1) [10, 12]. Cells infected with Salmonella were collected at zero or eight hours post infection (hpi). Total RNA was prepared from the neutrophil solutions using the RNeasy Mini Kit as per the manufacturer’s instructions (Qiagen, Cat. no. 74104). The RNA quantity and quality were determined using the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Samples with an RNA Integrity Number (RIN) < 7 or a yield < 10 μg were excluded from the experiment.
Deep sequencing, statistical analysis, and functional annotation
A total of six samples were collected from each group (three samples from male animals and three samples from female animals) at zero and eight hpi, and were randomly selected for transcriptome analysis. Sequencing libraries were prepared using the Illumina TruSeq RNA Sample Preparation kit according to the manufacturer’s protocol (Illumina Inc., USA). Sequencing was conducted using an Illumina HiSeq 2000 (Illumina Inc., USA) by single-read sequencing with a read length of 50 bp. The obtained raw reads were filtered by removing the low-quality reads, i.e., reads containing unknown bases (N) and reads containing bases with a quality value ≤ 5. Bowtie1  was used to map clean reads to the reference gene set, which was extracted from the NCBI reference sequence database . The LIMMA R package  was used to calculate read counts per gene per length, which was used to compare the differences in gene expression between samples collected at zero and eight hpi. The criteria for differentially expressed genes were controlled as FDR (false discovery rate) ≤ 0.05 and fold change ≥ 1.5 or ≤ 0.67 (standard).
The most current porcine gene annotation (Sus scrofa assembly 11.1, gene 99) was used to assign the transcripts to mouse RefSeq according to the dual best match method. InnateDB  was used to identify significantly up-regulated pathways between zero and eight hpi and DAVID  was used to annotate the genes. The GEREA bioinformatics tool  was used to identify the overrepresented regulator genes. All data discussed in this study have been deposited into the NCBI GEO database  under accession number GSE148236.
Measuring TRP53 levels following neutrophil infection with Salmonella using flow cytometry and Real-time PCR
Fifteen out of the twenty neutrophil samples (with the best yield of cell counts) were randomly selected and divided into five groups (after 2 h of recovering). Each group was used in separate experiments. Two groups were treated with RPL39 or RPL9 siRNA (10 nM, Nicolas’s sequence ) using Monceaux’s protocol . Another two groups were treated with TRP53 inhibitor (Pifithrin-α hydrobromide, 0.5 pmol/mL (final); 63208-82-2, R&D Systems, Inc, MN, USA), or its activator (NSC 146109 hydrochloride, 0.5 pmol/mL (final), 59474-01-0, R&D Systems, Inc, MN, USA) at 37 ℃. A fifth group was left untreated. Samples were collected at zero, four, and eight hours post treatment (hpt). The TRP53 level in the samples was determined by dual channel flow cytometry using Phospho-p53 (Cell Signaling Technology, Inc. 8514S) and CD14 antibodies (Cell Signaling Technology, Inc. 29943S) according to the manufacturer’s instructions. The data have been deposited in the Flow Repository database  under accession number FR-FCM-Z2JQ.
In order to measure neutrophil gene expression following pre-treatment with RPL39 siRNA, RPL9 siRNA, TRP53 activator, or TRP53 inhibitor and subsequent infection with Salmonella, a real-time PCR assay was performed using the SYBR® Green Real-Time PCR Master Mixes (Applied Biosystems™, Inc. 4367659) according to the manufacturer’s instructions. GAPDH and ACTB were used as the house keeping genes. The primer sequences are provided in Additional file 1.
Intracellular proliferation of Salmonella in neutrophils
Primary porcine neutrophils were isolated and infected with Salmonella as described above. The intracellular proliferation assay was performed in accordance with a previously established protocol [10, 12]. The neutrophils pre-treated with RPL39 siRNA, RPL9 siRNA, TRP53 activator, TRP53 inhibitor, or left untreated were washed twice and resuspended in PBS. Consequently, 106 viable GFP-labeled Salmonella bacteria cells (ATCC® 14028™ GFP) were mixed with neutrophils at a ratio of 100:1, and the mixture of neutrophils and bacteria was incubated at 37 °C, 5% CO2 for 2 h. The cells were then rinsed three times with PBS and RPMI 1640 medium (Roswell Park Memorial Institute 1640 Medium), mixed with 100 μg/mL (final) of gentamicin, and incubated for 2 h at 37 °C. The neutrophil cells were collected and then further cultured in 10 μg/mL of gentamicin medium in three replicates for 12 h. Cell samples were collected at 4 h and 8 h following the addition of Salmonella to the neutrophils. The bacteria-containing cells (GFP positive) were measured via flow cytometry using the FITC channel according to the manufacturer’s instructions. Data were deposited in the Flow Repository database  under accession number FR-FCM-Z2JR.
Salmonella Typhimurium regulates porcine neutrophil transcriptomes
A total of twelve samples (with the best RNA quality) of infected neutrophils were sequenced, yielding approximately 25 million reads per sample. A total of 14,150 transcripts were covered, with an average sequencing depth of 406X (Additional file 1). The sequencing data was found to contain ~ 1% of Salmonella sequences. The result revealed 1,781 transcripts that were differentially expressed between zero and eight hpi (FDR < 0.05 and fold change > 1.5, Table 1 lists the most significant (fdr) transcripts, the full list is available in Additional file 1). The transcripts that were most significantly differentially expressed were encoded by SLC10A1 (down-regulated 83.41-fold), MME (down-regulated 56.41-fold), DOCK4 (down-regulated 38.56-fold), NDUFB2 (up-regulated 30.26-fold), ABI3 (down-regulated 22.13-fold), and CHI3L1 (down-regulated 20.98-fold,). Interestingly, annotation indicated that the expression of a large number of innate immunity-related genes, including IFIT2, IFIT1, ZBP1, MX1, MX2, IFIT3, EIF2KAK2, and IRF7, was down-regulated after eight hours of Salmonella infection. Furthermore, 22 ribosomal proteins, including RPL9, RPS14, RPS11, RPL39, MRPS12, MRPS18C, RPL37, and MRPL20, were down-regulated after eight hours of Salmonella infection. A total of 68 mitochondrion-related proteins, including GFM1, NT5DC3, MUTYH, SOD1, CYP1B1, CRAT, PRDX4, TIMM44, ACADM, and YWHAG, were up-regulated after eight hours of Salmonella infection compared with without infection.
The ribosomal pathway was inhibited and the TRP53 pathway was activated in neutrophils following Salmonella Typhimurium infection
Pathway analysis indicated that 20 pathways were up-regulated and 25 pathways were down-regulated following Salmonella Typhimurium infection (P < 0.005, Table 2). The most down-regulated pathway was the ribosomal pathway, which included 12 down-regulated ribosomal protein genes (Additional file 1). The second most down-regulated pathway was the cytokine-cytokine receptor interaction pathway, which contains 14 differentially expressed genes. The third most down-regulated pathway was the interferon (IFN) α and β signaling pathways, which had 14 differentially expressed genes. There were also 6 mRNA translation-related pathways that were down-regulated, among which the eukaryotic translation initiation pathway, the peptide chain elongation pathway, and the eukaryotic translation termination pathway were most significantly down-regulated. Overall, these data indicated that ribosomal pathways were considerably impacted by Salmonella infection.
There were also several up-regulated pathways in the neutrophils following Salmonella infection (Table 2). The top three were microRNA (miRNA) biogenesis, propanoate metabolism, and pyruvate metabolism. Interestingly, the TRP53 pathway, which included 12 differentially expressed genes, was also significantly up-regulated. Among the differentially expressed ribosomal protein genes, RPS11, RPL9, and RPL39 were the most significant (Table 1 and Additional file 1). Interestingly, RPL39 and RPL9 are known to be highly associated with TRP53 levels . RPL39 and RPL9 encode the ribosomal protein L39 and L9, whereas TRP53 encodes the tumor protein p53, which is an important regulator in the intracellular proliferation of Salmonella enterica serovar Typhimurium LT2 in pigs . Therefore, RPL39, RPL9, and TRP53 were selected for further validation in the following analysis.
Silencing of RPL39 and RPL9 caused up-regulation of TRP53 level in neutrophils
Primary pig neutrophils were left untreated (Figure 1T0), or were treated with RPL39 siRNA, RPL9 siRNA, or were stimulated with TRP53 inhibitor or activator for four hpt (Figure 1T4) and eight hpt (Figure 1T8). TRP53 levels in each treatment were monitored via flow cytometry. Three subsets of cell populations emerged from the analysis of CD14/TRP53 in neutrophils at eight hpt: CD14high/TLR2high, CD14low/TRP53low, and CD14high/TLR2low (Figure 1T8). The percentage of CD14high/TLR2high cells was increased in RPL39 knock-down neutrophils at both four and eight hpt (P < 0.05). However, the proportion of CD14low/TRP53low cells remained almost unchanged (Figure 1A). The percentage of CD14high/TLR2high cells in RPL9 knock-down neutrophils remained unchanged at four hpt but was increased at eight hpt (P < 0.05). The proportion of CD14low/TRP53low cells after the RPL9 siRNA treatment remained almost unchanged at four hpt but was decreased at eight hpt (P < 0.05, Figure 1B). All three subset populations remained almost unchanged at both four and eight hpt after the TRP53 inhibitor treatment (Figure 1C). The percentage of CD14high/TRP53high cells was increased by 50% in samples exposed to the TRP53 activator at both four hpt and eight hpt, compared with the zero hour controls (Figure 1D). At four hpt, the CD14high/TLR2high population treated with the TRP53 activator was twice as large as the RPL39 and RPL9 silenced neutrophils. The neutrophils treated with the TRP53 inhibitor had the lowest CD14high/TLR2high population at four hpt. At eight hpt, the CD14high/TLR2high cell population was increased when treated with the TRP53 activator, RPL39 siRNA, and RPL9 siRNA. The CD14high/TLR2high cell population remained the lowest when treated with the TRP53 inhibitor. Therefore, treatment with RPL39 siRNA and RPL9 siRNA enhanced TRP53 expression, confirming their inverse association.
RPL39 and RPL9 siRNA treatment activated genes associated with cell cycle arrest and apoptosis and inhibited innate immunity genes
The transcription level of four TRP53 target genes (FAS, RB1, CASP6, and GADD45A) and two innate immunity genes (NFKB and IFNG) were investigated in neutrophils following the treatments and infections described above. The transcription level of FAS increased after exposure to the TRP53 activator, RPL39 siRNA, and RPL9 siRNA at both four and eight hpt (P < 0.05, Figure 2A). The transcription level of FAS in neutrophils treated with the TRP53 inhibitor remained unchanged at eight hpt. The transcription level of RB1 in neutrophils treated with RPL39 and RPL9 siRNA at four and eight hpt was double the zero hour control sample (Figure 2B), whereas the transcription level of RB1 in neutrophils treated with the TRP53 activator at four and eight hpt was approximately 2.5-fold higher than in the zero hour control. Our results also showed that the transcription level of RB1 in neutrophils treated with the TRP53 inhibitor remained almost the same as in the control samples. Similar to FAS and RB1, the transcription profile of CASP6 increased in neutrophils treated with RPL39 siRNA after four hours and was increased in RPL9 siRNA and TRP53 activator-treated neutrophils at both four and eight hpt (P < 0.05, Figure 2C). The transcription level of CASP6 in neutrophils treated with the TRP53 inhibitor remained stable at both four and eight hpt. We also found that the transcription levels of GADD45A in neutrophils treated with RPL39 siRNA, RPL9 siRNA, and TRP53 activator were significantly higher than in non-treated controls at both four and eight hpt (P < 0.05, Figure 2D). Conversely, the transcription level of GADD45A in the TRP53 inhibitor-treated samples at eight hpt was lower than in the controls. The transcription levels of IFNG in RPL39 siRNA, RPL9 siRNA, and TRP53 activator-treated neutrophils were significantly lower than in the non-treated controls at both four and eight hpt (P < 0.05, Figure 2E). The expression profile of NFKB was shown to be similar to IFNG, and expression was inhibited in most of the RPL39 siRNA, RPL9 siRNA, and TRP53 activator-treated samples (Figure 2F). However, at four and eight hours post TRP53 inhibitor treatment, the level of NFKB and IFNG mRNA remained almost the same as in non-treated controls.
The ribosomal/TRP53 pathway is likely to be associated with intracellular proliferation of Salmonella in infected neutrophils
Porcine neutrophils were left untreated (Figure 3T0) or were pre-treated with RPL39 siRNA, RPL9 siRNA, a TRP53 inhibitor, or a TRP53 activator before infection with GFP-labeled Salmonella for four (Figure 3T4) and eight hours hpt (Figure 3T8), during which intracellular Salmonella counts were monitored by flow cytometry. The percentage of GFPpos (GFP-positive) cells was increased when treated with RPL39 siRNA at both four and eight hpt (P < 0.05), and the percentage of GFPpos cells was approximately 15% higher at eight hpt than at four hpt (Figure 3A). The percentage of GFPpos cells was also increased in RPL9 siRNA-treated neutrophils at both four and eight hours (P < 0.05), with the percentage of GFPpos cells being 13% higher at eight compared with at four hpt (Figure 3B). Treatment with the TRP53 inhibitor presented with the lowest GFPpos cells (approximately 30%) at both four and eight hpt, indicating a lower number of bacteria (Figure 3C). At eight hpt, fluorescence had increased the most (45%) in GFPpos cells treated with the TRP53 activator, indicating a high level of intracellular Salmonella (Figure 3D).
Previous studies have demonstrated that Salmonella enterica serovar Typhimurium infection in piglets can lead to the inhibition of the transcription of ribosomal genes in peripheral blood [9, 10]. This has been confirmed in our study, wherein infection with Salmonella was shown to inhibit the transcription of 12 ribosomal genes in primary porcine neutrophils. This decrease in ribosomal transcription will strongly impact the activity of the ribosomal protein machine, and the initiation, extension, and/or termination of translation will be blocked, and finally will lead to the reduction in protein synthesis. Here, we found that the ribosomal protein genes RPL39 and RPL9 were highly down-regulated when neutrophils were infected with Salmonella. RPL39 and RPL9 are central protuberance-specific assembly factors that are the most important ribosomal proteins contributing to the maintenance of normal nucleolar structure. Therefore, the knock-down of RPL39 and RPL9 can prevent the formation of a normal nucleolar structure . Many ribosomal proteins are likely involved in the regulation of TRP53. Our data indicate that the decrease in RPL39 and RPL9 results in the up-regulation and accumulation of TRP53 protein in neutrophils.
Our results indicate that the Salmonella-mediated inhibition of RPL39 and RPL9 can increase the expression of FAS, RB1, CASP6, and GADD45A in a TRP53-dependent manner. We also found that two innate immunity genes, INFG and NFKB, were significantly inhibited by RPL39 siRNA, RPL9 siRNA, and TRP53 activator treatment. FAS encodes a protein containing a death domain and plays a central role in the physiological regulation of programmed cell death. FAS has also been implicated in the pathogenesis of various malignancies and immune diseases . The interaction of this receptor with its ligand leads to the formation of a death-inducing signaling complex that triggers a downstream caspase cascade, leading to apoptosis . RB1 encodes a protein that is a negative regulator of the cell cycle process and acts by binding and regulating the transcription factor E2F1s [25, 26]. CASP6 encodes a caspase protein, which plays a central role in the execution-phase of cell apoptosis . GADD45A is an important factor that maintains the cells in stressful and growth arrest conditions . FAS, RB1, CASP6, and GADD45A are downstream of the TRP53 cascade, and activation of these genes would lead to cell cycle arrest and apoptosis. Therefore, we hypothesize that inhibition of ribosomal genes and activation of apoptosis could be an important mechanism for Salmonella to regulate intercellular conditions, promoting survival and replication within neutrophils. Furthermore, the inhibition of NFKB and IFNG transcription and the down-regulation of the TNF pathway indicate that the infected neutrophils have decreased immune function, which would provide a niche for Salmonella survival and replication.
TRP53 is a tumor suppressor gene that balances cell survival and death in response to a variety of intrinsic and extrinsic stress signals [29, 30]. Infection with Salmonella enterica serovar Typhimurium LT2 has been demonstrated to increase the TRP53 level in the serum of piglets , which could induce cell-cycle arrest or apoptosis [31, 32]. It has been shown that TRP53 activity can be induced in a type I IFN-dependent manner . However, our results indicate that the IFN-α/INF-β signaling was significantly inhibited in Salmonella-infected neutrophils, which suggests that TRP53 was activated by effectors other than IFNs. TRP53 can direct E2F2-mediated growth arrest, which involves the target gene GADD45A . GADD45A has previously been shown to be up-regulated in Salmonella-challenged pigs  and is currently shown to be up-regulated in Salmonella-infected neutrophils. This further supports the hypothesis that during Salmonella infection, the cell cycle of neutrophils is arrested and apoptosis is promoted.
Here, we showed that the knock-down of RPL39 and RPL9, or the activation of TRP53, could promote intracellular Salmonella proliferation in neutrophils. We speculate that this impact on Salmonella growth is caused by favoring a cell cycle arrested state, allowing the bacteria to proliferate more successfully. This is similar to other documented cases where bacterial pathogens block cell cycle progression, which leads to favorable conditions for colonization and dissemination [35, 36].
This study described the inhibition of RPL39 and RPL9 transcription following Salmonella infection, which leads to the activation of TRP53. This ribosomal/TRP53 pathway is an important factor that influences the intracellular proliferation of Salmonella counts in neutrophils (summarized in Figure 4). However, detailed mechanisms of how Salmonella regulates the transcription level of ribosomal genes underlying this observation remain to be discovered.
colony forming units
false discovery rate
hours post infection
hours post treatment
rNA Integrity Number
reactive oxygen species
Hendriksen RS, Vieira AR, Karlsmose S, Lo Fo Wong DM, Jensen AB, Wegener HC, Aarestrup FM (2011) Global monitoring of Salmonella serovar distribution from the World Health Organization Global Foodborne Infections Network Country Data Bank: results of quality assured laboratories from 2001 to 2007. Foodborne Pathog Dis 8:887–900
Bearson SM, Allen HK, Bearson BL, Looft T, Brunelle BW, Kich JD, Tuggle CK, Bayles DO, Alt D, Levine UY, Stanton TB (2013) Profiling the gastrointestinal microbiota in response to Salmonella: low versus high Salmonella shedding in the natural porcine host. Infect Genet Evol 16:330–340
Burton NA, Schurmann N, Casse O, Steeb AK, Claudi B, Zankl J, Schmidt A, Bumann D (2014) Disparate impact of oxidative host defenses determines the fate of Salmonella during systemic infection in mice. Cell Host Microbe 15:72–83
Slauch JM (2011) How does the oxidative burst of macrophages kill bacteria? Still an open question, Mol Microbiol 80:580–583
Geddes K, Cruz F, Heffron F (2007) Analysis of cells targeted by Salmonella type III secretion in vivo. PLoS Pathog 3:e196
Chiu CH, Ou JT (1999) Intracellular Salmonella typhimurium induce lysis of human polymorphonuclear leukocytes which is not associated with the Salmonella virulence plasmid. Microbiol Immunol 43:9–14
Shiloh MU, Ruan J, Nathan C (1997) Evaluation of bacterial survival and phagocyte function with a fluorescence-based microplate assay. Infect Immun 65:3193–3198
Baron EJ, Proctor RA (1984) Inefficient in vitro killing of virulent or nonvirulent Salmonella typhimurium by murine polymorphonuclear neutrophils. Can J Microbiol 30:1264–1270
Huang TH, Uthe JJ, Bearson SM, Demirkale CY, Nettleton D, Knetter S, Christian C, Ramer-Tait AE, Wannemuehler MJ, Tuggle CK (2011) Distinct peripheral blood RNA responses to Salmonella in pigs differing in Salmonella shedding levels: intersection of IFNG. TLR and miRNA pathways, PLoS One 6:e28768
Huang T, Huang X, Shi B, Wang F, Feng W, Yao M (2018) Regulators of Salmonella-host interaction identified by peripheral blood transcriptome profiling: roles of TGFB1 and TRP53 in intracellular Salmonella replication in pigs. Vet Res 49:121
Uthe JJ, Wang Y, Qu L, Nettleton D, Tuggle CK, Bearson SM (2009) Correlating blood immune parameters and a CCT7 genetic variant with the shedding of Salmonella enterica serovar Typhimurium in swine. Vet Microbiol 135:384–388
Huang T, Huang X, Yao M (2018) miR-143 inhibits intracellular salmonella growth by targeting ATP6V1A in macrophage cells in pig. Res Vet Sci 117:138–143
Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10:R25
O'Leary NA, Wright MW, Brister JR, Ciufo S, Haddad D, McVeigh R, Rajput B, Robbertse B, Smith-White B, Ako-Adjei D, Astashyn A, Badretdin A, Bao Y, Blinkova O, Brover V, Chetvernin V, Choi J, Cox E, Ermolaeva O, Farrell CM, Goldfarb T, Gupta T, Haft D, Hatcher E, Hlavina W, Joardar VS, Kodali VK, Li W, Maglott D, Masterson P, McGarvey KM, Murphy MR, O'Neill K, Pujar S, Rangwala SH, Rausch D, Riddick LD, Schoch C, Shkeda A, Storz SS, Sun H, Thibaud-Nissen F, Tolstoy I, Tully RE, Vatsan AR, Wallin C, Webb D, Wu W, Landrum MJ, Kimchi A, Tatusova T, DiCuccio M, Kitts P, Murphy TD, Pruitt KD (2016) Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res 44:D733–745
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43:e47
Lynn DJ, Winsor GL, Chan C, Richard N, Laird MR, Barsky A, Gardy JL, Roche FM, Chan TH, Shah N, Lo R, Naseer M, Que J, Yau M, Acab M, Tulpan D, Whiteside MD, Chikatamarla A, Mah B, Munzner T, Hokamp K, Hancock RE, Brinkman FS (2008) InnateDB: facilitating systems-level analyses of the mammalian innate immune response. Mol Syst Biol 4:218
da Huang W, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4:44–57
Huang T, Huang X, Shi B, Yao M (2019) GEREDB: Gene expression regulation database curated by mining abstracts from literature. Journal of bioinformatics and computational biology 17:1950024
Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Holko M, Yefanov A, Lee H, Zhang N, Robertson CL, Serova N, Davis S, Soboleva A (2013) NCBI GEO: archive for functional genomics data sets–update. Nucleic Acids Res 41:D991–995
Nicolas E, Parisot P, Pinto-Monteiro C, de Walque R, De Vleeschouwer C, Lafontaine DL (2016) Involvement of human ribosomal proteins in nucleolar structure and p53-dependent nucleolar stress. Nat Commun 7:11390
Monceaux V, Chiche-Lapierre C, Chaput C, Witko-Sarsat V, Prevost MC, Taylor CT, Ungeheuer MN, Sansonetti PJ, Marteyn BS (2016) Anoxia and glucose supplementation preserve neutrophil viability and function. Blood 128:993–1002
Spidlen J, Breuer K, Rosenberg C, Kotecha N, Brinkman RR (2012) FlowRepository: a resource of annotated flow cytometry datasets associated with peer-reviewed publications. Cytometry A 81:727–731
Shen Y, Song Z, Lu X, Ma Z, Lu C, Zhang B, Chen Y, Duan M, Apetoh L, Li X, Guo J, Miao Y, Zhang G, Yang D, Cai Z, Wang J (2019) Fas signaling-mediated TH9 cell differentiation favors bowel inflammation and antitumor functions. Nat Commun 10:2924
Mou H, Moore J, Malonia SK, Li Y, Ozata DM, Hough S, Song CQ, Smith JL, Fischer A, Weng Z, Green MR, Xue W (2017) Genetic disruption of oncogenic Kras sensitizes lung cancer cells to Fas receptor-mediated apoptosis. Proc Natl Acad Sci U S A 114:3648–3653
Carreira S, Goodall J, Aksan I, La Rocca SA, Galibert MD, Denat L, Larue L, Goding CR (2005) Mitf cooperates with Rb1 and activates p21Cip1 expression to regulate cell cycle progression. Nature 433:764–769
Cho HS, Hayami S, Toyokawa G, Maejima K, Yamane Y, Suzuki T, Dohmae N, Kogure M, Kang D, Neal DE, Ponder BA, Yamaue H, Nakamura Y, Hamamoto R (2012) RB1 methylation by SMYD2 enhances cell cycle progression through an increase of RB1 phosphorylation. Neoplasia 14:476–486
Vigneswara V, Akpan N, Berry M, Logan A, Troy CM, Ahmed Z (2014) Combined suppression of CASP2 and CASP6 protects retinal ganglion cells from apoptosis and promotes axon regeneration through CNTF-mediated JAK/STAT signalling. Brain 137:1656–1675
Barreto G, Schafer A, Marhold J, Stach D, Swaminathan SK, Handa V, Doderlein G, Maltry N, Wu W, Lyko F, Niehrs C (2007) Gadd45a promotes epigenetic gene activation by repair-mediated DNA demethylation. Nature 445:671–675
Zwang Y, Oren M, Yarden Y (2012) Consistency test of the cell cycle: roles for p53 and EGR1. Cancer Res 72:1051–1054
Apostolidis PA, Lindsey S, Miller WM, Papoutsakis ET (2012) Proposed megakaryocytic regulon of p53: the genes engaged to control cell cycle and apoptosis during megakaryocytic differentiation. Physiol Genomics 44:638–650
Harris SL, Levine AJ (2005) The p53 pathway: positive and negative feedback loops. Oncogene 24:2899–2908
Schlereth K, Charles JP, Bretz AC, Stiewe T (2010) Life or death: p53-induced apoptosis requires DNA binding cooperativity. Cell Cycle 9:4068–4076
Takaoka A, Hayakawa S, Yanai H, Stoiber D, Negishi H, Kikuchi H, Sasaki S, Imai K, Shibue T, Honda K, Taniguchi T (2003) Integration of interferon-alpha/beta signalling to p53 responses in tumour suppression and antiviral defence. Nature 424:516–523
Sharma N, Timmers C, Trikha P, Saavedra HI, Obery A, Leone G (2006) Control of the p53–p21CIP1 Axis by E2f1, E2f2, and E2f3 is essential for G1/S progression and cellular transformation. J Biol Chem 281:36124–36131
Fehri LF, Rechner C, Janssen S, Mak TN, Holland C, Bartfeld S, Bruggemann H, Meyer TF (2009) Helicobacter pylori-induced modification of the histone H3 phosphorylation status in gastric epithelial cells reflects its impact on cell cycle regulation. Epigenetics 4:577–586
Khan R, Sancho-Shimizu V, Prendergast C, Roy MF, Loredo-Osti JC, Malo D (2012) Refinement of the genetics of the host response to Salmonella infection in MOLF/Ei: regulation of type 1 IFN and TRP3 pathways by Ity2. Genes Immun 13:175–183
We thank Chenglong Li, Yongxia Li, Shan Jiang, and Liang He for critically reviewing the manuscript for important intellectual content.
This project was funded by the National Natural Science Foundation of China [NSFC Grant Nos. 31902231 and 31402055], the College Students' Innovation and Entrepreneurship Training Program of Yangtze University [Grant No. 2019110], the Science and Technology Research Project of Department of Education of Hubei Province [Grant No. Q20171305], the Yangtze Youth Talents Fund [Grant No. 2015cqr12], and the Yangtze Youth Fund [Grant No. 2015cqn39]. The funding body played no role in the design of the study, or in the collection, analysis, or interpretation of data, or in writing the manuscript.
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The sample collection was approved by the Animal Care and Use Committee of Hubei Province (China, YZU-2018-0031).
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Huang, T., Jiang, C., Yang, M. et al. Salmonella enterica serovar Typhimurium inhibits the innate immune response and promotes apoptosis in a ribosomal/TRP53-dependent manner in swine neutrophils. Vet Res 51, 105 (2020). https://doi.org/10.1186/s13567-020-00828-3