Global transcriptome and mutagenic analyses of the acid tolerance response of Salmonella enterica serovar Typhimurium

Abstract

Salmonella enterica serovar Typhimurium (S. Typhimurium) is one of the leading causative agents of food-borne bacterial gastroenteritis. Swift invasion through the intestinal tract and successful establishment in systemic organs are associated with the adaptability of S. Typhimurium to different stress environments. Low-pH stress serves as one of the first lines of defense in mammalian hosts, which S. Typhimurium must efficiently overcome to establish an infection. Therefore, a better understanding of the molecular mechanisms underlying the adaptability of S. Typhimurium to acid stress is highly relevant. In this study, we have performed a transcriptome analysis of S. Typhimurium under the acid tolerance response (ATR) and found a large number of genes (∼47%) to be differentially expressed (more than 1.5-fold or less than -1.5-fold; P < 0.01). Functional annotation revealed differentially expressed genes to be associated with regulation, metabolism, transport and binding, pathogenesis, and motility. Additionally, our knockout analysis of a subset of differentially regulated genes facilitated the identification of proteins that contribute to S. Typhimurium ATR and virulence. Mutants lacking genes encoding the K(+) binding and transport protein KdpA, hypothetical protein YciG, the flagellar hook cap protein FlgD, and the nitrate reductase subunit NarZ were significantly deficient in their ATRs and displayed varied in vitro virulence characteristics. This study offers greater insight into the transcriptome changes of S. Typhimurium under the ATR and provides a framework for further research on the subject.

FIG 1

The acid tolerance response of Salmonella Typhimurium. Shown is the log-phase acid tolerance response of Salmonella Typhimurium wild-type (WT) strain SB300 in minimal E glucose medium. Both adapted cells (pH 4.4 for 1 h) and unadapted cells were challenged at pH 3.1 (3 N HCl) for 1, 2, and 4 h postchallenge. Bacterial counts were determined at the above time points, and the percentages of viability were calculated for the same time points. Statistical analysis was performed in GraphPad Prism version 6.0, using two-way ANOVA. Statistical significance: ***, P < 0.001; ****, P < 0.0001.

FIG 2

Global changes in gene expression under the ATR. (A) Experimental design. Total RNA was isolated at the indicated pH levels in duplicate. pH 7.5 was used as the reference pH. (B) Hierarchical clustering of differentially regulated genes showing sample duplicates under three pH conditions. Clustering revealed the partitioning of sample duplicates across pH conditions. (C) Sample duplicates displayed a high degree of correlation, with Pearson correlation coefficients ranging from 0.9 to 1. (D) Distribution of mean read counts during adaptation (pH 7.5 versus 4.1). (E) Distribution of mean read counts during challenge (pH 7.5 versus 3.1). Red dots indicate upregulated genes, green dots indicate downregulated genes, and black dots indicate no differential expression.

FIG 3

Expression profile of pathogenicity island-associated genes. Shown is a detailed transcriptional profile of genes that play a role in invasion (SPI1) and intracellular survival (SPI2) of S. Typhimurium. Each row represents a gene, with pH levels shown across columns. Fold change values are represented by the color bar alongside the figure. For further details, refer to Tables S4 and S5 in the supplemental material.

FIG 4

Expression profile of genes involved in flagellar assembly and chemotaxis. The values in the first and second columns represent fold change across the pH conditions indicated at the top of the columns.

FIG 5

Comparison of gene expression identified by RNA-seq and RT-PCR. The figure compares the mean fold change expression of sample duplicates under the ATR between RT-PCR and RNA-seq. Six upregulated and two downregulated genes were compared under three conditions: normal (pH 7.5), adapted (pH 4.4), and challenged (pH 3.1). gmk was used as an internal control, with target expression at pH 7.5 normalized to 1. Both qRT-PCR and RNA-seq data correlated well in terms of determining up- and downregulated genes; however, fold change values showed variation due to significant differences in the sensitivities of the two platforms.

FIG 6

Characterization of deletion mutants under the ATR and their roles in virulence. (A) Deletion mutants of differentially regulated genes were assayed for their survival under the ATR over a time course of 4 h with wild-type (WT) SB300 as a control. Growth curves of individual mutants and wild-type SB300 over a period of 8 h are shown in the inset. (B) Motility assay of deletion mutants and wild-type SB300. The average diameter (d [n = 3]) of motile cell growth in centimeters is shown in the bottom right of each figure. (C and D) Adhesion and invasion assays of the respective mutants and wild-type SB300 in HCT116 colon epithelial cells. The data are presented as the percentage of survival normalized to a wild-type value of 100%. (E and F) Macrophage uptake and survival assay of mutants and wild-type SB300 in RAW264.7 cells. The data represent three independent experiments performed in triplicate. Statistical analysis was performed in GraphPad Prism version 6.0, using t tests and two-way ANOVA. Statistical significance: *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001; ns, not significant.

FIG 7

Schematic representation of the genes involved in adaptation and survival of S. Typhimurium under acid stress. This model represents the transcriptional response of genes belonging to different functional modules (regulation, metabolism, transport and binding, pathogenesis, and motility) of S. Typhimuirum under the ATR. The genes and pathways mentioned in the Results and Discussion section have been reported. Colors indicate genes that were upregulated (red), downregulated (green), or nondifferentially regulated under both adaptation and challenge (gray) and genes that showed opposing levels of regulation under adaptation and challenge (orange).