RclS Sensor Kinase Modulates Virulence of Pseudomonas capeferrum

Abstract

Signal transduction systems are the key players of bacterial adaptation and survival. The orthodox two-component signal transduction systems perceive diverse environmental stimuli and their regulatory response leads to cellular changes. Although rarely described, the unorthodox three-component systems are also implemented in the regulation of major bacterial behavior such as the virulence of clinically relevant pathogen P. aeruginosa. Previously, we described a novel three-component system in P. capeferrum WCS358 (RclSAR) where the sensor kinase RclS stimulates the intI1 transcription in stationary growth phase. In this study, using rclS knock-out mutant, we identified RclSAR regulon in P. capeferrum WCS358. The RNA sequencing revealed that activity of RclSAR signal transduction system is growth phase dependent with more pronounced regulatory potential in early stages of growth. Transcriptional analysis emphasized the role of RclSAR in global regulation and indicated the involvement of this system in regulation of diverse cellular activities such as RNA binding and metabolic and biocontrol processes. Importantly, phenotypic comparison of WCS358 wild type and ΔrclS mutant showed that RclS sensor kinase contributes to modulation of antibiotic resistance, production of AHLs and siderophore as well as host cell adherence and cytotoxicity. Finally, we proposed the improved model of interplay between RclSAR, RpoS and LasIR regulatory systems in P. capeferrum WCS358.

Keywords: Pseudomonas; RNA sequencing; antibiotic resistance; sensor kinase; three-component system; virulence.

Figure 1

Gene co-expression. Venn diagrams depicted number of common and uniquely expressed genes in WCS358 wild type and ΔrclS mutant (A) in exponential growth phase; (B) in stationary growth phase; (C) in exponential and stationary growth phase.

Figure 2

Hierarchical clustering of DEGs detected in WCS358 wild type and ΔrclS mutant in exponential and stationary growth phase. Scaled log2 expression values are presented in red and blue indicating high and low expressions, respectively.

Figure 3

Summarized GO enrichment analysis of detected DEGs. The 20 most enriched GO terms are represented for exponential (A) and stationary (B) growth phase. The length of bar charts indicates statistical significance of each GO term (* p < 0.05).

Figure 4

KEGG enrichment analysis of detected DEGs. The top 20 enriched KEGG pathways of DEGs in exponential (A) and stationary (B) growth phase. The x-axis represents the gene ratio, ratio of DEGs in pathway to the total number of annotated genes in the pathway. The value of gene ratio is proportional to the degree of enrichment. The size of the dots indicates the number of DEGs in each pathway, while the dot color represents corrected p values. The color vicinity to red is proportional to the enrichment significance.

Figure 5

RT-qPCR based validation of RNA-seq analysis. Transcriptional level of eight selected genes in WCS358 wild type and ΔrclS mutant at two time points (OD = 1 and OD = 2) is represented as FPKM value (RNA-seq) and relative expression value normalized against those obtained for wild type in exponential growth phase (RT-qPCR). RT-qPCR data is represented as mean values ± standard deviations for three biological replicates. Student’s t-test was employed to compare differences between wild type and ΔrclS mutant measured by RT-qPCR (* p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001).

Figure 6

The effect of RclS knock-out to AHL production and biofilm formation in WCS358. (A) Production of AHLs by WCS358 wild type and ΔrclS mutant is represented as relative fluorescence units corrected for autofluorescence per unit of OD₆₀₀ (RFU per OD₆₀₀). Cell suspensions with 3-oxo-C10-HSL and 3-oxo-C12-HSL were used as a positive control. (B) Biofilm formation of WCS358 wild type and ΔrclS mutant was quantified by measuring absorbance at 595 nm after 24 and 48 h of incubation. The tests were performed in sextuplicate with three independent repeats. The results are represented as mean values ± standard deviations. Student’s t-test was employed to compare differences between wild type and ΔrclS mutant (**** p < 0.0001).

Figure 7

Cytotoxic effect and adhesion ability of WCS358 wild type and ΔrclS mutant using HaCaT keratynocite cell line as a model system. (A) Cytotoxicity level (%) of wild type and ΔrclS mutant measured by LDH assay was expressed relative to negative control (0%). (B) Adhesion ability of wild type and ΔrclS mutant was expressed as a ratio of adhered bacteria relative to added bacteria (log CFU/mL). The results are represented as mean values ± standard deviations for three biological replicates. Student’s t-test was employed to compare differences between wild type and ΔrclS mutant (** p < 0.01).

Figure 8

Improved interconnection model of P. capeferrum WCS358 regulatory systems (RclSAR, LasIR and RpoS) in stationary growth phase (improvement of model proposed by Bertani and Venturi (2004) [16], adapted with permission). Triggering of signal transduction pathway starting with RclS activation leads to increased expression of the lasI, lasR (this study) and rpoS genes [7]. Gene regulation network between RpoS, LasIR (PpuIR), RsaL and PsrA proteins were described in previous study [16]. Dashed lines indicate indirect gene regulation by RclS sensor kinase.