| Literature DB >> 27981238 |
Eric C Fitts1, Jourdan A Andersson1, Michelle L Kirtley1, Jian Sha1, Tatiana E Erova1, Sadhana Chauhan1, Vladimir L Motin2, Ashok K Chopra1.
Abstract
The Enterobacteriaceae family members, including the infamous Yersinia pestis, the causative agent of plague, have a highly conserved interbacterial signaling system that is mediated by the autoinducer-2 (AI-2) quorum-sensing molecule. The AI-2 system is implicated in regulating various bacterial virulence genes in diverse environmental niches. Deletion of the gene encoding the synthetic enzyme for the AI-2 substrate, luxS, leads to either no significant change or, paradoxically, an increase in in vivo bacterial virulence. We showed that deletion of the rbsA and lsrA genes, components of ABC transport systems that interact with AI-2, synergistically disrupted AI-2 signaling patterns and resulted in a more-than-50-fold decrease in Y. pestis strain CO92 virulence in a stringent pneumonic plague mouse model. Deletion of luxS or lsrK (encoding AI-2 kinase) from the ΔrbsA ΔlsrA background strain or complementation of the ΔrbsA ΔlsrA mutant with the corresponding gene(s) reverted the virulence phenotype to that of the wild-type Y. pestis CO92. Furthermore, the administration of synthetic AI-2 in mice infected with the ΔrbsA ΔlsrA ΔluxS mutant strain attenuated this triple mutant to a virulence phenotype similar to that of the ΔrbsA ΔlsrA strain in a pneumonic plague model. Conversely, the administration of AI-2 to mice infected with the ΔrbsA ΔlsrA ΔluxS ΔlsrK mutant did not rescue animals from lethality, indicating the importance of the AI-2-LsrK axis in regulating bacterial virulence. By performing high-throughput RNA sequencing, the potential role of some AI-2-signaling-regulated genes that modulated bacterial virulence was determined. We anticipate that the characterization of AI-2 signaling in Y. pestis will lead to reexamination of AI-2 systems in other pathogens and that AI-2 signaling may represent a broad-spectrum therapeutic target to combat antibiotic-resistant bacteria, which represent a global crisis of the 21st century. IMPORTANCEYersinia pestis is the bacterial agent that causes the highly fatal disease plague. The organism represents a significant concern because of its potential use as a bioterror agent, beyond the several thousand naturally occurring human infection cases occurring globally each year. While there has been development of effective antibiotics, the narrow therapeutic window and challenges posed by the existence of antibiotic-resistant strains represent serious concerns. We sought to identify novel virulence factors that could potentially be incorporated into an attenuated vaccine platform or be targeted by novel therapeutics. We show here that a highly conserved quorum-sensing system, autoinducer-2, significantly affected the virulence of Y. pestis in a mouse model of pneumonic plague. We also identified steps in autoinducer-2 signaling which had confounded previous studies and demonstrated the potential for intervention in the virulence mechanism(s) of autoinducer-2. Our findings may have an impact on bacterial pathogenesis research in many other organisms and could result in identifying potential broad-spectrum therapeutic targets to combat antibiotic-resistant bacteria, which represent a global crisis of the 21st century.Entities:
Keywords: Yersinia pestis; animal models; autoinducer-2; pneumonic plague; quorum sensing; transcriptomics; virulence
Year: 2016 PMID: 27981238 PMCID: PMC5156673 DOI: 10.1128/mSphere.00342-16
Source DB: PubMed Journal: mSphere ISSN: 2379-5042 Impact factor: 4.389
FIG 1 AI-2 levels in cell-free supernatants of WT Y. pestis CO92 and its various mutant strains. (A and B) Concentrations of AI-2 in culture supernatants during growth at 28°C (A) or 37°C (B) are shown, with absorbance of culture at 600 nm in insets. (C) AI-2 levels in cell-free supernatants following dosing of cultures with synthetic exogenous AI-2. Data are from three independent cultures per strain. Arithmetic means ± standard deviations from three independent experiments are shown. Statistical analysis was performed using pairwise t tests with multiple comparison correction.
FIG 2 Intracellular survival of WT Y. pestis CO92 and its various mutant strains in macrophages. (A) The intracellular survival of WT Y. pestis and its various mutants in a RAW 264.7 murine macrophage cell line was evaluated at 0 and 4 h postinfection (hpi). Luminescent reporter strains from each background were utilized to evaluate real-time reporting of bacterial survival in macrophages. (B) Phagocytosis of bacteria was determined by comparing luminescence of infectious dose after culture to luminescence at 0 h. Data are from three independent experiments per strain. Arithmetic means ± standard deviations are shown. Statistical analysis was performed using one-way analysis of variance (ANOVA) with Tukey post hoc correction.
FIG 3 In vivo virulence of various Y. pestis mutants. (A and B) Survival of female Swiss-Webster mice (n = 5 to 10) in a pneumonic plague model after challenge with the stated dose (equivalent to WT LD50, where 1 LD50 is 500 CFU) of the rbsA, lsrA, or ΔrbsA ΔlsrA deletion mutant (A) or the ΔrbsA ΔlsrA double deletion strain complemented with the Tn7 transposon (B). Data are representative of three independent experiments. Statistical analysis was performed using Kaplan-Meier survival curve analysis.
FIG 4 In vivo virulence and AI-2 levels in cell-free supernatants of ΔluxS and ΔlsrK mutants. (A and C) Concentrations of AI-2 in culture supernatants over a 30-h period of growth at 28°C. Error bars represent standard deviations from three independent experiments. (B and D) Survival of female Swiss-Webster mice (n = 5 to 10) in a pneumonic plague model after challenge with 10-LD50 equivalent of WT CO92, where 1 LD50 is 500 CFU. Data are representative of three independent experiments. Statistical analysis for animal studies was performed using Kaplan-Meier survival curve analysis.
FIG 5 Analysis of AI-2 mutant transcriptomes. (A) A heat map was constructed against mean counts of the top 100 most variable genes across all samples, including WT CO92 (WT), ΔrbsA ΔlsrA (RL), ΔluxS, and ΔrbsA ΔlsrA ΔluxS (RLS) mutants. (B and C) Distance maps were created using Poisson (B) or Euclidean (C) distance against the transcriptome of each mutant examined. (D) Relative transcript levels from the RNA-seq data set were plotted for selected genes, with the level of each gene in each strain being compared to its level in WT CO92. (E) Relative expression levels of selected genes from qRT-PCR data were plotted for the indicated strains after growth with exogenous AI-2 added at the indicated concentrations. Standard deviations of the results from 3 independent experiments are shown.
FIG 6 In vivo complementation of the ΔrbsA ΔlsrA ΔluxS mutant with exogenous synthetic AI-2. (A) Survival of female Swiss-Webster mice (n = 5) in a pneumonic plague model after challenge with 10-LD50 equivalent of WT CO92, where 1 LD50 is 500 CFU. Mice were dosed with the indicated concentrations of synthetic AI-2 in PBS via the intranasal (i.n.) route at the time of infection and at 24 h and 48 h postinfection. Data are representative of three independent experiments. Statistical analysis was performed using Kaplan-Meier survival curve analysis.
Bacterial strains used in this study
| Genotype | Description | Origin |
|---|---|---|
| WT CO92 | Virulent | CDC |
| Δ | 11 | |
| Δ | 11 | |
| 11 | ||
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| WT CO92::Tn | This study | |
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Description of primers used in study
| Primer | Description | Sequence (5′→3′) |
|---|---|---|
| P1 | FLP, ampicillin, forward | CGCCTGTAGTGCCATTTACC |
| P2 | FLP, ampicillin, reverse | CATTACGCTGACTTGACGGG |
| P3 | FLP, forward | CCCGTCAAGTCAGCGTAATG |
| P4 | FLP, reverse | GGTAGCGTTGCCAATGATGT |
| P5 | SacB, FLP, forward | AATGGCACTACAGGCGTGGGAATTCTGATCCTTTTTAACCCATCAC |
| P6 | SacB, FLP, reverse | TCATTGGCAACGCTACCGCCATTTGCCTGCTTTTATATAGT |
| P7 | λ Red, LsrA, forward | ATTTGTTCAGTCCCGTCAGTCAACATTGAGGGAGCGGAGGCAACATGCAAGTGTAGGCTGGAGCTGCTTC |
| P8 | λ Red, LsrA, reverse | CCGGTTATTTTGGATGAATTTCAACATGTTGCCTCCGACGCACCATGTTCCGGGGATCCGTCGACC |
| P9 | λ Red, LuxS, forward | TTAGAAAAATATGACTTTTTTATGAGGAGGTAACTAAATGCCATTATTGGGTGTAGGCTGGAGCTGCTTC |
| P10 | λ Red, LuxS, reverse | CGCCTTTTATCATTCTCCTGCCTACTGATACTGAGCACTAAATATGCAATATTCCGGGGATCCGTCGACC |
| P11 | LsrA, Tn | CCAACACTCGAGAGGGCAAATAGGGTGAGAATG |
| P12 | LsrA, Tn | TCCTTCGAATTCAGCCACTGCGTAATGAATGTTT |
| P13 | LsrA, reverse, sequencing | ATCTATCACCCCAGACTGCC |
| P14 | LsrA, forward, sequencing | CCATCACGCCGTTCATTGAA |
| P15 | LuxS, pBR322/Tn | TCCTTCGAATTCGCTTTGAAGAGTATTTAGCGCT |
| P16 | LuxS, Tn | CCAACAGGTACCAGCTTTACTGAACCCCCAGCC |
| P17 | LuxS, pBR322, reverse | CCAACAGTCGACAAAGCTTTACTGAACCCCCAGCC |
| P18 | LuxS, forward, sequencing | CAGTTATCTGCAGAGCGCGA |
| P19 | LuxS, reverse, sequencing | GACGCTTTAATCAGCGCCTT |
| P20 | λ Red, LsrK, forward | AGGGTATTCAAGAGGAGCGCGCAATGAGTCAACTCGATACGACTACCCCAGTGTAGGCTGGAGCTGCTTC |
| P21 | λ Red, LsrK, reverse | AATGAAGATAATCCATTTTAGAGGCAAGGAGCCTTCCAAAGAGACGTCGTTTCCGGGGATCCGTCGACCT |
| P22 | LsrK, reverse, sequencing | CGCCTTTAATCCTGCATGCT |
| P23 | LsrK, forward, sequencing | CAGATATTGCGGTCGTTGGG |