Next-Generation “-omics” Approaches Reveal a Massive Alteration of Host RNA Metabolism during Bacteriophage Infection of Pseudomonas aeruginosa

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Abstract

As interest in the therapeutic and biotechnological potentials of bacteriophages has grown, so has value in understanding their basic biology. However, detailed knowledge of infection cycles has been limited to a small number of model bacteriophages, mostly infecting Escherichia coli. We present here the first analysis coupling data obtained from global next-generation approaches, RNA-Sequencing and metabolomics, to characterize interactions between the virulent bacteriophage PAK_P3 and its host Pseudomonas aeruginosa. We detected a dramatic global depletion of bacterial transcripts coupled with their replacement by viral RNAs over the course of infection, eventually leading to drastic changes in pyrimidine metabolism. This process relies on host machinery hijacking as suggested by the strong up-regulation of one bacterial operon involved in RNA processing. Moreover, we found that RNA-based regulation plays a central role in PAK_P3 lifecycle as antisense transcripts are produced mainly during the early stage of infection and viral small non coding RNAs are massively expressed at the end of infection. This work highlights the prominent role of RNA metabolism in the infection strategy of a bacteriophage belonging to a new characterized sub-family of viruses with promising therapeutic potential.

Figures

  • Fig 1. PAK_P3 rapidly adsorbs to its host and efficiently produces new progenies. (A) Adsorption assays of PAK_P3 on P. aeruginosa strain PAK. (B)One-step growth curve of PAK_P3. Samples treated with (grey squares) or without (black diamonds) CHCl3. A logistic regression was used to fit the data. Four independent experiments were combined and data are presented as means with standard deviations.
  • Fig 2. PAK_P3 takes over the host cell transcription over the course of infection. Three independent biological replicates of RNA extracts were harvested from PAK_P3 infected cells at 0min, 3.5min and 13min post infection, as well as a single sample collected at 6.5min and all were subsequently sequenced. Plotting the percentage of reads mapping to the PAK_P3 genome (A) and to the host genome (B) over the course of infection shows that PAK_P3 progressively dominates the transcriptional environment of the cell with phage transcripts.
  • Fig 3. PAK_P3 alters expression of many host gene features by late infection. Differential expression analysis of host gene features comparing transcript abundance between phage negative controls (t = 0 min) and late infection (t = 13min) was performed. This comparison was made after normalizing the read counts that map to each host gene feature between both conditions, ignoring reads that map to the phage, which artificially enriches reads in the late condition. This method thus compares the negative control directly to a host transcript population that has been depleted by replacement with phage transcripts during infection, normalizing away the global depletion so that more specific shifts can be reported and independently tested for.
  • Fig 4. PAK_P3 alters P. aeruginosametabolite content over the course of infection. Percentage of altered Pseudomonasmetabolite ions during the course of infection (p-value 0,05, │Log2(fold change)│ 0,5), y-axis shows percentage and x-axis shows the time points during infection. In total 377 ions were measured.
  • Fig 5. Pathway enrichment analysis during PAK_P3 infection revealed its requirement on pyrimidine metabolism. Values of the enrichment analysis are shown for the significantly enriched pathways (rows) at the different time points (columns). The color scale indicates the cut-off for the p-values, where red and blue are used for, respectively, the pathways found enriched among increased and decreased metabolites.
  • Fig 6. Comparison of significant changes in transcriptomics andmetabolomics data from PAK_P3 infected cells reveals no direct correlation.On the left, the number of genes with a significant differential expression (│Log2(fold change)│ > 1.3, pvalue < 0.05) is shown. On the right, an overview of the number of metabolites with significantly changed levels (│Log2(fold change)│ > 0.5, p-value < 0.05) is shown. The middle column entails all studied metabolic pathways and indicated between brackets are, respectively, the total number of genes and metabolites involved in this pathway. Red = increase in transcript/ metabolite level, Blue = a decrease in transcript/metabolite level.
  • Fig 7. PAK_P3 transcription is temporally regulated. (A)Mapped reads were summarized into stranded count tables of Total Gene Reads that align to every 250bp of the PAK_P3 genome using the CLC Genomics Workbench. These read counts were then normalized against each other by the Total Count of reads that align to both phage and host genomes for each sample and then plotted. This allows us to show the relative abundance of phage transcripts over time in the context of the total transcript population. Red and green graphs represent reads mapping to the forward and reverse strands, respectively, for each replicate in each condition. The PAK_P3 genome is represented at the bottom of the panel with yellow arrows indicating defined coding sequences. (B) Enlargement of the PAK_P3 genome region encoding small RNAs. NA = nucleic acid
  • Fig 8. Molecular details of PAK_P3 infection cycle of P. aeruginosa strain PAK.Red and green colors correspond to phage and host elements respectively. A description of the figure is given in the text (see Discussion). Full arrows depict the three temporal stages of PAK_P3 infection cycle. Dashed arrows represent relations between metabolic pathways highlighted by our “-omics” analyses. AME = Auxiliary Metabolic Enzymes.

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Chevallereau, A., Blasdel, B. G., De Smet, J., Monot, M., Zimmermann, M., Kogadeeva, M., … Lavigne, R. (2016). Next-Generation “-omics” Approaches Reveal a Massive Alteration of Host RNA Metabolism during Bacteriophage Infection of Pseudomonas aeruginosa. PLoS Genetics, 12(7). https://doi.org/10.1371/journal.pgen.1006134

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