RNA-Sequencing Reveals the Progression of Phage-Host Interactions between phi R1-37 and Yersinia enterocolitica

Despite the expanding interest in bacterial viruses (bacteriophages), insights into the intracellular development of bacteriophage and its impact on bacterial physiology are still scarce. Here we investigate during lytic infection the whole-genome transcription of the giant phage vB_YecM_phi R1-37 (phi R1-37) and its host, the gastroenteritis causing bacterium Yersinia enterocolitica. RNA sequencing reveals that the gene expression of phi R1-37 does not follow a pattern typical observed in other lytic bacteriophages, as only selected genes could be classified as typically early, middle or late genes. The majority of the genes appear to be expressed constitutively throughout infection. Additionally, our study demonstrates that transcription occurs mainly from the positive strand, while the negative strand encodes only genes with low to medium expression levels. Interestingly, we also detected the presence of antisense RNA species, as well as one non-coding intragenic RNA species. Gene expression in the phage-infected cell is characterized by the broad replacement of host transcripts with phage transcripts. However, the host response in the late phase of infection was also characterized by up-regulation of several specific bacterial gene products known to be involved in stress response and membrane stability, including the Cpx pathway regulators, ATP-binding cassette (ABC) transporters, phage- and cold-shock proteins.Peer reviewe

Integrative omics analysis of Pseudomonas aeruginosa virus PA5oct highlights the molecular complexity of jumbo phages

Pseudomonas virus vB_PaeM_PA5oct is proposed as a model jumbo bacteriophage to investigate phage-bacteria interactions and is a candidate for phage therapy applications. Combining hybrid sequencing, RNA-Seq and mass spectrometry allowed us to accurately annotate its 286,783 bp genome with 461 coding regions including four non-coding RNAs (ncRNAs) and 93 virion-associated proteins. PA5oct relies on the host RNA polymerase for the infection cycle and RNA-Seq revealed a gradual take-over of the total cell transcriptome from 21% in early infection to 93% in late infection. PA5oct is not organized into strictly contiguous regions of temporal transcription, but some genomic regions transcribed in early, middle and late phases of infection can be discriminated. Interestingly, we observe regions showing limited transcription activity throughout the infection cycle. We show that PA5oct upregulates specific bacterial operons during infection including operons pncA-pncB1-nadE involved in NAD biosynthesis, psl for exopolysaccharide biosynthesis and nap for periplasmic nitrate reductase production. We also observe a downregulation of T4P gene products suggesting mechanisms of superinfection exclusion. We used the proteome of PA5oct to position our isolate amongst other phages using a gene-sharing network. This integrative omics study illustrates the molecular diversity of jumbo viruses and raises new questions towards cellular regulation and phage-encoded hijacking mechanisms

Rethinking Phage Ecology by Rooting it Within an Established Plant Framework

Despite the abundance and significance of bacteriophages to microbial ecosystems, no broad ecological frameworks exist within which to determine “bacteriophage types” that reflect their ecological strategies and ways in which they interact with bacterial cells. To address this, we repurposed the well-established Grime's triangular CSR framework, which classifies plants according to three axes: competitiveness (C), ability to tolerate stress (S), and capacity to cope with disturbance (R). This framework is distinguished from other accepted schemes, as it seeks to identify individual characteristics of plants to understand their biological strategies and roles within an ecosystem. Our repurposing of the CSR triangle is based on phage transcription and the observation that typically phages have three major distinguishable transcription phases: early, middle, and late. We hypothesize that the proportion of genes expressed in these phases reflects key information about the phage “ecological strategy,” namely the C, S, and R strategies, allowing us to examine phages in a similar way to how plants are projected onto the triangle. In the “phage version” of this scheme, we suggest: (1) that some phages prioritize the early phase of transcription that shuts off host defense mechanisms, which reflects competitiveness; (2) other phages prioritize tuning resource management mechanisms in the cell such as nucleotide metabolism during their “mid” expression profile to tolerate stress; and (3) a further subset of phages (termed Ruderals) survive disturbance by investing significant resources into regeneration so they express a higher proportion of their genes during late infection. We examined 42 published phage transcriptomes and show that they fall into discrete CSR categories according to their expression profiles. We discuss these positions in the context of their biology, which is largely consistent with our predictions of specific phage characteristics. In this opinion article, we suggest a starting point to ascribe phages into different functional types and thus understand them in an ecological framework. We suggest that this may have far-reaching implications for the application of phages in therapy and their exploitation to manipulate bacterial communities. We invite further use of this framework via our online tool; www.PhageCSR.ml

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

International audienceAs 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

Integrative omics analysis of Pseudomonas aeruginosa virus PA5oct highlights the molecular complexity of jumbo phages

Pseudomonas virus vB_PaeM_PA5oct is proposed as a model jumbo bacteriophage to investigate phage-bacteria interactions and is a candidate for phage therapy applications. Combining hybrid sequencing, RNA-Seq and mass spectrometry allowed us to accurately annotate its 286,783 bp genome with 461 coding regions including four non-coding RNAs (ncRNAs) and 93 virion-associated proteins. PA5oct relies on the host RNA polymerase for the infection cycle and RNA-Seq revealed a gradual take-over of the total cell transcriptome from 21% in early infection to 93% in late infection. PA5oct is not organized into strictly contiguous regions of temporal transcription, but some genomic regions transcribed in early, middle and late phases of infection can be discriminated. Interestingly, we observe regions showing limited transcription activity throughout the infection cycle. We show that PA5oct upregulates specific bacterial operons during infection including operons pncA-pncB1-nadE involved in NAD biosynthesis, psl for exopolysaccharide biosynthesis and nap for periplasmic nitrate reductase production. We also observe a downregulation of T4P gene products suggesting mechanisms of superinfection exclusion. We used the proteome of PA5oct to position our isolate amongst other phages using a gene-sharing network. This integrative omics study illustrates the molecular diversity of jumbo viruses and raises new questions towards cellular regulation and phage-encoded hijacking mechanisms.status: publishe

PAK_P3 rapidly adsorbs to its host and efficiently produces new progenies.

<p><b>(A)</b> Adsorption assays of PAK_P3 on <i>P</i>. <i>aeruginosa</i> strain PAK. <b>(B)</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.</p

PAK_P3 alters expression of many host gene features by late infection.

<p>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.</p

PAK_P3 alters <i>P</i>. <i>aeruginosa</i> metabolite content over the course of infection.

<p>Percentage of altered <i>Pseudomonas</i> metabolite 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.</p

Molecular details of PAK_P3 infection cycle of <i>P</i>. <i>aeruginosa</i> strain PAK.

<p>Red and green colors correspond to phage and host elements respectively. A description of the figure is given in the text (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006134#sec011" target="_blank">Discussion</a>). 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.</p