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Introducing differential RNA-seq mapping to track the early infection phase for Pseudomonas phage ɸKZ.

ABSTRACT: As part of the ongoing renaissance of phage biology, more phage genomes are becoming available through DNA sequencing. However, our understanding of the transcriptome architecture that allows these genomes to be expressed during host infection is generally poor. Transcription start sites (TSSs) and operons have been mapped for very few phages, and an annotated global RNA map of a phage - alone or together with its infected host - is not available at all. Here, we applied differential RNA-seq (dRNA-seq) to study the early, host takeover phase of infection by assessing the transcriptome structure of Pseudomonas aeruginosa jumbo phage ɸKZ, a model phage for viral genetics and structural research. This map substantially expands the number of early expressed viral genes, defining TSSs that are active ten minutes after ɸKZ infection. Simultaneously, we record gene expression changes in the host transcriptome during this critical metabolism conversion. In addition to previously reported upregulation of genes associated with amino acid metabolism, we observe strong activation of genes with functions in biofilm formation (cdrAB) and iron storage (bfrB), as well as an activation of the antitoxin ParD. Conversely, ɸKZ infection rapidly down-regulates complexes IV and V of oxidative phosphorylation (atpCDGHF and cyoABCDE). Taken together, our data provide new insights into the transcriptional organization and infection process of the giant bacteriophage ɸKZ and adds a framework for the genome-wide transcriptomic analysis of phage-host interactions.

SUBMITTER: Wicke L

PROVIDER: S-EPMC8244752 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundCancer progression can be tracked by gene expression changes that occur throughout early-stage to advanced-stage cancer development. The accumulated genetic changes can be detected when gene expression levels in advanced-stage are less variable but show high variability in early-stage. Normalizing advanced-stage expression samples with early-stage and clustering of the normalized expression samples can reveal cancers with similar or different progression and provide insight into clinical and phenotypic patterns of patient samples within the same cancer.ObjectiveThis study aims to investigate cancer progression through RNA-Seq expression profiles across the multi-stage process of cancer development.MethodsRNA-sequenced gene expression of Diffuse Large B-cell Lymphoma, Lung cancer, Liver cancer, Cervical cancer, and Testicular cancer were downloaded from the UCSC Xena database. Advanced-stage samples were normalized with early-stage samples to consider heterogeneity differences in the multi-stage cancer progression. WGCNA was used to build a gene network and categorized normalized genes into different modules. A gene set enrichment analysis selected key gene modules related to cancer. The diagnostic capacity of the modules was evaluated after hierarchical clustering.ResultsUnnormalized RNA-Seq gene expression failed to segregate advanced-stage samples based on selected cancer cohorts. Normalization with early-stage revealed the true heterogeneous gene expression that accumulates across the multi-stage cancer progression, this resulted in well segregated cancer samples. Cancer-specific pathways were enriched in the normalized WGCNA modules. The normalization method was further able to stratify patient samples based on phenotypic and clinical information. Additionally, the method allowed for patient survival analysis, with the Cox regression model selecting gene MAP4K1 in cervical cancer and Kaplan-Meier confirming that upregulation is favourable.ConclusionThe application of the normalization method further enhanced the accuracy of clustering of cancer samples based on how they progressed. Additionally, genes responsible for cancer progression were discovered.

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Introducing differential RNA-seq mapping to track the early infection phase for Pseudomonas phage ɸKZ.

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