Setting up a better infection: Overexpression of the early bacteriophage T4 gene motB during infection results in a more favorable tRNA pool for the phage
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ABSTRACT:
PROVIDER: PRJNA847232 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR19585870.fastq.gz | Fastqsanger.gz | |||
| SRR19585871.fastq.gz | Fastqsanger.gz | |||
| SRR19585872.fastq.gz | Fastqsanger.gz | |||
| SRR19585873.fastq.gz | Fastqsanger.gz | |||
| SRR19585874.fastq.gz | Fastqsanger.gz |
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Project description:Purpose: We investigated the effect of the T4 MotB protein on E. coli gene expression Method: E. coli BL21 (DE3) containing either pNW129 or pNW129-MotB were grown to early log phase (OD600 ~ 0.3) then induced with 0.2% arabinose for 20 minutes. T4 phage added to the culture at MOI10. Cells were then harvested at 0, 5, and 10 min time points and total RNA was isolated. The cDNA library was prepared using a modified RNATagSeq workflow as previously described (Shishkin, A.A. et al. 2015 Nat Methods). Optimum fragmentation of the total RNA samples in this library was determined to be 3 min at 94C in FastAP buffer (Thermo Fischer Scientific). The cDNA Library was run on a Bioanalyzer using the Agilent High Sensitivity DNA Kit to evaluate the quality of the library. The concentration of the cDNA library was determined by qPCR using the KAPA Library Quantification Kit (Kapa Biosystems, Wilmington, MA, USA) and CFX96 Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA). Sequencing was performed by the NIDDK Genomics Core facility using a MiSeq system with the single-end 50 bp Sequencing Kit (Illumina, San Diego, CA, USA). RNA-seq data was processed as previously described using E. coli str. K-12 substr. MG1655 (NC_000913.3) as the reference genome. Differential expression between conditions was represented as a fold change, and genes with both a fold change ≥2 or ≤ 0.5 and adjusted p value ≤ 0.05 were considered significant. Results: RNA-seq data revealed that the expression of 542 E. coli genes were significantly changed after motB expression. The expression of 704 and 706 E. coli genes were changed T4 5 min and 10 min post infection after MotB expression, respectively. After 5 min T4 infection, 34 T4 genes were significantly changed. Conclusion: T4 MotB modifies the pool of host tRNAs, creating a better infection for T4
2022-06-14 | GSE205715 | GEO
Project description:Background: Although many bacteriophage T4 early genes are nonessential with unknown functions, they are believed to aid in the takeover of the Escherichia coli host. Understanding the functions of these genes could be helpful to develop novel antibacterial strategies. MotB, encoded by a previously uncharacterized T4 early gene, is a DNA-binding protein that compacts the host nucleoid and alters host gene expression.Methods: MotB structure was predicted by AlphaFold 2. RNA-seq and mass spectrometry (MS) analyses were performed to determine RNA and protein changes when motB was overexpressed in E. coli BL21(DE3) ±5 min T4 infection.Results: MotB structure is predicted to be a two-domain protein with N-terminal Kyprides-Onzonis-Woese and C-terminal oligonucleotide/oligosaccharide-fold domains. In E. coli B, motB overexpression during infection does not affect T4 RNAs, but affects the expression of host genes, including the downregulation of 21 of the 84 chargeable host tRNAs. Many of these tRNAs are used less frequently by T4 or have a counterpart encoded within the T4 genome. The MS analyses indicate that the levels of multiple T4 proteins are changed by motB overexpression.Conclusion: Our results suggest that in this E. coli B host, motB is involved in establishing a more favorable tRNA pool for the phage during infection.
| S-EPMC9527043 | biostudies-literature
Project description:Purpose: We investigated how deletion of DksA or ppGpp, two E. coli global transcription regulators, affects T4 infection. Method: B606, B606 DdksA, and B606 ppGpp0 were grown at 37C to early/mid log phase (OD600 ~ 0.4) then infected with moi of 10 of either wt T4 or T4motAam and total RNA was isolated. 2.5 µg total RNA from each sample was treated with a Ribo-Zero rRNA Removal Kit (Gram-Negative Bacteria; Illumina San Diego, CA) to deplete rRNA. The enriched mRNA was fragmented, reverse-transcribed, ligated with dual indexes, and amplified using a TruSeq Stranded mRNA Library Prep Kit (Illumina, San Diego, CA). The resulting RNA-Seq libraries were pooled at equal concentrations and sequenced using on an Illumina MiSeq to generate 2 x 100 bp paired-end reads. Read data in fastq format was demultiplexed and aligned to E. coli B str. DE3 (NC_012971.2) reference genome using STAR v2.5.2, retaining unmapped reads (Dobin, Davis et al. 2013). Unmapped reads were then mapped in a second step to T4 reference (NC_000866.4). In both cases, default alignment behavior was altered with the following arguments: --outFilterScoreMinOverLread 0 --outFilterMatchNmin 30 --outFilterMatchNminOverLread 0 --clip3pAdapterSeq AGATCGGAAGAGCGTCGTGTA --alignIntronMax 1. RNA gene counts in both reference genomes were then quantified using the same NCBI gene definitions utilized in mapping index construction using the subread featureCounts v1.4.6-p3 package (Liao, Smyth et al. 2014). Differential expression between samples fchanges in gene expression was predetermined to entail a fold change of more than or equal to 2 and P value less than or equal to 0.05. at 5 minutes post-infection. Result: Both ppGpp0 and delta(dksA) increase wt T4 plaque size. However, ppGpp0 does not significantly alter burst size/latent period and only modestly affects T4 transcript abundance, while delta(dskA) increases burst size (2-fold), does not affect latent period, and increases the abundance of several Pe RNAs at 5 min post-transcription. delta(dskA) also increases T4motAam plaque size with a much shorter latent period compared to T4motAam/wt infection, and the levels of specific middle RNAs increase due to more transcription from Pe's that extend into these middle genes. Conclusion: We conclude that DksA attenuates T4 early gene expression. Consequently, delta(dksA) results in a more productive wt infection and ameliorates the poor expression of middle genes in a T4motAam infection.
2018-03-15 | GSE111808 | GEO
Project description:Bacteriophages are highly abundant viruses of bacteria. The major role of phages in shaping bacterial communities and their emerging medical potential as antibacterial agents has trig-gered a rebirth of phage research. To understand the molecular mechanisms by which phages hijack their host, omics technologies can provide novel insights into the organization of tran-scriptional and translational events occurring during the infection process. In this study, we ap-ply transcriptomics and proteomics to characterize the temporal patterns of transcription and protein synthesis during T4 phage infection of E. coli. We investigated the stability of E. coli-originated transcripts and proteins in the course of infection, identifying degradation of E. coli transcripts and preservation of the host proteome. Moreover, the correlation of the phage transcriptome and proteome reveals specific T4 phage mRNAs and proteins that are temporally decoupled, suggesting post-transcriptional and translational regulation mechanisms. This study provides the first comprehensive insights into the molecular takeover of E. coli by bacteriophage T4. This data set represents a valuable resource for future studies seeking to study molecular and regulatory events during infection. We created a user-friendly online tool, POTATO4, available to the scientific community to access gene expression patterns for E. coli and T4 genes.
2022-11-09 | GSE211026 | GEO
Project description:Microarray Analysis of Gene Expression during Bacteriophage T4 Infection
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Project description:Bacteriophages are highly abundant viruses of bacteria. The major role of phages in microbial ecology to shape bacterial communities and their emerging medical potential as antibacterial agents have triggered a rebirth of phage research. It is of particular interest to understand the molecular mechanisms by which phages gain control over their host. Omics technologies such as next-generation sequencing and protein-profiling technologies can provide novel insights into transcriptional and translational events occurring during the infection process. Thereby, the temporal organization of the transcriptome and proteome of the phage and their bacterial hosts can be monitored. In this study, we performed next-generation sequencing and proteomics to study the transcriptome and proteome of the T4 phage and its host during the infection in a time-resolved manner. Our data shows the temporally resolved appearance of bacteriophage T4 transcripts and proteins, confirming previously described subgrouping of T4 gene products into early, middle and late infection phases. We observe specific early transcripts giving rise to middle or late proteins indicating the existence of previously not reported post-transcriptional regulatory mechanisms controlling the translation of T4 mRNAs. Moreover, we investigated the stability of E. coli-originated transcripts and proteins in the course of infection, identifying degradation of E. coli transcripts and preservation of the host proteome. This study provides the first comprehensive insights into the transcriptomic and proteomic takeover by the bacteriophage T4, exemplifying the power and value of high-throughput technologies to simultaneously characterize multiple gene expression events. Moreover, we created a user-friendly application available to the entire scientific community to access gene expression patterns for their host and phage genes of interest.
2022-09-19 | PXD035873 | Pride
Project description:The following CGH experiments were conducted on four sectors (S1-S4) from a single primary ductal carcinoma tumor (T4).
2009-07-10 | GSE16601 | GEO
Project description:Genomic microarrays were used to examine the complex temporal program of gene expression exhibited by bacteriophage T4 during the course of development.The microarray data confirm the existence of distinct early, middle, and late transcriptional classes during the bacteriophage replicative cycle.This approach allows assignment of previously uncharacterized genes to specific temporal classes.The genomic expression data verify many promoter assignments and predict the existence of previously unidentified promoters. Keywords: time course
2005-11-18 | GSE3590 | GEO
Project description:Streptococcus mutans T4 genome sequencing project.
| PRJNA49799 | ENA