Bacteriophage self-counting in the presence of viral replication

Yao, Tianyou; Coleman, Seth; Nguyen, Thu Vu Phuc; Golding, Ido; Igoshin, Oleg A.

doi:10.1073/pnas.2104163118

Cited by 15 publications

(31 citation statements)

References 62 publications

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“… 2021 , Frei and Khammash 2021 , Yao et al . 2021 ). The importance of negative autoregulation in plant virus infection just starts to be appreciated.…”

Section: Immune Evasion Through Leader and Non-core Modules Of Potyvi...mentioning

confidence: 99%

Proteome expansion in thePotyviridaeevolutionary radiation

Pasin

Daròs

Tzanetakis

2022

FEMS Microbiology Reviews

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Potyviridae, the largest family of known RNA viruses (realm Riboviria), belongs to the picorna-like supergroup and has important agricultural and ecological impacts. Potyvirid genomes are translated into polyproteins, which are in turn hydrolyzed to release mature products. Recent sequencing efforts revealed an unprecedented number of potyvirids with a rich variability in gene content and genomic layouts. Here we review the heterogeneity of non-core modules that expand the structural and functional diversity of the potyvirid proteomes. We provide a family-wide classification of P1 proteinases into the functional Types A and B, and discuss pretty interesting sweet potato potyviral ORF (PISPO), putative zinc fingers, and alkylation B (AlkB) – non-core modules found within P1 cistrons. The atypical modules inosine triphosphate pyrophosphatase (ITPase/HAM1), as well as the pseudo tobacco mosaic virus-like coat protein (TMV-like CP) are discussed alongside homologs of unrelated virus taxa. Family-wide abundance of the multitasking helper component proteinase (HC-pro) is revised. Functional connections between non-core modules are highlighted to support host niche adaptation and immune evasion as main drivers of the Potyviridae evolutionary radiation. Potential biotechnological and synthetic biology applications of potyvirid leader proteinases and non-core modules are finally explored.

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“… 2021 , Frei and Khammash 2021 , Yao et al . 2021 ). The importance of negative autoregulation in plant virus infection just starts to be appreciated.…”

Section: Immune Evasion Through Leader and Non-core Modules Of Potyvi...mentioning

confidence: 99%

Proteome expansion in thePotyviridaeevolutionary radiation

Pasin

Daròs

Tzanetakis

2022

FEMS Microbiology Reviews

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“…Our smFISH protocol was described previously 34, 84 . Briefly, we first designed seven sets of antisense DNA oligonucleotide probes.…”

Section: Single-molecule Fluorescence In Situ Hybridization (Smfish)mentioning

confidence: 99%

“…To discard false positive spots, such as the ones resulting from nonspecific binding of smFISH probes, we performed a gating procedure as described in 34,84 . Briefly, we compared the 2D scatter plots of peak height versus spot area for all detected spots in the experimental samples to that from the negative control (the sample incubated with probes against lambda cI, see Section "smFISH").…”

Section: Mrna Quantificationmentioning

confidence: 99%

Transcription-replication interactions reveal principles of bacterial genome regulation

Yanai

Pountain

Jiang

et al. 2023

Preprint

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Organisms determine the transcription rates of thousands of genes through a few modes of regulation that recur across the genome1. These modes interact with a changing cellular environment to yield highly dynamic expression patterns2. In bacteria, the relationship between a gene’s regulatory architecture and its expression is well understood for individual model gene circuits3,4. However, a broader perspective of these dynamics at the genome-scale is lacking, in part because bacterial transcriptomics have hitherto captured only a static snapshot of expression averaged across millions of cells5. As a result, the full diversity of gene expression dynamics and their relation to regulatory architecture remains unknown. Here we present a novel genome-wide classification of regulatory modes based on each gene’s transcriptional response to its own replication, which we term the Transcription-Replication Interaction Profile (TRIP). We found that the response to the universal perturbation of chromosomal replication integrates biological regulatory factors with biophysical molecular events on the chromosome to reveal a gene’s local regulatory context. While the TRIPs of many genes conform to a gene dosage-dependent pattern, others diverge in distinct ways, including altered timing or amplitude of expression, and this is shaped by factors such as intra-operon position, repression state, or presence on mobile genetic elements. Our transcriptome analysis also simultaneously captures global properties, such as the rates of replication and transcription, as well as the nestedness of replication patterns. This work challenges previous notions of the drivers of expression heterogeneity within a population of cells, and unearths a previously unseen world of gene transcription dynamics.

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“…Spot based quantification. Spot recognition and the subsequent mRNA quantification were done as described previously 30,81 . Briefly, we used the Spätzcells software 30 to identify the spots in the fluorescent images.…”

Section: Cell Segmentationmentioning

confidence: 99%

Transcription-replication interactions reveal principles of bacterial genome regulation

Pountain

Jiang

Yao

et al. 2022

Preprint

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Regulation of gene activity during the cell cycle is fundamental to bacterial replication but is challenging to study in unperturbed, asynchronous bacterial populations. Using single cell RNA-sequencing of heterogeneousStaphylococcus aureuspopulations, we uncovered a global gene expression pattern dominated by chromosomal position. We show that this pattern results from the effect of DNA replication on gene expression, and inEscherichia coli, changes under different growth rates and modes of replication. By constructing a quantitative model in each species that links replication to cell cycle gene expression, we identified divergent genes that may be instead subject to distinct regulation, and applied this cell cycle framework to characterize heterogeneity in responses to antibiotic stress. Our approach reveals a highly dynamic cell cycle transcriptional landscape and may be broadly applicable across species.

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Bacteriophage self-counting in the presence of viral replication

Cited by 15 publications

References 62 publications

Proteome expansion in thePotyviridaeevolutionary radiation

Proteome expansion in thePotyviridaeevolutionary radiation

Transcription-replication interactions reveal principles of bacterial genome regulation

Transcription-replication interactions reveal principles of bacterial genome regulation

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